Body mass index and vital lung capacity as determinants of maximum oxygen volume (VO₂ max): assessing fitness in a sedentary population

Abstract

[Purpose]

The increasing prevalence of sedentary lifestyles in modern society has become a significant public health concern, correlating with a rise in obesity rates and various chronic diseases, including cardiovascular and respiratory diseases. A critical metric often assessed in health evaluations is maximum oxygen consumption (VO₂ max), which is instrumental in gauging an individual’s aerobic fitness level. University staff members who engage in limited physical activity are at risk of reduced vital lung capacity (VLC) due to elevated Body Mass Index (BMI). Therefore, this study aimed to determine the relationship between BMI and VLC as predictors of maximum oxygen consumption (VO₂ max) in a sedentary population.

[Methods]

An observational cross-sectional study was conducted among 75 male staff members, selected through purposive sampling. Data were collected by measuring BMI and waist circumference, performing spirometry to assess VLC, and performing the Harvard Step Test to assess VO₂ max. Multivariate analysis was performed using linear regression.

[Results]

The mean of BMI, VLC, and VO₂ max were 26.02 ± 3.70, 60.13 ± 15.45, and 40.40 ± 3.71. BMI (p = 0.002) and VLC (p = 0.05) were statistically significant independent predictors of VO₂ max in the sedentary population.

[Conclusion]

This study concluded that VO₂ max was negatively associated with BMI and positively associated with VLC.

INTRODUCTION

Obesity has become a significant global health problem, including in Indonesia. The prevalence of obesity among Indonesian adults has exceeded 28%, representing a substantial increase compared with previous years. Obesity is associated not only with metabolic diseases such as diabetes mellitus and hypertension, but also with impaired lung function and the overall cardiovascular system [1]. Excessive fat accumulation, particularly in the abdominal and thoracic regions, contributes to decreased lung compliance and increased chest wall stiffness. Abdominal fat accumulation can compress the diaphragm cranially, limiting lung expansion and increasing the breathing workload. This condition leads to a restrictive ventilatory disorder pattern, which can be assessed by reduced lung vital capacities, including forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1) [2].

Active smoking is also a significant risk factor for decreased lung function and reduced cardiovascular capacity. Harmful chemicals in cigarette smoke, such as nicotine, tar, and carbon monoxide, can cause direct lung tissue damage, leading to chronic inflammation and reduced gas exchange efficiency. A study by Vildania et al. (2021) showed a significant correlation between smoking severity and decreased lung function, with reductions in FEV1 and FVC proportional to the number of cigarettes smoked per day [3]. This condition is worsened by obesity. The combination of obesity and smoking can impair lung function and reduce the body’s capacity to provide and utilise oxygen, as indicated by the maximum oxygen volume (VO₂ max) parameter. VO₂ max is a crucial measure of cardiorespiratory fitness and has a substantial impact on a person’s ability to endure physical exertion. A decrease in VO₂ max not only indicates diminished physical capacity but also serves as a risk marker for chronic diseases, such as heart failure, chronic obstructive pulmonary disease (COPD), and metabolic syndrome [4].

A previous study reported that office workers aged 40-60 years who were active smokers had significantly lower VO₂ max values than non-smokers, especially when accompanied by an increased body mass index (BMI) [4]. Similar findings were reported in a 2021 study conducted in Indonesia, which identified negative relationships between BMI and vital lung capacity and VO₂ max among college students with sedentary lifestyles [5]. University employees and other office-based workers often perform tasks that require prolonged sitting and limited physical activity. Such sedentary occupational patterns have been associated with an increased risk of overweight and obesity due to reduced energy expenditure and prolonged sedentary behavior during working hours. Several studies have reported that sedentary work environments, particularly desk-based occupations such as academic or administrative positions, are associated with higher BMI and increased cardiometabolic risk factors among employees [6].

