Homicide rates: are they more effected by violence in general, or just gun violence?
This is a much more comprehensive, in-depth, larger sample-sized version of a recent post I wrote about the same topic. That analysis was very preliminary. I only had 15 cities in the data and there was a certain other statistical problem I didn't take into account.
I felt rushed to make it because I came across a post on Reddit. It was on r/dataisbeautiful and it had a few maps that correlated homicide with poverty and de-correlated homicide with gun ownership rates or something like that. I saw it x-posted to a subreddit I followed, which was a subreddit about guns. So it was used as a statistical basis to say something like: guns don't cause violence; guns aren't correlated to violence at all; poverty is the correlate, not guns, etc., and it had a lot of thumbs ups, a lot of support in the comments and zero push-back.
I saw this Reddit post around the time I had recently finished my most recent analysis of crime at the neighborhood level. Based on the data I was seeing during that analysis, I made a hypothesis that the amount of violence that uses a gun is an even more significant factor to homicide rates than total violence in general.
So I did a quick analysis and yeah, it seemed that gun violence correlated more with homicide than all-type violence. But I didn't wanna post that post anywhere because it was like, I didn't have much cities, it was a small sample size.
The genesis of this hypothesis
I may as well write about how I generated this hypothesis in the first place.
I came to this hypothesis because I was comparing neighborhoods in St. Louis and Winnipeg, and there was a lot of similarities between the worst neighborhoods in these cities with things like their robbery rates and aggravated assault rates, rates that we didn't see in any of the other cities I had data for. These two cities had uniquely high peaks for robbery and aggravated assault. But St. Louis was the only city that had uniquely high peaks for homicide.
So this made me scratch my head a bit... and think. I knew there was a lot of gun violence in St. Louis and I knew that generally speaking, there's not much gun violence in Canada. So my basic instinct told me that: the reason there is a discrepancy between homicide rates in these two cities' worst neighborhoods when the aggravated assault rates are equal is due to the difference in weapon choice or weapon tendencies.
So for example, when we look at the neighborhoods in St. Louis and Winnipeg that have an aggravated assault rate between 3,000 and 3,300 per 100,000 people, the average homicide rate in these St. Louis neighborhoods was 223.1, where in Winnipeg's it was 81.8.
So from this statistic, there's a couple different hypothesis we can generate. One would be the one I just stated about weapon tendencies. Another one someone might suggest is: well maybe that they just have stricter standards for aggravated assaults in St. Louis. But this doesn't seem to be the case, and actually it might even be the opposite, if we reason from looking at the other violent crimes in these same neighborhood groupings. For example, in these same Winnipeg neighborhoods, the average robbery rate was 1619.2, whereas in St. Louis's it was 806.3. For sexual violence, it was 525.6 in Winnipeg's whereas it was 197.7 in St. Louis's.
Furthermore, Winnipeg neighborhoods with a homicide rate between 90 to 140 per 100,000 residents on average had a robbery rate of 1654.6, sexual violence of 539.7 and aggravated assault of 3910.4. St. Louis's neighborhoods with the same homicide rate range had the following average rates: 583.2, 178.6 and 2064.8.
Lastly, between 2019 and 2021, 87.7% of major assaults in Winnipeg were stabbings, which only leaves 12.3% for all other types of weapons like guns, blunt objects and hands. In 2021 in St. Louis, 19.6% of aggravated assaults involved no weapon. So, I could dismiss the hypothesis that St. Louis's police force has more strict aggravated assault standards than Winnipeg's. The only other hypothesis that remained was the weapon tendency factor. So it was time to explore it.
Where the data is from
The data I'm using for this analysis is from the FBI's Crime Data Explorer for the year 2021.
Now, I tried to get data for every single American city that has over 100,000 people, but there are two different report types that police departments send to the FBI. Their original system was the SRS system, or the Summary Reporting System. And this system doesn't have the level of detail that is required to do the analysis I'm doing here because the SRS basically just shows the number of incidences for major crimes like rape, homicide, burglary and so on. They don't have any other details, like the weapon used, the location (ie: gas station, hotel, house), the relationship between the victim and perpetrator, and so on.
