An Analysis of Social Determinants of Health and Their Implications for Hepatitis C Virus Treatment in People Who Inject Drugs: The Case of Baltimore.

Background: Sixty-eight percent of the nearly 3.5 million people living with hepatitis C virus (HCV) in the United States are people who inject drugs (PWID). Despite effective treatments, uptake remains low in PWID. We examined the social determinants of health (SDoH) that affect the HCV care cascade. Methods: We conducted a secondary analysis of data from 720 PWID in a cluster-randomized trial. We recruited PWID from 12 drug-affected areas in Baltimore. Inclusion criteria were injection in the prior month or needle sharing in the past 6 months. Intake data consisted of a survey and HCV testing. Focusing on SDoH, we analyzed self-report of (1) awareness of HCV infection (in those with active or previously cured HCV) and (2) prior HCV treatment (in the aware subgroup). We used descriptive statistics and logistic regression for statistical analyses. Results: The 342 participants were majority male and Black with a median age of 52 years. Women were more likely to be aware of their status but less likely to be treated. Having a primary care provider and HIV-positive status were associated with increased awareness and treatment. Unhoused people had 51% lower odds of HCV treatment. People who reported that other PWID had shared their HCV status with them had 2.3-fold higher odds of awareness of their own status. Conclusions: Further study of gender disparities in HCV treatment access is needed. Increased social support was associated with higher odds of HCV treatment, suggesting an area for future interventions. Strategies to identify and address SDoH are needed to end HCV.

The Association of Oncology Provider Density With Black-White Disparities in Cancer Mortality in US Counties.

BACKGROUND: Black-White racial disparities in cancer mortality are well-documented in the US. Given the estimated shortage of oncologists over the next decade, understanding how access to oncology care might influence cancer disparities is of considerable importance. We aim to examine the association between oncology provider density in a county and Black-White cancer mortality disparities. METHODS: An ecological study of 1048 US counties was performed. Oncology provider density was estimated using the 2013 National Plan and Provider Enumeration System data. Black:White cancer mortality ratio was calculated using 2014-2018 age-standardized cancer mortality rates from State Cancer Profiles. Linear regression with covariate adjustment was constructed to assess the association of provider density with (1) Black:White cancer mortality ratio, and (2) cancer mortality rates overall, and separately among Black and White persons. RESULTS: The mean Black:White cancer mortality ratio was 1.12, indicating that cancer mortality rate among Black persons was on average 12% higher than that among White persons. Oncology provider density was significantly associated with greater cancer mortality disparities: every 5 additional oncology providers per 100 000 in a county was associated with a .02 increase in the Black:White cancer mortality ratio (95% CI: .007 to .03); however, the unexpected finding may be explained by further analysis showing that the relationship between oncology provider density and cancer mortality was different by race group. Every 5 additional oncologists per 100 000 was associated with a 1.6 decrease per 100 000 in cancer mortality rates among White persons (95% CI: -3.0 to -.2), whereas oncology provider density was not associated with cancer mortality among Black persons. CONCLUSION: Greater oncology provider density was associated with significantly lower cancer mortality among White persons, but not among Black persons. Higher oncology provider density alone may not resolve cancer mortality disparities, thus attention to ensuring equitable care is critical.

Our study provides timely information to address the growing concern about the need to increase oncology supply and the impact it might have on racial disparities in cancer outcomes. This analysis of counties across the US is the first study to estimate the association of oncology provider density with Black-White racial disparities in cancer mortality. We show that having more oncology providers in a county is associated with significantly lower cancer mortality among the White population, but is not associated with cancer mortality among the Black population, thereby leading to a disparity. Our findings suggest that having more oncology providers alone may be insufficient to overcome existing disadvantages for Black patients to access and use high-quality cancer care. These findings have important implications for addressing racial disparities in cancer outcomes that are persistent and well-documented in the US.

Health Care Expenditures for Black and White US Adults Living Under Similar Conditions.

