Preparing to Address Social Determinants of Health (SDOH): Approaches to Clinic Transformation.

CONTEXT: Pennsylvanians' health is influenced by numerous social determinants of health (SDOH). Integrating SDOH data into electronic health records (EHRs) is critical to identifying health disparities, informing public health policies, and devising interventions. Nevertheless, challenges remain in its implementation within clinical settings. In 2018, the Pennsylvania Department of Health (PADOH) received the Centers for Disease Control and Prevention's DP18-1815 "Improving the Health of Americans Through Prevention and Management of Diabetes and Heart Disease and Stroke" grant to strengthen SDOH data integration in Pennsylvania practices. IMPLEMENTATION: Quality Insights was contracted by PADOH to provide training tailored to each practice's readiness, an International Classification of Diseases, Tenth Revision (ICD-10) guide for SDOH, Continuing Medical Education on SDOH topics, and introduced the PRAPARE toolkit to streamline SDOH data integration and address disparities. Dissemination efforts included a podcast highlighting success stories and lessons learned from practices. From 2019 to 2022, Quality Insights and the University of Pittsburgh Evaluation Institute for Public Health (Pitt evaluation team) executed a mixed-methods evaluation. FINDINGS: During 2019-2022, Quality Insights supported 100 Pennsylvania practices in integrating SDOH data into EHR systems. Before COVID-19, 82.8% actively collected SDOH data, predominantly using PRAPARE tool (62.7%) and SDOH ICD-10 codes (80.4%). Amidst COVID-19, these statistics shifted to 65.1%, 45.2%, and 42.7%, respectively. Notably, the pandemic highlighted the importance of SDOH assessment and catalyzed some practices' utilization of SDOH data. Progress was evident among practices, with additional contribution to other DP18-1815 objectives. The main challenge was the variable understanding, utilization, and capability of handling SDOH data across practices. Effective strategies involved adaptable EHR systems, persistent efforts by Quality Insights, and the presence of change champions within practices. DISCUSSION: The COVID-19 pandemic strained staffing in many practices, impeding SDOH data integration into EHRs. Addressing the diverse understanding and use of SDOH data requires standardized training and procedures. Customized support and sustained engagement by facilitating organizations are paramount in ensuring practices' efficient SDOH data collection and integration.

Prediabetes Prevalence by Adverse Social Determinants of Health in Adolescents.

Importance: Several clinical practice guidelines advise race- and ethnicity-based screening for youth-onset type 2 diabetes (T2D) due to a higher prevalence among American Indian and Alaska Native, Asian, Black, and Hispanic youths compared with White youths. However, rather than a biological risk, this disparity likely reflects the inequitable distribution of adverse social determinants of health (SDOH), a product of interpersonal and structural racism. Objective: To evaluate prediabetes prevalence by presence or absence of adverse SDOH in adolescents eligible for T2D screening based on weight status. Design, Setting, and Participants: This cross-sectional study and analysis used data from the 2011 to 2018 cycles of the National Health and Nutrition Examination Survey. Data were analyzed from June 1, 2023, to April 5, 2024. Participants included youths aged 12 to 18 years with body mass index (BMI) at or above the 85th percentile without known diabetes. Main Outcomes and Measures: The main outcome consisted of an elevated hemoglobin A1c (HbA1c) level greater than or equal to 5.7% (prediabetes or undiagnosed presumed T2D). Independent variables included race, ethnicity, and adverse SDOH (food insecurity, nonprivate health insurance, and household income <130% of federal poverty level). Survey-weighted logistic regression was used to adjust for confounders of age, sex, and BMI z score and to determine adjusted marginal prediabetes prevalence by race, ethnicity, and adverse SDOH. Results: The sample included 1563 individuals representing 10 178 400 US youths aged 12 to 18 years (mean age, 15.5 [95% CI, 15.3-15.6] years; 50.5% [95% CI, 47.1%-53.9%] female; Asian, 3.0% [95% CI, 2.2%-3.9%]; Black, 14.9% [95% CI, 11.6%-19.1%]; Mexican American, 18.8% [95% CI, 15.4%-22.9%]; Other Hispanic, 8.1% [95% CI, 6.5%-10.1%]; White, 49.1% [95% CI, 43.2%-55.0%]; and >1 or other race, 6.1% [95% CI, 4.6%-8.0%]). Food insecurity (4.1% [95% CI, 0.7%-7.5%]), public insurance (5.3% [95% CI, 1.6%-9.1%]), and low income (5.7% [95% CI, 3.0%-8.3%]) were each independently associated with higher prediabetes prevalence after adjustment for race, ethnicity, and BMI z score. While Asian, Black, and Hispanic youths had higher prediabetes prevalence overall, increasing number of adverse SDOH was associated with higher prevalence among White youths (8.3% [95% CI, 4.9%-11.8%] for 3 vs 0.6% [95% CI, -0.7% to 2.0%] for 0 adverse SDOH). Conclusions and Relevance: Adverse SDOH were associated with higher prediabetes prevalence, across and within racial and ethnic categories. Consideration of adverse SDOH may offer a more actionable alternative to race- and ethnicity-based screening to evaluate T2D risk in youth.

