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Scandinavian Journal of Medicine & Science in Sports, 2025; 35:e70010
https://doi.org/10.1111/sms.70010
Scandinavian Journal of Medicine & Science in Sports
REVIEW OPEN ACCESS
Residual Effects of Physical Exercise After Periods of
Training Cessation in Older Adults: A Systematic Review
With Meta- Analysis and Meta- Regression
ÁngelBuendía- Romero1,2,3 | TomasVetrovsky4 | AlejandroHernández- Belmonte5 | MikelIzquierdo2,6 |
JavierCourel- Ibáñez7
1GENUD Toledo Research Group, Faculty of Sports Sciences, University of Castilla- La Mancha, Toledo, Spain | 2Centro de Investigación Biomédica en Red
Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain | 3Grupo Mixto de Fragilidad y Envejecimiento Exitoso
UCLM- SESCAM, Universidad de Castilla- La Mancha - Servicio de Salud de Castilla- La Mancha, IDISCAM, Toledo, Spain | 4Faculty of Physical Education
and Sport, Charles University, Prague, Czech Republic | 5Human Performance and Sports Science Laboratory. Faculty of Sport Sciences, University
of Murcia, Murcia, Spain | 6Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona,
Spain | 7Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Melilla, Spain
Correspondence: Javier Courel- Ibáñez (courel@ugr.es)
Received: 25 September 202 4 | Revised: 18 December 2024 | Accepted: 19 December 2024
Funding: Á.B.- R. is supported by CIBER FES (CB16/10/00477) and Plan Propio de Investigación of the University of Castilla- La Mancha and FEDER funds
from the European Union (2022- GRIN- 34296) and the Spanish Ministry of Science and Innovation (JDC2023- 052593- I). J.C.- I is supported by the Spanish
Ministry of Science and Innovation (Grant No. PID2019- 108202RA- I00). T.V. is supported by the Cooperatio Program, research area Sport Sciences—
Biomedical & Rehabilitation Medicine. A.H.- B. is supported by a predoctoral contract from the Spanish Ministry of Science (Grant No. FPU19/03258) and
the Spanish Ministry of Science and Innovation (JDC2023- 051020 - I). Funding for open access charge: Universidad de Granada / CBUA.
Keywords: deconditioning| functional impairments| long- term effects| physical inactivity
ABSTRACT
We aimed to determine the persisting effects of various exercise modalities and intensities on functional capacity after periods
of training cessation in older adults. A comprehensive search was conducted across the Cochrane Library, PubMed/MEDLINE,
Scopus, and Web of Science Core Collection up to March 2024 for randomized controlled trials examining residual effects of
physical exercise on functional capacity in older adults ≥ 60 years. The analysis encompassed 15 studies and 21 intervention
arms, involving 787 participants. The exercise and training cessation periods ranged from 8 to 43 weeks and 4 to 36 weeks, re-
spectively. Meta- analyses were performed using change scores from before the physical exercise to after the training cessation.
The effect sizes (ES) were calculated as the standardized mean differences between the intervention and control groups' change
scores. Subgroup analyses and meta- regressions explored the influence of participant characteristics, the magnitude of the effect
produced by the initial training program, various exercise modalities (resistance and multicomponent training) and intensities
(high and low), and subdomains of functional capacity (agility, balance, standing ability, walking ability, and stair walking). The
findings revealed that exercise interventions had a significant effect on preserving functional capacity after training cessation
(ES = 0.87; p < 0.01). This protective effect was consistent across various exercise modalities and intensities (ES ≥ 0.67; p ≤ 0.0 4).
The benefits obtained during the training program were positively associated with the residual effects observed after training
cessation (β = 0.73; p < 0.01), while age negatively influenced the persisting adaptations (β = −0.07; p < 0. 01). Cur rent evidence
suggests that exercise- based interventions, irrespective of modality and intensity, are highly effective in preventing functional
declines after training cessation among older adults.
This is a n open access ar ticle under the terms of t he Creative Commons Attr ibution-NonCommercial Lice nse, which permit s use, distribut ion and reproduction in a ny medium, provide d the
origin al work is properly cited a nd is not used for commer cial purpose s.
© 2025 T he Author(s). Scandinavi an Journal of Medi cine & Science In Sp orts published by J ohn Wiley & Sons Ltd .
2 of 14 Scandinavian Journal of Medicine & Science in Sports, 2025
1 | Introduction
Functional capacity refers to the ability to perform everyday
activities such as walking, rising from a chair, climbing stairs,
or maintaining balance [1]. Deficiencies in functional capac-
ity significantly impact autonomy, quality of life, and health-
related costs, especially as the population ages and becomes
more frail [2–4]. In individuals over 60 years of age, a severe
decline in functional capacity is associated with a 50% in-
crease in mortality risk [5]. Conversely, exercise is linked to
an extended period of good health and can potentially slow
down the progression of age- related illnesses among older
individuals [6]. Increasing physical activity levels offers sub-
stantial health and economic benefits, with the World Health
Organization (WHO) estimating a return of 1.7 € for every 1
€ invested in physical activity policies [7]. Therefore, exercise
emerges as a highly effective, cost- efficient strategy for pre-
venting, mitigating, and even reversing age- related functional
impairments [8, 9].
