Abstract
Objective
To examine the association between leisure-time physical activity (PA) and survival to age 85 with mobility limitation or death before age 85 after total knee (TKR) or total hip (THR) replacement for osteoarthritis.
Methods
This was a prospective study among participants from the Women’s Health Initiative (WHI), recruited during 1993–1998 (baseline age, 65–79 years) and followed through 2012. Medicare claims data were linked to WHI data to determine TKR (n=1,986) and THR (n=1,034). Self-reported PA was collected before total joint replacement (TJR).
Results
Women who were physically inactive before THR had the highest risk of mobility limitation at age 85 (odds ratio [OR]=2.36; 95% CI [CI]=1.30–4.26) compared with women who had the highest amount of PA (>17.42 MET-hours/week). Women who reported no moderate-to-vigorous PA (MVPA) before THR had the strongest risk of mobility limitation (OR=2.00; 95% CI=1.24–3.22) compared with women with the highest level of MPVA (≥15 MET-hours/week). Women who were physically inactive before TKR had the highest risk of mobility limitation (OR=1.68; 95% CI=1.15–2.45) compared with women who had the highest PA level. Women who reported no MVPA before TKR had the strongest risk of mobility limitation (OR=1.60; 95% CI=1.16–2.19) compared with women with the highest level of MPVA. There were significant dose-response associations of lower PA levels with increased risk of late-life mobility limitation and death.
Conclusion
Women with lower PA levels before TJR were more likely to experience mobility limitation in late life following TJR for hip or knee OA.
Keywords: arthroplasty, osteoarthritis, functional outcomes, physical activity, knee, hip
INTRODUCTION
Osteoarthritis (OA) is a major cause of disability among older people, affecting one in eight adults (1,2). Total joint replacement (TJR) surgery, including total hip (THR) and total knee (TKR) replacements, may be considered in cases of severe OA (3,4). More than one million THRs and TKRs are performed annually in the United States (5). With the growth of the aging population and rising OA prevalence, utilization of THRs and TKRs will increase four-fold by 2030 (2,6). However, few studies have followed OA patients and TJR recipients prospectively into late life to understand patterns of functional changes and to define strategies to prevent mobility limitation among those who survive into very old age.
Physical activity (PA) has been recommended for the successful management of OA and may improve physical function among patients with severe OA (7–12). In a randomized controlled trial among older adults with knee OA, participation in an aerobic exercise program was associated with less physical disability, less knee pain, and better physical performance 18 months after the trial (10). Some studies have observed that PA may lead to better function before TJR (13–15). Men and women scheduled to undergo THR who participated in a 6-week exercise program showed greater improvements in physical function scores before surgery (15). However, little attention has been placed on the relationship between PA before TJR and long-term functional health after surgery (15–18). Previous studies yielded conflicting results on the potential impact of pre-surgery exercise programs on post-surgery functional outcomes among TJR patients. Two prior studies observed that pre-surgery PA did not improve functional outcomes a year after surgery (15,16), but a randomized controlled trial showed that an 8-week, tailored exercise program before THR resulted in better physical function six months after surgery (17).
Maintaining mobility in old age is a key component of successful aging and is an important public health goal for OA patients (1,19). Previous studies among the general population showed that regular PA is associated with better mobility and physical function later in life (20–24). However, to our knowledge, no study has determined whether pre-operative PA is associated with maintaining mobility in old age among a cohort of patients who underwent TJR for OA. A potential link would strengthen the evidence base supporting increase of PA levels before TJR among hip and knee OA patients.
Using prospective data from the Women’s Health Initiative (WHI), we examined associations between leisure-time PA levels before TJR and survival to age 85 with mobility limitation or death before age 85 among women who underwent THR or TKR for OA.
MATERIALS AND METHODS
Study Population and Design
The WHI is a longitudinal study investigating determinants of chronic diseases in women. The study design has been previously described (25). Briefly, a cohort of 161,808 postmenopausal women aged 50 to 79 years was recruited from 40 United States clinical centers during 1993–1998. Women participated in one or more of three Clinical Trials (N=68,133), including one of two Hormone Therapy trials, or an Observational Study (N=93,676). In 2005, 77% of eligible women agreed to be followed through 2010 in the first Extension Study. In 2010, 87% of eligible women enrolled in an additional five years of follow-up in the second Extension Study. Our study was exclusive to women ages 65 years and older who were continuously enrolled in fee-for-service Medicare from baseline until the end of follow-up in 2012, and who underwent THR (N=1,034) or TKR (N=1,986) for OA at any time during follow-up (see Supplementary Methods and Supplementary Figures 1 and 2). Medicare claims data were used to identify THR and TKR. All participants provided written informed consent. This study complied with the Declaration of Helsinki and was approved by the Human Research Protections Program at the University of California, San Diego (Protocol No. 161486).
Physical Activity Assessment
At the baseline visit, women completed a questionnaire assessing usual participation in leisure-time PA. The questionnaire was completed on average 6.7 (standard deviation [SD] 3.7) years before TJR. The questionnaire has acceptable reliability, with high intraclass correlation coefficients for moderate-to-vigorous PA (MVPA) (r=0.77) and total PA (r=0.76) (26). Participants were asked how often they walk outside the home for more than 10 minutes without stopping, the duration of walking, and walking speed. Frequency categories were rarely or never, 1–3 times/month, 1 time/week, 2–3 times/week, 4–6 times/week, and ≥7 times/week. Duration categories for walking included <20 minutes, 20–39 minutes, 40–59 minutes, and ≥1 hour. Categories for walking speed included casual (slower than normal) strolling (<2 miles per hour [mph]), average or normal (2–3 mph), fairly fast (3–4 mph), and very fast (>4 mph). Participants reported how often and for how long at each session they participated in activities of light (e.g., slow dancing, bowling, and golf), moderate (e.g., biking outdoors, calisthenics, and easy swimming), and vigorous (i.e., that increased heart rate and produced sweating such as aerobics, aerobic dancing, and jogging) intensities. Frequency categories were none and 1, 2, 3, 4, or ≥5 days/week. Duration categories were <20 minutes, 20–39 minutes, 40–59 minutes, and ≥1 hour.
