ArticleNeuropsychiatric disease and treatment2020
Predictive Utility of Body Mass Index for Metabolic Syndrome Among Patients with Schizophrenia in Japan.
Article in Neuropsychiatric disease and treatment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Prevalence and predictors of metabolic syndrome among psychiatric patients receiving antipsychotic treatment in Africa: a systematic review and meta-analysis.BMC psychiatry · 2025Pooled it
- Relationship Between Family Support, C-Reactive Protein and Body Mass Index Among Outpatients with Schizophrenia.Healthcare (Basel, Switzerland) · 2025Article
- The Association Between Obesity Measures and Metabolic Syndrome Risk in Korean Adolescents Aged 10-18 Years.Journal of multidisciplinary healthcare · 2024Article
- Machine Learning Algorithm-Based Prediction Model for the Augmented Use of Clozapine with Electroconvulsive Therapy in Patients with Schizophrenia.Journal of personalized medicine · 2022Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundReliable and easy screening for metabolic syndrome (MetS) is important for patients with schizophrenia. The aim of this study was to assess the predictive utility of body mass index (BMI) for MetS among patients with schizophrenia in Japan.
methodsIn total, 8468 patients (4705 males, 3763 females) with schizophrenia or schizoaffective disorders based on the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV), or the International Classification of Diseases, tenth revision (ICD-10), were assessed for MetS using the criteria of the National Cholesterol Education Program Adult Treatment Panel III (ATP III-A). We applied a stratum-specific likelihood ratio (SSLR) analysis, which is independent of the prevalence of the target disease.
resultsThe mean (± standard deviation) age of these patients was 57.4 ± 13.5 years. The prevalence of MetS was 20.4%. Among males, the SSLRs predicting MetS were 0.03 (95% CI 0.02-0.06), 0.54 (95% CI 0.48-0.60), 2.77 (95% CI 2.44-3.14) and 8.75 (95% CI 7.40-10.36) for BMI <20 kg/m
conclusionThe predictive utility of BMI is confirmed, and BMI has more predictive value in males than in females. Patients with a BMI of 28 kg/m
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