The advent of sensor-augmented pump therapy with a low-glucose suspend (LGS) function (Medtronic Paradigm Veo System), allowing insulin to be automatically suspended for up to 2 h when sensor glucose falls below a preset threshold, has the potential to reduce the duration of hypoglycemia. In this report, we analyzed blood glucose profiles following a full 2-h insulin suspension activated by the LGS function, as well as examined different patterns of use among patients.

Data from a cohort of participants using the Veo system for up to 6 months were analyzed to determine the time and duration of insulin suspension activated by the LGS function. We further evaluated overnight suspend events with no patient response occurring prior to 3:00 a.m., which allowed us to determine the pattern of sensor glucose values with no patient intervention during and after the period of insulin suspension.

There were 3,128 LGS events during the 2,493 days evaluated. The median duration was 11.2 min, and 36% of events occurred overnight. There were 126 full 2-h suspend events that occurred overnight with no patient response, occurring before 3:00 a.m. For these events, the mean sensor glucose at the end of the 2-h suspend period was 99 ± 6 mg/dL ([means ± SE] 5.5 ± 0.3 mmol/L). The mean sensor glucose 2 h after insulin delivery resumed was 155 ± 10 mg/dL (8.6 ± 0.6 mmol/L). There were no episodes of severe hypoglycemia or diabetic ketoacidosis.

Analyses of sensor glucose patterns following insulin suspension activated by LGS suggest that this technology is safe and unlikely to be associated with adverse outcomes.

We ascertained incident diabetes among 3,740 Cardiovascular Health Study participants (1992–2007) based on use of hypoglycemic medications, fasting glucose ≥126 mg/dL, or nonfasting glucose ≥200 mg/dL. FABP4 and NEFA were measured on specimens collected between 1992 and 1993.

Mean age of the 3,740 subjects studied was 74.8 years. For each SD increase in log-FABP4, hazard ratios (HRs) for diabetes were 1.35 (95% CI 1.10–1.65) for women and 1.45 (1.13–1.85) for men controlling for age, race, education, physical activity, cystatin C, alcohol intake, smoking, self-reported health status, and estrogen use for women (P for sex-FABP4 interaction 0.10). BMI modified the FABP4-diabetes relation (P = 0.009 overall; 0.02 for women and 0.135 for men), in that statistically significant higher risk of diabetes was mainly seen in men with BMI <25 kg/m² (HR per SD: 1.78 [95% CI 1.13–2.81]). There was a modest and nonsignificant association of NEFA with diabetes (P_trend = 0.21). However, when restricted to the first 5 years of follow-up, multivariable-adjusted HRs for diabetes were 1.0 (ref.), 1.68 (95% CI 1.12–2.53), and 1.63 (1.07–2.50) across consecutive tertiles of NEFA (P_trend = 0.03).

Plasma FABP4 was positively associated with incident diabetes in older adults, and such association was statistically significant in lean men only. A significant positive association between plasma NEFA and incident diabetes was observed during the first 5 years of follow-up.

The prospective study included 2,181 type 1 diabetic patients from the EURODIAB Prospective Complications Study. At baseline, frequency of self-reported severe hypoglycemia, defined as episodes serious enough to require the help of another person, was assessed based on responses to a patient questionnaire. Both fatal/nonfatal CVD was assessed 7.3 years after baseline examination. At the follow-up visit, data on both severe and nonsevere hypoglycemic episodes in the previous year were collected through a questionnaire and markers of inflammation/stress response/endothelial injury measured by enzyme-linked immunosorbent assays in the 531 subjects of the nested case-control study, including 363 case subjects with one or more complications of diabetes and 168 control subjects with no evidence of any complication.

During the follow-up period, 176 patients had incident CVD. Logistic regression analysis showed that severe hypoglycemia at the baseline examination was not associated with incidence of CVD (adjusted odds ratios [95% CI]: one to two episodes, 0.87 [0.55–1.37]; three or more episodes, 1.09 [0.68–1.75]). Furthermore, follow-up serum levels of markers of endothelial damage/inflammation were not cross-sectionally associated with the frequency of hypoglycemic episodes.

Taken together our data do not support the hypothesis that in type 1 diabetes, severe hypoglycemia increases the risk of CVD.

We tested the hypothesis that intensive (systolic blood pressure [SBP] <120 mmHg) rather than standard (SBP 130–139 mmHg) blood pressure (BP) control improves health-related quality of life (HRQL) in those with type 2 diabetes.

Subjects were 1,028 ACCORD (Action to Control Cardiovascular Risk in Diabetes) BP trial HRQL substudy participants who completed baseline and one or more 12-, 36-, or 48-month HRQL evaluations. Multivariable linear regression assessed impact of BP treatment assignment on change in HRQL.

Over 4.0 years of follow-up, no significant differences occurred in five of six HRQL measures. Those assigned to intensive (vs. standard) BP control had statistically significant worsening of the Medical Outcomes Study 36-item short-form health survey (SF36) physical component scores (–0.8 vs. –0.2; P = 0.02), but magnitude of change was not clinically significant. Findings persisted across all prespecified subgroups.

Intensive BP control in the ACCORD trial did not have a clinically significant impact, either positive or negative, on depression or patient-reported HRQL.

We evaluated the addition of liraglutide to metformin in type 2 diabetes followed by intensification with basal insulin (detemir) if glycated hemoglobin (A1C) ≥7%.

In 988 participants from North America and Europe uncontrolled on metformin ± sulfonylurea, sulfonylurea was discontinued and liraglutide 1.8 mg/day added for 12 weeks (run-in). Subsequently, those with A1C ≥7% were randomized 1:1 to 26 weeks’ open-label addition of insulin detemir to metformin + liraglutide (n = 162) or continuation without insulin detemir (n = 161). Patients achieving A1C <7% continued unchanged treatment (observational arm). The primary end point was A1C change between randomized groups.

Of 821 participants completing the run-in, 61% (n = 498) achieved A1C <7% (mean change –1.3% from 7.7% at start), whereas 39% (n = 323) did not (–0.6% from 8.3% at start). During run-in, 167 of 988 (17%) withdrew; 46% of these due to gastrointestinal adverse events. At week 26, A1C decreased further, by 0.5% (from 7.6% at randomization) with insulin detemir (n = 162) versus 0.02% increase without insulin detemir (n = 157) to 7.1 and 7.5%, respectively (estimated treatment difference –0.52 [95% CI –0.68 to –0.36]; P < 0.0001). Forty-three percent of participants with insulin detemir versus 17% without reached A1C <7%. Mean weight decreased by 3.5 kg during run-in, then by 0.16 kg with insulin detemir or 0.95 kg without insulin detemir. In the randomized phase, no major hypoglycemia occurred and minor hypoglycemia rates were 0.286 and 0.029 events per participant-year with and without insulin detemir (9.2 vs. 1.3%).

