Association and Causation Indian Medical PG Practice Questions and MCQs
Practice Indian Medical PG questions for Association and Causation. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Association and Causation Indian Medical PG Question 1: Which type of study determines the odds ratio?
- A. Case control (Correct Answer)
- B. Cohort
- C. Cross sectional
- D. RCT
Association and Causation Explanation: ***Case control***
- **Case-control studies** compare individuals with a disease (cases) to individuals without the disease (controls) and look back in time to identify previous exposures.
- The **odds ratio** is the primary measure of association used in case-control studies, quantifying the odds of exposure among cases versus controls.
*Cohort*
- **Cohort studies** follow groups of individuals over time, some exposed to a risk factor and some not, to determine the incidence of a disease.
- They typically determine **relative risk**, which is the ratio of incidence rates in exposed versus unexposed groups.
*Cross sectional*
- **Cross-sectional studies** assess the prevalence of disease and exposure at a single point in time.
- They primarily measure **prevalence** and can be used to calculate a **prevalence odds ratio**, but they do not establish temporality between exposure and outcome.
*RCT*
- **Randomized controlled trials (RCTs)** are interventional studies where participants are randomly assigned to an intervention or control group to determine the effectiveness of a treatment or exposure.
- The main measure of effect in RCTs is often the **relative risk reduction**, **absolute risk reduction**, or **number needed to treat**, rather than the odds ratio for observational exposure.
Association and Causation Indian Medical PG Question 2: In pediatric growth assessment, what is the typical relationship observed between height and weight in healthy children?
- A. Negative Correlation
- B. No Correlation
- C. Inverse Relationship
- D. Positive Correlation (Correct Answer)
Association and Causation Explanation: ***Positive Correlation***
- In healthy children, as **height increases**, **weight generally also increases** in a predictable pattern, demonstrating a **positive correlation** between these two variables.
- This is a fundamental aspect of normal pediatric growth, where both height and weight increase together as children develop.
- The **correlation coefficient** between height and weight in healthy children is typically **strong and positive** (r > 0.7).
*Negative Correlation*
- A **negative correlation** would imply that as height increases, weight decreases, which contradicts normal growth patterns in healthy children.
- This relationship might be observed in certain pathological conditions (e.g., severe malnutrition with stunting) but is not characteristic of normal development.
*No Correlation*
- Stating **no correlation** would mean that changes in height have no predictable linear relationship with changes in weight, which contradicts well-established growth data.
- Height and weight are both key anthropometric indicators that are inherently linked during normal growth.
*Inverse Relationship*
- An **inverse relationship** is synonymous with a negative correlation, suggesting that as one variable increases, the other decreases.
- This is incorrect for normal pediatric growth, where height and weight generally trend upwards together throughout childhood.
Association and Causation Indian Medical PG Question 3: Which type of study is particularly vulnerable to selection bias?
- A. Case control study (Correct Answer)
- B. Cohort study
- C. Randomized controlled trial
- D. None of the options
Association and Causation Explanation: ***Case control study***
- Due to the **retrospective nature** of case-control studies, **selection bias** can occur when choosing cases and controls based on their exposure status.
- Controls might not be truly representative of the population from which the cases arose, leading to **skewed exposure frequencies** and biased association estimates.
*Cohort study*
- While cohort studies can experience selection bias, it primarily arises from **differential loss to follow-up** rather than the initial selection process directly affecting exposure assessment.
- Participants are typically selected before the outcome occurs, reducing bias related to outcome status influencing selection.
*Randomized controlled trial*
- **Randomization** is specifically designed to minimize selection bias by ensuring that baseline characteristics, including potential confounders, are evenly distributed between intervention and control groups.
- Blinding further reduces the risk of bias from participants or researchers influencing outcomes or exposures.
*None of the options*
- This option is incorrect because **case-control studies** are indeed particularly susceptible to selection bias due to their design.
Association and Causation Indian Medical PG Question 4: Which of the following best describes the concept where a suspected cause precedes the observed effect?
