CASE
EXAMPLE (ANSWERS):
Analysis of all cause mortality rates in Suffolk County,
Massachusetts, 1989-1991, by CT poverty strata. |
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|
|
|
| •
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 |
| |
|
