Örebro University
School of Health Sciences
Master program: Sports Physiology and Medicine, 120 credits Degree project, 45 credits, spring 2018
Past and present physical activity are independently associated to physical
function in elderly women
Table of Contents
Abstract ... 3
Introduction ... 4
Physical activity and sedentary behavior ... 4
Physical function in the aging population ... 5
PA and sedentary behavior in relation to physical function ... 6
Material and methods ... 8
Study design ... 8
Subjects and ethical consideration ... 8
Body composition ... 8
PA and sedentary behavior ... 9
History of physical activity ... 9
Physical function ... 9
Aerobic capacity ... 9
Maximal isometric leg strength ... 10
Maximal isometric arm strength ... 10
Scores of physical function ... 11
Statistical analysis ... 11
Results ... 11
Influence of present PA on physical function ... 12
Influence of past habitual physical activity on physical function ... 15
Discussion ... 16
Accelerometer-based objective assessment of present PA... 16
Self-reported past PA ... 20
Strengths and limitations ... 21
Societal implications ... 22
Conclusion ... 23
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Abstract
INTRODUCTION:
Physical function is an important predictor for health and all-cause mortality. Physical function is also known to decline as part of the aging process and may eventually lead to loss of independency. Both present and past physical activity (PA) habits as well as sedentary behavior are associated to physical function in elderly. It has however not been examined whether present and past PA may be associated to physical function independent of the other.
MATERIAL AND METHODS:
122 healthy community-dwelling older women (aged 65-70 years) were recruited for participation. Assessment of PA was performed by both accelerometry and self-report, body composition by bioelectrical impedance analysis, and physical function by strength and aerobic capacity testing. Analysis of variance (ANOVA) was used to investigate differences in physical function across tertiles of past and present PA habits adjusted by level of adiposity.
RESULTS:
Subjects in the highest PA tertile had higher aerobic capacity and higher combined aerobic capacity and leg strength compared to those in the lowest PA tertile, independent of adiposity and past PA habits (p < 0.05). Same results were evident for time spent in moderate- to vigorous physical activity (MVPA). Furthermore, subjects belonging to the highest tertile of past sports and
recreational exercise throughout adulthood had higher aerobic capacity, independent of present PA level and adiposity, compared to those belonging to the lowest tertile (p < 0.05). Additionally, physical function did not differ across tertiles of time spent in light physical activity (LPA) and time spent in sedentary behavior (p > 0.05).
CONCLUSION:
Both objectively assessed present and self-reported past PA habits are independently associated to physical function in older women, regardless of adiposity. Being physically active in adulthood may be beneficial for sustaining physical function in older years, regardless of present activity level.
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Introduction
Physical activity and sedentary behavior
Physical activity (PA) is an important factor for health across the lifespan (1). Health benefits of PA among elderly are numerous and include a more favorable body composition with a higher lean mass and lower fat mass, a higher bone mineral density and an improved cardiovascular profile. In addition, participating in PA increases average life expectancy and attenuates development of disability (2). Current recommendations for PA in elderly is 150 minutes of moderate- to vigorous physical activity (MVPA) per week (1). Physical inactivity, defined as not meeting the current recommendations, has been estimated to cause between 6–10% of the major non-communicable diseases such as coronary heart disease, type II diabetes and different types of cancer worldwide (3). A low PA level has also been associated with frailty and low aerobic fitness in elderly (4). In addition, a recent review suggests that lack of PA is an undervalued contributing cause to most chronic diseases and conditions, as well as being able to speed biological aging (5).
PA is a complex construct which has no gold standard method of measurement. This is due to no currently available method being able to capture all its aspects such as intensity, duration and perceived exertion across all types of free-living activities. Strategies to assess PA are therefore plenty and include common subjective methods such as self-report questionnaires, activity diaries and interviews. Objective measures of PA include the usage of accelerometers, pedometers or heart rate monitors as well as calculating PA level by energy expenditure (6). Studies in recent years have emphasized the importance of using objective measures of habitual PA when possible in order to minimize faulty activity tracking due to recall bias and bias to match socially desired traits (6–9). Habitual PA level decreases with age and substantial decreases in PA level are reported to occur after around midlife (10). With increasing age, a shift towards lighter intensities of PA is also evident. This is manifested by older adults spending more time in activities of a less physically demanding nature as compared to younger adults (11). In addition to this, the amount of daily MVPA has been reported to continue to decrease with aging, even in older subjects (12). While actual PA level among the general older population is difficult to fully elucidate due to its complex construct, it has repeatedly been reported that elderly women tend to be less physically active compared to their male counterparts (13,14).
