Long-Term Relationship Between Animal Product Consumption and Cancer Incidence: A Cointegration- and ARIMAX-Based Approach

Abstract Understanding how dietary habits shape the long-term incidence of hormone-sensitive cancers remains a major challenge. Conventional approaches, often constrained by short follow-up periods or static methods, risk producing spurious associations and weak conclusions. In this study, we analyzed exceptionally comprehensive Italian national time series (1961–2020 for meat and dairy consumption; 1984–2020 for cancer incidence) to investigate the association between diet and the development of breast and prostate cancer.We first employed Principal Component Analysis (PCA) to synthesize consumption data into a single index (PC1), thereby reducing multicollinearity among variables. We then applied a rigorous econometric framework that combined with ARIMAX modeling, designed to distinguish genuine long-term dynamics from superficial statistical associations.The analyses revealed evidence of cointegration between consumption and cancer incidence for both malignancies. In breast cancer, the optimal ARIMAX (0,0,1) model identified a positive and highly significant effect of PC1 with an 18-year latency (β = 0.108, p < 0.001). In prostate cancer, a model of identical structure showed an even larger and highly significant effect, with a 15-year latency (β = 0.384, p < 0.001). Both models passed all diagnostic checks, confirming statistical validity and robustness.These findings offer robust quantitative evidence of long-latency relationships between animal product consumption and hormone-sensitive cancers. More broadly, the study highlights the relevance of econometric methodologies in cancer epidemiology and emphasizes their potential to deepen our understanding of how cumulative dietary exposures influence population health.