scholarly journals The Role of Muscle Decline in Type 2 Diabetes Development: A 5-Year Prospective Observational Cohort Study

Nutrients ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 834 ◽  
Author(s):  
Katarzyna Maliszewska ◽  
Edyta Adamska-Patruno ◽  
Joanna Goscik ◽  
Danuta Lipinska ◽  
Anna Citko ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Cohort Study ◽  
Glucose Tolerance ◽  
Muscle Mass ◽  
Support Vector ◽  
Distribution Analysis

The major risk factors of T2DM (type 2 diabetes mellitus) development are still under investigation. We evaluate the possible risk factors associated with type 2 diabetes (T2DM) in adult subjects during a five-year prospective cohort study. We recruited 1160 subjects who underwent oral glucose tolerance test, anthropometric measurements, and body composition and body fat distribution analysis at a baseline visit and again at follow-up after approximately five years. The conclusions of this study are based on observation of 219 subjects who attended both the first and follow-up visits. The fasting serum insulin was measured, and HOMA-IR (homeostatic model assessment of insulin resistance) was calculated. During the follow-up period, T2DM was diagnosed in 7.4% of participants, impaired fasting glucose in 37.7%, and impaired glucose tolerance in 9.3%. Logistic regression models, adjusted for age, were constructed. The changes in glucose concentration, visceral fat tissue content, insulin resistance, and %loss of muscle mass were chosen as the potential predictors for T2DM development. A set of independent variables was extracted. The constructed feature set comprised change in HOMA-IR (OR (odds ratio) = 1.01, p < 0.01) and change in %loss of muscle mass (OR = 0.84, p < 0.03). With an aim to validate the prediction capability using the selected attributes, a support vector machine classifier and leave-one-out cross-validation procedure was applied, yielding 92.78% classification accuracy. Our results show the correlation between the %loss of muscle mass and T2DM development in adults, independent of changes in insulin resistance.

scholarly journals Different Contributions of Dyslipidemia and Obesity to the Natural History of Type 2 Diabetes: 3-Year Cohort Study in China

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Lu Liu ◽  
Xiaoling Guan ◽  
Zhongshang Yuan ◽  
Meng Zhao ◽  
Qiu Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cohort Study ◽  
Natural History ◽  
Glucose Tolerance ◽  
Serum Triglyceride ◽  
Glycemic Status ◽  
History Of

Aim. It is known that different stages of type 2 diabetes represent distinct pathophysiological changes, but how the spectrum of risk factors varies at different stages is not yet clarified. Hence, the aim of this study was to compare the effect of different metabolic variables on the natural history of type 2 diabetes. Methods. A total of 5,213 nondiabetic (normal glucose tolerance (NGT) and prediabetes) Chinese older than 40 years participated this prospective cohort study, and 4,577 completed the 3-year follow-up. Glycemic status was determined by standard oral glucose tolerance test both at enrollment and follow-up visit. Predictors for conversion in glycemic status were studied in a corresponding subcohort using the multiple logistic regression analysis. Results. The incidence of prediabetes and diabetes of the cohort was 93.6 and 42.2 per 1,000 person-years, respectively. After a 3-year follow-up, 33.1% of prediabetes patients regressed to NGT. The predictive weight of body mass index (BMI), serum triglyceride, total cholesterol, and systolic blood pressure in different paths of conversions among diabetes, prediabetes, and NGT differed. Specifically, BMI was the strongest predictor for regression from prediabetes to NGT, while triglyceride was most prominent for onset of diabetes. One SD increase in serum triglyceride was associated with a 1.29- (95% CI 1.10–1.52; P=0.002) or 1.12- (95% CI 1.01–1.27; P=0.039) fold higher risk of diabetes for individuals with NGT or prediabetes, respectively. Conclusion. Risk factors for different stages of diabetes differed, suggesting personalized preventive strategies for individuals with different basal glycemic statuses.