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Situated at the lowest end of the PA spectrum is another distinct construct, namely sedentary behavior. Sedentary behavior can be defined as any waking activity performed in a sitting or reclined position that requires an energy expenditure between 1.0–1.5 metabolic equivalent of task (MET) (15). Sedentary behavior has been associated with mortality in older adults (16) and
independently associated with clustered cardio-metabolic risk in adults with risk of diabetes type II (17). Sedentary behavior has furthermore been strongly related to metabolic syndrome independent of PA in older subjects (18). In contrary, there are reports questioning the independency of
sedentary behavior, suggesting that increasing PA rather than decreasing sedentary time should be the main focus for health (19,20).
Physical function in the aging population
Although there is no common definition of physical function, the term may be used to explain an individual’s capacity to perform physical tasks of various demands such as climbing stairs, walking and carrying load (21). Physical function is commonly assessed objectively using validated
functional tests that simultaneously measure multiple components of physical function such as balance, strength and mobility (22–24). However, physical function can also be assessed through direct strength testing and by the use of cardiorespiratory fitness tests (25–27). For elderly
populations, physical function is considered an important marker for present and future health as it has been associated with health-related quality of life, frailty, disability and all-cause mortality (4,28–31).
In parallel to being a highly important marker for health in older adults, physical function is also known to decline with age as part of the natural aging process. By using various measures of physical function it has been estimated that older adults between the ages of 60–83 experience an annual loss of around 0.9–3 % in functional capacity (32). Additionally, the decline in physical function is by certain measures seemingly accelerating with increased age (33,34). Higher rates of decline in physical function have further been related to increased risk of all-cause mortality and disability later in life (35). Additionally, older women may be a particularly vulnerable group as they are consistently performing worse compared to men in multiple tests of physical function, and may thus be closer to the threshold of losing independence (36).
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PA and sedentary behavior in relation to physical function
Associations between PA and physical function have been investigated for at least two decades in elderly. Most earlier research have however assessed habitual PA solely through questionnaires, and physical function has in many cases been assessed through self-report measures (37). This possibly limits detection of true relationships between the two as the risk of receiving unreliable data is elevated (38,39).
Studies investigating objectively measured PA in elderly have reported positive associations of MVPA and a large variety of objective measures of physical function including gait speed (26,40– 42), grip strength (42), elbow flexor strength and knee extensor strength (43), one-legged stance (40), aerobic capacity (27,44) as well as a large number of functional tests (23,40–47).
Associations of PA and physical function have though not always been consistent. Gerdhem et al. (2008) reported a significant relationship between accelerometer-measured MVPA and gait speed in elderly women, but no association between MVPA and isometric knee flexion/extension as well as one-legged stance (26). In addition, van der Velde et al. (2017b) reported positive associations between PA and isometric elbow flexion and knee extension in adults and elderly, while no associations were found for grip strength (43).
At lower intensities of PA such as <3 MET, typically named light physical activity (LPA), further discrepancies are found. LPA has been associated with performance in functional tests involving leg strength and gait in elderly, although only in elderly above 75 years of age (24). Furthermore, Jantunen et al. (2017) and van der Velde et al. (2017a) reported positive associations between LPA and the Senior Fitness Test (SFT) as well as cardiorespiratory fitness, although with associations being independent of age (27,45). Interestingly, Izawa et al. (2017) confirmed the associations between LPA and Timed Up and Go (TUG) as well as gait speed in elderly women. These associations were however not evident in older men (40).
Similar to PA, objectively measured sedentary behavior has negatively been associated with physical function in elderly based on a combined score of physical function, with a strength of the association comparable to at least that of MVPA (47). In addition, sedentary behavior has in recent reports been associated to gait speed, grip strength, elbow flexor strength as well as
cardiorespiratory fitness, although to a lesser extent compared to MVPA (27,43). Furthermore, when controlling for PA there are reports questioning the true independency of sedentary behavior
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and argue the negative relationship to physical function in elderly may rather be due to lack of PA (42,46).
A vast majority of previous studies in older adults with objectively measured PA and physical function have solely accounted for body mass index (BMI) as a variable of body composition. While BMI may provide valuable information regarding subject characteristics, it may not be optimal for the purpose of a confounder for physical function. This is because BMI is based on total body mass, which in turn is contributed to by both fat and fat-free mass, each with a distinct
association to physical function (48). Furthermore, aging is commonly accompanied by an increase in fat mass and a decrease in muscle mass, heavily shifting body composition while weight and thus BMI may be kept constant (49,50). This may in turn mask the true effect of body composition when assessing PA in relation to physical function. A more appropriate measure of body composition may therefore be relative adiposity, which previously has shown to be a strong predictor of physical function in older adults (41,51).
Another scarcely investigated aspect to address is the potential influence of past PA habits on present physical function. It has previously been reported that PA habits throughout adulthood are associated with present physical function in old age for both men and women (52–54). It has however not been investigated whether the potential effects past PA habits on physical function are independent of present PA level in elderly.
