County-Level Social Vulnerability Is Positively Associated with Cardiometabolic Disease in Colorado

Socio-ecological factors linked with changes in adults' dietary intake in Los Angeles County during the peak of the coronavirus 2019 pandemic

OBJECTIVE

Comprehensive studies examining longitudinal predictors of dietary change during the coronavirus disease 2019 pandemic are lacking. Based on an ecological framework, this study used longitudinal data to test if individual, social and environmental factors predicted change in dietary intake during the peak of the coronavirus 2019 pandemic in Los Angeles County and examined interactions among the multilevel predictors.

DESIGN

We analysed two survey waves (e.g. baseline and follow-up) of the Understanding America Study, administered online to the same participants 3 months apart. The surveys assessed dietary intake and individual, social, and neighbourhood factors potentially associated with diet. Lagged multilevel regression models were used to predict change from baseline to follow-up in daily servings of fruits, vegetables and sugar-sweetened beverages.

SETTING

Data were collected in October 2020 and January 2021, during the peak of the coronavirus disease 2019 pandemic in Los Angeles County.

PARTICIPANTS

903 adults representative of Los Angeles County households.

RESULTS

Individuals who had depression and less education or who identified as non-Hispanic Black or Hispanic reported unhealthy dietary changes over the study period. Individuals with smaller social networks, especially low-income individuals with smaller networks, also reported unhealthy dietary changes. After accounting for individual and social factors, neighbourhood factors were generally not associated with dietary change.

CONCLUSIONS

Given poor diets are a leading cause of death in the USA, addressing ecological risk factors that put some segments of the community at risk for unhealthy dietary changes during a crisis should be a priority for health interventions and policy.

An Analysis of the Social Determinants of Health in South Carolina's I-95 Corridor

BACKGROUND

One in four South Carolinians lives in a county along a nearly 200-mile stretch of Interstate 95 (I-95). Stretching from North Carolina to Georgia, this region is among the most rural, economically depressed, and racially/ethnically diverse in the state. Research is needed to identify social factors contributing to adverse health outcomes along the I-95 corridor, guide interventions, and establish a baseline for measuring progress. This study assessed social determinants of health in counties in South Carolina's I-95 corridor relative to the rest of the state.

METHOD

Data for South Carolina's 46 counties were extracted from the Centers for Disease Control and Prevention Minority Health Social Vulnerability Index (SVI), which grouped 34 census variables into six themes: socioeconomic status, household composition and disability, minority status and language, housing type and transportation, health care infrastructure, and medical vulnerability. Each theme was ranked from 0 (least vulnerable) to 1 (most vulnerable). Measures between regions were compared using the Wilcoxon-Mann-Whitney test.

RESULTS

Compared with counties outside the I-95 corridor (n = 29), counties in the corridor (n = 17) scored higher on socioeconomic status vulnerability (.67 and .82, respectively) and medical vulnerability (.65 and .79, respectively). No statistically significant differences were found across other themes.

CONCLUSION

Identifying social determinants of health in South Carolina's I-95 corridor is a crucial first step toward alleviating health disparities in this region. Interventions and policies should be developed in collaboration with local stakeholders to address distal social factors that create and reinforce health disparities.

Defining the Role of Social Vulnerability in Treatment and Survival in Localized Colon Cancer: A Retrospective Cohort Study

OBJECTIVE

To determine whether variations in Social Vulnerability Index (SVI) are associated with disparities in colon cancer surgery and mortality.

SUMMARY BACKGROUND DATA

Colon cancer mortality is influenced by health care access, which is affected by individual and community-level factors. Prior studies have not used the SVI to compare surgical access and survival in localized colon cancer patients. Further, it is unclear if those above 65 years are more vulnerable to variations in SVI.

METHODS

We queried the Texas and California Cancer Registries from 2004-2017 to identify patients with localized colonic adenocarcinoma and categorized patients into <65 and ≥65 years. Our outcomes were survival and access to surgical intervention. The independent variable was census tract social vulnerability index, with higher scores indicating more social vulnerability. We used multivariable logistic regression and Cox proportional hazards for analysis.

