BackgroundThe association between glioma risk and body mass index (BMI) remains obscure.MethodsThis study aimed to assess the association between glioma risk and BMI in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsThe onset of a total of 269 gliomas was observed during a median follow-up period of 12.04 years. Compared with the normal weight, overweight (HR: 1.05; 95% CI: 0.80, 1.39) and obesity (HR: 0.91; 95% CI: 0.56, 1.39) were not significantly associated with glioma risk. Further analysis showed a nonlinear relationship between glioma risk and BMI in men but not women. The multivariable-adjusted HRs per unit increase in BMI were 0.94 (95% CI: 0.89, 1.00; P = 0.037) in men with BMI >25 kg/m2 and 1.16 (95% CI: 0.98, 1.38; P = 0.075) in men with BMI <25 kg/m2.ConclusionThe present data provide evidence that there may be a nonlinear association between BMI and glioma risk in men. The risk of glioma decreased with increasing BMI among men with BMI >25 kg/m2. Future studies are needed to validate our observation.
BackgroundEpidemiological evidence that glioma has a slight male predominance implies that factors associated with sex hormones may play a role in the development of glioma. The association between oral contraceptive (OC) use and glioma risk remains controversial.MethodIn the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial of 70,516 women in the USA, Cox proportional hazards regression analyses were adopted to calculate the crude and adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Additionally, a meta-analysis combining the PLCO findings with those of other prospective cohorts was performed.ResultsDuring a mean follow-up of ~11.7 years, 110 of 70,516 women aged 50–78 years at baseline were diagnosed with glioma in PLCO studies. Compared with never users, an inverse association of borderline significance was found for OC users (HR 0.67, 95% CI 0.44–1.04, P = 0.074). Analyses assessing glioma risk according to the duration of OC use yielded no significant association. When PLCO was combined with four other prospective studies, there was an inverse association between OC use and glioma risk (HR 0.85, 95% CI 0.75–0.97, I2 = 0.0%). Further dose-response analysis showed a nonlinear, inverse relationship between OC use and glioma risk (P < 0.001).ConclusionsThis study provided some evidence of a nonlinear, inverse association between OC use and glioma risk. Future larger studies are warranted to validate this finding.
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