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.

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.

Epidemiology of Diabetes and Atherosclerotic Cardiovascular Disease Among Asian American Adults: Implications, Management, and Future Directions: A Scientific Statement From the American Heart Association.

Asian American individuals make up the fastest growing racial and ethnic group in the United States. Despite the substantial variability that exists in type 2 diabetes and atherosclerotic cardiovascular disease risk among the different subgroups of Asian Americans, the current literature, when available, often fails to examine these subgroups individually. The purpose of this scientific statement is to summarize the latest disaggregated data, when possible, on Asian American demographics, prevalence, biological mechanisms, genetics, health behaviors, acculturation and lifestyle interventions, pharmacological therapy, complementary alternative interventions, and their impact on type 2 diabetes and atherosclerotic cardiovascular disease. On the basis of available evidence to date, we noted that the prevalences of type 2 diabetes and stroke mortality are higher in all Asian American subgroups compared with non-Hispanic White adults. Data also showed that atherosclerotic cardiovascular disease risk is highest among South Asian and Filipino adults but lowest among Chinese, Japanese, and Korean adults. This scientific statement discusses the biological pathway of type 2 diabetes and the possible role of genetics in type 2 diabetes and atherosclerotic cardiovascular disease among Asian American adults. Challenges to provide evidence-based recommendations included the limited data on Asian American adults in risk prediction models, national surveillance surveys, and clinical trials, leading to significant research disparities in this population. The large disparity within this population is a call for action to the public health and clinical health care community, for whom opportunities for the inclusion of the Asian American subgroups should be a priority. Future studies of atherosclerotic cardiovascular disease risk in Asian American adults need to be adequately powered, to incorporate multiple Asian ancestries, and to include multigenerational cohorts. With advances in epidemiology and data analysis and the availability of larger, representative cohorts, furthering refining the Pooled Cohort Equations, in addition to enhancers, would allow better risk estimation in segments of the population. Last, this scientific statement provides individual- and community-level intervention suggestions for health care professionals who interact with the Asian American population.

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.

A Synopsis of the Evidence for the Science and Clinical Management of Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A Scientific Statement From the American Heart Association.

A growing appreciation of the pathophysiological interrelatedness of metabolic risk factors such as obesity and diabetes, chronic kidney disease, and cardiovascular disease has led to the conceptualization of cardiovascular-kidney-metabolic syndrome. The confluence of metabolic risk factors and chronic kidney disease within cardiovascular-kidney-metabolic syndrome is strongly linked to risk for adverse cardiovascular and kidney outcomes. In addition, there are unique management considerations for individuals with established cardiovascular disease and coexisting metabolic risk factors, chronic kidney disease, or both. An extensive body of literature supports our scientific understanding of, and approach to, prevention and management for individuals with cardiovascular-kidney-metabolic syndrome. However, there are critical gaps in knowledge related to cardiovascular-kidney-metabolic syndrome in terms of mechanisms of disease development, heterogeneity within clinical phenotypes, interplay between social determinants of health and biological risk factors, and accurate assessments of disease incidence in the context of competing risks. There are also key limitations in the data supporting the clinical care for cardiovascular-kidney-metabolic syndrome, particularly in terms of early-life prevention, screening for risk factors, interdisciplinary care models, optimal strategies for supporting lifestyle modification and weight loss, targeting of emerging cardioprotective and kidney-protective therapies, management of patients with both cardiovascular disease and chronic kidney disease, and the impact of systematically assessing and addressing social determinants of health. This scientific statement uses a crosswalk of major guidelines, in addition to a review of the scientific literature, to summarize the evidence and fundamental gaps related to the science, screening, prevention, and management of cardiovascular-kidney-metabolic syndrome.

Cardiovascular-Kidney-Metabolic Health: A Presidential Advisory From the American Heart Association.

