Profiles for Family Planning and Reproductive Health Programs 116 Countries

Publication date: 2005

2nd EDITION2nd EDITION Profiles for Family Planning and Reproductive Health Programs 116 COUNTRIES Profiles forFam ily Planning and Reproductive H ealth Program s 116 COUNTRIES R o ss ❖ Sto ver ❖ A d ela ja John Ross ❖ John Stover ❖ Demi Adelaja Profiles for Family Planning and Reproductive Health Programs 116 COUNTRIES John Ross John Stover Demi Adelaja Futures Group 2005 2nd EDITION Futures Group 80 Glastonbury Boulevard Glastonbury, Connecticut 06033 USA Cover design: Kim Farcot Printing: Paladin Commercial Printers Newington, Connecticut ISBN 1-59560-002-7 Copyright © 2005 by the Futures Group Any part of this volume may be copied or adapted to meet local needs without permission from the authors or the Futures Group, provided that the parts copied are distributed free or at cost (not for profit). Any commercial reproduc- tion requires prior permission from the Futures Group. The authors would appreciate receiving a copy of any materials in which the text or tables in the volume are used. Contents iii ContentsContentsContentsContentsContents Foreword . vii I. Geographic Patterns of Reproductive Health Problems .1 II. Past Trends in Contraceptive Use . 5 Total Contraceptive Use .5 Use by Method .5 Plateaus in Contraceptive Prevalence and Total Fertility Rates .6 Use by Source by Method .8 III. Future Trends in Contraceptive Use . 17 Projections for the Percentage Using Contraception . 18 Projections for Total Numbers Using Contraception . 19 Projections for Commodities Needed, by Method . 21 Projections for Commodity Costs . 21 IV. Demands on Services . 23 Growing Numbers of Women, Married Women, and Deliveries . 23 Youth: Current Needs and Services . 25 Unmet Need for Youth . 26 HIV/AIDS and Youth . 27 V. Maternal Health . 29 Maternal Mortality and Morbidity . 29 Antenatal, Delivery, and Tetanus Care . 31 Induced Abortion and Postabortion Contraception . 33 Program Efforts to Improve Maternal Health . 35 VI. Child Health . 39 Rates and Numbers of Child Deaths . 39 Risks of Death by Birth Categories . 39 Immunizations, ARI, and ORS . 41 VII. HIV/AIDS Programs and Shortfalls . 43 HIV/AIDS Incidence and Prevalence . 43 Goals and Strategies . 45 VIII. Five Program Objectives . 47 Goal No. 1: To Provide Full Access to a Variety of Contraceptive Methods . 47 Goal No. 2: To Satisfy Unmet Need and Intention to Use a Method . 50 Goal No. 3: To Reach the Desired Fertility Level . 56 Goal No. 4: To Attain the Replacement Fertility Level . 60 Goal No. 5: To Satisfy Millennium Development Goals and the Cairo Programme of Action . 66 Appendices: A: Supporting Tables (list follows) . A.1 B: Technical Appendix for Projection Methods . B.1 iv Contents Appendix A: Supporting Tables Sources for Supporting Tables . A.1 A.1. Contraceptive Use by Method Among Currently Married Women: All Surveys 1980 to Present, Developing Countries . A.3 A.2. Source of Supply for Modern Contraception Methods . A.17 A.3. Population, Number of All Women (15-49), and Married Women (15-49), for 2005, and Percent Using Contraception (latest survey), and Number of Users . A.22 A.4. Number of Married Women of Reproductive Age (15-49) for Four Dates, and Percent Currently Married . A.24 A.5. Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age . A.26 to A.33 a. Year 2005 . A.26 b. Year 2010 . A.28 c. Year 2015 . A.30 d. Year 2020 . A.32 A.6. Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) . A.34 to A.41 a. Year 2005 . A.34 b. Year 2010 . A.36 c. Year 2015 . A.38 d. Year 2020 . A.40 A.7. Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) . A.42 to A. 49 a. Year 2005 . A.42 b. Year 2010 . A.44 c. Year 2015 . . A.46 d. Year 2020 . A.48 A.8. Projected Contraceptive Costs by Method Among All Women (Aged 15-49) . A.50 to A. 57 a. Year 2005 . A.50 b. Year 2010 . A.52 c. Year 2015 . A.54 d. Year 2020 . A.56 A.9. Unmet Need, Percent Using, and Percent of Demand Satisfied . A.58 A.10. Intention to Use Contraception . A.60 A.11. Relationship of Unmet Need and Intention to Use Contraception . A.62 A.12. Ideal Number of Children, Total Fertility Rate and Wanted Fertility Rates, and Fertility Planning Status . A.66 A.13. Percent Distribution of the Gap to 75% Contraceptive Prevalence, by Region, Year 2005 Estimates . A.68 A.14. 1999 Program Effort Scores: Total and Four Dimension Scores as Percent of Maximum . A.70 A.15. Maternal Mortality Ratio (MMR), Number of Deaths Annually, Lifetime Risk, and Percent of Female Deaths (ages 15-49) That Are Pregnancy Related . A.72 A.16. Number of Abortions, Abortion Rate, and Abortion Ratio (1999 Estimates) . A.74 A.17. Percentage Receiving Antenatal Care, Tetanus Injections, and Delivery Care . A.76 A.18. Maternal and Neonatal Program Effort Index (MNPI), 1999 and 2002 Surveys: Country Scores as Percent of Maximum . A.78 A.19. Number of Births, Infant and Child Mortality Rates, and Number of Deaths, 2003 Estimates . A.82 Contents v A.20. Births According to Risk Category . A.84 A.21. Immunizations, ARI, and Re-hydration . A.86 A.22. Estimated Number of People Living with HIV/AIDS, Estimated Number of Orphans (AIDS and non AIDS), and Estimated AIDS Deaths, at the End of 2003 . A.88 A.23. Condom Needs . A.90 to A. 93 a. 2005 Projections . A.90 b. 2010 Projections . A.92 A.24. Comparative Information on Youth . A.94 A.25. Demographic Dividend: Percent of the Population Aged 15-59, from 1950 through 2000 and from 2005 through 2050 . A.96 to A.99 vii FFFFForororororeeeeewwwwworororororddddd This volume, an updated and enlarged edition of the first edition, was conceived as a way to assist ac- tion programs by bringing together much of the comparative data that bear upon family planning and reproductive health. A matrix for 116 countries was constructed to embrace time trends for each of nu- merous data sets. The object was to provide both reference information through supporting tables, and basic analyses through textual presentation. The body of the text comments on the chief patterns and trends of each feature, usually by region. The topics chosen embrace a continuum from the demographic context to past and future contraceptive use, to service burdens, maternal and child health, HIV/AIDS, and, finally, to a selection of alternative action objectives. Large countries are given special attention in most sections. Chapter 1 provides an overview of the disparate geographic pattern of reproductive health problems as a backdrop to the rest of the volume. Chapter 2 uses over 300 national surveys to describe contracep- tive use, including trends by method and source. Chapter 3 introduces a special projection method to anticipate future contraceptive use, again by method, with estimates of commodity needs and costs. Chapter 4 summarizes demands on services due to growing population numbers, with particular atten- tion to youth. Chapter 5 concerns maternal morbidity and mortality along with antenatal and delivery care, abortion frequency, and program effort to improve maternal health. Chapter 6 is a parallel chapter for child mortality, risks by type of birth, and program efforts for immunizations and other measures. Chapter 7 is devoted to the HIV/AIDS pandemic. Finally, Chapter 8 presents five action goals, includ- ing full access to contraception, satisfaction of unmet need and intention to use a method, achievement of the desired fertility level, attainment of replacement fertility, and movement toward the Millennium Goals. A set of 25 appendix tables supports these various topics. The intended audience encompasses the many international agencies active in family planning and re- productive health programs. It also includes officials and researchers in individual countries, who can find here a convenient source of information on their own situation, as well as comparative data for their region. We hope also that the text discussions will lead to a deeper understanding of some of the dy- namics that bear on each topic. Any compilation of information that covers numerous topics and many countries incurs a corresponding degree of indebtedness. We wish to express our gratitude to the David and Lucile Packard Foundation, the World Population Society, and The Centre for Population and Development Activities (CEDPA) for underwriting the work that produced this volume. We are grateful to a number of institutions that freely shared data, including Macro International, The United Nations Population Division, The United Na- tions Children Fund (UNICEF), the World Health Organization (WHO), and the World Bank. Our appre- ciation also goes to Cathy Johnson for manuscript preparation, layout, and production. The grant from the World Population Society that inspired this Profiles effort was in fact the Society’s last activity. For many years the Society was active in promoting greater understanding of the issues of population growth and the need for family planning, and in building political commitment to address these issues through effective action. The driving force behind the World Population Society was Phi- lander Claxton. Through his volunteer work at the World Population Society and his official positions with the US State Department and later at the Futures Group, Phil made enormous contributions to the field of international population assistance. He contributed to the post-World War II efforts to establish the United Nations, the World Bank, and country level institutions to help carry out his vision. Those who worked with Phil over the years learned much from his dedication to international development and his tireless efforts to promote appropriate policies and programs to ensure that all couples have the right and the means to achieve their desired family size. We hope that this book will make a contribu- tion to achieving that goal. The distribution of people and events is cast heavily into a relatively few coun- tries, with the remainder spread thinly over about a hundred others. The “size of the problem” is a complex topic: no matter what one considers, whether peo- ple, pregnancies, or deaths, a few coun- tries dominate the globe; a few countries also dominate within each region. We have chosen 116 countries as the subject of this report. These are restrict- ed to those having over one million pop- ulation, covering 98% of the developing world. Included are countries in Latin America, Asia, sub-Saharan Africa, and Middle East/North Africa, together with the five Central Asian Republics, the three Caucasus countries, and the set of Russia, Ukraine, and Moldova. The 116 countries contain over 5 billion people in the UN projections for 2005. A convenient breakdown is as follows (in thousands): China 1,322,273 India 1,096,917 Rest of Asia (except Japan) 1,123,870 Latin America 558,281 Sub-Saharan Africa 693,901 Middle East/North Africa 374,092 The five Central Asian Republics 58,881 The three Caucasus Countries 16,596 The developing world 5,244,811 The set of Russia, Ukraine, and Moldova 193,594 Grand total 5,438,405 As another overview still using the UN 2005 figures, ➤ China has 25% and India has 21% of the developing world, for nearly half of the total (see Figure 1.2). ➤ The top 9 countries (including those) contain two-thirds of the total. ➤ The top 16 countries contain three- fourths of the total. While China and India dominate the whole developing world, a similar im- balance exists within each region (see Figure 1.1). ➤ In the rest of Asia the next largest country, Indonesia, has only 6% of the region’s total; however it has one-sixth of the rest of Asia after the two giants are removed. It is also the world’s fourth largest country, since the breakup of the USSR. ➤ In Latin America, Brazil contains one- third of the total (33%) and Mexico has one-fifth (19%), for over one-half to- gether. The next two, Colombia and Ar- gentina, have only 8% and 7%. Peru and Venezuela have 5% each. Eight of the 24 countries each contains less than 1% of the region’s total. ➤ In sub-Saharan Africa, Nigeria has 19% of the total. Next is Ethiopia with 11% and D.R. Congo with only 8%. The top five, including South Africa and Tan- zania, dominate the 40 members of the region. With 49% of the total population they contain about one-half of all births, infant deaths, and maternal deaths in the region, with the other half spread over the other 37 countries. Fifteen countries each have less than 1% of the region’s population. ➤ In the Middle East/North Africa re- gion, Egypt and Turkey together have 40% of the total, with 20% each. The next two, Algeria and Sudan, have only 9% each. Morocco has 9%; all together these five (of 16) countries contain two- thirds (67%) of the region’s total. The number of women of childbearing age (15-49) is distributed very much as the total population. Concentration is heavy in China and India, and then with- in 2-5 countries within every region. The picture is similar for married/cohabiting women. Outside of China, the number of women aged 15-49 is growing by 9% from 2005 to 2010, and will grow by 17% from 2005 to 2015, totaling a one- sixth increase over 10 years. Growth for married/cohabiting women is essentially similar. Overall, 69.5% are married/co- habiting and while this may decline somewhat the percentage is not expected to change substantially over the planning period to 2005. See Appendix Tables A.6 and A.7. There is also a vast range among devel- oping countries in the pattern of deliver- ies, infant and child mortality, and ma- ternal mortality. Figure 1.2 depicts the uneven geographic distribution of some of these features, as follows. Deliveries follow much the same geo- graphic pattern as populations, except that China’s share is much smaller and sub-Saharan Africa’s share is much larg- er, reflecting their especially low and es- pecially high fertility rates in relation to the rest of the world. However for attended deliveries, the pat- tern changes sharply. China has 25% of all attended deliveries, whereas it has only 15% of all deliveries. Sub-Saharan Africa’s share drops from 20% of deliv- eries to only 15% of attended deliveries. Not surprisingly, infant and child deaths reverse that pattern. Maternal deaths reverse it even more: sub-Saharan Africa’s 41% exceeds the total for all other regions together out- side of India. GEOGRAPHIC PATTERNS OF REPRODUCTIVE HEALTH PROBLEMS Chapter 1Chapter 1Chapter 1Chapter 1Chapter 1 2 Chapter 1 Figure 1.1. Population in Developing Countries China 35% India 29% Other Asian Countries 20% Indonesia 6% Pakistan 4% Bangladesh 4% Viet Nam 2% Brazil 33% Other Latin American Countries 23% Mexico 19% Colombia 8% Argentina 7% Peru 5% Venezuela 5% OtherMiddleEast / NorthAfricanCountries 28% Egypt 20%Turkey 20% Algeria 9% Sudan 9% Morocco 9% Iraq 6% Populations of Asia Populations of Latin America Populations of the Middle East/North Africa Populations of the 15 Largest Developing Countries Populations of Sub-Saharan Africa China 34% India 28% Indonesia 6% Brazil 5% Pakistan 4% Bangladesh 4% Nigeria 3% Mexico 3% 2% Iran 2% Philippines 2% Egypt 2% Turkey 2% Thailand 2% Ethiopia 2% Viet Nam Other Sub-Saharan African Countries 37% Nigeria 19% Ethiopia 11% D.R. Congo 8% South Africa 7% Tanzania 6% Kenya 5% Uganda 4% Ghana 3% Chapter 1 3 Figure 1.2. Populations and Patterns of Deliveries, Infant and Child Mortality, and Maternal Mortality Populations by Region Deliveries Maternal Deaths Infant Deaths Child Deaths Deliveries Attended China 25% India 21% Rest of Asia 23% Sub-Saharan Africa 13% Latin America 11% Middle East/North Africa 7% China 15% India 21% Rest of Asia 24% Sub-Saharan Africa 20% Latin America 12% Middle East/North Africa 8% China 25% India 16% Rest of Asia 21% Sub-Saharan Africa 15% Latin America 14% Middle East/North Africa 10% China 2% India 25% Rest of Asia 19% Sub-Saharan Africa 41% Latin America 9% Middle East/North Africa 4% China 8% India 22% Rest of Asia 21% Sub-Saharan Africa 39% Latin America 4% Middle East/North Africa 6% China 8% India 21% Rest of Asia 20% Sub-Saharan Africa 42% Latin America 4% Middle East/North Africa 6% 4 Chapter 2 5 Chapter 2 presents past trends in contra- ceptive use for (1) total use, (2) use by method, (3) use by source by method, and (4) plateaus in contraceptive preva- lence and total fertility rates. Total Contraceptive Use The rich body of national surveys now available, encompassing some 301 sur- veys in 109 countries taken since 1980 (Appendix Table A.1), and many others prior to 1980, documents the revolution in family planning that has swept much of the developing world since the 1960s. The 1965 average was about 10% of couples using a method; now it is at 60% (UN 2003). The upward trends in most individual countries that dominate Fig- ure 2.1 testify to this revolution. The patterns by region follow. Sub-Saharan Africa. Change has lagged in sub-Saharan Africa but even there certain countries are impressive exceptions, enough so to undermine ear- ly fears that African cultures were near- ly immune to contraceptive adoption. Moreover, clear evidence has appeared of fertility declines in numerous African countries (Cohen, 1998; Kirk and Pillet, 1998; UN 2003). However, prospects are fundamentally different between Anglophone and Fran- cophone Africa (Figures 2.1a and 2.1b). Contraceptive use is rising in Anglo- phone countries and has reached signifi- cant levels in some, as in Kenya, Zimba- bwe, Botswana, South Africa, Namibia, and Zambia. Other trends are also up, though at lower levels, and Nigeria, the largest of all, is flat at a very low level. Francophone countries give a far differ- ent picture, one of very low use levels and only modest suggestions of change. All but Togo fall below 20% of couples using a method, even including tradi- tional methods, and any upward slopes are quite gentle. Remarkably, modern method use is below 13% everywhere. Latin America. Both South America and the Central America and Caribbean regions show patterns of steady rises in use, to substantial levels for many coun- tries (Figures 2.1c and 2.1d). High val- ues occur for Brazil, with its population of partly European extraction; Mexico, with a strong government program; and Colombia, with a strong private sector, along with Costa Rica, Cuba, Domini- can Republic, Jamaica, Peru, and Puerto Rico. Lower values appear for Haiti and Guatemala and Peru’s high values come heavily from traditional methods, though all three have risen somewhat. The Middle East/North Africa. Contra- ceptive use has risen steadily over the years in most countries surveyed (Figure 2.1e). Six of the 16 countries are at or above 60% of couples using a method: Algeria, Egypt, Lebanon, Morocco, Tuni- sia, and Turkey. However, Iraq, Sudan, Oman, and Yemen are at very low levels, although the latter two have risen recently. Asia. The immense continent of Asia is divided here into three sub-regions (Fig- ure 2.1). East Asia has the fewest mem- bers and the highest use levels, in China, Taiwan, Hong Kong, and South Korea. Considerable diversity is present else- where. In Southeastern Asia, the wide spread in use is accompanied by differ- ences in slope: Myanmar and Viet Nam are sharply up, while Indonesia’s rise is relatively steady though at a much high- er level. Southern Asia also presents a diverse pic- ture, from Pakistan at a remarkably low level to Bangladesh’s impressive rise over the years, to Sri Lanka with the highest level in the area. India is at 40-45% but is exceedingly diverse internally. In summary, contraceptive use has risen historically in much of the developing world. It is already at ceiling levels in some countries, and it continues to rise in many others. However, the pattern is uneven: a few of the largest countries, such as India, Pakistan, Nigeria and oth- ers, have far to go, and much of sub-Sa- haran Africa still registers low levels of use. Appendix Table A.1 provides the full results in surveys from 1980 on, and Appendix Tables A.5a-d give the pro- jected level for 116 countries at four dates from 2005 to 2020 (see Chapter 3). Use by Method Current use of each contraceptive meth- od reflects the history of its past adop- tions together with its continuation pat- tern. This is far different for resupply methods such as the pill or condom, where use can cease at any moment, than it is for sterilization, where protec- tion continues automatically for many years. This is one reason why steriliza- tion use has risen to substantial levels in some countries even though rather few couples adopt it in each year. The time trend for each method in each of 22 large countries appears in Figure 2.2. Note that the vertical scales differ, to better clarify the method patterns. The outstanding feature in most countries is the dependence upon only two or at most three methods (and only one method in India and Algeria). However in some countries the sum of all other methods, in the aggregate, protects an appreciable proportion of couples. Seven modern methods of contraception have been available for enough time to reveal the emergent international pat- terns. These are immediately evident in Appendix Table A.1. Overall, the pill and female sterilization are the front runners. For family planning, the con- dom is not dominant in any country, but HIV/AIDS campaigns in some countries have substantially increased its distribu- tion. Except for a few countries (includ- ing China) vasectomy is unimportant. The IUD is important in some countries but not in most. Vaginal applications have won only trivial use, and the new implant methods are of significant use thus far mainly in Indonesia. Each of the methods is now discussed in more detail. Sterilization stands out in Asia, with high figures in the group of China, Tai- wan, South Korea, Hong Kong, and Singapore, and also in Thailand, Sri PAST TRENDS IN CONTRACEPTIVE USE Chapter 2Chapter 2Chapter 2Chapter 2Chapter 2 6 Chapter 2 Lanka, Nepal, Bangladesh, and India. Major exceptions, with little steriliza- tion use, are Indonesia, Viet Nam, and Myanmar. Most Asian sterilization is for females, but male sterilization is sub- stantial in China, South Korea, and Ne- pal (and historically in India and Bang- ladesh, although less so now). Latin America has also seen extensive use of female sterilization, in the two largest countries of Brazil and Mexico, and in Colombia, Costa Rica, Cuba, Do- minican Republic, Ecuador, El Salva- dor, Guatemala, Honduras, Jamaica, Nicaragua, Panama, and Puerto Rico. Little use is made of male sterilization. An exception to the extensive use of fe- male sterilization is the group of Mus- lim countries in the Middle East/North Africa region. In Appendix Table A.1, all countries but one are below 5% of couples using sterilization. Tunisia is the exception; there women with at least a few children have been able to obtain sterilization, and 15% were using it by 1994. On the other hand, Egypt has very little sterilization activity and follows what amounts to an informal policy against it. As a result, the IUD is espe- cially prominent in most Middle East/ North African countries. Sub-Saharan Africa has registered only small figures for sterilization, except for 18% of couples using it in South Africa (as of the 1998 national survey). The trend is up however, in Mauritius at 7%, and Namibia at 8%. The other countries with surveys show nearly negligible lev- els of use. The pill accounts for more use than any other method except sterilization; it is prominent in countries in all regions. Among the 22 large countries in Figure 2.2, it plays an important role (10% or more couples using it) in Brazil and Co- lombia in Latin America (only 8% in Mexico); Bangladesh, Indonesia, Philip- pines, and Thailand in Asia; Algeria, Egypt and Iran in Middle East/North Af- rica; and South Africa in sub-Saharan Africa. Among smaller countries, at above 10% are Hong Kong; Libya, Mo- rocco, United Arab Emirates; Botswana, Mauritius, Zimbabwe; Costa Rica, Do- minican Republic, Ecuador, Honduras, Jamaica, Nicaragua, Panama, Paraguay, and Trinidad and Tobago. In a number of other countries pill use is below 10% of couples but still serves an appreciable share of users. All in all, the pill plays a considerably wider role across many countries than does the IUD or inject- able. The IUD’s pattern is one of minor use in most countries but with major excep- tions – most notably in China, where over one-third of all couples use it. It is the number one method in Egypt, where 37% of couples rely on it; 24% do so in Jordan, 22% in Tunisia, 11% in Libya, 16% in Syria, and 20% in Turkey. Viet Nam has always stressed use of IUD, es- pecially in the North, and nearly 40% of couples use it nationwide. In Taiwan 22%, and in South Korea 13% do so. In Cuba a full 44% of couples use the IUD. The IUD is also prominent within the Central Asian Republics: 38% of cou- ples use it in Kyrgyzstan, 42% in Kazak- hstan, and 52% in Uzbekistan, for the highest figure recorded. A remarkable instance of regional con- trasts is the popularity of the IUD in the Middle East/North Africa versus its near absence in sub-Saharan Africa. By far most surveys, throughout the entire re- gion, show barely 3% of couples using it. The absence of this long-continuation method, together with the neglect of the sterilization method, help explain the low levels of contraceptive prevalence and the elevated fertility rates in the continent. The injectable method has won steadi- ly increasing popularity in many coun- tries. The outstanding cases are Indone- sia (a rapid rise to 28% of couples using it in the 2000/03 survey, or nearly half of all contraceptive users) and South Africa (23% in 1998). In five Latin American countries use has risen rapidly and 10% to 15% of couples now use it. Increases are also notable in some sub-Saharan Af- rican countries, especially Botswana (10%), Kenya (16%), Malawi (16%), and Swaziland (12%). The condom sees relatively little use by married couples nearly everywhere. The only recent surveys of married couples reporting more than 10% using it are in the East Asia cases of Hong Kong, Sin- gapore, South Korea, and Taiwan. Oth- ers include Costa Rica (16%), Jamaica (17%), Trinidad and Tobago (12%), Mauritius (13%), Botswana (11%), and Ukraine (11%). Other countries are around the 5% level of use, or close to zero. (One qualification is that informa- tion on methods comes chiefly from fe- male respondents, who may underreport condom use.) Also, special programs for HIV/AIDS have raised condom use in some countries. Traditional methods of withdrawal and rhythm are still very important. They account for a substantial share of all use in many countries. Appendix Table A.1 provides figures for the percentage of couples relying on traditional methods. In summary, most countries are quite se- lective in their use, or non-use, of the seven principal modern methods. Most use only two or three to any appreciable degree. Sterilization and the pill have emerged as the favorites, but with some irregularity, since most Muslim coun- tries shy away from sterilization (in fa- vor of the IUD) and certain large coun- tries make little use of the pill. The IUD is prominent in selected countries both in the Middle East and elsewhere; the injectable in fewer. Condoms are used least (although some HIV/AIDS cam- paigns are increasing its use). Plateaus in Contraceptive Prevalence and Total Fertility Rates Contraceptive prevalence, as shown in Figure 2.1, has shown impressive in- creases in many countries of the devel- oping world, so much so that pauses in the upward paths have seemed strange. They have also caused considerable concern by the agencies that implement population programs and the donors that provide assistance. Therefore the ques- tion has repeatedly been raised as to how common plateaus have been. A search for plateaus was conducted for the 52 developing countries that have had three or more surveys each, since a Chapter 2 7 plateau can be evident only when a rise appears between two surveys that fails to continue to the next survey. The flat period that ensues, if flat “enough,” con- stitutes a plateau. Clearly, most intervals between surveys show prevalence on the rise (Figure 2.3). In a few cases, at the lower end of the figure, the change has been negative or near zero. Some of those cases how- ever occurred in countries where preva- lence has always been very low and a clear upward trend has not yet taken form. In the same way, prevalence at high levels naturally levels off, since it cannot rise forever. We therefore focus upon those countries where prevalence has reached at least 25% and is still be- low 60%. The rule employed is that the prevalence rise has to be at or below 0.3 points per year (e.g., from 30 to 30.3) to qualify as a plateau. Alternative rules were also applied in the original analy- sis (Ross, Abel, and Abel, 2004). The results appear in Table 2.1. Only ten plateaus were found out of a possi- ble 159, or about 6%. Thus they are few, and they are not concentrated in any one region. The general conclusion, even if the rule were made more inclusive, is that plateaus have been quite uncom- mon in the middle range of prevalence, between 25% and 60%. Table 2.1. Number of Plateaus by Region Possible No. Actual Percent East and SE Asia 32 0 - South Asia 21 2 9.5 Latin America 49 1 2.0 Middle East/No. Africa 24 3 12.5 Sub-Saharan Africa 33 4 12.1 All Regions 159 10 6.3 Other parts of the analysis produced im- portant features: Brevity: nearly all plateaus terminate after only one survey interval. Only five countries had plateaus that lasted for two consecutive intervals. Non-repetition: plateaus rarely repeat. Only five countries experienced two plateaus at different times. Balance between modern and tradition- al methods: in some plateaus, use of modern methods still rose but use of tra- ditional methods fell, leaving overall use flat. In other cases traditional use rose but modern use fell. Thus substitu- tion of one type of use for the other can occur within an overall failure to rise. Causes of plateaus: multiple factors can be at work when prevalence levels off: ➤ Program weakening: the public pro- gram suffers losses of funding or leader- ship or serious interruption of supply lines. ➤ Narrow method mix: the sub-group of users who want (or can tolerate) the few methods available becomes saturated. ➤ Lack of long-term methods: if preva- lence is based just on resupply methods, with their poor continuation rates, it sel- dom rises to a high level. Most countries with high prevalence have considerable use of either sterilization or the IUD or both. ➤ Competition from HIV programs in some African countries may be a factor, if they attract away personnel and re- sources from family planning activities. Also, high levels of HIV can decimate the capacity of health infrastructures. ➤ A very strong program, as in Indone- sia historically, can saturate demand, leaving little unmet need. ➤ Measurement error can be at work, es- pecially when two surveys come close together and the real prevalence change between them is relatively small. Why Don’t Plateaus Repeat? One like- ly reason for the non-repetition of pla- teaus is the dismay they create among managers and donors. Corrective ac- tions have been taken in the historical experience of Bangladesh and Egypt for example, when a national survey showed an interruption of the upward course of contraceptive use. This is not surprising given the substantial commit- ments made in policy support and re- sources. A further possibility for the persistent rise in prevalence in so many countries over so many surveys is the combined influence of program improvements, private sector motivation, and general modernization including better educa- tion, more females in the labor force, ur- banization, and ideational change. Interesting Cases: considerable interest has been devoted to the stalling of prev- alence found in the 2003 Kenyan survey. This is under an intensive analysis that testifies to the concern occasioned by a failure to improve in every survey. Indo- nesia and Jordan are unusual in having a series of annual surveys, and both have 1 5 2 9 21 27 31 29 17 8 4 1 4 0 5 10 15 20 25 30 35 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 No. in each interval (inclusive up to each mark) Fr eq ue nc y Figure 2.3. Annual Pace of Prevalence Increase (points per year for 159 survey intervals) 8 Chapter 2 showed flat trends in recent years. How- ever the latest (2003) DHS survey in In- donesia showed a rise from the 1997 DHS survey (Figure 2.4). Program Responses: these take numer- ous forms and are usually selective. A first step is analytic, to determine whether the plateau occurred in every province, in both rural and urban areas, in each education group, etc. If the lack of change is common to all sub-groups that is one thing, but if for example it occurs only in the rural sector or the least favored provinces, that suggests other responses. Program strengthening can include a change in provincial lead- ership, an improvement in the method mix, stimulation of the private sector through more lenient regulations, or other measures. In summary, plateaus are uncommon; they seldom repeat; there is seldom more than one in a country; and they of- ten stimulate corrective actions. The overriding tendency is that once preva- lence reaches the range of about 25% it continues upward. At very low levels and very high levels the patterns are flat, but for quite different reasons. Use by Source by Method The available cross-national informa- tion on the sources of contraceptive sup- ply/services appears in Table 2.2 and Appendix Table A.2. Cautions are in order regarding data on both levels and trends for sources. The four categories used in the tables are the only workable ones across multiple sur- veys and time periods. Definitions of public and private have varied, some- times even in successive surveys in the same country. Also, the boundaries be- tween government and private are some- times unclear to the respondent, often justifiably so where they are truly mixed, as in some social marketing out- lets. By far most contraceptive users in the developing world rely upon the govern- ment for their supplies or services. Con- sidering only large countries that con- tain a substantial body of users, public (largely government) supply dominates in China, India, Bangladesh, Pakistan, Thailand, Viet Nam, Mexico, Kenya, Tanzania, and the Philippines. By merg- ing all modern methods, Table 2.2 shows the overall reliance upon govern- ment sources in many countries. Appen- dix Table A.2 gives the full detail for source by method, for countries with past surveys. Since the most popular method is steril- ization or the pill, it follows that govern- ment is heavily involved. Most steriliza- tion users reside in China and India, as well as Mexico and a few other countries of substantial size where government generally dominates services. Unlike sterilization sources, pill sources are mixed. When the pill became inex- pensive due to mass production in the late 1960s, governments began to add it to their method mix, and soon afterward private companies extended its use in countries where ministries of health per- mitted its sale under prescription or where informal practices flourished. Government is responsible for most pill supply in the Philippines, Thailand, and Tanzania. However, the private sector is the major source in Brazil, Colombia, Mexico, Egypt, Turkey, and Indonesia. In Kenya, public and private sources have equal shares of pill supply. The IUD is next in total use, after steril- ization and the pill. China has by far the largest body of IUD users, over 70 mil- lion or over three-fifths of all IUD users in the developing world. Government also provides most IUDs in Indonesia, Pakistan, Philippines, Thailand, Viet Nam, Kenya, Tanzania, Morocco, Tur- key, Mexico, and a number of smaller countries. (Appendix Table A.6 projects users by method for each country.) The various education and residence groups obtain their methods from some- what different sources, especially since commercial outlets and private medical personnel exist chiefly in the urban sec- tor; also, the education level is higher there. Age also matters, since older and higher parity women tend toward the longer, automatic-continuation methods of the IUD and sterilization more than younger women do. A summary of these differentials appears in Curtis and Neit- zel (1996). Trends in the Source Mix. A leading question is whether a shift in contracep- tive supply is occurring in favor of the private sector. That would relieve some of the burden on government and inter- national donors, especially as popula- tions grow and prevalence of use rises. However, in surveys to date there is only the most limited evidence that such a shift is occurring. Among 28 countries with time trend in- formation, the percentage of use due to the government (public) rose in 13 and Figure 2.4. Indonesia: Percent of Couples Using Contraception, by Type of Survey 26.8 38.5 47.8 49.7 54.7 57.4 60.3 54.2 55.5 55.4 55.4 54.8 52.5 54.2 0 10 20 30 40 50 60 70 19 80 19 81 19 82 19 83 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 Pe rc e n t U si ng DHS SERIES SUSENAS SERIES Chapter 2 9 fell in 5, with 10 changing very little. Definite changes occurred in Indonesia, where the public percentage fell over time from 76% to 43% to 30%. In Ken- ya the public share fell from 68% to 58% to 46%. In Peru however, the per- centage rose from 48% to 70% to 79%. Cost burdens on governments and do- nors are relieved when the private sector grows, with greater roles for pharma- cies, shops, and private medical person- nel and facilities. This may occur when a method such as the injectable gains popularity and is available through pharmacies or private midwives, as in Indonesia. It can occur when a vigorous private agency establishes a full service network, as in Colombia. It can also oc- cur when a government deliberately en- livens the private sector, though that is rare, occurring mainly in Indonesia his- torically. References Cohen, Barney. “The Emerging Fertility Transition in Sub-Saharan Africa.” World Development 26(8):1431-61. Au- gust 1998. Curtis, Sian L. and Katherine Neitzel. Contraceptive Knowledge, Use, and Sources. DHS Comparative Studies No. 19. Calverton, Maryland: Macro Inter- national Inc. 1996. Kirk, Dudley, and Bernard Pillet. “Fer- tility Levels, Trends, and Differentials in Sub-Saharan Africa in the 1980s and 1990s.” Studies in Family Planning 29(1):1-22. 1998. Ross, John, Edward Abel, and Katherine Abel. “Plateaus During the Rise of Con- traceptive Prevalence.” International Fam- ily Planning Perspectives 30(1):39-44. 2004. United Nations, World Population Pros- pects: the 2002 Revision, Volume 1. New York: United Nations Population Division. 2003. United Nations, “World Contraceptive Use 2003: Trends in Contraceptive Prevalence, 1990-2000.” Wall Chart. New York: United Nations Population Division. December 2003. 10 Chapter 2 Table 2.2. Sources of Supply for Modern Contraception Methods* Distribution of Modern Use By Source Private Other Country Year Public Medical Private Other Sum Asia Bangladesh 1999/2000 64.9 21.9 6.8 5.4 100 Cambodia 2000 45.5 24.0 24.6 2.5 100 India 1998/99 76.0 17.3 5.3 0.3 100 Indonesia 2003 29.6 61.0 7.2 2.2 100 Nepal 2001 79.4 7.7 7.3 4.8 100 Pakistan 2001 54.1 9.5 32.1 4.3 100 Philippines 1998 72.0 26.4 1.3 0.1 100 Sri Lanka 1987 85.3 6.7 4.0 2.0 100 Thailand 1987 83.6 7.9 7.0 1.0 100 Viet Nam 2002 74.8 23.9 0.2 1.2 100 Latin America Bolivia 1998 41.5 55.8 0.7 0.7 100 Brazil 1996 43.1 54.1 1.1 0.7 100 Colombia 2000 27.4 69.4 - 2.3 100 Dominican Republic 2002 34.8 26.3 33.1 5.7 199 Ecuador 1987 46.5 44.7 1.4 6.6 100 El Salvador 1985 88.8 3.3 6.4 1.4 100 Guatemala 1998/99 34.5 62.2 0.5 1.4 100 Haiti 2000 24.1 30.4 28.2 16.9 100 Mexico 1987 61.7 14.3 21.8 1.9 100 Nicaragua 2001 58.0 18.4 19.5 4.1 100 Paraguay 1990 18.7 18.5 58.1 4.2 100 Peru 2000 79.3 16.6 2.2 1.6 100 Trinidad and Tobago 1987 38.4 23.3 36.9 0.6 100 Middle East/North Africa Egypt 2003 41.2 56.5 0.1 2.2 100 Jordan 2002 43.3 56.5 - 0.2 100 Morocco 1995 62.6 37.1 0.2 0.2 100 Sudan 1990 58.1 13.1 26.2 2.0 100 Tunisia 1988 76.5 8.8 14.1 0.2 100 Turkey 1998 55.8 42.2 0.7 0.7 100 Yemen 1987 49.4 47.5 - 0.2 100 Sub-Saharan Africa Benin 2001 45.5 23.4 26.7 3.2 100 Botswana 1988 94.2 3.5 1.3 0.3 100 Burkina Faso 1998/99 75.3 6.3 15.7 2.6 100 Burundi 1987 86.7 1.2 9.3 2.8 100 Cameroon 1998 31.9 39.5 27.8 0.4 100 Central African Rep. 1994/95 49.3 31.7 13.2 2.5 100 Chad 1996/97 59.3 11.5 4.2 24.4 100 Côte d’Ivoire 1998/99 30.8 35.8 28.6 3.6 100 Eritrea 2002 58.6 19.6 0.0 21.8 100 Ethiopia 2000 77.5 15.5 5.8 0.3 100 Gabon 2000 26.5 50.7 17.2 4.2 100 Ghana 1998 46.7 46.1 4.7 1.4 100 Guinea 1999 49.9 21.0 21.1 4.6 100 Kenya 2003 45.8 41.0 11.7 1.6 100 Liberia 1986 31.1 53.9 13.1 1.6 100 Madagascar 1997 52.1 39.2 7.6 0.6 100 Malawi 2000 68.0 15.3 4.0 12.4 100 Mali 2001 51.8 33.6 11.1 1.4 100 Mauritania 2000/01 69.2 22.4 0.1 6.5 100 Mozambique 1997 82.7 8.5 4.6 2.0 100 Namibia 2000 77.4 19.6 2.8 0.2 100 Niger 1998 83.6 9.1 6.9 - 100 Nigeria 2003 34.2 53.4 1.7 10.8 100 Rwanda 2000 69.0 22.6 7.2 0.9 100 Senegal 1997 68.3 21.1 9.1 0.7 100 South Africa 1998 83.6 14.4 0.3 0.6 100 Tanzania 1999 67.2 21.8 10.4 0.1 100 Togo 1998 48.0 14.8 35.8 0.2 100 Uganda 2000/01 36.0 46.1 15.7 1.4 100 Zambia 2001/02 60.9 20.4 17.1 0.4 100 Zimbabwe 1999 76.7 16.5 2.6 3.8 100 Central Asia Republics Kazakhstan 1999 89.5 6.9 - 2.5 100 Kyrgyzstan 1997 96.9 0.6 1.1 0.3 100 Turkmenistan 2000 98.5 1.0 0 0.2 100 Uzbekistan 1996 98.3 0.3 0.2 0.2 100 Caucasus Armenia 2000 88.2 3.0 - 1.8 100 *Male sterilization and vaginal methods are omitted due to small numbers of users in some survey samples. Column figures may not add to 100% since “missing” and “don’t know” replies are omitted. Source: Demographic and Health Surveys. Chapter 2 11 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Botswana Eritrea Ghana Kenya Lesotho Malawi Namibia Nigeria South Africa Swaziland Tanzania Uganda Zambia Zimbabwe 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Benin Burkina Faso Burundi Cameroon CenAfrRep Chad Congo, DR Cote d'Ivoire Guinea Madagascar Mali Mauritania Mauritius Niger Rwanda Senegal Togo 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Costa Rica Cuba Domin. Rep. El Salvador Guatemala Haiti Honduras Jamaica Mexico Nicaragua Panama Puerto Rico Trin & Tob 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Brazil Colombia Ecuador Paraguay Peru 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Algeria Egypt Iran Iraq Jordan Kuwait Lebanon Libya Morocco Oman Saudi Arabia Sudan Syria Tunisia Turkey U.A.E. Yemen 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 China Hong Kong Korea, Rep. Taiwan 2005 2005 2005 2005 2005 2005 Figure 2.1. Percentage Using Contraception Figure 2.1a Figure 2.1b Figure 2.1c Figure 2.1d Figure 2.1e Figure 2.1f Anglophone Africa Francophone Africa Central America and Caribbean South America East AsiaMiddle East/North Africa 12 Chapter 2 Algeria 0 5 10 15 20 25 30 35 40 45 50 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Bangladesh 0 5 10 15 20 25 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Brazil 0 5 10 15 20 25 30 35 40 45 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional China 0 5 10 15 20 25 30 35 40 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Cambodia Indonesia Laos Malaysia Myanmar Philippines Singapore Thailand Viet Nam 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 Bangladesh India Nepal Pakistan Sri Lanka 2005 2005 Figure 2.1g Figure 2.1h Figure 2.1. Percentage Using Contraception (Cont.) Figure 2.2. Time Trends for Percent of Married Women using Each Contraceptive Method Figure 2.2a Figure 2.2b Figure 2.2c Figure 2.2d Southeastern Asia Southern Asia Chapter 2 13 Colombia 0 5 10 15 20 25 30 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Egypt 0 5 10 15 20 25 30 35 40 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Ethiopia 0 1 1 2 2 3 3 4 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional India 0 5 10 15 20 25 30 35 40 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Indonesia 0 5 10 15 20 25 30 35 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Jordan 0 5 10 15 20 25 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Figure 2.2e Figure 2.2f Figure 2.2g Figure 2.2h Figure 2.2i Figure 2.2j Figure 2.2. Time Trends for Percent of Married Women Using Each Contraceptive Method (Cont.) 14 Chapter 2 Kenya 0 2 4 6 8 10 12 14 16 18 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Mexico 0 5 10 15 20 25 30 35 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Myanmar 0 2 4 6 8 10 12 14 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Nigeria 0 1 2 3 4 5 6 7 8 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Pakistan 0 1 2 3 4 5 6 7 8 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Philippines 0 5 10 15 20 25 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Figure 2.2k Figure 2.2l Figure 2.2m Figure 2.2n Figure 2.2o Figure 2.2p Figure 2.2. Time Trend for Percent of Married Women Using Each Contraceptive Method (Cont.) Chapter 2 15 South Africa 0 5 10 15 20 25 30 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Tanzania 0 1 2 3 4 5 6 7 8 9 10 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Thailand 0 5 10 15 20 25 30 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional 0 5 10 15 20 25 30 35 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Turkey Viet Nam 0 5 10 15 20 25 30 35 40 45 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Zimbabwe 0 5 10 15 20 25 30 35 40 1980 1985 1990 1995 2000 2005 F ster M ster Pill Inj/Implant IUD Condom Vaginals Traditional Figure 2.2q Figure 2.2r Figure 2.2s Figure 2.2u Figure 2.2t Figure 2.2. Time Trend for Percent of Married Women Using Each Contraceptive Method (Cont.) Figure 2.2v Chapter 3 17 This chapter presents projections from 2005 through 2020 for numbers of wom- en, contraceptive users, needed commod- ities, and commodity costs. The chapter is based upon the UN 2004 projections for numbers of women aged 15-49 and their total fertility rates, as well as upon a large body of national surveys that provide prevalence of use by method. The starting point is a projection of fu- ture prevalence for 116 countries, based upon the relationship of prevalence to the UN total fertility rates as shown in Figure 3.1. The projections are adjusted at the beginning to agree with the latest survey estimates or, for those lacking a survey, the regional average. Given the prevalence projections, other results fol- low as described below. Percentage using each method. To pro- duce projections for individual contra- ceptive methods, the body of past na- tional surveys was used to establish the relationship between total use and each method’s use. On average each method’s share changes through time as total use rises (Figures 3.2a and 3.2b), so the projected method mix in each country depends upon its path for total use. Two different sets of equations were used (given in the Technical Appendix) for Muslim and non-Muslim countries, since the mix in Muslim countries tends on average to contain less sterilization and more IUD use than elsewhere. The starting method mix was adjusted to match the actual mix in the most recent survey, just as total use was adjusted. Appendix Tables A.5.a-d provide the es- timates for total use and use by method for the 116 countries from 2005-2020. Also of interest is Appendix Table A.1, which contains all national surveys from 1980 onward, with sources provid- ed at the end. Numbers of users by method. To project the number of users of each method, the UN projections for numbers of women aged 15-49 were employed in combina- tion with the percent of women relying on each method. This was done for all women and also for married/cohabiting Figure 3.1. Contraceptive Prevalence and Total Fertility Rate Chapter 3Chapter 3Chapter 3Chapter 3Chapter 3 FUTURE TRENDS IN CONTRACEPTIVE USE women, using the UN proportions of married women as updated from recent surveys (proportions married are kept constant through time). Appendix Ta- bles A.6.a-d give the number of users by method for 2005-2020. (The propor- tions married appear in Appendix Table A.4.) Adjustments were made to these proce- dures to allow for a few special country cases, as when the original method mix was very unusual, and especially if total prevalence was already high and quite stable; for example in China most use for many years has been of male and fe- male sterilization and the IUD, at high levels, and in Brazil most use has been stable for female sterilization and the pill. Wherever total prevalence was al- ready above 65% the mix in the latest survey was kept constant, and this rule was applied also to India and to Indone- sia, where the mix was expected to change little, at least in the next five years. Commodities needed by method. The quantities of commodities needed were calculated for each method and each fu- ture year by reference to couple years of protection (CYP). One year of protection requires 15 pill cycles (rather than 13, to allow for wastage), 120 condoms or vaginal tablets, or 4 injectables. An IUD lasts 3.5 years on average and a male or female sterilization lasts about 9 years. (For CYP data see Stover et al., 1997, and Stover, Bertrand, and Shelton, 2000.) Quantities of commodities need- ed were obtained by these CYP values, applied to the numbers of users in each year. For the IUD and sterilization the commodities required depend upon new adoptions, which on average follow the time path for increasing users. (Method- ological details appear in the Technical Appendix.) Numbers of commodities by method for 2005-2020 are in Appendix Tables A.7.a-d. Costs for each method. Commodity costs were calculated by simply multi- plying the cost per method times its quantity in each year. The costs were in- creased by 10% to allow for internation- al transportation, but they do not in- clude costs for personnel, facilities, or any of the associated services and they do not adjust for inflation. Costs were calculated at US 24 cents per pill cycle, 96.5 cents per injectable dose, 3.5 cents per condom, 7.2 cents per vaginal ap- plication, 57.6 cents per IUD adoption, US$9.09 for female sterilization adop- tion and US$4.95 for male sterilization adoptions. (If modifications of these rules are preferred they can be easily 0 10 20 30 40 50 60 70 80 90 0 1 2 3 4 5 6 7 8 Total Fertility Rate C o n tr ac ep ti ve P re va le n ce 18 Chapter 3 applied to the numbers of users in the Appendix to generate alternative cost estimates.) Appendix Tables A.8.a-d give costs for each commodity by meth- od for 2005-2020. Summary. The various approaches above cover the essential features and yield estimates for prevalence, method mix, users, commodities, and costs for the 116 countries through time, taking into account numbers of women and proportions married. The following sec- tions discuss the results. Projections for the Percentage Using Contraception Because our projections for increases in contraceptive prevalence are governed by the declines in total fertility rates (TFRs), there is a U-shaped pattern to the prevalence projections. Countries with very high or very low TFRs are pro- jected to change least, while countries in the middle range are projected to change more rapidly. When the TFRs are translated to prevalence values the re- sults appear as shown in Table 3.1. Countries that in 2005 have prevalence below 10% improve only by 4.4 points by 2020, while countries in the middle, at 30-39%, improve by a full 15.9 points. At the highest level, 70% or above, the av- erage change is zero, with some coun- tries slightly above and some slightly below, depending upon the small chang- es in the TFR when it is near replace- ment. Next, changes in the method mix follow the average patterns in Figures 3.2a and 3.2b as noted above. In Muslim coun- tries, as total prevalence rises to about 25% (bottom axis), the share due to tra- ditional methods lessens while the shares due to the IUD and the pill gain sharply. At higher prevalence levels the pill loses ground to the IUD. The picture is quite different in the non-Muslim countries, where traditional method use is replaced by a gradual increase in fe- male sterilization, and secondarily by an increase for the IUD. The injectable plays a larger role in non-Muslim than in Muslim countries. The share of the pill is not much different between the Figure 3.2b. Method Mix – Non-Muslim Countries This model shows, on average, how method mix changes as total prevalence of use rises, as registered in past national surveys in many developing coun- tries. Traditional method use, at the top, declines as a proportion of all use, while female sterilization increases considerably. Pill use declines, while IUD use increases somewhat, as does condom use. Minor roles on average are played by male sterilization, injectables, and such vaginals as foaming tablets. Note that all these changes are relative ones, adding to 100 percent of use. Be- cause total use is increasing, up to about 80% of all couples, the number of pill users for example will be larger than suggested by the relative decline. This model is used for the projections of use by method in this report, with ad- justments for Muslim countries, whose method mix shows less sterilization and more IUD use, etc., and for certain other countries. See Appendix B, Technical Appendix for Projection Methods, for details. Figure 3.2a. Method Mix – Muslim Countries Pill Injection IUD Condom Female Sterilization Traditional Method 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Contraceptive Prevalence Male Sterilization Vaginal Application Pill Injection IUD Condom Female Sterilization Traditional Method 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Contraceptive Prevalence Male Sterilization Vaginal Application Pill Injection IUD Condom Female Sterilization Traditional Method 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Contraceptive Prevalence Male Sterilization Vaginal Application Pill Injection IUD Condom Female Sterilization Traditional Method 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Contraceptive Prevalence Male Sterilization Vaginal Application Pill Injection IUD Condom Female Sterilization Traditional Method 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Contraceptive Prevalence Male Sterilization Vaginal Application Pill Injection IUD Condom Female Sterilization Traditional Method 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Contraceptive Prevalence Male Sterilization Vaginal Application Chapter 3 19 two; the chief difference is in the strong preference for the IUD over sterilization in the Muslim group at the higher TFR levels. Projections for Total Numbers Using Contraception The numbers of contraceptive users will increase very substantially in the future due to population growth. As seen in Table 3.2, sizeable growth will occur in the numbers of married women and all women. (Because the percents married are kept constant the rates are nearly the same; minor differences occur be- cause country weights change as some countries grow more slowly than oth- ers.) Within five years 100 women will be replaced by 107 women, and by 115 women within 15 years. This is highly variable by country; China’s very slow growth affects the averages, which are higher elsewhere and are especially high in sub-Saharan Africa. The same overall growth will occur for married users, and it will be substantial- ly more for all users, to 119 users for ev- ery 100 now. Growth for users is much higher in many countries due to the dou- ble force of population growth and in- creases in the proportions using a meth- od. The figures also vary by region: they are much higher for sub-Saharan Africa and are higher in general when China is omitted. All this creates similar increases in resources needed, including supplies, facilities, training, and service arrange- ments. Even in the next five years, an increase of 9.1% must be absorbed. The sharp re- gional differences are apparent in Figure 3.3a, from China’s 2% rise to sub-Sahar- an Africa’s 30%. Note however that the predicted rise in contraceptive use in these projections is approximately tied to the UN projections for declines in the total fertility rates, and those are proba- bly optimistic in the case of sub-Saharan Africa. If fertility falls less than expect- ed, the associated rise in contraceptive use will be less. However, it is best for donors and governments to plan for more users rather than fewer, as a hedge against the usual shortages and interrup- tions in supply lines and services. Paralleling Figure 3.3a is Figure 3.3b, to show the regional pattern for the 15-year increases. It is very similar in appearance to Figure 3.4 except that sub-Saharan Af- rica’s increase is now more than double the next highest region, reflecting the long-range effects of the very young age structure in most countries there. In Chi- Table 3.2. Percentage Increases in Numbers of Married Women, All Women, Married Users, and All Users No. of No. of All No of No. of Married Women Women Married All Aged 15-49 Aged 15-49 Users Users 2005 - 2010 6.6 6.7 7.1 9.1 2005 - 2015 11.6 11.8 13.2 16.3 2005 - 2020 15.3 15.6 17.8 22.0 Figure 3.3a. Percent Increase Over the Next Five Years in Number of Contraceptive Users, 2005-2010, by Region Figure 3.3b. Percent Increase over the Next Fifteen Years in Number of Contraceptive Users, 2005-2020, by Region Table 3.1. Projected Increases in Prevalence According to Starting Level Starting Level Gain from (in 2005) 2005 2010 2015 2020 2005 to 2020 0-9% 7.3 8.0 9.5 11.7 4.4 10-19% 14.9 16.7 19.6 23.5 8.6 20-29% 25.4 28.5 32.8 37.6 12.3 30-39% 33.9 38.1 43.8 49.7 15.9 40-49% 44.8 48.5 52.6 56.3 11.5 50-59% 56.6 59.3 62.4 65.2 8.6 60-69% 64.8 66.3 67.6 68.4 3.6 70+ 76.5 76.7 76.7 76.5 0.0 1.7 15.6 12.1 9.2 16.6 30.1 0.7 9.1 0 5 10 15 20 25 30 35 China India Rest of Asia Latin America Middle East/North Africa Sub- Saharan Africa Central Asia Republics Caucasus Grand Total Pe rc en t I nc re as e 10.9 (6.8) 42.4 29.7 21.6 49.2 119.8 25.5 (8.2) 22.0 -20 0 20 40 60 80 100 120 140 China India Rest of Asia Latin America Middle East/North Africa Sub- Saharan Africa Central Asia Republics Caucasus Grand Total Pe rc en t I nc re as e 20 Chapter 3 na and in the Caucasus small declines occur, again due to the changing age structure. Turning to absolute numbers to be served, Figure 3.4 shows the changes. China again, although having the larg- est numbers, stabilizes at about 200 mil- lion users. India is slated to experience a drastic rise, nearly reaching China’s lev- el, due to the combination of population growth and a rise in the proportion using contraception. The rest of Asia will also face rapid growth, due not only to rising prevalence of use but also to the young age structures in Pakistan, Bangladesh, Indonesia, and elsewhere. Latin America and the Middle East/North Africa can expect milder increases, unlike sub-Sa- haran Africa where rapid growth is pro- jected. By method, users in 2005 are distribut- ed for each region in Table 3.3. Some 618 million users are estimated, 72% of them in Asia (see also the top three lines in Figure 3.5). Male and female steril- ization dominate in Asia, where they ac- count for 50% of users, and sterilization accounts for 45% of users in Latin Amer- ica. The IUD is next at over one-fifth of all users due largely to its extensive use in China. In percentage terms its share of use is exceptionally high in the Middle East/North Africa at one-third and in the former Soviet Union areas at above one- fifth. After the IUD comes the pill at 12% of all users. In general, only two methods account for most use within each region, al- though the two methods are not always the same: sterilization and the IUD in Asia; sterilization and the pill in Latin America; the IUD and pill in the Middle East/North Africa (and the IUD alone in the Central Asia Republics). In sub-Sa- haran Africa over 40% of use is due to the pill and injectable; 45% is due to the pill and IUD in the Caucasus. The overall pattern is that two modern methods, out of the seven candidates, emerge in each region as dominant. The eighth choice, traditional methods, con- tinues to be very important in both sub- Saharan Africa and the Middle East/North Africa, at 25%-30% of use respectively, and also in the former Soviet Union. User increases overall are projected at 9% by 2010 and by 16% by 2015, but higher for the pill (21%). Lesser increases occur for other methods, except for vaginals (small base in 2005) and traditionals. For absolute numbers the main annual in- creases are for female sterilization, 50 million more in 2020 than in 2005. Sterilization Any Region Total Female Male Pill Injectable IUD Condom Vaginals Traditional Number of Users (000), 2005 Asia 444,695 191,181 33,084 39,358 19,856 107,028 21,395 220 32,572 Latin America 72,639 30,624 1,735 14,600 3,612 7,946 4,844 265 9,013 Middle East/North Africa 30,406 2,266 45 7,287 1,223 10,000 1,882 272 7,430 Sub-Saharan Africa 35,498 3,953 260 7,724 7,984 2,347 2,431 250 10,550 Central Asia Republics 6,723 363 10 656 221 4,042 373 30 1,027 Caucasus 1,524 279 15 357 116 328 85 12 331 Moldova, Russia, Ukraine 26,761 6,488 826 3,105 690 5,871 3,920 210 5,651 Grand Total 618,246 235,154 35,976 73,087 33,703 137,562 34,930 1,259 66,575 Percent Distribution Within Each Region, 2005 Asia 100 43.0 7.4 8.9 4.5 24.1 4.8 0.0 7.3 Latin America 100 42.2 2.4 20.1 5.0 10.9 6.7 0.4 12.4 Middle East/North Africa 100 7.5 0.1 24.0 4.0 32.9 6.2 0.9 24.4 Sub-Saharan Africa 100 11.1 0.7 21.8 22.5 6.6 6.8 0.7 29.7 Central Asia Republics 100 5.4 0.2 9.8 3.3 60.1 5.5 0.4 15.3 Caucasus 100 18.3 1.0 23.4 7.6 21.5 5.6 0.8 21.7 Moldova, Russia, Ukraine 100 24.2 3.1 11.6 2.6 21.9 14.6 0.8 21.1 Grand Total 100 38.0 5.8 11.8 5.5 22.3 5.6 0.2 10.8 Total Numbers by Date (000), 2005-2020 2005 618,246 235,154 35,976 73,087 33,703 137,562 34,930 1,259 66,575 2010 674,595 256,401 37,456 81,408 36,788 146,061 38,274 1,537 76,672 2015 719,142 273,040 37,904 88,758 39,679 151,018 41,143 1,804 85,798 2020 754,284 285,353 37,246 95,575 42,107 153,319 44,013 2,078 94,593 Percent Growth in Users by Period, 2005-2020 2005 to 2010 9.1 9.0 4.1 11.4 9.2 6.2 9.6 22.0 15.2 2005 to 2015 16.3 16.1 5.4 21.4 17.7 9.8 17.8 43.3 28.9 2005 to 2020 22.0 21.3 3.5 30.8 24.9 11.5 26.0 65.1 42.1 Table 3.3. Projected Numbers (000s) and Percent of Contraceptive Users Among All Women, by Method, by Region for 2005, and for Four Dates 2005-2020 Chapter 3 21 Projections for Commodities Needed, by Method The user numbers above translate direct- ly into commodity needs by the rules explained above, based on couple years of protection. For example, the number of pill cycles needed in any country in 2005 is simply 15 times the number of users in that year. Note that the steriliza- tion figures are simply estimates for the number of procedures done annually, as a basis for country calculations (not in- cluded) of the kits and other supplies needed. Appendix Table A.5 projects the needs for each method by country and year, with regional totals. Here we sim- ply show the overall rise in total com- modities needed for pills, condoms, IUDs, and injectables for the developing world as a whole (Figure 3.4). Note that the condom figures are understated since they omit the need for disease pre- vention. Chapter 7 covers additional condom requirements. Percent Growth Region 2005 2010 2015 2020 2005 - 2010 2005 - 2015 2005-2020 China 190,332 193,657 189,661 177,471 1.7 (0.4) (6.8) India 145,278 167,896 188,581 206,841 15.6 29.8 42.4 Rest of Asia 257,291 282,694 302,364 317,716 9.9 17.5 23.5 Latin America 134,559 146,785 155,665 163,140 9.1 15.7 21.2 Middle East/North Africa 49,685 56,832 63,212 69,328 14.4 27.2 39.5 Sub-Saharan Africa 83,065 103,543 130,669 163,725 24.7 57.3 97.1 Central Asia Republics 6,688 9,004 10,869 12,060 34.6 62.5 80.3 Caucasus 2,793 2,807 2,671 2,556 0.5 (4.3) (8.5) Moldova, Russia, Ukraine 44,103 40,753 37,109 34,835 (7.6) (15.9) (21.0) Total 913,793 1,003,971 1,080,801 1,147,672 9.9 18.3 25.6 Table 3.4. Total Commodity Costs by Region and Year (thousands of U.S. dollars) Figure 3.4. Users of All Contraceptive Methods, 2005-2020, by Region Finding ways to cope with these large increases in users and commodities will occupy donors and governments for the foreseeable future. The role of the pri- vate sector will be quite important as a way of relieving these burdens. Howev- er, more creative ways are needed than those used heretofore if private sectors in many countries are to significantly enlarge their contribution. Projections for Commodity Costs As explained above, costs are calculated only for the purchase of commodities, with an addition of 10% to allow for in- ternational transportation costs. Table 3.4 presents total costs (for all methods) by region and year. China and India mainly cover their own commodities, and the largest costs occur in the Rest of Asia. Latin American comes next with its relatively high prevalence of use, and then sub-Saharan Africa, where preva- lence and the number of users is smaller. However sub-Saharan Africa will experi- ence an exceptionally fast growth of costs, rising by one-fourth by 2010, by over one-half by 2015, and almost dou- bling by 2020. Growth is rapid in India and in the Middle East/North Africa. It is also rapid in the Central Asian Repub- lics, reflecting the expected shift to modern contraceptives there. Costs should decline in China since total prev- alence is already high and flat, and the age structure will change toward fewer women aged 15-49. This is also expect- ed in Moldova, Russia, and Ukraine. For the developing world as a whole costs are projected to increase by 10% by 2010, 18% by 2015, and 26% by 2020. References Abou-Zahr, Carla and Tessa Wardlaw, “Maternal Mortality in 2000: Esti- mates Developed by WHO, UNICEF, and UNFPA.” http://www.childinfo.org/ maternal mortality in 2000.pdf. Henshaw, Stanley K., Susheela Singh, and Taylor Haas. “The Incidence of Abortion Worldwide.” International Family Planning Perspectives. Vol. 25, Supplement. Pages S30-S37. 