The Impact of Family Planning Programs on Unmet Need and Demand for Contraception John Bongaarts
Much of the existing literature on the demographic impact of family planning programs focuses on their role in increasing contraceptive use, which, in turn, accelerates fertility decline. What is not clear, however, is whether this effect operates solely through a reduction in unmet need brought about by eliminating obstacles to use or whether and to what extent the programs also affect demand for contraception through messages concerning the benefits of family planning. This article aims to shed additional light on this issue by analyzing data drawn from recent Demographic and Health Surveys conducted in 63 developing countries. The first section reviews general levels and trends in unmet need, demand, and use over the course of the fertility transition. The second section presents different types of evidence of program effects, including results from a controlled experiment and from country case studies. The evidence indicates a program impact on both unmet need and demand. (Studies in Family Planning 2014; 45[2]: 247–262)
F
amily planning programs are now widely considered a key part of any comprehensive development strategy. The international consensus on this issue is reflected in the UN Millennium Development Goals, specifically the MDG5 target of providing universal access to reproductive health by 2015. The 2012 London Summit on Family Planning, organized by the UK government and the Bill and Melinda Gates Foundation, strengthened political commitments and raised new funds, thus reaffirming the role of family planning in the global development agenda. The existence of substantial unmet need for contraception and large numbers of unplanned pregnancies has provided the main rationale for investments in family planning programs by governments and donors (Singh and Darroch 2012). The impact of these family planning programs on fertility and contraceptive use has been discussed extensively in the literature but remains a somewhat unsettled issue (Bongaarts et al. 2012). On one side of the debate are those who accept “demand theories,” which are based on conventional demographic transition theory (Notestein 1945 and 1953; Bryant 2007). This view argues that fertility declines are driven by socioeconomic development. In traditional agricultural societies, fertility is high to offset high mortality. As a society modernizes, economic and social changes increase the costs of raising children (e.g., cost for education) and reduces John Bongaarts is Vice President and Distinguished Scholar, Population Council, One Dag Hammarskjold Plaza, New York, NY 10017. Email: [email protected]. ©2014 The Population Council, Inc.
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their economic value (e.g., for labor and old-age security), resulting in a decline in desired family size and a rise in the demand for, and adoption of, birth control. Family planning programs are often seen as having only a marginal impact (Pritchett 1994). A key assumption of demand theories is that the cost of contraception is minimal and has little or no practical consequence. In the late 1960s and early 1970s, this assumption was questioned by evidence from fertility surveys conducted throughout the developing world. In particular, many women were not practicing contraception even though they did not want to become pregnant (Freedman and Berelson 1976). Later surveys confirmed this finding (Westoff and Ochoa 1991; Westoff and Bankole 1995). In addition, the substantial levels of induced abortion in developed and developing countries demonstrated that unintended pregnancies were common (Rochat et al. 1980; Tietze 1981; Singh et al. 2009). These findings led to an influential revision of the economic theory of fertility by Richard Easterlin (Easterlin 1975 and 1978; Easterlin and Crimmins 1985). Easterlin’s framework for the determinants of fertility added two key elements to demand theories. First, it acknowledged the role of biology in childbearing outcomes. Specifically, without efforts to control conception, women who are sexually active will bear large numbers of children. To avoid having unplanned births, couples must practice effective birth control. Second, Easterlin recognized that the cost of birth control could be substantial, thus discouraging potential users and leading to unplanned pregnancies. Easterlin’s theory provided the theoretical underpinnings for investments in family planning programs. The objective of these programs is to allow women to determine freely whether and when to have children by removing obstacles to contraceptive use. Potential obstacles include the substantial costs of contraceptive commodities (e.g., pills, condoms, IUDs), transportation to obtain contraceptives, and reimbursement of service providers. In addition, significant noneconomic costs can impede adoption of family planning, such as health concerns, social disapproval, spousal resistance, and unnecessary medical barriers. Another challenge to demand theories came in the 1970s and 80s when empirical tests of these theories were conducted using historical and contemporary data. The massive study of province-level data from European countries for the period 1870–1960 (Knodel and van de Walle 1979; Coale and Watkins 1986; Watkins 1986 and 1987) and analyses of fertility surveys in the 1970s and early 1980s (Cleland 1985; Cleland and Wilson 1987) failed to find the tight link between development indicators and fertility expected from conventional theories. Although most traditional societies do have high fertility when compared with modern industrial societies, the transition itself is poorly predicted by customary quantitative measures of development (Bongaarts and Watkins 1996). These unexpected findings led to a revision in the thinking about the fertility transition and to the introduction of theories of the “diffusion” of innovations in reproductive behavior (Cleland and Wilson 1987; Cleland 2001; Casterline 2001a and 2001b). Diffusion refers to the process by which new technologies, ideas, behaviors, and attitudes spread within a population through a variety of mechanisms (e.g., social networks, opinion leaders, media) independent of socioeconomic conditions. These past studies led to two hypotheses concerning the potential role of family planning programs. First, these programs can reduce unmet need by reducing obstacles to use and by providing access to contraceptive methods and services. This rationale is the most widely acStudies in Family Planning 45(2)
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cepted for these programs. Second, programs may produce a rise in the demand for contraception by implementing information, education, and communication (IEC) campaigns that spread ideas concerning the benefits of contraception and smaller families. This effect is suggested by diffusion theory and is supposed to operate in addition to the influence of socioeconomic variables on demand for children. Much of the existing literature on the demographic impact of family planning programs focuses on their role in increasing contraceptive use and accelerating fertility transitions. For example, an overview by Bongaarts and colleagues (2012) concludes that a high-quality family planning program that has a substantial IEC component can reduce the total fertility rate by approximately 1.5 births per woman. What is not clear, however, is whether this effect operates solely through a reduction in unmet need or whether and to what extent the programs also affect demand for contraception. This article aims to provide greater clarity on this issue. After a brief overview of levels and trends in unmet need, different types of evidence of this impact will be presented.
UNMET NEED AND SATISFACTION OF DEMAND FOR CONTRACEPTION Estimates of demand for contraception and the degree to which it is satisfied can be derived from responses to questions concerning fertility preferences and the use of contraceptives in Demographic and Health Surveys (DHSs) (Westoff and Ochoa 1991; Westoff and Bankole 1995; Westoff 2006 and 2012; Bradley et al. 2012). Married women who are fecund and do not wish to become pregnant soon are assumed to have a demand for contraception.1 Some of these women are practicing contraception and some are not. The former are current users whose need for a method of contraception is considered to have been met (even though they may not be satisfied with their current method); the latter are considered to have an unmet need for contraception. These definitions can be expressed as a formula: demand = current use + unmet need. Estimates for these measures are available from DHSs conducted most recently in 37 countries in sub-Saharan Africa, 15 countries in Asia/Middle East/North Africa, and 11 countries in Latin America.2 Regional averages (unweighted) of these country-specific estimates are provided in Figure 1. Sub-Saharan Africa has the lowest demand (54 percent) and the lowest contraceptive use (28 percent) while having the highest unmet need (26 percent). In the other regions, on average more than 70 percent of women want to avoid pregnancy, and three-quarters of them are practicing some method of contraception. The average level of unmet need is 20 percent in Asian/Middle Eastern/North African countries and 19 percent in Latin America. Among the developing countries examined here, the progress made through the fertility transition differs widely. At one end of the spectrum are early transitional countries—mostly in West and Central Africa—which are characterized by low education and income levels and 1 Estimates of unmet need include women who are pregnant or who have recently given birth if their pregnancy or most recent birth was unintended. 2 DHSs conducted in Europe or in countries formerly of the Soviet Union are not included in this analysis. For the full list of countries included in this analysis, see Appendix Table A1.
