master <- master %>% mutate(race=case_when(
            race==1~ "White",
            race==2~ "Black",
            race==3~ "Mixed",
            race==4~ "Asian")) %>% 

             
    mutate(
    BMI_cat=case_when( BMI<18.5 ~ "Underweight",
                       BMI>=18.5 & BMI< 24.9 ~ "Normal Range",
                       BMI>=24.9 & BMI<29.9 ~ "Overweight",
                       BMI>=29.9 ~"Obse")) %>% 
    mutate(CAD=case_when(
      MI == 1 | coronary_insufficiance== 1 ~ 1,
      TRUE ~ 0)) %>% 
      
    mutate(CVD=case_when(
             stroke== 1|
             stroke_sequel== 1 ~ 1,
      TRUE~0)) %>%  
    mutate(
    liver_disease=case_when(
      liver_disease=="0"~ "no disease", 
      TRUE~ "disease")) %>% mutate(ckd_stage=case_when(
        CKDEPIcrcys21>=60 ~ "stage 1 or 2 ",
        CKDEPIcrcys21<60 & CKDEPIcrcys21>=30 ~ "stage 3" ,
        CKDEPIcrcys21<30 ~ "stage 4 or 5
        "
      )) %>% 
    select(-ckd_stage) %>% 
    mutate(ckd_stage=case_when(mGFRadj>=60 ~ "stage 1 or 2",
                               mGFRadj>=30 &  mGFRadj< 60~ "stage 3",
                               mGFRadj<30 ~"stage 4"
                               ))%>% 
    mutate(age_65=ifelse(age>=65,1,0))

  
  master$race <- factor(master$race,levels = c("White","Mixed","Black","Asian"))
  master$BMI_cat <- factor(master$BMI_cat,levels = c("Underweight","Normal Range","Overweight","Obse"))

t test mean SMI by sex

table1(~SMI|gender,data=master)
Female
(N=235)		 Male
(N=230)		 Overall
(N=465)
SMI
Mean (SD) 46.6 (7.65) 54.2 (8.48) 50.4 (8.92)
Median [Min, Max] 45.5 [28.1, 69.5] 54.1 [36.6, 75.6] 49.8 [28.1, 75.6] 
t.test(SMI ~ gender, data = master)
## 
##  Welch Two Sample t-test
## 
## data:  SMI by gender
## t = -10.166, df = 455.95, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group Female and group Male is not equal to 0
## 95 percent confidence interval:
##  -9.092887 -6.146793
## sample estimates:
## mean in group Female   mean in group Male 
##             46.60850             54.22834

t test mean SMI by sex in CT-defined sarcopenia

master_sarcopenia <- master %>% filter(sarcopenia_prado==1)
table1(~SMI|gender,data=master_sarcopenia)
Female
(N=32)		 Male
(N=125)		 Overall
(N=157)
SMI
Mean (SD) 35.5 (2.81) 47.9 (4.86) 45.4 (6.74)
Median [Min, Max] 36.4 [28.1, 39.0] 48.3 [36.6, 54.9] 46.3 [28.1, 54.9] 
t.test(SMI ~ gender, data = master_sarcopenia)
## 
##  Welch Two Sample t-test
## 
## data:  SMI by gender
## t = -18.75, df = 84.277, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group Female and group Male is not equal to 0
## 95 percent confidence interval:
##  -13.69417 -11.06802
## sample estimates:
## mean in group Female   mean in group Male 
##             35.49953             47.88062

t test mean TAI by sex

table1(~TAI|gender,data=master)
Female
(N=235)		 Male
(N=230)		 Overall
(N=465)
TAI
Mean (SD) 148 (71.0) 114 (58.0) 131 (67.1)
Median [Min, Max] 135 [16.9, 374] 110 [5.38, 309] 125 [5.38, 374] 
t.test(TAI ~ gender, data = master)
## 
##  Welch Two Sample t-test
## 
## data:  TAI by gender
## t = 5.7054, df = 448.74, p-value = 2.11e-08
## alternative hypothesis: true difference in means between group Female and group Male is not equal to 0
## 95 percent confidence interval:
##  22.47459 46.09303
## sample estimates:
## mean in group Female   mean in group Male 
##             148.1098             113.8260