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中年和老年人中肥胖指数与新发高尿酸血症之间的关联存在性别差异:一项全国性纵向研究。

Sex-specific differences in the associations between adiposity indices and incident hyperuricemia among middle-aged and older adults: a nationwide longitudinal study.

机构信息

College of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan, China.

Department of Dermatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Front Endocrinol (Lausanne). 2024 Feb 9;15:1336471. doi: 10.3389/fendo.2024.1336471. eCollection 2024.

DOI:10.3389/fendo.2024.1336471
PMID:38405154
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10884268/
Abstract

OBJECTIVE

Although obesity is a known risk for hyperuricemia (HUA), the associations between adiposity indices and incident HUA and whether sex-specific differences exist is still unknown. We aimed to investigate the associations between adiposity indices and incident HUA in a longitudinal study.

METHODS

Data from the China Health and Retirement Longitudinal Study (CHARLS) in 2011-2012 and 2015-2016 were used to conduct a cohort study. Participants aged ≥45 years without HUA at baseline were included in this study. Adiposity indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio body roundness index (BRI), conicity index (CI), lipid accumulation product (LAP) index, waist-to-height ratio (WHtR), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI), were calculated. Logistic analysis was used to analyze the association between adiposity indices and incident HUA risk stratified by gender. Receiver operating characteristic curve analysis was performed to evaluate the power of predictions for incident HUA.

RESULTS

Of 5,873 participants aged 59.0 ± 8.7 years enrolled in this study, 578 (9.8%) participants developed HUA during the 4-year follow-up period. After adjusting for confounding variables, LAP, VAI, and CVAI showed significant association with incident HUA. BMI, WC, WHtR, BRI, and CI were significantly associated with incident HUA in women but not in men. LAP had the highest area under the curve (AUC) (0.612) followed by CVAI (0.596) in men, while CVAI had the highest AUC (0.707) followed by LAP (0.691) in women. All indices showed better predictive ability in women than in men.

CONCLUSION

Our findings indicated that adiposity indices were effective predictors of incident HUA and showed better predictive power in women than men. In clinical practice, adiposity indices could be used to assess and prevent incident HUA among Chinese middle-aged and older adults.

摘要

目的

尽管肥胖是高尿酸血症(HUA)的已知危险因素,但肥胖指数与 HUA 发病之间的关系以及是否存在性别特异性差异尚不清楚。本研究旨在通过一项纵向研究来探讨肥胖指数与 HUA 发病之间的关系。

方法

本研究使用了中国健康与养老追踪调查(CHARLS)2011-2012 年和 2015-2016 年的数据进行队列研究。本研究纳入了基线时无 HUA 的年龄≥45 岁的参与者。计算了体重指数(BMI)、腰围(WC)、腰高比体圆指数(BRI)、锥度指数(CI)、脂质蓄积产物(LAP)指数、腰高比(WHtR)、内脏脂肪指数(VAI)和中国内脏脂肪指数(CVAI)等肥胖指数。采用 Logistic 分析对性别分层的肥胖指数与 HUA 发病风险之间的关系进行分析。采用受试者工作特征曲线(ROC)分析评估对 HUA 发病的预测能力。

结果

在这项研究中,纳入了 5873 名年龄为 59.0±8.7 岁的参与者,其中 578 名(9.8%)参与者在 4 年的随访期间发生了 HUA。在调整了混杂因素后,LAP、VAI 和 CVAI 与 HUA 发病显著相关。BMI、WC、WHtR、BRI 和 CI 与女性的 HUA 发病显著相关,但与男性无关。LAP 在男性中的曲线下面积(AUC)最高(0.612),其次是 CVAI(0.596),而 CVAI 在女性中的 AUC 最高(0.707),其次是 LAP(0.691)。所有指数在女性中的预测能力均优于男性。

结论

本研究结果表明,肥胖指数是 HUA 发病的有效预测指标,在女性中的预测能力优于男性。在临床实践中,肥胖指数可用于评估和预防中国中老年人群的 HUA 发病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/4613fe8195f9/fendo-15-1336471-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/8dcf60849a6e/fendo-15-1336471-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/37708eefafeb/fendo-15-1336471-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/e76199927a12/fendo-15-1336471-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/4613fe8195f9/fendo-15-1336471-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/8dcf60849a6e/fendo-15-1336471-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/37708eefafeb/fendo-15-1336471-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/e76199927a12/fendo-15-1336471-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7028/10884268/4613fe8195f9/fendo-15-1336471-g004.jpg

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