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Canadian Journal of Public Health

, Volume 109, Issue 5–6, pp 845–854 | Cite as

Beyond the grey tsunami: a cross-sectional population-based study of multimorbidity in Ontario

  • Bridget L. RyanEmail author
  • Krista Bray Jenkyn
  • Salimah Z. Shariff
  • Britney Allen
  • Richard H. Glazier
  • Merrick Zwarenstein
  • Martin Fortin
  • Moira Stewart
Quantitative Research

Abstract

Objectives

To determine volumes and rates of multimorbidity in Ontario by age group, sex, material deprivation, and geography.

Methods

A cross-sectional population-based study was completed using linked provincial health administrative databases. Ontario residents were classified as having multimorbidity (3+ chronic conditions) or not, based on the presence of 17 chronic conditions. The volumes (number of residents) of multimorbidity were determined by age categories in addition to crude and age-sex standardized rates.

Results

Among the 2013 Ontario population, 15.2% had multimorbidity. Multimorbidity rates increased across successively older age groups with lowest rates observed in youngest (0–17 years, 0.2%) and highest rates in the oldest (80+ years, 73.5%). The rate of multimorbidity increased gradually from ages 0 to 44 years, with a substantial and graded increase in the rates as the population aged. The top five chronic conditions, of the 17 examined, among those with multimorbidity were mood disorders, hypertensive disorders, asthma, arthritis, and diabetes.

Conclusion

Much of the common rhetoric around multimorbidity concerns the aging ‘grey tsunami’. This study demonstrated that the volume of multimorbidity is derived from adults beginning as young as age 35 years old. A focus only on the old underestimates the absolute burden of multimorbidity on the health care system. It can mask the association of material deprivation and geography with multimorbidity which can turn our attention away from two critical issues: (1) potential inequality in health and health care in Ontario and (2) preventing younger and middle-aged people from moving into the multimorbidity category.

Keywords

Multimorbidity Chronic conditions Population health Ontario 

Résumé

Objectif

Déterminer les volumes et les taux de multimorbidité en Ontario selon le groupe d’âge, le sexe, la défavorisation matérielle et la géographie.

Méthode

Une étude populationnelle transversale a été exécutée en maillant des bases de données administratives de santé provinciales. Les résidents de l’Ontario ont été catégorisés comme ayant ou non des multimorbidités (3 états chroniques ou plus) en fonction de la présence de 17 états chroniques. Les volumes (nombre de résidents) de multimorbidité ont été déterminés par catégorie d’âge en plus des taux bruts et des taux standardisés pour l’âge et le sexe.

Résultats

Dans la population ontarienne de 2013, 15,2% des gens étaient atteints de multimorbidités. Les taux de multimorbidité augmentaient avec chaque groupe d’âge, les taux les plus faibles étant observés chez les plus jeunes (0-17 ans : 0,2%), et les taux les plus élevés, chez les plus âgés (80 ans et plus : 73,5%). Le taux de multimorbidité augmentait progressivement entre 0 et 44 ans, avec une hausse graduelle considérable dans les taux avec l’âge de la population. Sur les 17 états chroniques compris dans l’étude, les 5 états les plus courants chez les personnes atteintes de multimorbidités étaient les troubles de l’humeur, les troubles hypertensifs, l’asthme, l’arthrite et le diabète.

Conclusion

Le discours sur la multimorbidité s’articule principalement autour du « tsunami gris » du vieillissement. Notre étude démontre que le volume de multimorbidité comprend des adultes aussi jeunes que 35 ans. La restriction des études aux seules personnes âgées sous-estime le fardeau absolu de la multimorbidité sur le système de soins de santé. Elle peut masquer l’association entre la défavorisation matérielle ou la géographie et les multimorbidités, ce qui peut détourner notre attention de deux questions névralgiques : 1) les inégalités possibles sur le plan de la santé et des soins de santé en Ontario et 2) comment empêcher les jeunes et les personnes d’âge moyen de passer dans la catégorie des personnes atteintes de multimorbidités.

Mots-clés

Morbidité associée Maladies chroniques Santé des populations Ontario 

Notes

Funding

This study was supported by the ICES Western site through participation in the ICES Western Faculty Scholar’s Program. Support for Dr. Bridget Ryan’s participation in the ICES Western Faculty Scholars Program came from the Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University. Dr. Ryan was also funded by the Canadian Institutes of Health Research Community-based Primary Health Care Innovation Team, Patient-centred Innovations for Persons with Multimorbidity.

ICES is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care. Core funding for ICES Western is provided by the Academic Medical Organization of Southwestern Ontario, the Schulich School of Medicine & Dentistry, Western University and the Lawson Health Research Institute.

