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OBJECTIVE To estimate the benefits of screening and early treatment of type 2 diabetes compared with no screening and late treatment using a simulation model with data from the ADDITION-Europe study.RESEARCH DESIGN AND METHODS We used the Michigan Model, a validated computer simulation model, and data from the ADDITION-Europe study to estimate the absolute risk of cardiovascular outcomes and the relative risk reduction associated with screening and intensive treatment, screening and routine treatment, and no screening with a 3- or 6-year delay in the diagnosis and routine treatment of diabetes and cardiovascular risk factors.RESULTS When the computer simulation model was programmed with the baseline demographic and clinical characteristics of the ADDITION-Europe population, it accurately predicted the empiric results of the trial. The simulated absolute risk reduction and relative risk reduction were substantially greater at 5 years with screening, early diagnosis, and routine treatment compared with scenarios in which there was a 3-year (3.3% absolute risk reduction [ARR], 29% relative risk reduction [RRR]) or a 6-year (4.9% ARR, 38% RRR) delay in diagnosis and routine treatment of diabetes and cardiovascular risk factors.CONCLUSIONS Major benefits are likely to accrue from the early diagnosis and treatment of glycemia and cardiovascular risk factors in type 2 diabetes. The intensity of glucose, blood pressure, and cholesterol treatment after diagnosis is less important than the time of its initiation. Screening for type 2 diabetes to reduce the lead time between diabetes onset and clinical diagnosis and to allow for prompt multifactorial treatment is warranted. OBJECTIVE: To estimate the benefits of screening and early treatment of type 2 diabetes compared with no screening and late treatment using a simulation model with data from the ADDITION-Europe study.RESEARCH DESIGN AND METHODS: We used the Michigan Model, a validated computer simulation model, and data from the ADDITION-Europe study to estimate the absolute risk of cardiovascular outcomes and the relative risk reduction associated with screening and intensive treatment, screening and routine treatment, and no screening with a 3- or 6-year delay in the diagnosis and routine treatment of diabetes and cardiovascular risk factors.RESULTS: When the computer simulation model was programmed with the baseline demographic and clinical characteristics of the ADDITION-Europe population, it accurately predicted the empiric results of the trial. The simulated absolute risk reduction and relative risk reduction were substantially greater at 5 years with screening, early diagnosis, and routine treatment compared with scenarios in which there was a 3-year (3.3% absolute risk reduction [ARR], 29% relative risk reduction [RRR]) or a 6-year (4.9% ARR, 38% RRR) delay in diagnosis and routine treatment of diabetes and cardiovascular risk factors.CONCLUSIONS: Major benefits are likely to accrue from the early diagnosis and treatment of glycemia and cardiovascular risk factors in type 2 diabetes. The intensity of glucose, blood pressure, and cholesterol treatment after diagnosis is less important than the time of its initiation. Screening for type 2 diabetes to reduce the lead time between diabetes onset and clinical diagnosis and to allow for prompt multifactorial treatment is warranted.

OBJECTIVE To determine the benefit of multifactorial treatment on microvascular complications among people with type 2 diabetes detected by screening. RESEARCH DESIGN AND METHODS This study was a multicenter cluster randomized controlled trial in primary care with randomization at the practice level. In four centers in Denmark; Cambridge, U.K.; the Netherlands; and Leicester, U.K., 343 general practices participated in the trial. Eligible for follow-up were 2,861 of the 3,057 people with diabetes detected by screening included in the original trial. Biomedical data on nephropathy were collected in 2,710 (94.7%) participants, retinal photos in 2,190 (76.6%), and questionnaire data on peripheral neuropathy in 2,312 (80.9%). The prespecified microvascular end points were analyzed by intention to treat. Results from the four centers were pooled using fixed-effects meta-analysis. RESULTS Five years after diagnosis, any kind of albuminuria was present in 22.7% of participants in the intensive treatment (IT) group and in 24.4% in the routine care (RC) group (odds ratio 0.87 [95% CI 0.72–1.07]). Retinopathy was present in 10.2% of the IT group and 12.1% of the RC group (0.84 [0.64–1.10]), and severe retinopathy was present in one patient in the IT group and seven in the RC group. Neuropathy was present in 4.9% and 5.9% (0.95 [0.68–1.34]), respectively. Estimated glomerular filtration rate increased between baseline and follow-up in both groups (4.31 and 6.44 mL/min, respectively). CONCLUSIONS Compared with RC, an intervention to promote target-driven, intensive management of patients with type 2 diabetes detected by screening was not associated with significant reductions in the frequency of microvascular events at 5 years.

