[1] Lawal Y, Bello F, Kaoje YS. Prediabetes deserves more attention: a review. Clin Diabetes, 2020; 38, 328−38. doi:  10.2337/cd19-0101
[2] Zhang MQ, Lin C, Cai XL, et al. The association between GLP-1 receptor-based agonists and the incidence of asthma in patients with type 2 diabetes and/or obesity: a meta-analysis. Biomed Environ Sci, 2024; 37, 607−16. doi:  10.3967/bes2024.067
[3] Jiang SM, Yu TY, Di DX, et al. Worldwide burden and trends of diabetes among people aged 70 years and older, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Diabetes Metab Res Rev, 2024; 40, e3745. doi:  10.1002/dmrr.3745
[4] Wang LM, Peng W, Zhao ZP, et al. Prevalence and treatment of diabetes in China, 2013-2018. JAMA, 2021; 326, 2498−506. doi:  10.1001/jama.2021.22208
[5] American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2021. Diabetes Care, 2021; 44, S15−33. doi:  10.2337/dc21-S002
[6] World Health Organization, International Diabetes Federation. Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia. https://www.who.int/publications/i/item/definition-and-diagnosis-of-diabetes-mellitus-and-intermediate-hyperglycaemia.
[7] Karve A, Hayward RA. Prevalence, diagnosis, and treatment of impaired fasting glucose and impaired glucose tolerance in nondiabetic U. S. adults. Diabetes Care, 2010; 33, 2355−9. doi:  10.2337/dc09-1957
[8] Yip WCY, Sequeira IR, Plank LD, et al. Prevalence of pre-diabetes across ethnicities: a review of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) for classification of dysglycaemia. Nutrients, 2017; 9, 1273. doi:  10.3390/nu9111273
[9] Rooney MR, Rawlings AM, Pankow JS, et al. Risk of progression to diabetes among older adults with prediabetes. JAMA Intern Med, 2021; 181, 511−9. doi:  10.1001/jamainternmed.2020.8774
[10] Sun HL, Zhao T, Zhang DD, et al. Interactions of vitamin D receptor polymorphisms with hypertriglyceridemia and obesity in Chinese individuals susceptible to hypertension and diabetes comorbidity. Biomed Environ Sci, 2023; 36, 196−200.
[11] Jayedi A, Soltani S, Motlagh SZT, et al. Anthropometric and adiposity indicators and risk of type 2 diabetes: systematic review and dose-response meta-analysis of cohort studies. BMJ, 2022; 376, e067516.
[12] Garber AJ. Anti-obesity pharmacotherapy and the potential for preventing progression from prediabetes to type 2 diabetes. Endocr Pract, 2015; 21, 634−44. doi:  10.4158/EP14460.RA
[13] Li N, Lu CH, Ma YH, et al. Factors associated with progression of different prediabetic status to Diabetes: A Community-based cohort study. Diabetes Res Clin Pract, 2022; 184, 109193. doi:  10.1016/j.diabres.2022.109193
[14] Khan RMM, Chua ZJY, Tan JC, et al. From pre-diabetes to diabetes: diagnosis, treatments and translational research. Medicina (Kaunas), 2019; 55, 546. doi:  10.3390/medicina55090546
[15] Van Herpt TTW, Ligthart S, Leening MJG, et al. Lifetime risk to progress from pre-diabetes to type 2 diabetes among women and men: comparison between American Diabetes Association and World Health Organization diagnostic criteria. BMJ Open Diabetes Res Care, 2020; 8, e001529. doi:  10.1136/bmjdrc-2020-001529
[16] Veronese N, Noale M, Sinclair A, et al. Risk of progression to diabetes and mortality in older people with prediabetes: the English longitudinal study on ageing. Age Ageing, 2022; 51, afab222. doi:  10.1093/ageing/afab222
[17] Yin ZX, Gao X, Zhang XC, et al. Prevalence and correlates of healthy aging among elderly aged 65 years and over - 6 PLADs, China, 2019. China CDC Wkly, 2021; 3, 69−73. doi:  10.46234/ccdcw2021.019
[18] Yip W, Fu HQ, Chen AT, et al. 10 years of health-care reform in China: progress and gaps in universal health coverage. Lancet, 2019; 394, 1192−204. doi:  10.1016/S0140-6736(19)32136-1
[19] Guo YX, Wang AQ, Gao X, et al. Obesity is positively associated with depression in older adults: role of systemic inflammation. Biomed Environ Sci, 2023; 36, 481−9.
[20] Yin ZX, Chen J, Zhang J, et al. Dietary patterns associated with cognitive function among the older people in underdeveloped regions: finding from the NCDFaC study. Nutrients, 2018; 10, 464. doi:  10.3390/nu10040464
[21] Zhang XJ, Li YF, Kraus VB, et al. Development of 3-year risk prediction model for type 2 diabetes in older adults with prediabetes — China, 2019-2022. China CDC Wkly, 2025; 7, 701−6.
[22] Egan AM, Wood-Wentz CM, Mohan S, et al. Baseline fasting glucose level, age, sex, and body mass index and the development of diabetes in US adults. JAMA Netw Open, 2025; 8, e2456067. doi:  10.1001/jamanetworkopen.2024.56067
[23] Aoki J, Khalid O, Kaya C, et al. Progression from prediabetes to diabetes in a diverse U. S. population: a machine learning model. Diabetes Technol Ther, 2024; 26, 748−53. doi:  10.1089/dia.2024.0052
[24] Hou XH, Chen SY, Hu G, et al. Stronger associations of waist circumference and waist-to-height ratio with diabetes than BMI in Chinese adults. Diabetes Res Clin Pract, 2019; 147, 9−18. doi:  10.1016/j.diabres.2018.07.029
[25] Fan YX, Wang RD, Ding L, et al. Waist circumference and its changes are more strongly associated with the risk of type 2 diabetes than body mass index and changes in body weight in Chinese adults. J Nutr, 2020; 150, 1259−65. doi:  10.1093/jn/nxaa014
[26] Nakanga WP, Crampin AC, Mkandawire J, et al. Waist circumference and glycaemia are strong predictors of progression to diabetes in individuals with prediabetes in sub-Saharan Africa: 4-year prospective cohort study in Malawi. PLOS Glob Public Health, 2023; 3, e0001263. doi:  10.1371/journal.pgph.0001263
[27] Reaven GM. Pathophysiology of insulin resistance in human disease. Physiol Rev, 1995; 75, 473−86. doi:  10.1152/physrev.1995.75.3.473
[28] Kissebah AH, Krakower GR. Regional adiposity and morbidity. Physiol Rev, 1994; 74, 761−811. doi:  10.1152/physrev.1994.74.4.761
[29] Ligthart S, Van Herpt TTW, Leening MJG, et al. Lifetime risk of developing impaired glucose metabolism and eventual progression from prediabetes to type 2 diabetes: a prospective cohort study. Lancet Diabetes Endocrinol, 2016; 4, 44−51. doi:  10.1016/S2213-8587(15)00362-9
[30] Zhao XF, Yao TC, Song B, et al. The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis. Front Endocrinol (Lausanne), 2024; 15, 1355180. doi:  10.3389/fendo.2024.1355180