“Camminando e Leggendo ... Ricordo” (Walking and Reading ... I Remember): Prevention of Frailty Through the Promotion of Physical Activity and Reading in People with Mild Cognitive Impairment. Results from the TREDEM Registry

Abstract

Background:

Frailty is a condition of increased vulnerability to exogenous and endogenous stressors, which is correlated with aging, functional decline, institutionalization, hospitalization, and mortality. Given the multifaceted nature of frailty, programs aimed at its prevention are recommended to act on multiple domains.

Objective:

The present intervention program aimed at assessing the effects of combined physical and cognitive training in older people with mild cognitive impairment (MCI) and at investigating how their frailty status changed over one year of follow-up.

Methods:

Two-hundred and seven participants were recruited among outpatients of the Cognitive Impairment Center who agreed to receive a comprehensive assessment. Forty-six participants, who joined a structured program of physical activity and group readings for a period of one year, were defined as active. The remaining 161, who decided not to engage in those activities, were considered controls. In both groups, frailty status was assessed at baseline and over one year of follow-up.

Results:

Control participants showed twice the risk of becoming frail at 12 months compared with those in the active group. Participants in the active group had more than three times the probability of improving their frailty status compared with the control group from T0 to T12. Age and NPI scores were significantly associated with worsening frailty status. When analyses were restricted to participants who were robust at baseline, the frailty status varied significantly between groups over time.

Conclusion:

Findings of the present study confirm the beneficial effects of physical activity and reading to prevent frailty in older people with MCI.

Keywords

Cognitive frailty community multi-domain intervention neuroimaging TREDEM registry

INTRODUCTION

Frailty is a multidimensional construct that identifies a status of heightened vulnerability to negative health-related events [1]. Frailty arises from the progressive reduction of functional reserves within bodily systems, which impinges on the person’s physical and/or cognitive resources required to maintain homeostasis when facing environmental and/or endogenous stressors [2]. Frailty is highly prevalent in advanced age [2], with an overall weighted prevalence of 10.7% in community-dwelling adults aged 65 years or older [3], and it is correlated with functional decline, institutionalization, hospitalization, and mortality [1 , 5].

Given the global demographic transition, the prevention of frailty is a top public health priority to ensure the sustainability of health and social care systems [1 , 7]. Practical interventions for the prevention and management of frailty have been successfully implemented in community-dwelling older people [8]. However, the absence of robust, non-frail participants in those action plans and the paucity of studies considering cognitive and psychological well-being cast doubt on the actual efficacy of such interventions [8].

Because of the multifaceted nature of frailty, multi-domain, comprehensive interventions have better chances of success [9]. In this regard, it is noteworthy that physical frailty is often associated with cognitive impairment [1 , 10–16]. Indeed, impairments in physical function reduce socialization and favor an inactive lifestyle, thereby triggering a downward spiral involving both the physical and the cognitive domain [17]. In this scenario, cognitive frailty, defined as the co-occurrence of mild cognitive impairment (MCI) and physical frailty [17 –24], is envisioned as a prototypical condition to be targeted through comprehensive programs addressing physical, nutritional, cognitive, and psychological domains [17]. Yet, available clinical trials have mostly focused on the effects of physical and cognitive training on the progression of MCI into dementia, without explicitly assessing their impact on frailty [25 –27].

To fill this gap in knowledge, the present study was undertaken to explore the effectiveness of an easily achievable multi-domain intervention at preventing frailty in community-dwelling older people with MCI. The action plan followed the intervention model “Camminando e leggendo ... Ricordo” (“Walking and reading ... I remember”) that was developed as a secondary prevention strategy for persons with MCI [23].

METHODS

Study design and participants

“Camminando e leggendo ... Ricordo” (CLR) is a practical initiative of secondary prevention conducted in Treviso (Italy) and directed to persons with MCI. The study protocol has been published elsewhere [23]. Briefly, participants were recruited among the outpatients attending the Cognitive Impairment Center of the Local Health Authority n. 2 Marca Trevigiana (LHA2). Candidate participants were considered eligible for enrolment if they were diagnosed with MCI according to consensus criteria [28, 29]. Written informed consent was obtained from all eligible participants prior to adhering to the action plan. Exclusion criteria were: dementia, severe depression or neuropsychiatric symptoms as revealed by the Neuropsychiatric Inventory (NPI) [30], severe vision, hearing, or communication impairment, and other disorders that could impact adherence to the study procedures as per the study physician’s judgment. The study design of the Treviso Dementia (TREDEM) Registry (protocol no. 42326 of April 10, 2015) and of CLR (protocol no. 72060 of June 16, 2015) were both approved by the local Ethics Committee.

