Epidemiology Practice Questions

Q: Admission rate bias is?

Berksonian bias. ***Berksonian bias*** - **Berksonian bias** is a form of selection bias, also known as **admission rate bias**, that occurs when different rates of admission to a hospital or clinical setting distort the association between diseases or between a disease and a risk factor. - This bias arises because the hospitalized population may not be representative of the general population, leading to spurious associations or masking real ones. *Reporting bias* - **Reporting bias** is a type of information bias where the outcome or exposure information is reported inaccurately, often due to social desirability or recall issues. - It does not specifically refer to distortions stemming from hospital admission rates. *Response bias* - **Response bias** occurs when participants in a study alter their answers or behavior from what is true due to factors like leading questions, social desirability, or acquiescence. - This is an issue related to data collection, not an unrepresentative study population due to hospital admission protocols. *None of the options* - Berksonian bias directly corresponds to the definition of admission rate bias, making this option incorrect.

Q: Nosocomial infections are defined as infections that develop after how many hours of hospital admission?

A) 48 hours. ***A) 48 hours*** - Nosocomial infections, also known as **hospital-acquired infections (HAI)**, are defined as infections that develop **48 hours or more** after hospital admission. - This is the **standard definition** used by the **CDC, WHO**, and major medical textbooks including **Park's Textbook of Preventive and Social Medicine**. - The 48-hour threshold helps differentiate infections acquired during hospitalization from those that were **incubating at the time of admission** (typical incubation periods for most common infections are less than 48 hours). - Infections can also be classified as nosocomial if they occur **within 3 days after discharge** or **within 30 days after surgery**. *B) 72 hours* - While **72 hours** is occasionally mentioned in some contexts or specific institutional protocols, it is **not the standard definition** for nosocomial infections. - Using 72 hours would be too restrictive and could miss true hospital-acquired infections that manifest between 48-72 hours. - The universally accepted standard remains **48 hours**. *C) 24 hours* - An infection developing within **24 hours** is very likely to have been **present or incubating prior to admission**. - This timeframe is too short to establish that the infection was acquired during hospitalization. - Most common bacterial and viral infections have incubation periods longer than 24 hours. *D) 50 hours* - This is **not a standard threshold** for defining nosocomial infections. - The conventional definitions use **48 hours** as the cutoff point, which is based on typical incubation periods and epidemiological evidence.

Q: Which of the following is an example of prospective screening?

Neonate for thyroid diseases. ***Neonate for thyroid diseases*** - **Prospective/Mass screening** involves screening an **entire population or specific subgroup** before symptoms appear for early detection and intervention - **Neonatal screening for congenital hypothyroidism** is performed universally on all newborns to identify and treat the condition early, preventing severe developmental disabilities and intellectual impairment - This represents **true population-wide screening** applied systematically to every member of the birth cohort *Immigrant screening* - This is **selective screening** targeting a specific high-risk group rather than universal population screening - Primary goal is to **control disease transmission** and identify conditions posing public health risks upon entry - Not applied to the general population systematically *Pap smear for 45-year female* - This is an example of **organized screening** for cervical cancer in a specific age group - While valuable for secondary prevention, it targets women within defined age ranges (typically 21-65 years) - Not universal across all age groups like neonatal screening *Diabetes mellitus for 40-year male* - This represents **opportunistic or selective screening** based on age and risk factors - Not a universal population-wide program applied systematically to everyone - Typically done as part of routine health checks for at-risk individuals

Q: What is the expected percentage reduction in mortality risk from breast cancer with annual mammography screening after the age of 50?

