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Vol. 57. Issue 3.
Pages 172-178 (March 2021)
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Vol. 57. Issue 3.
Pages 172-178 (March 2021)
Original Article
Comparing Spirometric Reference Values From Childhood to Old Age Estimated by LMS and Linear Regression Models
Comparación de los valores de referencia espirométrica de la infancia a la vejez estimada mediante el método LMS y modelos de regresión lineal
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David Martínez-Briseñoa, Laura Gochicoa-Rangelb, Luis Torre-Bouscouletc, Silvia Cid-Juárezb, Rosario Fernández-Plataa, Luisa Martínez-Valdeavellanob, Sofía Chapela-Larab, Rodrigo del Río-Hidalgob, Rogelio Pérez-Padillad,
Corresponding author
perezpad@unam.mx

Corresponding author.
a Department of Epidemiology and Social Sciences in Health, National Institute of Respiratory Diseases “Ismael Cosío Villegas”, 4502 Mexico City, Mexico
b Department of Respiratory Physiology, National Institute of Respiratory Diseases “Ismael Cosío Villegas”, Mexico City, Mexico
c Medica Sur Hospital, Puente de Piedra 150, Mexico City, Mexico
d Department of Research in Smoking and COPD, National Institute of Respiratory Diseases “Ismael Cosío Villegas”, Mexico City, Mexico
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Figures (4)
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Tables (6)
Table 1. Descriptive statistics of the female subjects (N=3054).
Table 2. Descriptive statistics of the male subjects (N=6781).
Table 3. LMS models for spirometric variables in the female subjects.
Table 4. LMS models for spirometric variables of the male subjects.
Table 5. Adjustment of LMS and linear regression models for spirometric variables for the female subjects.
Table 6. LMS and LR models for spirometric variables for the male subjects.
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Additional material (1)
Abstract
Background

Proper reference values for lung function testing are essential for achieving adequate interpretations. The LMS procedure (lambda, mu, sigma) permits continuous analyses of entire populations avoiding gaps in the transition between childhood and adulthood. It also allows more precise calculations of average values, dispersion, and 5th percentiles, which are usually considered the lower limit of normality. The objective of this study was to compare our results fitted with the LMS method with standard multiple linear regression, and with those from international Global Lung Function Initiative (GLI) equations.

Methods

Data from 9835 healthy residents of the metropolitan area of Mexico City aged 8–80 years were compiled from several studies: EMPECE, PLATINO, adult Mexican workers and two unpublished studies. The LMS procedure and multiple linear regression models were fit to obtain reference equations using R software.

Results

Residuals from the LMS models had a median closer to zero, and smaller dispersion than those from the linear model, but differences although statistically significant were very small and of questionable practical relevance. For example, for females and ln(FEV1), median residual was −0.001 with p25 of −0.08 and p75 of 0.08 for LMS, compared with 0.004 (−0.08, 0.09) [p<0.05] for the linear model. Average spirometric values for a given height for our population, were higher than those predicted by the GLI study.

Conclusion

Continuous reference equations for the Mexican population calculated using the LMS technique showed slightly better fit than linear regression models.

Keywords:
Spirometry
Reference values
Altitude
Lambda, mu, sigma
Global Lung Function
Abbreviations:
ATS
ERS
NIOSH
GLI
FEV1
FVC
FEV1/FVC
LMS
BCCG
BIC
LLN
Resumen
Contexto general

Unos valores de referencia apropiados para las pruebas de la función pulmonar son esenciales para realizar unas interpretaciones adecuadas. El método LMS (lambda, mu, sigma) permite realizar análisis continuos de poblaciones enteras evitando brechas en la transición entre la infancia y la edad adulta. También permite cálculos más precisos de valores medios, dispersiones y percentiles 5, que generalmente se consideran el límite inferior de la normalidad. El objetivo de este estudio fue comparar nuestros resultados ajustados con el método LMS con la regresión lineal múltiple estándar y con los de las ecuaciones internacionales de la Iniciativa Global de Función Pulmonar (GLI).

Métodos

Se recopilaron datos de 9.835 residentes sanos del área metropolitana de la Ciudad de México con edades comprendidas entre 8 y 80 años a partir de varios estudios: EMPECE, PLATINO, trabajadores adultos mexicanos y 2 estudios no publicados. El método LMS y los modelos de regresión lineal múltiple se ajustaron para obtener ecuaciones de referencia utilizando el software R.

Resultados

Los residuos de los modelos LMS tuvieron una mediana más cercana a cero y una dispersión menor que las del modelo lineal, pero las diferencias, aunque estadísticamente significativas, fueron muy pequeñas y de una relevancia práctica cuestionable. Por ejemplo, para las mujeres y el ln(FEV1), la mediana residual fue de −0,001 con p25 de −0,08 y p75 de 0,08 para LMS, en comparación con 0,004 (−0,08, 0,09) (p<0,05) para el modelo lineal. Los valores espirométricos medios para una altura dada para nuestra población fueron más altos que los pronosticados por el estudio GLI.

Conclusión

Las ecuaciones de referencia continua para la población mexicana calculadas usando la técnica LMS mostraron un ajuste ligeramente mejor que los modelos de regresión lineal.

Palabras clave:
Espirometría
Valores de referencia
Altura
Lambda, mu, sigma
Iniciativa Global de Función Pulmonar

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