Supplementation of metformin with liraglutide and then insulin detemir was well tolerated in the majority of patients, with good glycemic control, sustained weight loss, and very low hypoglycemia rates.

In the U.K., people with diabetes are typically screened for retinopathy annually. However, diabetic retinopathy sometimes has a slow progression rate. We developed a simulation model to predict the likely impact of screening patients with type 2 diabetes, who have not been diagnosed with diabetic retinopathy, every 2 years rather than annually. We aimed to assess whether or not such a policy would increase the proportion of patients who developed retinopathy-mediated vision loss compared with the current policy, along with the potential cost savings that could be achieved.

We developed a model that simulates the progression of retinopathy in type 2 diabetes patients, and the screening of these patients, to predict rates of retinopathy-mediated vision loss. We populated the model with data obtained from a National Health Service Foundation Trust. We generated comparative 15-year forecasts to assess the differences between the current and proposed screening policies.

The simulation model predicts that implementing a 2-year screening interval for type 2 diabetes patients without evidence of diabetic retinopathy does not increase their risk of vision loss. Furthermore, we predict that this policy could reduce screening costs by ~25%.

Screening people with type 2 diabetes, who have not yet developed retinopathy, every 2 years, rather than annually, is a safe and cost-effective strategy. Our findings support those of other studies, and we therefore recommend a review of the current National Institute for Health and Clinical Excellence (NICE) guidelines for diabetic retinopathy screening implemented in the U.K.

We assessed the utility of the Diabetes Prevention Trial–Type 1 Risk Score (DPTRS) for identifying individuals who are highly likely to progress to type 1 diabetes (T1D) within 2 years.

The DPTRS was previously developed from Diabetes Prevention Trial–Type 1 (DPT-1) data and was subsequently validated in the TrialNet Natural History Study (TNNHS). DPTRS components included C-peptide and glucose indexes from oral glucose tolerance testing, along with age and BMI. The cumulative incidence of T1D was determined after DPTRS thresholds were first exceeded and after the first occurrences of glucose abnormalities.

The 2-year risks after the 9.00 DPTRS threshold was exceeded were 0.88 and 0.77 in DPT-1 (n = 90) and the TNNHS (n = 69), respectively. In DPT-1, the 2-year risks were much lower after dysglycemia first occurred (0.37; n = 306) and after a 2-h glucose value between 190 and 199 mg/dL was first reached (0.64; n = 59). Among those who developed T1D in DPT-1, the 9.00 threshold was exceeded 0.81 ± 0.53 years prior to the conventional diagnosis. Postchallenge C-peptide levels were substantially higher (P = 0.001 for 30 min; P < 0.001 for other time points) when the 9.00 threshold was first exceeded compared with the levels at diagnosis.

A DPTRS threshold of 9.00 identifies individuals who are very highly likely to progress to the conventional diagnosis of T1D within 2 years and, thus, are essentially in a preclinical diabetic state. The 9.00 threshold is exceeded well before diagnosis, when stimulated C-peptide levels are substantially higher.

Metabolite predictors of deteriorating glucose tolerance may elucidate the pathogenesis of type 2 diabetes. We investigated associations of circulating metabolites from high-throughput profiling with fasting and postload glycemia cross-sectionally and prospectively on the population level.

Oral glucose tolerance was assessed in two Finnish, population-based studies consisting of 1,873 individuals (mean age 52 years, 58% women) and reexamined after 6.5 years for 618 individuals in one of the cohorts. Metabolites were quantified by nuclear magnetic resonance spectroscopy from fasting serum samples. Associations were studied by linear regression models adjusted for established risk factors.

Nineteen circulating metabolites, including amino acids, gluconeogenic substrates, and fatty acid measures, were cross-sectionally associated with fasting and/or postload glucose (P < 0.001). Among these metabolic intermediates, branched-chain amino acids, phenylalanine, and α1-acid glycoprotein were predictors of both fasting and 2-h glucose at 6.5-year follow-up (P < 0.05), whereas alanine, lactate, pyruvate, and tyrosine were uniquely associated with 6.5-year postload glucose (P = 0.003–0.04). None of the fatty acid measures were prospectively associated with glycemia. Changes in fatty acid concentrations were associated with changes in fasting and postload glycemia during follow-up; however, changes in branched-chain amino acids did not follow glucose dynamics, and gluconeogenic substrates only paralleled changes in fasting glucose.

Alterations in branched-chain and aromatic amino acid metabolism precede hyperglycemia in the general population. Further, alanine, lactate, and pyruvate were predictive of postchallenge glucose exclusively. These gluconeogenic precursors are potential markers of long-term impaired insulin sensitivity that may relate to attenuated glucose tolerance later in life.

We used a mixed-methods approach to explore the relationships between participants’ perceptions of family members’ diabetes self-care knowledge, family members’ diabetes-specific supportive and nonsupportive behaviors, and participants’ medication adherence and glycemic control (A1C).

Adults with type 2 diabetes participated in focus group sessions that discussed barriers and facilitators to diabetes management (n = 45) and/or completed surveys (n = 61) to collect demographic information, measures of diabetes medication adherence, perceptions of family members’ diabetes self-care knowledge, and perceptions of family members’ diabetes-specific supportive and nonsupportive behaviors. Most recent A1C was extracted from the medical record.

Perceiving family members were more knowledgeable about diabetes was associated with perceiving family members performed more diabetes-specific supportive behaviors, but was not associated with perceiving family members performed fewer nonsupportive behaviors. Perceiving family members performed more nonsupportive behaviors was associated with being less adherent to one’s diabetes medication regimen, and being less adherent was associated with worse glycemic control. In focus groups, participants discussed family member support and gave examples of family members who were informed about diabetes but performed sabotaging or nonsupportive behaviors.

Participant reports of family members’ nonsupportive behaviors were associated with being less adherent to one’s diabetes medication regimen. Participants emphasized the importance of instrumental help for diabetes self-care behaviors and reported that nonsupportive family behaviors sabotaged their efforts to perform these behaviors. Interventions should inform family members about diabetes and enhance their motivation and behavioral skills around not interfering with one's diabetes self-care efforts.

