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. Author manuscript; available in PMC: 2018 Feb 1.
Published in final edited form as: Prev Med. 2016 Dec 6;95:103–109. doi: 10.1016/j.ypmed.2016.11.025

Changes in Physical Activity, Sedentary Time, and Risk of Falling: The Women's Health Initiative Observational Study

Jennifer W Bea a, Cynthia A Thomson b, Robert B Wallace c, Chunyuan Wu d, Rebecca A Seguin e, Scott B Going b, Andrea LaCroix f, Charles Eaton g, Judith K Ockene h, Michael J LaMonte i, Rebecca Jackson j, W Jerry Mysiw k, Jean Wactawski-Wende l
PMCID: PMC5289299  NIHMSID: NIHMS839927  PMID: 27932054

Abstract

Falling significantly affects quality of life, morbidity, and mortality among older adults. We sought to evaluate the prospective association between sedentary time, physical activity, and falling among post-menopausal women aged 50–79 y recruited to the Women's Health Initiative Observational Study between 1993 and 1998 from 40 clinical centers across the United States. Baseline (B) and change in each of the following were evaluated at year 3 (Y3) and year 6 (Y6; baseline n=93,676; Y3 n=76,598; Y6 n=75,428): recreational physical activity (MET-h/wk), sitting, sleeping (min/d), and lean body mass by dual energy X-ray absorptiometry (subset N=6,475). Falls per year (0, 1, 2, ≥3) were assessed annually by self-report questionnaire and then dichotomized as ≤1 and ≥2 falls/year. Logistic regression models were adjusted for demographics, body mass index, fall history, tobacco and alcohol use, medical conditions, and medications. Higher baseline activity was associated with greater risk of falling at Y6 (18%; p for trend <0.0001). Increasing sedentary time minimally decreased falling (1% Y3; 2% Y6; p<0.05). Increasing activity up to ≥ 9 MET-h/wk (OR: 1.12, 95%CI: 1.03-1.22) or maintaining ≥ 9 MET-h/wk (OR: 1.20, 95% CI: 1.13-1.29) increased falling at Y3 and Y6 (p for trend <0.001). Adding lean body mass to the models attenuated these relationships. Physically active lifestyles increased falling among post-menopausal women. Additional fall prevention strategies, such as balance and resistance training, should be evaluated to assist post-menopausal women in reaching or maintaining levels of aerobic activity known to prevent and manage several chronic diseases.

Keywords: accidental falls, falls, exercise, menopause, sedentary lifestyle

Introduction

The propensity to fall increases with aging, often due to other age related issues, such as impaired vision, balance, and mental acuity (Rubenstein, 2006). Although many falls result in minor injuries, approximately 10% will result in fractures which are associated with significant morbidity and mortality in the aged (Gillespie et al., 2012). Reductions in falls among community dwelling older adults engaging exercise interventions offers hope (Gillespie et al., 2012), as does the protection against fracture with higher baseline physical activity demonstrated in the Women's Health Initiative (WHI) (Robbins et al., 2007), but overall, the association between physical activity and falls in the literature has been inconsistent (Clarke et al., 2015). Physical activity patterns over time may prove to be more predictive of falls than exercise interventions or assessment of physical activity at a single time point. Longitudinal changes in physical activity and body composition, which may mediate the falls benefit of physical activity through preservation of muscle mass (LaStayo et al., 2003), are needed to better understand their independent and joint roles in falls risk. However, because prospective studies on older adults typically do not have repeated prospective measures on these factors, they have yet to be fully explored with respect to incidence of falling.

In the United States, physical activity decreases dramatically in adulthood, stabilizing at relatively low levels in middle aged women (Caspersen et al., 2000). Low levels of physical activity have been associated with decreased muscle mass (Morley et al., 2001). Meanwhile, sedentary time, distinctly different than insufficient moderate to vigorous physical activity (Owen et al., 2010), increases with aging (Clark et al., 2010). High sedentary time may also aid in skeletal muscle decline and has been shown to be a risk factor for falling in studies with 1-2 years follow-up (Thibaud et al., 2012).

