Sagittal abdominal diameter resembles waist circumference as a surrogate marker of insulin resistance in adolescents-Brazilian Metabolic Syndrome Study

Association of physical activity and sitting with metabolic syndrome and hyperglycemic clamp parameters in adolescents - BRAMS pediatric study

Introduction

Obesity and metabolic syndrome (MetS) have immediate and long-term consequences on adolescent health and well-being. Among the available treatments for MetS in adolescents, behavioral interventions such as increasing physical activity (PA) are preferred. This study aimed to investigate the association of PA and sitting time with MetS and a complete set of metabolic health parameters.

Methods

Data from the Pediatric Brazilian Metabolic Syndrome Study (BRAMS-P), a cross-sectional multicenter study conducted using a convenience sample of 448 Brazilian adolescents (10y-19y), were used. Sociodemographic and lifestyle information were collected using a standardized questionnaire. Daily PA and sitting time were estimated from the International PA Questionnaire. Anthropometric parameters, body composition, and blood pressure were measured by trained researchers. Blood lipids, uric acid, hepatic enzymes, creatinine, glycated hemoglobin, glucose, and insulin were measured in fasting blood samples, and the Homeostasis Model Assessment for Insulin Resistance was calculated. A subsample of 57 adolescents underwent the hyperglycemic clamp protocol.

Results

The odds for metabolic syndrome were higher among adolescents who spent >8h sitting (OR (95%CI)=2.11 (1.02 - 4.38)), but not in those classified as active (OR (95%CI)=0.98 (0.42 - 2.26)). Adolescents who spent more time sitting had higher BMI, waist circumference, sagittal abdominal diameter, neck circumference, percentage of body fat, and worse blood lipid profile. The insulin sensitivity index was moderately and positively correlated with moderate-to-high PA in minutes per day (rho=0.29; p=0.047).

Conclusion

Time spent sitting was associated with worse metabolic parameters and must be restricted in favor of adolescent health. Regular PA is associated with improved insulin sensitivity and may be encouraged not only in adolescents with obesity or metabolic disorders but also to prevent adverse metabolic outcomes in normal-weight adolescents.

Relationship between Sitting Time and Insulin Resistance in 6931 U.S. Adults: The Mediating Role of Abdominal Adiposity

This cross-sectional investigation examined the relationship between sitting time and insulin resistance in 6931 U.S. adults. The mediating effects of several covariates were evaluated. Self-reported sitting time, measured in minutes per day, was the exposure variable. Insulin resistance (IR), indexed using the natural log of the homeostatic model assessment of insulin resistance (L-HOMA-IR), was the outcome variable. This study used data collected from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Results showed a strong, positive, dose-response association between sitting time and insulin resistance after adjusting for age, sex, race, and year of assessment (F = 12.6, p < 0.0001). Across the sitting time tertiles (low, moderate, and high), the L-HOMA-IR means (±SE) each differed from each other (0.37 ± 0.008, 0.40 ± 0.012, and 0.43 ± 0.012). Further controlling for cigarette smoking and physical activity did not alter the significance of the relationship. Adding body mass index (BMI) to the demographic covariates weakened the relationship, but it remained significant. However, the association was no longer significant after adjusting for the demographic covariates and waist circumference (F = 1.1, p = 0.3349). None of the L-HOMA-IR means (±SE) differed from each other (0.40 ± 0.007, 0.41 ± 0.009, and 0.41 ± 0.008). Overall, waist circumference was a powerful mediating variable between sitting time and insulin resistance. Apparently, time spent sitting is a powerful predictor of IR. However, much of the association between sitting time and IR is a function of differences in waist size. As a strong measure of abdominal adiposity and a significant predictor of multiple metabolic diseases, managing waist size is a health practice to consider when insulin resistance is a concern.

The threshold value for identifying insulin resistance (HOMA-IR) in an admixed adolescent population: A hyperglycemic clamp validated study

Objective

To validate the homeostasis model assessment (HOMA) of insulin resistance (IR) as a surrogate to the hyperglycemic clamp to measure IR in both pubertal and postpubertal adolescents, and determine the HOMA-IR cutoff values for detecting IR in both pubertal stages.

Subjects and methods

The study sample comprised 80 adolescents of both sexes (aged 10-18 years; 37 pubertal), in which IR was assessed with the HOMA-IR and the hyperglycemic clamp.

