Birth seasonality in schizophrenia: Effects of gender and income status

Chin Cheng, El Wui Loh, Ching Heng Lin, Chin Hong Chan, Tsuo Hung Lan

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Aims The aim of this study was to examine the correlations of birth seasonality in schizophrenia, considering influences of gender and income status. Methods The sample consisted of 1 000 000 people in the general population randomly selected from the Taiwan National Health Insurance Research Database. Data for the birth-year period 1950-1989 were extracted for analysis (n = 631 911; 306 194 male, 325 717 female). Subjects with schizophrenia (2796 male, 2251 female) were compared with the general population. Subgroups divided by birth-year periods (10-year interval), gender, and income status (low, medium, high) were analyzed using both the Walter and Elwood seasonality and chi-squared tests. Results The winter/spring birth excess in schizophrenia was 5.3% when compared with the general population. There was a statistically significant excess in winter/spring births than summer/autumn births inschizophrenia patients (relative risk [RR], 1.12; 95% confidence interval [CI]: 1.06-1.18). This winter/spring birth excess in schizophrenia was observed only in female subjects (RR, 1.20; 95%CI: 1.10-1.30), not in male subjects (RR, 1.03; 95%CI: 0.98-1.14), in all subgroups of income status, but was most pronounced in the low income subgroup (RR, 1.20, 1.09, 1.13; 95% CI: 1.05-1.37, 1.01-1.17, 1.02-1.25 for low, medium, and high income status, respectively). Conclusion A gender difference with female predominance of the effect of birth seasonality in schizophrenia, and a more pronounced effect in low income status were noted.

Original languageEnglish
Pages (from-to)426-433
Number of pages8
JournalPsychiatry and Clinical Neurosciences
Volume67
Issue number6
DOIs
Publication statusPublished - Sep 2013

Keywords

  • epidemiology
  • schizophrenia
  • season of birth
  • seasonality

ASJC Scopus subject areas

  • Neuroscience(all)
  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health

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