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Original Research Articles

Relationship Between Obesity and Balance in the Community-Dwelling Elderly Population

A Cross-Sectional Analysis

Lee, Jae Joon MD; Hong, Dong Whan MD; Lee, Seung Ah MD, PhD; Soh, Yunsoo MD; Yang, Miryeong MD; Choi, Kwang Min MD; Won, Chang Won MD, PhD; Chon, Jinmann MD, PhD

Author Information
American Journal of Physical Medicine & Rehabilitation: January 2020 - Volume 99 - Issue 1 - p 65-70
doi: 10.1097/PHM.0000000000001292

Abstract

What Is Known

  • Direct relationship between obesity and fall efficacy has been reported in different age groups.

What Is New

  • Obesity share similar risk factors with falls, and therefore, impaired body balance increases the risk of falls particularly in obese elderly individuals.

The incidence and severity of fall-related complications rise with increasing age.1 Older adults may be more vulnerable to falls than younger ones because of the increased risk factors for falls because of the combination of comorbid diseases and age-related physiological decline,1 particularly sarcopenia, which is the age-associated loss of skeletal muscle mass and strength relative to its size.2 Factors contributing to falls are numerous and wide ranging; however, two salient intrinsic risk factors have been identified—muscle weakness and impaired balance.3 Greater lower limbs muscle weakness and poorer balance performance in fallers than in nonfallers have been well documented.3,4

Obesity is defined as abnormal and excessive fat accumulation with body mass index (BMI) values of 25 kg/m2 or greater in Asian populations. Asians generally have a higher proportion of body fat and BMI than do Western populations. Therefore, the World Health Organization suggests that reference values for the definition of obese should be lower for Asian populations.5 Obesity is related to various medical complications, such as heart disease, diabetes, cancer, breathing problems, and debilitating musculoskeletal conditions that worsen quality of life.6 Several studies have examined the relationship between obesity and postural control ability in different age groups. Hue et al.7 reported that increased body weight strongly correlated with decreased postural stability in the adult population (age range 24–61 yrs). Other studies have shown that obese children have worse motor performance than normal weight children; obese children showed relatively poor balance, decreased relative muscle strength, and different foot loading characteristics.8,9

Clinical balance assessment tools, such as the Berg Balance Scale (BBS), Timed Up and Go test (TUG), and Short Physical Performance Battery (SPPB) scores, are all reported to have high reliability and are used as initial screening tools for falls to categorize community-dwelling older adults into high- or low-fall risk groups.10,11 However, these assessment tools can be subjective depending on the examiner or the examinee and have limitations in their unsuitability to evaluate various factors that affect balance control.12 Recently, balance control abilities have been assessed using static or dynamic posturography. Posturography can quantitatively assess the balance control ability by measuring the postural sway and can measure more direct changes in the visual system, vestibular system, and somatic sense. Frames et al.13 reported that obese fallers have significantly higher sway area and sway ranges.

The characteristics of a compromised balance system are similar between obese individuals and a fall-susceptible population. However, little is known about the significant relationship between body weight and balance capacity, particularly in the elderly population. Direct relationship between obesity and fall efficacy has been reported.14 Therefore, this study aims to determine the influence of BMI on body balance and identify whether the impaired balance is influenced by muscle weakness and postural instability, which are major risk factors of fall, in a sample of a community-dwelling elderly population.

METHODS

Design and Participants

This cross-sectional study included 317 community-dwelling elderly individuals aged 65–92 yrs living without any support for activities of daily living in the community. The participants were recruited through an advertisement at Dongdaemun-gu public health center in Seoul, South Korea between May 2014 and April 2015. The following exclusion criteria were applied: known acute illnesses, current or recent fractures, vestibular or vision disorders (e.g., refraction errors, cataract, glaucoma, blindness), ongoing medications that could affect muscle strength and balance, unstable chronic diseases (e.g., unstable diabetes mellitus and uncompensated heart failure), malignant cancers and musculoskeletal disorders, and neurological problems, such as Parkinson disease and stroke. All participants were able to follow directions, respond appropriately to the survey questions, and participate in the interview process without assistance. Before participating in the study, all participants provided written informed consent by signing a form that summarized the purpose of the study, explained the risks and adverse effects, indicated that all information gathered would remain confidential, and assured the participants that they could withdraw at any time. Because this study is an observational study (cross-sectional study), it conforms to all STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for strengthening this observational study (see Supplemental Checklist, Supplemental Digital Content 1, http://links.lww.com/PHM/A862).