Impact of social determinants of health on progression from potentially life-threatening complications to near miss events and death during pregnancy and post partum in a middle-income setting: an observational study.

OBJECTIVE: To assess the potential associations between social determinants of health (SDH) and severe maternal outcomes (SMO), to better understand the social structural framework and the contributory, non-clinical mechanisms associated with SMO. STUDY DESIGN: Prospective observational study. STUDY SETTING: Tertiary referral centre in south-eastern region of India. PARTICIPANTS: One thousand and thirty-three women with potentially life-threatening complications (PLTC) were identified using WHO criteria. RISK FACTORS ASSESSED: Social Determinants of Health (SDH). PRIMARY OUTCOMES: Severe maternal outcomes, which include maternal near-miss and maternal death. STATISTICAL ANALYSIS: Logistic regression to assess the association between SDH and clinical factors on SMO, expressed as adjusted ORs (aOR) with a 95% CI. RESULTS: Of the 37 590 live births, 1833 (4.9%) sustained PLTC, and 380 (20.7%) developed SMO. Risk of SMO was higher with increasing maternal age (adjusted OR (aOR) 1.04 (95% CI 1.01 to 1.07)), multiparity (aOR 1.44 (1.10 to 1.90)), medical comorbidities (aOR 1.50 (1.11 to 2.02)), obstetric haemorrhage (aOR 4.63 (3.10 to 6.91)), infection (aOR 2.93 (1.83 to 4.70)), delays in seeking care (aOR 3.30 (2.08 to 5.23)), and admissions following a referral (aOR 2.95 (2.21 to 3.93)). SMO was lower in patients from socially backward community (aOR 0.45 (0.33 to 0.61)), those staying more than 10 km from hospital (aOR 0.56 (0.36 to 0.78)), those attending at least four antenatal visits (aOR=0.53 (0.36 to 0.78)) and those referred from resource-limited facilities (aOR=0.62 (0.46 to 0.84)). CONCLUSION: This study demonstrates the independent contribution of SDH to SMO among those sustaining PLTC in a middle-income setting, highlighting the need to formulate preventive strategies beyond clinical considerations.

Incidence of Traumatic Brain Injury in a Longitudinal Cohort of Older Adults.

Importance: Traumatic brain injury (TBI) occurs at the highest rate in older adulthood and increases risk for cognitive impairment and dementia. Objectives: To update existing TBI surveillance data to capture nonhospital settings and to explore how social determinants of health (SDOH) are associated with TBI incidence among older adults. Design, Setting, and Participants: This nationally representative longitudinal cohort study assessed participants for 18 years, from August 2000 through December 2018, using data from the Health and Retirement Study (HRS) and linked Medicare claims dates. Analyses were completed August 9 through December 12, 2022. Participants were 65 years of age or older in the HRS with survey data linked to Medicare without a TBI prior to HRS enrollment. They were community dwelling at enrollment but were retained in HRS if they were later institutionalized. Exposures: Baseline demographic, cognitive, medical, and SDOH information from HRS. Main Outcomes and Measures: Incident TBI was defined using inpatient and outpatient International Classification of Diseases, Ninth or Tenth Revision, diagnosis codes received the same day or within 1 day as the emergency department (ED) visit code and the computed tomography (CT) or magnetic resonance imaging (MRI) code, after baseline HRS interview. A cohort with TBI codes but no ED visit or CT or MRI scan was derived to capture diagnoses in nonhospital settings. Descriptive statistics and bivariate associations of TBI with demographic and SDOH characteristics used sample weights. Fine-Gray regression models estimated associations between covariates and TBI, with death as a competing risk. Imputation considering outcome and complex survey design was performed by race and ethnicity, sex, education level, and Area Deprivation Index percentiles 1, 50, and 100. Other exposure variables were fixed at their weighted means. Results: Among 9239 eligible respondents, 5258 (57.7%) were female and 1210 (9.1%) were Black, 574 (4.7%) were Hispanic, and 7297 (84.4%) were White. Mean (SD) baseline age was 75.2 (8.0) years. During follow-up (18 years), 797 (8.9%) of respondents received an incident TBI diagnosis with an ED visit and a CT code within 1 day, 964 (10.2%) received an incident TBI diagnosis and an ED code, and 1148 (12.9%) received a TBI code with or without an ED visit and CT scan code. Compared with respondents without incident TBI, respondents with TBI were more likely to be female (absolute difference, 7.0 [95% CI, 3.3-10.8]; P < .001) and White (absolute difference, 5.1 [95% CI, 2.8-7.4]; P < .001), have normal cognition (vs cognitive impairment or dementia; absolute difference, 6.1 [95% CI, 2.8-9.3]; P = .001), higher education (absolute difference, 3.8 [95% CI, 0.9-6.7]; P < .001), and wealth (absolute difference, 6.5 [95% CI, 2.3-10.7]; P = .01), and be without baseline lung disease (absolute difference, 5.1 [95% CI, 3.0-7.2]; P < .001) or functional impairment (absolute difference, 3.3 [95% CI, 0.4-6.1]; P = .03). In adjusted multivariate models, lower education (subdistribution hazard ratio [SHR], 0.73 [95% CI, 0.57-0.94]; P = .01), Black race (SHR, 0.61 [95% CI, 0.46-0.80]; P < .001), area deprivation index national rank (SHR 1.00 [95% CI 0.99-1.00]; P = .009), and male sex (SHR, 0.73 [95% CI, 0.56-0.94]; P = .02) were associated with membership in the group without TBI. Sensitivity analyses using a broader definition of TBI yielded similar results. Conclusions and Relevance: In this longitudinal cohort study of older adults, almost 13% experienced incident TBI during the 18-year study period. For older adults who seek care for TBI, race and ethnicity, sex, and SDOH factors may be associated with incidence of TBI, seeking medical attention for TBI in older adulthood, or both.

