Maternal and perinatal mortality by place of delivery in sub-Saharan Africa: a meta-analysis of population-based cohort studies

Abstract

BackgroundFacility-based delivery has gained traction as a key strategy for reducing maternal and perinatal mortality in developing countries. However, robust evidence of impact of place of delivery on maternal and perinatal mortality is lacking. We aimed to estimate the risk of maternal and perinatal mortality by place of delivery in sub-Saharan Africa.MethodsWe conducted a systematic review of population-based cohort studies reporting on risk of maternal or perinatal mortality at the individual level by place of delivery in sub-Saharan Africa. Newcastle-Ottawa Scale was used to assess study quality. Outcomes were summarized in pooled analyses using fixed and random effects models. We calculated attributable risk percentage reduction in mortality to estimate exposure effect. We report mortality ratios, crude odds ratios and associated 95% confidence intervals.ResultsWe found 9 population-based cohort studies: 6 reporting on perinatal and 3 on maternal mortality. The mean study quality score was 10 out of 15 points. Control for confounders varied between the studies. A total of 36,772 pregnancy episodes were included in the analyses. Overall, perinatal mortality is 21% higher for home compared to facility-based deliveries, but the difference is only significant when produced with a fixed effects model (OR 1.21, 95% CI: 1.02-1.46) and not when produced by a random effects model (OR 1.21, 95% CI: 0.79-1.84). Under best settings, up to 14 perinatal deaths might be averted per 1000 births if the women delivered at facilities instead of homes. We found significantly increased risk of maternal mortality for facility-based compared to home deliveries (OR 2.29, 95% CI: 1.58-3.31), precluding estimates of attributable risk fraction.ConclusionEvaluating the impact of facility-based delivery strategy on maternal and perinatal mortality using population-based studies is complicated by selection bias and poor control of confounders. Studies that pool data at an individual level may overcome some of these problems and provide better estimates of relative effectiveness of place of delivery in the region.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2458-14-1014) contains supplementary material, which is available to authorized users.

The Relationship between Health Facility-based Delivery and Child Mortality in Nigeria: Insights from 2013 Nigeria Demographic and Health Survey

“…However, this result is in line with similar studies conducted in Nigeria [31] and Malawi and Zambia [39] but in contrast with studies conducted n LMICs, [32] Bangladesh, [33] Indonesia, [34] Tanzania [35] and SSA. [36] Children of mothers aged 25-49 years were found to be significantly associated with increased risk of child mortality. This could be due to the non-utilization of maternal and child health services.…”

“…[31] Studies conducted on the impact of health facility-based delivery on child mortality elsewhere have shown that health facility-based delivery reduce the risk of child mortality. [32,33,34,35,36] Hence, the need for a study focusing on health facility-based delivery as the main predictor variable of child mortality in Nigeria to generate new knowledge on how best to address the problem of child survival. This study aims to examine the relationship between health facility-based delivery and child mortality in Nigeria.…”

“…[31][32][33][34][35][36]39] In the Andersen's Behavioural Model, the variables that determine the demand for health care are categorized into: predisposing factors (age, sex, ethnicity and household head characteristics); enabling factors (location, geopolitical zone, education, health insurance status and household income); and need factors (perceived severity of illness, self-reported health status, presence of physician diagnosing chronic diseases and overweight). In the Mosley-Chen Model which is an analytical framework for the study of the determinants of child survival in the developing countries including Nigeria, the variables that determine child mortality are categorized into: individuallevel variables (i.e.…”

An assessment of the effect of user fee policy reform on facility-based deliveries in rural Zambia

“…Despite this risk, more than 67% of Zambian women in rural areas deliver at home [1]. Home delivery is assumed to be a maternal mortality risk, because of its positive association with maternal mortality [3] (although more recent research is needed [4]) and the negative association between skilled assistance at birth and maternal mortality [5]. Although safe motherhood strategies [5] do not preclude home delivery, fewer than 50% of births in Zambia are attended to by a skilled assistant [6], implying that home delivery remains riskier.…”

The effect of a clinical decision-making mHealth support system on maternal and neonatal mortality and morbidity in Ghana: study protocol for a cluster randomized controlled trial

“…Thirdly, this study will not assess neonatal or maternal mortality at the community level. The attributable risk of death for neonates born at home compared to those born in health facilities in SSA is estimated to be 21% [53]. The DHIMS-2 database from which data for evaluation of the CRCT will be extracted is a web-based platform built on the District Health Information System-2 (DHIMS-2) open source software.…”