Demographics and Social Factors Associated With Persistent Nonuse of Video Appointments at a Multisite Health Care Institution: Cross-Sectional Study.

BACKGROUND: During the COVID-19 outbreak, video appointments became a popular method for health care delivery, particularly in the early stages of the pandemic. Although Mayo Clinic aimed to reduce face-to-face (F2F) appointments to prevent the spread of the virus, some patients continued seeing their health care providers in person. In the later stages of the pandemic, many patients became comfortable with video appointments, even if they were initially hesitant. However, a subset of patients continued to avoid video appointments. It is not yet clear what sociodemographic factors may be associated with this group of patients. OBJECTIVE: This cross-sectional study aimed to examine demographic and social determinant of health (SDoH) factors associated with persistent nonusers of video appointments among a sample of patients within a multistate health care organization. We also explored patient beliefs about the use of video for health care appointments. METHODS: We conducted a 1-time cross-sectional paper survey, mailed between July and December 2022, of patients matching the eligibility criteria: (1) aged ≥18 years as of April 2020, (2) Mayo Clinic Midwest, Florida, or Arizona patient, (3) did not use video appointment services during April-December 2020 but attended F2F appointments in the departments of primary care and psychiatry/psychology. The survey asked patients, "Have you ever had a video appointment with a healthcare provider?" "Yes" respondents were defined as "users" (adapted to video appointments), and "no" respondents were defined as "persistent nonusers" of video appointments. We analyzed demographics, SDoH, and patient beliefs toward video appointments in 2 groups: persistent nonusers of video appointments and users. We used chi-square and 2-tailed t tests for analysis. RESULTS: Our findings indicate that patients who were older, lived in rural areas, sought care at Mayo Clinic Midwest, and did not have access to the patient portal system were likely to be persistent nonusers of video appointments. Only 1 SDoH factor (not having a disability, handicap, or chronic disease) was associated with persistent nonuse of video appointments. Persistent nonusers of video appointments held personal beliefs such as discomfort with video communication, difficulty interpreting nonverbal cues, and personal preference for F2F appointments over video. CONCLUSIONS: Our study identified demographic (older age and rural residence), sociodemographic factors (not having a disability, handicap, or chronic disease), and personal beliefs associated with patients' decisions to choose between video versus F2F appointments for health care delivery. Health care institutions should assess patients' negative attitudes toward technology prior to introducing them to digital health care services. Failing to do so may result in its restricted usage, negative patient experience, and wasted resources. For patients who hold negative beliefs about technology but are willing to learn, a "digital health coordinator" could be assigned to assist with various digital health solutions.

Health Disparities in Multiple Sclerosis among Hispanic and Black Populations in the United States.

Multiple sclerosis (MS) is an acquired demyelinating disease of the central nervous system (CNS). Historically, research on MS has focused on White persons with MS. This preponderance of representation has important possible implications for minority populations with MS, from developing effective therapeutic agents to understanding the role of unique constellations of social determinants of health. A growing body of literature involving persons of historically underrepresented races and ethnicities in the field of multiple sclerosis is assembling. Our purpose in this narrative review is to highlight two populations in the United States: Black and Hispanic persons with multiple sclerosis. We will review the current understanding about the patterns of disease presentation, genetic considerations, response to treatment, roles of social determinants of health, and healthcare utilization. In addition, we explore future directions of inquiry as well as practical methods of meeting these challenges.

Neighborhood-level COVID vaccination and booster disparities: A population-level analysis across California.

Objectives: To describe vaccine and booster uptake by neighborhood-level factors in California. Methods: We examined trends in COVID-19 vaccination up to September 21, 2021, and boosters up to March 29, 2022 using data from the California Department of Public Health. Quasi-Poisson regression was used to model the association between neighborhood-level factors and fully vaccinated and boosted among ZIP codes. Sub-analyses on booster rates were compared among the 10 census regions. Results: In a minimally adjusted model, a higher proportion of Black residents was associated with lower vaccination (HR = 0.97; 95%CI: 0.96-0.98). However, in a fully adjusted model, proportion of Black, Hispanic/Latinx, and Asian residents were associated with higher vaccination rates (HR = 1.02; 95%CI: 1.01-1.03 for all). The strongest predictor of low vaccine coverage was disability (HR = 0.89; 95%CI: 0.86-0.91). Similar trends persisted for booster doses. Factors associated with booster coverage varied by region. Conclusions: Examining neighborhood-level factors associated with COVID-19 vaccination and booster rates uncovered significant variation within the large and geographically and demographically diverse state of California. Equity-based approaches to vaccination must ensure a robust consideration of multiple social determinants of health.

