Association of Body Mass Index and Abdominal Obesity with Myocardial Infarction: We Reveal Confounding Factors that Historically Distorted Causal Inferences
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Abstract
Cardiovascular diseases, mainly myocardial infarction and stroke, are the leading cause of death globally. Therefore, epidemiological research seems necessary to prevent cardiovascular events and mortality. However, real-world data from obesity metrics has intrinsic limitations for the assessment of causality. Despite of historical studies showing that the body mass index (BMI), the waist-to-hip ratio (WHR) and the waist circumference (WC) have been associated with increased risk of myocardial infarction, they might not be accurate from a causal inference.
Our aim was to summarize historical and novel findings about obesity metrics and myocardial infarction to evidence causal association biases. Method: an epidemiological review study was conducted while being original research when adding new anthropometrics in study design. Mathematical inequalities between the simple body measurements in anthropometrically healthy adults were described. Mean values and cut-offs for classic and several newer anthropometric variables were established. Classic metrics, ratios between the means of the simple measurements, a modulus |x| as a result of subtracting some measurement means from others (e.g., mean fat free mass minus fat mass) and somatotype ratings were collated. Mathematically, a non-zero difference for each modulus |x| in any population study would indicate an unbalanced distribution of the measurements between groups being compared, and therefore, the risk exposure levels differing. Thus, when between-groups the high-risk body compositions and somatotype ratings differ, any metric-associated risk is biased from a causal inference. After investigating large epidemiological studies, the historical omission of key anthropometric variables is stated, and as being uncontrolled confounding factors distorted causal inferences. Therefore, a protective overestimate of fat free mass and hip circumference over fat mass and WC, respectively, always occurred. Similarly, when the waist-to-height ratio values of >0.5 are associated; a protective underestimate of height over WC occurs. Any metric-associated risk is biased if prediction is made from WC or technologically measured body compositions without accounting for relative risk volume measures. In conclusion, summarizing the historical and novel findings regarding risk prediction, BMI, WHR and WC alone show evidence of causal association biases because of high-risk body compositions and risk exposure levels always differ between the groups being compared.
Keywords:
Myocardial infarction, body mass index, general obesity, abdominal obesity, kinanthropometry, bias, somatotype
Article Details
How to Cite
CASTELLANOS, Angel Martin.
Association of Body Mass Index and Abdominal Obesity with Myocardial Infarction: We Reveal Confounding Factors that Historically Distorted Causal Inferences.
Medical Research Archives, [S.l.], v. 12, n. 3, mar. 2024.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/5102>. Date accessed: 30 apr. 2024.
doi: https://doi.org/10.18103/mra.v12i3.5102.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
1. WHO. Cardiovascular Diseases (CVDs) World Health Organization (2021). Cardiovascular diseases (CVDs) (who.int)
2. Yusuf S, Hawken S, Ôunpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. The Lancet. 2004; 364: 937–952.
3. Egeland GM, Igland J, Vollset SE, et al. High population attributable fractions of myocardial infarction associated with waist-hip ratio. Obesity. 2016; 24 (5):1162-9.
4. Martín-Castellanos A, Cabañas-Armesilla MD, Barca-Durán FJ, et al. Obesity and risk of Myocardial Infarction in a Sample of European Males. Waist To-Hip-Ratio Presents Information Bias of the Real Risk of Abdominal Obesity. Nutr Hosp. 2017; 34: 88-95. doi.org/10.20960/nh.982. https://pubmed.ncbi.nlm.nih.gov/28244777
5. Peters SAE, Bots SH, Woodward M. Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank. J Am Heart Assoc. 2018; 7(5). pii: e008507. Doi: 10.1161/JAHA.117.008507.
6. Martin-Castellanos A, Martin-Castellanos P, Cabañas MD, et al. Adiposity-associated anthropometric indicators and myocardial infarction risk: Keys for waist to-height-ratio as metric in cardiometabolic health. AJFNH. 2018;3(5):100-107
7. Knowles R, Carter J, Jebb SA, et al. Associations of Skeletal Muscle Mass and Fat Mass With Incident Cardiovascular Disease and All-Cause Mortality: A Prospective Cohort Study of UK Biobank Participants. J Am Heart Assoc. 2021;10 (9):e019337. doi: 10.1161/JAHA.120.019337.
