Cai Yuzhou, Qian Jingxian
Department of Gastrointestinal Surgery, The First Affiliated Hospital of Kunming Medical University, Yunnan, China.
Department of Breast Surgery, The First Affiliated Hospital of Kunming Medical University, Yunnan, China.
Front Nutr. 2025 Aug 14;12:1576043. doi: 10.3389/fnut.2025.1576043. eCollection 2025.
High red meat consumption has been implicated in breast cancer development, yet comprehensive global burden assessments and health system relationships remain limited.
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.
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%) vs. Denmark's greatest decline (APC: -2.379%). Healthcare workforce analysis demonstrated strong initial correlations between nursing/midwifery density and disease burden ( = 0.68, 1990) that weakened substantially over time ( = 0.24, 2019), suggesting evolving detection-prevention dynamics. Health inequality analysis showed declining relative disparities (Concentration Index: 0.461-0.297) despite increasing absolute gaps. Machine learning projections forecast continued burden increases, with female deaths reaching 99,749 by 2050.
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.
大量食用红肉被认为与乳腺癌的发生有关，但全面的全球负担评估以及与卫生系统的关系仍然有限。
我们使用2021年全球疾病负担数据，对204个国家的乳腺癌死亡率和伤残调整生命年（DALYs）进行了分析。采用了年龄-时期-队列分析、分解分析、健康不平等评估、前沿分析以及与医疗劳动力密度的相关分析。机器学习模型（ARIMA、Prophet）提供了到2050年的预测。
尽管全球年龄标准化死亡率呈下降趋势（年度百分比变化：-0.772%），但乳腺癌绝对死亡人数从1990年的45,074人增加到2021年的81,506人，伤残调整生命年从140万增加到250万。出现了明显的地区差异：高收入地区呈下降趋势（西欧年度百分比变化：-1.736%），而发展中地区的负担则不断增加（北非/中东年度百分比变化：+2.026%）。分解分析表明，人口增长（100.266%）和老龄化（34.86%）是主要驱动因素，部分被流行病学改善所抵消（-35.127%）。土耳其的死亡率增幅最大（年度百分比变化：+3.924%），而丹麦的降幅最大（年度百分比变化：-2.379%）。医疗劳动力分析表明，护理/助产士密度与疾病负担之间最初存在很强的相关性（1990年相关系数 = 0.68），但随着时间的推移大幅减弱（2019年相关系数 = 0.24），这表明检测-预防动态在不断演变。健康不平等分析表明，尽管绝对差距在扩大，但相对差距在缩小（集中指数：0.461 - 0.297）。机器学习预测显示负担将持续增加，到 2050年女性死亡人数将达到99,749人。
与红肉消费相关的全球乳腺癌负担呈现出一种复杂的矛盾现象，即年龄标准化率下降的同时绝对负担却在上升，发达国家和发展中国家之间存在明显的不平等。医疗劳动力与疾病负担之间不断演变的关系凸显了从检测驱动的增加向以预防为重点的减少的动态转变。战略政策干预应优先考虑在发展中地区投资护理和物理治疗劳动力，针对年轻人群（25 - 34岁）实施特定年龄的预防策略，并制定考虑社会经济因素的因地制宜的饮食指南，以有效减轻全球乳腺癌负担。
