Social Problem Analysis: Suicides from 1999 to 2016 and Beyond

To show what can be done with data collected a public source such as the Centers for Disease Control, I produced a video about suicides. Suicide has been on the public radar recently because of the scrutiny it has received in the press. And the concerns expressed in the press about the rising numbers and rate of suicide.

When I was in college, I was taught that suicide was a largely based on the victim's emotional state. That the answers of how to address it were to be found in psychology and psychiatry. That may have been true then, but the data that I analyzed, that you will see in this movie, says that suicide may now be more of a socio-economic problem.

Here is the link to the video:

You tell me what you think after you've seen it.

Firearm Deaths and the Relationship to Firearm Ownership in the United States 1999 to 2016

For those readers who live outside of the US and who follow US controversies, probably one of the most mysterious and mystifying controversies is the US focus on firearms and their value. For better or for worse, the US Supreme Court has interpreted that the Second Amendment of the Constitution states that firearm ownership is an individual right. The entire reason for existence of organizations such as the National Rifle Association (NRA) is to insure that firearm ownership be as widespread as possible.

Having said that, I'm going to get into the politics of firearms and firearm ownership. What I shall do is present the results of the analysis of data that I have collected regarding firearm deaths from 1999 to 2016. The data comes from the CDC-Wonder and from Statista.com. The data was categorized by state and the analysis was on normed data (rates and percentages, not on raw numbers).

Death by Firearm

In the United States firearm deaths fall by in large into two categories: 1) Suicides and 2) Homicides. The CDC has three additional categories: Unintentional, Undetermined and Legal Intervention/Operations of War. Firearm deaths falling into these three categories are negligible.

The overall suicide rate by firearm in the United States is 7.4 per 100,000 population. It ranges from a high of 14.0 per 100,000 (Wyoming) and a low of 1.8 per 100,000 (Massachusetts). Percent of overall suicides by firearm is 52.2%. Ranges from a high of 70.7% (Mississippi) to a low of 20.4% (Hawaii).

The overall homicide rate by firearm in the United States is 3.3 per 100,000 population. Ranges from a high of 9.8 per 100,000 (Louisiana) to a low of 0.6 per 100,000 (New Hampshire). Percent of homicides by firearm overall is 48.3%. Ranges from a high of 74.8% (Alabama) to a low of 30.5% (South Dakota).

Suicides and Homicides by Firearm: Relationship to Household Firearm Ownership

From Statista.com I was able to find by state the percent of households that own one or more guns. I was interested to determine whether or not suicides and homicides have any relationship to firearm ownership or in this case, the percentage of households in a state that own one or more firearms. The estimated per capita firearm ownership in the US is about 91%. Meaning, for every 10 people there are 9 firearms. And this does not vary widely from state to state. Firearm ownership in the US tends to be concentrated in a relatively few number of households. 

In the US the average number of households that own one or more guns is 37.6%. Ranges from a high of 57.9% (Wyoming) and a low 6.7% (Hawaii).

Relationship of Household Firearm Ownership to Suicides

I decided to examine whether or not there was a relationship between these two measures in two ways. First, determining whether there is a correlation between the two factors and second, dividing the states into two equal groups, one where the percentage of household ownership was above the median and where the percentage of household ownership was below the median and determine whether there was a significant difference in the suicide rates.

Correlations

The calculated correlation: (Pearson's r)

• Between all suicides no matter how performed (crude rate by state) and percent of households that own 1+ firearms: .67 (p < .05).
• Between crude rate (by state) of firearm suicides and percent of households that own 1+ firearms: .84 (p < .05)

People are more likely to complete a suicide attempt when they're part of a household that owns a firearm. And when that suicide is carried out by a firearm, there's even a stronger relationship between household ownership and the rate of suicide.

High and Low Household Ownership

Dividing the states into two groups of high and low household firearm ownership, I found the following

• Low household ownership suicide rate: 5.8 per 100,000.
• High household ownership suicide rate: 9.0 per 100,000
• t test significant (p < .05)

Therefore, states with a higher percentage of households that own firearms have a significantly higher rate of suicide.

Relationship of Household Firearm Ownership to Homicides

As a preview, the relationship between firearm ownership and homicides differs from what I found with suicides. I examined the data the same way as I did with the suicides and I found no relationship. 

Here are my findings ...

