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Abstract

Numerous measures of physical function have been shown to be independently associated with frailty in older adults. This cross-sectional observational study aimed to identify the association between tests of physical function and frailty in community dwelling older adults and explore whether being overweight or obese increases the strength of this association. Mobility, balance, strength performance, and frailty status of 161 community dwelling older adults was measured. Logistic regression examined the association between these measures and frailty status. Participants with both poor performance on these measures (bottom 25% of performance within the cohort) and identified as being overweight or obese (body mass index [BMI] > 24.99) were compared to the rest of the cohort to identify whether weight status exacerbated the strength of these associations. Individually, BMI (odds ratio [OR]= 1.1, 95% CI = 1.0, 1.2; P = .030, trivial effect) and poor timed up and go (TUG) performance (OR = 1.5, 95% CI = 1.2, 1.7; P ≤ .001, small effect) were associated with frailty. Combinations of excess body mass and poor TUG (OR = 3.7, 95% CI = 1.5, 9.4; P = .006, moderate effect), balance (OR = 7.2, 95% CI = 2.3, 22.3; P = .001, large effect), mobility (OR = 3.7, 95% CI = 1.9, 7.4; P ≤ .001, moderate effect), and upper (OR = 4.5, 95% CI = 2.2, 9.2; P ≤ 001, large effect), and lower-body (OR = 3.7, 95%CI = 1.6, 8.5; P = .003, moderate effect) strength performance were significantly associated with frailty, as was being female (2.5, 95% CI = 1.3, 4.8; P = .005, moderate effect). Poor function and a high body mass are strongly associated with frailty and should be considered important qualities to assess when considering targeted frailty prevention strategies.

Keywords

elderly physical fitness BMI balance mobility upper and lower body strength

What this paper adds

This study provides comprehensive insight into the physical factors that are associated with frailty in community dwelling older adults.

Community-dwelling older adults with poor measures of balance, walking ability, and upper and lower body strength, are at a high likelihood of having frailty.

Excess body mass significantly exacerbates the likelihood of frailty in community-dwelling older adults.

Applications of study findings

The routine assessment of walking ability, balance, strength, and body mass index may have implications for improving functional capacity and reducing frailty induced conditions in older adults.

Older adults who present with poor physical function and a high BMI can be considered high risk and targeted for individualized frailty prevention strategies.

Targeted exercises, rehabilitation strategies, and lifestyle modifications can be designed as appropriate interventions to address walking ability, balance, functional performance, and excess body mass index.

Introduction

The number of people aged over 60 years is estimated to make up 22% of the total population by 2050.¹ It has been well documented that frailty, a state characterized by decreased physiological reserve, accelerated decline in physical function, and loss of resistance to stressors caused by accumulated age-related deficits, is associated with various negative health outcomes, including falls, fractures, dementia, hospitalization, disability, and poor quality of life.² There are numerous ways to diagnose frailty,³ however, one of the most common is the Fried’s criteria. The Fried et al’s criteria diagnoses an individual as being frail when they have at least 3 of the 5 following factors: physical weakness, low levels of physical activity, exhaustion, slow walking speed, and unintentional weight loss.^4,5 The Fried et al frailty criteria is the most common and well-validated measure of frailty in research and practice.^4,6 It has been estimated a single frail individual costs the healthcare system, more than 20,000 USD per year.⁷ Taking this into consideration, preventing frailty is a major public interest to reduce public health costs and healthcare burden.⁶

While the Fried’s frailty criteria offers a robust method of diagnosing frailty, the 5 measures used can be burdensome to participants, require specialist equipment, and can be time intensive to conduct. Furthermore, they don’t provide additional context into which physical factors should be prioritized to improve frailty once someone has been diagnosed. As such, the identification of physical factors that are most strongly associated with frailty may provide practitioners with a more ecologically valid method of identifying high risk individuals, while also providing insight into what qualities should be focused on for frailty prevention practices. A recent meta-analysis sought to identify those physical factors with the strongest association with frailty in older adults, and found that frail individuals were more likely to have lower walking speeds, worse lower and upper body strength, and poorer balance than non-frail individuals.⁸ However, whether health related factors, such as body mass index (BMI), exacerbate these associations remains unknown. Meta-analytic research has demonstrated that both excess adiposity and high BMIs are associated with frailty.⁹ Taking this into consideration, it is plausible that individuals with poorer health and poor physical performance may be at a greater likelihood of developing frailty than those with only poor physical performance, although this is yet to be explored in the literature. If this were the case, then this would provide practitioners working with older adults a simple and effective means of identifying individuals with the highest likelihood of having frailty to facilitate early intervention.