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FIGURE 1 Average of country percentages of married women of reproductive age having demand for and using contraceptives, by region Percent of married women of reproductive age
90 80 70 60 50 40 30 20 10 0
Demand
78 70
19a
20
54
60
26
50
Use Unmet need
28 Sub-Saharan Africa
Asia/ Middle East/ North Africa
Latin America
a Sum of unmet need plus use appears greater than demand because of rounding. NOTE: Difference between each pair of bars is the unmet need. SOURCES: 63 Demographic and Health Surveys.
high birth rates. At the other end of the spectrum are late transitional countries, such as Brazil, Colombia, and Turkey, having relatively high education and income levels and low fertility. It is plausible to assume that unmet need and demand vary by the stage of the transition. To examine this hypothesis, Figures 2–6 plot various indicators by the level of fertility as measured by the total fertility rate (TFR) for all DHSs examined. Figure 2 plots demand and use by TFR. Each country is represented by two markers: one for demand (black circles) and the other for current use of any method (gray circles). The TFR ranges from 7.2 births per woman in Niger in 1998 (demand = 26 percent; use = 8 percent) to 1.9 births per woman in Vietnam in 2002 (demand = 85 percent; use = 79 percent). As expected, demand and use are both inversely related to fertility. The relationships are approximately linear, but the slope for the relationship between TFR and contraceptive use is steeper than for the relationship between TFR and demand. As a result, the gap between demand and use (i.e., unmet need) declines as the TFR declines, as shown in Figure 3. High fertility countries FIGURE 2 Percentage of married women of reproductive age having demand for and using contraceptives, by TFR, 63 developing countries
Percent of married women of reproductive age
100 80
J J J JJ J JJ J JJ J J J J JJ JJ J JJ JJJ JJ J J JJJJ J J J J J J JJ J J J J J J J J J JJJ J J JJJ J J J J J J J J J
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Demand J JJ
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FIGURE 3 Percentage of married women of reproductive age having unmet need for contraception, by TFR, 63 developing countries
Percent having unmet need
100 80 60 40
J JJ J JJ J J
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J
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typically have levels of unmet need of approximately 30 percent, but by the end of the fertility transition this unmet need is much lower—usually less than 20 percent. Two additional indicators provide insight into the changing reproductive behavior at different points in the fertility transition. The first is the percent of demand that is satisfied (i.e., use ÷ demand), which is a direct measure of the extent to which women are able to achieve their reproductive preferences. As shown in Figure 4, this indicator differs sharply between high- and low-fertility countries. This finding is expected from the simultaneous decline in unmet need and the rise in demand as countries move through the fertility transition. Another useful indicator is the proportion of contraceptive users that relies on modern rather than traditional methods. One would expect countries having low fertility to generally have a wider choice of methods and to rely more on modern methods. This expectation FIGURE 4 Percentage of demand satisfied among married women of reproductive age having demand for contraceptives, by TFR, 63 developing countries
Percent of demand satisfied
100 80 60
J
J
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J J J J J J J J J
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FIGURE 5 Percentage of modern method users among married women of reproductive age who practice contraception, by TFR, 63 developing countries Percent of users using modern methods
100
J J J J
80
J JJ
J J JJJ
J J
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is more or less confirmed by the data in Figure 5, but the relationship between TFR and the percent using modern methods is weak. In sum, in countries in the early stages of the transition, unmet need is largest because use falls well short of demand. At lower levels of fertility, use and demand rise but use catches up with demand, and unmet need, therefore, tends to decline. As a result, the proportion of demand that is satisfied rises. Figures 2–5 present only cross-sectional evidence. Time series of these indicators in countries typically follow similar patterns over time as countries move through their transitions (data not shown). Some early-transition countries exhibit exceptions to this rule, with unmet need rising initially and demand rising faster than use. For example, in Uganda total unmet need rose from 29 percent to 41 percent between the 1995 and 2006 DHSs, a period during which use rose from 15 percent to 24 percent while demand increased from 44 percent to 64 percent. Such examples of countries in which unmet need, use, and demand all rise together are relatively rare.
IMPACT OF FAMILY PLANNING PROGRAMS The main hypotheses that will be tested below are that family planning programs reduce unmet need and increase use, demand, percent satisfied, and percent using modern methods. Unfortunately, the measurement of the effect of programs on a given indicator is not straightforward, because estimates of the size of the impact require the estimation of an unobservable quantity: the level of the indicator that would have been observed in a population in the absence of the family planning program. Subtracting the observed indicator from this hypothetical estimate yields the impact. Two alternative approaches that are available to obtain such estimates for populations are discussed below: controlled experiments and country case studies. Studies in Family Planning 45(2)
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Controlled Experiments The gold standard for evaluating interventions are controlled experiments, but few large-scale controlled experiments have been conducted to assess family planning programs because they are expensive and take a long time to complete. The largest and most influential quasi- experiment started in 1977 in Matlab, Bangladesh. At that time, Bangladesh was one of the poorest and most highly agricultural countries in the world, and skepticism regarding whether family planning would be accepted in such a traditional society was widespread. The experiment divided the Matlab district (population 173,000 in 1977) into experimental and control areas of approximately equal size. Individuals in the control area received the same minimal services as the rest of the country, whereas in the experimental area comprehensive high-quality family planning services were provided, aimed at reducing the costs (monetary, social, psychological, and health) of adopting contraception. The experimental area provided free services and supplies of a range of methods (condoms, injectables, IUDs, pills, and sterilization) together with home visits by well-educated female family planning workers. Outreach to husbands, village leaders, and religious leaders addressed potential social and familial objections from men (Cleland et al. 1994; Phillips et al. 1988). The impact of these intensive services on reproductive behavior was large and immediate. Within 18 months of the start of the program, the proportion of women practicing contraception in the experimental area rose from 5 percent to 33 percent (Cleland et al. 1994). In contrast, little change occurred in the control area or in the remainder of Bangladesh during the first few years. A survey in 1984 measured contraceptive prevalence at 39 percent in the intervention area and 17 percent in the control area (Koenig et al. 1987). In addition, by 1990 the intervention area had a much lower proportion of women of reproductive age practicing traditional methods: 6 percent, compared with 26 percent in the control area (Koenig et al. 1992). The rise in contraceptive prevalence and effectiveness of use in the experimental area led to a decline in the total fertility rate of approximately 1.5 births per woman below that in the control area (Cleland et al. 1994). This fertility difference was maintained from the beginning of the experiment through the 1980s, before narrowing slowly in the 1990s as services in the control area, and in all of Bangladesh, improved substantially. Although the experiment’s outcomes with regard to increasing contraceptive use, changing the method mix, and reducing fertility are well documented, the levels and trends in unmet need and demand for contraception have not been systematically documented. The only source of information regarding the topic is Koenig and colleagues’ 1984 survey, which included a question about women’s desire for more children. This is a proxy for the demand for limiting, but it is rather crude. Unfortunately, this survey lacks information regarding key variables needed to estimate unmet need and demand as defined by the DHS (Koenig et al. 1987). Figure 6 presents estimates from 1984 of contraceptive demand and use, unmet need for limiting births, and percent of limiters who are satisfied. No data regarding spacing are available. The results are largely as expected: in the treatment area, contraceptive use and percent satisfied are higher and unmet need is lower than in the comparison area. (Note again that unmet need is not measured in the standard DHS form and is only for limiting.) The only surprise is that the demand for limiting (i.e., percent of women who want no more children) is slightly lower in the intervention than in the control area. This finding is probably explained in part by the more extensive use of contraceptives for spacing births in June 2014
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FIGURE 6 Indicators for treatment and comparison areas, Matlab, Bangladesh, 1984 90 Treatment
70 60
55
60
50
45
40 28
27
30 20
15
Percent having demand for limiting
Percent of married women of reproductive age
80
Comparison 49
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Want no more children
Practicing contraception to limit births
Unmet need for limiting
Demand satisfied
SOURCE: Koenig et al. 1987.
the intervention area. With wider spacing, women in the intervention area reach their desired family size at a later age than women in the control area; thus, fewer women want no more children in the latter than in the former. In addition, the intervention focused on providing services rather than changing demand, and experimental and control areas saw similar declines in fertility preferences in the years before 1984 (Koenig et al. 1987; Freedman 1997).
