*****************************************************************************************************************;
* Example SUDAAN code to replicate NCHS Data Brief No. 364, Figures 1 - 3                                       *;
* Hypertension Prevalence Among Adults Aged 18 and Over: United States, 2017–2018                               *;
*                                                                                                               *;
* Ostchega,Y, Fryar,CD, Nwankwo, T, Nguyen, DT. Hypertension Prevalence Among Adults Aged 18 and Over:          *; 
* United States, 2017–2018. NCHS Data Brief. No 364. Hyattsville, MD: National Center for Health Statistics.    *;
* 2020.                                                                                                         *; 
*                                                                                                               *;
* Available at: https://www.cdc.gov/nchs/products/databriefs/db364.htm                                          *;
*****************************************************************************************************************;

 
%global  home macros titles liblabel; 
%let home     = ./; /*Insert path to Home folder where the macro is saved*/
 
/*** Include Korn and Graubard macro ***/ 
/*** This code assumes the macro is stored in a subfolder of home called 'macros' ***/ 

%include "&home\macros\KG_macro.sas";

options nocenter nodate nonumber pagesize=100 linesize=150;
OPTIONS FORMCHAR="|----|+|---+=|-/\<>*";

%put Run in SAS &sysver (maintenance release and release year: &sysvlong4)
 and SUDAAN Release 11.0.1 (SAS-Callable, 32 bit version);

** Macro To Download Data from NHANES website **;

%macro CreateDS(myDS);
  %let i = 1;
  %let DS = %scan(&myDS, &i);

  %do %until(&DS = %nrstr());
    %let Suffix = %lowcase(%substr(&DS, %eval(%length(&DS)-1)));
    %if (&Suffix = _j) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2017-2018/&DS..xpt"; %end;
    %else %if (&Suffix = _i) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2015-2016/&DS..xpt"; %end;
    %else %if (&Suffix = _h) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2013-2014/&DS..xpt"; %end;
    %else %if (&Suffix = _g) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2011-2012/&DS..xpt"; %end;
    %else %if (&Suffix = _f) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2009-2010/&DS..xpt"; %end;
    %else %if (&Suffix = _e) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2007-2008/&DS..xpt"; %end;
    %else %if (&Suffix = _d) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2005-2006/&DS..xpt"; %end;
    %else %if (&Suffix = _c) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2003-2004/&DS..xpt"; %end;
    %else %if (&Suffix = _b) %then %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/2001-2002/&DS..xpt"; %end;
    %else %do; filename &DS url "https://wwwn.cdc.gov/nchs/nhanes/1999-2000/&DS..xpt"; %end;
    libname &DS xport;

    data &DS;
      set &DS..&DS;
    run;

    %let i = %eval(&i+1);
    %let DS = %scan(&myDS, &i);
  %end;
%mend CreateDS;

** DOWNLOAD DATASETS **;
%CreateDS(demo bpq bpx);
%CreateDS(demo_b bpq_b bpx_b);
%CreateDS(demo_c bpq_c bpx_c);
%CreateDS(demo_d bpq_d bpx_d);
%CreateDS(demo_e bpq_e bpx_e);
%CreateDS(demo_f bpq_f bpx_f);
%CreateDS(demo_g bpq_g bpx_g);
%CreateDS(demo_h bpq_h bpx_h);
%CreateDS(demo_i bpq_i bpx_i);
%CreateDS(demo_j bpq_j bpx_j);


data demo; 
set demo 
demo_b 
demo_c 
demo_d 
demo_e 
demo_f 
demo_g 
demo_h 
demo_i 
demo_j ; run;

data bpx (keep=seqn bpxsy1-bpxsy4 bpxdi1-bpxdi4); 
set bpx 
bpx_b
bpx_c
bpx_d
bpx_e
bpx_f
bpx_g
bpx_h
bpx_i
bpx_j; run;


data bpq (keep=seqn bpq020 bpq050a BPQ100D); 
set bpq 
bpq_b 
bpq_c 
bpq_d 
bpq_e 
bpq_f 
bpq_g 
bpq_h 
bpq_i 
bpq_j ; run;

proc sort data=demo; by seqn; run;
proc sort data=bpq; by seqn; run;
proc sort data=bpx; by seqn; run;

data hyper_9918;
  merge demo
        bpq(keep=seqn bpq020 bpq050a BPQ100D)
        bpx(keep=seqn bpxsy1-bpxsy4 bpxdi1-bpxdi4);
                 by seqn; 
run; 