1999. Stover, John et al. Empirically Based Conversion Factors for Calculating Couple-Years of Protection. The EVAL- UATION Project. Carolina Population Center, Tulane University, and The Fu- tures Group International. 1997. Pub- lished also in the Evaluation Review, Vol. 24, No. 1, pp. 3-46, Feb. 2000. Sage Foundation. - 50,000 100,000 150,000 200,000 250,000 2005 2010 2015 2020 China India Rest of Asia Latin America Middle East/North Africa Sub-Saharan Africa Central Asia Republics N um be r o f U se rs (0 00 ) 22 Chapter 3 UNAIDS. Report On the Global AIDS Epidemic: 4th Global Report. Geneva: Joint United Nations Programme on HIV/AIDS. 2004. United Nations Population Division. World Population Prospects: The 2002 Revision. Volume I: Comprehensive Ta- bles. New York: United Nations. 2003. WHO Division of Reproductive Health. Unsafe Abortion: Global and Regional Estimates of the Incidence of Unsafe Abortion and Associated Mortality in 2000. Fourth Edition. Geneva: WHO. 2004. Figure 3.5. Projection of Annual Commodity Needs, Four Methods, 2005-2020, Developing World Total Number of Pill Cycles Needed (000) Total Number of Condoms Needed (000) for Family Planning (see Chapter 7 for information on Condom needs for HIV/AIDS) Total Number of IUDs Needed (000) Total Number of Injectables Needed (000) 1,096,306 1,221,123 1,331,368 1,433,625 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 2005 2010 2015 2020 4,191,594 4,592,916 4,937,106 5,281,562 2005 2010 2015 2020 39,303 41,732 43,148 43,806 2005 2010 2015 2020 134,811 147,151 158,716 168,429 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 2005 2010 2015 2020 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 37,000 38,000 39,000 40,000 41,000 42,000 43,000 44,000 45,000 Chapter 4 23 This chapter concerns demands on ser- vices, in both public and private sectors, that are implicit in increases in the sheer numbers of women, married women, and deliveries – depending however upon the region. In a few instances the population numbers will actually decline, but growth overall will be substantial in ev- ery five-year period. Births are projected to grow mainly in sub-Saharan Africa, not overall. Special attention goes to the growing numbers of youth, and contra- ceptive use among both married and sin- gle women. Unmet needs among youth are presented both for attendance at birth and for contraception services. Finally, HIV/AIDS among youth is briefly pre- sented. Growing Numbers of Women, Married Women, and Deliveries While the number of women, and mar- ried women, will certainly rise substan- tially in the developing world, the num- ber of births will not, according to the UN’s projections (Appendix Tables A.3- A.4). However this differs by region: Figure 4.1 (on the next page) shows the trends for China, India, and the major regions. Note that the numbers of women to ex- pect in the next 15 years are already born so the projections are fairly reli- able; also the proportions married through time are held constant, so the numbers married mirror those for all women but at lower levels. China’s age structure is such that a decline is expect- ed in numbers of women; the number of births also falls. India is different: large increases are projected for numbers of women, but the UN anticipates enough of a fall in the fertility rate to cause an actual decline in the number of births. In the rest of Asia, large increases are ex- pected for the population of women but births decline slightly. The other regions vary: in sub-Saharan Africa both women and births increase very sharply. In Latin America and the Middle East/North Africa, women be- come more numerous but births do not. The other three regions, all parts of the former USSR, are variable: more women are projected only in the Central Asia Republics, and the least declines in births in the Caucasus. The percentage changes for the regions are given in Table 4.1. Apart from Chi- na and the former USSR areas, all devel- oping areas experience substantial growth in each five-year period, on an ever-growing base. The picture for births is quite different, as explained above. Table 4.1. Percent Increases for Women, Married Women, and Births, by Region, 2005-2020 Percent Increases in Numbers of Women Aged 15-49 2005 to 2010 2010 to 2015 2015 to 2020 2005 to 2020 China 1.7 (2.0) (5.7) (6.0) India 8.9 7.2 5.0 22.5 Rest of Asia 8.9 6.8 5.7 22.9 Latin America 6.3 4.5 3.5 15.0 Middle East/North Africa 10.7 8.8 8.3 30.5 Sub-Saharan Africa 12.4 12.6 12.8 42.7 Central Asia Republics 6.2 3.1 3.3 13.1 Caucasus 0.6 (4.5) (3.2) (6.9) Moldova, Russia, Ukraine (6.7) (8.1) (6.2) (19.6) ALL REGIONS 6.7 4.8 3.5 15.6 Percent Increases in Numbers of Married Women Aged 15-49 China 1.7 (2.0) (5.7) (6.0) India 8.9 7.2 5.0 22.5 Rest of Asia 9.1 7.1 5.9 23.7 Latin America 6.3 4.5 3.5 15.0 Middle East/North Africa 10.7 8.9 8.3 30.5 Sub-Saharan Africa 12.9 13.1 13.3 44.7 Central Asia Republics 6.4 3.3 3.4 13.6 Caucasus 0.6 (4.5) (3.2) (7.0) Moldova, Russia, Ukraine (6.7) (8.1) (6.2) (19.6) ALL REGIONS 6.6 4.7 3.3 15.3 Percent Increases in Numbers of Births China 0.1 (1.5) (5.2) (6.5) India (1.2) (1.5) (3.1) (5.7) Rest of Asia 1.4 (0.1) (1.9) (0.6) Latin America (1.8) (2.3) (2.8) (6.8) Middle East/North Africa 2.5 (0.1) (0.7) 1.8 Sub-Saharan Africa 5.7 4.0 2.8 13.0 Central Asia Republics 0.0 (3.3) (6.1) (9.2) Caucasus 2.1 0.4 (5.3) (2.8) Moldova, Russia, Ukraine (0.2) (4.8) (9.1) (13.6) ALL REGIONS 1.4 0.1 (1.6) (0.1) Births for 22 large countries are high- lighted in Table 4.2. This list, in order by number of births in 2005, echoes the large role being played by India in all demographic matters. It has more births than China, and more than the next five countries together, or alternately, more than the bottom 14. Ten of these countries are projected by the UN to experience birth declines over the next 5 years. Posed against those are the large percentage of increases coming in Afghanistan (13%), D.R. Congo (9%), DEMANDS ON SERVICES Chapter 4Chapter 4Chapter 4Chapter 4Chapter 4 24 Chapter 4 Table 4.2. Number of Births Annually and Percentage Change for 22 Large Countries, 2005-2020 Number of Births (000s) Percentage Change 2005 2010 2015 2020 2005-2010 2010-2015 2015-2020 2005-2020 India 25,027 24,733 24,355 23,607 (1.2) (1.5) (3.1) (6) China 18,795 18,824 18,534 17,565 0.1 (1.5) (5.2) (6.5) Pakistan 5,672 6,022 6,189 6,164 6.2 2.8 (0.4) 8.7 Nigeria 4,909 5,088 5,136 5,093 3.6 0.9 (0.8) 3.7 Indonesia 4,479 4,380 4,242 4,074 (2.2) (3.1) (4.0) (9.1) Bangladesh 4,187 4,151 4,094 4,020 (0.8) (1.4) (1.8) (4.0) Brazil 3,438 3,324 3,188 3,048 (3.3) (4.1) (4.4) (11.4) Ethiopia 3,089 3,324 3,531 3,657 7.6 6.2 3.6 18.4 Congo DR 2,776 3,038 3,253 3,447 9.4 7.1 6.0 24.2 Mexico 2,265 2,189 2,100 2,000 (3.4) (4.1) (4.8) (11.7) Philippines 1,995 1,979 1,965 1,934 (0.8) (0.7) (1.6) (3.1) Egypt 1,967 2,020 1,960 1,885 2.7 (3.0) (3.8) (4.2) Viet Nam 1,646 1,682 1,684 1,611 2.1 0.2 (4.3) (2.1) Iran 1,465 1,569 1,553 1,408 7.1 (1.0) (9.4) (3.9) Turkey 1,459 1,404 1,325 1,274 (3.8) (5.6) (3.9) (12.7) Tanzania 1,456 1,481 1,476 1,441 1.7 (0.4) (2.3) (1.0) Uganda 1,393 1,589 1,794 2,002 14.1 12.9 11.6 43.8 Russia 1,237 1,241 1,182 1,073 0.3 (4.8) (9.2) (13.3) Afghanistan 1,217 1,378 1,486 1,559 13.2 7.8 4.9 28.1 Myanmar 1,147 1,101 1,065 1,025 (4.0) (3.3) (3.8) (10.7) Sudan 1,095 1,081 1,066 1,062 (1.2) (1.4) (0.4) (3.0) Thailand 1,061 1,023 993 970 (3.6) (2.9) (2.4) (8.6) Figure 4.1a. Numbers of Women Aged 15-49, by Region, 2005-2020 (000) Figure 4.1c. Numbers of Births Annually, by Region, 2005-2020 (000) Figure 4.1b. Numbers of Married Women Aged 15-49, by Region, 2005-2020 (000) 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 2005 2010 2015 2020 3 1 2 6 4 5 9 7 8 (1) China (2) India (3) Rest of Asia (4) Latin America (5) Middle East/North Africa (6) Sub-Saharan Africa (7) Central Asia Republics (8) Caucasus (9) Moldova, Russia, Ukraine Key: 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 2005 2010 2015 2020 0 3 1 2 6 4 5 9 7 8 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 2005 2010 2015 2020 3 1 2 6 4 5 9 7 8 Chapter 4 25 Ethiopia (8%), Iran (7%), Pakistan (6%), and Uganda (14%). This points to the need for plans that are specific to each country, notwithstanding the overall pic- ture of stability in birth numbers. Moreover, nearly every country needs substantial improvement in coverage and quality of services, so any relief from rising numbers of births does not allow for any relaxation of effort. Quite the contrary, especially since the picture given here depends heavily upon future fertility trends that may differ from those assumed. Youth: Current Needs and Services About one billion youth, aged 15-24, in- habit the developing world. They make up a fifth (19%) of the total population and will become a considerably larger share over the next decade in many countries. Selected highlights follow from UN projections and Appendix Ta- ble A.24, with information also on un- met need and HIV/AIDS. Distributions: China and India each has one-fifth of all youth (Table 4.3, column 1) and the rest of Asia has over a fifth, for 70% of the grand total. Africa con- tains 19% and Latin America 11%. There is very little variation across re- gions in the balance between youth 15- 19 and youth 20-24; it is essentially half and half (52%/48%). The share of population due to youth does not vary much around the overall 19% figure, but it is as low as 14%-16% in Cuba, Uruguay, the Republic of Ko- rea, Taiwan, and Ukraine. On the other hand, the percents run higher in sub-Sa- haran Africa, to 24%-26% in Botswana, Lesotho, Rwanda, and Swaziland, where fertility rates are higher. Time Trends: Overall, the developing world will see a 5% increase of youth by 2010, with rather little additional in- crease to 2020 (Table 4.3). However the picture is very different for the UN list of “least developed” countries (second row): growth is a full 12% by 2010, 24% by 2015, and 35% by 2020. That means that in the next 15 years every 100 mem- bers of this age group will be replaced by 135. This is reflected also in the row for Africa, which contains many of the least developed countries, with 30% growth by 2020. At the other extreme, China’s youth pop- ulation will decline, becoming 18% smaller by 2020 than it is now, a total re- duction of over 40 million persons be- tween 2005 and 2020 (bottom panel of table). Over the long run that accelerates the trend toward an aging population: it shrinks the numbers at the bottom of the Table 4.3. Time Trends from 2005 to 2020 for the Population Aged 15-24 Numbers Aged 15-24 (000) Percent Growth from 2005 Areas 2005 2010 2015 2020 2005-2010 2005-2015 2005-2020 Less developed 993,515 1,041,923 1,045,330 1,049,228 4.9 5.2 5.6 Least developed 154,844 174,118 191,802 209,319 12.4 23.9 35.2 Other less developed 838,671 867,806 853,528 839,910 3.5 1.8 0.1 Less developed ex. China 775,172 822,401 848,509 870,683 6.1 9.5 12.3 Africa 188,597 207,688 224,987 245,412 10.1 19.3 30.1 Asia 711,633 737,388 721,711 704,005 3.6 1.4 (1.1) China 217,349 218,593 195,952 177,735 0.6 (9.8) (18.2) India 211,254 224,657 231,221 232,353 6.3 9.5 10.0 Rest of Asia 283,030 294,137 294,539 293,916 3.9 4.1 3.8 Latin America 105,665 107,543 108,637 109,625 1.8 2.8 3.7 Added Numbers (000) Areas 2005-2010 2010-2015 2015-2020 Less developed na 48,408 3,407 3,898 Least developed na 19,274 17,684 17,517 Other less developed na 29,135 (14,278) (13,618) Less developed ex. China na 47,229 26,108 22,174 Africa na 19,091 17,299 20,425 Asia na 25,755 (15,677) (17,706) China na 1,244 (22,641) (18,217) India na 13,403 6,564 1,132 Rest of Asia na 11,107 402 (623) Latin America na 1,878 1,094 988 Source: UN 2004 Estimates and Projections. 26 Chapter 4 population pyramid and later provides few in the working ages to support the heavy load of older parents and grand- parents. India’s youth will increase by 10% in 2020 but most of that growth will occur before 2015, ten years from now. Some 13 million youth will be added by 2010 and another 6 million by 2015. Latin America will be the slowest grow- ing of the regions shown, up by only 2% by 2010 and 4% by 2020. All of these patterns reflect the current and future age distributions of childbearing-age women and the projected age-specific fertility rates. Marriage: The percent already married or cohabiting in the age group 15-19 var- ies a great deal. In Asia the variation is from 47% in Bangladesh or 34% in India down to 1% in the Republic of Korea, 8% in Malaysia and the Philippines, and 7% in Sri Lanka. Similar extremes, both high and low, occur in Latin America and in sub-Saharan Africa. These are remark- able differences in the age of first formal union and, to a large extent therefore, in the age at first birth. Single women are not included in most surveys in Asia or the Middle East/North Africa, but in Latin American surveys, up to 11% of single women aged 15-19 admit to sexual activity. The sub-Saharan pattern is quite different: the high range is about 40% admitting sexual activity, and numerous countries are in the teens and 20s. Contraception by single women: In the same two regions there is a substantial percent of sexually active single women who say they are using contraception. In Latin America, for the young age group 15-19, four countries report percents above 60%; other countries are in the 30s to 50s. In sub-Saharan Africa the range is greater because it starts lower, reflecting the low presence of contraception in gen- eral in some countries. Contraception by married women: The percents reported above are usually much lower for married women. Sexual- ly active adolescents are more likely to use some method, even if erratically, than the average married woman, since many of the latter are currently preg- nant, amenorrheic, or not sexually ac- tive. Childbearing is already common among women in the next age group, at 20-24. However in China, only 8% of all women 20-24 have given birth and only 16% have done so in Viet Nam and Sri Lanka. The other extremes are found in Bangladesh (61%), India (47%), and Nepal (51%). Figures in Latin America are restricted to a narrow range in the 30s and 40s. Many sub-Saharan African countries are well above that; several are in the 50s, 60s, and even the 70s. The lowest range is in the Middle East/North Africa (Appendix Table A.24). All births: Finally, the two age groups, 15-19 and 20-24, contribute a large share of all births, from a third to one- half. Very few of the 116 countries in Appendix Table A.24 are above the 50% figure. Most countries in Latin America and sub-Saharan Africa are clustered in the 40s, whereas somewhat more fall be- low that in Asia and especially in the Middle East/North Africa. Attended births: Large proportions of births are still unattended by trained per- sonnel (last column of Appendix Table A.24). Less than half attended is not un- common in Asia and sub-Saharan Africa. All births should be attended, but only 16 countries outside of the former USSR exceed 80% of births attended by trained personnel. Clearly, young adults constitute a major share of all pregnancy experience and childbearing throughout the developing world. The corresponding needs for edu- cation and services are substantial, par- ticularly since so much of this early ex- perience is for first pregnancies and first births. Unmet Need for Youth Youth account for much of the unmet need, just as they do for numbers of births. Most unmet need information is for married women, so they are dis- cussed first. Based on an international analysis of unmet need in 55 national surveys (Ross and Winfrey, 2002), the two age groups 15-19 and 20-24 account for a full one-third (32.8%) of unmet need in the whole married group, or 34.9 million women. In the Middle East/ North Africa region the percent falls well below the average, at only 23.3%, and in the Central Asia Republics the percent is lower too at 27.9%. Within sub-Saharan Africa the figure is 30.3%, Numbers (000) Ages 15-19 Ages 20-24 Ages 15-24 Total 11,445 23,469 34,914 Latin America 1,064 2,405 3,469 Sub-Saharan Africa 2,465 4,663 7,128 Asia (except China) 7,390 14,679 22,069 Middle East/North Africa 479 1,457 1,936 Central Asia Republic 47 265 312 Percents Ages 15-19 Ages 20-24 Ages 15-24 Total 24.5 22.5 23.1 Latin America 27.2 20.2 21.9 Sub-Saharan Africa 25.6 26.0 25.9 Asia (except China) 24.4 22.7 23.3 Middle East/North Africa 18.0 17.4 17.5 Central Asia Republic 14.0 15.8 15.5 Source: Ross and Winfrey, 2002. Table 4.4. Numbers and Percentages of Currently Married/In Union Women with Unmet Need, by Region, for Ages 15-19 and 20-24. Chapter 4 27 within Latin America 31.3%, and within Asia 35.4%. In sheer numbers young married women weigh heavily in the balance. They tend to be at low parities but many are interested in limiting child birth as well as spacing. More unmet need exists at ages 20-24 than at ages 15-19: 23.5 million vs. 11.4 million in Table 4.4. The age group 15- 19 is larger than the 20-24 group but fewer members of it are married or in union, therefore in terms of sheer num- bers the 20-24 group contains twice the number in need. The differential is even more extreme in the Middle East/North Africa and in the Central Asia Repub- lics. It is slightly less marked in sub-Sa- haran Africa because cohabitation be- gins earlier, and the entire 15-19 age group is considerably larger in relation to the 20-24 age group than it is else- where. The two young age groups are quite sim- ilar in the percent of married women having an unmet need, except in Latin America, as shown in Table 4.4. Overall, regional differences are small, although the Middle East/North Africa and the Central Asia Republics have 15%-17% in need compared to 22%-26% else- where. Sub-Saharan Africa has the highest per- cent with unmet need for both young married women and all married women, at about 25% for both groups (not shown here; see section on unmet need). How- ever the other regions show differences; young women have more unmet need by a considerable margin in Latin America (21.9% vs. 13.7%), in Asia (23.3% vs. 16.4%), and in the Central Asian Repub- lics (15.5% vs. 11.3%), though by rath- er little in the Middle East/North Africa (17.5% vs. 15.6%). Unmarried Women: Information is se- verely limited for unmarried women at young ages, except in sub-Saharan Afri- ca. There, among never-married women, the percentage with unmet need is 7.3% at ages 15-19 and 10.7% at ages 20-24. Among previously married women it is 15.4% and 15.7% respectively. HIV/AIDS and Youth Unmet need in the larger sense is made worse by the AIDS epidemic. Youth aged 15-24 account for half of all new HIV in- fections worldwide, and some 6,000 contract the virus each day (UNAIDS, 2004). Of all youth already living with HIV, two-thirds are in sub-Saharan Afri- ca, and of them most (75%) are female. At the end of 2003 the regional distribu- tion for youth living with HIV was as follows: Sub-Saharan Africa 62% Asia 22% Latin America 7% Middle East/North Africa 1% Eastern Europe & Central Asia 6% High-income countries 2% The future of the AIDS epidemic turns heavily upon the success of programs directed to youth. While many are al- ready infected, a majority are not, and if behavioral change can be established it will persist to later ages and help reduce the base of HIV carriers that generates new cases of AIDS. HIV prevalence, especially in sub-Sahar- an Africa, is much higher among teenage girls than boys. Ratios there range from 2 to 1 to as high as 4.5 to 1. An aggravat- ing factor is that large age differences exist between girls aged 15-19 and their male sexual partners, many of whom are already infected. (See the main section on HIV/AIDS in Chapter 4.) References UNAIDS, 2004 Report on the Global AIDS Epidemic: 4th Global Report. See p. 22. Ross, John, and William Winfrey. “Un- met Need for Contraception in the De- veloping World and the Former Soviet Union: An Updated Estimate.” Interna- tional Family Planning Perspectives 28(3):138-143. 2002. 28 Chapter 4 Chapter 4 29 MATERNAL HEALTH Chapter 5Chapter 5Chapter 5Chapter 5Chapter 5 Maternal health is a complex subject, too large to consider in great detail. Here we discuss four aspects, supported by Ap- pendix Tables A.15 through A.21. ➤ Maternal Mortality and Morbidity ➤ Antenatal, Delivery, and Tetanus Care ➤ Induced Abortion and Postabortion Contraception ➤ Program Efforts to Improve Maternal Health Maternal Mortality and Morbidity Maternal mortality has received continu- ing attention as a major problem of the developing world, but clear evidence of progress against it is lacking. The three international series of estimates of mater- nal mortality ratios (MMRs) for 1990, 1995, and 2000 show erratic trends for many countries, due to defective data and also to some changes in methodology. In addition the small number of deaths in some data sets produces large sampling errors. Still, the average MMR for all de- veloping countries declined from 528 in 1990 to 502 in 1995 to 444 in 2000 (the medians were 300, 255, and 230). De- clines also appear in long-term trend data for selected countries, including China (UN, 2002). Essentially no developing country has an MMR anywhere near the ratios in the West, where the average ratio in 2000 was 20. On average, in developing coun- tries about 1 woman in 61 can expect to die from pregnancy-related causes some- time during her reproductive career (Ta- ble 5.1); at worst, in some countries this is 1 in 10. The basic facts are not in dispute; here are examples from a World Bank (1999) review: ➤ Nearly 99% of the more than 500,000 maternal deaths each year occur in the developing world. ➤ Of all the human development indica- tors, the greatest discrepancy between developed and developing countries is in the risk of maternal death. ➤ Complications of pregnancy and child- birth are the leading cause of death and disability among women of reproductive age in developing countries. ➤ One in four women in these countries suffers from acute or chronic conditions related to pregnancy. ➤ At least 20% of the burden of disease among children below age five is attribut- able to conditions directly associated with poor maternal health, nutrition, and the quality of obstetric and newborn care. ➤ Most of this loss and suffering is pre- ventable. Within the developing world the regions differ significantly in average risk, but all are far above the rates for Europe and North America. In the following section we discuss three features, drawn from Appendix Table A.15: numbers, ratios, and lifetime risks. Due to defects in the original data, all fig- ures are approximations and the patterns presented must be viewed in general terms. Numbers of Deaths. The total numbers of deaths reflect population sizes and birth rates as well as the mortality risks, so the numbers are very uneven by re- gion. Asia has nearly one-half of the total (Table 5.2), due largely to India, and sub- Saharan Africa has about as many. India’s maternal deaths far exceed those of any other country. Its 136,000 deaths (Figure 5.1) compose over one-fourth (27%) of the developing world total; this vastly exceeds China’s total of 11,000, reflecting China’s fewer births and its much lower maternal mortality ratio of 56 vs. India’s 540. Other countries follow after India. Nige- ria has about 37,000 annual maternal deaths; Pakistan, D.R. Congo, and Ethio- pia have about 25,000 each; Afghanistan and Bangladesh have between 16,000 to 20,000; and numerous others have about 10,000 each. While all these estimates are subject to considerable error, Figure 5.1 identifies a rough ordering for large countries. The ratios (MMRs) are much higher in sub-Saharan Africa than in other regions. Within each region the MMRs vary sharply, as the distributions in Figure 5.2 demonstrate. However the central ten- dencies follow a clear ordering: in sub- Saharan Africa the range is from about 1800 to one-tenth of that. In Asia, apart from the single high figure (for Nepal), the range is from about 650 to quite low figures, and in Latin America the range starts at about 400 and also falls to low figures. The lowest ratios are in areas of the former Soviet Union, where the ex- tensive health systems have covered most women. Table 5.1. Women’s Lifetime Risk of Dying from Pregnancy and Childbirth Region Risk of Dying Developed Countries 1 in 2800 All Developing Countries 1 in 61 Sub-Saharan Africa 1 in 16 South Asia 1 in 43 East Asia and Pacific 1 in 360 Middle East and North Africa 1 in 100 Latin America and Caribbean 1 in 160 Source: AbouZahr and Wardlaw, 2004. Table 4.2. Table 5.2. Number and Percent of Maternal Deaths Annually (2000), Developing Countries Number of Maternal Deaths Country Annually Percent Asia 237,665 47.3 Latin America 21,570 4.3 Middle East/North Africa 20,362 4.1 Sub-Saharan Africa 220,925 44.0 Central Asia Republics 1,000 0.2 Caucasus 140 0.0 Moldova, Russia, Ukraine 990 0.2 Total 571,652 100.0 30 Chapter 5 These ratios partly overlap with the pic- ture for numbers of deaths. High ratios occur in Nepal and Pakistan, in Sudan and Yemen, and most especially in 17 sub-Saharan countries that have ratios of 1,000 or higher. The lifetime risks vary across a vast range, from 1 woman in 6 or 7 dying in Afghanistan, Angola, Malawi, Niger, and Sierra Leone to only 1 in 1,100 or more 136,000 37,000 26,000 24,000 24,000 20,000 16,000 11,000 11,000 11,000 10,000 10,000 9,700 9,300 8,700 7,900 6,800 6,400 6,000 5,400 - 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Ind ia Nig er ia Pa kis tan Co ng o, D.R . Eth iop ia Afg ha nis tan Ba ng lad es h Ch ina An go la Ke ny a Ind on es ia Ug an da Nig er Ma law i Bra zil Mo za m biq ue Ma li Su da n Ne pa l Bu rkin a Fa so Figure 5.1. Number of Maternal Deaths, 2000 (top 20 countries) 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Asia SubSaharan Africa Latin America Middle East/North Africa in South Korea, Chile, Cuba, and the former USSR. (These can be converted by their reciprocals to the percents im- plied: for example, 14% for a 1 in 7 risk.) The risk in each country reflects both the average number of births per woman (the TFR) and the risk per birth (the MMR), so women in countries with high fertility rates and high ratios will have the highest lifetime risks. (See Appendix Table A.15.) The MMR is normally stated as maternal deaths per 100,000 births. The same number of deaths can be compared to pregnancies rather than births. If about 120 million births occur in the develop- ing world, they represent perhaps two- thirds to three-fourths of all pregnancies. If there are at least 500,000 maternal deaths in these countries the overall ratio is about 415. However, with the 160 to 180 million pregnancies as the denomi- nator the ratio is less, at 277 to 313. That however still translates to one death per minute year around, in addition to many times more for serious disability. Strategies. A strong argument has been urged that highly specific measures are essential to reduce the numbers of mater- nal deaths. General improvements in so- cioeconomic status will not significantly lower maternal mortality rates, since most deaths occur for lack of well- equipped medical facilities close at hand and ready at short notice to assist the woman experiencing difficulty. Screen- ing in advance to identify high-risk sub- groups is not efficient, since “.the vast majority of high-risk women will deliver without incident. Furthermore, most women who develop life-threatening complications belong to low-risk groups.” (Maine and Rosenfield, 1999), Figure 5.2. MMR Values by Region, 2000 (3 groups to right are 5 CARs, 3 Caucasus, and Moldova, Russia, Ukraine) 136,000 Chapter 5 31 apparently because of their sheer num- bers in the population. The implications of such analyses are that sheer numbers of deaths will not fall greatly until there is close access to appropriate medical ser- vices to treat emergency cases. The exception is broad-scale family plan- ning since that reduces the overall num- ber of unplanned and unwanted pregnan- cies in the first place. Moreover, enlarged contraceptive use offsets abortions that would otherwise occur, many of which produce maternal deaths from septic pro- cedures. (See abortion section.) A full strategy to reduce the total number of maternal deaths in the developing world must take into account their high- ly concentrated geographic distribution (Figure 5.1). Within any country, deaths are a function of the number of women, the birth rate, and the risk per birth (or pregnancy). The latter is to some extent a function of unsafe abortions. Wider con- traceptive use addresses both the abortion rate and the birth rate, but the numbers of deaths will remain far too high until med- ical facilities improve in close proximity to most women. References AbouZahr, Carla, and Erica Royston. Maternal Mortality: A Global Factbook. Geneva: WHO. 1991. AbouZahr, Carla, and Tessa Wardlaw. “Maternal Mortality in 2000: Estimates Developed by WHO, UNICEF, and UNFPA.” Geneva: WHO. 2004. Adamson, P. “Women: Maternal Mortal- ity.” In: Adamson, P., ed. Progress of Na- tions. New York: UNICEF. Pp. 2-7. 1996. Maine, Deborah. Safe Motherhood Pro- grams: Options and Issues. New York: Columbia University, Center for Popula- tion and Family Health. 1991. Maine, Deborah, and Allan Rosenfield. “The Safe Motherhood Initiative: Why Has It Stalled?” American Journal of Public Health, Vol. 89, No. 4. Pages 480- 482. April 1999. Tsui, Amy, Judith N. Wasserheit, and John G. Haaga, eds. Reproductive Health in Developing Countries. Expanding Di- mensions, Building Solutions. Panel on Reproductive Health, Committee on Pop- ulation, Commission on Behavioral and Social Sciences and Education. National Research Council. Washington, DC: Na- tional Academy Press. 1997. UNICEF. The Progress of Nations. New York: UNICEF. 1996. United Nations. World Population Moni- toring 2002: Reproductive Rights and Reproductive Health: Selected Aspects. UN Commission on Population and De- velopment, Thirty-fifth Session, April 1- 5, 2002. Draft, page 107, citing data from WHO and UNICEF databases. WHO. Coverage of Maternal Care: A Listing of Available Information, Fourth Edition. Geneva: WHO. 1997. WHO. Mother-Baby Package: A Road Map for Implementation in Countries. Geneva: WHO, Division of Family Health. 1993. WHO and UNICEF. “Revised 1990 Esti- mates of Maternal Mortality: A New Ap- proach by WHO and UNICEF.” Geneva: WHO and UNICEF. April 1996. WHO / UNICEF / UNFPA. “Maternal Mortality in 1995: Estimates Developed by WHO, UNICEF, UNFPA.” Geneva: World Health Organization. 2001. World Bank. Safe Motherhood and the World Bank: Lessons from Ten Years of Experience. Washington, DC: The World Bank. June 1999. Antenatal, Delivery, and Tetanus Care Burdens upon the health system reflect large numbers of births and constraints that cause major shortfalls in the propor- tions of women currently served. Three functions are discussed below: antenatal care, tetanus immunizations, and delivery attendance. Antenatal care. Only about 70% of births are preceded by even a single ante- natal visit in the developing world as a whole. Across regions (Table 5.3) the range is from 65% to 69% in Asia, the Middle East/North Africa, and sub-Sa- haran Africa, and up to 87% in Latin America. It is 93% in the Central Asia Republics as an inheritance from the former USSR system. In terms of numbers of women unserved, a full 36 million women receive no ante- natal care annually (Table 5.3 and Ap- pendix Table A.17). By region, the esti- mates are 21.6 million in Asia, 1.5 mil- lion in Latin America, 2.9 million in the Middle East/North Africa, and 9.5 mil- lion in sub-Saharan Africa. Although the United Nations estimates that the total number of births per year in the develop- ing world as a whole has leveled off, the number will still increase in such large countries as Ethiopia and Pakistan, so even if the proportions of women assist- ed improve, the absolute numbers un- served may still rise. The distribution of countries according to the percent of women receiving antenatal care appears in Table 5.4, for 80 coun- tries. One-third (19) of countries fall be- low the 70% mark (column 2). That is, in these countries less than 70% of women receive antenatal care. In 15% of coun- tries, or about one in six, less than 50% of women receive care. However the decade of the 1990s saw notable progress in antenatal care accord- ing to a careful report issued recently (AbouZahr and Wardlaw, 2004). Defin- ing care as one or more antenatal visits and using data from 49 countries with multiple surveys, the overall trend was up from about 53% of pregnant women in 1990 to about 64% in 2000. The rise was sharpest in Asia and least in sub-Saharan Africa and the Middle East/North Africa. An encouraging finding was that over half of women receiving any care re- ceived at least four visits. Exceptions, however, include Bangladesh, Ethiopia, Morocco, Nepal, and Yemen, all of which have substantial percentages of women who have only one visit. South Asia, overall, had the lowest levels of antenatal care with only 50% of women getting even one visit. Delivery care. Professionally trained birth attendants, whether paramedics or doctors, and whether serving at home or 32 Chapter 5 in facilities, are the focus here. Coverage of births by professional attendants rests at about 59% of births for the developing world as a whole (Table 5.3). The range of variation across regions is consider- ably greater than it is for either tetanus or antenatal care since only 41% of deliver- ies are attended in sub-Saharan Africa. The Asia figure is a low 60%; a high fig- ure for China is offset by lower ones for Bangladesh, India, and Pakistan (Appen- dix A.17). (All regional figures above weight countries by number of deliver- ies.) Converted to numbers, these percentages mean the neglect of 28.4 million women in Asia, 2.1 million in Latin America, 2.7 million in the Middle East/North Africa, and 16.3 million in sub-Saharan Africa. Improvements in the proportions of births attended will tend to offset the increasing absolute numbers of births in countries like those mentioned above, but will still leave vast numbers unattended. The dis- tribution of countries by the percent of births attended is shown in Table 5.4. Again, a single fact is eloquent: one-half of countries attend less than 60% of births. One-fourth of countries attend less than 40% of births. Tetanus immunizations. A similar anal- ysis for tetanus shows about 70% of women receiving care, but compared with antenatal care more receive care in Asia and fewer in Latin America, Middle East/North Africa, and sub-Saharan Afri- ca (Table 5.3). It must be said that the original country data are quite rough and approximate; nevertheless the picture of serious shortfalls cannot be doubted. Translated to numbers about 16.1 million women are omitted from tetanus protec- tion in Asia, 3.7 million in both Latin America and Middle East/North Africa, and 10.8 million in sub-Saharan Africa. Again, the coming five-year increases in both women and births in certain large countries will elevate these numbers un- less the proportions served rise enough to counteract them. The distribution of countries by the per- cent of women receiving tetanus immuni- zations is shown in Table 5.4. It is consid- erably worse than the one in that table for antenatal care. Over half of countries fall below the 70% mark for women treated. Three-way comparison. Most countries in the developing world have large defi- ciencies in maternal care. Figure 5.3 gives the cumulative distribution of all countries by the percent of women re- ceiving care for the three services of an- tenatal visits, tetanus protection, and de- livery attendance. The ideal curve would stay very low along the bottom axis, indi- cating that few countries have low per- centages of care, and it would then rise very sharply at the right, placing most countries at the favorable high percentag- es. The space beneath each line reflects the failure to provide care. Thus the best curve is for antenatal visits and the worst is for attended deliveries. In between is tetanus; it crosses the 50% point for countries at the unfavorable point of only 60% of women with tetanus protection. Figure 5.3 is based upon 80 developing countries that have data for all three types of care, to create a fair comparison. The omitted countries include those that lack data on one or more types, and several of the omitted countries happen to be those with stronger health systems. When they are included the antenatal and tetanus curves are essentially unchanged, but the delivery curve is more favorable, lying close to the tetanus curve. Therefore the figure represents the situation for the less favored countries, which is probably more relevant to action planning. The burdens of care and the needs for ser- vices will rise inexorably in those devel- oping countries with increasing numbers of births. A race is under way between those increases and the effort to improve coverage of services, made more chal- lenging by the drive to also improve quality. Progress on coverage and quality may be largely cancelled in these coun- Table 5.3. Mean Regional Values for Care Received, with Numbers Unserved Percent of Women Receiving Care Numbers Unserved No. of Deliveries Antenatal Deliveries Tetanus (000s) Antenatal Deliveries Tetanus Asia 69.4 59.6 77.0 70,430 21.580 28,445 16,183 Latin America 86.9 82.1 68.2 11,511 1,504 2,061 3,660 Middle East/ North Africa 70.5 71.8 61.9 9,806 2,894 2,761 3,738 Sub-Saharan Africa 65.4 40.7 60.7 27,508 9,525 16,311 10,813 Central Asia Republics 92.5 93.7 u 1,187 89 74 u Caucasus 75.8 88.3 u 232 56 27 u Developing World 70.4 58.7 70.3* 120,675 35,748 49,796 35,812 u - unavailable *Figure would be somewhat higher with data for the two missing regions. Table 5.4. Distribution of Countries by the Percent of Women Receiving Care Percent Antenatal Care Attended Deliveries Tetanus Immunizations of Women No. of Cumulative No. of Cumulative No. of Cumulative Receiving Care Countries Percent Countries Percent Countries Percent 0-9 - - 1 1 2 3 10-19 - - 6 9 - 3 20-29 3 4 5 15 4 8 30-39 3 8 8 25 7 16 40-49 6 15 13 41 11 30 50-59 1 16 7 50 9 41 60-69 12 31 12 65 10 54 70-79 17 53 6 73 7 63 80-89 17 74 9 84 15 81 90-100 21 100 13 100 15 100 No. of countries 80 80 80 Source: Appendix Table A.10. Chapter 5 33 tries by the rising numbers of births un- less both efforts and resources are great- ly augmented. References AbouZahr, Carla and Tessa Wardlaw, An- tenatal Care in Developing Countries; Promises, Achievements, and Missed Op- portunities. An Analysis of Trends, Lev- els, and Differentials, 1990-2001. WHO and UNICEF 2004. UNICEF. The State of the World’s Children 2005. New York: UNICEF. Dec. 2004. United Nations. World Population Pros- pects: The 2002 Revision. Volume I, Comprehensive Tables. New York: Unit- ed Nations Population Division. See also the 2004 Revision. WHO. The World Health Report 1998. Geneva: World Health Organization. 1998. See also the 2005 edition. Induced Abortion and Postabortion Contraception Planners need to know the level of abor- tion activity to sense the burdens that weigh upon both maternal health and ser- vice networks. They also need to gauge the requirements for preventive care, in- cluding contraception and postabortion contraception. Here we provide three measures of abortion activity (Appendix Table A.16), using data drawn primarily from the World Health Organization and the Alan Guttmacher Institute. These data are only rough estimates for many coun- tries and should be used with caution. Recent regional data on abortion are shown in Table 5.5 (see also Henshaw, Singh, and Haas, 1999). Asia dominates the number of abortions done annually, with 55% of the table total and 57% of the developing world total. China is re- sponsible for much of this, but the rest of Asia still contains over half of abortions in the developing world with China re- moved. This reflects the large numbers in India, Indonesia, Pakistan, and the Phil- ippines. Latin America is next, due to the presence of Brazil, Mexico, and Venezu- ela. Next is sub-Saharan Africa, where Nigeria ranks first; in the Middle East/ North Africa, Turkey and Egypt have the largest numbers. In the five Central Asian Republics, Uzbekistan has an estimated two-thirds of the total. The number of abortions reflects two determinants: the number of pregnancies and the proportion aborted (the abortion ratio is however abortions per births). From another perspective, the numbers reflect the abortion rate (the proportion of all women having an abortion annual- ly). Thus, the size of the population, the number of pregnancies, and the proclivi- ty to terminate them, all enter in. Further, each of these three has its own prior de- terminants; most notably, increased con- traceptive use reduces the number of pregnancies and therefore the total num- ber of abortions. Rates vary across a wide range, from lows of only 6 to 10 (annual abortions per 1,000 women aged 15-49), to highs in the 60s and 70s. The rates and ranks in Appendix Table A.16 reflect these ex- tremes. An overview of regional differ- ences appears in Table 5.5; the rates are especially low in Western Asia and Northern Africa (corresponding largely to our designation of the Middle East/ North African region) and in sub-Saharan Africa. Next highest is Asia, and then Latin America. Much higher rates have been registered in the former Soviet Union regions. Within every region, there is rather wide country variation. The ratios of abortions per 100 births present a different picture from the rates for many individual countries, but the re- gional patterns are largely unchanged. The ratios are quite low in the Middle East/North Africa, higher in Asia and even higher in Latin America. In Appen- dix Table A.16 the highest averages are for the Central Asian Republics and for the group of Moldova, Russia, and Ukraine. Five of the ten highest country ratios occur in the former Soviet Union. Widespread contraceptive practice great- ly reduces the number of pregnancies and therefore the rate, but the ratio may either rise or fall. It may fall if most of the re- maining pregnancies are wanted ones, but it may rise if there are many contra- ceptive failures and a high proportion is aborted. In that case, most abortions serve as backup for defective contracep- tive methods (especially traditional meth- ods) or defective use of the methods. In other situations, where abortion is a pri- mary instrument of birth control, the abortion ratio can be very high, and it matters considerably whether the ratio is based on pregnancies or births. If in the Russian Federation two-thirds of preg- nancies are aborted that leaves one-third for births, so while the ratio is 66 per 100 pregnancies it is 66 per 33 births, or a standard ratio of 150. 10 20 30 40 50 60 70 80 90 100 0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90-100 Antenatal Deliveries Tetanus 0 C um ul at iv e P er ce nt o f C ou nt rie s Figure 5.3. Cumulative Distribution of Countries for Maternal Care: Antenatal Care, Tetanus Immunization, and Delivery Attendance Cumulative Percent of Women Receiving Care 34 Chapter 5 Regardless of whether abortion is legal or illegal, increased contraceptive use will cut into the base of unwanted pregnan- cies. In particular, postabortion contra- ception addresses the population most concerned. A strategy to offer advice and methods during the abortion episode is vital, since many women will not be seen again and many will go on to repeat abor- tions. Deaths: Unsafe abortions are thought to account for some 68,000 maternal deaths each year, or about 13% of all maternal deaths. Thus they constitute about one- eighth of the maternal deaths that occur in the developing world. Safer medical procedures, including new non-surgical ones, will save lives and reduce maternal morbidity. Abortion is made safer and less traumatic by the use of vacuum pro- cedures; these are now in common use in many developing countries. There are three general strategies to re- duce the numbers and rates of abortion, whether safe or unsafe: 1. Gross numbers will continue to occur mainly in a relatively small number of countries with large populations and high rates; therefore, regional and internation- al strategies should take account of the geographic pattern. 2. The abortion rates within countries will fall as the pregnancy rate falls, the key to which is the spread of reliable con- traceptive use. 3. The focused strategy of contraceptive offerings at the time of abortion will re- duce repeat abortions and orient action to the subgroup most prone both to have re- peat unwanted pregnancies and to termi- nate them. The scourge of unsafe abortions in much of the developing world can be reduced by better contraceptive offerings, to pro- vide more methods and easier access to more people. Abortion can be made saf- er through the spread of vacuum aspira- tion equipment. Contraception offered at the time of each abortion is especially important to reduce future unwanted pregnancies and repeat abortions. Con- traceptive failure can be reduced by the provision of better counseling and a wid- er choice of reliable methods. Table 5.5. Global and Regional Estimates of Annual Incidence of Unsafe Abortion and Mortality Due to Unsafe Abortion, by United Nations Regions, Around the Year 2000 Unsafe Abortion Incidence Mortality Due to Unsafe Abortion NUMBERS RATIOS RATES Unsafe Unsafe Abortions Unsafe Abortions Number of Percent of all Unsafe Abortion Abortions to 100 per 1000 Women Maternal Deaths Due Maternal Deaths to (thousands) Live Births Aged 15-44 to Unsafe Abortion Deaths 100,000 Live Births World 19,000 14 14 67,900 13 50 Developed countriesa 500 4 2 300 14 3 Developing countries 18,400 15 16 67,500 13 60 Africa 4,200 14 24 29,800 12 100 Eastern Africa 1,700 16 31 15,300 14 140 Middle Africa 400 9 22 4,900 10 110 Northern Africa 700 15 17 600 6 10 Southern Africa 200 16 17 400 11 30 Western Africa 1,200 13 25 8,700 10 90 Asiab 10,500 14 13 34,000 13 40 Eastern Asia - - - - - - South-central Asia 7,200 18 22 28,700 14 70 South-eastern Asia 2,700 23 21 4,700 19 40 Western Asia 500 10 12 600 6 10 Latin America & Caribbean 3,700 32 29 3,700 17 30 Caribbean 100 15 12 300 13 40 Central America 700 20 21 400 11 10 South America 2,900 39 34 3,000 19 40 Europe 500 7 3 300 20 5 Eastern Europe 400 14 6 300 26 10 Northern Europe 10 1 1 - 4 - Southern Europe 100 7 3 <100 13 1 Western Europe - - - - - - Northern America - - - - - - Oceaniab 30 12 17 <100 7 20 a Figures may not add exactly to totals because of rounding. b Japan, Australia and New Zealand have been excluded from the regional estimates, but are included in the total for developed countries. – No estimates are shown for regions where the incidence is negligible. Source: WHO, 2004. Chapter 5 35 *For details and additional information see Ross and Begala (2005) and other references below. The 13 components were based upon 81 items in a stan- dard questionnaire completed by 10-25 expert ob- servers in each country. References Henshaw, Stanley K., Susheela Singh, and Taylor Haas. “The Incidence of Abortion Worldwide.” International Family Plan- ning Perspectives, Vol. 25, Pages S30- S37. Supplement, 1999. Ross, John A. and Elizabeth Frankenberg. “Induced Abortion,” Ch. 9 in Findings from Two Decades of Family Planning Research. New York: The Population Council. 1993. Rossier, Clementine. “Estimating Induced Abortion Rates: A Review.” Studies in Family Planning 34(2):87-102, June 2003. WHO. “Global and Regional Estimates of Incidence of and Mortality due to Un- safe Abortion with a Listing of Available Country Data,” Table 2. Maternal and Newborn Health: Unsafe Abortion. Third Edition. Geneva: WHO. 1998. See also the Fourth Edition, Table 3. 2004. Singh, S., J. E. Darroch, M. Vlassoff, and J. Nadeau. Adding It Up: the Benefits of Investing in Sexual and Reproductive Health Care. New York: Alan Guttmach- er Institute and UNFPA. 2003. Program Efforts to Improve Maternal Health (See Appendix Table A.18) National programs to reduce maternal mortality and morbidity exist in every country. Surveys were conducted in both 1999 and 2002, in some 50 countries, to assess both the types and levels of effort devoted to these programs. A maternal and neonatal health programs index (MNPI) was used to measure 13 compo- nents of the programs.* Results in 1999 and 2002 matched close- ly by component, for the 43 countries that participated in both surveys (Figure 5.4). (Each score is the percent of maxi- mum, and the total score is the average of the 13 component scores.) The close match in pattern is reassuring as to the re- liability of the methodology since the surveys were done independently; it also indicates that, overall, little change oc- curred in the three years between sur- veys. The improvement was only from 54.9% in 1999 to 57.1% in 2002 for the total score, and it was also small for each of the components. That is not surprising since major shifts in effort large enough to affect the international average could hardly be expected in a short time. Among the 13 components the highest rating goes to newborn services (70% in both years), due in part to the successful immunization campaigns in many coun- tries. The bottom place is held by three components at about 50% of maximum effort: health center capacities, resources, and public education. Another low score is for access to services and it is especial- ly low for rural access. In the middle are six components at about 60% of maxi- mum: district hospital capacities, antena- tal and delivery services, family planning at health centers and at district hospitals, and policies bearing on safe pregnancy. The final two components, for training and monitoring/evaluation, are near 55%. The range across the 13 component scores is from 45% to 70%, demonstrat- ing that a strong selectivity exists in what government programs emphasize. Among regions there are also substantial differences. Table 5.6 for 2002 (all 55 countries) shows the 13 component scores for each region. The chief features are: ➤ The South Asia region (India, Paki- stan, Nepal, and Bangladesh) has the lowest total score, and it is lowest or tied for lowest on most of the components. ➤ Francophone sub-Saharan Africa is next lowest both on the total score and on the number of components for which it holds the bottom rank. ➤ East and Southeast Asia shows the highest total score, and it is highest on most components. ➤ The other regions fall at intermediate levels for the total score and most com- ponent scores. ➤ The greatest difference among re- gions is in access to services by most of the population. Thus public access to ma- ternal services varies greatly, both in the rural sector and in the urban sector. Access to services in the rural sector, where most of the population lives, is far worse than urban access. This appears in every region regardless of the overall lev- els (Figure 5.5). The disparity is close to 30% in every case. Figure 5.4. Comparison of 2002 and 1999 Surveys, by Component (43 Countries Included in Both Years) -10 0 10 20 30 40 50 60 70 80 90 100 He alt h C en ter Ca pa citi es Dis tric t H os pit al Ca pa citi es Pe rce nta ge wit h A cce ss to Ca re An ten ata l S erv ice s De live ry Se rv ice s Ne wb orn Se rvic es FP at He alt h C en ter s FP at Dis tric t H os pit als Po lici es tow ard Sa fe Pre gn an cy Re so ur ce s & Pr iva te Se cto r Inf or m ati on , Ed uc ati on Tra inin g A rra ng em en ts Mo nit or ing , E val ua tio n TO TA L Pe rc en t o f M ax im um S co re 2002 1999 Difference 36 Chapter 5 Figure 5.5. Rural and Urban Access Scores, by Region, 2002Relation to Maternal Mortality: The association between program effort and the maternal mortality ratio appears in Figure 5.6. All countries in the study are divided into three groups according to their MMR levels. The figure shows the score for each group on each of eight program features taken selectively from the various components. The heavy line is for countries with the lowest MMRs; this line lies to the outside of the figure, showing the highest effort scores on ev- ery feature. The sharpest relationships between pro- gram effort and maternal mortality ap- pear for access to postpartum family planning and to safe abortion, where the lines are farthest apart. They are also far apart for access to emergency treatment. Each of these has a plausible relationship to lower maternal mortality. Postpartum family planning programs encourage contraceptive use, which in turn avoids unwanted pregnancies with their elevated risks. Safe abortion services help avoid septic complications that cause deaths, and emergency treatment is vital in cases of hemorrhaging and other life-threaten- ing complications. Smaller differences appear where all scores are relatively high, as with antena- tal care access, and especially with im- munizations, which have received special attention in recent years. East and Latin America Middle East Anglophone Francophone Southeast South and the and Sub-Saharan Sub-Saharan All Asia Asia Caribbean North Africa Africa Africa Regions 1. Capacities of health centers 52.6 45.4 49.3 50.8 51.5 54.7 51.3 2. Capacities of district hospitals 65.9 58.8 61.8 75.6 61.4 58.5 62.8 3. Total access 70.2 37.2 56.1 68.8 54.4 39.6 53.3 3A. Rural access 62.2 30.7 40.6 53.8 45.5 30.5 42.4 3B. Urban access 85.1 59.2 67.6 80.9 71.0 58.4 69.0 4. Care at antenatal visits 60.5 50.0 65.9 58.7 67.9 67.4 64.2 5. Care at delivery 68.2 42.7 62.6 62.8 61.2 57.7 60.2 6. Care for newborns 75.1 57.0 75.7 76.8 72.0 70.0 72.1 7. Family planning at health centers 62.5 47.4 56.2 65.5 65.9 51.0 58.6 8. Family planning at district hospitals 68.2 59.8 59.3 57.3 61.4 51.1 58.5 9. Policies toward safe pregnancy 69.0 57.6 58.4 60.8 65.6 67.0 63.5 10. Resources 50.9 50.4 48.8 55.6 52.4 37.6 48.2 11. Information, education 61.8 51.5 41.4 51.8 53.6 50.0 50.5 12. Training arrangements 63.5 50.1 56.3 56.1 52.8 47.6 53.5 13. Monitoring, evaluation 65.8 48.6 57.4 55.3 59.7 54.2 57.1 Total Score 64.2 50.5 57.6 61.2 60.0 54.3 58.0 Note: The total score for all regions is 58.0%, for the 55 countries in 2002, while it is 57.1% for the 43 countries common to both surveys. 0 20 40 60 80 Emergency treatment access Attended deliveries Antenatal care access Safe abortion access Postpartum FP access Immunizations Training doctors Training nurses, midwives ____ MMR <250 __ __ MMR 250-749 - - - MMR 750+ 30.9 40.9 51.8 41.0 30.7 57.9 56.8 67.8 82.3 66.7 59.2 86.1 0 10 20 30 40 50 60 70 80 90 100 Francophone Sub-Saharan Africa Anglophone Sub-Saharan Africa Middle East and North Africa Latin America and the Caribbean South Asia East and Southeast Asia Percent of Maximum Urban Rural Table 5.6. Average Effort Scores by Component and Region, 2002 Figure 5.6. Program Efforts for Three Groups of Countries with Different MMR Levels Chapter 5 37 Summary: National programs to im- prove maternal health vary across a great range, from very low scores to relatively high ones. Differences are less at the re- gional level but are still substantial, de- pending upon the component of effort. However, sheer access to services is seri- ously compromised especially in the ru- ral sector, which puts pregnant women with complications in jeopardy. Separate surveys in 1999 and 2002 show very lit- tle improvement for countries taken as a whole. References Bulatao, R.A. and J.A. Ross. “Rating Maternal and Neonatal Health Services in Developing Countries.” Bulletin of the World Health Organization. 2002; 80:721-727. Hill, K., C. AbouZahr, and T. Wardlaw. “Estimates of Maternal Mortality for 1995.” Bulletin of the World Health Or- ganization. 2001; 79(3):182-198. See also WHO and UNICEF. Revised 1990 Estimates of Maternal Mortality: A New Approach by WHO and UNICEF. April 1996. See also AbouZahr, Carla and Tes- sa Wardlaw, “Maternal Mortality in 2000: Estimates Developed by WHO, UNICEF, and UNFPA.” Geneva: WHO. 2004. Ross, J.A. and J. Begala. “Measures of Strength for Maternal Health Programs in 55 Developing Countries: The MNPI Study. Maternal and Child Health Jour- nal, Vol. 9, No. 1, March 2005. Ross J.A., O.M.R. Campbell, and R.A. Bulatao. “The Maternal and Neonatal Programme Effort Index (MNPI).” Trop- ical Medicine and International Health. 2001; 6(10):787-798. Chapter 4 39 CHILD HEALTH Chapter 6Chapter 6Chapter 6Chapter 6Chapter 6 To provide an overview of child health in developing countries, this chapter takes up three features: ➤ The rates and numbers of child deaths ➤ The risks of death according to birth categories (birth intervals, birth orders, mother’s age) ➤ The status of programs for immuniza- tions, ARI, and ORS. Rates and Numbers of Child Deaths (see Appendix Table A.19) One determinant of child deaths is the number of births, so as birth rates fall the numbers of infant and child deaths either fall or grow more slowly than they other- wise would have. Birth rates have fallen by about half in the last four decades, and the large increases in contraceptive use deserve considerable credit for sav- ings in the numbers of infant and child deaths. Death rates are another matter: the risk to each child born can remain high even while births decline. However there is a selectivity that also works to reduce death rates. When birth rates fall there are fewer high-risk births to older wom- en and fewer short-interval births, and that lowers death rates even more. Latin America has the lowest regional infant mortality rate; at 27 per 1,000 births, it is well below that for the Mid- dle East/North Africa (45) or Asia (50). A doubling of those rates exists in sub- Saharan Africa (104). In the Central Asian Republics the rate is 62, but it is only 16 in the group of Moldova, Ukraine, and Russia (Table 6.1). Within regions countries vary consider- ably, as the Appendix table shows. The lowest IMR figures in Asia are a mere 3 to 7, while the highs are in the 80s and 90s (and 165 in Afghanistan). The range is narrower in Latin America; it starts as low as Asia does but rises only into the 30s, except for Bolivia (53) and Haiti (76). In the Middle East/North Africa the range is also from about 7 to the 30s, plus Iraq (102 est.). Sub-Saharan Afri- ca’s lowest figures are in the 40s, and the highs exceed 150. Of special interest is the ratio of child mortality to infant mortality. Where death rates are high, as in sub-Saharan Africa, the ratio is also high (1.69). When rates fall, the risk at ages 1-4 falls faster than the IMR does, partly because a portion of the IMR is due to birth de- fects, congenital malformations, etc. that do not respond to general environment improvements. Consequently the ratio is lowest in Latin America (1.18), where the two rates are lowest. In between are Asia (1.36) and the Middle East/North Africa (1.26). Widespread improve- ments, over time, lower both child and infant mortality rates, but more so for the child rates. Numbers of deaths are shown in Table 6.1. They total an estimated 11 million per year, equal to the entire population of some countries. The number would have been far more had birth rates not fallen by about half in the last four de- cades, but they remain far too high. Most deaths occur in Asia due to its popula- tion size, but sub-Saharan Africa’s high rates place it second, with four-fifths as many deaths as in Asia. China and India illustrate the interplay of population size, the birth rate, and the mortality rates. China’s larger popula- tion is offset by its low birth rate, result- ing in only 19 million births, well below India’s 25 million. China also has a child mortality rate of only 37 compared to India’s 87. The result is that China expe- riences 692,000 child deaths annually but India experiences 2.2 million. Risks of Death by Birth Categories (see Appendix Table A.20) Infants die at higher rates if they arrive too close to a preceding birth, if the mother is too old or too young, or if the birth is of a high order. DHS surveys have documented these elevated risks for many countries, as listed in the Appen- dix. Illustrative countries appear in Ta- ble 6.2. Figures in the first set of col- umns distribute all births according to a risk calculation: first births are bound to Table 6.1. Number of Births, Infant and Child Mortality Rates, and Number of Deaths, 2003 Estimates Under Age 5 Infant Annual Mortality Annual Annual No. Mortality Infant Rate Child of Births Rate (IMR) Deaths (U5MR) Deaths Asia 70,052,000 50 3,511,012 68 4,735,000 Latin America 11,538,000 27 313,896 32 372,000 Middle East/North Africa 9,657,000 45 431,910 57 547,000 Sub-Saharan Africa 26,813,000 104 2,790,496 176 4,705,000 Central Asia Rep. 1,178,000 65 76,474 80 94,000 Caucasus 229,000 62 14,102 70 16,000 Moldova, Russia, Ukraine 1,684,000 16 27,025 21 36,000 Total/Mean 121,151,000 59 7,164,915 87 10,505,000 40 Chapter 6 occur and are counted separately, and some births do not fall into any of the risk categories just mentioned. However other births fall into one or more catego- ries and are termed “any risk” births. The second set of columns show how many births fall into each type of risk: a short birth interval between the birth and the preceding one (if any), a birth order of 4 or above, and a birth to a mother at either age 35+ or below age 18. (Be- cause many births fall into two or more categories the four numbers total more than 100%.) Finally, the ratio of mortality among “any risk” births to “no risk” births is shown in the last column. (The mortali- ty risk is calculated as deaths among all births occurring in the last five years, so the exposure times vary depending upon how long ago the birth occurred.) The ratios shown vary greatly and are not available for all countries, so no region- al values are given. However the ranges are of interest: Asia about 1.3 to 3.3 Latin America about 1.2 to 3.1 Middle East/N. Africa about 1.5 to 2.0 Sub-Saharan Africa only 1.1 to 1.6 Remarkably, across 31 surveys in sub- Saharan Africa, not a single country has a ratio above 1.6. The apparent reason is that because the base mortality rates are high, even the births that fall into the safe categories carry high risks, not far below the others. That makes it clear that the ratios can decline over time either because the death rates in the risky categories fall, or because the rates in the safe categories rise. If the latter rates fall faster than the former ones do, the ratios will rise. In any case, the trend in a ratio can only be understood by reference to the underly- ing mortality rates in each category, to- gether with the distribution of births across the categories. Trends: When contraceptive use rises the percent of births at high orders falls and that reduces the risk of infant and child deaths. Each line in Figure 6.1 is for one country, showing the decline in the IMR as the percent of high order births fell. In most countries the two fell together. Moreover, the main pattern, in the overall diagonal from upper right to lower left, is consistent: high values go with high values, and low with low. Roughly, a 10% fall in the percent of high order births is accompanied by a 27 point fall in the IMR. Table 6.2. Births According to Risk Category Distribution of All Births Separate Risks by Birth Type* Birth Mortality Ratio, First No-Risk Any-Risk Total Interval Birth Age Below Any-Risk Birth Births Births Births Births <24 no. Order 4+ 35+ Age 18 to No-Risk Birth Asia Bangladesh 1999/2000 13.9 33.1 53.1 100 11.4 28.7 5.7 17.2 1.80 Philippines 1998 22.4 20.7 56.9 100 26.3 37.0 15.0 2.3 1.70 India 1998/99 20.1 29.3 50.7 100 20.3 28.7 4.1 9.1 2.00 Indonesia 2003 30.4 35.6 34.0 100 8.4 20.8 13.5 4.3 1.58 Pakistan 1990/91 14.8 19.1 66.1 100 27.3 50.1 12.9 3.6 2.00 Latin America 100 Brazil 1996 26.2 29.3 44.5 100 18.7 21.5 9.6 8.3 2.00 Colombia 2000 28.1 29.5 42.4 100 16.0 17.8 9.6 8.7 2.00 Haiti 2000 17.7 20.9 61.4 100 20.5 45.3 18.0 5.2 1.30 Mexico 1987 17.7 22.6 59.7 100 25.6 39.4 11.3 6.1 2.40 Peru 2000 24.9 26.8 48.3 100 13.8 30.9 15.2 5.5 1.30 Middle East/North Africa 100 Egypt 2003 26.5 32.5 41.0 100 14.4 26.0 10.8 3.1 1.57 Jordan 2002 18.7 20.0 61.3 100 33.4 43.0 13.9 1.5 1.65 Morocco 1992 16.8 18.9 64.3 100 20.4 51.5 19.7 2.3 1.60 Turkey 1998 29.9 29.9 40.2 100 16.8 22.3 7.1 4.4 2.00 Yemen 1997 11.3 14.1 74.5 100 30.6 59.0 16.2 4.7 1.60 Sub-Saharan Africa 100 Nigeria 2003 13.7 21.2 65.1 100 19.1 46.5 14.2 8.9 1.43 Senegal 1997 12.4 23.3 64.3 100 14.6 52.8 18.4 5.6 1.20 South Africa 1998 26.1 32.1 41.8 100 9.1 26.7 15.0 6.8 1.50 Tanzania 1999 17.2 26.2 56.6 100 12.7 43.0 12.8 6.5 1.10 Uganda 2000/01 11.2 21.8 67.0 100 22.6 49.2 11.5 7.6 1.20 * Because many births fall into two or more categories the four numbers total more than 100%. Chapter 6 41 Immunizations, ARI, and ORS (Appendix Table A.21) UNICEF’S annual reports provide com- prehensive immunization data, and the latest report (UNICEF 2005) contains regional estimates for 2003. The pattern in Figure 6.2 and Table 6.3 is fairly clear. Two regions, South Asia and sub- Saharan Africa, have the farthest to go, while the other four regions perform about equally well. They have attained a level of about 90% for four of the five immunization types shown. However a level of only about 70% has been at- tained for hepatitis (no data for South Asia). Figures for individual countries are in Appendix Table A.21. Regional results for acute respiratory in- fections (ARI) also appear in Table 6.3 for three regions: the Middle East/North Africa, South Asia, and sub-Saharan Af- rica. Only 12%-19% of children are re- ported to have suffered from ARI in the last two weeks, but of those only 39- 69% saw a health provider. Treatment is even more disappointing for children with diarrhea with oral rehydration solu- tions (ORS): in the four regions shown only 25% to 36% receive ORS. (Country figures are in Appendix Table A.21). 