Prevalence and factors associated with utilisation of postnatal care in Sierra Leone: a 2019 national survey

BMC Public Health, Volume 22, No. 1, Year 2022

Interpretation

Background: Within Sub-Saharan Africa, some countries still report unacceptably high rates of maternal and perinatal morbidity and mortality, despite improvements in the utilisation of maternity care services. Postnatal care (PNC) is one of the recommended packages in the continuum of maternity care aimed at reducing maternal and neonatal mortality. This study aimed to determine the prevalence and factors associated with PNC utilisation in Sierra Leone. Methods: We used Sierra Leone Demographic and Health Survey (UDHS) 2019 data of 7326 women aged 15 to 49 years. We conducted multivariable logistic regression to determine the factors associated with PNC utilisation, using SPSS version 25. Results: Out of 7326 women, 6625 (90.4, 95% CI: 89.9–91.2) had at least one PNC contact for their newborn, 6646 (90.7, 95% CI: 90.2–91.5) had a postnatal check after childbirth and 6274 (85.6, 95% CI: 85.0–86.6) had PNC for both their babies and themselves. Delivery by caesarean section (aOR 8.01, 95% CI: 3.37–19.07), having a visit by a health field worker (aOR 1.80, 95% CI: 1.46–2.20), having had eight or more ANC contacts (aOR 1.37, 95% CI: 1.08–1.73), having tertiary education (aOR 2.71, 95% CI: 1.32–5.56) and having no big problems seeking permission to access healthcare (aOR 1.51, 95% CI: 1.19–1.90) were associated with higher odds of PNC utilisation. On the other hand, being resident in the Northern (aOR 0.48, 95% CI: 0.29–0.78) and Northwestern regions (aOR 0.54, 95% CI: 0.36–0.80), belonging to a female headed household (aOR 0.69, 95% CI: 0.56–0.85) and being a working woman (aOR 0.66, 95% CI: 0.52–0.84) were associated with lower odds of utilizing PNC. Conclusion: Factors associated with utilisation of PNC services operate at individual, household, community and health system/policy levels. Some of them can be ameliorated by targeted government interventions to improve utilisation of PNC services. This study used secondary data from the 2019 Sierra Leone Demographic and Health Survey (SLDHS). Data were accessed from MEASURE DHS database at http://dhsprogram.com/data/available-datasets.cfm. SLDHS was a nationally representative cross-sectional survey implemented by Statistics Sierra Leone (Stats SL) with technical assistance from ICF intern through the DHS Program and funded by the United States Agency for International Development (USAID). The Demographic and Health Survey datasets are freely available to the public though researchers must register with MEASURE DHS and submit a request before accessing them. The 2019 SLDHS samples were selected using a stratified, two-stage cluster sampling design that resulted in the random selection of 13,872 households [4]. Detailed sampling procedures were published in the final report [4]. DHS uses different questionnaires; household questionnaire collects data on household environment, assets and basic demographic information of household members while women’s questionnaire collects data about women’s reproductive health, domestic violence and nutrition indicators. The individual record (IR) file used in this study contains all the collected data in the women’s questionnaire for de facto women plus some variables from the household questionnaire. This secondary analysis included women aged 15 to 49 years who had a live birth within 5 years preceding the survey and were either permanent residents or slept in the selected household the night preceding the survey. Out of the total weighted sample of 15,574 women in the data set, only 7326 had given birth within 5 years preceding the survey (Table 1). Of the 7326 women, 126 women had missing data leading to a total of 7200 women for logistic regression analysis (Table 3). Socio-demographic characteristics of women in Sierra Leone as per the 2019 SLDHS amissing 113 (1.5%) respondents bmissing 13 (0.2%) respondents Factors associated with PNC utilisation in Sierra Leone as per the 2019 SLDHS asignificant at < 0.05 The outcome variable was PNC utilisation which was considered as atleast one postnatal check for both the mother and the neonate within the postpartum period and was constructed into a binary variable coded as one (1) if the mother and neonate utilised PNC and zero (0) if no PNC utilisation for both mother and the neonate. This study included determinants of ANC initiation timing and frequency based on evidence from available literature and data [1, 7, 11, 14]. Twenty-one explanatory variables were used in this study. Maternal age was categorised as; (15–19 years, 20–34 years and 35–49 years). Wealth index is a measure of relative household economic status and was calculated by UDHS from information on household asset ownership using Principal Component Analysis, which was further categorised into poorest, poorer, middle, richer and richest quintiles [23]. Place of Residence was categorised into urban and rural. Region was categorised into four; Northern, Eastern, Southern, Western and Northwestern while level of Education was categorised into no education, primary education, secondary and tertiary education. Household Size was categorised as less than seven members and seven and above members (based on the dataset average of seven members per household). Sex of household head was categorised as male or female, working status categorized as: not working and working while marital status as married (this included those in formal and informal unions) and not married. Religion was categorised as Muslims and Christians and others, problems seeking permission and distance to health facility were categorised as big problem and no big problem while exposure to mass media and internet use (TV, radio, and newspapers) were categorized as yes and no. In the questionnaire, seeking permission to access healthcare and distance to health facility had three original responses: no problem, no big problem and big problem. However, none of the study participants reported no problem hence we only had two responses. Skilled birth attendance was categorised as yes and no, place of child birth as home and health facility and method of delivery as caesarean section and vaginal. Analysis was carried out based on the weighted count to account for the unequal probability sampling in different strata and to ensure representativeness of the survey results at the national and regional level. In order to account for the multi-stage cluster study design, complex sample package of SPSS (version 25.0) statistical software was used. We used SPSS version 25.0 statistical software complex samples package incorporating the following variables in the analysis plan to account for the multistage sample design inherent in the DHS dataset: individual sample weight, sample strata for sampling errors/design, and cluster number [24–26]. Use of complex samples package ensures that the sample design is incorporated into the analysis leading to accurate and reliable results. Before multivariable logistic regression, each exposure/predictor (independent variable) was assessed separately for its association with PNC utilisation using bivariable logistic regression and we presented the crude odds ratio (COR), 95% confidence interval (CI) and p-values. Independent variables associated with PNC utilisation with a p-value ≤0.25 at the bivariable level, and not strongly collinear with other independent variables (considered variance inflation factor (VIF) less than 2.5) [27] with other independent variables were considered for multivariable logistic regression to assess the independent effect of each variable on the PNC utilisation. Residence, wealth index, skilled birth attendance and place of delivery were not included in the multivariable model because they had VIFs above 2.5 with many other independent variables. Adjusted odds ratios (AOR), 95% confidence intervals (CI) and p-values were calculated with statistical significance level set at p-value < 0.05. Sensitivity analysis was done including the variables that had VIF above 2.5 but less than 5 and results are shown in Supplementary file 1.

