What is an exposure? What is a disease ? How do we measure them ?

1. What isanexposure?What isadisease?How do we measure them? Epidemiology matters: a new introduction to methodological foundations Chapter 3

2. Seven steps • Define the population of interest • Conceptualize and create measures of exposures and health indicators • Take a sample of the population • Estimate measures of association between exposures and health indicators of interest • Rigorously evaluate whether the association observed suggests a causal association • Assess the evidence for causes working together • Assess the extent to which the result matters, is externally valid, to other populations Epidemiology Matters – Chapter 1

3. What is a variable? • What are health indicators? • What is an exposure? • Measuring exposure and disease • Summary Epidemiology Matters – Chapter 3

4. What is a variable? • What are health indicators? • What is an exposure? • Measuring exposure and disease • Summary Epidemiology Matters – Chapter 3

5. What is a variable? A variableis any measured characteristic of individuals that differs across individuals Epidemiology Matters – Chapter 3

6. Variable examples • Age • Sex • Place of birth • Occupation • Education • Ethnicity • Cigarette smoking • Diet • Alcohol consumption • Blood pressure • Gun ownership • Diabetes • Pancreatic cancer • Depression Epidemiology Matters – Chapter 3

7. What is a variable? • What are health indicators? • What is an exposure? • Measuring exposure and disease • Summary Epidemiology Matters – Chapter 3

8. What are health indicators? • Population health is often defined by the absence of the occurrence of disease • Health indicators are typically measures of the occurrence of infections, syndromes, symptoms, and biological or subclinical markers • Health indicators can be measured over the life course and include measures of, for example, disability associated with adverse health states, potential years of life lost due to an illness • Health indicators can also be positive, e.g., well-being Epidemiology Matters – Chapter 3

9. Defining health indicators • Binary • Ordinal • Continuous Epidemiology Matters – Chapter 3

10. Binary health indicators • Variable that takes on two values • Health outcomes: present or absent • Examples • Individual has diabetes • Individual does not have cancer • Individual has Alzheimer’s disease • Individual does not have HIV Epidemiology Matters – Chapter 3

11. Ordinal health indicators • Variable that takes on multiple (>2) graded values • Examples Individual health rating • Question: How would you rate your health? • Response options: Excellent, Good, Fair, or Poor Symptom frequency • Question: How often do you experience night sweats? • Response options: Always, Often, Rarely, or Never Ability to perform health-related activity • Question: How difficult is it to climb a flight of stairs? • Response options: Very difficult, Somewhat difficult, or Not difficult Epidemiology Matters – Chapter 3

12. Continuous health indicators • Variable with continuous response options • Examples • Age • Weeks of pregnancy • Diastolic and systolic blood pressure • Cholesterol level • Viral load • Cancer stage Epidemiology Matters – Chapter 3

13. What is a variable? • What are health indicators? • What is an exposure? • Measuring exposure and disease • Summary Epidemiology Matters – Chapter 3

14. Exposure • Any measurable variable that affects or is associated with health • Variable can be from macro social environment to the molecular level • Examples • Policies and laws: areas with higher taxes on alcohol have lower alcohol consumption rates • Biological sex: Men die, on average, younger than women Epidemiology Matters – Chapter 3

15. Types of exposures • Acute • Chronic or stable • Time-varying Epidemiology Matters – Chapter 3

16. Acute exposures • Occur for a relatively short duration • Do not repeat • Examples • Natural disasters • Motor vehicle accident Epidemiology Matters – Chapter 3

17. Chronic exposures • Stable over time • May be present at birth • Examples • Pollution • Poverty • Policies and laws • Biological sex • Race and ethnicity • DNA sequence Epidemiology Matters – Chapter 3

18. Time-varying exposures • Vary across the life course of an individual • Examples • Diet • Exercise • Smoking • Alcohol consumption • Epidemiologists capture variation over time with different measures of exposure Epidemiology Matters – Chapter 3

19. Non-diseased Diseased Epidemiology Matters – Chapter 3

20. Smoking and exercise Epidemiology Matters – Chapter 3

21. Smoking and exercise Epidemiology Matters – Chapter 3

22. Smoking and exercise Epidemiology Matters – Chapter 3

23. Smoking and exercise Epidemiology Matters – Chapter 3

24. Smoking and exercise Epidemiology Matters – Chapter 3

25. Smoking and exercise Epidemiology Matters – Chapter 3

26. Smoking and exercise Epidemiology Matters – Chapter 3

27. Smoking and exercise Epidemiology Matters – Chapter 3

28. Summary: exposure Exposure: wide range of potential variables that individuals are ‘exposed to’ • Age • Sex • Education • Water consumption • Individual attendance at lecture today Epidemiology Matters – Chapter 3

