Frailty syndrome and the risk of vascular dementia: The Italian Longitudinal Study on Aging

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1 Alzheimer s & Dementia 9 (2013) Frailty syndrome and the risk of vascular dementia: The Italian Longitudinal Study on Aging Vincenzo Solfrizzi a, *, Emanuele Scafato b, Vincenza Frisardi c, Davide Seripa c, Giancarlo Logroscino d, Stefania Maggi e, Bruno P. Imbimbo f, Lucia Galluzzo b, Marzia Baldereschi g, Claudia Gandin b, Antonio Di Carlo g, Domenico Inzitari h, Gaetano Crepaldi e, Alberto Pilotto c,i, Francesco Panza c, *; for the Italian Longitudinal Study on Aging Working Groupy a Department of Geriatrics, Center for Aging Brain, Memory Unit, University of Bari, Bari, Italy b Population Health and Health Determinants Unit, National Centre for Epidemiology, Surveillance; and Health Promotion (CNESPS), Istituto Superiore di Sanita (ISS), Roma, Italy c Geriatric Unit and Gerontology-Geriatrics Research Laboratory, Department of Medical Sciences, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy d Department of Neurological and Psychiatric Sciences, University of Bari, Bari, Italy e Aging Section, Italian National Research Council (CNR), Aging Section, Padova, Italy f Research and Development Department, Chiesi Farmaceutici, Parma, Italy g Department of Neurological and Psychiatric Sciences, University of Firenze, Firenze, Italy h Institute of Neuroscience, Italian National Research Council (CNR), Firenze, Italy i Geriatric Unit, Azienda ULSS 16 Padova, S. Antonio Hospital, Padova, Italy Abstract Keywords: Background: Frailty is a clinical syndrome generally associated with a greater risk for adverse outcomes such as falls, disability, institutionalization, and death. Cognition and dementia have already been considered as components of frailty, but the role of frailty as a possible determinant of dementia, Alzheimer s disease (AD), and vascular dementia (VaD) has been poorly investigated. We estimated the predictive role of frailty syndrome on incident dementia and its subtypes in a nondemented, Italian, older population. Methods: We evaluated 2581 individuals recruited from the Italian Longitudinal Study on Aging sample population consisting of 5632 subjects aged 65 to 84 years and with a 3.9-year median follow-up. A phenotype of frailty according to a modified measurement of Cardiovascular Health Study criteria was operationalized. Dementia, AD, and VaD were classified using current published criteria. Results: Over a 3.5-year follow-up, 65 of 2581 (2.5%) older subjects, 16 among 252 frail individuals (6.3%), of which 9 were affected by VaD (3.6%), developed overall dementia. In a proportional hazards model, frailty syndrome was associated with a significantly increased risk of overall dementia (adjusted hazard ratio: 1.85; 95% confidence interval: ) and, in particular, VaD (adjusted hazard ratio: 2.68; 95% confidence interval: ). The risk of AD or other types of dementia did not significantly change in frail individuals in comparison with subjects without frailty syndrome. Conclusion: In our large population-based sample, frailty syndrome was a short-term predictor of overall dementia and VaD. Ó 2013 The Alzheimer s Association. All rights reserved. Vascular dementia; Cerebrovascular disease; Dementia; Alzheimer s disease; Cognition; Frailty y The members of the Italian Longitudinal Study on Aging Working Group can be found in the Appendix at the end of this article. *Corresponding author. Tel.: ; Fax: (V.S.) and Tel.: ; Fax: (F.P.). address: v.solfrizzi@geriatria.uniba.it (V.S.), geriat.dot@ geriatria.uniba.it (F.P.) 1. Background Frailty, an increasingly important concept in both clinical care of older persons and research on aging, has been defined as a biological syndrome of decreased reserve and resistance /$ - see front matter Ó 2013 The Alzheimer s Association. All rights reserved. doi: /j.jalz

2 114 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) to stressors, resulting from cumulative declines across multiple physiologic systems and causing vulnerability to adverse outcomes such as falls, disability, institutionalization, and death [1]. However, frailty is probably a more elusive concept, and at present, how best to operationalize frailty is controversial [2 4]. Using data from the Cardiovascular Health Study (CHS), Fried et al developed an operational definition of frailty in older subjects based on the presence of any three of the following five characteristics: shrinking, weakness, poor endurance, slowness, and low activity [1]. However, another definition of frailty was based on a multidimensional approach; therefore, for evaluation of frailty, a