Association Between Some Different Obesity Anthropometric Indices and Type 2 Diabetes Mellitus in Middle-Aged and Elderly Chinese Men and Women in Beijing, China: A Cross-Sectional Study

References

• Saeedi P, Petersohn I, Salpea P, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9(th) edition. Diabetes Res Clin Pract. 2019;157:107843. doi:10.1016/j.diabres.2019.107843
   PubMed Web of Science ®Google Scholar
• National Diabetes Research Group. Diabetes mellitus survey of 300,000 in fourteen provinces and cities of China. Chin Med J. 1981;20:678–681.
   Google Scholar
• Li Y, Teng D, Shi X, et al. Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study. BMJ. 2020;369:m997. doi:10.1136/bmj.m997
   PubMed Web of Science ®Google Scholar
• Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019;92:6–10. doi:10.1016/j.metabol.2018.09.005
   PubMed Web of Science ®Google Scholar
• Misra A, Bhardwaj S. Obesity and the metabolic syndrome in developing countries: focus on South Asians. Nestle Nutr Inst Workshop Ser. 2014;78:133–140.
   Google Scholar
• Wang C, Li J, Xue H, et al. Type 2 diabetes mellitus incidence in Chinese: contributions of overweight and obesity. Diabetes Res Clin Pract. 2015;107(3):424–432. doi:10.1016/j.diabres.2014.09.059
   PubMed Web of Science ®Google Scholar
• Boffetta P, McLerran D, Chen Y, et al. Body mass index and diabetes in Asia: a cross-sectional pooled analysis of 900,000 individuals in the Asia cohort consortium. PLoS One. 2011;6(6):e19930. doi:10.1371/journal.pone.0019930
   PubMed Web of Science ®Google Scholar
• Yu HJ, Ho M, Liu X, et al. Association of weight status and the risks of diabetes in adults: a systematic review and meta-analysis of prospective cohort studies. Int J Obes. 2022;23:1–3.
   Google Scholar
• Satoh H, Kishi R, Tsutsui H. Body mass index can similarly predict the presence of multiple cardiovascular risk factors in middle-aged Japanese subjects as waist circumference. Intern Med. 2010;49(11):977–982. doi:10.2169/internalmedicine.49.3006
   Web of Science ®Google Scholar
• Ying X, Song Z-Y, Zhao C-J, et al. Body mass index, waist circumference, and cardiometabolic risk factors in young and middle-aged Chinese women. J Zhejiang Univ Sci B. 2010;11(9):639–646. doi:10.1631/jzus.B1000105
   Web of Science ®Google Scholar
• Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13(3):275–286. doi:10.1111/j.1467-789X.2011.00952.x
   PubMed Web of Science ®Google Scholar
• Siddiquee T, Bhowmik B, Karmaker RK, et al. Association of general and central obesity with diabetes and prediabetes in rural Bangladeshi population. Diabetes Metab Syndr. 2015;9(4):247–251. doi:10.1016/j.dsx.2015.02.002
   Google Scholar
• Cornier MA, Després JP, Davis N, et al. Assessing adiposity: a scientific statement from the American Heart Association. Circulation. 2011;124(18):1996–2019. doi:10.1161/CIR.0b013e318233bc6a
   PubMed Web of Science ®Google Scholar
• Adeboye B, Bermano G, Rolland C. Obesity and its health impact in Africa: a systematic review. Cardiovasc J Afr. 2012;23(9):512–521. doi:10.5830/CVJA-2012-040
   PubMed Web of Science ®Google Scholar
• Zhang FL, Guo ZN, Wu YH, et al. Prevalence of stroke and associated risk factors: a population based cross sectional study from northeast China. BMJ Open. 2017;7(9):e015758. doi:10.1136/bmjopen-2016-015758
   PubMed Web of Science ®Google Scholar
• Xu Y, Wang L, He J, et al. Prevalence and control of diabetes in Chinese adults. JAMA. 2013;310(9):948‑959. doi:10.1001/jama.2013.168118
   Web of Science ®Google Scholar
• Chinese Diabetes Society. [Guideline for the prevention and treatment of type 2 diabetes mellitus in China (2020 edition)]. Chin J Diabetes Mellitus. 2021;13(4):315–409. Chinese.
