Comparison of pain,depression,quality of life,grip strength,and balance according to physical activity levels in office workers

Abstract

Background

Musculoskeletal problems are commonly observed among office workers.

Objective

This study aims to examine whether levels of physical activity are associated with differences in pain, depressive symptoms, quality of life, grip strength, and balance in office workers.

Methods

61 office workers (29 men and 32 women) who regularly used computers were included in the study. The Centers for Disease Control and Prevention Health-Related Quality of Life-4 for measuring the Quality of Life, the Visual Analog Scale for measuring pain, the Beck Depression Inventory for measuring mental health, the International Physical Activity Questionnaire–Short Form for measuring physical activity, the Biodex Balance System for measuring balance, and two distinct methods for measuring grip strength—the Jamar and Handgrip dynamometers—were all used in the assessments.

Results

A significant difference in pain during activity was found among the physical activity levels (inactive, minimally active, highly active) (p < 0.05). There was no difference in depression scores between the groups (p > 0.05). General quality of life scores were higher in the highly active group compared to both the inactive (p = 0.016) and minimally active (p = 0.020) groups. Right and left hand grip strength assessed with Jamar (p = 0.004, p = 0.044; respectively) and right hand grip strength assessed with handgrip (p = 0.04) were statistically significantly higher in the highly active group than in the inactive group. For balance with eyes open, anterior-posterior stabilization scores were significantly better in the highly active group compared to the inactive group (p = 0.004).

Conclusions

Physically active office workers exhibited superior outcomes in activity pain, quality of life, grip strength and balance compared to their less active counterparts.

Keywords

musculoskeletal physical activity quality of life body balance work related injury office workers

Introduction

Physical activity is defined as any bodily movement produced by skeletal muscles that requires energy expenditure.¹ During the COVID-19 pandemic, which has profoundly affected the entire world, the necessity of engaging in physical activity and maintaining a quality active lifestyle has been more strongly recognized. According to the results of a study conducted in Canada, 40.5% of individuals became less active during the pandemic, which imposed various restrictions on daily life.² However, physical activity is a crucial component that offers various benefits for individuals of all age groups. Regular physical activity reduces the risk of mortality, improves overall health, increases life expectancy, and helps decrease morbidity and mortality rates in individuals with chronic diseases.³ It is also considered a promising non-pharmacological approach for the treatment and prevention of depression in adults.⁴ Physical activity has protective effects in reducing the risk of hypertension, gestational diabetes, depressive symptoms, and the prevalence of common malignancies such as colon, breast, lung, and endometrial cancer.^5–8 Individuals with moderate to high levels of physical activity report significantly greater life satisfaction and happiness compared to those with low activity levels.⁹ Moreover, physical inactivity is associated with poor cognitive performance.¹⁰ Behavioral lifestyle interventions also reduce sedentary behavior in clinical populations and improve key cardiometabolic risk markers, such as waist circumference, body fat percentage, and glycemic control.¹¹

Given the broad impacts of physical activity on all segments of society and across all age groups, it is a particularly important issue for office workers, who are at risk of prolonged sedentary behavior due to occupational demands. From a biological perspective, research conducted in our country indicates that 81.7% of office workers report experiencing pain in at least one body region.¹² Office layout can also influence physical activity, as those working farther from the photocopier tend to have smaller waist circumferences.^13,14 Socially, regular physical activity can improve job satisfaction and quality of life for office workers.¹⁵ Given their elevated risk for numerous chronic diseases that negatively impact health-related quality of life, office workers should be encouraged to engage in physical activity to improve their overall well-being.¹⁶

Although numerous studies have established the general health benefits of physical activity, there remains a lack of detailed investigation into its multidimensional impact on office workers.^17,18 For example, Nguyen, Nguyen, and Kim (2021)¹⁶ conducted a systematic review and meta-analysis demonstrating that physical exercise improves health-related quality of life in office workers. While this provides valuable evidence for the overall benefits of exercise, the review primarily emphasized general quality of life outcomes and did not examine specific functional domains such as grip strength and balance, which are highly relevant to occupational performance and musculoskeletal health. Moreover, existing research often treats physical activity as a uniform construct without distinguishing between activity levels or their differential associations with biopsychosocial outcomes. This study addressed this gap by simultaneously evaluating pain, depressive symptoms, quality of life, grip strength, and balance according to physical activity levels in office workers. By integrating both psychosocial and functional measures, this study aimed to offer a more comprehensive perspective on how varying levels of physical activity influence health and work-related capacities. This approach may expands on previous literature and contributes practical insights for workplace health promotion strategies and aligns with broader frameworks such as the Total Worker Health approach. This study comprehensively evaluated the office workers from a biopsychosocial perspective according to their physical activity level. Therefore, the aim of this study was to determine whether there was differences in pain, depression, quality of life, grip strength, and balance across different levels of physical activity among office workers. Our research question was; Are there significant differences in pain, depressive symptoms, quality of life, hand grip strength, and balance among office workers with varying levels of physical activity (inactive, minimally active, highly active)?