Neighborhood deprivation and morbid obesity: Insights from the Houston Methodist Cardiovascular Disease Health System Learning Registry.

This study examined the relationship between a validated measure of socioeconomic deprivation, such as the Area Deprivation Index (ADI), and morbid obesity. We used cross-sectional data on adult patients (≥18 years) in the Houston Methodist Cardiovascular Disease Health System Learning Registry (located in Houston, Texas, USA) between June 2016 and July 2021. Each patient was grouped by quintiles of ADI, with higher quintiles signaling greater deprivation. BMI was calculated using measured height and weight with morbid obesity defined as ≥ 40 kg/m2. Multivariable logistic regression models were used to examine the association between ADI and morbid obesity adjusting for demographic (age, sex, and race/ethnicity) factors. Out of the 751,174 adults with an ADI ranking included in the analysis, 6.9 % had morbid obesity (n = 51,609). Patients in the highest ADI quintile had a higher age-adjusted prevalence (10.9 % vs 3.3 %), and about 4-fold odds (aOR, 3.8; 95 % CI = 3.6, 3.9) of morbid obesity compared to the lowest ADI quintile. We tested for and found interaction effects between ADI and each demographic factor, with stronger ADI-morbid obesity association observed for patients that were female, Hispanic, non-Hispanic White and 40-65 years old. The highest ADI quintile also had a high prevalence (44 %) of any obesity (aOR, 2.2; 95 % CI = 2.1, 2.2). In geospatial mapping, areas with higher ADI were more likely to have higher proportion of patients with morbid obesity. Census-based measures, like the ADI, may be informative for area-level obesity reduction strategies as it can help identify neighborhoods at high odds of having patients with morbid obesity.

A qualitative inquiry into the patient-related barriers to linkage and retention in HIV care within the community setting.

Background: People with the Human Immunodeficiency Virus (PWH) experience barriers to care within the community that impedes their progress from when they discover that they are HIV positive to becoming virally suppressed. For individuals with HIV to achieve sustained viral suppression, they must be linked to care to start receiving anti-retroviral therapy and remain retained in care for continuous treatment. However, HIV surveillance data shows that many PWH are not linked to care and become lost to continuous follow-up care. Although pharmacists, PWH, and social workers interact with one another and are aware of their roles in HIV care, their perspectives on barriers to linkage and retention in care have not been investigated collectively. Objectives: Explore the perspectives of PWH, pharmacists, and social workers on barriers to linkage and retention of HIV care within the community setting. Methods: Convenience sampling was used to recruit 15 stakeholders (five PWH, five community pharmacists, and five social workers) who participated in 1-h, semi-structured interviews based on three domains of the Patient-centered Medical Home Model including (1) experiences (individual and system-level barriers to care experienced by PWH), (2) activities (social workers and pharmacists initiatives that impact adherence to care)and (3) interventions (critical issues pharmacists can address in the community to engage PWH in their HIV care). We conducted a directed content analysis based on deductive coding. To establish rigor, we focused on Lincoln and Guba's criteria of rigorous qualitative methodology: credibility, dependability, confirmability, and transferability. Similarities and divergences of themes were discussed during data analysis and agreement was reached before interpretation. Results: Emergent themes uncovered barriers to linkage and retention in HIV care as HIV-related stigma, having mental health illnesses including a history of substance abuse and social determinants of health such as homelessness, food insecurity, and insurance issues. Conclusion: The perspectives of pharmacists, social workers, and PWH can provide insight into barriers that should be identified and addressed in people living with HIV to enhance their linkage and retention in care.

Impact of a mobile integrated healthcare and community paramedicine program on improving medication adherence in patients with heart failure and chronic obstructive pulmonary disease after hospital discharge: A pilot study.

