Affiliations: [a] School of Public Health, Peking Union Medical School, Beijing, China
| [b] Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA
| [c] Division of Graduate Medical Sciences, Boston University School of Medicine, Boston, MA, USA
| [d] Section of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA
| [e] Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, USA
| [f] National Heart Lung and Blood Institute Framingham Heart Study, Framingham, MA, USA
| [g] Department of Anatomy & Neurobiology, Neurology and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
Correspondence:
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Correspondence to: Rhoda Au, Boston University School of Medicine, Framingham Heart Study, 72 East Concord Street, B6, Boston, MA 02118, USA. Tel.: +1 508 935 3422; Fax: +1 617 638 8086; E-mail: [email protected].
Abstract: Background:Dementia is the leading cause of dependence and disability in the elderly population worldwide. However, currently there is no effective medication for dementia treatment. Therefore, identifying lifestyle-related risk factors including some that are modifiable may provide important strategies for reducing risk of dementia. Objective:This study aims to highlight associations between easily obtainable lifestyle risk factors in mid-life and dementia in later adulthood. Methods:Using data from the Framingham Heart Study Offspring cohort, we leveraged well-known classification models (decision tree classifier and random forests) to associate demographic and lifestyle behavioral data with dementia status. We then evaluated model performance by computing area under receiver operating characteristic (ROC) curve. Results:As expected, age was strongly associated with dementia. The analysis also identified ‘widowed’ marital status, lower BMI, and less sleep at mid-life as risk factors of dementia. The areas under the ROC curves were 0.79 for the decision tree, and 0.89 for the random forest model. Conclusion:Demographic and lifestyle factors that are non-invasive and inexpensive to implement can be assessed in midlife and used to potentially modify the risk of dementia in late adulthood. Classification models can help identify associations between dementia and midlife lifestyle risk factors. These findings inform further research, in order to help public health officials develop targeted programs for dementia prevention.
