 So now we welcome Dr. Ellen Freeman to begin her talk. Thank you very much and thank you for the opportunity to present some of my work today. Let me just see how this works here. All right, so thank you for the introduction. I am at University of Ottawa and this School of Epidemiology and Public Health. And for about the last 15 years or so, I've been working on ocular epidemiology. And so I was very, very pleased when I saw that the CLSA had included a measure on visual acuity, because it's extremely important that Canada has good quality data on visual impairment. So as many of you know, our population here in Canada is aging. So that means that a larger proportion of people are now 65 and older and that proportion keeps going up. And this is important for eye disease because so many eye diseases are in fact age-related. So diseases like cataract or age-related macular degeneration, they increase dramatically with age. And it's very expensive to the healthcare system to treat these diseases. Estimated that we spend billions of dollars per year treating these diseases. So I'm going to start by giving some background about vision, about the eye and what kinds of things can go wrong as we get older in the eye. And some of the literature that we do have on visual impairment and eye care utilization. And then I'll present my objectives, methods, results and implications. So this is a diagram of the eye and I just want to briefly go over how we see. And so for example, if you're looking at a flower, there's light reflecting off the flower and going into your eye from all different angles. And the cornea, which is the tissue on the front of the eye and the lens, which is the circular or the oval structure within the eye, those are the tissues responsible for bending the light rays and focusing the light rays into the correct spot on the back of the retina. The retina then processes that light and sends the signal onto the brain, where your brain interprets what you're seeing. And so if the cornea and the lens are not able to bend the light rays correctly so that the image focuses in the right place, then you have what's called refractive error. So for example, maybe you're near-sighted or you're far-sighted. And so obviously we have treatments that can address those problems with glasses or contact lenses. Other things that can go wrong with the eye can happen in the back of the eye and the retina. So for example, age-related macular degeneration is a disease where the macula, which is part of the retina, degenerates and causes vision loss. Also glaucoma is a disease of the retinal ganglion cells and optic nerve. And so those are some of the things that can go wrong as we age or throughout the lifespan and can affect our ability to see. So the major causes of visual impairment, the top two are things that we can easily treat, refractive error and cataract. And yet we see in country after country that these are the top two causes of visual impairment. So there's a lot of room for improvement in terms of the prevalence of visual impairment, if we can just address those two things better. The other three major causes of visual impairment, age-related macular degeneration, glaucoma and diabetic retinopathy, treatments exist for them that can slow the progression of vision loss, but you need to be diagnosed and then be compliant with the treatment recommendations. So when we talk about vision, I just want to point out that there's no single measure of vision. In fact, there are multiple measures of visual function. And the measure of visual function that I'm going to be focusing on today is visual acuity, which is a measure of how sharply you can see things or your resolving power of your visual system. But there's many other measures of visual function that are also important. Typically in epidemiological studies, if we're going to measure anything, we measure acuity and then sometimes other things as well. But I'll be focusing on visual acuity today. And so as I said, visual acuity is a measure of the spatial resolving power of your visual system. It indicates the angular size of the smallest detail that can be resolved. And it's measured under conditions of high contrast. So we use a letter chart that has black letters on a white background. And typically it's expressed in SNELA notation. How well you see is expressed in SNELA notation. So for example, if you have 2040 vision, that would mean that you see at 20 feet what someone with normal vision would see at 40 feet. Or we can also express it in meters such that 2040 vision would be equal to 612 vision. So the standard or the normal in SNELA notation is 2020 vision or 660 meters. But some people can see even better than that. Some people can see 2010, for example. So SNELA was a Dutch ophthalmologist who lived back in the 19th century. And he came up with the SNELA chart in which you have letters that get progressively smaller as you go down the chart. So for example, if you can only see the E, then you would have 2200 vision. Whereas if you could read the entire line of letters above the green line, you'd have 2030 vision. So you'll still find this chart in the doctor's offices all over the country. But for research purposes, we generally use the ETDRS chart, which stands for Early Treatment of Diabetic Retinopathy. And this was a major clinical trial done back in the 70s and 80s. And they really wanted to make sure that they could measure vision change in visual acuity as accurately as possible. And so they came up with a more standardized chart that was more reliable. So this chart, you'll see an equal number of letters on each line. The letters are of equal legibility. And there's uniform spacing between the letters and between the rows. And so the effect of all this is that there's better reproducibility. So if you ask, have someone take this chart and then have them take it again a few days later, the score is going to be more similar with this chart than it would