Regional differences in unmet need for contraception in Kenya: Insights from survey data

BMC Women's Health, Volume 15, No. 1, Year 2015

Interpretation

Background: Women are described as experiencing unmet need for contraception if they are fecund, sexually active and wish to postpone or limit childbearing but fail to use contraception to do so. The consequences of unmet need include unwanted pregnancy, induced abortions, school dropout due to pregnancy and premature maternal deaths. Global efforts aimed at addressing the adverse effects of unmet need abound. In Kenya, one in every four married women in the reproductive age bracket (15-49 years) has unmet need for contraception. Regional differences exist but the reasons behind these differences remain poorly understood. The purpose of this study was to examine the extent to which regional differentials in unmet need for contraception exists and to explain the regional differences in unmet need for contraception in Kenya. Methods: The paper used the Kenya Demographic and Health Survey (2008/09) data. Unmet need for contraception was measured based on the revised estimates contained in the survey. Summary statistics were used to show the percentage differences in the values of selected covariates across the high and low unmet need zones. The dependent variable had three categories: no unmet need, unmet need for spacing and unmet need for limiting births. The categorical nature of this dependent variable which is not ordered in any way lends itself to the use of multinomial logistic regression. The paper applied the seemingly unrelated estimation (suest) test to ascertain whether the covariate coefficients between the high and low unmet need zones were different. Stata Version 13.0 was used for analysis. Results: The percentage values of the selected covariates of unmet need for contraception were much higher in the high unmet need zone as compared to those observed in the low unmet need zones. On the overall, 15.4 % of women in the high unmet need zone had unmet need to space their next birth as compared to 8.6 % of their counterparts. Likewise, the percentage of women who wanted to limit further births stood at 14.1 % among women residing in high unmet need zones while those in low unmet need zones had 10.5 %. Further analysis based on seemingly unrelated estimation found that in general, a comparison of the coefficients been the high and low unmet need regions were significantly different (p < 0.05). Conclusion: Evidence from the nationally representative KDHS 2008/09 shows that regional differentials in the covariates of unmet need for contraception exist. There is need to address religious inhibitions that stymie contraceptive uptake especially in the high unmet need regions. Efforts should promote maternal education and economically empower women in order to reinforce individual and contextual attitudes towards the benefits of contraception. The government should also establish social franchise programs to increase access to costly long acting and permanent methods of contraception to poor women. This study used data drawn from the 2008/09 KDHS. The data are national in scope. Out of the 8444 women of reproductive age (15–49 years) that were interviewed during the 2008/09 KDHS, 5041 were either currently married women or were in a union. This paper analyses KDHS data for women who were married or in union due to the following reasons: first, this cohort is the most sexually active with the highest risk of experiencing unmet need and its adverse consequences. Secondly, married women or those in union are bound to face more opposition from their spouses in their decision to use family planning as compared to the rest. Finally, the methodology for estimating unmet need for contraception among married women or those in union is the most developed of them all and is widely used globally [1, 6]. Unmet need for family planning is computed from women’s fertility preference and current contraceptive behaviour. Married women who were pregnant were asked whether they wanted to get pregnant then. Those who wanted to become pregnant were categorized as not having unmet need for contraception. Among those who did not want to get pregnant then, they were asked whether they wanted to get pregnant later (after 2 years or more) or not at all. Those who wanted to get pregnant later were categorized as having unmet need to space while those who did not want the pregnancy at all were categorised as having unmet need to limit births. On the other hand, married women who were sexually active and were fecund but were not using any contraceptives were asked whether they wanted to get pregnant during their most recent pregnancy (within 5 years). Those who wished they could have postponed their last pregnancy by at least 2 years were categorized as having unmet need to space while those who did not want to get pregnant at all were classified as having unmet need to limit. Married women who were currently pregnant or not were also asked about their timing and future intentions of becoming pregnant. Out of all these questions, a measure was computed to categorize women who had met needs for contraception as well as unmet need for spacing and limiting further births. A detailed algorithm for the computation of unmet need estimates is available in earlier works on this subject [1]. In this study, a regional approach was adopted. Specifically, regions that had a higher than national rate of unmet need for contraception were categorized as high unmet need zones while their counterparts were categorized as low unmet need zones. Using this categorization, Rift Valley, Nyanza, Western and Coast provinces which had unmet need levels of 30.3 % were grouped as high unmet need zones since their rate exceeded the national rate of 25.6 %. On the other hand, Nairobi, Central, Eastern and North Eastern provinces were grouped as low unmet need zones since they only had unmet need levels of 18 % against the national average of 25.6 %. Details of unmet need for contraception for each province are shown in Fig. Fig.1.1. I employed the difference in difference estimates to illustrate the differences in the levels of unmet need between the high and low unmet need regions. This is shown in Table 1. Percentage distribution of unmet need to space and limit births by province and national level, KDHS 2008/09 Regional percentage change in unmet need in Kenya, KDHS 2008/09 UNS H unmet need to space in the high zones, UNS L unmet need to space in the low zones, UNL H unmet need to limit in the high zones, UNL L unmet need to limit in the low zones A multinomial logistic regression was applied in each of the two unmet need zones to assess the net effect of the covariates on unmet need status. This is an appropriate statistical procedure since the dependent variable has more than two unordered outcomes namely: women without unmet need, women with unmet need to space and women with unmet need to limit births. Using women without unmet need as the base outcome category, this study assessed the significance of the selected covariates on unmet need to space and to limit further births. Separate regression models were fitted for both the low and high unmet need zones. A one unit increase in any of the independent variables either increased or decreased the relative log odds of experiencing unmet need to space or limit vis-à-vis our base outcome (no unmet need). The fitted multinomial regression models were then compared using the seemingly unrelated estimation (suest) command in Stata version 13.0. The purpose of this comparison was to assess whether differences in the covariate coefficients existed between the high and low unmet need zones. Explanatory variables used in this study were categorized based on theory as well as the conventional practice. For instance, young women are more likely to use contraceptives for spacing while older women prefer methods that limit childbearing since they have already achieved their desired family size. The categories thus reflect these theoretical underpinnings. The categories used are as follows:- The household wealth status was computed using the principal component analysis (PCA) and the factor weights of the first component were used to place households in either poor, middle or rich category. Past studies show that the above factors are associated with unmet need for contraception [6, 7]. The ethical approval for KDHS 2008/09 was obtained from the Kenya Medical and Research Institute (KEMRI). Written informed consent was sought from eligible clients before administration of the survey. The author also formerly obtained permission to use KDHS data from MEASURE DHS which are freely available once permission is granted. The data are available on the following website: http://www.measuredhs.com.

