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The prevalence of depression related to precarious employment (PE) has become a significant public health concern, given the declining trend of the standard employment relationship. Research has focused on the mental health detrimental effects of employment conditions, whereas there is scarce evidence concerning the burden of depression that could be prevented by targeting precariousness. This paper estimates the impact of PE on the risk of depression and the attributable fraction within the active and working salaried population in Spain. Observational cross-sectional on data drawn from the Spanish portion of European Health Survey 2020. After applying selection criteria and descriptives, binary logistic regression models stratified by sex are used to examine the associations between a 9-categories combination of employment precariousness and occupational social class, and depressive symptoms. There is a higher risk of depression among individuals in PE and among those who are unemployed, with a notable gradient based on occupational social class for women. Adjusting by sex, age and foreign-born origin, we estimate that approximately 15.0% (95% confidence interval [CI]: 1.0%–26.2%) of depression cases among the working population and 33.3% (95% CI: 23.2%-43.2) among the active population can be attributed to PE. These findings highlight the public health impact of PE on mental health, provide evidence to estimate the economic burden linked to employment-related mental health, and underscore the need for policy changes and interventions at the level of labour markets and workplaces to mitigate the detrimental effects of PE. [ABSTRACT FROM AUTHOR]

In the context of the escalating burden of diabetes in low and middle-income countries (LMICs), there is a pressing concern about the widening disparities in care and outcomes across socioeconomic groups. This paper estimates health poverty measures among individuals with type 2 diabetes mellitus (T2DM) in Malaysia. Using data from the National Diabetes Registry between 2009 and 2018, the study linked 932,855 people with T2DM aged 40–75 to death records. Cox proportional hazards models were used to estimate the 5-year survival probabilities for each patient, stratified by age and sex, while controlling for comorbidities and area-based indicators of socio-economic status (SES), such as district-level asset-based indices and night-time luminosity. Measures of health poverty, based on the Foster-Greer-Thorbecke (FGT) measures, were employed to capture excessive risk of premature mortality. Two poverty line thresholds were used, namely a 5% and 10% reduction in survival probability compared to age and sex-adjusted survival probability of the general population. Counterfactual simulations estimated the extent to which comorbidities contribute to health poverty. 43.5% of the sample experienced health poverty using the 5% threshold, and 8.9% were health poor using the 10% threshold. Comorbidities contribute 2.9% for males and 5.4% for females, at the 5% threshold. At the 10% threshold, they contribute 7.4% for males and 3.4% for females. If all patients lived in areas of highest night-light intensity, poverty would fall by 5.8% for males and 4.6% for females at the 5% threshold, and 4.1% for males and 0.8% for females at the 10% threshold. In Malaysia, there is a high incidence of health poverty among people with diabetes, and it is strongly associated with comorbidities and area-based measures of SES. Expanding the application of health poverty measurement, through a combination of clinical registries and open spatial data, can facilitate simulations for health poverty alleviation. • Novel health poverty measures applied to T2DM in Malaysia using early mortality risk. • Administrative dataset comprising 1M adults combined with death records and SES. • Male gender, older age and area deprivation drive health poverty. • Nighttime luminosity reveals regional patterns in health poverty. • Combining luminosity data and medical datasets enhances risk stratification in LMICs. [ABSTRACT FROM AUTHOR]

Socioeconomic status (SES) is a robust correlate of mental health, and emerging research indicates that life course trajectories of SES (i.e., social mobility) may be more predictive for health outcomes than point-in-time SES assessments. This paper presents five primary meta-analyses to determine how mental health differs between social mobility groups. We conducted a systematic review of PsycINFO, Web of Science, and PubMed for studies of social mobility and mental health. We used random-effects multilevel meta-analyses to compare mental health problems between individuals who experienced upward mobility, downward mobility, stable high SES, and stable low SES. We included data from 21 studies and 157,763 unique participants yielding 105 effect sizes. Upwardly mobile participants experienced more mental health problems than stable high SES participants (d = 0.11), fewer mental health problems than stable low SES participants (d = −0.24), and fewer mental health problems than downwardly mobile participants (d = −0.17). Downwardly mobile individuals experienced more mental health problems than stable high SES participants (d = 0.26) and fewer mental health problems than stable low SES participants (d = −0.10). Subgroup analyses revealed that the magnitude of effects did not differ by continent of study, type of generational mobility (intergenerational vs. intragenerational), or SES indicator. Meta-regressions with continuous moderators (age, gender, race, study quality) were also non-significant. Taken together, these results indicate that both upwardly and downwardly mobile individuals experience more mental health problems than those who are persistently advantaged, and they both experience fewer mental health problems than those who are persistently disadvantaged. Our findings suggest that while current SES has a stronger association with adult mental health than childhood SES, it is important to also consider the impact of early life and prior generation SES to account for lingering effects of early disadvantage. • Social mobility has small but significant effects on subsequent mental health. • The socially mobile have more mental health problems than the always-advantaged. • The socially mobile have fewer mental health problems than the always-disadvantaged. • Current social class influences mental health more than early life social class. • Early life social class still has some lingering consequences for mental health. [ABSTRACT FROM AUTHOR]