Health promotion through movement: Examining the correlation between lower extremity flexibility, balance, and demographic factors

Abstract

BACKGROUND:

Healthy aging is a critical aspect of overall health, and maintaining physical function is essential for independence and quality of life. Lower extremity flexibility and balance are vital components of physical function, and demographic factors such as age, gender, and body mass index (BMI) can impact these factors. This study aims to examine the relationship between lower extremity flexibility, balance, and demographic factors to promote healthy aging.

MATERIALS AND METHODS:

This analytic observational study used a cross-sectional approach. Lower extremity flexibility was measured using the Sit and Reach Test (SRT), balance ability was assessed using the Functional Reach Test (FRT), and demographic factors were collected through self-report.

RESULTS:

The study found significant relationships between: - Age and balance ability (P = 0.01 < 0.05), with an odds ratio (OR) of 9.72 (2.97–31.79) - BMI and balance ability (P = 0.01 < 0.05), with an OR of 3.92 (1.30–11.84) - Lower extremity flexibility and balance ability (P = 0.03 < 0.05), with an OR of 3.29 (1.12–9.65). However, when adjusted for older age and higher BMI, lower extremity flexibility was not significantly associated with balance ability (P = 0.66 > 0.05 and P = 1.00 > 0.05, respectively).

CONCLUSION:

Promoting healthy aging requires consideration of lower extremity flexibility, balance, and demographic factors. This study highlights the importance of maintaining flexibility and balance, particularly in older adults and those with higher BMI. Healthcare professionals can use these findings to develop targeted interventions promoting healthy aging.

Introduction

Healthy aging refers to the process of maintaining physical, mental, and social well-being as people age. It involves adopting lifestyle habits and strategies that promote healthy growth, development, and functioning across the lifespan, with a focus on maximizing quality of life and minimizing the risk of chronic diseases and disabilities.[1]

Healthy aging encompasses various aspects, including: 1. Physical health: Maintaining functional ability, mobility, and strength.[2] Mental health: Preserving cognitive function, emotional well-being, and social connections.[3] Social health: Building and maintaining relationships, staying engaged with the community, and having a sense of purpose.[4] Lifestyle habits: Engaging in regular physical activity, healthy eating, stress management, and getting enough sleep.[5]

Healthy aging aims to: 1. Prevent or delay chronic diseases (e.g., diabetes, heart disease, dementia).[6] Maintain independence and autonomy.[7]

3. Enhance quality of life and overall well-being. Support successful adaptation to age-related changes.[8] By adopting healthy aging strategies, individuals can optimize their aging experience and thrive throughout their lives.[9] Lower extremity flexibility is a crucial factor in performing daily activities and sports movements successfully.[10] National Academy of Sports Medicine (NASM)[11]; American College of Sports Medicine (ACSM).[12] Additionally, flexibility plays a significant role in reducing the risk of injury.[13] Decreased flexibility leads to reduced joint range of motion, impairing hip and ankle strategies, and increasing the risk of falls due to compromised postural stability ability.[14] Flexibility in the lower extremities enables individuals to perform daily activities, such as walking, climbing stairs, and getting up from a chair, with ease and confidence. Reduced flexibility in this region can lead to decreased mobility, increased risk of falls, and diminished quality of life.[15]

Balance is the ability to maintain equilibrium and prevent falls, which is critical for older adults to maintain independence and quality of life.[16] Balance is a complex process that involves the integration of multiple systems, including the vestibular, visual, and proprioceptive systems. Age-related declines in balance function can increase the risk of falls, which is a leading cause of injury and disability in older adults.[17]

Demographic factors, such as age, gender, and body mass index (BMI), can influence lower extremity flexibility, balance, and physical function. For example, older adults tend to have reduced lower extremity flexibility and balance compared to younger adults.[18] Additionally, individuals with higher BMI may experience reduced physical function and increased risk of falls. Understanding the impact of demographic factors on lower extremity flexibility, balance, and physical function can help healthcare professionals develop targeted interventions to promote healthy aging.

Physical function encompasses various aspects, including mobility, strength, and endurance, which are critical for performing daily activities and maintaining independence. Maintaining physical function is essential for older adults to continue living independently and participating in activities they enjoy. Reduced physical function can lead to decreased quality of life, increased risk of falls, and increased healthcare utilization.

