Statistical methods
diabetes, stroke, depressive symptoms
HEART DISEASE, HYPERLIPIDEMIA, STROKE, REGRESSION, HYPERTENSION, DIABETES
Student’s t-test was performed to evaluate differences between values at baseline and after six months of follow-up. Box plots were used to visualize differences in TL and IL-6 levels at baseline and after six months of follow-up.Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off TL that predicted depressive symptoms requiring treatment in the elderly. We used TL as the test variable and the treatment history of depressive symptoms as the state variable (dependent variable) in the ROC curve analysis. The optimal cut-off TL was defined as showing the shortest distance from the upper left corner (where sensitivity=1 and specificity=1).Pearson’s correlation analysis was performed to evaluate the associations between TL and the questionnaire and physical activity scores and concentrations of blood biomarkers at baseline and after six months of follow-up.Scatterplots with a regression line were constructed to determine whether TL was associated with GDS-KR and CCI scores and IL-6 levels. Multivariable linear regression analyses were also performed to identify whether GDS-KR and CCI scores and serum IL-6 levels were independently associated with TL. In addition to separately including GDS-KR, CCI score, and IL-6 level, covariates such as sex, age, BMI, hypertension, diabetes, hyperlipidemia, heart disease, and stroke history were entered into the multivariable model. For a comparison with the multivariable linear regression results, univariable linear regression analysis was also performed using the same variables as those used in the multivariable analysis (A p-value < 0.05 was considered statistically significant. All statistical analyses were performed using R software version 4.1.2 and SPSS for Windows version 24.0 (IBM, Chicago, IL).