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An abundance of research has documented health inequalities by race and socioeconomic position (SEP) in the United States. However, conceptual and methodological challenges complicate the interpretation of study findings, thereby limiting progress in understanding health inequalities and in achieving health equity. Fundamental to these challenges is a lack of clarity about what race is and the implications of that ambiguity for scientific inquiry. Additionally, there is wide variability in how SEP is conceptualized and measured, resulting in a lack of comparability across studies and significant misclassification of risk. The objectives of this review are to synthesize the literature regarding common approaches to examining race and SEP health inequalities and to discuss the conceptual and methodological challenges associated with how race and SEP have been employed in public health research. Addressing health inequalities has become increasingly important as the United States trends toward becoming a majority-minority nation. Recommendations for future research are presented.

ObjectiveTo investigate the prevalence and sociodemographic associations of online dating in a demographically diverse U.S. national cohort of early adolescents.MethodsWe analyzed cross-sectional data from the Adolescent Brain Cognitive Development Study (Year 2, 2018-2020, ages 11-12; N = 10,157). Multivariable logistic regression analyses were employed to estimate associations between sociodemographic factors (e.g., age, sex, race/ethnicity, sexual orientation, household income, parental education) and early adolescent-reported online dating behaviors.ResultsOverall, 0.4% (n = 38) of participants reported ever using a dating app. Males (AOR 2.72, 95% CI 1.11-6.78) had higher odds of online dating compared to females, and sexual minority identification (e.g., lesbian, gay, or bisexual; AOR 12.97, 95% CI 4.32-38.96) was associated with greater odds of online dating compared to heterosexual identification.ConclusionGiven the occurrence of online dating among early adolescents despite age restrictions, interventions might address age misrepresentation. Adolescent sexual health education may consider incorporating anticipatory guidance on online dating, especially for males and sexual minorities. Future research could further investigate online dating patterns from early to late adolescence and associated health effects.

Polysocial risk scores were recently proposed as a strategy for improving the clinical relevance of knowledge about social determinants of health. Our objective in this study was to assess whether the polysocial risk score model improves prediction of cognition and all-cause mortality in middle-aged and older adults beyond simpler models including a smaller set of key social determinants of health. We used a sample of 13 773 individuals aged ≥50 years at baseline from the 2006-2018 waves of the Health and Retirement Study, a US population-based longitudinal cohort study. Four linear mixed models were compared: 2 simple models including a priori–selected covariates and 2 polysocial risk score models which used least absolute shrinkage and selection operator (LASSO) regularization to select covariates among 9 or 21 candidate social predictors. All models included age. Predictive accuracy was assessed via R 2 and root mean-squared prediction error (RMSPE) using training/test split validation and cross-validation. For predicting cognition, the simple model including age, race, sex, and education had an R 2 value of 0.31 and an RMSPE of 0.880. Compared with this, the most complex polysocial risk score selected 12 predictors (R 2 = 0.35 and RMSPE = 0.858; 2.2% improvement). For all-cause mortality, the simple model including age, race, sex, and education had an area under the receiver operating characteristic curve (AUROC) of 0.747, while the most complex polysocial risk score did not demonstrate improved performance (AUROC = 0.745). Models built on a smaller set of key social determinants performed comparably to models built on a more complex set of social "risk factors." [ABSTRACT FROM AUTHOR]

Background Empirical evaluation of inverse probability weighting (IPW) for self-selection bias correction is inaccessible without the full source population. We aimed to: (i) investigate how self-selection biases frequency and association measures and (ii) assess self-selection bias correction using IPW in a cohort with register linkage. Methods The source population included 17 936 individuals invited to the Copenhagen Aging and Midlife Biobank during 2009–11 (ages 49–63 years). Participants counted 7185 (40.1%). Register data were obtained for every invited person from 7 years before invitation to the end of 2020. The association between education and mortality was estimated using Cox regression models among participants, IPW participants and the source population. Results Participants had higher socioeconomic position and fewer hospital contacts before baseline than the source population. Frequency measures of participants approached those of the source population after IPW. Compared with primary/lower secondary education, upper secondary, short tertiary, bachelor and master/doctoral were associated with reduced risk of death among participants (adjusted hazard ratio [95% CI]: 0.60 [0.46; 0.77], 0.68 [0.42; 1.11], 0.37 [0.25; 0.54], 0.28 [0.18; 0.46], respectively). IPW changed the estimates marginally (0.59 [0.45; 0.77], 0.57 [0.34; 0.93], 0.34 [0.23; 0.50], 0.24 [0.15; 0.39]) but not only towards those of the source population (0.57 [0.51; 0.64], 0.43 [0.32; 0.60], 0.38 [0.32; 0.47], 0.22 [0.16; 0.29]). Conclusions Frequency measures of study participants may not reflect the source population in the presence of self-selection, but the impact on association measures can be limited. IPW may be useful for (self-)selection bias correction, but the returned results can still reflect residual or other biases and random errors. [ABSTRACT FROM AUTHOR]

Abstract Background There is a well-established cross-sectional association between income and health, but estimates of the causal effects of income vary substantially. Different definitions of income may lead to substantially different empirical results, yet research is often framed as investigating “the effect of income” as if it were a single, easily definable construct. Methods/Results The aim of this paper is to introduce a taxonomy for definitional and conceptual issues in studying individual- or household-level income for health research. We focus on (1) the definition of the income measure (earned and unearned; net, gross, and disposable; real and nominal; individual and household; relative and absolute income) and (2) the definition of the causal contrast (amount, functional form assumptions/transformations, direction, duration of change, and timing of exposure and follow-up). We illustrate the application of the taxonomy to four examples from the published literature. Conclusions Quantified estimates of causal effects of income on health and wellbeing have crucial relevance for policymakers to anticipate the consequences of policies targeting the social determinants of health. However, much prior evidence has been limited by lack of clarity in distinguishing between different causal questions. The present framework can help researchers explicitly and precisely articulate income-related exposures and causal questions.

Abstract Objective To investigate the prevalence and sociodemographic associations of online dating in a demographically diverse U.S. national cohort of early adolescents. Methods We analyzed cross-sectional data from the Adolescent Brain Cognitive Development Study (Year 2, 2018–2020, ages 11–12; N = 10,157). Multivariable logistic regression analyses were employed to estimate associations between sociodemographic factors (e.g., age, sex, race/ethnicity, sexual orientation, household income, parental education) and early adolescent-reported online dating behaviors. Results Overall, 0.4% (n = 38) of participants reported ever using a dating app. Males (AOR 2.72, 95% CI 1.11–6.78) had higher odds of online dating compared to females, and sexual minority identification (e.g., lesbian, gay, or bisexual; AOR 12.97, 95% CI 4.32–38.96) was associated with greater odds of online dating compared to heterosexual identification. Conclusion Given the occurrence of online dating among early adolescents despite age restrictions, interventions might address age misrepresentation. Adolescent sexual health education may consider incorporating anticipatory guidance on online dating, especially for males and sexual minorities. Future research could further investigate online dating patterns from early to late adolescence and associated health effects.

