Data for 3,129 U.S. counties, obtained from the Small Area Health Insurance Estimates and Area Health Resources Files, were used to analyze trends in uninsured rates among populations with a household income ≤138% of the federal poverty level. Multivariable analysis adjusted for the percentage of county populations aged 50–64 years, the percentage of women, Distressed Communities Index value, and rurality.

In 2012, 39% of the population in the Diabetes Belt and 34% in non-Belt counties were uninsured (P < 0.001). In 2016 in states where Medicaid was expanded, uninsured rates declined rapidly to 13% in Diabetes Belt counties and to 15% in non-Belt counties. Adjusting for county demographic and economic factors, Medicaid expansion helped reduce uninsured rates by 12.3% in Diabetes Belt counties and by 4.9% in non-Belt counties. In 2016, uninsured rates were 15% higher for both Diabetes Belt and non-Belt counties in the nonexpansion states than in the expansion states.

ACA-driven Medicaid expansion was more significantly associated with reduced uninsured rates in Diabetes Belt than in non-Belt counties. Initial disparities in uninsured rates between Diabetes Belt and non-Belt counties have not existed since 2014 among expansion states. Future studies should examine whether and how Medicaid expansion may have contributed to an increase in the use of health services in order to prevent and treat diabetes in the Diabetes Belt.

Patients with type 1 diabetes receiving regular care were recruited in this observational cross-sectional study and divided into four groups according to their Lp(a) levels in nmol/L (very low <10, low 10–30, intermediate 30–120, high >120). Prevalence of vascular complications was compared between the groups. In addition, the association between metabolic control, measured as HbA_1c, and Lp(a) was studied.

The patients (n = 1,860) had a median age of 48 years, diabetes duration of 25 years, and HbA_1c of 7.8% (61 mmol/mol). The median Lp(a) was 19 (interquartile range 10–71) nmol/L. No significant differences between men and women were observed, but Lp(a) levels increased with increasing age. Patients in the high Lp(a) group had higher prevalence of complications than patients in the very low Lp(a) group. The age- and smoking-status–adjusted relative risk ratio of having any macrovascular disease was 1.51 (95% CI 1.01–2.28, P = 0.048); coronary heart disease, 1.70 (95% CI 0.97–3.00, P = 0.063); albuminuria, 1.68 (95% CI 1.12–2.50, P = 0.01); and calcified aortic valve disease, 2.03 (95% CI 1.03–4.03; P = 0.042). Patients with good metabolic control, HbA_1c <6.9% (<52 mmol/mol), had significantly lower Lp(a) levels than patients with poorer metabolic control, HbA_1c >6.9% (>52 mmol/mol).

Lp(a) is a significant risk factor for macrovascular disease, albuminuria, and calcified aortic valve disease in patients with type 1 diabetes. Poor metabolic control in patients with type 1 diabetes is associated with increased Lp(a) levels.

We examined 590 participants with diabetes [399 type 1 diabetes (T1D) and 191 type 2 diabetes (T2D)] and 204 control patients without diabetes with at least 1 year of follow-up and classified them according to rapid corneal nerve fiber loss (RCNFL) if CNFL change was below the fifth percentile of the control patients without diabetes.

Control patients without diabetes were 37.9 ± 19.8 years old, had median follow-up of three visits over 3.0 years, and mean annual change in CNFL was –0.1% (90% CI, –5.9 to 5.0%). RCNFL was defined by values exceeding the fifth percentile of 6% loss. Participants with T1D were 39.9 ± 18.7 years old, had median follow-up of three visits over 4.4 years, and mean annual change in CNFL was –0.8% (90% CI, –14.0 to 9.9%). Participants with T2D were 60.4 ± 8.2 years old, had median follow-up of three visits over 5.3 years, and mean annual change in CNFL was –0.2% (90% CI, –14.1 to 14.3%). RCNFL prevalence was 17% overall and was similar by diabetes type [64 T1D (16.0%), 37 T2D (19.4%), P = 0.31]. RNCFL was more common in those with baseline DSP (47% vs. 30% in those without baseline DSP, P = 0.001), which was associated with lower peroneal conduction velocity but not with baseline HbA_1c or its change over follow-up.

