teacher note: module 2 overview content area: hypothesis-testing: cross-sectional study essential...

Teacher Note: Module 2 Overview

Content Area: Hypothesis-Testing: Cross-Sectional Study

Essential Questions: How can I select groups of people and collect data/evidence from them that will test my hypothesis? If my causal hypothesis is correct, how would the exposure and outcome be distributed in these groups? Enduring Understanding: Causal hypotheses can be tested by conducting investigations of the exposures and outcomes of selected groups of people as they go about their lives. Information from these observational studies can be used to determine if an exposure and an outcome are associated. Because observational studies are complicated by factors not controlled by the observer, when an association is found, other explanations in addition to causality also must be considered.

Core Concepts:• Testing hypotheses• Association• Exposure/outcome• Control group• 2x2 table• Observational studies• Study design/study plan• Study samples• Prevalence rate• Prevalence ratio• Statement of effect

Lessons:

2-1 Looking for Associations

2-2 Cross-Sectional Studies

2-3 Developing Hypothesis and Study Questions

2-4 Respect – Part II

2-5 Planning Study Conduct

2-6 Cross-Sectional Study - In Class

2-7 Cross-Sectional Study – In School

1Lesson 2-1: Looking for Associations Revised Sept 14, 2011

Teacher Note: Enduring Epidemiological Understandings for the Epidemiology and the Energy Balance Equation Curriculum

Lesson 2-1: Looking for Associations

1. Health and disease are not distributed haphazardly in a

population. There are patterns to their occurrence that can be identified through surveillance. Analysis of the patterns of health and disease distribution can provide clues for formulating hypotheses about their possible causes.

2. Causal hypotheses can be tested by conducting investigations of the exposures and outcomes of selected groups of people as they go about their lives. Information from these observational studies can be used to determine if an exposure and an outcome are associated. Because observational studies are complicated by factors not controlled by the observer, other explanations also must be considered.

2

Teacher Note: Authentic Assessment for Module 2 of the Epidemiology and the Energy Balance Equation Curriculum

3Lesson 2-1: Looking for Associations

Students will conduct, analyze, and interpret observational, cross-sectional studies among students in their class and then among students outside their class. Working in teams, students will have the opportunity to demonstrate their abilities to select a reasonable hypothesis of interest to them, design study questions about exposure and outcome, obtain informed consent, collect and manage data, calculate and compare prevalence rates, make accurate statements about whether their data support that hypothesis, and consider alternate explanations for what they observed. Reporting of results will be required, such as a written report, an item for the school newspaper, or an oral presentation or poster for students, teachers, and/or parents. Specific performance criteria will be used to help ensure that the experiences allow a genuine, realistic, and fair assessment of students’ comprehension of the Module 2 Enduring Epidemiological Understanding.

Start of Lesson 2-1

(estimate 2 class periods)


Big Ideas in Module 1

Review

5

• Descriptive epidemiology studies patterns of health events and behaviors in populations.

• Surveys are a useful tool for assessing patterns of health behaviors in youth.

• Understanding patterns of health behaviors in youth helps to generate hypotheses to explain those patterns.

Hypotheses about

associations

Generate

Module 1 – Descriptive epidemiology: You studied patterns of disease and health-related events and behaviors, and used the information to generate hypotheses about why these patterns exist.

Test

Bridge between the Two Sides of Epidemiology


Module 2 – Analytical epidemiology: You will test hypotheses by examining potential connections (associations) between health-related exposures and outcomes.

Hypothesis

Module 1

Descriptive Epidemiology

Module 2 Analytical Epidemiology

An Example About the Energy Balance Equation

Description of the increase in teenage overweight

Description of increases in teenagers eating junk food

Hypothesis: Eating junk food

can cause teenagers to become overweight

Scientific studies of the association between

teenagers eating junk food and their weight status


Hypotheses about

associations

Generate Test

Association Found between Lack of a Good Night’s Sleep and

Obesity

What does “association” mean?


