Publications by authors named "P M Samper Ots"
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.
Article Synopsis
- The study investigates how depression affects the relationship between job demands and job resources in maintaining employment.
- Data from a large population-based study showed that workers with depression are less likely to be employed when faced with high job demands compared to those without depression.
- Additionally, for those with depression, having high job resources does not mitigate the negative impact of high job demands, leading to more months out of employment.
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.
View Article and Find Full Text PDFBackground: This study aims to examine whether the presence of chronic diseases or multimorbidity moderates the associations between psychosocial working conditions and work exit through unemployment, work disability or early retirement.
Methods: Data from Lifelines (n=55 950), a prospective population-based cohort study, were enriched with monthly information on employment status from Statistics Netherlands. Working conditions were measured with the Copenhagen Psychosocial Questionnaire.
Article Synopsis
- - This study aimed to create models predicting involuntary exits from employment due to unemployment and disability benefits, assessing variations based on five chronic diseases.
- - Key predictors of unemployment and disability included being female, having low education, depression, smoking, obesity, poor work conditions, and low social support.
- - The models demonstrated low overall accuracy for predicting unemployment and disability benefits but showed improved predictions for specific chronic diseases, emphasizing the importance of considering these conditions in workplace assessments.