Predictors of women’s utilization of primary health care for skilled pregnancy care in rural Nigeria

  • BMC Pregnancy and Childbirth, Volume 18, No. 1, Year 2018

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Study Justification:
– The study aims to investigate the factors that predict the utilization of primary health care (PHC) facilities for skilled pregnancy care in rural Nigeria.
– This is important because PHC was designed to provide universal access to skilled maternity care for the prevention of maternal deaths, but little is known about its utilization in rural areas.
– Understanding the factors that influence the use of PHCs for antenatal and delivery care can help identify barriers and inform interventions to improve maternal health care in rural Nigeria.
Study Highlights:
– The study was conducted in Esan South East and Etsako East LGAs of Edo State, Nigeria.
– A total of 1408 randomly selected women of reproductive age were interviewed using a structured questionnaire.
– The study found that the antenatal care attendance rate was 62.1%, and the skilled delivery rate at PHCs was 46.6%.
– Reasons for use and non-use of PHCs for antenatal and delivery care were related to perceptions about long distances to PHCs, high costs of services, and poor quality of PHC service delivery.
– Level of education and marital status were significantly related to the use of PHCs for antenatal care.
– Factors such as education level, religion, partner’s employment, and number of children significantly influenced the odds of delivering in PHCs.
Recommendations for Lay Reader and Policy Maker:
– Efforts should be made to address the limiting factors of distance, costs, and quality of care in PHCs.
– Creative and innovative approaches should be used to increase the utilization of skilled pregnancy care in PHCs and reduce maternal mortality in rural Nigeria.
– Interventions should focus on improving access to PHCs, reducing costs, and enhancing the quality of care provided.
– Education and awareness programs should be implemented to promote the importance of skilled maternity care and encourage women to utilize PHCs.
– Collaboration between government agencies, healthcare providers, and community organizations is crucial to implement and sustain these interventions.
Key Role Players:
– Government agencies responsible for healthcare policy and funding.
– Healthcare providers, including doctors, nurses, and midwives.
– Community organizations and leaders.
– Non-governmental organizations (NGOs) working in maternal health.
– Researchers and academics specializing in maternal health.
Cost Items for Planning Recommendations:
– Infrastructure development: Improving and expanding PHC facilities.
– Training and capacity building: Providing training for healthcare providers on skilled maternity care.
– Outreach and awareness programs: Conducting education campaigns to promote the use of PHCs.
– Subsidies and financial support: Implementing measures to reduce the costs of services for pregnant women.
– Monitoring and evaluation: Establishing systems to monitor the implementation and impact of interventions.
– Research and data collection: Conducting further studies to assess the effectiveness of interventions and inform future policies.

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 design is a cross-sectional community-based study, which provides valuable insights into the factors that predict the use of primary health care facilities for skilled maternity care in rural Nigeria. The sample size of 1408 randomly selected women of reproductive age is adequate for this type of study. The data were analyzed using descriptive and multivariate statistical methods, which adds rigor to the analysis. The results show the antenatal care attendance rate and skilled delivery rate at primary health care facilities, as well as the reasons for use and non-use of these facilities. The study also identifies significant predictors of facility use for antenatal and delivery care. However, there are some limitations to consider. The study is based on self-reported data, which may be subject to recall bias. Additionally, the study is limited to two specific rural areas in Nigeria, which may limit the generalizability of the findings. To improve the strength of the evidence, future research could consider using a longitudinal design to better understand the causal relationships between the predictors and facility use. It would also be beneficial to include a larger and more diverse sample to enhance the generalizability of the findings.

