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Determine the association between socioeconomic status and self-reported noticing and using calorie menu labels in 2 states with high poverty and obesity.Cross-sectional study of responses to the 2016 Behavioral Risk Factor Surveillance System Menu Labeling Module.Representative sample of noninstitutionalized adults aged ≥ 18 years in West Virginia and Mississippi (n = 9,469).The outcomes were reported noticing and using menu labels to make decisions at fast-food restaurants. Independent variables were highest attained education and federal poverty level (% FPL).Generalized linear models estimated prevalence ratios for noticing and using menu labels. Models mutually adjusted for education, % FPL, age, sex, race/ethnicity, and body mass index.Eighty-six percent of respondents reported noticing, and 56% reported using menu labels. Compared with individuals with less than high school education, college graduates were 11% more likely to report noticing (95% confidence interval, 1.06-1.18; P0.001) and 18% more likely to report using (95% confidence interval, 1.06-1.30; P0.01) menu labels. Patterns were similar for % FPL.These data support further investigation of menu labels among subgroups and a larger geographic scope. Limitations of the menu labeling module question and the cross-sectional nature of the existing literature warrant additional research.

Background Complete Eats Rx is a fruit and vegetable prescription program designed to incentivize fruit and vegetable consumption among Supplemental Nutrition Assistance Program (SNAP) participants via $10 incentives distributed either weekly or per encounter to purchase fruits and vegetables at a mid-price supermarket chain in Washington State. Objective To better understand SNAP participants’ experience, and to determine perceived impacts and consequences of the program. Design Qualitative analysis of nine photovoice sessions. Participants chose the topics for discussion. Sessions were audiorecorded and transcribed. Thematic content analysis was performed to identify key emergent themes using Atlas.ti. Setting Spokane, Seattle, and Yakima, Washington. Participants Twenty-six individuals who received a fruit and vegetable prescription within the past 6 months, 23 of whom attended all three photovoice sessions offered at their site. Participants were recruited from three participating health care or public health organizations in Spokane, Seattle, and Yakima, Washington. Analysis Transcriptions were coded using inductive methods. Coded statements were organized into major themes. Coding structures and analysis were strengthened by iterative interactions between researchers. Results Participants reported Complete Eats Rx was an important resource for families and improved food security, diet quality, and the ability to purchase healthy foods, including a greater variety of fruits and vegetables. Primary barriers to food security and fruit and vegetable consumption included limited geographic accessibility and the high cost of fruits and vegetables, exacerbated by other financial constraints such as rising housing costs. Participants reported supermarket checkout difficulty because of embarrassment, stigmatization, and inability to redeem incentives. The most frequently mentioned barrier to perceived program acceptability was having only one supermarket chain as the acceptor of the incentive. Conclusion Partnering with supermarkets to accept fruit and vegetable incentives is a unique strategy to increase produce purchasing that can be adopted by other localities. Focus on geographic accessibility, appropriate price points, and positive shopping experiences via expansion to local grocers, improvements in staff interactions, and a transition to an electronic system may improve incentive redemption and usability.

BACKGROUND: High obesity rates among young black and Hispanic children place them at a higher risk for adult obesity and its co-morbidities. Neighborhoods with predominately racial and ethnic minority residents have fewer healthful food options, which may contribute to obesity disparities. Yet few studies have assessed the relationship between neighborhood food environments and obesity in this population. METHODS: Electronic health records from two pediatric primary care clinics serving predominately low-income, black and Hispanic children were used to create a cohort of 3,724 2-5 year-olds, encompassing 7,256 visits from 2007 to 2012 (mean 1.9 visits per patient, range: 1-5 visits per child). Longitudinal regression was used to model the association of mean body mass index z-score (BMI-z) over time and 3 measures of the neighborhood food environment: healthful food availability, availability of stores accepting the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) benefits, and fast food availability. RESULTS: Compared to peers in neighborhoods with no or few stores accepting WIC, children in neighborhoods with many WIC stores had higher BMI-z at age 2 years (average difference of 0.272 95% CI 0.041 – 0.503; p=0.021). No relationship was found for healthful food or fast food availability. Although children in neighborhoods with low fast food availability did not have statistically significantly different BMI-z at age 2 as compared to children in areas with high fast food availability, they did have a statistically significantly higher change in average BMI-z over time (0.006 per month, 0.000 – 0.012, p=0.024). CONCLUSIONS: Access to WIC stores was associated with lower obesity rates and more healthful average BMI-z over time and represents a potentially important neighborhood food environment characteristic influencing racial/ethnic disparities in childhood obesity among young black and Hispanic children. More studies are needed to assess what aspects of WIC stores may underlie the observed association. WHAT’S NEW: Access to WIC stores represents a potentially important neighborhood food environment characteristic influencing racial and ethnic disparities in childhood obesity among young black and Hispanic children.