0 20 40 60 80 100 120 140 10 20 30 40 50 60 70 Percent of Births at High Orders IM R Figure 6.1. Relation of the Infant Mortality Rate to the Percent of Births at Orders 4+ (Trends Across Multiple Surveys in 36 Countries) Figure 6.2. Percent Coverage for Immunizations, ARI, and ORS, by Region Source: UNICEF. State of the World’s Children 2005, p. 117. Indicator Notes: a Percentage of infants that received three doses of diphtheria, pertussis (whooping cough) and tetanus vaccine. b Percentage of infants that received three doses of hepatitis B vaccine. c Percentage of children (0-4 years) with acute respiratory infection (ARI) in the last two weeks. d Source: DHS, MICS, and other national household surveys. e Percentage of children (0-4 years) with ARI in the last two weeks taken to an appropriate health provider. f Source: DHS, MICS. g Percentage of children (0-4 years) with diarrhea in the last two weeks preceding the survey who received either oral rehydration therapy (oral rehydration solutions or recommended homemade fluids) or increased fluids and continued feeding. 0 10 20 30 40 50 60 70 80 90 100 TB DPT3 Polio3 Measles HepB3 Percent Immunized Central and Eastern Europe East Asia and Pacific Latin America and Caribbean Middle East and North Africa South Asia Sub-Saharan Africa Table 6.3. Percent Coverage for Immunizations, ARI, and ORS, by Region Under Age Five % with Diarrhea % with ARI Receiving Taken to ORS and 1-Year-Olds, % Immunized to Health Continued TB DPT3 Polio3 Measles HepB3 % with ARI Provider Feeding Notes - a - - b c d,e f,g East Asia & Pacific 91 86 87 82 66 - - - Latin America 96 89 91 93 73 - - 36 Middle East/N. Africa 88 87 87 88 71 12 69 - South Asia 82 71 72 67 1 19 57 26 Sub-Saharan Africa 74 60 63 62 30 14 39 32 Central & Eastern Europe 95 88 89 90 81 - - 25 Chapter 4 43 HIV/AIDS PROGRAMS AND SHORTFALLS Chapter 7Chapter 7Chapter 7Chapter 7Chapter 7 Table 7.1. Global Estimates of the HIV/AIDS Epidemic as of the End of 2003 People newly infected with HIV in 2003 Total 4.8 million Adults 4.1 million Children <15 years 630,000 Number of people living with HIV/AIDS Total 37.8 million Adults 35.7 million Children <15 years 2.1 million AIDS deaths in 2003 Total 2.9 million Adults 2.4 million Children <15 years 490,000 Total number of AIDS orphans in sub-Saharan Africa 12 million (AIDS orphans are defined as children under the age of 18 who have lost one or both parents to AIDS.) HIV/AIDS Incidence and Prevalence The HIV/AIDS epidemic has surprised the world in its rapid growth and in its severity. It strikes the young population of working age, mainly in the cities, but in some African countries it pervades the whole society and affects more than one-fourth of all adults. Global estimates. A summary of global estimates is provided by UNAIDS, which publishes an annual status report for HIV/AIDS in all regions. Most of this section is drawn from the 2004 re- port, as is Appendix Table A.13, which provides estimates by country for sever- al items of information. Highlights include the following (Table 7.1): ➤ In some regions AIDS is already the leading cause of death among adults (aged 15-49). ➤ Globally it is among the top ten caus- es of death. At current levels of new HIV infections, it may move into the top five. ➤ About 40 million people are infected with HIV; most will die within a decade although treatment programs to extend life are scaling up rapidly. Almost 3 mil- lion deaths in 2003 were due to AIDS. ➤ New infections are continuously be- ing added: about 4.8 million in 2003 alone. ➤ Over 600,000 children were infected with HIV in 2003, mostly through their mothers before or during birth or through breastfeeding. ➤ The high number of AIDS deaths to adults has created a large number of orphans. Figure 7.1 shows that there are almost a million orphans due to AIDS in five countries (Nigeria, South Africa, Zimbabwe, Tanzania and Uganda) and over 500,000 in four other countries. ➤ Only a tiny fraction of those with HIV know they have it. This disguises the ex- tent of the epidemic, invites denial, and hampers efforts to expand treatment. Growth rates. Countries differ in the patterns by which the HIV virus spreads. The prevalence of HIV infection among adults has stabilized in many countries in sub-Saharan Africa and Latin Ameri- ca but is still growing rapidly in parts of Eastern Europe and Asia. There are exceptions such as Thailand, Uganda, and Kenya that have experi- enced declines in HIV prevalence. The highest growth rates can be high in- deed, even where prevalence already falls within a high range. Figure 7.2 shows the 14-year HIV trend among pregnant women in parts of South Africa. The epidemic is most severe in southern Africa (Figure 7.3), where Namibia, South Africa, and Zimbabwe have infec- tion levels of 20-25% of all adults and Lesotho, Botswana, and Swaziland are even higher at about one-third or more of all adults aged 15-49. Nigeria South Africa Zimbabwe Tanzania Uganda Ethiopia Kenya Zambia Malawi Mozambique Côte d’Ivoire Burkina Faso Cameroon Burundi Ghana Rwanda Botswana Central African Republic Angola Lesotho Figure 7.1. Twenty African Countries with the Highest Number of Orphans Due to AIDS, 2003 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 Number of AIDS Orphans 44 Chapter 7 In Asia the pattern is different: levels are low in general, but population sizes are greater and small changes in rates can produce very large numbers of new cas- es (Table 7.2). Information is sparse for much of Asia but China’s prevalence probably doubled in recent years to over 800,000 cases. India has more infected people than any other country except South Africa, but this is still less than 1% of all adults. Figure 7.4 shows South Africa and India as first among the 20 countries with the largest absolute num- bers of HIV/AIDS cases. These reflect a balance between the country’s size and the percent affected. Ten countries ap- pear in both Figures 7.3 and 7.4 with the unfortunate distinction of having both very large numbers of cases and very high rates. These are Cameroon, Côte d’Ivoire, Kenya, Malawi, Mozambique, Nigeria, South Africa, Tanzania, Zam- bia, and Zimbabwe. Table 7.2. Adults and Children Living with HIV/AIDS by Region North Africa and Middle East 480,000 Sub-Saharan Africa 25,000,000 Caribbean 430,000 Latin America 1,600,000 East Asia and Pacific 900,000 South and Southeast Asia 6,500,000 Australia and New Zealand 32,000 North America 1,000,000 Western Europe 580,000 Eastern Europe and Central Asia 1,300,000 Total 37,822,000 Prevalence remains low (0.1% or less) in some large Asian countries: China, Indo- nesia, Pakistan, Philippines, and Sri Lanka. However, prevalence is notably higher in Myanmar, Thailand, and espe- cially Cambodia. In Latin America the picture is mixed. Adult prevalence is estimated at less than 1% in most countries, but overall some 1.6 million cases exist. Infection levels are quite high in certain popula- tions, especially injecting drug users, men who have sex with men, and com- mercial sex workers. In 1986 in Brazil women constituted one in 17 AIDS cas- es; now it is one in three. For HIV prev- alence in Latin America as a whole, about one-third of cases are women. Figure 7.2. HIV Prevalence Among Pregnant Women, Selected Provinces, South Africa, 1990-2003 Source: Department of Health, South Africa, various surveillance reports. Figure 7.3. Twenty Countries with the Highest Adult HIV/ AIDS Prevalence Levels, 2003 Figure 7.4. Twenty Countries with the Highest Number of People Living with HIV/AIDS (Adults and Children), 2003 South Africa India* Nigeria Zimbabwe Tanzania Ethiopia Mozambique Congo, D.R.* Kenya Zambia Malawi Russian Federation China Brazil Côte d’Ivoire Thailand Cameroon Uganda Sudan Ukraine Swaziland Botswana Lesotho Zimbabwe South Africa Namibia Zambia Malawi Central African Rep. Mozambique Tanzania Gabon Côte d’Ivoire Cameroon Kenya Burundi Liberia Haiti Nigeria Rwanda 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 Number of Adults and Children* 2002 Estimates 0 5 10 15 20 25 30 35 40 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 H IV P re va le nc e (% ) KwaZulu Natal Gauteng Free State Eastern Cape 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 Prevalence of Adults (15-49) Chapter 7 45 Because contraceptive use is widespread in Latin America fewer women become pregnant, which reduces the absolute number of mother-child transmissions; consequently there are fewer infected in- fants and fewer orphans when women die. In North Africa and the Middle East, the smallest region, data are very thin, but Sudan is the only country that estimates its adult HIV prevalence at above 1%. Only about 443,000 cases are estimated to exist (Table 7.2), less than 1% of the world’s total. Eastern Europe has some of the fastest- growing epidemics. Russia ranks twelfth in terms of countries with the most peo- ple living with HIV/AIDS (Figure 7.4). The epidemic there and elsewhere in the region is fueled by transmission among injecting drug users who share injection equipment. The HIV/AIDS epidemic has also contributed to an exploding tuber- culosis epidemic that is producing new strains of TB resistent to many of the drugs used to treat TB. Methods. Figures on prevalence and mortality are subject to much error. Prevalence estimates in sub-Saharan Af- rica come chiefly from women attending antenatal clinics and from some nation- al surveys. In the other regions estimates are based on surveillance among popula- tions at high risk. It is not enough just to measure current HIV prevalence, since it reflects the three different components of the recent flow of new cases, the in- herited bulk of cases from the past, and AIDS deaths. This can confuse any prognosis of growth. In a mature epi- demic prevalence may be stable, but this stability simply means that the number of new infections every year equals the number of people dying from AIDS each year. When prevalence stabilizes at a high level, such as 20-25% in Zimbabwe and South Africa, it means that about 2% of adults are dying each year from AIDS and another 2% are newly infected each year. Goals and Strategies The international community has adopt- ed several goals to guide the fight against HIV/AIDS. In 2001 the United Nations General Assembly Special Ses- sion on AIDS (UNGASS) developed a consensus on a strategy for addressing the epidemic. Other United Nations or- ganizations and meetings have elaborat- ed on particular parts of the strategy and many donors have developed their own targets. Among the key goals are: ➤ Reduce HIV prevalence among young people by 25% by 2005 in the most af- fected countries and by 2010 everywhere (UNGASS). ➤ Reduce infections due to mother-to- child transmission by 20% by 2005 and 50% by 2010 (UNGASS). ➤ Expand anti-retroviral treatment pro- grams to reach 3 million people by the end of 2005 (WHO). ➤ Halt and begin to reverse the HIV/ AIDS epidemic by 2015 (Millennium Development Goal). ➤ Provide anti-retroviral treatment to 2 million people by 2008, avert 7 million new HIV infections by 2010, and pro- vide care and support to 10 million peo- ple living with HIV/AIDS and orphans made vulnerable by HIV/AIDS by 2008 (U.S. President’s Emergency Plan for AIDS Relief). Comprehensive prevention programs have focused on mass media, condom promotion, control of sexually transmit- ted infections, voluntary counseling and testing, blood safety, school-based AIDS education, and outreach programs for sex workers, men who have sex with men, and injecting drug users. Condom distribution has increased dramatically in many countries, expanding to 50-100 million condoms per year in countries such as Ethiopia, Kenya, Nigeria, and Zimbabwe; however, even more are needed to cover all risky sex acts (Ap- pendix Table A.23). Recently more attention has been fo- cused on programs to promote absti- nence and reduce the number of people with multiple partners. Programs to pre- vent mother-to-child transmission are expanding rapidly in many countries. There have been some successes. Ugan- da and Thailand were able to dramatical- ly reduce prevalence during the 1990s. Senegal took early action to keep preva- lence at low levels. Recently prevalence has begun to decline in Kenya. Latin America has led the way in ex- panding access to anti-retroviral treat- ment with many countries there provid- ing universal access. In the last several years a new emphasis on treatment has led to a rapid expansion of the numbers of people receiving anti-retroviral thera- py in other regions as well, to over 700,000 by the end of 2004. This figure is expected to grow to 3 million in the near future. The expansion of treatment will mean better survival for millions of HIV-positive people. Efforts are also being made to address the consequences of the epidemic. Countries in sub-Saharan Africa are attempting to expand programs to support the millions of orphans and other children made vul- nerable by HIV/AIDS. Efforts are being made to address stigma and discrimina- tion and to improve the legal, cultural, and economic practices that increase vul- nerability for women, although progress has been slow. Strategies to control the epidemic differ according to the type of epidemic. In countries with low-level epidemics (prevalence less than 5% in all popula- tion groups) and concentrated epidemics (prevalence above 5% in some popula- tion groups but less than 1% in pregnant women), prevention efforts need to focus on those populations with the highest risks where most new infections are oc- curring. This includes injecting drug us- ers, men who have sex with men, and sex workers and their clients. Interven- tion now to stop transmission in these populations can prevent much larger ep- idemics in the future. In generalized ep- idemics (prevalence above 1% in preg- nant women) efforts need to be directed to all segments of the population. Ex- panding treatment access to meet the 46 Chapter 7 large numbers needing treatment re- quires not only more funding but also increased capacity to deliver drugs and manage patients on long-term care. Ex- panded access to treatment will not only save lives but may also help to improve the environment for prevention. Some prevention programs have expand- ed at rapid rates in the past few years. A survey of the coverage of prevention and care services in 2003 produced by the 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 2001 2003 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 2001 2003 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 2001 2003 0 10,000,000 20,000,000 30,000,000 40,000,000 50,000,000 2001 2003 Figure 7.6. The AIDS Program Effort Index by Region, 2003 Number of people receiving voluntary counseling and testing (VCT) Number of pregnant women offered services to prevent mother to-child transmission (PMTCT) Number of PLHA receiving anti-retroviral therapy (ART) Number of secondary school students receiving AIDS education Figure 7.5. Number of People Receiving Services in 2001 and 2003 for Countries Reporting in Both Surveys for VCT, PMTCT, ART, and AIDS Education - 10 20 30 40 50 60 70 80 90 100 Po litic al su pp or t Po licy an d pla nn ing Or ga niz ati on al str uc tur e Pro gra m re so ur ce s Ev al, m on , re se ar ch Le ga l an d re gu lat ory Hu m an rig hts Pre ve nti on pro gra m s Ca re pro gra m s Mi tiga tio n Eastern and Southern Africa Western and Central Africa Asia Latin America and Caribbean Eastern Europe POLICY Project (2003a) shows large in- creases in the past two years in the num- ber of people receiving voluntary coun- seling and testing, treatment to prevent mother-to-child transmission of HIV, anti-retroviral therapy and school-based AIDS education (Figure 7.5). Coverage of the population in need is still low for these services, however, and in other ar- eas the need is even greater, such as ef- fective programs for injecting drug users and men who have sex with men. National governments, bilateral and in- ternational donors, and private founda- tions have significantly increased the resources devoted to HIV/AIDS pro- grams to US$6 billion in 2004, but an estimated US$10–20 billion will be needed annually in the coming years to successfully address all the prevention, care and treatment, and mitigation needs. Although efforts to control the spread of AIDS and address its consequences have improved markedly in the past 5 years, much remains to be done. Figure 7.6 presents a profile of effort showing where efforts are strongest and where they are weakest. The AIDS Program Ef- fort Index (API) measures overall effort in 10 categories through interviews with national experts (POLICY Project 2003b). The 2003 round of the API, con- ducted in 54 countries, shows that most countries have done well in providing political support and the policy and planning required to address the epidem- ic. However, effort lags far behind in mobilizing and using financial resources and in protecting the human rights of people living with HIV/AIDS. References UNAIDS. Report on the Global HIV/ AIDS Epidemic, June 2004. Issued by UNAIDS/WHO, Joint United Nations Programme on HIV/AIDS (UNAIDS). World Health Organization. 2004. UNAIDS. Children on the Brink 2004. A Joint Report of New Orphan Estimates and a Framework for Action. UNAIDS, UNICEF, USAID. July 2004. POLICY Project 2003a. “Coverage of Selected Services for HIV/AIDS Preven- tion, Care and Support in Low- and Mid- dle-Income Countries in 2003.” USAID, UNAIDS, WHO, UNICEF, POLICY Project. 2003. POLICY Project 2003b. “The Level of Effort in the National Response to HIV/ AIDS: The AIDS Program Effort Index (API), 2003 Round.” USAID, UNAIDS, WHO, and the POLICY Project. Dec. 2003. Chapter 8 47 Introduction This chapter discusses five program ob- jectives: 1. To provide full access to a variety of contraceptive methods 2. To satisfy unmet need and intention to use a method 3. To reach the desired fertility level 4. To attain the replacement fertility level 5. To satisfy the Millennium Develop- ment Goals and the Cairo Programme of Action. These objectives have been stressed in various national plans or in the interna- tional discourse concerning the proper goals of action programs. The first objec- tive is the aim of providing good access to a full range of contraceptive methods to the population; this may be regarded as a necessary condition to attaining other objectives, and so it logically comes first. The second is meant to ad- dress unmet need and the level of ex- pressed intention to use contraception. The third overlaps with that; it is to assist couples in reaching the desired level of fertility. The fourth is to move toward the replacement fertility level, an objective that is present in numerous national plans. The fifth concerns both the Mil- lennium Development Goals and the Cairo Programme of Action: two sets of objectives recognized by the interna- tional community, that match to a great extent. Goal No. 1: To Provide Full Access to a Variety of Contraceptive Methods The Cairo ICPD meeting stressed the goal of providing full availability to family planning methods. The Pro- gramme of Action declared: “All countries should take steps to meet the family planning needs of their popu- lations as soon as possible and should, in all cases by the year 2015, seek to pro- vide universal access to a full range of safe and reliable family planning meth- ods.” And they should: “Recognize that appropriate methods for couples and individuals vary according to their age, parity, family-size preference and other factors, and ensure that women and men have information and access to the widest possible range of safe and ef- fective family planning methods.” However there is a long way to go before most couples are given a true choice of alternative methods. In this section we use selected scores from past cycles of the International Family Planning Effort Study (Ross and Stover, 2001). (See Ap- pendix Table A.14.) Of the 30 scores in the study, five concern the availability of contraceptive methods to the population. Country experts estimate what propor- tion of the population has ready access to each method – pill, IUD, male steril- ization, female sterilization, and con- dom. This is explicitly not the propor- tion currently using the method, but rather the proportion who have reason- able access to it. Table 8.1 and Figure 8.1 summarize the combinations of methods and the avail- ability of individual methods. The rule employed is that at least half of the pop- ulation must have access to a method for it to be considered available. For exam- ple, the pill is considered available by this rule in 83% of 88 countries (Table 8.1, top panel) and the IUD in 63%. Male sterilization is available in only 25% of countries while condoms are available in 85%. Our focus however is not upon single- method access but upon something clos- er to “full availability of contraception,” Table 8.1. Percent of Countries Making Contraceptive Methods and Combinations of Methods Available as of 1999 Sub- Latin Middle East/ Saharan Eastern All Asia America North Africa Africa Europe Countries Pill 94.4 100.0 90.9 61.3 80.0 83.0 IUD 77.8 82.6 90.9 22.6 100.0 62.5 Female sterilization 72.2 60.9 45.5 19.4 20.0 44.3 Male sterilization 55.6 30.4 18.2 6.5 20.0 25.0 Condom 88.9 91.3 90.9 77.4 80.0 85.2 Pill and IUD 77.8 82.6 90.9 22.6 80.0 61.4 Pill and female sterilization 72.2 60.9 45.5 19.4 20.0 44.3 IUD and female sterilization 72.2 60.9 45.5 16.1 20.0 43.2 Pill, IUD and female sterilization 72.2 60.9 45.5 16.1 20.0 43.2 Pill, IUD, female sterilization, condom 72.2 60.9 45.5 16.1 20.0 43.2 At least one long-term method 77.8 82.6 90.9 25.8 100.0 63.6 At least one short-term method 94.4 100.0 90.9 77.4 100.0 89.8 At least one long-term and at least one short-term method 77.8 82.6 90.9 25.8 100.0 63.6 No. of countries 18 23 11 31 5 88 Chapter 8Chapter 8Chapter 8Chapter 8Chapter 8 FIVE PROGRAM OBJECTIVES 48 Chapter 8 the topic of this section. That leads to the question of how many countries provide multiple methods. Therefore the second panel of Table 8.1 gives the percent of countries where both pill and IUD availability meet the 50% rule – similarly for each other combina- tion shown. Finally, the bottom panel al- lows for some flexibility in the provision of methods: in the first row a country qualifies if any long-term method ex- ceeds 50% availability – either male or female sterilization or the IUD. Numer- ous countries offer either the IUD or fe- male sterilization, which produces the relatively high 64% in the last column. In the second row a country qualifies if any short-term (resupply) method meets the 50% rule, either the pill or condom. Again, many countries offer at least one, so 90% qualify in the last column. The last line combines the two previous lines: a country qualifies only if it meets both criteria, which reduces the figure to 64%. The numbers necessarily decline as more stringent conditions are applied. Eighty-three percent of countries qualify for the pill alone, but only 61% qualify for the pill and IUD together, and only 43% for those plus female sterilization. Thus less than one-half of all countries provide those three methods to at least one-half of the population – a far cry from the ICPD goal. Even those may not do so uniformly throughout the country: Figure 8.1. Availability of Multiple Contraceptive Methods certain areas may have most access to just the pill and condom, and other areas only to the pill and sterilization. Regions differ in the combinations of methods they provide. The Middle East/ North Africa does poorly on combina- tions that include sterilization, whereas Asia and Latin America do considerably better. However the Middle East/North Africa improves in the bottom panel, where flexibility is allowed as to which methods qualify. Overall, Francophone sub-Saharan Afri- ca has the least method availability. By the Cairo ICPD mandate, it is farthest from the goal of “full availability.” It does best for condoms (top panel) but poorly for all other methods, which hurts its ratings in the combinations. The eas- iest route to an enlarged choice of meth- ods in the short term would be to add the pill to numerous outlets in both public and private sectors. However long-term methods are also needed both for auto- matic continuation and reliability. Distance to go to “full availability.” Observers have long noted the adjust- ments needed in certain country pro- grams. India and Nepal have a near-ex- clusive stress on sterilization, which calls for a better balance with temporary methods. Conversely, Indonesia’s cau- tion regarding sterilization has left many couples with unsatisfactory alternatives, and this occurs in Egypt as well. Viet Nam’s preoccupation with the IUD alone has driven many couples to high- failure temporary methods and to exces- sive numbers of abortions. The tendency in numerous countries toward only one or two methods appears in detail in the method mix data in Chapter 2. A different kind of problem prevails in some Francophone countries where no method at all is widely available to the mass of the population, as in Chad, Mali, Mauritania, and both Congos. This is equally true in some Anglophone coun- tries, such as Ethiopia and Nigeria. All these and others face the elementary need to deploy services to most of the population. Moreover, physical avail- ability of several contraceptive methods needs to be accompanied by services that are convenient and congenial to po- tential clients. Thus the overall picture is quite bleak for public access to a variety of contra- ceptive choices. The rule used here, that a method is “available” if it is readily accessible to at least half of the popula- tion, is a lenient one. Yet less than two- thirds of countries provide at least one long-term method and one short-term method to half of the population. Nevertheless there has been improve- ment over time. Figure 8.2 and Table 8.2 display the average availability scores from the international family planning effort studies, for male and fe- male sterilization, IUD, pill, and con- dom (each score is the percent of maxi- mum*). The figure is based on the 69 countries included in all years, which clarifies the time trend, but data are also shown in Table 8.2 for the 109 countries that were in at least one study. The general regional pattern is one of in- creasing availability, except for Latin America and Asia after 1989 when they were already at relatively high levels. The Middle East/North African region *The original scores ranged from zero to four, where four was any percentage over 80. Therefore the “maximum” here is best regarded as about 85%, so that a score of 60% in the table or figure is in fact about 51%. As a result, the figures shown are somewhat elevated. 0 10 20 30 40 50 60 70 80 90 100 Pill and IUD Pill and F ster IUD and F ster Pill, IUD, F ster Pill, IUD, F ster, condom At least one long-term method At least one short-term method At least one long-term and at least one short- term method Pe re nt o f C o u n tri e s R ea ch in g 50 % o f P o pu la tio n Chapter 8 49 Table 8.2. Time Trend of the Average Availability Score, 1982-1999, from Family Planning Effort Studies 69 Countries Included in All Studies No. of 1982 1989 1994 1999 Countries Latin America 54.6 69.4 69.6 71.2 19 Asia 59.8 66.7 64.4 70.3 16 Anglophone SSA 12.7 33.2 44.9 48.0 12 Francophone SSA 6.7 19.9 21.2 24.6 12 Middle East/N. Africa 26.7 50.0 61.9 64.6 10 All regions 35.8 50.8 54.6 57.9 69 109 Countries in One or More Studies No. of 1982 1989 1994 1999 Countries Latin America 54.8 68.6 66.0 69.9 24 Asia 56.9 59.2 63.0 71.3 24 Anglophone SSA 13.6 33.5 50.1 50.3 19 Francophone SSA 6.6 20.4 23.6 29.7 21 Middle East/N. Africa 18.2 36.4 52.5 61.2 16 Central Asia Rep. - - 17.7 52.7 5 All regions 32.5 44.6 51.9 57.5 109 has improved noticeably over the years. Anglophone sub-Saharan Africa has also improved, though in 1999 it was still below the 50% mark, and the bottom re- gion, Francophone sub-Saharan Africa, improved very little after 1989, persist- ing at a low level. The five Central Asian Republics (see table) improved marked- ly from 1994 to 1999 in making contra- ceptives available. The leveling off of the curves at about 70%, and the slowing of improvement by the Middle East/North Africa as it ap- proaches that level, suggest a kind of practical ceiling to average availability. Average availability is depressed partly by the inclusion of male sterilization, which still suffers from poor access in many countries. Access improvements have been selective, and have been most impressive for the pill and condom. References Ross, John. “The Question of Access.” Studies in Family Planning 26(4):241- 242. 1995. Ross, John, and W. Parker Mauldin. “Family Planning Programs: Efforts and Results, 1972-94.” Studies in Family Planning 27(3):137-147. 1996. Ross, John and John Stover. “The Fami- ly Planning Program Effort Index: 1999 Cycle.” International Family Planning Perspectives 27(3):119-129. Sept. 2001. United Nations Population Fund. Pro- gramme of Action: Adopted at the Inter- national Conference on Population and Development. Cairo, September 5-13, 1994. Pages 51, 53. Booklet published 1996. Wilkinson, Marilyn I., Wamucii Njogu, and Noureddine Abderrahim. The Avail- ability of Family Planning and Maternal and Child Health Services. DHS Com- parative Studies No. 7. Calverton, Mary- land: Macro International. 1993. Figure 8.2. Mean Availability Score for Five Contraceptive Methods, 69 Countries in All 4 Studies (Percent of Maximum Score) 0 10 20 30 40 50 60 70 80 1982 1989 1994 1999 M ea n Sc o re Latin America Asia Anglophone SSA Francophone SSA Middle East/N. Africa All regions 50 Chapter 8 Goal No. 2: To Satisfy Unmet Need and Intention to Use a Method Besides serving as one indicator of the public’s need for contraceptive assis- tance, unmet need can be supplemented by information on a woman’s own ex- pressed intention to use a method. Here we provide first the unmet need perspec- tive, and then additional information on intention to use. The unmet need concept has been useful through the years as a humane rationale for action programs and as evidence of a large subgroup in nearly every popula- tion whose needs have not yet been ad- dressed. As a counterpoint to target-driv- en approaches it has helped ease interna- tional opposition to family planning, partly by demonstrating that satisfying unmet need in many populations would raise contraceptive prevalence as much as meeting the targets would. That helps justify the discontinuance of worker tar- gets (Sinding et al., 1994) and in princi- ple can release workers from general re- cruitment efforts and let them focus on simply helping the truly interested cou- ples. Unmet need therefore has served as one of the considerations for program plan- ning, as it was in the 1994 Cairo ICPD meeting. At both international and re- gional levels it has been an important rationale for justifying donor funding and for winning the support of a broad spectrum of interest groups. This is true also within some individual countries, where it serves to help gauge the inter- ested market for family planning. For planning purposes however, where sur- vey data permit, the unmet need esti- mates should be reduced for women who do not intend to use, but increased to recognize omitted couples who intend to use a method. Unmet need reflects the puzzling gap between the desire to avoid pregnancy and the failure to use contraception. This gap changes in size during the transition from very low prevalence of contracep- tive use, as in Ethiopia for example, to very high prevalence, as in Thailand or Colombia over time. Unmet need starts small, since the desired family size is large, and ends small, since nearly ev- eryone is using a method. In between, unmet need tends to be rather large, since usually there is a serious lag in supplies and services to address the pub- lic’s growing desire to avoid unwanted pregnancies. Therefore the time trend in unmet need can disguise program im- provements if they are outrun by a rapid decline in desired family size. The data used here are based primarily upon the DHS definition of unmet need* since that is available for numer- ous countries. However the figures would be higher if the definition were expanded to sexually active single men and women, dissatisfied users, tradition- al method users, and amenorrheic wom- en close to the return of menses. In Viet Nam for example unmet need rises from 14% to 36% if traditional method users (who have a high abortion rate for fail- ures) are included (Phai et al., 1996). How rapidly can unmet need be erased? Programs work best by satisfying the in- terest that already exists, as good in it- self and as the best way to enlarge that interest. International experience (Ta- ble 8.3) indicates that an annual rise of about two points in prevalence is as much as can be expected, unless the pro- gram is exceptionally strong and the public is especially ready. A 2% rise per year in Ethiopia would require ten years for unmet need to fall from 35% to 15%, which is the current level in Bangladesh. Historically however, unmet need and prevalence have often not moved togeth- er. For example, in Kenya prevalence rose by 1.5 points annually from 1989 to 1993 and by 1.3 points annually from 1993 to 1998. However unmet need fell only slightly from 1989 to 1993, from 38.0 to 35.5, since the desire to avoid pregnancy changed nearly as fast as the prevalence level did. The ICPD directive to reduce unmet need translates in practice to a rise in contraceptive prevalence, in programs that focus on women or couples who are genuinely interested in postponing preg- nancy and in using contraception. Un- met need may rise during an intermedi- ate stage but it finally diminishes as con- traceptive prevalence increases to a high level. Meanwhile there is movement in and out of the pool of users and the var- ious unmet need categories. Trends in unmet need. In some coun- tries, most of them with medium to high prevalence, unmet need has declined over time, as illustrated by 15 of the 18 countries in Figure 8.3. It shows unmet need, contraceptive prevalence, and total demand (the sum of the other two) at two dates. In nearly all cases prevalence has risen and need has decreased. De- mand varies from 33% in Nigeria to over 80% in Colombia. Data covering most surveys over time confirms that unmet need has in general been declining as contraceptive use has risen. The proportion of total demand that is accounted for by contraceptive use is a useful measure; it is simply use divided by the sum of use plus need. Table 8.4 shows this measure by wealth quintiles; it documents clearly that persons in the bottom quintiles have the least part of their demand met by contraceptive use. The lowest figures are only 12.9% and 23.7% in the lowest quintile in Africa. Across the quintiles, each next wealthier group has more demand satisfied. That holds true in every region and in both time periods. A favorable feature in the table is that all quintiles and regions show improvement from the earlier to the later period. This general pattern is echoed in Figure 8.3. When the desired family size has fallen quickly, before contraceptive use has caught up, unmet need is large as a proportion of total demand. This pattern is visible in the demand range between 40% and 55%, as in Benin, Tanzania, *Women with unmet need are those who are mar- ried/cohabiting, fecund, not using a method, and wish to postpone birth at least two years. Women who are pregnant or amenorrheic have unmet need if they did not want the current pregnancy or recent birth either at that time or at all, but if a contracep- tive failure was responsible the woman is treated as having no unmet need. Chapter 8 51 Prevalence Circa 1990 Less than 1.0 1.0-1.9 2.0 or More Less than Rwanda (0.55) Niger 1.09 15 percent Angola (0.38) Gambia (0.22) Eritrea - Iraq - Afghanistan 0.12 Mali 0.24 Sudan 0.37 Ethiopia 0.38 Mauritania 0.47 Burkina Faso 0.67 Guinea 0.70 Chad 0.79 Senegal 0.79 Mean 0.24 15-34 Madagascar 0.32 Nigeria 1.03 Oman 2.16 percent Benin 0.44 Togo 1.13 Cambodia 2.26 Cameroon 0.52 Comoros 1.18 Yemen 2.27 Burundi 0.54 Uganda 1.49 D.R. Congo 2.37 Ghana 0.64 Pakistan 1.56 Central African Rep. 2.62 Swaziland 0.65 Haiti 1.59 Myanmar 3.18 Côte d'Ivoire 0.69 Zambia 1.62 Lesotho 0.96 Tanzania 1.89 Malawi 1.91 Laos 1.94 Mean 0.59 Mean 1.53 Mean 2.48 35-49 Trinidad and Tobago (1.12) Syria 1.09 percent Dominica 0.13 Philippines 1.14 Guyana 0.24 Kenya 1.31 Botswana 0.62 Guatemala 1.36 Saint Lucia 0.66 Nepal 1.62 India 0.75 Qatar 0.99 Mean 0.32 Mean 1.30 50-64 Turkey 0.14 Malaysia 1.03 Paraguay 2.00 percent Azerbaijan 0.30 Zimbabwe 1.05 Bolivia 2.01 Lebanon 0.32 Indonesia 1.11 Algeria 2.18 South Africa 0.66 Barbados 1.22 Grenada 2.27 Dominican Rep. 0.96 El Salvador 1.27 Morocco 2.57 Bahrain 1.40 Egypt 1.50 Honduras 1.51 Tunisia 1.70 Kuwait 1.73 Bangladesh 1.84 Jordan 1.95 Mean 0.48 Mean 1.44 Mean 2.21 65+ Mongolia (0.19) Colombia 1.08 Nicaragua 2.10 percent Mauritius (0.10) Brazil 1.09 Iran 2.37 Thailand 0.02 Jamaica 1.23 Uzbekistan 2.90 Cuba 0.25 Mexico 1.34 Rep. of Korea 0.49 Ecuador 1.39 Puerto Rico 0.52 Peru 1.43 China 0.62 Viet Nam 1.71 Sri Lanka 0.68 Kazakhstan 1.90 Costa Rica 0.81 Mean 0.35 Mean 1.40 Mean 2.46 Source: United Nations Population Division, "World Contraceptive Use 2003" Wall Chart. Table 8.3. Annual Percentage-Point Increase in Contraceptive Prevalence Around 1990-2000, by Prevalence at the Start of the Period 52 Chapter 8 Uganda, Malawi, and Guatemala. Note that while unmet need is large, its share of total demand declines over time as the prevalence bars grow more than the un- met need ones do. Another way to approach the interaction between prevalence and unmet need is by calculating the annual increase in prevalence as a percent of need at the time of the first survey. That is, how much of the initial unmet need is trans- lated into prevalence increases during the ensuing years? In Figure 8.4 the range is from 1% to 11% around an av- erage of about 5%. That suggests that in the middle range of prevalence, half of the initial unmet need could be satisfied over a decade. There is of course consid- erable circulation of individuals in and out of using statuses and unmet need cat- egories over time, but the net changes can be positive. Global estimates of need. Surveys pro- vide estimates of unmet need for many countries (Appendix Table A.9). By as- signing to unknown countries the region- al averages of the known countries we can obtain a crude picture of unmet need for most of the developing world. Table 8.5 presents the results: because unmet need has declined somewhat as contra- ceptive prevalence has risen in the devel- oping world, the overall level of unmet need for married women is about 17%, and about 13% for all women. The num- bers in need remain large due to popula- tion growth: 105 million for married women and another 8 million for unmar- ried women.* Most live in Asia; large numbers are also in sub-Saharan Africa, with smaller numbers in Latin America and Middle East/North Africa. Needs for spacing and limiting are about evenly balanced at 8%-9% each except in sub- Saharan Africa, where the ratio is about two to one. *Including Russia, Eastern Europe, the Caucasus, and the Baltic Republics another 9.1 million wom- en (both married and unmarried) are added, for a total of 122 million. 0 10 20 30 40 50 60 70 80 90 Nigeria 1990 Cameroon 1991 Benin 1996 Tanzania 1992 Uganda 1995 Malawi 1992 Guatemala 1995 India 1992.5 Zimbabwe 1994 Indonesia 1991 Egypt 1992 Jordan 1990 Bangladesh 1993.5 Turkey 1993 Bolivia 1994 Peru 1992 Dominican Rep. 1991 Colombia 1990 Percent Unmet Need Prevalence Figure 8.3. Trends in Unmet Need, Prevalence, and Demand Q1 Q2 Q3 Q4 Q5 All Quintiles Africa 1990-1995 12.9 16.0 17.7 24.7 36.9 22.9 1996-2000 23.7 25.2 29.1 37.2 48.0 33.9 Latin America 1990-1995 29.4 40.7 49.0 57.4 65.3 50.0 1996-2000 38.1 48.8 57.3 61.7 68.0 56.4 Asia 1990-1995 48.2 51.0 57.5 57.5 67.6 57.1 1996-2000 50.0 57.1 59.8 63.7 70.7 60.9 N. Africa/W. Asia 1990-1995 36.8 45.7 53.7 58.2 65.4 53.8 1996-2000 49.7 59.0 62.0 67.5 70.5 62.7 Global Average 1990-1995 29.2 35.8 40.4 46.2 55.6 42.7 1996-2000 37.9 44.4 49.3 54.7 62.1 50.8 Source: Bernstein, 2004. Table 8.4. Proportions of Demand Satisfied by Modern Contraceptive Use, by Wealth Quintile (Q1: poorest) (unweighted averages for selected countries within each region) Chapter 8 53 India has by far the most women with unmet need (Figure 8.5): some 32 mil- lion, accounting for 32% of all need in the developing world (China is assumed to have none by the DHS definition). The next country, Pakistan, has 7 million in need, for 8% of the total. Half of all couples in need live in the top five coun- tries, including Bangladesh, Indonesia, and Nigeria. Two-thirds of all need is in only 11 countries, showing the sharp geographic concentration of unmet need. Youth in need. The two age groups, 15- 19 and 20-24, account for 33% of all un- met need among married women, or 34.9 million women. The 20-24 age group contains twice the number in need as in the 15-19 age group (23.5 vs. 11.4 million). Sub-Saharan Africa has the highest proportion with unmet need – about one in four for both youth and for women of all ages. However, the other regions show differences: young women have more unmet need than do all wom- en by a considerable margin in Latin America (22% vs. 14%), in Asia (23% vs. 16%), and in the Central Asian Re- publics (16% vs. 11%), but by rather lit- tle in the Middle East and North Africa (18% vs. 16%). Details are in Chapter 4; see the “Youth” section. Intention to use a method. The unmet need perspective can be adjusted by in- formation on women’s own statements as to their intention to use contraception. Table 8.6 cross-classifies intention and need for 14 countries selected from Ap- pendix Table A.11 (it contains data from 78 surveys in 48 countries). The figure shows both sides of the adjustment: some of those with unmet need do not intend to use a method, but others with- out apparent need do plan to use. In Ken- ya 28% of nonusers (right-hand column) intend to use a method even though they are classified as having no unmet need – the same women represent 17% of all married women (left-hand column). They more than balance out the smaller group that has unmet need but plans not to use (10% on the right and 6% on the left). Among non-users in Table 8.6, from 15% to 47% of women lacking unmet need by the DHS definition still intend Figure 8.4. Percent of Unmet Need Converted to Annual Prevalence Increases Table 8.5. Number (000s) and Percent of Women with an Unmet Need for Contraception, by Region and Marital Status, 2000 Married Women Unmarried All Women All Spacing Limiting Women Numbers Developing world 113,647 105,205 55,402 49,803 8,442 Asia (ex. China) 63,650 61,142 31,658 29,484 2,508 Sub-Saharan Africa 27,997 23,550 15,269 8,281 4,447 Latin America 11,837 11,088 4,615 6,473 749 Middle East/North Africa 8,925 8,306 3,345 4,961 619 Central Asia 1,238 1,119 515 604 119 Percents Developing world 13.0 17.1 9.0 8.1 3.2 Asia (ex. China) 12.9 16.4 8.5 7.9 2.0 Sub-Saharan Africa 19.4 24.2 15.7 8.5 9.5 Latin America 8.5 13.7 5.7 8.0 1.3 Middle East/North Africa 10.6 15.6 6.3 9.3 2.0 Central Asia 8.5 11.4 5.2 6.2 2.6 Figure 8.5. Number of Married Women with Unmet Need: Top 20 Countries 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 35,000,000 Ind ia Pa kis tan Ba ng lad es h Nig er ia Ind on es ia Eth iop ia Ira n Ph ilip pin es Th ail an d Co ng o D .R. My an m ar Ne pa l Eg yp t Tu rke y Ug an da Ta nz an ia Ke ny a Ar ge nti na Ye m en Vie t N am 0 0 2 4 6 8 10 12 Gh an a Ma li Ma da ga sca r Be nin Ca me roo n Tu rke y Cô te d'Iv oir e Bo livi a Nig er Ke ny a Se ne ga l Ha iti Ug an da Nig eri a Eg ypt Ph ilip pin es Ma law i Ne pa l Zim ba bw e Ind ia Ta nz an ia Gu ate ma la Jo rda n Za mb ia Pe ru Ba ng lad esh Ind on es ia Co lom bia Do mi nic an Re pu blic Ka za kh sta n AV ER AG E Pe rc en t 54 Chapter 8 Table 8.6. Relation of Unmet Need and Intention to Use* to use. Among all married women the average across the 14 countries is 15% who plan to use even though they are classified without need. Among non-us- ers the average is 31%, a remarkable finding. This occurs due to an oddity in the DHS definition, which says that women who want a birth within two years have no need. Actually substantial numbers of those women do not want to become pregnant just yet; they wish to insure a delay of their next conception within the two-year period in question. These “in- tenders without need” need to be taken into account in program planning. One methodological note is in order: in- tention to use is divided in some surveys into intention to use within the next year vs. intention to use later. However many surveys do not use this distinction, so the data presented here refer to intention to use at anytime, whether in the next year or later. If data were available every- where on use within the next year that would be preferable, since that signals a firmer resolve in the short term and probably contains fewer courtesy re- plies. All the intention figures here would be lower if restricted to the next year. However the figures would be larger if amenorrheic women were included in the unmet need count. Nearly all women near their last birth say they do not want to become pregnant again soon, and many are close to resuming ovulation. For program purposes they are eminent- ly in need of information and access for contraception. Including all amenorrhe- ic women raises the proportion with un- met need by half, from an average of 22% to 33% in a study of 27 countries (Ross and Winfrey, 2002). (All amenor- rheic women were included regardless of future intention statements, but as noted, few such women wish to get preg- nant soon and many would intend to use.) Some analysts prefer a less inclu- sive rule, to retain only women who are at least four months from their last birth. That focuses upon women who are near- er to the resumption of menses, and avoids what may appear as an excessive estimate of need. Among All married women Among Married Non-Users Unmet Need Unmet need Yes No Using Yes No Totals Asia Bangladesh 2000 Intend to use Yes 13 20 Yes 28 44 71 No 3 11 No 6 23 28 15 31 54 33 67 100 India 1999 Intend to use Yes 12 19 Yes 22 38 60 No 4 16 No 8 31 40 16 35 48 31 68 100 Indonesia 2002 Intend to use Yes 4 13 Yes 11 32 43 No 4 18 No 11 46 56 9 31 60 22 78 100 Philippines 1998 Intend to use Yes 10 12 Yes 19 23 42 No 9 21 No 17 41 58 19 33 48 36 64 100 Latin America Colombia 2000 Intend to use Yes 5 11 Yes 23 47 70 No 1 6 No 4 27 30 6 17 77 27 73 100 Dominican Rep. 2002 Intend to use Yes 9 11 Yes 30 36 66 No 2 8 No 6 28 34 11 19 70 36 64 100 Peru 2000 Intend to use Yes 7 10 Yes 23 33 56 No 3 11 No 9 34 43 10 21 69 33 67 100 Middle East/North Africa Egypt 2000 Intend to use Yes 7 19 Yes 17 42 59 No 3 15 No 8 33 41 11 33 56 24 76 100 Turkey 1998 Intend to use Yes 7 12 Yes 19 33 52 No 3 14 No 9 38 47 10 26 64 28 72 100 Sub-Saharan Africa Ethiopia 2000 Intend to use Yes 24 18 Yes 26 20 46 No 11 39 No 12 42 54 35 57 8 38 62 100 Kenya 2003 Intend to use Yes 18 17 Yes 30 28 58 No 6 19 No 10 32 42 25 36 39 40 60 100 Nigeria 1999 Intend to use Yes 6 13 Yes 8 15 23 No 11 53 No 12 62 76 17 66 15 21 78 100 Tanzania 1999 Intend to use Yes 13 16 Yes 18 21 39 No 8 37 No 11 50 61 22 53 25 29 71 100 Uganda 2000 Intend to use Yes 26 22 Yes 34 28 62 No 8 21 No 11 27 38 35 43 23 45 55 100 *Intention to use at any time in the future. Source: Special tabulations provided courtesy of ORCMacro, Demographic and Health Surveys. Chapter 8 55 An examination of five DHS countries for women with sexual experience found that the inclusion of those amenorrheic women who either wanted no more chil- dren or wanted to wait increased the per- cent with unmet need by roughly half (Bernstein, 2005), a result that matches the one-half increase found just above. For surveys that do not ask about amen- orrheic status, reliance upon when the next child is wanted is especially rele- vant. In any case, explicit clarification of the rule is essential. Intention to use is a marker for the extent of serious interest in contraceptive use. In a Morocco panel study (Curtis and Westoff, 1996) stated intention was the best predictor of which women in fact adopted contraception after the initial survey. Intention to use can be measured in various groups of programmatic inter- est: one group is all married women; others are women classified with unmet need and women who are not now using a method (all three measures are includ- ed in Appendix Table A.11). The percent intending to use varies for several rea- sons: in Brazil few married women in- tend to use because most already do so, whereas in Nigeria the desired family size is still large, and access to methods is poor. In Pakistan religious objections and husband opposition may help ex- plain why 33% of married women have unmet need but the percent intending to use is still low. The Philippines presents yet another combination of factors, in- cluding some religious ambivalence. All three countries lack vigorous program action in the rural sector. In Kenya the high proportions planning to use perhaps reflect a better supply system and great- er personal freedom by women to adopt a method. It must be remembered that many wom- en who say they intend to use will in fact not do so, at least not in the near future. A wide range of deterrents exists such as personal ambivalence, family opposi- tion, and weak programs that provide neither information nor physical access to a choice of methods. Nevertheless the intention to use suggests the presence of a market for contraception that supple- ments unmet need information. In sum- mary, close attention should be paid by managers and planners to levels and trends for both intention to use and un- met need. They are the best gauges of public interest in contraceptive use, whether supplied by the public or private sector. References Bernstein, Stan. Personal communica- tion, January 17, 2005. Bernstein, Stan. “A Proposal for Includ- ing a Measure of Unmet Need for Con- traception and Adolescent Fertility or Early Marriage Levels as Indicators of the Reproductive Health Component of Gender Equality.” Report of the Inter- agency and Expert Group Meeting on MDG Indicators, 27 September 2004, link (labelled “Proposal for a Reproduc- tive Health-related Gender Equality In- dicator,” at www.unstats.un.org/unsd/mi/ techgroup/subgroups/Gender.htm), ac- cessed January 17, 2005. Curtis, S.L., and C.F. Westoff, “Intention to Use Contraceptives and Subsequent Contraceptive Behavior in Morocco.” Studies in Family Planning 27(5:239- 250). 1996. Phai, Nguyen Van, John Knodel, Mai Van Cam, and Hoang Xuyen. “Fertility and Family Planning in Vietnam: Evi- dence from the 1994 Intercensal Demo- graphic Survey.” Studies in Family Plan- ning 27(1):1-17. 1996. Robey, Bryant, John Ross, and Indu Bhushan. “Meeting Unmet Need: New Strategies.” Population Reports. Series J, No. 43, September 1996. Ross, John, and Laura Heaton. “Intend- ed Contraceptive Use Among Women Without an Unmet Need.” International Family Planning Perspectives 23(4): 149-154. December 1997. Ross, John and William Winfrey. “Un- met Need for Contraception in the De- veloping World and the Former Soviet Union: An Updated Estimate.” Interna- tional Family Planning Perspectives 28(3):138-143. 2002. Sinding, Steven W., John A. Ross, and Allan G. Rosenfield. “Seeking common Ground: Unmet need and demographic goals.” International Family Planning Perspectives 20(1):23-27. March 1994. United Nations. Levels and Trends of Contraceptive Use as Assessed in 2002. New York: United Nations Population Division. Westoff, C.F., and A. Bankole. “Unmet Need: 1990-1994.” DHS Comparative Studies No. 16, Calverton, Maryland: Macro International. June, 1995. 56 Chapter 8 Goal No. 3: To Reach the Desired Fertility Level (See Appendix Table A.12) The desired family size has fallen over time in most countries, and has consis- tently stayed below actual fertility as it too has fallen. A reasonable goal for a national program is to hasten movement to the desired level, and this section trac- es the mutual changes in both actual and desired fertility. A useful measure of desired fertility is the total wanted fertility rate (TWFR). In each survey it is the same as the total fertility rate (TFR) except that any birth that exceeds the respondent’s ideal fam- ily size is considered unwanted. Remov- ing such births leaves the TWFR. Thus for each woman her wanted fertility is al- ways below or equal to her actual fertili- ty as of the survey. The comparison of the two measures ap- pears in Figure 8.6. The TFR is every- where above the TWFR. On average the difference is about one child between the number wanted and the number in fact, and in some countries it is a two-child difference. Over the developing world this amounts to a large body of unwant- ed childbearing as expressed by the women themselves, quite apart from any public policy regarding fertility. Trends: The goal of bringing actual fer- tility in line with wanted (“desired”) fer- tility can be quite elusive. Desired fertil- ity is a receding target, since it has been declining in most developing countries. It is common for the current TFR to have fallen below earlier desired levels, but for the current desired level to have fallen well below the current TFR. A special analysis was conducted for time trends in 40 countries with multi- ple DHS surveys. Each line in Figures 8.7a – 8.7e shows the joint change in the TFR and the TWFR between the earliest and latest DHS surveys. The five figures are scaled identically, to highlight the regional differences in general levels. (Legends show the dates of each initial survey.) When the wanted fertility rate falls fast- er than the total fertility rate the gap be- tween the two increases with time rath- er than diminishes. One way of captur- ing this is by the slopes in Figure 8.7a, since each line shows how rapidly the TFR fell in relation to the fall in the TWFR. If they fell exactly together the slope would be 1.0; if the TFR fell fast- er the slope would exceed one, and if the TWFR fell faster the slope would be less than one. For example, in Nigeria, from 1990 to 2003, the TFR fell from 6.0 to 5.7, but in the meantime the TWFR fell from 5.8 to 5.3. The 0.3 fall in fertility was exceed- ed by the 0.5 fall in wanted fertility, en- larging the gap between the two. The re- sulting slope was 0.60: the ratio between the two changes. Here are the average slopes by region: (no. of countries in parentheses) Sub-Saharan Africa 0.84 (20) Other Regions 1.98 (20) Asia 1.39 (6) Latin America 1.86 (8) Middle East/North Africa 2.76 (6) All countries 1.38 (40) In sub-Saharan Africa, desired fertility has been declining faster than actual fer- tility, outpacing it and increasing the gap between the two. The averages for it and “other regions” are 0.84 and 1.98 respec- tively, a very large difference that re- flects the failure of fertility to fall as rap- idly as desired in sub-Saharan Africa. This is also reflected in the high levels of unmet need in that region and the pro- portions of births that are ill-timed or not wanted at all. In the other regions the TFR has fallen at nearly double the pace of the TWFR (1.98 average slope above), so behavior there has been catching up with desires. Gaps still remain however: all lines in Figure 8.7a (for 40 countries) fall above the line of equality between the TWFR and the TFR. That is one demonstration of the way yet to go to achieve the goal of matching desired fertility to actual fertility. The disparity is greatest in sub- Saharan Africa, where the trends show the failure of fertility to fall as rapidly as desired fertility has (Figure 8.7c). Births not wanted: Another way to state the goal in this section is by the reduc- tion in births that are ill-timed or not wanted. Survey respondents are asked about their most recent birth (or current pregnancy) and the results are tabulated as in Appendix Table A.12. They are dis- played by region in Figures 8.8a and 8.8b. Figure 8.6. Relation of the Total Fertility Rate (TFR) to the Total Wanted Fertility Rate (TWFR), 140 National DHS Surveys - 1 2 3 4 5 6 7 8 - 1 2 3 4 5 6 7 8 Total Wanted Fertility Rate (TWFR) To ta l F er tili ty R at e (T FR ) Chapter 8 57 Figure 8.7a Trends in the Relation of the Total Fertility Rate (TFR) to the Total Wanted Fertility Rate (TWFR) (40 countries with multiple DHS Surveys) Figure 8.7b Asia Figure 8.7d Latin America Figure 8.7c Sub-Saharan Africa Figure 8.7e Middle East/North Africa 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 TF R TWFR 1 2 3 4 5 6 7 8 TF R Bangladesh 1993/94 India 1992/93 Indonesia 1987 Nepal 1996 Philippines 1993 Viet Nam 1997 1 2 3 4 5 6 7 8 TWFR Benin 1996 Burkina Faso 1998/99 Cameroon 1991 Côte d'Ivoire 1994 Eritrea 1995 Ghana 1988 Kenya 1989 Madagascar 1992 Malawi 1992 Mali 1987 Namibia 1992 Niger 1992 Nigeria 1990 Rwanda 1992 Senegal 1986 Tanzania 1992 Togo 1988 Uganda 1988 Zambia 1992 Zimbabwe 1988 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 TWFR TF R Bolivia 1989 Brazil 1986 Colombia 1986 Dominican Republic 1986 Guatemala 1987 Haiti 1994/95 Nicaragua 1997/98 Peru 1986 1 2 3 4 5 6 7 8 TF R 1 2 3 4 5 6 7 8 TWFR Egypt 1988 Jordan 1990 Morocco 1987 Turkey 1993 Yemen 1991/92 1 2 3 4 5 6 7 8 TWFR 2 3 4 5 6 7 8 TF R 1 58 Chapter 8 0 10 20 30 40 50 60 70 Ph ilip pin es Ne pa l 2 00 1 Ba ng lad es h 1 99 9/2 00 0 Ca m bo dia 20 00 Vie t N am 20 02 Pa kis tan 19 90 /91 Ind ia 19 98 /99 Ind on es ia 20 02 /20 03 Bo livi a 2 00 3 Pe ru 20 00 Ha iti 2 00 0 Co lom bia 20 00 Bra zil 19 96 Nic ar ag ua 20 01 Do m inic an Re pu blic 20 02 Gu ate m ala 19 98 /99 Pa ra gu ay 19 90 Ye m en 19 97 Mo ro cc o 19 92 Jo rda n 20 02 Tu rke y 1 99 8 Eg yp t 2 00 0 Arm en ia 20 00 Ka za kh sta n 19 99 Ky rgy z R ep ub lic 19 97 Uz be kis tan 19 96 Tu rkm en ista n 20 00 Pe rc en t o f B irt hs Figure 8.8a Percent of Births Ill-Timed or Not Wanted: Recent DHS Surveys in Four Regions Figure 8.8b Percent of Births Ill-Timed or Not Wanted: Recent DHS Surveys in Sub-Saharan Africa 0 10 20 30 40 50 60 70 So uth Af ric a 19 98 Na m ibia 20 00 Ke ny a 20 03 Ga bo n 20 00 To go 19 98 Za mb ia 20 01 /02 Ma law i 2 00 0 Gh an a 20 03 Ug an da 20 00 /01 Zim ba bw e 19 99 Eth iop ia 20 00 Rw an da 20 00 Se ne ga l 1 99 7 Cô te d'Iv oir e 19 98 /99 Ma ur ita nia 20 00 /01 Ca m er oo n 19 98 Eri tre a 20 02 Mo za m biq ue 19 97 CA R 1 99 4/9 5 Bu rki na Fa so 20 03 Be nin 20 01 Ta nz an ia 19 99 Ma li 2 00 1 Gu ine a 19 99 Ma da ga sca r 2 00 3/2 00 4 Nig er ia 20 03 Nig er 19 98 Ch ad 19 96 /97 Pe rc en t o f B irt hs Countries vary considerably within each region, and the regions differ in their central tendencies. Latin America has the highest percentages of ill-timed or unwanted births, over 40% in seven of the nine countries shown. In sub-Sahar- an Africa only 8 of 28 countries are above the 40% level, partly because de- sired fertility levels are higher there. Using a cutoff of 20%, altogether, 42 of the 55 countries fall above that level, in- dicating that one birth in five is ill-timed or not wanted. Percent wanting no more children. A further measure of time trends in desired fertility is increases in the percent of women who say that they want no more children. Nineteen countries have infor- mation on this at two or three points in time, from World Fertility Surveys of the late 1970s through multiple DHS sur- veys to the early 1990s (data pertain only to fecund women in union) (Bankole and Westoff, 1995). The de- gree and consistency of upward trends in Figure 8.9 are remarkable, and they oc- cur in both periods shown. Table 8.7 adds the mean values: the average in- crease over the 10-15 year period hap- pens to be in the range of 10-15 points, a substantial shift, especially considering that the increase probably included more younger women, at lower parities. The percent wanting no more children increases sharply by family size (not shown), but regions differ sharply in the gradient. In much of sub-Saharan Africa few women want to stop unless they have Chapter 8 59 three children, but in Latin America many wish to stop at one child, and one- half to two-thirds of those with two chil- dren wish to stop. Middle East/North Africa is between these extremes, and Asian countries vary the range. More recent information, for more coun- tries, is given in Appendix Table A.12. Information is not available for all coun- tries in all regions, but the averages are as follows: Mean Percent Wanting No No. of More Children Countries Asia 45.0 10 Latin America 47.9 13 Middle East/North Africa 48.3 7 Sub-Saharan Africa 26.4 31 Central Asia Republics 51.2 4 All countries 37.4 65 The results are quite uniform in four re- gions, with 45% to 51% of married women not wanting more children. Sub-Saharan Africa falls well below that at only 26%, since desired family sizes are lower there and a higher percent of the population is made up of younger women, who still want another child. Figure 8.9. Trends in Desire for No More Children Table 8.7. Trends in Desire for No More Children WFS DHS-I DHSII,III Increase Sub-Saharan Africa Cameroon 3.0 15.0 12.0 Ghana 12.0 22.0 34.0 22.0 Kenya 17.0 49.0 52.0 35.0 Nigeria 5.0 14.0 9.0 Rwanda 19.0 36.0 17.0 Senegal 7.0 17.0 19.0 12.0 Sudan 17.0 23.0 6.0 Zimbabwe 32.0 31.0 (1.0) Means 11.4 28.6 28.7 17.3 Middle East/North Africa Egypt 53.0 64.0 68.0 15.0 Jordan 42.0 54.0 12.0 Morocco 42.0 48.0 53.0 11.0 Turkey 57.0 72.0 15.0 Means 48.5 56.0 61.8 13.3 Asia Indonesia 39.0 50.0 52.0 13.0 Pakistan 43.0 39.0 (4.0) Philippines 54.0 64.0 10.0 Means 45.3 50.0 51.7 6.3 Latin America Colombia 61.0 70.0 66.0 5.0 Dominican Republic 52.0 64.0 66.0 14.0 Paraguay 32.0 45.0 13.0 Peru 61.0 73.0 75.0 14.0 Means 51.5 69.0 63.0 11.5 Overall Means 34.2 46.5 47.5 12.1 Source: Table 4.4 in Bankole and Westoff, 1995. 