Proc format;
  value age   
  1="20-39" 
  2="40-59" 
  3="60+";
  value agecat 
  1="18-39" 
  2="40-59" 
  3="60+"
  0,-2='18 and over';
  value sexf   
  1='Men'
  2='Women'
  0,-2='All';
  value FPL  
  1='<=130'
  2='130-<=350'
  3='>350';
  VALUE EDUC    
  1='<HS grad or less'
  2='Some College'
  3='>=College graduate';

  value race4fmt 
  1='NH white'
  2='NH black'
  3='NH Asian'
  4='Hispanic'
  5='other';
  value hyper_new  
  1="New HTN" 
  0="no hypertension";
  value hyper_old  
  1="Old HTN" 
  0="no hypertension";
  value control  
  1="Controlled" 
  0="not controlled";
  value s     
  1='1999-2000'
  2='2001-2002'
  3='2003-2004'
  4='2005-2006'
  5='2007-2008'
  6='2009-2010'
  7='2011-2012'
  8='2013-2014'
  9='2015-2016' 
  10='2017-2018';
  value aware   
  1="aware" 
  0="unaware";
run;

* Create hypertension variable and covariates *;
data hyper9918;
  set hyper_9918;

   ** create age group category included**;
       
  if 18 le ridageyr lt 40 then agecat=1;
  else if 40 le ridageyr lt 60 then agecat=2;
  else if  ridageyr ge 60      then agecat=3;

  * race and Hispanic origin (starting with 2011-2012 cycle) *;
  if ridreth3=3 then race_et4=1;
  else if ridreth3=4 then race_et4=2;
  else if ridreth3=6 then race_et4=3;
  else if ridreth3 in (1,2) then race_et4=4;
  else if ridreth3=7 then race_et4=5;

  *income;
  if indfmpir >0.00 and indfmpir le 1.30 then FPL=1;
  else if indfmpir >1.30 and indfmpir le 3.50 then FPL=2;
  else if indfmpir >3.50 then FPL=3;
   
  *education;

  If ridageyr in (18,19) then do;
  if (dmdeduc3 >=0 and dmdeduc3 <15) or dmdeduc3=55 or dmdeduc3=66 then EDUC = 1; /*HS DIPLOMA or LESS*/
  else if dmdeduc3=15 then EDUC=2;      /*Some college*/
  end; 

  if dmdeduc2 in(1,2,3) then EDUC = 1;    /*HS DIPLOMA or LESS*/
  else if dmdeduc2=4 then EDUC=2;       /*Some college*/
  else if dmdeduc2=5  then EDUC =3;     /*COLLEGE*/

  **Hypertension prevalence;
  ** Count Number of Nonmissing SBP's & DBP's **;
  n_sbp = n(of bpxsy1-bpxsy4);
  n_dbp = n(of bpxdi1-bpxdi4);
  ** Set DBP Values Of 0 To Missing For Calculating Average **;
  array _DBP bpxdi1-bpxdi4;
  do over _DBP;
    if (_DBP = 0) then _DBP = .;
  end;  
  ** Calculate Mean Systolic and Diastolic **;
  mean_sbp = mean(of bpxsy1-bpxsy4);
  mean_dbp = mean(of bpxdi1-bpxdi4);
    ** Create Hypertensive Category Variable **;
      