OBJECTIVE To evaluate the incidence and relative risk of type 2 diabetes defined by the newly proposed HbA1c diagnostic criteria in groups categorized by different baseline HbA1c levels. RESEARCH DESIGN AND METHODS Using data from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with repeat HbA1c measurements, we estimated the prevalence of known and previously undiagnosed diabetes at baseline (baseline HbA1c ≥6.5%) and the incidence of diabetes over 3 years. We also examined the incidence and corresponding odds ratios (ORs) by different levels of baseline HbA1c. Incident diabetes was defined clinically (self-report at follow-up, prescribed diabetes medication, or inclusion on a diabetes register) or biochemically (HbA1c ≥6.5% at the second health assessment), or both. RESULTS The overall prevalence of diabetes was 4.7%; 41% of prevalent cases were previously undiagnosed. Among 5,735 participants without diabetes at baseline (identified clinically or using HbA1c criteria, or both), 72 developed diabetes over 3 years (1.3% [95% CI 1.0–1.5]), of which 49% were identified using the HbA1c criteria. In 6% of the total population, the baseline HbA1c was 6.0–6.4%; 36% of incident cases arose in this group. The incidence of diabetes in this group was 15 times higher than in those with a baseline HbA1c of CONCLUSIONS The cumulative incidence of diabetes defined using a newly proposed HbA1c threshold in this middle-aged British cohort was 1.3% over 3 years. Targeting interventions to individuals with an HbA1c of 6.0–6.4% might represent a feasible preventive strategy, although complementary population-based preventive strategies are also needed to reduce the growing burden of diabetes.

OBJECTIVE—To assess the performance of the Cambridge Risk Score (CRS) to predict undiagnosed hyperglycemia in Caribbean and South Asian people living in the U.K. RESEARCH DESIGN AND METHODS—The CRS uses routinely available data from primary care records to identify people at high risk for undiagnosed type 2 diabetes. The sensitivity, specificity, and area under the receiver operator characteristic (ROC) curve for the CRS cut point of 0.199 were 77, 72, and 80% (95% CI 68–91), respectively. The risk score was calculated for 248 Caribbean and 555 South Asian participants aged 40–75 years in the 1999 Health Survey for England. Undiagnosed hyperglycemia was considered present if fasting plasma glucose was ≥7.0 mmol/l or HbA1c was ≥6.5%. Sensitivity, specificity, and predictive values were calculated for various cut points of the risk score, and ROC curves were constructed. RESULTS—The area under the ROC curve was 67% (59–76) and 72% (67–78) for Caribbeans and South Asians, respectively. The optimal cut point in Caribbean participants was 0.236, sensitivity was 63% (46–77), and specificity was 63% (56–69). In the South Asian population, the optimal cut point was and 0.127, sensitivity was 69% (60–78), and specificity was 64% (60–69). CONCLUSIONS—The CRS, using routinely available data, can be used in a strategy to detect undiagnosed hyperglycemia in Caribbean and South Asian populations. The existence of ethnic group–specific cut points must be further established in future studies.

OBJECTIVE—Type 2 diabetes is a serious disease that is commonly undetected and for which screening is sometimes advocated. A number of risk factors are associated with prevalent undiagnosed diabetes. The use of routinely available information on these factors has been proposed as a simple and effective way of identifying individuals at high risk for having the disease. The objective of this study was to assess the effectiveness of the Cambridge risk score in a large and representative population. RESEARCH DESIGN AND METHODS—A risk score derived from data in a previous study was tested for its ability to detect prevalent undiagnosed hyperglycemia as measured by a GHb ≥6.0, 6.5, or 7% in 6,567 subjects aged 39–78 years in the European Prospective Investigation of Cancer−Norfolk cohort. RESULTS—For a specificity of 78%, the risk score predicted a GHb of ≥7.0% in subjects aged 39–78 years, with a sensitivity of 51% (95% CI 40–62). The areas under the receiver-operating characteristic (ROC) curve for GHb ≥6.0, 6.5, and 7% were 65.7% (63.8–67.6), 71.2% (68.4–75.2), and 74.2% (69.5–79.0), respectively. The area under the ROC curve was not significantly reduced if data on family and smoking history were unavailable for any of the cut-offs for GHb. CONCLUSIONS—The risk score performed as well as other previously reported models in all age groups. We concluded that a simple risk score using data routinely available in primary care can identify people with an elevated GHb with reasonable sensitivity and specificity, and it could therefore form part of a strategy for early detection of type 2 diabetes.