An abnormally rapid loss of CNFL of 6% per year or more occurs in 17% of diabetes patients. RCNFL may identify patients at highest risk for the development and progression of DSP.

We used logistic regression to examine associations of comorbidities with elevations in either troponin (≥85th percentile) among 1,835 participants in the Atherosclerosis Risk in Communities (ARIC) Study with diabetes (ages 67–89 years, 43% male, 31% black) at visit 5 (2011–2013). We used Cox models to compare associations of high cardiac troponins with mortality across comorbidity levels.

Elevations in either troponin (≥9.4 ng/L for hs-cTnI, ≥25 ng/L for hs-cTnT) were associated with prevalent coronary heart disease, heart failure, chronic kidney disease, pulmonary disease, hypoglycemia, hypertension, dementia, and frailty. Over a median follow-up of 6.2 years (418 deaths), both high hs-cTnI and high hs-cTnT further stratified mortality risk beyond comorbidity levels; those with a high hs-cTnI or hs-cTnT and high comorbidity were at highest mortality risk. Even among those with low comorbidity, a high hs-cTnI (hazard ratio [HR] 3.0 [95% CI 1.7, 5.4]) or hs-cTnT (HR 3.3 [95% CI 1.8, 6.2]) was associated with elevated mortality.

Many comorbidities were reflected by both hs-cTnI and hs-cTnT; elevations in either of the troponins were associated with higher mortality risk beyond comorbidity burden. High-sensitivity cardiac troponins may identify older adults at high mortality risk and be useful in guiding clinical care of older adults with diabetes.

We studied the effects of more intensive glycemic control in 11,071 patients with type 2 diabetes (T2D), without missing values, in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial, using Cox models.

During 5 years’ follow-up, intensive glycemic control reduced major vascular events (hazard ratio [HR] 0.90 [95% CI 0.83–0.98]), with the major driver being a reduction in the development of macroalbuminuria. There was no evidence of differences in the effect, regardless of baseline ASCVD risk or HbA_1c level (P for interaction = 0.29 and 0.94, respectively). Similarly, the beneficial effects of intensive glycemic control on all-cause mortality were not significantly different across baseline ASCVD risk (P = 0.15) or HbA_1c levels (P = 0.87). The risks of severe hypoglycemic events were higher in the intensive glycemic control group compared with the standard glycemic control group (HR 1.85 [1.41–2.42]), with no significant heterogeneity across subgroups defined by ASCVD risk or HbA_1c at baseline (P = 0.09 and 0.18, respectively).

The major benefits for patients with T2D in ADVANCE did not substantially differ across levels of baseline ASCVD risk and HbA_1c.

Standard summary metrics and functional data analysis (FDA) were applied to CGM data from the CONCEPTT trial (RT-CGM, n = 100; SMBG, n = 100) taken at baseline and at 24- and 34-weeks gestation. Multivariable regression analysis determined if temporal differences in 24-h glucose profiles occurred between comparators in each of the three groups.

FDA revealed that women using RT-CGM had significantly lower glucose (0.4–0.8 mmol/L [7–14 mg/dL]) for 7 h/day (0800 h–1200 h and 1600 h–1900 h) compared with those with SMBG. Women using pumps had significantly higher glucose (0.4–0.9 mmol/L [7–16 mg/dL]) for 12 h/day (0300 h to 0600 h, 1300 h to 1800 h, and 2030 h to 0030 h) at 24 weeks with no difference at 34 weeks compared with MDI. Women who had an LGA infant ran a significantly higher glucose by 0.4–0.7 mmol/L (7–13 mg/dL) for 4.5 h/day at baseline; by 0.4–0.9 mmol/L (7–16 mg/dL) for 16 h/day at 24 weeks; and by 0.4–0.7 mmol/L (7–13 mg/dL) for 14 h/day at 34 weeks.

FDA of temporal glucose profiles gives important information about differences in glucose control and its timing, which are undetectable by standard summary metrics. Women using RT-CGM were able to achieve better daytime glucose control, reducing fetal exposure to maternal glucose.

Using a group-based modeling approach, we identified sleep duration trajectories based on sleep duration in ages 20–25, 26–35, 36–45, and 46+ years, which were retrospectively assessed in 2009 among 60,068 women from the Nurses’ Health Study II (median age 54.9 years) who were free of diabetes, cardiovascular disease, and cancer. We investigated the prospective associations between sleep duration trajectories and diabetes risk (2009–2017) using multivariable Cox proportional hazards models.

