Differential relationship between physical activity and progression to diabetes by glucose tolerance status: the Inter99 Study

Physical activity and sedentary behavior show distinct associations with tissue-specific insulin sensitivity in adults with overweight

AIM

The aim of this study is to investigate associations between the physical activity (PA) spectrum (sedentary behavior to exercise) and tissue-specific insulin resistance (IR).

METHODS

We included 219 participants for analysis (median [IQR]: 61 [55; 67] years, BMI 29.6 [26.9; 32.0] kg/m² ; 60% female) with predominant muscle or liver IR, as determined using a 7-point oral glucose tolerance test (OGTT). PA and sedentary behavior were measured objectively (ActivPAL) across 7 days. Context-specific PA was assessed with the Baecke questionnaire. Multiple linear regression models (adjustments include age, sex, BMI, site, season, retirement, and dietary intake) were used to determine associations between the PA spectrum and hepatic insulin resistance index (HIRI), muscle insulin sensitivity index (MISI) and whole-body IR (HOMA-IR, Matsuda index).

RESULTS

In fully adjusted models, objectively measured total PA (standardized regression coefficient β = 0.17, p = 0.020), light-intensity PA (β = 0.15, p = 0.045) and moderate-to-vigorous intensity PA (β = 0.13, p = 0.048) were independently associated with Matsuda index, but not HOMA-IR (p > 0.05). A higher questionnaire-derived sport index and leisure index were associated with significantly lower whole-body IR (Matsuda, HOMA-IR) in men but not in women. Results varied across tissues: more time spent sedentary (β = -0.24, p = 0.045) and a higher leisure index (β = 0.14, p = 0.034) were respectively negatively and positively associated with MISI, but not HIRI. A higher sport index was associated with lower HIRI (β = -0.30, p = 0.007, in men only).

CONCLUSION

While we confirm a beneficial association between PA and whole-body IR, our findings indicate that associations between the PA spectrum and IR seem distinct depending on the primary site of insulin resistance (muscle or liver).

Metabolic and Anthropometric Parameters of Persons at Risk of Developing Type 2 Diabetes Mellitus Before and After 3 Months of Consuming Insoluble Dietary Fiber

Background:

Observational studies have shown that insoluble fiber (IF) can be effective in preventing type 2 diabetes (T2D), but there is a lack of experimental data on the effect of short-term consumption of IF on metabolic parameters. We tried to investigate whether there was an improvement in glycemia and body composition in individuals at risk for T2D after 3 months of IF consumption.

Methods:

This “Type 2 Diabetes Mellitus Prevention Ukraine (T2DPUA)” study describes participants with impaired fasting glucose (IFG) as determined by ADA criteria. The study involved 30 people, including 21 women (70%). Daily, 15 g of IF derived from wheat was used. T2DPUA did not have a placebo group and the intervention lasted 3 months. Evaluation of fasting plasma glucose (FPG) and 2h plasma glucose (2hPG), glycated hemoglobin (HbA1c), total cholesterol, HDL-cholesterol, triacylglycerols, uric acid, and γ-glutamyl transferase was performed. The baseline and 3-monthly anthropometric examinations included measurements of weight, waist and hip circumference. Fat mass was assessed by bioelectrical impedance analysis. Paired samples t-test or Wilcoxon test were used.

Result:

A decrease of FPG (P = .042), HbA1c (P < .001), 2hPG (P = .005), weight (P < .001), body mass index (P < .001), the proportion of body fat (P = .006), and the absolute amount of fat (P < .001), increases in systolic (P < .001) and diastolic (P = .008) blood pressure was shown. The number of people with hypertension did not change. The absolute amount of body fat decreased by almost 5% and tolerance to the standard glucose load improved by 15%. The dynamics of other metabolic parameters were not revealed.

Conclusion and Recommendation:

Data about improvement of glycemia and body composition over a short period of using IF by individuals with IFG are new and deserve larger studies.

The heterogeneity of reversion to normoglycemia according to prediabetes type is not explained by lifestyle factors

Healthy lifestyle interventions and drug therapies are proven to have a positive preventative influence on normal glucose regulation in prediabetes. However, little is known on the specific role that these factors play on reversion to normal glycemia according to type of prediabetes. We used data from the Observational prospective cohort study, The Cohort study in Primary Health Care on the Evolution of Patients with Prediabetes from 2012 to 2015. A total of 1184 individuals aged 30-74 years old were included and classified based on the ADA in three mutually exclusive groups using either fasting plasma glucose (FPG) levels (from 100 to 125 mg/dl, FPG group), HbA_1c (5.7-6.4%, HbA1c group) or both impaired parameters. Information on lifestyle factors and biochemical parameters were collected at baseline. Reversion to normal glucose regulation was calculated at third year of follow-up. Relationship of lifestyle factor and type of prediabetes with reversion were estimated using odds ratios (ORs) with 95% confidence intervals (95% CIs) adjusting by different groups of confounders. Proportion of reversion rates were 31% for FPG group, 31% for HbA1c group and 7.9% for both altered parameters group, respectively. Optimal life style factors such as BMI < 25 kg/m²[OR (95% CI): 1.90 (1.20-3.01)], high adherence to Mediterranean diet 1.78 (1.21-2.63) and absence of abdominal obesity 1.70 (1.19-2.43) were the strongest predictors for reversion to normal glucose. However, those did not modify the ORs of reversion to normal glucose. Taking as reference those with both impaired parameters, subjects with FPG impairment (FPG group) had an OR of 4.87 (3.10-7.65) and 3.72 (2.39-5.78) for HbA1c group. These estimates remained almost the same after further adjustment for biochemical parameters and lifestyle factors (4.55(2.84-7.28) and 3.09 (1.92-4.97), respectively). Optimal lifestyle factors showed to be a positive predictor for reversion to normal glucose regulation however, the differences of reversion risk according type of prediabetes are not explained by lifestyle factors.

