Vikram Singh Rawat1, Suhas Ganesh2, Somashekar Bijjal3, K Shanivaram Reddy4, Vikas Agarwal2, Renuka Devi2, Chennaveerachari Naveen Kumar5, Rita Christopher6, Jagadisha Thirthalli2. 1. Department of Psychiatry, All India Institute of Medical Sciences, Rishikesh, India. 2. Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bengaluru, India. 3. Dharwad Institute of Mental Health and Neuro Sciences, India. 4. Psychiatric rehabilitation services unit, National Institute of Mental Health and Neuro Sciences, India. 5. Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bengaluru, India. Electronic address: nkumar@nimhans.ac.in. 6. Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bengaluru, India.
Abstract
INTRODUCTION: Metabolic syndrome (MetS) has been extensively studied as a co-morbidity in patients with schizophrenia. A disparity is noted between hospital and community based estimates in India. We aimed to examine the prevalence and predictors of MetS in schizophrenia patients and general population controls in a rural population in South India. METHODS: Patients (n=157) and general population controls (n=263) were recruited from a rural area in South India. Diagnosis of MetS was established using International Diabetes Federation (IDF) criteria. Patients were also assessed on clinical parameters, treatment details, dietary and physical activity patterns. Predictors of MetS were estimated based on subgrouping of patients with and without MetS. RESULTS: 50 (31.8%) of the patients and 76 (28.9%) of the controls were diagnosed to have MetS. Female gender and ongoing antipsychotic exposure were noted to be significant predictors of MetS with odds ratio (95% confidence interval) of 2.87 (1.2-6.86) and 4.42 (1.37-14.25) respectively. Three empirically defined treatment groups 'never treated', 'ever treated' and 'continuous treatment' groups had odds ratios (95% CI) of 0.53 (1.68-6.58), 0.92 (0.5-1.69) and 3.33 (1.68-6.58) when compared to the control group. CONCLUSIONS: Patients who were naïve to antipsychotics had a significantly lower prevalence of MetS compared to general population. This finding doesn't support the antipsychotic independent risk for MetS in patients with schizophrenia. Female gender and regular antipsychotic exposure predicted MetS.
INTRODUCTION:Metabolic syndrome (MetS) has been extensively studied as a co-morbidity in patients with schizophrenia. A disparity is noted between hospital and community based estimates in India. We aimed to examine the prevalence and predictors of MetS in schizophreniapatients and general population controls in a rural population in South India. METHODS:Patients (n=157) and general population controls (n=263) were recruited from a rural area in South India. Diagnosis of MetS was established using International Diabetes Federation (IDF) criteria. Patients were also assessed on clinical parameters, treatment details, dietary and physical activity patterns. Predictors of MetS were estimated based on subgrouping of patients with and without MetS. RESULTS: 50 (31.8%) of the patients and 76 (28.9%) of the controls were diagnosed to have MetS. Female gender and ongoing antipsychotic exposure were noted to be significant predictors of MetS with odds ratio (95% confidence interval) of 2.87 (1.2-6.86) and 4.42 (1.37-14.25) respectively. Three empirically defined treatment groups 'never treated', 'ever treated' and 'continuous treatment' groups had odds ratios (95% CI) of 0.53 (1.68-6.58), 0.92 (0.5-1.69) and 3.33 (1.68-6.58) when compared to the control group. CONCLUSIONS:Patients who were naïve to antipsychotics had a significantly lower prevalence of MetS compared to general population. This finding doesn't support the antipsychotic independent risk for MetS in patients with schizophrenia. Female gender and regular antipsychotic exposure predicted MetS.
Authors: Elena G Kornetova; Alexander N Kornetov; Irina A Mednova; Anastasia A Goncharova; Valeria I Gerasimova; Ivan V Pozhidaev; Anastasiia S Boiko; Arkadiy V Semke; Anton J M Loonen; Nikolay A Bokhan; Svetlana A Ivanova Journal: Front Psychiatry Date: 2021-07-02 Impact factor: 4.157
Authors: Narayana Manjunatha; Channaveerachari Naveen Kumar; Kalaivanan Rakesh Chander; Kamaldeep Sadh; Guru S Gowda; B Vinay; H N Shashidhara; Rajani Parthasarathy; Girish N Rao; Suresh Bada Math; Jagadisha Thirthalli Journal: Indian J Psychiatry Date: 2019 Nov-Dec Impact factor: 1.759