Epidemiology — MCQs

Which of the following statements is/are true about proportional case rate of malaria? 1. This indicator is used since morbidity rate is difficult to determine 2. This is defined as the number of cases of malaria for every 100 patients seen in hospital OPDs 3. It is a crude index since cases are not related to their time and space distribution Select the correct answer using the code given below:

Epidemiology Indian Medical PG Practice Questions and MCQs

Question 1511: Which one of the following statements is correct regarding diabetes epidemiology?

A. Females are 2.5 times more at risk.
B. Its prevalence is not affected by age.
C. Central obesity is not linked with diabetes.
D. Maternal diabetes increases the risk of subsequent diabetes. (Correct Answer)

Explanation: ***Maternal diabetes increases the risk of subsequent diabetes.*** - Women who develop **gestational diabetes** have a significantly increased risk of developing **type 2 diabetes** later in life, often within 5-10 years postpartum. - This is due to underlying insulin resistance and pancreatic beta-cell dysfunction that becomes evident during pregnancy. *Females are 2.5 times more at risk.* - The prevalence of diabetes typically shows **no significant difference** between genders or is slightly higher in males in some populations. - Gender differences in diabetes risk are generally not that pronounced and vary by type and ethnicity. *Its prevalence is not affected by age.* - The **prevalence of type 2 diabetes significantly increases with age**, particularly after 45 years, due to factors like decreased physical activity, weight gain, and declining pancreatic beta-cell function. - While type 1 diabetes can occur at any age, its incidence also peaks in childhood and adolescence. *Central obesity is not linked with diabetes.* - **Central obesity**, characterized by excess **abdominal fat**, is a strong risk factor for **insulin resistance** and type 2 diabetes. - Visceral fat is metabolically active and releases inflammatory mediators and free fatty acids that impair insulin sensitivity.

Question 1512: Sullivan’s index is an indicator of:

A. Morbidity
B. Disability (Correct Answer)
C. Mortality
D. Health care delivery

Explanation: ***Disability*** - Sullivan's index, also known as **disability-free life expectancy**, is a measure that combines **mortality** and **morbidity** data to estimate the expected years an individual will live without disability. - It's a key indicator of the average number of years a person can expect to live in a **healthy or non-disabled state.** *Morbidity* - While related to morbidity, Sullivan's index specifically measures the **absence of disability**, rather than just the presence of disease or illness. - **Morbidity** refers to the state of being diseased or unhealthy, without necessarily quantifying the impact on daily function. *Mortality* - **Mortality** refers to the death rate or the number of deaths in a population. Sullivan's index uses mortality data in its calculation but is not solely an indicator of mortality. - It combines mortality with information on disability to provide a more nuanced picture of **population health.** *Health care delivery* - **Health care delivery** refers to the organization and provision of medical services. Sullivan's index measures health outcomes and does not directly indicate the quality or efficiency of healthcare delivery systems. - While improved healthcare can influence disability-free life expectancy, the index itself is a **health status measure**, not a healthcare system measure.

Question 1513: With reference to historical cohort study, which of the following statements is not correct?

A. Duration of study is shorter as compared to current cohort study.
B. Control subjects are selected from the current population without exposure. (Correct Answer)
C. Experience of cohort is assessed from existing records.
D. Outcomes have occurred before the start of the investigation.

Explanation: ***Control subjects are selected from the current population without exposure.*** - In a **historical cohort study**, all data, including information on both exposed and unexposed (control) groups, is collected retrospectively from existing records. Control subjects are not usually selected from the current population. - The defining characteristic of a historical cohort is that both exposure and outcome have already occurred and are recorded prior to the study's initiation. *Duration of study is shorter as compared to current cohort study.* - This statement is correct. Because historical cohort studies utilize **pre-existing data** and outcomes have already occurred, the **follow-up period** from the researcher's perspective is significantly compressed compared to a prospective (current) cohort study. - The actual exposure and outcome events may have spanned many years in the past, but the time taken by the researcher to conduct the study is often shorter. *Experience of cohort is assessed from existing records.* - This statement is correct. A hallmark of **historical cohort studies** is their reliance on **retrospective data collection** from existing sources like medical charts, employment records, or birth registries. - Researchers do not actively follow up with individuals but rather consult these documents to track exposure and outcome status. *Outcomes have occurred before the start of the investigation.* - This statement is correct. In a **historical cohort study**, both the defining exposure(s) and the subsequent health outcomes of interest have already transpired by the time the study is initiated. - The investigator looks back in time to identify cohorts based on past exposure and then ascertains their outcomes from records recorded in the past.

