Objectives To examine the association between environmental exposure to takeaway food outlets, takeaway food consumption, and body weight, while accounting for home, work place, and commuting route environments. Design Population based, cross sectional study, using data on individual participants’ diet and weight, and objective metrics of food environment exposure. Participants Working adults participating in the Fenland Study, Cambridgeshire, UK (n=5442, aged 29-62 years), who provided home and work addresses and commuting preferences. Takeaway food outlet exposure was derived using data from local authorities for individual environmental domains (at home, at work, and along commuting routes (the shortest route between home and work)), and for exposure in all three domains combined. Exposure was divided into quarters (Q); Q1 being the least exposed and Q4 being the most exposed. Main outcome measures Self reported consumption of takeaway type food (g/day; pizza, burgers, fried foods, and chips) using food frequency questionnaires, measured body mass index, and cut-offs for body mass index as defined by the World Health Organization. Results In multiple linear regression models, exposure to takeaway food outlets was positively associated with consumption of takeaway food. Among domains at home, at work, and along commuting routes, associations were strongest in work environments (Q4 v Q1; β coefficient=5.3 g/day, 95% confidence interval 1.6 to 8.7; P<0.05), with evidence of a dose-response effect. Associations between exposure in all three domains combined and consumption were greater in magnitude across quarters of exposure (Q4 v Q1; 5.7 g/day, 2.6 to 8.8; P<0.001), with evidence of a dose-response effect. Combined exposure was especially strongly associated with increased body mass index (Q4 v Q1; body mass index 1.21, 0.68 to 1.74; P<0.001) and odds of obesity (Q4 v Q1; odds ratio 1.80, 1.28 to 2.53; P<0.05). There was no evidence of effect modification by sex. Conclusions Exposure to takeaway food outlets in home, work, and commuting environments combined was associated with marginally higher consumption of takeaway food, greater body mass index, and greater odds of obesity. Government strategies to promote healthier diets through planning restrictions for takeaway food could be most effective if focused around the workplace.

Socioeconomic disparities in the food environment are known to exist but with little understanding of change over time. This study investigated the density of takeaway food outlets and presence of supermarkets in Norfolk, UK between 1990 and 2008. Data on food retail outlet locations were collected from telephone directories and aggregated within electoral wards. Supermarket presence was not associated with area deprivation over time. Takeaway food outlet density increased overall, and was significantly higher in more deprived areas at all time points; furthermore, socioeconomic disparities in takeaway food outlet density increased across the study period. These findings add to existing evidence and help assess the need for environmental interventions to reduce disparities in the prevalence of unhealthy food outlets.

Online food delivery services like Just Eat and Grubhub facilitate online ordering and home delivery of food prepared away-from-home. It is poorly understood how these services are used and by whom. This study investigated the prevalence of online food delivery service use and sociodemographic characteristics of customers, in and across Australia, Canada, Mexico, the UK, and the USA. We analyzed online survey data (n = 19,378) from the International Food Policy Study, conducted in 2018. We identified respondents who reported any online food delivery service use in the past 7 days and calculated the frequency of use and number of meals ordered. We investigated whether odds of any online food delivery service use in the past 7 days differed by sociodemographic characteristics using adjusted logistic regression. Overall, 15% of respondents (n = 2929) reported online food delivery service use, with the greatest prevalence amongst respondents in Mexico (n = 839 (26%)). Online food delivery services had most frequently been used once and the median number of meals purchased through this mode of order was two. Odds of any online food delivery service use were lower per additional year of age (OR: 0.95; 95% CI: 0.94, 0.95) and greater for respondents who were male (OR: 1.50; 95% CI: 1.35, 1.66), that identified with an ethnic minority (OR: 1.57; 95% CI: 1.38, 1.78), were highly educated (OR: 1.66; 95% CI: 1.46, 1.90), or living with children (OR: 2.71; 95% CI: 2.44, 3.01). Further research is required to explore how online food delivery services may influence diet and health.

