Forecasting Adult Weight Status Trends in Canada with Longitudinal Population-based Data
| dc.contributor.author | Staples, Mark | |
| dc.contributor.copyright-release | Not Applicable | en_US |
| dc.contributor.degree | Master of Applied Science | en_US |
| dc.contributor.department | Department of Industrial Engineering | en_US |
| dc.contributor.ethics-approval | Not Applicable | en_US |
| dc.contributor.external-examiner | Mohamed Abdolell | en_US |
| dc.contributor.graduate-coordinator | Alireza Ghasemi | en_US |
| dc.contributor.manuscripts | Not Applicable | en_US |
| dc.contributor.thesis-reader | John Blake | en_US |
| dc.contributor.thesis-supervisor | Peter Vanberkel | en_US |
| dc.contributor.thesis-supervisor | Stefan Kuhle | en_US |
| dc.date.accessioned | 2015-04-01T14:53:45Z | |
| dc.date.available | 2015-04-01T14:53:45Z | |
| dc.date.defence | 2015-03-13 | |
| dc.date.issued | 2015-04-01 | |
| dc.description.abstract | The prevalence of obesity in Canada and other Western countries has increased dramatically over the last 30 years. This project modelled future prevalence of weight status trends under a Markov framework by estimating transition probabilities between categorical weight states. A microsimulation was developed to track individual weight status histories through discrete-time updates. Model and simulation parameters were derived from a nationally representative longitudinal survey which followed 17,000 participants over a 20 year period. A series of weight prevention and intervention strategies were simulated to determine their potential impact on weight status trends and population health utility. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10222/56290 | |
| dc.language.iso | en_US | en_US |
| dc.subject | healthcare | en_US |
| dc.subject | simulation | en_US |
| dc.subject | obesity | en_US |
| dc.title | Forecasting Adult Weight Status Trends in Canada with Longitudinal Population-based Data | en_US |