Demographic, spatial, and temporal dietary intake patterns among 526,774 23andMe research participants

Objective To characterize dietary habits, their temporal and spatial patterns, and associations with body mass index (BMI) in the 23andMe study population. Design We present a large-scale cross-sectional analysis of self-reported dietary intake data derived from the web-based NHANES 2009-2010 dietary screener. Survey-weighted estimates for each food item were characterized by age, sex, race/ethnicity, education, and BMI. Temporal patterns were plotted over a 2-year time period, and average consumption for select food items was mapped by state. Finally, dietary intake variables were tested for association with BMI. Setting U.S. based adults 20-85 years of age participating in the 23andMe research program. Participants Participants were 23andMe customers who consented to participate in research (n=526,774) and completed web-based surveys on demographic and dietary habits. Results Survey-weighted estimates show very few participants met federal recommendations for fruit: 2.6%, vegetables: 5.9%, and dairy intake: 2.8%. Between 2017-2019, fruit, vegetables, and milk intake frequency declined, while total dairy remained stable and added sugars increased. Seasonal patterns in reporting were most pronounced for ice cream, chocolate, fruits, and vegetables. Dietary habits varied across the U.S., with higher intake of sugar and calorie dense foods characterizing areas with higher average BMI. In multivariate-adjusted models, BMI was directly associated with intake of processed meat, red meat, dairy, and inversely associated with consumption of fruit, vegetables, and whole grains. Conclusions 23andMe research participants have created an opportunity for rapid, large scale, real time nutritional data collection, informing demographic, seasonal and spatial patterns with broad geographical coverage across the U.S.