Body mass index (BMI) is a widely used anthropometric measure that reflects body fatness and serves as a screening tool for underweight, overweight, and obesity. It is calculated as body weight in kilograms divided by the square of height in metres and is strongly associated with overall health status [1]. Variations in BMI can significantly affect respiratory physiology, as both undernutrition and excess adiposity influence lung mechanics, gas exchange, and respiratory muscle performance [2,3].

Obesity can lead to reduced lung volumes due to mechanical compression of the thoracic cavity, elevation of the diaphragm, and increased airway resistance [4,5]. These changes often manifest as reductions in forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁) [6]. Conversely, low BMI and associated muscle wasting can impair respiratory muscle strength and reduce ventilatory capacity [7,8].

Pulmonary function tests (PFTs) provide objective measures of lung function, including airflow and lung volumes, and are valuable for detecting subclinical respiratory impairment [9]. Studies have shown variable associations between BMI and PFT parameters, with some reporting a linear decline in lung function at both extremes of BMI, while others have found only obesity to be detrimental.

Young adults, particularly those in the 18–25-year age group, generally exhibit optimal lung function. However, lifestyle changes, sedentary behaviour, and dietary patterns can influence both BMI and respiratory health. Investigating the relationship between BMI and lung function in this group may help in identifying early deviations from normal respiratory performance and guide preventive strategies.

The present study aimed to evaluate the relationship between BMI and key PFT parameters—FVC, FEV₁, FEV₁/FVC ratio, and peak expiratory flow rate (PEFR)—in healthy young adults, and to determine whether variations in BMI categories are associated with significant differences in pulmonary function.

A total of 100 healthy young adults aged 18–25 years were recruited from undergraduate medical students using simple random sampling. Inclusion criteria were absence of any known respiratory or cardiovascular disease, non-smoker status, and no recent history of acute respiratory infection. Participants with chest wall deformities, chronic illnesses, or those on medications affecting lung function were excluded.

Anthropometric Measurements

Height was measured to the nearest 0.1 cm using a wall-mounted stadiometer, and weight was recorded to the nearest 0.1 kg using a calibrated digital weighing scale, with participants barefoot and wearing light clothing. BMI was calculated as weight (kg) divided by height squared (m²). Participants were classified according to WHO criteria: underweight (<18.5 kg/m²), normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), and obese (≥30 kg/m²).

Pulmonary Function Testing

Spirometry was performed using a portable, computerised spirometer (Model: [Insert Model Name], Manufacturer: [Insert Company], Country) following the American Thoracic Society/European Respiratory Society guidelines. Each participant performed at least three acceptable manoeuvres, and the highest values were recorded. Parameters measured included:

• Forced Vital Capacity (FVC)
• Forced Expiratory Volume in 1 second (FEV₁)
• FEV₁/FVC ratio
• Peak Expiratory Flow Rate (PEFR)

Testing was done in a seated position, with participants wearing a nose clip and breathing through a disposable mouthpiece. Adequate rest was given between attempts to avoid fatigue.

Statistical Analysis

Data were entered into Microsoft Excel and analysed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation (SD) and categorical variables as frequencies and percentages. One-way analysis of variance (ANOVA) was used to compare mean PFT values across BMI categories, followed by post hoc Tukey’s test for pairwise comparisons. Pearson’s correlation coefficient was applied to assess the relationship between BMI and lung function parameters. A p-value <0.05 was considered statistically significant.

The study included 100 healthy young adults (mean age 20.9 ± 1.8 years), of which 56% were female and 44% were male. Based on BMI classification, 18% were underweight, 54% were normal weight, 20% were overweight, and 8% were obese.

Pulmonary Function Across BMI Categories

Mean FVC and FEV₁ values were highest in the normal BMI group, while both underweight and obese participants recorded lower values (Table 1). ANOVA revealed statistically significant differences in FVC (p = 0.003) and FEV₁ (p = 0.005) between groups, but no significant variation in FEV₁/FVC ratio (p = 0.412).