Background: The mobile integrated health-community paramedicine (MIH-CP) program affiliated with the University of Maryland Medical Center focuses on improving patient transitions from hospital to home by addressing both medical and social determinants of health. Until recently, only self-contained health systems could integrate inpatient and outpatient medication data. Without some means to track patients in transition, there is a significant risk of medication-related problems and errors. Objective: To evaluate the impact of the MIH-CP program on medication adherence among patients with congestive heart failure (CHF) and/or chronic obstructive pulmonary disease (COPD). Methods: This is a pilot observational study designed to compare adherence to drug regimens prescribed at hospital discharge (measured by the proportion of days covered [PDC]) between patients enrolled in the MIH-CP program and a propensity-matched control group. Propensity scores were calculated using 11 demographic, diagnostic, third-party payer, and patient care-associated variables. Discharge medication details were obtained from electronic medical records. PDC for each of the medications were calculated from pharmacy claims data. Results: Eighty-three patients were included in the study; forty-three patients were placed in the intervention group and 40 were propensity-matched controls. After adjusting for age, sex, and third-party payer, findings indicated that medication adherence was higher among patients enrolled in the MIH-CP program compared with control during the first 30 days post-discharge, specifically among patients diagnosed with CHF (8% difference in PDC, 95% confidence interval [CI], -0.12-0.28%) and COPD (14% difference, 95% CI, -0.15-0.43%), although neither result achieved statistical significance. The differences in medication adherence between patients who were enrolled and those who were not enrolled in the MIH-CP program diminished after 30 days post-discharge. Conclusion: This pilot study demonstrated a trend toward improved medication adherence among patients enrolled in the MIH-CP program. Future research involving a larger patient cohort will be required to confirm these preliminary findings.

Disparities in Morbidity After Spinal Cord Injury Across Insurance Types in the United States.

Objective: To compare the prevalence and incidence of, and adjusted hazards for comorbidities among adults with traumatic spinal cord injuries (TSCIs) across insurance types (private vs governmental insurance) in the United States. Patients and Methods: Privately insured (N=9081) and Medicare (N=7645) beneficiaries with a diagnosis of TSCI were included. Prevalence and incidence estimates of common psychological, cardiometabolic, and musculoskeletal morbidities were compared at baseline and at 4-years after index diagnosis, respectively. Survival models were used to quantify hazard ratios (HRs) for outcomes, controlling for insurance type, sociodemographic characteristics, and other comorbidities. Sensitivity analyses were conducted to determine the effects of insurance and race/ethnicity. Results: Adults with TSCIs on Medicare had a higher prevalence of any psychological (54.7% vs 35.4%), cardiometabolic (74.7% vs 70.1%), and musculoskeletal (72.8% vs 66.3%) morbidity than privately insured adults with TSCIs. Similarly, the 4-year incidences of most psychological (eg, depression: 37.6% [Medicare] vs 24.2% [private]), cardiometabolic (eg, type 2 diabetes: 22.5% [Medicare] vs 12.9% [private], and musculoskeletal (eg, osteoarthritis: 42.1% [Medicare] vs 34.6% [private]) morbidities were considerably higher among adults with TSCIs on Medicare. Adjusted survival models found that adults with TSCIs on Medicare had a greater hazard for developing psychological (HR, 1.40; 95% CI, 1.31-1.50) and cardiometabolic (HR, 1.21; 95% CI, 1.10-1.33) morbidities compared with privately insured adults with TSCI. There was evidence of both insurance and racial disparities. Conclusion: Adults with TSCIs on Medicare had significantly higher prevalence and risk for developing common physical and mental health comorbidities, compared with privately insured adults with TSCIs.

Post-9/11 veterans perceptions of the pandemic: Areas of greatest impact on health and well-being.

Objective: Assess potential impacts of the COVID-19 pandemic on a subset of Post-9/11 U.S. Veterans included in a study of post-traumatic epilepsy (PTE). Methods: Two measures were added to a structured health interview for Veterans during temporary pandemic research shutdown: a validated health questionnaire [1] previously completed by survey, and a semi-structured instrument developed to assess whether pandemic conditions affected responses to the health questionnaire and identify unique impacts. Interviews were conducted between August 2020 - February 2021. Scaled items were calculated and t-tests used to compare results. Open-ended items were coded using thematic analyses. Results: Veterans identified eight major areas of impact with negative and positive impacts: mental health, family, social, work/employment, access to resources, physical health, finances, and education. Innovation: The temporary shut-down of a large health study for Post-9/11 Veterans provided an opportunity to devise an instrument to assess COVID-19's impact on health and well-being. The instrument was accepted as of the first Veteran instrument in a pandemic SDOH research repository [2], and is being used in other studies. Conclusion: This study highlights the need to assess and understand interrelated relationships of factors impacting health and well-being, especially as COVID-19 moves from pandemic to endemic with reverberating effects across multiple social determinants of health (SDOH).

