Geographic Accessibility Of Food Outlets Not Associated With Body Mass Index Change Among Veterans, 2009-14

Influence of the food environment on obesity risk in a large cohort of US veterans by community type

OBJECTIVE

The aim of this study was to examine relationships between the food environment and obesity by community type.

METHODS

Using electronic health record data from the US Veterans Administration Diabetes Risk (VADR) cohort, we examined associations between the percentage of supermarkets and fast-food restaurants with obesity prevalence from 2008 to 2018. We constructed multivariable logistic regression models with random effects and interaction terms for year and food environment variables. We stratified models by community type.

RESULTS

Mean age at baseline was 59.8 (SD = 16.1) years; 93.3% identified as men; and 2,102,542 (41.8%) were classified as having obesity. The association between the percentage of fast-food restaurants and obesity was positive in high-density urban areas (odds ratio [OR] = 1.033; 95% CI: 1.028-1.037), with no interaction by time (p = 0.83). The interaction with year was significant in other community types (p < 0.001), with increasing odds of obesity in each follow-up year. The associations between the percentage of supermarkets and obesity were null in high-density and low-density urban areas and positive in suburban (OR = 1.033; 95% CI: 1.027-1.039) and rural (OR = 1.007; 95% CI: 1.002-1.012) areas, with no interactions by time.

CONCLUSIONS

Many healthy eating policies have been passed in urban areas; our results suggest such policies might also mitigate obesity risk in nonurban areas.

Effects of changes in residential fast-food outlet exposure on Body Mass Index change: longitudinal evidence from 92,211 Lifelines participants

BACKGROUND

Evidence on the association between fast-food outlet exposure and Body Mass Index (BMI) remains inconsistent and is primarily based on cross-sectional studies. We investigated the associations between changes in fast-food outlet exposure and BMI changes, and to what extent these associations are moderated by age and fast-food outlet exposure at baseline.

METHODS

We used 4-year longitudinal data of the Lifelines adult cohort (N = 92,211). Participant residential addresses at baseline and follow-up were linked to a register containing fast-food outlet locations using geocoding. Change in fast-food outlet exposure was defined as the number of fast-food outlets within 1 km of the residential address at follow-up minus the number of fast-food outlets within 1 km of the residential address at baseline. BMI was calculated based on objectively measured weight and height. Fixed effects analyses were performed adjusting for changes in covariates and potential confounders. Exposure-moderator interactions were tested and stratified analyses were performed if p < 0.10.

RESULTS

Participants who had an increase in the number of fast-food outlets within 1 km had a greater BMI increase (B(95% CI): 0.003 (0.001,0.006)). Decreases in fast-food outlet exposure were not associated with BMI change (B(95% CI): 0.001 (-0.001,0.004)). No clear moderation pattern by age or fast-food outlet exposure at baseline was found.

CONCLUSIONS

Increases in residential fast-food outlet exposure are associated with BMI gain, whereas decreases in fast-food outlet exposure are not associated with BMI loss. Effect sizes of increases in fast-food outlet exposure on BMI change were small at individual level. However, a longer follow-up period may have been needed to fully capture the impact of increases in fast-food outlet exposure on BMI change. Furthermore, these effect sizes could still be important at population level considering the rapid rise of fast-food outlets across society. Future studies should investigate the mechanisms and changes in consumer behaviours underlying associations between changes in fast-food outlet exposure and BMI change.

Food Insecurity in US Military Veterans

BACKGROUND

Food insecurity (FI) is an important public health issue for US veterans. For many veterans, civilian life is fraught with service-incurred health issues and socioeconomic challenges, each risk factors for FI. The FI literature on veterans is limited due to insufficient coverage of the topic's complexity and the methods used to study it in this population. No published analysis has evaluated how FI has been examined in US veterans.

OBJECTIVES

We assessed how FI has been examined in US military veterans by identifying (1) the major content areas, or domains, studied in association with FI and (2) the existing research gaps.

METHODS

A scoping literature review was conducted to map the main research domains of the FI literature and identify knowledge gaps. Electronic database and hand searches identified potentially relevant studies (n = 61). Data extraction, utilizing a standardized set of design parameters, was completed. Duplicate removal and application of inclusion/exclusion criteria resulted in the studies (n = 21) selected for critical review.

