Depression in old age deserves special attention in view of the fact of progressive population ageing, because of the way in which depression and risk factors interact in this period of life and the particularly negative impact of late-life depression on health and quality of life. This editorial aims to provide some insight into longitudinal aspects of depression in old age. Depression may follow varying trajectories (e.g. episode emergence, recurrence) across the lifespan. Late-life depression is not an exception. A symptom-based approach is presented as an appropriate research method to study the predictors and course of affective syndromes in old age. Findings from our studies on depressive symptom trajectories in old age revealed that participants with a course of unremitting elevated symptoms showed the highest levels of loneliness across the trajectory groups and that participants with subclinical symptoms also showed higher levels of loneliness than their counterparts with a minimal-symptom course trajectory. This highlights the need to address loneliness as a way of dealing with depression in old age. ; This work was supported by the 5-year Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project. The ATHLOS project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 635316; Instituto de Salud Carlos III-FIS under grant number PI16/00218; and Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM).
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. ; The ATHLOS project was funded by the European Union Horizon 2020 Research and Innovation Programme (grant number 635316). This study was supported by the 5-year ATHLOS project
