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The association between sedentary behaviour and sarcopenia in older adults: a systematic review and meta-analysis

BMC Geriatrics volume 23, Article number: 877 (2023) Cite this article

Abstract

Background

Sedentary behaviour is considered to contribute to sarcopenia when combined with physical inactivity. Whether sedentary behaviour is independently associated with sarcopenia remains controversial. The aim of this study is to explore the association between sedentary behaviour and sarcopenia in older adults in community and long-term care facility settings.

Methods

Eight electronic databases including MEDLINE, PsycINFO, Wanfang were searched from inception until August 2023. The review included cross-sectional and longitudinal studies concerning the association between sedentary behaviour and sarcopenia among participants over 60 years old. Evidence was pooled by both random-effects meta-analysis and narrative synthesis. Subgroup analyses explored variation according to adjustment of physical activity, settings, and measurements of sedentary behaviour and sarcopenia. Quality assessment for individual studies was performed with the Joanna Briggs Institute (JBI) Critical Appraisal Checklist.

Results

Seventeen articles (16 cross-sectional studies and 1 longitudinal study) of 25,788 participants from community or long-term care facility settings were included. The overall quality of the included studies was rated high. Meta-analysis of 14 cross-sectional studies showed that sedentary behaviour was independently positively associated with sarcopenia: pooled odd ratio 1.36 (95% confidence interval, 1.18–1.58). The independent positive association remained in subgroup analyses by adjustment of physical activity, settings, and measurements of sedentary behaviour and sarcopenia. The narrative analysis corroborated the findings of the meta-analysis and provided additional evidence suggesting that interruptions in sedentary periods were linked to a decreased likelihood of developing sarcopenia.

Conclusions

The findings support the hypothesis that sedentary behaviour is independently positively associated with sarcopenia in older adults, providing vital indications for the development of strategies to prevent sarcopenia.

Systematic review registration

The systematic review protocol has been registered with the PROSPERO database (CRD42022311399).

Peer Review reports

Background

Sarcopenia is defined as age-related loss of skeletal muscle mass plus loss of muscle strength and/or reduced physical performance [1]. The prevalence of sarcopenia worldwide is 10% among community-dwelling older adults while it is 38% among nursing home residents [2]. Sarcopenia is a strong predictor of a range of adverse clinical outcomes and is therefore an important public health concern. For example, it increases the risk of falls and fractures by approximately 90% in older people [3] and increase the risk of cognitive impairment two-fold [4]. It also increases the risk of disability, morbidity and mortality, and reduced quality of life for older adults [5,6,7,8]. Along with other risk factors, sedentary behaviour has been found to contribute significantly to sarcopenia when combined with physical inactivity [9, 10], and has been recommended to be an independent part from physical inactivity to achieve optimal musculoskeletal health [11, 12].

Sedentary behaviour is defined as any waking behaviour in a sitting, reclining or lying posture with low energy expenditure of ≤ 1.5 metabolic equivalent units (METs) [13, 14] while physical inactivity is when an individual does not perform a sufficient amount of physical activity to meet current age appropriate recommendations [11, 15]. Findings from systematic reviews suggest that greater sedentary time was related to an increased risk of all-cause mortality in older adults [16] and reduced cognitive function over the lifespan [17]. A meta-analysis provided support for the hypothesis that sedentary lifestyles are strong predictors of falls among older adults [18]. Some studies also indicated a relationship between sedentary behavior and metabolic syndrome, waist circumference, and overweightness/obesity [16]. An umbrella review reported that older adults (≥ 60 years) with physical inactivity are at an increased risk of all-cause and cardiovascular mortality, breast and prostate cancer, fractures, recurrent falls, disability in activities of daily life, functional limitation, cognitive decline, dementia, Alzheimer’s disease, and depression [19]. In addition, lower objectively measured sedentary behaviour and higher physical activity were reported to be associated with a better ability to complete activities of daily life and instrumental activities of daily life [20].

An important question is whether sedentary behaviour is independently associated with sarcopenia. Studies to date have reported inconsistent findings [21, 22], and the benefits of reducing sedentary time alone without increasing physical activity for people with sarcopenia remains unknown. This is largely because most exercise-based interventions only focus on increasing physical activity (e.g., resistance exercise training) with less consideration of reducing peoples’ sedentary behaviour [23,24,25,26,27,28,29]. The relationship between sedentary behaviour and sarcopenia has begun to be explored in recent studies. Some studies suggest that sarcopenia is an adverse outcome of sedentary behaviour [9, 30], whilst others suggest that sedentary behaviour is caused by sarcopenia and is a product of declining muscle mass and physical function [10, 31, 32].

Nevertheless, conflicting results are found across studies and positive association between sedentary behaviour and sarcopenia are not always found [22]. This paper is aimed to systematically examine the association between sedentary behaviour and sarcopenia among older adults.

Materials and methods

Protocol registration

We followed the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement (PRISMA 2020) [33] (Supplementary material 1) and registered the protocol with the PROSPERO database of systematic reviews (CRD42022311399).

Search strategy and eligibility criteria

Eight bibliographic databases were searched, including five English language databases (MEDLINE via Ovid, Excerpta Medica (Embase) via Ovid, PsycINFO via Ovid, CINAHL via EBSCOhost, Web of Science) and three Chinese language databases (Chinese National Knowledge Infrastructure, Wanfang and SinoMed). Electronic searches were performed from their inception to 8th August 2023. The electronic search terms were designed to be broad and inclusive of sarcopenia and its components. The following text words were applied: “sarcopenia” “sedentary” “sitting”, as well as the Medical Subject Heading (MeSH) terms if applicable. Detailed search strategies for each database were presented in supplementary material 2. Search strategies were adapted for the eight different databases. There were no restrictions on publication date or language. We supplemented the electronic searches by checking the reference lists of included studies and by consulting experts to identify potentially eligible studies.