Country Case Studies When two countries have similar social, economic, and cultural characteristics but one of these countries has implemented a family planning program and the other has not, beforeand-after comparisons are akin to a “natural experiment.” We can observe the difference in unmet need, contraceptive use, and demand for family planning between the two countries and attribute any differences largely to the existence of the family planning program in the “experimental” country. Four examples of such country pairs will be examined. Overviews will be presented first, followed by survey measures contrasting contraceptive access scores in the two countries of each pair. Bangladesh and Pakistan
These two countries were united as one nation from 1947 until Bangladesh was established after a civil war in 1971. As a result, these two populations still have much in common, and levels of development are broadly similar. Pakistan’s program has been weak, mostly as a result of lack of government commitment. In contrast, Bangladesh has implemented one of the world’s most effective voluntary family planning programs, using the experience and lessons from the Matlab experiment (Cleland et al. 1994 and 2006). A unique feature of the program is its staff of literate female workers who advise women and distribute supplies to their doorstep, thus overcoming the barriers posed by purdah (the practice of seclusion from public exposure among Muslim women) (Simmons et al. 1988). In addition, the government implemented a nationwide IEC program. For example, Radio Bangladesh, which is heard throughout the country, has devoted more than an hour each day to population and family planning issues since the 1980s (Khuda et al. 2001). Studies in Family Planning 45(2)
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Indonesia and the Philippines
Indonesia was one of the first Asian countries to implement a family planning program, and the program has had strong support from political leaders (Hull 2007). In contrast, the program in the Philippines has been weaker, in large part because of opposition by the Catholic Church (Herrin 2007). Kenya and Uganda
These neighboring countries in East Africa share a colonial history that has left an imprint on numerous institutions. Levels of development are broadly similar for the two countries. Until very recently, Uganda’s government has made little investment in family planning (a decision partly based on the fear of high AIDS mortality when the epidemic spread in the 1980s). In contrast, in the 1960s Kenya was one of the first countries in Africa to establish a family planning program, and it had substantial funding and technical support from bilateral and multilateral donors. The program included large-scale community-based distribution, providing rural clients with access to low-cost contraceptive services, and implemented nationwide IEC campaigns. After the mid-1990s, however, Kenya’s family planning program lost its priority, and the commitment of the government and international donors declined substantially. This neglect is one of the key reasons for the subsequent stalling of fertility near five births per woman (Blacker et al. 2005; Askew et al. 2009; Murunga et al. 2013). Rwanda and Burundi
These poor neighboring countries are among the most densely populated in Africa. Rwanda’s fertility was one of Africa’s highest in the twentieth century, but in the early 2000s the government renewed its lagging commitment to family planning in part to reduce rapid population growth. With strong support from international donors, access to contraceptive methods sharply increased throughout the country (Solo 2008; Murunga et al. 2013; Westoff 2013). Additionally, the president and other government officials spoke out about the need to reduce fertility, and a country-wide IEC program was implemented. In contrast, much less attention has been given to reproductive health in Burundi. For comparisons of reproductive measures in these countries to be useful, development levels must be similar and access to contraception must be different for the two countries in each pair. Table 1 examines these variables. The first column of Table 1 presents an index of access to modern methods from country respondents as estimated for 2009 by Ross and Smith (2011).3 This measure is available for seven of the eight countries examined here (Rwanda is missing). As expected, the countries that have weaker programs (Burundi, Pakistan, the Philippines, and Uganda) have relatively low access scores, whereas the scores for the countries having the stronger programs (Bangladesh, Indonesia, and Kenya) are substantially higher. 3 Ross and Smith (2011) collected data for 30 separate dimensions of family planning programs, including policies, services, evaluation, and access in 99 countries. These data were used to create a “family planning effort score” that incorporates all 30 dimensions. Six of the dimensions pertain to contraceptive access: access to condoms, pills, IUDs, injectables, female sterilization, and male sterilization. For the present study, I have created a “modern method access score,” which is the average of the scores of five of these six measures of access to modern contraceptive methods. Access to condoms was excluded from this average because condoms are distributed widely for HIV prevention. More detailed assessments of access and the service environment are available for a limited number of countries in which the DHS Program conducted Service Provision Assessment surveys (Wang et al. 2012).
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TABLE 1 Modern methods access score and human development index for four pairs of developing countries, 2009 Country pairs Bangladesh–Pakistan Indonesia–Philippines Kenya–Uganda Rwanda–Burundi Average (stronger–weaker)
Modern Human methods development access score index 59.6–37.0 0.502–0.508 56.3–24.1 0.611–0.643 43.5–39.2 0.505–0.445 na–34.1 0.417–0.340 53.1–33.4a 0.509–0.484
na = Not available. aExcludes Rwanda–Burundi pair. SOURCES: Ross and Smith 2011; UNDP 2013.
The average access score in the countries having stronger programs (53.1) exceeds that of the countries having weak programs (33.4) by nearly 20 points for the three pairs for which this comparison can be made. Given the above discussion of the situation in Burundi and Rwanda, it seems likely that if the access score had also been available for these two countries, the difference between them would be substantial. To assess development levels, the human development index (HDI) as estimated by the United Nations Development Programme is used (UNDP 2013). This index is obtained by combining indicators of life expectancy, educational attainment, and income into a composite index for countries. Estimates of the HDI in 2009 for the four country pairs are presented in Table 1. The HDIs of two pairs (Bangladesh–Pakistan and Indonesia–Philippines) are very similar, and the differences for the remaining two pairs are small. The average HDI of the stronger program countries is 0.509, compared with 0.484 for the weaker program countries. This difference is modest compared with the HDI range of 0.29 to 0.95 among all countries (not shown). FIGURE 7 Percentage of married women of reproductive age having unmet need for contraception, four pairs of developing countries
Percent having unmet need
40
38.0 Stronger program
35
31.0
30 25
22.0
20.8
20 15
Weaker program
25.6
25.2 16.8 13.1
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SOURCES: Most recent Demographic and Health Surveys.
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With these reassuring findings regarding the similarity of development and the difference in contraceptive access for countries in each pair, we can now proceed with an examination of differences in reproductive indicators. The expectation is that stronger program countries have lower unmet need, and have higher use, demand, percent satisfied, and percent using modern contraceptives, compared with the weak program country in each country pair. Figures 7–11 present these five indicators for all eight countries at the time of their most recent DHS survey (average year of survey is 2009). The results are clear: this hypothesis is confirmed in 20 out of the 20 comparisons (five indicators for four country pairs). FIGURE 8 Percentage of married women of reproductive age practicing contraception, four pairs of developing countries Stronger program
61.4
60
Percent practicing contraception
55.8
Weaker program
51.6
50.7
50
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40 29.6
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80 74.5
72.7
72.6
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Percent having contraceptive demand
FIGURE 9 Percentage of married women of reproductive age having demand for contraception, four pairs of developing countries
SOURCES: Most recent Demographic and Health Surveys.
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FIGURE 10 Percentage of demand satisfied among married women of reproductive age having demand for contraceptives, four pairs of developing countries
Percent of demand satisfied
90
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80
76.9
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FIGURE 11 Percentage of modern method users among married women of reproductive age who practice contraception, four pairs of developing countries Stronger program
93.5
90
85.1
80 70
87.4 80.8
86.6 75.5
73.3
67.1
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Percent of users using modern methods
100
SOURCES: Most recent Demographic and Health Surveys.
The findings from these country case studies suggest that a well-organized family planning program having a substantial IEC component can, on average: • • • • •
reduce unmet need by 10 percent (range 8.4–12.4) increase contraceptive use by 22 percent (range 19.7–29.7) increase demand by 12 percent (range 1.8–19.5) increase satisfaction of demand by 10 percent (range 12.7–29.0) increase use of modern methods by 14 percent (range 6.6–26.4).
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These calculations may slightly overestimate the program impact because the HDI is slightly higher in the stronger programs than in the weaker ones. In addition, these results are not derived from true controlled experiments, so ruling out unobserved confounding factors is not possible. Countries can, of course, differ from one another in characteristics that are not examined here (e.g., political systems, inequality, percent urban, and so forth). On the other hand, family planning services were not entirely absent in the weaker program populations examined above, so the differences do not estimate the full program impact.
