The age–period–cohort conundrum as two fundamental problems

O’Brien, Robert M.

doi:10.1007/s11135-010-9397-6

Cited by 28 publications

(19 citation statements)

References 18 publications

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“…Third, age‐period‐cohort modeling was used to examine age, period, and birth cohort effects. However, as calendar year minus age equals birth year, there is a perfect co‐linearity among age, period, and cohort effects, which makes it impossible to truly disentangle these effects . Fourth, the changes in the coverage of cancer registration during 30 years probably affect the results in both cancer incidence and mortality rates.…”

Section: Discussionmentioning

confidence: 99%

Distinctive lung cancer incidence trends among men and women attributable to the period effect in Shanghai: An analysis spanning 42 years

Xie

Qian

et al. 2020

Cancer Medicine

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Background: Many previous studies reported secular trend of lung cancer incidence and mortality, but little is known about the possible reasons for these trends. Methods: Data were obtained from Shanghai Cancer Registry. Age-standardized rates were calculated and average annual percent changes (AAPCs) were evaluated by Joinpoint regression. Age, period, and birth cohort effects were assessed by ageperiod-cohort models. Results: From 1973 to 2010, compared with long-time slowly increasing trend in women, male lung cancer incidence had significantly decreased between 2001 and 2009. After that lung cancer incidence rising sharply in women (AAPC = 14.13%, 95%CI: 2.68%-26.86%, P = .016) and similar rising trends without statistical significance in men (AAPC = 2.96, 95%CI: −2.47%-8.69%, P = .281) between 2010 and 2014. Age-period cohort model showed the different patterns of period effects for lung cancer incidence between men and women. The period effects for lung cancer incidence showed rising effect for women, whereas there was decline effect for lung cancer incidence for men. On the other hand, the model showed a significant period effect in both genders with a similar fashion in mortality, yielding steady falling trends during the entire study period. Conclusions: The distinctive patterns of lung cancer incidence between men and women may be attributable to significant period effects, which reflected the changes in public health policies or diagnostic practices and highlighted the urgent of continued monitoring of gender-specific risk factors for lung cancer incidence. K E Y W O R D Sage-period-cohort model, gender disparity, incidence, Lung cancer, mortality | 2931 XIE Et al.

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Section: Discussionmentioning

confidence: 99%

Distinctive lung cancer incidence trends among men and women attributable to the period effect in Shanghai: An analysis spanning 42 years

Xie

Qian

et al. 2020

Cancer Medicine

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“…Further, the use of APC modeling allowed us to examine age, period, and birth cohort effects. However, as calendar year minus age equals birth year (C=P-A), there is a perfect co-linearity between age, period and cohort effects, which makes it impossible to truly disentangle these effects [36]. This could explain the obvious correlation between the cohort effect and period effect that contribute to both cervical cancer incidence and mortality.…”

Section: Discussionmentioning

confidence: 99%

Incidence and mortality of gynaecological cancers: Secular trends in urban Shanghai, China over 40 years

Huang

Zheng

Wen

et al. 2016

European Journal of Cancer

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Aim Appraisal of cancer trends is essential for future cancer control, but relevant studies in China are scarce due to a lack of long-term data. With 40-years of cancer registry data, we sought to evaluate secular time trends in incidence and mortality of gynecological cancers in an urban Chinese population. Materials and methods Data on incidence and mortality of invasive cervical, uterine and ovarian cancer were collected by the Shanghai Cancer Registry. Age-standardized incidence and mortality rates were calculated for women aged 20–84 in urban Shanghai between 1973 and 2012. Age-period-cohort Poisson regression models were used to evaluate age, period and cohort effects. Overall linear trends, interpreted as the estimated annual percentage change (EAPC), were derived from the net drift in age-drift models. Results Overall, cervical cancer incidence and mortality substantially decreased (EAPC=−4.5% and −5.5%, respectively); however, an upward trend was apparent among younger women (age<60). Uterine cancer incidence increased slightly (EAPC=1.8%), while mortality decreased over time (EAPC=−2.4%). Ovarian cancer incidence and mortality both increased, although the increase in incidence (EAPC=1.8%) was larger than mortality (EAPC=0.6%). While cohort effects were most evident for cervical cancer incidence and mortality, significant age, period, and cohort effects were found for all three gynecological cancers evaluated. Conclusions These secular trends in incidence and mortality of gynecological cancers in Shanghai likely reflect changing risk factor profiles and improved cancer prognosis over time, and suggest new priorities and call for additional efforts for gynecological cancer prevention and control for women in China.

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“…Estimating APC models is problematic for two reasons. First, as argued by O'Brien (41), age, time and cohort effects are exactly mathematically confounded. Consequently, regressing a dependent variable on age, time, and cohort variables results in collinearity problems.…”

Section: Aging and Sustainable Employabilitymentioning

confidence: 99%

Time takes us all? A two-wave observational study of age and time effects on sustainable employability

Fleuren¹,

Amelsvoort²,

Grip³

et al. 2018

Scand J Work Environ Health

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Objectives Various cognitive and physical abilities decline with age. Consequently, sustainable employability research has focused on the labor market participation of older employees. However, it remains unclear whether age actually affects employees' work and labor-market functioning. A major complicating factor is that age effects can be distorted by time effects. That is, changes over time may not be due to aging but to some structural difference between the times of measurement. The present article aims to provide clarity by estimating age effects on sustainable employability while controlling for potential time effects. Methods Based on two-wave survey data from a sample of 2672 employees (ages 35‒65 years) multilevel regressions are estimated to analyze the effects of age and time on sustainable employability. Here, sustainable employability is operationalized as a formative construct consisting of nine dimensions, each capturing a different facet of an individual's ability to function at work and in the labor market. Results The analyses reveal that age has small effects on only two dimensions (employability and perceived health) while time affects three dimensions (fatigue, job performance, and skill gap) of sustainable employability. Moreover, for all dimensions of sustainable employability most variance exists between (61.43-84.96%) rather than within (15.04-38.57%) subjects. Conclusions These findings suggest that the process of aging has a limited effect on working individuals' capacities to function in their job and the labor market. Consequently, the focus on age in the context of sustainable employability policies and research may require reconsideration.

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The age–period–cohort conundrum as two fundamental problems

Abstract: Age–period–cohort models, Two fundamental problems, Constrained Generalized Linear Models, Intrinsic Estimator,

Cited by 28 publications

References 18 publications

Distinctive lung cancer incidence trends among men and women attributable to the period effect in Shanghai: An analysis spanning 42 years

Distinctive lung cancer incidence trends among men and women attributable to the period effect in Shanghai: An analysis spanning 42 years

Incidence and mortality of gynaecological cancers: Secular trends in urban Shanghai, China over 40 years

Time takes us all? A two-wave observational study of age and time effects on sustainable employability

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