Eligibility criteria were (1) Study design: Observational studies (cross-sectional studies and cohort studies) and baseline data of experimental studies (randomised control trials, quasi-randomised control trails, case-control studies); (2) Settings: Community or long-term care facility setting; (3) Population: Adults aged 60 years or older, without a neurological (e.g., motor neuron disease, stroke) or wasting condition (e.g., liver disease) affecting skeletal muscle health; (4) Sarcopenia: Widely accepted diagnostic criteria for sarcopenia, including the European Working Group on Sarcopenia in Older Persons (EWGSOP) [9, 34], EWGSOP2 criteria [9], the Foundation for the National Institutes of Health (FNIH) criteria [35], the Asian Working Group for Sarcopenia (AWGS) criteria [36] or the strength, assistance in walking, rising from a chair, climbing stairs, and falls questionnaire (SARC-F) [37]; (5) Sedentary behaviour: Objective or subjective measures of sedentary behaviour, recorded using any parameter, including sitting time, lying time, reclining time, counts per minute (CPM)-based intensity threshold values, and sedentary break times. Measurement tools could be self-reported questionnaires or any objectively physical devices (e.g., GT3X + accelerometers, activPAL device, etc.).

Data management and selection process

Search results were imported into EndNote 20.2, duplicates were removed, and then imported into Covidence software (http://www.covidence.org) to screen and identify eligible publications. Two reviewers (YM, YZ) independently screened and reviewed a random sample of 20% of all titles and abstracts. At this stage of the process, regular reviewer meetings were held to compare decisions on eligibility, discuss any uncertainties, and reach consensus. At the end of this process, the two reviewers reached agreement on all the 20% of the studies. Finally, one reviewer (YM) screened the remaining 80% of the titles and abstract independently. Records that appeared to meet the criteria or with any uncertainty were further screened in full text. Full text records were reviewed by both reviewers (YM, YZ) independently and discussed when there was any disagreement on eligibility. A third reviewer (CE or MM or HC) was invited when the disagreement was unresolved.

Data extraction and outcomes of interest

Data from included articles were extracted by two reviewers independently (YM, YZ) with the guidance of a data extraction template designed for the study. This form included the following information: (1) Article title, authors, year of publication, country; (2) Study design; (3) Participant description, including age, sex, ethnicity and medical conditions; (4) Setting, such as community or long-term care facility; (5) Sedentary behaviour definition and measurement method; (6) Sarcopenia definition and measurement method; (7) Main results – outcome of sarcopenia and explanatory variable of sedentary behaviour, and potential confounders such as age, sex, physical activity, nutritional status, and chronic diseases. When a study provided several adjusted models, the fully adjusted model was extracted; (8) Brief conclusion and limitations of the study. Corresponding authors of the articles were contacted in cases of missing information or data. The primary outcomes were the adjusted associations between sedentary behaviour and sarcopenia, expressed as Odd Ratio (OR) value or Relative Risk (RR) value or Hazard Risk (HR) value and 95% confidence intervals (CI). The secondary outcomes were (1) the relationship between sedentary behaviour and sarcopenic obesity, and/or components of sarcopenia, (2) sedentary break times and sarcopenia (sarcopenic obesity), and (3) sub-group analysis by adjustment of physical activity, setting, measure of sedentary behaviour, and measure of sarcopenia.

Quality assessment of included studies

Two reviewers (YM, YZ) independently conducted the quality assessment of included studies using assessment tools accordingly. For cross-sectional studies, the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies (8 items) was used [38]. For cohort studies, the JBI Critical Appraisal Checklist for Cohort Studies (11 items) was used [38]. Each item was scored as 0 or 1 or 2 points; 0 = the aspect does not meet the requirements (No), 1 = the aspect has been mentioned but without a detailed description (Uncertain), 2 = the aspect has been described in detail comprehensively (Yes). The summary score, obtained by dividing the total score by the maximum possible score, was used to classify studies as high quality ≥ 70%, medium quality 40–69%, or low quality < 40%. Both reviewers (YM, YZ) recorded the score process and classification. When there was any unresolved disagreement on the quality of studies between the two reviewers after discussion, a third reviewer (CE or MM or HC) was invited to discuss to reach an agreement.

Data synthesis

Data were synthesised using meta-analysis when studies presented (1) sedentary behaviour/time and dichotomous classifications of sarcopenia, and (2) were sufficiently homogenous from a clinical (i.e., population, outcome) and methodological (i.e., study design) point of view. The random-effect model was used to determine the pooled OR value for the association between sedentary behaviour and sarcopenia. Subgroup analysis was performed based on (1) adjustment of physical inactivity, (2) study setting, (3) measures of sedentary behaviour, (4) measures of skeletal muscle mass, muscle function, and (5) diagnostic criteria of sarcopenia. Narrative analysis was performed for data that did not meet the criteria for meta-analysis.

The statistical heterogeneity of the included studies was examined by the chi square-based Cochran’s Q statistic test and I2 statistic [39, 40]. p < 0.1 or I2 > 50% indicates significant heterogeneity [38]. Sensitivity analyses were used to test the effect of including different studies. For studies which were judged to be too clinically or methodologically heterogeneous, a narrative approach was used to synthesis the data [41]. To assess publication bias, funnel plots were inspected visually, and the Egger’s test was used. Statistical analyses were performed using the metan and metainf packages in the STATA v 15 (Stata Corp, College Station, TX). Two-tailed p values < 0.05 were considered statistically significant.

Results

Retrieval

A total of 4765 articles were identified through an initial literature search. After removing duplicates and screening of titles and abstracts, 196 full-text articles were assessed for eligibility. The main reason for ineligibility was the study not reporting the association between sedentary behaviour and sarcopenia. Finally, 17 articles [8, 10, 21, 22, 30,31,32, 42,43,44,45,46,47,48,49,50,51] were included (Fig. 1).