be with the SNELA chart. So there's different ways that visual acuity can be measured. So you can measure best corrected visual acuity in which case you would remove the effective refractive error. You would make sure that, okay, without refractive error, how well can the person see? So you would know that any additional reduced acuity is due to eye disease. You can also measure someone's visual acuity with them just wearing the glasses that they have on at the time, or maybe they don't have any glasses on at the time. And you would measure that if you're interested in what kind of vision this person has in their daily life. And furthermore, you can measure acuity under binocular conditions. So with both eyes open, or you can do it monocularly, so in one eye at a time. So Canada, it's very important that Canada has its own data on visual impairment. This is important for eye care planning purposes, as well as to know how we compare to other countries. And up to this point, I would say we have rather limited data on visual impairment. There have been studies, population based studies that have been done where they ask about the self report of visual difficulty. And so those are certainly valuable studies, but generally, you know, asking someone about their vision is not as good as the gold standard, which would be measuring their acuity. We do have one small study from Brantford, Ontario where visual acuity was measured. It was about 700 and some people. And so that is a very valuable study to have. But of course, we don't know if Brantford, Ontario is representative of the rest of the country. And then we have some work that's been done where people have taken US rates and applied them to the Canadian population. But of course, we don't know if the US rates are approximate the Canadian rates well. So there's a need for more data on visual impairment in Canada. So this is an example of a study done by Jacques Cé and Montreal a number of years ago now. So he looked, he used the self report of visual difficulty. And then he decided what indicated visual impairment or not. And the red line indicates the data from this study. So these data are from the Canadian study on health and aging. And they're the data just from Quebec. And so you can see how the prevalence of self reported visual impairment, you know, it's fairly low at age 70, but it increases pretty dramatically as you get into older age. There's also prior research, looking at the prevalence of eye care utilization. So this is data from my colleagues in Toronto, yapping, Jen and Graham trope. And so they use data from the Canadian Community Health Survey in years 2005 and 2000. And you can see how eye care utilization on the y axis, it's, you know, it's a bit higher in the teenage years. And then it goes down and young adults and then it starts to go up again in middle age and older age and it continues to go up. So how often should people be receiving eye care? So there are various guidelines. These are some guidelines from the Canadian Ophthalmological Society. There's also guidelines put out by the Canadian optometry Canadian optometry group. The ones from the COS are here and they have them stratified by whether someone is asymptomatic and low risk or if they're symptomatic or if they're high risk. So if you're asymptomatic low risk, they say you should go if you're an older adult every two years at least. If you're a middle age adult every five years, they say if you're symptomatic, you should go right away. So if you have any changes in visual acuity or visual field or color vision or physical changes to the eye that you should go right away. And in high risk patients, so that would be people with diabetes or cataract or macular degeneration or glaucoma or if you're a glaucoma suspect or if you have a family history of these conditions. They say you should go every year if you're 60 year older or every three years if you're between 40 and 50. So those are the guidelines put out by COS. The optometry group say that you should go every year once you're age 60. All right, so the objectives that I had were to look at the prevalence of visual impairment and its determinants and to determine how frequently people were using eye care and what were the determinants of using eye care. So for this work, I used the comprehensive cohort of the CLSA. So this included over 30,000 adults ages 45 to 85 from 11 sites in seven provinces. And the reason we used the comprehensive cohort instead of the tracking cohort was that visual acuity was measured in the comprehensive cohort. And so these data were collected between 2012 and 2015. So people were excluded from this cohort if they were in an institution, so like a nursing home, or if they were living on a First Nations reserve of settlement, if they were a full-time member of the Canadian Armed Forces, did not speak French or English, or had obvious cognitive impairment. So it's important to keep that in mind as you look at the data on visual impairment, because we know that, for example, people who are in nursing homes have higher rates of visual impairment. These were the 11 data collection sites in the comprehensive cohort. So just remember that so people had to live within 25 to 50 kilometers of the data collection site to be included. So obviously we don't have people in this cohort from the far north. We don't have people in the cohort from the provinces that were excluded. So people were sampled using provincial health registries and random digit dialing. And stratified sampling was used to ensure the adequate representation of different demographic groups. Visual acuity was measured using the ETDRS chart at two meter distance. And the primary outcome that I'm going to talk about is acuity measured with both eyes open, wearing the normal prescription for distance correction, if any. And we defined visual impairment as acuity worse than 2040. So this is the standard definition used in developed countries. I'm also