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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. [ABSTRACT FROM AUTHOR]

Background. To assess the associations between anxiety and depressive symptoms and post- COVID-19 condition (PCC) by exploring the direction of these associations and their relevance in the definition of PCC. Methods. Nationwide survey among French adults, recruited between March and April, 2022, using a quota method to capture a representative sample of the general population with regard to sex, age, socioeconomic status, size of the place of residence, and region. We included all participants who met the World Health Organization (WHO) definition of PCC in addition to a random sample of participants infected with SARS-COV-2 for at least 3 months but without PCC. Self-reported anxiety and depressive symptoms, chronic anxiety and depression (for more than 3 years), and anxiety and depression were measured using the GAD-2 and PHQ-2 questionnaires, respectively. Results. In a sample of 1,095 participants with PCC and 1,021 participants infected with SARSCOV- 2 without PCC, 21% had self-reported anxiety and 18% self-reported depression, whereas 33% and 20% had current measured symptoms of anxiety and depression, respectively. The high prevalence of these symptoms cannot only be explained by the characterization of PCC, as only 13.4% of anxiety symptoms and 7.6% of depressive symptoms met the WHO criteria for PCC. Only one participant met the WHO criteria based on self-reported anxiety or depressive symptoms alone, as these were always combined with other symptoms in patients with PCC. Chronic symptoms were associated with PCC (aOR 1.27; 95% CI: 1.00-1.61). In addition, measured anxiety was associated with PCC (aOR = 1.29; 95% CI: 1.02-1.62). Conclusions. Pre-COVID-19 chronic anxiety and depression may play a role in the development of PCC or share vulnerability factors with it. Our results challenge the inclusion of anxiety and depression in the definition of PCC. [ABSTRACT FROM AUTHOR]

Background Given the increasing burden of chronic conditions, multimorbidity is now a priority for healthcare and public health systems worldwide. Appropriate methodological approaches for assessing the phenomenon have not yet been established, resulting in inconsistent and incomplete descriptions. We aimed to estimate and characterize the burden of multimorbidity in the adult population in France in terms of number and type of conditions, type of underlying mechanisms, and analysis of the joint effects for identifying combinations with the most deleterious interaction effects on health status. Methods and findings We used a multistep approach to analyze cross-sectional and longitudinal data from 2 large nationwide representative surveys: 2010/2014 waves of the Health, Health Care, and Insurance Survey (ESPS 2010-2014) and Disability Healthcare Household Survey 2008 (HSM 2008), that collected similar data on 61 chronic or recurrent conditions. Adults aged [greater than or equal to]25 years in either ESPS 2010 (14,875) or HSM 2008 (23,348) were considered (participation rates were 65% and 62%, respectively). Longitudinal analyses included 7,438 participants of ESPS 2010 with follow-up for mortality (97%) of whom 3,798 were reinterviewed in 2014 (52%). Mortality, activity limitation, self-reported health, difficulties in activities/instrumental activities of daily living, and Medical Outcomes Study Short-Form 12-Item Health Survey were the health status measures. Multiple regression models were used to estimate the impact of chronic or recurrent conditions and multimorbid associations (dyads, triads, and tetrads) on health status. Etiological pathways explaining associations were investigated, and joint effects and interactions between conditions on health status measures were evaluated using both additive and multiplicative scales. Forty-eight chronic or recurrent conditions had an independent impact on mortality, activity limitations, or perceived heath. Multimorbidity prevalence varied between 30% (1-year time frame) and 39% (lifetime frame), and more markedly according to sex (higher in women), age (with greatest increases in middle-aged), and socioeconomic status (higher in less educated and low-income individuals and manual workers). We identified various multimorbid combinations, mostly involving vasculometabolic and musculoskeletal conditions and mental disorders, which could be explained by direct causation, shared or associated risk factors, or less frequently, confounding or chance. Combinations with the highest health impacts included diseases with complications but also associations of conditions affecting systems involved in locomotion and sensorial functions (impact on activity limitations), and associations including mental disorders (impact on perceived health). The interaction effects of the associated conditions varied on a continuum from subadditive and additive (associations involving cardiometabolic conditions, low back pain, osteoporosis, injury sequelae, depression, and anxiety) to multiplicative and supermultiplicative (associations involving obesity, chronic obstructive pulmonary disease, migraine, and certain osteoarticular pathologies). Study limitations included self-reported information on chronic conditions and the insufficient power of some analyses. Conclusions Multimorbidity assessments should move beyond simply counting conditions and take into account the variable impacts on health status, etiological pathways, and joint effects of associated conditions. In particular, the multimorbid combinations with substantial health impacts or shared risk factors deserve closer attention. Our findings also suggest that multimorbidity assessment and management may be beneficial already in midlife and probably earlier in disadvantaged groups., Author(s): Joël Coste 1,*, José M. Valderas 2, Laure Carcaillon-Bentata 1 Introduction The gains in life expectancy observed worldwide have increased the risk of living with chronic conditions [1]. Over [...]