Lifestyle Intervention With or Without Lay Volunteers to Prevent Type 2 Diabetes in People With Impaired Fasting Glucose and/or Nondiabetic Hyperglycemia: A Randomized Clinical Trial

IMPORTANCE

Nearly half of the older adult population has diabetes or a high-risk intermediate glycemic category, but we still lack trial evidence for effective type 2 diabetes prevention interventions in most of the current high-risk glycemic categories.

OBJECTIVE

To determine whether a group-based lifestyle intervention (with or without trained volunteers with type 2 diabetes) reduced the risk of progression to type 2 diabetes in populations with a high-risk glycemic category.

DESIGN, SETTING, AND PARTICIPANTS

The Norfolk Diabetes Prevention Study was a parallel, 3-arm, group-based, randomized clinical trial conducted with up to 46 months of follow-up from August 2011 to January 2019 at 135 primary care practices and 8 intervention sites in the East of England. We identified 141 973 people at increased risk of type 2 diabetes, screened 12 778 (9.0%), and randomized those with a high-risk glycemic category, which was either an elevated fasting plasma glucose level alone (≥110 and <126 mg/dL [to convert to millimoles per liter, multiply by 0.0555]) or an elevated glycated hemoglobin level (≥6.0% to <6.5%; nondiabetic hyperglycemia) with an elevated fasting plasma glucose level (≥100 to <110 mg/dL).

INTERVENTIONS

A control arm receiving usual care (CON), a theory-based lifestyle intervention arm of 6 core and up to 15 maintenance sessions (INT), or the same intervention with support from diabetes prevention mentors, trained volunteers with type 2 diabetes (INT-DPM).

MAIN OUTCOMES AND MEASURES

Type 2 diabetes incidence between arms.

RESULTS

In this study, 1028 participants were randomized (INT, 424 [41.2%] [166 women (39.2%)]; INT-DPM, 426 [41.4%] [147 women (34.5%)]; CON, 178 [17.3%] [70 women (%39.3)]) between January 1, 2011, and February 24, 2017. The mean (SD) age was 65.3 (10.0) years, mean (SD) body mass index 31.2 (5) (calculated as weight in kilograms divided by height in meters squared), and mean (SD) follow-up 24.7 (13.4) months. A total of 156 participants progressed to type 2 diabetes, which comprised 39 of 171 receiving CON (22.8%), 55 of 403 receiving INT (13.7%), and 62 of 414 receiving INT-DPM (15.0%). There was no significant difference between the intervention arms in the primary outcome (odds ratio [OR], 1.14; 95% CI, 0.77-1.7; P = .51), but each intervention arm had significantly lower odds of type 2 diabetes (INT: OR, 0.54; 95% CI, 0.34-0.85; P = .01; INT-DPM: OR, 0.61; 95% CI, 0.39-0.96; P = .033; combined: OR, 0.57; 95% CI, 0.38-0.87; P = .01). The effect size was similar in all glycemic, age, and social deprivation groups, and intervention costs per participant were low at $153 (£122).

CONCLUSIONS AND RELEVANCE

The Norfolk Diabetes Prevention lifestyle intervention reduced the risk of type 2 diabetes in current high-risk glycemic categories. Enhancing the intervention with DPM did not further reduce diabetes risk. These translatable results are relevant for current diabetes prevention efforts.

TRIAL REGISTRATION

ISRCTN Registry Identifier: ISRCTN34805606.

Trajectories of BMI Before Diagnosis of Type 2 Diabetes: The Rotterdam Study

OBJECTIVE

People with diabetes show great variability in weight gain and duration of obesity at the time of diagnosis. BMI trajectories and other cardiometabolic risk factors prior to type 2 diabetes were investigated.

METHODS

A total of 6,223 participants from the Rotterdam Study cohort were included. BMI patterns before diagnosis of diabetes were identified through latent class trajectories.

RESULTS

During a mean follow-up of 13.7 years, 565 participants developed type 2 diabetes. Three distinct trajectories of BMI were identified, including the "progressive overweight" group (n = 481, 85.1%), "progressive weight loss" group (n = 59, 10.4%), and "persistently high BMI" group (n = 25, 4.4%). The majority, the progressive overweight group, was characterized by a steady increase of BMI in the overweight range 10 years before diabetes diagnosis. The progressive weight loss group had fluctuations of glucose and marked beta cell function loss. The persistently high BMI group was characterized by a slight increase in insulin levels and sharp increase of insulin resistance accompanied by a rapid decrease of beta cell function.

CONCLUSIONS

Heterogeneity of BMI changes prior to type 2 diabetes was found in a middle-aged and elderly white population. Prevention strategies should be tailored rather than focusing only on high-risk individuals.

