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      The Burden of Atherosclerotic Cardiovascular Disease in South Asians Residing in Canada: A Reflection From the South Asian Heart Alliance

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          Abstract

          South Asians (SAs), originating from the Indian subcontinent (India, Pakistan, Sri Lanka, Bangladesh, Nepal, and Bhutan), represent one quarter of the global population and are the largest visible minority in Canada. SAs experience the highest rates of coronary artery disease in Canada. Although conventional cardiovascular risk factors remain predictive in SA, the excess risk is not fully explained by these risk factors alone. Abdominal obesity, metabolic syndrome, and insulin resistance likely contribute a greater risk in SAs than in other populations. The South Asian Heart Alliance has been recently formed to investigate and recommend the best strategies for the prevention of cardiometabolic disease in SAs in Canada. This topic review represents a comprehensive overview of the magnitude of cardiovascular disease in SAs in Canada, with a review of conventional and novel risk markers in the SA population. Both primary and secondary prevention strategies are suggested and when possible, adapted specifically for the SA population. The need for SAs and their healthcare professionals to be more aware of the problem and potential solutions, along with the need for population-specific research, is highlighted.

          Résumé

          Les Asiatiques du sud originaires du sous-continent indien (Inde, Pakistan, Sri Lanka, Bangladesh, Népal et Bhoutan) représentent le quart de la population mondiale et constituent la plus importante minorité visible au Canada. C’est aussi au sein de cette population qu’on observe les taux de coronaropathie les plus élevés au Canada. Bien que les facteurs de risque cardiovasculaire classiques conservent leur valeur prédictive chez les Asiatiques du sud, ils n’expliquent pas à eux seuls le risque excédentaire observé. L’obésité abdominale, le syndrome métabolique et l’insulinorésistance constituent vraisemblablement des facteurs de risque plus importants chez les Asiatiques du sud que dans les autres populations. La South Asian Heart Alliance a récemment été mise sur pied afin d’explorer les stratégies exemplaires pour la prévention des maladies cardiométaboliques chez les Asiatiques du sud au Canada et de formuler des recommandations à cet égard. Cette revue thématique présente un aperçu de l’importance des maladies cardiovasculaires au sein de la population des Asiatiques du sud du Canada, ainsi qu’un résumé des marqueurs de risque classiques et nouveaux dans cette population. Les auteurs proposent des stratégies de prévention primaire et secondaire adaptées, dans la mesure du possible, à la population des Asiatiques du sud. Ils font également ressortir l’importance de sensibiliser davantage les Asiatiques du sud et les professionnels de la santé aux risques et aux solutions possibles, ainsi que la nécessité de mener des recherches axées sur cette population particulière.

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          Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci.

          We carried out a genome-wide association study of type-2 diabetes (T2D) in individuals of South Asian ancestry. Our discovery set included 5,561 individuals with T2D (cases) and 14,458 controls drawn from studies in London, Pakistan and Singapore. We identified 20 independent SNPs associated with T2D at P < 10(-4) for testing in a replication sample of 13,170 cases and 25,398 controls, also all of South Asian ancestry. In the combined analysis, we identified common genetic variants at six loci (GRB14, ST6GAL1, VPS26A, HMG20A, AP3S2 and HNF4A) newly associated with T2D (P = 4.1 × 10(-8) to P = 1.9 × 10(-11)). SNPs at GRB14 were also associated with insulin sensitivity (P = 5.0 × 10(-4)), and SNPs at ST6GAL1 and HNF4A were also associated with pancreatic beta-cell function (P = 0.02 and P = 0.001, respectively). Our findings provide additional insight into mechanisms underlying T2D and show the potential for new discovery from genetic association studies in South Asians, a population with increased susceptibility to T2D.
