Impact of adiposity indices changes across the lifespan on risk of diabetes in women: trajectory modeling approach
Open accessAbstract
AIMS: The impact of life-course different adiposity indices on diabetes mellitus (DM) is poorly understood. We aimed to do trajectory analysis with repeated measurements of adiposity indices in the development of DM among women across the lifespan. METHODS: This study prospectively investigated the 1,681 population of Tehran Lipid and Glucose Study. At baseline, all individuals were free of diabetes. Trajectory analysis was used to identify homogeneous distinct clusters of adiposity indices trajectories and assign individuals to unique clusters. RESULTS: Of the 1681 healthy women, 320 progressed to the DM. Three distinct body mass index (BMI) trajectories and 2 distinct trajectories of other adiposity indices (waist circumstance (WC), conicity index (C-index), and body roundness index (BRI)) were chosen as the best fitting of the latent class growth mixture model. In the adjusted model, total participants [HR (CI 95%): 2.83 (2.05, 3.91); p < 0.001], and menopause [1.35 (1.10, 2.11); p = 0.001] and reproductive-age women [2.93 (1.80, 4.78); p = 0.003] of the high BMI trajectory compared to the ones in the low trajectory of BMI were more likely to develop DM. The high BRI in menopause had a significantly higher risk of DM compared to the low trajectory. In menopause (1.80 (1.26, 2.58)) and reproductive-age women (4.32 (2.49, 7.47)) with high trajectory of C-index, the DM risk decreased after adjustment. CONCLUSIONS: The risk of DM was greater for high BMI, WC, C-index, and BRI trajectories than for lower trajectories. Hence, the development of general, abdominal, and visceral obesity trajectories in the prevention of DM should be considered by clinicians.
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Mousavi et al. reported that during reproductive age, both BMI and BRI were significantly higher in female with diabetes than in those without, whereas after menopause, only BRI remained significantly different.
“Mousavi et al. [27], in a study of diabetes risk across the female life cycle, compared premenopausal and postmenopausal female and reported that during reproductive age, both BMI and BRI were significantly higher in female with diabetes than in those without, whereas after menopause, only BRI remained significantly different.”
From The discriminatory ability of the body roundness index and body mass index for metabolic diseases in Korean adults: a comparative study (2025) · cites this paper as [27]
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Kriska, A. M., Knowler, W. C., LaPorte, R. E., Drash, A. L., Wing, R. R., Blair, S. N., Bennett, P. H., & Kuller, L. H. (1990) · Diabetes Care · doi:10.2337/diacare.13.4.401 · Cited by 755 · cited 1× · see citing works
“The conicity index (C-index) and body roundness index (BRI) are proposed by the following formulas [37, 38]: Participants were asked about their physical activity by using a modifiable activity questionnaire [39, 40].”
MethodPlasma sex steroid hormones and risk of developing type 2 diabetes in women: a prospective study
Ding, E. L., Song, Y., Manson, J. E., Rifai, N., Buring, J. E., & Liu, S. (2007) · Diabetologia · doi:10.1007/s00125-007-0785-y · Cited by 208 · see citing works
Obesity in menopause - our negligence or an unfortunate inevitability
Kozakowski, J., Gietka-Czernel, M., Leszczyńska, D., & Majos, A. (2017) · Menopausal Review · doi:10.5114/pm.2017.68594 · Cited by 189 · see citing works
Weight History in Clinical Practice: The State of the Science and Future Directions
