Neighborhood Poverty and Influenza-Related Hospitalizations, FluSurv-NET, 2010-12
Methods: During the 2010-2011 and 2011-2012 surveillance seasons, FluSurv-NET identified 8716 hospitalized influenza cases. Of these, 7932 (91%) were geocoded and linked to US Census data. We used census tract as the neighborhood unit. Poverty was measured according to the 2008-2012 American Community Survey as household income below the federally defined poverty level. We categorized neighborhoods by their percent of households in poverty (<5%, 5-<10%, 10-<19%, ≥20%) and calculated age adjusted (2000 US Standard Population) influenza-related hospitalization incidence overall and for each FluSurv-NET site stratified by neighborhood poverty status. Denominator data for incidence calculations came from the 2010 US Census.
Results: For both seasons combined, the age adjusted cumulative incidence of influenza-related hospitalizations in high poverty (≥20%) neighborhoods was 43.4 per 100,000 population (95%CI: 42.3, 44.6), nearly twice the incidence in low poverty (<5%) neighborhoods (21.9 per 100,000, 95%CI: 20.8, 23.1). This relationship was observed in all 14 surveillance sites with the smallest disparity observed in Georgia (Standardized Rate Ratio (SRR) 1.3; 95%CI: 1.1, 1.7) and the greatest in Minnesota (SRR 3.4; 95%CI: 2.7, 4.3). Restricting the analysis to pediatric cases, the relationship also remained for the 13 surveillance sites with at least 10 cases aged <18 years. The SRR also varied by site for pediatric cases, ranging from 1.4 (95%CI: 1.0, 1.9) in Colorado to 5.0 (95%CI: 3.2, 7.8) in Minnesota.
Conclusions: High poverty neighborhoods consistently experienced greater influenza hospitalization rates than low poverty neighborhoods across all age groups, although the extent of this disparity varied by site. Studies have shown that neighborhood disadvantage and crowding correlate with lower resident health status. Linking geocoded surveillance data and US Census data can reveal vulnerable populations masked by conventional surveillance methods. Ongoing monitoring of area-based socioeconomic correlates of health may help target interventions where they are needed most.
Protection of the public in relation to communicable diseases including prevention or control
Social and behavioral sciences
Describe the relationship between census tract-level poverty and influenza-related hospitalization. Describe the value of analyzing surveillance data using an area-based socioeconomic status measure and the feasibility of doing it across multiple jurisdictions.
Keyword(s): Health Disparities/Inequities, Surveillance
Qualified on the content I am responsible for because: I have MD and MPH degrees and trained in internal and preventive medicine and infectious diseases. I was Connecticut State Epidemiologist for 25 years in charge of the state infectious disease surveillance and control programs. Currently I am Clinical Professor at the Yale School of Public Health where I work on a number of Emerging Infections Program projects including the influenza hospitalization surveillance project and have a number of influenza and health disparities-related publications.
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.