As such, the primary aim of this study was to identify the association between select, easy to implement, tests of physical function and frailty in community dwelling older adults. The secondary aim was to explore whether being overweight and obese and having poor performance on these tests was associated with an increased likelihood of frailty. The tests of physical function included the timed up and go test (TUG), single-leg stance test (SLST) of balance, the 30 s bicep curl test of upper body strength, the 30 s squat test of lower body strength, and finally the Tinetti Performance-Oriented Mobility Assessment (POMA) test.¹⁰ It was hypothesized that poor performance on all physical measures would be associated with frailty, and that this association would increase in overweight and obese individuals.

Methods

Study Design and Participants

This study implemented a cross sectional design in community-dwelling older adults living in Tehran, Iran, during the 2023 to 2024. The experimental outcome measurements were conducted at sports injuries and corrective exercise department of the Sport Science Research Institute of Iran, in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement.¹¹ Participants were included if they were female or male aged over 60 years and willing to take part in the study, ambulated with or without an assistive device, and able to provide informed consent.^12,13 They were excluded if they were living in a nursing home, hospitalized, bed-ridden, or receiving nursing home level care at home at the time of enrollment. To eliminate the influence of comorbidities of known pathology impacting upon the findings, participants who had been diagnosed with a neurological, orthopedic, or visual disorder (eg, Parkinson’s disease, knee replacement, or macular degeneration) directly impairing mobility were also excluded,¹⁰ as were those that had any major medical problems that would interfere with the safety of testing. The study was approved by the ethical committee of Sport Sciences Research Institute of Iran and complied with the declaration of Helsinki.¹⁴ This study was not preregistered on a trial registry or database.

Outcome Measures

Assessment of sociodemographic status, medical history, frailty, physical function, and anthropometry were organized by the principal investigator, and was collected by an independent specialist of the research team who was properly trained and had more than 5 years’ experience working with older adult populations. To minimize differences in data collection procedures, the same evaluator carried out data collection for all participants.

Sociodemographic Status

Information on chronological age, marital state, and level of education was collected for each participant using a custom data collection form.

Anthropometric

The standardized procedures described by Lohan et al were followed for the collection of anthropometric data. Body mass was measured using a portable scale (Seca^®, model 770, Germany) with a precision of 0.1 kg. Height was measured using a portable stadiometer (Seca Body meter^®, model 208, Germany) with a precision of 0.1 cm. BMI was calculated using height and weight (BMI = weight/height in m²).¹⁵ Participants were also categorized as underweight (<18.5 m/kg²), healthy (18.5-24.9 m/kg²), overweight (25.0-29.9 m/kg²), and obese (>30,0 m/kg²) in accordance to their BMI.¹⁶

Frailty (Fried’s Criteria)

Frailty was defined according to Fried et al.⁴ A participant was identified as frail by the presence of 3 or more of the following components including, weakness, slowness, low level of physical activity, unintentional weight loss (shrinking), and exhaustion.⁴ The specific frailty criteria are provided in Table 1, but in brief, weakness was identified by poor grip strength (adjusted for gender and body mass index); slowness by poor 8 foot up and go test time (adjusted for gender and height); low physical activity level by short version of the Minnesota leisure time activity questionnaire (adjusted for gender); shrinking by self-reported unintentional weight loss of more than 10 pounds during the past year; exhaustion was identified by self-reported exhaustion via 2 questions from the Center for Epidemiological Studies Depression Scale (CESD),¹⁷ being (a) I felt that everything I did was an effort; (b) I could not get going. These questions were answered using a 4-point Likert scale (0 = rarely or none of the time [<1 day], 1 = some or a little of the time [1-2 days], 2 = a moderate amount of the time [3-4 days], 3 = most of the time). Participants who answered a “2” or “3” to either of these questions were categorized having “exhaustion.”

