Associations of Long-Term Exposure to Temperature Variability with Glucose Metabolism: Results from KORA F4 and FF4.

BackgroundInsulin resistance (IR) occurs in 50–70% of women with polycystic ovary syndrome (PCOS) and can be applied as a prediabetic feature in PCOS.ObjectiveIn this study, indirect methods including fasting blood sugar (FBS), fasting insulin (FI), FBS/FI ratio, and quantitative insulin sensitivity check index (QUICKI) were compared with the homeostasis model assessment of insulin resistance (HOMA-IR) as a standard technique. The association of IR to sex hormone-binding globulin (SHBG) and several hormones was also analyzed.Materials and MethodsThis cross-sectional study was performed on 74 PCOS women. Sensitivity and specificity of each IR method was calculated based on HOMA-IR. Hormonal profiles of the patients were compared between the groups with defined normal and abnormal values of IR.ResultsTriglyceride levels had a positive association with FBS and HOMA-IR (p = 0.002 and p = 0.01, respectively) with a negative association to QUICKI and SHBG (p = 0.02 and p = 0.02, respectively). SHBG showed a significant negative association with FBS (p = 0.001). Dehydroepiandrosterone sulfate showed a positive association with FI (p = 0.002). Seven PCOS women showed abnormal SHBG levels ( 36 nmol/L) while expressed normal values of the rest of the studied variables. FI and QUICKI had the highest sensitivity while FBS/FI and QUICKI had the highest specificity when HOMA-IR was applied as a standard test.ConclusionSHBG and triglyceride had a significant negative and positive association with IR, respectively. HOMA-IR followed by FI and QUICKI is the most sensitive test for the detection of IR. SHBG levels can be a helpful biomarker for the diagnosis of PCOS.

To evaluate the role of adiposity in the relationship between specific and surrogate estimates of insulin-mediated glucose uptake (IMGU) in a large nondiabetic population. Healthy volunteers were classified by BMI into normal weight (<25.0 kg/m(2), n = 208), overweight (25.0-29.9 kg/m(2), n = 168), and obese (>or=30.0 kg/m(2), n = 109) groups. We then assessed how differences in BMI affect the correlation between steady-state plasma glucose (SSPG) concentration at the end of a 180-min infusion of octreotide, glucose, and insulin (a specific measure of IMGU) and five surrogate estimates: fasting plasma glucose, fasting plasma insulin, homeostasis model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), and area under the curve for insulin in response to oral glucose (I-AUC). Correlation coefficients (r values) between SSPG and surrogate measures of IMGU were all significant (P < 0.05), but the magnitude varied between BMI groups: normal weight: fasting plasma glucose 0.20, fasting plasma insulin 0.33, HOMA-IR 0.36, QUICKI -0.33, and I-AUC 0.69; overweight: fasting plasma glucose 0.19, fasting plasma insulin 0.55, HOMA-IR 0.55, QUICKI -0.54, and I-AUC 0.72; and obese: fasting plasma glucose 0.40, fasting plasma insulin 0.56, HOMA-IR 0.60, QUICKI -0.61, and I-AUC 0.69. The relationship between direct and surrogate estimates of IMGU varies with BMI, with the weakest correlations seen in the normal-weight group and the strongest in the obese group. In general, I-AUC is the most useful surrogate estimate of IMGU in all weight groups. Fasting plasma insulin, HOMA-IR, and QUICKI provide comparable information about IMGU. Surrogate estimates of IMGU based on fasting insulin and glucose account for no more than 13% of the variability in insulin action in the normal-weight group, 30% in the overweight group, and 37% in the obese group.