frailty index is used, which is calculated by considering a number of potential deficits [3]. These deficits can be symptoms, signs, diseases, disabilities, or abnormal laboratory values; therefore, an integral conceptual definition of frailty as a multisystem physiological change occurring in the elderly population that determines an increase of risk for accelerated physical and cognitive decline, disability, and death, even in absence of specific diseases, can be developed [3,4]. Thus, although some population-based studies confirmed original findings from the CHS of the overlaps and dissociations between frailty, disability, and comorbidity [5], important differences in the prevalence estimates of frailty were reported by other studies (from 6.9% to 22.7%) [2,5,6]. In this regard, very recently, in the Italian Longitudinal Study on Aging (ILSA), which evaluated 2581 individuals from a population-based sample of 5632 subjects aged 65 to 84 years, a phenotype of physical frailty was operationalized after slightly modifying the CHS criteria [1], and was identified by the presence of three or more frailty components. In the ILSA, a prevalence rate of 7.6% (95% confidence interval [CI]: ) for physical frailty in a community-defined cohort of 65- to 84-year-old subjects was found [7]. The inclusion of other common age-related conditions, potentially linked to frailty, is a topic of considerable debate [8]. Of these age-related conditions, cognition has already been considered as a component of frailty [9], and it has been demonstrated that it is associated with adverse health outcomes [6,10]. In the ILSA, both lower cognition and greater depressive symptoms were cross-sectionally associated with physical frailty [7]. Moreover, frail demented patients were at higher risk of all-cause mortality, but not of disability, over 3- and 7-year follow-up periods [7]. In a recent population-based study, frailty status in older Mexican Americans cognitively unimpaired at baseline was an independent predictor of cognitive decline over a 10-year period [11]. Furthermore, several studies have reported that physical frailty is significantly associated with low cognitive performances, including incidence of Alzheimer s disease (AD) [12], mild cognitive impairment (MCI) [13], and AD pathology in older persons with and without dementia [14]. At present, there is no population-based study in which frailty syndrome has been investigated as a possible determinant of vascular dementia (VaD). In the present study, we explored the hypothesis that frailty was associated with a greater risk of developing dementia and its subtypes in older individuals without cognitive impairment. 2. Methods 2.1. Setting The methods of the ILSA and the first and second survey data collection have been described in detail elsewhere [15,16]. A sample of 5632 free-living or institutionalized subjects aged 65 to 84 years was randomly selected from the electoral rolls of eight Italian municipalities after stratification for age and sex. Following the equal allocation strategy, in each study center, four age classes (65 69 years, years, years, and years) of 88 subjects for each sex were drawn up. The data of the present report have been obtained during the first prevalence survey study, between March 1992 and June 1993 (prevalence day: March 1, 1992), and the second prevalence survey study, between September 1995 and October 1996 (prevalence day: September 1, 1995). The study project was approved by the institutional review board of the eight municipalities. Voluntary informed consent was obtained from each subject and/or their relatives before enrollment Clinical examination and laboratory analyses In phase 1, each subject was administered a screening questionnaire, a series of brief screening tests to identify suspect cases for further investigation, and a clinical evaluation. In phase 2, suspected cases were clinically confirmed with a standardized clinical examination by a certified neurologist or geriatrician. Cases of coronary artery disease (myocardial infarction or angina pectoris), type 2 diabetes mellitus, hypertension, stroke, and peripheral artery disease were identified with a two-phase procedure, using clinical criteria described in detail elsewhere [15,16]. In particular, the main screening criteria for cognitive impairment or dementia were the Mini-Mental State Examination (MMSE) with a cutoff score of 23 [17] and a previous diagnosis reported by the respondent proxy. The diagnosis was based on the Diagnostic and Statistical Manual of Mental Disorders, third edition, revised, criteria for dementia syndrome [18]; the National Institute of Neurological and