Objective To systematically review the literature relating to the impact of multiple co-occurring modifiable risk factors for cognitive decline and dementia.
Design A systematic review and meta-analysis of the literature relating to the impact of co-occurring key risk factors for incident cognitive decline and dementia. All abstracts and full text were screened independently by two reviewers and each article assessed for bias using a standard checklist. A fixed effects meta-analysis was undertaken.
Data sources Databases Medline, Embase and PsycINFO were searched from 1999 to 2017.
Eligibility criteria For inclusion articles were required to report longitudinal data from participants free of cognitive decline at baseline, with formal assessment of cognitive function or dementia during follow-up, and an aim to examine the impact of additive or clustered comorbid risk factor burden in with two or more core modifiable risk factors.
Results Seventy-nine full-text articles were examined. Twenty-two articles (18 studies) were included reporting data on >40 000 participants. Included studies consistently reported an increased risk associated with greater numbers of intraindividual risk factors or unhealthy behaviours and the opposite for healthy or protective behaviours. A meta-analysis of studies with dementia outcomes resulted in a pooled relative risk for dementia of 1.20 (95% CI 1.04 to 1.39) for one risk factor, 1.65 (95% CI 1.40 to 1.94) for two and 2.21 (95% CI 1.78 to 2.73) for three or more, relative to no risk factors. Limitations include dependence on published results and variations in study outcome, cognitive assessment, length of follow-up and definition of risk factor exposure.
Conclusions The strength of the reported associations, the consistency across studies and the suggestion of a dose response supports a need to keep modifiable risk factor exposure to a minimum and to avoid exposure to additional modifiable risks. Further research is needed to establish whether particular combinations of risk factors confer greater risk than others.
PROSPERO registration number 42016052914.
- risk factors
- cognitive decline
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Strengths and limitations of this study
This is the first systematic robust evaluation of the evidence relating to impact of co-occurring modifiable risk factors for incident dementia and cognitive decline.
Strengths of this review include use of Cochrane-based methodology with a robust search strategy, detailed search terms and successful coverage of the data resulting in representation of study populations from 18 studies and 9 countries across Europe, Australia and North America with >40 000 participants and follow-up from midlife and late life.
Limitations include a lack of representation from other parts of the world and a restricted opportunity for evidence synthesis due to variability in reporting of individual study results.
Data were able to be combined for 5 of the 18 studies.
Modifiable risk factors for cognitive decline and dementia are now well established and several are similar to those for cancer and cardiovascular disease.1 2 In particular, these include smoking, low physical activity, sedentary lifestyle, poor diet, excess alcohol consumption, midlife obesity, high blood pressure, midlife high cholesterol and diabetes. Depression, low social engagement and low cognitive engagement have also been linked to risk of late-life dementia.1 2
To date, the literature linking such risk factors to incident cognitive decline and dementia has typically focused on the relationship between an individual risk factor and later cognitive outcome. Despite this, we know that the clustering or co-occurring of risk factors is the more likely scenario.3–5 Population observed risk factor clusters typically include smoking, excess alcohol intake, poor diet and low levels of exercise.3–5 However, although the best evidence for reduction in risk of cognitive decline comes from multifactorial clinical trials targeting multiple risk factors,6 there remains a lack of knowledge relating to the impact of risk factor burden and its composition. Targeting of effective public health risk reduction strategies for cognitive decline and dementia first requires identification of the ‘at-risk’ population. This, in turn, requires an understanding of the impact of co-occurring modifiable risk factors and the role of risk factor combinations or clusters (commonly occurring risk factor combinations) on incident dementia and cognitive decline.
Our objective is to systematically examine the literature addressing clustering or co-occurring modifiable risk factors for incident cognitive decline and dementia within individuals, and to estimate, using meta-analysis, the impact of exposure to one or more modifiable risk factors compared with absence of risk factors on the risk of future cognitive decline and dementia.
