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Updated: Jan 26, 2026

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Use of age-period-cohort analysis in cancer epidemiology research
Caitlin C Murphy1, Yang Claire Yang2
1Division of Epidemiology, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX; Harold C. Simmons Comprehensive Cancer Center, Dallas, TX.
Purpose Of Review:
Age-period-cohort (APC) models simultaneously estimate the effects of age - biological process of aging; time period - secular trends that occur in all ages simultaneously; and birth cohort - variation among those born around the same year or from one generation to the next. APC models inform understanding of cancer etiology, natural history, and disparities. We reviewed findings from recent studies (published 2008-2018) examining age, period, and cohort effects and summarized trends in age-standardized rates and age-specific rates by birth cohort. We also described prevalence of cancer risk factors by time period and birth cohort, including obesity, current smoking, human papilloma virus (HPV), and hepatitis C virus (HCV).
Recent Findings:
Studies (n=29) used a variety of descriptive analyses and statistical models to document age, period, and cohort trends in cancer-related outcomes. Cohort effects predominated, particularly in breast, bladder, and colorectal cancers, whereas period effects were more variable. No effect of time period was observed in studies of breast, bladder, and oral cavity cancers. Age-specific prevalence of obesity, current smoking, HPV, and HCV also varied by birth cohort, which generally paralleled cancer incidence and mortality rates.
Summary:
We observed strong cohort effects across multiple cancer types and less consistent evidence supporting the effect of time period. Birth cohort effects point to exposures early in life - or accumulated across the life course - that increase risk of cancer. Birth cohort effects also illustrate the importance of reconsidering the timing and duration of well-established risk factors to identify periods of exposure conferring the greatest risk.
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