Question 1514: Specificity of a test is =

A. (True positives X 100) / (True negatives + False positives) %
B. (True positives X 100) / (True positives + False negatives) %
C. (True negatives X 100) / (True negatives + False positives) % (Correct Answer)
D. (True negatives X 100) / (True positives + True negatives) %

Explanation: ***(True negatives X 100) / (True negatives + False positives) %*** - **Specificity** measures the proportion of **true negatives** correctly identified by the test among all individuals who do not have the disease. - It reflects the test's ability to **correctly identify healthy individuals** and avoid **false positives**. * (True positives X 100) / (True negatives + False positives) %* - This formula is incorrect for specificity, as it uses **true positives** in the numerator which is characteristic of **sensitivity**, not specificity. - The denominator includes true negatives but incorrectly adds **false positives**, which would be appropriate for the total number of individuals without the disease. * (True positives X 100) / (True positives + False negatives) %* - This formula represents the **sensitivity** of a test, not its specificity. - **Sensitivity** measures the proportion of **true positives** correctly identified by the test among all individuals who actually have the disease. * (True negatives X 100) / (True positives + True negatives) %* - This formula incorrectly includes **true positives** in the denominator, which is not relevant for calculating specificity. - The denominator should represent all truly negative cases (true negatives + false positives).

Question 1515: ‘Spot map’ in epidemiological studies refer to variation in the distribution of a disease at:

A. International level
B. Local level (Correct Answer)
C. Rural – urban level
D. National level

Explanation: ***Local level*** - A **spot map** is an epidemiological tool used to visualize the geographical distribution of disease cases within a **small, defined area**, such as a neighborhood or a single city. - It helps in identifying **clusters or hot-spots** of disease occurrence, which can be crucial for locating potential sources of infection or environmental hazards. *International level* - While disease distribution can be mapped internationally, a "spot map" specifically refers to a **finer-grain analysis** at a much smaller geographical scale, not across multiple countries. - Maps at the international level are often used for **global burden of disease** studies or pandemic tracking, which require broader summaries rather than individual case plotting. *Rural – urban level* - Mapping at the rural-urban level indicates differences between these two broad categories, but a spot map provides even more specific detail within those areas. - It shows the precise location of cases, allowing for insights into localized environmental or social factors, rather than just a general rural vs. urban comparison. *National level* - National-level mapping provides an overview of disease prevalence or incidence across an entire country, which is a much larger scale than a spot map. - A spot map is designed to highlight **precise locations** of cases within a more contained geographical area, making it less suitable for broad national-level trends.

Question 1516: Severity of a disease is measured by:

A. Incidence rate
B. Attributable risk
C. Relative risk
D. Case fatality rate (Correct Answer)

Explanation: ***Case fatality rate*** - The **case fatality rate (CFR)** directly measures the **severity** of a disease by indicating the proportion of individuals diagnosed with a disease who ultimately die from it. - A higher CFR implies a more lethal or severe disease. *Incidence rate* - The **incidence rate** measures the **frequency of new cases** of a disease in a population over a specified period. - It reflects how quickly a disease is spreading, not its severity. *Attributable risk* - **Attributable risk (AR)** quantifies the proportion of disease incidence in an exposed group that can be attributed to the exposure. - It measures the **public health impact** of an exposure, not the inherent severity of the disease itself. *Relative risk* - **Relative risk (RR)** compares the probability of an event (e.g., disease development) in an **exposed group** to the probability of the event in an **unexposed group**. - It indicates the **strength of association** between an exposure and a disease, not the severity of the disease in affected individuals.

Question 1517: An outbreak of Viral Hepatitis was reported from a town between June and August of a particular year. 60% of cases occurred in July. Exposure of the community to infection is from:

A. Multiple sources over prolonged periods
B. Multiple sources for a short period
C. A common single source for prolonged periods
D. A single source for a short period (Correct Answer)

Explanation: ***A single source for a short period*** - This describes a **point source outbreak**, the classic pattern seen in this scenario - **60% of cases in July** indicates exposure occurred over a **brief period** (likely days to weeks before July) - The 3-month span (June-August) represents the **distribution of cases around the incubation period** of viral hepatitis (typically 2-6 weeks for Hepatitis A) - Common examples: **contaminated water supply**, food at a community gathering, or other single exposure event - This is the **textbook presentation** of a point source epidemic with a characteristic sharp peak *Multiple sources for a short period* - This would produce **multiple peaks** or an irregular epidemic curve, not a single peak in July - Multiple sources would not create the concentrated 60% clustering observed - The pattern described is too uniform for multiple independent sources *A common single source for prolonged periods* - This describes a **continuous common source outbreak** with an extended epidemic curve - Cases would be **distributed more evenly** across June-August without a sharp peak - Example: ongoing contamination of a water supply over months - The 60% concentration in July rules out this pattern *Multiple sources over prolonged periods* - This would result in **endemic disease** or a very flat, prolonged epidemic curve - No sharp peak would be observed - The temporal clustering contradicts this pattern

Question 1518: Due to which of the following does seasonal trend of a disease occur? 1. Vector variation 2. Environmental factors 3. Change in herd immunity Select the correct answer using the code given below:

