Abstract
To characterise dietary habits, their temporal and spatial patterns and associations with BMI in the 23andMe study population. We present a large-scale cross-sectional analysis of self-reported dietary intake data derived from the web-based National Health and Nutrition Examination Survey 2009-2010 dietary screener. Survey-weighted estimates for each food item were characterised 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. US-based adults 20-85 years of age participating in the 23andMe research programme. Participants were 23andMe customers who consented to participate in research (n 526 774) and completed web-based surveys on demographic and dietary habits. Survey-weighted estimates show very few participants met federal recommendations for fruit: 2·6 %, vegetables: 5·9 % and dairy intake: 2·8 %. Between 2017 and 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 USA, with higher intake of sugar and energy dense foods characterising areas with higher average BMI. In multivariate-adjusted models, BMI was directly associated with the intake of processed meat, red meat, dairy and inversely associated with consumption of fruit, vegetables and whole grains. 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 USA.
Highlights
Poor dietary habits and inadequate physical activity are major drivers of elevated body mass index (BMI), which in turn increases the risk of developing adverse cardio-metabolic outcomes.[5]. Diet and physical activity represent the most actionable areas at both the individual and population levels to prevent chronic disease.[6]. While the majority of dietary recommendations are geared towards average effects with measurable benefits to population health, the science of precision nutrition has been uncovering informative subgroup variation
Here, we detail demographic, temporal, and spatial characteristics of dietary factors measured by the DSQ and how they relate to BMI among 23andMe research participants
Because 23andMe research participants are twice as likely to have a college education, more likely to be female, white, and older than the general US population, dietary habits differential across these characteristics were most changed by weighting the sample to better represent the broader free living US population of adults
Summary
Poor dietary habits and inadequate physical activity are major drivers of elevated body mass index (BMI), which in turn increases the risk of developing adverse cardio-metabolic outcomes.[5] Diet and physical activity represent the most actionable areas at both the individual and population levels to prevent chronic disease.[6] While the majority of dietary recommendations are geared towards average effects with measurable benefits to population health, the science of precision nutrition has been uncovering informative subgroup variation Among those who consume 22g/day or more of saturated fat, weight gain was more pronounced among those with the -265 C/C genotype of APOA2, an estimated 10-20% of the population, compared to those without it.[7] longer term health consequences, such as varying cardio-metabolic disease risk across combinations of exposures, are not well understood. Due to the growing size of the customer database, widespread geographical representation, and continuous data collection over time, data provided by 23andMe research participants represent a large enough sample to inform population-based inferences for a variety of health behaviors, including diet
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