Faculty Bibliography

Though food insecurity has long been recognised to impact health, population-specific determinants of food insecurity have recently been studied systematically as an important public health concern. Indeed, while immigrant populations face particular challenges to equitable access to the food system, many of these concerns have not been systematically described. To this end, we critically review recent work that demonstrates the importance of transportation and language access as independent determinants of access to food for immigrant populations. Furthermore, we highlight proposals to mitigate barriers to access, including both academic and community-driven approaches to create overlapping institutional commitments for inclusive policymaking that meets the specific needs of diverse populations.

OBJECTIVE:To assess the criterion validity of a dietary screener questionnaire adapted for Asian Americans (ADSQ) compared to Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA-24) food diary data amongst Chinese American Adults (CHAs). The ADSQ incorporated example ethnic foods from six Asian American groups. Lessons learned with respect to translating the ADSQ from English into Simplified Chinese were also documented. DESIGN/METHODS:Agreement between a two-day food diary (one weekend day and one weekday) and the ADSQ was assessed for vegetable, fruit, dairy, added sugar, fiber, calcium, and whole grain intake using paired t-tests to compare means and Spearman correlations to assess agreement between intake of food components. SETTING/METHODS:Data were collected online and via phone interviews. PARTICIPANTS/METHODS:Thirty-three CHAs aged 19-62 years (63.6% female). RESULTS:Mean differences were small for fruit, dairy, fiber, calcium, and whole grain intake, but were significantly different for vegetables and added sugar intake. Spearman correlations were < 0.5 and non-significant (p > 0.05) for all components. Both the ASA-24 and the ADSQ identified the same categories where CHAs intake is misaligned with dietary recommendations: whole grains, total fruit, and dairy. Difficulties were encountered in translating 13 out of 26 questions. CONCLUSIONS:The ADSQ may be a useful tool to identify intervention targets for improving dietary quality, but caution is warranted when interpreting vegetable and added sugar estimates. Differences in the English and Chinese languages underscore the need to take into account both literal translations and semantics in translating the ADSQ into other languages.

BACKGROUND:Emerging evidence suggests the potential mediating role of microbiome in health disparities. However, no analytic framework can be directly used to analyze microbiome as a mediator between health disparity and clinical outcome, due to the non-manipulable nature of the exposure and the unique structure of microbiome data, including high dimensionality, sparsity, and compositionality. METHODS:Considering the modifiable and quantitative features of the microbiome, we propose a microbial causal mediation model framework, SparseMCMM_HD, to uncover the mediating role of microbiome in health disparities, by depicting a plausible path from a non-manipulable exposure (e.g., ethnicity or region) to the outcome through the microbiome. The proposed SparseMCMM_HD rigorously defines and quantifies the manipulable disparity measure that would be eliminated by equalizing microbiome profiles between comparison and reference groups and innovatively and successfully extends the existing microbial mediation methods, which are originally proposed under potential outcome or counterfactual outcome study design, to address health disparities. RESULTS:Through three body mass index (BMI) studies selected from the curatedMetagenomicData 3.4.2 package and the American gut project: China vs. USA, China vs. UK, and Asian or Pacific Islander (API) vs. Caucasian, we exhibit the utility of the proposed SparseMCMM_HD framework for investigating the microbiome's contributions in health disparities. Specifically, BMI exhibits disparities and microbial community diversities are significantly distinctive between reference and comparison groups in all three applications. By employing SparseMCMM_HD, we illustrate that microbiome plays a crucial role in explaining the disparities in BMI between ethnicities or regions. 20.63%, 33.09%, and 25.71% of the overall disparity in BMI in China-USA, China-UK, and API-Caucasian comparisons, respectively, would be eliminated if the between-group microbiome profiles were equalized; and 15, 18, and 16 species are identified to play the mediating role respectively. CONCLUSIONS:The proposed SparseMCMM_HD is an effective and validated tool to elucidate the mediating role of microbiome in health disparity. Three BMI applications shed light on the utility of microbiome in reducing BMI disparity by manipulating microbial profiles. Video Abstract.

Low fruit and vegetable (FV) intake and high sugar-sweetened beverage (SSB) consumption are independently associated with an increased risk of developing cardiovascular disease (CVD). Many people in New York City (NYC) have low FV intake and high SSB consumption, partly due to high cost of fresh FVs and low cost of and easy access to SSBs. A potential implementation of an SSB tax and an FV subsidy program could result in substantial public health and economic benefits. We used a validated microsimulation model for predicting CVD events to estimate the health impact and cost-effectiveness of SSB taxes, FV subsidies, and funding FV subsidies with an SSB tax in NYC. Population demographics and health profiles were estimated using data from the NYC Health and Nutrition Examination Survey. Policy effects and price elasticity were derived from recent meta-analyses. We found that funding FV subsidies with an SSB tax was projected to be the most cost-effective policy from the healthcare sector perspective. From the societal perspective, the most cost-effective policy was SSB taxes. All policy scenarios could prevent more CVD events and save more healthcare costs among men compared to women, and among Black vs. White adults. Public health practitioners and policymakers may want to consider adopting this combination of policy actions, while weighing feasibility considerations and other unintended consequences.