Spanish-Speaking Caregiver Preferences for Social Determinants of Health Screening.

Equitable social determinants of health (SDOH) screening has been recommended by the Centers for Medicare & Medicaid Services and the Joint Commission; however, little is known about Spanish-speaking caregiver preferences on how they would like to be screened. We conducted a cross-sectional study at 3 pediatric clinics (October-December 2019). Caregivers completed (in English or Spanish) an SDOH screening preferences survey. Three hundred eighty-two of 443 caregivers approached (response rate = 86.2%) completed the survey. Most were female, preferred Spanish, and completed only high school. Spanish-speaking caregivers had greater odds of preferring verbal SDOH screening (odds ratio: 4.1; 95% confidence interval, 1.8-9.2) than English-speaking caregivers. Verbal SDOH screening should be a consideration in families who speak Spanish. Future studies should utilize qualitative methods to further explore Spanish-speaking caregiver preferences for SDOH screening.

Assessing the Impact of Social Determinants of Health on HIV Care Engagement in the Southern United States: A Cross-Sectional Study.

Recent studies have shown social determinants of health (SDOH) to impact HIV care engagement. This cross-sectional study (Oct 20-Apr 21) assessed the impact of a range of SDOH on HIV care engagement using data from HIV Care Connect, a consortium of three HIV care facility-led programs (Alabama, Florida, Mississippi). The exposures were captured using the PRAPARE (Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences) scale. The outcome was captured using the Index of Engagement in HIV Care scale. Participants (n = 132) were predominantly non-White (87%) and male (52%) with a median age of 41 years. Multivariable logistic regression adjusted for various sociodemographics showed lower HIV care engagement to be associated with being uninsured/publicly insured, having 1-3 unmet needs, socially integrating ≤five times/week, and having stable housing. Factors such as unmet needs, un-/underinsurance, and social integration may be addressed by healthcare and community organizations.

Assessing How Social Drivers of Health Affect Engagement in HIV Care in the Southern United StatesIt has been found that social factors that have a direct impact on health affect engagement in HIV Care among people living with HIV. We included various social drivers of health to see how they affect engagement in HIV Care. We used data between October 2020 and April 2021 from a project titled HIV Care Connect, which is a group of three facilities providing HIV care in Alabama, Florida, and Mississippi. We used social drivers of health as risk factors from a scale called PRAPARE (Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences). Engagement in HIV care was measured by using a scale called Index of Engagement in HIV Care. A total of 132 participants were included. Majority of the participants were of races other than white (87%), male (52%) and were aged 41 years on average. Statistical analysis showed that participants without insurance or with public insurance, participants with 1-3 unsatisfied needs, participants that met with other people less than or equal to five times a week, and participants that had reliable housing had lower engagement in HIV care. These factors have a potential to be addressed by healthcare and community organizations.

Social Determinants of Health and Delivery of Rehabilitation to Older Adults During ICU Hospitalization.

