Patterns and determinants of dropout from maternity care continuum in Nigeria

BMC Pregnancy and Childbirth, Volume 16, No. 1, Year 2016

Interpretation

Background: The maternal, newborn and child health care continuum require that mother/child pair should receive the full package of antenatal, intrapartum and postnatal care in order to derive maximum benefits. Continuity of care is a challenge in sub-Saharan Africa. In this study, we investigate the patterns and factors associated with dropout in the continuum of maternity (antenatal, delivery and postnatal) care in Nigeria. Method: Using women recode file from the 2013 Nigeria Demographic and Health Survey, we analysed data on 20,467 women with an index birth within 5 years prior to data collection. Background characteristics and pattern of dropouts were summarised using descriptive statistics. The outcome variable was dropout which we explored in three stages: antenatal, antenatal-delivery, delivery-6 weeks postnatal visit. Multilevel logistic regression models were fitted to identify independent predictors of dropout at each stage. Measure of effect was expressed as Odds Ratio (OR) with 95 % confidence interval (CI). Results: Overall, 12,392 (60.6 %) of all women received antenatal care among whom 38.1 % dropout and never got skilled delivery assistance. Of those who received skilled delivery care, 50.8 % did not attend postnatal visit. The predictors of dropout between antenatal care and delivery include problem with getting money for treatment (OR = 1.18, CI: 1.04-1.34), distance to health facility (OR = 1.31, CI: 1.13-1.52), lack of formal education, being in poor wealth quintile (OR = 2.22, CI: 1.85-2.67), residing in rural areas (OR = 1.98, CI: 1.63-2.41). Regional differences between North East, North West and South West were significant. Between delivery and postnatal visit, the same factors were also associated with dropout. Conclusion: The rate of dropout from maternity care continuum is high in Nigeria and driven by low or lack of formal education, poverty and healthcare access problems (distance to facility and difficulty with getting money for treatment). Unexpectedly, dropouts are high in South east and South south as well as in the Northern regions. Intervention programs focusing on community outreach about the benefits of continuum of maternal healthcare package should be introduced especially for women in rural areas and lower socio-economic strata. According to the World Bank, Nigeria is a lower-middle-income country with a population of 178.5 million people as at year 2014. There is wide geographical, ethnic, and health diversity as reflected in many of her demographic and health indices. Administratively, the country comprised of 36 states and a Federal Capital grouped into 6 geo-political zones: North West, North East, North Central, South East, South West and South- South. The population is young with 46 % being under 15 years. There are 3 tiers of government (Local, State and Federal) with each tier playing active roles in maternal and child health (MCH) care programmes. Total fertiility rate as at 2013 was 5.5 with 23 % of women aged 15–19 years having began childbearing [7]. The life expectancy at birth is 52 years. Under-5 mortality declined from 201 deaths per 1000 live births in 2003 to 128 per 1000 live births in 2013 while the maternal mortality ratio was 576 maternal deaths per 100, 000 live births [7]. There have been several programmes to promote MCH in the country but the introduction of the Midwives Service Scheme (MSS) in 2009 was a landmark initiative. The MSS was initiated by the National Primary Health Care Development Agency to address the acute shortage of skilled birth attendants in rural areas. The data for this study was extracted from the individual women recode data file for the 2013 Nigeria Demographic Health Survey (NDHS). NDHS 2013 is the fifth round of a nationally representative survey conducted to monitor population and reproductive health among Nigerians. Sampling and data collection techniques of the NDHS 2013 are described in the full published report [7]. The NDHS 2013 used a stratified 3-stage cluster design to select eligible respondents. The primary sampling units, referred to as clusters in this study were enumeration areas selected from a sampling frame prepared for the 2006 population and housing census. With a fixed sample of 45 households per 904 clusters (rural – 532; urban – 372), a total of 40, 680 households were selected and 38, 948 women aged 15–49 years successfully interviewed. Analysis was restricted to women with an index birth within 5 years preceeding the survey. The dependent variable in this study was dropout from maternity care continuum which was considered in 3 stages. Stage 1(model I) is the level of antenatal care (ANC) at which dropout was coded ‘1’ for those who did not receive antenatal care and ‘0’ for those who did. ANC here means at least one visit with a doctor, nurse or midwife providing care. In stage 2 (model II), those who got antenatal care but did not received skilled delivery assistance (from doctor, nurse/midwife) were deemed to be dropout and coded 1 (and otherwise 0). At the third stage (model III), those who got skilled delivery assistance but without the 6 week postnatal care were deemed to have dropped out and subsequently coded 1 (and otherwise 0). Antenatal care was derived from response to questions 408 and 409 asking women concerning their last birth within 5 years before the NDHS 2013. The questions were “(1) did you see anyone for antenatal care for this pregnancy?” [Yes/NO]. Those who answered in the affirmative were further asked “whom did you see?” For this study, those who saw a doctor, nurse/midwife were classified as having received antenatal care. Skilled delivery was ascertained from responses to question 433 which was “who assisted with the delivery of (NAME)?” Those that were assisted by doctor, nurse/midwife were deemed to have received skilled delivery assistance. Status of sixth week postnatal checkup was derived from question 442 (“In the two months after (NAME) was born, did any healthcare provider check on his/her health…..”). Women who gave a ‘yes’ response to the question were categorized as having received the 6th week postnatal checkup. For each model, we controlled for other covariates which are known to be associated with maternal healthcare utilisation [8, 9]. These included: maternal age, birth order, education, household wealth status, partner’s education, decision making authority (own health and visits to friends/families), rural/urban residence,geo-political zone and problems in accessing health care (getting permission to go to health facility, getting money for treatment and consultation, distance to health facility, fear of going alone, and attitude of health workers). We fitted mutilevel logistic regression models for each stage of dropout from the maternity care continuum described above to identify the associated independent factors. The multilevel model serves 2 purposes. First, it enabled us to control for dependence in data collected among respondents who live in the same neighbourhood (clusters). Secondly, the multilevel model allowed us to control for the effect of unmeasured/unobserved or latent variables at the cluster (community) level. Intentionally, no contextual variables were derived for inclusion in the analyses because investigation of contextual variables was not our primary interest in this study. Measure of fixed effects were expressed as Odds Ratio (OR) with their 95 % conficence interval (CI). Where: Yij = log odds of dropout at any stage of the maternity care continuum for woman i in cluster (community) j 0j = intercept for individual-level model (average risk of dropout at any stage in cluster j) Xikj = covariates (education, age group, wealth index, etc) Kj = coefficients for the individual level covariates eij = error terms for the individual-level model We estimated the intra-cluster correlation (ICC) in the dependent variable for stages I to III. The likelihood ratio test was used to check the significance of the random effects (intra-community correlation). The ICC capture the proportion of the total variation in risk of dropout that is attributable to differences between cluster.