The databases Medline, Embase and PsycINFO were searched for articles published between January 1999 and March 2017 using the search terms (cluster* or cluster analysis or summative or score or scoring or scale or scales or measure or measurement or additive or cumulative) AND (dementia or Alzheimer* or cognitive or cognition disorders) AND risk factors, limited to Adults and English language publications. See online supplementary text 1 for details. To maximise identification of eligible studies, online supplementary focused electronic searches were undertaken to include scoring-related terms and cluster-related terms separately with risk factors, vascular risk factors and ‘vrf’. Reference lists of the included articles were also reviewed (online supplementary text 1).
Supplementary file 1
Longitudinal studies with an explicit aim to examine the impact of additive or clustered modifiable risk factor burden for combinations of multiple core modifiable dementia risk factors (hypertension or high blood pressure, hypercholesterolaemia or high cholesterol, diabetes, high body mass index, smoking, excess alcohol, low physical activity and poor diet).
Some evidence or clear implication that participants were free of cognitive decline or dementia at baseline assessment.
Use of formal assessment of cognitive function or dementia or clear implication that formal dementia diagnosis took place (eg, cognitive decline assessed using general screening or neuropsychological testing, dementia diagnosis using standard diagnostic tools).
Report of cognitive decline or dementia outcomes.
Non-English publications (in the absence of resources for translation).
Studies based solely on medical records without systematic assessment of risk factors.
Since the modifiable risk factors for dementia are primarily thought to commence their influence from early adult to mid-adult life, publications relating to non-adult populations were excluded.
Publications with delirium as a primary end point and those including populations with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADISIL) were excluded. Delirium is associated with acute cognitive decline and CADISIL populations have particular risk factor characteristics and are at high risk of subcortical dementia occurring in middle age or early old age.
Publications reporting results for metabolic syndrome as a unitary risk factor were excluded. Metabolic syndrome represents a single particular cluster of vascular risk factors (usually defined as a requirement for 3/5 from obesity, high blood pressure, high plasma glucose, high serum triglycerides, low high-density lipoprotein levels) and its impact has already been examined systematically.7 8
As we were seeking to examine the impact of modifiable risk factors, we excluded studies that included non-modifiable risk factors as an integral part of their risk measure, that is, where we could not evaluate the impact of modifiable risk factor burden.
Finally, we excluded comments, letters, editorials, guidelines, consensus documents and conference proceedings.
Search strategies were co-designed by a qualified information professional (AB) and the principal investigator (RP) who conducted the literature searches. Screening of abstracts, or titles where abstracts were unavailable, was performed independently by two reviewers (RP, JP) with each reviewer compiling a list of studies for potential inclusion. The two reviewers compared lists with differences being resolved by discussion. Full-text copies of the selected papers were obtained by the principal investigator and assessed independently for inclusion by each reviewer. Reference lists of the selected manuscripts were screened to identify other potentially relevant published papers.
Data were extracted independently by each reviewer and included papers were independently assessed for quality by both reviewers. An overall agreed risk of bias judgement was arrived at by consensus. A formal quality scoring scheme was not used as these can have poor discriminant ability; however, each paper was assessed against the key factors adapted from the Critical Appraisal Skills Programme checklists for evaluating randomised controlled trials and cohort studies, respectively (http://www.casp-uk.net/casp-tools-checklists).
Data relating to the population reported in each study (number, age at baseline, % female at baseline), plus length of follow-up, risk factors included and where applicable, cut-off points used to define presence of risk factor, cognitive outcomes, methods of risk factor combination and analysis, covariates and reported results were extracted to a standard data extraction form. Where various versions of the results were available, the most conservative, most adjusted results were selected. Narrative synthesis was applied to describe and summarise the results of the included studies. Where summary measures included OR, HR or relative risks (RR), data relating to impact of clustering, defined as specific co-occurring risk factors or number of co-occurring modifiable risk factors were combined using meta-analytic techniques. The I2 measure was used to assess the percentage of variation across studies due to heterogeneity rather than chance. Where possible, publication bias was also examined using Egger’s test and visual inspection of funnel plots.
The protocol for this review is registered with PROSPERO: the International prospective register of systematic reviews CRD42016052914. Published data were used. Neither ethical approval nor consent for participation or publication was required.