Midpoint values for ranges of frequency and duration of PA sessions were imputed, and the product of frequency and duration was used to create “hours/week (h/wk)” variables. Metabolic equivalent (MET) values were assigned for vigorous, moderate, and light activities as 7, 4, and 3 METs, respectively (27). MET values for walking were assigned as 5, 4, 3, and 2 for very fast, fast, average or normal, and casual, respectively. The MET level was then multiplied by h/wk to compute separate variables for walking, light, moderate, and vigorous activities in MET-h/wk. MVPA was computed as the sum of average or normal and fast walking, moderate activity, and vigorous activity. Total PA was computed by summing across all activities.
Total PA and walking were divided into four categories, including 0 MET-h/wk and tertiles for the remainder of the data. MVPA was categorized as 0, >0 to <7.5, 7.5 to <15, and ≥15 MET-h/wk according to current federal guidelines recommending ≥7.5 MET-h/wk of MVPA (28). Women with 0 MET-h/wk of total PA (i.e., who reported rarely or never walking and no light PA or MVPA) were defined as being “physically inactive.”
Covariates
Participants reported demographic characteristics, lifestyle behaviors, and medical history at baseline via questionnaires. Demographic characteristics included race/ethnicity, education, income, and marital status. Lifestyle behaviors included smoking and alcohol consumption. Trained clinic staff measured height and weight at baseline. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared and categorized into established cutpoints: normal-weight (≤24.9 kg/m2), overweight (25–29.9 kg/m2), and obese (≥30 kg/m2) (29). Additional baseline covariates were self-rated health, joint pain or stiffness, and hormone therapy use, which was defined according to self-reported use and participation in the hormone therapy trials. Depressive symptoms were measured using the Burnham scale [30]. The Medicare data file was used to collect information on age at TJR.
Information on chronic diseases associated with loss of mobility (31–33), including coronary heart disease, stroke, congestive heart failure, peripheral arterial disease, diabetes, cancer, and hip fracture, was self-reported at baseline. Incident diseases were identified during study follow-up through periodic clinic visits and mailed questionnaires administered biannually to Clinical Trial participants and annually to Observational Study and Extension Study participants. All diseases, except for diabetes, were adjudicated by physician review of medical records. Diabetes was defined as self-reported physician diagnosis of diabetes treated with either oral medication or insulin, which has been previously validated (34).
Outcomes
Women were classified as having survived to age 85 or died before this age. Deaths were verified by physician adjudication using hospital records, autopsy or coroner’s reports, or death certificates. To ensure complete mortality follow-up, periodic linkage to the National Death Index was performed for all participants, including those lost to follow-up.
Late-life mobility status was assessed with the physical function subscale of the 36-item Short Form Health Survey (35), which participants completed annually after 2005. Among women who survived to age 85, mobility limitation was defined as reporting limitations in the ability to walk one block or climb one flight of stairs (31,32). The most recent measures with the least missing data that were collected within two years of the 85th birth year were used. Three possible aging outcomes were defined, similar to previous aging studies (36,37): survived to age 85 with mobility limitation; survived to age 85 with intact mobility (reference); or died before age 85. The age of 85 was selected because in US census reports, individuals ages 85 years and older comprise the “oldest-old” population, which is the fastest growing segment of the population ages 65 years and older (38).
Statistical Analysis
Baseline characteristics were compared across quartiles of total leisure-time PA using chi-square tests for categorical variables, and analysis of variance for normally distributed and Kruskal-Wallis tests for non-normally distributed continuous variables.
The analytic approach for this study was similar to that from previous prospective studies examining aging outcomes, in which the focus is not on associations with time-to–disability or -mortality, but rather mobility at advanced age or death before advanced age (36,37). Multinomial logistic regression models were used to examine associations between PA variables and the mobility outcome. Separate models were fit for total leisure-time PA, MVPA, walking, and walking speed as the primary exposures. Analyses were conducted separately for THR and TKR. Multivariable models were adjusted for age at first THR or TKR, race/ethnicity, study membership (Observational Study or Clinical Trial), education, baseline marital status, baseline alcohol consumption, baseline smoking, baseline BMI, hormone therapy use, number of chronic diseases, baseline depression, and occurrence of a second THR (or TKR). Models for THR were also adjusted for utilization of TKR and vice versa. Additional models were adjusted for baseline mobility to determine whether this factor mediated associations between PA variables and late-life mobility. To test for linear trend associations, continuous measures of PA variables were included in multivariable models. Interactions between PA variables and age at TJR and BMI were also tested.
In sensitivity analyses, to check for potential bias due to missing late-life functional data, women who survived to age 85 but had missing mobility data were assumed to have late-life mobility limitation in the models. A sensitivity analysis excluding women who received a TJR within two years of the baseline study visit was also conducted to determine if severe cases of hip or knee OA at the time of the baseline PA assessment biased findings. Finally, to determine if the timing of PA assessment biased findings, additional models were adjusted for number of years between the PA questionnaire and TJR.
P-values were two-sided and significant at P <0.05. Statistical analyses were conducted using SAS Version 9.3 (SAS Institute, Cary, NC).
RESULTS
The mean age at baseline was 69.5 (SD, 3.0; range, 65–79) years in the overall cohort. Women were followed for an average of 8.1 (SD, 3.5; range, 3–18) years after TJR. Furthermore, 94.9% were white, 3.0% were African American, and 2.2% were other racial/ethnic groups. In the THR cohort, 47.7% had mobility limitation at age 85, 35.3% had intact mobility at age 85, and 17.0% died before age 85. The mean age at first THR was 77.7 (SD 3.9; range, 67–84) years. In total, 20.6% had a second THR, 4.8% had a revision hip procedure, and 17.8% had TKR. In the TKR cohort, 48.7% had mobility limitation at age 85, 31.7% had intact mobility at age 85, and 19.6% died before age 85. The mean age at first TKR was 77.5 (SD 4.0; range, 67–84) years. Overall, 28.5% had a second TKR, 3.8% had a knee revision procedure, and 9.4% had THR.
At baseline, women with higher levels of total PA were more likely to be college graduates, have higher income, currently consume alcohol, and have excellent or very good self-rated health (Table 1). They were less likely to be obese, have depressive symptoms, have a history of chronic diseases, or report severe joint pain or stiffness at baseline. Women with lower PA levels were more likely to have mobility limitation at baseline. Half of women who reported not participating in any PA had baseline mobility limitation.
