Adherence to the World Cancer Research Fund/American Institute for Cancer Research recommendations and endometrial cancer risk: a multicentric case–control study.

Autor: Esposito, Giovanna, Turati, Federica, Serraino, Diego, Crispo, Anna, Negri, Eva, Parazzini, Fabio, La Vecchia, Carlo
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Zdroj: British Journal of Nutrition; 6/28/2023, Vol. 129 Issue 12, p2133-2141, 9p
Abstrakt: The World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) published evidence-based recommendations for cancer prevention focusing on body weight, physical activity, and diet. Our aim is to evaluate whether adherence to the WCRF/AICR recommendations could reduce endometrial cancer risk. We used data from a multicentric, Italian hospital-based case–control study (1992–2006) including 454 endometrial cancer cases and 908 age-matched controls. Adherence to the WCRF/AICR recommendations was measured using a score (range: 0–7) based on seven components: body mass index (BMI), physical activity and five dietary items; higher scores indicated higher adherence. Odds ratios (OR) were estimated by multiple (adjusted) conditional logistic regression models including terms for major confounders and energy intake. Adherence to the WCRF/AICR recommendations was inversely related to endometrial cancer risk (OR = 0·42, 95 % confidence interval (CI) 0·30, 0·61 for the highest compared with the lowest score quartile), with a significant trend of decreasing risk with increasing adherence. An inverse association was also observed for a score including only dietary recommendations (OR = 0·67, 95 % CI 0·46, 0·96 for the highest compared with the lowest score tertile). In stratified analyses, the association was stronger among women with a normal weight, those who were older, and consequently those in post-menopause, and those with ≥ 2 children. In conclusion, high adherence to the WCRF/AICR recommendations has a favourable role in endometrial cancer risk, which is not fully explained by body weight. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index