CONCLUSION The recent growth in investments in family planning programs is to a large extent based on the existence of an unmet need for contraception and on the assumption that such investments reduce unmet need. The preceding analysis examined evidence concerning the impact of family planning programs on unmet need and related indicators of reproductive behavior. The findings from the Matlab experiment and from comparisons of country pairs having stronger and weaker programs confirm that programs reduce unmet need and increase use. In addition, the proportion of demand that is satisfied and the proportion of women using modern methods are increased. Although the limitations of the country case study approach preclude drawing definitive conclusions, family planning programs appear to have two distinct effects on reproductive behavior. First, by making modern contraceptives more widely available and by removing obstacles to use, more women who do not want to become pregnant practice contraception, thereby reducing unmet need. With a given level of demand, an increase in use produces a corresponding decline in unmet need. The evidence also shows, however, that programs can have a second effect by raising the demand for contraception.4 This effect is expected according to diffusion theory and may be attributed to program IEC messages concerning the benefits of family planning and the diffusion of ideas about them. These findings imply that the overall impact of family planning programs on unmet need can be small or even absent when a rise in use is accompanied by a rise in demand. The impact on unmet need is indeed smaller than on use in the country case studies summarized earlier (Figures 7–11). This confounding effect of changes in demand complicates efforts to assess program impact and should be taken into account in future analysis of trends in unmet need. As noted by Caldwell and colleagues (1992), policymakers in countries where demand is still low (e.g., in the poorest African countries) have often given programs low priority, on the assumption that they would be unsuccessful and their impact would be small. This view seems too pessimistic. The finding that family planning programs can potentially raise demand through the implementation of appropriate IEC campaigns is particularly important for such countries.
4 See Bongaarts 2011 for an analysis of the effect of family planning programs on desired family size.
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APPENDIX TABLE A1 List of 63 countries included in analysis, by region and DHS survey year Region
DHS survey year
Sub-Saharan Africa Benin 2006 Burkina Faso 2010 Burundi 2010 Cameroon 2011 Central African Republic 1994–95 Chad 2004 Comoros 1996 Congo (Brazzaville) 2005 Congo Democratic Republic 2007 Cote d’Ivoire 1998–99 Eritrea 2002 Ethiopia 2011 Gabon 2000 Ghana 2008 Guinea 2005 Kenya 2008–09 Lesotho 2009 Liberia 2007 Madagascar 2008–09 Malawi 2010 Mali 2006 Mauritania 2000–01 Mozambique 2003 Namibia 2006–07 Niger 2006 Nigeria 2008 Rwanda 2010 Sao Tome and Principe 2008–09 Senegal 2010–11 Sierra Leone 2008 South Africa 1998 Swaziland 2006–07 Tanzania 2010 Togo 1998 Uganda 2011 Zambia 2007 Zimbabwe 2010–11
Region
DHS survey year
Middle East Egypt 2008 Jordan 2009 Morocco 2003–04 Turkey 1998 Yemen 1997 Asia Bangladesh 2007 Cambodia 2010 India 2005–06 Indonesia 2007 Maldives 2009 Nepal 2011 Pakistan 2006–07 Philippines 2008 Timor–Leste 2009–10 Vietnam 2002 Latin America Bolivia 2008 Brazil 1996 Colombia 2010 Dominican Republic 2007 Guatemala 1998–99 Guyana 2009 Haiti 2005–06 Honduras 2005–06 Nicaragua 2001 Paraguay 1990 Peru 2007–08
REFERENCES Askew, Ian, Alex Ezeh, John Bongaarts, and John Townsend. 2009. “Kenya’s Fertility Transition: Trends, determinants and implications for policy and programmes.” Nairobi: Population Council. Blacker, John, Collins Opiyo, Momodou Jasseh, Andy Sloggett, and John Ssekamatte-Ssebuliba. 2005. “Fertility in Kenya and Uganda: A comparative study of trends and determinants,” Population Studies 59(3): 355–373. Bongaarts, John. 2011. “Can family planning programs reduce high desired family size in sub-Saharan Africa?” International Perspectives on Sexual and Reproductive Health 37(4): 209–216. Bongaarts, John, John Cleland, John Townsend, Jane Bertrand, and Monica Das Gupta. 2012. Family Planning Programs for the 21st Century: Rationale and Design. New York: Population Council. Bongaarts, John and Susan Cotts Watkins. 1996. “Social interactions and contemporary fertility transitions,” Population and Development Review 22(4): 639–682. Studies in Family Planning 45(2)
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Bradley, Sarah, Trevor N. Croft, Joy D. Fishel, and Charles F. Westoff. 2012. “Revising unmet need for family planning.” DHS Analytical Studies No. 25. Calverton, MD: ICF International. Bryant, John. 2007. “Theories of fertility decline and the evidence from development indicators,” Population and Development Review 33(1): 101–127. Caldwell, John C., I.O. Orubuloye, and Pat Caldwell. 1992. “Fertility decline in Africa: A new type of transition? Population and Development Review 18(2): 211–242. Casterline, John. 2001a. “Diffusion processes and fertility transition: Introduction,” in John B. Casterline (ed.), Diffusion Processes and Fertility Transition: Selected Perspectives. Committee on Population, Division of Behavioral and Social Sciences and Education, National Research Council. Washington, DC: National Academies Press, pp. 1–38. ——— (ed.). 2001b. Diffusion Processes and Fertility Transition: Selected Perspectives, Committee on Population, Division of Behavioral and Social Sciences and Education, National Research Council. Washington, DC: National Academies Press. Cleland, John. 1985. “Marital fertility decline in developing countries: Theories and evidence,” in John Cleland and John Hobcraft (eds.), Reproductive Change in Developing Countries. Oxford: Oxford University Press, pp. 223–252. ———. 2001. “Potatoes and pills: An overview of innovation-diffusion contributions to explanations of fertility decline,” in John B. Casterline (ed.), Diffusion Processes and Fertility Transition: Selected Perspectives. Washington, DC: National Academies Press, pp. 39–65. Cleland, John, Stan Bernstein, Alex Ezeh, Anibal Faundes, Anna Glasier, and Jolene Innis. 2006. “Family planning: The unfinished agenda,” The Lancet 368(9549): 1810–1827. Cleland, John, James F. Phillips, Sajeda Amin, and G.M. Kamal. 1994. The Determinants of Reproductive Change in Bangladesh: Success in a Challenging Environment, Volume 1. Washington, DC: World Bank. Cleland, John and Christopher Wilson. 1987. “Demand theories of the fertility decline: An iconoclastic view,” Population Studies 41(1): 5–30. Coale, Ansley J. and Susan Cotts Watkins (eds.). 1986. The Decline of Fertility in Europe. Princeton: Princeton University Press. Easterlin, Richard A. 1975. “An economic framework for fertility analysis,” Studies in Family Planning 6(3): 54–63. ———. 1978. “The economics and sociology of fertility: A synthesis,” in Charles Tilly (ed.), Historical Studies of Changing Fertility. Princeton: Princeton University Press, pp. 57–113. Easterlin, Richard A. and Eileen M. Crimmins. 1985. The Fertility Revolution: A Supply–Demand Analysis. Chicago: University of Chicago Press. Freedman, Ronald. 1997. “Do family planning programs affect fertility preferences: A literature review,” Studies in Family Planning 28(1): 1–13. Freedman, Ronald and Bernard Berelson. 1976. “The record of family planning programs,” Studies in Family Planning 7(1): 1–40. Herrin, Alejandro. 2007. “Development of the Philippines’ Family Planning Program: The early Years, 1967-80,” in Warren C. Robinson and John A. Ross (eds.), The Global Family Planning Revolution: Three Decades of Population Policies and Programs. Washington, DC: World Bank, pp. 277–297. Hull, Terrence. 2007. “Formative years of family planning in Indonesia,” in Warren C. Robinson and John A. Ross (eds.), The Global Family Planning Revolution: Three Decades of Population Policies and Programs. Washington, DC: World Bank, pp. 235–256. Khuda, Barkat E., John C. Caldwell, Bruce K. Caldwell, et al. 2001. “Determinants of the fertility transition in Bangladesh,” in Zeba A. Sathar and James F. Philips (eds.), Fertility Transition in South Asia. Oxford: Oxford University Press, pp. 364–385. Knodel, John and Etienne van de Walle. 1979. “Lessons from the past: Policy implications of historical fertility studies,” Population and Development Review 5(2): 217–245. Koenig, Michael A., James F. Phillips, Ruth S. Simmons, and Mehrab Ali Khan. 1987. “Trends in family size preferences and contraceptive use in Matlab, Bangladesh,” Studies in Family Planning 18(3): 117–127. Koenig, Michael A., Ubaidur Rob, Mehrab Ali Khan, J. Chakraborty, and Vincent Fauveau. 1992. “Contraceptive use in Matlab, Bangladesh in 1990: Levels, trends, and explanations,” Studies in Family Planning 23(6): 352–364. June 2014
