Evidence map›Paper›PMID 41826475›Full record

ArticleScientific reports2026

Long-term associations between animal-source food consumption and breast and prostate cancer incidence based on cointegration and ARIMAX models.

Alessia Spada, Michele Tomaiuolo, Elisa Pia Amorusi, Nicholas Calà, Raffaele Ianzano, Pasquale Ieluzzi, Giovanni Emanuele Ricciardi, Antonio Tucci

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Alessia SpadaStatistics and Mathematics Area, Department of Economics, University of Foggia, Foggia, Italy. alessia.spada@unifg.it.
Michele TomaiuoloEtromapmacs Pole, Agorà Biomedical Sciences, 71010, Foggia, Italy.
Elisa Pia AmorusiEtromapmacs Pole, Agorà Biomedical Sciences, 71010, Foggia, Italy.
Nicholas CalàEtromapmacs Pole, Agorà Biomedical Sciences, 71010, Foggia, Italy.
Raffaele IanzanoEtromapmacs Pole, Agorà Biomedical Sciences, 71010, Foggia, Italy.
Pasquale IeluzziEtromapmacs Pole, Agorà Biomedical Sciences, 71010, Foggia, Italy.
Giovanni Emanuele RicciardiSchool of Medicine, Vita-Salute San Raffaele University, 20132, Milan, Italy.
Antonio TucciEtromapmacs Pole, Agorà Biomedical Sciences, 71010, Foggia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding whether and to what extent dietary habits influence the long-term incidence of hormone-sensitive cancers is undoubtedly a significant challenge. Conventional approaches, which are often limited to studies with short follow-up periods or methods that do not consider lag times, risk producing spurious associations and consequently lead to weak conclusions. In this study, we analyzed exceptionally long 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. Initially, to avoid the risk of multicollinearity between variables, dairy and meat consumption data were summarized into a single index (PC1), obtained using principal components analysis (PCA). We then applied a rigorous econometric framework to investigate long-term dynamics. The first step consisted of testing for cointegration between PC1 and the cancer incidence series. The second step was ARIMAX modeling, with PC1 included as an exogenous variable at a lag that minimizes the AICc criterion. The study revealed evidence of cointegration between consumption and cancer incidence for both cancers, i.e., a long-term equilibrium. For breast cancer, the optimal ARIMAX model (0,0,1) identified a positive and highly significant association with PC1 at a lag of 18 years (β = 0.108, p < 0.001). For prostate cancer, an identically structured model (0,0,1) showed an even stronger and highly significant association at 15 years (β = 0.384, p < 0.001). Both models passed the diagnostic tests, confirming their validity and statistical robustness. These findings provide consistent quantitative evidence of long-term association 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.

Indexed as

Breast NeoplasmsDairy ProductsDietFeeding BehaviorMeatProstatic NeoplasmsAnimalsFemaleHumansIncidenceItalyMalePrincipal Component AnalysisARIMAX modelBreast cancerCointegrationDairyMeatProstate cancer

Identifiers

PMID41826475
PMCPMC13046939

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