Purpose: To evaluate the association between diverse surrogate markers of insulin resistance and adiponectin concentrations. Methods: Four hundred healthy participants were included. Two different cohorts were formed according to the body mass index (BMI) values. Group 1 (n = 200) consisted of individuals with normal BMI values (18.50-24.99 kg/m2), whereas in Group 2 (n = 200) there were overweight or obese individuals (BMI ≥25.00 kg/m2). Homeostasis model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), and triglycerides-glucose index (TyG) were calculated. Serum adiponectin levels were measured by ELISA. A correlation analysis was performed to assess the association between serum adiponectin and HOMA-IR, QUICKI, and TyG. Results: Participants in Group 2 were older (age in years: Group 1, 33.3 ± 6.8 vs. Group 2, 36.4 ± 7.0, P < 0.001). There was no gender difference between groups. Overweight or obese participants had higher BMI, waist circumference, fat mass, fat ratio, fasting plasma glucose, fasting plasma insulin, triglycerides, total cholesterol, and low-density lipoprotein cholesterol values, whereas high-density lipoprotein cholesterol was higher in participants with normal BMI measures. Overweight or obese subjects were more insulin resistant (higher TyG index and HOMA-IR) and less insulin sensitive (lower QUICKI), P < 0.001 for all. Serum adiponectin levels were lower in Group 2 (serum adiponectin in ng/mL: Group 1, 11,880 ± 6838 vs. Group 2, 9115 ± 5766, P < 0.001). The correlation between TyG index and adiponectin was stronger than the correlation between QUICKI and adiponectin, and HOMA-IR and adiponectin (r for TyG and adiponectin -0.408, r for QUICKI and adiponectin 0.394, r for HOMA-IR and adiponectin -0.268, respectively, P < 0.001 for all correlations). Conclusions: TyG has a stronger association with adiponectin than HOMA-IR and QUICKI.

Background: Insulin resistance (IR) is common in overweight or obese individuals. Dysregulation of trace elements such as cobalt (Co) and manganese (Mn) has been associated with obesity and IR markers in individuals with diabetes. However, their role in non-diabetic states is less understood. Objective: This study aimed to analyze the association between serum Co and Mn levels and IR in overweight and obese women without diabetes. Methods: A total of 112 overweight or obese women were evaluated for their anthropometric, metabolic, and biochemical characteristics. To estimate IR, the homeostatic model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), triglyceride-glucose index (TyG), and triglyceride-glucose-body mass index (TyG-BMI) were calculated. Serum Co and Mn concentrations were quantified by inductively coupled plasma mass spectrometry (ICP-MS). Results: Our results show that 77% of participants exhibited central fat accumulation and a high prevalence of IR. Fasting insulin (FINS), HOMA-IR, and TyG-BMI were significantly higher in obese women, while adiponectin (Adpn) was lower. Moreover, Co was inversely associated with FINS (p = 0.003) and HOMA-IR (p = 0.011), and positively associated with QUICKI (p = 0.011) in obese women. In contrast, serum Mn levels showed negative correlations with fasting glucose (FG) (p = 0.021) and the TyG index (p = 0.048) in overweight women. Conclusions: Co serum levels were positively associated with FG and QUICKI and negatively associated with FINS and HOMA-IR in the obese group. Mn showed negative associations with FG and the TyG index, suggesting that these trace elements may play a role in the IR in people with obesity.

Highlights. Patients with coronary artery disease undergoing coronary artery bypass grafting have a high prevalence of type 2 diabetes mellitus and prediabetes. The frequency of postoperative stroke and hospital stay is significantly higher in patients with impaired carbohydrate metabolism.Insulin resistance markers are associated with a variety of perioperative characteristics, but according to multivariate analysis, only free fatty acids and HOMA-IR were independent predictors of hospitalacquired complications and long-term hospital stayAim. To analyze insulin resistance markers and their association with the preoperative outcome and in-hospital complications of coronary bypass grafting (CABG) in patients with type 2 diabetes mellitus (DM 2), prediabetes and normoglycemia.Methods. The study included 383 consecutive patients undergoing CABG at the same center. Glycemic status, free fatty acids (FFA), fasting insulin, glucose, lipid profile of all patients were determined before surgery and the following insulin resistance indices (IR) were calculated: HOMA-IR (Homeostasis Model Assessment of Insulin Resistance), QUICKI (Quantitative Insulin Sensitivity Check Index), Revised QUICKI, McAuley. Patients were divided into 2 groups: the group that included patients with carbohydrate metabolism disorders (CMD), type 2 diabetes mellitus and prediabetes (n = 192), and the group of patients without CMD (n = 191). Perioperative characteristics of patients, postoperative complications and their association with insulin resistance markers were analyzed.Results. FFA and calculated indices of insulin resistance such as HOMA-IR, QUICKI, RevisedQUICKI, and McAuley correlated with the following perioperative characteristics: the duration of surgical intervention and cardiopulmonary bypass, lipid levels, coagulation index, left ventricular dimension and myocardial diastolic function, etc. The analysis of in-hospital complications revealed that the frequency of postoperative stroke (p = 0.044) and hospital stay after CABG &gt;30 days (p = 0.014) was significantly higher in patients with CMD. According to the results of multivariate analysis, the predictors of the composite endpoint (hospital stay after CABG&gt;10 days and/or significant perioperative complication) were as follows: female sex (odds ratio (OR) 2.862, 95% confidence interval (CI) 1.062-7.712, p = 0.036); age (OR 1.085, 95%CI 1.027–1.147, p = 0.003); duration of cardiopulmonary bypass (OR 1.146, 95%CI 1.008–1.301, p = 0.035); body mass index (OR 1.125, 95% CI 1.035–1.222, p = 0.005), left atrial dimension (OR 5.916 95% CI 2.188–15.996, p&lt;0.001); any CMD (OR 1.436, 95%CI 1.029–2.003, p = 0.032), type 2 DM (OR 2.184, 95%CI 1.087–4.389, p = 0.027), FFA levels (OR 5.707, 95%CI 1.183–27.537, p = 0.029) and HOMA–IR index (OR 1.164, 95%CI 1.025–1.322, p = 0.019).Conclusion. FFA, HOMA-IR, QUICKI, Revised-QUICKI, and McAuley correlate with a variety of perioperative characteristics of patients undergoing CABG, but multivariate analysis revealed that only FFA levels and the HOMA-IR can be used as predictors of in-hospital complications and prolonged hospital stay.

