Nonlaboratory-Based Risk Assessment Algorithm for Undiagnosed Type 2 Diabetes Developed on a Nation-Wide Diabetes Survey

OBJECTIVE

To develop a New Chinese Diabetes Risk Score for screening undiagnosed type 2 diabetes in China.

RESEARCH DESIGN AND METHODS

Data from the China National Diabetes and Metabolic Disorders Study conducted from June 2007 to May 2008 comprising 16,525 men and 25,284 women aged 20–74 years were analyzed. Undiagnosed type 2 diabetes was detected based on fasting plasma glucose ≥7.0 mmol/L or 2-h plasma glucose ≥11.1 mmol/L in people without a prior history of diabetes. β-Coefficients derived from a multiple logistic regression model predicting the presence of undiagnosed type 2 diabetes were used to calculate the New Chinese Diabetes Risk Score. The performance of the New Chinese Diabetes Risk Score was externally validated in two studies in Qingdao: one is prospective with follow-up from 2006 to 2009 (validation 1) and another cross-sectional conducted in 2009 (validation 2).

RESULTS

The New Chinese Diabetes Risk Score includes age, sex, waist circumference, BMI, systolic blood pressure, and family history of diabetes. The score ranges from 0 to 51. The area under the receiver operating curve of the score for undiagnosed type 2 diabetes was 0.748 (0.739–0.756) in the exploratory population, 0.725 (0.683–0.767) in validation 1, and 0.702 (0.680–0.724) in validation 2. At the optimal cutoff value of 25, the sensitivity and specificity of the score for predicting undiagnosed type 2 diabetes were 92.3 and 35.5%, respectively, in validation 1 and 86.8 and 38.8% in validation 2.

CONCLUSIONS

The New Chinese Diabetes Risk Score based on nonlaboratory data appears to be a reliable screening tool to detect undiagnosed type 2 diabetes in Chinese population.Prevalence of type 2 diabetes is increasing dramatically worldwide. In China, the prevalence of type 2 diabetes increased from 5.5% in 2000–2001 (1) to 9.7% in 2007–2008 (2). Nearly 60% of individuals with type 2 diabetes had not been diagnosed previously (2). Mortality in individuals with previously undiagnosed type 2 diabetes was, however, as high as in those with known type 2 diabetes; both were higher than in people without type 2 diabetes (3). Obesity, hypertension, and dyslipidemia are also frequently clustered in an individual with undiagnosed type 2 diabetes (2,4,5). Early detection of type 2 diabetes and intervention may reduce exposure to long-term hyperglycemia and prevent or delay chronic diabetes complications. The currently used diagnostic tool for type 2 diabetes is 75-g oral glucose tolerance test (OGTT) and A1C (6). The OGTT is, however, time consuming, and the fasting status cannot be assured. The A1C test is less standard and relatively expensive. Consequently, their use in mass screening has been limited. Risk score developed based on demographic, anthropometric, and clinical information without a laboratory test has been proved to be a useful and cheap tool for a stepwise screening strategy for undiagnosed type 2 diabetes (7–17). This approach is particularly useful in China, considering a large population and an already high and still increasing prevalence of undiagnosed type 2 diabetes.A simple Chinese diabetes risk score has been reported based on data collected in Qingdao (7). Considering the diversity in economic development, culture, living environment, and dietary factors in different areas of China, we tried to develop a New Chinese Diabetes Risk Score for undiagnosed type 2 diabetes using the data of the China National Diabetes and Metabolic Disorders Study (exploratory population) that was conducted in 12 provinces and autonomous regions in addition to the municipalities of Beijing and Shanghai from June 2007 to May 2008. The performance of the New Chinese Diabetes Risk Score developed in this study is validated in two external studies in Qingdao. One of the two studies is prospective (validation 1) and the other cross-sectional (validation 2). The results of the validation of the indexed score are also compared with previously published diabetes risk scores that derived from Chinese (7), Caucasian (9,11,13,14,18), and other Asian populations (15,16,19,20).     

Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes

OBJECTIVE

Health administrative data are frequently used for diabetes surveillance, but validation studies are limited, and undiagnosed diabetes has not been considered in previous studies. We compared the test properties of an administrative definition with self-reported diabetes and estimated prevalence of undiagnosed diabetes by measuring glucose levels in mailed-in capillary blood samples.

RESEARCH DESIGN AND METHODS

A stratified random sample of 6,247 individuals (Quebec province) was surveyed by telephone and asked to mail in fasting blood samples on filter paper to a central laboratory. An administrative definition was applied (two physician claims or one hospitalization for diabetes within a 2-year period) and compared with self-reported diabetes alone and with self-reported diabetes or elevated blood glucose level (≥7 mmol/L). Population-level prevalence was estimated with the use of the administrative definition corrected for its sensitivity and specificity.

RESULTS

Compared with self-reported diabetes, sensitivity and specificity were 84.3% (95% CI 79.3–88.5%) and 97.9% (97.4–98.4%), respectively. Compared with diabetes by self-report and/or glucose testing, sensitivity was lower at 58.2% (52.2–64.6%), whereas specificity was similar at 98.7% (98.0–99.3%). Adjusted for sampling weights, population-level prevalence of physician-diagnosed diabetes was 7.2% (6.3–8.0%). Prevalence of total diabetes (physician-diagnosed and undiagnosed) was 13.4% (11.7–15.0%), indicating that ∼40% of diabetes cases are undiagnosed.

CONCLUSIONS

A substantial proportion of diabetes cases are missed by surveillance methods that use health administrative databases. This finding is concerning because individuals with undiagnosed diabetes are likely to have a delay in treatment and, thus, a higher risk for diabetes-related complications.The rapid rise in diabetes incidence and prevalence is placing substantial strains on health care systems in terms of management of both the disease itself and its complications (1). Accurate disease surveillance, therefore, is critical to making proper projections of health care needs and costs. In Canada, the National Diabetes Surveillance System (NDSS) tracks diabetes prevalence through physician billing and hospital admissions databases (2–4). Similar algorithms have been used in the U.S. and other countries (3,5–12). Although these administrative health database definitions have been validated through medical record (4,13), survey (4,6,8,14,15), and medication use data (4,10,16), no validation study of claims-based administrative algorithms has accounted for previously undiagnosed diabetes.In the current study, we validated an administrative database diabetes definition and estimated the prevalence of physician-diagnosed diabetes through a population-based health survey. We used a novel approach to estimate the prevalence of undiagnosed diabetes that involved mailed-in capillary blood samples in which fasting glucose levels were measured at a central laboratory. Finally, by using survey data and glucose levels to correct the administrative database diabetes definition, we estimated the actual diabetes prevalence and compared this with what would have been estimated by the uncorrected definition.     

GHb Level and Subsequent Mortality Among Adults in the U.S.

OBJECTIVE

To examine the association of hyperglycemia, as measured by GHb, with subsequent mortality in a nationally representative sample of adults.

RESEARCH DESIGN AND METHODS

We included adults aged ≥20 years who participated in Third National Health and Nutrition Examination Survey (1988–1994) and had complete information, including baseline diabetes status by self-report and measured GHb (n = 19,025) and follow-up through the end of 2000 for mortality.

RESULTS

In the overall population, higher levels of GHb were associated with increased risk of mortality from all causes, heart disease, and cancer. After adjustment for potential risk factors, the relative hazard (RH) for adults with GHb ≥8% compared with adults with GHb <6% was 2.59 (95% CI 1.88–3.56) for all-cause mortality, 3.38 (1.98–5.77) for heart disease mortality, and 2.64 (1.17–5.97) for cancer mortality. Among adults with diagnosed diabetes, having GHb ≥8% compared with GHb <6% was associated with higher all-cause mortality (RH 1.68, 95% CI 1.03–2.74) and heart disease mortality (2.48, 1.09–5.64), but there was no increased risk of cancer mortality by GHb category. Among adults without diagnosed diabetes, there was no significant association of all-cause, heart disease, or cancer mortality and GHb category.

