Elizabeth F. Jackson Ayaga A. Bawah Colin D. Baynes Katharine L. McFadden John E. Williams James F. Phillips

Transcription

1 The validity of survey data for measuring family planning service impact in a rural locality of northern Ghana Elizabeth F. Jackson Ayaga A. Bawah Colin D. Baynes Katharine L. McFadden John E. Williams James F. Phillips Elizabeth F. Jackson and Ayaga A. Bawah are Assistant Professors, Colin Baynes is Program Manager and Katharine McFadden is Doctoral Student, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, P&S Box 043, 60 Haven Avenue, B-2, New York, NY John Williams is Principal Medical Officer, Navrongo Health Research Center, Ghana. ej2217@columbia.edu This paper examines a decade of prospective panel survey data recording proximate fertility determinants and demographic surveillance data in a rural locality of northern Ghana where a quasi-experiment tested the impact of four contraceptive service provision strategies on fertility. Although treatments explain variance in observed fertility, analyses also reveal that fertility implied by proximate determinant responses exceeds observed fertility in areas with convenient doorstep family planning services. Analysis of longitudinal surveillance data suggests that community exposure to these doorstep services is associated with reproductive change. Results are consistent with the hypothesis that denial is most pronounced where observed fertility decline was greatest. The gap between fertility expected from proximate determinants and fertility observed from surveillance increases over time. This finding challenges the widely held assumption that survey appraisal of contraceptive use represents a valid endpoint for studies of the reproductive impact of community-based family planning services. Background Contraceptive prevalence is frequently used as an intermediate outcome to evaluate family planning programs because of the complexity, expense, and delay involved in measuring the long-term impact of services on fertility (Bertrand and Escudero 2002). Yet validation studies of self-reported contraceptive use are rare, despite evidence from several studies where selfreported family planning use may not correspond to fertility effects, either because contraception

2 substitutes for other proximate fertility determinants (Bledsoe, Hill et al. 1994) or because secrecy and the absence of spousal agreement can foster falsification of contraceptive use among survey respondents (Biddlecom and Fapohunda 1998). Investigations of validity that have compared women s self-reported use with their partner s self-reported use of a method reveal large discrepancies in levels of contraceptive use reported by husbands and wives, particularly in sub-saharan Africa (Becker and Costenbader 2001). Inconsistencies were attributed to a variety of factors including social desirability bias and possible covert use of contraception. In sub-saharan Africa, the prevalence of covert use of contraceptives, where contraceptives are used without spousal knowledge, is estimated between 7 percent in urban Zambia (Biddlecom and Fapohunda 1998) to 20 percent in rural Kenya (Maggwa, Mati et al. 1993). Another study in Uganda estimated covert use of contraceptives at 15 percent, with a range from 7 to 18 percent by urban and rural areas, respectively (Blanc et al. 1996). Denial of condom use has also been reported by almost half (44%) of women in semirural areas of Bangladesh (Ahmed, Schellstede et al. 1987). Studies that validate respondent- reported contraceptive use against clinical records are rare, with percent agreement results that have ranged from 52 to 90 percent (Rosenberg, Layde, et al. 1983). In Ghana, a 1995 validation study of the Navrongo Community Health and Family Planning Project (CHFP) showed that 20 percent of 194 women who were known users of injectable contraceptives denied use of a method when interviewed about their contraceptive status in the course of a DHS-like survey and 71 percent of their spouses reported that their wives were not currently using a method (Phillips, Adazu et al. 1997). Recent analysis of the long term fertility impact of the Navrongo Project demonstrated persistent though modest fertility decline particularly in areas with strong volunteer components that addressed the social costs of family planning (Phillips, Jackson et al. 2012). To clarify the contribution of contraceptive use to fertility decline, this paper assesses the proximate determinants of fertility in separate experimental localities where the CHFP was conducted over the 1994 to 2003 period. Demographic panel survey data on self-reported contraceptive use and other proximate determinants are available to augment demographic surveillance data on concomitant fertility levels. The availability of these data over a 10 year period permits time trend comparison of expected fertility rates based on survey data with observed fertility levels reported for cells of the Navrongo experiment. 2

