Introduction: Globally, Sierra Leone has some of the worst maternal and child health indicators. The situation is worsened by a dearth of evidence about the level of continuum of care, an evidence-based intervention aimed at reducing maternal and perinatal morbidity and mortality. Hence this study aimed to assess the level of and factors associated with continuum of maternal and newborn care in Sierra Leone. Method: This study analyzed secondary data from the 2019 Sierra Leone Demographic Health Survey. Analysis was restricted to women who had a live birth in the 5 years preceding the survey (n = 7326). Complete continuum of care was considered when a woman reported having had at least eight antenatal care contacts, skilled birth attendance and mother and baby had at least one postnatal check-up. Bi-variable and multivariable logistic regression were performed using the statistical package for the social sciences software version 25. Results: Only 17.9% (95% CI: 17.4–19.1) of the women utilized complete continuum of care for maternal and newborn health services in Sierra Leone. About 22% (95% CI: 21.3–23.1) utilized 8 or more antenatal care contacts, 88% (95% CI: 87.9–89.4) had skilled birth attendance while 90.7% (95% CI: 90.2–91.5) and 90.4% (95% CI: 89.9–91.2) of mothers and neonates utilized postnatal care respectively. Having started antenatal care within the first trimester (aOR 1.71, 95% CI: 1.46–2.00), being resident in the Southern region (aOR 1.85, 95% CI: 1.23–2.80), belonging to richer wealth quintile (aOR 1.76, 95% CI: 1.27–2.44), using internet (aOR 1.49, 95% CI: 1.12–1.98) and having no big problems seeking permission to access healthcare (aOR 1.34, 95% CI: 1.06–1.69) were significantly associated with utilization of continuum of care. Conclusion: The overall completion of continuum of maternal care is low, with ANC being the lowest utilized component of continuum of care. These findings call for urgent attention for maternal health stakeholders to develop and implement tailored interventions prioritizing women empowerment, access to affordable internet services, timely initiation of ANC contacts, women in developed regions such as the Western and those from poor households.
The Sierra Leone Demographic and Health Surveys (SLDHS) are cross-sectional surveys that are periodically conducted to obtain information on demographic, health and nutritional indicators of women of reproductive age (15–49 years), men (15 to 54 years) and children. This SLDHS was conducted over a 4 month period between 15th May 2019 and 31st August 2019 [11]. This national survey used stratified, two-stage cluster sampling design to obtain a representative sample of 13,872 households [11]. Weighted data was used to account for the unequal probability sampling in different strata. A detailed explanation of the sampling process is available elsewhere [11]. Women aged 15–49 years who were either permanent residents or visitors who had stayed in the selected households the night before the survey were eligible for interviews with a total of 15,574 women who were interviewed. Secondary analysis included women aged 15 to 49 years who had a live birth within 5 years preceding the survey (with the most recent birth being considered) and were either permanent residents or slept in the selected household the night preceding the survey. Out of the total weighted sample of 15,574 women in the data set, only 7326 had given birth within 5 years preceding the survey (as shown in Table 1). Of the 7326 women, 112 (1.5%) women had missing data on ANC initiation timing leading to a total of 7214 women who were considered for logistic regression analysis. Socio-demographic characteristics of women in Sierra Leone as per the 2019 SLDHS a= missing 112 (1.5%) respondents Complete continuum of maternal and newborn healthcare was the outcome variable and was constructed into a binary variable with complete coded as 1 and incomplete coded as 0. Complete continuum of maternal and newborn healthcare was considered when a woman reported having had all the three conditions/states: Eighteen independent variables were categorized into women and household characteristics, and were chosen basing on previous studies [20, 21, 30] and availability in the SLDHS database. Wealth index of household (categorized into quintiles: richest, richer, middle poorer and poorest), type of residence (urban and rural), and region that included the official five regions in the SLDHS (western, eastern, southern, northwestern and northern), household size (was originally a continuous variable and we categorized it into; less than 7 and, 7 and above) and sex of household head (male and female) Wealth index is a measure of relative household economic status and was calculated by DHS from information on household asset ownership using principal component analysis [11, 31]. Age (was originally a continuous variable and we categorized it into; 15–24, 25–34, and 35–49 years), level of education (no education, primary, secondary, and tertiary), exposure to newspapers/magazines, internet, radio and TV (yes and no), parity (1, 2–4 and 5 and above), ANC initiation timing (first trimester and after first trimester), marital status (married and not married), working status (working and not working) and decision making for seeking healthcare (involved and not involved). Religion was categorized as Islam and Christianity and others while problems seeking permission and distance to health facility were categorized as big problem and no big problem. In the questionnaire, seeking permission to access healthcare and distance to health facility had three original responses: no problem, no big problem and big problem. However, none of the study participants reported no problem hence we only had two responses. In order to account for the multi-stage cluster study design, complex sample package of SPSS (version 25.0) statistical software was used. Analysis was carried out based on the weighted count to account for the unequal probability sampling in different strata and to ensure representativeness of the survey results at the national and regional level. Before multivariable logistic regression analysis, cross tabulation was done and then independent variables were assessed for their association with CoC utilisation using bivariable logistic regression analysis and we presented the crude odds ratio (cOR), 95% confidence interval (CI) and p-values. Independent variables associated with CoC utilisation from literature and those with a p-value ≤0.25 at the bivariable level, and not strongly collinear (considered variance inflation factor less than 3) with other independent variables were considered for multivariable logistic regression to assess the independent effect of each variable on the CoC utilisation. Adjusted odds ratios (aOR), 95% confidence intervals (CI) and p-values were calculated with statistical significance level set at p-value < 0.05. Sensitivity analysis was done considering the old WHO recommendations of at least 4 ANC visits.
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