Study2025Open access

Global burden of disease changes related to high red meat diets and breast cancer from 1990 to 2021 and its prediction up to 2030

Tong Y, Ning H, Zhang Z, Zhang X, Tu H, Yang M, Li X, Liang T

Frontiers in nutrition · 2 citations

Review labels

Lumps processed with unprocessed meatNo stated lifestyle adjustment

Neutral facts our review recorded about how this study was done. They describe method, never whether we like the result.

How it was studied

Design
Cross-sectional study (classified by our AI screen)
Studied in
People
Main outcome
Clinical events such as disease or death
Intake measured by
Not stated

Who paid for it

Funding
Independent funding
University or hospital
University of Electronic Science and Technology of China

Based on 1 listed funder(s) and full-text disclosure statement.

Publication

Published
2025-06-04 · Front Nutr · vol. 12 · p. 1586299
Publisher
Frontiers Media
Cited
4 citations · more than 92% of similar papers · 3.6× the field average
Impact
Top 10% most cited in its field
References
47 works
Access
Open access (journal) · CC-BY
Research areas
Nutritional Studies and Diet · Cancer Risks and Factors · Global Cancer Incidence and Screening
Keywords
Breast cancer, Medicine, Demography, Burden of disease, Years of potential life lost, Disease burden, Disease, Cohort, Cancer, Environmental health, Public health, Gerontology, Life expectancy, Population, Internal medicine, Pathology

8 authors

From CN

  • Yujun TongMianyang Central Hospital
  • Hong NingUniversity of Electronic Science and Technology of China; Mianyang Central Hospital
  • Zhen ZhangMianyang Central Hospital
  • Xiaohong ZhangMianyang Central Hospital
  • Hsi‐Feng TuMianyang Central Hospital
  • Min YangUniversity of Electronic Science and Technology of China; Mianyang Central Hospital

Abstract

Background

Breast cancer associated with high red meat consumption has become a significant global health issue. This study aims to analyze the global and regional disease burden related to breast cancer attributable to high red meat diets from 1990 to 2021, and to predict future trends in disease burden through 2030, providing scientific evidence for the development of targeted public health strategies.

Methods

Data were extracted from the Global Burden of Disease (GBD) database, focusing on breast cancer-related attribution indicators, including the age-standardized rates (ASRs) of mortality, years of life lost (YLLs), years lived with disability (YLDs). The study analyzed the changes in breast cancer disease burden associated with high red meat consumption from 1990 to 2021 at the global level, across 21 regions, and in 204 countries. Future trends were projected using the Bayesian Age-Period-Cohort (BAPC) model.

Results

In 2021, breast cancer deaths attributable to excessive red meat diets totaled 81,506, with YLLs amounting to 2,135,620 person-years and YLDs accounting for 214,442 person-years. These values represent increases of 80.83, 72.69, and 65.37%, respectively, compared to 1990. Despite global decreases in the ASRs of mortality and YLLs (which decreased to 1.15/100,000 and 30.12/100,000, with EAPCs of -0.77 and -0.73, respectively), the ASR of YLDs remained relatively stable (EAPC of -0.12). Stratification by Socio-Demographic Index (SDI) revealed a significant decline in disease burden in high-SDI regions, while the ASR in low-SDI regions trended upward. Projections suggested that by 2030, the global ASR of breast cancer burden may stabilize, while the burden in low-SDI regions is expected to continue rising.

Conclusion

From 1990 to 2021, the global age-standardized rate of the breast cancer disease burden decreased, but disparities between regions with different SDI levels remain a major challenge. In the future, it is essential to prioritize addressing the burden in low-SDI regions and developing targeted interventions to optimize health resources, thereby mitigating the public health threat of breast cancer.

Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY).

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