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Centers for Disease Control and Prevention Morgantown, West Virginia June 20-24, 2011 Teach Epidemiology Professional Development Workshop Day 2.

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Presentation on theme: "Centers for Disease Control and Prevention Morgantown, West Virginia June 20-24, 2011 Teach Epidemiology Professional Development Workshop Day 2."— Presentation transcript:

1 Centers for Disease Control and Prevention Morgantown, West Virginia June 20-24, 2011 Teach Epidemiology Professional Development Workshop Day 2

2 2

3 3 Teach Epidemiology

4 4

5 Identifying Patterns and Formulating Hypotheses 5

6 6 Drug Use Among Racial and Ethnic Minorities a.American Indian or Alaskan Native - A person having origins in any of the original peoples of North and South America, who maintains cultural identification through tribal affiliations or community recognition. b.Asian or Pacific Islander - A person having origins in any of the original peoples of the Far East, Southeast Asia, the Indian subcontinent, or the Pacific Islands. This area includes, for example, China, India, Japan, Korea, the Philippine Islands, Hawaii, and Samoa. c.Black or African American - A person having origins in any of the Black racial groups of Africa. d.Hispanic - A person of Mexican, Puerto Rican, Cuban, Central or South American or other Spanish culture or origin, regardless of race. e.White - A person having origins in any of the original peoples of Europe, North Africa, or the Middle East. Identifying Patterns and Formulating Hypotheses

7 7 Drug Use Among Racial and Ethnic Minorities a.American Indian or Alaskan Native - A person having origins in any of the original peoples of North and South America, who maintains cultural identification through tribal affiliations or community recognition. b.Asian or Pacific Islander - A person having origins in any of the original peoples of the Far East, Southeast Asia, the Indian subcontinent, or the Pacific Islands. This area includes, for example, China, India, Japan, Korea, the Philippine Islands, Hawaii, and Samoa. c.Black or African American - A person having origins in any of the Black racial groups of Africa. d.Hispanic - A person of Mexican, Puerto Rican, Cuban, Central or South American or other Spanish culture or origin, regardless of race. e.White - A person having origins in any of the original peoples of Europe, North Africa, or the Middle East. Identifying Patterns and Formulating Hypotheses

8 8 Enforcing the requirements of the Voting Rights Act Reviewing State redistricting plans Collecting and presenting population and population characteristics data, labor force data, education data, and vital and health statistics Establishing and evaluating Federal affirmative action plans and evaluating affirmative action and discrimination in employment in the private sector Monitoring the access of minorities to home mortgage loans under the Home Mortgage Disclosure Act Enforcing the Equal Credit Opportunity Act Monitoring and enforcing desegregation plans in the public schools Assisting minority businesses under the minority business development programs Enforcing the Fair Housing Act Ways the Federal Government Uses Race / Ethnicity Data Identifying Patterns and Formulating Hypotheses

9 9 Does race and ethnicity make a difference? Identifying Patterns and Formulating Hypotheses

10 10 Race / Ethnic Group Percent Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States, 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Does race and ethnicity make a difference? Drug Used in Past Month Identifying Patterns and Formulating Hypotheses

11 11 Estimate Prevalence of Use of Any Illicit Drug Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month Does race and ethnicity make a difference? Race / Ethnic Group Percent Used in Past Month

12 Identifying Patterns and Formulating Hypotheses 12 Estimate Prevalence of Use of Any Illicit Drug Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic What hypotheses might explain this distribution? Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month Race / Ethnic Group Percent Used in Past Month

13 Identifying Patterns and Formulating Hypotheses 13 Estimate Prevalence of Use of Marijuana Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month 5.0 Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

14 Identifying Patterns and Formulating Hypotheses 14 Estimate Prevalence of Use of Marijuana Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month What hypotheses might explain this distribution? Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

15 Identifying Patterns and Formulating Hypotheses 15 Estimate Prevalence of Use of Cocaine Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month 0.8 Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

16 Identifying Patterns and Formulating Hypotheses 16 Estimate Prevalence of Use of Cocaine Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month What hypotheses might explain this distribution? Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

17 Identifying Patterns and Formulating Hypotheses 17 Estimate Prevalence of Use of Alcohol Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month 51.7 Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

18 Identifying Patterns and Formulating Hypotheses 18 Estimate Prevalence of Use of Alcohol Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month What hypotheses might explain this distribution? Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

19 Identifying Patterns and Formulating Hypotheses 19 Estimate Prevalence of Use of Cigarettes Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month 27.7 Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

20 Identifying Patterns and Formulating Hypotheses 20 Estimate Prevalence of Use of Cigarettes Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 6.2 Black, Non-Hispanic 6.2 American Indian / Alaskan Native 6.2 Asian / Pacific Islander 6.2 Hispanic 6.2 Race / Ethnic Group Percent Used in Past Month What hypotheses might explain this distribution? Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

21 Identifying Patterns and Formulating Hypotheses 21 Estimate Prevalence of Use of Marijuana Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 5.0 Black, Non-Hispanic 6.6 American Indian / Alaskan Native 8.0 Asian / Pacific Islander 2.6 Hispanic 4.5 Race / Ethnic Group Percent Used in Past Month Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

