Study from the United States: increased prevalence of kidney stones in patients with high weight-adjusted waist index.

Zhaohua Gui, Longshan Yu,Yan Chen,Mingxun Zhang,Jie He,Yunwu Hao

Frontiers in Nutrition(2024)

引用 0|浏览1
暂无评分
摘要
Objective:Using data from NHANES 2007-2018, to examine the association between WWI (weight-adjusted waist index) index and prevalence of kidney stones. Methods:Using multiple logistic regression analysis of the National Health and Nutrition Examination Survey (NHANES) 2007-2018, we evaluated the association between WWI index and the prevalence of kidney stones, followed by subgroup analysis of sensitive populations. Smooth curve fitting was used to determine whether there was a non-linear relationship between the WWI index and kidney stone prevalence, and threshold effect analysis was used to test this relationship. Results:Among 29,280 participants, 2,760 self-reported renal calculi. After adjustment for all confounders, there was a positive association between WWI and kidney stone prevalence (OR = 1.20, 95% CI: 1.12, 1.28), and this positive association was stronger with increasing WWI (and P = 0.01 for trend). Our results indicate a non-linear positive correlation between WWI index and kidney stones, with the saturation threshold effect analysis and the most important threshold value at 11.02. According to subgroup analysis, WWI showed the strongest association with kidney stone prevalence in participants aged 20-39 years, males, other US ethnic groups, and participants without hypertension and diabetes. Conclusion:Increased WWI is positively associated with increased incidence of kidney stones, and increased WWI is a high risk for kidney stones that should be treated with caution. This association should be more pronounced in people between the ages of 20 and 39 years, in men, in other US ethnic populations, and in participants who do not have hypertension or diabetes.
更多
查看译文
关键词
kidney stone prevalence,weight-adjusted waist index (WWI),NHANES,cross-sectional study,visceral obesity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要