Determinants of unmet need for family planning in rural Burkina Faso: A multilevel logistic regression analysis

BMC Pregnancy and Childbirth, Volume 17, No. 1, Year 2017

Interprétation

Background: Unmet need for family planning has implications for women and their families, such as unsafe abortion, physical abuse, and poor maternal health. Contraceptive knowledge has increased across low-income settings, yet unmet need remains high with little information on the factors explaining it. This study assessed factors associated with unmet need among pregnant women in rural Burkina Faso. Method: We collected data on pregnant women through a population-based survey conducted in 24 rural districts between October 2013 and March 2014. Multivariate multilevel logistic regression was used to assess the association between unmet need for family planning and a selection of relevant demand- and supply-side factors. Results: Of the 1309 pregnant women covered in the survey, 239 (18.26%) reported experiencing unmet need for family planning. Pregnant women with more than three living children [OR = 1.80; 95% CI (1.11-2.91)], those with a child younger than 1 year [OR = 1.75; 95% CI (1.04-2.97)], pregnant women whose partners disapproves contraceptive use [OR = 1.51; 95% CI (1.03-2.21)] and women who desired fewer children compared to their partners preferred number of children [OR = 1.907; 95% CI (1.361-2.672)] were significantly more likely to experience unmet need for family planning, while health staff training in family planning logistics management (OR = 0.46; 95% CI (0.24-0.73)] was associated with a lower probability of experiencing unmet need for family planning. Conclusion: Findings suggest the need to strengthen family planning interventions in Burkina Faso to ensure greater uptake of contraceptive use and thus reduce unmet need for family planning. The study used data from the baseline round of a survey which included multiple tools in order to evaluate the impact of a performance-based financing (PBF) intervention on access to and quality of a wide range of healthcare services. Specifically, this study used data from both the household survey and from the healthcare workers’ survey embedded within the larger set of tools needed for the impact evaluation. Both surveys were applied in the twenty-four (24) districts distributed in six (6) 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. 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 in the 24 districts. Second, one village was selected in each of the 448 catchment areas. Third, fifteen (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 or who had been pregnant in the twenty-four months prior to the survey date. Households were selected using a random route approach [27] until the desired sample size was achieved in each village. Within a household, information was collected on the overall household socio-demographic and economic profile as well as on individual illness patterns, health care seeking behaviour, and related expenditure (for both adults and children). Specifically, given our focus on unmet need for family planning among pregnant women, we considered as the effective sample for this study only the 1309 currently pregnant women included in the household survey. Currently pregnant women were asked whether their current pregnancy was intended, or whether they would have rather preferred not to have any more children, or to postpone the current pregnancy by at least 2 years. This allowed us to compute unmet need for family planning, further differentiating between unmet need for limiting and unmet need for spacing. The healthcare workers’ survey targeted the staff working at all 443 facilities included in the study. Specifically, at each facility, the aim was to interview at least three healthcare workers. Respondents were conveniently selected among the staff present in the facility on the day of the survey. Information was collected through means of a structured, close-ended questionnaire with several modules, covering healthcare worker’s roles and responsibilities, their work environment, their training with specific reference to family planning, and facility assessment on availability of family planning methods. Data collection was carried out by trained interviewers recruited and supervised by the colleagues at Centre-MURAZ. Both the household and the healthcare workers’ surveys relied on digital data collection, using Personal Digital Assistants (PDAs/mini computers) with data being sent to a central server on a daily basis using mobile phone connection. Table 1 reports the complete list of variables included in our analysis, which were derived from the household and healthcare workers’ survey, as well as 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 is expected to influence unmet need for family planning [28]. The outcome was defined as a dichotomous variable, differentiating between pregnant women with unmet need for family planning (coded as 1) and pregnant women without such unmet need (coded as 0). According to available information from WHO and demographic and health surveys (DHS) unmet need is estimated from non-contraceptive users (pregnant women and non-pregnant who are fecund and desire to have a child in at least 2 years’ time) [3, 6, 7]. Given the non-availability of information on the non-pregnant women explained in the methodological considerations section and the fact that evidence suggest that women (pregnant and non-pregnant) have differentiated needs and should be targeted in their different sects when designing family planning intervention, our focus on unmet need was among the pregnant women category [3, 6, 8, 17]. A pregnant woman was defined as having unmet need if she indicated in the questionnaire that her pregnancy was either wanted later (mistimed pregnancy) or she did not want to be pregnant (unwanted pregnancy) but was not using any method of contraception before the pregnancy. Women with mistimed pregnancies were classified as having unmet need for spacing while those with unwanted pregnancies were classified as having unmet need for limiting. These two (2) categories are referred to as total pregnant women with unmet need for family planning also referred to as women with unintended pregnancy consistent with the WHO and World Bank definition of unmet need among the pregnant women category which is often used as proxy for unmet need [28, 29]. Pregnant women who indicated that their current pregnancy was desired did not experience unmet need for family planning (intended pregnancies) [29]. Variables, their distribution in the study sample, and the expected coefficient sign (n = 1309) Most of the independent variables included in Table Table11 are self-explanatory. Number of living children was categorized into two groups with the classification being consistent with prior studies [30, 31]. We looked at sons living as important in relation to unmet need for family planning. In most patriarchal societies, male children are required to maintain the family lineage and as such, women are expected to give birth to male children. In line with prior research [32], household socio-economic status was assessed by computing a wealth index based on a combination of housing infrastructure and ownership of mobile goods, using multiple correspondence analysis. Four variables, defined in the literature as proximate variables, were included as measures of a woman and her partner’s attitude and decision making towards family planning. Proximate variables are intermediate variables that focus on attitude and decision making [1, 33, 34]. In our analysis, they were: woman’s approval of contraceptive use; partner’s approval of contraceptive use; couple discussion on family planning; and woman’s desire for fewer children in relation to partner. Their inclusion was motivated by the existence of prior evidence suggesting that partners’ involvement in family planning decisions is a key factor shaping women’s reproductive behaviour. Evidence indicates that most women positively adopt family planning methods when they perceive their partner’s approval of contraceptive use [28, 35]. A set of variables from the health facility assessment and from the healthcare provider survey was included to account for health system factors likely to influence unmet need for family planning. Distance to the referral health facility was assessed around the cut-off point of 5 km, in line with WHO guidelines on accessibility [36, 37]. 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 healthcare providers’ training, one looking at general training in family planning and one looking more specifically at logistics (procurement and stocking) concerning family planning products. Bivariate analysis was carried out to assess non-adjusted associations between the single variables and unmet need for family planning. For each of the independent explanatory variables included in our final analysis, we estimated the crude odd ratio using univariate logistic regression. We used multivariate multilevel logistic regression to identify significant associations between unmet need for family planning and the explanatory variables, while controlling for potential confounders. Specifically, we used the Stata command xtlogit [38, 39]. The application of multilevel (random-effect) modelling was used to account for the fact that women were clustered at the district level. Preliminary analysis had in fact detected important differences in unmet need for family planning across districts (Table 2). We purposely did not account for clustering at the household level, given that we recorded multiple women only in 37 households. Unmet need for family planning by region and district