8. Roth G, Mensah G, Johnson C, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019. J Am Coll Cardiol. 2020 Dec, 76 (25) 2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010.
9. Magnussen C, Ojeda FM, Leong DP, et al. Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality. N Engl J Med. 2023; 389(14):1273-1285. doi: 10.1056/NJMoa2206916.
10. Martin Castellanos A. Anthropometrics in Predicting Cardiovascular Disease Risk: Our Research Work Mathematically Demonstrates that Cardiovascular Sciences Were Always Confused for a Long Time [Internet]. Novel Pathogenesis and Treatments for Cardiovascular Disease. IntechOpen; 2023. Available from: http://dx.doi.org/10.5772/intechopen.105098
11. Martin-Castellanos A, MartinCastellanos P, Martin E, et al. Abdominal obesity and myocardial infarction risk: We demonstrate the anthropometric and mathematical reasons that justify the association bias of waist-to-hip ratio. Nutr Hosp. 2021; 38 (3): 502-510. doi.org/10.20960/nh.03416. https://pubmed.ncbi.nlm.nih.gov/33757289/
12. Castellanos AM. Anthropometric measures in predicting myocardial infarction risk. Do we know what we are measuring? Bias in research occurred worldwide when the true unhealthy body composition was not well compared. Medical Research Archives. 2021;9 (6):2-19. Available at: https://esmed.org/MRA/mra/article/view/2447. doi: https://doi.org/10.18103/mra.v9i6.2447
13. Castellanos AM. Anthropometrics and Myocardial Infarction Risk: A Misleading Evidence Was Accepted by Cardiovascular Sciences When Errors of Bias Were Overlooked Worldwide. When Should We End Discussion about the Optimal Metric? Medical Research Archives. 2022;10 (7):2-16. Available at: https://doi.org/10.18103/mra.v10i12.3463.
doi: https://doi.org/10.18103/mra.v10i12.3463
14. Martin Castellanos A. Why Predicting Health Risks from Either Body Mass Index or Waist-to-Hip Ratio Presents Causal Association Biases Worldwide: A Mathematical Demonstration. Acta Scientific Medical Sciences 7.7 (2023): 112-120. DOI: 10.31080/ASMS.2023.07.1605.
15. Powell-Wiley, Powell-Wiley TM, Poirier P, et al. Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation. 2021; 25; 143 (21):e984- e1010. doi: 10.1161/CIR.0000000000000973.
16. Woolcott OO, Bergman RN. Relative fat mass (RFM) as a new estimator of whole-body fat percentage ─ A crosssectional study in American adult individuals. Scientific Reports. 2018; 8 (1):10980.doi:10.1038/s41598-018-29362-1.
17. World Health Organization (WHO). Obesity and overweight-WHO/World Health Organization. Available in: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
18. Neovius M, Teixeira-Pinto A, Rasmussen F. Shift in the composition of obesity in young adult men in Sweden over a third of a century. Int J Obes (Lond). 2008; 32(5):832-6. doi: 10.1038/sj.ijo.0803784.
19. Mohammadi H, Ohm J, Discacciati A, et al. Abdominal obesity and the risk of recurrent atherosclerotic cardiovascular disease after myocardial infarction. Eur J Prev Cardiol. 2020; 27 (18):1944-52. Doi: 10.1177/2047487319898019.
20. Angeras O, Albertsson P, Karason K, et al. Evidence for obesity paradox in patients with acute coronary syndromes: a report from the Swedish Coronary Angiography and Angioplasty Registry. Eur Heart J. 2013; 34: 34 (5): 245–53. Doi: 10.1093/eurheartj/ehs217.
21. Castellanos AM. Waist-to-Height Ratio is an Optimal Metric in Predicting Myocardial Infarction Risk. Other Anthropometrics Widely used by Cardiology to Promote Cardiovascular Health Present Association Biases. Medical Research Archives. 2023;10 (12):2-16. Available at: https://esmed.org/MRA/mra/article/view/3463. doi: https://doi.org/10.18103/mra.v10i12.3463.
22. Martín-Castellanos A, Cabañas MD, Martín-Castellanos P, et al. The body composition and risk prediction in myocardial infarction men. Revealing biological and statistical error bias for both general obesity and waist-to-hip ra-tio. Card Res Med 2018; 2: 13-20.