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            Hypertension Canada’s 2018 Guidelines for Diagnosis, Risk Assessment, Prevention, and Treatment of Hypertension in Adults and Children

            Hypertension Canada provides annually updated, evidence-based guidelines for the diagnosis, assessment, prevention, and treatment of hypertension in adults and children. This year, the adult and pediatric guidelines are combined in one document. The new 2018 pregnancy-specific hypertension guidelines are published separately. For 2018, 5 new guidelines are introduced, and 1 existing guideline on the blood pressure thresholds and targets in the setting of thrombolysis for acute ischemic stroke is revised. The use of validated wrist devices for the estimation of blood pressure in individuals with large arm circumference is now included. Guidance is provided for the follow-up measurements of blood pressure, with the use of standardized methods and electronic (oscillometric) upper arm devices in individuals with hypertension, and either ambulatory blood pressure monitoring or home blood pressure monitoring in individuals with white coat effect. We specify that all individuals with hypertension should have an assessment of global cardiovascular risk to promote health behaviours that lower blood pressure. Finally, an angiotensin receptor-neprilysin inhibitor combination should be used in place of either an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker in individuals with heart failure (with ejection fraction < 40%) who are symptomatic despite appropriate doses of guideline-directed heart failure therapies. The specific evidence and rationale underlying each of these guidelines are discussed.
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              BMI Cut Points to Identify At-Risk Asian Americans for Type 2 Diabetes Screening

              Asian American Population According to the U.S. Census Bureau, an Asian is a person with origins from the Far East (China, Japan, Korea, and Mongolia), Southeast Asia (Cambodia, Malaysia, the Philippine Islands, Thailand, Vietnam, Indonesia, Singapore, Laos, etc.), or the Indian subcontinent (India, Pakistan, Bangladesh, Bhutan, Sri Lanka, and Nepal); each region has several ethnicities, each with a unique culture, language, and history. In 2011, 18.2 million U.S. residents self-identified as Asian American, with more than two-thirds foreign-born (1). In 2012, Asian Americans were the nation’s fastest-growing racial or ethnic group, with a growth rate over four times that of the total U.S. population. International migration has contributed >60% of the growth rate in this population (1). Among Asian Americans, the Chinese population was the largest (4.0 million), followed by Filipinos (3.4 million), Asian Indians (3.2 million), Vietnamese (1.9 million), Koreans (1.7 million), and Japanese (1.3 million). Nearly three-fourths of all Asian Americans live in 10 states—California, New York, Texas, New Jersey, Hawaii, Illinois, Washington, Florida, Virginia, and Pennsylvania (1). By 2060, the Asian American population is projected to more than double to 34.4 million, with its share of the U.S. population climbing from 5.1 to 8.2% in the same period (2). Overweight/Obesity and Type 2 Diabetes Risk for Asian Americans Although it is clear that increased body weight is a risk factor for type 2 diabetes, the relationship between body weight and type 2 diabetes is more properly attributable to the quantity and distribution of body fat (3–5). Abdominal circumference and waist and hip measurements, although highly correlated with cardiometabolic risk (6,7), do not differentiate subcutaneous from visceral adipose abdominal depots and are subject to interobserver variability. Imaging and other approaches can be used to more accurately assess fat distribution and quantify adiposity (4,8), but they are not readily available, economical, or useable on a large scale. Therefore, the measurement of body weight with various corrections for height is frequently used to assess risk for obesity-related diseases because it is the most economical and practical approach in both clinical and epidemiologic settings (9). The most commonly used measure is Quetelet’s index or BMI, defined as weight ÷ height2, with weight in kilograms and height in meters. However, BMI does not take into account the relative proportions of fat and lean tissue and cannot distinguish the location of fat distribution (10,11). The clinical value of measuring BMI from a diabetes diagnosis perspective lies in whether this measure can identify