Importance: Evidence suggests that racial disparities in health outcomes disappear or diminish when Black and White adults in the US live under comparable living conditions; however, whether racial disparities in health care expenditures concomitantly disappear or diminish is unknown. Objective: To examine whether disparities in health care expenditures are minimized when Black and White US adults live in similar areas of racial composition and economic condition. Design, Setting, and Participants: This cross-sectional study used a nationally representative sample of 7062 non-Hispanic Black or White adults who live in 2238 of 2275 US census tracts with a 5% or greater Black population and who participated in the Medical Expenditure Panel Study (MEPS) in 2016. Differences in total health care expenditures and 6 specific categories of health care expenditures were assessed. Two-part regression models compared expenditures between Black and White adults living in the same Index of Concentration at the Extremes (ICE) quintile, a measure of racialized economic segregation. Estimated dollar amount differences in expenditures were calculated. All analyses were weighted to account for the complex sampling design of the MEPS. Data analysis was performed from December 1, 2019, to August 7, 2023. Exposure: Self-reported non-Hispanic Black or non-Hispanic White race. Main Outcomes and Measures: Presence and amount of patient out-of-pocket and insurance payments for annual total health care expenditures; office-based, outpatient, emergency department, inpatient hospital, or dental visits; and prescription medicines. ICE quintile 5 (Q5) reflected tracts that were mostly high income with mostly White individuals, whereas Q1 reflected tracts that were mostly low income with mostly Black individuals. Results: A total of 7062 MEPS respondents (mean [SD] age, 49 [18] years; 33.1% Black and 66.9% White; 56.1% female and 43.9% male) who lived in census tracts with a 5% or greater Black population in 2016 were studied. In Q5, Black adults had 56% reduced odds of having any health care expenditures (odds ratio, 0.44; 95% CI, 0.27-0.71) compared with White adults, at an estimated $2145 less per year, despite similar health status. Among those in Q5 with any expenditures, Black adults spent 30% less on care (cost ratio, 0.70; 95% CI, 0.56-0.86). In Q3 (most racially and economically integrated), differences in total annual health care spending were minimal ($79 annually; 95% CI, -$1187 to $1345). Conclusions and Relevance: In this cross-sectional study of Black and White adults in the US, health care expenditure disparities diminished or disappeared under conditions of both racial and economic equity and equitable health care access; in areas that were mostly high income and had mostly White residents, Black adults spent substantially less. Results underscore the continuing need to recognize place as a contributor to race-based differences in health care spending.

Handling missing data in partially clustered randomized controlled trials.

Partially clustered designs are widely used in psychological research, especially in randomized controlled trials that examine the effectiveness of prevention or intervention strategies. In a partially clustered trial, individuals are clustered into intervention groups in one or more study arms, for the purpose of intervention delivery, whereas individuals in other arms (e.g., the waitlist control arm) are unclustered. Missing data are almost inevitable in partially clustered trials and could pose a major challenge in drawing valid research conclusions. This article focuses on handling auxiliary-variable-dependent missing at random data in partially clustered studies. Five methods were compared via a simulation study, including simultaneous multiple imputation using joint modeling (MI-JM-SIM), arm-specific multiple imputation using joint modeling (MI-JM-AS), arm-specific multiple imputation using substantive-model-compatible sequential modeling (MI-SMC-AS), sequential fully Bayesian estimation using noninformative priors (SFB-NON), and sequential fully Bayesian estimation using weakly informative priors (SFB-WEAK). The results suggest that the MI-JM-AS method outperformed other methods when the variables with missing values only involved fixed effects, whereas the MI-SMC-AS method was preferred if the incomplete variables featured random effects. Applications of different methods are also illustrated using an empirical data example. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The impact of the Prime Time Sister Circles® (PTSC) on blood pressure of low-income mid-life African American women in the United States.