Data Collection

The health assessment used self-administered questionnaires, and the interviews were conducted by trained staff. A standardized questionnaire covering basic demographic data, fall history, medical comorbidities, and current medication use was sent to each participant before physical examination and clinical balance assessment. Physical examination included measurements of weight, height, BMI, blood pressure, and the Korean version of the mini-mental state examination (K-MMSE). The cutoff point of K-MMSE to characterize normal cognition is more than 24. Each individual provided a subjective estimate of their knee pain as a visual analog scale score (0 = minimum, 10 = maximum).

Participants were categorized based on their BMI according to Asian reference values. A participant with a BMI of 25 kg/m2 or greater was allocated to the obese group, whereas the normal weight group had control individuals with BMI between 18.5 and 24.9 kg/m2.

Muscle Strength Measurement

The knee extension strength was measured using an isokinetic leg dynamometer (InBody CO, Ltd, Seoul, South Korea). Participants sat with their knee joint flexed to 90 degrees and were asked to extend their knee against the exercise machine’s resistance until the flexed angle reached 30 degrees. Participants performed one practice trial and three recorded measurements, and the maximum value was noted.

Static Postural Balance Measurement

Static posturography was conducted using the InBody posturography (InBody CO, Ltd). The InBody posturography device consists of four force plates and the pressure detector is installed below each force plate. Each force plate measures the perpendicular pressure of the anterior and posterior feet. When participants stood straight, pressure detectors detected the patterns of displacement at the center of the pressure and the total sway distance (TSD) was measured. Four different standing postures—firm surface with the eyes opened (FI-EO), firm surface with the eyes closed (FI-EC), foam rubber pillow on the floor of the machine with the eyes opened (FO-EO), and foam rubber pillow with the eyes closed (FO-EC)—were evaluated for the test, and each posture was measured for 32 secs. The change in the center of the pressure from the reference point was measured in centimeters; the sway distance was calculated in real time and its standard deviation was expressed as TSD. Total sway distance indicates the extent of postural sway, which therefore can be considered indicative of the overall stability and ability to compensate for changes in posture. A higher TSD indicates a more unstable posture.12 Participant performed one practice trial with 10 secs of each condition before the measurements. The resting time between measurements was 30 secs.

Clinical Balance Assessment

Berg Balance Scale

Berg Balance Scale comprises 14 items that evaluate functional movements common in daily living, involving sitting, standing, and changing position. Each task is scored on a five-point scale from 0 to 4; the maximum score was 56, with a lower score suggesting impaired stability.15

Timed Up and Go Test

Timed Up and Go test is a test of basic functional mobility in the elderly population. The participants are asked to follow this sequence of movements: rise from an armchair, walk 3 meters as fast as possible, cross a line on the floor, turn, walk back, and sit down again. The test was performed twice consecutively, and the mean of the scores in seconds was considered the TUG test score.16

Short Physical Performance Battery

Short Physical Performance Battery is a composite outcome measure of lower limb function, including strength, endurance, gait, and balance. It comprises the following three tests: balance, gait speed, and chair stands. The sum of the scores for these three components was considered the final SPPB score, which could range from 0 to 12, each individual score is on a 0–4 scale (12 indicating the highest degree of lower limb functioning).17

Statistical Analysis

Data were analyzed using the Statistical Package for the Social Sciences (SPSS), Version 13.0 for Windows (SPSS Inc, Chicago, IL). Sample size was calculated using G*power 3.1.9.2 (effect size d = 0.5, α = 0.05, power = 0.8). The total sample size needed was more than 160, because the dropout rate was predicted to be 20.0%. The data for the obese group and the normal weight group regarding the baseline characteristics and balance control abilities obtained from posturography using InBody, BBS, TUG, and SPPB tests were assessed using independent t tests or χ2 test of independence as appropriate. The Pearson’s correlation coefficient was used to compare the BMI and the results for three clinical assessment tests (BBS, TUG, and SPPB), TSD obtained from posturography and both knee extensor strength of each volunteer. Binary logistic regression analysis was performed to identify the variables that independently associated of fall history. Results with P values of less than 0.05 were considered statistically significant. To determine the clinical significance of all findings, effect sizes (Cohen’s d) were computed to examine the impact of obesity on baseline characteristics and outcomes.

Ethical Considerations

This study was approved by the ethics review committee in Kyung Hee Medical Hospital Institutional Review Board (KHUHMDIRB 1503-02) and was conducted in accordance with the ethical standards established in the Declaration of Helsinki (1964) and later amendments.

RESULTS

Herein, 258 patients were included in the final analysis. The study population comprised 77 men and 181 women with a mean ± SD age of 76.70 ± 4.60 yrs. Of the 258 participants, 131 (79% of women) were categorized into the obese group, whereas 127 (61% of women) were categorized into the normal weight group. In the obese group, 28 of 131 participants experienced falls and 6 of 127 participants in the normal weight group. Table 1 summarizes the baseline characteristics of both groups. The statistical analyses of the baseline characteristics revealed no significant differences between the two groups (P > 0.05) except for sex difference (P = 0.003) and number of fall history (P < 0.001).