0 10 20 30 40 50 60 70 80 Late 1970s Mid-Period Early 1990s Pe rc en t W an tin g No M o re Cameroon Ghana Kenya Nigeria Rwanda Senegal Sudan Zimbabwe Egypt Jordan Morocco Turkey Indonesia Pakistan Philippines Colombia Dominican Republic Paraguay Peru 60 Chapter 8 Goal No. 4: To Attain the Replacement Fertility Level Replacement fertility is normally set at a total fertility rate of 2.1, slightly above 2.0 to allow for some mortality. By this standard a number of developing coun- tries have approached or surpassed the goal of replacement. In Asia these in- clude most prominently China as well as South Korea (and perhaps North Korea), Taiwan, Hong Kong, Singapore, Thai- land, Viet Nam, Sri Lanka, and at least Kerala State in India. In Latin America there are Cuba, Puerto Rico, Trinidad and Tobago, probably Brazil, and nu- merous small Caribbean populations. Others are Mauritius, Kazakhstan, and Tunisia. Many other developing countries have moved far along the path toward low fer- tility and smaller family sizes, enough to produce, for the developing world as a whole, a 79% decline toward replace- ment over the past 35 years. Table 8.8 shows the United Nations TFR estimates for 1960-1965 and 2000-2005 (regions according to UN definitions). All regions began at traditionally high fertility lev- els, and all fell to levels that reflect tru- ly historic changes in marriage and re- productive behavior. East Asia, with China, has fallen below replacement, and Southeastern Asia and Latin Ameri- ca have fallen 89% of the way. The North Africa and Western Asia regions are the closest to the “Middle East/North Africa” region used elsewhere in this re- port; they fell by 78% and 68% respec- tively of the distance to replacement. Sub-Saharan Africa has moved only 30% of the way. Finally, a group of 48 countries (33 in Africa) identified by the UN as “least developed” (second row of table) have fallen only a third of the way. It is important to bear in mind that the total fertility rate is only one measure of fertility behavior. Unlike the crude rate or general fertility rate, it gives equal weight to every age group, and it is sometimes sensitive to short-term fluctuations, for example in age at first birth. It does not reflect population momentum: popula- tions will continue to grow for some de- cades after replacement is reached. How- ever the TFR has its own value, and it is a working proxy for movement toward the two-child family. What of the future? Predictions are haz- ardous, but the right-most column of Ta- ble 8.8 gives the UN’s projected dates for reaching replacement. Another approach to future develop- ments concerns one determinant of the TFR. Actions to hasten the fertility de- cline toward replacement may consider that the four most immediate determi- nants are contraceptive practice, abor- tion use, breastfeeding, and cohabita- tion. National policies have been direct- ed variously toward all of these, and all four have been important in different degrees in producing fertility declines. However past declines have come pre- dominantly from increased contracep- tive use, and that is examined next. The Gap in Contraceptive Prevalence Across many countries, a total fertility rate of 2.1 roughly represents the level at which the population size will eventual- ly stabilize. A total fertility rate of 2.1 corresponds to contraceptive practice by about 75% of couples. Past and future trends for prevalence are reviewed in earlier chapters; here we explore the dis- tance that countries have yet to go to reach the 75% level, taken for conve- nience as the gap to the replacement lev- el. Basically each country’s gap is the difference between its present number of contraceptive users and the number that would match a 75% prevalence level. In 2005 to achieve replacement level fer- tility would require about 800 million users. Currently there are about 630 mil- lion, so the gap is 170 million users. Under the medium projections of the United Nations Population Division, this gap would diminish slightly to 164 mil- lion by 2010, 161 million by 2015, and 155 million by 2025. The UN medium projection implies an annual growth rate in the number of family planning users of only 1.5% between 2005 and 2015, leaving a gap. To improve on this to eliminate the gap and achieve re- placement level fertility by 2015 would However in all regions there are similar subgroups: young women who still want one or more children; the very old, who want no more and are at low risk of con- ception; and of most programmatic con- cern, a large intermediate group that is liable to pregnancy and does not want it. In summary. The national program, hav- ing a goal to hasten the movement to the desired fertility level, can expect it to re- main out of reach; it may well fall as fast or faster than the actual fertility level does. That however is a favorable devel- opment, and it demonstrates the continu- ing presence of a public demand for con- traception. The various measures above give a common picture: there is a great deal of unwanted and ill-timed fertility across the developing world. To that must be added the large numbers of aborted pregnancies (Appendix Table A.16). Actual fertility still exceeds de- sired fertility in virtually every country. To contribute to the closing of each cur- rent gap the points of action are much the same as for addressing unmet need. They involve the essential features of a range of reliable contraceptive methods, well deployed to the mass of the popula- tion, accompanied by good service de- livery and full public information. References Bankole, Akinrinola and Charles F. Westoff, Childbearing Attitudes and In- tentions. DHS Comparative Studies No. 17. Calverton, Maryland: Macro Interna- tional Inc. 1995. Westoff, Charles F. Reproductive Prefer- ences: A Comparative View. DHS Com- parative Studies No. 3. Columbia, Mary- land: Institute for Resource Develop- ment. 1991. Chapter 8 61 Table 8.8. Total Fertility Rates: Percentage Declines Toward Replacement Fertility Extrapolateda UN TFR TFR TFR % Decline Date to Projected Date 1960-1965 1995-2000 Decline to TFR of 2.1 Reach 2.1 to Reach 2.1 Developing World 6.01 3.00 3.01 77 2008b 2035 Least Developed Countries 6.59 5.05 1.54 34 2065b 2045 Sub-Saharan Africa 6.69 5.48 1.21 26 2095b 2045 North Africa 7.08 3.58 3.50 70 2012b 2035 Western Asia 6.18 3.77 2.41 59 2022b 2045 Eastern Asia 5.19 1.77 3.42 111 NA NA South-central Asia 6.01 3.36 2.65 68 2014b 2035 South-eastern Asia 5.90 2.69 3.21 84 2004b 2018 Latin America 5.97 2.70 3.27 84 2004b 2035 Source: United Nations, 1998. aExtrapolation of trend from 1960-65 to 1995-2000. bEarlier dates result if the pace of decline is extrapolated from a more recent period. require an annual growth rate in family planning users of 3.6%, more than dou- ble the above rate. To take more time and eliminate the gap by 2020 would re- quire an annual growth rate for users of 2.6%. The additional contraceptive users re- quired to reach 75% prevalence for the developing world as a whole are highly concentrated in a few countries (Figure 8.10). India alone has nearly a third (31%) of the global total. It plus four others (Nigeria, Pakistan, Ethiopia, and Indonesia) account for half of the total. Altogether 12 countries account for two- thirds of the total, spreading the other third among 94 countries (Appendix Ta- ble A.13). Within each region (Figures 8.11a- 8.11e) the pattern of concentration of the gap is the same: within Asia, India has the bulk of the total, and in three other regions the top five countries contain half to two-thirds of the total (Table 8.9). Two factors create these extreme distri- butions: population size, and low preva- lence of use. A large country, with few users, requires a very large number of additional users to reach 75% preva- lence. India is large and has only an in- termediate level of prevalence; Pakistan, Nigeria, and Ethiopia are also large and have quite low prevalence. (These calculations use numbers of women 15-49 in union, and all figures are projections for the year 2005. Num- bers of women and proportions married are closely estimated by the United Na- tions, and prevalence of use comes from past surveys and from the projections ex- plained in Chapter 3 and in the Appen- dix.) Table 8.9. Concentration of Users Needed to Reach 75% Prevalence: Top Five Countries Within the Developing World and Within Each Region Percent of Percent of Percent of Country Total Gap Country Total Gap Country Total Gap Developing World Latin America Sub-Saharan Africa India 30.9 Mexico 20.1 Nigeria 22.3 Nigeria 7.3 Guatemala 12.8 Ethiopia 12.3 Pakistan 7.0 Venezuela 12.4 Congo, D.R. 6.3 Ethiopia 4.0 Argentina 11.8 Tanzania 5.1 Indonesia 3.6 Haiti 10.6 Mozambique 4.2 Total 52.8 Total 67.7 Total 50.2 Asia Middle East/North Africa Central Asia Republics India 57.3 Sudan 20.7 Tajikistan 34.2 Pakistan 13.0 Iraq 14.0 Uzbekistan 32.8 Indonesia 6.7 Egypt 11.9 Kazakhstan 15.7 Bangladesh 6.4 Yemen 11.1 Kyrgyzstan 10.0 Philippines 3.8 Saudi Arabia 10.0 Turkmenistan 7.3 Total 87.2 Total 67.7 Total 100.0 India 31% Nigeria 7% Pakistan 7%Ethiopia 4%Indonesia 4% Bangladesh 3% Congo, D.R. 2% Philippines 2% Sudan 2% Afghanistan 2% Myanmar 2% Tanzania 2% 94 Others 32% Figure 8.10. The “Gap”: Distribution of Additional Users Needed to Reach 75% Contraceptive Prevalence in the Developing World 62 Chapter 8 Figure 8.11. Percent Distribution of Gap to 75% Prevalence Figure 8.11a Figure 8.11b Figure 8.11c Me xic o Gu ate ma la Ve ne zu ela Arg en tin a Ha iti Bo livi a Pe ru Ch ile Ec ua do r Pa ra gu ay El Sa lva do r Ho nd ur as Pa na m a Tri nid ad an d T ob ag o Do mi nic an Re pu blic Nic ar ag ua Ur ug ua y Ja m aic a Cu ba Gu ya na 0 5 10 15 20 25 0 5 10 15 20 25 Su da n Ira q Eg ypt Ye m en Sa ud i A ra bia Tu rke y Sy ria Mo roc co Alg eri a Tu nis ia Un ited Ar ab Em ira tes Om an Lib ya Jor da n Le ba no n Ku wa it ASIA LATIN AMERICA MIDDLE EAST AND NORTH AFRICA 0 10 20 30 40 50 60 Ind ia Pa kis tan Ind on es ia Ba ng lad es h Ph ilip pin es Afg ha nis tan My an m ar Ne pa l Ca m bo dia Ma lay sia Ko re a, DP R Pa pu a Ne w Gu ine a La os Th aila nd Sri La nk a Ira n Bh uta n Chapter 8 63 Nig eri a Eth iop ia Co ng o, D. R. Ta nz an ia Mo za m biq ue Ug an da Ke ny a Gh an a Ma li Bu rki na Fa so Cô te d'Iv oir e Ma da ga sc ar Ca m er oo n An go la Nig er So m alia Gu ine a Se ne ga l Ch ad So uth Afr ica Ma law i Be nin Bu ru nd i Rw an da Za m bia Sie rra Le on e Eri tre a Zim ba bw e To go Lib eri a Ce ntr al Afr ica n Re p. Ma ur ita nia Co ng o Ga mb ia Gu ine a- Bis sa u Le so tho Ga bo n Sw azi lan d Bo tsw an a Na m ibia Ma ur itiu s 0 5 10 15 20 25 0 5 10 15 20 25 30 35 Tajikistan Uzbekistan Kazakhstan Kyrgyzstan Turkmenistan Figure 8.11d Figure 8.11e SUB-SAHARAN AFRICA CENTRAL ASIAN REPUBLICS Figure 8.11. Percent Distribution of Gap to 75% Prevalence (Cont.) 64 Chapter 8 The Demographic Dividend (Appendix Tables A.25a and A.25b) This section concerns potential benefits during the move toward replacement fer- tility, as the gap described (in the pre- ceding section) is closed. During the movement to higher contra- ceptive prevalence and lower fertility there is a window during which a demo- graphic bonus, or dividend, is available. Briefly, a falling fertility rate changes the age distribution, reducing the num- bers of young dependents. Then the pop- ulation of working age has a lightened burden and can devote more resources to better health, education, and job training for the children born in smaller families. In addition, resources are freed for the country’s economic growth (see Bloom, Canning, and Sevilla, 2003; also Bird- sall, Kelley, and Sinding, 2001). The changing age distribution is con- trasted in Figure 8.12 for the two re- gions of East Asia and sub-Saharan Afri- ca. Because fertility fell early in East Asia (especially in China, Japan, South Korea, and Taiwan), the working age population (taken as 15-64) rose rapidly as a percentage of the total, to over two- thirds of the total. It is peaking about now and will start a decline as the popu- lation ages and the elderly become more numerous. In the meantime the window exists during which resources are re- leased for the benefit of both the family and the nation. In sub-Saharan Africa this process is go- ing on much more slowly than in East Asia: the working ages have constituted only about half of the total and are only starting to increase. In the future the per- centage will rise as shown in the figure if the UN projections for fertility decline prove true. (Appendix Tables A.25a and A.25b give the percentage of working age adults for 116 countries from 1950 to 2050.) The various regions are compared in Figure 8.13. Latin America started as low as sub-Saharan Africa (1960) but changed rapidly and rose to nearly match Asia. Asia as a whole (including East Asia and also India, Pakistan, Bang- ladesh, Indonesia, and other large coun- tries) also started low but rose sharply and is projected by 2020 to reach 63% of the population in the working ages. The three developed regions all peaked around 2000 and then began the declines shown. Europe falls to the lowest level, about 53%, due to its aging populations, nearly as low as Latin America and sub- Saharan Africa were in 1960. Over time, the many young dependents are exchanged for the many elderly de- pendents. In between is the window, dur- ing which the demographic bonus is available. The window is larger to the extent that fertility does in fact decline, and this remains a leading issue through- out much of South Asia and sub-Saharan Africa. Seizing the Window The resources that are released during the window must be put to good use or the potential will be lost. Policies to ex- ploit these opportunities are critical. Examples follow (see Bloom, Canning, and Sevilla for details). ➤ Labor Force. • Greater investments in education and job training • Measures for job creation to absorb the large numbers of teenagers coming of age ➤ Health: a healthier population is de- sirable in itself and is more produc- tive economically. • Improved health for the labor force • Improved medical care for infants and children • Improved reproductive health care for women ➤ Reduction of unwanted pregnancies, to avoid pregnancy wastage, maternal morbidity, and loss of female produc- tivity and family nurturing. Full pro- vision of contraceptive information and services. ➤ Economic Growth. • Open trade policies and open econ- omies; reduction of corruption • Generation of capital through sav- ings by persons, businesses, gov- ernment • Encouragement of foreign invest- ment and appropriate donor assis- tance. The country that neglects such measures will be left at the same levels of illitera- cy, poor health, low job skills, and un- employment as before, and with a con- siderably enlarged population. At the other extreme, the country that estab- lishes favorable family planning poli- cies, wedded to enlightened policies dur- ing the window to improve health, edu- cation, job training, investment policies, and an open economy, will enter the next decade in a much improved position. References Birdsall, Nancy, Allen Kelley, and Steven Sinding, eds. Population Mat- ters: Demographic Change, Economic Growth, and Poverty in the Developing World. Oxford: Oxford University Press, 2001. Bloom, D., D. Canning, and J. Sevilla. “The Demographic Dividend: A New Perspective on the Economic Conse- quences of Population Change.” Popula- tion Matters Series. Santa Monica, Cal- ifornia: Rand. 2003. Countdown 2015: ICPD At Ten: Where Are We Now? Family Care International, the International Planned Parenthood Federation, and Population Action Inter- national. 2004. Chapter 8 65 45 50 55 60 65 70 19 50 19 55 19 60 19 65 19 70 19 75 19 80 19 85 19 90 19 95 20 00 20 05 20 10 20 15 20 20 20 25 20 30 20 35 20 40 20 45 20 50 Pe rc e n t o f T ot al Po pu la tio n East Asia Sub-Saharan Africa 45 50 55 60 65 1960 1980 2000 2020 2040 Pe rc en t o f T ot al P op ul at io n Africa Asia Latin America Europe North America Oceania Figure 8.12. Working Age Population as a Percentage of Total Population Figure 8.13. Trends for Working Age Populations in Six Regions 66 Chapter 8 Goal No. 5: To Satisfy the Millennium Development Goal and the Cairo Programme of Action (See Appendix Tables A.15 to A.23) The Millennium Development Goals (MDG) and the Cairo Programme of Ac- tion (CPA) have much in common. In fact neither set of goals can be achieved unless the other set is also achieved. The accompanying BOX # 1 gives the word- ing of each Millennium Goal with the comparable wording of a Cairo goal alongside, and the similarities are nota- ble. At the same time however, the MDGs omit the principal CPA goal, universal access to sexual and reproductive health information and services. Yet that goal is fundamental to the MDGs, as explained in BOX # 2. Each MDG either absolute- ly requires marked progress with repro- ductive health or would be substantially advanced by it. Here we focus first on three selected fea- tures of joint importance to both kinds of goals: • The dependency ratio • Primary school age children • Population density Next we provide a summary taken based on previous chapters pertaining to three formal Millennium Goals: • To reduce child mortality • To improve maternal health • To reduce HIV/AIDS The dependency ratio if improved lifts the burdens that slow progress on every goal. When fertility rates fall at a faster pace, the ratio of dependent children, with all their needs, is eased in relation to the numbers of working age popula- tion. The policy key is then to pay atten- tion to full education and services for contraceptive use and to the postpone- ment of marriage or cohabitation. Primary school age children have low enrollment rates in many countries, made worse by the rapid increases in their numbers. Projections of alternative fertility rates show the advantages to both the quantity and quality of educa- tion when the numbers of new entries to primary school stabilize. That releases resources to raise enrollment rates and to improve teacher training and other ele- ments of quality. Population density will rise in cities, where most population growth will oc- cur (due partly to rural in-migration), but there are serious rural problems also. In Ethiopia for example, the available ara- ble land per rural inhabitant will decline by one-third by 2015, limiting produc- tivity increases, harming the environ- ment, and reducing land fertility. Great- er population density is seldom helpful under current conditions in the develop- ing countries of intermediate and large populations. Slower population growth in general slows rural density increases. Millennium Goal to Reduce Child Mortality: Reduce by two-thirds the mortality rate among children under five Child mortality will fall from direct pub- lic health measures and from socioeco- nomic gains. In addition it will fall con- siderably faster if births are well-spaced and occur only between ages 18 and 35. That in turn requires ready access by the whole population, including youth, to contraceptive education and services. As BOX # 2 notes, mortality is elevated when births are unwanted. Moreover the capacity of the public health system to provide pregnancy care and medical ser- vices to infants is compromised when the numbers are excessive. The goal to reduce child mortality has two rather separate features: first, that contracep- tive use reduces the sheer numbers of births, and therefore of deaths, and sec- ond, that there is a helpful selectivity since well-spaced births to women of the right ages carry lower risks. This Millen- nium Goal will be significantly ad- vanced through attention to childbearing patterns. Child mortality is increased when a woman has more than four births, when births occur at intervals of less than two years, and when the mother is under the age of 18 or older than 35. The use of family planning tends to reduce the total number of births per woman and concen- trate them within the safest age range. The relationship between contraceptive prevalence and the proportion of births with any of these risk factors can be de- termined from the many national popu- lation and fertility surveys that have been conducted over the past 30 years. This same data set provides information on the relationship between under-five mortality and the proportion of births with any risk factor. According to these relationships the influence of contracep- tive use on under-five mortality is signif- icant. In sub-Saharan Africa, the under- five mortality rate in 2000 was about 175 deaths per 1000 live births. This rate would be reduced by 25% if the level of contraception use increased from 20% in 2000 to 30% in 2015 as implied by the medium projection of the United Na- tions Population Division. Thus in- creased use of family planning alone could achieve more than one-third of the reduction required to achieve this Mil- lennium Development Goal. Chapter 6 provides supporting informa- tion on these points, and Appendix Ta- bles A.19 through A.21 give mortality rates and risk information by type of birth. Millennium Goal to Improve Maternal Health: Reduce by three-quarters the ratio of women dying in childbirth Maternal deaths have been reduced his- torically primarily by reducing the num- ber of pregnancies. There is little evi- dence that the risks of death per preg- nancy have fallen in the developing world, but the absolute numbers are far less than they would have been if the overall total fertility rate had not fallen from about 6 in 1960 to about 3 current- ly. The fertility declines have been vital, as they have been with other goals. Maternal mortality falls into two parts: the portion due to unsafe abortions and the portion due to births. Measures to address these overlap, but post-abortion care, with family planning as an integral Chapter 8 67 part, is fundamental to avoiding repeat abortions. The parallel for births is the postpartum provision of contraceptive options. In both cases, unwanted repeat events can be avoided. Chapter 5 provides supporting informa- tion and Appendix Tables A.15 through A.18 give mortality rates and risk infor- mation by type of birth. Program effort makes a difference in lowering maternal mortality ratios. Pro- gram effort was measured in 1999 and 2002 in the MNPI studies (above) in some 55 countries, and an improvement from 40% of maximum effort to 75% of maximum effort was associated with a decline in the average MMR from about 850 to about 250. That is a 70% decline, quite close to the Millennium objective of a three-fourths fall. While these are cross-sectional associations and other forces are also at work, the MNPI mea- sures such key determinants as access to emergency care, the capabilities of facil- ities, the availability of family planning postpartum and postabortion, and the support gained from resources, training, and policies. Countries with those fea- tures are likely to experience consider- ably lower mortality ratios than coun- tries without them. Millennium Goal to Reduce HIV/ AIDS, Malaria, Tuberculosis, and Other Diseases: Halt and begin to reverse the spread of HIV/AIDS and the incidence of malar- ia and other major diseases The AIDS pandemic has stirred the world to action, but the pandemic con- tinues to win. The needed measures to combat it are now generally known, but some governments are still in denial, doing little, and resources are not suffi- cient. On the other hand, a determined government, with an open public com- mitment, sufficient resources, and wise strategies, can do much to limit new HIV infections, as demonstrated so far in a small number of developing countries. Without those local conditions in place, there are limits on what donor contribu- tions and technical expertise can accom- plish. All such efforts help, but major reversals of the epidemic will require a sea change in government commitments and programs. A close relation exists, as implied in the Goal, between AIDS and other diseases, especially the opportunistic ones such as tuberculosis, in addition to the debilitat- ing effects of AIDS that make recovery from malaria and other diseases more difficult. Treatment measures for AIDS cases provide some defense against these, but prevention of new HIV infec- tions is more basic. Interactions between the AIDS goal and other goals are notable, in both direc- tions. Unwanted childbearing is espe- cially unfortunate when the parents are debilitated by AIDS. The numbers of or- phans would be fewer if parents with AIDS had been able to control their child bearing. The capacities of public health systems to provide infant and child care have been weakened by the loss of medical personnel due to AIDS illnesses and deaths. In the other direc- tion, programs to make birth spacing and limiting more accessible will help allevi- ate all of these burdens due to AIDS. Direct actions to alleviate the AIDS problem will simultaneously advance the other goals. Chapter 7 provides supporting informa- tion, and Appendix Tables A.22 and A.23a and A.23b cover the detailed fea- tures, with projections. Summary Interactions are present throughout the MDG and CPA objectives, and together they advance the overarching goal of re- ducing extreme poverty. Direct measures must be applied to each goal separately, but they help each other and the syner- gisms among them are vital. A “turnkey” activity that does not appear as a Goal but is fundamental to easing the chal- lenges to all is the reduction of unwant- ed fertility. It applies to each goal: it cuts into the numbers in poverty and the numbers who are hungry, it relieves pressures on the schools to advance pri- mary education, it reduces the numbers of child deaths and maternal deaths, it works to reduce AIDS orphans and de- bilitating pregnancies among AIDS car- riers, it eases pressures upon the environ- ment, and it encourages donor commit- ments to ongoing programs. The re- quired investments to address unwanted childbearing give excellent value for the women and families involved, as well as for the countries. 68 Chapter 8 1. MDG: Eradicate extreme poverty and hunger. CPA: Aim at achieving poverty eradication. 2. MDG: Achieve universal primary education. CPA: Achieve universal access to quality education. 3. MDG: Promote gender equality and empower women. CPA: Countries should act to empower women and … eliminate inequalities between men and women…. 4. MDG: Reduce child mortality. CPA: Promote child health and survival. 5. MDG: Improve maternal health. CPA: Achieve a rapid and substantial reduction in maternal morbidity and mortality…including deaths and morbidity from unsafe abortion. 6. MDG: Combat HIV/AIDS, tuberculosis, malaria, and other diseases. CPA: Reduce the spread of HIV infection and minimize its impact. 7. MDG: Ensure environmental sustainability. CPA: Reduce unsustainable consumption and production patterns as well as negative impacts of demographic factors on the environment…. 8. MDG: Develop a global partnership for development. CPA: Urge that the international community adopt favorable macro economic policies for promoting sustained economic growth…. Goals 4, 5, and 6 are treated in detail in the preceding chapters, with support- ing data in the Appendices. BOX No. 1 Similarity of the Millennium Development Goals (MDG) and the Cairo Programme of Action (CPA) Chapter 8 69 Goal 1: Eradicate extreme poverty and hunger • Voluntary family planning can help people to have as many or as few children as they want and to decide when they will have them. • Fertility reduction opens the “demographic window,” an opportunity for accelerated social and economic development. • Large families dilute the assets of poorer households. Unwanted births deepen household poverty. • Smaller families allow more investment in each child’s health and education. • Improved data on people and their needs will advance policy development and the targeting of development programmes—and improve accountabil- ity. • Migration within and between countries can bring benefits and pose challenges in both sending and receiving areas. Policies can help maximize the gains to poor communities and individuals. • Better child spacing reduces competition for food within the household and improves children’s nutrition. Goal 2: Achieve universal primary education • Attempts to achieve universal education have left out poor children. • Large numbers of children in poor families mean that some children get no education. For others, education may be delayed, interrupted or shortened. • In poor families, girls are more likely than boys to be deprived of education. • Educational continuation depends on avoidance of unwanted pregnancies. Early initiation of sexual activity increases the risk of school dropout. In sub- Saharan Africa between 8 and 25 per cent of dropout rates are the result of pregnancy. • Early marriage interrupts girls’ schooling. Goal 3: Promote gender equality and empower women • Progress towards gender equality starts with the common indicators of literacy and education. It continues with health care, including personal, voluntary control over fertility. It is important that families and societies accept women’s wider social participation, and remove obstacles to it. • Girls and women need environments where they are safe from gender- based violence, including on the way to, from and in school. Goal 4: Reduce child mortality • Infant and child mortality are highest for the youngest mothers and after closely spaced births. • High fertility reduces the provision of health care to children. • Unwanted children are more likely to die than wanted ones. • A mother’s death increases the risk that her children will die. Goal 5: Improve maternal health • Care in pregnancy, during and after childbirth, and emergency obstetric care save women’s lives. • Pregnancy is riskiest earliest in life. Over 100,000 women are at risk of obstetric fistula each year, and over 2 million women have already been injured and stigmatized. • A woman’s lifetime risk of maternal death and illness depends on the number and safety of her pregnancies. • Family planning saves women’s lives. It reduces unwanted pregnancy, unsafe abortion and maternal death. Women’s empowerment will enable them to address the social conditions that endanger their health and lives. Goal 6: Combat HIV/AIDS, tuberculosis, malaria and other diseases • Half of new HIV infections are among young people. Preventing infection means enabling young people to protect themselves from sexually transmitted diseases. This includes teaching abstinence outside marriage, fidelity within it and responsible behaviour at all times, including the responsible use of condoms. • Male and female condoms must be available as needed. Poor countries need systems to guarantee an adequate supply of reproductive health commodities, and support in establishing and supplying the system. • Integrated reproductive health programmes that serve a variety of needs through the life cycle will encourage health service use and provide additional opportunities to address health needs holistically. Changing age structures will require long-term adjustments in health systems. • The pandemic has serious implications for the attainment of the other goals, particularly 1-5. Goal 7: Ensure environmental sustainability • Balancing resource use and ecological requirements will depend critically on population growth, location and movements, on patterns of resource consumption, and management of waste. • Rapid growth of poor rural populations puts enormous stress on local environments. Poor people need technologies to mediate their demands on resources. They also need better education and health services, including reproductive health, to improve well-being and bring down fertility. Appropriate policies will reduce urban migration and promote sustainable rural population growth. • The sustainable improvement of the lives of slum and shanty dwellers will depend on policies to address high urban growth rates, the result of natural increase and migration. Goal 8: Develop a global partnership for development • Population and reproductive health programmes have lagged in the least- developed countries, with their high levels of mortality and unwanted fertility. They will benefit most from higher international assistance and debt forgiveness, and domestic resources for health and education—and their effective use. They need affordable prices for essential drugs for treating HIV/AIDS, malaria and tuberculosis, and a secure supply of contraceptives. • Between 2000 and 2015 nearly 1.5 billion young men and women will join the 20-24 age group. They, and hundreds of millions of teenagers, will be looking for work. If they have jobs they will drive economic growth; if not they will fuel political instability. BOX No. 2 Reproductive Health, Family Planning and Population Promote Millennium Development Goals Appendix A A.1 AAAAAppendixppendixppendixppendixppendix AAAAA SUPPORTING TABLES Sources for Supporting Tables A.1. Contraceptive Use by Method Among Currently Married Women, Surveys 1980 to Present, Developing Countries. Demographic and Health Surveys (DHS) conducted in collabora- tion with ORC Macro; Reproductive Health Surveys conducted with the as- sistance of the U.S. Centers for Disease Control and Prevention; Arab-Gulf sur- veys; UNICEF Multiple Indicator Clus- ter Surveys; independent national sur- veys. See also source notes immediately following Appendix Table A.1. A.2. Source of Supply for Modern Contraception Methods. Recent DHS Surveys. A.3. Population, Number of All Wom- en (15-49), and Married Women (MWRA) (15-49), for 2005, and Percent Using Contraception (latest survey), and No. of Users. Number of women aged 15-49 is from United Nations, World Population Prospects, The 2002 Revision, Vol. 1, 2003. Percent married is from United Nations, Levels and Trends of Contraceptive Use as Assessed in 1994. New York: United Nations, 1996, with updates from recent national sur- veys. The percent using contraception is from the Appendix Table A.5 sources. Number of users of contraception is from Appendix Table A.6. A.4. Number of Married Women (MWRA) (15-49) (000s) for Four Dates, and Percent Currently Married. See above for Appendix Table A.3. A.5. Projected Contraceptive Preva- lence by Method Among Married Women (MWRA). Based on projection methods described in Chapter 3 and in Appendix B. A.6. Projected Number of Contracep- tive Users by Method Among All Wom- en (Aged 15-49) (000s). Based on pro- jection methods described in Chapter 3 and in Appendix B. A.7. Projected Contraceptive Com- modities by Method Among All Women (Aged 15-49) (000s). Based on projec- tion methods described in Chapter 3 and in Appendix B. A.8. Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s). Based on projection methods de- scribed in Chapter 3 and in Appendix B. A.9. Unmet Need, Percent Using, and Percent of Demand Satisfied. Recent DHS Surveys. A.10. Intention to Use Contraception. Recent DHS Surveys. A.11. Relationship of Unmet Need and Intention to Use Contraception. Special tabulations provided courtesy of ORC Macro from DHS Surveys. A.12. Ideal Number of Children, Total Fertility and Wanted Fertility Rates, and Fertility Planning Status. Recent DHS Surveys. A.13. Percent Distribution of the Gap to 75% Contraceptive Prevalence, by Region. Year 2005 Estimates. Calcula- tions from above tables for women, per- cent married, and number of users; UN Contraceptive Use 2003 Wall Chart; DHS and other recent national surveys. A.14. 1999 Program Effort Scores: Total and Four Dimension Scores as Percent of Maximum. From John Ross and John Stover, “The Family Planning Program Effort Index: 1999 Cycle,” In- ternational Family Planning Perspec- tives 27(3):119-129. September 2001. A.15. Maternal Mortality Ratio (MMR), Number of Deaths Annually, Lifetime Risk, and Percent of Female Deaths (ages 15-49) That Are Pregnancy Re- lated. From WHO and UNICEF. “Revised 1990 Estimates of Maternal Mortality: A New Approach by WHO and UNICEF.” Geneva: WHO and UNICEF. 1996. Also: Carla AbouZahr and Tessa Wardlaw, “Maternal Mortality in 2000: Estimates Developed by WHO, UNICEF, and UNFPA.” Geneva: WHO. 2004. Data base on-line accessed on Dec. 28, 2004: Millennium Goals; and WHO, UNICEF, and UNFPA websites. A.16. Number of Abortions, Abortion Rate, and Abortion Ratio (1999 Esti- mates). From Henshaw, S.K., S. Singh, and T. Haas. “The Incidence of Abortion Worldwide.” International Family Plan- ning Perspectives, Vol. 25, pages S30- S37. Supplement, 1999; and WHO, “Global and Regional Estimates of Inci- dence of Mortality due to Unsafe Abor- tion with a Listing of Available Country Data,” Table 2. Maternal and Newborn Health: Unsafe Abortion. Third Edition. Geneva: WHO. 1998. See also the Fourth Edition. A.17. Percentage Receiving Antenatal Care, Tetanus Injections, and Delivery Care. From UNICEF: State of the World’s Children 2005; The World Health Report 2005. Geneva: WHO. 2005. A.18. Maternal and Neonatal Pro- gram Effort Index (MNPI), 1999 and 2002 Surveys: Country Scores as Per- cent of Maximum. From surveys con- ducted by the Futures Group Interna- tional in 1999 and 2002. For the 1999 survey: J.A. Ross, O. Campbell, and R. Bulatao, “The Maternal and Neonatal Programme Effort Index (MNPI),” Tropi- cal Medicine and International Health 6(10):787-798. October 2001. For the 2002 survey: J.A. Ross and J.E. Begala, “Measures of Strength for Maternal health Programs in 55 Developing Countries: the MNPI Study.” Maternal and Child Health Journal, 9(1) 59-70. March 2005. A.2 Appendix A A.19. Number of Births, Infant and Child Mortality Rates, and Number of Deaths, 2003 Estimates. UNICEF: State of the World’s Children 2005; The World Health Report 2005. Geneva: World Health Organization. 2005. Unit- ed Nations, World Population Pros- pects, The 2002 Revision, Vol. 1, 2003. A.20. Births According to Risk Catego- ry. Recent DHS surveys. A.21. Immunizations, ARI, and Re-hy- dration. UNICEF: State of the World’s Children 2005; The World Health Re- port 2005. Geneva: World Health Orga- nization. 2005. A.22. Estimated Number of People Living with HIV/AIDS, Estimated Number of Orphans (AIDS and non- AIDS), and Estimated AIDS Deaths, at the End of 2003. UNAIDS 2004. Report on the Global AIDS Epidemic: 4th Glo- bal Report. Geneva: UNAIDS. Available at http://www.unaids.org; UNAIDS, UNICEF, USAID. 2004. Children on the Brink 2004: A Joint Report of New Or- phan Estimates and a Framework for Action. New York: UNICEF. Available at http://www.unicef.org A.23. Condom Needs: 2005-2010 Pro- jections. Calculations by the Futures Group International. A.24. Comparative Information on Youth. DHS surveys; United Nations, World Population Prospects, The 2002 Revision, Vol. 1, 2003; UNICEF: State of the World’s Children 2005. A.25. Demographic Dividend: Percent of the Population Aged 15-59, from 1950 through 2000 and 2005 through 2050. United Nations, World Popula- tion Prospects, The 2002 Revision, Vol. 1, 2003. Appendix A A.3 Table A.1. Contraceptive Use by Method Among Currently Married Women, All Surveys 1980 to Present, Developing Countries Sterilization Modern Injectable Any Country Date Total Prev. Methods Female Male Pill Implant IUD Condom Vaginals Trad.* Asia Afghanistan 2003 10.3 - - - - - - - - - Bangladesh 1981 18.6 11.0 4.0 1.0 3.5 0.4 0.4 2.0 0.3 7.6 Bangladesh 1983 19.1 14.0 6.2 1.2 3.3 0.2 1.0 2.0 0.3 5.4 Bangladesh 1985 25.2 18.3 7.8 2.0 5.1 0.5 1.4 2.0 0.2 6.9 Bangladesh 1989 30.8 23.2 8.5 1.0 9.6 0.6 1.4 2.0 0.1 7.6 Bangladesh 1991 39.9 31.2 9.1 1.0 13.9 2.6 1.8 3.0 - 8.7 Bangladesh 1993 44.6 36.2 8.1 1.0 17.4 4.5 2.2 3.0 - 8.4 Bangladesh 1996 49.2 41.5 7.6 1.0 20.8 6.2 1.8 4.0 - 7.7 Bangladesh 1999/00 53.8 43.4 6.7 0.5 23.0 7.7 1.2 4.3 - 10.3 Bhutan 1994 18.8 18.8 3.1 8.0 2.4 4.0 1.0 0.3 - - Cambodia 1995 12.5 6.8 1.3 - 1.3 2.3 1.6 - - 5.7 Cambodia 2000 23.8 18.5 1.5 - 7.2 7.4 1.3 0.9 0.2 5.4 China 1982 70.6 67.8 17.9 7.0 6.0 - 35.4 1.0 - 2.8 China 1985 74.0 73.0 27.0 10.0 5.0 - 29.0 2.0 - 1.0 China 1988 72.1 71.2 27.6 8.0 3.4 0.2 29.9 2.0 0.3 0.9 China 1992 83.4 83.2 35.0 10.0 3.0 0.2 33.0 2.0 - 0.2 China 1997 83.8 83.3 33.5 7.7 1.7 0.4 36.4 3.4 0.2 0.5 China, Hong Kong SAR 1982 72.3 63.9 19.9 1.2 19.4 2.7 3.5 14.6 2.6 8.4 China, Hong Kong SAR 1987 80.8 75.0 22.9 0.9 16.4 2.5 4.5 26.0 1.8 5.8 China, Hong Kong SAR 1992 86.0 80.0 19.0 1.0 17.0 - 5.0 35.0 3.0 7.0 India 1980 34.1 26.9 21.4 - 0.9 - 0.4 4.2 - 7.2 India 1988 44.9 39.9 31.3 - 1.4 - 1.9 5.3 - 5.0 India 1992/93 40.6 36.3 27.3 3.4 1.2 - 1.9 2.4 - 4.3 India 1998/99 48.2 42.8 34.2 1.9 2.1 - 1.6 3.1 - 5.4 Indonesia 1980 26.8 21.9 - - 14.3 - 6.7 0.9 - 4.9 Indonesia 1985 38.5 36.9 1.2 0.4 15.4 7.4 11.9 0.6 - 1.6 Indonesia 1987 47.7 44.0 3.1 0.2 16.1 9.8 13.2 1.6 - 3.7 Indonesia 1991 49.7 47.1 2.7 0.6 14.8 14.9 13.3 0.8 - 2.6 Indonesia 1994 54.7 52.1 3.1 0.7 17.1 19.4 a 10.3 0.9 2.7 Indonesia 1997 57.4 54.7 3.0 0.4 15.4 27.1 8.1 0.7 - 2.7 Indonesia 2002/03 60.3 56.7 3.7 0.4 13.2 32.1 b 6.2 0.9 - 3.7 c Iran 1992 65.0 45.0 8.0 1.0 23.0 - 7.0 6.0 - 20.0 Iran 1994 70.0 51.1 11.1 1.2 22.1 - 7.8 6.6 - 18.9 Iran 1997 72.9 56.0 15.5 1.9 20.9 2.9 8.3 5.4 1.1 - Korea, DPR 1990/92 61.8 53.0 4.1 0.3 0.1 - 48.5 - - 8.9 Korea, Rep. 1982 57.7 47.4 23.0 5.1 5.4 - 6.7 7.2 - 10.3 Korea, Rep. 1985 70.4 59.4 31.6 8.9 4.3 - 7.4 7.2 - 11.0 Korea, Rep. 1988 77.3 70.2 37.2 11.0 2.8 - 6.7 10.2 2.2 7.1 Korea ,Rep. 1992 79.4 69.5 35.3 12.0 3.0 - 9.0 10.2 - 9.9 Korea, Rep. 1994 77.4 66.8 28.6 11.6 1.8 - 10.5 14.3 - 10.6 Korea, Rep. 1997 80.5 66.9 24.1 12.7 1.8 - 13.2 15.1 - - Laos 2000 32.2 28.9 4.7 - 12.9 7.7 3.0 0.5 - 3.2 Malaysia 1984 51.4 29.8 7.5 0.2 11.6 0.5 2.2 7.7 0.2 21.6 Malaysia 1994 54.5 29.8 6.4 - 13.4 - 3.9 5.3 0.8 24.6 Mongolia 2000 67.4 54.3 1.3 0.2 8.3 39.3 0.3 4.3 0.7 13.1 Myanmar 1991 16.8 13.6 3.7 1.8 4.0 3.1 0.9 0.1 - 3.2 Myanmar 1997 32.7 28.4 5.5 2.2 7.4 11.7 1.3 0.1 - 4.3 Nepal 1981 6.8 6.8 2.4 2.9 1.1 0.1 0.1 0.4 - - Nepal 1986 13.9 13.9 6.3 5.7 0.8 0.5 0.1 0.6 - - Nepal 1991 22.7 21.8 10.9 6.8 1.0 2.1 0.2 0.5 - 0.9 Nepal 1996 28.5 26.0 12.1 5.4 1.4 4.5 0.3 1.9 0.1 2.5 Nepal 2001 39.3 35.4 15.0 6.3 1.6 9.0 0.4 2.9 - 4.0 Pakistan 1984 7.6 6.4 2.2 - 1.2 0.5 0.7 1.7 0.1 1.2 Pakistan 1990/91 11.9 9.0 3.5 - 0.7 0.8 1.3 2.7 - 2.9 Pakistan 1994 17.8 12.6 5.0 - 0.7 1.0 2.1 3.7 0.7 5.2 Pakistan 2000/01 27.6 20.2 6.9 - 1.9 2.6 3.5 5.5 - 7.4 Papua New Guinea 1996 25.9 19.6 7.6 0.2 4.4 6.8 0.1 0.5 - 6.3 Philippines 1983 30.1 17.8 9.1 - 4.9 0.1 2.5 1.2 - 12.3 Philippines 1986 43.6 20.6 11.4 - 5.9 0.2 2.4 0.7 - 23.0 Philippines 1988 36.2 21.6 11.4 - 6.9 0.2 2.4 0.7 - 14.6 Philippines 1993 40.0 24.9 11.9 0.4 8.5 0.1 3.0 1.0 - 15.1 Philippines 1998 46.1 28.2 10.3 - 9.9 2.4 3.7 1.6 - 18.1 Singapore 1982 74.2 73.0 22.3 0.6 11.6 - - 24.3 14.2 1.2 Singapore 1997 62.0 53.0 15.8 0.2 10.0 - 5.0 22.0 - 9.0 Appendix A A.4 Table A.1. Contraceptive Use by Method Among Currently Married Women, All Surveys 1980 to Present, Developing Countries Sterilization Modern Injectable Any Country Date Total Prev. Methods Female Male Pill Implant IUD Condom Vaginals Trad.* Sri Lanka 1981 42.7 30.2 17.9 3.5 2.2 1.3 2.8 2.5 - 12.5 Sri Lanka 1982 54.9 30.4 17.0 3.7 2.6 1.4 2.5 3.2 - 24.5 Sri Lanka 1987 62.0 40.5 24.8 4.9 4.1 2.7 2.1 1.9 - 21.5 Sri Lanka 1993 66.1 43.6 23.5 3.7 5.5 4.6 3.0 3.3 - 22.5 Taiwan 1980 69.0 53.0 16.0 1.0 6.0 - 22.0 8.0 - 16.0 Taiwan 1985 78.0 64.0 26.0 - 5.0 - 19.0 14.0 - 14.0 Taiwan 1991 81.9 73.8 26.4 1.7 4.2 - 22.4 19.1 0.1 8.1 Taiwan 1992 82.0 73.7 27.1 1.6 4.9 - 22.1 18.0 - 8.3 Thailand 1980 44.5 43.3 11.4 2.1 22.2 3.5 4.1 - - 1.2 Thailand 1981 59.0 56.3 18.7 4.2 20.2 7.1 4.2 1.9 - 2.7 Thailand 1984A 64.6 62.0 23.5 4.4 19.8 7.6 4.9 1.8 - 2.6 Thailand 1984B 58.9 58.6 18.9 3.3 23.4 7.4 5.6 - - 0.3 Thailand 1987 65.5 63.6 22.8 5.7 18.6 8.5 6.9 1.1 - 1.9 Thailand 1993 73.9 71.7 19.8 2.8 27.2 14.3 5.7 1.9 - 2.2 Thailand 1996/97 72.2 69.8 22.0 2.0 23.1 17.7 3.2 1.8 - 2.4 Viet Nam 1988 53.2 37.7 2.7 0.3 0.4 - 33.1 1.2 - 15.5 Viet Nam 1994 65.0 43.8 3.9 0.2 2.1 0.2 33.3 4.0 0.1 21.2 Viet Nam 1997 75.3 55.8 6.3 0.5 4.3 0.2 38.5 5.9 0.1 19.5 Viet Nam 2002 78.5 56.7 5.9 0.5 6.3 0.4 37.7 5.8 - 21.9 Latin America Bolivia 1983 26.0 12.0 3.0 - 3.0 1.0 4.0 - 1.0 14.0 Bolivia 1989 30.3 12.2 4.4 - 1.9 0.7 4.8 0.3 0.1 18.1 Bolivia 1994 45.4 17.8 4.6 - 2.8 0.8 8.1 1.3 0.1 27.6 Bolivia 1998 47.0 25.0 7.0 - 4 1.0 11.0 3.0 - 22.0 Bolivia 2000 53.4 27.3 4.3 - 3.8 3.2 12.6 3.3 - 26.1 Brazil 1986 65.8 56.7 26.9 0.8 25.2 0.6 1.0 1.7 0.5 9.1 Brazil 1996 76.7 70.3 40.1 2.6 20.7 1.2 1.1 4.4 0.1 6.4 Colombia 1980 48.5 41.0 10.7 0.2 17.4 - 8.1 - 4.6 7.5 Colombia 1986 64.8 52.5 18.3 0.4 16.4 2.4 11.0 1.7 2.3 12.3 Colombia 1990 66.1 54.7 20.9 0.5 14.1 2.2 12.4 2.9 1.7 11.4 Colombia 1995 72.7 59.7 25.6 0.7 12.9 3.2 11.2 4.3 1.8 13.0 Colombia 2000 76.9 64.0 27.1 1.0 11.8 4.2 12.4 6.1 1.5 13.0 Costa Rica 1981 65.2 55.9 17.3 0.5 20.6 2.2 5.7 8.4 1.2 9.3 Costa Rica 1986 69.5 58.2 13.9 0.5 20.7 1.0 8.0 13.4 0.7 11.3 Costa Rica 1992/93 75.0 64.6 19.7 1.3 18.0 1.0 8.7 15.7 0.2 10.4 Cuba 1987 70.0 67.0 22.0 - 10.0 - 33.0 2.0 - 3.0 Cuba 2000 73.3 72.1 19.0 - 3.6 1.0 43.5 5.0 0.1 1.3 Dominican Republic 1980 42.0 35.0 21.0 - 9.0 - 5.0 - - 7.0 Dominican Republic 1983 45.8 41.7 27.4 0.1 8.6 - 3.8 1.5 0.3 4.1 Dominican Republic 1986 50.0 46.7 32.9 0.1 8.8 0.3 3.0 1.4 0.2 3.3 Dominican Republic 1991 56.4 51.7 38.5 - 9.8 - 1.8 1.2 - 4.7 Dominican Republic 1996 63.7 59.2 40.9 0.1 12.9 0.5 2.5 1.4 0.3 4.0 Dominican Republic 2000 64.7 62.5 42.9 - 14.2 2.0 2.5 0.9 - 2.2 Dominican Republic 2002 69.8 65.8 45.8 0.1 13.5 2.4 2.2 1.3 - 4.4 Ecuador 1982 39.9 32.9 12.4 - 10.3 0.7 6.4 1.1 2.0 7.0 Ecuador 1987 44.3 35.8 15.0 - 8.5 0.7 9.8 0.6 1.2 8.5 Ecuador 1989 52.9 41.5 18.3 0.2 8.6 0.4 11.9 1.3 0.8 11.4 Ecuador 1994 56.8 44.4 19.8 - 10.2 - 11.8 2.6 - 12.5 Ecuador 1999 65.8 50.1 22.5 - 11.1 3.5 10.1 2.7 0.2 15.8 El Salvador 1985 47.3 44.5 31.8 0.7 6.6 0.7 3.3 1.2 0.2 2.8 El Salvador 1988 47.1 43.5 29.6 0.6 7.6 0.9 2.0 2.4 0.4 3.6 El Salvador 1993 53.3 48.3 31.5 0.4 8.7 3.6 2.1 2.1 - 5.0 El Salvador 1998 59.7 54.1 32.4 - 8.1 8.9 1.5 2.5 0.7 5.7 Guatemala 1983 25.0 20.6 10.2 0.9 4.7 - 2.6 1.2 1.0 4.4 Guatemala 1987 23.2 19.1 10.4 0.9 3.9 0.5 1.8 1.2 0.4 4.1 Guatemala 1995 31.4 26.9 14.3 1.5 3.8 2.5 2.6 2.2 - 4.5 Guatemala 1998/99 38.2 30.9 16.7 0.8 5.0 3.9 2.2 2.3 - 7.3 Guyana 2000 37.3 36.0 4.5 0.1 11.2 4.7 6.3 8.8 0.5 1.4 Haiti 1983 6.9 3.9 0.7 0.1 2.2 0.2 0.2 0.5 - 3.0 Haiti 1987 6.7 5.0 1.3 - 2.3 0.8 0.4 0.2 - 1.7 Haiti 1989 10.2 9.8 2.5 - 4.1 1.6 0.6 0.5 0.1 0.4 Haiti 1994 18.6 13.6 3.1 0.2 3.1 3.0 0.3 2.9 1.0 5.0 Haiti 2000 27.4 21.4 3.0 - 2.3 13.6 - 2.2 0.6 5.7 Honduras 1981 26.9 23.5 8.1 0.1 11.7 0.3 2.4 0.3 0.6 3.4 Honduras 1984 34.9 30.4 12.1 0.2 12.7 0.3 3.8 0.9 0.4 4.5 Honduras 1987 40.6 32.9 12.6 0.2 13.4 0.3 4.3 1.8 0.3 7.7 Honduras 1996 50.0 39.7 18.1 - 9.9 - 8.5 3.2 - 10.3 Honduras 2001 61.8 50.8 18.0 - 10.4 9.6 9.6 3.2 - 11.0 Appendix A A.5 Table A.1. Contraceptive Use by Method Among Currently Married Women, All Surveys 1980 to Present, Developing Countries Sterilization Modern Injectable Any Country Date Total Prev. Methods Female Male Pill Implant IUD Condom Vaginals Trad.* Jamaica 1983 51.4 48.4 10.9 - 19.3 7.6 2.0 7.6 1.0 3.0 Jamaica 1989 54.6 51.3 13.6 0.1 19.5 7.6 1.5 8.6 0.4 3.3 Jamaica 1993 66.5 64.3 13.4 - 23.7 6.4 1.1 17.9 1.7 2.2 Jamaica 1997 65.9 62.6 12.3 - 21.2 11.0 1.1 17.0 - 3.0 Mexico 1982 47.7 41.5 13.4 0.3 14.2 5.1 6.6 0.9 1.0 6.2 Mexico 1987 52.7 44.6 18.6 0.8 9.7 2.8 10.2 1.9 0.6 8.1 Mexico 1995 67.0 58.8 27.7 1.2 8.4 3.1 14.7 3.7 - 8.3 Mexico 1997 68.4 59.5 30.0 1.3 7.1 3.1 14.1 3.7 0.2 9.1 Nicaragua 1981 27.0 22.8 7.1 0.1 10.5 1.4 2.3 0.8 0.6 4.2 Nicaragua 1992 48.7 45.5 18.5 0.3 12.9 1.2 9.3 2.6 0.1 3.2 Nicaragua 1998 60.4 57.4 26.1 0.5 13.9 5.2 9.1 2.6 - 3.0 Nicaragua 2001 68.6 66.1 25.3 0.5 14.6 14.3 6.4 3.3 1.8 2.5 Panama 1984 58.2 54.2 32.4 0.4 11.8 0.8 6.0 1.6 1.2 4.0 Paraguay 1987 44.8 29.0 4.0 - 13.5 3.6 5.1 2.3 0.5 15.8 Paraguay 1990 48.4 35.3 7.4 - 13.6 5.2 5.7 2.6 0.8 13.1 Paraguay 1995 50.7 41.3 6.8 - 13.5 6.2 7.6 6.5 0.7 9.5 Paraguay 1998 57.4 47.7 8.0 - 13.1 7.5 11.1 7.3 0.5 14.6 Peru 1981 41.0 17.0 4.0 - 5.0 2.0 4.0 1.0 1.0 24.0 Peru 1986 45.8 23.0 6.1 - 6.5 1.3 7.4 0.7 1.0 22.8 Peru 1991 59.0 32.8 7.9 0.1 5.7 1.9 13.4 2.8 1.0 26.2 Peru 1996 64.2 41.3 9.5 0.2 6.2 8.0 12.0 4.4 0.7 22.9 Peru 2000 68.9 50.4 12.3 0.5 6.7 15.0 9.1 5.6 1.3 18.5 Puerto Rico 1982 64.1 57.6 38.6 4.0 7.7 - 3.6 3.7 - 6.5 Puerto Rico 1995/96 77.7 67.6 45.5 3.5 9.7 1.3 1.0 6.4 0.4 10.1 Trinidad & Tobago 1987 52.7 44.4 8.2 0.2 14.0 0.8 4.4 11.8 5.0 8.3 Middle East/North Africa Algeria 1986 35.5 31.3 1.3 - 26.5 0.6 2.1 0.6 0.2 4.2 Algeria 1992 50.7 42.8 1.1 - 38.7 0.1 2.4 0.5 0.2 7.9 Algeria 1995 52.0 49.1 - - 44.0 - 4.0 1.0 0.1 3.0 Algeria 2000 64.0 50.1 - - 44.3 - 4.3 1.5 - 13.3 Egypt 1980 24.2 22.7 0.7 0.1 16.5 0.1 4.0 1.1 0.2 1.5 Egypt 1981 33.8 30.8 1.1 - 20.5 0.2 6.9 1.1 1.0 3.0 Egypt 1984 29.7 28.7 1.5 - 16.5 0.3 8.4 1.3 0.7 1.0 Egypt 1988 37.8 35.4 1.5 - 15.3 0.1 15.7 2.4 0.4 2.4 Egypt 1992 47.1 44.8 1.1 - 12.9 0.5 27.9 2.0 0.4 2.3 Egypt 1995 47.9 45.5 1.1 - 10.4 2.4 30.0 1.4 0.1 2.4 Egypt 1997 54.5 51.8 1.4 - 10.2 3.9 34.6 1.5 0.2 2.7 Egypt 2000 56.1 53.9 1.4 - 9.5 6.3 35.5 1.0 0.2 2.1 Egypt 2003 60.0 56.6 0.9 - 9.3 8.8 36.7 0.9 0.1 3.4 Iraq 1989 13.7 10.4 1.4 - 4.7 0.5 2.8 1.0 - 3.4 Jordan 1983 26.0 20.8 3.8 - 7.8 0.2 8.3 0.6 0.1 5.2 Jordan 1985 26.5 22.3 4.9 - 6.0 0.1 10.8 0.4 0.1 4.2 Jordan 1990 40.0 26.9 5.6 - 4.6 - 15.3 0.8 0.6 13.1 Jordan 1997 52.6 37.7 4.2 - 6.5 0.7 23.1 2.4 0.5 14.9 Jordan 2002 55.8 41.2 2.9 - 7.5 0.9 23.6 3.4 2.9 14.6 Kuwait 1987 34.6 31.7 2.0 - 24.0 - 3.7 1.5 0.5 2.9 Kuwait 1996 50.2 40.9 2.1 - 28.8 - 6.8 2.9 0.3 9.3 Lebanon 1996 61.0 37.0 - - 10.0 - 17.0 - 10.0 24.0 Libya 1995 39.7 25.6 4.8 - 9.6 - 11.2 - - 14.1 Morocco 1980 19.7 16.6 0.8 - 13.9 - 1.6 0.3 - 3.1 Morocco 1983 25.5 21.2 1.7 - 16.8 - 2.0 0.4 0.3 4.3 Morocco 1987 35.9 28.9 2.2 - 22.9 0.3 2.9 0.5 0.1 7.0 Morocco 1992 41.5 35.5 3.0 - 28.1 0.1 3.2 0.9 0.2 6.0 Morocco 1995 50.3 42.4 4.3 - 32.2 0.1 4.3 1.4 0.1 7.8 Morocco 2003/04 63.0 54.8 2.7 - 40.1 2.1 5.4 1.5 0.1 11.0 Oman 1988 8.6 7.5 2.2 - 2.4 0.3 1.5 1.1 - 1.1 Oman 1995 23.7 18.2 4.5 - 6.1 3.8 2.2 1.5 - 5.6 Saudi Arabia 1996 31.8 28.5 1.0 - 19.6 0.2 6.6 0.9 0.2 3.3 Sudan 1989 8.7 5.6 0.8 - 3.9 0.1 0.7 0.1 - 3.1 Sudan 1992/93 8.3 6.9 0.9 - 5.1 0.2 0.6 - - 1.5 Syria 1993 36.1 28.3 2.2 - 9.9 - 15.7 0.3 0.2 7.8 Tunisia 1983 41.1 34.2 12.5 - 5.3 0.4 13.2 1.3 1.5 6.9 Tunisia 1988 49.8 40.4 11.5 - 8.8 0.8 17.0 1.3 1.0 9.4 Tunisia 1994 60.0 51.0 14.5 - 11.1 1.0 21.5 1.6 1.3 9.0 Turkey 1983 51.0 22.7 1.1 - 7.5 0.2 7.4 4.1 2.4 28.3 Turkey 1988 63.3 31.1 1.7 0.1 6.2 0.1 14.0 7.2 1.8 32.2 Turkey 1993 62.6 34.5 2.9 - 4.9 0.1 18.8 6.6 0.6 28.1 Turkey 1998 63.9 37.7 4.2 - 4.4 0.5 19.8 8.2 0.6 26.1 Appendix A A.6 Table A.1. Contraceptive Use by Method Among Currently Married Women, All Surveys 1980 to Present, Developing Countries Sterilization Modern Injectable Any Country Date Total Prev. Methods Female Male Pill Implant IUD Condom Vaginals Trad.* United Arab Emirates 1995 27.5 23.6 4.2 - 11.9 1.5 3.7 2.0 0.3 3.9 Yemen 1991 9.7 6.1 0.8 0.1 3.2 0.6 1.2 0.1 - 3.6 Yemen 1997 20.8 9.8 1.4 0.1 3.8 1.2 3.0 0.3 0.1 11.0 Sub-Saharan Africa Angola 2001 6.2 4.5 0.1 - 2.2 1.4 0.4 0.3 0.2 1.7 Benin 1981 9.2 0.5 - - 0.2 - 0.1 0.1 0.1 8.7 Benin 1996 16.4 3.4 0.4 - 0.5 0.7 0.5 0.7 0.1 13.0 Benin 2001 18.6 7.2 0.3 - 1.8 2.4 0.8 1.3 0.6 11.4 Botswana 1984 27.8 18.6 1.5 - 10.0 1.0 4.8 1.2 0.1 9.2 Botswana 1988 33.0 31.7 4.3 0.3 14.8 5.4 5.6 1.3 - 1.3 Botswana 2000 40.4 38.8 1.3 0.1 14.7 10.0 1.3 11.2 0.1 1.6 Burkina Faso 1993 7.9 4.2 0.3 - 2.1 0.1 0.7 0.8 0.1 3.7 Burkina Faso 1998/99 11.9 4.8 - - 1.8 1.1 0.4 1.2 0.4 7.0 Burkina Faso 2003 13.7 8.6 0.1 - 2.2 3.7 0.4 2.1 - 5.1 Burundi 1987 8.7 1.2 0.1 - 0.2 0.5 0.3 0.1 - 7.5 Burundi 2000 15.7 10.0 0.2 0.1 3.9 4.7 0.8 0.2 - 5.7 Cameroon 1991 16.1 4.3 1.2 - 1.2 0.4 0.3 0.9 0.3 11.8 Cameroon 1998 19.3 7.1 1.5 - 2.0 0.7 0.6 2.1 0.2 12.2 Central African Rep. 1994 14.8 3.2 0.4 - 1.1 0.6 0.1 1.0 0.1 11.5 Chad 1996 4.2 1.2 0.2 - 0.6 0.2 - 0.2 - 3.0 Chad 2000 7.9 2.1 0.6 - 1.1 0.2 0.1 - 0.1 5.9 Congo, D.R. 1991 7.7 2.0 0.3 - 0.4 0.5 0.1 0.6 0.2 5.7 Côte d'Ivoire 1980 2.9 0.5 - - 0.4 - 0.1 - - 2.4 Côte d'Ivoire 1994 11.4 4.3 0.2 - 2.2 0.8 0.3 0.7 0.1 7.1 Côte d'Ivoire 1998/99 15.0 7.3 0.1 - 3.5 1.4 0.4 1.8 - 6.6 Eritrea 1995 19.8 7.2 0.5 0.1 3.3 1.1 0.8 1.3 - 12.7 Eritrea 2002 8.0 5.1 0.2 - 1.4 2.6 0.4 0.6 - 2.9 Ethiopia 1990 4.1 2.6 0.3 - 1.9 - 0.3 0.1 - 1.5 Ethiopia 2000 8.1 6.3 0.3 - 2.5 3.1 0.1 0.3 - 1.8 Gabon 2000 29.0 12.0 1.0 - 5.0 1.0 - 5.0 - 18.0 Gambia 2000 9.6 8.9 0.2 - 3.9 3.9 0.8 0.1 - 0.7 Ghana 1993 20.3 10.1 0.9 - 3.2 1.6 0.9 2.2 1.2 10.2 Ghana 1998/99 22.0 13.3 1.3 - 3.9 3.2 0.7 2.7 1.4 8.7 Ghana 2003 25.2 18.7 1.9 - 5.5 6.4 0.9 3.2 0.5 6.8 Guinea 1999 6.2 4.2 - - 2.1 1.0 0.2 0.6 0.3 2.0 Guinea-Bissau 2000 7.6 3.6 0.3 - 0.3 0.5 2.3 0.1 - 4.1 Kenya 1984 17.0 9.6 2.6 - 3.1 0.5 3.0 0.3 0.1 7.4 Kenya 1989 26.9 17.9 4.7 - 5.2 3.3 3.7 0.5 0.4 9.0 Kenya 1993 32.7 27.3 5.5 - 9.5 7.2 4.2 0.8 0.1 5.4 Kenya 1998 39.0 31.5 6.2 - 8.5 12.6 2.7 1.3 - 7.5 Kenya 2003 39.3 31.5 4.3 - 7.5 16.0 2.4 1.2 - 7.8* Lesotho 1992 23.0 18.0 1.0 - 7.0 - 3.0 1.0 6.0 4.0 Lesotho 2000 30.4 29.5 1.3 0.1 9.4 14.0 2.6 1.8 0.2 0.9 Liberia 1986 6.4 5.5 1.1 - 3.3 0.3 0.6 - 0.2 0.9 Madagascar 1992 16.7 5.1 0.9 - 1.4 1.6 0.5 0.5 0.1 11.6 Madagascar 1997 19.3 9.8 1.0 - 2.4 5.1 0.5 0.7 0.1 9.5 Madagascar 2000 18.8 11.8 0.6 - 3.3 7.1 0.3 0.4 - 7.1 Malawi 1984 6.9 1.1 - - 0.7 0.1 0.3 - - 5.8 Malawi 1992 13.0 7.4 1.7 - 2.2 1.5 0.3 1.6 0.1 5.6 Malawi 1996 21.9 14.4 2.5 - 3.4 6.4 0.4 1.6 - 7.5 Malawi 2000 30.6 26.1 4.7 0.1 2.7 16.5 0.1 1.6 0.4 4.5 Mali 1987 4.7 1.3 0.1 - 0.9 0.1 0.1 - 0.1 3.4 Mali 1995 6.7 4.5 0.3 - 3.1 0.2 0.3 0.4 0.1 1.7 Mali 2001 8.1 5.7 0.3 - 2.8 2.2 0.2 0.3 - 2.3 Mauritania 1981 0.8 0.3 0.2 - - - - - 0.1 0.5 Mauritania 2000/01 8.0 5.1 - - 2.6 0.9 0.8 0.8 0.1 2.8 Mauritius 1985 75.4 45.6 4.7 - 21.0 6.2 2.3 10.8 0.6 29.8 Mauritius 1991 74.7 48.9 7.2 0.2 20.9 4.1 2.8 13.3 0.4 25.7 Mozambique 1997 5.6 5.1 0.7 - 1.5 2.3 0.3 0.3 - 0.5 Namibia 1989 26.4 26.1 6.0 0.1 6.6 12.5 0.9 - - 0.3 Namibia 1992 28.9 26.0 7.4 0.2 8.3 7.7 2.1 0.3 0.1 2.9 Niger 1992 4.4 2.3 0.1 - 1.5 0.5 0.2 - - 2.1 Niger 1997 8.2 4.6 0.1 - 2.8 1.5 0.1 - 0.1 3.6 Niger 2000 14.0 4.3 0.2 - 3.4 0.6 0.1 - - 9.7 Nigeria 1981 4.8 0.6 0.1 - 0.2 0.2 0.1 - - 4.2 Nigeria 1990 6.0 3.5 0.3 - 1.2 0.7 0.8 0.4 0.1 2.5 Nigeria 1999 15.3 8.6 0.3 - 2.4 2.5 2.0 1.2 0.2 6.7 Nigeria 2003 12.6 8.2 0.2 - 1.8 2.0 0.7 1.9 - 5.7 Appendix A A.7 Table A.1. Contraceptive Use by Method Among Currently Married Women, All Surveys 1980 to Present, Developing Countries Sterilization Modern Injectable Any Country Date Total Prev. Methods Female Male Pill Implant IUD Condom Vaginals Trad.* Rwanda 1983 10.1 0.9 - - 0.2 0.4 0.3 - - 9.2 Rwanda 1992 21.2 12.9 0.7 - 3.0 8.4 0.2 0.2 - 8.3 Rwanda 2000 13.2 4.3 0.8 - 1.0 1.9 - 0.4 0.3 9.0 Senegal 1986 11.3 2.4 0.2 - 1.2 0.1 0.7 0.1 0.1 8.9 Senegal 1992 7.4 4.8 0.4 - 2.2 0.2 1.4 0.4 0.1 2.6 Senegal 1997 12.9 8.1 0.5 - 3.3 1.7 1.6 0.6 - 4.9 Sierra Leone 2000 4.3 3.9 0.2 - 2.5 0.9 0.2 0.1 0.1 0.5 South Africa 1981 48.0 46.0 8.0 - 15.0 14.0 6.0 3.0 - 2.0 South Africa 1987 46.6 45.4 7.4 1.4 12.4 18.3 5.0 0.7 0.2 1.2 South Africa 1994 62.8 60.4 12.4 1.5 15.0 26.0 2.2 3.1 0.3 2.4 South Africa 1998 56.3 55.1 15.8 2.1 10.6 23.2 1.8 1.7 - 1.2 Swaziland 1988 19.9 17.2 3.1 0.2 5.6 5.6 1.8 0.7 0.2 2.7 Swaziland 2000 27.7 26.0 6.0 - 5.4 11.6 1.2 1.8 - 1.7 Tanzania 1991 10.4 6.6 1.6 - 3.4 0.4 0.4 0.7 - 3.8 Tanzania 1994 20.4 13.1 2.0 - 5.6 2.8 1.0 1.7 - 7.4 Tanzania 1996 18.4 13.3 1.9 - 5.5 4.5 0.6 0.8 - 4.7 Tanzania 1999 25.4 16.9 2.0 - 5.3 6.3 0.4 2.7 - 8.6 Togo 1988 12.1 3.1 0.6 0.2 0.4 0.2 0.8 0.4 0.6 9.1 Togo 1998 23.6 7.1 0.4 - 1.2 2.7 1.0 1.5 0.3 16.5 Togo 2000 25.7 9.3 0.7 - 2.5 4.0 0.2 1.6 0.3 16.4 Uganda 1988 4.9 2.5 0.8 - 1.1 0.4 0.2 - - 2.4 Uganda 1995 14.8 7.8 1.4 - 2.6 2.5 0.4 0.8 - 7.0 Uganda 1995 14.8 7.8 1.4 - 2.6 2.5 0.4 0.8 - 7.0 Uganda 2000/01 22.8 18.2 2.0 - 3.2 6.7 0.2 1.9 4.2 4.6 Zambia 1992 15.2 8.9 2.1 - 4.3 0.1 0.5 1.8 0.1 6.3 Zambia 1996 25.9 14.4 2.0 - 7.2 1.0 0.4 3.5 0.1 11.5 Zambia 2001/02 34.2 22.6 2.0 - 11.9 4.8 0.1 3.8 0.1 11.6 Zimbabwe 1984 38.4 26.6 1.6 0.1 22.6 0.8 0.7 0.7 0.1 11.8 Zimbabwe 1988 43.1 36.1 2.3 0.2 31.0 0.3 1.1 1.2 - 7.0 Zimbabwe 1994 48.1 42.2 2.3 0.2 33.1 3.2 1.0 2.3 - 5.9 Zimbabwe 1999 53.5 50.4 2.6 0.1 35.5 8.6 0.9 1.8 0.9 3.2 Central Asia Republics Kazakhstan 1995 59.1 46.1 0.7 - 1.8 0.3 39.6 3.7 - 13.0 Kazakhstan 1999 66.1 52.7 2.8 - 2.4 0.6 42.0 4.5 0.4 13.5 Kyrgyzstan 1997 59.5 48.9 1.8 - 1.7 1.3 38.2 5.7 0.1 10.7 Tajikistan 2000 33.9 27.3 0.2 0.1 0.6 0.9 25.1 0.4 - 6.6 Turkmenistan 2000 61.8 53.1 1.8 - 1.2 1.0 39.0 2.0 7.9 8.7 Uzbekistan 1996 55.5 51.3 0.7 - 1.7 1.4 45.8 1.7 - 4.2 Uzbekistan 2000 67.2 62.5 1.4 0.1 2.6 1.3 56.3 0.8 1.1 4.7 Uzbekistan 2002 67.7 62.8 2.6 - 1.6 2.0 51.8 2.0 - 7.7 Caucasus Armenia 2000 60.5 22.3 2.7 - 1.1 0.1 9.4 6.9 2.1 38.2 Azerbaijan 2001 55.4 11.9 1.2 - 1.0 - 6.1 3.2 0.4 43.5 Georgia 1999/00 40.5 19.8 1.6 - 1.0 - 9.7 6.3 1.1 20.7 Moldova, Russia, Ukraine Moldova 1997 73.4 49.8 3.4 - 2.1 - 38.4 5.9 - 23.6 Moldova 2000 62.4 42.8 1.1 - 3.3 - 34.5 3.5 0.3 19.6 Ukraine 1999 67.5 37.6 1.4 - 3.0 - 18.6 13.5 1.1 29.9 *For a few countries traditional methods include a small percent for breastfeeding with contraceptive intent. Notes: a. Indonesia, 1994: 15% injectable, 4.9% Norplant. b. Indonesia, 2002/03: 27.8% injectable, 4.3% Norplant. c. Indonesia, 2002/03: “any trad” including breastfeeding. Dashes mean the quantity is negligible. A.8 Appendix A Appendix A A.9 SUB-SAHARAN AFRICA BENIN, 1981–82: Ministère du Plan, de la Statistique et de l’Analyse Economique, Enquête Fécondité au Bénin: Rapport Préliminaire (May 1983), p. 233, Table 4.4.1. 1996: Institut National de la Statistique et de l’Analyse Economique, Benin Enquete Demo- graphique et de Sante 1996 (Demographic and Health Surveys, Macro International, April 1997). 2001: DHS, with Institut National de la Statis- tique et de l’Analyse Economique. BOTSWANA, 1984: W.G. Manyeneng, P. Khulumani, M.K. Larson, and A.A. Way, Botswana Family Health Survey 1984 (Family Health Division, Ministry of Health, and Westinghouse Public Applied Systems, July 1985), pp. 147, 150, and 151. 1988: Family Health Division, Ministry of Health, Botswana Family Health Survey II 1988 (Demographic and Health Surveys, Institute for Resource Development, Macro Systems, August 1989), p. 42. BURKINA FASO, 1998–99: DHS, with Bu- reau Central des Recensements et des Etudes de Population (BUCREP). 1992–93: Institut National de la Statistique et de la Demographie, Burkina Faso Enquete Demographique et de Sante 1993 (Demographic and Health Surveys, Macro International, June 1994). 2003: DHS, with Institut National de la Statistique et la Démo. BURUNDI, 1987: Ministère de l’Intérieur, Département de la Population, and Demographic and Health Surveys, Enquête Démographique et de Santé au Burundi 1987 (Institute for Re- source Development/Westinghouse, October 1988), p. 4. 1991: Direction Nationale du Deuxieme Recensement General de la Population et de l’Habitat, Enquête Démographique et de Sante Cameroun 1991 (Demographic and Health Sur- veys, Macro International, December 1992). 1998: Bureau Central des Recensement et des Etudes de Population (BUCREP) and Demo- graphic and Health Surveys, Enquête Démographique et de Sante au Cameroun 1998- Rapport Preliminaire (Macro Interna- tional, August 1998). CAMEROON, 1991: DHS, with Min. du Plan et de l’Amén. du Terr. 1998: DHS, with Bureau Central du Recense- ments et Études de Population. 2004: DHS, with DSCN and BUCREP. CAPE VERDE, 2004: DHS, with Instituto Nacional de Estatisticas. CENTRAL AFRICAN REPUBLIC, 1994– 95: Division des Statistiques et des Etudes Economiques, Republique Centrafricaine Enquete Demographique et de Sante 1994/1995 (Demographic and Health Surveys, Macro In- ternational, December 1995). CHAD, 1996–97: Bureau Central du Recensement, Direction de la Statistique, Tchad Enquete Demographique et de Sante 1996/1997 (Demographic and Health Surveys, Macro In- ternational, May 1998). 2004: DHS, with Inst. de la Stat., des Études Écon. et Demogra. CONGO-BRAZAVILLE, 2004: DHS, with Centre National de la Stat. et des Études Écon. CONGO, D.R., 1991: Suzanne M. Hurley, Leo Morris and Jay S. Friedman, 1991 Zaire Na- tional Immunization Survey Further Analysis of Data: Family Planning Module (Atlanta, Geor- Sources for Appendix Table A.1 The following sources are cited numerous times and are therefore abbreviated as indicated: Designated as Berent, 1982: J. Berent, Family Planning in Europe and USA in the 1970’s, WFS Comparative Studies No. 20 (International Statistical Institute and World Fertility Survey, 1982), Tables 1 and 6. Designated as Carrasco, 1981: E. Carrasco, Contraceptive Practice, WFS Comparative Studies No. 9, Cross-National Summaries (International Statistical Institute and World Fertility Survey, 1981). Designated as Morris, 1981: L. Morris et al., “Contraceptive Prevalence Surveys: A New Source of Family Planning Data,” Population Reports, Series M, No. 5 (May–June 1981), Table 3. Designated as London, 1985. K.A. London et al., “Fertility and Family Planning Surveys: An Update,” Population Reports, Series M, No. 5 (Sept.– Oct. 1985), Table 6. Designated as DHS: Demographic and Health Survey, carried out by Macro International, part of ORC Macro, Calverton, Maryland, USA. gia, Centers for Disease Control and Prevention, 1993), tables 11, 12. COMOROS, 1996: DHS, with Centre National de Doc. et de Rech. Sci. CÔTE D’IVOIRE, 1980–81: Ministère de l’Economie et des Finances, Enquête Ivoirienne sur la Fécondité 1980–81, Rapport Principal, Volume 2 (Abidjan: Direction de la Statistique, 1984). Data were calculated from Tables 1.6.1 and 4.4.1. 1998–99: DHS, with Inst. National de la Statistique. 1994: Institut National de la Statistique, Cote d’Ivoire Enquete Demographique et de Sante 1994 (Demographic and Health Surveys, Macro International, December 1995). ERITREA, 1995: National Statistics Office, Eritrea Demographic and Health Survey 1995 (Demographic and Health Surveys, Macro In- ternational, March 1997). 2002: DHS, with National Statistics and Evalu- ation Office. ETHIOPIA, 1990: Central Statistical Author- ity, The 1990 Family and Fertility Survey: Pre- liminary Report (Addis Ababa, 1991), Tables 4.1 and 4.6. 2000: DHS, with Central Statistical Authority. GABON, 1998: DHS, with Ministère de la Planification, de la Programmation du Développement et de l’Aménagement du Territoire Direction Générale de la Statistique et des Études Économiques. 2000: DHS, with Direction Générale de la Statistique. GHANA, 1980: Ghana Fertility Survey 1979– 1980, First Report, Volume 2 (Central Bureau of Statistics, 1983), Table 4.4.1. A.10 Appendix A 1998: DHS, with Ghana Statistical Service. 1988: Ghana Statistical Service, Ghana Demo- graphic and Health Survey 1988 (Demographic and Health Surveys, Institute for Resource De- velopment, Macro Systems, September 1989), p. 36. 1993–94: Ghana Statistical Service, Ghana De- mographic and Health Survey 1993 (Demo- graphic and Health Surveys, Macro Interna- tional, December 1994). 2003: DHS, with Ghana Statistical Service. GUINEA, 1992: DHS, with Direction Nationale de la Statistique. 1999: DSH, with Direction Nationale de la Statistique. 2004: DHS, with Direction Nationale de la Statistique. KENYA, 1984: Central Bureau of Statistics, Kenya Contraceptive Prevalence Survey 1984— First Report (Nairobi: Ministry of Planning and National Development, December 1984), p. 86. 1989: Kenya Demographic and Health Survey 1989 (National Council for Population and Development, and Demographic and Health Surveys, Institute for Resource Development, Macro Systems, October 1989), p. 35. 1993: Central Bureau of Statistics, National Council for Population and Development, Kenya Demographic and Health Survey 1993 (De- mographic and Health Surveys, Macro Interna- tional, May 1994). 1998: Central Bureau of Statistics, National Council for Population and Development, Kenya Demographic and Health Survey 1998- Pre- liminary Report (Demographic and Health Sur- veys, Macro International, September 1998). 2003: DHS, with Central Bureau of Statistics. LESOTHO, 2004: DHS, with Min. of Health and Social Welfare/Bureau of Statistics. LIBERIA, 1986: Bureau of Statistics, Ministry of Planning and Economic Affairs, Liberia De- mographic and Health Survey 1986 (Demo- graphic and Health Surveys, Institute for Re- source Development/Westinghouse, February 1988), p. 41. MADAGASCAR, 1992: Ministere de la Re- cherche Appliquee au Developpement, Mada- gascar Enquete Nationale Demgraphique et Sanitaire 1992 (Demographic and Health Sur- veys, Macro International, February 1994). 1997: Institut National de la Statistique, Mada- gascar Enquete Demographique et de Sante 1997 (Demographic and Health Surveys, Macro International, November 1998). 2003: DHS, with Institut. Nat. de la Stat. MALAWI, 1984: National Statistical Office, Family Formation Survey, 1984. 1992: National Statistical Office, Malawi De- mographic and Health Survey 1992 (Demo- graphic and Health Surveys, Macro Interna- tional, January 1994). 1996: National Statistical Office, Malawi Knowledge, Attitudes and Practices in Health Survey 1996 (Demographic and Health Surveys, Macro International, September 1997). 2000: DHS, with National Statistical Office. 2004: DHS, with National Statistical Office. MALI, 1987: Centre des Etudes et de Recher- che sur la Population pour le Développement, Enquête Démographique et de Santé au Mali 1987 (Demographic and Health Surveys, Insti- tute for Resource Development/Westinghouse, January 1989), p. 49. 1995–96: Ministere de la Sante, de la Solidarite et des Personnes Agees, Mali Enquete Demographique et de Sante 1995/1996 (De- mographic and Health Surveys, Macro Interna- tional, December 1996). 2001: DHS, with CPS/MSSPA et DNSI. MAURITANIA, 1981: Ministry of Economic and National Planning, Enquête Nationale Mauritanienne sur la Fécondité 1981, Rapport Principal, Volume 2 (March 1984), Table 4.4.1. 1985: Mauritius Contraceptive Prevalence Sur- vey 1985—Final Report (Evaluation Unit, Fam- ily Planning/Maternal–Child Health Division, Ministry of Health, February 1987), Table 26. 1991: Ministry of Health, Centers for Disease Control, Mauritius Contraceptive Prevalence Survey 1991- Final Report, June 1993. 2000–01: DHS, with Office National de la Statistique. 2003: DHS, with Office National de la Statistique. MOZAMBIQUE, 1997: Instituto Nacional de Estatistica, Mozambique Inquerito Demografico e de Saude 1997 (Demographic and Health Surveys, Macro International, August 1998). 2003: DHS, with Instituto Nacional de Estatistica. NAMIBIA, 1992: Ministry of Health and So- cial Services, Namibia Demographic and Health Survey 1992 (Demographic and Health Surveys, Macro International, May 1993). 2000: DHS, with Ministry of Health and So- cial Services. NIGER, 1992: Direction de la Statistique et des Comptes Nationaux Direction Générale du Plan Ministère des Finances et du Plan, Enquête Démographique et de Santé Niger 1992—Rap- port Préliminaire (Demographic and Health Surveys, Macro International, October 1992). 1997: Enquete Demographique et de Sante Niger 1997/1998- Rapport preliminaire, Macro International, September 1998. 1998: DHS, with Care International. NIGERIA, 1982: The Nigeria Fertility Survey 1981/82, Principal Report, Vol. II (Lagos, Fed- eral Office of Statistics, 1986), Tables 1.6.3 and 4.4.1. 1990: Nigeria Demographic and Health Survey 1990, Preliminary Report (Federal Office of Sta- tistics and Demographic and Health Surveys, Institute for Resource Development/Macro Sys- tems, March 1991), p. 8, Table 4. 1999: DHS, with National Population Com- mission. 2003: DHS, with National Population Com- mission. NIGERIA ONDO STATE, 1986: DHS, with Ministry of Health, Ondo State. RWANDA, 1983: Republic of Rwanda, Rwanda 1983 Enquête Nationale sur la Fécondité (Kigali: Office National de la Popula- tion, 1985), Tables 6.6, 6.7, 7.4, 7.7, and 7.10. 1992: Office National de la Population, Rwanda Enquete Demographique et de Sante 1992 (De- mographic and Health Surveys, Macro Interna- tional, February 1994). 2000: DHS, with Office National de la Popula- tion. 2004: DHS, with Office National de la Popula- tion. SENEGAL, 1986: Direction de la Statistique, Division des Enquêtes et de la Démographie, Enquête Démographique et de Santé au Sénégal, 1986 (Demographic and Health Surveys, Insti- tute for Resource Development/Westinghouse, 1988), p. 52. 1992–93: Division des Statistiques Demographiques, Enquete Demographique et Appendix A A.11 de Sante au Senegal 1992/1993 (Demographic and Health Surveys, Macro International, April 1994). 