Associations of weight-adjusted waist index with cardiovascular chest pain risk in U.S. adults

美国成年人体重调整后的腰围指数与心血管胸痛风险的关联

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Abstract

BACKGROUND: As an alternative to more conventional measures like waist circumference and BMI, the weight-adjusted waist index (WWI) is being thought of as a possibly more accurate way to assess the hazards associated with obesity. Nevertheless, the connection between it and chest pain, a significant symptom among adults, remains underexplored. METHOD: Analyzed from the 2011–2018 NHANES, 13,391 persons aged 40 years and above made up this cross-sectional study. Waist circumference was divided by body weight squared to determine the WWI. WWI was evaluated for its correlation with self-reported chest pain using multivariable logistic regression models, while accounting for pertinent variables. Trend tests and generalized additive models (GAMs) explore linear and nonlinear relationships, with subgroup analyses evaluating consistency across populations. RESULTS: The likelihood of chest pain was significantly higher in individuals with higher WWI. Specifically, for each one-unit increase in WWI, the likelihood of experiencing chest pain increased by 19% (95% CI: 1.07–1.31). Furthermore, individuals in the highest WWI quartile had a 31% higher chance of experiencing chest pain compared to those in the lowest quartile (95% CI: 1.04–1.65). When compared to traditional obesity metrics, WWI showed a stronger association with chest pain. The odds ratio for chest pain was 1.19 (95% CI: 1.07–1.31) for WWI, compared to 1.03 (95% CI: 1.00–1.03) for body mass index (BMI) and 1.01 (95% CI: 1.00–1.01) for waist circumference. CONCLUSION: There is a significant correlation between WWI and an increased likelihood of chest pain among American adults. Compared to traditional obesity metrics such as BMI and waist circumference, WWI offers a more reliable prediction of chest pain likelihood. These findings suggest that WWI could be integrated into clinical practice, allowing healthcare providers to more accurately identify individuals at elevated likelihood and implement targeted prevention and management strategies.

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