AI Digest

Study Justification:

This study aimed to investigate the prevalence and factors associated with the utilization of postnatal care (PNC) in Sierra Leone. Despite improvements in maternity care services, maternal and neonatal morbidity and mortality rates remain high in some countries in Sub-Saharan Africa. PNC is an essential component of maternity care that can help reduce these rates. Understanding the factors influencing PNC utilization can inform targeted interventions to improve access and utilization of PNC services.

Study Highlights:

– The study used data from the 2019 Sierra Leone Demographic and Health Survey, which included 7,326 women aged 15 to 49 years.
– Out of the total sample, 90.4% of women had at least one PNC contact for their newborn, 90.7% had a postnatal check after childbirth, and 85.6% had PNC for both themselves and their babies.
– Factors associated with higher odds of PNC utilization included delivery by caesarean section, having a visit by a health field worker, having eight or more antenatal care contacts, having tertiary education, and having no big problems seeking permission to access healthcare.
– Factors associated with lower odds of PNC utilization included being resident in the Northern and Northwestern regions, belonging to a female-headed household, and being a working woman.

Study Recommendations:

– The findings suggest that interventions to improve PNC utilization should target individual, household, community, and health system/policy levels.
– Government interventions should focus on improving access to healthcare, particularly in regions with lower PNC utilization rates.
– Efforts should be made to increase awareness and education about the importance of PNC, especially among women in female-headed households and working women.
– Collaboration between health field workers and communities can help promote PNC utilization and address barriers to access.

Key Role Players:

– Government health departments and ministries
– Non-governmental organizations (NGOs) working in maternal and child health
– Community health workers and volunteers
– Health facility staff, including doctors, nurses, and midwives
– Local community leaders and organizations
– Researchers and academics in the field of maternal and child health

Cost Items for Planning Recommendations:

– Training and capacity building for health workers on PNC guidelines and best practices
– Development and dissemination of educational materials and campaigns
– Infrastructure improvements in health facilities, including equipment and supplies for PNC services
– Outreach programs and community engagement activities
– Monitoring and evaluation of PNC utilization rates and outcomes
– Research and data collection to inform evidence-based interventions
– Coordination and collaboration between stakeholders through meetings and workshops

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it is based on a nationally representative survey and includes a large sample size. The study used multivariable logistic regression to determine factors associated with postnatal care (PNC) utilization. The results provide adjusted odds ratios and confidence intervals for various factors. To improve the evidence, the study could have included a discussion of potential limitations and biases in the data, as well as recommendations for future research or interventions to improve PNC utilization.

Abstract

This study used secondary data from the 2019 Sierra Leone Demographic and Health Survey (SLDHS). Data were accessed from MEASURE DHS database at http://dhsprogram.com/data/available-datasets.cfm. SLDHS was a nationally representative cross-sectional survey implemented by Statistics Sierra Leone (Stats SL) with technical assistance from ICF intern through the DHS Program and funded by the United States Agency for International Development (USAID). The Demographic and Health Survey datasets are freely available to the public though researchers must register with MEASURE DHS and submit a request before accessing them. The 2019 SLDHS samples were selected using a stratified, two-stage cluster sampling design that resulted in the random selection of 13,872 households [4]. Detailed sampling procedures were published in the final report [4]. DHS uses different questionnaires; household questionnaire collects data on household environment, assets and basic demographic information of household members while women’s questionnaire collects data about women’s reproductive health, domestic violence and nutrition indicators. The individual record (IR) file used in this study contains all the collected data in the women’s questionnaire for de facto women plus some variables from the household questionnaire. This secondary analysis included women