Does unmeasured confounding influence associations between the retail food environment and body mass index over time? The Coronary Artery Risk Development in Young Adults (CARDIA) study

Rummo, Pasquale E.; Guilkey, David K.; Ng, Shu Wen; Meyer, Katie A.; Popkin, Barry M.; Reis, Jared P.; Shikany, James M.; Gordon‐Larsen, Penny

doi:10.1093/ije/dyx070

Cited by 20 publications

(28 citation statements)

References 38 publications

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“…A flowchart of the selection process is presented in figure 1. From the 12 757 identified studies, after screening for relevant titles, abstracts and full manuscripts, 66 articles that fitted the eligibility criteria were selected 30–95. Summary characteristics are shown in table 2 and complete characteristics of the studies are shown in online supplementary file 2.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2020

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Context and objectivesNeighbourhood 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?DesignA 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.ResultsThis 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.ConclusionOur 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.

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Section: Resultsmentioning

confidence: 99%

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

et al. 2020

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“…Table 1 presents the three continuous food swamp measures we used, which were based on previous studies utilizing relative food environment measures [ 23 , 30 , 33 , 34 , 39 , 47 ]. All county-level food store data was sourced from the Food Environment Atlas.…”

Section: Data and Empirical Strategymentioning

confidence: 99%

“…We test the effect of food access on obesity rates by using a county-level unit of analysis [ 26 ]. This approach complements the current literature as it is more aggregated than the local community level [ 27 , 28 , 29 , 30 , 31 , 34 , 35 , 39 ], but less aggregated than the state level [ 32 , 42 ]. Previous work by Dunn [ 26 ] and Blanchard and Lyson [ 43 ] documents significant county-level variations in access to fast food restaurants or grocery stores.…”

Section: Introductionmentioning

confidence: 98%

“…Observational studies tend to assume that the food environment shapes individual health behaviors and health outcomes, but not vice versa. However, individuals may self-select into neighborhoods, and it is important that studies on neighborhood food environments and obesity account for this endogeneity problem [ 5 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Because it is not feasible to assign people to neighborhoods in an experimental design, statistical adjustments are necessary.…”

Section: Introductionmentioning

confidence: 99%

“…Third, this paper addresses the question of reverse causality , which is relevant because both individuals and the builders of food outlets choose to go into certain neighborhoods. Different statistical methods have been utilized to account for unobserved characteristics that may influence where individuals and food retailers choose to locate [ 5 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 40 ]. An increasingly common approach is to instrument for food store access with highways (counts within, or distance from, a predetermined geographic area), street connectivity or land zoned for commercial use [ 26 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

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Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States

Stowers

Schwartz

Brownell

2017

IJERPH

444

342

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This paper investigates the effect of food environments, characterized as food swamps, on adult obesity rates. Food swamps have been described as areas with a high-density of establishments selling high-calorie fast food and junk food, relative to healthier food options. This study examines multiple ways of categorizing food environments as food swamps and food deserts, including alternate versions of the Retail Food Environment Index. We merged food outlet, sociodemographic and obesity data from the United States Department of Agriculture (USDA) Food Environment Atlas, the American Community Survey, and a commercial street reference dataset. We employed an instrumental variables (IV) strategy to correct for the endogeneity of food environments (i.e., that individuals self-select into neighborhoods and may consider food availability in their decision). Our results suggest that the presence of a food swamp is a stronger predictor of obesity rates than the absence of full-service grocery stores. We found, even after controlling for food desert effects, food swamps have a positive, statistically significant effect on adult obesity rates. All three food swamp measures indicated the same positive association, but reflected different magnitudes of the food swamp effect on rates of adult obesity (p values ranged from 0.00 to 0.16). Our adjustment for reverse causality, using an IV approach, revealed a stronger effect of food swamps than would have been obtained by naïve ordinary least squares (OLS) estimates. The food swamp effect was stronger in counties with greater income inequality (p < 0.05) and where residents are less mobile (p < 0.01). Based on these findings, local government policies such as zoning laws simultaneously restricting access to unhealthy food outlets and incentivizing healthy food retailers to locate in underserved neighborhoods warrant consideration as strategies to increase health equity.

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Differences in the Neighborhood Retail Food Environment and Obesity Among US Children and Adolescents by SNAP Participation

Findling

Wolfson

Rimm

et al. 2018

Obesity

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Does unmeasured confounding influence associations between the retail food environment and body mass index over time? The Coronary Artery Risk Development in Young Adults (CARDIA) study

Abstract: Longitudinal associations between neighbourhood food outlets and BMI were greater in magnitude using a causal model, suggesting that weak findings in the literature may be due to residual confounding.

Cited by 20 publications

References 38 publications

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

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

Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States

Differences in the Neighborhood Retail Food Environment and Obesity Among US Children and Adolescents by SNAP Participation

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