Table 1.

Specific frailty diagnoses criteria.

Frailty phenotype	Measurement	Men	Women
Weakness	Grip strength (stratified by sex and BMI [kg/m²], maximum value of either hand)	BMI ≤ 24: grip strength ≤ 29 kg	BMI ≤ 23: grip strength ≤ 17 kg
		BMI ≤ 24.1-26: grip strength ≤ 30 kg	BMI ≤ 23.1-26: grip strength ≤ 17.3 kg
		BMI ≤ 26.1-28: grip strength ≤ 30 kg	BMI ≤ 26.1-29: grip strength ≤ 18 kg
		BMI > 28: grip strength ≤ 32 kg	BMI > 29: grip strength ≤ 21 kg
Slowness	Walking time (8 foot up and go test) (stratified by sex, averaged value of two repeated measurements)	Height ≤ 173 cm: walking time ≥ 7 s	Height ≤ 159 cm: walking time ≥ 7 s
Slowness		Height > 159 cm: walking time ≥ 6 s	Height > 173 cm: walking time ≥ 6 s
Low level of physical activity	Self-reported: Physical Activity Scale for the Elderly (9 items)	Kcals of physical activity per week < 383	Kcals of physical activity per week < 270
Shrinking	Unintentional weight loss	In the last year, self-report of losing more than 10 pounds (5 kg) unintentionally (ie, not due to dieting or exercise) or unintentional weight loss of at least 5% of body weight
Exhaustion	Two items of the CESD	(a) I felt that everything I did was an effort.
		(b) I could not get going.
		The question asked, “how often in the last week did you feel this way?” 0 = rarely or none of the time (<1 day), 1 = some or a little of the time (1-2 days), 2 = a moderate amount of the time (3-4 days), or 3 = most of the time.
		Participants answering “2” or “3” to either of these two questions were categorized as being exhausted.
Overall frailty status	Non-frail, and pre-frail: 0-2 affected criteria; frail: ≥3 affected criterion.

Hand grip strength

Hand grip strength was measured using a handheld dynamometer (Takei Kiki Kogyo, Tokyo, Japan). For this test, participants held their arm extended above their head directly in line with the side of their body, with the dynamometer facing outward. The participant was then squeezed the dynamometer handle as hard as possible for approximately 3 s, while slowly bringing it down toward their side. This test was performed twice, with a 1-min break between attempts. The best result (in kg) from the 2 attempts was used for analysis.¹⁸ Hand grip strength has been shown to be highly reliable in older adults (intraclass correlation coefficient [ICC] = 0.96-0.98).¹⁹

The 8 Foot Up and Go Test

During the 8 foot up and go test, participants are required to stand up from a chair with arm rests, walk to a cone placed 8 feet away, turn around, return to the chair, and sit back down in to their initial starting position.^20,21 Participants underwent 2 trials with a 1-min rest between each trial. The fastest trial was used for analysis. The 8 foot up and go test has been shown to be highly reliable in older adults (ICC = 0.93-0.98).²²

The International Physical Activity Questionnaires- Short Form

Physical activity levels were measured using the International Physical Activity Questionnaire - Short Form (IPAQ-SF) questionnaire. In this questionnaire participants were required to the average weekly amount of vigorous and moderate intensity physical activity, walking activities, and time spent sitting, they do. All exercise values were reported in minutes per week, while sitting time was reported in minutes per day. The 7-day IPAQ-SF is a valid measure of physical activity behavior in various populations.^23,24

Tinetti Performance Oriented Mobility Assessment (POMA)

