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Modeling risk categories to predict the longitudinal prevalence of childhood diarrhea in Indonesia
Laura C Sima1, Reuben Ng, Menachem Elimelech
1Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut; School of Public Health, Yale University, New Haven, Connecticut.
Abstract:
We present an innovative approach for analyzing diarrheal prevalence data that uses latent variables to model the relationships between multiple, interdependent environmental risk factors, and socioeconomic mediators. This strategy was applied to elucidate diarrheal longitudinal prevalence risk factors in children 1-4 years of age in low-income areas of Jakarta, Indonesia. Through a prospective cohort study, we identified 257 children who had at least one episode of diarrhea. At the onset of the study, we collected responses to 44 indicators, covering a wide range of previously identified diarrhea risk factors, including demographic and socioeconomic factors. We used exploratory factor analysis to uncover four latent categories of risk factors and their respective indicators from the initial pool of 44 indicators. Thereafter, we used structural equation modeling to model the relationships between the four risk categories and diarrheal longitudinal prevalence, controlling for socioeconomic and demographic covariates. Our final model elucidated several pathways to longitudinal diarrheal prevalence. Most notably, poverty exerts its effect on increased diarrheal prevalence via dual pathways: poor household hygiene and food quality, controlling for covariates. Implications of this and other findings for disease control in Jakarta are discussed.
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