Social determinants of health (SDOH) are an important contributor to health status and health outcomes. In this analysis, we compare SDOH measured both at the individual and population levels in patients with high comorbidity who receive primary care at Federally Qualified Health Centers in New York and Chicago and enrolled in the Tipping Points trial.

We analyzed individual- and population-level measures of SDOH in 1,488 patients with high comorbidity (Charlson Comorbidity Index ≥ 4) enrolled in Tipping Points. At the individual level, we used a standardized patient-reported questionnaire. At the population level, we employed patient addresses to calculate the Social Deprivation Index (SDI) and Area Deprivation Index. Multivariable regressions were conducted in addition to qualitative feedback from stakeholders.

Individual-level SDOH are distinct from population-level measures. Significant component predictors of population SDI are being unhoused, unable to pay for utilities, and difficulty accessing medical transportation. Qualitative findings mirrored these results. High comorbidity patients report significant SDOH challenges at the individual level. Fitting a binomial generalized linear model, the comorbidity score is significantly predicted by the composite individual SDOH index (p < 0.0001) controlling for age and race/ethnicity.

Individual- and population-level SDOH measures provide different risk assessments. The use of community-level SDI data is informative in the aggregate but should not be used to identify patients with individual unmet social needs. Health systems should implement a standardized individualized assessment of unmet SDOH needs and build strong, enduring partnerships with community-based organizations that can provide those services.

The COVID-19 pandemic is a disaster event. Exposure to stressors during and after disaster events is associated with negative mental health symptoms. To inform targeted COVID-19 recovery efforts, data are needed to understand which stressors play a key role in this relationship.

Cross-sectional survey data (demographics, impacts of COVID-19, social determinants of health, depression, and anxiety) were collected online from adults living in New York state between May and June 2020. Differences in the proportion of stressors (COVID-19 and social determinants) experienced by race/ethnicity were assessed using chi-square analyses. Logistic regression was used to assess which factors were associated with increased odds of depression and anxiety.

A majority (n = 258, 62.2%) of the 415 respondents reported being directly impacted by the pandemic. Non-white respondents reported a significantly larger proportion of stressors compared to white respondents. Under half of respondents reported depression (n = 171, 41.2%) and anxiety (n = 164, 39.5%). Healthcare and food concerns were associated with increased odds of depression and anxiety, and economic concerns were associated with increased odds of anxiety.

Findings underscore the need to respond to the COVID-19 mental health crisis by addressing social determinants of health.

Social determinants of health (SDoH), such as socioeconomics and neighborhoods, strongly influence health outcomes. However, the current state of standardized SDoH data in electronic health records (EHRs) is lacking, a significant barrier to research and care quality.

We conducted a PubMed search using “SDOH” and “EHR” Medical Subject Headings terms, analyzing included articles across five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Of 685 articles identified, 324 underwent full review. Key findings include implementation of tailored screening instruments, census and claims data linkage for contextual SDoH profiles, NLP systems extracting SDoH from notes, associations between SDoH and healthcare utilization and chronic disease control, and integrated care management programs. However, variability across data sources, tools, and outcomes underscores the need for standardization.

Despite progress in identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical for SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately, widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Social determinants of health (SDoH), such as food and financial insecurity and food assistance, are potentially modifiable factors that may influence breastfeeding initiation and duration. Knowledge gaps exist regarding the relationship between these SDoH and infant feeding practices. We explored the relationships of food and financial insecurity and food assistance with the continuation of breastfeeding at four months postpartum among mothers and whether race and ethnicity modified these associations.

Mothers retrospectively reported food and financial insecurity and receipt of food assistance (e.g. Women, Infants and Children and Supplemental Nutrition Assistance Program) during pregnancy with their first child and infant feeding practices (exclusive/mostly breastfeeding v. exclusive/mostly formula feeding) following the birth of their first child. Sociodemographic-adjusted modified Poisson regressions estimated prevalence ratios and 95 % CI.

Minneapolis-St. Paul, Minnesota.

Mothers who participated in the Life-course Experiences And Pregnancy study (LEAP) (n 486).

