Faculty Bibliography

During the COVID-19 pandemic in 2020, the Supplemental Nutrition Assistance Program (SNAP) Online Purchasing Pilot (OPP) was rapidly expanded across the US. This program, enabling direct-to-home grocery delivery, could be a transformative step towards improving fresh-food access. However, lack of information on which areas are serviced by SNAP OPP hinders the identification of potential demographic and regional disparities in access. Lessons from the initial implementation period are critical for understanding continuing inequities and informing the implementation of future programs. In California, SNAP OPP expanded food access for 85.9% of the state's SNAP households in 2020-21. Coverage was significantly greater in urban areas, covering 87.2% of CalFresh households in urban limited food access areas as compared with 29.9% of CalFresh households in rural limited food access areas. County-level COVID-19 rates did not have a meaningful association with SNAP OPP coverage.

BACKGROUND:There are persistent disparities in weight- and diet-related diseases by sexual orientation. Lesbian and bisexual females have a higher risk of obesity and cardiovascular disease compared to heterosexual females. Gay and bisexual males have a higher risk of diabetes and cardiovascular disease compared to heterosexual males. However, it remains unknown how sexual orientation groups differ in their dietary quality. OBJECTIVE:This study aimed to determine whether dietary quality differs by sexual orientation and sex among US adults. DESIGN/METHODS:This was a cross-sectional study of 24-h dietary recall data from a nationally representative sample of adults aged 20-65 participating in the 2011-2016 National Health and Nutrition Examination Survey (NHANES). PARTICIPANTS/SETTING/METHODS:Study participants were adults (n=8,851) with complete information on dietary intake, sexual orientation, and sex. MAIN OUTCOME MEASURES/METHODS:The main outcome measures were daily energy intake from 20 specific food and beverage groups and Healthy Eating Index-2015 (HEI-2015) scores for sexual orientation groups (heterosexual vs. gay/lesbian/bisexual (GLB)). STATISTICAL ANALYSES PERFORMED/METHODS:Ordinary least squares regressions were used to calculate adjusted means for each food and beverage group and HEI-2015, stratified by sex and controlling for covariates (e.g., age, race/ethnicity) and survey cycles (2011-2012; 2013-2014; 2015-2016). RESULTS:Among males, red and processed meat/poultry/seafood (p=0.01) and sandwiches (p=0.02) were smaller contributors to energy intake for gay/bisexual males compared to heterosexual males. Among females, cereals (p=0.04) and mixed dishes (p=0.02) were smaller contributors to energy intake for lesbian/bisexual females compared to heterosexual females. Gay/bisexual males had significantly higher total HEI-2015 scores than heterosexual males (53.40 ± 1.36 vs. 49.29 ± 0.32, difference=4.14, p=0.004). Lesbian/bisexual females did not differ in total or component HEI-2015 scores from heterosexual females. CONCLUSIONS:While GLB groups were similar for a variety of dietary outcomes compared to heterosexual groups, gay and bisexual males displayed healthier dietary quality for processed meat (by consuming smaller amounts) and overall dietary quality (according to HEI-2015) compared to heterosexual males.

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/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.

BACKGROUND:Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent. OBJECTIVE:To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment. METHODS:The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum. RESULTS:In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001). CONCLUSION/CONCLUSIONS:Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

INTRODUCTION/BACKGROUND:Little is known on the independent effects of generational status and acculturation on the consumption of specific foods among disaggregated Asian American (AA) populations. This study explores the associations of generational status and acculturation with dietary behaviors of a nationwide non-probability sample of 3018 AAs (57.6% East Asian American (EAA), 18.9% South Asian American (SAA), 19.4% Southeast Asian American (SEAA)). METHODS:Recruited participants completed an online dietary survey designed and adapted for AAs to assess a range of diet and food purchasing behaviors. Generational status was assessed through participant and parental country of birth (1st-Gen, 2nd-Gen, 3rd-Gen); the Marin Short Acculturation Scale was adapted to measure acculturation. Linear regression models assessed the association of generational status and acculturation with consumption of 11 food/nutrient groups, adjusted for socio-economic variables. RESULTS:Compared to estimated US averages, participants reported lower fruit, dairy, and seafood intake yet lower red and processed meat, and higher whole grain, calcium, and fiber intake. Compared to EAA, SAA reported higher dairy (1.72 vs. 1.46 cups/day) and calcium (1029 vs. 954 mg/day) intakes, while SEAA reported lower vegetable intake (1.66 vs. 1.78 cups/day). In adjusted analyses, processed meat intake was higher among 2nd-Gen and 3rd-Gen vs.1st-Gen (+0.029 times/day; +0.061 times/day) participants. Higher acculturation was associated with lower vegetable, fiber, and seafood intake (-0.005 cups/day; -0.02 g/day; -0.002 times/day). CONCLUSION/CONCLUSIONS:Greater attention to the role of generational status and acculturation in AA dietary behaviors is needed, and findings call for further research to understand the mechanisms behind the dietary influence of different socialization and acculturative processes.

Objective/UNASSIGNED:To describe the variability in the availability and price of sugary drinks, low-calorie drinks, and water/seltzer across high- and low-poverty census tracts in the five boroughs of New York City (NYC). Design/UNASSIGNED:Cross-sectional study. Our primary analysis compared the overall sample of beverages. Secondary analyses included tests for differences in the availability of beverage categories by neighborhood poverty level. Setting/UNASSIGNED:We collected data from 106 stores (31 supermarkets, 29 convenience stores, 29 pharmacies, 9 Targets, and 8 Dollar Trees) in NYC. Fifty-four stores were located in high-poverty census tracts and 52 were located in low-poverty census tracts. Results/UNASSIGNED:=0.01). Conclusions/UNASSIGNED:Sugary drinks were available in most food retail settings in NYC, with little variation by census tract poverty level. Interventions that raise the price of sugary drinks to make healthier alternatives, such as water, the more affordable option should be considered.

