Datasets underlying the analysis of the paper: "Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study" This upload includes the following: data_study.csv : contains socio-demographic, health- and lifestyle factors, and body scan variables of each participant healthscore.csv : contains the "healthy score" from the food frequency questions calculated from from five food categories: fruits, vegetables, wholegrain products, meat, and sweet/salty snacks. For each category the officially recommended minimum or maximum amount of weekly intake was used as the cut-off value and a point was assigned if the recommendation was met. A score from 0 to 5 was built to reflect the overall healthiness of the diet.

{"references": ["Sob C, Siegrist M, Hagmann D, Hartmann C. (2021) A longitudinal study examining the influence of diet-related compensatory behavior on healthy weight management. Appetite.;156, doi.org/10.1016/j.appet.2020.104975", "Hagmann, D., Siegrist, M., & Hartmann, C. (2019). Meat avoidance: Motives, alternative proteins and diet quality in a sample of Swiss consumers. Public Health Nutrition, 22(13), 2448-2459. doi:10.1017/S1368980019001277", "Ekingen, T., Sob, C., Hartmann, C., R\u00fchli FJ, Matthes KL, Staub K, Bender N (2022) Associations between hydration status, body composition, sociodemographic and lifestyle factors in the general population: a cross-sectional study. BMC Public Health 22, 900 (2022). https://doi.org/10.1186/s12889-022-13280-z"]}

Funding: Mäxi Foundation Zurich We thank Cynthia Sob, Christina Hartmann, Luana Giacone and Gian Limacher for their support with data collection