 Okay, hello and welcome. I'm Dr. Debra Sheetson. I'm just really, it's amazing to see all of you here, and I want to thank you for participating in the Canadian Longitudinal Study on Aging. Before we get started, I wanted to acknowledge the, that we acknowledge and respect the Lekwungen people on whose traditional territory the university stands and the Songhees, Esquimalt, and Wasnick peoples whose historical relationship with the land continues today. Thank you for waiting, and until 7.30 for the program part to begin, I know that wasn't clear, and we were supposed to have some coffee, and that didn't turn up, and so I apologize for that. Nobody likes powdered coffee, right? But I hope you enjoyed the fruit and the hummus and tamponade, and enjoyed knowing that you're part of this amazing group of people who are contributing to what we like to call really big science. This is the biggest study, probably in the world, 50,000 Canadians, 11 universities involved, and so you're really contributing to what we know about aging. And tonight we get to hear some of the most recent findings from some analyses that one of our own faculty here has done. So I'm excited that we're able to bring you all together for this, and that it's being broadcast to the participants who couldn't make it down. And you'll get to see this later and share it with your families also if you want because there'll be a web link available. So as I was saying, I'm Dr. Deborah Sheetz. I'm one of the co-site leads for the CLSA. I'm in the School of Nursing here at UVic. I share responsibility for this project with Dr. Lynn Young, who couldn't be here tonight. She's traveling out of the country, but she sends her regrets and wanted to make sure I acknowledged her work in this because it's a big project, and she's a wonderful collaborator. Your interest in the study reminds me how important our work is, and we really value your participation, so I hope that's coming through tonight. As you know, there's 11 sites across the country involved in this. McMaster in Hamilton is the lead site, our National Coordinating Center, and so they're basically collecting data on more than 50,000 Canadians age 45 to 85 and older. And we hope to follow you for a very long time, up to 2032, so we'll get to know each other pretty well over that time, right? I may not be leading this project by then. So many researchers now are analyzing currently collected data to generate findings to improve our understanding of aging and how to improve the lives of people in Canada and also around the world. It'll touch all generations, changing the way we live and approach growing older, and after four years, it's pretty exciting to reach this point. The study took over 10 years to get underway, and so four years in, we're at an exciting point. Before we get started, I want to introduce some of the key people behind the study, and first are our CLSA staff, many of whom you know. They aren't all here tonight, but I want to say it takes a really dedicated research team to collect the data, and so I want to introduce Dr. Joanne Miller, if you could stand up Joanne, and if you want to come up. She's our CLSA project coordinator as of August 2016, and she holds a doctorate in psychology and brings a lot of research experience on a wide range of community-based health and social policy topics. And so, welcome. Thank you very much for participating in the UVic CLSA site. It's, for those of you who I have not met, thank you for being here. There's a lot of faces, so you've been in the clinic since I've started in August. Deborah mentioned a large team here, so I'd just like to acknowledge all of the staff that work at the UVic site. Lindsay Cassie is here from the in-home site. She's also joined by Linda O'Cult, Nancy Davis, and Doris Davis. In the DCS site, when you come to see us at the Gorge Road Hospital, or if we've come to your home, there's myself. Monica Kelly, who makes an impression on folks because she's the new fee that will slip into her new fee dialect. We'll be later. Val Sotl, Belinda Freilich, Hira Makbo, Helen Berger, will be starting with us on Monday. Ashley Clark, Nina Naowanchuk. Sorry, I can't pronounce Nina's last name even after all this time. Has been one of our work study students. And Cynthia Chow has also been a work study student that's recently finished with us. So thank you for those that have come in. Thank you for those that are in the process of doing the in-home and your book to come in. And thank you for those that are still going to be booked for the in-home. Thank you, Joanne. Okay. And secondly, I want to acknowledge the Office of Research Services at UVic, which has provided extensive guidance and financial support for this really complex research endeavor. And so in particular, this is Jill Taylor right here. She's the Senior Projects Officer. She's been involved since the start of the project and continues to provide a lot of insight and guidance to us. I also want to publicly express my gratitude to Rachel Scarth, the Vice President of Research, and also to Mike England, the Financial Project Officer. So these are key people at UVic that this project couldn't happen without. Third, I want to acknowledge the support of Dr. Scott Huffer, the Director of ILA, the Institute for Aging and Lifelong Health, for his commitment to the science of the study. And the wonderful ILA staff who have provided support for this event and numerous other project-related work. So if you could please stand as I mentioned your names. Lois Holizki is up there in the back, and Arlene Samp is right here. And we've got Kara Pearson right here. Finchenza, Grupposa over here, and is Leah here? No, okay. I didn't see her earlier. And lastly, I want to thank Dr. Parminda Reina, who's the PI of the CLSA and his staff at the CLSA National Coordinating Center because they've provided the financial support for the refreshments to the satellite length. Just so many details around this. As you know, the CLSA is a strategic initiative of the Canadian Institutes of Health Research, which has provided funding for the study and supports also provided by the Canada Foundation for Innovation, as well as the provincial government of BC. Good evening, everyone. My name is Scott Huffer. I'm the Director of the Institute on Aging and Lifelong Health. Welcome. It's great to see all of