Association between Activity Space Exposure to Food Establishments and Individual Risk of Overweight

Abstract

ObjectiveEnvironmental exposure to food sources may underpin area level differences in individual risk for overweight. Place of residence is generally used to assess neighbourhood exposure. Yet, because people are mobile, multiple exposures should be accounted for to assess the relation between food environments and overweight. Unfortunately, mobility data is often missing from health surveys. We hereby test the feasibility of linking travel survey data with food listings to derive food store exposure predictors of overweight among health survey participants.MethodsFood environment exposure measures accounting for non-residential activity places (activity spaces) were computed and modelled in Montreal and Quebec City, Canada, using travel surveys and food store listings. Models were then used to predict activity space food exposures for 5,578 participants of the Canadian Community Health Survey. These food exposure estimates, accounting for daily mobility, were used to model self-reported overweight in a multilevel framework. Median Odd Ratios were used to assess the proportion of between-neighborhood variance explained by such food exposure predictors.ResultsEstimates of food environment exposure accounting for both residential and non-residential destinations were significantly and more strongly associated with overweight than residential-only measures of exposure for men. For women, residential exposures were more strongly associated with overweight than non-residential exposures. In Montreal, adjusted models showed men in the highest quartile of exposure to food stores were at lesser risk of being overweight considering exposure to restaurants (OR = 0.36 [0.21–0.62]), fast food outlets (0.48 [0.30–0.79]), or corner stores (0.52 [0.35–0.78]). Conversely, men experiencing the highest proportion of restaurants being fast-food outlets were at higher risk of being overweight (2.07 [1.25–3.42]). Women experiencing higher residential exposures were at lower risk of overweight.ConclusionUsing residential neighbourhood food exposure measures may underestimate true exposure and observed associations. Using mobility data offers potential for deriving activity space exposure estimates in epidemiological models.

Chemical and non-chemical stressors affecting childhood obesity: a systematic scoping review

“…Generally, the obesity epidemic is thought to be a result of chronic energy imbalance between calories consumed and calories expended. [17][18][19][20][21][22][23] In addition to physical activity and caloric intake, other non-chemical stressors that may influence weight include personal habits (e.g., smoking); psychosocial stress (e.g., parental divorce, domestic violence, exercising poor judgement, depression); access to health care; and/or aspects of the built and natural environments. [24][25][26][27] There is also increasing evidence that obesogens (i.e., chemical stressors) may influence obesity by affecting metabolic activities in the body.…”

Relative and absolute availability of fast-food restaurants in relation to the development of diabetes: A population-based cohort study

“…10 Other studies using smaller geographic levels (e.g., the number of FFR within walking distance of residential areas) found no association or results in the opposite direction. [11][12][13] Measures of FFR exposure also vary widely across studies (e.g., absolute numbers or density of outlets, proximity to outlets), and most studies on the topic are cross-sectional, which limits any conclusions about causality. 9 Moreover, there is a dearth of data exploring direct links between the retail food environment and the development of other dietrelated outcomes, like diabetes.…”

“…A growing number of recent reports indicate that relative measures, such as the ratio or proportion of various types of food retail outlets, may be more useful than absolute measures for understanding associations with dietary behaviours and related health outcomes, because they better reflect the balance of available resources. 11,12,14 A recent study from Ontario found a strong relationship between the concentration of fast-food relative to other types of restaurants and obesity in areas with high volumes of fast-food retailers. 11 In light of these findings, the primary aim of this study was to assess whether this exposure accelerates the risk of diabetes.…”

Considering daily mobility for a more comprehensive understanding of contextual effects on social inequalities in health: A conceptual proposal

“…Since few studies have yet empirically examined the relationship between inequalities in daily mobility and social inequalities in health, further empirical work is needed to do so and to refine the conceptual proposal. Empirical tests of the proposal will profit from the increasing use and development of novel tools and technologies which allow for the collection of detailed information on people's movement across space and activity places (Shareck et al, 2013, Kerr et al, 2011, Vallee et al, 2011, Chaix et al, 2012, Rainham et al, 2008, as well as methods to process spatialized data (Thierry et al, 2013), operationalize daily mobility and activity spaces (Rainham et al, 2010, Matthews andYang, 2013), and analyze their association with health (Matthews and Yang, 2013). …”

“…Furthermore, the integration of mobility in place and health research has benefited from an increasing reliance on novel technologies, such as global positioning systems (Rainham et al, 2008) and interactive mapping tools (Chaix et al, 2012), to track people across space. However, it has not been accompanied by substantial developments on the conceptual front.…”