AI Digest

Study Justification:

– The study aims to investigate the patterns and factors associated with dropout in the continuum of maternity care in Nigeria.
– This is important because the maternal, newborn, and child health care continuum require that mother/child pairs receive the full package of antenatal, intrapartum, and postnatal care in order to derive maximum benefits.
– Continuity of care is a challenge in sub-Saharan Africa, including Nigeria.
– Understanding the reasons for dropout can help inform interventions and programs to improve maternal healthcare utilization.

Highlights:

– Overall, 60.6% of women received antenatal care, but 38.1% of them dropped out and never received skilled delivery assistance.
– Of those who received skilled delivery care, 50.8% did not attend postnatal visits.
– Factors associated with dropout include problems with getting money for treatment, distance to health facility, lack of formal education, being in a poor wealth quintile, and residing in rural areas.
– Regional differences between North East, North West, South East, South South, and South West were also significant.
– Unexpectedly, dropouts were high in South East and South South regions as well as in the Northern regions.

Recommendations for Lay Reader and Policy Maker:

– Intervention programs focusing on community outreach about the benefits of the continuum of maternal healthcare package should be introduced.
– These programs should especially target women in rural areas and lower socio-economic strata.
– Efforts should be made to address the problems of getting money for treatment and the distance to health facilities.
– Education and awareness campaigns should be conducted to emphasize the importance of antenatal, delivery, and postnatal care.
– Regional differences in dropout rates should be further investigated to tailor interventions to specific regions.

Key Role Players:

– National Primary Health Care Development Agency
– Ministry of Health
– Local Government Authorities
– Non-governmental organizations (NGOs) working in maternal and child health
– Community health workers
– Health facility staff
– Women’s groups and community leaders

Cost Items for Planning Recommendations:

– Community outreach programs
– Education and awareness campaigns
– Training and capacity building for health workers
– Transportation and logistics for reaching rural areas
– Communication materials and media campaigns
– Monitoring and evaluation activities
– Research and data collection for ongoing assessment and improvement

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a large sample size (20,467 women) and uses data from the 2013 Nigeria Demographic and Health Survey. The study also employs multilevel logistic regression models to identify independent predictors of dropout at each stage of the maternity care continuum. However, to improve the evidence, the abstract could provide more information on the methodology used, such as the specific variables included in the regression models and any potential limitations of the study.

Abstract

According to the World Bank, Nigeria is a lower-middle-income country with a population of 178.5 million people as at year 2014. There is wide geographical, ethnic, and health diversity as reflected in many of her demographic and health indices. Administratively, the country comprised of 36 states and a Federal Capital grouped into 6 geo-political zones: North West, North East, North Central, South East, South West and South- South. The population is young with 46 % being under 15 years. There are 3 tiers of government (Local, State and Federal) with each tier playing active roles in maternal and child health (MCH) care programmes. Total fertiility rate as at 2013 was 5.5 with 23 % of women aged 15–19 years having began childbearing [7]. The life expectancy at birth is 52 years. Under-5 mortality declined from 201 deaths per 1000 live births in 2003 to 128 per 1000 live births in 2013 while the maternal mortality ratio was 576 maternal deaths per 100, 000 live births [7]. There have been several programmes to promote MCH in the country but the introduction of the Midwives Service Scheme (MSS) in 2009 was a landmark initiative. The MSS was initiated by the National Primary Health Care Development Agency to address the acute shortage of skilled birth attendants in rural areas. The data for this study was extracted from the individual women recode data file for the 2013 Nigeria Demographic Health Survey (NDHS). NDHS 2013 is the fifth round of a nationally representative survey conducted to monitor population and