The POMA is an assessment of functional ability that consists of 2 parts: gait and balance. The gait evaluation component has a maximum score of 12 points, while the balance evaluation has a maximum score of 16 points. Gait and balance scores are combined for a total possible score out of 28 points, whereby higher scores represent better function. To determine the participant’s gait quality, participant walked across a room 25 feet each way. During this walk, they were evaluated on hesitation, step length and height, leg distance, step symmetry and step continuity. For the balance component of the assessment, participants were assessed on their quality of movement and their ability to maintain balance in different positions, including sitting on a chair, standing up from a chair, standing balance, standing balance while tapping on their chest, a 360° rotation, standing balance with closed eyes, and sitting.²⁵ The POMA test has been shown to be reliable in older adults (ICC = 0.75-0.97).²⁶

Standing Stork Balance Test

The standing stork balance test was used to measure static balance. Participants were required to stand on their non-dominant leg with their opposite foot against the inside of the supporting knee and both of their hands on their hips.²⁷ The duration balance was maintained was the outcome of interest, with the time commencing when the heel left the floor and.²⁸ The test ended when one or both hands left the waist, the support foot changed position to maintain balance, or the foot resting on the supporting knee lost contact.²⁹ The standing stork balance test is a reliable indicator of balance.³⁰ In the instance where someone could not perform the test due to poor balance, they scored 0 s.

Timed Up and Go Test

Dynamic balance was evaluated using the timed up and go test (TUG). The TUG requires participants to stand up from a chair with an armrest, walk a distance of 3 m to a line on the floor, turn around, return to the chair, and sit back down into their initial starting position.^31,32 Participants underwent 2 trials with a 1 min rest between each trial. The fastest trial was used for analysis. TUG test has been shown to be highly reliable in older adults (ICC = 0.97-0.99).³³

The 30 Second Chair-Stand Test

Lower body strength was measured using the 30 s chair-stand test. For this test, participants were required to rise and sit back down in an armless chair 43 cm high as many times as they could during a 30 s period, while keeping their arms crossed on their chest the whole time. The total number of times the participant stood up within the 30 s period was the outcome of interest.^34,35 The 30 s chair-stand test provides a reliable and valid indicator of lower body strength in community-dwelling older adults (ICC = 0.97-0.98).^34,35

The 30 Second Arm Curl Test

Upper body strength was evaluated with the 30 s arm curl test. For this test participants performed as many repetitions of elbow flexion and extension while holding a 2.3 kg dumbbell while seated. They completed this test on both arms independently, and the total number of repetitions for each arm was recorded,^35,36 with the highest number used for analysis. The arm curl test provides a reliable (ICC = 0.88-0.99) and valid indicator of upper body strength in community-dwelling older adults.^35,36

Statistical Analysis

Data analysis was performed using Stata statistical software version 18 (College station, TX). The data is reported as mean ± standard deviation (SD) with 95% confidence intervals. Two group comparisons (frail vs non-frail older adults) were conducted using the Student’s t test for all continuous outcome measures, and a chi-squared test for all categorical outcome measures. The statistical significance level was .05 and effect sizes with 95% CI were presented for t-test comparisons. Where appropriate, effect sizes were quantified and considered small effect as values <0.2, medium effect <0.5 and large effects >0.8.³⁷ A univariate logistic regression was first used to establish the association between independent measures of physical function and frailty status. Variables that were significantly associated were then combined into a multivariate logistic regression analysis to assess the extent that confounders were acting on these relationships. Due to previous research suggesting that smoking³⁸ and gender may increase frailty risk,³⁹ the association between smoking status (yes/no), gender (male/female) and frailty was also examined Additionally, participants who demonstrated poor performance on these measures (considered as being in the bottom 25% of performance within the cohort) and were identified as being overweight or obese (BMI ≥ 24.99) were compared to the rest of the cohort to identify whether weight status exacerbates the association between poor physical function and frailty. Where appropriate, effect sizes were quantified using odds ratios (OR) and considered trivial (0.77-1.00 or 1.00-1.29), small (0.51-0.78 or 1.30-1.99), moderate (0.25-0.50 or 2.00-3.99), and large (≤0.24 or ≥4.00).⁴⁰ Based on the recruited sample size of 161 participants, considering 2 predictor variables for frailty (BMI and the specific physical test), a significance level of 0.05, and a desired power of 0.80, this study was adequately powered to detect moderate effect sizes (odds ratio) of at least 3.00.

