Inequality on the frontline: A multi-country study on gender differences in mental health among healthcare workers during the COVID-19 pandemic.

Healthcare workers (HCWs) were at increased risk for mental health problems during the COVID-19 pandemic, with prior data suggesting women may be particularly vulnerable. Our global mental health study aimed to examine factors associated with gender differences in psychological distress and depressive symptoms among HCWs during COVID-19. Across 22 countries in South America, Europe, Asia and Africa, 32,410 HCWs participated in the COVID-19 HEalth caRe wOrkErS (HEROES) study between March 2020 and February 2021. They completed the General Health Questionnaire-12, the Patient Health Questionnaire-9 and questions about pandemic-relevant exposures. Consistently across countries, women reported elevated mental health problems compared to men. Women also reported increased COVID-19-relevant stressors, including insufficient personal protective equipment and less support from colleagues, while men reported increased contact with COVID-19 patients. At the country level, HCWs in countries with higher gender inequality reported less mental health problems. Higher COVID-19 mortality rates were associated with increased psychological distress merely among women. Our findings suggest that among HCWs, women may have been disproportionately exposed to COVID-19-relevant stressors at the individual and country level. This highlights the importance of considering gender in emergency response efforts to safeguard women's well-being and ensure healthcare system preparedness during future public health crises.

Role of cardiovascular health factors in mediating social inequalities in the incidence of dementia in the UK: two prospective, population-based cohort studies.

Background: The contribution of modifiable risk factors to social inequalities in dementia, observed in longitudinal studies, remains unclear. We aimed to quantify the role of cardiovascular health factors, assessed using Life's Essential 8 (LE8) score, in mediating social inequalities in incidence of dementia and, for comparison, in incidence of stroke, coronary heart disease, and mortality. Methods: In this prospective, population-based cohort study, we collected data from the UK Whitehall II Study and UK Biobank databases. Participants were included if data were available on SEP, outcomes and LE8 (smoking, physical activity, diet, body mass index, blood pressure, fasting blood glucose, lipid levels, sleep duration). The primary outcome was incident dementia and secondary outcomes were stroke, coronary heart disease, and mortality. Outcomes were derived from electronic healthcare records. Socioeconomic position (SEP) was measured by occupation in Whitehall II and education in UK Biobank. Counterfactual mediation analysis was used to quantify the extent to which LE8 score explained the associations of SEP with all outcomes. Analyses involved Cox regression, accelerated failure time models, and linear regression; and were adjusted for age, sex, and ethnicity. Findings: Between 10.09.1985 and 29.03.1988, a total of 9688 participants (mean age ± SD 44.9 ± 6.0; 67% men) from the Whitehall II study, and between 19.12.2006 and 01.10.2010, 278,215 participants (mean age ± SD 56.0 ± 8.1; 47% men) from the UK Biobank were included. There were 606 and 4649 incident dementia cases over a median (interquartile range) follow-up of 31.7 (31.1-32.7) and 13.5 (12.7-14.1) years respectively in Whitehall II and UK Biobank. In Whitehall II, the hazard ratio was 1.85 [95% CI 1.42, 2.32] for the total effect of SEP on dementia and 1.20 [1.12, 1.28] for the indirect effect via the LE8, the proportion mediated being 36%. In UK Biobank, the total effect of SEP on dementia was 1.65 [1.54, 1.78]; the indirect effect was 1.11 [1.09, 1.12], and the proportion mediated was 24%. The proportions mediated for stroke, coronary heart disease, and mortality were higher, ranging between 34% and 63% in Whitehall II and between 36% and 50% in UK Biobank. Interpretation: In two well-characterised cohort studies, up to one third of the social inequalities in incidence of dementia was attributable to cardiovascular health factors. Promotion of cardiovascular health in midlife may contribute to reducing social inequalities in risk of dementia, in addition to cardiovascular diseases and all-cause mortality. This study used adult measures of SEP, further research is warranted using lifecourse measures of SEP. Funding: NIH (RF1AG062553).

Host genetic variants, Epstein-Barr virus subtypes, and the risk of nasopharyngeal carcinoma: Assessment of interaction and mediation.