There is a pressing need to develop and evaluate culturally tailored, community-based interventions that address hypertension management among low-income African American women. We employed a randomized controlled trial to test the effectiveness of the Prime Time Sister Circles® Program in reducing blood pressure and body mass index among low-income African American women ages with hypertension. Study participants (N = 339) were African American women aged 40-75 years who were diagnosed with hypertension and received their primary care at government funded health centers in Washington, D.C. Compared to the usual care group, Prime Time Sister Circles® participation was associated with a reduction in systolic BP by - 2.45 (CI - 6.13, 1.23) mmHg, a reduction in diastolic BP by - 3.66 mmHg (CI - 6.32, - 0.99), and a change in BMI by - 0.26 (CI - 2.00, 1.48) from baseline to 15 months. The results suggest that culturally tailored community-based interventions can improve hypertension management in low-income women.

The Lives Lost to Inequities: Avertable Deaths From Neurologic Diseases in the Past Decade.

BACKGROUND AND OBJECTIVES: Mortality rates for neurologic diseases are increasing in the United States, with large disparities across geographical areas and populations. Racial and ethnic populations, notably the non-Hispanic (NH) Black population, experience higher mortality rates for many causes of death, but the magnitude of the disparities for neurologic diseases is unclear. The objectives of this study were to calculate mortality rates for neurologic diseases by race and ethnicity and-to place this disparity in perspective-to estimate how many US deaths would have been averted in the past decade if the NH Black population experienced the same mortality rates as other groups. METHODS: Mortality rates for deaths attributed to neurologic diseases, as defined by the International Classification of Diseases, were calculated for 2010 to 2019 using death and population data obtained from the Centers for Disease Control and Prevention and the US Census Bureau. Avertable deaths were calculated by indirect standardization: For each calendar year of the decade, age-specific death rates of NH White persons in 10 age groups were multiplied by the NH Black population in each age group. A secondary analysis used Hispanic and NH Asian populations as the reference groups. RESULTS: In 2013, overall age-adjusted mortality rates for neurologic diseases began increasing, with the NH Black population experiencing higher rates than NH White, NH American Indian and Alaska Native, Hispanic, and NH Asian populations (in decreasing order). Other populations with higher mortality rates for neurologic diseases included older adults, the male population, and adults older than 25 years without a high school diploma. The gap in mortality rates for neurologic diseases between the NH Black and NH White populations widened from 4.2 individuals per 100,000 in 2011 to 7.0 per 100,000 in 2019. Over 2010 to 2019, had the NH Black population experienced the neurologic mortality rates of NH White, Hispanic, or NH Asian populations, 29,986, 88,407, or 117,519 deaths, respectively, would have been averted. DISCUSSION: Death rates for neurologic diseases are increasing. Disproportionately higher neurologic mortality rates in the NH Black population are responsible for a large number of excess deaths, making research and policy efforts to address the systemic causes increasingly urgent.

Evaluating the Impact of the Prime Time Sister Circles® Intervention on Reducing Depressive Symptoms Among African American Women with Uncontrolled Hypertension.

BACKGROUND: The Prime Time Sister Circles®, a randomized controlled trial (PTSC-RCT), assessed the impact of a community-based peer support program on hypertension management among African American women 40-75 years of age. While the PTSC-RCT was designed to evaluate changes in blood pressure control, subsequent sub-analyses revealed a high proportion of self-reported depressive symptoms in our sample. Accordingly, we conducted an ancillary investigation of the PTSC intervention on depression to ascertain its impact on reduced depressive symptoms in the study population. METHOD: Depressive symptoms were measured using an adapted version of the Center for Epidemiologic Studies Depression Scale Revised (CES-D-10). We used unadjusted and adjusted fixed effect models. Data for this study came from the PTSC-RCT. We collected data between 2017 and 2018 in Washington, DC. We used a balanced analytical sample of 172 African American, English-speaking women between 40 to 75 years old with uncontrolled hypertension. INTERVENTION: The intervention group participated in a 2-h, peer-based support group once a week for 13 weeks. A trained PTSC facilitator facilitated sessions with experts who delivered content on various topics, including psychosocial wellness (e.g., stress, depressive symptoms, anxiety management, and self-esteem), physical health (e.g., hypertension, inflammation, and heart disease), physical activity, and healthy nutrition. RESULTS: Results from the fixed-effects models indicated that participants in the PTSC program exhibited a greater reduction in CES-D-10 score at three months (Coeff: -1.99, 95% CI: -3.49, -0.49) and at 15 months (Coeff: -2.38, 95% CI: -3.94, -0.83), as compared to those in the control group. CONCLUSIONS: Evidence suggests that the Prime Time Sister Circles® intervention reduced depressive symptoms among African American women with low socioeconomic status and hypertension. TRIAL REGISTRATION: NCT04371614.