OBJECTIVE: This study aimed to assess the causal effect of a change in employment status on suicidal ideation and depressive symptoms by applying marginal structural models (MSM) with machine-learning (ML) algorithms. METHODS: We analyzed data from the 8–15^th waves (2013–2020) of the Korean Welfare Panel Study, a nationally representative longitudinal dataset. Our analysis included 13 294 observations from 3621 participants who had standard employment at baseline (2013–2019). Based on employment status at follow-up year (2014–2020), respondents were classified into two groups: (i) maintained standard employment (reference group), (ii) changed to non-standard employment. Suicidal ideation during the past year and depressive symptoms during the past week were assessed through self-report questionnaire. To apply the ML algorithms to the MSM, we conducted eight ML algorithms to build the propensity score indicating a change in employment status. Then, we applied the MSM to examine the causal effect by using inverse probability weights calculated based on the propensity score from ML algorithms. RESULTS: The random forest algorithm performed best among all algorithms, showing the highest area under the curve 0.702, 95% confidence interval (CI) 0.686–0.718. In the MSM with the random forest algorithm, workers who changed from standard to non-standard employment were 2.07 times more likely to report suicidal ideation compared to those who maintained standard employment (95% CI 1.16–3.70). A similar trend was observed in the analysis of depressive symptoms. CONCLUSIONS: This study found that a change in employment status could lead to a higher risk of suicidal ideation and depressive symptoms.

Background: Conversion therapy practices (CTPs) are discredited efforts that target lesbian, gay, bisexual, trans, queer, Two-Spirit, or other (LGBTQ2S+) people and seek to change, deny, or discourage their sexual orientation, gender identity, and/or gender expression. This study aims to investigate the prevalence of CTPs across Canadian provinces and territories and identify whether CTP bans reduce the prevalence of CTPs. Methods: We collected 119 CTPs from 31 adults (18+) in Canada who have direct experience with CTPs, know people who have gone to CTPs, or know of conversion therapy practitioners using a 2020 anonymous online survey. Mapping analysis was conducted using ArcGIS Online. CTP prevalence was compared between provinces/territories with and without bans using chi-square tests. Results: Three provinces and eleven municipalities had CTP bans. The prevalence of CTPs in provinces/territories with bans was 2.34 per 1,000,000 population (95% CI 1.65, 3.31). The prevalence of CTPs in provinces/territories without bans was 4.13 per 1,000,000 population (95% CI 3.32, 5.14). Accounting for the underlying population, provinces/territories with the highest prevalence of CTPs per 1,000,000 population were New Brunswick (6.69), Nova Scotia (6.50), and Saskatchewan (6.37). Conclusions: Findings suggest only 55% of Canadians were protected under CTP bans. The prevalence of CTPs in provinces/territories without bans was 1.76 times greater than provinces/territories with bans. CTPs are occurring in most provinces/territories, with higher prevalence in the west and the Atlantic. These findings and continued efforts to monitor CTP prevalence can help inform policymakers and legislators as society is increasingly acknowledging CTPs as a threat to the health and well-being of LGBTQ2S+ people.

This article provides a critical and genealogical analysis of the allostatic load research framework. AL research is used as a case study to analyse how the current biosocial context is articulated in the field of health inequalities research. Providing a contemporary analysis of AL studies with a genealogy of the AL concept, we show that the ambition to use biological tools to improve measurements, predictions, and ultimately public health action, is rooted in a history that predates current biosocial entanglements. We analyse the conceptual and methodological grounding of AL studies in relation to the ambitious propositions to address health inequalities they often convey. The difficulties in translating AL research findings into public health policies and the risks of biomedicalisation that could emerge through the use of AL are also addressed. While acknowledging these risks, however, we nuance the risk of depoliticisation associated with the biomedicalisation of social inequalities in health. In light of the historical analysis, we qualify the risks associated to a biologisation of social life that could emerge from AL research: it appears that these risks are more specifically rooted in methodological and epistemological problems that researchers would need to consider in the pursuit of AL research. [ABSTRACT FROM AUTHOR]

Introduction: Suicide rates are higher in prison than in the general population in most countries. The proximity of some suicides to prison events has only received little attention in comparative studies. The aim of this study was to assess the relationship between suicide and four prison events: conviction, disciplinary solitary confinement, nondisciplinary solitary confinement and inter‐prison transfer, in a national retrospective cohort study of people in prison. Methods: All incarcerations in France that occurred during 2017–2020 were eligible. Data were collected from an administrative database of the National Prison Service. Survival bivariate and multivariate analyses were performed with a Cox regression model. Results: Of 358,522 incarcerations were included, among which 469,348 events and 449 suicides occurred. In multivariate analysis, suicide risk was higher the first day of disciplinary solitary confinement (HR = 42.1 [21.5–82.7] and HR = 119.0 [71.5–197.9], before and after a government decree on the disciplinary system, respectively. It was higher within 2 weeks after a transfer (HR = 3.5 [2.3–5.2])) or entry in nondisciplinary solitary confinement (HR = 6.7 [3.4–13.3]) and lower within 2 weeks after a conviction (HR = 0.6 [0.4–1.0]). Conclusion: Solitary confinement and transfer were found to be precipitating factors of suicide in people who are incarcerated. These results offer interesting perspectives on prevention. [ABSTRACT FROM AUTHOR]

Background and Objectives Suicide rates typically increase during recessions. However, few studies have explored how recessions affect risk among older adults nearing retirement. This study used a large suicide mortality registry to characterize and quantify suicide related to retirement during the Great Recession (GR). Research Design and Methods Data come from the National Violent Death Reporting System (NVDRS, 2004–2017; N  = 53,298 suicide deaths age ≥50). We analyzed the text narratives (i.e. descriptions of the most salient circumstances to each suicide) of these decedents using natural language processing (NLP) to identify cases that were "retirement-related" (RR, e.g. anticipating, being unable to, or recently retiring). We used time-series analysis to quantify variation in RR over the GR, and compared these trends to retirees (i.e. decedents whose occupation was "retired") and all decedents aged ≥50. We used content and network analysis to characterize themes represented in the narratives. Results There were 878 RR cases (1.6% of suicides aged ≥50) identified by the NLP model; only 52% of these cases were among retirees. RR cases were younger (62 vs 75 years) and more educated (41.5% vs 24.5% college degree) than retirees. The rate of RR suicide was positively associated with indicators of the GR (e.g. short-term unemployment R 2 = 0.70, p  = .024), but economic indicators were not correlated with the suicide rate among retirees or older adults in general. Economic issues were more central to the narratives of RR cases during the GR compared to other periods. Discussion and Implications Recessions shape suicide risk related to retirement transitions. [ABSTRACT FROM AUTHOR]