Results

A total of 161 participants were included in this study (91 males and 70 females, age 68.01 ± 6.88 years, weight 69.87 ± 11.46 kg, height 1.63 ± 0.09 m, BMI 26.27 ± 4.49 kg/m²), of which 76 (47%) were identified as being frail. Figure 1 provides STROBE flow chart for this cross-sectional study. On average, frail individuals were older (P = .001), had higher BMIs (P = .027), and were less active (P = .001) than their non-frail and pre-frail counterparts. There were more females diagnosed with frailty than males (P = .004), and a higher proportion of widows diagnosed with frailty than single, married, or divorced participants (P = .007). Finally, a lower proportion of frail participants had undergone tertiary education than non-frail participants (P = .001). Table 2 provides the full demographic information for the populations studied.

Figure 1.

STROBE flow chart for cross-sectional study.

Table 2.

Characterization of the total sample study population and comparison by frailty phenotype for sociodemographic information.

	Total sample (n = 161, 100%)	Non-frail and pre-frail (n = 85, 53%)	Frail (n = 76, 47%)	P	Effect size d [95% CI]
Bio-sociodemographic
Age (years, Mean ± SD)	68.01 ± 6.88	64.79 ± 4.43	71.61 ± 7.35	.001*	−1.14 [−1.45 to 0.83]
Weight (kg, Mean ± SD)	69.87 ± 11.46	69.67 ± 11.06	70.10 ± 11.96	.813	−0.04 [−0.35 to 0.27]
Height (m, Mean ± SD)	1.63 ± 0.09	1.65 ± 0.08	1.61 ± 0.10	.008*	0.44 [0.13-0.76]
BMI (kg/m², Mean ± SD)	26.27 ± 4.49	25.53 ± 3.95	27.09 ± 4.92	.027*	−0.35 [−0.66 to 0.04]
Sex (n, %)				.004*
Male	91 (56.5%)	57 (67.1%)	34 (44.7%)
Female	70 (43.5%)	28 (32.9%)	42 (55.3%)
Marital state (n, %)				.007*
Single	1 (0.6%)	1 (1.2%)	0 (0%)
Married	129 (80.1%)	75 (88.2%)	54 (71.1%)
Widowed	28 (17.4%)	7 (8.2%)	21 (27.6%)
Divorced	3 (1.9%)	2 (2.4%)	1 (1.3%)
Smoking (n, %)				.663
Positive	32 (19.9%)	18 (21.2%)	14 (18.4%)
Negative	129 (80.9%)	67 (78.8%)	62 (81.6%)
Level of education (Degree; M 1;3)	1 (1; 3)	2 (1; 3)	1 (1; 1.75)	.001*
Eyesight problems (n, %)				.074
No problem	81 (50.3%)	47 (55.3%)	34 (44.7%)
Self-reported poor eyesight	43 (26.7%)	24 (28.2%)	19 (25.0%)
Eye glasses	37 (23.0%)	14 (16.5%)	23 (30.3%)
Hearing problems (n, %)				.212
No problem	123 (76.4%)	68 (80.0%)	55 (72.4%)
Poor hearing	35 (21.7%)	17 (20.0%)	18 (23.7%)
Hearing aids	3 (1.9%)	0 (0%)	3 (3.9%)
Falling incidence (n, %)	43 (26.7%)	12 (14.1%)	31 (40.8%)	.001*
Frailty syndrome (n, %)				.001*
Weakness	89 (55.3%)	28 (32.9%)	61 (80.3%)
Slowness	71 (44.1%)	16 (18.8%)	55 (72.4%)
energy	80 (49.7%)	14 (16.5%)	66 (86.8%)
Shrinking	80 (49.7%)	25 (29.4%)	55 (72.4%)
Low physical activity (Man < 383 women < 270)	49 (30.4%)	2 (2.4%)	47 (61.8%)
IPAQ (Kcal/week, Mean ± SD)	985.26 ± 909.11	1434.66 ± 1344.76	482.64 ± 477.31	.001*	0.92 [0.61-1.24]
TUG (s, Mean ± SD)	11.37 ± 8.95	8.82 ± 2.56	14.21 ± 12.17	.001*	−0.63 [−0.94 to −0.32]
Hand grip (kg, Mean ± SD)	25.01 ± 10.29	30.21 ± 9.40	19.20 ± 7.87	.001*	1.26 [0.95-1.58]
Tinetti
Tinetti balance (n, Mean ± SD)	11.58 ± 3.89	13.08 ± 3.22	9.89 ± 3.90	.001*	0.90 [0.59-1.21]
Tinetti walking (n, Mean ± SD)	7.97 ± 3.09	9.18 ± 2.65	6.62 ± 3.01	.001*	0.91 [0.59-1.22]
Tinetti total (n, Mean ± SD)	19.55 ± 6.37	22.26 ± 5.09	16.51 ± 6.32	.001*	1.01 [0.70-1.32]
30 s arm curl (n, Mean ± SD)	13.27 ± 3.17	14.34 ± 3.58	12.07 ± 2.09	˂.001*	0.76 [0.45-1.08]
30 s chair stand (n, Mean ± SD)	10.41 ± 4.10	12 ± 3.98	8.63 ± 3.47	˂.001*	0.90 [0.59-1.21]
Stork balance (s, Mean ± SD)	12.58 ± 12.66	17.97 ± 13.73	6.56 ± 7.82	˂.001*	1.01 [0.70-1.32]

