Journal of Epidemiology
Online ISSN : 1349-9092
Print ISSN : 0917-5040
Original Article
Epidemiologic Methods of Assessing Asthma and Wheezing Episodes in Longitudinal Studies: Measures of Change and Stability
Nelís Soto-RamírezAli H. ZiyabWilfried KarmausHongmei ZhangRamesh J. KurukulaaratchySusan EwartSyed Hasan Arshad
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Volume 23 (2013) Issue 6 Pages 399-410

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Abstract

Background: In settings in which diseases wax and wane, there is a need to measure disease dynamics in longitudinal studies. Traditional measures of disease occurrence (eg, cumulative incidence) do not address change or stability or are limited to stable cohorts (eg, incidence) and may thus lead to erroneous conclusions. To illustrate how different measures can be used to detect disease dynamics, we investigated sex differences in the occurrence of asthma and wheezing, using a population-based study cohort that covered the first 18 years of life.
Methods: In the Isle of Wight birth cohort (n = 1456), prevalence, incidence, cumulative incidence, positive and negative transitions, and remission were determined at ages 1 or 2, 4, 10, and 18 years. Latent transition analysis was used to simultaneously identify classes of asthma and wheezing (related phenotypes) and characterize transition probabilities over time. Trajectory analysis was used to characterize the natural history of asthma and wheezing.
Results: Regarding time-specific changes, positive and negative transition probabilities were more informative than other measures of associations because they revealed a sex switchover in asthma prevalence (P < 0.05). Transition probabilities were able to identify the origin of a sex-specific dynamic; in particular, prior wheezing transitioned to asthma at age 18 years among girls but not among boys. In comparison with latent transition analysis, trajectory analysis did not directly identify a switchover in prevalence among boys and girls.
Conclusions: In longitudinal analyses, transition analyses that impose minimal restrictions on data are needed in order to produce appropriate information on disease dynamics.

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© 2013 Nelís Soto-Ramírez et al. This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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