Factors Associated with Contraceptive Use among

Factors Associated with Contraceptive Use among Women of Reproductive Age in Rural Districts of Burkina Faso Joseph K. Wulifan, Jacob Mazalale, Albrecht Jahn, Hervé Hien, Patrick Christian Ilboudo, Nicolas Meda, Paul Jacob Robyn, Saidou Hamadou, Ousmane Haidara, Manuela De Allegri Journal of Health Care for the Poor and Underserved, Volume 28, Number 1, February 2017, pp. 228-247 (Article) Published by Johns Hopkins University Press DOI: https://doi.org/10.1353/hpu.2017.0019

For additional information about this article https://muse.jhu.edu/article/648757

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ORIGINAL PAPER

Factors Associated with Contraceptive Use among Women of Reproductive Age in Rural Districts of Burkina Faso Joseph K. Wulifan, PhD, MSc Jacob Mazalale, PhD, MSc Albrecht Jahn, Prof, PhD, MD Hervé Hien, PhD, MPH, MD Patrick Christian Ilboudo, PhD, MSc Nicolas Meda, Prof, HDR, PhD, MD Paul Jacob Robyn, PhD, MSc Saidou Hamadou T, MSc Ousmane Haidara, MD, MPH Manuela De Allegri, PhD, MSc Abstract: Given the current low contraceptive use and corresponding high levels of unwanted pregnancies leading to induced abortions and poor maternal health outcomes among rural populations, a detailed understanding of the factors that limit contraceptive use is essential. Our study investigated household and health facility factors that influence contraceptive use decisions among rural women in rural Burkina Faso. We collected data on fertile non-pregnant women in 24 rural districts in 2014. Of 8,657 women, 1,098 used a modern contraceptive. Women having a living son, a child younger than one year, and household wealth were more likely to use modern contraceptives. Women in polygamous marriages and women living at least 5 kilometers from a health facility were less likely to use contraception. We conclude that modern contraceptive use remains weak, hence, programs aiming to encourage contraceptive use must address barriers at both the health facility and the household level. Key words: Contraceptive use, family planning, sub-Saharan Africa, Burkina Faso.

JOSEPH K. WULIFAN is affiliated with the Institute of Public Health, Faculty of Medicine, Heidelberg University, Germany, and School of Business & Law, University for Development Studies in Ghana. JACOB MAZALALE is affiliated with the Institute of Public Health, Faculty of Medicine, Heidelberg University, and the School of Public Health and Family Medicine, College of Medicine, University of Malawi, Blantyre, Malawi. ALBRECHT JAHN and MANUELA DE ALLEGRI are affiliated with the Institute of Public Health, Faculty of Medicine, Heidelberg University. HERVÉ HIEN, PATRICK CHRISTIAN ILBOUDO and NICOLAS MEDA are affiliated with Centre MURAZ, in Bobo-Dioulasso, Burkina Faso. PAUL JACOB ROBYN, SAIDOU HAMADOU and OUSMANE HAIDARA T are affiliated with the World Bank in Ouagadougou, Burkina Faso. Please send correspondence to Joseph K. Wulifan, School of Business & Law, University for Development Studies, Box 36, Wa, Ghana; Email: [email protected].

© Meharry Medical College

Journal of Health Care for the Poor and Underserved 28 (2017): 228–247.

