Predicting Provider Workload Using Predicted Patient Risk Score and Social Determinants of Health in Primary Care Setting.

BACKGROUND: Provider burnout due to workload is a significant concern in primary care settings. Workload for primary care providers encompasses both scheduled visit care and non-visit care interactions. These interactions are highly influenced by patients' health conditions or acuity, which can be measured by the Adjusted Clinical Group (ACG) score. However, new patients typically have minimal health information beyond social determinants of health (SDOH) to determine ACG score. OBJECTIVES: This study aims to assess new patient workload by first predicting the ACG score using SDOH, age, and gender and then using this information to estimate the number of appointments (scheduled visit care) and non-visit care interactions. METHODS: Two years of appointment data were collected for patients who had initial appointment requests in the first year and had the ACG score, appointment, and non-visit care counts in the subsequent year. State-of-art machine learning algorithms were employed to predict ACG scores and compared with current baseline estimation. Linear regression models were then used to predict appointments and non-visit care interactions, integrating demographic data, SDOH, and predicted ACG scores. RESULTS: The machine learning methods showed promising results in predicting ACG scores. Besides the decision tree, all other methods performed at least 9% better in accuracy than the baseline approach which had an accuracy of 78%. Incorporating SDOH and predicted ACG scores also significantly improved the prediction for both appointments and non-visit care interactions. The R 2 values increased by 95.2 and 93.8%, respectively. Furthermore, age, smoking tobacco, family history, gender, usage of injection birth control, and ACG were significant factors for determining appointments. SDOH factors such as tobacco usage, physical exercise, education level, and group activities were strongly correlated with non-visit care interactions. CONCLUSION: The study highlights the importance of SDOH and predicted ACG scores in predicting provider workload in primary care settings.

"My Health, My Right:" There Is More to It than Meets the Eye.

The WHO's World Health Day 2024 slogan, "My health, my right," has been unpacked through the lens of an evolving social epidemiological understanding. The operative part of the theme merely reiterates international positions that have been established for a long and is unable to adequately incorporate advances in the understanding of the central role that structural determinants play in the production of ill-health. Given the urgency of addressing Sustainable Development Goal and Universal Health Coverage goals, the reduction of health inequities through the promotion of social justice is as much a governance imperative as moral.

Race and Ethnicity, Socioeconomic Factors, and Epigenetic Age Acceleration in Survivors of Childhood Cancer.

Importance: Current research in epigenetic age acceleration (EAA) is limited to non-Hispanic White individuals. It is imperative to improve inclusivity by considering racial and ethnic minorities in EAA research. Objective: To compare non-Hispanic Black with non-Hispanic White survivors of childhood cancer by examining the associations of EAA with cancer treatment exposures, potential racial and ethnic disparity in EAA, and mediating roles of social determinants of health (SDOH). Design, Setting, and Participants: In this cross-sectional study, participants were from the St Jude Lifetime Cohort, which was initiated in 2007 with ongoing follow-up. Eligible participants included non-Hispanic Black and non-Hispanic White survivors of childhood cancer treated at St Jude Children's Research Hospital between 1962 and 2012 who had DNA methylation data. Data analysis was conducted from February 2023 to May 2024. Exposure: Three treatment exposures for childhood cancer (chest radiotherapy, alkylating agents, and epipodophyllotoxin). Main Outcomes and Measures: DNA methylation was generated from peripheral blood mononuclear cell-derived DNA. EAA was calculated as residuals from regressing Levine or Horvath epigenetic age on chronological age. SDOH included educational attainment, annual personal income, and the socioeconomic area deprivation index (ADI). General linear models evaluated cross-sectional associations of EAA with race and ethnicity (non-Hispanic Black and non-Hispanic White) and/or SDOH, adjusting for sex, body mass index, smoking, and cancer treatments. Adjusted least square means (ALSM) of EAA were calculated for group comparisons. Mediation analysis treated SDOH as mediators with average causal mediation effect (ACME) calculated for the association of EAA with race and ethnicity. Results: Among a total of 1706 survivors including 230 non-Hispanic Black survivors (median [IQR] age at diagnosis, 9.5 [4.3-14.3] years; 103 male [44.8%] and 127 female [55.2%]) and 1476 non-Hispanic White survivors (median [IQR] age at diagnosis, 9.3 [3.9-14.6] years; 766 male [51.9%] and 710 female [48.1%]), EAA was significantly greater among non-Hispanic Black survivors (ALSM = 1.41; 95% CI, 0.66 to 2.16) than non-Hispanic White survivors (ALSM = 0.47; 95% CI, 0.12 to 0.81). Among non-Hispanic Black survivors, EAA was significantly increased among those exposed to chest radiotherapy (ALSM = 2.82; 95% CI, 1.37 to 4.26) vs those unexposed (ALSM = 0.46; 95% CI, -0.60 to 1.51), among those exposed to alkylating agents (ALSM = 2.33; 95% CI, 1.21 to 3.45) vs those unexposed (ALSM = 0.95; 95% CI, -0.38 to 2.27), and among those exposed to epipodophyllotoxins (ALSM = 2.83; 95% CI, 1.27 to 4.40) vs those unexposed (ALSM = 0.44; 95% CI, -0.52 to 1.40). The association of EAA with epipodophyllotoxins differed by race and ethnicity (ß for non-Hispanic Black survivors, 2.39 years; 95% CI, 0.74 to 4.04 years; ß for non-Hispanic White survivors, 0.68; 95% CI, 0.05 to 1.31 years) and the difference was significant (1.77 years; 95% CI, 0.01 to 3.53 years; P for interaction = .049). Racial and ethnic disparities in EAA were mediated by educational attainment (