We sought to determine whether prospectively assessed physical activity patterns, including sedentary time, are associated with the risk of falling over several years and whether risk of falling is mediated by body composition. We hypothesized that decreasing physical activity over time would be associated with increased risk of falling among postmenopausal women (Figure 1). High sedentary time was also hypothesized to increase risk of falling.

Figure 1.

Figure 1

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Hypothesized mediation model among participants in the Women's Health Initiative Observational Study recruited between 1993 and 1998 from 40 clinical centers across the United States (n=93,676)

Methods

Study Population

The WHI Study recruited postmenopausal women aged 50-79 y at 40 WHI clinical centers across the United States between 1993 and 1998 to four clinical trials and an observational study (1998; Hays et al., 2003). Only women enrolled in the observational study were included in this analysis (N=93,676); body composition was measured in those enrolled at the Pittsburgh, PA; Birmingham, AL; and Tucson-Phoenix, AZ sites (N=6,475) (Chen et al., 2008). The protocol and consent forms were approved by each institutional review board at each site and all participants provided written informed consent. For the present study, measurements taken at baseline, year 3 and year 6 of follow-up were used. The average follow-up time for incident falls in this study was 54 months.

Physical Activity Assessment

The frequency, intensity, and duration of walking, as well as moderate and vigorous recreational physical activity, were assessed using a reliable and valid questionnaire. Test-retest reliability was 0.67 - 0.71 (weighted κ coefficient) for individual physical activity variables on the WHI questionnaire and the questionnaire assessed activity levels correlated well with accelerometry (r=0.73) in a subset of the WHI. (Eaglehouse et al., 2016; Johnson-Kozlow et al., 2007; Langer et al., 2003; Manson et al., 2002; Meyer et al., 2009; Nguyen et al., 2013). Energy expenditure (MET-h/wk) was computed, as previously published (Ainsworth et al., 2000; Sims et al., 2012).

Based on the continuous physical activity data, 4 categories of baseline physical activity were created: no physical activity (0 MET-h/wk), ≤ 3 MET-h/wk, 3.1 to 8.9 MET-h/wk, and ≥ 9 MET-h/wk. Participants were classified as physically inactive (0 MET-h/wk), insufficiently active (>0 to < 9 MET-h/wk), and active (≥ 9 MET-h/wk of moderate-vigorous intensity physical activity) in approximate alignment with recommended physical activity levels (2008). Change in physical activity from baseline to year 3 and year 6 was categorized as follows.

  1. change/inactive: remaining in the inactive or insufficiently active category at baseline and follow-up

  2. increased activity: inactive or insufficiently active at baseline, but increased to ≥ 9 MET-h/wk at follow-up

  3. active maintainer: maintained ≥ 9 MET-h/wk at baseline and follow-up

  4. decreased/inactive: decreased physical activity categories from sufficiently active to insufficiently active or inactive, or decreased from insufficiently active to inactive category

Sedentary time was quantified separately by two questions in the questionnaire that asked how much time was spent sitting per day and lying down per day (hrs/d). Sedentary time is not equivalent to the inactive or insufficiently active terms above.

Anthropometry and Body Composition Assessment

Height and weight were measured without shoes on a wall-mounted stadiometer to the nearest 0.1 cm and balance-beam scale to the nearest 0.1 kg, respectively. BMI was calculated as weight (kg)/height (m)2. Body composition was determined by performing dual energy X-ray absorptiometry scans (DXA; QDR2000, 2000+, or 4500W; Hologic Inc, Bedford, MA) at 3 WHI clinical centers (Pittsburgh, PA; Birmingham, AL; and Tucson-Phoenix, AZ), each using the rigorous WHI quality assurance program (Chen et al., 2005). Measurements included both whole body and regional bone mineral density, lean body mass, and fat mass. Calibration equations were developed when an older DXA machine was replaced with a newer model (QDR2000 to QDR4500W) (Chen et al., 2005). Participants who completed the baseline and at least year 3 or year 6 follow-up visits were included in this analysis.