We acknowledge the importance of patient/carer/lay person involvement in research. Although patients/service users/lay people were not involved directly in the design of this systematic review, the development of the research question was supported and informed by several discussions held by the first author with older adult patient, carer and lay person groups on the subject of modifiable risk factors for dementia. As this was a review of published literature, there are no direct study participants and no opportunity to involve patients/carers or lay people in the development of outcome measures or in recruitment. We have thanked all participants of the contributing studies in the acknowledgements section and will be disseminating results to both lay and scientific audiences via presentations, publications and international dementia organisations.
The main systematic literature search resulted in 8916 records for review. The two supplementary focused electronic searches yielded 970 and 2870 records (supplementary text 1 shows all search strategies). A further 10 references were identified from reference lists and expert recommendation. Abstract review resulted in 101 records retained for full-text evaluation (figure 1). Seventy-nine records were excluded: 8 because it was unclear whether the sample populations had been free of cognitive decline at baseline,9–16 9 due to a lack of appropriate cognitive outcomes,17–25 49 due to a lack of appropriate risk factor data, combining modifiable and non-modifiable risk factors or where risk factor relationships were not evaluated.26–74 Eleven were not longitudinal75–85; one was a review article86 and one a commentary.87 Twenty-two articles relating to 18 cohort studies were included in the review.88–109 There were two studies with multiple publications: the Whitehall II study106 107 and the Washington Heights Ageing Project.89 94 97 The articles differed in inclusion of risk factors, outcomes and analysis methods and so all were reported in the narrative results. Six studies reported risk ratios for risk factor exposure and incident dementia or Alzheimer’s disease (AD) allowing meta-analyses.88 89 93 98 100 101
The included studies totalled over 40 000 individuals recruited from high-income countries: the USA,88–97 Sweden,98–100 Finland,101 the Netherlands,102 103 Germany,104 France,105 the UK,106 107 Australia108 and Korea109 (table 1). Study sample sizes ranged from 322102 to 8845.93 Two studies recruited only men88 98 and for five articles, >50% of the participants were male.95 102 103 106 107 There were no female-only studies. Study follow-up varied from 22 months92 to over 20 years.88 90 93 96 101 Detailed comparison of follow-up is difficult, as different articles provided the information in differing ways. However, a broad categorisation can be made into very short follow-up, estimated at <5 years,92 109 short follow-up, estimated at >5–10 years,89 94 95 99 100 104 106 108 moderate follow-up, estimated at >10–20 years91 97 98 102 103 105 107 and long follow-up, estimated at >20 years.88 90 93 96 101 There were 12 articles where baseline measures were taken in midlife (>40 and ≤65 years)88 93 96 98 99 101–103 105–108 and 9 articles where the baseline was in late life (>65 years).89 91 92 94 95 97 100 104 109 One study included those in earlier adult life with baseline age ~26 years.90
Eight manuscripts reported on dementia outcomes using standard diagnostic criteria,88 89 95 97 98 100 101 1032 used a dementia diagnosis made as part of medical treatment but did not give details of diagnostic criteria,93 1045 reported results specifically for AD88 89 97 98 100 and 12 reported on non-dementia cognitive outcomes. Cognitive measures included use of a screening test92 109 or a neuropsychological battery.91 94 96 99 102 105–108 See table 2 for details of the diagnostic criteria and assessment tools used by each study.
Risk factor measurement
Articles varied in their selection of risk factors and the risk factors varied in number (from 2 to 13) and definition. See table 1 and online supplementary table 1 for details of risk factors included in each study and the cutpoints used to define presence of risk factors. Substantial overlap was identified for coverage of risk factors between studies; the most commonly included risk factors being smoking and hypertension or high blood pressure, although no single risk factor was common to all studies (table 1).