Communicative Disorders and Stroke Alzheimer s Disease and Related Disorders Association criteria for possible and probable AD [19]; and the International Statistical Classification of Diseases and Related Health Problems,10th revision (ICD-10) criteria for VaD and other dementing diseases [20]. Body mass index was calculated as weight/height 2 (kg/m 2 ). Based on self-reports, smoking habits were categorized as ever or never. Furthermore, smoking habits were assessed by asking the study participants the amount of cigarettes they smoked and the ages when they started and stopped smoking; using these data, the variable pack-years (years smoked! usual number of cigarettes smoked/20 cigarettes per pack) was derived. Depressive symptoms were investigated using

3 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) Table 1 Characterization of frailty syndrome in the ILSA (modified Cardiovascular Health Study criteria) [1] Components of frailty* Weight loss Exhaustion Weakness y Slowness x Low physical activity { ILSA measurements Unintentional weight loss.5 kg in the past year (possibly supported by the answer to the question: Do you think that your clothes are wide? ) GDS score 10 and negative answer to the question: Do you feel full of energy? Negative chair stand test: Inability to stand from a chair unaided, or without using the arms (standardized by sex and body mass index) z Time 7 seconds spent to walk 5 m (standardized by sex and height) z Physical activity questionnaire: Inactive or light physical activity (retrospective evaluation) or asking Do you practice physical activity? (prospective evaluation) (standardized by sex) Abbreviations: ILSA, Italian Longitudinal Study on Aging; GDS, Geriatric Depression Scale, a score of,10 indicates absence of depression, between 10 and 19 mild depression, and.20 to a maximum of 30 severe depression. * Positive for phenotype of frailty syndrome: presence of three or more criteria. y Men 66/101 and women 97/151 frail individuals; c 2 : 0.56, P z Test included in the Motor Performance battery of the ILSA [26,27]. x Men 53/101 and women 72/151 frail individuals; c 2 : 0.03, P { Men 98/101 and women 140/151 frail individuals, c 2 : 2.15, P 5.14, as overly conservative measure of agreement between prospective and retrospective measurements for low activity was used (Cohen s k: 0.12, P,.01). the Italian version of the Geriatric Depression Scale (GDS) 30 items [21]. Functional status was assessed with the activities of daily living (ADL) scale, which determines the level of independence in the following six activities: bathing, dressing, toileting, transferring from bed to chair, continence, and feeding [22]. Ability in home management (using the telephone, shopping for personal items, preparing meals, doing personal laundry, managing money, doing light housework, managing drugs, and traveling independently) was assessed by the instrumental activities of daily living (IADL) scale [23]. The physical activity practice was assessed by the administration of a structured questionnaire, specifically developed for the InCHIANTI Study and also proposed for the ILSA, ascertaining physical activities retrospectively, as well as frequency and duration [24,25]. Levels of physical activity in the year before the interview were coded into an ordinal scale as follows: 1, hardly any physical activity; 2, mostly sitting (occasional walks, easy gardening); 3, light exercise (no sweating) 2 to 4 h/wk; 4, moderate exercise (sweat) 1 to 2 h/wk (level 4); 5, moderate exercise.3 h/wk; 6, intense exercise (at the limits).3 times/wk. According to this classification, we grouped the participants as follows: 1 to 3, inactive or light physical activity; 4 to 5, moderate physical activity; 6, intense physical activity [24]. Physical function was also ascertained prospectively with ADL and IADL tasks, as well as the GDS item Do you practice physical activity? [21]. Motor performance was assessed using the six tests of a battery designed to measure motor ability in older people [26,27]. In particular, three of them explored dynamic balance and coordination: time to stand from a chair unaided and without using the arms, the number of times a subject could step up onto a single 23-cm step in 10 seconds, and the number of errors made in performing a tandem walk along a 2-m line (5-cm wide). Three other tests assessed static balance: time standing on one leg, number of steps and time spent to walk 5 m, and number of steps to complete a180 turn. A total score, ranging from 0 (worst possible performance) to 14 (best possible performance), was obtained by summing up single items scores. Interobserver correlations for the