Associated risk factors and their interactions with type 2 diabetes among the elderly with prediabetes in rural areas of Yiyang City: A nested case-control study

To explore associated risk factors and their interactions with type 2 diabetes (T2DM) among the elderly with prediabetes in rural areas in China.A nested case-control study was conducted in a fixed cohort to identify the risk factors for T2DM among the elderly with prediabetes in rural areas of Yiyang City in China. A total of 37 elderly with T2DM were included in the cases group and 111 elderly subjects with prediabetes were matched in the control group. Data related to sociodemographic characteristics, lifestyle behavior, and anthropometric variables were collected by trained staff using standard tools. The risk factors for T2DM were determined using conditional logistic regression analysis, and their additive interactions were also explored.Multivariable conditional logistic regression analysis results showed that overweight/obesity (odds ratio [OR] = 4.80, 95% confidence interval [CI]: 1.20-12.28), family history of diabetes (OR = 3.63, 95% CI: 1.03-12.81), physically inactive (OR = 3.08, 95% CI: 1.14-8.30), high waist-to-hip ratio (WHR) (OR = 3.15, 95% CI: 1.27-7.80), and inadequate diabetes-specific health literacy (DSHL) (OR = 3.92, 95% CI: 1.14-13.48) increased the risk for T2DM. Additive interactions for T2DM were observed between a family history of diabetes and high WHR with a relative excess risk of interaction (RERI) of 10.02 (95% CI: 4.25, 15.78), and between high WHR and overweight or obesity, with an RERI of 3.90 (95% CI: 0.36, 7.44).The independent risk factors for T2DM are overweight or obesity, high WHR, family history of diabetes, physically inactive, and inadequate DSHL. High WHR as a risk factor for T2DM has additive interactions with family history of diabetes and overweight or obesity.

Effects of dietary and physical activity interventions on the risk of type 2 diabetes in South Asians: meta-analysis of individual participant data from randomised controlled trials

AIMS/HYPOTHESIS

Individuals of South Asian origin have a high risk of type 2 diabetes and of dying from a diabetes-attributable cause. Lifestyle modification intervention trials to prevent type 2 diabetes in high-risk South Asian adults have suggested more modest effects than in European-origin populations. The strength of the evidence of individual studies is limited, however. We performed an individual participant data meta-analysis of available RCTs to assess the effectiveness of lifestyle modification in South Asian populations worldwide.

METHODS

We searched PubMed, EMBASE, Cochrane Library and Web of Science (to 24 September 2018) for RCTs on lifestyle modification interventions incorporating diet and/or physical activity in South Asian adults. Reviewers identified eligible studies and assessed the quality of the evidence. We obtained individual participant data on 1816 participants from all six eligible trials (four from Europe and two from India). We generated HR estimates for incident diabetes (primary outcome) and mean differences for fasting glucose, 2 h glucose, weight and waist circumference (secondary outcomes) using mixed-effect meta-analysis overall and by pre-specified subgroups. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system to rate the quality of evidence of the estimates. The study is registered with the International Prospective Register of Systematic Reviews ([PROSPERO] CRD42017078003).

RESULTS

Incident diabetes was observed in 12.6% of participants in the intervention groups and in 20.0% of participants in the control groups. The pooled HR for diabetes incidence was 0.65 (95% CI 0.51, 0.81; I² = 0%) in intervention compared with control groups. The absolute risk reduction was 7.4% (95% CI 4.0, 10.2), with no interactions for the pre-specified subgroups (sex, BMI, age, study duration and region where studies were performed). The quality of evidence was rated as moderate. Mean difference for lifestyle modification vs control groups for 2 h glucose was -0.34 mmol/l (95% CI -0.62, -0.07; I² = 50%); for weight -0.75 kg (95% CI -1.34, -0.17; I² = 71%) and for waist -1.16 cm (95% CI -2.16, -0.16; I² = 75%). No effect was found for fasting glucose. Findings were similar across subgroups, except for weight for European vs Indian studies (-1.10 kg vs -0.08 kg, p = 0.02 for interaction).

CONCLUSIONS/INTERPRETATION

Despite modest changes for adiposity, lifestyle modification interventions in high-risk South Asian populations resulted in a clinically important 35% relative reduction in diabetes incidence, consistent across subgroups. If implemented on a large scale, lifestyle modification interventions in high-risk South Asian populations in Europe would reduce the incidence of diabetes in these populations.

Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia

BACKGROUND

Intermediate hyperglycaemia (IH) is characterised by one or more measurements of elevated blood glucose concentrations, such as impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and elevated glycosylated haemoglobin A1c (HbA1c). These levels are higher than normal but below the diagnostic threshold for type 2 diabetes mellitus (T2DM). The reduced threshold of 5.6 mmol/L (100 mg/dL) fasting plasma glucose (FPG) for defining IFG, introduced by the American Diabetes Association (ADA) in 2003, substantially increased the prevalence of IFG. Likewise, the lowering of the HbA1c threshold from 6.0% to 5.7% by the ADA in 2010 could potentially have significant medical, public health and socioeconomic impacts.

OBJECTIVES

To assess the overall prognosis of people with IH for developing T2DM, regression from IH to normoglycaemia and the difference in T2DM incidence in people with IH versus people with normoglycaemia.

SEARCH METHODS

We searched MEDLINE, Embase, ClincialTrials.gov and the International Clinical Trials Registry Platform (ICTRP) Search Portal up to December 2016 and updated the MEDLINE search in February 2018. We used several complementary search methods in addition to a Boolean search based on analytical text mining.

SELECTION CRITERIA

We included prospective cohort studies investigating the development of T2DM in people with IH. We used standard definitions of IH as described by the ADA or World Health Organization (WHO). We excluded intervention trials and studies on cohorts with additional comorbidities at baseline, studies with missing data on the transition from IH to T2DM, and studies where T2DM incidence was evaluated by documents or self-report only.

