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Metabolic syndrome and associated factors among severely ill psychiatric and non-psychiatric patients: a comparative cross-sectional study in Eastern Ethiopia

BACKGROUND: Metabolic syndrome is a major public health challenge in both developed and developing countries. The burden of this disease is high, even in patients with psychiatric disorders. However, very little is known about the association between metabolic syndrome and psychiatric illness in Eth...

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Detalles Bibliográficos
Autores principales: Fentie, Dilnessa, Derese, Tariku, Yazie, Bekele, Getachew, Yibeltal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579653/
https://www.ncbi.nlm.nih.gov/pubmed/34758878
http://dx.doi.org/10.1186/s13098-021-00750-4
Descripción
Sumario:BACKGROUND: Metabolic syndrome is a major public health challenge in both developed and developing countries. The burden of this disease is high, even in patients with psychiatric disorders. However, very little is known about the association between metabolic syndrome and psychiatric illness in Ethiopia. Therefore, the aim of this study was to investigate the magnitude of metabolic syndrome and its components among psychiatric clients. METHODS: A comparative cross-sectional study was undertaken between psychiatric patients and age—and sex-matched non-psychiatric controls at the Dilchora referral hospital. The study included 192 study participants (96 psychiatric patients and 96 non- psychiatric controls from general medical and surgical patients). The National Cholesterol Education Program: Adult Treatment Panel III criteria were used to diagnose metabolic syndromes. The data were cleaned and analyzed using the Statistical Package for Social Sciences, Version 21. All intergroup comparisons for continuous data were performed using an independent sample t-test, whereas categorical data were analyzed using the Chi-square test. Logistic regression analysis was used to identify the association between metabolic syndrome and the associated variables. RESULTS: The magnitude of metabolic syndrome among psychiatric patients was 36.5% (95%CI: 27.6, 47.4) compared to non-psychiatric control patients, 21.9% (95%CI: 13.5, 30.3), p = 0.02. The prevalence of MetS components, such as waist circumference (25.0% vs. 14.3%), lower-high density lipoprotein level (35.4% vs. 20.8%), higher systolic blood pressure (41.7% vs. 29.2%) and higher fasting blood glucose (40.6% vs. 18.8%) showed statistically significant differences between the exposed and non-exposed groups. Age greater than 50 years (AOR: 2.8, CI: 1.14, 20.0, p < 0.05); being female (AOR: 7.4, CI: 2.0, 27.6, p < 0.05), being urban residence (AOR: 6.4, CI: 2.2, 20.6, p < 0.05), ever alcohol intake (AOR: 5.3, CI: 1.3, 21.2), being physically inactive (AOR: 3.52, CI: 1.1, 12.9, p < 0.05) and family history of hypertension (AOR: 2.52, CI: 1.1, 12.2, p < 0.05) were independent predictors of metabolic syndrome (p < 0.05). CONCLUSIONS: There is a high burden of metabolic syndrome and its components in patients with severe psychiatric disorders. Therefore, screening and mitigation strategies for metabolic syndrome and their components should be implemented in the management of psychiatric disorders.