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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., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Public Health Association.)

Background: Compared to men, women live longer but have more years with disability. We assessed the contribution of gender differences in mortality and disability, total and by cause, to women's excess unhealthy life years (ULYs)., Methods: We used mortality data for France 2008 from Eurostat, causes of death from the CépiDc-INSERM-database; and disability and chronic conditions data from the French Disability Health Survey 2008-09. ULYs were calculated by the Sullivan method. The contributions of mortality and disability differences to gender differences in ULY were based on decomposition analyses., Results: Life expectancy of French women aged 50 was 36.3 years of which 19.0 were ULYs; life expectancy of men was 30.4 years of which 14.2 were ULYs. Of the 4.8 excess ULYs in women, 4.0 years were due to lower mortality. Of these 4.0 ULYs, 1.8 ULY originated from women's lower mortality from cancer, 0.8 ULY from heart disease and 0.3 ULY from accidents. The remaining 0.8 excess ULY in women were from higher disability prevalence, including higher disability from musculoskeletal diseases (+1.8 ULY) and anxiety-depression (+0.6 ULY) partly offset by lower disability from heart diseases (-0.8 ULY) and accidents (-0.3 ULY)., Conclusion: Lower mortality and higher disability prevalence contributed to women's longer life expectancy with disability. Women's higher disability prevalence due to non-fatal disabling conditions was partly offset by lower disability from heart disease and accidents. Conditions differentially impact gender differences in ULY, depending on whether they are mainly life-threatening or disabling. The conclusions confirm the health-survival paradox., (© The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association.)

Background: This study aims to illustrate the differences between approaches proposed for apportioning disability to different diseases in a multicausal situation, i.e. the unadjusted attributable fraction (AF), the adjusted AF, the average AF and the attribution method (AM). This information is useful to better interpret results obtained from cross-sectional data and help policy makers decide on public health strategies., Methods: Data for 29 931 individuals, representative of the French household population, who participated in the 2008-09 cross-sectional Disability-Health Survey, were included. Disability was defined as any limitation reported with the Global Activity Limitation Indicator. Unadjusted AFs were calculated using Levin's formula. Adjusted AFs were estimated for each disease by calculating predicted probabilities of disability for each individual in the dataset, under the assumption that the individual is unexposed to this specific disease (logistic model). Average AFs are based on the same methodology, but have the additional advantage that the average AFs for different diseases sum to the total AF associated with eliminating all diseases. AM accounts for competing risks and partitions total disability prevalence into additive contributions of different diseases and background disability (additive model)., Results: All methods obtained similar results with respect to the estimates of the disease contribution to disability prevalences and to ranking of the diseases, except unadjusted AFs, as the method ignores multimorbidity. Confounders other than diseases, such as age and gender, should be accurately taken into account., Conclusions: Conceptual differences, strengths and limitations of the different approaches were discussed., (© The Author(s) 2018; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Women report more disability than men perhaps due to gender differences in the prevalence of diseases and/or in their disabling impact. We compare the contribution of chronic diseases to disability in men and women in France, using a disability survey conducted in both private households and institutions, and we also examine the effect of excluding the institutionalized population., Methods: Data comprised 17 549 individuals age 50+, who participated in the 2008-09 French Disability Health Survey including people living in institutions. Disability was defined by limitations in activities people usually do due to health problems (global activity limitation indicator). Additive regression models were fitted separately by gender to estimate the contribution of conditions to disability taking into account multi-morbidity., Results: Musculoskeletal diseases caused most disability for both men (10.1%, CI: 8.1-12.0) and women (16.0%, CI 13.6-18.2). The second contributor for men was heart diseases (5.7%, CI: 4.5-6.9%), and for women anxiety-depression (4.0, CI 3.1-5.0%) closely followed by heart diseases (3.8%, CI 2.9-4.7%). Women's higher contribution of musculoskeletal diseases reflected their higher prevalence and disabling impact; women's higher contribution of anxiety-depression and lower contributions of heart diseases reflected gender differences in prevalence. Excluding the institutionalized population did not change the overall conclusions., Conclusions: The largest contributors to the higher disability of women than men are moderately disabling conditions with a high prevalence. Whereas traditional disabling conditions such as musculoskeletal diseases are more prevalent and disabling in women, fatal diseases such as cardiovascular disease are also important contributors in women and men.