1. Young Epidemiology Scholars Teaching Units Young Epidemiology Scholars Friday, June 29, 2007, 9:00 AM – Noon Mark Kaelin, EdD Montclair State University Department of Health and Nutrition Sciences College of Education and Human Services 973-655-7123 kaelinm@mail.montclair.edu

3. Pre-Workshop Assessment Young Epidemiology Scholars

4. DZ Epidemiology is … Young Epidemiology Scholars

5. Epidemiology is … … the study of the distribution and determinants of health-related states or events in specified populations and the application of this study to the control of health problems. Young Epidemiology Scholars

6. “… the blending of population thinking and group comparisons in an integrated theory to appraise health-related causal relationships characterizes epidemiology.” Epidemiology is … Young Epidemiology Scholars

7. “… the blending of population thinking and group comparisons in an integrated theory to appraise health-related causal relationships characterizes epidemiology.” Epidemiology is … Young Epidemiology Scholars

8. Top 8 Reasons to Teach / Learn about Epidemiology 1. 2. 3. 4. 5. 6. 7. 8.. Empowers students to be scientifically literate participants in the democratic decision-making process concerning public health policy. Empowers students to make more informed personal health-related decisions. Increases students’ media literacy and their understanding of public health messages. Increases students’ understanding of the basis for determining risk. Improves students’ mathematical and scientific literacy. Expands students’ understanding of scientific methods and develops their critical thinking skills. Provides students with another mechanism for exploring important, real world questions about their health and the health of others. Introduces students to an array of career paths related to the public’s health. Young Epidemiology Scholars

10. www.montclair.edu/detectives Young Epidemiology Scholars

11. http://www.cdc.gov/excite/ Young Epidemiology Scholars

12. http://www.collegeboard.com/yes/ Young Epidemiology Scholars

13. Diane-Marie St. George, Manuel Bayona, David Fraser, Mark Kaelin, Felicia McCrary, Flora Ichiou Huang, Mona Baumgarten, Chris Olsen, and Paul Stolley Young Epidemiology Scholars

15. http://www.collegeboard.com/yes/index.html Young Epidemiology Scholars

17. 26 Teaching Units Young Epidemiology Scholars

22. *

25. Assignment 3: World Trade Center & Atomic Bomb Attacks - Similarities & Differences Based on your reading of the MMWR “Surveillance for World Trade Center Disaster Health Effects Among Survivors of Collapsed and Damaged Buildings,” identify five similarities and five differences between the World Trade Center Health Registry and the surveillance system established to identify the effects of the A-bombs dropped on Hiroshima and Nagasaki (Assignment 2). Young Epidemiology Scholars

26. Scholarship Creativity Young Epidemiology Scholars

30. Enduring Understandings … the big ideas that reside at the heart of a discipline and have lasting value outside the classroom. Essential Questions … the questions, that when answered, create the enduring understandings. Content Make the content the answers to the questions. Young Epidemiology Scholars

31. Handout

37. Young Epidemiology Scholars Identifying Patterns of Health and Disease

38. Surveillance Identifying Patterns of Health and Disease The ongoing systematic collection, analysis, and interpretation of outcome-specific data for use in planning, implementation, and evaluation of public health practice closely integrated with the timely dissemination of these data to those who need to know.

39. Surveillance Identifying Patterns of Health and Disease

40. Young Epidemiology Scholars Identifying Patterns of Health and Disease

41. Descriptive Epidemiology How is the disease distributed. Who gets the disease? Where does the disease occur? When does the disease occur? Person Place Time PPT Identifying Patterns of Health and Disease

42. Epidemiological Factors PersonPlaceTime Sex Occupation Age SES Residence Events Anatomical Site Geographic Site Year Season Day, etc. Onset Identifying Patterns of Health and Disease

43. Purposes of Descriptive Epidemiology Compare trends between groups Plan health care services Generate hypotheses Identifying Patterns of Health and Disease

45. Epidemiological Factors PersonPlaceTime Sex Occupation Age SES Residence Events Anatomical Site Geographic Site Year Season Day, etc. Onset Identifying Patterns of Health and Disease

46. Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity: 1999-2000 Hidden Data Person Identifying Patterns of Health and Disease

47. Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity: 1999-2000 Person Identifying Patterns of Health and Disease

48. Epidemiological Factors PersonPlaceTime Sex Occupation Age SES Residence Events Anatomical Site Geographic Site Year Season Day, etc. Onset Identifying Patterns of Health and Disease

49. Place Identifying Patterns of Health and Disease

50. Place

51. Identifying Patterns of Health and Disease Place

52. Identifying Patterns of Health and Disease Place

53. Epidemiological Factors PersonPlaceTime Sex Occupation Age SES Residence Events Anatomical Site Geographic Site Year Season Day, etc. Onset Identifying Patterns of Health and Disease

