Circadian analysis of large human populations: inferences from the power grid

Chronobiol Int. 2015 Mar;32(2):255-61. doi: 10.3109/07420528.2014.965316. Epub 2014 Oct 6.

Abstract

Few, if any studies have focused on the daily rhythmic nature of modern industrialized populations. The present study utilized real-time load data from the U.S. Pacific Northwest electrical power grid as a reflection of human operative household activity. This approach involved actigraphic analyses of continuously streaming internet data (provided in 5 min bins) from a human subject pool of approximately 43 million primarily residential users. Rhythm analyses reveal striking seasonal and intra-week differences in human activity patterns, largely devoid of manufacturing and automated load interference. Length of the diurnal activity period (alpha) is longer during the spring than the summer (16.64 h versus 15.98 h, respectively; p < 0.01). As expected, significantly more activity occurs in the solar dark phase during the winter than during the summer (6.29 h versus 2.03 h, respectively; p < 0.01). Interestingly, throughout the year a "weekend effect" is evident, where morning activity onset occurs approximately 1 h later than during the work week (5:54 am versus 6:52 am, respectively; p < 0.01). This indicates a general phase-delaying response to the absence of job-related or other weekday morning arousal cues, substantiating a preference or need to sleep longer on weekends. Finally, a shift in onset time can be seen during the transition to Day Light Saving Time, but not the transition back to Standard Time. The use of grid power load as a means for human actimetry assessment thus offers new insights into the collective diurnal activity patterns of large human populations.

Keywords: Circadian; human; population activity analysis; power grid.

MeSH terms

  • Actigraphy
  • Automation
  • Biological Clocks
  • Body Temperature
  • Circadian Rhythm*
  • Electricity
  • Electroencephalography
  • Employment
  • Humans
  • Internet
  • Light
  • Northwestern United States
  • Power Plants / statistics & numerical data*
  • Seasons
  • Sleep / physiology*
  • Sunlight
  • Time Factors
  • United States