indicates statistically significant difference at p < 0.05.

Individually, BMI (OR = 1.1, 95% CI = 1.0, 1.2; P = .030, trivial effect) and poor TUG performance (OR = 1.5, 95% CI = 1.2, 1.7; P ≤ .001, small effect) were associated with an increased likelihood of frailty. Conversely, good balance (OR = 0.9, 95% CI = 0.8, 0.9; P ≤ .001, trivial effect), POMA Tinetti (OR = 0.8, 95% CI = 0.8, 0.9; P ≤ .001, trivial effect), and upper (OR = 0.7, 95% CI = 0.6, 0.9; P ≤ .001, small effect) and lower body (OR = 0.8, 95% CI = 0.7, 0.9; P ≤ .001, trivial effect) strength were all associated with a lower likelihood of frailty. Smoking status was not associated with frailty (OR = 0.8, 95% CI = 0.4, 1.8; P = .662, trivial effect), while being female was (2.5, 95% CI = 1.3, 4.8; P = .005, moderate effect). Results of the multivariate analysis indicated that poor TUG performance (OR = 1.3, 95% CI = 1.1, 1.5; P = .004, trivial effect) was still associated with an increased likelihood of frailty, while better balance (OR = 0.9, 95% CI = 0.9, 1.0; P = .007, trivial effect) and POMA Tinetti scores (OR = 0.9, 95% CI = 0.98, 1.0; P = .011, trivial effect) were still associated with a decreased likelihood. Greater BMI (OR = 1.1, 95% CI = 1.0, 1.2; P = .087, trivial effect) and better upper body strength (OR = 0.8, 95% CI = 0.7, 1.0; P = .052, trivial effect) were still associated with an increased and decreased likelihood of frailty, respectively, although they were no longer significant. Finally, lower body strength no longer had any notable association with frailty (OR = 1.1, 95% CI = 0.9, 1.3; P = .385, trivial effect), nor did being female (OR = 1.1, 95% CI = 0.5, 2.6; P = .784, trivial effect).

Table 3 presents the results of the logistic regression combining BMI status (overweight or obese) with poor performance on novel physical function measures. Results indicate that overweight and obese community dwelling adults with poor (bottom 25%) performance on select measures of physical function are significantly more likely to have frailty compared to the rest of the cohort. Most notably, participants who were overweight or obese and had poor balance were more than 7 times more likely to be frail (OR = 7.2, 95% CI = 2.3, 22.3; P = .006, large effect), while those who were overweight or obese with poor upper body strength were more than 4 times more likely (OR = 4.5, 95% CI = 2.2, 9.2; P < .001; moderate effect).

