ObjectiveTo explore the prevalence and risk factors of hypertension and diabetes in floating population in Hubei province, so as to provide reference for the prevention of chronic disease of floating population. MethodA multi-stages sampling was performed among six counties in Hubei province in 2012, according to the different occupations. A questionnaire survey was conducted to collect the demography, sociology and health-related behavioral characteristics of subjects. Then a univariate analysis and a multivariate analysis were conducted by SPSS 20.0 software. ResultsA total of 1 800 individuals were surveyed, and the prevalence of hypertension and diabetes in floating population was 22.7% and 4.9%, respectively. Univariate analysis indicated that significant associations were found between hypertension and such factors as age, occupations, smoking and life satisfaction (all P values < 0.05); and significant associations were found between diabetes and such factors as occupations, educational level and BMI (all P values < 0.05). The results of further logistic regression analysis showed that age (OR=2.194, 95% CI 1.940 to 2.483, P=0.001) and life satisfaction (OR=0.291, 95% CI 0.248 to 0.341, P=0.002) were independent risk factors of hypertension, and educational level (OR=3.219, 95%CI 2.016 to 7.565, P=0.011) and gender (OR=0.568, 95% CI 0.323 to 0.999, P=0.049) were independent risk factors of diabetes. ConclusionsThe prevalence of hypertension and diabetes are relative high in floating population of Hubei Province. Increasing age and low life satisfaction are independent risk factors of hypertension in floating population, while male and low educational level are independent risks factors of diabetes.
R software is a free and powerful statistical software, which has the functions of data processing and graphics drawing and is widely used in the meta-analysis. This article introduced detailed operation steps of rmeta package which is suitable for meta-analysis of binary data, and also can finish cumulative meta-analysis, draw standard summary plots, forest plot and funnel plot. In summary, the functions of rmeta package are simple and easy to mastery. There are some limitations of current version which need to be improved in the future.
As a valid method in systematic review, dose-response meta-analysis is widely used in investigating the relationship between independent variable and dependent variable, and which usually based on observational studies. With large sample size, observational studies can provide a reasonable amount of statistical power for meta-analysis. However, due to the design defects of observational studies, they tend to introduce many kinds of biases, which may influence the final results that make them deviation from the truth. Given the dead zone of methodology, there is no any bias adjusting method in dose-response meta-analysis. In this article, we will introduce some bias adjusting methods from other observational-study-based meta-analysis and make them suit for dose-response meta-analysis, and then compare the advantages and disadvantages of these methods.