• Homicide rate by household ownership: Correlation, .03 (Non significant)
• High and low rates of household ownership:
• High group, 3.5 per 100,000
• Low group, 3.2 per 100,000 
• t test (non significant)

Conclusions

1. Having a gun in your household may be bad for your health. Not by the hand of another, but by your own hand. 
2. Homicides and firearms: Whether you live in a high percentage ownership state or a low ownership state, your chances of being a homicide statistic by way of a firearm are about same. 

The US has 87th highest homicide rate (out of 219) in the world. We have the 48th highest suicide rate (but we are lower than Sweden).

Comments?

remoteprogrammingguru@gmail.com

Drugs Deaths: 1999 to 2016 and Predicting Outcomes in Future Years

The Centers for Disease Control (CDC) has a comprehensive online database known as Wonder (https://wonder.cdc.gov) that is accessible to all. So if you have public health related questions, the data to answer them can be found in Wonder.

Unless you've been living under a rock, you know that deaths from drug overdoses particularly opioid related deaths have been steady increasing. I am interested in not only in the number of deaths, but the rate of increase and what that suggests for the future. I believe you will find the results of my analysis both interesting and troubling, particularly for the future.

Here's a chart showing the number deaths from 1999 to 2016:

From 1999 to 2016 the drug related deaths increased from 19,128 to 63,632. I calculated multiple trend lines. The best fitting model is the polynomial you see above (based on the R squared value, the closer to 1, the better the fit). That means that the rate of increase is accelerating.

There's a problem with using actual number of deaths when determining trends. The US population is increasing and the number of deaths does not account for that. The number of deaths provides us with an understanding of just how bad the problem is, but it's not the measure to use when constructing a predictive model.

The CDC calculates what they call a "crude rate," that is, the number of deaths in any year per 100,000. The crude rate allows use control for population growth in our analysis.

Let's look at the graph of the data using "crude rate" as the measure:

The curves are similar. The best fitting trend line is a polynomial, however it does not differ greatly from a linear trend line. Anyway you view this, the trends are concerning.

Let's use the trend line to make predictions about the future: from 1999 to 2025.

This is using the trend line equation to predict the crude rate into 2025. This shows a steady increase in the drug related death rate. With rate of increase, the number of deaths per year would exceed 100,000 per year in 2023 to 2024. If this model holds, expect at least 250,000 drug related deaths during the 2020s. However, as bad as this is, it can get worse. Consider the analysis discussed below.

The some of the earlier years may be hiding a trend line that during more recent times may be much worse. Allow me to show you:

Instead of looking at all years, I decided to look at the more recent years and determine if the trend line had developed a steeper rise in recent years. The calculated trend line from 2008 to 2016 shows a much steeper rise than the trend line calculated from 1999 to 2016. Using this calculated trend line and extrapolating to 2025, this is what appears:

Using the equation derived from the 2008 to 2016 data, the picture that arises is much more concerning. In fact the crude rate in 2025 is twice the rate predicted by the trend line equation derived from the 1999 to 2016 data. This suggests that the number of drug related deaths would be near 500,000 by the mid 2020s and that the number of drug related deaths during the 2020s would be closer to 1 million to 1,500,000 where the number of deaths per year would be no less than 100,000 and possibly up to 150,000 each year. Most of these deaths would come about as a result of opioid overdoses.

I have read reports from others who suggest that 500,000 drug related deaths for the 2020s would make for a terrible crisis. All indications are that this crisis will be far, far worse. Powerful synthetic and more deadly opioids such as Fentanyl and Carfentanil have shown increasing usage. They are cheap, easily produced and easily smuggled.

Approximately 1,264,000 soldiers have died in all of America's wars spanning the Revolutionary War, the Civil War, World War II and to today. We could see the same number of deaths or more in the 2020s large as a result of opioid overdoses.

Caveats

As a rule, the more years of data available, the more confident you can be in the results. Thus in spite of what appears to be a clear acceleration in the crude rate, one should have greater confidence in the trend line equation, our predictive model, derived from the data collected between 1999 to 2016 than the equation derived from the data collected from 2008 to 2016.

However, the data from 2008 to 2016 cannot be ignored. Although there is less of it, it is the more recent data and may be indicative of an intensification of underlying processes driving towards an increasing death rate. This is the difference between predictive and explanatory: the difference in the trend lines is only suggestive. But it's probably worth the effort to determine see if the causal forces driving a possible dramatic shift in the rate of increase have somehow changed. That is out of my area of expertise. 

So I leave that to the experts ... I'm just running the numbers. 

remoteprogrammingguru@gmail.com