Epstein-Barr virus (EBV) and human leukocyte antigen (HLA) polymorphisms are well-known risk factors for nasopharyngeal carcinoma (NPC). However, the combined effects between HLA and EBV on the risk of NPC are unknown. We applied a causal inference framework to disentangle interaction and mediation effects between two host HLA SNPs, rs2860580 and rs2894207, and EBV variant 163364 with a population-based case-control study in NPC-endemic southern China. We discovered the strong interaction effects between the high-risk EBV subtype and both HLA SNPs on NPC risk (rs2860580, relative excess risk due to interaction [RERI] = 4.08, 95% confidence interval [CI] = 2.03-6.14; rs2894207, RERI = 3.37, 95% CI = 1.59-5.15), accounting for the majority of genetic risk effects. These results indicate that HLA genes and the high-risk EBV have joint effects on NPC risk. Prevention strategies targeting the high-risk EBV subtype would largely reduce NPC risk associated with EBV and host genetic susceptibility.

Preferred Language Mediates Association Between Race, Ethnicity, and Delayed Presentation in Critically Ill Patients With COVID-19.

Which social factors explain racial and ethnic disparities in COVID-19 access to care and outcomes remain unclear. OBJECTIVES: We hypothesized that preferred language mediates the association between race, ethnicity and delays to care. DESIGN SETTING AND PARTICIPANTS: Multicenter, retrospective cohort study of adults with COVID-19 consecutively admitted to the ICU in three Massachusetts hospitals in 2020. MAIN OUTCOME AND MEASURES: Causal mediation analysis was performed to evaluate potential mediators including preferred language, insurance status, and neighborhood characteristics. RESULTS: Non-Hispanic White (NHW) patients (157/442, 36%) were more likely to speak English as their preferred language (78% vs. 13%), were less likely to be un- or under-insured (1% vs. 28%), lived in neighborhoods with lower social vulnerability index (SVI) than patients from racial and ethnic minority groups (SVI percentile 59 [28] vs. 74 [21]) but had more comorbidities (Charlson comorbidity index 4.6 [2.5] vs. 3.0 [2.5]), and were older (70 [13.2] vs. 58 [15.1] years). From symptom onset, NHW patients were admitted 1.67 [0.71-2.63] days earlier than patients from racial and ethnic minority groups (p < 0.01). Non-English preferred language was associated with delay to admission of 1.29 [0.40-2.18] days (p < 0.01). Preferred language mediated 63% of the total effect (p = 0.02) between race, ethnicity and days from symptom onset to hospital admission. Insurance status, social vulnerability, and distance to the hospital were not on the causal pathway between race, ethnicity and delay to admission. CONCLUSIONS AND RELEVANCE: Preferred language mediates the association between race, ethnicity and delays to presentation for critically ill patients with COVID-19, although our results are limited by possible collider stratification bias. Effective COVID-19 treatments require early diagnosis, and delays are associated with increased mortality. Further research on the role preferred language plays in racial and ethnic disparities may identify effective solutions for equitable care.

A multistate approach for the study of interventions on an intermediate time-to-event in health disparities research.

We propose a novel methodology to quantify the effect of stochastic interventions for a non-terminal intermediate time-to-event on a terminal time-to-event outcome. Investigating these effects is particularly important in health disparities research when we seek to quantify inequities in the timely delivery of treatment and its impact on patients' survival time. Current approaches fail to account for time-to-event intermediates and semi-competing risks arising in this setting. Under the potential outcome framework, we define causal contrasts relevant in health disparities research and provide identifiability conditions when stochastic interventions on an intermediate non-terminal time-to-event are of interest. Causal contrasts are estimated in continuous time within a multistate modeling framework and analytic formulae for the estimators of the causal contrasts are developed. We show via simulations that ignoring censoring in intermediate and/or terminal time-to-event processes or ignoring semi-competing risks may give misleading results. This work demonstrates that a rigorous definition of the causal effects and joint estimation of the terminal outcome and intermediate non-terminal time-to-event distributions are crucial for valid investigation of interventions and mechanisms in continuous time. We employ this novel methodology to investigate the role of delaying treatment uptake in explaining racial disparities in cancer survival in a cohort study of colon cancer patients.

Statistical methods to examine contributors to racial disparities in perinatal outcomes.

Longstanding racial disparities in preterm birth in the US remain incompletely understood. Often investigators use interaction terms or stratify epidemiologic analyses by race and ethnicity to examine disparities. However, these approaches presume differential susceptibility to similar exposures. However, American life remains largely racially segregated. As such, vastly different doses of harmful and beneficial exposures exist across racial and ethnic groups. Differences in exposure patterns and their sources likely explain a larger proportion of racial health disparities (mediation) than differential responses to exposures by race (effect modification). Thus, recently developed, user-friendly mediation analysis may be a more relevant and powerful tool to quantify the contribution of specific exposures to racial disparities. Such statistical methods coupled with evaluation of real-world reduction of exposures to toxicants may be used to focus policymakers' efforts to improve perinatal health equity through targeted interventions.