To determine the benefit of multifactorial treatment on microvascular complications among people with type 2 diabetes detected by screening.This study was a multicenter cluster randomized controlled trial in primary care with randomization at the practice level. In four centers in Denmark; Cambridge, U.K.; the Netherlands; and Leicester, U.K., 343 general practices participated in the trial. Eligible for follow-up were 2,861 of the 3,057 people with diabetes detected by screening included in the original trial. Biomedical data on nephropathy were collected in 2,710 (94.7%) participants, retinal photos in 2,190 (76.6%), and questionnaire data on peripheral neuropathy in 2,312 (80.9%). The prespecified microvascular end points were analyzed by intention to treat. Results from the four centers were pooled using fixed-effects meta-analysis.Five years after diagnosis, any kind of albuminuria was present in 22.7% of participants in the intensive treatment (IT) group and in 24.4% in the routine care (RC) group (odds ratio 0.87 [95% CI 0.72-1.07]). Retinopathy was present in 10.2% of the IT group and 12.1% of the RC group (0.84 [0.64-1.10]), and severe retinopathy was present in one patient in the IT group and seven in the RC group. Neuropathy was present in 4.9% and 5.9% (0.95 [0.68-1.34]), respectively. Estimated glomerular filtration rate increased between baseline and follow-up in both groups (4.31 and 6.44 mL/min, respectively).Compared with RC, an intervention to promote target-driven, intensive management of patients with type 2 diabetes detected by screening was not associated with significant reductions in the frequency of microvascular events at 5 years.

OBJECTIVE To examine whether improvements in health behaviors are associated with reduced risk of cardiovascular disease (CVD) in individuals with newly diagnosed type 2 diabetes. RESEARCH DESIGN AND METHODS Population-based prospective cohort study of 867 newly diagnosed diabetic patients aged between 40 and 69 years from the treatment phase of the ADDITION-Cambridge study. Because the results for all analyses were similar by trial arm, data were pooled, and results were presented for the whole cohort. Participants were identified via population-based stepwise screening between 2002 and 2006, and underwent assessment of physical activity (European Prospective Investigation into Cancer-Norfolk Physical Activity Questionnaire), diet (plasma vitamin C and self-report), and alcohol consumption (self-report) at baseline and 1 year. A composite primary CVD outcome was examined, comprised of cardiovascular mortality, nonfatal myocardial infarction, nonfatal stroke, and revascularization. RESULTS After a median (interquartile range) follow-up period of 5.0 years (1.3 years), 6% of the cohort experienced a CVD event (12.2 per 1,000 person-years; 95% CI 9.3–15.9). CVD risk was inversely related to the number of positive health behaviors changed in the year after diabetes diagnosis. The relative risk for primary CVD event in individuals who did not change any health behavior compared with those who adopted three/four healthy behaviors was 4.17 (95% CI 1.02–17.09), adjusting for age, sex, study group, social class, occupation, and prescription of cardioprotective medication (P for trend = 0.005). CONCLUSIONS CVD risk was inversely associated with the number of healthy behavior changes adopted in the year after the diagnosis of diabetes. Interventions that promote early achievement of these goals in patients with newly diagnosed diabetes could help reduce the burden of diabetes-related morbidity and mortality.