Compliance with ethical standards

This study was approved by the institutional review board at Sunnybrook Health Sciences Centre, Toronto, Canada.

Conflict of interest

The authors declare that they have no conflicts of interest.

Disclaimer

This project was conducted at the Institute for Clinical Evaluative Sciences (ICES) Western Site. These datasets were linked using unique encoded identifiers and analyzed at the Institute for Clinical Evaluative Sciences (ICES). The data were analyzed by Britney Allen, MSc (Biostatistician at ICES Western). Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions, and statements expressed herein are those of the authors, and not necessarily those of CIHI or the other funding sources. No endorsement by CIHI or the other funding sources is intended or should be inferred.

Supplementary material

41997_2018_103_MOESM1_ESM.docx (18 kb)
ESM 1 (DOCX 17 kb)
41997_2018_103_MOESM2_ESM.docx (18 kb)
ESM 2 (DOCX 17 kb)

References

  1. Bains N. (2009). Standardization of rates. Report from the Association of Public Health Epidemiologists in Ontario (APHEO) through the Core Indicators for Public Health in Ontario Project.Google Scholar
  2. Barnett, K., Mercer, S. W., Norbury, M., Watt, G., Wyke, S., & Guthrie, B. (2012). Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet, 380, 37–43.  https://doi.org/10.1016/S0140-6736(12)60240-2.CrossRefPubMedGoogle Scholar
  3. Benchimol, E. I., Smeeth, L., Guttmann, A., Harron, K., Moher, D., Petersen, I., et al. (2015). The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. PLoS Med, 12(10), e1001885.  https://doi.org/10.1371/journal.pmed.1001885.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Boyd, C. M., & Fortin, M. (2010). Future of multimorbidity research: how should understanding of multimorbidity inform health system design? Public Health Review, 32, 451–474.CrossRefGoogle Scholar
  5. Brady, T. J., Anderson, L. A., & Kobau, R. (2015). Chronic disease self-management support: public health perspectives. Front Public Health, 2(Article 234), 1–5.Google Scholar
  6. Canadian Foundation for Healthcare Improvement. (2011). Myth: the aging populations is to blame for uncontrollable healthcare costs. Mythbusters: using evidence to debunk common misconceptions in Canadian Healthcare. February 2011. Retrieved June 23, 2017. http://www.cfhi-fcass.ca/sf-docs/default-source/mythbusters/Myth_AgingPopulation_EN_FINAL.pdf?sfvrsn=0
  7. CBC News. (2012). Baby boomers’ health demands will pose challenges. May 29, 2012. Retrieved Jun 23, 2017. http://www.cbc.ca/news/health/baby-boomers-health-demands-will-pose-challenges-1.1151890.
  8. Durbin, A., Moineddin, R., Lin, E., Steele, L. S., & Glazer, R. H. (2015). Examining the relationship between neighbourhood deprivation and mental health service use of immigrants in Ontario, Canada: a cross-sectional study. BMJ Open, 5, e006690.  https://doi.org/10.1136/bmjopen-2014-006690.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Fortin, M., Hudon, C., Haggerty, J., Akker, M., & Almirall, J. (2010). Prevalence estimates of multimorbidity: a comparative study of two sources. BMC Health Services Research, 10(1), 111.CrossRefGoogle Scholar
  10. Fortin, M., et al. (2012). A systematic review of prevalence studies on multimorbidity: toward a more uniform methodology. Annals of Family Medicine, 10, 142–151.CrossRefGoogle Scholar
  11. Fortin, M., Almirall, J., & Nicholson, K. (2017). Development of a research tool to document self-reported chronic conditions in primary care. Journal of Comorbidity, 7(1), 117–123.CrossRefGoogle Scholar
  12. Fung, K. Y., Luginaah, I. N., & Gorey, K. M. (2007). Impact of air pollution on hospital admissions in southwestern Ontario, Canada: generating hypotheses in sentinel high-exposure places. Environ Health, 6, 18.  https://doi.org/10.1186/1476-069X-6-18.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Hall RE, Khan F, Levi J, Ma H, Fang J, Martin C, et al. (2017). Ontario and LHIN 2015/16 stroke report cards and progress reports: Setting the bar higher. Toronto, ON: Institute for Clinical Evaluative Sciences Google Scholar
  14. Holzer BM, Siebenhuener K, Bopp M, Minder CE. (2014). Overcoming cut-off restrictions in multimorbidity prevalence estimates. BMC Public Health, 14: 780. http://www.biomedcentral.com/1471-2458/14/780.
