Kimberly M Yousey-Hindes1, James L Hadler. 1. Yale office of the Connecticut Emerging Infections Program, Yale School of Public Health, New Haven, USA. kimberly.yousey-hindes@yale.edu
Abstract
OBJECTIVES: We examined surveillance data for disparities in pediatric influenza-associated hospitalizations according to neighborhood socioeconomic status (SES) measures in New Haven County, Connecticut. METHODS: We geocoded influenza-associated hospitalization case data from the past 7 years for children from birth to age 17 years and linked these to US Census 2000 tract-level SES data. Following the methods of Harvard's Public Health Disparities Geocoding Project, we examined neighborhood SES variables, including measures of poverty and crowding. We calculated influenza-associated hospitalization incidence by influenza season and individual case characteristics, stratified by SES measures. RESULTS: Overall, the mean annual incidence of pediatric influenza-associated hospitalization in high-poverty and high-crowding census tracts was at least 3 times greater than that in low-poverty and low-crowding tracts. This disparity could not be fully explained by prevalence of underlying conditions or receipt of influenza vaccination. CONCLUSIONS: Linkage of geocoded surveillance data and census information allows for ongoing monitoring of SES correlates of health and may help target interventions. Our analysis indicates a correlation between residence in impoverished or crowded neighborhoods and incidence of influenza-associated hospitalization among children in Connecticut.
OBJECTIVES: We examined surveillance data for disparities in pediatric influenza-associated hospitalizations according to neighborhood socioeconomic status (SES) measures in New Haven County, Connecticut. METHODS: We geocoded influenza-associated hospitalization case data from the past 7 years for children from birth to age 17 years and linked these to US Census 2000 tract-level SES data. Following the methods of Harvard's Public Health Disparities Geocoding Project, we examined neighborhood SES variables, including measures of poverty and crowding. We calculated influenza-associated hospitalization incidence by influenza season and individual case characteristics, stratified by SES measures. RESULTS: Overall, the mean annual incidence of pediatric influenza-associated hospitalization in high-poverty and high-crowding census tracts was at least 3 times greater than that in low-poverty and low-crowding tracts. This disparity could not be fully explained by prevalence of underlying conditions or receipt of influenza vaccination. CONCLUSIONS: Linkage of geocoded surveillance data and census information allows for ongoing monitoring of SES correlates of health and may help target interventions. Our analysis indicates a correlation between residence in impoverished or crowded neighborhoods and incidence of influenza-associated hospitalization among children in Connecticut.
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