Noncomparability of Longitudinally and Cross-sectionally Determined Annual Change in Spirometry^1-3

Abstract

Annual decline in lung function determined longitudinally is often compared with predicted decline determined cross-sectionally. To test this comparison, spirometric data were collected 5 times over 5 yr from 52 adult male Caucasians. The age regression coefficient for FEV1 and FVC, determined cross-sectionally at each visit, was more than twice the longitudinal annual change computed from the same data as the mean of the slopes of each subject's regression lines. The discrepancy persisted even when the first visit was deleted to reduce learning effects on longitudinal estimates. This discrepancy may be partly explained by the sensitivity of cross-sectional analyses to past noxious influences, whereas longitudinal analyses are sensitive only to influences that continue to affect annual decline during the study period. We also found historical evidence of an increase in height-specific VC, which would artifactually steepen cross-sectionally determined regression lines. Thus, observed longitudinal changes of study cohorts should be compared with control longitudinal data.

The ageing of lung function: cross-sectional and longitudinal studies of an Inuit community

“…In contrast, the FVC of a 60 year old man decreased by 0.6-0.7 l, with parallel trends in FEV 1 . The secular trend to a faster ageing of male FEV 1 was confirmed in longitudinal data, and cannot, thus, be dismissed as an artifact of altered population demographics or curvilinearity of the ageing process.…”

“…In urban populations, longitudinal estimates of lung function ageing have been both greater [14], and smaller [1,4,20] than cross-sectional values, depending on the relative strengths of the various factors biasing the two estimates. In the present study, the longitudinal data suggested a curvilinearity of ageing.…”

“…The apparent rate of ageing of lung function differs between cross-sectional and longitudinal surveys [1][2][3][4]. Longitudinal data may be biased by recruitment of a health-conscious sample, selective retention or loss of subjects with respiratory disease, intersurvey changes in spirometer characteristics, learning of techniques, and secular changes of habitual physical activity (particularly among indigenous populations where there has been rapid adoption of a sedentary lifestyle).…”

Health hazard evaluation report: HETA-93-0501-2580, Western Zirconium, Ogden, Utah.

“…Previous longitudinal studies have established that FEV 1 normally declines 20-30 milliliters per year (ml/yr) in nonsmokers and 40-50 ml/yr in smokers. (31)(32)(33) Additional factors unrelated to work can cause this decline to be greater than expected (e.g. respiratory infections, air pollution), as can work exposures.…”

Annual lung function changes in young patients with chronic lung disease

“…This correction is not only crucial for monitoring patients with chronic lung disease and to evaluate individual therapeutic interventions, but is also important in longitudinal clinical trials where indices such as forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) are often primary end-points. Correction for lung growth is usually achieved by expressing lung function parameters as a percentage of predicted (% pred), although predictions derived from cross-sectional studies may not accurately reflect lung growth within an individual [1,2].…”