Table 1.
Baseline Characteristics by Total Physical Activity Among Older Women with Total Joint Replacement for Osteoarthritis
| Total Physical Activity, MET-hours/week
|
P-value | ||||
|---|---|---|---|---|---|
| 0 (N=371) |
>0 to 7 (N=789) |
>7 to 17.42 (N=839) |
>17.42 (N=819) |
||
| Age, years, mean (SD) | 69.8 (3.1) | 69.7 (2.9) | 69.4 (2.9) | 69.4 (2.9) | 0.01 |
| Race/ethnicity, no. (%) | |||||
| (N=370) | (N=787) | (N=836) | (N=816) | ||
| White | 352 (95.1) | 735 (93.4) | 795 (95.1) | 783 (96.0) | |
| African American | 9 (2.4) | 32 (4.1) | 24 (2.9) | 18 (2.2) | 0.36 |
| Other | 9 (2.4) | 20 (2.5) | 17 (2.0) | 15 (1.8) | |
| Education, no (%) | |||||
| (N=370) | (N=786) | (N=836) | (N=816) | ||
| Less than high school | 14 (3.8) | 31 (3.9) | 21 (2.5) | 19 (2.3) | |
| High school | 85 (23.0) | 153 (19.5) | 114 (13.6) | 103 (12.6) | |
| Some college | 151 (40.8) | 296 (37.7) | 288 (34.5) | 267 (32.7) | <0.001 |
| College graduate | 120 (32.4) | 306 (38.9) | 413 (49.4) | 427 (52.3) | |
| Income, no (%) | |||||
| (N=345) | (N=734) | (N=791) | (N=767) | ||
| <$20,000 | 69 (20.0) | 116 (15.8) | 107 (13.5) | 75 (9.8) | |
| $20,000–$50,000 | 174 (50.4) | 391 (53.3) | 401 (50.7) | 370 (48.2) | <0.001 |
| >$50,000 | 102 (29.6) | 227 (30.9) | 283 (35.8) | 322 (42.0) | |
| Marital status, no. (%) | |||||
| (N=370) | (N=787) | (N=837) | (N=818) | ||
| Married/living as | |||||
| married | 227 (61.4) | 497 (63.2) | 501 (59.9) | 517 (63.2) | |
| Widowed | 92 (24.9) | 186 (23.6) | 212 (25.3) | 203 (24.8) | 0.71 |
| Divorced/separated | 37 (10.0) | 69 (8.8) | 92 (11.0) | 73 (8.9) | |
| Never married | 14 (3.8) | 35 (4.5) | 32 (3.8) | 25 (3.1) | |
| Alcohol consumption, no (%) | |||||
| (N=367) | (N=783) | (N=839) | (N=816) | ||
| Non-drinker | 36 (9.8) | 80 (10.2) | 87 (10.4) | 61 (7.5) | |
| Past drinker | 83 (22.6) | 128 (16.4) | 117 (14.0) | 83 (10.2) | <0.001 |
| Current drinker | 248 (67.6) | 575 (73.4) | 635 (75.7) | 672 (82.4) | |
| Smoking status, no. (%) | |||||
| (N=362) | (N=783) | (N=830) | (N=816) | ||
| Never smoked | 190 (52.5) | 421 (53.8) | 440 (53.0) | 385 (47.2) | |
| Past smoker | 158 (43.7) | 329 (42.0) | 368 (44.3) | 408 (50.0) | 0.03 |
| Current smoker | 14 (3.9) | 33 (4.2) | 22 (2.7) | 23 (2.8) | |
| Body mass index, kg/m2, no (%) | |||||
| (N=367) | (N=783) | (N=831) | (N=810) | ||
| Normal weight | 53 (14.4) | 164 (21.0) | 226 (27.2) | 318 (39.3) | |
| Overweight | 114 (31.1) | 271 (34.6) | 355 (42.7) | 287 (35.4) | <0.001 |
| Obese | 200 (54.5) | 348 (44.4) | 250 (30.1) | 205 (25.3) | |
| Hormone therapy use, no. (%) | |||||
| (N=369) | (N=782) | (N=829) | (N=810) | ||
| Never | 132 (35.8) | 305 (39.0) | 280 (33.8) | 294 (36.3) | |
| Past | 96 (26.0) | 209 (26.7) | 221 (26.7) | 194 (24.0) | 0.19 |
| Current | 141 (38.2) | 268 (34.3) | 328 (39.6) | 322 (39.8) | |
| Self-rated health, no. (%) | |||||
| (N=369) | (N=784) | (N=832) | (N=811) | ||
| Excellent | 29 (7.9) | 69 (8.8) | 115 (13.8) | 183 (22.6) | |
| Very good | 119 (32.3) | 314 (40.1) | 364 (43.8) | 358 (44.1) | <0.001 |
| Good | 162 (43.9) | 339 (43.2) | 291 (35.0) | 241 (29.7) | |
| Fair/poor | 59 (16.0) | 62 (7.9) | 62 (7.5) | 29 (3.6) | |
| Burnham depression scale score ≥0.06, no. (%) | (N=361) | (N=773) | (N=823) | (N=794) | |
| 35 (9.7) | 65 (8.4) | 62 (7.5) | 44 (5.5) | 0.05 | |
| History of chronic diseasesa, no. (%) | (N=371) | (N=789) | (N=839) | (N=819) | |
| CHD | 41 (11.1) | 85 (10.8) | 86 (10.3) | 64 (7.8) | 0.15 |
| Stroke | 32 (8.6) | 66 (8.4) | 55 (6.6) | 60 (7.3) | 0.46 |
| CHF | 30 (8.1) | 39 (4.9) | 37 (4.4) | 21 (2.6) | <0.001 |
| PAD | 22 (5.9) | 30 (3.8) | 32 (3.8) | 27 (3.3) | 0.18 |
| Diabetes | 75 (20.2) | 137 (17.4) | 102 (12.2) | 118 (14.4) | <0.001 |
| Cancer | 110 (29.7) | 199 (25.2) | 236 (28.1) | 233 (28.5) | 0.33 |
| Hip fracture | 26 (7.0) | 52 (6.6) | 49 (5.8) | 40 (4.9) | 0.39 |
| Any disease | 226 (60.9) | 436 (55.3) | 431 (51.4) | 420 (51.3) | 0.006 |
| Mobility limitation, no. (%) | (N=368) | (N=781) | (N=830) | (N=809) | |
| 185 (50.3) | 243 (31.1) | 200 (24.1) | 127 (15.7) | <0.001 | |
| Joint pain, no. (%) | |||||
| (N=369) | (N=782) | (N=835) | (N=812) | ||
| None | 32 (8.7) | 92 (11.8) | 104 (12.5) | 139 (17.1) | |
| Mild | 144 (39.0) | 335 (42.8) | 406 (48.6) | 397 (48.9) | <0.001 |
| Moderate | 129 (35.0) | 278 (35.6) | 249 (29.8) | 224 (27.6) | |
| Severe | 64 (17.3) | 77 (9.9) | 76 (9.1) | 52 (6.4) | |
Note. Sample sizes for variables in each column do not sum to total due to missing data.
