Multimorbidity disease clusters in Aboriginal and non-Aboriginal Caucasian populations in Canada

Abstract

Introduction Patterns of multimorbidity, the co-occurrence of two or more chronic diseases, may not be constant across populations. Our study objectives were to compare prevalence estimates of multimorbidity in the Aboriginal population in Canada and a matched non-Aboriginal Caucasian population and identify the chronic diseases that cluster in these groups. Methods We used data from the 2005 Canadian Community Health Survey (CCHS) to identify adult (≥ 18 years) respondents who self-identified as Aboriginal or non-Aboriginal Caucasian origin and reported having 2 or more of the 15 most prevalent chronic conditions measured in the CCHS. Aboriginal respondents who met these criteria were matched on sex and age to non-Aboriginal Caucasian respondents. Analyses were stratified by age (18–54 years and ≥ 55 years). Prevalence was estimated using survey weights. Latent class analysis (LCA) was used to identify disease clusters. Results A total of 1642 Aboriginal respondents were matched to the same number of non-Aboriginal Caucasian respondents. Overall, 38.9% (95% CI: 36.5%–41.3%) of Aboriginal respondents had two or more chronic conditions compared to 30.7% (95% CI: 28.9%–32.6%) of non-Aboriginal respondents. Comparisons of LCA results revealed that three or four clusters provided the best fit to the data. There were similarities in the diseases that tended to co-occur amongst older groups in both populations, but differences existed between the populations amongst the younger groups. Conclusion We found a small group of younger Aboriginal respondents who had complex co-occurring chronic diseases; these individuals may especially benefit from disease management programs.

Chronic disease multimorbidity among the Canadian population: prevalence and associated lifestyle factors

“…This finding agrees with that reported in an American study in which aboriginals had higher prevalence [ 21 ]. The finding is inconsistent with some Canadian studies[ 6 , 14 , 16 ] which compared the prevalence of multimorbidity between aboriginal and white population. These studies showed higher prevalence of multimorbidity among aboriginals compared to whites, adjusting for income and other socioeconomic characteristics.…”

“…The few studies which have examined associations between lifestyle factors and multimorbidity suggest that the likelihood of multimorbidity increases with a more sedentary lifestyle ([ 22 , 23 ], obesity[ 24 ], and lower alcohol intake [ 25 – 27 ]. Most Canadian studies have reported mixed results regarding the socioeconomic and demographic risk factors for multimorbidity [ 6 , 7 , 14 – 16 ], with relatively little attention paid to lifestyle factors[ 16 ].…”

“…Despite the increasing prevalence of multimorbidity over time in Canada, little attention has been given to this issue in the health care system. The very few population-based studies conducted in Canada have focused on a limited number of chronic diseases[ 5 , 6 ] or potential correlates of multimorbidity[ 14 ], and/or investigated only demographic or geographic subpopulations[ 14 , 15 , 28 ]. To address this limitation, the present study has considered a more comprehensive list of chronic conditions, all ages, and all provinces of Canada.…”

Is ethnicity an appropriate measure of health care marginalization? A systematic review and meta-analysis of the outcomes of diabetic foot ulceration in Aboriginal populations

“…These populations have higher disease prevalence rates than the non-Aboriginal populations in similar geopolitical regions (state, province or country). [1][2][3][4][5] Common chronic diseases with higher prevalence rates include chronic obstructive pulmonary disease, 1 heart failure, 2 ischemic heart disease, hypertension, diabetes, renal disease 3 and multimorbidity disease. 4 These higher rates can be explained by a number of variables, including not only ethnicity but social and economic factors as well.…”

Segmentation analysis and the recovery of queuing parameters via the Wasserstein distance: a study of administrative data for patients with chronic obstructive pulmonary disease

“…The discovered relations enable the observations to be separated into latent classes according to their maximum likelihood class membership [13,22]. This method has proved useful in the study of comorbidity patterns as in [20,21] where combinations of demographic and clinical attributes are related to various subgroups of chronic diseases.…”