Background: Although Primary Health Care (PHC) was designed to provide universal access to skilled pregnancy care for the prevention of maternal deaths, very little is known of the factors that predict the use of PHC for skilled maternity care in rural parts of Nigeria – where its use is likely to have a greater positive impact on maternal health care. The objective of this study was to identify the factors that lead pregnant women to use or not use existing primary health care facilities for antenatal and delivery care. Methods: The study was a cross-sectional community-based study conducted in Esan South East and Etsako East LGAs of Edo State, Nigeria. A total of 1408 randomly selected women of reproductive age were interviewed in their households using a pre-tested structured questionnaire. The data were analyzed with descriptive and multivariate statistical methods. Results: The results showed antenatal care attendance rate by currently pregnant women of 62.1%, and a skilled delivery of 46.6% by recently delivered women at PHCs, while 25% of women delivered at home or with traditional birth attendants. Reasons for use and non-use of PHCs for antenatal and delivery care given by women were related to perceptions about long distances to PHCs, high costs of services and poor quality of PHC service delivery. Chi-square test of association revealed that level of education and marital status were significantly related to use of PHCs for antenatal care. The results of logistic regression for delivery care showed that women with primary (OR 3.10, CI 1.16-8.28) and secondary (OR 2.37, CI 1.19-4.71) levels education were more likely to receive delivery care in PHCs than the highly educated. Being a Muslim (OR 1.56, CI 1.00-2.42), having a partner who is employed in Estako East (OR 2.78, CI 1.04-7.44) and having more than five children in Esan South East (OR 2.00, CI 1.19-3.35) significantly increased the odds of delivery in PHCs. The likelihood of using a PHC facility was less for women who had more autonomy (OR 0.75, CI 0.57-0.99) as compared to women with higher autonomy. Conclusion: We conclude that efforts devoted to addressing the limiting factors (distance, costs and quality of care) using creative and innovative approaches will increase the utilization of skilled pregnancy care in PHCs and reduce maternal mortality in rural Nigeria.