timed and counted tests, such as the chair stand and rapid step ups, ranged from 0.93 to 0.99 [26]. Intraobserver reliability for the timed and counted tests yielded correlations of 0.71 for tandem gait errors, 0.80 for reaction time, and 0.89 to 0.96 for chair stand, rapid step ups, standing on one leg, step length, and walking speed [26]. The k values for interobserver agreement on gait abnormalities ranged from 0.38 for step asymmetry to 0.82 for an abnormal turn, and for intraobserver agreement, they ranged from 0.63 for path deviation to 0.82 for abnormal turn [26]. In the ILSA, the k agreement between independent examiners rating total score was This score showed a high internal consistency with ADL and IADL scores and independently predicted death and disability [27]. The Charlson comorbidity index (CCI), a weighted index that takes into account the number and the seriousness of comorbid disease, was performed [28]. Data on vital status were gathered directly from individuals or proxy responders. Death certificates were collected for each individual who had died. The date and cause of death for all participants who died were obtained from death certificates and other official sources, and trained physicians coded the cause of death according to the International Classification of Disease, 9th revision. Blood samples were obtained early in the morning after a 13-hour overnight fast. Serum albumin was measured by electrophoresis, as detailed elsewhere [29] Operationalization of the frailty syndrome A phenotype of frailty was operationalized after slightly modifying the CHS criteria [1], and was identified by the presence of three or more frailty components, as shown in Table 1. For the second component exhaustion, we considered only the demented patients who received an MMSE score of.15 to make plausible GDS scores [30]. At baseline, we excluded older subjects with severe sensorial deficit;

4 116 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) those who were bedridden or in wheelchairs; and those who had dizziness, severe osteoarthritis, a history of Parkinson disease, stroke, dementia, or an MMSE score of,15, as these conditions could potentially constitute frailty components as a consequence of a single disease (Figure 1) Statistical analysis All analyses have been performed using SAS statistical software (SAS/STAT user s guide, V.9.1; SAS Institute, Cary, NC [2004]). Except for pack-years of cigarettes (Mann Whitney U test), we used usual parametric statistical tests. In particular, for normally distributed variables measured with an interval scale of measurement, we used Student t test for independent samples (age, education, body mass index, MMSE, ADL, IADL, GDS, CCI, and serum albumin levels) and Pearson c 2 test for categorical variables (sex, frailty status, hypertension, type 2 diabetes mellitus, coronary artery disease, stroke, and congestive heart failure). Incidence rates of dementia (all causes) and types of dementia (AD, VaD, and other dementias) for frailty syndrome and its individual components were calculated as the number of events per 1000 person-years at risk. Cox proportional hazards models, which were modeled separately, excluding subjects affected by dementia or having an MMSE score of,15, were used to assess the independent contribution over 3 years (median duration of follow-up was 3.9 years) of baseline frailty syndrome to time to new events of dementia, AD, VaD, and other dementias. The proportional hazard assumption over time for the covariates of interest was checked, including in the Cox model, each covariate by time as a predictor variable. Indicators for frailty (three or more frailty criteria) were established, with the at-risk or nonfrail group (less than three frailty criteria) serving as the reference group. Partially adjusted hazard ratios (HRs) (adjusted for age categories [65 69 years, years, years, and years] and sex) were estimated for each outcome. Fully adjusted covariate Cox models were also fitted, using baseline covariates that could be predictive of dementia, AD, VaD, and other dementias: age categories (coded 1 for 65 69, coded 2 for 70 74, coded 3 for 75 79, and coded 4 for 80 84), sex (coded 0 for women and 1 for men), education, pack-years (pack-years cigarettes [coded 0 for packyears cigarettes 5 0 {never smoking} and 1 for pack-years cigarettes 0.5]), IADL score, MMSE, CCI, and serum albumin levels. Fig. 1. Attrition of the study population at the different phases of the survey, Italian Longitudinal Study on Aging ( ). Abbreviations: BMI, body mass index; ADL, activities of daily living; IADL, instrumental activities of daily living; CHS, Cardiovascular Health Study. 