Abstract

BackgroundBreast cancer is the most common cause of cancer—related death among women. In this paper, we studied the variations in the trends of Chinese female breast cancer mortality by age, period and cohort from 1990 to 2009.MethodsThe mortality data were collected from the Institute for Health Metrics and Evaluation. An age-period-cohort model and Intrinsic Estimator were used to estimate the age effect, period effect and cohort effect on the Chinese adult female breast cancer mortality risk.ResultsThe age effect on Chinese female breast cancer mortality initially increased, but then declined, and showed a reversed “J” shape with age. The period effect of breast cancer mortality continued to rise with the time period and increased by 59 % from 1990–1994 to 2005–2009. The cohort effect showed that the mortality risk of Chinese females born after 1911 was on the decline and decreased by 2.2336 from 1911 to 1989. The change rate of the cohort effect on breast cancer mortality fluctuated regularly. Three accelerating decreases and three decelerating decreases were noted in the variation law of the change rate.ConclusionThe results of study show the increasing mortality trend of breast cancer in Chinese female from 1990 to 2009, and the breast cancer mortality risk decreased with birth cohort.Electronic supplementary materialThe online version of this article (doi:10.1186/s12939-015-0211-x) contains supplementary material, which is available to authorized users.

Highlights

  • Cancer has become a serious public health challenge worldwide

  • According to the Globocan [1] data published by the International Agency for Research on Cancer (IARC), almost 1.67 million new breast cancer cases were diagnosed in 2012, which accounted for 25 % of all cancer cases in women

  • Wang YH [4] applied ageperiod-cohort model and coefficient constrained approach to study the influences on breast cancer mortality which was reflected by the effects of age, period and cohort

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Summary

Methods

Data source The national female breast cancer (coded in the ICD10) mortality rates were extracted from the Institute for Health Metrics and Evaluation (IHME, http:// ghdx.healthdata.org/). The statistics for a period of 5 years are required to make an APC model. Age-period-cohort model The APC model represents a classic epidemiological method that can be used to extract information from cross-sectional data regarding historical changes in the morbidity and mortality risk, termed the cohort effect [5]. The IE algorithm is a new and promising method to solve the unidentification problem associated with the APC model. It has since proven that unique solutions can be computed using the APC model with the IE algorithm [11, 12]. The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were used to evaluate the model

Results
Introduction
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