Résumé de l’IA

Study Justification:

– Unmet need for family planning has negative consequences for women and their families, such as unsafe abortion, physical abuse, and poor maternal health.
– Despite increased contraceptive knowledge, unmet need remains high in low-income settings.
– Little information is available on the factors that contribute to unmet need for family planning in rural Burkina Faso.

Study Highlights:

– The study collected data on pregnant women in 24 rural districts of Burkina Faso.
– Multivariate multilevel logistic regression was used to analyze the association between unmet need for family planning and relevant factors.
– The study found that women with more than three living children, those with a child younger than 1 year, those whose partners disapprove of contraceptive use, and those who desire fewer children than their partners are more likely to experience unmet need for family planning.
– Health staff training in family planning logistics management was associated with a lower probability of experiencing unmet need for family planning.

Study Recommendations:

– Strengthen family planning interventions in Burkina Faso to increase contraceptive use and reduce unmet need for family planning.

Key Role Players:

– Ministry of Health: Responsible for policy development and implementation of family planning interventions.
– Health Facilities: Provide access to family planning services and implement training programs for healthcare workers.
– Healthcare Workers: Deliver family planning services and provide counseling to women.
– Community Leaders: Promote awareness and acceptance of family planning methods.
– Non-Governmental Organizations: Support the implementation of family planning programs and provide resources and training.