going to show you data looking at visual acuity measured in each eye separately with and without pinhole correction. And so pinhole correction is when you use this black thing here, the occluder, which has holes in it. And so the eye with the occluder is open and the eye without the occluder is closed or it's blocked completely. And you so light only enters your eye through the holes. So it's only coming from straight ahead, as opposed to from all over the place. And so refractive error doesn't really happen when you look through small holes like this. So it removes the blur. And it's a way of estimating in a crude way how much visual impairment is due to refractive error. Eye cure utilization was measured using the question, during the last 12 months have you had contact with an ophthalmologist or optometrist about your health? And so anytime you're using a question to measure an outcome, it's it's valuable. If you know how well that question correlates with, for example, what's in the medical record. And so a group in states has looked at that and they found that there was good agreement between a question and what was in the medical records. So I'm going to show a couple of figures that include data such as the number of optometrists per 100,000 people by province. And we got that data from the Canadian Institute for Health Information. And we got the data on the number of ophthalmologists per province by the Canadian Medical Association. And we got the number of people per province from Statistics Canada. And we took all these data from the year 2013. So for the analysis logistic regression was used. And for all the analyses, I'm going to show you the complex study design was accounted for in the analyses using SDY commands and status. We used the sample weight, the straight of variable, and the primary sampling unit. So for visual acuity, there were some people who are missing data about one and a half percent or about 431 people. And this group was older by about three years. They were more likely to have low incomes, low household incomes, and they were more likely to smoke. And when you looked at the reason for why many of them were missing data, it was because they couldn't see the acuity chart. They couldn't see any letters. So the acuity chart is only appropriate for people who have acuity within a certain range. And then you either have to move the test distance closer to the person or use another method of measuring their acuity. So for people who couldn't see any letters on the chart, they were set to missing. And so it's important to remember that as I show you these data, we don't have people who couldn't see anything on the chart. So those people are basically blind. So the estimates that I'm going to show you are conservative. So this figure shows the prevalence of visual impairment by age group. So as you can see, you know, in the youngest age group, the prevalence is around 3%. And then in the oldest age group, it goes up to 16%. And this would continue to go up in those who are in their 90s. This table shows the prevalence of visual impairment overall in all the provinces that we had, as well as in each province. So in all the entire CLSA comprehensive cohort population, the percent who had visual impairment was 5.7%. But we did see a lot of difference between provinces. So for example, in Newfoundland and Labrador, almost 11% had visual impairment, whereas the low was in Manitoba where only 2.4% had visual impairment. If you take those age stratified rates within each province and then apply it to the population in that province, you can come up with the number of people that likely have visual impairment. You can come up with estimates of the numbers who have visual impairment. And then you can add all those up. And so I wrote here for Canada, but it's really just for the provinces that were included in the CLSA comprehensive cohort, so the seven provinces, you can about 660,000 people had visual impairment. So we also looked at the risk factors for visual impairment. And so this is a multiple logistic regression model with everything together, including the things in the footnote at the bottom. And we saw that older people were more likely to have visual impairment. People with lower income, for example, those making under 20,000 had two times the odds of visual impairment compared to those making over 100,000. That's household income. Current smokers were more likely to have visual impairment compared to never smokers. People with type 2 diabetes were more likely to have visual impairment. And the type 1 odds ratio was even higher than that, but that group was smaller, so it didn't reach statistical significance. And then people who said that their doctor told them they have memory problems, they were more likely to have visual impairment as well. And the variables in the bottom, none of them were significant, except province. Provence remained very statistically significant, even after adjusting for these other factors. So now I'm showing you data from the monocular measures of visual acuity. And in this case, I'm just showing you the right eye. So OD means right eye. And so the top line is the amount of visual impairment in the right eye. And the bottom line is the amount of visual impairment after pinhole correction. So that removes refractive error. So the difference between those lines indicates the amount of visual impairment that's due to refractive error. So in the older group, it's about 47%. That was due to refractive error. Whereas in the younger group, it's higher. It's a larger proportion. It's about 75%. So that makes sense because these eye diseases tend to become more frequent with age. So we don't have data from a comprehensive eye exam in the CLSA, but they did ask about the self-report of various common eye diseases. So of those who had visual impairment, 13% said that they had a cataract in the eye. 10% said that they had age-related macular degeneration. And 8% said