CHD = coronary heart disease; CHF = congestive heart failure; MET = metabolic equivalent of task; PAD = peripheral arterial disease.
Includes baseline and incident chronic diseases.
Relative to women with THR with the highest level of total PA (>17.42 MET-h/wk), physically inactive women (odds ratio [OR]=2.36; 95% confidence interval [CI]=1.30–4.26) had the highest odds of mobility limitation at age 85 (p for trend <0.001) in the multivariable model (Table 2). Compared with women with THR who reported ≥15 MET-h/wk of MVPA, the odds of mobility limitation were significantly higher for lower levels of MVPA and were highest in women with no MVPA (OR=2.00; 95% CI=1.24–3.22; p for trend <0.001). Relative to women with the highest amount of walking (>6.25 MET-h/wk), the odds of mobility limitation were strongest among women who did not engage in any walking (OR=1.81; 95% CI=1.20–2.72; p for trend=0.003). Furthermore, the odds of mobility limitation were approximately two-fold higher among women who reported casual (i.e., slower than normal) compared with fast walking speed (p for trend=0.02). There were significant dose-response associations of total PA, MVPA, walking, and walking speed with death before age 85. In models adjusting for baseline mobility, findings were no longer significant (data not shown).
Table 2.
Multivariable Associations of Physical Activity with Mobility Among Women with Total Hip Replacement for Osteoarthritisa
| No. survived to 85 with mobility limitation/total (%) | Survived to 85 with mobility limitationb OR (95% CI) | No. died before 85/total (%) | Died before 85b OR (95% CI) | |
|---|---|---|---|---|
| Total physical activity, MET-hours/weekc | ||||
| 0 | 67/117 (57.3) | 2.36 (1.30–4.26) | 25/117 (21.4) | 2.18 (0.98–4.84) |
| >0 to 7 | 149/286 (52.1) | 1.74 (1.16–2.61) | 59/286 (20.6) | 2.36 (1.32–4.22) |
| >7 to 17.42 | 151/320 (47.2) | 1.23 (0.85–1.78) | 49/320 (15.3) | 1.49 (0.85–2.62) |
| >17.42 | 126/311 (40.5) | 1 [Ref] | 43/311 (13.8) | 1 [Ref] |
| Moderate-to-vigorous physical activity, MET-hours/weekd | ||||
| 0 | 107/198 (54.0) | 2.00 (1.24–3.22) | 41/198 (20.7) | 2.03 (1.06–3.91) |
| >0 to <7.5 | 145/283 (51.2) | 1.83 (1.23–2.71) | 54/283 (19.1) | 2.12 (1.20–3.74) |
| 7.5 to <15 | 114/228 (50.0) | 1.63 (1.09–2.43) | 34/228 (14.9) | 2.00 (1.09–2.43) |
| ≥15 | 127/325 (39.1) | 1 [Ref] | 47/325 (14.5) | 1 [Ref] |
| Walkinge | ||||
| 0 | 166/312 (53.2) | 1.81 (1.20–2.72) | 64/312 (20.5) | 2.05 (1.13–3.72) |
| >0 to 2.5 | 102/211 (48.3) | 1.58 (1.02–2.45) | 47/211 (22.3) | 2.65 (1.42–4.95) |
| >2.5 to 6.25 | 102/224 (45.5) | 1.15 (0.77–1.72) | 33/224 (14.7) | 1.20 (0.64–2.27) |
| >6.25 | 123/287 (42.9) | 1 [Ref] | 32/287 (11.2) | 1 [Ref] |
| Walking Speedf | ||||
| Casual (slower than normal) | 103/210 (49.1) | 1.90 (1.13–3.20) | 54/210 (25.7) | 2.08 (1.03–4.19) |
| Average or normal | 227/468 (48.5) | 1.24 (0.83–1.83) | 59/468 (12.6) | 0.91 (0.50–1.65) |
| Fast | 79/196 (40.3) | 1 [Ref] | 27/196 (13.8) | 1 [Ref] |
CI = confidence interval; OR = odds ratio.
Reference group is survived to age 85 with intact mobility.
Adjusted for age at first total hip replacement, study membership, education, race/ethnicity, baseline marital status, baseline alcohol consumption, baseline smoking, baseline body mass index, total number of chronic diseases, hormone therapy use, baseline depression, second total hip replacement, and total knee replacement.
N for multivariable analyses = 960. P for trend (mobility limitation) = <0.001; P for trend (death) = 0.02.
N for multivariable analyses = 960. P for trend (mobility limitation) = <0.001; P for trend (death) = 0.03.
N for multivariable analyses = 960. P for trend (mobility limitation) = 0.003; P for trend (death) = 0.01.
N for multivariable analyses = 820. P for trend (mobility limitation) = 0.02; P for trend (death) = 0.03.
Inactive women with TKR had the highest odds of mobility limitation at age 85 (OR=1.68; 95% CI=1.15–2.45) and dying before age 85 (OR=1.79; 95% CI=1.09–2.95) compared with women who were the most physically active before TKR (p for trend for mobility=0.007 and p for trend for death=0.02) (Table 3). Compared with women engaging in ≥15 MET-h/week of MVPA, those with lower levels of MVPA had significantly increased odds of mobility limitation (p for trend=0.002). Women with no MVPA had a two-fold increased risk of dying before 85 years (OR=2.24; 95% CI=1.47–3.42; p for trend=0.01). Women with casual relative to fast walking speed had increased odds of mobility limitation (p for trend=0.007) and death (p for trend<0.001). After adjusting for baseline mobility, PA variables were no longer significantly associated with late-life mobility or death (data not shown).
