Metrological performances of the global chronic morbidity indicator of the Minimum European Health Module and implications for chronic disease prevalence and socioeconomic gradient estimations

Author:

Coste Joël1ORCID,Robine Jean-Marie23,Van Oyen Herman45,Carcaillon-Bentata Laure1

Affiliation:

1. French Public Health Agency (Santé Publique France) , Saint-Maurice, France

2. MMDN, University of Montpellier, EPHE , Montpellier, France

3. PSL Research University , Paris, France

4. Department of Epidemiology and Public Health, Sciensano , Brussels, Belgium

5. Department of Public Health and Primary Care, Ghent University , Ghent, Belgium

Abstract

Abstract Background Although the global chronic morbidity indicator (GCMI) of the Minimum European Health Module (MEHM) was not specifically designed to monitor chronic disease in the population, it is increasingly used for this purpose in Europe and elsewhere. However, its metrological characteristics have seldom been examined, with various sensitivity issues being raised. The present study investigated the metrological performances of the GCMI and analyzed its implications in terms of prevalence and demographic and socioeconomic gradients of chronic conditions in the population. Methods We used data from two large French nationwide representative surveys with cross-sectional and longitudinal data conducted between 2010 and 2021. The surveys used MEHM and collected data on numerous chronic conditions and socioeconomic indicators. Criterion and predictive validity of the GCMI regarding chronic conditions and the resultant socioeconomic gradients were compared with indicators based on reports of individual chronic conditions. Results GCMI sensitivity to capture chronic conditions varied from <20 to 80% depending on the chronic condition. Number of chronic conditions, gender, age and education were also associated with GCMI endorsement. However, the GCMI was predictive of mortality and activity limitations independently of individual conditions. Conclusion The varying lack of sensitivity depending on the chronic condition and the respondent’s sociodemographic status may bias estimates of demographic and socioeconomic gradients compared with indicators based on reports of individual chronic conditions. Differences between GCMI and list-based approaches should be more cautiously considered when monitoring chronic conditions in the population. These approaches should be viewed as complementary rather than contradictory or interchangeable.

Publisher

Oxford University Press (OUP)

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