The prime objective of the study was to estimate the prevalence and risk factors of multimorbidity based on the 2015-2016 CCHS data which included 109,659 participants drawn from all Canadian provinces and territories.
Multimorbidity was experienced by 33% of the study population. In comparison to other Canadian studies, this prevalence is lower than the 42.6% reported by Nicholsousing et al (2016)(17) based on a sample of respondents aged 18+. Our estimate is also higher than the prevalence computed by Robert et al (2016)(6), who reported a national prevalence of 2+ chronic conditions, based on five chronic conditions, to be 12.9%.The difference in estimates across different studies mainly arises from researchers’ choice of study groups/populations, the number of chronic conditions considered in the study, or both.The difference may also result from the type of data sources used (such as administrative vs self-reported surveys).For example, the estimated prevalence of multimorbidity by a recent work of Allisonet al (2017)(5) was based on people aged 40+years,considering only five chronic diseases, and using administrative data. The study by Allison and Colleague(5)study has few methodological similarities with ours in terms of target group, data sources used and number of chronic diseases considered; the only common trait was the both studies covered all provinces of Canada. In some instances, the definition of multimorbidity itself makes comparisons of prevalence difficult. For instance, while almost all Canadian studies defined multimorbidity as two or more conditions, a recent study by Andrew et al (2019)(16)used an outcome variable of 3 or more chronic conditions and reported a prevalence of multimorbidity in Canada of 14.0%.
The present study assessed the contributionof four lifestyle factors (physical activity level, alcohol intake, smoking and BMI) on multimorbidity.Findings showed a significant inverse association between physical activity level and the occurrence of multimorbidity. This is consistent with recent findings in high-income, middle-income, and low-income countries who reported higher physical activity was associated with multimorbidity (24,25). For instance,Lear etal. (2017)(24)based on a large cohort of 130 843 participants from 17 countries (including four low-income countries and seven middle-income countries), reported significant benefits of dose-dependent associations of all forms of physical activity with reduced mortality and cardiovascular disease risks.However, our findingscontrastwith some previous studies(13,35), mainly due to difference in the type of physical activity types considered in the individual studies (i.e., leisure versus general activities)(16).Regarding the observed relationship between activity and multimorbidity, one commonly known pathway for physical activity is that it helps to control excess body weight, and hence, significantly contributes to a reduction in the development of certain chronic diseases such as blood pressure, heart disease, and cancer(16).
The results of this study also showed a significantly higher likelihood of multimorbidity as participants’ BMI increased, a result consistent with other findings conducted around the world. For instance, in a recent study by Jovic and collogues (2016)(26), the proportion of participants who reported two or more chronic diseases increased with each BMI category in both sexes, reaching the highest values in obese category III. Obesity is often highlighted because it is simultaneously a disease and a risk factor for other chronic diseases , such as hypertension and diabetes(36).There is a general consensus among researchers and medical practitioners that weight loss or having optimal body weight is usually associated with reductions in the incidence of a number of morbidities, such as diabetes, stroke, heart disease, and others(37–39).This may partly explain why BMI is astrong predictor of multimorbidity in this study.
Recent studies investigating the association between multimorbidity and alcohol intake have reported inverse relationships, suggesting that moderate alcohol use may have protective effects against some chronic diseases, such as dementia, ischemic heart disease, and stroke(27–29). In addition, most previous studies have reporteda positive association between smoking and multimorbidity(6).However, most studies have not considered whether health behaviors interact with other variables to impact multimorbidity. Our analyses revealed that the relationship between smoking and multimorbidity was dependent on sex/gender, with smoking have a stronger association with multimorbidity among women than men. Similarly, the relationship between alcohol intake and multimorbidity was dependent on immigrant status; that isAdditional research is needed to clarify why the association between these two health behaviors and multimorbidity is modified by sex/gender and immigrant status.
Other than the lifestyle/ behavioral factors described above, our results also indicated that multimorbidity was associated with several sociodemographic factors, including a a dose response relationship with age. It is well established from other studies that older people are more prone to various commonly known chronic diseases such as heart failure and dementia(6,15,18). One plausible reason for the high multimorbidity in the older age group could be related to numerous age-related changes in the physiological state of the individual, for example, changes in metabolism, immune response, and organ function(40).
The results of this study also showed white participants to have a higherodds of multimorbidity than aboriginal and visible minority participants. This finding agrees with that reported in an American study, in which aboriginals had higher prevalence(23).The finding is inconsistent with someCanadian studies(6,14,16)who comparedthe prevalence of multimorbidity between aboriginal and white population.These studies showed a higher prevalence of multimorbidity among aboriginals compared to whites, adjusting for income and other socioeconomic characteristics. The difference might be due to study coverage and some methodological differences described above.
Widowed/divorced/separated respondents had much higher odds of experiencing multimorbidity compared to those married.While the mechanisms of how marital status influences disease outcomes is not clearly known, some studies attribute the lower multimorbidity among those partnered to improved mental health as a result of social support. (41,42).
We found an inverse, dose response relationship between household income and the prevalence of multimorbidity, indicating that the odds of multimorbidity decreasedas income increased. Previous research conducted in Canada and other parts of the world have reportedinconsistentresults, with some showing, consistent with the present study, a negative association (6,15,35), and others, positive or non-significant associations (20,21). Education was also found to be significant predictor of multimorbidity in the present study.Existing evidence suggest that low education level and poor economic condition may combine to increase the likelihood of multimorbidity(22). In other similar studies(18,23), those with higher education had significantly fewer reported diseases. Some authors argue that behind socioeconomic gradients in health are a higher prevalence of risky health behaviors among the poor, such as smoking and alcohol consumption, which are posited as the actual cause of socioeconomic gradients in health(16). However, a behavioral explanation is unlikely in this study, as associations between income and education remained, even after controlling for various health behaviors.The mechanisms by which SES affects multimorbidity likely involves multiple interacting material, behavioral, and psychosocial factorsoccurring throughout the life course(43). In terms of education, people with higher levels of education may better understand and adhere to the prevention and/or treatment of disease, while those with lower education levels may experience more problems related to self-management on a daily basis (41,44).