RESULTS

We included 73,923 patients with a mean age of 68.6 years (SD 13.0), mean SVI of 47.2 (SD 27.6), and 51.1% male. After adjustment, increasing SVI was associated with reduced odds of undergoing surgery (OR 0.996; 95% CI 0.995-0.997; P < 0.0001 and increased mortality (HR 1.002; 95% CI 1.001-1.002; P < 0.0001). Patients < 65 years were more sensitive to variation in SVI.

CONCLUSIONS

Increased social vulnerability was associated with reduced odds of receiving surgery for early-stage colon cancer as well as increased mortality. These findings amplify the need for policy changes at the local, state, and federal level to address community-level vulnerability to improve access to surgical care and reduce mortality.

Scoping Review of Screening and Assessment Tools for Social Determinants of Health in the Field of Cardiovascular Disease

BACKGROUND

Despite the importance of implementing the concept of social determinants of health (SDOH) in the clinical practice of cardiovascular disease (CVD), the tools available to assess SDOH have not been systematically investigated. We conducted a scoping review for tools to assess SDOH and comprehensively evaluated how these tools could be applied in the field of CVD.

METHODS AND RESULTS

We conducted a systematic literature search of PubMed and Embase databases on July 25, 2023. Studies that evaluated an SDOH screening tool with CVD as an outcome or those that explicitly sampled or included participants based on their having CVD were eligible for inclusion. In addition, studies had to have focused on at least one SDOH domain defined by Healthy People 2030. After screening 1984 articles, 58 articles that evaluated 41 distinct screening tools were selected. Of the 58 articles, 39 (67.2%) targeted populations with CVD, whereas 16 (27.6%) evaluated CVD outcome in non-CVD populations. Three (5.2%) compared SDOH differences between CVD and non-CVD populations. Of 41 screening tools, 24 evaluated multiple SDOH domains and 17 evaluated only 1 domain.

CONCLUSIONS

Our review revealed recent interest in SDOH in the field of CVD, with many useful screening tools that can evaluate SDOH. Future studies are needed to clarify the importance of the intervention in SDOH regarding CVD.

Associations between metals and metabolomic profiles related to diabetes among adults in a rural region

INTRODUCTION

Exposure to metals is associated with increased risk of type 2 diabetes (T2D). Potential mechanisms for metals-T2D associations involve biological processes including oxidative stress and disruption of insulin-regulated glucose uptake. In this study, we assessed whether associations between metal exposure and metabolite profiles relate to biological pathways linked to T2D.

MATERIALS AND METHODS

We used data from 29 adults rural Colorado residents enrolled in the San Luis Valley Diabetes Study. Urinary concentrations of arsenic, cadmium, cobalt, lead, manganese, and tungsten were measured. Metabolic effects were evaluated using untargeted metabolic profiling, which included 61,851 metabolite signals detected in serum. We evaluated cross-sectional associations between metals and metabolites present in at least 50% of samples. Primary analyses adjusted urinary heavy metal concentrations for creatinine. Metabolite outcomes associated with each metal exposure were evaluated using pathway enrichment to investigate potential mechanisms underlying the relationship between metals and T2D.

RESULTS

Participants had a mean age of 58.5 years (standard deviation = 9.2), 48.3% were female, 48.3% identified as Hispanic/Latino, 13.8% were current smokers, and 65.5% had T2D. Of the detected metabolites, 455 were associated with at least one metal, including 42 associated with arsenic, 22 with cadmium, 10 with cobalt, 313 with lead, 66 with manganese, and two with tungsten. The metabolic features were linked to 24 pathways including linoleate metabolism, butanoate metabolism, and arginine and proline metabolism. Several of these pathways have been previously associated with T2D, and our results were similar when including only participants with T2D.

CONCLUSIONS

Our results support the hypothesis that metals exposure may be associated with biological processes related to T2D, including amino acid, co-enzyme, and sugar and fatty acid metabolism. Insight into biological pathways could influence interventions to prevent adverse health outcomes due to metal exposure.

Social vulnerability and new mobility disability among adults with polymerase chain reaction (PCR)-confirmed SARS-CoV-2: Michigan COVID-19 Recovery Surveillance Study

OBJECTIVE

Understanding the relationship between social factors and persistent COVID-19 health outcomes, such as onset of a disability after a SARS-CoV-2 (the virus that causes COVID-19) infection, is an increasingly important public health issue. The purpose of this paper is to examine associations between social vulnerability and new onset of a mobility disability post-COVID-19 diagnosis.

