Title

Primary Factors Statistically Associated with Diarrheal Occurrences

Abstract

To successfully prevent diarrheal pathogen transmission, a variety of causal pathways should be considered. This study utilized a suite of tools to identify primary factors associated with diarrheal occurrences in a set of communities in Para, Brazil that had received a biosand filter (BSF). First, existing Demographic and Health Survey data sets from the departments of Para and Amazonas, Brazil were analyzed using three statistical techniques, namely: Mahalanobis-Taguchi Strategy, canonical correlation analysis, and latent factor regression. Second, results of statistical analyses were combined with a literature review and field observations to locally adapt a previously validated structural equation model (SEM) originally developed for Quiche, Guatemala. Third, a randomized household survey was used to collect data - including water sources, sanitation facilities, hygiene practices, socioeconomic statuses, education levels, BSF maintenance, and diarrheal occurrences - in Para, Brazil and analyzed with the hypothesized SEM. Household education level had the largest significant negative effect size on diarrheal occurrence, while improved water source had the largest positive significant effect size on diarrheal occurrence. Maintenance of the BSF in the home had a negligible effect size on diarrheal occurrence. Complex associations observed in the SEM between diarrheal occurrence and a variety of causal pathways support the view that a multibarrier intervention is warranted.

Department(s)

Engineering Management and Systems Engineering

Second Department

Civil, Architectural and Environmental Engineering

Keywords and Phrases

Sanitation; Water; Biosand filter; Brazil; Canonical correlation analysis; Diarrheal occurrences; Field observations; Socio-economic status; Statistical techniques; Structural equation modeling; Surveys; Article; Correlation analysis; Device maintenance; Diarrhea; Disease Association; Educational status; Effect size; Female; Field study; Household; Human; Hygiene; Male; Social status; Statistical analysis; Water supply; Water treatment; Structural equation modeling

International Standard Serial Number (ISSN)

1092-8758

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2018 Mary Ann Liebert Inc., All rights reserved.

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