Influence of Biochemical and Anthropometric Factors on the Presence of Insulin Resistance in Adolescents

González‐Jiménez, Emilio; Alonso, Miguel Ángel Montero; Padez, Cristina; García-García, Carmen J.; Perona, Javier S.

doi:10.1177/1099800416648207

Cited by 11 publications

(12 citation statements)

References 35 publications

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“…This underscores the importance of BMI and WC for predicting IR and is in accordance with our study results. Results of a cross-sectional study led by González-Jiménez et al showed that subjects with abnormal HOMA-IR values had significantly higher BMI, body fat content, and WC, and multivariate logistic regression analysis showed the highest OR for BMI, [ 19 ] which is consistent with our study results. Results from a study of Korean high school students showed that HOMA-IR was significantly associated with BMI and WC in both sexes.…”

Section: Discussionsupporting

confidence: 92%

“…Previous studies have reported the correlation between the obesity index and IR, but some results have been inconsistent. [ 16 – 19 ] Samouda et al [ 16 ] demonstrated that adding the body fat distribution score to the BMI can improve the prediction of cardiometabolic, inflammatory, and adipokines profiles. This underscores the importance of BMI and WC for predicting IR and is in accordance with our study results.…”

Section: Discussionmentioning

confidence: 99%

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Body mass index and waist circumference are better predictors of insulin resistance than total body fat percentage in middle-aged and elderly Taiwanese

Cheng¹,

Tsao

Tzeng

et al. 2017

Medicine

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The incidence of diabetes mellitus is rising worldwide, and prediabetic screening for insulin resistance (IR) has become ever more essential. This study aimed to investigate whether body mass index (BMI), waist circumference (WC), or body fat percentage (BF%) could be a better predictor of IR in a middle-aged and elderly population. In this cross-sectional, community-based study, 394 individuals (97 with IR and 297 without IR) were enrolled in the analysis. IR was measured by homeostasis model assessment (HOMA-IR), and subjects with HOMA-IR value ≧75th percentile were defined as being IR. Associations between IR and BMI, WC and BF% were evaluated by t test, chi square, Pearson correlation, logistic regression, and receiver operating characteristic (ROC) curves. A total of 394 community-dwelling, middle-aged, and elderly persons were enrolled; 138 (35%) were male, and 256 were female (65%). The mean age was 64.41 ± 8.46 years. A significant association was identified between BMI, WC, BF%, and IR, with Pearson correlation coefficients of 0.437 (P < .001), 0.412 (P < .001), and 0.361 (P < .001), respectively. Multivariate logistic regression revealed BMI (OR = 1.31; 95% CI = 1.20–1.42), WC (OR = 1.13; 95% CI = 1.08–1.17), and BF% (OR = 1.17; 95% CI = 1.11–1.23) to be independent predictors of IR. The area under curves of BMI and WC, 0.749 and 0.745 respectively, are greater than that of BF% 0.687. BMI and WC were more strongly associated with IR than was BF%. Excess body weight and body fat distribution were more important than total body fat in predicting IR.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Body mass index and waist circumference are better predictors of insulin resistance than total body fat percentage in middle-aged and elderly Taiwanese

Cheng¹,

Tsao

Tzeng

et al. 2017

Medicine

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“…Thus, our mediation analysis reinforces the relevance of adiposity as an important indicator of IR and diabetes risks. We also highlight that some measures of adiposity are considered simple, non-invasive, and low-cost methods that can be used to classify children, adolescents, and adults at risk of developing metabolic disorders, including IR and diabetes (Aristizabal et al 2015;Gonz alez-Jim enez et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Relationship between insulin resistance and adipocytokines: the mediator role of adiposity in children

Brand

Gaya

Dias

et al. 2020

Annals of Human Biology

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Background: Leptin and adiponectin interact with each other in the modulation of obesity and insulin resistance (IR) and it is also important to consider the role of cardiorespiratory and muscular fitness in these relationships. Aim: To analyse the relationship between IR with adipocytokines in children, and to test the mediation effect of %BF (percentage of body fat) in the association of IR with leptin, adiponectin, and L/A ratio. Subjects and methods: This cross-sectional study comprised a sample of 150 schoolchildren, aged 6-11 years, from school in Porto Alegre, Brazil. The following variables were evaluated: cardiorespiratory fitness (CRF), muscular fitness (MF), percentage of body fat (%BF), and biochemical variables (leptin, adiponectin, glucose, and insulin). Results: IR was associated with leptin and L/A ratio, after adjustments for age, sex, sexual maturation, and CRF. When adjusted for age, sex, sexual maturation, and MF, an association was found between IR with leptin and L/A ratio. Moreover, %BF was a mediator in the association between IR and leptin, as well as IR and L/A ratio, explaining 54% and 57% of these associations, respectively. Conclusion: Leptin and L/A ratio are positively associated with IR after adjustments. Also, %BF is a mediator in the associations between IR and leptin and L/A ratio.

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“…The importance of waist circumference in defining obesity instead of BMI-SDS is also emphasized in recent literature [ 8 , 23 , 29 , 30 ]. In the studied population, only in adolescents, waist circumference was associated with IR.…”

Section: Discussionmentioning

confidence: 99%

Predictors of Insulin Resistance in Children versus Adolescents with Obesity

et al. 2017

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Introduction Obesity is a risk factor to develop metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM). Insulin resistance (IR) plays a major part in both. With increasing incidence of childhood obesity, this retrospective study aimed to identify predictors of IR in children/adolescents with obesity to optimize screening for IR. Method Patients aged ≥ 2–≤ 18 years with obesity (BMI-SDS > 2.3) were included. IR was defined as HOMA-IR ≥ 3.4, and MetS if ≥3 of the following criteria were present: waist circumference and blood pressure ≥ 95th age percentile, triglycerides ≥ 1.7 mmol/l, HDL < 1.03 mmol/l, and fasting plasma glucose ≥ 5.6 mmol/l. Results In total, 777 patients were included. Of the 306 children, 51, 38, and 0 were diagnosed with IR, MetS, and T2DM, respectively. Of the 471 adolescents, 223, 95, and 0 were diagnosed with IR, MetS, and T2DM, respectively. In the multivariable regression model, BMI-SDS, preterm birth, and Tanner stage were associated with IR in children (6.3 (95% CI 1.3–31.1), 5.4 (95% CI 1.4–20.5), 2.2 (95% CI 1.0–4.8)), and BMI-SDS and waist circumference in adolescents (4.0 (95% CI 1.7–9.2), 3.7 (95% CI 1.5–9.4)). Conclusion Different IR predictors were observed in children/adolescents with obesity. These predictors can be used to optimize screening for IR in pediatric populations.

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Influence of Biochemical and Anthropometric Factors on the Presence of Insulin Resistance in Adolescents

Cited by 11 publications

References 35 publications

Body mass index and waist circumference are better predictors of insulin resistance than total body fat percentage in middle-aged and elderly Taiwanese

Body mass index and waist circumference are better predictors of insulin resistance than total body fat percentage in middle-aged and elderly Taiwanese

Relationship between insulin resistance and adipocytokines: the mediator role of adiposity in children

Predictors of Insulin Resistance in Children versus Adolescents with Obesity

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