Fig. 1
figure 1

Flowchart for study selection process

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Characteristics of included studies

Sixteen cross-sectional studies [8, 10, 21, 22, 30,31,32, 43,44,45,46,47,48,49,50,51] and one longitudinal study [42] were included. The 17 included articles comprised 25,788 participants with the age ranging from 60.0 to 92.7 years. The proportion of male and female participants in the total included sample were 45.6% and 54.4% respectively. In terms of the targeted population, 14 studies included community populations [8, 10, 21, 22, 32, 42,43,44,45,46,47,48, 50, 51], and three studies [30, 31, 49] recruited residents living in long-term care facilities. Regarding sarcopenia diagnostic criteria, nine studies [10, 21, 30,31,32, 42, 43, 45, 48] used the EWGSOP criteria [34], three studies [22, 44, 49] used EWGSOP2 criteria [9], and the remaining four articles diagnosed sarcopenia separately using the SARC-F questionnaire (n = 2) [47, 50], the AWGS criteria (n = 2) [46, 51] or FNIH criteria (n = 1) [8]. For the measurement of skeletal muscle mass, dual-energy X-ray absorptiometry (DXA) (n = 5) [8, 22, 32, 43, 48], bioelectrical impedance analysis (BIA) (n = 6) [30, 31, 44, 46, 49, 51], and anthropometrics and equations (n = 4) [10, 21, 42, 45] were used. Another two studies [47, 50] used SARC-F questionnaire to diagnose sarcopenia without a direct measurement of skeletal muscle mass. For measurement of skeletal muscle strength, hand grip strength (HGS) were used in most of the included studies except one study using leg muscle strength [32] and two studies not measuring this aspect [47, 50]. The assessment tools for sedentary behaviour were mainly self-reported questionnaires (n = 12) [10, 30,31,32, 42, 43, 45,46,47,48, 50, 51], such as the International Physical Activity Questionnaire [52] (IPAQ) [30, 31, 43, 45, 47, 48], and five studies adopted objective measurement of physical activity by using ActiGraph accelerometer [8, 21, 22, 44, 49]. All studies were classified as high-quality with scores ranging from 81.25 to 100%. Detailed study characteristics and the quality assessment results are shown in Tables 1 and 2 respectively.

Meta-analysis results

Fourteen cross-sectional studies [8, 10, 21, 30,31,32, 43,44,45,46,47, 49,50,51] with a total of 21,989 participants were pooled in the meta-analysis. In five studies [10, 46, 47, 50, 51] that grouped participants according to sedentary time in several categories, OR values from the group with the longest sedentary time were used. After adjusting for confounders including sex, age, BMI, education, physical activity, chronic diseases, etc., the pooled adjusted OR value of the association between sedentary behaviour and sarcopenia extracting from 14 articles [8, 10, 21, 30,31,32, 43,44,45,46,47, 49,50,51] was 1.36 (95%CI, 1.18–1.58). There was significant heterogeneity (p < 0.001, I2 = 80.2%) across studies. The high heterogeneity may result from with or without adjustment of physical activity, different settings, various measurements of sedentary behaviour and sarcopenia, different diagnostic criteria of sarcopenia. We further conducted subgroup analyses based on these factors.

Subgroup analyses showed a stronger association between sedentary behaviour and sarcopenia without adjustment for physical activity (OR 2.10, 95%CI 1.16, 3.82) than with adjustment for physical activity (OR 1.29, 95%CI 1.12, 1.49). However, the difference was not statistically significant ((between groups p = 0.117) (Fig. 2). As to different setting, studies enrolling community-dwelling older adults (OR 1.39, 95%CI 1.18, 1.65) tended to find a similar association between sedentary behaviour and sarcopenia with studies enrolling residents in long-term care facility (OR 1.38, 95%CI 0.83, 2.28) (between groups p = 0.961) (Fig. 3). In terms of measurement of sedentary behaviour, studies using self-reported questionnaire showed higher OR value (OR 1.66, 95%CI 1.29, 2.12) than the studies using objective physical measurement (OR 1.04, 95%CI 0.95, 1.15). The difference was statistically significant (between groups p = 0.001) (Fig. 4).

Fig. 2
figure 2

Forest plot of the associations between sedentary behaviour and sarcopenia by subgroup analysis based on with or without adjustment for physical activity

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Fig. 3
figure 3

Forest plot of the associations between sedentary behaviour and sarcopenia by subgroup analysis based on settings

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Fig. 4
figure 4

Forest plot of the associations between sedentary behaviour and sarcopenia by subgroup analysis based on sedentary behaviour measurement

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Additional subgroup analysis for different muscle mass and physical performance measurements also supported the positive association between sedentary behaviour and sarcopenia. The group not measuring skeletal muscle mass nor physical performance (the two studies using SARC-F questionnaire defining sarcopenia) demonstrated a significant stronger association (OR 2.87, 95%CI 1.47, 5.60). In contrast, the group that measured muscle mass using DXA (OR 1.17, 95%CI 1.00, 1.35) and the group that measured physical function using SPPB (OR 1.18, 95%CI 0.98, 1.40) showed the lowest OR values in the corresponding subgroup analysis (Table 3). As to different sarcopenia diagnostic criteria, we only conducted a subgroup meta-analysis for EWGSOP criteria because only it was used in more than three studies within the 14 studies included in meta-analysis part of this study, with a pooled OR of 1.17 (95%CI 1.01, 1.34).

The association between sedentary behaviour and sarcopenia was further confirmed by sensitivity analysis. Sensitivity analysis was performed repeatedly by removing one study each time, with the pooled OR fluctuating between 1.22 (95%CI 1.08–1.36) and 1.51 (95%CI 1.22–1.85). Removing any single study did not change the overall meta-analysis results indicating the finding as robust and reliable. The asymmetric funnel plot indicated a possible publication bias (Supplementary material 3), supported by the Egger’s test (p = 0.002).

Narrative synthesis results

Three studies [22, 42, 48] were only synthesised narratively due to heterogeneity. Overall, these studies supported a positive association between sedentary behaviour and sarcopenia, and sarcopenic obesity. In a 24-month prospective study, older adults who presented slow gait speed during the follow-up and with sedentary behaviour presented a higher risk of sarcopenia, independent of physical activity levels, age, and sex (HR 1.30, 95% CI 0.40, 4.24). At the same time, older adults who remained sedentary at 24-month follow-up also independently demonstrated a higher risk of sarcopenic obesity [42]. The study enrolling Quilombola, Afro-Brazilian residents, as participants found that older adults who were irregularly active or sedentary (not discriminated) were at least six times more likely to develop sarcopenia than those who were assessed to be active to very active [48]. Only one study examining the relationship between accelerometer-determined sedentary behaviour and probable or confirmed sarcopenia (not discriminated) in community-dwelling older adults demonstrated no association after multivariable adjustment [22].

