We constructed Cox models to derive hazard ratios and determine confounding and interaction effects for potentially modifiable risk factors for dementia and calculated mean percentage population attributable fractions for seven year incidence of mild cognitive impairment or dementia. The final model retained crystallised intelligence, depression, fruit and vegetable consumption, diabetes, and apolipoprotein E ε4 allele.
Relative impact of different risk factors
Estimations of population attributable fraction suggest that elimination of the ApoE ε4 allele from the general population would lead only to a 7.1% reduction in the number of incident cases of mild cognitive impairment or dementia over the next seven years. Genetic modification is clearly not a feasible goal for public health intervention, but as it constitutes one of the most significant risk factors for dementia we have taken it as a benchmark for the comparison of other exposures. The greatest impact in terms of prevention is estimated to come from increasing Neale adult reading test scores, leading to an 18.1% reduction in incidence of mild cognitive impairment or dementia. The reading test score—an indicator of crystallised intelligence, lifetime intellectual activity, and cultural exposure—is seen to have a greater impact than educational level, which was not retained by the initial risk model. This may be because it is a more accurate assessment of acquired learning than number of years of formal education in this generation, of whom many were exposed to war conditions (second world war and Spanish and Algerian civil wars), which interrupted schooling and professional training. Crystallised intelligence may be considered a proxy marker for exposure to intellectual activity, and determining whether this may have been confounded by association with higher physical activity might have been useful. Unfortunately, no simple, independent unitary measure of physical activity was available; however, a recent analysis has shown that the cognitive component of overall activity rather than the physical aspect is protective in relation to onset of dementia.27
The Neale adult reading test score is a combination of both genetic ability and cultural exposure, but this analysis cannot distinguish which component is having the effect of reducing incidence. In the absence of an answer to this central question, the public health message can only be to encourage literacy at all ages irrespective of innate ability.
Eliminating depression and diabetes and increasing fruit and vegetable consumption were estimated to lead to an overall 20.7% reduction in incidence of dementia. Of these, depression makes the greatest contribution; elimination of depression from the elderly population was estimated to lead to a mean 10.3% reduction in the number of new cases over seven years. Our analyses included treatment for depression and diabetes. The underlying assumption was that although treatment may have eliminated symptoms and reduced risk through decreasing length of exposure, the person has nevertheless been exposed to all the underlying negative biological effects associated with the disease state that may be linked to the aetiology of dementia, such as inflammation, increased permeability of the blood-brain barrier, damage to white matter, and raised cortisol concentrations. In this context, the corollary of our population attributable fraction analyses in terms of public health interventions is that these disorders should not so much be treated as prevented from occurring at all. This would imply targeting and monitoring of people at high risk and introducing preventive treatment where feasible.
However, the causal relation between depression and dementia remains unclear. Depression may be a prodromal sign of dementia, such that its treatment even at an early stage may not prevent onset of dementia, although previous research has suggested that its elimination can at least slow the rate of functional loss.45
Alternatively, depression may be an independent contributor to risk through, for example, inflammatory processes or hippocampal damage via a glucocorticoid cascade, such that treatment may delay onset. Meta-analyses have failed to adequately resolve this question,17
and an intervention programme aiming at preventing prolonged exposure to depression by early treatment (especially in family members of people with dementia) would greatly increase our current knowledge of this association.
Comparison with other studies
Recent papers reviewing promising strategies for prevention of dementia have underlined the importance of controlling vascular risk factors, mental activity, and depression, but have not been able to prioritise interventions or take into account exposure rates.46 47
Clinical research in recent years has focused principally on hypertension as an intervention measure; however, the HYVET-COG randomised controlled trial of prevention of hypertension actually found a lower two year incidence of dementia in the placebo group.48
Our analyses also suggest significant benefit not from elimination of hypertension alone but rather its associated risk factor diabetes. The recent study of Li et al further supports this finding, reporting significant reductions in the incidence of dementia among users of angiotensin receptor blockers,49
which offer increased protection against diabetes and stroke compared with other antihypertensive agents. However, given that the follow-up period in our study is shorter than that of some previous studies of hypertension, we may have underestimated the importance of this factor.
Potential for intervention
The general conclusion from our population attributable fraction analyses is that, in the continued absence of an effective treatment for the dementias, public health programmes should aim above all at prevention of diabetes, which is a well established risk factor for dementia, is unlikely to be simply a dementia prodrome, is highly prevalent, and is treatable. The high prevalence of this disorder in the elderly population means that intervention is likely to have a high impact and be cost effective, even though the relative risk is modest. Although increased fruit and vegetable consumption and crystallised intelligence also have high potential impact, their relation to dementia, and the intervening role of lifestyle factors, makes it difficult to formulate strategies for health intervention at a population level. Depression is also common, is relatively easy to treat, and frequently precedes onset of dementia; however, its status as a risk factor rather than (or as well as) an early feature of the dementia itself is not clear. Clinical levels of depression are, however, relatively easy to screen at a population level and should be treated whether or not they are a prodromal feature of dementia; this will in any case diminish the rate of functional loss.