Each exercise modality induces specific physiological ad-
aptations. Resistance training, involving the use of external
loads or body weight, primarily enhances muscle mass and
strength [8, 10, 11]. On the other hand, aerobic training, char-
acterized by continuous movements of large muscle groups for
an extended period to increase caloric expenditure, improves
systemic vascular function and metabolic profile [12, 13].
Interestingly, multicomponent training, which combines
resistance, aerobic, and balance exercises, has shown the
most promising outcomes in enhancing functional capacity
among older adults [8]. Furthermore, training intensity plays
a crucial role in eliciting exercise adaptations [14]. Evidence
suggests that high- intensity training programs, such as resis-
tance training exceeding 70% of the one- repetition maximum
(1RM), yield the greatest improvements in functional capacity
among the older population [15].
Preserving adequate functional capacity in older adults poses
challenges due to age- related degeneration affecting the mus-
culoskeletal system's ability to execute coordinated movements
[16, 17]. Additionally, exercise programs for older individuals are
often interrupted due to falls, illness, or hospitalizations [18], re-
sulting in partial or complete loss of the adaptations previously
gained [19]. Training cessation, combined with aging- related
degeneration, leads to impairments in muscle structure[17] and
function [20]. Among others, older adults experience decreases
in neural activity [21], lean mass [22], muscle strength, and
power [20]. All these factors combined contribute to difficulties
in carrying out activities of daily living [23]. Older individuals
with better physical conditions before the interruption tend to
experience a lesser decline in functional capacity during peri-
ods of training cessation [24]. Consequently, exercise may have
a residual effect, enabling the retention of positive changes gen-
erated by physical exercise even after training cessation [25–27].
Nevertheless, it remains unclear if the residual effects are pro-
duced after different exercise modalities and intensities.
This systematic review and meta- analysis aimed to summarize
the available evidence on the persisting effects of various exer-
cise modalities and intensities on functional capacity after peri-
ods of training cessation in older adults.
2 | Methods
This systematic review and meta- analysis were conducted ac-
cording to Preferred Reporting Items for Systematic Reviews
and Meta- analyses (PRISMA) and Cochrane Collaboration
guidelines [28]. The original protocol was prospectively regis-
tered with the International Prospective Register of Systematic
Reviews (PROSPERO) database (CRD42021235092) and pub-
lished elsewhere [29].
2.1 | Study Selection
The PICOS (Population, Intervention, Comparators, Outcomes,
Study design) approach for the eligibility of studies was used to
determine the inclusion and exclusion criteria.
Participants: People ≥ 60 years (considered as older adults ac-
cording to the WHO [30]) who have completed a physical
training program followed by an exercise cessation phase. No
restrictions for maximum age, diseases, gender, socio- economic
status, ethnicity, or geographical area were set.
Intervention: Training cessation periods that took place im-
mediately after an exercise intervention. A training cessation
period was defined as any follow- up phase without active and
voluntary physical activity (e.g., hospitalization or usual daily
activity). No duration restriction was set for either the exercise
program or the training cessation period.
Comparator: A control group not conducting a previous training
intervention but being evaluated before and after a time interval
identical to the experimental group.
Outcome measures: Subdomains of functional capacity (i.e.,
standing ability, walking ability, agility, gait speed, balance,
and stair walking) measured by validated physical assess-
ments (e.g., sit- to- stand, timed up and go [TUG], 6- min walk,
or static balance tests). Data from questionnaires were not
considered.
Studies: Randomized controlled trials (RCTs) including at least
one control group and one experimental group (which under-
went a training and subsequent detraining period). Studies
without primary data (e.g., reviews), investigations published in
non- peer- reviewed journals, and behavioral interventions were
excluded.
2.2 | Search Strategy
A search from the earliest record up to and including March
2024 was performed using the electronic databases Cochrane
Library, PubMed/MEDLINE, Scopus, and Web of Science Core
Collection. The systematic search strategy (Table S1), which
was adapted for each database, included the following combina-
tion of keywords: “elder,” “elderly,” “older adults,” “detraining,”
“training cessation,” “exercise interruption,” “deconditioning,”
“retraining,” and “physical restraint.” Moreover, the search
strategy was complemented with a screening of the references
and citations of studies included.
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2.3 | Data Extraction
Metadata was imported to Mendeley (v1.19.6, Elsevier,
London, UK) and processed in Microsoft Excel 2016 (Microsoft
Corporation, Redmond, WA, USA). After the automatic and
manual removal of duplicates, two researchers (Á.B.- R. and
J.C.- I.) independently screened the titles and abstracts, consid-
ering eligibility criteria (first- stage screening). Full texts of the
remaining studies were subjected to a second- stage screening.
Full- text studies not finally considered for the quantitative and
qualitative analyses were also recorded to justify their non-
inclusion based on the eligibility criteria. Any discrepancy be-
tween Á.B.- R. and J.C.- I. during the study selection process was
solved by a discussion with another researcher of the current
st udy (T.V ).
Data extracted for each study were: (1) study characteristics (total
sample number, sex, age, weight, height, body composition), (2)
training configuration (modality, volume, intensity, duration, ex-
ercises), (3) characteristics of the training cessation period (type
of inactivity and duration), and (4) changes before and after the
intervention. For quantitative analyses (meta- analyses), authors
collected the mean differences with standard deviation (SD).