OBJECTIVE—To review the effectiveness of interventions targeted at health care professionals and/or the structure of care in order to improve the management of diabetes in primary care, outpatient, and community settings. RESEARCH DESIGN AND METHODS—A systematic review of controlled trials evaluating the effectiveness of interventions targeted at health care professionals and aimed at improving the process of care or patient outcomes for patients with diabetes was performed. Standard search methods of the Cochrane Effective Practice and Organization of Care Group were used. RESULTS—A total of 41 studies met the inclusion criteria. The studies identified were heterogeneous in terms of interventions, participants, settings, and reported outcomes. In all studies, the interventions were multifaceted. The interventions were targeted at health care professionals only in 12 studies, at the organization of care only in 9 studies, and at both in 20 studies. Complex professional interventions improved the process of care, but the effect on patient outcomes remained less clear because such outcomes were rarely assessed. Organizational interventions that facilitated the structured and regular review of patients also showed a favorable effect on process measures. Complex interventions in which patient education was added and/or the role of a nurse was enhanced led to improvements in patient outcomes as well as the process of care. CONCLUSIONS—Multifaceted professional interventions and organizational interventions that facilitate structured and regular review of patients were effective in improving the process of care. The addition of patient education to these interventions and the enhancement of the role of nurses in diabetes care led to improvements in patient outcomes and the process of care.

OBJECTIVE The purpose of this study was to examine the performance of the UK Prospective Diabetes Study (UKPDS) Risk Engine (version 3) and the Framingham risk equations (2008) in estimating cardiovascular disease (CVD) incidence in three populations: 1) individuals with known diabetes; 2) individuals with nondiabetic hyperglycemia, defined as A1C ≥6.0%; and 3) individuals with normoglycemia defined as A1C RESEARCH DESIGN AND METHODS This was a population-based prospective cohort (European Prospective Investigation of Cancer-Norfolk). Participants aged 40–79 years recruited from U.K. general practices attended a health examination (1993–1998) and were followed for CVD events/death until April 2007. CVD risk estimates were calculated for 10,137 individuals. RESULTS Over 10.1 years, there were 69 CVD events in the diabetes group (25.4%), 160 in the hyperglycemia group (17.7%), and 732 in the normoglycemia group (8.2%). Estimated CVD 10-year risk in the diabetes group was 33 and 37% using the UKPDS and Framingham equations, respectively. In the hyperglycemia group, estimated CVD risks were 31 and 22%, respectively, and for the normoglycemia group risks were 20 and 14%, respectively. There were no significant differences in the ability of the risk equations to discriminate between individuals at different risk of CVD events in each subgroup; both equations overestimated CVD risk. The Framingham equations performed better in the hyperglycemia and normoglycemia groups as they did not overestimate risk as much as the UKPDS Risk Engine, and they classified more participants correctly. CONCLUSIONS Both the UKPDS Risk Engine and Framingham risk equations were moderately effective at ranking individuals and are therefore suitable for resource prioritization. However, both overestimated true risk, which is important when one is using scores to communicate prognostic information to individuals.

OBJECTIVE Low levels of physical activity appear to be associated with insulin resistance. However, the detailed associations of these complex relationships remain elusive. We examined the prospective associations between self-reported TV viewing time, objectively measured time spent sedentary, at light-intensity activity, and at moderate- and vigorous-intensity physical activity (MVPA) with insulin resistance. RESEARCH DESIGN AND METHODS In 192 individuals (81 men and 111 women) with a family history of type 2 diabetes, we measured physical activity and anthropometric and metabolic variables at baseline and after 1 year of follow-up in the ProActive UK trial. Physical activity was measured objectively by accelerometry. Insulin resistance was expressed as fasting insulin and the homeostasis model assessment score (HOMA-IR). RESULTS Baseline MVPA was a significant predictor of fasting insulin at follow-up (β = −0.004 [95% CI −0.007 to −0.0001], P = 0.022), and the association approached significance for HOMA-IR (β = −0.003 [−0.007 to 0.000002], P = 0.052), independent of time spent sedentary, at light-intensity activity, sex, age, smoking status, waist circumference, and self-reported TV viewing. Time spent sedentary and at light-intensity activity were not significantly associated with insulin resistance. The change in MVPA between baseline and follow-up was inversely related to fasting insulin (β = −0.003 [−0.007 to −0.0003], P = 0.032) and the HOMA-IR score (β = −0.004 [−0.008 to −0.001], P = 0.015) at follow-up, after adjustment for baseline phenotype in addition to the same confounders as above. CONCLUSIONS These results highlight the importance of promoting moderate-intensity activity such as brisk walking for improving insulin sensitivity and possibly other metabolic risk factors to prevent type 2 diabetes.