individuals who may have undiagnosed diabetes or may be at increased future risk for diabetes. In addition, measuring BMI also is important for managing diabetes for the purpose of weight control. BMI cutoffs have been established to identify overweight (BMI ≥25 kg/m2) or obese (BMI ≥30 kg/m2) individuals (12). However, these are based on information derived from the general population, based on risk of mortality, without consideration for racial or ethnic specificity and were not determined to specifically identify those at risk for diabetes. Recently, the U.S. Centers for Disease Control and Prevention presented initial findings from an oversampling of Asian Americans in the 2011–2012 National Health and Nutrition Examination Survey. These data, utilizing general population criteria for obesity, showed the prevalence of obesity in Asian Americans was only 10.8% compared with 34.9% in all U.S. adults (13). Paradoxically, many studies from Asia, as well as research conducted in several Asian American populations, have shown that diabetes risk has increased remarkably in populations of Asian origin, although in general these populations have a mean BMI significantly lower than defined at-risk BMI levels (14,15). Moreover, U.S. clinicians who care for Asian patients have noticed that many with diabetes do not meet the published criteria for obesity or even overweight (16). Epidemiologic studies have shown that there is a relationship between BMI and diabetes risk in Asians, but this risk is shifted to lower BMI values (17). At similar BMI levels, diabetes prevalence has been identified as higher in Asians compared with whites (18). This paradox may be partly explained by a difference in body fat distribution: there is a propensity for Asians to develop visceral versus peripheral adiposity, which is more closely associated with insulin resistance and type 2 diabetes than overall adiposity (19). Additionally, Asians of both sexes have been shown to have a higher percentage of body fat at any given BMI level compared with non-Hispanic whites; this suggests differences in body composition that may contribute to variations in diabetes prevalence (10). Defining the Issue The established definitions of at-risk BMI for overweight and obesity appear to be inappropriate for defining diabetes risk in Asian Americans. Thus, there is a need to examine the existing literature to determine what might constitute at-risk BMI levels for Asian Americans. The clinical relevance is to clarify the use of BMI as a simple initial screening tool to identify Asian Americans who may have diabetes (diagnosis) or be at risk for future diabetes (to implement prevention measures). Also of importance is the use of specific BMI cut points to identify Asian Americans who are eligible for weight-reduction services or treatment reimbursable by payers. Available data from Asia support the notion that Asians are already at risk for many obesity-related disorders even if they do not reach the BMI values associated with overweight or obesity in non-Asian populations (14). Population-wide weight gain is occurring throughout Asia. This has been attributed to environmental influences such as dietary changes and reductions in physical activity commonly associated with living in a Western culture (17). However, the impact of actually living in a Western culture may be different or more adverse than the effect of living in the native homeland and experiencing some of the lifestyle features representative of a Western culture. Rather than relying on hypothetical influences surmised from data from Asia, it is better therefore to directly examine the relationship of BMI to metabolic disorders such as type 2 diabetes among Asians living in the U.S. Although the U.S. Census has historically combined Asians, Native Hawaiians, and other Pacific Islanders, there are significant differences in physiology and body composition between Asians and the other two groups, so this review will focus only on examining studies in Asian Americans. Asian American Studies of Type 2 Diabetes and Overweight/Obesity Prospective cohort or longitudinal studies are the most suitable designs to measure type 2 diabetes incidence and delineate the relationship between BMI and diabetes. This research requires clinical ascertainment of BMI and nondiabetic status at baseline, followed by periodic reascertainment for a defined follow-up period or until diabetes is diagnosed. Glucose tolerance status should be evaluated by blood test, preferably including a 2-h 75-g oral glucose tolerance test (OGTT). This recommendation is based on