Cardiovascular-kidney-metabolic health reflects the interplay among metabolic risk factors, chronic kidney disease, and the cardiovascular system and has profound impacts on morbidity and mortality. There are multisystem consequences of poor cardiovascular-kidney-metabolic health, with the most significant clinical impact being the high associated incidence of cardiovascular disease events and cardiovascular mortality. There is a high prevalence of poor cardiovascular-kidney-metabolic health in the population, with a disproportionate burden seen among those with adverse social determinants of health. However, there is also a growing number of therapeutic options that favorably affect metabolic risk factors, kidney function, or both that also have cardioprotective effects. To improve cardiovascular-kidney-metabolic health and related outcomes in the population, there is a critical need for (1) more clarity on the definition of cardiovascular-kidney-metabolic syndrome; (2) an approach to cardiovascular-kidney-metabolic staging that promotes prevention across the life course; (3) prediction algorithms that include the exposures and outcomes most relevant to cardiovascular-kidney-metabolic health; and (4) strategies for the prevention and management of cardiovascular disease in relation to cardiovascular-kidney-metabolic health that reflect harmonization across major subspecialty guidelines and emerging scientific evidence. It is also critical to incorporate considerations of social determinants of health into care models for cardiovascular-kidney-metabolic syndrome and to reduce care fragmentation by facilitating approaches for patient-centered interdisciplinary care. This presidential advisory provides guidance on the definition, staging, prediction paradigms, and holistic approaches to care for patients with cardiovascular-kidney-metabolic syndrome and details a multicomponent vision for effectively and equitably enhancing cardiovascular-kidney-metabolic health in the population.

Disaggregated mortality from gastrointestinal cancers in Asian Americans: Analysis of United States death records.

Asian Americans (AAs) are heterogeneous, and aggregation of diverse AA populations in national reporting may mask high-risk groups. Gastrointestinal (GI) cancers constitute one-third of global cancer mortality, and an improved understanding of GI cancer mortality by disaggregated AA subgroups may inform future primary and secondary prevention strategies. Using national mortality records from the United States from 2003 to 2017, we report age-standardized mortality rates, standardized mortality ratios and annual percent change trends from GI cancers (esophageal, gastric, colorectal, liver and pancreatic) for the six largest AA subgroups (Asian Indians, Chinese, Filipinos, Japanese, Koreans and Vietnamese). Non-Hispanic Whites (NHWs) are used as the reference population. We found that mortality from GI cancers demonstrated nearly 3-fold difference between the highest (Koreans, 61 per 100 000 person-years) and lowest (Asian Indians, 21 per 100 000 person-years) subgroups. The distribution of GI cancer mortality demonstrates high variability between subgroups, with Korean Americans demonstrating high mortality from gastric cancer (16 per 100 000), and Vietnamese Americans demonstrating high mortality from liver cancer (19 per 100 000). Divergent temporal trends emerged, such as increasing liver cancer burden in Vietnamese Americans, which exacerbated existing mortality differences. There exist striking differences in the mortality burden of GI cancers by disaggregated AA subgroups. These data highlight the need for disaggregated data reporting, and the importance of race-specific and personalized strategies of screening and prevention.

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

The incomparability of old and new classification systems for describing the same data can be seen as a missing-data problem, and, under certain assumptions, multiple imputation may be used to "bridge" 2 classification systems. One example of such a change is the introduction of detailed Asian-American race/ethnicity classifications on the 2003 version of the US national death certificate, which was adopted for use by 38 states between 2003 and 2011. Using county- and decedent-level data from 3 different national sources for pre- and postadoption years, we fitted within-state multiple-imputation models to impute ethnicities for decedents classified as "other Asian" during preadoption years. We present mortality rates derived using 3 different methods of calculation: 1) including all states but ignoring the gradual adoption of the new death certificate over time, 2) including only the 7 states with complete reporting of all ethnicities, and 3) including all states and applying multiple imputation. Estimates from our imputation model were consistently in the middle of the other 2 estimates, and trend results demonstrated that the year-by-year estimates of the imputation model were more similar to those of the 7-state model. This work demonstrates how multiple imputation can provide a "forward bridging" approach to make more accurate estimates over time in newly categorized populations.

Thyroid cancer mortality is higher in Filipinos in the United States: An analysis using national mortality records from 2003 through 2012.