Different analyses aggregated risk factors or unhealthy behaviours or protective factors or healthy behaviours in different ways (table 2). Three used some form of clustering, cluster analysis, latent factors or principal component analysis and examined the relationship between membership of each cluster and cognitive outcome,95 99 105 15 studies categorised each risk factor as present or absent (1 or 0) and then generated a variable which was the total number of risk factors present.88–94 96 98 100 101 104 107–109 Three elaborated further by creating a weighted risk score97 102 103 and one used categories to combine two risk factors (alcohol and smoking) to examine additive impact.106
In general, studies used either linear, logistic or Cox proportional hazard regression (tables 2 and 3) to examine the relationship between baseline risk and cognitive outcomes; one study used latent growth curves106 and one provided graphical results only.96 Five studies looked at the inverse of risk factors and reported on protective or ideal health behaviours.90 91 97 104 109 Most studies adjusted for age, sex and education and/or socioeconomic status (tables 2 and 3); one adjusted for age and sex only102; one for sex only91; one for patterns of test completion and sex and in one case no information on the method of covariate adjustment was provided.96
Association between risk factors and cognitive outcomes and/or dementia
Study findings showed remarkable similarity with the majority reporting a relationship between exposure to increased risk factor load and subsequent poorer cognitive function or dementia (table 3). No clear differences of results were observed by baseline age group, that is, cohorts in midlife or late-life at baseline, or for length of follow-up, although the varied presentation of study results meant that formal statistical testing could not be performed.
Eleven articles reported a relationship between risk factors and cognitive outcomes88 89 92 93 96 98–103; three between unhealthy behaviours105–107 and poorer cognitive outcomes; three reported a relationship between protective factors97 104 109 and two between ideal health behaviours90 91 and better cognitive outcomes at follow-up. For the remaining studies, that is, those that reported a more mixed relationship between risk factor exposure and increased risk, the Personality and Total Health study found that only reaction time showed a relationship between risk factors and cognitive outcomes108; for the Schneider et al analyses of the Washington Heights study, risk factors were only associated with a small attenuation in decline in memory measures in black participants94 and in the Cache Country study, the unhealthy behaviours plus religious belief cluster showed an increased risk of dementia, while the unhealthy behaviour, non-religious group and the healthy behaviour groups did not.95 In addition to the Cache County study, two further studies examined the relationship between groups of co-occurring risk factors. The Supplementation en vitamines et mineraux antioxy dants study study reported that their unhealthy lifestyle latent factor was associated with poorer memory but not with executive function and that the main drivers for this association were low fruit and vegetable consumption and low physical activity.105 The Betula Study found that varying clusters of health components (metabolic, glycaemic, lipid, thyroid, inflammatory and nutritional clusters) had varying relationships with differing cognitive abilities with the metabolic component showing the strongest relationships99 (table 3).
Finally, results were essentially consistent across the studies with more than one publication. The Whitehall study found a relationship between increased risk factor exposure and different measures of cognitive decline using both latent growth curve106 and logistic regression analyses107; the Washington Heights study reported an increased risk of incident AD89 with greater numbers of risk factors and a lower risk of incident AD with greater health behaviours (diet and physical activity).97
Six studies provided various risk ratios for the impact of one, two or three or more risk factors; five for incident dementia88 93 98 100 101 (figure 2 and online supplementary text 2 show results of each meta-analysis) and three for AD (online supplementary figure 1).89 98 100 Forest plots of these showed a clear dose response such that higher numbers of risk factors were associated with an increased risk. Based on the rare disease assumption,110 RRs, ORs and HRs were combined in two separate meta-analyses, one for dementia and the other for AD, yielding pooled ratios for presence of one, two and three or more risk factors compared with no risk factors. A fixed effects meta-analysis was used because the number of studies was small preventing a good estimate of the between study variance, however for comparability results are also reported for a random effects model. See online supplementary text 2 for details of the meta-analyses. For dementia outcomes fixed effect pooled risk ratios for one risk factor were 1.2 (95% CI 1.0 to 1.4), for two risk factors 1.7 (95% CI 1.4 to 1.9) and for three or more risk factors 2.2 (95% CI 1.8 to 2.7).88 93 98 100 101 Results for the random effects model did not differ. Heterogeneity was low and there was no evidence of publication bias (online supplementary text 2). For AD,89 98 100 fixed effect pooled risk ratios for one risk factor were 1.2 (95% CI 0.9 to 1.5), for two risk factors 1.8 (95% CI 1.4 to 2.3) and for three or more risk factors 1.2 (95% CI 0.2 to 6.1). The results for the random effects model were 1.2 (95% CI 0.9 to 1.6) for one risk factor, 1.8 (95% CI 1.2 to 2.8) for two risk factors and 1.5 (95% CI 0.9 to 2.5) for three or more risk factors. For AD, the heterogeneity was high and the number of constituent studies was low, restricting analysis of publication bias (online supplementary text 2). Visual examination of the plotted results per incremental risk factor for the studies included in the meta-analysis showed no clear pattern by study baseline age, population sex distribution, length of follow-up or study covariates; however, the small numbers precluded meta-regression or other formal statistical testing.