The study was a cross-sectional community-based study conducted in Esan South East and Etsako East LGAs in Edo State in southern Nigeria. Edo State is one of Nigeria’s 36 federating States located in the South-South geo-political zone of the country. Both LGAs are located in the rural and riverine areas of the state, adjacent to River Niger, with Estako East in the northern part of the Edo State part of the river, while Esan South East is in the southern part. Administratively, each LGA comprises of 10 wards, with several communities located in each ward. The two LGAs have a total population of 313,717 persons, with Esan South East accounting for 167,721 and Etsako East LGA accounting for 145,996. The principal sources of maternity care in the two LGAs are Primary Health Centres (PHCs). However, Esan South East LGA has one General Hospital in Ubiaja (headquarters of the LGA) while Etsako East has one General Hospital in Agenebode (the LGA administrative headquarters) and another in nearby Fugar City. Several private hospitals also exist in both LGAs that offer maternal and child health services of various degrees of quality. These public and private facilities are used as additional to the existing PHCs or for referral maternal health services. The study was drawn from a survey conducted in July–August, 2017 as part of baseline data for the design of an on-going intervention research project to increase the access of rural women to skilled pregnancy care in 20 communities in Esan South East and Etsako East LGAs. A sample size of 1450 was derived for the project using the following formula: p0 = utilization of PHC for maternal and perinatal in the control arm (assumed to be − 5 reduction in the prevalence in the experiment site). p1 = utilization of PHC for maternal and perinatal care in the experimental arm. zα = Two-sided standard normal variate at 95% level of significance = 1.96. zβ = Statistical power at 80% = 0.84; n1 = no of study participants in the experimental group. n2 = no of study participants in the control group. We assume 50% since there is no literature from the geographical location of the study which reported the prevalence of utilization of PHCs for maternal and perinatal health care. Thus: Total sample size = 1318. 10% adjustment for non-response = 132. Total = 1450 (725 respondents in the experiment LGA and 725 in the control LGA). A multi-stage sampling technique was used to select communities and the respondents in each LGA. Two rural LGAs (Esan South East and Etsako East) were purposively selected from the 18 LGAs in Edo state. Each LGA is divided into 10 health/administrative wards, with each ward made up of communities. Twenty (20) communities were selected purposively for the study – 10 from each LGA. Five communities per LGA were selected from where a PHC facility is located, while the other five communities were those in areas where there are no PHC facilities. Particular communities were selected systematically. In Esan South East, PHCs are located in 24 communities, while 75 communities have no PHCs. In contrast, in Etsako East, PHC facilities are located in 27 communities, while 15 communities had no PHC facilities. A sample interval was generated and 5 communities were selected systematically from a list of communities with PHCs and 5 from communities without a PHC in each LGA. Within communities, households were listed and the number of women of reproductive age in each household was obtained. All eligible women in each household were interviewed. The eligibility criteria were age 15–45 years, ever married, currently pregnant or have had a birth in the 5 years preceding the survey. In Etsako, 1487 households were listed and there were 1051 women of reproductive age in the households. Out of the 1051, 707 eligible women were interviewed with a non-response rate of 2.5%. In Esan South East, 1975 households were listed with 1084 women of reproductive age, 701 eligible women were interviewed with 3.3% non-response. A total of 1408 eligible women were interviewed in the two LGAs, with 2.9% overall non-response rate. A questionnaire prepared by the investigators was used for data collection. The instrument (questionnaire) was pretested in a rural community with similar characteristics with the study locations. The questionnaire consisted of five sections. Section one contained the respondents’ socio-demographic characteristics; section 2 was related to partners’ and other family characteristics; section 3 contained questions on the respondents’ reproductive history; section 4 was on antenatal, intrapartum and postnatal care experience for current pregnancy and births in the preceding 5 years; while section 5 contained questions on reasons for use and non-use of PHCs for maternal and child care. Drawing from the literature, some reasons for use and non-use of a PHC facility for maternal health care were provided as multiple response options. The respondents selected as many options as are applicable to them. The following options of reasons for use were provided: cost not too much, no charges, facility is always open, provider is available, facility not far from my house, good quality service (subjective opinion of the respondent on the care provided in PHC facilities), husband wanted it, family wanted it, adequate security, other (specify). The reasons for non-use provided in the questionnaire were: cost too much, facilities not open, no provider in the facility, facility too far, no transport to facility, poor quality service (subjective view of the respondent on the care received), husband did not allow, family did not allow, no time because baby came suddenly, my culture forbids, no security, and other (specify). Additional reasons for use and non-use shown in the result tables were drawn from the other (specify) category. The questionnaire was entered into Computer-Assisted Personal Interviewing (CAPI) using a Census and Survey Processing System (CSPro) software (CSentry). CSPro is a public domain software package developed by the US Census Bureau and ICF International. It is widely used for entering, editing, tabulating and disseminating census and survey data. The software runs on the Microsoft windows and Android families of operating systems [33]. Thus, instead of the paper and pen interviewing, the CAPI facilitated accuracy and speed in the data collection process. The questionnaire was administered through face-to-face interviewing by trained field assistants. The questions were fielded in English or in Pidgin English as appropriate, since all women in both communities either understand English or Pidgin English. The dependent variable for antenatal care was place of antenatal care: PHC facility coded 1 and other facilities/home coded 0. The dependent variable for delivery care was place of delivery; use of a PHC facility was coded 1 while other facilities and home was coded 0. Drawing on the model of health services utilization and past studies on utilization of facilities for maternal care in Nigeria, the following independent variables were included in the analyses: age, highest level of education, exposure to media, religion, employment (working and not working), marital status (married, living together, widowed, divorced, and separated), age at marriage, partner’s age, partner’s highest education, partner’s employment, who pays for respondent’s health care (respondent alone, husband alone or others, and respondent with husband), level of autonomy (less, more and much), number of living children, education difference between respondent and partner (both have no education, husband more educated than wife, wife more educated than partner, and same level of education but not none), and LGA. Exposure to media was generated with frequency of listening to radio and watching television. The response options were everyday, at least once a week, less than once a week, and not at all. The responses were aggregated to generate a three-category measure of exposure to the media: high, moderate and no exposure. No exposure refers to neither listens to radio nor to television at all. An index for autonomy was generated with responses to 6 questions on ownership of land/house, participation in household decisions on respondent’s health, major purchases, daily purchases, visits to family and friends, food to be cooked. Ownership of land or house was included because women in the study location are allowed to own land or a house if they wish. The response options were respondent alone, husband alone, respondent and husband, and others. These responses were further collapsed into two categories labeled respondent alone or respondent with husband indicating autonomy (coded 1) husband alone & others indicating no autonomy (coded 0) for participation in decisions. Ownership of land/house was categorized into respondent alone or with husband indicating autonomy (coded 1), owns no land/house and husband alone owns as no autonomy (coded 0). Using principal component analysis, a three-category index of autonomy was generated (less, more and much); scale reliability coefficient was 0.70. A response of 0 in all 6 questions and 1 in 1–2 questions was less autonomy; response of 1 in 3–4 questions was more autonomy, and a response of 1 in 5–6 questions was much autonomy. Women’s participation in household decision-making, her health care, mobility, and ownership of land among others have been used in many previous studies as measures of women’s autonomy [34–36]. The current analysis is based on antenatal care for currently pregnant respondents, and delivery or intrapartum care for the most recent births by the respondents. The data were extracted from the CAPI devise, cleaned and analyzed with STATA 12 for windows. To describe the characteristics of the respondents, univariate analysis using percentages and summary statistics was conducted. Reasons for use and non-use of a PHC facility for maternal care (antenatal care for current pregnancy and delivery care for the most recent births) were elicited from multiple response options. The results are presented as number of responses and percentages for each of the specified options and a few additional categories drawn from the other (specify) option. To compare proportions for each reason for use and non-use of a PHC for antenatal and delivery care between the two LGAs, a two-sample test of proportions was conducted. Due to the small sample size for currently pregnant respondents who are receiving antenatal care (n = 175), a bivariate analysis using chi-squared test was conducted to test the relationship between the use of a PHC facility for antenatal care for currently pregnant respondents and selected characteristics of the respondents. Selection of the characteristics was based on their potential theoretical and practical influence on the use of a PHC facility for antenatal care. Binary logistic regression was conducted to determine the predictors of PHC facility use for delivery care during the most recent births by the respondents. Some of the independent variables were re-coded for the chi-squared test and the multivariate analysis because of zero or few cases in some categories. The variables that were re-coded for the chi-squared test were age, level of education, religion (traditionalist and others were dropped because they had few cases and cannot be merged with any other category), marital status, (widowed, divorced, and separated were dropped because of few cases even after collapsing the three as formerly married). Others were partner’s age, partner’s level of education, payment for respondent’s healthcare. In the multivariate analysis for delivery care, traditional and other religions were dropped due to few cases; age and partner’s age was entered as a continuous variables. The variables included in the logistic regression model were either significant in a bivariate logistic regression model at 0.05 or 0.10 level of significance or conceptually important drawing from the behavioral model of health services utilization, past studies and the authors’ knowledge of the study population. A Wald test was also conducted to test whether the explanatory variables in the logit model are simultaneously equal to zero. The test result was significant indicating that including these variables creates a statistically significant improvement in the fit of the model. The results of the logistic regression are presented as odds ratio (OR) with 95% confidence interval for the entire study population and for each LGA. Statistical significance for all the statistical analysis was set at 0.05.