Community-based participatory research application of an artificial intelligence-enhanced electrocardiogram for cardiovascular disease screening: A FAITH! Trial ancillary study.

Objective: With the emergence of artificial intelligence (AI)-based health interventions, systemic racism remains a concern as these advancements are frequently developed without race-specific data analysis or validation. To evaluate the potential utility of an AI-based cardiovascular diseases (CVD) screening tool in an under-resourced African-American cohort, we reviewed the AI-enhanced electrocardiogram (ECG) data of participants enrolled in a community-based clinical trial as a proof-of-concept ancillary study for community-based screening. Methods: Enrollees completed cardiovascular testing including standard 12-lead ECG and a limited echocardiogram (TTE). All ECGs were analyzed using previously published institution-based AI algorithms. AI-ECG predictions were generated for age, sex, and decreased left ventricular ejection fraction (LVEF). Diagnostic accuracy of the AI-ECG for decreased LVEF and sex was quantified using area under the receiver operating characteristic curve (AUC). Correlation between actual age and AI-ECG predicted age was assessed using Pearson correlation coefficients. Results: Fifty-four participants completed both an ECG and TTE (mean age 55 years [range 31-87 years]; 66.7% female). All participants were in sinus rhythm, and the median LVEF of the cohort was 60-65%. The AI-ECG for decreased LVEF demonstrated excellent performance with an AUC of 0.892 (95% confidence interval [CI] 0.708-1); sensitivity=50% (95% CI 9.5-90.5%; n=1/2) and specificity=96% (95% CI 86.8-98.9%; n=49/51). The AI-ECG for participant sex demonstrated similar performance with AUC of 0.944 (95% CI 0.891-0.998); sensitivity=100% (95% CI 82.4-100.0%; n=18/18) and specificity=77.8% (95% CI 61.9-88.3%; n=28/36). The AI-ECG predicted mean age was 55 years (range 26.9-72.6 years) with a strong correlation to actual age (R=0.769; p<0.001). Conclusion: Our analyses of previously developed AI-ECG algorithms for prediction of age, sex, and decreased LVEF demonstrated reliable performance in this community-based, African-American cohort. This novel, community-centric delivery of AI could provide valuable screening resources and appropriate referrals for early detection of highly-morbid CVD for under-resourced patient populations.

Impact of Social Vulnerability on Comorbid Cancer and Cardiovascular Disease Mortality in the United States.

Background: Racial and social disparities exist in outcomes related to cancer and cardiovascular disease (CVD). Objectives: The aim of this cross-sectional study was to study the impact of social vulnerability on mortality attributed to comorbid cancer and CVD. Methods: The Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database (2015-2019) was used to obtain county-level mortality data attributed to cancer, CVD, and comorbid cancer and CVD. County-level social vulnerability index (SVI) data (2014-2018) were obtained from the CDC's Agency for Toxic Substances and Disease Registry. SVI percentiles were generated for each county and aggregated to form SVI quartiles. Age-adjusted mortality rates (AAMRs) were estimated and compared across SVI quartiles to assess the impact of social vulnerability on mortality related to cancer, CVD, and comorbid cancer and CVD. Results: The AAMR for comorbid cancer and CVD was 47.75 (95% CI: 47.66-47.85) per 100,000 person-years, with higher mortality in counties with greater social vulnerability. AAMRs for cancer and CVD were also significantly greater in counties with the highest SVIs. However, the proportional increase in mortality between the highest and lowest SVI counties was greater for comorbid cancer and CVD than for either cancer or CVD alone. Adults <45 years of age, women, Asian and Pacific Islanders, and Hispanics had the highest relative increase in comorbid cancer and CVD mortality between the fourth and first SVI quartiles, without significant urban-rural differences. Conclusions: Comorbid cancer and CVD mortality increased in counties with higher social vulnerability. Improved education, resource allocation, and targeted public health interventions are needed to address inequities in cardio-oncology.

Identifying individual social risk factors using unstructured data in electronic health records and their relationship with adverse clinical outcomes.

