Mapping child growth failure in Africa between 2000 and 2015.
Ontology highlight
ABSTRACT:
SUBMITTER: Osgood-Zimmerman A
PROVIDER: S-EPMC6346257 | biostudies-literature | 2018 Feb
REPOSITORIES: biostudies-literature
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Project description:BackgroundDiarrheal diseases are the third leading cause of disease and death in children younger than 5 years of age in Africa and were responsible for an estimated 30 million cases of severe diarrhea (95% credible interval, 27 million to 33 million) and 330,000 deaths (95% credible interval, 270,000 to 380,000) in 2015. The development of targeted approaches to address this burden has been hampered by a paucity of comprehensive, fine-scale estimates of diarrhea-related disease and death among and within countries.MethodsWe produced annual estimates of the prevalence and incidence of diarrhea and diarrhea-related mortality with high geographic detail (5 km2) across Africa from 2000 through 2015. Estimates were created with the use of Bayesian geostatistical techniques and were calibrated to the results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016.ResultsThe results revealed geographic inequality with regard to diarrhea risk in Africa. Of the estimated 330,000 childhood deaths that were attributable to diarrhea in 2015, more than 50% occurred in 55 of the 782 first-level administrative subdivisions (e.g., states). In 2015, mortality rates among first-level administrative subdivisions in Nigeria differed by up to a factor of 6. The case fatality rates were highly varied at the national level across Africa, with the highest values observed in Benin, Lesotho, Mali, Nigeria, and Sierra Leone.ConclusionsOur findings showed concentrated areas of diarrheal disease and diarrhea-related death in countries that had a consistently high burden as well as in countries that had considerable national-level reductions in diarrhea burden. (Funded by the Bill and Melinda Gates Foundation.).
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Project description:HIV incidence in sub-Saharan Africa declined substantially between 2000 and 2015. In this analysis, we consider the relative associations of nine structural and individual determinants with this decline. A linear mixed effects model of logged HIV incidence rates versus determinants was used. The data were from mathematical modelling as part of the 2019 Global Burden of Disease Study in 43 sub-Saharan African countries. We used forwards selection to determine a single final model of HIV incidence rate. The association of economic variables and HIV knowledge with incidence was found to be driven by education, while ART coverage had the largest impact on other determinants' coefficients. In the final model, education years per capita contributed the most to explaining variation in HIV incidence rates; a 1-year increase in mean education years was associated with a 0.39 (- 0.56; - 0.2, t = - 4.48 p < 0.01) % decline in incidence rate while a unit increase in ART coverage was associated with a 0.81 (- 1.34; - 0.28, t = - 3.01, p < 0.01) % decline in incidence rate.
| S-EPMC8541936 | biostudies-literature
Project description:BACKGROUND:Undernutrition among children under 5 years of age continues to be a public health challenge in many low- and middle-income countries and can lead to growth stunting. Infectious diseases may also affect child growth, however their actual impact on the latter can be difficult to quantify. In this paper, we analyse data from 20 Demographic and Health Surveys (DHS) conducted in 13 African countries to investigate the relationship between malaria and stunting. Our objective is to make inference on the association between malaria incidence during the first year of life and height-for-age Z-scores (HAZs). METHODS:We develop a geostatistical model for HAZs as a function of both measured and unmeasured child-specific and spatial risk factors. We visualize stunting risk in each of the 20 analysed surveys by mapping the predictive probability that HAZ is below - 2. Finally, we carry out a meta-analysis by modelling the estimated effects of malaria incidence on HAZ from each DHS as a linear regression on national development indicators from the World Bank. RESULTS:A non-spatial univariate linear regression of HAZ on malaria incidence showed a negative association in 18 out of 20 surveys. However, after adjusting for spatial risk factors and controlling for confounding effects, we found a weaker association between HAZ and malaria, with a mix of positive and negative estimates, of which 3 out of 20 are significantly different from zero at the conventional 5% level. The meta-analysis showed that this variation in the estimated effect of malaria incidence on HAZ is significantly associated with the amount of arable land. CONCLUSION:Confounding effects on the association between malaria and stunting vary both by country and over time. Geostatistical analysis provides a useful framework that allows to account for unmeasured spatial confounders. Establishing whether the association between malaria and stunting is causal would require longitudinal follow-up data on individual children.
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