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How, what, and why: housing, water & sanitation and wealth patterns in a cross-sectional study of the Guarani Birth Cohort, the first Indigenous birth cohort in Brazil.

Authors :
Caldas ADR
Nobre AA
Brickley E
Alexander N
Werneck GL
Farias YN
Garcia Barreto Ferrão CT
Tavares FG
Pantoja LN
Duarte MCDL
Cardoso AM
Source :
Lancet regional health. Americas [Lancet Reg Health Am] 2023 May 05; Vol. 21, pp. 100496. Date of Electronic Publication: 2023 May 05 (Print Publication: 2023).
Publication Year :
2023

Abstract

Background: Despite the importance of social determinants of health, studies on the effects of socioeconomic, sanitary, and housing conditions on Indigenous child health are scarce worldwide. This study aims to identify patterns in housing, water & sanitation, and wealth (HSW) in the first Indigenous birth cohort in Brazil-The Guarani Birth Cohort.<br />Methods: Cross-sectional study using baseline data from The Guarani Birth Cohort. We used Multiple Correspondence Analysis and Cluster Analysis. The clusters identified were ordered in increasing degrees of access to public policies and wealth, defining the patterns of HSW. Finally, we explored the association between the patterns and one of the health outcomes, hospitalization, in the birth cohort.<br />Findings: Three patterns were identified for housing and water & sanitation, and four for wealth status, resulting in 36 combinations of patterns (3 × 3 × 4). More than 62% of children in the cohort were found with the lowest wealth patterns. The distribution of children across patterns in one dimension was not fully determined by the other two dimensions. Statistically significant associations were found between precarious households and extreme poverty, and hospitalization.<br />Interpretation: We observed substantial heterogeneity in the distribution of children across the 36 combinations. These findings highlight that, should the dimensions of HSW be associated with health outcomes, as seen for hospitalization, they should be considered separately in multivariable models, in order to improve the estimation of their independent effects.<br />Funding: National Council for Scientific and Technological Development, Brazil (CNPq); Oswaldo Cruz Foundation, Brazil (Fiocruz); Research Foundation of the State of Rio de Janeiro, Brazil (FAPERJ).<br />Competing Interests: All authors declare that they have no competing interests.<br /> (© 2023 The Author(s).)

Details

Language :
English
ISSN :
2667-193X
Volume :
21
Database :
MEDLINE
Journal :
Lancet regional health. Americas
Publication Type :
Academic Journal
Accession number :
37214221
Full Text :
https://doi.org/10.1016/j.lana.2023.100496