In academic settings, such as universities, sedentary lifestyles, work stress, high-calorie diets, and smoking can increase the risk of obesity and reduce physical capacity. Academic staff commonly experience substantial workloads, which may contribute to reduced physical activity and place them at a higher risk of chronic lung function impairment [7,8]. Unfortunately, to date, few studies have specifically examined the impact of obesity and smoking on lung function and aerobic capacity (VO₂ max) among university staff. Moreover, the preventive health monitoring program for faculty members remains limited in this regard. Therefore, it is vital to evaluate the risk factors that could affect pulmonary and cardiovascular health, especially among academic staff who smoke and are obese. The objective of this study was to examine the associations of body mass index (BMI) and vital lung capacity with maximal oxygen consumption (VO₂ max) and to identify their predictive roles in determining cardiorespiratory fitness among male academic staff with predominantly sedentary occupational activities.

METHODS

Participants of the Study

A cross-sectional study was conducted among 75 male academic staff members. The participants were selected using purposive sampling. The inclusion criteria were staff aged 25-60 years who had smoked at least one cigarette per day for the past year. Respondents with comorbidities such as chronic lung disease, heart disease, or severe musculoskeletal disorders, and those who declined to participate were excluded. A sedentary population refers to individuals whose occupational activities predominantly involve prolonged sitting and low levels of physical activity during working hours. Academic staff generally perform desk-based tasks such as teaching preparation, administrative work, and computer-related activities, all of which require extended periods of sitting and minimal physical movement [9].

Variables Measurements

Participants’ BMI was calculated based on body weight and height measurements. Body weight was recorded on calibrated digital scales, whereas height was measured using a microtoise while participants stood barefoot in an upright position against a wall. BMI values were categorised according to standard guidelines as follows: underweight (< 18.5 kg/m²), normal weight (18.5-24.9 kg/m²), overweight (25.0-29.9 kg/m²), and obesity (≥ 30.0 kg/m²). Waist circumference was measured using a standard protocol with a non-elastic tape measure. The measurement point was identified as the midpoint between the lower ribs and the iliac crest [9]. The Brinkman Index (BI) was classified by the number of cigarettes smoked per day multiplied by the duration of smoking in years: light (BI 1-200), moderate (BI 200-600), and heavy (BI > 600) smokers [10].

Vital lung capacity was assessed using spirometric measurements, specifically forced vital capacity (FVC) and forced expiratory volume in one second (FEV1). These parameters were measured using a calibrated spirometer, in which participants performed maximal inhalation followed by forced exhalation [11]. The Harvard Step Test was used to estimate cardiorespiratory fitness (VO₂ max). In this procedure, participants stepped up and down on a standardized platform at a constant rhythm for approximately five minutes or until exhaustion. After completing the exercise, heart rate was recorded during the recovery period at one, two, and three minutes post-exercise. These recovery heart rate values were then used to calculate a fitness index and estimate maximal oxygen consumption (VO₂ max). This method is widely used as a simple and reliable field test for assessing aerobic fitness and cardiovascular endurance [12,13].

Body weight was measured using a digital weighing scale (Omron HN-289, Omron Healthcare Co., Ltd., Kyoto, Japan). Height was measured using a portable stadiometer (Seca 213, Seca GmbH & Co. KG, Hamburg, Germany). Pulmonary function, including vital lung capacity, was assessed using a spirometer (MicroLab ML3500, CareFusion, United Kingdom) according to standard spirometry procedures. BMI was reported in kilograms per square meter (kg/m²), waist circumference in centimeters (cm), vital lung capacity as a percentage of the predicted value (%), and maximal oxygen consumption (VO₂ max) in milliliters per kilogram per minute (ml/kg/min). Participant characteristics and recruitment procedures are summarized in Figure 1.

Figure 1. Flow chart of study participants.

