Summary: A new online calculator can be used by individuals to assess their dementia risk and make lifestyle changes that can help decrease risk factors for neurodegeneration.
Source: Ottawa Hospital
Canadian researchers at The Ottawa Hospital, the University of Ottawa, the Bruyère Research Institute and ICES have built and validated an online calculator that empowers individuals 55 and over to better understand the health of their brain and how they can reduce their risk of being diagnosed with dementia in the next five years.
Their process was published today in the Journal of Epidemiology and Community Health, and the calculator is available at projectbiglife.ca.
Dementia is an umbrella term for loss of memory and other thinking abilities severe enough to interfere with daily life. Every year, 76,000 new cases of dementia are diagnosed in Canada, a number expected to increase as the population ages.
There is no cure or treatment for dementia. However, about a third of dementia may be preventable through lifestyle factors like physical activity, healthy eating, reducing alcohol and tobacco use, and managing conditions like diabetes and high blood pressure.
The researchers based the dementia calculator on survey data from over 75,000 Ontarians.
“What sets this dementia risk calculator apart is that you don’t need to visit a doctor for any tests,” said Dr. Stacey Fisher, the lead author of the study who performed the research largely in Ottawa while she was a PhD student supervised by Dr. Doug Manuel and Dr. Peter Tanuseputro at The Ottawa Hospital.
“People already have all the information they need to complete the calculator in the comfort of their home.” Dr. Fisher is currently a postdoctoral fellow at the University of Toronto and Public Health Ontario.
Factors in the Dementia Population Risk Tool (DemPoRT) include:
- Age
- Smoking status and lifetime exposure
- Alcohol consumption
- Physical activity
- Stress
- Diet
- Sense of belonging
- Ethnicity
- Immigration status
- Socioeconomic status of the neighbourhood
- Education
- Activities where assistance is needed
- Marital status
- Number of languages spoken
- Health conditions
The calculator can be used by individuals to assess their dementia risk and help them modify their lifestyle. The researchers also have a goal for policy makers to use this algorithm to do the same thing for the general population.
Through this research, the team has developed the first predictive tool designed to predict dementia at a population level. It can predict the number of new cases in the community, identify higher-risk populations, inform dementia prevention strategies, and will be used to support Canada’s national dementia strategy. By using regularly collected health data and surveys, population health experts have all the information they need to use the algorithm.
“This tool will give people who fill it out clues to what they can do to reduce their personal risk of dementia,” said Dr. Peter Tanuseputro, senior author of the study, and scientist at The Ottawa Hospital, investigator at the Bruyère Research Institute, adjunct scientist at ICES and assistant professor at the University of Ottawa.
“The COVID-19 pandemic has also made it clear that sociodemographic variables like ethnicity and neighbourhood play a major role in our health. It was important to include those variables in the tool so policy makers can understand how different populations are impacted by dementia, and help ensure that any prevention strategies are equitable.”
The dementia calculator will be added to a list of existing calculators on Project Big Life that help Canadians estimate their own life expectancy based on habits and lifestyle choices.
The calculator was based on data from the Statistics Canada Canadian Community Health Surveys housed at ICES. Currently designed for use in Canada, it can be adapted for any of the 100 countries around the world that collect health survey data.
Funding: The study was funded by the Canadian Institutes of Health Research and supported by ICES.
About this dementia research news
Source: Ottawa University
Contact: Amelia Buchanan – Ottawa University
Image: The image is credited to Project Big Life
Original Research: Open access.
“Development and validation of a predictive algorithm for risk of dementia in the community setting” by Stacey Fisher, Douglas G Manuel, Amy T Hsu, Carol Bennett, Meltem Tuna, Anan Bader Eddeen, Yulric Sequeira, Mahsa Jessri, Monica Taljaard, Geoffrey M Anderson, Peter Tanuseputro. Journal of Epidemiology and Community Health.
Abstract
Development and validation of a predictive algorithm for risk of dementia in the community setting
Background
Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed.
Methods
The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health Survey (survey years 2001 to 2012). Five-year incidence of physician-diagnosed dementia was ascertained by individual linkage to administrative healthcare databases and using a validated case ascertainment definition with follow-up to March 2017. Sex-specific proportional hazards regression models considering competing risk of death were developed using self-reported risk factors including information on socio-demographic characteristics, general and chronic health conditions, health behaviours and physical function.
Results
Among 75 460 respondents included in the combined derivation and validation cohorts, there were 8448 cases of incident dementia in 348 677 person-years of follow-up (5-year cumulative incidence, men: 0.044, 95% CI: 0.042 to 0.047; women: 0.057, 95% CI: 0.055 to 0.060). The final full models each include 90 df (65 main effects and 25 interactions) and 28 predictors (8 continuous). The DemPoRT algorithm is discriminating (C-statistic in validation data: men 0.83 (95% CI: 0.81 to 0.85); women 0.83 (95% CI: 0.81 to 0.85)) and well-calibrated in a wide range of subgroups including behavioural risk exposure categories, socio-demographic groups and by diabetes and hypertension status.
Conclusions
This algorithm will support the development and evaluation of population-level dementia prevention strategies, support decision-making for population health and can be used by individuals or their clinicians for individual risk assessment.
