UPSC-CMS 2017 — Community Medicine
36 Previous Year Questions with Answers & Explanations
The appropriate treatment for the baby of a woman who is HBsAg positive but HBeAg negative is
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:
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:
The appropriate statistical test to find out obesity as a significant risk factor for breast cancer is:
In a case control study, confounding factors can be minimized by the following EXCEPT:
Which one of the following is FALSE regarding confounding factor in epidemiological studies ?
Denominator in calculation of case fatality rate is:
An important measure of communicability of a disease is
Which of the following statements is NOT correct regarding case fatality rate?
Farmer's lung is caused by the inhalation of:
UPSC-CMS 2017 - Community Medicine UPSC-CMS Practice Questions and MCQs
Question 1: The appropriate treatment for the baby of a woman who is HBsAg positive but HBeAg negative is
- A. Passive immunisation soon after birth but active immunisation after one year of age
- B. Both active and passive immunisation soon after birth (Correct Answer)
- C. Only active immunisation soon after birth
- D. Only passive immunisation soon after birth
Explanation: **Both active and passive immunisation soon after birth** - **Active immunization** (Hepatitis B vaccine) provides long-term immunity by stimulating the infant's immune system to produce antibodies. - **Passive immunization** (Hepatitis B immune globulin, HBIG) provides immediate, short-term protection through pre-formed antibodies, crucial for preventing infection in the critical perinatal period. *Passive immunisation soon after birth but active immunisation after one year of age* - Delaying active immunization until after one year of age would leave a significant window during which the infant is vulnerable to **Hepatitis B infection** from the mother, as passive immunity is only temporary. - The combination of immediate active and passive immunisation is far more effective at preventing **perinatal transmission**. *Only active immunisation soon after birth* - Active immunization alone may not provide immediate enough protection through antibody development, leaving the infant susceptible to **Hepatitis B infection** during their first few weeks of life when exposure risk is highest. - The onset of protective immunity from the vaccine can take several weeks, which is insufficient for immediate protection against perinatal exposure. *Only passive immunisation soon after birth* - While passive immunisation provides immediate protection, it is only temporary and does not confer long-term immunity against **Hepatitis B**. - Without active immunisation, the infant would eventually lose the passively acquired antibodies and remain vulnerable to future **Hepatitis B exposures**.
Question 2: 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:
- A. 1, 2 and 3
- B. 2 and 3 only
- C. 1 and 2 only
- D. 3 only (Correct Answer)
Explanation: ***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
Question 3: 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:
- A. 1, 2 and 3
- B. 1 and 3 only
- C. 1 and 2 only
- D. 1 only (Correct Answer)
Explanation: ***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.
Question 4: The appropriate statistical test to find out obesity as a significant risk factor for breast cancer is:
- A. Chi-square test (Correct Answer)
- B. Wilcoxon’s signed rank test
- C. Student’s paired ‘t’ test
- D. Student’s unpaired ‘t’ test
Explanation: ***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.
Question 5: In a case control study, confounding factors can be minimized by the following EXCEPT:
- A. Matching of variables such as age and sex
- B. Stratification during analysis
- C. Increasing sample size for cases and controls (Correct Answer)
- D. Randomization during selection
Explanation: ***Increasing sample size for cases and controls*** - While increasing sample size improves the **precision** of an estimate and the statistical power of a study, it does **not** address or minimize **confounding factors**. - Confounding occurs when an extraneous variable distorts the observed association between an exposure and an outcome; a larger sample size might make the confounded association appear more statistically significant, but it **cannot remove the confounding itself**. - This is the method that does NOT minimize confounding. *Matching of variables such as age and sex* - **Matching** involves selecting controls that are similar to cases with respect to known confounding variables (e.g., age, sex, socioeconomic status). - This technique helps ensure that the groups being compared are balanced on these potential confounders, thereby **minimizing their influence** on the observed association. - Commonly used in case-control studies. *Stratification during analysis* - **Stratification** involves analyzing the association between exposure and outcome separately within subgroups (strata) defined by different levels of the confounding variable. - This allows researchers to assess if the association holds true within each stratum and estimate the true association **adjusted for the confounder**. - A standard analytical technique to control confounding. *Randomization during selection* - While **randomization** is primarily used in **randomized controlled trials (RCTs)** to distribute confounding factors equally between groups, **random selection of controls** in case-control studies can help ensure representativeness and minimize selection bias. - Although not the primary method for controlling confounding in case-control studies (where matching and stratification are preferred), random selection can contribute to reducing systematic differences between cases and controls. - This differs from "increasing sample size," which fundamentally cannot address confounding.
Question 6: Which one of the following is FALSE regarding confounding factor in epidemiological studies ?
- A. Source of bias is interpretation
- B. Associated both with exposure and disease
- C. Independent risk factor for disease in question
- D. Distributed equally between study and control groups (Correct Answer)
Explanation: ***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.