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Murunga, Violet I., Nyokabi R. Musila, Rose N. Oronje, and Eliya M. Zulu. 2013. “The role of political will and commitment in improving access to family planning in Africa.” Paper presented at the Annual Meeting of the Population Association of America, New Orleans, LA, 11–13 April 2013. http://paa2013.princeton.edu/papers/131780. Accessed 8 March 2014. Notestein, Frank. 1945. “Population—the long view,” in Theodore W. Schultz (ed.), Food for the World. Chicago: University of Chicago Press, pp. 36–57. ———. 1953. “Economic problems of population change,” in Proceedings of the Eighth International Conference of Agricultural Economists. London: Oxford University Press, pp. 13–31. Phillips, James F., Ruth Simmons, Michael A. Koenig, and J. Chakraborty. 1988. “Determinants of reproductive change in a traditional society: Evidence from Matlab, Bangladesh,” Studies in Family Planning 19(6): 313–334. Pritchett, Lant H. 1994. “Desired fertility and the impact of population policies,” Population and Development Review 20(1): 1–55. Rochat, Roger W., Dorine Kramer, Pramilla Seanayake, and Catherine Howell. 1980. “Induced abortion and health problems in developing countries,” The Lancet 316(8192): 484. Ross, John and Ellen Smith. 2011. “The family planning effort index: 1999, 2004, and 2009,” International Perspectives on Sexual and Reproductive Health 37(3): 125–133. Simmons, Ruth, Laila Baqee, Michael A. Koenig, and James F. Phillips. 1988. “Beyond supply: The importance of female family planning workers in rural Bangladesh,” Studies in Family Planning 19(1): 29–38. Singh, Susheela and Jacqueline E. Darroch. 2012. “Adding it up: Costs and benefits of contraceptive services—estimates for 2012.” New York: Guttmacher Institute and United Nations Population Fund (UNFPA). Singh, Susheela, Deirdre Wulf, Rubina Hussain, Akinrinola Bankole, and Gilda Sedgh. 2009. “Abortion worldwide: A decade of uneven progress.” Report. New York: Guttmacher Institute. Solo, Julie. 2008. “Family planning in Rwanda: How a taboo topic became priority number one.” Report. Chapel Hill, NC: IntraHealth International. Tietze, Christopher. 1981. Induced Abortion: A World Review. New York: Population Council. United Nations Development Programme (UNDP). 2013. Human Development Report 2013. The Rise of the South: Human Progress in a Diverse World. New York: UNDP. Wang, Wenjuan, Shanxiao Wang, Thomas Pullum, and Paul Ametepi. 2012. “How family planning supply and the service environment affect contraceptive use: Findings from four east African Countries.” DHS Analytical Studies No. 26. Calverton, MD: ICF International. Watkins, Susan Cotts. 1986. “Conclusions,” in Ansley J. Coale and Susan Cotts Watkins (eds.), The Decline of Fertility in Europe. Princeton: Princeton University Press, pp. 420–449. ———. 1987. “The fertility transition: Europe and the third world compared,” Sociological Forum 2(4): 645–673. Westoff, Charles F. 2006. “New estimates of unmet need and the demand for family planning.” DHS Comparative Reports No. 14. Calverton, MD: Macro International. ———. 2012. “Unmet need for modern contraceptive methods.” DHS Analytical Studies No. 28. Calverton, MD: ICF International. ———. 2013. “The recent fertility transition in Rwanda,” Population and Development Review 38(Suppl. S1): 169–178. Westoff, Charles F. and Akinrinola Bankole. 1995. “Unmet need: 1990–1994.” Demographic and Health Surveys Comparative Studies No. 16. Calverton, MD: Macro International. Westoff, Charles F. and Luis H. Ochoa. 1991. “Unmet need and the demand for family planning.” Demographic and Health Surveys Comparative Studies No. 5. Columbia, MD: Institute for Resource Development.
ACKNOWLEDGMENTS Eliya Zulu provided valuable comments on an earlier version of this paper. Data regarding the family planning effort score by country were provided by the Futures Group.
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Much of the existing literature on the demographic impact of family planning programs focuses on their role in increasing contraceptive use, which, in turn, accelerates fertility decline. What is not clear, however, is whether this effect operates solely through a reduction in unmet need brought about by eliminating obstacles to use or whether and to what extent the programs also affect demand for contraception through messages concerning the benefits of family planning. This article aims to shed additional light on this issue by analyzing data drawn from recent Demographic and Health Surveys conducted in 63 developing countries. The first section reviews general levels and trends in unmet need, demand, and use over the course of the fertility transition. The second section presents different types of evidence of program effects, including results from a controlled experiment and from country case studies. The evidence indicates a program impact on both unmet need and demand. (Studies in Family Planning 2014; 45[2]: 247–262)
F
amily planning programs are now widely considered a key part of any comprehensive development strategy. The international consensus on this issue is reflected in the UN Millennium Development Goals, specifically the MDG5 target of providing universal access to reproductive health by 2015. The 2012 London Summit on Family Planning, organized by the UK government and the Bill and Melinda Gates Foundation, strengthened political commitments and raised new funds, thus reaffirming the role of family planning in the global development agenda. The existence of substantial unmet need for contraception and large numbers of unplanned pregnancies has provided the main rationale for investments in family planning programs by governments and donors (Singh and Darroch 2012). The impact of these family planning programs on fertility and contraceptive use has been discussed extensively in the literature but remains a somewhat unsettled issue (Bongaarts et al. 2012). On one side of the debate are those who accept “demand theories,” which are based on conventional demographic transition theory (Notestein 1945 and 1953; Bryant 2007). This view argues that fertility declines are driven by socioeconomic development. In traditional agricultural societies, fertility is high to offset high mortality. As a society modernizes, economic and social changes increase the costs of raising children (e.g., cost for education) and reduces John Bongaarts is Vice President and Distinguished Scholar, Population Council, One Dag Hammarskjold Plaza, New York, NY 10017. Email: [email protected]. ©2014 The Population Council, Inc.
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their economic value (e.g., for labor and old-age security), resulting in a decline in desired family size and a rise in the demand for, and adoption of, birth control. Family planning programs are often seen as having only a marginal impact (Pritchett 1994). A key assumption of demand theories is that the cost of contraception is minimal and has little or no practical consequence. In the late 1960s and early 1970s, this assumption was questioned by evidence from fertility surveys conducted throughout the developing world. In particular, many women were not practicing contraception even though they did not want to become pregnant (Freedman and Berelson 1976). Later surveys confirmed this finding (Westoff and Ochoa 1991; Westoff and Bankole 1995). In addition, the substantial levels of induced abortion in developed and developing countries demonstrated that unintended pregnancies were common (Rochat et al. 1980; Tietze 1981; Singh et al. 2009). These findings led to an influential revision of the economic theory of fertility by Richard Easterlin (Easterlin 1975 and 1978; Easterlin and Crimmins 1985). Easterlin’s framework for the determinants of fertility added two key elements to demand theories. First, it acknowledged the role of biology in childbearing outcomes. Specifically, without efforts to control conception, women who are sexually active will bear large numbers of children. To avoid having unplanned births, couples must practice effective birth control. Second, Easterlin recognized that the cost of birth control could be substantial, thus discouraging potential users and leading to unplanned pregnancies. Easterlin’s theory provided the theoretical underpinnings for investments in family planning programs. The objective of these programs is to allow women to determine freely whether and when to have children by removing obstacles to contraceptive use. Potential obstacles include the substantial costs of contraceptive commodities (e.g., pills, condoms, IUDs), transportation to obtain contraceptives, and reimbursement of service providers. In addition, significant noneconomic costs can impede adoption of family planning, such as health concerns, social disapproval, spousal resistance, and unnecessary medical barriers. Another challenge to demand theories came in the 1970s and 80s when empirical tests of these theories were conducted using historical and contemporary data. The massive study of province-level data from European countries for the period 1870–1960 (Knodel and van de Walle 1979; Coale and Watkins 1986; Watkins 1986 and 1987) and analyses of fertility surveys in the 1970s and early 1980s (Cleland 1985; Cleland and Wilson 1987) failed to find the tight link between development indicators and fertility expected from conventional theories. Although most traditional societies do have high fertility when compared with modern industrial societies, the transition itself is poorly predicted by customary quantitative measures of development (Bongaarts and Watkins 1996). These unexpected findings led to a revision in the thinking about the fertility transition and to the introduction of theories of the “diffusion” of innovations in reproductive behavior (Cleland and Wilson 1987; Cleland 2001; Casterline 2001a and 2001b). Diffusion refers to the process by which new technologies, ideas, behaviors, and attitudes spread within a population through a variety of mechanisms (e.g., social networks, opinion leaders, media) independent of socioeconomic conditions. These past studies led to two hypotheses concerning the potential role of family planning programs. First, these programs can reduce unmet need by reducing obstacles to use and by providing access to contraceptive methods and services. This rationale is the most widely acStudies in Family Planning 45(2)
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cepted for these programs. Second, programs may produce a rise in the demand for contraception by implementing information, education, and communication (IEC) campaigns that spread ideas concerning the benefits of contraception and smaller families. This effect is suggested by diffusion theory and is supposed to operate in addition to the influence of socioeconomic variables on demand for children. Much of the existing literature on the demographic impact of family planning programs focuses on their role in increasing contraceptive use and accelerating fertility transitions. For example, an overview by Bongaarts and colleagues (2012) concludes that a high-quality family planning program that has a substantial IEC component can reduce the total fertility rate by approximately 1.5 births per woman. What is not clear, however, is whether this effect operates solely through a reduction in unmet need or whether and to what extent the programs also affect demand for contraception. This article aims to provide greater clarity on this issue. After a brief overview of levels and trends in unmet need, different types of evidence of this impact will be presented.