3 Setting Socio-cultural setting. The Navrongo CHFP is in a rural area of northern Ghana undergoing gradual economic and social change with increases in women s educational level, partial transition to a cash economy, and slow replacement of traditional religion with Christianity. Women s literacy increased almost three-fold from 1995, to 32 percent in 2003 (Table 1). Polygyny has declined by over one third, to 21 percent in The prevalence of traditional religion decreased by one half over the period from 1995 to [insert Table 1 about here] The Navrongo CHFP 1993 to The Navrongo CHFP was a quasi-experimental study of the Navrongo Health Research Centre that tested the hypothesis that convenient family planning service delivery could induce and sustain reproductive change in a traditional Sahelian cultural setting. The package of programs offered by the CHFP was designed through intensive social research to ensure that services would foster reproductive change and improve community health through a culturally sensitive approach (Binka, Nazzar et al. 1995; Nazzar, Adongo et al. 1995; Adongo, Phillips et al. 1997). Male opposition was identified as the most significant constraint to the success of the family planning program and special emphasis was placed on developing strategies to reach out to men and address women s concerns (Bawah, Akweongo et al. 1999). Two strategies were developed through a process of engaged social research and piloted for 18 months in the period. These strategies were zurugelu, or community volunteer, services in the context of concentrated community mobilization and male involvement, and doorstep family planning services offered by community health nurses. The nurse outreach approach trained and placed community health nurses in village locations. Communities built health compounds where nurses resided and provided services. Nurses also used motorbikes to provide door-step health and family planning services during visits to each household in their catchment area four times a year. This strategy revolutionized the connection between rural people and their health system which previously relied on fixed facilities that were greatly underutilized. The community volunteer, or zurugelu arm of the experiment involved intense collaboration with cultural leadership structures and social networks and used traditions of 3

4 communication and volunteerism to build trust in and support for the program (Nazzar, Adongo et al. 1995). Rural areas of Kassena-Nankana district were divided into four experimental cells where residents received nurse outreach and zurugelu services separately, in combination, or not at all (Figure 1). To minimize contamination, geographical boundaries between each cell were formed by natural barriers wherever possible. In addition, each cell contained discrete chieftancy areas so that involvement of traditional leaders would not contaminate results in the neighboring cell. The quasi-experiment was brought to scale beginning in late 1996, with the scale-up of each strategy within its geographical cell. In , zurugelu services with a focus on management of childhood illnesses were introduced into the Cell 4 comparison area, based on the UNICEF-sponsored child survival program policy known as High Impact Rapid Delivery (HIRD). These services lacked the focus on family planning that was vigorously implemented as part of the original zurugelu strategy in Cell 1 and in the Cell 3 combined strategy area. By the end of 2001, HIRD coverage was complete in Cell 4. Fertility impact of the CHFP. The total fertility rate steadily declined from 1995 to 2004 in areas of Kassena-Nankana district that were exposed to CHFP services. The odds of fertility decreased in cells receiving zurugelu and combined services, relative to the comparison area, with respective odds ratios of 0.91 and 0.86, p<0.01 (Phillips, Jackson et al. 2012). There was no reduction in fertility in Cell 2 which received nurse outreach but no zurugelu activities. [insert Figure 1 about here] Data and Research Methods Data. Birth events were captured by the Navrongo Demographic Surveillance System (NDSS), a system for continuous assessment of demographic dynamics (Mbacke and Phillips 2008). In quarterly rounds, trained interviewers visit all dwelling units in the study area and register persons present from previous observation rounds, in- and out-migrants, pregnancies, births, and deaths. Clerks update databases through a process of continuous error trapping, data correction, and reporting that permits appraisal of the population size and composition, routine fertility, mortality, and migration rates, and areal differentials (Binka, Ngom et al. 1999). 4