Calls-to-action in health research have described a need to improve research on race, ethnicity, and structural racism. Well-established cohort studies typically lack access to novel structural and social determinants of health (SSDOH) or precise race and ethnicity categorization, contributing to a loss of rigor to conduct informative analyses and a gap in prospective evidence on the role of structural racism in health outcomes. We propose and implement methods that prospective cohort studies can use to begin to rectify this, using the Women's Health Initiative (WHI) cohort as a case study. To do so, we evaluated the quality, precision, and representativeness of race, ethnicity, and SSDOH data compared with the target US population and operationalized methods to quantify structural determinants in cohort studies. Harmonizing racial and ethnic categorization to the current standards set by the Office of Management and Budget improved measurement precision, aligned with published recommendations, disaggregated groups, decreased missing data, and decreased participants reporting "some other race". Disaggregation revealed sub-group disparities in SSDOH, including a greater proportion of Black-Latina (35.2%) and AIAN-Latina (33.3%) WHI participants with income below the US median compared with White-Latina (42.5%) participants. We found similarities in the racial and ethnic patterning of SSDOH disparities between WHI and US women but less disparity overall in WHI. Despite higher individual-level advantage in WHI, racial disparities in neighborhood resources were similar to the US, reflecting structural racism. Median neighborhood income was comparable between Black WHI ($39,000) and US ($34,700) women. WHI SSDOH-associated outcomes may be generalizable on the basis of comparing across race and ethnicity but may quantitatively (but not qualitatively) underestimate US effect sizes. This paper takes steps towards data justice by implementing methods to make visible hidden health disparity groups and operationalizing structural-level determinants in prospective cohort studies, a first step to establishing causality in health disparities research.

BackgroundBinge-eating disorder (BED) is the most common eating disorder phenotype and is linked to several negative health outcomes. Yet, little is known about the social epidemiology of BED, particularly in early adolescence. The objective of this study was to examine the associations between sociodemographic characteristics and BED and binge-eating behaviors in a large, national cohort of 10-14-year-old adolescents in the United States (U.S.) METHODS: We conducted a cross-sectional analysis of two-year follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study (2018 - 2020) that included 10,197 early adolescents (10 - 14 years, mean 12 years) in the U.S. Multivariable logistic regression models were used to assess the associations between sociodemographic characteristics and BED and binge-eating behaviors, defined based on the Kiddie Schedule for Affective Disorders and Schizophrenia.ResultsIn this early adolescent sample (48.8% female, 54.0% White, 19.8% Latino/Hispanic, 16.1% Black, 5.4% Asian, 3.2% Native American, 1.5% Other), the prevalence of BED and binge-eating behaviors were 1.0% and 6.3%, respectively. Identifying as gay or bisexual (compared to heterosexual; adjusted odds ratio [AOR]: 2.25, 95% CI 1.01-5.01) and having a household income of less than $75,000 (AOR: 2.05, 95% CI: 1.21-3.46) were associated with greater odds of BED. Being male (AOR: 1.28, 95% CI: 1.06-1.55), of Native American (AOR: 1.60, 95% CI: 1.01-2.55) descent, having a household income less than $75,000 (AOR: 1.34, 95% CI: 1.08-1.65), or identifying as gay or bisexual (AOR for 'Yes' Response: 1.95, 95% CI: 1.31-2.91 and AOR for 'Maybe' Response: 1.81, 95% CI: 1.19-2.76) were all associated with higher odds of binge-eating behaviors.ConclusionSeveral sociodemographic variables showed significant associations with binge-eating behaviors, which can inform targeted screening, prevention, and education campaigns for BED among early adolescents.

Psychosocial risk factors, such as socioeconomic disadvantage and having close relatives with severe health conditions (RSHCs), may negatively impact an adolescent’s life. This study aimed to investigate the associations between adolescent experiences with RSHCs (no, one or several RSHCs), parental working status (PWS) (both parents working (both PW) or having ≥1 parent not working (≥1 PNW)) and the composite variable of RSCHs/PWS in relation to self-reported poor mental health. In 2020, population-based data on 15–18-year-olds (n = 3509) were collected from schools in Sörmland, Sweden. Relationships between the composite variable of RSCHs/PW and poor mental health were determined through logistic regression analyses in three different models. Odds ratios (ORs) are separately reported for girls and boys. Girls reporting several RSHCs/≥1 PNW displayed an OR of 5.05 (95% CI 2.82–9.04) in comparison with the reference group with no RSCHs/both PW when adjusting for grade and ethnicity. The corresponding OR for boys was 2.26 (95% CI 1.46–3.49). Further adjustments for protective factors for mental health attenuated the associations with poor mental health. In conclusion, adolescents with RSHC experiences in combination with parental unemployment are at increased risk of developing their own poor mental health, making this group particularly vulnerable.

Background: Several studies on noncommunicable diseases (NCDs) have been carried out worldwide, the basis of most of which is the identification of risk factors-modifiable (or behavioral) and metabolic. Majority of the NCDs are due to sociodemographic factors, lifestyle, and behavior, which can be prevented to a great extent. Thus, it is a health challenge and a necessity to identify such factors of NCDs. Objectives: The objective is to make a thorough systematic and comparative analysis of diverse machine learning (ML) classifiers and identify the best-performing model to study social determinants of NCDs. Materials and Methods: We used data from the Longitudinal Ageing Study in India, and predicted the prevalence of NCDs based on a set of sociodemographic, lifestyle, and behavioral risk factors by conducting a comparative analysis among 25 different algorithms. Results: Evaluating the performance metrics, the random forest model was found to be the most-suited method with 87.9% accuracy and hence chosen as the final model for the analysis. The model's performance was optimized by a hyper-parameter tuning process using grid-search with a 5-fold cross-validation strategy and results suggested that it was able to make accurate predictions on new instances. Conclusion: The epidemic of chronic illness cannot be completely addressed without comprehending the social determinants. With advancements in medical and health-care industry, ML has been applied to analyze diseases based on clinical parameters. This work is an attempt by the authors to explore and encourage the use of ML in the field of social epidemiology.

