The association between balance and free-living physical activity in an older community-dwelling adult population: a systematic review and meta-analysis

Background Poor balance is associated with an increased risk of falling, disability and death in older populations. To better inform policies and help reduce the human and economic cost of falls, this novel review explores the effects of free-living physical activity on balance in older (50 years and over) healthy community-dwelling adults. Methods Search methods: CENTRAL, Bone, Joint and Muscle Trauma Group Specialised register and CDSR in the Cochrane Library, MEDLINE, EMBASE, CINAHL, PsychINFO, and AMED were searched from inception to 7th June 2016. Selection criteria: Intervention and observational studies investigating the effects of free-living PA on balance in healthy community-dwelling adults (50 years and older). Data extraction and analysis: Thirty studies were eligible for inclusion. Data extraction and risk of bias assessment were independently carried out by two review authors. Due to the variety of outcome measures used in studies, balance outcomes from observational studies were pooled as standardised mean differences or mean difference where appropriate and 95% confidence intervals, and outcomes from RCTs were synthesised using a best evidence approach. Results Limited evidence provided by a small number of RCTs, and evidence from observational studies of moderate methodological quality, suggest that free-living PA of between one and 21 years’ duration improves measures of balance in older healthy community-dwelling adults. Statistical analysis of observational studies found significant effects in favour of more active groups for neuromuscular measures such as gait speed; functionality using Timed Up and Go, Single Leg Stance, and Activities of Balance Confidence Scale; flexibility using the forward reach test; and strength using the isometric knee extension test and ultrasound. A significant effect was also observed for less active groups on a single sensory measure of balance, the knee joint repositioning test. Conclusion There is some evidence that free-living PA is effective in improving balance outcomes in older healthy adults, but future research should include higher quality studies that focus on a consensus of balance measures that are clinically relevant and explore the effects of free-living PA on balance over the longer-term. Electronic supplementary material The online version of this article (10.1186/s12889-018-5265-4) contains supplementary material, which is available to authorized users.


Background
Balance, the ability to stay upright and steady whilst moving or stationary, is a complex skill, that requires the contribution from neuromuscular, cognitive, and sensory body systems [1][2][3]. Good balance is critical for health and well-being in an ageing population. However, whilst many different biological, environmental, socio-economic, and behavioural risk factors have been identified for poor balance [4][5][6][7][8][9][10], the ageing process itself is a key risk factor for poor balance. Through disease or degeneration, ageing results in a decline in systems responsible for balance [11], which increases the risk of falling, injury, loss of independence, illness and even mortality in older adults [8,[12][13][14]. It is estimated that falls affect between 28-35% of those aged 65 years or older, and 32-42% of those aged 70 years or older. Furthermore, the proportion of people aged 60 years or older is growing faster than any other age group and is estimated to reach two billion by 2050, potentially increasing the current human and economic cost of falls by 100% by 2030 [10,15,16]. Thus, fall prevention is a key challenge.
A body of evidence derived from clinical trials suggests that exercise, a sub-category of physical activity (PA) that is structured, planned, repetitive, and carried out over a relatively short time frame (from one month to a maximum of 12 months with the most frequent being three months) as outlined by Gillespie et al. (2012) [8] (159 studies; 79,193 participants) and Howe et al. (2011) [13] (94 studies; 9, 821 participants), can maintain balance in higher risk older adults such as those living in institutional care, women, or those with chronic illness (6,13,14]. It is also proposed that exercise may even reverse the effects of ageing on balance [17]. Exercise recommendations for older adults at higher risk of falls include individually tailored strength and balance exercise programmes such as Tai Chi programmes [10], and guidelines recommend 120-150 min per week of moderately-intensive PA such as aerobic or muscle strengthening exercise [18][19][20].
However, whilst evidence suggests that exercise can benefit unhealthy older adults at higher risk of falling, the effectiveness of less intensive PA, that is not defined as exercise, in healthy older adults who are at lower risk of falling is less well understood, and guidelines are less explicit in terms of PA type, duration, and intensity for this lower risk population [10,20]. Also, statistics suggest that exercise levels in older adults are falling [21,22], and barriers to exercise for them are identified as: fear regarding personal security; lack of time; lack of social support; lack of interest; lack of appropriate facilities; and environmental issues such as the weather [22][23][24].
Therefore, this review sought to investigate the effect of free-living PA on balance in an older, healthy adult population (aged 50 years or older), with the aim of informing policy and programmes designed to reduce the fall rate and increase PA levels in older adults. Free-living PA is defined as leisure activity based on personal interests and needs (walking, hiking, gardening, swimming, sport, and dance), travel activity (cycling or walking), occupational activity (labouring, gardening, heavy lifting), or planned exercise in the context of daily, family, and community activities (walking programmes, swimming clubs, Tai Chi clubs) [25][26][27].

