Multilevel Resilience and HIV Virologic Suppression Among African American/Black Adults in the Southeastern United States.

OBJECTIVE: To assess overall and by neighborhood risk environments whether multilevel resilience resources were associated with HIV virologic suppression among African American/Black adults in the Southeastern United States. SETTING AND METHODS: This clinical cohort sub-study included 436 African American/Black participants enrolled in two parent HIV clinical cohorts. Resilience was assessed using the Multilevel Resilience Resource Measure (MRM) for African American/Black adults living with HIV, where endorsement of a MRM statement indicated agreement that a resilience resource helped a participant continue HIV care despite challenges or was present in a participant's neighborhood. Modified Poisson regression models estimated adjusted prevalence ratios (aPRs) for virologic suppression as a function of categorical MRM scores, controlling for demographic, clinical, and behavioral characteristics at or prior to sub-study enrollment. We assessed for effect measure modification (EMM) by neighborhood risk environments. RESULTS: Compared to participants with lesser endorsement of multilevel resilience resources, aPRs for virologic suppression among those with greater or moderate endorsement were 1.03 (95% confidence interval: 0.96-1.11) and 1.03 (0.96-1.11), respectively. Regarding multilevel resilience resource endorsement, there was no strong evidence for EMM by levels of neighborhood risk environments. CONCLUSIONS: Modest positive associations between higher multilevel resilience resource endorsement and virologic suppression were at times most compatible with the data. However, null findings were also compatible. There was no strong evidence for EMM concerning multilevel resilience resource endorsement, which could have been due to random error. Prospective studies assessing EMM by levels of the neighborhood risk environment with larger sample sizes are needed.

Geospatial Distribution of Racial Disparities in Influenza Vaccination in Nursing Homes.

OBJECTIVES: This study aimed to assess the distribution of racial disparities in influenza vaccination between White and Black short-stay and long-stay nursing home residents among states and hospital referral regions (HRRs). DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: We included short-stay and long-stay older adults residing in US nursing homes during influenza seasons between 2011 and 2018. Included residents were aged ≥65 years and enrolled in Traditional Medicare. Analyses were conducted using resident-seasons, whereby residents could contribute to one or more influenza seasons if they resided in a nursing home across multiple seasons. METHODS: Our comparison of interest was marginalized vs privileged racial group membership measured as Black vs White race. We obtained influenza vaccination documentation from resident Minimum Data Set assessments from October 1 through June 30 of a particular influenza season. Nonparametric g-formula was used to estimate age- and sex-standardized disparities in vaccination, measured as the percentage point (pp) difference in the proportions of individuals vaccinated between Black and White nursing home residents within states and HRRs. RESULTS: The study included 7,807,187 short-stay resident-seasons (89.7% White and 10.3% Black) in 14,889 nursing homes and 7,308,111 long-stay resident-seasons (86.7% White and 13.3% Black) in 14,885 nursing homes. Among states, the median age- and sex-standardized disparity between Black and White residents was 10.1 percentage points (pps) among short-stay residents and 5.3 pps among long-stay residents across seasons. Among HRRs, the median disparity was 8.6 pps among short-stay residents and 5.0 pps among long-stay residents across seasons. CONCLUSIONS AND IMPLICATIONS: Our analysis revealed that the magnitudes of vaccination disparities varied substantially across states and HRRs, from no disparity in vaccination to disparities in excess of 25 pps. Local interventions and policies should be targeted to high-disparity geographic areas to increase vaccine uptake and promote health equity.

Examining the Relationship Between Multilevel Resilience Resources and Cardiovascular Disease Incidence, Overall and by Psychosocial Risks, Among Participants in the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study.

