TY - JOUR AU - Jacobs, E. J. AU - Newton, C. C. AU - Wang, Y. AU - Patel, A. V. AU - McCullough, M. L. AU - Campbell, P. T. PY - 2010 DA - 2010// TI - Waist circumference and all-cause mortality in a large US cohort JO - Arch Intern Med VL - 170 UR - https://doi.org/10.1001/archinternmed.2010.201 DO - 10.1001/archinternmed.2010.201 ID - Jacobs2010 ER - TY - JOUR AU - Moore, L. L. AU - Bradlee, M. L. AU - Singer, M. R. AU - Splansky, G. L. AU - Proctor, M. H. AU - Ellison, R. C. PY - 2004 DA - 2004// TI - BMI and waist circumference as predictors of lifetime colon cancer risk in Framingham study adults JO - Int J Obes VL - 28 UR - https://doi.org/10.1038/sj.ijo.0802606 DO - 10.1038/sj.ijo.0802606 ID - Moore2004 ER - TY - JOUR AU - Vazquez, G. AU - Duval, S. AU - Jacobs, D. R. AU - Silventoinen, K. PY - 2007 DA - 2007// TI - Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis JO - Epidemiol Rev VL - 29 UR - https://doi.org/10.1093/epirev/mxm008 DO - 10.1093/epirev/mxm008 ID - Vazquez2007 ER - TY - JOUR AU - Krakauer, N. Y. AU - Krakauer, J. C. PY - 2016 DA - 2016// TI - A new body shape index predicts mortality hazard independently of body mass index JO - Obes Epidemiol Pathog Treat A Multidiscip Approach VL - 7 ID - Krakauer2016 ER - TY - STD TI - 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. 2012:275–286. ID - ref5 ER - TY - STD TI - Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, et al. Waist circumference as a vital sign in clinical practice: a consensus statement from the IAS and ICCR working group on visceral obesity. Nat Rev Endocrinol. 2020;16(3):177–89. ID - ref6 ER - TY - JOUR AU - Okamoto, N. AU - Hosono, A. AU - Shibata, K. AU - Tsujimura, S. AU - Oka, K. AU - Fujita, H. PY - 2017 DA - 2017// TI - Accuracy of self-reported height, weight and waist circumference in a Japanese sample JO - Obes Sci Pract VL - 3 UR - https://doi.org/10.1002/osp4.122 DO - 10.1002/osp4.122 ID - Okamoto2017 ER - TY - STD TI - Bozeman SR, Hoaglin DC, Burton TM, Pashos CL, Ben-Joseph RH, Hollenbeak CS. Predicting waist circumference from body mass index. BMC Med Res Methodol. 2012;12(1):1–8. ID - ref8 ER - TY - BOOK AU - James, G. AU - Witten, D. AU - Hastie, T. AU - Tibshirani, R. PY - 2013 DA - 2013// TI - An introduction to statistical learning PB - Springer New York CY - New York UR - https://doi.org/10.1007/978-1-4614-7138-7 DO - 10.1007/978-1-4614-7138-7 ID - James2013 ER - TY - JOUR AU - Obermeyer, Z. AU - Emanuel, E. J. PY - 2016 DA - 2016// TI - Predicting the future-big data, machine learning, and clinical medicine JO - N Engl J Med VL - 375 UR - https://doi.org/10.1056/NEJMp1606181 DO - 10.1056/NEJMp1606181 ID - Obermeyer2016 ER - TY - JOUR AU - Bzdok, D. AU - Altman, N. AU - Krzywinski, M. PY - 2018 DA - 2018// TI - Points of significance: statistics versus machine learning JO - Nat Methods VL - 15 UR - https://doi.org/10.1038/nmeth.4642 DO - 10.1038/nmeth.4642 ID - Bzdok2018 ER - TY - STD TI - Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Data [data collection]. Hyattsville: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 1999–2017. https://wwwn.cdc.gov/nchs/nhanes UR - https://wwwn.cdc.gov/nchs/nhanes ID - ref12 ER - TY - STD TI - Office for National Statistics. Social and Vital Statistics Division, Food Standards Agency. National Diet and Nutrition Survey: Adults Aged 19 to 64 Years, 2000–2001 [data collection]: UK Data Service. SN: 5140; 2005. https://doi.org/10.5255/UKDA-SN-5140-1 ID - ref13 ER - TY - BOOK PY - 2015 DA - 2015// TI - China health and nutrition survey [data collection] ID - ref14 ER - TY - CHAP AU - Chen, T. AU - Guestrin, C. PY - 2016 DA - 2016// TI - XGBoost: a scalable tree boosting system BT - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining ID - Chen2016 ER -