In this context, no study has to the author’s knowledge investigated objective PA and sedentary behavior in relation to physical function, considering both specific measures of body composition as well as past PA habits. The aims of this study were therefore firstly to investigate the potential influence of objectively measured PA and sedentary behavior on various objective measures of physical function in elderly women. A second aim was to examine whether the potential influences of PA and sedentary behavior on physical function are independent of adiposity and past PA habits in adulthood. Lastly, a third aim was also to assess whether past PA habits may have an influence on present physical function in elderly women, regardless of current PA levels and adiposity.
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Material and methods
Study design
A cross-sectional study design was applied to address the study aims. PA was measured during a consecutive period of one week and all individual tests of physical function were conducted during the same day. To be included, participants had to be free of overt disease and aged between 65 and 70 years.
Subjects and ethical consideration
A total of 122 community-dwelling elderly women aged 65–70 were recruited through
advertisement in a local newspaper. All participants were living in an urban area in Sweden, were non-smokers, had no mobility disability and had not previously been diagnosed with coronary heart disease or diabetes mellitus. All procedures were performed according to principles set by the Declaration of Helsinki. Subjects were informed about the study background, insurance policy, responsible researchers, aims, test procedures, potential risks and benefits of participation, expected time-frame and how study results could be accessed after completion. All subjects were further informed about participation being voluntary and were acknowledged the possibility to withdraw from participation at any time. In order to ensure confidentiality, identities were coded and all data were stored on servers inaccessible to unauthorized personnel. A written informed consent was obtained from all subjects before participation. The study was approved by the regional ethics committee in Uppsala, Sweden.
Body composition
Height was assessed to the nearest 0.5 cm using a portable stadiometer with subjects being barefoot and standing upright. Weight was assessed to the nearest 0.1 kg using a digital scale with subjects wearing minimal clothing. Assessment of relative fat mass and muscle mass was conducted using bioelectrical impedance analysis (BIA) (TANITA BC-420MA, Tanita Corporation, Tokyo, Japan). All measurements were performed between 07:00–09:00 in the morning after an overnight fast.
9 PA and sedentary behavior
Physical activity and sedentary behavior were assessed using triaxial accelerometry (ActiGraph GT3x, Florida, USA) in epochs of 15 seconds. The accelerometer was placed on the right hip, fastened with an adjustable elastic band and worn consecutively for one week. Subjects were instructed to wear the monitor during all waking hours, with the exception of water activities, and note any event and time when the monitor was removed and re-applied. A minimum wear time of 4 days with at least 10 hours each day was required for inclusion. Sedentary behavior was defined as <100 counts per minute (CPM), LPA as 100–2020 CPM and MVPA as >2020 CPM in concordance with previous work (46,47,55). Accelerometer counts of >20,000 CPM were discarded as human movements and periods of 60 minutes of consecutive zero values was considered as non-wear time. All accelerometer-data are presented in Table 1.
History of physical activity
In order to assess past physical activity habits, the interview-based Historical Adulthood Physical Activity Questionnaire (HAPAQ) was used (56). Briefly, subjects were first asked a series of questions regarding specific life events and habits during a certain time period in order to facilitate remembrance. Subjects were then asked to estimate the time spent being physically active during the past 15 years based on a large variety of physical activity tasks. Subsequently, the same
questions were repeated using time periods of 10 years at the time, starting from the age of 20. Each physical activity task was assigned a MET-value and the total amount of MET-minutes was
calculated for the specific time period. Past physical activity was then divided into three blocks reflecting physical activity level in young adulthood (20–50 years), old adulthood (50–65 years) and throughout the entire adulthood. In addition, time spent walking was separated from all other types of sporting and recreational exercise in order to distinguish the potential influence of sports-related activities on physical function from that of walking.
Physical function Aerobic capacity
Maximal oxygen uptake (VO2max) was estimated using the submaximal Åstrand cycle test adjusted
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874E, Monark Exercise AB, Vansbro, Sweden) and followed standard guidelines (58). Briefly, after initial load was set, subjects pedaled at 50 revolutions per minute for 6–12 minutes. Load was adjusted if needed to ensure subjects reaching a steady-state heart rate of at least 120 beats per minute within the given time frame. Heart rate was measured by a heart rate monitor (Polar RS400, Polar Electro Oy, Kempele, Finland) and estimated VO2max was calculated by applying the
steady-state heart rate value to the adjusted Åstrand nomogram (57).
Maximal isometric leg strength
Maximal isometric strength of the knee extensors was measured unilaterally on the dominant leg using a force sensor (K. TOYO 333A, KTOYO co., Ltd, Uijeongbu-si, South Korea). Subjects were positioned sitting upright in an adjustable chair at a hip and knee angle of 90°. Restraining straps across the torso and pelvis were used to ensure stability and minimize initial countermovement. The force sensor was attached above the malleoli at one third of the distance between the lateral
malleolus and the lateral femoral epicondyle. Participants were instructed to perform a maximal isometric contraction as quickly as possible and maintain the contraction for 3–5 seconds while provided strong verbal encouragement. Each subject performed 3 trials separated by 2.5 minutes of rest.
