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Association between area- level poverty and HIV diagnoses, and differences by sex, New York City 2010-2011 Ellen Wiewel, HIV Epidemiology & Field Services.

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Presentation on theme: "Association between area- level poverty and HIV diagnoses, and differences by sex, New York City 2010-2011 Ellen Wiewel, HIV Epidemiology & Field Services."— Presentation transcript:

1 Association between area- level poverty and HIV diagnoses, and differences by sex, New York City 2010-2011 Ellen Wiewel, HIV Epidemiology & Field Services Program, New York City Department of Health & Mental Hygiene APHA abstract #296498, Session 4331.0, “Structural and Institutional Issues in HIV/AIDS,” Tuesday, November 18, 2014

2 Presenter Disclosures The following personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months: Ellen Wiewel No relationships to disclose

3 Place & social conditions matter Most investigations of determinants of HIV infection focus on individual traits (risk, race) Social conditions (e.g., neighborhood poverty) contribute to health disparities of many kinds, including HIV infection

4 Gap in research on HIV and neighborhood poverty Link between HIV and neighborhood poverty has not been explored by ZIP code in a US city and could inform local policy Are differences by neighborhood poverty level explained by differences in age and racial/ethnic composition?

5 Objectives Assess the association of neighborhood poverty with HIV diagnosis rates, after controlling for other neighborhood factors such as age and racial/ethnic composition Determine whether neighborhood poverty has different effects on HIV rates by sex

6 Methods (1) Ecological analysis Outcome: ZIP code-level HIV diagnosis rates among New York City residents 13+ years old, by sex

7 Methods (2) Sex-stratified negative binomial regression models measured effect of neighborhood-level poverty on diagnosis rates Covariates: neighborhood-level education, racial/ethnic composition, age distribution, and percent men who have sex with men

8 Data Sources Data source NYC HIV surveillance registry 2010-2011 NYC Community Health Survey 2009- 2011 American Community Survey 2007- 2011 US Census 2010 Population All NYC HIV cases Representative sample of NYC adults Representative sample of US population Every US resident Measures HIV diagnosesPercent MSM Poverty Education Sex Race/Ethnicity Age

9 Text Explanation of Data Sources Table Table of four data sources and the measures gleaned from each Data sources include NYC HIV surveillance registry, NYC Community Health Survey, American Community Survey, and US Census

10 Neighborhood Poverty Definition Percent in a ZIP with incomes below the federal poverty threshold Categories: 0-<10% (“low-poverty”) 10-<20% (“medium-poverty”) 20-<30% (“high-poverty”) 30-100% (“very-high-poverty ZIPs”)

11 Results (1) 180 residential NYC ZIP codes included 6,184 persons newly diagnosed with HIV in NYC in 2010-2011: 4,754 males and 1,430 females Overall annual HIV diagnosis rate: 44.8 per 100,000

12 Results (2) ZIP-level diagnosis rates in NYC ranged from 0.0 to 241.7 per 100,000 (median: 34.8 per 100,000) Median diagnosis rates by sex: – 56.2 per 100,000 males – 10.4 per 100,000 females

13 Figure 1b. Male HIV diagnosis ratesFigure 1c. Female HIV diagnosis rates Mapping Poverty and HIV in NYC

14 Text Explanation of Maps Three NYC ZIP code maps showing poverty rates and male and female HIV diagnosis rates High- and very-high-poverty ZIP codes appear to have higher male and female HIV diagnosis rates

15 Box Plots of Annualized HIV Diagnosis Rates per 100,000 Persons, by Neighborhood Poverty, NYC 2010-2011 Males Females

16 Text Explanation of Box Plots Two box plots of male and female HIV diagnosis rates by NYC ZIP code Males and females have higher HIV diagnosis rates as neighborhood poverty increases

17 Regression of Neighborhood Poverty and HIV Diagnosis Rates Among Males and Females in 180 NYC ZIP Codes, 2010-2011

18 Text Explanation of Regression Table Table of crude and adjusted rate ratios (RRs) from Poisson regression of ZIP code-level HIV diagnosis rates among males and females by neighborhood poverty level Crude and adjusted RRs increase with increasing poverty, and increase more among females than males

19 Summary of Findings (1) HIV diagnosis rates among males and females increased with increasing neighborhood poverty At all neighborhood poverty levels, higher diagnosis rates among males than females

20 Summary of Findings (2) Living in very-high- vs. low-poverty neighborhoods was associated with an increase in HIV diagnosis rates of 63% for males and 114% for females Relative difference in rates between neighborhoods with very high vs. low poverty particularly large for women

21 Limitations ZIP code is larger area than is optimal for detection of disparities (Census tract and Census block) Diagnosis rates rather than incidence rates (only diagnoses are reportable) Explained neither how poverty influences HIV nor why relative impact of poverty is larger on females

22 Strengths First ecological analysis of HIV diagnosis rates and poverty at the ZIP code level and in a US city One of few analyses to assess sex differences in the poverty-HIV relationship

23 Conclusions Area-based poverty was associated with HIV diagnoses in NYC, supporting interventions making structural and social changes Other structural urban HIV prevention should focus on higher-poverty areas Prevention strategies addressing poverty are important for males and (especially) females

24 Next Steps NYC health department already focuses HIV prevention, care, and treatment on higher-poverty areas Support other local place-based approaches to HIV prevention Future research: poverty’s influence on care continuum, e.g., linkage to care and viral suppression

25 Acknowledgments Coauthors Angelica Bocour, Laura Kersanske, Sara Bodach, Qiang Xia, and Sarah Braunstein (all with the New York City Department of Health & Mental Hygiene at the time of this analysis) NYC Department of Health & CUNY SPH Dean Dr. Ayman El-Mohandes for travel stipends

26 Contact Ellen Wiewel ewiewel@health.nyc.gov

27 Appendix. Distribution of model outcomes, covariates, and poverty level among New York City ZIP codes (N=180), for persons 13+ years old


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