A new approach to tracking of subjects at risk for hypercholesterolemia over a period of 15 years: the Amsterdam Growth and Health Study: The Amsterdam Growth and Health Study

Research output: Contribution to journalArticleAcademic

14 Citations (Scopus)


Because 'traditional' tracking analyses have some drawbacks, this paper presents a new method, which is based on generalized estimating equations (GEE). The new method is illustrated with data from the Amsterdam Growth and Health Study. In this observational longitudinal study six repeated measurements were carried out on 181 subjects (initial age 13 years) over a period of 15 years. Tracking was assessed for total cholesterol (TC), high density lipoprotein (HDL) and the TC/HDL ratio by calculating the odds ratio (OR) for subjects at risk at the age of 13 years regarding the development of their risk status over a 15 year period. These ORs can be interpreted as tracking coefficients. Three methods were compared: percentage of subjects who maintain their position in a certain risk group (i.e. univariate logistic regression), multivariate logistic regression and GEE. The three methods differ in the possibility of using all available data in the analysis and in the possibility of adjusting for certain covariates. Based on this, the GEE- approach seemed to be the most appropriate to calculate tracking coefficients for subjects at risk. When the risk groups were defined according to objective (absolute) risk values, for TC the GEE-OR was 10.1 (95% confidence interval (CI) 5.0-21.9), for HDL 14.4 (95% C1 7.2-28.7) and for the TC/HDL ratio 25.5 (95% CI 11.5-56.8). It can be concluded that the GEE-approach is very suitable to assess tracking for subjects at risk.
Original languageEnglish
Pages (from-to)293-300
Number of pages8
JournalEuropean Journal of Epidemiology
Issue number3
Publication statusPublished - Apr 1997


  • Adolescent
  • Cholesterol/blood
  • Female
  • Humans
  • Hypercholesterolemia/blood
  • Lipoproteins, HDL/blood
  • Longitudinal Studies
  • Male
  • Models, Statistical
  • Netherlands/epidemiology
  • Population Surveillance
  • Risk Factors

Cite this