CONCLUSIONS

These results highlight the importance of GHb levels in mortality risk among a nationally representative sample of adults with and without diagnosed diabetes and indicate that higher levels are associated with increased mortality in adults with diabetes.Hperglycemia has been associated with a wide range of adverse outcomes for individuals with glucose values both above and below the threshold for diabetes, including increased cardiovascular disease (CVD) and mortality (1). Studies have consistently found undiagnosed diabetes to be associated with increased risk of mortality (2–4), and many studies have also shown levels of glucose that are elevated, but not enough for a diagnosis of diabetes, such as impaired fasting glucose, to be associated with increased mortality (2–4).However, most of these studies are based on fasting or postprandial glucose (1–4), and few are based on GHb levels (3,5–8). The GHb level may be a better indicator of hyperglycemia because it provides a measure of an individual''s average glucose levels for the previous 3 months. Thus, it may provide a more stable snapshot of glucose levels when used in prospective cohort studies to examine the association of subsequent risk. Currently, GHb is monitored in the treatment of diabetes, and GHb targets for prevention of complications among individuals with diabetes have been established (9). Interest in the use of GHb for the diagnosis of diabetes is increasing (10), and an international effort is underway to standardize the measurement of GHb (11). This focus of GHb in clinical care measures (12) raises important questions about the long-term predictability of GHb.Examination of the relationship of GHb with mortality reveals several areas of uncertainty, including whether the relationship of GHb with mortality is similar among individuals with and without diabetes from both prospective cohort studies and clinical trials. A few prospective cohort studies have examined the association of GHb with risk of mortality (5–8) and shown an increased risk of mortality with increasing GHb level. Only two studies included individuals with diabetes, but these studies did not examine GHb levels by diabetes status, and none were representative of the general U.S. population.Recently published findings from three clinical trials among adults with diabetes have added to this uncertainty. The Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial showed that lower GHb levels increased risk of mortality and did not decrease CVD events (13). Whereas the Action in Diabetes and Vascular Disease—Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) study showed that lowering of GHb levels was associated with a decrease in micro- and macrovascular events and deaths from CVD (14) and the Veterans Administration Diabetes Trial reported that lower GHb levels were not associated with a reduction in cardiovascular events (15). These findings have not led to any changes in glycemic control recommendations (16).The Third National Health and Nutrition Examination Survey (NHANES III) is the first nationally representative survey to include a measure of GHb and has mortality status available through linkage to the National Death Index. The objective of this study was to examine the association of GHb with subsequent mortality in a nationally representative sample of U.S. adults.     

Comparison of near-patient capillary glucose measurement and a risk assessment questionnaire in screening for type 2 diabetes in a high-risk population in rural India

OBJECTIVE

To assess the utility of a point-of-care (POC) capillary blood glucose measurement as compared with routine clinical parameters in predicting undiagnosed diabetes in a low-resource rural India setting.

RESEARCH DESIGN AND METHODS

Nine hundred and ninety-four participants aged >30 years and stratified by age and sex were randomly selected from 20 villages in India. A clinical questionnaire, sampling for laboratory venous fasting plasma glucose (FPG), and POC capillary blood glucose assay were performed simultaneously. Diabetes diagnosis was based on the World Health Organization (WHO) definition using FPG. The capacity of the POC glucose to predict the presence of diabetes was assessed and compared with the questionnaire using area under the receiver operating characteristic curves (AUCs).

RESULTS

The AUC for POC glucose alone in predicting diabetes was 0.869 (95% CI 0.810–0.929). This was significantly better (P < 0.001 for AUC comparison) than the models based upon clinical variables alone (AUC for the best clinical model including age, BMI, hypertension, waist circumference: 0.694 [95% CI 0.621–0.766]). POC glucose appropriately reclassified the risk of up to one-third of participants ranked according to the clinical models. Adding the clinical variables to the POC glucose assay did not significantly improve the discriminatory capability beyond that achieved with the POC glucose measurement alone (all P > 0.37).

CONCLUSIONS

POC glucose testing appears to be a simple and reliable tool for identifying undiagnosed diabetes in a high-risk, resource-poor rural population. However, studies evaluating the cost effectiveness of introducing POC glucose testing are needed prior to widespread implementation.The prevalence of type 2 diabetes is rapidly increasing around the world (1). Developing countries are facing the largest increases both in absolute and relative terms (1). It is predicted that this will have devastating consequences on the economies and health systems of these countries. Successful prevention and early management of diabetes is therefore a major health priority (1,2).In many regions, up to 50% of people with diabetes remain undiagnosed (1,3,4). Failure to improve these levels of detection will mean that the opportunity to improve health outcomes with early intervention will be lost. Early treatment with successful glucose control significantly reduces the morbidity and mortality associated with diabetes (5,6). Earlier detection of diabetes also allows for the implementation of other treatments that reduce the vascular complications of diabetes (5,6).Universal screening for diabetes is not currently recommended due to a lack of good evidence for an accurate test. However, targeted screening is advocated in certain ethnic groups deemed at increased risk of diabetes (2). For some ethnic groups, implementation of targeted screening may require the entire population to be screened. This applies for instance to Asian Indian populations, which are at greater risk of developing diabetes (7) and have a high prevalence of diabetes both in urban (4) and rural settings (3). However to successfully apply screening to such populations requires accurate, safe, and low-cost diagnostic strategies that are easy to implement (8).In resource-poor settings, clinical variables–based risk assessment questionnaires or point-of-care (POC) glucose analysis may be reasonable screening tools (9). Both require little expertise and allow an individual''s risk of having undiagnosed diabetes to be immediately determined so that only those at high risk require a confirmatory diagnostic test. However, the value of risk assessment questionnaires (9–13) and POC glucose analysis (14–16) in resource-poor settings remains unclear. Additionally the performance of these different screening methods has not been compared in rural Asian Indian populations.The aim of this study was to quantify and compare the accuracy of strategies based on POC glucose, clinical variables, and the combination of both in predicting undiagnosed diabetes in an asymptomatic, resource-poor rural Asian Indian population.     

Cost-Effectiveness of Bariatric Surgery for Severely Obese Adults With Diabetes

OBJECTIVE

To analyze the cost-effectiveness of bariatric surgery in severely obese (BMI ≥35 kg/m²) adults who have diabetes, using a validated diabetes cost-effectiveness model.

RESEARCH DESIGN AND METHODS

We expanded the Centers for Disease Control and Prevention–RTI Diabetes Cost-Effectiveness Model to incorporate bariatric surgery. In this simulation model, bariatric surgery may lead to diabetes remission and reductions in other risk factors, which then lead to fewer diabetes complications and increased quality of life (QoL). Surgery is also associated with perioperative mortality and subsequent complications, and patients in remission may relapse to diabetes. We separately estimate the costs, quality-adjusted life-years (QALYs), and cost-effectiveness of gastric bypass surgery relative to usual diabetes care and of gastric banding surgery relative to usual diabetes care. We examine the cost-effectiveness of each type of surgery for severely obese individuals who are newly diagnosed with diabetes and for severely obese individuals with established diabetes.

RESULTS

In all analyses, bariatric surgery increased QALYs and increased costs. Bypass surgery had cost-effectiveness ratios of $7,000/QALY and $12,000/QALY for severely obese patients with newly diagnosed and established diabetes, respectively. Banding surgery had cost-effectiveness ratios of $11,000/QALY and $13,000/QALY for the respective groups. In sensitivity analyses, the cost-effectiveness ratios were most affected by assumptions about the direct gain in QoL from BMI loss following surgery.

