Trends in Low Birthweight Deliveries as an indicator of Malaria Transmission

Abstract

Low birthweight (LBW < 2500 g) is a phenomenon that is more pronounced in developing countries where infectious diseases are most prevalent. Malaria infection in all endemic areas of Sub-Saharan Africa has become an important factor associated with LBW during pregnancy with increased susceptibility to mothers of lower parities. Hence LBW can serve as an indicator of malaria transmission. In Kenya stable malaria occur in most parts of the coast and the western regions. Part of its control mechanism is to study the traits that are linked to its spread. This study examined trends of LBW prevalence in Kili Health Demographic and Surveillance System (KHDSS) area. Data on birth deliveries from Kili County Hospital (2006-2019) were used to study trends over time. Trend signi cance was assessed using the Mann-Kendall test while variations of LBW prevalence were assessed by the monthly seasonal indices obtained from the Moving Average Method. Change point analysis was conducted to establish point in time when signi cant change in LBW prevalence occurred. Seasonal Autoregressive Integrated Moving Average model that described the LBW prevalence over time was tted to assess the trend in the predicted values. Additive Logistic Regression was used to obtain Odds Ratio of LBW among primiparity with reference to multiparity and interpreted in relation to the contextual information regarding the changing landscape of malaria transmission. Spatial Scan Statistic (SaTScan) was used to identify local clusters of low birthweights. Findings from the study revealed a signi cant decreasing trend of LBW prevalence during the study period. Higher prevalence rateswere observed in the southern part of KHDSS depicting high malaria transmission as compared to the Northern region. Results from the change point analysis indicated a signi cant change in LBW prevalence at around 2014. Variations of LBW prevalence could be explained by changes in the climatic conditions, with increased prevalence experienced shortly during the rainy periods. LBW clusters were identi ed in various parts of the KHDSS. Odds ratios for LBW among the primiparity could be used to de ne the transition of malaria in Kenya. Findings hereby, can help the government improve on the measures to combat malaria transmission in the mostly a ected areas. Keywords: Low birthweight, Malaria, change point, time series, spatial distribution.