Importance: Older adults with socioeconomic disadvantage develop a greater burden of disability after critical illness than those without socioeconomic disadvantage. The delivery of in-hospital rehabilitation that can mitigate functional decline may be influenced by social determinants of health (SDOH). Whether rehabilitation delivery differs by SDOH during critical illness hospitalization is not known. Objective: To evaluate whether SDOH are associated with the delivery of skilled rehabilitation during critical illness hospitalization among older adults. Design, Setting, and Participants: This cohort study used data from the National Health and Aging Trends Study linked with Medicare claims (2011-2018). Participants included older adults hospitalized with a stay in the intensive care unit (ICU). Data were analyzed from August 2022 to September 2023. Exposures: Dual eligibility for Medicare and Medicaid, education, income, limited English proficiency (LEP), and rural residence. Main Outcome and Measures: The primary outcome was delivery of physical therapy (PT) and/or occupational therapy (OT) during ICU hospitalization, characterized as any in-hospital PT or OT and rate of in-hospital PT or OT, calculated as total number of units divided by length of stay. Results: In the sample of 1618 ICU hospitalizations (median [IQR] patient age, 81.0 [75.0-86.0] years; 842 [52.0%] female), 371 hospitalizations (22.9%) were among patients with dual Medicare and Medicaid eligibility, 523 hospitalizations (32.6%) were among patients with less than high school education, 320 hospitalizations (19.8%) were for patients with rural residence, and 56 hospitalizations (3.5%) were among patients with LEP. A total of 1076 hospitalized patients (68.5%) received any PT or OT, with a mean rate of 0.94 (95% CI, 0.86-1.02) units/d. After adjustment for age, sex, prehospitalization disability, mechanical ventilation, and organ dysfunction, factors associated with lower odds of receipt of PT or OT included dual Medicare and Medicaid eligibility (adjusted odds ratio, 0.70 [95% CI, 0.50-0.97]) and rural residence (adjusted odds ratio, 0.65 [95% CI, 0.48-0.87]). LEP was associated with a lower rate of PT or OT (adjusted rate ratio, 0.55 [95% CI, 0.32-0.94]). Conclusions and Relevance: These findings highlight the need to consider SDOH in efforts to promote rehabilitation delivery during ICU hospitalization and to investigate factors underlying inequities in this practice.

Self-Reported Social Determinants of Health and Area-Level Social Vulnerability.

Importance: Many health care systems are investing resources in identifying social determinants of health (SDoH) needs and facilitating interventions among the populations they serve. Because self-reported SDoH information is lacking, area-level measures are often used to estimate needs and direct resources. Objective: To describe the large-scale deployment of SDoH assessments by a health system and determine the extent to which self-reported SDoH needs identified therein are associated with census tract-level social vulnerability measured using the Social Vulnerability Index (SVI). Design, Setting, and Participants: This cross-sectional study assessed SDoH needs between January 1, 2020, and April 30, 2023, in both payer and clinical care settings. Modalities included telephonic outreach, face-to-face clinical interactions, self-entry into a tablet or kiosk, and web-based survey tools. Participants included individuals who responded to the assessment and had sufficient information for census tract identification. Respondents included both Highmark Health Plan members and nonmembers. Health plan members responded to the assessment through health plan programs or platforms, and both members and nonmembers responded to assessments during inpatient or outpatient encounters with the affiliated health system. Main Outcomes and Measures: Overall and domain-specific SDoH needs self-reported through assessments, and severity and complexity of needs identified. Residential social vulnerability measures included overall SVI and the 4 conceptual themes comprising overall SVI. Results: In total, 841 874 assessments were recorded for 401 697 individuals (55.1% women; median [IQR] age, 55 [41-70] years). Social determinants of health needs were identified in 120 769 assessments (14.3%). Across all SDoH domains, increasing SVI was associated with a higher positivity rate (eg, 11.2% of those residing in the lowest-risk SVI quintile reported a need compared with 22.7% among those residing in the highest-risk quintile). Associations varied by SDoH domain and SVI theme. After adjusting for demographic and screening characteristics, odds of positive screening among those residing in the highest-risk SVI quintile were 1.74 (95% CI, 1.62-1.86) to 3.73 (95% CI, 3.48-4.00) times the odds among those residing in lowest risk quintile. Conclusions and Relevance: In this cross-sectional study, the overall level of SDoH needs generally corresponded to area-level vulnerability. Some SDoH domains appeared far more sensitive to community characteristics than others. Notably, even among individuals from the highest-risk areas, the positive screening rate was roughly 1 in 4. These findings underscore the importance of individual-level SDoH data for service provision planning and health services research.

Multidimensional Approach to Exploring Neighborhood Determinants and Symptom Severity Among Individuals With Psychosis.

Importance: The impact of cumulative exposure to neighborhood factors on psychosis, depression, and anxiety symptom severity prior to specialized services for psychosis is unknown. Objective: To identify latent neighborhood profiles based on unique combinations of social, economic, and environmental factors, and validate profiles by examining differences in symptom severity among individuals with first episode psychosis (FEP). Design, Setting, and Participants: This cohort study used neighborhood demographic data and health outcome data for US individuals with FEP receiving services between January 2017 and August 2022. Eligible participants were between ages 14 and 40 years and enrolled in a state-level coordinated specialty care network. A 2-step approach was used to characterize neighborhood profiles using census-tract data and link profiles to mental health outcomes. Data were analyzed March 2023 through October 2023. Exposures: Economic and social determinants of health; housing conditions; land use; urbanization; walkability; access to transportation, outdoor space, groceries, and health care; health outcomes; and environmental exposure. Main Outcomes and Measures: Outcomes were Community Assessment of Psychic Experiences 15-item, Patient Health Questionnaire 9-item, and Generalized Anxiety Disorder 7-item scale. Results: The total sample included 225 individuals aged 14 to 36 years (mean [SD] age, 20.7 [4.0] years; 152 men [69.1%]; 9 American Indian or Alaska Native [4.2%], 13 Asian or Pacific Islander [6.0%], 19 Black [8.9%], 118 White [55.1%]; 55 Hispanic ethnicity [26.2%]). Of the 3 distinct profiles identified, nearly half of participants (112 residents [49.8%]) lived in urban high-risk neighborhoods, 56 (24.9%) in urban low-risk neighborhoods, and 57 (25.3%) in rural neighborhoods. After controlling for individual characteristics, compared with individuals residing in rural neighborhoods, individuals residing in urban high-risk (mean estimate [SE], 0.17 [0.07]; P = .01) and urban low-risk neighborhoods (mean estimate [SE], 0.25 [0.12]; P = .04) presented with more severe psychotic symptoms. Individuals in urban high-risk neighborhoods reported more severe depression (mean estimate [SE], 1.97 [0.79]; P = .01) and anxiety (mean estimate [SE], 1.12 [0.53]; P = .04) than those in rural neighborhoods. Conclusions and Relevance: This study found that in a cohort of individuals with FEP, baseline psychosis, depression, and anxiety symptom severity differed by distinct multidimensional neighborhood profiles that were associated with where individuals reside. Exploring the cumulative effect of neighborhood factors improves our understanding of social, economic, and environmental impacts on symptoms and psychosis risk which could potentially impact treatment outcomes.