you here tonight. It really is my pleasure to introduce Dr. Holly Tuko. Holly's a big reason why I'm here at the University of Victoria. I moved here about eight years ago. Holly Tuko is Professor in the Department of Psychology and a Research Associate now at the Institute on Aging and Lifelong Health, formerly known as the Center on Aging, here at the University of Victoria. Holly was Director of the Center on Aging from 2009 to 2014. She was influential in bringing the CLSA to Victoria and really essential to getting the study successfully set up and running here. It took many people, many hands, but Holly was just really influential in making this happen. Holly is a clinical neuropsychologist, and prior to joining the faculty at the University of Victoria, she was supervising psychologists at the clinic for Alzheimer's disease and related disorders at the University of British Columbia Hospital, and a member of the geriatric mental health outreach team in the Capital Region District. As a scientist practitioner, she has been highly active as a researcher throughout her career. She was awarded Senior Investigator Status with the Canadian Institutes of Health Research, Institute of Aging, for the period 2002 to 2007, for her research focused on mental health and aging, including the evolution of cognitive disorders. She was instrumental in developing the neuropsychological battery in the Canadian study on health and aging, a national longitudinal study of dementia, including Alzheimer's disease in Canada. Holly has been involved in the Canadian longitudinal study on aging since its inception in 2001 as the psychological health theme leader. The CLSA is designed to generate new knowledge concerning many interrelated clinical, psychological, and social factors that influence disease, health, and well-being. Holly's role has been vital to the success of this major Canadian longitudinal study. I'm delighted to present to you tonight Dr. Holly Tucho. So today I've been asked to speak to you about some of the research that I'm currently working on here at the University of Victoria. In 2016, we received funding from the Alzheimer Society of Canada in partnership with the Pacific Alzheimer Research Foundation to examine cognition in the Canadian longitudinal study on aging. So before I begin, I want to define some of these terms, so we all know what I'm talking about. The dictionary definition of cognition is conscious mental activities or the activities of thinking, understanding, learning, and remembering. These activities are often referred to as cognitive functions or different types of mental activity that we engage in as we go about our daily lives. It is generally acknowledged that adequate cognitive functioning is fundamental to living independently and managing everyday life. It's generally agreed upon that cognitive functions decline somewhat as we grow older. However, this decline typically does not interfere significantly with our independent everyday living. Neurocognitive disorders, on the other hand, are neurological or brain disorders that interfere with cognition and cognitive functions. There are many forms of neurocognitive disorders that are age-associated, meaning that they become more prevalent or more common as people grow older. Alzheimer disease and other dementias are examples of neurocognitive disorders that become more common as we age. Often, it's this change in a person's cognition or their cognitive activities that is first noticed in people with neurocognitive disorders and brings people to clinical attention. Physicians, psychologists, and other healthcare professionals typically perform an assessment of cognition or cognitive activities to determine how a person functions in relation to other people with similar characteristics, so of a similar age, of a similar gender, with a similar educational background, who speak a similar language. These and many other non-medical factors, often known as social determinants of health, contribute to one's cognitive abilities and must be taken into consideration when assessing cognition. So there are many reasons why someone's cognition may change. Fatigue or tiredness, we all know that if we've had a really taxing day, our thinking may not be at its best. Physical illness, we also know if we have the flu or really sick with an infection or something, we may not be thinking at our best. Medications can affect our thinking, and often on our prescription medications, there will be a little sticker that notes possible cognitive effects, and sometimes it says you shouldn't operate a motor vehicle or things like that. So lots of different things affect cognition. But when all of these other causes for cognitive change are ruled out, the underlying problem, if there's a problem and you rule out all those things, it may be a neurocognitive disorder like Alzheimer's disease. So it's really important to know how people with certain characteristics are expected to perform on measures of cognition, because that's fundamental to distinguishing between what's normal age-associated cognitive change and those cognitive changes associated with an underlying disorder like Alzheimer's disease. So that brings us to the second part of the title of my talk, and that is the CLSA. So you're in the CLSA, so you know what kinds of data are being collected, and you've heard a bit about the overall study. So what can this study tell us about how Canadians are functioning? So as you have heard, the CLSA is a strategic initiative of the Canadian Institutes of Health Research, one of the major funding bodies in Canada. And the Institute on Aging and Lifelong Health here at UVic, and through a partnership with Island Health, we have a data collection site here in Victoria, down at the Gorge Road Hospital, where you go to visit Joanne and the crew down there. We have 3,000 participants here in the Greater Victoria region taking part in this study. And that's one of the CLSA, as Deborah mentioned, is one of, if not the largest study of its type in the world. So here we have a picture of the data collection site team. This is from a few years ago, and so there's a bunch of faces there. Some of you may know them. Vincenza's right there in the front row on the far side here. I should get my little pointer so I can point at Vincenza. And there's various members of the