Nutrition Journal (Jun 2024)

Association of weight-adjusted waist index with all-cause mortality among non-Asian individuals: a national population-based cohort study

  • Ting Cao,
  • Ruijie Xie,
  • Jiusong Wang,
  • Meimei Xiao,
  • Haiyang Wu,
  • Xiaozhu Liu,
  • Songlin Xie,
  • Yanming Chen,
  • Mingjiang Liu,
  • Ya Zhang

DOI
https://doi.org/10.1186/s12937-024-00947-z
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 12

Abstract

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Abstract Introduction The Weight-Adjusted Waist Index (WWI) is a new indicator of obesity that is associated with all-cause mortality in Asian populations. Our study aimed to investigate the linear and non-linear associations between WWI and all-cause mortality in non-Asian populations in the United States, and whether WWI was superior to traditional obesity indicators as a predictor of all-cause mortality. Methods We conducted a cohort study using data from the 2011–2018 National Health and Nutrition Examination Survey (NHANES), involving 18,592 participants. We utilized Cox proportional hazard models to assess the association between WWI, BMI, WC, and the risk of all-cause mortality, and performed subgroup analyses and interaction tests. We also employed a receiver operating characteristics (ROC) curve study to evaluate the effectiveness of WWI, BMI, and WC in predicting all-cause mortality. Results After adjusting for confounders, WWI, BMI, and WC were positively associated with all-cause mortality. The performance of WWI, BMI, and WC in predicting all-cause mortality yielded AUCs of 0.697, 0.524, and 0.562, respectively. The data also revealed a U-shaped relationship between WWI and all-cause mortality. Race and cancer modified the relationship between WWI and all-cause mortality, with the relationship being negatively correlated in African Americans and cancer patients. Conclusions In non-Asian populations in the United States, there is a U-shaped relationship between WWI and all-cause mortality, and WWI outperforms BMI and WC as a predictor of all-cause mortality. These findings may contribute to a better understanding and prediction of the relationship between obesity and mortality, and provide support for effective obesity management strategies.

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