Global trends and health workforce analysis of breast cancer burden from high red meat consumption 1990-2050 using machine learning approach.

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 (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: 0.461-0.297) 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.