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J Urban Health ; 101(3): 629-637, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38652338

RESUMO

Diarrhea is a leading cause of death in children globally, mostly due to inadequate sanitary conditions and overcrowding. Poor housing quality and lack of tenure security that characterize informal settlements are key underlying contributors to these risk factors for childhood diarrhea deaths. The objective of this study is to better understand the physical attributes of informal settlement households in Latin American cities that are associated with childhood diarrhea. We used data from a household survey (Encuesta CAF) conducted by the Corporación Andina de Fomento (CAF), using responses from sampled individuals in eleven cities. We created a household deprivation score based on household water and sewage infrastructure, overcrowding, flooring and wall material, and security of tenure. We fitted a multivariable logistic regression model to estimate odds ratios (OR) and 95% confidence intervals (95% CI) to test the association between the deprivation score and its individual components and childhood diarrhea during the prior 2 weeks. We included a total of 4732 households with children, out of which 12.2% had diarrhea in the 2-week period prior to completing the survey. After adjusting for respondent age, gender, and city, we found a higher risk of diarrhea associated with higher household deprivation scores. Specifically, we found that the odds of diarrhea for children living in a mild and severe deprived household were 1.04 (95% CI 0.84-1.28) and 3.19 times (95% CI 1.80-5.63) higher, respectively, in comparison to households with no deprivation. These results highlight the connections between childhood health and deprived living conditions common in informal settlements.


Assuntos
Diarreia , Humanos , Diarreia/epidemiologia , Masculino , Pré-Escolar , Feminino , América Latina/epidemiologia , Lactente , Incidência , Características da Família , Fatores de Risco , Fatores Socioeconômicos , Cidades/epidemiologia , Habitação/estatística & dados numéricos , Modelos Logísticos , Saneamento , Recém-Nascido
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