Epidemiology — MCQs

Epidemiology Indian Medical PG Practice Questions and MCQs

Question 1711: In a class of 100 students, 40 are susceptible to chickenpox. If 28 students developed chickenpox within the next 2 weeks, what is the secondary attack rate (SAR) of chickenpox?

A. 60%
B. 90%
C. 80%
D. 70% (Correct Answer)

Explanation: **70% - Correct Answer** The **secondary attack rate (SAR)** measures the spread of disease among susceptible contacts after exposure to a primary case. It is calculated as: **SAR = (Number of new cases among susceptible contacts / Total number of susceptible contacts) × 100%** In this scenario: - New cases = 28 students - Susceptible contacts = 40 students - SAR = (28/40) × 100% = **70%** This is the correct application of the SAR formula, using only susceptible individuals as the denominator (not the total class of 100). *60% - Incorrect* - This would require 24 out of 40 susceptible students developing chickenpox (24/40 = 0.60) - Does not match the observed 28 cases *80% - Incorrect* - This would require 32 out of 40 susceptible students developing chickenpox (32/40 = 0.80) - Overestimates the number of cases compared to the observed 28 *90% - Incorrect* - This would require 36 out of 40 susceptible students developing chickenpox (36/40 = 0.90) - Significantly overestimates the attack rate and does not reflect the actual 28 cases observed

Question 1712: Which of the following statements is true regarding the iceberg of disease?

A. The tip of the iceberg represents the clinical cases. (Correct Answer)
B. Screening is primarily done for the tip of the iceberg.
C. Hypertension is a classical example of the iceberg of disease.
D. The clinician is primarily concerned with the hidden portion of the iceberg.

Explanation: ***The tip of the iceberg represents the clinical cases.*** - The **"iceberg phenomenon"** in epidemiology illustrates that only a small proportion of a disease's true burden (the "tip") is outwardly visible or clinically apparent. - These visible cases are the ones that present to healthcare facilities or are **diagnosed clinically**. - This is a **fundamental definition** of the iceberg concept and is universally true. *Screening is primarily done for the tip of the iceberg.* - **Screening programs** are primarily designed to detect the **"submerged portion"** (unapparent, preclinical, or undiagnosed cases) of the iceberg, not the already clinically evident "tip." - The goal of screening is **early detection** to prevent progression or reduce morbidity and mortality. - This statement is **incorrect** as it reverses the actual purpose of screening. *Hypertension is a classical example of the iceberg of disease.* - While hypertension is indeed **a good example** of the iceberg phenomenon with significant undiagnosed burden, the statement uses definite article "**a classical example**" rather than "**the only example**." - The iceberg concept applies to **many diseases** including both communicable (TB, polio, hepatitis) and non-communicable diseases (hypertension, diabetes, cancers). - This is **a valid example but not a defining characteristic** of the iceberg phenomenon itself, making Option A a more fundamentally correct statement about the concept. *The clinician is primarily concerned with the hidden portion of the iceberg.* - A **clinician's primary role** is to diagnose and treat patients who present with **clinical symptoms** (the "tip of the iceberg"). - **Public health professionals** and epidemiologists are more concerned with understanding and addressing the "hidden portion" through surveillance, screening, and prevention strategies. - This statement **reverses the actual roles** and is therefore incorrect.

Question 1713: Which of the following statements is true about cohort studies?

A. A study that follows participants over time to observe outcomes but does not measure incidence.
B. A study that describes characteristics of a population.
C. A study that can determine cause and effect.
D. A study that measures the incidence of a disease. (Correct Answer)

Explanation: ***A study that measures the incidence of a disease.*** - Cohort studies are **prospective studies** that follow a defined group of individuals over time to observe the development of diseases or health outcomes [1]. - By following an at-risk population and documenting new cases, they can directly calculate the **incidence rate** of a disease [1]. - This is the **primary strength** of cohort studies - they provide the best epidemiological evidence for disease incidence. *A study that describes characteristics of a population.* - This describes **descriptive studies** or **cross-sectional surveys**, which characterize a population at a single point in time. - While cohort studies may initially describe baseline characteristics, their primary purpose is to observe disease occurrence over time, not just description. *A study that follows participants over time to observe outcomes but does not measure incidence.* - This is **contradictory** - the act of following participants over time and observing new disease cases IS the measurement of incidence [1]. - Incidence (new cases per unit of person-time) is precisely what cohort studies are designed to measure. *A study that can determine cause and effect.* - While cohort studies establish **temporal relationships** (exposure precedes outcome) and provide strong evidence for causality, the word "determine" is too absolute. - Establishing definitive causation requires **multiple lines of evidence**, including criteria like biological plausibility, dose-response relationships, and consistency across studies. - **Randomized controlled trials** provide stronger causal evidence due to randomization eliminating confounding.

Question 1714: What is the prevalence of Rheumatic Heart Disease (RHD) in India in the 5-15 years age group based on school-based screening studies?