We examined relationships between resilience resources (optimism, social support, and neighborhood social cohesion) and cardiovascular disease (CVD) incidence and assessed potential effect-measure modification by psychosocial risk factors (e.g., stress, depression) among adults without CVD in 3 cohort studies (2000-2018): the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study. We fitted adjusted Cox models accounting for within-neighborhood clustering while censoring at dropout or non-CVD death. We assessed for effect-measure modification by psychosocial risks. In secondary analyses, we estimated standardized risk ratios using inverse-probability-weighted Aalen-Johansen estimators to account for confounding, dropout, and competing risks (non-CVD deaths) and obtained 95% confidence intervals (CIs) using cluster bootstrapping. For high and medium (versus low) optimism (n = 6,243), adjusted hazard ratios (HRs) for incident CVD were 0.94 (95% CI: 0.78, 1.13) and 0.90 (95% CI: 0.75, 1.07), respectively. Corresponding HRs were 0.88 (95% CI: 0.74, 1.04) and 0.92 (95% CI: 0.79, 1.06) for social support (n = 7,729) and 1.10 (95% CI: 0.94, 1.29) and 0.99 (95% CI: 0.85, 1.16) for social cohesion (n = 7,557), respectively. Some psychosocial risks modified CVD HRs. Secondary analyses yielded similar findings. For optimism and social support, an inverse relationship was frequently most compatible with the data, but a positive relationship was also compatible. For neighborhood social cohesion, positive and null relationships were most compatible. Thus, specific resilience resources may be potential intervention targets, especially among certain subgroups.

Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study.

Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. We conducted a simulation study to evaluate a super learner's predictions of 3 seasonal measures of influenza hospitalizations in the United States: peak hospitalization rate, peak hospitalization week, and cumulative hospitalization rate. We trained an ensemble machine learning algorithm on 15,000 simulated hospitalization curves and generated weekly predictions. We compared the performance of the ensemble (weighted combination of predictions from multiple prediction algorithms), the best-performing individual prediction algorithm, and a naive prediction (median of a simulated outcome distribution). Ensemble predictions performed similarly to the naive predictions early in the season but consistently improved as the season progressed for all prediction targets. The best-performing prediction algorithm in each week typically had similar predictive accuracy compared with the ensemble, but the specific prediction algorithm selected varied by week. An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. Future work should examine the super learner's performance using additional empirical data on influenza-related predictors (e.g., influenza-like illness). The algorithm should also be tailored to produce prospective probabilistic forecasts of selected prediction targets.

Geographic Variation in Racial Disparities in Receipt of High-Dose Influenza Vaccine Among US Older Adults.

BACKGROUND: Racial disparities in receipt of high-dose influenza vaccine (HDV) have been documented nationally, but whether small-area geographic variation in such disparities exists remains unknown. We assessed the distribution of disparities in HDV receipt between Black and White traditional Medicare beneficiaries vaccinated against influenza within states and hospital referral regions (HRRs). METHODS: We conducted a nationally representative retrospective cohort study of 11,768,724 community-dwelling traditional Medicare beneficiaries vaccinated against influenza during the 2015-2016 influenza season (94.3% White and 5.7% Black). Our comparison was marginalized versus privileged racial group measured as Black versus White race. Vaccination and type of vaccine were obtained from Medicare Carrier and Outpatient files. Differences in the proportions of individuals who received HDV between Black and White beneficiaries within states and HRRs were used to measure age- and sex-standardized disparities in HDV receipt. We restricted to states and HRRs with ≥ 100 beneficiaries per age-sex strata per racial group. RESULTS: We detected a national disparity in HDV receipt of 12.8 percentage points (pps). At the state level, the median standardized HDV receipt disparity was 10.7 pps (minimum, maximum: 2.9, 25.6; n = 30 states). The median standardized HDV receipt disparity among HRRs was 11.6 pps (minimum, maximum: 0.4, 24.7; n = 54 HRRs). CONCLUSION: Black beneficiaries were less likely to receive HDV compared to White beneficiaries in almost every state and HRR in our analysis. The magnitudes of disparities varied substantially across states and HRRs. Local interventions and policies are needed to target geographic areas with the largest disparities to address these inequities.

Endometrial Cancer Surgery With or Without Concomitant Stress Urinary Incontinence Surgery.