It is important to understand whether the publics' attitudes towards sugary beverage taxes (SBT) change after tax implementation to ensure the long-term success of tax policies. Seattle's SBT went into effect on January 1, 2018. We administered a mixed-mode survey to adults in Seattle and comparison areas, pre- and 2-years post-tax, to evaluate the impact of the SBT on 1) tax support and 2) perceived tax impacts (N = 2,933). Using a difference-in-differences approach, we employed adjusted income-stratified modified Poisson models to test the impacts of the tax on net changes in attitudes in Seattle versus the comparison areas, pre- to post-tax. Among lower-income individuals in Seattle, support for the tax increased by 14% (PR

This study explores the association between neighborhood social and economic change from 2009 to 2013 and changes in the retail food environment from 2013 to 2017 in Madrid (Spain). We classified neighborhoods into four types: decreasing SES, new housing/gentrifying, increasing SES, and aging (population and housing). Food store data was obtained from a retail spaces census and classified as supermarket, specialized small store, or fruit and vegetable store. Compared to aging areas, new housing/gentrifying and areas with increasing SES had a higher baseline presence and proportion of supermarkets and a lower proportion of specialized stores and fruit and vegetable stores. Areas with decreasing SES had an initially higher presence and proportion of fruit and vegetable stores but showed a declining trend in both presence and proportion of fruit and vegetable stores.

BACKGROUND The price of food has long been considered one of the major factors that affects food choices. However, the price metric (e.g., the price of food per calorie or the price of food per gram) that individuals predominantly use when making food choices is unclear. Understanding which price metric is used is especially important for studying individuals with severe budget constraints because food price then becomes even more important in food choice. OBJECTIVE We assessed which price metric is used by low-income individuals in deciding what to eat. METHODS With the use of data from NHANES and the USDA Food and Nutrient Database for Dietary Studies, we created an agent-based model that simulated an environment representing the US population, wherein individuals were modeled as agents with a specific weight, age, and income. In our model, agents made dietary food choices while meeting their budget limits with the use of 1 of 3 different metrics for decision making: energy cost (price per calorie), unit price (price per gram), and serving price (price per serving). The food consumption patterns generated by our model were compared to 3 independent data sets. RESULTS The food choice behaviors observed in 2 of the data sets were found to be closest to the simulated dietary patterns generated by the price per calorie metric. The behaviors observed in the third data set were equidistant from the patterns generated by price per calorie and price per serving metrics, whereas results generated by the price per gram metric were further away. CONCLUSIONS Our simulations suggest that dietary food choice based on price per calorie best matches actual consumption patterns and may therefore be the most salient price metric for low-income populations.