Abstract P130: Risk Factors for Progression to Type 2 Diabetes Mellitus From Prediabetes

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Margareta Hellgren ◽  
Ulf Lindblad ◽  
Bledar Daka
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Family History ◽  
Glucose Tolerance

Background and Aims: Individuals with prediabetes, impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT), have approximately 50% risk to develop type 2 diabetes mellitus (T2DM) within ten years. This paper examines risk factors for development of T2DM in individuals with prediabetes. Materials and Methods: A total of 2816 individuals were randomly selected and completed a careful physical examination and an oral glucose tolerance test. IFG and IGT was defined according to WHO. A representative sample of 1327 individuals were re-examined in a follow-up study after ten years. This study focuses on the participants who were diagnosed with prediabetes, IFG (n=67) and/or IGT (n=89) at baseline and who were re-examined at follow-up. Insulin resistance was estimated by HOMA-ir (Homeostatic Model Assessment for Insulin Resistance). Differences between the participants with prediabetes who developed T2DM and those who did not, were analyzed with general linear models and adjusted for age, sex and BMI. The risk to progress to T2DM in ten years was explored using binary logistic regression, adding the risk-factors one after another. Results: Of the 156 individuals with prediabetes 28% progressed to T2DM. Individuals who developed T2DM had higher BMI (α=3.2kg/m 2 , P<0.001), higher HbA1c (α=0.2 mmol/mol, P=0.047), higher C-reactive protein (α=3.3 mmol/L, P=0.040) and also significantly higher HOMAir (α=2.8, P<0.001) at base-line. The risk to develop T2DM increased in a step-wise manner in individuals with prediabetes when successively adding the risk-factors. Having a BMI ≥30kg/m 2 , a known family history for T2DM, HbA1c ≥37mmol/mol, HOMAir ≥2.8 and a low level of physical activity increased the risk to develop T2DM 5.6 times. Table 1. Conclusion: In individuals with prediabetes, those with additional risk-factors like obesity, HbA1c and HOMAir above mean values, family history for T2DM and a low level of physical activity require extra attention and intensive lifestyle interventions should be initiated.

scholarly journals Endothelin-1 predicts incident diabetic peripheral neuropathy in Type 2 Diabetes: a cohort study

2020 ◽  
Vol 182 (4) ◽  
pp. 429-438
Author(s):  
Sharon Li Ting Pek ◽  
Su Chi Lim ◽  
Keven Ang ◽  
Pek Yee Kwan ◽  
Wern Ee Tang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Cohort Study ◽  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Diabetes Duration ◽  
Endothelin 1

Introduction Diabetic peripheral neuropathy (DPN) is a common microvascular complication in patients with type 2 diabetes (T2D). Apart from hyperglycemia, few modifiable risk factors have been identified. Endothelin-1 is a potent vasoconstrictor peptide, implicated in the causal pathway of microangiopathy. We investigated whether baseline plasma endothelin-1 and other metabolic and vascular risk factors predicted the incidence of DPN. Design This is a 3-year observational, cohort study. Methods In patients with T2D (n = 2057), anthropometric data, fasting blood, and urine were collected for biochemistry and urine albumin/creatinine measurements. Forearm cutaneous endothelial reactivity was assessed by iontophoresis and laser Doppler flowmetry/imaging. Measurements were repeated on follow-up. Incident DPN was considered present if an abnormal finding in monofilament (<8 of 10 points) or neurothesiometer testing was ≥25 volts on either foot at 3-year follow-up, but normal at baseline. Plasma endothelin-1 was assessed by ELISA. Results At baseline, mean age of patients was 57.4 ± 10.8 years old and prevalence of DPN was 10.8%. Of the 1767 patients without DPN, 1250 patients returned for follow-up assessment ((2.9 ± 0.7) years), with a 10.7% incidence of DPN. Patients with incident DPN had significantly higher baseline endothelin-1 (1.43 (1.19–1.73) vs 1.30 (1.06–1.63)) pg/mL, P < 0.0001. Multivariable Cox proportional hazards ratio showed a 1-s.d. increase in log endothelin-1 (adjusted HR: 4.345 (1.451–13.009), P = 0.009), systolic blood pressure (per 10-unit) (adjusted HR: 1.107 (1.001–1.223), P = 0.047) and diabetes duration (adjusted HR: 1.025 (1.004–1.047), P = 0.017) predicted incident DPN, after adjustment for glycemic control, eGFR, albuminuria, peripheral arterial disease and retinopathy status. Conclusion Higher baseline endothelin-1, blood pressure and diabetes duration were significant and independent predictors for incident DPN. Validation of our findings in independent cohorts and molecular mechanistic studies will help better our understanding on the role of endothelin-1 in DPN.

scholarly journals Effect of Exercise Habit on Skeletal Muscle Mass Varies with Protein Intake in Elderly Patients with Type 2 Diabetes: A Retrospective Cohort Study