Statistical Analyses

The obtained data were analysed using computer-based statistical software. Each variable was calculated and represented as a mean and a number (percentage) in the table. Spearman’s correlation was performed to determine significant associations between the study variables and VO₂ max. The significance level (p-value) was set at 0.05. Multivariate analysis was conducted using multiple linear regression with backward selection to assess independent predictors of VO₂ max among participants. The initial regression model included BMI, waist circumference, and vital lung capacity (VLC) as potential independent variables based on their theoretical relevance to cardiorespiratory fitness. The backward elimination procedure was then sequentially removed non-significant variables until the final model identified the most significant predictors of VO₂ max. Before regression analysis, the basic assumptions of linear regression, including normality, linearity, and multicollinearity, were assessed to ensure model validity. All statistical analyses were performed using IBM SPSS Statistics version 25.0 (IBM Corp., Armonk, NY, USA).

Ethical Committee Statement

The present research received ethical approval from the Health Research Ethics Committee of the Faculty of Medicine, Universitas Malikussaleh (No. 12/UN45.2.6/KEPK/2025).

RESULTS

Participant Demographics

Seventy-five participants were enrolled in this study. The mean age of the participants was 41.77 ± 6.92 years. The mean age of smoking was 21.92 ± 8.98 years, the age of first smoking was 19.85 ± 4.98 years, and the 18.89 ± 10.52 cigarettes smoked/day. The mean height and weight of the participants were 166.16 ± 6.41 cm and 71.96 ± 13.48 kg, respectively. The mean VO₂ max, waist circumference, and vital lung capacity were 40.40 ± 3.70 ml/kg/min, 85.68 ± 7.95 cm, and 60.13 ± 15.45%, respectively (Table 1).

Table 1.

Characteristics of the participants

Characteristics of the study participants	n
	Minimum	Maximum	Mean	SD
Age (year)	26	58	41.77	6.92
Duration of smoking (years)	6	38	21.92	8.98
Age of first smoking (year)	14	37	19.85	4.98
Number of cigarettes smoked/day	5	48	18.89	10.52
Height (cm)	145	183	166.16	6.41
Body weight (kg)	43	110	71.96	13.48
VO2 max (ml/kg/min)	31.00	46.90	40.40	3.70
Waist circumference	61	108	85.68	7.95
Vital lung capacity (%)	22.70	93.87	60.13	15.45

n = 75; SD: Standard Deviation.

As shown in Table 2, the majority of the participants had grade 1 obesity (42.7%) and were moderate smokers (77.3%).

Table 2.

Proportions of body mass index and Brinkman index of the participants

Variables	n	Percentage (%)
Body mass index (BMI) (kg/m2)
Underweight	1	1.3
Normal weight	20	26.7
Overweight	11	14.7
Obesity grade 1	32	42.7
Obesity grade 2	11	14.7
Brinkman index (BI)
Light	6	8
Moderate	58	77.3
Heavy	10	13.3

The Kolmogorov-Smirnov test indicated that the variables BMI, waist circumference, and vital lung capacity were abnormal (p ≤ 0.05); therefore, Spearman’s rank correlation was performed. As indicated in Table 3, VO₂ max was significantly associated with BMI, waist circumference, and vital lung capacity in the Spearman’s correlation analysis. BMI (p = 0,003; r = -0.35) and waist circumference (p value = 0,018; r = -0.27) showed a reliable negative correlation with VO₂ max, suggesting that as BMI and waist circumference increase, VO₂ max tends to decrease. Vital lung capacity was identified as a reliable positive correlate of VO₂ max (p = 0,044; r = 0.23), suggesting that as lung vital capacity increases, VO₂ max tends to increase.

Table 3.

Relationship between BMI, waist circumference, and vital lung capacity with VO₂ max

	VO2 max
	Mean	S.E	r	p-value
BMI (kg/m2)	26.02	3.70	-0.35	0,003*
Waist circumference (cm)	85.68	7.95	-0.27	0.018*
Vital lung capacity (%)	60.13	15.45	0.23	0.044*

Data were analysed using Spearman’s correlation test.

^*Statistical significance was set at p ≤ 0.05.

S.E: Standard Error.