CONCLUSIONS

Our analysis indicates that gastric bypass and gastric banding are cost-effective methods of reducing mortality and diabetes complications in severely obese adults with diabetes.In recent years, bariatric surgery has emerged as a popular treatment to reduce body weight and improve obesity-related complications, particularly in the diabetic population. Several studies have shown that surgery can lead to significant weight loss, with excess body weight reduced by >50% (1,2). Although weight loss declines over time, the Swedish Obese Subjects (SOS) Study found significant weight loss even 10 years after surgery (3,4). In addition to sustained weight loss, bariatric surgery may provide additional benefits to people with diabetes. Among severely obese patients with diabetes, bariatric surgery often leads to diabetes remission, with remission rates that are as high as 80% in the short run (1) and that remain significant in the long run (3,4).Although the evidence suggests that bariatric surgery is a successful long-term treatment of obesity for people with diabetes, it is an expensive procedure. The average cost of surgery exceeds $13,000 (5), with additional costs possible in the months following surgery (6). This raises the question of whether bariatric surgery is cost-effective for severely obese people with diabetes.Several studies have estimated the cost-effectiveness of bariatric surgery and found that surgery is either cost-effective (7–10) or that it leads to cost savings over time (6,11–13). The existing studies tend to be relatively simple, and only two (10,13) focus on people with diabetes. The studies generally do not model the microvascular complications associated with diabetes, the effect of surgery on blood pressure and cholesterol levels, or the resulting outcomes.This study used the Centers for Disease Control and Prevention (CDC)-RTI Diabetes Cost-Effectiveness Model to analyze the cost-effectiveness of bariatric surgery in severely obese adults with diabetes. We separately estimated the cost-effectiveness of gastric bypass surgery relative to usual diabetes care and the cost-effectiveness of gastric banding surgery relative to usual diabetes care. Gastric bypass and gastric banding are the two forms of bariatric surgery most commonly studied (1). We examined the cost-effectiveness of each type of surgery for severely obese people who are newly diagnosed with diabetes (no more than 5 years after diagnosis) and for people with established diabetes (at least 10 years after diagnosis).     

Socioeconomic Status and Mortality: Contribution of health care access and psychological distress among U.S. adults with diagnosed diabetes

OBJECTIVE

Although several studies have examined the association between socioeconomic status (SES) and mortality in the general population, few have investigated this relationship among people with diabetes. This study sought to determine how risk of mortality associated with measures of SES among adults with diagnosed diabetes is mitigated by association with demographics, comorbidities, diabetes treatment, psychological distress, or health care access and utilization.

RESEARCH DESIGN AND METHODS

The study included 6,177 adults aged 25 years or older with diagnosed diabetes who participated in the National Health Interview Surveys (1997–2003) linked to mortality data (follow-up through 2006). SES was measured by education attained, financial wealth (either stocks/dividends or home ownership), and income-to-poverty ratio.

RESULTS

In unadjusted analysis, risk of death was significantly greater for people with lower levels of education and income-to-poverty ratio than for those at the highest levels. After adjusting for demographics, comorbidities, diabetes treatment and duration, health care access, and psychological distress variables, the association with greater risk of death remained significant only for people with the lowest level of education (relative hazard 1.52 [95% CI 1.04–2.23]). After multivariate adjustment, the risk of death was significantly greater for people without certain measures of financial wealth (e.g., stocks, home ownership) (1.56 [1.07–2.27]) than for those with them.

CONCLUSIONS

The findings suggest that after adjustments for demographics, health care access, and psychological distress, the level of education attained and financial wealth remain strong predictors of mortality risk among adults with diabetes.Socioeconomic status (SES) is a complex construct determined by an individual’s or group’s relative position within a society (1) and based on socially derived economic factors. These relative levels of position within the societal hierarchy may result in inequalities in health. In epidemiologic research, SES is most commonly measured in terms of education, income, occupational social class, and, less often, financial wealth (1–4). Occupational social class often relates to whether an individual is employed in, for example, a nonmanagerial, managerial, working class, or professional capacity. Financial wealth relates to the accumulated assets of an individual, often measured in terms of investments, savings, home ownership, or other sources of economic security. However, recent empirical evidence indicates that these measures are not equally accurate indicators of SES (5,6).Epidemiologic studies using a variety of SES measures have consistently shown that, in the general population, mortality risk increases as SES decreases (7–11). Furthermore, there is evidence that the influence of SES is cumulative over an individuals’ life (11).Adults with low SES are disproportionately affected by diabetes and its complications (12). Among adults with diabetes, lower SES is associated with many factors known to contribute to poor health outcomes, including reduced access to and underuse of recommended preventive care, poor metabolic control, and psychological distress (12). Studies have examined the association between SES and mortality from diabetes in the general population (13,14) and the relationship of SES and mortality among people with diabetes (15–21). However, most studies have focused on only one measure of SES (13,15,16) or have used area-based SES measures (19,20). Furthermore, although some studies have included behavioral and clinical characteristics (18,21), none have included additional measures such as health care access and use or psychological factors.Many possible factors may explain the associations of SES with mortality risk (22–24), including poorer overall health, increased number of comorbid conditions, lack of access to or underuse of health care services, and psychological factors. Psychological factors including depression, anxiety, or emotional problems may influence acute and chronic cardiovascular disease risk and overall health (25–27). A previous national study showed that adults with diagnosed diabetes and comorbid depression have a greater than twofold increased risk of mortality (25). Lower SES is associated with increased risk of mortality among adults with or without diagnosed diabetes and among people with depression (28).Although several studies have examined the association between socioeconomic position and mortality in the general population, few have investigated the relationship among people with diabetes, and fewer still have evaluated the contribution of health care access and psychological distress to this relationship. Therefore, we designed this study to 1) determine whether increased risk of mortality is associated with SES measures among adults with diagnosed diabetes, and 2) determine whether increased risk is mitigated by the association of demographic factors, comorbidities, diabetes treatment and duration, health care access and utilization, or psychological distress.     

Hemoglobin A1c as a diagnostic tool for diabetes screening and new-onset diabetes prediction: a 6-year community-based prospective study

OBJECTIVE

Various cutoff levels of hemoglobin A_1c (A1C) have been suggested to screen for diabetes, although more consensus about the best level, especially for different ethnicities, is required. We evaluated the usefulness of A1C levels when screening for undiagnosed diabetes and as a predictor of 6-year incident diabetes in a prospective, population-based cohort study.

RESEARCH DESIGN AND METHODS

A total 10,038 participants were recruited from the Ansung-Ansan cohort study. All subjects underwent a 75-g oral glucose tolerance test at baseline and at each biennial follow-up. Excluding subjects with a previous history of diabetes (n = 572), the receiver operating characteristic curve was used to evaluate the diagnostic accuracy of the A1C cutoff. The Cox proportional hazards model was used to predict diabetes at 6 years.

RESULTS

At baseline, 635 participants (6.8%) had previously undiagnosed diabetes. An A1C cutoff of 5.9% produced the highest sum of sensitivity (68%) and specificity (91%). At 6 years, 895 (10.2%) subjects had developed incident diabetes. An A1C cutoff of 5.6% had the highest sum of sensitivity (59%) and specificity (77%) for the identification of subsequent 6-year incident diabetes. After multivariate adjustment, men with baseline A1C ≥5.6% had a 2.4-fold increased risk and women had a 3.1-fold increased risk of new-onset diabetes.

CONCLUSIONS

A1C is an effective and convenient method for diabetes screening. An A1C cutoff of 5.9% may identify subjects with undiagnosed diabetes. Individuals with A1C ≥5.6% have an increased risk for future diabetes.The prevalence of type 2 diabetes is increasing rapidly. In the U.S., >13% of adults have been diagnosed with type 2 diabetes (1), and a similar prevalence has been reported in Asia (2). Up to 25% of newly diagnosed diabetic patients already had microvascular complications, which suggests that there is a 6- to 7-year time lag between the onset and the diagnosis of type 2 diabetes (3).When considering the clinical implications of diabetes and its complications, it is important to identify individuals with undiagnosed diabetes or those who are prone to diabetes in the near future. The American Diabetes Association (ADA) recommends screening asymptomatic people at 3-year intervals using a fasting plasma glucose (FPG) test or 2-h oral glucose tolerance test (OGTT) (4). However, it is not easy to perform the OGTT in primary practice, and it is debatable whether the FPG concentration alone provides an accurate diagnosis of diabetes, as indicated by the estimated 40% of people who have undiagnosed diabetes (1).The hemoglobin A_1c (A1C) level is measured in a standardized test that produces data consistent with those of the international A1C-derived average glucose and the Diabetes Control and Complications Trial (5,6). The A1C level provides a reliable measure of chronic glycemic control without the need for a fasting or timed sample, and it correlates well with the risk of long-term diabetes complications and mortality (7,8). Several population-based studies have investigated the utility of the A1C level for detecting undiagnosed diabetes and the potential to use the A1C level as a good screening tool for type 2 diabetes (9,10). However, the recent ADA redefinition of the diagnosis of diabetes using an A1C level ≥6.5%, which considers many aspects of diagnostic testing and the economic burden, raises concerns about the possible delay in diagnosing diabetes (11,12). Thus, there is widespread debate about the appropriate A1C cutoff value for diagnosing diabetes.To evaluate the predictive value of the A1C level and to find the appropriate A1C cutoff for identifying undiagnosed diabetes and new-onset diabetes over a 6-year follow-up, we analyzed the data from a large-scale, prospective cohort study of people from a homogeneous ethnic background.     

