Using Address Information to Identify Hardships Reported by Families of Children Hospitalized With Asthma
| Autor: | Robert S. Kahn, Andrew F. Beck, Jeffrey M. Simmons, Anita N. Shah, Kristen Timmons, Bin Huang, Katherine A. Auger |
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| Rok vydání: | 2017 |
| Předmět: |
Male
Gerontology Adolescent Geographic Mapping Health Services Accessibility White People Article Cohort Studies 03 medical and health sciences 0302 clinical medicine Residence Characteristics 030225 pediatrics Environmental health medicine Humans 030212 general & internal medicine Social determinants of health Child Poverty Socioeconomic status Asthma Family Characteristics Insurance Health Primary Health Care business.industry Hispanic or Latino Census medicine.disease United States Black or African American Hospitalization Cross-Sectional Studies Social Class Socioeconomic Factors Child Preschool Pediatrics Perinatology and Child Health Geocoding Cohort Income Household income Female business human activities |
| Zdroj: | Academic Pediatrics. 17:79-87 |
| ISSN: | 1876-2859 |
| DOI: | 10.1016/j.acap.2016.07.003 |
| Popis: | Socioeconomic hardship is common among children hospitalized for asthma but often not practically measurable. Information on where a child resides is universally available. We sought to determine the correlation between neighborhood-level socioeconomic data and family-reported hardships.Caregivers of 774 children hospitalized with asthma answered questions regarding income, financial strain, and primary care access. Addresses were geocoded and linked to zip code-, census tract-, and block group-level (neighborhood) data from the US Census. We then compared neighborhood median household income with family-reported household income; percentage of neighborhood residents living in poverty with family-reported financial strain; and percentage of neighborhood households without an available vehicle with family-reported access to primary care. We constructed heat maps and quantified correlations using Kendall rank correlation coefficient. Receiver operator characteristic curves were used to assess predictive abilities of neighborhood measures.The cohort was 57% African American and 73% publicly-insured; 63% reported income$30,000, 32% endorsed ≥4 financial strain measures, and 38% reported less than adequate primary care access. Neighborhood median household income was significantly and moderately correlated with and predictive of reported household income; neighborhood poverty was similarly related to financial strain; neighborhood vehicle availability was weakly correlated with and predictive of primary care access. Correlations and predictions provided by zip code measures were similar to those of census tract and block group.Universally available neighborhood information might help efficiently identify children and families with socioeconomic hardships. Systematic screening with area-level socioeconomic measures has the potential to inform resource allocation more efficiently. |
| Databáze: | OpenAIRE |
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