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Background: Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories. Materials and methods: This study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018–2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24–28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM. Results: GDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6–6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI. Conclusion: The present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM. [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women. This disorder affects 6–15% of women of childbearing age worldwide. It is diagnosed with hyperandrogenism, polycystic ovaries, and chronic anovulation with insulin resistance. This study aimed to assess the prevalence of insulin resistance (IR) in 4 phenotypes of PCOS, and its relationship with demographic, clinical, and paraclinical individual characteristics in a sample of Iranian PCOS patients. Methods: This particular cross-sectional investigation involved 160 female participants, aged between 18 and 45 years, who were receiving care at gynecology clinics in Urmia, northwestern Iran. All the participants had been diagnosed with PCOS and were categorized into one of four phenotypes. All the participants underwent clinical evaluations, paraclinical assessments, and ultrasound scans. IR was defined as HOMA-IR > 2.5. The statistical significance level was 0.05. Results: Among the 160 participants, the prevalences of the 4 phenotypes were: A: 83 (51.9%), B: 37 (23.1%), C: 21 (13.1%), and D: 19 (11.9%). IR was detected in 119 participants (74.4%); its rate was significantly different between the 4 phenotypes (p-value: 0.008) as A: 62 (74.7%), B: 34 (91.9%), C: 12 (57.1%), D: 11 (57.9%). Linear and logistic regression analyses were performed to control confounding factors. In linear regression, PCOS phenotype, classic phenotype (A&B), economic status, and Hb levels were significantly related to HOMA-IR; in logistic regression Hb levels, exercise, economic status, and PCOS phenotypes were significantly associated with insulin resistance. Conclusions: The most prevalent PCOS phenotype in this study was A. PCOS phenotypes were significantly related to insulin resistance and HOMA-IR, with the highest levels of insulin resistance and HOMA-IR observed in phenotype B. Determining the phenotype of PCOS may be helpful for better management of PCOS and its associated complications. However, further investigations are recommended in this regard. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes is one of the most common metabolic disorders during pregnancy. Some studies have reported the effect of vitamin D deficiency on the incidence of this disorder. Therefore, the purpose of the present study was to determine the effect of vitamin D supplementation on fasting blood glucose (FBG) levels, fasting blood insulin (FBI) levels and insulin resistance index (HOMA-IR) (primary outcomes) and symptoms of depression, musculoskeletal pain, frequency of gestational diabetes and the frequency of abortion (secondary outcomes). Methods: In this triple-blind randomized controlled trial, 88 pregnant women at 8–10 weeks of pregnancy who had the vitamin D of less than 30 ng/ml were randomly assigned to the vitamin D group (n = 44) and control group (n = 44) using block randomization. The vitamin D group received 4,000 units of vitamin D tablets daily and the control group received placebo tablets for 18 weeks. Independent t-test, Mann-Whitney U and ANCOVA tests were used to analyze the data. Results: After the intervention, there was no statistically significant difference between the two groups in terms of FBG (P = 0.850), FBI (P = 0.353), HOMA-IR (P = 0.632), mean score of depressive symptoms (P = 0.505), frequency of gestational diabetes (P = 0.187) and frequency of abortion (P = 1.000) and there was only a difference in terms of serum vitamin D level (P = 0.016) and musculoskeletal pain including knee pain (P = 0.025), ankle pain (P < 0.001) and leg pain (P < 0.001). Conclusion: Vitamin D could improve the musculoskeletal pain in pregnant women but couldn't decrease FBG, FBI, HOMA-IR, depression symptoms score, incidence of GDM and abortion. Trial registration: Iranian Registry of Clinical Trials (IRCT): IRCT20120718010324N59. Date of registration: 4/11/2020. URL: https://en.irct.ir/user/trial/50973/view; Date of first registration: 21/11/2020. [ABSTRACT FROM AUTHOR]

Background: Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance. Methods: The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18–75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI). Results: People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR. Conclusions: In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations. [ABSTRACT FROM AUTHOR]