A. 1-2 per 1000
B. 5-7 per 1000 (Correct Answer)
C. 10-12 per 1000
D. 13-15 per 1000

Explanation: ***Correct: 5-7 per 1000*** - School-based screening studies focusing on the 5-15 years age group in India reveal a prevalence of **rheumatic heart disease (RHD)** ranging from **5 to 7 per 1000** children. - This prevalence highlights the significant public health burden of RHD within this vulnerable age demographic in India. - Multiple echocardiographic screening studies across different regions of India consistently report this range as the average prevalence. *Incorrect: 1-2 per 1000* - This range is generally considered too low for the true prevalence of RHD in school-aged children in India, as documented by multiple studies. - It might represent prevalence rates in regions with very strong primary prevention programs or different demographic groups. - Underestimates the actual disease burden in the Indian context. *Incorrect: 10-12 per 1000* - While higher than the actual average, this range is typically considered an overestimate for the general prevalence of RHD in this age group from school-based screenings in India. - Such high numbers might be seen in extremely high-risk or specific endemic areas but do not represent the national average. *Incorrect: 13-15 per 1000* - This range is significantly higher than the reported average prevalence of RHD in school-based screening studies in India. - This would indicate an alarmingly widespread and uncontrolled incidence of RHD, which is not supported by current epidemiological data. - May represent historical data from decades ago or specific high-risk pockets rather than current national estimates.

Question 1715: In the context of epidemiology, standardization is most important for which of the following distributions?

A. Sex distribution
B. Age distribution (Correct Answer)
C. Disease distribution
D. None of the options

Explanation: ***Age distribution*** - **Standardization** (e.g., age adjustment) is crucial when comparing health outcomes or disease rates between populations with different **age structures**. - This method removes the confounding effect of age, allowing for a more accurate comparison of underlying risk factors or disease incidence. *Sex distribution* - While sex can influence disease prevalence, its distribution is generally less variable and confounding than age when comparing populations, making standardization for sex less universally critical than for age. - Differences in sex distribution can still be accounted for, but often through direct stratification rather than complex standardization methods. *Disease distribution* - **Disease distribution** itself is what we often aim to measure and compare, rather than a characteristic necessitating standardization to understand other variables. - Standardization techniques are applied to demographic features (like age or sex) to understand their impact on disease distribution, not to the disease distribution itself. *None of the options* - This option is incorrect because **age distribution** is a primary factor where standardization is essential in epidemiology to ensure valid comparisons. - Ignoring age differences when comparing populations can lead to misleading conclusions about disease risk or health statuses.

Question 1716: What is the primary difference between descriptive and analytic studies in epidemiology?

A. Analytic studies test hypotheses about relationships between health outcomes and exposures.
B. Descriptive studies are always retrospective while analytic studies are prospective.
C. Descriptive studies describe the distribution of health outcomes in a population.
D. Descriptive studies do not test hypotheses but generate them. (Correct Answer)

Explanation: ***Descriptive studies do not test hypotheses but generate them*** - **Descriptive epidemiology** focuses on identifying patterns, trends, and frequencies of health events, often summarized by person, place, and time. - While they do not formally test hypotheses, they are crucial for **generating new hypotheses** that can then be investigated by analytic studies. - This is the **primary and fundamental difference** between descriptive and analytic approaches in epidemiology. *Analytic studies test hypotheses about relationships between health outcomes and exposures* - This statement accurately describes analytic studies, which formally test hypotheses. - However, it only describes one side (analytic) without contrasting it with the key feature of descriptive studies. - It doesn't capture the **primary difference** by showing both sides of the distinction. *Descriptive studies are always retrospective while analytic studies are prospective* - This is **incorrect** - both descriptive and analytic studies can be either retrospective or prospective. - For example, **cohort studies** (analytic) can be retrospective, and **cross-sectional surveys** (descriptive) can be prospective. - Study design timing is independent of whether a study is descriptive or analytic. *Descriptive studies describe the distribution of health outcomes in a population* - This is a correct characteristic of descriptive studies, as they quantify health events by **person, place, and time**. - While true, it only describes what descriptive studies do, without addressing the fundamental difference of **hypothesis generation vs. hypothesis testing**.

Question 1717: What is the expected effect on incidence [I] and prevalence [P] when an effective treatment for a disease is introduced in a community?

A. No change in P & I
B. Both P & I will decrease
C. P will decrease & I will increase
D. P will decrease & I will remain the same (Correct Answer)

Explanation: ***P will decrease & I will remain the same*** - An effective treatment reduces the **duration of disease** by curing existing cases faster, which directly decreases **prevalence** (P = Incidence × Duration) - **Incidence** measures the rate of *new cases* occurring, which is unaffected by treatment of existing cases, so **incidence remains unchanged** - This is the fundamental epidemiological principle for treatment interventions *No change in P & I* - Incorrect because effective treatment shortens disease duration, which must reduce the number of existing cases at any given time - **Prevalence** will definitely decrease when cases recover faster *Both P & I will decrease* - While treatment correctly decreases **prevalence** by shortening disease duration, it does not prevent *new infections* from occurring - **Incidence** (new case rate) remains unchanged unless there's a preventive intervention like vaccination or behavioral change *P will decrease & I will increase* - Correctly identifies that **prevalence** decreases with effective treatment - However, there's no mechanism by which treatment would increase **incidence** of new cases - Treatment affects existing patients, not the rate of new infections

Question 1718: Which of the following statements is not true regarding the International Classification of Diseases?

