A Census Tract–Level Examination of Social Determinants of Health among Black/African American Men with Diagnosed HIV Infection, 2005–2009—17 US Areas

African American men’s health has at times been regarded as irrelevant to the health and well-being of the communities where they are born, grow, live, work, and age. The uniqueness of being male and of African descent calls for a critical examination and deeper understanding of the psycho-socio-historical context in which African American men have lived. There is a critical need for scholarship that better contextualizes African American Male Theory and cultural humility in terms of public health. Furthermore, the focus of much of the social determinants of health and health equity policy literature has been on advocacy, but few researchers have examined why health-related public policies have not been adopted and implemented from a political and theoretical policy analysis perspective. The purpose of this article will be to examine African American men’s health within the context of social determinants of health status, health behavior, and health inequalities—elucidating policy implications for system change and providing recommendations from the vantage point of health equity.

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Book Review: Social Determinants of Health Among African American Men

American Journal of Men s Health ◽

10.1177/1557988313490787 ◽

2013 ◽

Vol 7 (4_suppl) ◽

pp. 43S-44S

Author(s):

Leonard Jack

Keyword(s):

African American ◽

Social Determinants Of Health ◽

Social Determinants ◽

African American Men ◽

Determinants Of Health

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Geographic Differences and Social Determinants of Health Among People With HIV Attributed to Injection Drug Use, United States, 2017

Public Health Reports ◽

10.1177/00333549211007168 ◽

2021 ◽

pp. 003335492110071

Author(s):

Chan Jin ◽

Ndidi Nwangwu-Ike ◽

Zanetta Gant ◽

Shacara Johnson Lyons ◽

Anna Satcher Johnson

Keyword(s):

United States ◽

Health Insurance ◽

Drug Use ◽

Hiv Infection ◽

Social Determinants Of Health ◽

Social Determinants ◽

Census Tract ◽

People Who Inject Drugs ◽

Hiv Diagnosis ◽

Census Tract Level

Objective People who inject drugs are among the groups most vulnerable to HIV infection. The objective of this study was to describe differences in the geographic distribution of HIV diagnoses and social determinants of health (SDH) among people who inject drugs (PWID) who received an HIV diagnosis in 2017. Methods We used data from the National HIV Surveillance System (NHSS) to determine the counts and percentages of PWID aged ≥18 with HIV diagnosed in 2017. We combined these data with data from the US Census Bureau’s American Community Survey at the census tract level to examine regional, racial/ethnic, and population-area-of-residence differences in poverty status, education level, income level, employment status, and health insurance coverage. Results We observed patterns of disparity in HIV diagnosis counts and SDH among the 2666 PWID with a residential address linked to a census tract, such that counts of HIV diagnosis increased as SDH outcomes became worse. The greatest proportion of PWID lived in census tracts where ≥19% of the residents lived below the federal poverty level, ≥18% of the residents had <high school diploma, the median annual household income was <$40 000, and ≥16% of the residents did not have health insurance or a health coverage plan. Conclusion To our knowledge, our study is the first large-scale, census tract–level study to describe SDH among PWID with diagnosed HIV in the United States. The findings of substantial disparities in SDH among people with HIV infection attributed to injection drug use should be further examined. Understanding the SDH among PWID is crucial to reducing disparities in HIV diagnoses in this population.

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Social determinants of health and hospital readmissions: can the HOSPITAL risk score be improved by the inclusion of social factors?

BMC Health Services Research ◽

10.1186/s12913-020-05989-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Shirlene Obuobi ◽

Rhys F. M. Chua ◽

Stephanie A. Besser ◽

Corey E. Tabit

Keyword(s):