numerous studies, including research on Asian Americans, indicating that OGTT detects a greater number of individuals with diabetes compared with fasting glucose criteria (20–22). This type of longitudinal study design enables 1) identification of baseline BMI values associated with increased diabetes risk over a defined follow-up and 2) capture of BMI data at the earliest time point following diabetes diagnosis. The sensitivity and specificity of BMI cut points can then be identified using analytic techniques such as receiver operating characteristic curves or rate of misclassification. Historically, such prospective cohort data are uncommon in Asian American populations. The majority of peer-reviewed publications on diabetes among Asian Americans are cross-sectional studies in which BMI, calculated from self-reported weight and height, and diabetes status are assessed simultaneously. In 2004, data from the Behavioral Risk Factor Surveillance System (BRFSS) showed that the odds of prevalent diabetes were 60% higher for Asian Americans than non-Hispanic whites after adjusting for BMI, age, and sex (23). The National Health Interview Survey (NHIS; 1997–2008 data) (24) found that the odds of prevalent diabetes were 40% higher in Asian Americans relative to non-Hispanic whites after adjusting for differences in age and sex. In fully adjusted logistic regression models including an adjustment for BMI as a categorical variable (underweight/normal weight: BMI 55 years, incident diabetes was not associated with baseline BMI. In participants ≤55 years of age, the 5-year relative risk of diabetes associated with BMI was 26.5 (95% CI 3.4−204) but was 0.8 (95% CI 0.4−1.7) for those >55 years of age. Thus in this analysis at 5 years, BMI predicted risk for diabetes in Japanese Americans ≤55 years of age but not in those >55 years of age. In a subsequent analysis of 424 initially nondiabetic Japanese Americans who were followed for additional 5 years (total of 10 years), 74 developed diabetes (36). Those developing diabetes had a mean BMI of 25.4 ± 3.7 kg/m2, while those who remained nondiabetic had a mean BMI of 23.8 ± 3.1 kg/m2. The odds of incident diabetes for a 1 SD increase in BMI were 1.57 (95% CI 1.23−2.02). Thus, these two studies indicate that BMI is a significant risk factor for incident diabetes in Japanese Americans and that the BMI levels at which diabetes develops are quite low. However, neither report provided an inflection point for BMI at which risk was significantly increased. A multiethnic cohort study identified nondiabetic adults in Ontario, Canada, using Statistics Canada’s 1996 National Population Health Survey and the Canadian Community Health Survey (31). Survey participants living in Ontario, aged ≥30 years at the time of survey, and who self-reported as South Asian (n = 1,001) or Chinese (n = 866) comprised the Asian cohorts and were followed for a median of 6 years. Also included were blacks (n = 747) and non-Hispanic whites (n = 57,210). BMI was based on self-reported weight and height at baseline, and incident diabetes cases were ascertained through record linkage with the population-based Ontario Diabetes Database using a validated administrative data algorithm. Participants were followed from the survey interview date to the date of diabetes diagnosis, death, or at the end of the study. At baseline, mean BMI was 24.6 kg/m2 among South Asians, 22.6 kg/m2 among Chinese, 26.1 kg/m2 among blacks, and 26.1 kg/m2 among non-Hispanic whites. Researchers found that incident diabetes risk, adjusted for age, sex, sociodemographic characteristics, and BMI, was significantly higher for South Asians (20.8/1,000 person-years; HR 3.40), blacks (16.3/1,000; 1.99), and Chinese (9.3/1,000; 1.87), compared with non-Hispanic whites (9.5/1,000). The BMI cutoff value at which diabetes incidence was equivalent to BMI 30 kg/m2 for non-Hispanic whites was estimated at 24 kg/m2 for South Asians, 25 kg/m2 for Chinese, and 26 kg/m2 for blacks. Additionally, the median age at diagnosis was younger for South Asians (49 years) and Chinese (55 years) compared with blacks (57 years) and non-Hispanic whites (58 years). Last, the Multiethnic Cohort (32) in Hawaii included non-Hispanic whites, Native Hawaiians, and Japanese Americans. The Hawaii data from this cohort were linked to two diabetes care registries (Blue Cross/Blue Shield and Kaiser Permanente Hawaii). Incident type 2 diabetes was identified by self-report of medical conditions between 1999 and 2003, a medication questionnaire, and linkage with health insurance plans in 2007. Native Hawaiians had the