 examination of the increased risk for falls amongst individuals with knee osteoarthritis. And our presenter today will be Jessica Wong. Sorry, Jessica Wilfong. Jessica is a research associate at the Schroeder Arthritis Institute with the Kremble Research Institute at the University Health Network. She is a member of the Arthritis Community Research and Epidemiology Unit, which partners with Arthritis Society Canada to disseminate information on the prevalence and impact of arthritis in Canada. Her research focuses on investigating the epidemiology of arthritis, primarily osteoarthritis, the most common type of arthritis and the impact and burden in the population. So I will now turn it over to Jessica. Welcome. Okay, perfect. Thank you so much for the introduction. So today I'll be presenting, as Jennifer mentioned, on the examination of the increased risk factor for falls among individuals with knee osteoarthritis. So the objective is to present findings from our published work by the same title, which was published in Arthritis Care and Research earlier this year. So a little bit of background. The burden of falls in the world, the Global Burden of Diseases Study in 2017 listed falls as the 18th leading cause of disability-adjusted life years. And the second, oh, and disability-adjusted life years are defined as the number of healthy years lost due to ill health disability or early death. And falls were also listed as the second leading cause of death due to unintentional injuries in the world. Specifically in Canada, falls are the leading cause of hospitalizations and emergency department visits for injury and trauma. In this report, they found that 72% of emergency department visits made for falls were made by patients under the age of 65, while 71% of hospitalizations for falls were made by patients older than 65 years. So really falls are a problem across adulthood, but you can see that it becomes a bit more severe of an issue in the older age groups. In 2018, they found that falls accounted for $10.3 billion or just over a third of the total cost of injury. So how common are falls? About 20 to 30% of Canadian seniors experience one or more falls per year, and 6% of Canadian seniors experience a serious injury resulting from a fall. And we know that the prevalence of falls is expected to rise with the aging of the Canadian population. So there are three major risk factors, major categories of risk factors for falls. They include behavioral or activity related factors, extrinsic or environment related factors, and intrinsic or person related factors. Now the cause of a fall or multiple falls may result from a complex interaction of risk factors, either between these different groups, even within these different groups. So identifying those most at risk is quite a difficult task. Just to go into some more details here, the some examples of behavioral factors or those external factors that may result in a fall are lack of physical activity, risk-taking behavior, poor nutrition or hydration, alcohol intake, especially excessive, and improper medication use. Some example of extrinsic or those environment related factors are falling on the stairs or steps, falling due to tripping hazards, having a lack of adaptations, inappropriate walking aids, footwear and clothing, poor lighting in your environment or unstable furniture. And finally, some examples of intrinsic or those person related factors are advanced age, having a history of falls, having previous fractures, especially in the lower limbs, having impaired balance or gait, poor vision, pain, being on certain medications, and having certain comorbidities or chronic conditions. One of which, for example, is Neosteoarthritis or OA, as I'll be referring to it throughout the presentation, which is of particular importance and interest in our group. So a little bit of background on NeoA, just very basically it's a generative joint disease of the knee. It results from the breakdown of cartilage in the knee. So as you can see on the left, we have an image of a healthy knee joint. At the top, you can see articular cartilage, which is a tough, rubbery tissue on the ends of the bones that allow you to bend and move your knee. And then below that, we have the meniscal cartilage, which absorbs shock from pressure and load on your knee. Now, OA has often been described as being caused by wear and tear of the joint associated with aging, which has led to the misbelief that OA is an inevitable result of use of a joint over time. It's now understood that OA is actually a result of a body's failed attempt to repair joint tissues that are damaged due to things like abnormal joint loading, joint injury, and inflammation. So in a healthy joint, our cartilage is being broken down and regenerated in harmony, and that's facilitated by healthy movement of the joint. But in OA, that occurs when there is more degeneration than regeneration, which we can see in the knee joint on the right side there. Now, when the cartilage breaks down, we lose some of the joint space between those two pieces of cartilage. And when the cartilage breaks down, the bones in the knee joint rub together, and this can cause friction, which results in pain, stiffness, and swelling. And importantly, in the context of fall risk, can cause knee instability and the feeling that the knee could buckle or give out. So how common is knee OA? There's an estimated 15% of Canadian adults age 20 plus are diagnosed with OA in general. Now, we