Methods

Study design and participants

This study was conducted in the Department of Physiotherapy and Rehabilitation at the Faculty of Health Sciences, Karadeniz Technical University, between January 2023 and December 2024, with the participation of 61 individuals. The study was designed as a prospective and descriptive study. Ethics committee approval was obtained from Karadeniz Technical University Health Sciences Scientific Research Ethics Committee for this study (Number: E13562490-199-312067-25). A signed informed consent form was obtained from the participants. All procedures performed involving human participants followed the Declaration of Helsinki. Inclusion criteria were being between 25–55 years of age, having no movement restrictions, and having worked as an office employee for at least 5 years. Exclusion criteria were having a chronic, systemic, or infectious disease (e.g., diabetes, hypertension, COPD), sustaining an injury or undergoing surgery within the past 6 months, having had COVID-19 in the past 12 months, or having sought medical attention in the past 6 months due to a condition that may restrict physical activity.¹⁹ In this study, “office workers” were defined as individuals employed in administrative or clerical roles, who spent at least 6 h per workday seated and performing desk-based tasks, such as computer work, document preparation, or phone-based communication. All participants were employed full time (i.e., ≥ 40 h per week). We also confirm that the participants were asymptomatic at the time of the study and had no current diagnosis of musculoskeletal, or neurological disorders based on self-report.

The study population consisted of office workers aged 25–55 residing in the city of Trabzon. Participants were recruited from public universities (Trabzon University and Karadeniz Technical University) and municipal offices in Trabzon, Türkiye. Informational brochures describing the study aims and procedures were distributed within these institutions. Office workers who expressed interest and met the inclusion criteria were then enrolled in the study. Sample size was determined based on the effect size reported in a similar study.¹² For three physical activity groups (inactive, minimally active, and highly active), a total sample of 60 participants was calculated to provide 90% power with a 5% margin of error and a 0.4 effect size (Cohen's f). G*Power version 3.0.10 (Axel Buchner, Universität Kiel) was used for the sample size calculation.

Measurements

The data were obtained from the participants via face-to-face evaluations. After completing the sociodemographic data form (age, height, weight, education level, etc.), the following evaluations were conducted:

Visual Analog Scale (VAS)

Pain was evaluated using a horizontal 10-cm line on a plain white sheet labeled “no pain” on one end and “unbearable pain” on the other. Participants were asked to mark their pain level on the line. The point marked was measured in centimeters, providing a score out of 10 for pain intensity.¹⁹

Beck Depression Inventory (BDI)

Mental health was assessed using the BDI, which consists of 21 items rated on a 0–3 scale. Higher scores indicate more severe depressive symptoms: 10–16 points suggest mild depression, 17–29 indicate moderate, and 30–63 indicate severe depression.²⁰ For Turkish population, the internal consistency coefficients were high for both the nonclinical (α = 0.90) and clinical (α = 0.89) groups. Additionally, the test–retest reliability demonstrated strong stability (r = 0.94).²¹

International Physical Activity Questionnaire – Short Form (IPAQ-SF)

This internationally validated tool²² identifies sedentary lifestyles through questions about physical activity done for at least 10 consecutive minutes in the past 7 days. It evaluates time spent in vigorous activity, moderate activity, walking, and sitting. These durations are converted into MET-minutes/week using standardized MET (metabolic equivalent of task) values (1 MET = 3.5 ml/kg/min). Physical activity classification was based on MET values. Those with a total weekly physical activity level below 600 MET-minutes were defined as inactive. The total weekly physical activity level was determined as minimally active between 600 METs and 1500 METs. Those with a total weekly physical activity level of 3000MET and above were defined as highly active.