22 Identifying Patterns and Formulating Hypotheses 22 Estimate Prevalence of Use of Marijuana Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? White, Non-Hispanic 5.0 Black, Non-Hispanic 6.6 American Indian / Alaskan Native 8.0 Asian / Pacific Islander 2.6 Hispanic 4.5 Race / Ethnic Group Percent Used in Past Month White, Non-Hispanic 5.0 Black, Non-Hispanic 6.6 American Indian / Alaskan Native 8.0 Asian / Pacific Islander 2.6 Hispanic 4.5 Estimate Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in United States: 1998 Any Illegal Drug Use06.2 Marijuana05.0 Cocaine00.8 Alcohol51.7 Cigarettes27.7 Drug Percent Used in Past Month

23 Identifying Patterns and Formulating Hypotheses 23 Estimate Prevalence of Use of Marijuana Among Hispanic Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? Puerto Rican Mexican Cuban Central American South American Other Race / Ethnic Group Percent Used in Past Month 4.5 Estimate Prevalence of Use of Marijuana Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 White, Non-Hispanic Black, Non-Hispanic American Indian / Alaskan Native Asian / Pacific Islander Hispanic Race / Ethnic Group Percent Used in Past Month

24 Identifying Patterns and Formulating Hypotheses 24 Estimate Prevalence of Use of Marijuana Among Hispanic Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 Does race and ethnicity make a difference? Puerto Rican Mexican Cuban Central American South American Other Race / Ethnic Group Percent Used in Past Month What hypotheses might explain this distribution? Estimate Prevalence of Use of Marijuana Among Persons Age 12 and Older in United States, By Race and Ethnicity: 1998 White, Non-Hispanic Black, Non-Hispanic American Indian / Alaskan Native Asian / Pacific Islander Hispanic Race / Ethnic Group Percent Used in Past Month

25 25 Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity: White Black American Indian / Alaskan Native Asian / Pacific Islander Hispanic Hidden Data Identifying Patterns and Formulating Hypotheses

26 26 White Black American Indian / Alaskan Native Asian / Pacific Islander Hispanic Identifying Patterns and Formulating Hypotheses Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity:

27 27 Hidden Data Identifying Patterns and Formulating Hypotheses Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity:

28 28 What hypotheses might explain this distribution? Identifying Patterns and Formulating Hypotheses Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity:

29 29 Fundamental Epidemiological Understandings

30 30 Time Check 8:15 AM

31 31

32 32 Teach Epidemiology

33 33 Time Check 9:15 AM

34 34

35 35 Teach Epidemiology

36 Teachers Team-Teaching Teachers (TTTT) Existing Lesson Team leads other workshop participants in a portion of a selected existing epidemiological lesson.

37 37 They can then use that ability to think about their own thinking … to grasp how other people might learn. They know what has to come first, and they can distinguish between foundational concepts and elaborations or illustrations of those ideas. They realize where people are likely to face difficulties developing their own comprehension, and they can use that understanding to simplify and clarify complex topics for others, tell the right story, or raise a powerfully provocative question. Ken Bain, What the Best College Teachers Do Metacognition Teach Epidemiology Epi – Grades 6-12

38 38 Teach Epidemiology Enduring Epidemiological Understandings

39 39 Time Check 10:15 AM

40 40

41 41 Teach Epidemiology

42 42 Time Check 10:30 AM

43 43

44 44 Teach Epidemiology

45 Teachers Team-Teaching Teachers (TTT) Teach Existing Epidemiological Lessons (EL) (4 Groups) Team leads other workshop participants in a portion of a selected existing epidemiological lesson.

46 46 They can then use that ability to think about their own thinking … to grasp how other people might learn. They know what has to come first, and they can distinguish between foundational concepts and elaborations or illustrations of those ideas. They realize where people are likely to face difficulties developing their own comprehension, and they can use that understanding to simplify and clarify complex topics for others, tell the right story, or raise a powerfully provocative question. Ken Bain, What the Best College Teachers Do Metacognition Teach Epidemiology Epi – Grades 6-12

47 47 Teach Epidemiology Enduring Epidemiological Understandings

48 48 Time Check 10:15 AM

49 49

50 50 Teach Epidemiology

51 View a News Item from an Epidemiological Perspective Team leads other workshop participants in the analysis of a news item from an epidemiological perspective. Teach Epidemiology Teachers Team-Teaching Teachers (TTT)

52 52 They can then use that ability to think about their own thinking … to grasp how other people might learn. They know what has to come first, and they can distinguish between foundational concepts and elaborations or illustrations of those ideas. They realize where people are likely to face difficulties developing their own comprehension, and they can use that understanding to simplify and clarify complex topics for others, tell the right story, or raise a powerfully provocative question. Ken Bain, What the Best College Teachers Do Metacognition Teach Epidemiology Epi – Grades 6-12

53 53 Teach Epidemiology Enduring Epidemiological Understandings

54 54 Teach Epidemiology Enduring Epidemiological Understandings

55 55 Time Check Noon

56 56

57 57 Teach Epidemiology

58 58 Time Check 1:00 PM

59 59

60 60 Teach Epidemiology

61 Teach Epidemiology Workshop—Day 2 Diane Marie M. St. George, PhD University of MD School of Medicine

62 Back to EU 2 and 3 Why study patterns of disease? Why is a description of the person, place, and time elements of a disease distribution important?

63 Epidemiologic Studies Descriptive epidemiology  Describes patterns of disease  Suggests hypotheses about relationships between “exposures” and “health-related conditions” Analytic epidemiology  Tests hypotheses  Evaluates relationships  Always in a search for causality  Knowing causation helps us to prevent and treat disease and promote health

64 Enduring Understandings 4. A hypothesis can be tested by comparing the frequency of disease in selected groups of people with and without an exposure to determine if the exposure and the disease are associated. 5. When an exposure is hypothesized to have a beneficial effect, studies can be designed in which a group of people is intentionally exposed to the hypothesized cause and compared to a group that is not exposed. 6. When an exposure is hypothesized to have a detrimental effect, it is not ethical to intentionally expose a group of people. In these circumstances, studies can be designed that observe groups of free- living people with and without the exposure.