1997: Division des Statistiques Demograph- iques, Enquete Demographique et de Sante au Senegal 1997 (Demographic and Health Sur- veys, Macro International, December 1997). 1999: DHS, with SERDHA. 2004: DHS, with Centre de Rech. pour le Dév. Humain. SOUTH AFRICA, 1981: J.L. Van Tonder, Fer- tility Survey 1981: Data Concerning the Col- ored Population of South Africa (Pretoria: Hu- man Sciences Research Council), Tables 4.4.1. and 4.5.4. 1998: DHS, with Dept. of Health/Med. Re- search Council. SUDAN, 1989–90: Department of Statistics, Ministry of Economic and National Planning, Sudan Demographic and Health Survey 1989– 1990 (Demographic and Health Surveys, Insti- tute for Resource Development, Macro Systems, May 1991), p. 42. SWAZILAND, 1988: Swaziland Ministry of Health, Centers for Disease Control, Swaziland 1988 Family Health Survey- Final Report, March 1990. TANZANIA, 1991–92: Planning Commission, Tanzania Bureau of Statistics, Tanzania Demo- graphic and Health Survey 1991/1992 (Demo- graphic and Health Surveys, Macro International, June 1993). 1994: Planning Commission, Tanzania Bureau of Statistics, Tanzania Knowledge, Attitudes and Practices Survey 1994 (Demographic and Health Surveys, Macro International, July 1995). 1996: Planning Commission, Tanzania Bureau of Statistics, Tanzania Demographic and Health Survey 1996 (Demographic and Health Surveys, Macro International, August 1997). 1999: DHS, with National Bureau of Statistics. TOGO, 1988: Unité de Recherche Démographique, Université de Benin, Enquête Démographique et de Santé au Togo 1988 (Demographic and Health Surveys, Institute for Resource Development, Macro Systems, Decem- ber 1989), p. 45. 1998: Direction de la Statistique, Enquete Demographique et de Sante au Togo 1998- Rapport Preliminaire, July 1998. UGANDA, 1988–89: Ministry of Health, Uganda Demographic and Health Survey 1988/ 1989 (Demographic and Health Surveys, Insti- tute for Resource Development, Macro Systems, October 1989), p. 33. 1995: Statistics Department, Uganda Demo- graphic and Health Survey 1995 (Demographic and Health Surveys, Macro International, Au- gust 1996). 2000–2001: DHS, with Uganda Bureau of Sta- tistics. ZAMBIA, 1992: University of Zambia, Central Statistical Office, Zambia Demographic and Health Survey 1992 (Demographic and Health Surveys, Macro International, March 1993). 1996: Central Statistical Office, Ministry of Health, Zambia Demographic and Health Sur- vey 1996 (Demographic and Health Surveys, Macro International, September 1997). 2001–02: DHS, with Central Statistical Office. ZIMBABWE, 1984: Zimbabwe Reproductive Health Survey 1984 (National Family Planning Council and Westinghouse Public Applied Sys- tems, 1985), p. 121. 1988: Central Statistical Office, Ministry of Fi- nance, Economic Planning and Development, Zimbabwe Demographic and Health Survey, 1988 (Demographic and Health Surveys, Insti- tute for Resource Development, Macro Systems, December 1989), p. 51. 1994: Central Statistical Office, Zimbabwe De- mographic and Health Survey 1994 (Demo- graphic and Health Surveys, Macro Interna- tional, September 1995). 1999: DHS, with Central Statistical Office. LATIN AMERICA/CARIBBEAN BELIZE, 1991: Central Statistical Office, Min- istry of Finance; Belize Family Life Association; Ministry of Health, Division of Reproductive Health; and Centers for Disease Control, 1991 Belize Family Health Survey Final Report May, 1992 (U.S. Department of Health and Human Services, Public Health Service, Centers for Dis- ease Control, Atlanta, May 1992). BOLIVIA, 1983: R.B. Coloma and B.P. de Ormacnea, Bolivia ’83: Encuesta de Prevalencia de Medicamentos (Consultora Boliviana de Reproduccion Humana and Westinghouse Health Systems), pp. 87, 95, and 100. 1989: Encuesta Nacional de Demografía y Salud 1989 (Instituto Nacional de Estadistica, Demo- graphic and Health Surveys, Institute for Resource Development, Macro Systems, 1990), p. 42. 1993–94: Instituto Nacional de Estadistica, Bo- livia Encuesta Nacional de Demografia y Salud 1994 (Demographic and Health Surveys, Macro International, October 1994). 1998: DHS, with Instituto Nacional de Estadistica, Bolivia Encuesta Nacional de Demografia y Salud 1994 (Demographic and Health Surveys, Macro International, Decem- ber 1998). 2003: DHS, with Instituto Nacional de Estadistica. BRAZIL, 1986: Sociedade Civil Bem-Estar Familiar no Brasil (BEMFAM) and Demographic and Health Surveys, Brazil Demographic and Health Survey, 1986 Preliminary Report (Insti- tute for Resource Development/Westinghouse, December 1986), p. 22. 1996: Sociedade Civil Bem-Estar Familiar no Brasil (BEMFAM) and Demographic and Health Surveys, Brasil Pesquisa Nacional Sobre Demografia e Saude 1996 (Macro International, March 1997). COLOMBIA, 1980: Ministerio de Salud de Colombia, Second Contraceptive Prevalence Survey Colombia 1980 (Westinghouse Health Systems, May 1982), pp. 43 and 47. 1986: Corporación Centro Regional de Población, Ministerio de Salud de Colombia, Encuesta de Prevalencia, Demografía y Salud 1986 (Demographic and Health Surveys, Insti- tute for Resource Development/Westinghouse), p. 52. 1990: PROFAMILIA (Asociación Pro- Bienestar de la Familia Colombiana), Colombia, Encuesta de Prevalencia Demográfica y Salud 1990—Informe Preliminar (Demographic and Health Surveys, Institute for Resource Develop- ment, Macro Systems, October 1990), p. 13. 1995: Asociacion Pro-Bienestar de la Familia Colombiana, Colombia Encuesta Nacional de Demografia y Salud 1995 (Demographic and Health Surveys, Macro International, October 1995). 2000: DHS, with PROFAMILIA. COSTA RICA, 1981: L. Rosero, Fecundidad y Anticoncepcion en Costa Rica 1981 (San Jose: Asociación Demográfica Costarricense,1981), Tables 27 and 35. 1986: Centers for Disease Control, The Costa Rica Fertility and Health Survey, 1986: Final English Language Report (Atlanta, 1987), Tables 6–1 and 7–4. A.12 Appendix A 1993: Centers for Disease Control, Fecunidad y Formacion de la Familia- Encuesta Nacional de Salud Reproductiva de 1993, May 1994. CUBA, 1987: Sonia Catasus Cervera and Juan Carlos Alfonso Fraga, “La transicion de la fecundidad en Cuba”, paper presented at the Seminar on Fertility Transition in Latin America, Buenos Aires, Argentina, 3-6 April 1990, orga- nized by the International Union for the Scien- tific Study of Population. DOMINICAN REPUBLIC, 1980: J. Hob- craft and G. Rodríguez, The Analysis of Repeat Fertility Surveys: Examples from Dominican Re- public (World Fertility Survey Scientific Report No. 29, International Statistical Institute and World Fertility Survey, 1982), Table 12. 1983–84: Consejo Nacional de Población y Fa- milia (CONAPOFA) and Demographic and Health Surveys, Republica Dominicana Encues- ta Nacional del Uso de Anticonceptivos— Mujeres—Informe de Resultados (Santo Dom- ingo: Institute for Resource Development/West- inghouse, February 1987), p. 117. 1986: Consejo Nacional de Población y Familia (CONAPOFA) and Demographic and Health Surveys, Republica Dominicana Encuesta Demografía y Salud 1986 (Santo Domingo: In- stitute for Resource Development/Westinghouse, December 1987), p. 39. 1991: Instituto de Estudios de Poblacion y Desarrollo, PROFAMILIA, Republica Dominicana Encuesta Demografica y de Salud 1991 (Demographic and Health Surveys, Macro International, September 1992). 1996: Asociacion Dominicana Pro Bienestar de la Familia (PROFAMILIA), Republica Dominicana Encuesta Demografica y de Salud 1996 (Demographic and Health Surveys, Macro International, June 1997). 1999: DSH, with CESDEM. 2002: DHS, with CESDEM. ECUADOR, 1979–80: Instituto Nacional de Estadistica y Censos, Encuesta Nacional de Fecondidas Ecuador 1979, Anexo Estadistico (WFS, 1984). 1982: Ministerio de Salud Pública, Encuesta Nacional de Salud Materno Infantil y Variables Demográficas, Ecuador, 1982—Informe Final (Instituto Nacional de Investigaciones, Nutricionales y Medico Social, 1984), p. 99, Table 6.7. 1987: Centro de Estudios de Población y Paternidad Responsable, Ecuador Encuesta 1994–95: Institut Haitien de l’Enfance, Haiti Enquete Mortalite, Morbidite et Utilisation des Services 1994/1995 (Demographic and Health Surveys, Macro International, December 1995). 2000: DHS, with Institut Haitien de l’Enfance. 2004: DHS, with Institut Haitien de l’Enfance. HONDURAS, 1981: M. Suazo et al., Hondu- ras: Encuesta Nacional de Prevalencia del Uso de Anticonceptivos (Tegucigalpa: Ministerio de Salud Pública y Asistencia Social and Westinghouse Health Systems, 1983), Tables 6.1, 6.3, 7.2, and 7.3. 1984: B. Janowitz, P. Bailey, J. Ochoa, and M. Suazo, “Contraceptive Use and Fertility in Hon- duras, 1981–84,” Studies in Family Planning 18, 5 (September–October 1987), pp. 291–301. 1987: Honduran Ministry of Public Health, ASHONPLAFA, Epidemiology and Family Health Survey Honduras 1987—Final Report (Family Health International, May 1989), p. 185. 1996: Ministerio de Salud, Honduras Encuesta Nacional de Epidemiologia y Salud Familiar 1996- Informe Final (Centers for Disease Con- trol, November 1997). JAMAICA, 1983: D. Powell, Report on the Jamaican Contraceptive Prevalence Survey, 1983 (Kingston: National Family Planning Board; Maryland: Westinghouse Health Systems, 1984), Table 6–3. 1989: A National Family Planning Board Re- port, Contraceptive Prevalence Survey Jamaica, 1989—Final Report (December 1989), p. 153. 1993: A National Family Planning Board Re- port, Contraceptive Prevalence Survey Jamaica, 1993 (Atlanta: Centers for Disease Control, December 1994). 1997: A National Family Planning Board Re- port, Reproductive Health Survey Jamaica, 1997- Final Report (Atlanta: Centers for Dis- ease Control, February 1999). MEXICO, 1982: M.U. Fuentes et al., “Fecundidad, Anticoncepción, y Planificación Familar en Mexico,” Comercio Exterior 34, 7 (July 1984). 1987: Dirección General de Planificación Famil- iar, Secretaría de Salud, Mexico, Encuesta Nacional sobre Fecundidad y Salud 1987 (De- mographic and Health Surveys, Institute for Re- source Development/Westinghouse, March 1988), pp. 42 and 45. 2000: DHS, with National Institute of Public Health. Nacional de Demografía y Salud Familiar 1987 (Demographic and Health Surveys, Institute for Resource Development/Westinghouse, July 1987), Table 4. 1989: Centro de Estudios de Población y Paternidad Responsable, Ecuador Encuesta Demográfica y de Salud Materna e Infantil, Endemain—1989 (Centers for Disease Control, 1990), p. 56, Table 4.7. EL SALVADOR, 1985: Asociación Demo- gráfica Salvadoreña, El Salvador, Encuesta Nacional de Salud Familiar—FESAL 85 (De- mographic and Health Surveys, Institute for Re- source Development/Westinghouse, September 1988), p. 60. 1988: Centers for Disease Control, 1988 Fam- ily Health Survey- Final English Language Re- port, December 1989. 1993: El Salvador Encuesta Nacional de Salud Familiar (National Family Health Survey)- Fesal-93, April 1994. GUATEMALA, 1983: R.S. Monteith, J.E. Anderson, M.A. Pineda, R. Santiso, and M. Oberle, “Contraceptive Use and Fertility in Gua- temala,” Studies in Family Planning 16, 5 (Sep- tember–October 1985), p. 282. 1987: Ministerio de Salud Pública y Asistencia Social, Guatemala Encuesta Nacional de Salud Materno–Infantil 1987 (Demographic and Health Surveys, Institute for Resource Development/ Westinghouse, March 1989), p. 48. 1995: Ministerio de Salud Publica y Asistencia Social, Guatemala Encuesta Nacional de Salud Maternal Infantil 1995 (Demographic and Health Surveys, Macro International, October 1996). 1997 (In-depth): DHS, with Instituto Nactional de Estadistica. 1998–99: DHS, with Instituto Nacional de Estadistica (interim). HAITI, 1983: M. Ayad, F. Pierre, and H. Jemai, Planification Familiale, Fécondité et Santé en Haïti 1983 (Département de la Santé Publique et de la Population, Westinghouse Public Applied Sys- tems, August 1985), p. 87. 1987: Institut Haitien de l’Enfance, Haiti L’Enquete Sur la Mortalite, la Morbidite, et l’Utilisation des Services 1987 (Demographic and Health Surveys, Macro International). 1989: Child Health Institute, Haiti National Con- traceptive Prevalence Survey 1989—Preliminary Report (CDC/Division of Reproductive Health, May 1990), p. 26. Appendix A A.13 NICARAGUA, 1981: Instituto Nacional de Estadisticas y Censos, “Report on 1981 Survey” (Managua, 1986), Tables 7.2 and 7.10. 1992: Centers for Disease Control, Encuesta Sobre Salud Familiar Nicaragua 92-93- Informe Final, November 1993. 1997–98: DHS, with Instituto Nacional de Estadisticas y Censos. 1998: Ministerio de Salud, Republica de Nica- ragua Encuesta Nicaraguense de Demografia y de Salud, 1998- Informe Preliminar (Programa de Encuestas de Demografia y Salud, Macro International, September 1998). 2001: DHS, with Instituto Nacional de Estadisticas y Censos. PANAMA, 1984: Ministry of Health and United States CDC, Maternal–Child Health/Family Planning Survey, Panama 1984: Final English Language Report (Atlanta, 1986), Table 7–6. PARAGUAY, 1987: United Nations, Levels and Trends of Contraceptive Use as Assessed in 1988 (United Nations, 1989). 1990: Centro Paraguayo de Estudios de Población, Paraguay Encuesta Nacional de Demografía y Salud, 1990, Informe Preliminar (Demographic and Health Surveys, Institute for Resource Development/Macro Systems), p. 10, Table 5. 1995: Centers for Disease Control, Paraguay Encuesta Nacional de Demografia y Salud Reproductiva 1995/1996, October 1997. PERU, 1981: Aspectos Demográficos y Prevalencia de Anticonceptivos en el Peru, Resultados de la Primera Encuesta Nacional de Prevalencia de Anticonceptivos 1981 (Instituto Nacional de Estadistica, Westinghouse Health Systems, 1983), p. 110. 1986: Consejo Nacional de Población, Dirección General de Demografía, Instituto Nacional de Estadistica, Encuesta Demografía y de Salud Fa- miliar (Endes 1986)—Informe General (Demo- graphic and Health Surveys, Institute for Re- source Development, April 1988), p. 62. 1991: Instituto Nacional de Estadistica e Informatica, Peru Encuesta Demografica y de Salud Familiar 1991/1992 (Demographic and Health Surveys, Macro International, Septem- ber 1992). 1996: Instituto Nacional de Estadistica e Informatica, Peru Encuesta Demografica y de Salud Familiar 1996- Informe Principal (De- mographic and Health Surveys, Macro Interna- tional, June 1997). 2002: DHS, with Instituto Nacional de Estadisticas. PUERTO RICO, 1982: C.W. Warren, “Fertil- ity Determinants in Puerto Rico, Draft Report” (Atlanta: CDC, 1986), Table 4.1. 1995: Centers for Disease Control, Puerto Rico Encuesta de Salud Reproductiva 1995/1996, May 1998. TRINIDAD AND TOBAGO, 1987: Family Planning Association of Trinidad and Tobago, Trinidad and Tobago Demographic and Health Survey 1987 (Demographic and Health Surveys, Institute for Resource Development/ Westinghouse, November 1988), pp. 18 and 31. MIDDLE EAST/NORTH AFRICA ALGERIA, 1986: Centre National d’Analyses pour la Planification, Enquête National sur la Fécondité—Rapport National Final (March 1989). 1992: Office Nationale des Statistiques, “Alge- ria Maternal and Child Health Survey,” Studies in Family Planning 25, 3 (May/June 1994), pp. 191-195. EGYPT, 1980: A.M. Khalifa, H.A.A.H. Sayed, M.N. El-Khorazaty, A.A. Way, Family Planning in Rural Egypt 1980, A Report on the Results of the Egypt Contraceptive Prevalence Survey (Population and Planning Board and Westinghouse Health Systems, December 1982). 1981–82: United Nations, Recent Levels and Trends of Contraceptive Use as Assessed in 1988 (New York: United Nations, 1989). 1984: H.A.A.H. Sayed, M.N. El-Khorazaty, and A.A. Way, Fertility and Family Planning in Egypt, 1984 (Egypt National Population Council and Westinghouse Public Applied Systems, Decem- ber 1985), pp. 155–156, Table 9.4. 1988: Egypt Demographic and Health Survey 1988 (Egypt National Population Council and Demographic and Health Surveys, Institute for Resource Development, Macro Systems, Octo- ber 1989), p. 95, Table 6. 1993: Egypt Demographic and Health Survey 1992: Preliminary Report. National Population Council and Demographic and Health Surveys, Macro International Inc., March 1993. 1995: Egypt Demographic and Health Survey 1995. National Population Council and Demo- graphic and Health Surveys, Macro Interna- tional, Inc., September 1996. 1997: DHS, with El-Zanaty & Associates (in- terim). 1997: Egypt Demographic and Health Survey 1997. Macro International, Inc., June 1998. 2000: DHS, with National Population Council. 2002: DHS, with Ministry of Health and Popu- lation/El-Zanaty & Associates. 2003: DHS, with Ministry of Health and Popu- lation/El-Zanaty & Associates. JORDAN, 1983: J.E. Anderson, L. Morris, and A. Abdel-Aziz, Jordan Fertility and Family Health Survey 1983 (Amman: Department of Statistics; Atlanta: CDC, 1983), Table 7–1. 1985: C. Warren, L. Morris, and F. Higari, Jor- dan Husbands’ Fertility Survey 1985; Report of Principal Findings (Amman: Department of Sta- tistics; Atlanta: CDC, 1987), Table 7–6. 1990: Department of Statistics, Ministry of Health, Jordan Population and Family Health Survey 1990 (Demographic and Health Surveys, Institute for Resource Development/Macro In- ternational, June 1991). 1997: Department of Statistics, Jordan Popu- lation and Family Health Survey 1997 (Demo- graphic and Health Surveys, Macro Interna- tional, December 1998). 2002: DHS, with Department of Statistics. KUWAIT, 1987: Rashoud, Rashid Al and Samir Farid, eds. State of Kuwait Ministry of Health, Kuwait Child Health Survey 1987, 1991. MOROCCO, 1980: Ministère de la Santé Publique, Enquête Nationale sur la Planification Familiale et la Fécondité au Maroc 1979–1980, Volume 4 (WFS, 1984), p. 286, Table 4.4.1. 1983–84: Planification Familiale, Fécondité et Santé au Maroc 1983–84: Rapport de l’Enquête Nationale de Prévalence Contraceptive (Ministère de la Santé Publique and Westinghouse Public Applied Systems, February 1985), p. 79. 1987: M. Azelmat, M. Ayad, and H. Belhachmi, Enquête Nationale sur la Planification Familiale, la Fécondité et la Santé de la Population au Maroc 1987 (Ministère de la Santé Publique and De- mographic and Health Surveys, Institute for Re- source Development/Westinghouse, March 1989), p. 50. 1992: Ministere de la Sante Publique, Maroc Enquete Nationale sur la Population et la Sante 1992 (Demographic and Health Surveys, Macro International, August 1993). 1995: Ministere de la Sante Publique, Maroc Enquete de Panel sur la Population et la Sante 1995 (Demographic and Health Surveys, Macro International, January 1996). A.14 Appendix A 1983: S.N. Mitra and G.N. Kamal, Bangladesh Contraceptive Prevalence Survey 1983—Final Report (Mitra and Associates, July 1985), Table 3. 1985: S.N. Mitra, Bangladesh Contraceptive Prevalence Survey 1985—Final Report (Mitra and Associates, December 1987), Table 5.1. 1989: Md. Najmul Huq and John Cleland, Bangladesh Fertility Survey 1989 (Dhaka: NIPORT, March 1990), p. A62. 1991: Mitra and Associates, Bangladesh Con- traceptive Prevalence Survey, 1991, draft tables (Dhaka, n.d.). 1993–94: Ministry of Health and Family Wel- fare, Bangladesh Demographic and Health Survey 1993/1994 (Demographic and Health Surveys, Macro International, December 1994). 1996–97: Ministry of Health and Family Wel- fare, Bangladesh Demographic and Health Survey 1996/1997 (DHS, with NIPORT, Mitra and Associates, and Macro International, De- cember 1997). 1999–2000: DHS, with Mitra & Associates/ NIPORT. 2003–04: DHS, with Mitra & Associates/ NIPORT. CAMBODIA, 1998: DHS, with SAWA Cam./ National Institute of Public Health. 2000: DHS, with National Institute of Statis- tics/MOH. CHINA, 1982: S. Qui, S. Wu, and M. Wang, “Birth Control of Women of Reproductive Age,” in An Analysis of a National One-per-Thousand Population Sample Survey in Birth Rate: Popu- lation and Economics, Special Issue (Beijing: Institute of Population and Economic Research, 1983). 1985: State Family Planning Commission, Popu- lation and Family Planning Statistics 1985 (Beijing, 1986). 1988: State Family Planning Commission, Na- tional Fertility Sample Survey (National Results), p. 20, Table 2–10; and pp. 275–278, Table 4–9. 1992: Centers for Disease Control, 1992 Na- tional Fertility and Family Planning Survey, China. HONG KONG, 1982: Family Planning Asso- ciation of Hong Kong, Family Planning Knowl- edge, Attitude and Practice in Hong Kong, 1982 (Hong Kong, 1984), Tables 7.1.1–1 and 7.4.1–1. 1987: The Task Force on the Study of Family Planning Knowledge, Attitude and Practice in Hong Kong 1987 (Family Planning Association of Hong Kong, 1989), p. 51, Table 6.1.1; and p. 55, Table 6.5.1. INDIA, 1980: M.E. Khan and C.V.S. Prasad, Family Planning Practices in India: Second All India Survey (Baroda: Operations Research Group, 1983), pp. 133 and 142. 1982: The sterilization percentage is taken from the 1982–83 estimate of the Ministry of Health and Family Welfare, with the percentage of va- sectomies and tubal ligations being estimated from annual reports of the numbers of male and female sterilizations, using the attrition factors estimated by the government of India, and with adjustment to the grand total estimated by the government of India. Other figures were taken from the 1980 Operations Research Group re- port, with an adjustment of the 5.6% conven- tional contraceptive users reported in Table 7.4 being split between pill and IUD users on the basis of figures reported in Table 7.8. 1988–89: Third All-India Family Planning Sur- vey, 1988–89 (Baroda: Operations Research Group), pp. 103 and 105. 1992: International Institute for Population Sci- ences, India National Family Health Survey 1992/1993, August 1995. 1998-99: DHS, with International Institute for Population Sciences. INDONESIA, 1985: Biro Pusat Statistik, A Brief Note on the Results of the 1985 Intercensal Popu- lation Survey, Seri Supas No. 4 (Jakarta, 1986), Table 12. 1987: Central Bureau of Statistics, National Fam- ily Planning Coordinating Board, National In- donesia Contraceptive Prevalence Survey 1987 (Demographic and Health Surveys, Institute for Resource Development/Westinghouse, January 1989), p. 50. 1991: Central Bureau of Statistics, National Family Planning Coordinating Board, Indone- sia Demographic and Health Survey 1991 (De- mographic and Health Surveys, Macro Interna- tional, October 1992). 1994: Central Bureau of Statistics, National Family Planning Coordinating Board, Indone- sia Demographic and Health Survey 1994 (De- mographic and Health Surveys, Macro Interna- tional, October 1995). 1997: DHS, with Central Bureau of Statistics/ NFPCB/MOH. 2002–03: DHS, with Central Bureau of Statis- tics/NFPCB/MOH. 2003–04: DHS, with SEIS – Ministére de la Santé. OMAN, 1988: Suleiman, Murtadha J., Ahmed Al-Ghassany, and Samir Farid, eds. Ministry of Health, Oman Child Health Survey 1988, 1992. NEPAL, 1996: Ministry of Health, Nepal Fam- ily Health Survey 1996 (Demographic and Health Surveys, Macro International, March 1997). TUNISIA, 1983: M. Ayad and Y. Zoughlami, “Fécondité et Planification Familiale en Tunisie 1983,” Rapport sur les Résultats de l’Enquête Tunisienne sur la Prévalence de la Contracep- tion (Ministère de la Famille et de la Promotion de la Femme, Office National de la Famille et de la Population, and Westinghouse Public Applied Systems, July 1985), p. 87. 1988: Office Nationale de la Famille et de la Popu- lation, Enquête Démographique et de Santé en Tunisie 1988 (Demographic and Health Surveys, Institute for Resource Development, Macro Sys- tems, October 1989), p. 68. TURKEY, 1983: Hacettepe Institute of Popula- tion Studies, 1983 Turkish Population and Health Survey (Ankara, 1987), Tables II–5 and VI–13. 1988: Hacettepe Institute of Population Studies, 1988 Turkish Population and Health Survey (Ankara, 1989), Tables II.6.18 and II.4.1. 1993: Ministry of Health, General Directorate of Mother and Child Health and Family Plan- ning, Turkey Demographic and Health Survey 1993 (Demographic and Health Surveys, Macro International, October 1994). 1998: DHS, with Hacettepe Institute of Popula- tion Studies. YEMEN, 1991–92: Central Statistical Organi- zation, Pan Arab Project for Child Development, Yemen Demographic and Maternal and Child Health Survey 1991/92: Preliminary Report (De- mographic and Health Surveys, Macro Interna- tional, September 1992). 1997: Central Statistical Organization, Yemen Demographic and Maternal and Child Health Survey1997 (Demographic and Health Surveys, Macro International, April 1998). ASIA BANGLADESH, 1981: S. Waliullah and S.N. Mitra, “The Contraceptive Prevalence Studies,” in Recent Trends in Fertility and Mortality in Bangladesh (Dhaka: Population and Develop- ment Planning Unit, Planning Commission, De- cember 1984). Appendix A A.15 KOREA, Republic of, 1982: Korean Institute for Population and Health, Report on the 1982 Korean National Family Planning and Health Survey (Seoul, 1982), pp. 119–120 and 172. 1985: J.N. Hun, H.S. Kaun, and L.J. Kum, “Per- sonal Networks and the Adoption of Family Plan- ning in Rural Korea,” in 1985 Survey of Fertility and Family Health (Seoul: Korea Institute for Population and Health, 1985). 1988: M. Moon, C. Lee, Y. Oh, and S. Lee, 1988 Survey Report on the National Fertility and Fam- ily Health Status (Seoul: Korean Institute for Health and Social Affairs, June 1989), p. 73. MALAYSIA, 1984: United Nations, World Population Trends and Policies: 1987 Monitor- ing Report (1987), Tables 5.1 and 5.2. 1994: National Population and Family Devel- opment Board (NPFDB) Malaysia, Family Pro- file Malaysia. Kuala Lumpur: NPFDB (1999), Figure 5.4. MYANMAR, 1991: Myanmar Population Changes and Fertility Survey 1991. 1997: Department of Population, Myanmar Fertility and Reproductive Health Survey 1997- Preliminary Report, October 1998. NEPAL, 1981: Nepal Contraceptive Prevalence Survey Report 1981 (Nepal Family Planning and Maternal–Child Health Project, Ministry of Health, and Westinghouse Health Systems, 1983), Table 8.1. 1986: Ministry of Health, Nepal Fertility and Family Planning Survey Report 1986 (Kathmandu, 1987), Tables 10.1, 10.9, 10.18, and 10.23. 1987: DHS, with New ERA. 1992: Ministry of Health, Nepal Fertility, Family Planning, and Health Status Survey: A Prelimi- nary Report (Kathmandu, 1992). 1996: DHS, with Ministry of Health/New ERA. 2001: DHS, with New ERA. PAKISTAN, 1985: Population Welfare Divi- sion, Monitoring and Statistics Wing, Pakistan Contraceptive Prevalence Survey, 1984–85 (Islamabad: Ministry of Planning and Develop- ment, Government of Pakistan, 1986), Tables VII.10, VII.11, and V.7. 1990–91: National Institute of Population Stud- ies, Pakistan Demographic and Health Survey 1990/91 (Demographic and Health Surveys, In- stitute of Resource Development/Macro Inter- national, August 1991). 1994: Ministry of Population Welfare, Pakistan Contraceptive Prevalence Survey 1994/1995- Final Report (Population Council, March 1998). PHILIPPINES, 1983: J. Cabibon, “Current Contraceptive Practice, Philippines and Its Thir- teen Regions,” Paper 1B (Manila: University of the Philippines, 1985). 1986: M.B. Concepcion, I.Z. Feranil, and E.A. de Guzman, “1986 Contraceptive Prevalence Survey: Philippines and Its Thirteen Regions” (University of the Philippines, Population Insti- tute, n.d., unpublished), Table 2. 1988: M.B. Concepcion (ed.), First Report on the 1988 National Demographic Survey (Uni- versity of the Philippines, Population Institute, n.d., unpublished). 1993: National Statistics Office, Philippines National Demographic Survey 1993 (Demo- graphic and Health Surveys, Macro Interna- tional, May 1994). 1998: National Statistics Office, Philippines National Demographic and Health Survey 1998- Preliminary Report (Demographic and Health Surveys, Macro International, July 1998). 2003: DHS, with National Statistics Office/ Dept. of Health. SINGAPORE, 1982: S.C. Emmanuel, S.B. Li, T.P. Ng, and A.J. Chen, Third National Family Planning and Population Survey in Singapore 1982 (Singapore Family Planning and Popula- tion Board, 1984), Tables 4.2 and 4.6. SRI LANKA, 1981: United Nations Economic and Social Commission for Asia and the Pacific, The Use of Contraception in the Asian and Pa- cific Region, Population Research Leads, No. 21 (Bangkok, 1985), pp. 5 and 27. 1982: Department of Census and Statistics, Sri Lanka Contraceptive Prevalence Survey Report 1982 (Westinghouse Health Systems, 1983), Table 6.5. 1987: Department of Census and Statistics, Min- istry of Plan Implementation, Sri Lanka Demo- graphic and Health Survey 1987 (Demographic and Health Surveys, Institute for Resource De- velopment/Westinghouse, May 1988), p. 65. TAIWAN,1980, 1986: Taiwan Provincial Insti- tute of Family Planning and Health, Annual Re- port 1987 (Feb. 1988), p. 39, Table 7. 1985: M.C. Chang, R. Freedman, and T.H. Sun, “Trends in Fertility, Family Size Preferences, and Family Planning Practices: Taiwan 1961–1980,” Studies in Family Planning 12, 5 (May 1981). 1991: Employment of Low-Income Households in Taiwan, National Taiwan University. THAILAND, 1980: Chintana Pejaranonda and Aphichat Chamratrithirong, Fertility and Family Planning, 1980 Population and Housing Census, Subject Report No. 3, Bangkok (n.d.), table 12. 1981: J. Knodel, A. Chamratrithirong, N. Chayovan, and N. Debavalya, Fertility in Thai- land: Trends, Differentials and Proximate Deter- minants, Committee on Population and Demog- raphy Report No. 13 (Washington, DC: National Academy Press, 1982), Tables 34 and 36. 1984: P. Kamnuansilpa and A. Chamratrithirong, Fertility in Thailand: Results from the Contra- ceptive Prevalence Survey (Bangkok: National Family Planning Board, 1985), Tables 4.2, 5.2, 5.6, and 5.11. 1987: Institute for Population Studies, Chulalongkorn University, Thailand Demo- graphic and Health Survey 1987 (Demographic and Health Surveys, Institute for Resource De- velopment/Westinghouse, May 1988), p. 56. VIET NAM, 1988: Vietnam Demographic and Health Survey 1988 (National Committee for Population and Family Planning, Hanoi, Novem- ber 1990). 1994: Viet Nam Intercensal Demographic Sur- vey 1994- Major Findings. Statistical Publish- ing House, Ha Noi, May 1995. 1997: National Committee for Population and Family Planning, Viet Nam Demographic and Health Survey 1997, Hanoi, March 1999. 2002: DHS, with Commission for Pop. Fam. & Children/GSO. CAUCASUS AZERBAIJAN, 2001: Florina Serbanescu et al., eds., Reproductive Health Survey Axerbaijan, 2001 (Adventist Development and Relief Agency (ADRA) and collaborating agencies, and the Centers for Disease Control and Pre- vention (DRH/CDC)). ARMENIA, 2000: DHS, with Nat. Stat. Ser- vice/MOH. GEORGIA, 1999–2000: Florina Serbanescu et al., Reproductive Health Survey Georgia, 1999 (Republic of Georgia and Centers for Dis- ease Control and Prevention (DRH/CDC), Oc- tober 2001). A.16 Appendix A CENTRAL ASIA KAZAKHSTAN, 1995: DHS, with Institute of Obstetrics & Pediatrics, MOH. 1999: DHS, with National Institute of Nutri- tion. KYRGYZSTAN, 1997: Ministry of Health of the Kyrgyz Republic, Kyrgyz Republic Demo- graphic and Health Survey 1997 (Demographic and Health Surveys, Macro International, Au- gust 1998). 1997: DHS, with Settlmt. and Land Rec. Dep., Min. of Agr. TURKMENISTAN, 2000: DHS, with MCH/ MOH/MIT. UZBEKISTAN, 1996: Ministry of Health of the Republic of Uzbekistan, Uzbekistan Demo- graphic and Health Survey 1996 (Demographic and Health Surveys, Macro International, Sep- tember 1997). 2000: DHS, with Min. of Macroeconomics/ MOH. 2002: DHS, with Min. of Macroeconomics/ MOH. OTHER COUNTRIES MOLDOVA, 1997: Moldovan Ministry of Health, Centers for Disease Control, Reproduc- tive Health Survey Moldova, 1997- Final Re- port, December 1998. RUSSIA, 1996: All-Russian Centre for Public Opinion and Market Research; Centers for Dis- ease Control and Prevention, Division of Re- productive Health, USA; and 1996 Russia Women’s Reproductive Health Survey: A Study of Three Sites, May 1998. Appendix A A.17 Table A.2. Source of Supply for Modern Contraception Methods* Country Female Sterilization Pill Injection IUD Condom All Modern Methods Asia Bangladesh 1999/2000 Public 90.6 56.4 85.2 89.8 19.8 64.9 Private medical 3.7 30.2 2.3 3.1 52.4 21.9 Other private - 8.7 - 0.7 23.5 6.8 Other 4.9 4.0 11.3 6.0 2.8 5.4 Cambodia 2000 Public 92.0 38.2 56.6 29.1 26.9 45.5 Private medical 3.8 17.5 36.6 31.2 4.8 24.0 Other private - 43.1 2.7 1.3 54.6 24.6 Other 2.7 0.6 2.7 4.9 10.0 2.5 India 1998/99 Public 85.3 20.6 - 54.1 13.9 76.0 Private medical 13.1 40.6 - 43.1 39.3 17.3 Other private 1.1 34.8 - 1.5 37.3 5.3 Other 0.1 0.7 - 1.0 0.7 0.3 Indonesia 2003 Public 66.1 18.9 19.8 39.8 3.5 29.6 Private medical 33.9 55.0 76.4 54.0 85.3 61.0 Other private - 23.1 2.6 2.7 7.7 7.2 Other - 2.9 1.1 3.3 3.6 2.2 Nepal 2001 Public 85.8 55.3 86.0 64.3 46.0 79.4 Private medical 6.8 7.6 5.1 11.0 4.2 7.7 Other private 1.1 30.1 7.7 18.5 38.1 7.3 Other 6.2 7.1 1.3 4.5 11.7 4.8 Pakistan 2001 Public 86.1 40.0 62.4 65.0 17.3 54.1 Private medical 7.8 4.4 16.5 16.6 2.1 9.5 Other private 6.1 43.2 20.7 16.6 74.0 32.1 Other - 12.5 0.5 1.9 6.5 4.3 Philippines 1998 Public 65.6 76.4 92.0 82.4 41.4 72.0 Private medical 32.7 22.7 7.5 15.8 54.1 26.4 Other private 1.1 0.9 0.5 1.2 3.8 1.3 Other 0.1 - - - 0.7 0.1 Sri Lanka 1987 Public 94.7 66.4 66.8 95.0 31.9 85.3 Private medical 2.9 11.8 31.7 5.0 3.8 6.7 Other private - 18.0 - - 50.3 4.0 Other 0.6 3.3 1.5 - 12.2 2.0 Thailand 1987 Public 91.6 70.1 86.6 96.7 50.7 83.6 Private medical 8.0 5.1 11.7 3.3 5.7 7.9 Other private - 21.6 1.1 - 39.9 7.0 Other - 3.2 0.6 - 0.8 1.0 Viet Nam 2002 Public 99.8 65.1 - 93.9 40.4 74.8 Private medical - 32.8 - 5.7 56.9 23.9 Other private - 0.3 - 0.2 0.1 0.2 Other 0.2 1.8 - 0.1 2.6 1.2 Latin America Bolivia 1998 Public 62.7 19.1 19.6 49.6 8.3 41.5 Private medical 36.6 79.0 79.4 49.5 78.6 55.8 Other private - 1.6 - 0.2 2.6 0.7 Other 0.4 0.2 0.5 0.3 3.4 0.7 Brazil 1996 Public 70.9 7.8 3.9 47.4 9.3 43.1 Private medical 27.2 90.5 94.3 51.5 77.1 54.1 Other private - 1.2 1.8 - 7.3 1.1 Other 0.4 0.4 - 1.1 3.8 0.7 Colombia 2000 Public 43.0 6.5 8.0 42.3 1.4 27.4 Private medical 56.8 90.0 91.0 57.6 80.3 69.4 Other private - - - - - - Other - 2.6 0.8 0.1 13.9 2.3 Appendix A A.18 Table A.2. Source of Supply for Modern Contraception Methods* Country Female Sterilization Pill Injection IUD Condom All Modern Methods Dominican Republic 2002 Public 52.6 12.9 56.4 48.2 3.8 34.8 Private medical 45.5 5.6 28.7 48.0 3.8 26.3 Other private - 74.9 13.7 1.1 75.8 33.1 Other 1.8 6.6 1.1 2.6 16.6 5.7 Ecuador 1987 Public 67.7 34.4 35.0 27.0 26.3 46.5 Private medical 31.4 46.9 45.0 64.2 57.9 44.7 Other private - 3.4 10.0 0.3 5.3 1.4 Other 0.6 13.0 10.0 7.5 10.5 6.6 El Salvador 1985 Public 96.5 63.2 28.9 93.1 28.8 88.8 Private medical 2.5 4.1 21.4 5.9 - 3.3 Other private - 28.4 49.8 - 69.0 6.4 Other 1.0 4.3 - 1.0 2.2 1.4 Guatemala 1998/99 Public 43.2 20.7 36.1 26.9 7.3 34.5 Private medical 54.5 71.9 62.6 73.1 83.7 62.2 Other private - 2.6 0.5 - - 0.5 Other 0.9 4.9 0.9 - - 1.4 Haiti 2000 Public 55.5 21.9 24.0 - 4.5 24.1 Private medical 23.4 41.2 25.8 33.2 37.4 30.4 Other private 18.1 24.3 39.4 66.8 4.8 28.2 Other 2.2 12.6 10.8 - 52.6 16.9 Mexico 1987 Public 78.9 32.5 12.9 76.6 40.3 61.7 Private medical 20.5 2.0 4.5 19.6 - 14.3 Other private - 62.9 79.2 - 54.6 21.8 Other 0.6 2.3 1.8 3.8 3.1 1.9 Nicaragua 2001 Public 66.9 58.1 73.2 59.6 32.6 58.0 Private medical 31.3 8.0 10.4 36.0 6.2 18.4 Other private - 31.2 14.6 0.8 51.1 19.5 Other 1.8 3.3 1.7 3.6 10.1 4.1 Paraguay 1990 Public 52.2 9.4 4.0 20.0 0.9 18.7 Private medical 38.9 3.4 7.1 48.2 3.8 18.5 Other private 7.6 81.6 82.6 28.8 84.0 58.1 Other 0.8 4.9 6.3 2.9 9.1 4.2 Peru 2000 Public 83.0 83.0 94.2 75.7 40.3 79.3 Private medical 13.7 13.2 3.7 16.3 55.7 16.6 Other private 1.8 1.9 1.1 6.1 0.7 2.2 Other 1.4 2.0 1.0 1.2 3.0 1.6 Trinidad and Tobago 1987 Public 67.1 30.6 14.3 43.8 28.7 38.4 Private medical 31.1 15.7 85.7 55.4 12.4 23.3 Other private - 53.2 - - 56.7 36.9 Other 1.3 0.3 - 0.8 0.3 0.6 Middle East/North Africa Egypt 2003 Public 34.0 14.8 82.0 61.2 14.0 41.2 Private medical 62.1 84.4 14.5 38.4 83.2 56.5 Other private - - 0.2 0.3 - 0.1 Other 4.0 0.9 3.4 0.1 2.8 2.2 Jordan 2002 Public 68.0 36.5 46.7 28.0 37.3 43.3 Private medical 32.0 63.2 53.3 72.0 61.7 56.5 Other private - - - - - - Other - - - 1.0 - 0.2 Morocco 1995 Public 83.8 58.2 - 83.2 35.3 62.6 Private medical 16.2 41.4 - 16.8 64.7 37.1 Other private - - - - - 0.2 Other - 0.2 - - - 0.2 Sudan 1990 Public 80.0 58.7 66.7 36.1 - 58.1 Private medical 13.3 4.8 33.3 61.1 - 13.1 Other private - 34.6 - - 100.0 26.2 Other 4.4 1.4 - 2.8 - 2.0 Appendix A A.19 Table A.2. Source of Supply for Modern Contraception Methods* Country Female Sterilization Pill Injection IUD Condom All Modern Methods Tunisia 1988 Public 96.7 40.6 31.3 88.8 41.2 76.5 Private medical 2.4 8.2 68.8 11.0 7.8 8.8 Other private - 50.1 - - 51.0 14.1 Other - 0.8 - 0.1 - 0.2 Turkey 1998 Public 76.9 26.1 29.3 71.8 27.8 55.8 Private medical 20.8 73.6 60.1 27.6 66.9 42.2 Other private - - 5.6 0.3 2.2 0.7 Other 0.4 0.4 - 0.1 2.2 0.7 Yemen 1997 Public 73.7 51.3 19.6 48.0 33.4 49.4 Private medical 21.6 45.1 75.1 51.4 61.8 47.5 Other private - - - - - - Other - 0.2 - 0.3 - 0.2 Sub-Saharan Africa Benin 2001 Public 74.2 35.3 77.8 89.6 8.2 45.5 Private medical 19.1 28.7 19.8 10.4 28.4 23.4 Other private - 30.2 2.4 - 55.2 26.7 Other - 3.5 - - 6.9 3.2 Botswana 1988 Public 91.4 96.5 95.6 93.5 69.9 94.2 Private medical 7.9 2.0 4.0 6.5 1.1 3.5 Other private - 1.2 - - 11.6 1.3 Other 0.6 0.3 - - 3.2 0.3 Burkina Faso 1998/99 Public 100.0 85.3 94.5 89.4 7.3 75.3 Private medical - 8.0 5.5 5.3 12.6 6.3 Other private - 2.9 - - 75.8 15.7 Other - 3.7 - 5.3 4.2 2.6 Burundi 1987 Public 100.0 85.1 97.4 87.3 - 86.7 Private medical - - 1.3 3.2 - 1.2 Other private - 14.9 1.3 9.5 54.7 9.3 Other - - - - 45.3 2.8 Cameroon 1998 Public 64.3 37.1 81.1 64.0 4.3 31.9 Private medical 34.8 54.9 16.6 36.0 36.5 39.5 Other private - 7.4 2.2 - 58.0 27.8 Other - 0.5 - - 0.6 0.4 Central African Rep. 1994/95 Public 64.9 59.6 78.5 50.0 26.4 49.3 Private medical 25.3 34.1 17.9 50.0 34.5 31.7 Other private - 4.7 - - 30.0 13.2 Other - - 3.6 - 5.1 2.5 Chad 1996/97 Public 77.8 60.5 91.6 100.0 22.7 59.3 Private medical 22.2 11.7 8.4 - 10.0 11.5 Other private - 3.1 - - 11.4 4.2 Other - 24.6 - - 53.6 24.4 Côte d'Ivoire 1998/99 Public 100.0 45.4 75.3 67.6 1.0 30.8 Private medical - 42.7 24.7 32.4 34.5 35.8 Other private - 11.9 - - 54.1 28.6 Other - - - - 8.0 3.6 Eritrea 2002 Public - 73.5 91.0 - 11.3 58.6 Private medical - 20.7 7.3 - 30.7 19.6 Other private - - - - - - Other - 5.7 1.7 - 58.0 21.8 Ethiopia 2000 Public 85.8 71.8 91.9 44.7 32.0 77.5 Private medical 14.2 21.5 8.0 55.3 18.0 15.5 Other private - 5.6 0.1 - 41.3 5.8 Other - 0.1 - - 2.3 0.3 Gabon 2000 Public 66.7 30.4 64.8 30.5 18.6 26.5 Private medical 30.7 67.8 35.2 69.5 44.6 50.7 Other private - 1.8 - - 28.1 17.2 Other - - - - 6.8 4.2 Appendix A A.20 Table A.2. Source of Supply for Modern Contraception Methods* Country Female Sterilization Pill Injection IUD Condom All Modern Methods Ghana 1998 Public 78.7 33.3 88.0 91.7 15.9 46.7 Private medical 21.3 60.1 10.9 8.3 68.1 46.1 Other private - 1.2 1.1 - 13.4 4.7 Other - 3.1 - - 1.9 1.4 Guinea 1999 Public 90.0 49.6 82.4 66.7 12.6 49.9 Private medical - 23.9 12.0 33.3 27.1 21.0 Other private - 22.6 5.7 - 38.9 21.1 Other - - - - 17.1 4.6 Kenya 2003 Public 53.9 48.5 61.5 48.9 16.1 45.8 Private medical 45.3 45.5 37.7 50.5 25.9 41.0 Other private - 2.2 - - 56.2 11.7 Other 0.8 3.8 0.9 0.5 1.8 1.6 Liberia 1986 Public 62.3 21.3 40.8 49.8 31.5 31.1 Private medical 35.1 60.2 50.1 50.2 1.7 53.9 Other private - 17.9 9.1 - 26.7 13.1 Other 2.6 0.6 - - 26.7 1.6 Madagascar 1997 Public 77.8 48.7 55.9 43.5 18.6 52.1 Private medical 16.4 43.9 38.0 54.4 45.7 39.2 Other private - 5.7 6.0 2.0 34.4 7.6 Other - 1.7 - - 1.3 0.6 Malawi 2000 Public 42.5 67.3 79.7 67.2 42.4 68.0 Private medical 17.2 19.2 15.4 12.9 5.8 15.3 Other private - 1.0 - - 43.8 4.0 Other 40.3 12.5 4.6 19.9 7.1 12.4 Mali 2001 Public 78.1 38.9 75.5 75.1 6.9 51.8 Private medical 3.8 45.6 19.9 22.4 43.8 33.6 Other private - 12.8 4.0 - 37.0 11.1 Other 5.1 0.6 0.3 - 7.4 1.4 Mauritania 2000/01 Public 61.3 77.4 83.5 61.9 32.6 69.2 Private medical - 19.8 4.4 31.2 48.5 22.4 Other private - 0.3 - - - 0.1 Other 38.7 0.8 9.9 6.9 15.8 6.5 Mozambique 1997 Public 98.8 70.9 93.1 98.0 33.9 82.7 Private medical 1.2 17.5 1.6 - 29.9 8.5 Other private - 7.8 4.7 - 3.3 4.6 Other - 0.2 - - 25.0 2.0 Namibia 2000 Public 71.8 86.3 95.8 53.3 72.1 77.4 Private medical 24.8 11.8 2.9 43.9 12.6 19.6 Other private - - 0.2 - 13.7 2.8 Other - 0.4 0.1 - 0.6 0.2 Niger 1998 Public 88.8 79.8 96.5 90.2 36.3 83.6 Private medical - 12.3 2.8 9.8 17.4 9.1 Other private - 8.0 0.8 - 46.3 6.9 Other - - - - - - Nigeria 2003 Public - 18.6 48.4 65.5 4.1 34.2 Private medical - 74.0 48.0 32.5 59.2 53.4 Other private - 1.9 - - 4.7 1.7 Other - 5.5 3.5 2.1 32.0 10.8 Rwanda 2000 Public 93.7 70.0 80.1 71.0 16.8 69.0 Private medical 6.3 28.8 19.5 29.0 39.2 22.6 Other private - - - - 39.1 7.2 Other - - - - 4.9 0.9 Senegal 1997 Public 66.6 73.6 92.1 66.8 22.9 68.3 Private medical 32.2 17.8 4.6 17.2 57.2 21.1 Other private 1.2 7.9 3.3 14.9 13.0 9.1 Other - - - - 5.4 0.7 Appendix A A.21 Table A.2. Source of Supply for Modern Contraception Methods* Country Female Sterilization Pill Injection IUD Condom All Modern Methods South Africa 1998 Public 76.4 73.2 93.0 53.1 77.1 83.6 Private medical 22.2 24.8 6.3 46.3 7.4 14.4 Other private - 0.2 - - 7.9 0.3 Other - 1.3 0.2 - 5.4 0.6 Tanzania 1999 Public 69.8 79.4 88.1 77.6 18.1 67.2 Private medical 26.9 17.7 11.9 22.4 38.8 21.8 Other private - 2.7 - - 42.2 10.4 Other - 0.2 - - - 0.1 Togo 1998 Public 87.8 37.6 91.6 82.9 14.9 48.0 Private medical 9.7 15.4 7.4 17.1 18.0 14.8 Other private - 42.3 0.5 - 66.3 35.8 Other 2.6 - 0.4 - 0.1 0.2 Uganda 2000/01 Public 67.3 30.7 46.6 66.4 9.1 36.0 Private medical 29.8 67.1 51.3 33.6 33.2 46.1 Other private - 1.7 1.3 - 52.6 15.7 Other - - 0.2 - 4.8 1.4 Zambia 2001/02 Public 40.1 67.1 83.1 32.1 39.2 60.9 Private medical 58.4 19.9 16.2 67.9 11.5 20.4 Other private - 12.2 - - 45.8 17.1 Other - 0.2 - - 1.3 0.4 Zimbabwe 1999 Public 61.7 80.5 84.4 53.4 40.1 76.7 Private medical 22.6 15.7 10.9 44.2 21.3 16.5 Other private - 0.6 - - 33.3 2.6 Other 13.4 3.0 4.7 2.4 3.0 3.8 Central Asia Republics Kazakhstan 1999 Public 99.5 85.5 100.0 94.6 50.2 89.5 Private medical - 7.7 - 4.6 25.2 6.9 Other private - - - - - - Other 0.5 4.9 - 0.7 15.5 2.5 Kyrgyzstan 1997 Public 100.0 90.1 99.2 98.8 85.5 96.9 Private medical - - 0.8 0.2 3.9 0.6 Other private - 3.7 - - 8.7 1.1 Other - 3.3 - - 1.0 0.3 Turkmenistan 2000 Public 100.0 96.4 100.0 99.2 84.0 98.5 Private medical - 3.6 - 0.6 9.8 1.0 Other private - - - - - - Other - - - - 3.0 0.2 Uzbekistan 1996 Public 100.0 88.3 100.0 98.7 96.5 98.3 Private medical - 2.8 - 0.2 0.9 0.3 Other private - 6.3 - - - 0.2 Other - 2.6 - - 2.6 0.2 Caucasus Armenia 2000 Public 98.8 95.8 100.0 97.7 69.7 88.2 Private medical 1.2 1.2 - 1.7 5.5 3.0 Other private - - - - - - Other - 2.9 - - 5.0 1.8 *Male sterilization and vaginal methods are omitted due to small numbers of users in some survey samples. Also, column totals may not add to 100% since "missing" and "don't know" replies are omitted. Note: Dashes mean the quantity is negligible. Appendix A A.22 Table A.3. Population, Number of All Women (15-49), and Married Women (MWRA) (15-49), for 2005, and Percent Using Contraception (latest survey), and Number of Users Country Population (000) in 2005* Women 15-49 (000) in 2005 % Married (latest est.) MWRA (000) in 2005 % MWRA Using Contraception and Year No. of Married Users, 2005 est. Asia Afghanistan 25,971 5,825 74.4 4,336 4.8 2000 208 Bangladesh 152,593 38,421 76.2 29,277 53.8 1999/00 15,751 Bhutan 2,392 558 62.0 346 - - - Cambodia 14,825 3,692 59.1 2,182 23.8 2000 519 China 1,322,273 361,724 75.3 272,344 83.8 1997 228,224 China, Hong Kong SAR 7,182 2,138 55.5 1,186 86.2 1992 1,022 India 1,096,917 275,525 75.1 206,920 48.2 1998/99 99,735 Indonesia 225,313 62,110 70.9 44,036 60.3 2002/03 26,554 Iran 70,675 20,000 60.8 12,161 72.9 1997 8,866 Korea, DPR 22,876 6,153 73.1 4,497 61.8 1990/92 2,779 Korea, Rep. 48,182 13,452 62.6 8,421 80.5 1997 6,779 Laos 5,918 1,440 72.1 1,038 32.2 2000 334 Malaysia 25,325 6,551 59.6 3,903 54.5 1994 2,127 Mongolia 2,667 778 62.6 487 67.4 2000 328 Myanmar 50,696 13,812 51.1 7,058 32.7 1997 2,308 Nepal 26,289 6,232 78.5 4,892 39.3 2001 1,923 Pakistan 161,151 37,455 71.1 26,630 27.6 2000 7,350 Papua New Guinea 5,959 1,461 71.2 1,040 25.9 1996 269 Philippines 82,809 21,482 59.6 12,804 46.5 1998 5,954 Singapore 4,372 1,171 61.7 722 62.0 1997 448 Sri Lanka 19,366 5,229 56.7 2,965 66.1 1993 1,960 Taiwan 23,023 5,808 64.7 3,758 75.5 - 2,837 Thailand 64,081 18,543 61.5 11,404 72.2 1996/97 8,234 Viet Nam 83,585 23,766 64.1 15,234 78.5 2002 11,959 Total/Mean 3,544,441 933,328 72.6 677,641 64.4 436,468 Latin America Argentina 39,311 9,824 62.7 6,160 - - - Bolivia 9,138 2,254 59.4 1,339 53.4 2000 715 Brazil 182,798 51,564 60.1 30,990 76.7 1996 23,769 Chile 16,185 4,237 56.5 2,394 - - - Colombia 45,600 12,366 51.2 6,331 76.9 2000 4,869 Costa Rica 4,327 1,173 74.1 869 75.0 1992/93 651 Cuba 11,353 3,048 62.1 1,894 73.3 2000 1,388 Dominican Republic 8,998 2,379 59.8 1,423 69.8 2002 993 Ecuador 13,379 3,545 62.8 2,226 65.8 1999 1,465 El Salvador 6,709 1,774 60.8 1,079 59.7 1998 644 Guatemala 12,978 3,092 65.8 2,034 38.2 1998/99 777 Guyana 768 222 31.7 70 37.3 2000 26 Haiti 8,549 2,208 58.7 1,296 27.4 2000 355 Honduras 7,257 1,804 58.1 1,048 61.8 2001 648 Jamaica 2,701 736 49.8 366 65.9 1997 241 Mexico 106,385 29,534 60.1 17,750 68.4 1997 12,141 Nicaragua 5,727 1,434 56.8 814 68.6 2001 559 Panama 3,235 852 56.8 484 58.2 1984 282 Paraguay 6,160 1,541 61.3 944 57.4 1998 542 Peru 27,968 7,333 56.1 4,114 68.9 2000 2,835 Puerto Rico 3,915 1,036 58.4 605 77.7 1995/96 470 Trinidad and Tobago 1,311 384 54.4 209 38.2 2000 80 Uruguay 3,463 837 59.8 501 - - - Venezuela 26,640 7,024 51.2 3,596 - - - Total/Mean 554,856 150,203 58.9 88,538 70.4 53,451 Middle East/North Africa Algeria 32,877 9,118 45.7 4,169 64.0 2000 2,668 Egypt 74,878 19,450 62.8 12,215 60.0 2003 7,329 Iraq 26,555 6,446 54.4 3,504 13.7 1989 480 Jordan 5,750 1,449 51.7 749 55.8 2002 418 Kuwait 2,671 638 53.9 344 50.2 1996 173 Lebanon 3,761 1,081 64.2 694 61.0 1996 423 Libya 5,768 1,596 34.7 553 39.7 1995 220 Morocco 31,564 8,779 55.3 4,855 63.0 2003/04 3,058 Oman 3,020 641 62.0 397 23.7 1995 94 Saudi Arabia 25,626 6,023 59.3 3,574 31.8 1996 1,137 Sudan 35,040 8,578 55.5 4,761 8.3 1992/93 395 Syria 18,650 5,000 62.5 3,126 36.1 1993 1,129 Tunisia 10,042 2,878 56.2 1,618 60.0 1994 971 Turkey 73,302 19,797 69.0 13,660 63.9 1998 8,729 United Arab Emirates 3,106 635 76.8 487 27.5 1995 134 Yemen 21,480 4,654 67.4 3,137 20.8 1997 652 Total/Mean 374,092 96,762 59.8 57,843 48.4 28,009 Appendix A A.23 Table A.3. Population, Number of All Women (15-49), and Married Women (MWRA) (15-49), for 2005, and Percent Using Contraception (latest survey), and Number of Users Country Population (000) in 2005* Women 15-49 (000) in 2005 % Married (latest est.) MWRA (000) in 2005 % MWRA Using Contraception and Year No. of Married Users, 2005 est. Sub-Saharan Africa Angola 14,533 3,182 65.4 2,082 6.2 2001 129 Benin 7,103 1,702 73.4 1,249 18.6 2001 232 Botswana 1,801 458 39.1 179 40.4 2000 72 Burkina Faso 13,798 3,087 80.4 2,482 13.7 2003 340 Burundi 7,319 1,727 67.2 1,160 15.7 2000 182 Cameroon 16,564 3,964 66.9 2,652 19.3 1998 512 Central African Republic 3,962 925 69.4 642 27.9 2000 179 Chad 9,117 2,009 78.2 1,571 7.9 2000 124 Congo 3,921 866 56.2 487 - - - Congo, D.R. 56,079 12,509 67.9 8,498 31.4 2001 2,668 Côte d'Ivoire 17,165 4,097 61.3 2,511 15.0 1998/99 377 Eritrea 4,456 1,045 65.5 685 8.0 2002 55 Ethiopia 74,189 16,867 63.7 10,744 8.1 2000 870 Gabon 1,375 336 54.1 182 32.7 2000 59 Gambia 1,499 362 71.4 259 9.6 2000 25 Ghana 21,833 5,513 64.6 3,561 25.2 2003 897 Guinea 8,788 2,022 82.4 1,666 6.2 1999 103 Guinea-Bissau 1,584 346 68.7 238 7.6 2000 18 Kenya 32,849 8,447 61.4 5,186 38.3 2003 1,986 Lesotho 1,797 478 52.4 251 30.4 2000 76 Liberia 3,603 807 67.5 545 6.4 1986 35 Madagascar 18,409 4,246 62.8 2,667 18.8 2000 501 Malawi 12,572 2,773 71.5 1,983 30.6 2000 607 Mali 13,829 3,021 83.5 2,522 8.1 2001 204 Mauritania 3,069 724 58.8 426 8.0 2000/01 34 Mauritius 1,244 343 62.5 214 74.7 1991 160 Mozambique 19,495 4,746 74.4 3,531 5.6 1997 198 Namibia 2,032 482 38.7 186 43.7 2000 81 Niger 12,873 2,713 84.2 2,284 14.0 2000 320 Nigeria 130,236 29,818 70.0 20,873 12.6 2003 2,630 Rwanda 8,607 2,142 48.5 1,039 13.2 2000 137 Senegal 10,587 2,578 68.1 1,756 12.9 1997 226 Sierra Leone 5,340 1,238 67.6 837 - - 36 Somalia 10,742 2,363 67.4 1,593 - - - South Africa 45,323 12,420 43.2 5,365 56.3 1998 3,021 Swaziland 1,087 270 59.2 160 27.7 2000 44 Tanzania 38,365 9,128 65.8 6,007 25.4 1999 1,526 Togo 5,129 1,209 67.9 821 25.7 2000 211 Uganda 27,623 5,837 67.4 3,934 22.8 2000/01 897 Zambia 11,043 2,429 61.3 1,489 34.2 2001/02 509 Zimbabwe 12,963 3,109 61.1 1,900 53.5 1999 1,016 Total/Mean 693,901 162,336 65.6 106,414 20.4 21,301 Central Asia Republics Kazakhstan 15,364 4,359 62.9 2,742 66.1 1999 1,812 Kyrgyzstan 5,278 1,440 69.5 1,001 59.5 1997 595 Tajikistan 6,356 1,720 75.2 1,292 33.9 2000 438 Turkmenistan 5,015 1,398 61.7 862 61.8 2000 533 Uzbekistan 26,868 7,474 68.1 5,090 65.0 2002 3,308 Total/Mean 58,881 16,390 67.0 10,987 60.9 6,687 Caucasus Armenia 3,043 906 64.1 581 60.5 2000 351 Azerbaijan 8,527 2,546 64.0 1,629 55.4 2001 902 Georgia 5,026 1,333 64.8 864 40.5 1999/00 350 Total/Mean 16,596 4,785 64.2 3,073 52.2 1,603 Moldova, Russia, Ukraine Moldova 4,259 1,198 68.7 823 62.4 2000 514 Russian Federation 141,553 38,735 67.4 26,107 - - - Ukraine 47,782 12,585 67.3 8,470 67.5 1999 5,717 Total/Mean 193,594 52,519 67.4 35,401 67.0 6,231 Grand Total/Mean 5,436,360 1,416,323 69.2 979,897 59.0 553,750 *Excluding Moldova, Russia, and Ukraine, the other 113 countries contain 99.5% of the “Less Developed Regions” as classified by the U.N. Population Division. Note: Dashes in the last three columns mean no survey available. The other columns are from the UN 2002 estimates and projections and UN estimates for the percent married. Appendix A A.24 Table A.4. Number of Married Women of Reproductive Age (MWRA) (15-49) (000s) for Four Dates, and Percent Currently Married Country % Married (latest survey or est.)* 2005 2010 2015 2020 Asia Afghanistan 74.4 4,734 5,754 6,805 7,987 Bangladesh 1999/2000 76.2 27,653 30,941 33,824 36,554 Bhutan 62.0 320 373 424 474 Cambodia 2000 59.1 2,187 2,450 2,656 2,879 China 75.3 272,264 277,021 271,304 253,867 China, Hong Kong SAR 55.5 1,214 1,184 1,123 1,078 India 1998/99 75.1 209,590 228,888 245,925 260,218 Indonesia 2003 70.9 43,794 46,155 47,941 49,083 Iran 60.8 12,089 13,351 13,876 14,320 Korea, DPR 73.1 4,450 4,594 4,646 4,489 Korea, Rep. 62.6 8,311 8,058 7,673 7,136 Laos 72.1 1,038 1,182 1,333 1,492 Malaysia 59.6 3,903 4,279 4,589 4,871 Mongolia 62.6 483 518 537 554 Myanmar 51.1 7,160 7,733 8,078 8,233 Nepal 2001 78.5 5,326 6,076 6,821 7,516 Pakistan 71.1 27,078 31,086 34,849 38,624 Papua New Guinea 71.2 1,029 1,176 1,318 1,444 Philippines 1998 59.6 12,819 14,214 15,480 16,565 Singapore 61.7 714 719 696 653 Sri Lanka 1987 56.7 3,192 3,265 3,275 3,240 Taiwan 64.7 3,758 4,436 4,999 5,498 Thailand 1987 61.5 11,125 11,239 11,115 10,966 Viet Nam 2002 64.1 15,275 16,572 17,114 17,527 Total/Mean 65.8 679,509 721,264 746,400 755,268 Latin America Argentina 62.7 6,090 6,453 6,778 7,041 Bolivia 1998 59.4 1,339 1,502 1,660 1,814 Brazil 1996 60.1 31,121 32,427 33,391 34,430 Chile 56.5 2,472 2,573 2,585 2,580 Colombia 2000 51.2 6,331 6,764 7,078 7,303 Costa Rica 74.1 869 935 978 1,012 Cuba 62.1 1,889 1,876 1,733 1,575 Dominican Republic 2002 59.8 114 127 142 158 Ecuador 1987 62.8 2,156 2,326 2,493 2,627 El Salvador 1985 60.8 1,112 1,221 1,328 1,410 Guatemala 1998/99 65.8 1,982 2,304 2,651 3,020 Guyana 31.7 69 68 66 63 Haiti 2000 58.7 1,298 1,405 1,513 1,626 Honduras 58.1 1,038 1,190 1,337 1,471 Jamaica 49.8 351 360 359 352 Mexico 1987 60.1 17,964 19,291 20,252 20,737 Nicaragua 2001 56.8 800 914 1,024 1,122 Panama 56.8 484 520 553 580 Paraguay 1990 61.3 944 1,068 1,190 1,316 Peru 2000 56.1 4,114 4,490 4,809 5,064 Puerto Rico 58.4 585 592 592 591 Trinidad & Tobago 1987 54.4 207 204 192 185 Uruguay 59.8 501 514 527 540 Venezuela 51.2 3,629 3,946 4,198 4,435 Total/Mean 57.9 87,460 93,071 97,430 101,051 Middle East/North Africa Algeria 45.7 4,256 4,679 4,871 5,022 Egypt 2003 62.8 11,995 13,100 14,202 15,504 Iraq 54.4 3,829 4,446 5,090 5,744 Jordan 2002 51.7 740 848 963 1,051 Kuwait 53.9 360 409 448 482 Lebanon 64.2 625 660 686 698 Libya 34.7 560 610 658 700 Morocco 1992 55.3 4,815 5,141 5,402 5,664 Oman 62.0 367 429 488 543 Saudi Arabia 59.3 3,451 4,080 4,662 5,216 Sudan 1990 55.5 4,922 5,565 6,219 6,847 Syria 62.5 3,159 3,588 4,004 4,416 Tunisia 1988 56.2 1,627 1,724 1,755 1,755 Turkey 1998 69.0 13,661 14,558 15,314 15,878 United Arab Emirates 76.8 675 807 914 998 Yemen 1997 67.4 3,179 3,810 4,516 5,332 Total/Mean 58.2 58,222 64,454 70,192 75,849 Appendix A A.25 Table A.4. Number of Married Women of Reproductive Age (MWRA) (15-49) (000s) for Four Dates, and Percent Currently Married Country % Married (latest survey or est.)* 2005 2010 2015 2020 Sub-Saharan Africa Angola 65.4 2,387 2,774 3,177 3,654 Benin 2001 73.4 1,412 1,657 1,932 2,245 Botswana 1988 39.1 179 172 166 163 Burkina Faso 1998/99 80.4 2,360 2,780 3,262 3,813 Burundi 1987 67.2 1,194 1,451 1,618 1,832 Cameroon 1998 66.9 2,619 2,940 3,260 3,593 Central African Rep. 1994/95 69.4 651 711 784 864 Chad 1996/97 78.2 1,673 1,912 2,208 2,587 Congo 56.2 496 570 678 807 Congo, D.R. 67.9 8,634 10,020 11,649 13,677 Côte d'Ivoire 1998/99 61.3 2,580 2,917 3,303 3,711 Eritrea 2002 65.5 683 805 943 1,096 Ethiopia 2000 63.7 11,367 13,090 14,917 16,895 Gabon 2000 54.1 181 204 223 240 Gambia 71.4 262 298 337 379 Ghana 1998 64.6 3,500 3,949 4,388 4,847 Guinea 1999 82.4 1,695 1,931 2,219 2,546 Guinea-Bissau 68.7 238 274 320 378 Kenya 2003 61.4 5,079 5,677 6,443 7,470 Lesotho 52.4 249 243 238 235 Liberia 1986 67.5 496 564 648 754 Madagascar 1997 62.8 2,708 3,138 3,640 4,168 Malawi 2000 71.5 2,022 2,268 2,610 2,987 Mali 2001 83.5 2,480 2,905 3,439 4,048 Mauritania 2000/01 58.8 426 490 563 647 Mauritius 62.5 214 219 217 217 Mozambique 1997 74.4 3,541 3,874 4,265 4,710 Namibia 2000 38.7 190 209 226 239 Niger 1998 84.2 2,481 2,921 3,485 4,155 Nigeria 2003 70.0 20,884 23,687 26,798 30,250 Rwanda 2000 48.5 1,102 1,247 1,392 1,554 Senegal 1997 68.1 1,931 2,234 2,541 2,863 Sierra Leone 67.6 865 958 1,083 1,230 Somalia 67.4 1,309 1,509 1,755 2,019 South Africa 1998 43.2 5,490 5,361 5,242 5,212 Swaziland 59.2 156 153 150 147 Tanzania 1999 65.8 5,934 6,650 7,484 8,375 Togo 1998 67.9 985 1,142 1,319 1,518 Uganda 2000/01 67.4 4,063 4,911 6,020 7,397 Zambia 61.3 1,598 1,771 1,991 2,249 Zimbabwe 1999 61.1 1,985 2,085 2,165 2,239 Total/Mean 64.9 108,299 122,671 139,099 158,007 Central Asia Republics Kazakhstan 1999 62.9 2,666 2,632 2,525 2,482 Kyrgyzstan 1997 69.5 996 1,064 1,100 1,148 Tajikistan 75.2 1,278 1,430 1,570 1,699 Turkmenistan 2000 61.7 840 922 960 1,001 Uzbekistan 1996 68.1 4,978 5,488 5,782 6,090 Total/Mean 67.5 10,757 11,534 11,937 12,419 Caucasus Armenia 2000 64.1 568 550 513 490 Azerbaijan 64.0 1,612 1,681 1,640 1,591 Georgia 64.8 781 737 677 634 Total/Mean 64.3 2,961 2,968 2,829 2,715 Moldova, Russia, Ukraine Moldova 68.7 822 796 757 726 Russian Federation 67.4 26,648 24,784 22,816 21,793 Ukraine 67.3 8,282 7,748 7,010 6,452 Total/Mean 67.8 35,752 33,328 30,583 28,971 Grand Total 62.9 982,958 1,049,290 1,098,471 1,134,280 *Means are weighted according to numbers of women aged 15-49. Appendix A A.26 Table A.5a. Year 2005: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 6.3 1.0 0.2 0.1 0.0 - 0.9 0.1 4.0 Bangladesh 59.1 7.3 0.5 22.8 7.5 5.3 4.4 0.1 11.2 Bhutan 43.3 11.8 0.4 10.5 4.8 3.7 1.4 0.3 10.3 Cambodia 22.1 2.2 0.2 4.9 7.0 1.3 0.9 0.0 5.5 China 80.0 33.6 9.6 2.9 0.2 31.7 1.9 - 0.2 China, Hong Kong SAR 80.0 17.5 0.9 15.6 - 4.6 32.2 2.8 6.4 India 53.5 38.1 2.1 2.3 - 1.8 3.5 - 5.6 Indonesia 61.1 3.7 0.4 17.7 28.3 6.3 0.9 0.1 3.6 Iran 80.0 13.1 1.4 26.1 - 9.2 7.8 - 22.3 Korea, DPR 68.6 21.2 2.3 11.3 3.5 11.6 7.5 0.5 10.8 Korea, Rep. 80.0 29.6 12.0 1.9 - 10.9 14.8 - 11.0 Laos 38.2 10.0 0.3 9.6 4.6 2.8 1.0 0.3 9.6 Malaysia 72.7 10.0 0.3 14.8 2.2 9.8 9.0 0.4 26.4 Mongolia 64.4 19.6 1.8 11.6 4.0 9.9 6.0 0.5 11.0 Myanmar 37.4 9.2 0.9 9.0 6.5 2.7 0.9 0.2 8.0 Nepal 40.9 14.4 4.7 4.1 7.9 1.4 2.6 0.1 5.6 Pakistan 29.9 6.1 0.1 4.4 2.5 4.6 4.6 0.1 7.6 Papua New Guinea 32.4 9.2 0.2 6.2 7.4 0.7 0.7 0.1 8.0 Philippines 54.3 13.2 0.4 11.3 3.2 5.1 2.5 0.1 18.4 Singapore 76.1 23.9 3.1 10.8 2.7 14.6 10.0 0.5 10.6 Sri Lanka 71.9 25.6 4.0 6.0 5.0 3.3 3.6 - 24.4 Taiwan 82.0 27.1 1.6 4.9 - 22.1 18.0 - 8.3 Thailand 71.5 22.2 2.0 23.3 16.6 3.2 1.8 - 2.4 Viet Nam 79.2 4.5 0.3 4.9 1.8 43.3 6.3 - 18.1 Total/Mean 65.1 27.6 4.8 6.0 3.1 15.6 3.1 0.0 5.0 Latin America Argentina 64.7 19.7 1.9 11.6 3.9 10.0 6.1 0.5 11.0 Bolivia 55.5 9.6 0.3 5.9 1.9 11.7 3.3 0.1 22.7 Brazil 78.5 41.3 2.7 21.3 1.2 1.1 4.5 0.1 6.3 Chile 68.5 21.2 2.3 11.3 3.5 11.6 7.5 0.5 10.8 Colombia 76.9 27.5 1.0 12.0 4.3 12.6 6.2 0.8 12.5 Costa Rica 80.0 21.1 1.4 19.3 1.1 9.3 16.8 0.2 10.7 Cuba 72.5 22.6 2.7 11.1 3.1 13.1 8.7 0.5 10.7 Dominican Republic 71.9 45.6 0.2 15.2 1.4 3.4 0.9 - 5.2 Ecuador 60.0 18.0 1.4 11.9 4.5 8.2 4.6 0.4 11.2 El Salvador 64.8 30.9 0.5 9.5 8.0 4.0 3.7 0.1 8.0 Guatemala 50.2 19.5 1.6 9.7 0.8 5.3 2.5 1.7 9.1 Guyana 65.8 20.2 2.0 11.5 3.8 10.5 6.5 0.5 10.9 Haiti 28.8 3.8 0.4 3.4 12.3 0.5 2.5 0.0 5.8 Honduras 64.7 19.2 0.5 11.1 8.3 10.1 4.2 0.1 11.2 Jamaica 69.7 13.0 - 22.4 11.7 1.2 18.0 - 3.5 Mexico 72.7 30.0 1.3 9.1 3.4 15.9 4.0 - 9.0 Nicaragua 69.6 24.7 1.2 13.8 10.9 8.5 4.9 0.2 5.4 Panama 70.2 35.9 0.8 13.7 1.4 8.1 3.0 1.3 5.9 Paraguay 64.4 10.9 0.3 14.2 7.6 12.1 7.9 0.5 10.9 Peru 68.7 12.5 0.5 6.8 15.4 9.3 5.7 0.6 17.8 Puerto Rico 79.1 46.4 3.6 9.8 1.3 1.0 6.5 0.4 10.2 Trinidad and Tobago 64.6 19.8 1.9 11.4 3.8 10.2 6.3 0.5 10.8 Uruguay 65.2 19.9 1.9 11.5 3.8 10.3 6.3 0.5 10.9 Venezuela 60.8 18.3 1.5 11.7 4.2 8.6 5.0 0.4 11.0 Total/Mean 71.7 29.6 1.8 14.1 3.7 7.9 5.0 0.3 9.3 Middle East/North Africa Algeria 56.6 2.6 0.1 33.4 1.6 9.4 2.0 0.2 7.3 Egypt 57.9 2.5 0.1 10.6 5.9 32.4 1.5 0.3 4.6 Iraq 26.6 2.1 0.1 9.7 0.3 5.9 1.8 0.8 6.0 Jordan 58.4 4.3 0.1 9.8 2.0 22.0 3.5 0.4 16.3 Kuwait 49.0 3.9 0.1 24.3 1.5 9.2 2.3 0.6 7.2 Lebanon 65.1 7.5 0.3 13.2 4.5 19.8 4.1 0.5 15.4 Libya 44.9 5.3 0.1 11.8 0.9 12.2 0.7 0.1 13.7 Morocco 53.8 4.9 0.1 28.6 1.1 7.6 1.9 0.2 9.4 Oman 35.0 5.8 0.1 10.4 1.0 5.6 2.4 3.6 6.0 Saudi Arabia 46.7 4.7 0.3 14.1 2.9 12.1 2.1 0.4 10.0 Sudan 13.6 1.5 0.0 6.7 0.1 1.5 0.2 0.3 3.3 Syria 56.1 4.0 0.1 13.9 1.1 20.5 1.2 0.3 15.0 Tunisia 78.5 9.9 0.2 10.2 5.7 25.5 6.0 0.5 20.5 Turkey 67.0 4.5 - 4.7 0.5 21.0 8.7 0.6 27.0 United Arab Emirates 30.6 3.7 0.2 11.9 0.9 5.8 1.7 1.2 5.1 Yemen 41.8 3.1 0.2 8.6 2.5 7.0 0.9 0.2 19.4 Total/Mean 51.5 3.6 0.1 13.2 2.2 16.5 3.1 0.4 12.3 Appendix A A.27 Table A.5a. Year 2005: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 14.3 1.5 0.4 2.8 2.4 0.7 1.1 0.1 5.3 Benin 20.1 0.6 0.0 2.6 2.5 1.2 1.4 0.1 11.7 Botswana 53.4 9.5 0.7 20.5 7.5 8.5 2.5 0.1 4.1 Burkina Faso 17.9 0.3 0.0 3.0 1.9 0.8 1.7 0.2 10.1 Burundi 8.6 0.1 - 0.2 0.5 0.3 0.1 - 7.4 Cameroon 23.3 2.0 0.1 3.7 1.0 1.5 2.3 0.3 12.4 Central African Republic 19.7 0.7 0.0 2.2 0.9 0.6 1.3 0.2 13.8 Chad 3.6 0.2 - 0.6 0.2 - 0.2 - 2.4 Congo 17.8 3.3 0.2 4.4 2.8 0.8 0.6 0.1 5.7 Congo, D.R. 7.0 0.2 - 0.5 0.4 0.1 0.5 0.1 5.2 Côte d'Ivoire 19.2 0.5 0.0 5.2 1.7 1.1 2.2 0.0 8.3 Eritrea 9.0 0.2 0.1 1.5 2.7 0.5 0.7 0.0 3.3 Ethiopia 8.9 0.3 0.1 2.6 3.2 0.2 0.4 0.0 2.1 Gabon 31.2 2.8 0.0 5.8 1.4 0.7 4.3 0.1 16.1 Gambia 16.5 1.1 0.0 4.5 2.2 1.2 0.7 0.1 6.5 Ghana 25.7 2.6 0.0 5.2 3.9 1.0 2.7 0.9 9.4 Guinea 7.8 0.5 0.0 2.6 1.2 0.2 0.8 0.0 2.5 Guinea-Bissau 8.5 1.2 0.2 1.7 0.3 - 0.8 0.1 4.2 Kenya 38.3 6.3 0.0 8.6 12.6 2.7 1.3 0.0 6.8 Lesotho 31.6 3.5 0.0 9.4 7.4 3.4 1.4 0.1 6.4 Liberia 12.0 1.3 0.3 2.4 2.0 0.6 0.9 0.1 4.5 Madagascar 31.6 5.6 0.1 3.6 16.9 0.3 1.7 0.0 3.3 Malawi 27.3 2.3 0.0 4.0 6.6 0.9 0.9 0.2 12.4 Mali 7.6 0.4 0.0 3.1 2.4 0.2 0.4 0.0 1.0 Mauritania 8.7 0.2 0.0 2.7 0.9 0.8 0.9 0.0 3.1 Mauritius 79.2 7.6 0.2 22.2 4.4 3.0 14.1 0.4 27.4 Mozambique 6.7 0.8 0.1 1.6 2.8 0.4 0.5 0.0 0.5 Namibia 46.5 10.5 0.8 9.3 14.8 2.5 4.5 0.2 4.0 Niger 3.6 0.1 0.0 1.1 0.6 0.0 0.0 0.0 1.6 Nigeria 20.5 1.0 0.0 3.7 3.5 2.6 1.5 0.3 8.0 Rwanda 13.2 1.0 0.0 1.4 2.2 0.2 0.5 0.0 7.8 Senegal 14.0 0.9 0.0 4.5 2.2 2.1 0.8 0.3 3.1 Sierra Leone 15.5 1.7 0.2 5.1 0.7 2.0 0.8 0.2 4.7 Somalia 12.1 2.1 0.0 6.1 0.6 1.1 0.1 0.4 1.7 South Africa 58.8 16.8 2.0 11.2 20.1 3.2 2.4 0.1 3.0 Swaziland 48.6 9.3 0.6 12.9 11.2 4.7 2.0 0.5 7.5 Tanzania 32.1 3.7 0.0 7.2 7.6 0.9 3.0 0.0 9.7 Togo 31.6 1.0 0.0 3.2 3.4 2.4 1.9 0.4 19.4 Uganda 17.6 2.0 - 3.2 6.7 0.2 1.9 - 3.6 Zambia 38.1 3.3 0.0 12.7 5.2 0.5 3.8 0.1 12.4 Zimbabwe 61.8 7.4 0.5 33.6 8.5 3.3 3.1 0.1 5.3 Total/Mean 22.6 2.9 0.2 5.0 5.4 1.4 1.5 0.1 6.1 Central Asia Republics Kazakhstan 63.9 2.9 - 2.5 0.6 43.4 4.7 0.4 9.4 Kyrgyzstan 64.4 3.9 0.1 5.8 2.5 33.5 5.4 0.2 12.9 Tajikistan 49.7 5.1 0.3 14.2 3.2 13.4 2.4 0.4 10.7 Turkmenistan 53.7 3.2 0.1 5.5 1.9 31.4 2.4 0.1 9.1 Uzbekistan 60.1 2.8 0.1 5.9 2.4 38.5 2.5 0.2 7.8 Total/Mean 59.9 3.2 0.1 5.8 2.0 36.1 3.3 0.3 9.1 Caucasus Armenia 57.0 17.1 1.3 11.3 4.2 7.8 4.4 0.4 10.6 Azerbaijan 55.0 5.9 0.3 13.5 3.6 15.9 3.1 0.4 12.3 Georgia 40.2 11.1 0.4 9.6 4.3 3.6 1.5 0.3 9.3 Total/Mean 51.5 9.4 0.5 12.1 3.9 11.1 2.9 0.4 11.2 Moldova, Russia, Ukraine Moldova 77.4 24.4 3.2 10.6 2.5 15.1 10.4 0.5 10.6 Russian Federation 75.7 23.7 3.0 10.8 2.7 14.4 9.8 0.5 10.7 Ukraine 68.1 1.4 - 3.0 - 18.8 13.7 0.8 30.3 Total/Mean 73.9 18.6 2.3 9.0 2.1 15.4 10.7 0.6 15.2 Grand Total 57.2 21.9 3.4 7.0 3.2 12.8 3.0 0.1 5.9 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.28 Table A.5b. Year 2010: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 11.0 1.7 0.3 0.8 0.1 0.2 1.3 0.2 6.4 Bangladesh 62.3 7.5 0.4 20.8 6.9 9.4 4.5 0.2 12.7 Bhutan 49.2 13.8 0.6 11.5 5.0 4.8 2.1 0.4 11.0 Cambodia 24.4 3.3 0.2 5.7 6.6 1.4 0.8 0.1 6.3 China 80.0 33.6 9.6 2.9 0.2 31.7 1.9 - 0.2 China, Hong Kong SAR 80.0 17.5 0.9 15.6 - 4.6 32.2 2.8 6.4 India 56.6 40.4 2.2 2.5 - 1.9 3.7 - 5.9 Indonesia 63.0 3.9 0.4 18.3 29.2 6.5 0.9 0.1 3.8 Iran 80.0 13.1 1.4 26.1 - 9.2 7.8 - 22.3 Korea, DPR 69.4 21.5 2.4 11.2 3.4 11.9 7.7 0.5 10.8 Korea, Rep. 80.0 29.6 12.0 1.9 - 10.9 14.8 - 11.0 Laos 44.6 12.0 0.4 10.8 5.0 3.7 1.5 0.3 10.7 Malaysia 76.6 10.1 0.2 13.1 3.7 16.6 7.9 0.4 24.4 Mongolia 66.7 20.5 2.1 11.4 3.6 10.9 6.9 0.5 10.8 Myanmar 39.3 10.8 0.4 9.5 4.3 3.4 1.4 0.3 9.2 Nepal 44.3 14.7 3.8 6.2 7.2 2.5 2.6 0.2 7.0 Pakistan 33.7 5.7 0.1 6.8 2.6 6.2 4.0 0.2 8.1 Papua New Guinea 36.1 10.1 0.3 7.5 6.9 1.5 0.9 0.1 8.8 Philippines 58.0 15.4 0.9 11.7 3.7 6.6 3.5 0.2 16.0 Singapore 76.0 23.9 3.1 10.8 2.7 14.5 9.9 0.5 10.6 Sri Lanka 72.7 25.9 4.1 6.1 5.1 3.3 3.6 - 24.7 Taiwan 82.0 27.1 1.6 4.9 - 22.1 18.0 - 8.3 Thailand 72.0 22.3 2.0 23.5 16.7 3.3 1.8 - 2.4 Viet Nam 80.0 4.6 0.3 5.0 1.8 43.7 6.4 - 18.2 Total/Mean 66.2 28.2 4.7 6.2 3.1 15.5 3.2 0.1 5.3 Latin America Argentina 65.8 20.1 2.0 11.5 3.8 10.4 6.5 0.5 10.9 Bolivia 61.4 13.2 0.8 7.9 2.6 11.9 4.3 0.2 20.4 Brazil 79.9 42.0 2.7 21.7 1.3 1.2 4.6 0.1 6.4 Chile 69.2 21.4 2.3 11.3 3.4 11.8 7.6 0.5 10.8 Colombia 79.0 28.3 1.0 12.3 4.4 12.9 6.4 0.8 12.8 Costa Rica 80.0 21.1 1.4 19.3 1.1 9.3 16.8 0.2 10.7 Cuba 72.2 22.5 2.7 11.1 3.1 13.0 8.6 0.5 10.8 Dominican Republic 74.1 47.0 0.2 15.7 1.4 3.5 1.0 - 5.4 Ecuador 62.6 18.7 1.4 12.4 4.6 8.5 4.8 0.5 11.6 El Salvador 67.2 28.8 1.0 10.2 6.9 6.2 4.9 0.2 8.9 Guatemala 56.8 20.8 1.8 10.9 1.6 6.6 3.3 1.6 10.2 Guyana 67.8 20.9 2.2 11.3 3.5 11.3 7.2 0.5 10.8 Haiti 31.5 5.2 0.3 4.9 10.9 1.0 2.2 0.1 6.8 Honduras 70.6 21.3 1.3 11.5 7.0 11.7 5.9 0.3 11.6 Jamaica 71.2 13.3 - 22.9 11.9 1.2 18.4 - 3.6 Mexico 75.2 31.0 1.3 9.4 3.5 16.5 4.1 - 9.3 Nicaragua 74.4 25.3 1.9 13.2 8.4 11.0 7.0 0.3 7.4 Panama 72.1 32.9 1.4 13.2 1.9 9.7 4.7 1.1 7.3 Paraguay 69.8 14.3 0.9 14.2 7.0 13.0 8.5 0.6 11.4 Peru 71.2 13.0 0.5 7.1 15.9 9.6 5.9 0.6 18.5 Puerto Rico 79.6 46.6 3.6 9.8 1.3 1.0 6.5 0.4 10.2 Trinidad and Tobago 64.4 19.7 1.9 11.4 3.8 10.1 6.2 0.5 10.8 Uruguay 66.3 20.3 2.0 11.5 3.7 10.7 6.7 0.5 10.9 Venezuela 62.7 19.0 1.6 11.8 4.2 9.2 5.4 0.5 11.1 Total/Mean 73.6 30.2 1.9 14.4 3.7 8.3 5.3 0.3 9.6 Middle East/North Africa Algeria 58.0 4.1 0.2 26.2 2.5 12.5 2.6 0.3 9.6 Egypt 61.2 3.9 0.1 11.6 5.7 29.8 2.2 0.3 7.5 Iraq 31.2 2.6 0.1 11.1 0.8 7.0 1.8 0.8 6.9 Jordan 63.1 5.5 0.2 11.1 2.9 22.3 3.9 0.4 16.8 Kuwait 50.0 4.6 0.2 19.0 2.4 11.7 2.5 0.5 9.2 Lebanon 66.3 7.7 0.3 12.8 4.6 20.3 4.3 0.5 15.8 Libya 47.4 5.3 0.2 12.7 1.8 13.0 1.4 0.2 12.9 Morocco 55.6 5.4 0.1 24.4 2.0 10.4 2.3 0.3 10.6 Oman 38.5 5.4 0.2 11.6 1.6 7.6 2.3 2.6 7.2 Saudi Arabia 52.1 5.3 0.3 14.8 3.3 14.0 2.6 0.5 11.3 Sudan 15.4 1.7 0.1 6.9 0.3 1.8 0.4 0.3 3.9 Syria 60.5 5.2 0.1 14.1 2.2 20.8 2.2 0.4 15.5 Tunisia 80.0 10.2 0.2 9.7 5.8 26.2 6.3 0.5 21.1 Turkey 68.5 4.6 - 4.8 0.5 21.5 8.9 0.7 27.6 United Arab Emirates 31.5 3.5 0.2 11.5 1.3 6.6 1.6 0.9 5.9 Yemen 54.1 4.5 0.3 11.4 3.3 10.9 1.7 0.3 21.7 Total/Mean 54.2 4.3 0.1 12.6 2.5 17.0 3.5 0.5 13.6 Appendix A A.29 Table A.5b. Year 2010: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 18.4 2.2 0.4 3.8 3.1 0.9 1.3 0.1 6.7 Benin 24.5 1.0 0.1 4.3 2.7 2.3 1.5 0.2 12.4 Botswana 56.2 12.0 0.9 18.5 6.8 8.6 3.2 0.2 6.1 Burkina Faso 22.9 0.6 0.1 4.4 2.2 1.6 2.0 0.2 11.8 Burundi 9.3 0.1 0.0 0.2 0.6 0.3 0.1 0.0 7.9 Cameroon 26.9 2.4 0.1 5.8 1.2 3.0 2.2 0.3 11.8 Central African Republic 22.3 1.1 0.1 3.6 1.0 1.4 1.4 0.2 13.6 Chad 3.9 0.2 0.0 0.6 0.2 - 0.2 0.0 2.6 Congo 19.0 3.5 0.2 4.6 2.9 0.8 0.6 0.1 6.1 Congo, D.R. 7.7 0.2 0.0 0.6 0.5 0.1 0.6 0.1 5.6 Côte d'Ivoire 22.9 1.1 0.1 6.8 1.8 2.3 2.1 0.1 8.5 Eritrea 10.7 0.5 0.1 1.9 2.9 0.5 0.9 0.0 3.9 Ethiopia 10.9 0.6 0.1 3.0 3.5 0.3 0.6 0.0 2.9 Gabon 34.5 5.0 0.1 7.1 2.3 1.4 3.6 0.2 14.9 Gambia 19.2 2.1 0.1 5.2 2.7 1.3 0.7 0.2 7.1 Ghana 29.2 4.3 0.1 6.4 4.2 1.4 2.3 0.8 9.7 Guinea 9.4 0.7 0.0 3.0 1.2 0.3 0.9 0.0 3.2 Guinea-Bissau 10.6 1.5 0.2 2.1 0.4 0.0 1.0 0.2 5.1 Kenya 41.4 7.2 0.0 9.3 12.8 3.0 1.4 0.0 7.5 Lesotho 34.1 5.3 0.1 9.6 6.8 3.4 1.4 0.1 7.4 Liberia 13.8 1.5 0.4 2.8 2.3 0.6 1.0 0.1 5.1 Madagascar 39.0 7.7 0.2 5.3 