We documented 1,797 incident diabetes cases over a median follow-up of 7.8 years (442,437 person-years). Six sleep duration trajectories were identified: persistent 5-, 6-, 7-, or 8-h sleep duration and increased or decreased sleep duration. After multivariable adjustment for diabetes risk factors, compared with the persistent 7-h sleep duration group, the hazard ratio was 1.43 (95% CI 1.10, 1.84) for the 5-h group, 1.17 (1.04, 1.33) for the 6-h group, 0.96 (0.84, 1.10) for the 8-h group, 1.33 (1.09, 1.61) for the increased sleep duration group, and 1.32 (1.10, 1.59) for the decreased sleep duration group. Additional adjustment for time-updated comorbidities and BMI attenuated these associations, although a significantly higher risk remained in the decreased sleep duration group (1.24 [1.03, 1.50]).

Persistent short sleep duration or changes in sleep duration from early to middle adulthood were associated with higher risk of type 2 diabetes in later life. These associations were weaker after obesity and metabolic comorbidities were accounted for.

This multicenter, double-blind, treat-to-target trial randomized participants to faster aspart (n = 546) or IAsp (n = 545). All available information, regardless of treatment discontinuation or use of ancillary treatment, was used for evaluation of effect.

Noninferiority for the change from baseline in HbA_1c 16 weeks after randomization (primary end point) was confirmed for faster aspart versus IAsp (estimated treatment difference [ETD] –0.04% [95% CI –0.11; 0.03]; –0.39 mmol/mol [–1.15; 0.37]; P < 0.001). Faster aspart was superior to IAsp for change from baseline in 1-h postprandial glucose (PPG) increment using a meal test (ETD –0.40 mmol/L [–0.66; –0.14]; –7.23 mg/dL [–11.92; –2.55]; P = 0.001 for superiority). Change from baseline in self-measured 1-h PPG increment for the mean over all meals favored faster aspart (ETD –0.25 mmol/L [–0.42; –0.09]); –4.58 mg/dL [–7.59; –1.57]; P = 0.003). The overall rate of treatment-emergent severe or blood glucose (BG)–confirmed hypoglycemia was statistically significantly lower for faster aspart versus IAsp (estimated treatment ratio 0.81 [95% CI 0.68; 0.97]).

In combination with insulin degludec, faster aspart provided effective overall glycemic control, superior PPG control, and a lower rate of severe or BG-confirmed hypoglycemia versus IAsp in adults with type 2 diabetes not optimally controlled with a basal-bolus regimen.

This article reports on a prospective, randomized, open-label, blinded end point trial with nested case-control study. Asymptomatic younger adults with T2D were randomized 1:1:1 to a 12-week intervention of 1) routine care, 2) supervised aerobic exercise training, or 3) a low-energy (~810 kcal/day) MRP. Participants underwent echocardiography, cardiopulmonary exercise testing, and cardiac magnetic resonance (CMR) at baseline and 12 weeks. The primary outcome was change in left ventricular (LV) peak early diastolic strain rate (PEDSR) as measured by CMR. Healthy volunteers were enrolled for baseline case-control comparison.

Eighty-seven participants with T2D (age 51 ± 7 years, HbA_1c 7.3 ± 1.1%) and 36 matched control participants were included. At baseline, those with T2D had evidence of diastolic dysfunction (PEDSR 1.01 ± 0.19 vs. 1.10 ± 0.16 s^–1, P = 0.02) compared with control participants. Seventy-six participants with T2D completed the trial (30 routine care, 22 exercise, and 24 MRP). The MRP arm lost 13 kg in weight and had improved blood pressure, glycemia, LV mass/volume, and aortic stiffness. The exercise arm had negligible weight loss but increased exercise capacity. PEDSR increased in the exercise arm versus routine care (β = 0.132, P = 0.002) but did not improve with the MRP (β = 0.016, P = 0.731).

In asymptomatic working-age adults with T2D, exercise training improved diastolic function. Despite beneficial effects of weight loss on glycemic control, concentric LV remodeling, and aortic stiffness, a low-energy MRP did not improve diastolic function.