  ** Create Hypertensive Category Variable (code used in previous DB definitions)************************;

  **NOTE: These category variables can be defined as 1=100 and 0=0. In that case, means and semeans are used in 
  SUDAAN procedure instead of percent and sepercent***;

  if (mean_sbp >= 130 or mean_dbp >= 80 or bpq050a = 1) then do; Hyper_new = 1;
  if (mean_sbp >= 130 or mean_dbp >= 80) then Controlled = 0;
  else if (n_sbp > 0 and n_dbp > 0) then Controlled = 1;
  end;
  else if (n_sbp > 0 and n_dbp > 0) then Hyper_new = 0;

    
  if (mean_sbp >= 140 or mean_dbp >= 90 or bpq050a = 1) then do; Hyper_old = 1;
  if (mean_sbp >= 140 or mean_dbp >= 90) then Controlold = 0;
  else if (n_sbp > 0 and n_dbp > 0) then Controlold = 1;
  end;
  else if (n_sbp > 0 and n_dbp > 0) then Hyper_old = 0;


  ***aware**********************************************************************;
  if bpq020=1 then aware=1;
  else if bpq020=2 then aware=0;

  **Subpopulation of interest ***************************************************;

  if ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0) then sel1=1;  

  * indicator for overall estimates *;
  one=1;
run;


**************************************************************************;
*Subsetting NHANES 2017-2018 data*;
**************************************************************************;
data hyper_1718; 
  set hyper9918; 
  if sddsrvyr=10; 
run;

* sort by strata and PSU before running SUDAAN procedures *;
proc sort data = hyper_1718;
  by sdmvstra sdmvpsu;
run;


*********************************************************;
*             AGE-ADJUSTED PREVALENCE RATES             *;
*********************************************************;


title "Age-adjusted Prevalence of hypertension, by sex, age, race and Hispanic origin, and education level";

* Age-adjustment weights for adults aged 18 and over from estimated year 2000 Census population, with age groups 18-39,40-59, 60+ years;
%let ageShares = 0.4203  0.3572  0.2225;

proc descript data=hyper_1718 atlevel1=1 atlevel2=2 ;
  * Nest statement: PSUs nested within Strata accounts for the design effects*;
  nest sdmvstra sdmvpsu;
  * Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
  weight wtmec2yr;
  * Subpopx statement: specify the subpopulation of interest (the inclusion criteria) *;
  subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0); 
  * Class statement: specify categorical variable(s)*;
  class one riagendr agecat race_et4 educ /nofreq;
  * Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
  var hyper_new ;
  catlevel 1 ;
  * Stdvar statement: specifies the variables used to calculate the standard age proportions*;
  stdvar agecat;
  * Stdwgt statement: specifies the precalculated standard age proportions*;
  stdwgt   &ageShares; 
  /*ALTERNATIVE*;
  stdwgt   0.4203  0.3572  0.2225; */
  * Table(s) statement: specifies cross-tabulations for which estimates are requested. *;
  * request age-standardized estimates of interest *;
  * also request age-specific estimates (i.e. interaction with agecat) which are needed to calculate Korn and Graubard confidence intervals *;
  tables riagendr*agecat
         riagendr*race_et4*agecat
         riagendr*educ*agecat;
  print nsum percent sepercent lowpct uppct/style=nchs percentfmt=f8.1 lowpctfmt=f8.1 uppctfmt=f8.1;
  output nsum percent sepercent atlev1 atlev2 /filename=HTNp percentfmt=f8.1 sepercentfmt=f8.1 replace;
  rtitle "Tables 1,2,3 Age adjusted prevalence of hypertension (new=130/80;old=140/90),by sex,age, r/e adults 18 years and older, US, 2017-2018";
  rfootnote "Age standardized by the direct method to the year 2000 census population estimates using the age groups 18-39,40-59, 60+ years";
  rformat agecat agecat.;
  rformat riagendr sexf.;
  rformat race_et4 race4fmt.;
  rformat educ educ.;
run;

