Associations between farmers' market shopping behaviours and objectively measured and self-reported fruit and vegetable intake in a diverse sample of farmers' market shoppers: a cross-sectional study in New York City and rural North Carolina.
Academic Article
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
OBJECTIVE: To examine cross-sectional associations between farmers' market shopping behaviours and objectively measured and self-reported fruit and vegetable (FV) intake among rural North Carolina (NC) and New York City (NYC) shoppers. DESIGN: Cross-sectional intercept surveys were used to assess self-reported FV intake and three measures of farmers' market shopping behaviour: (1) frequency of purchasing FV; (2) variety of FV purchased and (3) dollars spent on FV. Skin carotenoids, a non-invasive biomarker for FV intake, were objectively measured using pressure-mediated reflection spectroscopy. Associations between farmers' market shopping behaviours and FV intake were examined using regression models that controlled for demographic variables (e.g. age, sex, race, smoking status, education, income and state). SETTING: Farmers' markets (n 17 markets) in rural NC and NYC. PARTICIPANTS: A convenience sample of 645 farmers' market shoppers. RESULTS: Farmers' market shoppers in NYC purchased a greater variety of FV and had higher skin carotenoid scores compared with shoppers in rural NC. Among all shoppers, there was a positive, statistically significant association between self-reported frequency of shopping at farmers' markets and self-reported as well as objectively assessed FV intake. The variety of FV purchased and farmers' market spending on FV also were positively associated with self-reported FV intake, but not skin carotenoids. CONCLUSION: Those who shop for FV more frequently at a farmers' markets, purchase a greater variety of FV and spend more money on FV have higher self-reported, and in some cases higher objectively measured FV intake. Further research is needed to understand these associations and test causality.