Associations between media consumption habits, physical activity, socioeconomic status, and glycemic control in children, adolescents, and young adults with type 1 diabetes

OBJECTIVE

To evaluate the relationship between media consumption habits, physical activity, socioeconomic status, and glycemic control in youths with type 1 diabetes.

RESEARCH DESIGN AND METHODS

In the cross-sectional study, self-report questionnaires were used to assess media consumption habits, physical activity, and socioeconomic status in 296 children, adolescents, and young adults with type 1 diabetes. Clinical data and HbA_1c levels were collected. Risk factors were analyzed by multiple regression.

RESULTS

Youths with type 1 diabetes (aged 13.7 ± 4.1 years, HbA_1c 8.7 ± 1.6%, diabetes duration 6.1 ± 3.3 years) spent 2.9 ± 1.8 h per day watching television and using computers. Weekly physical activity was 5.1 ± 4.5 h. Multiple regression analysis identified diabetes duration, socioeconomic status, and daily media consumption time as significant risk factors for glycemic control.

CONCLUSIONS

Diabetes duration, socioeconomic status, and daily media consumption time, but not physical activity, were significant risk factors for glycemic control in youths with type 1 diabetes.The pivotal Diabetes Control and Complications Trial (DCCT) and Epidemiology of Diabetes Interventions and Complications (EDIC) study demonstrate that poor glycemic control is associated with an increased risk of developing complications in type 1 diabetes (1). Various factors contributing to glycemic control have been identified (2). Immutable parameters such as age, sex, diabetes duration, and socioeconomic status have a major effect on metabolic control (2–6). Lower socioeconomic status is an important determinant for poor glycemic control (4,5). Modifiable factors influencing metabolic control are diabetes-related knowledge, frequency of blood glucose monitoring, and daily insulin dose (3,4,6,7). Lastly, psychosocial parameters are important in achieving good glycemic control (3–5,8–10). The influence of physical activity on metabolic control is unclear (9,11,12).Recent research addresses the influence of modern life habits on general health. Youths spend more and more time watching television and using computers. Many studies suggest that sedentary behaviors such as watching television lead to obesity in children (13,14). In one study in youths with type 1 diabetes, Margeirsdottir et al. (15) showed that poor metabolic control was associated with extensive television watching. However, the authors did not examine other covariables, such as socioeconomic status, which is associated with both glycemic control and media consumption (4,5,16,17). Hence, the aim of this study was to examine the impact of media consumption habits, physical activity, and socioeconomic status on glycemic control in youths with type 1 diabetes.     

Personal and Relationship Challenges of Adults With Type 1 Diabetes: A qualitative focus group study

OBJECTIVE

Little is known about the psychosocial challenges of adults living with type 1 diabetes or its impact on partner relationships. This qualitative study was undertaken to gain better understanding of these issues.

RESEARCH DESIGN AND METHODS

Four focus groups were held, two with adult type 1 diabetic patients (n = 16) and two with partners (n = 14). Two broad questions were posed: “What are the emotional and interpersonal challenges you have experienced because you have (your partner has) type 1 diabetes?” and “How does the fact that you have (your partner has) type 1 diabetes affect your relationship with your partner, positively and/or negatively?” Sessions were recorded and transcribed, and analyzed by a team of four researchers, using constant comparative methods to identify core domains and concepts.

RESULTS

Four main domains were identified: 1) impact of diabetes on the relationship, including level of partner involvement, emotional impact of diabetes on the relationship, and concerns about child-rearing; 2) understanding the impact of hypoglycemia; 3) stress of potential complications; and 4) benefits of technology. Themes suggest that, although partner involvement varies (very little to significant), there exists significant anxiety about hypoglycemia and future complications and sources of conflict that may increase relationship stress. Partner support is highly valued, and technology has a positive influence.

CONCLUSIONS

Adults with type 1 diabetes face unique emotional and interpersonal challenges. Future research should focus on gaining a better understanding of how they cope and the effect of psychosocial stressors and coping on adherence, quality of life, and glycemic control.Studies of people with type 1 diabetes have focused on children and young adults and describe many emotional and interpersonal challenges. Youth are at increased risk for psychiatric, eating, and substance abuse disorders, interpersonal problems, nonadherence, and poor quality of life (1,2). “Emerging” adults must address the responsibilities of intensive self-care (e.g., healthcare access) while managing normative challenges (e.g., jobs) (3,4).Little is known about common psychosocial challenges of adults with type 1 diabetes. Type 1 diabetes is a challenging disease. Those diagnosed as children live with the disease for most of their lives. All are vulnerable to complications that affect quality of life (5). Self-care is demanding, requiring frequent testing, insulin adjustment, and hypervigilance against hypoglycemia. Studies show the negative effects on quality of life of male sexual dysfunction (6) and of frequent or traumatic severe hypoglycemia episodes (7). The odds of depression are two times higher for adults with type 1 diabetes (8), and disordered eating and insulin omission are concerns (9). Effective coping skills are important; they relate to better glycemic control (10,11) and regimen adherence (10,12). Personal models of type 1 diabetes that are more negative (e.g., less perceived control) relate to poorer coping and clinic attendance (13). Overall, the literature on psychosocial challenges and factors affecting the outcomes of adult type 1 diabetic patients is lacking.One area studied is the effect of family support on outcomes. Greater family conflict for youth with type 1 diabetes, and less family support for adults, predicts poorer adherence (14,15). For adults with type 2 diabetes, greater marital satisfaction relates to lower risk of developing metabolic syndrome (16), better marital quality relates to better quality of life and adherence (17–19), and nonsupportive partner behaviors relate to poorer medication adherence (20). Also, partners of people with type 2 diabetes may experience as much, or more, distress as the patient (21).One would expect similar significant effects on important relationships of adult type 1 diabetic patients. One study found that those who achieved improved glycemic control with continuous glucose monitoring also reported that their “significant other” encouraged and participated with them (22). One study of spouses of patients who had recently experienced severe hypoglycemia found greater distress and marital conflict than spouses whose partners had not, and even more fear of hypoglycemia than the patients (23). Generally, little is known about these intra- and interpersonal challenges.We adopted a qualitative approach to better understand the unique psychosocial challenges of adults with type 1 diabetes, and patient/partner perspectives on how diabetes impacts their relationships (24). We chose focus groups, not individual interviews, because data are obtained from the communication between participants, as they share experiences and comment on different perspectives. Also, sometimes participants are more open when less inhibited members explore difficult topics, and more open in a group format (25).     

A simple screening score for diabetes for the Korean population: development, validation, and comparison with other scores

OBJECTIVE

We developed and validated a self-assessment score for diabetes risk in Korean adults and compared it with other established screening models.

RESEARCH DESIGN AND METHODS

The Korea National Health and Nutrition Examination Survey (KNHANES) 2001 and 2005 data were used to develop a diabetes screening score. After excluding patients with known diabetes, 9,602 participants aged ≥20 years were selected. Undiagnosed diabetes was defined as a fasting plasma glucose ≥126 mg/dL and/or nonfasting plasma glucose ≥200 mg/dL. The SAS Survey Logistic Regression analysis was used to determine predictors of undiagnosed diabetes (n = 341). We validated our model and compared it with other existing methods using the KNHANES 2007–2008 data (n = 8,391).

RESULTS

Age, family history of diabetes, hypertension, waist circumference, smoking, and alcohol intake were independently associated with undiagnosed diabetes. We calculated a diabetes screening score (range 0–11), and a cut point of ≥5 defined 47% of adults as being at high risk for diabetes and yielded a sensitivity of 81%, specificity of 54%, positive predictive value of 6%, and positive likelihood ratio of 1.8 (area under the curve [AUC] = 0.73). Comparable results were obtained in validation datasets (sensitivity 80%, specificity 53%, and AUC = 0.73), showing better performance than other non-Asian models from the U.S. or European population.