RESULTS

Eight research domains were determined: FI prevalence, health status, dietary practices, health care utilization, economic instability, homelessness/housing instability, food program participation, and community/emergency preparedness-the most dominant was health status and the least dominant were social determinants (ie, homelessness/housing instability, food program participation). Research on validity and usability of FI assessment methods in veterans was virtually absent. Military service factors, longitudinal effects, FI among women, intervention effectiveness, and other areas lacked sufficient inquiry.

CONCLUSION

Research is required on lesser examined content areas and methodology to optimize surveillance and policy for veteran FI.

Neighbourhood effects on obesity: scoping review of time-varying outcomes and exposures in longitudinal designs

CONTEXT AND OBJECTIVES

Neighbourhood effect research on obesity took off in the early 2000s and was composed of mostly cross-sectional observational studies interested in various characteristics of the built environment and the socioeconomic environment. To limit biases related to self-selection and life course exposures, many researchers apply longitudinal designs in their studies. Until now, no review has specifically and exclusively examined longitudinal studies and the specific designs of these studies. In this review, we intend to answer the following research question: how are the temporal measurements of contextual exposure and obesity outcomes integrated into longitudinal studies that explore how neighbourhood-level built and socioeconomic environments impact adult obesity?

DESIGN

A systematic search strategy was designed to address the research question. The search was performed in Embase, Web of Science and PubMed, targeting scientific papers published before 1 January 2018. The eligible studies reported results on adults, included exposure that was limited to neighbourhood characteristics at the submunicipal level, included an outcome limited to obesity proxies, and reported a design with at least two exposure measurements or two outcome measurements.

RESULTS

This scoping review identified 66 studies that fit the eligibility criteria. A wide variety of neighbourhood characteristics were also measured, making it difficult to draw general conclusions about associations between neighbourhood exposure and obesity. We applied a typology that classified studies by whether exposure and outcome were measured as varying or fixed. Using this typology, we found that 32 studies reported both neighbourhood exposure and obesity outcomes that were varying in time; 28 reported varying outcomes but fixed exposures; and 6 had fixed outcomes and varying exposures.

CONCLUSION

Our typology illustrates the variety of longitudinal designs that were used in the selected studies. In the light of our results, we make recommendations on how to better report longitudinal designs and facilitate comparisons between studies.

Associations of Unhealthy Food Environment With the Development of Coronary Artery Calcification: The CARDIA Study

Background

While prior studies have linked the neighborhood environment and development of subclinical atherosclerosis, it is unknown whether living in neighborhoods with greater availability of “unhealthy” food outlets (fast‐food chain restaurants and convenience stores) is associated with risk of developing coronary artery calcification (CAC).

Methods and Results

We included 2706 CARDIA study (Coronary Artery Risk Development in Young Adults) participants who underwent CAC measurement during follow‐up years 15 (2000–2001), 20 (2005–2006), and 25 (2010–2011). Neighborhood features examined included percentage of all food outlets that were convenience stores and fast‐food chain restaurants within a 3‐km Euclidean buffer distance from each participant's residence. Econometric fixed effects models, which by design control for all time‐invariant covariates, were used to model the longitudinal association between simultaneous within‐person change in percentage food outlet and change in CAC. At baseline (year 15), 9.7% of participants had prevalent CAC. During 10 years of follow‐up, 21.1% of participants developed CAC. Each 1‐SD increase in percentage of convenience stores was associated with a 1.34 higher odds of developing CAC (95% CI: 1.04, 1.72) after adjusting for individual‐ and neighborhood‐level covariates; however, there was no significant association between increased percentage of fast‐food chain restaurants and developing CAC (odds ratio=1.15; 95% CI: 0.96, 1.38). There were no significant associations between increases in either food outlet percentage and progression of CAC.

Conclusions

Our findings suggest that increases in the relative availability of convenience stores in participants' neighborhoods is related to the development of CAC over time.

Neighborhood Walkability and BMI Change: A National Study of Veterans in Large Urban Areas

OBJECTIVE

Improving neighborhood walkability has been proposed as a policy intervention to reduce obesity. The objective of this study was to evaluate longitudinal relationships between neighborhood walkability and body weight among adults living in large urban areas.