Assessment of Falls

A self-report medical history questionnaire that included the following question was collected at baseline and by mail annually: “During the past 12months, how many times did you fall and land on the floor or ground: none, 1 time, 2 times, 3 or more times?” Participants were asked not to include falls due to sports activities such as snow- or water-skiing or horseback riding.(Anderson et al., 2003)

Assessment of Covariates

Years since menopause were determined by last reported menstrual bleeding, time of bilateral oophorectomy, or initiation of menopausal hormone therapy. Self-report questionnaires were used to obtain information on demographics, medical history, medications, smoking and alcohol use, and prior hormone therapy use at baseline. Diet and physical function were assessed by a validated food frequency questionnaire (Block et al., 1990) and the Medical Outcomes Study Scale (Ware and Sherbourne, 1992), respectively.

Statistical Analysis

Descriptive statistics were computed and tests for significant differences were performed using analysis of variance (ANOVA) for continuous variables and Chi Squared tests for categorical variables. Logistic regression models were developed to determine the odds of falling based on baseline physical activity category and sedentary time, as well as change in physical activity (categories and continuous) over three and six years. In alignment with a prior WHI publications, (Bea et al., 2011; Cauley et al., 2007; Chen et al., 2004) a binary variable of ≥2 falls per year was used for risk of falling in all models. A history of ≥2 falls per year is a significant predictor of a recurrent faller (Stalenhoef et al., 2002) and higher fall rates are associated with frailty related fractures (Schwartz et al., 2005). Factors that have been associated with falling and body composition in the literature were selected a priori as covariates, including age, BMI, ethnicity, education, years since menopause, tobacco and alcohol use, number of falls at baseline, diabetes, hypertension, fainting, general health, physical function, and medication use including hormone therapy, beta blocker, antianxiety agent, hypnotic, narcotic, and sedative use. Geographic region, by latitude of the responsible clinical center at the time of enrollment, waist circumference, and total body fat did not significantly affect the models, so were not included. Exclusions included those with prior stroke, peripheral artery disease, multiple sclerosis, and Parkinson's Disease, or missing covariates. Change in activity models were stratified by body mass index (BMI ≥ 30kg/m2) due to previous associations with falls (Beck et al., 2009).

Results

Overall, the mean physical activity level for the cohort was 13.7 (±14.4) MET-h/wk at baseline, 13.6 (±14.6) MET-h/wk at year 3, and 13.1 (±14.2) MET-h/wk at year 6. The change in physical activity across the cohort was -0.4 (±12.4) MET-h/wk from baseline to year 3 and -0.9 (±13.5) MET-h/wk from baseline to year 6. Total sedentary time (hrs/d spent sitting or sleeping) was 15.0 (±4.2) hrs/d at baseline, 14.7 (±3.7) hrs/d at year 3 and 14.7(±3.8) hrs/d at year 6. Inactive time was reduced by -0.38 (±3.9) from baseline to year 3 and remained stable at year 6.

Baseline activity levels varied by race/ethnicity, highest level of education, years postmenopausal, and baseline fall history. There were more obese individuals in the inactive group. The less-active and non-active groups were more likely to report medical conditions, medication use, smoking, and lower alcohol consumption compared to others. Women in the highest category of physical activity had the highest lean mass at baseline (Table 1) and follow-up, however, they decreased physical activity and lost greater absolute appendicular lean mass over time compared to others (Table 2).

Table 1.

Baseline demographic and medical history characteristics by physical activity group among participants in the Women's Health Initiative Observational Study recruited between 1993 and 1998 from 40 clinical centers across the United States (n=93,676)

