Basic Terminology in Population Studies

1. بسم الله الرحــــــمـن الرحيم

2. Basic Terminology Population: • Population is the term statisticians use to describe a largest collection of items or entities that have something in common and for which we have an interest at a particular time. • A population consists of all elements: individuals, items, or objects whose characteristics are being studied. In medicine, population generally refers to patients or other living organisms. • The population being studied is also called the target population.

3. Basic Terminology Sample: • A portion of the population selected for study is referred to as a sample. • Suppose that we would like to know the weights of all the students at KSU. If we collect for analysis the weights of pharmacy students only, that is, we have a sample. KSU students: Population Pharmacy students: Sample Representative sample: • A representative sample contains the characteristics of the population as closely as possible.

4. Basic Terminology Random sample: • A sample drawn in such a way that each element of the population has some chance of being selected. Simple random sample: • If the chance of being selected is the same for each element of the population, it is called a simple random sample.

5. Basic Terminology A cohort: • A “cohort” is a group of people who have something in common. • Can represent the source population—the population from which cases of disease arise. • Examples of cohorts: • All employees in an office building • Everyone who attended a football game • All the residents of a neighborhood

6. Basic Terminology Variable: • A variable is a characteristic under study that assumes different values for different elements. • Some examples of variables include: • Diastolic blood pressure. • Heart rate. • The heights of adult's males. • The weights of preschool children. • Stage of bladder cancer patients. • Pain score of patients postoperatively. Observation or measurement:It is the value of the variable for a single element e.g. SBP is the variable; 120 is the observation

7. Basic Terminology Parameter: • Descriptive measure derived from a population. • Usually we don’t know the value of the parameter; consequently, we are estimating it from the sample. • For example if we want to know the mean age of all Saudi bladder cancer cases. This mean will be calculated from information collected from all bladder cancer cases in Saudi Arabia. • Usually impossible to calculate.

8. Basic Terminology Statistic: • Descriptive measure from a sample. • For example if we want to know the mean age of all Saudi bladder cancer cases. We take a portion of bladder cancer cases and calculate the mean age.

9. Basic Terminology • Randomization: • The process by which each subject has the same chance of being assigned to either intervention or control. • Tends to produce study groups comparable with respect to known and unknown risk factors, • Removes investigator bias in the allocation of participants, and guarantees that statistical tests will have a valid significance levels.

10. Basic Terminology • Blinding: Keeping the identity of treatment assignments masked for: • Subject => Single-blind • Subject + Investigator => Double-blind • Purpose of blinding:Bias reduction

11. Blinding • A clinical trial, ideally, should have a double-blind design to avoid potential problems of bias during data collection and assessment. • In studies where such a design is impossible, a single- blind design and other measures to reduce potential bias are favored.

12. Ethical Considerations • If the physician feels that one treatment better than another for a particular patient, he or she cannot randomly assign a treatment. • It is unethical not to treat a patient in a manner that the physician believes is best. • Thus, if the physician is convinced that one of the treatments is better for the patient, the patient should not be entered in the study, and if at any time during the study there is a clear indication that one treatment is better, randomization of patients should be stooped. • To avoid termination of trials due to physician’s bias before any statistical significance has been obtained, results of the trial should be kept from the participating physicians until a decision of whether or not to stop the trial has been reached by an advisory committee.

13. What is a Cohort? • A “cohort” is a group of people who have something in common. • Can represent the source population—the population from which cases of disease arise. • Examples of cohorts: • All employees in an office building • Everyone who attended a football game • All the residents of a neighborhood

14. Cohort Studies • Tend to be retrospective (exposures in the past in relation to disease that has already happened). • Occurrence of disease in exposed group compared to occurrence of disease in unexposed group = risk ratio. • Risk ratio tells whether disease is associated with exposure and strength of association.

15. Identifying a Cohort • To use a cohort study, you must identify every person in the cohort. • Possible when the group is small and well defined (e.g., wedding reception, cruise ship, school). • Option to interview every member of the cohort or a sample of the cohort.

16. Identifying a Cohort • Sometimes it may be difficult to define a suitable cohort. • Can you find every single person who ate at the Main Street Restaurant on October 10-20?. • How would you locate every person buying and/or eating contaminated lunch meat from a local supermarket chain? • An alternative: The case-control study.

17. Case-Control Studies • The most frequently used type of study in outbreaks. • Can be quickly implemented. • Can be used when cohort study might be large and time-consuming. • Identify people with disease (case-patients) and people without disease (controls), then ask everyone about past exposures. • You already know who is sick through doctor diagnosis, lab culture, or health department.

18. Retrospective cohort study is the most appropriate study design here. If fewer than 200 people involved, should consider interviewing everyone. Case-Control or Cohort: Which one is right? Figure 1: Easily identifiable cohort (e.g., School picnic, wedding) Not ill n=81 Ill n=34 Total N = 115

19. A case-control study could be used for efficiency here. Or capture entire cohort using e-mail or mail surveys. Or identify cohorts within the larger cohort (e.g., a single dormitory on a college campus). Case-Control or Cohort: Which one is right? Figure 2: Easily identifiable but large cohort (e.g., cruise ship, college campus) Not ill n=2354 Ill n=21 Total N = 2375