reproductive health among Nigerians. Sampling and data collection techniques of the NDHS 2013 are described in the full published report [7]. The NDHS 2013 used a stratified 3-stage cluster design to select eligible respondents. The primary sampling units, referred to as clusters in this study were enumeration areas selected from a sampling frame prepared for the 2006 population and housing census. With a fixed sample of 45 households per 904 clusters (rural – 532; urban – 372), a total of 40, 680 households were selected and 38, 948 women aged 15–49 years successfully interviewed. Analysis was restricted to women with an index birth within 5 years preceeding the survey. The dependent variable in this study was dropout from maternity care continuum which was considered in 3 stages. Stage 1(model I) is the level of antenatal care (ANC) at which dropout was coded ‘1’ for those who did not receive antenatal care and ‘0’ for those who did. ANC here means at least one visit with a doctor, nurse or midwife providing care. In stage 2 (model II), those who got antenatal care but did not received skilled delivery assistance (from doctor, nurse/midwife) were deemed to be dropout and coded 1 (and otherwise 0). At the third stage (model III), those who got skilled delivery assistance but without the 6 week postnatal care were deemed to have dropped out and subsequently coded 1 (and otherwise 0). Antenatal care was derived from response to questions 408 and 409 asking women concerning their last birth within 5 years before the NDHS 2013. The questions were “(1) did you see anyone for antenatal care for this pregnancy?” [Yes/NO]. Those who answered in the affirmative were further asked “whom did you see?” For this study, those who saw a doctor, nurse/midwife were classified as having received antenatal care. Skilled delivery was ascertained from responses to question 433 which was “who assisted with the delivery of (NAME)?” Those that were assisted by doctor, nurse/midwife were deemed to have received skilled delivery assistance. Status of sixth week postnatal checkup was derived from question 442 (“In the two months after (NAME) was born, did any healthcare provider check on his/her health…..”). Women who gave a ‘yes’ response to the question were categorized as having received the 6th week postnatal checkup. For each model, we controlled for other covariates which are known to be associated with maternal healthcare utilisation [8, 9]. These included: maternal age, birth order, education, household wealth status, partner’s education, decision making authority (own health and visits to friends/families), rural/urban residence,geo-political zone and problems in accessing health care (getting permission to go to health facility, getting money for treatment and consultation, distance to health facility, fear of going alone, and attitude of health workers). We fitted mutilevel logistic regression models for each stage of dropout from the maternity care continuum described above to identify the associated independent factors. The multilevel model serves 2 purposes. First, it enabled us to control for dependence in data collected among respondents who live in the same neighbourhood (clusters). Secondly, the multilevel model allowed us to control for the effect of unmeasured/unobserved or latent variables at the cluster (community) level. Intentionally, no contextual variables were derived for inclusion in the analyses because investigation of contextual variables was not our primary interest in this study. Measure of fixed effects were expressed as Odds Ratio (OR) with their 95 % conficence interval (CI). Where: Yij = log odds of dropout at any stage of the maternity care continuum for woman i in cluster (community) j 0j = intercept for individual-level model (average risk of dropout at any stage in cluster j) Xikj = covariates (education, age group, wealth index, etc) Kj = coefficients for the individual level covariates eij = error terms for the individual-level model We estimated the intra-cluster correlation (ICC) in the dependent variable for stages I to III. The likelihood ratio test was used to check the significance of the random effects (intra-community correlation). The ICC capture the proportion of the total variation in risk of dropout that is attributable to differences between cluster.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services that provide pregnant women with information about antenatal care, delivery, and postnatal care. These tools can also send reminders for appointments and provide access to healthcare providers for virtual consultations.