OBJECTIVE: To compare quality of life (QOL) among patients with endometrial intraepithelial neoplasia or early-stage endometrial cancer and stress urinary incontinence (SUI) who chose to have concomitant surgery with cancer surgery alone. METHODS: A multicenter, prospective cohort study was conducted across eight U.S. sites. Potentially eligible patients were screened for SUI symptoms. Those who screened positive were offered referral to urogynecology and incontinence treatment, including concomitant surgery. Participants were categorized into two groups: 1) concomitant cancer and SUI surgery or 2) cancer surgery alone. The primary outcome was cancer-related QOL as measured by the FACT-En (Functional Assessment of Cancer Therapy-Endometrial) (range 0-100; higher score indicates better QOL). The FACT-En and questionnaires assessing urinary symptom-specific severity and effects were assessed before surgery and 6 weeks, 6 months, and 12 months after surgery. Adjusted median regression accounting for clustering was used to examine the relationship between SUI treatment group and FACT-En scores. RESULTS: Of 1,322 (53.1%) patients, 702 screened positive for SUI with 532 analyzed; 110 (21%) chose concomitant cancer and SUI surgery, and 422 (79%) chose cancer surgery alone. FACT-En scores increased for both the concomitant SUI surgery and cancer surgery-only groups from the preoperative to the postoperative period. After adjustment for timepoint and preoperative covariates, the median change in FACT-En score (postoperative-preoperative) was 1.2 points higher (95% CI -1.3 to 3.6) for the concomitant SUI surgery group compared with the cancer surgery-only group across the postoperative period. Median time until surgery (22 days vs 16 days; P <.001), estimated blood loss (150 mL vs 72.5 mL; P <.001), and operative time (185.5 minutes vs 152 minutes; P <.001) were all greater for the concomitant cancer and SUI surgery group compared with the cancer-only group, respectively. CONCLUSION: Concomitant surgery did not result in improved QOL compared with cancer surgery alone for endometrial intraepithelial neoplasia and patients with early-stage endometrial cancer with SUI. However, FACT-En scores were improved in both groups.

Change talk subtypes as predictors of alcohol use following brief motivational intervention.

OBJECTIVE: To examine the relative importance of client change language subtypes as predictors of alcohol use following motivational interviewing (MI). METHOD: Participants were 164 heavy drinkers (57.3% female, Mage = 28.5 years, 13.4% Hispanic/Latinx, 82.9% White) recruited during an emergency department visit who received MI for alcohol and human immunodeficiency virus/sexual risk in a randomized-controlled trial. MI sessions were coded with the motivational interviewing skill code (MISC) and the generalized behavioral intervention analysis system (GBIAS). Variable importance analyses used targeted maximum likelihood estimation to rank order change language subtypes defined by these systems as predictors of alcohol use over 9 months of follow-up. RESULTS: Among GBIAS change language subtypes, higher sustain talk (ST) around change planning was ranked the most important predictor of drinks per week (b = -5.57, 95% CI [-8.11, -3.02]) and heavy drinking days (b = -2.07, 95% CI [-3.17, -0.98]); this talk reflected (a) rejection of alcohol abstinence as a desired change goal, (b) rejection of specific change strategies, or (c) discussion of anticipated challenges in changing drinking. Among MISC change language subtypes, higher ST around taking steps-reflecting recent escalations in drinking described by a small minority of participants-was ranked the most important predictor of drinks per week (b = 22.71, 95% CI [20.29, 25.13]) and heavy drinking days (b = -2.45, 95% CI [1.68, 3.21]). CONCLUSIONS: Results challenge the assumption that all ST during MI is a negative prognostic indicator and highlight the importance of the context in which change language emerges. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Characterizing the neighborhood risk environment in multisite clinic-based cohort studies: A practical geocoding and data linkages protocol for protected health information.

BACKGROUND: Maintaining patient privacy when geocoding and linking residential address information with neighborhood-level data can create challenges during research. Challenges may arise when study staff have limited training in geocoding and linking data, or when non-study staff with appropriate expertise have limited availability, are unfamiliar with a study's population or objectives, or are not affordable for the study team. Opportunities for data breaches may also arise when working with non-study staff who are not on-site. We detail a free, user-friendly protocol for constructing indices of the neighborhood risk environment during multisite, clinic-based cohort studies that rely on participants' protected health information. This protocol can be implemented by study staff who do not have prior training in Geographic Information Systems (GIS) and can help minimize the operational costs of integrating geographic data into public health projects. METHODS: This protocol demonstrates how to: (1) securely geocode patients' residential addresses in a clinic setting and match geocoded addresses to census tracts using Geographic Information System software (Esri, Redlands, CA); (2) ascertain contextual variables of the risk environment from the American Community Survey and ArcGIS Business Analyst (Esri, Redlands, CA); (3) use geoidentifiers to link neighborhood risk data to census tracts containing geocoded addresses; and (4) assign randomly generated identifiers to census tracts and strip census tracts of their geoidentifiers to maintain patient confidentiality. RESULTS: Completion of this protocol generates three neighborhood risk indices (i.e., Neighborhood Disadvantage Index, Murder Rate Index, and Assault Rate Index) for patients' coded census tract locations. CONCLUSIONS: This protocol can be used by research personnel without prior GIS experience to easily create objective indices of the neighborhood risk environment while upholding patient confidentiality. Future studies can adapt this protocol to fit their specific patient populations and analytic objectives.

