Obesity and Heath-Carter Somatotyping of 3438 Adults in the Xinjiang Uygur Autonomous Region of China by Multivariate Analysis

Overview

Journal Diabetes Metab Syndr Obes

Publisher Dove Medical Press

Specialty Endocrinology

Date 2021 Feb 24

PMID 33623401

Citations 1

Authors

Xiaoyuan Liu

Wenhui Li

Youfeng Wen

Guochang Xu

Guojian Zhou

Quanying Qu

Ying Hu

Yueriguli Saitierding

Maierdanjang Mohetaer

Yeerkenbieke Buerlan

Xuejun Zhong

Huanjiu Xi

Affiliations

Soon will be listed here.

Abstract

Introduction: This study aimed to investigate the somatotype and obesity of adults in the Xinjiang Uygur Autonomous Region of China and to explore multivariate path analysis for the feasibility and scientificity of using somatotypes to evaluate obesity.

Subjects And Methods: According to anthropometric methods, a cross-sectional study was performed on 10 indexes of 3438 adults (1690 men and 1748 women, aged > 20 years) living in the Xinjiang Uygur Autonomous Region of China (including Kazakh, Kyrgyz, Xibe, Uzbek, Tatar and Tajik). The Heath-Carter anthropometric method and body mass index (BMI) were used to evaluate somatotype and obesity, respectively. The feasibility and scientificity of using somatotypes to evaluate obesity were analysed by correspondence analysis.

Results: Among the six populations, the somatotypes were mainly distributed as endomorphic mesomorph, mesomorph-endomorph and mesomorphic endomorph populations, accounting for 66.5% of males and 78.8% of females. The obesity rate (27.4% in males, 27.8% in females) of the six populations in the Xinjiang Uygur Autonomous Region of China was much higher than the average Chinese adult obesity rate (12.1%) and the global adult obesity rate (male: 11%, female: 15%). The distribution of BMI was significantly different (male: 0.000, female: 0.033) in different populations, and the incidence of overweight and obesity in the Xinjiang Uygur Autonomous Region of China increased gradually. This study found that there were significant differences in somatotype distribution among different obesity groups in the Xinjiang Uygur Autonomous Region of China (P=0.000). There was a strong correlation between overweight or obesity and endomorph-mesomorph, endomorphic mesomorph and mesomorphic endomorph. Furthermore, this study indicated that using somatotypes to evaluate obesity was reliable and scientific.

Conclusion: This study concluded that the somatotype of overweight or obese people was mainly related to endomorphic mesomorph, mesomorph-endomorph, and mesomorphic endomorph.

Citing Articles

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Liu X, Song F, Liu F, Mao Z, Qu S Heliyon. 2022; 8(10):e11129.

PMID: 36281412 PMC: 9586908. DOI: 10.1016/j.heliyon.2022.e11129.

References

Popkin B, Monteiro C, Swinburn B . Overview: Bellagio Conference on Program and Policy Options for Preventing Obesity in the Low- and Middle-Income Countries. Obes Rev. 2013; 14 Suppl 2:1-8. DOI: 10.1111/obr.12108. View

Ferretti F, Mariani M . Simple vs. Complex Carbohydrate Dietary Patterns and the Global Overweight and Obesity Pandemic. Int J Environ Res Public Health. 2017; 14(10). PMC: 5664675. DOI: 10.3390/ijerph14101174. View

Lao X, Ma W, Sobko T, Zhang Y, Xu Y, Xu X . Dramatic escalation in metabolic syndrome and cardiovascular risk in a Chinese population experiencing rapid economic development. BMC Public Health. 2014; 14:983. PMC: 4247017. DOI: 10.1186/1471-2458-14-983. View

Liu G, Ma C, Wang P, Zhang P, Qu X, Liu S . Pilose antler peptide potentiates osteoblast differentiation and inhibits osteoclastogenesis via manipulating the NF-κB pathway. Biochem Biophys Res Commun. 2017; 491(2):388-395. DOI: 10.1016/j.bbrc.2017.07.091. View

Bolado Jimenez C, Fernadez Ovalle H, Munoz Moreno M, Aller de la Fuente R, de Luis Roman D . Undernutrition measured by the Mini Nutritional Assessment (MNA) test and related risk factors in older adults under hospital emergency care. Nutrition. 2019; 66:142-146. DOI: 10.1016/j.nut.2019.04.005. View

. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet. 2016; 387(10026):1377-1396. PMC: 7615134. DOI: 10.1016/S0140-6736(16)30054-X. View

Yao X, Frommlet F, Zhou L, Zu F, Wang H, Yan Z . The prevalence of hypertension, obesity and dyslipidemia in individuals of over 30 years of age belonging to minorities from the pasture area of Xinjiang. BMC Public Health. 2010; 10:91. PMC: 2838812. DOI: 10.1186/1471-2458-10-91. View

Galic B, Pavlica T, Udicki M, Stokic E, Mikalacki M, Korovljev D . Somatotype characteristics of normal-weight and obese women among different metabolic subtypes. Arch Endocrinol Metab. 2016; 60(1):60-5. PMC: 10118907. DOI: 10.1590/2359-3997000000159. View

Oliveira T, Albuquerque I, Ferreira Stringhini M, Mortoza A, Morais B . THE NUTRITIONAL STATUS OF HOSPITALIZED CHILDREN AND ADOLESCENTS: A COMPARISON BETWEEN TWO NUTRITIONAL ASSESSMENT TOOLS WITH ANTHROPOMETRIC PARAMETERS. Rev Paul Pediatr. 2017; 35(3):273-280. PMC: 5606174. DOI: 10.1590/1984-0462/;2017;35;3;00006. View

10.

Frankl J, Sherwood A, Clegg D, Scherer P, Oz O . Imaging Metabolically Active Fat: A Literature Review and Mechanistic Insights. Int J Mol Sci. 2019; 20(21). PMC: 6862590. DOI: 10.3390/ijms20215509. View

11.

Buffa R, Succa V, Garau D, Marini E, Floris G . Variations of somatotype in elderly Sardinians. Am J Hum Biol. 2005; 17(4):403-11. DOI: 10.1002/ajhb.20141. View

12.

Wang H, Wang J, Liu M, Wang D, Liu Y, Zhao Y . Epidemiology of general obesity, abdominal obesity and related risk factors in urban adults from 33 communities of Northeast China: the CHPSNE study. BMC Public Health. 2012; 12:967. PMC: 3509037. DOI: 10.1186/1471-2458-12-967. View

13.

Flegal K, Kit B, Orpana H, Graubard B . Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013; 309(1):71-82. PMC: 4855514. DOI: 10.1001/jama.2012.113905. View

14.

Zhou B . Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults--study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci. 2002; 15(1):83-96. View

15.

Jaacks L, Vandevijvere S, Pan A, McGowan C, Wallace C, Imamura F . The obesity transition: stages of the global epidemic. Lancet Diabetes Endocrinol. 2019; 7(3):231-240. PMC: 7360432. DOI: 10.1016/S2213-8587(19)30026-9. View

16.

Nelson M, Fiatarone M, Layne J, Trice I, Economos C, Fielding R . Analysis of body-composition techniques and models for detecting change in soft tissue with strength training. Am J Clin Nutr. 1996; 63(5):678-86. DOI: 10.1093/ajcn/63.5.678. View

17.

Lee D, Keum N, Hu F, Orav E, Rimm E, Willett W . Comparison of the association of predicted fat mass, body mass index, and other obesity indicators with type 2 diabetes risk: two large prospective studies in US men and women. Eur J Epidemiol. 2018; 33(11):1113-1123. DOI: 10.1007/s10654-018-0433-5. View

18.

Sanchez-Rodriguez D, Marco E, Ronquillo-Moreno N, Maciel-Bravo L, Gonzales-Carhuancho A, Duran X . ASPEN-AND-ESPEN: A postacute-care comparison of the basic definition of malnutrition from the American Society of Parenteral and Enteral Nutrition and Academy of Nutrition and Dietetics with the European Society for Clinical Nutrition and Metabolism.... Clin Nutr. 2018; 38(1):297-302. DOI: 10.1016/j.clnu.2018.01.017. View

19.

Mechelli F, Arendt-Nielsen L, Stokes M, Agyapong-Badu S . Validity of Ultrasound Imaging Versus Magnetic Resonance Imaging for Measuring Anterior Thigh Muscle, Subcutaneous Fat, and Fascia Thickness. Methods Protoc. 2019; 2(3). PMC: 6789827. DOI: 10.3390/mps2030058. View

20.

Susanne C, Bodzsar E, Castro S . Factor analysis and somatotyping, are these two physique classification methods comparable?. Ann Hum Biol. 1998; 25(5):405-14. DOI: 10.1080/03014469800006652. View