Social Determinants of Cardiovascular Risk Factors Among Asian American Subgroups.

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.

Temporal Trends in Cardiovascular Disease Prevalence Among Asian American Subgroups.

BACKGROUND: Asian and multiracial individuals represent the 2 fastest growing racial and ethnic groups in the United States, yet most prior studies report Asian American and Native Hawaiian or Other Pacific Islander as a single racial group, with limited data on cardiovascular disease (CVD) prevalence among subgroups. We sought to evaluate temporal trends in CVD burden among disaggregated Asian subgroups. METHODS AND RESULTS: Patients with CVD based on International Classification of Diseases, Ninth Revision and Tenth Revision (ICD-9 and ICD-10) coding who received care from a mixed-payer health care organization in California between 2008 and 2018 were classified into self-identified racial and ethnic subgroups (non-Hispanic White [NHW], Asian Indian, Chinese, Filipino, Japanese, Korean, Native Hawaiian or Other Pacific Islander, and multiracial groups). Adjusted trends in CVD prevalence over time by subgroup were compared using logistic regression. Among 3 494 071 patient-years, prevalence of CVD increased faster among all subgroups except Japanese and Native Hawaiian or Other Pacific Islander patients (P<0.01 for each, reference: NHW). Filipino patients had the highest overall CVD prevalence, which increased from 34.3% to 45.1% over 11 years (increase from 17.3%-21.9%, P<0.0001, reference: NHW). Asian Indian patients had the fastest increase in CVD prevalence over time (16.9%-23.7%, P<0.0001, reference: NHW). Among subcategories of disease, hypertension increased faster among Asian Indian, Chinese, Filipino, Korean, and multiracial groups (P<0.01 for all, reference: NHW), and coronary artery disease increased faster among Asian Indian, Chinese, Filipino, and Japanese groups (P<0.05 for each, reference: NHW). CONCLUSIONS: The increasing prevalence of CVD among disaggregated Asian, Native Hawaiian or Other Pacific Islander, and multiracial subgroups over time highlights the importance of tailored approaches to addressing CVD in these diverse subpopulations.

Patterns and gaps in guideline-directed statin use for atherosclerotic cardiovascular disease by race and ethnicity.

Objective: There remain disparities by race and ethnicity in atherosclerotic cardiovascular disease (ASCVD). Statins reduce low-density lipoprotein cholesterol (LDL-c) and improve ASCVD outcomes. ASCVD treatment patterns across disaggregated race and ethnicity groups are incompletely understood. We aimed to evaluate statin use and LDL-c control for ASCVD by race and ethnicity. Methods: From an electronic health record (EHR)-based cohort from a multisite Northern California health system, we included adults with an ASCVD diagnosis from 2010 to 2021 and at least 2 primary care visits, stratified by race and ethnicity (Non-Hispanic White [NHW], Non-Hispanic Black [Black], Hispanic, and Asian). Hispanic (Mexican, Puerto Rican, Other) and Asian (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, Other) groups were disaggregated. Primary outcomes were 1-year post-ASCVD statin use (prescription) and LDL-c control (at least one value <70 mg/dL). Adjusted odds ratios (ORs) were estimated using logistic regression. Results: Of 133,158 patients, there were 89,944 NHW, 6,294 Black, 12,478 (9.4 %) Hispanic and 13,179 (9.9 %) Asian patients. At 1 year after incident ASCVD, there was suboptimal statin use (any statins <60 %, high-intensity <25 %) and LDL-c control (<30 %) across groups, with lowest proportions in Black patients for statin use (46.7 %, any statin) and LDL-c control (10.7 %, OR 0.89 (0.81-0.97), referent NHW). Disaggregation of Asian and Hispanic groups unmasked within-group heterogeneity. Conclusions: In patients with incident ASCVD, we describe suboptimal and heterogenous 1-year post-ASCVD guideline-directed statin use and 1-year post-ASCVD LDL-c control across disaggregated race and ethnicity groups. Findings may improve understanding of ASCVD treatment disparities and guide implementation.

Obesity Disparities Among Adult Single-Race and Multiracial Asian and Pacific Islander Populations.

