scholarly journals Body composition and risk for metabolic alterations in female adolescents

2014 ◽  
Vol 32 (2) ◽  
pp. 207-215 ◽  
Author(s):  
Eliane Rodrigues de Faria ◽  
Cristiana Araújo Gontijo ◽  
Sylvia do Carmo C. Franceschini ◽  
Maria do Carmo G. Peluzio ◽  
Silvia Eloiza Priore
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Body Composition ◽  
Density Lipoprotein ◽  
Female Adolescents ◽  
Fasting Insulin ◽  
Height Ratio ◽  
Metabolic Alterations ◽  
Waist To Height Ratio ◽  
Body Fat Percent

OBJECTIVE: To study anthropometrical and body composition variables as predictors of risk for metabolic alterations and metabolic syndrome in female adolescents.METHODS: Biochemical, clinical and corporal composition data of 100 adolescents from 14 to 17 years old, who attended public schools in Viçosa, Southeastern Brazil, were collected.RESULTS: Regarding nutritional status, 83, 11 and 6% showed eutrophia, overweight/obesity and low weight, respectively, and 61% presented high body fat percent. Total cholesterol presented the highest percentage of inadequacy (57%), followed by high-density lipoprotein (HDL - 50%), low-density lipoprotein (LDL - 47%) and triacylglycerol (22%). Inadequacy was observed in 11, 9, 3 and 4% in relation to insulin resistance, fasting insulin, blood pressure and glycemia, respectively. The highest values of the fasting insulin and the Homeostasis Model Assessment-Insulin Resistance(HOMA-IR) were verified at the highest quartiles of body mass index (BMI), waist perimeter, waist-to-height ratio and body fat percent. Body mass index, waist perimeter, and waist-to-height ratio were the better predictors for high levels of HOMA-IR, blood glucose and fasting insulin. Waist-to-hip ratio was associated to arterial hypertension diagnosis. All body composition variables were effective in metabolic syndrome diagnosis.CONCLUSIONS: Waist perimeter, BMI and waist-to-height ratio showed to be good predictors for metabolic alterations in female adolescents and then should be used together for the nutritional assessment in this age range.

scholarly journals A waist-to-height ratio of 0.54 is a good predictor of metabolic syndrome in 16-year-old male and female adolescents

2018 ◽  
Vol 85 (3) ◽  
pp. 269-274 ◽  
Author(s):  
Fabian Vasquez ◽  
Paulina Correa-Burrows ◽  
Estela Blanco ◽  
Sheila Gahagan ◽  
Raquel Burrows
Keyword(s):  
Metabolic Syndrome ◽  
Good Predictor ◽  
Female Adolescents ◽  
Height Ratio ◽  
Male And Female ◽  
Waist To Height Ratio

scholarly journals Probability and Body Composition of Metabolic Syndrome in Young Adults: Use of the Bayes Theorem as Diagnostic Evidence of the Waist-to-Height Ratio

Stats ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 21-31 ◽  
Author(s):  
Ashuin Kammar ◽  
María Hernández-Hernández ◽  
Patricia López-Moreno ◽  
Angélica Ortíz-Bueno ◽  
María Martínez-Montaño
Keyword(s):  
Metabolic Syndrome ◽  
Young Adults ◽  
Body Composition ◽  
Conditional Probability ◽  
Adult Population ◽  
Bayes Theorem ◽  
Height Ratio ◽  
Anthropometric Parameters ◽  
Anthropometric Parameter ◽  
Waist To Height Ratio

Metabolic syndrome (MS) directly increases the risk of cardiovascular diseases. Childhood and adulthood have been the most studied in MS, leaving aside the young adult population. This study aimed to compare the epidemiological probabilities between MS and different anthropometric parameters of body composition. Using a cross-sectional study with the sample of 1351 young adults, different body composition parameters were obtained such as Waist Circumference (WC), Body Mass Index (BMI), Body Fat% (BF%), Waist-to-Height Ratio (WHtR), and Waist-Hip Ratio. The Bayes Theorem was applied to estimate the conditional probability that any subject developed MS with an altered anthropometric parameter of body composition. Areas under receiver operating characteristic curves (AUCs) and adjusted odds ratios of the five parameters were analyzed in their optimal cutoffs. The conditional probability of developing MS with an altered anthropometric parameter was 17% in WHtR, WC, and Waist-hip R. Furthermore, body composition parameters were adjusted by age, BMI, and gender. Only WHtR (OR = 9.43, CI = 3.4–26.13, p < 0.0001), and BF% (OR = 3.18, CI = 1.42–7.13, p = 0.005) were significant, and the sensitivity (84%) and the AUCs (86%) was higher in WHtR than other parameters. In young adults, the WHtR was the best predictor of metabolic syndrome.

scholarly journals Insulin Resistance of Normal Weight Central Obese Adolescents in Korea Stratified by Waist to Height Ratio: Results from the Korea National Health and Nutrition Examination Surveys 2008–2010

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Won Kyoung Cho ◽  
Hyojin Kim ◽  
Hyun Young Lee ◽  
Kyung Do Han ◽  
Yeon Jin Jeon ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
National Health ◽  
Central Obesity ◽  
Normal Weight ◽  
Female Adolescents ◽  
Height Ratio ◽  
Health And Nutrition ◽  
High Insulin ◽  
Waist To Height Ratio ◽  
Wbc Count