Data sources, searches, and extraction
This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations and the Cochrane Handbook for Systematic Reviews of Interventions [28,29]. To strengthen the methodological approach of the review a protocol was developed a priori using the same guidelines and registered on PROS-PERO (CRD42016039114).
Eight electronic databases were searched for relevant articles published up until June 2016 and included (the Central Register of Controlled Trials (CENTRAL), the Cochrane Database of Systematic Reviews (CDSR), the Cochrane Bone, Joint and Muscle Trauma Group Specialised, MED-LINE, EMBASE, CINAHL, PsycINFO, and AMED). Search terms were related to population (healthy, < 50 yrs); intervention (physical activity; activities of daily living, physical mobility, leisure activities, exercise, walking, travel activity, work activity); and outcome of interest (balance, equilibrium, postural control). Details of the MEDLINE search strategy can be found in Additional file 1. In addition, the National Institute for Health Research library [30] and published research on the longitudinal studies of ageing from the English Longitudinal Study of Ageing (ELSA) [31], and the Irish Longitudinal Study on Ageing (TILDA) [32] were screened. Relevant systematic reviews were also manually screened.
Studies were included if they: 1) used an intervention design, or an observational design, 2) included a form of free-living PA, 3) reported a balance outcome measure [33,34], 4) included a comparison group, 5) included a healthy adult population of 50 years or older, 6) were published in English, 7) were peer-reviewed, and 8) had full text. Excluded were studies including unhealthy older adults with conditions that might impact balance [8]; those studies that met the definition of free-living PA but which took place in a researcher environment or a healthcare facility; and those that included only seated PA [19,35], interventions such as drug therapy or supplements (e.g. vitamin D), or educational or counselling programmes. Details of excluded studies and reasons can be found in Additional file 2.
Using REFWorks (v. 2.0; ProQuest; Mitchigan, US) [36], titles, abstracts and key words were screened independently by two reviewers against the inclusion criteria. The full-text of eligible articles were then screened independently by two reviewers and data extracted using a pre-tested data extraction form [29]. Discrepancies were resolved by consensus or by third party adjudication. Table 1 shows characteristics of included studies.
Risk of bias assessment was carried out independently by two reviewers, trialled with a small number of studies to check for understanding, and disagreements were resolved by consensus or third-party adjudication. The Cochrane Collaboration tool was used to assess the quality of included intervention studies [29] by considering their internal validity and risk of bias. The approach considers studies are low risk of bias where risk is low across all domains or most information was from studies at low risk; unclear risk where risk is unclear across all domains or most information was from studies at unclear risk; and high risk of bias where one or more domains were high risk or the proportion of information from studies at high risk was sufficient to affect the interpretation of the results. Observational studies were assessed using a variation of the Newcastle Ottawa Scale (NOS) [37][38][39][40], and in the absence of formal threshold scores for rating quality [40] studies were rated as high risk of bias if scored four stars or below, and low risk of bias if scored five stars and above (maximum stars possible was ten).

