Self-Administration of Aspirin After Chest Pain for the Prevention of Premature Cardiovascular Mortality in the United States: A Population-Based Analysis.

BACKGROUND: Aspirin, an effective, low-cost pharmaceutical, can significantly reduce mortality if used promptly after acute myocardial infarction (AMI). However, many AMI survivors do not receive aspirin within a few hours of symptom onset. Our aim was to quantify the mortality benefit of self-administering aspirin at chest pain onset, considering the increased risk of bleeding and costs associated with widespread use. METHODS AND RESULTS: We developed a population simulation model to determine the impact of self-administering 325 mg aspirin within 4 hours of severe chest pain onset. We created a synthetic cohort of adults ≥ 40 years old experiencing severe chest pain using 2019 US population estimates, AMI incidence, and sensitivity/specificity of chest pain for AMI. The number of annual deaths delayed was estimated using evidence from a large, randomized trial. We also estimated the years of life saved (YOLS), costs, and cost per YOLS. Initiating aspirin within 4 hours of severe chest pain onset delayed 13 016 (95% CI, 11 643-14 574) deaths annually, after accounting for deaths due to bleeding (963; 926-1003). This translated to an estimated 166 309 YOLS (149391-185 505) at the cost of $643 235 (633 944-653 010) per year, leading to a cost-effectiveness ratio of $3.70 (3.32-4.12) per YOLS. CONCLUSIONS: For <$4 per YOLS, self-administration of aspirin within 4 hours of severe chest pain onset has the potential to save 13 000 lives per year in the US population. Benefits of reducing deaths post-AMI outweighed the risk of bleeding deaths from aspirin 10 times over.

Trends and disparities in prevalence of cardiometabolic diseases by food security status in the United States.

BACKGROUND: Previous studies have demonstrated the association between food security and cardiometabolic diseases (CMDs), yet none have investigated trends in prevalence of CMDs by food security status in the United States (US). METHODS: Serial cross-sectional analysis of the US nationally representative data from National Health and Nutrition Examination Survey (1999-2018) was conducted among adults aged 20 years or older. Food security status was defined by the US Household Food Security Survey Module (full, marginal, low, and very low food security). We estimated the age-adjusted prevalence of CMDs including obesity, hypertension, diabetes, and coronary heart disease by food security status. Racial and ethnic disparities in age-adjusted prevalence of CMDs by food security status were also assessed. RESULTS: A total of 49,738 participants were included in this analysis (weighted mean age 47.3 years; 51.3% women). From 1999 to 2018, the age-adjusted prevalence of CMDs was lower in full food secure group as compared with other groups. For example, trends in hypertension decreased from 49.7% (47.5-51.8%) to 45.9% (43.8-48.0%) (P-trend = 0.002) among the full and from 54.2% (49.9-58.5%) to 49.7% (46.8-52.6%) (P-trend = 0.02) among the marginal but remained stable among the low at 49.7% (47.9-51.6%) and among the very low at 51.1% (48.9-53.3%) (P-interaction = 0.02). Prevalence of diabetes increased from 8.85% (8.15-9.60%) to 12.2% (11.1-13.5%) among the full (P-trend < 0.001), from 16.5% (13.2-20.4%) to 20.9% (18.6-23.5%) (P-trend = 0.045) among the marginal and from 14.6% (11.1-19.0%) to 20.9% (18.8-23.3%) (P-trend = 0.001) among the low but remained stable at 18.8% (17.0-20.9) among the very low (P-trend = 0.35) (P-interaction = 0.03). Racial and ethnic differences in prevalence of CMD by food security status were observed. For example, among individuals with full food secure status, the prevalence of diabetes was 9.08% (95% CI, 8.60-9.59%) for non-Hispanic whites, 17.3% (95% CI, 16.4-18.2%) for non-Hispanic blacks, 16.1% (95% CI, 15.0-17.4%) for Hispanics and 14.9% (95% CI, 13.3-16.7%) for others. CONCLUSIONS AND RELEVANCE: Prevalence of CMDs was greatest among those experiencing food insecurity, and food insecurity disproportionately affected racial/ethnic minorities. Disparities in CMD prevalence by food security status persisted or worsened, especially among racial/ethnic minorities.

Prescription medication use during pregnancy in the United States from 2011 to 2020: trends and safety evidence.