Additional data from three studies included in the meta-analysis [8, 21, 32] also contributed to the narrative analysis, supporting the negative association between breaks in sedentary time and risk of sarcopenia, and sarcopenic obesity. Using an isotemporal substitution model, one study [8] found that the reallocation of one hour per day of sedentary behaviour with moderate-to-vigorous physical activity (MVPA) lowered sarcopenia risk (OR 0.52, 95%CI 0.36–0.75; P < 0.001), and when moderate-to-vigorous physical activity was substituted with sedentary behaviour, the sarcopenia risk was raised (OR 1.92, 95%CI 1.33, 2.77; P < 0.001). A cross-sectional study in a community setting suggested that self-reported breaks in sedentary time were associated with a lower risk of sarcopenia (OR 0.26, 95%CI 0.05, 1.39) [32]. Another cross-sectional study also found that for community-dwelling older men, sedentary breaks were marginally associated with a reduced risk of sarcopenic obesity (RR 0.84 [95% CI 0.71, 0.99]). In addition, it also reported a marginal association between sedentary time and increased risk of severe sarcopenia (RR 1.07 [95% CI 0.91, 1.26]) and sarcopenic obesity (RR 1.18 [95% CI 0.99, 1.40]), independent of physical activity levels [21].

Discussion

This systematic review and meta-analysis highlighted the independent positive association between sedentary behaviour and sarcopenia, regardless of adjustment of physical activity, community or long-term care facility settings, or different measurements of sedentary behaviour and sarcopenia. Our findings align with recent studies. For instance, a systematic review demonstrated that sedentary behaviour and physical inactivity is strongly associated with reduced skeletal muscle strength and diminished muscle power, which are critical characteristic of sarcopenia [53]. A 2-year longitudinal cohort study also suggested that older adults who maintained sedentary behaviour and exhibited low gait speed during the follow-up were at a greater risk of sarcopenia [42].

Lower gait speed of older adults with sarcopenia may be a possible factor which explains the association between sedentary behaviour and sarcopenia. It has been found that low gait speed is associated with high sedentary behaviour [54]. On the one hand, older adults with a slower gait speed are more likely to have poorer functional status and overall health [55], and to experience multiple falls [56], therefore, they are prone to choose sedentary behaviour in their daily life. On the other hand, accumulating sedentary time for prolonged time is independently related to the disuse of muscle and tendon [57, 58]. Severe muscle disuse induces rapid muscle atrophy [59, 60], leading to a vicious circle. Several plausible physiological mechanisms could also offer insight into the association. First, high level of sedentary behaviour may result in diminished muscle protein synthetic response by reducing muscle anabolic sensitivity [11]. The decreased sensitivity of muscles to anabolic signals is likely a significant factor in the muscle loss and decline in physical function (i.e., sarcopenia) [11]. Second, prolonged sitting time could enhance the levels of chronic low-grade inflammation [61] and increase deep adipose tissue and visceral adiposity [29], which have been shown to promote muscle wasting, ultimately stimulating protein catabolism and suppressing muscle synthesis [62].

The subgroup analysis demonstrated the adjustment of physical activity do not result in statistically significant difference on the independent association between sedentary behaviour and sarcopenia. Former studies also suggested that prolonged involvement in sedentary activities detrimentally affects skeletal muscle mass and functional abilities among older adults, regardless of their engagement in physical activity [31, 32]. Hence, it is recommended to consider sedentary behaviour and physical inactivity as two distinct risk factors, each requiring targeted interventions to attain optimal musculoskeletal health [11, 63, 64]. Results of narrative analysis found that breaks in sedentary time and replacing sedentary time with physical activity contribute to reduced risk of sarcopenia [8, 21, 32]. This is supported by the study that found breaking-up sedentary time is associated with physical function in older adults [65]. Further research also indicates that breaking up sedentary time regularly with a sufficient level of movement that goes beyond a simple muscular contraction (such as walking instead of merely standing) could potentially be effective in maintaining skeletal muscle anabolic sensitivity, muscle mass, and physical function in older adults [66].

The findings from subgroup analysis indicated that sedentary behavior raised the risk of sarcopenia by around 40% in both community-dwelling older adults and long-term care facility residents. Studies have indicated that individuals over the age of 60 spend around 80% of their waking hours engaged in sedentary activities, equating to approximately 8 to 12 h each day [67,68,69]. Particularly among residents in long-term care facilities, a significant 85% of their waking hours are occupied by sedentary activities [70]. The prevalence of sarcopenia among long-term care facility residents (38%) is also higher than in the community-dwelling older adults (10%) [2]. Given the functional limitations and multimorbidity of the majority of residents in long-term care facilities, interventions that target the reduction of sedentary behavior rather than demanding physical exercise might be a more significant, practical and approachable approach to combat sarcopenia. This is also well reflected in recent recommendations and guidelines which make it a priority to reduce sedentary behaviour among all long-term care facility residents [63, 64]. Notably, we only identified three cross-sectional studies conducted in long-term care facilities, more studies with diverse study design are warranted to explore sedentary behaviour and sarcopenia in long-term care facilities.

Results of subgroup analysis showed that sedentary behaviour significantly increased the risk of sarcopenia by 66% in the group using self-reported questionnaires, which is almost sixteen-fold higher than that of the group using objective physical devices measurement (4%). The difference may be attributed to recall bias and a low correlation between subjective and objective measures of sedentary time [71, 72]. Some included studies using self-reported questionnaires to measure sedentary time only used a single question “how much time did you usually spend on sitting during the last 7 days” [30, 31, 47, 73]. However, this broad question without detailed prompts could be difficult for older adults to recall [74], and tends to misestimate their sedentary time compared to objective measures [75, 76]. To increase the validity of self-reported questionnaires, additional detail of types or examples of activities on a daily basis and a visual analogue scale are recommended [71, 76]. Ecological momentary assessment (EMA) gathering real-time self-reports of behaviours, contexts, emotional states, and perceptions in naturalistic setting may also be an effective way to reduce recall bias [77]. On the other hand, the potential motivational effect of sedentary behaviour measurement devices may diminish the association between sedentary behaviour and sarcopenia. Wearing a device that monitors activity time are used to enhance intervention effect and compliance [78, 79]. The feeling of novelty and being supervised with a physical device may motivate older adults to increase their activity, termed reactivity [80]. From this perspective, objective measurement instruments of sedentary behaviour can also serve as a part of sedentary behaviour intervention.