aged 15 to 49 years who had a live birth within 5 years preceding the survey and were either permanent residents or slept in the selected household the night preceding the survey. Out of the total weighted sample of 15,574 women in the data set, only 7326 had given birth within 5 years preceding the survey (Table 1). Of the 7326 women, 126 women had missing data leading to a total of 7200 women for logistic regression analysis (Table 3). Socio-demographic characteristics of women in Sierra Leone as per the 2019 SLDHS amissing 113 (1.5%) respondents bmissing 13 (0.2%) respondents Factors associated with PNC utilisation in Sierra Leone as per the 2019 SLDHS asignificant at < 0.05 The outcome variable was PNC utilisation which was considered as atleast one postnatal check for both the mother and the neonate within the postpartum period and was constructed into a binary variable coded as one (1) if the mother and neonate utilised PNC and zero (0) if no PNC utilisation for both mother and the neonate. This study included determinants of ANC initiation timing and frequency based on evidence from available literature and data [1, 7, 11, 14]. Twenty-one explanatory variables were used in this study. Maternal age was categorised as; (15–19 years, 20–34 years and 35–49 years). Wealth index is a measure of relative household economic status and was calculated by UDHS from information on household asset ownership using Principal Component Analysis, which was further categorised into poorest, poorer, middle, richer and richest quintiles [23]. Place of Residence was categorised into urban and rural. Region was categorised into four; Northern, Eastern, Southern, Western and Northwestern while level of Education was categorised into no education, primary education, secondary and tertiary education. Household Size was categorised as less than seven members and seven and above members (based on the dataset average of seven members per household). Sex of household head was categorised as male or female, working status categorized as: not working and working while marital status as married (this included those in formal and informal unions) and not married. Religion was categorised as Muslims and Christians and others, problems seeking permission and distance to health facility were categorised as big problem and no big problem while exposure to mass media and internet use (TV, radio, and newspapers) were categorized as yes and no. In the questionnaire, seeking permission to access healthcare and distance to health facility had three original responses: no problem, no big problem and big problem. However, none of the study participants reported no problem hence we only had two responses. Skilled birth attendance was categorised as yes and no, place of child birth as home and health facility and method of delivery as caesarean section and vaginal. Analysis was carried out based on the weighted count to account for the unequal probability sampling in different strata and to ensure representativeness of the survey results at the national and regional level. In order to account for the multi-stage cluster study design, complex sample package of SPSS (version 25.0) statistical software was used. We used SPSS version 25.0 statistical software complex samples package incorporating the following variables in the analysis plan to account for the multistage sample design inherent in the DHS dataset: individual sample weight, sample strata for sampling errors/design, and cluster number [24–26]. Use of complex samples package ensures that the sample design is incorporated into the analysis leading to accurate and reliable results. Before multivariable logistic regression, each exposure/predictor (independent variable) was assessed separately for its association with PNC utilisation using bivariable logistic regression and we presented the crude odds ratio (COR), 95% confidence interval (CI) and p-values. Independent variables associated with PNC utilisation with a p-value ≤0.25 at the bivariable level, and not strongly collinear with other independent variables (considered variance inflation factor (VIF) less than 2.5) [27] with other independent variables were considered for multivariable logistic regression to assess the independent effect of each variable on the PNC utilisation. Residence, wealth index, skilled birth attendance and place of delivery were not included in the multivariable model because they had VIFs above 2.5 with many other independent variables. Adjusted odds ratios (AOR), 95% confidence intervals (CI) and p-values were calculated with statistical significance level set at p-value < 0.05. Sensitivity analysis was done including the variables that had VIF above 2.5 but less than 5 and results are shown in Supplementary file 1.