Importance: Despite increasing numbers of multiracial individuals, they are often excluded in studies or aggregated within larger race and ethnicity groups due to small sample sizes. Objective: To examine disparities in the prevalence of obesity among single-race and multiracial Asian and Pacific Islander individuals compared with non-Hispanic White (hereafter, White) individuals. Design, Setting, and Participants: This cross-sectional study used electronic health record (EHR) data linked to social determinants of health and health behavior data for adult (age ≥18 years) members of 2 large health care systems in California and Hawai'i who had at least 1 ambulatory visit to a primary care practitioner between January 1, 2006, and December 31, 2018. Data were analyzed from October 31, 2022, to July 31, 2023. Exposure: Self-identified race and ethnicity provided in the EHR as a single-race category (Asian Indian, Chinese, Filipino, Japanese, Native Hawaiian only, Other Pacific Islander, or White) or a multiracial category (Asian and Pacific Islander; Asian, Pacific Islander, and White; Asian and White; or Pacific Islander and White). Main Outcomes and Measures: The main outcome was obesity (body mass index [BMI] ≥30.0), based on last measured height and weight from the EHR. Logistic regression was used to examine the association between race and ethnicity and odds of obesity. Results: A total of 5229 individuals (3055 [58.4%] male; mean [SD] age, 70.73 [11.51] years) were examined, of whom 444 (8.5%) were Asian Indian; 1091 (20.9%), Chinese; 483 (9.2%), Filipino; 666 (12.7%), Japanese; 91 (1.7%), Native Hawaiian; 95 (1.8%), Other Pacific Islander; and 888 (17.0%), White. The percentages of individuals who identified as multiracial were as follows: 417 (8.0%) were Asian and Pacific Islander; 392 (7.5%), Asian, Pacific Islander, and White; 248 (4.7%), Asian and White; and 414 (7.9%), Pacific Islander and White. A total of 1333 participants (25.5%) were classified as having obesity based on standard BMI criteria. Obesity was highest among people who identified as Asian, Pacific Islander, and White (204 of 392 [52.0%]) followed by those who identified as Other Pacific Islander (47 of 95 [49.5%]), Native Hawaiian (44 of 91 [48.4%]), and Pacific Islander and White (186 of 414 [44.9%]). After accounting for demographic, socioeconomic, and health behavior factors, people who identified as Asian, Pacific Islander, and White (odds ratio [OR], 1.80; 95% CI, 1.37-2.38) or Pacific Islander and White (OR, 1.55; 95% CI, 1.18-2.04) had increased odds of obesity compared with White individuals. All single-race Asian groups had lower odds of obesity compared with White individuals: Asian Indian (OR, 0.29; 95% CI, 0.20-0.40), Chinese (OR, 0.22; 95% CI, 0.17-0.29), Filipino (OR, 0.46; 95% CI, 0.35-0.62), and Japanese (OR, 0.38, 95% CI, 0.29-0.50). Conclusions and Relevance: In this study, multiracial Asian and Pacific Islander individuals had an increased prevalence of obesity compared with many of their single-race counterparts. As the number of multiracial individuals increases, it will be important for clinical and public health systems to track disparities in these populations.

Relationship between body mass index and cardiometabolic health in a multi-ethnic population: A project baseline health study.

Objective: Obesity is associated with a higher risk of cardiovascular disease. Understanding the associations between comprehensive health parameters and body mass index (BMI) may lead to targeted prevention efforts. Methods: Project Baseline Health Study (PBHS) participants were divided into six BMI categories: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2), class I obesity (30-34.9 kg/m2), class II obesity (35-39.9 kg/m2), and class III obesity (BMI ≥40 kg/m2). Demographic, cardiometabolic, mental health, and physical health parameters were compared across BMI categories, and multivariable logistic regression models were fit to evaluate associations. Results: A total of 2,493 PBHS participants were evaluated. The mean age was 50±17.2 years; 55 % were female, 12 % Hispanic, 16 % Black, and 10 % Asian. The average BMI was 28.4 kg/m2±6.9. The distribution of BMI by age group was comparable to the 2017-2018 National Health and Nutrition Examination Survey (NHANES) dataset. The obesity categories had higher proportions of participants with CAC scores >0, hypertension, diabetes, lower HDL-C, lower vitamin D, higher triglycerides, higher hsCRP, lower mean step counts, higher mean PHQ-9 scores, and higher mean GAD-7 scores. Conclusion: We identified associations of cardiometabolic and mental health characteristics with BMI, thereby providing a deeper understanding of cardiovascular health across BMI.

Risk of Gastric Adenocarcinoma in a Multiethnic Population Undergoing Routine Care: An Electronic Health Records Cohort Study.