0METs (N=12,636) >0-3METs (N=9,954) 3.1-8.9METs (N=21,192) ≥9METs (N=48,843) p-value
N % N % N % N %
Age group at screening 50-59 4215 33.36 3142 31.57 6610 31.19 15411 31.55 <0.001
60-69 5341 42.27 4323 43.43 9147 43.16 21925 44.89 .
70-79 3080 24.37 2489 25.01 5435 25.65 11507 23.56 .
Race/ ethnicity White 9707 76.82 7823 78.59 17456 82.37 42223 86.45 <0.001
Black 1612 12.76 1132 11.37 1874 8.84 2943 6.03 .
Hispanic 692 5.48 492 4.94 868 4.10 1423 2.91 .
American Indian 80 0.63 63 0.63 94 0.44 179 0.37 .
Asian/Pacific Islander 351 2.78 300 3.01 580 2.74 1422 2.91 .
Unknown 194 1.54 144 1.45 320 1.51 653 1.34 .
Education 0-8 years 386 3.08 234 2.37 380 1.81 476 0.98 <0.001
Some high school 766 6.11 519 5.26 836 3.98 1116 2.30 .
High school diploma/GED 2841 22.67 1993 20.18 3745 17.82 6370 13.15 .
School after high school 4817 38.44 3875 39.24 7875 37.46 16999 35.09 .
College degree or higher 3722 29.70 3255 32.96 8184 38.93 23484 48.48 .
Years < 10 yrs 3539 29.46 2712 28.72 6086 29.90 14849 31.39 <0.001
menopausal >=10 yrs 8472 70.54 6730 71.28 14266 70.10 32453 68.61 .
Smoking status Never 6332 50.68 5198 52.96 11077 52.84 24026 49.76 <0.001
Past 4878 39.04 3769 38.40 8422 40.17 22134 45.84 .
Current 1284 10.28 848 8.64 1466 6.99 2128 4.41 .
Alcohol intake Non Drinker 7028 55.71 5111 51.42 9327 44.06 17292 35.45 <0.001
<= 1 drink/day 4437 35.17 3913 39.37 9522 44.98 24292 49.80 .
> 1 drink/day 1150 9.12 915 9.21 2319 10.96 7200 14.76 .
Treated diabetes (pills or shots) No 11797 93.50 9285 93.43 20191 95.40 47383 97.12 <0.001
Yes 820 6.50 653 6.57 973 4.60 1403 2.88 .
History of hypertension Never hypertensive 7454 59.71 5937 60.31 13410 63.95 34250 70.68 <0.001
Untreated hypertensive 1123 9.00 826 8.39 1742 8.31 3613 7.46 .
Treated hypertensive 3906 31.29 3081 31.30 5816 27.74 10595 21.86 .
Hormone Therapy use Never used 5635 44.63 4502 45.26 8875 41.91 18527 37.97 <0.001
Past user 1924 15.24 1497 15.05 3190 15.06 7147 14.65 .
Current user 5067 40.13 3948 39.69 9110 43.02 23122 47.39 .
Beta blockers use No 11399 90.21 9025 90.67 19174 90.48 45422 93.00 <0.001
Yes 1237 9.79 929 9.33 2017 9.52 3421 7.00 .
Antianxiety agents use No 12035 95.24 9531 95.75 20387 96.21 47423 97.09 <0.001
Yes 601 4.76 423 4.25 804 3.79 1420 2.91 .
Hypnotics use No 12197 96.53 9652 96.97 20578 97.11 47612 97.48 <0.001
Yes 439 3.47 302 3.03 613 2.89 1231 2.52 .
Narcotics use No 12167 96.29 9651 96.96 20732 97.83 48115 98.51 <0.001
Yes 469 3.71 303 3.04 459 2.17 728 1.49 .
Sedative use No 12501 98.93 9854 99.00 21015 99.17 48458 99.21 0.007
Yes 135 1.07 100 1.00 176 0.83 385 0.79 .
Fainted, last 12 months No 12157 97.05 9599 97.28 20507 97.44 47406 97.64 0.001
Yes 369 2.95 268 2.72 539 2.56 1144 2.36 .
Prior falls, last 12 months None 8390 66.87 6585 66.50 14184 67.35 33297 68.51 <0.001
1 time 2498 19.91 1988 20.08 4253 20.19 9524 19.60 .
2 times 1023 8.15 858 8.66 1787 8.48 3851 7.92 .
3 or more times 635 5.06 471 4.76 837 3.97 1930 3.97 .
Physical function > 90 No 9585 77.64 7463 76.60 14252 68.40 25128 52.28 <0.001
Yes 2760 22.36 2280 23.40 6584 31.60 22935 47.72 .
Body Mass Index (kg/m2), baseline <25 3376 27.12 2881 29.24 7744 36.95 23408 48.48 <0.001
25 - <30 3988 32.03 3268 33.17 7461 35.60 16408 33.99 .
>=30 5085 40.85 3704 37.59 5755 27.46 8464 17.53 .
Body composition Mean SD Mean SD Mean SD Mean SD p-value
Whole body lean mass (%) 54.60 7.42 54.06 6.88 56.25 7.29 58.70 7.34 <0.001
Appendicular lean mass (kg) 15.05 2.98 14.83 3.12 14.47 2.85 14.26 2.46 <0.001
Activity
Total Physical activity, (MET-hrs/wk) 0.00 0.00 1.62 0.69 5.72 1.74 23.15 13.94 <0.001
Time spent sitting (hrs/d) 7.94 3.72 7.57 3.43 7.40 3.36 6.87 3.19 <0.001
Time spent sleeping (hrs/d) 7.76 2.60 7.79 2.47 7.83 2.33 7.92 2.18 <0.001
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Table 2.

