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

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.

scholarly journals An Examination of Geographic Differences in Social Determinants of Health Among Women with Diagnosed HIV in the United States and Puerto Rico, 2017

2021 ◽  
Vol 15 (1) ◽  
pp. 10-20
Author(s):  
Ndidi Nwangwu-Ike ◽  
Chan Jin ◽  
Zanetta Gant ◽  
Shacara Johnson ◽  
Alexandra B. Balaji
Keyword(s):  
United States ◽  
Puerto Rico ◽  
Health Insurance ◽  
Social Determinants ◽  
Census Tract ◽  
The United States ◽  
Adult Women ◽  
Hiv Diagnosis ◽  
Census Tracts ◽  
Census Tract Level

Objective: To examine differences, at the census tract level, in the distribution of human immunodeficiency virus (HIV) diagnoses and social determinants of health (SDH) among women with diagnosed HIV in 2017 in the United States and Puerto Rico. Background: In the United States, HIV continues to disproportionately affect women, especially minority women and women in the South. Methods: Data reported in the National HIV Surveillance System (NHSS) of the Centers for Disease Control and Prevention were used to determine census tract-level HIV diagnosis rates and percentages among adult women (aged ≥18 years) in 2017. Data from the American Community Survey were combined with NHSS data to examine regional differences in federal poverty status, education level, income level, employment status, and health insurance coverage among adult women with diagnosed HIV infection in the United States and Puerto Rico. Results: In the United States and Puerto Rico, among 6,054 women who received an HIV diagnosis in 2017, the highest rates of HIV diagnoses generally were among those who lived in census tracts where the median household income was less than $40,000; at least 19% lived below the federal poverty level, at least 18% had less than a high school diploma, and at least 16% were without health insurance. Conclusion: This study is the first of its kind and gives insight into how subpopulations of women are affected differently by the likelihood of an HIV diagnosis. The findings show that rates of HIV diagnosis were highest among women who lived in census tracts having the lowest income and least health coverage.

scholarly journals A Census Tract–Level Examination of Differences in Social Determinants of Health Among People With HIV, by Race/Ethnicity and Geography, United States and Puerto Rico, 2017

2021 ◽  
pp. 003335492199037
Author(s):  
Shacara Johnson Lyons ◽  
Zanetta Gant ◽  
Chan Jin ◽  
André Dailey ◽  
Ndidi Nwangwu-Ike ◽  
...  
Keyword(s):  
United States ◽  
Puerto Rico ◽  
Health Insurance ◽  
Census Tract ◽  
Hiv Diagnosis ◽  
Census Tract Level ◽  
Race Ethnicity ◽  
Vacant Housing ◽  
Racial Ethnic ◽  
Hispanic White

Objective Social and structural factors, referred to as social determinants of health (SDH), create pathways or barriers to equitable sexual health, and information on these factors can provide critical insight into rates of diseases such as HIV. Our objectives were to describe and identify differences, by race/ethnicity and geography, in SDH among adults with HIV. Methods We conducted an ecological study to explore SDH among people with HIV diagnosed in 2017, by race/ethnicity and geography, at the census-tract level in the United States and Puerto Rico. We defined the least favorable SDH as the following: low income (<$40 000 in median annual household income), low levels of education (≥18% of residents have <high school diploma), high levels of poverty (≥19% of residents live below the federal poverty level), unemployment (≥6% of residents in the workface do not have a job), lack of health insurance (≥16% of residents lack health insurance), and vacant housing (≥15% of housing units are vacant). Results HIV diagnosis rates increased 1.4 to 4.0 times among men and 1.5 to 5.5 times among women as census-tract poverty levels increased, education levels decreased, income decreased, unemployment increased, lack of health insurance increased, and vacant housing increased. Among racial/ethnic groups by region and SDH, we observed higher HIV diagnosis rates per 100 000 population among non-Hispanic Black (49.6) and non-Hispanic White (6.5) adults in the South and among Hispanic/Latino (27.4) adults in the Northeast than in other regions. We observed higher HIV diagnosis rates per 100 000 population among non-Hispanic Black (44.3) and Hispanic/Latino (21.1) adults than among non-Hispanic White (5.1) adults. Conclusion Our findings highlight the importance of SDH in HIV infection and support the need for effective, targeted local interventions to specific populations based on HIV diagnoses and prevalence to prevent infection and reduce racial/ethnic disparities.

Linkage to HIV Medical Care and Social Determinants of Health Among Adults With Diagnosed HIV Infection in 41 States and the District of Columbia, 2017

2021 ◽  
pp. 003335492110299
Author(s):  
Myrline Gillot ◽  
Zanetta Gant ◽  
Xiaohong Hu ◽  
Anna Satcher Johnson
Keyword(s):  
Health Insurance ◽  
Hiv Infection ◽  
Medical Care ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Determinants Of Health ◽  
Hiv Care ◽  
Care Outcomes

Objectives To reduce the number of new HIV infections and improve HIV health care outcomes, the social conditions in which people live and work should be assessed. The objective of this study was to describe linkage to HIV medical care by selected demographic characteristics and social determinants of health (SDH) among US adults with HIV at the county level. Methods We used National HIV Surveillance System data from 42 US jurisdictions and data from the American Community Survey to describe differences in linkage to HIV medical care among adults aged ≥18 with HIV infection diagnosed in 2017. We categorized SDH variables into higher or lower levels of poverty (where <13% or ≥13% of the population lived below the federal poverty level), education (where <13% or ≥13% of the population had <high school diploma), and health insurance coverage (where <12% or ≥12% of the population lacked health insurance). We calculated prevalence ratios (PRs) and 95% CIs. Results Of 33 204 adults with HIV infection diagnosed in 2017, 78.4% were linked to HIV medical care ≤1 month after diagnosis. Overall, rates of linkage to care were significantly lower among men and women living in counties with higher versus lower poverty (PR = 0.96; 95% CI, 0.94-0.97), with lower versus higher health insurance coverage (PR = 0.93; 95% CI, 0.92-0.94), and with lower versus higher education levels (PR = 0.97; 95% CI, 0.96-0.98). Conclusions Increasing health insurance coverage and addressing economic and educational disparities would likely lead to better HIV care outcomes in these areas.

