Fast-food outlet availability and obesity: Considering variation by age and methodological diversity in 22,889 Yorkshire Health Study participants

Associations between the neighbourhood food environment and food and drink purchasing in England during lockdown: A repeated cross-sectional analysis

INTRODUCTION

Evidence for the effect of neighbourhood food environment (NFE) exposures on diet in the UK is mixed, potentially due to exposure misclassification. This study used the first national COVID-19 lockdown in England as an opportunity to isolate the independent effects of the NFE exposure on food and drink purchasing, and assessed whether these varied by region.

METHODS

Transaction-level purchasing data for food and drink items for at-home (1,221 households) and out-of-home consumption (171 individuals) were available from the GB Kantar Fast Moving Consumer Goods Panel for London and the North of England. The study period included 23rd March to 10th May 2020 ('lockdown'), and the same period in 2019 for comparison. NFE exposures included food outlet density and proximity, and NFE composition within a 1 km network buffer around the home. Associations were estimated for both years separately, adjusted for individual and household characteristics, population density and area deprivation. Interaction terms between region and exposures were explored.

RESULTS

There were no consistent patterns of association between NFE exposures and food and drink purchasing in either time period. In 2019, there was some evidence for a 1.4% decrease in energy purchased from ultra-processed foods for each additional 500 m in the distance to the nearest OOH outlet (IR 0.986, 95% CI 0.977 to 0.995, p = 0.020). In 2020, there was some evidence for a 1.8% reduction in total take-home energy for each additional chain supermarket per km2 in the neighbourhood (IR 0.982, 95% CI 0.969, 0.995, p = 0.045). Region-specific effects were observed in 2019 only.

DISCUSSION

Findings suggest that the differences in exposure to the NFE may not explain differences in the patterns or healthiness of grocery purchasing. Observed pre-pandemic region-specific effects allude to the importance of geographical context when designing research and policy. Future research may assess associations for those who relied on their NFE during lockdown.

Changes in the number of new takeaway food outlets associated with adoption of management zones around schools: A natural experimental evaluation in England

By the end of 2017, 35 local authorities (LAs) across England had adopted takeaway management zones (or "exclusion zones") around schools as a means to curb proliferation of new takeaways. In this nationwide, natural experimental study, we evaluated the impact of management zones on takeaway retail, including unintended displacement of takeaways to areas immediately beyond management zones, and impacts on chain fast-food outlets. We used uncontrolled interrupted time series analyses to estimate changes from up to six years pre- and post-adoption of takeaway management zones around schools. We evaluated three outcomes: mean number of new takeaways within management zones (and by three identified sub-types: full management, town centre exempt and time management zones); mean number on the periphery of management zones (i.e. within an additional 100 m of the edge of zones); and presence of new chain fast-food outlets within management zones. For 26 LAs, we observed an overall decrease in the number of new takeaways opening within management zones. Six years post-intervention, we observed 0.83 (95% CI -0.30, -1.03) fewer new outlets opening per LA than would have been expected in absence of the intervention, equivalent to an 81.0% (95% CI -29.1, -100) reduction in the number of new outlets. Cumulatively, 12 (54%) fewer new takeaways opened than would have been expected over the six-year post-intervention period. When stratified by policy type, effects were most prominent for full management zones and town centre exempt zones. Estimates of intervention effects on numbers of new takeaways on the periphery of management zones, and on the presence of new chain fast-food outlets within management zones, did not meet statistical significance. Our findings suggest that management zone policies were able to demonstrably curb the proliferation of new takeaways. Modelling studies are required to measure the possible population health impacts associated with this change.

Fast food proximity and weight gain in childhood and adolescence: Evidence from Great Britain

We study the relationship between proximity to fast food restaurants and weight gain from late childhood to early adolescence. We use the Millennium Cohort Study, a UK-wide nationally representative longitudinal study, linked with granular geocoded food outlet data to measure the presence of fast food outlets around children's homes and schools from ages 7 to 14. We find that proximity to fast food outlets is associated with increased weight (body mass index, overweight, obese, body fat, weight), but only among those with maternal education below degree level. Within this sample, those with lower levels of emotional regulation are at heightened risk of weight gain.

Associations between area deprivation and changes in the digital food environment during the COVID-19 pandemic: Longitudinal analysis of three online food delivery platforms

Online food delivery services facilitate access to unhealthy foods and have proliferated during the COVID-19 pandemic. This study explores associations between neighbourhood deprivation and exposure to online food delivery services and changes in exposure by deprivation during the first year of the pandemic. Data on food outlets delivering to 661 postcode districts in London and the North of England in 2020 and 2021 were collected from three online delivery platforms. The association between area deprivation and overall exposure to online food delivery services was moderated by region, with evidence of a positive relationship between count of outlets and deprivation in the North of England, and a negative relationship in London. There was no association between area deprivation and growth of online food delivery services. Associations between neighbourhood deprivation and exposure to the digital food environment vary geographically. Consequently, policies aimed at the digital food environment need to be tailored to the local context.