65 Boys are more likely than girls to want to go to this field trip.  What are we comparing? Proportion of girls who will want to go on the trip to proportion of boys who will want to go on the trip.  What is the causal inference? Gender  Wanting to attend the field trip This “Teach Epi” thing…it will work better for Ms. Smith’s kids than mine.  What are we comparing? Proportion of Smith’s students who will engage with epidemiology to proportion of my students who will engage with epidemiology.  What is the causal inference? Class  Engagement with the science of epidemiology

66 Heart attacks Descriptive epidemiology showed the following patterns:  In certain Midwestern communities, increasing incidence of heart attacks over time  More heart attacks among farmworkers than non- farmworkers in those communities  More heart attacks among males than among females What is your hypothesis?

67 Testing hypotheses about MI Hypothesis: Exposure to pesticides increases risk of MI. How might you go about evaluating this hypothesis?

68 Testing hypotheses about MI Hypothesis: Exposure to pesticides increases risk of MI. Evaluate the hypothesis using an:  Ecologic study

69 Ecologic study of pesticide exposure and MI Exposure is pesticide  Measured as proportion of land area devoted to wheat Outcome is MI  Measured as a rate per 100,000 Plot data on a graph What might you expect to see?

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72 Ecologic Study Key element  Group-level estimates Quantify relationships  Graphical displays  Correlation coefficient Advantages  Study group-level variables, e.g. policies, laws, community socioeconomic status  Use existing data sources  Use fewer resources (time, money, subject burden) Disadvantage  Ecologic fallacy

73 Testing hypotheses about MI Hypothesis: Exposure to pesticides increases risk of MI. Evaluate the hypothesis using a:  Cross-sectional study

74 Cross-sectional study of pesticide exposure and MI Exposure is pesticide  Measured as pesticide application history Outcome is MI  Measured as yes or no Count responses What might you expect to see?

75 Pesticides and MI MI+MI- Pesticide+ Pesticide- 200

76 Pesticides and MI MI+MI- Pesticide Pesticide So, is pesticide usage associated with MI?

77 Pesticides and MI MI+MI- Pesticide Pesticide What is the prevalence of MI? What is the prevalence of MI among pesticide users? What is the prevalence of MI among non-users?

78 Pesticides and MI MI+MI- Pesticide Pesticide What is the prevalence of MI? 70/200 = 35% What is the prevalence of MI among pesticide users? = 60/150 = 40% What is the prevalence of MI among non-users? = 10/50 = 20%

79 Cross-sectional Study Key element  Snapshot of one point in time Quantify association  Prevalence ratio Advantages  Individual data  Quick, cheap Disadvantages  Difficult to assess temporality because measure E and D simultaneously  Inefficient for E or D that are rare  Inefficient for D that are rapidly fatal or of short duration

80 Testing hypotheses about MI Hypothesis: Exposure to pesticides increases risk of MI. Evaluate the hypothesis using a:  Case-control study

81 Case-control study of pesticide exposure and MI Exposure is pesticide  Measured as pesticide application history Outcome is MI  Measured as yes or no Want to ensure that you have enough cases to do your study, so select for those with MI Find those without MI Ask them about exposures to pesticides What might you expect to see?

82 Pesticides and MI MI+MI- Pesticide+ Pesticide

83 Pesticides and MI MI+MI- Pesticide Pesticide What is the prevalence of MI?

84 Case-control Study Odds = probability an event will occur/probability that an event will not occur Odds of exposure in cases = (among cases) probability of being exposed/probability one was not exposed What is odds of exposure in controls? = (among controls) probability of being exposed/ probability one was not exposed What is Odds Ratio?

85 Pesticides and MI MI+MI- Pesticide Pesticide What is the odds of exposure among the cases? What is the odds of exposure among the controls? What is the OR?

86 Pesticides and MI MI+MI- Pesticide Pesticide What is the odds of exposure among the cases? (60/100)/(40/100) = 60/40 = 1.5 What is the odds of exposure among the controls? (10/90) =.11 What is the OR? ~ 13.5

87 Case-control Study Key elements  Compare individuals selected on the basis of disease status  Classic epidemiologic study design Quantify association  Odds Ratio Advantages  Can be less expensive and time-consuming than follow-up studies  Efficient for rare diseases Disadvantages  May be resource-intensive because of need to screen so many  Difficult to assess temporality

88 Testing hypotheses about MI Hypothesis: Exposure to pesticides increases risk of MI. Evaluate the hypothesis using a:  Cohort study

89 Cohort study of pesticide exposure and MI Exposure is pesticide  Measured as pesticide application history Outcome is MI  Measured as yes or no Want to ensure that you have enough exposed persons to do your study, so select for those with pesticide exposure Find those without pesticide exposure Follow them up over time to ascertain MI status What might you expect to see?

90 Pesticides and MI MI+MI- Pesticide+100 Pesticide

91 Pesticides and MI MI+MI- Pesticide Pesticide What is the incidence of MI among the pesticide users? What is the incidence of MI among the non-users? What is the risk ratio?

