Student research committee, Shiraz University of Medical Sciences, Shiraz, Iran.
Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
BMC Endocr Disord. 2021 Mar 22;21(1):54. doi: 10.1186/s12902-021-00716-7.
The assessment of the natural history of metabolic syndrome (MetS) has an important role in clarifying the pathways of this disorder.
This study purposed to provide a rational statistical view of MetS progression pathway.
We performed a systematic review in accordance with the PRISMA Statement until September 2019 in the Medline/PubMed, Scopus, Embase, Web of Science and Google Scholar databases. From the 68 found studies, 12 studies were eligible for review finally.
The selected studies were divided in 2 groups with Markovian and non-Markovian approach. With the Markov approach, the most important trigger for the MetS chain was dyslipidemia with overweight/obesity in the under-50 and with hypertension in the over-50 age group, where overweight/obesity was more important in women and hypertension in men. In non-Markov approach, the most common trigger was hypertension. Transition probability (TP) from no component to MetS were higher in all Markovian studies in men than in women. In the Markovians the combination of dyslipidemia with overweight/obesity and in non-Markovians, hyperglycemia with overweight/obesity were the most common combinations. Finally, the most important components, which predict the MetS, were 2-component states and hyperglycemia in Markovian approach and overweight/obesity in non-Markovians.
Among the components of the MetS, dyslipidemia and hypertension seems to be the main developer components in natural history of the MetS. Also, in this chain, the most likely combination over time that determines the future status of people seems to be the combination of dyslipidemia with obesity or hyperglycemia. However, more research is needed.
代谢综合征(MetS)自然史的评估对于阐明该疾病的发病途径具有重要作用。
本研究旨在为 MetS 进展途径提供合理的统计观点。
我们按照 PRISMA 声明进行了系统综述,检索了截至 2019 年 9 月的 Medline/PubMed、Scopus、Embase、Web of Science 和 Google Scholar 数据库。从 68 项研究中,最终有 12 项研究符合纳入标准。
入选的研究分为 Markov 模型和非 Markov 模型两组。采用 Markov 模型,MetS 链的最重要触发因素是超重/肥胖伴血脂异常(50 岁以下人群)和高血压(50 岁以上人群),超重/肥胖在女性中更为重要,而高血压在男性中更为重要。采用非 Markov 模型,最常见的触发因素是高血压。所有 Markov 模型研究中,男性发生无任何成分向 MetS 转变的转移概率(TP)均高于女性。在 Markov 模型中,血脂异常伴超重/肥胖和非 Markov 模型中,高血糖伴超重/肥胖是最常见的组合。最后,在 Markov 模型中,预测 MetS 的最重要成分是 2 成分状态和高血糖,而非 Markov 模型中则是超重/肥胖。
在 MetS 的各个成分中,血脂异常和高血压似乎是 MetS 自然史中的主要发展成分。此外,在这条链中,随着时间的推移,最有可能决定人们未来状态的组合似乎是血脂异常与肥胖或高血糖的组合。然而,还需要更多的研究。