A. It is revised once in 10 years
B. It was devised by UNICEF (Correct Answer)
C. It is accepted for National and International use
D. The 10th revision consists of 22 major chapters

Explanation: ***It was devised by UNICEF*** **(CORRECT - This statement is FALSE)** - The **International Classification of Diseases (ICD)** was developed and maintained by the **World Health Organization (WHO)**, not UNICEF. - **UNICEF** focuses on children's welfare and health, while **WHO** is the primary international health agency responsible for global health standards. - Since the question asks for the statement that is **NOT TRUE**, this is the correct answer. *It is revised once in 10 years* **(Incorrect - This statement is TRUE)** - The **ICD** is indeed typically revised approximately every **10 years** to incorporate new medical knowledge, diseases, and public health needs. - This regular revision cycle ensures the classification remains relevant and up-to-date with medical advancements and epidemiological trends. *It is accepted for National and International use* **(Incorrect - This statement is TRUE)** - The **ICD** is widely accepted and used globally by countries for **mortality and morbidity statistics**, health management, and reimbursement systems. - Its standardization allows for consistent **data collection** and comparison of health information across different regions and countries. *The 10th revision consists of 22 major chapters* **(Incorrect - This statement is TRUE)** - **ICD-10** (the 10th revision) is structured into **22 chapters**, each covering a specific category of diseases and health problems. - These chapters organize diagnoses logically, facilitating **data coding** and analysis in healthcare.

Question 1719: Which of the following statements about natural experiments is false?

A. Researcher has no control over the allocation of subjects
B. All are correct
C. They utilize naturally occurring events or policy changes to approximate experimental conditions
D. Includes Randomized controlled trials [RCTs] as an example of natural experiments. (Correct Answer)

Explanation: ***Includes Randomized controlled trials [RCTs] as an example of natural experiments*** - This statement is **false** because **Randomized Controlled Trials (RCTs)** are a form of **experimental study design** where researchers actively intervene and randomly assign participants to treatment or control groups. - In contrast, **natural experiments** capitalize on naturally occurring events or policies that create exposure groups without direct researcher intervention. - RCTs are the gold standard for experimental studies, while natural experiments are a type of **observational study** that mimics experimental conditions. *Researcher has no control over the allocation of subjects* - This statement is **true** and accurately describes a key characteristic of **natural experiments**. - The exposure or intervention is determined by nature, policy changes, or external circumstances, not by the researcher. - The lack of researcher control over allocation is what fundamentally differentiates natural experiments from true experimental designs like RCTs. *They utilize naturally occurring events or policy changes to approximate experimental conditions* - This statement is **true** and describes the fundamental principle of natural experiments. - Examples include studying health effects of smoking bans, natural disasters, or policy implementations that create "treatment" and "control" groups naturally. - These studies leverage real-world variations to draw causal inferences. *All are correct* - This statement is **false** because the option "Includes RCTs as an example of natural experiments" is definitively incorrect.

Question 1720: Which measure is considered crucial for formulating a National Health Policy?

A. Measure of association between exposure and outcome (Relative risk)
B. Frequency of new disease cases (Incidence rate)
C. Proportion of cases linked to exposure (Attributable risk) (Correct Answer)
D. Estimate of exposure-outcome odds (Odds ratio)

Explanation: ***Proportion of cases linked to exposure (Attributable risk)*** - **Attributable risk** quantifies the proportion of disease cases in a population that can be attributed to specific **exposures**. - This measure is crucial for health policy as it helps prioritize interventions by identifying diseases and their causative factors that, if eliminated, would lead to the largest reduction in disease burden. *Measure of association between exposure and outcome (Relative risk)* - **Relative risk** indicates the strength of the association between an exposure and an outcome, comparing the risk of disease in exposed versus unexposed groups. - While important for understanding etiology, it doesn't directly quantify the **health burden** in the population that could be prevented by removing the exposure. *Frequency of new disease cases (Incidence rate)* - **Incidence rate** measures the rate at which new cases of a disease occur in a population over a specified period. - While it provides insight into disease spread, it doesn't directly identify how much of that spread is **preventable** by addressing specific risk factors for policy formulation. *Estimate of exposure-outcome odds (Odds ratio)* - The **odds ratio** is an estimate of the likelihood of an outcome occurring given exposure, usually in case-control studies. - Similar to relative risk, it indicates the **strength of association** but doesn't directly translate into the preventable disease burden at a population level.

Practice by Chapter

Principles of Epidemiology

Practice Questions

Measures of Disease Frequency

Practice Questions

Epidemiological Study Designs

Practice Questions

Descriptive Epidemiology

Practice Questions

Analytical Epidemiology

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Experimental Epidemiology

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Screening for Disease

Practice Questions

Surveillance Systems

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Investigation of an Epidemic

Practice Questions

Association and Causation

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Modern Epidemiological Methods

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Critical Appraisal of Epidemiological Studies

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