Scores from pre- training, post- training, and training cessation
period were used for statistical analyses. Otherwise, missing
numerical data were obtained from figures using the reliable
WebPlotDigitizer software [31]. Missing SD was estimated from
standard errors using the following formula [28, 32]:
The low and high intensity was defined for aerobic training
based on the percentage of maximal heart rate (77%), heart-
rate reserve (60%), and rate of perceived exertion (RPE, 15/20)
[14]. Resistance training intensity was categorized as low or
high intensity based on %1RM (69%1RM) [14] and RPE (13/20
or 7/10) [33, 34]. Power training (i.e., resistance at a maximal
intended velocity in the concentric phase) was considered high-
intensity when participants conducted each repetition as fast
as possible against ≥ 60 %1R M [14]. When the intensity of aer-
obic and resistance training progressively increased during an
intervention, the average intensity was used for classification.
Multicomponent training was classified as high- intensity when
the programs comprising it were categorized as high- intensity.
If a study had two groups performing a different training mo-
dality, these intervention arms were coded as a separate study.
2.4 | Quality Assessment and Certainty
of Evidence
The Cochrane tool for assessing the risk of bias in randomized
trials (RoB 2 tool) was implemented [35]. A high risk of bias
was considered when the score was ≥ 5 points. The Grading of
Recommendations Assessment, Development, and Evaluation
(GRADE) framework was used to rate the certainty of the ev-
idence, graded as High, Moderate, Low, or Very Low based
on the presence or extent of study limitations, inconsistency
of the effect, imprecision, and publication bias [36]. The RoB2
and GRADE tools were independently implemented by two
researchers (Á.B.- R and J.C.- I.), including a third one (T.V.)
when there was a discrepancy.
2.5 | Data Synthesis and Analysis
The effect sizes (ES) were calculated as the standardized mean
differences (Hedges' g) [37] between the intervention and con-
trol groups' change scores from pre- training to the end of the
training cessation period. Meta- analyses were performed using
robust variance estimation (RVE) with small- sample correc-
tions [38, 39]. RVE is a form of random- effects meta- regression
for multilevel data structures, which allows for multiple effect
sizes from the same study to be included in a meta- analysis,
even when information on the covariance of these effect sizes
is unavailable. Instead, RVE estimates the variance of meta-
regression coefficient estimates using the observed residuals. It
does not require distributional assumptions and does not make
any requirements on the weights [38, 39]. Observations were
weighted by the inverse of the sampling variance. Subgroup
analyses were performed when the number of interventions was
≥ 5, as recommended by Cochrane [28], to explore the effects
of different training modalities, intensities, and subdomains of
functional capacity. The pooled ES were considered significant
at p ≤ 0.05 and rated as small (0.20–0.49), moderate (0.50– 0.79),
or large (≥ 0. 80) [40]. The heterogeneity of results across studies
was evaluated using the I [2] (the percentage of total variation
attributed to between- study heterogeneity), which was inter-
preted as small (< 25%), moderate (25%–50%), or high (> 50%)
[41]. Potential effect moderators (participants' age, training mo-
dality and intensity, training duration, duration of the cessation
period, and training effect) were explored with univariable and
multivariable meta- regression models. The training effect was
calculated as the standardized mean difference between the in-
tervention and control groups' change scores from pre- training
to post- training. Finally, the presence of publication bias was
assessed using a visual inspection of the funnel plots and a
random- effects version of Egger's regression test. All analyses
were performed using the metafor and robumeta packages in R
(The R Foundation for Statistical Computing, Vienna, Austria).
3 | Results
3.1 | Literature Selection
Initially, a total of 3383 articles were retrieved through the da-
tabase search. Following this, duplicate papers (n = 1312) were
removed either automatically or manually. Subsequently, the
remaining 2071 titles and abstracts were screened based on the
predefined inclusion criteria, constituting the first- stage screen-
ing. From this screening, 43 full- text articles were assessed in
detail during the second- stage screening. Finally, 15 articles
were selected for qualitative analysis and 14 for quantitative
analysis (Figure1).
3.2 | Study Characteristics
We analyzed 15 RCTs (Table 1) involving 787 older adults
(553 women) with a mean age ranging from 64 to 92 years old
SD
=
√
n∙(upper limit −lower limit of 95 %confidence interval)∕
3.92
4 of 14 Scandinavian Journal of Medicine & Science in Sports, 2025
at baseline [42–56]. Seven studies recruited both male and
female participants [42, 44, 50, 51, 53, 55, 56], six recruited
only females [43, 45, 46, 48, 52, 54], and two studies specif-
ically analyzed a male- only population [47, 49]. In seven
studies, participants with chronic diseases such as type 2
diabetes or special physical conditions like prefrailty, insti-
tutionalization, or a VO2max < 20 mL/kg/min were included
[43, 44, 47, 51, 53, 55, 56]. The participants' demographics were
79.4% Europeans [44–50, 52, 53, 55, 56], 11.8% Americans
[42, 43], and 8.8% Asians [51, 54]. The mean duration of the
exercise programs was 16 weeks (range 8–43 weeks). Weekly
training frequency examined included 2 times per week [44–
49, 53, 55, 56], 3 times per week [42, 43, 50–52] and 5 times per
week [54]. The exercise cessation period varied between 4 and
36 weeks, with a mean duration of 11 weeks. One study had a
follow- up period of 240 weeks [46]. During this period, all par-
ticipants were instructed to avoid any type of regular exercise
and to carry on with their normal daily activities. No injuries,
illnesses, surgeries, or physical restraints were reported in the
included studies.