17.8 1.0 2.0 0.1 4.9 Malawi 32.5 4.2 0.1 5.6 6.9 1.4 1.0 0.2 13.1 Mali 10.2 0.7 0.0 4.0 2.8 0.3 0.5 0.0 1.7 Mauritania 10.3 0.4 0.0 3.2 1.0 0.9 1.0 0.0 3.8 Mauritius 79.9 7.7 0.2 22.4 4.4 3.0 14.2 0.4 27.6 Mozambique 7.9 0.8 0.1 1.8 2.9 0.5 0.7 0.0 1.1 Namibia 51.2 12.7 0.9 10.3 12.4 4.0 4.5 0.3 6.2 Niger 12.9 0.6 0.1 4.2 1.8 0.5 0.3 0.2 5.3 Nigeria 25.6 2.5 0.0 5.1 4.1 2.8 1.6 0.3 9.2 Rwanda 16.2 1.7 0.1 2.3 2.7 0.3 0.6 0.0 8.5 Senegal 16.6 1.2 0.1 5.5 2.1 2.5 0.9 0.3 4.0 Sierra Leone 17.5 1.9 0.2 5.7 0.8 2.3 0.9 0.2 5.3 Somalia 15.2 2.4 0.1 7.3 0.7 1.6 0.2 0.4 2.5 South Africa 60.7 17.6 2.0 11.4 16.1 4.9 3.3 0.2 5.2 Swaziland 53.5 12.0 0.8 13.1 9.7 5.8 2.7 0.5 8.8 Tanzania 38.1 6.2 0.1 8.7 7.5 1.7 2.9 0.1 10.7 Togo 38.3 1.9 0.1 6.0 3.6 4.8 2.2 0.4 19.3 Uganda 20.0 2.3 0.0 3.7 7.5 0.2 2.1 0.0 4.1 Zambia 45.8 6.0 0.2 14.1 5.8 1.6 4.2 0.2 13.7 Zimbabwe 66.4 11.7 1.1 28.5 7.3 5.9 4.5 0.2 7.1 Total/Mean 25.5 3.7 0.2 5.7 5.2 1.8 1.6 0.2 7.0 Central Asia Republics Kazakhstan 64.5 2.9 - 2.5 0.6 43.8 4.7 0.4 9.5 Kyrgyzstan 67.2 6.0 0.2 9.1 3.6 28.1 5.1 0.4 14.9 Tajikistan 54.5 5.7 0.3 14.7 3.5 15.1 2.8 0.5 11.9 Turkmenistan 56.2 4.7 0.2 9.2 2.8 25.1 2.8 0.3 11.0 Uzbekistan 62.8 5.0 0.2 9.3 3.4 30.1 3.2 0.3 11.3 Total/Mean 62.1 4.6 0.1 8.2 2.7 31.2 3.7 0.4 11.2 Caucasus Armenia 56.7 16.9 1.3 11.3 4.2 7.7 4.3 0.4 10.6 Azerbaijan 55.0 5.9 0.3 13.5 3.6 15.9 3.1 0.4 12.3 Georgia 40.5 11.2 0.4 9.7 4.3 3.7 1.5 0.3 9.3 Total/Mean 51.7 9.3 0.5 12.1 3.9 11.3 2.9 0.4 11.3 Moldova, Russia, Ukraine Moldova 77.3 24.3 3.2 10.6 2.5 15.1 10.4 0.5 10.6 Russian Federation 75.0 23.5 3.0 10.9 2.8 14.1 9.6 0.5 10.7 Ukraine 67.8 1.4 - 3.0 - 18.8 13.6 0.8 30.1 Total/Mean 73.4 18.4 2.3 9.0 2.2 15.2 10.5 0.6 15.2 Grand Total 57.9 22.2 3.3 7.1 3.3 12.7 3.1 0.1 6.2 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.30 Table A.5c. Year 2015: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 15.9 2.2 0.3 2.3 0.3 0.9 1.6 0.2 7.9 Bangladesh 64.9 7.8 0.4 18.7 6.4 12.9 4.6 0.3 13.9 Bhutan 53.7 15.4 0.9 11.9 5.0 6.0 2.9 0.4 11.3 Cambodia 26.4 4.5 0.2 6.3 6.0 1.6 0.8 0.1 6.9 China 80.0 33.6 9.6 2.9 0.2 31.7 1.9 - 0.2 China, Hong Kong SAR 80.0 17.5 0.9 15.6 - 4.6 32.2 2.8 6.4 India 59.2 42.2 2.4 2.6 - 2.0 3.8 - 6.2 Indonesia 64.7 4.0 0.4 18.8 30.0 6.6 1.0 0.1 3.9 Iran 80.0 13.1 1.4 26.1 - 9.2 7.8 - 22.3 Korea, DPR 69.9 21.6 2.4 11.2 3.3 12.1 7.9 0.5 10.8 Korea, Rep. 80.0 29.6 12.0 1.9 - 10.9 14.8 - 11.0 Laos 50.4 14.1 0.7 11.6 5.1 5.0 2.3 0.4 11.2 Malaysia 79.7 10.4 0.2 11.2 4.9 22.3 7.2 0.5 23.1 Mongolia 68.6 21.2 2.3 11.3 3.5 11.6 7.5 0.5 10.8 Myanmar 40.0 11.1 0.4 9.6 4.3 3.6 1.5 0.3 9.3 Nepal 46.9 15.0 3.0 7.6 6.6 3.5 2.8 0.2 8.1 Pakistan 36.6 5.4 0.2 8.7 2.6 7.6 3.4 0.2 8.4 Papua New Guinea 38.8 10.9 0.3 8.4 6.4 2.2 1.1 0.2 9.2 Philippines 60.8 17.2 1.3 11.7 3.8 8.0 4.6 0.3 13.9 Singapore 75.2 23.6 3.0 10.9 2.8 14.2 9.6 0.5 10.7 Sri Lanka 72.7 25.9 4.1 6.1 5.1 3.3 3.6 - 24.7 Taiwan 82.0 27.1 1.6 4.9 - 22.1 18.0 - 8.3 Thailand 72.1 22.4 2.0 23.5 16.7 3.3 1.8 - 2.4 Viet Nam 80.0 4.6 0.3 5.0 1.8 43.7 6.4 - 18.2 Total/Mean 67.0 28.7 4.5 6.3 3.2 15.3 3.3 0.1 5.6 Latin America Argentina 66.8 20.5 2.1 11.4 3.6 10.9 6.9 0.5 10.8 Bolivia 66.5 16.7 1.4 9.3 2.9 12.4 5.8 0.3 17.7 Brazil 80.0 42.0 2.7 21.7 1.3 1.2 4.6 0.1 6.4 Chile 69.7 21.6 2.4 11.2 3.4 12.0 7.8 0.5 10.8 Colombia 80.0 28.6 1.1 12.5 4.4 13.1 6.4 0.8 13.0 Costa Rica 80.0 21.1 1.4 19.3 1.1 9.3 16.8 0.2 10.7 Cuba 72.0 22.4 2.6 11.1 3.1 12.9 8.5 0.5 10.8 Dominican Republic 76.0 48.2 0.2 16.1 1.4 3.5 1.0 - 5.5 Ecuador 64.7 19.3 1.5 12.8 4.8 8.8 4.9 0.5 12.0 El Salvador 69.2 26.9 1.5 10.6 5.8 8.4 6.0 0.3 9.6 Guatemala 63.0 22.0 2.0 11.6 2.2 8.3 4.6 1.3 10.9 Guyana 69.3 21.5 2.4 11.2 3.4 11.9 7.7 0.5 10.8 Haiti 33.8 6.7 0.3 6.2 9.4 1.5 2.0 0.2 7.6 Honduras 75.5 23.2 2.1 11.4 5.5 13.5 8.0 0.4 11.4 Jamaica 72.5 13.5 - 23.3 12.1 1.2 18.7 - 3.6 Mexico 76.4 31.5 1.4 9.6 3.5 16.7 4.2 - 9.5 Nicaragua 78.3 25.9 2.7 12.1 5.9 13.5 9.1 0.4 8.7 Panama 74.0 29.9 2.0 12.5 2.2 11.4 6.5 0.9 8.6 Paraguay 74.8 17.8 1.7 13.6 5.9 14.2 9.5 0.6 11.6 Peru 73.3 13.4 0.5 7.3 16.4 9.9 6.1 0.7 19.0 Puerto Rico 79.6 46.7 3.6 9.8 1.3 1.0 6.5 0.4 10.2 Trinidad and Tobago 63.8 19.5 1.8 11.4 3.8 9.9 6.1 0.5 10.8 Uruguay 67.3 20.7 2.2 11.3 3.6 11.2 7.1 0.5 10.8 Venezuela 64.4 19.6 1.8 11.7 4.0 9.8 5.9 0.5 11.1 Total/Mean 74.7 30.4 1.9 14.4 3.7 8.7 5.5 0.3 9.7 Middle East/North Africa Algeria 59.1 5.4 0.2 19.9 3.3 15.2 3.1 0.4 11.7 Egypt 63.8 5.1 0.2 12.1 5.5 27.6 2.9 0.4 10.1 Iraq 35.0 3.1 0.2 12.0 1.4 8.2 1.9 0.7 7.6 Jordan 67.0 6.7 0.2 11.6 3.7 22.6 4.3 0.4 17.3 Kuwait 50.9 5.3 0.3 14.3 3.2 13.9 2.6 0.4 10.9 Lebanon 67.4 7.9 0.3 12.5 4.7 20.8 4.5 0.5 16.3 Libya 49.5 5.4 0.2 13.2 2.5 13.7 2.0 0.3 12.2 Morocco 57.0 5.8 0.2 20.7 2.7 12.9 2.7 0.3 11.7 Oman 40.6 5.2 0.2 12.1 1.9 8.9 2.3 2.0 7.9 Saudi Arabia 56.5 6.0 0.3 14.7 3.7 15.8 3.0 0.5 12.5 Sudan 16.9 1.8 0.1 7.0 0.5 2.2 0.5 0.3 4.4 Syria 64.1 6.3 0.2 13.8 3.2 21.1 3.1 0.4 16.0 Tunisia 80.0 10.2 0.2 9.7 5.8 26.2 6.3 0.5 21.1 Turkey 69.8 4.6 - 4.9 0.6 21.9 9.1 0.7 28.2 United Arab Emirates 32.1 3.3 0.2 11.2 1.7 7.1 1.5 0.6 6.5 Yemen 66.9 6.5 0.3 12.5 4.3 16.3 3.1 0.4 23.6 Total/Mean 56.6 5.0 0.2 11.9 2.8 17.6 3.9 0.5 14.7 Appendix A A.31 Table A.5c. Year 2015: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 23.3 3.3 0.5 5.0 3.7 1.1 1.4 0.2 8.0 Benin 29.1 1.6 0.1 6.4 2.8 3.8 1.7 0.2 12.4 Botswana 58.4 14.1 1.1 16.7 6.1 8.8 3.9 0.3 7.5 Burkina Faso 28.7 1.2 0.1 6.5 2.6 3.0 2.2 0.3 12.8 Burundi 11.6 0.2 0.0 0.5 0.8 0.4 0.2 0.0 9.4 Cameroon 29.8 2.7 0.2 7.6 1.5 4.6 2.0 0.3 10.9 Central African Republic 25.3 1.6 0.1 5.4 1.2 2.7 1.4 0.2 12.7 Chad 4.8 0.3 0.0 0.7 0.2 - 0.3 0.0 3.2 Congo 22.7 4.3 0.2 5.6 3.5 1.0 0.7 0.2 7.2 Congo, D.R. 9.8 0.3 0.0 0.8 0.7 0.2 0.7 0.1 6.8 Côte d'Ivoire 26.1 1.7 0.2 8.2 1.9 3.8 1.9 0.2 8.3 Eritrea 12.5 0.9 0.2 2.4 3.0 0.6 0.9 0.0 4.5 Ethiopia 12.9 1.1 0.1 3.4 3.6 0.4 0.7 0.0 3.7 Gabon 37.0 6.9 0.2 8.0 2.9 2.0 3.0 0.2 13.7 Gambia 21.5 3.2 0.1 5.7 3.0 1.3 0.7 0.2 7.3 Ghana 31.9 5.9 0.1 7.3 4.3 1.8 2.0 0.7 9.7 Guinea 11.3 1.0 0.1 3.6 1.2 0.5 1.0 0.1 3.8 Guinea-Bissau 15.0 2.1 0.3 3.3 0.6 0.3 1.3 0.2 6.8 Kenya 47.6 9.5 0.2 10.6 12.5 3.9 1.9 0.1 8.9 Lesotho 36.0 6.9 0.2 9.7 6.2 3.4 1.3 0.2 8.0 Liberia 17.8 2.1 0.4 3.6 3.0 0.8 1.2 0.1 6.5 Madagascar 47.0 10.5 0.4 7.3 16.9 2.4 2.6 0.2 6.8 Malawi 37.7 6.6 0.2 7.2 6.7 2.2 1.3 0.2 13.2 Mali 13.0 1.0 0.1 5.0 2.9 0.8 0.7 0.1 2.5 Mauritania 12.2 0.7 0.1 3.8 1.0 1.2 1.0 0.1 4.3 Mauritius 80.0 7.7 0.2 22.4 4.4 3.0 14.2 0.4 27.6 Mozambique 9.2 0.8 0.2 2.0 2.9 0.5 0.8 0.0 2.0 Namibia 54.7 14.5 1.1 10.9 10.3 5.3 4.7 0.3 7.6 Niger 22.9 1.4 0.1 7.9 2.5 2.7 0.6 0.3 7.4 Nigeria 31.0 4.8 0.1 6.7 4.6 3.1 1.5 0.3 10.0 Rwanda 19.5 2.8 0.1 3.5 3.1 0.6 0.6 0.1 8.7 Senegal 19.0 1.6 0.1 6.4 1.9 3.1 1.0 0.3 4.6 Sierra Leone 21.8 2.3 0.3 7.2 1.1 3.1 1.1 0.3 6.4 Somalia 18.7 2.7 0.1 8.4 0.9 2.3 0.4 0.4 3.4 South Africa 62.4 18.5 2.0 11.5 12.2 6.7 4.3 0.3 7.1 Swaziland 57.2 14.3 1.1 13.0 8.3 6.9 3.6 0.5 9.6 Tanzania 43.5 9.0 0.3 9.9 7.0 3.0 3.0 0.2 11.1 Togo 44.8 3.0 0.2 8.8 3.8 8.0 2.4 0.5 18.1 Uganda 27.5 3.5 0.0 5.2 9.7 0.5 2.7 0.0 5.8 Zambia 53.9 9.7 0.6 14.8 5.9 3.6 4.8 0.3 14.2 Zimbabwe 69.8 15.2 1.6 24.1 6.2 8.2 5.9 0.3 8.3 Total/Mean 29.1 4.8 0.3 6.6 5.1 2.4 1.8 0.2 7.9 Central Asia Republics Kazakhstan 64.5 2.9 - 2.5 0.6 43.8 4.7 0.4 9.5 Kyrgyzstan 69.6 7.8 0.2 11.3 4.6 23.6 4.9 0.5 16.7 Tajikistan 58.4 6.3 0.3 14.5 3.9 16.7 3.2 0.5 13.1 Turkmenistan 58.2 5.9 0.2 12.1 3.6 19.9 3.3 0.4 12.7 Uzbekistan 65.1 6.9 0.2 11.8 4.2 23.1 4.0 0.4 14.5 Total/Mean 64.0 5.9 0.2 10.0 3.3 26.8 4.1 0.4 13.2 Caucasus Armenia 56.1 16.7 1.2 11.3 4.2 7.5 4.2 0.4 10.6 Azerbaijan 55.0 5.9 0.3 13.5 3.6 15.9 3.1 0.4 12.3 Georgia 40.3 11.2 0.4 9.7 4.3 3.7 1.5 0.3 9.3 Total/Mean 51.7 9.1 0.5 12.2 3.9 11.4 2.9 0.4 11.3 Moldova, Russia, Ukraine Moldova 76.7 24.1 3.1 10.7 2.6 14.8 10.2 0.5 10.6 Russian Federation 74.4 23.3 2.9 10.9 2.9 13.9 9.4 0.5 10.7 Ukraine 67.2 1.4 - 3.0 - 18.6 13.5 0.8 29.9 Total/Mean 72.8 18.3 2.2 9.1 2.2 15.0 10.3 0.6 15.1 Grand Total 58.2 22.3 3.1 7.3 3.3 12.5 3.1 0.1 6.4 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.32 Table A.5d. Year 2020: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 21.3 2.7 0.4 4.5 0.7 2.4 1.7 0.3 8.6 Bangladesh 66.9 8.0 0.3 16.8 5.9 15.8 4.7 0.4 15.1 Bhutan 57.2 16.7 1.1 12.0 4.7 7.1 3.8 0.4 11.4 Cambodia 28.0 5.5 0.2 6.9 5.5 1.7 0.7 0.2 7.3 China 80.0 33.6 9.6 2.9 0.2 31.7 1.9 - 0.2 China, Hong Kong SAR 80.0 17.5 0.9 15.6 - 4.6 32.2 2.8 6.4 India 61.3 43.7 2.4 2.7 - 2.1 4.0 - 6.4 Indonesia 65.7 4.0 0.4 19.0 30.4 6.7 1.0 0.1 3.9 Iran 80.0 13.1 1.4 26.1 - 9.2 7.8 - 22.3 Korea, DPR 70.0 21.7 2.4 11.2 3.3 12.1 7.9 0.5 10.8 Korea, Rep. 80.0 29.6 12.0 1.9 - 10.9 14.8 - 11.0 Laos 55.1 15.9 1.0 11.8 4.9 6.4 3.3 0.4 11.3 Malaysia 80.0 10.2 0.2 9.8 5.8 26.1 6.3 0.5 21.2 Mongolia 69.7 21.6 2.4 11.2 3.4 12.0 7.8 0.5 10.8 Myanmar 40.3 11.2 0.4 9.6 4.3 3.6 1.5 0.3 9.3 Nepal 48.8 15.2 2.4 8.7 6.0 4.4 2.9 0.3 8.8 Pakistan 38.7 5.1 0.2 10.0 2.7 8.7 3.0 0.3 8.7 Papua New Guinea 40.9 11.5 0.4 9.1 5.9 2.9 1.4 0.2 9.5 Philippines 63.2 18.8 1.6 11.6 3.8 9.3 5.6 0.4 12.1 Singapore 74.4 23.3 2.9 10.9 2.9 13.9 9.4 0.5 10.7 Sri Lanka 72.7 25.9 4.1 6.1 5.1 3.3 3.6 - 24.7 Taiwan 82.0 27.1 1.6 4.9 - 22.1 18.0 - 8.3 Thailand 72.1 22.4 2.0 23.5 16.7 3.3 1.8 - 2.4 Viet Nam 80.0 4.6 0.3 5.0 1.8 43.7 6.4 - 18.2 Total/Mean 67.4 29.0 4.3 6.5 3.2 14.9 3.4 0.1 5.9 Latin America Argentina 67.8 20.9 2.2 11.3 3.5 11.3 7.2 0.5 10.8 Bolivia 70.7 19.6 2.0 10.1 3.0 13.2 7.3 0.4 15.1 Brazil 80.0 42.0 2.7 21.7 1.3 1.2 4.6 0.1 6.4 Chile 70.0 21.7 2.4 11.2 3.3 12.1 7.9 0.5 10.8 Colombia 80.0 28.6 1.1 12.5 4.4 13.1 6.4 0.8 13.0 Costa Rica 80.0 21.1 1.4 19.3 1.1 9.3 16.8 0.2 10.7 Cuba 71.8 22.3 2.6 11.1 3.2 12.8 8.5 0.5 10.8 Dominican Republic 77.6 49.2 0.2 16.4 1.5 3.6 1.0 - 5.7 Ecuador 66.3 19.8 1.5 13.1 4.9 9.0 5.1 0.5 12.3 El Salvador 70.9 25.4 2.0 10.8 4.7 10.3 7.1 0.4 10.1 Guatemala 68.8 23.1 2.4 11.7 2.5 10.4 6.4 1.1 11.2 Guyana 70.0 21.7 2.4 11.2 3.3 12.1 7.9 0.5 10.8 Haiti 35.7 7.9 0.3 7.2 8.1 2.1 1.8 0.2 8.1 Honduras 79.5 24.8 2.9 10.9 4.1 15.3 10.0 0.4 11.1 Jamaica 73.6 13.7 - 23.7 12.3 1.2 19.0 - 3.7 Mexico 77.3 31.9 1.4 9.7 3.6 16.9 4.3 - 9.6 Nicaragua 80.0 25.9 3.2 11.2 3.9 15.2 10.5 0.5 9.6 Panama 75.5 27.3 2.5 11.7 2.4 13.0 8.2 0.7 9.6 Paraguay 78.7 20.7 2.4 12.8 4.8 15.5 10.6 0.6 11.4 Peru 75.0 13.7 0.6 7.5 16.8 10.1 6.2 0.7 19.5 Puerto Rico 79.6 46.7 3.6 9.8 1.3 1.0 6.5 0.4 10.2 Trinidad and Tobago 63.1 19.2 1.8 11.4 3.9 9.7 5.9 0.5 10.8 Uruguay 68.3 21.1 2.3 11.3 3.5 11.5 7.4 0.5 10.8 Venezuela 65.8 20.1 2.0 11.6 3.8 10.4 6.5 0.5 11.0 Total/Mean 75.5 30.6 2.0 14.4 3.7 9.0 5.7 0.3 9.7 Middle East/North Africa Algeria 60.2 6.5 0.3 14.5 3.9 17.5 3.5 0.4 13.5 Egypt 65.9 6.1 0.2 12.3 5.3 25.8 3.5 0.4 12.3 Iraq 38.0 3.5 0.2 12.5 1.8 9.3 1.9 0.6 8.2 Jordan 70.1 7.7 0.2 11.7 4.4 23.0 4.8 0.5 17.9 Kuwait 51.6 5.4 0.3 13.5 3.4 14.6 2.7 0.4 11.4 Lebanon 68.3 8.0 0.2 12.4 4.8 21.2 4.6 0.5 16.6 Libya 51.2 5.5 0.3 13.4 3.2 14.4 2.5 0.4 11.6 Morocco 58.2 6.2 0.2 17.5 3.3 15.0 3.1 0.4 12.6 Oman 42.2 5.1 0.2 12.5 2.2 9.9 2.2 1.5 8.5 Saudi Arabia 60.0 6.5 0.3 14.3 4.0 17.4 3.4 0.5 13.6 Sudan 18.1 1.9 0.2 7.1 0.7 2.6 0.6 0.3 4.7 Syria 67.0 7.2 0.2 13.2 4.0 21.5 3.9 0.5 16.6 Tunisia 80.0 10.2 0.2 9.7 5.8 26.2 6.3 0.5 21.1 Turkey 70.9 4.7 - 4.9 0.6 22.2 9.2 0.7 28.6 United Arab Emirates 32.6 3.2 0.3 10.9 1.9 7.6 1.4 0.3 7.0 Yemen 79.9 9.0 0.2 11.0 5.5 22.6 5.0 0.5 26.1 Total/Mean 58.8 5.6 0.2 11.1 3.2 18.3 4.2 0.5 15.7 Appendix A A.33 Table A.5d. Year 2020: Projected Contraceptive Prevalence by Method Among Married Women of Reproductive Age (MWRA) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 28.6 5.1 0.5 6.5 4.3 1.6 1.4 0.2 9.1 Benin 33.8 2.3 0.2 8.5 2.9 5.8 1.8 0.3 12.1 Botswana 60.2 15.8 1.3 15.1 5.4 9.1 4.5 0.3 8.6 Burkina Faso 35.1 2.0 0.2 8.7 2.9 5.3 2.4 0.3 13.3 Burundi 14.9 0.7 0.1 1.1 1.2 0.6 0.3 0.0 10.9 Cameroon 32.1 3.0 0.2 9.0 1.7 5.9 1.9 0.3 10.1 Central African Republic 28.0 2.0 0.2 7.1 1.5 4.1 1.4 0.3 11.5 Chad 6.0 0.5 0.0 0.8 0.3 - 0.4 0.0 3.9 Congo 27.9 5.7 0.2 6.9 4.1 1.4 0.8 0.2 8.6 Congo, D.R. 12.8 0.8 0.1 1.5 1.2 0.3 0.9 0.2 8.0 Côte d'Ivoire 28.6 2.2 0.2 9.2 1.9 5.0 1.8 0.2 8.1 Eritrea 14.2 1.5 0.2 2.9 3.0 0.6 0.8 0.1 5.0 Ethiopia 15.0 1.8 0.2 3.9 3.6 0.5 0.6 0.1 4.5 Gabon 38.8 8.4 0.3 8.7 3.4 2.6 2.7 0.3 12.6 Gambia 23.2 4.1 0.1 6.1 3.2 1.4 0.6 0.2 7.5 Ghana 33.9 7.2 0.2 8.0 4.4 2.2 1.7 0.6 9.7 Guinea 13.1 1.2 0.1 4.2 1.2 1.0 1.0 0.1 4.3 Guinea-Bissau 20.3 2.6 0.4 5.2 0.8 1.4 1.5 0.3 8.1 Kenya 54.1 12.4 0.6 11.6 11.2 5.4 2.8 0.2 10.0 Lesotho 37.5 8.2 0.2 9.8 5.7 3.5 1.4 0.2 8.5 Liberia 22.5 3.2 0.5 4.9 3.6 1.1 1.3 0.2 7.8 Madagascar 55.3 13.8 0.8 9.0 14.7 4.6 3.7 0.3 8.4 Malawi 42.4 9.1 0.3 8.6 6.4 3.2 1.7 0.3 12.8 Mali 16.2 1.3 0.1 6.1 2.9 1.5 0.8 0.1 3.4 Mauritania 14.3 1.0 0.1 4.6 1.0 1.6 1.1 0.1 4.7 Mauritius 80.0 7.7 0.2 22.4 4.4 3.0 14.2 0.4 27.6 Mozambique 10.5 1.0 0.2 2.2 2.8 0.6 0.9 0.1 2.8 Namibia 57.4 15.9 1.3 11.2 8.5 6.5 5.0 0.4 8.6 Niger 33.8 2.6 0.2 11.3 3.0 6.2 1.1 0.4 9.1 Nigeria 36.1 7.3 0.2 8.1 4.8 3.5 1.6 0.3 10.4 Rwanda 22.5 4.0 0.1 4.7 3.4 0.9 0.6 0.1 8.7 Senegal 20.9 1.9 0.2 7.2 1.8 3.7 1.0 0.3 5.0 Sierra Leone 27.0 2.8 0.3 9.0 1.4 4.3 1.3 0.3 7.5 Somalia 22.5 2.9 0.1 9.5 1.2 3.4 0.6 0.4 4.3 South Africa 63.8 19.2 2.0 11.5 8.8 8.2 5.2 0.4 8.6 Swaziland 60.0 16.0 1.3 12.7 7.1 7.9 4.4 0.5 10.1 Tanzania 48.0 11.5 0.6 10.6 6.3 4.3 3.2 0.3 11.2 Togo 50.3 4.2 0.2 10.7 3.9 11.1 2.8 0.5 17.0 Uganda 38.2 6.2 0.1 7.7 11.5 1.3 3.3 0.1 8.2 Zambia 61.7 13.8 1.1 14.7 5.5 6.3 5.9 0.4 14.1 Zimbabwe 72.5 18.0 2.1 20.4 5.2 10.2 7.2 0.4 9.1 Total/Mean 32.9 6.2 0.4 7.5 4.9 3.2 2.0 0.2 8.6 Central Asia Republics Kazakhstan 64.5 2.9 - 2.5 0.6 43.8 4.7 0.4 9.5 Kyrgyzstan 71.6 8.6 0.2 11.8 5.1 22.6 5.0 0.5 17.8 Tajikistan 61.6 6.8 0.3 14.1 4.1 18.1 3.6 0.5 14.1 Turkmenistan 60.0 6.7 0.3 13.3 4.1 17.8 3.6 0.5 13.8 Uzbekistan 67.0 7.8 0.3 12.6 4.6 20.7 4.4 0.5 16.1 Total/Mean 65.6 6.6 0.2 10.6 3.7 25.2 4.4 0.5 14.4 Caucasus Armenia 55.5 16.5 1.2 11.2 4.3 7.3 4.0 0.4 10.5 Azerbaijan 55.0 5.9 0.3 13.5 3.6 15.9 3.1 0.4 12.3 Georgia 39.9 11.0 0.4 9.6 4.3 3.6 1.4 0.3 9.3 Total/Mean 51.6 9.0 0.5 12.2 3.9 11.5 2.9 0.4 11.3 Moldova, Russia, Ukraine Moldova 75.9 23.8 3.1 10.8 2.7 14.5 9.9 0.5 10.6 Russian Federation 73.6 23.0 2.8 11.0 3.0 13.5 9.1 0.5 10.7 Ukraine 66.5 1.4 - 3.0 - 18.4 13.4 0.8 29.6 Total/Mean 72.1 18.2 2.2 9.2 2.3 14.6 10.1 0.6 14.9 Grand Total 58.1 22.2 3.0 7.4 3.4 12.2 3.2 0.1 6.7 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.34 Table A.6a. Year 2005: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 297 50 7 2 1 - 41 5 191 Bangladesh 16,339 2,013 134 6,298 2,076 1,456 1,230 30 3,103 Bhutan 138 38 1 34 15 12 5 1 33 Cambodia 484 48 4 108 154 29 19 1 121 China 217,811 91,408 26,116 7,835 522 86,184 5,223 - 522 China, Hong Kong SAR 972 212 11 190 - 56 391 34 78 India 112,073 79,952 4,455 4,924 - 3,751 7,268 - 11,723 Indonesia 26,771 1,641 177 7,760 12,403 2,749 399 44 1,596 Iran 9,671 1,586 171 3,157 - 1,114 943 - 2,700 Korea, DPR 3,053 942 100 508 158 511 326 22 486 Korea, Rep. 6,649 2,457 996 155 - 902 1,228 - 911 Laos 397 104 3 100 48 29 10 3 100 Malaysia 3,391 494 13 764 33 145 507 13 1,422 Mongolia 311 95 9 56 19 48 29 2 53 Myanmar 2,681 660 63 645 469 194 65 15 570 Nepal 2,176 768 252 220 421 76 138 5 296 Pakistan 8,102 1,659 20 1,185 675 1,251 1,239 24 2,050 Papua New Guinea 334 95 2 64 76 7 7 1 82 Philippines 7,086 1,723 57 1,475 424 669 321 17 2,400 Singapore 544 170 21 80 21 102 69 4 78 Sri Lanka 2,296 817 129 191 160 104 115 - 779 Taiwan 3,082 1,018 60 184 - 831 676 - 312 Thailand 8,258 2,562 233 2,690 1,912 373 210 - 279 Viet Nam 11,779 672 47 734 267 6,436 937 - 2,687 Total 444,695 191,181 33,084 39,358 19,856 107,028 21,395 220 32,572 Latin America Argentina 3,938 1,202 113 707 238 610 372 28 668 Bolivia 910 157 4 97 32 193 53 1 372 Brazil 29,410 15,456 1,002 7,979 464 424 1,696 39 2,351 Chile 1,695 522 54 287 91 279 177 12 273 Colombia 6,304 2,256 83 982 352 1,032 508 67 1,024 Costa Rica 667 176 12 161 9 78 140 2 89 Cuba 1,369 430 - 196 - 645 39 - 59 Dominican Republic 1,203 762 4 254 23 56 16 - 88 Ecuador 1,281 385 30 250 92 178 101 9 235 El Salvador 857 409 7 125 106 53 49 2 106 Guatemala 1,070 415 35 206 16 114 53 37 193 Guyana 45 14 1 8 3 7 4 0 8 Haiti 482 64 6 57 206 8 43 1 98 Honduras 749 222 6 128 96 117 49 2 130 Jamaica 384 72 - 123 64 6 99 - 19 Mexico 14,004 5,779 250 1,753 651 3,067 772 - 1,732 Nicaragua 699 264 5 152 151 67 34 - 26 Panama 409 227 3 83 6 42 11 8 28 Paraguay 719 121 4 158 85 135 88 6 122 Peru 3,291 601 24 327 738 444 273 29 854 Puerto Rico 489 286 22 60 8 6 40 3 63 Trinidad and Tobago 134 41 4 24 8 21 13 1 22 Uruguay 326 100 10 58 19 51 31 2 55 Venezuela 2,205 664 55 424 153 313 181 16 398 Total 72,639 30,624 1,735 14,600 3,612 7,946 4,844 265 9,013 Middle East/North Africa Algeria 2,408 110 5 1,421 67 402 84 11 309 Egypt 6,941 302 7 1,271 712 3,887 184 31 547 Iraq 1,020 81 2 373 13 224 68 32 228 Jordan 432 31 1 73 15 163 26 3 121 Kuwait 176 14 0 87 5 33 8 2 26 Lebanon 407 46 2 86 28 122 25 3 95 Libya 251 30 1 66 5 69 4 1 77 Morocco 2,623 240 4 1,394 55 370 92 10 459 Oman 128 21 0 38 4 21 9 13 22 Saudi Arabia 1,610 161 11 488 100 418 74 15 344 Sudan 671 74 2 332 7 73 8 13 162 Syria 1,773 126 3 438 34 648 39 10 475 Tunisia 1,277 300 - 229 21 443 34 26 224 Turkey 9,150 608 - 637 73 2,867 1,187 87 3,692 United Arab Emirates 207 25 1 80 6 39 12 8 35 Yemen 1,330 98 7 274 78 222 27 7 615 Total 30,406 2,266 45 7,287 1,223 10,000 1,882 272 7,430 Appendix A A.35 Table A.6a. Year 2005: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 341 35 9 67 58 16 27 3 127 Benin 425 12 1 56 52 26 29 3 246 Botswana 207 37 3 79 29 33 10 0 16 Burkina Faso 531 9 1 89 56 23 51 5 299 Burundi 116 1 - 3 7 4 1 - 99 Cameroon 1,171 100 3 187 49 78 117 13 626 Central African Republic 181 7 0 20 8 5 12 1 127 Chad 81 5 - 14 5 - 5 - 54 Congo 88 16 1 22 14 4 3 1 28 Congo, D.R. 604 17 - 43 35 9 43 9 449 Côte d'Ivoire 1,284 35 3 350 117 75 144 3 556 Eritrea 175 4 1 30 53 9 14 0 64 Ethiopia 1,825 66 11 528 655 34 91 2 438 Gabon 57 5 0 11 2 1 8 0 29 Gambia 61 4 0 17 8 5 3 1 24 Ghana 1,337 134 2 271 201 52 141 47 489 Guinea 131 8 0 44 20 4 13 0 42 Guinea-Bissau 20 3 0 4 1 - 2 0 10 Kenya 2,555 419 0 572 843 182 87 0 452 Lesotho 150 17 0 44 35 16 7 0 31 Liberia 59 6 2 12 10 3 5 0 22 Madagascar 750 133 3 85 402 8 40 1 78 Malawi 976 83 1 144 236 31 33 5 443 Mali 252 14 1 104 79 7 13 0 33 Mauritania 37 1 0 12 4 3 4 0 13 Mauritius 202 19 1 56 11 8 36 1 70 Mozambique 373 44 3 91 154 23 29 0 28 Namibia 197 44 3 39 62 11 19 1 17 Niger 89 2 0 28 15 1 1 1 41 Nigeria 8,543 407 9 1,529 1,453 1,074 640 111 3,321 Rwanda 193 15 1 20 33 3 7 0 114 Senegal 424 27 1 137 67 63 25 8 95 Sierra Leone 134 15 2 44 6 18 7 2 41 Somalia 158 27 0 80 8 15 1 5 22 South Africa 5,176 1,479 180 982 1,769 284 212 8 262 Swaziland 106 20 1 28 24 10 4 1 16 Tanzania 2,510 290 3 562 592 67 236 4 756 Togo 565 17 1 56 60 42 34 7 347 Uganda 1,175 134 - 214 447 13 127 - 240 Zambia 793 69 1 264 108 11 79 3 257 Zimbabwe 1,447 173 13 786 198 77 72 3 125 Total 35,498 3,953 260 7,724 7,984 2,347 2,431 250 10,550 Central Asia Republics Kazakhstan 1,980 90 - 77 19 1,346 144 13 292 Kyrgyzstan 664 40 1 60 26 346 56 2 133 Tajikistan 635 65 4 182 40 171 31 6 137 Turkmenistan 451 27 1 46 16 264 20 1 76 Uzbekistan 2,992 142 5 292 120 1,915 122 8 389 Total 6,723 363 10 656 221 4,042 373 30 1,027 Caucasus Armenia 324 97 7 64 24 44 25 2 60 Azerbaijan 887 96 4 217 59 256 49 7 199 Georgia 314 87 3 75 34 28 11 2 73 Total 1,524 279 15 357 116 328 85 12 331 Moldova, Russia, Ukraine - Moldova 637 29 - 18 - 333 51 - 205 Russian Federation 20,164 6,334 826 2,820 690 3,888 2,671 139 2,794 Ukraine 5,960 124 - 266 - 1,650 1,197 71 2,652 Total 26,761 6,488 826 3,105 690 5,871 3,920 210 5,651 Grand Total 618,246 235,154 35,976 73,087 33,703 137,562 34,930 1,259 66,575 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.36 Table A.6b. Year 2010: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 633 99 15 43 7 10 77 11 371 Bangladesh 19,284 2,329 135 6,421 2,130 2,899 1,387 65 3,918 Bhutan 184 51 2 43 19 18 8 1 41 Cambodia 599 82 5 139 161 35 20 2 155 China 221,616 93,005 26,573 7,972 531 87,690 5,315 - 531 China, Hong Kong SAR 947 207 11 185 - 54 381 33 76 India 129,521 92,399 5,148 5,690 - 4,335 8,400 - 13,548 Indonesia 29,078 1,783 193 8,431 13,467 2,987 434 48 1,734 Iran 10,681 1,751 189 3,487 - 1,231 1,041 - 2,982 Korea, DPR 3,187 983 104 531 165 533 341 23 507 Korea, Rep. 6,446 2,382 966 150 - 874 1,191 - 883 Laos 527 142 5 128 60 44 18 4 126 Malaysia 3,919 571 15 883 38 167 586 15 1,643 Mongolia 346 106 11 59 19 56 36 2 56 Myanmar 3,036 836 29 734 332 267 106 23 710 Nepal 2,690 896 229 374 439 154 160 10 428 Pakistan 10,474 1,784 43 2,129 796 1,925 1,231 53 2,513 Papua New Guinea 424 119 3 88 81 17 10 2 103 Philippines 8,398 2,237 125 1,689 529 957 508 36 2,317 Singapore 546 171 21 80 21 102 69 4 78 Sri Lanka 2,372 845 133 198 165 108 119 - 805 Taiwan 3,638 1,202 71 217 - 980 798 - 368 Thailand 8,398 2,606 237 2,736 1,943 379 213 - 284 Viet Nam 12,902 736 51 804 291 7,050 1,027 - 2,943 Total 479,848 207,321 34,316 43,211 21,195 112,875 23,474 333 37,124 Latin America Argentina 4,244 1,299 127 745 245 673 417 30 706 Bolivia 1,129 242 14 146 48 219 80 4 376 Brazil 31,198 16,396 1,063 8,464 491 450 1,799 41 2,494 Chile 1,780 548 57 301 96 293 185 13 287 Colombia 6,924 2,478 91 1,079 386 1,134 558 73 1,125 Costa Rica 717 189 12 173 10 84 151 2 96 Cuba 1,355 426 - 194 - 639 39 - 58 Dominican Republic 1,328 842 4 281 25 62 17 - 97 Ecuador 1,440 435 37 272 97 209 123 10 256 El Salvador 975 418 15 148 100 91 71 3 130 Guatemala 1,405 515 44 270 40 163 82 39 253 Guyana 46 14 1 8 3 7 4 0 8 Haiti 571 95 6 88 198 17 41 2 123 Honduras 937 283 17 153 93 155 79 3 153 Jamaica 402 75 - 129 67 7 104 - 20 Mexico 15,547 6,417 278 1,946 721 3,405 857 - 1,923 Nicaragua 855 323 6 186 184 82 42 - 32 Panama 452 251 3 92 6 47 12 9 31 Paraguay 881 180 11 179 88 164 107 7 144 Peru 3,724 680 28 370 834 503 309 33 967 Puerto Rico 498 292 22 61 8 6 41 3 64 Trinidad and Tobago 131 40 4 23 8 21 13 1 22 Uruguay 341 104 10 61 20 53 33 2 57 Venezuela 2,474 749 65 465 164 362 214 18 438 Total 79,352 33,291 1,916 15,834 3,931 8,847 5,378 294 9,861 Middle East/North Africa Algeria 2,712 191 8 1,226 116 585 119 15 451 Egypt 8,016 508 15 1,523 744 3,900 295 43 987 Iraq 1,387 117 5 493 37 313 82 34 306 Jordan 535 47 1 94 25 189 33 4 142 Kuwait 205 19 1 78 10 48 10 2 38 Lebanon 438 49 2 92 30 132 27 3 102 Libya 289 32 1 77 11 79 8 1 79 Morocco 2,892 280 7 1,271 102 543 121 14 552 Oman 165 23 1 50 7 33 10 11 31 Saudi Arabia 2,124 218 13 602 135 573 104 18 461 Sudan 856 93 5 386 18 101 20 15 218 Syria 2,171 186 5 507 78 747 77 14 557 Tunisia 1,379 324 - 248 23 479 37 28 242 Turkey 9,976 663 - 694 79 3,125 1,294 95 4,025 United Arab Emirates 254 28 2 93 11 53 13 7 48 Yemen 2,061 172 10 433 126 417 63 13 826 Total 35,461 2,951 77 7,867 1,552 11,316 2,314 318 9,065 Appendix A A.37 Table A.6b. Year 2010: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 512 60 12 104 85 24 36 4 186 Benin 607 25 2 107 66 56 38 4 308 Botswana 209 45 3 69 25 32 12 1 23 Burkina Faso 802 22 2 155 78 54 71 7 412 Burundi 152 2 0 4 9 5 2 0 130 Cameroon 1,517 134 6 327 70 172 124 16 667 Central African Republic 224 11 1 36 10 14 14 2 136 Chad 100 6 0 16 5 - 6 0 67 Congo 108 20 1 26 17 5 3 1 35 Congo, D.R. 769 21 1 55 46 12 57 11 565 Côte d'Ivoire 1,728 83 8 512 139 177 157 9 643 Eritrea 247 11 3 43 67 12 20 1 91 Ethiopia 2,559 134 25 696 818 61 138 6 681 Gabon 70 10 0 14 5 3 7 0 30 Gambia 80 9 0 22 11 5 3 1 30 Ghana 1,710 254 4 375 245 81 136 46 570 Guinea 182 13 1 58 24 5 17 1 62 Guinea-Bissau 29 4 1 6 1 0 3 0 14 Kenya 3,088 537 3 695 959 226 107 2 559 Lesotho 158 25 1 45 32 16 6 1 34 Liberia 78 8 2 16 13 4 6 1 29 Madagascar 1,038 204 5 142 473 28 53 2 131 Malawi 1,348 175 3 232 285 58 43 8 544 Mali 394 26 2 156 108 13 21 1 66 Mauritania 50 2 0 16 5 4 5 0 18 Mauritius 208 20 1 58 11 8 37 1 72 Mozambique 483 46 8 108 178 29 43 1 70 Namibia 239 59 4 48 58 19 21 1 29 Niger 376 17 2 124 52 15 8 5 154 Nigeria 12,106 1,171 23 2,406 1,948 1,326 735 142 4,354 Rwanda 269 28 1 38 44 6 10 1 141 Senegal 583 44 3 192 74 89 32 10 139 Sierra Leone 168 18 2 55 8 22 9 2 51 Somalia 229 37 1 110 11 24 3 6 37 South Africa 5,216 1,516 170 983 1,380 424 284 16 443 Swaziland 115 26 2 28 21 12 6 1 19 Tanzania 3,339 547 13 763 660 153 258 11 934 Togo 793 39 2 124 75 100 45 9 399 Uganda 1,614 187 0 296 606 20 171 0 334 Zambia 1,058 139 5 326 133 38 96 5 316 Zimbabwe 1,633 287 27 702 181 145 111 6 175 Total 46,188 6,025 352 10,289 9,036 3,495 2,951 343 13,696 Central Asia Republics Kazakhstan 1,972 89 - 77 19 1,340 144 13 290 Kyrgyzstan 740 66 2 100 40 309 56 4 164 Tajikistan 780 81 4 210 50 216 40 7 171 Turkmenistan 518 43 2 85 26 232 26 3 102 Uzbekistan 3,446 273 10 510 185 1,652 178 17 622 Total 7,455 552 18 981 320 3,749 443 43 1,348 Caucasus Armenia 312 93 7 62 23 42 24 2 58 Azerbaijan 924 100 5 227 61 267 51 7 207 Georgia 299 83 3 71 32 27 11 2 69 Total 1,535 276 15 360 116 336 86 12 334 Moldova, Russia, Ukraine Moldova 616 29 - 18 - 322 49 - 198 Russian Federation 18,591 5,840 762 2,600 636 3,585 2,463 128 2,576 Ukraine 5,551 116 - 248 - 1,537 1,115 66 2,470 Total 24,758 5,984 762 2,866 636 5,443 3,627 194 5,244 Grand Total 674,596 256,401 37,456 81,408 36,788 146,061 38,274 1,537 76,672 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.38 Table A.6c. Year 2015: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 1,079 152 22 156 23 65 109 17 535 Bangladesh 21,947 2,626 132 6,315 2,150 4,365 1,543 99 4,717 Bhutan 228 65 4 50 21 25 13 2 48 Cambodia 702 120 5 169 160 42 20 3 184 China 217,043 91,085 26,024 7,807 520 85,880 5,205 - 520 China, Hong Kong SAR 898 196 10 176 - 52 361 31 72 India 145,479 103,783 5,783 6,391 - 4,870 9,435 - 15,217 Indonesia 31,030 1,904 206 9,008 14,353 3,191 463 51 1,853 Iran 11,101 1,820 197 3,624 - 1,279 1,082 - 3,099 Korea, DPR 3,245 1,001 106 541 168 543 347 23 517 Korea, Rep. 6,138 2,268 920 143 - 833 1,134 - 841 Laos 672 188 9 154 68 67 31 5 149 Malaysia 4,372 637 17 985 43 187 654 17 1,833 Mongolia 368 114 12 61 19 62 40 3 58 Myanmar 3,234 895 33 776 349 290 117 25 749 Nepal 3,196 1,024 205 522 448 241 188 16 553 Pakistan 12,741 1,872 64 3,039 909 2,643 1,193 81 2,939 Papua New Guinea 512 144 5 111 84 30 15 3 122 Philippines 9,589 2,719 199 1,844 599 1,260 718 54 2,196 Singapore 524 164 20 77 20 98 66 4 75 Sri Lanka 2,381 848 134 198 166 108 119 - 808 Taiwan 4,099 1,355 80 245 - 1,105 900 - 415 Thailand 8,316 2,581 235 2,710 1,924 375 211 - 282 Viet Nam 13,324 760 53 831 300 7,280 1,060 - 3,039 Total 502,219 218,320 34,474 45,932 22,323 114,891 25,024 433 40,823 Latin America Argentina 4,528 1,392 143 772 246 741 467 32 735 Bolivia 1,352 339 28 190 60 253 117 6 359 Brazil 32,156 16,900 1,096 8,724 506 464 1,854 42 2,571 Chile 1,802 555 57 305 97 297 188 13 291 Colombia 7,336 2,626 97 1,144 407 1,202 591 78 1,192 Costa Rica 750 198 13 181 10 87 158 2 101 Cuba 1,247 392 - 178 - 588 36 - 53 Dominican Republic 1,429 906 4 302 27 67 19 - 104 Ecuador 1,595 486 45 289 98 245 148 11 273 El Salvador 1,092 425 24 168 91 132 95 5 152 Guatemala 1,796 627 57 330 63 237 132 38 311 Guyana 46 14 1 8 3 7 4 0 8 Haiti 661 131 7 121 183 30 39 3 148 Honduras 1,126 346 31 170 82 202 119 5 171 Jamaica 409 76 - 132 69 7 106 - 20 Mexico 16,598 6,851 297 2,078 769 3,636 915 - 2,053 Nicaragua 1,008 381 8 220 217 96 50 - 38 Panama 492 274 3 100 7 51 14 10 34 Paraguay 1,052 250 23 191 83 200 134 8 162 Peru 4,105 749 30 408 918 554 341 37 1,066 Puerto Rico 498 292 22 61 8 6 41 3 64 Trinidad and Tobago 123 38 4 22 7 19 12 1 21 Uruguay 355 108 10 63 21 55 34 3 60 Venezuela 2,702 822 75 492 168 411 249 19 464 Total 84,257 35,177 2,077 16,647 4,139 9,588 5,862 317 10,451 Middle East/North Africa Algeria 2,881 262 11 971 159 738 149 19 571 Egypt 9,059 720 23 1,723 776 3,915 412 53 1,437 Iraq 1,784 159 9 610 69 420 96 35 387 Jordan 645 65 2 112 36 218 42 4 167 Kuwait 228 24 1 64 14 62 12 2 49 Lebanon 462 52 2 97 32 139 29 3 108 Libya 325 35 1 87 17 90 13 2 80 Morocco 3,117 317 10 1,133 146 706 149 19 637 Oman 198 25 1 59 9 43 11 10 39 Saudi Arabia 2,632 279 15 685 171 737 140 22 584 Sudan 1,049 112 8 438 32 139 32 17 272 Syria 2,565 251 7 553 126 846 122 17 642 Tunisia 1,404 329 - 252 23 487 37 29 246 Turkey 10,685 710 - 744 85 3,347 1,386 101 4,311 United Arab Emirates 293 30 2 102 15 65 13 5 60 Yemen 3,022 294 13 563 196 736 138 19 1,064 Total 40,350 3,664 105 8,193 1,906 12,690 2,781 357 10,653 Appendix A A.39 Table A.6c. Year 2015: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 739 106 15 160 118 36 44 6 256 Benin 842 47 4 185 81 111 48 7 360 Botswana 210 51 4 60 22 32 14 1 27 Burkina Faso 1,179 50 4 265 105 124 92 11 527 Burundi 212 4 1 9 15 8 4 0 172 Cameroon 1,869 170 10 477 95 288 127 20 681 Central African Republic 280 17 1 59 14 29 16 2 140 Chad 142 10 0 21 7 - 9 0 94 Congo 154 29 2 38 24 7 5 1 49 Congo, D.R. 1,139 36 6 95 82 22 87 15 796 Côte d'Ivoire 2,232 144 14 700 162 322 164 15 712 Eritrea 338 25 4 64 81 16 24 1 122 Ethiopia 3,472 285 38 909 960 99 175 13 993 Gabon 82 15 0 18 7 5 7 1 30 Gambia 101 15 0 27 14 6 3 1 35 Ghana 2,077 387 8 477 281 117 129 43 634 Guinea 250 21 2 79 27 12 22 2 85 Guinea-Bissau 48 7 1 11 2 1 4 1 22 Kenya 4,034 805 18 901 1,058 332 160 9 751 Lesotho 164 31 1 44 28 15 6 1 36 Liberia 115 14 3 24 19 5 8 1 42 Madagascar 1,440 321 13 224 518 75 78 5 207 Malawi 1,810 318 9 347 324 106 61 12 633 Mali 596 45 4 229 134 35 31 3 115 Mauritania 69 4 0 22 6 6 6 0 24 Mauritius 207 20 1 58 11 8 37 1 71 Mozambique 623 55 13 133 196 36 56 2 133 Namibia 276 73 6 55 52 27 24 2 38 Niger 799 50 5 276 86 94 20 9 258 Nigeria 16,589 2,550 56 3,590 2,436 1,633 809 173 5,342 Rwanda 360 52 2 65 57 11 11 2 161 Senegal 757 63 6 256 76 123 38 11 183 Sierra Leone 237 25 3 78 12 33 12 3 70 Somalia 328 48 2 148 16 41 6 8 59 South Africa 5,243 1,551 164 971 1,021 559 358 24 596 Swaziland 120 30 2 27 17 14 8 1 20 Tanzania 4,291 892 33 973 691 293 294 20 1,094 Togo 1,071 73 4 210 90 192 58 11 433 Uganda 2,719 351 2 519 955 47 265 3 578 Zambia 1,399 253 15 384 153 94 125 7 369 Zimbabwe 1,784 388 41 615 159 210 151 8 212 Total 60,393 9,431 516 13,801 10,211 5,225 3,593 456 17,163 Central Asia Republics Kazakhstan 1,893 86 - 73 18 1,286 138 12 279 Kyrgyzstan 793 89 3 129 52 269 56 5 190 Tajikistan 917 99 5 228 60 262 50 7 205 Turkmenistan 559 57 2 116 35 191 31 4 122 Uzbekistan 3,762 396 13 681 243 1,337 230 25 836 Total 7,923 726 23 1,228 409 3,345 505 53 1,633 Caucasus Armenia 288 86 6 58 22 38 21 2 54 Azerbaijan 902 97 5 221 60 260 50 7 202 Georgia 273 76 3 65 29 25 10 2 63 Total 1,462 259 14 344 111 323 81 11 319 Moldova, Russia, Ukraine Moldova 581 27 - 17 - 304 47 - 187 Russian Federation 16,974 5,332 696 2,374 581 3,273 2,249 117 2,352 Ukraine 4,983 104 - 222 - 1,379 1,001 59 2,217 Total 22,538 5,463 696 2,613 581 4,956 3,296 177 4,756 Grand Total 719,143 273,040 37,904 88,758 39,679 151,018 41,143 1,804 85,798 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.40 Table A.6d. Year 2020: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Asia Afghanistan 1,699 214 28 363 56 190 137 24 688 Bangladesh 24,469 2,920 127 6,125 2,169 5,789 1,704 131 5,504 Bhutan 271 79 5 57 22 34 18 2 54 Cambodia 806 158 5 198 159 49 21 4 211 China 203,094 85,231 24,352 7,306 487 80,361 4,870 - 487 China, Hong Kong SAR 863 188 10 169 - 50 347 30 69 India 159,565 113,832 6,343 7,010 - 5,341 10,348 - 16,691 Indonesia 32,255 1,982 214 9,374 14,900 3,321 482 54 1,928 Iran 11,456 1,878 203 3,740 - 1,320 1,117 - 3,198 Korea, DPR 3,142 969 103 523 163 526 336 22 500 Korea, Rep. 5,709 2,109 856 133 - 774 1,055 - 782 Laos 822 237 15 177 73 96 50 6 169 Malaysia 4,658 678 18 1,049 45 199 696 18 1,954 Mongolia 386 120 13 62 19 67 43 3 60 Myanmar 3,316 919 34 794 356 300 122 25 765 Nepal 3,670 1,146 183 656 450 329 220 21 665 Pakistan 14,956 1,972 83 3,875 1,024 3,362 1,171 108 3,362 Papua New Guinea 591 166 6 131 85 42 20 3 137 Philippines 10,658 3,167 278 1,951 643 1,568 940 70 2,041 Singapore 486 152 19 71 19 91 61 3 70 Sri Lanka 2,356 839 132 196 164 107 118 - 800 Taiwan 4,508 1,490 88 269 - 1,215 990 - 456 Thailand 8,204 2,546 231 2,673 1,898 370 208 - 278 Viet Nam 13,645 778 54 851 308 7,456 1,086 - 3,113 Total 511,585 223,771 33,400 47,752 23,038 112,956 26,160 524 43,983 Latin America Argentina 4,772 1,472 155 796 248 797 508 34 761 Bolivia 1,570 436 45 225 66 293 163 9 334 Brazil 33,156 17,426 1,130 8,995 521 478 1,912 43 2,651 Chile 1,806 556 58 306 97 297 188 13 291 Colombia 7,569 2,710 100 1,180 420 1,240 610 80 1,230 Costa Rica 776 205 14 187 10 91 163 2 104 Cuba 1,130 355 - 161 - 533 32 - 48 Dominican Republic 1,519 963 4 321 29 71 20 - 111 Ecuador 1,724 529 53 298 97 278 174 12 283 El Salvador 1,187 425 33 182 80 172 119 7 170 Guatemala 2,233 751 76 381 81 339 207 36 362 Guyana 44 13 1 8 3 7 4 0 7 Haiti 749 165 7 151 169 43 38 4 171 Honduras 1,303 406 47 179 67 252 163 7 182 Jamaica 408 76 - 131 68 7 105 - 20 Mexico 17,198 7,099 308 2,153 796 3,767 948 - 2,127 Nicaragua 1,128 427 8 246 241 108 56 - 42 Panama 528 294 4 107 7 54 15 11 36 Paraguay 1,224 321 37 199 74 242 166 9 177 Peru 4,423 808 33 440 989 598 368 39 1,149 Puerto Rico 496 291 22 61 8 6 41 3 64 Trinidad and Tobago 117 36 3 21 7 18 11 1 20 Uruguay 368 113 11 65 22 58 35 3 62 Venezuela 2,919 894 87 512 169 463 287 21 486 Total 88,348 36,769 2,237 17,307 4,268 10,211 6,332 334 10,890 Middle East/North Africa Algeria 3,021 326 13 727 198 877 177 22 680 Egypt 10,212 940 29 1,909 822 4,006 538 64 1,904 Iraq 2,182 202 12 718 102 533 111 35 470 Jordan 737 81 2 123 46 242 50 5 188 Kuwait 249 26 1 65 16 70 13 2 55 Lebanon 476 54 2 100 33 143 29 4 111 Libya 359 38 2 94 22 101 18 3 81 Morocco 3,338 353 13 1,004 188 861 177 22 720 Oman 229 27 1 68 12 54 12 8 46 Saudi Arabia 3,129 341 15 745 208 905 178 25 711 Sudan 1,236 130 11 489 46 179 43 18 320 Syria 2,958 319 10 582 175 951 170 20 732 Tunisia 1,404 329 - 252 23 487 37 29 246 Turkey 11,252 748 - 783 89 3,525 1,460 107 4,540 United Arab Emirates 325 32 3 109 19 76 14 3 70 Yemen 4,257 480 13 585 294 1,203 267 26 1,390 Total 45,364 4,427 128 8,352 2,292 14,213 3,295 393 12,264 Appendix A A.41 Table A.6d. Year 2020: Projected Number of Contraceptive Users by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Any Trad. Sub-Saharan Africa Angola 1,045 185 17 237 156 57 51 8 334 Benin 1,135 79 6 285 96 195 59 9 405 Botswana 213 56 5 53 19 32 16 1 30 Burkina Faso 1,684 97 7 419 138 253 115 15 640 Burundi 308 14 1 23 26 11 6 1 225 Cameroon 2,215 206 14 619 119 407 132 23 697 Central African Republic 342 25 2 86 18 50 17 3 140 Chad 210 18 1 29 10 - 15 1 135 Congo 225 46 2 56 33 11 6 2 69 Congo, D.R. 1,757 103 12 202 161 42 121 21 1,093 Côte d'Ivoire 2,751 208 19 886 186 482 170 22 778 Eritrea 446 48 5 92 95 20 26 2 156 Ethiopia 4,563 532 47 1,175 1,083 150 197 23 1,357 Gabon 93 20 1 21 8 6 6 1 30 Gambia 123 22 1 32 17 7 3 1 40 Ghana 2,440 521 13 574 314 157 126 40 695 Guinea 334 31 3 108 30 25 25 3 109 Guinea-Bissau 77 10 1 19 3 5 6 1 31 Kenya 5,309 1,218 54 1,141 1,095 527 273 19 981 Lesotho 168 37 1 44 26 16 6 1 38 Liberia 170 24 3 37 27 8 10 1 59 Madagascar 1,940 484 29 317 516 163 129 9 294 Malawi 2,332 499 19 473 350 176 92 16 706 Mali 872 71 7 329 154 81 43 6 181 Mauritania 92 7 1 30 7 10 7 1 31 Mauritius 206 20 1 58 11 8 37 1 71 Mozambique 784 76 17 165 209 42 65 4 207 Namibia 305 85 7 60 45 35 26 2 46 Niger 1,406 108 8 468 125 259 45 15 378 Nigeria 21,783 4,380 127 4,910 2,868 2,088 957 204 6,250 Rwanda 463 83 2 97 70 18 11 3 178 Senegal 941 83 8 323 79 165 45 13 226 Sierra Leone 333 35 4 111 17 53 16 4 92 Somalia 453 59 3 192 23 69 12 9 87 South Africa 5,331 1,600 164 964 734 685 432 30 722 Swaziland 123 33 3 26 15 16 9 1 21 Tanzania 5,296 1,273 63 1,169 699 470 356 30 1,236 Togo 1,386 115 6 295 108 305 76 13 468 Uganda 4,647 752 13 932 1,392 156 396 11 996 Zambia 1,808 404 33 430 161 184 174 11 412 Zimbabwe 1,916 475 55 538 138 270 190 10 240 Total 78,026 14,138 785 18,024 11,383 7,715 4,506 592 20,884 Central Asia Republics Kazakhstan 1,861 84 - 72 18 1,265 136 12 274 Kyrgyzstan 851 102 3 140 60 268 60 6 212 Tajikistan 1,047 116 5 239 70 307 61 8 240 Turkmenistan 600 67 3 133 41 178 36 5 138 Uzbekistan 4,080 476 15 765 283 1,258 270 29 983 Total 8,439 846 26 1,349 472 3,277 562 60 1,848 Caucasus Armenia 272 81 6 55 21 36 20 2 52 Azerbaijan 875 94 4 215 58 252 49 7 196 Georgia 253 70 3 61 27 23 9 2 59 Total 1,400 245 13 330 106 311 77 11 306 Moldova, Russia, Ukraine Moldova 551 26 - 16 - 288 44 - 177 Russian Federation 16,033 5,037 657 2,243 548 3,092 2,124 111 2,222 Ukraine 4,538 95 - 203 - 1,256 912 54 2,019 Total 21,122 5,157 657 2,461 548 4,636 3,080 165 4,418 Grand Total 754,284 285,353 37,246 95,575 42,107 153,319 44,013 2,078 94,593 Note: Dashes mean the quantity is negligible. Appendix A A.42 Table A.7a. Year 2005: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 5.50 1 36 3 - 4,866 627 Bangladesh 223.66 15 94,470 8,304 416 147,572 3,590 Bhutan 4.20 0 505 62 3 550 127 Cambodia 5.37 0 1,617 615 8 2,260 87 China 10,156.41 2,902 117,524 2,089 24,624 626,796 - China, Hong Kong SAR 23.58 1 2,848 - 16 46,902 4,020 India 8,883.51 495 73,856 - 1,072 872,199 - Indonesia 182.31 20 116,406 49,613 786 47,893 5,321 Iran 176.19 19 47,357 - 318 113,141 - Korea, DPR 104.63 11 7,627 634 146 39,140 2,599 Korea, Rep. 272.98 111 2,319 - 258 147,407 - Laos 11.54 0 1,496 193 8 1,213 368 Malaysia 54.86 1 11,454 133 41 60,826 1,580 Mongolia 10.53 1 845 77 14 3,471 269 Myanmar 73.28 7 9,682 1,876 55 7,836 1,850 Nepal 85.33 28 3,299 1,682 22 16,554 604 Pakistan 184.32 2 17,770 2,700 357 148,703 2,849 Papua New Guinea 10.56 0 958 303 2 821 80 Philippines 191.46 6 22,121 1,697 191 38,498 2,019 Singapore 18.90 2 1,193 84 29 8,241 454 Sri Lanka 90.82 14 2,869 641 30 13,773 - Taiwan 113.16 7 2,762 - 237 81,173 - Thailand 284.64 26 40,348 7,649 106 25,152 - Viet Nam 74.63 5 11,012 1,069 1,839 112,466 - Total 21,242 3,676 590,374 79,423 30,579 2,567,454 26,444 Latin America Argentina 133.53 13 10,599 953 174 44,659 3,396 Bolivia 17.43 0 1,460 127 55 6,411 176 Brazil 1,717.33 111 119,678 1,857 121 203,510 4,625 Chile 57.96 6 4,303 364 80 21,196 1,447 Colombia 250.68 9 14,736 1,406 295 60,940 7,992 Costa Rica 19.56 1 2,413 36 22 16,836 214 Cuba 47.81 - 2,934 - 184 4,694 - Dominican Republic 84.72 0 3,812 92 16 1,893 - Ecuador 42.73 3 3,757 368 51 12,147 1,122 El Salvador 45.45 1 1,882 425 15 5,872 201 Guatemala 46.08 4 3,097 66 33 6,413 4,402 Guyana 1.54 0 121 11 2 518 39 Haiti 7.07 1 862 825 2 5,115 92 Honduras 24.66 1 1,920 384 34 5,843 183 Jamaica 7.95 - 1,850 257 2 11,865 - Mexico 642.16 28 26,289 2,605 876 92,638 - Nicaragua 29.29 1 2,282 604 19 4,127 - Panama 25.28 0 1,243 23 12 1,348 1,011 Paraguay 13.48 0 2,372 341 39 10,549 730 Peru 66.73 3 4,907 2,951 127 32,811 3,515 Puerto Rico 31.82 2 904 33 2 4,823 301 Trinidad and Tobago 4.55 0 354 31 6 1,567 115 Uruguay 11.08 1 870 78 15 3,763 281 Venezuela 73.83 6 6,359 612 90 21,740 1,925 Total 3,403 193 219,003 14,447 2,270 581,278 31,769 Middle East/North Africa Algeria 12.23 1 21,313 269 115 10,113 1,272 Egypt 33.50 1 19,068 2,849 1,110 22,127 3,731 Iraq 8.96 0 5,588 50 64 8,183 3,828 Jordan 3.49 0 1,090 59 47 3,112 322 Kuwait 1.56 0 1,311 21 9 992 246 Lebanon 5.11 0 1,286 111 35 3,017 364 Libya 3.28 0 991 21 20 465 85 Morocco 26.61 0 20,904 221 106 11,075 1,152 Oman 2.38 0 573 14 6 1,055 1,574 Saudi Arabia 17.86 1 7,319 400 119 8,839 1,745 Sudan 8.19 0 4,979 26 21 993 1,617 Syria 13.99 0 6,570 137 185 4,637 1,249 Tunisia 33.29 - 3,439 84 127 4,065 3,127 Turkey 67.56 - 9,555 291 819 142,462 10,424 United Arab Emirates 2.78 0 1,205 25 11 1,409 1,008 Yemen 10.91 1 4,114 313 64 3,271 898 Total 252 5 109,308 4,893 2,857 225,813 32,642 Appendix A A.43 Table A.7a. Year 2005: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 3.88 1 1,002 231 5 3,188 306 Benin 1.29 0 838 209 7 3,499 324 Botswana 4.09 0 1,192 117 9 1,179 52 Burkina Faso 0.96 0 1,329 222 7 6,155 557 Burundi 0.15 - 40 27 1 161 - Cameroon 11.11 0 2,799 195 22 14,002 1,545 Central African Republic 0.76 0 306 31 1 1,446 166 Chad 0.50 - 203 18 - 542 - Congo 1.83 0 324 55 1 337 82 Congo, D.R. 1.92 - 648 138 2 5,181 1,036 Côte d'Ivoire 3.89 0 5,257 467 21 17,337 394 Eritrea 0.49 0 443 210 3 1,717 22 Ethiopia 7.34 1 7,922 2,619 10 10,912 215 Gabon 0.56 0 158 10 0 927 30 Gambia 0.44 0 250 33 1 321 65 Ghana 14.93 0 4,066 803 15 16,934 5,690 Guinea 0.88 0 653 80 1 1,574 29 Guinea-Bissau 0.33 0 60 3 - 226 42 Kenya 46.54 0 8,577 3,372 52 10,485 17 Lesotho 1.84 0 667 141 5 800 36 Liberia 0.70 0 177 40 1 540 53 Madagascar 14.77 0 1,278 1,608 2 4,785 77 Malawi 9.21 0 2,159 943 9 3,911 660 Mali 1.58 0 1,557 317 2 1,563 49 Mauritania 0.10 0 175 16 1 439 6 Mauritius 2.16 0 846 44 2 4,305 129 Mozambique 4.92 0 1,372 617 6 3,439 38 Namibia 4.91 0 589 250 3 2,268 94 Niger 0.26 0 418 60 0 130 136 Nigeria 45.19 1 22,931 5,810 307 76,745 13,340 Rwanda 1.67 0 304 130 1 882 28 Senegal 2.96 0 2,062 269 18 2,999 942 Sierra Leone 1.63 0 659 26 5 856 213 Somalia 3.01 0 1,204 30 4 123 578 South Africa 164.32 20 14,737 7,076 81 25,455 945 Swaziland 2.26 0 421 97 3 515 119 Tanzania 32.20 0 8,435 2,370 19 28,343 442 Togo 1.92 0 847 240 12 4,096 840 Uganda 14.84 - 3,205 1,789 4 15,223 - Zambia 7.69 0 3,959 432 3 9,529 338 Zimbabwe 19.18 1 11,792 792 22 8,598 344 Total 439 29 115,856 31,937 670 291,671 29,980 Central Asia Republics Kazakhstan 9.97 - 1,154 77 385 17,305 1,538 Kyrgyzstan 4.47 0 899 103 99 6,714 295 Tajikistan 7.19 0 2,728 161 49 3,686 660 Turkmenistan 2.98 0 690 64 75 2,372 151 Uzbekistan 15.73 1 4,374 480 547 14,684 957 Total 40 1 9,844 885 1,155 44,760 3,601 Caucasus Armenia 10.77 1 962 95 13 2,974 284 Azerbaijan 10.63 0 3,260 235 73 5,907 846 Georgia 9.66 0 1,128 135 8 1,377 287 Total 31 2 5,351 465 94 10,259 1,417 Moldova, Russia, Ukraine Moldova 3.28 - 273 - 95 6,141 - Russian Federation 703.82 92 42,307 2,760 1,111 320,530 16,713 Ukraine 13.80 - 3,991 - 471 143,687 8,515 Total 721 92 46,571 2,760 1,677 470,359 25,228 Grand Total 26,128 3,997 1,096,306 134,811 39,303 4,191,594 151,081 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.44 Table A.7b. Year 2010: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 11.05 2 652 28 3 9,266 1,288 Bangladesh 258.73 15 96,313 8,519 828 166,457 7,853 Bhutan 5.71 0 642 75 5 944 167 Cambodia 9.09 1 2,087 645 10 2,408 229 China 10,333.84 2,953 119,577 2,126 25,054 637,745 - China, Hong Kong SAR 22.99 1 2,777 - 16 45,732 3,920 India 10,266.57 572 85,354 - 1,239 1,007,991 - Indonesia 198.07 21 126,472 53,870 853 52,034 5,782 Iran 194.58 21 52,301 - 352 124,954 - Korea, DPR 109.23 12 7,962 661 152 40,860 2,713 Korea, Rep. 264.66 107 2,249 - 250 142,915 - Laos 15.81 1 1,923 238 13 2,107 484 Malaysia 63.40 2 13,238 153 48 70,300 1,826 Mongolia 11.81 1 885 75 16 4,266 296 Myanmar 92.85 3 11,003 1,329 76 12,669 2,783 Nepal 99.57 25 5,608 1,756 44 19,166 1,258 Pakistan 198.20 5 31,934 3,183 550 147,749 6,334 Papua New Guinea 13.26 0 1,322 324 5 1,226 191 Philippines 248.53 14 25,330 2,116 274 61,010 4,324 Singapore 19.00 2 1,199 84 29 8,284 456 Sri Lanka 93.84 15 2,965 661 31 14,231 - Taiwan 133.57 8 3,260 - 280 95,818 - Thailand 289.52 26 41,040 7,772 108 25,583 - Viet Nam 81.76 6 12,064 1,164 2,014 123,206 - Total 23,036 3,813 648,158 84,780 32,250 2,816,921 39,904 Latin America Argentina 144.39 14 11,171 981 192 50,045 3,645 Bolivia 26.90 2 2,189 192 63 9,551 456 Brazil 1,821.78 118 126,956 1,964 129 215,887 4,907 Chile 60.86 6 4,518 382 84 22,257 1,519 Colombia 275.33 10 16,184 1,543 324 66,932 8,778 Costa Rica 21.05 1 2,596 38 24 18,115 231 Cuba 47.32 - 2,904 - 183 4,646 - Dominican Republic 93.57 0 4,211 101 18 2,091 - Ecuador 48.37 4 4,082 387 60 14,749 1,254 El Salvador 46.44 2 2,217 400 26 8,465 403 Guatemala 57.25 5 4,049 158 47 9,881 4,653 Guyana 1.56 0 123 11 2 525 40 Haiti 10.55 1 1,323 792 5 4,890 220 Honduras 31.39 2 2,298 373 44 9,463 407 Jamaica 8.33 - 1,939 269 2 12,441 - Mexico 713.01 31 29,190 2,882 973 102,859 - Nicaragua 35.84 1 2,792 737 23 5,049 - Panama 27.93 0 1,373 25 13 1,490 1,117 Paraguay 19.99 1 2,685 351 47 12,880 856 Peru 75.53 3 5,554 3,335 144 37,138 3,979 Puerto Rico 32.41 2 921 33 2 4,912 307 Trinidad and Tobago 4.46 0 348 31 6 1,524 113 Uruguay 11.58 1 909 81 15 3,930 293 Venezuela 83.20 7 6,972 657 104 25,648 2,151 Total 3,699 213 237,505 15,725 2,528 645,368 35,329 Middle East/North Africa Algeria 21.20 1 18,392 465 167 14,332 1,837 Egypt 56.49 2 22,844 2,977 1,114 35,368 5,109 Iraq 13.00 1 7,391 149 89 9,820 4,105 Jordan 5.22 0 1,414 99 54 3,976 421 Kuwait 2.10 0 1,164 39 14 1,214 244 Lebanon 5.50 0 1,383 120 38 3,244 391 Libya 3.60 0 1,159 43 23 1,008 173 Morocco 31.11 1 19,072 409 155 14,559 1,721 Oman 2.60 0 745 27 9 1,183 1,330 Saudi Arabia 24.20 1 9,035 540 164 12,498 2,208 Sudan 10.36 1 5,783 71 29 2,351 1,856 Syria 20.65 1 7,606 314 213 9,299 1,666 Tunisia 35.97 - 3,716 90 137 4,391 3,378 Turkey 73.66 - 10,417 317 893 155,315 11,365 United Arab Emirates 3.11 0 1,390 43 15 1,524 831 Yemen 19.16 1 6,498 505 119 7,620 1,514 Total 328 9 118,009 6,209 3,233 277,702 38,148 Appendix A A.45 Table A.7b. Year 2010: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 6.63 1 1,563 341 7 4,320 462 Benin 2.78 0 1,599 266 16 4,578 526 Botswana 4.96 0 1,029 101 9 1,424 90 Burkina Faso 2.47 0 2,332 312 16 8,491 869 Burundi 0.21 0 59 37 2 251 3 Cameroon 14.93 1 4,902 282 49 14,879 1,968 Central African Republic 1.23 0 538 41 4 1,657 224 Chad 0.66 0 242 22 - 699 7 Congo 2.25 0 397 67 1 412 101 Congo, D.R. 2.38 0 832 185 3 6,801 1,300 Côte d'Ivoire 9.25 1 7,685 555 51 18,830 1,054 Eritrea 1.20 0 652 268 3 2,374 74 Ethiopia 14.86 3 10,447 3,273 17 16,502 714 Gabon 1.12 0 216 18 1 872 46 Gambia 0.97 0 323 44 2 362 82 Ghana 28.20 0 5,620 978 23 16,341 5,529 Guinea 1.49 0 873 96 2 2,086 96 Guinea-Bissau 0.47 0 87 4 0 321 60 Kenya 59.71 0 10,421 3,834 65 12,844 264 Lesotho 2.74 0 670 127 4 753 69 Liberia 0.93 0 233 53 1 701 70 Madagascar 22.70 1 2,123 1,890 8 6,309 263 Malawi 19.39 0 3,484 1,140 16 5,123 992 Mali 2.91 0 2,339 432 4 2,543 172 Mauritania 0.22 0 234 19 1 572 22 Mauritius 2.22 0 871 46 2 4,436 133 Mozambique 5.13 1 1,626 710 8 5,118 122 Namibia 6.57 0 721 231 5 2,512 145 Niger 1.93 0 1,853 208 4 902 580 Nigeria 130.16 3 36,090 7,791 379 88,248 17,039 Rwanda 3.16 0 567 178 2 1,150 91 Senegal 4.84 0 2,886 294 25 3,862 1,166 Sierra Leone 2.03 0 826 33 6 1,067 266 Somalia 4.09 0 1,654 44 7 369 757 South Africa 168.48 19 14,740 5,522 121 34,062 1,944 Swaziland 2.87 0 422 84 4 704 120 Tanzania 60.81 1 11,452 2,641 44 30,935 1,316 Togo 4.37 0 1,864 298 29 5,350 1,091 Uganda 20.73 0 4,439 2,425 6 20,559 33 Zambia 15.48 1 4,895 533 11 11,527 559 Zimbabwe 31.92 3 10,532 723 41 13,274 684 Total 669 39 154,340 36,145 999 354,124 41,102 Central Asia Republics Kazakhstan 9.93 - 1,148 77 383 17,227 1,531 Kyrgyzstan 7.28 0 1,496 159 88 6,742 475 Tajikistan 9.04 0 3,154 201 62 4,798 784 Turkmenistan 4.77 0 1,279 104 66 3,115 320 Uzbekistan 30.35 1 7,644 740 472 21,306 2,026 Total 61 2 14,721 1,281 1,071 53,189 5,136 Caucasus Armenia 10.36 1 931 93 12 2,831 274 Azerbaijan 11.08 1 3,399 245 76 6,158 882 Georgia 9.21 0 1,071 128 8 1,334 273 Total 31 2 5,401 465 96 10,323 1,429 Moldova, Russia, Ukraine Moldova 3.17 - 264 - 92 5,938 - Russian Federation 648.91 85 39,006 2,545 1,024 295,525 15,409 Ukraine 12.85 - 3,717 - 439 133,827 7,930 Total 665 85 42,988 2,545 1,555 435,290 23,340 Grand Total 28,489 4,162 1,221,123 147,151 41,732 4,592,916 184,387 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.46 Table A.7c. Year 2015: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 16.94 2 2,342 94 18 13,050 2,014 Bangladesh 291.76 15 94,732 8,598 1,247 185,114 11,926 Bhutan 7.27 0 755 84 7 1,502 205 Cambodia 13.29 1 2,529 639 12 2,458 387 China 10,120.58 2,892 117,110 2,082 24,537 624,584 - China, Hong Kong SAR 21.80 1 2,633 - 15 43,361 3,717 India 11,531.44 643 95,870 - 1,391 1,132,177 - Indonesia 211.61 23 135,116 57,413 912 55,591 6,177 Iran 202.23 22 54,356 - 365 129,865 - Korea, DPR 111.24 12 8,108 672 155 41,612 2,763 Korea, Rep. 252.01 102 2,141 - 238 136,085 - Laos 20.88 1 2,314 270 19 3,725 609 Malaysia 70.74 2 14,770 170 53 78,432 2,037 Mongolia 12.65 1 908 74 18 4,814 313 Myanmar 99.40 4 11,645 1,396 83 14,064 2,960 Nepal 113.79 23 7,826 1,790 69 22,581 1,916 Pakistan 208.02 7 45,588 3,635 755 143,205 9,757 Papua New Guinea 15.98 1 1,666 335 8 1,770 305 Philippines 302.10 22 27,664 2,397 360 86,114 6,438 Singapore 18.21 2 1,149 80 28 7,938 437 Sri Lanka 94.22 15 2,977 664 31 14,289 - Taiwan 150.53 9 3,674 - 316 107,978 - Thailand 286.73 26 40,644 7,695 107 25,336 - Viet Nam 84.43 6 12,458 1,202 2,080 127,230 - Total 24,258 3,830 688,974 89,290 32,826 3,002,876 51,961 Latin America Argentina 154.70 16 11,576 985 212 56,021 3,870 Bolivia 37.63 3 2,847 238 72 14,088 769 Brazil 1,877.74 122 130,856 2,023 132 222,519 5,057 Chile 61.63 6 4,575 387 85 22,539 1,538 Colombia 291.82 11 17,154 1,628 343 70,941 9,304 Costa Rica 22.01 1 2,715 40 25 18,942 241 Cuba 43.56 - 2,673 - 168 4,277 - Dominican Republic 100.65 0 4,529 109 19 2,249 - Ecuador 53.99 5 4,329 393 70 17,814 1,378 El Salvador 47.20 3 2,513 364 38 11,413 609 Guatemala 69.68 6 4,956 252 68 15,889 4,589 Guyana 1.55 0 122 11 2 521 39 Haiti 14.50 1 1,813 732 9 4,633 362 Honduras 38.39 3 2,554 329 58 14,238 650 Jamaica 8.48 - 1,974 274 2 12,665 - Mexico 761.24 33 31,164 3,074 1,039 109,816 - Nicaragua 42.28 1 3,294 867 28 5,956 - Panama 30.46 0 1,497 27 15 1,624 1,218 Paraguay 27.76 3 2,869 330 57 16,062 975 Peru 83.27 3 6,123 3,673 158 40,945 4,387 Puerto Rico 32.41 2 921 33 2 4,913 307 Trinidad and Tobago 4.17 0 329 29 5 1,404 106 Uruguay 12.04 1 946 84 16 4,089 305 Venezuela 91.38 8 7,376 673 118 29,848 2,336 Total 3,909 231 249,706 16,557 2,739 703,407 38,041 Middle East/North Africa Algeria 29.09 1 14,562 636 211 17,931 2,292 Egypt 79.99 3 25,840 3,105 1,119 49,460 6,391 Iraq 17.63 1 9,149 275 120 11,489 4,154 Jordan 7.17 0 1,682 144 62 5,010 518 Kuwait 2.61 0 960 57 18 1,419 232 Lebanon 5.81 0 1,461 126 40 3,426 413 Libya 3.93 0 1,298 66 26 1,577 258 Morocco 35.22 1 17,001 584 202 17,911 2,230 Oman 2.83 0 888 38 12 1,320 1,158 Saudi Arabia 30.95 2 10,279 685 211 16,749 2,609 Sudan 12.46 1 6,570 127 40 3,795 2,047 Syria 27.88 1 8,293 505 242 14,659 2,059 Tunisia 36.61 - 3,782 92 139 4,469 3,438 Turkey 78.90 - 11,158 339 956 166,358 12,173 United Arab Emirates 3.35 0 1,532 60 19 1,598 629 Yemen 32.67 1 8,439 784 210 16,553 2,261 Total 407 12 122,893 7,625 3,626 333,724 42,861 Appendix A A.47 Table A.7c. Year 2015: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 11.77 2 2,393 473 10 5,222 673 Benin 5.24 0 2,772 323 32 5,736 800 Botswana 5.61 0 896 87 9 1,661 119 Burkina Faso 5.54 0 3,981 421 36 10,998 1,298 Burundi 0.48 0 128 59 2 464 19 Cameroon 18.91 1 7,160 378 82 15,278 2,354 Central African Republic 1.94 0 888 55 8 1,869 300 Chad 1.12 0 308 28 - 1,117 42 Congo 3.26 0 566 94 2 562 143 Congo, D.R. 4.05 1 1,422 329 6 10,422 1,830 Côte d'Ivoire 16.02 2 10,494 646 92 19,623 1,846 Eritrea 2.80 0 967 324 5 2,864 162 Ethiopia 31.65 4 13,633 3,839 28 20,962 1,580 Gabon 1.70 0 267 26 1 809 61 Gambia 1.67 0 404 57 2 379 101 Ghana 43.05 1 7,148 1,124 33 15,466 5,154 Guinea 2.34 0 1,190 110 3 2,584 207 Guinea-Bissau 0.75 0 159 7 0 496 95 Kenya 89.44 2 13,519 4,231 95 19,175 1,052 Lesotho 3.48 0 665 114 4 734 95 Liberia 1.51 0 354 77 2 953 104 Madagascar 35.65 1 3,353 2,072 21 9,389 598 Malawi 35.32 1 5,212 1,297 30 7,338 1,428 Mali 4.96 0 3,439 536 10 3,759 405 Mauritania 0.44 0 323 23 2 703 50 Mauritius 2.21 0 867 45 2 4,415 133 Mozambique 6.10 1 1,991 783 10 6,694 269 Namibia 8.11 1 823 207 8 2,833 191 Niger 5.56 1 4,146 344 27 2,378 1,119 Nigeria 283.30 6 53,856 9,743 467 97,066 20,718 Rwanda 5.79 0 975 229 3 1,280 194 Senegal 7.00 1 3,836 305 35 4,619 1,354 Sierra Leone 2.82 0 1,174 47 9 1,459 367 Somalia 5.30 0 2,222 65 12 780 933 South Africa 172.29 18 14,558 4,085 160 42,993 2,829 Swaziland 3.33 0 409 70 4 901 119 Tanzania 99.08 4 14,599 2,764 84 35,288 2,444 Togo 8.10 0 3,145 360 55 6,980 1,333 Uganda 38.98 0 7,781 3,821 13 31,805 301 Zambia 28.08 2 5,767 610 27 14,942 875 Zimbabwe 43.09 5 9,224 637 60 18,128 974 Total 1,048 57 207,011 40,843 1,493 431,126 54,670 Central Asia Republics Kazakhstan 9.53 - 1,102 73 367 16,537 1,470 Kyrgyzstan 9.83 0 1,936 210 77 6,726 624 Tajikistan 10.95 1 3,426 242 75 6,051 886 Turkmenistan 6.34 0 1,744 139 55 3,762 463 Uzbekistan 44.03 1 10,213 973 382 27,562 2,966 Total 81 3 18,421 1,637 956 60,638 6,408 Caucasus Armenia 9.54 1 865 87 11 2,559 253 Azerbaijan 10.81 1 3,316 239 74 6,009 860 Georgia 8.41 0 981 117 7 1,207 250 Total 29 2 5,162 443 92 9,774 1,363 Moldova, Russia, Ukraine Moldova 2.99 - 249 - 87 5,600 - Russian Federation 592.48 77 35,614 2,323 935 269,825 14,069 Ukraine 11.54 - 3,337 - 394 120,137 7,119 Total 607 77 39,200 2,323 1,416 395,562 21,189 Grand Total 30,338 4,212 1,331,368 158,716 43,148 4,937,106 216,492 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.48 Table A.7d. Year 2020: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 23.73 3 5,443 224 54 16,381 2,834 Bangladesh 324.42 14 91,876 8,677 1,654 204,533 15,697 Bhutan 8.81 1 849 90 10 2,147 241 Cambodia 17.57 1 2,965 634 14 2,566 539 China 9,470.13 2,706 109,583 1,948 22,960 584,443 - China, Hong Kong SAR 20.94 1 2,529 - 14 41,652 3,570 India 12,648.00 705 105,153 - 1,526 1,241,803 - Indonesia 220.21 24 140,607 59,601 949 57,850 6,428 Iran 208.71 23 56,097 - 377 134,023 - Korea, DPR 107.68 11 7,849 650 150 40,280 2,675 Korea, Rep. 234.39 95 1,991 - 221 126,569 - Laos 26.34 2 2,651 290 27 5,948 734 Malaysia 75.37 2 15,737 181 57 83,571 2,171 Mongolia 13.30 1 934 74 19 5,201 327 Myanmar 102.09 4 11,915 1,425 86 14,611 3,033 Nepal 127.33 20 9,837 1,800 94 26,441 2,534 Pakistan 219.06 9 58,129 4,095 961 140,511 12,938 Papua New Guinea 18.50 1 1,965 339 12 2,373 410 Philippines 351.94 31 29,267 2,571 448 112,774 8,389 Singapore 16.89 2 1,066 74 26 7,363 405 Sri Lanka 93.20 15 2,945 657 31 14,135 - Taiwan 165.55 10 4,041 - 347 118,757 - Thailand 282.87 26 40,096 7,591 106 24,995 - Viet Nam 86.46 6 12,759 1,231 2,130 130,300 - Total 24,863 3,711 716,282 92,153 32,273 3,139,226 62,924 Latin America Argentina 163.51 17 11,947 993 228 60,988 4,064 Bolivia 48.42 5 3,374 262 84 19,527 1,074 Brazil 1,936.18 126 134,929 2,086 137 229,444 5,215 Chile 61.76 6 4,585 387 85 22,586 1,541 Colombia 301.09 11 17,699 1,680 354 73,195 9,599 Costa Rica 22.78 2 2,810 42 26 19,605 250 Cuba 39.47 - 2,422 - 152 3,875 - Dominican Republic 107.00 0 4,815 116 20 2,391 - Ecuador 58.76 6 4,473 387 79 20,822 1,477 El Salvador 47.25 4 2,726 318 49 14,291 796 Guatemala 83.47 8 5,710 323 97 24,791 4,330 Guyana 1.49 0 118 11 2 503 38 Haiti 18.39 1 2,267 676 12 4,515 496 Honduras 45.13 5 2,692 266 72 19,588 882 Jamaica 8.45 - 1,966 273 2 12,610 - Mexico 788.81 34 32,293 3,184 1,076 113,793 - Nicaragua 47.41 1 3,693 965 31 6,678 - Panama 32.63 0 1,604 29 16 1,740 1,305 Paraguay 35.68 4 2,979 297 69 19,873 1,091 Peru 89.75 4 6,600 3,955 171 44,131 4,728 Puerto Rico 32.33 2 919 33 2 4,900 306 Trinidad and Tobago 3.96 0 317 29 5 1,308 101 Uruguay 12.51 1 982 88 16 4,246 317 Venezuela 99.29 10 7,684 675 132 34,417 2,507 Total 4,085 249 259,602 17,072 2,917 759,819 40,118 Middle East/North Africa Algeria 36.24 1 10,909 791 251 21,250 2,687 Egypt 104.48 3 28,636 3,286 1,145 64,574 7,677 Iraq 22.42 1 10,771 407 152 13,321 4,161 Jordan 9.00 0 1,843 185 69 6,005 596 Kuwait 2.92 0 972 65 20 1,576 245 Lebanon 5.98 0 1,505 130 41 3,530 426 Libya 4.24 0 1,408 88 29 2,136 335 Morocco 39.26 1 15,060 750 246 21,223 2,696 Oman 3.05 0 1,017 48 15 1,456 988 Saudi Arabia 37.94 2 11,170 832 259 21,396 2,966 Sudan 14.41 1 7,330 184 51 5,151 2,209 Syria 35.42 1 8,729 700 272 20,406 2,428 Tunisia 36.61 - 3,781 92 139 4,469 3,438 Turkey 83.08 - 11,750 357 1,007 175,184 12,818 United Arab Emirates 3.50 0 1,630 77 22 1,627 395 Yemen 53.30 1 8,772 1,174 344 32,086 3,061 Total 492 14 125,283 9,166 4,061 395,389 47,124 Appendix A A.49 Table A.7d. Year 2020: Projected Contraceptive Commodities by Method Among All Women (Aged 15-49) (000s) Sterilization Country Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 20.54 2 3,553 625 16 6,089 956 Benin 8.75 1 4,277 385 56 7,127 1,135 Botswana 6.20 1 800 77 9 1,902 142 Burkina Faso 10.82 1 6,280 551 72 13,806 1,837 Burundi 1.61 0 340 103 3 746 69 Cameroon 22.88 2 9,278 476 116 15,821 2,713 Central African Republic 2.78 0 1,297 71 14 2,084 381 Chad 2.01 0 437 39 - 1,840 131 Congo 5.09 0 838 134 3 767 210 Congo, D.R. 11.49 1 3,037 643 12 14,571 2,564 Côte d'Ivoire 23.07 2 13,289 745 138 20,459 2,627 Eritrea 5.33 1 1,387 380 6 3,148 279 Ethiopia 59.08 5 17,619 4,333 43 23,600 2,781 Gabon 2.22 0 311 33 2 765 74 Gambia 2.43 0 487 69 2 396 120 Ghana 57.88 1 8,607 1,256 45 15,108 4,840 Guinea 3.41 0 1,619 121 7 3,019 356 Guinea-Bissau 1.10 0 292 13 1 687 140 Kenya 135.33 6 17,118 4,380 151 32,776 2,336 Lesotho 4.08 0 661 103 4 741 116 Liberia 2.67 0 550 109 2 1,194 154 Madagascar 53.76 3 4,750 2,066 47 15,479 1,077 Malawi 55.42 2 7,091 1,401 50 11,090 1,927 Mali 7.85 1 4,939 616 23 5,154 768 Mauritania 0.74 0 445 27 3 818 91 Mauritius 2.21 0 865 45 2 4,402 132 Mozambique 8.44 2 2,478 837 12 7,784 459 Namibia 9.40 1 893 182 10 3,168 228 Niger 11.95 1 7,016 502 74 5,366 1,747 Nigeria 486.62 14 73,650 11,471 597 114,828 24,508 Rwanda 9.24 0 1,461 280 5 1,366 318 Senegal 9.25 1 4,842 315 47 5,346 1,529 Sierra Leone 3.88 0 1,664 68 15 1,955 492 Somalia 6.57 0 2,877 94 20 1,382 1,078 South Africa 177.82 18 14,467 2,935 196 51,813 3,585 Swaziland 3.66 0 392 59 5 1,078 117 Tanzania 141.39 7 17,538 2,796 134 42,671 3,637 Togo 12.76 1 4,420 430 87 9,133 1,569 Uganda 83.53 1 13,973 5,567 45 47,563 1,288 Zambia 44.88 4 6,450 644 52 20,889 1,262 Zimbabwe 52.75 6 8,069 554 77 22,834 1,217 Total 1,571 87 270,355 45,531 2,204 540,767 70,989 Central Asia Republics Kazakhstan 9.37 - 1,084 72 361 16,261 1,445 Kyrgyzstan 11.39 0 2,097 240 77 7,194 700 Tajikistan 12.85 1 3,583 281 88 7,370 971 Turkmenistan 7.43 0 1,996 162 51 4,303 548 Uzbekistan 52.93 2 11,473 1,132 360 32,366 3,500 Total 94 3 20,233 1,888 936 67,494 7,164 Caucasus Armenia 8.99 1 824 83 10 2,365 240 Azerbaijan 10.49 0 3,218 232 72 5,831 835 Georgia 7.77 0 912 109 6 1,092 232 Total 27 1 4,954 425 89 9,287 1,306 Moldova, Russia, Ukraine Moldova 2.84 - 236 - 82 5,315 - Russian Federation 559.65 73 33,640 2,194 883 254,873 13,290 Ukraine 10.50 - 3,039 - 359 109,392 6,482 Total 573 73 36,916 2,194 1,325 369,580 19,772 Grand Total 31,706 4,138 1,433,625 168,429 43,806 5,281,562 249,397 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.50 Table A.8a. Year 2005: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 310 55 5 10 4 - 187 50 Bangladesh 42,301 2,236 81 24,940 8,814 264 5,682 284 Bhutan 275 42 1 133 66 2 21 10 Cambodia 1,235 54 3 427 652 5 87 7 China 190,332 101,554 15,800 31,026 2,218 15,602 24,132 - China, Hong Kong SAR 3,129 236 7 752 - 10 1,806 318 India 145,278 88,826 2,695 19,498 - 679 33,580 - Indonesia 88,089 1,823 107 30,731 52,665 498 1,844 421 Iran 18,925 1,762 104 12,502 - 202 4,356 - Korea, DPR 5,598 1,046 60 2,013 672 92 1,507 206 Korea, Rep. 9,783 2,729 603 612 - 163 5,675 - Laos 798 115 2 395 205 5 47 29 Malaysia 6,215 549 8 3,024 141 26 2,342 125 Mongolia 578 105 5 223 81 9 134 21 Myanmar 5,801 733 38 2,556 1,991 35 302 147 Nepal 4,362 853 153 871 1,786 14 637 48 Pakistan 15,590 1,843 12 4,691 2,866 226 5,725 226 Papua New Guinea 721 106 1 253 322 1 32 6 Philippines 11,354 1,914 35 5,840 1,801 121 1,482 160 Singapore 977 189 13 315 89 18 317 36 Sri Lanka 2,973 908 78 758 681 19 530 - Taiwan 5,173 1,131 36 729 - 150 3,125 - Thailand 22,794 2,846 141 10,652 8,119 67 968 - Viet Nam 10,311 746 28 2,907 1,135 1,165 4,330 - Total 592,901 212,402 20,016 155,859 84,308 19,375 98,847 2,094 Latin America Argentina 7,312 1,335 68 2,798 1,011 110 1,719 269 Bolivia 993 174 3 385 135 35 247 14 Brazil 59,622 17,172 606 31,595 1,971 77 7,835 366 Chile 3,115 580 33 1,136 386 51 816 115 Colombia 11,106 2,507 50 3,890 1,493 187 2,346 633 Costa Rica 1,557 196 7 637 38 14 648 17 Cuba 1,550 478 - 774 - 117 181 - Dominican Republic 2,036 847 2 1,006 97 10 73 - Ecuador 2,416 427 18 992 390 32 468 89 El Salvador 1,658 454 4 497 451 10 226 16 Guatemala 1,985 461 21 817 70 21 247 349 Guyana 84 15 1 32 12 1 20 3 Haiti 1,383 71 4 228 875 1 197 7 Honduras 1,426 247 4 507 408 21 225 14 Jamaica 1,299 79 - 488 273 1 457 - Mexico 20,399 6,421 151 6,940 2,765 555 3,567 - Nicaragua 1,711 293 3 602 641 12 159 - Panama 746 253 2 328 24 8 52 80 Paraguay 1,613 135 2 626 362 24 406 58 Peru 6,732 667 15 1,295 3,133 80 1,263 278 Puerto Rico 816 318 13 239 35 1 186 24 Trinidad and Tobago 248 46 2 94 33 4 60 9 Uruguay 605 111 6 230 83 9 145 22 Venezuela 4,146 738 33 1,679 650 57 837 152 Total 134,559 34,024 1,049 57,817 15,335 1,439 22,379 2,516 Middle East/North Africa Algeria 6,601 122 3 5,627 286 73 389 101 Egypt 10,248 335 4 5,034 3,024 704 852 295 Iraq 2,278 90 1 1,475 53 41 315 303 Jordan 561 35 0 288 63 29 120 26 Kuwait 448 16 0 346 23 6 38 19 Lebanon 677 51 1 340 118 22 116 29 Libya 354 33 0 262 22 12 18 7 Morocco 6,607 266 2 5,519 235 67 426 91 Oman 360 24 0 151 15 4 41 125 Saudi Arabia 3,097 179 7 1,932 425 76 340 138 Sudan 1,605 82 1 1,315 28 13 38 128 Syria 2,416 140 2 1,735 146 117 179 99 Tunisia 1,814 333 - 908 89 80 156 248 Turkey 10,336 676 - 2,523 309 519 5,485 826 United Arab Emirates 515 28 1 318 27 7 54 80 Yemen 1,769 109 4 1,086 332 40 126 71 Total 49,685 2,517 28 28,857 5,194 1,810 8,694 2,585 Appendix A A.51 Table A.8a. Year 2005: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 704 39 6 264 245 3 123 24 Benin 621 13 0 221 222 5 135 26 Botswana 537 41 2 315 124 6 45 4 Burkina Faso 882 10 0 351 236 4 237 44 Burundi 48 1 - 11 29 1 6 - Cameroon 1,734 111 2 739 207 14 539 122 Central African Republic 192 8 0 81 33 1 56 13 Chad 99 5 - 54 19 - 21 - Congo 182 18 1 85 58 1 13 6 Congo, D.R. 620 19 - 171 147 2 199 82 Côte d'Ivoire 2,637 39 2 1,388 496 14 667 31 Eritrea 415 5 1 117 223 2 66 2 Ethiopia 5,394 73 7 2,091 2,780 6 420 17 Gabon 96 6 0 42 11 0 36 2 Gambia 123 4 0 66 35 1 12 5 Ghana 3,188 149 1 1,074 853 9 652 451 Guinea 330 9 0 172 85 1 61 2 Guinea-Bissau 34 3 0 16 3 - 9 3 Kenya 6,747 465 0 2,264 3,580 33 404 1 Lesotho 381 18 0 176 149 3 31 3 Liberia 123 7 1 47 43 0 21 4 Madagascar 2,385 148 2 337 1,707 1 184 6 Malawi 1,873 92 1 570 1,002 6 151 52 Mali 829 16 0 411 337 1 60 4 Mauritania 82 1 0 46 17 1 17 0 Mauritius 470 22 0 223 47 1 166 10 Mozambique 1,208 49 2 362 655 4 132 3 Namibia 568 49 2 156 265 2 87 7 Niger 192 3 0 110 63 0 5 11 Nigeria 16,884 452 6 6,054 6,168 194 2,955 1,057 Rwanda 272 17 0 80 138 0 34 2 Senegal 1,061 30 1 544 285 11 115 75 Sierra Leone 272 16 1 174 28 3 33 17 Somalia 433 30 0 318 32 3 5 46 South Africa 14,260 1,643 109 3,890 7,511 51 980 75 Swaziland 269 23 1 111 103 2 20 9 Tanzania 6,205 322 2 2,227 2,516 12 1,091 35 Togo 730 19 0 223 254 8 158 67 Uganda 3,482 148 - 846 1,899 2 586 - Zambia 1,976 77 1 1,045 458 2 367 27 Zimbabwe 4,526 192 8 3,113 841 14 331 27 Total 83,065 4,392 158 30,586 33,901 425 11,229 2,374 Central Asia Republics Kazakhstan 1,518 100 - 305 82 244 666 122 Kyrgyzstan 736 45 1 237 109 63 258 23 Tajikistan 1,191 72 2 720 171 31 142 52 Turkmenistan 431 30 0 182 68 48 91 12 Uzbekistan 2,812 157 3 1,155 509 347 565 76 Total 6,688 403 6 2,599 939 732 1,723 285 Caucasus Armenia 612 108 4 254 101 8 115 23 Azerbaijan 1,560 106 3 861 249 46 227 67 Georgia 621 97 2 298 143 5 53 23 Total 2,793 310 9 1,413 494 59 395 112 Moldova, Russia, Ukraine Moldova 402 33 - 72 - 60 236 - Russian Federation 36,004 7,037 500 11,169 2,930 704 12,340 1,324 Ukraine 7,697 138 - 1,054 - 299 5,532 674 Total 44,103 7,208 500 12,295 2,930 1,063 18,109 1,998 Grand Total 913,793 261,256 21,766 289,425 143,101 24,903 161,376 11,966 Note: Dashes mean the quantity is negligible. Means are weighted according to number of women aged 15-49. Appendix A A.52 Table A.8b. Year 2010: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 782 111 9 172 30 2 357 102 Bangladesh 44,693 2,587 82 25,427 9,043 525 6,409 622 Bhutan 361 57 1 170 80 3 36 13 Cambodia 1,447 91 3 551 685 6 93 18 China 193,657 103,328 16,076 31,568 2,257 15,874 24,553 - China, Hong Kong SAR 3,050 230 7 733 - 10 1,761 310 India 167,896 102,655 3,115 22,533 - 785 38,808 - Indonesia 95,670 1,981 117 33,389 57,183 541 2,003 458 Iran 20,901 1,946 115 13,807 - 223 4,811 - Korea, DPR 5,843 1,092 63 2,102 701 97 1,573 215 Korea, Rep. 9,485 2,646 584 594 - 158 5,502 - Laos 1,049 158 3 508 253 8 81 38 Malaysia 7,182 634 9 3,495 163 30 2,707 145 Mongolia 636 118 7 234 80 10 164 23 Myanmar 6,019 928 18 2,905 1,411 48 488 220 Nepal 5,344 996 138 1,481 1,864 28 738 100 Pakistan 20,356 1,982 26 8,431 3,379 349 5,688 502 Papua New Guinea 893 133 2 349 344 3 47 15 Philippines 14,359 2,485 76 6,687 2,246 173 2,349 342 Singapore 982 190 13 317 89 18 319 36 Sri Lanka 3,071 938 80 783 702 20 548 - Taiwan 6,106 1,336 43 861 - 177 3,689 - Thailand 23,176 2,895 143 10,834 8,250 69 985 - Viet Nam 11,288 817 31 3,185 1,235 1,276 4,743 - Total 644,248 230,333 20,761 171,114 89,994 20,434 108,451 3,160 Latin America Argentina 7,849 1,444 77 2,949 1,041 122 1,927 289 Bolivia 1,503 269 9 578 204 40 368 36 Brazil 63,243 18,216 643 33,517 2,085 81 8,312 389 Chile 3,271 609 34 1,193 406 53 857 120 Colombia 12,196 2,753 55 4,273 1,638 205 2,577 695 Costa Rica 1,675 210 8 685 41 15 697 18 Cuba 1,534 473 - 767 - 116 179 - Dominican Republic 2,249 936 2 1,112 107 11 80 - Ecuador 2,699 484 22 1,078 411 38 568 99 El Salvador 1,858 464 9 585 424 16 326 32 Guatemala 2,614 572 26 1,069 168 29 380 369 Guyana 85 16 1 32 12 1 20 3 Haiti 1,508 105 4 349 840 3 188 17 Honduras 1,752 314 10 607 396 28 364 32 Jamaica 1,361 83 - 512 286 1 479 - Mexico 22,640 7,129 168 7,706 3,060 616 3,960 - Nicaragua 2,091 358 4 737 782 15 194 - Panama 825 279 2 363 26 8 57 88 Paraguay 1,882 200 7 709 373 30 496 68 Peru 7,614 755 17 1,466 3,540 91 1,430 315 Puerto Rico 831 324 14 243 35 1 189 24 Trinidad and Tobago 243 45 2 92 33 4 59 9 Uruguay 632 116 6 240 86 10 151 23 Venezuela 4,632 832 39 1,841 697 66 