The role of age and body mass index on cancer occurrence in a hypertensive population:a retrospective cohort study / 复旦学报（医学版）

Objective To analyze the combined effect of body mass index(BMI)and age with cancer occurrence among a hypertensive population in Minhang District,Shanghai.Methods Participants of this study were 212 394 hypertensive patients without cancer in Minhang District,Shanghai,registered in the electronic health information system from 2007 to 2015.Age and BMI were included as smoothing functions in the generalized additive Cox proportional risk model.The bivariate response model was constructed to visualize results using surface plots and to comprehensively analyze the association of BMI and age with the risk of cancer occurrence.Results A total of 22 141 participants developed cancer by Dec 31,2018.The association between age and the risk of cancer incidence showed an overall linear trend while the association between BMI and the risk of cancer incidence showed an overall"U"shape.BMI at about 26 kg/m2 showed the lowest risk of cancer incidence.The risk of cancer occurrence increased with increasing age in people with different BMIs.The associations between BMI and the risk of cancer incidence were different at different age groups:there was no significant association between BMI and the risk of cancer incidence in the young people(20-44 years).While in the middle-aged and older people aged over 45 years,BMI was associated with the risk of cancer incidence in a"U"shape.The lowest risk of cancer incidence was around the BMI of 26 kg/m2.Conclusion BMI among the population with hypertension should be controlled in a reasonable range,especially in the middle-aged and older population,to prevent cancer occurrence.

Introduction and application of quantile regression method in medical reserach / 复旦学报（医学版）

This article introduced the basic theory of quantile regression and its application in medical and public health research for methodological reference.We fit the quantile regression model to cross-sectional data from the National Health and Nutrition Examination Survey to estimate the association between sleep duration and depression levels at different quantiles of depression levels.The method showed that among people with low levels of depression,sleep duration was not significantly associated with depression level.While among people with higher levels of depression,the association of sleep duration with depression level became much more pronounced.The real data analysis shows that quantile regression can provide a comprehensive analysis of association between exposure and continuous outcome,and identify subgroups that are more sensitive to exposure,providing recommendations for targeted interventions.The method showed promising application value in medical and public health research.

Introduction and application of non-parametric regression method in medical research / 复旦学报（医学版）

This article introduced the basic theory of non-parametric regression and its application in medical and public health research for methodological reference.We conducted Cox proportional hazard models with restricted cubic splines using chronic disease management data from a Center for Disease Control and Prevention.We aimed to explore the separate and combined effects of mean fasting blood glucose level and glucose variability on all-cause mortality among individuals with type 2 diabetes.A non-linear association was observed between glucose variability and the risk of all-cause mortality.The association between glucose variability and all-cause mortality was stronger at higher mean fasting blood glucose levels compared to lower levels.The non-parametric regression methods comprehensively explored dose-response relationships between continuous exposure and outcome,revealing the combined effects of continuous exposures,which provided recommendations for targeted interventions.The method showed promising application value in medical and public health research.