From Policy to Practice: Assessing the State Innovation Models Initiative's Early Success in Incorporating Social Determinants of Health in ASCVD Hospitalizations in the United States.

The study examines effects of the CMS State Innovation Models(SIM) on capturing social risk factors in adults hospitalized with Atherosclerotic Cardiovascular Disease (ASCVD). Using a difference-in-differences(DID) approach with propensity score weights, the study compared documentation of secondary diagnosis of SDOH/social factors using ICD-9 V codes ("SDOH codes") in adults hospitalized with ASCVD as a primary diagnosis (N= 1,485,354). Data were gathered from January 1, 2010, to September 30, 2015, covering the period before and after the SIM implementation in October 2013. From January 2010 to September 2015, SDOH codes were infrequently utilized among adults with ASCVD(0.55%, 95% CI: 0.43%-0.67%). SDOH codes with ASCVD increased from pre- to post-period in SIM states(0.56% to 0.93%) and comparison states (0.46% to 0.56%). SIM implementation was associated with greater improvement in SDOH codes utilization (adjusted OR 1.30, 95%CI: 1.18-1.43) during ASCVD hospitalizations. The odds of SDOH codes utilization were 86% higher in ED admissions(AOR 1.86, 95%CI: 1.76-1.97) than in routine admissions with ASCVD. Findings were similar when limiting population to older adults(>=65 years) enrolled in Medicare(AOR 1.50, 95%CI 1.31-1.71), whereas not significant for Medicaid beneficiaries. The study points to challenges for healthcare providers in documenting SDOH in adults with ASCVD.

Relationship between Unstable Housing, Food Insecurity, and Vision Status in the MI-SIGHT Community Eye Disease Screening Program.

PURPOSE: Assess rate of visual impairment (VI) from uncorrected refractive error (URE) and associations with demographic and socioeconomic factors among low-income patients presenting to the Michigan Screening and Intervention for Glaucoma and Eye Health through Telemedicine (MI-SIGHT) program. DESIGN: Cross-sectional study. PARTICIPANTS: Adults ≥ 18 years without acute ocular symptoms. METHODS: MI-SIGHT program participants received a telemedicine-based eye disease screening and ordered glasses through an online optical shop. Participants were categorized based on refractive error (RE) status: VI from URE (presenting visual acuity [PVA] ≤ 20/50, best corrected visual acuity [BCVA] ≥ 20/40), URE without VI (PVA ≥ 20/40, had ≥ 2 lines of improvement to BCVA), and no or adequately corrected RE (PVA ≥ 20/40, < 2 line improvement to BCVA). Patient demographics, self-reported visual function, and satisfaction with glasses obtained through the program were compared between groups using analysis of variance, Kruskal-Wallis, chi-square, and Fisher exact testing. MAIN OUTCOME MEASURES: PVA, BCVA, and presence of VI (defined as PVA ≤ 20/50). RESULTS: Of 1171 participants enrolled in the MI-SIGHT program during the first year, the average age was 55.1 years (standard deviation = 14.5), 37.7% were male, 54.1% identified as Black, and 1166 (99.6%) had both PVA and BCVA measured. VI was observed in 120 (10.3%); 96 had VI from URE (8.2%), 168 (14.4%) had URE without VI, and 878 (75.3%) had no or adequately corrected RE. A smaller percentage of participants with VI from URE reported having a college degree and a larger percentage reported income < $10 000 compared to participants with no or adequately corrected RE (3.2% versus 14.2%, P = 0.02; 45.5% versus 21.6%, respectively, P < 0.0001. Visual function was lowest among participants with VI from URE, followed by those with URE without VI, and then those with no or adequately corrected RE (VFQ9 composite score 67.3 ± 19.6 versus 77.0 ± 14.4 versus 82.2 ± 13.3, respectively; P < 0.0001). 71.2% (n = 830) ordered glasses for an average cost of $36.80 ± $32.60; 97.7% were satisfied with their glasses. CONCLUSIONS: URE was the main cause of VI at 2 clinics serving low-income communities and was associated with reduced vision-related quality of life. An online optical shop with lower prices made eyeglasses accessible to low-income patients. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Assessing New York City's COVID-19 Vaccine Rollout Strategy: A Case for Risk-Informed Distribution.

