title: Development of a metric for tracking and comparing population health based on the minimal generic set of domains of functioning and health.
abstract: BACKGROUND
  The following minimal set of valid health domains for tracking the health of both clinical and general populations has recently been proposed: 1) energy and drive functions, 2) emotional functions, 3) sensation of pain, 4) carrying out daily routine, 5) walking and moving around, and 6) remunerative employment. This study investigates whether these domains can be integrated into a sound psychometric measure to adequately assess, compare, and monitor the health of populations.
  
  
  METHODS
  Data from waves 3 and 4 of the English Longitudinal Study of Ageing (ELSA) were analysed (N = 9779 and 11,050). From ELSA, 12 items operationalizing the six domains of the minimal generic set were identified. The Partial Credit Model (PCM) was applied to create a health metric based on these items. The Item Response Theory (IRT) model assumptions of unidimensionality, local independence, and monotonicity were evaluated, and Differential Item Functioning (DIF) was examined for sex and age groups. The psychometric properties of: 1) internal consistency reliability, 2) construct validity, and 3) sensitivity to change were evaluated to establish the final health metric.
  
  
  RESULTS
  IRT model assumptions were found to be fulfilled. None of the items showed DIF by sex or age group. The final health metric demonstrated sound psychometric properties.
  
  
  CONCLUSIONS
  The health metric developed in this study - based on the domains of the minimal generic set - proved useful for a wide range of health comparisons, especially for different groups of persons, and both cross-sectionally and over time. Monitoring health over time provides especially useful information for health care providers and health policymakers and both in clinical settings and the general population. The developed health metric offers a wide range of applications, including comparisons of levels of health among different groups in the general population, clinical populations, and even populations within and across different countries.
authors.affiliation: Department of Medical Informatics, Biometry and Epidemiology-IBE, Chair for Public Health and Health Services Research, Research Unit for Biopsychosocial Health, LMU Munich, Munich, Germany.
authors.forename: Cornelia
authors.initials: C
authors.lastname: Oberhauser
authors.affiliation: Surveys, Measurement and Analysis, Department of Measurement and Health Information Systems, World Health Organization, Geneva, Switzerland.
authors.forename: Somnath
authors.initials: S
authors.lastname: Chatterji
authors.affiliation: Department of Medical Informatics, Biometry and Epidemiology-IBE, Chair for Public Health and Health Services Research, Research Unit for Biopsychosocial Health, LMU Munich, Munich, Germany.
authors.forename: Carla
authors.initials: C
authors.lastname: Sabariego
authors.affiliation: Department of Medical Informatics, Biometry and Epidemiology-IBE, Chair for Public Health and Health Services Research, Research Unit for Biopsychosocial Health, LMU Munich, Munich, Germany ; Faculty of Social and Human Sciences, School of Psychology, University of Southampton, Southampton, UK ; Swiss Paraplegic Research, Nottwil, Switzerland.
authors.forename: Alarcos
authors.initials: A
authors.lastname: Cieza
keywords: Construct validity; Functioning; Health; Health metric; Internal consistency reliability; Item Response Theory; Minimal generic set; Partial Credit Model; Psychometric properties; Sensitivity to change