Table 1. Comparison of pulmonary function parameters across BMI categories (n = 100)

Correlation Between BMI and Lung Function

Pearson correlation analysis demonstrated a moderate negative correlation between BMI and FVC (r = −0.36, p < 0.01) as well as BMI and FEV₁ (r = −0.34, p < 0.01) (Table 2). No significant correlation was observed between BMI and FEV₁/FVC ratio (p = 0.284).

Table 2. Correlation between BMI and pulmonary function parameters

The findings indicate that higher BMI is associated with lower lung volumes, with the most optimal values recorded in the normal BMI group (Table 1 and Table 2).

The present study demonstrated a significant association between body mass index and pulmonary function in healthy young adults, with both underweight and obese individuals showing reduced FVC and FEV₁ values compared to those with normal BMI. The FEV₁/FVC ratio remained within normal limits across all BMI categories, suggesting a predominantly restrictive pattern rather than obstructive airway involvement.

Our finding that higher BMI is linked to lower lung volumes agrees with earlier studies reporting that excess adipose tissue in the thoracoabdominal region can mechanically restrict lung expansion, elevate the diaphragm, and increase airway resistance [1,2]. Obesity-related reductions in FVC and FEV₁ have been documented in multiple populations, including young adults [3,4]. This mechanical load, combined with increased metabolic demand, may contribute to reduced pulmonary reserve [5].

Interestingly, underweight participants in our study also showed diminished lung volumes, consistent with previous reports linking low BMI to reduced respiratory muscle mass and strength [6,7]. Malnutrition-related muscle wasting can compromise ventilatory capacity even in otherwise healthy individuals [8].

The negative correlations observed between BMI and FVC/FEV₁ in our cohort are in line with findings from Chen et al., who reported that increased central adiposity negatively impacts lung mechanics irrespective of overall body weight [9]. Similarly, Canoy et al. found that abdominal obesity was more predictive of lung function decline than general obesity [10].

In contrast, the FEV₁/FVC ratio did not differ significantly between BMI categories in our study, which aligns with results from Jones and Nzekwu, indicating that BMI primarily affects lung volumes rather than causing obstructive changes [11]. PEFR also declined in both high and low BMI groups, which may reflect compromised expiratory muscle performance [12].

The optimal lung function values observed in the normal BMI group underscore the importance of maintaining a healthy weight. Prior studies have demonstrated that lifestyle modifications targeting weight optimisation can lead to improvements in lung function and respiratory symptoms [13,14].

Our findings have public health implications, particularly for young adults who may not perceive themselves at risk for respiratory impairment. Educational interventions promoting healthy weight maintenance may serve as preventive strategies against early pulmonary function decline [15].

Limitations of this study include its cross-sectional nature, which prevents causal inferences, and the absence of body composition analysis, which could differentiate between fat and muscle mass contributions to BMI. Additionally, the sample was limited to medical students, potentially restricting generalisability. Future studies should include longitudinal follow-up and incorporate additional measures such as waist circumference, body fat percentage, and respiratory muscle strength testing.

This study demonstrates that both underweight and obesity are associated with reduced pulmonary function in healthy young adults, while normal BMI is linked to optimal lung volumes. Maintaining a healthy body weight may help preserve respiratory capacity and prevent early functional decline.

