This study found a negative association of anthropometric (BMI and WHtR) and body composition parameters (DXA- and BOD POD-measured fat mass) with pulmonary function assessed by FEV1 and FVC in both genders, particularly in men. The adjusted models showed that, for every increase of 1 kg/m2 in BMI, FVC decreased by 12 ml in men and by 6 ml in women and FEV1 decreased by 10 ml and 5 ml, respectively. Regarding the body composition parameters, for every 1% increase in BOD POD-measured fat mass, FVC decreased by 15 ml in men and by 8 ml in women and FEV1 decreased by 12 ml and 6 ml, respectively. Similar values were obtained for the DXA measurements in which FVC decreased by 11 ml in men and by 7 ml in women for every 1% increase in fat mass and FEV1 decreased by 11 ml and 6 ml, respectively (Additional Table 3).
Rowe et al. (31) evaluated the association of different anthropometric measures (BMI, waist circumference, hip circumference, waist-hip ratio, WHtR, and skinfolds) with pulmonary function assessed by FVC and FEV1. Although the authors did not report height as a confounding variable in the methods, the linear regression models were adjusted for height, except for the models using BMI and WHtR. The R2 was used as a measure to compare the associations. The associations with the highest R2 for both FEV1 and FVC in men and women were obtained when skinfold thickness was used, followed by waist circumference, and the worst associations were obtained using BMI and WHtR. These results suggest that height is an important factor in the study of associations and that it can be addressed in different ways.
Some previous studies have shown that waist circumference is a better marker of obesity than BMI in the association with pulmonary function. This can be explained by the fact that waist circumference is a direct marker of central obesity and an indirect marker of visceral fat accumulation; however, those studies adjusted for height in their analyses2,6,32,33. In the present study, when height was added to the model (supplemental results), waist circumference was found to be significantly associated with FEV1 in men and women and with FVC in men. Each 1-cm increase in waist circumference decreased FEV1 and FVC by 6 ml in men and by 2 ml in women.
An increasing number of studies have demonstrated the importance of assessing obesity beyond BMI, using more accurate measures of the amount and distribution of body fat, and differentiating fat mass from lean mass. Methods such as bioimpedance, computed tomography, magnetic resonance imaging, BOD POD, and DXA have been employed in an attempt to avoid erroneous classifications of obesity based only on BMI34. Today, DXA is considered the gold standard for this assessment35,36.
In all models, BOD POD-measured body fat was associated with a greater negative variation in both FEV1 and FVC in men and women when compared to the other methods. Similar values were observed for the association of pulmonary function with DXA-measured fat mass, indicating that the relationship of obesity with pulmonary function is based on the content and endocrinological function of fat mass, in addition to the respiratory mechanical injury. Recent studies using fat mass measured by computed tomography found that both visceral adipose tissue and total adipose tissue are associated with poor pulmonary function, irrespective of waist circumference22,36,37.
Obesity is known to affect pulmonary function regardless of the presence of respiratory, cardiovascular, or metabolic diseases4,7,8, interfering with respiratory mechanics and lung-thorax compliance. Furthermore, studies have demonstrated that adipose tissue, especially the visceral adipose tissue, is an active tissue in terms of inflammation (cytokine production) and endocrinological activity, releasing hormones that also interfere with pulmonary function13,15,16.
This study has several strengths. It has used cross-sectional data from a birth cohort, which allows us to obtain a large and representative sample of the population studied, in addition to being subjected to standardization and quality techniques of a longitudinal study in which the responsibility to record detailed quality data is fundamental. Additionally, the study employed sophisticated and accurate methods for body composition measurement. On the other hand, the study has limitations. Its cross-sectional design does not allow to evaluate the causal relationship between obesity and pulmonary function reduction, nor how weight evolution over the time influences the maximal lung function and its decline over the years. The study used a population sample with a limited age range from the city of Ribeirao Preto, whose socioeconomic pattern differs from that of most other Brazilian cities, impairing generalization of our findings to other ages and regions. The original project also did not have this study as the central objective. It is difficult to extract data from a questionnaire that was predefined with other initial general objectives. Some anthropometric parameters such as hip circumference and skinfold thickness that could be useful for comparison with other publications were not measured.
There are other variables that can confuse the association between obesity and pulmonary function, such as diet and socioeconomic status which were not included. Another limitation is that pulmonary function was evaluated only by spirometry. It is known that obesity can change other functional parameters such as volume and gas exchange variables, which spirometry does not measure.
Since reduced pulmonary function and obesity have been consistently shown to be independent predictors of morbidity and mortality and previous studies have demonstrated an association between the two, identification of the method that best demonstrates this association can provide more information about the interaction between adiposity and lung physiology. The present data demonstrate the advantage of more accurate measurements of fat content (BOD POD and DXA) over anthropometric measures. The results mainly indicate the inferiority of the one-dimensional variable waist circumference, which failed to demonstrate the association that was evidenced by WHtR and BMI, probably because waist circumference is a variable that does not contain height. This understanding may be important for future studies, for clinical assessments, and for elaboration of public health policies.