Faculty Bibliography

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.

Objective/UNASSIGNED:COVID-19 has changed diet and food shopping behaviors, but a lack of disaggregated data by racial and ethnic subgroup makes it challenging to identify whether specific populations are experiencing greater challenges in safely securing an adequate food supply and engaging in healthy eating behaviors during the pandemic. Thus, the objective of this study was to measure such changes among Asian-American (AA) adults, overall and by ethnic subgroup. Methods/UNASSIGNED:Using a nationally derived nonprobability sample, 3084 AA adults were recruited, including 1737 East Asian, 570 South Asian, 587 Southeast Asian, and 124 multiethnic Asian adults. Participants completed an online survey with questions related to sociodemographics, health status, and diet and food shopping behaviors, including questions related to COVID-19. Logistic and linear regression were used to compare differences in survey responses by Asian ethnic subgroup. Results/UNASSIGNED:Compared to other AA subgroups, a higher percentage of Asian Indian (17%), Filipino (13%), Vietnamese (12%), and Korean (11%) adults reported no longer getting food resources they were receiving before COVID-19 (e.g., mobile meals, food pantry items). The percentage of Filipino (8%) and Vietnamese (7%) adults who reported not having enough money to buy food they need was also higher than other AA subgroups. And a higher percentage of Asian Indian adults (7%) reported not having a way to get to the food store since COVID-19 than other AA subgroups. Conclusions/UNASSIGNED:Previous work has not included disaggregated data, which may mask important disparities in food access and food insecurity among people hit hardest by COVID-19, such as Filipino, Vietnamese, and Asian Indian households.

PURPOSE/OBJECTIVE:To examine how the choice of neighborhood food environment definition impacts the association with diet. METHODS:) 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<0.001). 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.

Simulated online grocery store platforms are innovative tools for studying nutrition-related policies and point-of-selection/point-of-purchase interventions in online retail settings, yet there is no clear guidance on how to develop these platforms for experimental research. Thus, we created a standardized guide for the development of an online grocery store, including a detailed description of (1) methods for acquiring and cleaning online grocery store data, and (2) how to design a two-dimensional online grocery store experimental platform. We provide guidance on how to address product categorization, product order/sorting and product details, including how to identify outliers and conflicting nutritional information and methods for standardizing prices. We also provide details regarding our process of "tagging" food items that can be leveraged by future studies examining policies and point-of-selection/point-of-purchase interventions targeting red and processed meat and fruits and vegetables. We experienced several challenges, including obtaining accurate and up-to-date product information and images, and accounting for the presence of store-brand products. Regardless, the methodology described herein will enable researchers to examine the effects of a wide array of nutrition-related policies and interventions on food purchasing behaviors in online retail settings, and can be used as a template for reporting procedures in future research.

BACKGROUND:Offering financial incentives promotes increases in fruit and vegetable purchases in farmers' markets and supermarkets. Yet, little is understood about whether food-insecure adults purchase more fruits and vegetables as a result of receiving financial incentives in mobile produce market settings. METHODS:In 2018-2019, Food on the Move provided a 50% discount to customers using Supplemental Nutrition Assistance Program (SNAP) benefits to purchase fruit and vegetables from 16 market locations in Rhode Island (n = 412 market occasions). We used mixed multivariable linear regression to estimate the difference in total dollar sales per transaction per month between SNAP transactions and non-SNAP transactions. We also estimated the difference in out-of-pocket dollar sales per transaction per month between SNAP and non-SNAP transactions, less the 50% discount. This reflects the actual amount spent on fresh fruits and vegetables purchased per visit. In both models, we controlled for the number of market sites per month, with fixed effects for quarter and year. We estimated random intercept variance for date of transaction and market site to adjust for clustering. RESULTS:In 2018-2019, the majority of market transactions (total n = 13,165) were SNAP transactions [n = 7.988 (63.0%)]. On average, customers spent $17.38 (SD = 16.69) on fruits and vegetables per transaction per month. However, customers using SNAP benefits spent significantly more on FVs per transaction per month [$22.01 (SD = 17.97)] compared to those who did not use SNAP benefits [9.81 (SD = 10.68)] (β = $10.88; 95% CI: 10.18, 11.58). Similarly, out-of-pocket dollar sales per SNAP transaction per month (i.e., less the 50% discount) were significantly higher [$11.42 (SD = 9.44)] relative to non-SNAP transactions [$9.40 (SD = 9.33)] (β = $1.85; 95% CI: 1.44, 2.27). CONCLUSIONS:Financial incentives contributed to higher fruit and vegetable purchases among low-income customers who shop at mobile produce markets by making produce more affordable. Higher spending on fruits and vegetables may promote healthy diet behaviors and reduce chronic disease risk among food-insecure adults.