Using data from the National Health and Nutrition Examination Survey, 1999–2008, we identified 1,221 U.S. adults (age 18–64 years) with self-reported diabetes. Access was measured by current health insurance coverage, number of times health care was received over the past year, and routine place to go for health care. Diabetes control measures included the proportion of people with A1C >9%, blood pressure ≥140/90 mmHg, and non-HDL cholesterol ≥130 mg/dL.

An estimated 16.0% of known diabetic adults were uninsured. Diabetes control profiles were worse among uninsured than among insured persons (A1C >9% [34.1 vs. 16.5%, P = 0.002], blood pressure ≥140/90 mmHg [31.8 vs. 22.8%, P < 0.05], and non-HDL cholesterol ≥130 mg/dL [67.1 vs. 65.4%, P = 0.7]). Compared with insured persons, uninsured persons were more likely to have A1C >9% (multivariate-adjusted odds ratio 2.4 [95% CI 1.2–4.7]). Compared with those who reported four or more health care visits in the past year, those who reported no health care visits were more likely to have A1C >9% (5.5 [1.2–26.3]) and blood pressure ≥140/90 mmHg (1.9[1.1–3.4]).

In people with diabetes, lack of health care coverage is associated with poor glycemic control. In addition, low use of health care service is associated with poor glucose and blood pressure control.

Levels of AGE-LDL and oxLDL in ICs were measured in 517 patients of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) cohort. Retinopathy was assessed by stereoscopic fundus photography. Cox proportional hazards models were used to assess the effect of AGE-LDL-ICs and oxLDL-ICs on retinopathy progression.

In unadjusted models, higher baseline levels of AGE-LDL-ICs and oxLDL-ICs significantly predicted progression of diabetic retinopathy outcomes. After adjustment by study-design variables (treatment group, retinopathy cohort, duration of type 1 diabetes, and baseline albumin excretion rate [AER], hemoglobin A_1c (HbA_1c), and Early Treatment Diabetic Retinopathy Study [ETDRS] score), one SD increase in IC levels was associated with 47% (hazard ratio [HR] 1.47 [95% CI 1.19–1.81]; AGE-LDL-IC) and 45% (1.45 [1.17–1.80]; oxLDL-IC) increased risk of developing proliferative diabetic retinopathy (PDR) and 37% (1.37 [1.12–1.66]; to both ICs) increased risk of progressing to severe nonproliferative retinopathy. Analyses were stratified by retinopathy cohort because results differed between primary and secondary cohorts. For AGE-LDL-ICs, HR for progression to PDR was 2.38 (95% CI 1.30–4.34) in the primary cohort and attenuated in the secondary cohort (1.29 [1.03–1.62]). Similar results were observed for oxLDL-ICs.

Increased levels of AGE-LDL and oxLDL in ICs are associated with increased risk for progression to advanced retinopathy in patients with type 1 diabetes, indicating that the antibody response to modified LDL plays a significant role in retinopathy progression.

We assembled data from hyperinsulinemic-euglycemic clamps (120 mU/m² ⋅ min insulin dose) performed at the Pennington Biomedical Research Center between 2001 and 2011. Subjects were divided into subjects with diabetes (n = 51) and subjects without diabetes (n = 116) by self-report and/or fasting glucose ≥126 mg/dL.

We found that 75% of individuals with a GDR <5.6 mg/kg fat-free mass (FFM) + 17.7 ⋅ min were truly insulin resistant. Cutoff values for GDRs normalized for body weight, body surface area, or FFM were 4.9 mg/kg ⋅ min, 212.2 mg/m² ⋅ min, and 7.3 mg/kgFFM ⋅ min, respectively. Next, we used classification tree models to predict GDR from routinely measured clinical and biochemical variables. We found that individual insulin resistance could be estimated with good sensitivity (89%) and specificity (67%) from the homeostasis model assessment of insulin resistance (HOMA-IR) >5.9 or 2.8< HOMA-IR <5.9 with HDL <51 mg/dL.

We developed a cutoff for defining insulin resistance from hyperinsulinemic-euglycemic clamps. Moreover, we now provide classification trees for predicting insulin resistance from routinely measured clinical and biochemical markers. These findings extend the clamp from a research tool to providing a clinically meaningful message for participants in research studies, potentially providing greater opportunity for earlier recognition of insulin resistance.

A prospective cohort of 3,413 Americans, aged 18–30 years, without HTN in 1985 (baseline) were enrolled. Six follow-ups were conducted in 1987, 1990, 1992, 1995, 2000, and 2005. Fasting insulin and glucose levels were assessed by a radioimmunoassay and hexokinase method, respectively. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% CIs of incident HTN (defined as the initiation of antihypertensive medication, systolic blood pressure ≥140 mmHg, or diastolic blood pressure ≥90 mmHg).

During the 20-year follow-up, 796 incident cases were identified. After adjustment for potential confounders, participants in the highest quartile of insulin levels had a significantly higher incidence of HTN (HR 1.85 [95% CI 1.42–2.40]; P_trend < 0.001) compared with those in the lowest quartile. The positive association persisted in each sex/ethnicity/weight status subgroup. A similar dose-response relation was observed when insulin-to-glucose ratio or homeostatic model assessment of insulin resistance was used as exposure.

Fasting serum insulin levels or hyperinsulinemia in young adulthood was positively associated with incidence of HTN later in life for both men and women, African Americans and Caucasians, and those with normal weight and overweight. Our findings suggested that fasting insulin ascertainment may help clinicians identify those at high risk of HTN.

To assess the association of compliance with treatment (medication and clinic appointments) and all-cause mortality in people with insulin-treated type 2 diabetes.

Data were extracted from U.K. general practice records and included patients (N = 15,984) who had diagnostic codes indicative of type 2 diabetes or who had received a prescription for an oral antidiabetic agent and were treated with insulin. Records in the 30 months before the index date were inspected for clinical codes (recorded at consultation) indicating medication noncompliance or medical appointment nonattendance. Noncompliance was defined as missing more than one scheduled visit or having at least one provider code for not taking medications as prescribed. Relative survival postindex date was compared by determining progression to all-cause mortality using Cox proportional hazards models.

