Place of residence in Dortmund is associated with dietary intake and BMI-SDS in children and adolescents: Findings from the DONALD cohort study

Abstract

Objective:

To determine whether location of residence in a German urban food environment shows associations with habitual dietary intake or anthropometrics in children and adolescents (6-18 years).

Methods:

Using data from the DONALD cohort study, we grouped participants according to their residence in north vs. south of Dortmund, Germany. We applied robust multi-level mixed effects regression models using residence as predictor and (1) anthropometric data (body mass index standard deviation score (BMI-SDS)) or (2) dietary data (daily intake of energy (kcal), macronutrients (in percentage of total daily energy intake) or food groups [g/1000kcal]) as outcome. Analyses were carried out on 1,235 geocoded 3-day weighed dietary records, collected from 360 participants (292 for dietary intake) in the longitudinal DONALD study between 2014 and 2019. Models were adjusted for age, sex, and socio-economic status (SES).

Results:

We find that 52 (14.4%) participants reside in the north and 308 (85.6 %) in the south of Dortmund. In the fully adjusted models, residence in the south was associated with lower BMI-SDS (β =-0.42, p =0.02), lower intake of sugar-sweetened beverages (β = -48.24, p = 0.04) and higher intake of vegetables (β = 11.69, p = 0.03). Differences remain even when controlling for individual SES. No significant association was found for macronutrients or other food groups (meat and fish, fruits, dairy, grains, sweets).

Conclusion:

Our results suggest that place of residence may play a crucial role in determining health in the urban context, specifically by explaining variation in dietary intake. This driver is observable even when controlling for the SES of the individual’s household. This indicates that dietary intake may in part be impacted by factors outside individual-level indicators. Further research is required to identify the precise pathway(s) of location of residence on nutrition and quantify the food environment in different city areas past socio-economic background variables.