987 170 Total 146,785 36,986 1,159 62,701 16,692 1,601 24,847 2,798 Middle East/North Africa Algeria 6,369 212 5 4,855 494 106 552 146 Egypt 12,238 565 9 6,031 3,160 706 1,362 405 Iraq 3,002 130 3 1,951 158 57 378 325 Jordan 752 52 1 373 105 34 153 33 Kuwait 445 21 1 307 42 9 47 19 Lebanon 728 55 1 365 127 24 125 31 Libya 455 36 1 306 46 14 39 14 Morocco 6,579 311 4 5,035 434 98 561 136 Oman 408 26 0 197 29 6 46 105 Saudi Arabia 3,968 242 8 2,385 573 104 481 175 Sudan 1,965 104 3 1,527 76 18 90 147 Syria 3,176 206 3 2,008 333 135 358 132 Tunisia 1,959 360 - 981 96 87 169 268 Turkey 11,269 737 - 2,750 336 566 5,980 900 United Arab Emirates 579 31 1 367 46 10 59 66 Yemen 2,938 192 6 1,716 536 75 293 120 Total 56,832 3,279 47 31,154 6,591 2,049 10,692 3,021 Appendix A A.53 Table A.8b. Year 2010: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 1,055 66 8 413 362 4 166 37 Benin 961 28 1 422 282 10 176 42 Botswana 498 50 2 272 107 6 55 7 Burkina Faso 1,379 25 1 616 332 10 327 69 Burundi 68 2 0 16 39 1 10 0 Cameroon 2,506 149 4 1,294 299 31 573 156 Central African Republic 282 12 0 142 43 3 64 18 Chad 121 7 0 64 23 - 27 1 Congo 224 22 1 105 71 1 16 8 Congo, D.R. 808 24 1 220 197 2 262 103 Côte d'Ivoire 3,556 92 5 2,029 589 32 725 84 Eritrea 569 12 2 172 284 2 91 6 Ethiopia 7,099 149 15 2,758 3,474 11 635 57 Gabon 126 11 0 57 20 1 34 4 Gambia 164 10 0 85 47 1 14 7 Ghana 3,888 282 3 1,484 1,038 15 629 438 Guinea 437 15 1 230 102 1 80 8 Guinea-Bissau 50 5 0 23 4 0 12 5 Kenya 7,977 597 2 2,751 4,070 41 494 21 Lesotho 377 27 0 177 135 3 29 5 Liberia 161 9 1 61 56 1 27 6 Madagascar 3,066 227 3 561 2,007 5 243 21 Malawi 2,612 194 2 920 1,210 10 197 79 Mali 1,220 29 1 617 458 2 98 14 Mauritania 109 2 0 62 21 1 22 2 Mauritius 484 22 0 230 48 1 171 11 Mozambique 1,451 51 5 429 754 5 197 10 Namibia 615 66 3 190 245 3 97 12 Niger 813 19 1 489 220 3 35 46 Nigeria 24,101 1,301 14 9,528 8,270 240 3,398 1,350 Rwanda 423 32 1 150 189 1 44 7 Senegal 1,382 48 2 762 312 16 149 92 Sierra Leone 340 20 1 218 34 4 41 21 Somalia 604 41 0 437 47 4 14 60 South Africa 13,082 1,685 103 3,891 5,861 77 1,311 154 Swaziland 269 29 1 112 89 2 27 10 Tanzania 7,766 608 8 3,023 2,804 28 1,191 104 Togo 1,164 44 1 492 317 18 206 86 Uganda 4,751 207 0 1,172 2,574 4 792 3 Zambia 2,510 155 3 1,292 565 7 444 44 Zimbabwe 4,475 319 16 2,780 768 26 511 54 Total 103,543 6,694 213 40,746 38,368 633 13,634 3,255 Central Asia Republics 121 Kyrgyzstan 991 73 1 395 169 56 260 38 Tajikistan 1,425 90 3 833 214 39 185 62 Turkmenistan 684 48 1 338 110 42 120 25 Uzbekistan 4,392 303 6 2,018 785 299 820 160 Total 9,004 614 11 3,886 1,360 679 2,048 407 Caucasus Armenia 590 104 4 246 98 8 109 22 Azerbaijan 1,626 111 3 897 260 48 237 70 Georgia 590 92 2 283 136 5 51 22 Total 2,807 306 9 1,426 494 61 397 113 Moldova, Russia, Ukraine Moldova 388 32 - 70 - 58 229 - Russian Federation 33,196 6,488 461 10,298 2,702 649 11,378 1,220 Ukraine 7,168 128 - 981 - 278 5,152 628 Total 40,753 6,649 461 11,349 2,702 985 16,759 1,849 Grand Total 1,003,971 284,861 22,661 322,376 156,201 26,441 176,827 14,603 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.54 Table A.8c. Year 2015: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 1,574 169 13 618 100 12 502 160 Bangladesh 45,995 2,917 80 25,009 9,127 790 7,127 945 Bhutan 442 73 2 199 89 5 58 16 Cambodia 1,615 133 3 668 678 8 95 31 China 189,661 101,196 15,745 30,917 2,210 15,547 24,046 - China, Hong Kong SAR 2,892 218 6 695 - 9 1,669 294 India 188,581 115,303 3,498 25,310 - 882 43,589 - Indonesia 102,062 2,116 125 35,671 60,944 578 2,140 489 Iran 21,723 2,022 119 14,350 - 232 5,000 - Korea, DPR 5,950 1,112 64 2,141 714 98 1,602 219 Korea, Rep. 9,032 2,520 557 565 - 151 5,239 - Laos 1,316 209 5 611 287 12 143 48 Malaysia 8,012 707 10 3,899 181 34 3,020 161 Mongolia 674 126 7 240 79 11 185 25 Myanmar 6,398 994 20 3,074 1,482 53 541 234 Nepal 6,293 1,138 124 2,066 1,901 44 869 152 Pakistan 24,777 2,080 39 12,035 3,858 479 5,513 773 Papua New Guinea 1,056 160 3 440 356 5 68 24 Philippines 17,042 3,021 121 7,303 2,544 228 3,315 510 Singapore 941 182 12 303 85 18 306 35 Sri Lanka 3,083 942 81 786 705 20 550 - Taiwan 6,881 1,505 48 970 - 200 4,157 - Thailand 22,950 2,867 142 10,730 8,168 68 975 - Viet Nam 11,657 844 32 3,289 1,276 1,318 4,898 - Total 680,606 242,554 20,857 181,889 94,781 20,798 115,611 4,115 Latin America Argentina 8,332 1,547 86 3,056 1,045 134 2,157 306 Bolivia 2,047 376 17 752 253 46 542 61 Brazil 65,183 18,775 663 34,546 2,147 84 8,567 401 Chile 3,312 616 35 1,208 410 54 868 122 Colombia 12,919 2,918 59 4,529 1,728 218 2,731 737 Costa Rica 1,752 220 8 717 43 16 729 19 Cuba 1,412 436 - 706 - 106 165 - Dominican Republic 2,419 1,006 3 1,196 115 12 87 - Ecuador 2,966 540 27 1,143 417 44 686 109 El Salvador 2,048 472 15 663 386 24 439 48 Guatemala 3,325 697 34 1,308 267 43 612 363 Guyana 85 15 1 32 12 1 20 3 Haiti 1,617 145 4 479 777 5 178 29 Honduras 2,063 384 19 674 350 37 548 51 Jamaica 1,386 85 - 521 291 1 488 - Mexico 24,168 7,612 180 8,227 3,263 658 4,228 - Nicaragua 2,465 423 5 870 921 17 229 - Panama 899 305 2 395 29 9 63 96 Paraguay 2,132 278 14 758 351 36 618 77 Peru 8,391 833 18 1,617 3,899 100 1,576 347 Puerto Rico 831 324 14 243 35 1 189 24 Trinidad and Tobago 228 42 2 87 31 3 54 8 Uruguay 658 120 6 250 90 10 157 24 Venezuela 5,030 914 46 1,947 715 74 1,149 185 Total 155,665 39,082 1,256 65,923 17,575 1,736 27,081 3,013 Middle East/North Africa Algeria 5,823 291 7 3,844 676 134 690 182 Egypt 14,050 800 14 6,822 3,296 709 1,904 506 Iraq 3,737 176 5 2,415 292 76 442 329 Jordan 943 72 1 444 152 39 193 41 Kuwait 425 26 1 253 61 11 55 18 Lebanon 769 58 1 386 134 25 132 33 Libya 551 39 1 343 71 16 61 20 Morocco 6,461 352 6 4,488 620 128 690 177 Oman 454 28 1 234 40 8 51 92 Saudi Arabia 4,744 309 9 2,714 727 133 645 207 Sudan 2,332 125 5 1,735 135 25 146 162 Syria 3,889 279 5 2,189 536 153 564 163 Tunisia 1,994 366 - 998 97 88 172 272 Turkey 12,069 789 - 2,946 360 606 6,405 964 United Arab Emirates 627 34 1 405 64 12 62 50 Yemen 4,344 327 8 2,228 832 133 637 179 Total 63,212 4,070 64 32,444 8,094 2,297 12,848 3,395 Appendix A A.55 Table A.8c. Year 2015: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 1,521 118 9 632 502 7 201 53 Benin 1,434 52 2 732 343 20 221 63 Botswana 467 56 2 237 93 6 64 9 Burkina Faso 2,104 55 2 1,051 447 23 423 103 Burundi 122 5 0 34 62 1 18 1 Cameroon 3,314 189 6 1,890 402 52 588 186 Central African Republic 414 19 1 234 58 5 72 24 Chad 169 11 0 81 30 - 43 3 Congo 317 33 1 149 100 1 22 11 Congo, D.R. 1,319 41 3 375 349 4 401 145 Côte d'Ivoire 4,585 160 8 2,771 686 58 755 146 Eritrea 756 28 3 255 344 3 110 13 Ethiopia 8,964 316 23 3,599 4,075 18 807 125 Gabon 152 17 0 71 28 1 31 5 Gambia 208 17 0 107 60 1 15 8 Ghana 4,540 430 5 1,887 1,193 21 595 408 Guinea 574 23 1 314 117 2 100 16 Guinea-Bissau 84 7 1 42 8 0 19 8 Kenya 9,847 894 11 3,569 4,492 60 738 83 Lesotho 370 35 0 175 121 3 28 8 Liberia 237 15 2 93 81 1 37 8 Madagascar 3,871 356 8 885 2,199 14 361 47 Malawi 3,526 353 5 1,376 1,376 19 283 113 Mali 1,711 50 2 908 568 6 145 32 Mauritania 147 4 0 85 25 1 27 4 Mauritius 482 22 0 229 48 1 170 11 Mozambique 1,711 61 8 526 831 6 258 21 Namibia 650 81 3 217 219 5 109 15 Niger 1,715 56 3 1,095 365 17 92 89 Nigeria 33,101 2,833 34 14,218 10,342 296 3,737 1,641 Rwanda 626 58 1 257 243 2 49 15 Senegal 1,717 70 4 1,013 324 22 178 107 Sierra Leone 481 28 2 310 49 6 56 29 Somalia 821 53 1 587 69 7 30 74 South Africa 11,982 1,723 99 3,843 4,336 101 1,655 224 Swaziland 264 33 1 108 74 3 35 9 Tanzania 9,404 991 20 3,854 2,934 53 1,359 194 Togo 1,705 81 2 830 382 35 269 106 Uganda 7,758 390 1 2,054 4,056 8 1,225 24 Zambia 3,121 281 9 1,522 648 17 575 69 Zimbabwe 4,380 431 25 2,435 676 38 698 77 Total 130,669 10,478 312 54,651 43,354 946 16,598 4,330 Central Asia Republics Kazakhstan 1,450 95 - 291 78 233 637 116 Kyrgyzstan 1,190 98 2 511 223 49 259 49 Tajikistan 1,624 109 3 904 257 47 233 70 Turkmenistan 888 63 1 461 147 35 145 37 Uzbekistan 5,716 440 8 2,696 1,033 242 1,061 235 Total 10,869 807 14 4,863 1,737 606 2,335 508 Caucasus Armenia 545 95 4 228 92 7 99 20 Azerbaijan 1,586 108 3 876 254 47 231 68 Georgia 540 84 2 259 124 4 46 20 Total 2,671 288 8 1,363 470 59 376 108 Moldova, Russia, Ukraine Moldova 366 30 - 66 - 55 216 - Russian Federation 30,308 5,924 421 9,402 2,465 592 10,388 1,114 Ukraine 6,435 115 - 881 - 250 4,625 564 Total 37,109 6,069 421 10,349 2,465 897 15,229 1,678 Grand Total 1,080,801 303,347 22,932 351,481 168,477 27,339 190,079 17,146 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.56 Table A.8d. Year 2020: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Asia Afghanistan 2,818 237 17 1,437 238 34 631 224 Bangladesh 46,952 3,244 77 24,255 9,211 1,048 7,875 1,243 Bhutan 519 88 3 224 95 6 83 19 Cambodia 1,785 176 3 783 673 9 99 43 China 177,471 94,692 14,733 28,930 2,068 14,548 22,501 - China, Hong Kong SAR 2,778 209 6 668 - 9 1,604 283 India 206,841 126,467 3,837 27,760 - 967 47,809 - Indonesia 106,055 2,202 130 37,120 63,266 601 2,227 509 Iran 22,418 2,087 123 14,810 - 239 5,160 - Korea, DPR 5,759 1,077 62 2,072 690 95 1,551 212 Korea, Rep. 8,400 2,344 518 526 - 140 4,873 - Laos 1,585 263 9 700 308 17 229 58 Malaysia 8,537 754 11 4,155 192 36 3,217 172 Mongolia 705 133 8 246 79 12 200 26 Myanmar 6,556 1,021 21 3,146 1,512 54 563 240 Nepal 7,170 1,273 111 2,597 1,911 60 1,018 201 Pakistan 28,977 2,190 50 15,346 4,347 609 5,410 1,025 Papua New Guinea 1,199 185 4 519 360 8 91 32 Philippines 19,433 3,519 168 7,727 2,729 284 4,342 664 Singapore 873 169 11 281 79 16 283 32 Sri Lanka 3,050 932 80 777 697 19 544 - Taiwan 7,567 1,655 53 1,067 - 220 4,572 - Thailand 22,641 2,828 140 10,585 8,058 67 962 - Viet Nam 11,938 865 33 3,368 1,306 1,350 5,017 - Total 702,028 248,610 20,207 189,099 97,821 20,448 120,860 4,984 Latin America Argentina 8,751 1,635 94 3,154 1,054 144 2,348 322 Bolivia 2,570 484 27 891 278 53 752 85 Brazil 67,212 19,360 684 35,621 2,214 87 8,834 413 Chile 3,319 618 35 1,210 411 54 870 122 Colombia 13,329 3,011 60 4,672 1,783 224 2,818 760 Costa Rica 1,813 228 8 742 44 16 755 20 Cuba 1,280 395 - 639 - 96 149 - Dominican Republic 2,571 1,070 3 1,271 123 13 92 - Ecuador 3,180 588 32 1,181 411 50 802 117 El Salvador 2,195 472 20 720 338 31 550 63 Guatemala 4,090 835 46 1,508 343 61 954 343 Guyana 82 15 1 31 11 1 19 3 Haiti 1,725 184 4 599 718 8 174 39 Honduras 2,343 451 28 711 283 46 754 70 Jamaica 1,380 84 - 519 289 1 485 - Mexico 25,041 7,887 186 8,525 3,379 682 4,381 - Nicaragua 2,755 474 5 975 1,024 20 257 - Panama 963 326 2 424 31 10 67 103 Paraguay 2,375 357 22 786 315 44 765 86 Peru 9,040 897 20 1,742 4,199 108 1,699 374 Puerto Rico 829 323 14 243 35 1 189 24 Trinidad and Tobago 217 40 2 84 30 3 50 8 Uruguay 683 125 7 259 93 10 163 25 Venezuela 5,398 993 53 2,029 717 84 1,325 199 Total 163,140 40,851 1,353 68,535 18,122 1,848 29,253 3,177 Middle East/North Africa Algeria 5,279 362 8 2,880 840 159 818 213 Egypt 15,930 1,045 18 7,560 3,488 725 2,486 608 Iraq 4,445 224 7 2,843 432 96 513 330 Jordan 1,096 90 1 486 196 44 231 47 Kuwait 448 29 1 257 69 13 61 19 Lebanon 792 60 1 397 138 26 136 34 Libya 636 42 1 372 94 18 82 27 Morocco 6,359 393 8 3,976 796 156 817 214 Oman 495 30 1 268 51 10 56 78 Saudi Arabia 5,443 379 9 2,949 883 164 824 235 Sudan 2,687 144 7 1,935 195 32 198 175 Syria 4,558 354 6 2,304 743 172 786 192 Tunisia 1,994 366 - 998 97 88 172 272 Turkey 12,710 831 - 3,102 379 638 6,745 1,015 United Arab Emirates 656 35 2 430 81 14 63 31 Yemen 5,799 533 8 2,316 1,247 218 1,235 242 Total 69,328 4,918 78 33,075 9,730 2,573 15,222 3,732 Appendix A A.57 Table A.8d. Year 2020: Projected Contraceptive Costs by Method Among All Women (Aged 15-49) (000s) Sterilization Country Total Female Male Pill Injectable IUD Condom Vaginals Sub-Saharan Africa Angola 2,138 205 10 938 663 10 234 76 Benin 2,029 88 4 1,129 409 35 274 90 Botswana 448 62 3 211 81 6 73 11 Burkina Faso 3,078 108 4 1,658 585 46 532 146 Burundi 252 16 1 90 109 2 29 6 Cameroon 4,089 229 8 2,449 505 74 609 215 Central African Republic 566 28 1 342 75 9 80 30 Chad 259 20 1 115 41 - 71 10 Congo 463 51 1 221 142 2 30 17 Congo, D.R. 2,379 115 7 802 683 8 561 203 Côte d'Ivoire 5,624 231 11 3,508 791 87 788 208 Eritrea 973 53 3 366 403 4 121 22 Ethiopia 11,026 591 28 4,651 4,599 27 909 220 Gabon 176 22 0 82 35 1 29 6 Gambia 252 24 0 128 73 1 15 10 Ghana 5,186 579 8 2,272 1,334 28 582 383 Guinea 741 34 2 427 129 5 116 28 Guinea-Bissau 141 11 1 77 13 1 26 11 Kenya 12,097 1,353 33 4,519 4,650 95 1,262 185 Lesotho 366 41 1 174 110 3 29 9 Liberia 349 27 2 145 116 1 46 12 Madagascar 4,712 538 17 1,254 2,193 30 596 85 Malawi 4,536 554 12 1,872 1,487 32 427 153 Mali 2,314 79 4 1,304 654 15 198 61 Mauritania 194 7 0 117 29 2 31 7 Mauritius 480 22 0 228 48 1 169 10 Mozambique 1,981 84 10 654 889 8 300 36 Namibia 673 94 4 236 193 6 122 18 Niger 2,901 119 5 1,852 533 47 207 138 Nigeria 43,302 4,866 77 19,444 12,176 378 4,421 1,941 Rwanda 858 92 1 386 297 3 53 25 Senegal 2,067 92 5 1,278 334 30 206 121 Sierra Leone 676 39 2 439 72 10 75 39 Somalia 1,078 66 2 759 100 13 53 85 South Africa 11,215 1,778 99 3,819 3,115 124 1,995 284 Swaziland 258 37 2 103 62 3 42 9 Tanzania 11,066 1,414 38 4,630 2,967 85 1,643 288 Togo 2,286 128 3 1,167 457 55 352 124 Uganda 12,402 835 8 3,689 5,909 28 1,831 102 Zambia 3,792 449 20 1,703 683 33 804 100 Zimbabwe 4,303 527 33 2,130 588 49 879 96 Total 163,725 15,707 475 71,374 48,331 1,397 20,820 5,622 Central Asia Republics Kazakhstan 1,426 94 - 286 77 229 626 114 Kyrgyzstan 1,305 114 2 554 255 49 277 55 Tajikistan 1,792 129 3 946 298 56 284 77 Turkmenistan 1,016 74 2 527 172 32 166 43 Uzbekistan 6,521 529 9 3,029 1,202 228 1,246 277 Total 12,060 940 16 5,341 2,004 593 2,599 567 Caucasus Armenia 516 90 4 218 88 6 91 19 Azerbaijan 1,539 105 3 850 246 46 224 66 Georgia 501 78 2 241 116 4 42 18 Total 2,556 272 8 1,308 451 56 358 103 Moldova, Russia, Ukraine Moldova 348 28 - 62 - 52 205 - Russian Federation 28,628 5,596 397 8,881 2,329 560 9,813 1,053 Ukraine 5,860 105 - 802 - 227 4,212 513 Total 34,835 5,729 397 9,746 2,329 839 14,229 1,566 Grand Total 1,147,672 317,027 22,534 378,477 178,787 27,755 203,340 19,752 Note: Dashes mean the quantity is negligible. Means are weighted according to numbers of women aged 15-49. Appendix A A.58 Table A.9. Unmet Need, Percent Using, and Percent of Demand Satisfied Unmet Need Currently Using Demand for Contraception Country Space Limit Total Space Limit Total Space Limit Total % of Demand Satisfieda Asia Afghanistan - - - - - - - - - - Bangladesh 1999/2000 8.0 7.3 15.3 15.6 38.1 53.8 24.7 46.1 70.8 78.3 Bhutan - - - - - - - - - - Cambodia 2000 14.4 15.2 29.7 9.4 14.4 23.8 23.8 29.6 53.5 44.5 China - - - - - - - - - - China, Hong Kong SAR - - - - - - - - - - India 1998/99 8.3 7.5 15.8 3.5 44.7 48.2 11.8 52.2 64.0 75.3 Indonesia 2003 4.0 4.6 8.6 24.2 36.2 60.3 28.8 41.0 69.7 87.6 Iran - - - - - - - - - - Korea, DPR - - - - - - - - - - Korea, Rep. - - - - - - - - - - Laos - - - - - - - - - - Malaysia - - - - - - - - - - Mongolia - - - - - - - - - - Myanmar - - - - - - - - - - Nepal 2001 11.4 16.4 27.8 3.8 35.5 39.3 15.2 51.9 67.1 58.6 Pakistan 2001 12.1 20.9 33.0 6.7 20.9 27.6 18.8 41.8 60.6 45.5 Papua New Guinea - - - - - - - - - - Philippines 1998 8.2 10.6 18.8 13.1 34.7 47.8 23.6 45.9 69.5 73.0 Singapore - - - - - - - - - - Sri Lanka - - - - - - - - - - Taiwan - - - - - - - - - - Thailand - - - - - - - - - - Viet Nam 2002 2.0 2.8 4.8 13.9 64.6 78.5 16.4 67.9 84.3 94.3 Latin America Argentina - - - - - - - - - - Bolivia 1998 6.8 19.3 26.1 13.3 35.0 48.3 20.1 54.3 74.4 65.0 Brazil 1996 2.6 4.7 7.3 14.0 62.8 76.7 17.6 68.3 85.8 91.5 Chile - - - - - - - - - - Colombia 2000 2.7 3.5 6.2 18.4 58.6 76.9 22.9 63.3 86.3 92.8 Costa Rica - - - - - - - - - - Cuba - - - - - - - - - - Dominican Republic 2002 6.7 4.2 10.9 14.8 54.9 69.8 22.5 59.5 82.0 86.8 Ecuador - - - - - - - - - - El Salvador - - - - - - - - - - Guatemala 1998/99 11.8 11.3 23.1 8.5 29.7 38.2 21.0 41.2 62.2 62.9 Guyana - - - - - - - - - - Haiti 2000 16.0 23.8 39.8 9.8 18.3 28.1 25.7 42.1 67.8 41.4 Honduras - - - - - - - - - - Jamaica - - - - - - - - - - Mexico - - - - - - - - - - Nicaragua 2001 5.9 8.7 14.6 20.5 48.1 68.6 26.4 56.8 83.2 82.5 Panama - - - - - - - - - - Paraguay 1990 8.8 6.2 15.0 23.6 24.8 48.4 35.0 31.3 66.3 77.4 Peru 2000 3.6 6.7 10.2 20.3 48.5 68.9 25.7 56.8 82.5 87.6 Puerto Rico - - - - - - - - - - Trinidad and Tobago - - - - - - - - - - Uruguay - - - - - - - - - - Venezuela - - - - - - - - - - Middle East/North Africa Algeria - - - - - - - - - - Egypt 2003 3.5 6.0 9.5 12.9 47.1 60.0 17.1 53.5 70.6 86.5 Iraq - - - - - - - - - - Jordan 2002 5.6 5.5 11.0 25.5 30.3 55.8 33.0 36.8 69.7 84.2 Kuwait - - - - - - - - - - Lebanon - - - - - - - - - - Libya - - - - - - - - - - Morocco 1992 8.5 11.2 19.7 14.1 27.4 41.5 24.1 40.1 64.2 69.3 Oman - - - - - - - - - - Saudi Arabia - - - - - - - - - - Sudan - - - - - - - - - - Syria - - - - - - - - - - Tunisia - - - - - - - - - - Turkey 1998 3.8 6.3 10.1 14.3 49.6 63.9 19.0 56.6 75.6 86.6 United Arab Emirates - - - - - - - - - - Yemen 1997 17.2 21.4 38.6 7.2 13.6 20.8 24.4 35.0 59.4 35.0 Appendix A A.59 Table A.9. Unmet Need, Percent Using, and Percent of Demand Satisfied Unmet Need Currently Using Demand for Contraception Country Space Limit Total Space Limit Total Space Limit Total % of Demand Satisfieda Sub-Saharan Africa Angola - - - - - - - - - - Benin 2001 17.5 9.7 27.2 12.0 6.6 18.6 29.5 16.3 45.8 40.6 Botswana - - - - - - - - - - Burkina Faso 1998/99 19.0 6.8 25.8 9.0 2.8 11.9 28.0 9.7 37.7 31.5 Burundi - - - - - - - - - - Cameroon 13.3 6.4 19.7 12.1 7.3 19.3 25.4 13.7 39.1 49.5 Central African Rep. 1994/95 11.6 4.6 16.2 11.9 2.9 14.8 23.5 7.5 31.0 47.7 Chad 1996/97 6.6 3.1 9.7 3.1 1.0 4.1 9.7 4.1 13.8 30.0 Congo - - - - - - - - - - Congo, D.R. - - - - - - - - - - Côte d'Ivoire 1998/99 20.0 7.6 27.7 10.0 5.0 15.0 30.1 12.6 42.7 35.2 Eritrea 2002 21.0 6.0 27.0 5.0 3.0 8.0 26.1 9.0 35.1 22.9 Ethiopia 2000 21.8 13.9 35.8 3.7 4.3 8.1 25.6 18.3 43.8 18.4 Gabon 2000 19.9 8.0 28.0 24.0 8.7 32.7 43.9 16.8 60.7 53.9 Gambia - - - - - - - - - - Ghana 1998 11.2 11.8 23.0 12.3 9.7 22.0 23.5 21.5 45.0 48.8 Guinea 1999 16.0 8.2 24.2 3.6 2.6 6.2 19.6 10.8 30.4 20.5 Guinea-Bissau - - - - - - - - - - Kenya 2003 14.4 10.1 24.5 14.3 25.0 39.3 30.2 35.7 65.8 62.8 Lesotho - - - - - - - - - - Liberia - - - - - - - - - - Madagascar 1997 14.1 11.4 25.6 7.9 11.6 19.4 22.0 23.0 45.0 43.2 Malawi 2000 17.2 12.5 29.7 12.7 17.9 30.6 29.9 30.4 60.3 50.8 Mali 2001 20.9 7.6 28.5 5.1 3.0 8.1 25.9 10.7 36.6 22.1 Mauritania 2000/01 22.9 8.6 31.6 5.1 2.9 8.0 28.1 11.5 39.5 20.2 Mauritius - - - - - - - - - - Mozambique 1997 16.9 5.6 22.5 2.6 3.0 5.6 19.5 8.6 28.1 20.0 Namibia 2000 10.5 14.7 25.1 13.1 30.7 43.7 23.5 45.3 68.9 63.5 Niger 1998 14.0 2.7 16.6 6.9 1.3 8.2 20.9 4.0 24.9 33.0 Nigeria 2003 11.8 5.1 16.9 7.8 4.8 12.6 19.6 9.9 29.5 42.7 Rwanda 2000 24.0 11.6 35.6 7.3 5.9 13.2 31.3 17.5 48.8 27.1 Senegal 1997 25.5 9.4 34.8 8.0 4.9 12.9 33.5 14.3 47.8 27.1 Sierra Leone - - - - - - - - - - Somalia - - - - - - - - - - South Africa 1998 4.7 10.3 15.0 14.4 41.8 56.3 19.1 52.1 71.2 79.0 Swaziland - - - - - - - - - - Tanzania 1999 13.8 8.0 21.8 15.1 10.3 25.4 28.9 18.3 47.2 53.7 Togo 21.4 10.9 32.3 14.6 8.9 23.5 36.0 19.8 55.8 42.1 Uganda 2000/01 20.7 13.9 34.6 11.2 11.6 22.8 31.9 25.5 57.3 39.7 Zambia 2001/02 16.8 10.6 27.4 19.2 15.0 34.2 36.1 25.6 61.6 55.5 Zimbabwe 1999 7.3 5.6 12.9 29.4 24.1 53.5 38.0 30.2 68.2 81.0 Central Asia Republics Kazakhstan 1999 3.6 5.1 8.7 23.0 43.0 66.1 26.9 48.3 75.2 88.5 Kyrgyzstan 1997 4.5 7.2 11.6 26.3 33.3 59.5 30.7 40.5 71.2 83.6 Tajikistan - - - - - - - - - - Turkmenistan 2000 5.2 4.9 10.1 22.0 39.8 61.8 27.5 44.7 72.2 86.0 Uzbekistan 1996 6.6 7.0 13.7 20.2 35.4 55.6 26.8 42.4 69.3 80.3 Caucasus Armenia 2000 2.6 9.3 11.8 11.8 48.7 60.5 15.1 58.5 73.6 84.0 Azerbaijan - - - - - - - - - - Georgia - - - - - - - - - - Moldova, Russia, Ukraine Moldova - - - - - - - - - - Russian Federation - - - - - - - - - - Ukraine - - - - - - - - - - Note: Dashes mean no data available. a. “Demand” is the sum of need and met need (current use). Current use divided by demand gives the percent of demand satisfied. In this table and in the DHS published reports the figures shown can slightly exceed the ratio of use to demand, due to modifications in the definitions of need or use. Appendix A A.60 Table A.10. Intention to Use Contraception Timing for Intention to Use Contraception Country Use In Next 12 Months Use Later Unsure about Timing Unsure about Use Does Not Intend Asia Afghanistan - - - - - Bangladesh 1999/2000 - - 70.8 2.7 26.3 Bhutan - - - - - Cambodia 2000 —— 42.3 —— - 12.9 44.7 China - - - - - China, Hong Kong SAR - - - - - India 1998/99 20.9 37.8 1.5 5.3 34.3 Indonesia 2003 —— 43.1 —— - 13.7 42.4 Iran - - - - - Korea, DPR - - - - - Korea, Rep. - - - - - Laos - - - - - Malaysia - - - - - Mongolia - - - - - Myanmar - - - - - Nepal 2001 —— 73.2 —— - 2.7 24.1 Pakistan - - - - - Papua New Guinea - - - - - Philippines 1998 32.8 8.0 0.8 3.9 53.9 Singapore - - - - - Sri Lanka 1987 21.4 13.5 2.8 13.2 48.0 Taiwan - - - - - Thailand 1987 27.2 12.9 8.6 6.9 44.2 Viet Nam 2002 44.8 13.3 1.1 3.1 37.3 Latin America Argentina - - - - - Bolivia 1998 35.2 9.5 0.5 6.6 46.9 Brazil 1996 42.0 13.9 0.6 1.7 40.3 Chile - - - - - Colombia 2000 —— 69.6 —— - 2.7 27.7 Costa Rica - - - - - Cuba - - - - - Dominican Republic 2002 —— 65.9 —— —— 2.8 —— 30.6 Ecuador 1987 32.5 5.1 4.5 11.5 46.5 El Salvador 1985 - - - - - Guatemala 1998/99 25.8 6.0 0.5 2.9 64.1 Guyana - - - - - Haiti 2000 —— 56.4 —— - 5.1 38.5 Honduras - - - - - Jamaica - - - - - Mexico —— - —— - - - Nicaragua 2001 —— 61.7 —— —— 5.7 —— 32.3 Panama - - - - - Paraguay 1990 29.8 3.5 4.9 9.1 52.3 Peru 2000 —— 55.9 —— - 5.6 37.7 Puerto Rico - - - - - Trinidad & Tobago 1987 27.9 6.4 7.4 11.5 46.4 Uruguay - - - - - Venezuela - - - - - Middle East/North Africa Algeria - - - - - Egypt 2003 —— 46.8 —— —— 3.1 —— 49.9 Iraq - - - - - Jordan 2002 —— 59.6 —— —— 4.7 —— 35.7 Kuwait - - - - - Lebanon - - - - - Libya - - - - - Morocco 1992 36.5 7.6 1.1 2.9 51.4 Oman - - - - - Saudi Arabia - - - - - Sudan 1990 13.1 4.0 1.3 4.7 76.8 Syria - - - - - Tunisia 1988 36.3 8.8 5.1 5.1 44.7 Turkey 1998 35.3 14.7 1.4 3.6 43.7 United Arab Emirates - - - - - Yemen 1997 9.0 4.0 10.5 12.2 64.2 Appendix A A.61 Table A.10. Intention to Use Contraception Timing for Intention to Use Contraception Country Use In Next 12 Months Use Later Unsure about Timing Unsure about Use Does Not Intend Sub-Saharan Africa Angola - - - - - Benin 2001 —— 52.9 —— - 10.4 36.0 Botswana 1988 39.9 4.8 2.1 5.1 48.0 Burkina Faso 1998/99 32.1 10.3 2.1 10.4 45.1 Burundi 1987 11.5 16.8 4.1 11.6 55.9 Cameroon 1998 23.6 11.5 0.8 7.0 56.9 Central African Rep. 1994/95 32.6 0.8 0.3 2.9 63.2 Chad 1996/97 9.7 4.7 0.5 6.4 78.6 Congo - - - - - Congo, D.R. - - - - - Côte d'Ivoire 1998/99 29.9 15.4 1.0 6.5 47.2 Eritrea 2002 15.7 10.4 —— 3.0 —— 70.7 Ethiopia 2000 —— 45.7 —— - 1.5 52.8 Gabon 2000 —— 40.5 —— - 9.1 49.8 Gambia - - - - - Ghana 1998 30.1 16.1 1.8 6.4 45.4 Guinea 1999 24.4 11.7 0.2 4.3 58.7 Guinea-Bissau - - - - - Kenya 2003 —— 57.8 —— —— 3.9 —— 37.9 Lesotho - - - - - Liberia 1986 - - 32.1 11.3 56.6 Madagascar 1997 31.6 12.4 0.7 5.6 49.5 Malawi 2000 —— 73.9 —— - 2.8 23.3 Mali 2001 —— 37.3 —— - 12.0 50.5 Mauritania 2000/01 —— 11.7 —— - 9.1 78.9 Mauritius - - - - - Mozambique 1997 23.2 2.9 0.8 19.8 52.7 Namibia 2000 —— 63.9 —— —— 5.6 —— 29.5 Niger 1998 22.2 6.2 0.9 7.1 63.5 Nigeria 2003 —— 27.4 —— —— 8.4 —— 63.8 Rwanda 2000 —— 52.6 —— - 8.5 38.8 Senegal 1997 24.2 9.7 3.1 10.2 52.8 Sierra Leone - - - - - Somalia - - - - - South Africa 1998 33.6 10.0 0.9 5.3 46.7 Swaziland - - - - - Tanzania 1999 —— 38.8 —— - 4.6 56.2 Togo 1998 36.9 14.4 1.6 8.5 38.3 Uganda 2000/01 —— 62.1 —— - 9.7 28.0 Zambia - - - - - Zimbabwe 1999 —— 66.7 —— - 4.1 28.7 Central Asia Republics Kazakhstan 1999 —— 44.7 —— - 10.1 44.3 Kyrgyzstan 1997 40.2 22.0 3.8 5.1 28.5 Tajikistan - - - - - Turkmenistan 2000 —— 46.6 —— - 13.5 38.9 Uzbekistan 1996 21.9 18.9 1.8 16.8 40.6 Caucasus Armenia 2000 —— 35.5 —— - 17.4 47.1 Azerbaijan - - - - - Georgia - - - - - Moldova, Russia, Ukraine Moldova - - - - - Russian Federation - - - - - Ukraine - - - - - Note: Dashes mean no data available. Appendix A A.62 Table A.11. Relationship of Unmet Need and Intention to Use Contraception Overlap Between Unmet Need and Intention to Use All Married Women Married Women Not Using Contraceptives Unmet Need Unmet Need Country Intention to Use Yes No Using Total Intention to Use Yes No Total Asia Bangladesh 1997 Yes 13 22 35 Yes 25 43 68 No 3 13 65 No 6 26 31 Total 16 35 49 100 Total 31 69 100 Bangladesh 2000 Yes 13 20 33 Yes 28 44 71 No 3 11 67 No 6 23 28 Total 15 31 54 100 Total 33 67 100 Cambodia 2000 Yes 17 16 32 Yes 22 21 42 No 13 31 68 No 17 40 58 Total 30 47 24 100 Total 39 61 100 India 1993 Yes 6 9 17 Yes 11 15 29 No 10 30 83 No 17 51 71 Total 17 39 41 100 Total 28 66 100 India 1999 Yes 12 19 31 Yes 22 38 60 No 4 16 69 No 8 31 40 Total 16 35 48 100 Total 31 68 100 Indonesia 1997 Yes 4 13 17 Yes 10 31 41 No 5 20 83 No 11 48 59 Total 9 33 57 100 Total 22 79 100 Indonesia 2002 Yes 4 13 17 Yes 11 32 43 No 4 18 83 No 11 46 56 Total 9 31 60 100 Total 22 78 100 Nepal 1996 Yes 24 21 45 Yes 33 29 63 No 8 19 55 No 11 27 37 Total 31 40 29 100 Total 44 56 100 Nepal 2001 Yes 23 22 44 Yes 37 36 73 No 5 11 56 No 9 18 27 Total 28 33 39 100 Total 46 54 100 Philippines 1998 Yes 10 12 22 Yes 19 23 42 No 9 21 78 No 17 41 58 Total 19 33 48 100 Total 36 64 100 Viet Nam 2002 Yes 3 9 13 Yes 16 43 59 No 1 7 87 No 6 34 40 Total 5 17 79 100 Total 23 78 100 Latin America Bolivia 1994 Yes 14 13 27 Yes 26 24 50 No 9 18 72 No 16 33 49 Total 23 31 45 100 Total 43 58 100 Bolivia 1998 Yes 15 9 23 Yes 29 16 45 No 11 17 76 No 21 32 54 Total 26 26 48 100 Total 50 49 100 Colombia 2000 Yes 5 11 16 Yes 23 47 70 No 1 6 84 No 4 27 30 Total 6 17 77 100 Total 27 73 100 Dominican Rep. 1991 Yes 12 12 24 Yes 28 27 55 No 5 15 76 No 11 34 45 Total 17 26 56 100 Total 39 60 100 Dominican Rep. 1996 Yes 10 11 21 Yes 26 31 57 No 3 12 79 No 8 34 42 Total 13 24 64 100 Total 34 66 100 Dominican Rep. 1999 Yes 10 11 20 Yes 31 35 66 No 2 8 80 No 7 26 34 Total 12 19 69 100 Total 39 61 100 Dominican Rep. 2002 Yes 9 11 20 Yes 30 36 66 No 2 8 80 No 6 28 34 Total 11 19 70 100 Total 36 64 100 Guatemala 1995 Yes 11 11 22 Yes 15 16 32 No 14 33 78 No 20 48 68 Total 24 44 31 100 Total 36 64 100 Guatemala 1999 Yes 11 9 20 Yes 17 15 32 No 12 29 80 No 20 47 67 Total 23 39 38 100 Total 37 63 100 Haiti 1994 Yes 26 10 36 Yes 31 12 43 No 19 28 64 No 23 34 57 Total 45 37 18 100 Total 54 46 100 Haiti 2000 Yes 27 14 41 Yes 37 19 56 No 13 19 59 No 18 26 44 Total 40 32 28 100 Total 55 45 100 Appendix A A.63 Table A.11. Relationship of Unmet Need and Intention to Use Contraception Overlap Between Unmet Need and Intention to Use All Married Women Married Women Not Using Contraceptives Unmet Need Unmet Need Country Intention to Use Yes No Using Total Intention to Use Yes No Total Nicaragua 1997 Yes 11 12 23 Yes 27 31 58 No 4 12 77 No 10 31 41 Total 15 25 60 100 Total 37 63 100 Nicaragua 2001 Yes 11 9 19 Yes 34 28 62 No 4 8 81 No 12 26 38 Total 15 17 69 100 Total 46 54 100 Paraguay 1990 Yes 7 12 20 Yes 14 24 38 No 8 24 80 No 15 47 61 Total 15 37 48 100 Total 29 71 100 Peru 1992 Yes 11 13 24 Yes 28 32 59 No 4 12 75 No 9 30 39 Total 16 26 59 100 Total 38 62 100 Peru 1996 Yes 9 12 21 Yes 24 34 58 No 4 11 79 No 10 32 42 Total 12 24 64 100 Total 34 66 100 Peru 2000 Yes 7 10 17 Yes 23 33 56 No 3 11 82 No 9 34 43 Total 10 21 69 100 Total 33 67 100 Middle East/North Africa Egypt 2000 Yes 7 19 26 Yes 17 42 59 No 3 15 74 No 8 33 41 Total 11 33 56 100 Total 24 76 100 Morocco 1992 Yes 11 16 27 Yes 19 27 45 No 9 23 73 No 15 39 54 Total 20 39 42 100 Total 34 66 100 Turkey 1998 Yes 7 12 19 Yes 19 33 52 No 3 14 81 No 9 38 47 Total 10 26 64 100 Total 28 72 100 Sub-Saharan Africa Benin 1996 Yes 17 22 38 Yes 20 26 46 No 9 36 61 No 11 43 54 Total 26 58 16 100 Total 31 69 100 Benin 2001 Yes 18 25 43 Yes 22 31 53 No 9 29 56 No 11 35 46 Total 27 54 19 100 Total 34 66 100 Burkina Faso 1992 Yes 12 11 23 Yes 16 14 30 No 12 40 77 No 16 53 69 Total 25 51 25 100 Total 33 67 100 Burkina Faso 1999 Yes 16 23 39 Yes 18 26 45 No 10 39 61 No 11 45 55 Total 26 62 12 100 Total 29 71 100 Cameroon 1998 Yes 11 18 29 Yes 14 22 36 No 9 43 71 No 11 53 64 Total 20 61 19 100 Total 24 76 100 Central African Rep. 1994 Yes 13 16 29 Yes 15 19 34 No 4 53 71 No 4 62 66 Total 16 69 15 100 Total 19 81 100 Chad 1997 Yes 3 9 14 Yes 3 9 15 No 6 72 86 No 7 75 85 Total 10 81 4 100 Total 10 85 100 Côte d'Ivoire 1994 Yes 17 15 32 Yes 19 17 36 No 11 46 68 No 12 52 64 Total 27 61 11 100 Total 31 69 100 Côte d'Ivoire 1998 Yes 19 21 39 Yes 22 24 46 No 9 37 61 No 10 43 54 Total 28 57 15 100 Total 33 68 100 Ethiopia 2000 Yes 24 18 42 Yes 26 20 46 No 11 39 58 No 12 42 54 Total 35 57 8 100 Total 38 62 100 Gabon 2000 Yes 15 12 27 Yes 23 18 41 No 13 27 72 No 19 40 59 Total 28 39 33 100 Total 42 58 100 Ghana 1993 Yes 25 16 41 Yes 31 20 51 No 12 27 59 No 15 34 49 Total 37 43 20 100 Total 46 54 100 Ghana 1998 Yes 21 17 37 Yes 27 21 48 No 13 28 63 No 16 36 52 Total 34 45 22 100 Total 43 57 100 Appendix A A.64 Table A.11. Relationship of Unmet Need and Intention to Use Contraception Overlap Between Unmet Need and Intention to Use All Married Women Married Women Not Using Contraceptives Unmet Need Unmet Need Country Intention to Use Yes No Using Total Intention to Use Yes No Total Ghana 2003 Yes 23 18 41 Yes 30 24 54 No 11 23 59 No 15 30 46 Total 34 41 25 100 Total 46 55 100 Guinea 1999 Yes 15 19 34 Yes 16 20 36 No 9 50 65 No 10 53 63 Total 24 70 6 100 Total 26 74 100 Kenya 1998 Yes 19 20 39 Yes 31 33 63 No 5 17 61 No 8 28 36 Total 24 37 39 100 Total 39 61 100 Kenya 2003 Yes 18 17 35 Yes 30 28 58 No 6 19 65 No 10 32 42 Total 25 36 39 100 Total 40 60 100 Madagascar 1992 Yes 21 14 35 Yes 25 16 41 No 12 37 66 No 14 45 59 Total 32 51 17 100 Total 39 61 100 Madagascar 1997 Yes 17 20 36 Yes 20 24 45 No 9 35 64 No 11 44 55 Total 26 55 19 100 Total 32 68 100 Malawi 1992 Yes 26 25 50 Yes 29 29 58 No 10 26 50 No 12 30 42 Total 36 51 13 100 Total 41 59 100 Malawi 2000 Yes 25 27 51 Yes 36 38 74 No 5 13 49 No 7 19 26 Total 30 40 31 100 Total 43 57 100 Mali 1996 Yes 16 20 36 Yes 17 21 38 No 10 47 64 No 11 51 62 Total 26 68 7 100 Total 28 72 100 Mali 2001 Yes 15 19 34 Yes 17 21 37 No 13 44 66 No 14 48 63 Total 29 63 8 100 Total 31 69 100 Mauritania 2000 Yes 6 5 11 Yes 7 5 12 No 26 55 89 No 28 60 88 Total 32 60 8 100 Total 34 66 100 Mozambique 1997 Yes 10 15 25 Yes 11 16 27 No 12 56 74 No 13 60 73 Total 23 72 6 100 Total 24 76 100 Namibia 1992 Yes 10 11 22 Yes 14 16 31 No 12 38 78 No 16 53 69 Total 22 49 29 100 Total 31 69 100 Niger 1992 Yes 7 12 20 Yes 8 13 20 No 11 65 80 No 12 68 80 Total 19 77 4 100 Total 20 81 100 Niger 1998 Yes 7 20 27 Yes 8 21 29 No 9 56 73 No 10 61 71 Total 17 75 8 100 Total 18 82 100 Nigeria 1999 Yes 6 13 19 Yes 8 15 23 No 11 53 79 No 12 62 76 Total 17 66 15 100 Total 21 78 100 Rwanda 1992 Yes 30 19 49 Yes 38 24 62 No 9 21 51 No 11 27 38 Total 39 40 21 100 Total 49 51 100 Rwanda 2000 Yes 22 24 46 Yes 25 28 53 No 14 27 54 No 16 31 47 Total 36 51 13 100 Total 41 59 100 Senegal 1993 Yes 15 12 26 Yes 16 13 28 No 15 52 74 No 16 56 72 Total 29 63 8 100 Total 32 68 100 Senegal 1997 Yes 19 13 32 Yes 22 15 37 No 16 39 68 No 18 45 63 Total 35 52 13 100 Total 40 60 100 Tanzania 1999 Yes 13 16 29 Yes 18 21 39 No 8 37 71 No 11 50 61 Total 22 53 25 100 Total 29 71 100 Togo 1998 Yes 22 18 41 Yes 29 24 53 No 10 26 59 No 13 34 47 Total 32 44 24 100 Total 42 58 100 Appendix A A.65 Table A.11. Relationship of Unmet Need and Intention to Use Contraception Overlap Between Unmet Need and Intention to Use All Married Women Married Women Not Using Contraceptives Unmet Need Unmet Need Country Intention to Use Yes No Using Total Intention to Use Yes No Total Uganda 1995 Yes 22 26 48 Yes 26 30 56 No 7 30 52 No 8 36 44 Total 29 56 15 100 Total 34 66 100 Uganda 2000 Yes 26 22 48 Yes 34 28 62 No 8 21 52 No 11 27 38 Total 35 43 23 100 Total 45 55 100 Zambia 1992 Yes 20 20 41 Yes 24 24 48 No 10 34 59 No 12 40 52 Total 31 54 15 100 Total 36 64 100 Zambia 1996 Yes 22 27 49 Yes 29 37 66 No 5 20 51 No 7 27 34 Total 27 48 26 100 Total 36 64 100 Zambia 2001 Yes 22 24 46 Yes 34 36 70 No 5 15 54 No 8 22 30 Total 27 38 34 100 Total 42 58 100 Zimbabwe 1994 Yes 11 23 34 Yes 22 43 65 No 3 14 66 No 6 28 34 Total 15 37 48 100 Total 29 71 100 Zimbabwe 1999 Yes 10 21 31 Yes 21 46 67 No 3 12 69 No 7 26 33 Total 13 34 54 100 Total 28 72 100 Central Asia Republics Kazakhstan 1995 Yes 8 12 20 Yes 18 30 48 No 8 13 80 No 20 32 52 Total 16 25 59 100 Total 39 62 100 Kazakhstan 1999 Yes 6 10 15 Yes 17 28 45 No 3 16 85 No 8 46 54 Total 9 25 66 100 Total 26 74 100 Kyrgyzstan 1997 Yes 8 19 27 Yes 20 46 66 No 4 10 73 No 9 25 34 Total 12 29 60 100 Total 29 71 100 Uzbekistan 1996 Yes 6 13 19 Yes 14 29 43 No 8 18 81 No 17 40 57 Total 14 31 56 100 Total 31 69 100 Caucasus Armenia 2000 Yes 6 8 14 Yes 16 20 36 No 6 20 86 No 14 51 64 Total 12 28 61 100 Total 30 70 100 Appendix A A.66 Table A.12. Ideal Number of Children, Total Fertility and Wanted Fertility Rates, and Fertility Planning Status Time Wanted Last Birth/Pregnancy Country % Wanted Then % Wanted Later % Did Not Want % Who Want No More Children Mean Ideal No. of Children TFR* TWFR** Asia Afghanistan - - - - - - - Bangladesh 1999/2000 66.9 19.3 13.5 51.7 2.5 3.3 2.2 Bhutan - - - - - - - Cambodia 2000 66.7 8.9 23.5 35.2 3.6 3.8 3.0 China - - - - - - - China, Hong Kong SAR - - - - - - - India 78.4 11.9 9.4 27.5 2.7 2.8 2.1 Indonesia 2003 82.4 9.6 7.2 54.2 2.9 2.6 2.2 Iran - - - - - - - Korea, DPR - - - - - - - Korea, Rep. - - - - - - - Laos - - - - - - - Malaysia - - - - - - - Mongolia - - - - - - - Myanmar - - - - - - - Nepal 2001 64.1 13.8 21.6 44.3 2.6 4.1 2.5 Pakistan 2001 - - - 43.9 - 4.8 - Papua New Guinea - - - - - - - Philippines 1998 54.2 26.9 18.2 51.4 3.2 3.7 2.7 Singapore - - - - - - - Sri Lanka 1987 - - - 35.3 3.1 2.7 2.2 Taiwan - - - - - - - Thailand 1987 - - - 37.3 2.8 2.2 1.8 Viet Nam 2002 75.9 13.6 9.3 69.0 2.4 1.9 1.6 Latin America Argentina - - - - - - - Bolivia 1998 47.6 20.2 31.7 64.8 2.6 4.2 2.5 Brazil 1996 50.6 26.1 22.3 31.6 2.3 2.5 1.8 Chile - - - - - - - Colombia 2000 47.6 29.2 23.1 41.5 2.3 2.6 1.8 Costa Rica - - - - - - - Cuba - - - - - - - Dominican Republic 2002 55.5 30.0 13.2 66.2 3.3 - - Ecuador 1987 - - - 48.3 3.0 4.2 2.8 El Salvador 1985 - - - 30.3 3.6 4.2 4.0 Guatemala 1998/99 69.7 18.0 11.8 40.9 3.4 5.0 4.1 Guyana - - - - - - - Haiti 2000 43.9 26.0 29.8 53.8 3.1 4.7 2.8 Honduras - - - - - - - Jamaica - - - - - - - Mexico 1987 - - - 42.6 3.0 4.0 2.8 Nicaragua 2001 51.2 20.9 27.4 64.7 3.2 3.2 2.3 Panama - - - - - - - Paraguay 1990 76.1 16.9 6.7 36.3 3.9 4.7 4.0 Peru 2000 43.8 25.3 30.7 54.5 2.4 2.8 1.8 Puerto Rico - - - - - - - Trinidad and Tobago 1987 - - - 46.8 2.9 3.1 2.2 Uruguay - - - - - - - Venezuela - - - - - - - Middle East/North Africa Algeria - - - - - - - Egypt 2003 - - - 63.0 2.8 3.2 2.5 Iraq - - - - - - - Jordan 2002 66.9 17.2 15.9 43.9 4.3 3.7 2.6 Kuwait - - - - - - - Lebanon - - - - - - - Libya - - - - - - - Morocco 2003 - - - 51.0 - - - Oman - - - - - - - Saudi Arabia - - - - - - - Sudan 1990 - - - 24.4 5.9 4.7 4.2 Syria - - - - - - - Tunisia 1988 - - - 45.9 3.5 4.2 2.9 Turkey 1998 69.2 11.2 18.8 62.1 2.4 2.6 1.9 United Arab Emirates - - - - - - - Yemen 1997 54.6 23.0 21.8 47.8 4.5 6.5 4.6 Appendix A A.67 Table A.12. Ideal Number of Children, Total Fertility and Wanted Fertility Rates, and Fertility Planning Status Time Wanted Last Birth/Pregnancy Country % Wanted Then % Wanted Later % Did Not Want % Who Want No More Children Mean Ideal No. of Children TFR* TWFR** Sub-Saharan Africa Angola - - - - - - - Benin 2001 77.2 17.5 4.9 25.6 4.9 5.6 4.6 Botswana 1988 - - - 30.9 4.7 4.9 3.9 Burkina Faso 2003 - - - 23.2 - 6.2 - Burundi 1987 - - - 23.5 5.3 6.9 5.8 Cameroon 1998 70.9 20.4 6.1 18.1 6.0 4.8 4.3 Central African Republic 1994/95 75.7 16.0 7.0 11.9 6.4 5.1 4.7 Chad 1996/97 90.0 7.9 0.9 9.8 8.3 6.4 6.1 Congo - - - - - - - Congo, D.R. - - - - - - - Côte d'Ivoire 1998/99 70.7 23.8 4.9 20.6 5.4 5.2 4.5 Eritrea 2002 73.8 19.5 5.9 17.6 6.3 4.8 4.4 Ethiopia 2000 63.0 19.6 17.3 31.7 5.3 5.5 4.7 Gabon 2000 54.9 37.6 6.8 22.1 4.9 4.2 3.5 Gambia - - - - - - - Ghana 2003 - - - 34.1 - 4.4 - Guinea 1999 79.9 13.5 3.9 20.6 5.7 5.5 5.0 Guinea-Bissau - - - - - - - Kenya 2003 55.2 24.9 19.6 48.6 4.3 4.9 3.6 Lesotho - - - - - - - Liberia 1986 - - - 16.1 6.0 6.7 6.1 Madagascar 1997 73.5 13.8 12.0 37.1 5.3 6.0 5.2 Malawi 2000 59.6 18.3 21.7 37.5 5.0 6.3 5.2 Mali 2001 79.2 16.6 3.2 21.2 6.2 6.8 6.1 Mauritania 2000/01 71.2 22.1 6.3 19.0 6.2 4.5 4.1 Mauritius - - - - - - - Mozambique 1997 74.2 20.1 3.7 16.2 5.9 5.2 4.7 Namibia 2000 54.0 21.7 23.3 42.9 4.0 4.2 3.4 Niger 1998 86.7 11.0 1.0 9.5 8.2 7.2 7.0 Nigeria 2003 84.7 9.5 5.0 18.3 7.3 5.7 5.3 Rwanda 2000 64.3 22.8 12.5 33.0 4.9 5.8 4.7 Senegal 1997 64.1 27.2 6.8 22.5 5.3 5.7 4.6 Sierra Leone - - - - - - - Somalia - - - - - - - South Africa 1998 45.7 35.5 17.3 43.6 2.9 2.9 2.3 Swaziland - - - - - - - Tanzania 1999 77.5 11.4 11.0 26.7 5.3 5.6 4.8 Togo 1998 57.1 33.3 8.1 28.2 4.5 5.2 4.2 Uganda 2001/02 59.4 21.4 18.9 33.5 4.7 5.9 4.9 Zambia 2000/01 60.3 24.8 14.6 36.4 4.8 6.9 5.3 Zimbabwe 1999 62.4 30.2 7.2 38.2 3.9 4.0 3.4 Central Asia Republics Kazakhstan 1999 82.4 8.3 8.9 55.4 2.8 2.0 1.9 Kyrgyzstan 1997 86.4 7.6 5.4 45.1 3.7 3.4 3.1 Tajikistan - - - - - - - Turkmenistan 2000 94.3 2.2 1.2 53.2 3.3 2.9 2.7 Uzbekistan 1996 94.7 2.4 1.9 50.9 3.6 3.3 3.1 Caucasus Armenia 2000 83.2 9.2 7.5 71.7 2.7 1.7 1.5 Azerbaijan - - - - - - - Georgia - - - - - - - Moldova, Russia, Ukraine Moldova - - - - - - - Russian Federation - - - - - - - Ukraine - - - - - - - * Total fertility rate. ** Total wanted fertility rate. Note: Dashes mean no data available. Appendix A A.68 Table A.13. Percent Distribution of the Gap to 75% Contraceptive Prevalence, by Region, Year 2005 Estimates Country Females 15-49 (000) % Married MWRA (000) % MWRA Using Contraception No. of Married Users (000) 75% of MWRA Gap Percent Dist. of Gapa Asia India 275,525 75.1 206,920 48.2 99,735 155,190 55,454 57.3 Pakistan 37,455 71.1 26,630 27.6 7,350 19,973 12,623 13.0 Indonesia 62,110 70.9 44,036 60.3 26,554 33,027 6,473 6.7 Bangladesh 38,421 76.2 29,277 53.8 15,751 21,958 6,207 6.4 Philippines 21,482 59.6 12,804 46.5 5,954 9,603 3,649 3.8 Afghanistan 5,825 74.4 4,336 4.8 208 3,252 3,044 3.1 Myanmar 13,812 51.1 7,058 32.7 2,308 5,293 2,985 3.1 Nepal 6,232 78.5 4,892 39.3 1,923 3,669 1,747 1.8 Cambodia 3,692 59.1 2,182 23.8 519 1,637 1,117 1.2 Malaysia 6,551 59.6 3,903 54.5 2,127 2,927 800 0.8 Korea, DPR 6,153 73.1 4,497 61.8 2,779 3,373 594 0.6 Papua New Guinea 1,461 71.2 1,040 25.9 269 780 510 0.5 Laos 1,440 72.1 1,038 32.2 334 779 444 0.5 Thailand 18,543 61.5 11,404 72.2 8,234 8,553 319 0.3 Sri Lanka 5,229 56.7 2,965 66.1 1,960 2,224 264 0.3 Iran 20,000 60.8 12,161 72.9 8,866 9,121 255 0.3 Bhutan 558 62.0 346 - 128 259 131 0.1 Singapore 1,171 61.7 722 62.0 448 542 94 0.1 Mongolia 778 62.6 487 67.4 328 365 37 0.0 Taiwan 5,808 64.7 3,758 75.5 2,837 2,818 - - China, Hong Kong SAR 2,138 55.5 1,186 86.2 1,022 889 - - Korea, Rep. 13,452 62.6 8,421 80.5 6,779 6,315 - - Viet Nam 23,766 64.1 15,234 78.5 11,959 11,425 - - China 361,724 75.3 272,344 83.8 228,224 204,258 - - Latin America Mexico 29,534 60.1 17,750 68.4 12,141 13,312 1,171 20.1 Guatemala 3,092 65.8 2,034 38.2 777 1,526 749 12.8 Venezuela 7,024 51.2 3,596 - 1,976 2,697 722 12.4 Argentina 9,824 62.7 6,160 - 3,932 4,620 688 11.8 Haiti 2,208 58.7 1,296 27.4 355 972 617 10.6 Bolivia 2,254 59.4 1,339 53.4 715 1,004 289 5.0 Peru 7,333 56.1 4,114 68.9 2,835 3,086 251 4.3 Chile 4,237 56.5 2,394 1,545 1,795 251 4.3 Ecuador 3,545 62.8 2,226 65.8 1,465 1,670 205 3.5 Paraguay 1,541 61.3 944 57.4 542 708 166 2.9 El Salvador 1,774 60.8 1,079 59.7 644 809 165 2.8 Honduras 1,804 58.1 1,048 61.8 648 786 138 2.4 Panama 852 56.8 484 58.2 282 363 81 1.4 Trinidad and Tobago 384 54.4 209 38.2 80 157 77 1.3 Dominican Republic 2,379 59.8 1,423 69.8 993 1,067 74 1.3 Nicaragua 1,434 56.8 814 68.6 559 611 52 0.9 Uruguay 837 59.8 501 - 339 376 37 0.6 Jamaica 736 49.8 366 65.9 241 275 33 0.6 Cuba 3,048 62.1 1,894 73.3 1,388 1,420 32 0.6 Guyana 222 31.7 70 37.3 26 53 27 0.5 Costa Rica 1,173 74.1 869 75.0 651 651 - - Puerto Rico 1,036 58.4 605 77.7 470 454 - - Colombia 12,366 51.2 6,331 76.9 4,869 4,748 - - Brazil 51,564 60.1 30,990 76.7 23,769 23,242 - - Middle East/North Africa Sudan 8,578 55.5 4,761 8.3 395 3,571 3,175 20.7 Iraq 6,446 54.4 3,504 13.7 480 2,628 2,148 14.0 Egypt 19,450 62.8 12,215 60.0 7,329 9,161 1,832 11.9 Yemen 4,654 67.4 3,137 20.8 652 2,353 1,700 11.1 Saudi Arabia 6,023 59.3 3,574 31.8 1,137 2,681 1,544 10.0 Turkey 19,797 69.0 13,660 63.9 8,729 10,245 1,516 9.9 Syria 5,000 62.5 3,126 36.1 1,129 2,345 1,216 7.9 Morocco 8,779 55.3 4,855 63.0 3,058 3,641 583 3.8 Algeria 9,118 45.7 4,169 64.0 2,668 3,127 459 3.0 Tunisia 2,878 56.2 1,618 60.0 971 1,213 243 1.6 United Arab Emirates 635 76.8 487 27.5 134 366 232 1.5 Oman 641 62.0 397 23.7 94 298 204 1.3 Libya 1,596 34.7 553 39.7 220 415 195 1.3 Jordan 1,449 51.7 749 55.8 418 562 144 0.9 Lebanon 1,081 64.2 694 61.0 423 520 97 0.6 Kuwait 638 53.9 344 50.2 173 258 85 0.6 Appendix A A.69 Table A.13. Percent Distribution of the Gap to 75% Contraceptive Prevalence, by Region, Year 2005 Estimates Country Females 15-49 (000) % Married MWRA (000) % MWRA Using Contraception No. of Married Users (000) 75% of MWRA Gap Percent Dist. of Gapa Sub-Saharan Africa Nigeria 29,818 70.0 20,873 12.6 2,630 15,655 13,025 22.3 Ethiopia 16,867 63.7 10,744 8.1 870 8,058 7,188 12.3 Congo, D.R. 12,509 67.9 8,498 31.4 2,668 6,374 3,705 6.3 Tanzania 9,128 65.8 6,007 25.4 1,526 4,505 2,979 5.1 Mozambique 4,746 74.4 3,531 5.6 198 2,648 2,450 4.2 Uganda 5,837 67.4 3,934 22.8 897 2,950 2,054 3.5 Kenya 8,447 61.4 5,186 38.3 1,986 3,890 1,903 3.3 Ghana 5,513 64.6 3,561 25.2 897 2,671 1,774 3.0 Mali 3,021 83.5 2,522 8.1 204 1,892 1,687 2.9 Burkina Faso 3,087 80.4 2,482 13.7 340 1,861 1,521 2.6 Côte d'Ivoire 4,097 61.3 2,511 15.0 377 1,884 1,507 2.6 Madagascar 4,246 62.8 2,667 18.8 501 2,000 1,499 2.6 Cameroon 3,964 66.9 2,652 19.3 512 1,989 1,477 2.5 Angola 3,182 65.4 2,082 6.2 129 1,562 1,432 2.5 Niger 2,713 84.2 2,284 14.0 320 1,713 1,394 2.4 Somalia 2,363 67.4 1,593 - 13 1,195 1,181 2.0 Guinea 2,022 82.4 1,666 6.2 103 1,250 1,146 2.0 Senegal 2,578 68.1 1,756 12.9 226 1,317 1,090 1.9 Chad 2,009 78.2 1,571 7.9 124 1,178 1,054 1.8 South Africa 12,420 43.2 5,365 56.3 3,021 4,024 1,003 1.7 Malawi 2,773 71.5 1,983 30.6 607 1,487 880 1.5 Benin 1,702 73.4 1,249 18.6 232 937 704 1.2 Burundi 1,727 67.2 1,160 15.7 182 870 688 1.2 Rwanda 2,142 48.5 1,039 13.2 137 779 642 1.1 Zambia 2,429 61.3 1,489 34.2 509 1,117 607 1.0 Sierra Leone 1,238 67.6 837 4.3 36 627 591 1.0 Eritrea 1,045 65.5 685 8.0 55 514 459 0.8 Zimbabwe 3,109 61.1 1,900 53.5 1,016 1,425 408 0.7 Togo 1,209 67.9 821 25.7 211 616 405 0.7 Liberia 807 67.5 545 6.4 35 408 374 0.6 Central African Rep. 925 69.4 642 27.9 179 482 302 0.5 Mauritania 724 58.8 426 8.0 34 319 285 0.5 Congo 866 56.2 487 - 93 365 272 0.5 Gambia 362 71.4 259 9.6 25 194 169 0.3 Guinea-Bissau 346 68.7 238 7.6 18 178 160 0.3 Lesotho 478 52.4 251 30.4 76 188 112 0.2 Gabon 336 54.1 182 32.7 59 136 77 0.1 Swaziland 270 59.2 160 27.7 44 120 76 0.1 Botswana 458 39.1 179 40.4 72 134 62 0.1 Namibia 482 38.7 186 43.7 81 140 58 0.1 Mauritius 343 62.5 214 74.7 160 161 1 0.0 Central Asia Republics Tajikistan 1,720 75.2 1,292 33.9 438 969 531 34.2 Uzbekistan 7,474 68.1 5,090 65.0 3,308 3,817 509 32.8 Kazakhstan 4,359 62.9 2,742 66.1 1,812 2,056 244 15.7 Kyrgyzstan 1,440 69.5 1,001 59.5 595 750 155 10.0 Turkmenistan 1,398 61.7 862 61.8 533 647 114 7.3 Caucasus Azerbaijan 2,546 64.0 1,629 55.4 902 1,221 319 45.5 Georgia 1,333 64.8 864 40.5 350 648 298 42.5 Armenia 906 64.1 581 60.5 351 436 84 12.0 Moldova, Russia, Ukraine Ukraine 12,585 67.3 8,470 67.5 5,717 6,352 635 86.0 Moldova 1,198 68.7 823 62.4 514 617 104 14.0 Russian Federation 38,735 67.4 26,107 - 20,446 19,581 - - Notes: a Countries are ordered within each region according to last column. Percent distributions omit countries with negative numbers, e.g., China, where prevalence is already above 75%. MWRA: married/in union women, 15-49. Dashes mean no data available. Estimated in calculations. Appendix A A.70 Table A.14. 1999 Program Effort Scores: Total and Four Dimension Scores as Percent of Maximum Dimension Scores Country Total Score Policy Services Evaluation Availability Asia Afghanistan - - - - - Bangladesh 74 70 75 72 81 Bhutan - - - - - Cambodia 46 56 45 50 32 China, Hong Kong SAR 86 89 87 70 88 Hong Kong 57 63 41 32 100 India 65 72 58 60 72 Indonesia 82 84 86 81 72 Iran 71 70 62 68 94 Korea, DPR - - - - - Korea, Rep. 55 45 39 63 97 Laos 39 51 41 36 18 Malaysia 69 72 61 86 72 Mongolia 38 31 35 26 58 Myanmar 37 34 38 59 27 Nepal 57 61 56 67 49 Pakistan 57 59 57 52 57 Papua New Guinea - - - - - Philippines 57 56 50 66 67 Singapore - - - - - Sri Lanka 69 67 71 49 76 Taiwan 79 74 67 96 100 Thailand 75 61 72 95 89 Viet Nam 76 82 74 66 79 Latin America Argentina 30 33 21 36 40 Bolivia 49 46 44 45 64 Brazil 59 50 46 59 100 Chile 61 50 56 60 86 Colombia 64 44 66 78 80 Costa Rica 32 38 21 19 57 Cuba 86 65 90 100 100 Dominican Republic 50 43 52 44 58 Ecuador 46 47 43 47 50 El Salvador 46 49 45 41 46 Guatemala 37 35 32 35 51 Guyana 46 42 44 56 51 Haiti 51 59 50 39 51 Honduras 44 43 41 40 52 Jamaica 62 71 59 63 58 Mexico 75 79 62 84 90 Nicaragua 49 35 53 60 55 Panama 49 61 34 60 61 Paraguay 56 56 43 59 81 Peru 59 65 42 60 85 Puerto Rico 62 49 53 66 97 Trinidad and Tobago 59 55 59 62 63 Uruguay 34 22 30 54 47 Venezuela 29 32 12 13 71 Middle East/North Africa Algeria 68 81 55 100 60 Egypt 57 63 58 60 46 Iraq - - - - - Jordan 47 47 45 53 48 Kuwait - - - - - Lebanon 60 49 63 74 61 Libya - - - - - Morocco 57 57 51 76 61 Oman 50 41 45 59 81 Saudi Arabia - - - - - Sudan 35 41 40 39 12 Syria 66 52 74 88 56 Tunisia 71 80 71 88 52 Turkey 59 71 44 61 76 United Arab Emirates - - - - - Yemen 37 56 27 33 36 Appendix A A.71 Table A.14. 1999 Program Effort Scores: Total and Four Dimension Scores as Percent of Maximum Dimension Scores Country Total Score Policy Services Evaluation Availability Sub-Saharan Africa Angola - - - - - Benin 45 46 48 54 30 Botswana - - - - - Burkina Faso 54 58 59 60 33 Burundi - - - - - Cameroon 44 53 52 54 10 Central African Rep. 50 66 57 50 13 Chad 43 67 44 52 4 Congo 35 56 26 29 27 Congo D.R. - - - - - Côte d'Ivoire 50 56 52 71 27 Eritrea - - - - - Ethiopia 44 48 49 43 28 Gabon 34 27 37 40 40 Gambia - - - - - Ghana 63 68 61 72 58 Guinea 60 61 64 63 48 Guinea-Bissau - - - - - Kenya 62 55 64 63 67 Lesotho 62 62 58 77 61 Liberia - - - - - Madagascar 42 44 48 44 26 Malawi 50 57 58 53 23 Mali 58 55 70 73 31 Mauritania 37 35 39 55 25 Mauritius 71 67 67 91 75 Mozambique 43 49 37 52 40 Namibia 54 66 30 63 84 Niger 47 59 50 61 16 Nigeria 45 47 49 38 38 Rwanda 62 77 60 66 44 Senegal 55 58 54 64 46 Sierra Leone - - - - - Somalia - - - - - South Africa 54 62 45 46 65 Swaziland - - - - - Tanzania 55 64 65 46 27 Togo 63 64 67 75 45 Uganda 54 62 57 60 34 Zambia 50 42 57 62 39 Zimbabwe 61 61 63 79 49 Central Asia Republics Kazakhstan 42 36 42 38 51 Kyrgyzstan 49 45 43 54 64 Tajikistan 54 58 48 68 55 Turkmenistan 59 49 59 65 68 Uzbekistan 55 69 48 41 60 Caucasus Armenia - - - - - Azerbaijan - - - - - Georgia - - - - - Moldova, Russia, Ukraine Moldova - - - - - Russia - - - - - Ukraine - - - - - Note: Dashes mean no data available. Appendix A A.72 Table A.15. Maternal Mortality Ratio (MMR), Number of Deaths Annually, Lifetime Risk, and Percent of Female Deaths (ages 15-49) That Are Pregnancy Related Maternal Mortality Ratios Country MMR for 1990 MMR for 2000 MDG Goal* by 2015 (3/4 fall from 1990) Maternal Deaths, 2000 Lifetime Risk of Maternal Death (1 in), 2000 % of Female Deaths 15-49 Pregnancy Related, 2000 Asia Afghanistan 1,700 1,900 425 20,000 6 46 Bangladesh 850 380 213 16,000 59 24 Bhutan 1,600 420 400 310 37 21 Cambodia 900 450 225 2,100 36 18 China 95 56 24 11,000 830 - China, Hong Kong SAR 7 - 2 - - - India 570 540 143 136,000 48 Indonesia 650 230 163 10,000 150 6 Iran 120 76 30 1,200 370 5 Korea, DPR 70 67 18 260 590 2 Korea, Rep. 130 20 33 120 2,800 - Laos 650 650 163 1,300 25 19 Malaysia 80 41 20 220 660 - Mongolia 65 110 16 65 300 - Myanmar 580 360 145 - 75 9 Nepal 1,500 740 375 6,000 24 24 Pakistan 340 500 85 26,000 31 16 Papua New Guinea 930 300 233 470 62 11 Philippines 280 200 70 4,100 120 12 Singapore 10 30 3 15 1,700 - Sri Lanka 140 92 35 300 430 - Taiwan - - - - - - Thailand 200 44 50 520 900 - Viet Nam 160 130 40 2,000 270 6 Latin America Argentina 100 82 25 590 410 - Bolivia 650 420 163 1,100 47 18 Brazil 220 260 55 8,700 140 12 Chile 65 31 16 90 1,100 - Colombia 100 130 25 1,300 240 8 Costa Rica 55 43 14 40 690 - Cuba 95 33 24 45 1,600 - Dominican Republic 110 150 28 300 200 7 Ecuador 150 130 38 400 210 7 El Salvador 300 150 75 250 180 10 Guatemala 200 240 50 970 74 21 Guyana 170 43 30 200 7 Haiti 1,000 680 250 1,700 29 17 Honduras 220 110 55 220 190 - Jamaica 120 87 30 45 380 - Mexico 110 83 28 1,900 370 - Nicaragua 160 230 40 400 88 19 Panama 55 160 14 100 210 Paraguay 160 170 40 280 120 14 Peru 280 410 70 2,500 73 20 Puerto Rico 25 15 1,800 - Trinidad and Tobago 90 160 23 30 330 - Uruguay 85 27 21 15 1,300 - Venezuela 120 96 30 550 300 - Middle East/North Africa Algeria 160 140 40 1,000 190 9 Egypt 170 84 43 1,400 310 - Iraq 310 250 78 2,000 65 16 Jordan 150 41 38 70 450 - Kuwait 29 5 7 2 6,000 - Lebanon 300 150 75 100 240 6 Libya 220 97 55 140 240 8 Morocco 610 220 153 1,700 120 19 Oman 190 87 48 80 170 29 Saudi Arabia 130 23 33 160 610 - Sudan 660 590 165 6,400 30 23 Syria 180 160 45 780 130 14 Tunisia 170 120 43 210 320 5 Turkey 180 70 45 1,000 480 5 United Arab Emirates 26 54 7 20 500 4 Yemen 1,400 570 350 5,300 19 38 Appendix A A.73 Table A.15. Maternal Mortality Ratio (MMR), Number of Deaths Annually, Lifetime Risk, and Percent of Female Deaths (ages 15-49) That Are Pregnancy Related Maternal Mortality Ratios Country MMR for 1990 MMR for 2000 MDG Goal* by 2015 (3/4 fall from 1990) Maternal Deaths, 2000 Lifetime Risk of Maternal Death (1 in), 2000 % of Female Deaths 15-49 Pregnancy Related, 2000 Sub-Saharan Africa Angola 1,500 1,700 375 11,000 7 40 Benin 990 850 248 2,200 17 34 Botswana 250 100 63 50 200 9 Burkina Faso 930 1,000 233 5,400 12 37 Burundi 1,300 1,000 325 2,800 12 40 Cameroon 550 730 138 4,000 23 29 Central African Rep. 700 1,100 175 1,600 15 37 Chad 1,500 1,100 375 4,200 11 46 Congo 890 510 223 690 26 32 Congo, D.R. 870 990 218 24,000 13 36 Côte d'Ivoire 810 690 203 3,900 25 24 Eritrea 1,400 630 350 930 24 33 Ethiopia 1,400 850 350 24,000 14 33 Gabon 500 420 125 200 37 23 Gambia 1,100 540 275 270 31 27 Ghana 740 540 185 3,500 35 23 Guinea 1,600 740 400 2,700 18 30 Guinea-Bissau 910 1,100 228 590 13 35 Kenya 650 1,000 163 11,000 19 49 Lesotho 610 550 153 380 32 22 Liberia 560 760 140 1,200 16 33 Madagascar 490 550 123 3,800 26 23 Malawi 560 1,800 140 9,300 7 54 Mali 1,200 1,200 300 6,800 10 39 Mauritania 930 1,000 233 1,200 14 37 Mauritius 120 24 30 5 1,700 - Mozambique 1,500 1,000 375 7,900 14 35 Namibia 370 300 93 190 54 17 Niger 1,200 1,600 300 9,700 7 50 Nigeria 1,000 800 250 37,000 18 32 Rwanda 1,300 1,400 325 4,200 10 49 Senegal 1,200 690 300 2,500 22 27 Sierra Leone 1,800 2,000 450 4,500 6 39 Somalia 1,600 1,100 400 5,100 10 43 South Africa 230 230 58 2,600 120 9 Swaziland 560 370 140 120 49 17 Tanzania 770 1,500 193 2,100 10 46 Togo 640 570 160 1,000 26 25 Uganda 1,200 880 300 10,000 13 37 Zambia 940 750 235 3,300 19 34 Zimbabwe 570 1,100 143 5,000 16 44 Central Asia Republics Kazakhstan 80 210 20 560 190 2 Kyrgyzstan 110 110 28 110 290 4 Tajikistan 130 100 33 160 250 10 Turkmenistan 55 31 14 40 790 6 Uzbekistan 55 24 14 130 1,300 5 Caucasus Armenia 50 55 13 20 1,200 2 Azerbaijan 22 94 6 100 520 3 Georgia 33 32 8 20 1,700 2 Moldova, Russia, Ukraine Moldova 60 36 15 20 1,500 - Russian Federation 75 67 19 830 1,000 - Ukraine 50 35 13 140 2,000 - *MDG: Millennium Development Goal. Note: Dashes mean no data available. Appendix A A.74 Table A.16. Number of Abortions, Abortion Rate, and Abortion Ratio (1999 Estimates) Country Number of Abortions (000s) Ratio: Abortions per 1000 Females 15-49 per year Ratio:Abortions per 1000 Births Asia Afghanistan 69 14 6 Bangladesh 398 12 12 Bhutan 10 23 13 Cambodia 129 49 36 China 11,729 34 58 China, Hong Kong SAR 19 11 29 India 5,743 24 23 Indonesia 1,939 35 41 Iran 169 10 7 Korea, DPR - - - Korea, Rep. 458 35 66 Laos 82 71 35 Malaysia 208 38 38 Mongolia 45 66 61 Myanmar 567 45 44 Nepal 116 21 14 Pakistan 841 25 16 Papua New Guinea - - - Philippines 788 42 38 Singapore 21 21 38 Sri Lanka 40 8 12 Taiwan - - - Thailand 223 13 22 Viet Nam 1,183 57 61 Latin America Argentina 345 38 48 Bolivia 64 33 24 Brazil 1,687 36 52 Chile 161 41 55 Colombia 337 30 38 Costa Rica 27 27 31 Cuba 151 50 104 Dominican Republic 73 34 37 Ecuador 121 38 39 El Salvador 35 22 21 Guatemala 122 49 29 Guyana 15 61 80 Haiti 31 16 12 Honduras 107 73 52 Jamaica 21 31 38 Mexico 495 19 21 Nicaragua 37 32 25 Panama 24 32 38 Paraguay 66 52 40 Peru 232 35 38 Puerto Rico 19 20 30 Trinidad and Tobago 20 55 90 Uruguay 26 33 48 Venezuela 402 67 70 Middle East/North Africa Algeria 77 10 9 Egypt 253 15 15 Iraq 74 14 9 Jordan 18 12 8 Kuwait 17 34 42 Lebanon 17 20 22 Libya 20 16 8 Morocco 67 9 9 Oman 10 20 9 Saudi Arabia 74 18 11 Sudan 86 12 9 Syria 40 11 9 Tunisia 23 9 10 Turkey 335 19 24 United Arab Emirates 3 7 8 Yemen 68 19 8 Appendix A A.75 Table A.16. Number of Abortions, Abortion Rate, and Abortion Ratio (1999 Estimates) Country Number of Abortions (000s) Ratio: Abortions per 1000 Females 15-49 per year Ratio:Abortions per 1000 Births Sub-Saharan Africa Angola - - - Benin 37 28 15 Botswana 6 15 11 Burkina Faso 23 9 4 Burundi 25 17 9 Cameroon 40 12 7 Central African Rep. - - - Chad 10 6 4 Congo 12 19 10 Congo, D.R. 82 8 4 Côte d'Ivoire 207 64 38 Eritrea - - - Ethiopia 308 24 10 Gabon 3 13 8 Gambia 2 7 5 Ghana 113 25 16 Guinea 79 47 21 Guinea-Bissau 10 38 22 Kenya 172 25 16 Lesotho 8 16 10 Liberia 18 32 12 Madagascar 56 16 8 Malawi 41 17 8 Mali 24 10 4 Mauritania 4 7 5 Mauritius 10 32 47 Mozambique 199 47 25 Namibia 7 17 11 Niger 22 10 4 Nigeria 413 17 8 Rwanda 24 15 8 Senegal 55 27 15 Sierra Leone 9 9 4 Somalia 37 18 7 South Africa 204 20 16 Swaziland 4 17 12 Tanzania 112 15 8 Togo 20 20 11 Uganda 174 39 16 Zambia 58 28 16 Zimbabwe 61 22 14 Central Asia Republics Kazakhstan 306 70 100 Kyrgyzstan 49 42 43 Tajikistan 55 38 29 Turkmenistan 36 33 29 Uzbekistan 680 114 100 Caucasus Armenia - - - Azerbaijan - - - Georgia - - - Moldova, Russia, Ukraine Moldova - - - Russia 2,824 72 200 Ukraine 993 78 200 Note: Dashes mean no data available. Appendix A A.76 Table A.17. Percentage Receiving Antenatal Care, Tetanus Injections, and Delivery Care No. of Visits by Women with at Least One Visit (1993-2003)* Country % with 1+ Visits During Pregnancy (1995-2003) No. Seen Antenatally at Least Once (minimum est.)** 1 2-3 4+ % of Pregnant Women Given Tetanus, 2003 est. % Deliveries with Skilled Attendant, 1995-2003*** Asia Afghanistan 37 420,320 - - - 40 14 Bangladesh 40 1,673,200 31 47 21 89 14 Bhutan - - - - - - 24 Cambodia 38 180,500 - - - 43 32 China 90 16,835,400 - - - - 97 China, Hong Kong SAR - - - - - - - India 60 15,031,200 6 37 56 78 43 Indonesia 92 4,153,800 3 19 77 51 68 Iran 77 1,096,480 - - - - 90 Korea, DPR - - - - - - 97 Korea, Rep. - - - - - - 100 Laos 27 54,000 - - - 36 19 Malaysia - - - - - - 97 Mongolia 97 56,260 - - - - 99 Myanmar 76 890,720 - - - 77 56 Nepal 28 230,160 24 52 23 69 11 Pakistan 43 2,367,580 15 30 53 57 23 Papua New Guinea 78 138,060 - - - 34 53 Philippines 88 1,760,880 5 26 69 70 60 Singapore - - - - - - 100 Sri Lanka 95 296,400 - - - - 97 Taiwan - - - - - - - Thailand 92 998,200 - - - - 99 Viet Nam 86 1,409,540 - - - 79 85 Total/Mean 70 47,592,700 - - - 72 60 Latin America Argentina 95 690,650 - - - - 99 Bolivia 83 211,650 8 21 70 - 65 Brazil 86 3,011,720 1 8 89 - 88 Chile 95 269,800 - - - - 100 Colombia 91 885,430 3 9 88 - 86 Costa Rica 70 54,600 - - - - 98 Cuba 100 129,000 - - - - 100 Dominican Republic 99 200,970 2 9 89 - 99 Ecuador 69 203,550 - - - - 69 El Salvador 76 122,360 - - - - 69 Guatemala 84 351,960 3 12 83 - 41 Guyana 81 12,960 - - - - 86 Haiti 79 198,290 10 37 52 52 24 Honduras 83 170,150 - - - - 56 Jamaica 99 53,460 - - - - 95 Mexico 86 1,972,840 - - - - 86 Nicaragua 86 146,200 5 19 75 - 67 Panama 72 50,400 - - - - 90 Paraguay 89 153,970 4 21 74 - 71 Peru 84 524,160 6 22 72 - 59 Puerto Rico - - - - - - - Trinidad and Tobago 92 15,640 - - - - 96 Uruguay 94 53,580 - - - - 100 Venezuela 94 546,140 - - - - 94 Total/Mean 87 10,029,480 - - - - 82 Middle East/North Africa Algeria 81 586,440 - - - - 92 Egypt 69 1,318,590 5 22 70 71 69 Iraq 77 676,830 - - - 70 72 Jordan 99 149,490 4 12 84 - 100 Kuwait 95 47,500 - - - - 98 Lebanon 87 60,030 - - - - 89 Libya 81 103,680 - - - - 94 Morocco 68 480,760 29 47 24 - 40 Oman 100 91,000 - - - - 95 Saudi Arabia 90 685,800 - - - - 91 Sudan 60 660,000 - - - 35 86 Syria 71 348,610 - - - - 76 Tunisia 92 151,800 - - - - 90 Turkey 68 1,005,720 11 26 62 37 81 United Arab Emirates 97 47,530 - - - - 96 Yemen 45 405,450 27 34 33 31 22 Total/Mean 71 6,819,230 - - - - 72 Appendix A A.77 Table A.17. Percentage Receiving Antenatal Care, Tetanus Injections, and Delivery Care % with 1+ Visits During Pregnancy (1995-2003) No. Seen Antenatally at Least Once (minimum est.)