Public Health Disparities Geocoding Monograph (2004)

The Public Health Geocoding Monograph (2004) is part of the Public Health Disparities Geocoding Project, which provides free, accessible resources to use geocoding and area-based social metrics (ABSMs) to improve monitoring of and action to address health inequities.

The Public Health Disparities Geocoding Monograph (2004) introduces geocoding and using area-based socioeconomic measures with public health surveillance data. It includes a “how to” section as well as in-depth information about the census tract poverty level.

Contents of the monograph

Executive Summary

The executive summary describes the motivation behind the Public Health Disparities Geocoding Project, and summarizes the methodology, key findings, and recommendations.

Introduction

The introduction provides a more in-depth look at the history of geocoding and area-based measures, the objectives of our project, and our main findings. We include a glimpse of what routine public health surveillance of socioeconomic disparities in health could look like if conducted over a variety of health outcomes over the lifecourse, from birth to death, using a single area-based socioeconomic measure at the census tract level.

Publications Page

The publications page is a comprehensive list of the publications of the Public Health Disparities Geocoding Project, and includes pdf copies of all of our published work.

Geocoding primer

We provide a primer on the basics of geocoding, including descriptions of the many options and services available, and the nitty-gritty details of address cleaning, address formatting, and evaluation of geocoding accuracy.

Generating ABSMs

In generating ABSMs we describe the concepts, methods, and measures behind creating area-based socioeconomic measures, including a summary table of the 19 theoretically justified area-based socioeconomic measures we created based on 1990 U.S. Census data (see ABSM Creation Table).

Analytic Methods

In the section on analytic methods, we provide details on how to merge geocoded surveillance data with Census derived population denominators and area-based socioeconomic measures. We also present basic epidemiologic methods for generating descriptive statistics, including directly age-standardized incidence rates, incidence rate ratios and rate differences, the relative index of inequality, and population attributable fraction. Examples are provided for each of these techniques, and each section is further detailed in our comprehensive Case Example.

Multi-level modeling

The section on multi-level modeling provides guidance on why and how to use this analytic approach.

Visual display of data

The section on visual display of data focuses on issues relevant to surveillance reporting, including for health inequities.

Case example

The case example provides an opportunity for programmers and data managers to try out the techniques we describe on a test dataset, drawn from all-cause mortality cases in Suffolk County, MA, from 1989 to 1991. We provide test datasets, a step-by-step description of the programming tasks, sample SAS code, and examples of the resulting output.

Data resource – US Census Tract Level Poverty Data (1980, 1990, 2000)

Finally, to facilitate further research on socioeconomic gradients in health with respect to our recommended area-based socioeconomic measure (CT poverty), we have made available Census Tract Level Poverty Data for ALL census tracts in the United States, for 1980, 1990, and 2000.