92 Pesticides and MI MI+MI- Pesticide Pesticide What is the incidence of MI among the pesticide users? = 70% What is the incidence of MI among the non-users? = 35% What is the risk ratio? = 2.0

93 Cohort Study Key element  Select based on exposure status and follow-up over time Quantify association  Relative risk (risk ratio) Advantages  Minimizes confusion about temporality  Ideal for rare exposures Disadvantages  May have to screen many to get exposed group  Large, time-consuming, expensive especially if disease is relatively rare and/or slow to develop  Inefficient for rare diseases

94 Testing hypotheses about MI Hypothesis: Exposure to pesticides increases risk of MI. Evaluate the hypothesis using a:  Randomized controlled trial

95 RCT study of pesticide exposure and MI Exposure is pesticide  Measured as pesticide exposure Outcome is MI  Measured as yes or no Want to ensure maximal control over study parameters, so you decide who gets exposed and who does not Follow up over time to ascertain MI status What might you expect to see?

96 Pesticides and MI MI+MI- Pesticide+ Pesticide- 200

97 Pesticides and MI MI+MI- Pesticide Pesticide What is the incidence of MI among the pesticide users? What is the incidence of MI among the non-users? What is the risk ratio?

98 Pesticides and MI MI+MI- Pesticide Pesticide What is the incidence of MI among the pesticide users? = 70% What is the incidence of MI among the non-users? = 35% What is the risk ratio? = 2.0

99 Randomized Controlled Trial Key elements  Assign treatments to individuals and follow up to ascertain disease status.  The researcher controls primary exposure under study. Exposures can be treatments (drug, surgery) or preventive measures (water fluoridation, exercise regimens).  Ethical considerations may preclude use of this design. Quantify association  Relative risk (risk ratio) Advantages  Random assignment serves to “equate” groups  Closest to “true experiment” Disadvantages  Expensive and time-consuming  Subjects are often highly selected group because the requirements of participants can often be extensive

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101 Childhood cancer and residential electric consumption Canada Rank provinces by REC Rank provinces by cancer rates: surveillance data What is exposure/risk factor/agent? What is disease/health outcome? What study design?

102 Ecologic Study r=0.74r=0.78 r=0.58r=0.44

103 Literacy and misunderstanding prescription drug labels Adults in primary care clinic waiting rooms Low literacy = reading at 5 th grade level or below Example: Take one tsp by mouth 3 times daily What is exposure? What is health outcome? What is study design?

104 Cross-sectional Study Misunderstand Amoxicillin label Understand label Low literacyAB Adequate literacy CD

105 Cross-sectional Study Misunderstand Amoxicillin label Understand label Low literacy Adequate literacy Please reproduce the 2X2 table on paper.

106 Cross-sectional Study What proportion of adults had low literacy? = 75/282 = 27% What proportion of adults misunderstood the labels? = 67/282 = 24% What proportion of adults who had low literacy misunderstood the labels? = 31/75 = 41% What proportion of adults with adequate literacy misunderstood the labels? =36/207 = 17% How did the misunderstanding of the low literate adults compare with that of the adequately literate adults? = 41%/17% = 2.4

107 Household pesticides and Wilms tumor Early age at onset suggests in utero exposures 523 cases of Wilms tumor 517 controls Pesticide use in home from month before conception through date of diagnosis/date of telephone call What is exposure? Health condition? Study design?

108 Case-control Study Wilms+Wilms- Pesticide in yard+ AB Pesticide in yard- CD

109 Case-control Study Wilms+Wilms- Pesticide in yard Pesticide in yard OR = (158/352)/(157/344) ≈ 1.0

110 HIV status and risk of menstrual abnormalities Women’s Interagency HIV Study ~2500 HIV+ and ~1300 HIV- women enrolled Ask about amenorrhea at baseline and follow-up What is exposure? health condition? study design?

111 Cohort Study AmenorrheaMenstrual period w/in past 6 mos HIV HIV

112 Cohort study What is risk of amenorrhea among HIV+ women? = 141/1034 = 14% What is risk of amenorrhea among HIV- women? = 37/383 = 10% What is the risk among HIV+ women relative to the risk among HIV- women? Relative Risk = 1.4

113 Vitamin D supplementation and risk of falls and fractures among the elderly 149 residential facilities in Australia Randomly assigned to 2 years on calcium plus Vitamin D or placebo Double-masked Study diaries maintained by caregivers What is exposure? health condition? study design?

114 RCT Fall+Fall- Vitamin D supplement Placebo185127

115 RCT What is risk of falls among the treatment group? = 170/313 = 54% What is risk of falls among the comparison group? =185/312 = 59% What is RR? = 54%/59% = 0.9

116 Enduring Understandings 4. A hypothesis can be tested by comparing the frequency of disease in selected groups of people with and without an exposure to determine if the exposure and the disease are associated. 5. When an exposure is hypothesized to have a beneficial effect, studies can be designed in which a group of people is intentionally exposed to the hypothesized cause and compared to a group that is not exposed. 6. When an exposure is hypothesized to have a detrimental effect, it is not ethical to intentionally expose a group of people. In these circumstances, studies can be designed that observe groups of free- living people with and without the exposure.

117 117 Time Check 2:45 PM

118 118

119 119 Teach Epidemiology

120 120 Time Check 3:00 PM

121 121

122 122 Teach Epidemiology

123 123 Ecologic Study Study in which the units investigated are populations or groups of people rather than individuals.