- A. Temporal association (Correct Answer)
- B. Consistency of association
- C. Strength of association
- D. Coherence of association
Association and Causation Explanation: ***Temporal association***
- This principle in **causal inference** emphasizes that for a factor to be a cause, it must precede the effect.
- In epidemiology, it's crucial to establish that exposure occurred **before the disease manifestation**.
*Consistency of association*
- Refers to the observation of a **similar association across different studies** and populations.
- While important for causal inference, it does not directly address the timing of cause and effect.
*Strength of association*
- Quantifies how often the **exposure and outcome co-occur**, often measured by relative risk or odds ratio.
- A strong association is more likely to be causal, but it doesn't confirm that the cause came before the effect.
*Coherence of association*
- Implies that the observed association should be **consistent with existing biological and medical knowledge**.
- This criterion supports the plausibility of an association but doesn't specifically deal with the temporal sequence.
Association and Causation Indian Medical PG Question 5: A researcher wanted to prove the relation between COPD and smoking. He collected patients records from government hospitals and records of cigarette sales from the finance and taxation department. This is an example of which study design:
- A. Cross-sectional
- B. Posological study
- C. Ecological study (Correct Answer)
- D. Operations research
Association and Causation Explanation: ***Ecological study***
- This study design involves analyzing data at a **population level**, rather than individual patient data. The researcher used aggregated data from hospital records (COPD prevalence) and cigarette sales (smoking rates) for populations or groups, not individual patients.
- It examines the relationship between an exposure (smoking) and an outcome (COPD) by comparing disease frequencies in different populations with varying levels of exposure.
*Cross-sectional*
- A cross-sectional study measures the **prevalence** of a disease and exposure at a **single point in time** in individuals.
- It does not involve comparing population-level aggregates or using secondary data from different sources to establish associations between population groups.
*Posological study*
- A posological study focuses on the **dosage** and administration of drugs, often to determine optimal therapeutic regimens.
- This term is irrelevant to the described research design, which is concerned with the relationship between smoking and COPD.
*Operations research*
- Operations research is a discipline that applies analytical methods to improve **decision-making and efficiency** within organizations or systems.
- This field is primarily concerned with optimizing processes and resource allocation, not establishing epidemiological associations between risk factors and diseases.
Association and Causation Indian Medical PG Question 6: Hill's criteria of causal association are all Except
- A. Coherence
- B. Consistency
- C. Specificity of association
- D. Sensitivity (Correct Answer)
Association and Causation Explanation: ***Sensitivity***
- **Sensitivity** is a measure of a **screening or diagnostic test's ability** to correctly identify true positives. It is not part of Hill's criteria for assessing causality.
- Hill's criteria focus on establishing a causal link between an exposure and an outcome, not on the performance of a diagnostic test.
*Coherence*
- **Coherence** refers to the requirement that a causal explanation should not contradict generally accepted **facts of natural history** and **biology**.
- It suggests that the causal relationship should make sense within known scientific principles.
*Consistency*
- **Consistency** means that similar results have been observed in **different studies** or settings, increasing the likelihood of a causal relationship.
- Repeated observations of the association under various conditions strengthen the evidence for causality.
*Specificity of association*
- **Specificity of association** suggests that a single exposure leads to a **single disease** and not multiple diseases, and a single disease is caused by a single exposure.
- While considered a criterion, it is often seen as a **weaker criterion** because many exposures can cause multiple outcomes, and many diseases have multiple causes.
Association and Causation Indian Medical PG Question 7: The difference between the incidence in the exposed and non-exposed group is best given by:
- A. Attributable risk (Correct Answer)
- B. Population attributable risk
- C. Odds ratio
- D. Relative risk
Association and Causation Explanation: ***Attributable risk***
- **Attributable risk** (AR), also known as risk difference, directly quantifies the absolute difference in disease incidence between an **exposed group** and an **unexposed group**.
