Objective: Examine the independent associations and interaction between early-life adversity and residential ambient air pollution exposure on relative buccal telomere length (rBTL). Methods: Experiences of abuse, neglect, household challenges, and related life events were identified in a cross-sectional sample of children aged 1 to 11 years (n = 197) using the 17-item Pediatric ACEs and Related Life Event Screener (PEARLS) tool. The PEARLS tool was analyzed both as a total score and across established domains (Maltreatment, Household Challenges, and Social Context). Ground-level fine particulate matter (PM2.5) concentrations were matched to residential locations for the 1 and 12 months before biospecimen collection. We used multivariable linear regression models to examine for independent associations between continuous PM2.5 exposure and PEARLS score/domains with rBTL. In addition, effect modification by PEARLS scores and domains on associations between PM2.5 exposure and rBTL was examined. Results: Study participants were 47% girls, with mean (standard deviation) age of 5.9 (3.4) years, median reported PEARLS score of 2 (interquartile range [IQR], 4), median 12-month prior PM2.5 concentrations of 11.8 mu g/m(3) (IQR, 2.7 mu g/m(3)), median 1-month prior PM2.5 concentrations of 10.9 mu g/m(3) (IQR, 5.8 mu g/m(3)), and rBTL of 0.1 (IQR, 0.03). Mean 12-month prior PM2.5 exposure was inversely associated with rBTL (beta = -0.02, 95% confidence interval = -0.04 to -0.01). Although reported PEARLS scores and domains were not independently associated with rBTL, we observed a greater decrement in rBTL with increment of average annual PM2.5 as reported Social Context domain items increased (p-interaction < .05). Conclusions: Our results suggest that adverse Social Context factors may accelerate the association between chronic PM2.5 exposure on telomere shortening during childhood.

Background Social determinants of health (SDOH) play a significant role in the development of cardiovascular risk factors. We investigated SDOH associations with cardiovascular risk factors among Asian American subgroups. Methods and Results We utilized the National Health Interview Survey, a nationally representative survey of US adults, years 2013 to 2018. SDOH variables were categorized into economic stability, neighborhood and social cohesion, food security, education, and health care utilization. SDOH score was created by categorizing 27 SDOH variables as 0 (favorable) or 1 (unfavorable). Self‐reported cardiovascular risk factors included diabetes, high cholesterol, high blood pressure, obesity, insufficient physical activity, suboptimal sleep, and nicotine exposure. Among 6395 Asian adults aged ≥18 years, 22.1% self‐identified as Filipino, 21.6% as Asian Indian, 21.0% as Chinese, and 35.3% as other Asian. From multivariable‐adjusted logistic regression models, each SD increment of SDOH score was associated with higher odds of diabetes among Chinese (odds ratio [OR], 1.45; 95% CI, 1.04–2.03) and Filipino (OR, 1.24; 95% CI, 1.02–1.51) adults; high blood pressure among Filipino adults (OR, 1.28; 95% CI, 1.03–1.60); insufficient physical activity among Asian Indian (OR, 1.42; 95% CI, 1.22–1.65), Chinese (OR, 1.58; 95% CI, 1.33–1.88), and Filipino (OR, 1.24; 95% CI, 1.06–1.46) adults; suboptimal sleep among Asian Indian adults (OR, 1.20; 95% CI, 1.01–1.42); and nicotine exposure among Chinese (OR, 1.56; 95% CI, 1.15–2.11) and Filipino (OR, 1.50; 95% CI, 1.14–1.97) adults. Conclusions Unfavorable SDOH are associated with higher odds of cardiovascular risk factors in Asian American subgroups. Culturally specific interventions addressing SDOH may help improve cardiovascular health among Asian Americans.

