| ORIGINAL ARTICLE |
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| Year : 2021 | Volume
: 5
| Issue : 1 | Page : 24-29 |
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Prevalence and correlates of metabolic syndrome in severe mental illness: A cross-sectional survey of inpatients at a tertiary care institute
Akshada Suresh Sabnis1, Anil Rane1, Abhijit Nadkarni2
1 Institute of Psychiatry and Human Behaviour, Bambolim, Goa, India, India
2 Tertiary Care Psychiatry Hospital, London School of Hygiene and Tropical Medicine, London, UK
Correspondence Address:
Dr. Akshada Suresh Sabnis
Institute of Psychiatry and Human Behaviour, Bambolim - 403 202, Goa,
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/aip.aip_117_20
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Background: People with severe mental illness (SMI) die prematurely. They also have disproportionately high burden of diabetes, dyslipidemia, and obesity, which is further compounded by unhealthy lifestyle such as sedentary behavior and substance use. Consequently, there is a high prevalence of metabolic syndrome (MetS) in this population. MetS has been reported in 10%–50% of SMI patients, but its risk factors have been poorly studied. Aims: The aim of the study is to assess the prevalence and correlates of MetS in SMI. Methodology: A cross-sectional study at a tertiary care psychiatry hospital was conducted. A total of 304 consecutive inpatients with SMI were administered the WHO-STEPS-2 questionnaire, Brief Psychiatric Rating Scale, and World Health Organization Disability Assessment Schedule (WHODAS); and biochemical measures such as lipid and blood sugar levels were measured. Summary statistics (means and proportions) were described, followed by univariate and multivariate analyses to examine the associations between variables. Results: 25.7% of SMI patients had diabetes mellitus and 43.09% had elevated cholesterol; 23.4% (95% confidence interval 18.6–28.1) had MetS and it was associated with age (P < 0.01), female gender (P < 0.001), being married (P < 0.01), weight (P < 0.001), body mass index (P < 0.001), waist and hip circumference (P < 0.001), and duration of psychiatric illness (P < 0.001). On multivariate analyses, only age (P = 0.002), female gender (P < 0.001), body weight (P < 0.001), abnormal waist to hip ratio (W: H ratio) (P = 0.02), and lower use of alcohol (P = 0.01) were significantly associated with MetS. Conclusion: Patients with SMI have a high burden of cardiometabolic risk factors. Monitoring of traditional risk factors such as W: H ratio is an important and cheap option to screen for risk of MetS.
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