The validation study reported that the Turkish IPAQ-SF has acceptable levels of reliability and validity in the adult population. The test–retest reliability was found to be high, with intraclass correlation coefficients (ICC) ranging from 0.69 to 0.99. Furthermore, the questionnaire showed moderate concurrent validity when compared with an accelerometer (r = 0.33), supporting its use in population-based research, including among office workers.²³

The Centers for Disease Control and Prevention (CDC)- Health-related quality of life (HRQOL) scale (CDC HRQOL-4)

The CDC HRQOL-4 questionnaire is a short and practical measurement tool developed by the Centers for Disease Control and Prevention (CDC) to assess the subjective perception of health of individuals. The questionnaire consists of four basic questions: general health status, physical health in the last 30 days, mental health and the total number of unhealthy days. The CDC HRQOL-4, which is designed to be used in large-scale public health research, is particularly preferred for monitoring quality of life at the public health level, identifying health inequalities and evaluating the effectiveness of intervention programmes.²⁴

Grip Strength

Grip strength, indicative of general strength and forearm and wrist function, was measured using a hand dynamometer. Grip strength is also positively associated with hand function performance. Participants were seated and instructed to squeeze the dynamometer three times per hand. The mean of the three attempts was recorded in kilograms for both hands.²⁵

Balance Assessment

Dynamic balance was evaluated using the Biodex Stability System (Biodex 945-302, Biodex Medical Systems Inc., USA), which consists of a movable platform and a display screen. Participants were instructed verbally and shown a demonstration prior to testing. They were asked to maintain the on-screen marker within a designated area while standing on the moving platform. The direction and degree of sway were digitally recorded by the system.²⁶

Statistical analysis

Data were analyzed using SPSS version 26.0 for Windows. Normality of the data was tested using the Kolmogorov–Smirnov test. Normally distributed numerical variables were expressed as mean ± standard deviation, while non-normally distributed variables were expressed as median and interquartile range. Categorical variables were presented as frequencies and percentages. Participants were categorized into three groups based on their physical activity level (inactive, minimally active, highly active). For normally distributed variables, intergroup comparisons were made using One-Way ANOVA and post-hoc Tukey tests. For non-normally distributed variables, the Kruskal-Wallis H test was used, and Mann-Whitney U test with Bonferroni correction was applied for pairwise comparisons. A p-value of <0.05 was considered statistically significant.

Results

Demographic characteristics

The study was completed by 29 male (%48) and 32 female (%52) office workers. The mean age of the participants was 36.2 ± 7.7 year. Seventeen of the participants were smokers. The majority of participants (n = 57, 93%) were right-hand dominant, whereas only a small proportion (n = 4, 7%) were left-hand dominant. When the gender distribution across the groups was examined, the highly active group had a statistically significantly higher number of male participants and fewer female participants compared to the inactive group (p = 0.009). Regarding body weight, the minimally active group included significantly more overweight individuals than the inactive group (p = 0.028) (Table 1). The highly active group had significantly more individuals with postgraduate education and fewer individuals with undergraduate and high school education compared to the minimally active group (p = 0.010). There were no statistically significant differences between the groups in terms of age, height, or body mass index (BMI) (p = 0.230 for age, p = 0.106 for height and p = 0.127 for BMI). Among smokers, the average duration of smoking was 145.88 ± 95.74 months (minimum: 12 months, maximum: 288 months), and the average number of cigarettes smoked per day was 9.04 ± 6.05 packs. The majority of participants were right-hand dominant and the distribution of physical activity levels did not differ significantly according to dominant hand (p = 0.795). (Table 1).

Table 1.

Demographic characteristics of participants by physical activity level.