Maximal isometric arm strength
Maximal isometric strength of the elbow flexors was measured on the dominant side using the same force sensor. Subjects remained seated upright and fastened with straps. The arm was positioned at 90° elbow flexion and palms were facing upwards with a closed fist. The force sensor was attached at one fourth of the distance between the radial styloid process and the lateral epicondyle. Subjects were asked to perform a maximal isometric elbow flexion as quickly as possible and maintain maximal tension for at least 3 seconds. A total of 3 trials was performed with a rest period of 2.5 minutes between each trial. Strong verbal encouragement was provided throughout testing.
11 Scores of physical function
Physical function scores were derived by standardizing (z-scores) the results obtained in all physical function tests. A composite z-score weighing results from different physical function tests was obtained by averaging z-scores. Three composite z-scores were created; one for combined aerobic capacity and maximal isometric leg strength (z-scoreaerobicleg), one for combined maximal isometric
leg and arm strength (z-scorestrength) and one score for a combined measure of all physical tests
(z-scoretotal). The use composite z-scores has been reported in previous literature and may be a more
comprehensive measure of all-round physical function (46,47).
Statistical analysis
Normality was checked using Shapiro-Wilk’s normality test and skewed dependent variables were transformed if necessary to fit a normal distribution. Factorial analysis of variance (ANOVA) was used to investigate differences in physical function across tertiles of present PA and past PA behaviors. When analyzing influence of present PA, adjustment for amount of past PA habits was made. When analyzing influence of past PA, adjustment for amount of present PA habits was made. Results were also adjusted by level of adiposity. When significant main effects were observed across tertiles, the Holm-Sidak post-hoc procedure was further employed to determine between-tertile effects. Homoscedasticity was checked using Levene’s test in order to ensure that
assumptions for the analyses were met. All accelerometer-data were analyzed in relation to total wear time and all measures of physical function were analyzed in relation to body weight. A priori power analysis performed in G*Power version 3.1.9.2 (59) revealed that at least 99 subjects were required in order to detect a medium size effect (0.3), with an alpha level set at 0.05 and a power of 0.8. All statistical analyses were performed in IBM SPSS Statistics for Windows version 24.0 (IBM Corp., New York, USA). Data are presented as mean ± standard deviation (SD).
Results
Subject characteristics are presented in Table 1. Three subjects were excluded due to incomplete accelerometer-data. Remaining subjects wore the accelerometer for 5.8 ± 0.5 days with an average daily wear time of 14.2 ± 1.0 hours. 117 subjects had complete data for objective physical activity,
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strength measurements, body composition and HAPAQ. 107 subjects had complete data for aerobic capacity. Values for maximal isometric arm strength were transformed and an outlier was removed from z-scoreaerobicleg in order to fit a normal distribution.
Table 1. Subject characteristics (mean ± SD). n = 119.
Age (years) 67.5 ± 1.7
Weight (kg) 68.7 ± 11.3
Height (m) 1.65 ± 5.69
Body mass index (kg/m2) 25.6 ± 4.7
Body fat (%) 36.2 ± 6.2
Skeletal muscle mass (%) 30.6 ± 4.0
VO2max (ml/kg/min)# 28.11 ± 7.28
Maximal isometric arm strength (N/kg) 1.47 ± 0.48
Maximal isometric leg strength (N/kg) 2.68 ± 0.69
CPM (average daily counts/min) 313.2 ± 117.1
Time in MVPA (min) 37.79 ± 23.7
Time in LPA (min) 224.8 ± 51.5
Time in sedentary behavior (min) 587.3 ± 70.4
SD; standard deviation, VO2max; maximal oxygen uptake, CPM; counts per minute, MVPA;
moderate- to vigorous physical activity, LPA; light physical activity, #; n = 107.
Influence of present PA on physical function
There was a main effect of present PA level on VO2max (p = 0.001), z-scoreaerobicleg (p = 0.001) and
z-scoretotal (p = 0.005). Among these variables, subjects in the third tertile of PA had significantly
higher physical function compared to those in the least physically active tertile. The main effect of present PA remained significant on VO2max and z-scoreaerobicleg but was no longer present on
z-scoretotal after adjustment for age, body composition and past physical activity habits (Table 2). In
addition, there was no significant main effect of present PA on maximal isometric arm and leg strength (p = 0.77 and 0.21, respectively) and z-scorestrength (p = 0.32).
