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Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study
BACKGROUND: Over the past decade, the prevalence of food insecurity declined in the United States but curiously climbed in Philadelphia, Pennsylvania, a sizable metropolitan area where many households experience food insecurity and are dependent on programs like SNAP. Therefore, we aimed to determin...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10334625/ https://www.ncbi.nlm.nih.gov/pubmed/37430317 http://dx.doi.org/10.1186/s12889-023-16208-3 |
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author | Inguito, Kai Joa, Brandon Gardner, James Fung, Eric N. Layer, Laura Fritz, Karen |
author_facet | Inguito, Kai Joa, Brandon Gardner, James Fung, Eric N. Layer, Laura Fritz, Karen |
author_sort | Inguito, Kai |
collection | PubMed |
description | BACKGROUND: Over the past decade, the prevalence of food insecurity declined in the United States but curiously climbed in Philadelphia, Pennsylvania, a sizable metropolitan area where many households experience food insecurity and are dependent on programs like SNAP. Therefore, we aimed to determine the burden of food insecurity among populations near Philadelphia Federally Qualified Health Center (FQHC) clinic sites. METHODS: This cross-sectional study was conducted in North Philadelphia, a populous and impoverished section of Philadelphia with many zip codes reporting 30–45% or more of the population below the federal poverty line. Students and clinicians affiliated with a local FQHC conducted surveys on residents (n = 379) within 1-mile radiuses of three FQHC sites, using the Hunger Vital Sign™, a validated food security tool. Survey data were collected through door-to-door visits in the summer of 2019. We used simple, age-adjusted bivariable, and multivariable logistic regression models to predict food insecurity with independent variables, including age, sex, language preference, and BMI category. RESULTS: Food insecurity in North Philadelphia was much higher (36.9%) than previously reported in Philadelphia and nationwide. Food insecurity was inversely associated with age (AOR = 0.98, 95% CI: 0.97, 1.00), overweight (AOR = 0.58, 95% CI: 0.32, 1.06), and obesity (AOR = 0.60, 95% CI: 0.33, 1.09). CONCLUSION: In North Philadelphia, the burden of food insecurity is higher than in the greater Philadelphia area, Pennsylvania state, and the rest of the nation and is predicted by age and BMI of residents. These findings demonstrate a need for more locally targeted research and interventions on food insecurity in impoverished urban settings. |
format | Online Article Text |
id | pubmed-10334625 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103346252023-07-12 Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study Inguito, Kai Joa, Brandon Gardner, James Fung, Eric N. Layer, Laura Fritz, Karen BMC Public Health Research Article BACKGROUND: Over the past decade, the prevalence of food insecurity declined in the United States but curiously climbed in Philadelphia, Pennsylvania, a sizable metropolitan area where many households experience food insecurity and are dependent on programs like SNAP. Therefore, we aimed to determine the burden of food insecurity among populations near Philadelphia Federally Qualified Health Center (FQHC) clinic sites. METHODS: This cross-sectional study was conducted in North Philadelphia, a populous and impoverished section of Philadelphia with many zip codes reporting 30–45% or more of the population below the federal poverty line. Students and clinicians affiliated with a local FQHC conducted surveys on residents (n = 379) within 1-mile radiuses of three FQHC sites, using the Hunger Vital Sign™, a validated food security tool. Survey data were collected through door-to-door visits in the summer of 2019. We used simple, age-adjusted bivariable, and multivariable logistic regression models to predict food insecurity with independent variables, including age, sex, language preference, and BMI category. RESULTS: Food insecurity in North Philadelphia was much higher (36.9%) than previously reported in Philadelphia and nationwide. Food insecurity was inversely associated with age (AOR = 0.98, 95% CI: 0.97, 1.00), overweight (AOR = 0.58, 95% CI: 0.32, 1.06), and obesity (AOR = 0.60, 95% CI: 0.33, 1.09). CONCLUSION: In North Philadelphia, the burden of food insecurity is higher than in the greater Philadelphia area, Pennsylvania state, and the rest of the nation and is predicted by age and BMI of residents. These findings demonstrate a need for more locally targeted research and interventions on food insecurity in impoverished urban settings. BioMed Central 2023-07-10 /pmc/articles/PMC10334625/ /pubmed/37430317 http://dx.doi.org/10.1186/s12889-023-16208-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Inguito, Kai Joa, Brandon Gardner, James Fung, Eric N. Layer, Laura Fritz, Karen Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study |
title | Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study |
title_full | Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study |
title_fullStr | Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study |
title_full_unstemmed | Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study |
title_short | Differentials and predictors of food insecurity among Federally Qualified Health Center target populations in Philadelphia: a cross-sectional study |
title_sort | differentials and predictors of food insecurity among federally qualified health center target populations in philadelphia: a cross-sectional study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10334625/ https://www.ncbi.nlm.nih.gov/pubmed/37430317 http://dx.doi.org/10.1186/s12889-023-16208-3 |
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