UPSC-CMS 2017 - Community Medicine PYQs Practice Questions

Q: Which of the following is/are the measure(s) of dispersion? 1. Mode 2. Median 3. Standard Deviation Select the correct answer using the code given below:

3 only. ***Correct: 3 only*** - **Standard Deviation** is a direct measure of dispersion that quantifies the amount of variation or spread of data values around the mean - It indicates how much individual data points deviate from the average, making it a key statistic for understanding the **spread** within a dataset - Other common measures of dispersion include **range, variance, interquartile range, and coefficient of variation** *Incorrect: 1, 2 and 3* - **Mode** and **Median** are measures of **central tendency**, not dispersion - They describe the center or typical value of a dataset, not the spread or variability - While they provide insight into the data's distribution, they do not quantify how spread out the data points are *Incorrect: 2 and 3 only* - **Median** is a measure of **central tendency** representing the middle value when data is ordered, not a measure of dispersion - Only **Standard Deviation** from this option is a measure of dispersion, making this choice incorrect *Incorrect: 1 and 2 only* - Both **Mode** and **Median** are measures of **central tendency** - Mode indicates the most frequent value and Median represents the middle value - Neither provides information about how **spread out** or dispersed the data points are around the center [Practice more Community Medicine PYQs on OnCourse]

Q: Which among the following is/are the examples of primordial prevention ? 1. Adopting healthy lifestyles from childhood 2. Immunization of infants 3. Screening of cervical cancer Select the correct answer using the code given below:

1 only. ***1 only*** - **Primordial prevention** aims to prevent the emergence of risk factors in the population, typically through establishing conditions that minimize hazards to health. **Adopting healthy lifestyles from childhood** (such as healthy eating habits, regular physical activity, avoiding smoking and alcohol) prevents the development of risk factors for chronic diseases like obesity, hypertension, and diabetes later in life. - This is the classic example of primordial prevention - intervening before risk factors even develop. *1 and 2 only* - While adopting healthy lifestyles is primordial prevention, **immunization of infants** is actually **primary prevention**, not primordial prevention. - **Primary prevention** prevents disease occurrence in susceptible individuals by interventions like immunization, which protects against specific diseases but does not prevent the emergence of risk factors themselves. - The disease agents already exist in the environment; vaccination simply prevents their effect on the individual. *1, 2 and 3* - **Immunization** is **primary prevention** (not primordial), and **screening for cervical cancer** is **secondary prevention** (early detection and treatment of existing disease). - This option incorrectly classifies both immunization and screening as primordial prevention. *1 and 3 only* - **Screening for cervical cancer** is a form of **secondary prevention** as it aims for early detection and prompt treatment of an existing disease or pre-cancerous condition, not the prevention of risk factors. - This option incorrectly includes secondary prevention and excludes statement 2, which while also incorrect as primordial, makes this combination wrong. [Practice more Community Medicine PYQs on OnCourse]

Q: The appropriate statistical test to find out obesity as a significant risk factor for breast cancer is:

Chi-square test. ***Chi-square test*** - The **chi-square test** is used to determine if there is a **significant association** between two **categorical variables**. - In this scenario, both obesity (yes/no) and breast cancer (yes/no) are categorical, making chi-square appropriate to assess if obesity is a risk factor. *Wilcoxon’s signed rank test* - This is a **non-parametric test** used for comparing two related samples or repeated measurements on a single sample, especially when data are not normally distributed. - It is not suitable for assessing the association between two independent categorical variables like obesity and breast cancer. *Student’s paired ‘t’ test* - The **paired t-test** is used to compare the means of two related groups or measurements from the same subject under different conditions (e.g., before and after an intervention). - This test is designed for **continuous data** and would not be appropriate for the categorical variables of obesity and breast cancer. *Student’s unpaired ‘t’ test* - The **unpaired t-test** (also known as independent samples t-test) is used to compare the means of two independent groups for a **continuous outcome variable**. - It is not suitable when both the exposure (obesity) and the outcome (breast cancer) are categorical variables. [Practice more Community Medicine PYQs on OnCourse]

Q: Which one of the following is FALSE regarding confounding factor in epidemiological studies ?