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Table 2. Mean (95% CI) differences in physical function between tertiles of PA (CPM) expressed
in relation to tertile 1. n = 104–119. VO2max (ml/kg/min) z-scoreaerobicleg (z-score) z-scoretotal (z-score) Modela T1 (low) 0 0 0 T2 2.39 (-1.48–6.27) 0.19 (-0.15–0.53) 0.11 (-0.24–0.46) T3 (high) 4.74* (0.66–8.81) 0.40* (0.04–0.76) 0.28 (-0.09–0.65) Modelb T1 (low) 0 0 0 T2 2.47 (-1.55–6.48) 0.23§ (-0.11–0.56) 0.11 (-0.25–0.47) T3 (high) 4.91* (0.71–9.11) 0.44* (0.08–0.80) 0.30 (-0.08–0.67) Modelc T1 (low) 0 0 0 T2 2.00 (-1.84–5.83) 0.18 (-0.17–0.53) 0.09 (-0.28–0.45) T3 (high) 4.25* (0.28–8.23) 0.39* (0.02–0.75) 0.28 (-0.10–0.65)
CPM; counts per minute, T; tertile, VO2max; predicted maximal oxygen uptake, z-scoreaerobicleg;
composite z-score of VO2max and isometric leg strength, z-scoretotal; composite z-score of all
physical function variables. *p < 0.05.
aAdjusted for age and fat%.
bAdjusted for age, fat% and walking activities throughout adulthood.
cAdjusted for age, fat% and sports and recreational exercise throughout adulthood.
Similarly to CPM, MVPA demonstrated a main effect on VO2max (p = 0.005), z-scoreaerobicleg (p =
0.001) and z-scoretotal (p = 0.01), with higher physical function among participants spending most
time in MVPA (highest tertile) compared to those spending the least amount of time in MVPA (lowest tertile). After adjusting for age, body composition and past physical activity habits the main effect of MVPA remained on VO2max and z-scoreaerobicleg, but not on z-scoretotal (Table 3). Likewise,
there was no main effect of MVPA on maximal isometric arm and leg strength (p = 0.75 and 0.08, respectively) and z-scorestrength (p = 0.31). There was no main effect of LPA on neither physical
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Table 3. Mean (95% CI) differences in physical function between tertiles of MVPA expressed in
relation to tertile 1. n = 104–119. VO2max (ml/kg/min) z-scoreaerobicleg (z-score) z-scoretotal (z-score) Modela T1 (low) 0 0 0 T2 0.33 (-3.52–4.17) 0.12 (-0.22–0.46) 0.05 (-0.30–0.40) T3 (high) 4.25* (0.21–8.29) 0.38* (0.02–0.73) 0.25 (-0.11–0.62) Modelb T1 (low) 0 0 0 T2 0.50 (-3.49–4.49) 0.14 (-0.21–0.48) 0.08 (-0.29–0.43) T3 (high) 4.72* (0.41–9.02) 0.40* (0.03–0.77) 0.26 (-0.13–0.65) Modelc T1 (low) 0 0 0 T2 0.96 (-2.86–4.78) 0.14 (-0.21–0.49) 0.07 (-0.30–0.43) T3 (high) 4.28* (0.29–8.27) 0.38* (0.01–0.75) 0.27 (-0.11–0.65)
MVPA; moderate- to vigorous physical activity, T; tertile, VO2max; predicted maximal oxygen
uptake, z-scoreaerobicleg; composite z-score of VO2max and isometric leg strength, z-scoretotal;
composite z-score of all physical function variables. *p < 0.05.
aAdjusted for age and fat%.
bAdjusted for age, fat% and walking activities throughout adulthood.
cAdjusted for age, fat% and sports and recreational exercise throughout adulthood.
For sedentary behavior, a main effect was detected on VO2max, with participants demonstrating
significantly higher aerobic capacity in the lowest tertile and middle tertile compared to the most sedentary tertile (p = 0.025 and 0.007, respectively). There was also a main effect of sedentary behavior on z-scoreaerobicleg (p = 0.042), with a statistical difference between the lowest and highest
tertile, explaining that subjects spending the least amount of time in sedentary behavior had significantly higher physical function compared to the most sedentary tertile. The main effect of sedentary behavior on VO2max remained significant after adjusting for age, body composition and
past walking activities, but not when replacing past walking activities with past sports and
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adjusting for either past physical activity habit or age and body composition (Table 4). Furthermore, there was no main effect of sedentary behavior on maximal isometric arm and leg strength (p = 0.72 and 0.37, respectively), z-scorestrength (p = 0.55) and z-scoretotal (p = 0.08).
Influence of past habitual physical activity on physical function
For past sports and recreational exercise throughout adulthood, there was a main effect on VO2max
which was independent of present physical activity, age and body composition, where subjects who reported most past habitual sports and recreational exercise (highest tertile) demonstrated a higher aerobic capacity compared to those reporting the least (lowest tertile) (p < 0.05). No other
significant main effect of past sports and recreational exercise was detected. Similar results were obtained when examining past sports and recreational exercise divided into different age categories (between 20–50 years and 50–65 years).
Past walking activities through adulthood demonstrated a main effect on z-scoreaerobicleg
independently of age, body composition and CPM or MVPA (p < 0.05), but not independent of LPA or sedentary behavior (p > 0.05). In contrast, no main effect of past walking activities was detected when exploring age categories 20–50 years and 50–65 years.