Ten percent of mothers reported food insecurity, 43 % financial insecurity and 22 % food assistance during their pregnancies. At four months postpartum, 63 % exclusively/mostly breastfed and 37 % exclusively/mostly formula-fed. We found a lower adjusted prevalence of breastfeeding at four months postpartum for mothers who reported experiencing food insecurity (0·65; 0·43–0·98) and receiving food assistance (0·66; 0·94–0·88) relative to those who did not. For financial insecurity (aPR 0·92; 0·78, 1·08), adjusted estimates showed little evidence of an association.

We found a lower level of breastfeeding among mothers experiencing food insecurity and using food assistance. Resources to support longer breastfeeding duration for mothers are needed. Moreover, facilitators, barriers and mechanisms of breastfeeding initiation and duration must be identified.

This study explores the transformative effects of the Community Plunge, an educational program at the Wake Forest University School of Medicine (WFUSOM), on healthcare delivery, community engagement, and trainee perspectives. It addresses the broader context of health outcomes, where clinical care only accounts for 20%, emphasizing the critical role of social determinants of health (SDOH) and individual behaviors in the remaining 80%.

WFUSOM’s Community Plunge, established in 2002, involves a guided tour of the community, discussions with residents, and debriefing sessions. Qualitative interviews with 20 clinicians were conducted to extract key themes and insights.

The study identified several key outcomes. First, participants gained crucial insights into the community’s history, structural challenges, and prevalent SDOH, enhancing their understanding of the diverse patient populations they serve. Second, the program positively influenced clinician attitudes, fostering empathy, reducing paternalism, and promoting holistic patient care. Third, participants expressed a desire for increased community involvement and reported career trajectory changes toward advocacy and volunteerism. However, challenges such as time constraints were acknowledged.

The study advocates for collaborative efforts to enhance the program’s impact, including proactive measures to ensure respectful engagement during community tours. It positions the Community Plunge as an innovative, scalable, and transformative strategy for experiential SDOH exposure, crucial for the evolving social consciousness of healthcare learners.

Social determinants of health (SDOH) can contribute to disparities that negatively impact health outcomes and healthcare utilization. Comprehensive screening is frequently overlooked during inpatient clinical care. This pilot aimed to evaluate the capturability of a multi-domain SDOH screening tool during hospitalization, as well as correlation of SDOH needs to readmissions.

The Protocol for Responding to and Assessing Patients’ Assets, Risks and Experiences (PRAPARE) screening tool was implemented on admission with adult inpatients at an academic tertiary medical center in central Pennsylvania. A total of 80 patients were screened over an 8-week period using the PRAPARE tool.

43.7% of participants were identified as having at least one SDOH need and 21.2% were identified as having two or more needs. Of the participants identified as having at least one SDOH need through PRAPARE screening, 42.5% experienced a readmission within 30 days, compared to 15% readmissions among participants with no identified SDOH needs. For each additional SDOH need a patient had, the odds they experienced a readmission increased by 2.2 times.

The study findings suggest that utilization of the PRAPARE screening tool has the ability to capture significant SDOH needs among hospitalized patients. This study also suggests that higher SDOH needs correlate to increased odds of experiencing a hospital readmission.

Leveraging the National COVID-19 Cohort Collaborative (N3C), a nationally sampled electronic health records repository, we explored associations between individual-level social determinants of health (SDoH) and COVID-19-related hospitalizations among racialized minority people with human immunodeficiency virus (HIV) (PWH), who have been historically adversely affected by SDoH.

We retrospectively studied PWH and people without HIV (PWoH) using N3C data from January 2020 to November 2023. We evaluated SDoH variables across three domains in the Healthy People 2030 framework: (1) healthcare access, (2) economic stability, and (3) social cohesion with our primary outcome, COVID-19-related hospitalization. We conducted hierarchically nested additive and adjusted mixed-effects logistic regression models, stratifying by HIV status and race/ethnicity groups, accounting for age, sex, comorbidities, and data partners.

Our analytic sample included 280,441 individuals from 24 data partner sites, where 3,291 (1.17%) were PWH, with racialized minority PWH having higher proportions of adverse SDoH exposures than racialized minority PWoH. COVID-19-related hospitalizations occurred in 11.23% of all individuals (9.17% among PWH, 11.26% among PWoH). In our initial additive modeling, we observed that all three SDoH domains were significantly associated with hospitalizations, even with progressive adjustments (adjusted odds ratios [aOR] range 1.36–1.97). Subsequently, our HIV-stratified analyses indicated economic instability was associated with hospitalization in both PWH and PWoH (aOR range 1.35–1.48). Lastly, our fully adjusted, race/ethnicity-stratified analysis, indicated access to healthcare issues was associated with hospitalization across various racialized groups (aOR range 1.36–2.00).