Using community-based participatory research methods to build the foundation for an equitable integrated health data system within a Canadian urban context.

Health inequalities amplified by the COVID-19 pandemic have disproportionately affected racialized and equity-deserving communities across Canada. In the Municipality of Peel, existing data, while limited, illustrates that individuals from racialized and equity-deserving communities continue to suffer, receive delayed care, and die prematurely. In response to these troubling statistics, grassroots community advocacy has called on health systems leaders in Peel to work with community and non-profit organizations to address the critical data and infrastructure gaps that hinder addressing the social determinants of health in the region. To support these advocacy efforts, we used a community-based participatory research approach to understand how we might build a data collection ecosystem across sectors, alongside community residents and service providers, to accurately capture the data about the social determinants of health. This approach involved developing a community engagement council, defining the problem with the community, mapping what data is actively collected and what is excluded, and understanding experiences of sociodemographic data collection from community members and service providers. Guided by community voices, our study focused on sociodemographic data collection in the primary care context and identified which service providers use and collect these data, how data are used in their work, the facilitators and barriers to data use and collection. Additionally, we gained insight into how sociodemographic data collection could be respectful, safe, and properly governed from the perspectives of community members. From this study, we identify a set of eight recommendations for sociodemographic data collection and highlight limitations. This foundational community-based work will inform future research in establishing data governance in partnership with diverse and equity-deserving communities.

Case-Based Specialty Training for Medical Students to Elicit Social Determinants of Health.

Introduction: Without explicit education and training on how social determinants of health (SDoH) impact patient care and health outcomes, medical schools are failing to effectively equip future physicians to serve their patients. We created this workshop on health equity with a focus on SDoH to help students more effectively communicate with diverse populations. Methods: Third-year medical students and faculty were provided with class guides, learning objectives, role-play vignettes containing clerkship-specific history and physical exams, schedules, and discussion questions during a 2-hour session centered on SDoH. The workshop's impact was measured through mixed-methods analysis of surveys. Results: Based on pre- and postsurvey results from 87 participants, medical students strongly agreed that (1) SDoH factor more into a patient's health outcomes than the clinical encounter (pre: 67%, post: 87%), (2) it is their duty to gather information about SDoH (pre: 86%, post: 97%), (3) neighborhood safety is one of the key SDoH (pre: 88%, post: 97%), (4) they understood the impact of upstream interventions (pre: 35%, post: 93%), (5) they could efficiently screen all patients for SDoH at every medical encounter (pre: 27%, post: 86%), and (6) they could find preliminary resources to quickly assist patients in need of help regarding particular SDoH (pre: 26%, post: 85%). Discussion: This was the first iteration of this workshop; challenges involved piloting the content, time restraints, and organizational structure of the workshop design. Future directions include making SDoH curricula an integral part of undergraduate medical education and diverse clinical environments.