Cost Items for Planning Recommendations:

– Training Programs: Budget for training healthcare workers in family planning logistics management.
– Contraceptive Supplies: Allocate funds for the procurement and stocking of barrier contraceptives, hormonal contraceptives, and IUDs.
– Awareness Campaigns: Set aside funds for community outreach and education on family planning methods.
– Monitoring and Evaluation: Include resources for monitoring and evaluating the impact of family planning interventions.
Please note that the provided cost items are general suggestions and may vary based on the specific context and needs of Burkina Faso.

Force de la preuve

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a multilevel logistic regression analysis using data from a population-based survey. The study provides specific odds ratios and confidence intervals to quantify the associations between various factors and unmet need for family planning. To improve the evidence, the abstract could include more information on the sample size and the representativeness of the survey. Additionally, it would be helpful to mention any limitations or potential biases in the study design or data collection process.

Abstrait

The study used data from the baseline round of a survey which included multiple tools in order to evaluate the impact of a performance-based financing (PBF) intervention on access to and quality of a wide range of healthcare services. Specifically, this study used data from both the household survey and from the healthcare workers’ survey embedded within the larger set of tools needed for the impact evaluation. Both surveys were applied in the twenty-four (24) districts distributed in six (6) 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. 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 in the 24 districts. Second, one village was selected in each of the 448 catchment areas. Third, fifteen (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 or who had been pregnant in the twenty-four months prior to the survey date. Households were selected using a random route approach [27] until the desired sample size was achieved in each village. Within a household, information was collected on the overall household socio-demographic and economic profile as well as on individual illness patterns, health care seeking behaviour, and related expenditure (for both adults and children). Specifically, given our focus on unmet need for family planning among pregnant women, we considered as the effective sample for this study only the 1309 currently pregnant women included in the household survey. Currently pregnant women were asked whether their current pregnancy was intended, or whether they would have rather preferred not to have any more children, or to postpone the current pregnancy by at least 2 years. This allowed us to compute unmet need for family planning, further differentiating between unmet need for limiting and unmet need for spacing. The healthcare workers’ survey targeted the staff working at all 443 facilities included in the study. Specifically, at each facility, the aim was to interview at least three healthcare workers. Respondents were conveniently selected among the staff present in the facility on the day of the survey. Information was collected through means of a structured, close-ended questionnaire with several modules, covering healthcare worker’s roles and responsibilities, their work environment, their training with specific reference to family planning, and facility assessment on availability of family planning methods. Data collection was carried out by trained interviewers recruited and supervised by the colleagues at Centre-MURAZ. Both the household and the healthcare workers’ surveys relied on digital data collection, using Personal Digital Assistants (PDAs/mini computers) with data being sent to a central server on a daily basis using mobile phone connection. Table 1 reports the complete list of variables included in our analysis, which were derived from the household and healthcare workers’ survey, as well as 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 is expected to influence unmet need for family planning [28]. The outcome was defined as a dichotomous variable, differentiating between pregnant women with unmet need for family planning (coded as 1) and pregnant women without such unmet need (coded as 0). According to available information from WHO and demographic and health surveys (DHS) unmet need is estimated from non-contraceptive users (pregnant women and non-pregnant who are fecund and desire to have a child in at least 2 years’ time) [3, 6, 7]. Given the non-availability of information on the non-pregnant women explained in the methodological considerations section and the fact that evidence suggest that women (pregnant and non-pregnant) have differentiated needs and should be targeted in their different sects when designing family planning intervention, our focus on unmet need was among the pregnant women category [3, 6, 8, 17]. A pregnant woman was defined as having unmet need if she indicated in the questionnaire that her pregnancy was either wanted later (mistimed pregnancy) or she did not want to be pregnant (unwanted pregnancy) but was not using any method of contraception before the pregnancy. Women with mistimed pregnancies were classified as having unmet need for spacing while those with unwanted pregnancies were classified as having unmet need for limiting. These two (2) categories are referred to as total pregnant women with unmet need for family planning also referred to as women with unintended pregnancy consistent with the WHO and World Bank definition of unmet need among the pregnant women category which is often used as proxy for unmet need [28, 29]. Pregnant women who indicated that their current pregnancy was desired did not experience unmet need for family planning (intended pregnancies) [29]. Variables, their distribution in the study sample, and the expected coefficient sign (n = 1309) Most of the independent variables included in Table Table11 are self-explanatory. Number of living children was categorized into two groups with the classification being consistent with prior studies [30, 31]. We looked at sons living as important in relation to unmet need for family planning. In most patriarchal societies, male children are required to maintain the family lineage and as such, women are expected to give birth to male children. In line with prior research [32], household socio-economic status was assessed by computing a wealth index based on a combination of housing infrastructure and ownership of mobile goods, using multiple correspondence analysis. Four variables, defined in the literature as proximate variables, were included as measures of a woman and her partner’s attitude and decision making towards family planning. Proximate variables are intermediate variables that focus on attitude and decision making [1, 33, 34]. In our analysis, they were: woman’s approval of contraceptive use; partner’s approval of contraceptive use; couple discussion on family planning; and woman’s desire for fewer children in relation to partner. Their inclusion was motivated by the existence of prior evidence suggesting that partners’ involvement in family planning decisions is a key factor shaping women’s reproductive behaviour. Evidence indicates that most women positively adopt family planning methods when they perceive their partner’s approval of contraceptive use [28, 35]. A set of variables from the health facility assessment and from the healthcare provider survey was included to account for health system factors likely to influence unmet need for family planning. Distance to the referral health facility was assessed around the cut-off point of 5 km, in line with WHO guidelines on accessibility [36, 37]. 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 healthcare providers’ training, one looking at general training in family planning and one looking more specifically at logistics (procurement and stocking) concerning family planning products. Bivariate analysis was carried out to assess non-adjusted associations between the single variables and unmet need for family planning. For each of the independent explanatory variables included in our final analysis, we estimated the crude odd ratio using univariate logistic regression. We used multivariate multilevel logistic regression to identify significant associations between unmet need for family planning and the explanatory variables, while controlling for potential confounders. Specifically, we used the Stata command xtlogit [38, 39]. The application of multilevel (random-effect) modelling was used to account for the fact that women were clustered at the district level. Preliminary analysis had in fact detected important differences in unmet need for family planning across districts (Table 2). We purposely did not account for clustering at the household level, given that we recorded multiple women only in 37 households. Unmet need for family planning by region and district