METHODS

In this retrospective longitudinal study of United States military veterans using Department of Veterans Affairs health care, Veterans Affairs clinical and administrative data (2007-2014) were linked to environmental measures constructed from public (2006-2014) and proprietary (2008-2014) sources, and linear regression models with person fixed effects were used to estimate associations between walkability and BMI among 758,434 men and 70,319 women aged 20 to 80 years in 2009 to 2014.

RESULTS

Neighborhood walkability was associated with small reductions in BMI. Effects were most pronounced among men aged 30 to 49 and 50 to 64. For women, differences were largest in the two youngest age groups, 20 to 29 and 30 to 49, though only estimates for all women combined were statistically significant. For women aged 30 to 49, effect sizes grew when the sample was limited to those who remained in the same neighborhood during the entire follow-up period.

CONCLUSIONS

Investments in the built environment to improve walkability may be a useful strategy for weight control in some segments of the adult population.

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Associations between food environment typologies and body mass index: Evidence from Yorkshire, England

International research linking food outlets and body mass index (BMI) is largely cross-sectional, yielding inconsistent findings. However, addressing the exposure of food outlets is increasingly considered as an important adult obesity prevention strategy. Our study investigates associations between baseline food environment types and change in BMI over time. Survey data were used from the Yorkshire Health Study (n=8,864; wave one: 2010-2012, wave two: 2013-2015) for adults aged 18-86. BMI was calculated using self-reported height (cm) and weight (kg). Restaurants, cafés, fast-food, speciality, convenience and large supermarkets were identified from the Ordnance Survey Point of Interest database within 1600m radial buffer of home postcodes. K-means cluster analysis developed food environment typologies based on food outlets and population density. Large supermarkets, restaurants, cafés, fast-food, speciality and convenience food outlets all clustered together to some extent. Three neighbourhood typologies were identified. However, multilevel models revealed that relative to cluster one all were unrelated to change in BMI (cluster 2, b= -0.146 [-0.274, 0.566]; cluster 3, b= 0.065 [-0.224, 0.356]). There was also little evidence of gender-based differences in these associations when examined in a three-way interaction. Policymakers may need to begin to consider multiple types of food outlet clusters, while further research is needed to confirm how these relate to changed BMI.

The price of ultra-processed foods and beverages and adult body weight: Evidence from U.S. veterans

The consumption of ultra-processed foods in the U.S. and globally has increased and is associated with lower diet quality, higher energy intake, higher body weight, and poorer health outcomes. This study drew on individual-level data on measured height and weight from U.S. Department of Veterans Affairs medical records for adults aged 20 to 64 from 2009 through 2014 linked to food and beverage price data from the Council for Community and Economic Research to examine the association between the price of ultra-processed foods and beverages and adult body mass index (BMI). We estimated geographic fixed effects models to control for unobserved heterogeneity of prices. We estimated separate models for men and women and we assessed differences in price sensitivity across subpopulations by socioeconomic status (SES). The results showed that a one-dollar increase in the price of ultra-processed foods and beverages was associated with 0.08 lower BMI units for men (p ≤ 0.05) (price elasticity of BMI of -0.01) and 0.14 lower BMI units for women (p ≤ 0.10) (price elasticity of BMI of -0.02). Higher prices of ultra-processed foods and beverages were associated with lower BMI among low-SES men (price elasticity of BMI of -0.02) and low-SES women (price elasticity of BMI of -0.07) but no statistically significant associations were found for middle- or high-SES men or women. Robustness checks based on the estimation of an individual-level fixed effects model found a consistent but smaller association between the price of ultra-processed foods and beverages and BMI among women (price elasticity of BMI of -0.01) with a relatively larger association for low-SES women (price elasticity of BMI of -0.04) but revealed no association for men highlighting the importance of accounting for individual-level unobserved heterogeneity.

Would increasing access to recreational places promote healthier weights and a healthier nation?

Addressing gaps in evidence on causal associations, this study tested the hypothesis that better access to recreational places close to home helps people to maintain lower body mass index (BMI) using a retrospective longitudinal study design and up to 6 years of data for the same individuals (1,522,803 men and 183,618 women). Participants were military veterans aged 20-64 who received healthcare through the U.S. Department of Veterans Affairs in 2009-2014 and lived in a metropolitan area. Although there were cross-sectional associations, we found no longitudinal evidence that access to parks and fitness facilities was associated with BMI for either men or women in the full sample or in subgroups of residential movers and stayers. Our findings suggest that simply increasing the number of parks and fitness facilities may not be enough to achieve needed population-level reductions in weight.