UNMET NEED AND SATISFACTION OF DEMAND FOR CONTRACEPTION Estimates of demand for contraception and the degree to which it is satisfied can be derived from responses to questions concerning fertility preferences and the use of contraceptives in Demographic and Health Surveys (DHSs) (Westoff and Ochoa 1991; Westoff and Bankole 1995; Westoff 2006 and 2012; Bradley et al. 2012). Married women who are fecund and do not wish to become pregnant soon are assumed to have a demand for contraception.1 Some of these women are practicing contraception and some are not. The former are current users whose need for a method of contraception is considered to have been met (even though they may not be satisfied with their current method); the latter are considered to have an unmet need for contraception. These definitions can be expressed as a formula: demand = current use + unmet need. Estimates for these measures are available from DHSs conducted most recently in 37 countries in sub-Saharan Africa, 15 countries in Asia/Middle East/North Africa, and 11 countries in Latin America.2 Regional averages (unweighted) of these country-specific estimates are provided in Figure 1. Sub-Saharan Africa has the lowest demand (54 percent) and the lowest contraceptive use (28 percent) while having the highest unmet need (26 percent). In the other regions, on average more than 70 percent of women want to avoid pregnancy, and three-quarters of them are practicing some method of contraception. The average level of unmet need is 20 percent in Asian/Middle Eastern/North African countries and 19 percent in Latin America. Among the developing countries examined here, the progress made through the fertility transition differs widely. At one end of the spectrum are early transitional countries—mostly in West and Central Africa—which are characterized by low education and income levels and 1 Estimates of unmet need include women who are pregnant or who have recently given birth if their pregnancy or most recent birth was unintended. 2 DHSs conducted in Europe or in countries formerly of the Soviet Union are not included in this analysis. For the full list of countries included in this analysis, see Appendix Table A1.
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FIGURE 1 Average of country percentages of married women of reproductive age having demand for and using contraceptives, by region Percent of married women of reproductive age
90 80 70 60 50 40 30 20 10 0
Demand
78 70
19a
20
54
60
26
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Use Unmet need
28 Sub-Saharan Africa
Asia/ Middle East/ North Africa
Latin America
a Sum of unmet need plus use appears greater than demand because of rounding. NOTE: Difference between each pair of bars is the unmet need. SOURCES: 63 Demographic and Health Surveys.
high birth rates. At the other end of the spectrum are late transitional countries, such as Brazil, Colombia, and Turkey, having relatively high education and income levels and low fertility. It is plausible to assume that unmet need and demand vary by the stage of the transition. To examine this hypothesis, Figures 2–6 plot various indicators by the level of fertility as measured by the total fertility rate (TFR) for all DHSs examined. Figure 2 plots demand and use by TFR. Each country is represented by two markers: one for demand (black circles) and the other for current use of any method (gray circles). The TFR ranges from 7.2 births per woman in Niger in 1998 (demand = 26 percent; use = 8 percent) to 1.9 births per woman in Vietnam in 2002 (demand = 85 percent; use = 79 percent). As expected, demand and use are both inversely related to fertility. The relationships are approximately linear, but the slope for the relationship between TFR and contraceptive use is steeper than for the relationship between TFR and demand. As a result, the gap between demand and use (i.e., unmet need) declines as the TFR declines, as shown in Figure 3. High fertility countries FIGURE 2 Percentage of married women of reproductive age having demand for and using contraceptives, by TFR, 63 developing countries
Percent of married women of reproductive age
100 80
J J J JJ J JJ J JJ J J J J JJ JJ J JJ JJJ JJ J J JJJJ J J J J J J JJ J J J J J J J J J JJJ J J JJJ J J J J J J J J J
J J
60 40 J
20 J
0
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Demand J JJ
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4 TFR
Use
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FIGURE 3 Percentage of married women of reproductive age having unmet need for contraception, by TFR, 63 developing countries
Percent having unmet need
100 80 60 40
J JJ J JJ J J
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J
8
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4 TFR
JJ
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0
typically have levels of unmet need of approximately 30 percent, but by the end of the fertility transition this unmet need is much lower—usually less than 20 percent. Two additional indicators provide insight into the changing reproductive behavior at different points in the fertility transition. The first is the percent of demand that is satisfied (i.e., use ÷ demand), which is a direct measure of the extent to which women are able to achieve their reproductive preferences. As shown in Figure 4, this indicator differs sharply between high- and low-fertility countries. This finding is expected from the simultaneous decline in unmet need and the rise in demand as countries move through the fertility transition. Another useful indicator is the proportion of contraceptive users that relies on modern rather than traditional methods. One would expect countries having low fertility to generally have a wider choice of methods and to rely more on modern methods. This expectation FIGURE 4 Percentage of demand satisfied among married women of reproductive age having demand for contraceptives, by TFR, 63 developing countries
Percent of demand satisfied
100 80 60
J
J
40
J
JJ
J J J J J J J J J
20
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JJ J J J JJ J J J J JJ J J J J J J J J J JJ
JJ
J J
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FIGURE 5 Percentage of modern method users among married women of reproductive age who practice contraception, by TFR, 63 developing countries Percent of users using modern methods
100
J J J J
80
J JJ
J J JJJ
J J
J JJ
60 J
J J J
J
J J J
J
J J
J J
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is more or less confirmed by the data in Figure 5, but the relationship between TFR and the percent using modern methods is weak. In sum, in countries in the early stages of the transition, unmet need is largest because use falls well short of demand. At lower levels of fertility, use and demand rise but use catches up with demand, and unmet need, therefore, tends to decline. As a result, the proportion of demand that is satisfied rises. Figures 2–5 present only cross-sectional evidence. Time series of these indicators in countries typically follow similar patterns over time as countries move through their transitions (data not shown). Some early-transition countries exhibit exceptions to this rule, with unmet need rising initially and demand rising faster than use. For example, in Uganda total unmet need rose from 29 percent to 41 percent between the 1995 and 2006 DHSs, a period during which use rose from 15 percent to 24 percent while demand increased from 44 percent to 64 percent. Such examples of countries in which unmet need, use, and demand all rise together are relatively rare.