Predictors of VO₂ Max Analysis

As shown in Table 4, the independent predictors of VO₂ max among the participants were BMI (B = -0.29; 95% CI = -0.47-0.12) and vital lung capacity (B = 0.05; 95% CI = 0.01-0.10). The p-value for vital lung capacity (VLC) in the multivariate regression model was confirmed to be p = 0.050, which meets the predefined threshold for statistical significance (p ≤ 0.05). Although the bivariate analysis indicated that waist circumference (p = 0.018) was significantly associated with VO₂ max, this association lost significance in the multivariate analysis.

Table 4.

VO₂ max Prediction Model of the study participant

Model	Variables	VO2 max
		t	B (95% CI)	R2	p-value
Model 1	BMI	-2.45	-0.31 (-0.57-0.06)	0,208	0,016*
	Vital lung capacity	1.98	0.05 (0.01-0.10)		0,050*
	Waist circumference	0.24	0.02 (-0.13-0.16)		0,811
Model 2	BMI	-3.27	-0.29 (-0.47-0.12)	0,207	0,002*
	Vital lung capacity	1.98	0.05 (0.01-0.10)		0,050*

Data were analysed using multiple linear regression with the backward method of analysis.

^*Statistical significance was set at p ≤ 0.05. (CI = 95%).

DISCUSSION

Obesity assessment relies not only on BMI but also on other anthropometric parameters, such as waist circumference and waist-to-hip ratio, as indicators of central obesity [14]. There are two main patterns of body fat distribution: central and peripheral. Central obesity is characterised by increased fat accumulation in the thorax, abdomen, and visceral organs. Peripheral obesity is characterised by fat accumulation in the hips, thighs, and legs, as well as in subcutaneous tissues. This distinction is important because central obesity has a more direct impact on lung mechanics and a more significant effect on metabolic inflammation [15]. Obesity and smoking may exert synergistic adverse effects on pulmonary function and cardiorespiratory fitness. Excess body fat, particularly central obesity, can mechanically restrict lung expansion and reduce lung compliance, while smoking contributes to airway inflammation, oxidative stress, and impaired gas exchange. When these two factors coexist, their combined effects may accelerate the decline in lung function and further compromise aerobic capacity, thereby increasing the risk of respiratory and cardiovascular diseases [16].

In occupational health research, sedentary work environments are increasingly recognized as important determinants of cardiometabolic and respiratory health. Prolonged sitting and limited physical activity in desk-based occupations may contribute to increased BMI and reduced cardiorespiratory fitness. Excess body weight can mechanically affect respiratory function by limiting chest wall expansion and reducing lung volumes, thereby influencing aerobic capacity. Therefore, examining BMI and pulmonary function within sedentary occupational groups provides important insight into the determinants of cardiorespiratory fitness [17].

Our study indicated negative correlations between Body Mass Index (BMI) and VO₂ max (r = -0.35; p = 0.003) and between waist circumference and VO₂ max (r = -0.27; p = 0.018). Conversely, vital lung capacity was positively correlated with VO₂ max (r = 0.23; p = 0.044). Further analysis reported that BMI and vital lung capacity were independent predictors of VO₂ max in a sedentary population. Recent studies confirmed that obesity is closely associated with decreased vital lung capacity. Increasing BMI and waist circumference significantly reduce lung function parameters, such as forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) [16,18].

Furthermore, excessive body composition, particularly visceral fat, has been reported to suppress lung expansion, thereby reducing vital lung capacity and cardiorespiratory fitness [19]. Similarly, we observed negative correlations between BMI and waist circumference and between BMI and VO₂ max. Physiologically, abdominal fat accumulation increases chest wall resistance and decreases lung compliance, thereby reducing vital lung capacity. This condition results in a decrease in VO₂ max due to reduced oxygen supply to the muscle tissue.