The most reasonable way forward, taking into account the above considerations, would be the construction of an intervention programme within the general population aimed at early screening for glucose tolerance and insulin resistance and early treatment of raised depressive symptoms. These risk factors have been highlighted by previous epidemiological research, but this is the first study of comparative benefit, estimating the relative advantages of elimination of various risk factors. These factors are not necessarily the most important in terms of disease causality, but rather those whose elimination, by virtue of their frequency as well as their risk level, is likely to have the greatest impact in reducing the number of future cases.
This leads to the final question of the age at which such interventions should be made. Given that prevention rather than treatment of these chronic states is to be the focus of intervention, this would imply targeting a younger age group. Empirical evidence would seem to support this; for example, dementia is linked to diabetes and early changes in cerebrovascular vessels in mid-life.50 51
A great limitation of current epidemiological and clinical research on dementia has been its focus on cohorts over the age of 65, so that reliably estimating the extent of exposure to subclinical states before the onset of disorders such as depression and diabetes or determining the age at which intervention and prevention are most likely to be maximally effective has been impossible. Does controlling insulin resistance or eliminating depression have the same impact on incidence if it is carried out at 40 and 70 years?
Strengths and limitations
The main strength of our analyses is the use of a prospective database with diagnoses of dementia validated by neurologists, and not just according to a diagnostic algorithm, and also the inclusion of measures of almost all known modifiable risk factors. To our knowledge, this is the first attempt to model the effects of a theoretical population-wide prevention strategy which compares the relative effect of the removal of significant exposures.
The study is, however, open to several criticisms. We have made many decisions about level of exposure (for example biological thresholds and duration of symptoms), which may influence both hazard ratios and population attributable fraction calculations. Dimensional variables have been treated as binary, as required for population attributable fraction calculations, thus precluding the formulation of more precise clinical directives at an individual level but facilitating comparisons across cohorts. Although the calculation of potential impact fractions would have permitted the use of multiple categories and not just binary high and low exposure with these variables,52
the method assumes linearity, which we observed to not be the case. The use of potential impact fractions is also not considered appropriate when empirical data are available.
Although our model has examined individual risk factors while adjusting for all the others, we do not know, for example, to what extent they are inter-dependent in the real world such that totally eliminating one might modulate the appearance of others owing to other factors not accounted for here. Our findings should thus be validated in other datasets, using alternative definitions of exposure, before the construction of a public health intervention programme is considered. We have also made a decision to include mild cognitive impairment with dementia, although some of these people may not ever develop dementia. This seemed preferable to classifying them with the participants without dementia, given the very high risk of dementia in this group; retrospectively, this seems to have been the right decision given that only 7.6% of participants who developed full dementia in our study did not pass through a phase of mild cognitive impairment, thus confirming its status as a prodrome.
Our principal aim has been to show that the application of population attributable fractions to epidemiological studies of dementia may provide more meaningful directions for future public health initiatives than are currently used. However, the effectiveness of neutralising risk factors rests on the extent of the causal relation between the risk factor and onset of dementia. The risk factors included in this study have all been associated with credible underlying causative hypotheses, and confounding has been taken into account for a large number of factors, but the effect of their elimination cannot be precisely estimated in the absence of this information.
Conclusions and policy implications
The estimation of mean percentage population attributable fractions from a longitudinal study of risk factors for dementia suggests that reduction in the incidence of dementia over the next seven years would be maximised by the elimination of diabetes and possibly also depression (on the assumption that causality can be established such that it is clearly shown to be a risk factor and not just a disease prodrome). Increasing crystallised intelligence and consumption of fruit and vegetables also seem to have a potentially high impact at a population level but are difficult to implement as health prevention targets, as we cannot determine at which level of exposure they provide protective effects, and their relation to dementia is not easily differentiated from those of other lifestyle factors. Diabetes, or perhaps more specifically insulin resistance, stands for the moment as the primary target given that causality has been more clearly established than for the other factors highlighted in this analysis. Population attributable fraction calculations can provide only a crude estimate of impact on incidence, but they make a significant statement about public health priorities in disease prevention in the face of current knowledge. Epidemiological intervention studies in cohorts including younger adults are clearly needed to test the impact of intervention measures.
What is already known on this topic
- Multiple potentially modifiable clinical and environmental risk factors for dementia have been identified from population studies
What this study adds
- The relative impact on the incidence of dementia and mild cognitive impairment of removing different risk factors provides a hierarchy of priorities for public health interventions
- Removing diabetes and depression along with increasing crystallised intelligence and fruit and vegetable consumption seem to have a greater impact than modifying genetic risk
- Diabetes, and perhaps also depression, should be the principal targets of future population based health prevention programmes