Testing Black-White Disparities in Biological Aging Among Older Adults in the United States: Analysis of DNA-Methylation and Blood-Chemistry Methods.

Biological aging is a proposed mechanism through which social determinants drive health disparities. We conducted proof-of-concept testing of 8 DNA-methylation (DNAm) and blood-chemistry quantifications of biological aging as mediators of disparities in healthspan between Black and White participants in the 2016 wave of the Health and Retirement Study (n = 9,005). We quantified biological aging from 4 DNAm "clocks" (Horvath, Hannum, PhenoAge, and GrimAge clock), a DNAm pace-of-aging measure (DunedinPoAm), and 3 blood-chemistry measures (PhenoAge, Klemera-Doubal method biological age, and homeostatic dysregulation). We quantified Black-White disparities in healthspan from cross-sectional and longitudinal data on physical performance tests, self-reported limitations in activities of daily living, and physician-diagnosed chronic diseases, self-rated health, and survival. DNAm and blood-chemistry quantifications of biological aging were moderately correlated (Pearson's r = 0.1-0.4). The GrimAge clock, DunedinPoAm, and all 3 blood-chemistry measures were associated with healthspan characteristics (e.g., mortality effect-size hazard ratios were 1.71-2.32 per standard deviation of biological aging) and showed evidence of more advanced/faster biological aging in Black participants than in White participants (Cohen's d = 0.4-0.5). These measures accounted for 13%-95% of Black-White differences in healthspan-related characteristics. Findings suggest that reducing disparities in biological aging can contribute to building health equity.

Social deprivation is associated with poor kidney transplantation outcome in children.

Socioeconomic status is an important determinant of health. Its impact on kidney transplantation outcome has been studied among adults but data in children are scarce, especially in Europe. Here, we investigate the association between the level of social deprivation (determined by the continuous score European Deprivation Index) and graft failure risk in pediatric kidney transplant recipients. All patients listed under 18 years of age who received a first kidney transplant between 2002 and 2014 in France were included. Of 1050 kidney transplant recipients (males 59%, median age at transplantation 13.2 years, preemptive transplantation 23%), 211 graft failures occurred within a median followup of 5.9 years. Thirty-seven percent of these patients belong to the most deprived quintile, suggesting that deprivation is more frequent in pediatric patients with end-stage kidney disease (ESKD) than in the general population. Five- and ten-year graft survival were 85% and 69%, respectively, in the most deprived quintile vs. 90% and 83%, respectively, in the least deprived quintile. At any time after transplantation, patients in the most deprived quintile had almost a two-fold higher hazard of graft failure compared with the least deprived quintile, after adjustment for age at renal replacement therapy, duration of dialysis, primary kidney disease, and rural/urban living environment (hazard ratio 1.99; 95% confidence interval 1.20-3.28). The hazard of graft failure did not differ significantly between girls and boys. Thus, our findings suggest a lower socioeconomic status is independently associated with poor graft outcome in pediatric kidney transplantation.

Strengthening multi-sectoral collaboration on critical health issues: One Health Systems Mapping and Analysis Resource Toolkit (OH-SMART) for operationalizing One Health.

Addressing critical global health issues, such as antimicrobial resistance, infectious disease outbreaks, and natural disasters, requires strong coordination and management across sectors. The One Health approach is the integrative effort of multiple sectors working to attain optimal health for people, animals, and the environment, and is increasingly recognized by experts as a means to address complex challenges. However, practical application of the One Health approach has been challenging. The One Health Systems Mapping and Analysis Resource Toolkit (OH-SMART) introduced in this paper was designed using a multistage prototyping process to support systematic improvement in multi-sectoral coordination and collaboration to better address complex health concerns through an operational, stepwise, and practical One Health approach. To date, OH-SMART has been used to strengthen One Health systems in 17 countries and has been deployed to revise emergency response frameworks, improve antimicrobial resistance national action plans and create multi agency infectious disease collaboration protocols. OH-SMART has proven to be user friendly, robust, and capable of fostering multi-sectoral collaboration and complex system-wide problem solving.

The Mediating Effect of Pupils' Physical Fitness on the Relationship Between Family Socioeconomic Status and Academic Achievement in a Danish School Cohort.