The other system that the FBI has is the NIBRS, which stands for National Incidence Based Reporting System, and this is the new and improved system. It's been in existence for a couple decades but recently in 2021, a lot of cities started to send these reports instead of the SRS. With that being said, a lot of police departments still only send that SRS data. So basically, if there's a city of 100,000 that you don't see in the data, it's because they did not have that sweet sweet NIBRS data. There were a lot of trends by state. So for example, California and Florida were examples of states where most of their cities did not send NIBRS styled data. So even though California has over 70 cities with over 100,000 people, only 6 of these cities actually use the NIBRS system.
And that's not the only thing that disqualified certain cities from being included in the analysis here.
One problem with the data
Something I noticed about the data was how much the percentage of aggravated assaults that had a stated weapons and an unstated weapons varied by city. To explain what this means, I will give an example. There were 3,942 aggravated assaults in Indianapolis, but only 3,180 stated the weapon used to perpetrate that aggravated assault: gun (1,795), knife (474), blunt object (324), hands (494), other (93). That leaves 762 aggravated assaults with an unstated weapon, and an "unstated %" or "N/A %" of 19.3%. These ranges varied a lot. The city with the highest unstated % was 52.9% in Columbus, GA.
This is a problem. We cannot model or estimate the total number of say, shootings in a city, based off of the percentage of aggravated assaults that used a gun among "weapon-stated" aggravated assaults, because it's very possible that certain weapons have higher "stated rates" than others. For example, what I would think to be the case is that often times, it was unstated when "personal weapons" (no weapon, ie: hands, feet, teeth, nails, headbutts, etc.) were used. Likewise, I would think that with guns and knives, like if an assault is a shooting or a stabbing, in most cases that that would be included in the report and stated. And so it's not reasonable and it would possibly heavily skew the data and make it very muddy if I said, "okay well, 50.6% of the aggravated assaults in Little Rock use guns. Therefore, 50.6% of the unstated aggravated assaults should be allocated to the gun column". For context, there were 1,358 aggravated assaults that had unstated weapons, so if I modelled it, I would add roughly 700 extra shootings to the data of Little Rock. And I just can't do that because it could be the case that most of the unstated aggravated assaults are just "strongarm assaults".
It's also not super great to put in the same correlation graph / table a city with an unstated % of 40.2% and one with a unstated % of 2.2%. This would also heavily skew the data because only 59.8% of aggravated assaults are allocated to a specific weapon in the first city while 97.8% of aggravated assaults are allocated to a specific weapon in the second city. The data for city #1 possibly underrepresents the weapons a lot. Thus, the stats might say that city #2 has more stabbings than city #1, but if city #1 had an unstated % of only 2.2% as well, then the stats might show that city #1 has more stabbings than city #2.
So to deal with this problem, I made certain groupings based off of the unstated %. This should deal with any skew that might result from what I just wrote above. It might not actually end up creating a skew, but we want to be as precise as possible. The groupings I made were: 0% to 9.9%, 10% to 14.9% and 15% to 19.9%. I would've split the first group into two groups: 0.% to 4.9% and 5% to 9.9%, but there weren't enough cities in these two ranges, the sample size was too small, so I combined them into one larger group. I threw out all of the cities that had an unstated % of 20% or over: wanting to be as accurate as possible while still having a large enough sample size to work with. This leaves us with 82 cities.
All of this data can be found here in a PDF chart or here in a spreadsheet file.
Data #1: homicide vs. aggravated assaults by weapon
The tables below show the aggravated assaults by the weapon used and then correlates each of these statistics with homicides. Know that "shooting" means aggravated assault with a gun, "knifing" means aggravated assault with a knife, "clubbing" means aggravated assault with a blunt object, and "beating" means aggravated assault without any weapon. Furthermore, "all-weapon" means all aggravated assaults that used a weapon. I explain more about the importance of this category later on in the article.
