Association between waist-to-hip ratio and risk of myocardial infarction: a systematic evaluation and meta-analysis.

BACKGROUND

Myocardial infarction(MI) is one of the most serious health threats. Despite the increasing number of clinical methods used to predict the onset of MI, the prediction of MI is still unsatisfactory and necessitates new methods.

OBJECTIVE

To systematically review observational studies from the past two decades on the association between waist-to-hip ratio (WHR) and MI risk.

METHODS

Original literature on the correlation between WHR and MI was searched in PubMed, Embase, Web of Science, Cochrane Library, Science Direct, CNKI, and Wanfang up to January 31, 2024. Two researchers independently screened, extracted data, and assessed quality using the Newcastle-Ottawa Scale (NOS) and Revman5.3. Meta-analysis with Stata 16.0 calculated the combined Odd ratio (OR) for WHR and MI risk. Heterogeneity was assessed with the statistic to select the appropriate effects model. Subgroup analysis, meta-regression, sensitivity analysis, and funnel plots tested for heterogeneity and publication bias.

RESULTS

A total of 22 observational studies were included, involving 709,093 participants. The meta-analysis showed that an elevated WHR was significantly associated with an increased risk of MI, with a pooled odds ratio (OR) of 1.98 [95% Confidence interval (CI): 1.75-2.24] and high heterogeneity (  = 91.5%,  < 0.0001). Subgroup analysis revealed a stronger association between WHR and MI in women (OR: 1.99, 95% CI: 1.43-2.77) compared to men (OR: 1.74, 95% CI: 1.36-2.22). Regional analysis indicated that the association between WHR and MI risk was highest in Asian populations (OR: 2.93 95% CI: 1.61-5.33), followed by American (OR: 1.73, 95% CI: 1.45-2.08) and European populations (OR: 2.19, 95% CI: 1.49-3.22). Sensitivity analysis demonstrated that the results remained stable after excluding one study.

CONCLUSION

In the general adult population, a higher WHR is a potentially significant association for MI and has predictive value for MI.