BACKGROUND: Medication use during pregnancy has increased in the United States despite the lack of safety data for many medications. OBJECTIVE: This study aimed to inform research priorities by examining trends in medication use during pregnancy and identifying gaps in safety information on the most commonly prescribed medications. STUDY DESIGN: We identified population-based cohorts of commercially (MarketScan 2011-2020) and publicly (Medicaid Analytic eXtract/Transformed Medicaid Statistical Information System Analytic Files 2011-2018) insured pregnancies ending in live birth from 2 health care utilization databases. Medication use was based on filled prescriptions between the date of last menstrual period through delivery, as well as the period before the last menstrual period and during specific trimesters. We also included a cross-sectional representative sample of pregnancies ascertained by the National Health and Nutrition Examination Survey (2011-2020), with information on prescription medication use during the preceding month obtained through maternal interviews. Teratogen Information System was used to classify the available evidence on teratogenic risk. RESULTS: Among over 3 million pregnancies, the medications most commonly dispensed at any time during pregnancy were analgesics, antibiotics, and antiemetics. The top medications were ondansetron (16.8%), amoxicillin (13.5%), and azithromycin (12.4%) in MarketScan, nitrofurantoin (22.2%), acetaminophen (21.3%; mostly as part of acetaminophen-hydrocodone products), and ondansetron (19.5%) in Medicaid Analytic eXtract/Transformed Medicaid Statistical Information System Analytic Files, and levothyroxine (5.0%), sertraline (2.9%), and insulin (2.9%) in the National Health and Nutrition Examination Survey group. The most commonly dispensed suspected teratogens during the first trimester were antithyroid medications. The use of antidiabetic and psychotropic medications has continued to increase in the United States during the last decade, opioid dispensation has decreased by half, and antibiotics and antiemetics continue to be common. For one-quarter of medications, there is insufficient evidence available to characterize their safety profile in pregnancy. CONCLUSION: There is a need for more drug research in pregnant patients. Future research should focus on anti-infectives with high utilization and limited level of evidence on safety for use during pregnancy. Although lack of evidence is not evidence of safety concerns, it does not indicate risk either. In many instances, the benefits outweigh the risks when these medications are used clinically, and some of the medications with no proven safety may be necessary to treat patients.

Methods for retrospectively improving race/ethnicity data quality: a scoping review.

Improving race and ethnicity (hereafter, race/ethnicity) data quality is imperative to ensure underserved populations are represented in data sets used to identify health disparities and inform health care policy. We performed a scoping review of methods that retrospectively improve race/ethnicity classification in secondary data sets. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searches were conducted in the MEDLINE, Embase, and Web of Science Core Collection databases in July 2022. A total of 2 441 abstracts were dually screened, 453 full-text articles were reviewed, and 120 articles were included. Study characteristics were extracted and described in a narrative analysis. Six main method types for improving race/ethnicity data were identified: expert review (n = 9; 8%), name lists (n = 27, 23%), name algorithms (n = 55, 46%), machine learning (n = 14, 12%), data linkage (n = 9, 8%), and other (n = 6, 5%). The main racial/ethnic groups targeted for classification were Asian (n = 56, 47%) and White (n = 51, 43%). Some form of validation evaluation was included in 86 articles (72%). We discuss the strengths and limitations of different method types and potential harms of identified methods. Innovative methods are needed to better identify racial/ethnic subgroups and further validation studies. Accurately collecting and reporting disaggregated data by race/ethnicity are critical to address the systematic missingness of relevant demographic data that can erroneously guide policymaking and hinder the effectiveness of health care practices and intervention.

Looking Across and Within: Immigration as a Unifying Structural Factor Impacting Cardiometabolic Health and Diet.

Introduction: Immigration has been identified as an important social determinant of health (SDH), embodying structures and policies that reinforce positions of poverty, stress, and limited social and economic mobility. In the public health literature with regard to diet, immigration is often characterized as an individual-level process (dietary acculturation) and is largely examined in one racial/ethnic subgroup at a time. For this narrative review, we aim to broaden the research discussion by describing SDH common to the immigrant experience and that may serve as barriers to healthy diets. Methods: A narrative review of peer-reviewed quantitative, qualitative, and mixed methods studies on cardiometabolic health disparities, diet, and immigration was conducted. Results: Cardiometabolic disease disparities were frequently described by racial/ethnic subgroups instead of country of origin. While cardiovascular disease and obesity risk differed by country of origin, diabetes prevalence was typically higher for immigrant groups vs United States (US)-born individuals. Common barriers to achieving a healthy diet were food insecurity; lack of familiarity with US food procurement practices, food preparation methods, and dietary guidelines; lack of familiarity and distrust of US food processing and storage methods; alternative priorities for food purchasing (eg, freshness, cultural relevance); logistical obstacles (eg, transportation); stress; and ethnic identity maintenance. Conclusions: To improve the health of immigrant populations, understanding similarities in cardiometabolic health disparities, diet, and barriers to health across immigrant communities-traversing racial/ethnic subgroups-may serve as a useful framework. This framework can guide research, policy, and public health practices to be more cohesive, generalizable, and meaningfully inclusive.