DATA COLLECTION AND ANALYSIS

One review author extracted study characteristics, and a second author checked the extracted data. We used a tailored version of the Quality In Prognosis Studies (QUIPS) tool for assessing risk of bias. We pooled incidence and incidence rate ratios (IRR) using a random-effects model to account for between-study heterogeneity. To meta-analyse incidence data, we used a method for pooling proportions. For hazard ratios (HR) and odds ratios (OR) of IH versus normoglycaemia, reported with 95% confidence intervals (CI), we obtained standard errors from these CIs and performed random-effects meta-analyses using the generic inverse-variance method. We used multivariable HRs and the model with the greatest number of covariates. We evaluated the certainty of the evidence with an adapted version of the GRADE framework.

MAIN RESULTS

We included 103 prospective cohort studies. The studies mainly defined IH by IFG5.6 (FPG mmol/L 5.6 to 6.9 mmol/L or 100 mg/dL to 125 mg/dL), IFG6.1 (FPG 6.1 mmol/L to 6.9 mmol/L or 110 mg/dL to 125 mg/dL), IGT (plasma glucose 7.8 mmol/L to 11.1 mmol/L or 140 mg/dL to 199 mg/dL two hours after a 75 g glucose load on the oral glucose tolerance test, combined IFG and IGT (IFG/IGT), and elevated HbA1c (HbA1c5.7: HbA1c 5.7% to 6.4% or 39 mmol/mol to 46 mmol/mol; HbA1c6.0: HbA1c 6.0% to 6.4% or 42 mmol/mol to 46 mmol/mol). The follow-up period ranged from 1 to 24 years. Ninety-three studies evaluated the overall prognosis of people with IH measured by cumulative T2DM incidence, and 52 studies evaluated glycaemic status as a prognostic factor for T2DM by comparing a cohort with IH to a cohort with normoglycaemia. Participants were of Australian, European or North American origin in 41 studies; Latin American in 7; Asian or Middle Eastern in 50; and Islanders or American Indians in 5. Six studies included children and/or adolescents.Cumulative incidence of T2DM associated with IFG5.6, IFG6.1, IGT and the combination of IFG/IGT increased with length of follow-up. Cumulative incidence was highest with IFG/IGT, followed by IGT, IFG6.1 and IFG5.6. Limited data showed a higher T2DM incidence associated with HbA1c6.0 compared to HbA1c5.7. We rated the evidence for overall prognosis as of moderate certainty because of imprecision (wide CIs in most studies). In the 47 studies reporting restitution of normoglycaemia, regression ranged from 33% to 59% within one to five years follow-up, and from 17% to 42% for 6 to 11 years of follow-up (moderate-certainty evidence).Studies evaluating the prognostic effect of IH versus normoglycaemia reported different effect measures (HRs, IRRs and ORs). Overall, the effect measures all indicated an elevated risk of T2DM at 1 to 24 years of follow-up. Taking into account the long-term follow-up of cohort studies, estimation of HRs for time-dependent events like T2DM incidence appeared most reliable. The pooled HR and the number of studies and participants for different IH definitions as compared to normoglycaemia were: IFG5.6: HR 4.32 (95% CI 2.61 to 7.12), 8 studies, 9017 participants; IFG6.1: HR 5.47 (95% CI 3.50 to 8.54), 9 studies, 2818 participants; IGT: HR 3.61 (95% CI 2.31 to 5.64), 5 studies, 4010 participants; IFG and IGT: HR 6.90 (95% CI 4.15 to 11.45), 5 studies, 1038 participants; HbA1c5.7: HR 5.55 (95% CI 2.77 to 11.12), 4 studies, 5223 participants; HbA1c6.0: HR 10.10 (95% CI 3.59 to 28.43), 6 studies, 4532 participants. In subgroup analyses, there was no clear pattern of differences between geographic regions. We downgraded the evidence for the prognostic effect of IH versus normoglycaemia to low-certainty evidence due to study limitations because many studies did not adequately adjust for confounders. Imprecision and inconsistency required further downgrading due to wide 95% CIs and wide 95% prediction intervals (sometimes ranging from negative to positive prognostic factor to outcome associations), respectively.This evidence is up to date as of 26 February 2018.

AUTHORS' CONCLUSIONS

Overall prognosis of people with IH worsened over time. T2DM cumulative incidence generally increased over the course of follow-up but varied with IH definition. Regression from IH to normoglycaemia decreased over time but was observed even after 11 years of follow-up. The risk of developing T2DM when comparing IH with normoglycaemia at baseline varied by IH definition. Taking into consideration the uncertainty of the available evidence, as well as the fluctuating stages of normoglycaemia, IH and T2DM, which may transition from one stage to another in both directions even after years of follow-up, practitioners should be careful about the potential implications of any active intervention for people 'diagnosed' with IH.

Determinants of Change in Glycemic Status in Individuals with Prediabetes: Results from a Nationwide Cohort Study in Germany