5 Fertility determinants and background characteristics on a subset of NDSS compounds were monitored in yearly panel surveys. Instruments recorded trends in marriage, contraceptive use, and postpartum abstinence for women in each of the four experimental areas. The present analysis uses panel data for each year from 1994 through For each woman, information from yearly panels was linked with demographic surveillance data 2, 3, and 4 quarter-years after the panel interview date. Panel surveys were mainly administered in the final quarter of each year. For example, a woman interviewed in the 4 th quarter of 1994 for the 1994 panel would be linked with fertility outcomes in the 2 nd, 3 rd, and 4 th quarters of To be included in the analysis, a woman s demographic surveillance records had to show that she was between the ages of 15 and 49 and that she was resident 9 months prior to delivery so that experimental exposure at the time of conception could be assessed. The number of women in the merged dataset was 11,247 and the dataset included a total of 47,505 person-years of observation. On average, records for each woman included information from 4.2 yearly panel surveys. Methods: Proximate Determinants Analysis. To elucidate the dynamics of reproductive change in the Navrongo project, we conducted an analysis of the proximate determinants of fertility based on the Bongaarts method (Bongaarts 1978) with certain modifications suggested by Stover (Stover 1998). Expected total fertility was calculated using two equations: (1) Cm = ( ) ( ) ( ) Cm m(a) g(a) TFR TM =, where is the index of proportion married is the age specific proportion married is the age specific marital fertility rate is the total fertility rate, and is the total marital fertility rate. (2) TFR = PF * Ca * Cm * Ci * Cf * Cu, where PF is potential fertility, the TFR of a population of women 15 to 49 who are sexually active, fecund, not practicing contraception or breastfeeding and not postpartum abstinent (Stover 1998) Ca Ci Cf Cu is the abortion index is the index of postpartum insusceptibility is the index of infecundability, and is the index of contraception. 5

6 Successive Navrongo panel surveys measured infecundability inconsistently over time and therefore we based Cf on the 1993 Ghana DHS which reported that 14.3 percent of sexually active women were infecund (Stover 1998), assigning Cf a value of.857. Because data on abortion are not available in the panel survey, we used Stover s estimate of PF * Ca = 22.9 for Ghana from 1993 DHS data (Stover 1998). Stover calls for replacement of Cm with Cx, an index of sexual activity. Data on sexual activity was measured inconsistently in the panel and so we used Bongaarts index of proportion married instead. We calculated age-specific values for Cm using m(a), the age specific proportion married or living with a sexual partner, and the ASFR (Bongaarts 1978). Age-specific values for Ci were calculated as the combined effect of breastfeeding and postpartum abstinence (Bongaarts 1982; Stover 1998). Finally, age-specific values for Cu were calculated according to Bongaarts original model (Bongaarts 1978). Methods: Multivariable Analysis. Our second analysis investigated relationships between determinants of fertility measured in panel surveys from 1994 to 2003, experimental exposure, and birth outcomes at the individual level using a multivariable model. The goal of this analysis was to obtain an alternate view of CHFP health service impact on fertility regulation behavior and fertility outcomes. Exposure to CHFP services was assessed in the quarter 9 months prior to the first of three quarters of demographic surveillance data linked with each woman s panel data. Fertility regulation behaviors were measured using two questions from the yearly panel survey: (1) Have you resumed sexual relations since the birth of (name of last born child)? (2) (If currently doing something/using any method to delay or avoid pregnancy) Which method are you using? Responses were broken into four categories of (1) exclusive use of a modern contraceptive method (oral pill, IUD, injection, diaphragm, foam, jelly, condom, Norplant, or male or female sterilization) without postpartum abstinence; (2) postpartum abstinence or other method use (withdrawal, rhythm/periodic abstinence, prolonged abstinence, or other ) without use of a modern method; (3) use of both a modern method and postpartum abstinence; and (4) no fertility regulation. Because postpartum abstinence was measured separately, overlap was possible between postpartum abstinence and any of the reported methods to delay or avoid pregnancy. There was no overlap between modern contraceptive use and non-modern methods because only one response was allowed to the survey question about current method use.