don't have good estimates of knee OA specifically in Canada, but we do know that knee OA is the most common form of OA. And there was a study that came from residents in Alberta, which estimated the prevalence of knee OA to be about 11% for adults age 18 plus. So really, it's a very prevalent condition in the country. Here we have a graph, which is based on data from the Canadian Chronic Disease Surveillance System. It depicts the prevalence of OA and Canadians age 20 plus over time from 2007 to 2021. So here on the left Y axis, we have the percent of people with diagnosed OA in Canada. And on the X axis here, we have the fiscal year from 2007 to 2021. The males are represented by the lighter green triangles at the top there. And then males are the yellow squares. And we have both sexes together represented by the dark green circles. As you can see, the trends depict the increasing prevalence of OA over the years, regardless of sex. And this prevalence is predicted to continue increasing as the Canadian population ages, just as we predict that falls prevalence will increase as well for the same reason. So now putting everything together, knee OA is a known risk factor for falls. And we know that fall prevention is also an important clinical target among individuals with knee OA because falling can cause further damage to the joint and other injuries leading to decreased physical activity and social participation. Data from a representative national sample in the US showed that older adults with arthritis are at an increased risk of fall-related injuries and are more than twice as likely to have recurrent falls. That's defined usually as falling two or more times within a year. And this is all compared to people without any arthritis. This is important as recurrent fallers are known to experience worse health and negative outcomes than those who are not recurrent fallers. We also, there is also research that shows that older adults with knee OA are at an increased risk of recurrent falls regardless of the severity of their OA. Now, knowing all we know about the relationship between knee OA and falls, unfortunately the mechanisms and risk factors contributing to falls in individuals with knee OA is not yet fully understood. There was a recent review, systematic review of risk factors for falls in individuals with knee OA, but it only yielded very few articles that met their inclusion criteria. And just to quickly summarize, their inclusion criteria was simply studies involving individuals with knee OA that was confirmed either using standard classification criteria or self-reported doctor diagnosis among people who were older than age 18 and had to have a history of falls. So really not a very stringent inclusion criteria despite only finding a few articles that fit. After reviewing what few articles were available, the authors graded the risk factors for falls identified in the studies as having strong, moderate, limited or conflicting evidence supporting them. As you can see here, no risk factors were found to have strong evidence of being associated with falling among individuals with knee OA. Factors with moderate evidence were impaired balance, decreased knee muscle strength, increased number of symptomatic joints and comorbidities. Limited evidence was available for knee instability, the use of walking aids and impaired proprioception. And just quickly, proprioception is basically our ability to know where and how our body is oriented in our surroundings. And finally, with conflicting evidence, they found pain. So it's important to highlight here that the grading of a strong and moderate level of evidence for these risk factors was hampered primarily by the low number of studies available, not the quality of the studies themselves. On an individual basis, all but one study included in the review was rated as high quality. The main conclusions from this review were really that we need more evidence to be able to make stronger conclusions about what the risk factors were falling are among individuals with knee OA. And this is exactly what we set out to do. So the purpose of the current study was to better understand more about the nature of falls among individuals with knee OA using a Canadian population-based longitudinal study. So longitudinal study is just a study that looks at the same participants over a period of time. We broke this down into four main objectives. First was just to confirm knee OA as a risk factor for falling in our specific sample. Second, we wanted to characterize the profile of risk factors for falling separately among those with and those without knee OA. Our third objective was to examine the context surrounding a fall, including where and how the fall occurred, so getting some of that environmental context. And then fourth, because recurrent fallers are known to experience worse outcomes and those with knee OA are more likely to be recurrent fallers, we wanted to look specifically at those risk factors that contribute to an individual with knee OA experiencing two or more falls in our fourth objective. So heading into some methods. We used the baseline and three-year follow-up of the Canadian Longitudinal Study on Aging. Specifically, we used the comprehensive cohort, which includes just over 30,000 individuals, age 45 to 85 years at baseline. Now, in our analytic sample, we included both those who responded yes and no to the question, has a doctor ever told you that you have osteoarthritis in the knee? But for