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Neighborhood socioeconomic status and influenza hospitalizations among children: New Haven County, Connecticut, 2003-2010

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  • Yousey-Hindes, K.M.
  • Hadler, J.L.

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.

Suggested Citation

  • Yousey-Hindes, K.M. & Hadler, J.L., 2011. "Neighborhood socioeconomic status and influenza hospitalizations among children: New Haven County, Connecticut, 2003-2010," American Journal of Public Health, American Public Health Association, vol. 101(9), pages 1785-1789.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2011.300224_9
    DOI: 10.2105/AJPH.2011.300224
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    Cited by:

    1. Samuel V Scarpino & James G Scott & Rosalind M Eggo & Bruce Clements & Nedialko B Dimitrov & Lauren Ancel Meyers, 2020. "Socioeconomic bias in influenza surveillance," PLOS Computational Biology, Public Library of Science, vol. 16(7), pages 1-19, July.
    2. Carroll-Scott, Amy & Gilstad-Hayden, Kathryn & Rosenthal, Lisa & Peters, Susan M. & McCaslin, Catherine & Joyce, Rebecca & Ickovics, Jeannette R., 2013. "Disentangling neighborhood contextual associations with child body mass index, diet, and physical activity: The role of built, socioeconomic, and social environments," Social Science & Medicine, Elsevier, vol. 95(C), pages 106-114.
    3. Stolte, Allison & Merli, M. Giovanna & Hurst, Jillian H. & Liu, Yaxing & Wood, Charles T. & Goldstein, Benjamin A., 2022. "Using Electronic Health Records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research," Social Science & Medicine, Elsevier, vol. 296(C).
    4. Laurens Holmes & Michael Enwere & Janille Williams & Benjamin Ogundele & Prachi Chavan & Tatiana Piccoli & Chinacherem Chinaka & Camillia Comeaux & Lavisha Pelaez & Osatohamwen Okundaye & Leslie Staln, 2020. "Black–White Risk Differentials in COVID-19 (SARS-COV2) Transmission, Mortality and Case Fatality in the United States: Translational Epidemiologic Perspective and Challenges," IJERPH, MDPI, vol. 17(12), pages 1-18, June.
    5. Ivan J. Ramírez & Jieun Lee, 2020. "COVID-19 Emergence and Social and Health Determinants in Colorado: A Rapid Spatial Analysis," IJERPH, MDPI, vol. 17(11), pages 1-15, May.

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