ORIGINAL RESEARCH article
Front. Nutr.
Sec. Nutritional Epidemiology
Volume 12 - 2025 | doi: 10.3389/fnut.2025.1576043
Global Trends and Health Workforce Analysis of Breast Cancer Burden from High Red Meat Consumption 1990 to 2050 Using Machine Learning Approach
Provisionally accepted
- 1Department of Gastrointestinal and Hernia Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, China
- 2Kunming Medical University, Kunming, China
- 3Department of Breast Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, China
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Background: High red meat consumption has been implicated in breast cancer development, yet comprehensive global burden assessments and health system relationships remain limited.. Methods: We analyzed breast cancer mortality and disability-adjusted life years (DALYs) using Global Burden of Disease 2021 data across 204 countries. Age-period-cohort analysis, decomposition analysis, health inequality assessment, frontier analysis, and correlation analysis with healthcare workforce density were employed. Machine learning models (ARIMA, Prophet) provided projections to 2050. Results: Despite declining global age-standardized mortality rates (APC: -0.772%), absolute breast cancer deaths increased from 45,074 (1990) to 81,506 (2021), with DALYs rising from 1.4 to 2.5 million. Profound regional disparities emerged: high-income regions showed declining trends (Western Europe APC: -1.736%) while developing regions experienced increasing burdens (North Africa/Middle East APC: +2.026%). Decomposition analysis revealed population growth (100.266%) and aging (34.86%) as primary drivers, partially offset by epidemiological improvements (-35.127%). Turkey exhibited the largest mortality increase (APC: +3.924%) versus Denmark's greatest decline (APC: -2.379%). Healthcare workforce analysis demonstrated strong initial correlations between nursing/midwifery density and disease burden (r=0.68, 1990) that weakened substantially over time (r=0.24, 2019), suggesting evolving detection-prevention dynamics. Health inequality analysis showed declining relative disparities (Concentration Index: 0.461 to 0.297) despite increasing absolute gaps. Machine learning projections forecast continued burden increases, with female deaths reaching 99,749 by 2050 . Conclusions: The global breast cancer burden associated with red meat consumption presents a complex paradox of declining age-standardized rates alongside rising absolute burden, with pronounced inequalities between developed and developing nations. The evolving relationship between healthcare workforce and disease burden highlights shifting dynamics from detection-driven increases to prevention-focused reductions. Strategic policy interventions should prioritize nursing and physical therapy workforce investment in developing regions, implement age-specific prevention strategies for younger populations (25-34 years), and establish context-specific dietary guidelines that consider socioeconomic factors to effectively reduce global breast cancer burden
Keywords: breast cancer, red meat consumption, Global burden of disease, Health Disparities, Healthcare workforce density
Received: 14 Feb 2025; Accepted: 28 Jul 2025.
Copyright: © 2025 Cai and Qian. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jingxian Qian, Kunming Medical University, Kunming, China
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