23. Williams SR1, Jones E, Bell W, et al. Body habitus and coronary heart disease in men. A review with reference to methods of body habitus assessment. Eur Heart J. 1997; 18: 376-393.
24. Williams SR, Goodfellow J, Davies B, et al. Somatotype and angiographically determined atherosclerotic coronary artery disease in men. Am J Hum Biol. 2000; 12: 128-138.
25. Carte JEL. The Heath-Carter Anthropometric Somatotype Instruction Manual. Department of Exercise and Nutritional Sciencies. San Diego State University: San Diego CA: USA. 2002.
26. Berglund L, Risérus U, Hambreaus K. Repeated measures of body mass index and waist circumference in the assessment of mortality risk in patients with myocardial infarction. Ups J Med Sci. 2019; 124(1):78-82. doi:10.1080/03009734.2018.14946 44.
27. Aune D, Sen A, Prasad M, et al. BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3·74 million deaths among 30·3 million participants. BMJ. 2016; 353: i2156.
28. Bhaskaran K, Dos-Santos-Silva I, Leon DA, et al. Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3·6 million adults in the UK. Lancet Diabetes Endocrinol. 2018; 6 (12):944-953. doi: 10.1016/S2213-8587(18)30288-2.
29. Liu J, Tse LA, Liu Z, et al. PURE (Prospective Urban Rural Epidemiology) study in China. Predictive Values of Anthropometric Measurements for Cardiometabolic Risk Factors and Cardiovascular Diseases Among 44 048 Chinese. J Am Heart Assoc. 2019. 8 (16): e010870. doi: 10.1161/JAHA. 118.010870.
30. Mehran L, Amouzegar A, Fanaei SM, et al. Anthropometric measures and risk of all-cause and cardiovascular mortality: An 18 years follow-up. Obes Res Clin Pract. 2022; 16 (1):63-71. doi: 10.1016/j.orcp.2021.12.004.
31. Dikaiou P, Björck L, Adiels M, et al. Obesity, overweight and risk for cardiovascular disease and mortality in young women. Eur J Prev Cardiol. 2021; 28 (12):1351-1359. doi: 10.1177/2047487320908983.
32. Rost, S., Freuer, D., Peters, A. et al. New indexes of body fat distribution and sex-specific risk of total and cause-specific mortality: a prospective cohort study. BMC Public Health. 2018;18 (1): 427. https://doi.org/10.1186/s12889-018-5350-8
33. Chi JH, Lee BJ. Association of myocardial infarction and angina pectoris with obesity and biochemical indices in the South Korean population. Sci Rep. 2022; 12 (1):13769. doi: 10.1038/s41598-022-17961-y.
34. Myint PK, Kwok CS, Luben RN, et al. Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease. Heart. 2014; 100 (20):1613-9. doi: 10.1136/heartjnl-2014-305816.
35. Carrión-Martínez A, Buckley B, Orenes-Piñero E, et al. Anthropometric Measures and Risk of Cardiovascular Disease: Is there an Opportunity for Non-Traditional Anthropometric Assessment? A Review. Rev Cardiovasc Med. 2022; 23(12), 414. Available at: https://doi.org/10.31083/j.rcm2312414
36. Powell-Wiley, Powell-Wiley TM, Poirier P, et al. Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation. 2021; 25; 143 (21):e984e1010. doi: 10.1161/CIR.0000000000000973.
37. Visseren FLJ, Mach F, Smulders YM, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021; 42(34):3227-337. doi:10.1093/eurheartj/ehab484. Erratum in: Eur Heart J. 2022; 43(42): 4468.
38. Ross R, Neeland IJ, Yamashita S, 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. doi: 10.1038/s41574-019-0310-7.
39. Standards of Medical Care in Diabetes—2022 Abridged for Primary Care Providers. Clin Diabetes. 2022; 40 (1):10–38. Available at: https://doi.org/10.2337/cd22-as01
40. Cho JH, Rhee EJ, Park SE, et al. Taskforce Team of the Obesity Fact Sheet of the Korean Society for the Study of Obesity. The Risk of Myocardial Infarction and Ischemic Stroke According to Waist Circumference in 21,749,261 Korean Adults: A Nationwide Population-Based Study. Diabetes Metab J. 2019; 43 (2):206-221. doi: 10.4093/dmj.2018.0039.