CONCLUSIONS

This self-assessment score may be useful for identifying Korean adults at high risk for diabetes. Additional studies are needed to evaluate the utility and feasibility of this score in various settings.Type 2 diabetes is one of the most common and rapidly increasing chronic metabolic disorders in the world. It causes serious complications and mortality, with a large burden to the public health care system as well as to patients. More than 189 million people had diabetes in 2003 worldwide (1), and this number is expected to rise more rapidly in the future as obesity increases, the population becomes older, and physical activity levels of most people decrease. The overall prevalence of diabetes in Korea was ~9.1% (2.6 million people) in 2005 (2) and increased to 9.7% in 2008, according to an analysis of the 2008 Korea National Health and Nutrition Examination Survey (KNHANES) (3). More strikingly, 32% (0.8 million) of patients with diabetes are undiagnosed; 4.9 million subjects in 2005 were estimated to have impaired fasting glucose, accounting for 17.4% of Korean adults (2,4).Among middle-aged Korean adults, more than one-half (56%) were first diagnosed with diabetes in the survey (2), indicating that a significant number of individuals potentially may be at risk for undiagnosed diabetes. Considering the large proportion of patients with impaired fasting glucose or undiagnosed diabetes, early screening and detection in these patients is essential to avoid diabetes-related morbidity, reduce the cost of health care, and prevent the deterioration of the quality of life. Many risk score questionnaires and algorithms have been developed and validated in various countries and ethnic groups to identify patients at high risk for diabetes (5–11). However, most have been designed for whites, and there are only a few scoring systems for Asian populations (6,9,11). Risk scores derived from certain populations may not be applicable to other ethnic groups (12,13); therefore, there is a need to establish a diabetes risk score for the Korean population. Moreover, having their own score may make people more motivated to use the method. In addition, the majority of models consist of diverse variables, including laboratory profiles and BMI, which require additional blood assays or mathematical calculations (6–10).The aim of our study was to develop and validate a self-assessment score for diabetes risk in Korean adults using simple clinical parameters, including anthropometric and lifestyle risk factors, to provide a reliable and easy tool for the layperson without the need for a clinician’s input. We also compared the new algorithm with other existing screening models derived from different ethnic populations.     

Screening for Diabetes and Pre-Diabetes With Proposed A1C-Based Diagnostic Criteria

OBJECTIVE

An International Expert Committee (IEC) and the American Diabetes Association (ADA) proposed diagnostic criteria for diabetes and pre-diabetes based on A1C levels. We hypothesized that screening for diabetes and pre-diabetes with A1C measurements would differ from using oral glucose tolerance tests (OGTT).

RESEARCH DESIGN AND METHODS

We compared pre-diabetes, dysglycemia (diabetes or pre-diabetes), and diabetes identified by the proposed criteria (A1C ≥6.5% for diabetes and 6.0–6.4% [IEC] or 5.7–6.4% [ADA] for high risk/pre-diabetes) with standard OGTT diagnoses in three datasets. Non-Hispanic white or black adults without known diabetes who had A1C and 75-g OGTT measurements were included from the prospective Screening for Impaired Glucose Tolerance study (n = 1,581), and from the National Health and Nutrition Examination Survey (NHANES) III (n = 2014), and NHANES 2005–2006 (n = 1,111).

RESULTS

OGTTs revealed pre-diabetes in 35.8% and diabetes in 5.2% of combined study subjects. A1C provided receiver operating characteristic (ROC) curve areas for diabetes of 0.79–0.83, but ROC curve areas were ≤0.70 for dysglycemia or pre-diabetes. The proposed criteria missed 70% of individuals with diabetes, 71–84% with dysglycemia, and 82–94% with pre-diabetes. Compared with the IEC criteria, the ADA criteria for pre-diabetes resulted in fewer false-negative and more false-positive result. There were also racial differences, with false-positive results being more common in black subjects and false-negative results being more common in white subjects. With use of NHANES 2005–2006 data, ∼5.9 million non-Hispanic U.S. adults with unrecognized diabetes and 43–52 million with pre-diabetes would be missed by screening with A1C.

CONCLUSIONS

The proposed A1C diagnostic criteria are insensitive and racially discrepant for screening, missing most Americans with undiagnosed diabetes and pre-diabetes.Diabetes affects >21 million American adults (1,2), with a lifetime risk ranging from 20 to 50+%, depending on sex and race (3). Identification of diabetes and its precursor, pre-diabetes, can permit management to prevent complications or delay progression from pre-diabetes to diabetes. Because most U.S. health care systems do not have systematic screening programs, many Americans have undiagnosed diabetes and pre-diabetes, and, therefore, these individuals are not initiating programs targeted at prevention (2).An International Expert Committee (IEC) recently proposed new diagnostic criteria based on measurement of A1C, with A1C ≥6.5% for diabetes and 6.0–6.4% for “high risk” of progression to diabetes (4). The American Diabetes Association (ADA) subsequently proposed A1C ≥6.5% for the diagnosis of diabetes and 5.7–6.4% for the highest risk to progress to diabetes (5).Because A1C testing is readily available in the U.S., is relatively well standardized, exhibits low intraindividual variation, and does not require fasting or restriction to certain times of the day (6), many clinicians might wish to use A1C measurements to screen for diabetes and pre-diabetes. However, the proposed diagnostic criteria were based largely on identification of diabetic retinopathy, and use of the proposed criteria as a screening test is not understood. The IEC A1C criteria have recently been compared with testing with fasting glucose or oral glucose tolerance tests (OGTTs) in various populations to diagnose diabetes (7–13) and high-risk/pre-diabetes (10,11,13), but the ADA A1C criteria have not been studied.We hypothesized that A1C diagnostic criteria would fail to identify many subjects with unrecognized diabetes or pre-diabetes. We evaluated the proposed criteria as screening tests in three populations, compared with the OGTT as a “gold standard” used for identification of diabetes and pre-diabetes around the world (14).     

Physical Activity, Adiposity, and Diabetes Risk in Middle-Aged and Older Chinese Population: The Guangzhou Biobank Cohort Study

OBJECTIVE

Physical activity may modify the association of adiposity with type 2 diabetes. We investigated the independent and joint association of adiposity and physical activity with fasting plasma glucose, impaired fasting glucose, and type 2 diabetes in a Chinese population.

RESEARCH DESIGN AND METHODS

Middle-aged and older Chinese (n = 28,946, ≥50 years, 72.4%women) from the Guangzhou Biobank Cohort Study were examined in 2003–2008. Multivariable regression was used in a cross-sectional analysis.

RESULTS

BMI, waist circumference, and waist-to-hip ratio (WHR) were positively associated with type 2 diabetes after multiple adjustment, most strongly for WHR with odds ratio (OR) of 3.99 (95% CI 3.60–4.42) for highest compared with lowest tertile. Lack of moderate-to-vigorous physical activity, but not walking, was associated with diabetes with an OR of 1.29 (1.17–1.41). The association of moderate-to-vigorous activity with fasting glucose varied with WHR tertiles (P = 0.01 for interaction). Within the high WHR tertile, participants who had a lack of moderate-to-vigorous activity had an OR of 3.87 (3.22–4.65) for diabetes, whereas those who were active had an OR of 2.94 (2.41–3.59).