Previous studies investigating determinants of changes in glycemic status among individuals with prediabetes mainly focused on glucose-defined prediabetes. In this study, we examined determinants of a regression to normoglycemia or a progression to diabetes among individuals with HbA1c-defined prediabetes. The study included 817 participants (18-79 years) with prediabetes (HbA1c 5.7-6.4% (39-47 mmol/mol)) at baseline. Glycemic status at follow-up was categorized as diagnosed diabetes (self-reported physician diagnosis or antidiabetic medication), undiagnosed diabetes (HbA1c ≥ 6.5% (≥48 mmol/mol)), prediabetes (as defined at baseline), and normoglycemia (HbA1c < 5.7% (<39 mmol/mol)). Determinants of glycemic changes were identified by multinomial logistic regression (OR (95% CI)), with those remaining in the prediabetic state as reference. During a mean follow-up time of 12.0 years, 33.8% of the participants reverted to normoglycemia, 7.2% progressed to undiagnosed diabetes, 12.8% progressed to diagnosed diabetes, and 46.2% remained prediabetic. Determinants of a regression to normoglycemia were female sex (male vs. female: 0.67 (0.46; 0.98)) and higher HDL cholesterol levels (1.17 (1.02; 1.35) per 10 mg/dl). Determinants of a progression to undiagnosed or diagnosed diabetes were higher values of BMI (1.10 (1.02; 1.18); 1.13 (1.06; 1.21) per kg/m²), waist circumference (1.04 (1.01; 1.07); 1.06 (1.03; 1.09) per cm), alanine aminotransferase (1.06 (1.03; 1.09); 1.07 (1.03; 1.10) per U/l), and gamma-glutamyl transferase (1.02 (1.00; 1.03); 1.03 (1.01; 1.04) per U/l). Higher age (1.04 (1.02; 1.06) per year), female sex (male vs. female: 0.56 (0.33; 0.97)), and parental history of diabetes (yes vs. no: 1.82 (1.05; 3.15)) were further associated with a progression to diagnosed diabetes, whereas higher triglyceride levels (1.03 (1.01; 1.06) per 10 mg/dl) were associated with a progression to undiagnosed diabetes. In conclusion, among the investigated determinants, potentially modifiable anthropometric and metabolic markers were associated with glycemic changes in individuals with HbA1c-defined prediabetes. The findings of this study demonstrate the need for more refined case finding strategies for diabetes prevention.

Lifestyle and the Prevention of Type 2 Diabetes: A Status Report

Diabetes is a costly disease affecting 387 million individuals globally and 28 million in the United States. Its precursor, prediabetes, affects 316 and 86 million individuals globally and in the United States, respectively. People living with elevated blood glucose levels are at high risk for all-cause mortality and numerous cardiometabolic ailments. Fortunately, diabetes can be prevented or delayed by maintaining a healthy lifestyle and a healthy body weight. In this review, we summarize the literature around lifestyle diabetes prevention programs and provide recommendations for introducing prevention strategies in clinical practice. Overall, evidence supports the efficacy and effectiveness of lifestyle diabetes prevention interventions across clinical and community settings, delivery formats (eg, individual-, group-, or technology-based), and implementers (eg, clinicians, community members). Evidence-based diabetes prevention strategies that can be implemented in clinical practice include brief behavior change counseling, group-based education, community referrals, and health information technologies. These strategies represent opportunities where practitioners, communities, and health care systems can work together to provide individuals with education, support and opportunities to maintain healthy, diabetes-free lifestyles.

Prevention of Diabetes: Countless Opportunities and Clear Challenges

Prevention of diabetes poses significant challenges; especially when applied as public health intervention. While several trials, most importantly Diabetes Prevention Program, show that intensive lifestyle modification leading to weight loss is the most important intervention, many individuals and some populations may show resistance to these interventions. Roadblocks to lifestyle intervention alone or in combination include: age, some ethnic groups (e.g., south Asians), genetic make-up, and some characteristics of body phenotype. Recent data show that non-alcoholic fatty liver disease along with insulin resistance may constitute 'metabolically unhealthy phenotype'. These subgroups would need more intensive interventions to convert prediabetes to normal glucose regulation. Whether 'fatty pancreas' and sarcopenia, latter more often seen in Asian Indians and with advancing age, are other phenotypes requiring intensive and different interventions (e.g., more resistance exercise in latter) remains to be researched. Further, variations in dietary quality (Mediterranean diet enriched with extra virgin olive oil, high-protein diets) without changing much of calories, provide attractive options for intervention. Many of such innovations require more research. Translation of lessons from diabetes prevention studies to general population is daunting but possible. However, such community-based interventions need substantial human and material resources, which pose hurdles in underserved populations and developing countries. In such situations, low-cost modalities, for example, use of trained community educators and digital and social media, constitute attractive approaches.

Physical Activity and Improvement of Glycemia in Prediabetes by Different Diagnostic Criteria

Context

The effects of physical activity (PA) on improvement of glycemia may differ between prediabetic individuals defined by oral glucose tolerance test vs glycated hemoglobin (HbA1c).

Objective

We studied the association between PA and improvement of glycemia in individuals with prediabetes defined by glucose vs HbA1c criteria.

Design, Setting, and Participants

From the Whitehall II study, 957 participants with prediabetes defined by isolated impaired fasting glucose (i-IFG), isolated impaired glucose tolerance (i-IGT), or both and 457 with prediabetes defined by HbA1c were included.

Main Outcome Measures

The associations of PA with concomitant changes in glucose-related outcomes during 5 years of follow-up were analyzed. A recursive partitioning analysis was performed to study heterogeneity in the association between baseline PA and the probability of reversion to normoglycemia.

Results

After 5 years of follow-up, 405 (42%) individuals with glucose-defined prediabetes reverted to normal glucose tolerance (NGT). A 5-year increase in moderate-to-vigorous-intensity PA was associated with improvements in insulin sensitivity and β-cell function, but PA was not generally associated with reversion to NGT. Only among women ≥50 years with i-IFG or i-IGT, higher amounts of PA were associated with higher probability of reversion to NGT. In HbA1c-defined prediabetes, only 20 individuals (4.4%) reverted to normoglycemia, and PA was not associated with improvement in glycemic markers.

Conclusions

PA may be particularly important for reversion to normoglycemia among older women with i-IFG or i-IGT. Individuals with prediabetes identified by HbA1c have a low probability of reversion to normoglycemia, and their changes in glycemia are not related to PA.