This study reviews the impact of eligibility policies in the early rollout of the COVID-19 vaccine on coverage and probable outcomes, with a focus on New York City. We conducted a retrospective ecological study assessing age 65+, area-level income, vaccination coverage, and COVID-19 mortality rates, using linked Census Bureau data and New York City Health administrative data aggregated at the level of modified zip code tabulation areas (MODZCTA). The population for this study was all individuals in 177 MODZCTA in New York City. Population data were obtained from Census Bureau and New York City Health administrative data. The total mortality rate was examined through an ordinary least squares (OLS) regression model, using area-level wealth, the proportion of the population aged 65 and above, and the vaccination rate among this age group as predictors. Low-income areas with high proportions of older people demonstrated lower coverage rates (mean vaccination rate 52.8%; maximum coverage 67.9%) than wealthier areas (mean vaccination rate 74.6%; maximum coverage 99% in the wealthiest quintile) in the first 3 months of vaccine rollout and higher mortality over the year. Despite vaccine shortages, many younger people accessed vaccines ahead of schedule, particularly in high-income areas (mean coverage rate 60% among those 45-64 years in the wealthiest quintile). A vaccine program that prioritized those at greatest risk of COVID-19-associated morbidity and mortality would have prevented more deaths than the strategy that was implemented. When rolling out a new vaccine, policymakers must account for local contexts and conditions of high-risk population groups. If New York had focused limited vaccine supply on low-income areas with high proportions of residents 65 or older, overall mortality might have been lower.

Understanding social risk factors in patients presenting to the emergency Department for Acute Heart Failure: A pilot study.

BACKGROUND: The standard of care for congestive heart failure (CHF) aims to slow disease progression and maximize patient function, however there is an increase in emergency department (ED) revisits and readmissions. Social risk factors play a role in the disease management and prognosis of CHF. There is a gap in the identification of low-risk CHF patient who would be safely discharged using an initial social risk factor stratification. OBJECTIVES: To generate a social risk profile for patients presenting to the ED with acute CHF exacerbation and identify variables that may increase the risk of 7-day and overall mortality, 30-day ED revisit, and readmission. METHODS: We conducted a pilot prospective survey-based study among adult patients presenting to the ED with acute CHF exacerbation. The combination of a self-report questionnaire and retrospective chart review was used to generate a CHF risk profile. RESULTS: A total of 62 patients were recruited in the pilot study with a mean age of 69.5 years. The preliminary data indicated that prior to this ED visit, 21% of patients were not aware of a previous CHF diagnosis; 64.5% of patients rated their sleep quality as poor or very poor; 72.6% reported orthopnea; and 43.5% reported recent weight gain. 37.1% of patients did not adhere to dietary recommendations and some patients did not adhere to their medication regime 100%. CONCLUSION: This study suggests establishing a social risk profile for patients presenting to the ED with CHF can help formulate a CHF-specific care plan and optimize multidisciplinary management to reduce ED revisits and readmissions.

The relationship between community social risk factors and regional hospital-reported cash, negotiated, and chargemaster prices for 14 common services.

BACKGROUND: Social risk factors are key drivers of the geographic variation in spending in the United States but little is known how community-level social risk factors are associated with hospital prices. Our objective was to describe the relationship between regional hospital-reported prices and social risk factors by price type (chargemaster, cash, commercial, Medicare, and Medicaid). METHODS: This cross-sectional analysis used newly available hospital-reported prices from acute general hospitals in 2022. The prices were for 14 common services. Prices were winsorized at 98%, wage index-adjusted, standardized by service, and aggregated to hospital service areas (HSAs). For social risk, we used 23 measures across 5 domains of social risk (socioeconomic position; race, ethnicity, and culture; gender; social relationships; and residential and community context). Spearman's correlation was used to estimate associations between median prices and social risk by price type. RESULTS: Prices were reported from 2,386 acute general hospitals in 45% (1,502 of 3,436) HSAs. Correlations between regional prices and other social risk factors varied by price type (range: -0.19 to 0.31). Chargemaster and cash prices were significantly correlated with the most community characteristics (10 of 23, 43%) followed by commercial prices (8, 35%). Medicare and Medicaid prices were only significantly correlated with 1 measure (all p < 0.01). All price types were significantly correlated with the percentage of uninsured (all p < 0.01). Chargemaster, cash, and commercial prices were positively correlated with percentage of Hispanic residents, residents with limited English proficiency, and non-citizens (all p < 0.05). CONCLUSIONS: While regional correlations between prices and social risk factors were weak across all prices, chargemaster, cash, and commercial prices were more like closely aligned with community-level social risk factors than the two public payers (Medicare and Medicaid). Chargemaster, cash, and commercial hospital prices appeared to be higher in socially disadvantaged communities. Further research is needed to clarify the relationship between prices and community social risk factors.

