Falls, particularly in older adults, are associated with significant morbidity and mortality (12). Several factors are associated with increased incidence of falls, such as older age (19), gender (5), race-ethnicity (13), medications (18), comorbid illness (9), visual acuity (8), and hearing sensitivity (25). Fear of falling is also an important risk factor for falls and has been linked to adverse psychological, physical and functional changes in older adults (3). Falls and fear of falling are complex and interrelated constructs with each being considered a risk factor for the other. Additionally, individuals with dysfunctional balance are more likely to fall and tend to be less active (21,15), with this inactivity increasing the incidence of falls through various mechanisms, such as muscle atrophy, muscle weakness, reduced flexibility, and gait impairments (2,4,11,17). As a result, regular participation in safe forms of physical activity may help to prevent falls and reduce societal costs associated with injurious falls (22).
Most balance and fall prevention interventions have been conducted in community, institutional, residential care, or other clinic-based populations (14,23). To our knowledge, no population-based studies have examined the association between objectively measured physical activity and balance in a nationally representative sample. As a result, previous studies may lack generalizability and are limited by the use of self-report physical activity methodology, which is prone to considerable measurement error (20). Therefore, the primary purpose of this study was to examine the association between objectively measured physical activity (i.e., accelerometry technology) and balance in a nationally representative sample of U.S. adults. A particular interest of this study was to examine whether light-intensity physical activity, in addition to moderate-to-vigorous physical activity (MVPA), is associated with balance. If so, this may have strong practical implications for strength and conditioning professionals as light-intensity physical activity may be a more palatable and feasible intensity to promote among older individuals at risk of falls and/or have a fear of falling.
Experimental Approach to the Problem
Data from the 2003–2004 National Health and Nutrition Examination Survey (NHANES) were used, as this is the only NHANES cycle with both accelerometry and balance data. National Health and Nutrition Examination Survey is an ongoing survey conducted by the National Center for Health Statistics, which evaluates a representative sample of non-institutionalized U.S. civilians, selected by a complex, multistage probability design.
Among participants in the 2003–2004 NHANES, 3,299 were eligible for the accelerometry and balance component (age range: 40-85 yrs). After excluding those with missing balance and covariate data (i.e., age, gender, education, race-ethnicity, body mass index (BMI), comorbidity index, vision, hearing, and medication use), 2,406 participants remained. Among these, 575 were excluded because of insufficient accelerometry data (i.e., <4 days of 10+ hours per day of monitoring), which left an analytic sample of 1,831 adult participants. Previous studies have also shown a high number of missing/incomplete accelerometry data and have demonstrated potential biases associated with incomplete data (10). As a result, Table 1 shows characteristics of the analyzed sample (n = 1,831) compared with those excluded because of insufficient accelerometry data (n = 585). Overall, and in this sample, those included in the analyses were similar to those excluded with the exception of education and vision. Excluded participants were less educated (38.7 vs. 46.2% had some college or more) and had worse vision (49.2 vs. 41.6% had fair or worse vision).
All procedures for data collection were approved by the National Center for Health Statistics Ethics Review Board (no university institutional review board approval is needed), and all participants provided written informed consent before data collection. National Health and Nutrition Examination Survey data are publically accessible online (http://www.cdc.gov/nchs/).
Assessment of Balance
Participants aged 40 years and older were eligible for the balance assessment. For safety precautions, participants were excluded if they felt unable to stand on their own, had current symptoms of dizziness or lightheadedness, weighed more than 275 lbs, could not fit into the standardized safety gait belt, required a leg brace to stand unassisted, or had a foot or leg amputation.
Before balance testing, participants completed a questionnaire regarding their subjective views on difficulty with falling in the past 12 months. Specifically, they were asked, “During the past 12 months, have you had difficulty with falling?” The questionnaire contained no items on actual falls or fall frequency.
Balance testing consisted of using the modified Romberg Test of Standing Balance on firm and compliant support surfaces. This test evaluated the participants ability to stand unassisted under 4 different conditions (ordered in increasing levels of difficulty) designed to test sensory inputs from the vestibular system, vision, and proprioception: test 1—eyes open, firm surface; test 2—eyes closed, firm surface; test 3—eyes open, compliant surface; and test 4—eyes closed, compliant surface. Participants were allowed 2 trials for each condition. For all tests, balance was scored as pass or fail. With tests 1 and 2 lasting 15 seconds and tests 3 and 4 lasting 30 seconds, test failure was defined as the participant needing to open their eyes, moving their arms or feet to increase stability, or beginning to fall or requiring assistance to maintain balance. For this study, and similar to others (1), participants were classified as having dysfunctional balance if they failed any of the 4 test conditions. Functional balance, in contrast, was operationally defined as successful completion of all 4 of the test conditions.
