Place Matters

Background Structural racism is an upstream influencer of social determinants of health, which impact cardiovascular disease (CVD) death rates. The association between structural racism and CVD death rates has not been conclusively quantified, and this association may vary by race/ethnicity. Method Year 2020 census data on disparities in income, wealth, education, employment, and digital access and segregation were available at the census block group level and were used to quantify structural racism’s effects. Data from each block group and its 9 nearest neighbors were used to compute the structural racism sub-scores for that block group, which were transformed to a scale of 1-100 based on 100 quantiles. The composite score was then calculated as the weighted sum of the sub-scores (weights in Table 1). Mean structural racism score (SRS), weighted by population of each block group, was computed for each county in the United States. Then SRS was fit as the exposure in linear models controlling for state and predicting 2020 county-level CVD death rates per 100,000 adults for all residents, non-Hispanic Black (NHB) residents, non-Hispanic White (NHW) residents, and Hispanic residents, as reported by the Centers for Disease Control. Results: Data from 50 states and the District of Columbia were used (3137 counties). A 1-point higher SRS score (range 1-100) was associated with 1.0 (95% CI: 0.8, 1.3) more CVD deaths per 100,000 adults. Among NHB residents, there were 1.5 (95% CI: 1.0, 2.0) more CVD deaths per 1-point higher SRS score. Among Hispanic and NHW residents, CVD deaths were 0.8 (95% CI: 0.4, 1.2) and 0.6 (95% CI: 0.3, 0.8) higher per 1-point higher SRS. Conclusion: Structural racism is associated with greater CVD mortality among all United States residents, but the magnitude of association is greatest among NHB residents. Eliminating structural racism is likely to reduce CVD mortality of all residents while reducing race-based disparities in CVD mortality.

Social determinants of health and coronavirus disease 2019 in pregnancy

Understanding the current burden of coronavirus disease 2019 (COVID-19) deaths in vulnerable populations will help inform efforts by policymakers to address disparities in COVID-19 outcomes. The objective of this study was to examine the association between COVID-19 deaths and the county-level proportions of non-Hispanic Black and Hispanic residents. A retrospective study using COVID-19 mortality data from USA Facts linked to data from the US Census Bureau, the Health Resources & Services Administration Area Health Resources file, and the US Census Bureau. Negative binomial regression was used to estimate the association between the total county COVID-19 deaths during consecutive 30-day intervals and the proportion of non-Hispanic Blacks and Hispanic residents after adjusting for resident demographics, comorbidity burden, rurality, social determinants of health, and health care resources. In April, counties (n=179) with >40% Blacks had 6-fold higher death rates than counties (n=1521) with <2% Blacks [incident rate ratio (IRR)=6.58, 95% confidence interval (CI): 3.29-13.2, P<0.001]. These counties had higher death rates until October, but were no different than referent counties in November. In April, death rates in counties with >40% Hispanic residents were similar to death rates in counties with <2% Hispanic residents. Death rates in these counties peaked in August (IRR=3.14, 95% CI: 1.69-5.82, P<0.001) but were also no different than referent counties in November. These effects were robust after adjusting for county-level characteristics. Before August, death rates differed little by insurance status, but since then, counties with >15% uninsurance rates had up to 2-fold higher mortality rates (IRR=1.97, 95% CI: 1.19-3.27, P<0.001) than counties with <5% uninsurance rates. Counties with high concentrations of non-Hispanic Blacks were disproportionately affected by COVID-19 throughout most of the pandemic, but other social determinants of health such as health insurance are now playing a more prominent role than race and ethnicity.

HIV disproportionately affects Hispanic/Latino people in the United States, and factors other than individual attributes may be contributing to these differences. We examined differences in the distribution of HIV diagnosis and social determinants of health (SDH) among US-born and non-US-born Hispanic/Latino adults in the United States and Puerto Rico. We used data reported to the Centers for Disease Control and Prevention's National HIV Surveillance System (NHSS) to determine US census tract-level HIV diagnosis rates and percentages among US-born and non-US-born Hispanic/Latino adults aged ≥18 for 2017. We merged data from the US Census Bureau's American Community Survey with NHSS data to examine regional differences in federal poverty level, education, median household income, employment, and health insurance coverage among 8648 US-born (n = 3328) and non-US-born (n = 5320) Hispanic/Latino adults. A comparison of US-born and non-US-born men by region showed similar distributions of HIV diagnoses. The largest percentages occurred in census tracts where ≥19% of residents lived below the federal poverty level, ≥18% did not finish high school, the median household income was <$40 000 per year, ≥6% were unemployed, and ≥16% did not have health insurance. A comparison of US-born and non-US-born women by region showed similar distributions. The findings of higher numbers of HIV diagnoses among non-US-born Hispanic/Latino adults than among US-born Hispanic/Latino adults, regional similarities in patterns of SDH and HIV percentages and rates, and Hispanic/Latino adults faring poorly in each SDH category are important for understanding SDH barriers that may be affecting Hispanic/Latino adults with HIV in the United States.