* Call macro to calculate Korn and Graubard confidence intervals, for age-adjusted estimates *;
* see the macro documentation for more detail on options *;
%calculate_KornGraubard_CIs(age_adjusted=yes, dropAgeSpecific=no);

data HTNp_KG2;
  set HTNp_KG;
  * Keep age-specific estimates only for table 1 *;
  if (tableno in (2,3) and agecat not in (0,-2)) then delete;
  * delete totals for tables 2 and 3 *;
  if race_et4=0 or educ=0 then delete;
run;

proc print data=HTNp_KG2 (where=(tableno=1)) noobs label;
  var riagendr agecat nsum percent sepercent;
  title "Data table for Figure 1. Prevalence of hypertension among adults aged 18 and over, by sex and age: United States, 2017–2018";
  footnote "Estimates for age group 18 and over are age adjusted by the direct method to the U.S. Census 2000 population using age groups 18–39, 40–59, and 60 and over.";
run; 

proc print data=HTNp_KG2 (where=(tableno=2 and race_et4 in (1,2,4))) noobs label;
  var riagendr race_et4 nsum percent sepercent;
  label race_et4="Race and Hispanic origin";
  title "Data table for Figure 2. Age-adjusted prevalence of hypertension among adults aged 18 and over, by sex and race and Hispanic origin: United States, 2017–2018";
  footnote "All estimates are age adjusted by the direct method to the U.S. Census 2000 population using age groups 18–39, 40–59, and 60 and over.";
run; 

proc print data=HTNp_KG2 (where=(tableno=3 )) noobs label;
  var riagendr educ nsum percent sepercent;  
  title "Data table for Figure 3. Age-adjusted prevalence of hypertension among adults aged 18 and over, by sex and education: United States, 2017–2018";
  footnote "All estimates are age adjusted by the direct method to the U.S. Census 2000 population using age groups 18–39, 40–59, and 60 and over.";
run; 

title;
footnote;

*********************************************************************************;
*T-TESTS;
*tests between sexes;
**********************************************************************************;
title "Figure 1: Pairwise t tests for unadjusted prevalence of hypertension, by age and sex, adults 18 years and older, US, 2017-2018";

proc descript data=hyper_1718 filetype=sas nomarg;
* Nest statement: PSUs nested within Strata accounts for the design effects*;
nest sdmvstra sdmvpsu;
* Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
weight wtmec2yr;
* Subpopx statement: specify the subpopulation of interest (the inclusion criteria*;
subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
* Class statement: specify categorical variable(s)*;
class  sddsrvyr riagendr agecat race_et4 educ /nofreq;
* Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
var  hyper_new;
catlevel 1;
* Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
a one-dimensional distribution is generated for each variable in the class statement.*;
table  agecat;
/* Contrast statement: requests specified t-tests*;*/
contrast riagendr =(-1 1 )/name="contrast Male-Female";
/* Pairwise statement: requests all contrasts*;*/
pairwise riagendr/name="pairwise sex";
print nsum="samsize" percent sepercent T_PCT P_PCT  /style=nchs percentfmt=f8.1;
rformat agecat agecat.;
rformat riagendr sexf.;
rformat race_et4 race4fmt.;
rformat educ educ.;
rformat sddsrvyr s.;
run;

title "Figure 1: Pairwise t tests for age-adjusted prevalence of hypertension, by sex, adults 18 years and older, US, 2017-2018";

proc descript data=hyper_1718 filetype=sas nomarg;
  * Nest statement: PSUs nested within Strata accounts for the design effects*;
  nest sdmvstra sdmvpsu;
  * Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
  weight wtmec2yr;
  * Subpopx statement: specify the subpopulation of interest (the inclusion criteria) *;
  subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
  * Class statement: specify categorical variable(s)*;
  class  riagendr agecat /nofreq;
  * Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
  var  hyper_new;
  catlevel 1;
  * Stdvar statement: specifies the variables used to calculate the standard age proportions*;
  stdvar agecat;
  * Stdwgt statement: specifies the precalculated standard age proportions*;
  stdwgt   &ageShares; 
  * Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
  a one-dimensional distribution is generated for each variable in the class statement.*;
  table  _one_;
  /* Contrast statement: requests specified t-tests*;*/
  contrast riagendr =(-1 1 )/name="contrast Male-Female";
  /* Pairwise statement: requests all contrasts*;*/
  pairwise riagendr/name="pairwise sex";
  print nsum="samsize" percent sepercent T_PCT P_PCT  /style=nchs percentfmt=f8.1;
  rformat agecat agecat.;
  rformat riagendr sexf.;
  rformat race_et4 race4fmt.;
  rformat educ educ.;
  rformat sddsrvyr s.;
run;