7 Multivariable analysis controlled for confounding by background characteristics and other fertility determinants that could have differed between the areas receiving CHFP intervention services. Fertility regulation behavior was considered separately from other fertility determinants because exposure to CHFP services would only directly influence regulation behavior (Figure 2). The joint effects of type of service exposure and regulation behavior on fertility outcomes were assessed for each combination of exposure and behavior through inclusion of interaction terms. Coital frequency data and data on menopause and sterility were not consistently measured in the panel survey and therefore there are listed as unmeasured in the diagram. [insert Figure 2 about here] Results Proximate Determinants Analysis. Comparison of expected fertility calculated using the proximate determinants of fertility, and fertility observed in demographic surveillance, revealed high levels of unexplained fertility decline. Unexplained fertility decline is said to occur when the expected TFR calculated from the proximate determinants is greater than the TFR observed from demographic surveillance. Analysis of the proximate determinants shows that postpartum insusceptibility is by far the most influential determinant in reducing women s fertility, typical for this region of sub- Saharan Africa (Figure 3). The impact of the Navrongo CHFP can be seen through trends in contraceptive use. Increases in the prevalence of contraception are greatest in Cells 1 and 3, where zurugelu activities were deployed. Some gains in the Cell 2 nurse outreach area were observed, and minimal gains occurred in the comparison area from 1994 to Exposure to CHFP services also appears correlated with unexplained fertility decline. Data appear erratic, but in general, unexplained fertility decline was least prevalent in the Cell 4 comparison area and more prevalent in Cells 1, 2 and 3, where fixed facility family planning services were augmented by community volunteers, nurse outreach, or both, respectively. [insert Figure 3 about here] 7

8 Low fertility unexplained by the proximate determinants. Subsequently, we investigated relationships between determinants of fertility measured in panels from 1994 to 2003, experimental exposure, and birth outcomes from demographic surveillance in a multivariable model. This analysis assessed the fertility impact that arose from the different types of experimental exposure acting through each of the three fertility regulation behaviors at the individual level. Multivariable analysis confirmed the finding of the proximate determinants analysis; after controlling for all determinants of fertility including marital status, education, age, time, pregnancy at time of panel, postpartum amenorrhea at time of panel, and fertility regulation behavior at time of panel, fertility is still lower in experimental areas relative to the comparison area. Women receiving any CHFP services had between 0.8 and 0.9 times the odds of subsequently having a birth compared to women in the comparison area receiving no services (Table 2, Model 1). Interaction terms between experimental exposure and fertility regulation categories were not statistically significant (Table 2, Model 2). However, joint effects are presented in spite of this in order to illuminate possible differences in the way CHFP services impacted fertility through each mode of fertility regulation behavior. Linear combinations of estimators from Model 2 are presented in Table 3. Among women who are using any kind of abstinence (postpartum, prolonged, or periodic), withdrawal or another non-modern method, the odds of subsequently giving birth are significantly lower in each of the three experimental areas relative to the comparison (Table 3, Group B). There are no differences between women receiving CHFP services in this group. In summary, use of abstinence or other non-modern methods appears to be more effective in experimental areas. There are a number of reasons why this could be the case. First, all combinations of CHFP health services may increase motivation to control fertility. Therefore, women in CHFP areas who are practicing abstinence or another non-modern method may be adhering to these methods more closely or using them longer. Related to this concept, women may be more likely to use abstinence or other traditional methods for limiting rather than for spacing which would also increase duration of abstinence (Blanc and Grey 2002). Finally, women in experimental areas who report abstinence or non-modern method use who do not report use of a modern method may be concealing use of a modern contraceptive method in panel surveys. If many women in this group in CHFP areas use modern methods (but choose not to report this in panel surveys) while women with the same reported behaviors in the comparison 8

