1. 1 Seminar 5: Applied Epidemiology Kaplan University School of Health Sciences

2. 2 Chapter 6: Study Design: Ecologic, Cross- Sectional, Case-Control Study

3. 3 Outline  Introduction  Observational Versus Experimental Approaches in Epidemiology  Overview of Study Designs  Ecologic Studies  Cross-sectional Studies  Case-Control Studies  Conclusion

4. 4 Introduction  Many study design options are available to the epidemiologists.  The choice of study designs depend on the amount of information that is already know about a particular health issue.  When relatively little is known, the investigator should not commence a costly and lengthy study.  A more prudent approach would be to employ, for example, using existing data.

5. 5 Introduction  As knowledge increase, and the complexity of the research questions increase, more rigorous study designs may be merited.  The major study designs differs from one another in several respects (page 243).

6. 6 Observational Versus Experimental Approaches  Combination of manipulation of the study factor (exposure) (M) and randomization of study subjects (R) produce three different study types: experimental, quasi- experimental, and observational (Table 6- 1 on page 244).

7. 7 Overview of Study Designs  Experimental Studies  Quasi-experimental Studies  Observational Studies

8. 8 Experimental Studies  Maintain the greatest control over the research setting.  The investigator both manipulate the study factor and randomly assign subjects to the exposed and non-exposed groups.  Examples: Clinical trials Clinical trials Community interventions Community interventions

9. 9 Quasi-Experimental Studies  Involve manipulation of the study factor but not randomization of study subjects.  Example: Seat belt use in different states.  Can be used for program evaluation using before and after appropriate indices.

10. 10 Observational Studies  In some instances an experiment would be impractical and in others, unethical. Association of smoking and diseases Association of smoking and diseases  Much of epidemiologic research is relegated to observational studies.  No manipulation of the study factor, nor randomization of study subjects.  Observational studies make use of careful measurement of exposure and disease to draw inferences about etiology.

11. 11 Observational Studies  1. Descriptive studies include case reports, case series, and cross-sectional studies.  2. Analytic studies include ecologic studies, case-control studies, and cohort studies. To test specific etiologic hypotheses To test specific etiologic hypotheses To generate new etiologic hypotheses To generate new etiologic hypotheses To suggest mechanisms of causation To suggest mechanisms of causation To generate preventive hypotheses To generate preventive hypotheses To suggest and identify potential intervention methods. To suggest and identify potential intervention methods.

12. 12 The 2 by 2 Table  It is an important tool in evaluating the association between exposure and disease. Disease Status Disease Status Exposure Yes YesNoTotal YesABA+B NoCDC+D TotalA+CB+D

13. 13 Ecologic Studies  Example: Data on the average of mortality and average air pollutant level are available within each census tract. The association between air pollution and mortality.  This hypothetical example illustrates one of the typical schemas for an ecologic study, using group data or population, not individuals as the unit of analysis.

14. 14 Ecologic Comparison Studies  (Sometimes called cross-sectional ecologic studies) involve an assessment of the correlation between exposure rates and disease rates among different groups or populations over the same time period  Usually there are more than 10 groups or populations.

15. 15 Ecologic Comparison Studies  The important characteristics of ecologic studies is that the level of exposure for each individual in the unit being study is unknown.  Ecologic studies generally make use of secondary data (i.e. already collected data)– quick, simple to conduct, and inexpensive.

16. 16 Ecologic Trend Studies  Involve correlation of changes in exposure with changes in disease over time within the same location (community, country, etc).  Example: there has been a consistently downward trend in the incidence of and mortality from coronary heart disease.  Ecologic correlation could be generated to support the claim that this trend reflects increased prescription of antihypertension medications or the number of coronary bypass surgeries performed.

17. 17 Ecologic studies: disadvantages  Ecologic fallacy is defined as the bias that may occur because an association observed between variables on an aggregate level does not necessarily represent the association that exist at an individual level.  Inaccurate exposure-disease quantification: Imprecision in the measurement of exposure and disease makes accurate quantification of the exposure-disease associations difficulty.

18. 18 Cross-Sectional Studies  Prevalence studies: individual’s exposure and disease measures are obtained simultaneously.  Typically descriptive in nature, they provide quantitative estimates of the magnitude of a problem but do not measure the temporal (time) ordering of cause and effect.

19. 19 CSSs: Sampling Schemes  Probability sample: every element in the population has a nonzero probability of being included in the sample.  Non-probability sample: not a probability sample.

20. 20 Probability Sampling  Simple random samples: same probability of being selected for each individual.  Systematic samples: simple, systemic rules: every 10 th person entering a mall.  Stratified samples: sampling is performed within each stratum (distinct subgroups according to some important characteristic, such as age, sex, or socioeconomic status...)

21. 21 Non-probability Sampling  Include quota samples and judgmental samples.  Quota samples: to obtain a fixed number of subjects regardless of their distribution in the population  Judgmental samples: to select subjects on the basis of the investigator’s perception that the sample will be representative of the population as a whole.

22. 22 Examples of Cross-sectional Studies  Page 258-262: 3 examples to illustrate a number of important applications of this design  Limitations stem mainly from their relative lack of utility for studies of disease etiology. Prevalent cases represent survivors Prevalent cases represent survivors It is hard to study rare disease. It is hard to study rare disease.