Qualitative analysis included 21 intervention arms from
15 RCTs. Eleven interventions conducted multicomponent
training [42, 45, 46, 48, 50, 51, 53, 55], nine on resistance
training [42–44, 47, 49, 52, 56], and one on aerobic training
[54]. Seven experimental groups performed high- intensity
training [42, 47, 50, 55, 56], 12 conducted low- intensity train-
ing [43–49, 51–53, 56], and two did not control the intensity
[46, 54]. Quantitative analysis included 21 exercise interven-
tions from 15 RCTs and 24 outcomes, [42–53, 55, 56] grouped
in standing ability [42–45, 48–52, 55, 56], agility [42, 43, 45, 47,
49–51, 53, 56], gait speed [43, 46, 47, 53, 55, 56], static balance
[42, 46, 50, 54, 56], stair walking [47, 50, 51, 53], and walking
ability [45, 48].
3.3 | Meta- Analysis
Forest plots are depicted in FiguresS1–S11. Overall, there was
a medium and significant protective effect on functional ca-
pacity in favor of the training groups (ES = 0.88 [CI: 0.47 to
1.29], p < 0.01, I2 = 81%). Results from subgroup analyses are
shown in Table2. Results for individual subdomains of func-
tional capacity independently revealed positive and significant
effects on agility, walking ability, standing ability, and stair
walking (ES ≥ 0 .61; p < 0.05; I2 = 0%–85%), as well as positive
FIGUR E | Flowchart illustrating the di fferent phases of the search and study selection, according to t he PRISMA (Prefer red Reporting Items for
Systematic Reviews and Meta- Analyses) statements.
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TABLE | Characteristics of studies included.
Study Sample at baseline Training intervention Adherence ratio
Exercise
cessation Outcomes
Ansai etal. 2016 [42] MT group (n = 23)
RT group (n = 23)
C group (n = 23)
82.4 ± 2. 4 y
68.1% females, healthy
older adults
16 wk., 3 d/wk.; supervi sed
High- intensity MT
13 min AT, 3 min interval
training from 60% to 85% HRR
20 min RT, 4 exercises, 3 set of 15
rep, intensity 14–17 RPE (6–20)
10 min balance, static
and dynamic exercise
increasing difficult level
High- intensity RT
6 exercises. 3 sets of 10- 12RM
2- s concentric and 4- s
eccentric phase
MT: 34.7%
RT: 56.5%
6 wk Standing ability:
STS 5 reps (stopwatch)
Agility:
Dual- task TUG (stopwatch)
Balance (stopwatch):
Dominant- leg balance
No dominant- leg balance
Tandem balance
Bezerra- Melo etal. 2022 [43] RT group (n = 12)
C group (n = 12)
66.5 ± 5.9 y
100% females with
type 2 diabetes
12 wk, 3 d/wk., super vised
Low- intensity RT
8–18 exercises, 1 set of 10
rep 11–12 RPE (6–20)
No reported 4 wk Standing ability:
STS 5 reps (stopwatch)
Agility:
RCHo (stopwatch)
Gait speed:
10 m (stopwatch)
Caldo- Silva etal. 2021 [44] RT group (n = 12)
C group (n = 15)
84.9 ± 4.7 y, i nstitutionalized
older adults
16 wk., 2 d/wk. supervi sed
Low- intensity RT
9 exercises, 2–3 set of 10–20
rep, intensity 4–6 RPE (0–10)
70% 8 wk Standing ability:
STS 5 reps (stopwatch)
Carvalho etal. 2009 [45] MT group (n = 32)
C group (n = 25)
69 ± 3.5 y
100% females, healthy
older adults
32 wk., 2 d/wk. superv ised
Low- intensity MT
AT, 20- 25 min walking,
jogging, or dancing to
intensity 12–14 RPE (6–20)
RT, 12 exercise, 1- 3set of 8–15
reps to 12–16 RPE (6–20)
10 min balance, static
and dynamic exercise
increasing difficult level
91% 12 wk Standing ability:
STS 30 s (stopwatch)
Agility:
TUG (stopwatch)
Walking ability :
6- min walk test (meters)
(Continues)
6 of 14 Scandinavian Journal of Medicine & Science in Sports, 2025
Study Sample at baseline Training intervention Adherence ratio
Exercise
cessation Outcomes
Englund etal. 2009 [46] MT group (n = 18)
C group (n = 16)
72.4 ± 3.7 y
100% females, healthy
older adults
43 wk., 2 d/wk., superv ised
Self- paced intensity MT
AT, 10 min walking or jogging
RT, 4 exercise, 2 set of 8–12 reps
Balance, 5 min static
and dynamic exercise
increasing difficult level
No reported 240 wk Balance:
Dominant- leg balance (stopwatch)
Gait speed
30 m (stopwatch)
Fatouros etal. 2005 [47] High- intensity RT group (n = 2 0)
Low- intensity RT group (n = 18)
C group (n = 14)
71.2 ± 4.1 y
100% males, sedentary older
adults (VO2max < 20 mL /kg/min)
24 wk., 2 d/wk ., s upervised
8 exercises, 2–3 set
Low- intensity RT: 14–16
reps 50%–55%1RM
3 min rest
High- intensity RT: 6–8
reps 80%–85%1RM
6 min rest
2–3 s concentric phase, 2–3 s
eccentric phase and 2–4 s
pause between reps
No reported 36 wk Agility:
TUG (photocells)
Stair walking (photocells)
Walking up 8 stairs
Walking down 8 stairs
Gait speed:
15 m (photoc ells)
González- Ravé etal. 2020 [48] MT group (n = 12)
MT with extra aquagym
session group (n = 12)
MT with extra hypertrophy
session group (n = 12)
C group (n = 12)
65.7 ± 4.5 y
100% females, healthy
older adults
10 wk., 1–2 d/wk., supervised
Low- intensity MT
AT, 40 min with continuous
(60%–70% HRE) and intermittent
exertion (70%–80% HRE).
