Unhealthy food options in the school environment are associated with diet quality and body weights of elementary school children in Canada

Abstract

Objective: Increasing evidence links unhealthy food environments with diet quality and overweight/obesity. Recent evidence has demonstrated that relative food environment measures outperform absolute measures. Few studies have examined the interplay between the two measures. We examined the separate and combined effects of the absolute and relative densities of unhealthy food outlets within 1600 metre buffers around elementary schools on children’s diet- and weight-related outcomes. Design: This is a cross-sectional study of 812 children, from 39 schools. The Youth Healthy Eating Index (Y-HEI) and daily vegetables and fruit servings were derived from the Harvard Food Frequency Questionnaire (FFQ) for Children and Youth. Measured heights and weights determined body mass index (BMI) z-scores. Food outlets were ranked as healthy, somewhat healthy, and unhealthy according to provincial pediatric nutrition guidelines. Multilevel mixed-effects regression models were used to assess the effect of absolute (number) and relative (proportion) densities of unhealthy food outlets within 1600 metres around schools on diet quality and weight status. Setting: Two urban centres in the province of Alberta, Canada. Participants: Grade 5 students (10-11 years). Results: For children attending schools with a higher absolute number (36+) of unhealthy food outlets within 1600 metres, every 10% increase in the proportion of unhealthy food outlets was associated with 4.1 lower Y-HEI score and 0.9 fewer daily vegetables and fruit. Conclusions: Children exposed to a higher relative density of unhealthy food outlets around a school had lower diet quality, specifically in areas where the absolute density of unhealthy food outlets was also high.

Seeing the food swamp for the weeds: Moving beyond food retail mix in evaluating young people's food environments

“…Refinement of NutriGARR could involve assessing the nutrient profile of individual menu items for calculating a weighted index, potentially made easier through online menu databases like Menu Stat ( Menu Stat, 2021 )—although such resource-intensive information might initially need to come about via voluntary certification of food retailers through self-assessment for meeting nutrition guidelines. Nonetheless, the NutriGARR classification has been effectively used in other research to identify a relationship between the presence and proportion of CLO food retailers surrounding schools and reduced daily fruit and vegetable intake in grade 5 students ( Sim et al, 2020 ).…”

What counts? Adding nuance to retail food environment measurement tools in a Canadian context

“…Our retailer sub-categories could be used in at least three additional ways by research, practice, and/or policy teams: 1) applying our coding beyond Alberta, since many of the retailer categories in our codebook exist elsewhere in North America; 2) extending the mRFEI by inductively developing unique sub-categories based on local data and/or excluded categories outlined in Table 1 (with transparent reporting of codebook details); and 3) developing new geospatial indicators based on indicated and other sub-categories. For example, Alberta's Nutrition Guidelines' (46) healthfulness labels for foods and beverages (choose most often, choose sometimes, choose least often) could be applied to retailer sub-categories to assess implementation of jurisdiction-specific nutrition policies, as has been done by team collaborators (11,31,47) . Using such guidelines could be one step towards moving past binary https://doi.org/10.1017/S1368980023000733 Published online by Cambridge University Press Accepted manuscript categorizations of retailers as healthy/less healthy.…”