A. 1, 2 and 3 (Correct Answer)
B. 2 and 3 only
C. 1 and 3 only
D. 1 only

Explanation: ***1, 2 and 3*** - **Vector variation** (e.g., mosquito populations increasing during warmer months) is a critical factor causing seasonal patterns in vector-borne diseases like malaria, dengue, and Japanese encephalitis. - **Environmental factors** such as temperature, humidity, and rainfall directly affect pathogen survival, vector breeding, transmission efficiency, and host susceptibility, leading to characteristic seasonal patterns (e.g., respiratory infections in winter, diarrheal diseases in summer). - **Changes in herd immunity** can contribute to temporal disease patterns, though this factor more commonly drives long-term cyclical patterns (multi-year cycles) rather than short-term seasonal variations. The accumulation of susceptible individuals (through births) and waning immunity can influence disease occurrence patterns over time. *2 and 3 only* - This option incorrectly excludes **vector variation**, which is a primary determinant of seasonality for many infectious diseases, particularly arthropod-borne infections. - Vector activity shows marked seasonal fluctuations that directly correlate with disease incidence. *1 and 3 only* - This option incorrectly excludes **environmental factors**, which are fundamental drivers of seasonal disease patterns. - Temperature, humidity, precipitation, and other climatic variables directly influence pathogen viability, vector ecology, and human behavioral patterns that affect disease transmission. *1 only* - This option is too restrictive, considering only **vector variation** while neglecting the significant contributions of **environmental factors** and **temporal changes in population immunity** to disease occurrence patterns. - Seasonal trends result from complex interactions among multiple factors.

Question 1519: The pattern of disease in a community described in terms of the important factors which influence its occurrence is known as:

A. Experimental epidemiology
B. Confounding
C. Community diagnosis (Correct Answer)
D. Iceberg phenomenon

Explanation: ***Community diagnosis*** - This term refers to the process of identifying and characterizing the health problems and needs of a **defined population** or community, considering influencing factors. - It involves analyzing health status, risk factors, and available resources to plan effective interventions. *Experimental epidemiology* - This involves conducting **randomized controlled trials** and other intervention studies to test hypotheses about cause-and-effect relationships in disease. - It focuses on evaluating the effectiveness of interventions, rather than describing the entire pattern of disease occurrence. *Confounding* - **Confounding** occurs when a third variable distorts the observed association between an exposure and an outcome. - It is a bias that can mislead conclusions in observational studies, not a description of the disease pattern itself. *Iceberg phenomenon* - The **iceberg phenomenon** illustrates that only a fraction of severe cases of a disease (the "tip of the iceberg") are clinically apparent, while a larger proportion of subclinical or asymptomatic cases remain hidden. - It describes the hidden burden of disease, not the overall pattern or influencing factors.

Question 1520: Which of the following statements is/are true about proportional case rate of malaria? 1. This indicator is used since morbidity rate is difficult to determine 2. This is defined as the number of cases of malaria for every 100 patients seen in hospital OPDs 3. It is a crude index since cases are not related to their time and space distribution Select the correct answer using the code given below:

A. 2 only
B. 3 only
C. 1, 2 and 3 (Correct Answer)
D. 2 and 3 only

Explanation: ***1, 2 and 3*** - All three statements accurately describe the **proportional case rate of malaria** (also known as proportional morbidity). - Statement 1 is correct: This indicator is used because calculating true **morbidity rates** requires accurate population denominator data, which is often difficult to obtain in resource-limited settings. The proportional case rate provides a practical alternative using hospital-based data. - Statement 2 is correct: It is defined as **(Number of malaria cases / Total OPD patients) × 100**, representing malaria cases per 100 patients seen in hospital outpatient departments. - Statement 3 is correct: It is a **crude index** because it's a ratio (not a true rate) that doesn't account for the population at risk, temporal trends, or geographical distribution of cases. It merely reflects the relative burden among those seeking care. *2 only* - This option is incomplete. While statement 2 correctly defines the calculation method, it incorrectly excludes statements 1 and 3, which are also true. - The proportional case rate is indeed calculated as malaria cases per 100 OPD patients, but this alone doesn't explain its purpose or limitations. *3 only* - This option is incomplete. While statement 3 correctly identifies it as a **crude index** with limitations in temporal and spatial analysis, it incorrectly excludes statements 1 and 2. - Understanding why it's crude (statement 3) without knowing why it's used (statement 1) and how it's calculated (statement 2) provides an incomplete picture. *2 and 3 only* - This option is incomplete. While statements 2 and 3 are both correct, it incorrectly excludes statement 1. - The fundamental rationale for using proportional case rate—the difficulty in determining true morbidity rates—is missing, making this option less comprehensive than the correct answer.

Practice by Chapter

Principles of Epidemiology

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Measures of Disease Frequency

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Epidemiological Study Designs

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Descriptive Epidemiology

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Analytical Epidemiology

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Experimental Epidemiology

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Screening for Disease

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Surveillance Systems

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Investigation of an Epidemic

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Association and Causation

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Modern Epidemiological Methods

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Critical Appraisal of Epidemiological Studies

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