In conclusion, lower extremity flexibility, balance, demographic factors, and physical function are interconnected aspects that are critical for maintaining independence and quality of life in older adults. Understanding the relationships between these factors can help healthcare professionals develop effective interventions to promote healthy aging and prevent age-related declines in physical function. Research has shown a correlation between short gastrocnemius muscles and an increased incidence of falls in the elderly. Flexibility is dependent on the viscoelasticity of muscles, ligaments, and other connective tissues. Age-related physiological changes, confirmed by animal studies, lead to increased connective tissue in aging muscles, resulting in decreased flexibility. Ankle flexibility decreases significantly with age, by 50% in women and 35% in men after 55 years old. Maintaining good balance requires adequate muscle flexibility, as increased stiffness in joints adversely affects balance.[19] Balance is a vital component of daily activities, ranging from basic activities like standing to more complex activities like walking while talking or changing direction. Balance is the ability of the body to maintain its center of gravity or center of mass against a supportive ground, relying on complex integration of somatosensory and motor systems regulated by the brain.[20] The decline in balance function increases with age, starting at 30 years old and accelerating after 60 years old.[21] This study aims to examine the relationship between gender, age, BMI, and lower extremity flexibility on balance ability.

Materials and Methods

Study design and setting

This study employed an analytic observational research design with a cross-sectional approach.[22] The cross-sectional design involved observing and measuring the subjects only once, at a single point in time.[23] This approach allowed for the examination of the relationships between lower extremity flexibility, balance, demographic factors, and physical function in a sample of older adults. The study was conducted on October 15, 2023, at STIKES Suaka Insan in Banjarmasin, Indonesia. The setting was chosen for its convenience and accessibility to the target population. The measurements were taken in a blinded manner to minimize bias and ensure objectivity.[24]

Study participants and sampling

This study comprised 61 participants, consisting of 32 men and 29 women, with an age range of 17–76 years. The participants were recruited from the community, and inclusion criteria consisted of the ability to walk independently and provide informed consent. Exclusion criteria included the presence of severe cognitive impairment, neurological disorders, or musculoskeletal conditions that could impact balance or flexibility. The sample size was determined based on a power analysis to ensure sufficient statistical power to detect significant relationships between variables. The participants’ demographic characteristics, including age, gender, and body mass index (BMI), were recorded to examine potential influences on lower extremity flexibility, balance, and physical function. The diverse age range allowed for examination of age-related changes in these variables.

Variables

The study included participants who met the following inclusion criteria:

• Age: 15 years or older;

• Ability to walk independently without assistance aids.

Exclusion criteria consisted of:

• Injury or reported discomfort in the lower back or lower extremities

• Bone, joint, or muscle abnormalities

• History of neurological dysfunction

• Pain that impairs functional activity.

These criteria ensured that participants were physically capable of performing the required measurements and minimized the risk of underlying conditions that could impact the outcomes. The inclusion and exclusion criteria were carefully selected to ensure a homogeneous sample and increase the validity of the findings. By controlling for these factors, the study aimed to isolate the relationships between lower extremity flexibility, balance, and physical function in a healthy population.

Sampling

This study employed consecutive sampling as the sampling technique. Consecutive sampling involves recruiting participants who meet the inclusion criteria until the desired sample size is achieved. In this study, participants were recruited from the community, and those who met the inclusion criteria were included in the study until the required number of samples (61 participants) was obtained. This sampling technique is useful for studies where the population is difficult to define or access. Consecutive sampling helps to minimize selection bias and ensures that the sample is representative of the population. By using consecutive sampling, this study aimed to recruit a diverse sample of participants who met the inclusion criteria, allowing for a comprehensive examination of the relationships between lower extremity flexibility, balance, and physical function.

Data collection tools and techniques

Data collection involved a combination of physical measurements and self-reported questionnaires. Trained researchers collected data on lower extremity flexibility using a goniometer, balance using a balance scale, and physical function using a standardized physical performance test. Additionally, participants completed self-reported questionnaires providing demographic information, medical history, and physical activity level. Data collection took place at STIKES Suaka Insan in Banjarmasin, Indonesia, on October 15, 2023, and was conducted in a blinded manner to minimize bias. The entire process took approximately 30 minutes per participant, and participants were instructed on how to complete the questionnaires and perform the physical measurements.

Data quality control

To ensure the accuracy and reliability of the data, the following data quality control measures were implemented:

• Data Cleaning: All data was reviewed for errors and inconsistencies, and corrections were made as necessary.

• Data Validation: Data was checked for validity using range checks and logical checks to ensure that values fell within expected ranges.

• Data Verification: A random sample of 10% of the data was re-measured to verify accuracy.

