In this assignment, you will be working with the Framingham Study data to answer theresearch question, is high blood pressure associated with risk of death? Follow thesteps below. Submit your responses to the questions below, as well as your SAS log, viaCanvas.Complete the following steps.Step 1 (4 points): Import frmgham2.sas7bdat file, examine the meta data and first 10observations of the data file. Subset the dataset to only include observations wherePERIOD=1. Run a PROC FREQ to examine the frequencies of data for Death (DEATH),Incident MI or Stroke (CVD), Sex (SEX), and Anti-Hypertensive Meds (BPMEDS). Run aPROC MEANS to examine data for Age at exam (AGE), systolic blood pressure (SYSBP)and diastolic blood pressure (DIABP).Step 2 (3 points): Create a binary high blood pressure variable wherehigh blood pressure is defined as systolic blood pressure ?130 mm HgOR diastolic blood pressure ?80 mm Hg. Run a PROC FREQ to examine theprevalence of high blood pressure in the sample.Step 3 (4 points): Create a 2×2 table comparing your newly created high blood pressurevariable against the outcome of death and then run a PROC LOGISTIC statement tocompute the unadjusted odds ratio and 95% confidence interval for this relationship.Interpret the odds ratio. Provide a one sentence interpretation of the associationbetween high blood pressure and deth.Step 4 (3 points): Consider the role of Age in the association you tested in Step 3.Determine whether you should consider age as a confounder, effect modifier ormediator in this association. If you determine age to be a confounder, then estimate andpresent age-adjusted odds ratios. If you determine age to be an effect modifier, thenestimate and present age-stratified odds ratios. If you determine age to be a mediator, itshould not be included in your multivariable regression model. Provide 1-2 sentencerationale for your determination as well as a one sentence interpretation of theassociation between high blood pressure and death.
Step 5 (3 points): Consider the role of Sex in the model you tested in Step 3. Determinewhether you should consider sex a confounder, effect modifier or mediator in thisassociation. If you determine sex to be a confounder, then estimate and present sex-adjusted odds ratios. If you determine sex to be an effect modifier, then estimate andpresent sex-stratified odds ratios. If you determine sex to be a mediator, it should not beincluded in your multivariable regression model. Provide 1-2 sentence rationale for yourdetermination as well as a one sentence interpretation of the association between highblood pressure and death.Step 6 (3 points): Consider the role of anti-hypertensive medication use in the model youtested in Step 5. Determine whether anti-hypertensive medication use serves as aconfounder, effect modifier or mediator in this association and present the appropriateanalyses. Provide a 1-2 sentence rationale for your determination as well as a onesentence interpretation of the association between high blood pressure and death.Step 7 (Bonus 5): Re-run your regression models from prior steps but estimate riskratios (and 95% confidence intervals) rather than odds ratios. Describe how the riskratios compare to your previously estimated odds ratios.