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Background: Whether worldwide increases in life expectancy are accompanied by a better health status is still a debate. People age differently, and there is a need to disentangle whether healthy-ageing pathways can be shaped by cohort effects. This study aims to analyse trends in health status in two large nationally representative samples of older adults from England and the USA.Methods: The sample comprised 55 684 participants from the first seven waves of the English Longitudinal Study of Ageing (ELSA), and the first 11 waves of the Health and Retirement Study (HRS). A common latent health score based on Bayesian multilevel item response theory was used. Two Bayesian mixed-effects multilevel models were used to assess cohort effects on health in ELSA and HRS separately, controlling for the effect of household wealth and educational attainment.Results: Similar ageing trends were found in ELSA (β = -0.311; p < 0.001) and HRS (β = -0.393; p < 0.001). The level of education moderated the life-course effect on health in both ELSA (β = -0.082; p < 0.05) and HRS (β = -0.084; p < 0.05). A birth-year effect was found for those belonging to the highest quintiles of household wealth in both ELSA (β = 0.125; p < 0.001) and HRS (β = 0.170; p < 0.001).Conclusions: Health inequalities have increased in recent cohorts, with the wealthiest participants presenting a better health status in both the USA and English populations. Actions to promote health in the ageing population should consider the increasing inequality scenario, not only by applying highly effective interventions, but also by making them accessible to all members of society. [ABSTRACT FROM AUTHOR]

• The three-class solution best fits the data with the classes that are characterised by adolescents with high probability of emotional disorders (Class I), high probability with behavioural disorders (Class II), and with low probability of mental disorders (Class III). • Adolescents in the emotional disorders comorbidity class were more likely to be girls, while as adolescents in the behavioural disorders comorbidity class were more likely to be boys. • Adolescents in the emotional and behavioural disorders comorbidity classes were more likely to live with their non-biological parents. The aim of this study was to identify the number of comorbidity profiles among adolescents. Sociodemographic factors associated with the comorbidity profiles were also examined. Latent class analysis was conducted using data from the National Comorbidity Survey Adolescent Supplement (NCS-A), a representative sample of adolescents (N = 10,123) in the United States. Latent classes were derived from 26 lifetime mental disorders which were assessed using the World Health Organization Composite International Diagnostic Instrument (CIDI). A three-class solution provided the best fit for the data, with classes labelled as comorbid emotional disorders (Class I), comorbid behavioural disorders (Class II), and normative (Class III). Class I (15.62% of the participants) included adolescents with a high probability of having anxiety, depressive, and intermittent explosive disorder. Class II (6.97%) was characterised by adolescents with a high probability of having substance use, behavioural disorders, and major depression. Class III (77.41%) was characterised by adolescents with a low probability of having any mental disorders. Characterising comorbid profile of mental disorders using person-based approach yields a higher-order classification that could have important clinical implications. [ABSTRACT FROM AUTHOR]

Background: The rapid growth of the size of the older population is having a substantial effect on health and social care services in many societies across the world. Maintaining health and functioning in older age is a key public health issue but few studies have examined factors associated with inequalities in trajectories of health and functioning across countries. The aim of this study was to investigate trajectories of healthy ageing in older men and women (aged ≥45 years) and the effect of education and wealth on these trajectories., Methods: This population-based study is based on eight longitudinal cohorts from Australia, the USA, Japan, South Korea, Mexico, and Europe harmonised by the EU Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) consortium. We selected these studies from the repository of 17 ageing studies in the ATHLOS consortium because they reported at least three waves of collected data. We used multilevel modelling to investigate the effect of education and wealth on trajectories of healthy ageing scores, which incorporated 41 items of physical and cognitive functioning with a range between 0 (poor) and 100 (good), after adjustment for age, sex, and cohort study., Findings: We used data from 141 214 participants, with a mean age of 62·9 years (SD 10·1) and an age range of 45-106 years, of whom 76 484 (54·2%) were women. The earliest year of baseline data was 1992 and the most recent last follow-up year was 2015. Education and wealth affected baseline scores of healthy ageing but had little effect on the rate of decrease in healthy ageing score thereafter. Compared with those with primary education or less, participants with tertiary education had higher baseline scores (adjusted difference in score of 10·54 points, 95% CI 10·31-10·77). The adjusted difference in healthy ageing score between lowest and highest quintiles of wealth was 8·98 points (95% CI 8·74-9·22). Among the eight cohorts, the strongest inequality gradient for both education and wealth was found in the Health Retirement Study from the USA., Interpretation: The apparent difference in baseline healthy ageing scores between those with high versus low education levels and wealth suggests that cumulative disadvantage due to low education and wealth might have largely deteriorated health conditions in early life stages, leading to persistent differences throughout older age, but no further increase in ageing disparity after age 70 years. Future research should adopt a lifecourse approach to investigate mechanisms of health inequalities across education and wealth in different societies., Funding: European Union Horizon 2020 Research and Innovation Programme., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)