7.1 - 7.3 See text pp. 151 - 152.
7.4 Direct age-adjustment, fictitious State. Here are vital statistics for the fictitious state of X for the year 1991.
TABLE. Vital statistics, fictitious State X |
||
Age |
Deaths |
Population |
0 - 4 |
952 |
400,000 |
5 -24 |
640 |
1,000,000 |
25 - 44 |
1040 |
500,000 |
45 - 64 |
2023 |
250,000 |
65 - 74 |
4442 |
200,000 |
75+ |
6887 |
100,000 |
Total |
15,984 |
2,450,000 |
(A) Using a
population multiplier of 100,000, calculate the crude mortality rate for the
state. By comparison, recall that the crude mortality rate for
(B) Calculate
age-specific death rates in fictitious state X. (Use
population multipliers of 100,000 throughout this problem.) Compare
these age-specific rates to
(C) Explain
why the crude rates differ in State X and
(D) Using
the standard million reported in Table 7.3 (p. 145) as the reference population
distribution, adjust state X's death rate using the direct method. How does the
adjusted rate compare to
(E) Why did
7.5 Mortality
in Latkaland, indirect adjustment. The table below reports vital
statistics for Latkaland for the year 1990.
TABLE. Vital statistics, Latkaland, 1990 |
||
Age |
Deaths |
Population |
0 - 4 |
? |
7909 |
5 - 24 |
? |
24,560 |
25 - 44 |
? |
13,764 |
45 - 64 |
? |
6921 |
65 - 74 |
? |
1485 |
75+ |
? |
524 |
Total |
300 |
55,163 |
(A) Calculate
the crude mortality rate in Latkaland. (Note: By comparison,
the crude mortality rate for the US was approximately 860 per 100,000 in 1990.)
(B) Using the vital statistics for the
(C) Determine the total number of expected deaths in Latkaland for all
ages combined.
(D) Calculate the SMR for Latkaland. Interpret this statistic.
7.6 Source: Ahlbom
& Norell, 1990, p. 44, #10 (modified without permission). Among the
male employees in a certain occupational group there were 40 cases of
myocardial infarction in a year. This table shows the number of male employees
according to age and the age-specific incidence rates for the male population
in the country as a whole. Compare the incidence of myocardial infarction in
the occupational group and the general population by calculating the SMR.
Interpret this finding.
Data for 7.6 |
||
Age |
No. of employees |
Rate for country |
35-44 |
8000 |
0.5 / 1000 |
44-54 |
2000 |
4 / 1000 |
55-64 |
2000 |
9 / 1000 |
7.7 Source: Ahlbom
& Norell, 1990, p. 44, #11. In an epidemiologic study, male
vulcanization workers were compared to all working men with regard to the cumulative
incidence of esophageal cancer during a 13-year period. Results are shown in this
table:
|
Vulcanization Workers |
|
Comparison Group |
||
Age |
Cases |
No. |
|
Cases |
No. |
15- 24 |
? |
651 |
|
0 |
337,000 |
25 - 34 |
? |
518 |
|
6 |
431,000 |
35 - 44 |
? |
500 |
|
90 |
522,000 |
45 - 54 |
? |
465 |
|
381 |
507,000 |
55 - 64 |
? |
211 |
|
626 |
367,000 |
Total |
8 |
2345 |
|
1103 |
21,640,000 |
Perform an indirect age adjustment by calculating the SMR. Interpret this finding.
7.8 Source: Ahlbom
& Norell, 1990, p. 43, #9. A group (group A) of 6000 people participated
in a program for prevention of disease. Another group (group B) of 5000 people
did not participate and serve as a reference group. During the course of a year
there were 36 cases of the disease in Group A and 35 cases in group B. Results
are shown in this table according to two age categories:
|
Group A |
|
Group B |
||
Age |
Cases |
P-yrs |
|
Cases |
P-yrs |
Younger |
4 |
2000 |
|
20 |
4000 |
Older |
32 |
4000 |
|
15 |
1000 |
Total |
36 |
6000 |
|
35 |
5000 |
Calculate age-specific rates within the two groups. Then, make a direct age adjustment (standardization) by using equal weights for the two age groups (i.e., w1 = w2 = 0.5) to compare the two groups.
7.9 Source: Ahlbom
& Norell, 1990, p. 45, #12. Random samples of men between the ages of
30 – 69 are taken from the catchment are of two hospitals. The occurrence
of chronic bronchitis was recorded using a validated questionnaire about
current symptoms. Results are shown in this table:
|
Population A |
Population B |
|||
Age |
No. w/ bronchitis |
No. in sample |
|
No. w/ bronchitis |
No. in sample |
30 - 39 |
5 |
1000 |
|
25 |
5000 |
40 - 49 |
20 |
2000 |
|
40 |
3000 |
50 - 59 |
50 |
4000 |
|
20 |
1000 |
60 - 69 |
50 |
3000 |
|
20 |
1000 |
Total |
125 |
10000 |
|
105 |
10000 |
Perform a direct age-adjustment between the two population with equal weights for the different age groups (i.e., w1 = w2 = w3 = w4 = 0.25).
Last update: 03/08/2009