Highlights • We investigate household SES, neighborhood SES and childhood obesity. • Sample was nationally representative of US first graders in 2011. • Both SES variables–household and neighborhood SES–were associated with obesity. • No evidence of greater prevalence of obesity due to low SES on both dimensions. • In low SES neighborhoods, high household SES did not mitigate obesity prevalence. • In low SES households, high neighborhood SES did not mitigate obesity prevalence., Both low family socioeconomic status (SES) and low neighborhood SES have been associated with higher levels of childhood obesity. However, little is known about how these two factors operate together. The purpose of this study was to determine if the association between neighborhood SES and obesity varies across household SES. We used the first-grade round of the Early Childhood Longitudinal Study, Kindergarten Class of 2011 (ECLS-K:2011). Household SES was defined based on income, education, and occupation. Neighborhood SES was defined by the percent of households living in poverty in the child’s school district. Log-binomial regression models estimated the association between neighborhood SES and obesity and tested whether this association varied by household SES. We found the association between neighborhood SES and obesity varied significantly by household SES (p-interaction = 0.002). For children in the lowest tertile of neighborhood SES, prevalence of obesity was not statistically significantly different comparing children with low, middle or high household SES (Predicted probability (PP)lowest 0.20 (95% CI: 0.17, 0.23), PPmiddle 0.21 (95%CI: 0.18, 0.24), PPhighest 0.16 (95%CI: 0.12, 0.20)). Conversely, within the highest and the middle tertiles of neighborhood SES, children with high household SES have significantly lower prevalence of obesity compared to children with the lowest household SES (PP: 0.09 (95%CI: 0.07, 0.11) vs 0.19 (0.16, 0.21) and (PP: 0.07 (95%CI: 0.05, 0.09) vs 0.17 (0.13, 0.21) for highest vs lowest household SES in middle and high neighborhood SES, respectively). Hence, low-SES in either variable is enough to be associated with increased prevalence of obesity.

OBJECTIVES: Examine the relationship between household food insecurity (HFS; i.e., access to nutritionally adequate and safe food) and disordered eating behaviors (i.e., restriction, bingeing, insulin manipulation, etc.) among a sample of young adults with youth-onset type 1 (T1D) or type 2 diabetes (T2D). METHODS: We used cross-sectional data from the SEARCH for Diabetes in Youth Study. Individuals (n = 792) ages ≥18 years completed the U.S. Household Food Security Survey Module and the Diabetes Eating Problem Survey-Revised (DEPS-R) between 2016 and 2019. We converted HFS scores to a 10-point scale and dichotomized scores into food secure (HFS ≤ 2.2) vs. food insecure (HFS > 2.2). Multivariable linear regression was used to evaluate the association of HFS with continuous DEPS-R score (i.e., 0–80, with a greater score indicating greater symptoms of disordered eating), adjusting for potential confounders (i.e., sex, age, race/ethnicity, education, household income, insurance, depressive symptoms, and duration of diabetes). We further stratified analyses by diabetes type. RESULTS: Participants were on average 23.8 ± 3.7 years, 59.6% female, 49.6% non-Latino white, and had a mean diabetes duration of 11.5 ± 3.1 years. The overall mean DEPS-R score was 17.3 ± 10.0 points. Mean DEPS-R scores in individuals living in food secure households (n = 709) and food insecure households (n = 83) were 16.6 ± 9.45 and 23.4 ± 12.4, respectively. The adjusted DEPS-R scores were 3.6 points (95% CI = 1.5, 5.7; P 0.05). CONCLUSIONS: Lower household food security in young adults with T1D, but not T2D, is associated with increased disordered eating scores. These results may allow clinicians and other public health professionals to target individuals with low household food security as being at higher risk for potential disordered eating, particularly those with T1D. FUNDING SOURCES: NIDDK & CDC.

National Heart, Lung, and Blood Institute Kruse Family Publications Award Background: There has been limited research regarding the Supplemental Nutritional Assistance Program (SNAP) and recipients' dietary quality during the days and weeks after benefit disbursement.Objective: We examined the relation between participants' stages in the SNAP cycle and their macronutrient consumption, Healthy Eating Index (HE!) scores, and fruit and vegetable intake.Design: in this cross-sectional study, we analyzed single 24-h dietary recalls collected from 244 African American SNAP participants recruited near 24 corner stores in Baltimore City. A multiple linear regression analysis and bootstrapping were used.Results: Among participants who received a SNAP benefit 15 d before being surveyed, energy intake (1.35%; 95% CI: 0.01%, 2.73%), energy intake adjusted for minimum energy requirements (3.86%; 95% CI: 0.06%. 7.96%), total fat intake (1.96%; 95% CI: 0.29%, 3.8%), saturated fat intake (2.02%; 95% Cl: 0.23%, 4.01%), and protein intake (2.09%; 95% Cl: 0.70%, 3.62%) were higher per each 1-d increase in the TSSD.Conclusions: These findings suggest that the relation between the TSSD and macronutrient intake might be U-shaped, with higher intake of calories, fat, and protein in individuals in the very early and late stages of their SNAP cycles. Foods high in these nutrients might be cheaper, more accessible, and have a longer shelf-life than healthier options, such as fruit, vegetables, and whole grains, for SNAP participants when their benefits run out. Additional efforts are needed to investigate the effect of the TSSD on dietary intake by using a longitudinal design and to improve the quality of dietary intake in African American SNAP participants. Johns Hopkins Sch Publ Health, Dept Int Hlth, Baltimore, MD USA Johns Hopkins Sch Publ Health, Dept Hlth Behav & Soc, Baltimore, MD USA Universidade Federal de São Paulo, Dept Hlth Sci, São Paulo, Brazil Universidade Federal de São Paulo, Dept Hlth Sci, São Paulo, Brazil National Heart, Lung, and Blood Institute: 1R21HL102812-01A1 Web of Science