Table 3.
Multivariable Associations of Physical Activity with Mobility Among Women with Total Knee Replacement for Osteoarthritisa
| No. survived to 85 with mobility limitation/total (%) | Survived to 85 with mobility limitationb OR (95% CI) | No. died before 85/total (%) | Died before 85b OR (95% CI) | |
|---|---|---|---|---|
| Total physical activity, MET-hours/weekc | ||||
| 0 | 144/275 (52.4) | 1.68 (1.15–2.45) | 69/275 (25.1) | 1.79 (1.09–2.95) |
| >0 to 7 | 281/556 (50.5) | 1.39 (1.04–1.85) | 127/556 (22.8) | 1.61 (1.09–2.38) |
| >7 to 17.42 | 289/580 (49.8) | 1.24 (0.94–1.62) | 100/580 (17.2) | 1.11 (0.75–1.64) |
| >17.42 | 254/575 (44.2) | 1 [Ref] | 93/575 (16.2) | 1 [Ref] |
| Moderate-to-vigorous physical activity, MET-hours/weekd | ||||
| 0 | 225/455 (49.5) | 1.60 (1.16–2.19) | 125/455 (27.5) | 2.24 (1.47–3.42) |
| >0 to <7.5 | 261/500 (52.2) | 1.39 (1.04–1.84) | 94/500 (18.8) | 1.44 (0.96–2.18) |
| 7.5 to <15 | 219/436 (50.2) | 1.39 (1.03–1.86) | 82/436 (18.8) | 1.49 (0.98–2.27) |
| ≥15 | 263/595 (44.2) | 1 [Ref] | 88/595 (14.8) | 1 [Ref] |
| Walkinge | ||||
| 0 | 334/660 (50.6) | 1.52 (1.12–2.05) | 161/660 (24.4) | 1.35 (0.90–2.02) |
| >0 to 2.5 | 218/444 (49.1) | 1.21 (0.89–1.67) | 91/444 (20.5) | 1.17 (0.76–1.80) |
| >2.5 to 6.25 | 225/437 (51.5) | 1.20 (0.88–1.63) | 57/437 (13.0) | 0.66 (0.41–1.04) |
| >6.25 | 191/445 (42.9) | 1 [Ref] | 80/445 (18.0) | 1 [Ref] |
| Walking Speedf | ||||
| Casual (slower than normal) | 219/458 (47.8) | 1.66 (1.16–2.38) | 125/458 (27.3) | 2.73 (1.62–4.59) |
| Average or normal | 406/830 (48.9) | 1.33 (0.99–1.80) | 131/830 (15.8) | 1.42 (0.88–2.29) |
| Fast | 138/317 (43.5) | 1 [Ref] | 36/317 (11.4) | 1 [Ref] |
CI = confidence interval; OR = odds ratio.
Reference group is survived to age 85 with intact mobility.
Adjusted for age at first total knee replacement, study membership, education, race/ethnicity, baseline marital status, baseline alcohol consumption, baseline smoking, baseline body mass index, total number of chronic diseases, hormone therapy use, baseline depression, second total knee replacement, and total hip replacement.
N for multivariable analyses = 1863. P for trend (mobility limitation) = 0.007; P for trend (death) = 0.02.
N for multivariable analyses = 1863. P for trend (mobility limitation) = 0.002; P for trend (death) = 0.01.
N for multivariable analyses = 1863. P for trend (mobility limitation) = 0.01; P for trend (death) = 0.25.
N for multivariable analyses = 1510. P for trend (mobility limitation) = 0.007; P for trend (death) = <0.001.
Findings did not vary by age at TJR or BMI. In sensitivity analyses, findings were not altered after excluding women who underwent a THR or TKR within two years of the baseline study visit. In sensitivity analyses assuming that women who survived to age 85 with missing data for mobility had late-life mobility limitation in the multivariable models, findings were similar. Adjustment for number of years between PA assessment and TJR did not alter the findings (data not shown).
DISCUSSION
In this prospective study, women who engaged in lower amounts of total PA and MVPA before TJR for hip or knee OA had increased risk of late-life mobility limitation as well as death. Risks for poor mobility and death were also significantly increased among women with slower walking speed. These findings were independent of demographic characteristics, lifestyle behaviors, BMI, and chronic conditions that may impair function. Our data underscore that a large proportion of women with hip or knee OA may reach old age with poor mobility despite TJR.
Among the general population, PA levels measured in midlife or early old age predicted mobility and physical functioning later in life (20–24). A community-based study among older men and women observed that regular PA (i.e., walking, gardening, or vigorous exercise) at least 3 times/week was associated with maintaining the ability to walk a half mile or up and down stairs without help four years later (24). Among men and women aged 70 to 89 years, a PA intervention compared with a health education program was associated with decreased risk of developing mobility disability, defined as the inability to walk 400 meters without help (22). Our findings build upon previous research by examining a cohort consisting exclusively of OA patients, an important consideration given that OA is a leading cause of disability among older adults (1).
Although there is some evidence that PA may improve physical function before TJR (14), it is unclear whether it optimizes long-term post-operative outcomes, because most studies have been limited by short post-surgery follow-up periods (15–17,39,40). A 6-week exercise intervention immediately before THR or TKR did not improve functional outcomes at six months after surgery (15). However, the long-term effectiveness of PA in minimizing disability among OA patients may depend on remaining physically active over time. For example, hip and knee OA patients who remained adherent to recommended home exercises for up to five years showed greater improvements in physical function (11). The dose-response associations of total PA, MVPA, and walking with mobility in old age and death in our study suggest that there may be long-term advantages in being physically active for women with hip or knee OA. Furthermore, the stronger associations of PA with mobility limitation among women with THR than TKR support future studies examining whether PA confers greater benefit for patients with hip or knee OA.
Some studies showed that patient PA levels do not change post-operatively, despite evidence that PA after TJR is associated with improved function (39,41–43). The research to date demonstrates that there may be advantages in PA both pre- and post-operatively. Accordingly, instilling behavioral change among TJR patients to participate in greater amounts of PA may be important for improvement of functional health in the long term.
