Anthropometric indices as surrogates for estimating abdominal visceral and subcutaneous adipose tissue: A meta-analysis with 16,129 participants

Ping, Zhiguang; Pei, Xiaoting; Xia, Peige; Chen, Yuansi; Guo, Rui; Hu, Chenxi; Imam, Mustapha Umar; Chen, Yanzi; Sun, Panpan; Liu, Li

doi:10.1016/j.diabres.2018.08.005

Cited by 29 publications

(22 citation statements)

References 38 publications

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“…Obesity is the consequence of an excessive body fat accumulation due to an imbalance of energy intake and energy expenditure [2]. Diagnosis of obesity is usually established by assessing the body mass index (BMI) ≥ 30 kg/m 2 .…”

Section: Introductionmentioning

confidence: 99%

“…This anthropometric measurement has some limitations, because the correlation between body fat and BMI is not constant. Assessing body fat distribution with measurements such as waist circumference or waist-to-hip ratio may improve evaluation and diagnosis of obesity [2]. Currently, DualEnergy X ray Absorptiometry-DEXA, is considered as the reference method in the assessment of body composition [3].…”

Section: Introductionmentioning

confidence: 99%

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Asthma and Obesity: Two Diseases on the Rise and Bridged by Inflammation

Bantulà

Roca‐Ferrer

Arismendi

et al. 2021

JCM

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Asthma and obesity are two epidemics affecting the developed world. The relationship between obesity and both asthma and severe asthma appears to be weight-dependent, causal, partly genetic, and probably bidirectional. There are two distinct phenotypes: 1. Allergic asthma in children with obesity, which worsens a pre-existing asthma, and 2. An often non allergic, late-onset asthma developing as a consequence of obesity. In obesity, infiltration of adipose tissue by macrophages M1, together with an increased expression of multiple mediators that amplify and propagate inflammation, is considered as the culprit of obesity-related inflammation. Adipose tissue is an important source of adipokines, such as pro-inflammatory leptin, produced in excess in obesity, and adiponectin with anti-inflammatory effects with reduced synthesis. The inflammatory process also involves the synthesis of pro-inflammatory cytokines such as IL-1β, IL-6, TNFα, and TGFβ, which also contribute to asthma pathogenesis. In contrast, asthma pro-inflammatory cytokines such as IL-4, IL-5, IL-13, and IL-33 contribute to maintain the lean state. The resulting regulatory effects of the immunomodulatory pathways underlying both diseases have been hypothesized to be one of the mechanisms by which obesity increases asthma risk and severity. Reduction of weight by diet, exercise, or bariatric surgery reduces inflammatory activity and improves asthma and lung function.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Asthma and Obesity: Two Diseases on the Rise and Bridged by Inflammation

Bantulà

Roca‐Ferrer

Arismendi

et al. 2021

JCM

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“…It is interesting that we identified leptin as a top-ranking factor for obesity defined by waist circumference, but not for obesity defined by BMI. We know that waist circumference is more closely correlated with visceral fat [19], which is metabolically active where dysregulation of adipokine and cytokines acts as a key mechanism in obesity-related consequence, such as CVD [20–22]. Notably, salivary leptin has been found to exhibit a correlation coefficient of 0.78 with plasma level [23].…”

Section: Discussionmentioning

confidence: 99%

“…Our findings suggest an importance of leptin in evaluating obesity by the waist circumference of children which does not appear when considering BMI percentile. Since leptin is an adipokine that is generally recognized as representing adipose tissue mass while BMI cannot differentiate between fat and lean muscle mass [6, 19], measurement by waist circumference is most relevant to obesity. This is particularly true for 10-year-old adolescents since their measurements were taken as puberty was being initiated.…”

Section: Discussionmentioning

confidence: 99%

A Data Mining Approach Identified Salivary Biomarkers That Discriminate between Two Obesity Measures

