Canadian Journal of Public Health

, Volume 94, Issue 6, pp 453–457 | Cite as

The Seasonality of Total Hospitalizations in Ontario by Age and Gender

A Time Series Analysis
  • Eric J. CrightonEmail author
  • Rahim Moineddin
  • Ross E. G. Upshur
  • Muhammad Mamdani



Consistent and predictable seasonal fluctuations in hospitalizations have been demonstrated for diverse communicable and non-communicable health conditions. The objective of this study was to examine the seasonal patterns of all hospitalizations by age and gender in order to determine whether the hospital system for a large geographical area was subject to consistent, predictable temporal variations.


A retrospective population-based study of approximately 14 million residents of Ontario was conducted to assess temporal patterns in all hospitalizations from April 1, 1988 to March 31, 2000. Time series analysis, using spectral analysis, was conducted to assess seasonal variations and trends over time and to account for autocorrelation.


Conspicuous seasonality in hospitalizations was found in every age group for both sexes with the exception of males between the ages of 20 and 39. The average monthly variability ranged from lows of 15% for the age group 20–29 for both sexes, to highs of 34% in males between 5 and 9 years. For the total population, this represents a 12-year average variability of approximately 20% or 20,000 out of 97,000 hospitalizations. For both sexes, peak hospitalizations typically occurred in the spring and autumn for the youngest and oldest age groups, and in January for the middle age groups.


Seasonal factors play an important role in the utilization of hospital services in Ontario. The determinants of this seasonality, which include environmental and social/behavioural factors, are not well understood.



Des fluctuations saisonnières régulières et prévisibles du nombre d’hospitalisations ont été constatées pour divers troubles médicaux transmissibles et non transmissibles. Nous avons voulu examiner les schémas saisonniers selon l’âge et le sexe pour l’ensemble des hospitalisations afin de déterminer si l’appareil hospitalier d’une vaste zone géographique faisait l’objet de variations temporelles régulières et prévisibles.


Une étude rétrospective fondée sur la population des résidents de l’Ontario (environ 14 millions de personnes) a permis d’évaluer les schémas temporels de l’ensemble des hospitalisations entre le 1er avril 1988 et le 31 mars 2000. Au moyen d’une analyse spectrale, nous avons analysé des séries chronologiques pour évaluer les variations saisonnières et les tendances au fil du temps et expliquer l’autocorrélation.


Des cycles saisonniers apparents dans les hospitalisations ont été constatés dans tous les groupes d’âge et pour les deux sexes, sauf chez les hommes de 20 à 39 ans. La variabilité mensuelle moyenne présentait des creux de 15 % dans le groupe des 20 à 29 ans des deux sexes et des crêtes de 34 % chez les garçons de 5 à 9 ans. Pour l’ensemble de la population, ceci représente une variabilité moyenne d’environ 20 % sur 12 ans, soit 20 000 hospitalisations sur 97 000. Pour les deux sexes, on observe en général des crêtes d’hospitalisations au printemps et à l’automne dans les groupes les plus jeunes et les plus âgés, et en janvier dans les groupes d’âge moyen.