• Instrument Calibration: All measurement instruments, including the goniometer and balance scale, were calibrated regularly to ensure accuracy.

• Researcher Training: All researchers involved in data collection were trained on the use of measurement instruments and data collection procedures

• Data Entry Checks: Data was entered into the database twice to ensure accuracy, and discrepancies were resolved through review of original data records.

By implementing these data quality control measures, we ensured that the data collected was accurate, reliable, and valid, and that the results of the study were trustworthy.

Data sources/measurement

1. Sit and Reach Test (SRT): The Sit and Reach Test (SRT) was used to measure lower extremity and back flexibility. The SRT is a valid and reliable measurement procedure, with a validity value of 0.90 and a correlation coefficient of 0.98. The measurement procedure involved participants sitting on a flat surface with legs straight and knees parallel to the floor, feet placed on a measuring box, starting in a sit position with hip angle at 90°, arms placed on the box with palms down and hands stacked, initial position value recorded, participant reaching forward as far as possible without changing leg position, final position value recorded, and SRT distance calculated as the difference in centimeters between final and initial position values.

2. Functional Reach Test (FRT): The Functional Reach Test (FRT) was used to assess balance ability. The FRT has good inter-rater reliability (0.99) and intra-rater reliability (0.98). The measurement procedure involved participant standing with feet shoulder-width apart, close to a wall, arms raised parallel to shoulders, initial position measurement recorded, parallel to fingertips, participant reaching forward as far as possible without moving legs, final position measurement recorded, parallel to fingertips, and measurement value calculated by subtracting final position from initial position in centimeters.

Data Analysis

Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) 26.0 software. The Chi-Square test was employed to examine the relationships between variables, with a significance level set at 5% (α = 0.05). However, when the expected count was less than 5, Fisher’s Exact test was used instead. The Odds Ratio (OR) was calculated to assess the influence of the independent variable on the dependent variable. The interpretation of the OR was as follows: OR = 1 indicated no association, OR > 1 indicated a positive association, and OR < 1 indicated a negative association. This analytical approach enabled the examination of the relationships between lower extremity flexibility, balance, and physical function, while controlling for demographic factors.

Ethics Approval

This study received ethics approval from the Institutional Review Board (IRB) of STIKES Suaka Insan). The IRB reviewed the study protocol, informed consent form, and all data collection instruments to ensure that the study was conducted by ethical standards. The approval number for this study is: (REC.2023.02.001). All participants provided written informed consent before participating in the study, and their rights and confidentiality were protected throughout the study. The study was conducted in compliance with the Declaration of Helsinki and the principles of good clinical practice.

Results

The demographic characteristics of the respondents in this study provide a snapshot of the population under investigation. The age range of the respondents spanned nearly six decades, from a youthful 17 years old to a mature 76 years old, with a mean age of 46.2 years. In terms of gender, the study had a relatively balanced mix of male and female respondents, with a slight majority of males. The respondents’ body mass index (BMI) also varied, with a mean BMI of 22.7 kg/m² and a range that included both underweight and overweight individuals.

Demographic characteristics of respondents

The study consisted of 32 (53.5%) male and 29 (47.5%) female respondents as shown in Table 1. The mean age of the respondents was 46.2 ± 19.1 years, ranging from 17 to 76 years old. The majority of respondents (55.7%) were younger than 50 years old, while 44.3% were 50 years old or older. The mean Body Mass Index (BMI) of the respondents was 22.7 ± 4.3 kg/m², with a range of 12.2–42.6 kg/m². Based on categorized BMI, 62.3% of respondents had a lower BMI (<23 kg/m²), while 37.7% had a higher BMI (≥23 kg/m²) [Figures 1 and 2].

Table 1.

Respondent Characteristics

Variables	n (61)	%
Gender
Male	32	52.5
Female	29	47.5
Age
<50 years old	34	55.7
≥50 years old	27	44.3
BMI
<23 kg/m2	38	62.3
≥23 kg/m2	23	37.7

BMI: Body Mass Index. Source: Prepared by the author (2024)

Figure 1.

Sit and reach test

Figure 2.

Functional reach test

Exploring the relationships between variables and balance ability

The study investigated the relationships between various factors and balance ability, shedding light on the potential influences on this crucial aspect of physical function. The analysis revealed intriguing insights into the connections between demographic characteristics, physical attributes, and balance ability.

