Reproductive Health Disparities in Rural Nigeria

The study utilized data obtained from the 2018 Nigeria Demographic and Health Survey (NDHS). The survey is a cross-sectional study and data were generated using standardized interviewer-administered questionnaires from a nationally representative sample of women aged (15 (link)–49) on socioeconomic, demographic and health variables. For this study, the analyzes covered a weighted sample of 13,151 currently married and cohabiting rural women who were sexually active and reported to have given birth to at least a child in the five years that preceded the survey (i.e. 2013–2018).
The outcome variables selected for this study were based on empirical evidence which includes; 1) the use of contraceptive methods, 2) the number of ANC visits, 3) facility delivery services and 4) the postnatal check provider. Information on these outcome variables as generated from the 2018 NDHS was re-categorized from their original frequency ranges in the dataset. Therefore, women who used a modern contraceptive method, had at least four ANC visits during their most recent pregnancy, delivered in a public or private hospital and skilled postnatal check of a mother during the first 2 days after childbirth/before discharge from a doctor, nurse/midwife or auxiliary nurse/midwife were categorized as ‘1’ and ‘0’ if otherwise.
The main explanatory variables in this study are household poverty-wealth and women's decision-making measures including the following three subjects: 1) decision on respondent's healthcare, 2) decision on large household purchases, and 3) decision on how to spend respondent's earnings. Therefore, women who made independent decisions on any of the three subjects represent decision-making autonomy and may influence seeking healthcare for themselves (22 (link)). In this context, household poverty-wealth was estimated as adopted in a previous study to explain household poverty-wealth status in African standards where there is high inequality in income distribution (23 (link)). Some covariates influencing the outcome variables including age, education, work status, region, distance to health facility and health insurance were included in the analysis as control variables based on empirical evidence.
Data analysis was conducted with Stata software (version 15) at univariate, bivariate and multivariate levels. The dataset was carefully checked for missing values which were excluded and weighted with the appropriate sampling weights as per the Demographic and Health Survey sampling scheme. At the bivariate level, unadjusted logistic regression as shown in Table 2 was employed to investigate the association between the outcome and explanatory variables. Table 3 presented the adjusted logistic regression at the multivariate level to examine the odds of using reproductive and maternal health services. The statistical significance was set at p<0.05 and measures of association were expressed as odds ratio with 95% confidence intervals.