Identification of Risk Factors Affecting Impaired Fasting Glucose and Diabetes in Adult Patients from Northeast China

BACKGROUND

Besides genetic factors, the occurrence of diabetes is influenced by lifestyles and environmental factors as well as trace elements in diet materials. Subjects with impaired fasting glucose (IFG) have an increased risk of developing diabetes mellitus (DM). This study aimed to explore risk factors affecting IFG and diabetes in patients from Northeast China.

METHODS

A population-based, cross-sectional survey of chronic diseases and related risk factors was conducted in Jilin Province of Northeast China. All adult residents, aged 18-79, were invited to participate in this survey using the method of multistage stratified random cluster sampling. One hundred thirty-four patients with IFG or DM and 391 healthy control subjects were recruited. We compared demographic factors, body size measurements, healthy-related behaviors, and hair metallic element contents between IFG/diabetes patients and healthy individuals.

RESULTS

IFG/diabetes patients had a greater weight, waist, hip, and body mass index (BMI) than control subjects. Significant differences in the content of zinc (Zn), potassium (K), copper (Ca), and sodium (Na) as well as Cu/Zn ratios between IFG or DM patients and control subjects (p < 0.05) were also observed. Hair Cu, selenium (Se), and Na contents were positively correlated with blood glucose levels (Cu: rs = 0.135, p = 0.002; Se: rs = 0.110, p = 0.012; Na: rs = 0.091, p = 0.038). Polytomous logistic regression adjusting for age, sex, family history of diabetes and BMI, showed that subjects with high BMI were more likely to develop IFG and DM (IFG: OR = 1.15, OR 95% CI = 1.02-1.29; DM: OR = 1.15, OR 95% CI = 1.01-1.33). Moreover, rarely or never eating fruits was a risk factor for DM (OR = 5.46, OR 95% CI = 1.87-15.98) but not for IFG (OR = 1.70, OR 95% CI = 0.72-4.02). Subjects with abdominal obesity or DM history were more susceptible to DM (abdominal obesity: OR = 2.99, OR 95% CI = 1.07-8.37; DM history: OR = 2.69, OR 95% CI = 1.01-7.20). We found that subjects living in Changling County had a significantly lower chance to suffer from IFG (OR and 95% CI for OR: 0.25, 0.08-0.74). Men and 60-69 years old subjects were at increased risk for IFG (male: OR = 3.51, OR 95% CI = 1.34-9.18; age 60-69: OR = 6.64, OR 95% CI = 1.36-32.47). We did not find significant associations of IFG or DM with certain lifestyles (such as eating more meat, exercise or physical activity, smoking, or alcohol drinking) or the content of some metallic elements (such as iron (Fe), Zn , K, calcium (Ca), Na, or magnesium (Mg)).

CONCLUSIONS

This study demonstrated that less or no fruit eating, DM family history, abdominal obesity conferred vulnerability to DM. Living in Changling County, men and 60-69 years old subjects were found to be risk factors for IFG. Subjects with high BMI were more likely to develop IFG and DM.

Physical activity and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis

We investigated the association between specific types of physical activity and the risk of type 2 diabetes in a systematic review and meta-analysis of published studies. PubMed, Embase and Ovid databases were searched for prospective studies and randomized trials up to 2nd of March 2015. Summary relative risks (RRs) were calculated using a random effects model. Eighty-one studies were included. The summary RRs for high versus low activity were 0.65 (95 % CI 0.59-0.71, I(2) = 18 %, n = 14) for total physical activity, 0.74 (95 % CI 0.70-0.79, I(2) = 84 %, n = 55) for leisure-time activity, 0.61 (95 % CI 0.51-0.74, I(2) = 73 %, n = 8) for vigorous activity, 0.68 (95 % CI 0.52-0.90, I(2) = 93 %, n = 5) for moderate activity, 0.66 (95 % CI 0.47-0.94, I(2) = 47 %, n = 4) for low intensity activity, and 0.85 (95 % CI 0.79-0.91, I(2) = 0 %, n = 7) for walking. Inverse associations were also observed for increasing activity over time, resistance exercise, occupational activity and for cardiorespiratory fitness. Nonlinear relations were observed for leisure-time activity, vigorous activity, walking and resistance exercise (p nonlinearity < 0.0001 for all), with steeper reductions in type 2 diabetes risk at low activity levels than high activity levels. This meta-analysis provides strong evidence for an inverse association between physical activity and risk of type 2 diabetes, which may partly be mediated by reduced adiposity. All subtypes of physical activity appear to be beneficial. Reductions in risk are observed up to 5-7 h of leisure-time, vigorous or low intensity physical activity per week, but further reductions cannot be excluded beyond this range.

Trend analysis of diabetic prevalence and incidence in a rural area of South Korea between 2003-2008

Aims/Introduction:  This study determined the change in prevalence of diabetes and prediabetes over a period of 5 years in South Korea. The incidence of diabetes and prediabetes and risk factors associated with the development of diabetes were also investigated.

Materials and Methods:  The Dalseong population‐based cohort survey recruited 1806 subjects who were over 20‐years‐old in 2003. Five years later, 1287 of the original subjects were re‐evaluated and 187 new subjects were added to the study. All participants completed a questionnaire, were given a physical examination, and provided blood samples for analysis including 2 h oral glucose tolerances.