Objective: To analyze the relationship between perceived discrimination over the life course, social status, and limited health literacy (HL). Methods: 5040 adults who participated in the 2023 Survey of Racism and Public Health. We applied stratified multilevel models adjusted for sociodemographic characteristics. Results: The average age was 47 years, 48% identified as White, 20% as Latinx, and 17% as Black. In the overall sample, we observed associations of perceived discrimination (b = 0.05, 95% CI: 0.01, 0.09), subjective social status (b = −0.16, 95% CI: −0.23, −0.10), and their interaction (b = 0.02, 95% CI: 0.01, 0.03). More perceived discrimination was associated with lower HL in the White and Multiracial participants. Higher subjective social status was associated with higher HL in the White and Latinx participants. There was a statistically significant interaction between perceived discrimination and subjective social status on HL among the White, Latinx, and Multiracial participants. Conclusion: This analysis has implications for public health practice, indicating that multi-level interventions are needed to address limited HL. Innovation: Our findings provide novel insights for identifying key SDOH indicators to assess in clinical settings to provide health literate care.

BackgroundBased on findings from other contexts, informed by intergroup contact theory, that more contact is associated with less stigma, we hypothesized that community members with greater exposure to cases of Ebola virus disease (EVD) were less likely to report EVD-related stigma towards EVD survivors. We assessed personal stigmatizing attitudes towards Ebola survivors, which reflects personal fear and judgement, as well as perceived stigma towards EVD survivors, which reflects an individual's perception of the attitudes of the community towards a stigmatized group.MethodsFrom September 2016 to July 2017, we conducted a cross-sectional, community-based study of EVD-related stigma among individuals who did not contract Ebola in four EVD-affected rural communities of Kono District, Sierra Leone. We identified individuals from all quarantined households and obtained a random sample of those who were unexposed. Exposed individuals either lived in a quarantined household or were reported to have been in contact with an EVD case. Our explanatory variable was proximity to an EVD case during the outbreak. Our primary outcome was stigma towards EVD survivors, measured by a 6-item adapted HIV-related stigma index validated in Zambia and South Africa, with 1 item reflecting personal stigmatizing attitudes and 5 items reflecting perceived community stigma. The 6-item EVD stigma index had good internal consistency (Cronbach's alpha=0.82). We used modified Poisson and negative binomial regression models, adjusting for potential confounders, to estimate the association between exposure proximity and EVD stigma.ResultsWe interviewed 538 participants aged 12 to 85 years. Most (57%) had been quarantined. Over one-third (39%) reported personal stigmatizing attitudes or perceived community stigma; the most frequently endorsed item was fear and judgment towards EVD survivors. Having contact with someone with EVD was significantly associated with a lower likelihood of perceived community stigma (prevalence ratio [PR], 0.26; 95% CI, 0.13-0.54) and personal stigmatizing attitudes (PR, 0.44; 95% CI, 0.29-0.65). In contrast, being quarantined was significantly associated with a higher likelihood of perceived community stigma (PR, 3.9; 95% CI, 1.5-10.1).ConclusionsIn this cross-sectional study, we found evidence of an inverse relationship between EVD-related stigma and contact with an EVD case. This finding substantiates intergroup contact theory and may form the basis for anti-stigma interventions.

Smoking among Spanish women has increased during the last 50 years and is considered by some authors a modern epidemic. However, mortality risk by cohorts may differ at a regional level, given that health inequalities (and the determinants of smoking and its consequences) are regionally patterned. We applied an Age-Period-Cohort model to identify birth cohort effects on female lung cancer mortality in Spain. We found a strong linear increase in lung cancer mortality during the 1980–2019 period in all regions. Cohorts born between 1935 and 1955 presented a higher relative risk of death at a national and subnational level. However, we found diverging cohort patterns across regions afterward, with some regions presenting a slight mortality improvement (or stagnation) in their youngest cohorts, while in other regions mortality kept increasing. This suggests that inequalities in lung cancer mortality in Spain among women are not only generationally based, but that generational risks also vary across space. Some of the regions that presented improvements in mortality among its younger cohorts are Madrid, Navarra, and the Basque Country, which are some of the wealthiest in the Country. While speculative, this could imply that improvements at a regional level might be associated with factors related to structural conditions that result in the adoption of healthy behaviors. [ABSTRACT FROM AUTHOR]

Psychosocial risk factors, such as socioeconomic disadvantage and having close relatives with severe health conditions (RSHCs), may negatively impact an adolescent's life. This study aimed to investigate the associations between adolescent experiences with RSHCs (no, one or several RSHCs), parental working status (PWS) (both parents working (both PW) or having ≥1 parent not working (≥1 PNW)) and the composite variable of RSCHs/PWS in relation to self-reported poor mental health. In 2020, population-based data on 15–18-year-olds (n = 3509) were collected from schools in Sörmland, Sweden. Relationships between the composite variable of RSCHs/PW and poor mental health were determined through logistic regression analyses in three different models. Odds ratios (ORs) are separately reported for girls and boys. Girls reporting several RSHCs/≥1 PNW displayed an OR of 5.05 (95% CI 2.82–9.04) in comparison with the reference group with no RSCHs/both PW when adjusting for grade and ethnicity. The corresponding OR for boys was 2.26 (95% CI 1.46–3.49). Further adjustments for protective factors for mental health attenuated the associations with poor mental health. In conclusion, adolescents with RSHC experiences in combination with parental unemployment are at increased risk of developing their own poor mental health, making this group particularly vulnerable. [ABSTRACT FROM AUTHOR]

INTRODUCTION Today, non-communicable diseases (NCDs) represent the highest morbidity and mortality burden worldwide, with high body mass index (BMI) as one of the main risk factors. NCDs mortality rate and prevalence of high BMI have a clear relationship with wealth but not with other economic indicators such as income inequality. There are well-known theories in dispute - social integration and neomaterial - trying to reveal this relationship. METHODS In this ecological study, utilizing open datasets from World Bank (WB) and Global Health Observatory, we explore the associations between countries' economic indicators (income and income inequality) and relevant health outcomes (NCDs mortality rate and prevalence of high BMI) using bivariate correlations. To investigate the impact of inequality on health among similar-wealth nations, countries were grouped by the WB's income classification method. RESULTS Multiple correlation analyses were conducted, revealing significant associations between the health variables and economic indicators, but more robust with income than inequality. Specifically, high BMI was positively correlated with income (r=0.46, p<0.05) and negatively correlated with inequality (r= -0.17, p<0.05). NCDs mortality rate showed a negative correlation with income (r= -0.54, p<0.05) and a positive correlation with inequality (r=0.20, p<0.05). At the income level groups, most associations were no longer observable, remaining a few in the higher income groups without a clear pattern. CONCLUSIONS Globally, while income inequality may be related to worse health outcomes, this association is significant only once poverty has been largely overcome, compatible with both theories in dispute. Whether these associations observed at a general level are maintained at the grouped level will depend on the health outcomes studied, the construction of the wealth indicator, and the methodological limitations of country-income grouped analysis. These characteristics, typical of ecological studies on health inequity, could explain the literature's mixed results in this regard. [ABSTRACT FROM AUTHOR]

