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      Prevalence of Diabetes by Race and Ethnicity in the United States, 2011-2016

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          Abstract

          During 2011-2016, how prevalent was diabetes among major race/ethnicity groups and subgroups of Hispanic and non-Hispanic Asian adults in the United States? In this cross-sectional study that included 7575 adults, the age- and sex-adjusted diabetes prevalence was 12.1% for non-Hispanic white, 20.4% for non-Hispanic black, 22.1% for Hispanic, and 19.1% for non-Hispanic Asian groups. The diabetes prevalence also differed significantly among Hispanic or non-Hispanic Asian subgroups. In the United States in 2011-2016, the prevalence of diabetes varied across racial/ethnic groups. The prevalence of diabetes among Hispanic and Asian American subpopulations in the United States is unknown. To estimate racial/ethnic differences in the prevalence of diabetes among US adults 20 years or older by major race/ethnicity groups and selected Hispanic and non-Hispanic Asian subpopulations. National Health and Nutrition Examination Surveys, 2011-2016, cross-sectional samples representing the noninstitutionalized, civilian, US population. The sample included adults 20 years or older who had self-reported diagnosed diabetes during the interview or measurements of hemoglobin A 1c (HbA 1c ), fasting plasma glucose (FPG), and 2-hour plasma glucose (2hPG). Race/ethnicity groups: non-Hispanic white, non-Hispanic black, Hispanic and Hispanic subgroups (Mexican, Puerto Rican, Cuban/Dominican, Central American, and South American), non-Hispanic Asian and non-Hispanic Asian subgroups (East, South, and Southeast Asian), and non-Hispanic other. Diagnosed diabetes was based on self-reported prior diagnosis. Undiagnosed diabetes was defined as HbA 1c 6.5% or greater, FPG 126 mg/dL or greater, or 2hPG 200 mg/dL or greater in participants without diagnosed diabetes. Total diabetes was defined as diagnosed or undiagnosed diabetes. The study sample included 7575 US adults (mean age, 47.5 years; 52% women; 2866 [65%] non-Hispanic white, 1636 [11%] non-Hispanic black, 1952 [15%] Hispanic, 909 [6%] non-Hispanic Asian, and 212 [3%] non-Hispanic other). A total of 2266 individuals had diagnosed diabetes; 377 had undiagnosed diabetes. Weighted age- and sex-adjusted prevalence of total diabetes was 12.1% (95% CI, 11.0%-13.4%) for non-Hispanic white, 20.4% (95% CI, 18.8%-22.1%) for non-Hispanic black, 22.1% (95% CI, 19.6%-24.7%) for Hispanic, and 19.1% (95% CI, 16.0%-22.1%) for non-Hispanic Asian adults (overall P  < .001). Among Hispanic adults, the prevalence of total diabetes was 24.6% (95% CI, 21.6%-27.6%) for Mexican, 21.7% (95% CI, 14.6%-28.8%) for Puerto Rican, 20.5% (95% CI, 13.7%-27.3%) for Cuban/Dominican, 19.3% (95% CI, 12.4%-26.1%) for Central American, and 12.3% (95% CI, 8.5%-16.2%) for South American subgroups (overall P  < .001). Among non-Hispanic Asian adults, the prevalence of total diabetes was 14.0% (95% CI, 9.5%-18.4%) for East Asian, 23.3% (95% CI, 15.6%-30.9%) for South Asian, and 22.4% (95% CI, 15.9%-28.9%) for Southeast Asian subgroups (overall P  = .02). The prevalence of undiagnosed diabetes was 3.9% (95% CI, 3.0%-4.8%) for non-Hispanic white, 5.2% (95% CI, 3.9%-6.4%) for non-Hispanic black, 7.5% (95% CI, 5.9%-9.1%) for Hispanic, and 7.5% (95% CI, 4.9%-10.0%) for non-Hispanic Asian adults (overall P  < .001). In this nationally representative survey of US adults from 2011 to 2016, the prevalence of diabetes and undiagnosed diabetes varied by race/ethnicity and among subgroups identified within the Hispanic and non-Hispanic Asian populations. This national survey study uses National Health and Nutrition Examination Survey (NHANES) 2011-2016 data to estimate differences in the prevalence of diagnosed and undiagnosed diabetes among US adults 20 years or older by major race/ethnicity groups and selected Hispanic and non-Hispanic Asian subpopulations.

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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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            Contributions of  -Cell Dysfunction and Insulin Resistance to the Pathogenesis of Impaired Glucose Tolerance and Impaired Fasting Glucose

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              Short-term variability in measures of glycemia and implications for the classification of diabetes.

              Short-term variability in measures of glycemia has important implications for the diagnosis of diabetes mellitus and the conduct and interpretation of epidemiologic studies. Our objectives were to characterize the within-person variability in fasting glucose, 2-hour glucose, and hemoglobin A1c (HbA1c) levels and to assess the impact of using repeated measurements for classification of diabetes. We analyzed repeated measurements from 685 fasting participants without diagnosed diabetes from the National Health and Nutrition Examination Survey III Second Examination, a substudy conducted from 1988 to 1994 in which repeated examinations were conducted approximately 2 weeks after the original examination. Two-hour glucose levels had substantially more variability (within-person coefficient of variation [CV(w)], 16.7%; 95% confidence interval [CI], 15.0 to 18.3) compared with either fasting glucose (CV(w), 5.7%; 95% CI, 5.3 to 6.1) or HbA1c (CV(w,) 3.6%; 95% CI, 3.2 to 4.0) levels. The proportion of persons with a fasting glucose level of 126 mg/dL or higher (to convert to millimoles per liter, multiply by 0.0555) on the first test who also had a second glucose level of 126 mg/dL or higher was 70.4% (95% CI, 49.8% to 86.2%). Results were similar using the 2-hour glucose cutoff point of 140 mg/dL or higher. The prevalence of undiagnosed diabetes using a single fasting glucose level of 126 mg/dL or higher was 3.7%. If a second fasting glucose level of 126 mg/dL or higher was used to confirm the diagnosis (American Diabetes Association guidelines), the prevalence decreased to 2.8% (95% CI, 1.5% to 4.0%), a 24.4% decrease. We found high variability in 2-hour glucose levels relative to fasting glucose levels and high variability in both of these relative to HbA1c levels. Our findings suggest that studies that strictly apply guidelines for the diagnosis of diabetes (2 glucose measurements) may arrive at substantially different prevalence estimates compared with studies that use only a single measurement.
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                Author and article information

                Journal
                JAMA
                JAMA
                American Medical Association (AMA)
                0098-7484
                December 24 2019
                December 24 2019
                : 322
                : 24
                : 2389
                Affiliations
                [1 ]National Center for Chronic Disease Prevention and Health Promotion, Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
                [2 ]Division of General Internal Medicine, University of California, San Francisco
                [3 ]University of California, San Diego, La Jolla
                [4 ]Emory University, Atlanta, Georgia
                [5 ]Imperial College London, London, United Kingdom
                [6 ]University of Washington, Seattle
                Article
                10.1001/jama.2019.19365
                6990660
                31860047
                c678fd08-e3a4-4bd7-87f6-e8a2c6478e4a
                © 2019
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