AI Digest

Study Justification:

– Unmet need for contraception in Kenya is a significant issue with adverse consequences such as unwanted pregnancies, induced abortions, school dropout due to pregnancy, and maternal deaths.
– Global efforts to address unmet need exist, but regional differences in Kenya remain poorly understood.
– This study aims to examine the extent of regional differences in unmet need for contraception in Kenya and provide insights into the reasons behind these differences.

Highlights:

– The study used data from the Kenya Demographic and Health Survey (2008/09) to analyze regional differences in unmet need for contraception.
– Results showed that the percentage of women with unmet need for contraception was higher in regions with high unmet need compared to regions with low unmet need.
– The study used multinomial logistic regression to assess the net effect of various factors on unmet need status.
– Differences in the covariate coefficients between high and low unmet need regions were found to be significant.
– The study suggests addressing religious inhibitions, promoting maternal education, and empowering women economically to improve contraceptive uptake.
– The government is recommended to establish social franchise programs to increase access to costly long-acting and permanent methods of contraception for poor women.

Recommendations:

– Address religious inhibitions that hinder contraceptive uptake, especially in regions with high unmet need.
– Promote maternal education and economic empowerment of women to reinforce positive attitudes towards contraception.
– Establish social franchise programs to increase access to costly long-acting and permanent methods of contraception for poor women.

Key Role Players:

– Government agencies responsible for health and family planning policies and programs.
– Non-governmental organizations (NGOs) working in the field of reproductive health and family planning.
– Religious leaders and organizations to address religious inhibitions.
– Educational institutions to promote maternal education.
– Women’s empowerment organizations to support economic empowerment of women.

Cost Items for Planning Recommendations:

– Funding for awareness campaigns and educational programs on contraception.
– Resources for training healthcare providers on family planning counseling and services.
– Budget for establishing and maintaining social franchise programs for increased access to contraception.
– Investment in research and monitoring to evaluate the effectiveness of interventions and adjust strategies accordingly.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study used nationally representative data from the Kenya Demographic and Health Survey (KDHS) and applied statistical analysis to examine regional differences in unmet need for contraception in Kenya. The methodology and analysis techniques used are appropriate. However, the abstract could be improved by providing more specific details about the results, such as the magnitude of the regional differences and the statistical significance of the findings. Additionally, the abstract could benefit from a clearer explanation of the actionable steps to address the regional differences in unmet need, such as specific strategies to address religious inhibitions and promote maternal education and economic empowerment.