All participants received a comprehensive evaluation, including clinical, cognitive, behavioral, functional, physical, and neuroimaging assessments, as described in the TREDEM Registry [31 –35]. The study population included 207 participants with MCI, recruited from June 17, 2015 to April 23, 2018. Each of them completed a one-year observation period and received four neuropsychological assessments.

Participants were asked to take part in a two days/week physical training carried out in collaboration with “Strada Facendo”, a local amateur sports association, which provided exercise trainers for these activities. The physical training was offered in groups and consisted in a 30 min walking session at moderate intensity on a dirt path, with participants walking one to two miles depending on their physical capacities. Afterwards, 30 min of exercises for joint mobilization, flexibility and balance were performed. Resistance training with small equipment and light weights as well as gait training with rapid changes of direction and speed variation were also included. Each session ended with seven minutes of stretching. The trainer also encouraged the participants to walk and perform aerobic activities during the free time. Together with the physical training, a bimonthly group reading activity, led by experienced trainers of the no-profit association “Selaluna”, was proposed. CLR adheres to the local network “Lasciamo il segno” (Let’s leave our footprints), which is dedicated to the promotion of physical activity in the Treviso district in accordance with the Toronto Charter [36].

Participants who decided to self-engage in the proposed program were considered as the active group. Sixty-eight active participants were initially enrolled. However, 22 of them did not complete the 12-month intervention (average drop-out time: 5.4 months) or the four neuropsychological assessments, leaving a total of 46 participants who fully joined the program. The 161 participants who decided not to take part in the training, due to housing distance, lack of transport means, or personal preference, were included in the control group. Outcome measures were collected in both groups by trained psychologists who were not involved in any of the proposed activities.

Assessments

Both the active and the control group received four neuropsychological evaluations over a period of one year. After baseline assessment (T0), participants were evaluated at three (T3) and six months (T6), and at the last testing session offered at 12 months (T12).

Each assessment consisted in a comprehensive neuropsychological testing session including: Mini-Mental State Examination [37, 38], Clinical Dementia Rating Scale [39], Digit Span [40], Short Story Memory Test [40], Rey-Auditory Verbal Learning Test (RAVLT) [41], Attentive Matrices [42], Phonemic and Semantic Verbal Fluencies [40, 42], Token Test [40], Design Copy Test [42], Clock Drawing Test [43], Cognitive Estimation Test [43], NPI with its subscales of Frequency of symptoms (F), Gravity (G), Frequency×Gravity Index (F×G) and Distress of the caregiver [30], Geriatric Depression Scale (GDS) [44], Hamilton Depression Rating Scale [45], Activities of Daily Living (ADL) [46], Instrumental ADL (IADL) [47], Mediterranean Style Dietary Pattern Score (MSDPS) [48], Psychological General Well Being Index (PSGWBI) [49], and a questionnaire for the detection of frailty developed by Cesari et al. [6]. This questionnaire categorizes the person as robust, pre-frail, or frail. Hereby, results of the questionnaire for frailty identification are reported for participants who completed all four evaluations.

Several potential confounding variables were considered. In particular, as mentioned above, a wide set of measures was recorded during the first clinical assessment at the LHA2 Cognitive Impairment Center before T0, according to the TREDEM Registry protocol [31 –35]. Among these measurements and tests, the Multidimensional Prognostic Index (MPI) was computed [50]. MPI provides an estimation of one-year mortality on the basis of ADL, IADL, Short Portable Mental Status Questionnaire (SPMSQ) [51], Mini Nutritional Assessment (MNA) [52], Exton Smith Scale (ESS) [53], number of medications, social support network, and the Cumulative Illness Rating Scale (CIRS) [54]. The MPI produces an estimate of the mortality risk at one year expressed as a probability value ranging from 0 to 1. Values from 0.00 to 0.33 indicate a low risk of death, while a moderate risk corresponds to a value from 0.34 to 0.66, and values from 0.67 to 1 refer to high mortality risk [50].