Associations between the food environment and food and drink purchasing using large-scale commercial purchasing data: a cross-sectional study

BACKGROUND

Evidence for an association between the local food environment, diet and diet-related disease is mixed, particularly in the UK. One reason may be the use of more distal outcomes such as weight status and cardiovascular disease, rather than more proximal outcomes such as food purchasing. This study explores associations between food environment exposures and food and drink purchasing for at-home and out-of-home (OOH) consumption.

METHODS

We used item-level food and drink purchase data for London and the North of England, UK, drawn from the 2019 Kantar Fast Moving Consumer Goods panel to assess associations between food environment exposures and household-level take-home grocery (n=2,118) and individual-level out-of-home (n=447) food and drink purchasing. Density, proximity and relative composition measures were created for both supermarkets and OOH outlets (restaurants and takeaways) using a 1 km network buffer around the population-weighted centroid of households' home postcode districts. Associations between food environment exposure measures and frequency of take-home food and drink purchasing, total take-home calories, calories from fruits and vegetables, high fat, salt and sugar products, and ultra-processed foods (UPF), volume of take-home alcoholic beverages, and frequency of OOH purchasing were modelled using negative binomial regression adjusted for area deprivation, population density, and individual and household socio-economic characteristics.

RESULTS

There was some evidence for an inverse association between distance to OOH food outlets and calories purchased from ultra-processed foods (UPF), with a 500 m increase in distance to the nearest OOH outlet associated with a 1.1% reduction in calories from UPF (IR=0.989, 95%CI 0.982-0.997, p=0.040). There was some evidence for region-specific effects relating to purchased volumes of alcohol. However, there was no evidence for an overall association between food environment exposures and take-home and OOH food and drink purchasing.

CONCLUSIONS

Despite some evidence for exposure to OOH outlets and UPF purchases, this study finds limited evidence for the impact of the food environment on household food and drink purchasing. Nonetheless, region-specific effects regarding alcohol purchasing indicate the importance of geographical context for research and policy.

Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III

Objective

To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI).

Methods

The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education.

Results

Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity.

Conclusion

Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

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Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed.

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Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change.

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There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.

Childhood obesity, is fast food exposure a factor?

Access to fast food has often been blamed for the rise in obesity which in turn has motivated policies to curb the spread of fast food. However, robust evidence in this area is scarce, particularly using data outside of the US. It is difficult to estimate a causal effect of fast food given spatial sorting and ever-present exposure. We investigate whether the residential access to fast food increased BMI of adolescents at a time when fast food restaurants started to open in the UK. The time period presents the study with large spatial and temporal differences in exposure as well as plausibly exogenous variation. We merge data on the location and timing of the first openings of all fast food outlets in the UK from 1968-1986, with data on objectively measured BMI from the 1970 British Cohort Survey. The relationship between adolescent BMI and the distance from the respondents' homes and time since opening, is studied using OLS and Instrumental Variables regression. We find that fast food exposure had no effect on BMI. Extensive robustness checks do not change our conclusion.

From healthy food environments to healthy wellbeing environments: Policy insights from a focused ethnography with low-income parents' in England

Overweight and obesity continue to increase globally. In England, as in many other countries, this disproportionately affects people who experience socioeconomic deprivation. One factor blamed for inequalities in obesity is unhealthy food provisioning environments (FPEs), leading to a focus on policies and interventions to change FPEs. This paper aims to provide insights into how FPE policies could more effectively tackle inequalities in obesity by addressing a key research gap: how the structural contexts in which people live their lives influence their interaction with their FPEs. It aims to understand how low-income families engage with FPEs through in-depth focused ethnographic research with 60 parents across three locations in England: Great Yarmouth, Stoke-on-Trent, and the London Borough of Lewisham. Analysis was guided by sociological perspectives. FPEs simultaneously push low-income families towards unhealthy products while supporting multiple other family needs, such as social wellbeing. FPE policies and interventions to address obesity must acknowledge this challenge and consider not just the makeup of FPEs themselves but how various structural contexts shape how people come to use them.