BACKGROUND: Gastric adenocarcinoma (GAC) is often diagnosed at advanced stages and portends a poor prognosis. We hypothesized that electronic health records (EHR) could be leveraged to identify individuals at highest risk for GAC from the population seeking routine care. METHODS: This was a retrospective cohort study, with endpoint of GAC incidence as ascertained through linkage to an institutional tumor registry. We utilized 2010 to 2020 data from the Palo Alto Medical Foundation, a large multispecialty practice serving Northern California. The analytic cohort comprised individuals ages 40-75 receiving regular ambulatory care. Variables collected included demographic, medical, pharmaceutical, social, and familial data. Electronic phenotyping was based on rule-based methods. RESULTS: The cohort comprised 316,044 individuals and approximately 2 million person-years (p-y) of observation. 157 incident GACs occurred (incidence 7.9 per 100,000 p-y), of which 102 were non-cardia GACs (incidence 5.1 per 100,000 p-y). In multivariable analysis, male sex [HR: 2.2, 95% confidence interval (CI): 1.6-3.1], older age, Asian race (HR: 2.5, 95% CI: 1.7-3.7), Hispanic ethnicity (HR: 1.9, 95% CI: 1.1-3.3), atrophic gastritis (HR: 4.6, 95% CI: 2.2-9.3), and anemia (HR: 1.9, 95% CI: 1.3-2.6) were associated with GAC risk; use of NSAID was inversely associated (HR: 0.3, 95% CI: 0.2-0.5). Older age, Asian race, Hispanic ethnicity, atrophic gastritis, and anemia were associated with non-cardia GAC. CONCLUSIONS: Routine EHR data can stratify the general population for GAC risk. IMPACT: Such methods may help triage populations for targeted screening efforts, such as upper endoscopy.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.

BACKGROUND: The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS: The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Statistical Methods to Evaluate Surrogate Markers.

BACKGROUND: There is tremendous interest in evaluating surrogate markers given their potential to decrease study time, costs, and patient burden. OBJECTIVES: The purpose of this statistical workshop article is to describe and illustrate how to evaluate a surrogate marker of interest using the proportion of treatment effect (PTE) explained as a measure of the quality of the surrogate marker for: (1) a setting with a general fully observed primary outcome (eg, biopsy score); and (2) a setting with a time-to-event primary outcome which may be censored due to study termination or early drop out (eg, time to diabetes). METHODS: The methods are motivated by 2 randomized trials, one among children with nonalcoholic fatty liver disease where the primary outcome was a change in biopsy score (general outcome) and another study among adults at high risk for Type 2 diabetes where the primary outcome was time to diabetes (time-to-event outcome). The methods are illustrated using the Rsurrogate package with a detailed R code provided. RESULTS: In the biopsy score outcome setting, the estimated PTE of the examined surrogate marker was 0.182 (95% confidence interval [CI]: 0.121, 0.240), that is, the surrogate explained only 18.2% of the treatment effect on the biopsy score. In the diabetes setting, the estimated PTE of the surrogate marker was 0.596 (95% CI: 0.404, 0.760), that is, the surrogate explained 59.6% of the treatment effect on diabetes incidence. CONCLUSIONS: This statistical workshop provides tools that will support future researchers in the evaluation of surrogate markers.

Asthma heterogeneity among Asian American children: The California Health Interview Survey.

BACKGROUND: The Asian American (AsA) population is heterogenous and rapidly growing; however, little is known regarding childhood asthma burden among AsA ethnic groups. The relation between obesity and asthma in AsA ethnic groups also remains unclear. OBJECTIVE: To evaluate asthma prevalence and the relation of obesity to asthma risk among children in 7 AsA ethnic groups. METHODS: We analyzed data from the California Health Interview Survey from 2011 to 2020. AsA ethnicities were self-reported. Body mass index z-scores, calculated from self-reported height/weight, were used to categorize children by obesity status, based on body mass index-for-age growth charts. Prevalence of self-reported lifetime doctor-diagnosed asthma and asthma attack in the last 12 months was calculated. We performed multivariable logistic regressions adjusting for age and sex. RESULTS: Of 34,146 survey respondents, 12.2% non-Hispanic White and 12.5% AsA children reported lifetime asthma. Among AsA ethnic groups, however, lifetime asthma ranged from 5.1% (Korean American) to 21.5% (Filipino American). Non-Hispanic White children and AsA children had a similar lifetime asthma prevalence (adjusted odds ratio [aOR], 1.05; 95% CI, 0.71-1.55; P = .81), but prevalence was lower in Korean American children (aOR, 0.37; 95% CI, 0.19-0.73; P = .004) and higher in Filipino American children (aOR, 1.97; 95% CI, 1.22-3.17; P = .006). The lifetime asthma prevalence of different AsA ethnic groups persisted even when stratified by obesity status. CONCLUSION: Childhood lifetime asthma prevalence varied among AsA ethnic groups, with lowest prevalence in Korean American children and highest prevalence in Filipino American. Further characterization of asthma burden among AsA ethnic groups may help guide asthma screening and prevention measures and offer new insights into asthma pathogenesis.