The Economic Burden of Racial, Ethnic, and Educational Health Inequities in the US.

Importance: Health inequities exist for racial and ethnic minorities and persons with lower educational attainment due to differential exposure to economic, social, structural, and environmental health risks and limited access to health care. Objective: To estimate the economic burden of health inequities for racial and ethnic minority populations (American Indian and Alaska Native, Asian, Black, Latino, and Native Hawaiian and Other Pacific Islander) and adults 25 years and older with less than a 4-year college degree in the US. Outcomes include the sum of excess medical care expenditures, lost labor market productivity, and the value of excess premature death (younger than 78 years) by race and ethnicity and the highest level of educational attainment compared with health equity goals. Evidence Review: Analysis of 2016-2019 data from the Medical Expenditure Panel Survey (MEPS) and state-level Behavioral Risk Factor Surveillance System (BRFSS) and 2016-2018 mortality data from the National Vital Statistics System and 2018 IPUMS American Community Survey. There were 87 855 survey respondents to MEPS, 1 792 023 survey respondents to the BRFSS, and 8 416 203 death records from the National Vital Statistics System. Findings: In 2018, the estimated economic burden of racial and ethnic health inequities was $421 billion (using MEPS) or $451 billion (using BRFSS data) and the estimated burden of education-related health inequities was $940 billion (using MEPS) or $978 billion (using BRFSS). Most of the economic burden was attributable to the poor health of the Black population; however, the burden attributable to American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander populations was disproportionately greater than their share of the population. Most of the education-related economic burden was incurred by adults with a high school diploma or General Educational Development equivalency credential. However, adults with less than a high school diploma accounted for a disproportionate share of the burden. Although they make up only 9% of the population, they bore 26% of the costs. Conclusions and Relevance: The economic burden of racial and ethnic and educational health inequities is unacceptably high. Federal, state, and local policy makers should continue to invest resources to develop research, policies, and practices to eliminate health inequities in the US.

Using Community Health Workers to Address Barriers to Participation and Retention in Diabetes Prevention Program: A Concept Paper.

OBJECTIVE: The PreventionLink of Southern Maryland is a 5-year project to eliminate barriers to participation and retention in the National Diabetes Prevention Program (DPP) lifestyle change program to prevent or delay the onset of type 2 diabetes in adults with prediabetes. This is the study to identify the obstacles to participation and retention in the DPP lifestyle change program among high burden populations and learn how CHWs have reduced the identified barriers to participation and retention for high burden populations. METHODS: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to conduct this literature review. We have used the Scopus and PubMed, including all types of studies and peer-reviewed documents published in English between 2010 and 2020. RESULTS: From 131 identified articles, 18 articles were selected for qualitative synthesis. The reviewed literature documented following as main barriers to participate in a DPP lifestyle change program: time, cost, lack of transportation, cost of transportation, commute distance, technology access, access to facilities and community programs, caregiver responsibilities, lack of health literacy and awareness, and language. CHWs can address these barriers to participation and retention, they were involved in educating and supporting roles; they worked as bridges between healthcare providers and participants and as intervention team members. CONCLUSIONS: Diabetes prevention program participants with social determinant risk factors who most need CHW services are unlikely to have financial resources to pay for CHW services out-of-pocket. Hence, the public and private health plans that pay for their prediabetes care should consider paying for these CHW services and there is a need to trust more to CHW and have them as a "community health teams" member.

