Kristen Sportiello, Mina Shah, Alexandra Buda, Isaiah Mwanza, Manoj Mathews, David R Bearden
{"title":"Causes of Pediatric Deaths in Lusaka, Zambia: A Quantitative Geographic Information Systems Approach","authors":"Kristen Sportiello, Mina Shah, Alexandra Buda, Isaiah Mwanza, Manoj Mathews, David R Bearden","doi":"10.1101/2024.09.17.24313836","DOIUrl":null,"url":null,"abstract":"Background\nWhile childhood mortality has been declining in Zambia, it remains high at 58 per 1000 live births. Importantly, many leading causes of mortality in Zambia are preventable. This study was conducted to identify clusters of childhood mortality, causes of death of recently deceased children, barriers to care, and risk factors for mortality in Lusaka, Zambia. Methods\nThis study was conducted as a prospective cohort study. Family members or lawfully authorized representatives (LARs) were interviewed when they came to pick up death certificates for recently deceased children from Lusaka Childrens Hospital. Each interview included a verbal autopsy, determination of the childs location of residence, and collection of demographic information. Demographic data was also collected from a healthy control group. Quantitative Geographic Information Systems was used to visualize mortality and evaluate for clustering. Results\nLeading primary causes of death included malnutrition (21%), complications of chronic illnesses (16%), and central nervous system infections (13%), while the leading barriers to care were cost (58%) and difficulties with travel (53%). Compared to controls, recently deceased children came from families with significantly lower incomes (1905 Kwacha vs. 2412 Kwacha, p = 0.03) and were significantly more likely to have a history of malnutrition (16.7% vs. 1.4%, p = 0.005). Mortality was clustered in two high-population density, low-income neighborhoods in Lusaka. Conclusions\nSystems to reduce financial barriers to care and improve access to transportation could reduce childhood mortality in Lusaka. The aforementioned neighborhoods are ideal locations for public health interventions or improved healthcare services.","PeriodicalId":501276,"journal":{"name":"medRxiv - Public and Global Health","volume":"49 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Public and Global Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.17.24313836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background
While childhood mortality has been declining in Zambia, it remains high at 58 per 1000 live births. Importantly, many leading causes of mortality in Zambia are preventable. This study was conducted to identify clusters of childhood mortality, causes of death of recently deceased children, barriers to care, and risk factors for mortality in Lusaka, Zambia. Methods
This study was conducted as a prospective cohort study. Family members or lawfully authorized representatives (LARs) were interviewed when they came to pick up death certificates for recently deceased children from Lusaka Childrens Hospital. Each interview included a verbal autopsy, determination of the childs location of residence, and collection of demographic information. Demographic data was also collected from a healthy control group. Quantitative Geographic Information Systems was used to visualize mortality and evaluate for clustering. Results
Leading primary causes of death included malnutrition (21%), complications of chronic illnesses (16%), and central nervous system infections (13%), while the leading barriers to care were cost (58%) and difficulties with travel (53%). Compared to controls, recently deceased children came from families with significantly lower incomes (1905 Kwacha vs. 2412 Kwacha, p = 0.03) and were significantly more likely to have a history of malnutrition (16.7% vs. 1.4%, p = 0.005). Mortality was clustered in two high-population density, low-income neighborhoods in Lusaka. Conclusions
Systems to reduce financial barriers to care and improve access to transportation could reduce childhood mortality in Lusaka. The aforementioned neighborhoods are ideal locations for public health interventions or improved healthcare services.