Association Found between Lack of a Good Night’s Sleep and Obesity

9

What does it mean?

Make a statement about what it means when we say that two things are associated with each other, such as in the headline, "Association Found between Lack of a Good Night’s Sleep and Obesity."


What do we mean when we say that there is an association between two things?

Associated

Tied Related

Linked

Things that are associatedare linked in some way that makes them

turn up together.

… associated with each other


Things that are associated are linked in some way that makes them turn up

together.

Things That Turn Up Together


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

Students Who Bring Their Lunch to

School Eat Less Junk Food

Higher Risk of Obesity Among Teens with More

Video-Game Playing

Breakfast Each Day May Keep Colds Away

Study Concludes: Movies Influence

Youth Smoking

Study Links Iron

Deficiency to Math

Scores

Study Links Physical Fitness to Academic Achievement

Proximity of Fast Food Restaurants to Schools and Adolescent Obesity



13

Exposures and Outcomes in Analytical Studies . . .

What kinds of exposures and outcomes are studied?

• Exposures A health-related behavior A health-related event A lifestyle or socioeconomic factor A chemical or physical exposure Psychological stress Something else with which one comes in contact

• Outcomes A health-related behavior Infectious disease Chronic disease Trauma, Injury Any other temporary or permanent health condition


How do we conduct these analytical studies?


Epidemiologists’ Laboratories


What do epidemiologists look like?

Our Epidemiology Laboratory


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 Experiments (unplanned)


18

Natural Experiments (unplanned)


Planned Observational Studies of Natural Experiments

19

An epidemiological study of a natural experiment in which the investigator is not involved in the

intervention other than to record, classify, count, and analyze results.


In-Class and In-School Observational Studies of Natural Experiments


21

Questions About Conducting Analytical Studies . . .

What kinds of skills and interests are needed to conduct analytical epidemiology studies?

• Interest in investigations and solving mysteries• Critical thinking• Analytical/mathematical skills• Enjoyment in working with people • Team player

How do analytical studies answer health-related questions?

• Collect information on exposures and outcomes from individuals in populations, in order to identify potential health-related associations


Lesson 2-1: Looking for Associations 22

Association Two things linked in some way that makes them turn up together

Hypothesis An educated guess - an unproven idea, based on an observation that can be supported or refuted through investigation

Exposure Something that impacts a person and is suspected of causing an effect; something with which a person comes in contact;

Outcome The result of an exposure

Natural Experiment 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 An epidemiological study of a natural experiment - in which the investigator is not involved in any intervention, other than to record, classify, count, and analyze results.

Review of Common Words Used in Analytical Epidemiology

23

Possible break point between class periods


The 2x2 table is a tool used to express the number of people

with and without the exposure and with and without

the outcome.

An Important Tool in Analytical Epidemiology The 2x2 Table


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


TotalOverweightNot

overweight

Eating junk food

Not eating junk food

Exposure

Outcome / Disease

a b

c d

2x2 Table

What people are in cell a?

cell b?

cell c?

cell d?


TotalOverweightNot

overweight

Eating junk food

Not eating junk food

Exposure

Outcome / Disease

c d

2x2 Table

Is there a comparison group in this 2x2 table?

If yes, where are they?


People who participate in a study and do not have the exposure of interest

People whose results are compared to the group that was exposed

Comparison Group


Exposed

Not Exposed

OutcomeNo

Outcome TotalTests hypotheses

Analytic Epidemiology

Summary So Far . . .

