The Public Health Disparities
Geocoding Project Monograph

Geocoding and Monitoring US Socioeconomic Inequalities in Health:
An introduction to using area-based socioeconomic measures
WHY?
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HOW TO
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TOOLS
Executive Summary
Introduction
Publications
Geocoding
Generating ABSMs
Analytic Methods
Multi-level Modeling
Visual Display
Case Example
U.S. Census Tract Poverty Data

Glossary

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 4:
Now merge the combined numerator and denominator data from Step 3 with the ABSM data, by AREAKEY.
CASE EXAMPLE
ANALYTIC METHODS
SAS PROGRAMMING
click here to download SAS program
The file rawabsm.csv is a comma-delimited file containing the 189 census tracts in Suffolk County, and the % of persons living below poverty for each tract, categorized into 4 categories (1=0-4.9%, 2=5-9.9%, 3=10-19.9%, 4=20-100%). Next, in order to generate rates for categories of a specific ABSM, it is necessary to aggregate OVER areas into strata defined by AGECAT and ABSM. Numerators and denominators from census tracts with missing ABSM data for a particular ABSM are typically excluded from that analysis.

PROC IMPORT OUT= rawabsm
DATAFILE= "G:\monograph\example\rawabsm.csv"
DBMS=CSV REPLACE;
GETNAMES=YES;
DATAROW=2;
RUN;

PROC SORT DATA=rawabsm ;
BY AREAKEY ;
RUN ;


DATA Step4 ;
MERGE Step3 rawabsm ;
BY AREAKEY ;
RUN ;
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This work was funded by the National Institutes of Health (1RO1HD36865-01) via the National Institute of Child Health & Human Development (NICHD) and the Office of Behavioral & Social Science Research (OBSSR).
Copyright © 2004 by the President and Fellows of Harvard College - The Public Health Disparities Geocoding Project.