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Table 4. Mean (95% CI) differences in physical function between tertiles of sedentary behavior
expressed in relation to tertile 1. n = 104–119. VO2max (ml/kg/min) z-scoreaerobicleg (z-score) z-scoretotal (z-score) Modela T1 (low) 0 0 0 T2 1.65 (-2.32–5.62) -0.02 (-0.37–0.34) 0.01 (-0.35–0.38) T3 (high) -2.96† (-6.92–1.01) -0.26 (-0.62–0.10) -0.18 (-0.55–0.18) Modelb T1 (low) 0 0 0 T2 1.63 (-2.53–5.79) -0.05 (-0.42–0.31) -0.01 (-0.38–0.37) T3 (high) -2.98† (-7.10–1.14) -0.29 (-0.65–0.07) -0.20 (-0.57–0.18) Modelc T1 (low) 0 0 0 T2 1.60 (-2.37–5.57) -0.03 (-0.40–0.35) 0.00 (-0.38–0.38) T3 (high) -2.24 (-6.22–1.74) -0.25 (-0.62–0.12) -0.17 (-0.55–0.21)
T; tertile, VO2max; predicted maximal oxygen uptake, z-scoreaerobicleg; composite z-score of VO2max
and isometric leg strength, z-scoretotal; composite z-score of all physical function variables.
†significant from ‘T2’ p < 0.05.
aAdjusted for age and fat%.
bAdjusted for age, fat% and walking activities throughout adulthood.
cAdjusted for age, fat% and sports and recreational exercise throughout adulthood.
Discussion
Accelerometer-based objective assessment of present PA
This study in older community-dwelling women supports the association between objectively measured PA and physical function, and provides an extended and novel support for these associations by controlling for important confounding factors. Among all PA subcategories, total present PA level and time spent in MVPA were most associated to physical function, demonstrating main effects on both aerobic capacity and the combined score of aerobic capacity and isometric leg strengthacross all models (Table 2–3). It is Important to notice that all models were included for interpretation although one model including total present PA level did not pass the assumption of
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homoscedasticity. This model was however included based on results highly similar to those in the remaining models, leading to the belief that the actual effect of total present PA was not affected to a major extent by having somewhat heteroscedastic groups in that particular model.
After adjusting for confounders, differences in physical function between tertiles of present PA level were solely detected for aerobic capacity and the z-score consisting of both aerobic capacity and isometric leg strength. This is opposed to a previously reported study in middle-aged to older adults reporting significant associations between objectively measured physical activity and both isometric elbow flexor strength as well as and isometric knee extensor strength (43). Possible reasons for the discrepancies may be the use of step-frequency instead of accelerometer-counts for PA assessment and a different statistical approach in which more specific body composition measures, such as relative adiposity, were not included in the aforementioned study. Additional possible factors may be that in the study by van der Velde et al. (2017b), a large amount of participants were used, enabling detection of very small effect sizes, as well as that the
aforementioned study included a less homogeneous population, particularly in terms of leg strength (43). In contrast, Leblanc et al. (2015) did not find any associations between objectively measured PA and isometric elbow flexor strength in adults between the ages of 20–91 years. This was
explained by the authors as possibly being due to using hip-worn accelerometers, which may not be as sensitive in tracking PA primarily involving upper-body movement (60). This argument could also be applied to the present study as it is reasonable to believe that upper-body PA, such as lifting and using objects during e.g. gardening activities may be associated to upper-body strength. It is furthermore expected that PA measured in elderly would be more strongly associated to lower-limb function and aerobic capacity as PA primarily involving these two components, such as walking, is the primary type of PA practiced among older adults (61).
Quite surprisingly, even prior to adjusting for confounding factors, neither strength measure did statistically differ among groups of present PA. This was somewhat unexpected for maximal isometric knee extension, as objectively measured PA previously has been related to other strength-involving functional measures of the lower extremities in older adults (23,41,42,45). A trend was though evident among groups of MVPA for isometric knee extensor strength, which possibly could have been detected statistically with a slightly larger sample size. These results are however similar to those reported by Gerdhem et al. (2008) who did not detect any association between PA and
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isometric leg strength in a sample of 80-year-old women, despite not adjusting for any confounding factors (26). Additional studies in older adults have reported equivocal results depending on type of lower extremity strength measure used (e.g. isometric strength, isokinetic peak torque,
one-repetition maximum or peak power) (25,44), leading to the conclusion that the relationship between PA and strength-related measures may vary and has yet to be fully elucidated in elderly.
Furthermore, based on the well-documented effect of resistance exercise on muscle strength and power (62,63), it is possible that these types of activities performed by the participants in the present study may not have been sufficiently tracked by the accelerometer, thus leading to limited possibilities to detect an effect.
