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
Main Article Content
Abstract
Obesity is a major risk factor for myocardial infarction (MI). However, how to measure whole-risk with simple baseline characteristics? Anthropometrically, association for metrics does not equate causation on incident MI. Besides, association may present effects of bias rather than the true putative risk may be responsible for all or much of the epidemiological causality, and a different body composition between groups with similar baseline confounding variables may provide false-positives in outcomes. Thus, in evaluating whole-risk by anthropometry all metrics are not enterely valid at all times, and the lack of balance between measurements will be particularly prone to the generation of false-positive results. The purpose of this article is to critically review key findings for association biases from different studies. From the INTERHEART, waist-to-hip ratio (WHR) has been deemed as an excellent MI risk predictor, and other results have conferred to WHR a greater excess risk in women than in men. Nevertheless, a novel insight have revealed that WHR-associated risk would appear biased if metrics to compare had no balance and equivalence relation. Baseline characteristics of thousands of MI cases are well known, but anthropometry, mathematics and epidemiology have taught us something, and comment on it below. To date, no method was used to address biases for balancing the distribution of measurements between groups to be compared. Thus, WHR and waist circumference as being mathematical fraction and unit of whole-length, repectivelly, presented association biases when true unhealthy body composition was not well compared by group and by sex. It occurred for unbalancing both measurements and unhealthy body composition when comparing strength of association for metrics. Only waist-to-height ratio as being measure directly associated to a volume of risk yields no biases and should be the metric used to compare the body composition of risk, either by age or by sex.
Keywords:
Myocardial infarction, risk prediction, obesity, anthropometric indicator, body composition, bias
Article Details
How to Cite
CASTELLANOS, Angel Martin.
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, [S.l.], v. 9, n. 6, june 2021.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/2447>. Date accessed: 05 nov. 2024.
doi: https://doi.org/10.18103/mra.v9i6.2447.
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.
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Doi: 10.1161/JAHA.117.008507.
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Doi: 10.1093/aje/kwh281.
23. 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 (1): 88-95. doi.org/10.20960/nh.982.
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30. Guasch-Ferré M, Bulló M, Martínez-González MA, et al. Waist-to-Height Ratio and Cardiovascular Risk Factors in Elderly Individuals at High Cardiovascular Risk. PLoS ONE. 2012; 7 (8):e43275.
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33. Swainson MG, Batterham AM, Tsakirides C, et al. Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables. PLoS One. 2017; 12 (5): e0177175.
Doi: 10.1371/journal.pone.0177175
34. Hajian-Tlaki K, Heidari B. Comparison of abdominal obesity measures in predicting of 10-year cardiovascular risk in an Iranian adult population using ACC/AHA risk model: A population based cross sectional study. Diabetes Metab Syndr. 2018; 12 (6):991-7. doi: 10.1016/j.dsx.2018.06.012.
35. Howell CR, Mehta T, Ejima K, et al. Body Composition and Mortality in Mexican American Adults: Results from the National Health and Nutrition Examination Survey. Obesity (Silver Spring). 2018; (8):1372-80. doi: 10.1002/oby.22251.
36. Segura-Fragoso A, Rodríguez-Padial L, Alonso-Moreno FJ, et al. Anthropometric measurements of general and central obesity and discriminative capacity on cardiovascular risk: RICARTO study. Semergen. 2019; 45 (5): 323-32.
Doi: 10.1016/j.semerg.2019.02.013.
37. Ramírez-Vélez R, Pérez-Sousa MÁ, Izquierdo M, et al. Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering? Nutrients. 2019;11 (8):1701. doi: 10.3390/nu11081701.
38. Czernichow S, Kengne AP, Stamatakis, E, et al. Body mass index, waist circumference and waist-hip ratio: which is the better discriminator of cardiovascular disease mortality risk?: evidence from an individual-participant meta-analysis of 82 864 participants from nine cohort studies. Obes Rev. 2011; 12 (9):680-7.
Doi: 10.1111/j.1467-789X. 2011. 00879.x.
