Literature DB >> 30641722

Frequency of metabolic syndrome and its associated factors in health care workers.

Elnaz Niazi1, Maryam Saraei2, Omid Aminian3, Nazanin Izadi4.   

Abstract

BACKGROUND: In recent decades, metabolic syndrome is one of the most important public health risk factors. Having this in mind, the present study was conducted to evaluate the frequency of metabolic syndrome and its associated risk factors in healthcare workers.
METHOD: This study is a cross-sectional study conducted on 410 healthcare workers in a teaching hospital in Iran. Demographic, occupational, and psychosocial characteristics were assessed using questionnaire. Assessment of metabolic syndrome of hospital staff was performed at workplace during their medical examination.
RESULTS: The frequency of metabolic syndrome was found to be 22.4%. This relationship was found among blood pressure and occupational stress, despite the fact that there was no significant relationship between metabolic syndrome and occupational stress. Higher age, having shift work, and inactivity were associated with metabolic syndrome.
CONCLUSION: Considering the high frequency of metabolic syndrome among Iranian healthcare workers, it is advised that effective management should be employed to correct the occupational and psychosocial factors associated with this syndrome.
Copyright © 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Health care worker; Metabolic syndrome; Occupational stress

Mesh:

Year:  2018        PMID: 30641722     DOI: 10.1016/j.dsx.2018.10.013

Source DB:  PubMed          Journal:  Diabetes Metab Syndr        ISSN: 1871-4021


  4 in total

1.  Metabolic and Obesity Phenotype Trajectories in Taiwanese Medical Personnel.

Authors:  Hsin-Yun Chang; Jer-Hao Chang; Yin-Fan Chang; Chih-Hsing Wu; Yi-Ching Yang
Journal:  Int J Environ Res Public Health       Date:  2022-07-04       Impact factor: 4.614

2.  Effects of diet versus diet plus aerobic and resistance exercise on metabolic syndrome in obese young men.

Authors:  Mohamed Ahmed Said; Mohamed Abdelmoneem; Mohamed Chaab Alibrahim; Moustafa Ahmed Elsebee; Ahmed Abdel Hamed Kotb
Journal:  J Exerc Sci Fit       Date:  2020-03-14       Impact factor: 3.103

3.  Machine learning-aided risk prediction for metabolic syndrome based on 3 years study.

Authors:  Haizhen Yang; Baoxian Yu; Ping OUYang; Xiaoxi Li; Xiaoying Lai; Guishan Zhang; Han Zhang
Journal:  Sci Rep       Date:  2022-02-10       Impact factor: 4.379

Review 4.  Shift work and the risk for metabolic syndrome among healthcare workers: A systematic review and meta-analysis.

Authors:  Piumika Sooriyaarachchi; Ranil Jayawardena; Toby Pavey; Neil A King
Journal:  Obes Rev       Date:  2022-06-22       Impact factor: 10.867

  4 in total

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