Existing classifications of community type do not differentiate urban cores from surrounding non-rural areas, an important distinction for analyses of community features and their impact on health. Inappropriately classified community types can introduce serious methodologic flaws in epidemiologic studies and invalid inferences from findings. To address this, we evaluate a modification of the United States Department of Agriculture's Rural Urban Commuting Area codes at the census tract, propose a four-level categorization of community type, and compare this with existing classifications for epidemiologic analyses. Compared to existing classifications, our method resulted in clearer geographic delineations of community types within urban areas.

There is a lack of quantitative research examining how the pandemic has affected individuals at different income levels. The Asian American population has the highest level of income inequality and serves as an excellent case study for examining differences in experience between income groups. A non-probability sample of 3084 Asian American adults living in the US was surveyed in June 2020, examining health-related behaviors and outcomes. Descriptive analyses and chi-squared statistics were conducted to identify differences in income groups (low, medium, high) among Asian Americans across regional subgroups (East, South, Southeast, Multiethnic) and disaggregated ethnicities (Chinese, Asian Indian, Japanese, and Filipino). In bivariable analyses, a significantly (p < 0.05) greater percentage of high-income individuals during the pandemic reported having enough money to buy the food they needed, a away to get to the store for food, and reported stores where they get food had everything they needed. High-income Chinese, Japanese, and Filipino individual also noted that, since the COVID-19 crisis, they are now working partially or fully from home. In the total sample, multivariable adjusted logistic regressions revealed medium- and low-income individuals to have low odds of working partially or fully from home (AOR:0.55, 95%CI:0.42-0.72), higher odds of not having enough money to buy the food they needed (AOR:3.54, 95%CI:1.43-11.81), and higher odds of eating less (AOR:1.58, 95%CI:1.14-2.22). These results highlight the importance of considering income distribution when characterizing disparities in health behaviors within racial/ethnic minority groups and underscore the need to bolster the infrastructure supporting low-income Asian Americans.

Importance/UNASSIGNED:Diabetes causes substantial morbidity and mortality among adults in the US, yet its incidence varies across the country, suggesting that neighborhood factors are associated with geographical disparities in diabetes. Objective/UNASSIGNED:To examine the association between neighborhood food environment and risk of incident type 2 diabetes across different community types (high-density urban, low-density urban, suburban, and rural). Design, Setting, and Participants/UNASSIGNED:This is a national cohort study of 4 100 650 US veterans without type 2 diabetes. Participants entered the cohort between 2008 and 2016 and were followed up through 2018. The median (IQR) duration of follow-up was 5.5 (2.6-9.8) person-years. Data were obtained from Veterans Affairs electronic health records. Incident type 2 diabetes was defined as 2 encounters with type 2 diabetes International Classification of Diseases, Ninth Revision or Tenth Revision codes, a prescription for diabetes medication other than metformin or acarbose alone, or 1 encounter with type 2 diabetes International Classification of Diseases Ninth Revision or Tenth Revision codes and 2 instances of elevated hemoglobin A1c (≥6.5%). Data analysis was performed from October 2020 to March 2021. Exposures/UNASSIGNED:Five-year mean counts of fast-food restaurants and supermarkets relative to other food outlets at baseline were used to generate neighborhood food environment measures. The association between food environment and time to incident diabetes was examined using piecewise exponential models with 2-year interval of person-time and county-level random effects stratifying by community types. Results/UNASSIGNED:The mean (SD) age of cohort participants was 59.4 (17.2) years. Most of the participants were non-Hispanic White (2 783 756 participants [76.3%]) and male (3 779 555 participants [92.2%]). The relative density of fast-food restaurants was positively associated with a modestly increased risk of type 2 diabetes in all community types. The adjusted hazard ratio (aHR) was 1.01 (95% CI, 1.00-1.02) in high-density urban communities, 1.01 (95% CI, 1.01-1.01) in low-density urban communities, 1.02 (95% CI, 1.01-1.03) in suburban communities, and 1.01 (95% CI, 1.01-1.02) in rural communities. The relative density of supermarkets was associated with lower type 2 diabetes risk only in suburban (aHR, 0.97; 95% CI, 0.96-0.99) and rural (aHR, 0.99; 95% CI, 0.98-0.99) communities. Conclusions and Relevance/UNASSIGNED:These findings suggest that neighborhood food environment measures are associated with type 2 diabetes among US veterans in multiple community types and that food environments are potential avenues for action to address the burden of diabetes. Tailored interventions targeting the availability of supermarkets may be associated with reduced diabetes risk, particularly in suburban and rural communities, whereas restrictions on fast-food restaurants may help in all community types.

No brief dietary screeners are available that capture dietary consumption patterns of Asian Americans. The purpose of this article is to describe the cultural adaptation of the validated Dietary Screener Questionnaire (DSQ) for use by clinicians, researchers, and community-based partners seeking to understand and intervene on dietary behaviors among English-speaking Asian Americans, for the six largest Asian subgroups (Chinese, Filipino, Asian Indian, Vietnamese, Korean, Japanese) in the United States. This was mainly accomplished by adding culturally specific examples of foods to the questionnaire items via searching online databases and soliciting input from members of our community partner network representing each of the six largest Asian subgroups. Over half of the 26 items on the DSQ were modified to include more culturally specific foods. Developing high-quality tools that reflect the diversity of the U.S. population are critical to implement nutrition interventions that do not inadvertently widen health disparities.