Factors associated with use of long-acting reversible and permanent contraceptives among married women in rural Kenya: A community-based cross-sectional study in Kisii and Kilifi counties

PLoS ONE, Volume 17, No. 10 October, Year 2022

Interpretation

Long-acting and permanent contraceptive methods (LAPM) are effective and economical methods for delaying or limiting pregnancies, however they are not widely used. The Kenya government is promoting the use of modern methods of family planning through various mechanisms. This study aimed to determine the prevalence and factors associated with the use of LAPM among married women of reproductive age in targeted rural sub-counties of Kilifi and Kisii counties, Kenya. Baseline and end line Data from a program implemented on improving Access to Quality Care and Extending and Strengthening Health Systems (AQCESS) in Kilifi and Kisii counties of Kenya were used. Multi-stage sampling was used to sample 1117 and 1873 women for the end line and baseline surveys, respectively. Descriptive analysis was used to explore the respondents’ characteristics and use of LAPM on a self-weighted samples. Univariable and multivariable binary logistic regression models using svy command were used to assess factors associated with the use of LAPM. A total of 762 and 531 women for the baseline and end line survey, respectively were included in this study. The prevalence of use of LAPM for baseline and end line survey were 21.5% (95% CI: 18.7–24.6%) and 23.2% (95% CI: 19.6%-27.0%), p-value = 0.485. The use of LAPM in Kisii and Kilifi counties was higher than the national average in both surveys. The multivariable analysis for the end line survey showed having 3–5 number of children ever born (aOR = 2.04; 95% CI: 1.24–3.36) and future fertility preference to have another child (aOR = 0.50; 95% CI: 0.26–0.96) were significantly associated with odds of LAPM use. The baseline showed that having at least secondary education (aOR = 1.93; 95%CI: 1.04–3.60), joint decision making about woman’s own health (aOR = 2.08; 95%CI: 1.36–3.17), and intention to have another child in future (aOR = 0.59; 95%CI: 0.40–0.89) were significantly associated with the use of LAPM. Future fertility preference to have another child was significantly associated with the use of LAPM in the two surveys. Continued health promotion and targeted media campaigns on the use of LAPM in rural areas with low socioeconomic status is needed in order to improve utilization of these methods. Programs involving men in decision making on partner’s health including family planning in the rural areas should be encouraged. The study used data from the baseline and end-line survey of the AQCESS project, conducted between August and September 2016 and January and February 2020, respectively in four rural targeted implementation sub-counties of Kisii and Kilifi counties. The AQCESS project aimed to contribute to the reduction of maternal and under-five mortalities in Kenya; its organization and implementation have been described in our previous papers [35, 36]. The project promoted the use of family planning through community sensitisation messages by the community health volunteers (CHVs) as one of the implementation activities, however, there was no family planning commodity provided by the project during the implementation period. Details of design and conduct of baseline survey is discussed in our previous paper [35]; the below sections described the design and conduct of the end line survey. The repeat cross-sectional survey was conducted in Kaloleni and Rabai sub-counties in Kilifi County and Bomachoge Borabu sub-county in Kisii County with a population of 304,778 and 129,617, respectively [36]. The maternal mortality rate in Kilifi was 448 deaths per 100,000 live births, and an under-five mortality rate of 87 deaths per 1,000 live births [36], with 70% of the population living below the poverty line. Under-five mortality rates in Kisii County was 36 deaths per 100,000 live births, however only 44% of its population living below the poverty line. Both counties have a high teenage pregnancy rate (Kisii 18.4% and Kilifi 21.8%) [36], which is higher than the national average of 18% [14, 36]. Kaloleni and Rabai sub-counties are served by 40 health facilities, while Bomachoge Borabu County is served by 12 health facilities [36]. About 82% and 93% of health facilities in Kilifi and Kisii offer family planning (FP) services; 49% and 93% of which offer services to adolescents, respectively. The CPR for the regions in 2014 were 34.1% and 66.1% for Kilifi and Kisii counties [20]. There are numerous structural challenges, including limited human healthcare resources, poor access to health services due to geographical and transportation barriers, and limited healthcare infrastructure, including a high physician and nurse to population ratio in these counties [36]. The survey employed a two-stage sampling procedure considering a village as a cluster: In the first stage of sampling, a selection of 30 villages in each of the two sites were selected based on probability proportional to the number of households in each village. The second stage involved a random selection of households from a master frame of the household listing in the selected villages. The household listings were provided by the village elders who were familiar with the village boundaries. No further sampling was carried at the selected household level. All assented and consented women aged 15–49 years old and permanent residents of the selected villages were included in the survey. The minimum sample size of 1788 