41. Han SY, Kim NH, Kim DH, et al. Associations between Body Mass Index, Waist Circumference, and Myocardial Infarction in Older Adults Aged over 75 Years: A Population-Based Cohort Study. Medicina. 2022; 58(12):1768. https://doi.org/10.3390/medicina58121768
42. Wiebe N, Stenvinkel P, Tonelli M. Associations of Chronic Inflammation, Insulin Resistance, and Severe Obesity With Mortality, Myocardial Infarction, Cancer, and Chronic Pulmonary Disease. JAMA Netw Open. 2019; 2(8):e1910456. doi: 10.1001/jamanetworkopen.2019.10456.
43. Barrea L, Muscogiuri G, Pugliese G, et al. Metabolically Healthy Obesity (MHO) vs. Metabolically Unhealthy Obesity (MUO) Phenotypes in PCOS: Association with Endocrine-Metabolic Profile, Adherence to the Mediterranean Diet, and Body Composition. Nutrients. 2021;13(11):3925. doi: 10.3390/nu13113925.
44. Rådholm K, Chalmers J, Ohkuma T, et al. Use of the waist-to-height ratio to predict cardiovascular risk in patients with diabetes: Results from the ADVANCE-on study. Diabetes, Obesity and Metabolism. 2018; 20: 1903–1910.
45. Zhao H, Huang R, Jiang M, et al. Myocardial Tissue-Level Characteristics of Adults With Metabolically Healthy Obesity. J Am Coll Cardiol Img. 2023; 16 (7):889-901. https://doi.org/10.1016/j.jcmg.2023.01.022.
46. Lingvay I, Brown-Frandsen K, Colhoun HM, et al. SELECT Study Group. Semaglutide for cardiovascular event reduction in people with overweight or obesity: SELECT study baseline characteristics. Obesity (Silver Spring). 2023; 31(1):111-122. doi: 10.1002/oby.23621.
47. 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: a systematic review and meta-analysis. Obes Rev. 2012; 13: 275-86. doi: 10.1111/j.1467-789X.2011.00952.x.
48. Seltzer CC, Kannel WB, Dawber TR, et al. Somatotypes and Coronary Heart Disease: The Framingham Study. 1971. Available at:
http//legacy.library.ucsf.edu/tid/hqq59c00/pdf.
49. Malina RM, Katzmarzyk PT, Song TMK et al. Somatotype and cardiovascular risk factors in healthy adults. Am J Hum Biol. 1997; 9(1): 11-19. Available at: https://doi.org/10.1002/(SICI)1520-6300(1997)9:1<11::AID-AJHB3>3.0.CO;2-T
50. Mahmood SS, Levy D, Vasan RS, et al. The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective. Lancet. 2014; 383 (9921):999-1008. doi: 10.1016/S0140-6736(13)61752-3.
51. Martín-Castellanos A, Cabañas MD, Martín P, et al. The body composition in myocardial infarction males. Novel findings in both the association and relationship between anthropometric indicators of risk. JONNPR. 2017; 2 (9): 388-398. DOI: 10.19230/jonnpr.1547.
52. Chen Y, Jiang J, Shi J, et al. Association of Visceral Fat Index and percentage Body Fat and Anthropometric Measures with Myocardial Infarction and Stroke. J Hypertens. 2016; 5: 235.doi: 10.4172/2167-1095.1000235.
53. Romero-Saldaña M, Tauler P, Vaquero-Abellán M, et al. Validation of a non-invasive method for the early detection of metabolic syndrome: a diagnostic accuracy test in a working population. BMJ Open. 2018; 8(10):e020476. doi: 10.1136/bmjopen-2017-020476.
54. Castellanos AM. Abdominal obesity in predicting myocardial infarction risk. Waist-to-Hip Ratio: The metric that confused cardiology worldwide for a long time. J Cardiol Cardiovasc Med. 2021; 6: 026-028. DOI: 10.29328/journal.jccm.1001113.
55. Dhar S, Das PK, Bhattacharjee B, et al. Predictive Value of Waist Height Ratio, Waist Hip Ratio and Body Mass Index in Assessing Angiographic Severity of Coronary Artery Disease in Myocardial Infarction Patients. Mymensingh Med J. 2020; 29 (4): 906-13.
56. Gruzdeva O, Borodkina D, Uchasova E, et al. Localization of fat depots and cardiovascular risk. Lipids Health Dis. 2018;17(1):218. doi: 10.1186/s12944-018-0856-8.