INTRODUCTION: Family socioeconomic status influences pupils' academic achievements, and studies have established positive associations between physical fitness and academic achievements. However, whether physical fitness mediates the relationship remains unknown. OBJECTIVE: We investigated if pupils' physical fitness mediates the pathway between family socioeconomic status and academic achievement using causal inference-based mediation analysis. METHODS: This study included 527 girls and 552 boys between 13 and 15 years of age from the Danish municipality of Aalborg. Physical fitness was measured through VO2max tests in 2010 and demographic data were obtained from nationwide registers. Family socioeconomic status was classified into four levels ranging from 1 to 4, where level 1 represents the lowest and level 4 the highest based on either family income or education. RESULTS: Controlling for sex, ethnicity, age, and parents' cohabitation status, all total effects display higher academic achievement with increased family socioeconomic status. Splitting the effects, the direct effects reveal the existence of other pathways not involving physical fitness. The indirect effects established physical fitness as a mediator showing that pupils from family socioeconomic status levels one, three, and four changes grade by - 0.13 [95% confidence interval (CI) - 0.26, - 0.01], 0.07 (95% CI 0.00, 0.14), and 0.24 (95% CI 0.14, 0.34), respectively, compared to socioeconomic status level two. The corresponding proportions mediated are 18% (95% CI 1, 57), 6% (95 CI 0, 13), and 12% (95% CI 7, 18) when family socioeconomic status is based on education. Classifying family socioeconomic status on income, pupils from family socioeconomic status levels one, three, and four show grade changes of - 0.07 (95% CI - 0.16, 0.02), 0.22 (95% CI 0.13, 0.32), and 0.26 (95% CI 0.15, 0.37), respectively, compared to socioeconomic status level two. The corresponding proportions mediated are 12% (95% CI - 6, 41), 30% (95% CI 16, 54), and 20% (95% CI 12, 32). CONCLUSION: In conclusion, pupils' physical fitness partially mediated the pathway between family socioeconomic status and academic achievement.

Socioeconomic and Tobacco Mediation of Ethnic Inequalities in Mortality over Time: Repeated Census-mortality Cohort Studies, 1981 to 2011.

BACKGROUND: Racial/ethnic inequalities in mortality may be reducible by addressing socioeconomic factors and smoking. To our knowledge, this is the first study to estimate trends over multiple decades in (1) mediation of racial/ethnic inequalities in mortality (between Maori and Europeans in New Zealand) by socioeconomic factors, (2) additional mediation through smoking, and (3) inequalities had there never been smoking. METHODS: We estimated natural (1 and 2 above) and controlled mediation effects (3 above) in census-mortality cohorts for 1981-1984 (1.1 million people), 1996-1999 (1.5 million), and 2006-2011 (1.5 million) for 25- to 74-year-olds in New Zealand, using a weighting of regression predicted outcomes. RESULTS: Socioeconomic factors explained 46% of male inequalities in all three cohorts and made an increasing contribution over time among females from 30.4% (95% confidence interval = 18.1%, 42.7%) in 1981-1984 to 41.9% (36.0%, 48.0%). Including smoking with socioeconomic factors only modestly altered the percentage mediated for males, but more substantially increased it for females, for example, 7.7% (5.5%, 10.0%) in 2006-2011. A counterfactual scenario of having eradicated tobacco in the past (but unchanged socioeconomic distribution) lowered mortality for all sex-by-ethnic groups and resulted in a 12.2% (2.9%, 20.8%) and 21.2% (11.6%, 31.0%) reduction in the absolute mortality gap between Maori and Europeans in 2006-2011, for males and females, respectively. CONCLUSIONS: Our study predicts that, in this high-income country, reducing socioeconomic disparities between ethnic groups would greatly reduce ethnic inequalities in mortality over the long run. Eradicating tobacco would notably reduce ethnic inequalities in absolute but not relative mortality.

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for a binary exposure in cancer mortality. We conduct numerical analyses to study the bias and efficiency of these estimators. Furthermore, we compare 2 different model selection strategies based on 1) Akaike's Information Criterion and the Bayesian Information Criterion and 2) machine learning algorithms, and we illustrate double-robust estimators' performance in a real-world setting. In simulations with correctly specified models and near-positivity violations, all but the naive estimators had relatively good performance. However, the augmented inverse-probability-of-treatment weighting estimator showed the largest relative bias. Under dual model misspecification and near-positivity violations, all double-robust estimators were biased. Nevertheless, the targeted maximum likelihood estimator showed the best bias-variance trade-off, more precise estimates, and appropriate 95% confidence interval coverage, supporting the use of the data-adaptive model selection strategies based on machine learning algorithms. We applied these methods to estimate adjusted 1-year mortality risk differences in 183,426 lung cancer patients diagnosed after admittance to an emergency department versus persons with a nonemergency cancer diagnosis in England (2006-2013). The adjusted mortality risk (for patients diagnosed with lung cancer after admittance to an emergency department) was 16% higher in men and 18% higher in women, suggesting the importance of interventions targeting early detection of lung cancer signs and symptoms.