IMPACT OF FAMILY PLANNING PROGRAMS The main hypotheses that will be tested below are that family planning programs reduce unmet need and increase use, demand, percent satisfied, and percent using modern methods. Unfortunately, the measurement of the effect of programs on a given indicator is not straightforward, because estimates of the size of the impact require the estimation of an unobservable quantity: the level of the indicator that would have been observed in a population in the absence of the family planning program. Subtracting the observed indicator from this hypothetical estimate yields the impact. Two alternative approaches that are available to obtain such estimates for populations are discussed below: controlled experiments and country case studies. Studies in Family Planning 45(2)
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Controlled Experiments The gold standard for evaluating interventions are controlled experiments, but few large-scale controlled experiments have been conducted to assess family planning programs because they are expensive and take a long time to complete. The largest and most influential quasi- experiment started in 1977 in Matlab, Bangladesh. At that time, Bangladesh was one of the poorest and most highly agricultural countries in the world, and skepticism regarding whether family planning would be accepted in such a traditional society was widespread. The experiment divided the Matlab district (population 173,000 in 1977) into experimental and control areas of approximately equal size. Individuals in the control area received the same minimal services as the rest of the country, whereas in the experimental area comprehensive high-quality family planning services were provided, aimed at reducing the costs (monetary, social, psychological, and health) of adopting contraception. The experimental area provided free services and supplies of a range of methods (condoms, injectables, IUDs, pills, and sterilization) together with home visits by well-educated female family planning workers. Outreach to husbands, village leaders, and religious leaders addressed potential social and familial objections from men (Cleland et al. 1994; Phillips et al. 1988). The impact of these intensive services on reproductive behavior was large and immediate. Within 18 months of the start of the program, the proportion of women practicing contraception in the experimental area rose from 5 percent to 33 percent (Cleland et al. 1994). In contrast, little change occurred in the control area or in the remainder of Bangladesh during the first few years. A survey in 1984 measured contraceptive prevalence at 39 percent in the intervention area and 17 percent in the control area (Koenig et al. 1987). In addition, by 1990 the intervention area had a much lower proportion of women of reproductive age practicing traditional methods: 6 percent, compared with 26 percent in the control area (Koenig et al. 1992). The rise in contraceptive prevalence and effectiveness of use in the experimental area led to a decline in the total fertility rate of approximately 1.5 births per woman below that in the control area (Cleland et al. 1994). This fertility difference was maintained from the beginning of the experiment through the 1980s, before narrowing slowly in the 1990s as services in the control area, and in all of Bangladesh, improved substantially. Although the experiment’s outcomes with regard to increasing contraceptive use, changing the method mix, and reducing fertility are well documented, the levels and trends in unmet need and demand for contraception have not been systematically documented. The only source of information regarding the topic is Koenig and colleagues’ 1984 survey, which included a question about women’s desire for more children. This is a proxy for the demand for limiting, but it is rather crude. Unfortunately, this survey lacks information regarding key variables needed to estimate unmet need and demand as defined by the DHS (Koenig et al. 1987). Figure 6 presents estimates from 1984 of contraceptive demand and use, unmet need for limiting births, and percent of limiters who are satisfied. No data regarding spacing are available. The results are largely as expected: in the treatment area, contraceptive use and percent satisfied are higher and unmet need is lower than in the comparison area. (Note again that unmet need is not measured in the standard DHS form and is only for limiting.) The only surprise is that the demand for limiting (i.e., percent of women who want no more children) is slightly lower in the intervention than in the control area. This finding is probably explained in part by the more extensive use of contraceptives for spacing births in June 2014
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FIGURE 6 Indicators for treatment and comparison areas, Matlab, Bangladesh, 1984 90 Treatment
70 60
55
60
50
45
40 28
27
30 20
15
Percent having demand for limiting
Percent of married women of reproductive age
80
Comparison 49
24
10 0
Want no more children
Practicing contraception to limit births
Unmet need for limiting
Demand satisfied
SOURCE: Koenig et al. 1987.
the intervention area. With wider spacing, women in the intervention area reach their desired family size at a later age than women in the control area; thus, fewer women want no more children in the latter than in the former. In addition, the intervention focused on providing services rather than changing demand, and experimental and control areas saw similar declines in fertility preferences in the years before 1984 (Koenig et al. 1987; Freedman 1997).
Country Case Studies When two countries have similar social, economic, and cultural characteristics but one of these countries has implemented a family planning program and the other has not, beforeand-after comparisons are akin to a “natural experiment.” We can observe the difference in unmet need, contraceptive use, and demand for family planning between the two countries and attribute any differences largely to the existence of the family planning program in the “experimental” country. Four examples of such country pairs will be examined. Overviews will be presented first, followed by survey measures contrasting contraceptive access scores in the two countries of each pair. Bangladesh and Pakistan
These two countries were united as one nation from 1947 until Bangladesh was established after a civil war in 1971. As a result, these two populations still have much in common, and levels of development are broadly similar. Pakistan’s program has been weak, mostly as a result of lack of government commitment. In contrast, Bangladesh has implemented one of the world’s most effective voluntary family planning programs, using the experience and lessons from the Matlab experiment (Cleland et al. 1994 and 2006). A unique feature of the program is its staff of literate female workers who advise women and distribute supplies to their doorstep, thus overcoming the barriers posed by purdah (the practice of seclusion from public exposure among Muslim women) (Simmons et al. 1988). In addition, the government implemented a nationwide IEC program. For example, Radio Bangladesh, which is heard throughout the country, has devoted more than an hour each day to population and family planning issues since the 1980s (Khuda et al. 2001). Studies in Family Planning 45(2)
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Indonesia and the Philippines
Indonesia was one of the first Asian countries to implement a family planning program, and the program has had strong support from political leaders (Hull 2007). In contrast, the program in the Philippines has been weaker, in large part because of opposition by the Catholic Church (Herrin 2007). Kenya and Uganda
These neighboring countries in East Africa share a colonial history that has left an imprint on numerous institutions. Levels of development are broadly similar for the two countries. Until very recently, Uganda’s government has made little investment in family planning (a decision partly based on the fear of high AIDS mortality when the epidemic spread in the 1980s). In contrast, in the 1960s Kenya was one of the first countries in Africa to establish a family planning program, and it had substantial funding and technical support from bilateral and multilateral donors. The program included large-scale community-based distribution, providing rural clients with access to low-cost contraceptive services, and implemented nationwide IEC campaigns. After the mid-1990s, however, Kenya’s family planning program lost its priority, and the commitment of the government and international donors declined substantially. This neglect is one of the key reasons for the subsequent stalling of fertility near five births per woman (Blacker et al. 2005; Askew et al. 2009; Murunga et al. 2013). Rwanda and Burundi
These poor neighboring countries are among the most densely populated in Africa. Rwanda’s fertility was one of Africa’s highest in the twentieth century, but in the early 2000s the government renewed its lagging commitment to family planning in part to reduce rapid population growth. With strong support from international donors, access to contraceptive methods sharply increased throughout the country (Solo 2008; Murunga et al. 2013; Westoff 2013). Additionally, the president and other government officials spoke out about the need to reduce fertility, and a country-wide IEC program was implemented. In contrast, much less attention has been given to reproductive health in Burundi. For comparisons of reproductive measures in these countries to be useful, development levels must be similar and access to contraception must be different for the two countries in each pair. Table 1 examines these variables. The first column of Table 1 presents an index of access to modern methods from country respondents as estimated for 2009 by Ross and Smith (2011).3 This measure is available for seven of the eight countries examined here (Rwanda is missing). As expected, the countries that have weaker programs (Burundi, Pakistan, the Philippines, and Uganda) have relatively low access scores, whereas the scores for the countries having the stronger programs (Bangladesh, Indonesia, and Kenya) are substantially higher. 3 Ross and Smith (2011) collected data for 30 separate dimensions of family planning programs, including policies, services, evaluation, and access in 99 countries. These data were used to create a “family planning effort score” that incorporates all 30 dimensions. Six of the dimensions pertain to contraceptive access: access to condoms, pills, IUDs, injectables, female sterilization, and male sterilization. For the present study, I have created a “modern method access score,” which is the average of the scores of five of these six measures of access to modern contraceptive methods. Access to condoms was excluded from this average because condoms are distributed widely for HIV prevention. More detailed assessments of access and the service environment are available for a limited number of countries in which the DHS Program conducted Service Provision Assessment surveys (Wang et al. 2012).
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TABLE 1 Modern methods access score and human development index for four pairs of developing countries, 2009 Country pairs Bangladesh–Pakistan Indonesia–Philippines Kenya–Uganda Rwanda–Burundi Average (stronger–weaker)
Modern Human methods development access score index 59.6–37.0 0.502–0.508 56.3–24.1 0.611–0.643 43.5–39.2 0.505–0.445 na–34.1 0.417–0.340 53.1–33.4a 0.509–0.484
na = Not available. aExcludes Rwanda–Burundi pair. SOURCES: Ross and Smith 2011; UNDP 2013.
