Skip to main content

Charting Death and Thinking about Epidemics

What are the leading causes of death in the United States?

Based on what you have read or learned from news sources, what did you expect to see in the top five? If you thought of one that is missing, perhaps it is in the top 10. Still, when you look at the numbers, you may be surprised to learn how few people die in a given year, given the size of the US population.

My point in this post is that we ought to examine total data instead of being guided by the headlines of news stories and misleading charts when we want to understand a health or social condition.

According to the Centers for Disease Control and Prevention, the five leading causes of death in 2017 were heart disease, cancer, unintentional injury, chronic lower respiratory disease, and stroke. The report includes more causes, but I chose the top five based on the deaths per 100,000 U.S. standard population.

When you add the numbers for the five causes, you find the top five causes of death accounted for 445 people out of 100,000 people. Thus, less than 1% of the population died from the top five causes.

The chart illustrates a helpful way to report data. Instead of reporting percentages, just give the numbers of people for any condition in relationship to a population value. In this case, the relevant population value is Americans (actually an estimate of the U.S. population based on the 2010 census).

It is usually better to report data in terms of how many people with a condition out of 100 people, but as you can see, out of a sample of 100 people, we might have no dead people! And, fewer than 2 people died of these causes out of 1,000 people! So, it is important to select a population size that makes sense in terms of all the available data.

About Totals

I would like to know how many people died in the United States. It just seems to make sense. If you are going to tell me how many people died out of some portion of the population, why not tell me the total figure?

Interestingly, there is a total death figure for 2016, which is 2,744,248. That gives us a death rate of 849.3 people out of 100,000 population. The total population estimate for 2016 is 323,071,342. So, less than 1% of the population died in 2016.

I would also like to know how many people died out of 100,000 people in 2017. The online figure is 731.9 per 100,000 so I will fix that fraction of a person and say 732 people out of 100,000. The 2018 CDC report tells us that 2,813, 503 deaths were registered. I see that they only know about registered deaths. Presumably, people could die and not be registered. so, it is good to pay attention to the details.

They don't tell us how many people are in their estimate of the population-- the last census was in 2010. But they did write that they estimated the 2017 population based on 2010 census data. I did a search and found a census table estimate for 2017 = 327, 147, 121, according to the website.

The statisticians are pretty good, but it is important to know that we are dealing with estimates. We really don't know how many people died in the USA in 2017. Still, I bet the numbers are good estimates.

I don't require absolute certainty when it comes to data about human beings. Anyway, if you are interested, you could estimate the number of people who died in 2017 or, you can wait until the data are provided.


Another useful lesson to note here is the lack of scary headlines. We just have the facts reported in a responsible way. There are no news media telling us about this epidemic or another in an effort to sell a story.

We know that less than 1 out of 100 people died in 2016 (849 out of 100,000 rounded). If a person had 1,000 friends on social media then, 8 or 9 might have died if, and only if, the friends were similar in age and other relevant variables to people in the general U.S. population. My guess is, any friendship group probably does not represent a proportionate sample of the US population so, we will need to be careful in generalizing about all people based on our friendship groups.

It is truly sad for loving family members when people die of any cause. When we look at the total population, we see that even for the leading causes, not many of us die every year. Of course, healthcare personnel and other decision-makers ought to pay attention to trends--especially when we can do something about a particular cause of death.

If you were going to write that we have an epidemic based on the number of people dying, what figure would you say is worthy of the term epidemic? The dictionaries are not helpful because they refer to an epdemic as a "widespread" problem such as a disease. Truly, 1% of almost 330 million people is a lot of human beings. The number of people who did not die is of course the reverse so, more than 99% did not die.

We are wise to keep total figures in mind when we want to truly understand the scope of a particular cause of death or other social concern.


The death rate increased 100% when two people die this year compared to one person who died last year.

Perhaps you already know this? It is a deceptive practice. Suppose one person died after taking drug XYZ this year. Then, next year two people died after taking the same drug. Two people out of thousands or millions is a very small number, but the increase in deaths equals 100%! We do not know how many people took drug XYZ and are living quite happily! It's good to be careful how people are reporting data. We really need to know all the relevant data when making informed decisions.

Read more about Creating Surveys

Read more about Applied Statistics


Corrections and helpful comments are welcome.


My Page

My Books  

 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

Publications (many free downloads)
  Academia   Geoff W Sutton   (PhD)
  ResearchGate   Geoffrey W Sutton   (PhD)


Popular posts from this blog

Personal Self-Concept Questionnaire (PSQ)

  The Personal Self-Concept Questionnaire  ( PSQ )   Overview The Personal Self-Concept Questionnaire (PSQ) measures self-concept based on ratings of 18 items, which are grouped into four categories: Self-fulfilment, autonomy, honesty, and emotional self-concept. Subscales : The PSQ has four subscales 1. Self-fulfilment (6 items) 2. Autonomy (4 items) 3. Honesty (3 items) 4. Emotional self-concept (5 items)  👉 [ Read more about Self-Concept and Self-Identity] The PSQ is a Likert-type scale with five response options ranging from totally disagree to totally agree. Reliability and Validity In the first study, coefficient alpha = .85 and in study two, alpha = .83. Data analysis supported a four-dimensional model (see the four categories above). Positive correlations with other self-concept measures were statistically significant. Other notes The authors estimated it took about 10 minutes to complete the PSQ. Their first study included people ages 12 to 36 ( n = 506). In the second s

Student Self-Efficacy

  Assessment name:  STUDENT SELF-EFFICACY SCALE * Note. This post has been updated to provide an available measure of student self-efficacy. ———- Scale overview:  The  student self-efficacy scale i s a 10-item measure of self-efficacy. It was developed using data from university nursing students in the United States. Authors: Melodie Rowbotham and Gerdamarie Schmitz Response Type:  A four-choice rating scale as follows: 1 = not at all true 2 = hardly true 3 = moderately true 4 = exactly true   Self-efficacy is the perception that a person can act in a way to achieve a desired goal.  Scale items There are 10 items. Examples: I am confident in my ability to learn, even if I am having a bad day. If I try hard enough, I can obtain the academic goals I desire.   Psychometric properties The authors reported that their sample scores ranged from 25 to 40 with a scale mean of 34.23 ( SD  = 3.80. Internal consistency was high at alpha = .84. The authors reported the results of a principal compon

Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ)

  Scale name: Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ) Scale overview: The Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ) is a 29-item self-report measure of both mathematics self-efficacy and mathematics anxiety. Author: Diana Kathleen May Response Type: Items are rated on a 5-point Likert-type scale following a “no response” option: 1 = Never 2 = Seldom 3 = Sometimes 4 = Often 5 = usually Sample items 1. I feel confident enough to ask questions  in my mathematics class. 6. I worry that I will not be able to get a  good grade in my mathematics course.   Subscales and basic statistics for the MSEAQ       Self-Efficacy M = 44.11, SD = 10.78, alpha = .93       Anxiety M = 46.47, SD = 12.61, alpha = .93       Total Scale M = 90.58, SD = 22.78, alpha = .96 Reliability: See the Cronbach’s alpha levels reported above. Validity: There were significant positive correlations with similar measures. The results of a Fa