TABLE 1
TABLE 1:
Baseline demographic and clinical characteristics of the normal weight group and obese group (N = 258)

Table 2 summarizes the results of the three clinical balance assessments (BBS, TUG, and SPPB), knee extension strength, and TSD of the obese and normal weight groups. The obese group had poorer scores in the clinical balance assessment than the normal group. There were statistically significant differences in BBS (P = 0.020), TUG (P = 0.001), and SPPB (P = 0.003) findings between the two groups. When the 14 BBS items were separately analyzed, the obese group scored significantly lower only for one item, that is, standing on one leg (P = 0.018). Among the subcategories of SPPB, the balance test, gait speed test, and chair stand test scores were lower (P = 0.040, P = 0.022, P = 0.046, respectively) in the obese group than in the normal weight group. Measured knee extensor strength was 16.39 ± 7.39 kg in the right side, 15.48 ± 7.59 kg in the left side of the normal weight group, and 13.42 ± 8.03 kg in the right side, 13.08 ± 7.35 kg in the left side of the obese group. Knee extensor strength was reduced bilaterally in the obese group than in the normal weight group. The results of the TSD obtained using posturography of the two groups were summarized in Table 2. The obese group had a higher TSD than the normal weight group in the FI-EC and FO-EC postures (P < 0.05), whereas there were no significant differences between the two groups in the FI-EO and FO-EO postures (P > 0.05).

TABLE 2
TABLE 2:
Clinical balance assessment scores, knee extension strength, and TSD of the normal weight group and obese group (N = 258)

Correlations between BMI and other variables are summarized in Table 3. Upon checking the statistically significant variables, it was obvious that BMI had a low but significant correlation with BBS, TUG, SPPB, FI-EC, and both knee extensor strength.

TABLE 3
TABLE 3:
Correlations among the variables (N = 258)

Table 4 lists the results of the multiple logistic regression analysis as various predictors (age, sex, BMI, clinical balance assessments, muscle strength, TSD) to objective variable (fall history). Body mass index, age, and SPPB total score were demonstrated to be a significant (P < 0.05) predictor of fall risk. Regarding BMI, the odd ratios for respondents with fallers were 1.390 (95% confidence interval [CI] = 1.175–1.645, P < 0.001).

TABLE 4
TABLE 4:
Logistic regression: Association of fall history (N = 258)

DISCUSSION

The objective of this study was to determine whether obesity negatively affects the balance performance in the elderly population and to find out whether there is a relationship of obesity with muscle weakness and postural instability, which are known risk factors of falls. On comparing both groups, a statistically significant correlation was found between BMI and the results of three clinical balance assessment tools (BBS, TUG, and SPPB). Our study also found that between BMI and muscle strength of the lower limbs, there was a negative correlation. However, because there was a weak correlation, these data need to be further investigated in the future to provide proof of this relationship between BMI and the other variables. The obese group showed greater TSD than the normal weight group on posturography, which was consistent with the findings of the study of Rossi-Izquierdo et al.18 that obesity had a negative effect on postural instability.

In our study, the BMI appear as a predictor of fall history among the community-dwelling elderly population. This finding is supporting a recent report about high BMI has a negative effect on fall efficacy.14 In addition, our results of examining the correlation between obesity and main risk factors of fall (muscle strength, impaired balance) showed that there was a statistically significant correlation with obesity. Therefore, it is believed that the risk of a fall is increased for obese elderly population because muscle weakness and postural instability exist.

Of the baseline demographic characteristics, the sex showed a significant difference between the normal group and the obese group (χ2 = 9.120, P = 0.003). Nakagawa et al.19 suggested that there was no difference between the two sexes in relation to postural balance in the elderly population and only the older age group presented a great risk of falling. As a result, age may affect balance, but there is no significant difference based on sex in the elderly population. This fact has been confirmed from our study that age increased the odds ratio for developing fall but not the sex.