Strengths and limitations

There are some strengths of this review. First, the strict inclusion of studies which used validated sarcopenia definitions, taking confounders into consideration enhanced the rigour of our results. Besides, searching across three widely used Chinese bibliographic databases provided greater coverage of possible related studies. Several limitations of our review should be addressed. First, only one longitudinal study meeting our eligibility criteria was included. Due to the heterogeneity, only cross-sectional studies were included in the meta-analysis. More longitudinal studies focusing on this topic are warranted. Second, almost all the included studies only reported the OR/RR/HR value between sedentary behaviour presented in terms of categorical format and sarcopenia, rather than continuous sedentary time. This may have caused some bias of different cut-off points when synthesising. Furthermore, most studies included in the meta-analysis were adjusted for age, chronic diseases and physical activity when exploring the association between sedentary behaviour and sarcopenia, but nutritional status, which is a key risk factor for sarcopenia [9, 81], was not commonly adjusted for. A standard set of confounders covering the main risk factors of sarcopenia is recommended in further studies. Finally, even though studies which comprised populations from both the community and long-term care facility settings were included, only three studies from long-term care facilities were identified. This limits the generalizability of the findings across settings and reveals the priority for future research in long-term care facilities.

Conclusion

In conclusion, sedentary behaviour is independently positively associated with sarcopenia in older adults, regardless of adjustment of physical activity, settings, measurements of sedentary behaviour and sarcopenia. The findings provide vital indications for the development of strategies to prevent sarcopenia.

Table 1 Characteristics of the included studies
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Table 2 Quality assessment results of results included studies using the JBI critical appraisal checklist
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Table 3 Subgroup analysis of the associations between sarcopenia and sedentary behaviour with different skeletal muscle mass measures, and physical performance measures
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Data Availability

The data used and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ACE I/D:

Angiotensin-Converting enzyme Insertion/Deletion

ASMM:

Appendicular skeletal muscle mass

AWGS:

Asian Working Group for Sarcopenia

BFM:

Body fat mass

BIA:

Bioelectrical impedance analysis

BMI:

Body mass index

CI:

Confidence intervals

CPM:

Counts per minutes

DXA:

dual-energy X-ray absorptiometry

EMA:

Ecological momentary assessment

EWGSOP:

European Working Group on Sarcopenia in Older Persons

FM%:

Fat mass percentage

FNIH:

The Foundation for the National Institutes of Health

GS:

Gait speed

GPAQ:

Global physical activity questionnaire

HGS:

Hand grip strength

HR:

Hazard Risk

IPAQ:

International Physical Activity Questionnaire

IPAQ-SV:

International physical activity questionnaire-short version

JBI:

Joanna Briggs Institute

IADL:

Instrumental Activity of Daily Living

LMM:

Low muscle mass

LMS:

Low muscle strength

LPP:

Low physical performance

LPA:

Light physical activity

MeSH:

Medical Subject Heading

MVPA:

Moderate-to-vigorous physical activity

OR:

Odd Ratio

PASE:

Physical activity scale for the elderly

PRISMA 2020:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement

RR:

Relative Risk

SD:

Standard deviation

SMM:

Skeletal muscle mass

SPPB:

Short physical performance battery

SARC-F:

The strength, assistance in walking, rising from a chair, climbing stairs, and falls questionnaire

TUG:

Time up to go

WC:

Waist circumference

WHR:

Waist-to-hip ratio

References

  1. Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: Consensus Report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15(2):95–101.

    Article  PubMed  Google Scholar 

  2. Papadopoulou SK, Tsintavis P, Potsaki G, Papandreou D. Differences in the prevalence of Sarcopenia in Community-Dwelling, nursing home and hospitalized individuals. A systematic review and Meta-analysis. J Nutr Health Aging. 2020;24(1):83–90.

    Article  CAS  PubMed  Google Scholar 

  3. Yeung SSY, Reijnierse EM, Pham VK, Trappenburg MC, Lim WK, Meskers CGM, et al. Sarcopenia and its association with falls and fractures in older adults: a systematic review and meta-analysis. J Cachexia Sarcopenia Muscle. 2019;10(3):485–500.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Peng TC, Chen WL, Wu LW, Chang YW, Kao TW. Sarcopenia and cognitive impairment: a systematic review and meta-analysis. Clin Nutr. 2020;39(9):2695–701.

    Article  PubMed  Google Scholar 

  5. Beaudart C, Zaaria M, Pasleau F, Reginster JY, Bruyère O. Health Outcomes of Sarcopenia: A Systematic Review and Meta-Analysis. Wright JM, editor. PLoS ONE. 2017;12(1):e0169548.

  6. Landi F, Cruz-Jentoft AJ, Liperoti R, Russo A, Giovannini S, Tosato M, et al. Sarcopenia and mortality risk in frail older persons aged 80 years and older: results from ilSIRENTE study. Age Ageing. 2013;42(2):203–9.

    Article  PubMed  Google Scholar 

  7. Sousa AS, Guerra RS, Fonseca I, Pichel F, Amaral TF. Sarcopenia and length of hospital stay. Eur J Clin Nutr. 2016;70(5):595–601.

    Article  CAS  PubMed  Google Scholar 

  8. Sánchez-Sánchez JL, Mañas A, García‐García FJ, Ara I, Carnicero JA, Walter S, et al. Sedentary behaviour, physical activity, and Sarcopenia among older adults in the TSHA: isotemporal substitution model. J Cachexia Sarcopenia Muscle. 2019;10(1):188–98.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31.

    Article  PubMed  Google Scholar 

  10. Smith L, Tully M, Jacob L, Blackburn N, Adlakha D, Caserotti P, et al. The Association between Sedentary Behavior and Sarcopenia among adults aged ≥ 65 years in low- and Middle-Income Countries. IJERPH. 2020;17(5):1708.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Shad BJ, Wallis G, van Loon LJC, Thompson JL. Exercise prescription for the older population: the interactions between physical activity, sedentary time, and adequate nutrition in maintaining musculoskeletal health. Maturitas. 2016;93:78–82.