Geographic Variation in Influenza Vaccination Disparities Between Hispanic and Non-Hispanic White US Nursing Home Residents.

Background: Disparities in influenza vaccination exist between Hispanic and non-Hispanic White US nursing home (NH) residents, but the geographic areas with the largest disparities remain unknown. We examined how these racial/ethnic disparities differ across states and hospital referral regions (HRRs). Methods: This retrospective cohort study included >14 million short-stay and long-stay US NH resident-seasons over 7 influenza seasons from October 1, 2011, to March 31, 2018, where residents could contribute to 1 or more seasons. Residents were aged ≥65 years and enrolled in Medicare fee-for-service. We used the Medicare Beneficiary Summary File to ascertain race/ethnicity and Minimum Data Set assessments for influenza vaccination. We calculated age- and sex-standardized percentage point (pp) differences in the proportions vaccinated between non-Hispanic White and Hispanic (any race) resident-seasons. Positive pp differences were considered disparities, where the proportion of non-Hispanic White residents vaccinated was greater than the proportion of Hispanic residents vaccinated. States and HRRs with ≥100 resident-seasons per age-sex stratum per racial/ethnic group were included in analyses. Results: Among 7 442 241 short-stay resident-seasons (94.1% non-Hispanic White, 5.9% Hispanic), the median standardized disparities in influenza vaccination were 4.3 pp (minimum, maximum: 0.3, 19.2; n = 22 states) and 2.8 pp (minimum, maximum: -3.6, 10.3; n = 49 HRRs). Among 6 758 616 long-stay resident-seasons (93.7% non-Hispanic White, 6.5% Hispanic), the median standardized differences were -0.1 pp (minimum, maximum: -4.1, 11.4; n = 18 states) and -1.8 pp (minimum, maximum: -6.5, 7.6; n = 34 HRRs). Conclusions: Wide geographic variation in influenza vaccination disparities existed across US states and HRRs. Localized interventions targeted toward areas with high disparities may be a more effective strategy to promote health equity than one-size-fits-all national interventions.

Social support, psychosocial risks, and cardiovascular health: Using harmonized data from the Jackson Heart Study, Mediators of Atherosclerosis in South Asians Living in America Study, and Multi-Ethnic Study of Atherosclerosis.

Purpose: Social support may have benefits on cardiovascular health (CVH). CVH is evaluated using seven important metrics (Life's Simple 7; LS7) established by the American Heart Association (e.g., smoking, diet). However, evidence from longitudinal studies is limited and inconsistent. The objective of this study is to examine the longitudinal relationship between social support and CVH, and assess whether psychosocial risks (e.g., anger and stress) modify the relationship in a racially/ethnically diverse population. Methods: Participants from three harmonized cohort studies - Jackson Heart Study, Mediators of Atherosclerosis in South Asians Living in America, and Multi-Ethnic Study of Atherosclerosis - were included. Repeated-measures modified Poisson regression models were used to examine the overall relationship between social support (in tertiles) and CVH (LS7 metric), and to assess for effect modification by psychosocial risk. Results: Among 7724 participants, those with high (versus low) social support had an adjusted prevalence ratio (aPR) and 95% confidence interval (CI) for ideal or intermediate (versus poor) CVH of 0.99 (0.96-1.03). For medium (versus low) social support, the aPR (95% CI) was 1.01 (0.98-1.05). There was evidence for modification by employment and anger. Those with medium (versus low) social support had an aPR (95% CI) of 1.04 (0.99-1.10) among unemployed or low anger participants. Corresponding results for employed or high anger participants were 0.99 (0.94-1.03) and 0.97 (0.91-1.03), respectively. Conclusion: Overall, we observed no strong evidence for an association between social support and CVH. However, some psychosocial risks may be modifiers. Prospective studies are needed to assess the social support-CVH relationship by psychosocial risks in racially/ethnically diverse populations.