29. Summary: exposure Exposure: wide range of potential variables that individuals are ‘exposed to’ • Age • Sex • Education • Water consumption • Individual attendance at lecture today What type of exposures are these? Epidemiology Matters – Chapter 3

30. Summary: exposure Exposure: wide range of potential variables that individuals ‘exposed to’ • Age continuous chronic • Sex binary chronic • Education ordinal chronic • Water consumption binary time-varying • Individual attendance at lecture today binary acute Epidemiology Matters – Chapter 3

31. Characterizing exposures • Duration of exposure • Latency and critical windows Epidemiology Matters – Chapter 3

32. Exposure duration • Duration that individual is exposed matters for production of adverse healthfor certain exposures Epidemiology Matters – Chapter 3

33. Exposure duration, examples Smoking • Smoking a cigarette is unlikelyto have long-term health consequences • Smoking > a pack of cigarettes per day for 40 years is likelytohave long-term health consequences Trans fat • One trans fat and calorie laden meal is unlikelyto affect health • Years of unhealthy eating is likelytoaccumulate to adversely impact health Epidemiology Matters – Chapter 3

34. Exposure timing • Timing of the exposure across the life course may also be important for the production of health • Core concepts: Latency and critical windows Epidemiology Matters – Chapter 3

35. Exposure timing, examples • Latency Low birth weight associated with the development of chronic diseases in adulthood • Critical window Extreme caloric restriction during first trimester of fetal development associated with schizophrenia development in adulthood Epidemiology Matters – Chapter 3

36. Examples, exposure timing Epidemiology Matters – Chapter 3

37. Examples, exposure timing Epidemiology Matters – Chapter 3

38. Examples, exposure timing Epidemiology Matters – Chapter 3

39. Examples, exposure timing Epidemiology Matters – Chapter 3

40. Examples, exposure timing Epidemiology Matters – Chapter 3

41. What is a variable? • What are health indicators? • What is an exposure? • Measuring exposure and disease • Summary Epidemiology Matters – Chapter 3

42. Measuring exposure and disease • In previous sections we have conceptualized the exposures and health indicators of interest • Now we are interested in measuring these factors • Good measurement of variables is critical for epidemiologists Epidemiology Matters – Chapter 3

43. Measurement example • Research question • Are individuals who have depression more likely to be overweight than individuals without depression? • Measuring depression • Constellation of symptoms • Condition characterized by disabling feelings of hopelessness, sadness, and loss of interest in activities • Measuring overweight • Obesity = Body Mass Index (BMI) ≥ 30 Epidemiology Matters – Chapter 3

44. Measurement • Be clear about the construct being measured • Assess the reliability of the measures • Assess the validity of the measures Epidemiology Matters – Chapter 3

45. Measurement example, clarity • Be clear about the construct being measured • Depression: validated scale • Obesity: BMI ≥ 30 • If measurements include respondent answered questions, make sure questions are easily interpretable, short, clear, and precise. • Instead of “Are you depressed?” • Try “In the past week have you felt happy most of the time?” Epidemiology Matters – Chapter 3

46. Reliability and validity of measures Epidemiology Matters – Chapter 3

47. Reliability and validity of measures Not valid or reliable Valid and reliable Reliable not valid Epidemiology Matters – Chapter 3

48. Reliability and validity of measures Not valid or reliable Scale does not work Valid and reliable Scale works perfectly Reliable not valid Scale consistently weighs people 5 pounds more than they weight Epidemiology Matters – Chapter 3

49. Dimensions of reliability • Test-retest reliability: Would the respondent answer the question similarly if asked at ≥ 2 time points? • Internal consistency: Are all the items used to assess the construct indicative of that construct? • Inter-rater reliability: Would ≥ 2 independent raters all rate the response the same? Epidemiology Matters – Chapter 3

50. Measurement validity Questions to consider when assessing validity • What is the gold standard? • What are the sensitivity and specificity of our measure as compared to the gold standard? Epidemiology Matters – Chapter 3