CONCLUSIONS

In this population, WHR was a better measure of adiposity-related diabetes risk than BMI or waist circumference. Higher moderate-to-vigorous activity was associated with lower diabetes risk, especially in abdominally obese individuals.Type 2 diabetes is a worldwide cause of morbidity and mortality. Adiposity, especially abdominal adiposity, seems to be at the core of development of hyperglycemia and type 2 diabetes (1). Increased physical activity may mitigate some of the diabetogenic impact of adiposity (2–4). Individuals who are obese but fit could even have a lower risk of mortality than those who are normal weight but unfit (5,6). However, being physically active does not completely abolish the obesity-related risk for cardiovascular disease and associated mortality (7). Adiposity is still the main risk factor for the development of type 2 diabetes (2–4,8). Although increased physical activity has been shown to be associated with reduced type 2 diabetes risk independent of adiposity, the protective effects may differ by the level of adiposity. However, the group that could benefit most from physical activity for the prevention of diabetes is still unclear (2–4,8–10).Understanding the relationship between adiposity and physical activity is important to stratify risk groups for the development of effective diabetes prevention strategies from public health and clinical perspectives. Most of the studies relate to Caucasians (2–4,8–10), whereas Asians, including Chinese and Indians, are possibly more vulnerable to insulin resistance (11). The number of Chinese adults with type 2 diabetes was estimated to be ∼28.1 million in 2000 and may double by 2030, with China being second only to India (12). The purpose of this study was to investigate the independent and joint association of adiposity and physical activity with fasting plasma glucose, impaired fasting glucose (IFG), and type 2 diabetes in 28,946 middle-aged and older Chinese participants in the Guangzhou Biobank Cohort Study.     

Extended Family History of Type 1 Diabetes and Phenotype and Genotype of Newly Diagnosed Children

OBJECTIVE

To determine the frequency of newly diagnosed diabetic children with first- and second-degree relatives affected by type 1 diabetes and to characterize the effects of this positive family history on clinical markers, signs of β-cell autoimmunity, and HLA genotype in the index case.

RESEARCH DESIGN AND METHODS

Children (n = 1,488) with type 1 diabetes diagnosed under 15 years of age were included in a cross-sectional study from the Finnish Pediatric Diabetes Register. Data on family history of diabetes and metabolic decompensation at diagnosis were collected using a questionnaire. Antibodies to β-cell autoantigens (islet cell antibodies, insulin autoantibodies, GAD antibodies, and antibodies to the islet antigen 2 molecule) and HLA genotypes were analyzed.

RESULTS

A total of 12.2% of the subjects had a first-degree relative with type 1 diabetes (father 6.2%, mother 3.2%, and sibling 4.8%) and 11.9% had an affected second-degree relative. Children without affected relatives had lower pH (P < 0.001), higher plasma glucose (P < 0.001) and β-hydroxybutyrate concentrations (P < 0.001), a higher rate of impaired consciousness (P = 0.02), and greater weight loss (P < 0.001). There were no differences in signs of β-cell autoimmunity. The familial cases carried the HLA DR4-DQ8 haplotype more frequently than sporadic cases (74.0 vs. 67.0%, P = 0.02).

CONCLUSIONS

When the extended family history of type 1 diabetes is considered, the proportion of sporadic diabetes cases may be reduced to <80%. A positive family history for type 1 diabetes associates with a less severe metabolic decompensation at diagnosis, even when only second-degree relatives are affected. Autoantibody profiles are similar in familial and sporadic type 1 diabetes, suggesting similar pathogenetic mechanisms.Familial clustering of type 1 diabetes is a conspicuous feature; the risk of developing type 1 diabetes is 8–15-fold higher in first-degree relatives (1–6) and twofold in second-degree relatives (1,7). Despite this, the vast majority of children are diagnosed with the sporadic form of diabetes. The proportion of children with an affected first-degree relative at the time of diagnosis is ∼10–12% (7–13), and after decades of follow-up, this frequency increases to >20% (8,14,15). Fathers transmit the disease to their offspring more often than mothers (3,16). Accordingly, at diagnosis, 4–7% of children have a father with type 1 diabetes whereas only 1.5–3% have an affected mother (7–12,17). Fewer reports exist on type 1 diabetes in the extended family. Depending on the definition of second-degree relatives and length of time from the diagnosis of the index case, 5–16% of children with type 1 diabetes have an affected second-degree relative (1,5,11,17–19).Familial and sporadic type 1 diabetes have been suggested to differ in terms of pathogenetic mechanisms (20,21). The risk-associated HLA genotypes have been observed more often in familial type 1 diabetes (8,20,22,23), although not all studies have found significant differences (24). Two studies have noticed no differences in diabetes-associated autoantibodies, e.g., insulin autoantibodies (IAAs) (8), GAD antibodies (GADAs) (8), or islet cell antibodies (ICAs) (8,20). A recent study from Israel reported, however, higher frequencies of IAAs and a higher number of positive antibody responses among familial cases (13). In families with prior experience of type 1 diabetes in a first-degree relative, the clinical status of the child at diagnosis is less severe (8,13,21).Data on the possible pathogenetic differences between familial and sporadic type 1 diabetes are still inconsistent and based on a positive family history in first-degree relatives only. To further our understanding of familial clustering of type 1 diabetes, we used data from the large, nationwide Finnish Pediatric Diabetes Register for a cross-sectional observational study. Since the knowledge of the effects of an extended family history on the diabetes of the index case is lacking, we included information on second-degree relatives (grandparents and siblings of parents). β-Cell autoimmunity, metabolic decompensation at diagnosis, and HLA genetics were compared in children with familial or sporadic type 1 diabetes. We postulated to see a stronger genetic susceptibility to type 1 diabetes and a milder metabolic decompensation in children with a positive family history for type 1 diabetes, whereas no differences were expected in the autoantibody profile.     

Association of depressive symptoms with impaired glucose regulation, screen-detected, and previously known type 2 diabetes: findings from the Finnish D2D Survey

OBJECTIVE

To study the association between impaired glucose regulation (IGR), screen-detected type 2 diabetes, and previously known diabetes and depressive symptoms.

RESEARCH DESIGN AND METHODS

Altogether, 2,712 participants from three hospital districts in Finland attended a health examination. Cutoff scores ≥10 and ≥16 in the 21-item Beck Depression Inventory (BDI-21) were used for depressive symptoms. The participants were defined as having known diabetes if they reported diabetes. An oral glucose tolerance test was used to detect normal glucose regulation (NGR), impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and screen-detected diabetes. The participants were defined as having IGR if they had IFG or IGT.

RESULTS

Prevalence of depressive symptoms, defined as a BDI-21 cutoff score ≥10, was 14.4% for those with NGR, 13.7% for those with IGR, 14.8% for those with screen-detected diabetes, and 26.4% for those with previously known diabetes. The corresponding prevalences for a cutoff score ≥16 were 3.4, 3.4, 4.2, and 7.5%, respectively. Compared with NGR and adjusted for demographic, lifestyle, and biological factors, the odds ratios for IGR, screen-detected diabetes, and previously known diabetes were 0.91 (95% CI 0.69–1.20), 0.70 (0.45–1.08), and 1.35 (0.84–2.15), respectively, for a cutoff score ≥10. For a cutoff score ≥16, the corresponding odds ratios were 1.05 (0.62–1.76), 0.87 (0.40–1.90), and 1.56 (0.69–3.50), respectively.

CONCLUSIONS

Participants with diagnosed diabetes had a higher prevalence of depressive symptoms than participants with NGR, IGR, and previously unknown diabetes. When potential confounding factors were included in the analysis, previously known diabetes was not significantly associated with depressive symptoms.It is widely recognized that depression is more common among people with diabetes than in the general population (1). However, previous studies (2–10) that have assessed the relationship between depressive symptoms and impaired glucose tolerance (IGT) or diabetes have been inconsistent. A German study (4) that included 4,597 subjects and a Dutch study (2) that included 4,747 participants found no association between type 2 diabetes and depressive symptoms. In a general-practice setting study that included 2,849 male and 3,160 female subjects, depression was not more prevalent in people with screen-detected diabetes or impaired glucose regulation (IGR) than in people with normal glucose regulation (NGR) (5). Contrary to these studies, within the Hertfordshire Cohort Study (6) there was a relationship between depression scores and diagnosed and previously undiagnosed diabetes. A U.S. study (8) including 4,293 U.S. veterans indicated that men with undiagnosed type 2 diabetes had nearly double the odds of major depression compared with those with normal fasting glucose.In 1992, it was stated about the relationship between depression and diabetes that “the etiology is unknown but is probably complex; and biological, genetic, and psychological factors remain as potential contributors. Several neuroendocrine and neurotransmitter abnormalities common to both depression and diabetes have been identified, adding to etiological speculations” (11). It has been suggested that stress-induced activation of the hypothalamic-pituitary-adrenal axis may result in the development of metabolic abnormalities and depression (12). In addition, possible neuroendocrine abnormalities associated with both diabetes and depressive symptoms may include abnormalities in vitamin B₁₂ and sex hormone–binding globulin (SHBG) levels. Low vitamin B₁₂ levels have been found to relate to type 2 diabetes (13) and depressive symptoms (14–16). Low levels of SHBG may predict diabetes (17). SHBG binds circulating sex hormones, which have been suggested to be associated with depressive symptoms (18). In addition to these biological factors, the observed association between diabetes and depressive symptoms could be a reflection of the burden of diabetes and comorbidities.In the present study, our aim was to analyze the prevalence of depressive symptoms in people with NGR, IGR (including impaired fasting glycemia and impaired glucose tolerance), screen-detected (previously unknown) diabetes, and previously known type 2 diabetes. Furthermore, our aim was to study the association between glucose tolerance and depressive symptoms, taking into account potential confounding demographic and biological factors as well as comorbidity.     

