Scholarlink

Background <p>Rheumatoid arthritis (RA) represents a pressing global health challenge. While obesity is a controllable risk factor for RA patients, traditional body measurements like body mass index (BMI) have shown limitations in assessing risk. The weight-adjusted waist index (WWI), a new measurement method, provides better insight into belly fat distribution patterns. This research seeks to understand how WWI relates to both all-cause mortality and cardiovascular disease (CVD) mortality in people with RA.</p> Methods <p>Researchers conducted a longitudinal analysis examining participants diagnosed with RA using data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999–2018. The study introduced a novel anthropometric measure, WWI, by dividing the waist circumference (WC) measurement by the body weight’s square root. The main outcomes of this study were all-cause mortality and cardiovascular mortality. The research team employed several statistical approaches: multivariable Cox proportional hazards models, restricted cubic spline (RCS) analysis, and survival assessment through Kaplan-Meier (KM) analysis. The investigation accounted for confounding factors and incorporated both subgroup and sensitivity analyses to ensure result reliability. To evaluate the effectiveness of different indicators in predicting mortality, we conducted receiver operating characteristic (ROC) analyses.</p> Results <p>This investigation encompassed 2,564 qualified participants with 102 months as the median follow-up duration. Analysis using a fully adjusted statistical model demonstrated that mortality risk exhibited a progressive increase corresponding to elevated WWI values. RCS analysis revealed two distinct patterns: the relationship between WWI and all-cause mortality followed an inverted-U configuration, whereas cardiovascular mortality demonstrated a linear association with WWI. Survival analysis indicated that RA patients with lower WWI measurements demonstrated markedly improved survival outcomes. Further statistical testing through both sensitivity and subgroup analyses confirmed that these relationships remained robust across different population demographics. ROC curve analysis demonstrated that WWI surpasses both BMI and WC in predicting mortality among RA patients.</p> Conclusions <p>The study revealed that elevated WWI levels corresponded with increased all-cause and CVD mortality, suggesting its utility as a prognostic indicator in this population.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Association of weight-adjusted waist index with all-cause and cardiovascular disease mortality among rheumatoid arthritis population: a cohort study from the NHANES 1999–2018

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月1日

查看全文
  • Song Liu,
  • Siyuan Chen,
  • Yifeng Huang,
  • Qizhang Man,
  • Ying Yang,
  • Jinfeng Wen,
  • Hao Xie,
  • Lei Fan

摘要

Background

Rheumatoid arthritis (RA) represents a pressing global health challenge. While obesity is a controllable risk factor for RA patients, traditional body measurements like body mass index (BMI) have shown limitations in assessing risk. The weight-adjusted waist index (WWI), a new measurement method, provides better insight into belly fat distribution patterns. This research seeks to understand how WWI relates to both all-cause mortality and cardiovascular disease (CVD) mortality in people with RA.

Methods

Researchers conducted a longitudinal analysis examining participants diagnosed with RA using data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999–2018. The study introduced a novel anthropometric measure, WWI, by dividing the waist circumference (WC) measurement by the body weight’s square root. The main outcomes of this study were all-cause mortality and cardiovascular mortality. The research team employed several statistical approaches: multivariable Cox proportional hazards models, restricted cubic spline (RCS) analysis, and survival assessment through Kaplan-Meier (KM) analysis. The investigation accounted for confounding factors and incorporated both subgroup and sensitivity analyses to ensure result reliability. To evaluate the effectiveness of different indicators in predicting mortality, we conducted receiver operating characteristic (ROC) analyses.

Results

This investigation encompassed 2,564 qualified participants with 102 months as the median follow-up duration. Analysis using a fully adjusted statistical model demonstrated that mortality risk exhibited a progressive increase corresponding to elevated WWI values. RCS analysis revealed two distinct patterns: the relationship between WWI and all-cause mortality followed an inverted-U configuration, whereas cardiovascular mortality demonstrated a linear association with WWI. Survival analysis indicated that RA patients with lower WWI measurements demonstrated markedly improved survival outcomes. Further statistical testing through both sensitivity and subgroup analyses confirmed that these relationships remained robust across different population demographics. ROC curve analysis demonstrated that WWI surpasses both BMI and WC in predicting mortality among RA patients.

Conclusions

The study revealed that elevated WWI levels corresponded with increased all-cause and CVD mortality, suggesting its utility as a prognostic indicator in this population.