scholarly journals Body Fat Distribution in Trunk and Legs Are Associated With Cardiometabolic Risk Clustering Among Chinese Adolescents Aged 10-18 Years Old

2020 ◽  
Author(s):  
Qingmei Yang ◽  
Ping Ma ◽  
Hao Zhang ◽  
Rongrong Cai ◽  
Yangyang Dong ◽  
...  

Abstract Background: The association between total fat, body fat distribution and cardiometabolic risk factors are highly controversial among adolescents. The aim of the present study was to evaluate the association of body fat distribution with cardiometabolic risk factors clustering among Chinese adolescents.Methods: In this cross-sectional study a total of 1175 adolescents aged 10 to 18 years underwent a comprehensive assessment of cardimetabolic risk factors. Body fat analysis was performed with Bioelectrical impedance analysis. Results: Individuals with the CVRFs ≥1 or CVRFs ≥2 had higher indices of body fat distribution such as body fat mass(BFM) compared to those with normal CVRFs (all P<0.001). The prevalence of CVRFs ≥1, CVRFs ≥2 increased with increasing of the quartile of BFM, TBFM, ABFM, LBFM, PBF, VFL compared to normal subjects. After adjusted for age and sex, the study indicated an linear relationship between TBFM(β=0.693, 95%CI:0.363,1.023), LBFM(β=-1.471, 95%CI:-2.768,-0.175) and CVRFs z-score. Logistic regression models suggested TBFM was associated with CVRFs≥1 and CVRFs≥2 by higher odds. Lower odds of LBFM was associated with CVRFs≥2. Conclusions A significant association between body fat mass of trunk(TBFM), body fat mass of leg(LBFM) and cluster of cardiometabolic risk factors was showed in the study. It suggested to reduce body fat mass of trunk and increase body fat mass of leg were essential for adolescents to prevent cardiovascular risk factors clustering.

Author(s):  
Qingmei Yang ◽  
Ping Ma ◽  
Hao Zhang ◽  
Rongrong Cai ◽  
Yangyang Dong ◽  
...  

Abstract Objectives The aim of the present study was to evaluate the association of body fat distribution with cardiometabolic risk factors clustering among Chinese adolescents. Methods In this cross sectional study a total of 1,175 adolescents aged 10–18 years underwent a comprehensive assessment of cardimetabolic risk factors. Body fat analysis was performed with bioelectrical impedance analysis (BIA). Results Individuals with the CVRFs≥1 or CVRFs≥2 had higher indices of body fat distribution such as body fat mass (BFM) compared to those with normal CVRFs (all p<0.001). The prevalence of CVRFs≥1, CVRFs≥2 increased with increasing of the quartile of BFM, TBFM, ABFM, LBFM, PBF, VFL compared to normal subjects. After adjusted for age and sex, the study indicated an linear relationship between TBFM (β = 0.693, 95% CI:0.363, 1.023), LBFM (β = −1.471, 95% CI:−2.768, −0.175) and CVRFs z-score. Logistic regression models suggested TBFM was associated with CVRFs≥1 and CVRFs≥2 by higher odds. Lower odds of LBFM was associated with CVRFs≥2. Conclusions The contribution of the fat mass in specific region on the cardiovascular risk factors clustering is different among adolescents. The trunk fat is associated with higher clustered cardiometabolic risk, while leg fat mass is the protective factor.


PLoS ONE ◽  
2017 ◽  
Vol 12 (9) ◽  
pp. e0185403 ◽  
Author(s):  
Theodora W. Elffers ◽  
Renée de Mutsert ◽  
Hildo J. Lamb ◽  
Albert de Roos ◽  
Ko Willems van Dijk ◽  
...  

2017 ◽  
Vol 263 ◽  
pp. e175 ◽  
Author(s):  
T.(Dorine) W. Elffers ◽  
Renée De Mutsert ◽  
Hildo J. Lamb ◽  
Albert De Roos ◽  
J.A.P.(Ko) Willems Van Dijk ◽  
...  

1990 ◽  
Vol 70 (4) ◽  
pp. 888-893 ◽  
Author(s):  
C. M. DE RIDDER ◽  
P. F. BRUNING ◽  
M. L. ZONDERLAND ◽  
J. H. H. THIJSSEN ◽  
J. M. G. BONFRER ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yide Yang ◽  
Ming Xie ◽  
Shuqian Yuan ◽  
Yuan Zeng ◽  
Yanhui Dong ◽  
...  

Abstract Background We aimed to assess the associations between adiposity distribution and cardiometabolic risk factors among overweight and obese adults in China, and to demonstrate the sex differences in these associations. Methods A total of 1221 participants (455 males and 766 females) were included in this study. Percentage of body fat (PBF) of the whole body and regional areas, including arm, thigh, trunk, android, and gynoid, were measured by the dual-energy X-ray absorptiometry method. Central adiposity was measured by waist circumference. Clustered cardiometabolic risk was defined as the presence of two or more of the six cardiometabolic risk factors, namely, high triglyceride, low high density lipoprotein, elevated glucose, elevated blood pressure, elevated high sensitivity C-reactive protein, and low adiponectin. Linear regression models and multivariate logistic regression models were used to assess the associations between whole body or regional PBF and cardiometabolic risk factors. Results In females, except arm adiposity, other regional fat (thigh, trunk, android, gynoid) and whole-body PBF are significantly associated with clustered cardiometabolic risk, adjusting for age, smoking, alcohol drinking, physical activity, and whole-body PBF. One-SD increase in Z scores of the thigh and gynoid PBF were significantly associated with 80 and 78% lower odds of clustered cardiometabolic risk (OR: 0.20, 95%CI: 0.12–0.35 and OR: 0.22, 95%CI: 0.12–0.41). Trunk, android and whole-body PBF were significantly associated with higher odds of clustered risk with OR of 1.90 (95%CI:1.02–3.55), 2.91 (95%CI: 1.75–4.85), and 2.01 (95%CI: 1.47–2.76), respectively. While in males, one-SD increase in the thigh and gynoid PBF are associated with 94% (OR: 0.06, 95%CI: 0.02–0.23) and 83% lower odds (OR: 0.17, 95%CI: 0.05–0.57) of clustered cardiometabolic risk, respectively. Android and whole-body PBF were associated with higher odds of clustered cardiometabolic risk (OR: 3.39, 95%CI: 1.42–8.09 and OR: 2.45, 95%CI: 1.53–3.92), but the association for trunk PBF was not statistically significant (OR: 1.16, 95%CI: 0.42–3.19). Conclusions Adiposity distribution plays an important role in the clustered cardiometabolic risk in participants with overweight and obese and sex differences were observed in these associations. In general, central obesity (measured by android PBF) could be the best anthropometric measurement for screening people at risk for CVD risk factors for both men and women. Upper body fat tends to be more detrimental to cardiometabolic health in women than in men, whereas lower body fat is relatively more protective in men than in women.


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