Kushner, R. F., Batsis, J. A., Butsch, W. S., Davis, N., Golden, A., Halperin, F., Kidambi, S., Machineni, S., Novick, M., Port, A., et al. (2020) · Obesity · doi:10.1002/oby.22642 · Cited by 55 · see citing works
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Research works printed but not linked: 72
- [1]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. Diabetes Res Clin Pract. 2019;157:107843. 31518657 10.1016/j.diabres.2019.107843 · DOI · Paper page
- [2]Sun H, Saeedi P, Karuranga S, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119. 10.1016/j.diabres.2021.109119. PubMed PMID: 34879977; eng. 34879977 10.1016/j.diabres.2021.109119 PMC11057359 · DOI · Paper page
- [3]Lin X, Xu Y, Pan X, et al. Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Sci Rep. 2020;10(1):1–11. 32901098 PMC7478957
- [4]Khan MAB, Hashim MJ, King JK, et al. Epidemiology of type 2 diabetes - global burden of Disease and Forecasted trends. J Epidemiol Glob Health. 2020;10(1):107–11. 10.2991/jegh.k.191028.001. PubMed PMID: 32175717; PubMed Central PMCID: PMCPmc7310804. eng. 32175717 10.2991/jegh.k.191028.001 PMC7310804 · DOI
- [5]Dunachie S, Chamnan P. The double burden of diabetes and global infection in low and middle-income countries. Trans R Soc Trop Med Hyg. 2018;113(2):56–64. 10.1093/trstmh/try124. 10.1093/trstmh/try124 PMC6364794 30517697 · DOI
- [6]Beulens JWJ, Pinho MGM, Abreu TC et al. Environmental risk factors of type 2 diabetes—an exposome approach. Diabetologia 2022 2022/02/01;65(2):263–74. 10.1007/s00125-021-05618-w 34792619 · DOI
- [7]Kautzky-Willer A, Harreiter J, Pacini G. Sex and gender differences in risk, pathophysiology and complications of type 2 diabetes Mellitus. Endocr Rev. 2016;37(3):278–316. 10.1210/er.2015-1137. PubMed PMID: 27159875; PubMed Central PMCID: PMCPmc4890267. eng. 27159875 10.1210/er.2015-1137 PMC4890267 · DOI · Paper page
- [8]Hurt RT, Kulisek C, Buchanan LA, et al. The obesity epidemic: challenges, health initiatives, and implications for gastroenterologists. Gastroenterol Hepatol. 2010;6(12):780. PMC3033553 21301632
- [9]Hruby A, Hu FB. The epidemiology of obesity: a big picture. PharmacoEconomics. 2015;33:673–89. 25471927 10.1007/s40273-014-0243-x PMC4859313 · DOI
- [10]Akoumianakis I, Antoniades C. The interplay between adipose tissue and the cardiovascular system: is fat always bad? Cardiovascular Res. 2017;113(9):999–1008. 10.1093/cvr/cvx111 28582523 · DOI
- [11]Booth A, Magnuson A, Fouts J, et al. Adipose tissue: an endocrine organ playing a role in metabolic regulation. Horm Mol Biol Clin Investig. 2016;26(1):25–42. 26910750 10.1515/hmbci-2015-0073 · DOI
- [12]Piqueras P, Ballester A, Durá-Gil JV, et al. Anthropometric indicators as a tool for diagnosis of obesity and other health risk factors: a literature review. Front Psychol. 2021;12:631179. 34305707 10.3389/fpsyg.2021.631179 PMC8299753 · DOI
- [13]Kapoor N, Lotfaliany M, Sathish T, et al. Obesity indicators that best predict type 2 diabetes in an Indian population: insights from the Kerala Diabetes Prevention Program. J Nutr Sci. 2020;9:e15. 10.1017/jns.2020.8. PubMed PMID: 32328239; PubMed Central PMCID: PMCPmc7163399. eng. 32328239 10.1017/jns.2020.8 PMC7163399 · DOI
- [14]Liu XC, Liu YS. Comparison of six anthropometric measures in discriminating diabetes: a cross-sectional study from the National Health and Nutrition Examination Survey. 2022;14(7):465–75. 10.1111/1753-0407.13295. PubMed PMID: 35841213. PMC9310044 35841213 · DOI
- [15]Maessen MF, Eijsvogels TM, Verheggen RJ, et al. Entering a new era of body indices: the feasibility of a body shape index and body roundness index to identify cardiovascular health status. PLoS ONE. 2014;9(9):e107212. 25229394 10.1371/journal.pone.0107212 PMC4167703 · DOI · Paper page