Associations between variables and balance ability

From Table 2, the results showed no significant relationship between gender and balance ability (P = 0.20 > 0.05). However, a significant relationship was found between age and balance ability (P = 0.01 < 0.05), with an odds ratio (OR) of 9.72 (95% CI: 2.97–31.79), indicating that older age is associated with decreased balance ability. Additionally, a significant relationship was found between BMI and balance ability (P = 0.01 < 0.05), with an OR of 3.92 (95% CI: 1.30–11.84), suggesting that higher BMI is associated with decreased balance ability. Furthermore, lower extremity flexibility was found to have a significant relationship with balance ability (P = 0.03 < 0.05), with an OR of 3.29 (95% CI: 1.12–9.65), indicating that decreased flexibility is associated with decreased balance ability.

Table 2.

Analysis of Relationship to Balance Ability

Variables	Balance Ability		P	OR (95% CI)
	Good n=31 (%)	Poor n=30 (%)
Gender
Male	19 (61.3)	13 (43.3)	0.20a	2.07 (0.75–5.75)
Female	12 (38.7)	17 (56.7)
Age
<50 years old	25 (80.6)	9 (30)	0.01a	9.72 (2.97–31.79)
≥50 years old	6 (19.4)	21 (70)
BMI
<23 kg/m2	24 (77.4)	14 (46.7)	0.01a	3.92 (1.30–11.84)
≥23 kg/m2	7 (22.6)	16 (53.3)
LEF
Good	23 (74.2)	14 (46.7)	0.03a	3.29 (1.12–9.65)
Poor	8 (25.5)	16 (53.3)

BMI: Body Mass Index; LEF: Lower Extremity Flexibility. ^aChi Square Test; ^bFisher’s Exact Test. Source: Prepared by the author (2024)

Analysis of the relationship to balance ability variables

The study examined the relationships between various variables and balance ability, revealing significant associations. Gender showed no significant relationship with balance ability (P = 0.20 > 0.05). However, age (<50 years old vs. ≥50 years old) demonstrated a significant relationship (P = 0.01 < 0.05), with an OR of 9.72 (95% CI: 2.97–31.79). Similarly, BMI (<23 kg/m^{2 vs.} ≥23 kg/m²) showed a significant relationship (P = 0.01 < 0.05), with an OR of 3.92 (95% CI: 1.30–11.84). Lower extremity flexibility (LEF) also exhibited a significant relationship (P = 0.03 < 0.05), with an OR of 3.29 (95% CI: 1.12–9.65). Further Analysis of Lower Extremity Flexibility When adjusting for other independent variables, lower extremity flexibility was not significantly associated with balance ability when adjusted for older age (P = 0.66 > 0.05) and higher BMI (P = 1.00 > 0.05). However, good lower extremity flexibility and younger age showed a significant association with good balance ability (P = 0.03 < 0.05), with an OR of 6.56 (95% CI: 1.21–35.73). Additionally, good lower extremity flexibility and lower BMI demonstrated a significant association with good balance ability (P = 0.01 < 0.05), with an OR of 7.50 (95% CI: 1.70–33.03).

Investigating the relationship between lower extremity flexibility and balance ability

The study delved into the relationship between lower extremity flexibility and balance ability, taking into account the potential influences of age and BMI. By adjusting for these factors, the analysis aimed to uncover the unique contributions of lower extremity flexibility to balance ability.

Analysis of the relationship between lower extremity flexibility and balance ability based on age and BMI adjustment

The study examined the relationship between lower extremity flexibility and balance ability, adjusting for age and BMI. Among participants younger than 50 years old, good lower extremity flexibility was significantly associated with good balance ability (P = 0.03 < 0.05), with an OR of 6.56 (95% CI: 1.21–35.73). However, this association was not significant among participants 50 years old or older (P = 0.66 > 0.05). When adjusting for BMI, good lower extremity flexibility was significantly associated with good balance ability among participants with a BMI < 23 kg/m² (P = 0.01 < 0.05), with an OR of 7.50 (95% CI: 1.70–33.03) [Table 3]. In contrast, no significant association was found among participants with a BMI ≥23 kg/m² (P = 1.00 > 0.05).

Table 3.