those who responded no, we excluded any individuals who responded yes to any of the other questions about other types of arthritis in the CLSA, which includes OA in one or both hands, OA in the hip, rheumatoid arthritis, or the question on any other type of arthritis. This way we could create a clean no arthritis group. So this exclusion left us with a final analytic sample of nearly 22,000 individuals with and without knee OA. Our primary outcome, we defined an injurious fall within the past 12 months reported at follow-up one. So this was determined if a respondent answered yes to the question in the last 12 months, have you had any injuries that were serious enough to limit some of your normal activities? And also answering yes to the question, was this injury or were any of these injuries caused by a fall? Those who responded yes to both were then asked how many times they had fallen in the past 12 months, and we categorized the number of falls as none, zero, one, or multiple, which was defined as true or more. Participants were then asked, where did this fall happen? Now, this fall refers to the fall which occurred within the past 12 months that caused the most serious injury or problem to the participant. They were provided the response options of the fall happened inside of their home, outside of their home, but inside a building, or outdoors. Just for simplicity, we decided to combine those first two groups to have indoors and outdoors. Then participants were asked, how did your fall happen? For those who fell indoors or outdoors, they were provided response options in the middle there, standing or walking, fell well on the stairs or steps, fell well exercising, fell from a height or other. Specifically those who fell indoors were also provided the options that they fell from the furniture, they fell getting in and out of the bathtub, or they fell getting in or out of the shower. And for those who fell outdoors, specifically they were provided the option of if they fell on the snow or ice. So again, to simplify things, we recategorized a bit. We kept standing or walking as a lone category, on the stairs or steps as a lone category, and exercising as a lone category. But then the remaining reasons were then lumped into a general other category, specific to whether the fall occurred indoors or outdoors. We had many predictors of interest that we wanted to look at. These were all characteristics reported at baseline that we wanted to assess to see if they predicted a fall reported at follow-up. So some of the predictors of interest, of course, NEOA is one of the major ones. We wanted to see if reporting a baseline injurious fall was predictive of falling later, age at baseline, BMI, alcohol use, knee symptoms, which were defined as in the past four weeks, having knee pain on most days, having knee pain while climbing downstairs or walking down slopes, or experiencing knee swelling, a lower body fracture, which was defined as reporting ever having suffered a break or fracture of the hip, leg, knee, ankle, foot, or toes. We were also interested to see if self-rated vision predicted falling, and whether certain chronic conditions and impaired physical performance predicted falling. And we're gonna go into more detail about those final two points in the following slides. So chronic conditions we were interested in all have some form of research around them that have connected them with falls. As we were interested in respiratory conditions, cardiovascular disease, urinary incontinence, neurologic conditions, diabetes, high blood pressure and depression. And for those final three, diabetes, high blood pressure and depression, participants were also considered to have the condition. If they reported taking medication for the condition as well, as medications for these three conditions specifically have also been shown to be associated with falls. Now moving into the physical performance measures we were interested in. First, we looked at the standing balance test, which is the time and seconds for how long a participant is able to balance on one leg before their foot touches the ground or they lose their balance and touch the wall in front of them. Based on previous research done using CLSA data, we chose a cutoff of 4.5 seconds, such that if a participant balanced for 4.5 seconds or less, this was considered impaired balance. Next, we looked at the timed up and go test. This is the time and seconds for how long it takes a participant to stand up from an arm chair, walk three meters, turn around, walk back to the chair and sit down again at their normal pace. Again, we used the same study to choose a cutoff of 14.2 seconds, such that if a participant took 14.2 seconds or more to perform the task, this was considered impaired mobility. Finally, we looked at the chair rise test. This is the time and seconds. It takes for a participant to stand up from a chair and sit back down five times as quickly as possible with no rest in between. Using the same study, we identified a cutoff of 15.9 seconds, such that if a participant performed the task in 15.9 seconds or more, this was considered impaired balance and coordination. Now, moving on to the findings. Some general characteristics of the sample, we found that 19% of the sample reported NEOA. Now, this prevalence of NEOA is a bit higher than I reported in the background slides, but that's just because participants in the CLSA are a bit older. And as we mentioned, the prevalence of NEOA increases