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低收入和中等收入国家儿童及青少年的代谢综合征:一项系统评价与荟萃分析

Metabolic syndrome among children and adolescents in low and middle income countries: a systematic review and meta-analysis.

作者信息

Bitew Zebenay Workneh, Alemu Ayinalem, Ayele Ermias Getaneh, Tenaw Zelalem, Alebel Anmut, Worku Teshager

机构信息

St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia.

Ethipian Public Health Institute, Addis Ababa, Ethiopia.

出版信息

Diabetol Metab Syndr. 2020 Oct 27;12:93. doi: 10.1186/s13098-020-00601-8. eCollection 2020.

DOI:10.1186/s13098-020-00601-8
PMID:33117455
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7590497/
Abstract

BACKGROUND

Metabolic syndrome (MetS) is a clustering of cardiovascular risk factors, which is rising in the low and middle income countries (LMICs). There are various studies with inconsistent findings that are inconclusive for policy makers and program planners. Thus, this systematic review and meta-analysis aimed at estimating the pooled prevalence of MetS and its components in LMICs.

METHODS

Electronic searches were conducted in international databases including PubMed, Web of Science, EMBASE (Elsevier), Scopus, CINAHL (EBSCOhost), Science direct (Elsevier), Food Science and Technology Abstracts (FSTA), Global Health and Medline, and other sources (World Cat, Google Scholar, and Google). The pooled estimates were computed in the random effect model. The pooled prevalence was computed using the three diagnostic methods (IDF, ATP III and de Ferranti). Publication bias was verified using funnel plot and Egger's regression test. Subgroup and sensitivity analysis were performed to identify the possible sources of heterogeneity among the included studies.

RESULT

In this study, 142,142 children and adolescents from 76 eligible articles were included to compute the pooled prevalence of MetS and its components in LMCIs. MeTs among overweight and obese population was computed from 20 articles with the pooled prevalence of 24.09%, 36.5%, and 56.32% in IDF, ATP III and de Ferranti criteria, respectively. Similarly, a total of 56 articles were eligible to compute the pooled prevalence of MetS in the general population of children and adolescents. Hence, Mets was found in 3.98% (IDF), 6.71% (ATP III) and 8.91% (de Ferranti) of study subjects. Regarding the components of MetS, abdominal obesity was the major component in overweight and obese population and low HDL-C was the most common component in the general population. This study also revealed that males were highly affected by MetS than females.

CONCLUSION

This study illustrates that MetS among children and adolescents is an emerging public health challenge in LMICs, where the prevalence of obesity is on the move. Preventive strategies such as community and school based intervention need to be designed. Promoting physical activities and healthy eating behaviors could avert this problem.

摘要

背景

代谢综合征(MetS)是心血管危险因素的聚集,在低收入和中等收入国家(LMICs)呈上升趋势。有各种研究结果不一致,这对政策制定者和项目规划者来说尚无定论。因此,本系统评价和荟萃分析旨在估计LMICs中MetS及其组成部分的合并患病率。

方法

在包括PubMed、科学网、EMBASE(爱思唯尔)、Scopus、CINAHL(EBSCOhost)、科学Direct(爱思唯尔)、食品科学与技术文摘(FSTA)、全球健康和Medline等国际数据库以及其他来源(世界Cat、谷歌学术和谷歌)进行电子检索。采用随机效应模型计算合并估计值。使用三种诊断方法(IDF、ATP III和de Ferranti)计算合并患病率。使用漏斗图和Egger回归检验验证发表偏倚。进行亚组和敏感性分析以确定纳入研究中异质性的可能来源。

结果

在本研究中,纳入了来自76篇符合条件文章的142142名儿童和青少年,以计算LMICs中MetS及其组成部分的合并患病率。从20篇文章中计算出超重和肥胖人群中的MetS,根据IDF、ATP III和de Ferranti标准,合并患病率分别为24.09%、36.5%和56.32%。同样,共有56篇文章符合计算儿童和青少年普通人群中MetS合并患病率的条件。因此,在3.98%(IDF)、6.71%(ATP III)和8.91%(de Ferranti)的研究对象中发现了MetS。关于MetS的组成部分,腹部肥胖是超重和肥胖人群中的主要组成部分,而低HDL-C是普通人群中最常见的组成部分。本研究还表明,男性比女性受MetS的影响更大。

结论

本研究表明,在肥胖患病率不断上升的LMICs中,儿童和青少年中的MetS是一个新出现的公共卫生挑战。需要设计社区和学校干预等预防策略。促进体育活动和健康饮食行为可以避免这个问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/9fceabc5fd4a/13098_2020_601_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/c26b32a91d7c/13098_2020_601_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/442405af3bbe/13098_2020_601_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/1dadea869e4f/13098_2020_601_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/9fceabc5fd4a/13098_2020_601_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/c26b32a91d7c/13098_2020_601_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/68a4b9a138b1/13098_2020_601_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/5c1d2b1a00bb/13098_2020_601_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/1c0f0678ae5b/13098_2020_601_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/442405af3bbe/13098_2020_601_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/73720772adf0/13098_2020_601_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/1dadea869e4f/13098_2020_601_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f00/7590497/9fceabc5fd4a/13098_2020_601_Fig8_HTML.jpg

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