Furthermore, according to the TREDEM protocol, during the first assessment at the LHA2 Cognitive Impairment Center, a computerized tomography (CT) scan or magnetic resonance imaging (MRI) was obtained for all participants. Based on neuroimaging data, the presence or absence of overall brain atrophy (cortical or subcortical or both) was assessed qualitatively by two independent raters: a neuroradiologist and another physician from the Cognitive Impairment Center, both experienced in imaging valuation. The presence of cortical and subcortical cerebral vascular disease was ascertained through the Hierarchical Vascular Rating Scale (HVRS) [55]. Investigators performing these observations were different from those involved in neuropsychological testing nor did they attend the training sessions of the active group.

Statistical analysis

Primary analysis

All statistical analyses were carried out using R software (ver. 3.5.0) [56]. In order to test the homogeneity of active and control groups, their main participant characteristics were analyzed via t-test and Kruskal-Wallis chi-squared test for continuous and categorical variables, respectively [57]. A p value less than 0.05 was considered statistically significant.

Based on the results of the frailty questionnaire, a binary variable was created to indicate the presence or absence of frailty (“frail” or “pre-frail” versus “robust”). This variable was used as the outcome variable in multivariate logistic regression models. Two additional variables were created to indicate improvement (transition from “frail” to “pre-frail”, or from “pre-frail” to “robust”) or worsening of frailty status (transition from “robust” to “pre-frail”, or from “pre-frail” to “frail”). These variables were the outcomes of other multivariate logistic regression models. Primary analyses were conducted in the group of 207 MCI participants with complete neuropsychological assessments.

Secondary analysis

A mixed-effects logistic regression model [58] was adopted for the subgroup of people classified as “robust” at the first measurement. By using a random effect for subject in order to overcome the lack of a condition of independence, this model allowed considering all measurements taken and assessing those features that influenced a variation in frailty to a larger extent. This analysis was conducted in a group of 113 MCI participants found to be “robust” at T0 and who completed all evaluations.

RESULTS

Descriptive statistics

Table 1 shows the characteristics of the participants in the active group (n = 46) and in the control group (n = 161) who completed all four testing sessions. The two groups appeared to be substantially homogeneous. Statistically significant differences were detected for mean age (74.6 years in the active group and 76.7 years in the control group; p < 0.05) and for the CIRS comorbidity index (CI), with a higher CI in the active group (p < 0.05). The inferential statistical analyses took these differences into consideration.

Table 1

Main characteristics of the study population

	Active participants			Controls
	(46 : 22.2%)			(161 : 77.8%)
	Mean	Median	SD	Mean	Median	SD	Pe
Age	74.6	74.5	5.5	76.7	78.0	6.4	<0.05
Education	8.1	7.5	4.0	7.8	5.0	4.0	n.s.
MMSE	26.4	26.4	2.0	26.0	26.7	2.5	n.s.
CDR	0.5	0.5	0	0.5	0.5	0	n.s.
SVFT	12.6	12.3	3.4	12.6	12.0	3.2	n.s.
HDRS	7.6	7.0	4.2	8.5	7.0	5.0	n.s.
NPI F×G	16.2	16.0	9.0	18.6	16.0	12.5	n.s.
MSDPS	38.2	38.8	7.3	37.0	37.2	7.0	n.s.
HVRS	1.1	1.0	1.2	1.4	1.0	1.4	n.s.
MPI	0.2	0.19	0.1	0.21	0.19	0.11	n.s.
MNA	25.5	25.5	1.9	24.9	25.5	2.3	n.s.
CIRS SI	1.5	1.5	0.3	1.5	1.5	0.2	n.s.
Frequency		Percentage	Frequency		Percentage
MPI (categorized)							n.s
Low	42		91.3	144		89.4
Moderate	4		8.7	17		10.6
MNA (categorized)							n.s.
Normal	39		84.8	110		68.32
At risk	7		15.2	39		24.22
Undernourished	0		0	12		7.45
Frailty domain							n.s.
Frail	0		0	2		1.2
Pre-frail	18		39.1	74		46.0
Robust	28		60.9	85		52.8
CIRS CI							<0.05
0	4		8.7	28		18.4
1	7		15.22	29		19.1
2	10		21.74	31		20.4
3	11		23.91	33		21.7
4	6		13.04	17		11.2
5	5		10.87	10		6.6
6	3		6.52	3		1.9
7	0		0	1		0.7
Sex							n.s.
M	21		45.7	74		46
F	25		54.3	87		54
Brain Atrophy							n.s.
Absent	10		21.7	30		18.6
Present	36		78.3	131		81.4