39. Nalini M, Sharafkhah M, Poustchi H, et al. Comparing Anthropometric Indicators of Visceral and General Adiposity as Determinants of Overall and Cardiovascular Mortality. F. Arch Iran Med. 2019; 22 (6):301-9.
40. 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.
41. Davidson FE, Matsha TE, Erasmus RT, et al. The discriminatory power of visceral adipose tissue area vs anthropometric measures as a diagnostic marker for metabolic síndrome in South African women. Diabetol Metab Syndr. 2019; 11:93. doi:10.1186/s13098-019-0483-1
42. Gavriilidou NN, Pihlsgard M, Elmstahl S. Anthropometric reference data for elderly Swedes and its disease related pattern. Eur J Clin Nutr. 2015; 69 (9):1066-75.
43. Tchernof A, Despres JP. Pathophysiology of human visceral obesity: an update. Physiol Rev. 2013; 93:359–404.
44. Williams SR, 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: 376-93.
45. Mohammadi H, Ohm J, Discacciati A, Sundstrom J, 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.
46. Fox CS, Massaro JM, Hoffmann U, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007; 116 (1):39-48.
47. Woolcott OO, Bergman RN. Relative fat mass (RFM) as a new estimator of whole-body fat percentage ─ A crosssectional study in American adult individuals. ScientificReports. 2018; 8 (1):10980.doi:10.1038/s41598-018-29362-1.
48. Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behavioral Research. 2011; 46: 399-424.
Doi: 10.1080/00273171.2011.568786
49. Martin-Castellanos A, Martin-Castellanos 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. English. doi: 10.20960/nh.03416. Epub ahead of print. PMID: 33757289. https://www.nutricionhospitalaria.org/articles/onlinefirst. (Accessed March 2021)
50. Lee HW, Hong TJ, Hong JY, et al. Korea Working Group on Myocardial Infarction Investigators. Waist-hip ratio and 1-year clinical outcome in patients with non-ST-elevation myocardial infarctions. Coron Artery Dis. 2016; 27 (5):357-64. Doi: 10.1097/MCA.0000000000000369.
51. Medina-Inojosa JR, Batsis JA, Supervia M, et al. Relation of Waist-Hip Ratio to Long-Term Cardiovascular Events in Patients With Coronary Artery Disease. Am J Cardiol. 2018; 121 (8): 903-9. doi: 10.1016/j.amjcard.2017.12.038.
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2. WHO. Obesity and overweight; 2014 [updated June 2016; accessed 21Feb 2019]. Fact sheet No 311. Available in: http//www.who.int/mediacentre/factsheets/fs311/en/
3. Cornier MA, Després JP, Davis N, et al. Assessing adiposity: a scientific statement from the American Heart Association. Circulation. 2011; 124 (18): 1996-2019.
4. Yusuf S, Hawken S, Ounpuu S, et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet. 2005; 366; 1640-9.
5. Gelber RP, Gaziano JM, Orav EJ, et al. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008; 52 (8):605-15. doi:10.1016/j.jacc.2008.03.066
6. Zhu J, Su X, Li G, et al. The incidence of acute myocardial infarction in relation to overweight and obesity: a meta-analysis. Arch Med Sci. 2014;10 (5):855-62. doi:10.5114/aoms.2014.46206
7. Gruson E, Montaye M, Kee F, et al. Anthropometric assessment of abdominal obesity and coronary heart disease risk in men: the PRIME study. Heart. 2010; 96 (2):136-40. doi: 10.1136/hr.2009.171447.
8. Lassale C, Tzoulaki I, Moons KGM, et al. Separate and combined associations of obesity and metabolic health with coronary heart disease: a pan-European case-cohort analysis. Eur Heart J. 2018; 39 (5): 397-406. Doi.10.1093/eurheartj/ehx448.
9. Choi D, Choi S, Son JS, et al. Impact of Discrepancies in General and Abdominal Obesity on Major Adverse Cardiac Events. J Am Heart Assoc. 2019; 8 (18):e013471. doi:10.1161/JAHA.119.013471.
10. Lloyd-Jones DM, Hong J, Labarthe D, et al. Defining and Setting National Goals for Cardiovascular Health Promotion and Disease Reduction: The American Heart Association´s strategic impact Goal through 2020 and beyond. Circulation. 2010; 121: 586-613. Doi: 10.1161/CIRCULATIONAHA.109.192703.
11. Fang N, Jiang M, Fan Y. Ideal cardiovascular health metrics and risk of cardiovascular disease or mortality: A meta-analysis. Int J Cardiol. 2016; 214:279-83.
Doi: 10.1016/j.ijcard.2016.03.210.
12. Alberti KG, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009; 120 (16): 1640-5.
13. World Health Organization. Waist circumference and waist-hip ratio: report of a WHO expert consultation, Geneva, 8-11 December 2008. World Health Organization. 2011. http://www.who.int/iris/handle/10665/44583. (Accessed Dec 2020).
14. Ladeiras-Lopes R, Sampaio F, Bettencourt N, et al. The Ratio Between Visceral and Subcutaneous 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.
15. 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.
16. Brown JC, Harhay MO, Harhay MN. Anthropometrically-predicted visceral adipose tissue and mortality among men and women in the third national health and nutrition examination survey (NHANES III). Am J Hum Biol. 2017; 29:e22898. doi:10.1002/ajhb.22898
17. 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.
18. Nilson G, Hedberg P, Leppert J, et al. Basic Anthropometric Measures in Acute Myocardial Infarction Patients and Individually Sex- and Age-Matched Controls from the General Population. J Obes. 2018; 2018: 3839482. doi: 10.1155/2018/3839482.
19. Cao Q, Yu S, Xiong W, et al. Waist-hip ratio as a predictor of myocardial infarction risk. A systematic review and meta-analysis. Medicine. 2018; 27-30 (e11639). doi.org/10.1097/MD.0000000000011639
20. Joseph P, Yusuf S, Lee SF, et al. Prognostic validation of a non-laboratory and a laboratory based cardiovascular disease risk score in multiple regions of the world. Heart. 2017; 0: 1-7. Doi: 10.1136/heartjnl-2017-311609.
21. 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.
22. Nicklas BJ, Penninx BH, Cesari M, et al. Association of Visceral Adipose Tissue with Incident Myocardial Infarction in Older Men and Women The Health, Aging and Body Composition Study. Am J Epidemiol. 2004; 160:741-9.
Doi: 10.1093/aje/kwh281.
23. 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 (1): 88-95. doi.org/10.20960/nh.982.
24. Martin-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 ratio. Card Res Med. 2018; 2: 13-20.
25. Song X, Jousilahti P, Stehouwer CD, et al. Comparison of various surrogate obesity indicators as predictors of cardiovascular mortality in four European populations. Eur J Clin Nutr. 2013; 67 (12): 1298-302. doi: 10.1038/ejcn.2013.203.
26. 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. Doi: 10.1186/s12889-018-5350-8.
27. 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): 100-7. http://www.aascit.org/journal/ajfnh. (Accessed Dec 2020).
28. Pischon T, Boeing H, Hoffmann K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med. 2008; 359:2105-20.
29. 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), 275-86.
30. Guasch-Ferré M, Bulló M, Martínez-González MA, et al. Waist-to-Height Ratio and Cardiovascular Risk Factors in Elderly Individuals at High Cardiovascular Risk. PLoS ONE. 2012; 7 (8):e43275.
Doi: 10.1371/journal.pone.0043275.
31. Kang SH, Cho KH, Park JW, et al. Comparison of waist to height ratio and body indices for prediction of metabolic disturbances in the Korean population: the Korean National Health and Nutrition Examination Survey 2008-2011. BMC Endocr Disord. 2015; 15:79. doi: 10.1186/s12902-015-0075-5.
32. Lam BC, Koh GC, Chen C, et al. Comparison of Body Mass Index (BMI), Body Adiposity Index (BAI), Waist Circumference (WC), Waist-To-Hip Ratio (WHR) and Waist-To-Height Ratio (WHtR) as predictors of cardiovascular disease risk factors in an adult population in Singapore. PLoS One. 2015; 16; 10 (4): e0122985. doi: 10.1371/journal.pone.0122985.
