Sophia E Day1, Kinjia Hinterland2, Christa Myers3, Leena Gupta4, Tiffany G Harris5, Kevin J Konty6. 1. Bureau of Epidemiology Services, New York City Department of Health and Mental Hygiene, 42-09 28th St., Long Island City, NY 11101. sday@health.nyc.gov. 2. Bureau of Epidemiology Services, New York City Department of Health and Mental Hygiene, 42-09 28th St., Long Island City, NY 11101. khinterl@health.nyc.gov. 3. Center for Health Equity, New York City Department of Health and Mental Hygiene, 42-09 28th St., Long Island City, NY 11101. cmyers@health.nyc.gov. 4. Bureau of Epidemiology Services, New York City Department of Health and Mental Hygiene, 42-09 28th St., Long Island City, NY 11101. lsgupta@gmail.com. 5. Bureau of Epidemiology Services, New York City Department of Health and Mental Hygiene, 42-09 28th St., Long Island City, NY 11101. th2604@columbia.edu. 6. Division of Epidemiology, New York City Department of Health and Mental Hygiene, 42-09 28th St., Long Island City, NY 11101. kkonty@health.nyc.gov.
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.
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.
Authors: Avinash Chandran; Aliza K Nedimyer; Zachary Y Kerr; Cathleen O'Neal; James Mensch; Susan W Yeargin Journal: J Athl Train Date: 2020-10-01 Impact factor: 2.860
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