BACKGROUND Use of generalized linear models with continuous, non-linear functions for age, period and cohort makes it possible to estimate these effects so they are interpretable, reliable and easily displayed graphically. To demonstrate the methods we use data on the prevalence of obesity among Australian women from two independent data sources obtained using different study designs. METHODS We used data from two long-running nationally representative studies: seven cross-sectional Australian National Health Surveys conducted between 1995 and 2017-18, each involving 6000-8000 women; and the Australian Longitudinal Study on Women's Health which started in 1996 and involves more than 57,000 women in four age cohorts who are re-surveyed at three-yearly intervals or annually. Age-period-cohort analysis was conducted using generalized linear models with splines to describe non-linear continuous effects. RESULTS When analysed in the same way both data sets showed similar patterns. Prevalence of obesity increased with age until late middle age and then declined; increased only slightly across surveys; but increased steadily with birth year until the 1960s and then accelerated. CONCLUSIONS The methods illustrated here make the estimation and visualisation of age, period and cohort effects accessible and interpretable. Regardless of how the data are collected (from repeated cross-sectional surveys or longitudinal cohort studies), it is clear that younger generations of Australian women are becoming heavier at younger ages. Analyses of trends in obesity should include cohort, in addition to age and period, effects in order to focus preventive strategies appropriately.

中文翻译：

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使用肥胖流行率数据说明了灵活的年龄组模型。

背景技术对年龄，时期和队列的具有连续非线性函数的广义线性模型的使用使得可以估计这些影响，使得它们是可解释的，可靠的并且容易以图形方式显示。为了证明这些方法，我们使用了来自澳大利亚妇女中肥胖发生率的数据，这些数据来自使用不同研究设计获得的两个独立数据来源。方法我们使用了两项长期在全国范围内具有代表性的研究的数据：1995年至2017-18年间进行的七个横断面澳大利亚国民健康调查，每个调查涉及6000至8000名女性。以及澳大利亚妇女健康纵向研究始于1996年，涉及4个年龄段的57,000多名妇女，每三年或每年进行一次重新调查。使用带有样条的广义线性模型进行年龄-同期队列分析，以描述非线性连续效应。结果当以相同的方式进行分析时，两个数据集都显示出相似的模式。肥胖的发生率随着年龄的增长而增加，直到中年后期才有所下降。在所有调查中仅略有增加；但随着出生年份的增加而稳定增长，直到1960年代，然后加速增长。结论此处说明的方法使对年龄，时期和队列影响的估计和可视化变得容易理解。无论如何收集数据（通过重复的横断面调查或纵向队列研究），很明显，年轻一代的澳大利亚妇女在年轻时变得越来越重。肥胖趋势分析应包括年龄，年龄，年龄，