2. Community Health Workers: Train and deploy community health workers to provide education and support to pregnant women in rural areas. These workers can conduct home visits, provide basic antenatal care, and refer women to healthcare facilities when necessary.

3. Telemedicine: Establish telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals via video conferencing. This can help address the issue of distance to health facilities and improve access to skilled care during delivery.

4. Financial Support Programs: Implement programs that provide financial assistance to pregnant women who face challenges in accessing healthcare due to lack of funds. This can help reduce the financial barriers to receiving antenatal, delivery, and postnatal care.

5. Public Awareness Campaigns: Launch campaigns to raise awareness about the importance of continuity of care throughout the maternity care continuum. These campaigns can target both urban and rural areas and emphasize the benefits of receiving antenatal, delivery, and postnatal care.

6. Infrastructure Development: Invest in improving the infrastructure of healthcare facilities, particularly in rural areas. This includes ensuring the availability of skilled healthcare providers, necessary medical equipment, and reliable transportation for pregnant women.

7. Partnerships and Collaboration: Foster partnerships between government agencies, non-governmental organizations, and private sector entities to collectively address the challenges of access to maternal health. This can involve sharing resources, expertise, and best practices to improve the overall quality and availability of maternal healthcare services.

It is important to note that the specific implementation of these innovations would require further research, planning, and collaboration with relevant stakeholders in the healthcare sector.

AI Innovations Description

Based on the study titled “Patterns and determinants of dropout from maternity care continuum in Nigeria,” the following recommendation can be developed into an innovation to improve access to maternal health:

Intervention programs focusing on community outreach about the benefits of the continuum of maternal healthcare package should be introduced, especially for women in rural areas and lower socio-economic strata. This can be achieved through the following steps:

1. Community Health Workers: Train and deploy community health workers to educate and raise awareness about the importance of antenatal, intrapartum, and postnatal care. These workers can provide information on the benefits of each stage of care and address any misconceptions or concerns.