23. 23 Case-Control Studies  Consider two groups: case group (every one has the disease of interest) and a control group (everyone is free of the disease).  A case-control study seeks to identify possible causes of the disease by finding out how a case group and control group differ.

24. 24 Case-Control Studies  Because disease does not occur randomly, the case group mush have been exposed to some factor that contributed to the causation.  CCSs are a mainstay of epidemiology.  Cases and controls are selected and data are collected about past exposure that may have contributed to disease.  The unit of observation and unit of analysis are the individual.

25. 25 Case-Control Studies  Usually the data on exposure are collected by the investigators.  Data on disease are often collected by someone other than the investigators, especially if one is making use of special registries or surveillance systems for case identification.

26. 26 Selection of Cases  Two tasks are involved in selection: defining a case conceptually and identifying a case operationally.  The definition of a case is influenced by a number of factors. Whether there are standard diagnostic criteria Whether there are standard diagnostic criteria The severity of the disease The severity of the disease Where or not the criteria to diagnose the disease are subjective or objective. Where or not the criteria to diagnose the disease are subjective or objective.

27. 27 Sources of Cases  The ideal situation is to identify and enroll all incident cases in a defined population in a specified time period.  The advantage of using incident case is that, when all cases in a population are identified, the can be little question of their representativeness.

28. 28 Selection of Controls  The ideal controls should have the same characteristics as the cases, except for the exposure of interest).  That is, if the controls were equal to the cases in all respects other than disease and the hypothesized risk factor, one would be in a stronger position to ascribe differences in disease status to the exposure of interest.

29. 29 Selection of Controls  To overcome the potential impact of systematic case-control differences in demographic and other characteristics upon the outcome, we can use matching.  Two methods of matching are the use of matched pairs (individual matching) and frequency matching (group matching).  Select one or more controls so that the study has enough statistical power.

30. 30 Sources of Controls  Population-Based Controls  Patients from the Same Hospital as the Cases  Relatives or Associates of Cases

31. 31 Measure of Association  The 2 by 2 table on page 269 shows the disease and exposure status classification.  EXHIBIT 6-1 Sample Calculation of an Odds Ratio. Please read this section and post your thoughts and your questions for discussion.

32. 32 Measure of Association  Interpretation of OR  RR=1: the odds of exposure are equal among the cases and controls and suggests that a particular exposure is not a risk factor for the disease in this study.  RR>1: the odds of exposure among cases are greater than among controls.  0<RR<1

33. 33 Measure of Association  Under certain conditions, the OR provide a good approximation of the risk associated with a given exposure. These conditions are listed on page 271.  Table 6-6 on page 272: Examples of Research Conducted with Case-Control Studies

34. 34 Summary of Case-Control Studies  Case-control studies tend to be smaller in sample size and relative quick and easy to complete as well as cost effective.  The smaller sample size increases the likelihood that a case-control study will be repeated to create consistent results from different populations.  Limitations are included on page 276.

35. 35 Chapter 7: Study Design: Cohort Studies

36. 36 Cohort Studies Defined  A cohort is defined as a population group, or subset thereof (distinguished by a common characteristic), that is followed over a period of time.  Different cohorts may be exposed to different environmental and societal changes. The influence of membership in a particular cohort is known as a cohort effect.

37. 37 Cohort Studies Defined  Cohort analysis refers to the tabulation and analysis of morbidity and mortality rates in relationship to the ages of a cohort identified at a particular period of time and followed as they pass through different ages during part of their life span.  Table 7-1 on page 286 reproduces Frost’s data.

38. 38 Cohort Studies Defined  Figure 7-2 (page 288): Changes in prevalence of cigarette smoking among successive birth cohorts of U.S. men, 1900-1987.  Table 7-2: Lung cancer death rate for the UK and USA (one row for one cohort).

39. 39 Cohort Studies Defined  Life Tables: give estimates for survival during time intervals and present the cumulative survival probability at the end of the interval.  Cohort life table  Period life table (page 200)  EXHIBIT 7-1 (page 202): Explanations of the columns of the life table

40. 40 Cohort Studies Defined  Survival Curves: show the survival probability over time (Figure 7-4 on page 204).  These curves have numerous applications in research on many situations (diseases, etc).

41. 41 Cohort Studies  Population-Based Cohort Studies: the cohort includes either an entire population or a representative sample of the population.  Exposure-Based Cohort Studies: for rare exposure, certain occupational groups could be used, as in the battery industries with lead exposure.

42. 42 Temporal Differences in Cohort Designs  Prospective Cohort Studies: collect data on exposure at baseline and follow up for occurrence of disease at some time in the future.  Retrospective Cohort Studies: use historical data to determine exposure level as some baseline in the past; follow-up for subsequent occurrences of disease between baseline and the present is performed.

43. 43 Practical Considerations  Availability of Exposure Data  Size and Cost of the Cohort  Data collection and Data Management  Follow-up Issues  Sufficiency of Scientific Justification Page 303-307

44. 44 Measures of Interpretation and Examples  Rate ratio or relative risk: a ratio of incidence rate in the exposed group to the incidence rate in the nonexposed group.  Calculation is provided in EXHIBIT 7-2: Sample problem on page 308.

45. 45 Summary of Cohort Studies  Direct determination of risk  Providing stronger evidence of an exposure-disease association than the case-control study  Allowing examination of multiple outcomes  Limitations: taking considerable effort to conduct; loss to follow-up; changing exposure over time

46. 46  Any questions?