Social determinants of health (SDoH), such as financial resources and housing stability, account for between 30% and 55% of people's health outcomes. While many studies have identified strong associations between specific SDoH and health outcomes, little is known about how SDoH co-occur to form subtypes critical for designing targeted interventions. Such analysis has only now become possible through the All of Us program. This study aims to analyze the All of Us dataset for addressing two research questions: (1) What are the range of and responses to survey questions related to SDoH? and (2) How do SDoH co-occur to form subtypes, and what are their risks for adverse health outcomes? For question 1, an expert panel analyzed the range of and responses to SDoH questions across 6 surveys in the full All of Us dataset (N=372,397; version 6). For question 2, due to systematic missingness and uneven granularity of questions across the surveys, we selected all participants with valid and complete SDoH data and used inverse probability weighting to adjust their imbalance in demographics. Next, an expert panel grouped the SDoH questions into SDoH factors to enable more consistent granularity. To identify the subtypes, we used bipartite modularity maximization for identifying SDoH biclusters and measured their significance and replicability. Next, we measured their association with 3 outcomes (depression, delayed medical care, and emergency room visits in the last year). Finally, the expert panel inferred the subtype labels, potential mechanisms, and targeted interventions. The question 1 analysis identified 110 SDoH questions across 4 surveys covering all 5 domains in Healthy People 2030. As the SDoH questions varied in granularity, they were categorized by an expert panel into 18 SDoH factors. The question 2 analysis (n=12,913; d=18) identified 4 biclusters with significant biclusteredness (Q=0.13; random-Q=0.11; z=7.5; P<.001) and significant replication (real Rand index=0.88; random Rand index=0.62; P<.001). Each subtype had significant associations with specific outcomes and had meaningful interpretations and potential targeted interventions. For example, the Socioeconomic barriers subtype included 6 SDoH factors (eg, not employed and food insecurity) and had a significantly higher odds ratio (4.2, 95% CI 3.5-5.1; P<.001) for depression when compared to other subtypes. The expert panel inferred implications of the results for designing interventions and health care policies based on SDoH subtypes. This study identified SDoH subtypes that had statistically significant biclusteredness and replicability, each of which had significant associations with specific adverse health outcomes and with translational implications for targeted SDoH interventions and health care policies. However, the high degree of systematic missingness requires repeating the analysis as the data become more complete by using our generalizable and scalable machine learning code available on the All of Us workbench.

e13559 Background: Social determinants of health (SDOH) are both drivers of health disparities and barriers to clinical research participation, particularly among historically underserved or marginalized populations. Using real-world data (RWD), diversity plans in cancer clinical trials frequently aim to reduce disparities and improve representation. Our aim was to describe the representativeness of patients with advanced non-small cell lung cancer (aNSCLC) with respect to race, ethnicity and person-level SDOH in a curated electronic health record (EHR) database. Methods: This was a retrospective cohort study of individuals diagnosed with aNSCLC between 2016–2022 in a US-based oncology EHR database (ConcertAI). Information on person-level SDOH was derived from linkage of curated EHR data to administrative claims and consumer financial data. These data were also compared to a sample of patients diagnosed with first primary NSCLC from the Surveillance, Epidemiology, and End Results (SEER) Program and American Community Survey (ACS), where possible. The Kaplan-Meier product limit estimator was used to compare time from advanced diagnosis to treatment initiation. Results: From an overall sample of 17,772 patients with aNSCLC, a total of 10,390 patients had 1 or more SDOH characteristics of interest documented. Compared with patients without linked SDOH data, a higher proportion of patients with linked person-level SDOH data were non-Hispanic (NH) White patients (79% vs 71%) and lower proportions were NH Black (10% vs 13%), NH Asian/Pacific Islander (2% vs 4%) and Hispanic patients (2% vs 4%). Patients with linked SDOH were also more likely to have aNSCLC progressed from an earlier stage and received biomarker testing for targetable alterations. Overall, 54% of patients were married, 38% completed a bachelor’s degree or higher, 14% worked in a blue-collar occupation, and 61% had an individual income of ≤$35,000. All 4 of these SDOH characteristics differed significantly by race/ethnicity. Differences in time-to-treatment initiation were statistically significant by marital status (median of 50 [married] vs 55 [not married] days; P=0.02) and individual income (median of 50 [&gt;$60,000] vs 55 [≤$30,000] days; P=0.04). Patients with aNSCLC in these data differed from patients in SEER and ACS estimates with respect to greater representation of patients who are NH White, have lower levels of education, and lower individual income. Conclusions: This analysis demonstrated the feasibility of measuring person-level SDOH using EHR from patients with aNSCLC treated at oncology clinics across the US. RWD with linked SDOH characteristics should be used cautiously to address the representativeness gap in evidence from oncology trials given their potential inherent selection biases.