57. Weschenfelder C, Kris-Etherton PM. Abdominal Subcutaneous Adipose Tissue, Diet, and Risk of Cardiovascular Disease: What do we Know? Int J Cardiovasc Sci. 2021;35 (1):46-7. DOI: 10.36660/ijcs.20210233
58. Fox CS, Massaro JM, Hoffmann U, et al. Ab-dominal visceral and subcutaneous adipose tis-sue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007; 116 (1):39-48.
59. Ladeiras-Lopes R, Sampaio F, Bettencourt N, et al. The Ratio Between Visceral and Subcu-taneous Abdominal Fat Assessed by Computed Tomography Is an Independent Predictor of Mortality and Cardiac Events. Rev Esp Cardiol (Engl Ed). 2017; 70 (5): 331-7.
60. Magudia K, Bridge CP, Bay CP, et al. Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events. Am J Roentgenol. 2023; 220 (2):236-244. doi: 10.2214/AJR.22.27977.
61. Fernandes DPS, Lopes Juvanhol L, Nobre AA, et al. Central adiposity as a predictor of mortality in older adults: Identification of cutoffs using generalized additive models. Front. Nutr. 2023; 10:1132006. doi: 10.3389/fnut.2023.1132006.
62. Jayedi A, Soltani S, Zargar MS, et al. Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ. 2020; 370:m3324. doi: 10.1136/bmj.m3324.
2. Yusuf S, Hawken S, Ôunpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. The Lancet. 2004; 364: 937–952.
3. Egeland GM, Igland J, Vollset SE, et al. High population attributable fractions of myocardial infarction associated with waist-hip ratio. Obesity. 2016; 24 (5):1162-9.
4. Martín-Castellanos A, Cabañas-Armesilla MD, Barca-Durán FJ, et al. Obesity and risk of Myocardial Infarction in a Sample of European Males. Waist To-Hip-Ratio Presents Information Bias of the Real Risk of Abdominal Obesity. Nutr Hosp. 2017; 34: 88-95. doi.org/10.20960/nh.982. https://pubmed.ncbi.nlm.nih.gov/28244777
5. Peters SAE, Bots SH, Woodward M. Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank. J Am Heart Assoc. 2018; 7(5). pii: e008507. Doi: 10.1161/JAHA.117.008507.
6. Martin-Castellanos A, Martin-Castellanos P, Cabañas MD, et al. Adiposity-associated anthropometric indicators and myocardial infarction risk: Keys for waist to-height-ratio as metric in cardiometabolic health. AJFNH. 2018;3(5):100-107
7. Knowles R, Carter J, Jebb SA, et al. Associations of Skeletal Muscle Mass and Fat Mass With Incident Cardiovascular Disease and All-Cause Mortality: A Prospective Cohort Study of UK Biobank Participants. J Am Heart Assoc. 2021;10 (9):e019337. doi: 10.1161/JAHA.120.019337.
8. Roth G, Mensah G, Johnson C, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019. J Am Coll Cardiol. 2020 Dec, 76 (25) 2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010.
9. Magnussen C, Ojeda FM, Leong DP, et al. Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality. N Engl J Med. 2023; 389(14):1273-1285. doi: 10.1056/NJMoa2206916.
10. Martin Castellanos A. Anthropometrics in Predicting Cardiovascular Disease Risk: Our Research Work Mathematically Demonstrates that Cardiovascular Sciences Were Always Confused for a Long Time [Internet]. Novel Pathogenesis and Treatments for Cardiovascular Disease. IntechOpen; 2023. Available from: http://dx.doi.org/10.5772/intechopen.105098
11. Martin-Castellanos A, MartinCastellanos P, Martin E, et al. Abdominal obesity and myocardial infarction risk: We demonstrate the anthropometric and mathematical reasons that justify the association bias of waist-to-hip ratio. Nutr Hosp. 2021; 38 (3): 502-510. doi.org/10.20960/nh.03416. https://pubmed.ncbi.nlm.nih.gov/33757289/
12. Castellanos AM. Anthropometric measures in predicting myocardial infarction risk. Do we know what we are measuring? Bias in research occurred worldwide when the true unhealthy body composition was not well compared. Medical Research Archives. 2021;9 (6):2-19. Available at: https://esmed.org/MRA/mra/article/view/2447. doi: https://doi.org/10.18103/mra.v9i6.2447
13. Castellanos AM. Anthropometrics and Myocardial Infarction Risk: A Misleading Evidence Was Accepted by Cardiovascular Sciences When Errors of Bias Were Overlooked Worldwide. When Should We End Discussion about the Optimal Metric? Medical Research Archives. 2022;10 (7):2-16. Available at: https://doi.org/10.18103/mra.v10i12.3463.