3. Results Figure 1 shows sample size and attrition according to the CHS criteria, with frailty syndrome diagnosed in 252 of 2851 (7.6%) individuals. Differences in mean age ( vs , P,.01, evaluated by separate variance t test) and sex (Pearson c , P,.01) were observed between participants and nonparticipants (2581 participants: 1414 [50.2%] men and 1167 women [41.4%]; 3051 nonparticipants: 1401 [49.8%] men and 1650 [58.6%] women). Some frailty components (weakness, slowness, and low activity) present at baseline were adjusted for some characteristics of study population, according to the CHS criteria (Table 1). Sociodemographic and clinical characteristics of participants eligible for frailty analyses who did not develop versus those who developed dementia are shown in Table 2. At baseline, those subjects who developed dementia during the study period (n 5 65) were more likely to be older, to have lower level of education, heavier smoking habit, lower MMSE score, more ADL and IADL impairments, more serious comorbidity, as well as frailty status, and to be more depressed. Over a 3.5-year follow-up, 65 of 2581 (2.5%) older subjects developed overall dementia (16 among 252 frail individuals [6.3%]), 33 (1.3%) developed AD (4 among 252 frail individuals affected by AD [1.6%]), 24 (0.9%) developed VaD (9 among 252 frail individuals affected by VaD [3.6%]), and 8 (0.3%) developed other dementias (2 patients with frontotemporal dementia and 6 patients with dementia not otherwise specified) (3 among 252 frail individuals affected by other dementias [1.2%]). In individuals with and without frailty syndrome, the incidence rates (the number of events per 1000 personyears at risk) of overall dementia, AD, VaD, and other

5 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) Table 2 Baseline demographic and clinical characteristics of participants eligible for frailty analyses who did not develop versus those who developed dementia. The ILSA (first prevalence survey, ) Variable Entire cohort (n ) Subjects who did not develop dementia (n ) Subjects who developed dementia (n 5 65) Women (%) 1166 (45.18) 1133 (45.03) 33 (50.77).36* Age (years) ,.01 y Education (years) ,.01 y Pack-years z 0.6 ( ) 0.85 ( ) 0 (0 4.5) BMI y Mini-Mental State Examination ,.01 y Activities of daily living ,.01 y Instrumental activities of daily living ,.01 y GDS y Frail status (%) 252 (9.76) 236 (9.38) 16 (24.62).01* Charlson comorbidity index ,.01 y Hypertension (%) 1789 (69.31) 1738 (69.08) 51 (78.46).11* Type 2 diabetes (%) 330 (12.79) 326 (12.96) 4 (6.15).11* Coronary artery disease (%) 322 (12.48) 314 (12.48) 8 (12.31).97* Stroke (%) 48 (1.86) 42 (1.67) 6 (9.23),.01* Congestive heart failure (%) 155 (6.01) 153 (6.08) 2 (3.08).31* Albumin (mg/dl) y * Pearson c 2 test. y Student t test for independent samples. z Mann Whitney U test. P value dementias were slightly higher for weakness than for other frailty components (Table 3). Compared with the older subjects without frailty, those with frailty status were more likely to have overall dementia (HR: 1.85; 95% CI: ) and, in particular, VaD (HR: 2.68; 95% CI: ) in a multivariate adjusted model (Table 4). The risk of AD or other types of dementia in the whole study population was not significantly different in frail individuals compared with subjects without frailty syndrome (Table 4). 4. Discussion In a large cohort of Italian older individuals free of cognitive impairment at baseline, it was found that frailty syndrome at baseline was associated with a greater risk of developing overall dementia and, in particular, VaD. These associations remained statistically significant also in analyses that controlled for disability and vascular diseases and risk factors. The present results confirmed those from previous crosssectional studies reporting that frailty was associated with the level of cognition and dementia [1,7 9,11]. The increased risk of incident overall dementia reported in our study was very similar to that reported in the unadjusted model of the Three-City Study, in which being frail at baseline led to twice the cumulative risk of dementia at 4 years; however, after adjusting for sociodemographic and health covariates, frailty status did not remain a statistically significant predictor of dementia [9]. Two longitudinal population-based studies indicated that frailty syndrome was a predictor of cognitive impairment in a 10-year follow-up [11], and that it was associated with the rate of cognitive decline in a 3-year follow-up period [12]. The Rush Memory and Aging Project also found that physical frailty increased the risk for MCI [13], although there is still controversy whether cognitive