Waist-to-height ratio surpasses conventional metrics in predicting cardiovascular disease risk

In a recent study published in The American Journal of Clinical Nutrition, researchers investigated the independent associations of body fat percentage (BF%) and waist-to-height ratio (WHtR) and the risk of future ischemic cardiovascular disease (CVD), including its main subtypes (ischemic stroke [IS] and myocardial infarction [MI]). While previous work has compared the accuracy of a combination of both metrics with body mass index [BMI], the current most frequently used obesity estimate, their independent predictive power remained hitherto unknown.

Study: Waist-to-height ratio and body fat percentage as risk factors for ischemic cardiovascular disease: a prospective cohort study from UK Biobank. Image Credit: crystal light / ShutterstockStudy: Waist-to-height ratio and body fat percentage as risk factors for ischemic cardiovascular disease: a prospective cohort study from UK Biobank. Image Credit: crystal light / Shutterstock

This study used a UK Biobank-derived sample cohort comprising 468,333 individuals followed over 12 years for their study. Study findings reveal that WHtR is linearly associated with CVD risk. Notably, the metric significantly outperforms currently existing central obesity measures such as waist-to-hip ratio [WHR] and waist circumference [WC]) in predicting subsequent ischemic CVD risk. Contrasting previous hypotheses, BF% displayed poor predictive power, suggesting that its assumed predictive power was due to its correlation with WHtR and not its independent association with CVD. These findings suggest that WHtR may replace WHR and WC in population-wide obesity censuses and highlight visceral fat as a primary target in weight management interventions.

Introduction

Cardiovascular diseases (CVDs) are the foremost cause of human mortality globally, claiming an estimated 17.9 million lives annually. Obesity, commonly defined as a body mass index (BMI measured in kg/m2)>30, is a well-established predictor of CVD. Alarmingly, the prevalence of obesity has more than tripled in the past four decades, with an estimated 2.3 billion individuals presently suffering from the condition. Obesity-attributable premature deaths have correspondingly doubled in just the last 20 years, making it a public health issue requiring urgent, population-wide interventions.

While the association between BMI and CVD risk is well established, a growing body of literature criticized the former's use, particularly when making etiological interferences pertaining to CVD risk, because it is a general measure of obesity incapable of considering differences in body fat distribution or composition. Body fat percentage (BF%) has been suggested as an improvement over BMI due to its relatively accurate measure of body composition.

Recently, central measures of obesity (such as waist-to-hip ratio [WHR] and waist circumference [WC]) are increasingly being investigated as CVD risk predictors due to their additional benefit of measuring body fat distribution. Encouragingly, clinical trials are increasingly reporting central obesity measures as more accurate CVD risk predictors than their general obesity predecessors. Waist-to-height ratio (WHtR) is one such metric computed by dividing WC by height. The most recent United Kingdom (UK) obesity guidelines recommend its use as a population-wide obesity metric due to a large number of studies reporting its association with subsequent CVD risk.

Unfortunately, these studies almost exclusively compare a combination of WC or WHR with BMI, with only a handful of studies evaluating the associations of BF% or WHtR with ischemic CVD. The few studies that have compared the latter conduct these comparisons in unison, with no evidence for the independent effects of either BF% or WHtR. Notably, these studies have reported confounding outcomes.

About the study

The current study addresses this knowledge gap by investigating the independent associations of WHtR and BF% with ischemic CVD. The study sample cohort was derived from the UK Biobank, a large-scale, long-term prospective cohort comprising more than 500,000 individuals between the ages of 40 and 69 years from Wales, Scotland, and England. Study inclusion criteria comprised the lack of CVD events at baseline, completed anthropometric data, and ongoing pregnancy during the study period.

Data collection was carried out using a bioelectric impedance analyzer (BIA) for BF%, a telescopic height rod device for height, and a tape measure for WC. WHtR was derived from WC and height. Additionally, sociodemographic, ethnicity, and medical health records were obtained from the UK Biobank repository. Finally, physical activity was measured using the Physical Activity Questionnaire. The study follow-up period was 12 years between 2009 and 2021, with outcomes of interest including incident ischemic CVD (primary outcomes) and MI or IS (secondary outcomes).