Background:Endocrine abnormalities related to polycystic ovary Syndrome (PCOS) are important problems.Objective:To compare serum leptin levels between infertile women with and without PCOS. To rank sensitivity of six indirect methods for detection of insulin resistance (IR) and to evaluate the association between leptin and IR in PCOS group.Materials and methods:This Case-controlled study performed on 189 infertile women referred to Shiraz Mother and Child Hospital during 2012-2015. Ninety-nine PCOS cases according to Rotterdam criteria were compared to 90 cases without PCOS. Serum leptin, body mass index (BMI), several hormones, and their correlation coefficients with leptin were compared. IR in PCOS women was measured by indirect methods, including fasting blood sugar (FBS), fasting insulin (FI), glucose/insulin, homeostatic model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), and MacAuley index. Association between IR and leptin was evaluated. Independent sample t-test and Pearson’s test were used.Results: Infertile women with PCOS had higher BMI (26.47±3.62 vs. 24.82±5.18 kg/m2) and serum leptin levels (41.79±187.89 vs. 19.38±12.57 ng/mL). Leptin showed significant association with weight and BMI in both groups (p<0.001) and to age in non-PCOS group. HOMA-IR showed the highest rate of IR followed by FI and QUICKI methods. The mean leptin levels had positive association with IR assessed by HOMA-IR (p<0.001), QUICKI (p<0.001), FI (p=.002), and FBS (p=0.02).Conclusion:BMI and IR have positive association with serum leptin in PCOS infertile women. HOMA-IR followed by FI and QUICKI is the most sensitive test for detection of IR.

Dysregulation in the circadian system induced by variants of clock genes has been associated with type 2 diabetes. Evidence for the role of cryptochromes, core components of the system, in regulating glucose homeostasis is not supported by CRY1 candidate gene association studies for diabetes and insulin resistance in human, suggesting possible dietary influences. The purpose of this study was to test for interactions between a CRY1 polymorphism, rs2287161, and carbohydrate intake on insulin resistance in two independent populations: a Mediterranean (n = 728) and an European origin North American population (n = 820). Linear regression interaction models were performed in two populations to test for gene–diet interactions on fasting insulin and glucose and two insulin-related traits, homeostasis model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI). In addition, fixed effects meta-analyses for these interactions were performed. Cohort-specific interaction analyses showed significant interactions between the CRY1 variant and dietary carbohydrates for insulin resistance in both populations (p < 0.05). Findings from the meta-analyses of carbohydrate–single nucleotide polymorphism interactions indicated that an increase in carbohydrate intake (% of energy intake) was associated with a significant increase in HOMA-IR (p = 0.011), fasting insulin (p = 0.007) and a decrease in QUICKI (p = 0.028), only among individuals homozygous for the minor C allele. This novel finding supports the link between the circadian system and glucose metabolism and suggests the importance this CRY1 locus in developing personalized nutrition programs aimed at reducing insulin resistance and diabetes risk.