BACKGROUND: Well-differentiated thyroid carcinoma has a favorable prognosis, but patients with multiple recurrences have drastically lower survival. Filipinos in the United States are known to have high rates of thyroid cancer incidence and disease recurrence. To the authors' knowledge, it is unknown whether Filipinos also have higher thyroid cancer mortality rates. METHODS: The authors studied thyroid cancer mortality in Filipino, non-Filipino Asian (NFA), and non-Hispanic white (NHW) adults using US death records (2003-2012) and US Census data. Age-adjusted mortality rates and proportional mortality ratios (PMRs) were calculated. Sex, nativity status, age at death, and educational attainment also were examined. RESULTS: The authors examined 19,940,952 deaths. The age-adjusted mortality rates due to thyroid cancer were highest in Filipinos (1.72 deaths per 100,000 population; 95% confidence interval [95% CI], 1.51-1.95) compared with NFAs (1.03 per 100,000 population; 95% CI, 0.95-1.12) and NHWs (1.17 per 100,000 population; 95% CI, 1.16-1.18). Compared with NHWs, higher proportionate mortality was observed in Filipino women (3-5 times higher) across all age groups, and among Filipino men, the PMR was 2 to 3 times higher in the subgroup aged >55 years. Filipinos who completed a higher educational level had a notably higher PMR (5.0) compared with their counterparts who had not (3.5). CONCLUSIONS: Negative prognostic factors for thyroid cancer traditionally include age >45 years and male sex. The results of the current study demonstrate that Filipinos die of thyroid cancer at higher rates than NFA and NHW individuals of similar ages. Highly educated Filipinos and Filipino women may be especially at risk of poor thyroid cancer outcomes. Filipino ethnicity should be factored into clinical decision making in the management of patients with thyroid cancer. Cancer 2017;123:4860-7. © 2017 American Cancer Society.

Clocks Moving at Different Speeds: Cultural Variation in the Satisfaction With Wait Time for Outpatient Care.

OBJECTIVE: To explore racial/ethnic differences in satisfaction with wait time of scheduled office visits by comparing electronic health record (EHR)-based, patient-reported, and patient satisfaction with wait time STUDY SETTING: : A large multispecialty ambulatory care organization in Northern California. Patient experience surveys were collected between 2010 and 2014. Surveys were mailed after randomly selected nonurgent visits. Returned survey data were linked to EHR data for surveyed visits. STUDY DESIGN: Observational, retrospective study designed to assess differences in patient-reported wait time, wait-time satisfaction, and actual EHR-recorded wait time with respect to self-reported race/ethnicity. Multivariate regression models with provider random effects were used to evaluate differences. RESULTS: Asian subgroups (Chinese, Asian Indian, Filipino, Japanese, Korean, and Vietnamese) and Latinos gave poorer ratings for wait time than non-Hispanic whites (NHWs). The average wait time reported by Asians was longer than that reported by NHWs. On the basis of EHR data, however, no minority group was likely to wait longer, and all, except for Japanese (10%), were more likely to be late for the appointment (16%: Filipino and 23%: Asian Indian), than NHWs (13%). CONCLUSIONS: Given actual wait times, Asians perceive longer wait time and were less satisfied with wait times. Asians may have different expectations about wait time at the clinic.

First Trimester Hemoglobin A1c Prediction of Gestational Diabetes.

Objective The objective of this study is to examine whether a first trimester hemoglobin A1c (A1C) of 5.7 to 6.4% predicts an abnormal second trimester oral glucose tolerance test (OGTT). Methods We conducted a retrospective cohort study of all women screened with A1C through 13 (6/7) weeks' gestation between January 1, 2011, and December 31, 2012. Prediabetic women (A1C of 5.7-6.4%) were compared with women with a normal first trimester A1C (< 5.7%). The primary outcome was an abnormal 2-hour, 75-g OGTT as defined by the International Association of Diabetes and Pregnancy Study Groups. Results There were 2,812 women who met inclusion criteria of whom 6.7% (n = 189) were prediabetic. Women with prediabetes were more likely to have gestational diabetes mellitus (GDM) even after adjusting for potential confounders (29.1 vs. 13.7%; adjusted relative risk, 1.48; 95% confidence interval, 1.15-1.89). There were no statistically significant differences in secondary outcomes except that women with prediabetes had less excessive gestational weight gain. A prediabetic-range A1C in the first trimester was associated with a 13% sensitivity and a 94% specificity for predicting GDM Conclusion Although women with prediabetes by first trimester A1C are significantly more likely to have GDM, the low sensitivity of an A1C in this range renders it a poor test to identify women who will develop GDM.

Racial/ethnic differences in dyslipidemia patterns.