Contrary to total present PA level and MVPA, LPA demonstrated no main effect on any of the physical function variables, even without adjusting for confounding factors, implying that PA at higher intensities may be the decisive factor for the association to physical function in older women. This is both similar to and opposing to previously reported objective studies in similar populations. In one of the studies that did find significant associations between LPA and physical function, the Senior Fitness Test (SFT) was used for physical assessment, involving several aspects of physical function including mobility, strength, gait and balance (45). In this study, LPA (defined as 1.5-3 MET) was positively associated to the total score gained from the test battery, which in turn was predominantly affected by the gait component. As walking is the most common type of PA in elderly (61), it not surprising that a measure of physical function heavily depending on gait performance was associated to LPA. In addition to this, the aforementioned study was based on a much larger sample size (n = 695) compared to the present study which enables detection of smaller effect sizes (45). In the other study, based on data from over two thousand subjects, LPA was associated to aerobic capacity, which in turn was estimated using a submaximal cycle ergometer test (27). In this study a step-frequency of ≤ 110 steps per minute was considered as LPA, based on evidence that a step-frequency at around 100 steps per minute is similar to 3 METs in adults (27). This may not however be an accurate method for determining intensity in older women, as they may reach higher intensity levels at lower step-frequencies (64). This could mean that a presumed intensity of LPA could in fact have been well over the cut off limit for MVPA (>3 MET) in the older subjects included in the study, thus possibly contributing to an inaccurately large influence of LPA on aerobic capacity.
19
Similar to the present study, Yasunaga et al. (2017) did not detect any significant associations between LPA, defined as 1.5–3 METs, and several measures of physical function in an elderly population between the ages 65-84 years (65). In addition, Osuka et al. (2015) only found
associations between LPA and physical function in elderly women above the age of 75, suggesting that LPA may play an important role for physical function solely in older and more inactive elderly (24). Interestingly, in the study by Izawa et al. (2017) where LPA was divided into 2 blocks (1.0– 1.9 MET and 2.0–2.9 MET), only the higher intensity block of LPA was associated with physical function. This adds to the reasoning that while lower intensities of PA could have an impact on physical function, there may be a threshold of minimum intensity for effects to be detected in the lighter-intensity span (40). A key challenge of such an idea is that intensity-thresholds are
individual for each subject and may vary to a large extent even in an homogenous group of elderly (66). This may further explain why time spent in LPA was not related to physical function in the present sample of healthy older women, and why previous reports are ambiguous.
In contrast to total present PA and MVPA, time spent in sedentary behavior only demonstrated a main effect on aerobic capacity, which was, however, not present when adjusting for sports and recreational exercise habits during adulthood (Table 4). While self-report data should be interpreted with caution, these results may be interpreted as past PA of a more demanding nature has a
protective effect on the potential influence of sedentary behavior on physical function in older women. These results are in line with previous findings in a large sample of middle-aged to older adults where associations between sedentary behavior and several other measures of physical function did not persist when further adjusting for time spent in MVPA (42). Similarly, van der Velde et al. (2017b) lost the majority of the associations between sedentary behavior and physical function when controlling for PA at higher intensities in the final model (43). These results are though opposed to those of Santos et al. (2012) and Sardinha et al. (2015), both reporting
associations of sedentary behavior and a test battery of physical function independent of time spent in MVPA (46,47). In the aforementioned studies however, the study samples consisted of 65-103 year olds (46) and 65-94 year olds (47) respectively, as compared to the 65-70 year olds
participating in the present study. In these studies the older women were also considerably less physically active on a moderate level as compared to the present study, with an average
participation in MVPA of 22.5 min/day (46) and 16.1 min/day (47) respectively, while subjects in the present study participated in MVPA on average 37.8 min/day. Furthermore, subjects in the
20
present study had a mean BMI of 25.6 as compared to 27.7 and 27.8 among the older women participating in the previously mentioned studies (46,47). It is therefore possible that sedentary behavior is detrimental for physical function only in older and more overweight women with insufficient engagement in MVPA.
Only one previous study containing healthy elderly women has to the author’s knowledge specifically assessed objectively measured PA and sedentary behavior in relation to aerobic capacity. In that particular study, both sedentary behavior and higher intensity physical activity (arguably similar to MVPA) were related to aerobic capacity independently of each other, although with PA having a considerably larger effect (27). While the results of the aforementioned study did differ to some extent compared to the present study, the explanation may lie in a series of factors. Firstly, a different methodology was used for quantifying activity and its intensity (step-counts and posture instead of CPM) and secondly, a different statistical approach was used that only accounted for BMI as a measure of body composition. Lastly, their method for quantifying aerobic capacity was by estimating maximum power output instead of VO2max, which furthermore was estimated
using either heart rate or rating of perceived exertion depending on the subject (27). In the present study, aerobic capacity was quantified as VO2max based on the Åstrand cycle test, which
consistently estimates VO2max based on heart rate, for a more reliable measure of aerobic capacity
(57). Further, an important aspect of the present study to consider is that differences in VO2max were
only observed between the middle and highest (most sedentary) tertile. The reason why a statistical difference in VO2max was not detected between the lowest and highest tertiles of sedentary behavior
is uncertain, but could be due to the sample size not allowing detection of smaller effects after adjusting for confounding factors.