Shi¹,

Goodson²

2019

Journal of Obesity

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Background. A key mechanism of obesity involves dysregulation of metabolic and inflammatory markers. This study aimed to identify salivary biomarkers and other factors associated with obesity using an ensemble data mining approach. Methods. For a random cohort of over 700 subjects from 8137 Kuwait children (10.00 ± 0.67 years), four data mining methods were applied to identify important variables associated with obesity, including logistic regression by lasso regularization (Lasso), multivariate adaptive regression spline (MARS), random forests (RF), and boosting classification trees (BT). Each algorithm generated a variable importance rank list, based on an internal cross-validation procedure. An aggregated importance ranking was constructed by averaging the rank ordering of variables from individual list, weighted by the classification performance of respective models. Subsequently, the subset of top-ranking variables that were identified with at least three algorithms was evaluated by classification performance using receiver operating characteristic (ROC) analysis with bootstrap percentile resampling. Results. Obesity was defined either by the waist circumference (OBW) or by the body mass index (BMI) (OBWHO). We identified C-reactive protein (CRP), insulin, leptin, adiponectin, as salivary biomarkers associated with OBW, plus a clinical feature fitness level. A similar set of biomarkers was identified for OBWHO, but not including leptin. Tree-based clustering analysis revealed patterns that were significantly different between the OBW and OBWHO subjects. Conclusion. A data mining approach based on multiple algorithms is useful for identifying factors associated with phenotypes, especially in cases where relationships are not salient, and a consensus from multiple methods can help produce a more generalizable subset of features. In this case, we have demonstrated that evaluation using the waist circumference includes association with high levels of salivary leptin, which is not seen with evaluation by BMI.

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“…The cutoff-point of subcutaneous fat mass was 1.2 cm [11, 12]. Waist circumferences were used for representing visceral fat mass since waist circumference is a reliable index for visceral adiposity [13, 14]. The cutoff points of waist circumferences were 90 cm for men and 80 cm for women, according to Asian cutoff points.…”

Section: Methodsmentioning

confidence: 99%

Subcutaneous fat mass is associated with genetic risk scores related to proinflammatory cytokine signaling and interact with physical activity in middle-aged obese adults

Daily¹,

Yang

Liu

et al. 2019

Nutr Metab (Lond)

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Background and aimsSubcutaneous fat mass is negatively correlated with atherogenic risk factors, but its putative benefits remain controversial. We hypothesized that genetic variants that influence subcutaneous fat mass would modulate lipid and glucose metabolism and have interactions with lifestyles in Korean middle-aged adults with high visceral fat.Materials and methodsSubcutaneous fat mass was categorized by dividing the average of subscapular skin-fold thickness by BMI and its cutoff point was 1.2. Waist circumferences were used for representing visceral fat mass with Asian cutoff points. GWAS of subjects aged 40–65 years with high visceral fat (n = 3303) were conducted and the best gene-gene interactions from the genetic variants related to subcutaneous fat were selected and explored using the generalized multifactor dimensionality reduction. Genetic risk scores (GRS) were calculated by weighted GRS that was divided into low, medium and high groups.ResultsSubjects with high subcutaneous fat did not have dyslipidemia compared with those with low subcutaneous fat, although both subject groups had similar amounts of total fat. The best model to influence subcutaneous fat included IL17A_rs4711998, ADCY2_rs326149, ESRRG_rs4846514, CYFIP2_rs733730, TCF7L2_rs7917983, ZNF766_rs41497444 and TGFBR3_rs7526590. The odds ratio (OR) for increasing subcutaneous fat was higher by 2.232 folds in the high-GRS group, after adjusting for covariates. However, total and LDL cholesterol, triglyceride and C-reactive protein concentrations in the circulation were not associated with GRS. Subjects with high-GRS had higher serum HDL cholesterol levels than those with low-GRS. Physical activity and GRS had an interaction with subcutaneous fat. In subjects with low physical activity, the odds ratio for high subcutaneous fat increased by 2.232, but subcutaneous fat deposition was not affected in the high-GRS group with high physical activity.ConclusionObese adults with high-GRS had more subcutaneous fat, but they did not show more dyslipidemia and inflammation compared to low-GRS. High physical activity prevented subcutaneous fat deposition in subjects with high GRS for subcutaneous fat.

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Anthropometric indices as surrogates for estimating abdominal visceral and subcutaneous adipose tissue: A meta-analysis with 16,129 participants

Cited by 29 publications

References 38 publications

Asthma and Obesity: Two Diseases on the Rise and Bridged by Inflammation

Asthma and Obesity: Two Diseases on the Rise and Bridged by Inflammation

A Data Mining Approach Identified Salivary Biomarkers That Discriminate between Two Obesity Measures

Subcutaneous fat mass is associated with genetic risk scores related to proinflammatory cytokine signaling and interact with physical activity in middle-aged obese adults

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