9 area are truly not using modern methods, then fertility would be lower in CHFP areas than in the comparison area. [insert Table 2 about here] The second finding of interest is that women in experimental areas who report that they are not regulating their fertility have, for the most part, lower fertility than women in the comparison area (Table 3, Group D). Among women in zurugelu areas and women in combined nurse and zurugelu areas, the odds of giving birth are 0.81 times and.84 times the odds of giving birth among women in comparison areas, respectively, both with p< [insert Table 3 about here] This finding suggests either that (1) women in experimental areas are failing to report fertility regulation or that (2) women in experimental areas are more likely to, within a short time interval, begin to regulate their fertility, than are women in the comparison area. Given the prevalence of postpartum abstinence, and stigma against modern contraception (Bawah, Akweongo et al. 1999), it seems likely that women who report no fertility regulation are concealing modern contraceptive use. Although women in any study area might deny use of modern contraception, prevalence of modern contraception is highest in areas where CHFP services are offered. Therefore, among women who report no fertility regulation, the prevalence of denial would be expected to be higher in CHFP areas relative to the comparison area. It is not possible to distinguish between this denial explanation and the other possibility that women who report no fertility regulation at the time of the panel are more likely to begin controlling their fertility if they are in areas where services are provided at the doorstep level. Joint effects indicate fertility is the same among women who report practicing modern contraception and among women who report use of a modern method in addition to postpartum abstinence, regardless of exposure to any type of health services (Table 3, Groups A and C). Discussion Reported fertility regulation behavior is not high enough to explain fertility decline in the context of the Navrongo CHFP project. This paper reports discrepancies in observed and 9

10 expected fertility between CHFP service areas and control areas in an analysis of the proximate determinants of fertility and through multivariable modeling. Increased adherence to and/or duration of abstinence and other non-modern methods of fertility regulation, in combination with denial of modern contraceptive use, in CHFP service areas appear to be responsible for the discrepancies. Early study of the validity of self-reported contraceptive use as a measure (Phillips, Adazu et al. 1997) lends support to the conclusion that women continue to deny use of modern contraceptives even in areas where community education about family planning has been pervasive. Additional analyses of these early data indicate increased denial of modern methods with increased levels of community mobilization and education about family planning. Therefore, denial of modern contraceptive use in CHFP areas may be even higher than in the comparison area. Simple calculations show that even if denial is at a lower level in experimental areas, the level of unreported use may be far higher in these areas because of higher prevalence of contraceptives in general. For example, if only half of women in CHFP areas deny use while every woman in the comparison area denies use, and 30% of women in CHFP areas are using modern methods while only 10% of women in the comparison area are using these methods, the total level of denial will still be much higher in CHFP areas (Table 4). We cannot rule out the possibility that women s preferences are changing and that their fertility regulation behaviors alter rapidly, especially in experimental areas. A study of the stability of reproductive preferences in the 1995 and 1997 panel surveys found that over 20% of women changed their desire for additional children (Debpuur and Bawah 2000). Women in areas where family planning services are offered at the doorstep level may be more able to begin to act on changes in their fertility preferences, and more quickly, compared to their counterparts in areas without convenient services. Finally, increased efficacy of traditional methods is a fertility-reducing mechanism of the CHFP that has received little attention to date. It appears that women in experimental areas have greater adherence to and/or duration of use of methods such as postpartum abstinence. This is likely to be the result of community sensitization to the health risks of high fertility and the health benefits of birth spacing and limiting that took place as part of both the nurse and zurugelu components of the CHFP. [insert Table 4 about here] 10