54. Epidemiological Factors PersonPlaceTime Sex Occupation Age SES Residence Events Anatomical Site Geographic Site Year Season Day, etc. Onset Identifying Patterns of Health and Disease

55. Data shown in these maps were collected through CDC’s Behavioral Risk Factor Surveillance System. Each year, state health departments use standard procedures to collect data through a series of monthly telephone interviews with U.S. adults. Surveillance Identifying Patterns of Health and Disease

56. Obesity Trends* Among U.S. Adults BRFSS, 1985 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14%

57. Obesity Trends* Among U.S. Adults BRFSS, 1986 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14%

58. Obesity Trends* Among U.S. Adults BRFSS, 1987 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14%

59. Obesity Trends* Among U.S. Adults BRFSS, 1988 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14%

60. Obesity Trends* Among U.S. Adults BRFSS, 1989 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14%

61. Obesity Trends* Among U.S. Adults BRFSS, 1990 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14%

62. Obesity Trends* Among U.S. Adults BRFSS, 1991 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%

63. Obesity Trends* Among U.S. Adults BRFSS, 1992 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%

64. Obesity Trends* Among U.S. Adults BRFSS, 1993 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%

65. Obesity Trends* Among U.S. Adults BRFSS, 1994 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%

66. Obesity Trends* Among U.S. Adults BRFSS, 1995 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%

67. Obesity Trends* Among U.S. Adults BRFSS, 1996 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%

68. Obesity Trends* Among U.S. Adults BRFSS, 1997 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24%

69. Obesity Trends* Among U.S. Adults BRFSS, 1998 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24%

70. Obesity Trends* Among U.S. Adults BRFSS, 1999 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24%

71. Obesity Trends* Among U.S. Adults BRFSS, 2000 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24%

72. (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2001 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29%

73. (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2002 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29%

74. (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2003 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29%

75. (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2004 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29%

76. (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2005 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

77. 1995 Obesity Trends* Among U.S. Adults BRFSS, 1990, 1995, 2005 (*BMI 30, or about 30 lbs overweight for 5’4” person) 2005 1990 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

78. Young Epidemiology Scholars Identifying Patterns of Health and Disease

80. Young Epidemiology Scholars Identifying Patterns of Health and Disease

83. Young Epidemiology Scholars Identifying Patterns of Health and Disease

94. Young Epidemiology Scholars Identifying Patterns of Health and Disease

95. As a group, take the next 45 minutes to prepare to teach a 15 minute investigation to your fellow workshop participants. Have workshop participants experience part of the investigation. Talk with workshop participants about how you prepared to teach and how you decided to teach what you did. Young Epidemiology Scholars

96. Class 1 Class 2 Class 3

99. Young Epidemiology Scholars Class 1 Class 2 Class 3

102. At first glance these articles are about _____________________________ but, based on our understanding of epidemiology, we can see that they are about person, place, and time, counting, dividing, and comparing, numerators and denominators, associations, causation, confounding, prevention, and policy. a Bausch & Lomb lens solution Young Epidemiology Scholars

103. At first glance these articles are about _____________________________ but, based on our understanding of epidemiology, we can see that they are about person, place, and time, counting, dividing, and comparing, numerators and denominators, associations, causation, confounding, prevention, and policy. E. Coli and spinach

104. At first glance these articles are about _____________________________ but, based on our understanding of epidemiology, we can see that they are about person, place, and time, counting, dividing, and comparing, numerators and denominators, associations, causation, confounding, prevention, and policy. To understand something as a specific instance of a more general case … is to have learned not only a specific thing but also a model for understanding other things like it that one may encounter. J. Bruner, The Process of Education, 1960 Understanding Young Epidemiology Scholars

105. Give people fish, they have food for a day, Teach people how to fish, they have food for a lifetime. Young Epidemiology Scholars

106. EEP students, Khadijah Hunter, Jared Turner, and Danielle McAllister, ask students at Rosa Parks High School what they think epidemiology is. What would your answer have been when you were in high school? Young Epidemiology Scholars

107. www.epiedmovement.org Young Epidemiology Scholars

108. YES Teaching Units Professional Development Workshop “… a professional community that discusses new teacher materials and strategies and that supports the risk taking and struggle entailed in transforming practice.” Young Epidemiology Scholars

109. Post-Workshop Assessment Young Epidemiology Scholars

110. Young Epidemiology Scholars Teaching Units Friday, June 29, 2007, 9:00 AM – Noon Mark Kaelin, EdD Montclair State University Department of Health and Nutrition Sciences College of Education and Human Services 973-655-7123 kaelinm@mail.montclair.edu Thank You Young Epidemiology Scholars