We found that women with slower self-reported walking speed had increased risk of mobility limitation and death. Faster walking speed has been associated with decreased risk of knee OA (44). Among non-disabled older adults, walking speed is a predictor of future disability and mortality (45). Our results suggest that walking speed may also be a marker of future aging outcomes among OA patients with TJR.
The benefits of PA in the setting of OA include attenuation of joint loading, maintenance of joint stability, and assistance with joint motion and elasticity of periarticular tissues, all of which are important to maintaining function (1). Extended periods of inactivity due to OA increase risk of obesity, cardiovascular disease, and other conditions that may lead to poor function (1); however, our findings were independent of these diseases. All women who joined the WHI were ambulatory at baseline. Nonetheless, we observed that women who were less physically active were more likely to have difficulty walking one block or climbing one flight of stairs at baseline. Moreover, after controlling for baseline mobility, dose-response associations of PA with late-life mobility limitation and death were no longer significant. Because baseline PA and mobility were both assessed at the same study visit, we could not determine whether PA resulted in better mobility before TJR and consequently in late life. Notably, it was previously shown that OA patients with better pre-operative function achieved greater improvements in function after THR and TKR; however, factors such as PA that could result in better pre-operative function were not assessed (46).
Limitations of our study include self-reported PA and lack of information on strength, resistance, and flexibility exercises. Self-reported PA correlates weakly with objectively-measured PA, which may provide a better estimate of time spent in activities of varying intensity (47). Although we categorized PA levels resulting in loss of power, we also tested linear trend associations using continuous measures. We lacked information on specific types (e.g., household or work-related) of activity. Self-reported total energy expenditure from the WHI PA questionnaire correlates weakly with objectively-measured total energy expenditure, and thus may be prone to measurement error (48). PA was collected at baseline and several years before TJR. However, this approach is consistent with previous studies linking PA patterns in midlife and early old age to late-life disability (20–24). Our study consisted only of fee-for-service beneficiaries, thus findings may not be generalized to women enrolled in Medicare managed care plans. In the WHI, fee-for-service beneficiaries are more likely to be white and of a higher socioeconomic status. Because 95% of women in this sub-cohort of WHI women were white, we could not evaluate ethnic differences. Many women who survived to age 85 had missing information on late-life mobility. However, after fitting models assuming that these women had late-life mobility limitation, findings were similar, suggesting that our findings were not biased by missing outcome data. Our study was focused on examination of healthy aging outcomes in TJR recipients and did not address if PA levels were associated with increased risk of mortality among TJR survivors.
A strength of our study is the population-based sample of women followed for a long period of time after TJR, which provided the unique opportunity to assess late-life functional outcomes. The combination of WHI and Medicare data was a rich resource to examine the association of PA with late-life functional outcomes and death.
In conclusion, women with higher levels of total PA, MVPA, and walking, as well as faster walking speed, before TJR for hip or knee OA were more likely to have intact mobility in late life and have decreased risk of death. Additional studies are warranted to determine whether engaging in PA before TJR reduces risk of disability among patients with severe hip or knee OA.
Supplementary Material
Acknowledgments
We would like to acknowledge the following Women’s Health Initiative Investigators: Program Office: (National Heart, Lung, and Blood Institute, Bethesda, Maryland) Jacques Rossouw, Shari Ludlam, Dale Burwen, Joan McGowan, Leslie Ford, and Nancy Geller Clinical Coordinating Center: (Fred Hutchinson Cancer Research Center, Seattle, WA) Garnet Anderson, Ross Prentice, Andrea LaCroix, and Charles Kooperberg
Investigators and Academic Centers: (Brigham and Women's Hospital, Harvard Medical School, Boston, MA) JoAnn E. Manson; (MedStar Health Research Institute/Howard University, Washington, DC) Barbara V. Howard; (Stanford Prevention Research Center, Stanford, CA) Marcia L. Stefanick; (The Ohio State University, Columbus, OH) Rebecca Jackson; (University of Arizona, Tucson/Phoenix, AZ) Cynthia A. Thomson; (University at Buffalo, Buffalo, NY) Jean Wactawski-Wende; (University of Florida, Gainesville/Jacksonville, FL) Marian Limacher; (University of Iowa, Iowa City/Davenport, IA) Robert Wallace; (University of Pittsburgh, Pittsburgh, PA) Lewis Kuller; (Wake Forest University School of Medicine, Winston-Salem,NC) Sally Shumaker.
Funding
This work was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases [grant T32 AR064194 to A.H.S.], the National Heart, Lung, and Blood Institute [contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C], and the Women’s Health Center of Excellence at the University of California, San Diego School of Medicine.
Role of the sponsor: The National Heart, Lung, and Blood Institute has representation on the Women’s Health Initiative Steering Committee, which governed the design and conduct of the study, the interpretation of the data, and preparation and approval of manuscripts.