Objective: To determine the prevalence of individual-level social risk factors documented in unstructured data from electronic health records (EHRs) and the relationship between social risk factors and adverse clinical outcomes. Study setting: Inpatient encounters for adults (≥18 years) at the University of Virginia Medical Center during a 12-month study period between July 2018 and June 2019. Inpatient encounters for labor and delivery patients were excluded, as well as encounters where the patient was discharged to hospice, left against medical advice, or expired in the hospital. The study population included 21,402 inpatient admissions, representing 15,116 unique patients who had at least one inpatient admission during the study period. Study design: We identified measures related to individual social risk factors in EHRs through existing workflows, flowsheets, and clinical notes. Multivariate binomial logistic regression was performed to determine the association of individual social risk factors with unplanned inpatient readmissions, post-discharge emergency department (ED) visits, and extended length of stay (LOS). Other predictors included were age, sex, severity of illness, location of residence, and discharge destination. Results: Predictors of 30-day unplanned readmissions included severity of illness (OR = 3.96), location of residence (OR = 1.31), social and community context (OR = 1.26), and economic stability (OR = 1.37). For 30-day post-discharge ED visits, significant predictors included location of residence (OR = 2.56), age (OR = 0.60), economic stability (OR = 1.39), education (OR = 1.38), social and community context (OR = 1.39), and neighborhood and built environment (OR = 1.61). For extended LOS, significant predictors were age (OR = 0.51), sex (OR = 1.18), severity of illness (OR = 2.14), discharge destination (OR = 2.42), location of residence (OR = 0.82), economic stability (OR = 1.14), neighborhood and built environment (OR = 1.31), and education (OR = 0.79). Conclusions: Individual-level social risk factors are associated with increased risk for unplanned hospital readmissions, post-discharge ED visits, and extended LOS. While individual-level social risk factors are currently documented on an ad-hoc basis in EHRs, standardized SDoH screening tools using validated metrics could help eliminate bias in the collection of SDoH data and facilitate social risk screening.

Spatial variations and social determinants of life expectancy in China, 2005-2020: A population-based spatial panel modelling study.

Background: Social determinants of health (SDOH) produce a broad range of life expectancy (LE) disparities. In China, limited literatures were found to report association between SDOH and LE at ecological level during a consecutive period of time from the spatial perspectives. This study aimed to determine the existence, quantify the magnitude, and interpret the association between SDOH and LE in China. Methods: Provincial-level LE were estimated from mortality records during 2005-2020 from National Mortality Surveillance System in China. A spatial panel Durbin model was used to investigate LE associated SDOH proxies. Spatial spillover effects were introduced to interpret direct and indirect effects caused by SDOH during long-term and short-term period on LE disparities. Findings: Nationwide, LE increased from 73.1 (95% confidence interval (CI): 71.3, 74.4) years to 77.7 (95%CI: 76.5, 78.7) years from 2005 to 2020. Unequally spatial distribution of LE with High-High clustering in coastal areas and Low-Low clustering in western regions were observed. Locally, it was estimated that SDOH proxies statistically significant related to an increase of LE, including GDP (coefficient: 0.02, 95%CI: 0.00, 0.03), Gini index (coefficient: 2.35, 95%CI: 1.82, 2.88), number of beds in health care institutions (coefficient: 0.02, 95%CI: 0.00, 0.05) and natural growth rate of resident population (coefficient: 0.02, 95%CI: 0.01, 0.02). Direct and indirect effects decomposition during long-term and short-term of LE associated SDOH proxies demonstrated that GDP, urbanization rate, unemployment rate, education attainment, Gini index, number of beds in health care institutions, sex ratio, gross dependence ratio and natural growth rate of resident population not only affected local LE, but also exerted spatial spillover effects towards geographical neighbors. Interpretation: Spatial variations of LE existed at provincial-level in China. SDOH regarding socioeconomic development and equity, healthcare resources, as well as population characteristics not only affected LE disparities at local scale but also among nearby provinces. Externalities of policy of those SDOH proxies should be took into consideration to promote health equity nationally. Comprehensive approaches on the basis of population strategy should be consolidated to optimize supportive socioeconomic environment and narrow the regional gap to reduce health disparities and increase LE. Funding: National Key Research & Development Program of China (Grant No.2018YFC1315301); Ministry of Education of China Humanities and Social Science General Program (Grant No.18YJC790138).