with age. Now, of those just over 4,000 individuals with NEOA, 10% reported having at least one injurious fall at follow up. This breaks down to 6% who reported one fall and 4% who reported two or more falls. Now we'll go objective by objective with our findings. Again, just a reminder, the first objective was to confirm NEOA as a risk factor for falling. So this is one of our figures in our published paper. On the y-axis here, we have the percent or proportion of people who report a fall. And on the x-axis, we have arthritis status and age group. So we can compare between those with and without NEOA within each age group. The black portion of the bar indicates the percent of people that reported having just one fall at follow up. And the lighter gray portion indicates the percent of people that reported having two or more falls at follow up. So together, the full bar indicates the percent of people that reported having one or more falls at follow up. The error bars there are the 95% confidence limits for that overall percent of people reporting one or more falls. So based on the confidence limits and the fact that they do not overlap, we can see that the proportion of people reporting one or more falls is significantly higher among those with NEOA compared to those without within each age group. This is our published table one. I will walk you through it. No need to get bogged down in all the numbers here. But just to orient you here on the left, we have those baseline characteristics or those variables we wanted to see if they predict falls that I listed out earlier. And up here, we are stratifying by those with NEOA and those without NEOA. And then within each of these groups, we're making comparison between fallers and non-fallers. And I'll just highlight here that the values in the table are percents. So the percent of people who report these baseline characteristics. And I will highlight the important findings here. We found that fallers are more likely to report at baseline and injurious fall, knee symptoms, lower body fracture, various chronic conditions, and impaired physical performance. And these differences are seen among both those with and without NEOA, with very little difference between the two groups. So first statistical analysis, we wanted to see which of these baseline characteristics would indeed predict reporting a fall at follow up compared to not. So therefore we use the logistic regression analysis, which is a common statistical tool for modeling the probability of a binary or two option outcomes such as we have here. Did someone fall? Yes or no. This is our table two, the results from our logistic regression. So just again to highlight on the left here, we have those same baseline characteristics we've been looking at. And this time we have three separate logistic regressions. Right now we're just focusing on model one in the first column, which includes the full analytic sample, both those with and without NEOA. The values in the table are odds ratios, which are very basically a numerical measure of the relationship between the baseline characteristics and the occurrence of a fall. So here we see, I'll highlight the main finding. So here we see that the odds ratio for the baseline characteristic of having diagnosed NEOA is greater than one and the confidence interval does not overlap one and is therefore statistically significant, which in summary means that the risk or odds of falling is indeed significantly higher for individuals with NEOA compared to those without. So we've confirmed objective one in our sample. Onto objective two, which was to characterize the profile of risk factors for falling among those with and without NEOA. So we're going back to that same table, only now we're focusing on these final two columns. Model two includes just those with NEOA and model three includes just those without NEOA. Highlighting the important findings here, we found that significant risk factors among both those with and without NEOA were having a baseline fall and having a lower body fracture. Now highlighting the findings that were unique among those with NEOA, we found that urinary incontinence and having a neurologic condition were significant risk factors for falling among those with NEOA. And finally highlighting those findings just for those without NEOA. We found that the significant risk factors for falling among those without NEOA were being female, having depression or taking medication for depression and having impaired balance. So we've really highlighted two different risk factor profiles, but there are quite a few similarities between the two groups as well. So onto our objective three, which was to examine the context surrounding a fall, including where and how the fall occurred. So here for this objective, we took only individual to experience the fall from the analytic sample because these would be the only people who answered the questions about where and how the fall occurred. So just looking simply at that indoors versus outdoors variable, we found that individuals with NEOA were significantly more likely to report falling indoors compared to those without NEOA. So that's almost 47% of people with NEOA reporting falling indoors compared to just 39% of people without NEOA. We do see a difference in who fell outdoors with more people without NEOA reporting falling outdoors, though this difference was not statistically significant. Now just looking at those who fell indoors, we're looking at