impairment may be a symptom of frailty or whether MCI is a separate syndrome or, indeed, a sign of early dementia [13,14]. Recently, the National Institute on Aging and the Alzheimer s Association also charged a workgroup with the task of revising the 1984 criteria for AD dementia [31], developing criteria for the symptomatic predementia phase of AD (MCI due to AD) [32], and defining the preclinical stages of AD for research purposes and toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious [33]. In particular, for MCI due to AD, the workgroup developed core clinical criteria that could be used by health care providers without access to advanced imaging techniques or cerebrospinal fluid analysis, and research criteria that could be used in clinical research settings, including clinical trials; the second set of criteria incorporates the use of biomarkers based on imaging and cerebrospinal fluid measures [32]. Recent studies raised the possibility that AD pathology may contribute to frailty or that frailty and AD pathology share a common pathogenesis [14]. However, we are aware of only one longitudinal population-based study that has examined the association of frailty or change in frailty with incident AD [12]. In fact, findings from the Rush Memory and Aging Project involving 820 subjects during a 3-year follow-up showed that the risk of developing AD was 2.5 times higher when frailty was present at baseline [12]. In the ILSA sample, the presence of frailty did not increase the risk of AD. Differences in the tools used in estimating the different

6 Table 3 Incidence rates of dementias, AD, VaD, and other dementias for each component of frailty syndrome in individuals with and without frailty. The ILSA (first and second surveys, ) Components of frailty syndrome Dementia AD VaD Other dementias Number of events Rate 1000 per person-years (95% CI) Number of events Rate 1000 per person-years (95% CI) Number of events Rate 1000 per person-years (95% CI) Number of events Rate 1000 per person-years (95% CI) With frailty Weight loss Presence ( ) ( ) 0 Exhaustion Presence ( ) ( ) ( ) ( ) Weakness Presence ( ) ( ) ( ) ( ) Slowness Presence ( ) ( ) ( ) ( ) Low physical Presence ( ) ( ) ( ) ( ) activity Three or more frailty Presence ( ) ( ) ( ) ( ) components Without frailty Weight loss Presence ( ) ( ) 0 Exhaustion Presence ( ) ( ) ( ) ( ) Weakness Presence ( ) ( ) ( ) ( ) Slowness Presence ( ) ( ) ( ) ( ) Low physical activity Presence ( ) ( ) ( ) ( ) Abbreviations: AD, Alzheimer s disease; VaD, vascular dementia. Table 4 HRs of incident overall dementia, AD, VaD, and other dementias. The ILSA (first and second surveys, ) Types of dementia New events HR unadjusted (95% CI) HR partially adjusted (95% CI)* HR fully adjusted (95% CI) y Overall dementia ( ) 2.14 ( ) 1.85 ( ) AD ( ) 0.77 ( ) 0.62 ( ) Vascular dementia ( ) 5.07 ( ) 2.68 ( ) Other dementias ( ) 4.08 ( ) 2.69 ( ) Abbreviation: HR, hazard ratio. * HRs were adjusted for age and sex (coded 0 for women and 1 for men) in partially adjusted models. y HRs were adjusted for age categories (coded 1 for 65 69, coded 2 for 70 74, coded 3 for 75 79, and coded 4 for 80 84), sex (coded 0 for women and 1 for men), education, pack-years (pack-years cigarettes [coded 0 for pack-years cigarettes 5 0 {never smoking} and 1 for pack-years cigarettes 0.5]), instrumental activities of daily living score, Mini-Mental State Examination score at baseline, Charlson comorbidity index score, and serum albumin levels in fully adjusted models. 118 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013)

7 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) components of the frailty syndrome and different age and sex distribution of the samples could explain discrepancies from previous findings [12]. In the present study, in older subjects with and without frailty syndrome, the incidence rates of overall dementia, AD, VaD, and other dementias were slightly higher for weakness than for other frailty syndrome components. Several of the individual components used to construct the measure of frailty in this study, including altered gait, slowed movement, weight loss, and muscle weakness, have been associated with the development of dementia and incident AD [34 37]. Our findings on the role of muscle weakness in predicting dementia confirmed those of a previous study on a relationship between grip strength and risk of AD [35]. Furthermore, increased muscle strength was associated with a decrease in the risk of incident AD and incident MCI and with a slower rate of decline in global cognitive function during a mean follow-up of 3.6 years [37]. To the best of our knowledge, the present study was