1. 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
2
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.
3. 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 |
||
|
Age |
No. of employees |
Rate for country |
|
35-44 |
8000 |
0.5 / 1000 |
|
44-54 |
2000 |
4 / 1000 |
|
55-64 |
2000 |
9 / 1000 |
4. 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.
5. Source: Ahlbom & Norell, 1990. 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.
6. 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