IntroductionThe objective of this study was to compare the associations of accelerometer-derived total activity counts per day and minutes of bouted moderate to vigorous physical activity (MVPA) with insulin resistance.MethodsThe sample included 2,394 adults (aged ≥20 y) from the 2003–2006 National Health and Nutrition Examination Survey. Time spent in MVPA, measured by using 2 cutpoints (≥2,020 counts/min [MVPA2,020] and ≥760 counts/min [MVPA760]), was calculated for bouts of at least 8 to 10 minutes. Total activity counts per day reflects the total amount of activity across all intensities. Insulin resistance was measured via the homeostatic model assessment of insulin resistance (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI). Two nested regression models regressed HOMA-IR and QUICKI, respectively, on minutes of bouted MVPA and total activity counts per day. We used an adjusted Wald F statistic to illustrate strength of association.ResultsAfter adjustment for covariates, total activity counts per day was more strongly associated with both HOMA-IR (adjusted Wald F = 36.83 , P < .001) and QUICKI (adjusted Wald F = 29.44, P < .001) compared with MVPA2,020 (HOMA-IR, adjusted Wald F = 4.00, P = .06; QUICKI, adjusted Wald F = 1.08, P = .31).Total activity counts per day was more strongly associated with both HOMA-IR (adjusted Wald F = 13.64, P < .001) and QUICKI (adjusted Wald F = 12.10, P < .001) compared with MVPA760 (HOMA-IR, adjusted Wald F = 1.13, P = .30; QUICKI, adjusted Wald F = 0.97, P = .33).ConclusionOur study indicated that total activity counts per day has stronger associations with insulin resistance compared with minutes of bouted MVPA. The most likely explanation is that total activity counts per day captures data on light physical activity and intermittent MVPA, both of which influence insulin resistance.

Background: To examine the effect of Tai Chi Chuan (TCC) practice on glucose and lipid metabolism and related hormones in TCC practitioners. Methods: Twenty-one TCC practitioners and nineteen healthy controls were included in this study. Classical Yang’s TCC was practiced by the TCC practitioners. The percentage changes in serum total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), serum glucose (SG), serum insulin, serum insulin level, homeostatic model assessment of insulin resistance (HOMA-IR), log(HOMA-IR), quantitative insulin sensitivity check index (QUICKI), and serum endothelin-1 (ET-1) before and 30 min after resting or TCC practice were compared between healthy controls and TCC practitioners. Results: Before TCC or resting, the serum insulin level, HOMA-IR, and log(HOMA-IR) of the TCC practitioners were significantly lower than those of healthy subjects, whereas the QUICKI of the TCC practitioners was significantly higher than that of healthy subjects. Thirty min after TCC practice, the %TC, %HDL-C, %QUICKI, and %ET-1 were all significantly decreased, whereas the %SG, %serum insulin, and %HOMA-IR were significantly increased in the TCC group as compared to the control group 30 min after resting. Conclusions: The serum glucose, insulin level and insulin resistance were enhanced, whereas the cholesterol, HDL-C and ET-1 levels were reduced 30 min after TCC practice. The mechanism underlying these effects of TCC 30 min after TCC is not clear yet.