Social Determinants Of Health ◽

Risk Score ◽

Social Determinants ◽

Census Tract ◽

Predictive Accuracy ◽

Hospital Readmissions ◽

Tertiary Care ◽

Determinants Of Health ◽

Census Tract Level ◽

C Statistic

Abstract Background The HOSPITAL Risk Score (HRS) predicts 30-day hospital readmissions and is internationally validated. Social determinants of health (SDOH) such as low socioeconomic status (SES) affect health outcomes and have been postulated to affect readmission rates. We hypothesized that adding SDOH to the HRS could improve its predictive accuracy. Methods Records of 37,105 inpatient admissions at the University of Chicago Medical Center were reviewed. HRS was calculated for each patient. Census tract-level SDOH then were combined with the HRS and the performance of the resultant “Social HRS” was compared against the HRS. Patients then were assigned to 1 of 7 typologies defined by their SDOH and a balanced dataset of 14,235 admissions was sampled from the larger dataset to avoid over-representation by any 1 sociodemographic group. Principal component analysis and multivariable linear regression then were performed to determine the effect of SDOH on the HRS. Results The c-statistic for the HRS predicting 30-day readmission was 0.74, consistent with published values. However, the addition of SDOH to the HRS did not improve the c-statistic (0.71). Patients with unfavorable SDOH (no high-school, limited English, crowded housing, disabilities, and age > 65 yrs) had significantly higher HRS (p < 0.05 for all). Overall, SDOH explained 0.2% of the HRS. Conclusion At an urban tertiary care center, the addition of census tract-level SDOH to the HRS did not improve its predictive power. Rather, the effects of SDOH are already reflected in the HRS.

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FACETS: using open data to measure community social determinants of health

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocx117 ◽

2017 ◽

Vol 25 (4) ◽

pp. 419-422 ◽

Cited By ~ 5

Author(s):

Michael N Cantor ◽

Rajan Chandras ◽

Claudia Pulgarin

Keyword(s):

Social Determinants Of Health ◽

Social Determinants ◽

Census Tract ◽

National Level ◽

Open Data ◽

Community Level ◽

Determinants Of Health ◽

Data Sources ◽

Open Architecture ◽

Census Tract Level

Abstract Objective To develop a dataset based on open data sources reflective of community-level social determinants of health (SDH). Materials and Methods We created FACETS (Factors Affecting Communities and Enabling Targeted Services), an architecture that incorporates open data related to SDH into a single dataset mapped at the census-tract level for New York City. Results FACETS (https://github.com/mcantor2/FACETS) can be easily used to map individual addresses to their census-tract-level SDH. This dataset facilitates analysis across different determinants that are often not easily accessible. Discussion Wider access to open data from government agencies at the local, state, and national level would facilitate the aggregation and analysis of community-level determinants. Timeliness of updates to federal non-census data sources may limit their usefulness. Conclusion FACETS is an important first step in standardizing and compiling SDH-related data in an open architecture that can give context to a patient’s condition and enable better decision-making when developing a plan of care.

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Social determinants of health among African–American men

Journal of Men s Health ◽

10.1016/j.jomh.2009.12.002 ◽

2010 ◽

Vol 7 (1) ◽

pp. 11-19 ◽

Cited By ~ 51

Author(s):

Clare Xanthos ◽

Henrie M. Treadwell ◽

Kisha Braithwaite Holden

Keyword(s):

African American ◽

Social Determinants Of Health ◽

Social Determinants ◽

African American Men ◽

Determinants Of Health

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Social determinants of health affecting treatment of pediatric brain tumors

Journal of Neurosurgery Pediatrics ◽

10.3171/2019.4.peds18594 ◽

2019 ◽

Vol 24 (2) ◽

pp. 159-165

Author(s):

Jillian M. Berkman ◽

Jonathan Dallas ◽

Jaims Lim ◽

Ritwik Bhatia ◽

Amber Gaulden ◽

...

Keyword(s):

African American ◽

Health Disparities ◽

Brain Tumors ◽

Social Determinants Of Health ◽

Social Determinants ◽

Determinants Of Health ◽

Cns Tumor ◽

Initial Symptoms ◽

Caucasian Patients

OBJECTIVELittle is understood about the role that health disparities play in the treatment and management of brain tumors in children. The purpose of this study was to determine if health disparities impact the timing of initial and follow-up care of patients, as well as overall survival.METHODSThe authors conducted a retrospective study of pediatric patients (< 18 years of age) previously diagnosed with, and initially treated for, a primary CNS tumor between 2005 and 2012 at Monroe Carell Jr. Children’s Hospital at Vanderbilt. Primary outcomes included time from symptom presentation to initial neurosurgery consultation and percentage of missed follow-up visits for ancillary or core services (defined as no-show visits). Core services were defined as healthcare interactions directly involved with CNS tumor management, whereas ancillary services were appointments that might be related to overall care of the patient but not directly focused on treatment of the tumor. Statistical analysis included Pearson’s chi-square test, nonparametric univariable tests, and multivariable linear regression. Statistical significance was set a priori at p < 0.05.RESULTSThe analysis included 198 patients. The median time from symptom onset to initial presentation was 30.0 days. A mean of 7.45% of all core visits were missed. When comparing African American and Caucasian patients, there was no significant difference in age at diagnosis, timing of initial symptoms, or tumor grade. African American patients missed significantly more core visits than Caucasian patients (p = 0.007); this became even more significant when controlling for other factors in the multivariable analysis (p < 0.001). African American patients were more likely to have public insurance, while Caucasian patients were more likely to have private insurance (p = 0.025). When evaluating survival, no health disparities were identified.CONCLUSIONSNo significant health disparities were identified when evaluating the timing of presentation and survival. A racial disparity was noted when evaluating missed follow-up visits. Future work should focus on identifying reasons for differences and whether social determinants of health affect other aspects of treatment.