Elevated A1C in Adults Without a History of Diabetes in the U.S.

OBJECTIVE

The purpose of this study was to examine the prevalence and correlates of elevated A1C in a large, nationally representative sample of adults without diabetes in the U.S.

RESEARCH DESIGN AND METHODS

We analyzed data from 15,934 participants aged ≥20 years without diagnosed diabetes who had A1C measurements in the 1999–2006 National Health and Nutrition Examination Survey, a cross-sectional and nationally representative sample of the U.S. population.

RESULTS

The overall prevalence of A1C >6% was 3.8%, corresponding to 7.1 million adults without diabetes in the U.S. population. Approximately 90% of these individuals had fasting glucose ≥100 mg/dl. Older age, male sex, non-Hispanic black race/ethnicity, hypercholesterolemia, higher BMI, and lower attained education were significantly associated with having a higher A1C level even among individuals with normal fasting glucose (<100 mg/dl) and after multivariable adjustment.

CONCLUSIONS

A single elevated A1C level (A1C >6%) is common in the general population of adults without a history of diabetes and is highly reliable for the detection of elevated fasting glucose. Nondiabetic adults with elevated A1C are likely to have impaired fasting glucose and an array of other risk factors for type 2 diabetes and cardiovascular disease.A1C is an integrated measure of circulating glucose levels and tracks well in individuals over time. Epidemiological studies have shown that A1C values in nondiabetic adults predict incident diabetes (1–5), cardiovascular disease morbidity and mortality (6–10), and total mortality (7). In these studies, A1C values well within in the “normal” range (i.e., A1C <6%) were independently associated with clinical outcomes. There is currently renewed interest in using A1C for diagnosis and/or screening for diabetes (11); however, there have been few epidemiological investigations of A1C in nondiabetic adults. The objective of the present study was to examine the prevalence and correlates of elevated A1C in a large, nationally representative sample of U.S. adults without diagnosed diabetes who participated in the National Health and Nutrition Examination Survey (NHANES) (1999–2006). We hypothesized that 1) elevated A1C levels (e.g., A1C >6%) are common in the general population of nondiabetic adults in the U.S. and 2) A1C levels would be associated with risk factors for type 2 diabetes and its complications even in the absence of elevated glucose levels.     

Effect of Pharmacological Treatment of Depression on A1C and Quality of Life in Low-Income Hispanics and African Americans With Diabetes: A randomized, double-blind, placebo-controlled trial

OBJECTIVE

To determine whether pharmacological treatment of depression in low-income minorities with diabetes improves A1C and quality of life (QOL).

RESEARCH DESIGN AND METHODS

This was a 6-month, randomized, double-blind, placebo-controlled trial. Patients were screened for depression using Whooley''s two-question tool at a county diabetes clinic. Depression was confirmed (or not) with the Computerized Diagnostic Interview Survey (CDIS) software program, and the severity of depression was assessed monthly by the Hamilton Depression Scale (HAM-D). Depressed subjects with A1C levels ≥8.0% were randomly assigned to receive either sertraline or placebo. Diabetes care was provided by nurses following detailed treatment algorithms who were unaware of therapy for depression.

RESULTS

A total of 150 subjects answered positively to at least one question on Whooley''s questionnaire. The positive predictive value for depression diagnosed by CDIS was 69, 67, and 84% for positive answers to question 1 only, question 2 only, or both, respectively. Of the 89 subjects who entered the study, 75 completed. An intention-to-treat analysis revealed significant differences between baseline and 6 months in HAM-D and pain scores, QOL, and A1C and systolic blood pressure levels in both groups, with no differences between groups for the first three but a significantly greater decrease with sertraline in A1C and systolic blood pressure levels. Changes in HAM-D scores and A1C levels were significantly correlated in all subjects (P = 0.45 [P < 10⁻⁶]).

CONCLUSIONS

In this low-income minority population, pharmacological treatment of depression significantly improved A1C and systolic blood pressure levels compared with placebo.The prevalence of depression among people with diabetes is more than twice that of the general population (1). Coexistence of depression in persons with diabetes is associated with worse glycemic control (2), which may be due to less adherence to self-care behaviors and medications (3). Eventually, there is increased morbidity (4) and mortality (5) and higher medical costs (6).The prevalence of untreated depression in people with diabetes is higher in minorities (1). Yet, screening for and treating depression are less common in this population (7). Very little research has been published on diabetes and depression with a focus on minority populations, who have significant disparities in outcomes (8), such as higher A1C levels (9), increased rates of complications (10), and more severe depression (8).Depression is associated with worse glycemic control (2). Some studies have evaluated whether treatment of depression will improve A1C levels (11–20). However, these drug studies were open label, were of short duration, and/or were conducted in highly educated (more than high school education) Caucasian populations. Most showed that although depression was improved, A1C levels were not. We sought to determine whether use of antidepressants in a minority population with uncontrolled diabetes improved their A1C levels, quality of life (QOL), and depression compared with placebo.     

Correlates of age onset of type 2 diabetes among relatively young black and white adults in a community: the Bogalusa Heart Study

OBJECTIVE

The risk factors for middle-age onset of type 2 diabetes are well known. However, information is scant regarding the age onset of type 2 diabetes and its correlates in community-based black and white relatively young adults.

RESEARCH DESIGN AND METHODS

This prospective cohort study consisted of normoglycemic (n = 2,459) and type 2 diabetic (n = 144) adults aged 18–50 years who were followed for an average of 16 years.

RESULTS

The incidence rate of the onset of type 2 diabetes was 1.6, 4.3, 3.9, and 3.4 per 1,000 person-years for age-groups 18–29, 30–39, and 40–50 and total sample, respectively. Incidences of diabetes increased with age by race and sex groups (P for trend ≤0.01); higher in black females versus white females and blacks versus whites in total sample (P < 0.05). In a multivariable Cox model, baseline parental diabetes (hazard ratio [HR] 5.24) and plasma insulin were significantly associated with diabetes incidence at the youngest age (18–29 years); black race, BMI, and glucose at age 30–39 years; female sex, parental diabetes (HR 2.44), BMI, ratio of triglycerides and HDL cholesterol (TG/HDL-C ratio), and glucose at age 40–50 years; and black race, parental diabetes (HR 2.44), BMI, TG/HDL-C ratio, and glucose in whole cohort. Further, patients with diabetes, regardless of age onset, displayed a significantly higher prevalence of maternal history of diabetes at baseline (P < 0.01).