Assessing changes in the food retail environment during the COVID-19 pandemic: opportunities, challenges, and lessons learned.

BACKGROUND: COVID-19 mitigation strategies have had an untold effect on food retail stores and restaurants. Early evidence from New York City (NYC) indicated that these strategies, among decreased travel from China and increased fears of viral transmission and xenophobia, were leading to mass closures of businesses in Manhattan's Chinatown. The constantly evolving COVID -19 crisis has caused research design and methodology to fundamentally shift, requiring adaptable strategies to address emerging and existing public health problems such as food security that may result from closures of food outlets. OBJECTIVE: We describe innovative approaches used to evaluate changes to the food retail environment amidst the constraints of the pandemic in an urban center heavily burdened by COVID-19. Included are challenges faced, lessons learned and future opportunities. METHODS: First, we identified six diverse neighborhoods in NYC: two lower-resourced, two higher-resourced, and two Chinese ethnic enclaves. We then developed a census of food outlets in these six neighborhoods using state and local licensing databases. To ascertain the status (open vs. closed) of outlets pre-pandemic, we employed a manual web-scraping technique. We used a similar method to determine the status of outlets during the pandemic. Two independent online sources were required to confirm the status of outlets. If two sources could not confirm the status, we conducted phone call checks and/or in-person visits. RESULTS: The final baseline database included 2585 food outlets across six neighborhoods. Ascertaining the status of food outlets was more difficult in lower-resourced neighborhoods and Chinese ethnic enclaves compared to higher-resourced areas. Higher-resourced neighborhoods required fewer phone call and in-person checks for both restaurants and food retailers than other neighborhoods. CONCLUSIONS: Our multi-step data collection approach maximized safety and efficiency while minimizing cost and resources. Challenges in remote data collection varied by neighborhood and may reflect the different resources or social capital of the communities; understanding neighborhood-specific constraints prior to data collection may streamline the process.

COVID-19 Leads to Dramatic Changes in the Food Retail Environment in New York City: May-July 2020.

A systematic assessment of the effect of COVID-19 on the food retail environment-an important determinant of health-has not been conducted. Our objective was to assess the impact of COVID-19 on closures of restaurants, food retail stores, and fresh produce vendors in New York City (NYC). We conducted a cross-sectional study following the peak of COVID-19 in six neighborhoods in NYC. Two Chinese ethnic neighborhoods and four higher/lower resourced comparison neighborhoods were selected a priori based on 14 sociodemographic indicators. The primary outcome was indefinite/temporary closures or absence of food businesses. Of 2720 food businesses identified, produce vendors and restaurants were more likely to close than food retail stores. A higher proportion of food businesses closed in Chinese ethnic neighborhoods vs. comparison neighborhoods. COVID-19 impacted food businesses in six NYC neighborhoods examined in this period, with the greatest effect observed for Chinese ethnic neighborhoods.

ART uptake and adherence among female sex workers (FSW) globally: A scoping review.

We conducted the first scoping literature review on ART uptake and adherence among Female Sex Workers (FSW), following PRISMA-ScR guidelines. Searches were conducted in PubMed, Embase, CINAHL, PsycInfo, and Sociological Abstracts. Eligibility criteria included: reporting an ART uptake or adherence result among FSW aged 18 or older; peer-reviewed; published in English between 1996 and 2018. Our search identified 6,735 studies; 30 met eligibility requirements. ART uptake ranges from 0 to 100% and adherence ranges from 50-90%, depending on measurement methods. Uptake and adherence influencing factors are mapped onto a social ecological model (SEM). Knowledge and beliefs, substance use, food insecurity and sex-work engagement were negatively associated, while older age, relationships and social support were positively associated with ART uptake and adherence. Standardised methods to measure uptake and adherence prevalence must be established for data comparison. Evidence regarding ART uptake and adherence barriers and facilitators span multiple SEM levels, although more research is needed regarding structural and occupational level influencers. Results suggest that the multi-level ART uptake and adherence barriers faced by FSW require complex multi-level evidence-based interventions. Study findings can inform ART interventions, future research, and offer guidance to other support services with FSW, such as PrEP interventions.

