The study utilised women’s file of the 2014 GDHS. The 2014 GDHS, which is the current and sixth edition of the surveys, captures information on prevention and treatment of malaria for children under five, women’s reproductive performance, family planning, maternal and child health and other information relevant for maternal and child health policies. The implementing partners of the survey include the Ghana Statistical Service (GSS), the Ghana Health Service (GHS), and the National Public Health Reference Laboratory (NPHRL) of the GHS with technical aid from the Inner-City Fund (ICF) International. The survey adopted the Demographic and Health Survey (DHS) standardised questionnaire which is developed by the Measure DHS programme .
The 2014 GDHS used an updated sampling frame which was developed by the Ghana Statistical Service for the 2010 Population and Housing Census. This sampling frame do not include nomadic and institutional populations such as persons in hotels, barracks, and prisons. The survey followed a stratified sampling procedure in order to capture specific indicators at the national level whilst taking into account the rural and urban locations .
Firstly, sample points, referred to as clusters constituting enumeration areas (EAs) outlined for the 2010 PHC were selected. This resulted to 427 clusters (i.e. 216 and 211 urban and rural clusters respectively). Secondly, a systematic sampling technique was applied to select households and thereafter, a household listing was undertaken in all the selected EAs. Finally, households to be included in the survey were randomly selected from the list. This led to the selection of approximately 30 households from each cluster. In all, 9656 eligible women (comprising 4753 and 4903 women from urban and rural locations respectively) were identified for the survey. However, a total of 9396 women, consisting of 4602 from urban and 4794 from rural settings were interviewed, leading to 97% response rate. However, the current study was restricted to 1442 rural women with complete information on PNC utilisation and the selected explanatory variables. The study was restricted to rural residents because the 2014 GDHS revealed that the proportion of rural residents (21%) who do not obtain PNC are three times more than urban residents who do not obtain PNC (7%) . Additionally, health facilities and health personnel are concentrated in urban Ghana . Further information about the sampling procedure, pre-testing and field activities are available in the 2014 GDHS report .
Definition of variables
The outcome variable for this study was “Postnatal Care (PNC)”. According to WHO, postnatal stage starts immediately after childbirth and goes into 6 weeks (42 days) after childbirth . Therefore, in the DHS Women’s Questionnaire, all women who had a birth in the 5 years preceding the survey were asked whether a health care provider checked them after giving birth or within 2 months after birth accompanied by ‘Yes’, ‘No’ and ‘Don’t Know’. However, for precision in responses, ‘don’t know’ responses were excluded from the analysis. ‘No’ was coded as ‘0’ signifying those who did not receive postnatal check-up and ‘Yes’ as ‘1’, thus those who had postnatal check-up. PNC plays a key role in maternal health by giving women access to varied reproductive health services [1, 2, 14].
Sixteen independent variables were selected. These are age, marital status, ecological zone, education, wealth status, religion, ethnicity, occupation, total children ever born, partner’s education, frequency of reading newspaper/magazine, frequency of listening to radio, frequency of watching television, health decision making, holds a valid national health insurance scheme (NHIS) card and getting medical help for self: distance is a problem. For clarity of presentation, education was recoded into no education = 1, primary = 2 and secondary or higher = 3; wealth status was recoded into poor = 1, middle = 2 and rich = 3; region of residence was recoded into the three ecological zones of the country, consisting of Coastal = 1, Middle = 2 and Savanna = 3. Occupation was recoded into not working = 1 and working = 2; religion was recoded into Christian = 1, Islam = 2, Traditionalist = 3 and No religion = 4; total children ever born was recoded into one birth = 1, two births = 2, three births = 3 and four or more births = 4 guided by the current total fertility rate of the country . Partner’s education was recoded into no education = 1, primary = 2 and secondary or above = 3; and finally health decision making capacity was recoded into alone = 1 and not alone = 2. These variables were selected because of their theoretical importance and practical significance to maternal healthcare utilisation [21, 22]. Frequency of reading newspaper/magazine, listening to radio and watching television were included in the analysis because they have been found as significant predictors of antenatal care utilisation and skilled birth attendance [23, 24].
We first computed the distribution of PNC attendance among women aged 15–49 in rural Ghana. This was followed by a bivariate analysis of socio-demographics and PNC attendance among rural women in Ghana with their respective chi-square of independence test. Since our outcome variable ‘PNC utilisation’ was binary, the binary logistic regression was considered appropriate for the study. This estimation technique was used because it gives room for predictions of outcome variables that are dichotomous in nature. The binary logistic regression was fitted to assess correlates of PNC at 95% confidence interval. Our results was presented in adjusted odds ratio (AOR) and any AOR less than 1 was interpreted as reduced likelihood of PNC attendance whilst AOR above 1 depicts an increased likelihood of PNC utilisation. The weighting factor (v005/100000) inherent in the dataset was applied to cater for the survey sampling errors whilst the ‘linktest’ command and goodness-of-fit were applied to assess the fitness of our model (see Additional files 1 and 2: Appendix 1 and 2 for details). Variance inflation factor (VIF) test for multicollinearity was conducted and the results indicated no evidence of multicollinearity among independent variables (see Additional files 3: Appendix 3). All analyses were done using Stata version 14.0.
Since the authors of this manuscript did not participate in the actual data gathering processes, we sought no ethical clearance. However, we sought permission to use the data set from Measure DHS. Meanwhile, Measure DHS reported that ethical clearance was obtained from the Institutional Review Board of ICF International and Ethical Review Committee of Ghana Health Service . Also, they ensured that every information that could reveal respondents’ identities were excluded from the dataset before they released the data to the public domain. The data set is freely available to the public at www.measuredhs.org.