households was calculated for the survey based on the following assumptions: an expected increase in the contraceptive prevalence rate between the baseline (2016) and end-line (2020) periods of 10%; 80% as the power; 95% level of significance; design effect of two; and a 20% non-response rate to account for absent household members during data collection. Figs Figs11 and and22 highlights the final study sample size for endline and baseline respectively after excluding women who were pregnant, unmarried, last menstruated more than six months before the survey, menopausal, never menstruated, did not know their last date of menstruation period, and those who preferred not to answer. Trained enumerators collected data using tablets pre-installed with a standardized electronic questionnaire programmed on the Open Data Kit (ODK) software in English and the local languages of the study areas (Giriama, Ekegusi, and Swahili). The questionnaire adapted questions from the Demographic and Health Surveys and Multiple Indicator Cluster Surveys to allow for comparison. The questionnaire was pretested in the nearby villages which were not part of the actual survey before the start of the actual survey. Each supervisor was assigned team of six enumerators to manage; the supervisor ensured that the sampled households were interviewed and repeat visits conducted to absent household members conducted. After three unsuccessful repeat visits, a household was considered to have absent members for the duration of the survey. The collected data were synchronized into a secure, password-protected cloud-based server, allowing for real-time data quality assurance. Other quality checks performed during data collection included random spot-checks, close supervision of the enumerators, routine data cleaning, and addressing all identified issues prior to the start of data collection on any given day. The main outcome variable was LAPM use, which was assessed based on two questions: (i) “Are you or your partner currently doing something or using any method to delay or avoid getting pregnant?” and (ii) “What are you currently doing to delay or avoid pregnancy?”. Based on responses to the question (ii), women were classified as LAPM user (intrauterine contraceptive devices, implants, and male and female sterilization) or otherwise a non-user of LAPM. The non-users of LAPM includes users of short-acting/traditional methods (emergency contraception, injectable, male condoms, oral contraceptive pills, and traditional FP methods) and non-users of any method of contraceptive. Specifically the main outcome was binary in nature defined as: Where Yi, is the response for the ith individual woman. Independent variables were identified based on a review of literature of previous studies on LAPM [19, 30, 31, 37–44] and included age measured in completed years at the time of the interview categorized into age groups (15–19, 20–29, 30–39, and 40–49 years); level of education (none, primary, and secondary and above), household wealth tercile (poor, middle, and rich), future fertility preference (no more/none and have ((an)other) child(ren), number of children ever born (CEB) as at the time of the survey (0–2, 3–5 and 6 or more), exposure to media was classified as yes for those who had listened to radio or watched television or read newspaper or accessed social media at least once a week and no for those who had not [23] and the main decision-maker on a woman’s health (woman alone, woman with a partner, and other). The other decision-makers included the husband/partner alone, father or father-in-law, mother or mother-in-law, other male family members, and other female family members. Household wealth terciles were generated based on a wealth score computed using the principal component analysis approach using household assets and materials for the dwelling floor, roof, and external wall [45]. Variables on exposure to media and number of children ever born were not collected during the baseline survey. Data were explored descriptively using the median and interquartile range (IQR) for continuous variables and frequencies and percentages for categorical variables. Chi-square test was used to compare the difference between the categorical groups. The multivariable logistic model was used to assess the factors associated with the use of LAPM while controlling for other variables. All the variable were considered to be important in explaining the outcome and were adjusted for in the multivariable logistic regression. The crude (cOR) and adjusted odds ratio (aOR) with the 95% confidence interval (CI) for the estimates is reported, and a p-value of less than 0.05 was considered statistically significant. We used “svy” set command in Stata to account for clustering due to complex sampling design of the study at village level. All analysis were conducted in Stata (15, StataCorp LLC, College Station, TX). The study was approved by the Aga Khan University Institutional Ethics Review Committee and research permit provided by the National Commission for Science, Technology, and Innovation. County approvals were obtained from the Ministries of Health in Kisii and Kilifi Counties. Written informed consent were obtained from each participant before the start of data collection, with those who could not write providing consent using their thumbprint. Women aged 15–17 years old provided assent and additional consent from their parents/guardians or whoever they were comfortable with consenting on their behalf. The survey was conducted in line with the Helsinki Declaration on Research involving Human Subjects.