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amily planning is defined as a conscious effort by couples to space or limit the number of children they have.1,2 Although knowledge on contraception in most low and middle income countries (LMICs) has increased over the last few decades, access to contraception use is still problematic for many women who wish to space or limit child birth.1,2 As a result, most LMICs, particularly those in Asia, the Middle East, the Caribbean, and sub-Saharan Africa, are still characterized by low contraceptive prevalence and generally high fertility rates.3–6 Although in these settings reproductive health policies and family planning programs started already in the early 1960s, women often continue to have more children than they wish to.3,7 In spite of existing family planning programs, one in three women who desire to postpone or limit child birth still has limited access to contraception use.4,6,8,9 In most LMICs, non-use of contraceptives results in unintended pregnancies (mistimed/unwanted at time of conception) and high fertility rates,10,11 with important consequences for women’s and children’s health, population growth, and ultimately for economic development.3,7 Specifically, countries in sub-Saharan Africa (SSA) are characterized by particularly low rates of contraceptive prevalence, which result in high fertility rates, ultimately shaping a continuous trend towards population growth. In 2013, the region reported a total fertility rate (TFR) of 5.1, equivalent to roughly twice the rate recorded in South Asia (2.8) and in Latin America and the Caribbean (2.2). In SSA, only two out of five women report using a modern method of contraception, compared with one out of two in South Asia and three out of four in East Asia.9 Still, estimates computed at the continental level conceal important differences reported at the country level, with ongoing fertility transitions already taking place in selected settings, such as Ghana and Kenya where total fertility rates have dropped to 4.2 and 4.4 respectively.12 Just to highlight existing differences across settings, contraceptive prevalence is estimated at 27% in Ghana, 20% in Liberia, 10% in Mali, 14.5% in Niger, 15% in Nigeria, and 22% in Senegal.11,13 In general, low contraceptive use has been attributed to a mixture of socio-economic and cultural factors impeding access to modern family planning methods.14 Low contraceptive use seems to continue to prevail in spite of governments’ explicit efforts to promote family planning measures as a means of curbing further population growth.15 Research efforts have mostly been channeled towards assessing contraceptive use and/or unmet need for family planning, but limited attention has been paid to assessing jointly the effect of individual, household, and health system factors on the decision not to use a modern method of family planning. A recent scoping review identified the persistence of a substantial knowledge gaps in understanding reasons shaping decisions to use or not to use modern contraceptives across different SSA settings. In particular, the review identified the need for continuous research and for context-specific research, given that both ongoing socio-political and economic changes and the overall socio-cultural setting shape women’s decisions to use or not to use modern contraceptives. The lack of sound evidence concerning how individual, household, and health system factors interact to shape women’s decisions to use or not to use modern contraceptives is particularly acute in Burkina Faso, the country at the core of our study. Studies based in Burkina Faso have mostly focused on understanding causes and consequences

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of unintended pregnancies and induced abortions16 rather than on women’s use of contraceptives. The only two studies looking specifically at factors associated with contraceptive use in Burkina Faso are outdated, since they were published in 2001 and 2005,17,18 and may therefore no longer reflect the reality of women living in this country. The need for evidence in this setting is profound. With a population of 18 million people, Burkina Faso is one of the fastest growing nations in West Africa.12 Reproductive health indicators portray an unpleasant picture. The 2010 Demographic Health Survey reported that almost one in two women starts childbearing by age 18.19 Currently, Burkina Faso has an average total fertility rate of 6.0 children per woman and a relatively low rate of modern contraceptive use, estimated at 16% among women of reproductive age.12,16 As a consequence of low contraceptive use, an estimated 29% of women face an unmet need for family planning, defined in relation to women not using a modern contraceptive method in spite of their wish to limit or delay childbirth.12,16 Substantial differences in contraceptive use have been reported across rural and urban settings in Burkina Faso.9,20 This study sought to fill this gap in knowledge by simultaneously examining demand-side and supply-side factors associated with contraceptive use in rural Burkina Faso. Findings are expected to guide policy makers to identify policy and implementation gaps and design adequate programs aimed at increasing contraceptive use to reduce maternal mortality and improve maternal health outcomes.

Methods Study setting: We used data from the baseline round of a survey set to evaluate the impact of a forthcoming performance-based financing (PBF)21 intervention on access to and quality of a wide range of health care services. Specifically, we used data from both the household survey and the health care workers’ survey embedded within the larger set of tools needed for the impact evaluation. These surveys were applied in the 24 districts distributed in six regions of Burkina Faso (Boucle du Mouhoun, Centre-Est, Centre-Nord, Centre-Ouest, Nord, and Sud-Ouest) where PBF was to be rolled out starting in April, 2014. Study design, sample size and data collection: Data were collected from October 2013 to March 2014. The household survey relied on a three-stage cluster sampling technique. First, clusters were defined to reflect the catchment areas of the 448 health facilities (primary health care facilities, district hospitals, and regional hospitals) present in the 24 districts. Second, one village was randomly selected (among all villages in the catchment area) in each of the 448 catchment areas. Third, 15 households were selected in each village. Households were selected on the basis of whether there was a woman living in the household who was currently pregnant, had been pregnant or had a delivery in the 24 months prior to the survey date. Households were selected using a random route approach until the desired sample size was achieved in each village. Specifically, interviewers began their selection by tossing a bottle in a randomly selected spot in the village and then interviewing households in the indicated direction until achieving the desired sample size.22 The total sample included 6,720 households. Within a household, information was collected on the overall household socio-demographic