Data synthesis and analysis
Data were grouped by study design [41], by PA type [42] and then according to balance outcome measure (direct or indirect) [13,33]. Where data were available and appropriate as per the guidelines outlined by the Cochrane Handbook for Systematic Reviews of Interventions [29] a statistical analysis was conducted in RevMan [43] where standardised mean values (95% confidence intervals (CI)) for balance outcomes between more active and less active groups were compared. Where studies involved multiple intervention groups and more than one group met the inclusion criteria, PA interventions were only compared to minimal intervention controls to avoid double counting [44], in accordance with Ainsworth et al.'s Compendium of Physical Activities' [45]. Additionally, where studies included groups that compared PA levels by gender or age rather than by 'less' or 'more' PA, then where possible, these groups were combined [29]. Due to the statistical and clinical heterogeneity in the balance measures being combined a random-effects model was used to pool the analyses, and heterogeneity was considered large where p < 0.1, and the I 2 > 50% [29]. Funnel plots that included effect size and standard error were used to examine asymmetry and to assess reporting bias. Post-hoc sensitivity analyses were carried out to assess the possible influence of risk of bias and heterogeneity on the robustness and overall validity of the results where studies were excluded that met high risk of bias criteria (e.g. observational studies with 4 stars or below on NOS; RCTs identified as high risk according to Cochrane's risk of bias tool).
Where insufficient data were available to complete a meta-analysis the data were synthesised qualitatively using a best evidence synthesis advocated by van Tulder et al. [46] where evidence is considered 1) strong; consistent findings in multiple RCTs assessed as having low risk of bias; 2) moderate; consistent findings in one RCT assessed as having low risk of bias, and one or more RCTs assessed as having high risk of bias, or by generally consistent findings in multiple RCTs assessed as having high risk of bias; 3) limited or conflicting evidence; only one RCT (assessed as having either a low or high risk of bias), or inconsistent findings in multiple RCTs; and 4) no available evidence; no published RCTs that have assessed interventional effect.

Results
A total of 2364 articles were identified by the search strategy. From the title, abstract, and keywords, two reviewers independently identified 82 relevant studies for full text review. From the full text review, 52 were excluded resulting in 30 papers being reviewed (n = 1547 participants). The process, including reasons for exclusions, is shown in Fig. 1 [28].
Observational studies Design, sample size, and location Twenty-six studies were observational (one prospective cohort [47], and 25 cross sectional). Sample size ranged from 23 [48] to 170 [47] with an average of 54 participants, but only one study carried out a sample size calculation [49].
There was a lack of demographics in included studies where only one study reported marital status [57], and one study reported ethnicity and education [49].

Balance
Overall, studies included multiple balance measures, except for three that included only one measure [51,59,71].
Secondary outcome measures Three studies used the Sensory Organisational Test (SOT) [48,51,66] (n = 139 participants). Force platforms for the measurement of sway for static or dynamic balance were used in 17 studies (n = 1028 participants) [47-50, 55, 56, 58-62, 64, 65, 67- 69,72]. The ability to maintain balance whilst standing on a tilt board was measured in one study (n = 48 participants) [52]. Table 2 presents a summary table of the risk of bias of included observational studies and shows that in general studies were of moderate quality (n = 14 studies). All studies rated poor in terms of comparability of participants; the majority (n = 14 studies) failed to provide details relating to selection process, but the measures of balance included in studies were validated and stated in the main objective.

Quality
Effects of more PA versus less PA Primary outcomes (indirect measures of balance). Initial analyses included 16 variables (20 studies; n = 1053 participants) ( Table 3). Sensitivity analysis removed five variables (which are excluded from Table 3) due to their high risk of bias (maximal walking speed, functional reach in back, left and right directions, and range of motion), resulting in only 11 variables (13 studies; 733 participants).
Sensitivity analyses showed significant differences between more and less active groups for two variables (preferred walking speed and SLS), which were not identified in initial analyses, but otherwise did not alter findings (Table 3). Table 3 shows that more active groups achieved faster gait speed (SMD 0.66 m/s); better results for two measures of strength using ultra sound tests (SMD 0.57) and isometric knee extension tests (SMD 0.64); better results for three measures of functionality with longer time on SLS test (SMD 1.17s), higher scores on ABC (SMD 1.47), and faster time taken to complete the TUG test (SMD − 0.70s); and better Sensory measures Less active groups achieved statistically significant better results for one sensory measure of balance with better results on knee joint repositioning tests (SMD − 1.37). There was no statistically significant difference between more active and less active groups for neuromuscular measures such as handgrip strength or cognitive measures such as MMSE scores or reaction time.