S.D., standard deviation; n.s., non-significant; MMSE, Mini-Mental State Examination; CDR, Clinical Dementia Rating scale; SVFT, Semantic Verbal Fluency Test; HDRS, Hamilton Depression Rating Scale; NPI F×G, Neuropsychiatric Inventory Frequency × Gravity; MSDPS, Mediterranean Style Dietary Pattern Score; HVRS, Hierarchical Vascular Rating Scale; MPI, Multidimensional Prognostic Index; MNA, Mini Nutritional Assessment; CIRS SI, Cumulative Illness Rating Scale Severity Index; CIRS CI, Cumulative Illness Rating Scale Comorbidity Index. CIRS CI data were not available for 9 controls.

Differences in the proportion of frail persons between and within groups over time

This analysis was conducted in 207 participants who completed the four assessments (46 people in the active group and 161 in the control group). In these analyses as well as in those described later, frailty was treated as a dichotomous variable by grouping pre-frailty and frailty participants (‘presence of frailty’) as opposed to robustness (‘absence of frailty’). Comparisons in the proportion of frail participants between the active and the control group at T0 were performed. As reported in Table 2, no differences were found between groups at T0 (Kruskal-Wallis chi-squared = 1.2428, df = 1, p = 0.2649). When performing the same analysis at T12, however, differences in the number of frail participants emerged between groups (Kruskal-Wallis chi-squared = 8.58, df = 1, p < 0.004). Indeed, the number of frail participants in the control group increased significantly from T0 to T12 (Kruskal-Wallis chi-squared = 7.17, df = 1, p = 0.007), while it remained unchanged in the active group (Kruskal-Wallis chi-squared = 0.5192, df = 1, p = 0.4712) (Table 2).

Table 2

Proportion of frail participant in the two groups at T0 and at T12

	T0 evaluation				T12 evaluation
	Controls		Active participants		Controls		Active participants
Robust	85	53%	28	61%	69	43%	31	67%
Frail	76	47%	18	39%	92	57%	15	33%
Total	161	100%	46	100%	161	100%	46	100%

The proportion of frail participants did not differ between groups at T0 (Kruskal-Wallis chi-squared = 1.2428, df = 1, p = 0.2649). The proportion of frail participants differed between the control and the active group at T12 (Kruskal-Wallis chi-squared = 8.58, df = 1, p < 0.004), with an increase in the proportion of frail participants among controls at T12 versus T0 (Kruskal-Wallis chi-squared = 7.17, df = 1, p = 0.007), but not in the active group (Kruskal-Wallis chi-squared = 0.5192, df = 1, p = 0.4712).

To explore possible effects of other variables on frailty, a multivariate logistic regression was performed, with presence/absence of frailty at T12 as the dependent variable. Besides group allocation (active or control), covariates were age, sex, HVRS score, presence of brain atrophy, CIRS, MPI, years of education, NPI F×G index, presence of frailty at T0. The model that best fitted the data is presented in Table 3. The control group showed twice the risk of becoming frail at T12 than the active group (p = 0.03). Moreover, a higher number of years of education seemed to protect from frailty (p = 0.04), whereas every added point to the NPI F×G scale increased the risk of frailty by 4% (p = 0.01).

