Novel Regression Equations Incorporating Aging-specific Contributions of Various Explanatory Variables in Predicting Spirometric Parameters in Non-Obese, Japanese Adults

Abstract

Aim: To develop the novel regression equations that predict spirometric parameters (SPs) in concert with aging-specific corrections for four explanatory variables, including age, height, body weight, and fat fraction of body mass. Subjects: A large cohort of nonsmoking, non-obese, healthy adults in the general population in Japan (males: 3,056, females: 6,783). Methods: Supposing that SP is described by an aging-dependent, logarithmic, additive function of age, height, body weight, and fat fraction of body mass, gender- and aging-specific regression equations predicting the forced vital capacity (FVC), forced expiratory volume after one second (FEV1), FEV1/FVC, peak expiratory flow rate (PEF), forced expiratory flow rate at 50% expiration of the FVC (FEF50), and forced expiratory flow rate at 75% expiration of the FVC (FEF75) were established. The partial regression coefficients of explanatory variables against a specific SP were decided by a step-wise, multiple-regression analysis with least-squares minimization. Results: Age and fact fraction of body mass exerted negative impacts, whereas height and body weight had positive impacts on various SPs in an aging-dependent and/or aging-independent manner. These aging-related contributions of explanatory variables were highly gender-specific. Body weight and fat fraction of body mass concurrently played an important role in prescribing the SP, particularly in females. Conclusions: The gender-specific, aging-related corrections of age, height, body weight, and fat fraction body mass are important for deciding various spirometric parameters. If the aging-dependent and/or aging-independent contributions of body weight and/or fat fraction of body mass are ignored, substantial errors emerge for the reference means and lower limits of normal of specific SPs