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

1. Mobile Health Clinics: Implementing mobile health clinics that travel to rural areas, bringing skilled pregnancy care directly to women who may have limited access to primary health care facilities.

2. Telemedicine: Utilizing telemedicine technology to connect pregnant women in rural areas with healthcare professionals, allowing them to receive prenatal care and consultations remotely.

3. Community Health Workers: Training and deploying community health workers in rural communities to provide education, support, and basic prenatal care to pregnant women, bridging the gap between communities and formal healthcare facilities.

4. Financial Incentives: Implementing financial incentives, such as subsidies or cash transfers, to encourage pregnant women in rural areas to seek skilled pregnancy care at primary health care facilities.

5. Improving Infrastructure: Investing in infrastructure development to improve transportation networks and access to primary health care facilities, reducing the barriers of distance and transportation costs.

6. Quality Improvement Initiatives: Implementing quality improvement initiatives at primary health care facilities to address concerns about the poor quality of care, ensuring that women receive skilled and respectful maternity care.

7. Health Education Programs: Developing and implementing health education programs that specifically target rural communities, providing information on the importance of skilled pregnancy care and addressing misconceptions or cultural barriers.

8. Partnerships with Traditional Birth Attendants: Collaborating with traditional birth attendants to improve their skills and knowledge, ensuring that they can provide safe and appropriate care to pregnant women while also promoting referrals to primary health care facilities when necessary.

9. Public-Private Partnerships: Establishing partnerships between public and private healthcare providers to expand access to skilled pregnancy care in rural areas, leveraging the resources and expertise of both sectors.

10. Data-Driven Approaches: Using data and analytics to identify areas with low utilization of primary health care facilities for skilled maternity care, allowing for targeted interventions and resource allocation to improve access.

