A Large Cohort Study Concerning Age-Dependent Impacts of Anthropometric Variables on Spirometric Parameters in Nonsmoking Healthy Adults

BACKGROUNDS Although height (H) has been considered the principal anthropometric variable governing lung function, the age-dependent differences in its influences on determining spirometric parameters (SPs) have not been conclusively investigated. Moreover, there has been no study centered on age-dependent effects of other anthropometric variables, including body weight (BW) and body fat mass (BFM) on SPs. In addition, the age-dependent influences of these anthropometric variables are anticipated to differ quantitatively between male and female participants. METHODS A total of 16,919 nonsmoking healthy Japanese adults (men: 6,116, women: 10,803) were partitioned into six groups stratified by gender and age at intervals of 20-years: young-, middle-, and advanced-age groups of either gender. Using a model in which a SP was described by a logarithmic additive function of age, H, BW, and BFM, we determined the partial regression coefficients of the respective anthropometric variables to predict the reference means of SPs, including FVC, FEV1, FEV1/FVC, PEF, FEF50, and FEF75, in the six groups. RESULTS/DISCUSSION Although the impact of H on FVC and FEV1 was relatively homogeneous irrespective of gender and age, its homogeneity faded for flow parameters, particularly in the female middle- and advanced-age groups, indicating that the age-dependent contribution of H to SPs was enhanced more in women. The impact of BW on SPs differed depending on age, and this effect was also more conspicuous for female participants. H and BW generally exerted positive effects on SPs, whereas BFM had negative effects. Opposite effects of BW and BFM were observed in the female middle-age group in particular. CONCLUSIONS The effects of anthropometric variables on spirometric parameters are highly age-dependent, particularly in women, leading to the conclusion that the assumption of age-independent, constant partial regression coefficients of anthropometric variables while predicting the reference mean of a certain spirometric parameter may result in substantial errors.