AI Digest

Study Justification:

– Long-acting and permanent contraceptive methods (LAPM) are effective and economical for delaying or limiting pregnancies.
– The use of LAPM is not widely adopted among married women in rural Kenya.
– The Kenyan government is promoting modern family planning methods, including LAPM, through various mechanisms.
– This study aimed to determine the prevalence and factors associated with the use of LAPM among married women in rural sub-counties of Kilifi and Kisii counties, Kenya.

Study Highlights:

– The study used data from the baseline and end-line surveys of the AQCESS project, which aimed to improve access to quality care and strengthen health systems in Kilifi and Kisii counties.
– Multi-stage sampling was used to select 1117 women for the end-line survey and 1873 women for the baseline survey.
– The prevalence of LAPM use was 21.5% at baseline and 23.2% at end-line, higher than the national average.
– Factors associated with LAPM use included the number of children ever born and future fertility preference.
– Having at least secondary education, joint decision making about women’s health, and intention to have another child in the future were also associated with LAPM use.

Recommendations for Lay Reader and Policy Maker:

– Continued health promotion and targeted media campaigns are needed to improve the utilization of LAPM in rural areas with low socioeconomic status.
– Programs involving men in decision making on their partner’s health, including family planning, should be encouraged in rural areas.

Key Role Players:

– Community health volunteers (CHVs) for community sensitization messages on family planning.
– Health facilities and healthcare providers for the provision of family planning services.
– Ministries of Health in Kisii and Kilifi Counties for county-level approvals and support.
– The National Commission for Science, Technology, and Innovation for research permit.

Cost Items for Planning Recommendations:

– Health promotion and media campaign expenses.
– Training and capacity building for CHVs and healthcare providers.
– Provision of family planning commodities and supplies.
– Monitoring and evaluation costs for program implementation.
– Research and data collection expenses.
– Administrative and coordination costs.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study provides detailed information about the methodology, sample size, and statistical analysis. However, the abstract does not mention any limitations of the study or potential biases. To improve the strength of the evidence, the authors could include a discussion of the limitations and potential biases in the abstract.