11 Conclusion Exposure to health and family planning services in a traditional society is occurring in the complex societal circumstances that govern reproductive behavior. The provision of family planning services interact with fertility-regulating customs, which in turn interact with the practice of bridewealth and related pronatalist norms and beliefs of men. In this context, the social institutional determinants of fertility that sustain high fertility norms among men can be at odds with emerging preferences and ideas about childbearing that a program can introduce among women. Spousal discord, non-communication, and even secrecy can emerge as a consequence of the disconnect between emerging reproductive change and the persistence of engrained customs and beliefs. Interviews about reproduction interact with these ideational contradictions. Questions about contraceptive behavior are asked in a social context that can compromise validity. Thus, the more successful that a program may be in introducing reproductive change, the less valid may be its evaluation strategy. Our study has shown that if indicators of impact are confined to self- reported contraceptive behavior, then program impact would have been least reliably measured by answers to questions about contraception in communities where fertility impact is most pronounced. Acknowledgements The Navrongo project was supported by grants to the Population Council from the Finnish International Development Agency and the United States Agency for International Development and also by grants to the Navrongo Health Research Centre from the Rockefeller Foundation. This research was supported by the William and Flora Hewlett Foundation and the National Center for Advancing Translational Sciences, National Institutes of Health, through Columbia University s Irving Institute Grant Number UL1 TR The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. 11

12 References Adongo, P. B., J. F. Phillips, et al Cultural factors constraining the introduction of family planning among the Kassena-Nankana of northern Ghana. Social Science & Medicine, 45(12): Ahmed, G., W. P. Schellstede, et al Underreporting of Contraceptive Use in Bangladesh. International Family Planning Perspectives, 13(4): Bawah, A. A Spousal communication and family planning behavior in Navrongo: a longitudinal assessment. Studies in Family Planning, 33(2): Bawah, A. A., P. Akweongo, et al Women's fears and men's anxieties: the impact of family planning on gender relations in northern Ghana. Studies in Family Planning, 30(1): Becker, S. and E. Costenbader Husbands' and wives' reports of contraceptive use. Studies in Family Planning, 32(2): Bertrand, J. and G. Escudero Compendium of Indicators for Evaluating Reproductive Health Programs. Chapel Hill, NC, MEASURE Evaluation. Biddlecom A.E., B.M. Fapohunda Covert contraceptive use: prevalence, motivations, and consequences. Studies in Family Planning, 29(4): Binka, F. N., A. Nazzar, et al The Navrongo Community Health and Family Planning Project. Studies in Family Planning, 26(3): Binka, F. N., P. Ngom, et al Assessing population dynamics in a rural African society: The Navrongo Demographic Surveillance System. Journal of Biosocial Science, 31(3): Blanc, A. K. and S. Grey Greater than expected fertility decline in Ghana: Untangling a puzzle. Journal of Biosocial Science, 34(4): Blanc, A.K., et al Negotiating Reproductive Outcomes in Uganda. Calverton, MD: Macro International and Kampala, Uganda: Institute of Statistics and Applied Economics. Bledsoe, C. H., A. G. Hill, et al Constructing Natural Fertility - the Use of Western Contraceptive Technologies in Rural Gambia. Population and Development Review, 20(1): Bongaarts, J Framework for Analyzing Proximate Determinants of Fertility. Population and Development Review, 4(1): Bongaarts, J The fertility-inhibiting effects of the intermediate fertility variables. Studies in Family Planning, 13(6-7): Debpuur, C. and A. Bawah Are reproductive preferences stable? Evidence from rural Northern Ghana. GENUS LVIII(2): Doctor, H. V., J. F. Phillips, et al The influence of changes in women's religious affiliation on contraceptive use and fertility among the Kassena-Nankana of northern Ghana. Studies in Family Planning, 40(2): Mbacke, C. and J. F. Phillips Longitudinal Community Studies in Africa: Challenges & Contributions to Health Research. Asia-Pacific Population Journal, 23(3): Nazzar, A., P. B. Adongo, et al Developing a culturally appropriate family planning program for the Navrongo experiment. Studies in Family Planning, 26(6): Phillips, J. F., K. Adazu, et al Denial of contraceptive use among known contraceptive adopters in a rural area of northern Ghana. Annual Meeting of the Population Association of America, March Washington, D.C. 12