The Community Health Advocacy Initiative: A Longitudinal Experiential Curriculum in Community Engagement for Preclerkship Medical Students.

Introduction: Community partnership is a key strategy for addressing the social determinants of health and achieving health equity. There are few examples of curricula for undergraduate medical education that teach all, rather than self-selected, medical students to collaborate with community members to improve health. We describe the design and implementation of the Community Health Advocacy Initiative (CHAI) curriculum, a new yearlong educational program for medical students at Northwestern University's Feinberg School of Medicine. Methods: CHAI aimed to fill the curricular gap in social determinants of health education by providing medical students with the knowledge and skills to improve the health of patients through collaborations with community partners. This longitudinal curriculum included structured faculty mentorship and an applied community experience. Results: The CHAI curriculum was delivered to 164 second-year medical students in academic year 2021-2022. Faculty mentors rated most students as meeting expectations for application of community partnership principles and demonstration of professionalism. Qualitative analysis of faculty mentor comments demonstrated that medical students exhibited positive outcomes in engaging with community organizations, overcoming barriers, developing feasible and impactful goals, and advancing their own knowledge and skills. Discussion: Implementing a community health curriculum for all medical students is feasible and represents an important model for teaching about the importance of community partnerships in addressing the social determinants of health.

Racial and social inequities in medication use: A review of articles responding to the Journal of Managed Care + Specialty Pharmacy's Call to Action.

This article provides a summary of Viewpoint and Research articles responding to the 2020 Journal of Managed Care + Specialty Pharmacy Call to Action to address racial and social inequities in medication use. We find great heterogeneity in terms of topic, clinical condition examined, and health disparity addressed. Common recommendations across Viewpoint articles include the need to increase racial and ethnic diversity in clinical trial participants, the need to address drug affordability and health insurance literacy, and the need to incentivize providers and plans to participate in diversity initiatives, such as the better capture of information on social determinants of health (SDOH) in claims data to be able to address SDOH needs. Across research articles, we also find a large range of approaches and study designs, spanning from randomized controlled trials to surveys to observational studies. These articles identify disparities in which minoritized beneficiaries are shown to be less likely to receive medications and vaccines, as well as less likely to be adherent to medications, across a variety of conditions. Finally, we discuss Healthy People 2030 as a potential framework for future health disparity researchers.

What Would Equitable Harm Reduction Look Like?

Structural determinants of health frameworks must express antiracism to be effective, but racial and ethnic inequities are widely documented, even in harm reduction programs that focus on person-centered interventions. Harm reduction strategies should express social justice and health equity, resist stigma and discrimination, and mitigate marginalization experiences among people who use drugs (PWUD). To do so, government and organizational policies that promote harm reduction must acknowledge historical and ongoing patterns of racializing drug use. This article gives examples of such racialization and offers recommendations about how harm reduction programming can most easily and effectively motivate equitable, antiracist care for PWUD.

Assessment of adherence to treatment recommendations among patients with heart failure: a cross-sectional study.

