Dose-response meta-analysis, an important tool in investigating the relationship between a certain exposure and risk of disease, has been increasingly applied. Traditionally, the dose-response meta-analysis was only modelled as linearity. However, since the proposal of more powerful function models, which contains both linear, quadratic, cubic or more higher order term within the regression model, the non-linearity model of dose-response relationship is also available. The packages suit for R are available now. In this article, we introduced how to conduct a dose-response meta-analysis using dosresmeta and mvmeta packages in R.
ObjectivesTo investigate the level of ankle-brachial index (ABI) of health examination population in Chongqing municipality and analyze the risk factors related to the level of ABI, so as to provide basis for effective evaluation of atherosclerotic lesions and their severity, as well as early detection, intervention and treatment of clinical cardiovascular diseases. MethodsA total of 22 886 subjects aged from 20 to 85 undergoing health examination in the medical examination center of First Affiliated Hospital of Chongqing Medical University in Chongqing municipality from January to December in 2016 were retrospectively analyzed. ABI and related physiological and biochemical data were collected. The relationship between ABI and age was analyzed using stepwise logistic regression model combined with restricted cubic splines. ResultsThe detection rate of abnormal ABI was 3.31% in 22 886 subjects undergoing health examination with 2.90% in males and 3.92% in females. The subjects aged below 40 presented the highest detection rate of abnormal ABI (6.17%) with 4.72% in males and 8.66% in females. The subjects were divided into two groups, one with ABI≤0.9 and one with ABI>0.9; the differences in age and levels of body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) between the two groups were statistically significant (allP<0.05). Multivariate stepwise logistic regression combined with restricted cubic splines showed that age, gender and BMI were presented as independent factors affecting ABI, among which the age below 40 (OR=2.885, 95%CI (2.445, 3.404),P<0.0001) was the main risk factor. A curve relating age to probability of abnormal ABI was produced after correcting for the influences of sex and BMI, stratified by gender and BMI into different subgroups, showing a U-shaped curve of decreasing initially and then increasing between the probability of abnormal ABI and age. ConclusionsThe detection rate of abnormal ABI based on individuals undergoing health examination in Chongqing municipality was 3.31%. A U-shaped curve of downward trend followed by an upward one was shown between probability of abnormal ABI and age after correcting for the influences of gender and BMI. The clinical significance of ABI≤0.9 for youth population (20 to 40 years old) without cardiovascular risk factors requires further exploration.