BackgroundAlthough racial and ethnic disparities in allergic diseases have previously been observed, the relationship between social determinants of health (SDoH) and allergic disease prevalence among disaggregated Asian American (AsA) subgroups is poorly understood.ObjectiveTo examine the association of SDoH with allergic disease prevalence among disaggregated AsA subgroups.MethodsUsing the 2011-2018 National Health Interview Survey, we examined caregiver-reported race and ethnicity, SDoH, and allergic diseases. We compared survey-weighted allergic disease prevalence by AsA subgroup. Subgroup-stratified multivariable logistic regression accounting for age, sex, child/parent nativity, and survey year modeled the association between SDoH and allergic disease prevalence. We provide predicted probabilities of having each allergic disease based on exposure to each SDoH.ResultsWe examined data from 5042 non-Hispanic AsA children representing 3,264,768 AsA children. Approximately 25% of all AsA children reported at least one allergic disease, ranging from 20% of Asian Indian children to 30% of Filipino/a children. The number of unfavorable SDoH was lowest among Asian Indian and Chinese children (mean 0.7) and highest among "other Asian" children (mean 1.2). In stratified analyses, financial instability and inaccessible healthcare were associated with greater probability of allergic diseases among some, but not all AsA subgroups. Lower parent education level, food insecurity, and rent/other housing arrangement were associated with lower probability of allergic disease among some AsA children.ConclusionThere was heterogeneity in the association of SDoH and allergic disease prevalence among AsA children. Further study of SDoH may inform modifiable environmental factors for allergic disease among AsA children.

ObjectiveMultiple studies have shown that racially minoritized groups had disproportionate COVID-19 mortality relative to non-Hispanic White individuals. However, there is little known regarding mortality by immigrant status nationally in the United States, despite being another vulnerable population.Study designThis was an observational cross-sectional study using mortality vital statistics system data to calculate proportionate mortality ratios (PMRs) and mortality rates due to COVID-19 as the underlying cause.MethodsRates were compared by decedents’ identified race, ethnicity (Hispanic vs non-Hispanic), and immigrant (immigrants vs US born) status. Asian race was further disaggregated into “Asian Indian,” “Chinese,” “Filipino,” “Japanese,” “Korean,” and “Vietnamese.”ResultsOf the over 3.4 million people who died in 2020, 10.4% of all deaths were attributed to COVID-19 as the underlying cause (n = 351,530). More than double (18.9%, n = 81,815) the percentage of immigrants who died of COVID-19 compared with US-born decedents (9.1%, n = 269,715). PMRs due to COVID-19 were higher among immigrants compared with US-born individuals for non-Hispanic White, non-Hispanic Black, Hispanic, and most disaggregated Asian groups. Among disaggregated Asian immigrants, age- and sex-adjusted PMR due to COVID-19 ranged from 1.58 times greater mortality among Filipino immigrants (95% confidence interval [CI]: 1.53, 1.64) to 0.77 times greater mortality among Japanese immigrants (95% CI: 0.68, 0.86). Age-adjusted mortality rates were also higher among immigrant individuals compared with US-born people.ConclusionsImmigrant individuals experienced greater mortality due to COVID-19 compared with their US-born counterparts. As COVID-19 becomes more endemic, greater clinical and public health efforts are needed to reduce disparities in mortality among immigrants compared with their US-born counterparts.