13 Phillips, J. F., E. F. Jackson, et al The Long-term Fertility Impact of the Navrongo Project in Northern Ghana. Studies in Family Planning, 43(3): Rosenberg, M.J., P.M. Layde, H.W. Ory, L.T. Strauss, J.B Rooks, and G.L. Rubin Agreement between women s histories of oral contraceptive use and physician records. International Journal of Epidemiology, 12(1): Stover, J Revising the Proximate Determinants of Fertility Framework: What Have We Learned in the Past 20 Years? Studies in Family Planning, 29(3):

14 Table 1. Characteristics of women ages in Kassena-Nankana district, 1995 and Characteristic No. Percent No. Percent Literacy Yes No 698 4, ,859 3, Current Marital Status Not Married Polygynous Monogamous No Information 1,362 1,748 2, ,398 1,216 2, Ethnicity Kassim Nankam Builsa Other 2,762 2, ,994 2, Religion Traditional Christian Muslim Other 3,181 1, ,698 3, Total 5,288 5,840 Note: Data are from the Navrongo Panel Survey System 1995 and Previous publication of 1995 panel data show total of 5,254 women (Bawah 2002) or 5,288 women (Doctor, Phillips et al. 2009). Previous publication of 2003 panel data show total of 5,842 women (Doctor, Phillips et al. 2009). Percentage totals for background characteristics are identical or almost identical in each year. Discrepancies are the result of failure to archive clean datasets and inability to replicate approaches to data cleaning. 14

15 Mobilizing Ministry of Health outreach Mobilizing traditional community organization No Yes Forest Navrongo town Comparison (Cell 4) Zurugelu (Cell 1) Nurse outreach (Cell 2) Zurugelu & nurse (Cell 3) No Comparision Zurugelu 4 1 Yes Nurse outreach Zurugelu & nurse Kilometers N Figure 1. Geographic zones corresponding to CHFP cells in Kassena-Nankana District (Source: Binka, et al. 1995) 15

16 Figure 2. Conceptual diagram used as basis for multivariable analysis Background Characteristics -Married or in union -Ever attended school -Calendar year -Age Other Determinants of Fertility -Pregnant -Experiencing postpartum amenorrhea -Coital Frequency (Not measured) -Fecundability (Not measured) Exposure to CHFP Services -Zurugelu -Nurse -Combined Reported Fertility Regulation Behavior -Exclusively using modern contraceptive method -Exclusively abstinent/using other contraceptive method -Using modern contraceptive and abstinent -No fertility regulation Birth Event Figure 3. The proximate determinants of fertility from panel surveys and predicted expected fertility, compared with observed total fertility rates from demographic surveillance, by experimental cell among women 15-49,