We studied the risk of all-cause mortality in relation to long-term visit-to-visit HbA_1c variability, expressed as coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV), from the 8th month to the transition. Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratio (HR) and 95% CI.

Compared with the standard therapy group (n = 4,728), the intensive therapy group (n = 4,755) had significantly lower mean HbA_1c (6.6% [49 mmol/mol] vs. 7.7% [61 mmol/mol], P < 0.0001) and lower CV, VIM, and ARV (P < 0.0001). In multivariate adjusted analysis, all three HbA_1c variability indices were significantly associated with total mortality in all patients as well as in the standard- and intensive-therapy groups analyzed separately. The hazard ratios for a 1-SD increase in HbA_1c variability indices for the all-cause mortality were 1.19 and 1.23 in intensive and standard therapy, respectively. Cross-tabulation analysis showed the third tertile of HbA_1c mean and VIM had significantly higher all-cause mortality (HR 2.05; 95% CI, 1.17–3.61; P < 0.01) only in the intensive-therapy group.

Long-term visit-to-visit HbA_1c variability was a strong predictor of all-cause mortality. HbA_1c VIM combined with HbA_1c mean conferred an increased risk for all-cause mortality in the intensive-therapy group.

Up to September 2018, 1.4 million office BP measurements in 79,849 children and adolescents (aged 5–20 years) with T1DM have been documented in the DPV (Diabetes Prospective Follow-up) registry. BP values of the most recent year were aggregated, and BP values of 74,677 patients without antihypertensive medication were analyzed (median age 16 years and diabetes duration 5.3 years and 52.8% boys). BP values were classified according to AAP 2017 and the references of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) (2011) and the Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents (fourth report) (2004).

Of the patients, 44.1%, 29.5%, and 26.5% were hypertensive according to AAP 2017, KiGGS, and fourth report, respectively. Differences in prevalence of HTN were strongly age dependent: <10 years, AAP 2017 31.4%, KiGGS 30.7%, fourth report 19.6%; 10 to <15 years, AAP 2017 30.9%, KiGGS 31.2%, fourth report 22.4%; and ≥15 years, AAP 2017 53.2%, KiGGS 28.4%, fourth report 30.0%. Among teenagers ≥15 years, 59.1% of boys but only 46.3% of girls were classified as hypertensive by AAP 2017 but only 21.1%/26% of boys and 36.7%/34.4% of girls by KiGGS/fourth report, respectively.

Classification of BP as hypertension depends strongly on the normative data used. Use of AAP 2017 results in a significant increase in HTN in teenagers ≥15 years with T1DM, particularly in boys. AAP 2017 enhances the awareness of elevated BP in children, particularly in patients with increased risk for cardiovascular disease.

We conducted a retrospective, cross-sectional analysis of 2003–2016 National Health and Nutrition Examination Survey (NHANES) data. We included people ≥18 years who had ever been told they had diabetes, had an HbA_1C >6.4%, or had a fasting plasma glucose >125 mg/dL. Pregnant women, and those aged <20 years receiving only insulin were excluded. We assessed trends in use of ADA’s seven preferred classes from 2003–2004 to 2015–2016. We also examined use by hypoglycemia risk (sulfonylureas, insulin, and meglitinides), weight effect (sulfonylureas, thiazolidinediones [TZDs], insulin, and meglitinides), cardiovascular benefit (canagliflozin, empagliflozin, and liraglutide), and cost (brand-name medications and insulin analogs).

The final sample included 6,323 patients. The proportion taking any medication increased from 58% in 2003–2004 to 67% in 2015–2016 (P < 0.001). Use of metformin and insulin analogs increased, while use of sulfonylureas, TZDs, and human insulin decreased. Following the 2012 ADA recommendation, the choice of drug did not vary significantly by older age, weight, or presence of cardiovascular disease. Patients with low HbA_1C, or HbA_1C <6%, and age ≥65 years were less likely to receive hypoglycemia-inducing medications, while older patients with comorbidities were more likely. Insurance, but not income, was associated with the use of higher-cost medications.

Following ADA recommendations, the use of metformin increased, but physicians generally did not individualize treatment according to patients’ characteristics. Substantial opportunities exist to improve pharmacologic management of diabetes.