Results:  Age‐adjusted prevalence of diabetes rose from 6.7% in 2003 to 9.1% in 2008. The prevalence of prediabetes also increased from 18.5% in 2003 to 28.4% in 2008. The incidence rates of diabetes and prediabetes were 18.3 per 1000 person‐years and 55.4 per 1000 person‐years, respectively. The development of diabetes was associated with impaired fasting glucose (IFG) (odds ratio [OR] 5.661), impaired glucose tolerance (IGT) (OR: 6.013), age (OR 1.013), and waist‐to‐hip ratio (OR 1.513). After excluding the IFG and IGT, systolic blood pressure (OR 1.023), high‐sensitivity C‐reactive protein (hsCRP; OR 1.097), triglyceride (OR 1.002) and waist‐to‐hip ratio (OR 1.696) were statistically significant risk factors in a multivariate logistic regression analysis.

Conclusions:  A significant rise in the prevalence of diabetes and prediabetes was observed between 2003 and 2008. In addition, this study newly demonstrated that waist‐to‐hip ratio and hsCRP were associated with the development of diabetes after adjusting for several confounding factors. (J Diabetes Invest, doi: 10.1111/j.2040‐1124.2010.00045.x, 2010)

Combined heart rate- and accelerometer-assessed physical activity energy expenditure and associations with glucose homeostasis markers in a population at high risk of developing diabetes: the ADDITION-PRO study

OBJECTIVE

Regular physical activity (PA) reduces the risk of developing type 2 diabetes, and different subtypes of dysglycemia have shown different associations with PA. To better understand the associations of PA and glucose homeostasis, we examined the association of objectively measured PA energy expenditure (PAEE) with detailed measures of glucose homeostasis.

RESEARCH DESIGN AND METHODS

In 1,531 men and women, with low to high risk of developing type 2 diabetes, we measured 7 days of PAEE using a combined accelerometry and heart rate monitor (ActiHeart). Measures and indices of glucose homeostasis were derived from a 3-point oral glucose tolerance test in addition to measures of long-term glycemia (glycated hemoglobin A1c and advanced glycation end products). Associations of PAEE with glucose homeostasis markers were examined using linear regression models.

RESULTS

Median age (IQR) was 66.6 years (62.1-71.6) (54% men) with a median ActiHeart wear time of 6.9 days (6.0-7.1) and PAEE level of 33.0 kJ/kg/day (23.5-46.1). In fully adjusted models, we found higher levels of PAEE to be positively associated with insulin sensitivity and negatively with insulin 2 h after glucose load (P<0.05).

CONCLUSIONS

Even in an elderly population with low levels of PA, we found higher objectively measured PAEE levels to be associated with a more beneficial glucose metabolic profile. Although our findings are cross-sectional, they indicate that even without high-intensity exercise, increasing the overall level of PAEE slightly in an entire population at risk for developing type 2 diabetes may be a realistic and worthwhile goal to reach in order to achieve beneficial effect in terms of glucose metabolism.

Trajectories of cardiometabolic risk factors before diagnosis of three subtypes of type 2 diabetes: a post-hoc analysis of the longitudinal Whitehall II cohort study

BACKGROUND

Most clinicians acknowledge that type 2 diabetes is multifactorial and has heterogeneous characteristics, but neither prevention nor treatment is systematically stratified. To address the heterogeneity of the disease, we examined whether patients diagnosed on the basis of fasting glucose concentrations, those diagnosed on the basis of 2 h concentrations, and those diagnosed on the basis of both criteria differed in terms of pathogenesis or cardiovascular risks.

METHODS

Retrospectively, we analysed trajectories of cardiometabolic risk factors and 10 year cardiovascular risks in the prospective Whitehall II study cohort by use of multilevel longitudinal modelling. Participants were diagnosed by 75 g oral glucose-tolerance tests. We classified those diagnosed with type 2 diabetes into three subgroups: diagnosed on the basis of fasting glucose concentrations, diagnosed on the basis of 2 h glucose concentrations, and diagnosed on the basis of both concentrations. We also developed a classification tree for identification of individuals who are likely to have high fasting and 2 h glucose concentrations, but for whom only fasting concentrations are available.

RESULTS

Median follow-up was 14·2 years with 15,826 person-examinations (1991-2009). Of 10,308 individuals, 6843 were included and 6569 remained diabetes free. 274 cases of type 2 diabetes were identified: 55 had high fasting glucose concentrations only, 148 had high 2 h concentrations only, and 71 had high fasting and 2 h concentrations. At diagnosis, participants with high fasting and 2 h glucose concentrations had higher mean body-mass indices (30·9 kg/m(2) [SD 5·7]) than did those with high fasting concentrations (28·4 kg/m(2) [4·4]; p=0·0009) or 2 h concentrations (27·9 kg/m(2) [4·9]; <0·0001). Mean glycated haemoglobin A1c concentrations were also higher in the fasting and 2 h subgroup (7·4% [1·6]) than in the fasting (5·9% [0·5]; <0·0001) or 2 h (5·9% [0·6]; <0·0001) sugroups. Additionally, the fasting and 2 h subgroup had a higher proportion of individuals with moderate or high risk of cardiovascular disease than did the fasting subgroup (p=0·02). A classic pattern of β-cell decompensation before diagnosis was noted only in the fasting and 2 h subgroup. Additionally, glucose concentrations and insulin resistance accelerated more substantially before diagnosis in the fasting and 2 h subgroup than in the fasting subgroup or the 2 h subgroup.

INTERPRETATION

Patients with type 2 diabetes diagnosed on the basis of increased fasting glucose concentrations or 2 h glucose concentrations, or both, have distinct cardiometabolic risk development before diagnosis.

FUNDING

UK Medical Research Council, UK Economic and Social Research Council, British Heart Foundation, UK Health and Safety Executive, UK Department of Health, US National Heart Lung and Blood Institute, US National Institute on Aging, US Agency for Health Care Policy Research, and John D and Catherine T MacArthur Foundation.

