ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023
Incidence of Metabolic Syndrome and Its Risk Factors in Elderly with Nonalcoholic Fatty Liver Disease.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Multistate markov model analysis of metabolic syndrome progression in a community-based longitudinal cohort study.Diabetology & metabolic syndrome · 2026Article
- MicroRNAs as Key Regulators in the Progression of Metabolic Dysfunction-Associated Steatotic Liver Disease: A Bioinformatics Analysis.Biomedicines · 2026Article
- Four-years change of BMI and waist circumference are associated with metabolic syndrome in middle-aged and elderly Chinese.Scientific reports · 2024Article
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4 authors.
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Abstract
Purpose: This study aimed to determine the incidence of metabolic syndrome (MetS) and its predictors in older patients with nonalcoholic fatty liver disease. Patients and Methods: This retrospective cohort study analyzed repeated health surveillance data collected between 2009 and 2018 at Mackay Memorial Hospital, Taiwan. MetS was defined based on the modified National Cholesterol Education Program Adult Treatment Panel III (Taiwan revision). Participants were diagnosed with fatty liver disease using abdominal ultrasonography. The exclusion criteria included age <65 years, having viral hepatitis, frequent alcohol consumption, and pre-existing MetS. Logistic regression analysis was conducted, adjusting for sex and age. Results: We enrolled 758 older participants; 457 (60.3%) with preexisting metabolic syndrome were excluded. We studied the remaining 301 participants (39.7%), with a mean age of 71.3 ± 5.4 years. The cumulative incidence of MetS was 43.5% after a mean follow-up period of 4.2 years; moreover, it was higher in women as well as in participants with diabetes and hypertriglyceridemia. After adjusting for age and sex, we identified the following risk factors for MetS: baseline high fasting plasma glucose levels (adjusted odds ratio [aOR] =1.75; 95% confidence interval [CI] 1.03-2.95), baseline hypertriglyceridemia (aOR = 2.26; 95% CI 1.15-4.47), and baseline large waist circumference (aOR =1.71; 95% CI 1.01-2.89). Furthermore, increased waist circumference and fasting plasma glucose levels at follow-up were significant risk factors. Conclusion: There is a high incidence of MetS among older individuals with nonalcoholic fatty liver disease; further, women and individuals with diabetes or hypertriglyceridemia are at risk of developing MetS. Moreover, waist circumference and fasting plasma glucose levels were positively associated with the risk of MetS.
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