that they had glaucoma. So those are other possible causes of visual impairment besides refractive error. All right. So now moving on to eye care utilization. Again, some people are missing data on eye care utilization, about 5% of the comprehensive cohort. There was no difference in age between those who had data on this question and those who didn't. But there was a difference in income. So the people without data were more likely to have low household incomes and they were more likely to currently smoke. And that's not an exhaustive comparison. These are just some of the major factors that I picked to show. So this graph shows the prevalence of eye care utilization by age group. So in the younger age group, about 50% saw an eye care provider in the last year. And in the older age groups, about 75% or 6%. Overall, about 57% saw an eye care provider in the last year. When we look by province, so the darker the color, the lower the percentage who used eye care in the last year. And the white provinces don't have data. Ontario in the lighter yellow color had the highest percentage of people who used eye care. And the provinces with the lowest percentage included Manitoba, Quebec, Newfoundland and Labrador. And yeah. We then looked at the percent who used eye care utilization on the y-axis by the rate of optometrists on the x-axis. So this is adjusted for population. And we did that for each province. And you can see a linear trend here with the exception of Quebec, which didn't fit the linear trend. So for example, Newfoundland and Labrador had the lowest number of optometrists per 100,000 people at about 11. And they also had the lowest percentage of people who said they used eye care in the last year. Whereas Ontario had a very high rate of optometrists, 16 optometrists per 100,000 people, and they had the highest percent who used eye care. So you've got a linear trend there, with the exception of Quebec, which had about 17 optometrists per 100,000 people but had fairly average eye care utilization at about 55%. And we didn't see a trend when we looked at the eye care utilization by ophthalmologists. So just in case people don't know, an optometrist has a doctor of optometry and they're kind of the frontline eye care providers. Whereas an ophthalmologist has an MD and does surgery and treats, you know, does glaucoma surgery or cataract surgery. And so they're complementary to one another. And so we don't see this relationship, this linear trend between eye care utilization and the number of ophthalmologists for 100,000 people. We also looked at eye care utilization by certain high-risk groups, for example, people with glaucoma and people with diabetes. So the guidelines are that groups with glaucoma or diabetes, once they're age 60, they should be seen every year by an eye care provider. And you can see that for the glaucoma group, about 20% aren't being seen every year. For the diabetes group, about 30% aren't seen in the last year. So there's definitely room for improvement there. So we also, this is a logistic regression model looking at the variables that were associated with eye care utilization. And so older people were more likely to use eye care. Men were less likely to use eye care than women. You can tell by the odds ratio less than one. Those with lower incomes were less likely to use eye care. Those with less than a bachelor's degree were less likely to use eye care than those with more than a bachelor's degree. And current smokers were less likely to use eye care than never smokers. And this model contains more variables that I'll show on the next page. So we also put some of the eye disease variables in there. And as you can expect, so those people with type one and type two diabetes were more likely to use eye care. So especially type one, which occurs earlier in life, and the longer you have diabetes, the more likely you are to have complications of diabetes like diabetic retinopathy. So that group is the most likely to use eye care. People with glaucoma are more likely to use eye care as well as people with cataract and macular degeneration. And then with visual impairment in the model, with all those eye diseases, it didn't reach statistical significance, but it's significant without the eye diseases in the model. So that model also included marital status, ethnicity, urban rural residents and province. The only province of those four was statistically significant. So we saw differences by province for both visual impairment and eye care utilization. So, you know, we can only really speculate about why those differences exist. Obviously, Canada is a huge country. The provinces are very different in terms of the populations that live there in terms of the economies. When we adjusted, though, for demographic factors, we still saw that province was associated with both visual impairment and eye care utilization. So, you know, we don't think it's due to differences in education or income, for example. There are also differences in eye care coverage between the provinces. So, for example, Newfoundland Labrador does not cover an annual eye exam for seniors. All the other provinces in the CLSA, Comprehensive Cohort, do cover an eye exam at least every two years for seniors. And then there are some other differences as well. And finally, they also differ in terms of the availability of optometrists and ophthalmologists. For example, Newfoundland Labrador has the lowest optometrist rate. So those are some possible reasons why we saw provincial differences, but at this point we can only speculate. We would need further research to really investigate that in more detail. So lower income was related to more visual impairment and less eye care utilization. This was true even when adjusting for education. So, you know, getting an eye exam is in cheap. It's about $100. And then, you know, glasses, even if you buy the cheapest pair, it's still going to cost you about $150. And, you know, it can cost you many