the first report of an increased risk of incident VaD linked to the presence of a frailty syndrome at baseline. Our findings suggested that factors associated with the development of frailty and its components were also associated with the development of dementia and VaD. For example, risk factors for cardiovascular disease (e.g., diabetes) and common vascular diseases (e.g., congestive heart failure, brain infarcts) have been related to both frailty [38] and VaD [39]. In fact, several studies showed that comorbidities such as congestive heart failure, myocardial infarction, peripheral vascular diseases, diabetes, and hypertension increase the risk for frailty [38]. The association between frailty and increased risk of incident VaD may be linked to an underlying increased risk of stroke and cerebrovascular disease. In particular, in older patients after myocardial infarction within 6 months of discharge, frailty status was an independent predictor of ischemic stroke [40]. Furthermore, in a cohort of acute care hospital inpatients aged 70 years with atrial fibrillation, compared with the nonfrail participants, the frail participants had significantly higher rates of stroke and death [41]. In the present study, the association between frailty and VaD persisted in analyses controlling for vascular risk factors and diseases, although many of the vascular measures were determined according to self-report. Moreover, physical frailty proximate to death was related to level of AD pathology but not to the presence of cerebral infarcts or Lewy body disease [14], although the postmortem assessment did not directly assess motor brain regions and therefore might underestimate the association of frailty with cerebral infarcts or Lewy body pathology. However, both frailty and VaD are complex concepts, and it is likely that many other factors are also involved. In particular, evidence of overlap between degenerative and vascular disorders is emerging from pathological and epidemiological studies suggesting common pathogenic mechanisms, such as neurotransmitter abnormalities [42], and that vascular-related risk factors may play a critical role in the development of cognitive decline and AD during aging [43]. In fact, vascular pathology of the aging brain and AD includes cerebral amyloid angiopathy, which leads to lobar mass hemorrhages, small or recurrent bleeds and ischemic infarcts, microvascular degeneration, disorder of the blood brain barrier, white matter lesions, microinfarctions, lacunes, and cerebral hemorrhages [44]. Beyond the possible role of vascular risk factors and vascular-related diseases, there are several potential pathways by which frailty could contribute to cognitive decline; however, at present, the mechanisms underlying this suggested association remained unclear. One of these underlying pathogenetic factors may be inflammation. Increased markers of inflammation, such as C-reactive protein or proinflammatory interleukins, are common and have been implicated in frailty [45], cognitive impairment [46], and dementia [47]. In some forms of dementia, particularly AD, primary and supplementary motor cortices, the substantia nigra, and the striatum are often altered [48]. Studies have shown that alterations in these areas of the brain are associated with modifications in the components of frailty such as weight loss and slow gait [49,50], suggesting the possibility that changes in neural systems that control motor function, metabolism, and fatigue may be present in frailty. Some other less well-studied, but potential, mechanisms may include decreased energy production or metabolic issues and stress. These different mechanisms are not mutually exclusive and underscore the need for future studies to further explicate the biological basis of the association between frailty syndrome and cognitive impairment in old age. The strengths of the present study were its prospective design, the population-based setting, and its large number of subjects, although the number of the new cases was relatively small. Nonetheless, some limitations in this study have to be considered. In particular, small number of new cases affects precision of punctual measurements of association. Standard error in Cox models was 0.34 for all dementias, 0.42 for AD, 1.88 for VaD, and 1.44 for other dementias, and these results reflect quitewide 95% CI for HR for the latter two dementia types. In the ILSA, among factors that are potential risk factors for dementia and might be associated with some frailty components, thereby acting as potential confounders, we did not have information on the apolipoprotein E 4 allele status. Furthermore, our model appears to