The Public Health Disparities Geocoding Project Monograph Geocoding and Monitoring US Socioeconomic Inequalities in Health: An introduction to using area-based socioeconomic measures
 WHY? READ MORE HOW TO TRY IT OUT! TOOLS Executive Summary Introduction Publications Geocoding Generating ABSMs Analytic Methods Multi-level Modeling Visual Display Case Example U.S. Census Tract Poverty Data
 STEP BY STEP COMPARISON A step by step comparison of each task of the Case Example, the relevant section of Analytic Methods, and sample SAS code (click here for a pdf version of all 8 steps) Step by Step 1 Step by Step 2 Step by Step 3 Step by Step 4 Step by Step 5 Step by Step 6 Step by Step 7 Step by Step 8
 Step 1: Aggregate the numerator data. CASE EXAMPLE ANALYTIC METHODS SAS PROGRAMMING click here to download SAS program The file rawcase.csv is a comma delimited file containing all deaths occurring in Suffolk County, Massachusetts, between 1989 and 1992. Each person who died is represented by one line in the data file. The variable “AGE” gives the age at death. The variable “AREAKEY” is the geocode to the census tract level. Data from public health databases are typically formatted such that each record represents one person (or case report). Once these data have been geocoded, they need to be aggregated before linking to denominator and ABSM data. Before aggregating, however, one should exclude all records that are not geocoded, do not meet the case definition, or are missing data on the important covariates (e.g. age, in the case of simple age-standardized analyses; age, sex, and race/ethnicity in the case of more complex stratified analyses). One can think of the basic unit of aggregation as a cell, defined by age and other covariates, within an area/geocode. Once aggregated, this cell within an area can be linked to a relevant population denominator. The cell contains a count of all cases within that area that meet the specified age and other covariate criteria. Since our goal is eventually to create rates, we call this count of cases the “numerator.” PROC IMPORT OUT= rawcase DATAFILE= "G:\monograph\example\rawcase.csv" DBMS=CSV REPLACE; GETNAMES=YES; DATAROW=2; RUN; DATA Step1a ; SET rawcase ; IF 0<=AGE<15 THEN AGECAT=1 ; IF 15<=AGE<25 THEN AGECAT=2 ; IF 25<=AGE<45 THEN AGECAT=3 ; IF 45<=AGE<65 THEN AGECAT=4 ; IF AGE>=65 THEN AGECAT=5 ; RUN ; PROC FREQ DATA=Step1a NOPRINT ; TABLES AREAKEY*AGECAT /OUT=Step1b ; RUN ;