Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis.
J Epidemiol. 2013;23(6):399-410. doi: 10.2188/jea.je20120201. Epub 2013 Aug 31.
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.
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.
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.
In longitudinal analyses, transition analyses that impose minimal restrictions on data are needed in order to produce appropriate information on disease dynamics.
在疾病时起时落的环境中,需要在纵向研究中衡量疾病动态。传统的疾病发生衡量方法(例如累积发病率)不能解决变化或稳定性问题,或者仅限于稳定队列(例如发病率),因此可能导致错误的结论。为了说明如何使用不同的方法来检测疾病动态,我们使用一项基于人群的研究队列,该队列涵盖了生命的头 18 年,调查了哮喘和喘息在性别上的发生差异。
在怀特岛出生队列中(n = 1456),在 1 岁或 2 岁、4 岁、10 岁和 18 岁时确定了哮喘和喘息的患病率、发病率、累积发病率、阳性和阴性转变以及缓解情况。使用潜在转变分析同时确定哮喘和喘息的相关表型的类别,并描述随时间的转变概率。使用轨迹分析描述哮喘和喘息的自然病史。
关于特定时间的变化,阳性和阴性转变概率比其他关联衡量方法更具信息量,因为它们揭示了哮喘患病率的性别转变(P < 0.05)。转变概率能够识别性别特异性动态的起源;特别是,在女孩中,18 岁时先前的喘息转变为哮喘,但在男孩中没有。与潜在转变分析相比,轨迹分析并没有直接识别男孩和女孩中患病率的转变。
在纵向分析中,需要进行对数据施加最小限制的转变分析,以便提供有关疾病动态的适当信息。