Assessment of Physical Activity
Participants who were able to walk were asked to wear an ActiGraph 7164 accelerometer on their right hip for 7 days. Accelerometers were affixed to an elastic belt that was worn around the participant's waist near the iliac crest. Participants were asked to wear the accelerometer during all activities except water-based activities and sleeping. The accelerometer measured the frequency, intensity, and duration of physical activity by generating an activity count proportional to the measured acceleration. Estimates for physical activity were summarized in 1-minute time intervals. Minutes with activity counts ≥2,020 were classified as MVPA (24), with light-intensity physical activity defined as activity counts between 100 and 2019. Only those participants with at least 4 days of 10 or more hours per day of accelerometer wear time were included in the analyses to make sure that data adequately captured habitual physical activity patterns (24). To monitor the amount of time the device was worn, nonwear was defined by a period of a minimum of 60 consecutive minutes of zero activity counts, with the allowance of 1–2 minutes of activity counts between 0 and 100 (24).
Measurement of Covariates
Information about age (binned by decade), gender, race/ethnicity, and education were obtained from questionnaires. Participants were classified as having 0 or 1+ comorbidities based on self-report of having a history of coronary heart disease, stroke, cancer, arthritis, diabetes, kidney disease, or hypertension. Participants self-reported their vision and hearing function, with vision categorized as excellent, good, fair, poor, or very poor, with hearing function defined as good, a little trouble, lot of trouble, or deaf. Participants also indicated whether any potential balance problems were a result of medication they were taking. Lastly, BMI was calculated from measured weight and height (kg·m−2).
All statistical analyses were performed using procedures from sample survey data using STATA (StataCorp., version 12.0, College Station, TX) to account for the complex survey design used in NHANES. To account for oversampling, non-response, non-coverage, and to provide nationally representative estimates, all analyses included the use of appropriate survey sample weights, clustering and primary sampling units. In an effort to maintain nationally representative estimates, the sample weights for those with 4 or more days of valid accelerometry data were ratio-adjusted to maintain the age, sex, and race-ethnicity distribution of the full sample.
Means were computed for continuous variables and proportions were computed for categorical variables. To examine the association between physical activity (independent variable) and balance status, a multivariable logistic regression model was computed. Similarly, a multivariable logistic regression was used with self-reported difficulty with falling serving as the outcome variable. Moderate-to-vigorous physical activity was log-transformed because it failed tests of normality. Model covariates included age, gender, education, race-ethnicity, BMI, comorbidity index, vision, hearing, and medication use. All covariates were entered into the model at the same time as there was no evidence of multicollinearity based on correlations <0.8 between covariate pairs (max observed correlation <0.40), mean variance inflation factor <6 (observed mean = 1.1), individual variance inflation factors <10 (highest observed = 1.7), and tolerance statistics >0.1 (all observed to be >0.50). Statistical significance was established p ≤ 0.05.
Physical activity estimates across balance status and difficulty with falls, respectively, are shown in Figures 1 and 2. Participants with dysfunctional balance engaged in less light-intensity physical activity than those with functional balance (319.8 vs. 352.5 min·d−1; p ≤ 0.05) (Figure 1). Similarly, those with dysfunctional balance engaged in less MVPA than those with functional balance (16.1 vs. 22.8 min·d−1; p ≤ 0.05) (Figure 1). Participants who had difficulty with falling within the past 12 months engaged in less light-intensity physical activity than those who self-reported not having difficulty with falling (295.0 vs. 341.0 min·d−1; p ≤ 0.05). Similarly, participants who had difficulty with falling within the past 12 months engaged in less MVPA than those without difficulty (9.0 vs. 20.5 min·d−1; p ≤ 0.05).
Table 2 shows the odds of having functional balance based on physical activity levels. For every 60-minute increase in light-intensity physical activity, participants were 10% (p = 0.04) more likely to have functional balance. Similarly, for every 1-minute increase in log-transformed MVPA, participants were 24% (p = 0.04) more likely to have functional balance.
Table 3 shows the odds of having difficulty with falling in the past 12 months based on physical activity levels. Light-intensity physical activity was not significant (p = 0.06); however, for every 1-minute increase in log-transformed MVPA, participants were 41% (p = 0.009) less likely to have difficulty with falling in the past 12 months.