This article explores the use of infectious disease mathematical modeling to address health disparities, specifically in relation to the COVID-19 pandemic. It emphasizes the significance of understanding the factors that contribute to disparities and how they can be mitigated. The article provides examples of different mathematical models used to examine health equity issues, including deterministic compartmental models and agent-based models. These models have been utilized to investigate the impact of social determinants on disease transmission and outcomes, as well as to inform policy recommendations. The article concludes by stressing the need for improved data and further research to gain a better understanding of and address health disparities in future pandemics. The authors argue that incorporating social determinants into infectious disease modeling can help shape policies that tackle health disparities. [Extracted from the article]

The integration of multiple ancillary services into mental health treatment settings may improve outcomes, but there are no national studies addressing whether comprehensive services are distributed equitably. We investigated whether the availability of a wide range of service types differs based on the facility's racial/ethnic composition. We used the 2020 National Mental Health Services Survey to identify twelve services offered in outpatient mental health treatment facilities (N = 1,074 facilities). We used logistic regression to model each of the twelve services, predicted by the percentage of a facility's clientele that was White, Black, and Hispanic, adjusted for covariates. Facilities with the highest proportions of Black and Hispanic clientele demonstrated the lowest predicted probabilities of offering comprehensive and integrated services. Our findings offer context around upstream factors that may, in part, drive treatment disparities. We orient our findings around frameworks of structural racism and inequities in mental healthcare. [ABSTRACT FROM AUTHOR]

The Korean Social Life, Health, and Aging Project (KSHAP) was a multidisciplinary prospective study conducted in South Korea that measured various health biomarkers from blood, hair, and brain magnetic resonance imaging, and we examined their associations with sociocentric (global) social network data of older adults in 2 entire villages (or cohorts). Cohort K included participants aged 60 years or older, and cohort L included participants aged 65 years or older. We performed a baseline survey involving 814 of the 860 individuals (94.7% response rate) in cohort K in 2012 and 947 of the 1,043 individuals (90.8% response rate) in cohort L in 2017. We gathered longitudinal data for 5 waves in cohort K from 2011 to 2019 and 2 waves in cohort L from 2017 to 2022. Here, we describe for the first time the follow-up design of the KSHAP, the changes in social networks, and various biomarkers over a number of years. The data for cohort K are publicly available via the Korean Social Science Data Archive as well as the project website, and the data for cohort L will be shared soon. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Community disadvantage is associated with late‐life cognition. Few studies examine its contribution to racial disparities in cognition/cognitive change. METHODS: Inverse probability weighted models estimated expected mean differences in cognition/cognitive change attributed to residing in less advantaged communities, defined as cohort top quintile of Area Deprivation Indices (ADI): childhood 66–100; adulthood ADI 5‐99). Interactions by race tested. RESULTS: More Black participants resided in less advantaged communities. Semantic memory would be lower if all participants had resided in less advantaged childhood (b = ‐0.16, 95% confidence interval [CI] = ‐0.30, ‐0.03) or adulthood (b = ‐0.14, 95% CI = ‐0.22, ‐0.04) communities. Race interactions indicated that, among Black participants, less advantaged childhood communities were associated with higher verbal episodic memory (interaction p‐value = 0.007) and less advantaged adulthood communities were associated with lower semantic memory (interaction p‐value = 0.002). DISCUSSION: Examining racial differences in levels of community advantage and late‐life cognitive decline is a critical step toward unpacking community effects on cognitive disparities. [ABSTRACT FROM AUTHOR]

Objectives: Oral health conditions can be determined by a series of factors that include psychosocial aspects. Therefore, this study aimed to investigate the association between psychosocial aspects and self‐reported oral health in Brazilian older adults. Methods: The Brazilian Longitudinal Study of Ageing (ELSI‐Brazil) baseline data was analysed to develop this cross‐sectional study. The outcome was self‐reported oral health, and the psychosocial aspects included neighbourhood trust, life satisfaction and depressive symptoms. The associations were determined through Poisson regression models, controlling for socioeconomic, demographic and behavioural characteristics. Results: A total of 9365 individuals with aged 50 years or over were included in this study. Individuals with good life satisfaction had 16% (PR: 0.84; 95% CI: 0.78–0.90) lower prevalence of having poor self‐reported oral health. Individuals who have depressive symptoms and do not trust in the neighbourhood presented 17% (PR: 1.17; 95% CI: 1.09–1.25) and 12% (PR: 1.12; 95% CI: 1.04–1.21) higher prevalence of poor self‐report oral health compared to those who did not show depressive symptoms and trust the neighbourhood. Conclusion: Our findings suggest that positive psychosocial aspects are moderately associated with better self‐reported oral health. Therefore, we suggest that psychological health and social interaction should be present in public health policy actions. [ABSTRACT FROM AUTHOR]

In the United States, adolescent depression increased beginning in 2008–2010, coinciding with the Great Recession. We investigated whether this time of changing economic circumstances impacted adolescent depression and treatment. We analyzed data for adolescents aged 12–17 years from the 2004-2019 National Survey on Drug Use and Health (N = 256,572). Adolescents' past-year major depressive episodes (MDEs) were measured by self-reported symptoms. MDE treatment included seeing a health professional or receiving MDE medication. We tested how MDE and MDE treatment changed from pre-Great Recession (2004 to Fall 2007) to post-Great Recession (Winter 2007–2019) using interrupted time-series segmented regression models, accounting for seasonality and autocorrelation and testing for moderation by household poverty. The Great Recession was not associated with an immediate increase in MDE prevalence (β :-0.77 [i.e., quarter-year change in prevalence], 95% confidence interval (CI): −2.23, 0.69). However, the increase in MDE prevalence accelerated following the Great Recession (β : 0.29, 95% CI: 0.13, 0.44). The Great Recession was not associated with immediate or long-term changes in adolescent MDE treatment (immediate β : −2.87, 95% CI: −7.79, 2.04; long-term β : 0.03, 95% CI: −0.46, 0.51). Effects were similar for households by poverty status. The Great Recession was not associated with increased adolescent depression prevalence, although there was an acceleration in the trend of adolescent MDE following the recession. The prevalence of MDE treatment remained stable. Adolescent depression prevention efforts should be heightened as prevalence increases, including actively engaging caregivers as family supports to alleviate potential negative implications of economic distress for adolescent MDE. [ABSTRACT FROM AUTHOR]