Implementing a Social Needs Screening and Referral Program Among Veterans: Assessing Circumstances & Offering Resources for Needs (ACORN).

BACKGROUND: The Department of Veterans Affairs (VA) healthcare system routinely screens Veterans for food insecurity, housing instability, and intimate partner violence, but does not systematically screen for other health-related social needs (HRSNs). OBJECTIVES: To (1) develop a process for systematically identifying and addressing Veterans' HRSNs, (2) determine reported prevalence of HRSNs, and (3) assess the acceptability of HRSN screening among Veterans. DESIGN: "Assessing Circumstances and Offering Resources for Needs" (ACORN) is a Veteran-tailored HRSN screening and referral quality improvement initiative. Veterans were screened via electronic tablet for nine HRSNs (food, housing, utilities, transportation, legal needs, social isolation, interpersonal violence, employment, and education) and provided geographically tailored resource guides for identified needs. Two-week follow-up interviews with a purposive sample of Veterans explored screening experiences. PARTICIPANTS: Convenience sample of Veterans presenting for primary care at a VA urban women's health clinic and suburban community-based outpatient clinic (October 2019-May 2020). MAIN MEASURES: Primary outcomes included prevalence of HRSNs, Veteran-reported acceptability of screening, and use of resources guides. Data were analyzed using descriptive statistics, chi-square tests, and rapid qualitative analysis. KEY RESULTS: Of 268 Veterans screened, 50% reported one or more HRSNs. Social isolation was endorsed most frequently (29%), followed by educational needs (19%), interpersonal violence (12%), housing instability (9%), and utility concerns (7%). One in five Veterans reported at least one form of material hardship. In follow-up interviews (n = 15), Veterans found screening acceptable and felt VA should continue screening. No Veterans interviewed had contacted recommended resources at two-week follow-up, although several planned to use resource guides in the future. CONCLUSION: In a VA HRSN screening and referral program, Veterans frequently reported HRSNs, felt screening was important, and thought VA should continue to screen for these needs. Screening for HRSNs is a critical step towards connecting patients with services, identifying gaps in service delivery, and informing future resource allocation.

Association of Insurance Type With Inpatient Surgery 30-Day Complications and Costs.

INTRODUCTION: Safety-net hospitals (SNHs) have higher postoperative complications and costs versus low-burden hospitals. Do low socioeconomic status/vulnerable patients receive care at lower-quality hospitals or are there factors beyond providers' control? We studied the association of private, Medicare, and vulnerable insurance type with complications/costs in a high-burden SNH. METHODS: Retrospective inpatient cohort study using National Surgical Quality Improvement Program (NSQIP) data (2013-2019) with cost data risk-adjusted by frailty, preoperative serious acute conditions (PASC), case status, and expanded operative stress score (OSS) to evaluate 30-day unplanned reoperations, any complication, Clavien-Dindo IV (CDIV) complications, and hospitalization variable costs. RESULTS: Cases (Private 1517; Medicare 1224; Vulnerable 3648) with patient mean age 52.3 y [standard deviation = 14.7] and 47.3% male. Adjusting for frailty and OSS, vulnerable patients had higher odds of PASC (aOR = 1.71, CI = 1.39-2.10, P < 0.001) versus private. Adjusting for frailty, PASC and OSS, Medicare (aOR = 1.27, CI = 1.06-1.53, P = 0.009), and vulnerable (aOR = 2.44, CI = 2.13-2.79, P < 0.001) patients were more likely to undergo urgent/emergent surgeries. Vulnerable patients had increased odds of reoperation and any complications versus private. Variable cost percentage change was similar between private and vulnerable after adjusting for case status. Urgent/emergent case status increased percentage change costs by 32.31%. We simulated "switching" numbers of private (3648) versus vulnerable (1517) cases resulting in an estimated variable cost of $49.275 million, a 25.2% decrease from the original $65.859 million. CONCLUSIONS: Increased presentation acuity (PASC and urgent/emergent surgeries) in vulnerable patients drive increased odds of complications and costs versus private, suggesting factors beyond providers' control. The greatest impact on outcomes may be from decreasing the incidence of urgent/emergent surgeries by improving access to care.

