Stata 14.2 ic

Frequency data are reported as numbers and percentages, and continuous data are presented as mean ± standard deviation. Multivariable logistic regression analyses were performed to estimate the odds ratio (OR) and 95% confidence interval (CI) for low levels of handgrip strength, skeletal muscle mass index, calf circumference, or possible sarcopenia with NT (continuous variable) or MF (continuous variable). For all analyses, independent variables were adjusted for sex, age, BMI, smoking, alcohol consumption, and physical activity in Model 1. Model 2 was additionally adjusted for diabetes mellitus. Multivariable logistic regression analyses were performed to estimate the OR and 95% CI for the diabetes mellitus outcome with NT (continuous variable) or MF (continuous variable). For all analyses, independent variables were adjusted for sex, age, BMI, smoking, alcohol consumption, and physical activity in Model 1, and additionally adjusted for possible sarcopenia in Model 2. Statistical analyses were performed using STATA 14.2/IC. All p-values for statistical tests were two-tailed, and values <0.05 were regarded as statistically significant.

The quantitative variables were expressed as the mean and standard deviation (SD) for those with a normal distribution and as the median and interquartile range (IQR1, IQR3) for those with a nonnormal distribution. Categorical variables were expressed as absolute and relative frequencies. Differences were estimated with ANOVA for numerical variables and with the chi² test for categorical variables. Kaplan–Meier curves were used for the survival analysis with a closing date of August 1, 2018. The data were entered and analysed using the program STATA 14.2 IC (StataCorp LLC, USA).