Neuromuscular measures
Secondary outcomes (direct measures of balance). Twelve variables were included in analyses (14 studies; n = 801 participants) ( Table 4: analyses highlighted*). However, for sensitivity analyses three studies were removed, due to high risk of bias (n = 162 participants) leaving ten variables (11 studies; n = 639 participants) for analysis: significance levels decreased for static body stability eyes open and eyes closed (speed).
More active groups achieved statistically significant better results in three secondary outcome measures, with better tilt board results on directional control (SMD 1.02), and maximum excursion (SMD 1.09) as well as SOT visual ratios (SMD 0.13).
There was no statistically significant difference between more and less active groups for other measures of static or dynamic balance.
Intervention studies Design, sample size, and location Due to the inclusion criteria only four randomised controlled trials (RCTs) were included [49,[73][74][75]. Sample size ranged from 20 [74] to 60 [49] with an average of 38 participants, and only one study [49] justified sample size. Of the four studies, one was US based [49] and the country for the remainder was not specified.

Participants
Participants across all studies were defined as healthy and resided in the community (62% women; mean age = 68.78 years), but there was a lack of more detailed demographic information. Average age of participants was 61-70 years in three studies [49,73,74], and 71 years or over in one study [75].

Physical activity
All studies included a less active group and a more active group, and all PA interventions were land based where two included '3D PA' (n = 109 participants) (Tai Chi) [49,75], and two included 'General PA' (n = 41 participants) (walking) [73,74]. Only one study used a validated PA assessment tool used (e.g. PASS) [49].
Intervention duration ranged from a minimum of three months [73,74] to a maximum of six months [49,75]. All four provided results at baseline and post-trial commencement, at three months [73], at four months [74], at both two and six months [75], and at both three and six months [49].

Balance
All studies included a neuromuscular balance measure, but only one included a measure of the cognitive system (MMSE) [49], and none included any sensory system measures.
Secondary outcome measures.
One study used the SOT [75], and three used force plate platforms [49,73,74]. Figure 2 presents a summary table of the risk of bias of included intervention studies, and shows a high risk of bias for all studies.

Effects of more PA versus less PA
Due to the limited number of studies and lack of common outcomes, a best evidence synthesis was explored [46].

Key findings relating to direct measures of balance
Two studies reported direct measures [49,73], but only one study provided these measures post-intervention measuring neuromuscular system health using gait speed only [73],and found that walking improved gait speed in more active groups. However, the study was at high risk of bias [29] and of low methodological quality (level 3) [46] and so provides limited evidence. Key findings relating to secondary measures of balance All four studies reported secondary measures of balance (e.g. SOT vestibular, BoS, and static and dynamic balance), and found that intervention groups had better balance scores. However, all studies were at high risk of bias [29] and of low methodological quality [46], and so evidence is again limited.
Key findings overall There is limited evidence that freeliving PA improves measures of balance in older healthy community-dwelling adults.

Subgroup analyses
The heterogeneity in the nature of the outcome data relating to age, type of PA and duration of effect meant that it was not possible to explore the effects of PA in relation to these variables.

