Changes in the disease burden of breast cancer along with attributable risk factors in China from 1990 to 2019 and its projections: An analysis of the global burden of disease study 2019

Abstract

Background: To investigate the secular trends in breast cancer burden with attributable risk factors, and make projections over time, which would contribute to the control and prevention of breast cancer.

Methods: We extracted detailed data on breast cancer incident cases and age-standardized incidence rate (ASIR), deaths and age-standardized mortality rate (ASMR), disability-adjusted life-years (DALYs), and age-standardized DALYs rate (ASDR), as well as the attributable risk factors in China from the Global Burden of Diseases Study 2019. The estimated annual percentage change (EAPC) was calculated to quantify the changing trends. The national DALYs attributable to Socio-demographic Index (SDI) values were also presented. Projections to 2030 were estimated using the Bayesian age-period-cohort model.

Results: From 1990 to 2019, the number of breast cancer incident cases increased fourfold to 375,484, with deaths and DALYs over doubling to 96.306 and 2,957,454, respectively. The ASIR (EAPC = 2.84; 95% CI, 2.74-2.95) and ASMR (EAPC = 0.06; 95% CI, 0.00-0.12) increased, while the ASDR decreased with the EAPC of -0.13 (95% CI, -0.19 to -0.06) at the same period. The ASDR varied across provincial regions, which appeared to be in a wave-like upcurve with SDI values increasing. High body mass index became the first contribution to breast cancer DALYs for females in 2019, and alcohol use for males. Breast Cancer incident cases and deaths would increase to 587.7 and 125.6 thousand in 2030, of which there will be 577.1 and 122.7 thousand for females, and 10.6 and 2.9 thousand for males, respectively.

Conclusion: Breast cancer remains a major public health problem in China. The absolute burden has been increasing over time, and varied across sex and regions. To control the potential risk factors and develop specific strategies will help to reduce the disease burden.

Keywords: breast cancer; disease burden; risk factor; spatiotemporal trend.

FIGURE 1

The temporal trend in number and ASRs of breast cancer incidence (A), mortality (B), and DALYs (C) by sex in China, 1990–2019. The bar graphs represent the observed number and the error bars indicate the 95% uncertainty intervals (UIs); the line charts represent the ASRs and the shading indicates the 95% UIs. ASR, age‐standardized rate; DALYs, disability‐adjusted life‐years. The male information is also separately shown in Supplementary Materials.

FIGURE 2

The trend in number and rates of breast cancer incidence (A), mortality (B), and DALYs (C) by age and sex in China, 2019. The bar graphs represent the observed number and the error bars indicate the 95% uncertainty intervals (UIs); the line charts represent the age‐specific rates and the shading indicates the 95% UIs. DALY, disability‐adjusted life‐years. The male information is also separately shown in Supplementary Materials.

FIGURE 3

The subnational trend in breast cancer DALYs in China, 2017. (A) The age‐standardized DALY rate of breast cancer in 34 provinces of China. (B) The association between age‐standardized DALY rate (per 100,000) and Socio‐demographic Index values in 34 provinces of China. DALY, disability‐adjusted life‐year.

FIGURE 4

The temporal trend in proportion of breast cancer DALYs attributable to risk factors by sex, from 1990 to 2019 (A) and for different age groups in 2019 (B). DALY, disability‐adjusted life‐year.

FIGURE 5

The projection of breast cancer incidence and mortality from 2020 to 2030 in China. (A) Age‐standardized incidence rate for male. (B) Age‐standardized mortality rate for male. (C) Age‐standardized incidence rate for female. (D) Age‐standardized mortality rate for female. (E) The projected number of incident cases; (F) The projected number of deaths. The dots present the observed values. The solid lines present the projected values. The dash‐and‐dot lines and light‐green shading present the reference calculated based on the observed values in 2019.