Characteristics	Inactive (n = 20)	Minimally Active (n = 20)	Highly Active (n = 21)	F/ H	P value
Characteristics	Mean ± SDMedian (IQR)	Mean ± SDMedian (IQR))	Mean ± SDMedian (IQR)	F/ H	P value
Age (years)	36.45 ± 7.71	37.95 ± 7.68	33.86 ± 7.55	1.507	0.230^a
Height (cm)	164.50(10) 165.60 ± 7.21	169.50(15) 169.70 ± 7.94	173.00(14) 171.05 ± 7.64	4.492	0.106^b
Weight (kg)	68.85 ± 11.74	80.35 ± 16.56	75.83 ± 11.87	3.656	0.032*^a
BMI (kg/m²)	25.17 ± 4.45	27.79 ± 4.97	25.80 ± 2.92	2.142	0.127^a
Gender (M/F)	5 M (25%),15F (75%)	10 M (50%), 10F (50%)	14 M (66.7%), 7F (33.3%)	0.027	0.024*^c
Marital Status	3 Single (15%), 17 Married (83%)	7 Single (35%), 1 Divorced (5%), 12 Married (60%)	10 Single (47.6%), 11Married (52.4%)	0.105	0.125^c
Education Level	2 HS (10%), 3 UG (15%), 15 PG (75%)	4 HS (20%), 8 UG (40%), 8 PG (40%)	1 HS (4.8%), 2 UG (9.5%) 18 PG (85.7%)	0.034	0.035^c
Smoking (Yes/No)	4 (20%) 16 (80%)	6 (30%) 14 (70%)	7 (33.3%) 14 (66.7%)	0.615	0.605^c
Dominant hand (right/left)	19 (95%) 1 (5%)	19 (95%) 1 (5%)	19 (90%) 2 (10%)	0.460	0.795^c

IQR: Interquartile Range, SD: Standard Deviation, HS: High School, UG: Undergraduate, PG: Postgraduate.

p^a: p value obtained using One-Way Analysis of Variance. p^b: The p value obtained using Kruskal Wallis H test. p^c: The p value obtained using the Chi-Square test. Note: ‘F’ value is given when One-Way Analysis of Variance is used and ‘H’ value is given when Kruskal-Wallis H test is used.

Pain

A significant difference in pain during activity, as measured by the Visual Analog Scale (VAS), was found among the groups (p = 0.031). Pairwise comparisons showed that this difference was between the inactive and highly active groups (p = 0.015). No significant differences were observed among the groups regarding resting pain or night-time pain (p = 0.270 for resting pain and p = 0.213 for night-time pain) (Table 2).

Table 2.

Pain levels by physical activity group (VAS scores).

Pain Type	Inactive (n = 20)	Minimally Active (n = 20)	Highly Active (n = 21)	H	P value	Post-hoc P value
Pain Type	Median (IQR)	Median (IQR)	Median (IQR)
Resting Pain	3.9 (0–5)	2.5 (0–4)	1.7 (0–3.5)	2.618	0.270	-
Activity Pain	5.8 (3–6)	4 (2.7–5.7)	2 (0–4.3)	6.940	0.031	0.015 HA < IA
Night Pain	5 (0–6)	1 (0–5)	0.8 (0–3.5)	3.095	0.213	-

VAS Visual Analogue Scale, IQR: Interquartile Range. p: The p value obtained using Kruskal Wallis H test. HA: Highly Active, IA: Inactive

Depression and quality of life

There was no statistically significant difference in depression scores between the groups (p = 0.085). However, general quality of life scores were significantly higher in the highly active group compared to both the inactive (p = 0.016) and minimally active (p = 0.020) groups. No statistically significant differences were found among the groups for the physical, mental, and leisure activity subdomains of the quality of life scale (p = 0.305 for physical, p = 0.079 for mental and p = 0.073 for leisure activity) (Table 3).

Table 3.

Depression and quality of life scores by physical activity level.

Measure	Inactive (n = 20)	Minimally Active (n = 20)	Highly Active (n = 21)	H/F	p	Post-hoc P value
Measure	Median (IQR)Mean ± SD	Median (IQR)Mean ± SD	Median (IQR)Mean ± SD	H/F	p	Post-hoc P value
BDI	10 (4–13)	10 (8–13)	6 (2–9)	4.934	0.085^b	-
QoL
General QoL	3 (2–4)	3 (2–4)	4 (3–4)	7.491	0.024*^b	HA > IA 0.016HA > MA0.020
Physical	5.44 ± 6.81	5.37 ± 8.94	2.65 ± 2.60	1.212	0.305^a	-
Mental	6.56 ± 8.45	7.47 ± 9.41	2.70 ± 4.21	2.660	0.079^a	-
Leisure	4.17 ± 5.15	4.42 ± 7.58	0.90 ± 1.51	2.741	0.073^a	-

BDI: Beck Depression Inventory, IQR: Interquartile Range, SD: Standard Deviation. p^a: P value obtained using One-Way Analysis of Variance. p^b: P value obtained using Kruskal Wallis H test. Note: ‘F’ value is given when One-Way Analysis of Variance is used and ‘H’ value is given when Kruskal Wallis H test is used. HA: Highly Active, IA: Inactive, MA: Minimally Active

Grip strength

Right-hand grip strength measured using the Jamar dynamometer was significantly higher in the highly active group compared to the inactive group (p = 0.004). Similarly, left-hand grip strength also demonstrated a statistically significant difference between the highly active and inactive participants (p = 0.044). Furthermore, right-hand grip strength measured using the handgrip dynamometer was found to be significantly greater in the highly active group than in the inactive group (p = 0.04) (Table 4).