I present this data within the groupings I mentioned earlier. So we can see that in the 0% to 9.9% group, shootings correlate with homicide with a 0.68 Pearson correlation coefficient, whereas total aggravated assaults is just 0.44, 0.52 for knifing, 0.28 for blunt objects, 0.16 for personal weapons and 0.53 for all weapons.
Quick pit-stop: the correlation coefficient quantifies linear correlation. A score of 1.0 means a perfect correlation, and this score goes all the way down to -1.0 The closer to 1.0 the number is means the better the correlation is. -1.0 means there is a negative correlation and the closer to 0.0 means the weaker the correlation is (or if there is no correlation at all).
For the next group, 10% to 14.9%, we have 0.85 for shootings, 0.56 for knives, 0.47 for clubbing, 0.37 for beatings, 0.69 for total aggravated assaults and 0.76 for assaults with weapons.
For the last group here, 15% to 19.9%, we have 0.85 for shootings, 0.29 for knifing, 0.32 for blunt objects, 0.25 for personal weapons, 0.66 for total aggravated assaults and 0.60 for assaults with weapons.
Then if we make all three of these groups into one mega group: 0% to 19.9%, we would have the following correlation coefficients: 0.80 for shootings, 0.40 for knifing, 0.30 for blunt objects, 0.22 for personal weapons, 0.60 for total aggravated assaults and 0.67 for assaults with weapons.
Below is a graphical representation I call color ribbons. I used these in a recent post I wrote, you can get more explanation on them there, but basically they assign colors to numerical values which are represented as bars in big vertical stacks of these colored bars. In the color ribbons below, the darker the red, the higher the number. In this case, the numbers are rates of certain types of violence (ie: shootings, beatings, homicides, etc.).
I like using this visualization to show correlation because looking at scatter plots can be very overwhelming if there is a lot of data on it. Even with a strong correlation, the scatter plot dots don't line up perfectly. It can even be hard to tell the difference between a correlation coefficient of say 0.75 and 0.60 to the untrained eye. With these color ribbons, I find it's much easier to distinguish between smaller correlation differences, such as a 0.75 correlation and a 0.60 correlation, and thus it makes it easier to present the difference in certain correlates.
All of the ribbons are ordered vertically by city via its homicide rate. Basically what this means is that the homicide rate ribbon goes from the lowest homicide rate to the highest homicide rate, and that order of cities does not change in any of the other ribbons. For example, the city with the lowest homicide rate here is Provo, Utah, so that's the first / the top colored bar in the homicide ribbon, and therefore it is the first bar in every other ribbon. Baton Rouge has the highest homicide rate of the cities here, so it's the last / bottom bar in each of the ribbons. So even though Baton Rouge does not have the highest knifing rate of the cities here, it's still the last bar on the knifing ribbon because it's the last bar on the homicide ribbon. The homicide ribbon determines the city order for all of the other ribbons!
This will help us look at correlation better. Basically what we're looking for is which ribbon looks the smoothest next to the homicide ribbon, the most gradual change from white to dark red.
We can see that the shooting ribbon has smoothest transition of all them. It transitions the most seamlessly, whereas the other ones all look more like barcodes than gradients.
The main takeaway here is that gun violence correlates with murder significantly more than violence in general. In other words: the weapon used to perpetuate the violence is a more significant factor than the how frequent the violence is in regards to homicide rates.
Data #2: kill percentage by weapon
If we tally all of the aggravated assaults by weapons and the homicides by weapon, we can get a kill percentage by weapon. We take the number of homicides and divide that by the total number of homicides and aggravated assaults together per that weapon and multiply that by 100: # of hom. w/ gun รท (# of hom. w/ gun + # of ag. as. w/ gun) x 100 = kill percentage of guns. As we can see in the table below, the kill percentage for a gun is 7.08%, 1.22% for knives, 0.54% for blunt objects and 0.49% for personal weapons.
Caveat here! This is not the actual lethality rate for personal weapons... or any other weapon either. Let me quickly explain how aggravated assault classification works. There are two things to note here.