COVID-19, Social Determinants of Health, and Opportunities for Preventing Cardiovascular Disease: A Conceptual Framework.

The COVID-19 pandemic has disrupted the social, economic, and health care systems in the United States and shined a spotlight on the burden of disease associated with social determinants of health (SDOH). Addressing SDOH, while a challenge, provides important opportunities to mitigate cardiovascular disease incidence, morbidity, and mortality. We present a conceptual framework to examine the differential effects of the COVID-19 pandemic on SDOH across demographically diverse populations, focusing on the short- and long-term development of cardiovascular disease, as well as future research opportunities for cardiovascular disease prevention. The COVID-19 pandemic exerted negative shifts in SDOH and cardiovascular risk factors (ie, smoking, body mass index, physical activity, dietary behavior, cholesterol, blood pressure, and blood sugar). For example, evidence suggests that unemployment and food insecurity have increased, whereas health care access and income have decreased; changes to SDOH have resulted in increases in loneliness and processed food consumption, as well as decreases in physical activity and hypertension management. We found that policy measures enacted to mitigate economic, social, and health issues inadequately protected populations. Low-income and racial and ethnic minority communities, historically underserved populations, were not only disproportionately adversely affected by the pandemic but also less likely to receive assistance, likely attributable in part to the deep structural inequities pervasive in our society. Effective and culturally appropriate interventions are needed to mitigate the negative health impacts of historical systems, policies, and programs that created and maintain structural racism, especially for immigrants, racial and ethnic minorities, and populations experiencing social disadvantage.

Contrasting the experiences for high- and low-income Asian Americans during COVID-19.

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.

Evaluating Closures of Fresh Fruit and Vegetable Vendors During the COVID-19 Pandemic: Methodology and Preliminary Results Using Omnidirectional Street View Imagery.

BACKGROUND: The COVID-19 pandemic has significantly disrupted the food retail environment. However, its impact on fresh fruit and vegetable vendors remains unclear; these are often smaller, more community centered, and may lack the financial infrastructure to withstand supply and demand changes induced by such crises. OBJECTIVE: This study documents the methodology used to assess fresh fruit and vegetable vendor closures in New York City (NYC) following the start of the COVID-19 pandemic by using Google Street View, the new Apple Look Around database, and in-person checks. METHODS: In total, 6 NYC neighborhoods (in Manhattan and Brooklyn) were selected for analysis; these included two socioeconomically advantaged neighborhoods (Upper East Side, Park Slope), two socioeconomically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, Google Street View was used to virtually walk down each street and identify vendors (stores, storefronts, street vendors, or wholesalers) that were open and active in 2019 (ie, both produce and vendor personnel were present at a location). Past vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was geotagged as a Google Maps pinpoint that research assistants then physically visited. Using the "notes" feature of Google Maps as a data collection tool, notes were made on which of three categories best described each vendor: (1) open, (2) open with a more limited setup (eg, certain sections of the vendor unit that were open and active in 2019 were missing or closed during in-person checks), or (3) closed/absent. RESULTS: Of the 135 open vendors identified in 2019 imagery data, 35% (n=47) were absent/closed and 10% (n=13) were open with more limited setups following the beginning of the COVID-19 pandemic. When comparing boroughs, 35% (28/80) of vendors in Manhattan were absent/closed, as were 35% (19/55) of vendors in Brooklyn. Although Google Street View was able to provide 2019 street view imagery data for most neighborhoods, Apple Look Around was required for 2019 imagery data for some areas of Park Slope. Past surveillance data helped to identify 3 additional established vendors in Chinatown that had been missed in street view imagery. The Google Maps "notes" feature was used by multiple research assistants simultaneously to rapidly collect observational data on mobile devices. CONCLUSIONS: The methodology employed enabled the identification of closures in the fresh fruit and vegetable retail environment and can be used to assess closures in other contexts. The use of past baseline surveillance data to aid vendor identification was valuable for identifying vendors that may have been absent or visually obstructed in the street view imagery data. Data collection using Google Maps likewise has the potential to enhance the efficiency of fieldwork in future studies.

Characterising urban immigrants' interactions with the food retail environment.

