Anthropometric determinants of lung function in apparently healthy individuals

Abstract

Background Forced vital capacity (FVC) and peak expiratory flow rate (PEFR) are used to assess and monitor the management of lung pathology. Objectives Our study documented spirometry reference values for apparently healthy Nigerians and developed predictive equations for pulmonary function. Method A cross-sectional survey involving healthy adult Nigerians included anthropometric measurements of weight, height, waist, hip circumference (HC), sagittal abdominal diameter (SAD) and percentage body fat. Anthropometric indices (body mass index [BMI] and waist-to-hip ratio [WHR]) were estimated and pulmonary function tests (FVC, forced expiratory volume in 1 s [FEV1], PEFR, FEV1/FVC ratio) measured. The association amongst selected anthropometric and socio-demographic variables and pulmonary function test parameters were established using t -tests and Pearson’s product moment correlation tests. The predictors of pulmonary function were established using stepwise multiple linear regression models. Results Four hundred and forty-four adults (156 [35.1%] men) were included, mean age 37.3 ± 8.25 (range 22–25) years. Male participants had significantly higher lung volumes than females ( p < 0.05). Age, height, weight and percentage body fat had significant low correlations with lung function test parameters ( p < 0.05). Fat-free mass (FFM), fat mass (FM), SAD, height and age of participants were main predictors of FVC and FEV1 ( R 2 = 0.43 and 0.41, respectively). Fat-free mass and SAD were main predictors of PEFR ( R 2 = 0.53). Sagittal abdominal diameter and age were main predictors of FEV1/FVC ratio ( R 2 = 0.34). Conclusion Fat-free mass, FM, height, age and SAD are important determinants of lung volumes and key variables for predictive equations of pulmonary function. Clinical implications An accurate documentation of pulmonary function values for apparently healthy Nigerian adults may be useful in identifying deviations from normative values thereby giving an index of suspicion for the diagnosis of pulmonary dysfunction. Keywords anthropometric; lung function; spirometry; fat-free mass; apparently healthy.

Relationship between pulmonary function and anthropometric measurements and body composition in young women

“…In a study, while total body fat and abdominal obesity were negatively related to pulmonary function, increased lean mass was related with lower lung function and FEV1/FVC 30 . Similarly, Ogunlana et al reported that the fat mass of the participants had a significant negative correlation with lung function variables except FVC, whilst the FFM had a significant moderate positive correlation with FVC and FEV1 28 . In another study, although individuals are of normal body weight, increased body fat mass affected pulmonary function (FEV1 and FVC) negatively.…”

“…It has been shown that there is a relationship between waist circumference, which is one of the parameters of abdominal obesity, and pulmonary functions 9,10 . In a study, waist circumference and hip circumference showed significant weak negative correlations with FEV1/FVC ratio 28 . Besides, Ishikawa et al showed that the anthropometric and body composition parameters were negatively associated with FVC and FEV1 32 .…”

“…The lean body mass, fat mass and height were important determinants of lung volumes and associated with pulmonary function 28 . Obese individuals may have smaller caliber airways due to excess body adipose tissue, which may lead to decreased airway flow 15,29 .…”

Modeling of appropriate spirometric indicators in practically healthy young women from Podillia with ectomorphic somatotype

“…But it should be noted that the majority of such studies focus on the cardiovascular system [10,11,13,18,20,23]. Although recently, scientists emphasize the need to study the interrelationships and interdependencies between indicators of respiratory organs and body structure parameters [1,9,15]. The relevance and practical importance of studying this issue is determined by the prevalence and progression of respiratory diseases among different population cohorts [6,16,17,25] and the need for an individual approach to determining normative indicators [1,14].…”

One size does not fit all—Why do pediatric spirometry estimates vary across populations “down under”?

“…Other anthropometric factors like weight or body composition such as fat mass may also systematically differ between ethnic groups. Some studies indicate that body composition can influence lung function in children and adults 4,9,10 while others suggest that this effect is negligible 11 . Collaro et al frankly acknowledged that samples of White and First Nations children were collected 20 years apart, and secular time trends are known to affect the timing of puberty, anthropometric characteristics, and lung function 12 …”