Those identified as clinic nonattenders were more likely to be smokers, younger, have higher HbA_1c, and have more prior primary care contacts and greater morbidity (P < 0.001). Those identified as medication noncompliers were more likely to be women (P = 0.001), smokers (P = 0.014), and have higher HbA_1c, more prior primary care contacts, and greater morbidity (all P < 0.001). After adjustment for confounding factors, medication noncompliance (hazard ratio 1.579 [95% CI 1.167–2.135]), clinic nonattendance of one or two missed appointments (1.163 [1.042–1.299]), and clinic nonattendance of greater than two missed appointments (1.605 [1.356–1.900]) were independent risk factors for all-cause mortality.

Medication noncompliance and clinic nonattendance, assessed during routine care by primary care physicians or their staff, were independently associated with increased all-cause mortality in patients with type 2 diabetes receiving insulin.

To assess potential alterations in soluble and endogenous secretory receptors for advanced glycation end products (sRAGE and esRAGE) in normal-weight (NW) and obese (Ob) children born small (SGA) and large (LGA) compared with appropriate for gestational age (AGA) subjects and to explore if birth weight (BW), insulin resistance (IR), and obesity represent independent risk factors.

We categorized 130 prepubertal children into six groups according to BW and obesity and evaluated sRAGE, esRAGE, and homeostasis model assessment of IR.

sRAGE and esRAGE were lower in Ob SGA and LGA children than Ob AGA subjects (all P < 0.05), and in NW SGA and LGA children than NW AGA subjects (all P < 0.05). Interestingly, BW and IR were significantly and independently related to RAGE.

sRAGE and esRAGE are decreased in SGA and LGA children, and BW and IR seem to play an important role in the reduction of RAGE.

This retrospective cohort study included 455 chronic kidney disease (CKD) patients (144 with type 2 diabetic nephropathy and 311 with nondiabetic CKD) who were hospitalized at Osaka General Medical Center for a CKD educational program between April 2001 and December 2007. The primary outcome was progression to renal replacement therapy. Participants were categorized based on serum Mg level into Low-Mg (serum Mg level ≤1.8 mg/dL) and High-Mg (serum Mg level >1.8 mg/dL) groups with the previously published normal lower limit chosen as the cutoff point.

Of the subjects with type 2 diabetic nephropathy, 102 progressed to ESRD during follow-up (median, 23 months). A multivariate Cox proportional hazards model showed that after adjustment for various demographic factors and laboratory data, the Low-Mg group had a 2.12-fold higher risk of ESRD than the High-Mg group (95% CI 1.28–3.51; P = 0.004). In contrast, 135 of the nondiabetic CKD subjects progressed to ESRD during follow-up (median, 44 months). No significant difference in outcome was found between the Low- and High-Mg groups of this population (adjusted hazard ratio, 1.15; 95% CI 0.70–1.90; P = 0.57).

Hypomagnesemia is a novel predictor of ESRD in patients with type 2 diabetic nephropathy.

A total of 1,016 subjects, aged 70 years, were investigated in the Prospective Investigation of the Vasculature in Uppsala Seniors Study. Four phthalate metabolites were detected in almost all participant sera by an API 4000 liquid chromatograph/tandem mass spectrometer. Type 2 diabetes was defined as the use of pharmacological hypoglycemic agents or a fasting plasma glucose >7.0 mmol/L.

A total of 114 subjects were shown to have diabetes. Following adjustment for sex, BMI, serum cholesterol and triglycerides, educational level, and smoking and exercise habits, high levels of the phthalate metabolites monomethyl phthalate (MMP) (P < 0.01), monoisobutyl phthalate (MiBP) (P < 0.05), and monoethyl phthalate (MEP) (P < 0.05), but not mono(2-ethylhexyl) phthalate, were associated with an increased prevalence of diabetes. Using the fasting proinsulin–to–insulin ratio as a marker of insulin secretion and the homeostasis model assessment-insulin resistance index as a marker of insulin resistance, MiBP was mainly related to poor insulin secretion, whereas MEP and MMP mainly were related to insulin resistance.

The findings in this cross-sectional study showed that several phthalate metabolites are related to diabetes prevalence, as well as to markers of insulin secretion and resistance. These findings support the view that these commonly used chemicals might influence major factors that are regulating glucose metabolism in humans at the level of exposure of phthalate metabolites seen in the general elderly population.

We conducted a cross-sectional descriptive study to determine the prevalence of two types of incorrect COD causal sequences with data from the Multiple Cause Mortality File of the year 2004.

Among deaths in which diabetes was reported as the first diagnosis on line a, b, c, or d in Part I of the death certificate in the U.S., 21% had below diabetes placement error (ranged from 30% in Maryland to 7% in Hawaii) and 11% had above diabetes placement error (ranged from 18% in Kentucky to 5% in California). The net effects of the two types of error ranged from –0.7% in Nevada to 19.6% in the District of Columbia.

Because the rates of incorrect reporting of diabetes-related COD causal sequence varied across states, the comparability of the diabetes death rate between states may have been compromised.

Data came from 1,233 adults who self-reported diabetes in the 2005–2008 National Health and Nutrition Examination Survey. Participants reported their last ABC level and goals specified by their physician (not validated by medical record data). Analysis included descriptive statistics and logistic regression.

Among participants tested in the past year, 48% stated their last A1C level. Overall, 63% stated their last blood pressure level and 22% stated their last LDL cholesterol level. Knowledge of ABC levels was greatest in non-Hispanic whites, lowest in Mexican Americans, and higher with more education and income (all P ≤ 0.02). Demographic associations were similar for those reporting physician-specified ABC goals at the American Diabetes Association–recommended levels (A1C <7%, blood pressure <130/80 mmHg, and LDL cholesterol <100 mg/dL). Nineteen percent of participants stated that their provider did not specify an A1C goal compared with 47% and 41% for blood pressure and LDL cholesterol goals, respectively. For people who self-reported A1C <7.0%, 83% had an actual A1C <7.0%. Otherwise, participant knowledge was not significantly associated with risk factor control, except for in those who knew their last LDL cholesterol level (P = 0.046 for A1C <7.0%). Results from logistic regression corroborated these findings.

Ample opportunity exists to improve ABC knowledge. Diabetes education should include behavior change components in addition to information on ABC clinical measures.

To evaluate the effects of canagliflozin, a sodium-glucose cotransporter 2 inhibitor, in type 2 diabetes mellitus inadequately controlled with metformin monotherapy.