Disparities in insurance status negatively affect patients with infantile hypertrophic pyloric stenosis.

PURPOSE: Infantile hypertrophic pyloric stenosis (IHPS) is suspected to have worse outcomes when length of illness prior to presentation is prolonged. Our objective was to evaluate how social determinants of health influence medical care and outcomes for babies with IHPS. METHODS: A retrospective review was performed over 10 years. Census data were used as proxy for socioeconomic status via Geo-Identification codes and correlated with food access and social vulnerability variables. The cohort was subdivided to understand the impact of Medicaid Managed Care (MMC). RESULTS: The cohort (279 cases) was divided into two groups; early group from 2011 to 2015 and late from 2016 to 2021. Cases in the late group were older at the time of presentation (41.5 vs. 36.5 days; p = 0.022) and presented later in the disease course (12.8 vs. 8.9 days; p = 0.021). There was no difference in race (p = 0.282), gender (p = 0.874), or length of stay. CONCLUSIONS: Patients who presented with IHPS after implementation of phased MMC were older, had a longer symptomatic course, and shorter pylorus measurements. Patients with public insurance after the implementation of MMC were more likely to follow-up with an outpatient pediatrician within a month of hospitalization. These results suggest that MMC may have improved access to care for infants with IHPS.

Communication and Social Determinants of Cancer Preventive Behaviors in Adolescents From Low Socio-Economic Backgrounds in India: A Cross-Sectional Study.

PURPOSE: Promoting cancer preventive behaviors among adolescents, especially those from lower socioeconomic backgrounds, is crucial due to the significant impact of health behaviors in adolescence on disease risk in adulthood. With India witnessing a rise in cancer incidence and mortality, adolescence becomes a pivotal stage for establishing healthy habits, emphasizing the need for early cancer prevention efforts. METHODS: This cross-sectional study used survey data from 2242 adolescents attending public schools of Mumbai, India. Multiple logistic regression was conducted to determine the associations between cancer preventive behaviors and: (1) the individual and social determinants of health, and (2) media exposure. FINDINGS: Merely 21.5% of the adolescents ate fruits and vegetables daily, 50% of the adolescents exercised 3 or more times a week, and 20% of the adolescents admitted having used tobacco and/or supari. Girls were found to have lower odds of exercising, as well as using tobacco and/or supari. Wealth and father's education were positively associated with all 3 cancer preventive behaviors. Media exposure was negatively associated, with television exposure linked to reduced fruits and vegetables consumption, while movies and social media exposure were associated with increased tobacco and/or supari use. INTERPRETATION: Our findings suggest that individual and social determinants of health and media exposure can influence cancer preventive health behaviors in low socio-economic status (SES) adolescents. Efforts to increase awareness to promote cancer preventive behaviors among the adolescents, particularly low SES adolescents, a population more vulnerable to poor health outcomes, is critical.

This study investigates factors that can influence cancer preventive behaviors among low socioeconomic status (SES) adolescents, focusing on dietary habits, physical activity, and avoidance of tobacco and areca nut. Our study gathered data from an underrepresented population of India, which is more vulnerable to poor health outcomes and have less access to health care. Our findings can alert public health officials, policy makers and non-governmental organizations to target this population and customize their intervention strategies to promote health and prevent cancer.

Poor reporting limited consideration of EDI in the Australian guidelines for the clinical care of people with COVID-19.