Feasibility of the FINDRISC questionnaire to identify individuals with impaired glucose tolerance in Swedish primary care. A cross-sectional population-based study

AIM

To evaluate the performance of the FINDRISC questionnaire as a tool to recruit individuals with impaired glucose tolerance for lifestyle intervention programmes.

METHODS

A cross-sectional population-based study in primary Health Care Centres in a middle-sized Swedish town. All 9734 individuals, aged 35-75 years, living within a defined area, were invited by mail to fill in and return the FINDRISC questionnaire. Participants with a risk score ≥ 15 (n = 525) were invited to perform an oral glucose tolerance test while those with known diabetes were excluded.

RESULTS

In total, 5452 questionnaires (58%) were returned and revealed a mean risk-score of 8.5 ± 4.5 (mean ± SD). We found that 525 participants had a risk-score ≥ 15 and 302 (58%) were further examined with an oral glucose tolerance testing (OGTT). Among them we detected 11% with previously undiagnosed Type 2 diabetes, 16% with impaired glucose tolerance and 29% with impaired fasting glucose. A FINDRISC score ≥ 15 was associated with a positive predictive value of 55% for impaired glucose metabolism (impaired fasting glucose + impaired glucose tolerance + Type 2 diabetes) and of 16% for impaired glucose tolerance, respectively. The positive predictive value for impaired glucose tolerance did not increase to more than 17% when choosing the cut-point 17, while there was a significant increase in the positive predictive value for impaired glucose metabolism (70%).

CONCLUSIONS

The FINDRISC questionnaire is a useful instrument for identification of individuals with impaired glucose metabolism but seems less effective for detection of individuals with impaired glucose tolerance. Strategies to find individuals with impaired glucose tolerance for implementation of lifestyle changes in primary care should therefore be developed further.

Improvement in insulin sensitivity following a 1-year lifestyle intervention program in viscerally obese men: contribution of abdominal adiposity

The objectives of the study were to quantify the effect of a 1-year healthy eating-physical activity/exercise lifestyle modification program on insulin sensitivity in viscerally obese men classified according to their glucose tolerance status and to evaluate the respective contributions of changes in body fat distribution vs changes in cardiorespiratory fitness (CRF) to the improvements in indices of plasma glucose/insulin homeostasis. Abdominally obese, dyslipidemic men (waist circumference ≥90 cm, triglycerides ≥1.69 mmol/L, and/or high-density lipoprotein cholesterol <1.03 mmol/L) were recruited. The 1-year intervention/evaluation was completed by 104 men. Body weight, composition, and fat distribution were assessed by dual-energy x-ray absorptiometry/computed tomography. Cardiorespiratory fitness and cardiometabolic risk profile were measured. After 1 year, insulin sensitivity improved in association with decreases in both visceral (VAT) and subcutaneous adiposity (SAT) as well as with the improvement in CRF, regardless of baseline glucose tolerance. Further analyses were performed according to changes in glucose tolerance status: improvement (group I, n = 39), no change (group N, n = 50), or worsening (group W, n = 15) after 1 year. Groups I and N improved their insulin sensitivity and their CRF, whereas group W did not, while losing less VAT than groups I and N. Multiple regressions showed that reduction in VAT was associated with an improvement in homeostasis model assessment of insulin resistance, whereas reduction in SAT was rather associated with improvement of the insulin sensitivity index of Matsuda. Changes in CRF were not independently associated with changes in indices of plasma glucose/insulin homeostasis. A 1-year lifestyle intervention improved plasma glucose/insulin homeostasis in viscerally obese men, including those with normal glucose tolerance status at baseline. Changes in SAT and VAT but not in CRF appeared to mediate these improvements.

High cardiorespiratory fitness is more beneficial in pre-diabetic men than women

OBJECTIVES

To investigate gender-specific relationships between cardiorespiratory fitness and factors that predict the development of diabetes and to identify the risk factors that predict fasting plasma glucose and 2-hour plasma glucose levels.

INTRODUCTION

Different risk factors (e.g., low cardiorespiratory fitness) may cause elevated plasma glucose levels in men compared to women. Therefore, gender-specific analyses are needed.

METHODS

Cardiorespiratory fitness (maximal power output achieved during a standard cycle ergometry test), resting blood pressure, total serum cholesterol, high-density lipoprotein cholesterol and triglyceride levels were measured in 32 pre-diabetic men (mean age: 57.2 ± 6.8 years; mean body mass index (BMI): 28.5 ± 3.0 kg/m²) and 40 pre-diabetic women (mean age: 55.0 ± 7.3 years, mean BMI: 30.4 ± 5.7 kg/m²). A stepwise regression with backward variable selection was performed to construct models that predict 2-hour and fasting plasma glucose levels.

RESULTS

Maximal power output was inversely related to the 2-hour plasma glucose level in the entire group (r= -0.237, p<0.05), but this relationship was significant only for males (r= -0.404, p<0.05). No significant correlation was found between female gender and cardiorespiratory fitness. Age and cardiorespiratory fitness were significant predictors of 2-hour plasma glucose levels in men. High-density lipoprotein cholesterol was predictive of 2-hour plasma glucose levels in women. Triglycerides in women and BMI in men were the only predictors of fasting plasma glucose levels.

CONCLUSIONS

These findings may have consequences for the development of gender-specific diabetes prevention programs. Whereas increasing cardiorespiratory fitness should be a key goal for men, improving the lipid profile seems to be more beneficial for women. However, the present results do not negate the positive effects of increasing cardiorespiratory fitness in women.