RT, 8–10 exercises, 3 set of
12–15 reps 60%–70%1RM with
moderate execution speed.
Balance, static, and dynamic
exercise increasing difficult
level 3–5 set of 2- 3 min /30s
Hypertrophy session: 8
exercises, 2–3 set of 8–12 reps
70%–80%1RM /1–3 min of rest
Aquagym session: 8 exercises,
3set of 20 reps 7- 8RPE
(6–20)/30 s −2 min of rest
No reported 4 wk Standing ability:
STS 30 s (stopwatch)
Walking ability :
6- min walk test (meters)
Jumping ability:
CMJ (contact barriers)
Abalakov (contact barriers)
(Continues)
TABLE | (Continued)
7 of 14
Study Sample at baseline Training intervention Adherence ratio
Exercise
cessation Outcomes
Kalapotharakos etal. 2010
[49]
RT group (n = 8)
C groups (n = 7)
82.4 ± 2. 6 y
100% males, community-
dwelling older adults
8 wk., 2 d/wk., superv ised
Low- intensity RT
6 exercises, 3 set of 10 reps
70% 3RM/30 –90 s rest
90% 6 wk Standing ability:
STS 5 reps (stopwatch)
Agility:
TUG (stopwatch)
Walking ability :
6- min walk test (meters)
Lacroix etal. 2015 [50] MT supervised group (n = 22)
MT unsupervised group (n = 22)
C group (n = 22)
72.83 ± 3.7 y
62.12% females, healthy
older adults
12 wk., 3 d/wk.
High- intensity MT
RT, 5 exercise, 3 set of 8–15 reps
12–16 RPE (6–20)/1–2 min rest
Balance, static, and dynamic
exercise, 4 set of 20–60 s/30 s rest
Supervised: 91.7%
Unsupervised:
97. 4%
12 wk Standing ability:
STS 5 reps (stopwatch)
Agility:
TUG (stopwatch)
Balance:
Eyes closed (force plate)
Stair walking (stopwatch):
Walking up 8 stairs
Walking down 8 stairs
Park & Lee 2015 [51] MT group (n = 2 4)
C group (n = 13)
54% females, older adults
with type 2 diabetes
12 wk., 3 d/wk. super vised
Low- intensity MT
RT, 6 exercises, 1–3
set of 10- 12reps 45%–
75%1RM/1 min rest
AT, 1–3 set of 3–5 min cycling
or walking at 9–14 RPE (6–20)
No reported 8 wk Standing ability:
STS 30 s (stopwatch)
Stair walking:
Number of steps in 2 min (stopwatch)
Agility:
TUG (stopwatch)
Pereira etal. 2012 [52] RT group (n = 20)
C group (n = 17)
65.3 ± 2.7 y
100% females, healthy
older adults
12 wk., 3 d/wk., super vised
Low- intensity RT
6 exercises, 3 set of 4–10 rep,
intensity 40- 75%RM/2 min rest
91.6% 6 wk Standing ability:
STS 30 s (stopwatch)
Jumping ability:
CMJ (trigonometric carpet)
Serra- Rexach etal. 2011 [53] MT group (n = 20)
C group (n = 29)
92 ± 2 y
80% females, institutionalized
older adults
8 wk., 2 d/wk., superv ised
Low- intensity MT
AT, 10- 15 min cycling
12–13 RPE (6–20)
RT, 6 exercises, 1–3 set of 8–10
rep 30%–70%RM/1- 2 min rest
74.6% 4 wk Agility:
TUG (stopwatch)
Stair walking
Walking up 4 stairs (stopwatch)
Gait speed:
8 m (stopwatch)
(Continues)
TABLE | (Continued)
8 of 14 Scandinavian Journal of Medicine & Science in Sports, 2025
Study Sample at baseline Training intervention Adherence ratio
Exercise
cessation Outcomes
Sun etal. 2018 [54]AT group (n = 16)
C group (n = 16)
64.3 ± 3. 3 y
100% females, healthy
older adults
16 wk., 5 d/wk., superv ised
Self- paced intensity AT
10 to 40 min brisk walking
(breathing accelerated)
80% 8 wk Balance (foot pressure plate):
One leg balance with eyes open
One leg balance with eyes closed
Telenius etal. 2015 [55] MT group (n = 87)
C group (n = 83)
86.9 ± 7.4 y
73.5% females, institutionalized
older adults with dementia
12 wk, 2 d/w, supervised
High- intensity MT
RT, 2 exercises, 1 set of 12 reps
12RM. Rest no reported
Balance, 2 static, or dynamic
exercises performed near
the limits of maintaining
postural stability
75% 12 wk Standing ability:
STS 30 s (stopwatch)
Gait speed:
6 m (stopwatch)
Zech etal. 2012 [56] RT group (n = 2 4)
RT (power) group (n = 24)
C group (n = 22)
77.6 ± 6.1 y
70% females, prefrail
older adults
12 wk., 2 d/wk., super vised