Abstract

This study used data drawn from the 2008/09 KDHS. The data are national in scope. Out of the 8444 women of reproductive age (15–49 years) that were interviewed during the 2008/09 KDHS, 5041 were either currently married women or were in a union. This paper analyses KDHS data for women who were married or in union due to the following reasons: first, this cohort is the most sexually active with the highest risk of experiencing unmet need and its adverse consequences. Secondly, married women or those in union are bound to face more opposition from their spouses in their decision to use family planning as compared to the rest. Finally, the methodology for estimating unmet need for contraception among married women or those in union is the most developed of them all and is widely used globally [1, 6]. Unmet need for family planning is computed from women’s fertility preference and current contraceptive behaviour. Married women who were pregnant were asked whether they wanted to get pregnant then. Those who wanted to become pregnant were categorized as not having unmet need for contraception. Among those who did not want to get pregnant then, they were asked whether they wanted to get pregnant later (after 2 years or more) or not at all. Those who wanted to get pregnant later were categorized as having unmet need to space while those who did not want the pregnancy at all were categorised as having unmet need to limit births. On the other hand, married women who were sexually active and were fecund but were not using any contraceptives were asked whether they wanted to get pregnant during their most recent pregnancy (within 5 years). Those who wished they could have postponed their last pregnancy by at least 2 years were categorized as having unmet need to space while those who did not want to get pregnant at all were classified as having unmet need to limit. Married women who were currently pregnant or not were also asked about their timing and future intentions of becoming pregnant. Out of all these questions, a measure was computed to categorize women who had met needs for contraception as well as unmet need for spacing and limiting further births. A detailed algorithm for the computation of unmet need estimates is available in earlier works on this subject [1]. In this study, a regional approach was adopted. Specifically, regions that had a higher than national rate of unmet need for contraception were categorized as high unmet need zones while their counterparts were categorized as low unmet need zones. Using this categorization, Rift Valley, Nyanza, Western and Coast provinces which had unmet need levels of 30.3 % were grouped as high unmet need zones since their rate exceeded the national rate of 25.6 %. On the other hand, Nairobi, Central, Eastern and North Eastern provinces were grouped as low unmet need zones since they only had unmet need levels of 18 % against the national average of 25.6 %. Details of unmet need for contraception for each province are shown in Fig. Fig.1.1. I employed the difference in difference estimates to illustrate the differences in the levels of unmet need between the high and low unmet need regions. This is shown in Table 1. Percentage distribution of unmet need to space and limit births by province and national level, KDHS 2008/09 Regional percentage change in unmet need in Kenya, KDHS 2008/09 UNS H unmet need to space in the high zones, UNS L unmet need to space in the low zones, UNL H unmet need to limit in the high zones, UNL L unmet need to limit in the low zones A multinomial logistic regression was applied in each of the two unmet need zones to assess the net effect of the covariates on unmet need status. This is an appropriate statistical procedure since the dependent variable has more than two unordered outcomes namely: women without unmet need, women with unmet need to space and women with unmet need to limit births. Using women without unmet need as the base outcome category, this study assessed the significance of the selected covariates on unmet need to space and to limit further births. Separate regression models were fitted for both the low and high unmet need zones. A one unit increase in any of the independent variables either increased or decreased the relative log odds of experiencing unmet need to space or limit vis-à-vis our base outcome (no unmet need). The fitted multinomial regression models were then compared using the seemingly unrelated estimation (suest) command in Stata version 13.0. The purpose of this comparison was to assess whether differences in the covariate coefficients existed between the high and low unmet need zones. Explanatory variables used in this study were categorized based on theory as well as the conventional practice. For instance, young women are more likely to use contraceptives for spacing while older women prefer methods that limit childbearing since they have already achieved their desired family size. The categories thus reflect these theoretical underpinnings. The categories used are as follows:- The household wealth status was computed using the principal component analysis (PCA) and the factor weights of the first component were used to place households in either poor, middle or rich category. Past studies show that the above factors are associated with unmet need for contraception [6, 7]. The ethical approval for KDHS 2008/09 was obtained from the Kenya Medical and Research Institute (KEMRI). Written informed consent was sought from eligible clients before administration of the survey. The author also formerly obtained permission to use KDHS data from MEASURE DHS which are freely available once permission is granted. The data are available on the following website: http://www.measuredhs.com.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services that provide information and reminders about contraception, prenatal care, and maternal health. These tools can help women in remote areas access important health information and stay connected with healthcare providers.

2. Community Health Workers: Train and deploy community health workers to provide education, counseling, and support for family planning and maternal health. These workers can reach women in underserved areas and provide personalized care and guidance.

3. Telemedicine: Implement telemedicine services to connect women in remote areas with healthcare providers. This allows for remote consultations, monitoring, and follow-up care, reducing the need for women to travel long distances for healthcare services.

4. Social Franchise Programs: Establish social franchise programs to increase access to affordable and quality maternal health services, including contraception. These programs can partner with private healthcare providers to expand their reach and ensure that services are accessible to all women, regardless of their socioeconomic status.