how the fall occurred. So for those who fell indoors, those with NEOA were significantly more likely to say they fell while standing or walking compared to those without NEOA. Those without NEOA were much more likely than those with NEOA to report that it occurred while on the stairs or steps or while exercising, though these differences were not statistically significantly different. We speculate that it's possible that individuals with NEOA, especially those experiencing knee pain or other symptoms may use more caution when walking down the stairs or steps or while exercising or potentially avoid these activities altogether, which may result in these differences. Next, just looking at falls that occurred outdoors. Again, we see that individuals with NEOA were significantly more likely to report falling while standing or walking compared to those without NEOA. And they were also slightly more likely to report falling on the stairs or steps. So again, this isn't significant. Those without NEOA on the other hand were most likely to report exercising or an other reason as the cause of their fall, which if you remember other for outdoors, including falling on the snow or ice. Again, we suggest that the latter two activities are potentially activities that someone with NEOA may exercise greater caution while attempting or avoid altogether. I also want to pause here to acknowledge that those with NEOA were only significantly more likely to report having an injurious fall while doing very basic physical activities such as standing or walking, which is truly the only unavoidable activity on the list here. And now on to our final objective, which was to identify risk factors that contribute to an individual with NEOA experiencing two or more falls. So we're gonna bring you back to the figure we showed you right at the beginning. And we see that although there are some differences in the number of people with NEOA who report having one fall, again that black part of the bar, the biggest differences between those with and without NEOA are in the percent of people reporting two or more falls or those recurrent fallers as we've been calling them. Just as summary, overall among those with NEOA, 6% reported one fall and 4% reported two or more falls, whereas in those without NEOA, only 4% reported one fall and just 1% reported two or more falls. So therefore for this final objective, we wanted to focus on just those individuals with NEOA and what predicts reporting zero, one or multiple falls. So here's our table with the values in here, the percents again, so the percent of people reporting the different baseline characteristics. But this time we're just looking at individuals with NEOA and we're stratifying them by whether they experienced zero falls, one fall or two or more falls. If you remember, and then highlighting the important findings, individuals with NEOA who reported two or more falls were more likely to report a previous injurious fall, knee symptoms, a lower body fracture and impaired physical performance compared to those reporting zero falls or those reporting one fall. So now if you remember before, our outcome had two categories. Did someone fall yes or no? Here we have three possible outcomes. Did someone fall no yes once or yes more than once? So therefore we have to use a different statistical tool because there is a clear ordering of the categories of the outcome. We started with an ordinal logistic regression. So this statistical tool assumes something called the proportional odds assumption, which is basically that for each of the baseline characteristics included in the model, the effect of the characteristic is consistent or proportional for each increase in the level of the outcome. In our case, this would mean the effect is the same whether we are comparing one or two or more falls to none. So comparing any number of falls to none or whether we are comparing multiple two or more falls to either zero or one falls. Using a score test, we found that the proportional odds assumption was violated and therefore we used a different statistical tool called a partial proportional odds model, which I will walk you through the results of in the following slides. But basically for the predictors where the assumption is not violated, we can present one cumulative odds ratio as we've been doing previously. And for the variables where the assumption is violated, we present two separate odds ratios for those two separate comparison groups we identified. So looking at that, this is our table with the results of the partial proportional odds model. Again, the values in the table are odds ratios. And just to highlight the significant findings here, we see similar findings to what we had before when we were looking at the risk factor profile among those with NEOA. We have baseline fall, lower fracture, urinary incontinence and neurologic conditions, which should all be familiar. But now we also have two novel risk factors that appear, having a respiratory condition and having impaired balance. So we're gonna go through groups of these bit by bit. So first highlighting those risk factors which did not violate the proportional odds assumption. So therefore we have one cumulative odds ratio to present. Here we find that having a lower body fracture and having urinary incontinence were both significant predictors of reporting any number of falls that follow up. And the effect was the same regardless of the comparison groups. Next, having had a fall