Any attempt or potential to harm someone with a deadly weapon is considered to be an aggravated assault. So if you point a gun at someone and there's a legitimate chance that you will shoot them, even if you never fire the gun, or if you fire and miss, that's aggravated assault. Same with a knife. If you have a knife in your hand and you try to swing at someone, and they dodge it and run away, that's considered to be an aggravated assault. With crime statistics, it's about the consequence of what could have happened. These tend to be different legally, but insofar as statistics goes, they are one in the same.
The best example to explain this logic is with robbery. The goal of crime statistics is to quantify the amount of violence in an area: relevant for safety statistics and also so that law enforcement can get a general idea of how much crime is going on to guide them on budgetary matters. In this sense, an attempted robbery and an actual robbery indicate the same thing.
So let's say you're a professional UFC fighter. Someone tries to rob you. Let's say they try to strongarm rob you, which means without a weapon. And the person who tries to strongarm rob you is a big guy. He's taller than you. He's more muscular than you. So he tries to rob you, but you're a professional UFC fighter and you kick the feces, dung, doodoo, poo and poop outta him. So he didn't rob you. He tried to. But that's still considered a robbery, and the reason is because if it were another person in that circumstance, they probably would've gotten robbed.
The same thing could be said about a burglary. For example, someone smashes your window and goes into your house. But oh wait, you have a huge aggressive loud barking dog and they run out and they don't steal a thing. Well, if the house they broke into didn't have a big dog, then their stuff would've gotten stolen.
So that's caveat number one. The point here is to say, the kill percentages with weapons are higher than these figures indicate because a lot of these aggravated assault incidences are examples like I just stated: someone pointed a gun at someone, or someone shot but missed. Or someone threw a hammer at you, but they missed. That would be considered an aggravated assault with a blunt object. That could've hit a bystander, or someone with slower reflexes. That's the point of that.
The second caveat here is that: an aggravated assault is an assault that causes "aggravated bodily harm", or with a weapon. An assault with a deadly weapon is always an aggravated assault. And so, blunt objects, knives, guns, they're all deadly weapons. That's always an aggravated assault. But in regards to your hands or your legs, whether an assault with your "personal weapons" is considered to be an aggravated assault solely depends on how badly you hurt the person. And this will likely even vary by police department. There's different standards. There's no objective criteria here, which is also why certain cities might have higher aggravated assault rates than another city, but that could just be due to one city being more strict about what it considers to be an aggravated assault with personal weapons compared to the next city.
So to give an example here, Fargo, ND has 65.6% of its aggravated assaults with personal weapons. It's likely that they're more liberal with what they consider to be an aggravated assault with hands. Fargo has a homicide rate of 4.8, whereas if we compare this to another city with a similar homicide rate, Stamford, Connecticut, which has a homicide rate of 4.4 but an aggravated assault rate only one third that of Fargo, and its aggravated assault by personal weapons percentage is only 27.7% (also roughly one third of Fargo's). So it seems like Fargo has a much lower standard for its aggravated assaults for hands than Stamford.
A city which is pretty extreme is Newark, which only 6.7% of its aggravated assaults are by hands, and it has a homicide rate of 19.3 but an aggravated assault rate of 306.9, which is lower than Fargo's. So they seem to be a lot more conservative with what they consider to be aggravated assaults by hand.
To deal with this problem, I made another category called "all-weapon aggravated assaults" or simply "assaults with a weapon", which subtracts "beatings" from "total aggravated assaults".
So anyway, the point here is that: hands are not nearly as lethal as blunt objects, even though their kill percentages are similar here. It's really just comparing a severe beating with hands versus any type of assault with a blunt object (which includes things like an attempted but failed attack and one smack with a golf club to the legs).
So the hands' kill percentage is misleading, period. But the other three should be accurate in a relational or relative sense. The numbers themselves are probably lower than reality due to the fact these include attempted assaults with the weapons as well. So for example, it's probably not the case that only 1.22% of knife attacks result in a death. It's probably higher than that. Same with shootings. It's unlikely that only 7.08% of people shot die. Same with blunt objects, people getting attack with hammers, brass knuckles and baseball bats. These numbers are probably higher. But what probably is the same is their relative differences. So, it's probably the case that guns are 5.8 times more lethal than knives, and that knives are 2.3 times more lethal than blunt objects. So this statistic is probably good at telling us the relative lethality rates, but not the actual lethality rate.