124 124 Ecologic Study

125 Hypothetical Ecologic Study Relationship Between Income and Auto Accident 3 communities each with a population of 7 people This hypothetical ecologic study is described in AV Diez-Roux’s article, “Bringing Context Back into Epidemiology: Variables and Fallacies in Multilevel Analysis,” in the American Journal of Public Health, 1998;88:216–222.

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132 132 Ecologic Study Ecological Fallacy An error in inference due to failure to distinguish between information obtained from groups versus individuals. An association observed between variables at a population level does not necessarily hold true for individual members of these populations.

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136 136 Ecologic Study Ecological Fallacy An error in inference due to failure to distinguish between information obtained from groups versus individuals. An association observed between variables at a population level does not necessarily hold true for individual members of these populations.

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138 138 Outcome Exposure a c b d Ecologic Study

139 139

140 Which came first? EggChicken Detectives in the Classroom – Investigation 3-5: Reversed Time Order

141 141 Which happened first?

142 142

143 143 Random Assignment

144 144 Random Assignment

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150 150 National Research Council, Learning and Understanding Teach Epidemiology Enduring Epidemiological Understandings Knowledge that “… is connected and organized, and … ‘conditionalized’ to specify the context in which it is applicable.”

151 151 Association Found Between Coffee and Pancreatic Cancer Associated Teach Epidemiology

152 152 What do we mean when we say that there is an association between two things? Associated TiedRelated Linked Things that are associated are linked in some way that makes them turn up together. Associated Teach Epidemiology

153 153 Things that are associated are linked in some way that makes them turn up together. Associated Teach Epidemiology

154 154 Suicide Higher in Areas with Guns Smoking Linked to Youth Eating Disorders Snacks Key to Kids’ TV- Linked Obesity: China Study Family Meals Are Good for Mental Health Lack of High School Diploma Tied to US Death Rate Study Links Spanking to Aggression Breakfast Each Day May Keep Colds Away Study Concludes: Movies Influence Youth Smoking Study Links Iron Deficiency to Math Scores Kids Who Watch R-Rated Movies More Likely to Drink, Smoke Pollution Linked with Birth Defects in US Study Depressed Teens More Likely to Smoke Associated Teach Epidemiology

155 155 Epidemiologic studies that are concerned with characterizing the amount and distribution of health and disease within a population. Descriptive Epidemiology Teach Epidemiology

156 156 Epidemiologic studies that are concerned with determinants of disease and the reasons for relatively high or low frequencies of disease in specific population subgroups. Analytical Epidemiology Teach Epidemiology

157 157 Hypothesis Formulating Descriptive Epidemiology Testing Analytical Epidemiology An unproven idea, based on observation or reasoning, that can be supported or refuted through investigation An educated guess Hypothesis Teach Epidemiology

158 158 Hypothesis: Buprenorphine will stop heroin addicts from using heroin. Making Group Comparisons and Identifying Associations Teach Epidemiology

159 159 Population Trial 1 Making Group Comparisons and Identifying Associations

160 160 Population 500 Heroin Addicts Sample 100 Heroin Addicts 10 Weeks Trial 1 Making Group Comparisons and Identifying Associations

161 161 Population 500 Heroin Addicts Sample 100 Heroin Addicts 10 Weeks 21 Heroin Addicts Tested Negative for Heroin Trial 1 Making Group Comparisons and Identifying Associations

162 162 Bupe Tested Positive for Heroin Total Tested Negative for Heroin Trial 1 Making Group Comparisons and Identifying Associations Teach Epidemiology

163 163 When you can measure what you are speaking about, and express it in numbers, you know something about it. Lord Kelvin But when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind. Making Group Comparisons and Identifying Associations Teach Epidemiology

164 164 A measure of how often an outcome occurs in a defined population in a defined period of time. It consists of a numerator and a denominator. Risk The numerator is the number of people in the population or sample who experienced the outcome and the denominator is the total number of people in the population or sample. Population / Sample Outcome Denominator Numerator Making Group Comparisons and Identifying Associations Teach Epidemiology

165 165 … the risk of a negative heroin test was 21 / 100 in a 10-week period 21 tested negative for heroin 100 study subjects Numerator Denominator Risk Making Group Comparisons and Identifying Associations Teach Epidemiology

166 166 A measure of how often an outcome occurs in a defined group of people in a defined period of time. The likelihood of an outcome occurring. Risk / Rate Making Group Comparisons and Identifying Associations Teach Epidemiology

167 167 Trial 1 Bupe Tested Positive for Heroin Tested Negative for Heroin or 21 % Calculating Risk Risk of Negative Heroin Test Total Making Group Comparisons and Identifying Associations Teach Epidemiology

168 168 Process of predicting from what is observed in a sample to what is true for the entire population. Inference Making Group Comparisons and Identifying Associations Teach Epidemiology

169 169 Trial 1 What does this tell you about the hypothesis? Buprenorphine will stop heroin addicts from using heroin. Inference Probe Bupe Tested Positive for Heroin Tested Negative for Heroin or 21 % Risk of Negative Heroin Test Total Making Group Comparisons and Identifying Associations Teach Epidemiology

170 170 People who participate in a trial, but do not get the treatment. People whose results are compared to the group that was treated. Control Group Making Group Comparisons and Identifying Associations Teach Epidemiology

171 or 21 % Tested Positive for Heroin Tested Negative for Heroin Bupe Control Group Extend and label the table to include a control group. Risk of Negative Heroin Test Total Making Group Comparisons and Identifying Associations Teach Epidemiology