at baseline and having a neurologic condition were also risk factors for having any number of falls that follow up. The difference here is that the proportional odds assumption was violated. So therefore the risk is different whether we are comparing any number of falls to none here or whether we are comparing multiple falls to having zero or one fall. As you can see here for both factors, the risk is higher for experiencing multiple falls than it is for experiencing any number of falls. So that was an interesting finding. Next, we'll highlight those two novel risk factors having a respiratory condition and having impaired balance. For both of these risk factors, the proportional odds assumption was also violated. But in this case, the odds ratio for experiencing any number of falls was not significant. So, but the odds ratio for experiencing multiple falls was significant. So having a respiratory condition or impaired balance are only risk factors for experiencing multiple falls. And the lack of association with experiencing any number of falls is why we did not see these risk factors emerge in our previous logistic regressions. So doing this method has really revealed other potential risk factors among people with NEOA. So that's the end of our published results. In response to our publication, we did receive a letter to the editor highlighting some concern about potential residual confounders we had not considered in our study that may, in their opinion, impact our study results and conclusions, namely our finding that NEOA is an independent risk factor for falls. So in the following slides, we'll highlight some of their concerns as well as our response. So first, they were concerned that we could, we did not consider the severity of chronic conditions that we included in our model and that it may affect the study results and conclusions. And we agree that this is a potential issue if the severity of chronic conditions differs between those with and without NEOA. Now, we unfortunately do not have the data to determine whether there is a difference. However, even if it is the case that co-occurring disease severities are greater among those with NEOA and this contributes to increased falls in this group, the fact remains that for those living with NEOA, there is an increased risk of falls. So we don't predict that including this would have any effect on our study results and conclusions. They were also concerned that we did not consider the severity of NEOA specifically. And again, we agree this is a potential issue if the risk of falling differed across different levels of NEOA severity. And again, this is unfortunately not something we have the data to look at. But as we cited in our background, both in this presentation and in our published study, there was a study conducted that found that while there was a small degree of elevated fall risk with increasing NEOA severity, the risk was still significant among those with mild disease. So as our population-based NEOA sample as we have here likely includes individuals with a full range of OA severities, we believe our findings still support that fall prevention efforts should focus on all stages and severities of NEOA and that NEOA is still an independent risk factor for falling regardless. And finally, there was some concern that we didn't include chronic kidney disease. Again, we agree this may be a potential issue if there are differences in the prevalence of chronic kidney disease between those with and without NEOA. And there is some evidence that has shown chronic kidney disease to be associated with fall risk and the variable is readily available in the CLSA. So we decided to reanalyze the data. And this was the table that we included with our response. You'll be familiar again with those baseline characteristics on the left. This model one here is the same model as we included in our original paper. And now model two here is the same exact model just adding chronic kidney disease into the model. So highlighting the important findings for chronic kidney disease and Neosurethritis, we found that chronic kidney disease is indeed a significant risk factor for falling. But the risk of falling remains significantly higher for individuals with NEOA compared to those without. So there's no impact on our conclusions based on including this extra variable. So moving into some strengths of our study were the use of a large longitudinal population-based sample, namely the CLSA. This allowed for the inclusion of adults with NEOA across a wide range of ages from middle-aged to elderly adults. And in fact, very few population-based studies ask about OA specifically as opposed to the general umbrella term of arthritis, which includes over a hundred different conditions. And even fewer studies ask about OA in specific joints. And it is a great benefit to our research that the CLSA does include this more specific information for a few select joints, specifically the knee, hip, and the hand. So it would also be beneficial to have information about OA as a whole disease, which can occur in any joint in the body. And as this disease, which impacts such a large proportion of the population, especially among older adults. And OA is associated with the presence and management of other conditions, which affect the elderly, and therefore is really an important, it's really important to understand from a population-based perspective. Another huge strength due to the CLSA was the ability to stratify by the