OBJECTIVES: Actively addressing issues of equity, diversity, and inclusion (EDI) in healthcare guidelines provides an important avenue ensure that individuals and communities receive high-quality healthcare that meets their needs. In 2020, the National Clinical Evidence Taskforce was charged with developing Australian living guidelines for COVID-19 (the Guidelines). It was intended that the Guidelines would consider the biological and social determinants of health (BSDH) underpinning evidence-based recommendations for of the treatment of COVID-19. The objective of this paper is to describe the evidence available on BSDH that is reported in published trials of disease-modifying therapies for COVID-19. STUDY DESIGN AND SETTING: Published papers of randomized controlled trials that informed clinical recommendations (for and against drug therapies for COVID-19) in the Guidelines were reviewed retrospectively using a case series design. We extracted reported characteristics relating to BSDH. These included age, sex, gender, geographical location, ethnicity (including indigenous), disability, migrant status, income, education, employment, and social support. A descriptive analysis was conducted to illustrate the characteristics available for use in guideline development. RESULTS: A total of 115 peer-reviewed papers describing randomized control trials of drug interventions for the treatment of COVID-19 were included. BSDH characteristics were poorly reported. Geographical location of the study was the only category reported in all papers. While age and sex were reported in most papers (n = 109 and 108, respectively), ethnicity was reported in only one-third of papers (n = 40), social support was reported in only three papers, and employment in one paper. No paper reported on gender, disability, migrant status, income, or education. CONCLUSION: Consideration of EDI issues is a crucial component of guideline development. Although these issues were widely recognized to impact on health outcomes from COVID-19, reporting of these characteristics was poor in COVID trials. Urgent action is needed to improve reporting of EDI characteristics if they are to be meaningfully considered in guideline processes, and health inequity is overcome.

The impact of devolution on local health systems: Evidence from Greater Manchester, England.

Devolution and decentralisation policies involving health and other government sectors have been promoted with a view to improve efficiency and equity in local service provision. Evaluations of these reforms have focused on specific health or care measures, but little is known about their full impact on local health systems. We evaluated the impact of devolution in Greater Manchester (England) on multiple outcomes using a whole system approach. We estimated the impact of devolution until February 2020 on 98 measures of health system performance, using the generalised synthetic control method and adjusting for multiple hypothesis testing. We selected measures from existing monitoring frameworks to populate the WHO Health System Performance Assessment framework. The included measures captured information on health system functions, intermediatory objectives, final goals, and social determinants of health. We identified which indicators were targeted in response to devolution from an analysis of 170 health policy intervention documents. Life expectancy (0.233 years, S.E. 0.012) and healthy life expectancy (0.603 years, S.E. 0.391) increased more in GM than in the estimated synthetic control group following devolution. These increases were driven by improvements in public health, primary care, hospital, and adult social care services as well as factors associated with social determinants of health, including a reduction in alcohol-related admissions (-110.1 admission per 100,000, S.E. 9.07). In contrast, the impact on outpatient, mental health, maternity, and dental services was mixed. Devolution was associated with improved population health, driven by improvements in health services and wider social determinants of health. These changes occurred despite limited devolved powers over health service resources suggesting that other mechanisms played an important role, including the allocation of sustainability and transformation funding and the alignment of decision-making across health, social care, and wider public services in the region.

Cardiovascular Risk Associated With Social Determinants of Health at Individual and Area Levels.

Importance: The benefit of adding social determinants of health (SDOH) when estimating atherosclerotic cardiovascular disease (ASCVD) risk is unclear. Objective: To examine the association of SDOH at both individual and area levels with ASCVD risks, and to assess if adding individual- and area-level SDOH to the pooled cohort equations (PCEs) or the Predicting Risk of CVD Events (PREVENT) equations improves the accuracy of risk estimates. Design, Setting, and Participants: This cohort study included participants data from 4 large US cohort studies. Eligible participants were aged 40 to 79 years without a history of ASCVD. Baseline data were collected from 1995 to 2007; median (IQR) follow-up was 13.0 (9.3-15.0) years. Data were analyzed from September 2023 to February 2024. Exposures: Individual- and area-level education, income, and employment status. Main outcomes and measures: ASCVD was defined as the composite outcome of nonfatal myocardial infarction, death from coronary heart disease, and fatal or nonfatal stroke. Results: A total of 26 316 participants were included (mean [SD] age, 61.0 [9.1] years; 15 494 women [58.9%]; 11 365 Black [43.2%], 703 Chinese American [2.7%], 1278 Hispanic [4.9%], and 12 970 White [49.3%]); 11 764 individuals (44.7%) had at least 1 adverse individual-level SDOH and 10 908 (41.5%) had at least 1 adverse area-level SDOH. A total of 2673 ASCVD events occurred during follow-up. SDOH were associated with increased risk of ASCVD at both the individual and area levels, including for low education (individual: hazard ratio [HR], 1.39 [95% CI, 1.25-1.55]; area: HR, 1.31 [95% CI, 1.20-1.42]), low income (individual: 1.35 [95% CI, 1.25-1.47]; area: HR, 1.28 [95% CI, 1.17-1.40]), and unemployment (individual: HR, 1.61 [95% CI, 1.24-2.10]; area: HR, 1.25 [95% CI, 1.14-1.37]). Adding area-level SDOH alone to the PCEs did not change model discrimination but modestly improved calibration. Furthermore, adding both individual- and area-level SDOH to the PCEs led to a modest improvement in both discrimination and calibration in non-Hispanic Black individuals (change in C index, 0.0051 [95% CI, 0.0011 to 0.0126]; change in scaled integrated Brier score [IBS], 0.396% [95% CI, 0.221% to 0.802%]), and improvement in calibration in White individuals (change in scaled IBS, 0.274% [95% CI, 0.095% to 0.665%]). Adding individual-level SDOH to the PREVENT plus area-level social deprivation index (SDI) equations did not improve discrimination but modestly improved calibration in White participants (change in scaled IBS, 0.182% [95% CI, 0.040% to 0.496%]), Black participants (0.187% [95% CI, 0.039% to 0.501%]), and women (0.289% [95% CI, 0.115% to 0.574%]). Conclusions and Relevance: In this cohort study, both individual- and area-level SDOH were associated with ASCVD risk; adding both individual- and area-level SDOH to the PCEs modestly improved discrimination and calibration for estimating ASCVD risk for Black individuals, and adding individual-level SDOH to PREVENT plus SDI also modestly improved calibration. These findings suggest that both individual- and area-level SDOH may be considered in future development of ASCVD risk assessment tools, particularly among Black individuals.

