An Alzheimer's dementia cumulative risk model in a sample of general population over 65: Public health implications

Abstract

Background and objectives

With the population ageing, the identification of modifiable risk factors for dementia represents a public health priority. Co-occurrence of risk factors in the same individual is more frequent than an isolated appearance and may create synergistic effects, with an increased risk of negative outcomes such as dementia and mortality. We aim to study the cumulative risk of incident Alzheimer's Dementia (AD) in a community sample aged >65 (n= 3044).

Methods

To this end, we will examine the impact on the risk of AD of the co-occurrence of variables that have previously been shown to increase risk: age, gender, education, marital status, depression, anxiety, body mass index (BMI) and hearing loss.

Results

The most frequent number of co-occurring risk factors was 3. We found a cumulative increased risk of both death and AD by the confluence of 2 or more risk factors. Using a competing risk regression model, each increase in a co-occurring risk factor was associated with a significant increase in the risk of incident AD of more than two-fold. By the analysis of the Population Attributable Fractions (PAF) of AD due to several risk factors, we found that if 4 or more co-occurring risk factors could be eliminated from the population, the prevalence of AD would be reduced by approximately 38%.

Conclusion

Our study offers an estimate of the impact that preventive interventions could have if the number of modifiable risk factors of AD at a population level.