Table 3

Multivariate logistic regression assessing differences in the proportion of frail participants over time, with presence/absence of frailty at T12 as the dependent variable

	Crude OR (95% CI)	Adjusted OR (95% CI)	p (Wald’s test)	p (LR-test)
Age (cont. var.)	1.05 (1, 1.11)	1.04 (0.98, 1.09)	0.188	0.183
HVRS (cont. var.)	1.22 (0.98, 1.51)	1.16 (0.93, 1.46)	0.195	0.193
Education (cont. var.)	0.92 (0.85, 0.99)	0.92 (0.85, 1)	0.044	0.04
Group: controls versus active participants	2.64 (1.31, 5.3)	2.25 (1.08, 4.7)	0.031	0.028
NPI F×G (cont. var)	1.04 (1.01, 1.07)	1.04 (1.01, 1.07)	0.014	0.011
Frail at T0: yes versus no	2.06 (1.16, 3.67)	1.63 (0.87, 3.05)	0.124	0.124

The control group had twice the risk of the active group of becoming frail at T12. A higher number of years of education protected from frailty. Every added point to the NPI F×G scale increased the risk of frailty at T12 by 4%. HVRS, Hierarchical Vascular Rating Scale; NPI F×G, Neuropsychiatric Inventory Frequency×Gravity.

Factors associated with improvement of frailty status

The stratification according to the initial frailty category allowed exploring which factors could have an impact on improving the frailty status (i.e., transition from “frail” to “pre-frail” or from “pre-frail” to “robust”). At the univariate analysis, participants in the active group had three times the probability of improving their frailty status compared with those in the control group (OR = 3.2; CI 1.11, 9.27; p = 0.03) (Table 4a). When age, sex, HVRS score, presence of brain atrophy, MPI, and NPI were entered in a logistic regression analysis, allocation to the active group remained the only statistically significant variable (OR = 3.25; CI 0.98, 10.7; p < 0.05) (Table 4b).

Table 4a

Number of participants who changed their frailty status from T0 to T12

	Controls	%	Active participants	%
No improvement	136	84%	35	76%
Improvement	25	16%	11	24%
Total	161	100%	46	100%

Participants in the active group had three times the probability of improving their frailty status compared with those in the control group (OR = 3.2; CI 1.11, 9.27; p = 0.03).

Table 4b

Multivariate logistic regression predicting improvement in frailty status from T0 to T12

	Crude OR (95% CI)	Adjusted OR (95% CI)	p (Wald’s test)	p (LR-test)
HVRS	0.9 (0.64,1.27)	0.87 (0.58,1.31)	0.496	0.493
Brain Atrophy	0.95 (0.28, 3.29)	1.61 (0.39, 6.61)	0.509	0.506
MPI	0.9 (0.27, 3.01)	1.06 (0.29, 3.92)	0.928	0.928
Education	1.06 (0.95,1.19)	1.07 (0.94,1.21)	0.294	0.292
Group: Active participants versus Controls	3.21 (1.11, 9.27)	3.25 (0.98, 10.7)	0.053	0.048
Sex	0.75 (0.31,1.79)	0.77 (0.29, 2.05)	0.603	0.602
Age	0.99 (0.90,1.06)	1.01 (0.92,1.09)	0.900	0.900
NPI F×G	0.99 (0.95,1.03)	0.99 (0.95, 1.03)	0.757	0.756

Participants in the active group had more than 3 times the probability of participants in the control group to improve their condition of frailty. HVRS, Hierarchical Vascular Rating Scale; MPI, Multidimensional Prognostic Index; NPI F×G, Neuropsychiatric Inventory Frequency×Gravity.

Factors associated with worsening of frailty status

Potential factors associated with worsening frailty status (i.e., transition from “robust” to “pre-frail”, or from “pre-frail” to “frail”) were explored. The same initial covariates described in the previous model were considered. The model that best fitted the data is presented in Table 5. Age (OR = 1.07; CI 1.00, 1.15; p = 0.048), HVRS score (OR = 1.35; CI 0.99, 1.84; p = 0.056), and NPI (OR = 1.07; CI 1.02, 1.12; p < 0.001) were found to be significantly associated with worsening frailty status, while years of education appeared to be protective (OR = 0.88; CI 0.77, 0.99; p = 0.026).

Table 5

Multivariate logistic regression predicting worsening in frailty status from T0 to T12

	Crude OR (95% CI)	Adjusted OR (95% CI)	p (Wald’s test)	p (LR-test)
Age	1.02 (0.96,1.08)	1.07 (1.00, 1.15)	0.055	0.048
HVRS	1.13 (0.89,1.43)	1.35 (0.99, 1.84)	0.062	0.056
Education	0.92 (0.84,1.01)	0.88 (0.77, 0.99)	0.036	0.026
NPI F×G	1.02 (0.99,1.04)	1.07 (1.02, 1.12)	0.002	<0.001

Age, HVRS score and NPI had a significant role in worsening frailty status, while years of education were protective. HVRS, Hierarchical Vascular Rating Scale; NPI F×G, Neuropsychiatric Inventory Frequency×Gravity.