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and economic profile as well as on individual illness patterns, health care-seeking behavior, and related expenditure (for both adults and children). Specifically, given our focus on contraceptive use among fertile non-pregnant women, we considered as the effective sample for this study the 8,657 currently fertile and non-pregnant women included in the household survey. The fertile and non-pregnant women were asked whether they had used any modern contraceptive method within the past six months to delay or limit childbirth. The health care workers’ survey targeted staff working at all the 448 facilities included in the study. Specifically, at each facility, the aim was to interview at least three health care workers. Respondents were conveniently selected as the staff present in the facility on the day of the survey. Information was collected by means of a structured, closed-ended questionnaire with several modules, covering health care workers’ roles and responsibilities, their work environment, their training specific to family planning, and facility assessment on availability of modern family planning methods. Data collection was carried out by trained interviewers recruited and supervised by senior researchers from University of Heidelberg and from Centre MURAZ. The household survey relied on digital data collection using personal digital assistants (PDAs/mini-computers) with data being sent to a central server located in Centre MURAZ on a daily basis using a mobile phone connection. The health care workers’ survey relied on a traditional pen and paper method, followed by double independent data entry directly at Centre MURAZ. Study variables: Table 1 reports the complete list of variables included in our analysis, their distribution in the sample, and the expected direction of the estimated coefficient. Information from the two surveys was merged into one dataset (matched at the health facility level) to account for the fact that a mixture of demand-side (i.e., pertaining to women, their partners, and their households) and supply-side (i.e., pertaining to health system) factors are expected to influence contraceptive use among women.23,24 The outcome was defined as a dichotomous variable, differentiating between contraceptive users (coded as 1) and non-users (coded as 0). A fertile and non-pregnant woman was defined as contraceptive user if she indicated using a modern contraceptive method to limit or delay pregnancy. A fertile and non-pregnant woman was defined as contraceptive non-user if she indicated not using a modern contraceptive method to limit or delay pregnancy.25 Most of the independent variables included in Table 1 are self-explanatory. The number of living children was categorized into two groups with the classification being consistent with prior studies.26,27 We looked at sons living as important in relation to contraceptive use decisions. In most patriarchal societies, male children are required to maintain the family lineage and therefore women are expected to give birth to male children.1,23,7,23,24 In line with prior research,28 household socioeconomic status was assessed by computing a wealth index based on a combination of housing infrastructure and ownership of mobile goods using multiple correspondence analysis (e.g., ownership of land/house, durable goods, animals). In line with our own prior research,29 four variables, referred to in the literature as proximate variables, were included as measures of a woman and her partner’s attitude and decision making concerning contraceptive use. Proximate variables are intermediate

Table 1. VARIABLES DISTRIBUTION IN THE STUDY SAMPLE AND THEIR EXPECTED COEFFICIENT SIGN N = 8,657

Variables Outcome: Contraceptive use Explanatory: Woman’s age Number of children: Number of living sons: Experienced death of a child: Children less than 1 year:

Marriage type: Woman religion: Wealth index

Residence Woman’s approval of contraceptive use Partner’s approval of contraceptive use Couple discussion on contraceptive use Desired number of children (Woman vs Man) Distance to Health Facility

Measurement

Expected coefficient sign

N

%

0 = non-contraceptive users 1 = contraceptive users

7,559 1,098

87.32 12.68

NA

15–49 years (continuous) [mean/SD] 0 = Fewer than 4 children 1 = 4 and more children 0 = No living son 1 = At least one living son 0 = Did not experience child’s death 1 = Experienced child’s death 0 = Has no child younger than 1 year 1 = Has a child younger than 1 year 0 = Monogamy 1 = Polygamy 0 = Muslim 1 = Christian 1 = Poorest 2 = Second quintile 3 = Middle quintile 4 = Fourth quintile 5 = Least poor 0 = Urban 1 = Rural 0 = Approve 1 = Disapprove 0 = Approve 1 = Disapprove 0 = Never 1 = At least once 0 = Same 1 = Other

27.89

7.55

+

6,771 1,886 2,151 6,506 6,972

78.21 21.79 24.85 75.15 80.54

1,685 605

19.46 6.99

8,052

93.01

+

5,005 3,652 5,542 3,115 1,516 1,572 1,688 1,868 2,013 672 7,985 6,712 1,945 4,230 4,427 4,370 4,287 3.615 5,042

57.81 42.19 64.02 35.98 17.51 18.16 19.50 21.58 23.25 7.76 92.24 77.53 22.47 48.86 51.14 50.48 49.52 41.76 58.24