Our study included K-MMSE and visual analog scale to assess knee pain in data collection. Previous studies have reported that a positive correlation between MMSE and balance function20 and knee osteoarthritis are important factors affecting balance.21 There is little evidence that knee pain directly affects the balance, but the presence of pain may reflexively inhibit the muscles around the knee, which could compromise effective and timely motor responses in postural control.21

This study found a negative correlation between BMI and isokinetic knee extensor muscle strength. The previous study reported a greater absolute maximum muscle strength in obese individuals than in nonobese ones.22 However, Rolland et al.23 reported that with increasing BMI, lower limb strength increased only in active women and did not change in sedentary women. In addition, Hulens et al.24 revealed that muscle impairment may be independently involved with an association of insufficient physical activity. Similarly, obese elderly individuals apparently have relatively less recreational physical activity than the normal weight group, and their sedentary lifestyle may have an influence on the loss of muscle mass and strength. Moreover, obesity complicated with an osteosarcopenic state has shown to exacerbate functional limitations, leading to increased difficulty in performing physical functions that require strength and possibly an even greater difficulty in maintaining postural stability.25 Unlike in our study, muscle strength was reported to be a powerful predictor of falls risk.3 This inconsistent finding may be due to the fact that lower limb muscle strength at hip joint, mobilization, and strength of ankle have a higher association with balance performance, which is not included in our study.26,27 We recommend the inclusion of various lower limb muscle strength in future studies. According to a study published by Brech et al.,28 the knee extensor was a fundamental factor in the chair standing task among other muscles. Diminished extensor strength leads to the disproportion between the hamstring muscles and the quadriceps. In addition, impairment of concentric contraction of the quadriceps, which causes the imbalance in displacements of the center of gravity during the movement, might be the root cause of postural instability and falls.28

Adequate postural control depends on the combination of somatosensory, vestibular, and visual information of the body movement. Our study found that obese elderly individuals had greater TSD than normal weight individuals in the eyes-closed condition on firm or foam floors. These results suggest that visual inputs compensate for postural instability and that individuals with obesity are less capable than normal weight individuals in maintaining postural stability. Hue et al.7 suggested that obese individuals have reduced sensory functions in the lower limbs because of the high pressure exerted on them by the high body weight. Birtane and Tuna29 reported that obese individuals have a larger plantar contact area and greater mean pressure values. These results are important because the desensitization of mechanoreceptor afferents may be induced by prolonged suprathreshold stimulation, and under such circumstances, sensory signals from mechanoreceptor would be less reliable. Bensmaïa et al.30 have also shown that prolonged suprathreshold vibratory stimulation was found to result in a reversible decrement in afferent sensitivity. In our study, obese individuals showed greater postural instability in the eyes-closed condition but not in the eyes open condition. We anticipated that foam base with eyes open will lead to a significantly different result between the obese and normal weighted groups; however, TSD did not significantly differ between firm and foam bases with eyes open. We hypothesize that these results were preferentially influenced by visual compensation rather than decreased foot mechanoreceptor activity. Several previous studies have reported that visual systems are most important to compensate for the loss of balance in the elderly population.31

The relations between obesity and the results of clinical balance assessment tools identified in our study revealed that the elderly population with obesity had decreased balance control ability as per their lower limb physical performance as well as inadequate functional mobility in all tests. However, considering a maximum score of 56 in the BBS, the mean score of 53.39 in normal group and 52.52 in the obese group was generally high suggesting the existence of ceiling effect. Recently, the BBS cutoff score suggested for fall risk was ranging from 45 to 51 points.15 The high score observed in our studies indicates that for obese elderly, the BBS is probably not the best option for detecting balance problems and risk for falls. In addition, the between-group difference of BBS, TUG, and SPPB presented in the current study was statistically significant but was not clinically significant. All items in Table 2 revealed to have a small effect size (d < 0.5). As a result, these balance assessment tools should not be used alone to screen for fall risks among community-dwelling obese elderly population.

This study has some limitations. Because this was a cross-sectional study, we can find an association among variables but cannot demonstrate causality. A longitudinal study including a large cohort is needed to reach generalizable results with a greater degree of confidence. In addition, there was a sex difference in baseline demographic characteristics. Although the impact of sex on balance is not as important as mentioned previously in the discussion section, it clearly affects muscle strength.22 This can act as a selection bias in our study and limit the interpretation of results. Lastly, the findings may only be generalizable to a relatively healthy population of elderly living in the community and may not apply to residents of care facilities, who have different risk profiles for balance compared with the general population.

CONCLUSIONS

The relationship between obesity and the clinical balance assessment tools, such as BBS, TUG, and SPPB, suggests that balance performing ability is poorer in obese elderly population. However, these statistically significant results lack clinical significance, we need to be careful when independently using these tests in initial screening for the risk of falls among the community-dwelling elderly population with obesity. Our study findings indicate that impaired balance in obese elderly individuals is associated with weak lower limb strength and increased postural sway. Our findings imply that obesity shares similar risk factors with falls, and therefore, impaired body balance increases the risk of falls in obese elderly individuals. In addition, the logistic regression analysis of our study showed that BMI-based obesity can be an independent fall risk as well as age and balance.

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Keywords:

Elderly; Obesity; Falls; Posturography; Balance

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