Background: There is no study regarding developing a valid index to predict insulin-related disorders in the Iranian population based on their dietary habits and lifestyle. In the current study, we aimed to develop and validate insulinemic potential indices of diet and lifestyle in Iranian adults. Methods: In this cross-sectional study, we analysed data of 1063 men and women aged ≥ 25 years among participants of the examination three of Tehran lipid and glucose study (TLGS) (2006–2008). Dietary intakes were assessed using a valid semi-quantitative food frequency questionnaire. Dietary and lifestyle indices were developed using stepwise linear regression analysis based on dietary intakes, body mass index, and physical activity data. Fasting serum insulin concentration and homeostatic model assessment for insulin resistance (HOMA-IR) were used as biomarkers of hyperinsulinemia (HI) and insulin resistance (IR). Validation analyses were performed in examination four of TLGS. Results: We developed four indices related to insulin homeostasis, including the dietary index for HI (DIH), the dietary index for IR (DIR), the lifestyle index for HI (LIH), and the lifestyle index for IR (LIR). Based on multivariable-adjusted models, the relative values of the biomarker in subjects in the highest quartile of indices were 45% for LIH (95% CI 1.36–1.55, Ptrend < 0.001), 28% for DIR (95% CI 1.13–1.42, Ptrend = 0.019), and 51% for LIR (95% CI 1.41–1.61, Ptrend < 0.001), higher than those in the reference quartile, respectively. Conclusion: We designed and validated indices to determine the insulin potential of diet and lifestyle for the Iranian population, according to Iran's demographic and dietary intake characteristics. [ABSTRACT FROM AUTHOR]

Background: To examine the association between changes in fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), and insulin-glucose ratio (IGR) levels, over approximately 3 years with incident hypertension. Methods: A total of 2814 Iranian participants (1123 men) without hypertension and known diabetes at baseline and the first examination were followed for a median of 6.32 years. The associations between quartiles of changes in fasting insulin and IR indices with incident hypertension were assessed using multivariate Cox proportional hazard regression analyses with first quartile as reference. The models were adjusted for baseline values of insulin or each IR index, and age, sex, smoking, physical activity, educational levels, marital status, history of cardiovascular diseases, baseline levels of systolic and diastolic blood pressures, estimated glomerular filtration rate, triglycerides, total cholesterol, high-density lipoprotein cholesterol, fasting plasma glucose (only for insulin change) and both body mass index (BMI) per se, and its change. Akaike's information criteria (AIC) was applied as indicator for goodness of fit of each predictive model. The discrimination ability of models was calculated using the Harrell's C statistic. Results: During the study, 594 incident cases of hypertension (253 men) were identified. The 4th quartile of changes in insulin, HOMA-IR, and IGR showed hazard ratios (95% confidence interval) of 1.31 (1.01–1.69), 1.18 (0.92–1.52), and 1.53 (1.18–1.98) for hypertension, respectively, in fully-adjusted models. Changes in fasting insulin levels and IR indices showed significant increasing trends for incident hypertension, moving from 1st to 4th quartiles (all P-values < 0.05). Focusing on model fitness, no superiority was found between changes in fasting insulin, HOMA-IR, and IGR to predict incident hypertension. The discriminatory powers of changes in fasting insulin and IR indices as assessed by C index were similar (i.e. about 80%). Conclusion: Changes in fasting insulin and IR indices were significantly associated with developing hypertension among normotensive population even after considering BMI changes. [ABSTRACT FROM AUTHOR]