Background: Social determinants of health are important contributors to maternal and child health outcomes. Limited existing research examines the relationship between housing instability during pregnancy and perinatal care utilization. Our objective was to evaluate whether antenatal housing instability is associated with differences in perinatal care utilization and outcomes. Materials and Methods: Participants who were surveyed during their postpartum hospitalization were considered to have experienced housing instability if they answered affirmatively to at least one of six screening items. The primary outcome was adequacy of prenatal care measured by the Adequacy of Prenatal Care Utilization index. Maternal, neonatal, and postpartum outcomes, including utilization and breastfeeding, were also collected as secondary outcomes. Multivariable logistic regression models were adjusted for sociodemographic and clinical covariates. Results: In this cohort (N = 490), 11.2% (N = 55) experienced housing instability during pregnancy. Participants with unstable housing were more likely to have inadequate prenatal care (17.3% vs. 3.9%; odds ratio [OR] 5.11, 95% confidence interval [CI] 2.15-12.14, p < 0.001), but findings were not significant after adjustment (aOR 1.72, 95% CI 0.55-5.41, p = 0.35). Similarly, postpartum visit attendance was lower for individuals with unstable housing (79.6% vs. 91.2%), but there was no difference in the odds of the postpartum visit attendance after adjustment (OR 0.69, 95% CI 0.29-1.66, p = 0.14). Conclusions: There were no statistically significant association with the maternal, neonatal, and other postpartum secondary outcomes. Housing instability appears to be a risk marker that is related to other social determinants of health. Given the range of housing instability experiences, future research must account for specific types and degrees of housing instability and their potential perinatal consequences.

Background: Diabetes is a major health burden in Mexican American populations, especially among those in the Lower Rio Grande Valley (LRGV) in the border region of Texas. Understanding the roles that social determinants of health (SDOH) play in diabetes management programs, both at the individual and community level, may inform future intervention strategies.Methods: This study performed a secondary data analysis on 1,568 individuals who participated in Salud y Vida (SyV), a local diabetes and chronic disease management program, between October 2013 and September 2018 recruited from a local clinic. The primary outcome was the reduction of hemoglobin A1C (HbA1C) at the last follow-up visit compared to the baseline. In addition to age, gender, insurance status, education level and marital status, we also investigated 15 community (census tract) SDOH using the American Community Survey. Because of the high correlation in the community SDOH, we developed the community-level indices representing different domains. Using Bayesian multilevel spatial models that account for the geographic dependency, we were able to simultaneously investigate the individual- and community-level SDOH that may impact HbA1C reduction.Results: After accounting for the diabetes self-management education classes taken by the participants and their length of stay in the program, we found that older age at baseline, being married (compared to being widowed or divorced) and English speaking (compared to Spanish) were significantly associated with greater HbA1C reduction. Moreover, we found that the community level SDOH were also highly associated with HbA1C reduction. With every percentile rank decrease in the socioeconomic advantage index, we estimated an additional 0.018% reduction in HbA1C [95% CI (−0.028, −0.007)]. Besides the socioeconomic advantage index, urban core opportunity and immigrant's cohesion and accessibility indices were also statistically associated with HbA1C reduction.Conclusion: To our knowledge, our study is the first to utilize Bayesian multilevel spatial models and simultaneously investigate both individual- and community-level SDOH in the context of diabetes management. Our findings suggest that community SDOH play an important role in diabetes control and management, and the need to consider community and neighborhood context in future interventions programs to maximize their overall effectiveness.

