This study shows that fighting against hypertension, diabetes and physical inactivity could reduce the prevalence of dementia in 2040 in France by as much as 33% in men and 26% in women and would increase life expectancy without dementia at age 65 of 3.4 years in men and 2.6 years in women. This impact would be higher in men because they are more frequently exposed to these risk factors (currently 76% of men versus 60% of women have at least one of these risk factors at age 65). Among the three factors, hypertension has the largest impact on dementia burden since this is, by far, the most prevalent (69% in men and 49% in women). The disappearance of hypertension alone could decrease dementia prevalence by 21% in men and 16% in women while intervention targeting only diabetes or physical inactivity would lead to a reduction in dementia prevalence of only 4–7%. In the case of disappearance of diabetes, due to a fairly high reduction in mortality in parallel with the reduction in dementia prevalence, the lifelong probability of dementia and the mean time spent in dementia would not change in this scenario.
The proposed methodology has major assets. First, unlike previously published evaluation of intervention scenarios on dementia burden [11, 12, 13] or computation of attributable risk for some risk factors [6, 10], it accounts for the impact of change in risk factors distribution on mortality. This is an essential issue since most modifiable risk factors of dementia are also associated with mortality which is indeed the major competing risk of dementia in the elderly. The methods also account for the frequent co-exposure of elderly subjects to 2 or 3 risk factors. Moreover, the Monte-Carlo approach makes possible to forecast the impact of intervention scenarios on many indicators of the disease burden. Finally, the algorithm allows computing confidence intervals for the predictions accounting for the variances of the estimates of the input parameters when they are known.
At first glance, the scenarios assessed could appear too optimistic since we assumed a total disappearance of the risk factors. However, the first objective of this kind of approach is to provide alternative measures to the attributable risk to quantify the impact of exposures, alone or combined, on a disease accounting for their effect on mortality. From a Public Health perspective, our scenarios provide the magnitude of the maximum change that can be expected in dementia burden from efficient interventions targeting the considered risk factors and highlight the contribution of each factor. Given these assessments rely on previous estimations of many input parameters (the dementia incidence, the hazard ratios, the prevalence of exposures,…) subject to uncertainty, we think it is more meaningful to quantify the variance of the predictions rather than to refine the intervention scenarios. Nevertheless, the methods have been implemented in an R-package freely available that can be used for testing different scenarios or evaluating the impact of other risk factors or other diseases.
To our knowledge, only one study evaluated the impact of interventions targeting vascular risk factors on dementia burden while accounting for their impact on mortality [20]. Using a micro-simulations model for a birth cohort, Zissimopoulos et al. [20] estimated that hypertension disappearance and reduction of diabetes would have a lower impact on the burden of dementia in the United States than what we found. Indeed, they found a slight increase of years spent with dementia and lifetime risk of dementia due to an increase of the overall life expectancy. The main reason for this difference is probably the values of the input parameters for the association of diabetes and hypertension with dementia and death. The association parameters for dementia used in Zissimopoulos et al. were very low and thus probably lower than the association parameters for death (which are not given in their article). In addition, we assumed that the intervention does not modify the mortality with dementia which is probably not the case in Zissimopoulos et al. [20]. We previously showed that the relative values of the hazard ratios for dementia and death were the most influential on the impact of intervention modifying the risk factor prevalence [26].
As all projection studies evaluating the impact of a decrease in risk factors prevalence, this study relies on the assumption of a causal effect of hypertension, diabetes and physical inactivity on dementia, which is still debated. However, we selected modifiable risk factors for which there is convincing evidence of a strong association with dementia based on longitudinal studies fulfilling the temporality criterion for causality [4]. Moreover, studies support a reduction of brain volume and an increase of white matter hyperintensities in hypertension patients [27] while cognitive dysfunctions in patients with diabetes could involve several mechanisms including vascular complications [28, 29].
Finally, it is useful to note that our estimates of life expectancies (overall or without dementia) are different from standard estimates in demography. The demographs compute life expectancy using only mortality and incidence estimates from the target year (2040) while we simulate the life expectancy of subjects aged 65 in 2040 accounting for the evolution of mortality in the next years. Due to the decreasing trend of mortality over years, our estimate is expected to be larger than standard estimates.
Relying on current estimates of the (assumed causal) effects of vascular risk factors on dementia and death, this study shows that interventions aiming at decreasing the prevalence of these modifiable risk factors could be an efficient way to reduce the future burden of dementia. Since such interventions would also increase the overall life expectancy and consequently the size of the oldest population, which is at the highest risk of dementia, the expected change in the various measures of dementia burden highly depends on the relative effect on dementia incidence and mortality. Using the methodology made available in the R package MCSPCD, the projections can be adapted for different countries according to the mortality rate and refined when updated estimates of the relative effect on dementia incidence and mortality will be available.