Epidemiology: Principles and Practices

This document covers the principles and practices of epidemiology. It includes calculations of incidence rates, age-specific incidence rates, and standardized incidence rates. It also discusses prevalence and incidence measurements, observational studies, and WHO health statistical profiles for Australia, India, and Zimbabwe.

Running head: EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
Name of the Student
Name of the University
Author’s Note:

1EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
Question 1 (a):
City A:
Crude incidence rate per 100,000 men = (650/600,000) X 100,000 = 108.33
Incidence rate per 100,000 men for the age group of 0 – 44,
= (50/500,000) X 100,000 = 10
Incidence rate per 100,000 men for the age group of 45 – 64,
= (250/75,000) X 100,000 = 333.33
Incidence rate per 100,000 men for the age group of 65+,
= (350/25,000) X 100,000 = 1400
City B:
Crude incidence rate per 100,000 men = (3580/2,500,000) X 100,000 = 143.2
Incidence rate per 100,000 men for the age group of 0 – 44,
= (80/1,500,000) X 100,000 = 5.33
Incidence rate per 100,000 men for the age group of 45 – 64,
= (1000/600,000) X 100,000 = 166.67
Incidence rate per 100,000 men for the age group of 65+,
= (2500/400,000) X 100,000 = 625
Comparison of crude and age specific incidence rates of City A and B are provided in the
Table below:

2EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
Table 1.1 Crude and age specific incidence rates of City A and B
Incidence Rate City A City B
0-44 age group 10 5.33
45-64 age group 333.33 166.67
65+ age group 1400 625
Crude 108.33 143.2
From the above table, it can be observed that the age-specific incidence rates are higher in
case of City A in comparison with City B. On the contrary, the crude incidence rate is higher
in case of City B in comparison with City A. This reason behind this incident is that the City
B has higher number of older population which might have affected the overall crude
incidence rate.
Question 1 (b):
The age structures of the two cities are unequal. City B have a higher percentage (16%) of
people who belongs to the age group 65+ in comparison with City A. City A have only
4.16% people who belong to the same category. Similarly, City A has higher percentage of
people (83.33%) that belongs to the age group 0 – 44 years in comparison with City B. City B
have 60% people who belong to the same category. This disparity is noticeable between the
two cities in the age group of 45 – 64 years as well. Hence, the age structure of these two city
are unequal. Due to this unequal distribution, the comparison result of the two cities will be
distorted and the comparison of crude results will not be valid. The higher crude incidence
rate of City B might be because City B has higher percentage older population.
Question 1 (c):
Direct standardized incidence rate for City A:

3EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
Observed cases in City A = 650
Expected cases in City A with respect to standard population = (650/600,000) X 100,000 =
108.33
Hence, Standardized Incidence rate = (650/108.33) X 100 = 600.01
Direct standardized incidence rate for City B:
Observed cases in City B = 3580
Expected cases in City B with respect to standard population = (3580/2,500,000) X 100,000 =
143.2
Hence, Standardized Incidence rate = (3580/143.2) X 100 = 2500
From the above data, it can be seen that the Standardized Incidence Rate (SIR) is higher with
respect to Crude Incidence Rate for both the City A and City B. Therefore, it can be
concluded that the occurrence of prostate cancer in these two towns are much higher than the
expected incidence.
Question 1 (d):
Percentage of affected individual in each age group is provided for both the city in the below
table:
Table 1.2Percentage of affected individual in each age group is provided for City A and City
B
Percentage of people affected by prostate cancer
Age Group City A City B
0 – 44 0.01 % 0.005 %
45 – 64 0.33 % 0.17 %
65 + 1.4 % 0.625 %

4EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
From the above the table, it is clear the percentage of affected people rapidly increased with
the increase of age in the population. In case of City A, the percentage of affected individual
increased more than 100 times (140) from the age group of 0 – 44 to 65 and above. Similar
trend can be noticed in case of City B. In this case, the increase is 125 times. Hence, the
occurrence of cancer increases with the age. Therefore, it can be concluded that the age is a
risk factor for prostate cancer for both cities.
Question 2 (a):
In the year 2000, the risk population was = 5,458 women
Cases of cervical cancer = 92 women
Therefore, the prevalence for the year 2000 is = (92/5458) X 100 = 1.68 %
In the year 2000, the risk population was = 5,366women
Cases of cervical cancer = 60 women
Therefore, the prevalence for the year 2005 is = (60/5366) X 100 = 1.12 %
Question 2 (b):
Number of total population at risk = 5,458 women
Cases of CIN = (92+60) = 152
Therefore, incidence of cervical cancer in these women = (152/5458) X 100 = 2.78%
The above measure of incidence is a ‘cumulative incidence measurement’ as it considered the
total number incident during a particular period of time and does not take into account when
the incidents occurred (Dobler, 2017).

5EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
Question 2 (c):
Number of risk population = 60
Period duration = 5 year
Time of onset = 3 year; therefore disease free year = 2
Hence, Incidence rate of these women is = (60/120) person-year = 0.5 /person- year.
Question 3 (a):
The exposure factor for this study is the use of inhaled corticosteroids.
Question 3 (b):
The outcome of this study is that the subcapsular cataracts are 2.6 times more common
among the user of inhaled corticosteroids.
Question 3 (c):
This study is an observational study and has been conducted over a period of two year. Also,
sample population has been divided into two groups: exposed and unexposed. Therefore,
design of this study can be classified as a ‘Cohort Study’ (CASP Checklists, 2019).
Question 3 (d):
The investigators did not consider the fact that the outcome might be interfered with other
substances or medication used by the sample population. They did not take any precaution to
negate the fact.
Question 4 (a):
Table 4.1WHO health statistical profiles for Australia, India and Zimbabwe
Data in 2013 Australia India Zimbabwe
1. Population (thousands) 23343 1252140 14150
2. Number of deaths
(thousands)
150.0 9944.9 138.2
3. Crude mortality (per 100,000) 642.59 794.23 976.68

6EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
4. Population proportion
Under 15 (%) 19 29 40
Over 60 (%) 20 8 6
5. Under 5 mortality rate (per
1000 live births)
4 53 89
6. Maternal mortality ratio(per
100,000 live births)
6 190 470
7. Life expectancy (years), 2012
At birth 83 66 58
At age 60 25 17 18
8. Probability of dying, 2012
(before age 70)
Male 26 % 69% 74%
Female 17% 60% 65%
9. Citation (WHO: Australia,
2015)
(WHO: India,
2015)
(WHO:
Zimbabwe,
2015)
Note: Crude mortality= total number of deaths/ total population
From the above table, it is quite clear that the health condition most advanced and progressive
in Australia, followed by India and Zimbabwe. The data from this table also justifies the
country status of Australia, India and Zimbabwe which are First World, Developing and
Third World country respectively (World Health Organization, 2016). Total population is
highest in case of India and it is much higher than the Australia and Zimbabwe combined.
Amongst the three country, the crude mortality rate per 100,000 population is highest in
Zimbabwe (~977), even though the population in Zimbabwe is lowest among the three
country. The percentage of population over 60 is highest in Australia (20 %) and this signifies
the strength and advancement of Australia’s medical compared to the other two countries.
Not only this, but Australia is stands out in the parameters of under-five and maternity
mortality rate, life expectancy and probability of dying before the age of 70. These data
signifies that the overall development, infrastructure and medical healthcare far more

7EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
advanced and strong compared to India and Zimbabwe. With regard to India and Zimbabwe,
the situation of Zimbabwe is particularly bleak. Zimbabwe has the lowest life expectancy at
birth and highest under-five and maternity mortality rate, and probability of dying before the
age of 70. Maternal mortality rate in Zimbabwe (470) particularly stands out as it is more
than double of the next highest. In a nutshell, it can be concluded that Australia has the best
infrastructure and quality of life followed by India and Zimbabwe. However, India needs to
improve with regard to infrastructure to reach the standard of Australia.

8EPIDEMIOLOGY: PRINCIPLES AND PRACTICES
References:
WHO: Australia (2015). Australia: WHO statistical profile. Retrieved from
https://www.who.int/gho/countries/aus.pdf
CASP Checklists (2019). CASP - Critical Appraisal Skills Programme. Retrieved from
https://casp-uk.net/casp-tools-checklists/
Dobler, C. C. (2017). Cumulative Incidence and Incidence Rate Ratio for Estimation of Risk
of Tuberculosis in Patients With Cancer. Clinical Infectious Diseases, 65(8), 1423-
1423. Doi: https://doi.org/10.1093/cid/cix516
WHO: India. (2015). India: WHO statistical profile. Retrieved from
https://www.who.int/gho/countries/ind.pdf
World Health Organization. (2016). World health statistics 2016: monitoring health for the
SDGs sustainable development goals. World Health Organization. ISBN-10:
9241565268.
WHO: Zimbabwe. (2015). Zimbabwe: WHO statistical profile. Retrieved from
https://www.who.int/gho/countries/zwe.pdf