References
- 1.Felson DT, Lawrence RC, Dieppe PA, Hirsch R, Helmick CG, Jordan JM, et al. Osteoarthritis: new insights. Part 1: the disease and its risk factors. Ann Intern Med. 2000;133:635–46. doi: 10.7326/0003-4819-133-8-200010170-00016. [DOI] [PubMed] [Google Scholar]
- 2.Hunter DJ, Schofield D, Callander E. The individuals and socioeconomic impact of osteoarthritis. Nat Rev Rheumatol. 2014;10:437–41. doi: 10.1038/nrrheum.2014.44. [DOI] [PubMed] [Google Scholar]
- 3.George LK, Ruiz D, Sloan FA. The effects of total knee arthroplasty on physical functioning in the older population. Arthritis Rheum. 2008;58:3166–71. doi: 10.1002/art.23888. [DOI] [PubMed] [Google Scholar]
- 4.George LK, Ruiz D, Sloan FA. The effects of total hip arthroplasty on physical functioning in the older population. J Am Geriatr Soc. 2008;56:1057–62. doi: 10.1111/j.1532-5415.2008.01685.x. [DOI] [PubMed] [Google Scholar]
- 5.Agency for Healthcare Research and Quality. HCUP projections: mobility/orthopedic procedures 2003 to 2012. Rockville: Agency for Healthcare Research and Quality; 2012. (HCUP publication no. 2012-03). United States, September 2012. [Google Scholar]
- 6.Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of primary revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007;89:780–5. doi: 10.2106/JBJS.F.00222. [DOI] [PubMed] [Google Scholar]
- 7.Westby MD. A health professional’s guide to exercise prescription for people with arthritis: a review of aerobic fitness activities. Arthritis Rheum. 2001;45:501–11. doi: 10.1002/1529-0131(200112)45:6<501::aid-art375>3.0.co;2-y. [DOI] [PubMed] [Google Scholar]
- 8.Penninx BW, Messier SP, Rejeski WJ, Williamson JD, DiBari M, Cavazzini C, et al. Physical exercise and the prevention of disability in activities of daily living in older persons with osteoarthritis. Arch Intern Med. 2001;161:2309–16. doi: 10.1001/archinte.161.19.2309. [DOI] [PubMed] [Google Scholar]
- 9.Juhl C, Christensen R, Roos EM, Zhang W, Lund H. Impact of exercise type and dose on pain and disability in knee osteoarthritis: a systematic review and meta-regression analysis of randomized controlled trials. Arthritis Rheumatol. 2014;66:622–36. doi: 10.1002/art.38290. [DOI] [PubMed] [Google Scholar]
- 10.Ettinger WH, Burns R, Messier SP, Applegate W, Rejeski WJ, Morgan T, et al. A randomized trial comparing aerobic exercise and resistance exercise with a health education program in older adults with knee osteoarthritis: The Fitness Arthritis and Senior Trial (FAST) JAMA. 1997;277:25–31. [PubMed] [Google Scholar]
- 11.Pisters MF, Veenhof C, Schellevis FG, Twisk JW, Dekker J, De Bakker DH. Exercise adherence improving long-term patient outcome in patients with osteoarthritis of the hip and/or knee. Arthritis Care Res (Hoboken) 2010;62:1087–94. doi: 10.1002/acr.20182. [DOI] [PubMed] [Google Scholar]
- 12.van Baar M, Assendelft WJ, Dekker J, Oostendorp RA, Bijlsma JW. Effectiveness of exercise therapy in patients with osteoarthritis of the hip or knee. Arthritis Rheum. 1999;42:1361–9. doi: 10.1002/1529-0131(199907)42:7<1361::AID-ANR9>3.0.CO;2-9. [DOI] [PubMed] [Google Scholar]
- 13.Gill SD, McBurney H. Does exercise reduce pain and improve physical function before hip or knee replacement surgery? A systematic review and meta-anslysis of randomized controlled trials. Arch Phys Med Rehabil. 2013;94:164–76. doi: 10.1016/j.apmr.2012.08.211. [DOI] [PubMed] [Google Scholar]
- 14.Gill SD, McBurney H. Exercise reduces pain and improves physical function for people awaiting hip replacement surgery. Br J Sports Med. 2014;48:477–8. doi: 10.1136/bjsports-2013-092726. [DOI] [PubMed] [Google Scholar]
- 15.Rooks DS, Huang J, Bierbaum BE, Bolus SA, Rubano J, Connolly CE, et al. Effect of preoperative exercise on measures of functional status in men and women undergoing total hip and knee arthroplasty. Arthritis Rheum. 2006;55:700–8. doi: 10.1002/art.22223. [DOI] [PubMed] [Google Scholar]
- 16.Poortinga S, van den Akker-Scheek I, Bulstra SK, Stewart RE, Stevens M. Preoperative physical activity level has no relationship to the degree of recovery one year after primary total hip or knee arthroplasty: a cohort study. PLoS One. 2014:e115559. doi: 10.1371/journal.pone.0115559. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gilbey HJ, Ackland TR, Wang AW, Morton AR, Trouchet T, Tapper J. Exercise improves early functional recovery after total hip arthroplasty. Clin Orthop Relat Res. 2003;408:193–200. doi: 10.1097/00003086-200303000-00025. [DOI] [PubMed] [Google Scholar]
- 18.D’Lima DD, Colwell CW, Morris BA, Hardwick ME, Kozin F. The effect of preoperative exercise on total knee replacement outcomes. Clin Orthop Relat Res. 1996;326:174–82. doi: 10.1097/00003086-199605000-00020. [DOI] [PubMed] [Google Scholar]
- 19.Rantakokko M, Manty M, Rantanen T. Mobility decline in old age. Exerc Sport Sci Rev. 2013;41:19–25. doi: 10.1097/JES.0b013e3182556f1e. [DOI] [PubMed] [Google Scholar]
- 20.Patel KV, Coppin AK, Manini TM, Lauretani F, Bandinelli S, Ferrucci L, et al. Midlife physical activity and mobility in older age: the InCHIANTI Study. Am J Prev Med. 2006;31:217–24. doi: 10.1016/j.amepre.2006.05.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Stenholm S, Koster A, Valkeinen H, Patel KV, Bandinelli S, Guralnik JM, et al. Association of physical activity history with physical function and mortality in old age. J Gerontol A Biol Sci Med Sci. 2016;71:496–501. doi: 10.1093/gerona/glv111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Gill TM, Guralnik JM, Pahor M, Church T, Fielding RA, King AC, et al. Effect of structured physical activity on overall burden and transitions between states of major mobility disability in older persons: secondary analysis of a randomized trial. Ann Intern Med. 2016;165:833–40. doi: 10.7326/M16-0529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Chang M, Saczynski JS, Snaedal J, Bjornsson S, Einarsson B, Garcia M, et al. Midlife physical activity preserves lower extremity function in older adults: Age Gene/Environment Susceptibility-Reykjavik Study. J Am Geriatr Soc. 2013;61:237–42. doi: 10.1111/jgs.12077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.LaCroix AZ, Guralnik JM, Berkman LF, Wallace RB, Satterfield S. Maintaining mobility in late life II. Smoking, alcohol consumption, physical activity, and body mass index. Am J Epidemiol. 1993;137:858–69. doi: 10.1093/oxfordjournals.aje.a116747. [DOI] [PubMed] [Google Scholar]