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Social determinants of health in male forensic patients admitted at a tertiary psychiatric hospital in South Africa

International Journal of Social Psychiatry ◽

10.1177/00207640211060261 ◽

2021 ◽

pp. 002076402110602

Author(s):

Keabetswe Mogase ◽

Tshepiso Moeketsi ◽

Funeka B Sokudela

Keyword(s):

Health Outcomes ◽

Social Determinants Of Health ◽

Social Determinants ◽

Social Factors ◽

Psychiatric Patients ◽

Determinants Of Health ◽

Main Stream ◽

Multivariate Statistical ◽

Black African ◽

Forensic Patients

Introduction: Social factors are increasingly being used to determine health outcomes. The concept of social determinants of health has been used to shape policies that address disparities. There is a paucity of such studies in the forensic setting. This study aimed to use social determinants of health to identify social factors that are associated with being a male forensic patient. Methods: The study was a retrospective two-group (forensic and non-forensic) comparison clinical record review. Association was identified through independent and multivariate statistical analysis. Results: The study sample comprised of 296 patients, 56.4% ( n = 167) of which were non-forensic. The majority of the sample was black African, 50 years and older, single, unemployed and had attended main-stream schooling. Race ( p < .01), employment status ( p < .02), not completing high school ( p < .01), previous imprisonment ( p < .01), drug use ( p < .01) and not being on medication prior to admission ( p < .01) were significantly associated with being a forensic patient. Multivariate logistic regression analyses also confirmed these associations. Conclusion: Social determinants of health ought to be targeted to improve health outcomes of psychiatric patients. Collaborations between mental health, public health, law and policy makers as well as non-/governmental agencies may lead to change. Human rights of individuals with mental illness may thus be enhanced in the long run.

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California Healthy Places Index: Frames Matter

Public Health Reports ◽

10.1177/0033354919849882 ◽

2019 ◽

Vol 134 (4) ◽

pp. 354-362

Author(s):

Neil Maizlish ◽

Tracy Delaney ◽

Helen Dowling ◽

Derek A. Chapman ◽

Roy Sabo ◽

...

Keyword(s):

Life Expectancy ◽

Social Determinants Of Health ◽

Social Determinants ◽

Census Tract ◽

Well Being ◽

Determinants Of Health ◽

Policy Action ◽

Census Tracts ◽

Life Expectancy At Birth ◽

The Social

Introduction: We describe the California Healthy Places Index (HPI) and its performance relative to other indexes for measuring community well-being at the census-tract level. The HPI arose from a need identified by health departments and community organizations for an index rooted in the social determinants of health for place-based policy making and program targeting. The index was geographically granular, validated against life expectancy at birth, and linked to policy actions. Materials and Methods: Guided by literature, public health experts, and a positive asset frame, we developed a composite index of community well-being for California from publicly available census-tract data on place-based factors linked to health. The 25 HPI indicators spanned 8 domains; weights were derived from their empirical association with tract-level life expectancy using weighted quantile sums methods. Results: The HPI’s domains were aligned with the social determinants of health and policy action areas of economic resources, education, housing, transportation, clean environment, neighborhood conditions, social resources, and health care access. The overall HPI score was the sum of weighted domain scores, of which economy and education were highly influential (50% of total weights). The HPI was strongly associated with life expectancy at birth ( r = 0.58). Compared with the HPI, a pollution-oriented index did not capture one-third of the most disadvantaged quartile of census tracts (representing 3 million Californians). Overlap of the HPI’s most disadvantaged quartile of census tracts was greater for indexes of economic deprivation. We visualized the HPI percentile ranking as a web-based mapping tool that presented the HPI at multiple geographies and that linked indicators to an action-oriented policy guide. Practice Implications: The framing of indexes and specifications such as domain weighting have substantial consequences for prioritizing disadvantaged populations. The HPI provides a model for tools and new methods that help prioritize investments and identify multisectoral opportunities for policy action.

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