Change in lean body mass, energy expenditure and physical activity from baseline to years three and six of follow-up by physical activity group among participants in the Women's Health Initiative Observational Study recruited between 1993 and 1998 from 40 clinical centers across the United States (n=93,676)

Inactive 0 METs (>0-3) METs (3.1- 8.9) METs >= 9 METS p-value
Mean SD Mean SD Mean SD Mean SD
Change from Baseline to Year 3
Whole body lean mass (%) -0.46 3.19 -0.37 3.31 -0.60 3.18 -0.87 3.17 <0.001
Appendicular lean mass (kg) -0.60 3.19 -0.41 3.21 -0.74 3.26 -1.17 3.47 <0.001
Physical activity, (MET-hrs/wk) 3.54 7.13 3.56 7.51 2.56 8.61 -3.29 14.58 <0.001
Time spent sitting (hrs/d) -0.49 3.41 -0.48 3.25 -0.45 3.17 -0.37 3.01 <0.001
Time spent sleeping (hrs/d) 0.19 2.62 0.13 2.56 0.05 2.39 -0.04 2.23 <0.001
Change from Baseline to Year 6
Whole body lean mass (%) -0.23 4.43 -0.06 3.89 -0.55 3.87 -1.02 3.85 <0.001
Appendicular lean mass (kg) -1.13 4.16 -1.02 3.31 -1.27 3.67 -2.23 3.78 <0.001
Physical activity, (MET-hrs/wk) 4.27 7.84 4.25 8.49 2.84 9.62 -4.71 15.32 <0.001
Time spent sitting (hrs/d) -0.53 3.68 -0.57 3.46 -0.53 3.35 -0.42 3.20 <0.001
Time spent sleeping (hrs/d) 0.25 2.69 0.22 2.54 0.13 2.45 0.03 2.27 <0.001
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Overall, the risk of falling was significantly increased (18%) over six, but not three years of follow up among those with ≥9MET-h/wk of physical activity at baseline compared to being inactive at baseline (p for trend < 0.001; Table 3). However, when stratified on BMI, the non-obese women were at 12% greater risk of falling over three years if they were active as compared to their inactive counterparts (p for trend = 0.04).

Table 3.

