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Association between area-level poverty and HIV diagnoses, and differences by sex, New York City 2010-2011
Social conditions can exacerbate health inequities. We assessed the independent association of neighborhood poverty with HIV diagnosis rates and whether poverty has different effects by sex.
Methods
We calculated HIV diagnosis rates among persons 13+ years old by ZIP code, by sex and neighborhood poverty level, using 2010-2011 New York City (NYC) HIV surveillance data and Census 2010. Neighborhood poverty levels from American Community Survey 2007-2011 were percentage of residents in a ZIP with incomes below the federal poverty threshold, categorized as 0-<10% (“lowest-poverty”), 10-<20% (“medium-poverty”), 20-<30% (“high-poverty”), and 30-100% (“highest-poverty ZIPs”). Sex-stratified negative binomial Poisson regression models measured the effect of neighborhood-level poverty on HIV diagnosis rates, controlling for neighborhood-level education, race/ethnicity, age, and percent men who have sex with men.
Results
In 2010-2011, 6,184 persons were newly diagnosed with HIV in NYC. Median diagnosis rates per 100,000 increased by neighborhood poverty level overall (13.7 in lowest-poverty, 34.3 in medium-poverty, 50.6 in high-poverty, and 75.6 in highest-poverty ZIPs) and for males (20.1, 51.7, 82.3, 115.1, respectively) and females (2.4, 10.4, 20.0, 41.7, respectively). In multivariable analysis, higher neighborhood poverty remained associated with higher diagnosis rates among males (adjusted rate ratio (ARR)=1.63 [95% CI:1.34-1.97] for highest- vs. lowest-poverty ZIPs) and females (ARR=2.14 [95% CI:1.46-3.14]).
Conclusions
Living in highest-poverty vs. lowest-poverty urban neighborhoods was associated with increased HIV diagnosis rates. After controlling for other factors, diagnosis rates among females were relatively more sensitive to neighborhood poverty than those among males. Improvement of social conditions, such as alleviating poverty, may help decrease HIV diagnosis rates.
Learning Areas:
EpidemiologyLearning Objectives:
Describe the association of area-level poverty with HIV diagnosis rates
Compare the effect of poverty on HIV diagnoses between men and women
Keyword(s): HIV/AIDS, Poverty
Qualified on the content I am responsible for because: I am an epidemiologist who has worked for 10 years with the NYC HIV surveillance registry. I have led complex analyses and published results. I hold a Master of Health Science degree in Infectious Disease Epidemiology from the Johns Hopkins Bloomberg School of Public Health and have completed all coursework for a Doctor of Public Health degree in Epidemiology at the City University of New York. I have used Census and American Community Survey data.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.