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Background: Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. Objective: This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. Methods: Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003–2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. Results: Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was − 0.004 (SD = 2.5; min = − 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. Conclusions: The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options. [ABSTRACT FROM AUTHOR]

Purpose: To examine how the choice of neighborhood food environment definition impacts the association with diet.Methods: Using food frequency questionnaire data from the Reasons for Geographic and Racial Differences in Stroke study at baseline (2003-2007), we calculated participants' dietary inflammation score (DIS) (n = 20,331); higher scores indicate greater pro-inflammatory exposure. We characterized availability of supermarkets and fast food restaurants using several geospatial measures, including density (i.e., counts/km2) and relative measures (i.e., percentage of all food stores or restaurants); and various buffer distances, including administrative units (census tract) and empirically derived buffers ("classic" network, "sausage" network) tailored to community type (higher density urban, lower density urban, suburban/small town, rural). Using generalized estimating equations, we estimated the association between each geospatial measure and DIS, controlling for individual- and neighborhood-level sociodemographics.Results: The choice of buffer-based measure did not change the direction or magnitude of associations with DIS. Effect estimates derived from administrative units were smaller than those derived from tailored empirically derived buffer measures. Substantively, a 10% increase in the percentage of fast food restaurants using a "classic" network buffer was associated with a 6.3 (SE = 1.17) point higher DIS (P< .001). The relationship between the percentage of supermarkets and DIS, however, was null. We observed high correlation coefficients between buffer-based density measures of supermarkets and fast food restaurants (r = 0.73-0.83), which made it difficult to estimate independent associations by food outlet type.Conclusions: Researchers should tailor buffer-based measures to community type in future studies, and carefully consider the theoretical and statistical implications for choosing relative (vs. absolute) measures. [ABSTRACT FROM AUTHOR]

Males are more likely to be diagnosed with autism than females, and at earlier ages, yet few studies examine sex differences in screening. This study explored sex differences in psychometric properties, recommended cutoff scores, and overall scores of the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up. Participants were 28,088 toddlers enrolled in four early detection of autism studies. Children (N = 731) at high likelihood for autism attended evaluations after screening and/or primary care clinician concern. Females were less likely to screen at high likelihood for autism at each stage of screening and therefore less likely to be invited for evaluations. Positive predictive value was significantly lower among females than males, but sensitivity was similar. False positive females were likely to have another developmental delay. Cutoff scores for males and females matched recommended guidelines. Final scores on the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up did not differ between males and females diagnosed with autism, but did for the overall sample identified at high likelihood for autism. Our findings suggest that females are less likely to be referred for evaluations, but the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up accurately identifies both males and females with autism at established cutoffs. Future research should examine methods to reduce false positive in females. This study examined a widely used autism screening tool, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up to identify differences in screening for autism between toddler males and females. Examining sex differences in screening for autism in toddlerhood is important as it determines who will be referred for evaluations and receive diagnoses, which is critical for access to autism-specific early intervention. This study found that females were less likely to screen positive and be invited for evaluations compared with males. Females at high likelihood for autism were less likely to be diagnosed with autism, which decreases confidence in the screener's results. Importantly, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up accurately identified both males and females with autism. Future research should examine ways to improve accuracy in screening results for females. [ABSTRACT FROM AUTHOR]

Area-level neighborhood socioeconomic status (NSES) is often measured without consideration of spatial autocorrelation and variation. In this paper, we compared a non-spatial NSES measure to a spatial NSES measure for counties in the USA using principal component analysis and geographically weighted principal component analysis (GWPCA), respectively. We assessed spatial variation in the loadings using a Monte Carlo randomization test. The results indicated that there was statistically significant variation (p = 0.004) in the loadings of the spatial index. The variability of the census variables explained by the spatial index ranged from 60 to 90%. We found that the first geographically weighted principal component explained the most variability in the census variables in counties in the Northeast and the West, and the least variability in counties in the Midwest. We also tested the two measures by assessing the associations with county-level diabetes prevalence using data from the CDC's US Diabetes Surveillance System. While associations of the two NSES measures with diabetes did not differ for this application, the descriptive results suggest that it might be important to consider a spatial index over a global index when constructing national county measures of NSES. The spatial approach may be useful in identifying what factors drive the socioeconomic status of a county and how they vary across counties. Furthermore, we offer suggestions on how a GWPCA–based NSES index may be replicated for smaller geographic scopes. [ABSTRACT FROM AUTHOR]

Objective: We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D).Research Design and Methods: As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural.Results: Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways.Conclusions: Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways. [ABSTRACT FROM AUTHOR]