*********************************************************************************;
*ANALYSIS OF TRENDS;
**********************************************************************************;
title "Figure 1: Trends by age group for unadjusted prevalence of hypertension, by sex, adults 18 years and older, US, 2017-2018";

proc descript data=hyper_1718 filetype=sas ;
* Nest statement: PSUs nested within Strata accounts for the design effects*;
nest sdmvstra sdmvpsu;
* Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
weight wtmec2yr;
* Subpopx statement: specify the subpopulation of interest (the inclusion criteria*;
subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
* Class statement: specify categorical variable(s)*;
class  sddsrvyr riagendr agecat race_et4 educ /nofreq;
* Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
var  hyper_new;
catlevel 1;
* Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
a one-dimensional distribution is generated.*;
table  riagendr;
* Polynomial statement: requests analysis of linear and quadratic trends*;
polynomial agecat=2/name="Age trends";
print nsum="samsize" percent sepercent T_PCT P_PCT  /style=nchs percentfmt=f8.1;
rformat agecat agecat.;
rformat riagendr sexf.;
rformat race_et4 race4fmt.;
rformat educ educ.;
rformat sddsrvyr s.;
run;

*********************************************************************************;
*T-TESTS;
*tests between race and Hispanic origin;
**********************************************************************************;
title "Figure 2: Pairwise t tests for age-adjusted prevalence of hypertension, by  sex, and race and Hispanic origin, adults 18 years and older, US, 2017-2018";

proc descript data=hyper_1718 filetype=sas notsorted;
* Nest statement: PSUs nested within Strata accounts for the design effects*;
nest sdmvstra sdmvpsu;
* Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
weight wtmec2yr;
* Subpopx statement: specify the subpopulation of interest (the inclusion criteria*;
subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
* Class statement: specify categorical variable(s)*;
class  sddsrvyr riagendr agecat race_et4 educ /nofreq;
* Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
var  hyper_new;
catlevel 1;
* Stdvar statement: specifies the variables used to calculate the standard age proportions*;
stdvar agecat;
* Stdwgt statement: specifies the precalculated standard age proportions*;
stdwgt   &ageShares; 
/*ALTERNATIVE*;
stdwgt   0.4203  0.3572  0.2225; */
* Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
a one-dimensional distribution is generated.*;
table riagendr;
* Contrast statement: requests specified t-tests*;
contrast race_et4 = (-1 1 0 0 0)/ name="NHW v NHB";
contrast race_et4 = (-1 0 0 1 0)/ name="NHW v Hispanic";
contrast race_et4 = (0 -1 0 1 0)/ name="NHB v Hispanic";
* Pairwise statement: requests all contrasts*;
pairwise race_et4/name="pairwise race";
print nsum="samsize" percent sepercent T_PCT P_PCT  /style=nchs percentfmt=f8.1 ;
rformat agecat agecat.;
rformat riagendr sexf.;
rformat race_et4 race4fmt.;
run;

*********************************************************************************;
*T-TESTS;
*tests between sexes;
**********************************************************************************;
title "Figure 3: Pairwise t tests for age-adjusted prevalence of hypertension, by sex and education level, adults 18 years and older, US, 2017-2018";

proc descript data=hyper_1718 filetype=sas notsorted;
* Nest statement: PSUs nested within Strata accounts for the design effects*;
nest sdmvstra sdmvpsu;
* Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
weight wtmec2yr;
* Subpopx statement: specify the subpopulation of interest (the inclusion criteria*;
subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
* Class statement: specify categorical variable(s)*;
class  sddsrvyr riagendr agecat race_et4 educ /nofreq;
* Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
var  hyper_new;
catlevel 1;
* Stdvar statement: specifies the variables used to calculate the standard age proportions*;
stdvar agecat;
* Stdwgt statement: specifies the precalculated standard age proportions*;
stdwgt   &ageShares; 
/*ALTERNATIVE*;
stdwgt   0.4203  0.3572  0.2225; */
* Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
a one-dimensional distribution is generated.*;
table educ;
* Contrast statement: requests specified t-tests*;
contrast riagendr =(-1 1 )/name="contrast Male-Female";
* Pairwise statement: requests all contrasts*;
pairwise riagendr/name="pairwise sex";
print nsum="samsize" percent sepercent T_PCT P_PCT  /style=nchs percentfmt=f8.1 ;
rformat agecat agecat.;
rformat riagendr sexf.;
rformat educ educ.;
run;