METHODS

We used data from the Michigan COVID-19 Recovery Surveillance Study, a population-based probability survey of adults with PCR-confirmed SARS-CoV-2 infection in Michigan between January 2020-May 2022 (n = 4295). We used the Minority Health Social Vulnerability Index (MHSVI), with high county-level social vulnerability defined at or above the 75th percentile. Mobility disability was defined as new difficulty walking or climbing stairs. We regressed mobility disability on the overall MHSVI, as well as sub-themes of the index (socioeconomic status, household composition/disability, minority and language, housing type, healthcare access, and medical vulnerability), using multivariable logistic regression, adjusting for age, race, sex, education, employment, and income.

RESULTS

Living in a county with high (vs. low) social vulnerability was associated with 1.38 times higher odds (95% confidence interval [CI]:1.18-1.61) of reporting a new mobility disability after a COVID-19 diagnosis after adjustment. Similar results were observed for the socioeconomic status and household composition/disability sub-themes. In contrast, residents of highly racially diverse counties had lower odds (odds ratio 0.74, 95% CI: 0.61, 0.89) of reporting a new mobility disability compared to low diversity counties.

CONCLUSIONS

Mitigating the effects of social vulnerabilities requires additional resources and attention to support affected individuals.

Does the Disparity Patterning Differ between Diagnosed and Undiagnosed Hypertension among Adults? Evidence from Indonesia

Background: Healthcare systems in many low- and middle-income countries (LMICs) are not yet designed to tackle the high and increasing burden of non-communicable diseases (NCDs), including hypertension. As a result, a large proportion of people with disease or risk factors are undiagnosed. Policymakers need to understand the disparity better to act. However, previous analyses on the disparity in undiagnosed hypertension, especially from LMICs, are lacking. Our study assessed the geographic and socioeconomic disparity in undiagnosed hypertension and compared it with diagnosed hypertension. Methods: We used the Basic Health Survey (Riskesdas) 2018 and performed geospatial and quantitative analyses across 514 districts in Indonesia. Dependent variables included diagnosed and undiagnosed hypertension among adults (18+ years) and by gender. Results: A high prevalence of undiagnosed hypertension at 76.3% was found, with different patterns of disparity observed between diagnosed and undiagnosed hypertension. Diagnosed hypertension was 1.87 times higher in females compared with males, while undiagnosed hypertension rates were similar between genders. Urban areas had up to 22.6% higher rates of diagnosed hypertension, while undiagnosed hypertension was 11.4% more prevalent among females in rural areas. Districts with higher education rates had up to 25% higher diagnosed hypertension rates, while districts with lower education rates had 6% higher rates of undiagnosed hypertension among females. The most developed regions had up to 76% and 40% higher prevalence of both diagnosed and undiagnosed hypertension compared with the least developed regions. Conclusion: The disparity patterning differs between diagnosed and undiagnosed hypertension among adults in Indonesia. This highlights the need for effective measures, including healthcare system reforms to tackle NCDs in LMICs.

A Longitudinal Study of Exposure to Manganese and Incidence of Metabolic Syndrome

The association between manganese (Mn) and metabolic syndrome (MetS) is unclear, and no prior study has studied this association longitudinally. The aim of this study was to assess longitudinal associations of Mn exposure with MetS and metabolic outcomes. We used data from the San Luis Valley Diabetes Study (SLVDS), a prospective cohort from rural Colorado with data collected from 1984−1998 (n = 1478). Urinary Mn was measured at baseline (range = 0.20−42.5 µg/L). We assessed the shape of the cross-sectional association between Mn and MetS accounting for effect modification by other metals at baseline using Bayesian kernel machine regression. We assessed longitudinal associations between baseline quartiles of Mn and incident MetS using Fine and Gray competing risks regression models (competing risk = mortality) and between quartiles of Mn and metabolic outcomes using linear mixed effects models. We did not observe evidence that quartiles of Mn were associated with incident MetS (p-value for trend = 0.52). Quartiles of Mn were significantly associated with lower fasting glucose (p-value for trend < 0.01). Lead was found to be a possible effect modifier of the association between Mn and incident MetS. Mn was associated with lower fasting glucose in this rural population. Our results support a possible beneficial effect of Mn on diabetic markers.