Blood Pressure and Later-Life Cognition in Hispanic and White Adults (BP-COG): A Pooled Cohort Analysis of ARIC, CARDIA, CHS, FOS, MESA, and NOMAS.

BACKGROUND: Ethnic differences in cognitive decline have been reported. Whether they can be explained by differences in systolic blood pressure (SBP) is uncertain. OBJECTIVE: Determine whether cumulative mean SBP levels explain differences in cognitive decline between Hispanic and White individuals. METHODS: Pooled cohort study of individual participant data from six cohorts (1971-2017). The present study reports results on SBP and cognition among Hispanic and White individuals. Outcomes were changes in global cognition (GC) (primary), executive function (EF) (secondary), and memory standardized as t-scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1 SD difference in cognition. Median follow-up was 7.7 (Q1-Q3, 5.2-20.1) years. RESULTS: We included 24,570 participants free of stroke and dementia: 2,475 Hispanic individuals (median age, cumulative mean SBP at first cognitive assessment, 67 years, 132.5 mmHg; 40.8% men) and 22,095 White individuals (60 years,134 mmHg; 47.3% men). Hispanic individuals had slower declines in GC, EF, and memory than White individuals when all six cohorts were examined. Two cohorts recruited Hispanic individuals by design. In a sensitivity analysis, Hispanic individuals in these cohorts had faster decline in GC, similar decline in EF, and slower decline in memory than White individuals. Higher time-varying cumulative mean SBP was associated with faster declines in GC, EF, and memory in all analyses. After adjusting for time-varying cumulative mean SBP, differences in cognitive slopes between Hispanic and White individuals did not change. CONCLUSION: We found no evidence that cumulative mean SBP differences explained differences in cognitive decline between Hispanic and White individuals.

How Income Inequality and Race Concentrate Depression in Low-Income Women in the US; 2005-2016.

Aim: To estimate the association between income and depressive symptoms in adult women, ages 20 years and older. Methods: Data for this study came from the 2005-2016 National Health and Nutrition Examination Survey (NHANES). We measured the presence of depressive symptoms by using a 9-item PHQ (Public Health Questionnaire, PHQ-9) and the Poverty to Income Ratio (PIR) as a proxy for income. We employed Negative Binomial Regression (NBRG) and logistic regression models in a sample of 11,420 women. We adjusted models by age, racial/ethnic groups, marital status, education, health insurance, comorbidity, and utilization of mental health professionals. We calculated the Gini Coefficient (GC) as a measure of income inequality, using PIR. Results: Between 2005 and 2016, 20.1% of low-PIR women suffered from depression (PHQ ≥10) compared with 12.0% of women in medium-PIR and 5.0% in high-PIR. The highest probabilities of being depressed were in Black Non-Hispanics (BNH) and Hispanics (12.0%), and then in White NH (WNH; 9.1%). The results of NBRG have shown that women in medium-PIR (0.90 [CI: 0.84-0.97]) and high-PIR 0.76 (CI: 0.70-0.82) had a lower incidence-rate ratio than women in low-PIR. The logistic regression results showed that income is protective in High-PIR groups (OR = 0.56, CI [0.43-0.73]). Conclusion: Policies to treat depression should prioritize the needs of low-income women of all racial groups and women.

How place and race drive the numbers of fatal police shootings in the US: 2015-2020.

Place and race are two important predictors of fatal police shootings. We used Mapping Police Violence Data and the Washington Post Fatal Force Data to determine whether a county's deprivation status within communities influences the association between the number of fatal police shootings, and how the number of fatal police shootings differs by race and ethnicity. We categorized counties based on the Social Vulnerability Index (SVI) to three categories: low-, medium-, and high-SVI. The analytical sample included 3136 US counties between 2015 and 2020; during this time, 5525 individuals were fatally shot by police. Our findings show that place strongly impacts the number of fatal police shootings. Among all fatal shootings, 713 occurred in low-SVI counties, 1660 in middle-SVI, and 3152 in high-SVI counties. Race played a significant role; fatal shooting deaths increased by 2.3 times among White individuals, 9.6 times among Black individuals, and 15 times among Hispanic individuals between low- and high-SVI counties. The results of negative binomial regressions show a strong association between fatal police shootings and the counties' characteristics. In comparison with low-SVI counties, residents in counties with moderate and high-SVI are more likely to be fatally shot by police by 4.9 and 5.8 percentage points. In addressing violence and fatal police shootings, the vulnerability of counties and the population's racial composition play significant roles and need specific attention in addressing systemic racial disparities in the criminal justice system.