doi: https://doi.org/10.18103/mra.v10i12.3463
14. Martin Castellanos A. Why Predicting Health Risks from Either Body Mass Index or Waist-to-Hip Ratio Presents Causal Association Biases Worldwide: A Mathematical Demonstration. Acta Scientific Medical Sciences 7.7 (2023): 112-120. DOI: 10.31080/ASMS.2023.07.1605.
15. Powell-Wiley, Powell-Wiley TM, Poirier P, et al. Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation. 2021; 25; 143 (21):e984- e1010. doi: 10.1161/CIR.0000000000000973.
16. Woolcott OO, Bergman RN. Relative fat mass (RFM) as a new estimator of whole-body fat percentage ─ A crosssectional study in American adult individuals. Scientific Reports. 2018; 8 (1):10980.doi:10.1038/s41598-018-29362-1.
17. World Health Organization (WHO). Obesity and overweight-WHO/World Health Organization. Available in: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
18. Neovius M, Teixeira-Pinto A, Rasmussen F. Shift in the composition of obesity in young adult men in Sweden over a third of a century. Int J Obes (Lond). 2008; 32(5):832-6. doi: 10.1038/sj.ijo.0803784.
19. Mohammadi H, Ohm J, Discacciati A, et al. Abdominal obesity and the risk of recurrent atherosclerotic cardiovascular disease after myocardial infarction. Eur J Prev Cardiol. 2020; 27 (18):1944-52. Doi: 10.1177/2047487319898019.
20. Angeras O, Albertsson P, Karason K, et al. Evidence for obesity paradox in patients with acute coronary syndromes: a report from the Swedish Coronary Angiography and Angioplasty Registry. Eur Heart J. 2013; 34: 34 (5): 245–53. Doi: 10.1093/eurheartj/ehs217.
21. Castellanos AM. Waist-to-Height Ratio is an Optimal Metric in Predicting Myocardial Infarction Risk. Other Anthropometrics Widely used by Cardiology to Promote Cardiovascular Health Present Association Biases. Medical Research Archives. 2023;10 (12):2-16. Available at: https://esmed.org/MRA/mra/article/view/3463. doi: https://doi.org/10.18103/mra.v10i12.3463.
22. Martín-Castellanos A, Cabañas MD, Martín-Castellanos P, et al. The body composition and risk prediction in myocardial infarction men. Revealing biological and statistical error bias for both general obesity and waist-to-hip ra-tio. Card Res Med 2018; 2: 13-20.
23. Williams SR1, Jones E, Bell W, et al. Body habitus and coronary heart disease in men. A review with reference to methods of body habitus assessment. Eur Heart J. 1997; 18: 376-393.
24. Williams SR, Goodfellow J, Davies B, et al. Somatotype and angiographically determined atherosclerotic coronary artery disease in men. Am J Hum Biol. 2000; 12: 128-138.
25. Carte JEL. The Heath-Carter Anthropometric Somatotype Instruction Manual. Department of Exercise and Nutritional Sciencies. San Diego State University: San Diego CA: USA. 2002.
26. Berglund L, Risérus U, Hambreaus K. Repeated measures of body mass index and waist circumference in the assessment of mortality risk in patients with myocardial infarction. Ups J Med Sci. 2019; 124(1):78-82. doi:10.1080/03009734.2018.14946 44.
27. Aune D, Sen A, Prasad M, et al. BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3·74 million deaths among 30·3 million participants. BMJ. 2016; 353: i2156.
28. Bhaskaran K, Dos-Santos-Silva I, Leon DA, et al. Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3·6 million adults in the UK. Lancet Diabetes Endocrinol. 2018; 6 (12):944-953. doi: 10.1016/S2213-8587(18)30288-2.
29. Liu J, Tse LA, Liu Z, et al. PURE (Prospective Urban Rural Epidemiology) study in China. Predictive Values of Anthropometric Measurements for Cardiometabolic Risk Factors and Cardiovascular Diseases Among 44 048 Chinese. J Am Heart Assoc. 2019. 8 (16): e010870. doi: 10.1161/JAHA. 118.010870.