1. Elsaidy WH, Alzahrani SA, Boodai SM. Exploring the correlation between body mass index and lung function test parameters: a cross-sectional analytical study. BMC Res Notes. 2024 Oct 24;17(1):320. doi: 10.1186/s13104-024-06967-6. PMID: 39449075.
2. Wang S, Sun X, Hsia TC, Lin X, Li M. The effects of body mass index on spirometry tests among adults in Xi'an, China. Medicine (Baltimore). 2017 Apr;96(15):e6596. doi: 10.1097/MD.0000000000006596. PMID: 28403098.
3. Attaur-Rasool S, Shirwany TA. Body mass index and dynamic lung volumes in office workers. J Coll Physicians Surg Pak. 2012 Mar;22(3):163-7. PMID: 22414357.
4. Peralta GP, Marcon A, Carsin AE, Abramson MJ, Accordini S, Amaral AF, et al. Body mass index and weight change are associated with adult lung function trajectories: the prospective ECRHS study. Thorax. 2020 Apr;75(4):313-20. doi: 10.1136/thoraxjnl-2019-213880. PMID: 32098862.
5. Bekkers MB, Wijga AH, Gehring U, Koppelman GH, de Jongste JC, Smit HA, et al. BMI, waist circumference at 8 and 12 years of age and FVC and FEV1 at 12 years of age; the PIAMA birth cohort study. BMC Pulm Med. 2015 Apr 22;15:39. doi: 10.1186/s12890-015-0032-0. PMID: 25896340.
6. Börekçi S, Demir T, Görek Dilektaşlı A, Uygun M, Yıldırım N. A simple measure to assess hyperinflation and air trapping: 1-forced expiratory volume in three seconds/forced vital capacity. Balkan Med J. 2017 Apr 5;34(2):113-8. doi: 10.4274/balkanmedj.2015.0857. PMID: 28418337.
7. Chen Y, Rennie D, Cormier YF, Dosman J. Waist circumference is associated with pulmonary function in normal-weight, overweight, and obese subjects. Am J Clin Nutr. 2007 Jan;85(1):35-9. doi: 10.1093/ajcn/85.1.35. PMID: 17209174.
8. Martinez-Arnau FM, Buigues C, Fonfría-Vivas R, Cauli O. Respiratory function correlates with fat mass index and blood triglycerides in institutionalized older individuals. Endocr Metab Immune Disord Drug Targets. 2022;22(10):1029-39. doi: 10.2174/1871530322666220329150813. PMID: 35352657.
9. Fortis S, Corazalla EO, Wang Q, Kim HJ. The difference between slow and forced vital capacity increases with increasing body mass index: a paradoxical difference in low and normal body mass indices. Respir Care. 2015 Jan;60(1):113-8. doi: 10.4187/respcare.03403. PMID: 25316893.
10. Pahwa P, Karunanayake CP, Rennie DC, Chen Y, Schwartz DA, Dosman JA. Association of the TLR4 Asp299Gly polymorphism with lung function in relation to body mass index. BMC Pulm Med. 2009 Sep 21;9:46. doi: 10.1186/1471-2466-9-46. PMID: 19772581.
11. Balte P, Karmaus W, Roberts G, Kurukulaaratchy R, Mitchell F, Arshad H. Relationship between birth weight, maternal smoking during pregnancy and childhood and adolescent lung function: a path analysis. Respir Med. 2016 Dec;121:13-20. doi: 10.1016/j.rmed.2016.10.010. PMID: 27888986.
12. Do JG, Park CH, Lee YT, Yoon KJ. Association between underweight and pulmonary function in 282,135 healthy adults: a cross-sectional study in Korean population. Sci Rep. 2019 Oct 4;9(1):14308. doi: 10.1038/s41598-019-50488-3. PMID: 31586079.
13. Wang W, Ma D, Li T, Ying Y, Xiao W. People with older age and lower FEV1%pred tend to have a smaller FVC than VC in pre-bronchodilator spirometry. Respir Physiol Neurobiol. 2014 Apr 1;194:1-5. doi: 10.1016/j.resp.2014.01.003. PMID: 24448311.
14. Senevirathna N, Amarasiri L, Jayamanne D, Manel K, Liyanage G. Thinness negatively affects lung function among Sri Lankan children. PLoS One. 2022 Aug 2;17(8):e0272096. doi: 10.1371/journal.pone.0272096. PMID: 35917365.
15. Çolak Y, Marott JL, Vestbo J, Lange P. Overweight and obesity may lead to under-diagnosis of airflow limitation: findings from the Copenhagen City Heart Study. COPD. 2015 Feb;12(1):5-13. doi: 10.3109/15412555.2014.933955. PMID: 25290888.