Our study underscores the importance of assessing individual-level SDoH variables to unravel the complex interplay of these factors for racialized minority groups.

Type 2 diabetes (T2DM) poses a significant public health challenge, with pronounced disparities in control and outcomes. Social determinants of health (SDoH) significantly contribute to these disparities, affecting healthcare access, neighborhood environments, and social context. We discuss the design, development, and use of an innovative web-based application integrating real-world data (electronic health record and geospatial files), to enhance comprehension of the impact of SDoH on T2 DM health disparities.

We identified a patient cohort with diabetes from the institutional Diabetes Registry (N = 67,699) within the Duke University Health System. Patient-level information (demographics, comorbidities, service utilization, laboratory results, and medications) was extracted to Tableau. Neighborhood-level socioeconomic status was assessed via the Area Deprivation Index (ADI), and geospatial files incorporated additional data related to points of interest (i.e., parks/green space). Interactive Tableau dashboards were developed to understand risk and contextual factors affecting diabetes management at the individual, group, neighborhood, and population levels.

The Tableau-powered digital health tool offers dynamic visualizations, identifying T2DM-related disparities. The dashboard allows for the exploration of contextual factors affecting diabetes management (e.g., food insecurity, built environment) and possesses capabilities to generate targeted patient lists for personalized diabetes care planning.

As part of a broader health equity initiative, this application meets the needs of a diverse range of users. The interactive dashboard, incorporating clinical, sociodemographic, and environmental factors, enhances understanding at various levels and facilitates targeted interventions to address disparities in diabetes care and outcomes. Ultimately, this transformative approach aims to manage SDoH and improve patient care.

To evaluate differences in the percentage of expenditure on food groups in Mexican households according to the gender of the household head and the size of the locality.

Analysis of secondary data from the National Household Income and Expenditure Survey (ENIGH) 2018. We estimated the percentage of expenditure on fifteen food groups according to the gender of the head of household and locality size and evaluated the differences using a two-part model approach.

Mexico, 2018.

A nationally representative sample of 74 647 Mexican households.

Female-headed households allocated a lower share of expenditure to the purchase of sweetened beverages and alcoholic beverages and higher percentages to milk and dairy, fruits and water. In comparison with metropolitan households, households in rural and urban localities spent more on cereals and tubers, sugar and honey, oil and fat and less on food away from home.

Households allocate different percentages of expenditure to diverse food groups according to the gender of the head of the household and the size of the locality where they are located. Future research should focus on understanding the economic and social disparities related to differences in food expenditure, including the gender perspective.

Screening for health-related social needs (HRSNs) within health systems is a widely accepted recommendation, however challenging to implement. Aggregate area-level metrics of social determinants of health (SDoH) are easily accessible and have been used as proxies in the interim. However, gaps remain in our understanding of the relationships between these measurement methodologies. This study assesses the relationships between three area-level SDoH measures, Area Deprivation Index (ADI), Social Deprivation Index (SDI) and Social Vulnerability Index (SVI), and individual HRSNs among patients within one large urban health system.

Patients screened for HRSNs between 2018 and 2019 (N = 45,312) were included in the analysis. Multivariable logistic regression models assessed the association between area-level SDoH scores and individual HRSNs. Bivariate choropleth maps displayed the intersection of area-level SDoH and individual HRSNs, and the sensitivity, specificity, and positive and negative predictive values of the three area-level metrics were assessed in relation to individual HRSNs.

The SDI and SVI were significantly associated with HRSNs in areas with high SDoH scores, with strong specificity and positive predictive values (∼83% and ∼78%) but poor sensitivity and negative predictive values (∼54% and 62%). The strength of these associations and predictive values was poor in areas with low SDoH scores.

While limitations exist in utilizing area-level SDoH metrics as proxies for individual social risk, understanding where and how these data can be useful in combination is critical both for meeting the immediate needs of individuals and for strengthening the advocacy platform needed for resource allocation across communities.