2. Mobile Clinics: Establish mobile clinics that can travel to remote areas to provide antenatal, intrapartum, and postnatal care services. This will help overcome the challenge of distance to health facilities and ensure that women in rural areas have access to essential healthcare services.

3. Financial Support: Implement programs that provide financial support to women who face difficulties in accessing healthcare due to lack of money. This can include subsidies for transportation costs or the provision of health insurance coverage specifically for maternal health services.

4. Education and Empowerment: Implement programs that focus on improving education and empowering women, particularly in rural areas and lower socio-economic strata. This can include initiatives that provide scholarships or vocational training opportunities to young girls and women, enabling them to make informed decisions about their health and seek appropriate care.

5. Collaboration and Partnerships: Foster collaboration between government agencies, non-governmental organizations, and community-based organizations to ensure a coordinated and comprehensive approach to improving access to maternal health. This can involve sharing resources, expertise, and best practices to maximize the impact of interventions.

By implementing these recommendations, it is expected that access to maternal health services will be improved, leading to better health outcomes for mothers and their children in Nigeria.

AI Innovations Methodology

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

1. Strengthening Community Outreach Programs: Implementing community outreach programs that educate and raise awareness about the benefits of receiving the full package of antenatal, intrapartum, and postnatal care. These programs should specifically target women in rural areas and lower socio-economic strata.

2. Improving Healthcare Access: Addressing the challenges related to healthcare access, such as distance to health facilities and difficulties in obtaining money for treatment. This can be done by increasing the number of healthcare facilities in remote areas, providing transportation services for pregnant women, and implementing financial support programs for maternal healthcare.

3. Enhancing Education and Awareness: Promoting formal education among women to empower them with knowledge about maternal health and the importance of receiving continuous care. This can be achieved through educational campaigns, community workshops, and partnerships with local schools and organizations.

4. Strengthening Skilled Birth Attendant Programs: Expanding the Midwives Service Scheme (MSS) and similar initiatives to ensure an adequate number of skilled birth attendants in rural areas. This can be achieved by providing training, incentives, and support for midwives and other healthcare professionals working in maternal health.

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 the number of women receiving antenatal care, skilled delivery assistance, and postnatal visits. This data can be obtained through surveys, interviews, and health facility records.

2. Baseline Assessment: Analyze the current state of access to maternal health services by examining the dropout rates at different stages of the maternity care continuum. Identify the factors associated with dropout, such as distance to health facilities, financial constraints, and educational levels.

3. Intervention Implementation: Implement the recommended interventions, such as community outreach programs, improved healthcare access, education initiatives, and skilled birth attendant programs. Monitor the implementation process and collect data on the interventions’ reach and effectiveness.

4. Impact Evaluation: Compare the data collected after the interventions with the baseline assessment to measure the impact of the recommendations on improving access to maternal health. Calculate indicators such as the reduction in dropout rates, increase in the number of women receiving antenatal care, skilled delivery assistance, and postnatal visits.

5. Statistical Analysis: Use statistical methods, such as multilevel logistic regression models, to identify the independent predictors of dropout at each stage of the maternity care continuum. Measure the effect of the interventions by calculating odds ratios and confidence intervals.

6. Interpretation and Reporting: Analyze the results and interpret the findings to understand the effectiveness of the recommendations in improving access to maternal health. Prepare a comprehensive report highlighting the impact of the interventions, identifying successful strategies, and providing recommendations for further improvement.

By following this methodology, policymakers and healthcare professionals can gain insights into the effectiveness of different interventions and make informed decisions to improve access to maternal health in Nigeria.

Author

Dima Health

Statistics:

Citations: 49

Identifiers:

DOI: 10.1186/s12884-016-1083-9

Research Areas:

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

Study Countries:

Nigeria

Study Design:

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

Study Approach:

Quantitative

Participants Gender:

Female