Predicting young children's quality of life

Soc Sci Med. 2003 Oct;57(7):1277-88. doi: 10.1016/s0277-9536(02)00507-5.

Abstract

This paper represents an investigation into the determinants of young children's quality of life (QOL) in Thailand. The empirical work is based upon a sample of 498 children (aged 5-8); 220 were urban children and 278 children of construction workers in Bangkok. Their QOL was assessed using a new self-report QOL measure for children. Multiple regression analyses indicated that the father's income and education, type of school, mode of transportation to school, and the amount of time that the child spent on extra study courses were significant explanatory variables. It was found that these factors had different influences on the QOL of urban children and those of construction workers. Extra sport-related activities and extra work (other than housework) improved the QOL of urban children, while the QOL of construction workers' children was directly linked to father's education and income. This result is consistent with income having a diminishing marginal effect on the QOL of children. There is also evidence that amongst construction workers' children, boys have a lower QOL than girls. The different causal explanations for the QOL of urban and construction workers' children suggests that it is context specific, and what impacts one group of children's QOL within a particular context may not impact another group in a different situation. This has important policy implications. Throughout the study we could find no significant impact of health on QOL-neither chronic, acute nor severe illness has any significant impact on QOL. This is consistent with the hypothesis that QOL is influenced by expectations (Social Science and Medicine 41 (10) (1995) 1403). Findings of the effects of social and environmental factors on children's QOL are new in this field and should be further investigated.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child
  • Child Welfare / statistics & numerical data*
  • Child, Preschool
  • Employment
  • Female
  • Health Status
  • Housing
  • Humans
  • Male
  • Marital Status
  • Multivariate Analysis
  • Population Dynamics
  • Quality of Life*
  • Schools
  • Social Support
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Thailand / epidemiology
  • Urban Population / statistics & numerical data*