Atherosclerotic cardiovascular disease risk assessment: An American Society for Preventive Cardiology clinical practice statement.

Risk for atherosclerotic cardiovascular disease (ASCVD) shows considerable heterogeneity both in generally healthy persons and in those with known ASCVD. The foundation of preventive cardiology begins with assessing baseline ASCVD risk using global risk scores based on standard office-based measures. Persons at low risk are generally recommended for lifestyle management only and those at highest risk are recommended for both lifestyle and pharmacologic therapy. Additional "risk enhancing" factors, including both traditional risk factors and novel biomarkers and inflammatory factors can be used to further assess ASCVD risk, especially in those at borderline or intermediate risk. There are also female-specific risk enhancers, social determinants of health, and considerations for high-risk ethnic groups. Screening for subclinical atherosclerosis, especially with the use of coronary calcium screening, can further inform the treatment decision if uncertain based on the above strategies. Persons with pre-existing ASCVD also have variable risk, affected by the number of major ASCVD events, whether recurrent events have occurred recently, and the presence of other major risk factors or high-risk conditions. Current guidelines define high to very high risk ASCVD accordingly. Accurate ASCVD risk assessment is crucial for the appropriate targeting of preventive therapies to reduce ASCVD risk. Finally, the clinician-patient risk discussion focusing on lifestyle management and the risks and benefits of evidence-based pharmacologic therapies to best lower ASCVD risk is central to this process. This clinical practice statement provides the preventive cardiology specialist with guidance and tools for assessment of ASCVD risk with the goal of appropriately targeting treatment approaches for prevention of ASCVD events.

Assessment of U.S. heart transplantation equity as a function of race: Observational analyses of the OPTN database.

Background: Racial disparities in heart transplantation (HT) outcomes are suspected but uncertain. The additional impact of a recent change in donor allocation on disparities in HT in the United States (US) is unknown. We hypothesize racial disparities in HT are present and may be worsened by new allocation practices. Methods: Cohort: Adults listed for HT before and after a heart allocation policy change (Era 1: Oct 18th, 2015 - Oct 18th, 2018, Era 2: Oct 18th, 2018-June 30, 2021). The primary outcome was the rate of HT by race (Black vs. White), assessed using multivariable competing risk analysis (compete: waitlist removal for death or clinical deterioration). Final adjusted models included co-morbidities, SES and community-level Social Determinants of Health. The secondary outcome was waitlist removal for death or clinical deterioration. Results: Of 17,384 waitlist candidates (Era 1: 9,150, Era 2: 8,234), Black waitlist candidates had a lower rate of HT compared to White waitlist candidates in Era 1 (adjusted HR 0·90, 95 % CI 0·84-0·97, p = 0·0053) and in Era 2 (adjusted HR 0·81, 95 % CI 0·75-0·88, p <0·0001, era race interaction p=0·056). The rate of waitlist removal for death or deterioration was similar between races in Era 1 (adjusted HR 0·92, 95 % 0·77-1·1, p = 0·38), but increased for Black candidates in Era 2 (adjusted HR 1·34, 95 % CI 1·09-1·65, p = 0·0054, era race interaction p = 0·0051). Interpretation: Both the measured rate of transplantation and rate of delisting for death or clinical deterioration have worsened for Black compared to White waitlist candidates under the new allocation system. Causes for these disparities require further study. Funding: University of Minnesota Department of Cardiology funds.

Development and validation of a polysocial risk score for atherosclerotic cardiovascular disease.