172 ? or ? % No Bupe Control Group Making Group Comparisons or 21 % Tested Positive for Heroin Tested Negative for Heroin Bupe Risk of Negative Heroin Test Total Making Group Comparisons and Identifying Associations Teach Epidemiology

173 ? or ? % No Bupe Making Group Comparisons or 21 % Tested Positive for Heroin Tested Negative for Heroin Bupe ExposureExposure Outcome / Disease ab cd Risk of Negative Heroin Test Total Making Group Comparisons and Identifying Associations Teach Epidemiology

174 or 21 % Total Bupe 100 ? or ? % No Bupe Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Making Group Comparisons and Identifying Associations Teach Epidemiology

175 175 A cross-classification of data where categories of one variable are presented in rows and categories of another variable are presented in columns The simplest contingency table is the 2x2 table. Contingency Table Making Group Comparisons and Identifying Associations Teach Epidemiology

176 176 Population 500 Heroin Addicts Sample 100 Heroin Addicts 10 Weeks 21 Heroin Addicts Tested Negative for Heroin Trial 1 Making Group Comparisons and Identifying Associations

177 177 Trial 2 Total ? 100 ? % a b c d Bupe Tested Negative for Heroin Tested Positive for Heroin No Bupe100 ? ? % Risk of Negative Heroin Test Making Group Comparisons and Identifying Associations Teach Epidemiology

178 178 E Assigned E O O O O Making Group Comparisons and Identifying Associations Volunteer Heroin Addicts Teach Epidemiology

179 % or a b c d Bupe Trial 2 No Bupe Probe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Making Group Comparisons and Identifying Associations Teach Epidemiology

180 % or a b c d Bupe Trial 2 No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Making Group Comparisons and Identifying Associations Teach Epidemiology

181 % or a b c d Bupe Trial 2 No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Inference: Process of predicting from what is observed in a sample to what is occurring in the entire population Making Group Comparisons and Identifying Associations Teach Epidemiology

182 182 When you can measure what you are speaking about, and express it in numbers, you know something about it. Lord Kelvin But when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind. Making Group Comparisons and Identifying Associations Teach Epidemiology

183 183 The value obtained by dividing one quantity by another Ratio Making Group Comparisons and Identifying Associations Teach Epidemiology

184 % or a b c d Bupe Trial 2 No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Ratio: The value obtained by dividing one quantity by another Risk Ratio: The ratio of two risks 1 Risk Ratio Making Group Comparisons and Identifying Associations Teach Epidemiology

185 % or a b c d Bupe Trial 2 No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Ratio: The value obtained by dividing one quantity by another Risk Ratio: The ratio of two risks 1 Risk Ratio Create a formula a a + b c c + d Making Group Comparisons and Identifying Associations Teach Epidemiology

186 % or a b c d Bupe Trial 2 No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or 1 Risk Ratio Relative Risk: The ratio of the risk of an outcome among the exposed to the risk of the outcome among the unexposed. Relative Risk Making Group Comparisons and Identifying Associations Teach Epidemiology

187 % or a b c d Bupe Trial 2 No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or 1 Risk Ratio Relative Risk Inference: Process of predicting from what is observed in a sample to what is occurring in the entire population The inference here is that there is no effect of Buprenorphine Making Group Comparisons and Identifying Associations Teach Epidemiology

188 188 Trial 3 ? 100 ? % 100 or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test ? 100 ? % 100 or Making Group Comparisons and Identifying Associations Teach Epidemiology

189 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Trial 3 Making Group Comparisons and Identifying Associations Teach Epidemiology

190 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Trial 3 Making Group Comparisons and Identifying Associations Teach Epidemiology

191 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Inference: Process of predicting from what is observed in a sample to what is occurring in the entire population Trial 3 Making Group Comparisons and Identifying Associations Teach Epidemiology

192 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Relative Risk Relative Risk: The ratio of the risk of an outcome among the exposed to the risk of the outcome among the unexposed Trial 3 Making Group Comparisons and Identifying Associations Teach Epidemiology

193 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Relative Risk 0.34 The heroin addicts who received Bupe were ___ times as likely to test negative for heroin as those who did not receive Bupe Trial 3 Making Group Comparisons and Identifying Associations Teach Epidemiology

194 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Relative Risk 0.34 Inference: Process of predicting from what is observed in a sample to what is occurring in the entire population. Trial 3 Making Group Comparisons and Identifying Associations Teach Epidemiology

195 195 Trial 4 ? 100 ? % 100 or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test ? 100 ? % 100 or Making Group Comparisons and Identifying Associations Teach Epidemiology

196 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Trial 4 Making Group Comparisons and Identifying Associations Teach Epidemiology

197 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Trial 4 Making Group Comparisons and Identifying Associations Teach Epidemiology

198 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Relative Risk Relative Risk: The ratio of the risk of an outcome among the exposed to the risk of the outcome among the unexposed. 3.5 Trial 4 Making Group Comparisons and Identifying Associations Teach Epidemiology

199 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Relative Risk 3.5 The heroin addicts who received Bupe were ___ times as likely to test negative for heroin as those who did not receive Bupe. 3.5 Trial 4 Making Group Comparisons and Identifying Associations Teach Epidemiology

200 % or a b c d Bupe No Bupe Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test % or Relative Risk 3.5 Inference: Process of predicting from what is observed in a sample to what is occurring in the entire population. Trial 4 Making Group Comparisons and Identifying Associations Teach Epidemiology