Changes in frailty status over time

To explore changes in frailty status over the four testing sessions, statistical analysis was restricted to participants who were robust at T0 (controls = 85, actives = 28, total number = 113).

Homogeneity was assessed for the active and control groups through Kruskal-Wallis chi-squared test and t-test for categorical and continuous variables, respectively. No significant between-group differences were found, except for the CIRS CI, with the active showing a greater number of moderate to severe diseases than the control group.

To verify if there were differences between the active and the control group at different time-points, we estimated a mixed-effects logistic regression model with frailty as a binary outcome variable, age as continuous predictor, and sex, time and groups as categorical predictors (Table 6). Multiple responses from the same participant could not be regarded as independent from one another; hence, we added a random effect to account for subject variation. A one-unit increase in age was associated with an increase of 7% of the OR to become frail. Women were found to have a doubled OR than men (OR = 2.27, CI 1.3, 4.0). The control group had three times the probability of becoming frail compared with the active group (OR = 3.01, CI 1.46, 6.21). The last time point (T12) had almost a doubled OR compared with measurements at T3, while there were no significant differences with T6 (Table 6).

Table 6

Mixed effect logistic regression testing frailty at different time-points

	Adjusted OR	95% CI	p_r (> \|z\|)
(Intercept)	0.00	0.00, 0.00	<0.01	**
Age	1.07	1.06, 1.08	<0.01	**
Sex: Female versus Male	2.27	1.28, 4.04	<0.01	**
Group: Control versus Active participants	3.01	1.46, 6.21	<0.01	**
T6 versus T3	1.12	0.59, 2.13	0.73
T12 versus T3	1.87	1.02, 3.52	0.05	*

A one-unit increase in age was associated with an increase of 7% of the OR to become frail. Women showed to have a doubled OR to be frail compared with men. The control group had three times the probability of becoming frail compared with the active group. At T12 there was almost a doubled OR to become frail compared with measurement at T3, while there were no significant differences between measurements at T3 or T6.

DISCUSSION

Frailty is a condition of increased vulnerability to exogenous and endogenous stressors caused by deterioration of a person’s physiological systems [1]. It is pervasive in the older population [2] and, therefore, represents a topic of primary interest for public health [7]. Programs aimed at preventing and managing frailty are recommended to act on multiple levels through physical activity, healthy diet, cognitive training, and socialization. The mutual influence between physical and cognitive decline has led the scientific community to consider persons with cognitive frailty ideal recipients of multi-domain programs [17].

Some randomized controlled trials (RCTs) have tested the effects of physical and cognitive trainings in older people with MCI [25 –27]. However, these studies examined the results of trainings on cognitive decline, without taking into account their effects on the construct of frailty. On the other hand, while some programs targeting frailty have been implemented [8], none of them included participants with MCI nor were changes in frailty status investigated considering also robust participants in the sample.

The fact that an inactive lifestyle is associated with frailty in older adults is well established [59]. The effects of physical interventions on physical function have been evaluated in over 47 trials in older adults with poor performance status, 16 of which were conducted in community-dwelling older people. Only three trials have identified frail older adults specifically [60 –62]; however, none of them used frailty as an outcome measure. An RCT in community-living prefrail and frail older adults compared the effects of 6-month interventions with nutritional supplementation, physical training, cognitive training, and combination treatment versus standard care in reducing frailty [63]. Three of those six months were carried out at home and home activities were only self-reported. Other studies also evaluated the effectiveness of interventions to prevent frailty by proposing, at least in part, home-based physical activity without having objective control over the actual completion of the assigned exercises [64 –66].

In our study, physical and reading activities were monitored and verified at each meeting by experienced trainers throughout the whole observation period. The study was therefore able to detect objective data and was not solely based on activities carried out at home, whose execution can only be reported. To the best of our knowledge, the current action plan is the first to target older people with MCI and to investigate how their frailty status changed over a one-year follow-up.

