Diverging death risks: Mortality as a corollary of economic, social, cultural and person capital.

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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.

A capital-based approach to better understand health inequalities: Theoretical and empirical explorations.

Background: 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. Methods: 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. Results: 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). Conclusions: 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.

Increases in symptoms of depression and anxiety in adults during the initial phases of the COVID-19 pandemic are limited to those with less resources: Results from the Lifelines Cohort Study.

BACKGROUND: The COVID-19 pandemic may have a differential impact on mental health based on an individual's capital, i.e. resources available to maintain and enhance health. We assessed trajectories of depression and anxiety symptoms, and their association with different elements of capital. METHODS: Data on 65,854 individuals (mean baseline age = 50·4 (SD = 12·0) years) from the Lifelines COVID-19 cohort were used. Baseline mental health symptoms were on average measured 4.7 (SD = 1·1) years before the first COVID-19 measurement wave, and subsequent waves were (bi)weekly (March 30─August 05, 2020). Mental health symptom trajectories were estimated using a two-part Latent Class Growth Analysis. Class membership was predicted by economic (education, income, and occupation) and person capital (neuroticism, poor health condition, and obesity) FINDINGS: Most individuals were unlikely to report symptoms of depression (80·6%) or anxiety (75·9%), but stable-high classes were identified for both conditions (1·6% and 6·7%, respectively). The stable-high depression class saw the greatest increase in symptoms after COVID, and the stable-high anxiety class reported an increase in the probability of reporting symptoms after COVID. At the first COVID-measurement, the mean number of symptoms increased compared to baseline (depression:4·7 vs 4·1; anxiety:4·3 vs 4·2); the probability of reporting symptoms also increased (depression:0·96 vs 0·65; anxiety:0·92 vs 0·70). Membership in these classes was generally predicted by less capital, especially person capital; odds ratios for person capital ranged from 1·10-2·22 for depression and 1·08-1·51 for anxiety. INTERPRETATION: A minority of individuals, possessing less capital, reported an increase in symptoms of depression or anxiety after COVID. FUNDING: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Adulthood Socioeconomic Position and Type 2 Diabetes Mellitus-A Comparison of Education, Occupation, Income, and Material Deprivation: The Maastricht Study.

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.