OBJECTIVE: To date, the extent to which social determinants of health (SDOH) may help identify individuals with atherosclerotic cardiovascular disease (ASCVD) - beyond traditional risk factors - has not been quantified using a cumulative social disadvantage approach. The objective of this study was to develop, and validate, a polysocial risk score (PsRS) for prevalent ASCVD in a nationally representative sample of adults in the United States (US). METHODS: We used data from the 2013-2017 National Health Interview Survey. A total of 38 SDOH were identified from the database. Stepwise and criterion-based selection approaches were applied to derive PsRS, after adjusting for traditional risk factors. Logistic regression models were fitted to assign risk scores to individual SDOH, based on relative effect size magnitudes. PsRS was calculated by summing risk scores for individual SDOH, for each participant; and validated using a separate validation cohort. RESULTS: Final sample comprised 164,696 adults. PsRS included 7 SDOH: unemployment, inability to pay medical bills, low income, psychological distress, delayed care due to lack of transport, food insecurity, and less than high school education. PsRS ranged from 0-20 and exhibited excellent calibration and discrimination. Individuals with the highest PsRS (5th quintile) had nearly 4-fold higher ASCVD prevalence, relative to those with the lowest risk scores (1st quintile). Area under receiver operating curve (AU-ROC) for PsRS with SDOH alone was 0.836. Addition of SDOH to the model with only demographic and clinical risk factors (AU-ROC=0.852) improved overall discriminatory power, with AU-ROC for final PsRS (demographics + clinical + SDOH) = 0.862. CONCLUSIONS: Cumulatively, SDOH may help identify individuals with ASCVD, beyond traditional cardiovascular risk factors. In this study, we provide a unique validated PsRS for ASCVD in a national sample of US adults. Future study should target development of similar scores in diverse populations, and incorporate longitudinal study designs.

Relationship between a comprehensive social determinants of health screening and type 2 diabetes mellitus.

Social determinants of health are conditions that influence an individual's health. Investigators explored associations between social needs and type 2 diabetes (T2DM) diagnoses through retrospective chart review (October 2017-Septemeber 2018) and statistical analyses of an 11-domain social needs questionnaire routinely administered in a large health system in Kansas City, Kansas (n = 26,093, temporal relationship between diagnoses and screening undetermined). Except for childcare needs, all social needs were more commonly reported in patients with a T2DM diagnosis. Domains with the strongest associations were prescription cost, transportation, and health literacy. These findings may inform health system and social service provider partnerships to offer assistance in specific domains.

Landscape analysis for a community-designed intervention to enhance early childhood development in San Francisco.

To determine the appropriate components for a community-based intervention for early childhood development, a broad series of stakeholder interviews was completed in a three-month period (January-March 2019) and a systematic review of their responses was performed. Additionally, 11 citywide assessment reports for child equity were reviewed and added to the information matrix. We performed this population-based assessment in San Francisco, a dense urban environment with roughly 43,000 children under the age of 5. The city has high rates of income inequity, with roughly half of the children considered to be living in low-income or poverty conditions. Interviews were conducted with 34 stakeholders representing various sectors, including community organizations, government, healthcare, and academia. Nine main concerns surrounding low-income families and children (LIFC) living in San Francisco were extracted from stakeholder interviews. The concerns were divided into subcategories based on a socioecological health model. City-funded, community-based, family resource centers were an identified space for performing an early childhood health intervention supporting LIFC. Furthermore, any proposed intervention to support LIFC must be implemented with a culturally tailored focus, as a one-size-fits-all, clinic-based model is not desired. Community-engaged and culturally specific activities are requested and required for effectively promoting early childhood development in an urban environment. In this article we propose that additional work towards implementing community-based interventions with support from the clinic are needed.

Canadian report card on health equity across the life-course: Analysis of time trends and cross-national comparisons with the United Kingdom.

Addressing social determinants of health (SDoH) has been acknowledged as an essential objective for the promotion of both population health and health equity. Extant literature has identified seven potential areas of investment to address SDoH: investments in sexual and reproductive health and family planning, early learning and child care, education, universal health care, as well as investments to reduce child poverty, ensure sustainable economic development, and control health hazards. The aim of this paper is to produce a 'report card' on Canada's success in reducing socioeconomic and health inequities pertaining to these seven policy domains, and to assess how Canadian trends compare to those in the United Kingdom (UK), a country with a similar health and welfare system. Summarising evidence from published studies and national statistics, we found that Canada's best successes were in reducing socioeconomic inequalities in early learning and child care and reproductive health-specifically in improving equity in maternal employment and infant mortality. Comparative data suggest that Canada's outcomes in the latter areas were like those in the UK. In contrast, Canada's least promising equity outcomes were in relation to health hazard control (specifically, tobacco) and child poverty. Though Canada and the UK observed similar inequities in smoking, Canada's slow upward trend in child poverty prevalence is distinct from the UK's small but steady reduction of child poverty. This divergence from the UK's trends indicates that alternative investment types and levels may be needed in Canada to achieve similar outcomes to those in the UK.