The average access score in the countries having stronger programs (53.1) exceeds that of the countries having weak programs (33.4) by nearly 20 points for the three pairs for which this comparison can be made. Given the above discussion of the situation in Burundi and Rwanda, it seems likely that if the access score had also been available for these two countries, the difference between them would be substantial. To assess development levels, the human development index (HDI) as estimated by the United Nations Development Programme is used (UNDP 2013). This index is obtained by combining indicators of life expectancy, educational attainment, and income into a composite index for countries. Estimates of the HDI in 2009 for the four country pairs are presented in Table 1. The HDIs of two pairs (Bangladesh–Pakistan and Indonesia–Philippines) are very similar, and the differences for the remaining two pairs are small. The average HDI of the stronger program countries is 0.509, compared with 0.484 for the weaker program countries. This difference is modest compared with the HDI range of 0.29 to 0.95 among all countries (not shown). FIGURE 7 Percentage of married women of reproductive age having unmet need for contraception, four pairs of developing countries
Percent having unmet need
40
38.0 Stronger program
35
31.0
30 25
22.0
20.8
20 15
Weaker program
25.6
25.2 16.8 13.1
10
nd ga
U
i ru nd
da
Bu
an Rw
n sta
h
Pa ki
a
ny
Ke
Ba
ng
lad
es
es pp in
ili
Ph
In
do ne
sia
0
a
5
SOURCES: Most recent Demographic and Health Surveys.
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With these reassuring findings regarding the similarity of development and the difference in contraceptive access for countries in each pair, we can now proceed with an examination of differences in reproductive indicators. The expectation is that stronger program countries have lower unmet need, and have higher use, demand, percent satisfied, and percent using modern contraceptives, compared with the weak program country in each country pair. Figures 7–11 present these five indicators for all eight countries at the time of their most recent DHS survey (average year of survey is 2009). The results are clear: this hypothesis is confirmed in 20 out of the 20 comparisons (five indicators for four country pairs). FIGURE 8 Percentage of married women of reproductive age practicing contraception, four pairs of developing countries Stronger program
61.4
60
Percent practicing contraception
55.8
Weaker program
51.6
50.7
50
45.5
40 29.6
30
23.7
21.9
20 10
a nd ga
ru Bu
U
nd
i
da an Rw
a
ny
Ke
Ba
ng
Pa
ki
sta
n
h lad
es
es in pp
ili Ph
In
do
ne
sia
0
SOURCES: Most recent Demographic and Health Surveys.
80 74.5
72.7
72.6
Stronger program
72.4
71.1
70
61.7
60
54.8
Weaker program
52.9
50 40 30 20
a
ny
Ke
ga
nd i ru
Bu
an da Rw
n
Pa ki
sta
h es lad Ba ng
es pi n
lip
Ph i
In
do ne
sia
0
nd a
10
U
Percent having contraceptive demand
FIGURE 9 Percentage of married women of reproductive age having demand for contraception, four pairs of developing countries
SOURCES: Most recent Demographic and Health Surveys.
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FIGURE 10 Percentage of demand satisfied among married women of reproductive age having demand for contraceptives, four pairs of developing countries
Percent of demand satisfied
90
Stronger program
82.4
80
76.9
Weaker program
71.3
69.7
70
63.9
60
54.1
50
42.3
40
38.4
30 20 10
ga
nd a
a
ny
Ke
U
da Bu ru nd i
Rw an
Ba n
Pa
ki sta n
ad es h gl
es pp in
ili
Ph
In
do n
es ia
0
SOURCES: Most recent Demographic and Health Surveys.
FIGURE 11 Percentage of modern method users among married women of reproductive age who practice contraception, four pairs of developing countries Stronger program
93.5
90
85.1
80 70
87.4 80.8
86.6 75.5
73.3
67.1
Weaker program
60 50 40 30 20
Rw an da Bu ru nd i
ki sta n
Pa
es h ng lad
a
ny
Ke
Ba
In do ne sia Ph ili pp in es
0
nd a
10
U ga
Percent of users using modern methods
100
SOURCES: Most recent Demographic and Health Surveys.
The findings from these country case studies suggest that a well-organized family planning program having a substantial IEC component can, on average: • • • • •
reduce unmet need by 10 percent (range 8.4–12.4) increase contraceptive use by 22 percent (range 19.7–29.7) increase demand by 12 percent (range 1.8–19.5) increase satisfaction of demand by 10 percent (range 12.7–29.0) increase use of modern methods by 14 percent (range 6.6–26.4).
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These calculations may slightly overestimate the program impact because the HDI is slightly higher in the stronger programs than in the weaker ones. In addition, these results are not derived from true controlled experiments, so ruling out unobserved confounding factors is not possible. Countries can, of course, differ from one another in characteristics that are not examined here (e.g., political systems, inequality, percent urban, and so forth). On the other hand, family planning services were not entirely absent in the weaker program populations examined above, so the differences do not estimate the full program impact.
CONCLUSION The recent growth in investments in family planning programs is to a large extent based on the existence of an unmet need for contraception and on the assumption that such investments reduce unmet need. The preceding analysis examined evidence concerning the impact of family planning programs on unmet need and related indicators of reproductive behavior. The findings from the Matlab experiment and from comparisons of country pairs having stronger and weaker programs confirm that programs reduce unmet need and increase use. In addition, the proportion of demand that is satisfied and the proportion of women using modern methods are increased. Although the limitations of the country case study approach preclude drawing definitive conclusions, family planning programs appear to have two distinct effects on reproductive behavior. First, by making modern contraceptives more widely available and by removing obstacles to use, more women who do not want to become pregnant practice contraception, thereby reducing unmet need. With a given level of demand, an increase in use produces a corresponding decline in unmet need. The evidence also shows, however, that programs can have a second effect by raising the demand for contraception.4 This effect is expected according to diffusion theory and may be attributed to program IEC messages concerning the benefits of family planning and the diffusion of ideas about them. These findings imply that the overall impact of family planning programs on unmet need can be small or even absent when a rise in use is accompanied by a rise in demand. The impact on unmet need is indeed smaller than on use in the country case studies summarized earlier (Figures 7–11). This confounding effect of changes in demand complicates efforts to assess program impact and should be taken into account in future analysis of trends in unmet need. As noted by Caldwell and colleagues (1992), policymakers in countries where demand is still low (e.g., in the poorest African countries) have often given programs low priority, on the assumption that they would be unsuccessful and their impact would be small. This view seems too pessimistic. The finding that family planning programs can potentially raise demand through the implementation of appropriate IEC campaigns is particularly important for such countries.
4 See Bongaarts 2011 for an analysis of the effect of family planning programs on desired family size.
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APPENDIX TABLE A1 List of 63 countries included in analysis, by region and DHS survey year Region
DHS survey year
Sub-Saharan Africa Benin 2006 Burkina Faso 2010 Burundi 2010 Cameroon 2011 Central African Republic 1994–95 Chad 2004 Comoros 1996 Congo (Brazzaville) 2005 Congo Democratic Republic 2007 Cote d’Ivoire 1998–99 Eritrea 2002 Ethiopia 2011 Gabon 2000 Ghana 2008 Guinea 2005 Kenya 2008–09 Lesotho 2009 Liberia 2007 Madagascar 2008–09 Malawi 2010 Mali 2006 Mauritania 2000–01 Mozambique 2003 Namibia 2006–07 Niger 2006 Nigeria 2008 Rwanda 2010 Sao Tome and Principe 2008–09 Senegal 2010–11 Sierra Leone 2008 South Africa 1998 Swaziland 2006–07 Tanzania 2010 Togo 1998 Uganda 2011 Zambia 2007 Zimbabwe 2010–11
Region
DHS survey year
Middle East Egypt 2008 Jordan 2009 Morocco 2003–04 Turkey 1998 Yemen 1997 Asia Bangladesh 2007 Cambodia 2010 India 2005–06 Indonesia 2007 Maldives 2009 Nepal 2011 Pakistan 2006–07 Philippines 2008 Timor–Leste 2009–10 Vietnam 2002 Latin America Bolivia 2008 Brazil 1996 Colombia 2010 Dominican Republic 2007 Guatemala 1998–99 Guyana 2009 Haiti 2005–06 Honduras 2005–06 Nicaragua 2001 Paraguay 1990 Peru 2007–08
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ACKNOWLEDGMENTS Eliya Zulu provided valuable comments on an earlier version of this paper. Data regarding the family planning effort score by country were provided by the Futures Group.
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