Background: Incarceration is associated with negative impacts on mental health. Probation, a form of community supervision, has been lauded as an alternative. However, the effect of probation versus incarceration on mental health is unclear. Our objective was to estimate the impact on mental health of reducing sentencing severity at individuals' first adult criminal–legal encounter. Methods: We used the US National Longitudinal Survey on Youth 1997, a nationally representative dataset of youth followed into their mid-thirties. Restricting to those with an adult encounter (arrest, charge alone or no sentence, probation, incarceration), we used parametric g-computation to estimate the difference in mental health at age 30 (Mental Health Inventory-5) if (1) everyone who received incarceration for their first encounter had received probation and (2) everyone who received probation had received no sentence. Results: Among 1835 individuals with adult encounters, 19% were non-Hispanic Black and 65% were non-Hispanic White. Median age at first encounter was 20. Under hypothetical interventions to reduce sentencing, we did not see better mental health overall (Intervention 1, incarceration to probation: RD = −0.01; CI = −0.02, 0.01; Intervention 2, probation to no sentence: RD = 0.00; CI = −0.01, 0.01) or when stratified by race. Conclusion: Among those with criminal–legal encounters, hypothetical interventions to reduce sentencing, including incremental sentencing reductions, were not associated with improved mental health. Future work should consider the effects of preventing individuals' first criminal–legal encounter. [ABSTRACT FROM AUTHOR]

Trust is predictive of civic cooperation and economic growth. Recently, the U.S. public has demonstrated increased partisan division and a surveyed decline in trust in institutions. There is a need to quantify individual and community levels of trust unobtrusively and at scale. Using observations of language across more than 16,000 Facebook users, along with their self-reported generalized trust score, we develop and evaluate a language-based assessment of generalized trust. We then apply the assessment to more than 1.6 billion geotagged tweets collected between 2009 and 2015 and derive estimates of trust across 2,041 U.S. counties. We find generalized trust was associated with more affiliative words (love, we, and friends) and less angry words (hate and stupid) but only had a weak association with social words primarily driven by strong negative associations with general othering terms (“they” and “people”). At the county level, associations with the Centers for Disease Control and Prevention (CDC) and Gallup surveys suggest that people in high-trust counties were physically healthier and more satisfied with their community and their lives. Our study demonstrates that generalized trust levels can be estimated from language as a low-cost, unobtrusive method to monitor variations in trust in large populations.

Abstract Background The widening of group-level socioeconomic differences in body mass index (BMI) has received considerable research attention. However, the predictive power of socioeconomic position (SEP) indicators at the individual level remains uncertain, as does the potential temporal variation in their predictive value. Examining this is important given the increasing incorporation of SEP indicators into predictive algorithms and calls to reduce social inequality to tackle the obesity epidemic. We thus investigated SEP differences in BMI over three decades of the obesity epidemic in England, comparing population-wide (SEP group differences in mean BMI) and individual-level (out-of-sample prediction of individuals’ BMI) approaches to understanding social inequalities. Methods We used repeated cross-sectional data from the Health Survey for England, 1991–2019. BMI (kg/m2) was measured objectively, and SEP was measured via educational attainment, occupational class, and neighbourhood index of deprivation. We ran random forest models for each survey year and measure of SEP adjusting for age and sex. Results The mean and variance of BMI increased within each SEP group over the study period. Mean differences in BMI by SEP group also increased: differences between lowest and highest education groups were 1.0 kg/m2 (0.4, 1.6) in 1991 and 1.3 kg/m2 (0.7, 1.8) in 2019. At the individual level, the predictive capacity of SEP was low, though increased in later years: including education in models improved predictive accuracy (mean absolute error) by 0.14% (− 0.9, 1.08) in 1991 and 1.05% (0.18, 1.82) in 2019. Similar patterns were obtained for occupational class and neighbourhood deprivation and when analysing obesity as an outcome. Conclusions SEP has become increasingly important at the population (group difference) and individual (prediction) levels. However, predictive ability remains low, suggesting limited utility of including SEP in prediction algorithms. Assuming links are causal, abolishing SEP differences in BMI could have a large effect on population health but would neither reverse the obesity epidemic nor reduce much of the variation in BMI.

In their 2022 paper, Kensbock, Alkærsig, and Lomberg provide compelling evidence of an increased risk in treated depressive, anxiety, and stress-related disorders within workplaces, associated with the introduction of new hires who either have treated disorders themselves or are hired from workplaces with an increased prevalence of treated disorders. The authors interpret these findings as evidence of a "contagion" effect for psychiatric disorders, illustrative of workplace spread of disorder that may affect the mental health of employees. In this commentary, we contextualize these findings through psychiatric epidemiology. The evidence provided by Kensbock and colleagues is consistent with a long history of evidence in psychiatric and social epidemiology illustrating that many health outcomes are affected by those in our social networks and that psychiatric disorders, in particular, evidence spatial and temporal autocorrelation as well as social network spread that can be best conceptualized through well-known infectious disease principles. Thus, there is a large empirical literature that supports the findings of Kensbock, Alkærsig, and Lomberg. That said, the findings should not be overinterpreted; they fit some patterns of previous literature and known facts about psychiatric disorders, but not all. They also must be appropriately situated within the literature on workplace determinants of mental well-being more generally and, in particular, the global movements to situate the rights of workers with mental illness for employment protections and safe working conditions. [ABSTRACT FROM AUTHOR]

Background: Suicide is a leading cause of death globally, with approximately 800,000 deaths annually and accounting for 1.5% of all deaths. Risk factors are multifaceted, encompassing individual factors (such as genetics, family history and mental illnesses) and environmental factors (such as economic conditions, social support and life events). In prisons, suicide rates are markedly higher than in the general population, particularly in Italy, where the prisoner suicide rate is approximately 20 times that of the non‐incarcerated population. There is, however, little research on suicide in Italian prisons. Aims: To analyse the characteristics of all people who died by suicide in Italian prisons between 2010 and 2020. Methods: We carried out a records‐based cohort study analysing official data from the Italian Ministry of Justice on prison suicides between 2010 and 2020. The data were cross‐referenced and, when required, supplemented with information from Ristretti Orizzonti, a journal specialising in health and living conditions in prisons, as well as from the website of ISTAT (Italian National Statistical Institute), newspapers, radio broadcasts and news agencies. Results: Factors associated with an increased risk of suicide in prisons were nighttime periods, the months of June, July and October, a relatively brief duration of detention (<6 months), having been convicted of murder, male gender, being about 40 years old, having access to hanging materials and being interned (i.e. subjected to the execution of custodial security measures) or awaiting trial. Prison overcrowding was not a risk factor for suicide. Conclusion: Our findings hold substantial implications for suicide prevention in Italian prisons as they suggest both characteristics of individuals and characteristics of the institutions that could be taken as risk indicators. This knowledge can inform the development of targeted interventions to manage both individual and environmental factors better, leading to improved prison conditions and reduced suicide rates. Furthermore, our research establishes a foundation for more systematic and in‐depth investigations that could further improve suicide prevention strategies in Italian prisons, ultimately influencing policy changes in both practice and research, including perhaps establishing a national database on every completed suicide in prisons. [ABSTRACT FROM AUTHOR]

Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016–2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33–43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.'s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES—especially the composite measure and income—is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood. [ABSTRACT FROM AUTHOR]

To determine if income inequality at the census division level is associated with alcohol consumption and abuse among junior high and high school students. Data on adolescents are from the Cannabis use, Obesity, Mental health, Physical activity, Alcohol use, Smoking, and Sedentary behavior (COMPASS) study. Participant data (n = 19,759) were collected during three survey waves (2016–2017, 2017–2018, and 2018–2019) and linked to 30 census divisions within four Canadian provinces. Data on income inequality and other area-level factors were derived from the 2016 Canadian census. Multilevel logistic regression modelling was used to quantify the associations between income inequality, monthly alcohol consumption, and binge drinking. After adjusting for covariates, students living in census divisions within the second and third quintiles of income inequality experienced an average 80% (OR = 1.80, 95% CI = 1.08–3.02) and 92% (OR = 1.92, 95% CI = 1.05–3.51) increased odds of engaging in monthly binge drinking, respectively, compared to those living in the first quintile. Similarly, adolescents living in census divisions within the second inequality quintile experienced an average 169% (OR = 2.69, 95% CI = 1.45, 4.99) increased odds of engaging in weekly binge drinking, compared to those living in the first quintile. There was no significant association between higher income inequality and current monthly alcohol consumption. Moderate area-level income inequality within census divisions was adversely associated with alcohol consumption among adolescents. Future work should investigate the potential mechanisms that mediate this relationship. [ABSTRACT FROM AUTHOR]

In this commentary, invited for the 100th anniversary of the Journal , we discuss the addition of randomized experiments, along with natural experiments that emulate randomized trials using observational data, as designs in the social epidemiologist's toolbox. These approaches transform the way we define and ask questions about social exposures. They compel us to ask questions about how well-defined interventions change a social exposure that might lead to changes in health. As such, experiments are of unique public health and policy significance. We argue that they are a powerful approach to advance our understanding of how well-defined changes in social exposures impact health, and how credible social policy reforms may be instrumental to address health inequalities. We focus on two research designs. The first is a "pure" randomized controlled trial (RCT) in which the investigator defines and randomly assigns the intervention. The second is a natural experiment, which exploits the fact that policies or interventions in the real world often involve an element of random assignment, emulating an RCT. To give the reader our bottom line: While acknowledging their limits, we continue to be very excited about the promise of RCTs and natural experiments to advance social epidemiology. [ABSTRACT FROM AUTHOR]

In this paper, I applied criminological theory to the epidemiological understanding of health-related deviant behavior such as problematic drug use. To that end, I built and subsequently tested an epidemiological model informed by macro-level criminological theory that helped explain the spatial distribution of accidental drug deaths across neighborhoods in a heavily suburban area (i.e. unincorporated Miami-Dade County, FL), analyzing toxicology reports from the Miami-Dade County Medical Examiner Department. Estimating a negative binomial analysis of drug abuse that predicted drug-related death rates from 2013 through 2017, I drew insights from the following place-based control theories or perspectives in macro criminology: social disorganization, relative deprivation, immigration revitalization, social institutions, and drug enforcement. I found support for social disorganization theory and the immigration revitalization and social institutions perspectives. Since drug abuse is deviant behavior that is both criminal and health-related, criminology and epidemiology appear to overlap with one another. Epidemiology, the study of disease distribution among populations, would profit by integrating insights from social control theories of criminology. Researchers interested in the social context of neighborhoods and the clustering of drug deaths can apply macrocriminological theory to social epidemiology, which concerns itself with the social determinants of health. [ABSTRACT FROM AUTHOR]

Different sexes and genders experience differentiated risks of acquiring infections, including drug-resistant infections, and of becoming ill. Different genders also have different health-seeking behaviours that shape their likelihood of having access to and appropriately using and administering antimicrobials. Consequently, they are distinctly affected by antimicrobial resistance (AMR). As such, it is crucial to incorporate perspectives on sex and gender in the study of both AMR and antimicrobial use in order to present a full picture of AMR's drivers and impact. An intersectional approach to understanding gender and AMR can display how gender and other components 'intersect' to shape the experiences of individuals and groups affected by AMR. However, there are insufficient data on the burden of AMR disaggregated by gender and other socio-economic characteristics, and where available, it is fragmented. For example, to date, the best estimate of the global burden of bacterial AMR published in The Lancet does not consider gender or other social stratifiers in its analysis. To address this evidence gap, we undertook a scoping review to examine how sex and gender compounded by other axes of marginalization influence one's vulnerability and exposure to AMR as well as one's access to and use of antimicrobials. We undertook a gendered analysis of AMR, using intersectionality as a concept to help us understand the multiple and overlapping ways in which different people experience exposure vulnerability to AMR. This approach is crucial in informing a more nuanced view of the burden and drivers of AMR. The intersectional gender lens should be taken into account in AMR surveillance, antimicrobial stewardship, infection prevention and control and public and professional awareness efforts, both donor and government funded, as well as national and international policies and programmes tackling AMR such as through national action plans. [ABSTRACT FROM AUTHOR]

Jewish suicides increased heavily under Nazi-rule. This research investigated risk factors for dying from suicide according to sociodemographic characteristics, local context, and time periods. Nazi-registration of Amsterdam residents of Jewish origin in 1941 linked to death and suicide lists. The added suicides after the Nazi-invasion (1940, n = 115) and the suicides when deportation trains ran (1942/1943, n = 182) were each matched to 25 controls using sex and age. Suicide was compared across migrant, occupational, marital, and religious status and neighborhood religiosity. Conditional logistic regression was applied, stratified by time period. In 1940, immigrant (cf. native born, odds ratio (OR) 1.89, 95%CI 1.21–2.96, p =.005) and married Jews (cf. previously married) showed higher suicide risk; members of Israelite Congregations (cf. nonmembers, OR 0.35, 95%CI 0.22–0.56, p <.001) showed reduced risk. Jews living in low synagogue rate neighborhoods showed higher risk compared to those living in neighborhoods without any synagogues (OR 2.48, 95%CI 1.65–3.72, p <.001) while those living in high synagogue rate neighborhoods showed no increased risk (OR 0.58, 95%CI 0.30–1.11, p =.10). In 1942/1943, the association between religious status (OR 1.07, 95%CI 0.67, 1.72, p =.77), synagogue rate (OR 1.27, 95%CI 0.91–1.77, p =.16), immigrant status (OR 1.30, 95%CI 0.92–1.84, p =.14) and suicide attenuated; Jews in managerial/professional occupations (cf. workers) or unmarried (cf. married) showed higher risk. In 1940, immigrants' higher suicide risk likely indicates greater fear of Nazis while religious affiliation's lower risk might indicate a protective effect of religious belief. In 1942/1943, risk differences markedly attenuated likely indicating increased fear of Nazis among all Jews. Religiously affiliated Jews showed reduced risk of dying from suicide after the Nazi-invasion Jewish immigrants showed higher risk of dying from suicide after the Nazi-invasion By 1942/1943, these risks attenuated indicating fear of the Nazis spread and nullified religion's protection [ABSTRACT FROM AUTHOR]