Patient-Reported Social Risks and Clinician Decision Making: Results of a Clinician Survey in Primary Care Community Health Centers.

PURPOSE: To assess the extent that patients' social determinants of health (SDOH) influence safety-net primary care clinicians' decisions at the point of care; examine how that information comes to the clinician's attention; and analyze clinician, patient, and encounter characteristics associated with the use of SDOH data in clinical decision making. METHODS: Thirty-eight clinicians working in 21 clinics were prompted to complete 2 short card surveys embedded in the electronic health record (EHR) daily for 3 weeks. Survey data were matched with clinician-, encounter-, and patient-level variables from the EHR. Descriptive statistics and generalized estimating equation models were used to assess relationships between the variables and the clinician reported use of SDOH data to inform care. RESULTS: Social determinants of health were reported to influence care in 35% of surveyed encounters. The most common sources of information on patients' SDOH were conversations with patients (76%), prior knowledge (64%), and the EHR (46%). Social determinants of health were significantly more likely to influence care among male and non-English-speaking patients, and those with discrete SDOH screening data documented in the EHR. CONCLUSIONS: Electronic health records present an opportunity to support clinicians integrating information about patients' social and economic circumstances into care planning. Study findings suggest that SDOH information from standardized screening documented in the EHR, combined with patient-clinician conversations, may enable social risk-adjusted care. Electronic health record tools and clinic workflows could be used to support both documentation and conversations. Study results also identified factors that may cue clinicians to include SDOH information in point-of-care decision-making. Future research should explore this topic further.

Examining How Social Risk Factors Are Integrated Into Clinical Settings Using Existing Data: A Scoping Review.

PURPOSE: Integrating social care into clinical care requires substantial resources. Use of existing data through a geographic information system (GIS) has the potential to support efficient and effective integration of social care into clinical settings. We conducted a scoping literature review characterizing its use in primary care settings to identify and address social risk factors. METHODS: In December 2018, we searched 2 databases and extracted structured data for eligible articles that (1) described the use of GIS in clinical settings to identify and/or intervene on social risks, (2) were published between December 2013 and December 2018, and (3) were based in the United States. Additional studies were identified by examining references. RESULTS: Of the 5,574 articles included for review, 18 met study eligibility criteria: 14 (78%) were descriptive studies, 3 (17%) tested an intervention, and 1 (6%) was a theoretical report. All studies used GIS to identify social risks (increase awareness); 3 studies (17%) described interventions to address social risks, primarily by identifying relevant community resources and aligning clinical services to patients' needs. CONCLUSIONS: Most studies describe associations between GIS and population health outcomes; however, there is a paucity of literature regarding GIS use to identify and address social risk factors in clinical settings. GIS technology may assist health systems seeking to address population health outcomes through alignment and advocacy; its current application in clinical care delivery is infrequent and largely limited to referring patients to local community resources.

Social Risk Factors That Increase Cardiovascular and Breast Cancer Risk.

PURPOSE OF REVIEW: Cardiovascular disease (CVD) and breast cancer (BC) are significant causes of mortality globally, imposing a substantial health burden. This review article aims to examine the shared risk factors and social determinants that contribute to the high prevalence of both diseases, with a focus on social risk factors. RECENT FINDINGS: The common risk factors for CVD and BC, such as hypertension, diabetes, obesity, aging, and physical inactivity, are discussed, emphasizing their modifiability. Adhering to ideal cardiovascular health behaviors has shown a trend toward lower BC incidence. Increased risk of CVD-related mortality is significantly impacted by age and race in BC patients, especially those over 45 years old. Additionally, racial disparities in both diseases highlight the need for targeted interventions. Social determinants of health, including socioeconomic status, education, employment, and neighborhood context, significantly impact outcomes for both CVD and BC. Addressing social factors is vital in reducing the burden of both CVD and BC and improving overall health equity.