Of the 22 articles, 14 were assessed as having an overall medium risk of bias88 92 93 95 96 98 99 101 102 104–107 109; 7 as having a low risk89 90 94 97 100 103 108 and 1 as having high risk.91 Risk of bias was assessed with regard to recruitment, exposure (eg, assessments of risk factor exposure), outcome (eg, assessment tools, use of blinded assessors) and follow-up (eg, attrition, length of follow-up) (online supplementary table 2). Several studies analysed population-based cohorts,89 92–97 99–103 108 109 some specifying that their analyses were based on selective populations.90 91 95 96 98 101 102 105 Two studies were specifically designed to recruit selective populations; the Honolulu Asia Ageing Study which only included Japanese American men living in Honolulu88 and the Whitehall study which recruited exclusively from a civil servant population.106 107 Two further studies recruited from previously existing healthcare provider or insurance databases.93 104 All studies used recognised and standard measures to characterise baseline risk factors, although variation in the evidence base, current guidelines and recommendations at the time of study data collection and analysis inevitably resulted in diverse risk factor definitions.
Regarding outcome measurement and length of follow-up, two studies reported follow-up likely to be <5 years, putting them at risk of reverse causality92 109; however, five studies reported long (ie, >20 years) follow-up88 90 93 96 101 and three of these reported incident dementia outcomes.88 93 101 Two studies used dementia outcomes taken from medical databases,93 104 which may have underestimated the number of cases, but all other studies used standard diagnostic criteria or standard neuropsychological tests. The majority of studies reported on incident dementia or on change in cognitive function assessed using neuropsychological tests; however, five studies reported cognitive function only at follow-up, potentially including prevalent, rather than incident, cases of poor function.90 96 102 105 107 The majority of studies adjusted for age, sex and education, although some carried out further adjustment for wider covariates. Finally, details of how researchers had accounted for missing data and attrition were not consistently reported with information provided in around half the articles.90 92 94 96 97 99 100 105–108
This systematic review of the evidence base relating to intraindividual co-occurring modifiable risk factors for dementia and cognitive decline found a clear relationship between the presence of/exposure to greater numbers of baseline risk factors and an increased risk of later cognitive decline or incident dementia. The converse was also seen in identifying a relationship between greater numbers of protective factors or healthy behaviours and a reduced risk of cognitive decline or dementia.
Studies reporting risk ratios for all-cause dementia per incremental risk factor consistently demonstrated a clear dose-response relationship. When combined in a meta-analysis, a 20% increase in dementia risk with the presence of one risk factor (combined risk ratio 1.2 (95% CI 1.0 to 1.4)) was observed rising to 65% for two risk factors (1.7 (95% CI 1.4 to 1.9)). Presence of three risk factors doubled the risk of dementia with a combined risk ratio of 2.2 (95% CI 1.8 to 2.7). Fewer studies and incident cases were identified for a similar meta-analysis of AD with the dose response only being evident for the presence of one and two risk factors.
Although data relating to summed risk or protective factors showed clear relationships with cognitive outcomes, limited data were available on clustering of specific risk factors and subsequent cognitive outcomes. Only three studies used statistical clustering techniques and the methods are too diverse and the results too varied to allow conclusions to be drawn.