hundreds of dollars depending on what kind of frames and what kind of lenses you want. And, you know, if you have to change your glasses every few years, this can get very expensive for middle age and older adults. So we also saw that smoking was related to more visual impairment and less eye care utilization. So we know from prior research that smoking is a risk factor for age-related macular degeneration and certain types of cataract. But we also know that smokers participate less in preventive health measures. So it just may be that they're less likely to go get their eyes checked. Lower education was related to less eye care utilization. So, you know, even if you have the money to go see an eye care provider, if you're not aware that you should be going or you're not aware that it's not normal for your vision to get worse with age, then you might not know to go. So Australia, for example, has had public health campaigns to try to help with this and they've demonstrated some preliminary effectiveness with their campaign. So this would be something that could be considered. So how do the results here with the CLSA compare to other findings? So in the CLSA comprehensive cohort, we saw 5.7 percent had visual impairment with the age range of 45 to 85. In the United States, the NHANES study found that 6.4 percent had visual impairment, so but that was in a much wider age range of those 12 and older. In Melbourne, Australia, 4 percent had visual impairment and that's 40 plus. If you look just in the Ontario sites, we can compare to the Brantford, Ontario study. So just in the two Ontario sites in Hamilton and Ottawa, 3.5 percent had visual impairment in the CLSA and that compares very closely to the 2.7 percent that Barbara Robinson and colleagues found in Brantford, Ontario. So we found that 57 percent used eye care in the last year in the CLSA. In the prior work done using the CCHS study in 2005, 40 percent used eye care, but it's a younger age group, so it's not surprising it's less than what we found. In the United States, behavioral risk factor survey study, they found that 69 percent used eye care that's in an age range of 50 plus and in the Australian Blue Mountains eye study, they found that 62 percent used eye care. So this estimate is very similar to those. So the strengths of this work are that these data are really coming from all across Canada, from seven provinces, from 11 different cities, and visual acuity was measured using the E2DRS chart. And I think the fact that they included household income is really valuable. It turned out to be really important in these analyses. A lot of times epidemiological studies don't ask for it. I think they think it's a bit invasive, but it is important. The limitations, so we didn't have a comprehensive eye exam done by an ophthalmologist to determine the primary cause of visual impairment. And also, you know, our findings may not generalize to those not included in the eligibility criteria. So those in nursing homes, for example, or those in the far north, and our estimates of visual impairment are conservative because some people could not see any letters on the E2DRS chart. And finally, the fact that these data are cross-sectional does not allow assessment of the temporality between the risk factors and the various outcomes. So what does this all mean? You know, not surprisingly, refractive error is a leading cause of visual impairment in Canada. And because this is so easily treatable, it's something that can be targeted by policymakers to try to reduce this as a cause of visual impairment. And, you know, I think provinces should really think about how they can remove cost as an obstacle to eye care utilization. You know, I think in Canada, we believe that people should have equal access to healthcare and the fact that low-income people are not using it and are more likely to be visually impaired is a concern. And finally, the fact that people with diabetes are not getting eye care every year once they're older, that's also a concern. And I think we should consider a more education and outreach to this group. So I'd like to acknowledge my fellow co-authors on this work. I'd also like to acknowledge the funding from CIHR, both to me personally and for the CLSA study as a whole. And I'd like to acknowledge the principal investigators of the CLSA, Drs. Raina Wilson and Kirkland. And I'd be happy to take any questions. Thank you, Dr. Freeman. That was really great. Very, very interesting. So we'll go ahead and now open it up to questions. Just a reminder that muting remains on, but you can enter your questions into the chat window at the bottom right corner of the Webex window down here where people are sending questions at any time. And I'll go ahead and read through them. So we'll go ahead and get started. Dr. Kristen North asked the participants that could not see letters on the ETDRS chart go on to have pinhole acuity measured. So that's a good question. So on the protocol for visual acuity, I believe it started with the monocular acuity and then the pinhole acuity and then the binocular acuity. I'm not sure what the protocol was if they couldn't see the letters with each eye, if they went on to have pinhole. It's a good question, something that I'll have to clarify with them. So if I'm right, this is Carol. I believe that SOPs are posted online. So everybody should be able to see the visual acuity SOPs and see how that goes. Yes, yes, they are posted online. So please enter your questions into the chat box. As we're waiting for hopefully a couple more to come through, I'll ask a couple. So it's a really great presentation on the distribution of visual acuity problems. You decodimized your visual impairment. Are you planning on doing anything else, looking at gradations between visual problems? You mean looking at it with more categories or as a continuous measure? Yeah. We could do that. We could see are there different risk factors for more severe visual impairment