** No. of Visits by Women with at Least One Visit (1993-2003)* % of Pregnant Women Given Tetanus, 2003 est. % Deliveries with Skilled Attendant, 1995-2003*** Sub-Saharan Africa Angola 66 470,580 - - - 72 45 Benin 81 225,180 5 28 66 56 66 Botswana 97 52,380 - - - - 94 Burkina Faso 73 453,330 8 52 37 50 31 Burundi 78 237,120 - - - 46 25 Cameroon 75 422,250 4 28 66 65 60 Central African Rep. 62 89,280 6 38 53 63 44 Chad 42 174,720 10 47 42 43 16 Congo - - - - - 59 - Congo, D.R. 68 1,807,440 - - - 48 61 Côte d'Ivoire 88 516,560 16 49 34 80 63 Eritrea 70 114,100 - - - 55 28 Ethiopia 27 807,840 22 38 39 24 6 Gabon 94 38,540 - - - 54 86 Gambia 91 45,500 - - - - 55 Ghana 92 609,960 6 23 70 70 44 Guinea 71 257,020 5 28 64 74 35 Guinea-Bissau 62 45,880 - - - 66 35 Kenya 88 908,160 4 30 65 66 41 Lesotho 85 46,750 - - - - 60 Liberia 85 141,950 - - - 56 51 Madagascar 71 510,490 5 45 49 55 46 Malawi 94 501,960 2 28 68 70 61 Mali 57 370,500 10 30 54 32 41 Mauritania 64 76,800 - - - 41 57 Mauritius - - - - - - 99 Mozambique 76 588,240 5 32 52 57 48 Namibia 91 59,150 7 21 64 85 78 Niger 41 271,420 12 59 29 36 16 Nigeria 58 2,795,600 2 13 72 51 35 Rwanda 92 338,560 12 75 13 76 31 Senegal 79 295,460 7 72 20 75 58 Sierra Leone 68 166,600 - - - 62 42 Somalia 32 165,120 - - - - 34 South Africa 94 945,640 - - - 52 84 Swaziland 87 31,320 - - - - 70 Tanzania 49 704,620 3 24 73 83 36 Togo 73 136,510 5 37 56 47 49 Uganda 92 1,211,640 7 40 51 48 39 Zambia 93 421,290 2 22 74 60 43 Zimbabwe 93 380,370 1 16 68 60 73 Total/Mean 65 17,435,830 - - - 53 41 Central Asia Republics Kazakhstan 91 227,500 - - - - 99 Kyrgyzstan 97 108,640 - - - - 98 Tajikistan 71 106,500 - - - - 71 Turkmenistan 98 104,860 - - - - 97 Uzbekistan 97 542,230 - - - - 96 Total/Mean 93 1,089,730 - - - - 92 Caucasus Armenia 92 26,680 - - - - 97 Azerbaijan 66 97,680 - - - - 84 Georgia 95 49,400 - - - - 96 Total/Mean 76 173,760 - - - - 88 Moldova, Russia, Ukraine Moldova 99 48,510 - - - - 99 Russian Federation - - - - - - 99 Ukraine - - - - - - 100 Total/Mean 99 48,510 - - - - 99 Grand Total/Mean 71 83,189,240 - - - - 60 * Columns add to 100% except for "don't know" and "missing" entries. ** Number of births times percent seen at least once. *** Data refer to the most recent year between 1995 and 2003. Note: Dashes mean no data available. Appendix A A.78 Table A.18. Maternal and Neonatal Program Effort Index (MNPI), 1999 and 2002 Surveys: Country Scores as Percent of Maximum 1 2 3 4 5 6 7 Country Health Center Capacities District Hospital Capacities Percentage with Access to Care Antenatal Services Delivery Services Newborn Services FP at Health Centers Asia Bangladesh 2002 55 76 43 56 45 61 50 Bangladesh 1999 47 59 31 51 40 55 62 China 2002 64 69 78 54 71 75 66 China 1999 56 67 75 49 72 74 68 India 2002 42 59 50 52 44 57 51 Indonesia 2002 51 65 61 50 62 66 59 Indonesia 1999 54 69 53 55 57 71 66 Iran 2002 67 84 91 85 84 89 87 Iran 1999 61 82 81 73 79 87 87 Myanmar 2002 57 77 60 72 69 76 58 Myanmar 1999 50 81 59 68 70 76 50 Nepal 2002 45 49 26 54 47 63 55 Nepal 1999 24 46 17 42 38 59 37 Pakistan 2002 40 51 30 38 34 47 33 Pakistan 1999 30 41 25 32 29 46 29 Philippines 2002 35 48 71 59 66 76 63 Philippines 1999 24 41 69 51 59 73 59 Viet Nam 2002 56 70 80 67 73 82 67 Viet Nam 1999 32 65 74 63 66 73 59 Latin America Bolivia 2002 60 56 43 67 65 79 57 Bolivia 1999 51 54 40 53 55 67 47 Brazil 2002 41 67 70 63 64 74 38 Brazil 1999 53 74 64 65 64 78 55 Dominican Rep. 2002 45 60 59 65 57 66 40 Dominican Rep. 1999 55 64 70 67 69 83 58 Ecuador 2002 46 62 55 70 67 81 65 Ecuador 1999 44 64 53 69 59 77 58 El Salvador 2002 63 63 51 75 68 79 73 El Salvador 1999 47 63 48 64 50 73 60 Guatemala 2002 34 50 41 52 44 61 41 Guatemala 1999 43 61 40 63 55 69 40 Haiti 2002 39 44 28 55 50 60 47 Haiti 1999 37 56 32 52 45 53 38 Honduras 2002 67 73 72 80 79 93 70 Honduras 1999 45 65 50 61 55 72 48 Mexico 2002 43 71 73 62 64 79 60 Mexico 1999 49 68 66 54 63 79 64 Nicaragua 2002 43 54 54 56 58 72 54 Nicaragua 1999 46 62 50 66 56 75 59 Panama 2002 64 87 83 90 83 93 74 Paraguay 2002 46 54 50 56 53 69 54 Paraguay 1999 49 60 57 64 63 70 61 Middle East/North Africa Algeria 2002 56 79 69 43 60 66 43 Algeria 1999 55 79 67 51 65 73 51 Egypt 2002 46 72 62 54 59 78 67 Egypt 1999 48 69 74 60 63 79 71 Jordan 2002 39 82 79 60 71 84 66 Morocco 2002 59 71 61 71 59 77 85 Sudan 2002 31 53 52 44 42 59 54 Sudan 1999 31 50 52 47 55 67 53 West Bank 2002 56 79 75 54 63 79 57 West Bank 1999 43 59 73 50 62 79 46 Yemen 2002 33 58 44 43 43 63 52 Yemen 1999 17 28 29 37 29 41 42 Continued Appendix A A.79 Table A.18. Maternal and Neonatal Program Effort Index (MNPI), 1999 and 2002 Surveys: Country Scores as Percent of Maximum 8 9 10 11 12 13 Country FP at District Hospitals Policies toward Safe Pregnancy Resources & Private Sector Information, Education Training Arrangements Monitoring, Evaluation Total Score (average) Asia Bangladesh 2002 61 65 50 55 56 48 55 Bangladesh 1999 71 57 45 46 38 40 49 China 2002 79 79 41 70 73 78 69 China 1999 80 80 30 59 64 76 65 India 2002 68 56 56 49 58 53 53 Indonesia 2002 66 62 44 54 47 56 57 Indonesia 1999 68 71 52 59 60 60 61 Iran 2002 78 56 61 55 68 67 75 Iran 1999 83 75 67 66 61 66 74 Myanmar 2002 56 63 57 64 70 65 65 Myanmar 1999 60 60 54 58 65 66 63 Nepal 2002 67 68 50 64 56 59 54 Nepal 1999 55 61 39 45 33 42 41 Pakistan 2002 43 41 45 38 31 33 39 Pakistan 1999 41 34 38 23 22 28 32 Philippines 2002 64 68 54 52 60 60 60 Philippines 1999 61 56 54 60 61 59 56 Viet Nam 2002 76 74 59 69 67 69 70 Viet Nam 1999 74 68 51 65 64 67 63 Latin America Bolivia 2002 55 61 65 47 61 58 60 Bolivia 1999 46 54 55 41 58 60 52 Brazil 2002 44 60 47 38 44 55 54 Brazil 1999 64 62 65 54 55 64 63 Dominican Rep. 2002 35 53 46 30 46 55 51 Dominican Rep. 1999 55 65 51 48 65 63 63 Ecuador 2002 68 68 67 44 57 59 62 Ecuador 1999 59 57 50 43 49 57 57 El Salvador 2002 80 62 42 38 69 74 64 El Salvador 1999 66 48 37 31 64 58 55 Guatemala 2002 50 47 43 30 52 44 45 Guatemala 1999 45 48 55 26 56 52 50 Haiti 2002 50 51 35 35 42 42 44 Haiti 1999 48 44 41 30 37 33 42 Honduras 2002 74 71 68 65 74 60 73 Honduras 1999 56 64 51 44 62 56 56 Mexico 2002 73 59 49 48 54 69 62 Mexico 1999 78 47 45 46 61 54 60 Nicaragua 2002 55 45 39 35 62 52 52 Nicaragua 1999 61 48 44 35 57 53 55 Panama 2002 77 75 49 53 73 78 75 Paraguay 2002 51 50 35 34 42 44 49 Paraguay 1999 64 63 43 44 54 44 57 Middle East/North Africa Algeria 2002 53 50 55 40 54 41 54 Algeria 1999 59 43 50 41 52 50 57 Egypt 2002 54 71 67 60 56 61 62 Egypt 1999 62 71 64 47 55 60 63 Jordan 2002 61 61 62 51 54 54 63 Morocco 2002 60 65 54 56 64 70 66 Sudan 2002 39 41 37 37 41 29 43 Sudan 1999 39 57 41 44 69 58 51 West Bank 2002 44 58 54 50 52 50 59 West Bank 1999 39 55 63 48 57 50 56 Yemen 2002 49 63 37 50 44 43 48 Yemen 1999 44 49 35 35 26 30 34 Continued Appendix A A.80 Table A.18. Maternal and Neonatal Program Effort Index (MNPI), 1999 and 2002 Surveys: Country Scores as Percent of Maximum 1 2 3 4 5 6 7 Country Health Center Capacities District Hospital Capacities Percentage with Access to Care Antenatal Services Delivery Services Newborn Services FP at Health Centers Sub-Saharan Africa Angola 2002 47 32 45 78 50 58 71 Angola 1999 54 58 36 68 68 69 63 Benin 2002 60 65 62 68 58 73 63 Benin 1999 58 64 49 63 63 78 59 Botswana 2002 84 71 78 89 85 95 90 Burkina Faso 2002 55 58 39 66 55 68 67 Cameroon 2002 57 58 52 79 67 77 47 Chad 2002 34 43 22 53 49 59 35 Congo 2002 46 51 15 64 58 73 44 Congo 1999 44 56 52 60 57 75 40 Congo, D.R. 2002 41 53 33 59 59 68 34 Congo, D.R. 1999 51 64 38 67 60 71 37 Côte d'Ivoire 2002 53 64 45 69 55 76 44 Ethiopia 2002 35 39 21 46 38 51 51 Ethiopia 1999 47 60 27 51 41 59 60 Ghana 2002 55 66 54 70 61 72 72 Ghana 1999 59 81 54 68 63 78 70 Guinea 2002 53 60 42 73 59 73 55 Guinea 1999 45 59 40 69 64 79 59 Kenya 2002 40 57 51 58 47 62 59 Kenya 1999 35 55 41 47 45 64 65 Madagascar 2002 62 62 37 65 56 72 60 Madagascar 1999 55 51 48 72 69 79 65 Mali 1999 65 63 42 71 69 75 66 Mauritania 2002 65 49 52 72 63 67 60 Mozambique 2002 56 65 54 62 69 78 66 Mozambique 1999 46 47 42 48 53 66 50 Namibia 2002 55 85 76 86 79 88 81 Niger 2002 53 53 34 62 46 59 51 Nigeria 2002 56 62 49 70 66 75 57 Nigeria 1999 42 54 41 57 53 64 47 Rwanda 2002 63 75 37 71 58 76 40 Rwanda 1999 47 66 44 59 45 68 34 Senegal 2002 67 68 42 76 65 70 63 Senegal 1999 63 63 40 67 67 75 72 South Africa 2002 65 70 70 78 72 84 74 South Africa 1999 59 63 73 67 58 76 62 Tanzania 2002 51 72 45 67 56 68 62 Tanzania 1999 42 66 47 55 49 62 53 Uganda 2002 55 70 49 67 60 68 58 Uganda 1999 50 64 41 58 55 67 58 Zambia 2002 37 59 52 61 55 66 59 Zambia 1999 29 57 37 50 46 61 51 Zimbabwe 2002 55 58 60 75 76 82 70 Zimbabwe 1999 49 68 66 69 69 85 63 Continued Appendix A A.81 Table A.18. Maternal and Neonatal Program Effort Index (MNPI), 1999 and 2002 Surveys: Country Scores as Percent of Maximum 8 9 10 11 12 13 Country FP at District Hospitals Policies toward Safe Pregnancy Resources & Private Sector Information, Education Training Arrangements Monitoring, Evaluation Total Score (average) Sub-Saharan Africa Angola 2002 49 63 45 57 43 50 53 Angola 1999 55 62 39 54 64 66 58 Benin 2002 63 75 42 48 50 66 61 Benin 1999 61 66 41 40 39 58 57 Botswana 2002 81 80 81 80 67 74 81 Burkina Faso 2002 61 66 37 51 50 56 56 Cameroon 2002 65 73 42 60 47 58 60 Chad 2002 32 61 33 46 47 46 43 Congo 2002 36 60 37 39 40 27 45 Congo 1999 35 65 38 44 46 37 50 Congo, D.R. 2002 38 57 30 37 43 45 46 Congo, D.R. 1999 39 46 35 32 48 41 48 Côte d'Ivoire 2002 46 64 35 46 38 46 52 Ethiopia 2002 48 52 34 31 33 40 40 Ethiopia 1999 54 57 39 41 39 48 48 Ghana 2002 67 78 54 58 59 67 64 Ghana 1999 68 85 61 51 59 69 67 Guinea 2002 55 72 34 58 52 61 58 Guinea 1999 48 80 45 58 54 62 59 Kenya 2002 65 57 38 34 37 41 50 Kenya 1999 71 55 34 28 33 39 47 Madagascar 2002 60 75 44 55 63 62 60 Madagascar 1999 62 68 43 46 45 68 59 Mali 1999 64 74 40 60 68 73 64 Mauritania 2002 43 64 40 41 45 53 55 Mozambique 2002 59 70 47 47 64 70 62 Mozambique 1999 47 69 34 43 55 68 52 Namibia 2002 80 64 78 59 67 83 75 Niger 2002 49 61 35 53 47 59 51 Nigeria 2002 57 70 46 55 47 53 59 Nigeria 1999 48 57 38 51 39 44 49 Rwanda 2002 53 69 40 60 46 58 57 Rwanda 1999 53 68 40 46 48 50 52 Senegal 2002 65 73 39 57 51 66 62 Senegal 1999 63 73 39 39 49 50 59 South Africa 2002 72 70 65 54 60 74 70 South Africa 1999 57 65 65 43 57 55 62 Tanzania 2002 64 71 56 57 56 66 61 Tanzania 1999 57 65 46 58 47 54 54 Uganda 2002 59 70 60 65 59 61 61 Uganda 1999 62 69 55 62 56 59 58 Zambia 2002 60 64 46 63 50 56 56 Zambia 1999 53 58 37 35 30 46 46 Zimbabwe 2002 60 69 48 53 55 72 64 Zimbabwe 1999 63 71 43 55 62 73 64 Appendix A A.82 Table A.19. Number of Births, Infant and Child Mortality Rates, and Number of Deaths, 2003 Estimates Under Age 5 Country Annual No. of Births Infant Mortality Rate Annual Infant Deaths Mortality Rate (USMR) Annual Child Deaths Asia Afghanistan 1,136,000 165 187,440 257 292,000 Bangladesh 4,183,000 46 192,418 69 289,000 Bhutan 77,000 70 5,390 85 7,000 Cambodia 475,000 97 46,075 140 67,000 China 18,706,000 30 561,180 37 692,000 China, Hong Kong SAR - - - - - India 25,052,000 63 1,578,276 87 2,180,000 Indonesia 4,515,000 31 139,965 41 185,000 Iran 1,424,000 33 46,992 39 56,000 Korea, DPR 364,000 42 15,288 55 20,000 Korea, Rep. 562,000 5 2,810 5 3,000 Laos 200,000 82 16,400 91 18,000 Malaysia 545,000 7 3,815 7 4,000 Mongolia 58,000 56 3,248 68 4,000 Myanmar 1,172,000 76 89,072 107 125,000 Nepal 822,000 61 50,142 82 67,000 Pakistan 5,506,000 81 445,986 103 567,000 Papua New Guinea 177,000 69 12,213 93 16,000 Philippines 2,001,000 27 54,027 36 72,000 Singapore 41,000 3 123 3 123 Sri Lanka 312,000 13 4,056 15 5,000 Taiwan 289,835 5 1,594 6 1,802 Thailand 1,085,000 23 24,955 26 28,000 Viet Nam 1,639,000 19 31,141 23 38,000 Total/Mean 70,052,000 50 3,511,012 68 4,735,000 Latin America Argentina 727,000 17 12,359 20 15,000 Bolivia 255,000 53 13,515 66 17,000 Brazil 3,502,000 33 115,566 35 123,000 Chile 284,000 8 2,272 9 3,000 Colombia 973,000 18 17,514 21 20,000 Costa Rica 78,000 8 624 10 1,000 Cuba 129,000 6 774 8 1,000 Dominican Republic 203,000 29 5,887 35 7,000 Ecuador 295,000 24 7,080 27 8,000 El Salvador 161,000 32 5,152 36 6,000 Guatemala 419,000 35 14,665 47 20,000 Guyana 16,000 52 832 69 1,000 Haiti 251,000 76 19,076 118 30,000 Honduras 205,000 32 6,560 41 8,000 Jamaica 54,000 17 918 20 1,000 Mexico 2,294,000 23 52,762 28 64,000 Nicaragua 170,000 30 5,100 38 6,000 Panama 70,000 18 1,260 24 2,000 Paraguay 173,000 25 4,325 29 5,000 Peru 624,000 26 16,224 34 21,000 Puerto Rico - - - - - Trinidad and Tobago 17,000 17 289 20 340 Uruguay 57,000 12 684 14 1,000 Venezuela 581,000 18 10,458 21 12,000 Total/Mean 11,538,000 27 313,896 32 372,000 Middle East/North Africa Algeria 724,000 35 25,340 41 30,000 Egypt 1,911,000 33 63,063 39 75,000 Iraq 879,000 102 89,658 125 110,000 Jordan 151,000 23 3,473 28 4,000 Kuwait 50,000 8 400 9 450 Lebanon 69,000 27 1,863 31 2,000 Libya 128,000 13 1,664 16 2,000 Morocco 707,000 36 25,452 39 28,000 Oman 91,000 10 910 12 1,000 Saudi Arabia 762,000 22 16,764 26 20,000 Sudan 1,100,000 63 69,300 93 102,000 Syria 491,000 16 7,856 18 9,000 Tunisia 165,000 19 3,135 24 4,000 Turkey 1,479,000 33 48,807 39 58,000 United Arab Emirates 49,000 7 343 8 392 Yemen 901,000 82 73,882 113 102,000 Total/Mean 9,657,000 45 431,910 57 547,000 Appendix A A.83 Table A.19. Number of Births, Infant and Child Mortality Rates, and Number of Deaths, 2003 Estimates Under Age 5 Country Annual No. of Births Infant Mortality Rate Annual Infant Deaths Mortality Rate (USMR) Annual Child Deaths Sub-Saharan Africa Angola 713,000 154 109,802 260 185,000 Benin 278,000 91 25,298 154 43,000 Botswana 54,000 82 4,428 112 6,000 Burkina Faso 621,000 107 66,447 207 129,000 Burundi 304,000 114 34,656 190 58,000 Cameroon 563,000 95 53,485 166 93,000 Central African Rep. 144,000 115 16,560 180 26,000 Chad 416,000 117 48,672 200 83,000 Congo 164,000 81 13,284 108 18,000 Congo, D.R. 2,658,000 129 342,882 205 545,000 Côte d'Ivoire 587,000 117 68,679 192 113,000 Eritrea 163,000 45 7,335 85 14,000 Ethiopia 2,992,000 112 335,104 169 506,000 Gabon 41,000 60 2,460 91 4,000 Gambia 50,000 90 4,500 123 6,000 Ghana 663,000 59 39,117 95 63,000 Guinea 362,000 104 37,648 160 58,000 Guinea-Bissau 74,000 126 9,324 204 15,000 Kenya 1,032,000 79 81,528 123 127,000 Lesotho 55,000 63 3,465 84 5,000 Liberia 167,000 157 26,219 235 39,000 Madagascar 719,000 78 56,082 126 91,000 Malawi 534,000 112 59,808 178 95,000 Mali 650,000 122 79,300 220 143,000 Mauritania 120,000 120 14,400 183 22,000 Mauritius 19,000 16 304 18 342 Mozambique 774,000 109 84,366 158 122,000 Namibia 65,000 48 3,120 65 4,000 Niger 662,000 154 101,948 262 173,000 Nigeria 4,820,000 98 472,360 198 954,000 Rwanda 368,000 118 43,424 203 75,000 Senegal 374,000 78 29,172 137 51,000 Sierra Leone 245,000 166 40,670 284 70,000 Somalia 516,000 133 68,628 225 116,000 South Africa 1,006,000 53 53,318 66 66,000 Swaziland 36,000 105 3,780 153 6,000 Tanzania 1,438,000 104 149,552 165 237,000 Togo 187,000 78 14,586 140 26,000 Uganda 1,317,000 81 106,677 140 184,000 Zambia 453,000 102 46,206 182 82,000 Zimbabwe 409,000 78 31,902 126 52,000 Total/Mean 26,813,000 104 2,790,496 176 4,705,000 Central Asia Republics Kazakhstan 250,000 63 15,750 73 18,000 Kyrgyzstan 112,000 59 6,608 68 8,000 Tajikistan 150,000 92 13,800 118 18,000 Turkmenistan 107,000 79 8,453 102 11,000 Uzbekistan 559,000 57 31,863 69 39,000 Total/Mean 1,178,000 65 76,474 80 94,000 Caucasus Armenia 29,000 30 870 33 1,000 Azerbaijan 148,000 75 11,100 91 13,000 Georgia 52,000 41 2,132 45 2,000 Total/Mean 229,000 62 14,102 70 16,000 Moldova, Russia, Ukraine Moldova 49,000 26 1,274 32 2,000 Russian Federation 1,226,000 16 19,616 21 26,000 Ukraine 409,000 15 6,135 20 8,000 Total/Mean 1,684,000 16 27,025 21 36,000 Grand Total/Mean 121,151,000 59 7,164,915 87 10,505,000 Note: Dashes mean no data available. Appendix A A.84 Table A.20. Births According to Risk Category Distribution of All Births Separate Risks by Birth Type* Country First Births No Risk Births Any Risk Births Total Births Birth Interval <24 mo. Birth Order 4+ Age 35+ Below Age 18 Mortality Ratio, Any Risk to No Risk Births Asia Afghanistan - - - - - - - - - Bangladesh 1999/2000 13.9 33.1 53.1 100 11.4 28.7 5.7 17.2 1.80 Bhutan - - - - - - - - - Cambodia 2000 15.9 26.4 57.7 100 17.0 44.7 20.1 2.8 1.30 China - - - - - - - - - China, Hong Kong SAR - - - - - - - - - India 1989/99 20.1 29.3 50.7 100 20.3 28.7 4.1 9.1 2.00 Indonesia 2003 30.4 35.6 34.0 100 8.4 20.8 13.5 4.3 1.58 Iran - - - - - - - - - Korea, DPR - - - - - - - - - Korea, Rep. - - - - - - - - - Laos - - - - - - - - - Malaysia - - - - - - - - - Mongolia - - - - - - - - - Myanmar - - - - - - - - - Nepal 2001 17.5 29.8 52.7 100 17.3 36.1 9.2 6.6 1.50 Pakistan 1990/91 14.8 19.1 66.1 100 27.3 50.1 12.9 3.6 2.00 Papua New Guinea - - - - - - - - - Philippines 1998 22.4 20.7 56.9 100 26.3 37.0 15.0 2.3 1.70 Singapore - - - - - - - - - Sri Lanka 1987 27.4 29.3 43.3 100 19.3 22.7 11.7 2.1 1.30 Taiwan - - - - - - - - - Thailand - - - - - - - - 1.70 Viet Nam 2002 37.9 36.7 25.4 100 9.5 12.0 9.0 1.5 3.26 Latin America Argentina - - - - - - - - - Bolivia 1998 18.6 22.4 59.0 100 21.5 41.4 16.4 4.7 1.80 Brazil 1996 26.2 29.3 44.5 100 18.7 21.5 9.6 8.3 2.00 Chile - - - - - - - - - Colombia 2000 28.1 29.5 42.4 100 16.0 17.8 9.6 8.7 2.00 Costa Rica - - - - - - - - - Cuba - - - - - - - - - Dominican Republic 1999 25.9 29.9 44.2 100 19.8 18.4 6.6 9.3 1.20 Ecuador 1987 19.1 22.4 58.5 100 25.9 39.3 12.2 5.1 2.50 El Salvador 1985 17.4 22.4 60.2 100 26.2 36.6 9.8 8.9 1.90 Guatemala 1998/99 16.1 21.1 62.8 100 24.6 42.9 13.3 6.8 1.30 Guyana - - - - - - - - - Haiti 2000 17.7 20.9 61.4 100 20.5 45.3 18.0 5.2 1.30 Honduras - - - - - - - - - Jamaica - - - - - - - - - Mexico 1987 17.7 22.6 59.7 100 25.6 39.4 11.3 6.1 2.40 Nicaragua 1997/98 16.3 23.1 60.7 100 23.4 36.9 9.9 11.0 2.10 Panama - - - - - - - - - Paraguay 1990 19.7 19.6 60.8 100 28.0 41.4 16.3 4.7 3.10 Peru 2000 24.9 26.8 48.3 100 13.8 30.9 15.2 5.5 1.30 Puerto Rico - - - - - - - - - Trinidad and Tobago 1987 24.6 24.9 50.5 100 26.9 28.8 8.2 4.1 2.50 Uruguay - - - - - - - - - Venezuela - - - - - - - - - Middle East/North Africa Algeria - - - - - - - - - Egypt 2003 26.5 32.5 41.0 100 14.4 26.0 10.8 3.1 1.57 Iraq - - - - - - - - - Jordan 2002 18.7 20.0 61.3 100. 33.4 43.0 13.9 1.5 1.65 Kuwait - - - - - - - - - Lebanon - - - - - - - - - Libya - - - - - - - - - Morocco 1992 16.8 18.9 64.3 100 20.4 51.5 19.7 2.3 1.60 Oman - - - - - - - - - Saudi Arabia - - - - - - - - - Sudan 1990 13.8 18.4 67.8 100 23.3 53.1 13.5 4.9 1.50 Syria - - - - - - - - - Tunisia 1988 19.5 19.4 61.2 100 28.9 43.7 13.8 0.8 2.00 Turkey 1998 29.9 29.9 40.2 100 16.8 22.3 7.1 4.4 2.00 United Arab Emirates - - - - - - - - - Yemen 1997 11.3 14.1 74.5 100 30.6 59.0 16.2 4.7 1.60 Appendix A A.85 Table A.20. Births According to Risk Category Distribution of All Births Separate Risks by Birth Type* Country First Births No Risk Births Any Risk Births Total Births Birth Interval <24 mo. Birth Order 4+ Age 35+ Below Age 18 Mortality Ratio, Any Risk to No Risk Births Sub-Saharan Africa Angola - - - - - - - - - Benin 2001 16.4 26.2 57.4 100 12.3 46.4 14.3 5.5 1.40 Botswana 1988 17.9 29.5 52.6 100 10.5 39.8 12.8 8.1 0.90 Burkina Faso 1998/99 12.4 23.3 64.3 100 14.1 52.9 17.8 5.8 1.20 Burundi 1987 15.5 23.9 60.6 100 18.2 51.7 17.2 0.9 1.20 Cameroon 1998 12.9 22.8 64.3 100 19.3 46.8 12.1 9.9 1.60 Central African Republic 1994/95 12.8 22.8 64.4 100 19.9 45.4 11.1 9.5 1.50 Chad 1996/97 10.6 21.7 67.8 100 19.2 50.1 10.7 9.8 1.10 Congo - - - - - - - - - Congo D.R. - - - - - - - - - Côte d'Ivoire 1998/99 14.1 25.5 60.4 100 12.4 43.6 13.4 10.6 1.20 Eritrea 2002 14.3 25.0 60.8 100 16.0 46.9 21.9 5.3 1.61 Ethiopia 2000 14.1 22.4 63.4 100 15.9 50.8 17.3 5.4 1.40 Gabon 2000 14.6 25.0 60.4 100 15.6 39.2 9.8 13.5 1.20 Gambia - - - - - - - - - Ghana 1998 19.3 29.1 51.6 100 10.1 41.4 18.0 4.2 1.30 Guinea 1999 9.2 23.8 67.1 100 13.8 51.2 13.9 10.4 1.40 Guinea-Bissau - - - - - - - - - Kenya 2003 18.0 25.8 56.2 100 17.5 40.4 12.3 6.9 1.55 Lesotho - - - - - - - - - Liberia 1986 11.6 22.9 65.5 100 23.1 45.6 13.0 9.9 1.30 Madagascar 1997 13.5 19.6 66.9 100 24.3 46.8 13.9 9.1 1.60 Malawi 2000 16.5 27.7 55.8 100 13.1 41.6 12.8 7.3 1.10 Mali 2001 9.6 20.2 70.2 100 18.0 54.4 15.8 8.5 1.50 Mauritania 2000/01 14.3 22.7 62.9 100 17.6 48.3 17.0 6.0 1.20 Mauritius - - - - - - - - - Mozambique 1997 12.7 28.3 59.1 100 14.3 42.1 12.9 10.2 1.40 Namibia 2000 23.1 29.6 47.4 100 9.8 32.7 17.1 6.4 1.48 Niger 1998 8.0 18.0 74.0 100 20.3 56.6 14.1 10.1 1.30 Nigeria 2003 13.7 21.2 65.1 100 19.1 46.5 14.2 8.9 1.43 Rwanda 2000 18.3 23.1 58.6 100 18.8 46.3 21.9 1.9 1.30 Senegal 1997 12.4 23.3 64.3 100 14.6 52.8 18.4 5.6 1.20 Sierra Leone - - - - - - - - - Somalia - - - - - - - - - South Africa 1998 26.1 32.1 41.8 100 9.1 26.7 15.0 6.8 1.50 Swaziland - - - - - - - - - Tanzania 1999 17.2 26.2 56.6 100 12.7 43.0 12.8 6.5 1.10 Togo 1998 14.7 27.0 58.3 100 11.6 49.3 16.9 4.6 1.40 Uganda 2000/01 11.2 21.8 67.0 100 22.6 49.2 11.5 7.6 1.20 Zambia 2001/02 14.3 27.0 58.7 100 12.3 43.3 12.5 9.2 1.10 Zimbabwe 1999 25.8 32.5 41.7 100 7.4 29.8 11.9 7.5 1.40 Central Asia Republics Kazakhstan 1999 33.2 28.1 38.7 100 20.2 16.5 8.2 2.2 1.40 Kyrgyzstan 1997 29.8 27.0 43.3 100 20.3 25.8 6.5 1.3 1.10 Tajikistan - - - - - - - - - Turkmenistan 2000 31.8 26.0 42.2 100 24.2 20.5 7.8 0.7 1.30 Uzbekistan 2002 30.0 36.0 34.0 100 16.0 18.0 6.2 1.1 1.37 Caucasus Armenia 2000 34.9 31.4 33.7 100 20.3 9.6 4.7 3.3 1.40 Azerbaijan - - - - - - - - - Georgia - - - - - - - - - Moldova, Russia, Ukraine Moldova - - - - - - - - - Russia - - - - - - - - - Ukraine - - - - - - - - - *Columns are not additive since births can fall into multiple categories. Note: Dashes mean no data available. Appendix A A.86 Table A.21. Immunizations, ARI, and Re-hydration 1-Year-Old Children % Immunized 2003 Children Under Age 5 Country TB DPT3 Polio3 Measles HepB3 % with ARI 1998-2003 % with ARI Taken to Health Provider % with Diarrhea Receiving ORS and Continued Feeding 1994-2003 Asia Afghanistan 56 54 54 50 - 19 28 - Bangladesh 95 85 85 77 - 18 27 35 Bhutan 93 95 96 88 95 - - - Cambodia 76 69 69 65 - 20 35 - China 93 90 91 84 70 - - - China, Hong Kong SAR - - - - - - - - India 81 70 70 67 - 19 64 22 Indonesia 82 70 70 72 75 8 57 61 Iran 99 99 99 99 98 24 93 - Korea, DPR 88 68 99 95 - - - - Korea, Rep. 87 97 94 96 91 - - - Laos 65 50 52 42 50 1 36 37 Malaysia 99 96 97 92 95 - - - Mongolia 98 98 98 98 98 2 78 66 Myanmar 79 77 76 75 - 4 48 48 Nepal 91 78 76 75 15 23 24 43 Pakistan 82 67 69 61 - - - 33 Papua New Guinea 60 54 41 49 53 13 75 - Philippines 91 79 80 80 40 - 46 37 Singapore 97 92 92 88 92 - - - Sri Lanka 99 99 98 99 - - - - Taiwan - - - - - - - - Thailand 99 96 97 94 95 - - - Viet Nam 98 99 96 93 78 20 71 24 Latin America Argentina 99 88 91 97 - - - - Bolivia 94 81 79 64 81 - 49 59 Brazil 99 96 99 99 91 - - 28 Chile 94 99 99 99 - - - - Colombia 96 91 91 92 93 13 51 44 Costa Rica 87 88 88 89 86 - - - Cuba 99 71 98 99 99 - - - Dominican Republic 90 65 60 79 81 20 61 53 Ecuador 99 89 99 99 58 - - - El Salvador 90 88 87 99 75 42 - - Guatemala 97 83 83 75 - 18 64 22 Guyana 95 90 91 89 90 5 78 40 Haiti 71 43 43 53 - 39 63 41 Honduras 91 92 92 95 92 - - - Jamaica 88 81 80 78 19 3 39 21 Mexico 99 91 92 96 91 - - - Nicaragua 94 86 86 93 86 31 57 49 Panama 87 86 83 83 86 - - - Paraguay 70 77 77 91 77 - - - Peru 94 89 89 95 60 20 58 46 Puerto Rico - - - - - - - - Trinidad and Tobago - 91 91 88 76 3 74 31 Uruguay 99 91 91 95 91 - - - Venezuela 91 68 86 82 75 9 72 51 Middle East/North Africa Algeria 98 87 87 84 - - - - Egypt 98 98 98 98 98 10 70 29 Iraq 93 81 84 90 70 7 76 - Jordan 67 97 97 96 97 6 72 - Kuwait - 99 99 97 99 - - - Lebanon - 92 92 96 88 4 74 - Libya 99 93 93 91 91 - - - Morocco 92 91 91 90 90 - 35 - Oman 98 99 99 98 99 - - - Saudi Arabia 94 95 95 96 95 - - - Sudan 53 50 50 57 - 5 57 38 Syria 99 99 99 98 98 18 66 - Tunisia 93 95 95 90 92 9 43 - Turkey 89 68 69 75 68 12 37 19 United Arab Emirates 98 94 94 94 92 - - - Yemen 67 66 66 66 42 23 32 23 Appendix A A.87 Table A.21. Immunizations, ARI, and Re-hydration 1-Year-Old Children % Immunized 2003 Children Under Age 5 Country TB DPT3 Polio3 Measles HepB3 % with ARI 1998-2003 % with ARI Taken to Health Provider % with Diarrhea Receiving ORS and Continued Feeding 1994-2003 Sub-Saharan Africa Angola 62 46 45 62 - - - 32 Benin 99 88 88 83 81 12 29 42 Botswana 99 97 97 90 78 39 14 7 Burkina Faso 83 84 83 76 - 14 22 - Burundi 84 74 69 75 - 13 40 16 Cameroon 82 73 72 61 - 7 25 33 Central African Republic 70 40 40 35 - 10 32 47 Chad 72 47 48 61 - 12 22 50 Congo 60 50 50 50 - 4 38 - Congo, D.R. 68 49 55 54 - 11 36 17 Côte d'Ivoire 66 54 54 56 48 - - 34 Eritrea 91 83 83 84 83 19 44 - Ethiopia 76 56 57 52 - 24 16 38 Gabon 89 38 31 55 - 13 48 44 Gambia 99 90 90 90 90 8 75 38 Ghana 92 80 80 80 80 10 44 24 Guinea 78 45 43 52 - 16 39 29 Guinea-Bissau 84 77 75 61 - 10 64 23 Kenya 87 73 67 72 73 18 46 15 Lesotho 83 79 78 70 - 7 49 29 Liberia 43 38 39 53 - 39 70 - Madagascar 72 55 58 55 55 6 47 47 Malawi 91 84 85 77 84 27 27 51 Mali 63 69 65 68 79 10 43 45 Mauritania 84 76 75 71 - 10 39 - Mauritius 92 92 93 94 92 - - - Mozambique 87 72 70 77 72 10 51 33 Namibia 92 82 82 70 - 18 53 39 Niger 64 52 51 64 - 12 27 43 Nigeria 48 25 39 35 - 10 31 28 Rwanda 88 96 96 90 96 12 20 16 Senegal 77 73 73 60 - 7 27 33 Sierra Leone 87 70 60 73 - 9 50 39 Somalia 65 40 40 40 - - - - South Africa 97 94 94 83 94 19 75 37 Swaziland 97 95 95 94 95 10 60 24 Tanzania 91 95 97 97 95 14 68 38 Togo 84 64 63 58 - 9 30 25 Uganda 96 81 82 82 63 23 65 29 Zambia 94 80 80 84 - 15 69 24 Zimbabwe 92 80 80 80 80 16 50 80 Central Asia Republics Kazakhstan 99 99 99 99 99 3 48 22 Kyrgyzstan 99 98 98 99 99 - - 16 Tajikistan 99 82 84 89 57 1 51 29 Turkmenistan 99 98 99 97 97 1 51 - Uzbekistan 98 98 99 99 99 0 57 33 Caucasus Armenia 92 94 96 94 93 11 25 48 Azerbaijan 99 97 98 98 98 3 36 40 Georgia 87 76 75 73 49 4 99 - Moldova, Russia, Ukraine Moldova 98 98 98 96 99 1 78 52 Russian Federation 97 98 97 96 94 - - - Ukraine 98 97 99 99 77 - - - Data refer to the most recent year available during the period specified in the column heading. ARI: Acute Respiratory Infection. Note: Dashes mean no data available. Appendix A A.88 Table A.22. Estimated Number of People Living with HIV/AIDS, Estimated Number of Orphans (AIDS and non-AIDS), and Estimated AIDS Deaths, at the End of 2003 Number Infected with HIV Country Adult Prevalence (percent ages 15-49 infected with HIV) Adults (15-49) Children (0-14) Adults and Children AIDS Deaths in Adults and Children AIDS Orphans Orphans from All Causes Asia Afghanistan - - - - - - 14,000 Bangladesh - - - - - - 59,000 Bhutan - - - - - - 1,000 Cambodia 2.6 170,000 7,300 170,000 15,000 - 7,000 China 0.1 830,000 - 840,000 44,000 - 370,000 China, Hong Kong SAR 0.1 2,600 - 2,600 <200 - - India - - - - - - 400,000 Indonesia 0.1 110,000 - 110,000 2,400 - 76,000 Iran 0.1 31,000 - 31,000 800 - 29,000 Korea, DPR - - - - - - 7,000 Korea, Rep. <0.1 8,300 - 8,300 <200 - 11,000 Laos 0.1 1,700 - 1,700 <200 - 3,000 Malaysia 0.4 51,000 - 52,000 2,000 - 10,000 Mongolia <0.1 <500 - <500 <200 - 1,000 Myanmar 1.2 320,000 7,600 330,000 20,000 - 20,000 Nepal 0.5 60,000 - 61,000 3,100 - 11,000 Pakistan 0.1 73,000 - 74,000 4,900 - 77,000 Papua New Guinea 0.6 16,000 - 16,000 600 - 2,000 Philippines <0.1 8,900 - 9,000 <500 - 37,000 Singapore 0.2 4,100 - 4,100 <200 - - Sri Lanka <0.1 3,500 - 3,500 <200 - 6,000 Taiwan - - - - - - - Thailand 1.5 560,000 12,000 570,000 58,000 - 20,000 Viet Nam 0.4 200,000 - 220,000 9,000 - 30,000 Total 2,450,100 - 2,503,200 159,800 - 1,191,000 Latin America Argentina 0.7 120,000 - 130,000 1,500 - 12,000 Bolivia 0.1 4,800 - 4,900 <500 - 4,000 Brazil 0.7 650,000 - 660,000 15,000 - 58,000 Chile 0.3 26,000 - 26,000 1,400 - 5,000 Colombia 0.7 180,000 - 190,000 3,600 - 17,000 Costa Rica 0.6 12,000 - 12,000 900 - 1,000 Cuba 0.1 3,300 - 3,300 <200 - 3,000 Dominican Republic 1.7 85,000 2,200 88,000 7,900 - 4,000 Ecuador 0.3 20,000 - 21,000 1,700 - 5,000 El Salvador 0.7 28,000 - 29,000 2,200 - 3,000 Guatemala 1.1 74,000 - 78,000 5,800 - 7,000 Guyana 2.5 11,000 600 11,000 1,100 - 400 Haiti 5.6 260,000 19,000 280,000 24,000 - 4,000 Honduras 1.8 59,000 3,900 63,000 4,100 - 3,000 Jamaica 1.2 21,000 <500 22,000 900 - 1,000 Mexico 0.3 160,000 - 160,000 5,000 - 42,000 Nicaragua 0.2 6,200 - 6,400 <500 - 3,000 Panama 0.9 15,000 - 16,000 <500 - 1,000 Paraguay 0.5 15,000 - 15,000 600 - 3,000 Peru 0.5 80,000 - 82,000 4,200 - 11,000 Puerto Rico - - - - - - - Trinidad and Tobago 3.2 28,000 700 29,000 1,900 - 400 Uruguay 0.3 5,800 - 6,000 <500 - 1,000 Venezuela 0.7 100,000 - 110,000 4,100 - 10,000 Total 1,964,100 - 2,042,600 85,900 - 198,800 Middle East/North Africa Algeria 0.1 9,000 - 9,100 <500 - - Egypt <0.1 12,000 - 12,000 700 - - Iraq <0.1 <500 - <500 - - - Jordan <0.1 <500 - 600 <200 - - Kuwait - - - - - - - Lebanon 0.1 2,800 - 2,800 <200 - - Libya 0.3 10,000 - 10,000 - - - Morocco 0.1 15,000 - 15,000 - - - Oman 0.1 1,300 - 1,300 <200 - - Saudi Arabia - - - - - - - Sudan 2.3 380,000 21,000 400,000 23,000 91,000 1,300,000 Syria <0.1 <500 - <500 <200 - - Tunisia <0.1 1,000 - 1,000 <200 - - Turkey - - - - - - - United Arab Emirates - - - - - - - Yemen 0.1 12,000 - 12,000 - - - Total 443,100 - 463,800 23,700 - - Appendix A A.89 Table A.22. Estimated Number of People Living with HIV/AIDS, Estimated Number of Orphans (AIDS and non-AIDS), and Estimated AIDS Deaths, at the End of 2003 Number Infected with HIV Country Adult Prevalence (percent ages 15-49 infected with HIV) Adults (15-49) Children (0-14) Adults and Children AIDS Deaths in Adults and Children AIDS Orphans Orphans from All Causes Sub-Saharan Africa Angola 3.9 220,000 23,000 240,000 21,000 110,000 1,000,000 Benin 1.9 62,000 5,700 68,000 5,800 34,000 340,000 Botswana 37.3 330,000 25,000 350,000 33,000 120,000 160,000 Burkina Faso 4.2 270,000 31,000 300,000 29,000 260,000 830,000 Burundi 6.0 220,000 27,000 250,000 25,000 200,000 660,000 Cameroon 6.9 520,000 43,000 560,000 49,000 240,000 930,000 Central African Republic 13.5 240,000 21,000 260,000 23,000 110,000 290,000 Chad 4.8 180,000 18,000 200,000 18,000 96,000 500,000 Congo 4.9 80,000 10,000 90,000 9,700 97,000 260,000 Congo, D.R. - - - - - - - Côte d'Ivoire 7.0 530,000 40,000 570,000 47,000 310,000 940,000 Eritrea 2.7 55,000 5,600 60,000 6,300 39,000 230,000 Ethiopia 4.4 1,400,000 120,000 1,500,000 120,000 720,000 3,900,000 Gabon 8.1 45,000 2,500 48,000 3,000 14,000 57,000 Gambia 1.2 6,300 500 6,800 600 2,000 45,000 Ghana 3.1 320,000 24,000 350,000 30,000 170,000 1,000,000 Guinea 3.2 130,000 9,200 140,000 9,000 35,000 42,000 Guinea-Bissau - - - - - - 81,000 Kenya 6.7 1,100,000 100,000 1,200,000 150,000 650,000 1,700,000 Lesotho 28.9 300,000 22,000 320,000 29,000 100,000 180,000 Liberia 5.9 96,000 8,000 100,000 7,200 36,000 230,000 Madagascar 1.7 130,000 8,600 140,000 7,500 30,000 1,000,000 Malawi 14.2 810,000 83,000 900,000 84,000 500,000 1,000,000 Mali 1.9 120,000 13,000 140,000 12,000 75,000 730,000 Mauritania 0.6 8,900 - 9,500 <500 2,000 140,000 Mauritius - - - - - - - Mozambique 12.2 1,200,000 99,000 1,300,000 110,000 470,000 1,500,000 Namibia 21.3 200,000 15,000 210,000 16,000 57,000 120,000 Niger 1.2 64,000 5,900 70,000 4,800 24,000 680,000 Nigeria 5.4 3,300,000 290,000 3,600,000 310,000 1,800,000 7,000,000 Rwanda 5.1 230,000 22,000 250,000 22,000 160,000 810,000 Senegal 0.8 41,000 3,100 44,000 3,500 17,000 460,000 Sierra Leone - - - - - - - Somalia - - - - - - - South Africa 21.5 5,100,000 230,000 5,300,000 370,000 1,100,000 2,200,000 Swaziland 38.8 200,000 16,000 220,000 17,000 65,000 100,000 Tanzania 8.8 1,500,000 140,000 1,600,000 160,000 980,000 2,500,000 Togo 4.1 96,000 9,300 110,000 10,000 54,000 240,000 Uganda 4.1 450,000 84,000 530,000 78,000 940,000 2,000,000 Zambia 16.5 830,000 85,000 920,000 89,000 630,000 1,100,000 Zimbabwe 24.6 1,600,000 120,000 1,800,000 170,000 980,000 1,300,000 Total 21,984,200 1,759,400 23,756,300 2,079,400 11,227,000 36,255,000 Central Asia Republics Kazakhstan 0.2 16,400 - 16,500 <200 - - Kyrgyzstan 0.1 3,900 - 3,900 <200 - - Tajikistan <0.1 <200 - <200 - - - Turkmenistan <0.1 <200 - <200 - - - Uzbekistan 0.1 11,000 - 11,000 <500 - - Total 31,300 - 31,400 - - - Caucasus Armenia 0.1 2,500 - 2,600 <200 - - Azerbaijan <0.1 1,400 - 1,400 - - - Georgia 0.1 3,000 - 3,000 <200 - - Total 6,900 - 7,000 - - - Moldova, Russia, Ukraine Moldova 0.2 5,500 - 5,500 - - - Russian Federation 1.1 860,000 - 860,000 - - - Ukraine 1.4 360,000 - 360,000 20,000 - - Total 1,225,500 - 1,225,500 20,000 - - Grand Total 28,105,200 30,029,800 Note: Due to rounding, totals may not equal the sum of column or row figures. Dashes mean no data available. Appendix A A.90 Table A.23a. Condom Needs: 2005 Projections Condom Requirements to Meet Coverage Targets Country Commercial Sex Contacts (000s) Sex Between Men (000s) Casual Sex Contacts (000s) Risky Regular Partnerships (000s) Total Condoms Required (000s) Asia Afghanistan 478 48 6,083 11,128 17,737 Bangladesh 1,214 3,573 33,983 72,418 111,189 Bhutan 1,512 36 625 1,017 3,190 Cambodia 942 316 5,240 2,959 9,458 China 71,156 2,847 641,719 556,661 1,272,382 China, Hong Kong SAR - - - - - India 49,571 31,404 159,349 487,061 727,385 Indonesia 4,167 3,587 36,667 92,996 137,418 Iran 1,138 1,502 15,740 12,466 30,847 Korea, DPR 967 10 6,170 11,286 18,432 Korea, Rep. 2,408 493 13,644 24,959 41,504 Laos 130 96 2,063 2,550 4,839 Malaysia 788 0 2,979 11,992 15,759 Mongolia 117 67 758 1,387 2,329 Myanmar 1,047 296 13,149 24,053 38,545 Nepal 544 1,337 10,998 21,324 34,202 Pakistan 2,976 33 37,930 69,384 110,324 Papua New Guinea 1,698 124 1,859 3,401 7,082 Philippines 6,404 899 10,596 38,930 56,829 Singapore - - - - - Sri Lanka 1,359 1,737 11,940 19,856 34,891 Taiwan - - - - - Thailand 2,596 - 19,404 14,810 36,810 Viet Nam 499 1,820 10,403 41,882 54,604 Total 151,711 50,225 1,041,299 1,522,522 2,765,757 Latin America Argentina 1,730 901 17,584 33,516 53,731 Bolivia 426 11 4,993 5,439 10,869 Brazil 62,131 1,986 251,000 347,618 662,736 Chile 492 899 4,395 10,994 16,780 Colombia 2,993 170 26,976 25,376 55,516 Costa Rica 220 274 2,059 2,412 4,965 Cuba 597 284 29,662 13,907 44,450 Dominican Republic 1,845 464 10,905 4,246 17,460 Ecuador 546 409 8,048 9,999 19,001 El Salvador 171 535 2,052 4,425 7,182 Guatemala 389 318 5,187 8,263 14,157 Guyana 65 46 362 549 1,022 Haiti 879 323 11,164 6,587 18,954 Honduras 359 118 3,147 4,806 8,429 Jamaica 129 65 1,596 1,869 3,659 Mexico 3,870 272 39,612 69,870 113,624 Nicaragua 289 181 3,133 3,670 7,273 Panama 201 156 907 2,269 3,534 Paraguay 311 143 3,515 4,118 8,087 Peru 1,149 37 16,578 36,716 54,479 Puerto Rico 46 41 29 35 151 Trinidad and Tobago 53 97 292 730 1,172 Uruguay 160 133 4,389 2,194 6,875 Venezuela 2,733 1,281 16,008 18,752 38,774 Total 81,785 9,143 463,590 618,361 1,172,879 Middle East/North Africa Algeria 518 684 7,197 5,665 14,064 Egypt 1,118 142 14,686 11,631 27,576 Iraq 370 148 5,137 4,043 9,699 Jordan 107 343 1,241 977 2,668 Kuwait - - - - - Lebanon 60 107 866 682 1,714 Libya 136 180 1,276 1,004 2,596 Morocco 506 1,022 6,823 5,977 14,328 Oman 40 52 757 600 1,449 Saudi Arabia 315 416 5,676 4,468 10,874 Sudan 4,370 - 3,559 3,841 11,769 Syria 270 357 3,611 2,843 7,081 Tunisia 163 317 2,247 1,769 4,496 Turkey 1,119 1,477 15,627 12,376 30,599 United Arab Emirates - - - - - Yemen 274 361 3,825 2,902 7,362 Total 9,365 5,606 72,527 58,778 146,276 Appendix A A.91 Table A.23a. Condom Needs: 2005 Projections Condom Requirements to Meet Coverage Targets Country Commercial Sex Contacts (000s) Sex Between Men (000s) Casual Sex Contacts (000s) Risky Regular Partnerships (000s) Total Condoms Required (000s) Sub-Saharan Africa Angola 787 - 9,476 9,277 19,540 Benin 973 - 4,601 4,858 10,431 Botswana 290 - 6,055 2,745 9,090 Burkina Faso 825 - 15,422 14,192 30,440 Burundi 236 - 1,110 1,953 3,300 Cameroon 2,610 - 24,673 15,444 42,727 Central African Rep. 506 - 1,265 1,155 2,925 Chad 649 - 2,704 2,470 5,823 Congo 732 - 1,994 2,543 5,269 Congo, D.R. 5,129 - 19,883 37,234 62,245 Côte d'Ivoire 3,724 - 37,611 19,760 61,095 Eritrea 273 - 2,717 1,566 4,555 Ethiopia 3,562 - 29,895 8,235 41,693 Gabon 355 - 1,086 992 2,433 Gambia 247 - 944 1,057 2,249 Ghana 2,490 - 9,990 6,205 18,684 Guinea 1,262 - 11,831 6,059 19,152 Guinea-Bissau 155 - 1,591 1,453 3,198 Kenya 3,988 - 53,361 39,965 97,314 Lesotho 190 - 2,064 1,885 4,140 Liberia 481 - 2,678 2,445 5,604 Madagascar 937 - 5,802 13,973 20,712 Malawi 586 - 11,133 10,338 22,056 Mali 1,755 - 2,329 2,036 6,120 Mauritania 576 - 2,322 2,121 5,018 Mauritius 142 - 18 46 206 Mozambique 2,241 - 15,354 17,746 35,341 Namibia 203 - 5,188 4,031 9,422 Niger 775 - 4,364 2,971 8,110 Nigeria 17,783 - 65,888 72,371 156,042 Rwanda 134 - 3,394 2,258 5,786 Senegal 1,172 - 3,557 12,897 17,626 Sierra Leone 615 - 3,933 3,591 8,139 Somalia 881 - 2,948 2,692 6,522 South Africa 9,413 - 72,661 52,015 134,089 Swaziland 94 - 466 425 985 Tanzania 4,196 - 50,277 26,912 81,385 Togo 711 - 7,211 5,146 13,068 Uganda 832 - 27,923 20,881 49,637 Zambia 666 - 14,199 15,350 30,215 Zimbabwe 1,712 - 25,479 14,437 41,628 Total 74,886 - 565,396 463,732 1,104,015 Central Asia Republics Kazakhstan 243 303 20,819 19,956 41,321 Kyrgyzstan 79 110 1,882 5,029 7,100 Tajikistan 92 128 2,263 6,046 8,529 Turkmenistan 78 108 1,831 4,891 6,908 Uzbekistan 473 567 6,166 26,279 33,486 Total 966 1,216 32,960 62,201 97,343 Caucasus Armenia 188 86 2,462 3,553 6,290 Azerbaijan 267 186 3,116 8,326 11,894 Georgia 154 107 1,739 4,647 6,646 Total 609 379 7,317 16,526 24,830 Moldova, Russia, Ukraine Moldova 129 117 965 4,113 5,325 Russian Federation 4,390 3,051 50,410 134,693 192,545 Ukraine 637 974 6,813 29,035 37,459 Total 5,156 4,143 58,188 167,842 235,328 Grand Total/Mean 324,478 70,712 2,241,277 2,909,962 5,546,429 Notes: These figures represent estimates of the number of condoms required to protect against the transmission of HIV in the most risky situations. We assume that condom utilization will be highest in situations with the most risk. Dashes mean no data available. These projections assume that the percentage of acts covered by condom use increases from current levels in 2003 to target levels by 2010. Coverage targets vary by type of sex and severity of the epidemic. Epidemics in each country are classified by adult HIV prevalence as very low (<0.5%), low (>0.5% and <1.0%), medium (>1.0% and <5%) and high (>5%). Coverage targets by 2010 for very low, low, medium and high epidemics are: commercial sex and sex between men 60/70/80/80%, casual contacts 20/40/60/60%, and risky regular partnerships 10/10/20/30%. Risky regular partnerships are marriages and other long-term unions where at least one partner also has partners outside this relationship. The number of people with casual contacts and the number of risky regular partnerships are estimated from survey data (mostly DHS) on the percentage of men and women engaging in sex with non-marital, non- cohabiting partners. The number of sex workers and men who have sex with men is estimated from country studies, where available. Default assumptions, used when country-specific data are not available, are 4% of adult urban females (15-49) are sex workers and 2% of adult males (15-49) have sex with other men. Country specific data on coital frequency are used where available. Otherwise default values are applied. These are 200 contacts a year for sex workers, 45 for sex between men, 25 for casual sex, and 66 for regular partnerships. We assume 10% condom loss due to wastage. Appendix A A.92 Table A.23b. Condom Needs: 2010 Projections Condom Requirements to Meet Coverage Targets Country Commercial Sex Contacts (000s) Sex Between Men (000s) Casual Sex Contacts (000s) Risky Regular Partnerships (000s) Total Condoms Required (000s) Asia Afghanistan 2,057 272 13,631 14,591 30,551 Bangladesh 5,062 19,684 79,588 88,554 192,888 Bhutan 8,258 274 1,245 1,290 11,067 Cambodia 2,346 1,755 8,450 6,004 18,555 China 411,841 20,521 748,507 617,450 1,798,319 China, Hong Kong SAR - - - - - India 204,338 171,038 479,640 575,398 1,430,415 Indonesia 25,848 25,507 107,238 107,123 265,716 Iran 6,458 9,795 60,322 47,775 124,350 Korea, DPR 3,924 52 11,850 12,684 28,510 Korea, Rep. 9,771 2,642 24,904 26,657 63,973 Laos 336 701 3,363 3,189 7,590 Malaysia 5,654 1 11,462 14,373 31,490 Mongolia 484 367 1,536 1,644 4,031 Myanmar 4,281 1,596 26,154 27,995 60,026 Nepal 1,621 3,067 16,136 19,970 40,793 Pakistan 12,544 186 80,937 86,632 180,300 Papua New Guinea 7,110 685 3,993 4,274 16,063 Philippines 25,839 6,456 38,112 47,147 117,553 Singapore - - - - - Sri Lanka 5,547 9,369 22,441 21,836 59,193 Taiwan - - - - - Thailand 12,349 - 24,816 16,510 53,675 Viet Nam 2,919 9,890 39,609 49,670 102,088 Total 758,588 283,857 1,803,934 1,790,765 4,637,144 Latin America Argentina 7,763 4,841 52,085 51,667 116,356 Bolivia 1,782 60 10,817 7,210 19,869 Brazil 255,361 6,818 310,296 409,474 981,949 Chile 2,050 5,241 16,055 16,637 39,983 Colombia 12,400 923 55,447 39,699 108,469 Costa Rica 914 1,490 4,257 3,796 10,457 Cuba 2,411 1,501 31,564 20,198 55,675 Dominican Republic 6,001 2,588 14,207 10,841 33,637 Ecuador 2,263 2,217 16,545 15,646 36,670 El Salvador 709 2,902 6,939 7,029 17,579 Guatemala 2,634 2,317 14,399 13,961 33,310 Guyana 186 262 837 793 2,078 Haiti 4,880 1,794 20,410 14,931 42,015 Honduras 1,501 645 8,423 7,999 18,569 Jamaica 528 350 3,244 2,893 7,015 Mexico 24,078 1,694 113,103 109,235 248,110 Nicaragua 1,216 997 6,911 6,162 15,286 Panama 559 1,145 3,426 3,550 8,679 Paraguay 1,308 789 7,557 6,737 16,391 Peru 5,067 247 34,602 43,654 83,570 Puerto Rico 187 215 58 52 512 Trinidad and Tobago 216 514 1,006 1,043 2,779 Uruguay 463 480 5,014 3,305 9,260 Venezuela 11,351 6,960 33,349 29,734 81,393 Total 345,827 46,991 770,550 826,244 1,989,611 Middle East/North Africa Algeria 2,947 4,469 27,594 21,836 56,846 Egypt 6,345 928 56,698 44,904 108,875 Iraq 2,149 990 20,687 16,370 40,195 Jordan 623 2,286 4,910 3,885 11,704 Kuwait - - - - - Lebanon 338 696 3,311 2,620 6,964 Libya 782 1,188 4,825 3,818 10,613 Morocco 2,882 6,688 25,519 22,354 57,443 Oman 233 354 2,879 2,280 5,747 Saudi Arabia 1,843 2,794 22,291 17,639 44,567 Sudan 18,275 - 6,286 6,170 30,731 Syria 1,565 2,374 14,335 11,343 29,618 Tunisia 919 2,058 8,334 6,594 17,905 Turkey 6,310 9,570 58,540 46,364 120,783 United Arab Emirates - - - - - Yemen 1,631 2,474 15,583 12,265 31,953 Total 46,841 36,869 271,790 218,443 573,943 Appendix A A.93 Table A.23b. Condom Needs: 2010 Projections Condom Requirements to Meet Coverage Targets Country Commercial Sex Contacts (000s) Sex Between Men (000s) Casual Sex Contacts (000s) Risky Regular Partnerships (000s) Total Condoms Required (000s) Sub-Saharan Africa Angola 6,389 - 18,216 15,458 40,064 Benin 4,129 - 9,642 8,345 22,116 Botswana 993 - 6,262 3,933 11,188 Burkina Faso 3,052 - 21,244 18,002 42,298 Burundi 1,046 - 2,556 3,378 6,980 Cameroon 10,368 - 43,325 30,601 84,294 Central African Rep. 1,986 - 2,233 1,854 6,074 Chad 2,766 - 4,976 4,133 11,875 Congo 3,041 - 4,706 4,296 12,043 Congo, D.R. 22,001 - 62,128 61,620 145,749 Côte d'Ivoire 9,292 - 51,618 35,325 96,235 Eritrea 1,228 - 3,881 2,719 7,828 Ethiopia 16,376 - 53,330 33,314 103,019 Gabon 1,431 - 1,966 1,632 5,029 Gambia 647 - 1,967 1,735 4,348 Ghana 10,576 - 27,608 10,106 48,291 Guinea 3,134 - 20,071 13,998 37,203 Guinea-Bissau 665 - 2,926 2,430 6,021 Kenya 16,670 - 76,731 56,667 150,068 Lesotho 707 - 3,323 2,759 6,789 Liberia 2,013 - 4,801 3,987 10,801 Madagascar 7,530 - 20,613 23,213 51,356 Malawi 2,450 - 17,295 14,558 34,303 Mali 5,576 - 4,101 3,362 13,039 Mauritania 2,471 - 4,234 3,516 10,221 Mauritius 669 - 64 67 800 Mozambique 9,378 - 32,254 28,699 70,331 Namibia 785 - 6,212 4,445 11,441 Niger 3,566 - 8,211 5,083 16,860 Nigeria 75,190 - 200,365 119,703 395,258 Rwanda 797 - 4,724 4,537 10,058 Senegal 6,776 - 9,844 13,589 30,209 Sierra Leone 2,463 - 6,816 5,661 14,940 Somalia 3,933 - 5,535 4,597 14,066 South Africa 33,084 - 79,450 60,133 172,668 Swaziland 341 - 789 655 1,786 Tanzania 18,379 - 86,254 55,411 160,044 Togo 2,276 - 11,509 8,790 22,576 Uganda 5,386 - 38,702 35,221 79,309 Zambia 4,804 - 20,485 18,804 44,094 Zimbabwe 5,613 - 28,558 19,577 53,748 Total 309,981 - 1,009,521 745,914 2,065,416 Central Asia Republics Kazakhstan 1,386 2,102 23,272 20,119 46,880 Kyrgyzstan 447 678 4,839 5,743 11,706 Tajikistan 519 786 5,931 7,039 14,275 Turkmenistan 444 673 4,844 5,749 11,710 Uzbekistan 2,312 3,506 23,796 30,642 60,257 Total 5,108 7,747 62,682 69,292 144,828 Caucasus Armenia 1,037 521 3,107 3,239 7,903 Azerbaijan 1,490 1,130 7,894 9,369 19,883 Georgia 837 635 3,951 4,689 10,112 Total 3,364 2,285 14,952 17,297 37,898 Moldova, Russia, Ukraine Moldova 732 555 3,318 4,272 8,878 Russian Federation 23,951 18,163 111,244 132,025 285,383 Ukraine 3,798 5,760 22,774 29,326 61,657 Total 28,481 24,478 137,336 165,623 355,918 Grand Total 1,498,189 402,227 4,070,765 3,833,578 9,804,759 Notes: These figures represent estimates of the number of condoms required to protect against the transmission of HIV in the most risky situations. We assume that condom utilization will be highest in situations with the most risk. Dashes mean no data available. These projections assume that the percentage of acts covered by condom use increases from current levels in 2003 to target levels by 2010. Coverage targets vary by type of sex and severity of the epidemic. Epidemics in each country are classified by adult HIV prevalence as very low (<0.5%), low (>0.5% and <1.0%), medium (>1.0% and <5%) and high (>5%). Coverage targets by 2010 for very low, low, medium and high epidemics are: commercial sex and sex between men 60/70/80/80%, casual contacts 20/40/60/60%, and risky regular partnerships 10/10/20/30%. Risky regular partnerships are marriages and other long-term unions where at least one partner also has partners outside this relationship. The number of people with casual contacts and the number of risky regular partnerships are estimated from survey data (mostly DHS) on the percentage of men and women engaging in sex with non-marital, non- cohabiting partners. The number of sex workers and men who have sex with men is estimated from country studies, where available. Default assumptions, used when country-specific data are not available, are 4% of adult urban females (15-49) are sex workers and 2% of adult males (15-49) have sex with other men. Country specific data on coital frequency are used where available. Otherwise default values are applied. These are 200 contacts a year for sex workers, 45 for sex between men, 25 for casual sex, and 66 for regular partnerships. We assume 10% condom loss due to wastage. Appendix A A.94 Table A.24. Comparative Information on Youth Country Population Ages 15-24 (000), 2005 Ages 15-24 as % of Total Population 2005 % Currently Married* (women 15-19) % Sexually Active, (single women 15-19) % Using Contraception (sexually active single women 15-19) % Using Contraception (married women 15-19) % Giving Birth by Age 20-24 % of All Births in 2000-2005 Due to Youth 15-24 % Births Attended by Trained Personnel <20 years Asia Afghanistan 5,737 19.2 53 - - - - 39.9 - Bangladesh 28,735 20.3 47 - - 33.0 61.3 54.0 11.0 Bhutan 458 21.2 - - - - - 36.6 - Cambodia 3,404 24.2 12 - - - 28.7 41.3 36.2 China 217,349 16.5 4 - - 11.0 8.0 41.5 - China, Hong Kong SAR 915 13.0 2 - - - - 16.7 - India 211,254 19.1 34 - - 7.0 47.1 50.5 41.5 Indonesia 42,335 19.0 14 - - 47.3 27.5 44.9 58.2 Iran 17,629 25.4 22 - - 34.0 - 45.0 - Korea, DPR 3,605 16.0 - - - - - 13.9 - Korea, Rep. 6,952 14.5 1 - - - - 16.5 - Laos 1,204 20.3 - - - - - 43.1 - Malaysia 4,594 18.1 8 - - - - 25.8 - Mongolia 589 22.2 3 - - - 22.0 48.6 - Myanmar 9,934 19.7 16 - - 21.3 - 28.2 45.2° Nepal 5,440 20.1 40 - - 7.0 51.0 50.4 20.8 Pakistan 33,746 21.4 15 - - 4.8 31.0 38.9 37.8° Papua New Guinea 1,155 19.6 19 - - - - 38.5 - Philippines 16,836 20.3 8 0.3 - 18.0 21.0 35.9 51.3 Singapore 551 12.7 1 - - - - 11.8 - Sri Lanka 3,718 17.9 7 - - 20.0 16.0 35.6 81.6 Taiwan 3,364 14.5 1 - - - - - - Thailand 10,895 17.0 17 - - 43.0 24.0 45.6 61.1 Viet Nam 17,446 20.7 4 - - 22.8 15.9 32.3 74.0 Total/Mean 647,845 18.3 - - - - - - - Latin America Argentina 6,603 17.0 10 - - - - 43.5 - Bolivia 1,779 19.4 11 10.0** 63.5 31.0 36.0 42.7 66.9 Brazil 35,342 19.0 14 11.6 66.0 54.0 32.0 51.1 88.0 Chile 2,785 17.1 10 - - - - 41.6 - Colombia 8,349 18.3 14 4.9 81.3 51.0 36.0 47.7 85.8 Costa Rica 856 19.8 15 - - 53.0 - 50.0 95.0 Cuba 1,590 14.1 27 - 50.1 - - 47.0 - Dominican Republic 1,836 20.6 18 2.9 41.4 41.5 33.3 57.7 98.5 Ecuador 2,568 19.4 17 - 27.0 36.8 43.9 60.7 El Salvador 1,320 19.2 22 11.0** - 23.0 46.0 48.3 88.3 Guatemala 2,551 20.3 24 0.3 31.2 15.0 45.0 49.4 38.9 Guyana 145 19.3 12 - - - - 45.3 - Haiti 2,006 23.5 16 5.4 42.9 11.0 31.3 38.8 33.5 Honduras 1,513 21.0 23 - - 28.0 49.0 50.5 - Jamaica 503 19.0 7 - - 68.0 - 51.4 - Mexico 20,295 19.0 18 5.0** - 30.0 35.0 45.5 67.7 Nicaragua 1,216 22.2 22 0.7 53.4 55.2 47.9 55.2 85.0 Panama 579 17.9 19 - - 24.0 - 47.8 - Paraguay 1,259 20.4 16 5.6 23.0 37.0 37.0 44.2 63.3 Peru 5,400 19.3 10 2.2 71.7 46.0 30.1 40.1 57.4 Puerto Rico 620 15.7 15 - - - - 49.9 - Trinidad and Tobago 270 20.7 20 7.0** 25.0 42.0 29.7 45.2 98.9 Uruguay 517 14.9 11 - - - - 43.2 - Venezuela 5,180 19.4 18 - - - - 51.7 - Total/Mean 105,082 18.8 - - - - - - - Middle East/North Africa Algeria 7,424 22.6 9 - - - - 27.5 - Egypt 15,442 20.9 14 - - 25.4 23.3 43.4 67.5 Iraq 5,809 20.2 18 - - 4.0 - 34.2 - Jordan 1,139 20.0 6 - - 21.3 12.7 29.4 99.6 Kuwait 415 15.4 11 - - 8.0 54c 27.8 98f Lebanon 657 18.4 - - - - - 31.6 - Libya 1,318 22.5 - - - - - 18.7 - Morocco 6,479 20.6 10 - - 32.0 17.0 29.9 47.0 Oman 538 21.0 36 - - 3.0 61c 37.7 88f Saudi Arabia 4,548 18.5 15 - - - - 26.5 - Sudan 7,272 20.1 15 - - 4.0 26.0 33.0 68.1 Syria 4,369 22.9 - - - - - 34.3 - Tunisia 2,098 20.8 4 - - 11.0 13.0 22.3 80.9 Turkey 13,496 18.4 13 - - 34.0 25.0 44.7 83.3 United Arab Emirates 783 17.4 17 - - - - 37.6 - Yemen 4,497 21.4 26 - - 9.0 45.0 42.4 50.0 Total/Mean 76,283 20.3 - - - - - - - Appendix A A.95 Table A.24. Comparative Information on Youth Country Population Ages 15-24 (000), 2005 Ages 15-24 as % of Total Population 2005 % Currently Married* (women 15-19) % Sexually Active, (single women 15-19) % Using Contraception (sexually active single women 15-19) % Using Contraception (married women 15-19) % Giving Birth by Age 20-24 % of All Births in 2000-2005 Due to Youth 15-24 % Births Attended by Trained Personnel <20 years Sub-Saharan Africa Angola 3,216 20.2 - - - - - 52.6 - Benin 1,733 20.5 23 9.0 32.8 9.0 45.0 46.1 73.0 Botswana 431 24.4 6 26.0 35.2 17.0 55.0 48.3 85.6 Burkina Faso 2,722 20.6 34 21.3 42.5 7.8 62.0 45.6 35.1 Burundi 1,703 22.6 6 3.0** 27.8 4.0 27.0 36.7 37.5 Cameroon 3,501 21.5 34 36.7 72.6 15.0 54.0 49.0 58.3 Central African Republic 850 21.0 39 26.4 25.2 13.0 61.0 50.5 50.5 Chad 1,905 19.5 47 10.8 14.2 3.0 71.0 49.6 17.4 Congo 791 19.8 16 - - - - 44.8 - Congo, D.R. 11,482 20.0 24 - - 3.0 - 54.2 - Côte d'Ivoire 3,983 21.9 24 45.8 54.1 11.0 55.7 50.1 50.8 Eritrea 906 20.6 29 0.3 - 2.4 42.4 43.8 30.0 Ethiopia 15,643 20.2 23 - 45.7 - 43.6 40.1 6.6 Gabon 285 20.6 18 - 64.5 - 58.4 51.0 89.1 Gambia 287 18.9 53 - - - - 45.0 - Ghana 4,727 21.4 13 15.8 45.0 8.4 40.6 41.3 48.4 Guinea 1,793 19.1 44 - 42.4 3.0 66.2 48.0 40.3 Guinea-Bissau 299 18.8 - - - - - 47.3 - Kenya 7,847 22.9 18 22.9 49.4 16.4 45.4 49.3 47.0 Lesotho 461 25.7 17 - - - - 43.9 - Liberia 663 20.2 32 41.0 12.4 2.0 64.0 50.9 61.7 Madagascar 3,627 19.5 28 27.0 18.0 6.0 57.0 45.7 44.8 Malawi 2,553 19.8 33 - 17.8 11.0 61.7 50.0 57.6 Mali 2,747 20.3 46 6.9 23.8 5.0 67.3 49.7 45.9 Mauritania 587 19.1 24 - - - 34.7 37.2 52.8 Mauritius 198 15.9 11 - - 46.0 - 40.6 - Mozambique 4,015 20.3 45 27.8 7.0 1.0 65.0 39.0 46.5 Namibia 428 21.1 5 16.4 49.9 45.2 39.5 37.7 78.4 Niger 2,701 19.4 60 2.3 1.8 6.0 70.0 49.9 17.1 Nigeria 27,316 20.8 32 16.8 40.0 4.3 45.7 45.6 26.1 Rwanda 2,151 23.8 7 7.0** 27.6 11.0 30.9 38.2 36.9 Senegal 2,495 21.4 28 9.0** 34.5 6.0 43.0 42.3 44.7 Sierra Leone 1,049 19.0 58 - - - - 51.4 - Somalia 1,557 18.9 - - - - - 50.2 - South Africa 9,624 20.3 5 36.6 67.9 66.0 40.1 43.9 90.2 Swaziland 271 26.2 - - - - - 41.7 - Tanzania 8,236 21.5 25 11.9 27.9 7.0 56.2 49.4 49.8 Togo 1,272 20.7 19 42.9 56.2 15.0 38.0 40.7 56.0 Uganda 5,865 20.4 29 3.6 51.6 10.0 70.0 52.6 48.7 Zambia 2,565 22.0 24 9.5 16.0 17.0 60.9 52.0 46.1 Zimbabwe 3,286 25.3 22 14.0** 37.0 - 47.6 55.2 79.9 Total/Mean 147,772 20.8 - - - - - - - Central Asia Republics Kazakhstan 2,915 19.7 8 - 60.3 39.0 22.1 53.6 99.0 Kyrgyzstan 1,098 20.9 12 0.4 - 29.0 37.0 47.7 97.6 Tajikistan 1,467 22.5 14 - - - - 39.5 - Turkmenistan 1,041 21.5 6 - - - 14.5 33.7 97.4 Uzbekistan 5,768 21.7 7 - - 26.8 23.3 59.7 99.0 Total/Mean 12,288 21.2 - - - - - - - Caucasus Armenia 601 19.9 9 - - - 25.5 61.5 95.6 Azerbaijan 1,718 20.4 9 - - - - 48.3 - Georgia 740 16.5 17 - - - - 51.6 - Total/Mean 3,059 19.2 - - - - - - - Moldova, Russia, Ukraine Moldova 801 19.0 14 - 66.0 78.0 - 56.3 - Russian Federation 24,303 17.0 13 - - - - 53.8 - Ukraine 7,331 15.8 15 - - - - 57.6 - Total/Mean 32,435 16.7 - - - - - - - Overall Total 1,024,764 18.8 - - - - - - - * May include formal and/or informal unions ** Data are based on single teens who have ever had intercourse rather than those reporting intercourse in the last four weeks z: number rounds to zero °: indicates that data include all participants 15-19 years Dash means no data available. Appendix A A.96 Table A.25. Demographic Dividend: Percent of the Population Aged 15-59, from 1950 through 2000 Country 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Asia Afghanistan 52.8 52.8 52.6 52.2 51.8 51.6 51.5 51.4 51.4 51.5 51.8 Bangladesh 56.2 54.1 51.8 49.5 48.7 49.1 50.7 51.9 53.2 54.4 56.4 Bhutan 54.4 54.7 54.5 53.8 53.4 53.1 52.9 52.5 51.8 49.8 50.8 Cambodia 53.2 53.2 53.0 52.6 52.1 53.1 54.9 51.9 50.9 48.2 51.8 China 59.0 55.3 53.9 52.8 53.4 53.6 57.1 61.6 63.7 64.2 65.0 China, Hong Kong SAR 65.9 60.4 54.3 53.9 56.5 60.8 64.4 65.3 65.9 67.3 69.3 India 55.5 55.4 54.6 53.8 53.6 54.0 55.0 55.9 56.8 57.5 58.9 Indonesia 54.6 55.4 54.8 53.5 52.7 53.3 54.1 56.0 57.8 59.8 61.6 Iran 52.7 50.9 49.6 49.3 49.5 49.8 50.4 50.9 51.3 52.0 57.4 Korea, DPR 53.7 55.8 58.3 59.5 55.4 56.0 59.0 63.2 65.5 64.3 63.5 Korea, Rep. 52.9 55.1 52.8 51.7 52.5 56.4 60.0 63.2 66.5 67.6 68.2 Laos 53.5 54.0 53.9 53.4 53.3 53.3 53.2 50.4 50.1 50.8 51.6 Malaysia 51.8 51.5 49.4 48.8 49.9 52.3 55.0 55.7 57.7 58.1 59.3 Mongolia 52.6 52.2 51.9 51.6 51.5 51.5 52.0 52.8 52.5 55.3 59.2 Myanmar 56.7 54.6 53.3 52.8 52.8 52.7 52.9 54.1 56.1 58.2 60.1 Nepal 55.1 55.2 55.3 54.9 54.1 53.6 53.6 53.5 53.2 53.0 53.1 Pakistan 53.8 53.7 53.1 52.6 52.5 52.5 52.8 52.9 52.5 51.7 52.5 Papua New Guinea 54.6 54.2 53.3 52.6 52.7 52.6 52.6 53.0 53.9 54.2 55.7 Philippines 50.9 49.9 49.3 49.1 49.8 50.8 52.0 53.0 54.2 55.4 56.9 Singapore 55.8 55.2 53.0 51.6 55.5 60.5 65.8 67.8 70.1 68.4 67.6 Sri Lanka 52.6 52.5 51.9 52.4 54.1 56.7 58.3 58.7 59.8 61.8 64.4 Taiwan - - - - - - - - - - - Thailand 52.8 52.6 50.8 49.7 50.3 52.4 55.6 59.0 61.9 64.2 65.2 Viet Nam 61.2 57.8 53.2 48.9 48.4 49.4 50.9 52.5 53.9 55.6 59.2 Latin America Argentina 62.4 61.4 60.4 60.0 59.9 59.4 57.6 56.6 56.5 57.9 59.0 Bolivia 53.0 52.6 51.8 51.6 51.5 51.4 52.0 52.2 52.9 53.5 54.2 Brazil 53.6 52.9 51.4 50.9 51.9 53.7 55.7 57.1 58.6 61.1 63.4 Chile 56.4 54.6 53.3 52.5 53.0 55.3 58.3 60.3 60.9 61.0 61.4 Colombia 52.4 50.4 48.7 48.1 48.9 51.0 53.6 56.1 57.7 59.0 60.3 Costa Rica 51.0 49.4 47.7 47.3 49.0 52.6 55.6 57.2 57.2 58.6 60.2 Cuba 56.9 57.1 57.8 55.4 53.7 52.8 57.3 62.3 65.2 65.3 65.1 Dominican Republic 50.3 49.5 48.5 47.8 48.0 49.9 52.9 55.4 56.2 57.6 59.9 Ecuador 52.4 50.8 49.6 48.7 49.3 50.1 51.3 52.9 54.9 57.1 59.2 El Salvador 52.2 51.1 49.6 49.1 49.1 49.7 49.9 50.6 52.8 55.7 57.2 Guatemala 51.6 50.6 49.6 49.1 49.8 49.9 49.5 48.9 49.0 49.7 51.1 Guyana 52.3 49.0 46.4 47.5 47.1 50.4 53.3 54.8 56.6 59.7 62.5 Haiti 55.0 53.8 52.8 51.9 51.8 51.9 51.6 50.7 50.0 51.4 53.8 Honduras 51.0 50.6 49.6 48.4 47.8 47.9 48.6 49.4 50.3 51.4 53.1 Jamaica 58.2 56.7 51.7 48.5 44.6 46.3 50.5 53.9 54.8 56.5 58.9 Mexico 50.9 49.4 48.1 47.4 47.4 47.9 49.5 52.1 55.6 58.2 59.9 Nicaragua 51.3 49.7 48.0 47.2 47.6 48.0 48.3 48.2 49.3 50.6 52.8 Panama 53.3 51.5 50.4 49.7 49.7 50.6 52.8 55.5 57.5 59.1 60.6 Paraguay 52.1 49.2 46.7 45.4 47.4 49.2 51.4 52.0 52.6 53.2 55.1 Peru 52.8 52.1 51.0 50.3 50.5 51.2 52.5 54.1 55.6 57.4 59.4 Puerto Rico 50.7 50.1 49.6 53.1 53.9 57.1 57.2 58.4 59.6 61.1 61.9 Trinidad and Tobago 53.5 51.6 51.1 51.7 51.2 54.3 57.7 58.3 57.8 60.7 65.4 Uruguay 60.3 60.7 60.3 59.7 59.2 58.2 58.4 57.7 57.6 58.0 58.1 Venezuela 53.1 51.1 50.1 49.2 49.6 51.8 54.3 55.5 56.1 57.6 59.4 Middle East/North Africa Algeria 53.1 52.3 50.4 48.4 45.4 46.3 47.7 50.3 52.4 55.6 59.1 Egypt 55.2 53.9 52.1 49.8 51.9 53.5 54.3 54.4 54.0 55.5 58.3 Iraq 49.9 49.9 49.8 49.6 49.4 49.3 49.7 50.4 51.3 52.5 53.8 Jordan 46.9 48.0 49.5 49.8 49.4 48.5 46.0 47.8 48.4 54.4 55.4 Kuwait 59.4 59.1 61.6 59.1 54.0 53.0 57.5 60.8 61.3 55.8 64.3 Lebanon 55.4 53.9 50.8 48.7 48.7 51.3 52.5 54.7 56.9 57.9 60.3 Libya 50.8 50.4 50.8 51.2 50.6 50.2 49.6 49.7 52.1 56.2 60.6 Morocco 51.0 51.0 50.8 48.8 46.2 47.6 50.6 52.5 54.2 56.8 59.0 Oman 52.7 52.7 52.1 51.6 51.3 51.3 51.3 51.1 49.8 50.3 51.7 Saudi Arabia 52.4 51.8 51.2 50.7 50.4 50.9 51.3 52.6 53.0 50.9 52.3 Sudan 50.9 51.5 51.8 51.9 51.2 50.8 51.0 51.7 52.9 53.7 54.4 Syria 51.7 50.8 49.8 44.9 44.9 46.2 46.6 47.3 47.7 50.5 54.4 Tunisia 53.1 52.3 50.4 48.1 47.6 50.4 52.5 54.4 55.8 57.7 61.9 Turkey 55.7 54.5 52.2 51.6 51.9 53.0 54.3 57.2 57.9 59.8 61.5 United Arab Emirates 52.1 51.4 50.9 57.8 61.0 68.4 69.4 69.7 67.8 67.6 68.9 Yemen 51.5 51.8 51.9 52.1 51.4 44.7 45.5 46.5 47.1 48.0 46.3 Appendix A A.97 Table A.25. Demographic Dividend: Percent of the Population Aged 15-59, from 2005 through 2050 Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Asia Afghanistan 51.9 51.9 52.3 53.2 54.5 55.8 57.0 58.3 59.9 61.8 Bangladesh 58.2 59.9 60.9 62.3 63.5 64.5 64.7 64.2 63.0 62.0 Bhutan 52.4 53.7 54.5 55.6 57.2 59.2 61.1 62.7 63.7 63.6 Cambodia 53.7 55.0 56.0 57.1 59.1 62.0 64.8 66.9 65.5 64.0 China 67.4 67.5 65.8 64.2 62.1 59.4 57.2 56.4 55.5 53.8 China, Hong Kong SAR 70.4 69.0 66.2 62.1 58.1 55.7 53.5 51.9 50.9 50.7 India 60.5 62.1 63.4 64.2 64.3 63.6 62.6 61.9 60.9 59.7 Indonesia 63.4 64.9 65.5 65.1 64.2 63.0 61.8 60.4 58.9 57.7 Iran 62.2 64.8 64.8 64.5 64.3 64.6 64.9 64.2 61.3 58.1 Korea, DPR 63.3 64.2 65.7 64.6 62.7 60.3 59.0 59.4 59.0 58.0 Korea, Rep. 67.7 67.4 66.1 63.1 59.9 56.7 53.5 51.6 50.4 50.4 Laos 53.9 55.6 57.1 58.4 60.3 62.6 64.5 65.3 64.7 63.4 Malaysia 60.4 62.4 63.4 63.5 63.0 62.3 61.5 61.0 60.2 59.4 Mongolia 64.1 67.0 67.5 66.7 65.3 64.6 63.5 61.8 59.8 57.2 Myanmar 61.9 64.0 65.4 65.7 64.9 63.6 62.4 61.3 60.1 58.7 Nepal 53.7 54.9 56.4 58.0 59.6 61.4 63.2 64.5 64.6 64.0 Pakistan 53.4 54.4 55.3 56.6 58.3 60.5 62.8 64.6 65.1 64.4 Papua New Guinea 56.2 58.0 59.0 59.7 60.4 61.4 62.3 63.4 64.2 64.6 Philippines 58.7 60.8 62.6 64.2 64.7 64.1 63.0 62.2 61.3 60.1 Singapore 68.0 68.2 66.0 61.2 55.8 51.6 49.9 50.4 51.2 51.1 Sri Lanka 65.3 65.2 64.2 63.2 62.0 60.8 59.7 58.0 56.1 55.1 Taiwan - - - - - - - - - - Thailand 65.8 66.0 66.0 65.2 63.3 61.0 59.1 57.5 56.5 55.8 Viet Nam 63.4 66.5 66.2 65.0 63.5 62.6 61.9 60.6 58.8 56.6 Latin America Argentina 59.7 60.2 60.5 60.9 61.1 60.9 60.2 58.8 57.8 56.9 Bolivia 55.5 57.2 59.0 60.5 61.9 62.9 63.5 63.5 63.0 61.8 Brazil 64.8 65.1 64.5 63.7 62.5 61.5 60.4 58.9 57.5 56.5 Chile 62.1 62.6 62.3 61.1 59.6 58.7 58.2 57.9 57.6 56.7 Colombia 61.5 62.7 63.0 62.8 62.0 61.1 60.6 59.9 59.1 58.2 Costa Rica 61.8 62.3 62.2 61.8 61.1 60.6 60.4 59.7 58.7 57.5 Cuba 65.8 65.3 64.1 62.8 58.9 55.0 52.0 51.6 51.6 50.6 Dominican Republic 61.5 62.1 62.2 62.2 61.9 61.6 61.1 60.5 59.3 58.4 Ecuador 61.0 62.6 63.4 63.9 63.8 63.1 62.0 60.6 59.3 58.1 El Salvador 58.5 60.0 61.7 63.0 63.7 63.7 62.6 61.0 59.8 58.8 Guatemala 52.8 54.8 56.9 59.1 61.1 62.7 63.8 64.2 63.8 62.9 Guyana 63.4 63.9 64.5 64.1 62.6 60.2 57.3 54.7 52.5 51.8 Haiti 56.6 57.6 58.6 59.9 61.3 62.7 63.8 63.9 63.1 61.5 Honduras 55.3 57.9 60.0 61.7 62.9 63.7 64.2 64.0 63.0 61.7 Jamaica 60.9 62.7 63.6 63.4 62.6 61.6 60.6 59.5 58.0 56.7 Mexico 61.5 62.9 63.7 63.8 63.3 62.2 60.3 58.7 57.4 56.3 Nicaragua 54.5 56.8 59.0 61.0 62.5 63.6 64.2 64.0 63.0 61.9 Panama 62.1 63.1 63.6 63.3 62.3 61.0 59.6 58.6 57.6 56.5 Paraguay 57.0 58.5 58.9 59.4 60.1 60.9 61.8 62.7 62.6 61.9 Peru 61.3 62.8 63.6 64.0 63.8 63.1 62.0 60.5 59.1 57.8 Puerto Rico 61.8 61.8 61.4 60.8 60.2 59.4 58.1 56.6 55.7 55.1 Trinidad and Tobago 68.3 68.3 66.2 63.6 61.2 60.2 58.9 56.7 52.9 50.3 Uruguay 58.4 59.0 59.5 59.5 59.1 58.7 57.8 56.8 56.4 55.9 Venezuela 61.0 62.0 62.5 62.7 62.5 62.1 61.7 60.6 59.6 58.4 Middle East/North Africa Algeria 62.1 64.1 65.4 66.0 65.3 64.1 62.9 61.3 59.6 58.1 Egypt 61.5 63.4 64.5 64.7 64.4 63.8 63.5 62.7 61.1 59.1 Iraq 55.3 56.0 57.4 59.2 61.3 63.4 64.8 65.1 64.0 62.4 Jordan 55.7 56.2 58.3 60.5 62.2 62.9 63.3 63.3 62.8 61.9 Kuwait 69.5 67.3 62.9 60.8 61.4 64.1 64.9 62.3 58.2 54.7 Lebanon 63.4 65.9 66.4 66.3 65.2 63.1 61.2 60.0 58.7 57.1 Libya 61.5 60.6 61.7 64.1 66.0 65.6 63.7 61.8 59.6 58.7 Morocco 61.1 62.6 63.9 64.8 65.0 64.2 62.7 61.4 60.3 59.3 Oman 53.1 53.1 52.3 53.0 54.6 56.5 58.3 59.9 61.5 62.7 Saudi Arabia 53.6 54.1 54.2 55.1 57.0 59.3 61.4 62.7 64.0 64.0 Sudan 55.1 56.4 58.0 59.8 61.4 63.1 64.2 64.5 63.9 62.9 Syria 58.2 59.4 60.3 61.8 63.7 65.2 65.4 64.0 61.9 60.2 Tunisia 65.2 66.5 65.5 64.4 63.7 63.2 62.0 60.0 57.6 55.9 Turkey 62.0 63.9 64.9 64.6 63.3 62.2 60.8 59.2 57.8 57.5 United Arab Emirates 70.0 67.3 62.8 58.4 56.9 57.1 57.1 57.1 56.2 54.8 Yemen 45.5 46.4 48.0 49.1 49.6 50.3 51.5 53.3 55.5 57.7 Appendix A A.98 Table A.25. Demographic Dividend: Percent of the Population Aged 15-59, from 1950 through 2000 Country 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Sub-Saharan Africa Angola 53.9 53.8 53.4 52.9 52.3 51.5 50.5 49.3 48.3 47.7 47.3 Benin 50.2 49.3 49.6 48.7 48.0 50.4 48.9 48.0 47.0 47.6 49.4 Botswana 47.7 49.1 47.8 46.1 45.4 46.6 48.0 48.7 50.0 52.0 53.4 Burkina Faso 52.7 53.4 53.2 51.9 49.5 47.4 46.3 45.7 46.2 46.6 46.5 Burundi 53.9 52.2 50.9 49.8 50.1 49.0 49.8 50.9 50.1 48.8 48.1 Cameroon 54.6 54.5 54.2 53.3 52.2 50.9 50.0 49.3 49.3 49.9 51.3 Central African Rep. 56.3 55.7 54.7 53.6 53.4 53.0 52.0 51.5 50.3 50.7 50.9 Chad 55.5 55.2 54.4 53.1 52.2 51.0 50.1 49.5 49.2 48.9 48.6 Congo 54.2 53.8 53.1 52.0 51.0 50.1 49.5 49.5 49.4 49.3 48.7 Congo, D.R. 50.7 51.1 51.3 51.5 51.4 50.1 49.4 48.6 48.2 48.4 46.7 Côte d'Ivoire 52.9 52.8 51.9 50.4 50.3 50.1 50.2 49.6 49.3 50.8 52.9 Eritrea 49.6 50.6 51.2 51.6 51.2 51.2 51.4 51.7 51.5 51.3 51.4 Ethiopia 51.1 51.3 51.5 51.3 51.1 50.9 51.0 51.2 51.0 50.7 50.1 Gabon 57.2 57.7 58.0 58.2 58.3 57.2 56.1 55.2 53.9 52.6 51.1 Gambia 55.3 55.1 55.1 54.4 53.3 53.1 52.6 52.1 53.4 54.2 54.6 Ghana 50.8 50.6 50.4 50.2 50.1 49.9 49.7 49.2 50.1 51.5 54.0 Guinea 53.5 52.4 51.3 50.5 50.5 50.7 50.3 49.8 49.8 50.7 51.5 Guinea-Bissau 56.9 56.5 55.9 54.6 54.1 53.1 52.8 52.3 51.7 51.3 50.9 Kenya 53.9 51.2 47.9 46.2 45.9 45.6 45.4 45.4 46.4 49.4 52.3 Lesotho 52.4 53.2 53.7 53.7 53.1 52.8 52.7 52.7 53.1 53.8 54.2 Liberia 53.5 53.5 53.2 52.6 51.2 50.5 50.2 49.5 44.0 43.5 52.8 Madagascar 53.5 52.4 51.2 50.0 50.2 50.4 50.4 50.3 50.3 50.5 50.5 Malawi 49.4 49.8 50.1 50.2 49.7 49.1 48.5 48.7 48.7 48.9 49.0 Mali 52.0 51.7 51.3 50.9 50.1 49.7 49.0 48.8 48.8 48.5 48.1 Mauritania 53.6 53.4 53.1 52.7 52.2 51.8 51.3 49.7 50.1 50.3 51.1 Mauritius 50.1 49.7 49.4 49.4 52.0 55.8 58.6 60.9 62.0 63.9 65.4 Mozambique 53.6 53.9 53.7 53.2 52.0 51.2 50.7 50.7 50.9 51.2 50.9 Namibia 53.0 53.4 53.2 53.0 52.1 50.8 48.7 48.4 51.1 51.0 50.6 Niger 52.0 50.9 49.4 48.2 48.1 47.7 47.1 46.6 46.6 46.8 46.9 Nigeria 53.2 52.2 51.3 50.3 50.3 50.2 50.1 49.3 49.0 49.4 50.2 Rwanda 50.2 50.9 50.8 50.3 48.8 47.8 47.3 47.5 48.8 49.6 51.5 Senegal 52.9 52.4 51.6 50.8 50.7 50.5 50.0 49.7 49.9 50.6 51.5 Sierra Leone 55.4 54.9 54.3 53.6 52.9 52.2 51.8 51.6 51.4 51.5 51.0 Somalia 54.1 52.6 50.9 49.8 49.6 49.1 48.6 48.1 47.9 48.4 48.1 South Africa 55.5 54.1 53.0 52.3 51.9 52.1 53.2 54.8 56.6 58.7 60.3 Swaziland 52.4 52.1 51.4 50.7 50.1 49.6 49.3 50.0 50.9 52.3 53.1 Tanzania 50.3 50.5 50.3 50.0 49.3 48.3 48.6 48.8 49.5 50.2 51.0 Togo 51.9 51.4 51.0 50.4 50.2 49.8 49.4 49.3 49.6 50.3 50.9 Uganda 50.8 49.7 49.6 49.5 49.0 48.5 48.0 48.0 47.8 47.4 47.0 Zambia 50.8 51.0 50.8 50.4 49.6 48.5 48.2 48.5 49.6 49.5 48.9 Zimbabwe 52.7 51.2 49.7 47.4 46.8 46.9 46.8 48.5 49.6 49.4 50.1 Central Asia Republics Kazakhstan 55.4 59.2 55.5 53.0 54.2 56.8 59.4 59.6 58.8 60.6 61.8 Kyrgyzstan 58.6 59.1 53.5 48.9 49.4 51.7 55.2 55.3 54.1 54.9 57.1 Tajikistan 58.7 58.9 52.8 46.7 45.9 47.9 50.9 51.5 50.6 51.3 53.8 Turkmenistan 57.6 57.8 52.7 48.2 47.8 49.8 52.7 53.6 53.3 54.1 55.9 Uzbekistan 59.2 59.0 52.6 46.7 46.1 48.9 52.4 53.1 52.6 53.7 56.7 Caucasus Armenia 54.4 57.6 52.9 50.1 52.5 57.3 61.9 61.8 59.6 59.9 63.1 Azerbaijan 56.5 59.2 52.8 47.7 47.8 52.1 58.3 60.0 58.8 58.1 60.5 Georgia 58.2 61.1 59.1 56.7 57.4 59.2 62.0 62.0 60.4 60.5 60.8 Moldova, Russia, Ukraine Moldova 60.7 61.7 59.2 56.5 58.2 60.3 62.4 61.0 59.3 60.3 63.2 Russian Federation 61.9 63.9 60.7 59.7 61.5 63.1 64.9 63.5 61.1 62.1 63.5 Ukraine 61.8 64.7 63.0 61.0 61.0 61.2 63.1 62.0 60.1 61.2 61.6 Appendix A A.99 Table A.25. Demographic Dividend: Percent of the Population Aged 15-59, from 2005 through 2050 Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Sub-Saharan Africa Angola 47.1 47.1 47.5 48.6 49.9 51.2 52.7 54.3 56.1 58.1 Benin 51.1 52.0 52.8 53.6 54.8 56.6 58.6 60.5 62.3 63.8 Botswana 54.3 56.0 57.7 59.3 61.3 63.8 65.7 66.0 64.9 63.5 Burkina Faso 47.2 47.7 48.6 49.9 51.5 53.0 54.5 56.0 57.6 59.5 Burundi 51.3 52.3 50.9 50.6 52.2 54.4 56.3 57.5 58.4 59.9 Cameroon 52.7 53.9 54.9 56.3 58.2 60.3 62.5 64.2 64.6 64.1 Central African Rep. 51.2 52.4 53.5 54.7 56.2 58.3 60.6 62.7 64.3 64.7 Chad 48.4 48.6 49.3 50.5 52.1 53.6 55.3 57.3 59.6 62.3 Congo 48.3 48.5 49.4 50.6 52.0 53.5 55.2 57.2 59.5 62.0 Congo, D.R. 46.6 47.0 47.8 49.0 50.7 52.5 54.6 56.9 59.4 62.1 Côte d'Ivoire 54.7 55.2 55.7 57.3 59.7 62.6 64.8 65.5 64.6 63.3 Eritrea 52.1 53.1 54.2 55.3 56.6 58.1 60.1 62.3 64.1 64.7 Ethiopia 50.0 50.1 50.7 51.8 53.1 54.4 56.0 57.6 59.3 60.9 Gabon 50.4 50.4 51.3 52.8 54.7 56.7 59.0 61.6 64.0 65.0 Gambia 54.9 55.7 56.8 57.9 59.0 60.4 62.3 64.0 64.9 64.5 Ghana 55.7 56.9 57.8 59.3 61.2 63.3 64.7 64.8 63.5 62.1 Guinea 52.1 52.6 53.6 54.6 56.1 57.5 59.2 60.8 62.6 64.3 Guinea-Bissau 50.6 50.7 51.1 52.3 53.7 55.3 57.1 59.3 61.8 64.0 Kenya 54.8 55.9 57.0 59.1 61.8 64.4 65.4 65.0 63.7 62.7 Lesotho 54.2 54.4 55.5 56.7 57.8 59.6 62.4 65.1 66.5 66.0 Liberia 50.8 46.0 46.2 49.9 52.8 53.8 54.2 55.1 56.9 59.8 Madagascar 51.0 52.0 53.1 54.2 55.4 56.8 58.4 60.3 62.3 63.9 Malawi 49.5 50.2 51.0 51.8 52.9 54.3 56.0 57.7 59.4 61.2 Mali 47.9 47.8 48.4 49.5 51.0 52.2 53.5 55.1 57.1 59.4 Mauritania 51.0 51.1 51.6 52.7 54.3 55.8 57.5 59.4 61.7 63.8 Mauritius 66.1 66.9 65.6 63.6 61.5 60.2 59.5 57.9 56.9 56.4 Mozambique 51.0 51.6 53.1 54.4 55.7 57.2 59.2 61.5 63.8 65.4 Namibia 51.7 53.8 55.5 56.7 58.1 60.2 62.8 64.9 65.4 64.2 Niger 46.6 46.6 47.1 48.2 49.5 50.6 51.7 53.1 54.7 56.6 Nigeria 51.1 52.3 53.5 55.1 57.1 59.5 62.1 64.3 65.1 64.6 Rwanda 52.3 52.4 53.1 54.4 56.2 57.9 59.4 60.8 62.3 63.8 Senegal 52.7 54.0 55.3 56.8 58.6 60.7 62.9 64.6 65.2 64.7 Sierra Leone 50.3 49.9 50.4 51.6 52.9 54.1 55.6 57.4 59.7 62.2 Somalia 47.7 47.3 47.9 49.0 50.2 51.3 52.7 54.3 56.1 58.0 South Africa 60.8 60.6 61.2 62.1 62.2 61.7 61.4 61.9 62.5 62.7 Swaziland 53.6 54.1 55.1 56.2 57.5 59.5 62.2 64.6 65.7 65.0 Tanzania 52.1 53.4 55.1 56.8 58.8 61.0 63.2 65.1 65.5 64.6 Togo 51.7 52.7 53.7 54.9 56.5 58.3 60.3 62.3 64.0 64.5 Uganda 46.6 46.6 47.3 48.7 50.3 51.9 53.4 55.1 57.1 59.5 Zambia 49.1 50.2 51.5 52.9 54.4 56.3 58.1 60.0 61.7 63.6 Zimbabwe 51.6 53.7 55.5 57.7 60.8 64.0 65.8 65.8 64.8 63.8 Central Asia Republics Kazakhstan 65.8 66.6 65.3 63.6 62.6 62.8 62.2 60.8 59.0 56.8 Kyrgyzstan 62.1 65.1 65.6 64.3 63.1 63.0 62.6 61.7 60.0 57.7 Tajikistan 59.8 64.0 65.8 65.2 64.1 64.2 64.1 63.5 61.8 59.0 Turkmenistan 59.6 62.6 64.4 65.1 64.9 64.2 63.4 62.7 61.7 60.0 Uzbekistan 62.1 65.7 66.2 64.9 63.9 63.9 63.5 62.3 60.3 57.8 Caucasus Armenia 69.0 71.8 70.2 66.4 63.4 62.0 60.4 57.6 53.1 48.3 Azerbaijan 66.2 70.7 70.5 67.5 64.2 62.3 61.3 59.7 56.6 52.8 Georgia 64.0 65.2 64.5 62.5 59.9 58.6 57.2 55.3 52.7 49.8 Moldova, Russia, Ukraine Moldova 67.5 69.0 67.2 64.8 63.2 63.0 62.0 59.7 56.1 52.2 Russian Federation 68.1 68.1 65.7 62.7 60.8 60.3 59.0 56.6 53.0 49.3 Ukraine 64.9 66.4 65.1 62.9 60.9 60.1 58.2 55.8 52.5 49.0 Appendix B B.1 TECHNICAL APPENDIX FOR PROJECTION METHODS AAAAAppendix Bppendix Bppendix Bppendix Bppendix B The following steps were followed in producing the projections for contracep- tive prevalence, method mix, users, commodities, and costs. 1. Numbers of women of reproductive age (15-49) were taken from the UN Population Division’s 2002 round of es- timates and projections. 2. Percents of women married/cohabit- ing were taken from recent national sur- veys and censuses. They were kept con- stant through time. 3. Numbers of married/cohabiting wom- en were the product of (1) and (2). 4. Total fertility rates (TFRs) were taken from the UN Population Division’s 2002 round of estimates and projections, us- ing the medium set of projections. 5. Percents of married/cohabiting wom- en using contraception (CPRs) were tak- en from the latest survey (if no survey the regional average was assigned to the country). Then the future CPRs were es- timated from the TFRs, based upon the close association between the two in 273 observations for 101 countries. 6. A CPR adjustment factor: since not all countries lie exactly on the regres- sion line for CPR versus TFR, an adjust- ment factor was used to retain the gap through time. This factor was simply the ratio of the CPR from the survey to the estimated CPR from the regression equa- tion. 7. The final CPR for each year was the estimated CPR from its association with the TFR, multiplied by the adjustment factor, insuring that each country main- tained its difference from the regression line over time. This meant that the rea- sons for the difference (variations in per- cent married, post-partum infecundabili- ty, sterility, etc.) continued to exert the same influence on the CPR-TFR rela- tionship as they did at the baseline. 8. Numbers of users of contraception among married women were calculated by multiplying the numbers of married women by the CPRs. 9. Unmarried users were added to total users by a ratio of prevalence between all women and married women, using survey information for 55 countries with surveys covering both groups. For other countries no allowance was made for un- married users. 10. Method mix was estimated from two sets of equations that described how the share of each method changed as a func- tion of the overall CPR level. These equa- tions were estimated from the same data set of 273 national surveys from 101 countries. Separate sets of equations (listed below) were estimated for Muslim and non-Muslim countries, since Mus- lim countries tend toward more IUD use and less sterilization use than do non- Muslim countries. The two patterns that result appear as figures in Chapter 3, showing how the average method mix is associated with the CPR. (One proviso is that the body of past surveys may un- derestimate future growth in the inject- able, since in some countries it has be- come more prominent in recent years.) 11. Exceptions to the above were made, to keep the survey mix constant through time for all countries having prevalence above 65%. At that high level of contra- ceptive use a country’s own method mix is much less likely to change in the fu- ture to match the overall model. In addi- tion, the mix was kept constant for the two large countries of India and Indone- sia, considering their unique patterns. 12. Commodities were calculated from users by CYP rules, and total costs were generated from the unit cost for each contraceptive. The CYP rules are: CYP Conversion Rules Method CYP Factor Pills 15 per year Injectable 4 per year Condoms 120 per year VFT 120 per year IUD Divide by 3.5 Implant Divide by 3.5 Female St. Divide by 9 Male St. Divide by 9 Unit costs were applied to the numbers of commodities according to the follow- ing (estimated with weights according to the approximate shares of the two ma- jor donors, UNFPA and USAID, at the different prices they normally pay. The cost for condoms for example is greater for USAID than for the UNFPA). Unit Costs for Methods U.S. Cents Pills 24.0 Injectable 96.5 Condoms 3.5 VFT 7.2 IUD 57.6 U.S. Dollars Female St. 9.09 Male St. 4.95 After all costs were calculated, for each method and each region, they were en- larged by 10%, to allow for transporta- tion from the source to the port of entry. Equations for Calculating the Method Mix by Country and Year The method mix is projected as a func- tion of total prevalence, using the body of past surveys to determine how the share of each method depends upon the level of total prevalence. The two sets of equations below apply first to most coun- tries (non-Muslim) and second to Muslim countries, where on average the IUD is used more in preference to sterilization. METHODOLOGY FOR PROJECTING FAMILY PLANNING USERS BY YEAR AND METHOD B.2 Appendix B For example, in the first row in the ta- ble, the value of pill prevalence for each value of total prevalence is the sum of (a) total prevalence times 0.4898, plus (b) total prevalence squared times -0.0035, plus (c) the con- stant -2.3692. For example if total prev- alence is 40%, pill prevalence is the sum of (40 x 0.4398) + (40 x 40 x 0.0035) - 2.3692, or 20.8%. By applying this equation to each level of total preva- lence the share due to the pill is ob- tained at all levels. The results for all methods are adjusted to make the total 100%. Total Prevalence Total Prevalence2 Constant Non-Muslim Pill 0.4398 (0.0035) (2.3692) IUD (0.0501) 0.0030 0.7150 Injection 0.1853 (0.0020) 0.0814 Vaginals 0.0089 (0.0000) (0.0136) Condom (0.1549) 0.0034 2.2576 Female Sterilization 0.3430 0.0001 (2.8227) Male Sterilization (0.0536) 0.0011 0.7910 Traditional 0.2815 (0.0021) 1.3606 Muslim Pill 0.6089 (0.0056) (3.0028) IUD 0.2804 0.0010 (2.5274) Injection 0.0588 0.0002 (0.2100) Vaginals 0.0092 (0.0000) 0.0723 Condom (0.0227) 0.0011 0.8991 Female Sterilization 0.0389 0.0010 0.8490 Male Sterilization 0.0065 (0.0001) 0.1292 Traditional 0.0200 0.0025 3.7906 Futures Group One Thomas Circle, NW, Suite 200 Washington, DC 20005, USA 80 Glastonbury Blvd. Glastonbury, CT, 06033, USA ISBN 1-59560-002-7 A Constella Company

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