data demo4_nh3;

Use the data and set statements to refer to your analytic dataset.

if hfa8r>=0 then do;

      if hfa8r<12 then HIGHSCHL=1;

      else if hfa8r=12 then HIGHSCHL=2;

      else if hfa8r>12 then HIGHSCHL=3;

Use the if, then, and else statements to create a simple high school education categorical variable (HIGHSCHL) from a complex categorical education variable.

if (20 <= hsageir <= 39) and hsageu=2 then age3cat=1;

Use the if, then, and else statements statement to create an age categorical variable (age3cat) from a continuous variable.

      n_sbp = n(of pep6g1 pep6h1 pep6i1);
      n_dbp = n(of pep6g3 pep6h3 pep6i3);
      *Setting DBP values of 0 as missing for calculating average;
      array _DBP pep6g3 pep6h3 pep6i3;
      do over _DBP;
      if (_DBP = 0) then _DBP = .;
      end; 

Use these function statements to count the number of systolic and diastolic blood pressure readings. Then use the array statement (where _DBP is the name of the array) to set any diastolic blood pressure readings of "0" to missing, so that a reading of "0" does not affect the blood pressure means.

mean_sbp = mean(of pep6g1 pep6h1 pep6i1);

Use these function statements to calculate mean systolic and diastolic blood pressures.

  if n_sbp>0 and n_dbp>0 then do;
  if mean_sbp>=140 then SBP140=1;
  else SBP140=0;
  if mean_dbp>=90 then DBP90=1;
  else DBP90=0;
  end;
 if HTNMED>=0 and SBP140>=0 and DBP90>=0 then do;
 if HTNMED=1 or SBP140=1 or DBP90=1 then HBP=1;
 else HBP=0;
 end;

Use the if, then, and else statements to define a new variable, hbp (high blood pressure = 1 or 0), based on a series of conditions that indicate hypertension from the questionnaire and examination variables.

  end;
run;

Use the if, then, and else statements to define a new variable, hlp (hyperlipidemia = 1 or 0), based on a series of conditions that indicate high lipid levels from the questionnaire and examination variables.

proc freq data=demo4_nh3;
where hsageu=2 and hsageir>=20 and dmpstat=2;
      table HTNMED*hae2*hae5a

 HBP*HTNMED*SBP140*DBP90/list missing;
      table CHOLMED*hae7*hae9d HLP*CHOLMED*HLP_lab/list missing;
      title 'Check regroup/recode/definitions categorical variables';

Use the proc freq procedure to create a cross tabulation of the original categorical variables for high blood pressure and hyperlipidemia by their respective recoded variables. Use the where statement to select the participants who were age 20 years and older and who had both the home interview and the MEC exam.

proc means data=demo4_nh3 N min max;
where hsageu=2 and hsageir>=20 and dmpstat=2;
      var hsageir;
      class age3cat;
      title 'Check if each age category is in the corrected age range';

proc means data=demo4_nh3 N min max;
where hsageu=2 and hsageir>=20 and dmpstat=2;
      var mean_DBP;
      class DBP90;
      title 'Check if DBP >=90 is defined correctly';

proc means data=demo4_nh3 N min max;
where hsageu=2 and hsageir>=20 and dmpstat=2;
      var tcp;
      class HLP_lab;
      title 'Check if TC>=240 is defined correctly';

Use the proc means procedure to calculate the mean, minimum, and maximum values for the original continuous variables. Use the where statement to select the participants who were age 20 years and older and who had both the home interview and the MEC exam. The class statement will separate the original continuous variable into categories of the derived variables. This is done to check that coding of the derived variable, based on cut-off points of the continuous variable, is correct.