Citation

Jahan S, Wraith D, Dunne MP, Naish S, McLean D. Int. J. Biometeorol. 2020; ePub(ePub): ePub.

Affiliation

Queensland Centre for Mental Health Research, The Park Centre for Mental Health Treatment, Research and Education, Brisbane, Queensland, 4076, Australia.

Copyright

(Copyright © 2020, International Society of Biometeorology, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s00484-020-01910-3

PMID

32281005

Abstract

Schizophrenia is a severe neuropsychiatric disorder with heterogeneous aetiology mostly affecting younger people and causing immense disability. Seasonal patterns may be observed in schizophrenia hospital admissions with possible association with changing climatic parameters and socio-demographic characteristics. This study critically reviewed studies that have assessed seasonal variations of hospital admissions for schizophrenia and/or explored an association with climate parameters and/or other potential factors. Following PRISMA guidelines, a systematic literature search was conducted using electronic databases (e.g. MEDLINE, Science Direct, PsycINFO, Pub Med) from inception to February 29, 2020. Thirty five papers were identified, of which only six (17.1%) examined evidence for a seasonal pattern or monthly excess of hospital admissions and the remaining twenty nine (82.9%) assessed climatic and socio-demographic attributes relating to the seasonal pattern or increased hospitalisation for schizophrenia. While most studies reported a summer peak in hospital admission rates, other studies reported a winter peak. Most of the evidence indicated that higher temperatures (> 28 °C) were positively correlated with schizophrenia admission rates. The individual effects of other climatic parameters (e.g. relative humidity, rainfall, atmospheric pressure, sunlight) were less frequently assessed. Males, people of 21-60 years old, and those married were more vulnerable to climatic variability specifically to higher temperatures. Further studies using large sample sizes, analysis of a wide range of interacting environmental variables and sophisticated statistical approaches are needed to better understand the underlying mechanisms involved. This will also provide more reliable statistical evidence that will help in the prevention and better management of cases.

Language: en

Keywords

Climatic factor; Neuro-chemical imbalance; Seasonal pattern; Socio-demographic attribute