+

0 = Less than 5km 1 = 5 or more km

+ – +

– –

+ + + + + +

4,340 50.13 + 4,317 49.87 (Continued on p. 233)

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Table 1. (continued)

Variables Barrier contraceptives Hormonal contraceptives IUD contraceptives Health worker training on FP Health worker training on FP logistics

Measurement 0 = Not available 1 = Available 0 = Not available 1 = Available 0 = Not available 1 = Available 0 = Not trained 1 = Trained 0 = Not trained 1 = Trained

N 1,198 7,459 1,020 7,637 6,012 2,645 5,778 2,879 7,476 1,181

% 13.84 86.16 11.78 86.16 69.45 30.55 66.74 33.26 86.36 13.64

Expected coefficient sign

+ + + + +

variables that focus on attitudes and decision making.3,6,30 In our analysis, these variables included: woman’s approval of contraceptive use; partner’s approval of contraceptive use; couple discussion on family planning; and desire for children with partner. Their inclusion was motivated by the existence of prior evidence suggesting that partners’ involvement in family planning decisions is an important factor in shaping women’s reproductive behavior. Evidence indicates that most women positively adopt family planning methods when they perceive their partner’s approval of contraceptive use.23,24 A set of variables from the health facility assessment and from the health care provider survey was included to account for health system factors likely to influence contraceptive use. Distance to the referral health facility was assessed around the cut-off point of five kilometers, in line with WHO guidelines on accessibility.31,32 We included a measure of the contraceptives available at each facility, distinguishing between barrier contraceptives, hormonal contraceptives, and IUD. We included two variables to assess health care providers’ training, one looking at general training in family planning and the other looking more specifically at logistics (procurement and stocking) concerning family planning products. Analytical approach: We analyzed the data using a sequential approach, defined in relation to two steps. First, we employed bivariate analysis to explore the relationship between contraceptive use and each of the explanatory variables. Then, we employed hierarchical multivariate logistic regression to verify the associations detected with the bivariate analysis while controlling for potential confounding. We applied random effects modeling because we observed large variations in the contraception prevalence rate across districts, therefore we assumed women to be clustered at the district level. We estimated the odds of a woman using contraceptives in a household ( jth) living in a particular district (dth). The hierarchical logistic regression model can be written as a linear function of the explanatory variables in the form;

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Contraceptive use in Burkina Faso Logit(yjd) = α + β1jdx1jd + β2jdx2jd + β3jdx3jd + , . . . , + βzjdxzjd + δd

Where (yj) is the log (to base e) of the odds ratio (OR) of a woman is 1, α is a random effect model intercept making up of two terms; δd fixed effects component for district d and d is the district. x1jd, x2jd, x3jd, and xzjd are exponential variables at the individual and district level. β1jd, β2jd, β3jd, and βzjd are regression coefficients. The multilevel logistic regression assisted in identifying significant associations between the explanatory variables and contraceptive use, while controlling for potential confounders (individual woman characteristics, household and health facility factors— all variables included in Table 1). Specifically, we used the Stata command xtlogit.33,34 The application of multilevel (random-effect) modelling was preferred as it accounted for the fact that women were clustered at the district level. Preliminary analysis had in fact detected important differences in contraceptive use across districts (Table 2). Ethics approval: The study protocol was approved by the Ethics Committee of the Faculty of Medicine of the University of Heidelberg, Germany (protocol number S-272/2013) and by the Ethics Committee of the Ministry of Health in Burkina Faso (protocol number 2013-7-066). All women were informed on the objectives and modalities of the study and signed an informed consent form prior to the interview. Community and district leaders were also informed of the study and consented to it. The baseline results were systematically shared with stakeholders and representatives from the World Bank and Centre MURAZ including representatives from the National, Regional, and District levels. Open and active interaction with the participants from the research area was meant to shape future research policy and to establish rapport with research communities.

Results Descriptive analysis: The household survey reached a total of 10,001 women aged 15 to 49 years, who were either currently pregnant or had a delivery/child in the prior 24 months. Of these 10,001 women, 1,309 women were pregnant while 8,692 women were not pregnant. Among the non-pregnant, 35 women were infertile, leaving us with an effective sample of fertile non-pregnant women of 8,657. Of the currently non-pregnant and fertile women, 1,098 (12.68%) were using a modern contraceptive. Table 2 reports important differences in contraceptive use across regions and districts. Women in Centre-Nord reported the highest prevalence of contraceptive use (18.49%), closely followed by Boucle du Mouhoun and Sud-Ouest with a prevalence of 14.79% and 14.69% respectively. Centre-Ouest and Nord regions recorded the lowest contraceptive use prevalence of 9.09% and 9.13%. Contraceptive use across study districts was highest among women in Zabré (22.41%), Ziniaré (22.12%), Boromo (21.05%), Kongoussi (19.37%) and Ouargaye (17.47%). The districts with low contraceptive use prevalence included Tenkodogo (5.01%), Nanoro (4.88%), Yako (4.40%), with Boussé (4.11%) being the absolute lowest. Multivariate analysis: The second set of results in Table 3 report multivariate analyses on contraceptive use. The multivariate analyses comprised the bivariate (unadjusted) and the multilevel logistic regression models. From the bivariate results, a positive

