Cited by 140Global Maternal and Child HealthChild Nutrition and Water AccessPoverty, Education, and Child Welfare

Determinants of child morbidity in Latin America: A pooled analysis of interactions between parental education and economic status

Hatt, Laurel E., Waters, Hugh R.·2006·Social Science & Medicine

Abstract

Diarrhea and respiratory infections account for more than two-fifths of all deaths among children under five. Parental education and economic status are well-known risk factors for child morbidity, but little is known about whether education and economic status operate synergistically or independently to influence children's health. Confirming the presence and direction of such interactions is important to better target education and development policies. Our objective is to test for interactions between parental education and economic status in predicting the risk of diarrhea and respiratory illness among children under five, before and after adjusting for key proximate risk factors. We pool 12 Demographic and Health Surveys (DHS) and nine Living Standards Measurement Surveys (LSMS) from Latin America, creating two large databases. Quintiles of economic status are constructed from principal components asset indices. We use logistic regression to analyze episodes of diarrhea and respiratory illness, and interactions between economic quintile and maternal and paternal education are evaluated via likelihood ratio tests. We find that mother's education and quintile interact synergistically in the DHS data, while results are inconclusive in the LSMS data. The effect of increasing maternal education appears to be more protective for children in wealthy families than for children in poor families. Conversely, improvements in economic status reduce health risks more for children whose mothers are better educated. Father's education is protective and operates independently of economic status. Our findings imply that poverty alleviation efforts occurring in concert with programs to educate women and girls will be more effective for improving children's health than either approach alone.

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Crossref · 10.1016/j.socscimed.2005.06.007

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  • Women's education is associated with improvements in economic productivity, decision-making ability, contraception use, age at first birth, family size, maternal mortality and morbidity, and educational attainment among their children.

    “Evidence suggests that women’s education is associated with improvements in economic productivity, decision-making ability, contraception use, age at first birth, family size, maternal mortality and morbidity, and educational attainment among their children [13–18].”

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Authors
Hatt, L. E., & Waters, H. R.
Affiliations
Johns Hopkins University (US)
Corresponding author
Hatt, Laurel E.
Venue
Social Science & Medicine
Publisher
Elsevier BV
Published
2006-01
Volume
62
Issue
2
Pages
375-386
ISSN
0277-9536 (ISSN-L)
OpenAlex
W2063053632
Cited by
140
References
30
Citations by year
2026: 4 · 2025: 2 · 2024: 5 · 2023: 8 · 2022: 5 · 2021: 14 · 2020: 7 · 2019: 7 · 2018: 8 · 2017: 5 · 2016: 7 · 2015: 6 · 2014: 9 · 2013: 14 · 2012: 6
FWCI
3.19
Type
journal article
Language
en
Open access
closed
Locations
  • Social Science & Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Global Maternal and Child Health
  • Health Sciences › Nursing › Nutrition and Dietetics › Child Nutrition and Water Access
  • Social Sciences › Safety Research › Poverty, Education, and Child Welfare
Keywords
child morbidity, parental education, economic status, maternal education, paternal education, diarrhea, respiratory infections, children under five, poverty reduction, women's education, household assets, Latin America
MeSH terms
Adult, Child Welfare, Child, Preschool, Diarrhea, Educational Status, Humans, Income, Infant, Infant, Newborn, Latin America, Morbidity, Parents, Respiratory Tract Infections, Risk Factors, Socioeconomic Factors, Logistic Models, Risk Assessment

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