ABSTRACT
Body mass index (BMI) has been increasing globally in recent decades. Previous studies reported that BMI was associated with sex hormone levels, but the results were generated via linear regression or logistic regression, which would lose part of information. Quantile regression analysis can maximize the use of variable information. Our study compared the associations among different regression models. The participants were recruited from the Center of Reproductive Medicine, The First Hospital of Jilin University (Changchun, China) between June 2018 and June 2019. We used linear, logistic, and quantile regression models to calculate the associations between sex hormone levels and BMI. In total, 448 men were included in this study. The average BMI was 25.7 (standard deviation [s.d.]: 3.7) kg m-2; 29.7% (n = 133) of the participants were normal weight, 45.3% (n = 203) of the participants were overweight, and 23.4% (n = 105) of the participants were obese. The levels of testosterone and estradiol significantly differed among BMI groups (all P < 0.05). In linear regression and logistic regression, BMI was associated with testosterone and estradiol levels (both P < 0.05). In quantile regression, BMI was negatively associated with testosterone levels in all quantiles after adjustment for age (all P < 0.05). BMI was positively associated with estradiol levels in most quantiles (≤80th) after adjustment for age (all P < 0.05). Our study suggested that BMI was one of the influencing factors of testosterone and estradiol. Of note, the quantile regression showed that BMI was associated with estradiol only up to the 80th percentile of estradiol.
Subject(s)
Male , Humans , Body Mass Index , Cross-Sectional Studies , Gonadal Steroid Hormones , Regression Analysis , Estradiol , TestosteroneABSTRACT
Purpose@#The evidence of adherence to cancer prevention guidelines and endometrial cancer (EC) risk has been limited and controversial. This study summarizes and quantifies the relationship between adherence to cancer prevention guidelines and EC risk. @*Materials and Methods@#The online databases PubMed, Web of Science, and EMBASE were searched for relevant publications up to June 2, 2020. This study had been registered at PROSPERO. The registration number is CRD42020149966. Study quality evaluation was performed based on the Newcastle-Ottawa Scale. The I2 statistic was used to estimate heterogeneity among studies. Egger’s and Begg’s tests assessed potential publication bias. Summary hazard ratios (HRs) and 95% confidence intervals (CIs) for the relationship between adherence to cancer prevention guidelines score was assigned to participants by summarizing individual scores for each lifestyle-related factor. The scores ranged from least healthy (0) to most healthy (20) and the EC risk was calculated using a randomeffects model. @*Results@#Five prospective studies (four cohort studies and one case‑cohort study) consisted of 4,470 EC cases, where 597,047 participants were included. Four studies had a low bias risk and one study had a high bias risk. Summary EC HR for the highest vs. lowest score of adherence to cancer prevention guidelines was 0.54 (95% CI, 0.40 to 0.73) and had a high heterogeneity (I2=86.1%). For the dose-response analysis, an increment of 1 significantly reduced the risk of EC by 6%. No significant publication bias was detected. @*Conclusion@#This study suggested that adherence to cancer prevention guidelines was negatively related to EC risk.
ABSTRACT
Objective To investigate selcnium(Se) levels of environment and human body in Gaomi City and Zichuan District of Shandong. Methods Lijiaying Township in Gaomi City of Weifang City, Zhaili Township and Longquan Township in Zichuan District of Zibo City were selected. Two farming soil samples at different spot, local wheat and corn, residents nail samples from 3 to 4 families were collected in each natural village in the investigated towns. The contents of Se were detected by 2,3-diamino naphthalene fluorescence method. Results Se level of the soil, wheat, corn, and nails in Lijiaying [(0.054 ± 0.019), (0.022 ± 0.009), (0.018 ± 0.007), (0.365 ± 0.108)mg/kg] was significantly lower than that in Zhaili [(0.425 ± 0.080), (0.130 ± 0.043), (0.098 ± 0.026), (0.751 ± 0.134)mg/kg] and Longquan[(0.487 ± 0.153), (0.112 ± 0.030), (0.097 ± 0.029), (0.735 ± 0.145)mg/kg;P < 0.01]. In Lijiaying, Se was deficient in soil, wheat, corn(< 0.200, < 0.025 mg/kg), above Se deficiency diagnosis and below Se-adequate level in the nail, while in Zhaili and Longquan, the Se level in the soil (0.425, 0.487 mg/kg), wheat(0.130, 0.112 mg/kg), corn (0.098, 0.097 mg/kg), nails (0.751, 0.735 mg/kg) was adequate (≥0.400 mg/kg). Conclusions The external environment is Se-deficient in Lijiaying, Se-adequate in Longquan and Zhaili. The selenium level in human body is consistent with the external environment.