Relative weight-related costs of healthcare use by children--results from the two German birth cohorts, GINI-plus and LISA-plus

Econ Hum Biol. 2011 Jul;9(3):302-15. doi: 10.1016/j.ehb.2011.02.001. Epub 2011 Mar 2.

Abstract

Obesity among children and adolescents is a growing public health burden. According to a national reference among German children and adolescents aged 3-17 years, 15% are overweight (including obese) and 6.3% are obese. This study aims to assess the economic burden associated with overweight and obesity in children based on a cross-sectional survey from two birth cohort studies: the GINI-plus - German Infant Nutritional Intervention plus Non-Intervention study (3287 respondents aged 9 to <12 years) and the LISA-plus study - Influence of life-style factors on the development of the immune system and allergies in East and West Germany (1762 respondents aged 9 to <12 years). Using a bottom-up approach, we analyse direct costs induced by the utilisation of healthcare services and indirect costs emerging from parents' productivity losses. To investigate the impact of Body Mass Index (BMI) on costs, we perform various descriptive analyses and estimate a two-part regression model. Average annual total direct medical costs of healthcare use are estimated to be €418 (95% CI [346-511]) per child, split between physician (22%), therapist (29%), hospital (41%) and inpatient rehabilitation costs (8%). Bivariate analysis shows considerable differences between BMI groups: €469 (severely underweight), €468 (underweight), €402 (normal weight), €468 (overweight) and €680 (obese). Indirect costs make up €101 per year on average and tend to be higher for obese children, although this was not statistically significant. Drawing on these results, differences in healthcare costs between BMI groups are already apparent in children.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Weight*
  • Child
  • Cohort Studies
  • Confidence Intervals
  • Cost of Illness
  • Costs and Cost Analysis / methods
  • Female
  • Germany
  • Health Expenditures*
  • Humans
  • Male
  • Odds Ratio
  • Regression Analysis