ArticleMedicine2020
Prevalence of and lifestyle factors associated with metabolic syndrome determined using multi-level models in Chinese adults from a cross-sectional survey.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Associations Between Metabolic Score for Visceral Fat and Venous Thromboembolism Among 118 619 Participants With Metabolic Syndrome: Insights From Epidemiology to Genetic Susceptibility.Journal of the American Heart Association · 2026Article
- Metabolic syndrome as a prognostic factor in advanced pancreatic cancer: a predictive model and chemotherapy evaluation.World journal of surgical oncology · 2025Article
- Correlation between obesity-related indices and hyperuricemia among the elderly population in China: A cross-sectional study.Medicine · 2025Article
- Serum amyloid beta 42 levels correlated with metabolic syndrome and its components.Frontiers in endocrinology · 2024Article
- Long-term prognostic value of macrophage migration inhibitory factor in ST-segment elevation myocardial infarction patients with metabolic syndrome after percutaneous coronary intervention.Frontiers in cardiovascular medicine · 2022Article
- Prevalence and Influencing Factors of Metabolic Syndrome among Adults in China from 2015 to 2017.Nutrients · 2021Article
- Impact ofMicroorganisms · 2021Review
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
People living in the same area are more likely to experience similar socioeconomic characteristics, which leads to cluster effect and influences the generalizability of data regarding metabolic syndrome (MetS). However, previous studies did not consider or adjust for the cluster effect of living circumstances. The aim of this study was to determine the prevalence of MetS and associated lifestyle factors in Chinese adults 18 to 80 years of age, using multi-level generalized estimation equation (GEE).The participants came from a large-scale cross-sectional population survey. A total of 28,062 participants underwent all the blood tests. Participants meeting at least 3 of the 5 diagnostic criteria were defined as having MetS. Multi-level GEE was used to evaluate the relationship between MetS and lifestyle covariates to control the cluster effect of living circumstances. Odds ratios (ORs) and their 95% confidence intervals (CIs) were used to assess the strength of each relationship.A total of 65.70% of the participants had at least 1 clinical feature of MetS, and 2926 were diagnosed with MetS (prevalence 14.03%). 32.74%, 18.93%, 10.25%, 3.25%, and 0.53% of the participants had 1, 2, 3, 4, and 5 components, respectively. The prevalence of MetS in men (12.31%) was lower than in women (15.57%). After controlling for the cluster effect of living circumstances, many demographic and lifestyle characteristics were associated with MetS. Overweight (OR = 1.670, 95%CI: 1.600-1.743), obesity (OR = 2.287, 95% CI: 2.136-2.449), current alcohol consumption (OR = 1.053, 95% CI: 1.020-1.086), physical labor (OR=1.070, 95% CI: 1.040-1.101), a high-salt diet (OR=1.040, 95% CI: 1.009-1.071), hyperuricemia (OR=1.264, 95% CI: 1.215-1.316), short sleep duration (OR=1.032, 95% CI: 1.009-1.055), and a family history of cardiovascular disease (OR=1.065, 95% CI: 1.019-1.113), or cerebrovascular disease (OR=1.055, 95% CI: 1.007-1.104) increased the risk of MetS. The risk of MetS increased 6.9% (OR = 1.069, 95% CI: 1.053-1.085) with each 5% increase in body fat percentage.MetS has become a serious public health challenge in China. Many lifestyle factors have been found to be closely associated with MetS, including obesity, a high-salt diet, alcohol consumption, and short sleep duration. Therefore, changes in lifestyle are very important for adults to reduce the prevalence of MetS.
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