15-20%. ***15-20%*** - Current evidence from **meta-analyses and systematic reviews** shows that annual mammography screening in women aged 50 and older reduces breast cancer mortality by approximately **15-20%**. - This estimate is supported by the **U.S. Preventive Services Task Force (USPSTF)** and **Canadian Task Force on Preventive Health Care** based on modern randomized controlled trials. - The benefit reflects **earlier detection** and treatment of breast cancer in this age group. *20-25%* - This range **slightly overestimates** the mortality reduction demonstrated in contemporary evidence-based reviews. - While some older studies reported benefits in this range, more rigorous modern analyses support a lower estimate. *25-30%* - This represents **older estimates** from earlier meta-analyses that have been revised downward with more recent data. - Contemporary evidence-based guidelines do **not support** this level of mortality reduction for routine mammography screening. - This figure may have included methodological biases present in older trials. *30-35%* - This range **significantly overestimates** the mortality benefit of mammography screening. - No current evidence-based guidelines support this level of mortality reduction for average-risk women aged 50 and above. - Such high estimates are not supported by modern randomized controlled trials.

Q: What is the significance of the 1st of July in demographic studies?

1st July. ***1st July*** - The **1st of July** is often considered the **mid-year population estimate** in demographic studies. - This date is crucial for calculating rates (e.g., birth rates, death rates) and making projections, as it provides a standardized reference point that balances out seasonal population fluctuations. *1st January* - While a significant date for many annual administrative purposes, the **1st of January** represents the beginning of the year, not the mid-point. - Using this date for population counts can sometimes overemphasize the population at the start of a new calendar cycle, potentially skewing annual rate calculations. *1st September* - The **1st of September** falls in the third quarter of the year and does not represent a standard mid-year point for demographic estimations. - This date has no widely recognized statistical significance for population estimation in demographic contexts. *15th June* - The **15th of June** is close to the middle of the year but is not the conventionally adopted date for mid-year population estimates. - Demographers prefer standard, easily replicable dates for consistency across regions and studies.

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

Proportion of cases linked to exposure (Attributable risk). ***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.

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

P will decrease & I will remain the same. ***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 1

Admission rate bias is?

Accepted Answer

Berksonian bias

Answer

Reporting bias

Answer

Response bias

Answer

None of the options

Question 2

Nosocomial infections are defined as infections that develop after how many hours of hospital admission?

Accepted Answer

A) 48 hours

Answer

B) 72 hours

Answer

C) 24 hours

Answer

D) 50 hours

Question 3

Which of the following is an example of prospective screening?

Accepted Answer

Neonate for thyroid diseases

Answer

Immigrant screening

Answer

Pap smear for 45-year female

Answer

Diabetes mellitus for 40-year male

Question 4

The difference in incidence between exposed and non-exposed groups in epidemiological studies is best described as:

Accepted Answer

Difference in incidence between exposed and non-exposed groups

Answer

Measure of association between exposure and outcome

Answer

Total impact of exposure on disease occurrence in a population

Answer

Ratio of incidence in exposed versus non-exposed groups

Question 5

What is the expected percentage reduction in mortality risk from breast cancer with annual mammography screening after the age of 50?

Accepted Answer

15-20%

Answer

30-35%

Answer

25-30%

Answer

20-25%

Question 6

During investigation of an epidemic, the area is declared free of epidemic when?

Accepted Answer

Twice the incubation period of the disease since occurrence of the last case

Answer

Thrice the incubation period of the disease since occurrence of the last case

Answer

The longest incubation period for the disease

Answer

Incubation period for the disease plus two standard deviations

Question 7

What is the significance of the 1st of July in demographic studies?

Accepted Answer

1st July

Answer

1st January

Answer

1st September

Answer

15th June

Question 8

Why are standardized death rates used in health comparisons?

Accepted Answer

For valid comparison between populations with different demographic characteristics

Answer

Calculations are more accurate.

Answer

To avoid selection bias.

Answer

None of the options.

Question 9

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

Accepted Answer

Proportion of cases linked to exposure (Attributable risk)

Answer

Measure of association between exposure and outcome (Relative risk)

Answer

Frequency of new disease cases (Incidence rate)

Answer

Estimate of exposure-outcome odds (Odds ratio)

Question 10

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

Accepted Answer

P will decrease & I will remain the same

Answer

No change in P & I

Answer

Both P & I will decrease

Answer

P will decrease & I will increase

Epidemiology — MCQs

Epidemiology — MCQs

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