BACKGROUND: Heart failure (HF) is a chronic condition characterized by significant impairment of the cardiovascular system, leading to a decline in health-related quality of life, recurrent hospitalizations, and increased mortality risk. It poses a substantial challenge for modern medicine, particularly when patients fail to adhere to therapeutic recommendations. The primary aim of this study was to evaluate the level of adherence to therapeutic guidelines among patients with HF and identify factors influencing adherence levels. METHODS: The study comprised 105 HF patients admitted to the cardiology department. A diagnostic survey approach was utilized, employing the Adherence in Chronic Diseases Scale (ACDS) along with a self-developed questionnaire. RESULTS: The findings revealed that 39.05% of participants exhibited a moderate level of adherence to therapeutic recommendations, while 34.29% reported high adherence and 26.67% displayed low adherence. Most of the patients (n = 66) had a rather good level of knowledge. Factors such as higher education (p < 0.001), engagement in mental work (p = 0.001), favorable socioeconomic status (p < 0.001), being in a stable relationship (p < 0.001), and residing with family (p < 0.001) were associated with increased adherence levels. The multivariable linear regression model indicated significant (p < 0.05) independent predictors that positively influenced the ACDS score, including being in a relationship, widowhood, and average or poor financial situation. Conversely, factors such as obesity and respiratory diseases were associated with a decrease in the ACDS score (p < 0.05). CONCLUSIONS: This study underscores the moderate adherence level to therapeutic recommendations among HF patients. Sociodemographic factors including education level, relationship status, occupation, financial stability, and living arrangements significantly impact adherence. Conversely, patients with obesity, respiratory conditions, or frequent HF-related hospitalizations demonstrate lower adherence. Patient education emerges as a pivotal factor influencing adherence. Tailored interventions targeting these factors could enhance adherence and optimize HF management outcomes.

Estudio de prevalencia, conocimiento y control de la hipertensión arterial en barrios vulnerables de Argentina / Prevalence, knowledge and control of arterial hypertension in vulnerable neighborhoods of Argentina: A Cross-sectional Study

Introducción: La hipertensión arterial (HTA) representa el principal factor de riesgo individual, con mayor carga a nivel mundial de enfermedades cardiovasculares (ECV). En nuestro país, algunos trabajos epidemiológicos han mostrado marcadas diferencias en las prevalencias de estos factores de riesgo de acuerdo con la población evaluada. Sin embargo, no hay estudios epidemiológicos de evaluación de factores de riesgo cardiovascular exclusivos referentes a barrios vulnerables con muy bajos recursos económicos, socioculturales y poca accesibilidad a los sistemas de salud. Materiales y métodos: Estudio observacional de corte transversal multicéntrico en habitantes de comunas vulnerables de muy bajos recursos, como asentamientos populares y barrios carenciados con muestreo aleatorizado simple de casas. Se realizaron tomas de presión arterial (PA), medidas antropométricas, así como cuestionarios epidemiológicos, económicos y socioculturales. Se describen los hallazgos: prevalencia, conocimiento y control de la PA en las distintas regiones. Se efectuó una regresión logística para determinar las variables independientes a los resultados principales. Resultados: Se analizaron 989 participantes. La prevalencia de HTA global fue de 48,2%. Un total de 82% tenía un índice de masa corporal (IMC) >25 kg/m2. De estos pacientes, 45,3% tenían menos de seis años de educación. Este último aspecto se asoció a mayor prevalencia de HTA de forma independiente. De los hipertensos, 44% desconocían su padecimiento y solo en 17,2% estaba controlado, asociándose esto a tener obra social (OS) y mayor nivel educativo. Únicamente 24% estaban bajo tratamiento combinado. Conclusión: La prevalencia de HTA en barrios vulnerables es elevada, superando a la de otros estratos sociales con niveles de conocimiento, tratamiento y control de la HTA bajos, similar a otras poblaciones. Se detectó un uso insuficiente de la terapia combinada.

Introduction: Hypertension (HTN) represents the primary individual risk factor, contributing significantly to the global burden of cardiovascular diseases (CVD). In our country, epidemiological research has highlighted substantial variations in the prevalence of these risk factors across different populations. However, there is a lack of epidemiological studies assessing exclusive cardiovascular risk factors within vulnerable neighborhoods characterized by extremely limited economic resources, sociocultural challenges, and inadequate healthcare access. Methods: A multicenter cross-sectional observational study was conducted among individuals residing in economically deprived and marginalized communities, including informal settlements and underprivileged neighborhoods. Simple random sampling of households was employed. Blood pressure measurements, anthropometric assessments, and epidemiological, economic, and sociocultural questionnaires were administered. Results encompass prevalence rates, awareness levels, and blood pressure control across diverse regions. Logistic regression was utilized to identify independent variables influencing primary outcomes. Results: A total of 989 participants were analyzed. The overall prevalence of hypertension was 48.2%. About 82% had a body mass index (BMI) >25. Approximately 45.3% had less than 6 years of formal education. Independent association was established between education levels below 6 years and higher hypertension prevalence Among hypertensive individuals, 44% were unaware of their condition, with only 17.2% achieving control, correlated with having health insurance and a higher educational background. Merely 24% were receiving combined therapy. Conclusion: The prevalence of hypertension within vulnerable neighborhoods is alarmingly high, surpassing rates in other social strata. Knowledge, treatment, and control levels of hypertension are suboptimal, comparable to other populations... (AU)