Development and Validation of the American Heart Association's PREVENT Equations.

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Risk of Incident Asthma Among Young Asian American, Native Hawaiian, and Pacific Islander Children from Age 3 to 7 Years in a Northern California Healthcare System.

Incident childhood asthma risk has not been examined among diverse Asian American, Native Hawaiian, and Pacific Islander subgroups. In a large California healthcare system, incident asthma was higher among young Filipino/a, Native Hawaiian/Pacific Islander, and South Asian children compared with non-Hispanic White children, whereas Chinese and Japanese children were similar.

Associations Between Ultra-processed Food Consumption and Cardiometabolic Health Among Older US Adults: Comparing Older Asian Americans to Older Adults From Other Major Race-Ethnic Groups.

Using data from the National Health and Nutrition Examination Survey (2001-2018; N = 19,602), this study examined whether ultra-processed food (UPF) consumption is associated with cardiometabolic health (obesity, hypertension, high cholesterol, and diabetes), among White, Black, Hispanic, and Asian Americans (AA) US adults 50 or older. Diet was assessed using 24 hour dietary recall. NOVA dietary classification system was used to calculate the percentage of caloric intake derived from UPFs. Cardiometabolic information was assessed through physical examination, blood tests, and self-reported medication information. A median of 54% (IQR: 40%, 68%) of caloric intake was attributed to UPFs and was lowest for AAs (34%, IQR: 20%, 49%) and highest for White adults (56%; IQR: 42, 69%). In multivariable adjusted models, UPF consumption was associated with greater odds of obesity, high cholesterol, and diabetes. UPF consumption is associated with poor cardiometabolic health among all US older adults. For AAs, UPFs may be particularly obesogenic.

Opportunities to Increase Science of Diversity and Inclusion in Clinical Trials: Equity and a Lack of a Control.

The United States witnessed a nearly 4-fold increase in personal health care expenditures between 1980 and 2010. Despite innovations and obvious benefits to health, participants enrolled in clinical trials still do not accurately represent the racial and ethnic composition of patients nationally or globally. This lack of diversity in cohorts limits the generalizability and significance of results among all populations and has deep repercussions for patient equity. To advance diversity in clinical trials, robust evidence for the most effective strategies for recruitment of diverse participants is needed. A major limitation of previous literature on clinical trial diversity is the lack of control or comparator groups for different strategies. To date, interventions have focused primarily on (1) community-based interventions, (2) institutional practices, and (3) digital health systems. This review article outlines prior intervention strategies across these 3 categories and considers health policy and ethical incentives for substantiation before US Food and Drug Administration approval. There are no current studies that comprehensively compare these interventions against one another. The American Heart Association Strategically Focused Research Network on the Science of Diversity in Clinical Trials represents a multicenter, collaborative network between Stanford School of Medicine and Morehouse School of Medicine created to understand the barriers to diversity in clinical trials by contemporaneous head-to-head interventional strategies accessing digital, institutional, and community-based recruitment strategies to produce informed recruitment strategies targeted to improve underrepresented patient representation in clinical trials.

Novel Prediction Equations for Absolute Risk Assessment of Total Cardiovascular Disease Incorporating Cardiovascular-Kidney-Metabolic Health: A Scientific Statement From the American Heart Association.

Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by the American Heart Association in response to the high prevalence of metabolic and kidney disease. Epidemiological data demonstrate higher absolute risk of both atherosclerotic cardiovascular disease (CVD) and heart failure as an individual progresses from CKM stage 0 to stage 3, but optimal strategies for risk assessment need to be refined. Absolute risk assessment with the goal to match type and intensity of interventions with predicted risk and expected treatment benefit remains the cornerstone of primary prevention. Given the growing number of therapies in our armamentarium that simultaneously address all 3 CKM axes, novel risk prediction equations are needed that incorporate predictors and outcomes relevant to the CKM context. This should also include social determinants of health, which are key upstream drivers of CVD, to more equitably estimate and address risk. This scientific statement summarizes the background, rationale, and clinical implications for the newly developed sex-specific, race-free risk equations: PREVENT (AHA Predicting Risk of CVD Events). The PREVENT equations enable 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure), include estimated glomerular filtration rate as a predictor, and adjust for competing risk of non-CVD death among adults 30 to 79 years of age. Additional models accommodate enhanced predictive utility with the addition of CKM factors when clinically indicated for measurement (urine albumin-to-creatinine ratio and hemoglobin A1c) or social determinants of health (social deprivation index) when available. Approaches to implement risk-based prevention using PREVENT across various settings are discussed.