BACKGROUND: No studies have comprehensively examined the prevalence of dyslipidemia, a major risk factor for cardiovascular disease, among diverse racial/ethnic minority groups. The primary aim of this study was to identify racial/ethnic differences in dyslipidemia among minorities including Asian Americans (Asian Indian, Chinese, Filipino, Japanese, Korean, or Vietnamese), Mexican Americans, and blacks compared with non-Hispanic whites. METHODS AND RESULTS: Using a 3-year cross section (2008-2011), we identified 169 430 active primary care patients (35 years or older) from an outpatient healthcare organization in northern California. Age-standardized prevalence rates were calculated for 3 dyslipidemia subtypes: high triglycerides (fasting laboratory value ≥150 mg/dL), low levels of high-density lipoprotein cholesterol (fasting laboratory value <40 mg/dL [men] and <50 mg/dL [women]), and high levels of low-density lipoprotein cholesterol (fasting laboratory value ≥130 mg/dL or taking low-density lipoprotein-lowering agents). Odds ratios were calculated by multivariable logistic regression, with adjustment for patient characteristics (age, measured body mass index, smoking). Compared with non-Hispanic whites, every minority subgroup had an increased prevalence of high triglycerides except blacks. Most minority groups had an increased prevalence of low high-density lipoprotein cholesterol, except for Japanese and blacks. The prevalence of high low-density lipoprotein cholesterol was increased among Asian Indians, Filipinos, Japanese, and Vietnamese compared with non-Hispanic whites. CONCLUSIONS: Minority groups, except for blacks, were more likely to have high triglyceride/low high-density lipoprotein cholesterol dyslipidemia. Further research is needed to determine how racial/ethnic differences in dyslipidemia affect racial/ethnic differences in cardiovascular disease rates.

Racial/Ethnic Differences in Gestational Diabetes Prevalence and Contribution of Common Risk Factors.

BACKGROUND: The White House, the American Heart Association, the Agency for Healthcare Research and Quality, and the National Heart, Lung and Blood Institute have all recently acknowledged the need to disaggregate Asian American subgroups to better understand this heterogeneous racial group. This study aims to assess racial/ethnic differences in relative contribution of risk factors of gestational diabetes mellitus (GDM) among Asian subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese), Hispanics, non-Hispanic blacks, and non-Hispanic whites. METHODS: Pregnant women in 2007-2012 were identified through California state birth certificate records and linked to the electronic health records in a large mixed-payer ambulatory care organisation in Northern California (n = 24 195). Relative risk and population attributable fraction (PAF) for specific racial/ethnic groups were calculated to assess the contributions of advanced maternal age, overweight/obesity (Centers for Disease Control and Prevention (CDC) standards and World Health Organization (WHO)/American Diabetes Association (ADA) body mass index cut-offs for Asians), family history of type 2 diabetes, and foreign-born status. RESULTS: GDM was most prevalent among Asian Indians (19.3%). Relative risks were similar across all race/ethnic groups. Advanced maternal age had higher PAFs in non-Hispanic whites (22.5%) and Hispanics (22.7%). Meanwhile family history (Asian Indians 22.6%, Chinese 22.9%) and foreign-borne status (Chinese 40.2%, Filipinos 30.2%) had higher PAFs in Asian subgroups. Overweight/obesity was the most important GDM risk factor for non-Hispanic whites, Hispanics, Asian Indians, and Filipinos when the WHO/ADA cut-off points were applied. Advanced maternal age was the only risk factor studied that was modified by race/ethnicity, with non-Hispanic white and Hispanic women being more adversely affected than other racial/ethnic groups. CONCLUSIONS: Overweight/obesity, advanced maternal age, family history of type 2 diabetes, and foreign-borne status are important risk factors for GDM. The relative contributions of these risk factors differ by race/ethnicity, mainly due to differences in population prevalence of these risk factors.

Diabetes Prevention and Weight Loss with a Fully Automated Behavioral Intervention by Email, Web, and Mobile Phone: A Randomized Controlled Trial Among Persons with Prediabetes.