Introduction: Environmental metal exposure has been linked with multi-system toxicity and elevated stress hormones, and high metal concentrations have been observed among Asian Americans. Metal exposure may also increase Allostatic Load (AL), or physiologic “wear-and-tear” on the body. Hypothesis: Metal biomarker concentration is associated with high AL among non-Hispanic Asian (NHA) and non-Hispanic White (NHW) adults. Methods: AL scores were calculated based on 9 biomarkers representing cardiovascular, metabolic, and immune system function using data from the National Health and Nutrition Examination Survey (2015-2020). High AL was defined as having ≥3 high-risk biomarkers based on empirically defined thresholds. Lead, cadmium, and mercury were quantified in blood while arsenic, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) were measured in urine. Metal concentrations were categorized into empirically-defined sample tertiles. Survey-weighted logistic regression analyses controlled for demographic, socioeconomic, and health behavior variables. Analyses were also stratified by NHA and NHW. Results: The study sample consisted of 5,012 adults [mean age: 50.4, SE: 0.5] (21.6% foreign-born NHA, 2.7% US-born NHA, and 75.7% NHW). Prevalence of high AL was 38.2% among NHW, 32.4% among foreign-born NHA, and 19.3% among US-born NHA. Metal exposure demonstrated heterogenous relationships with AL ( Table ). Individuals in the highest tertile of cadmium exposure had 38% greater odds of having high AL than those in the lowest tertile, however this association was attenuated after controlling for socioeconomic status and health behaviors. Lead, mercury, arsenic, DMA, and MMA were associated with lower odds of high AL. Relationships were similar when stratified by NHW and NHA. Conclusion: The association between metals and AL differs by metal type in our study population. Future studies should explore the mechanistic pathways between high metal exposure and AL.

Introduction: Limited disaggregated Asian subgroup data exist on the association between cardiovascular (CV) risk factors and acculturation level. Hypothesis: The association between acculturation levels and CV risk factors will differ by Asian subgroups. Methods: We used the National Health Interview Survey, a nationally representative US survey, years 2014-18. Acculturation was defined using the sum of: (a) years in the US (b) citizenship (c) English proficiency. An acculturation index was created and categorized as low, moderate, or high (scores of 0-1, 2 and ≥ 3, respectively). Self-reported risk factors included high cholesterol, obesity, tobacco use, physical activity level, diabetes and hypertension. Age-adjusted, weighted proportions were used to compare the prevalence of CV risk factors between Asian subgroups using Rao-Scott Chi Square. Results: Study sample consisted of 10,891 adults, representing 7.5 million US adults ≥ 18 years (46 % male; mean age 48.3 [SD 15.7]). The distribution by race/ethnicity was Asian Indian 15.1%, Chinese 12.9%, Filipino 10.2%, other Asian 18.2%, and NHW 43.7%. We found a positive association between prevalence of high cholesterol and acculturation level among all Asian subgroups, with increases of 50 to 90% when comparing low vs high acculturation ( Table ). Filipinos had a higher prevalence of obesity and tobacco use associated with higher acculturation level (p< 0.05), but this was not observed among other Asian subgroups. In contrast, physical activity levels were higher among Asian subgroups with higher acculturation levels. No differences were seen for prevalence of hypertension or diabetes based on acculturation level. Conclusion: This study demonstrates that acculturation level was associated with higher prevalence of CV risk factors with significant variability among Asian subgroups. It highlights the need for more studies to better understand these differences based on acculturation level and can help inform targeted, culturally specific interventions.

Objective:This cross-sectional study aims to better understand the heterogeneous associations of acculturation level on CV risk factors among disaggregated Asian subgroups. We hypothesize that the association between acculturation level and CV risk factors will differ significantly by Asian subgroup. Methods:We used the National Health Interview Survey (NHIS), a nationally representative US survey, years 2014-18. Acculturation was defined using: (a) years in the US, (b) US citizenship status, and (c) level of English proficiency. We created an acculturation index, categorized into low vs. high (scores of 0-3 and 4, respectively). Self-reported CV risk factors included diabetes, high cholesterol, hypertension, obesity, tobacco use, and sufficient physical activity. Rao-Scott Chi Square was used to compare age-standardized, weighted prevalence of CV risk factors between Asian subgroups. We used logistic regression analysis to assess associations between acculturation and CV risk factors, stratified by Asian subgroup. Results:The study sample consisted of 6,051 adults ≥ 18 years of age (53.9% female; mean age 46.6 [SE 0.33]). The distribution by race/ethnicity was Asian Indian 26.9%, Chinese 22.8%, Filipino 18.1%, and other Asian 32.3%. The association between acculturation and CV risk factors differed by Asian subgroups. From multivariable adjusted models, high vs. low acculturation was associated with: high cholesterol amongst Asian Indian (OR=1.57, 95% CI: 1.11, 2.37) and other Asian (OR=1.48, 95% CI: 1.10, 2.01) adults, obesity amongst Filipino adults (OR= 1.62, 95% CI: 1.07, 2.45), and sufficient physical activity amongst Chinese (OR= 1.54, 95% CI: 1.09, 2.19) and Filipino adults (OR=1.58, 95% CI: 1.10, 2.27). Conclusion:This study demonstrates that acculturation is heterogeneously associated with higher prevalence of CV risk factors among Asian subgroups. More studies are needed to better understand these differences that can help to inform targeted, culturally specific interventions.