Low- intensity RT:
concentric phase with
controlled velocity (2–3 s)
High- intensity RT (power):
concentric phase as
rapidly as possible
7 exercises, 2 set of 6–15 rep
10–16 RPE (6–20)/2 min rest
No reported 24 wk Standing ability:
STS 5 reps (stopwatch)
Agility:
TUG (stopwatch)
Balance test (stopwatch):
Feet together
Semi- tandem
Tandem position
Gait speed:
6 m (stopwatch)
Abbreviations: AT, aerobic tra ining; C, control; CMJ, countermovement jump; d, day; wk, week; GS, gait speed; HRE, heart rate estimated; HRR, heart rate reser ve; MT, multicomponent training; RCHo, st anding up, circling t wo
cones 3 m behind the chair in a V shape, as fast as possible; RPE , rate of perceived exertion; RT, resistance training; STS, sit- to- stand test; R M, repetition maximum; TUG, time up and go test.
TABLE | (Continued)
9 of 14
but non- significant effects on gait speed (ES = 0.38, p = 0.0 6,
I2 = 43%) and balance (E S = 0.48, p = 0.05, I2 = 55%). Mod alities
comparisons found positive effects for both multicompo-
nent and resistance training (ES ≥ 0.84, p < 0.05, I2 ≤ 84%).
Intensities comparisons found positive effects for both high-
intensity and low- intensity interventions (ES ≥ 0. 67, p ≤ 0.03,
I2 ≤ 84%). The combination of modality and intensity with
each functional capacity subdomain indicated large and sig-
nificant protective effects on standing ability for all training
modalities and intensities (ES ≥ 0.96 , p < 0.0 4, I2 = 80% –88%)
and walking ability after low- intensity training (ES = 0.88,
p < 0.05; I2 = 0) in favor of the exercise groups. The results of
the GRADE assessment ranged from very low to moderate
quality of evidence (TableS2).
3.4 | Meta- Regression
Univariable meta- regression analysis (Table3) revealed that the
training effect (i.e., change between the pre- and post- exercise
intervention) and age significantly influenced the preservation
of functional capacity after training cessation. The benefits
obtained during the training program were positively associ-
ated with the residual effects observed after training cessation
TABLE | Subgroup meta- analyses for different training modalities, intensities, and subdomains of functional capacity. Effect sizes explain the
changes from baseline to after the detraining period in favor of the training group.
Outcomes k n ES 95% CI p I2 (%)
Modalities
Multicomponent training 11 455 0.89 0.33 to 1.46 < 0.0 01*83.6
Resistance training 9233 0.84 0.02 to 1.66 0.045*81.7
Intensities
High intensity 7325 0.67 0.10 to 1.23 0.027*73.4
Low intensity 12 329 1.06 0.37 to 1.75 0.006*84.0
Functional capacity subdomains
Agility 11 328 0.61 0.13 to 1.09 0.018*68.8
Balance 8237 0.48 −0.01 to 0.97 0.051 55.0
Gait speed 8350 0.38 −0.01 to 0.77 0.056 43.0
Stair walking 6 181 1.26 0.09 to 2.42 0.039*85.0
Walking ability 5120 0.88 0.01 to 1.75 0.049*0.0
Standing ability 16 562 1.35 0.77 to 1.94 > 0.001*84.8
Multicomponent training
Agility 6206 0.67 −0.24 to 1.59 0.116 80.8
Standing ability 9 381 1.51 0.65 to 2.36 0.004*87.8
Resistance training
Agility 5122 0.48 −0.11 to 1.07 0.087 8.9
Standing ability 7 181 1.16 0.12 to 2.20 0.034*81.7
Gait speed 5128 0.64 −0.10 to 1.37 0.073 46.1
High intensity
Agility 5152 0.44 −0.05 to 0.92 0.067 0.0
Standing ability 6 298 0.96 0.08 to 1.85 0.038*79.9
Balance 5151 0.53 −0.27 to 1.33 0.138 62.0
Low intensity
Agility 6176 0.72 −0.24 to 1.69 0.111 79.9
Standing ability 10 264 1.59 0.72 to 2.46 0.002*82.2
Walking ability 5120 0.88 0.01 to 1.75 0.049*0.0
*Signi ficant differences (p < 0.05).
Abbreviations: CI, confidence interval; ES, effect size (Hedges' g), I2, heterogeneity; k, number of inter ventions; n, total number of participants.