Includes an unexposed comparison group

Can use a 2x2 table to explore a possible association between exposure and outcome


Suicide Higher in Areas with Guns


Higher Risk of Obesity among Teens with More Video-Game Playing


Students who bring their lunch to school

eat less junk food

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


Pollution Linked with Birth Defects in US Study




a b

dc

2x2 Table

An Apple a Day Keeps the Doctor Away

Total


a b

dc

2x2 Table


An Apple a Day

Infrequent Doctor Visits

No Apple a Day

Frequent Doctor Visits Total


a b

dc

People who are not exposed

dc

2x2 Table


Total

33

An Apple a Day

Infrequent Doctor Visits

No Apple a Day

Frequent Doctor Visits


Total

a b

dc

2x2 Table



Total

a b

dc

2x2 Table


Physically Fit

Lower Grades

Higher Grades

Not Physically Fit


Total

a b

dc

People who are exposed

a b

2x2 Table


Physically Fit

Lower Grades

Higher Grades

Not Physically Fit


a b

dc

2x2 Table

Total

Kids Who Watch R-Rated Movies More Likely to Drink or Smoke


a b

dc

2x2 Table

R-Rated Movies

TotalDrink or Smoke


Do Not Drink or Smoke

No R-Rated

Movies


a b

dc

People who are exposed and have the outcome

a

Total



2x2 Table

R-Rated Movies

Drink or Smoke

Do Not Drink or Smoke

No R-Rated Movies

a b

dc

2x2 Table


Total


a b

dc

2x2 Table


Smoke

Eating Disorder

Do Not Smoke

No Eating

Disorder Total


a b

dc

People who are exposed and do not have the outcome

b

2x2 Table


Smoke

Eating Disorder

Do Not Smoke

No Eating

Disorder Total


a b

dc

2x2 Table


Total


a b

dc

2x2 Table


Family Meals

Total

Good Mental Health

Poor Mental

Health

No Family

Meals


a b

dc

People who are not exposed and do not have the outcome

d

2x2 Table


Family Meals

Total

Good Mental Health

Poor Mental

Health

No Family

Meals


a b

dc

2x2 Table

Study Links Iron Deficiency to Math Scores

Total


a b

dc

2x2 Table


Iron Deficiency

Poor Math

Scores

No Iron

Deficiency

Good Math

Scores Total


a b

dc

People who do not have the outcome and are not exposed

d

2x2 Table


Iron Deficiency

Poor Math

Scores

No Iron

Deficiency

Good Math

Scores Total


a b

dc

2x2 Table


Total


a b

dc


ObeseNot

Obese Total


2x2 Table

Fast Food Restaurant(s)

Near School

No Fast Food Restaurant(s)

Near School

a b

dc

People who do not have the outcome

d

b


ObeseNot

Obese Total

51

Fast Food Restaurant(s)

Near School

No Fast Food Restaurant(s)

Near School


2x2 Table

a b

dc

Total

Higher Risk of Obesity among Teens with More Video Game Playing


2x2 Table

a b

dc

More Video Game

Playing

Obese

Less Video Game

Playing

Not Obese Total



2x2 Table

a b

dc

ObeseNot

Obese Total

People who are not exposed and have the outcome

c


More Video Game

Playing

Less Video Game

Playing


2x2 Table

Module 2 Enduring Understanding


2. Causal hypotheses can be tested by conducting investigations

of the exposures and outcomes of selected groups of people as they go about their lives. Information from these observational studies can be used to determine if an exposure and an outcome are associated. Because observational studies are complicated by factors not controlled by the observer, when an association is found, other explanations in addition to causality also must be considered

Kid-Friendly Translation: Illness and health may be linked to one or more causes. Using groups of people, we can study possible causes related to our daily lives, such as choices about what we do, and where we live and work. When we find a link between health/illness and such a factor, it might be a causal link, but we also have to consider other explanations for the connection.

Big Ideas in Lesson 2-1

• Two things are associated when they “turn up together.”

• Epidemiologists study associations.

• Descriptive epidemiology generates hypotheses about associations and analytical epidemiology tests hypotheses about associations.

• A common way to test hypotheses is with an observational study of a natural experiment.

• The 2x2 table is a useful tool for numerically expressing associations between exposure and outcome in a group of individuals.

Re-Cap


teacher note: module 2 overview content area: hypothesis-testing: cross-sectional study essential...

Documents

crosssectional studies

associations students

causal hypothesis

design study questions

planning study conduct

developing hypothesis

causal hypotheses

reasonable hypothesis