BACKGROUND: One-third of US adults, 86 million people, have prediabetes. Two-thirds of adults are overweight or obese and at risk for diabetes. Effective and affordable interventions are needed that can reach these 86 million, and others at high risk, to reduce their progression to diagnosed diabetes. OBJECTIVE: The aim was to evaluate the effectiveness of a fully automated algorithm-driven behavioral intervention for diabetes prevention, Alive-PD, delivered via the Web, Internet, mobile phone, and automated phone calls. METHODS: Alive-PD provided tailored behavioral support for improvements in physical activity, eating habits, and factors such as weight loss, stress, and sleep. Weekly emails suggested small-step goals and linked to an individual Web page with tools for tracking, coaching, social support through virtual teams, competition, and health information. A mobile phone app and automated phone calls provided further support. The trial randomly assigned 339 persons to the Alive-PD intervention (n=163) or a 6-month wait-list usual-care control group (n=176). Participants were eligible if either fasting glucose or glycated hemoglobin A1c (HbA1c) was in the prediabetic range. Primary outcome measures were changes in fasting glucose and HbA1c at 6 months. Secondary outcome measures included clinic-measured changes in body weight, body mass index (BMI), waist circumference, triglyceride/high-density lipoprotein cholesterol (TG/HDL) ratio, and Framingham diabetes risk score. Analysis was by intention-to-treat. RESULTS: Participants' mean age was 55 (SD 8.9) years, mean BMI was 31.2 (SD 4.4) kg/m(2), and 68.7% (233/339) were male. Mean fasting glucose was in the prediabetic range (mean 109.9, SD 8.4 mg/dL), whereas the mean HbA1c was 5.6% (SD 0.3), in the normal range. In intention-to-treat analyses, Alive-PD participants achieved significantly greater reductions than controls in fasting glucose (mean -7.36 mg/dL, 95% CI -7.85 to -6.87 vs mean -2.19, 95% CI -2.64 to -1.73, P<.001), HbA1c (mean -0.26%, 95% CI -0.27 to -0.24 vs mean -0.18%, 95% CI -0.19 to -0.16, P<.001), and body weight (mean -3.26 kg, 95% CI -3.26 to -3.25 vs mean -1.26 kg, 95% CI -1.27 to -1.26, P<.001). Reductions in BMI, waist circumference, and TG/HDL were also significantly greater in Alive-PD participants than in the control group. At 6 months, the Alive-PD group reduced their Framingham 8-year diabetes risk from 16% to 11%, significantly more than the control group (P<.001). Participation and retention was good; intervention participants interacted with the program a median of 17 (IQR 14) of 24 weeks and 71.1% (116/163) were still interacting with the program in month 6. CONCLUSIONS: Alive-PD improved glycemic control, body weight, BMI, waist circumference, TG/HDL ratio, and diabetes risk. As a fully automated system, the program has high potential for scalability and could potentially reach many of the 86 million US adults who have prediabetes as well as other at-risk groups. TRIAL REGISTRATION: Clinicaltrials.gov NCT01479062; https://clinicaltrials.gov/ct2/show/NCT01479062 (Archived by WebCite at http://www.webcitation.org/6bt4V20NR).

Leading causes of death in Vietnamese Americans: An ecological study based on national death records from 2005-2020.

BACKGROUND: Disaggregated data is a cornerstone of precision health. Vietnamese Americans (VietAms) are the fourth-largest Asian subgroup in the United States (US), and demonstrate a unique burden of disease and mortality. However, most prior studies have aggregated VietAms under the broader Asian American category for analytic purposes. This study examined the leading causes of death among VietAms compared to aggregated Asian Americans and non-Hispanic Whites (NHWs) during the period 2005-2020. METHODS: Decedent data, including underlying cause of death, were obtained from the National Center for Health Statistics national mortality file from 2005 to 2020. Population denominator estimates were obtained from the American Community Survey one-year population estimates. Outcome measures included proportional mortality, age-adjusted mortality rates per 100,000 (AMR), and annual percent change (APC) in mortality over time. Data were stratified by sex and nativity status. Due to large differences in age structure, we report native- and foreign-born VietAms separately. FINDINGS: We identified 74,524 VietAm decedents over the study period (71,305 foreign-born, 3,219 native-born). Among foreign-born VietAms, the three leading causes of death were cancer (26.6%), heart disease (18.0%), and cerebrovascular disease (9.0%). Among native-born VietAms the three leading causes were accidents (19.0%), self-harm (12.0%), and cancer (10.4%). For every leading cause of death, VietAms exhibited lower mortality compared to both aggregated Asians and NHWs. Over the course of the study period, VietAms witnessed an increase in mortality in every leading cause. This effect was mostly driven by foreign-born, male VietAms. CONCLUSIONS AND RELEVANCE: While VietAms have lower overall mortality from leading causes of death compared to aggregated Asians and NHWs, these advantages have eroded markedly between 2005 and 2020. These data emphasize the importance of racial disaggregation in the reporting of public health measures.

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.

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.

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.