************************************************************************
* Program:  C:\NHANES\age_adj_mean_sas.sas                             *
* Proposal: Generate age adjusted means using SAS Survey Procedures    * 
************************************************************************;
LIBNAME NH "C:\NHANES\data\your_dir";
OPTIONS NODATE NOCENTER;
option ls=72;

proc format;                                       
                                                   
VALUE sexfmt   1 = 'Male'                          
               2 = 'Female'                        
                ;                              
VALUE racefmt  1 = 'NH-White'
               2 = 'NH-Black'
			   3 = 'Mex-Am'
			   4 = 'Other'
			   ;                    
VALUE agefmt                             
               1 = '20-39'                               
               2 = '40-59'                               
			   3 = '60+'       
				;         

run;                                      
                                                 
DATA ANALYSIS_DATA;
SET NH.ANALYSIS_DATA;
  
if ridstatr = 2;  ***examined  ;

if ridageyr ge 20 then sel=1;
else sel=2;

age = .;
if 20 LE ridageyr LE 39 then age=1;
if 40 LE ridageyr LE 59 then age=2;   
if ridageyr GE 60 then age=3;  

race=.;
if ridreth1=3 then race=1;
if ridreth1=4 then race=2; 
if ridreth1=1 then race=3;
if ridreth1=2 or ridreth1=5 then race=4;
 
LABEL                           
       age = 'AGE GROUP'    
	   race = 'Race Ethnicity'	
       riagendr = 'Gender'  
                     ;                                                     
                                                             
                                           
                                                               
RUN;

title;

/*race/ethnicity*/
 proc surveyreg data=analysis_data nomcar;
     STRATA sdmvstra;
	 cluster sdmvpsu;
	 weight wtmec4yr;
	 class race age;
	 MODEL    bmxbmi=race age race*age /noint solution;
	 ESTIMATE 'NH White      '  race 1 0 0 0 age .3966 .3718 .2316 race*age .3966 .3718 .2316 0 0 0 0 0 0 0 0 0, 
               
              'NH Black      '  race 0 1 0 0 age .3966 .3718 .2316 race*age 0 0 0 .3966 .3718 .2316 0 0 0 0 0 0, 
               
              'Mex Amer     '  race 0 0 1 0 age .3966 .3718 .2316 race*age 0 0 0 0 0 0 .3966 .3718 .2316 0 0 0;
     TITLE    'Age-adjusted means & standard errors of body mass index:';
     title2   'NHANES 1999-2002';
run;

 
/*total*/
 proc surveyreg data=analysis_data nomcar;
     STRATA sdmvstra;
	 cluster sdmvpsu;
	 weight wtmec4yr;
	 class race age;
	 MODEL    bmxbmi=age/noint solution;
	 ESTIMATE 'Total                      ' age .3966 .3718 .2316;
     TITLE    'Age-adjusted means & standard errors of body mass index:';
     title2   'NHANES 1999-2002';
run;

/*gender,race/ethnicity*/
 proc surveyreg data=analysis_data nomcar;
     STRATA sdmvstra;
	 cluster sdmvpsu;
	 weight wtmec4yr;
	 class riagendr race age;
	 MODEL    bmxbmi=riagendr race age  riagendr*race*age /noint solution;
	 ESTIMATE 'NH White Men' riagendr 1 0  race 1 0 0 0 age .3966 .3718 .2316 riagendr*race*age .3966 .3718 .2316 0 0 0 0 0 0 0 0 0
                 0 0 0 0 0 0 0 0 0 0 0 0,
              'NH Black Men' riagendr  1 0  race 0 1 0 0 age .3966 .3718 .2316 riagendr*race*age   0 0 0 .3966 .3718 .2316 0 0 0 0 0 0
                 0 0 0 0 0 0 0 0 0 0 0 0,
              'Mex Amer men' riagendr 1 0  race 0 0 1 0 age .3966 .3718 .2316 riagendr*race*age   0 0 0 0 0 0 .3966 .3718 .2316 0 0 0
                 0 0 0 0 0 0 0 0 0 0 0 0,
      
	          'NH white Women' riagendr 0 1 race 1 0 0 0 age .3966 .3718 .2316 riagendr*race*age 0 0 0 0 0 0 0 0 0 0 0 0  .3966 .3718 .2316 0 0 0 0 0 0 0 0 0 0 0 0,

              'NH Black Women' riagendr 0 1 race 0 1 0 0 age .3966 .3718 .2316 riagendr*race*age 0 0 0 0 0 0 0 0 0 0 0 0  0 0 0 .3966 .3718 .2316 0 0 0 0 0 0,

              'Mex Amer Women' riagendr 0 1 race 0 0 1 0 age .3966 .3718 .2316 riagendr*race*age  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .3966 .3718 .2316 0 0 0 0 0 0 ;
     TITLE    'Age-adjusted means & standard errors of body mass index:';
     title2   'NHANES 1999-2002';
run;




/*gender*/
proc surveyreg data=analysis_data nomcar;
     STRATA sdmvstra;
	 cluster sdmvpsu;
	 weight wtmec4yr;
	 class riagendr race age;
	 MODEL    bmxbmi=riagendr age riagendr*age/noint solution;
	 ESTIMATE  'Males                ' riagendr 1 0 age .3966 .3718 .2316 riagendr*age .3966 .3718 .2316 0 0 0 0 0 , 
               'Females              ' riagendr 0 1 age .3966 .3718 .2316 riagendr*age 0 0 0 .3966 .3718 .2316 0 0 ;
     TITLE    'Age-adjusted means & standard errors of body mass index:';
     title2   'NHANES 1999-2002';
run;