30. Mehran L, Amouzegar A, Fanaei SM, et al. Anthropometric measures and risk of all-cause and cardiovascular mortality: An 18 years follow-up. Obes Res Clin Pract. 2022; 16 (1):63-71. doi: 10.1016/j.orcp.2021.12.004.
31. Dikaiou P, Björck L, Adiels M, et al. Obesity, overweight and risk for cardiovascular disease and mortality in young women. Eur J Prev Cardiol. 2021; 28 (12):1351-1359. doi: 10.1177/2047487320908983.
32. Rost, S., Freuer, D., Peters, A. et al. New indexes of body fat distribution and sex-specific risk of total and cause-specific mortality: a prospective cohort study. BMC Public Health. 2018;18 (1): 427. https://doi.org/10.1186/s12889-018-5350-8
33. Chi JH, Lee BJ. Association of myocardial infarction and angina pectoris with obesity and biochemical indices in the South Korean population. Sci Rep. 2022; 12 (1):13769. doi: 10.1038/s41598-022-17961-y.
34. Myint PK, Kwok CS, Luben RN, et al. Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease. Heart. 2014; 100 (20):1613-9. doi: 10.1136/heartjnl-2014-305816.
35. Carrión-Martínez A, Buckley B, Orenes-Piñero E, et al. Anthropometric Measures and Risk of Cardiovascular Disease: Is there an Opportunity for Non-Traditional Anthropometric Assessment? A Review. Rev Cardiovasc Med. 2022; 23(12), 414. Available at: https://doi.org/10.31083/j.rcm2312414
36. Powell-Wiley, Powell-Wiley TM, Poirier P, et al. Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation. 2021; 25; 143 (21):e984e1010. doi: 10.1161/CIR.0000000000000973.
37. Visseren FLJ, Mach F, Smulders YM, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021; 42(34):3227-337. doi:10.1093/eurheartj/ehab484. Erratum in: Eur Heart J. 2022; 43(42): 4468.
38. Ross R, Neeland IJ, Yamashita S, 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. doi: 10.1038/s41574-019-0310-7.
39. Standards of Medical Care in Diabetes—2022 Abridged for Primary Care Providers. Clin Diabetes. 2022; 40 (1):10–38. Available at: https://doi.org/10.2337/cd22-as01
40. Cho JH, Rhee EJ, Park SE, et al. Taskforce Team of the Obesity Fact Sheet of the Korean Society for the Study of Obesity. The Risk of Myocardial Infarction and Ischemic Stroke According to Waist Circumference in 21,749,261 Korean Adults: A Nationwide Population-Based Study. Diabetes Metab J. 2019; 43 (2):206-221. doi: 10.4093/dmj.2018.0039.
41. Han SY, Kim NH, Kim DH, et al. Associations between Body Mass Index, Waist Circumference, and Myocardial Infarction in Older Adults Aged over 75 Years: A Population-Based Cohort Study. Medicina. 2022; 58(12):1768. https://doi.org/10.3390/medicina58121768
42. Wiebe N, Stenvinkel P, Tonelli M. Associations of Chronic Inflammation, Insulin Resistance, and Severe Obesity With Mortality, Myocardial Infarction, Cancer, and Chronic Pulmonary Disease. JAMA Netw Open. 2019; 2(8):e1910456. doi: 10.1001/jamanetworkopen.2019.10456.
43. Barrea L, Muscogiuri G, Pugliese G, et al. Metabolically Healthy Obesity (MHO) vs. Metabolically Unhealthy Obesity (MUO) Phenotypes in PCOS: Association with Endocrine-Metabolic Profile, Adherence to the Mediterranean Diet, and Body Composition. Nutrients. 2021;13(11):3925. doi: 10.3390/nu13113925.
44. Rådholm K, Chalmers J, Ohkuma T, et al. Use of the waist-to-height ratio to predict cardiovascular risk in patients with diabetes: Results from the ADVANCE-on study. Diabetes, Obesity and Metabolism. 2018; 20: 1903–1910.
45. Zhao H, Huang R, Jiang M, et al. Myocardial Tissue-Level Characteristics of Adults With Metabolically Healthy Obesity. J Am Coll Cardiol Img. 2023; 16 (7):889-901. https://doi.org/10.1016/j.jcmg.2023.01.022.