Table 4.

Hand grip strength (kg) by physical activity level.

Test	Inactive (n = 20)	Minimally Active (n = 20)	Highly Active (n = 21)	F	p	Post-hoc P value
Test	Mean ± SD	Mean ± SD	Mean ± SD	F	p	Post-hoc P value
Jamar - Right	28.95 ± 2.95	37.67 ± 3.29	41.39 ± 2.58	5.778	0.005*^a	HA > IA0.004
Jamar - Left	28.75 ± 2.92	35.63 ± 3.28	37.90 ± 2.66	3.199	0.048*a	HA > IA0.044
Handgrip - Right	29.33 ± 4.15	34.51 ± 2.64	42.48 ± 3.94	3.332	0.043*^a	HA > IA0.04
Handgrip - Left	28.19 ± 4.68	31.36 ± 2.87	39.75 ± 3.17	2.714	0.075^a	-

SD: Standard Deviation, p^a: P value obtained using One-Way Analysis of Variance. HA: Highly Active, IA: Inactive, MA: Minimally Active

Balance

For balance with eyes open, anterior-posterior stabilization scores were significantly better in the highly active group compared to the inactive group (p = 0.004). No statistically significant differences were found among the groups for eyes- opened and closed balance measures (p = 0.238 for eyes opened total stabilization, p = 0.523 for eyes opened total sway, p = 0.821 for eyes closed total stabilization and p = 0.988 for eyes closed total sway) (Table 5).

Table 5.

Balance by physical activity level.

Parameter			Inactive (n = 20)	Minimally Active (n = 20)	Highly Active (n = 21)	F/ H	p	Post-hoc P value
Parameter			Mean ± SDMedian (IQR)	Mean ± SDMedian (IQR)	Mean ± SDMedian (IQR)
Eyes-opened	Total	Stabilization	0.51 ± 0.03	0.51 ± 0.07	0.41 ± 0.02	1.474	0.238^a	-
	Total	Sway	0.52 ± 0.04	0.51 ± 0.04	0.46 ± 0.02	0.655	0.523^a	-
	Anterior/ Posterior	Stabilization	0.40(0.20–0.50)	0.40(0.20–0.50)	0.30 (0.08–0.35)	7.807	0.020*^b	HA < IA0.004
	Anterior/ Posterior	Sway	0.47 ± 0.03	0.47v0.04	1.86 ± 1.42	0.915	0.406^a	-
	Left/Right	Stabilization	0.20 ± 0.02	0.18 ± 0.02	0.15 ± 0.01	1.187	0.313^a	-
	Left/Right	Sway	0.21 ± 0.02	0.20 ± 0.01	0.62 ± 0.44	0.861	0.428^a	-
Eyes-closed	Total	Stabilization	1.52 ± 0.10	1.60 ± 0.26	1.43 ± 0.13	0.198	0.821^a	-
	Total	Sway	1.09 ± 0.05	1.11 ± 0.11	1.11 ± 0.10	0.012	0.988^a	-
	Anterior/ Posterior	Stabilization	1.27 ± 0.09	1.31 ± 0.23	1.31 ± 0.13	0.020	0.980^a	-
	Anterior/ Posterior	Sway	1.01 ± 0.05	1.05 ± 0.10	1.09 ± 0.10	0.190	0.827^a	-
	Left/Right	Stabilization	0.59 ± 0.07	0.56 ± 0.14	0.34 ± 0.04	2.212	0.119^a	-
	Left/Right	Sway	0.39 ± 0.03	0.37 ± 0.05	0.28 ± 0.02	2.450	0.095^a	-

IQR: Interquartile Range, SD: Standard Deviation. p^a: P value obtained using One-Way Analysis of Variance. p^b: P value obtained using Kruskal Wallis H test. Note: ‘F’ value is given when One-Way Analysis of Variance is used and ‘H’ value is given when Kruskal Wallis H test is used. HA: Highly Active, IA: Inactive.