OBJECTIVES: To assess the relationship between maternal employment and children's dietary diversity in rural Guatemala. METHODS: A mixed-method design was used to compare quantitative findings on children's dietary diversity collected from Food Frequency Questionnaires (FFQs) (n = 802), with qualitative data from in-depth interviews (IDIs) with a sub-sample of participants (n = 20). Mothers reported the number of times per week their child consumed select food items from seven food groups (grains, legumes, vitamin A-rich fruits & vegetables, other fruits & vegetables, eggs, dairy and meat). The total for each food item was then divided by seven to find the number of times the child consumed each food per day. Then, the daily consumption of all food items within a category was totaled for each food group. If the total for the food group was at least one, the child was given one point for daily consumption, with a maximum dietary diversity score (DDS) of seven. Using multivariate linear regression, we compared the DDS of children of employed mothers to the DDS of children of unemployed mothers. We used separate multivariate logistic regression models to estimate the association between maternal employment and consumption of each food group. Models were adjusted for maternal (age, education, marital status, parity), child (age, sex), and household (size) characteristics. IDIs explored the mechanisms by which food purchasing and preparation, as well as child-feeding behavior differed for employed and unemployed women. RESULTS: Maternal employment (versus unemployment) was associated with higher dietary diversity scores for children (β = 0.3; 95% CI: 0.06,0.54). The odds of consuming each food group did not differ significantly between children of employed and unemployed women, except for dairy (OR: 1.9, 95% CI: 1.0, 2.6), but the general trend suggested children of employed women were more likely to consume six of the seven food groups. Qualitative data indicates that employed women purchase higher quality and greater quantities of food. CONCLUSIONS: Maternal employment is associated with higher children's dietary diversity scores in rural Guatemala. Quantitative and qualitative data suggests that maternal employment is related to food purchasing behavior. FUNDING SOURCES: Mathile Institute & Global Obesity Prevention Center at Johns Hopkins Bloomberg School of Public Health.

The classification of places as either urban or rural is typically based on an absolute threshold of population and/or population density. However, conceptual definitions of urbanization and urbanicity encompass dimensions beyond solely population size and population density. Multiple important distinguishing urban characteristics beyond population size have been described. The crude classification of places as urban or rural coupled with infrequent updates to this information creates a measure that is prone to misclassification error. An improved measure of urbanicity would draw information from the domains that characterize urban and rural places, would be sensitive to changes over time, and would represent gradations on the continuum from rural to urban environments. The goal of the current study was to develop such a scale from existing data, test whether the scale was reliable and valid, and assess whether it provided information beyond what could be determined from the traditional urban/rural dichotomous variable. We utilized established scaling procedures from the psychometric literature to construct and evaluate a multicomponent scale to measure urban features on a continuum in China. We also provided an example of its potential contribution to health research by examining its relationship with the adult body mass index (BMI). Because the scale was constructed and tested using established scaling procedures and using a wide array of variables, it represents an improvement over previous attempts at such a scale and will provide a reliable and valid measurement tool for researchers in this arena. We demonstrate that the scale predicts the incidence of overweight/obesity populations in China, but it promises to be most useful for other economic, demographic, social welfare, and health outcomes.