The Public Health Disparities
Geocoding Project Monograph

Geocoding and Monitoring US Socioeconomic Inequalities in Health:
An introduction to using area-based socioeconomic measures
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Case Example
U.S. Census Tract Poverty Data
Glossary
CASE EXAMPLE (ANSWERS):
Analysis of all cause mortality rates in Suffolk County, Massachusetts, 1989-1991, by CT poverty strata.
• Step 5: For each category of CT poverty,
calculate the age-standardized incidence rate, using the year 2000 standard million.

d. Calculate the age-standardized incidence rate, standardized to the year 2000 standard million, and the corresponding “gamma” confidence intervals for the direct standardized rates.

 
CT poverty
IRst (age standardized rate per 100,000)
95% confidence intervals ("gamma" intervals)
 
0-4.9%
 730
 (680,
783)
5-9.9%
966
(941,
992)
10-19.9%
1014
(987,
1041)
20-100%
1019
(993,
1046)
SAS Output
 
Obs Cindpov IRW LGAM2 UGAM2
1 1 0.007297 .00679633 0.007825
2 2 0.009662 .00940757 0.009922
3 3 0.010140 .00987470 0.010411
4 4 0.010193 .00993398 0.010457
Step 6: Estimate the age-standardized incidence rate difference
and the age-standardized incidence rate ratio [see Analytic Methods section 4]
comparing the age standardized rates in each poverty stratum
to the rate in the least impoverished poverty stratum (0-4.9%).

Calculate the 95% confidence limits on the incidence rate difference and incidence rate ratio. Fill out the table below.

 
CT poverty
IRDrst (age standardized incidence rate difference)
95% confidence intervals
IRrst (age standardized incidence rate ratio)
95% confidence intervals
 
0-4.9%
0
(reference)
1.00
(reference)
5-9.9%
236
(115,
358)
1.32
(1.23,
1.43)
10-19.9%
284
(161,
407)
1.39
(1.29,
1.50)
20-100%
290
(167,
412)
1.40
1.30,
1.50)
SAS Output
 
Obs
Cindpov
IRD
L_IRD
U_IRD
IRR
L_IRR
U_IRR
1
1
0
-.001538594
.001538594
1.00000
0.90593
1.10383
2
2
.002365223
0.001147229
.003583217
1.32413
1.22878
1.42687
3
3
.002843004
0.001614570
.004071438
1.38960
1.28963
1.49732
4
4
.002895946
0.001673817
.004118075
1.39686
1.29671
1.50474
Step 7: Estimate the relative index of inequality (RII) [see Analytic Methods section 5]
for CT level poverty in relation to all cause mortality.

a. Estimate the approximate cumulative distribution function for CT poverty, based on the population denominator for each poverty stratum (summed up over age).

b. Calculate the expected cases in each CT poverty stratum, based on the age-standardized incidence rate.

c. Fit a Poisson log linear model, modeling the expected number of cases as a function of the approximate cumulative distribution of CT poverty, using the population denominator as an offset.

d. Exponentiate the beta term from this model to get the relative index of inequality.

   
RII (relative index of inequality)
95% confidence intervals
 
Estimate
1.15
(1.09,
1.21) 
 
SAS Output
 
Obs Parameter riiest riilo95 riihi95
1 dxpct 1.15024 1.09242 1.21113
• Step 8: Calculate the population attributable fraction [see Analytic Methods section 6]
of all cause mortality due to CT poverty.

a. Starting with the data from Step 4, sum up over AREAKEY into strata defined by AGECAT and CT poverty.

b. Calculate (i) the total cases in each age stratum, over poverty; and (ii) the rate in the reference group of CT poverty.

c. Calculate stratum specific rates, rate ratios, and case fractions.

d. Calculate the age-stratum-specific population attributable fractions.

e. Calculate the grand total of all cases to use in calculating weights for all age strata.

f. Finally, calculate the aggregated population attributable fraction, using the age specific weights based on proportion of cases in each age stratum.

    
Aggregated population attributable fraction
  
Estimate 25.5%
SAS Output
 
Obs AFPAGG
1 0.25479
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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.