Table 3.

Logistic regression combining BMI status (overweight or obese) with poor performance on novel physical function measures.

Overweight and obese combined with:	n	OR (95% CI)	P	Effect size descriptor
Poor TUG	26	3.7 (1.5, 9.4)	.006	Moderate effect
Poor balance	24	7.2 (2.3, 22.3)	.001	Large effect
Poor POMA Tinetti	56	3.7 (1.9, 7.4)	<.001	Moderate effect
Poor upper body strength	55	4.5 (2.2, 9.2)	<.001	Large effect
Poor lower body strength	32	3.7 (1.6, 8.5)	.003	Moderate effect

Discussion

This study provides comprehensive insight into the physical factors that are associated with frailty in community dwelling older adults, while also identifying the extent to which excess body mass increases the strength of this association. Findings indicate that individuals who are overweight or obese with poor balance and strength may be up to 7 times more as likely to have frailty, and should be considered at need of intervention.

The results of this study largely align with previous research, demonstrating that poor walking ability (TUG test), mobility, strength, and balance, are all associated with an increased likelihood of frailty.^41
-43 When examined both independently and in a multivariate model, the TUG test was the most strongly associated with frailty. This is likely due to the role that walking speed plays in the completion of the test, which has previously been linked to frailty in several cohort studies^41
-43 and is considered a strong indicator of health status. This is also likely to explain the relationship observed between POMA Tinetti performance and frailty, as the test also involves the assessment of gait, as well as the relationship observed with balance performance and frailty, given the known association between static balance and gait performance in older adults.⁴⁴ Similarly, the association with frailty and upper and lower body strength is a plausible one. It is well known that reductions in muscle strength occur with age in the general population, increasing the likelihood of developing sarcopenia amongst a host of other functional deficits.⁴⁵ This loss of strength makes performing physical activity more challenging, leading to lower physical activity levels,⁴⁶ which is one of the criteria for diagnosing frailty. Likewise, given that grip strength is both a known predictor of whole-body strength⁴⁷ and a key component of frailty diagnosis, it stands to reason that both upper and lower body strength would be associated with frailty in this cohort. However, it is important to note that while both upper and lower body strength were associated with frailty when analyzed independently, they were no longer significant when included in the multivariate model. As such, it is unlikely they should be used to screen for frailty when other measures of balance, gait, and function, are available.

In conjunction with the present findings regarding physical performance, it is also important to note that frail individuals were more likely to be female, widowed, and of a lower education status, than non-frail individuals. Prior research has demonstrated that females are more likely to be diagnosed with frailty than males across a wide range of ages,⁴⁸ with a common explanation being that females generally have lower levels of functional capacity than males, which is exacerbated with age. Our findings would support this suggestion, where being female was only significantly associated with frailty when analyzed independently and was no longer significantly associated when included in the multivariate model. Similarly, prior research across a host of older adult populations has shown that widows are more likely to be frail than married individuals,⁴⁹ as are those with a lower level of education,⁵⁰ which aligns with the findings of the present study. While the exact reason for this finding is unclear, both marital status and education level are associated with physical activity levels in older adults,⁵¹ which is likely to reduce the likelihood of developing frailty.

While multiple studies have indicated that poor physical performance and BMI are independently associated with frailty, to the authors knowledge, this is the first time it has been demonstrated that the strength of this association is increased in individuals who are overweight or obese and have poor physical performance. This is particularly noteworthy when 1 of the 5 criteria for diagnosing frailty relates to unintentional weight loss (ie, shrinking), further highlighting the extent to which high BMI exacerbates frailty in those with poor physical function. Prior research has identified an association between being overweight or obese and frailty (hazard ratio [HR] = 1.31, 95% CI 1.02, 1.69) in what may be the largest cohort (n = 29 937) of older adults studied to date,⁵² which aligns closely with the findings from the present study. This may be explained by the fact that overweight older adults are on average less active⁵³ and have slower walking speeds⁵⁴ than those in a normal bodyweight range. However, when combined with poor physical performance, the association with frailty increased significantly. Results indicated that individuals who were overweight or obese and had poor TUG scores, POMA scores, or lower body strength, were more than 3 times more likely to have frailty, while those with poor upper body strength scores were more than 4 times more likely. Finally, those with poor balance were more than 7 times more likely. While the exact reasons for these findings are unclear, it may be that individuals who have both high BMI and lower strength and balance measures have a higher proportion of fat mass compared to lean mass, which is typified of sarcopenic obesity, a condition associated with frailty.⁵⁵