highest incidence (15.5/1,000 person-years), followed by Japanese Americans (12.5/1,000), while non-Hispanic whites had the lowest incidence (5.8 cases/1,000). The authors compared the HR of incident diabetes at different BMI cut points for each racial/ethnic group and found that Japanese Americans had a significantly higher incidence of diabetes at BMI 22.0–24.9 kg/m2 than Hawaiians or non-Hispanic whites. Diabetes risk for Japanese Americans was higher than for non-Hispanic whites at all BMI levels. Even at BMI cut points of <22 kg/m2 and 22.0−24.9 kg/m2, respectively, HRs were higher among Japanese Americans compared with non-Hispanic whites at BMI cut points of 25.0−29.9 kg/m2. New Cross-sectional Analysis Most recently, in an effort to ascertain the lowest BMI cut point that might be practical for identifying Asian American adults (aged ≥45 years) with previously undiagnosed type 2 diabetes, a group of investigators presented a new analysis at the 2014 Scientific Sessions of the American Diabetes Association (ADA) based on combined data from four cohort studies (39).The data set included participants without a prior diabetes diagnosis, aged ≥45 years, with no non-Asian admixture. Participant data were obtained from the University of California San Diego Filipino Health Study, San Diego, CA (n = 421); North Kohala Study, Hawaii, HI (n = 115 Filipinos, 129 Japanese, 18 other Asian); Seattle Japanese-American Community Diabetes Study, Seattle, WA (n = 371); and the Mediators of Atherosclerosis in South Asians Living in America (MASALA), San Francisco, CA, and Chicago, IL (n = 609). All 1,663 participants underwent 2-h 75-g OGTT, and diabetes diagnosis was based on ADA 2014 criteria (40). In the total sample, a BMI ≥26 kg/m2 cut point had the lowest misclassification rate (false-positive + false-negative rates) and highest Youden’s index (sensitivity + specificity −1). Sensitivity approximated specificity at BMI ≥25.4 kg/m2; however, limiting screening at BMI ≥25 kg/m2 would miss 36% of Asian Americans with newly diagnosed type 2 diabetes. In the same study, Araneta et al. (39) found that screening Asian Americans at a BMI cut point of ≥23.5 kg/m2 identified approximately 80% of those with undiagnosed type 2 diabetes. Among Japanese Americans, lowering the BMI screening cut point to ≥22.8 kg/m2 achieved 80% sensitivity. The same study also showed that limiting screening to HbA1c ≥6.5% fails to identify almost half of Asian Americans with diabetes and 44% who had isolated postchallenge hyperglycemia would be missed without an OGTT. Conclusions This comprehensive review and analysis of the association between BMI and diabetes in Asian Americans illustrates that Asian Americans have a higher prevalence of type 2 diabetes at relatively lower BMI cut points than whites. Given that established BMI cut points indicating elevated diabetes risk are inappropriate for Asian Americans, establishing a specific BMI cut point to identify Asian Americans with or at risk for future diabetes would be beneficial to the potential health of millions of Asian American individuals. Generally, the rationale behind the conventional BMI cut point has been the observation that overweight and obese adults (18 years of age or older) with a BMI of ≥25 kg/m2 have increased risks of both morbidity and mortality. Adults who meet or exceed the 25 kg/m2 BMI threshold are at increased risk of developing coronary heart disease, hypertension, hypercholesterolemia, type 2 diabetes, and other diseases, in addition to showing increases in mortality (41). However, while the studies reviewed herein do indicate increased diabetes prevalence among Asian Americans with BMIs below the 25 kg/m2 threshold, a recent study (42) found no evidence to suggest an increased risk of total mortality among Asian Americans within the BMI range of 20 to <25 kg/m2. Therefore, it is important to note that the aim of this position statement is not to redefine BMI cut points that constitute overweight and obesity thresholds as they relate to mortality or morbidity in Asian Americans. Instead, the intent is to clarify how to use BMI as a simple initial screening tool to identify Asian Americans who may have diabetes or be at risk for future diabetes. The question being considered is the most appropriate BMI cut point indicative of elevated risk of diabetes in Asian Americans. Historically, there has been a general acknowledgment that a BMI cutoff point lower than 25 kg/m2 would increase the likelihood of identifying diabetes or diabetes risk in Asians. Thus in the Diabetes Prevention Program (DPP), a BMI value of 