- [16]Thomas DM, Bredlau C, Bosy-Westphal A, et al. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity. 2013;21(11):2264–71. 23519954 10.1002/oby.20408 PMC3692604 · DOI · Paper page
- [17]Després J-P. Abdominal obesity: the most prevalent cause of the metabolic syndrome and related cardiometabolic risk. Eur Heart J Supplements. 2006;8(supplB):B4–12. 10.1093/eurheartj/sul002. 10.1093/eurheartj/sul002 · DOI · Paper page
- [18]April-Sanders AK, Rodriguez CJ. Metabolically healthy obesity redefined. JAMA Netw Open. 2021;4(5):e218860–218860. 33961041 10.1001/jamanetworkopen.2021.8860 · DOI
- [19]Frayn KN. Visceral fat and insulin resistance—causative or correlative? Br J Nutr. 2000;83(S1):S71–7. 10889795 10.1017/S0007114500000982 · DOI
- [20]Opoku AA, Abushama M, Konje JC. Obesity and Menopause. Best Practice & Research Clinical Obstetrics & Gynaecology. 2023:102348. 37244787
- [21]Kim C. Does menopause increase diabetes risk? Strategies for diabetes prevention in midlife women. Women’s Health. 2012;8(2):155–67. 22375719
- [22]Lee HR, Shin J, Han K, et al. Obesity and risk of diabetes mellitus by menopausal status: a nationwide cohort study. J Clin Med. 2021;10(21):5189. 34768709 10.3390/jcm10215189 PMC8584465 · DOI
- [23]Abe M, Fujii H, Funakoshi S et al. Comparison of body Mass Index and Waist circumference in the prediction of diabetes: a retrospective longitudinal study. 2021;12(10):2663–76. 10.1007/s13300-021-01138-3. PubMed PMID: 34448106. PMC8479044 34448106 · DOI
- [24]Yang T, Zhao B. Evaluation of the Association between Obesity Markers and type 2 diabetes: a Cohort Study based on a physical examination Population. 2021;2021:6503339. 10.1155/2021/6503339. PubMed PMID: 34993251. PMC8727144 34993251 · DOI
- [25]Yang J, Wang F, Wang J et al. Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study. BMC Geriatr. 2018 2018/09/17;18(1):218. 10.1186/s12877-018-0912-2 PMC6142386 30223783 · DOI
- [26]Tuglo LS. Comparison of adiposity anthropometric indices and their associations with visceral fat levels determined by bioelectrical impedance analysis among diabetic patients. Sci Rep. 2022;12(1):17824. 10.1038/s41598-022-22848-z. 2022/10/24. 36280694 10.1038/s41598-022-22848-z PMC9592612 · DOI
- [27]Wang L, Liu H, Zhang S, et al. Obesity index and the risk of diabetes among Chinese women with prior gestational diabetes. Diabet Med. 2014;31(11):1368–77. 24961948 10.1111/dme.12532 · DOI
- [28]He L, Fan B, Li C, et al. Association between Body Mass Index and Diabetes Mellitus are mediated through endogenous serum sex hormones among Menopause Transition women: a longitudinal cohort study. Int J Environ Res Public Health. 2023;20(3):1831. 10.3390/ijerph20031831. PubMed PMID. 36767197 10.3390/ijerph20031831 PMC9914507 · DOI
- [29]Hu Y, Bhupathiraju SN, de Koning L, et al. Duration of obesity and overweight and risk of type 2 diabetes among US women. Obesity. 2014;22(10):2267–73. 25131512 10.1002/oby.20851 PMC4180760 · DOI
- [30]Kim ES, Jeong JS, Han K, et al. Impact of weight changes on the incidence of diabetes mellitus: a Korean nationwide cohort study. Sci Rep. 2018;8(1):3735. 29487293 10.1038/s41598-018-21550-3 PMC5829255 · DOI
- [31]Park KY, Hwang HS. Body Weight Fluctuation as a Risk Factor for Type 2 Diabetes: Results from a Nationwide Cohort Study. 2019;8(7). 10.3390/jcm8070950. PubMed PMID: 31261984. PMC6678837 31261984 · DOI
- [33]Nguena Nguefack HL, Pagé MG, Katz J et al. Trajectory modelling techniques useful to epidemiological research: a comparative narrative review of approaches. Clin Epidemiol. 2020:1205–22. PMC7608582 33154677