Social Risk Factors Influence Pediatric Emergency Department Utilization and Hospitalizations.

OBJECTIVE: To characterize the association of children's social risk factors with total number of emergency department (ED) visits or hospitalization and time to first subsequent ED or hospitalization. STUDY DESIGN: This was a retrospective cohort study of patients seen at a general pediatric clinic between 2017 and 2021 with documented ≥1 social risk factors screened per visit. Negative binomial or Poisson regression modeled ED utilization and hospitalizations as functions of the total number of risk factors or each unique risk factor. Time-varying Cox models were used to evaluate differences between those who screened positive and those who screened negative, controlling for demographic and clinical covariates. RESULTS: Overall, 4674 patients (mean age, 6.6 years; 49% female; 64% Hispanic; 21% Black) were evaluated across a total of 20 927 visits. Children with risk factors had higher rates of attention-deficit hyperactivity disorder, failure to gain weight, asthma, and prematurity compared with children with no risk (all P < .01). Adjusted models show a positive association between increased total number of factors and ED utilization (incidence rate ratio [IRR], 1.18; 95% CI, 1.12-1.23) and hospitalizations (IRR, 1.36; 95% CI, 1.26-1.47). There were no associations between a positive screen and time to first ED visit (hazard ratio [HR], 0.95; 95% CI, 0.85-1.06; P = .36) or hospitalization (HR, 1.15; 95% CI, 0.84-1.59; P = .40). CONCLUSIONS: Social risk factors were associated with increased ED utilization and hospitalizations at the patient level but were not significantly associated with time to subsequent acute care use. Future research should evaluate the effect of focused interventions on health care utilization, such as those addressing food insecurity and transportation challenges.

Clinically Screening Hospital Patients for Social Risk Factors Across Multiple Hospitals: Results and Implications for Intervention Development.

BACKGROUND: Hospitals are increasingly screening patients for social risk factors to help improve patient and population health. Intelligence gained from such screening can be used to inform social need interventions, the development of hospital-community collaborations, and community investment decisions. OBJECTIVE: We evaluated the frequency of admitted patients' social risk factors and examined whether these factors differed between hospitals within a health system. A central goal was to determine if community-level social need interventions can be similar across hospitals. DESIGN AND PARTICIPANTS: We described the development, implementation, and results from Northwell Health's social risk factor screening module. The statistical sample included patients admitted to 12 New York City/Long Island hospitals (except for maternity/pediatrics) who were clinically screened for social risk factors at admission from June 25, 2019, to January 24, 2020. MAIN MEASURES: We calculated frequencies of patients' social needs across all hospitals and for each hospital. We used chi-square and Friedman tests to evaluate whether the hospital-level frequency and rank order of social risk factors differed across hospitals. RESULTS: Patients who screened positive for any social need (n = 5196; 6.6% of unique patients) had, on average, 2.3 of 13 evaluated social risk factors. Among these patients, the most documented social risk factor was challenges paying bills (29.4%). The frequency of 12 of the 13 social risk factors statistically differed across hospitals. Furthermore, a statistically significant variance in rank orders between the hospitals was identified (Friedman test statistic 30.8 > 19.6: χ2 critical, p = 0.05). However, the hospitals' social need rank orders within their respective New York City/Long Island regions were similar in two of the three regions. CONCLUSIONS: Hospital patients' social needs differed between hospitals within a metropolitan area. Patients at different hospitals have different needs. Local considerations are essential in formulating social need interventions and in developing hospital-community partnerships to address these needs.

Incentivizing Excellent Care to At-Risk Groups with a Health Equity Summary Score.