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Table 2. CONTRACEPTIVE USE BY REGION AND DISTRICT Non-users N (%)

Users N (%)

Boucle Du Mouhoun

7,559 (87.32) 1,244 (85.21)

1,098 (12.68) 216 (14.79)

Centre-Est

1,015 (88.11)

137 (11.89)

Centre-Nord

1,411 (81.51)

320 (18.49)

Centre-Ouest

1,490 (90.91)

149 (9.09)

Nord

1,911 (90.87)

192 (9.13)

Region

Sud-Ouest

488 (85.31)

84 (14.69)

District

Non-users N (%)

Users N (%)

Boromo Nouna Solenzo Toma Manga Ouargaye Tenkodogo Zabre Barsalgho Kaya Kongoussi Ziniare Koudougou Nanoro Reo Sapouy Bousse Gourcy Ouahigouya Yako Batie Dano Diebougou Gaoua

7,559 (87.32) 120 (78.95) 504 (87.35) 493 (84.56) 127 (85.81) 142 (90.45) 411 (82.53) 417 (94.99) 45 (77.59) 49 (87.50) 636 (83.25) 483 (80.63) 243 (77.88) 909 (91.82) 78 (95.12) 212 (89.45) 291 (88.18) 210 (95.89) 422 (88.66) 1,018 (89.69) 261 (95.60) 122 (85.92) 53 (86.89) 245 (84.48) 68 (86.08)

1,098 (12.68) 32 (21.05) 73 (12.65) 90 (15.44) 21 (14.19) 15 (9.55) 87 (17.47) 22 (5.01) 13 (22.41) 7 (12.50) 128 (16.75) 116 (19.37) 69 (22.12) 81 (8.18) 4 (4.88) 25 (10.55) 39 (11.82) 9 (4.11) 54 (11.34) 117 (10.31) 12 (4.40) 20 (14.08) 8 (13.11) 45 (15.52) 11 (13.92)

association was detected between women having a living son [OR = 1.67; 95% CI (1.42–1.97)], having a child younger than one year [OR = 5.71; 95% CI (3.46–9.42)], couples having family planning discussions at least once [OR = 2.27; 95% CI (1.98–2.59)], household wealth, and contraceptive use. A negative association was detected between being in a polygamous marriage [OR = 0.66; CI (0.57–0.75)], a woman’s disapproval of contraceptive use [OR = 0.11; CI (0.81–0.15)], partner disapproval of contraceptive use [OR = 0.19; CI (0.16–0.23)], living within five kilometers and beyond to a health facility [OR = 0.74; 95% CI (0.65–0.84)] and contraceptive use. Multilevel analysis: Table 3 reports estimates from the multilevel logistic regression. We detected a positive association between women having a living son [OR = 1.28; 95% CI (1.06–1.56)], having a child younger than one year [OR = 3.73; 95% CI (2.17–6.39)], couple who in the last six months had discussions on family planning for at least once [OR = 1.95; 95% CI (1.69–2.25)], household wealth, and contraceptive use. A

Table 3. ODDS RATIO ESTIMATES FOR THE MULTIVARIATE ANALYSIS ON CONTRACEPTIVE USE Unadjusted Simple logit

Adjusted Multilevel logistic regression

Variables

OR

CI

OR

CI

Woman’s age (continuous)