Les facteurs saisonniers jouent un rôle important dans l’utilisation des services hospitaliers en Ontario. Les déterminants de ces cycles saisonniers, dont des facteurs environnementaux et socio-comportementaux, sont encore mal compris.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Upshur RE, Knight K, Goel V. Time-series analysis of the relation between influenza virus and hospital admissions of the elderly in Ontario, Canada, for pneumonia, chronic lung disease, and congestive heart failure. Am J Epidemiol 1999;149(1):85–92.CrossRefGoogle Scholar
  2. 2.
    Saynajakangas P, Keistinen T, Tuuponen T. Seasonal fluctuations in hospitalisation for pneumonia in Finland. Int J Circumpolar Health 2001;60(1):34–40.PubMedGoogle Scholar
  3. 3.
    Lanska DJ, Hoffmann RG. Seasonal variation in stroke mortality rates. Neurology 1999;52(5):984–90.CrossRefGoogle Scholar
  4. 4.
    Mamdani MM, Upshur RE. Fall-related hospi-talizations: What’s in season? Can J Public Health 2001;92(2):113–16.PubMedGoogle Scholar
  5. 5.
    Jacobsen SJ, Sargent DJ, Atkinson EJ, O’Fallon WM, Melton LJ, 3rd. Population-based study of the contribution of weather to hip fracture sea-sonality. Am J Epidemiol 1995;141(1):79–83.CrossRefGoogle Scholar
  6. 6.
    Crighton EJ, Mamdani MM, Upshur RE. A population based time series analysis of asthma hospitalisations in Ontario, Canada: 1988 to 2000. BMC Health Serv Res 2001;1(1):7.CrossRefGoogle Scholar
  7. 7.
    Fleming DM, Cross KW, Sunderland R, Ross AM. Comparison of the seasonal patterns of asthma identified in general practitioner episodes, hospital admissions, and deaths. Thorax 2000;55(8):662–65.CrossRefGoogle Scholar
  8. 8.
    Harju T, Keistinen T, Tuuponen T, Kivela SL. Seasonal variation in childhood asthma hospitalisations in Finland, 1972–1992. Eur J Pediatr 1997;156(6):436–39.CrossRefGoogle Scholar
  9. 9.
    Mao Y, Semenciw R, Morrison H, Wigle DT. Seasonality in epidemics of asthma mortality and hospital admission rates, Ontario, 1979–86. Can J Public Health 1990;81(3):226–28.PubMedGoogle Scholar
  10. 10.
    Boulay F, Berthier F, Schoukroun G, Raybaut C, Gendreike Y, Blaive B. Seasonal variations in hospital admission for deep vein thrombosis and pulmonary embolism: Analysis of discharge data. BMJ 2001;323(7313):601–2.CrossRefGoogle Scholar
  11. 11.
    Weiss KB. Seasonal trends in US asthma hospi-talizations and mortality. JAMA 1990;263(17):2323–28.CrossRefGoogle Scholar
  12. 12.
    Douglas AS, Rawles JM, Alexander E, Allan TM. Winter pressure on hospital medical beds. BMJ 1991;303(6801):508–9.CrossRefGoogle Scholar
  13. 13.
    Schwartz J, Marcus A. Mortality and air pollution in London: A time series analysis. Am J Epidemiol 1990;131(1):185–94.CrossRefGoogle Scholar
  14. 14.
    Katsouyanni K, Schwartz J, Spix C, Touloumi G, Zmirou D, Zanobetti A, et al. Short term effects of air pollution on health: A European approach using epidemiologic time series data: The APHEA protocol. J Epidemiol Community Health 1996;50 Suppl 1:S12–S18.CrossRefGoogle Scholar
  15. 15.
    Osborne ML, Vollmer WM, Buist AS. Periodicity of asthma, emphysema, and chronic bronchitis in a northwest health maintenance organization. Chest 1996;110(6):1458–62.CrossRefGoogle Scholar
  16. 16.
    Donaldson GC, Keatinge WR. Excess winter mortality: Influenza or cold stress? Observational study. BMJ 2002;324(7329):89–90.CrossRefGoogle Scholar
  17. 17.
    Durning SJ, Cation LJ, Buttram JW. Medical meteorology: Whether weather influences admissions. Mayo Clin Proc 2001;76(4):449.CrossRefGoogle Scholar
  18. 18.
    Cold exposure and winter mortality from ischaemic heart disease, cerebrovascular disease, respiratory disease, and all causes in warm and cold regions of Europe. The Eurowinter Group. Lancet 1997;349(9062):1341–46.CrossRefGoogle Scholar
  19. 19.
    Storr J, Lenney W. School holidays and admissions with asthma. Arch Dis Child 1989;64(1):103–7.CrossRefGoogle Scholar
  20. 20.
    Ford D, Nault F. Changing fertility patterns, 1974 to 1994. Health Rep 1996;8(3):39–46(Eng); 43–51(Fre).PubMedGoogle Scholar

Copyright information

© The Canadian Public Health Association 2003

Authors and Affiliations

  • Eric J. Crighton
    • 1
    Email author
  • Rahim Moineddin
    • 2
  • Ross E. G. Upshur
    • 3
    • 5
  • Muhammad Mamdani
    • 4
    • 6
  1. 1.Primary Care Research UnitSunnybrook and Women’s College Health Sciences CentreTorontoCanada
  2. 2.Department of Family and Community MedicineUniversity of TorontoCanada
  3. 3.Primary Care Research UnitSunnybrook and Women’s College Health Sciences CentreCanada
  4. 4.Institute of Clinical Evaluative Sciences (ICES)Canada
  5. 5.Department of Family and Community Medicine and Public Health SciencesUniversity of TorontoCanada
  6. 6.Faculty of PharmacyUniversity of TorontoCanada

Personalised recommendations