BACKGROUND: Social risk factors (SRFs) such as minority race-and-ethnicity or low income are associated with quality-of-care, health, and healthcare outcomes. Organizations might prioritize improving care for easier-to-treat groups over those with SRFs, but measuring, reporting, and further incentivizing quality-of-care for SRF groups may improve their care. OBJECTIVE: To develop, as a proof-of-concept, a Health Equity Summary Score (HESS): a succinct, easy-to-understand score that could be used to promote high-quality care to those with SRFs in Medicare Advantage (MA) health plans, which provide care for almost twenty million older and disabled Americans and collect extensive quality measure and SRF data. DESIGN: We estimated, standardized, and combined performance scores for two sets of quality measures for enrollees in 2013-2016 MA health plans, considering both current levels of care, within-plan improvement, and nationally benchmarked improvement for those with SRFs (specifically, racial-and-ethnic minority status and dual-eligibility for Medicare and Medicaid). PARTICIPANTS: All MA plans with publicly reported quality scores and 500 or more 2016 enrollees. MAIN MEASURES: Publicly reported clinical quality and patient experience measures. KEY RESULTS: Almost 90% of plans measured for MA Star Ratings received a HESS; plans serving few patients with SRFs were excluded. The summary score was moderately positively correlated with publicly reported overall Star Ratings (r = 0.66-0.67). High-scoring plans typically had sizable enrollment of both racial-and-ethnic minorities (38-42%) and dually eligible beneficiaries (29-38%). CONCLUSIONS: We demonstrated the feasibility of developing and estimating a HESS that is intended to promote and incentivize excellent care for racial-and-ethnic minorities and dually eligible MA enrollees. The HESS measures SRF-specific performance and does not simply duplicate overall plan Star Ratings. It also identifies plans that provide excellent care to large numbers of those with SRFs. Our methodology could be extended to other SRFs, quality measures, and settings.

Examining the association of social risk with heart failure readmission in the Veterans Health Administration.

BACKGROUND: Previous research has found that social risk factors are associated with an increased risk of 30-day readmission. We aimed to assess the association of 5 social risk factors (living alone, lack of social support, marginal housing, substance abuse, and low income) with 30-day Heart Failure (HF) hospital readmissions within the Veterans Health Affairs (VA) and the impact of their inclusion on hospital readmission model performance. METHODS: We performed a retrospective cohort study using chart review and VA and Centers for Medicare and Medicaid Services (CMS) administrative data from a random sample of 1,500 elderly (≥ 65 years) Veterans hospitalized for HF in 2012. Using logistic regression, we examined whether any of the social risk factors were associated with 30-day readmission after adjusting for age alone and clinical variables used by CMS in its 30-day risk stratified readmission model. The impact of these five social risk factors on readmission model performance was assessed by comparing c-statistics, likelihood ratio tests, and the Hosmer-Lemeshow goodness-of-fit statistic. RESULTS: The prevalence varied among the 5 risk factors; low income (47 % vs. 47 %), lives alone (18 % vs. 19 %), substance abuse (14 % vs. 16 %), lacks social support (2 % vs. <1 %), and marginal housing (< 1 % vs. 3 %) among readmitted and non-readmitted patients, respectively. Controlling for clinical factors contained in CMS readmission models, a lack of social support was found to be associated with an increased risk of 30-day readmission (OR 4.8, 95 %CI 1.35-17.88), while marginal housing was noted to decrease readmission risk (OR 0.21, 95 %CI 0.03-0.87). Living alone (OR: 0.9, 95 %CI 0.64-1.26), substance abuse (OR 0.91, 95 %CI 0.67-1.22), and having low income (OR 1.01, 95 %CI 0.77-1.31) had no association with HF readmissions. Adding the five social risk factors to a CMS-based model (age and comorbid conditions; c-statistic 0.62) did not improve model performance (c-statistic: 0.62). CONCLUSIONS: While a lack of social support was associated with 30-day readmission in the VA, its prevalence was low. Moreover, the inclusion of some social risk factors did not improve readmission model performance. In an integrated healthcare system like the VA, social risk factors may have a limited effect on 30-day readmission outcomes.

Loneliness is associated with risk of cognitive impairment in the Survey of Health, Ageing and Retirement in Europe.

