Day 3 Prevalence 1 Continuing with Tools for

Day 3 Prevalence 1

Continuing with Tools for Doing the Study On an average school day, how many hours do you watch TV? ✔ From questions to answers A. I do not watch TV on an average school day ✔ From answers to counts B. Less than 1 hour per day C. 1 hour per day From counts to prevalence D. 2 hours per day E. 3 hours per day F. 4 hours per day From prevalence to statements G. 5 or more hours per day 2

Continuing with tools for doing a study ✔What are you curious about? ✔From curiosity to a hypothesis ✔From a hypothesis to questions ✔From questions to answers ✔From answers to counts From counts to prevalence From prevalence to statements Interpretation – Conclusions - Communication 3

Three main tools 4

Review - Tool # 1 1. Cross-sectional study design: a relatively quick way to test a hypothesis a d e l l ca dy s e tim e stu e m nc So e l a prev An observational study A sn apsh ot of w is go hat ing o n One poi nt in time 5

Review - Tool # 2 2. Contingency table: puts numbers in a table so we can get from answers to counts e r osu p x s e ome w o tc Sh u o and The table simples t is th e 2 x table 2 Handy for calculations Everyon e is in the table somewh ere 6

Tool # 3 3. Prevalence – calculations to quantify outcomes in populations; prevalence ratios (comparisons) provide a measure of association between exposure and outcome s a ted or a l lcu tion a C rac ge a f t a cen per Eve out ryone com wit and e – h the lon rece g-te nt rm Especially used in cross-sectional studies 7

From Epi Textbooks The main outcome measure obtained from a cross-sectional study is prevalence. A cross-sectional study is sometimes called a prevalence study. 8

Prevalence The number of people with a specified condition or event, among a specified population and at a specified time The proportion of a population found to have a condition (typically a disease such as diabetes or a health-related behavior such as smoking or seat-belt use) 9

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Express it in numbers The Numerator is the number of people in the population or sample who experienced the outcome or effect, in this case, wearing blue. The Denominator is the total number of people in the population or sample, in this case, total number of students in the class. 11

Prevalence of wearing blue Numerator The number of students who are wearing blue Denominator All the students in the class 12

Prevalence of wearing blue # in class x 100 = % wearing blue = Prevalence 13

Prevalence of wearing glasses Numerator The number of students who are wearing glasses Denominator All the students in the class 14

Prevalence of wearing glasses # wearing glasses # in class x 100 = % wearing glasses = Prevalence 15

Numerator The number of students who had cereal for breakfast Denominator All the students in the class 16

Numerator The number of students who walked to school Denominator All the students in the class 17

Numerator The number of students who. . . ? Denominator All the students in the class 18

Prevalence Ratio A comparison of two prevalences Calculated by dividing the prevalence of the outcome in the exposed by the prevalence of the outcome in the unexposed a/(a+b) divided by c/(c+d). 19

High school students who send more text messages/day are more likely to binge drink compared to students who send fewer text messages/day. Binge drinker Hypertexter Not a hypertexter Not a binge drinker 30 70 Total 100 Prevalence Ratio Prevalence 30 % 100 a b 1. 4 c d 88 312 400 88 22 % 400 a c a+b ÷ c + d People who ______________________ are ______ times as likely to ________________ compared to people who _________________ 20

High school students who send more text messages/day are more likely to binge drink compared to students who send fewer text messages/day. Binge drinker Hypertexter Not a hypertexter Not a binge drinker 30 70 Total 100 Prevalence Ratio Prevalence 30 % 100 a b 1. 4 c d 88 312 400 88 22 % 400 Hyper-texters are 1. 4 times as likely to binge drink than those who are not hyper-texters. 21

Interpretation of Prevalence Ratios Results Interpretation Prevalence Ratio POSITIVE ASSOCIATION - the prevalence Above 1. 0 rate among the exposed group is greater than the prevalence rate among the unexposed group 22

Teenagers who are not restricted from watching R-rated films are more likely to try smoking compared to teenagers who have restrictions on watching R-rated films. Tried smoking No restriction Partial or complete restriction Did not try smoking 656 771 Total 1427 Prevalence Ratio Prevalence 656 46 % 1427 a b 3. 5 c d 413 2704 3117 413 13% 3117 a c a+b ÷ c + d People who ______________________ are ______ times as likely to ________________ compared to people who _________________ 23

Teenagers who are not restricted from watching R-rated films are more likely to try smoking compared to teenagers who have restrictions on watching R-rated films. Tried smoking No restriction Partial or complete restriction Did not try smoking 656 771 Total 1427 Prevalence Ratio Prevalence 656 46 % 1427 a b 3. 5 c d 413 2704 3117 413 13% 3117 Teenagers who have no restrictions on watching R-rated films are 3. 5 times as likely to try smoking as those who have restrictions. 24