These innovations, when implemented effectively, have the potential to improve access to skilled pregnancy care in rural Nigeria and reduce maternal mortality rates.
AI Innovations Description
The study conducted in rural Nigeria identified several factors that predict the use of Primary Health Care (PHC) facilities for skilled maternity care. These factors include perceptions about long distances to PHCs, high costs of services, and poor quality of PHC service delivery. The study also found that level of education and marital status were significantly related to the use of PHCs for antenatal care.

Based on these findings, here are some recommendations that can be developed into an innovation to improve access to maternal health:

1. Improve infrastructure: Address the issue of long distances to PHCs by improving the infrastructure and accessibility of these facilities. This can be done by building more PHCs in rural areas and ensuring that they are easily accessible to pregnant women.

2. Reduce costs: Find innovative ways to reduce the costs associated with skilled maternity care at PHCs. This can include providing subsidies or financial assistance to pregnant women who cannot afford the services, implementing community-based health insurance schemes, or exploring public-private partnerships to make services more affordable.

3. Enhance quality of care: Invest in training and capacity building for healthcare providers at PHCs to improve the quality of care provided. This can include training on best practices for antenatal and delivery care, as well as improving the overall infrastructure and equipment available at PHCs.

4. Increase awareness and education: Implement community-based education programs to raise awareness about the importance of skilled maternity care and the services available at PHCs. This can include conducting health campaigns, organizing community meetings, and using local media channels to disseminate information.

5. Empower women: Promote women’s autonomy and decision-making power in accessing maternal health services. This can be done through community empowerment programs that aim to increase women’s knowledge and decision-making abilities regarding their own healthcare.

By implementing these recommendations, it is possible to increase the utilization of skilled pregnancy care in PHCs and reduce maternal mortality in rural Nigeria.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations to improve access to maternal health in rural Nigeria:

1. Improve infrastructure: Enhance the physical infrastructure of Primary Health Centers (PHCs) in rural areas by providing necessary equipment, supplies, and facilities. This includes ensuring the availability of clean water, electricity, and adequate space for antenatal and delivery care.

2. Increase healthcare workforce: Increase the number of skilled healthcare providers, such as doctors, nurses, and midwives, in rural areas. This can be achieved through recruitment and deployment strategies, as well as training and capacity building programs.

3. Reduce financial barriers: Implement strategies to reduce the financial burden associated with accessing maternal healthcare services. This can include providing subsidies or financial assistance for antenatal and delivery care, as well as exploring options for health insurance coverage specifically for maternal health services.

4. Improve quality of care: Enhance the quality of care provided at PHCs by ensuring that healthcare providers are trained in evidence-based practices for maternal health. This includes promoting respectful and culturally sensitive care, as well as implementing quality assurance mechanisms to monitor and improve service delivery.

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

1. Define indicators: Identify key indicators that measure access to maternal health, such as the percentage of women receiving antenatal care at PHCs, the percentage of women delivering at PHCs, and the distance traveled to access care.

2. Collect baseline data: Gather baseline data on the identified indicators from the target population in rural Nigeria. This can be done through surveys, interviews, or existing data sources.

3. Implement interventions: Implement the recommended interventions in selected communities or areas within the target population. This may involve infrastructure improvements, workforce expansion, financial support programs, and quality improvement initiatives.

4. Monitor and evaluate: Continuously monitor and evaluate the impact of the interventions on the identified indicators. This can be done through follow-up surveys, interviews, or data analysis. Compare the post-intervention data with the baseline data to assess the changes in access to maternal health.

5. Analyze and interpret results: Analyze the data collected and interpret the results to determine the effectiveness of the interventions in improving access to maternal health. This can involve statistical analysis, such as comparing pre- and post-intervention data using appropriate statistical tests.

6. Adjust and refine interventions: Based on the findings, make adjustments and refinements to the interventions as needed. This may involve scaling up successful interventions, addressing any challenges or barriers identified, and continuously monitoring and evaluating the impact of the interventions over time.

By following this methodology, it is possible to simulate the impact of recommended interventions on improving access to maternal health in rural Nigeria and inform future decision-making and resource allocation.


Statistics:
Citations: 38
Identifiers:
DOI: 10.1186/s12884-018-1730-4
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
Study Countries:
Multi-Countries, Niger, Nigeria
Study Design:
Case-Control Study, Cross Sectional Study, Grounded Theory, randomised-control-trial
Study Approach:
Quantitative
Participants Gender:
Female
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