   Google Scholar
• Joint committee issued Chinese guideline for the management of dyslipidemia in adults. [2016 Chinese guideline for the management of dyslipidemia in adults]. Zhonghua Xin Xue Guan Bing Za Zhi. 2016;44(10):833–853. Chinese. doi:10.3760/cma.j.issn.0253-3758.2016.10.005
   PubMedGoogle Scholar
• Zeng Q, He Y, Dong S, et al. Optimal cut-off values of BMI, waist circumference and waist: height ratio for defining obesity in Chinese adults. Br J Nutr. 2014;112(10):1735–1744. doi:10.1017/S0007114514002657
   PubMed Web of Science ®Google Scholar
• Wang S, Ma W, Yuan Z, et al. Association between obesity indices and type 2 diabetes mellitus among middle-aged and elderly people in Jinan, China: a cross-sectional study. BMJ Open. 2016;6(11):e012742. doi:10.1136/bmjopen-2016-012742
   PubMed Web of Science ®Google Scholar
• Zhang FL, Ren JX, Zhang P, et al. Strong association of Waist Circumference (WC), Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), and Waist-to-Hip Ratio (WHR) with diabetes: a population-based cross-sectional study in Jilin Province, China. J Diabetes Res. 2021;2021:8812431. doi:10.1155/2021/8812431
   PubMed Web of Science ®Google Scholar
• Bennet L, Stenkula K, Cushman SW, et al. BMI and waist circumference cut-offs for corresponding levels of insulin sensitivity in a Middle Eastern immigrant versus a native Swedish population-the MEDIM population based study. BMC Public Health. 2016;16(1):1242. doi:10.1186/s12889-016-3892-1
   Web of Science ®Google Scholar
• Hartwig S, Kluttig A, Tiller D, et al. Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study. BMJ Open. 2016;6(1):e9266. doi:10.1136/bmjopen-2015-009266
   Web of Science ®Google Scholar
• Lu Y, Yang H, Xu Z, et al. Association between different obesity patterns and the risk of developing type 2 diabetes mellitus among adults in Eastern China: a cross-sectional study. Diabetes Metab Syndr Obes. 2021;14:2631–2639. doi:10.2147/DMSO.S309400
   PubMed Web of Science ®Google Scholar
• Scheen AJ, Van Gaal LF. Combating the dual burden: therapeutic targeting of common pathways in obesity and type 2 diabetes. Lancet Diabetes Endocrinol. 2014;2(11):911–922. doi:10.1016/S2213-8587(14)70004-X
   PubMed Web of Science ®Google Scholar
• Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev. 2002;3(3):141–146. doi:10.1046/j.1467-789X.2002.00065.x
   PubMedGoogle Scholar
• Xia MF, Chen Y, Lin HD, et al. A indicator of visceral adipose dysfunction to evaluate metabolic health in adult Chinese. Sci Rep. 2016;1(6):38214. doi:10.1038/srep38214
   Web of Science ®Google Scholar
• Chen X, Duan M, Hou R, et al. Prevalence of abdominal obesity in Chinese middle-aged and older adults with a normal body mass index and its association with type 2 diabetes mellitus: a nationally representative cohort study from 2011 to 2018. Diabetes Metab Syndr Obes. 2021;14:4829–4841. doi:10.2147/DMSO.S339066
   PubMed Web of Science ®Google Scholar
• Toth MJ, Tchernof A, Sites CK, et al. Effect of menopausal status on body composition and abdominal fat distribution. Int J Obes Relat Metab Disord. 2000;24(2):226–231. doi:10.1038/sj.ijo.0801118
   PubMed Web of Science ®Google Scholar
• Misso ML, Jang C, Adams J, et al. Differential expression of factors involved in fat metabolism with age and the menopause transition. Maturitas. 2005;51(3):299–306. doi:10.1016/j.maturitas.2004.08.013
   Web of Science ®Google Scholar
• Ge Q, Li M, Xu Z, et al. Comparison of different obesity indices associated with type 2 diabetes mellitus among different sex and age groups in Nantong, China: a cross-section study. BMC Geriatr. 2022;22(1):20. doi:10.1186/s12877-021-02713-w
   PubMed Web of Science ®Google Scholar
• Luo J, Hendryx M, Laddu D, et al. Racial and ethnic differences in anthropometric measures as risk factors for diabetes. Diabetes Care. 2019;42(1):126–133. doi:10.2337/dc18-1413
   PubMed Web of Science ®Google Scholar
• Wei W, Xin X, Shao B, et al. The relationship between anthropometric indices and type 2 diabetes mellitus among adults in north-east China. Public Health Nutr. 2014;31:1–9.
   Google Scholar
• Li WC, Chen IC, Chang YC, et al. Waist-to-height ratio, waist circumference and body mass index as indices of cardiometabolic risk among 36,642 Taiwanese adults. Eur J Nutr. 2013;52(1):57–65. doi:10.1007/s00394-011-0286-0
   PubMed Web of Science ®Google Scholar
• Alberti KG, Zimmet P, Shaw J. Metabolic syndrome a new world-wide definition. A consensus statement from the international diabetes federation. Diabet Med. 2006;23(5):469–480. doi:10.1111/j.1464-5491.2006.01858.x
   PubMed Web of Science ®Google Scholar