account for more risk factors for VaD rather than AD; it lacked information on, for example, a family history of AD. The physical activity was assessed with the administration of a structured questionnaire specifically developed for the InCHIANTI Study and also proposed for the ILSA [24,25]. However, the reliability and validity of this physical activity assessment have not been established, and the recall of physical activity was only retrospective. To limit the potential misclassification, we also ascertained, prospectively, physical function with ADL and IADL tasks, as well with one related GDS item [19].However, the classification of mild-to-moderate VaD could be affected by the tools used for neuropsychological assessment or the cutoffs chosen for cognitive tests. In fact, in the present 3

8 120 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) study, we failed to screen for executive function impairment, insensitively detected by the MMSE, a major source of our case definition. Several studies report limitations of the MMSE in screening for dementia and cognitive impairment, especially in subcortical infarctions and small vessel disease, where it would not differentiate between focal and diffuse lesions. Furthermore, it would be insensitive to right-sided lesions [51,52]. Our MMSE threshold was very low, implying that participants could have had mild-to-moderate cognitive impairment at baseline, and some of the self-reported MMSE items could be called into question. However, to partially correct this possible bias, we introduced MMSE score at baseline as an adjustment in all multivariate statistical models. Finally, ICD-10 criteria for VaD diagnosis have a high sensitivity but a rather low specificity, and are quite inclusive, as compared, for example, with National Institute of Neurological Disorders and Stroke-Association Internationale pour la Recherche et l Enseignement en Neurosciences (NINDS-AIREN) criteria, probably the most useful in research settings [53]. Furthermore, although the current clinical criteria for VaD are not interchangeable, some studies have suggested a good agreement between NINDS- AIREN and ICD-10 (concordance: 85%) [53]. Future studies will need to address whether preventing frailty syndrome may prevent VaD onset in healthy older individuals. Acknowledgments This work was supported by the ILSA (Italian National Research Council CNR-Targeted Project on Ageing grants PF40 and 95973PF40) and by the Ministero della Salute, IRCCS Research Program , Line 2: Malattie complesse. V.S. and F.P. contributed to the concept and are guarantors. V.S. and F.P. also contributed to the interpretation and coordinated the manuscript preparation. V.S. completed the statistical analysis. E.S., V.F., D.S., G.L., S.M., B.P.I., L.G., M.B., C.G., A.D.C., D.I., G.C., and A.P. all contributed to further interpretations and commenting on drafts of the manuscript in its preparation and approved the final submission. V.S. and F.P. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The funding agencies had no role in design or conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. This study was approved by institutional review boards of the eight Italian universities involved. The study was based on administrative data sets, and the participants were not identifiable to the authors. 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10 122 V. Solfrizzi et al. / Alzheimer s & Dementia 9 (2013) Appendix The Italian Longitudinal Study on Aging Working Group E. Scafato, MD (Scientific Coordinator), G. Farchi, MSc, L. Galluzzo, MA, C. Gandin, MD, Istituto Superiore di Sanita, Roma; A. Capurso, MD, F. Panza, MD, PhD, V. Solfrizzi, MD, PhD, V. Lepore, MD, P. Livrea, MD, University of Bari; L. Motta, MD, G. Carnazzo, MD, M. Motta, MD, P. Bentivegna, MD, University of Catania; S. Bonaiuto, MD, G. Cruciani, MD, D. Postacchini, MD, Italian National Research Centre on Aging (INRCA), Fermo; D. Inzitari, MD, L. Amaducci, MD, University of Firenze; A. Di Carlo, MD, M. Baldereschi, MD, Italian National Research Council (CNR), Firenze; C. Gandolfo, MD, M. Conti, MD, University of Genova; N. Canal, MD, M. Franceschi, MD, San Raffaele Institute,Milano; G. Scarlato,MD, L. Candelise, MD, E. Scapini, MD, University of Milano; F. Rengo, MD, P. Abete, MD, F. Cacciatore, MD, University of Napoli; G. Enzi, MD, L. Battistin, MD, G. Sergi, MD, G. Crepaldi, MD, University of Padova; S. Maggi, MD, N. Minicucci, MD, M. Noale, MD, Italian National Research Council (CNR), Aging Section, Padova; F. Grigoletto, ScD, E. Perissinotto, ScD, Institute of Hygiene, University of Padova; P. Carbonin, MD, Universita Cattolica del Sacro Cuore, Roma.