Cox regression models were constructed to analyze 20 years of data from the Danish National Patient Registry with respect to effect of the antihyperglycemic therapies on the three end points.

A total of 66,807 people with type 2 diabetes were treated with metformin (MET) including a combination of second- and third-line therapies. People on MET plus sulfonylurea (SU) had the highest risk of all end points, except for severe hypoglycemia, for which people on MET plus basal insulin (BASAL) had a higher risk. The lowest risk of major adverse cardiovascular events was seen for people on a regimen including a glucagon-like peptide 1 (GLP-1) receptor agonist. People treated with MET, GLP-1, and BASAL had a lower risk of all three end points than people treated with MET and BASAL, especially for severe hypoglycemia. The lowest risk of all three end points was, in general, seen for people treated with MET, sodium–glucose cotransporter 2 inhibitor, and GLP-1.

Findings from this study do not support SU as the second-line treatment choice for patients with type 2 diabetes. Moreover, the results indicate that adding a GLP-1 for people treated with MET and BASAL could be considered, especially if those people suffer from severe hypoglycemia.

We included 27 participants with a history of TNDM currently with (n = 24) or without (n = 3) relapse of diabetes, and 16 non-TNDM relatives known to be carriers of causal genetic defects and currently with (n = 9) or without (n = 7) diabetes. Insulin sensitivity and secretion were assessed by hyperinsulinemic-euglycemic clamp and arginine-stimulation testing in a subset of 8 TNDM participants and 7 relatives carrying genetic abnormalities, with and without diabetes, compared with 17 unrelated control subjects without diabetes.

In TNDM participants, age at relapse correlated positively with age at puberty (P = 0.019). The mean insulin secretion rate and acute insulin response to arginine were significantly lower in TNDM and relatives of participants with diabetes than in control subjects (4.7 [3.6–5.9] vs. 13.4 [11.8–16.1] pmol/kg/min, P < 0.0001; and 84.4 [33.0–178.8] vs. 399.6 [222.9–514.9] µIU/mL, P = 0.0011), but were not different between participants without diabetes (12.7 [10.4–14.3] pmol/kg/min and 396.3 [303.3–559.3] µIU/mL, respectively) and control subjects. Socioeducational attainment was lower in TNDM participants than in the general population, regardless of diabetes duration.

Relapse of diabetes occurred earlier in TNDM participants compared with relatives and was associated with puberty. Both groups had decreased educational attainment, and those with diabetes had lower insulin secretion capacity; however, there was no difference in insulin resistance in adulthood. These forms of diabetes should be included in maturity-onset diabetes of the young testing panels, and relatives of TNDM patients should be screened for underlying defects, as they may be treated with drugs other than insulin.

We included 2,236 adults aged ≥65 years without known diabetes from the 2005–2016 National Health and Nutrition Examination Survey. Diabetes was defined using: 1) the Endocrine Society approach (HbA_1c ≥6.5%, FPG ≥126 mg/dL, or 2-h plasma glucose ≥200 mg/dL among those with HbA_1c 5.7–6.4% or FPG 100–125 mg/dL); and 2) a standard approach (HbA_1c ≥6.5% or FPG ≥126 mg/dL). Treatment eligibility was defined using HbA_1c cut points (≥7 to ≥9%). OGTT screening costs were estimated using Medicare fee schedules.

Diabetes prevalence was 15.7% (~5.0 million) using the Endocrine Society’s approach and 7.3% (~2.3 million) using the standard approach. Treatment eligibility ranged from 5.4 to 0.06% and 11.8–1.3% for diabetes cases identified through the Endocrine Society or standard approach, respectively. By definition, diabetes identified exclusively through the Endocrine Society approach had HbA1_1c <6.5% and would not be recommended for glucose-lowering treatment. Screening all older adults with prediabetic HbA_1c/FPG (~18.3 million) with OGTT could cost between $737 million and $1.7 billion.

Adopting the 2019 Endocrine Society guidelines would substantially increase the number of older adults classified as having diabetes, require significant financial resources, but likely offer limited benefits.