5. Financial Incentives: Introduce financial incentives, such as conditional cash transfers or vouchers, to encourage women to seek and utilize maternal health services. These incentives can help overcome financial barriers and increase utilization of essential services.

6. Addressing Religious Inhibitions: Develop culturally sensitive approaches to address religious inhibitions that may hinder contraceptive uptake. This can involve engaging religious leaders and communities in discussions about the importance of family planning and maternal health.

7. Maternal Education and Economic Empowerment: Implement programs that promote maternal education and economic empowerment. By improving women’s education and economic opportunities, they are more likely to make informed decisions about their reproductive health and have better access to maternal health services.

8. Long-Acting and Permanent Contraceptive Methods: Increase access to long-acting and permanent contraceptive methods, such as intrauterine devices (IUDs) and sterilization, especially for women in low-income settings. This can be done through subsidized or free distribution programs and training healthcare providers on the safe and effective use of these methods.

It is important to note that these recommendations are based on the information provided and may need to be tailored to the specific context and needs of the population in Kenya.

AI Innovations Description

The study titled “Regional differences in unmet need for contraception in Kenya: Insights from survey data” explores the regional disparities in unmet need for contraception in Kenya and provides recommendations to improve access to maternal health.

Based on the findings of the study, the following recommendations can be developed into innovations to improve access to maternal health:

1. Address religious inhibitions: Religious beliefs and practices can hinder contraceptive uptake, especially in regions with high unmet need. Innovative approaches should be developed to address these inhibitions and promote the acceptance and use of contraception.

2. Promote maternal education: Maternal education plays a crucial role in empowering women and improving their knowledge about reproductive health and family planning. Innovative programs should be designed to promote maternal education, including awareness campaigns, workshops, and educational materials.

3. Economic empowerment of women: Economic empowerment can positively impact women’s decision-making power and their ability to access and use contraception. Innovative initiatives should focus on providing economic opportunities and support to women, such as vocational training, microfinance programs, and entrepreneurship development.

4. Establish social franchise programs: Access to costly long-acting and permanent methods of contraception can be a challenge for poor women. Innovative solutions, such as social franchise programs, can be established to increase access to these methods and ensure affordability for women in need.

By implementing these recommendations as innovative solutions, access to maternal health can be improved, leading to a reduction in unmet need for contraception, unwanted pregnancies, induced abortions, school dropout due to pregnancy, and premature maternal deaths.

AI Innovations Methodology

Based on the information provided, here are some potential recommendations to improve access to maternal health:

1. Address religious inhibitions: Religious beliefs can often hinder contraceptive uptake, especially in regions with high unmet need for contraception. Efforts should be made to engage with religious leaders and communities to promote a better understanding of the benefits of contraception and to dispel any misconceptions.

2. Promote maternal education: Maternal education plays a crucial role in improving access to maternal health. Efforts should be made to ensure that women have access to quality education, which can empower them to make informed decisions about their reproductive health.

3. Economic empowerment of women: Economic empowerment can have a positive impact on access to maternal health. By providing women with economic opportunities and resources, they can have more control over their reproductive choices and access to healthcare services.

4. Establish social franchise programs: Social franchise programs can help increase access to costly long-acting and permanent methods of contraception for poor women. These programs can provide affordable and quality reproductive health services in underserved areas.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Data collection: Collect data on key indicators related to maternal health, such as contraceptive use, maternal mortality rates, education levels, and economic status. This data can be obtained through surveys, interviews, and existing databases.

2. Define variables: Define variables that represent the recommendations, such as religious inhibitions, maternal education, economic empowerment, and social franchise program availability. These variables should be measurable and quantifiable.

3. Analyze regional differences: Use statistical methods, such as multinomial logistic regression, to analyze regional differences in unmet need for contraception and access to maternal health services. Compare the values of selected covariates across high and low unmet need zones to identify patterns and disparities.

4. Simulate impact: Use simulation techniques, such as difference-in-differences estimation, to simulate the impact of the recommendations on improving access to maternal health. This involves comparing the outcomes (e.g., contraceptive use, maternal mortality rates) before and after implementing the recommendations in different regions.

5. Evaluate results: Evaluate the results of the simulation to assess the effectiveness of the recommendations in improving access to maternal health. Identify any significant changes in the outcomes and determine the extent to which the recommendations have contributed to these changes.

6. Refine and iterate: Based on the evaluation results, refine the recommendations and methodology as needed. Iterate the process to continuously improve access to maternal health and address any remaining disparities.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and available data.

Author

Dima Health

Statistics:

Citations: 10

Identifiers:

DOI: 10.1186/s12905-015-0240-z

Research Areas:

Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Kenya

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female