10 of 14 Scandinavian Journal of Medicine & Science in Sports, 2025
(β = 0.66; p < 0.01), while age negatively impacted the persisting
adaptations ( β = −0.06; p < 0.01). However, among the other mod-
erators examined, including training modality, intensity, and du-
ration of training cessation, there were no significant findings
observed in either the univariable or multivariable models.
3.5 | Risk of Bias
The risk of bias is summarized in Figure S12. Eleven studies
presented “some concerns” [42, 44–52, 54] and four studies
“low risk.” [43, 53, 55, 56] The funnel is presented in FigureS13.
Visual inspection revealed an asymmetrical shape confirmed
with Egger's test (p = 0.004). This asymmetry was not related to
publication bias but a result of large heterogeneity across studies.
4 | Discussion
While the benefits of regular exercise across the lifespan are
well- established [57–59], emerging evidence highlights its pro-
tective effect during periods of inactivity caused by falls, illness,
or hospitalizations. This is particularly important in frail popu-
lations such as older adults who commonly suffer from adverse
events that force them to interrupt physical activity levels for
days, weeks, or even months. However, there is still limited un-
derstanding regarding the exercise prescription (i.e., different
exercise modalities and intensities) to achieve the residual ef-
fects [26, 27]. The objective of this study was to systematically re-
view and analyze the current evidence from 21 different exercise
programs, focusing on their ability to counteract deconditioning
during training cessation periods in older adults. The findings
revealed that engaging in physical training twice a week for over
2 months before a hiatus of at least 1 month can significantly
preserve functional capacity, including agility, walking ability,
standing ability, and stair walking (Table2). It is worth noting
that positive effects were observed for gait speed and balance,
with results close to reaching statistical significance (p = 0.056
and p = 0.051, respectively). These results reaffirm that exer-
cise programs have long- lasting benefits on several subdomains
of functional capacity (with the exception of balance) in older
adults, regardless of the duration of training and exercise ces-
sation [60].
The meta- analysis demonstrated that functional capacity was
preserved (large effect size) regardless of the exercise modal-
ity and intensity (Table2, FiguresS2–S5). The evidence favors
multicomponent as the preferred modality for enhancing func-
tional capacity in older adults [61]. However, considering that
functional capacity is strongly influenced by individual strength
levels [62], it is expected that both modalities would lead to im-
provements in agility, walking ability, standing ability and stair
walking. This study revealed that the functional adaptations
achieved through either resistance or multicomponent training
are similarly retained following a period of training cessation.
Notably, due to substantial heterogeneity among interventions,
a dose–response relationship could not be identified. Therefore,
further exploration is needed to understand the time- dependent
relationship between exercise duration and the length of the
inactivity period, specifically regarding the regression of func-
tional capacity adaptations.
Exercise- induced strength adaptations primarily depend on
the intensity and volume of training performed within each
set [63]. The understanding of these parameters has improved,
leading to a re- evaluation of traditional beliefs that advocated
for high loads (> 85% of 1RM) and reaching muscular failure
[64–66]. Current approaches emphasize the use of technology-
based training methods to individualize intensity and manage
fatigue on a daily or weekly basis to optimize recovery while
maximizing performance gains [67]. This paradigm has proven
successful in both high- level sports settings [68] and clinical
environments, where it has been employed to assist resistance
training with older adults [69]. Recognizing the significance of
exercise intensity, our study analyzed the interventions based
on this factor. However, contrary to our expectations, we did
not observe a substantial influence of exercise intensity on the
preservation of functional capacity following periods of inac-
tivity. This unexpected finding raises questions about the effec-
tiveness of the methods used to ensure that participants were
working at the intended intensity. It is worth emphasizing that
a significant portion of the reviewed interventions (57%) relied
on self- rated perceived exertion scales, such as the RPE scale
(Table 1). Although self- rated scales are easily accessible [70],
their accuracy may be biased by individuals' training experi-
ence, with less- experienced individuals tending to underreport
(and consequently underestimate) intensity, especially at light
and moderate levels that do not approach muscular failure [71].
Supporting the limitations of self- rated tools, the largest and lon-
gest randomized controlled trial on exercise for older adults [72]
found no differences in overall mortality rates among three self-
directed interventions (national guidelines vs. high- intensity
exercise vs. moderate- intensity exercise), aligning with findings
from supervised interventions employing objective monitoring
methods. Therefore, to enhance the precision of exercise inter-
ventions in older adults, it would be advisable to combine self-
rated assessments with objective tools to better control intensity
and manage fatigue [71].
TABLE | Meta- regression analyses for different moderators.
Moderators Beta 95% CI p
Sample age (years) −0.06 −0.10 to −0.02 0.006*
Training effect (ES) 0.66 0.32 to 1.01 0.003*
Exercise modality (ES)a−0.05 −0.97 to 0.87 0.660
Exercise intensity (ES)b0.29 −0.53 to 1.10 0.461
Training duration
(we eks)
−0.02 −0.09 to 0.05 0.408
Detraining duration
(we eks)
−0.01 −0.03 to 0.02 0.381
Note: Beta coefficients explain the changes in the detraining ef fect size (ES)
either per unit of change in the moderator (for continuous moderators: age,
training effect, training, and detraining duration) or between t wo conditions (for
binary moderators: exercise modality and intensity).