Lower serum apelin levels in women with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a leading endocrine disorder in reproductive-aged women. While dietary interventions are widely advocated, the distinct roles of adiposity and dietary inflammation in driving PCOS phenotypes remain unclear. Therefore, this study aimed to dissect the contributions of body mass index (BMI) and dietary inflammatory index (DII) to hyperandrogenism and insulin resistance (IR) in PCOS. This cross-sectional study included 115 women with PCOS who visited gynecology and infertility clinics affiliated with Tabriz University of Medical Sciences. Data from the DII were computed using a validated 168-item semi-quantitative food frequency questionnaire. The free androgen index (FAI) was calculated as follows: (total testosterone (nmol/L)/SHBG (nmol/L)) × 100. The relationships between the BMI and DII and FAI, the Homeostasis model assessment of insulin resistance (HOMA-IR), the Homeostasis model assessment of β-cell function (HOMA-β), the quantitative insulin sensitivity check index (QUICKI), sex hormone binding globulin (SHBG), testosterone, fasting insulin (FI), and fasting blood sugar (FBS) were assessed using descriptive and analytical statistics. The general linear model was applied to adjust for confounders. The mean (standard deviation, SD) BMI and FAI among subjects were 26.27 (3.82) kg/m2 and 1.5 ± 1.5%, respectively. The median DII (range: -3.66 (most anti-inflammatory) to 4.31 (most pro-inflammatory)) was 0.75. Significant direct relationships were observed between the BMI and FAI (p < 0.001), HOMA-IR (p = 0.008), QUICKI (p = 0.002), testosterone (p < 0.001), FI (p = 0.017), FBS (p = 0.004), and Ferriman Gallwey score (p < 0.001). No significant associations were found between DII and the aforementioned biomarkers (p > 0.05). A normal BMI was associated with a significantly lower hirsutism score (β = -3.94, p = 0.003), fasting blood sugar (β = -10.02, p < 0.001), fasting insulin (β = -4.05, p = 0.042), HOMA-β (β = -1.20, p = 0.012), QUICKI (β = -0.19, p = 0.015), testosterone (β = -0.34, p < 0.001), and free androgen index (β = -0.96, p = 0.025) compared to an obese BMI after adjusting for confounders. No significant associations were observed for DII categories (median split) across any biomarkers or hirsutism. Adiposity (measured by BMI)-not dietary inflammation-was independently associated with key PCOS manifestations, demonstrating significant positive relationships with hyperandrogenism markers (FAI, testosterone), insulin resistance (HOMA-IR), and clinical hirsutism. A normal BMI was correlated with clinically meaningful reductions in metabolic-androgen parameters compared to obesity. Thus, weight loss and a generally healthy diet may need to be combined to impact PCOS features significantly.

BackgroundTo investigate the association between markers of insulin metabolism and carotid intima-media thickness(cIMT) among overweight and obese children and adolescents.MethodsA total of 378 children and adolescents aged from 6 to 13 years, with WHO body mass index Z-Scores ≥2 were enrolled in this study. We measured fasting serum insulin and glucose, conducted a homeostatic model assessment of insulin resistance(HOMA-IR), and calculated the quantitative insulin sensitivity check index(QUICKI). Carotid intima-media thickness was measured in the common carotid artery with high-resolution ultrasonography.ResultsThe study participants consisted of 198 boys and 180 girls with a mean(±SD) age of 9.3 ± 1.7 years, 18.3% being pre-pubertal. In boys, after controlling for confounders, a one-SD increase in fasting insulin and HOMA-IR were associated with 0.351 mm(P < 0.001) and 0.350 mm(P < 0.001) increases in cIMT, respectively. However, a one-SD increase in QUICKI was associated with a − 0.305 mm(P = 0.001) decrease in cIMT. When categorizing into tertiles, a one-SD increase in fasting insulin and HOMA-IR were associated with 87 and 81% increases in the odds of higher categories of cIMT(both P < 0.05). However, a one-SD increase in QUICKI was associated with 37% lower odds of higher categories of cIMT(P = 0.022). No significant associations were found among girls.ConclusionThis study demonstrated that insulin resistance and sensitivity markers were independent predictors of cIMT in overweight and obese boys, but not in girls, highlighting the importance of chronically elevated insulin levels for predisposing these boys to alterations in their vascular structure.