    Article  PubMed  Google Scholar 

  12. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451–62.

    Article  PubMed  Google Scholar 

  13. on behalf of SBRN Terminology Consensus Project Participants, Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, et al. Sedentary Behavior Research Network (SBRN) – terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):75.

    Article  Google Scholar 

  14. Sedentary Behaviour Research Networ. Letter to the editor: standardized use of the terms sedentary and sedentary behaviours. Appl Physiol Nutr Metab. 2012;37(3):540–2.

    Article  Google Scholar 

  15. Kohl HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, et al. The pandemic of Physical Inactivity: global action for public health. The Lancet. 2012;380(9838):294–305.

    Article  Google Scholar 

  16. de Rezende LFM, Rey-López JP, Matsudo VKR. Luiz O do C. Sedentary behavior and health outcomes among older adults: a systematic review. BMC Public Health. 2014;14(1):333.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Falck RS, Davis JC, Liu-Ambrose T. What is the association between sedentary behaviour and cognitive function? A systematic review. Br J Sports Med. 2017;51(10):800–11.

    Article  PubMed  Google Scholar 

  18. Jiang Y, Wang M, Liu S, Ya X, Duan G, Wang Z. The association between sedentary behavior and falls in older adults: a systematic review and meta-analysis. Front Public Health. 2022;10:1019551.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Cunningham C, O’ Sullivan R, Caserotti P, Tully MA. Consequences of Physical Inactivity in older adults: a systematic review of reviews and meta-analyses. Scand J Med Sci Sports. 2020;30(5):816–27.

    Article  PubMed  Google Scholar 

  20. Amaral Gomes ES, Ramsey KA, Rojer AG, Reijnierse EM, Maier AB. The Association of objectively measured physical activity and sedentary behavior with (Instrumental) activities of Daily Living in Community-Dwelling older adults: a systematic review. CIA. 2021;16:1877–915.

    Article  Google Scholar 

  21. Aggio DA, Sartini C, Papacosta O, Lennon LT, Ash S, Whincup PH, et al. Cross-sectional associations of objectively measured physical activity and sedentary time with Sarcopenia and sarcopenic obesity in older men. Prev Med. 2016;91:264–72.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Scott D, Johansson J, Gandham A, Ebeling PR, Nordstrom P, Nordstrom A. Associations of accelerometer-determined physical activity and sedentary behavior with Sarcopenia and incident falls over 12 months in community-dwelling Swedish older adults. J Sport Health Sci. 2021;10(5):577–84.

    Article  PubMed  Google Scholar 

  23. Bunout D, Barrera G, de la Maza P, Avendaño M, Gattas V, Petermann M, et al. The impact of nutritional supplementation and resistance training on the health functioning of free-living Chilean elders: results of 18 months of follow-up. J Nutr. 2001;131(9):2441S–6S.

    Article  CAS  PubMed  Google Scholar 

  24. Bonnefoy M, Cornu C, Normand S, Boutitie F, Bugnard F, Rahmani A, et al. The effects of exercise and protein-energy supplements on body composition and muscle function in frail elderly individuals: a long-term controlled randomised study. Br J Nutr. 2003;89(5):731–9.

    Article  CAS  PubMed  Google Scholar 

  25. Suetta C, Andersen JL, Dalgas U, Berget J, Koskinen S, Aagaard P, et al. Resistance training induces qualitative changes in muscle morphology, muscle architecture, and muscle function in elderly postoperative patients. J Appl Physiol (1985). 2008;105(1):180–6.

    Article  PubMed  Google Scholar 

  26. Kemmler W, von Stengel S, Engelke K, Häberle L, Mayhew JL, Kalender WA. Exercise, body composition, and functional ability: a randomized controlled trial. Am J Prev Med. 2010;38(3):279–87.

    Article  PubMed  Google Scholar 

  27. Binder EF, Yarasheski KE, Steger-May K, Sinacore DR, Brown M, Schechtman KB, et al. Effects of Progressive resistance training on body composition in frail older adults: results of a randomized, controlled trial. J Gerontol A Biol Sci Med Sci. 2005;60(11):1425–31.

    Article  PubMed  Google Scholar 

  28. Goodpaster BH, Chomentowski P, Ward BK, Rossi A, Glynn NW, Delmonico MJ, et al. Effects of physical activity on strength and skeletal muscle fat infiltration in older adults: a randomized controlled trial. J Appl Physiol (1985). 2008;105(5):1498–503.

    Article  PubMed  Google Scholar 

  29. Rydwik E, Lammes E, Frändin K, Akner G. Effects of a physical and nutritional intervention program for frail elderly people over age 75. A randomized controlled pilot treatment trial. Aging Clin Exp Res. 2008;20(2):159–70.

    Article  PubMed  Google Scholar 

  30. Senior HE, Henwood TR, Beller EM, Mitchell GK, Keogh JWL. Prevalence and risk factors of Sarcopenia among adults living in nursing homes. Maturitas. 2015;82(4):418–23.

    Article  PubMed  Google Scholar 

  31. Reid N, Keogh JW, Swinton P, Gardiner PA, Henwood TR. The Association of sitting Time with Sarcopenia Status and Physical Performance at Baseline and 18-Month Follow-Up in the residential aged care setting. J Aging Phys Act. 2018;26(3):445–50.

    Article  PubMed  Google Scholar 

  32. Gianoudis J, Bailey CA, Daly RM. Associations between sedentary behaviour and body composition, muscle function and sarcopenia in community-dwelling older adults. Osteoporos Int. 2015;26(2):571–9.

    Article  CAS  PubMed  Google Scholar 

  33. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older people. Age Ageing. 2010;39(4):412–23.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Studenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB, et al. The FNIH Sarcopenia Project: Rationale, Study description, Conference recommendations, and final estimates. The Journals of Gerontology: Series A. 2014;69(5):547–58.

    Google Scholar 

  36. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21(3):300–307e2.

    Article  PubMed  Google Scholar 

  37. Malmstrom TK, Morley JE. SARC-F: a simple questionnaire to rapidly diagnose Sarcopenia. J Am Med Dir Assoc. 2013;14(8):531–2.