OBJECTIVES: To test whether loneliness is associated with the risk of cognitive impairment up to 11 years later in a European sample of middle-aged and older adults. The study examines whether this association is independent of measures of social isolation, depression, and other risk factors for cognitive impairment and dementia. METHODS: Participants (N = 14 114) from the Survey of Health, Ageing and Retirement in Europe (SHARE) answered a single item on loneliness at baseline and were assessed for cognitive impairment every 2-to-3 years for 11 years. Participants who scored at least 1.5 standard deviations below the age-graded mean on both a memory recall task and verbal fluency task were classified as impaired. A three-item measure of loneliness was available for a sample of respondents followed up to 4 years. RESULTS: Feeling lonely was associated with increased risk of incident cognitive impairment (HR = 1.31, 95%CI = 1.19-1.44), after accounting for age, sex, education, and SHARE country strata. The association was robust but reduced in magnitude when controlling for clinical and behavioral risk factors, health-related activity limitations, social isolation, social disengagement, and depressive symptoms. The association was not moderated by socio-demographic factors and was also apparent when using the three-item loneliness scale instead of the single-item measure. CONCLUSIONS: These findings expand the extant literature on loneliness and the risk of cognitive impairment in older adulthood. Loneliness is one modifiable factor that can be intervened prior to the development of severe impairment or dementia.

Posting, texting, and related social risk behavior while high.

Background: Posting on social media can have lasting consequences in one's social life and career. Research has not yet focused on social media or more modern forms of communication as social risk factors for individuals high on drugs. This study aims to examine prevalence and correlates of engaging in social media posting and related behavior while high. Methods: We examined data from 872 adults (39.8% female) who were surveyed entering electronic dance music (EDM) parties in New York City and reported lifetime illegal drug use. Participants were asked whether they were ever high on a drug while (1) posting on social media, (2) calling or texting someone, and (3) being in a photo. Those answering affirmatively were also asked whether they later regretted the behavior. We examined demographic and drug-related correlates of these behaviors. Results: Of the participants, 34.3% posted on social media while high (with 21.4% regretting it), 55.9% had texted or called someone while high (with 30.5% regretting it), and 47.6% had been in a photo while high (with 32.7% regretting it). Females and young adults (ages 18-24) were at high risk for posting on social media while high and at higher risk for engaging in more of these behaviors. Past-month marijuana users in particular were at increased risk for engaging in each of these behaviors. Conclusion: Engaging in these behaviors while high on drugs appears to be prevalent, and prevention and harm reduction efforts should seek to prevent or reduce likelihood of social harm that can result from such situations.

Experiences of Community Violence Among Adults with Chronic Conditions: Qualitative Findings from Chicago.

BACKGROUND: Community violence is an important social determinant of health in many high-poverty, urban communities. OBJECTIVE: The purpose of this study was to explore and characterize self-described experiences of community violence among adults with chronic health conditions. DESIGN: Qualitative study design was implemented in 2017 using in-depth, semi-structured focus groups and interviews; data were collected from two clinical sites located in geographic epicenters of high violent crime in Chicago. PARTICIPANTS: Adult patients, ages 35 years and older, who had at least one chronic condition. APPROACH: Data were analyzed using grounded theory and the constant comparison method. KEY RESULTS: The overall sample (N = 51) was predominantly female (67%) and black non-Hispanic (75%); a large proportion had hypertension (65%), arthritis (55%), obesity (53%), and/or diabetes (45%). The majority reported that a close friend or family member was seriously injured or killed due to community violence (71%); a similar proportion had never discussed their experiences of community violence with a healthcare provider (73%). Several major themes emerged: (1) perceived risk of being targeted, (2) chronic stress and worry, (3) hypervigilance, (4) social breakdown, (5) chronic isolation, (6) constrained choice (loss of freedom), (7) limited access to material resources, and (8) inadequate healthcare responses. CONCLUSIONS: Patients often struggled to balance the challenges imposed by community violence with the demands of living with and managing their chronic conditions. Emergent themes may inform practical targets for addressing community violence as a social determinant of health in vulnerable populations.

[The Medical Social Characteristics of Women with Oncologic Diseases].