- [34]Qian T, Masino AJ. Latent patient cluster discovery for robust future forecasting and new-patient generalization. PLoS ONE. 2016;11(9):e0162812. 27636203 10.1371/journal.pone.0162812 PMC5026362 · DOI
- [35]Azizi F, Ghanbarian A, Momenan AA, et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran lipid and glucose study phase II. Trials. 2009;10(1):1–15. 19166627 10.1186/1745-6215-10-5 PMC2656492 · DOI
- [36]Azizi F, Zadeh-Vakili A, Takyar M. Review of Rationale, Design, and initial findings: Tehran lipid and glucose study. Int J Endocrinol Metab. 2018;16(4 Suppl). 10.5812/ijem.84777. PubMed PMID: 30584442; PubMed Central PMCID: PMCPmc6289309. eng. e84777. PMC6289309 30584442 · DOI
- [37]Valdez R. A simple model-based index of abdominal adiposity. J Clin Epidemiol. 1991;44(9):955–6. 1890438 10.1016/0895-4356(91)90059-I · DOI
- [38]Thomas DM, Bredlau C, Bosy-Westphal A, et al. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obes (Silver Spring). 2013;21(11):2264–71. 10.1002/oby.20408. PubMed PMID: 23519954; PubMed Central PMCID: PMCPmc3692604. eng. 10.1002/oby.20408 PMC3692604 23519954 · DOI · Paper page
- [39]Ainsworth BE, Haskell WL, Whitt MC, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9):S498–504. 10993420 10.1097/00005768-200009001-00009 · DOI · Paper page
- [41]Association AD. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes—2021. Diabetes Care. 2021;44(Supplement1):S15–33. 33298413 10.2337/dc21-S002 · DOI · Paper page
- [42]Peacock K, Ketvertis KM, Doerr C. Menopause (Nursing). 2021. 33760453
- [43]Nagin DS. Group-based trajectory modeling: an overview. Handbook of quantitative criminology. 2010:53–67. PMC2994902 21132047
- [44]Caliński T, Harabasz J. A dendrite method for cluster analysis. Commun Statistics-theory Methods. 1974;3(1):1–27. 10.1080/03610927408827101 · DOI
- [45]Ray S, Turi RH, editors. Determination of number of clusters in k-means clustering and application in colour image segmentation. Proceedings of the 4th international conference on advances in pattern recognition and digital techniques; 1999: Calcutta, India.
- [46]Davies DL, Bouldin DW. A cluster separation measure. IEEE Trans Pattern Anal Mach Intell. 1979 (2):224–7. 21868852
- [47]Wondmkun YT, Obesity. Insulin resistance, and type 2 diabetes: associations and therapeutic implications. Diabetes Metab Syndr Obes. 2020;13:3611–6. 10.2147/dmso.s275898. PubMed PMID: 33116712; PubMed Central PMCID: PMCPmc7553667. eng. 33116712 10.2147/dmso.s275898 PMC7553667 · DOI · Paper page
- [48]Karastergiou K, Smith SR, Greenberg AS, et al. Sex differences in human adipose tissues - the biology of pear shape. Biol Sex Differ. 2012;3(1):13. 10.1186/2042-6410-3-13. PubMed PMID: 22651247; PubMed Central PMCID: PMCPmc3411490. eng. 22651247 10.1186/2042-6410-3-13 PMC3411490 · DOI · Paper page
- [49]Okosun IS, Seale JP, Lyn R. Commingling effect of gynoid and android fat patterns on cardiometabolic dysregulation in normal weight American adults. Nutr Diabetes. 2015 2015/05/01;5(5):e155–155. 10.1038/nutd.2015.5 PMC4450460 25985091 · DOI
- [50]Liu W, Liu J, Shao S et al. Obesity at a young age is associated with development of diabetes mellitus: a prospective cohort study in rural China. Postgraduate Medicine. 2020 2020/11/16;132(8):709–13. 10.1080/00325481.2020.1778383 32500799 · DOI
- [51]Cao C, Hu H, Zheng X, et al. Association between central obesity and incident diabetes mellitus among Japanese: a retrospective cohort study using propensity score matching. Sci Rep. 2022;12(1):13445. 10.1038/s41598-022-17837-1. PubMed PMID: 35927472; PubMed Central PMCID: PMCPmc9352654. eng. 35927472 10.1038/s41598-022-17837-1 PMC9352654 · DOI
