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Inequities in food access during the COVID19 pandemic: a multilevel, mixed methods pilot study.
Aepala, Megha R; Guan, Alice; Cruz, Tessa; Sowell, Jamaica; Mattias, Brenda; Lin, Katherine; Hassberg, Analena Hope; Shariff-Marco, Salma; DeRouen, Mindy C; Akom, Antwi.
Afiliación
  • Aepala MR; Department of Epidemiology and Biostatistics | University of California, San Francisco.
  • Guan A; Department of Epidemiology and Biostatistics | University of California, San Francisco.
  • Cruz T; The Social Innovation and Urban Opportunity Lab, Streetwyze | UCSF & San Francisco State University | Oakland, CA.
  • Sowell J; Roots Community Health Center | Oakland, CA.
  • Mattias B; The Social Innovation and Urban Opportunity Lab, Streetwyze | UCSF & San Francisco State University | Oakland, CA.
  • Lin K; Department of Epidemiology and Biostatistics | University of California, San Francisco.
  • Hassberg AH; Department of Sociology | California State University, Los Angeles.
  • Shariff-Marco S; Department of Epidemiology and Biostatistics | University of California, San Francisco.
  • DeRouen MC; Department of Epidemiology and Biostatistics | University of California, San Francisco.
  • Akom A; The Social Innovation and Urban Opportunity Lab, Streetwyze | UCSF & San Francisco State University | Oakland, CA.
Res Sq ; 2024 Aug 09.
Article en En | MEDLINE | ID: mdl-39149448
ABSTRACT

Background:

Innovative data integration may serve to inform rapid, local responses to community needs. We conducted a mixed methods pilot study among communities of color or low-income in the San Francisco Bay Area amid the COVID-19 pandemic to assess a hypothesized data model to inform rapid response efforts.

Methods:

Between 2020-2021, we collected (1) qualitative data through neighborhood reports submitted via Streetwyze, a mobile neighborhood mapping platform; (2) survey data on social and economic circumstances; and (3) geospatial data among residents of three counties. Qualitative data were coded and then integrated with survey and geospatial data. We used descriptive analyses to examine participants' experiences with food in their neighborhoods.

Results:

Seventy percent of participants reported food insecurity before and after the pandemic began in March 2020. Within neighborhood reports, food was the most frequently occurring sub-theme within the Goods and Resources parent themes (68% and 49% of reports, respectively). Security (88%), resource programs (88%), outdoor space (84%), and equity (83%) were more likely to be mentioned by participants who were food insecure compared to those who were not (12%, 12%, 16%, 17%, respectively). Mentions of food in neighborhood reports more often occurred in census tracts with lower socioeconomic status and more area-level food insecurity.

Conclusion:

Individuals who were food insecure reported a constellation of needs beyond food, including needs related to safety and greater social equity. Our data model illustrates the potential for rapid assessment of community residents' experiences to provide enhanced understanding of community-level needs and effective support in the face of changing circumstances.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Res Sq Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Res Sq Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos