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Ge J, Peng W, Lu J. Predictive Value of Life's Crucial 9 for Cardiovascular and All-Cause Mortality: A Prospective Cohort Study From the NHANES 2007 to 2018. J Am Heart Assoc. 2024; 13(20): e036669.

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Article

Body Shape Index and Cardiovascular Health: Life’s Essential 8 and Crucial 9

1Health Promotion Research, Havre, Montana, USA

2Kinesmetrics Lab, Tallahassee, Florida, USA


American Journal of Cardiovascular Disease Research. 2024, Vol. 9 No. 2, 23-31
DOI: 10.12691/ajcdr-9-2-3
Copyright © 2024 Science and Education Publishing

Cite this paper:
Peter D. Hart. Body Shape Index and Cardiovascular Health: Life’s Essential 8 and Crucial 9. American Journal of Cardiovascular Disease Research. 2024; 9(2):23-31. doi: 10.12691/ajcdr-9-2-3.

Correspondence to: Peter  D. Hart, Health Promotion Research, Havre, Montana, USA. Email: pdhart@outlook.com

Abstract

Background: Obesity has been a growing concern to public health and novel measures of body composition could aid prevention efforts. A body shape index (BSI) is a relatively new measure that adjusts waist circumference for height and weight and may be a good predictor of cardiovascular outcomes. The aim of this study was to examine the population-level association between BSI and cardiovascular health (CVH) in adults. Methods: The 2017-2020 (pre-pandemic) National Health and Nutrition Examination Survey (NHANES) was used. BSI (m11/6/kg2/3) was computed for adults 20+ years of age using measured height, weight, and waist circumference (WC). CVH was assessed using the American Heart Association (AHA) Life’s Essential 8 (LE8) metric along with an additional psychological health component that yields Life’s Crucial 9 (LC9). Multiple linear regression and multinomial logistic regression were used to regress different forms of CVH onto BSI quartiles while controlling for age, sex, race, and income. Results: Approximately 36.6% (95% CI: 33.6 – 39.7) of adults had high-risk BSI with rates increasing linearly with age (p < .001). Bivariate correlations showed BSI was indirectly associated with LE8 (r = -.294, p < .001) and LC9 (r = -.289, p < .001). Adults with high-risk BSI had lower mean LE8 (60.6 vs 68.2, p < .001) and mean LC9 (63.9 vs 70.8, p < .001) as compared to their low-risk counterparts. In the fully adjusted model predicting LE8, adults in BSI Q1 (b = 9.3, p < .001), Q2 (b = 3.6, p = .003), and Q3 (b = 2.1, p = .006) had greater LE8 than those in Q4 (p trend < .001). Similarly, the fully adjusted model predicting LC9 showed adults in BSI Q1 (b = 8.5, p < .001), Q2 (b = 3.4, p = .005), and Q3 (b = 1.9, p = .008) had greater LC9 than those in Q4 (p trend < .001). Finally, the fully adjusted multinomial logistic regression model showed adults in BSI Q2, Q3, and Q4 had 1.77, 1.81, and 2.13 (respectively, all ps < .05) times the odds of adults in BSI Q1 to have moderate CVH over high CVH. Furthermore, adults in BSI Q2, Q3, and Q4 had 3.57, 4.26, and 5.96 (respectively, all ps < .05) times the odds of adults in BSI Q1 to have low CVH over high CVH. Conclusion: This study has shown that a novel measure of body composition is predictive of cardiovascular risk in U.S. adults. Specifically, BSI was found to have an indirect relationship with both continuous (i.e., LE8 and LC9) and categorical (i.e., high, moderate, and low CVH) forms of CVH. BSI may be a useful metric to consider in addition to conventional measures when predicting cardiovascular risk in adults.

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