1.00 1.00

0.99–1.01

1.00 0.99

0.98–1.00

1.00 1.06

0.91–1.24

1.00 1.06

0.86–1.30

1.00 1.67

1.42–1.97

1.00 1.28

1.06–1.56

1.00 1.00

0.85–1.18

1.00 0.94

0.79–1.13

1.00 5.71

3.46–9.42

1.00 3.73

2.17–6.39

1.00 0.66

0.57–0.75

1.00 0.79

0.67–0.92

1.00 1.07

0.94–1.22

1.00 1.15

0.98–1.36

1.00 1.12 1.39 1.64 2.23

0.88–1.44 1.10–1.76 1.31–2.05 1.80–2.76

1.00 1.19 1.43 1.83 2.43

0.92–1.55 1.12–1.84 1.44–2.33 1.92–3.07

1.00 0.80

0.64–1.00

1.00 0.85

0.66–1.10

1.00 0.11

0.08–0.15

1.00 0.30

0.21–0.42

1.00 0.19

0.16–0.23

1.00 0.28

0.23–0.34

1.00 2.27

1.98–2.59

Number of children: Less than 4 children 4+ children Number of living sons: No living son At least one living son Experienced death of a child: Did not experience child’s death Experienced child’s death Children less than 1 year: Has no child younger than 1 year Has a child younger than 1 year Marriage type: Monogamy and others Polygamy Woman religion: Muslim Christianity & others Wealth index: Poorest Second quintile Middle quintile Fourth quintile Least poor Residence Urban Rural Woman approval of contraceptive use Approve Disapprove Partner’s approval of contraceptive use Approve Disapprove Couple discussion on contraceptive use Never At least once

1.00 1.95 1.69–2.25 (Continued on p. 237)

Table 3. (continued) Unadjusted Simple logit Variables Desired number of chn (Woman vs Man) Same Others Distance to Health Facility Less than 5km 5+km Barrier contraceptives Not available Available Hormonal contraceptives Not available Available IUD contraceptives Not available Available Health worker training on FP Not trained Trained Health worker training on FP logistics Not trained Trained rho Variance Standard deviation Log-likelihood Wald chi2(16); p > chi2/Wald chi2(22); p > chi2 Likelihood-ratio test of rho (Chibar2(01); p> = chibar2 Chi2 (df);p > chi2 Pseudo R-square Observations Clusters (Districts)

Adjusted Multilevel logistic regression

OR

CI

OR

CI

1.00 0.53

0.46–1.60

1.00 1.03

0.88–1.20

1.00 0.74

0.65–0.84

1.00 0.69

0.60–0.80

1.00 0.94

0.79–1.13

1.00 0.95

0.64–1.43

1.00 0.99

0.81–1.20

1.00 0.99

0.63–1.56

1.00 0.88

0.76–1.01

1.00 0.93

0.76–1.13

1.00 1.02

0.89–1.16

1.00 1.06

0.89–1.26

1.00 0.94

0.78–1.14

1.00 0.85

0.67–1.07

0.0697161 –1.40 0.49

NB: Adjusted for individual woman, household and health facility variables.

0.03–0.13 –2.14–0.65 0.34–0.71 –2790.3387 626.51; 0.00 88.96; p < 0.001 915.28 < 0.0001 0.1390 8,657 24

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negative association was detected between being in a polygamous marriage [OR = 0.79; CI (0.67–0.92)], woman’s disapproval of contraceptive use [OR = 0.30; CI (0.21–0.42)], partner disapproval of contraceptive use [OR = 0.28; CI (0.23–0.34)], living at least five kilometers away from a health facility [OR = 0.69; 95% CI (0.60–0.80)] and contraceptive use. Apart from distance to health facility, we did not detect any significant difference between contraceptive use and health facility factors. The Model reported a Rho of 0.697161, statistically significant at p < .001. This value is a reflection of residual heterogeneity in contraceptive use across districts, which could not be accounted for and explained by the explanatory variables included in the model.

Discussion Our study makes a unique contribution to the literature since it is one of very few studies explicitly assessing both demand and supply-side factors associated with contraceptive use in Burkina Faso specifically, and in sub-Saharan Africa more generally.17,18,24 Our study detected the prevalence for contraceptive use at 12.6%, a value that is slightly lower than what is generally reported in literature on Burkina Faso, where the rate of contraceptive use prevalence has been estimated at 16%.12,16,35,36 Differences between our estimates and previously published estimates may be due to differences in the estimation method used (assessing contraceptive use among fertile women who had a pregnancy or delivery in the prior 24 months vs. assessing contraceptive use among all fertile non-pregnant women). In our study we estimated contraceptive use among a population of fertile non-pregnant women who had a pregnancy or a delivery in the prior 24 months captured by the study, while prior studies estimated contraceptive prevalence among the population of all fertile non-pregnant women.37,38 In addition, we must acknowledge the effect that our predominantly rural sample (over 90%) could have had on the estimate. It is a known fact that fertility rates motivated by a desire for children are generally higher in rural communities.16 This could have contributed to the generation of lower estimates than what was observed in more balanced rural-urban samples. Further population-based studies specific to Burkina Faso are needed to confirm the value of our hypothesis, justifying the lower rate of contraceptive use observed in our study. With less than one in eight women reporting use of modern contraceptives, our study clearly indicates that contraceptive use is still well below desirable standards.12 The low contraceptive prevalence rate observed represents an important reason for concern from a population perspective. Women who do not use contraceptives are often the focus of family planning programs because they exhibit a discrepancy between their fertility intentions and contraceptive use.39,40 Contraceptive non-use bears important consequences for a woman and her family, including unwanted pregnancies, unsafe abortions, and poor maternal health outcomes. Ultimately, contraceptive use among rural women is likely to result in significant improvements in women’s health while also limiting further population growth to enable the country to overcome some of the challenges to sustainable development.16,23 In addition to estimating the contraceptive prevalence rate among rural communities in the country, our study identified some important factors shaping decisions related