Foreclosures and weight gain: Differential associations by longer neighborhood exposure

While home foreclosure can lead to mental and physical health declines in persons experiencing the foreclosure, whether neighborhood foreclosures can affect the health of other residents is debatable. Using a racially/ethnically diverse sample of Chicago metropolitan area residents linked to foreclosure data from 2008 to 2014, we assessed whether exposure to neighborhood foreclosure fillings was associated with changes in objectively measured body mass index (BMI) over time. Using a retrospective longitudinal design, we employed fixed-effects regression models that controlled for individual- and neighborhood-level covariates to test the association of neighborhood foreclosures and BMI in >60,000 individuals and for individuals who did not move during the follow-up period. We also adjusted for the non-linear association of age and BMI and comorbidities and employed a series of sensitivity analysis to test for robustness. In fully adjusted models, a standard-deviation increase in neighborhood foreclosure filings within 500 m was associated with increases in BMI for individuals who did not move (nonmovers) (mean = 0.03 BMI units, 95% confidence interval: 0.01, 0.06). Neighborhood foreclosure rates were not associated with changes in BMI for the full sample. Given the potential deleterious effects of neighborhood foreclosure on individuals with longer exposure to the local vicinity, clarifying the potential health effects of neighborhood foreclosures would help policymakers when planning actions to prevent home losses, predatory home loans, and that aim to more efficiently return foreclosure properties to productive uses.

The Food & Fitness Community Partnerships: Results From 9 Years of Local Systems and Policy Changes to Increase Equitable Opportunities for Health

The Food & Fitness (F&F) community partnerships, funded by the W.K. Kellogg Foundation from 2007 to 2016, were established to create community-determined change in the conditions that affect health and health equity in neighborhoods. The focus of the work has been to increase access to locally grown good food (food that is healthy, sustainable, fair, and affordable), and safe places for physical activity for children and families in communities with inequities across the United States through changes in policies, community infrastructure, and systems at the local level. This article describes the outcomes related to systems and policy change over 9 years of community change efforts in the F&F partnerships. Characteristics of the F&F communities where the work took place; the change model that emerged from the work; efforts and changes achieved related to community food, school food, and active living/built environment; overall factors in the community that helped or hindered the work of the partnerships; and a depiction of the community-determined process for change employed by the partnerships are described. Local systems and policy change is a long-term process. Community-determined efforts that build capacity for systems change, commitment to long-term funding, and provision of technical assistance tailored to community needs were elements that contributed to success in the F&F work. Achieving intermediate outcomes on the road to policy and systems change created a way to monitor success and make midcourse corrections when needed.

Local Food Environments, Suburban Development, and BMI: A Mixed Methods Study

More than half the world’s population now live in urban settlements. Worldwide, cities are expanding at their fringe to accommodate population growth. Low-density residential development, urban sprawl, and car dependency are common, contributing to physical inactivity and obesity. However, urban design and planning can modify urban form and enhance health by improving access to healthy food, public transport, and services. This study used a sequential mixed methods approach to investigate associations between food outlet access and body mass index (BMI) across urban-growth and established areas of Melbourne, Australia, and identify factors that influence local food environments. Population survey data for 3141 adults were analyzed to examine associations, and 27 interviews with government, non-government, and private sector stakeholders were conducted to contextualize results. Fast food density was positively associated with BMI in established areas and negatively associated in urban-growth areas. Interrelated challenges of car dependency, poor public transport, and low-density development hampered healthy food access. This study showed how patterns of suburban development influence local food environments and health outcomes in an urbanized city context and provides insights for other rapidly growing cities. More nuanced understandings of the differential effect of food environments within cities have potential to guide intra-city planning for improving health and reducing inequities.

Food Insecurity, Food "Deserts," and Glycemic Control in Patients With Diabetes: A Longitudinal Analysis

OBJECTIVE

Both food insecurity (limited food access owing to cost) and living in areas with low physical access to nutritious foods are public health concerns, but their relative contribution to diabetes management is poorly understood.

