Large-scale diet tracking data reveal disparate associations between food environment and diet.
Tim AlthoffHamed NilforoshanJenna HuaJure LeskovecPublished in: Nature communications (2022)
An unhealthy diet is a major risk factor for chronic diseases including cardiovascular disease, type 2 diabetes, and cancer 1-4 . Limited access to healthy food options may contribute to unhealthy diets 5,6 . Studying diets is challenging, typically restricted to small sample sizes, single locations, and non-uniform design across studies, and has led to mixed results on the impact of the food environment 7-23 . Here we leverage smartphones to track diet health, operationalized through the self-reported consumption of fresh fruits and vegetables, fast food and soda, as well as body-mass index status in a country-wide observational study of 1,164,926 U.S. participants (MyFitnessPal app users) and 2.3 billion food entries to study the independent contributions of fast food and grocery store access, income and education to diet health outcomes. This study constitutes the largest nationwide study examining the relationship between the food environment and diet to date. We find that higher access to grocery stores, lower access to fast food, higher income and college education are independently associated with higher consumption of fresh fruits and vegetables, lower consumption of fast food and soda, and lower likelihood of being affected by overweight and obesity. However, these associations vary significantly across zip codes with predominantly Black, Hispanic or white populations. For instance, high grocery store access has a significantly larger association with higher fruit and vegetable consumption in zip codes with predominantly Hispanic populations (7.4% difference) and Black populations (10.2% difference) in contrast to zip codes with predominantly white populations (1.7% difference). Policy targeted at improving food access, income and education may increase healthy eating, but intervention allocation may need to be optimized for specific subpopulations and locations.
Keyphrases
- physical activity
- human health
- weight loss
- type diabetes
- healthcare
- cardiovascular disease
- body mass index
- mental health
- public health
- randomized controlled trial
- risk assessment
- magnetic resonance imaging
- adipose tissue
- machine learning
- insulin resistance
- quality improvement
- young adults
- coronary artery disease
- cardiovascular events
- cancer therapy
- deep learning