22 kg/m2 was selected as the eligibility BMI for Asians (43). The 2014 ADA “Standards of Medical Care in Diabetes” (40) indicates that there is compelling evidence that lower BMI cut points, specifically BMI cutoff value of 24 kg/m2 in South Asians and 25 kg/m2 in Chinese, denote increased diabetes risk in some racial and ethnic groups, although the ADA Standards fall short of identifying an exact cut point. However in 2000, a group cosponsored jointly by the Regional Office for the Western Pacific (WPRO) of the World Health Organization, the International Association for the Study of Obesity, and the International Obesity Task Force published in an extensive monograph a recommendation that the BMI value to denote overweight in Asians should be ≥23 kg/m2 and ≥25 kg/m2 for obesity (44). Subsequently, the World Health Organization consultation group identified potential public health action points along the BMI continuum ranging from 23.0 to 27.5 kg/m2 and proposed that each country make decisions regarding the definitions of increased risk for its population (45). They did not identify an exact cut point. In addition, some Asian countries have taken steps to set new BMI obesity cut points for their populations. In 1992, the Japan Society for the Study of Obesity (JASSO) decided to define BMI ≥25 kg/m2 as obesity (46). In China, a BMI of 24 kg/m2 was found to have the best sensitivity and specificity for risk-factor identification and was recommended as the cutoff point for overweight. A BMI of 28 kg/m2 was found to identify risk factors with specificity approximately 90% and was recommended as the cutoff point for obesity (47). Likewise, the diagnostic cutoff for overweight BMI in India (48) is 23 kg/m2. Determining the optimal BMI cut point for identifying Asian Americans at elevated risk for diabetes is complex. There is tremendous heterogeneity among the Asian American subgroups. For example, data from the DISTANCE study might suggest a conventional BMI cut point of 25 kg/m2 as an acceptable threshold (29), especially for South Asians and Southeast Asians. In contrast, the Women’s Health Initiative (28), the Seattle Japanese-American Community Diabetes Study (36), the multiethnic cohort study from Canada (31), and the Multiethnic Cohort in Hawaii (32) would lend support to lowering the BMI cut point, especially for East Asians (Chinese and Japanese). In light of the diabetes epidemic, there is an urgent need to increase early detection and activate the at-risk public toward diabetes prevention. Adopting a single lower and uniform BMI cut point for Asian Americans would serve to increase opportunities for education, intervention, behavior and lifestyle change, and diagnosis. In support of this approach, data from Araneta et al. (39) suggest that for diabetes screening purposes BMI cut points with a sensitivity of 80% fall consistently between 23–24 kg/m2 for nearly all Asian American subgroups (with levels slightly lower for Japanese). This makes a rounded cut point of 23 kg/m2 practical. In determining a single BMI cut point, it is important to balance sensitivity and specificity so as to provide a valuable screening tool without numerous false positives. Furthermore, for a screening tool to be most valuable, it must be at least as useful as other commonly available tools. A BMI cut point of 23 kg/m2 will have greater sensitivity than the ADA general screening questionnaire’s (ADA Type 2 Diabetes Risk Test) sensitivity of 70–80% (49). An argument can be made to push the BMI cut point to lower than 23 kg/m2 in favor of even further increased sensitivity. However, this would lead to an unacceptably low specificity (13.1%) (39). The authors of this position statement propose that the analysis of BMI and diabetes in Asian Americans and subsequent recommendation of an Asian American−specific BMI cut point of 23 kg/m2 for diabetes screening in the U.S. have the advantage of being predicated on available data for Asian Americans, not Asian country data. In this way, this recommendation takes into consideration not only genetic and physiologic factors but also environmental and lifestyle context. Further, it is based on a comprehensive review of available literature with focus on longitudinal studies and includes data from several large Asian American subgroups. However, the analysis is limited in several ways. First, no uniform method of diagnosis was used in the studies upon which this recommendation is based. Diagnostic methods ranged from medication usage data, self-report, HbA1c, fasting blood glucose, and OGTT. Studies using diagnostic methods other