Examining relationships between perceived neighborhood social cohesion and ideal cardiovascular health and whether psychosocial stressors modify observed relationships among JHS, MESA, and MASALA participants.

BACKGROUND: Psychosocial stressors increase the risks for cardiovascular disease across diverse populations. However, neighborhood level resilience resources may protect against poor cardiovascular health (CVH). This study used data from three CVH cohorts to examine longitudinally the associations of a resilience resource, perceived neighborhood social cohesion (hereafter referred to as neighborhood social cohesion), with the American Heart Association's Life's Simple 7 (LS7), and whether psychosocial stressors modify observed relationships. METHODS: We examined neighborhood social cohesion (measured in tertiles) and LS7 in the Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, and Mediators of Atherosclerosis in South Asians Living in America study. We used repeated-measures, modified Poisson regression models to estimate the relationship between neighborhood social cohesion and LS7 (primary analysis, n = 6,086) and four biological metrics (body mass index, blood pressure, cholesterol, blood glucose; secondary analysis, n = 7,291). We assessed effect measure modification by each psychosocial stressor (e.g., low educational attainment, discrimination). RESULTS: In primary analyses, adjusted prevalence ratios (aPR) and 95% confidence intervals (CIs) for ideal/intermediate versus poor CVH among high or medium (versus low) neighborhood social cohesion were 1.01 (0.97-1.05) and 1.02 (0.98-1.06), respectively. The psychosocial stressors, low education and discrimination, functioned as effect modifiers. Secondary analyses showed similar findings. Also, in the secondary analyses, there was evidence for effect modification by income. CONCLUSION: We did not find much support for an association between neighborhood social cohesion and LS7, but did find evidence of effect modification. Some of the effect modification results operated in unexpected directions. Future studies should examine neighborhood social cohesion more comprehensively and assess for effect modification by psychosocial stressors.

Recommendations for Using Causal Diagrams to Study Racial Health Disparities.

There have been calls for race to be denounced as a biological variable and for a greater focus on racism, instead of solely race, when studying racial health disparities in the United States. These calls are grounded in extensive scholarship and the rationale that race is not a biological variable, but instead socially constructed, and that structural/institutional racism is a root cause of race-related health disparities. However, there remains a lack of clear guidance for how best to incorporate these assertions about race and racism into tools, such as causal diagrams, that are commonly used by epidemiologists to study population health. We provide clear recommendations for using causal diagrams to study racial health disparities that were informed by these calls. These recommendations consider a health disparity to be a difference in a health outcome that is related to social, environmental, or economic disadvantage. We present simplified causal diagrams to illustrate how to implement our recommendations. These diagrams can be modified based on the health outcome and hypotheses, or for other group-based differences in health also rooted in disadvantage (e.g., gender). Implementing our recommendations may lead to the publication of more rigorous and informative studies of racial health disparities.

Toward a Clearer Definition of Selection Bias When Estimating Causal Effects.

Selection bias remains a subject of controversy. Existing definitions of selection bias are ambiguous. To improve communication and the conduct of epidemiologic research focused on estimating causal effects, we propose to unify the various existing definitions of selection bias in the literature by considering any bias away from the true causal effect in the referent population (the population before the selection process), due to selecting the sample from the referent population, as selection bias. Given this unified definition, selection bias can be further categorized into two broad types: type 1 selection bias owing to restricting to one or more level(s) of a collider (or a descendant of a collider) and type 2 selection bias owing to restricting to one or more level(s) of an effect measure modifier. To aid in explaining these two types-which can co-occur-we start by reviewing the concepts of the target population, the study sample, and the analytic sample. Then, we illustrate both types of selection bias using causal diagrams. In addition, we explore the differences between these two types of selection bias, and describe methods to minimize selection bias. Finally, we use an example of "M-bias" to demonstrate the advantage of classifying selection bias into these two types.

Illustrating How to Simulate Data From Directed Acyclic Graphs to Understand Epidemiologic Concepts.