Objectives: This study investigated the effects of levothyroxine replacement therapy on insulin resistance, lipid profile, and thyroid function in patients with untreated primary hypothyroidism. 105 patients with hypothyroidism with indication for levothyroxine replacement were enrolled in the present study. Insulin, fasting blood glucose and lipid profile were assessed at the beginning of diagnosis and three months after levothyroxine replacement. Insulin resistance was calculated by hemostasis model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI)., Results: Our data revealed a significant reduction in body mass index (27.18 ± 4.27 versus 26.81 ± 4.18 kg/m2, p = 0.028), cholesterol (199.79 ± 37.61 versus 178.10 ± 32.25 mg/dl, p < 0.001), triglyceride (160.41 ± 71.86 versus 146 ± 61.11 mg/dl, p = 0.012), low density lipoprotein-cholesterol (123.54 ± 30.7 versus 107.08 ± 26.98 mg/dl, p < 0.001), fasting insulin (8.91 ± 3.92 versus 8.05 ± 2.65 mIU/l, p < 0.001), and thyroid stimulating hormone (47.47 ± 3.4 versus 2.22 ± 1.84 µIU/ml, p < 0.001) levels before and after drug intervention. However, no statistical differences were observed in HOMA-IR, QUICKI, and high density lipoprotein-cholesterol. In conclusion, in patients with untreated primary hypothyroidism, levothyroxine replacement therapy based on HOMA-IR and QUICKI did not improve insulin resistance; however, lipid profile was significantly improved following levothyroxine administration., Trial Registration: This study was registered in the Iranian Registry of Clinical Trials (IRCT) with ID number: IRCT20130610013612N10 on the date 2019-09-02., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Abstract: We assessed the threshold of homeostasis model assessment (HOMA) values to determine insulin resistance (IR) in a sample of Iranians and examined the associations of IR with metabolic syndrome (MetS). Study comprised 1327 non-diabetic and non-hypertensive subjects (438 men, 838 women; aged 20–77 years) incurred in four different locations (Tehran, Iran), 2005–2008.Lower limit of the top quintile of HOMA values in subjects without any metabolic abnormality was considered as the threshold of IR. This threshold was 1.8 (1.7 men; 1.8 women). Overall, 41.1% (36.3% men; 41.5% women) of subjects had IR. HOMA cut-off to determine MetS was 1.95 for ATPIII definition, and 1.85 for IDF. IR associated MetS (ATPIII: odds ratio (OR)=2.9, 95% CI=2.2–3.9, p <0.05; IDF: OR=2.94, 95% CI: 2.3–3.8, p <0.05). Sensitivity of MetS to detect IR was 22.4% for IDF and 36.2% for ATPIII criteria. In multivariate models, HOMA was predicted by waist circumference, and inversely by age and serum HDL-cholesterol. In this study, the cut point of HOMA to detect IR was lower than other populations. IR is an unyielding correlate of MetS; but definitions of MetS are insensitive measures of IR in our population. [Copyright &y& Elsevier]

Objectives: Insulin resistance is the most common metabolic change associated with obesity. The present study aimed to investigate the relationship between insulin resistance and body composition especially adipose tissue in a randomized Tehrani population., Methods: This study used data of 2,160 individuals registered in a cross-sectional study on were randomly selected from among subjects who were referred to nutrition counseling clinic in Tehran, from April 2016 to September 2017. Insulin resistance was calculated by homeostasis model assessment formula. The odds ratio (95% CI) was calculated using logistic regression models., Results: The mean age of the men was 39 (±10) and women were 41 (±11) (the age ranged from 20 to 50 years). The risk of increased HOMA-IR was 1.03 (95% CI: 1.01-1.04) for an increase in one percent of Body fat, and 1.03 (95% CI: 1.00-1.05) for an increase in one percent of Trunk fat. Moreover, the odds ratio of FBS for an increase in one unit of Body fat percent and Trunk fat percent increased by 1.05 (adjusted odds ratio [95% CI: 1.03, 1.06]) and 1.05 (95% CI: 1.02, 1.08). Also, the risk of increased Fasting Insulin was 1.05 (95% CI: 1.03-1.07) for an increase in one unit of Body fat percent, and 1.05 (95% CI: 1.02-1.08) for an increase in one unit of Trunk fat percent., Conclusions: The findings of the present study showed that there was a significant relationship between HOMA-IR, Fasting blood sugar, Fasting Insulin, and 2 h Insulin with percent of Body fat, percent of Trunk fat., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)