A BSTRACT Introduction: Spirometric reference values are essential for diagnosing and managing respiratory diseases. However, existing equations, such as those from the Global Lung Initiative (GLI), may not fully represent North African populations. This study aims to establish spirometric and plethysmographic reference equations for healthy Algerian adults using the Lambda-Mu-Sigma (LMS) method within generalized additive models for location, scale, and shape (GAMLSS). Methods: A cross-sectional study was conducted between 2014 and 2016 at Rouiba Hospital, Algiers, Algeria. A total of 482 healthy nonsmoking adults (240 men and 242 women) aged 18–85 years were included. Pulmonary function tests, including spirometry and plethysmography, were performed according to the American Thoracic Society/European Respiratory Society guidelines. Data were analyzed using the LMS method within GAMLSS modeling in R software to develop predictive equations incorporating age and height as key variables. Results: The study established reference equations for spirometric and plethysmographic parameters, including forced expiratory volume in 1 s (FEV 1 ), forced vital capacity (FVC), total lung capacity (TLC), residual volume (RV), and functional residual capacity (FRC). The predicted values differed significantly from GLI-2012 and GLI-2021 reference equations, particularly for FRC, RV, and RV/TLC, which were underestimated by GLI norms. For men, the GLI equations underestimated FRC (−32.6%), RV (−35.2%), and TLC (−19%), while for women, underestimations were FRC (−14.9%), RV (−8.1%), and TLC (−4.7%). In addition, FEV 1 /FVC and other key indices varied between the GLI predictions and the new equations, emphasizing the need for localized reference standards. Conclusion: This study provides the first LMS-GAMLSS-based spirometric and plethysmographic reference equations for healthy Algerian adults. The findings demonstrate that GLI-2012 and GLI-2021 equations are only partially applicable to this population, necessitating region-specific equations to improve diagnostic accuracy. These newly developed equations offer a more precise assessment of lung function in Algeria and similar populations.
Ketfi et al. (Wed,) studied this question.