The oncologic pathology is covered by the group of socially significant diseases and ranks second position in the structure of population mortality in the Russian Federation, being one of the actual medical social problems of modern society. In the Russian Federation and all over the world, over last years, a steady rise of morbidity of malignant neoplasms is observed. At that, it is more intensive among female population. Both medical biological and social hygienic risk factors play a significant role in the development of these diseases. In this connection, significant interest represents study of individual medical social characteristics of females with oncologic pathology and their impact on health of this contingent and on development of disease itself. The medical social study, based on the developed program, covered 607 females with oncologic diseases and 605 females without this pathology (control group). The computer database was organized. To provide a possibility of in-death statistical processing of data, all qualitative indices were converted into number form using technology based on the expert appraisal. The technique of mathematical statistics was applied to analyze relationship of medical social characteristics. The functional dependences were built. The key risk factors were detected. The regression analysis was applied to develop mathematical models describing relationship between health of patients and their leaving on disability status and individual medical social risk factors. The testing confirmed efficiency of the developed models. The results of applied analysis and the developed prognostic models are proposed to be applied within the framework of stage-by-stage dispensary observation and control of health of females with oncologic diseases with the purpose of prevention at early stages and in case of complications of main and concomitant diseases.

Social and structural factors related to HIV risk among truck drivers passing through the Iringa region of Tanzania.

Truck drivers and their assistants have been identified as groups at higher risk for HIV infection. We sought to identify and describe the social and structural factors that may contribute to HIV risk among truck drivers who visit rest stops in Iringa, Tanzania, a region characterized by high levels of migration and mobility. This analysis was part of a comprehensive strategic assessment to examine HIV risk factors in Iringa. This analysis focuses on 11 in-depth interviews with truck drivers and a transport owner. A semi-structured interview guide was developed to elicit open-ended responses and enable probing. Interviews were conducted in Swahili, transcribed, and translated into English. Data analysis followed thematic analysis procedures that included initial reading of transcripts, development of a codebook and identification of themes through in-depth reading of transcripts. Drivers described structural risk factors for HIV including work conditions, the power imbalance between male drivers and their sexual partners and minimal perceived HIV risk with certain partners (e.g., regular partners and women selling sex). Multiple and inter-related social norms associated with truck stop environments influenced HIV risk, including peer influence and expectations, presence of sex workers, ability to purchase sex throughout their travel and alcohol consumption. These distinct social norms in truck stops and other rest points facilitated behavior that many participants said they would not engage in elsewhere. HIV prevention strategies with truck drivers should address individual, social and structural barriers to HIV prevention through partnerships with the health and transportation sectors, local government and local communities. HIV prevention services should be adapted to drivers' times and places of availability, for example, condom provision where/when drivers make decisions about or have sex. A focus on positive messaging and addressing specific challenges including the continual challenge of re-choosing and reinforcing decisions to engage in safer sexual behaviors is important.

Association of cumulative social risk with mortality and adverse cardiovascular disease outcomes.

BACKGROUND: Quantifying the cumulative effect of social risk factors on cardiovascular disease (CVD) risk can help to better understand the sources of disparities in health outcomes. METHOD AND RESULTS: Data from the Heart Strategies Concentrating on Risk Evaluation (HeartSCORE) study were used to create an index of cumulative social risk (CSR) and quantify its association with incident CVD and all-cause mortality. CSR was defined by assigning a score of 1 for the presence of each of 4 social factors: i) racial minority status (Black race), ii) single living status, iii) low income, and iv) low educational level. Hazard ratios (HRs) were computed using Cox-regression models, adjusted for CVD risk factors. Over a median follow-up period of 8.3 years, 127 incident events were observed. The incidence of the primary outcome for subgroups of participants with 0, 1, and ≥2 CSR scores was 5.31 (95% CI, 3.40-7.22), 10.32 (7.16-13.49) and 17.80 (12.94-22.67) per 1000 person-years, respectively. Individuals with CSR score of 1 had an adjusted HR of 1.85 (1.15-2.97) for incident primary outcomes, compared to those with score of 0. The corresponding HR for individuals with CSR score of 2 or more was 2.58 (1.60-4.17). CONCLUSION: An accumulation of social risk factors independently increased the likelihood of CVD events and deaths in a cohort of White and Black individuals.