Analyzing Spatial Distribution of Antenatal Care Utilization in West Africa Using a Geo-additive Zero-Inflated Count Model

Modeling the spatial patterns of antenatal care utilization in Nigeria with inference based on Pólya-Gamma mixtures

Despite the vast advantages of making antenatal care visits, the service utilization among pregnant women in Nigeria is suboptimal. A five-year monitoring estimate indicated that about 24% of the women who had live births made no visit. The non-utilization induced excessive zeroes in the outcome of interest. Thus, this study adopted a zero-inflated negative binomial model within a Bayesian framework to identify the spatial pattern and the key factors hindering antenatal care utilization in Nigeria. We overcome the intractability associated with posterior inference by adopting a Pólya-Gamma data-augmentation technique to facilitate inference. The Gibbs sampling algorithm was used to draw samples from the joint posterior distribution. Results revealed that type of place of residence, maternal level of education, access to mass media, household work index, and woman's working status have significant effects on the use of antenatal care services. Findings identified substantial state-level spatial disparity in antenatal care utilization across the country. Cost-effective techniques to achieve an acceptable frequency of utilization include the creation of a community-specific awareness to emphasize the importance and benefits of the appropriate utilization. Special consideration should be given to older pregnant women, women in poor antenatal utilization states, and women residing in poor road network regions.

How applicable is geospatial analysis in maternal and neonatal health in sub-Saharan Africa? A systematic review

Background

Sub-Saharan Africa (SSA) has the world's highest maternal and neonatal morbidity and mortality and has shown the slowest progress in reducing them. In addition, there is substantial inequality in terms of maternal and neonatal morbidity and mortality in the region. Geospatial studies can help prioritize scarce resources by pinpointing priority areas for implementation. This systematic review was conducted to explore the application of geospatial analysis to maternal and neonatal morbidity and mortality in SSA.

Methods

A systematic search of PubMed, SCOPUS, EMBASE, and Web of Science databases was performed. All observational and qualitative studies that reported on maternal or neonatal health outcomes were included if they used a spatial analysis technique and were conducted in a SSA country. After removing duplicates, two reviewers independently reviewed each study's abstract and full text for inclusion. Furthermore, the quality of the studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists. Finally, due to the heterogeneity of studies, narrative synthesis was used to summarize the main findings, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was strictly followed to report the review results. A total of 56 studies were included in the review.

Results

We found that geospatial analysis was used to identify inequalities in maternal and neonatal morbidity, mortality, and health care utilization and to identify gaps in the availability and geographic accessibility of maternal health facilities. In addition, we identified a few studies that used geospatial analysis for modelling intervention areas. We also detected challenges and shortcomings, such as unrealistic assumptions used by geospatial models and a shortage of reliable, up-to-date, small-scale georeferenced data.

Conclusions

The use of geospatial analysis for maternal and neonatal health in SSA is still limited, and more detailed spatial data are required to exploit the potential of geospatial technologies fully.

Adverse Birth Outcomes Due to Exposure to Household Air Pollution from Unclean Cooking Fuel among Women of Reproductive Age in Nigeria

Exposure to household air pollution (HAP) from cooking with unclean fuels and indoor smoking has become a significant contributor to global mortality and morbidity, especially in low- and middle-income countries such as Nigeria. Growing evidence suggests that exposure to HAP disproportionately affects mothers and children and can increase risks of adverse birth outcomes. We aimed to quantify the association between HAP and adverse birth outcomes of stillbirth, preterm births, and low birth weight while controlling for geographic variability. This study is based on a cross-sectional survey of 127,545 birth records from 41,821 individual women collected as part of the 2018 Nigeria Demographic and Health Survey (NDHS) covering 2013-2018. We developed Bayesian structured additive regression models based on Bayesian splines for adverse birth outcomes. Our model includes the mother's level and household characteristics while correcting for spatial effects and multiple births per mother. Model parameters and inferences were based on a fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulations. We observe that unclean fuel is the primary source of cooking for 89.3% of the 41,821 surveyed women in the 2018 NDHS. Of all pregnancies, 14.9% resulted in at least one adverse birth outcome; 14.3% resulted in stillbirth, 7.3% resulted in an underweight birth, and 1% resulted in premature birth. We found that the risk of stillbirth is significantly higher for mothers using unclean cooking fuel. However, exposure to unclean fuel was not significantly associated with low birth weight and preterm birth. Mothers who attained at least primary education had reduced risk of stillbirth, while the risk of stillbirth increased with the increasing age of the mother. Mothers living in the Northern states had a significantly higher risk of adverse births outcomes in 2018. Our results show that decreasing national levels of adverse birth outcomes depends on working toward addressing the disparities between states.