Furthermore, the study found that vital lung capacity was progressively associated with VO₂ max, suggesting that improved lung function is associated with higher VO₂ max values. The relationship between vital lung capacity and maximal oxygen uptake (VO₂ max) is of significant interest in respiratory and exercise physiology. Numerous studies have shown a progressive association between these two parameters, with critical implications for clinical practice and physical fitness assessment. Parameters such as forced expiratory volume (FEV1) and forced vital capacity (FVC) are influenced by body height, weight, and age, establishing the effects of these physiological changes on both lung function and aerobic capacity. Higher lung volumes allow individuals to achieve greater ventilatory capacities during physical activity, thus supporting increased oxygen uptake and delivery to the muscles, which is essential for a higher VO₂ max [20,21].

The progressive association between vital lung capacity and maximal oxygen uptake (VO₂ max) is particularly critical when evaluating sedentary lifestyles, in which reduced physical activity can significantly affect pulmonary health and exercise performance. The relationship between lung function parameters, such as forced vital capacity (FVC) and forced expiratory volume in one second (FEV1), correlates with VO₂ max, even in less active populations. Individuals who engage in prolonged inactivity are at higher risk of developing respiratory issues, such as reduced lung volumes, which can negatively affect VO₂ max [22].

The results of the present study demonstrate a positive association between vital lung capacity (VLC) and maximal oxygen consumption (VO₂ max). Participants with higher VLC values tended to exhibit higher VO₂ max levels, indicating better cardiorespiratory fitness. However, due to the cross-sectional design of this study, the findings do not establish a progressive or causal relationship but rather indicate a significant positive correlation between pulmonary function and aerobic capacity. Previous studies have also reported that lung function parameters are positively associated with cardiorespiratory fitness, suggesting that greater pulmonary capacity may support improved oxygen uptake during physical activity [19].

Furthermore, most respondents were moderate smokers. Smoking worsens lung function and reduces aerobic capacity. Previous studies showed that smokers have a significantly lower VO₂ max than non-smokers, which is associated with reduced oxygen diffusion due to alveolar damage. Smoking significantly worsens lung function and reduces VO₂ max through various mechanisms, including direct alveolar damage, impaired gas exchange, and systemic inflammatory effects [23,24]. Smoking also impairs cardiovascular fitness by triggering widespread inflammation and contributing to the development of atherosclerosis, thus complicating the link between lung function and aerobic capacity. Both lung and heart health are crucial components to consider in a comprehensive assessment of fitness, especially in populations regularly exposed to tobacco smoke [25].

Therefore, the high proportion of smokers in this population may have amplified the negative relationship between BMI and waist circumference with VO₂ max. These findings suggest that weight control, waist circumference reduction, increased vital lung capacity through aerobic exercise, and smoking cessation programs may be effective strategies for improving cardiorespiratory fitness in a sedentary population. Good lung function contributes to increased vital lung capacity through physiological fitness, training, and avoidance of harmful environmental exposures. Understanding these relationships enables better management of lung health, particularly in at-risk populations and in those recovering from respiratory conditions. In individuals with compromised lung function, such as smokers or those suffering from chronic respiratory diseases, VO₂ max values are often lower than normal. Consequently, interventions that improve lung function through weight management, aerobic exercise, or pulmonary rehabilitation are critical for enhancing aerobic capacity in these populations [26].

In conclusion, the findings of this study demonstrate that body mass index (BMI) and vital lung capacity are significant predictors of maximal oxygen consumption (VO₂ max) among individuals with predominantly sedentary occupational activities. Higher BMI was associated with lower VO₂ max, while greater vital lung capacity was positively associated with improved aerobic capacity. These results highlight the important role of body composition and pulmonary function in determining cardiorespiratory fitness. Therefore, interventions aimed at maintaining a healthy body weight and improving lung function, such as regular physical activity and healthy lifestyle modifications, may enhance VO₂ max and overall health outcomes in sedentary populations.

Furthermore, the implications of this study extend to future investigations that should prioritise the development of targeted interventions to enhance lung function and VO₂ max in diverse populations. By understanding and addressing the interrelationships among BMI, vital lung capacity, and aerobic fitness, more effective public health strategies can be developed to mitigate the adverse effects of sedentary lifestyles and obesity, ultimately improving health outcomes.