Examining associations between regional food-related implicit biases and regional obesogenic and environmental risk factors

Authors

• MB Siroty
• JL Howell
• JMP Bittner
• BK Cheon

Abstract

Implicit biases are automatic associations that are partially shaped by the environment and may influence judgments and behaviors. When measured in aggregate (e.g., regionally), they may reflect systemic biases like structural racism. Therefore, obesogenic qualities of environments may be reflected in aggregated implicit biases towards unhealthy food, which in turn may drive higher obesity rates. Although previous research has shown individual-level implicit biases favoring the taste and acceptability of healthy/low-fat (vs. unhealthy/high-fat) food and relationships between adverse food environments and socioeconomic conditions, these factors have never been studied as predictors of food biases. We will examine county-wide aggregates of implicit and explicit (self-reported) food-related biases and their relationships with county obesity rates, regional food environments (fast-food restaurant density), and socioeconomic conditions (median household income) that may promote obesity. Implicit bias will be measured via an Implicit Association Test, a computerized task that compares reaction times of different combinations of concepts (i.e., healthy food vs. unhealthy food) and attributes (i.e. good-tasting vs. bad-tasting). Responses from two United States-based online surveys measuring these food-related biases (palatability/unpalatability of healthy vs. unhealthy food, n ≈ 11,504; acceptability/shame of low- vs. high-fat food, n ≈ 12,129) will be aggregated and analyzed by county of residence. We hypothesize that lower median household income and higher density of fast-food restaurants will predict stronger county-wide health-disfavoring food biases (unhealthy/high-fat foods as palatable and acceptable), and these biases will predict higher obesity rates. This work aims to promote food-related biases when considering diet-related conditions in the US.

Scientific Focus Area: Social and Behavioral Sciences

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