Baseline physical activity and falling at years three and six among participants in the Women's Health Initiative Observational Study recruited between 1993 and 1998 from 40 clinical centers across the United States (n=93,676)

Non-Fallers Fallers* Odds Ratio 95% CI p value
Three Years Follow-up
All 0METs 8871 1034 . . . .
>0-3METs 7041 860 0.95 (0.86, 1.05) 0.02
3.1- 8.9METs 15689 1757 0.95 (0.87, 1.03) .
≥9METS 37886 3460 1.04 (0.96, 1.12) .
BMI≥30 0METs 3482 458 . . . .
>0-3METs 2510 383 0.85 (0.73, 0.99) 0.10
3.1- 8.9METs 4048 568 0.86 (0.75, 0.99) .
≥9METS 6143 751 0.93 (0.81, 1.06) .
BMI<30 0METs 5389 576 . . . .
>0-3METs 4531 477 1.04 (0.91, 1.18) 0.04
3.1- 8.9METs 11641 1189 1.02 (0.91, 1.14) .
≥9METS 31743 2709 1.12 (1.01, 1.24) .
Six Years Follow-up
All 0METs 8556 1085 . . . .
>0-3METs 6843 859 1.01 (0.92, 1.12) <0.001
3.1- 8.9METs 15389 1735 1.04 (0.95, 1.13) .
≥9METS 37579 3382 1.18 (1.09, 1.27) .
BMI≥30 0METs 3332 510 . . . .
>0-3METs 2470 347 1.11 (0.95, 1.29) 0.12
3.1- 8.9METs 3995 523 1.10 (0.96, 1.26) .
≥9METS 6126 712 1.17 (1.03, 1.34) .
BMI<30 0METs 5224 575 . . . .
>0-3METs 4373 512 0.95 (0.84, 1.09) <0.001
3.1- 8.9METs 11394 1212 1.00 (0.90, 1.12) .
≥9METS 31453 2670 1.16 (1.05, 1.28) .
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a

Faller≥2falls per year. All models were adjusted for age, BMI (Body Mass Index), ethnicity, education, years since menopause, smoking, alcohol, number of falls at baseline, diabetes, hypertension, fainted, general health, hormone status, Beta blocker, Antianxiety agents, Hypnotics, narcotics, sedatives, physical function >= 90.

The odds of falling increased by 1% with increased walking at both three and six years (p=0.02) and increased vigorous activity at three, but not at six years, when evaluating change in activity as a continuous variable. Increased sitting slightly decreased falls over 6 years (OR: 0.98, 95%CI: 0.98-0.99, p<0.001), while time spent lying down decreased odds of falling by 2% and 3% at three and six years, respectively (p<0.001). Stratification by obesity did not significantly affect these results (data not shown).

In categorical analyses, increased or maintained adequate physical activity (≥9MET-h/wk) significantly increased odds of falling, by 12% and 20%, respectively, compared to those that remained inactive between baseline and year three (Table 4; p for trend <0.001). Models stratified by obesity were consistent with results from the entire cohort. After 6 years, the odds of falling increased to 30% for those that maintained a physically active lifestyle overall (p for trend <0.001), but 36% among the non-obese (p for trend <0.001).

Table 4.

Odds falling based on change in physical activity (METs/wk) categories among participants in the Women's Health Initiative Observational Study recruited between 1993 and 1998 from 40 clinical centers across the United States (n=93,676)