Utilizing social determinants of health to identify most vulnerable neighborhoods–Latent class analysis and GIS map

This paper primarily aims to construct a conceptual model of social determinants of health (SDoH), which will serve as a vital tool for identifying the feedback mechanisms that influence population health outcomes. Additionally, it seeks to simulate both the immediate and long-term effectiveness of proposed SDoH interventions on population health. We developed a system dynamics model of SDoH based on literature review and insights from community health experts. This model enables us to simulate the effectiveness of proposed interventions on population health, using CVD as a representative example of health outcomes. The model results highlight a promising approach for enhancing population health. The neighborhood intervention stands out among the various interventions, demonstrating the most significant impact on health compared to other individual interventions. This finding underscores the potential of neighborhood-focused strategies in improving overall population health. This paper provides a clear explanation and causal framework for why investing in programs that enhance SDoH can improve population health. It introduces a powerful tool such as a causal map of SDoH, enabling policymakers and stakeholders to gain a more profound, dynamic understanding of the relationship between SDoH and health outcomes. This knowledge may help to make informed decisions and implement effective interventions.

Social Determinants of Health (SDOH) are conditions that influence health outcomes. SDOHs are screened and addressed in many clinics and hospitals to reduce patients' social needs. Research indicates how unaddressed SDOH can negatively impact chronic illness, along with the daily life of pediatric patients. SDOH's role in pediatric patients includes food security, housing stability, access to healthcare, caregiver education, and parental mental health. Previous research has addressed these factors; however, the lack of staff education prevents effective compliance and follow-up on SDOH screening. Challenges remain in implementing and integrating SDOH into routine well-child visits. This scoping review will evaluate and assess the effectiveness of staff education on SDOH and its effect on the compliance of SDOH screenings for subsequent well-child visits.

To characterize the barriers and opportunities associated with racial and ethnic disparities in blood pressure (BP) control. Blood pressure (BP) control rates in the USA have worsened over the last decade, with significantly lower rates of control among people from racial and ethnic minority groups, with non-Hispanic (NH) Black persons having 10% lower control rates compared to NH White counterparts. Many factors contribute to BP control including key social determinants of health (SDoH) such as health literacy, socioeconomic status, and access to healthcare as well as low awareness rates and dietary habits. Numerous pharmacologic and non-pharmacologic interventions have been developed to reduce racial and ethnic disparities in BP control. Among these, dietary programs designed to help reduce salt intake, faith-based interventions, and community-based programs have found success in achieving better BP control among people from racial and ethnic minority groups. Disparities in the prevalence and management of hypertension persist and remain high, particularly among racial and ethnic minority populations. Ongoing efforts are needed to address SDoH along with the unique genetic, social, economic, and cultural diversity within these groups that contribute to ongoing BP management inequalities.

This article provides information on the benefits of the American Community Survey (ACS). The ACS is slotted to replace the decennial census long form by collecting essentially the same information throughout the decade rather than once every 10 years. With updated information researchers will be able to track changes over time and measure relative differences among population groups and areas. The basic design of the survey is self-enumeration through mail-out and mail-back operation in every county to a representative sample of about 3 million addresses across the country. Effective final response rates for the ACS have been about 97%. The ACS field staff work full-time in their areas and can explain to local communities how the ACS benefits them. Because of this the ACS has not encountered the kind of resistance from respondents that the census long form has. The Census Bureau has been developing the ACS since 1996 when it was tested in just four sites. The ACS has since expanded to 31 diverse sites collecting data that can be compared with Census 2000 results. These comparisons are laying the groundwork for the transition from the long form to the ACS. The plan is to fully implement the survey in 2003 and continue data collection every year thereafter.