Distributed equally between study and control groups. ***Distributed equally between study and control groups*** - A **confounding factor** is, by definition, **not equally distributed** between study (exposed) and control (unexposed) groups, as this unequal distribution leads to the observed bias. - If a potential confounder were equally distributed, it would not distort the relationship between the exposure and the outcome. *Source of bias is interpretation* - Confounding is a source of **bias in interpretation** because it can create a spurious association or mask a true one between an exposure and an outcome. - It leads to an incorrect conclusion about the causal relationship, even if the data collection itself was accurate. *Associated both with exposure and disease* - For a variable to be a confounder, it must be **associated with the exposure** being studied (e.g., smoking is associated with alcohol consumption). - It must also be an **independent risk factor for the disease** outcome (e.g., alcohol consumption is an independent risk factor for esophageal cancer). *Independent risk factor for disease in question* - A confounder must be an **independent risk factor** for the disease outcome, separate from its association with the primary exposure. - This means it influences the disease risk regardless of the exposure being investigated. [Practice more Community Medicine PYQs on OnCourse]

Question 1

Which of the following is/are the measure(s) of dispersion?

1. Mode

2. Median

3. Standard Deviation
Select the correct answer using the code given below:

Accepted Answer

3 only

Answer

1, 2 and 3

Answer

2 and 3 only

Answer

1 and 2 only

Question 2

Which among the following is/are the examples of primordial prevention ?

1. Adopting healthy lifestyles from childhood
2. Immunization of infants
3. Screening of cervical cancer

Select the correct answer using the code given below:

Accepted Answer

1 only

Answer

1, 2 and 3

Answer

1 and 3 only

Answer

1 and 2 only

Question 3

The appropriate statistical test to find out obesity as a significant risk factor for breast cancer is:

Accepted Answer

Chi-square test

Answer

Wilcoxon’s signed rank test

Answer

Student’s paired ‘t’ test

Answer

Student’s unpaired ‘t’ test

Question 4

In a case control study, confounding factors can be minimized by the following EXCEPT:

Accepted Answer

Increasing sample size for cases and controls

Answer

Matching of variables such as age and sex

Answer

Stratification during analysis

Answer

Randomization during selection

Question 5

Which one of the following is FALSE regarding confounding factor in epidemiological studies ?

Accepted Answer

Distributed equally between study and control groups

Answer

Source of bias is interpretation

Answer

Associated both with exposure and disease

Answer

Independent risk factor for disease in question

Question 6

Denominator in calculation of case fatality rate is:

Accepted Answer

Total number of cases due to the disease concerned

Answer

Total number of hospital admissions

Answer

Total number of deaths due to all causes

Answer

Total number of deaths due to the disease concerned

Question 7

An important measure of communicability of a disease is

Accepted Answer

Secondary attack rate

Answer

Incidence rate

Answer

Prevalence rate

Answer

Case fatality rate

Question 8

Which of the following statements is NOT correct regarding case fatality rate?

Accepted Answer

One of the measures related to virulence

Answer

It is the ratio of deaths to cases expressed as percentage

Answer

Very useful indicator for both acute and chronic diseases

Answer

Variation can occur for the same disease because of changes in the agent factors

Question 9

Farmer's lung is caused by the inhalation of:

Accepted Answer

Grain dust with actinomycetes

Answer

Cotton fibre dust

Answer

Sugarcane dust

Answer

Silica dust

Question 10

Suraksha Clinics are conducted under the aegis of which National Health Programme?

Accepted Answer

Reproductive and Child Health Programme

Answer

Iodine Deficiency Disorders Programme

Answer

National AIDS Control Programme

Answer

Revised National Tuberculosis Control programme

UPSC-CMS 2017 — Community Medicine