Diabetes and the social, biologic, and behavioral determinants of endometrial cancer in the United States.

BACKGROUND: Endometrial cancer is one of the most common types of cancer that affects women's reproductive system. The risk of endometrial cancer is associated with biologic, behavioral and social determinants of health (SDOH). The focus of the work is to investigate the cumulative effect of this cluster of covariates on the odds of endometrial cancer that heretofore have only been considered individually. METHODS: We conducted a quantitative study using the Behavioral Risk Factor Surveillance System (BRFSS) national data collected in 2020. Data analysis using weighted Chi-square test and weighted logistic regression were carried out on 84,118 female study participants from the United States. RESULTS: Women with diabetes mellitus were approximately twice as likely to have endometrial cancer compared to women without diabetes (OR 1.54; 95%CI: 1.01-2.34). Biologic factors that included obesity (OR 3.10; 95% CI: 1.96-4.90) and older age (with ORs ranging from 2.75 to 7.21) had a significant increase in the odds of endometrial cancer compared to women of normal weight and younger age group of 18 to 44. Among the SDOH, attending college (OR 1.83; 95% CI: 1.12-3.00) was associated with increased odds of endometrial cancer, while renting a home (OR 0.50; 95% CI: 0.28-0.88), having other arrangements (OR 0.05; 95% CI: 0.02-0.16), being divorced (OR 0.55; 95% CI: 0.30-0.99), and having higher incomes ranging from $35,000 to $50,000 (OR 0.35; 95% CI: 0.16-0.78), and above $50,000 (OR 0.29; 95% CI: 0.14-0.62), were all associated with decreased odds of endometrial cancer. As for race, Black women (OR 0.24; 95% CI: 0.07-0.84) and women of other races (OR 0.37; 95% CI: 0.15-0.88) were shown to have lower odds of endometrial cancer compared to White women. CONCLUSION: Our results revealed the importance of adopting a comprehensive approach to the study of the associated factors of endometrial cancer by including social, biologic, and behavioral determinants of health. The observed social inequity in endometrial cancer among women needs to be addressed through effective policies and changes in social structures to advocate for a standardized healthcare system that ensures equitable access to preventive measures and quality of care.

Cumulative inequality in social determinants of health in relation to depression symptom: An analysis of nationwide cross-sectional data from U.S. NHANES 2005-2018.

Social determinants of health (SDoH) have been linked to a higher likelihood of experiencing mental health problems. This study aimed to investigate whether the accumulation of unfavorable SDoH is associated with depression symptom. Data was gathered from a representative population participating in the U.S. National Health and Nutrition Examination Survey spanning from 2005 to 2018. Self-reported SDoH were operationalized according to the criteria outlined in Healthy People 2030, with a cumulative measure of unfavorable SDoH calculated for analysis. The presence of depression symptom was identified using the Patient Health Questionnaire in a representative sample of 30,762 participants (49.2 % males) representing 1,392 million non-institutionalized U.S. adults, with 2,675 (8.7 %) participants showing depression symptom. Unfavorable SDoH were found to be significantly and independently associated with depression symptom. Individuals facing multiple unfavorable SDoHs were more likely to experience depression symptom (P for trend < 0.001). For instance, a positive association was observed in participants exposed to six or more unfavorable SDoHs with depression symptom (AOR = 3.537, 95 % CI: 1.781, 7.075, P-value < 0.001). The findings emphasize that the likelihood of developing depression symptom significantly increases when multiple SDoHs are present, compared to just a single SDoH.

Role of Insulin Use and Social Determinants of Health on Non-melanoma Skin Cancer: Results From the Behavioral Risk Factor Surveillance System.