Although overt thyrotoxicosis is associated with reduced insulin sensitivity (IS), the effects of subclinical thyrotoxicosis (SCTox) (i.e., suppressed serum thyroid-stimulating hormone with free thyroxine and tri-iodothyronine within the reference range) on glucose metabolism are not clear. SCTox may be of endogenous origin or due to ingestion of supraphysiological amounts of thyroid hormone. Our hypotheses were that reduced IS is present in SCTox and that the degree of reduction differs between SCTox of endogenous and exogenous origin. The study population consisted of 125 premenopausal, normal-weight women, divided into four groups: exogenous SCTox due to L-T4 treatment for benign goiter or hypothyroidism (SCTox-ExogG) (n = 53), endogenous SCTox (SCTox-Endog) (n = 12), exogenous SCTox due to L-T4 treatment for differentiated thyroid cancer (SCTox-ExogDTC) (n = 20), and finally euthyroid women (C) (n = 40) as a control group. After a mixed meal challenge, glucose and insulin were determined at baseline and 120 minutes later. IS was assessed by homeostasis model assessment of insulin resistance (HOMA-IR) index, quantitative IS check index (QUICKI), and 2 hours IS Avignon's index amended by Aloulou for mixed food. Secretion by pancreatic B-cells was calculated by HOMA-B index. Comparison among groups was done by analysis of variance followed by Tukey test. Linear regression analysis of T3 versus HOMA-IR was calculated. IS was reduced in all types of SCTox when compared with C. All SCTox groups had significantly higher levels of insulin (baseline and postmeal) and HOMA-IR and lower values of QUICKI and Aloulou when compared with controls. SCTox-Endog, however, had higher baseline insulin levels and HOMA-IR and a lower QUICKI index than the rest of the SCTox groups. Although within the normal range, total T4, free T4, and T3 levels were also significantly higher in the SCTox groups than in euthyroids. In SCTox-Endog, T3/T4 ratio was increased above the rest of SCTox groups. A moderate linear relationship between T3 and HOMA-IR was found in the whole population. IR is associated with SCTox of either endogenous or exogenous origin. However, based on our findings of lower IS compared with the rest of the SCTox groups, the endogenous subclinical form might have an even larger metabolic impact.

The G-allele of the single nucleotide polymorphism (SNP) rs10830963 in MTNR1B (melatonin receptor 1B gene) is associated with type 2 diabetes mellitus and glucose levels in adults. The aim of this study was to analyze whether there is an allele-dosage effect on glucose metabolism in overweight children and to explore if changes in glucose metabolism in a lifestyle intervention do also depend on genotype. We genotyped rs10830963 in 1118 overweight children and adolescents [mean age 10.7 yr, mean body mass index (BMI) 27.8 kg/m2]; 340 of these individuals completed a 1-yr lifestyle intervention (mean age 10.7 yr, mean BMI 27.9 kg/m2). The degree of overweight [BMI-SDS (standard deviation score)], fasting insulin, glucose, homeostasis model assessment for insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index (QUICKI) were measured before and after intervention. We showed a significant relationship between rs10830963 and basal glucose levels [β:1.101, 95% confidence interval (CI) 0.316-1.886 mg/dL per risk allele; p = 0.006] by linear regression adjusted for age, age(2), and sex. There was no effect of the allele on insulin or indices of insulin resistance or sensitivity. After the 1-yr lifestyle intervention, we observed a significant reduction of BMI-SDS as well as an improvement of HOMA-IR and QUICKI, but no evidence for an association between rs10830963 genotype and changes of glucose levels. The G-allele of rs10830693 in the MTNR1B gene was significantly related to glucose levels, while an impact of this genetic variant on the changes in glucose metabolism in children participating in a lifestyle intervention was not observable.

This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to summarize the effect of vitamin D supplementation on glucose homeostasis parameters and lipid profiles in gestational diabetes (GDM) patients. We conducted an electronic systematic search of MEDLINE, and 4 other research databases from inception to August 2016, in addition to performing hand searches and consulting with experts in the field. The index of heterogeneity between studies was determined using Cochran (Q) and I-squared tests. Given the existing heterogeneity between studies, a fix or random effect model was performed to estimate the standardized mean difference (SMD) for each variable by using inverse variance method and Cohen statistics. Six randomized clinical trials (187 subjects and 184 controls) were included. The results showed that vitamin D supplementation significantly reduced the homeostasis model assessment of insulin resistance (HOMA-IR) [SMD -0.66; 95% confidence interval (CI), -1.14 to -0.18], homeostatic model assessment-B cell function (HOMA-B) (SMD -0.52; 95% CI, -0.79 to -0.25), LDL-cholesterol levels (SMD -0.33; 95% CI, -0.58 to -0.07), and significantly increased quantitative insulin sensitivity check index (QUICKI) (SMD 0.73; 95% CI, 0.26 to 1.20). We found no beneficial effect of vitamin D supplementation on fasting plasma glucose (FPG), insulin, HbA1c, total-, HDL-cholesterol, and triglycerides concentrations. In conclusion, this meta-analysis demonstrated that vitamin D supplementation may lead to an improvement in HOMA-IR, QUICKI, and LDL-cholesterol levels, but did not affect FPG, insulin, HbA1c, triglycerides, total- and HDL-cholesterol levels; however, vitamin D supplementation increased HOMA-B.