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The conceptual relationship between health indicators and quality of life: results from the cross‐cultural analysis of the EUROHIS field study
Author(s) -
Schmidt Silke,
Power Mick,
Bullinger Monika,
Nosikov Anatoliy
Publication year - 2005
Publication title -
clinical psychology and psychotherapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.315
H-Index - 76
eISSN - 1099-0879
pISSN - 1063-3995
DOI - 10.1002/cpp.432
Subject(s) - mental health , structural equation modeling , psychology , quality of life (healthcare) , sample (material) , health indicator , regression analysis , environmental health , health care , quality (philosophy) , gerontology , medicine , statistics , population , psychiatry , mathematics , economics , philosophy , epistemology , psychotherapist , chemistry , chromatography , economic growth
The aim of this study was to determine the performance of various health indicators to predict quality of life, mental health and general health from a conceptual point of view. The EUROHIS study (see Nosikov and Gudex, 2003) includes a broad range of health care and health behaviour related indicators, such as preventive care, health care utilization, use of medicine, physical health, mental health, alcohol consumption, physical activity and quality of life. Data on various health indicators and quality of life were collected from 10 countries, amounting to a sample size of 4849 (2750 females and 2099 males). An analytical approach was employed to investigate the interrelationship between indicators of each particular indicator set (such as alcohol consumption) and between conceptually different indicator sets. Regression analyses as well as structural equation modelling were employed, pooled across all countries as well as separately for different groups of countries. Findings indicate a higher extent of cross‐cultural variation in health behaviour and the QOL measures than in mental health and physical health. In regression analyses, results showed strong and consistent effects of various health behaviour indicators to predict quality of life ( R 2 = 0.48), mental health ( R 2 = 0.48) or general health ( R 2 = 0.45). However, a differential effect of socio‐demographic variables, in particular education, and health behavioural determinants was found in different groups of countries. In the structural equation modelling, good fit indices were observed for the model determining physical and mental health factors by different health behaviour factors. Findings suggest that quality of life rather mediates mental outcomes in this particular set of health indicators in a European sample than functions as an outcome variable. However, it was not possible to include sociodemographic data in the whole model but only in each of the latent factors. This finding still requires replication, both in different clinical groups and in longitudinal data. Copyright © 2005 John Wiley & Sons, Ltd.