Abstract

The study used data from the baseline and end-line survey of the AQCESS project, conducted between August and September 2016 and January and February 2020, respectively in four rural targeted implementation sub-counties of Kisii and Kilifi counties. The AQCESS project aimed to contribute to the reduction of maternal and under-five mortalities in Kenya; its organization and implementation have been described in our previous papers [35, 36]. The project promoted the use of family planning through community sensitisation messages by the community health volunteers (CHVs) as one of the implementation activities, however, there was no family planning commodity provided by the project during the implementation period. Details of design and conduct of baseline survey is discussed in our previous paper [35]; the below sections described the design and conduct of the end line survey. The repeat cross-sectional survey was conducted in Kaloleni and Rabai sub-counties in Kilifi County and Bomachoge Borabu sub-county in Kisii County with a population of 304,778 and 129,617, respectively [36]. The maternal mortality rate in Kilifi was 448 deaths per 100,000 live births, and an under-five mortality rate of 87 deaths per 1,000 live births [36], with 70% of the population living below the poverty line. Under-five mortality rates in Kisii County was 36 deaths per 100,000 live births, however only 44% of its population living below the poverty line. Both counties have a high teenage pregnancy rate (Kisii 18.4% and Kilifi 21.8%) [36], which is higher than the national average of 18% [14, 36]. Kaloleni and Rabai sub-counties are served by 40 health facilities, while Bomachoge Borabu County is served by 12 health facilities [36]. About 82% and 93% of health facilities in Kilifi and Kisii offer family planning (FP) services; 49% and 93% of which offer services to adolescents, respectively. The CPR for the regions in 2014 were 34.1% and 66.1% for Kilifi and Kisii counties [20]. There are numerous structural challenges, including limited human healthcare resources, poor access to health services due to geographical and transportation barriers, and limited healthcare infrastructure, including a high physician and nurse to population ratio in these counties [36]. The survey employed a two-stage sampling procedure considering a village as a cluster: In the first stage of sampling, a selection of 30 villages in each of the two sites were selected based on probability proportional to the number of households in each village. The second stage involved a random selection of households from a master frame of the household listing in the selected villages. The household listings were provided by the village elders who were familiar with the village boundaries. No further sampling was carried at the selected household level. All assented and consented women aged 15–49 years old and permanent residents of the selected villages were included in the survey. The minimum sample size of 1788 households was calculated for the survey based on the following assumptions: an expected increase in the contraceptive prevalence rate between the baseline (2016) and end-line (2020) periods of 10%; 80% as the power; 95% level of significance; design effect of two; and a 20% non-response rate to account for absent household members during data collection. Figs Figs11 and and22 highlights the final study sample size for endline and baseline respectively after excluding women who were pregnant, unmarried, last menstruated more than six months before the survey, menopausal, never menstruated, did not know their last date of menstruation period, and those who preferred not to answer. Trained enumerators collected data using tablets pre-installed with a standardized electronic questionnaire programmed on the Open Data Kit (ODK) software in English and the local languages of the study areas (Giriama, Ekegusi, and Swahili). The questionnaire adapted questions from the Demographic and Health Surveys and Multiple Indicator Cluster Surveys to allow for comparison. The questionnaire was pretested in the nearby villages which were not part of the actual survey before the start of the actual survey. Each supervisor was assigned team of six enumerators to manage; the supervisor ensured that the sampled households were interviewed and repeat visits conducted to absent household members conducted. After three unsuccessful repeat visits, a household was considered to have absent members for the duration of the survey. The collected data were synchronized into a secure, password-protected cloud-based server, allowing for real-time data quality assurance. Other quality checks performed during data collection included random spot-checks, close supervision of the enumerators, routine data cleaning, and addressing all identified issues prior to the start of data collection on any given day. The main outcome variable was LAPM use, which was assessed based on two questions: (i) “Are you or your partner currently doing something or using any method to delay or avoid getting pregnant?” and (ii) “What are you currently doing to delay or avoid pregnancy?”. Based on responses to the question (ii), women were classified as LAPM user (intrauterine contraceptive devices, implants, and male and female sterilization) or otherwise a non-user of LAPM. The non-users of LAPM includes users of short-acting/traditional methods (emergency contraception, injectable, male condoms, oral contraceptive pills, and traditional FP methods) and non-users of any method of contraceptive. Specifically the main outcome was binary in nature defined as: Where Yi, is the response for the ith individual woman. Independent variables were identified based on a review of literature of previous studies on LAPM [19, 30, 31, 37–44] and included age measured in completed years at the time of the interview categorized into age groups (15–19, 20–29, 30–39, and 40–49 years); level of education (none, primary, and secondary and above), household wealth tercile (poor, middle, and rich), future fertility preference (no more/none and have ((an)other) child(ren), number of children ever born (CEB) as at the time of the survey (0–2, 3–5 and 6 or more), exposure to media was classified as yes for those who had listened to radio or watched television or read newspaper or accessed social media at least once a week and no for those who had not [23] and the main decision-maker on a woman’s health (woman alone, woman with a partner, and other). The other decision-makers included the husband/partner alone, father or father-in-law, mother or mother-in-law, other male family members, and other female family members. Household wealth terciles were generated based on a wealth score computed using the principal component analysis approach using household assets and materials for the dwelling floor, roof, and external wall [45]. Variables on exposure to media and number of children ever born were not collected during the baseline survey. Data were explored descriptively using the median and interquartile range (IQR) for continuous variables and frequencies and percentages for categorical variables. Chi-square test was used to compare the difference between the categorical groups. The multivariable logistic model was used to assess the factors associated with the use of LAPM while controlling for other variables. All the variable were considered to be important in explaining the outcome and were adjusted for in the multivariable logistic regression. The crude (cOR) and adjusted odds ratio (aOR) with the 95% confidence interval (CI) for the estimates is reported, and a p-value of less than 0.05 was considered statistically significant. We used “svy” set command in Stata to account for clustering due to complex sampling design of the study at village level. All analysis were conducted in Stata (15, StataCorp LLC, College Station, TX). The study was approved by the Aga Khan University Institutional Ethics Review Committee and research permit provided by the National Commission for Science, Technology, and Innovation. County approvals were obtained from the Ministries of Health in Kisii and Kilifi Counties. Written informed consent were obtained from each participant before the start of data collection, with those who could not write providing consent using their thumbprint. Women aged 15–17 years old provided assent and additional consent from their parents/guardians or whoever they were comfortable with consenting on their behalf. The survey was conducted in line with the Helsinki Declaration on Research involving Human Subjects.