Nutrients ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 3220 ◽  
Author(s):  
Yoshitaka Hashimoto ◽  
Ayumi Kaji ◽  
Ryosuke Sakai ◽  
Fuyuko Takahashi ◽  
Rena Kawano ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Skeletal Muscle ◽  
Cohort Study ◽  
Muscle Mass ◽  
Protein Intake ◽  
Retrospective Cohort ◽  
Skeletal Muscle Mass ◽  
Exercise Habit

Exercise has been reported to be effective in maintaining and recovering muscle; however, the effect of exercise combined with adequate or inadequate protein intake on muscle mass is not clear. Therefore, this study investigates the effect of exercise habit on changes in muscle mass, with adequate or inadequate protein intake. This retrospective cohort study included 214 elderly patients with type 2 diabetes. The rate of skeletal muscle mass index (SMI) change (%) was defined as ((SMI at follow-up minus SMI at baseline)/(follow-up years [kg/m2/year] × SMI at baseline [kg/m2])) × 100. Adequate protein intake was defined as protein intake ≥1.2 g/kg ideal body weight/day. During a mean follow-up duration of 18.0 (7.1) months, the rate of SMI change was −1.14 (4.10)% in the whole sample. The rate of SMI change of non-habitual exercisers with inadequate protein intake, habitual exercisers with inadequate protein intake, non-habitual exercisers with adequate protein intake, and habitual exercisers with adequate protein intake was −1.22 (3.71), −2.31 (3.30), −1.88 (4.62), and 0.36 (4.29)%, respectively. Compared with patients with exercise habit and adequate protein intake, the odds ratio for decreasing SMI was 2.50 (0.90–6.90, p = 0.078) in patients with no exercise habit and inadequate protein intake, 3.58 (1.24–10.4, p = 0.019) in those with exercise habit and inadequate protein intake, and 3.03 (1.27–7.22, p = 0.012) in those with no exercise habit and adequate protein intake, after adjusting for covariates. Therefore, exercise habit without adequate protein intake was associated with an increased risk of decreasing SMI compared with exercise habit with adequate protein intake.

scholarly journals The Finnish Diabetes Risk Score Is Associated with Insulin Resistance and Progression towards Type 2 Diabetes

2009 ◽  
Vol 94 (3) ◽  
pp. 920-926 ◽  
Author(s):  
Peter E. H. Schwarz ◽  
Jiang Li ◽  
Manja Reimann ◽  
Alta E. Schutte ◽  
Antje Bergmann ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Cohort Study ◽  
Glucose Tolerance ◽  
Area Under The Curve ◽  
Diabetes Risk ◽  
Operating Characteristics ◽  
Cross Sectional Survey ◽  
Cross Sectional

Abstract Objective: The Finnish Diabetes Risk Score (FINDRISC) questionnaire is a practical screening tool to estimate the diabetes risk and the probability of asymptomatic type 2 diabetes. In this study we evaluated the usefulness of the FINDRISC to predict insulin resistance in a population at increased diabetes risk. Design: Data of 771 and 526 participants in a cross-sectional survey (1996) and a cohort study (1997–2000), respectively, were used for the analysis. Data on the FINDRISC and oral glucose tolerance test parameters were available from each participant. The predictive value of the FINDRISC was cross-sectionally evaluated using the area under the curve-receiver operating characteristics method and by correlation analyses. A validation of the cross-sectional results was performed on the prospective data from the cohort study. Results: The FINDRISC was significantly correlated with markers of insulin resistance. The receiver operating characteristics-area under the curve for the prediction of a homeostasis model assessment insulin resistance index of more than five was 0.78 in the cross-sectional survey and 0.74 at baseline of the cohort study. Moreover, the FINDRISC at baseline was significantly associated with disease evolution (P &lt; 0.01), which was defined as the change of glucose tolerance during the 3 yr follow-up. Conclusions: The results indicate that the FINDRISC can be applied to detect insulin resistance in a population at high risk for type 2 diabetes and predict future impairment of glucose tolerance.

scholarly journals Association of urinary RBP4 with insulin resistance, inflammation, and microalbuminuria