OBJECTIVE—To examine the effectiveness of a theory-driven self-management course in reducing cardiovascular risk in patients with screen-detected type 2 diabetes, taking ongoing medical treatment into account. RESEARCH DESIGN AND METHODS—A total of 196 screen-detected patients, receiving either intensive pharmacological or usual-care treatment since diagnosis (3–33 months previously), were subsequently randomized to a control or intervention condition (self-management course). A 2 × 2 factorial design evaluated the behavioral intervention (self-management course versus control) nested within the medical treatment (intensive versus usualcare), using multilevel regression modeling to analyze changes in patients’ BMI, A1C, blood pressure (BP), and lipid profiles over 12 months, from the start of the 3-month course to 9-month follow-up. RESULTS—The self-management course significantly reduced BMI (−0.77 kg/m2) and systolic BP (−6.2 mmHg) up until the 9-month follow-up, regardless of medical treatment. However, intensive medical treatment was also independently associated with lower BP, A1C, total cholesterol, and LDL before the course and further improvements in systolic BP (−4.7 mmHg). Patients receiving both intensive medical treatment and the self-management course therefore had the best outcomes. CONCLUSIONS—This self-management course was effective in achieving sustained reductions in weight and BP, independent of medical treatment. A combination of behavioral and medical interventions is particularly effective in reducing cardiovascular risk in newly diagnosed patients.

OBJECTIVE—We sought to examine the independent associations between different dimensions of physical activity with intermediary and clustered metabolic risk factors in overweight individuals with an increased risk of type 2 diabetes to inform future preventive action. RESEARCH DESIGN AND METHODS—We measured total body movement and five other subcomponents of physical activity by accelerometry in 258 adults (aged 30–50 years) with a family history of type 2 diabetes. We estimated aerobic fitness from an incremental treadmill exercise test. We measured body composition by bioimpedance and waist circumference, blood pressure, fasting triglycerides, HDL cholesterol, glucose, and insulin with standard methods. We constructed a standardized continuously distributed variable for clustered risk. RESULTS—Total body movement (counts · day−1) was significantly and independently associated with three of six risk factors (fasting triglycerides, insulin, and HDL) and with clustered metabolic risk (P = 0.004) after adjustment for age, sex, and obesity. Time spent at moderate- and vigorous-intensity physical activity (MPVA) was independently associated with clustered metabolic risk (P = 0.03). Five- and 10-min bouts of MVPA, time spent sedentary, time spent at light-intensity activity, and aerobic fitness were not significantly related with clustered risk after adjustment for confounding factors. CONCLUSIONS—Total body movement is associated with intermediary phenotypic risk factors for cardiovascular disease and metabolic disease and with clustered metabolic risk independent of aerobic fitness and obesity. Increasing the total amount of physical activity in sedentary and overweight individuals may have beneficial effects on metabolic risk factors.

To assess the performance of the Cambridge Risk Score (CRS) to predict undiagnosed hyperglycemia in Caribbean and South Asian people living in the U.K.The CRS uses routinely available data from primary care records to identify people at high risk for undiagnosed type 2 diabetes. The sensitivity, specificity, and area under the receiver operator characteristic (ROC) curve for the CRS cut point of 0.199 were 77, 72, and 80% (95% CI 68-91), respectively. The risk score was calculated for 248 Caribbean and 555 South Asian participants aged 40-75 years in the 1999 Health Survey for England. Undiagnosed hyperglycemia was considered present if fasting plasma glucose was/=7.0 mmol/l or HbA(1c) was/=6.5%. Sensitivity, specificity, and predictive values were calculated for various cut points of the risk score, and ROC curves were constructed.The area under the ROC curve was 67% (59-76) and 72% (67-78) for Caribbeans and South Asians, respectively. The optimal cut point in Caribbean participants was 0.236, sensitivity was 63% (46-77), and specificity was 63% (56-69). In the South Asian population, the optimal cut point was and 0.127, sensitivity was 69% (60-78), and specificity was 64% (60-69).The CRS, using routinely available data, can be used in a strategy to detect undiagnosed hyperglycemia in Caribbean and South Asian populations. The existence of ethnic group-specific cut points must be further established in future studies.