number of falls. So because we know from previous work and reiterated in our findings, there are important differences between recurrent and non-recurrent fallers, which we are able to dive deeper into. Some limitations of our research, the self-reported nature of the question about falls. So some researcher shows that individuals with poor cognitive function are less likely to recall falling in the previous 12 months. Up of participants in the CLSA were screened for mild cognitive impairment at baseline and follow-up. So this is likely not a significant issue. There's also the self-reported nature of the question about NEOA, which may introduce some recall bias, but self-reported OA has been found to be a valid measure of the prevalence in population-based surveillance studies. So again, likely not a significant issue. We were also unable to assess the contribution of many of the extrinsic or behavioral factors that were listed, and further research would benefit from being able to dive into those and examining the interaction between those and the intrinsic factors that we examined today. And we also used a very specific definition for falls. So with this, we just need to keep in mind that our findings are specific to injurious falls and may not be generalizable to falls which do not result in an injury. So in conclusion, a quick summary of our findings, we found that NEOA is indeed an independent risk factor for experiencing one or more injurious falls. We found that urinary incontinence and neurologic conditions were unique risk factors for falling among those with NEOA and potentially important clinical targets. For fall prevention, we also found it's important to consider environmental factors when assessing the risk of falling among those with NEOA. And really to acknowledge again, that those with NEOA were only significantly more likely to report having an injurious fall while doing very basic physical activities such as standing or walking. And that really reflects what a problem this is among that group. Finally, we found that the fall risk profile differs for those with NEOA who experienced multiple falls. We found that respiratory conditions and impaired balance were only risk factors for recurrent fallers. So our finding support that fall prevention is an important clinical target, especially among individuals with NEOA as falling can cause further damage to the joint and other injury. Our study provides important modifiable intrinsic risk factors and important target environments associated with falling among individuals with NEOA that may provide opportunities for clinical intervention and fall prevention strategies. So just a quick thank you slide. Special thank you to my co-authors on this project, Lisa Badly and Anthony Pruccio and the entire team at ACRU. I'd also like to thank Arthritis Society Canada with whom we have collaborated with on a number of arthritis projects. And of course, thank you to the CLSA for providing the data that made this project possible and for allowing me the opportunity to present her findings to all of you today. Great. Thank you very much, Jessica. I think lots of questions have come up already and I'm sure people have lots that are spinning around in their mind. I guess the first one, which is a great place to start is a definition of osteoarthritis. I don't think you put one at the beginning and normally sometimes that's a place to start, but what was your definition that you used? So I defined, sorry, I'll just scroll back, I defined NEOA in particular, but just to, OA can occur in any joint and is very similar in different joints. So it's just a degenerative joint disease and it results from the breakdown of cartilage in whatever joint that it's in. So whether it's injury or inflammation, there's too much breakdown of the cartilage and not enough regeneration of the cartilage. And as I said before too, it was often defined as a wear and tear disease, but we now know that it's actually OA in general as a result of the body's failed attempt to repair joint tissues. And so it's really a whole body disease that's likely incorporating systemic inflammation and other issues that really just break down the ability of the joint to function properly. Great. And in terms of specifically NEOA, the question is wondering how is NEOA diagnosed in the CLSA data and what criteria was used? Yep. So in the CLSA, Neosterearthritis was defined if a participant self-reported, doctor diagnosed NEOA. So there was one question that asked if a participant had been diagnosed with NEOA and if someone indicated that yes, they had been diagnosed by a doctor, then we considered that a diagnosis of NEOA. Great. Now we have a couple of questions from Denise. So the first one is, you showed respiratory conditions increase the risk for falls. Any thoughts on why this may be the case? Yeah, good question. So I had to do a little digging on that because we weren't sure why that showed up either. But it turns out that having a respiratory condition such as COPD or asthma can prevent blood from being properly oxygenated. So that means that the lungs and brain aren't receiving enough oxygen and this can lead to chronic dizziness. This is especially a problem when going to a standing position from laying or sitting. And generally lack of blood oxygenation can also cause weakness in the legs and balance issues, both of which can certainly contribute to the risk of falls as well. Yeah. And just to follow up because another