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Related Experiment Videos

Longitudinal changes in time domain spirogram indices and their variability

T Nakadate1, T Sato, J Kagawa

  • 1Dept of Hygiene and Public Health, Tokyo Women's Medical College, Japan.

The European Respiratory Journal
|June 1, 1994
PubMed
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Longitudinal analysis of spirogram indices in middle-aged men reveals significant between-subject variability. Transit time indices show larger annual increases longitudinally than cross-sectionally, necessitating distinct reference values.

Area of Science:

  • Pulmonary Function Testing
  • Occupational Health
  • Longitudinal Data Analysis

Background:

  • Spirometry is crucial for assessing lung function and detecting respiratory diseases.
  • Understanding longitudinal changes and variability in spirometry indices is essential for accurate clinical interpretation.
  • Previous studies often relied on cross-sectional data, potentially underestimating true longitudinal changes.

Purpose of the Study:

  • To describe longitudinal changes and variability in time domain spirogram indices.
  • To compare longitudinal estimates with cross-sectional estimates for key spirometry parameters.
  • To analyze the contribution of between-subject variability to overall variance in these indices.

Main Methods:

  • Forced expiratory spirograms were measured in 326 middle-aged male factory employees over 5 years.

Related Experiment Videos

  • A subset of 225 healthy subjects with reliable data from at least three surveys was analyzed.
  • Longitudinal models were used to analyze mean transit time (MTT), standard transit time (STT), their log-transformed values, and time constant distribution indices (Mu, Sigma).

    • Main Results:

    • Longitudinally estimated annual increases in MTT, STT, ln(MTT), and ln(STT) were approximately three times larger than cross-sectional estimates.
    • Estimates for Mu and Sigma were comparable between longitudinal and cross-sectional analyses.
    • Between-subject variability significantly contributed to all indices, being notably higher than error variance, especially for mean components.

    Conclusions:

    • Longitudinal transit time index data should not be compared directly with cross-sectional reference values.
    • The error variance in longitudinal repeated spirometry measurements is likely lower than previously reported cross-sectional values.
    • Significant inter-individual differences in lung function progression necessitate personalized monitoring approaches.