Matériaux

N/A

Innovations

Based on the information provided, here are some potential innovations that could be recommended to improve access to maternal health:

1. Mobile clinics: Implementing mobile clinics that travel to rural areas can provide access to maternal health services for pregnant women who may not have easy access to healthcare facilities.

2. Telemedicine: Using telemedicine technology, healthcare providers can remotely provide consultations and advice to pregnant women in rural areas, improving access to maternal health services.

3. Community health workers: Training and deploying community health workers in rural areas can help bridge the gap in access to maternal health services by providing education, support, and basic healthcare services to pregnant women.

4. Performance-based financing: Implementing a performance-based financing system can incentivize healthcare providers to improve the quality and availability of maternal health services, leading to better access for pregnant women.

5. Improving contraceptive availability: Ensuring a reliable supply of contraceptives in healthcare facilities can help address the unmet need for family planning and reduce unintended pregnancies, ultimately improving maternal health outcomes.

6. Partner involvement programs: Implementing programs that encourage partner involvement in family planning decisions can help address barriers and improve access to maternal health services for pregnant women.

7. Strengthening health system logistics: Providing training and support for health staff in family planning logistics management can help improve the availability and accessibility of maternal health services.

These innovations can help address the factors contributing to unmet need for family planning and improve access to maternal health services in rural Burkina Faso.

AI Innovations Description

Based on the study titled “Determinants of unmet need for family planning in rural Burkina Faso: A multilevel logistic regression analysis,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthen family planning interventions: The study found that pregnant women with more than three living children, those with a child younger than 1 year, and women who desired fewer children compared to their partners’ preferred number of children were significantly more likely to experience unmet need for family planning. To address this, innovative interventions can be developed to increase awareness and access to family planning methods, particularly targeting women with multiple children and those who desire to limit or space their pregnancies.