*****************************************************************************;
                     *FIGURE 4**;
*****************************************************************************;
Title "Figure 4: Age-adjusted trend in hypertension prevalence among adults aged 18 and over, by sex: United States, 1999–2018";

%let ageShares = 0.4203  0.3572  0.2225;

proc descript data=hyper9918 notsorted atlevel1=1 atlevel2=2 nomarg;
* Nest statement: PSUs nested within Strata accounts for the design effects*;
nest sdmvstra sdmvpsu;
* Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
weight wtmec2yr;
* Subpopx statement: specify the subpopulation of interest (the inclusion criteria*;
subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
* Class statement: specify categorical variable(s)*;
class  sddsrvyr riagendr agecat race_et4/nofreq;
* Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
var hyper_new;
catlevel 1;
* Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
a one-dimensional distribution is generated.*;
tables  sddsrvyr riagendr*sddsrvyr; 
* Stdvar statement: specifies the variables used to calculate the standard age proportions*;
stdvar agecat;
* Stdwgt statement: specifies the precalculated standard age proportions*;
stdwgt   &ageShares;
/*ALTERNATIVE*;
stdwgt   0.4203  0.3572  0.2225;*/ 
print nsum percent sepercent /style=nchs percentfmt=f8.1 sepercentfmt=f8.1 ;
output nsum percent sepercent atlev1 atlev2 /filename=HTNp replace;
rtitle "Age-adjusted trend in hypertension prevalence among adults aged 18 and over, by sex: United States, 1999–2018";
rformat agecat agecat.;
rformat riagendr sexf.;
rformat race_et4 race4fmt.;
rformat hyper_new hyper_new.;
rformat sddsrvyr s.;
run;


*********************************************************************************;
*Analysis of trends;
**********************************************************************************;
Title " Trend test for age-adjusted prevalence of hypertension, adults 18 years and older, US, 1999-2016";

proc descript data=hyper9918 filetype=sas nomarg notsorted;
* Nest statement: PSUs nested within Strata accounts for the design effects*;
nest sdmvstra sdmvpsu;
* Weight statement: specify appropriate weight, accounts for the unequal probability of sampling and non-response.*;
weight wtmec2yr;
* Subpopx statement: specify the subpopulation of interest (the inclusion criteria*;
subpopx ridageyr >=18 and ridexprg ne 1 and (n_sbp ne 0 or n_dbp ne 0);
* Class statement: specify categorical variable(s)*;
class  sddsrvyr riagendr race_et4 agecat/nofreq ;
* Var statement: specify the analysis variable(s),and the level(s) of the analysis variable(s)*;
var  hyper_new; 
catlevel 1;
* Table(s) statement: specifies cross-tabulations for which estimates are requested. If a table statement is not present, 
a one-dimensional distribution is generated.*;
table _one_ riagendr;
* Stdvar statement: specifies the variables used to calculate the standard age proportions*;
stdvar agecat;
* Stdwgt statement: specifies the precalculated standard age proportions*;
stdwgt   &ageShares; 
/*ALTERNATIVE*;
stdwgt   0.4203  0.3572  0.2225;*/ 
* Poly statement: requests analysis of linear and quadratic trends*;
poly sddsrvyr=2 / name="HTN trend";
print nsum="samsize" percent sepercent T_PCT P_PCT  /style=nchs percentfmt=f8.1 ;
rformat agecat agecat.;
rformat riagendr sexf.;
rformat hyper_new hyper_new.;
run;