To our knowledge, this is the first review to examine the impact of intraindividual co-occurring modifiable risk factors and risk of dementia and cognitive decline. As such, comparison to prior similar work in this area is difficult, however, scoring systems involving the sum, or weighted sum of individual risk factors, including both modifiable and non-modifiable risk factors, have been widely used in other areas such as cancer,111 all-cause mortality112 and, especially, cardiovascular disease.113 A recent systematic review reported on 363 such cardiovascular disease risk scores or models114 and several such cardiovascular and other scores have also been used to predict dementia outcomes.46 Our findings are congruent with such scoring systems and are biologically plausible with higher numbers of vascular risk factors in midlife associated with elevated amyloid deposition in addition to vascular damage.115 What our findings add is the first quantifiable estimation of the impact of risk factor accrual. What we were unable to add is evidence related to particular risk factor clusters. In fact, data on the impact of modifiable risk factor clusters are rare, although recent work on all-cause mortality found that combinations of specific risk factors, for example, physical inactivity, prolonged sitting and short or long sleep duration are associated with higher levels of mortality risk.112
Our review is inevitably limited by its exclusive dependence on published results. This meant that we were unable to: i) statistically evaluate trends within individual studies, ii) evaluate the impact of additional covariates, iii) evaluate the impact of particular population characteristics or iv) the potential for particular risk factors having a greater or lesser impact. We were also unable to explore the relationship between specific risk factor clusters or between greater risk factor burden and cognition beyond that assessed by the included studies and there was considerable variability in the modifiable risk factors addressed in each study (online supplementary table 1), thus limiting the opportunity for unpicking individual factor impact. A further limitation relates to restricting inclusion to known and widely accepted modifiable risk factors. While this makes findings more amenable to public health dissemination, it may omit important unknown or emerging modifiable risk factors, such as air pollution.116 117 Furthermore, despite not being amenable to intervention and therefore not the focus of this review non-modifiable risk factors also undoubtedly play a role. The use of a binary classification for risk or protective factors, while clinically practical, may also have resulted in a loss of subtlety, particularly since definitions of risk differed across studies. Risk factors are also associated with participant attrition and few studies took this into account in modelling. Furthermore, few papers considered potential treatment effects. Finally, although we concentrated on adulthood, emerging evidence is suggesting a potential role for accrual of exposure to vascular risk factors in childhood and poorer cognition in midlife.118
Inevitably results drawn from longitudinal cohort studies are subject to bias, and, as is often the case in systematic reviews, the length of follow-up, assessment of outcomes and use of covariates varied. The strength of the evidence also needs to take into account the two studies contributing more than one analysis. Furthermore, generalisability may also be limited since the study populations were drawn exclusively from high-income countries and, as such, may reflect a more homogeneous, and potentially more medicated or treated, population than those in low-income and middle-income countries where risk factor prevalence, recognition and treatment rates may differ.
A further consideration in the existing studies is the way in which age is considered beyond its role as a covariate. Age is the most important risk factor for dementia well into the tenth decade119 and although not a modifiable risk factor, it is a source of important and thus far poorly understood heterogeneity in risk for many diseases of older age, including dementia.120 The role of age, or time, in evaluating duration, as well as presence, of risk factors may be key and so far few studies have examined this.121–126 Ageing is associated with widespread processes of deficit accumulation: beginning at molecular and subcellular levels,127 and scaling up128 to become detectable as biomarkers129; then by routine laboratory methods130 and then clinically.130 In general, the studies of deficit accumulation, in both general samples and in special groups such as people with HIV-AIDS131 or intellectual disabilities,132 show that any risk factors which are age-related and adverse (eg, associated with mortality) will increase the risk of cognitive decline. This sometimes raises the objection that combining deficits in this manner makes it hard to know which ones are important. The counterargument is that this is not how age-related disease works. Often, many of the factors that in the aggregate are strongly associated with dementia (and which notably reduce the explanatory value of age) are not themselves significantly associated with cognitive decline when considered one at a time.124–126 The better remedy is to consider which other factors might mitigate (eg, health protective behaviours) or exacerbate (eg, social vulnerability) the adverse effects of such deficits on cognition.125 As this approach is comparatively new—at least in its application to cognitive decline and dementia—there is as yet little to review. Given, however, the recent report from two prospective, community-based autopsy studies, showing that in one-quarter of patients with a history of delirium, accelerated cognitive decline was not related to classical neuropathology suggests that there is much to learn about how late-life dementia is related to overall health.133 Such observations encourage widening the scope of investigative approaches.