A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models.

OBJECTIVE: Health care providers increasingly rely upon predictive algorithms when making important treatment decisions, however, evidence indicates that these tools can lead to inequitable outcomes across racial and socio-economic groups. In this study, we introduce a bias evaluation checklist that allows model developers and health care providers a means to systematically appraise a model's potential to introduce bias. MATERIALS AND METHODS: Our methods include developing a bias evaluation checklist, a scoping literature review to identify 30-day hospital readmission prediction models, and assessing the selected models using the checklist. RESULTS: We selected 4 models for evaluation: LACE, HOSPITAL, Johns Hopkins ACG, and HATRIX. Our assessment identified critical ways in which these algorithms can perpetuate health care inequalities. We found that LACE and HOSPITAL have the greatest potential for introducing bias, Johns Hopkins ACG has the most areas of uncertainty, and HATRIX has the fewest causes for concern. DISCUSSION: Our approach gives model developers and health care providers a practical and systematic method for evaluating bias in predictive models. Traditional bias identification methods do not elucidate sources of bias and are thus insufficient for mitigation efforts. With our checklist, bias can be addressed and eliminated before a model is fully developed or deployed. CONCLUSION: The potential for algorithms to perpetuate biased outcomes is not isolated to readmission prediction models; rather, we believe our results have implications for predictive models across health care. We offer a systematic method for evaluating potential bias with sufficient flexibility to be utilized across models and applications.

Value of Triage Treatment Strategies to Distribute Hepatitis C Direct-Acting Antiviral Agents in an Integrated Healthcare System: A Cost-Effectiveness Analysis.

OBJECTIVES: This study aimed to assess the cost-effectiveness of fibrosis-based direct-acting antiviral treatment policies for patients with chronic hepatitis C virus at the Kaiser Permanente Mid-Atlantic States health system. METHODS: We used a Markov model to compare the lifetime costs and effects of treating patients with chronic hepatitis C virus at different stages of disease severity, or all stages simultaneously, based on a fibrosis score from the US healthcare sector perspective and societal perspective. The initial distribution of patients across fibrosis scores, the effectiveness of direct-acting antiviral therapy, and follow-up and monitoring protocols were specific to the Kaiser Permanente Mid-Atlantic States health system. Direct and indirect costs, transition probabilities, and utilities were derived from the literature. Deterministic and probabilistic sensitivity analyses were performed to assess the robustness of our results. RESULTS: The "Treat All" option was dominant from both the societal and healthcare sector perspectives. The conclusion was robust in deterministic sensitivity analysis. The range of incremental costs between the less restrictive policies was small-the difference between the "Treat F1+" and the "Treat All" option was only $111 per person. Probabilistic sensitivity analyses showed, at both the $100 000/quality-adjusted life-year and $150 000/quality-adjusted life-year thresholds, there was a 70% chance that the "Treat All" option was more cost-effective than the "Treat F1+" option. CONCLUSIONS: We found that expanded treatment access is cost-effective and, in many cases, cost saving. Although our results are primarily applicable to a regional integrated healthcare system, it offers some direction to any healthcare setting faced with resource constraints in the face of highly priced drugs.

How Income Inequality and Race/Ethnicity Drive Obesity in U.S. Adults: 1999-2016.

