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Prevalence and predictors of metabolic syndrome in schizophrenia patients from Assam
Dulmoni Das1,2, Kaustubh Bora3,4, Banti Baruah1
1Department of Mental Health Nursing, Regional College of Nursing, Guwahati, Assam.
Background:
Metabolic abnormalities contribute enormously to morbidity and mortality in schizophrenia.
Objectives:
Our objectives were to determine the (i) prevalence of metabolic syndrome (MS); and (ii) predictors for MS in schizophrenia patients from Assam.
Materials And Methods:
Seventy-five schizophrenia patients were evaluated for MS. Risk factors were assessed by odds ratios (ORs) with 95% confidence intervals (CIs).
Results:
Fifty-nine patients (78.7%) had a metabolic abnormality. Twenty-two patients (29.3%, 95% CI: 19.9%-40.8%) fulfilled the criteria for MS. Female gender (adjusted OR = 7.8, 95% CI: 1.7-36.4), smoking (adjusted OR = 7.9, 95% CI: 1.7-35.8), family history of chronic lifestyle disease (adjusted OR = 4.4, 95% CI: 1.3-15.2), and atypical antipsychotic use (adjusted OR = 4.3, 95% CI: 1.1-16.9) significantly predicted MS.
Conclusion:
Metabolic abnormalities exist widely in schizophrenics from Assam. Females, smokers, and those with family history of chronic diseases and using atypical antipsychotics are at greater risk.
Insights
Metabolic syndrome is common in schizophrenia patients in Assam, affecting nearly 30%. Female gender, smoking, family history of chronic disease, and atypical antipsychotic use are key predictors.
Area of Science:
- Psychiatry
- Metabolic Health
- Epidemiology
Background:
- Metabolic abnormalities significantly increase morbidity and mortality in schizophrenia patients.
- Understanding these metabolic issues is crucial for improving patient outcomes.
Purpose of the Study:
- To determine the prevalence of metabolic syndrome (MS) in schizophrenia patients from Assam.
- To identify predictors associated with MS in this population.
Main Methods:
- A cross-sectional study evaluated 75 schizophrenia patients for metabolic syndrome.
- Risk factors were assessed using odds ratios (ORs) and 95% confidence intervals (CIs).
Main Results:
- A high prevalence of metabolic abnormalities was observed, with 78.7% of patients affected.
- 29.3% of patients met the criteria for metabolic syndrome.
- Significant predictors for MS included female gender, smoking, family history of chronic lifestyle disease, and atypical antipsychotic use.
Conclusions:
- Metabolic abnormalities are widespread among schizophrenia patients in Assam.
- Females, smokers, individuals with a family history of chronic diseases, and those on atypical antipsychotics face a higher risk of MS.