Simulation methods are a powerful set of tools that can allow researchers to better characterize phenomena from the real world. As such, the ability to simulate data represents a critical set of skills that epidemiologists should use to better understand epidemiologic concepts and ensure that they have the tools to continue to self-teach even when their formal instruction ends. Simulation methods are not always taught in epidemiology methods courses, whereas causal directed acyclic graphs (DAGs) often are. Therefore, this paper details an approach to building simulations from DAGs and provides examples and code for learning to perform simulations. We recommend using very simple DAGs to learn the procedures and code necessary to set up a simulation that builds on key concepts frequently of interest to epidemiologists (e.g., mediation, confounding bias, M bias). We believe that following this approach will allow epidemiologists to gain confidence with a critical skill set that may in turn have a positive impact on how they conduct future epidemiologic studies.

Is overweight or obesity associated with anemia in children? Follow-up of Samoans in the Ola Tuputupua'e "Growing Up" study.

OBJECTIVES: Globally, there is growing evidence of a double burden of malnutrition with obesity coexisting alongside micronutrient deficiencies across the life course. An emergent double burden poses a threat to health during childhood in Samoa: among 2-4-year-olds with overweight/obesity, 42.9% were anemic. Previous research suggests that obesity-related inflammation may increase the risk of iron deficiency or anemia in children. To test this hypothesis, we examined whether overweight/obesity at 2-4 is associated with anemia at 3.8-6 years old among Samoan children. METHODS: Data were obtained from the Ola Tuputupua'e "Growing Up" cohort study. Overweight/obesity at 2-4 years old was classified by body mass index-for-age Z-score > +2 SD. Anemia was defined as hemoglobin < 110 g/L for under 5-year-olds and < 115 g/L for 5-6-year-olds. Prevalence ratios (PRs) for anemia at 3.8-6 years old were estimated by fitting modified Poisson regression models. RESULTS: In our sample of 197 children, 16.24% (n = 32) were affected by overweight/obesity at 2-4 years old and 26.90% (n = 53) had anemia at 3.8-6 years old. After covariate adjustment, the prevalence of anemia was 18% lower among children with overweight/obesity at 2-4 years old compared to those without (PR:0.82; 95% CI:0.42-1.63); however, the corresponding confidence interval was imprecise and inclusive of a higher prevalence. CONCLUSIONS: There was not strong evidence to support a relationship between overweight/obesity and anemia in Samoan children, suggesting that obesity-related inflammation may not be related to iron deficiency nor anemia in this setting. Further investigation of the antecedents of overweight/obesity and anemia is critical to inform integrated action to improve health in Samoa.

Development of Long and Short Forms of the Multilevel Resilience Resource Measure for African American/Black Adults Living with HIV.

Understanding resilience in relation to HIV-related outcomes may help address racial/ethnic disparities, however, significant gaps in its measurement preclude in-depth study. Thus, this research aims to develop and evaluate the psychometric properties of long and short forms of the Multilevel Resilience Resource Measure for African American/Black Adults Living with HIV. To develop the items, we conducted a mixed methods study (N = 48) and reviewed published resilience measures. We completed content validity index analyses to ensure the items reflected the resilience construct. Next, we conducted 20 cognitive interviews and a field survey (N = 400). The long and short forms demonstrated acceptable to excellent psychometric properties based on factorial validity, internal consistency and convergent validity and on measurement invariance (conducted for the short form only). These measures provide a comprehensive framework to examine resilience and HIV-related outcomes and can inform resilience-building interventions to reduce racial and ethnic health disparities.

Advancing the Social Epidemiology Mission of the American Journal of Epidemiology.

Social epidemiology is concerned with how social forces influence population health. Rather than focusing on a single disease (as in cancer or cardiovascular epidemiology) or a single type of exposure (e.g., nutritional epidemiology), social epidemiology encompasses all the social and economic determinants of health, both historical and contemporary. These include features of social and physical environments, the network of relationships in a society, and the institutions, politics, policies, norms and cultures that shape all of these forces. This commentary presents the perspective of several editors at the Journal with expertise in social epidemiology. We articulate our thinking to encourage submissions to the Journal that: 1) expand knowledge of emerging and underresearched social determinants of population health; 2) advance new empirical evidence on the determinants of health inequities and solutions to advance health equity; 3) generate evidence to inform the translation of research on social determinants of health into public health impact; 4) contribute to innovation in methods to improve the rigor and relevance of social epidemiology; and 5) encourage critical self-reflection on the direction, challenges, successes, and failures of the field.

Urinary Cadmium and Incident Heart Failure: A Case-Cohort Analysis Among Never-Smokers in Denmark.