than OGTT might have understated diabetes prevalence (20–22,39). Second, some studies were not based on BMI data available at the time of incident diabetes. Rather, most studies reported the association between baseline BMI and diabetes diagnosis, with these measurements as much as 5–10 years apart in some instances. Therefore, these data do not accurately reflect the relationship of BMI to diabetes diagnosis at the time of diagnosis. Third, the number of robust studies is limited. Additional research will help to further elucidate current findings on the relationship between BMI and incident diabetes in Asian Americans. Fourth, while some data exist for several Asian ethnic subgroups, insufficient disaggregated data are available for many of the Asian ethnic groups that comprise this very heterogeneous population. Much is known about how to prevent diabetes for those at risk (primary prevention) and about how to prevent or reduce complications in those with diabetes (secondary prevention). Diabetes is no longer the same life-threatening, life-limiting condition it was a century or even several decades ago. However, without increased prevention and early diagnosis the benefits of these strategies will not be fully realized. Because Asian Americans’ risk for diabetes is under-recognized based on the existing BMI criteria, this population may not be afforded the same opportunity as others for increased prevention and early diagnosis. It is imperative to better screen and diagnose America’s fastest-growing ethnic group based on the BMI cut point that more appropriately applies to them. While more research is needed to identify better risk markers than BMI and future research efforts will undoubtedly bring us closer to understanding the metabolic profiles of specific ethnic subgroups, with the subsequent development of appropriate personalized medicine, there is an urgent need for action now, even in the absence of perfect data. ADA Recommendation Testing for diabetes should be considered for all Asian American adults who present with a BMI of ≥23 kg/m2.
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                Author and article information

                Contributors
                Journal
                CJC Open
                CJC Open
                CJC Open
                Elsevier
                2589-790X
                30 October 2019
                November 2019
                30 October 2019
                : 1
                : 6
                : 271-281
                Affiliations
                [a ]Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, Alberta, Canada
                [b ]Department of Medicine, McMaster University, Hamilton, and Canadian Collaborative Research Network, Brampton, Ontario, Canada
                [c ]Department of Cardiac Sciences, Division of Cardiac Surgery, University of Calgary, Calgary, Alberta, Canada
                [d ]Division of Cardiology, Department of Medicine, New York University School of Medicine, New York, New York, USA
                [e ]Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario
                [f ]Division of Cardiology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
                [g ]Nursing and Community Health Sciences, University of Calgary, Calgary, Canada
                [h ]Department of Medicine, University of British Columbia, Vancouver, Canada
                [i ]Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
                [j ]Department of Pathology and Molecular Medicine, Department of Clinical Epidemiology and Biostatistics, Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
                [k ]Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
                [l ]Division of Endocrinology, University of Toronto, Toronto, Ontario, Canada
                Author notes
                []Corresponding author: Dr Kevin R. Bainey, Mazankowski Alberta Heart Institute, University of Alberta, 2C2.12 WMC, 8440 112 St, Edmonton, Alberta T6G 2B7, Canada. Tel.: +1-780-407-2176; fax: +1-780-4076452. Kevin.Bainey@ 123456albertahealthservices.ca
                [‡]

                These authors share first authorship.

                Article
                S2589-790X(19)30062-9
                10.1016/j.cjco.2019.09.004
                7063609
                32159121
                55b39b3f-df19-415c-a3b4-2d940941f3c8
                © 2019 Canadian Cardiovascular Society. Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 12 August 2019
                : 25 September 2019
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