- [52]Garbuzova EV, Shcherbakova LV, Rymar OD, et al. Triglycerides, Obesity and Education Status Are Associated with the risk of developing type 2 diabetes in young adults, Cohort Study. J Personalized Med. 2023;13(9):1403. 10.3390/jpm13091403. PubMed PMID:. 10.3390/jpm13091403 PMC10533043 37763170 · DOI
- [53]Zajacova A, Huzurbazar S, Greenwood M, et al. Long-term BMI trajectories and health in older adults:hierarchical clustering of functional curves. J Aging Health. 2015;27(8):1443–61. doi: 10.1177/0898264315584329. PubMed PMID: 25953813. 25953813 10.1177/0898264315584329 PMC5436799 · DOI
- [54]Jiali L, Bingbing F, Mengke W, et al. Trajectories of early to mid-life adulthood BMI and incident diabetes: the China Health and Nutrition Survey. BMJ Open Diabetes Research & Care. 2020;8(1):e000972. 10.1136/bmjdrc-2019-000972 PMC7202728 32327441 · DOI
- [55]Botoseneanu A, Liang J. Latent heterogeneity in long-term trajectories of body mass index in older adults. J Aging Health. 2013;25(2):342–63. 23264442 10.1177/0898264312468593 PMC4325276 · DOI
- [56]Peter RS, Keller F, Klenk J, et al. Body mass trajectories, diabetes mellitus, and mortality in a large cohort of Austrian adults. Med (Baltim). 2016;95(49):e5608. 10.1097/md.0000000000005608. PubMed PMID: 27930587; PubMed Central PMCID: PMCPmc5266059. eng. 10.1097/MD.0000000000005608 PMC5266059 27930587 · DOI
- [57]Nano J, Dhana K, Asllanaj E, et al. Trajectories of BMI before diagnosis of type 2 diabetes: the Rotterdam study. Obesity. 2020;28(6):1149–56. 32379398 10.1002/oby.22802 PMC7317538 · DOI
- [58]Kan Y, Liu L, Li X, et al. Association between distinct body mass index trajectories according to the group-based trajectory modeling and the risk of incident diabetes: a systematic review. Obes Rev. 2022;23(12):e13508. 36269000 10.1111/obr.13508 · DOI
- [59]Gray LA, Breeze PR, Williams EA. BMI trajectories, morbidity, and mortality in England: a two-step approach to estimating consequences of changes in BMI. Obesity. 2022;30(9):1898–907. 35920148 10.1002/oby.23510 PMC9546036 · DOI
- [60]Talaei M, Sadeghi M, Marshall T et al. Anthropometric indices predicting incident type 2 diabetes in an Iranian population: the Isfahan Cohort Study. Diabetes Metab. 2013 2013/10/01/;39(5):424–31. 10.1016/j.diabet.2013.04.001 23867722 · DOI
- [61]Woldegebriel AG, Fenta KA, Aregay AB et al. Effectiveness of anthropometric measurements for identifying diabetes and prediabetes among civil servants in a regional city of northern ethiopia: a cross-sectional study. Journal of nutrition and metabolism. 2020;2020. PMC7166279 32322417
- [62]Yang J, Wang F, Wang J, et al. Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study. BMC Geriatr. 2018;18:1–9. 30223783 10.1186/s12877-018-0912-2 PMC6142386 · DOI
- [63]Alwash SM, McIntyre HD, Mamun A. The association of general obesity, central obesity and visceral body fat with the risk of gestational diabetes mellitus: evidence from a systematic review and meta-analysis. Obes Res Clin Pract. 2021;15(5):425–30. 34391692 10.1016/j.orcp.2021.07.005 · DOI · Paper page
- [64]Lin CL, Yu NC. Association of Body Composition with Type 2 Diabetes: A Retrospective Chart Review Study. 2021;18(9). 10.3390/ijerph18094421. PubMed PMID: 33919339. PMC8122668 33919339 · DOI
- [65]Sneed NM, Morrison SA. Body composition methods in adults with type 2 diabetes or at risk for T2D: a clinical review. Curr Diab Rep. 2021;21:1–16. 33730341 10.1007/s11892-021-01381-9 · DOI