condition that we had had some questions about why it might cause more falls was urinary incontinence. But like respiratory conditions, NEOA is associated with difficulty moving to a standing position from laying down or sitting just due to basic balance impairments and mobility limitations. And this may contribute to slowness which leads to an increased risk of falls in response to urgency to get to the bathroom in a timely manner. So I think you answered the second question as well which was other factors you were able to consider what else might be contributing to falls in people with knee OA? Great. Then I will go on to the next one from Shannon. Hi, Jessica. That was a great presentation. You presented in a very professional and relatable way. I'm wondering if you looked at any self-reported quality of life impact differences between knee OA, between the knee OA group and the non-OA group? That's a great question. That's not something that we looked at but definitely something that would be interesting to look at. Again, I think we do know that quality of life due to pain, activity limitations, all these symptoms and multiple joints, the quality of life is quite a bit lower in people with knee OA compared to people without knee OA. And I would imagine that we'd see the same thing among fallers in the two groups as well. Great. Well, those are all the questions we have. So if anybody has any last questions and wanted to pop them up, we do have a few more minutes. But maybe I'd like to just might as well move to thanking you now. And we really appreciate researchers like you coming to these webinars. We always have a good group of researchers and CLSA participants that attend. I'd like to remind everyone that the next deadline for data access is January 17th of 2024. You can visit the CLSA website under Data Access to review what data is available as well as additional details of the application process. I'd also like to remind everyone to complete their anonymous survey before you exit today. And before we move on to the final slide though, we do have time for a couple questions that did come in. So I'm gonna go back to questions now. So the question is, did you consider diseases like neurological problems like dizziness or migniers? I don't even know, mine ears. Maybe you know what that is. And the non-clinical me does not. Yep. So we did look at neurologic conditions, not that one specifically. But I believe this included multiple sclerosis, Parkinson's disease, and maybe dementia was the other one. And we did find that neurologic conditions did play a role in increasing the risk of falls among those with NEOA. This is likely due to the fact that these neurologic conditions really affect the brain and central nervous system, which are key to maintaining balance and our compensatory actions to avoid falls. So sort of a comment slash question. It's interesting that the function measures like impaired balance were not significantly related to the fall risk in NEOA patients in the multivariable model. Any speculation on why that relationship would be weaker in this group? Yeah, so we found it interesting as well that we didn't see this relationship come up among people with NEOA, as you can see on this slide, in the original analysis. But then when we looked at the risk factors for multi-joint, sorry, multiple falls, we did find that impaired balance did come up. So it's just a matter of the fact that impaired balance may not be a risk factor for just experiencing one fall among those with NEOA, but it certainly is a risk factor for being a recurrent faller among those people with NEOA. Okay. And sort of a follow-up comment that what was the comment you made on fall prevention strategies? Do you, oh, and Alham clarified that it was Meniere disease. That's what I thought it was when you typed it in. But so the question was, you commented on fall prevention strategies? Yeah. So we think that the results of this study are key indicators of some potential fall prevention strategies. So we've identified intrinsic and also modifiable risk factors. So we have things like urinary incontinence or a neurologic condition. If we can do things to treat those, maybe we'll reduce the fall risk within people with NEOA. Unfortunately, there's not much we can do except to prevent falls in the first place or preventing lower fractures in the first place to take care of those other risk factors. And again, treating respiratory conditions, even training balance because there's a lot of exercises that can be done to help people improve their balance that may also help prevent falls. And the next CLSA webinar is going to explore the topic, successful aging in Canada, findings from the Canadian longitudinal studies. And it will be presented on Tuesday, December 19th at noon Eastern time by Dr. Mabel Ho of the Factor Inventosh Faculty of Social Work at the University of Toronto. Registration details for the webinar as usual will be posted on our webinar. And they're also available in the chat box of the webinar today. And then finally, if there are any other additional questions, I'm sure Jessica would be able to, would be happy to answer them if you emailed her directly or you can email them to us at the CLSA. And I guess the last thing is just remember that the CLSA does promote the webinar series using the hashtag CLSA webinar. And we do invite you to follow us on Twitter as well at CLSA underscore ELCV. So thank you again and I wish everybody a wonderful day.