APC analysis is a statistical technique used to assess how age, time period, and birth cohort each independently influence health outcomes, such as cancer rates. These three factors are interrelated, and APC analysis helps disentangle their distinct impacts. Age effects refer to changes in disease risk as individuals grow older, with certain cancers becoming more prevalent in older age groups. Period effects capture shifts in disease rates that impact all age groups at a specific time, often due to factors like new diagnostic methods or public health campaigns. Cohort effects relate to the shared experiences of individuals born during the same period, which may influence their health later in life, such as through lifestyle choices or environmental exposures. APC analysis employs statistical models like the Intrinsic Estimator (IE) method to evaluate the contribution of each factor, offering a deeper understanding of disease trends and informing public health strategies.