title: The health impact of child labor in developing countries: evidence from cross-country data.
abstract: OBJECTIVE
  Research on child labor and its effect on health has been limited. We sought to determine the impact of child labor on children's health by correlating existing health indicators with the prevalence of child labor in selected developing countries.
  
  
  METHODS
  We analyzed the relationship between child labor (defined as the percentage of children aged 10 to 14 years who were workers) and selected health indicators in 83 countries using multiple regression to determine the nature and strength of the relation. The regression included control variables such as the percentage of the population below the poverty line and the adult mortality rate.
  
  
  RESULTS
  Child labor was significantly and positively related to adolescent mortality, to a population's nutrition level, and to the presence of infectious disease.
  
  
  CONCLUSIONS
  Longitudinal studies are required to understand the short- and long-term health effects of child labor on the individual child.
authors.affiliation: University of Bocconi at the World Bank, Human Development Network, Washington, DC, USA. roggero@unimi.it
authors.forename: Paola
authors.initials: P
authors.lastname: Roggero
authors.forename: Viviana
authors.initials: V
authors.lastname: Mangiaterra
authors.forename: Flavia
authors.initials: F
authors.lastname: Bustreo
authors.forename: Furio
authors.initials: F
authors.lastname: Rosati
mesh_terms: D000293:Adolescent; D002648:Child; D046688:Child Mortality; D002669:Child Welfare / Q000706:statistics & numerical data*; D003431:Cross-Cultural Comparison; D003906:Developing Countries; D004463:Ecology; D004651:Employment / Q000706:statistics & numerical data*; D005260:Female; D015658:HIV Infections / Q000453:epidemiology; D006305:Health Status Indicators; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D044342:Malnutrition / Q000453:epidemiology; D011203:Poverty / Q000706:statistics & numerical data; D011640:Public Policy; D012044:Regression Analysis; D012499:Sanitation; D014480:United Nations