Background: During the COVID-19 pandemic, Asians/Asian Americans have experienced co-occurring threats of anti-Asian racism, economic challenges, and negative mental and physical health symptoms. Objectives: We examined the co-occurrence of COVID-19-related anti-Asian discrimination and collective racism, economic stressors, and mental and physical health challenges for Asians/Asian Americans during the COVID-19 pandemic. We also examined Asian/Asian American subgroups associated with these threats. Methods: Nationally representative data from the 2021 Asian American and Native Hawaiian/Pacific Islander COVID-19 Needs Assessment Project (unweighted N = 3,508) were used to conduct a latent profile analysis to identify unique typologies of the co-occurrence of these threats. We also conducted chi-square analyses to investigate subgroup differences by latent profile. Results: We identified five distinct latent profiles: multi-threat impact, low impact, collective racism, health challenges, and economic/health challenges. Forty percent of Asians/Asian Americans were in the multi-threat impact profile, indicating high levels across COVID-19-related threats. Subgroup analyses revealed significant differences in profile membership. East Asians, US-born Asians/Asian Americans, and those aged 25"“44 seemed to be particularly affected by the proposed syndemic; results also differed by income. Conclusion: Asians/Asian Americans have experienced co-occurring and interrelated threats during COVID-19 that suggest the presence of a syndemic. Results from our study point to vulnerable Asian/Asian American subgroups and the need for targeted public health efforts to address racism, health challenges, and economic challenges in the context of COVID-19.

Objective: The objective of this study was to evaluate the relative validity of the nine-item Diet Risk Score (DRS) among Chinese American adults using Healthy Eating Index (HEI)-2015 scores. We provide insights into the application of the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) for this population, and report on lessons learned from carrying out participant recruitment during the COVID-19 pandemic. Methods: Thirty-three Chinese American adults (mean age=40; 36% male) were recruited from the community and through ResearchMatch. Participants completed the DRS and two 24-hour food records, which were entered into the ASA 24-Hour Dietary Assessment Tool (ASA24) by community health workers (CHWs). HEI-2015 scores were calculated from each food record and an average score was obtained for each participant. One-way analysis of variance and Spearman correlations were used to compare total and component scores between the DRS and HEI-2015. Results: Mean HEI-2015 score was 56.7/100 (SD 10.6) and mean DRS score was 11.8/27 (SD 4.7), with higher scores reflecting better and worse diets, respectively. HEI-2015 and DRS scores were inversely correlated (r=-0.43, p<0.05). The strongest correlations were between HEI-2015 Total Vegetables and DRS Vegetables (r=-0.5, p<0.01), HEI-2015 Total Vegetables and Green Vegetables (r=-0.43, p=0.01) and HEI-2015 Seafood/Plant Protein and DRS Fish (r=-0.47, p<0.01). The inability to advertise and recruit for the study in person at community centres due to pandemic restrictions impeded the recruitment of less-acculturated individuals. A lack of cultural food items in the ASA24 database made it difficult to record dietary intake as reported by participants. Conclusion: The DRS can be a valuable tool for physicians to identify and reach Chinese Americans at risk of cardiometabolic disease.

OBJECTIVE:The aims of the study were to describe the up-to-date trend of total, diagnosed, and undiagnosed diabetes and prediabetes, assess their associated disparities among population subgroups, and examine their relationship with sociodemographic factors among adults in the United States. STUDY DESIGN/METHODS:This was a cross-sectional study from a nationally representative sample of US adults (aged ≥20 years) who participated in the National Health and Nutrition Examination Survey. METHODS:level of 5.7%-6.4% or a fasting plasma glucose level of 100-125 mg/dL. All estimates were age standardized to the 2010 US census population for age groups 20-44, 45-64, and 65+ years. All analyses accounted for the complex survey design. Logistic regressions were used to conduct the analyses. RESULTS:A total of 21,600 (mean, 47.2 years [SD, 14.7]) individuals were analyzed. From 1999 to 2018, the age-standardized prevalence increased significantly from 9.17% to 14.7% (difference, 5.52%; 95% confidence interval [CI], 2.69%-8.35%; P-trend <0.001) for total diabetes, increased from 6.15% to 11.0% (difference, 4.79%; 95% CI, 2.27%-7.32%; P-trend<0.001) for diagnosed diabetes and remained stable from 3.01% to 3.73% (difference, 0.72%; 95% CI, -0.47% to 1.91%; P-trend = 0.19) for undiagnosed diabetes. The age-standardized prevalence of prediabetes increased significantly from 29.5% to 48.3% (difference, 18.8%; 95% CI, 13.3%-24.4%; P-trend<0.001). Disparities persisted with higher prevalence among adults with obesity and populations that have been marginalized, including racial and ethnic minorities, low income, less educated Americans, and those living in food-insecure household. CONCLUSIONS:The prevalence of diabetes and prediabetes increased significantly from 1999 to 2018 among US adults. There are substantial and persistent disparities among racial and ethnic minorities, populations experiencing socio-economic disadvantages, and adults with obesity.