Application of the Distributed Lag Models for Examining Associations Between the Built Environment and Obesity Risk in Children (QUALITY cohort)

Features of the neighbourhood environment are associated with physical activity and nutrition habits in children and may be a key determinant for obesity risk. Studies commonly use a fixed, pre-specified buffer size for the spatial scale to construct environment measures and apply traditional methods of linear regression to calculate risk estimates. However, incorrect spatial scales can introduce biases. Whether the spatial scale changes depending on a person’s age and sex is largely unknown. Distributed lag models (DLM) were recently proposed as an alternative methodology to fixed, pre-specified buffers. The DLM coefficients follow a smooth association over distance, and a pre-specification of buffer size is not required. Therefore, the DLMs may provide a more accurate estimation of association strength, as well as the point in which the association disappears or is no longer clinically meaningful. Using a subsample of the QUALITY cohort (an ongoing longitudinal investigation of the natural history of obesity in Quebec youth, N=281, Mean(age)=9.6 at baseline), we aimed to apply the DLM to determine whether the association between the residential neighbourhood built environment (BE) and obesity risk in children differed depending on age and sex. A second objective aimed to compare the DLM model with that of a linear regression model (which used pre-specified circular buffer sizes). Different distances of association between the Retail Food Environment and BMI z-score were obtained for 1st and 2nd follow-ups, which also varies by sex. No significant association between the Recreational Facilities Environment and MVPA were detected.