Base Model Change in % Lean Body Mass Adjusted
Non-Fallers Fallers* OR 95% CI p value Non-Fallers Fallers* OR 95% CI p value
Baseline to Year 3
All No change/ Inactive 22466 2721 . . . . 1528 185 . . . .
Increase 7711 774 1.12 (1.02, 1.22) <0.001 481 41 1.35 (0.93, 1.97) 0.010
Active maintainer 28003 2281 1.21 (1.13, 1.29) . 1362 120 1.16 (0.88, 1.52) .
Decrease 8929 1066 0.95 (0.88, 1.03) . 538 82 0.73 (0.54, 0.98) .
BMI≥30 No change/ Inactive 7560 1100 . . . . 500 78 . . . .
Increase 1878 237 1.13 (0.96, 1.32) 0.03 126 13 1.44 (0.74, 2.81) 0.60
Active maintainer 3777 415 1.15 (1.01, 1.30) . 192 28 0.93 (0.56, 1.54) .
Decrease 2126 313 0.92 (0.80, 1.07) . 126 19 0.84 (0.47, 1.52) .
BMI<30 No change/ Inactive 14906 1621 . . . . 1020 106 . . . .
Increase 5833 537 1.12 (1.00, 1.24) <0.001 351 28 1.33 (0.83, 2.12) 0.006
Active maintainer 24226 1866 1.23 (1.14, 1.33) . 1160 90 1.23 (0.88, 1.71) .
Decrease 6803 753 0.96 (0.87, 1.06) . 408 62 0.66 (0.46, 0.95) .
Baseline to Year 6
All No change/Inactive 20943 2588 . . . . 1312 157 . . . .
Increase 8278 841 1.11 (1.02, 1.21) <0.001 434 44 1.04 (0.72, 1.51) 0.72
Active maintainer 25906 2007 1.30 (1.22, 1.39) . 1136 92 1.19 (0.88, 1.60) .
Decrease 10543 1218 1.03 (0.95, 1.11) . 567 68 1.03 (0.74, 1.42) .
BMI≥30 No change/Inactive 6979 1006 . . . . 424 62 . . . .
Increase 2127 273 1.04 (0.90, 1.21) 0.30 125 11 1.51 (0.74, 3.08) 0.65
Active maintainer 3361 369 1.12 (0.98, 1.28) . 146 16 1.18 (0.63, 2.22) .
Decrease 2472 309 1.11 (0.96, 1.28) . 148 22 0.94 (0.53, 1.67) .
BMI<30 No change/ Inactive 13964 1582 . . . . 876 94 . . . .
Increase 6151 568 1.15 (1.03, 1.27) <0.001 308 33 0.91 (0.58, 1.41) 0.72
Active maintainer 22545 1638 1.36 (1.26, 1.47) . 980 75 1.16 (0.82, 1.66) .
Decrease 8071 909 1.01 (0.92, 1.11) . 414 46 1.05 (0.70, 1.57) .
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a

Faller≥2falls per year. All models were adjusted for age, BMI (Body Mass Index), ethnicity, education, years since menopause, smoking, alcohol, number of falls at baseline, diabetes, hypertension, fainted, general health, hormone status, Beta blocker, Antianxiety agents, Hypnotics, narcotics, sedatives, physical function ≥90.

When adjusted for change in lean mass, the pattern of increased odds of falling with increasing physical activity was similar to that of the entire cohort for the first three years (p for trend = 0.01), while decreased physical activity appeared to have a protective effect against falling when adjusting for changes in lean mass. Those with a BMI < 30kg/m2 drove the relationship between decreases in physical activity and falling over 3 years. This relationship did not persist over six years.

Discussion

Contrary to our hypothesis, we found that active lifestyles and increases in physical activity over time were associated with increased fall risks among postmenopausal women aged 50-79 at baseline. Although reduction in falls has been supported by several exercise interventions (Gillespie et al., 2012), the positive studies tended to include multifactorial interventions (i.e. combination of physical activity, balance training, home hazards assessment, medication assessment, technical aids, etc.) and were typically limited to adults older than those in the WHI and those at high risk of falling. Community dwelling adults often do not employ multifactorial activity programs or activities designed to improve physical function (Lewis et al., 2015). Large longitudinal studies examining physical activity associations with falls in community dwelling older adults have suggested that physical activity may increase fall risk, although the risk is likely modified by type of activity and level of physical function or mobility (Jefferis et al., 2015; Lewis et al., 2015; Mertz et al., 2010; Peeters et al., 2010). Walking, in particular, the physical activity often selected by older women (Booth et al., 1997; Garcia et al., 2015; Sorkin et al., 2015), has been problematic for older adults in other studies (Mertz et al., 2010; Nikander et al., 2011 [Feb 15 2011 Epub ahead of print]). Postmenopausal women who spent greater time walking (>3hrs/wk) in a large, five-year study (N=2780) experienced more fractures, which authors suggest may be attributable to increased falls (Nikander et al., 2011 [Feb 15 2011 Epub ahead of print]).