BACKGROUND: Epidemiologic studies suggest cadmium exposure is associated with cardiovascular disease risk, including heart failure. However, prior findings may be influenced by tobacco smoking, a dominant source of cadmium exposure and risk factor for heart failure. The present study leverages up to 20 years of follow-up in the Danish Diet, Cancer and Health cohort to examine the relationship between urinary cadmium and incident heart failure among people who never smoked. METHODS: Between 1993 and 1997, 19,394 never-smoking participants (ages 50-64 years) enrolled and provided a urine sample. From this sample, we randomly selected a subcohort of 600 men and 600 women and identified 958 incident heart failure cases occurring between baseline and 2015. Using a case-cohort approach, we estimated adjusted hazard ratios (aHR) for heart failure in Cox proportional hazards models with age as the time scale. RESULTS: Participants had relatively low concentrations of urinary cadmium, as expected for never smokers (median = 0.20; 25th, 75th = 0.13, 0.32 µg cadmium/g creatinine). In adjusted models, we found that higher urinary cadmium was associated with a higher rate of incident heart failure overall (aHR = 1.1 per interquartile range difference [95% CI = 1.0, 1.2). In sex-stratified analyses, the association seemed restricted to men (aHR = 1.5 [95% CI = 1.2, 1.9]). CONCLUSIONS: In this cohort of people who never smoked tobacco, environmental cadmium was positively associated with incident heart failure, especially among men.

Multilevel resilience resources and cardiovascular disease in the United States: A systematic review and meta-analysis.

Objective: This systematic review and meta-analysis aimed to quantify the relationship between resilience resources at the individual (e.g., optimism), interpersonal (e.g., social support), and neighborhood (e.g., social environment) levels, and cardiovascular outcomes among adults in the United States. Method: On 9/25/2020, electronic databases (PubMed, Embase, CINAHL, PsycINFO) were systematically searched for randomized controlled trials, nonrandomized intervention studies, and prospective cohort studies that examined the relationship between resilience resources at the individual, interpersonal, or neighborhood level and cardiovascular outcomes. Studies that met the eligibility criteria were summarized narratively and quantitatively. Because relevant search results yielded only observational studies, risk of bias was assessed using an adapted version of the Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-I) tool. Results: From 4,103 unique records, 13 prospective cohort studies with a total of 310,906 participants met the eligibility criteria, and six of these studies were included in the meta-analyses. Most relevant studies found that higher levels of individual-level resilience resources were associated with lower incidence of adverse cardiovascular outcomes, with point estimates ranging from .46 to 1.18. Interpersonal-level resilience resources (i.e., social network) were associated with a lower coronary heart disease risk (risk ratio, .76; 95% CI [.56, 1.02]). Neighborhood-level resilience resources (i.e., perceived social cohesion and residential stability) were associated with a lower odds of stroke (odds ratio, .92; 95% CI [.84, 1.01]). Conclusions: Evidence suggests that higher levels of resilience resources are associated with better cardiovascular outcomes. However, more prospective studies with diverse populations are needed to strengthen the evidence. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Relationship between Urine Creatinine and Urine Osmolality in Spot Samples among Men and Women in the Danish Diet Cancer and Health Cohort.

Assays of urine biomarkers often use urine creatinine to account for urinary dilution, even though creatinine levels are influenced by underlying physiology and muscle catabolism. Urine osmolality-a measure of dissolved particles including ions, glucose, and urea-is thought to provide a more robust marker of urinary dilution but is seldom measured. The relationship between urine osmolality and creatinine is not well understood. We calculated correlation coefficients between urine creatinine and osmolality among 1375 members of a subcohort of the Danish Diet, Cancer, and Health Cohort, and within different subgroups. We used linear regression to relate creatinine with osmolality, and a lasso selection procedure to identify other variables that explain remaining variability in osmolality. Spearman correlation between urine creatinine and osmolality was strong overall (ρ = 0.90; 95% CI: 0.89-0.91) and in most subgroups. Linear regression showed that urine creatinine explained 60% of the variability in urine osmolality, with another 9% explained by urine thallium (Tl), cesium (Cs), and strontium (Sr). Urinary creatinine and osmolality are strongly correlated, although urine Tl, Cs, and Sr might help supplement urine creatinine for purposes of urine dilution adjustment when osmolality is not available.