Obesity is a major public health problem both globally and within the U.S. It varies by multiple factors, including but not limited to income and sex. After controlling for potential covariates, there is little evidence to determine the association between income and obesity and how obesity may be moderated by sex and family income. We examined the association between income and obesity in U.S. adults aged 20 years and older, and tested whether this relationship differs by race or ethnicity groups. For this analysis, we used data from the 1999-2016 National Health and Nutrition Examination Surveys (NHANES). Obesity was determined using Body Mass Index ≥ 30 kg/m2; the Gini coefficient (GC) was calculated to measure income inequality using the Poverty Income Ratio (PIR). We categorized the PIR into five quintiles to examine the relationship between income inequality and obesity. For the first set of analyses, we used a modified Poisson regression in a sample of 36,665 adults, with an almost equal number of men and women (women's ratio was 50.6%), including 17,303 white non-Hispanics (WNH), 7475 black non-Hispanics (BNHs), and 6281 Mexican Americans. The models included age, racial/ethnic groups, marital status, education, health behaviors (smoking and drinking status and physical activities), health insurance coverage, self-reported health, and household structure (live alone and size of household). Adjusting for potential confounders, our findings showed that the association between PIR and obesity was positive and significant more frequently among WNH and BNH in middle and top PIR quintiles than among lower-PIR quintiles; this association was not significant in Mexican Americans (MAs). Results of GC in obese women showed that in comparison with WNHs (GC: 0.34, S.E.: 0.002), BNHs (GC: 0.38, S.E.: 0.004) and MAs (GC: 0.41, S.E.: 0.006) experienced higher income inequality, and that BNH obese men experienced the highest income inequality (GC: 0.45, S.E.: 0.011). The association between PIR and obesity was significant among WNHs and BNHs men in the 3rd, 4th and 5th PIR quintiles. The same association was not found for women. In treating obesity, policymakers should consider not only race/ethnicity and sex, but also strategies to reduce inequality in income.

Internet Access, Social Risk Factors, and Web-Based Social Support Seeking Behavior: Assessing Correlates of the "Digital Divide" Across Neighborhoods in The State of Maryland.

We aimed to empirically measure the degree to which there is a "digital divide" in terms of access to the internet at the small-area community level within the State of Maryland and the City of Baltimore and to assess the relationship and association of this divide with community-level SDOH risk factors, community-based social service agency location, and web-mediated support service seeking behavior. To assess the socio-economic characteristics of the neighborhoods across the state, we calculated the Area Deprivation Index (ADI) using the U.S. Census, American Community Survey (5-year estimates) of 2017. To assess the digital divide, at the community level, we used the Federal Communications Commission (FCC) data on the number of residential fixed Internet access service connections. We assessed the availability of and web-based access to community-based social service agencies using data provided by the "Aunt Bertha" information platform. We performed community and regional level descriptive and special analyses for ADI social risk factors, connectivity, and both the availability of and web-based searches for community-based social services. To help assess potential neighborhood linked factors associated with the rates of web-based social services searches by individuals in need, we applied logistic regression using generalized estimating equation modeling. Baltimore City contained more disadvantaged neighborhoods compared to other areas in Maryland. In Baltimore City, 20.3% of neighborhoods (defined by census block groups) were disadvantaged with ADI at the 90th percentile while only 6.6% of block groups across Maryland were in this disadvantaged category. Across the State, more than half of all census tracts had 801-1000 households (per 1000 households) with internet subscription. In contrast, in Baltimore City about half of all census tracts had only 401-600 of the households (per 1000 households) with internet subscriptions. Most block groups in Maryland and Baltimore City lacked access to social services facilities (61% of block groups at the 90th percentile of disadvantage in Maryland and 61.3% of block groups at the 90th percentile of disadvantage in Baltimore City). After adjusting for other variables, a 1% increase in the ADI measure of social disadvantage, resulting in a 1.7% increase in the number of individuals seeking social services. While more work is needed, our findings support the premise that the digital divide is closely associated with other SDOH factors. The policymakers must propose policies to address the digital divide on a national level and also in disadvantaged communities experiencing the digital divide in addition to other SDOH challenges.

