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人体测量指数与中老年人群多种疾病发生发展的相关性:一项回顾性队列研究。

Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study.

机构信息

Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.

Department of pharmacy, Zhengzhou people's hospital, Zhengzhou, Henan, People's Republic of China.

出版信息

PLoS One. 2022 Oct 14;17(10):e0276216. doi: 10.1371/journal.pone.0276216. eCollection 2022.

DOI:10.1371/journal.pone.0276216
PMID:36240163
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9565419/
Abstract

BACKGROUND

Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study.

METHODS

Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity.

RESULTS

A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m2 and WC≥90 (men)/80 (women) group and BMI≥24 kg/m2 and WC≥90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC≥90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18).

CONCLUSIONS

Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.

摘要

背景

先前的研究探讨了体重指数(BMI)与多种疾病之间的关系。然而,其他肥胖指标与它们的动态变化及与多种疾病之间的关系尚未得到系统评估。因此,我们旨在通过回顾性队列研究,调查 BMI 及其他肥胖指标(包括腰围、腰高比、腰围除以身高 0.5、体圆度指数)及其变化与中年及老年人多种疾病风险之间的关联。

方法

本研究的数据来自 2017 年至 2021 年金水地区年度健康检查数据集。使用 Cox 回归模型计算风险比(HR)和 95%置信区间(CI),以评估基线和人体测量指标动态变化对多种疾病风险的影响。

结果

本研究共纳入 75028 名参与者,5886 名参与者在随访期间发生多种疾病。多变量 Cox 回归分析显示,随着人体测量指标(BMI、腰围、腰高比、腰围除以身高 0.5 和体圆度指数)的增加,多种疾病的风险呈递增趋势(均 P<0.001)。无论基线时的一般肥胖状况如何,腰围增加与多种疾病的高风险相关。与基线 BMI<24kg/m2 和 WC<90(男性)/80(女性)的受试者相比,BMI<24kg/m2 和 WC≥90(男性)/80(女性)组和 BMI≥24kg/m2 和 WC≥90(男性)/80(女性)组的 HR(95%CI)分别为 1.31(1.08,1.61)和 1.82(1.68,1.97)。此外,腰围的动态变化可以反映多种疾病的风险。当基线 WC<90(男性)/80(女性)的受试者在随访期间进展为 WC≥90(男性)/80(女性)时,多种疾病的风险显著增加(HR=1.78;95%CI,1.64,1.95),而基线时 WC 异常但随访时恢复正常的受试者的多种疾病风险较随访时 WC 仍异常的受试者(HR=2.00;95%CI,1.82,2.18)有所降低(HR=1.40;95%CI,1.26,1.54)。

结论

中心性肥胖是中年和老年人群多种疾病发生的独立且可改变的危险因素。除了 BMI 的临床测量外,中心性肥胖指标 WC 的测量可能为识别中国中年和老年人群的多种疾病提供额外的益处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/3bb6aac01194/pone.0276216.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/fcb62920e06d/pone.0276216.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/b0ea41e0f6f0/pone.0276216.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/3bb6aac01194/pone.0276216.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/fcb62920e06d/pone.0276216.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/b0ea41e0f6f0/pone.0276216.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c47/9565419/3bb6aac01194/pone.0276216.g003.jpg

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