OBJECTIVE: The food retail environment is an important determinant of food access and the ability to achieve a healthy diet. However, immigrant communities may procure their food in different ways than the mainstream population owing to preferences for specific cultural products or limited English language proficiency. The objective of this analysis was to describe the grocery shopping patterns and behaviours of one of the largest immigrant groups in New York City, Chinese Americans - a group experiencing high poverty and cardio-metabolic disparities. DESIGN: Cross-sectional survey data. SETTING: Community-based sample. PARTICIPANTS: Self-identified Chinese Americans in the New York metropolitan area (n 239). RESULTS: Three shopping patterns were identified: type 1: shopped weekly at an ethnic grocery store - and nowhere else; type 2: shopped weekly at a non-ethnic grocery store, with occasional shopping at an ethnic store and type 3: did not perform weekly shopping. Type 1 v. type 2 shoppers tended to have lower education levels (37·5 v. 78·0 % with college degree); to be on public insurance (57·6 v. 22·8 %); speak English less well (18·4 v. 41·4 %); be food insecure (47·2 v. 24·2 %; P < 0·01 for all) and to travel nearly two miles further to shop at their primary grocery store (ß = -1·55; 95 % CI -2·81, -0·30). DISCUSSION: There are distinct grocery shopping patterns amongst urban-dwelling Chinese Americans corresponding to demographic and sociocultural factors that may help inform health interventions in this understudied group. Similar patterns may exist among other immigrant groups, lending preliminary support for an alternative conceptualisation of how immigrant communities interact with the food retail environment.

Disparities in Sources of Added Sugars and High Glycemic Index Foods in Diets of US Children, 2011-2016.

INTRODUCTION: Added sugars and high glycemic index (GI) foods might play a role in cardiometabolic pathogenesis. Our study aimed to describe the top sources of added sugars and types of high GI foods in diets of children by race/ethnicity. METHODS: We examined data for 3,112 children, aged 6 to 11 years from the National Health and Nutrition Examination Survey (NHANES), 2011 to 2016. Mean intake was estimated and linear regression models tested for differences by race/ethnicity. Population proportions for food sources were created and ranked, accounting for survey weighting when appropriate. RESULTS: Asian American and Mexican American children had the lowest reported added sugar intake. Cereals were observed to contribute highly to added sugar intake. Soft drinks did not contribute as much added sugar intake for Asian American children as it did for children of other races/ethnicities. Asian American children consumed significantly more high GI foods than other groups. Types of high GI foods differed meaningfully across racial/ethnic groups (ie, Mexican American: burritos/tacos; other Hispanic, White, and Black: pizza; Asian American: rice). Rice accounted for 37% of total high GI foods consumed by Asian American children. CONCLUSIONS: Sources of added sugars and types of high GI foods in children's diets vary across racial/ethnic groups. Targeting foods identified as top sources of added sugars for all race/ethnicities and focusing on substitution of whole grains may reduce obesity, diabetes, and related cardiometabolic risk more equitably.

Characterizing Sugar-Sweetened Beverage Consumption for US Children and Adolescents by Race/Ethnicity.

OBJECTIVES: To examine racial/ethnic differences in type of SSB most frequently consumed and in correlates of youth sugar-sweetened beverage (SSB) intake. METHODS: Data were obtained from the National Health and Nutrition Examination Survey (NHANES), 2011-2016, for children and adolescents aged 5-17 years (n = 6507). The main outcome was SSB consumption (i.e., sodas, sweetened fruit drinks, nectars, sports and energy drinks, sweetened coffees and teas, enhanced waters). Mean and proportions of SSB intake were estimated accounting for complex sampling strategy and weighting. Multivariable regression models were developed for each race/ethnicity and age group. RESULTS: Two-thirds of children and adolescents reported consuming SSB on a given day. Among consumers, mean SSB consumption was greatest for Black children and White adolescents and lowest for Asian American children and adolescents. The most popular type of SSB consumed was sweetened fruit drinks among children and soda among adolescents, except among White and Mexican American children for whom soda and Black adolescents for whom sweetened fruit drinks were most popular. Female sex and water intake were negatively associated with SSB consumption across most races/ethnicities. Screen time, dentist visits, nativity, and guardian education were associated with SSB intake among a subset of races/ethnicities. CONCLUSIONS: Associations between covariates and SSB intake as well as types of beverages preferred vary by race/ethnicity, as such chronic disease policies should not be 'one size fits all'. Targeted interventions for specific groups of vulnerable youths hold promise for further reducing SSB consumption, including directing efforts towards reducing sweetened fruit drinks for Black children.