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较高的体重指数会增加新型冠状病毒肺炎的严重程度吗?一项系统评价与荟萃分析。

Does higher body mass index increase COVID-19 severity? A systematic review and meta-analysis.

作者信息

Chowdhury Akibul Islam, Alam Mohammad Rahanur, Rabbi Md Fazley, Rahman Tanjina, Reza Sompa

机构信息

Department of Food Technology and Nutrition Science, Noakhali Science and Technology University, Bangladesh.

Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Bangladesh.

出版信息

Obes Med. 2021 May;23:100340. doi: 10.1016/j.obmed.2021.100340. Epub 2021 Apr 15.

Abstract

INTRODUCTION

Obesity and higher BMI is one of the leading comorbidities to increase the risk of COVID-19 severity. This paper presents a systematic review and meta-analysis estimating the effects of overweight and obesity on COVID-19 disease severity.

METHOD

Two electronic databases (Medline and Cochrane library) and one grey literature database (Grey Literature Report) were searched. The risks of bias of the selected studies were assessed by using the Navigation Guide method for human data. Both random and fixed effect meta-analyses were determined using Review Manager (RevMan) software version 5.4.

RESULTS

After initial screening, 12 studies were fulfilled the eligibility criteria, comprising a total of 405359 patients, and included in the systematic review. The pooled risk of COVID-19 severity was 1.31 times higher based on both fixed and random effect model among those overweight patients, 0% and 2.09 and 2.41 times higher based on fixed and random effect respectively among obese patients, 42% compared to healthy individuals.

CONCLUSION

Overweight and obesity are found to be risk factors for disease severity of COVID-19 patients. However, further assessment of metabolic parameters is required to estimate the risk factors of COVID-19 patients and understanding the mechanism between COVID-19 and body mass index.

摘要

引言

肥胖和较高的体重指数是增加新冠病毒疾病严重程度风险的主要合并症之一。本文进行了一项系统综述和荟萃分析,以评估超重和肥胖对新冠病毒疾病严重程度的影响。

方法

检索了两个电子数据库(Medline和Cochrane图书馆)和一个灰色文献数据库(灰色文献报告)。使用针对人类数据的导航指南方法评估所选研究的偏倚风险。使用Review Manager(RevMan)5.4版软件进行随机和固定效应荟萃分析。

结果

初步筛选后,12项研究符合纳入标准,共纳入405359例患者,并纳入系统综述。在超重患者中,基于固定效应模型和随机效应模型,新冠病毒疾病严重程度的合并风险分别高出1.31倍;在肥胖患者中,基于固定效应模型和随机效应模型,分别高出2.09倍和2.41倍,与健康个体相比分别高出42%。

结论

超重和肥胖被发现是新冠病毒患者疾病严重程度的危险因素。然而,需要进一步评估代谢参数,以估计新冠病毒患者的危险因素,并了解新冠病毒与体重指数之间的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b659/8046705/2530bc155193/gr1_lrg.jpg

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