2. Address partner disapproval: The study also found that pregnant women whose partners disapproved of contraceptive use were more likely to experience unmet need for family planning. It is important to involve partners in family planning discussions and education to address misconceptions and promote supportive attitudes towards contraception. Innovative approaches can include couple counseling and education programs to engage partners in the decision-making process.

3. Improve health staff training: The study highlighted that health staff training in family planning logistics management was associated with a lower probability of experiencing unmet need for family planning. Investing in comprehensive training programs for healthcare providers can enhance their knowledge and skills in delivering family planning services effectively. This can include training on counseling techniques, contraceptive methods, and supply chain management.

4. Utilize digital data collection: The study utilized digital data collection using Personal Digital Assistants (PDAs/mini computers) with data being sent to a central server on a daily basis using mobile phone connection. This innovative approach can be further expanded to improve data collection and monitoring of maternal health indicators. By leveraging technology, real-time data can be collected, analyzed, and used to inform decision-making and resource allocation for maternal health programs.

5. Tailor interventions to regional and district-specific needs: The study identified variations in unmet need for family planning across different regions and districts in Burkina Faso. To ensure effective and targeted interventions, it is important to consider the unique socio-cultural, economic, and geographical factors influencing maternal health access in each region and district. Innovations can include context-specific approaches, such as community-based outreach programs and mobile clinics, to reach underserved populations.

By implementing these recommendations and developing innovative approaches, access to maternal health can be improved, leading to better health outcomes for women and their families in Burkina Faso.

AI Innovations Methodology

To improve access to maternal health, here are some potential recommendations:

1. Increase availability and affordability of contraceptives: Ensure that a wide range of contraceptives are readily available in rural areas of Burkina Faso at affordable prices. This can be achieved through partnerships with pharmaceutical companies, government subsidies, and community-based distribution programs.

2. Strengthen family planning education and awareness: Implement comprehensive family planning education programs that target both women and men in rural communities. These programs should provide accurate information about contraceptive methods, their benefits, and how to access them.

3. Improve healthcare provider training: Provide healthcare workers with training on family planning counseling and services. This includes training on contraceptive methods, counseling techniques, and addressing cultural and religious beliefs that may hinder contraceptive use.

4. Enhance community engagement: Engage community leaders, religious leaders, and traditional birth attendants in promoting the importance of maternal health and family planning. This can help reduce stigma and increase acceptance of contraceptive use.

5. Strengthen health system infrastructure: Improve the availability and quality of maternal health services in rural areas. This includes ensuring that health facilities have the necessary equipment, supplies, and skilled healthcare providers to provide comprehensive maternal health care.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Baseline data collection: Collect data on the current status of maternal health access in rural Burkina Faso. This can include information on the availability of maternal health services, contraceptive use rates, unmet need for family planning, and other relevant indicators.

2. Define indicators and targets: Identify specific indicators that will be used to measure the impact of the recommendations. For example, indicators could include the percentage increase in contraceptive use, reduction in unmet need for family planning, and improvement in the availability of maternal health services.

3. Develop a simulation model: Use statistical modeling techniques to develop a simulation model that can estimate the potential impact of the recommendations on the defined indicators. This model should take into account the baseline data, as well as the potential effects of the recommendations on various factors influencing access to maternal health.

4. Input data and run simulations: Input the relevant data into the simulation model and run multiple simulations to estimate the potential impact of the recommendations. This can help identify the most effective strategies and prioritize interventions.

5. Analyze results and make recommendations: Analyze the results of the simulations to determine the potential impact of the recommendations on improving access to maternal health. Based on the findings, make recommendations for policy and programmatic interventions that can be implemented to achieve the desired improvements.

6. Monitor and evaluate: Implement the recommended interventions and continuously monitor and evaluate their impact on access to maternal health. This will help identify any necessary adjustments or additional interventions that may be needed to achieve the desired outcomes.

Auteur

Dima Health

Statistics:

Citations: 23

Identifiers:

DOI: 10.1186/s12884-017-1614-z

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Violence and Injury

Study Countries:

Burkina Faso

Study Design:

Cross Sectional Study, Grounded Theory, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Male & Female

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