Editor—The increasing prevalence of opioid-related deaths across the USA prompted the US Department of Health and Human Services to declare opioid overdoses a public health crisis in 2017.1,2 Here we hypothesised that disaggregating opioid-related overdose deaths and intention by race will uncover differences in geography, age, and opioid overdose intention within the USA. To test our hypothesis, we conducted an observational, cross-sectional study utilising death certificate data from the US National Vital Statistics System (NVSS) dataset containing vital events from 2005 to 2017 under a data use agreement.

Background: Limited disaggregated Asian subgroup data exists on the impact of social determinants of health (SDOH) on optimal cardiovascular (CV) health. Hypothesis: Compared to non-Hispanic whites (NHW), Asian subgroups have a greater likelihood of optimal CV health, but this observation may be attenuated after controlling for SDOH. Methods: We analyzed results from the National Health Interview Survey (2013-2018), a nationally representative sample. Self-reported SDOH variables include demographics, food security, healthcare access, financial security, and neighborhood cohesion. We conducted stepwise, multivariable logistic regression, analyzing the association between race/ethnicity and CV risk profile score iteratively controlling for SDOH, based on the presence of CV risk factors (RF): diabetes mellitus, hypertension, obesity, smoking, insufficient physical activity, and high cholesterol. CV risk profile sum was categorized as optimal (0-1 RF) or sub-optimal (≥ 2 RF). Results: Our study sample included 112,380 individuals [mean age 49.1 (SD 18.6)]: 92.7% NHW, 1.6% Asian Indian, 1.5% Chinese, 1.6% Filipino, and 2.6% other Asian. The final model, adjusted for all domains of SDOH, showed that odds for optimal CV health for Filipinos compared to NHW were not significant (OR= 1.06, 95% CI: 0.90, 1.24, p = 0.47). After adjusting for all SDOH, Chinese had the highest odds of optimal CV health compared to NHWs (OR=2.47, 95% CI: 2.08, 2.94, p < 0.001), while the greatest change was observed for Asian Indians [Model 1: OR 1.94 (95% CI 1.7, 2.22) versus Model 5: OR 1.7 (95% CI 1.47, 1.96)]. Conclusion: Asian Indian, Chinese, and other Asian subgroups had a higher likelihood of optimal CV health compared to NHWs after controlling for SDOH but no significant differences were observed for Filipinos. This association was modestly attenuated only for Asian Indians after controlling for all SDOH. Future research should focus on the modifying effects that race/ethnicity may have on the association between SDOH and optimal CV health.

