Literaturnachweis - Detailanzeige
Autor/inn/en | Day, Sophia E.; Hinterland, Kinjia; Myers, Christa; Gupta, Leena; Harris, Tiffany G.; Konty, Kevin J. |
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Titel | A School-Level Proxy Measure for Individual-level Poverty Using School-Level Eligibility for Free and Reduced-Price Meals |
Quelle | In: Journal of School Health, 86 (2016) 3, S.204-214 (11 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0022-4391 |
DOI | 10.1111/josh.12371 |
Schlagwörter | Poverty; Eligibility; Lunch Programs; Race; Ethnicity; Socioeconomic Status; Health; Risk; Health Behavior; Evaluation Methods; Comparative Analysis; Institutional Characteristics; Family Income; Neighborhoods; Correlation; High School Students; National Surveys; New York; Youth Risk Behavior Survey Armut; Eignung; Mittagessen; Rasse; Abstammung; Ethnizität; Socio-economic status; Sozioökonomischer Status; Gesundheit; Risiko; Health behaviour; Gesundheitsverhalten; Familieneinkommen; Neighbourhoods; Nachbarschaft; Korrelation; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin |
Abstract | Background: Socioeconomic status (SES) impacts health outcomes. The Youth Risk Behavior Survey (YRBS), like many school-based data sources, lacks individual-level poverty information. We propose using school-level percentages of student eligibility for free/reduced-price meals (%FRPM) as a proxy for individual-level poverty. Methods: Using the New York City (NYC) 2009 YRBS, we created school-level poverty quartiles to append to individual YRBS records by ranking schools by %FRPM. We compared this with 2 other school-level poverty measures using students' home and school neighborhood-level poverty and measured the association of these 3 school-level proxies with individual's household income. Last, we evaluated health outcomes by race/ethnicity and poverty to demonstrate the importance of accounting for poverty. Results: The school-level measure that used %FRPM had the strongest association with household income. When the school-level individual poverty proxy was included in illustrative analyses using YRBS data, patterns by poverty within race/ethnicity emerged that were not seen when looking at race/ethnicity alone. Conclusions: Using a poverty measure to analyze school-based data will provide a better understanding of the impact of SES on health outcomes. Based on our evaluation, when individual-level information is not available, we propose using school-level %FRPM, which are publicly available throughout the United States. (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2020/1/01 |