Average sunrise time predicts depression prevalence

J Psychosom Res. 2003 Aug;55(2):99-105. doi: 10.1016/s0022-3999(02)00479-8.

Abstract

Objective: Folk wisdom has it that early rising is associated with being "healthy, wealthy and wise." A physiologic explanation may be Wiegand's "Depressiogenic Theory of Sleep," which posits that excessive REM sleep causes depression. Sleeping late increases REM sleep, and thus may increase depression risk. Published depression prevalence research does not use arising time, but average sunrise time (AST) for cities might serve as an analogue for arising time. Two studies of depression prevalence in urban populations, the EURODEP Programme, which measured geriatric depression in nine European cities, and the Epidemiologic Catchment Area (ECA) study of five US centres, have so far lacked satisfactory explanations for the striking differences in depression prevalence between cities. It was hypothesized that differences in rising times between cities, as determined by AST, could explain the variability in depression prevalences.

Methods: Correlations were calculated for published depression prevalences from the EURODEP and ECA studies, and AST for each site.

Results: For both studies, depression prevalences are significantly correlated with AST, with later sunrise (corresponding to earlier arising times in relation to sunrise) associated with lower depression prevalence.

Conclusions: The hypothesis that later rising from sleep is associated with increased depression was supported. The findings also suggest that a city's depression prevalence could be reduced by simple public health measures to manipulate AST, such as going to Daylight Saving Time (DST) year-round or shifting time-zone boundaries. For individuals, getting up earlier from sleep may be helpful in depression.

Publication types

  • Review

MeSH terms

  • Aging / psychology
  • Depression / epidemiology*
  • Depression / etiology
  • Humans
  • Photoperiod*
  • Prevalence
  • Public Policy
  • Sleep, REM*
  • Time Factors
  • Urban Population