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BMC Public Health ; 18(1): 173, 2018 01 24.
Artigo em Inglês | MEDLINE | ID: mdl-29361922

RESUMO

BACKGROUND: In January 2015, Berkeley, California became the first city in the Unites States to impose a tax on sugar-sweetened beverages. The tax is intended to discourage purchase of sugary beverages and promote consumption of healthier alternatives such as tap water. The goal of the study was to assess the condition of public drinking water fountains and determine if there is a difference in access to clean, functioning fountains based on race or socio-economic status. METHODS: A mobile-GIS App was created to locate and collect data on existing drinking water fountains in Berkeley, CA. Demographic variables related to race and socio-economic status (SES) were acquired from the US Census - American Community Survey database. Disparities in access to, or condition of drinking water fountains relative to demographics was explored using spatial analyses. Spatial statistical-analysis was performed to estimate demographic characteristics of communities near the water fountains and logistic regression was used to examine the relationship between household median income or race and condition of fountain. RESULTS: Although most fountains were classified as functioning, some were dirty, clogged, or both dirty and clogged. No spatial relationships between demographic characteristics and fountain conditions were observed. DISCUSSION: All geo-located data and a series of maps were provided to the City of Berkeley and the public. CONCLUSIONS: The geo-database created as an outcome of this study is useful for prioritizing maintenance of existing fountains and planning the locations of future fountains. The methodologies used for this study could be applied to a wide variety of asset inventory and assessment projects such as clinics or pharmaceutical dispensaries, both in developed and developing countries.


Assuntos
Água Potável , Abastecimento de Água/estatística & dados numéricos , Bebidas/economia , California , Sistemas de Informação Geográfica , Humanos , Modelos Logísticos , Grupos Raciais/estatística & dados numéricos , Classe Social , Análise Espacial , Inquéritos e Questionários , Edulcorantes , Impostos , Abastecimento de Água/normas
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