In multivariate models age, sex, and number of medicines were included as covariables.
In these multivariate models, age was significantly and negatively associated with incident A1C-DM, FPG-DM, or FPG/A1C-DM.
In multivariate models, age, smoking, BMI, systolic BP, pulse pressure, cholesterol, presence of metabolic syndrome and eGFRCKD-EPI were included.
The following confounders were included in the multivariate models: age, body mass index (BMI), Karnofsky score, presence of COPD, oxygen saturation and urea (table 3).
In the multivariate models, age, sex, educational levels, BMI, eGFR, CES-DK scores, hypertension, type 2 diabetes, hyperlipidemia, and smoking and drinking status were adjusted.
In multivariate models, age was an independent predictor of both arterial wall thickening and plaque formation, and lymphopenia was an independent risk factor for plaque formation.
In the multivariate model, age, clinical stage, and comorbidity were found to be negatively associated with the survival rate.
In the multivariate model, age, SNP panel RR and BMI were significantly associated with breast cancer diagnosis.
In the multivariate model age, gender, being happy/not thinking about one's weight and not knowing one's ideal weight were associated with misperception.
At first, variables that were significant at P < 0.20 on the univariate analysis were entered into the multivariate model (age, erythrocyte sedimentation rate and C-reactive protein).
For the 1999 2000 survey period, in the final multivariate model, age group and time of sample collection were the only significant variables in addition to log-transformed creatinine.