Supplemental nutrition assistance program 2009 expansion and cardiometabolic markers among low-income adults.

A 2009 Supplemental Nutrition Assistance Program (SNAP) policy change that expanded eligibility and increased benefit amounts has been associated with reduced food insecurity. This study tests the hypothesis that the SNAP policy change corresponds with improved stress- and nutrition-sensitive cardiometabolic markers. This study included non-pregnant participants aged 18-59 with annual family incomes ≤185% of the federal poverty guideline from the repeated cross-sectional NHANES study. Those living in SNAP eligible households (income ≤130% of the poverty guideline) were compared to those who were likely non-eligible (income 131%-≤185%). Difference-in-differences analyses compared hemoglobin A1c (%), CRP (mg/dL), total cholesterol (mg/dL), LDL (mg/dL) and waist circumference (cm) across groups before (2007-2008) and after (2009-2010) the SNAP policy change. Sampling weights were applied. Adjusting for demographic, socioeconomic, household and health factors, there were statistically significant difference-in-differences estimates for hemoglobin A1c (p = 0.003, n = 3723) and total cholesterol (p = 0.028, n = 3710). SNAP eligible adults had no difference in hemoglobin A1c after the policy change and, among those less than 40 years of age, 5 mg/dL lower total cholesterol levels whereas likely non-SNAP eligible adults had 0.14% higher hemoglobin A1c and no difference in total cholesterol after the policy change. The 2009 SNAP expansion was associated with improved nutrition-sensitive cardiometabolic markers in SNAP-eligible adults. This study found less of an upward trend in hemoglobin A1c levels for young and middle aged adults and decreased total cholesterol for young adults. These results highlight the potential role of SNAP to prevent costly chronic conditions among low-income U.S. adults.

Race, ethnicity, poverty and the social determinants of the coronavirus divide: U.S. county-level disparities and risk factors.

BACKGROUND: Communities with more Black or Hispanic residents have higher coronavirus rates than communities with more White residents, but relevant community characteristics are underexplored. The purpose of this study was to investigate poverty-, race- and ethnic-based disparities and associated economic, housing, transit, population health and health care characteristics. METHODS: Six-month cumulative coronavirus incidence and mortality were examined using adjusted negative binomial models among all U.S. counties (n = 3142). County-level independent variables included percentages in poverty and within racial/ethnic groups (Black, Hispanic, Native American, Asian), and rates of unemployment, lacking a high school diploma, housing cost burden, single parent households, limited English proficiency, diabetes, obesity, smoking, uninsured, preventable hospitalizations, primary care physicians, hospitals, ICU beds and households that were crowded, in multi-unit buildings or without a vehicle. RESULTS: Counties with higher percentages of Black (IRR = 1.03, 95% CI: 1.02-1.03) or Hispanic (IRR = 1.02, 95% CI: 1.01-1.03) residents had more coronavirus cases. Counties with higher percentages of Black (IRR = 1.02, 95% CI: 1.02-1.03) or Native American (IRR = 1.02, 95% CI: 1.01-1.04) residents had more deaths. Higher rates of lacking a high school diploma was associated with higher counts of cases (IRR = 1.03, 95% CI: 1.01-1.05) and deaths (IRR = 1.04, 95% CI: 1.01-1.07). Higher percentages of multi-unit households were associated with higher (IRR = 1.02, 95% CI: 1.01-1.04) and unemployment with lower (IRR = 0.96, 95% CI: 0.94-0.98) incidence. Higher percentages of individuals with limited English proficiency (IRR = 1.09, 95% CI: 1.04-1.14) and households without a vehicle (IRR = 1.04, 95% CI: 1.01-1.07) were associated with more deaths. CONCLUSIONS: These results document differential pandemic impact in counties with more residents who are Black, Hispanic or Native American, highlighting the roles of residential racial segregation and other forms of discrimination. Factors including economic opportunities, occupational risk, public transit and housing conditions should be addressed in pandemic-related public health strategies to mitigate disparities across counties for the current pandemic and future population health events.