Statistical analysis comprised both descriptive statistics and proportional hazards computation. For the former, means and standard deviations (SDs) were used for continuous data, and frequency and percentages were used for categorical data. Hazards ratios were computed using Cox proportional hazards models, adjusted from sex, region, age, ethnicity, and education. Alcohol, smoking, and physical activity levels were further accounted for in all models. Finally, Pearson correlation coefficients were computed to investigate potential correlations between BF% and WHtR, which may explain previously reported confounds.

Study findings and conclusions

Of the more than 500,000 UK Biobank participants, 468,333 met the study inclusion criteria and were included in the present study. Over the 12-year follow-up period, 20,151 participants developed ischemic CVD events, 13,604 developed MIs, and 6,681 developed ISs. Consistent with previous research, the current study identified central obesity as a significant risk predictor of CVD. Notably, this association was independent of general obesity measures (i.e., BMI and BF%). The study highlighted the identification of WHtR as an independent, linearly associated risk predictor of ischemic CVD. In contrast, while BF% initially presented a linear association with CVD, adjusting for the former collaboration with WHtR effectively eliminated this relationship.

Contrary to current belief, BF% is not a good independent predictor of ischemic CVD despite being a more accurate measure of body fat composition than BMI. On the other hand, WHtR outperformed all currently used estimates of body fat composition and distribution. This suggests that abdominal visceral fat plays an essential role in CVD pathology and must be the focus of future anti-CVD interventions. However, additional research is required to establish the underlying mechanism of this interaction.

Journal reference:
  • Feng, Q., Bešević, J., Conroy, M., Omiyale, W., Woodward, M., Lacey, B., & Allen, N. (2024). Waist-to-height ratio and body fat percentage as risk factors for ischemic cardiovascular disease: a prospective cohort study from UK Biobank. In The American Journal of Clinical Nutrition (Vol. 119, Issue 6, pp. 1386–1396). Elsevier BV, DOI – 10.1016/j.ajcnut.2024.03.018, https://www.sciencedirect.com/science/article/pii/S0002916524003885
Hugo Francisco de Souza

Written by

Hugo Francisco de Souza

Hugo Francisco de Souza is a scientific writer based in Bangalore, Karnataka, India. His academic passions lie in biogeography, evolutionary biology, and herpetology. He is currently pursuing his Ph.D. from the Centre for Ecological Sciences, Indian Institute of Science, where he studies the origins, dispersal, and speciation of wetland-associated snakes. Hugo has received, amongst others, the DST-INSPIRE fellowship for his doctoral research and the Gold Medal from Pondicherry University for academic excellence during his Masters. His research has been published in high-impact peer-reviewed journals, including PLOS Neglected Tropical Diseases and Systematic Biology. When not working or writing, Hugo can be found consuming copious amounts of anime and manga, composing and making music with his bass guitar, shredding trails on his MTB, playing video games (he prefers the term ‘gaming’), or tinkering with all things tech.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Francisco de Souza, Hugo. (2024, June 12). Waist-to-height ratio surpasses conventional metrics in predicting cardiovascular disease risk. News-Medical. Retrieved on September 27, 2024 from https://www.news-medical.net/news/20240612/Waist-to-height-ratio-surpasses-conventional-metrics-in-predicting-cardiovascular-disease-risk.aspx.

  • MLA

    Francisco de Souza, Hugo. "Waist-to-height ratio surpasses conventional metrics in predicting cardiovascular disease risk". News-Medical. 27 September 2024. <https://www.news-medical.net/news/20240612/Waist-to-height-ratio-surpasses-conventional-metrics-in-predicting-cardiovascular-disease-risk.aspx>.

  • Chicago

    Francisco de Souza, Hugo. "Waist-to-height ratio surpasses conventional metrics in predicting cardiovascular disease risk". News-Medical. https://www.news-medical.net/news/20240612/Waist-to-height-ratio-surpasses-conventional-metrics-in-predicting-cardiovascular-disease-risk.aspx. (accessed September 27, 2024).

  • Harvard

    Francisco de Souza, Hugo. 2024. Waist-to-height ratio surpasses conventional metrics in predicting cardiovascular disease risk. News-Medical, viewed 27 September 2024, https://www.news-medical.net/news/20240612/Waist-to-height-ratio-surpasses-conventional-metrics-in-predicting-cardiovascular-disease-risk.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Diligence associated with better cardiovascular outcomes in type 2 diabetes patients