33. Swainson MG, Batterham AM, Tsakirides C, et al. Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables. PLoS One. 2017; 12 (5): e0177175.
Doi: 10.1371/journal.pone.0177175
34. Hajian-Tlaki K, Heidari B. Comparison of abdominal obesity measures in predicting of 10-year cardiovascular risk in an Iranian adult population using ACC/AHA risk model: A population based cross sectional study. Diabetes Metab Syndr. 2018; 12 (6):991-7. doi: 10.1016/j.dsx.2018.06.012.
35. Howell CR, Mehta T, Ejima K, et al. Body Composition and Mortality in Mexican American Adults: Results from the National Health and Nutrition Examination Survey. Obesity (Silver Spring). 2018; (8):1372-80. doi: 10.1002/oby.22251.
36. Segura-Fragoso A, Rodríguez-Padial L, Alonso-Moreno FJ, et al. Anthropometric measurements of general and central obesity and discriminative capacity on cardiovascular risk: RICARTO study. Semergen. 2019; 45 (5): 323-32.
Doi: 10.1016/j.semerg.2019.02.013.
37. Ramírez-Vélez R, Pérez-Sousa MÁ, Izquierdo M, et al. Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering? Nutrients. 2019;11 (8):1701. doi: 10.3390/nu11081701.
38. Czernichow S, Kengne AP, Stamatakis, E, et al. Body mass index, waist circumference and waist-hip ratio: which is the better discriminator of cardiovascular disease mortality risk?: evidence from an individual-participant meta-analysis of 82 864 participants from nine cohort studies. Obes Rev. 2011; 12 (9):680-7.
Doi: 10.1111/j.1467-789X. 2011. 00879.x.
39. Nalini M, Sharafkhah M, Poustchi H, et al. Comparing Anthropometric Indicators of Visceral and General Adiposity as Determinants of Overall and Cardiovascular Mortality. F. Arch Iran Med. 2019; 22 (6):301-9.
40. 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.
41. Davidson FE, Matsha TE, Erasmus RT, et al. The discriminatory power of visceral adipose tissue area vs anthropometric measures as a diagnostic marker for metabolic síndrome in South African women. Diabetol Metab Syndr. 2019; 11:93. doi:10.1186/s13098-019-0483-1
42. Gavriilidou NN, Pihlsgard M, Elmstahl S. Anthropometric reference data for elderly Swedes and its disease related pattern. Eur J Clin Nutr. 2015; 69 (9):1066-75.
43. Tchernof A, Despres JP. Pathophysiology of human visceral obesity: an update. Physiol Rev. 2013; 93:359–404.
44. Williams SR, 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: 376-93.
45. Mohammadi H, Ohm J, Discacciati A, Sundstrom J, 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.
46. Fox CS, Massaro JM, Hoffmann U, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007; 116 (1):39-48.
47. Woolcott OO, Bergman RN. Relative fat mass (RFM) as a new estimator of whole-body fat percentage ─ A crosssectional study in American adult individuals. ScientificReports. 2018; 8 (1):10980.doi:10.1038/s41598-018-29362-1.
48. Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behavioral Research. 2011; 46: 399-424.
Doi: 10.1080/00273171.2011.568786
49. Martin-Castellanos A, Martin-Castellanos 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. English. doi: 10.20960/nh.03416. Epub ahead of print. PMID: 33757289. https://www.nutricionhospitalaria.org/articles/onlinefirst. (Accessed March 2021)
50. Lee HW, Hong TJ, Hong JY, et al. Korea Working Group on Myocardial Infarction Investigators. Waist-hip ratio and 1-year clinical outcome in patients with non-ST-elevation myocardial infarctions. Coron Artery Dis. 2016; 27 (5):357-64. Doi: 10.1097/MCA.0000000000000369.
51. Medina-Inojosa JR, Batsis JA, Supervia M, et al. Relation of Waist-Hip Ratio to Long-Term Cardiovascular Events in Patients With Coronary Artery Disease. Am J Cardiol. 2018; 121 (8): 903-9. doi: 10.1016/j.amjcard.2017.12.038.
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