Discussion

The aim of this study was to compare multidimensional health indicators such as pain, depression, quality of life, grip strength, and balance across different physical activity levels in office workers. According to the study findings, increased physical activity was significantly associated with lower activity-related pain. Also, increased physical activity was significantly related to higher general quality of life, greater grip strength, and better anterior-posterior balance with eyes open. These results suggest that physical activity not only supports general health but may also play a protective and enhancing role in addressing work-related musculoskeletal issues and functional capacity.

Our findings revealed significant differences between groups in terms of gender, weight, and education level according to physical activity levels. Notably, the proportion of men was significantly higher and women significantly lower in the highly active group, indicating a gender-based disparity in physical activity engagement. This aligns with existing literature on office workers. Women often report lower activity levels due to greater domestic responsibilities, cultural norms, safety concerns, and limited access to physical activity opportunities.²⁷ Although it is often assumed that higher physical activity is associated with lower body weight, our findings did not show a linear relationship across activity levels. Interestingly, while the minimally active group demonstrated a higher prevalence of overweight individuals, the inactive group had a lower average body weight compared to both the minimally and highly active groups. This paradoxical result may be influenced by several unmeasured factors such as nutritional habits, body composition (e.g., lower muscle mass in inactive individuals), metabolic rate, or health conditions that could affect both activity and weight status. Therefore, instead of suggesting a direct causal relationship, our findings highlight the complex and potentially non-linear interaction between physical activity, sedentary behavior, and body weight among office workers. These results underscore the need for future studies to consider additional factors such as diet, muscle mass, and metabolic health to better understand this relationship.²⁸ In terms of education level, a greater proportion of individuals in the highly active group held postgraduate degrees. This supports previous research suggesting that higher education levels may contribute to greater awareness, health literacy, and time management abilities related to physical activity.^29,30 These results underscore the importance of considering demographic factors such as gender, weight, and education in efforts to promote physical activity among office workers.

Office work typically involves prolonged static postures associated with reading, writing, repetitive movements, poor hand positioning, and insufficient forearm support.²⁸ Among computer-using office workers, the leading contributors to musculoskeletal pain include non-ergonomic chairs, improper keyboard and mouse use, repetitive movements, poor posture, and suboptimal workplace ergonomics.³¹ Thus, musculoskeletal pain in office workers is influenced not only by behavioral factors but also by environmental and organizational risk factors. Unlike most of the existing literature, the study evaluated resting, activity-related, and night-time pain across physical activity levels. The results showed that individuals in the highly active group reported significantly lower levels of activity-related pain. While causality cannot be established, the observed association between physical activity and reduced musculoskeletal discomfort suggests that promoting regular movement may be beneficial for office workers. Additionally, the relatively high pain scores observed in all groups emphasize the need for ergonomics education to help reduce physical strain in office settings.

Although there was no statistically significant differences in depression scores between physical activity groups, prior research strongly supports the mental health benefits of physical activity. Meta-analyses involving office workers have shown that regular physical activity significantly reduces the frequency and severity of depressive symptoms.^14,28,32 Depression risk is also associated with prolonged sitting, low job satisfaction, and psychosocial stress — all of which physical activity may help to mitigate.³³ The absence of a significant difference in depression levels in this study may be due to generally low depression scores across participants, or to the failure to distinguish adequately between physical activity types, intensities, and frequencies. Furthermore, psychological evaluations such as depression can be influenced by cultural factors, individual perception, and reporting behavior. Future research should evaluate the relationship between physical activity and depression using more sensitive instruments and longitudinal study designs.

This study found that general quality of life scores was significantly higher in the highly active group. This finding is consistent with current literature demonstrating that physical activity positively impacts health-related quality of life. Multicenter studies among office workers have identified positive correlations between regular physical activity and both physical and mental components of quality of life.^16,28 Physical activity is especially beneficial in improving energy levels, perceived general health, and social functionality. The absence of significant differences in the physical, mental, and leisure subdomains in this study may indicate that these dimensions are more sensitive to individual factors. Additionally, the specific type of activity may have limited the impact on subdomains. Some studies suggest that leisure-time physical activity (rather than occupational physical activity) plays a more central role in enhancing quality of life.²⁹ Therefore, it may be concluded that consistent, adequately dosed, and sustainable physical activity maximizes its benefits for quality of life.