Self-reported past PA
This is to the author’s knowledge the first study to assess the potential effect of past PA habits on physical function, taking into account objectively measured present PA. Due to its main effect on aerobic capacity independently of objectively measured present PA, past sport and recreational exercise in adulthood is seemingly an important factor for present physical function in elderly women. Although no extensive comparison can be made, the results of sports and recreational exercise are in line with a previous study examining self-reported past sports and exercise habits
21
separately in relation to several measures of physical function in middle-aged women (54).
Additionally, in the aforementioned study, reported past sports and exercise was associated not only to physical tests involving aerobic capacity, but also to grip strength (54). This is in contrast to the present study, where no associations to any functional measure involving strength were detected, even without adjusting for confounding factors. A strength of the aforementioned study is the continuous follow-up of self-reported PA habits across a 15 year period prior to objective testing of physical function, which presumably reduces recall bias (54). However, due to only tracking PA during the last 15 years, potential effects of sports and exercise earlier in adulthood were not
investigated. In the present study, sports and recreational exercise habits were assessed from the age of 20 using a validated questionnaire, and demonstrated that these habits even in the young
adulthood were associated to aerobic capacity in older years. In addition, Pluijm et al. (2007) reported similar results, with positive associations between past PA habits in younger age and physical function in older age. In the aforementioned study however, all types of PA were included and no attempt to assess past PA at different intensities was made (53). Although both strength and aerobic capacity decreases with age, especially among inactive individuals (67), the results of the present study indicate that aerobic capacity attained in younger ages was maintained to a larger extent as compared to strength, despite low volumes of present PA.
While self-reported walking activities throughout adulthood did in fact demonstrate a main effect on one of the functional scores, it was not the case when the other time periods of walking activities (20–50 and 50–65 years) were used in the analysis. Furthermore, the detected main effect of
walking activities throughout adulthood was only independent of total present PA in the model where homoscedasticity was violated, and was not present when replacing total present PA with either LPA or sedentary behavior. It was therefore interpreted as this may have occurred by chance, and was thus regarded as a false-positive result. Therefore, a non-significant effect of past walking activities on physical function does, in a similar fashion as the objective results, support the notion that intensity is the decisive factor for physical function in healthy older women.
Strengths and limitations
A strength of the study is the use of objective measures for both present PA and physical function, minimizing the potential effect by bias. Further, measures of physical function used in the present
22
study incorporated upper-body and lower-body strength as well as aerobic capacity separately, which allowed for assessment of distinct components of physical function in relation to PA. Additionally, this is the first study to the author’s knowledge to include both objectively measured present PA as well as self-reported past PA habits allowing a novel possibility to investigate their distinct association to physical function.
As with all studies, the present study does not come without limitations. Firstly, a notable limitation of the present study is the cross-sectional design which only allows for assessment of variables gained at a single time point, thus lacking sufficient evidence to conclude cause-and-effect
relationships. It is therefore possible that a lower physical function at baseline may have contributed to a lower PA level in older age, and thus be the true cause of the positive association between physical function and PA level in elderly women (68). Secondly, the method used to measure relative adiposity has a larger variability compared to other methods such as dual-energy x-ray absorptiometry, which potentially could have affected the results (69). Thirdly, due the narrow inclusion criteria, the results of this study may yield limited benefits to a broader population of both men and women of different ages. Lastly, it is important to consider that while analyses based on data from very large study populations may yield a great amount of statistically significant associations, the effect sizes of the associations may be modest and not necessarily be clinically meaningful to the individual (70).
Societal implications
This study supports previously reported evidence that increasing PA, especially >3 MET, is
important in order to maintain physical function in elderly, regardless of level of adiposity. Results further imply that in order to prevent lifestyle-related physical decline in elderly, the societal focus should remain on increasing participation in MVPA among old individuals but also to promote PA at intensities comparable to sports and recreational exercise throughout adulthood. Furthermore, among relatively young, less overweight and sufficiently physically active older adults, decreasing sedentary behavior per se may not provide any additional benefits for maintaining physical function and should therefore not be a societal focus in elderly.
23 Conclusion
A higher level of PA is associated to a higher physical function in healthy elderly women,
regardless of adiposity and past PA habits. In order to sustain physical function, increasing the time spent being physically active in MVPA is seemingly more important as compared to reducing the time spent in sedentary behavior. Furthermore, being physically active at intensities corresponding to at least that of MVPA throughout adulthood may provide positive effects on aerobic capacity that can be sustained at an older age, even at lower levels of current PA.
24
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