In spite of these results, the benefits of physical activity for prevention and management of most of the prevalent chronic diseases in the United States, including osteoporosis, diabetes, cardiovascular disease, and some cancers (2008), likely outweigh the risks of falling. Further, exercise has been shown to reduce the risk of injury given a fall (Uusi-Rasi et al., 2015) and those who are more mobile prior to injury tend to have better outcomes (Thorngren et al., 2005). The minimal protection against falls due to greater sedentary time herein should be interpreted with caution, as well, as cardiovascular and other health benefits would be sacrificed with reduced activity. The distribution of medical conditions, medications, and falls across physical activity categories at baseline imply that the women self-limited physical activity if balance impairing medications, chronic conditions, or prior falls were present, as noted by others (2011; Bruce et al., 2002).

The results support the notion that aerobic activity alone among older adults is not enough to prevent falling in older populations (Clarke et al., 2015; Voukelatos et al., 2015). The increased opportunities for interaction with environmental hazards, and therefore greater opportunities for falling (Feldman and Chaudhury, 2008), need to be counterbalanced by the ability to adapt to these challenges. We would suggest that the complimentary strength and balance activities recommended by both the Physical Activity Guidelines for Americans (2008) and the Clinical Practice Guideline for Prevention of Falls in Older Persons (2011) be further publicized and evaluated. The adoption rate and efficacy of these multifactorial recommendations longitudinally (Clarke et al., 2015), along with suggested environmental strategies in older adults (Feldman and Chaudhury, 2008) requires further exploration, though early pilot work suggests an effective multifactorial fall prevention strategy can be habituated (Fleig et al., 2016).

The similarity in results with and without lean mass adjustment aligns with the lack of association between change in lean mass and physical activity demonstrated in the WHI previously (Sims et al., 2013) and further supports the need for activities beyond aerobic training to enhance physical function and potentially muscle quality, rather than lean mass per se. In support of this assertion, the Hispanic Established Population for the Epidemiologic Study of the Elderly (H-EPESE; N=1011 aged ≥75yrs) recently demonstrated that participants with high physical activity and low physical function had a greater fall risk than those with high physical activity and high physical function (Lewis et al., 2015). However, in The British Regional Heart Study (N=3137) those with initial low mobility participating benefited from increasing activity, while those without mobility limitations did not (Jefferis et al., 2015), suggesting the need to better understand the utility of initial mobility screening and activity planning in older adults.

Limitations

Statistical adjustment for potential confounding factors, may not fully account for differences between activity groups. Additionally, self-report physical activity measures, although validated herein and practical in large cohorts, have limitations. We could not separate falls occurring during activity from other falls which might be differentially related with physical activity and sedentary time. Objective measures of physical function were not available across this subset of WHI and fall data collection did not fully conform to Prevention of Falls Network Europe recommendations due to study completion prior to the consensus statement (Lamb et al., 2005). The study is not generalizable to younger women or men.

Conclusion

Physically active lifestyles increased falling among post-menopausal women. Additional fall prevention strategies, such as balance and resistance training, should be evaluated to assist post-menopausal women in reaching or maintaining the level of aerobic activity known to prevent and manage several chronic diseases.

Highlights.

Among postmenopausal women:

  • Increasing physical activity (PA) may be associated with a greater risk of falling.

  • Increasing sedentary time may slightly decrease risk of falling.

  • Falls risk must be weighed against PA benefits for prevention of chronic diseases.

  • Further research is needed to improve safety and support continued PA with aging.

Acknowledgments

We are thankful for the contribution of the WHI Investigators and staff at the clinical centers, clinical coordinating center, and project office.

Funding: This work was supported by National Cancer Institute (CA023074); and the WHI program which is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C).

Abbreviations

ANOVA

analysis of variance

BMI

body mass index

DXA

dual energy X-ray absorptiometry

MET

metabolic equivalent of task

H-EPESE

Hispanic Established Population for the Epidemiologic Study of the Elderly

SD

standard deviation

WHI

Women's Health Initiative

Footnotes

Disclosure Statement: The authors have declared no conflicts of interest.

Short List of WHI 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

Women's Health Initiative Memory Study: (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker

For a list of all the investigators who have contributed to WHI science, please visit: https://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Long%20List.pdf

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