Background: Greater exposures to fast-food outlets and lower levels of education are independently associated with less healthy diets and obesity. Lit

Socio-ecological models of behaviour suggest that dietary behaviours are potentially shaped by exposure to the food environment (‘foodscape’). Research on associations between the foodscape and diet and health has largely focussed on foodscapes around the home, despite recognition that non-home environments are likely to be important in a more complete assessment of foodscape exposure. This paper characterises and describes foodscape exposure of different types, at home, at work, and along commuting routes for a sample of working adults in Cambridgeshire, UK. Home and work locations, and transport habits for 2,696 adults aged 29–60 were drawn from the Fenland Study, UK. Food outlet locations were obtained from local councils and classified by type - we focus on convenience stores, restaurants, supermarkets and takeaway food outlets. Density of and proximity to food outlets was characterised at home and work. Commuting routes were modelled based on the shortest street network distance between home and work, with exposure (counts of food outlets) that accounted for travel mode and frequency. We describe these three domains of food environment exposure using descriptive and inferential statistics. For all types of food outlet, we found very different foodscapes around homes and workplaces (with overall outlet exposure at work 125% higher), as well as a potentially substantial exposure contribution from commuting routes. On average, work and commuting environments each contributed to foodscape exposure at least equally to residential neighbourhoods, which only accounted for roughly 30% of total exposure. Furthermore, for participants with highest overall exposure to takeaway food outlets, workplaces accounted for most of the exposure. Levels of relative exposure between home, work and commuting environments were poorly correlated. Relying solely on residential neighbourhood characterisation greatly underestimated total foodscape exposure in this sample, with levels of home exposure unrelated to levels of away from home exposure. Such mis-estimation is likely to be expressed in analyses as attenuated parameter estimates, suggesting a minimal ‘environmental’ contribution to outcomes of interest. Future work should aim to assess exposure more completely through characterising environments beyond the residential neighbourhood, where behaviours related to food consumption are likely to occur.

Household income (as a marker of socioeconomic position) and neighbourhood fast-food outlet exposure may be related to diet and body weight, which are key risk factors for non-communicable diseases. However, the research evidence is equivocal. Moreover, understanding the double burden of these factors is a matter of public health importance. The purpose of this study was to test associations of neighbourhood fast-food outlet exposure and household income, in relation to frequency of consumption of processed meat and multiple measures of adiposity, and to examine possible interactions. We employed an observational, cross-sectional study design. In a cohort of 51,361 adults aged 38–72 years in Greater London, UK, we jointly classified participants based on household income (£/year, four groups) and GIS-derived neighbourhood fast-food outlet proportion (counts of fast-food outlets as a percentage of all food outlets, quartiles). Multivariable regression models estimated main effects and interactions (additive and multiplicative) of household income and fast-food outlet proportion on odds of self-reported frequent processed meat consumption (> 1/week), measured BMI (kg/m2), body fat (%), and odds of obesity (BMI ≥ 30). Income and fast-food proportion were independently, systematically associated with BMI, body fat, obesity and frequent processed meat consumption. Odds of obesity were greater for lowest income participants compared to highest (OR = 1.54, 95% CI: 1.41, 1.69) and for those most-exposed to fast-food outlets compared to least-exposed (OR = 1.51, 95% CI: 1.40, 1.64). In jointly classified models, lowest income and highest fast-food outlet proportion in combination were associated with greater odds of obesity (OR = 2.43, 95% CI: 2.09, 2.84), with relative excess risk due to interaction (RERI = 0.03). Results were similar for frequent processed meat consumption models. There was no evidence of interaction on a multiplicative scale between fast-food outlet proportion and household income on each of BMI (P = 0.230), obesity (P = 0.054) and frequent processed meat consumption (P = 0.725). Our study demonstrated independent associations of neighbourhood fast-food outlet exposure and household income, in relation to diet and multiple objective measures of adiposity, in a large sample of UK adults. Moreover, we provide evidence of the double burden of low income and an unhealthy neighbourhood food environment, furthering our understanding of how these factors contribute jointly to social inequalities in health.