Practically, it is important to note that in this study, individuals with poor performance on any single physical test were more likely to have frailty. However, when combined in a multivariate analysis, the only significant predictors of frailty were TUG, balance, and POMA Tinetti scores. This suggests that these 3 tests alone could be used as simple and reliable means of identifying individuals at high a likelihood of becoming frail. Moreover, given the extent to which excess body mass increased this association, individuals with both poor physical performance and categorized as either overweight or obese should be considered high risk and targeted for individualized prevention strategies. Potential strategies could include exercise training to improve strength and function, and dietary interventions to reduce fat mass. Based upon the findings of this study, practitioners working with community dwelling older adults should consider routine balance and functional testing, in conjunction with the routine measurement of BMI, to identify individuals who may be at a high likelihood of having frailty.

Limitations

There are limitations that should be considered with these findings. This study was conducted in a small homogenous sample of community-dwelling older adults from a single city. As such, it is unclear if these findings generalize older populations from other countries, where different cultural influences may impact exercise and health practices. Similarly, due to the number of participants included in the study, the extent to which marital and education status influenced the association of physical performance measures with frailty could not be examined. Additionally, as this study was cross-sectional, it does not provide insight into the how physical performance measures are likely to impact the possibility of becoming frail in the future. It may be that frailty risk is greater the longer someone presents with poor physical performance, which was not captured in this study. Lastly, it is important to note that the population studied excluded those who required an assistive device to ambulate, and had been diagnosed with neurological, orthopedic, and visual disorders, and were generally healthy and physically able. It is therefore unclear the extent to which these findings would replicate in less able older adults.

Conclusion

Community-dwelling older adults with poor measures of balance and walking ability are more likely to be diagnosed with frailty, and excess body mass significantly exacerbates this. Older adults who present with poor physical function and a high BMI should be considered higher risk and targeted for individualized frailty prevention strategies.

Footnotes

Authors’ Contributions

M.H.1 and M.H.4 conceived the study. M.H.1 collected the data. M.H.4, M.S. and P.N. supervised the data collection. M.H.4, M.H.1 and H.B. analyzed the data. M.H.4 and H.B. performed the statistical analysis. M.H.1, M.H.4 and H.B. wrote the draft. All authors reviewed and approved the manuscript.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, M.H.4, upon reasonable request.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Considerations

This study has been carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki), and was also approved by the institutional review board of Sport Sciences Research Institute of Iran (IR.SSRC.REC.1401.025). Signed informed consent to participate in the study was obtained from all participants.

ORCID iD

Mahdi Hosseinzadeh

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Excess Body Mass Exacerbates the Association Between Poor Physical Function and Frailty in Older Community Dwelling Adults

Abstract

Keywords

Introduction

Methods

Study Design and Participants

Outcome Measures

Sociodemographic Status

Anthropometric

Frailty (Fried’s Criteria)

Hand grip strength

The 8 Foot Up and Go Test

The International Physical Activity Questionnaires- Short Form

Tinetti Performance Oriented Mobility Assessment (POMA)

Standing Stork Balance Test

Timed Up and Go Test

The 30 Second Chair-Stand Test

The 30 Second Arm Curl Test

Statistical Analysis

Results

Discussion

Limitations

Conclusion

Footnotes

Authors’ Contributions

Data Availability Statement

Declaration of Conflicting Interests

Funding

Ethical Considerations

ORCID iD

References