For the past three years, the Saint Louis University American Society for Biochemistry and Molecular Biology (SLU ASBMB) student chapter has planned and held “A Day in the Clinical Laboratory.” We selected 20 sophomore and junior students from local St. Louis high schools to learn about and perform different laboratory techniques in order to complete our designed case study. During the day, we had four lab stations that included hematology, urinalysis, blood bank, and chemistry. The laboratory techniques and case study were challenging in order to allow the students to think critically and to ensure interest in the study. The individual labs were all connected, and it showed how different clinical laboratories are done and how there is a need for collaboration between different departments in order to get a diagnosis for patients. Each group of students had 30 minutes at each station to ensure that they had enough time to complete the task and to ask any questions that they had. The students that came had an interest in science or medicine, and this program allowed them to get early exposure to research, science, technology, engineering, and mathematics fields. The event was free of charge and provided them the opportunity to see the importance in research and allowed them to network with different faculty mentors. Parents and teachers were also invited to attend, and student volunteers led a tour of the University campus facilities. High school students and their parents and teachers had the opportunity to speak with Saint Louis University Doisy College of Health Sciences Faculty on college application advising and additional opportunities available to local students interested in a scientific career. The event was run by SLU ASBMB students. At the end of the day, high school students were surveyed anonymously. All students gave positive feedback, and everyone expressed interest in attending another “A Day in the Clinical Laboratory” event.Support or Funding InformationFinancial support was received from the ASBMB Student Chapter Outreach Grant and the Saint Louis University Student Government Association.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Hemoglobinopathies are the most prevalent monogenetic disorder worldwide, and sickle cell disease is the most prevalent and severe structural hemoglobinopathy. Globally, over 85% of the sickle cell gene penetrance occurs in sub‐Saharan Africa (64.4%) and Arab‐India (22.7%) which contains the poorest countries on earth. Diagnosing sickle cell disease remains problematic in these populations where poverty severely limits clinic budgets, country infrastructure, and healthcare education making the use of modern diagnostic methods impractical. By modifying an established sodium metabisulfite method to detect sickle cells, we developed a simple, rapid, cost‐effective, microscopic method to distinguish the homozygous genotype (SS) seen in sickle cell disease (SCD) from the heterozygous genotype (AS) seen in sickle cell trait (SCT). We hypothesized that the two zygosities can be differentiated by observing the number, intensity, and rate of sickle cell formation over time. A solution of 2% sodium metabisulfite was prepared and 15 μL was mixed with 15 uL of patient blood and 5uL of the mixture was transferred to a microscope slide for evaluation using 100x oil immersion brightfield microscopy. Sickle cells were counted in one hour intervals for three hours and judged for sickling intensity on a 0–4+ Likert Scale. It was determined that 4+ sickle cells at 3 hours incubation optimally differentiated SS from AS genotypes. SS samples had an average of 135, 4+ sickle cells (N=10) compared to 12, 4+ sickle cells in the sickle cell trait samples (N=5) at three hours. Although more data are being collected, this inexpensive method can potentially be used to diagnose SCD and SCT, benefiting countries where there are limited resources. Support or Funding Information AL is supported by DeNardo Education and Research Foundation Fellowship. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

ABSTRACT The objective of this study was to develop a simple, inexpensive, and rapid confirmatory test using a sodium metabisulfite microscopic method to distinguish AS from SS genotype in patients with positive test results for hemoglobin S. Equal volumes of de-identified EDTA blood and 2% sodium metabisulfite were mixed, placed on a microscope slide with coverslip, and observed for sickling at 30-minute intervals over 3 hours. Sickle cells were enumerated per 200 red blood cells (RBCs) under 100x oil immersion and placed into 4 Likert categories (1+ to 4+) based on degree of sickling. In AS samples, 2+ and 3+ sickle cells rose most rapidly, and 4+ sickle cells showed the steepest rise in the SS samples. Based on these data, the number of 4+ sickle cells were counted every 30-minutes over 3 hours in 5 AS and 28 SS samples at 37°C. The mean numbers of 4+ sickle cells in AS samples were 4.75 per 200 RBCs at 2 hours and 17.75 per 200 RBCs at 3 hours. SS samples yielded 78.29 per 200 RBCs at 2 hours and 115.43 per 200 RBCs at 3 hours. Two-hour incubation showed a statistical difference (P = 0.00024) among groups in the shortest time and may be used to distinguish SS from AS genotypes. More testing is needed to determine cut points to distinguish genotype.