Aim: The social environment (SE), including social contacts, norms and support, is an understudied element of the living environment which impacts health. We aim to comprehensively summarize the evidence on the association between the SE and risk factors of cardiometabolic disease (CMD). Methods: We performed a systematic review and meta-analysis based on studies published in PubMed, Scopus and Web of Science Core Collection from inception to 16 February 2021. Studies that used a risk factor of CMD, e.g., HbA1c or blood pressure, as outcome and social environmental factors such as area-level deprivation or social network size as independent variables were included. Titles and abstracts were screened in duplicate. Study quality was assessed using the Newcastle-Ottawa Scale. Data appraisal and extraction were based on the study protocol published in PROSPERO. Data were synthesized through vote counting and meta-analyses. Results: From the 7521 records screened, 168 studies reported 1050 associations were included in this review. Four meta-analyses based on 24 associations suggested that an unfavorable social environment was associated with increased risk of cardiometabolic risk factors, with three of them being statistically significant. For example, individuals that experienced more economic and social disadvantage had a higher “CVD risk scores” (OR = 1.54, 95%CI: 1.35 to 1.84). Of the 458 associations included in the vote counting, 323 (71%) pointed towards unfavorable social environments being associated with higher CMD risk. Conclusion: Higher economic and social disadvantage seem to contribute to unfavorable CMD risk factor profiles, while evidence for other dimensions of the social environment is limited.

Socioeconomic factors appear to impact mental health conditions such as depression, but little is known about the relative and combined role of neighborhood and personal socioeconomic deprivation among Hispanics/Latinos. This study examined cross-sectional associations of neighborhood and personal socioeconomic deprivation with depression symptoms in a US Hispanic/Latino population from the San Diego Field Center of the Hispanic Community Health Study/Study of Latinos (n = 3,851). Depression symptoms were assessed with the ten-item Centers for Epidemiological Studies in Depression Scale. Neighborhood socioeconomic deprivation was a composite of eleven variables (e.g., neighborhood income, education, employment, household crowding). Greater personal socioeconomic deprivation based on education, income, and employment was generally associated with higher depression symptoms, including after adjusting for neighborhood socioeconomic deprivation. Greater neighborhood socioeconomic deprivation was associated with higher depression symptoms in females but not males, but the association in females became non-significant when adjusting for personal socioeconomic deprivation. Neighborhood socioeconomic deprivation did not significantly interact with personal socioeconomic deprivation in relation to depression symptoms. The present findings support the association of personal socioeconomic status with mental health (indicated by depression symptoms) among Hispanic/Latino populations, whereas neighborhood socioeconomic deprivation did not relate to depression beyond the impact of personal indicators.

Extensive economic research demonstrates correlations between unions with wages, income inequality, health insurance, discrimination, and other factors. Corresponding epidemiologic literature demonstrates correlations between income, income inequality, insurance, discrimination, and other factors with health. The first purpose of this narrative review is to link these literatures and identify 28 possible pathways whereby labor unions might affect the health of workers. This review is restricted to effects within workplaces; we do not consider unions' political activities. This review covers studies from the US, Europe, and Canada from 1980 through April 1, 2021. Pathways are grouped within five domains informed by the CDC 5-domain model of social determinants of health and the traditional 3-domain model of occupational medicine. Linked pathways include wages, inequality, excessive overtime, job satisfaction, employer-provided health insurance (EPHI), and discrimination. Second, we identify studies analyzing correlations between unions directly with health outcomes that do not require links. Outcomes include occupational injuries, sickness absence, and drug overdose deaths. Third, we offer judgments on the strength of pathways and outcomes --- labeled "consensus," "likely," "disputed" or "unknown" --- based on literature summaries. In our view, whereas there are four "consensus" pathways and outcomes and 16 "likely" pathways and outcomes for unions improving health, there are no "consensus" or "likely" pathways for harming health. The strongest "consensus" pathways and outcomes with salubrious associations include EPHI, OSHA inspections, dangerous working conditions, and injury deaths. Fourth, we identify research gaps and suggest methods for future studies. Unions are an underappreciated social determinant of health.

Numerous epidemiologic studies have documented environmental health disparities according to race/ethnicity (R/E) to inform targeted interventions aimed at reducing these disparities. Yet, the use of R/E under the potential outcomes framework implies numerous underlying assumptions for epidemiologic studies that are often not carefully considered in environmental health research. In this commentary, we describe the current state of thinking about the interpretation of R/E variables in etiologic studies. We then discuss how such variables are commonly used in environmental epidemiology. We observed three main uses for R/E: i) as a confounder, ii) as an effect measure modifier and iii) as the main exposure of interest either through descriptive analysis or under a causal framework. We identified some common methodological concerns in each case and provided some practical solutions. The use of R/E in observational studies requires particular cautions in terms of formal interpretation and this commentary aims at providing a practical resource for future studies assessing racial/ethnic health disparities in environmental research.

Biosocial Medicine, with its emphasis on the full integration of the person's biology and biography, proposes a strategy for clinical research and the practice of medicine that is transformative for the care of individual patients. In this paper, we argue that Biology is one component of what makes a person unique, but it does not do so alone. Biography, the lived experience of the person, integrates with biology to create a unique signature for each individual and is the foundational concept on which Biosocial Medicine is based. Biosocial Medicine starts with the premise that the individual patient is the focus of clinical care, and that average results for "ideal" patients in population level research cannot substitute for the "real" patient for whom clinical decisions are needed. The paper begins with a description of the case-based method of clinical reasoning, considers the strengths and limitations of Randomized Controlled Trials and Evidence Based Medicine, reviews the increasing focus on precision medicine and then explores the neglected role of biography as part of a new approach to the tailored care of patients. After a review of the analytical challenges in Biosocial Medicine, the paper concludes by linking the physician's commitment to understanding the patient's biography as a critical element in developing trust with the patient.