chronic disease epidemiologist Interview Questions and Answers

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100 Interview Questions and Answers for a Chronic Disease Epidemiologist

  1. What are the main differences between incidence and prevalence in chronic disease epidemiology?

    • Answer: Incidence refers to the number of *new* cases of a disease occurring within a defined population over a specific period. Prevalence refers to the *total* number of existing cases (both new and old) within a defined population at a specific point in time. In chronic diseases, prevalence is often higher than incidence because people can live with these conditions for many years.

  2. Explain the concept of relative risk (RR) and odds ratio (OR) and when you would use each.

    • Answer: Relative risk (RR) measures the risk of developing a disease in an exposed group compared to an unexposed group in a cohort study. Odds ratio (OR) measures the odds of exposure among cases compared to controls in a case-control study. RR is preferred when data comes from a cohort study and is a more direct measure of risk. OR is used in case-control studies and is an approximation of RR when the disease is rare.

  3. Describe different study designs used in chronic disease epidemiology (e.g., cohort, case-control, cross-sectional).

    • Answer: Cohort studies follow a group of individuals over time to observe the incidence of disease. Case-control studies compare individuals with a disease (cases) to those without (controls) to identify risk factors. Cross-sectional studies assess disease prevalence and exposure at a single point in time. Each design has strengths and weaknesses regarding causality, cost, and time commitment.

  4. What are confounding factors and how do you address them in epidemiological studies?

    • Answer: Confounding factors are variables that distort the relationship between an exposure and an outcome. Methods to address confounding include randomization (in experimental studies), stratification, matching, and statistical adjustment (e.g., regression analysis).

  5. Explain the concept of effect modification and how it differs from confounding.

    • Answer: Effect modification occurs when the effect of an exposure on an outcome differs depending on the level of another variable (the modifier). Unlike confounding, which distorts the true association, effect modification represents a true biological interaction. It should be reported, not controlled.

  6. Discuss the importance of bias in epidemiological research and strategies to minimize it.

    • Answer: Bias is a systematic error that distorts the true association between exposure and outcome. Types of bias include selection bias, information bias, and confounding. Minimizing bias involves careful study design, standardized data collection protocols, blinding, and appropriate statistical analysis.

  7. What are some common chronic diseases you are familiar with, and what are some of their known risk factors?

    • Answer: Examples include cardiovascular disease (risk factors: hypertension, smoking, high cholesterol), type 2 diabetes (risk factors: obesity, family history, physical inactivity), cancer (risk factors vary greatly by cancer type, but include smoking, genetics, exposure to carcinogens), and chronic obstructive pulmonary disease (COPD) (risk factors: smoking, air pollution).

  8. Describe the role of multilevel modeling in chronic disease epidemiology.

    • Answer: Multilevel modeling (or hierarchical modeling) is used when data is nested or clustered (e.g., individuals within communities, patients within hospitals). It allows for the analysis of data at multiple levels, accounting for the correlation within clusters and providing more accurate estimates of effects.

  9. How do you interpret a hazard ratio (HR) from a Cox proportional hazards model?

    • Answer: A hazard ratio (HR) from a Cox proportional hazards model represents the instantaneous risk of an event (e.g., death, disease onset) in one group compared to another group, adjusting for other factors. An HR > 1 indicates an increased risk in the exposed group, while an HR < 1 indicates a decreased risk.

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