This was a double-blind, placebo-controlled, parallel-group, multicenter, dose-ranging study in 451 subjects randomized to canagliflozin 50, 100, 200, or 300 mg once daily (QD) or 300 mg twice daily (BID), sitagliptin 100 mg QD, or placebo. Primary end point was change in A1C from baseline through week 12. Secondary end points included change in fasting plasma glucose (FPG), body weight, and overnight urinary glucose-to-creatinine ratio. Safety and tolerability were also assessed.

Canagliflozin was associated with significant reductions in A1C from baseline (7.6–8.0%) to week 12: –0.79, –0.76, –0.70, –0.92, and –0.95% for canagliflozin 50, 100, 200, 300 mg QD and 300 mg BID, respectively, versus –0.22% for placebo (all P < 0.001) and –0.74% for sitagliptin. FPG was reduced by –16 to –27 mg/dL, and body weight was reduced by –2.3 to –3.4%, with significant increases in urinary glucose-to-creatinine ratio. Adverse events were transient, mild to moderate, and balanced across arms except for a non–dose-dependent increase in symptomatic genital infections with canagliflozin (3–8%) versus placebo and sitagliptin (2%). Urinary tract infections were reported without dose dependency in 3–9% of canagliflozin, 6% of placebo, and 2% of sitagliptin arms. Overall incidence of hypoglycemia was low.

Canagliflozin added onto metformin significantly improved glycemic control in type 2 diabetes and was associated with low incidence of hypoglycemia and significant weight loss. The safety/tolerability profile of canagliflozin was favorable except for increased frequency of genital infections in females.

Data were drawn from the baseline assessment of the QUALITY cohort, which included 630 white youth (aged 8–10 years at recruitment), with at least one obese biological parent. IS was measured by two fasting indices (insulin, homeostasis model assessment of insulin resistance) and an oral glucose tolerance test (OGTT)–based index (Matsuda IS index [Matsuda-ISI]). Fitness was measured by Vo_2peak; percent fat mass (PFM) was measured by dual-energy X-ray absorptiometry; 7-day MVPA was measured with accelerometry. SB indicators included average hours daily of self-report screen time (SBst), and average minutes daily at <100 counts/min from accelerometry (SBacc). Multivariable linear regression models were adjusted for age, sex, season, and puberty.

MVPA and SBacc were independently associated with IS, but this was no longer statistically significant after accounting for PFM. SBst was negatively associated with IS in girls only, even after controlling for physical activity (PA), fitness, and adiposity; for each additional hour of SBst daily, IS decreased by 4.6–5.6% across all IS indices. Fitness was positively associated with IS (measured by Matsuda-ISI) after accounting for PA, SB, and PFM; for every 1 unit increase in Vo_2peak, Matsuda-ISI increased by approximately 1.0% (P < 0.05).

In children with an obese parent, PA and SBacc are associated with IS, but this association is mediated by adiposity. SBst is negatively associated with IS in girls, beyond its known impact on adiposity. Finally, fitness is independently associated with better IS measured by OGTT.

One hundred ten patients with type 2 diabetes were randomized to receive sweet foods containing either 50 g/day isomaltulose or sucrose for 12 weeks as part of their habitual diet under free-living conditions. HbA_1c at 12 weeks was the primary outcome parameter.

In the final analysis comprising 101 patients, isomaltulose did not significantly affect HbA_1c at 12 weeks (sucrose: 7.39 ± 0.78%, isomaltulose: 7.24 ± 0.76%; regression coefficient [b]: 0.02 [95% CI: –0.21 to 0.25], P = 0.844). Triglycerides at 12 weeks were significantly lower in the isomaltulose versus the sucrose group (b: 34.01 [6.59–61.44], P = 0.016). Other secondary parameters did not significantly differ between groups.

Isomaltulose did not influence glycemic control assessed as HbA_1c in type 2 diabetes under free-living conditions but was associated with lower triglyceride levels.

We examined the 11-year incidence of T2D in relation to quantity and variety of fruit, vegetables, and combined F&V intake in a case-cohort study of 3,704 participants (n = 653 diabetes cases) nested within the European Prospective Investigation into Cancer and Nutrition-Norfolk study, who completed 7-day prospective food diaries. Variety of intake was derived from the total number of different items consumed in a 1-week period. Multivariable, Prentice-weighted Cox regression was used to estimate hazard ratios (HRs) and 95% CIs.

A greater quantity of combined F&V intake was associated with 21% lower hazard of T2D (HR 0.79 [95% CI 0.62–1.00]) comparing extreme tertiles, in adjusted analyses including variety. Separately, quantity of vegetable intake (0.76 [0.60–0.97]), but not fruit, was inversely associated with T2D in adjusted analysis. Greater variety in fruit (0.70 [0.53–0.91]), vegetable (0.77 [0.61–0.98]), and combined F&V (0.61 [0.48–0.78]) intake was associated with a lower hazard of T2D, independent of known confounders and quantity of intake comparing extreme tertiles.

These findings suggest that a diet characterized by a greater quantity of vegetables and a greater variety of both F&V intake is associated with a reduced risk of T2D.

Using a nationwide health checkup database of 228,778 Japanese aged ≥20 years (mean 63.2 years; 39.3% men; none had pre-existing cardiovascular disease), we examined the association between high pulse pressure, defined as the highest quintile of pulse pressure (≥63 mmHg, n = 40,511), and proteinuria (≥1+ on dipstick, n = 12,090) separately in subjects with diabetes (n = 27,913), prediabetes (n = 100,214), and normal glucose tolerance (n = 100,651).

The prevalence of proteinuria was different among subjects with diabetes, prediabetes, and normal glucose tolerance (11.3 vs. 5.0 vs. 3.9%, respectively; P < 0.001). In subjects with diabetes, but not those with prediabetes or normal glucose tolerance, high pulse pressure was associated with proteinuria independently of significant covariates, including systolic BP (odds ratio 1.15 [95% CI 1.04–1.28]) or diastolic or mean BP (all P < 0.01). In patients with diabetes, a +1 SD increase of pulse pressure (+13 mmHg) was associated with proteinuria, even after adjustment for systolic BP (1.07 [1.00–1.13]) or diastolic or mean BP (all P < 0.05).

Among the Japanese general population, there was a significant difference in the association between high pulse pressure and proteinuria among subjects with diabetes, prediabetes, and normal glucose tolerance. Only in diabetes was high pulse pressure associated with proteinuria independent of systolic, diastolic, or mean BP levels.