Disparities and Trends in Routine Adult Vaccination Rates Among Disaggregated Asian American Subgroups, National Health Interview Survey 2006-2018.

Introduction: Vaccination rates may be improved through culturally tailored messages, but little is known about them among disaggregated Asian American subgroups. We assessed the vaccination rates for key vaccines among these subgroups. Methods: Using the National Health Interview Survey, we analyzed recent vaccination rates (2015-2018, n=188,250) and trends (2006-2018) among Asians (Chinese [n=3,165], Asian Indian [n=3,525], Filipino [n=3,656], other Asian [n=5,819]) and non-Hispanic White adults (n=172,085) for 6 vaccines (the human papillomavirus, hepatitis B, pneumococcal, influenza, tetanus-diphtheria [tetanus], and shingles vaccines). We controlled demographic, socioeconomic, and health-related variables in multivariable logistic regression and predicted marginal modeling analyses. We also computed vaccination rates among Asian American subgroups on the 2015-2018 National Health Interview Survey data stratified by foreign-born and U.S.-born status. We used Joinpoint regression to analyze trends in vaccination rates. All analyses were conducted in 2021 and 2022. Results: Among Asians, shingles (29.2%; 95% CI=26.6, 32.0), tetanus (53.7%; 95% CI=51.8, 55.6), and pneumococcal (53.8%; 95% CI=50.1, 57.4) vaccination rates were lower than among non-Hispanic Whites. Influenza (47.9%; 95% CI=46.2, 49.6) and hepatitis B (40.5%; 95% CI=39.0, 42.7) vaccination rates were similar or higher than among non-Hispanic Whites (48.4%; 95% CI=47.9, 48.9 and 30.7%; 95% CI=30.1, 31.3, respectively). Among Asians, we found substantial variations in vaccination rates and trends. For example, Asian Indian women had lower human papillomavirus vaccination rates (12.9%; 95% CI=9.1, 18.0) than all other Asian subgroups (Chinese: 37.9%; 95% CI=31.1, 45.2; Filipinos: 38.7%; 95% CI=29.9, 48.3; other Asians: 30.4%; 95% CI=24.8, 36.7) and non-Hispanic Whites (36.1%; 95% CI=34.8, 37.5). Being male, having lower educational attainment and income, having no health insurance or covered by public health insurance only, and lower frequency of doctor visits were generally associated with lower vaccine uptakes. Foreign-born Asian aggregate had lower vaccination rates than U.S.-born Asian aggregate for all vaccines except for influenza. We also found subgroup-level differences in vaccination rates between foreign-born and U.S.-born Asians. We found that (1) foreign-born Chinese, Asian Indians, and other Asians had lower human papillomavirus and hepatitis B vaccination rates; (2) foreign-born Chinese and Filipinos had lower pneumococcal vaccination rates; (3) foreign-born Chinese and Asian Indians had lower influenza vaccination rates; and (4) all foreign-born Asian subgroups had lower tetanus vaccination rates. Conclusions: Vaccination rates and trends differed among Asian American subgroups. Culturally tailored messaging and interventions may improve vaccine uptakes.

Can earlier biomarker measurements explain a treatment effect on diabetes incidence? A robust comparison of five surrogate markers.

INTRODUCTION: We measured and compared five individual surrogate markers-change from baseline to 1 year after randomization in hemoglobin A1c (HbA1c), fasting glucose, 2-hour postchallenge glucose, triglyceride-glucose index (TyG) index, and homeostatic model assessment of insulin resistance (HOMA-IR)-in terms of their ability to explain a treatment effect on reducing the risk of type 2 diabetes mellitus at 2, 3, and 4 years after treatment initiation. RESEARCH DESIGN AND METHODS: Study participants were from the Diabetes Prevention Program study, randomly assigned to either a lifestyle intervention (n=1023) or placebo (n=1030). The surrogate markers were measured at baseline and 1 year, and diabetes incidence was examined at 2, 3, and 4 years postrandomization. Surrogacy was evaluated using a robust model-free estimate of the proportion of treatment effect explained (PTE) by the surrogate marker. RESULTS: Across all time points, change in fasting glucose and HOMA-IR explained higher proportions of the treatment effect than 2-hour glucose, TyG index, or HbA1c. For example, at 2 years, glucose explained the highest (80.1%) proportion of the treatment effect, followed by HOMA-IR (77.7%), 2-hour glucose (76.2%), and HbA1c (74.6%); the TyG index explained the smallest (70.3%) proportion. CONCLUSIONS: These data suggest that, of the five examined surrogate markers, glucose and HOMA-IR were the superior surrogate markers in terms of PTE, compared with 2-hour glucose, HbA1c, and TyG index.