Abbreviation: CI, confidence interval.
*Signi ficant differences (p < 0.05).
aReference condition: multicomponent training.
bReference condition: high intensity.
11 of 14
Despite the well- established healing effects of exercise, its im-
proper implementation can have detrimental consequences[73].
Nowadays, various accessible methodologies are being em-
ployed in both healthy [74] and unhealthy [75] older adult popu-
lations to facilitate exercise monitoring and enhance the quality
of interventions. Resistance training interventions, for instance,
can benefit from the use of force sensors [76, 77] or linear
transducers [69] to accurately adjust intensity and volume. In
aerobic training, intensity levels can be supervised using heart
rate monitors [78] in combination with RPE measurements for
more precise monitoring. Additionally, velocity parameters can
be implemented for walking interventions [79], while power
meters can be utilized for cycling interventions [75] to moni-
tor external load. Therefore, the above- mentioned approaches
should complement the implementation of effective and tailored
interventions.
The meta- regression analyses showed a significant influence of
moderators on the residual effects of physical exercise on func-
tional capacity (Table3). The benefits obtained during the train-
ing program (i.e., the change between the pre- and post- exercise
intervention) were positively associated with the residual effects
observed after training cessation. This influence of the training
effect, and consequently, greater functional capacity is consis-
tent with previous studies analyzing the residual adaptations
of exercise training on functional capacity after short and long
detraining periods [25, 60]. This finding supports the fact that
individuals with higher fitness levels may experience less func-
tional decline compared to those with lower physical condition
[24]. On the other hand, the age of participants negatively influ-
enced the residual effects of exercise training, which indicates
that older adults with higher age reported lower residual effects.
This finding would agree with previous studies analyzing the
effects of the exercise cessation period, where the oldest par-
ticipants (i.e., ≥ 74 years) reported no residual effect on walk-
ing ability, while younger participants (i.e., ≤ 73 years) showed
long- lasting benefits in this capacity [80, 81]. Hence, it is of vital
importance to maintain regular physical exercise or reduce as
much as possible exercise cessation periods in the oldest popu-
lation. Among the characteristics of participants influencing the
residual effects of exercise training, institutionalization could
play a significant role. Despite the inclusion of 15 studies in
this systematic review, only 3 RCTs with institutionalized older
adults were included in the meta- analysis [44, 53, 55], which is
limited to conducting subgroup analyses according to Cochrane
guidelines [28]. However, the subgroup meta- analysis for agility
(FigureS6) and standing ability (FigureS9) reported the lowest
effect sizes in studies with institutionalized participants com-
pared to community- dwelling older adults. While these results
may suggest that institutionalized older adults report lower re-
sidual effects, these findings should be interpreted with caution
due to the limited number of studies and lack of subgroup meta-
analysis for this condition. Therefore, future studies analyzing
the potential inf luence of institutionalization on the residual
effects are needed.
The adherence rate to exercise programs is a critical factor in
ensuring their effectiveness [82]. However, only 11 out of 21
training programs (52%) reported adherence rates, with an aver-
age of 77% (Table1). Overall, adherence to all exercise programs
was high, regardless of the training modality, with rates of 77%
for resistance and multicomponent training. Interestingly, low-
intensity training reported a higher adherence rate (83%) com-
pared to high- intensity training (71%). Although these results
may suggest that low- intensity training is a preferable strategy
for improving adherence, these findings should be interpreted
with caution due to the limited number of interventions examin-
ing adherence and the potential inaccuracies in intensity moni-
toring. Reporting adherence rates should be a standard practice
for exercise- based interventions involving older adults to evalu-
ate the effectiveness of exercise programs and promote the phys-
ical health and safety of this population [83] Furthermore, these
adherence rates can provide valuable insights into the barriers
that hinder older adults from participating in exercise inter-
ventions and help in devising long- term strategies to enhance
engagement.
5 | Study Limitations
This research is not exempt from limitations. First, some of the
examined outcomes showed moderate to high levels of hetero-
geneity. Second, the lack of consensus on the assessment meth-
ods limits the ability to compare studies and interpret findings.
Third, we had to estimate results from studies that only reported
them graphically or lacked some specific statistic (e.g., SD).
Finally, we categorized exercise intensity dichotomously accord-
ing to established cut- off values due to the several methods of
monitoring intensity in the studies included.
6 | Perspectives
This study adds new evidence to the existing literature as the
first systematic review and meta- analysis focused on the pres-
ervation of functional capacity after training cessation in older
adults. The key resu lts indicate that exercise- based interventions,
regardless of modality (resistance or multicomponent training)
or intensity (high or low), exhibit residual effects that preserve
functional capacity even after training cessation. Older adults
with greater exercise- related benefits prior to training cessation
showed better long- lasting effects, while those of greater age
experienced a lower preservation of functional capacity. These
findings advocate for the implementation of tailored interven-
tions that prioritize exercise modalities and intensities that op-
timize adherence and maximize the enhancement of functional
capacity in older adults, especially in the oldest population.
Conflicts of Interest
The authors declare no conflicts of interest.
Data Availability Statement
The data that support the findings of this study are available from the
corresponding author upon reasonable request.
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Supporting Information
Additional supporting information can be found online in the
Supporting Information section.