  15. Kiran, T., Kopp, A., Moineddin, R., & Glazier, R. H. (2015). Longitudinal evaluation of physician payment reform and team-based care for chronic disease management and prevention. CMAJ, 187(17), E494–E502.CrossRefGoogle Scholar
  16. Kiran, T., Kopp, A., & Glazier, R. H. (2016). Those left behind from voluntary medical home reforms in Ontario, Canada. Annals of Family Medicine, 14(6), 517–525.CrossRefGoogle Scholar
  17. Koné Pefoyo, A. J., Bronskill, S. E., Gruneir, A., Calzavara, A., Thavorn, K., Petrosyan, Y., et al. (2015). The increasing burden and complexity of multimorbidity. BMC Public Health, 15, 415.  https://doi.org/10.1186/s12889-015-1733-2.CrossRefPubMedCentralGoogle Scholar
  18. Matheson, F. I., Dunn, J. R., Smith, K. L. W., Moineddin, R., & Glazier, R. H. (2012). Development of the Canadian Marginalization Index: a new tool for the study of inequality. Canadian Journal of Public Health, 103(Suppl. 2), S12–S16.PubMedGoogle Scholar
  19. Ontario Local Health Integration Network. (2014). Ontario’s LHINs. © Queen’s Printer for Ontario. Retrieved June 23, 2017. http://www.lhins.on.ca/
  20. Ontario Ministry of Health and Long Term Care. (2012). Legislation: Local Health System Integration Act, 2006. © Queen’s Printer for Ontario. Retrieved June 23, 2017. http://www.health.gov.on.ca/en/common/legislation/lhins/default.aspx
  21. Ontario Ministry of Health and Long-Term Care. (2015). Putting patients first: action plan for health care. http://www.health.gov.on.ca/en/ms/ecfa/healthy_change/. Retrieved November 16, 2015.
  22. Ontario Ministry of Health and Long Term Care. (2017). Data Catalogue: Legislation: Local Health Integration Network (LHIN) Offices. © Queen’s Printer for Ontario Added January 17, 2017. Retrieved June 23, 2017. https://www.ontario.ca/data/local-health-integration-network-office-lhin-locations
  23. Statistics Canada. (2013). Postal Code OM Conversion File (PCCF). Statistics Canada Catalogue no. 92-154-X.Google Scholar
  24. Statistics Canada. (2015). The Daily: Canada’s population estimates: age and sex, July 1, 2015. Updated September 29, 2015. Retrieved July 7, 2017. http://www.statcan.gc.ca/daily-quotidien/150929/dq150929b-eng.htm
  25. Statistics Canada. (2012). The Canadian population in 2011: age and sex. Catalogue no. 98-311-X2011001. Statistics Canada.Google Scholar
  26. The Globe and Mail (2015) Canada’s health-care system braces for hike in costs with influx of seniors. November 8, 2015. Retrieved June 23, 2017. https://www.theglobeandmail.com/globe-investor/retirement/canadas-health-care-system-braces-for-hike-in-costs-with-influx-of-seniors/article27169986/
  27. The Star (2015). Get moving on prepaing for ‘grey tsunami’: Editorial. February 2, 2015. Retrieved June 23, 2017. https://www.thestar.com/opinion/editorials/2015/02/02/get-moving-on-preparing-for-greytsunami-editorial.html.
  28. van den Akker, M., Buntinx, F., Roos, S., & Knottnerus, J. A. (2001). Problems in determining occurrence rates of multimorbidity. Journal of Clinical Epidemiology, 54(7), 675–679.CrossRefGoogle Scholar
  29. Violan, C., Foguet-Boreu, Q., Flores-Meteo, G., Salisbury, C., Blom, J., Freitag, M., et al. (2014). Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS One, 9(7), e102149.  https://doi.org/10.1371/journal.pone.0102149.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Wilkins R. (2004). Neighbourhood income quintiles derived from Canadian postal codes are apt to be misclassified in rural but not urban areas. working paper. Statistics Canada.Google Scholar

Copyright information

© The Canadian Public Health Association 2018

Authors and Affiliations

  1. 1.Centre for Studies in Family Medicine, Department of Family Medicine; Department of Epidemiology & Biostatistics, Schulich School of Medicine & DentistryWestern UniversityLondonCanada
  2. 2.Western Site (ICES Western)Institute of Clinical Evaluative SciencesLondonCanada
  3. 3.Arthur Labatt School of NursingWestern UniversityLondonCanada
  4. 4.Central Site (ICES Central)Institute for Clinical Evaluative SciencesTorontoCanada
  5. 5.Centre for Research on Inner City Health at St. Michael’s HospitalTorontoCanada
  6. 6.Department of Family and Community MedicineUniversity of TorontoTorontoCanada
  7. 7.Department of Family MedicineUniversité de SherbrookeChicoutimiCanada

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