Discussion
This review explored the role of free-living PA in relation to balance outcomes across multiple body systems, and summarises two types of evidence. The majority of evidence was from cross sectional studies (26 studies) of moderate methodological quality, and a much smaller number was from RCTs (four studies) of low methodological quality. The evidence from cross sectional studies found that free-living PA [25][26][27] is beneficial for balance in older healthy community-dwelling adults (50 years and over), where more active groups experienced better performance on indirect measures of gait speed, strength, functionality and flexibility, and on direct measures of directional control, maximum excursion and SOT visual ratios. These findings extend the results from a previous longitudinal research exploring PA and physical performance by Cooper et al., that found that leisure-time PA carried out over the longer-term (17 years) can improve neuromuscular measures of strength in middle-aged adults (36-53 yrs) [76]. Additionally, evidence from the limited number of RCTs suggests that free-living PA improves measures of balance in the short-term (three-six months) in older healthy community-dwelling adults which extends the findings from previous research, that short-term (three-six months) exercise, a sub-category of PA, improves balance performance in older unhealthy adults [8,13].
It is evident from this study that few RCTs have explored free-living PA and balance and that most evidence has been derived from observational studies, thus potentially providing insufficient clinical trial data on which to base clear conclusions. However, research suggests that the effects of free-living PA require a longer duration of study than that afforded by RCTs [77]. This review included observational studies that explored free-living PA of between one and 21 years' duration. In contrast, Howe et al.'s [13] systematic review of RCTs found no evidence that free-living PA such as walking or cycling, of up to 6 months' duration, improved measures of balance in older unhealthy adults. Thus, the benefits realised from free-living PA may be cumulative over time, and future research should consider the appropriateness of the study design involved in exploring associations between free-living PA and balance.
A strength of this review is that it considers balance as a multidimensional construct [1,3] rather than a single system, and as a result, includes measures across neuromuscular, cognitive and sensory body systems, thus measures balance holistically. However, it is evident that whilst this review sought to include measures from multiple body systems, the majority of studies focused on neuromuscular measures (19 of 30 studies) and a smaller number included cognitive (ten) measures, and even less included sensory measures (three). Additionally, this study found no effect for cognitive measures relating to PA level, and this may be due to the inclusion of healthy older adults in the present study. As a result, future studies should seek to include measures across all the body systems required for balance, and include unhealthy adults.
Studies in the review reported validated measures for both balance and PA. Whilst most measures of PA were subjective, except for those in one study [47], the balance measures included were mainly objective, thus reducing any measurement bias due to self-reporting and or recall bias in the results [78].
There are some limitations to be taken into account when considering these findings. For example, sample size for both cross-sectional studies and RCTs were small ranging from 20 to 170 participants, and only justified by a power calculation in one study [49] which may give rise to Type II errors. Additionally, the observational studies included were cross sectional studies and therefore no causal relationship between free-living PA and balance can be determined. Also, participants were either volunteers or recruited using convenience sampling, therefore the generalisability of the findings is limited. In addition, whilst this review included multiple balance measures across different body systems, the number of different outcome measures (n = 40) restricted the ability to compare and pool results, and therefore future research in this emerging area should consider establishing a consensus of relevant balance measures across all body systems to aid analysis and fully understand the effects of free-living PA on balance.
In summary, this review suggests that free-living PA improves balance performance in older healthy adults both in the short-term and long-term using validated and objective measures across multiple body systems. Further research that incorporates higher quality studies is warranted, with the inclusion of longitudinal studies that provide large samples of participants using robust selection processes, and appropriate data over multiple time points. For example, studies such as NICOLA (Northern Ireland Cohort of Longitudinal Ageing) [79], TILDA (The Irish Longitudinal Study of Ageing) [32], and ELSA (English Longitudinal Study of Ageing) [31] include large samples of communitydwelling participants (50 years and over) (8500, 8504 and 11, 391 respectively); provide data across multiple timepoints (between three and 11 years); adhere to the Gateway to Global Ageing Initiative [80] which improves the harmonisation of balance outcomes, therefore reducing the variability of outcomes and improving comparability of results; and include balance measures across multiple body systems that are objective and validated.

Conclusion
In conclusion, there is limited evidence from a small number of RCTs, and moderate quality of evidence from observational studies that suggests that free-living PA improves measures of balance in older communitydwelling healthy adults, particularly in respect of fall prevention. Future research should consider longitudinal studies of good methodological quality to improve the overall robustness of the findings.