than more moderate visual impairment? I did it this way mainly because that's the way the other studies have done it. But yeah, I wanted to look at blindness but we didn't have the protocol to measure blindness in this study. But yeah, often people will look at visual impairment or at blindness. I was going to ask, there's no question, are you blind or are you legally blind anywhere? It's a good question. Not that I've found up to this point, but I'm going to make a note about that because I mean, blindness is typically quite rare, but it's such a large study that we probably have a fairly large number of people. But I'll see if there's a question on that. So we have another question from Walter Wittich. Do you believe that the ratio of optometrists to service access may be influenced by the fact that there are only optometry schools in Quebec and Ontario? That's a good question. Right. It's hard for me to say. You know, I think Walter could probably answer that question better than I could. You know, there did seem to be a high rate of optometrists in Quebec. So that may have something to do with the fact that there's a school there. I know we also sometimes have people go to the States and go and train elsewhere. You know, there has been a paper looking at access to eye care and whether it seems to be too low in various places. And I think the conclusion was that it seemed like we had adequate eye care access in Canada, but that doesn't mean that, you know, if you have to drive a little bit further in a certain city that maybe it wouldn't influence you to go less often. So, you know, I'm not, hopefully that answered your question, Walter. Yeah, the little follow up statement struck me that the usage was was so low, even though there should be more optometrists in QC, I guess, because of the optometry schools. That the usage in Quebec was lower. Yes, it did surprise me a bit that the usage in Quebec was lower, yet their rate of visual impairment was low as well. So I don't quite know how to explain that. So I'll go ahead and ask another question and hopefully somebody from the field will ask more questions. So, you know, it kind of begs looking for future directions or future associations between visual impairments and possibly cognitive decline or social isolation, participation. You can come up with a whole bunch of interesting associations, transportation or workforce utilization. Are you planning any of those things for the future, particularly maybe for the longitudinal study? Yes, so for the cross sectional data, I'm proposed to look at mobility and we've already started on that work and I wanted to look at employment as well. So those are kind of the next end depression as well. Those were the things that I proposed to look at in my abstract. And then for the longitudinal data, I think it'd be interesting to look at the incidence of visual impairment, just again, because I don't think we have any data on incidence of visual impairment. So it would be very valuable for Canada. Absolutely. And so when you start thinking kind of longitudinally, do you think that we're having any kind of changes over time? Or do you think that there's changing trends with our aging society for visual issues? Because there's just not enough information Canada-wide to be able to judge. Hard to say. When we compare the eye care utilization to what was found in the early 2000s, I think it's fairly similar. And I think there are some provinces that are lagging behind the other provinces, probably because of eye care coverage, I'm guessing, or maybe educational issues as well. As far as the prevalence of eye disease, hard to say what's going on. I mean, obviously, more and more adults are going to be, a higher proportion of adults are going to be older. So that's going to lead to more age-related disease. And so we need to make sure that we're ready for that in terms of our eye care system. Absolutely. Well, I'll ask one last question and give people time maybe to ask one last question here. And are you planning on doing anything with the image data that the CLSA has? Any retinal image or eye pressure measurement information? Are you planning to do anything else with kind of measurement issues out of the collection? So it's a good question. I requested quite a bit of data already and I've got my hands full just with that. But I know that my colleagues throughout Canada are probably thinking about those data. And those are going to be very valuable data, looking at intraocular pressure and the images, as you said. So I don't have any immediate plans right now for that. But hopefully someone else does. Okay. Any other questions from the field? If one comes through, then we'll ask it. Here we go. So here's a question from Annie. Have you looked at whether those who access eye care had better visual acuity? That's also a very good question. Yeah. So generally the people who access eye care were the ones who had the worst vision or the eye disease. If they don't have, you know, poor vision, they're, yeah. Well, the people who access eye care were more likely to have bad vision actually. That makes sense. Yeah. Yeah. Okay. Well, thank you again very, very much. We appreciate your participation in the CLSA webinar series and for being here with us today. Thank you very much. Thank you. I'd like to remind everyone that the CLSA data access request applications are ongoing. The next deadline for applications is in January 29th, 2018. So please visit the CLSA website under data access to review available data to see further information about the platform and to look at details about the application process. I'd also like to say that our next webinar scheduled for January will be welcoming Dr. Holly Touko to present on the development of dormative data and comparison standards for the cognitive measures employed in the CLSA. So please register soon and join us for next month's webinar. Thank you everyone again for attending today's presentation.