201 % or Bupe Trial 1 Total Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test What do the results tell us about the hypothesis that Buprenorphine will stop heroin addicts from using heroin? Nothing Making Group Comparisons and Identifying Associations Teach Epidemiology

202 202 Trial 1 Trial 2 Trial 3 Trial 4 Making Group Comparisons and Identifying Associations Teach Epidemiology

203 203 Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% Making Group Comparisons and Identifying Associations Teach Epidemiology

204 204 Risk of Negative Heroin Test Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Bupe No Bupe Bupe No Bupe Bupe Total Relative Risk No Bupe Total Relative Risk Total Tested Negative for Heroin Tested Positive for Heroin Relative Risk Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% Making Group Comparisons and Identifying Associations Teach Epidemiology

205 205 Risk of Negative Heroin Test Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Bupe No Bupe Bupe No Bupe Bupe Total Relative Risk No Bupe Total Relative Risk Total Tested Negative for Heroin Tested Positive for Heroin Relative Risk Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% or 21% or 21% or 21% Making Group Comparisons and Identifying Associations Teach Epidemiology

206 206 Risk of Negative Heroin Test Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Bupe No Bupe Bupe No Bupe Bupe Total Relative Risk No Bupe Total Relative Risk Total Tested Negative for Heroin Tested Positive for Heroin Relative Risk Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% or 21% or 21% or 21% or 21% Bupe is not associated with having a negative test for heroin. Making Group Comparisons and Identifying Associations Teach Epidemiology

207 207 Risk of Negative Heroin Test Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Bupe No Bupe Bupe No Bupe Bupe Total Relative Risk No Bupe Total Relative Risk Total Tested Negative for Heroin Tested Positive for Heroin Relative Risk Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% or 21% or 21% or 21% or 21% Bupe is not associated with having a negative test for heroin or 62% Bupe is associated with having a positive test for heroin!.34 Making Group Comparisons and Identifying Associations Teach Epidemiology

208 208 Risk of Negative Heroin Test Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Bupe No Bupe Bupe No Bupe Bupe Total Relative Risk No Bupe Total Relative Risk Total Tested Negative for Heroin Tested Positive for Heroin Relative Risk Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% or 21% or 21% or 21% or 21% Bupe is not associated with having a negative test for heroin or 62% Bupe is associated with having a positive test for heroin! or 6% Bupe is associated with having a negative test for heroin. 3.5 Making Group Comparisons and Identifying Associations Teach Epidemiology

209 209 Risk of Negative Heroin Test Nothing Bupe Total Trial 1 Trial 2 Trial 3 Trial 4 Bupe No Bupe Bupe No Bupe Bupe Total Relative Risk No Bupe Total Relative Risk Total Tested Negative for Heroin Tested Positive for Heroin Relative Risk Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin Risk of Negative Heroin Test Tested Negative for Heroin Tested Positive for Heroin or 21% or 21% or 21% or 21% or 21% Bupe is not associated with having a negative test for heroin or 62% Bupe is associated with having a positive test for heroin! or 6% Bupe is associated with having a negative test for heroin. 3.5 Nothing Compared to what? Making Group Comparisons and Identifying Associations Teach Epidemiology

210 210 Buprenorphine Buprenorphine & Naloxone Placebo Making Group Comparisons and Identifying Associations Teach Epidemiology Handout

211 211 National Research Council, Learning and Understanding Teach Epidemiology Enduring Epidemiological Understandings Knowledge that “… is connected and organized, and … ‘conditionalized’ to specify the context in which it is applicable.”

212 212

213 213 Suicide Higher in Areas with Guns Smoking Linked to Youth Eating Disorders Snacks Key to Kids’ TV- Linked Obesity: China Study Family Meals Are Good for Mental Health Lack of High School Diploma Tied to US Death Rate Study Links Spanking to Aggression Breakfast Each Day May Keep Colds Away Study Concludes: Movies Influence Youth Smoking Study Links Iron Deficiency to Math Scores Kids Who Watch R-Rated Movies More Likely to Drink, Smoke Pollution Linked with Birth Defects in US Study Depressed Teens More Likely to Smoke In the News

214 214 Total ab dc 2 x 2 Table Suicide Higher in Areas with Guns

215 215 Total ab dc People who are exposed ab 2 x 2 Table Suicide Higher in Areas with Guns Areas with Guns No Suicide Suicide Areas without Guns

216 216 ab dc 2 x 2 Table Total Kids Who Watch R-Rated Movies More Likely to Drink, Smoke

217 217 ab dc 2 x 2 Table R-Rated Movies Total Drink & Smoke Kids Who Watch R-Rated Movies More Likely to Drink, Smoke No Drink & Smoke No R-Rated Movies

218 218 ab dc People who are exposed and have the outcome a 2 x 2 Table R-Rated Movies Total Drink & Smoke Kids Who Watch R-Rated Movies More Likely to Drink, Smoke No Drink & Smoke No R-Rated Movies

219 219 ab dc 2 x 2 Table Family Meals Are Good for Mental Health Total

220 220 ab dc 2 x 2 Table Family Meals Are Good for Mental Health Family Meals Total Mental Health No Mental Health No Family Meals

221 221 ab dc People who are not exposed and do not have the outcome d 2 x 2 Table Family Meals Are Good for Mental Health Family Meals Total Mental Health No Mental Health No Family Meals

222 222 ab dc 2 x 2 Table Study Links Iron Deficiency to Math Scores Total

223 223 ab dc 2 x 2 Table Study Links Iron Deficiency to Math Scores Iron Deficiency Poor Math Scores No Iron Deficiency Good Math Scores Total