But the main takeaway here is that: guns are 5.8 times more lethal than knives and 13.1 times more lethal than blunt objects. And that's significant. This statistic goes hand in hand with the prior homicide correlation statistics we saw with total violence vs. gun violence.
Data #3: grouping cities by gun usage percentage
The next thing I did here was I grouped each city by the percentage of aggravated assaults that use guns. This doesn't take into account the total aggravated assaults or the homicide rate, or anything like that. Just the weapon tendencies, that's all this takes into account: what weapons the people use... hot how often they use them, not how frequent the violence is... just the weapon tendencies for when violence occurs.
So to give an example which really demonstrates this point: in Round Rock, Texas, 53.5% of the aggravated assaults are with guns, but it only has an aggravated assault rate of 87.9 and a homicide rate 2.5. Compare this with Evansville, Indiana, where only 24.6% of aggravated assaults use guns, but the aggravated rate is 584.0, and the homicide rate is 16.2. The point is that, the following tables just looks at weapon tendencies. There is no skew for cities with higher gun usage rates to have higher total violence rates.
The groupings I made were as follows: cities with a 50%+ gun-usage percentage, then ranges of 10% the rest of the way, from 40% to 49.9% all the way down to 0.0% to 9.9%. There were only two cities over 60%, so I just put them in the 50%+ group... there was not a big enough sample size to make a 60%+ group.
As we can see here, basically every single group has a similar average aggravated assault rate, apart from the 0.0% to 9.9% group, which has a pretty significantly lower rate, but this is mere chance. If I had more cities in the 0.0% to 9.9% group, it would probably makes it way towards the mid 300's like the other groupings. The small sample size for this group allows it to be skewed heavily.
To take into account the differing aggravated assault rates, I made another statistics, which is the ratio of homicides per aggravated assaults. For example, 1:19 means one homicide for every 19 aggravated assaults. 1:136 means one homicide for every 136 aggravated assaults.
Cities with a gun-usage percentage over 50% have an average aggravated assault rate of 359.4 and an average homicide rate of 18.9. Cities with a gun-usage percentage between 10 and 19.9% have a practically identical average aggravated assault rate of 356.6 but an average homicide rate that is 4.5 times lower at 4.1.
The main take-away is that the homicide rate correlates linearly very well with the gun-usage percentage, but not with the aggravated assault rates. Essentially this means: guns don't cause or increase general violence, but they make the violence that does happen more lethal.
Data #4: homicide vs. weapon usage percentages
We're now going to be looking at the linear correlation between the weapon usage percentage by weapon and the homicide rate.
As we see here, guns have a correlation coefficient of 0.57, where as the rest have negative coefficients: knives at -0.19, blunt objects at -0.13 and hands at -0.36.
So, the higher the knife usage percentage is, the lower the homicide rate (ever so slightly) tends to be. Does this mean knives are safe? Hell no. It just means that guns are so much more lethal. The reason why knives have a negative correlation is because the higher percentage of assaults that are knifings necessarily means that a smaller percentage are shootings. We've already seen the kill percentage by weapon, so this makes sense.
Conclusion
I think the initial thought for most people is that general violence would correlate with homicide most strongly. And it does correlate to a certain extent, but it doesn't correlate as well as gun violence does. This doesn't mean that total violence doesn't correlate with homicide at all, it just means that gun violence correlates with death more than all-type violence. But the point is that, knife violence would have to be 5.3 times more frequent than gun violence in a city for them to have equal effects on the homicide rate. So an area with 115 knife-related assaults and 9 gun-related assaults (124 violence instances) will likely have the same amount of homicides as an area with 25 knife-related assaults and 25 gun-related assaults (50 violence instances). Using the kill percentages, both areas would have 2 homicides.
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