This is part 2 of our series of articles based on a yearlong injury study we (semi) recently concluded. In the first analytical look at the injury study data, we will be focusing on whether the people who sustained an injury during the course of the study differed from the people who didn’t sustain an injury.

This is part 2 of our series of articles based on a yearlong injury study we (semi) recently concluded. We’re writing this with the assumption you’ve already read part 1, so check it out if you haven’t already, or give it a skim to refresh your memory if it’s been a while since you read it.

In the first analytical look at the injury study data, we will be focusing on whether the people who sustained an injury during the course of the study differed from the people who didn’t sustain an injury. For this specific article, we will be ignoring the time component of our survey data. As an example, a person who was injured on the first day of the study and person injured on the last day are both considered injured, without any distinction of the time differences.

Here is a classic Table 1 that breaks out each of the responses to the baseline questionnaire by status at the end of the study. Due to the high proportion of individuals who did not complete the study (lost to follow-up), they are included as well.

Without any statistical testing, the three groups appear to be relatively similar based on the eye test. It’s important to note that sex, height, and weight are linked, so as the proportion of female lifters decreases from injured, lost to follow-up, and not injured, the average body weight decreases as well. Why height does not follow that pattern is, at this moment, not known. In addition to stratifying by outcome, we can also stratify by sex, as seen in Table 2.

We can see from Table 2 that generally speaking, the female study participants were slightly older and newer to lifting than the male participants, though they had about the same amount of powerlifting experience. Further, there is an approximately 9% difference in the proportion of individuals who were injured between male and female participants (36.1% of the males got injured, compared to 27.6% of the females), although not a statistically significant difference.

However, let’s break down the injury numbers by sex a little further. Table 3 presents the proportion of participants who were injured based on their sex and if they had physical limitations at baseline.

For example, of the 67 male participants who indicated they had physical limitations at baseline, 38 were injured throughout the course of the study. In comparison, of the 185 male participants who indicated they did not have physical limitations at baseline, only 53 were injured during the study. The difference between male and female participants did not rise to the level of statistical significance, but this will be an area of inquiry moving forward.

Lastly, Table 4 breaks out the injury locations by sex.

From my practical experience, I can say that the fact that there were no female participants with pectoral or elbow injuries is not surprising. I feel those tend to occur predominantly with heavy absolute load benching. It seems that shoulder and low back injuries are the most common injury sites in both sexes.

This is just the entry point into injury-related analysis. Moving forward in the next article, we will be dealing with the injury data with the time component included. As an oversimplification, if three men get injured over the course of the study and three women get injured over the course of the study, the absolute count of injuries is the same between sexes. However, if the three men were injured on the 30th day of the study, and the three women were injured on the 365th day of the study, the rates of injury by sex are different. We’ll be using that framework with a variety of time metrics (calendar days, days lifted, days benched, etc.) and group comparisons (sex, previous sport experience, physical limitations, etc.) to attempt to get an accurate picture of injury risk for recreational powerlifters similar to our population.

Greg’s Commentary

These data are consistent with the other research in the area. A leading predictor of injury is prior injury, so it’s not at all surprising that the people who had physical limitations prior to the study were significantly more injury-prone. I think that suggests that it’s important for powerlifters to be thorough and conservative when rehabbing injuries. Most of us are wired in such a way that we’re willing to train through pain, and we want to rush back into hard training as quickly as possible following an injury. Sometimes that works out, but the risk of one injury snowballing into more increases when you’re trying to train through physical limitations.

The overall number of people injured may surprise you. Of the 160 people who finished the study (either sustained an injury or made it through the whole year uninjured), almost ¾ of them sustained an injury. That seems to conflict with the finding that injury rates in powerlifting are only ~3-5 per 1000 hours of training. Assuming someone trains for five hours per week, that would mean you’d expect a lifter to get injured about once every four years, on average (or, stated another way, you’d expect about ¼ of lifters to get injured per year). However, keep in mind that we used a pretty broad definition of “injury” 1, compared to the more conservative definition 2 used in other research. In another study on powerlifters using a pretty liberal definition of “injury,” 3 70% were injured at the single point in time when data was collected, so I’d say the overall injury rate seen in our study is to be expected. Taken collectively, the data suggest that powerlifters sustain minor injuries pretty frequently, but more serious injuries are pretty rare; comparable to triathlon training, but less common than long distance running or most team sports.

Our data suggest that women may have been a bit less likely to sustain an injury than men, though the difference wasn’t statistically significant. That’s in line with other research: while some data suggest that women sustain injuries less frequently during lifting than men, other studies fail to find significant differences. Overall, I think the literature suggests that women may be a bit less likely to sustain an injury during lifting than men, but the difference in risk isn’t particularly large. Whether that’s due to training with lower absolute loads, smarter training decisions (in my experience, women are less likely to push well past the point of form breakdown and do YOLO sets during training), or inherent differences due to other factors (i.e. the protective and regenerative effects of estrogen), we don’t yet know.

The injury site data is also consistent with other research. The lower back and shoulder frequently show up as common injury sites in the injury research on strength sports. As a shallow ball-and-socket joint, the shoulder has less inherent stability than hinge joints like knees and elbows, or a deeper ball-and-socket joint (the hips), so it’s not too shocking that it’s a common injury site, especially given the amount of stress placed on the shoulder when benching, which can take the shoulder to near end-ROM for flexion and horizontal flexion, especially for folks with longer arms. Back injuries in powerlifting are a huge can of worms, but they may be related to form breakdown and spinal flexion in the squat and deadlift. Rather than rehash the entire spinal flexion debate in this article, I’d recommend you check out this piece from Sam Spinelli. Prior research has also found pretty high rates of knee injuries, which we didn’t see in our study.

Finally, it was a relief to see that the folks who dropped out of the study “looked” pretty similar to the folks who finished. Since we weren’t paying participants, dropouts were inevitable. If we would have seen that they were substantially different from the folks who finished, that would have justified some skepticism about our results. My initial assumption was that a lot of the people who were lost to follow-up may have gotten injured, gotten down on lifting, and did not want to be reminded of the injury by filling out the survey. Since their rate of physical limitations entering the study was more similar to the folks who finished without an injury, though, that makes me think that their injury rate may have been a bit lower than the cohort that wasn’t lost to follow-up, and they just dropped out of the study for other reasons. If that’s the case, our data may overestimate injury rates slightly. Ultimately, however, their overall similarity to the folks that finished tells us that the dropout rate isn’t a big enough confounder to fully preclude further analyses.

Stay tuned! The time gap between parts 2 and 3 of this series shouldn’t be as big as the gap between parts 1 and 2. When thesis stuff started ramping up for me, everything except for research and MASS was put way on the back burner. We’ll be returning to a more consistent content schedule now, though.