Results

In the multivariable linear regression analysis, adjusted for sex, age, and waist circumference, the HOMA-IR was independently and negatively associated with the clamp-derived insulin sensitivity index in both pubertal (unstandardized coefficient - B = -0.087, 95% confidence interval [CI] = -0.135 to -0.040) and postpubertal (B = -0.101, 95% CI, -0.145 to -0.058) adolescents. Bland-Altman plots showed agreement between the predicted insulin sensitivity index and measured clamp-derived insulin sensitivity index in both pubertal stages (mean =-0.00 for pubertal and postpubertal); all P > 0.05. The HOMA-IR showed a good discriminatory power for detecting IR with an area under the receiver operator characteristic curve of 0.870 (95% CI, 0.718-0.957) in pubertal and 0.861 (95% CI, 0.721-0.947) in postpubertal adolescents; all P < 0.001. The optimal cutoff values of the HOMA-IR for detecting IR were > 3.22 (sensitivity, 85.7; 95% CI, 57.2-98.2; specificity, 82.6; 95% CI, 61.2-95.0) for pubertal and > 2.91 (sensitivity, 63.6; 95% CI, 30.8-89.1, specificity, 93.7; 95%CI, 79.2-99.2) for postpubertal adolescents.

Conclusion

The threshold value of the HOMA-IR for identifying insulin resistance was > 3.22 for pubertal and > 2.91 for postpubertal adolescents.

Anthropometric Indicators of Body Composition Associated With Lipid and Glycemic Profiles in Overweight Brazilian Children and Adolescents From 2008 to 2020

Background

Anthropometric indicators have been used to predict health problems. The objective was to determine which indicators present better correlation with dyslipidemia, hyperglycemia and peripheral insulin resistance, as well as the cutoff points capable of predicting lipid and glycemic alterations in Brazilian children and adolescents.

Methods

A cross-sectional study conducted with 568 overweight individuals, aged between 5 and 18 years, living in Southeast and South Brazilian regions, submitted to anthropometric and body composition evaluation by bioimpedance, in addition to fasting laboratory tests [total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), fasting glycemia, and homeostasis model assessment–insulin resistance (HOMA-IR)]. Pearson's correlation was used to evaluate the association between anthropometric indicators and serum biomarkers. The ROC curve with Youden's J index was used to suggest anthropometric cutoff points with better ability to predict or rule out lipid and glycemic changes.

Results

Cutoff points obtained for the z-score of body mass index (BMI), waist circumference (WC), and waist circumference for height (WC/H) showed high specificity (52 to 87%) and low sensitivity (23 to 59%), indicating greater ability to exclude changes in HDL-c, TG, and HOMA-IR levels. Cutoff points suggested for BMI ranged from +1.86 to +2.20 z-score. WC cutoff points ranged from +1.29 to +1.72, and, for the WC/H index, from +1.21 to +1.25. It was suggested the use of the following cutoff points to rule out changes in HDL-c, TG, and HOMA-IR values in clinical practice: BMI < z-score +2 and WC/H < z-score +1.29. In body fat percentage (BFP) analyses, the cutoff point < of 34% may be able to rule out changes in HDL-c (specificity of 70%), while the cutoff point > 36.6% may be able to predict changes in the HOMA-IR index (sensitivity of 76%).

Conclusion

It is not yet possible to state which anthropometric parameter has the best correlation with lipid and glycemic alterations in overweight children and adolescents. We suggest considering BMI, WC, and WC/H cutoff points together to rule out changes in HDL-c, TG, and HOMA-IR, and use the BFP cutoff point to predict changes in HOMA-IR.

Prolactin Is Associated With Insulin Resistance and Beta-Cell Dysfunction in Infertile Women With Polycystic Ovary Syndrome

BACKGROUND

Our study aimed to investigate if serum prolactin (PRL) levels associated with insulin resistance and beta-cell dysfunction in infertile patients with polycystic ovary syndrome (PCOS).

METHODS

This was a retrospective cross-sectional study performed in the reproductive medicine center of the first affiliated hospital of Wenzhou Medical University. From January 2007 to August 2018, a total of 792 PCOS and 700 non-PCOS infertile women were included. All patients' prolactin levels were in the normal range. PCOS was diagnosed according to the Rotterdam Criteria. Anthropometric parameters, blood pressure, serum prolactin levels, sex hormones, fasting lipids, fasting plasma glucose (FPG), fasting insulin (FINS) and hepatic biological parameters were measured in all subjects.

RESULTS

Serum prolactin levels in PCOS women were significantly decreased compared with levels in non-PCOS women after adjusting for age and BMI (P < 0.05). Moreover, we found that prolactin levels were positively associated with high-density lipoprotein cholesterol (HDL-C) and negatively associated with age, BMI, waist circumference (WC), hip circumference (HC), luteinizing hormone/follicle stimulating hormone (LH/FSH), estradiol (E₂), FINS, homeostasis model assessment of insulin resistance (HOMA-IR), homeostasis model assessment of β (HOMA-β), triglyceride (TG) and alanine aminotransferase (ALT) (P < 0.05). After adjusting for age and BMI, multiple linear regression analysis revealed that LH, LH/FSH, E₂, FINS, HOMA-IR, and HOMA-β were negatively associated with serum PRL (P < 0.05).