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to contraceptive use. On the one hand, having a son, having a child younger than one year, being less poor and having discussed family planning at least once as a couple were all factors positively associated with contraceptive use. On the other hand, being in a polygamous marriage, own disapproval of contraceptive use, a partner’s disapproval of contraceptive use and the distance to a health facility were all factors negatively associated with contraceptive use. The positive association between having a living son and contraceptive use is consistent with existing literature41–44 and can be explained in relation to the fact that in many sub-Saharan African contexts, bearing male children is still an important determinant of women’s status in a given society.45,46 Available evidence points to the fact that in strongly patriarchal societies where more prominence is placed on male sons, women will continue to give birth until they have a male child.45–49 Modifying this behavior requires interventions that reach beyond the mere provision of family planning methods through the health system, since it requires altering social representations of women’s status and values within society as a whole. Our finding that women with children below one year were more likely to use a modern contraceptive method is similarly consistent with the literature.50 This finding is suggestive of the existence of programs that adequately target the period immediately following childbirth. In turn, in spite of an overall low contraceptive prevalence rate, this provides indication of good clinical practices. Evidence shows that the childbirth interval should be at least two years,37,51 since closely spaced births are associated with increased morbidity and mortality for both mothers and their babies.37,52 The association observed between higher household socio-economic status and a greater probability that modern contraceptives are used was also not surprising and well aligned with the bulk of existing literature.30,53–56 The association between wealth and contraceptive use can be explained in relation to increased access to the financial means needed actually to purchase contraceptives.53,54 It must be noted that use of modern family planning in SSA entails a financial commitment from the user, especially in contexts like Burkina Faso where provision of contraceptives occurs within the framework of health services subject to the payment of user fees. In line with prior evidence,57,58 the association observed between increased distance and reduced probability of contraceptive use suggests that the need to travel to a distant health facility further increases both direct and indirect costs incurred by women to obtain contraceptives, imposing an additional barrier on access. Available evidence suggests that proximity and free access to family planning services predisposes women to modern contraceptive use in most rural settings.59–61 Consistent with our finding, three prior studies from SSA found that women in polygamous unions were more pronatalist and for that matter less likely than their monogamous peers to limit or delay childbearing.62–64 A plausible explanation for this finding, which contradicts our original hypothesis, could be that, due to the many wives, women in polygamous marriages might enjoy less decision-making autonomy over their bodies vis à vis their partners. In a context where households face considerable costs to access modern contraceptives, increased complexity over intra-household allocation of resources in polygamous (and therefore larger) households may also explain these observed lower utilization rates. Efforts should therefore be explicitly channeled towards