Materials

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop and implement mobile applications or text messaging services to provide pregnant women and new mothers with important health information, reminders for prenatal and postnatal care appointments, and access to teleconsultations with healthcare providers.

2. Community Health Worker (CHW) Training and Support: Strengthen the training and support for CHWs who play a crucial role in providing maternal health services in rural areas. This could include providing them with updated training materials, regular supervision and mentoring, and access to necessary medical supplies and equipment.

3. Telemedicine Services: Establish telemedicine services that allow pregnant women in remote areas to consult with healthcare providers through video calls or phone consultations. This can help address the shortage of healthcare professionals in rural areas and provide timely advice and guidance to pregnant women.

4. Transportation Support: Develop transportation initiatives that provide affordable and accessible transportation options for pregnant women to reach healthcare facilities for prenatal and postnatal care, as well as for emergency obstetric care when needed.

5. Community-Based Maternal Health Programs: Implement community-based programs that focus on raising awareness about maternal health, promoting healthy behaviors during pregnancy, and providing support networks for pregnant women. These programs can be facilitated by CHWs and community leaders to ensure cultural sensitivity and community engagement.

6. Integration of Family Planning Services: Strengthen the integration of family planning services within maternal health programs to ensure that women have access to a range of contraceptive options and can make informed decisions about their reproductive health.

7. Quality Improvement Initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that maternal health services are provided in a safe and respectful manner. This can include training healthcare providers on best practices, improving infrastructure and equipment, and implementing systems for monitoring and addressing any gaps in service delivery.

8. Financial Support: Explore innovative financing mechanisms, such as health insurance schemes or conditional cash transfer programs, to reduce financial barriers to accessing maternal health services. This can help ensure that cost is not a deterrent for women seeking care.

It is important to note that the specific recommendations should be tailored to the local context and needs of the target population.

AI Innovations Description

The study mentioned in the description focuses on factors associated with the use of long-acting reversible and permanent contraceptives (LAPM) among married women in rural Kenya. The study found that the prevalence of LAPM use in the targeted sub-counties of Kilifi and Kisii counties was higher than the national average. Factors associated with LAPM use included the number of children ever born and future fertility preference.