Clustering of Social Determinants of Health as an Indicator of Meaningful Subgroups within an African American Population: Application of Latent Class Analysis.

BACKGROUND: Health disparities between people who are African American (AA) versus their White counterparts have been well established, but disparities among AA people have not. The current study introduces a systematic method to determine subgroups within a sample of AA people based on their social determinants of health. METHODS: Health screening data collected in the West Side of Chicago, an underserved predominantly AA area, in 2018 were used. Exploratory latent class analysis was used to determine subgroups of participants based on their responses to 16 variables, each pertaining to a specific social determinant of health. RESULTS: Four unique clusters of participants were found, corresponding to those with "many unmet needs", "basic unmet needs", "unmet healthcare needs", and "few unmet needs". CONCLUSION: The findings support the utility of analytically determining meaningful subgroups among a sample of AA people and their social determinants of health. Understanding the differences within an underserved population may contribute to future interventions to eliminate health disparities.

Charting a Path to the Quintuple Aim: Harnessing AI to Address Social Determinants of Health.

The Quintuple Aim seeks to improve healthcare by addressing social determinants of health (SDOHs), which are responsible for 70-80% of medical outcomes. SDOH-related concerns have traditionally been addressed through referrals to social workers and community-based organizations (CBOs), but these pathways have had limited success in connecting patients with resources. Given that health inequity is expected to cost the United States nearly USD 300 billion by 2050, new artificial intelligence (AI) technology may aid providers in addressing SDOH. In this commentary, we present our experience with using ChatGPT to obtain SDOH management recommendations for archetypal patients in Philadelphia, PA. ChatGPT identified relevant SDOH resources and provided contact information for local organizations. Future exploration could improve AI prompts and integrate AI into electronic medical records to provide healthcare providers with real-time SDOH recommendations during appointments.

The Dynamic Relationship between Social Cohesion and Urban Green Space in Diverse Communities: Opportunities and Challenges to Public Health.

Social cohesion is a key factor within social determinants of health and well-being. Urban green spaces can provide environments that potentially facilitate meaningful and positive social interactions that promote social cohesion, equity, human health, and well-being. However, the lack of integration of existing research on social cohesion, urban green spaces, and public health in diverse (e.g., racially and ethnically) communities limits culturally relevant strategies to address health disparities. In this manuscript, we synthesize research on the potential of urban green spaces to promote social cohesion and public health in historically excluded communities. Particularly, we explore the development of social cohesion as it relates to the social environment, built environment, leisure opportunities, green space maintenance, safety, and green gentrification. We highlight key factors and their application to meet opportunities and challenges to social and public health. A conceptual framework is presented to provide an overview and illustrate connections found in the literature.

Prevalence and socio-economic determinants of growth and developmental delays among Iranian children aged under five years: A cross sectional study.

