Despite interest in the built food environment, little is known about the validity of commonly used secondary data. The authors conducted a comprehensive field census identifying the locations of all food outlets using a handheld global positioning system in 8 counties in South Carolina (2008–2009). Secondary data were obtained from 2 commercial companies, Dun & Bradstreet, Inc. (D&B) (Short Hills, New Jersey) and InfoUSA, Inc. (Omaha, Nebraska), and the South Carolina Department of Health and Environmental Control (DHEC). Sensitivity, positive predictive value, and geospatial accuracy were compared. The field census identified 2,208 food outlets, significantly more than the DHEC (n = 1,694), InfoUSA (n = 1,657), or D&B (n = 1,573). Sensitivities were moderate for DHEC (68%) and InfoUSA (65%) and fair for D&B (55%). Combining InfoUSA and D&B data would have increased sensitivity to 78%. Positive predictive values were very good for DHEC (89%) and InfoUSA (86%) and good for D&B (78%). Geospatial accuracy varied, depending on the scale: More than 80% of outlets were geocoded to the correct US Census tract, but only 29%–39% were correctly allocated within 100 m. This study suggests that the validity of common data sources used to characterize the food environment is limited. The marked undercount of food outlets and the geospatial inaccuracies observed have the potential to introduce bias into studies evaluating the impact of the built food environment.

BackgroundIn many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods.Main textWe review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees.ConclusionsDecision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12982-017-0064-4) contains supplementary material, which is available to authorized users.

This trial did not demonstrate a significant effect of STYH participation on change in mean minutes of MVPA or mean BMI 12 months after classes ended, although there was a non-significant association with odds of reduction of BMI ( = 0.07). This study has implications for design of intervention studies in people with intellectual disability (ID).

Objective Commercial listings of food retail outlets are increasingly used by community members, food policy councils, and in multi-level intervention research to identify areas with limited access to healthier food. This study quantified the amount of count, type and geospatial error in two commercial data sources. Methods InfoUSA and Dun & Bradstreet (D&B) were compared to a validated field census and validity statistics calculated. Results Considering only completeness, D&B data undercounted 24% of existing supermarkets and grocery stores and InfoUSA 29%. Additionally, considering accuracy of outlet type assignment increased the undercount error to 42% and 39%, respectively. Marked overcount existed as well and only 43% of existing supermarkets were correctly identified with respect to presence, outlet type, and location. Conclusions and Implications Relying exclusively on secondary data to characterize the food environment will result in substantial error. While extensive data cleaning can offset some error, verification of outlets with a field census is still the method of choice.

BackgroundPurchases at small/non-traditional food stores tend to have poor nutritional quality, and have been associated with poor health outcomes, including increased obesity risk The purpose of this study was to examine whether customers who shop at small/non-traditional food stores with more health promoting features make healthier purchases.MethodsIn a cross-sectional design, data collectors assessed store features in a sample of 99 small and non-traditional food stores not participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in Minneapolis/St. Paul, MN in 2014. Customer intercept interviews (n = 594) collected purchase data from a bag check and demographics from a survey. Store measures included fruit/vegetable and whole grain availability, an overall Healthy Food Supply Score (HFSS), healthy food advertisements and in-store placement, and shelf space of key items. Customer nutritional measures were analyzed using Nutrient Databases System for Research (NDSR), and included the purchase of ≥1 serving of fruits/vegetables; ≥1 serving of whole grains; and overall Healthy Eating Index-2010 (HEI-2010) score for foods/beverages purchased. Associations between store and customer measures were estimated in multilevel linear and logistic regression models, controlling for customer characteristics and store type.ResultsFew customers purchased fruits and vegetables (8%) or whole grains (8%). In fully adjusted models, purchase HEI-2010 scores were associated with fruit/vegetable shelf space (p = 0.002) and the ratio of shelf space devoted to healthy vs. less healthy items (p = 0.0002). Offering ≥14 varieties of fruit/vegetables was associated with produce purchases (OR 3.9, 95% CI 1.2–12.3), as was having produce visible from the store entrance (OR 2.3 95% CI 1.0 to 5.8), but whole grain availability measures were not associated with whole grain purchases.ConclusionsStrategies addressing both customer demand and the availability of healthy food may be necessary to improve customer purchases.Trial registrationClinialTrials.gov: NCT02774330. Registered May 4, 2016 (retrospectively registered).Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-017-0531-x) contains supplementary material, which is available to authorized users.