Question 7: Denominator in calculation of case fatality rate is:
- A. Total number of cases due to the disease concerned (Correct Answer)
- B. Total number of hospital admissions
- C. Total number of deaths due to all causes
- D. Total number of deaths due to the disease concerned
Explanation: ***Total number of cases due to the disease concerned*** - The **case fatality rate (CFR)** measures the **proportion of deaths** among individuals diagnosed with a specific disease. - The denominator for CFR is defined as the **total number of confirmed cases** of that disease in a given population and time period. - Formula: CFR = (Deaths from disease / Total cases of disease) × 100 *Total number of hospital admissions* - This value represents the total number of individuals admitted to the hospital, which may include patients with various conditions, not just the specific disease of interest. - Using this as the denominator would incorrectly dilute the severity of the disease in question by including individuals not directly affected by it. *Total number of deaths due to all causes* - This figure encompasses all deaths in a population, regardless of cause, and is typically used in calculations like the **crude death rate**. - It does not specifically relate to the severity or outcome of a particular disease and therefore cannot serve as the denominator for case fatality. *Total number of deaths due to the disease concerned* - This value represents the **numerator** in the calculation of the case fatality rate, as it quantifies the number of deaths attributable to the specific disease. - Using it as the denominator would lead to a calculation of 100% if the number of deaths equals the number of cases, which would be incorrect for CFR calculations.
Question 8: An important measure of communicability of a disease is
- A. Secondary attack rate (Correct Answer)
- B. Incidence rate
- C. Prevalence rate
- D. Case fatality rate
Explanation: ***Secondary attack rate*** - The **secondary attack rate** quantifies the probability of infection among **susceptible contacts** of a primary case. - It is a direct measure of the **person-to-person transmissibility** or **communicability** of an infectious disease within a defined population. - Calculated as: (Number of cases among contacts / Total number of susceptible contacts) × 100 *Incidence rate* - The **incidence rate** measures the rate at which **new cases** of a disease occur in a population over a specified period. - While related to disease spread, it does not specifically describe transmission from an existing case to a close contact. *Prevalence rate* - The **prevalence rate** measures the **proportion of individuals** in a population who have a disease at a specific point in time or over a period. - It reflects the burden of existing disease but provides no direct information about how easily the disease spreads from one person to another. *Case fatality rate* - The **case fatality rate** (CFR) indicates the **proportion of individuals** diagnosed with a disease who die from that disease. - It is a measure of the **severity or lethality** of a disease, not its communicability or transmissibility.
Question 9: Which of the following statements is NOT correct regarding case fatality rate?
- A. It is the ratio of deaths to cases expressed as percentage
- B. Very useful indicator for both acute and chronic diseases
- C. Variation can occur for the same disease because of changes in the agent factors
- D. One of the measures related to virulence (Correct Answer)
Explanation: ***One of the measures related to virulence*** - This statement is **incorrect**. The **case fatality rate (CFR)** is a measure of the **severity of a disease** within a specific population of affected individuals, typically related to a specific outbreak or period. - While it reflects disease severity, it is not a direct measure of **virulence**, which describes the pathogen's ability to cause damage to the host and is an intrinsic property of the infectious agent itself. *It is the ratio of deaths to cases expressed as percentage* - This is a **correct definition** of the case fatality rate (CFR), calculated as the number of deaths from a disease divided by the total number of cases of that disease, expressed as a percentage. - It quantifies the proportion of individuals diagnosed with a specific disease who ultimately die from it. *Very useful indicator for both acute and chronic diseases* - This statement is **correct**. The case fatality rate is a valuable indicator for assessing the severity and impact of both **acute diseases** (e.g., infectious outbreaks) and **chronic diseases** (e.g., cancer survival). - It helps in understanding the prognosis and lethality of a condition in affected individuals. *Variation can occur for the same disease because of changes in the agent factors* - This statement is **correct**. Case fatality rates for the same disease can vary significantly due to changes in **agent factors** (e.g., strain virulence, drug resistance), host factors (e.g., age, immune status), and environmental factors (e.g., access to healthcare). - For example, different strains of influenza can have varying case fatality rates due to differences in their inherent pathogenicity.
Question 10: Farmer's lung is caused by the inhalation of:
- A. Cotton fibre dust
- B. Sugarcane dust
- C. Grain dust with actinomycetes (Correct Answer)
- D. Silica dust
Explanation: ***Grain dust with actinomycetes*** - **Farmer's lung** is a type of **hypersensitivity pneumonitis** caused by inhaling dust from moldy hay or other agricultural products contaminated with **thermophilic actinomycetes**. - These bacteria trigger an immune response in the lungs, leading to inflammation and respiratory symptoms. *Cotton fibre dust* - Inhalation of **cotton fiber dust** is associated with **byssinosis**, a different occupational lung disease. - Byssinosis typically presents with chest tightness and shortness of breath, often worse on the first day of the work week. *Sugarcane dust* - Exposure to **sugarcane dust** can lead to **bagassosis**, another form of hypersensitivity pneumonitis. - While similar in mechanism to farmer's lung, the specific antigen is different (from sugarcane rather than moldy hay). *Silica dust* - Inhalation of **silica dust** causes **silicosis**, a chronic, progressive occupational lung disease characterized by pulmonary fibrosis. - Silicosis is common in miners, quarry workers, and others exposed to silica, and it is not a hypersensitivity reaction but a direct fibrotic response.