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reaching out to women in polygamous unions to understand what additional barriers to access they face and empower them to overcome these barriers. Not surprisingly, both women’s and their partners’ disapproval of contraceptive use were observed to be associated with a reduced probability of using a modern contraceptive. Our findings are consistent both with prior evidence from Ethiopia24,65 and from Ghana,66,67 pointing at the strong influence that partners’ opinions hold on women’s reproductive choices. Prior research has indicated that men are often hesitant to approve of contraceptive use out of fear of losing their role as heads of the family or indirectly encouraging their spouses to be promiscuous.45,46,48,49 This suggests an urgent need to broaden family planning efforts to target couples rather than women alone, reaching out to men to encourage a behavioural shift on their part as well.54,60 Proof that this approach may yield its benefits comes from the fact that both our study and prior research identified a positive association between couple discussion on family planning and increased contraceptive use.20,24 Surprisingly, in spite of our explicit wish to explore jointly supply-side and demandside factors, our findings did not identify any statistically significant association between use of modern contraceptives and features of health service provision. In light of prior evidence,33 we would have expected to observe an effect. Our inability to detect an effect at this level could be attributed partially to two factors. On one side, we might have selected health service variables that were not relevant in shaping the outcome of interest. Still, our selection was constrained by the data available in the health facility assessment. On the other side, one could also consider that demand-side rather than supply-side factors shape decisions on contraceptive use in Burkina Faso, suggesting that supply is of sufficient quality to provide adequate availability of family planning services to those who wish to use them. Further qualitative inquiry is required to understand better what factors might have shaped our quantitative results. Methodological considerations: As we appraise the generalizability of our findings, we need to acknowledge the possibility that the associations observed between selected explanatory variables and contraceptive use may be context-dependent and not necessarily applicable to other LMICs, even within sub-Saharan Africa. It is possible that additional explanatory variables not available in our datasets may also be relevant in shaping decisions on contraceptive use. Still, the range and scope of the variables included in our study were consistent with prior research. Similarly, we ought to recognize the intrinsic bias of an analysis that relies exclusively on quantitative methods, thus making it impossible for the research team to investigate the role of unmeasurable dimensions, such as cultural beliefs and values. Last, we must consider the approach adopted in estimating contraceptive prevalence using a population of only currently non-pregnant fertile women who had a pregnancy or delivery in the prior 24 months. It would have been desirable to extend the estimation to cover the entire population of fertile non-pregnant women of reproductive age, but this was not possible due to the specific sampling techniques adopted to suit the broader study objectives of health service quality, use among pregnant women and women who had a delivery or a child in the prior 24 months (i.e., the impact evaluation of the forthcoming PBF program). Last, we need to recognize the existence of residual variance due to district characteristics not measurable in a quantitative survey. Fur-

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ther qualitative inquiry is urgently needed to shed light on which features at the district level can explain the observed geographical heterogeneity in use of modern contraceptives. Conclusion: Contraceptive use is important in its own right. It is an established fact that use of modern contraceptives reduces unintended pregnancy and unsafe abortions, and by doing so helps to curb maternal and neonatal mortality and morbidity. It is important to acquire a detailed understanding of women’s fertility intentions to ensure an adequate extension of family planning services that meet women’s needs and preferences. With fewer than one in every eight women using modern contraceptives, our study detects some of the lowest rates reported in low-income settings with socio-demographic characteristics similar to those of Burkina Faso.68 This points to an urgent need to expand family planning efforts, specifically targeting women from lower socio-economic strata, those living at a greater distance from health facilities, and those in polygamous unions. Community-based family planning interventions should be considered as an accompanying measure to strengthen current service provision and reach a larger number of women.69,70 Enhancing women’s access to family planning is instrumental in counteracting the current trend in low contraceptive use in Burkina Faso.

Declaration Data Sharing The original data from which this study was developed are available in the university database. The STATA and Excel data files for this analysis were uploaded together with the manuscript. Competing interest The survey data used in preparing this manuscript was financed by the World Bank’s Health Results Innovation Trust Fund (HRITF). The salaries of all other authors from the World Bank and the Center MURAZ were paid for by the World Bank whilst this study was planned and carried out, and during the preparation of this manuscript. JKW, JM, AJ and MDA declare no competing interests. Authors’ contribution JKW and MDA conceptualized the study design, defined the analytical model and drafted the manuscript. JKW carried out the analysis with guidance from MDA. JM assisted in cross checking variables in STATA and the results. MDA, AJ contributed in shaping the study to reflect regional and global context. HH, PCI, NM, PJR, SH, and OH contributed to tool development and were in charge of data collection. All authors contributed substantially to shaping the final draft of the manuscript.

Acknowledgments This work was supported by the World Bank through the Health Results Innovation Trust Fund (HRITF). The findings, interpretations and conclusions expressed in the

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paper are entirely those of the authors, and do not represent the views of the World Bank, its Executive Directors, or the countries they represent. We wish to thank our partners at the Ministry of Health in Burkina Faso for helping develop the study methodology and tools, and facilitating data collection. The author is also grateful to the respondents who agreed to participate in this survey, the Katholische Akademische Ausländer-Dienst (KAAD) for supporting the author with a student stipend during his studies in Germany and Dr. Aurélia Souares, the project coordinator at the University of Heidelberg for the four hours per month student financial support/contract throughout the project period.

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