Materials

Innovations

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and reminders about postnatal care, including appointment reminders, breastfeeding support, and information on common postpartum complications.

2. Community Health Workers: Train and deploy community health workers to provide postnatal care services in remote or underserved areas. These workers can conduct home visits, provide education on postnatal care, and identify and refer women with complications.

3. Telemedicine: Establish telemedicine services to connect women in rural areas with healthcare providers who can provide remote consultations and guidance on postnatal care. This can help overcome geographical barriers and improve access to specialized care.

4. Maternal Health Vouchers: Implement a voucher system that provides financial assistance to women for accessing postnatal care services. This can help reduce financial barriers and increase utilization of postnatal care.

5. Public Awareness Campaigns: Launch public awareness campaigns to educate women and their families about the importance of postnatal care and the available services. This can help address cultural and social barriers that may prevent women from seeking care.

6. Strengthening Health Systems: Invest in improving the overall health system infrastructure, including increasing the number of healthcare facilities, ensuring availability of essential supplies and medications, and training healthcare providers on postnatal care.

7. Integration of Services: Integrate postnatal care services with other maternal and child health services, such as antenatal care and family planning. This can improve continuity of care and increase the likelihood of women accessing postnatal care.

8. Maternity Waiting Homes: Establish maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away. This can ensure that women have a safe place to stay before and after childbirth, increasing their access to postnatal care.

9. Public-Private Partnerships: Foster partnerships between the government and private sector to improve access to postnatal care. This can involve leveraging private healthcare providers and facilities to expand service coverage.