Interpretation of Prevalence Ratios Results Interpretation Prevalence Ratio POSITIVE ASSOCIATION - the prevalence Above 1. 0 rate among the exposed group is greater than the prevalence rate among the unexposed group 25

Students living in urban areas engage in more experimenting with prescription drugs than students living in rural areas. Did not Did Experiment experiment Urban 95 905 Total 1000 95 Prevalence Ratio 9. 5 % 1000 a b Rural Prevalence 0. 73 c d 130 870 1000 13. 0 % 1000 a c a+b ÷ c + d People who ______________________ are ______ times as likely to ________________ compared to people who _________________ 26

Students living in urban areas engage in more experimenting with prescription drugs than students living in rural areas. Did not Experiment experiment Urban 95 905 Total 1000 95 Prevalence Ratio 9. 5 % 1000 a b Rural Prevalence 0. 73 c d 130 870 1000 13. 0 % 1000 Students in urban areas are 0. 73 times as likely to experiment with prescription drugs than students in rural areas. 27

Interpretation of Prevalence Ratios Results Interpretation Prevalence Ratio POSITIVE ASSOCIATION - the prevalence Above 1. 0 rate among the exposed group is greater than the prevalence rate among the unexposed group 28

Interpretation of Prevalence Ratios Results Interpretation Prevalence Ratio POSITIVE ASSOCIATION - the prevalence Above 1. 0 rate among the exposed group is greater than the prevalence rate among the unexposed group Prevalence Ratio NEGATIVE ASSOCIATION the prevalence Below 1. 0 rate among the exposed group is lower than the prevalence rate among the unexposed group 29

Interpretation of Prevalence Ratios Results Interpretation Prevalence Ratio POSITIVE ASSOCIATION - the prevalence Above 1. 0 rate among the exposed group is greater than the prevalence rate among the unexposed group Prevalence Ratio NEGATIVE ASSOCIATION the prevalence Below 1. 0 rate among the exposed group is lower than the prevalence rate among the unexposed group Prevalence Ratio NO ASSOCIATION – the prevalence rate At or Near 1. 0 among the exposed group is similar or the same as the prevalence rate among the unexposed group • A prevalence ratio of 1. 1 is a weak positive association, while a prevalence ratio of 3. 1 is a strong positive association • A prevalence ratio of 0. 95 is a weak negative association, while a ratio of 0. 45 is a strong negative association 30

Results from some Epi Teams in Paterson NJ Epi Stars - Drinking at least 2 cans or a 20 -ounce bottle of non-diet soda every day leads to a crash (feeling tired) - PR = 2. 5 Pop Science – A healthy breakfast is associated with playing in an organized sport - PR = 0. 96 Hypertensions – Receiving a daily, weekly, or monthly allowance is related to eating junk food/unhealthy food more than twice a day - PR = 1. 6 Dr. Observation – Healthy eating (at least 2 servings of fruit and vegetables a day) results in better grades (“doing well in school”) - PR = 1. 0 31

Quick Summary of Cross-Sectional Study Calculations • Questions about exposure and outcome are answered simultaneously. • Answers on exposure and outcome can be put into a 2 x 2 table. o A “yes/no” answer will fit o If using a multiple choice question, a predetermined “cut point” is needed to define a “higher/lower” range to fit into a 2 x 2 table. • Counts in the 2 x 2 table allow calculations of prevalence • Comparisons of prevalences (prevalence ratio) allows a statement about the association between exposure and outcome. 32

Measure of Risk The prevalence ratio (PR) is a measure of risk used in cross-sectional studies. It compares prevalence in the exposed to prevalence in the unexposed. A ratio of 1. 0 denotes no difference between the two groups. Examples Interpreting PR and Confidence Intervals No difference between exposed and unexposed Prevalence Ratio

Breakout Assignment Prevalence 34

Perform a few practice calculations as needed 35

Deck Worksheet – page 2 Calculate the prevalence of the outcome – for the exposed group and for the unexposed group. Calculate the prevalence ratio. Populate the 2 x 2 table on page 1 with the above information. Make a statement that uses the prevalence ratio to describe size of the association. 36

Study Proposal: Section 6 6. Data Analysis Plan 6 a. Contingency Table 6 b. Prevalence among exposed 6 c. Prevalence among unexposed 6 d. Prevalence Ratio 6 e. Statement of results 6 f. How prevalence ratio will be used in your study 37