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

Pre-Workshop Assessment Young Epidemiology Scholars

DZ Epidemiology is … Young Epidemiology Scholars

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

“… 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

“… 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

Top 8 Reasons to Teach / Learn about Epidemiology 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

Young Epidemiology Scholars

Young Epidemiology Scholars

Young Epidemiology Scholars

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

Young Epidemiology Scholars

26 Teaching Units Young Epidemiology Scholars

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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

Scholarship Creativity Young Epidemiology Scholars

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

Handout

Young Epidemiology Scholars Identifying Patterns of Health and Disease

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.

Surveillance Identifying Patterns of Health and Disease

Young Epidemiology Scholars Identifying Patterns of Health and Disease

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

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

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

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

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

Estimated Prevalence of Recent Illegal Drug Use by Race / Ethnicity: Person Identifying Patterns of Health and Disease

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

Place Identifying Patterns of Health and Disease

Place

Identifying Patterns of Health and Disease Place

Identifying Patterns of Health and Disease Place

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

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

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

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

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

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

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

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

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

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%

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%

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%

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%

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%

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%

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%

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%

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%

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%

(*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%

(*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%

(*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%

(*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%

(*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%

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

Young Epidemiology Scholars Identifying Patterns of Health and Disease

Young Epidemiology Scholars Identifying Patterns of Health and Disease

Young Epidemiology Scholars Identifying Patterns of Health and Disease

Young Epidemiology Scholars Identifying Patterns of Health and Disease

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

Class 1 Class 2 Class 3

Young Epidemiology Scholars Class 1 Class 2 Class 3

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

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

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

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

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

Young Epidemiology Scholars

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

Post-Workshop Assessment Young Epidemiology Scholars

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 Thank You Young Epidemiology Scholars