The active group was characterized by a higher number of disease conditions compared with the control group. A possible explanation for this finding is that people with some non-serious illness may have been motivated to engage in the proposed activities to seek health benefits through physical activity and cognitive stimulation.

The analyses of MCI participants who completed all testing sessions confirmed that bi-weekly light physical activity and group reading were effective at preventing frailty. In fact, the number of frail participants in the active group did not increase over one year, whereas frail participants in the control group increased in number from T0 to T12. When covariates were considered, education was found to be a protective factor against frailty, while allocation to the control group and a greater burden of neuropsychiatric symptoms increased the risk of becoming frail. These results showed that walking and physical activity combined with reading successfully prevent frailty, thereby supporting physical and cognitive training for the promotion of healthy aging.

Moreover, when considering participants who improved their frailty status (from “frail” to “pre-frail” or from “pre-frail” to “robust”), the only factor showing a significant role in ameliorating the frailty condition was participation in the active group. This, again, confirmed the importance of physical activity and reading in old age and underlined the fact that being physically and cognitively active not only prevents frailty, but can also restore robustness. On the other hand, age, HVRS score, and NPI were associated with worsening of frailty, while years of education appeared to be protective.

With respect to the factors predicting frailty in each of the four testing sessions, being part of the control group tripled the probability of becoming frail during one year. For all the participants considered, there was also an effect of time: at T12 the odds of being frail were almost doubled relative to T3. These results are in line with the other outcomes of this action plan, confirming the positive effect of remaining physically and cognitively active in older age to prevent and reverse frailty.

Overall, the results of the present action plan outline the efficacy of a simple intervention, such as walking and reading, to successfully achieve prevention of frailty and restoration of robustness in older people with MCI. One of the factors that protected from frailty in the active group might have been the socialization promoted by participating in the proposed activities. In fact, high levels of loneliness are associated with an increased risk of becoming physically frail or pre-frail [67].

Our study presents several strengths. First, participants were non-selected, “real-world” community-dwellers. In addition, remarkable effects in terms of frailty prevention and management were obtained through a simple intervention in which older adults with MCI can easily engage. The engagement in physical and cognitive activities was objectively determined de visu by qualified trainers, rather than being self-reported by participants. Furthermore, unlike other studies such as the MEFAP project [66], an RCT which planned to use only physical activity aimed at pre-frail people, our study used both physical activity and reading proposing them to robust, pre-frail and frail participants. Finally, the present action plan received a prize as a “Quality project for the scientific methodology and accurate statistical evidence” assigned by the scientific committee of the “General State of Health Promotion in the province of Treviso” conference, held in Treviso in December 2019.

Some limitations of our study need to be mentioned. The first limitation is the relatively small sample size of the active group, which could limit the generalization of findings. It was quite difficult to recruit participants willing to engage in the active group, as most older people had not practiced any sports activities in their life, and even fewer had been regular readers. For the same reasons, we opted to let participants decide which group they preferred to join, rather than allocating them randomly. This choice granted optimal adherence to the study procedures. At the same time, our approach reduced the chances that highly motivated participants, if allocated to the control group, could engage in physical activity on their own, thereby diluting the intervention effects. Furthermore, although there has been a state of genuine uncertainty on the part of us regarding the final effects of the proposed activities, we did not want to deny motivated participants the opportunity to engage in activities that could potentially be useful for their health [68, 69]. Another limitation of the study is that the observation lasted 12 months, which does not allow inferring about the effects of our program over the long term.

Conclusion

The goal of the present action plan was to investigate whether simple activities such as walking and reading would protect against frailty in a sample of older people with MCI in the Treviso area, Italy. CLR targeted a population at risk of cognitive frailty via a practical action plan for health promotion based on socially engaging activities accessible to all. The results obtained by comparing participants who performed physical and cognitive activities with the control group confirm the positive effects of walking and reading as tools to prevent and contrast frailty in advanced age.

Footnotes

ACKNOWLEDGMENTS

We would like to thank “Strada Facendo”, a local amateur sports association, and “Selaluna”, a non-profit association of readers, for the enthusiasm, passion, and skills shown by collaborating with the CLR study.

Authors’ disclosures available online ().

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