Multiple mediators approach to study environmental chemicals as determinants of health disparities.

A major goal of health disparities research is to identify and intervene upon modifiable risk factors that help explain the observed associations between social factors and adverse health outcomes. To this end, statistical methods incorporating mediation analysis have shown promise, as they quantify the contribution of an intermediate variable in an exposure-outcome association. A growing body of literature suggests that environmental chemicals can contribute to health disparities. However, evaluating environmental chemicals as an important component of health disparities introduces methodological complexities that may make standard mediation approaches inadequate. Specific to environmental health is the issue of evaluating both the source and biomarker of the environmental toxicant in order to calculate the proportion of the disparity that would remain had we intervened on the modifiable factors. Recent methodological developments on multiple mediators can improve efforts to integrate both source and biomarker of exposure into epidemiological studies of health disparities. We illustrate a conceptual framework and present how mediation techniques can be used to address environmental health disparities questions. With this, we provide a methodological tool that has the potential to advance this growing field, while simultaneously informing public health prevention and policy surrounding the impact of environmental factors on health disparities.

Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators.

BACKGROUND: The recent Ebola virus disease (EVD) outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered. METHODS: To investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2) in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models. RESULTS: The polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic. DISCUSSION: By combining two common methods-estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models-we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur.

Estimating causal contrasts involving intermediate variables in the presence of selection bias.

An important goal across the biomedical and social sciences is the quantification of the role of intermediate factors in explaining how an exposure exerts an effect on an outcome. Selection bias has the potential to severely undermine the validity of inferences on direct and indirect causal effects in observational as well as in randomized studies. The phenomenon of selection may arise through several mechanisms, and we here focus on instances of missing data. We study the sign and magnitude of selection bias in the estimates of direct and indirect effects when data on any of the factors involved in the analysis is either missing at random or not missing at random. Under some simplifying assumptions, the bias formulae can lead to nonparametric sensitivity analyses. These sensitivity analyses can be applied to causal effects on the risk difference and risk-ratio scales irrespectively of the estimation approach employed. To incorporate parametric assumptions, we also develop a sensitivity analysis for selection bias in mediation analysis in the spirit of the expectation-maximization algorithm. The approaches are applied to data from a health disparities study investigating the role of stage at diagnosis on racial disparities in colorectal cancer survival. Copyright © 2016 John Wiley & Sons, Ltd.

The Role of Stage at Diagnosis in Colorectal Cancer Black-White Survival Disparities: A Counterfactual Causal Inference Approach.

BACKGROUND: To date, a counterfactual framework has not been used to study determinants of social inequalities in cancer. Considering the case of colorectal cancer, for which racial/ethnic differences in stage at diagnosis and survival are well documented, we quantify the extent to which black versus white survival disparities would be reduced had disparities in stage at diagnosis been eliminated in a large patient population. METHODS: We obtained data on colorectal cancer patients (diagnosed between 1992 and 2005 and followed until 2010) from US-SEER (Surveillance, Epidemiology, and End Results) cancer registries. We employed a counterfactual approach to estimate the mean survival time up to the 60th month since diagnosis for black colorectal cancer patients had black-white disparities in stage at diagnosis been eliminated. RESULTS: Black patients survive approximately 4.0 [confidence interval (CI), 4.6-3.2] months less than white patients within five years since diagnosis. Had disparities in stage at diagnosis been eliminated, survival disparities decrease to 2.6 (CI, 3.4-1.7) months, an approximately 35% reduction. For patients diagnosed after the age of 65 years, disparities would be halved, while reduction of approximately 30% is estimated for younger patients. Survival disparities would be reduced by approximately 44% for women and approximately 26% for men. CONCLUSIONS: Employing a counterfactual approach and allowing for heterogeneities in black-white disparities across patients' characteristics, we give robust evidence that elimination of disparities in stage at diagnosis contributes to a substantial reduction in survival disparities in colorectal cancer. IMPACT: We provide the first evidence in the SEER population that elimination of inequities in stage at diagnosis might lead to larger reductions in survival disparities among elderly and women.