The Lancet Regional Health. Americas (May 2023)

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 BrazilResearch in context

  • Aline Diniz Rodrigues Caldas,
  • Aline Araújo Nobre,
  • Elizabeth Brickley,
  • Neal Alexander,
  • Guilherme Loureiro Werneck,
  • Yasmin Nascimento Farias,
  • Carla Tatiana Garcia Barreto Ferrão,
  • Felipe Guimarães Tavares,
  • Lídia de Nazaré Pantoja,
  • Márcia Cristina da Luz Duarte,
  • Andrey Moreira Cardoso

Journal volume & issue
Vol. 21
p. 100496

Abstract

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Summary: 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. 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. 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. 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. 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).

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