Multimorbidity (multiple conditions) and polypharmacy (multiple medications) are increasingly common, yet there is a need to better understand the prevalence of co-occurrence. In this systematic review, we examined the prevalence of multimorbidity and polypharmacy among adults (≥18 years) and older adults (≥65 years) in clinical and community settings. Six electronic databases were searched, and 87 studies were retained after two levels of screening. Most studies focused on adults 65 years and older and were done in population-based community settings. Although the operational definitions of multimorbidity and polypharmacy varied across studies, consistent cut-points (two or more conditions and five or more medications) were used across most studies. In older adult samples, the prevalence of multimorbidity ranged from 4·8% to 93·1%, while the prevalence of polypharmacy ranged from 2·6% to 86·6%. High heterogeneity between studies indicates the need for more consistent reporting of specific lists of conditions and medications used in operational definitions.

Background: Multimorbidity is a complex issue in modern medicine and a more nuanced understanding of how this phenomenon occurs over time is needed.Aim: To determine the prevalence, characteristics, and patterns of patients living with multimorbidity, specifically the unique combinations (unordered patterns) and unique permutations (ordered patterns) of multimorbidity in primary care.Design and setting: A retrospective cohort analysis of the prospectively collected data from 1990 to 2013 from the Canadian Primary Care Sentinel Surveillance Network electronic medical record database.Method: Adult primary care patients who were aged ≥18 years at their first recorded encounter were followed over time. A list of 20 chronic condition categories was used to detect multimorbidity. Computational analyses were conducted using the Multimorbidity Cluster Analysis Tool to identify all combinations and permutations.Results: Multimorbidity, defined as two or more and three or more chronic conditions, was prevalent among adult primary care patients and most of these patients were aged <65 years. Among female patients with two or more chronic conditions, 6075 combinations and 14 891 permutations were detected. Among male patients with three or more chronic conditions, 4296 combinations and 9716 permutations were detected. While specific patterns were identified, combinations and permutations became increasingly rare as the total number of chronic conditions and patient age increased.Conclusion: This research confirms that multimorbidity is common in primary care and provides empirical evidence that clinical management requires a tailored, patient-centred approach. While the prevalence of multimorbidity was found to increase with increasing patient age, the largest proportion of patients with multimorbidity in this study were aged <65 years.

Introduction: multimorbidity has become an increasingly important issue for many populations around the world, including Canada. The objectives of this study were to estimate the prevalence of multimorbidity at first follow-up and to identify factors associated with multimorbidity using data from the Canadian Longitudinal Study on Aging (CLSA). Methods: this study included 27,701 community-dwelling participants in the first follow-up of the CLSA. Multimorbidity was operationalised using two definitions (Public Health and Primary Care), as well as the cut-points of two or more chronic conditions (MM2+) and three or more chronic conditions (MM3+). The prevalence of multimorbidity was calculated at first follow-up and multivariable regression models were used to identify correlates of multimorbidity occurrence. Results: the prevalence of multimorbidity at first follow-up was 32.3% among males and 39.3% among females when using the MM2+ Public Health definition, whereas the prevalence was 67.2% among males and 75.8% among females when using the MM2+ Primary Care definition. Older age, lower alcohol consumption, lower physical activity levels, dissatisfaction with sleep quality, dissatisfaction with life and experiencing social limitations due to health conditions were significantly associated with increased odds of multimorbidity for both males and females, regardless of the definition of multimorbidity used. Conclusion: various sociodemographic, behavioural and psychosocial factors are associated with multimorbidity. Future research should continue to examine how the prevalence of multimorbidity changes with time and how these changes may be related to specific risk factors. This future research should be supplemented with studies examining the longitudinal impacts of multimorbidity over time.