2014 ◽  
Vol 171 (4) ◽  
pp. 443-449 ◽  
Author(s):  
Se Eun Park ◽  
Nam Seok Lee ◽  
Ji Woo Park ◽  
Eun-Jung Rhee ◽  
Won-Young Lee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Arterial Stiffness ◽  
Glucose Tolerance ◽  
Cardiometabolic Risk ◽  
Urinary Albumin ◽  
Metabolic Parameters ◽  
The Relationship

ObjectiveSerum concentrations of retinol-binding protein 4 (RBP4) are elevated in type 2 diabetes and associated with the severity of insulin resistance; however, there are few data about the relationship between urinary RBP4 levels and metabolic parameters. We assessed urinary RBP4 as a new biomarker by establishing its relationship with clinical parameters associated with insulin resistance and urinary albumin excretion.Design and methodsWe measured RBP4 in the serum and urine of 689 subjects with diverse glucose tolerance status. We also evaluated the relationship between urinary RBP4 and cardiometabolic risk factors, including insulin resistance, high-sensitivity C-reactive protein (hsCRP), arterial stiffness, and microalbuminuria.ResultsUrinary RBP4 levels were higher in insulin-resistant subjects with prediabetes or type 2 diabetes than in subjects with normal glucose tolerance (NGT) (type 2 diabetes>prediabetes>NGT; allP<0.001). Urinary RBP4 correlated strongly with homeostasis model assessments of insulin resistance (HOMA-IR), fasting glucose, triglycerides, blood pressure, hsCRP, arterial stiffness, estimated glomerular filtration rate, and urinary albumin-to-creatinine ratio (allP<0.01). HOMA-IR and arterial stiffness were found to be independent determinants of urinary RBP4 concentration. Furthermore, urinary RBP4 was highly predictive of microalbuminuria (odds ratio 2.6, 95% CI 1.6–4.2), even after adjustment for other metabolic parameters. The area under the ROC curve for urinary RBP4 to detect the presence of microalbuminuria was 0.80±0.02 (95% CI 0.76–0.84) and the cut-off value was 157.01 μg/gCr.ConclusionsUrinary RBP4 concentrations were elevated in patients with dysregulation of glucose metabolism and were related to various cardiometabolic risk factors including insulin resistance, inflammation, and microalbuminuria.

scholarly journals Muscle strength, an independent determinant of glycemic control in older adults with long-standing type 2 diabetes: a prospective cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bo Kyung Koo ◽  
Seoil Moon ◽  
Min Kyong Moon
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Older Adults ◽  
Glycemic Control ◽  
Muscle Mass ◽  
Older Patients ◽  
Primary Outcome ◽  
Muscle Quality

Abstract Background Although the proportion of older patients with type 2 diabetes mellitus (T2DM) has increased, few studies have reported the factors affecting glucose levels in older patients with long-standing T2DM. This study assessed the determinants of glycemic control in older adults with T2DM of a duration of ≥10 years, including muscle mass, muscle quality, and β-cell function. Methods This was a prospective study of older patients aged ≥60 years with a T2DM duration of ≥10 years. The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) index, handgrip strength (HGS), and body composition through bioelectrical impedance analysis were assessed. The primary outcome was a composite of: (i) increment of glycated hemoglobin (HbA1c) from the baseline ≥0.6% and (ii) HbA1c ≥ 9% at any time point during the follow-up period. To find the predicting determinants of the outcome, we performed the Cox proportional hazard analysis. Results Among 100 patients (mean age, 64.0 ± 8.6 years; median duration of diabetes, 20 [interquartile range (IQR), 17–23] years; median HbA1c at baseline, 7.1 [IQR, 6.7–7.4] %), the primary outcome was observed in 40 (40.0%) patients during 4.0 (IQR 2.3–5.0) years of follow-up. A Cox proportional hazards model adjusted for age, sex, baseline HbA1c, obesity, duration of DM and anti-diabetic medication at baseline showed that low HGS and insulin resistance at the baseline were independent determinants of the primary outcome (hazard ratio [HR] = 2.23 [95% confidence interval (CI), 1.06–4.72] and 2.39 [95% CI, 1.18–4.83], respectively). Sex stratification confirmed that HGS and muscle mass were independent determinants of the primary outcome only in women (HR per quartile, 0.58 [95% CI, 0.37–0.93] and 0.46 [95% CI, 0.25–0.85], respectively). `. Conclusions Low HGS and insulin resistance were independent risk factors for aggravated glycemic control among older patients with long standing T2DM.

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