RESEARCH DESIGN AND METHODS

This was a prospective cohort study. A random sample of patients with diabetes in a primary care network completed food insecurity assessment in 2013. Low physical food access at the census tract level was defined as no supermarket within 1 mile in urban areas and 10 miles in rural areas. HbA_1c measurements were obtained from electronic health records through November 2016. The relationship among food insecurity, low physical food access, and glycemic control (as defined by HbA_1c) was analyzed using hierarchical linear mixed models.

RESULTS

Three hundred and ninety-one participants were followed for a mean of 37 months. Twenty percent of respondents reported food insecurity, and 31% resided in an area of low physical food access. In adjusted models, food insecurity was associated with higher HbA_1c (difference of 0.6% [6.6 mmol/mol], 95% CI 0.4-0.8 [4.4-8.7], P < 0.0001), which did not improve over time (P = 0.50). Living in an area with low physical food access was not associated with a difference in HbA_1c (difference 0.2% [2.2 mmol/mol], 95% CI -0.2 to 0.5 [-2.2 to 5.6], P = 0.33) or with change over time (P = 0.07).

CONCLUSIONS

Food insecurity is associated with higher HbA_1c, but living in an area with low physical food access is not. Food insecurity screening and interventions may help improve glycemic control for vulnerable patients.

Long-Term Weight Loss Effects of a Behavioral Weight Management Program: Does the Community Food Environment Matter?

This study examined whether community food environments altered the longer-term effects of a nationwide behavioral weight management program on body mass index (BMI). The sample was comprised of 98,871 male weight management program participants and 15,385 female participants, as well as 461,302 and 37,192 inverse propensity-score weighted matched male and female controls. We measured the community food environment by counting the number of supermarkets, convenience stores, and fast food restaurants within a 1-mile radius around each person's home address. We used difference-in-difference regression models with person and calendar time fixed effects to estimate MOVE! effects over time in sub-populations defined by community food environment attributes. Among men, after an initial decrease in BMI at 6 months, the effect of the program decreased over time, with BMI increasing incrementally at 12 months (0.098 kg/m², p < 0.001), 18 months (0.069 kg/m², p < 0.001), and 24 months (0.067 kg/m², p < 0.001). Among women, the initial effects of the program decreased over time as well. Women had an incremental BMI change of 0.099 kg/m² at 12 months (p < 0.05) with non-significant incremental changes at 18 months and 24 months. We found little evidence that these longer-term effects of the weight management program differed depending on the community food environment. Physiological adaptations may overwhelm environmental influences on adherence to behavioral regimens in affecting longer-term weight loss outcomes.

Neighborhood Resources to Support Healthy Diets and Physical Activity Among US Military Veterans

Introduction

Among the nearly 21 million military veterans living in the United States, 64.0% of women and 76.1% of men are overweight or obese, higher rates than in the civilian population (56.9% of women and 69.9% of men). Attributes of the residential environment are linked to obesity. The objective of this study was to characterize the residential environments of the US veteran population with respect to availability of food and recreational venues.

Methods

We used American Community Survey data to determine the concentration of veterans (the percentage of veterans among the adult population) in all continental US census tracts in 2013, and we used proprietary data to construct measures of availability of food and recreational venues per census tract. Using descriptive statistics and ordinary least-squares regression, we examined associations between the concentration of veterans per census tract and those residential environmental features.

Results

In census tracts with high concentrations of veterans, residents had, on average, 0.5 (interquartile range, 0–0.8) supermarkets within a 1-mile radius, while residents in census tracts with low concentrations of veterans had 3.2 (interquartile range, 0.6–3.7) supermarkets. Patterns were similar for grocery and convenience stores, fast food restaurants, parks, and commercial fitness facilities. In adjusted analyses controlling for census-tract–level covariates, veteran concentration remained strongly negatively associated with availability of those food and recreational venues. In nonmetropolitan tracts, adjusted associations were greatly attenuated and even positive.

Conclusion

Where veterans live is strongly associated with availability of food outlets providing healthy (and unhealthy) foods and with recreational venues, raising questions about the contributions of veterans’ residential environments to their high obesity rates. Additional research is needed to address those questions.