We conducted a 2-year longitudinal, multisite study of 225 youth with type 1 diabetes recruited at the cusp of adolescence (aged 9–11 years) to describe the mutual influences of glycemic control as measured by HbA_1c and treatment adherence as measured by blood glucose monitoring frequency (BGMF) during the transition to adolescence.

HbA_1c increased from 8.2 to 8.6% (P < 0.001) and BGMF decreased from 4.9 to 4.5 checks per day (P < 0.02) during the 2-year period. Changes in the BGMF slope predicted changes in HbA_1c. A change (increase) in HbA_1c was associated with a change (decrease) in BGMF of 1.26 (P < 0.001) after controlling for covariates.

The magnitude of the effect of declining treatment adherence (BGMF) on glycemic control in young adolescents may be even greater than declines observed among older adolescents. BGMF offers a powerful tool for targeted management of glycemic control for type 1 diabetes during the critical transition to adolescence.

The hyperinsulinemic-euglycemic clamp procedure with stable isotopically labeled tracer infusions was performed in 40 obese (BMI 36.2 ± 0.6 kg/m², mean ± SEM) and 26 lean (22.5 ± 0.3 kg/m²) subjects with normal glucose tolerance. Insulin was infused at different rates to achieve low, medium, and high physiological plasma concentrations.

In obese subjects, palmitate and glucose R_a in plasma decreased with increasing plasma insulin concentrations. The decrease in endogenous glucose R_a was greater during low-, medium-, and high-dose insulin infusions (69 ± 2, 74 ± 2, and 90 ± 2%) than the suppression of palmitate R_a (52 ± 4, 68 ± 1, and 79 ± 1%). Insulin-mediated increase in glucose disposal ranged from 24 ± 5% at low to 253 ± 19% at high physiological insulin concentrations. The suppression of palmitate R_a and glucose R_a were greater in lean than obese subjects during low-dose insulin infusion but were the same in both groups during high-dose insulin infusion, whereas stimulation of glucose R_d was greater in lean than obese subjects across the entire physiological range of plasma insulin.

Endogenous glucose production and adipose tissue lipolytic rate are both very sensitive to small increases in circulating insulin, whereas stimulation of muscle glucose uptake is minimal until high physiological plasma insulin concentrations are reached. Hyperinsulinemia within the normal physiological range can compensate for both liver and adipose tissue insulin resistance, but not skeletal muscle insulin resistance, in obese people who have normal glucose tolerance.

For this analysis, 2,256 relatives positive for at least one BAA, of whom 142 developed diabetes, were tested for ZnT8A, ICA, and HLA genotype followed by biannual oral glucose tolerance tests. ZnT8A were also tested in 911 randomly chosen antibody-negative relatives.

ZnT8A were associated with the other BAA (548 of 2,256 [24.3%] BAA⁺ vs. 8 of 911 [0.8%] BAA^–, P < 0.001) and BAA number (177 of 1,683 [10.5%] single-, 221 of 384 [57.6%] double-, and 150 of 189 [79.4%] triple-BAA positivity, P < 0.001). The 4-year diabetes risk was higher in single BAA⁺ relatives with ZnT8A than ZnT8A^– relatives (31 vs. 7%, P < 0.001). In multivariable analysis, age ≤20 years (hazard ratio 2.13, P = 0.03), IA-2A (2.15, P = 0.005), IAA (1.73, P = 0.01), ICA (2.37, P = 0.002), and ZnT8A (1.87, P = 0.03) independently predicted diabetes, whereas HLA type (high and moderate vs. low risk) and GAD65A did not (P = 0.81 and 0.86, respectively).

In relatives with one standard BAA, ZnT8A identified a subset at higher diabetes risk. ZnT8A predicted diabetes independently of ICA, the standard BAA, age, and HLA type. ZnT8A should be included in type 1 diabetes prediction and prevention studies.

Treatment-naive patients or those receiving metformin, sulfonylurea, or thiazolidinedione entered a 10-week pioglitazone dose-optimization period with only pioglitazone. They were then randomized, along with patients previously receiving pioglitazone ≥30 mg, to 48 weeks of double-blind dapagliflozin 5 (n = 141) or 10 mg (n = 140) or placebo (n = 139) every day plus open-label pioglitazone. The primary objective compared hemoglobin A1c (HbA1c) change from baseline with dapagliflozin plus pioglitazone versus placebo plus pioglitazone at week 24. Primary analysis was based on ANCOVA model using last observation carried forward; all remaining analyses used repeated-measures analysis.

At week 24, the mean reduction from baseline in HbA1c was –0.42% for placebo versus –0.82 and –0.97% for dapagliflozin 5 and 10 mg groups, respectively (P = 0.0007 and P < 0.0001 versus placebo). Patients receiving pioglitazone alone had greater weight gain (3 kg) than those receiving dapagliflozin plus pioglitazone (0.7–1.4 kg) at week 48. Through 48 weeks: hypoglycemia was rare; more events suggestive of genital infection were reported with dapagliflozin (8.6–9.2%) than placebo (2.9%); events suggestive of urinary tract infection showed no clear drug effect (5.0–8.5% for dapagliflozin and 7.9% for placebo); dapagliflozin plus pioglitazone groups had less edema (2.1–4.3%) compared with placebo plus pioglitazone (6.5%); and congestive heart failure and fractures were rare.

In patients with type 2 diabetes inadequately controlled on pioglitazone, the addition of dapagliflozin further reduced HbA1c levels and mitigated the pioglitazone-related weight gain without increasing hypoglycemia risk.

Beginning in 2000, survey and medical record information was obtained from 8,334 participants in Translating Research Into Action for Diabetes (TRIAD), a multicenter prospective observational study of diabetes care in managed care. The National Death Index was searched annually to obtain data on deaths over an 8-year follow-up period (2000–2007). Predictors examined included age, sex, race, education, income, smoking, age at diagnosis of diabetes, duration and treatment of diabetes, BMI, complications, comorbidities, and medication use.

There were 1,616 (19%) deaths over the 8-year period. In the most parsimonious equation, the predictors of all-cause mortality included older age, male sex, white race, lower income, smoking, insulin treatment, nephropathy, history of dyslipidemia, higher LDL cholesterol, angina/myocardial infarction/other coronary disease/coronary angioplasty/bypass, congestive heart failure, aspirin, beta blocker, and diuretic use, and higher Charlson Index.