    Article  PubMed  Google Scholar 

  38. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K. Chapter 7: Systematic reviews of etiology and risk. In: Aromataris E, Munn Z, editors. JBI Manual for Evidence Synthesis. JBI; 2020. (In: Aromataris E, Munn Z, editors. JBI Manual for Evidence Synthesis).

  39. Li Sjun, Jiang H, Yang H, Chen W, Peng J, Sun M, wei et al. The Dilemma of Heterogeneity Tests in Meta-Analysis: A Challenge from a Simulation Study. Gao JX, editor. PLoS ONE. 2015;10(5):e0127538.

  40. Higgins JPT. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Moola S, Munn Z, Sears K, Sfetcu R, Currie M, Lisy K, et al. Conducting systematic reviews of association (etiology): the Joanna Briggs Institute’s approach. Int J Evid Based Healthc. 2015;13(3):163–9.

    Article  PubMed  Google Scholar 

  42. Ribeiro Santos V, Dias Correa B, De Souza Pereira CG, Alberto Gobbo L. Physical activity decreases the risk of Sarcopenia and Sarcopenic Obesity in older adults with the incidence of clinical factors: 24-Month prospective study. Exp Aging Res. 2020;46(2):166–77.

    Article  PubMed  Google Scholar 

  43. Meier NF, Lee DC. Physical activity and sarcopenia in older adults. Aging Clin Exp Res. 2020;32(9):1675–87.

    Article  PubMed  Google Scholar 

  44. Taani MH, Apchemengich I, Sima CD. Malnutrition-Sarcopenia Syndrome and Self-Management behaviors in Continuing-Care Retirement Community residents. Geriatr (Basel). 2021;7(1):9.

    Article  Google Scholar 

  45. da Silva JRD, Freire IV, Ribeiro ÍJS, Dos Santos CS, Casotti CA, Dos Santos DB, et al. Improving the comprehension of sarcopenic state determinants: an multivariate approach involving hormonal, nutritional, lifestyle and genetic variables. Mech Ageing Dev. 2018;173:21–8.

    Article  PubMed  Google Scholar 

  46. Mo YH, Su YD, Dong X, Zhong J, Yang C, Deng WY, et al. Development and validation of a Nomogram for Predicting Sarcopenia in Community-Dwelling older adults. J Am Med Dir Assoc. 2022;23(5):715–721e5.

    Article  PubMed  Google Scholar 

  47. Tzeng PL, Lin CY, Lai TF, Huang WC, Pien E, Hsueh MC, et al. Daily lifestyle behaviors and risks of Sarcopenia among older adults. Arch Public Health. 2020;78(1):113.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Sinesio Silva Neto L, Gomes de Oliveira Karnikowski M, Barbosa Osório N, Barbosa Mendes M, Galato D, Barbaresco Gomide L et al. Association between Sarcopenia and quality of life in quilombola elderly in Brazil. IJGM. 2016;89.

  49. Escribà-Salvans A, Jerez-Roig J, Molas-Tuneu M, Farrés-Godayol P, Moreno-Martin P, Goutan-Roura E, et al. Sarcopenia and associated factors according to the EWGSOP2 criteria in older people living in nursing homes: a cross-sectional study. BMC Geriatr. 2022;22(1):350.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Batista PP, Perracini MR, Amorim JSCD, Lima MDCCD, Lima CA, Pereira DS, et al. Prevalence risk of Sarcopenia in older Brazilian adults during the pandemic: a cross-sectional analysis of the Remobilize Study. Sao Paulo Med J. 2023;141(4):e2022159.

    Article  Google Scholar 

  51. Yao X. Effects of different levels of physical activity on suffering from Sarcopenia in the elderly dwelling in community. Nurs Res. 2022;36(8):1375–9.

    Google Scholar 

  52. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.

    Article  PubMed  Google Scholar 

  53. Ramsey KA, Rojer AGM, D’Andrea L, Otten RHJ, Heymans MW, Trappenburg MC, et al. The association of objectively measured physical activity and sedentary behavior with skeletal muscle strength and muscle power in older adults: a systematic review and meta-analysis. Ageing Res Rev. 2021;67:101266.

    Article  PubMed  Google Scholar 

  54. Fini NA, Bernhardt J, Holland AE. Low gait speed is associated with low physical activity and high sedentary time following Stroke. Disabil Rehabil. 2021;43(14):2001–8.

    Article  PubMed  Google Scholar 

  55. Middleton A, Fritz SL, Lusardi M. Walking speed: the Functional Vital sign. J Aging Phys Act. 2015;23(2):314–22.

    Article  PubMed  Google Scholar 

  56. Fritz S, Lusardi M. White paper: walking speed: the sixth vital sign. J Geriatr Phys Ther. 2009;32(2):46–9.

    Article  PubMed  Google Scholar 

  57. Gennuso KP, Thraen-Borowski KM, Gangnon RE, Colbert LH. Patterns of sedentary behavior and physical function in older adults. Aging Clin Exp Res. 2016;28(5):943–50.

    Article  PubMed  Google Scholar 

  58. Gennuso KP, Gangnon RE, Matthews CE, Thraen-Borowski KM, Colbert LH. Sedentary behavior, physical activity, and markers of Health in older adults. Med Sci Sports Exerc. 2013;45(8):1493–500.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Kortebein P, Ferrando A, Lombeida J, Wolfe R, Evans WJ. Effect of 10 days of Bed rest on skeletal muscle in healthy older adults. JAMA. 2007;297(16):1769.

    Article  Google Scholar 

  60. Bostock EL. Hypo-activity induced skeletal muscle atrophy and potential nutritional interventions: a review. WJTM. 2013;2(3):36.

    Article  Google Scholar 

  61. Henson J, Yates T, Edwardson CL, Khunti K, Talbot D, Gray LJ, et al. Sedentary time and markers of chronic low-grade inflammation in a high risk population. PLoS ONE. 2013;8(10):e78350.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Bano G, Trevisan C, Carraro S, Solmi M, Luchini C, Stubbs B, et al. Inflammation and sarcopenia: a systematic review and meta-analysis. Maturitas. 2017;96:10–5.