Study on Spatial Structure Characteristics of the Tourism and Leisure Industry

By taking Beijing as the case site, using open-source Point of Interest data, and employing spatial visualization techniques, this study explores the spatial structural characteristics of the Beijing tourism and leisure industry and its sub-sectors. It has been found that (1) the nearest neighbor indexes of the tourism and leisure industry and its sub-sectors are all less than 1, indicating that the tourism and leisure industry and its sub-sectors in Beijing exhibit a spatial clustering distribution. Scenic spots have the largest R-value of 0.52 and, thus, the lowest degree of clustering. The minimum R-value of 0.15 is found in catering, marking the highest degree of clustering in the industry; (2) the main directional trend of the tourism and leisure industry and its sub-sectors in Beijing is the “northeast-southwest” direction, the south-north directional dispersion is dominant, and scenic spots demonstrate a more noticeable trend of spatial dispersion; (3) within the area from Sanlitun Street in the north to Panjiayuan Street in the south, and from Chaoyangmen Street in the west to Liulitun Street in the east, is situated the largest portion of cluster centers with the highest degree of clustering in Beijing’s tourism and leisure industry. The contiguous high-density cluster center of catering starts from Sanlitun Street in the north to Jinsong Street in the south, and from Chaoyangmen Street in the west to Liulitun Street in the east. The cluster of shopping and entertainment shows a checkerboard pattern in the CZCF and NUDZ. The high-value cluster of accommodation occurs primarily around Sanlitun, Panjiayuan, and Qianmen; (4) the distribution of three grades of hot spot areas and non-significant areas of tourism and leisure, catering, accommodation, and shopping and entertainment in Beijing demonstrates a circular pattern that centers around the CZCF and expands outward in sequence. High-value hot spot streets for this area are dominated by Beixinqiao Street, Hepingli Street, Sanlitun Street, Heping Street, and Tuanjiehu Street; and the high-value cold spot streets of the area are chiefly in Fuzizhuang Township, Wangping Town, Miaofeng Mountain Town, and Tanzhesi Town.

Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

Background

Unhealthy food environments may contribute to unhealthy diets and risk of overweight and obesity through increased consumption of fast-food. Therefore, we aimed to study the association of relative exposure to fast-food restaurants (FFR) with overall diet quality and risk of overweight and obesity in a sample of older adults.

Methods

We analyzed cross-sectional data of the EPIC-NL cohort (n = 8,231). Data on relative FFR exposure was obtained through linkage of home address in 2015 with a retail outlet database. We calculated relative exposure to FFR by dividing the densities of FFR in street-network buffers of 400, 1000, and 1500 m around the home of residence by the density of all food retailers in the corresponding buffer. We calculated scores on the Dutch Healthy Diet 2015 (DHD15) index using data from a validated food-frequency questionnaire. BMI was categorized into normal weight (BMI < 25), overweight (25 ≤ BMI < 30), and obesity (BMI ≥ 30). We used multivariable linear regression (DHD15-index) and multinomial logistic regression (weight status), using quartiles of relative FFR exposure as independent variable, adjusting for lifestyle and environmental characteristics.

Results

Relative FFR exposure was not significantly associated with DHD15-index scores in the 400, 1000, and 1500 m buffers (β_Q4vsQ1= -0.21 [95 %CI: -1.12; 0.70]; β_Q4vsQ1= -0.12 [95 %CI: -1.10; 0.87]; β_Q4vsQ1 = 0.37 [95 %CI: -0.67; 1.42], respectively). Relative FFR exposure was also not related to overweight in consecutive buffers (OR_Q4vsQ1=1.10 [95 %CI: 0.97; 1.25]; OR_Q4vsQ1=0.97 [95 %CI: 0.84; 1.11]; OR_Q4vsQ1= 1.04 [95 %CI: 0.90–1.20]); estimates for obesity were similar to those of overweight.

Conclusions

A high proportion of FFR around the home of residence was not associated with diet quality or overweight and obesity in this large Dutch cohort of older adults. We conclude that although the food environment may be a determinant of food choice, this may not directly translate into effects on diet quality and weight status. Methodological improvements are warranted to provide more conclusive evidence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12937-021-00713-5.

Neighborhood Ethnic Composition and Self-rated Health Among Chinese and Vietnamese American Immigrants

Immigrants tend to live in areas with higher co-ethnic density, and the effect of neighborhood ethnic composition could be particularly salient for health. This study explored associations between neighborhood ethnic composition and self-rated health among Asian immigrants. We analyzed data collected at baseline from 670 Chinese and Vietnamese immigrants enrolled in a lifestyle intervention trial. Residential addresses were geocoded and combined with neighborhood socio-demographic profiles based on census data. We used generalized estimating equations to examine neighborhood ethnic composition and self-rated health. Independent of individual-level factors, living in neighborhoods more densely populated by whites was associated with poor/fair self-rated health. Neighborhood household income and density of participants' own ethnic group were not associated with poor/fair self-rated health. More research is warranted to disentangle reasons why Chinese and Vietnamese immigrants living in white-concentrated neighborhoods reported poorer self-rated health, including investigating effects of discrimination, relative deprivation, and availability of social resources.

