流行病学通常被称为公共卫生的“基石”，它是一门研究疾病的分布和决定因素，健康状况，或人群间的活动和应用于控制健康问题的学科。由于流行病学与现实生活息息相关，并更好地评估公共卫生项目和政策，学生将理解流行病学的研究方法，通过这一门课所学到的理论知识应用到当今的公共健康问题。本课程通过流行病学的视框，探讨了心血管疾病和传染病等公共卫生问题，对地区情况和全球情况都进行了讨论。 翻译: Yi Zhou

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來自 The University of North Carolina at Chapel Hill 的課程

流行病学：基础公共卫生科学

1344 個評分

流行病学通常被称为公共卫生的“基石”，它是一门研究疾病的分布和决定因素，健康状况，或人群间的活动和应用于控制健康问题的学科。由于流行病学与现实生活息息相关，并更好地评估公共卫生项目和政策，学生将理解流行病学的研究方法，通过这一门课所学到的理论知识应用到当今的公共健康问题。本课程通过流行病学的视框，探讨了心血管疾病和传染病等公共卫生问题，对地区情况和全球情况都进行了讨论。 翻译: Yi Zhou

從本節課中

Understanding Measures of Disease Frequency

This module introduces measures of disease frequency.

- Dr. Karin YeattsClinical Associate Professor

Department of Epidemiology, UNC Gillings School of Global Public Health - Dr. Lorraine AlexanderClinical Associate Professor, Director of Distance Learning (North Carolina Institute for Public Health)

Department of Epidemiology, UNC Gillings School of Global Public Health

[NOISE].

In this segment, we are going to talk about the

measure of health outcome occurrence or disease known as odds.

[MUSIC]

In this segment we will have the following learning objectives.

They include both defining and calculating the measure of odds.

Knowing when to choose the measure of odds for the appropriate situation.

And interpreting odds within the context of public health research.

In statistics, we refer to odds as the

ratio of the probability that an event, such

as a disease, will occur, to the probability

that the event, or disease, will not occur.

Odds are sometimes used in epidemiology to their convenient mathematical properties.

We will use p as the symbol for a probability.

The mathematical formula for odds is p divided

by the quantity 1 minus p. You may be wondering why we use the

odds as a measure, since we already have other measures to use in epidemiology.

Such as prevalence, risk, and rate.

Odds are easy to calculate and interpret.

Odds tend to have more meaning

to clinicians and lay-people compared to rates.

The use of odds can be used to provide

information to patients in clinical settings

since odds can be easily understood.

In addition, later in this course, you will learn about why the

measure of odds is important in certain studies, such as case control studies.

Sometimes we are not able to access or collect risk or rate data,and odds data

are our only feasible option. Now that you've been given a definition

of odds, let's go through a few examples. Here again is the formula for odds.

And you've been given the probability of an event is 0.20.

Then let's calculate the odds using this formula.

So the numerator will be 0.20, and then you will

divide it by the quantity 1 minus 0.20, which gives

you 0.25. Or you can have the ratio, constructed

as the ratio 1:4. Let's try another example.

If the probability of diabetes in a patient is 5%,

then the odds of diabetes are, let's plug 0.05 into

our formula. So you get p, or 0.05,

divided by 1 minus 0.05, or

0.052632. To get a more easily understood ratio,

you can then divide both sides by 0.05 to get a 1 to 19 ratio.

Let's try a third example. Out of 100 births, the probability

of having a boy is 51%, while the probability of having a girl is 49%.

So to calculate the odds, you would take p, which is 51, and divide

it by the probability of having a girl, which is 1 minus p, or 49.

And this gives

you the odds of 1.04.

Now we'll give you the opportunity to try it on your own.

This concludes this segment on the measure of

health outcome occurrence or disease occurrence known as odds.

So to summarize what we covered in this segment.

We learned how to define and calculate the measure of odds,

choose the measure of odds for the appropriate situation, and interpret

the odds within the context of public health research.

[MUSIC]