BACKGROUND: The main cause of growth and development delays remains unknown, but it can occur as an interaction between genetic, environmental, and socio-economic factors. OBJECTIVE: The aim of the study was to investigate the prevalence and social determinants of growth and developmental delays among children aged under five years in Qazvin, Iran. METHODS: A cross-sectional study was conducted between January 2019 to December 2020 with participation of 1800 mothers with children aged 4-60 months who were referred to comprehensive health centers in Qazvin city, Iran. Structural and intermediate social determinants of health were assessed including: parents and children socio-demographic characteristics, families' living and economic status, parents' behavioral factors, household food security, mother's general health, and perceived social support. Children's growth was assessed based on their anthropometric assessment and their development was assessed using their age-specific Ages and Stages Questionnaire. Data were analyzed using univariable and multivariable logistic regression models using SPSS software version 24 and Stata version 14. RESULTS: The prevalence of developmental problems in each domain were 4.28% for personal and social delay, 5.72% for gross motor delay, 6.5% for communication delay, 6.72% for fine motor delay, and 8% for problem-solving delay. The prevalence of weight growth delays was 13.56% and height growth delays was 4.66%. Communication, gross motor, and problem-solving delays were higher among children whose fathers' smoked cigarettes. Fine motor delays were lower among mothers with education status of high school diploma and university degree vs. the under diploma group. Personal and social delay was significantly higher among families with fair economic status and lower among children when their fathers were employed (vs. unemployed). Weight and height growth delays were higher among mothers who had experienced pregnancy complications and household food insecure families, respectively. CONCLUSION: There are different predictors of growth and developmental delay problems among Iranian children aged under five years including fathers' smoking, families' economic status, and household food insecurity as well as history of mothers' pregnancy complications. The present study's findings can be used to screen for at-risk of growth and developmental delays among children and could help in designing and implementation of timely interventions.

Impact of Social Determinants of Health on Predictive Models for Outcomes After Congenital Heart Surgery.

BACKGROUND: Despite documented associations between social determinants of health and outcomes post-congenital heart surgery, clinical risk models typically exclude these factors. OBJECTIVES: The study sought to characterize associations between social determinants and operative and longitudinal mortality as well as assess impacts on risk model performance. METHODS: Demographic and clinical data were obtained for all congenital heart surgeries (2006-2021) from locally held Congenital Heart Surgery Collaborative for Longitudinal Outcomes and Utilization of Resources Society of Thoracic Surgeons Congenital Heart Surgery Database data. Neighborhood-level American Community Survey and composite sociodemographic measures were linked by zip code. Model prediction, discrimination, and impact on quality assessment were assessed before and after inclusion of social determinants in models based on the 2020 Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model. RESULTS: Of 14,173 total index operations across New York State, 12,321 cases, representing 10,271 patients at 8 centers, had zip codes for linkage. A total of 327 (2.7%) patients died in the hospital or before 30 days, and 314 children died by December 31, 2021 (total n = 641; 6.2%). Multiple measures of social determinants of health explained as much or more variability in operative and longitudinal mortality than clinical comorbidities or prior cardiac surgery. Inclusion of social determinants minimally improved models' predictive performance (operative: 0.834-0.844; longitudinal 0.808-0.811), but significantly improved model discrimination; 10.0% more survivors and 4.8% more mortalities were appropriately risk classified with inclusion. Wide variation in reclassification was observed by site, resulting in changes in the center performance classification category for 2 of 8 centers. CONCLUSIONS: Although indiscriminate inclusion of social determinants in clinical risk modeling can conceal inequities, thoughtful consideration can help centers understand their performance across populations and guide efforts to improve health equity.

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.

Estimating the causal effects of income on health: how researchers' definitions of "income" matter.

BACKGROUND: There is a well-established cross-sectional association between income and health, but estimates of the causal effects of income vary substantially. Different definitions of income may lead to substantially different empirical results, yet research is often framed as investigating "the effect of income" as if it were a single, easily definable construct. METHODS/RESULTS: The aim of this paper is to introduce a taxonomy for definitional and conceptual issues in studying individual- or household-level income for health research. We focus on (1) the definition of the income measure (earned and unearned; net, gross, and disposable; real and nominal; individual and household; relative and absolute income) and (2) the definition of the causal contrast (amount, functional form assumptions/transformations, direction, duration of change, and timing of exposure and follow-up). We illustrate the application of the taxonomy to four examples from the published literature. CONCLUSIONS: Quantified estimates of causal effects of income on health and wellbeing have crucial relevance for policymakers to anticipate the consequences of policies targeting the social determinants of health. However, much prior evidence has been limited by lack of clarity in distinguishing between different causal questions. The present framework can help researchers explicitly and precisely articulate income-related exposures and causal questions.

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.