To dine in or not to dine in: A comparison of food selection and preparation behaviours in those with and without food security

Issue addressed

Vulnerable populations are disproportionately affected by food insecurity, resulting in heightened risk of suboptimal dietary intake. Food insecure people appear to implement several coping strategies and dietary compromises to avoid hunger. Less explored in the literature is how these strategies impact consumption of food inside and outside of the home.

Methods

An online survey was completed by adults (n = 1292) residing in one of five Australian states. The questionnaire comprised of the six‐item US Household Food Security Survey Module, 12 socio‐demographic variables and 32 questions related to elements of food literacy.

Results

Food insecure respondents were more likely to frequent fast food vs (P = .002), takeaway (P < .001) and food courts (P < .001) than their food secure counterparts. Food secure respondents reported greater use of raw (P = .043) and fresh, pre‐prepared produce (P = .002) when cooking, whereas food insecure respondents were more likely to prepare food using only frozen, pre‐packaged products (P < .001). No significant differences were found between food security status and the enjoyment and social bonding derived from cooking.

Conclusions

Food insecure respondents appeared to be accessing a poorer quality of food through greater consumption of takeaway and fast food. These dietary compromises are most likely related to perceived financial, time or cooking facility constraints and to a lesser extent food literacy skills.

So what?

This study highlights some of the health and social inequities apparent within food insecure populations. Food insecure households should be supported to access healthy fresh food and in‐home cooking practices. While a multi strategy approach is required, healthy food environment policy, particularly in disadvantaged areas, should be considered to guarantee that all Australians have dignified access to nutritious food.

Disentangling individual and neighborhood differences in the intention to quit smoking in Asian American male smokers

Numerous studies have assessed individual-level factors associated with intention to quit smoking. However, fewer studies have assessed how neighborhood and built environment also contribute towards individual-level behavior. We used baseline data of 340 Chinese and Vietnamese male daily smokers from August 2015 to November 2017 living in the San Francisco Bay Area, who enrolled in a lifestyle intervention trial. The outcome variable was intention to quit in 30 days. To understand the role of contextual factors participants' residential addresses were geocoded, and neighborhood median income, ethnic composition, and tobacco retail density were computed. Individual level analysis suggested that Vietnamese American men had greater intention to quit smoking (OR = 2.90 CI = 1.59, 5.26) in comparison to Chinese Americans. However, after adding neighborhood level factors to the model, no ethnic group difference was observed. Neighborhood household median income (OR = 0.74, CI = 0.64, 0.86) and tobacco retail counts (OR = 0.79, CI = 0.67, 0.94) were negatively associated with intention to quit. Years lived in the U.S. was the only individual level factor associated with intention to quit. By comparing two Asian American groups that live in heterogeneous neighborhoods, we identify key environmental and policy drivers that are associated with quit intention. Future studies aimed at influencing individual-level behavior should take into consideration the neighborhood context and built environment characteristics.

Neighborhood physical food environment and cardiovascular risk factors in India: Cross-sectional evidence from APCAPS

There has been increasing interest in associations between neighborhood food environments and cardiovascular risk factors. However, results from high-income countries remain inconsistent, and there has been limited research from low- and middle-income countries. We conducted a cross-sectional analysis of the third wave follow-up of the Andhra Pradesh children and parents study (APCAPS) (n = 5764, median age 28.8 years) in south India. We examined associations between the neighborhood availability (vendor density per km2 within 400 m and 1600 m buffers of households) and accessibility (distance from the household to the nearest vendor) of fruit/vegetable and highly processed/take-away food vendors with 11 cardiovascular risk factors, including adiposity measures, glucose-insulin, blood pressure, and lipid profile. In fully adjusted models, higher density of fruit/vegetable vendors within 400 m of participant households was associated with lower systolic blood pressure [-0.09 mmHg, 95% confidence interval (CI): -0.17, -0.02] and diastolic blood pressure (-0.10 mmHg, 95% CI: -0.17, -0.04). Higher density of highly processed/take-away food vendors within 400 m of participant households was associated with higher Body Mass Index (0.01 Kg/m2, 95% CI: 0.00, 0.01), waist circumference (0.22 mm, 95% CI: 0.05, 0.39), systolic blood pressure (0.03 mmHg, 95% CI: 0.01, 0.06), and diastolic blood pressure (0.03 mmHg, 95% CI: 0.01, 0.05). However, within 1600 m buffer, only association with blood pressure remained robust. No associations were found for between neighborhood accessibility and cardiovascular risk factors. Lower density of fruit/vegetable vendors, and higher density of highly processed/take-away food vendors were associated with adverse cardiovascular risk profiles. Public health policies regarding neighborhood food environments should be encouraged in south India and other rural communities in south Asia.