- It represents the amount of disease incidence (or risk) in the exposed group that is **directly attributable to the exposure**, assuming a causal relationship.
*Population attributable risk*
- **Population attributable risk** (PAR) measures the proportion of disease incidence in the **total population** that is attributable to the exposure.
- It takes into account both the impact of the exposure and the **prevalence of the exposure** in the population, which is distinct from simply comparing exposed and non-exposed groups.
*Odds ratio*
- The **odds ratio** (OR) is a measure of association between an exposure and an outcome, representing the **odds of an outcome occurring in the exposed group** compared to the odds of it occurring in the unexposed group.
- It does not directly express the difference in incidence but rather the **ratio of odds**, often used in case-control studies.
*Relative risk*
- **Relative risk** (RR), or risk ratio, is the ratio of the **incidence of an outcome in the exposed group** to the incidence in the unexposed group.
- It indicates how many times more likely an exposed group is to develop the outcome compared to an unexposed group, expressing a **ratio rather than a difference**.
Association and Causation Indian Medical PG Question 8: In a cohort study conducted with 100 individuals in each group (exposed and non-exposed), out of those exposed to the risk factor, 10 are diseased, and out of those not exposed to the risk factor, only 5 are diseased. What is the relative risk?
- A. 2 (Correct Answer)
- B. 1.5
- C. 0.75
- D. 1
Association and Causation Explanation: ***Correct Option: 2***
- The **incidence in the exposed group** is 10/100 = 0.1.
- The **incidence in the non-exposed group** is 5/100 = 0.05.
- **Relative risk (RR)** is calculated as the ratio of the incidence in the exposed group to the incidence in the non-exposed group: 0.1 / 0.05 = 2.
- This indicates that the **exposed group has twice the risk** of developing the disease compared to the non-exposed group.
*Incorrect Option: 1.5*
- This value would be obtained if the ratio of incidences was 0.075 / 0.05 or 0.1/0.066, which is not consistent with the given data.
- An RR of 1.5 indicates a **lesser strength of association** than what is observed in this study.
*Incorrect Option: 0.75*
- This value would result if the incidence in the exposed group was *lower* than in the non-exposed group (e.g., 0.05 / 0.066), suggesting a **protective effect**.
- An RR < 1 implies that exposure is protective rather than a risk factor, which contradicts the given data.
*Incorrect Option: 1*
- A **relative risk of 1** indicates there is no difference in the risk of disease between the exposed and non-exposed groups.
- This would mean the incidence rate in both groups is identical (e.g., 0.1 / 0.1 = 1), which contradicts the provided data where exposed group has higher incidence.
Association and Causation Indian Medical PG Question 9: What is the most important criterion in a causal relationship hypothesis?
- A. Temporal association (Correct Answer)
- B. Coherence of association
- C. Specificity of association
- D. Strength of association
Association and Causation Explanation: ***Temporal association***
- This is the **sine qua non** of causality, meaning the exposure or cause must always precede the outcome or effect in time.
- Without the exposure occurring before the disease, a causal link cannot be established, even if other criteria are met.
*Coherence of association*
- This refers to the consistency of findings with current scientific knowledge and **biological plausibility**.
- While important for supporting causality, a coherent explanation is not sufficient in itself to prove causation and may even be misleading if current knowledge is incomplete.
*Specificity of association*
- This criterion suggests that a single exposure should lead to a single outcome, or a single outcome should be caused by a single exposure.
- However, many diseases have **multiple causes**, and many exposures can lead to multiple effects, making this a weak criterion in modern epidemiology.
*Strength of association*
- A **strong association**, often measured by a high relative risk or odds ratio, makes a causal relationship more likely but does not guarantee it.
- Strong associations can still be due to **confounding factors** or bias, and weak associations can be causal.
Association and Causation Indian Medical PG Question 10: 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)
Association and Causation 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.
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Framework for assessing if an observed association is likely causal. Fulfilling more criteria strengthens causal inference; not all are required. 📌 Mnemonic: "BTS CAPS CE".
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