Based on the findings of the study, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Continued Health Promotion and Targeted Media Campaigns: Implement targeted media campaigns and health promotion activities in rural areas with low socioeconomic status. These campaigns should focus on raising awareness about the benefits and availability of LAPM, addressing misconceptions, and providing accurate information about family planning options.

2. Involvement of Men in Decision Making: Encourage programs that involve men in decision making regarding their partner’s health, including family planning. Engaging men in discussions about family planning can help increase their understanding and support for LAPM use, leading to improved access and utilization.

3. Strengthening Healthcare Infrastructure: Address structural challenges such as limited human healthcare resources, poor access to health services due to geographical and transportation barriers, and limited healthcare infrastructure. This can be done by increasing the number of healthcare providers, improving transportation networks, and expanding healthcare facilities in rural areas.

4. Collaboration with Community Health Volunteers (CHVs): Collaborate with CHVs to deliver family planning messages and provide counseling on LAPM. CHVs play a crucial role in reaching remote communities and can help increase awareness and acceptance of LAPM through community sensitization.

5. Integration of Family Planning Services: Integrate family planning services into existing healthcare programs and facilities. This can ensure that women have access to a range of contraceptive methods, including LAPM, during routine healthcare visits.

By implementing these recommendations, it is expected that access to maternal health will be improved, leading to better reproductive health outcomes for women in rural areas of Kenya.

AI Innovations Methodology

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

1. Increase availability of long-acting and permanent contraceptive methods (LAPM): Ensure that health facilities in rural areas have a sufficient supply of LAPM, including intrauterine contraceptive devices, implants, and male and female sterilization. This can be achieved through partnerships with pharmaceutical companies, government initiatives, and donor support.

2. Strengthen community sensitization and education: Implement targeted media campaigns and community outreach programs to raise awareness about the benefits and availability of LAPM. This can include radio and television advertisements, informational brochures, and community health volunteers providing education and counseling.

3. Improve access to family planning services: Address structural challenges such as limited human healthcare resources, poor access to health services due to geographical and transportation barriers, and limited healthcare infrastructure. This can involve increasing the number of healthcare providers, improving transportation networks, and expanding healthcare facilities in rural areas.

4. Involve men in decision-making: Encourage programs that involve men in decision-making regarding family planning and maternal health. This can be done through community engagement activities, workshops, and educational campaigns that emphasize the importance of shared decision-making between partners.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of women using LAPM, the number of healthcare facilities offering family planning services, and the level of awareness about family planning methods among the target population.

2. Collect baseline data: Gather data on the current status of the indicators before implementing the recommendations. This can be done through surveys, interviews, and data analysis of existing health records.

3. Implement the recommendations: Roll out the recommended interventions, such as increasing the availability of LAPM, conducting community sensitization campaigns, and improving access to family planning services. Monitor the implementation process and ensure that the interventions are being carried out effectively.

4. Collect post-intervention data: After a certain period of time, collect data on the indicators again to assess the impact of the recommendations. This can involve conducting follow-up surveys, analyzing health facility records, and tracking changes in awareness and utilization of family planning methods.

5. Analyze and compare data: Compare the baseline and post-intervention data to determine the impact of the recommendations on improving access to maternal health. Use statistical analysis techniques to identify significant changes and trends in the indicators.

6. Evaluate and adjust: Evaluate the effectiveness of the recommendations and identify areas for improvement. Based on the findings, make any necessary adjustments to the interventions to further enhance access to maternal health.

By following this methodology, it will be possible to simulate the impact of the recommendations on improving access to maternal health and make informed decisions for future interventions.

Authors & Co-Authors

Statistics:

Authors: 5

Identifiers:

DOI: 10.1371/journal.pone.0275575

Research Areas:

Community Interventions, Disparities, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Technology and Innovations

Study Countries:

Kenya

Study Design:

Case-Control Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Male & Female