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

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.

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

2017 ◽  
Vol 25 (4) ◽  
pp. 419-422 ◽  
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.

scholarly journals Social Determinants of Health and Disparities in Linkage to Care Among Newly Diagnosed HIV Cases – South Carolina, 2009–2011

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S419-S420 ◽  
Author(s):  
Harmeet Gill ◽  
Oluwole Babatunde ◽  
Sharon Weissman
Keyword(s):  
South Carolina ◽  
Racial Disparities ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Census Tract ◽  
Linkage To Care ◽  
Male Gender ◽  
Determinants Of Health ◽  
Newly Diagnosed ◽  
Hiv Diagnosis

Abstract Background Key to improved HIV outcomes is early diagnosis, linkage to care (LTC), retention in care (RIC) and viral load (VL) suppression. As treatment for HIV has become more effective, the gap in racial disparities has widened for LTC, RIC and VL. Social determinants of health (SDH) are conditions such as poverty level, income, education, employment that are responsible for most health inequities. SDH are drivers of disparities in HIV prevalence. The objective of this study is to evaluate the impact of SDH on racial disparities on time to LTC for newly diagnosed HIV infected individuals in South Carolina (SC). Methods Data was obtained from the SC enhanced HIV/AIDS Reporting System. Analysis includes individuals diagnosed with HIV in SC from 2009–2011. LTC was calculated as the time from HIV diagnosis to first CD4 or VL test. Early LTC was defined as within 30 days. Late LTC was &gt;30 to 365 days. Individuals not LTC by 365 days were considered to have never been linked to care (NLTC). Census tract data was used to determine SHD (poverty, education, income, and unemployment) based on residence at the time of HIV diagnosis. Descriptive analysis was performed on data from newly infected individuals. Factors potentially associated with late LTC and NLTC including patient demographics, behavioral risk, residence at diagnosis and SDH were investigated. Results From 2009–2011, 2151 individuals were newly diagnosed with HIV. Of these 1636 (76.1%) were LTC early, 285 (13.2%) were LTC late and 230 (10.7%) were NLTC. NLTC was associated with male gender, lower initial CD4 count, and earlier stage of HIV at time of diagnoses (P &lt;0.01). In multivariable analysis early HIV stage at HIV diagnosis (aOR: 1.82; 95% CI 1.3, 2.5) and living in census tracts with lower income (aOR 0.65; 95% CI 0.44, 0.97) are associated with late LTC. Male gender (aOR 2.66; 95% CI 1.49, 4.76) unknown HIV risk group (aOR 2.03; 95% CI 1.11, 2.74) and early HIV stage at diagnosis (aOR 4.59; 95% CI 2.33, 9.04) are associated with NLTC. Conclusion In SC, almost ¼ of newly diagnosed HIV infected individuals from 2009–2011 were LTC late or NLTC. SDH were not associated with late LTC or NLTC. Living in a low income census tract was associated with a lower risk for late LTC, possible because of access to Ryan White Services. Male gender and earlier HIV stage were factors with greatest association with late LTC and NLTC. Disclosures All authors: No reported disclosures.

scholarly journals Associations between Greenspace and Gentrification-Related Sociodemographic and Housing Cost Changes in Major Metropolitan Areas across the United States

2021 ◽  
Vol 18 (6) ◽  
pp. 3315
Author(s):  
Leah H. Schinasi ◽  
Helen V. S. Cole ◽  
Jana A. Hirsch ◽  
Ghassan B. Hamra ◽  
Pedro Gullon ◽  
...  
Keyword(s):  
United States ◽  
Census Tract ◽  
Household Income ◽  
The United States ◽  
Effect Modification ◽  
Ethnic Composition ◽  
Housing Cost ◽  
Census Tract Level ◽  
Specific Distribution ◽  
Meta Analyses

Neighborhood greenspace may attract new residents and lead to sociodemographic or housing cost changes. We estimated relationships between greenspace and gentrification-related changes in the 43 largest metropolitan statistical areas (MSAs) of the United States (US). We used the US National Land Cover and Brown University Longitudinal Tracts databases, as well as spatial lag models, to estimate census tract-level associations between percentage greenspace (years 1990, 2000) and subsequent changes (1990–2000, 2000–2010) in percentage college-educated, percentage working professional jobs, race/ethnic composition, household income, percentage living in poverty, household rent, and home value. We also investigated effect modification by racial/ethnic composition. We ran models for each MSA and time period and used random-effects meta-analyses to derive summary estimates for each period. Estimates were modest in magnitude and heterogeneous across MSAs. After adjusting for census-tract level population density in 1990, compared to tracts with low percentage greenspace in 1992 (defined as ≤50th percentile of the MSA-specific distribution in 1992), those with high percentage greenspace (defined as >75th percentile of the MSA-specific distribution) experienced higher 1990–2000 increases in percentage of the employed civilian aged 16+ population working professional jobs (β: 0.18, 95% confidence interval (CI): 0.11, 0.26) and in median household income (β: 0.23, 95% CI: 0.15, 0.31). Adjusted estimates for the 2000–2010 period were near the null. We did not observe evidence of effect modification by race/ethnic composition. We observed evidence of modest associations between greenspace and gentrification trends. Further research is needed to explore reasons for heterogeneity and to quantify health implications.

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