Effects of Reductions in Body Mass Index on the Future Osteoarthritis Burden in Canada: A Population‐Based Microsimulation Study

Abstract

Objective. Osteoarthritis (OA) is the most common joint disease and a major cause of disability. Incidence and prevalence of OA are expected to increase due to population aging and increased levels of obesity. The purpose of this study was to project the effect of hypothetical interventions that change the distribution of body mass index (BMI) on OA burden in Canada. Methods. We used a microsimulation computer model of OA based on the Population Health Model platform. The model used demographic predictions for Canada and population data from an administrative database in British Columbia and national Canadian surveys.Results. Under the base-case scenario, between 2010 and 2030, OA prevalence is expected to increase from 11.5% to 15.6% in men and 16.3% to 21.1% in women. In scenarios assuming, on average, a 0.3-, 0.5-, or 1-unit drop in BMI per year, OA prevalence in 2030 would reach 14.9%, 14.6%, and 14.2% in men and 20.3%, 19.7%, and 18.5%, in women, respectively. Under these scenarios, the proportion of new cases prevented would be 9.5%, 13.2%, and 16.7%, respectively, in men, and 9.1%, 15.2%, and 25.0% in women. Targeting only those people ages ‡50 years for weight reduction would achieve approximately 70% of the impact of a full population strategy. Targeting only the obese (BMI ‡30) would likely result in a larger benefit for men than women. Conclusion. Due to the aging of the population, OA will remain a major and growing health issue in Canada over the next 2 decades, regardless of the course of the obesity epidemic.

Alzheimer’s and other dementias in Canada, 2011 to 2031: a microsimulation Population Health Modeling (POHEM) study of projected prevalence, health burden, health services, and caregiving use

“…These authors specifically cite Canada’s Population Health Model (POHEM) – developed for chronic diseases such as diabetes, cardiovascular disease, and arthritis – as an example of a microsimulation model that more robustly includes population dynamics (birth, deaths, and migration) and disease progression (from disease-free to disease with varying levels of health-related quality of life or health care use) [7–9]. As well, more complex modeling approaches have the benefit of synthesizing a wide range of data sources to generate a more comprehensive viewpoint of the disease, meaning that microsimulation models provide insight for complex connected systems [10].…”

Distribution and Drivers of Average Direct Cost of Osteoarthritis in Canada From 2003 to 2010

“…The POHEM is a continuous‐time, dynamic, microsimulation model that was developed to characterize the lifecycle dynamics of the Canadian population . POHEM‐OA was developed by Kopec et al and was used in projecting the total direct cost of OA in Canada in a previous publication . The POHEM‐OA model uses the Canadian Community Health Survey (CCHS) in 2001 to sample individuals for its initial population.…”

“…In our first scenario analysis, to examine the effect of the obesity epidemic, we evaluated the effect of change in BMI in the population on the average cost of OA during the study period. BMI is modeled as an autoregression model that includes age, sex, income, education, region, and previous BMI . Together with age and sex, BMI is then used as a risk factor in determining OA incidence in POHEM‐OA .…”

“…BMI is modeled as an autoregression model that includes age, sex, income, education, region, and previous BMI . Together with age and sex, BMI is then used as a risk factor in determining OA incidence in POHEM‐OA . To evaluate the effect of change in BMI, we compared the base case scenario with the scenario in which BMI of every individual was assumed to remain the same during the study period.…”

“…The total cost burden of OA is significant compared to that of other chronic diseases , both due to OA's high prevalence and its relatively high average cost . Several studies have evaluated the increasing trend in the number of total joint replacement (TJR) surgeries due to OA and changes in the prevalence of OA . Nonetheless, very few have evaluated OA's cost trend , and little information is available about the drivers and distribution of OA's average cost .…”