In an effort to better quantify the impact of adulthood socioeconomic circumstances on prediabetes and type 2 diabetes (T2DM), we set out to examine the relative importance of four adulthood socioeconomic indicators. Using cross-sectional data from The Maastricht Study on 2011 middle-aged older men and women, our findings indicate that low educational level (OR = 1.81, 95% CI = 1.24–2.64), low occupational level (OR = 1.42, 95% CI = 0.98–2.05), and material deprivation (OR = 1.78, 95% CI = 1.33–2.38) were independently associated with T2DM. Low income (OR = 1.28, 95% CI = 0.88–1.87) was the strongest, albeit not significant, SEP (socioeconomic position) correlate of prediabetes. This association confirms SEP as a multifaceted concept and indicates the need to measure SEP accordingly. In order to tackle the social gradient in prediabetes and T2DM, one should, therefore, address multiple SEP indicators and their possible pathways.

The persistence of health inequalities may be driven by differences in education and income, but also by other economic and non-economic factors. Our aim was to explore how the association between single-dimensional health and socioeconomic status (SES) changes when including health-related person capital, economic capital, social capital, cultural capital and attractiveness and personality capital. We used a capital-based approach to understand health inequalities. It presumes intertwined relationships between broadly measured health (‘health-related person capital’) and embodied resources (‘attractiveness and personality capital’) on the one hand, and ESC capital, i.e., economic, social, and cultural resources on the other. We used cross-sectional data on 152,592 participants from the Dutch Lifelines cohort study and estimated correlations using partial least squares structural equation modelling. The correlation between SES and health-related person capital (r = 0.15) was stronger than the correlations between SES and single-dimensional health (physical and mental health; r = 0.12 and r = 0.04, respectively). ESC capital, combining economic, social and cultural capital, showed a correlation of 0.34 with health-related person capital. This was stronger than the correlation between health-related person capital and economic capital alone (r = 0.19). Lastly, the correlation between health-related person capital and ESC capital increased when health related, attractiveness and personality resources were combined into a single person capital construct (from r = 0.34 to r = 0.49). This exploratory study shows the empirical interconnectedness of various types of resources, and their potential role in the persistence of health inequalities. Our findings corroborate the idea of considering health as a multidimensional concept, and to extend conventional SES indicators to a broader measurement of economic and non-economic resources.

The Longitudinal Aging Study Amsterdam (LASA) is an ongoing prospective cohort study of older adults in the Netherlands, with data on multiple domains of functioning available over a period of more than 30 years of follow-up. The study started in 1992 with a nationally representative sample of older adults aged 55–84 years. Over the years, three refresher cohorts (two cohorts aged 55–64 years in 2002 and in 2012, and one cohort aged 60–86 years in 2024) were added. The main aim of LASA was to describe determinants, trajectories and consequences of (changes in) physical, cognitive, emotional and social functioning. LASA has multiple strengths, including its multidisciplinary character, the very long period of follow-up, and the cohort-sequential design which enables the study of longitudinal changes as well as historical time trends in functioning. So far, findings based on data from LASA have been reported in more than 800 scientific publications (see www.lasa-vu.nl). In this article, we provide an update of the design and methods of LASA, including a description of several ancillary studies such as the Loneliness study and the COVID-19 study.

Intrinsic capacity (IC), as defined by the World Health Organization (WHO), represents an individual's physical and mental capacities across five domains: locomotion, cognition, vitality, psychology, and sensory. As a key determinant of functional ability (FA), IC supports meaningful activities, and its decline predicts FA deterioration. Monitoring IC over time may help detect early decline and guide interventions. However, it is not clear how (domains of) IC change during normal ageing. Therefore, this study aimed to identify IC trajectories in both women and men and their associations with functional limitation (proxy of FA) and Quality of Life during ageing. Data were used from the Longitudinal Aging Study Amsterdam (LASA), a nationally representative Dutch cohort followed over 10 years (1726 females, 1520 males). Latent Class (Growth) Analysis was used to identify trajectories. Three composite IC trajectories were identified in both sexes: most favourable (females: 37.0 %, males: 35.5 %), intermediate (females: 51.1 %, males: 54.4 %), and least favourable (females: 11.9 %, males: 10.1 %). Domain-specific trajectories varied, with three trajectories for vitality, sensory, and psychology in females, while locomotion had two. Males had only two sensory trajectories, while other domains followed similar patterns as in females. The least favourable IC trajectories were associated with worse functional limitations and lower QoL (SF-12 physical and mental scores) in both sexes. Distinct trajectories of composite and domain-specific IC highlight heterogeneity in ageing patterns, with differences between sexes and across IC domains. While composite IC reflects overall capacity, domain-specific trajectories may identify distinct risks and intervention targets.

Diverging death risks are associated with a wide range of social factors, including not only education and income but also other economic and non-economic resources. The aim of this study was to assess the association of mortality risks with four types of resources: economic, social, cultural and person capital. We used data of 2,952 participants from the Disparities in the Netherlands survey and annual mortality data from Statistics Netherlands for the period 2014 to 2021. Economic capital was measured through education, income, occupation, home equity, and liquid assets. Social capital was measured by the strength of social ties, the size of the core discussion network, and access to people in resourceful positions; cultural capital by lifestyle, digital skills, and mastery of English, and person capital by self-rated health, impediments to climbing stairs, self-confidence, self-image, people’s appearance, and body mass index. To accommodate the fact that each capital was derived from several indicators, we used Partial Least Squares (PLS) Cox Regression. In multiple regression, higher economic, cultural, and person capital were associated with lower mortality (hazard ratio, 0.77; 95% confidence interval [CI, 0.65 to 0.90], 0.77 [0.64–0.93] and 0.80; [0.70–0.92]), adjusted for all capital measures and sex. The finding that more economic, cultural and person capital is associated with lower mortality provides empirical support for an approach that uses a broad spectrum of capital measures - hitherto rarely included simultaneously in epidemiological research - in order to understand diverging death risks. By integrating sociological concepts, cohort data, and epidemiological research methods, our study highlights the need for further research on the interplay between different forms of resources in shaping health inequalities. In designing public health interventions, we advocate the adoption of a multidimensional capital-based framework for tackling social disparities in mortality.