CONCLUSIONS

Low serum PRL levels within the normal range associates with a higher incidence of insulin resistance and beta-cell dysfunction in infertile women with PCOS.

Alternative waist-to-height ratios associated with risk biomarkers in youth with diabetes: comparative models in the SEARCH for Diabetes in Youth Study

BACKGROUND/OBJECTIVES

The waist-to-height ratio (WHtR) estimates cardiometabolic risk in youth without need for growth charts by sex and age. Questions remain about whether waist circumference measured per protocol of the National Health and Nutrition Examination Survey (WNHAHtR) or World Health Organization (WWHOHtR) can better predict blood pressures and lipid parameters in youth.

PARTICIPANTS/METHODS

WHtR was measured under both anthropometric protocols among participants in the SEARCH Study, who were recently diagnosed with diabetes (ages 5-19 years; N = 2 773). Biomarkers were documented concurrently with baseline anthropometry and again ~7 years later (ages 10-30 years; N = 1 712). For prediction of continuous biomarker outcomes, baseline WNHAHtR or WWHOHtR entered semiparametric regression models employing restricted cubic splines. To predict binary biomarkers (high-risk group defined as the most adverse quartile) linear WNHAHtR or WWHOHtR terms entered logistic models. Model covariates included demographic characteristics, pertinent medication use, and (for prospective predictions) the follow-up time since baseline. We used measures of model fit, including the adjusted-R2 and the area under the receiver operator curves (AUC) to compare WNHAHtR and WWHOHtR.

RESULTS

For the concurrent biomarkers, the proportion of variation in each outcome explained by full regression models ranged from 23 to 46%; for the prospective biomarkers, the proportions varied from 11 to 30%. Nonlinear relationships were recognized with the lipid outcomes, both at baseline and at follow-up. In full logistic models, the AUCs ranged from 0.75 (diastolic pressure) to 0.85 (systolic pressure) at baseline, and from 0.69 (triglycerides) to 0.78 (systolic pressure) at the prospective follow-up. To predict baseline elevations of the triglycerides/HDL cholesterol ratio, the AUC was 0.816 for WWHOHtR compared with 0.810 for WNHAHtR (p = 0.003), but otherwise comparisons between alternative WHtR protocols were not significantly different.

CONCLUSIONS

Among youth with recently diagnosed diabetes, measurements of WHtR by either waist circumference protocol similarly helped estimate current and prospective cardiometabolic risk biomarkers.

Homeostatic model assessment of adiponectin (HOMA-Adiponectin) as a surrogate measure of insulin resistance in adolescents: Comparison with the hyperglycaemic clamp and homeostatic model assessment of insulin resistance

BACKGROUND

Studies on adults have reported inverse association between the homeostatic model assessment (HOMA) of adiponectin (HOMA-Adiponectin) and the insulin resistance assessed by the glucose clamp technique. To our knowledge, in the pediatric population this association has not been previously investigated.

OBJECTIVES

To evaluate the association between the HOMA-Adiponectin and the insulin resistance assessed by the glucose clamp technique in adolescents, and to compare the accuracy of HOMA-Adiponectin and HOMA-insulin resistance (HOMA-IR) for identifying insulin resistance.

METHODS

This was a cross-sectional study of 56 adolescents (aged 10-18 years). Insulin resistance was assessed using the HOMA-IR, HOMA-Adiponectin and the hyperglycaemic clamp technique. The clamp-derived insulin sensitivity index, HOMA-Adiponectin, and HOMA-IR were log-transformed to get closer to a normal distribution before analysis.

RESULTS

In the multivariable linear regression analysis controlling for sex and Tanner stage, HOMA-Adiponectin was inversely associated with the clamp-derived insulin sensitivity index (unstandardized coefficient [B] = -0.441; P < 0.001). After additional adjustment for waist circumference-to-height ratio, this association remained significant (B = -0.349; P = < 0.001). Similar results were observed when HOMA-IR replaced HOMA-Adiponectin in the model (B = -1.049 and B = -0.968 after additional adjustment for waist circumference-to-height ratio); all P < 0.001. The area under the receiver operating characteristic curve for predicting insulin resistance was 0.712 (P = 0.02) for HOMA-Adiponectin and 0.859 (P < 0.0001) HOMA-IR.

CONCLUSIONS

The HOMA-Adiponectin was independently associated with insulin resistance and exhibited a good discriminatory power for predicting it. However, it did not show superiority over HOMA-IR in the diagnostic accuracy.