scholarly journals O12.1 Using Social Determinants to PredictNeisseria GonorrhoeaeInfection Risk at the Census Tract-Level: Findings from the STD Surveillance Network (SSuN), United States

2013 ◽  
Vol 89 (Suppl 1) ◽  
pp. A48.3-A49 ◽  
Author(s):  
M Stenger ◽  
M Samuel ◽  
H Weinstock
Keyword(s):  
United States ◽  
Social Determinants ◽  
Census Tract ◽  
Surveillance Network ◽  
Census Tract Level

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 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.

scholarly journals Racial Disparity and Social Determinants in Receiving Timely Surgery Among Stage I–IIIA Non-small Cell Lung Cancer Patients in a U.S. Southern State

2021 ◽  
Vol 9 ◽  
Author(s):  
Paige Neroda ◽  
Mei-Chin Hsieh ◽  
Xiao-Cheng Wu ◽  
Kathleen B. Cartmell ◽  
Rachel Mayo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Social Determinants ◽  
Census Tract ◽  
Racial Disparity ◽  
Poverty Level ◽  
Lung Cancer Patients ◽  
Delayed Surgery ◽  
Census Tract Level ◽  
Black Patients

Delayed surgery is associated with worse lung cancer outcomes. Social determinants can influence health disparities. This study aimed to examine the potential racial disparity and the effects from social determinants on receipt of timely surgery among lung cancer patients in Louisiana, a southern state in the U.S. White and black stage I–IIIA non-small cell lung cancer patients diagnosed in Louisiana between 2004 and 2016, receiving surgical lobectomy or a more extensive surgery, were selected. Diagnosis-to-surgery interval &gt;6 weeks were considered as delayed surgery. Social determinants included marital status, insurance, census tract level poverty, and census tract level urbanicity. Multivariable logistic regression and generalized multiple mediation analysis were conducted. A total of 3,616 white (78.9%) and black (21.1%) patients were identified. The median time interval from diagnosis to surgery was 27 days in whites and 42 days in blacks (P &lt; 0.0001). About 28.7% of white and 48.4% of black patients received delayed surgery (P &lt; 0.0001). Black patients had almost two-fold odds of receiving delayed surgery than white patients (adjusted odds ratio: 1.91; 95% confidence interval: 1.59–2.30). Social determinants explained about 26% of the racial disparity in receiving delayed surgery. Having social support, private insurance, and living in census tracts with lower poverty level were associated with improved access to timely surgery. The census tract level poverty level a stronger effect on delayed surgery in black patients than in white patients. Tailored interventions to improve the timely treatment in NSCLC patients, especially black patients, are needed in the future.

scholarly journals Disparities in Shigellosis Incidence by Census Tract Poverty, Crowding, and Race/Ethnicity in the United States, FoodNet, 2004–2014

2020 ◽  
Vol 7 (2) ◽  
Author(s):  
Tanya Libby ◽  
Paula Clogher ◽  
Elisha Wilson ◽  
Nadine Oosmanally ◽  
Michelle Boyle ◽  
...  
Keyword(s):  
United States ◽  
Incidence Rate ◽  
Census Tract ◽  
Negative Binomial ◽  
Geographic Location ◽  
Negative Binomial Regression ◽  
The United States ◽  
Incidence Rates ◽  
Surveillance Network ◽  
Race Ethnicity

Abstract Background Shigella causes an estimated 500 000 enteric illnesses in the United States annually, but the association with socioeconomic factors is unclear. Methods We examined possible epidemiologic associations between shigellosis and poverty using 2004–2014 Foodborne Diseases Active Surveillance Network (FoodNet) data. Shigella cases (n = 21 246) were geocoded, linked to Census tract data from the American Community Survey, and categorized into 4 poverty and 4 crowding strata. For each stratum, we calculated incidence by sex, age, race/ethnicity, and FoodNet site. Using negative binomial regression, we estimated incidence rate ratios (IRRs) comparing the highest to lowest stratum. Results Annual FoodNet Shigella incidence per 100 000 population was higher among children &lt;5 years old (19.0), blacks (7.2), and Hispanics (5.6) and was associated with Census tract poverty (incidence rate ratio [IRR], 3.6; 95% confidence interval [CI], 3.5–3.8) and household crowding (IRR, 1.8; 95% CI, 1.7–1.9). The association with poverty was strongest among children and persisted regardless of sex, race/ethnicity, or geographic location. After controlling for demographic variables, the association between shigellosis and poverty remained significant (IRR, 2.3; 95% CI, 2.0–2.6). Conclusions In the United States, Shigella infections are epidemiologically associated with poverty, and increased incidence rates are observed among young children, blacks, and Hispanics.

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.

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