Background. To evaluate insulin resistance of normal weight central obese 13–18-year-old male and female adolescents stratified by waist to height ratio (WHR).Methods. Data were obtained from the Korea National Health and Nutrition Examination Survey (K-NHANES) conducted during 2008–2010. Central obesity was defined as that in the upper quartile of age and sex specific WHR. Subjects were classified into no central obesity normal weight (NW), central obesity normal weight (CONW), no central obesity overweight (OW), and central obesity overweight (COOW).Results. The prevalence of CONW was 9.6% (83/832) in female and 7.0% (61/909) in male. CONW showed higher levels of insulin (P<0.006), HOMA-IR (P<0.006), and ALT (P<0.001) than NW in female. CONW had higher levels of insulin (P<0.0001), HOMA-IR (P<0.0001), and WBC count (P<0.021) and lower level of HDL (P<0.0001) than NW in male. WHR and BMI had similar significant correlations with MS components. CONW showed 2.5 times (95% confidence interval, 1.21–5.00) more likelihood to have high insulin resistance than NW in male.Conclusions. Screening for central obesity using WHR in clinical setting is recommended.

scholarly journals The Association of Metabolic Syndrome Components with Anthropometric Measurements

2021 ◽  
Vol 10 (2) ◽  
pp. 65-73
Author(s):  
Cagla Ozdemir ◽  
Cenk Aypak ◽  
Suleyman Gorpelioglu
Keyword(s):  
Metabolic Syndrome ◽  
Density Lipoprotein ◽  
Neck Circumference ◽  
Anthropometric Measurements ◽  
Hip Circumference ◽  
Height Ratio ◽  
Waist Hip Ratio ◽  
Arm Circumference ◽  
Waist To Height Ratio ◽  
Metabolic Syndrome Components

Aim: This study aims to research the association of metabolic syndrome components with anthropometric measurements like arm circumference, neck circumference, hip circumference, waist-hip ratio, and waist-to-height ratio, which are applied rarely. Methods: This cross-sectional study was conducted with 292 patients in November-December 2019. The arm circumference, neck circumference, waist circumference, hip circumference, waist-hip ratio, waist-to-height ratio, and body mass index measurements of the patients were made. Glucose, high-density lipoprotein, low-density lipoprotein, systolic, and diastolic blood pressure measurements were also recorded. The association between metabolic syndrome components and anthropometric measurements was analyzed. Results: Metabolic syndrome is diagnosed in 32.8% of the participants. According to body mass index, 18.6% of the patients were normal, 34.2% were overweight, and 47.2% were obese. There was a significant difference between the patients with and without metabolic syndrome in terms of laboratory parameters, blood pressure values, and anthropometric measurements. In the diagnosis of metabolic syndrome, optimal cut-off values for arm circumference, neck circumference, hip circumference, waist-hip ratio, and waist-to-height ratio were determined as 31.75 (AUC=0.703), 34.85 (AUC=0.763), 113.75 (AUC=0.757), 0.90 (AUC=0.701), 0.61 (AUC=0.769) for females while they were 35.75 (AUC=0.573), 39.75 (AUC=0.795), 111.5 (AUC=0.607), 0.96 (AUC=0.888), 0.61 (AUC=0.888) for males respectively. Conclusion: A significant correlation was detected between arm circumference, neck circumference, hip circumference, waist-hip ratio, and waist-to-height ratio, and metabolic syndrome components. However, low-density lipoprotein was not correlated with neck circumference and high-density lipoprotein with waist-to-height ratio. Keywords: metabolic syndrome, anthropometric measurement, body mass index, obesity, lipid profile

scholarly journals Waist-to-height ratio as a clinical predictor for cardiovascular risks and insulin resistance in children and adolescents with exogenous obesity

2021 ◽  
Vol 69 (1) ◽  
Author(s):  
Hend Soliman ◽  
Samah Ahmed ◽  
Amany Ibrahim
Keyword(s):  
Insulin Resistance ◽  
Cardiovascular Risk ◽  
Lipid Profile ◽  
Children And Adolescents ◽  
Density Lipoprotein ◽  
Model Assessment ◽  
Height Ratio ◽  
Clinical Predictor ◽  
Waist To Height Ratio ◽  
Risk Ratios

Abstract Background Obesity is one of the most challenging clinical syndromes associated with deleterious health problems. Waist-to-height ratio (WHtR), a newer index for abdominal fat assessment, can be a superior tool in the evaluation of cardiometabolic risk. This study aimed to determine the relation between WHtR and lipid cardiovascular risk ratios and insulin resistance (IR) in children and adolescents with exogenous obesity. Results This analytical cross-sectional study included 80 children and adolescents with exogenous obesity, compared to 80 age- and sex-matched healthy non-overweight non-obese controls. Fasting lipid profile (total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL) and low-density lipoprotein (LDL)), fasting insulin, and fasting blood glucose were done and lipoprotein risk ratios were calculated; TC/HDL, LDL/HDL, non-HDL/HDL, and TG/HDL). In addition, homeostatic model assessment for IR (HOMA IR), triglyceride glucose index (TyG), TyG-BMI, and TyG-WC were calculated. The study group included 55 (34.4%) males and 105 (65.6%) females with a mean age of 13.6 ± 2.22 years. Obese group had significantly higher TC, TG, LDL, non-HDL, LDL/HDL, TC/HDL, non-HDL/HDL, and TG/HDL, with significantly lower HDL. In addition, they had significantly higher FBG, HOMA IR, TyG, TyG-BMI, and TyG-WC indices compared to the control group. There were statistically significant correlations between WHtR and lipid profile, lipid risk ratios and indices of IR. WHtR was found to be an independent predictor of IR by linear regression analysis. Conclusion WHtR can be an excellent, easy, and reliable clinical predictor for cardiovascular risk and IR in children and adolescents with exogenous obesity.

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