17 Table 2. Odds of having a birth among 11,247 women interviewed in panel surveys from 1994 to 2003, relative to women in the comparison area (Model 1) (Model 2) OR p- value 95% CI OR p- value 95% CI Background Characteristics Married or living together 3.80 p<0.001 (3.31, 4.36) 3.80 p<0.001 (3.31, 4.37) Ever attended school 0.94 p<0.09 (0.87, 1.01) 0.94 p<0.08 (0.87, 1.01) Year 0.99 p<0.07 (0.98, 1.00) 0.99 p<0.07 (0.98, 1.00) Age p<0.001 (5.87, 39.41) p<0.001 (5.85, 39.31) Age squared 0.94 p<0.001 (0.91, 0.96) 0.94 p<0.001 (0.91, 0.96) (Age-20) squared 1.07 p<0.001 (1.03, 1.10) 1.07 p<0.001 (1.03, 1.10) (Age-24) squared 1.00 p<0.96 (0.99, 1.01) 1.00 p<0.96 (0.99, 1.01) (Age-34) squared 1.00 p<0.13 (0.99, 1.00) 1.00 p<0.13 (0.99, 1.00) Other Determinants of Fertility Pregnant 1.78 p<0.001 (1.58, 1.99) 1.78 p<0.001 (1.59, 1.99) Current postpartum amenorrhea 0.37 p<0.001 (0.33, 0.41) 0.37 p<0.001 (0.33, 0.41) Fertility Regulation Behavior Using modern contraceptive only 0.58 p<0.001 (0.50, 0.69) 0.59 p<0.001 (0.45, 0.78) Currently abstinent or using other contraceptive method only 0.80 p<0.001 (0.73, 0.88) 0.84 p<0.001 (0.74, 0.95) Using both modern contraceptive method and abstinence 0.69 p<0.05 (0.49, 0.99) 0.35 p<0.04 (0.13, 0.95) No current fertility regulation behavior (reference) Experimental Exposure Cell 1 zurugelu services 0.78 p<0.001 (0.70, 0.87) 0.81 p<0.01 (0.69, 0.94) Cell 2 nurse outreach 0.88 p<0.02 (0.79, 0.97) 0.90 p<0.17 (0.77, 1.05) Cell 3 combined services 0.80 p<0.001 (0.74, 0.87) 0.84 p<0.001 (0.74, 0.94) Cell 4 comparison (reference) Exposure/Fertility Regulation Interaction Zurugelu X Using modern contraceptive only 0.81 p<0.39 (0.50, 1.31) Zurugelu X Currently abstinent or using other contraceptive method only 0.94 p<0.63 (0.74, 1.20) Zurugelu X Using both modern contraceptive method and abstinence 2.63 p<0.13 (0.75, 9.19) Nurse X Using modern contraceptive only 0.93 p<0.79 (0.54, 1.59) Nurse X Currently abstinent or using other contraceptive method only 0.95 p<0.65 (0.76, 1.19) Nurse X Using both modern contraceptive method and abstinence 1.95 p<0.34 (0.50, 7.58) Combined X Using modern contraceptive only 1.05 p<0.78 (0.74, 1.51) Combined X Currently abstinent or using other contraceptive method only 0.88 p<0.16 (0.74, 1.05) Combined X Using both modern contraceptive method and abstinence 2.13 p<0.19 (0.69, 6.56)

18 Table 3. The relative odds of having a birth among 11,247 women interviewed in panel surveys from 1994 to 2003, by treatment exposure and fertility regulation behavior, in contrast to women in the comparison area reporting the same fertility regulation behavior Cell 1: Zurugelu (Volunteer) Cell 2: Community Nurse Cell 3: Zurugelu + Nurse Cell 4: Comparison Group A: Exclusively using modern contraceptive method OR = 0.66 (0.42, 1.03) p = OR = 0.83 (0.50, 1.39) p=0.483 OR = 0.88 (0.63, 1.23) p=0.455 OR = 1.0 (Reference) Group B: Postpartum abstinent and/or using another method and not using a modern method OR = 0.76 (0.64, 0.91) p <0.001 OR = 0.85 (0.73, 0.999) p=0.048 OR = 0.74 (0.64, 0.84) p<0.001 OR = 1.0 (Reference) Group C: Postpartum abstinent and using a modern method OR = 2.13 (0.62, 7.36) p=0.231 OR = 1.75 (0.46, 6.71) p=0.415 OR = 1.78 (0.58, 5.45) p=0.316 OR = 1.0 (Reference) Group D: No Fertility Regulation OR = 0.81 (0.69, 0.94) P<0.001 OR = 0.90 (0.77, 1.05) p=0.170 OR = 0.84 (0.74, 0.94) P<0.001 OR = 1.0 (Reference) Table 4. Illustration of hypothetical effect of lower denial rates and higher modern contraceptive (MC) prevalence in experimental areas versus the comparison Women using MC Use of MC Reported Use of MC Denied Women not using MC Non-use Reported Percent reporting no use but using MC TOTAL CHFP Service Areas Comparison Area % (15 of 85) % (10 of 100) 100