46. Lingvay I, Brown-Frandsen K, Colhoun HM, et al. SELECT Study Group. Semaglutide for cardiovascular event reduction in people with overweight or obesity: SELECT study baseline characteristics. Obesity (Silver Spring). 2023; 31(1):111-122. doi: 10.1002/oby.23621.
47. 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: a systematic review and meta-analysis. Obes Rev. 2012; 13: 275-86. doi: 10.1111/j.1467-789X.2011.00952.x.
48. Seltzer CC, Kannel WB, Dawber TR, et al. Somatotypes and Coronary Heart Disease: The Framingham Study. 1971. Available at:
http//legacy.library.ucsf.edu/tid/hqq59c00/pdf.
49. Malina RM, Katzmarzyk PT, Song TMK et al. Somatotype and cardiovascular risk factors in healthy adults. Am J Hum Biol. 1997; 9(1): 11-19. Available at: https://doi.org/10.1002/(SICI)1520-6300(1997)9:1<11::AID-AJHB3>3.0.CO;2-T
50. Mahmood SS, Levy D, Vasan RS, et al. The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective. Lancet. 2014; 383 (9921):999-1008. doi: 10.1016/S0140-6736(13)61752-3.
51. Martín-Castellanos A, Cabañas MD, Martín P, et al. The body composition in myocardial infarction males. Novel findings in both the association and relationship between anthropometric indicators of risk. JONNPR. 2017; 2 (9): 388-398. DOI: 10.19230/jonnpr.1547.
52. Chen Y, Jiang J, Shi J, et al. Association of Visceral Fat Index and percentage Body Fat and Anthropometric Measures with Myocardial Infarction and Stroke. J Hypertens. 2016; 5: 235.doi: 10.4172/2167-1095.1000235.
53. Romero-Saldaña M, Tauler P, Vaquero-Abellán M, et al. Validation of a non-invasive method for the early detection of metabolic syndrome: a diagnostic accuracy test in a working population. BMJ Open. 2018; 8(10):e020476. doi: 10.1136/bmjopen-2017-020476.
54. Castellanos AM. Abdominal obesity in predicting myocardial infarction risk. Waist-to-Hip Ratio: The metric that confused cardiology worldwide for a long time. J Cardiol Cardiovasc Med. 2021; 6: 026-028. DOI: 10.29328/journal.jccm.1001113.
55. Dhar S, Das PK, Bhattacharjee B, et al. Predictive Value of Waist Height Ratio, Waist Hip Ratio and Body Mass Index in Assessing Angiographic Severity of Coronary Artery Disease in Myocardial Infarction Patients. Mymensingh Med J. 2020; 29 (4): 906-13.
56. Gruzdeva O, Borodkina D, Uchasova E, et al. Localization of fat depots and cardiovascular risk. Lipids Health Dis. 2018;17(1):218. doi: 10.1186/s12944-018-0856-8.
57. Weschenfelder C, Kris-Etherton PM. Abdominal Subcutaneous Adipose Tissue, Diet, and Risk of Cardiovascular Disease: What do we Know? Int J Cardiovasc Sci. 2021;35 (1):46-7. DOI: 10.36660/ijcs.20210233
58. Fox CS, Massaro JM, Hoffmann U, et al. Ab-dominal visceral and subcutaneous adipose tis-sue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007; 116 (1):39-48.
59. Ladeiras-Lopes R, Sampaio F, Bettencourt N, et al. The Ratio Between Visceral and Subcu-taneous Abdominal Fat Assessed by Computed Tomography Is an Independent Predictor of Mortality and Cardiac Events. Rev Esp Cardiol (Engl Ed). 2017; 70 (5): 331-7.
60. Magudia K, Bridge CP, Bay CP, et al. Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events. Am J Roentgenol. 2023; 220 (2):236-244. doi: 10.2214/AJR.22.27977.
61. Fernandes DPS, Lopes Juvanhol L, Nobre AA, et al. Central adiposity as a predictor of mortality in older adults: Identification of cutoffs using generalized additive models. Front. Nutr. 2023; 10:1132006. doi: 10.3389/fnut.2023.1132006.
62. Jayedi A, Soltani S, Zargar MS, et al. Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ. 2020; 370:m3324. doi: 10.1136/bmj.m3324.