This study also found that the grip strength of the highly active group was significantly greater than that of the inactive group. However, it is important to note that grip strength is significantly influenced by sex, and our sample included both male and female participants. In this respect, our results should be interpreted with caution. Our findings contrasts with findings from Genin et al.,³³ who reported no significant difference in grip strength between active and inactive office workers. Our findings indicated that higher levels of regular physical activity were associated with better grip strength among office workers. Since office workers may experience frequent hand and wrist pain or injuries, promoting physical activity could be especially beneficial for this population. The difference between our findings and those of Genin et al. could be attributed to differences in measurement methods, professional roles within sample groups, and whether hand dominance was considered in the analysis.³³ Further research that targets different muscle groups and accounts for limb asymmetries is needed to better understand the relationship between physical activity and grip strength.

Finally, our results revealed that the highly active group performed significantly better in balance tests with eyes open in the anterior-posterior direction, although no significant differences were observed with eyes closed. Onofrei and Amaricai³⁴ reported that individuals with low physical activity had impaired postural control and increased lateral sway under eyes-closed conditions. Similarly, Zhu et al.²⁸ found a positive relationship between physical activity and static balance, while Arca et al.³⁵ observed lower dynamic balance performance among desk-bound employees. These studies support our findings regarding better open-eye balance in physically active individuals. The absence of significant group differences under eyes-closed conditions indicates that postural control relies heavily on visual input, and the elimination of this input may attenuate the observable effects of physical activity on balance performance. When visual stimuli are removed, balance relies more heavily on internal proprioceptive input, which may override the benefits conferred by physical activity alone.

Limitations

This study is limited in several ways. First, the use of the IPAQ-Short Form provides a general estimate of physical activity in terms of MET-minutes per week but does not capture more detailed information such as the frequency, duration, intensity, or type of physical activity. These additional parameters could have provided deeper insights into how specific patterns of activity are related to outcomes such as pain, grip strength, and balance. Second, the sample size was relatively small, and sex differences were not controlled for, which may have influenced outcomes such as grip strength and balance. Moreover, the cross-sectional design precludes causal interpretations. Future studies with larger samples and objective, longitudinal assessments are needed to clarify these associations. Additionally, future studies should consider more objective evaluation methods such as ergometers or laboratory-based maximal aerobic capacity tests to enhance measurement accuracy.

Conclusions

In conclusion, this study indicates that physically active office workers demonstrate better performance in several health and wellness indicators compared to their less active counterparts. These findings suggest that physical activity plays not only a general health-promoting role, but also a protective and enhancing role in improving pain and quality of life, increasing grip strength, and enhancing balance. The findings of this study have potential implications for workplace health promotion strategies. Although causality cannot be established, higher physical activity levels appear beneficial for both physical and psychosocial health in this population. Promoting regular movement and ergonomic practices in the workplace may help reduce sedentary-related risks and enhance employee well-being.

Footnotes

ORCID iD

Umut Apaydın

Ethical approval

Karadeniz Technical University Health Sciences Scientific Research Ethics Committee approved this study (Number: E13562490-199-312067-25).

Informed consent

A signed informed consent form was obtained from the participants.

CRediT authorship contribution statement

Umut Apaydın: Conceptualization, Methodology, Investigation, Writing – original draft, Emre Şenocak: Data collection, Formal analysis, Kübra Canlı: Data collection, Formal analysis, Nurhayat Korkmaz Üçüncü: Data Collection, Murat Emirzeoğlu: Methodology, Investigation, Data Collection, Turgay Altunalan: Methotology, Critical editing of the manuscript, Bayram Dündar: Data Collection, Melike Gültekin: Data Collection, Arzu Erden Güner: Conceptualization, Methodology, Investigation, Critical editing of the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Office of Scientific Research Projects of Karadeniz Technical University. Project number: TAY-2023-10459.

Karadeniz Technical University, (grant number TAY-2023-10459).

Declaration of conflicting interests

Ethics committee approval was obtained from Karadeniz Technical University Health Sciences Scientific Research Ethics Committee for this study (Number: E13562490-199-312067-25). A signed informed consent form was obtained from the participants.

Data availability

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

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