Objective Fruit and vegetable intake (F&V) is influenced by behavioral and environmental factors, but these have rarely been assessed simultaneously. We aimed to quantify the relative influence of supermarket availability, perceptions of the food environment, and shopping behavior on F&V intake. Design A cross-sectional study. Setting Eight-counties in South Carolina, USA, with verified locations of all supermarkets. Subjects A telephone survey of 831 household food shoppers ascertained F&V intake with a 17-item screener, primary food store location, shopping frequency, perceptions of healthy food availability, and calculated GIS-based supermarket availability. Path analysis was conducted. We report standardized beta coefficients on paths significant at the 0.05 level. Results Frequency of grocery shopping at primary food store (β=0.11) was the only factor exerting an independent, statistically significant direct effect on F&V intake. Supermarket availability was significantly associated with distance to food store (β=-0.24) and shopping frequency (β=0.10). Increased supermarket availability was significantly and positively related to perceived healthy food availability in the neighborhood (β=0.18) and ease of shopping access (β=0.09). Collectively considering all model paths linked to perceived availability of healthy foods, this measure was the only other factor to have a significant total effect on F&V intake. Conclusions While the majority of literature to date has suggested an independent and important role of supermarket availability for F&V intake, our study found only indirect effects of supermarket availability and suggests that food shopping frequency and perceptions of healthy food availability are two integral components of a network of influences on F&V intake.

Background Snacking behaviors have been linked with higher energy intake and excess weight. However results have been inconsistent. Moreover, few data are available on the extent to which snacking affects diet quality. Objective This study describes snacking behaviors, including total snacking energy, frequency, time of day, and percentage of snacking energy intake by food groups, and their associations with diet quality and BMI. Design Snacking behaviors and dietary intake were examined cross-sectionally among 233 adults participating in a community-based worksite nutrition intervention from September 2010–February 2013. Three telephone-administered 24-hour dietary recalls were collected (two weekday; one weekend day). Diet quality was characterized by the Healthy Eating Index (HEI)-2010 and BMI was computed using measured height and weight. Setting The setting was a large metropolitan medical complex in Minneapolis, Minnesota. Main outcome measures Outcome measures included diet quality and BMI. Statistical analyses General linear regression models were used to examine associations between each of the snacking behaviors as independent variables, and diet quality and BMI as dependent variables. Results Percent of snacking energy from fruit & juice (β=0.13, P=0.001) and nuts (β=0.16, P=0.008) were significantly positively associated with diet quality. Percent of snacking energy from desserts and sweets (β=−0.16, P<0.001) and sugar-sweetened beverages (β=−0.22, P=0.024) were significantly inversely associated. Percent of snacking energy from vegetables (β=−0.18, P=0.044) was significantly associated with lower BMI. Percent snacking energy from desserts and sweets was significantly associated with a higher BMI (β=0.04, P=0.017). Conclusions Snack food choices, but not total energy from snacks, frequency or time of day, were significantly associated with diet quality and BMI.

The primary purpose of this study was to examine differences among youth with avoidant/restrictive food intake disorder (ARFID) by age, weight status, and symptom duration. A secondary goal was to report the frequencies of ARFID using DSM-5 clinical presentations (i.e., fear of aversive consequences, lack of interest in food, sensory sensitivities). Participants (N = 102), ages 8–18 years, were recruited through an eating disorder service within a pediatric hospital. They were evaluated using semi-structured interviews and questionnaires. Patients were assigned to groups according to age, weight status, and symptom duration. Frequencies of clinical presentations, including combinations of DSM-5 categories, were also examined. Our findings suggest that adolescents presented with higher rates of Depression (p = 0.04). Youth with chronic ARFID symptoms presented with significantly lower weight (p = 0.03), and those with acute symptoms rated significantly higher suicidal ideation and/or self- harm (p = 0.02). Half of patients met criteria for more than one ARFID symptom presentation. This study provides preliminary evidence that youth with ARFID differ in clinical presentation depending on age, weight status, and symptom duration, and highlights safety concerns for those with acute symptoms of ARFID. High rates of overlapping symptom presentations might suggest a dimensional approach in the conceptualization of ARFID.