We report the resource utilization, costs, and effectiveness measures from the ongoing ASK program compared with usual care (i.e., no screening). Additionally, we report a practical screening scenario by including utilization and costs relevant to routine screening in clinical practice. Finally, we project the potential cost-effectiveness of ASK and routine screening by identifying clinical benchmarks (i.e., diabetic ketoacidosis [DKA] events avoided, HbA_1c improvements vs. no screening) needed to meet value thresholds of $50,000–$150,000 per quality-adjusted life-year (QALY) gained over a lifetime horizon.

Cost per case detected was $4,700 for ASK screening and $14,000 for routine screening. To achieve value thresholds of $50,000–$150,000 per QALY gained, screening costs would need to be offset by cost savings through 20% reductions in DKA events at diagnosis in addition to 0.1% (1.1 mmol/mol) improvements in HbA_1c over a lifetime compared with no screening for patients who develop type 1 diabetes. Value thresholds were not met from avoiding DKA events alone in either scenario.

Presymptomatic type 1 diabetes screening may be cost-effective in areas with a high prevalence of DKA and an infrastructure facilitating screening and monitoring if the benefits of avoiding DKA events and improved HbA_1c persist over long-run time horizons. As more data are collected from ASK, the model will be updated with direct evidence on screening effects.

Data were drawn from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial and the Veterans Affairs Diabetes Trial (VADT). Coefficient of variation (CV) and average real variability (ARV) were calculated for systolic (SBP) and diastolic blood pressure (DBP) along with maximum and cumulative mean SBP and DBP during both trials.

In ACCORD, CV and ARV of SBP and DBP were associated with increased risk of HF, even after adjusting for other risk factors and mean blood pressure (e.g., CV-SBP: hazard ratio [HR] 1.15, P = 0.01; CV-DBP: HR 1.18, P = 0.003). In the VADT, DBP variability was associated with increased risk of HF (ARV-DBP: HR 1.16, P = 0.001; CV-DBP: HR 1.09, P = 0.04). Further, in ACCORD, those with progressively lower baseline blood pressure demonstrated a stepwise increase in risk of HF with higher CV-SBP, ARV-SBP, and CV-DBP. Effects of blood pressure variability were related to dips, not elevations, in blood pressure.

Blood pressure variability is associated with HF risk in individuals with type 2 diabetes, possibly a consequence of periods of ischemia during diastole. These results may have implications for optimizing blood pressure treatment strategies in those with type 2 diabetes.

We thoroughly characterized 6,726 patients with recently diagnosed diabetes. After a median of 2.8 years, we sent a detailed questionnaire on neuropathy, including the Michigan Neuropathy Screening Instrument questionnaire (MNSIq), to identify possible DPN (score ≥4) and the Douleur Neuropathique en 4 Questions (DN4) questionnaire for possible associated neuropathic pain (MNSIq ≥4 + pain in both feet + DN4 score ≥3).

Among 5,249 patients with data on both DPN and pain, 17.9% (n = 938) had possible DPN, including 7.4% (n = 386) with possible neuropathic pain. In regression analyses, central obesity (waist circumference, waist-to-hip ratio, and waist-to-height ratio) was markedly associated with DPN. Other important metabolic factors associated with DPN included hypertriglyceridemia ≥1.7 mmol/L, adjusted prevalence ratio (aPR) 1.36 (95% CI 1.17; 1.59); decreased HDL cholesterol <1.0/1.2 mmol/L (male/female), aPR 1.35 (95% CI 1.12; 1.62); hs-CRP ≥3.0 mg/L, aPR 1.66 (95% CI 1.42; 1.94); C-peptide ≥1,550 pmol/L, aPR 1.72 (95% CI 1.43; 2.07); HbA_1c ≥78 mmol/mol, aPR 1.42 (95% CI 1.06; 1.88); and antihypertensive drug use, aPR 1.34 (95% CI 1.16; 1.55). Smoking, aPR 1.50 (95% CI 1.24; 1.81), and lack of physical activity (0 vs. ≥3 days/week), aPR 1.61 (95% CI 1.39; 1.85), were also associated with DPN. Smoking, high alcohol intake, and failure to increase activity after diabetes diagnosis associated with neuropathic pain.

Possible DPN was associated with metabolic syndrome factors, insulin resistance, inflammation, and modifiable lifestyle habits in early type 2 diabetes.