Risk of death can be predicted in people with type 2 diabetes using simple demographic, socioeconomic, and biological risk factors with fair reliability. Such prediction equations are essential for computer simulation models of diabetes progression and may, with further validation, be useful for patient management.

We performed a cohort study of 3,138 Cardiovascular Health Study participants (age ≥65 years) without diabetes. Insulin sensitivity index (ISI) was calculated from fasting and 2-h postload insulin and glucose concentrations. Associations of ISI and fasting insulin concentration with all-cause mortality were tested using Cox proportional hazards models, adjusting for demographic variables, prevalent cardiovascular disease, lifestyle variables, waist circumference, and LDL cholesterol. Subsequent models were additionally adjusted for or stratified by glomerular filtration rate estimated using serum cystatin C (eGFR).

A total of 1,810 participants died during the 14.7 year median follow-up. Compared with the highest quartile of ISI, the lowest quartile (most insulin resistant) was associated with 21% (95% CI 6–41) and 11% (–3 to 29) higher risks of death without and with adjustment for eGFR, respectively. Compared with the lowest quartile of fasting insulin concentration, the highest quartile was associated with 22% (4–43) and 4% (–12 to 22) higher risks of death without and with adjustment for eGFR, respectively. Similar attenuation by eGFR was observed when blood pressure, triglycerides, HDL cholesterol, and C-reactive protein were included in models.

Insulin resistance measured as ISI or fasting insulin concentration is associated with increased risk of death among older adults, adjusting for conventional confounding characteristics. Impaired kidney function may mediate or confound this relationship.

In total, 342 prevalent youth (aged 1–18 years) with type 2 diabetes, 1,011 youth with type 1 diabetes, and 1,710 control subjects identified from 1986 to 2007 were anonymously linked to health care records housed at the Manitoba Centre for Health Policy to assess long-term outcomes using ICD codes.

Youth with type 2 diabetes were found to have a fourfold increased risk of renal failure versus youth with type 1 diabetes. Risk factors associated with renal failure were renin angiotensin aldosterone system inhibitor use and albuminuria in adolescence. Compared with control subjects (age, sex, and postal code matched), youth with type 2 diabetes had a 23-fold increased risk of renal failure and a 39-fold increased risk of dialysis. Kaplan-Meier survival at 10 years was 91.4% in the type 2 diabetic group versus 99.5% in the type 1 diabetic group (P < 0.0001). Renal survival was 100% at 10 years in both groups. It decreased to 92.0% at 15 years and 55.0% at 20 years in the type 2 diabetic group but remained stable in the type 1 diabetic group (P < 0.0001).

Youth with type 2 diabetes are at high risk of adverse renal outcomes and death. Albuminuria and angiotensin aldosterone system inhibitor use, which may be a marker of severity of disease, are associated with poor outcomes in early adulthood.

At 8, 14, 21, 27, and 33 gestational weeks, insulin requirements and hemoglobin A_1c were compared between 15 twin pregnant women from 2000 to 2011 and 108 singleton pregnant women from 2004 to 2006.

In twin pregnancies, the weekly increase in daily insulin dose between 14 and 27 weeks was higher than in singleton pregnancies (median 3.0 [range 0.9–4.9] versus 1.5 international units [–1.5–5.9]; P = 0.008) and remained stable from 27 to 33 weeks. The increment in total insulin requirement from before pregnancy until 33 weeks tended to be higher in twin pregnancies (103 [36–257%] versus 71% [–20–276%]; P = 0.07). Throughout pregnancy, hemoglobin A_1c was similar in twin and singleton pregnancies.

In twin pregnancies, the weekly increase in insulin dose between 14 and 27 weeks was doubled compared with singleton pregnancies.

Maternal and in utero enterovirus infections were studied in 171 offspring who presented with type 1 diabetes before the age of 11 years and in 316 control subjects matched for date and place of birth, gender, and HLA-DQ risk alleles for diabetes. Acute enterovirus infections were diagnosed by increases in enterovirus IgG and IgM in samples taken from the mother at the end of the first trimester of pregnancy and cord blood samples taken at delivery.

Signs of maternal enterovirus infection were observed in altogether 19.3% of the mothers of affected children and in 12.0% of the mothers of control children (P = 0.038). This difference was seen in different HLA risk groups and in both genders of the offspring, and it was unrelated to the age of the child at the diagnosis of diabetes or the age of the mother at delivery.

These results suggest that an enterovirus infection during pregnancy is not a major risk factor for type 1 diabetes in childhood but may play a role in some susceptible subjects.

Retrospective cohort study (fiscal year [FY] 2001 to FY 2004) of 42,826 veterans with new-onset diabetes in FY 2003. Veterans were classified into five chronic comorbid illness groups (CCIGs): none, concordant only, discordant only, both concordant and discordant, and dominant. Five diabetes-related care measures were assessed in FY 2004 (guideline-consistent testing and treatment goals for HbA_1c and LDL cholesterol and diabetes-related outpatient visits). Analyses included logistic regressions adjusting for age, race, sex, marital status, priority code, and interaction between CCIGs and visit frequency.

Only 20% of patients had no comorbidities. Mean number of visits per year ranged from 7.8 (no CCIG) to 17.5 (dominant CCIG). In unadjusted analyses, presence of any illness was associated with equivalent or better care. In the fully adjusted model, we found interaction between CCIG and visit frequency. When visits were <7 per year, the odds of meeting the goal of HbA_1c <8% were similar in the concordant (odds ratio 0.96 [95% CI 0.83–1.11]) and lower in the discordant (0.90 [0.81–0.99]) groups compared with the no comorbidity group. Among patients with >24 visits per year, these odds were insignificant. Dominant CCIG was associated with substantially reduced care for glycemic control for all visit categories and for lipid management at all but the highest visit category.

Our study indicates that diabetes care varies by types of comorbidity. Concordant illnesses result in similar or better care, regardless of visit frequency. Discordant illnesses are associated with diminished care: an effect that decreases as visit frequency increases.

Individuals were selected for diagnostic sequencing if they displayed features atypical for their diagnostic label. From 247 case subjects with clinically labeled type 1 diabetes, we sequenced hepatocyte nuclear factor 1 α (HNF1A) and hepatocyte nuclear factor 4 (HNF4A) in 20 with residual β-cell function ≥3 years from diagnosis (random or glucagon-stimulated C-peptide ≥0.2 nmol/L). From 322 with clinically labeled type 2 diabetes, we sequenced HNF1A and HNF4A in 80 with diabetes diagnosed ≤30 years and/or diabetes diagnosed ≤45 years without metabolic syndrome. We also sequenced the glucokinase (GCK) in 40 subjects with mild fasting hyperglycemia.