Analysis of the Relationship Between Lower Extremity Flexibility and Balance Ability Based on Age and BMI

Adjustment Variables	Lower Extremity Flexibility	Balance Ability		P	OR (95% CI)
		Good n (%)	Poor n (%)
<50 years old	Good	21 (84)	4 (44.4)	0.03b	6.56 (1.21-35.73)
	Poor	4 (16)	5 (55.6)
≥50 years old	Good	2 (33.3)	10 (47.6)	0.66b	0.55 (0.08-3.68)
	Poor	4 (66.7)	11 (52.4)
<23 kg/m2	Good	18 (75)	4 (28.6)	0.01a	7.50 (1.70-33.03)
	Poor	6 (25)	10 (71.4)
≥23 kg/m2	Good	5 (71.4)	10 (62.5)	1.00b	1.50 (0.22-10.30)
	Poor	2 (28.6)	6 (37.5)

^aChi Square Test; ^bFisher’s Exact Test. Source: Prepared by the author (2024)

Discussion

This study investigated the relationships between gender, age, BMI, and lower extremity flexibility with balance ability, yielding intriguing insights. The results revealed that gender does not have a significant relationship with balance ability, consistent with previous research by Steinberg.[25] However, age and BMI demonstrated significant relationships, with younger age and lower BMI serving as preventive variables against poor balance ability. Furthermore, the study found a significant correlation between lower extremity flexibility and balance ability, with excellent flexibility acting as a deterrent against poor balance ability.

The findings align with previous research, which suggests that age-related declines in sensory information and cognitive deficits contribute to balance impairments.[26] Higher BMI adversely affects balance ability, potentially due to decreased medial-lateral and anterior-posterior stability.[27,28,29] Reduced flexibility can lead to falls, and previous research has linked small gastrocnemius muscles to increased fall risk in the elderly.[30] The study’s results emphasize the importance of evaluating lower extremity flexibility before starting recovery programs to improve balance.

Insights and implications

The study’s findings have significant implications for injury prevention and functional performance, particularly in populations with lower limb injuries or undergoing rehabilitation. The importance of lower extremity flexibility in maintaining balance ability highlights the need for targeted exercises and interventions to improve flexibility and reduce fall risk. Additionally, the study’s results suggest that muscle strength variables should be included in future research to fully understand the relationship between flexibility and balance ability.

The correlation between lower extremity flexibility and balance ability is complex and influenced by various factors. Nakagawa’s[31] study found a strong positive correlation between sagittal balance ability and ankle or gastrocnemius muscle flexibility. Teyhen’s[32,33,34,35,36] research supports the results of this study, reporting a positive relationship between better gastrocnemius muscle flexibility and good balance ability in healthy soldiers. Anterior dynamic balance has been reported to be a risk factor for lower limb injury and a factor to predict functional performance on return to sport after anterior cruciate ligament reconstruction.[37,38,39,40]

In conclusion, this study contributes to the understanding of the relationships between gender, age, BMI, and lower extremity flexibility with balance ability.[41,42,43] The findings highlight the importance of evaluating lower extremity flexibility and addressing age-related declines in sensory information and cognitive deficits to improve balance ability.[44,45,46,47,48] Future research should include muscle strength variables to fully understand the relationship between flexibility and balance ability, and targeted exercises and interventions should be developed to improve flexibility and reduce fall risk.[49,50,51,52,53,54]

Conclusion

In conclusion, this study demonstrated that age, BMI, and lower extremity flexibility all have a significant impact on balance ability. Specifically, maintaining lower extremity flexibility and a lower BMI at a young age is crucial in preventing poor balance ability. However, this study also highlighted that lower extremity flexibility is not the sole variable influencing balance ability, and other factors should be considered. A limitation of this study is the exclusion of additional variables that may impact static and dynamic balance ability.

Future research should aim to address this limitation by investigating other factors, such as muscle strength, sensory information, and cognitive deficits, to determine their impact on balance ability. By exploring these factors, researchers can gain a more comprehensive understanding of the complex relationships influencing balance ability and develop targeted interventions to improve balance and reduce fall risk. Ultimately, this knowledge can inform the development of effective prevention and rehabilitation strategies for individuals with balance impairments.

Author contributions

UW, EEU, and BS are the principal investigators for this study. They led the study design, oversaw data collection and analysis, and were involved in manuscript drafting and revising. DP managed the study and was involved in data collection, data analysis, and drafting and revising the final manuscript. AR led data analysis and manuscript drafting, and finalization. IIL was involved in data analysis and interpretation, as well as drafting and revising the final manuscript. All authors approved the final version of this manuscript.

Conflict of interest

The authors declare there is no conflict of interest.

Funding Statement

This project was supported by BPPT and LPDP (BPI Kemendikbudristek) Indonesia. This research received support from STIKES Suaka Insan through a publication grant.