Notwithstanding these limitations, this is the most comprehensive and, to our knowledge, the first synthesis of evidence on the impact of co-occurring risk factors for dementia. It presents an evidence base that is largely consistent and may imply a potentially very simple relationship such that the higher the number of risk factors to which a person is exposed the greater their risk. The potential for a causal relationship is supported by the consistent finding across studies, the use of population-based samples although with some inevitable risk of bias, the longitudinal nature of the data, the suggestion of a dose-response relationship and the strength of the association between the summed risk factors. Further research is required to determine whether particular combinations of risk factors have greater impacts on cognitive function than others, which clinical thresholds should be used to classify risk or whether relationships differ in different population groups, for example, at extreme age. More understanding is also needed for the relationship between modifiable and non-modifiable factors and risk factor combinations, not least to stratify population subgroups and identify those at highest risk. Currently, the best course of action for both individuals and health organisations would be to seek to keep modifiable risk factor exposure to a minimum and to prevent exposure to further risk factors. The current findings support the use of risk indices for screening those at high risk of dementia and indicated for intervention.
The evidence relating to the impact of co-occurring, within individual, risk factors and the risk of cognitive decline or dementia is highly consistent. It demonstrates that greater numbers of risk factors are associated with worse cognitive outcomes and greater numbers of protective factors with better cognitive outcomes. We provide quantitative evidence of a dose response such that one risk factor is associated with an 20% increase in risk of incident dementia, two risk factors with an 65% increased risk and three or more with a doubling of risk. Our results support the need for clinicians, public health organisations and individuals to keep risk factor exposure to a minimum and even where risk factors are present to prevent further accrual.
The authors gratefully acknowledge the contribution and commitment of the participants and study teams from each of the constituent studies used in the review.
Contributors RP conceived and designed the study, carried out the data extraction, analysis and drafted the manuscript. AB helped design the study and the search strategy and commented on the manuscript. KR helped design the study, and commented on the manuscript. JP helped design the study, extracted the data and commented on the manuscript. CDE advised on the statistical methods and commented on the manuscript. KJA helped design the study and commented on the manuscript. All authors had full access to study data.
Funding No funding was received specifically for this work. RP is funded by the Australian Dementia Collaborative Research Centre. AB’s input into the literature search and review design was undertaken under his University of Sheffield employment contract. KR is funded through the Dalhousie Medical Research Foundation as the Kathryn Allen Weldon Professor of Alzheimer’s Research and receives research funding from the Canadian Institutes of Health Research, the Canadian Frailty Network and the Fountain Family Research Fund of the Queen Elizabeth II Health Sciences Centre. JP received no support from any organisation for the submitted work. KJA is funded by NHMRC Fellowship APP1102694.
Competing interests RP, AB, JP, CDE, KJA report no disclosures. KR founded DGI Clinical, which has contracts with pharma for individualised outcome measurement and for data analytics, including in dementia studies with Otsuka and Roche. In 2017, he participated in an Advisory Board meeting on dementia for Lundbeck and in 2014 spoke at a satellite symposium at the Alzheimer Association International Conference, sponsored by Nutricia.
Patient consent Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement The data supporting the results are publicly available in the published literature. RP affirms that the manuscript is an accurate honest and transparent account of the study being reported. No important aspects of the study have been omitted, any discrepancies between the study as planned and registered are explained. Funding bodies had no role in the inception, design, completion or publication of this work.
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