    Article  PubMed  Google Scholar 

  63. de Souto Barreto P, Morley JE, Chodzko-Zajko W, Pitkala H, Weening-Djiksterhuis K, Rodriguez-Mañas E. Recommendations on Physical Activity and Exercise for older adults living in Long-Term Care facilities: a taskforce report. J Am Med Dir Assoc. 2016;17(5):381–92.

    Article  PubMed  Google Scholar 

  64. Peyrusqué E, Buckinx F, Kergoat MJ, Aubertin-Leheudre M. Exercise guidelines to Counteract Physical Deconditioning in Long-Term Care facilities: what to do and how to do it? J Am Med Dir Assoc. 2023;24(5):583–98.

    Article  PubMed  Google Scholar 

  65. Sardinha LB, Santos DA, Silva AM, Baptista F, Owen N. Breaking-up sedentary time is Associated with physical function in older adults. The journals of Gerontology Series A: Biological sciences and Medical sciences. 2015;70(1):119–24.

  66. Bailey DP, Locke CD. Breaking up prolonged sitting with light-intensity walking improves postprandial glycemia, but breaking up sitting with standing does not. J Sci Med Sport. 2015;18(3):294–8.

    Article  PubMed  Google Scholar 

  67. Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, et al. Amount of Time Spent in sedentary behaviors in the United States, 2003–2004. Am J Epidemiol. 2008;167(7):875–81.

    Article  PubMed  Google Scholar 

  68. Davis MG, Fox KR, Hillsdon M, Sharp DJ, Coulson JC, Thompson JL. Objectively measured physical activity in a diverse sample of older Urban UK adults. Med Sci Sports Exerc. 2011;43(4):647–54.

    Article  PubMed  Google Scholar 

  69. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U. Global physical activity levels: surveillance progress, pitfalls, and prospects. The Lancet. 2012;380(9838):247–57.

    Article  Google Scholar 

  70. Parry S, Chow M, Batchelor F, Fary RE. Physical activity and sedentary behaviour in a residential aged care facility. Australas J Ageing. 2019;38(1):E12–8.

    Article  PubMed  Google Scholar 

  71. Chastin SFM, Dontje ML, Skelton DA, Čukić I, Shaw RJ, Gill JMR, et al. Systematic comparative validation of self-report measures of sedentary time against an objective measure of postural sitting (activPAL). Int J Behav Nutr Phys Act. 2018;15(1):21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Sagelv EH, Hopstock LA, Johansson J, Hansen BH, Brage S, Horsch A, et al. Criterion validity of two physical activity and one sedentary time questionnaire against accelerometry in a large cohort of adults and older adults. BMJ Open Sport Exerc Med. 2020;6(1):e000661.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Ohashi K, Ishikawa T, Hoshi A, Suzuki M, Mitobe Y, Yamada E, et al. Relationship between Sarcopenia and both physical activity and lifestyle in patients with Chronic Liver Disease. J Clin Med Res. 2018;10(12):920–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Heesch KC, Hill RL, Aguilar-Farias N, van Uffelen JGZ, Pavey T. Validity of objective methods for measuring sedentary behaviour in older adults: a systematic review. Int J Behav Nutr Phys Act. 2018;15(1):119.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Harvey JA, Chastin SFM, Skelton DA. Prevalence of sedentary behavior in older adults: a systematic review. Int J Environ Res Public Health. 2013;10(12):6645–61.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Cleland C, Ferguson S, Ellis G, Hunter RF. Validity of the International Physical Activity Questionnaire (IPAQ) for assessing moderate-to-vigorous physical activity and sedentary behaviour of older adults in the United Kingdom. BMC Med Res Methodol. 2018;18(1):176.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Dunton GF. Ecological Momentary Assessment in Physical Activity Research. Exerc Sport Sci Rev. 2017;45(1):48–54.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Munir F, Biddle SJH, Davies MJ, Dunstan D, Esliger D, Gray LJ, et al. Stand more AT work (SMArT work): using the behaviour change wheel to develop an intervention to reduce sitting time in the workplace. BMC Public Health. 2018;18(1):319.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Samdal GB, Eide GE, Barth T, Williams G, Meland E. Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses. Int J Behav Nutr Phys Act. 2017;14(1):42.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Baumann S, Groß S, Voigt L, Ullrich A, Weymar F, Schwaneberg T, et al. Pitfalls in accelerometer-based measurement of physical activity: the presence of reactivity in an adult population. Scand J Med Sci Sports. 2018;28(3):1056–63.

    Article  CAS  PubMed  Google Scholar 

  81. Cheng L, Sit JWH, Chan HYL, Choi KC, Cheung RKY, Wong MMH, et al. Sarcopenia risk and associated factors among Chinese community-dwelling older adults living alone. Sci Rep. 2021;11(1):22219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work is supported by King’s College London and China Scholarship Council (K-CSC-202106370016). The views and arguments expressed here are those of the author and do not necessarily represent the official views of King’s College London and China Scholarship Council. Samantha Coster has contributed to the polishing and publication process of this article. We would like to express our appreciation to all contributors and supporters to this work.

Funding

Y. Mo is supported by King’s College London and China Scholarship Council (K-CSC-202106370016). M. Maddocks is supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration South London. The views expressed in this publication are those of the author(s) and not necessarily those of the CSC, NHS, NIHR or the Department of Health and Social Care. There is no role of the funding body in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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  1. Cicely Saunders Institute of Palliative Care, Policy and Rehabilitation, Florence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King’s College London, London, UK

    Yihan Mo, Yuxin Zhou, Catherine Evans & Matthew Maddocks

  2. The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, SAR, China

    Helen Chan

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The study protocol was prepared by YM, MM, CE, and HC. Study selection and data extraction were performed by YM and YZ. Data analysis and interpretation were conducted by YM, MM, YZ, CE. The manuscript was drafted by YM, MM and YZ. Critical revision of the manuscript was performed by MM, CE, HC, YZ and YM. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. All authors read and approved the final manuscript.

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Mo, Y., Zhou, Y., Chan, H. et al. The association between sedentary behaviour and sarcopenia in older adults: a systematic review and meta-analysis. BMC Geriatr 23, 877 (2023). https://doi.org/10.1186/s12877-023-04489-7

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BMC Geriatrics

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