In the type 1 diabetic group, two HNF1A mutations were found (0.8% prevalence). In type 2 diabetic subjects, 10 HNF1A, two HNF4A, and one GCK mutation were identified (4.0%). Only 47% of MODY case subjects identified met current guidelines for diagnostic sequencing. Follow-up revealed a further 12 mutation carriers among relatives. Twenty-seven percent of newly identified MODY subjects changed treatment, all with improved glycemic control (HbA_1c 8.8 vs. 7.3% at 3 months; P = 0.02).

The systematic use of widened diagnostic testing criteria doubled the numbers of MODY case subjects identified compared with current clinical practice. The yield was greatest in young adult-onset type 2 diabetes. We recommend that all patients diagnosed before age 30 and with presence of C-peptide at 3 years duration are considered for molecular diagnostic analysis.

Randomized, double-blind, 12-week study of 361 patients not on glucose-lowering therapy (HbA_1c 7–10%) allocated to one of four once-daily subcutaneous dose increase regimens: lixisenatide 2-step (10 μg for 1 week, 15 μg for 1 week, and then 20 μg; n = 120), lixisenatide 1-step (10 μg for 2 weeks and then 20 μg; n = 119), placebo 2-step (n = 61), or placebo 1-step (n = 61) (placebo groups were combined for analyses). Primary end point was HbA_1c change from baseline to week 12.

Once-daily lixisenatide significantly improved HbA_1c (mean baseline 8.0%) in both groups (least squares mean change vs. placebo: –0.54% for 2-step, –0.66% for 1-step; P < 0.0001). Significantly more lixisenatide patients achieved HbA_1c <7.0% (52.2% 2-step, 46.5% 1-step) and ≤6.5% (31.9% 2-step, 25.4% 1-step) versus placebo (26.8% and 12.5%, respectively; P < 0.01). Lixisenatide led to marked significant improvements of 2-h postprandial glucose levels and blood glucose excursions measured during a standardized breakfast test. A significant decrease in fasting plasma glucose was observed in both lixisenatide groups versus placebo. Mean decreases in body weight (~2 kg) were observed in all groups. The most common adverse events were gastrointestinal—nausea was the most frequent (lixisenatide 23% overall, placebo 4.1%). Symptomatic hypoglycemia occurred in 1.7% of lixisenatide and 1.6% of placebo patients, with no severe episodes. Safety/tolerability was similar for the two dose regimens.

Once-daily lixisenatide monotherapy significantly improved glycemic control with a pronounced postprandial effect (75% reduction in glucose excursion) and was safe and well tolerated in type 2 diabetes.

We have determined circulating TF-PCA and other coagulation factors under basal (hyperglycemic) conditions, after acute correction of hyperglycemia, in response to 24 h of selective hyperglycemia, and in response to 24 h of hyperglycemia plus hyperinsulinemia in nine type 1 diabetic patients and in seven nondiabetic control subjects.

As shown previously in patients with type 2 diabetes, basal TF-PCA and plasma coagulation factor VIIa (FVIIa) were higher in patients with type 1 diabetes than in nondiabetic control subjects. However, in contrast with type 2 diabetes, normalizing glucose did not decrease the elevated TF-PCA levels, and raising glucose or glucose plus insulin levels did not increase TF-PCA.

Patients with type 1 diabetes have elevated circulating TF-PCA and FVIIa levels and are in a procoagulant state that may predispose them to acute cardiovascular events. The mechanisms regulating TF-PCA in patients with type 1 and type 2 diabetes are different and should be further explored.

Sedentary patients with type 2 diabetes (n = 606) were enrolled in 22 outpatient diabetes clinics and randomized to twice-a-week supervised aerobic and resistance training plus exercise counseling versus counseling alone for 12 months. Baseline to end-of-study changes in cardiorespiratory fitness, strength, and flexibility, as assessed by Vo_2max estimation, a 5–8 maximal repetition test, and a hip/trunk flexibility test, respectively, were calculated in the whole cohort, and multiple regression analyses were applied to assess the relationship with cardiovascular risk factors.

Changes in Vo_2max, upper and lower body strength, and flexibility were significantly associated with the variation in the volume of physical activity, HbA_1c, BMI, waist circumference, high-sensitivity C-reactive protein (hs-CRP), coronary heart disease (CHD) risk score, and inversely, HDL cholesterol. Changes in fitness predicted improvements in HbA_1c, waist circumference, HDL cholesterol, hs-CRP, and CHD risk score, independent of study arm, BMI, and in case of strength, also waist circumference.

Physical activity/exercise-induced increases in fitness, particularly muscular, predict improvements in cardiovascular risk factors in subjects with type 2 diabetes independently of weight loss, thus indicating the need for targeting fitness in these individuals, particularly in subjects who struggle to lose weight.

In the population-based prospective Hoorn Study, 394 individuals with preserved LV systolic and diastolic function participated, of whom 87 had impaired glucose metabolism and 128 had type 2 diabetes. Measurements including arterial ultrasound and echocardiography were performed according to standardized protocols.

The presence of type 2 diabetes was associated with more severe LV systolic and diastolic dysfunction 8 years later: LV ejection fraction was 2.98% (95% CI 0.46–5.51) lower, and left atrial (LA) volume index, LV mass index, and tissue Doppler-derived E/e' were 3.71 mL/m² (1.20–6.22), 5.86 g/m^2.7 (2.94–8.78), and 1.64 units (0.95–2.33) higher, respectively. Furthermore, presence of impaired glucose metabolism or type 2 diabetes was associated with 8-year increases in LV mass index. More arterial stiffness (measured as a lower distensibility) was associated with LV diastolic dysfunction 8 years later: LA volume index, LV mass index, and E/e' at follow-up were higher. Subsequent adjustments for baseline mean arterial pressure and/or LV diastolic dysfunction did not eliminate these associations. Associations of type 2 diabetes and arterial stiffness with markers of LV diastolic dysfunction were largely independent of each other.

Both glucose status and arterial distensibility are independently associated with more severe LV diastolic dysfunction 8 years later and with deterioration of LV diastolic dysfunction. Therefore, type 2 diabetes and arterial stiffness may relate to LV diastolic dysfunction through different pathways.

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.

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).

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.