- [66]Tatsumi Y, Ohno Y, Morimoto A, et al. Age differences in the risk of diabetes incidence according to body mass index level in Japanese women: BMI and diabetes in women. Obes Res Clin Pract. 2013;7(6):e455–63. 24308888 10.1016/j.orcp.2012.05.001 · DOI
- [67]Lee HR, Shin J, Han K et al. Obesity and risk of diabetes Mellitus by Menopausal Status: a Nationwide Cohort Study. 2021;10(21). 10.3390/jcm10215189. PubMed PMID: 34768709. PMC8584465 34768709 · DOI
- [68]Giráldez-García C, Franch‐Nadal J, Sangrós FJ, et al. Adiposity and diabetes risk in adults with prediabetes: heterogeneity of findings depending on age and anthropometric measure. Obesity. 2018;26(9):1481–90. 30070055 10.1002/oby.22256 · DOI
- [69]Global BMIMC, Di Angelantonio E, Bhupathiraju Sh N, et al. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 2016;388(10046):776–86. 10.1016/s0140-6736(16)30175-1. PubMed PMID: 27423262; PubMed Central PMCID: PMCPmc4995441. eng. 27423262 10.1016/s0140-6736(16)30175-1 PMC4995441 · DOI · Paper page
- [70]Freeman EW, Sammel MD, Lin H, et al. Obesity and reproductive hormone levels in the transition to menopause. Menopause. 2010;17(4):718–26. 10.1097/gme.0b013e3181cec85d. PubMed PMID: 20216473; PubMed Central PMCID: PMCPmc2888623. eng. 20216473 10.1097/gme.0b013e3181cec85d PMC2888623 · DOI
- [71]De Paoli M, Zakharia A, Werstuck GH. The role of estrogen in insulin resistance: a review of clinical and preclinical data. Am J Pathol. 2021;191(9):1490–8. 34102108 10.1016/j.ajpath.2021.05.011 · DOI
- [72]Greendale GA, Sternfeld B, Huang M et al. Changes in body composition and weight during the menopause transition. JCI Insight. 2019;4(5). PMC6483504 30843880
- [74]Rehunen SK, Kautiainen H, Korhonen PE, et al. A high lean body mass is not protecting from type 2 diabetes in the presence of a high body fat mass. Diabetes Metab. 2021;47(6):101219. 33418084 10.1016/j.diabet.2020.101219 · DOI
- [76]Van De Schoot R, Sijbrandij M, Winter SD, et al. The GRoLTS-checklist: guidelines for reporting on latent trajectory studies. Struct Equation Modeling: Multidisciplinary J. 2017;24(3):451–67. 10.1080/10705511.2016.1247646 · DOI · Paper page
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Yoon, S. J., & Kwon, H.-J. (2025) · Epidemiology and Health · doi:10.4178/epih.e2025069
“Consistent with this, Mousavi et al. [27], in a study of diabetes risk across the female life cycle, compared premenopausal and postmenopausal female and reported that during reproductive age, both BMI and BRI were significantly higher in female with diabetes than in those without, whereas after…”
- Authors
- Mousavi, M., Saei Ghare Naz, M., Firouzi, F., Azizi, F., & Ramezani Tehrani, F.
- Affiliations
- Research Institute for Endocrine Sciences (IR)
- Islamic Azad University, Tehran (IR)
- Venue
- BMC Public Health
- Published
- 2024-09-06
- Volume
- 24
- Issue
- 1
- Pages
- 2429-2429
- ISSN
- 1471-2458 (ISSN-L)
- PMC
- PMC11378475
- OpenAlex
- W4402313931
- Cited by
- 7
- References
- 4
- Citations by year
- 2026: 2 · 2025: 5
- FWCI
- 2.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Public Health (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Shahid Beheshti University of Medical Sciences
- Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Keywords
- diabetes mellitus, adiposity indices, body mass index trajectories, waist circumference, conicity index, body roundness index, abdominal obesity, visceral obesity, menopause, women of reproductive age, women, diabetes risk
- MeSH terms
- Adult, Aged, Diabetes Mellitus, Female, Humans, Iran, Middle Aged, Prospective Studies, Risk Factors, Body Mass Index, Adiposity
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