- 25.The Women’s Health Initiative Study Group. Design of the Women’s Health Initiative study design. Control Clin Trials. 1998;19:61–109. doi: 10.1016/s0197-2456(97)00078-0. [DOI] [PubMed] [Google Scholar]
- 26.Meyer AM, Evenson KR, Morimoto L, Siscovick D, White E. Test-retest reliability of the Women’s Health Initiative physical activity questionnaire. Med Sci Sports Exerc. 2009;41:530–8. doi: 10.1249/MSS.0b013e31818ace55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32:S498–504. doi: 10.1097/00005768-200009001-00009. [DOI] [PubMed] [Google Scholar]
- 28.Nelson ME, Rejeski J, Blair SN, Duncan PW, Judge JO, King AC, et al. Physical activity and public health in older adults. Med Sci Sports Exerc. 2007;39:1435–45. doi: 10.1249/mss.0b013e3180616aa2. [DOI] [PubMed] [Google Scholar]
- 29.National Institutes of Health. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. Obes Res. 1998;6:515–2095. [PubMed] [Google Scholar]
- 30.Burnham MA, Wells KB, Leake B, Landsverk J. Development of a brief screening instrument for detecting depressive disorders. Med Care. 1988;26:775–89. doi: 10.1097/00005650-198808000-00004. [DOI] [PubMed] [Google Scholar]
- 31.Guralnik JM, LaCroix AZ, Abbott RD, Berkman LF, Satterfield S, Evans DA, et al. Maintaining mobility in late life. I. Demographic characteristics and chronic conditions. Am J Epidemiol. 1993;137:845–57. doi: 10.1093/oxfordjournals.aje.a116746. [DOI] [PubMed] [Google Scholar]
- 32.Houston DK, Ding J, Nicklas BJ, Harris TB, Lee JS, Nevitt MC, et al. Overweight and obesity over the adult life course and incident mobility limitation in older adults: the Health, Aging and Body Composition Study. Am J Epidemiol. 2009;169:927–36. doi: 10.1093/aje/kwp007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Kopelman P. Health risks associated with overweight and obesity. Obes Rev. 2007;8(suppl 1):13–17. doi: 10.1111/j.1467-789X.2007.00311.x. [DOI] [PubMed] [Google Scholar]
- 34.Margolis KL, Lihong Q, Brzyski R, Bonds DE, Howard BV, Kempainen S, et al. Validity of diabetes self-reports in the Women’s Health Initiative: comparison with medication inventories and fasting glucose measurements. Clin Trials. 2008;5:240–7. doi: 10.1177/1740774508091749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Ware JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36) Med Care. 1992;30:473–83. [PubMed] [Google Scholar]
- 36.Willcox BJ, He Q, Chen R, Yano K, Masaki KH, Grove JS, et al. Midlife risk factors and healthy survival in men. JAMA. 2006;296:2343–50. doi: 10.1001/jama.296.19.2343. [DOI] [PubMed] [Google Scholar]
- 37.Rillamas-Sun E, LaCroix AZ, Waring ME, Kroenke CH, LaMonte MJ, Vitolins MZ, et al. Obesity and late-age survival without major disease or disability in older women. JAMA Intern Med. 2014;174:98–106. doi: 10.1001/jamainternmed.2013.12051. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.United States Census Bureau. 65+ in the United States: 2010. Suitland: United States Census Bureau; 2014. (USCB publication no. P23-212). United States, June 2014. [Google Scholar]
- 39.Zech A, Hendrich S, Pfeifer K. Association between exercise therapy dose and functional improvements in the early postoperative phase after hip and knee arthroplasty: An observational study. PM R. 2015;7:1064–72. doi: 10.1016/j.pmrj.2015.04.008. [DOI] [PubMed] [Google Scholar]
- 40.Kwok IH, Paton B, Haddad FS. Does pre-operative physiotherapy improve outcomes in primary total knee arthroplasty? – A systematic review. J Arthroplasty. 2015;30:1657–63. doi: 10.1016/j.arth.2015.04.013. [DOI] [PubMed] [Google Scholar]
- 41.Harding P, Holland AE, Delany C, Hinman RS. Do activity levels increase after total hip and knee arthroplasty? Clin Orthop Relat Res. 2014;472:1502–1511. doi: 10.1007/s11999-013-3427-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Arnold JB, Walters JL, Ferrar KE. Does physical activity increase after total hip or knee arthroplasty for osteoarthritis? A systematic review. J Orthop Sports Phys Ther. 2016;46:431–442. doi: 10.2519/jospt.2016.6449. [DOI] [PubMed] [Google Scholar]
- 43.Kuster MS. Exercise recommendations after total joint replacement: A review of the current literature and proposal of scientifically based guidelines. Sports Med. 2002;32:433–445. doi: 10.2165/00007256-200232070-00003. [DOI] [PubMed] [Google Scholar]
- 44.Purser JL, Golightly YM, Feng Q, Helmick CG, Renner JB, Jordan JM. Association of slower walking speed with incident knee osteoarthritis-related outcomes. Arthritis Care Res (Hoboken) 2012;64:1028–35. doi: 10.1002/acr.21655. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Abellan van Kan G, Rolland Y, Andrieu S, Bauer J, Beauchet O, Bonnefoy M, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging. 2009;13:881–9. doi: 10.1007/s12603-009-0246-z. [DOI] [PubMed] [Google Scholar]
- 46.Fortin PR, Clarke AE, Joseph L, Liang MH, Tanzer M, Ferland D, et al. Outcomes of total hip and knee replacement: Preoperative functional status predicts outcomes at six months after surgery. Arthritis Rheum. 1999;42:1722–8. doi: 10.1002/1529-0131(199908)42:8<1722::AID-ANR22>3.0.CO;2-R. [DOI] [PubMed] [Google Scholar]
- 47.Dyrstad SM, Hansen BH, Holme IM, Anderssen SA. Comparison of self-reported versus accelerometer-measured physical activity. Med Sci Sports Exerc. 2014;46:99–106. doi: 10.1249/MSS.0b013e3182a0595f. [DOI] [PubMed] [Google Scholar]
- 48.Neuhouser ML, Di C, Tinker LF, Thomson C, Sternfeld B, Mossavar-Rahmani Y, et al. Physical activity assessment: biomarkers and self-report of activity-related energy expenditure in the WHI. Am J Epidemiol. 2013;177:576–585. doi: 10.1093/aje/kws269. [DOI] [PMC free article] [PubMed] [Google Scholar]
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