10. Quality Improvement Initiatives: Implement quality improvement initiatives to enhance the overall quality of postnatal care services, including training healthcare providers, improving infection prevention and control measures, and ensuring respectful and patient-centered care.

It is important to note that the specific context and needs of Sierra Leone should be taken into consideration when implementing these innovations.

AI Innovations Description

Based on the information provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Targeted Government Interventions: The study identified several factors associated with the utilization of postnatal care (PNC) services in Sierra Leone. To improve access to maternal health, the government can develop targeted interventions that address these factors. For example, interventions can focus on increasing the number of health field workers who visit postnatal mothers, promoting the importance of PNC during antenatal care visits, and ensuring that women with tertiary education have access to PNC services.

2. Mobile Health (mHealth) Solutions: Utilizing mobile technology can be an innovative way to improve access to maternal health services. Mobile health (mHealth) solutions can be developed to provide information and reminders about the importance of PNC, as well as facilitate appointment scheduling and follow-up care. This can help overcome barriers such as distance to health facilities and lack of awareness about PNC services.

3. Community-Based Interventions: Engaging the community can play a crucial role in improving access to maternal health. Community health workers can be trained to provide PNC services and educate women about the importance of postnatal care. This can help increase awareness, reduce stigma, and ensure that women receive the necessary care in their own communities.

4. Public-Private Partnerships: Collaborating with private healthcare providers can expand access to maternal health services. The government can establish partnerships with private clinics and hospitals to ensure that PNC services are available in both public and private healthcare facilities. This can help increase the options available to women and reduce the burden on public healthcare facilities.

5. Financial Support: Lack of financial resources can be a barrier to accessing maternal health services. The government can explore innovative financing mechanisms, such as health insurance schemes or conditional cash transfers, to provide financial support to women seeking PNC services. This can help alleviate the financial burden and increase utilization of PNC services.

Overall, developing and implementing these recommendations as innovative solutions can help improve access to maternal health services, specifically postnatal care, in Sierra Leone.

AI Innovations Methodology

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

1. Strengthening ANC services: Increase the number of ANC contacts and promote early initiation of ANC to ensure that pregnant women receive comprehensive care throughout their pregnancy.

2. Enhancing health worker visits: Increase the frequency of health worker visits to provide education, support, and monitoring during the postnatal period.

3. Addressing barriers to healthcare access: Implement targeted interventions to address the challenges faced by women in seeking permission to access healthcare, especially in rural areas.

4. Improving education and awareness: Promote education and awareness campaigns to inform women about the importance of PNC and the available services.

5. Addressing regional disparities: Develop strategies to address the lower utilization of PNC services in the Northern and Northwestern regions of Sierra Leone.

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

1. Data collection: Collect data on the current utilization of PNC services, including the number of women accessing PNC, their demographic characteristics, and factors associated with PNC utilization.

2. Baseline analysis: Analyze the collected data to determine the current prevalence and factors associated with PNC utilization in Sierra Leone.

3. Intervention design: Based on the identified factors associated with PNC utilization, design interventions targeting the identified barriers and challenges.

4. Simulation modeling: Use simulation modeling techniques, such as agent-based modeling or system dynamics modeling, to simulate the impact of the interventions on improving access to maternal health. This involves creating a virtual model that represents the healthcare system and population dynamics, and simulating different scenarios with the interventions in place.

5. Evaluation and analysis: Evaluate the simulated scenarios to assess the potential impact of the interventions on improving access to maternal health. Analyze the results to identify the most effective interventions and their potential outcomes.

6. Recommendations: Based on the simulation results, provide recommendations for implementing the interventions that are most likely to have a positive impact on improving access to maternal health in Sierra Leone.

It is important to note that the methodology described above is a general framework and the specific details may vary depending on the available data, resources, and expertise.

Authors & Co-Authors

Statistics:

Citations: 5

Authors: 4

Identifiers:

DOI: 10.1186/s12889-022-12494-5

Research Areas:

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

Study Countries:

Sierra Leone

Study Design:

Case-Control Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female