CONCLUSIONS

In relatively young adults, predictability of baseline cardiometabolic risk factors along with race, sex, and parental history of diabetes for the onset of type 2 diabetes varied by age-group. These findings have implications for early prevention and intervention in relatively young adults.Earlier national survey data portend that the prevalence and incidence of diabetes are rising in the United States (1,2). Impaired glucose homeostasis has become one of the most common causes of death in the U.S. (2). The progressive global epidemic of obesity has resulted in obesity being a major causal factor detected in prediabetes and type 2 diabetes (1).A number of studies have indicated that hyperinsulinemia/insulin resistance is associated with cardiometabolic risk factors including obesity, dyslipidemia, and hypertension, a constellation of disorder characteristics of the metabolic syndrome commonly found in diabetes (3–8). Further, the impaired glucose homeostasis among offspring of young-age onset, maternal type 2 patients with diabetes has been attributed to perinatal exposures and related increase in diabetes risk (9). The optimal strategy for preventing the onset of type 2 diabetes postulates the knowledge of its modifiable cardiometabolic risk factors (8). However, most studies have been performed on the prevalence of type 2 diabetes (3,4,6,9) with single, baseline measurements at middle and older age (1,5,7,9–11). Information is lacking on the correlates among relatively young adults in a community on the age-onset of type 2 diabetes. The present analysis examines the occurrence of diabetes at increasing ages as part of the Bogalusa Heart Study, a biracial (black and white), community-based investigation of the evolution of cardiovascular disease risk beginning in childhood (12).     

In Vivo Insulin Sensitivity and Lipoprotein Particle Size and Concentration in Black and White Children

OBJECTIVE

To examine sex-specific black/white differences in lipoprotein profile and the role of visceral adiposity and to assess the relationship between insulin sensitivity and lipoprotein profiles in each group.

RESEARCH DESIGN AND METHODS

Fasting lipoprotein particle size and concentration and visceral adipose tissue (VAT) were determined in 226 children (117 black, 101 male) aged 8 to <18 years. The relationship between lipoproteins and insulin sensitivity was evaluated in a subset of 194 children (100 black, 88 male) who underwent a hyperinsulinemic-euglycemic clamp.

RESULTS

Black male children had smaller VLDL and black female children had larger HDL size than their white counterparts. Overall, blacks had larger LDL size with no sex-specific race differences. After adjusting for VAT and sex, only VLDL size and concentrations remained significantly favorable in blacks. Analysis of lipoprotein particle size and concentration across insulin sensitivity quartiles revealed that in both racial groups, the most insulin-resistant children had higher concentrations of small dense LDL, small HDL, and large VLDL and smaller LDL and HDL sizes than their more insulin-sensitive counterparts.

CONCLUSIONS

The previously reported favorable lipoprotein profiles in black versus white children is partly due to race differences in VAT. In both groups, however, the most insulin-resistant youths have a high-risk atherogenic profile of small dense LDL, small HDL, and large VLDL, akin to the atherogenic lipoprotein pattern in adults with coronary artery disease.Type 2 diabetes and insulin resistance in children are associated with dyslipidemia (1,2), characterized by elevated triglycerides and LDL cholesterol and low concentrations of HDL cholesterol (1–3). In addition to traditional lipid profiles, evidence suggests that insulin resistance and type 2 diabetes are associated with changes in lipoprotein particle size and subclass concentration (2,4). These are important to assess, as traditional lipid measurements only partially predict disease risk (5). Recently, the SEARCH for Diabetes in Youth study (2) reported that 36% of youth with type 2 diabetes and 62% of those with poorly controlled diabetes had small dense LDL. Similarly, low proportions of large and high proportions of small HDL particles are found in children with type 2 diabetes and overweight, insulin-resistant children (4). However, whereas some investigators reported associations between LDL (6,7), HDL (8), and VLDL (6) particle size and fasting insulin, others did not (9). High triglyceride and low HDL cholesterol concentrations together with small, dense LDL in children with type 2 diabetes and insulin resistance are similar to the atherogenic lipoprotein phenotype in adults with coronary artery disease (10,11).Black children, despite being insulin resistant and hyperinsulinemic (12,13) compared with their white counterparts, have favorable lipid concentrations including lower LDL and triglyceride and higher HDL concentrations (3,14,15), larger HDL and LDL and smaller VLDL particles, and favorable lipoprotein subclass concentrations (6,8). Why black children have favorable lipoprotein profiles despite insulin resistance is not clear. One explanation could be lower visceral adiposity in black than in white children despite similar overall adiposity (15). In black adults insulin resistance is not a good marker of triglyceride or HDL cholesterol concentrations or lipoprotein particle size (16). Thus, the relationship between in vivo insulin sensitivity and lipoprotein profiles in black and white children needs to be examined if at-risk children are to be identified for early treatments to improve lipoprotein profiles and if those treatments are to be pertinent in children of different ethnicity.In the present study, therefore, we determined lipoprotein particle size and subclass concentrations in black and white children and measured in vivo insulin sensitivity to test the following hypotheses: 1) the favorable lipoprotein phenotype in black children is probably due to lower visceral adipose tissue (VAT) than in whites and 2) the relationship between insulin sensitivity and lipoprotein profile is similar between black and white children.     

Racial and Ethnic Differences in an Estimated Measure of Insulin Resistance Among Individuals With Type 1 Diabetes

OBJECTIVE

Insulin resistance is greater in racial/ethnic minorities than in non-Hispanic whites (NHWs) for those with and without type 2 diabetes. Because previous research on insulin resistance in type 1 diabetes was limited to NHWs, racial/ethnic variation in an estimated measure of insulin resistance in type 1 diabetes was determined.

RESEARCH DESIGN AND METHODS

The sample included 79 individuals with type 1 diabetes diagnosed at age <18 years (32.9% NHWs, 46.8% non-Hispanic black [NHB], 7.6% other/mixed, and 12.7% Hispanic) and their families. Estimated glucose disposal rate (eGDR) (milligrams per kilogram per minute; a lower eGDR indicates greater insulin resistance) was calculated using A1C, waist circumference, and hypertension status.

RESULTS

Mean current age was 13.5 years (range 3.2–32.5) and diabetes duration was 5.7 years (0.1–19.9). eGDR was inversely associated with age. Compared with that in NHWs, age-adjusted eGDR was significantly lower among nonwhites (NHB, other/mixed, and Hispanic: Δ = −1.83, P = 0.0006). Age-adjusted eGDR was negatively associated with body fat, triglycerides, urinary albumin/creatinine, acanthosis nigricans, parental obesity, and parental insulin resistance and positively related to HDL and sex hormone–binding globulin. In multivariable analysis, lower eGDR was significantly associated with older age, nonwhite race/ethnicity, acanthosis, and lower HDL.

CONCLUSIONS

Minorities with type 1 diabetes are significantly more insulin resistant, as measured by eGDR, than NHWs. Exploring potential mechanisms, including disparities in care and/or physiological variation, may contribute to preventing racial/ethnic differences in insulin resistance–associated outcomes.Insulin resistance is common in type 2 diabetes (1) and seems to play a role in the natural history (2) and risk of complications (3) in type 1 diabetes as well. Measurement of insulin resistance in type 1 diabetes is difficult because methods used in nondiabetic and type 2 individuals, e.g., insulin or homeostasis model assessment (4), cannot be used in hypoinsulinemia. The euglycemic-hyperinsulinemic clamp has been used; however, it is labor-intensive and invasive and therefore is not suitable for population-based studies. In response, a derived measure of insulin resistance, the estimated glucose disposal rate (eGDR), has been developed using clinical measures and is strongly correlated with clamp-measured insulin resistance (5).Consistent with clamp studies in type 1 diabetes (2), lower eGDR is associated with older age (6), longer duration of diabetes (6), greater adiposity (6), family history of type 2 diabetes (5), poor glycemic control (5), and elevated lipids (6). Low eGDR predicts incident retinopathy (3), nephropathy (3,6), neuropathy (7), and cardiovascular disease in type 1 diabetes (3,6). These findings are primarily based on non-Hispanic white (NHW) adults.Previous research shows racial/ethnic differences in insulin resistance for healthy individuals and those with type 2 diabetes. For example, minority adults with and without type 2 diabetes were more insulin resistant than their NHW counterparts (1,8). Similarly, in nondiabetic youth, minorities were more insulin resistant than NHWs (9,10). Despite these findings, to our knowledge, there are no data on insulin resistance in minorities with type 1 diabetes.Therefore, we sought to determine 1) whether racial/ethnic differences in insulin resistance, as measured by eGDR, exist in type 1 diabetes and 2) whether the association of eGDR with factors traditionally related to insulin resistance differed by race/ethnicity. It was hypothesized that insulin resistance is greater in minorities than in whites and that associations with insulin resistance are consistent across race/ethnicity.