Most residents in New York City (NYC) do not consume sufficient fruits and vegetables every day. Difficulties with access and high prices of fruits and vegetables in some neighborhoods contribute to different consumption patterns across NYC neighborhoods. We developed an agent-based model (ABM) to predict dietary behaviors of individuals at the borough and neighborhood levels. Model parameters were estimated from the 2014 NYC Community Health Survey, United States Census data, and the literature. We simulated six hypothetical interventions designed to improve access and reduce the price of fruits and vegetables. We found that all interventions would lead to increases in fruit and vegetable consumption but the results vary substantially across boroughs and neighborhoods. For example, a 10% increase in the number of fruit/vegetable vendors combined with a 10% decrease in the prices of fruits and vegetables would lead to a median increase of 2.28% (range: 0.65%-4.92%) in the consumption of fruits and vegetables, depending on neighborhood. We also found that the impact of increasing the number of vendors on fruit/vegetable consumption is more pronounced in unhealthier local food environments while the impact of reducing prices on fruits/vegetable consumption is more pronounced in neighborhoods with low levels of education. An agent-based model of dietary behaviors that takes into account neighborhood context has the potential to inform how fruit/vegetable access and pricing strategies may specifically work in tandem to increase the consumption of fruits and vegetables at the local level.
Keywords: Agent-based modeling; Food policy; Nutrition; Systems science; Urban health.
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