The primary purpose of this study was to examine the association between objectively measured physical activity and balance in a nationally representative sample of U.S. adults. Findings of this study confirm intervention studies in that individuals engaging in higher levels of accelerometer-assessed physical activity (both light-intensity and MVPA) were more likely to have functional balance. Additionally, higher levels of MVPA were also associated with a reduced likelihood of having difficulty with falling.
Many older adults may limit their regular physical activity for a host of reasons that might include but are not limited to fatigue, fear of falling, and the development of age related conditions such as osteoarthritis. Balance is an important attribute required for safe mobility and is dependent on a number of interrelated mechanisms and interdependent systems. Although this study does not confirm preventive effects of physical activity on the number or frequency of actual falls, successful performance by individuals (i.e., receiving a “pass” score) on the balance tests performed in this study does appear to provide an objective relationship between regular physical activity and balance performance.
A recent Cochrane Review (6) on interventions for preventing falls in community dwelling older people concluded that there was no evidence of any effects for cognitive behavioral interventions on rate of falls or risk of falling. However, this same Cochrane Review did report benefits of group and home-based exercise programs by reducing the rate of falls and risks of falling. Educational programs developed to increase knowledge of risk factors and promote positive behaviors have been reported to have only marginal benefits, and the findings are inconclusive at best for actually preventing falls. The benefits of conducting standardized individual risk assessments, like the balance tests performed in this study, may be a critical component in helping individuals truly understand their functional abilities and limitations when they are provided information specific to age and gender related normative values. Additionally, physical performance assessments using standardized tests such as the Timed Up and Go, Timed Sit to Stand, and Four Square Step Test, can also establish baseline function, increase individual awareness of deficits, and guide effective intervention strategies. One program that has demonstrated effectiveness is the Matter of Balance intervention program (7). The Matter of Balance Program (7) incorporates light-intensity physical activity exercises and balance training, a cognitive-behavior intervention and social support. The 8-session program includes specific elements that promote the view that falls and fear of falling are controllable, sets realistic goals for gradually increasing activity, addresses environmental factors to reduce falls risk and promotes light-intensity physical activity to increase strength and balance.
A limitation of this study was the inability to determine number of actual falls or fall frequency. Another limitation includes the cross-sectional study design, rendering causal relationships not possible. It is possible that individuals with better balance engaged in more physical activity because of enhanced functional capacity and possibly having greater confidence in participating in instrumental activities of daily living; however, it is plausible to suggest that increasing activity behavior may play a causal role in increasing balance and reducing falls, as previous intervention studies have shown such an effect and have also demonstrated potential mechanisms (e.g., improve gait function, general mobility, and increase lower limb strength) to elucidate this relationship. Despite these noted limitations, major strengths of this study include the use of an objective measure of physical activity, an objective measure of balance, and using a nationally representative sample to examine this relationship.
In conclusion, the results of this study contribute to the existing literature on the important relationship between falls risk and physical activity levels. Regular physical activity, regardless of intensity, may have health benefits for older adults and is associated with functional balance. Falls are a major public health problem and have serious implications on health care costs associated with falls, on quality of life and may threaten community dwelling older adults' independence. As the risk of falls generally increases with advancing age, strategies are needed to identify the risk factors and incorporate effective interventions aimed at recognition and prevention. Important to any prevention program is the regular, simple, and cost effective methods of screening balance. Many of the balance measures such as the Romberg test described in this study meet these criteria, but as Pardasaney et al. (16) reported in a recent systematic analysis study, these balance measures may not adequately assess the postural control demands in daily activities that involve dynamic stability, changing environments, multi-tasking, object interaction, or obstacle negotiation. Future studies are needed to further examine performance indicators on individual balance measures and their relationship with physical activity levels.
Findings from this study demonstrate that both light-intensity physical activity and MVPA were associated with better functional balance among a nationally representative sample of U.S. adults. Our finding that light-intensity physical activity is particularly important as light-intensity physical activity, compared with MVPA, may be a more feasible and palatable approach to promoting physical activity among individuals at risk for falling (e.g., elderly). This is an encouraging finding as most physical activity related research has focused on MVPA, with less research demonstrating a beneficial effect of light-intensity physical activity. Based on these findings, health care professionals should encourage light-intensity physical activity, and when appropriate, MVPA, to help reduce injurious falls. Other forms of exercise, such as strength training, should be promoted to augment the effects of ambulatory activity.
All authors disclose no conflicts of interest. No funding was used to prepare this manuscript.
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Keywords:Copyright © 2014 by the National Strength & Conditioning Association.
accelerometry; light-intensity physical activity; functional balance