BACKGROUND: Non-melanoma skin cancer (NMSC) is a frequent type of malignancy with a steadily increasing incidence rate worldwide. Although NMSC was shown to be associated with diabetes, no studies have addressed the extent to which insulin use influences the risk of NMSC in light of social determinants of health (SDOH). We conducted a quantitative study that examined the interplay between insulin use, SDOH, additional covariates, and NMSC among individuals with diabetes. METHODS: We based our analysis on the 2020 Behavioral Risk Factor Surveillance System (BRFSS), a national survey conducted yearly in the US. We performed weighted chi-squared test, logistic regression, and survival analyses on 8685 eligible participants with diabetes enrolled in the BRFSS. RESULTS: Kaplan Meier survival curves showed higher probability of NMSC event-free survival for participants with diabetes using insulin compared to participants with diabetes not using insulin (log-rank test P < .001). Significant associations were detected between insulin use and reduced odds of NMSC (OR .56; 95% CI: .38-.82), and decreased hazard (HR .36; 95% CI: .21-.62), along with indices of SDOH. CONCLUSIONS: Our findings suggest that socioeconomic differences related to the healthcare system and behavioral patterns are linked to discrepancies in the use of insulin and the development of NMSC.

Examining Excess Mortality Associated With the COVID-19 Pandemic for Renters Threatened With Eviction.

Importance: Residential evictions may have increased excess mortality associated with the COVID-19 pandemic. Objective: To estimate excess mortality associated with the COVID-19 pandemic for renters who received eviction filings (threatened renters). Design, Setting, and Participants: This retrospective cohort study used an excess mortality framework. Mortality based on linked eviction and death records from 2020 through 2021 was compared with projected mortality estimated from similar records from 2010 through 2016. Data from court records between January 1, 2020, and August 31, 2021, were collected via the Eviction Lab's Eviction Tracking System. Similar data from court records between January 1, 2010, and December 31, 2016, also collected by the Eviction Lab, were used to estimate projected mortality during the pandemic. We also constructed 2 comparison groups: all individuals living in the study area and a subsample of those individuals living in high-poverty, high-filing tracts. Exposures: Eviction filing. Main Outcomes and Measures: All-cause mortality in a given month. The difference between observed mortality and projected mortality was used as a measure of excess mortality associated with the pandemic. Results: The cohort of threatened renters during the pandemic period consisted of 282 000 individuals (median age, 36 years [IQR, 28-47]). Eviction filings were 44.7% lower than expected during the study period. The composition of threatened renters by race, ethnicity, sex, and socioeconomic characteristics during the pandemic was comparable with the prepandemic composition. Expected cumulative age-standardized mortality among threatened renters during this 20-month period of the pandemic was 116.5 (95% CI, 104.0-130.3) per 100 000 person-months, and observed mortality was 238.6 (95% CI, 230.8-246.3) per 100 000 person-months or 106% higher than expected. In contrast, expected mortality for the population living in similar neighborhoods was 114.6 (95% CI, 112.1-116.8) per 100 000 person-months, and observed mortality was 142.8 (95% CI, 140.2-145.3) per 100 000 person-months or 25% higher than expected. In the general population across the study area, expected mortality was 83.5 (95% CI, 83.3-83.8) per 100 000 person-months, and observed mortality was 91.6 (95% CI, 91.4-91.8) per 100 000 person-months or 9% higher than expected. The pandemic produced positive excess mortality ratios across all age groups among threatened renters. Conclusions and Relevance: Renters who received eviction filings experienced substantial excess mortality associated with the COVID-19 pandemic.

Association of social determinants of health-related diagnosis codes with postoperative outcomes.

BACKGROUND: The association of an individual's social determinants of health-related problems with surgical outcomes has not been well-characterized. The objective of this study was to determine whether documentation of social determinants of a health-related diagnosis code (Z code) is associated with postoperative outcomes. METHODS: This retrospective cohort study included surgical cases from a single institution's national surgical quality improvement program (NSQIP) clinical registry from October 2015 to December 2021. The primary predictor of interest was documentation of a Z code for social determinants of health-related problems. The primary outcome was 30-day postoperative morbidity. Secondary outcomes included postoperative length of stay, disposition, and 30-day postoperative mortality, reoperation, and readmission. Multivariable regression models were fit to evaluate the association between the documentation of a Z code and outcomes. RESULTS: Of 10,739 surgical cases, 348 patients (3.2%) had a documented social determinants of health-related Z code. In multivariable analysis, documentation of a Z code was associated with increased odds of morbidity (20.7% vs. 9.9%; adjusted odds ratio [aOR], 1.88; 95% confidence interval [CI], 1.39-2.53), length of stay (median, 3 vs. 1 day; incidence rate ratio, 1.49; 95% CI, 1.33-1.67), odds of disposition to a location other than home (11.3% vs. 3.9%; aOR, 2.86; 95% CI, 1.89-4.33), and odds of readmission (15.3% vs. 6.1%; aOR, 1.99; 95% CI, 1.45-2.73). CONCLUSIONS: Social determinants of health-related problems evaluated using Z codes were associated with worse postoperative outcomes. Improved documentation of social determinants of health-related problems among surgical patients may facilitate improved risk stratification, perioperative planning, and clinical outcomes.