STUDY QUESTIONDo social determinants of health (SDoH) influence the age at menopause among women?SUMMARY ANSWERIn our study, adverse SDoH, particularly family low income-to-poverty ratio (PIR), low education level, and the marital status of being widowed, are associated with earlier age at menopause.WHAT IS KNOWN ALREADYSome prior studies have considered certain SDoH variables (such as educational attainment and marital status) as potential factors influencing age at menopause, but systematic evidence clearly defining the relationship between multidimensional SDoH and menopausal age remains lacking.STUDY DESIGN, SIZE, DURATIONThis cross-sectional analysis included 6083 naturally menopausal women from 10 cycles (1999–2018) of the United States National Health and Nutrition Examination Survey (NHANES) and excluded cases of surgical menopause.PARTICIPANTS/MATERIALS, SETTING, METHODSThe participants were derived from a nationally representative sample of the NHANES 1999–2018 in the USA. Eight SDoH variables were assessed: employment, PIR, food security, education, healthcare access, health insurance, housing stability, and marital status. Age at menopause was determined by self-reported last menstrual period among women with natural menopause. This study constructed weighted multivariate linear regression models and weighted quantile sum (WQS) analyses and calculated regression coefficients (β) and their 95% CIs. Subgroup analyses and sensitivity analyses were used to verify the robustness of our findings.MAIN RESULTS AND THE ROLE OF CHANCEAfter adjusting for relevant confounding factors, adverse PIR, education level, and marital status (such as being widowed) were significantly associated with earlier age at menopause. Specifically, compared to women with a PIR ≥500%, women with a PIR between 100% and 300% or PIR ≤100% had an earlier age at menopause by 0.877 years (95% CI: −1.526, −0.229, P = 0.008) and 1.296 years (95% CI: −2.105, −0.487, P = 0.002), respectively. Additionally, compared to women with an educational level of college or above, women with a high school education or less than a high school education had earlier age at menopause by 1.262 years (High school: 95% CI = −1.914, −0.609, P < 0.001) and 1.403 years (Less than high school: 95% CI = −2.062, −0.743, P < 0.001), respectively. Compared to women who were married or living with a partner, widowed women had earlier age at menopause by 1.363 years (95% CI = −1.887, −0.839, P < 0.001). Analysis using a WQS regression model based on decile categorization demonstrated that each 1-unit increase in the composite exposure index of adverse SDoH factors was associated with 3.302 years earlier age at menopause in women (95% CI = −4.129, −2.476, P < 0.001). The PIR contributed most substantially to the inverse association between SDoH and age at menopause.LIMITATIONS, REASONS FOR CAUTIONThe cross-sectional design limits causal inference. Unmeasured confounders (e.g. parity, previous hormone use, chemical exposures) and recall bias may persist despite sensitivity analyses.WIDER IMPLICATIONS OF THE FINDINGSThese findings substantiate the implementation of integrated multidimensional interventions targeting economic stability, housing security, employment support, and healthcare access, which would likely yield substantially greater benefits than single-dimensional policy adjustments. Moreover, material deprivation factors may exert profoundly stronger effects on reproductive aging than previously thought.STUDY FUNDING/COMPETING INTEREST(S)This work was supported by the National Key Research and Development Program of China (2023YFC2705700), the Interdisciplinary Innovative Talents Foundation from Renmin Hospital of Wuhan University (JCRCYG-2022-009), and the National Natural Science Foundation of China (72474005). All authors declare no competing interests.TRIAL REGISTRATION NUMBERN/A.

The singular message in Global Health Law is that we must strive to achieve global health with justice--improved population health, with a fairer distribution of benefits of good health. Global health entails ensuring the conditions of good health--public health, universal health coverage, and the social determinants of health--while justice requires closing today’s vast domestic and global health inequities. These conditions for good health should be incorporated into public policy, supplemented by specific actions to overcome barriers to equity. A new global health treaty grounded in the right to health and aimed at health equity--a Framework Convention on Global Health (FCGH)--stands out for its possibilities in helping to achieve global health with justice. This far-reaching legal instrument would establish minimum standards for universal health coverage and public health measures, with an accompanying national and international financing framework, require a constant focus on health equity, promote Health in All Policies and global governance for health, and advance the principles of good governance, including accountability. While achieving an FCGH is certainly ambitious, it is a struggle worth the efforts of us all. The treaty’s basis in the right to health, which has been agreed to by all governments, has powerful potential to form the foundation of global governance for health. From interpretations of UN treaty bodies to judgments of national courts, the right to health is now sufficiently articulated to serve this role, with the individual’s right to health best understood as a function of a social, political, and economic environment aimed at equity. However great the political challenge of securing state agreement to the FCGH, it is possible. States have joined other treaties with significant resource requirements and limitations on their sovereignty without significant reciprocal benefits from other states, while important state interests would benefit from the FCGH. And from integrating the FCGH into the existing human rights system to creative forms of compliance and enforcement and strengthened domestic legal and political accountability mechanisms, the treaty stands to improve right to health compliance. The potential for the FCGH to bring the right to health nearer universal reality calls for us to embark on the journey towards securing this global treaty.