224 224 ab dc People who do not have the outcome and are not exposed d 2 x 2 Table Study Links Iron Deficiency to Math Scores Iron Deficiency Poor Math Scores No Iron Deficiency Good Math Scores Total

225 225 ab dc 2 x 2 Table Pollution Linked with Birth Defects in US Study Total

226 226 ab dc 2 x 2 Table Pollution Linked with Birth Defects in US Study Pollution Birth Defects No Pollution No Birth Defects Total

227 227 ab dc People who are not exposed dc 2 x 2 Table Pollution Linked with Birth Defects in US Study Pollution Birth Defects No Pollution No Birth Defects Total

228 228 ab dc 2 x 2 Table Depressed Teens More Likely to Smoke Total

229 229 ab dc People who do not have the outcome d b 2 x 2 Table Depressed Teens More Likely to Smoke Depression Smoke No Depression No Smoke Total

230 230 ab dc 2 x 2 Table Smoking Linked to Youth Eating Disorders Total

231 231 ab dc 2 x 2 Table Smoking Linked to Youth Eating Disorders Smoke Eating Disorders No Smoke No Eating Disorders Total

232 232 ab dc People who are exposed and do not have the outcome b 2 x 2 Table Smoking Linked to Youth Eating Disorders Smoke Eating Disorders No Smoke No Eating Disorders Total

233 233 ab dc 2 x 2 Table Total Study Links Spanking to Aggression

234 234 ab dc People who have the outcome a c 2 x 2 Table Study Links Spanking to Aggression Spanking Aggression No Spanking Total No Aggression

235 235 ab dc 2 x 2 Table Total Snacks Key to Kids’ TV-Linked Obesity – China Study

236 236 ab dc 2 x 2 Table Snacks Key to Kids’ TV-Linked Obesity – China Study Snacks Obesity No Snacks No Obesity Total People who are not exposed and have the outcome c

237 237

238 238 National Research Council, Learning and Understanding Teach Epidemiology Enduring Epidemiological Understandings Knowledge that “… is connected and organized, and … ‘conditionalized’ to specify the context in which it is applicable.”

239 239 Laboratory Teach Epidemiology Making Group Comparisons and Identifying Associations

240 240 Laboratory Teach Epidemiology Making Group Comparisons and Identifying Associations

241 241 Naturally occurring circumstances in which groups of people within a population have been exposed to different levels of the hypothesized cause of an outcome. Natural Experiment Teach Epidemiology Making Group Comparisons and Identifying Associations

242 242 An epidemiologic study of a natural experiment in which the investigator is not involved in the intervention other than to record, classify, count, and statistically analyze results. Observational Study Teach Epidemiology Making Group Comparisons and Identifying Associations

243 243 An epidemiologic experiment in which subjects are assigned into groups to receive or not receive a hypothesized beneficial intervention. Controlled Trial Teach Epidemiology Making Group Comparisons and Identifying Associations

244 244 Buprenorphine Buprenorphine will stop heroin addicts from using heroin. Teach Epidemiology Making Group Comparisons and Identifying Associations

245 245 Naturally occurring circumstances in which groups of people within a population have been exposed to different levels of the hypothesized cause of an outcome. Observational Study of a Natural Experiment Epidemiologic studies of natural experiments in which the investigator is not involved in the intervention other than to record, classify, count, and statistically analyze results. Teach Epidemiology Making Group Comparisons and Identifying Associations

246 246 Making Group Comparisons and Identifying Associations Teach Epidemiology

247 247 Making Group Comparisons and Identifying Associations Teach Epidemiology

248 248 Stephen Jay Gould (survivor of abdominal mesothelioma) Absolutely nothing in the available arsenal of anti-emetics worked at all. I was miserable and came to dread the frequent treatments with an almost perverse intensity. I had heard that marijuana often worked well against nausea. I was reluctant to try it because I had never smoked any substance habitually (and didn’t even know how to inhale). Moreover, I had tried marijuana twice (in the 1960s) … and had hated it …. Marijuana worked like a charm …. The sheer bliss of not experiencing nausea - and not having to fear it for all the days intervening between treatments - was the greatest boost I received in all my year of treatment, and surely the most important effect upon my eventual cure. Making Group Comparisons and Identifying Associations Teach Epidemiology

249 249 A particular or detached incident or fact of an interesting nature; a biographical incident or fragment; a single passage of private life. Anecdote Making Group Comparisons and Identifying Associations Teach Epidemiology

250 250 Science Transforming Anecdote to Science Making Group Comparisons and Identifying Associations Teach Epidemiology Anecdote

251 251 Time Healthy People - E Random Assignment E DZ Controlled Trial Time Healthy People - E E DZ Cohort Study Time Case-Control Study - DZ E E E E Time Cross-Sectional Study - E E DZ Making Group Comparisons and Identifying Associations Teach Epidemiology

252 252 Time Healthy People - E Random Assignment E DZ Controlled Trial Time Healthy People - E E DZ Cohort Study Time Case-Control Study - DZ E E E E Time Cross-Sectional Study - E E DZ d b c a Making Group Comparisons and Identifying Associations Teach Epidemiology

253 The goal of every epidemiological study is to harvest valid and precise information about the relationship between an exposure and a disease in a population. The various study designs merely represent different ways of harvesting this information. Essentials in Epidemiology in Public Health Ann Aschengrau and George R. Seage III Making Group Comparisons and Identifying Associations Teach Epidemiology

254 254 Time Check 4:00 PM


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