Sex disparity in the association between metabolic-anthropometric phenotypes and risk of obesity-related cancer: a prospective cohort study.

BACKGROUND: Sex disparity between metabolic-obesity (defined by body mass index, BMI) phenotypes and obesity-related cancer (ORC) remains unknown. Considering BMI reflecting overall obesity but not fat distribution, we aimed to systematically assess the association of our newly proposed metabolic-anthropometric phenotypes with risk of overall and site-specific ORC by sex. METHODS: A total of 141,579 men (mean age: 56.37 years, mean follow-up time: 12.04 years) and 131,047 women (mean age: 56.22 years, mean follow up time: 11.82 years) from the UK Biobank was included, and designated as metabolic-anthropometric phenotypes based on metabolic status (metabolically healthy/unhealthy), BMI (non-obesity/obesity) and body shape (pear/slim/apple/wide). The sex-specific association of different phenotypes with overall and site-specific ORC was assessed by hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression models. RESULTS: We found metabolically unhealthy and/or obesity phenotypes conveyed a higher risk in men than in women for overall ORC and colorectal cancer compared with metabolically healthy non-obesity phenotype (Pinteraction < 0.05). Of note, metabolically healthy obesity phenotype contributed to increased risks of most ORC in men (HRs: 1.58 ~ 2.91), but only correlated with higher risks of endometrial (HR = 1.89, 95% CI: 1.54-2.32) and postmenopausal breast cancers (HR = 1.17, 95% CI: 1.05-1.31) in women. Similarly, even under metabolically healthy, men carrying apple and wide shapes phenotypes (metabolically healthy apple/wide and metabolically healthy non-obesity apple/wide) suffered an increased risk of ORC (mainly colorectal, liver, gastric cardia, and renal cancers, HRs: 1.20 ~ 3.81) in comparison with pear shape or non-obesity pear shape. CONCLUSIONS: There was a significant sex disparity between metabolic-anthropometric phenotypes and ORC risk. We advised future ORC prevention and control worth taking body shape and sex disparity into account.

EAT-Lancet Diet Pattern, Genetic Predisposition, Inflammatory Biomarkers, and Risk of Lung Cancer Incidence and Mortality.

SCOPE: The association between a planetary and sustainable EAT-Lancet diet and lung cancer remains inconclusive, with limited exploration of the role of genetic susceptibility and inflammation. METHODS AND RESULTS: The study includes 175 214 cancer-free participants in the UK Biobank. Fourteen food components are collected from a 24-h dietary recall questionnaire. A polygenic risk score is constructed through capturing the overall risk variants for lung cancer. Sixteen inflammatory biomarkers are assayed in blood samples. Participants with the highest EAT-Lancet diet scores (≥12) have a lower risk of lung cancer incidence (hazard ratio [HR] = 0.64, 95% confidence interval [CI]: 0.51-0.80) and mortality (HR = 0.65, 95% CI: 0.48-0.88), compared to those with the lowest EAT-Lancet diet scores (≤8). Interestingly, there is a significantly protective trend against both lung adenocarcinoma and lung squamous cell carcinoma with higher EAT-Lancet diet scores. Despite no significant interactions, a risk reduction trend for lung cancer is observed with increasing EAT-Lancet diet scores and decreasing genetic risk. Ten inflammatory biomarkers partially mediate the association between the EAT-Lancet diet and lung cancer risk. CONCLUSION: The study depicts a lower risk of lung cancer conferred by the EAT-Lancet diet associated with lower inflammation levels among individuals with diverse genetic predispositions.