team at that point in time when this picture was taken. There's some more folks from the CLSA. This is our 1,000th participant who may be here tonight, I don't know, and some of the team members at that time. And there's Lynn, whoops, back up. There's Lynn Young. Deborah mentioned Lynn, who is the other site lead here in Victoria, who's not with us here tonight. And this is participant number 3,000 and some of the team members down at the data collection site. So we've seen a lot of people here, a lot of people in Victoria have taken part, which we are very grateful for, to be able to have this amount of data. Most data collection sites are quite a bit smaller than ours, and we have a very active group of participants in the Victoria region. We've got one more picture here. That's participant number 3,075. We went past our 3,000 mark and actually collected 75 more participants. So we've done a lot of work here in Victoria over the last few years. So when we say that the CLSA is a research platform, what does that mean? It's not a research study per se, it's a platform. So a research platform is an infrastructure to enable state-of-the-art interdisciplinary population-based research and evidence-based decision-making that will lead to better health and quality of life for Canadians. So we collect the data through the CLSA so it's an infrastructure, it's a way to collect the data from people all across the country, and then researchers will get additional funding to actually analyze the data and do specific studies. So the CLSA itself is a data collection mechanism or platform. So data is collected two different ways for this study. 30,097 people have been seen for face-to-face interviews through home interviews and visits to the data collection sites across the country. The data collection sites are the red dots, so here they are, St. John's, Halifax, et cetera. This is where the 30,000 people have been seen, and here we are on our little rock in the ocean. We also collect data, and we have collected data from 21,241 telephone interviews to include people who may not live near a data collection site. We still want to know about those Canadians, but they don't live close enough to a data collection site to come in and be seen face-to-face, so we do interviews with them over the telephone, and they are the black dots. So you see all across the country there have been telephone interviews going on, so we get a very good population-based sample of the whole country. So as you know, being participants in this study, we find out an awful lot about you in the data collection. So it's a study that collects information across a broad range of topics in quite a bit of depth. So you see all the different things that we do to you here. We look at your height and weight, your waist and hip measurements. We don't tell anybody those things, so your blood pressure, your grip strength, see how fast you can get up out of the chair and go. We look at your vision, balance, spirometry. That's lungs, right? We look at body composition. Put you in the dexa machine. We look at your bone density. Your aortic calcification, your ECG, carotid thickness, intima-media thickness, and there's our cognitive assessment that I'm going to tell you a bit more about today. We also get specimens, so blood and urine, and we get all this other information where we ask you questions about chronic diseases, medications, health care utilization, oral health, blah, blah, blah. And then psychosocial, we have social participation, social networks, caregiving, moods, psychological distress, PTSD symptoms, injuries, personality traits, retirement planning, and then lifestyle and social demographic things, smoking, alcohol consumption, physical activity, birth location, marital status, education. We know you better than you know yourselves. So tons and tons of information, and that's going to be the most important part of this study. Most studies only maybe look at personality or they only look at social participation, but we look at all of these things in 50,000 people. So we'll be able to make connections across these different areas where most studies can't do that. So in the future we'll be able, so here we talk about administrative linkage. In the future those things may happen, we're not actually doing that at the moment, but there's the possibility that we can link with other data if you give us permission to do that. So at our baseline, the first time you came in to see us, most of our participants were reasonably healthy, and so we have a benchmark for comparison that can be used for comparison with other people in Canada. So the way the sample was selected was a random sample, and also we screened for severe health problems, so at baseline most people were relatively healthy. So our little cognitive measures there, what I'm going to tell you about today, is how these can be used to create comparison standards for Canadians that can be used to help identify changes in cognition greater than would be expected for other Canadians, and that links back to what I was saying about neurocognitive disorders. So you will recognize some of the measures here. So again, there's some pictures. This is from our data collection site here. You'll recognize the mosquito there who takes the blood, and here are the cognitive assessments. These are the assessments, some of the assessments that we collect from you. So overall, I guess I can look back there, overall we now have data for 51,338 participants that are available to the research community. So any researchers can request the data to be able to analyze and ask a huge variety of questions of the data. So we have comprehensive physical assessment data and the blood markers from 30,000 and 97 participants who visited the data collection sites. In 2015, we applied here at UVic, applied for funding from the Alzheimer's Society of Canada and the Pacific Alzheimer Research Foundation to examine specifically the cognitive measures in the CLSA telephone and comprehensive interviews and received funding in 2016 to conduct this research. So our team of researchers, I'm the lead researcher here at UVic. We also have team members from across the country involved in this study. So Lauren Griffith at McMaster, Megan O'Connell who is a UVic graduate who's now an associate professor at the University of Saskatchewan, Martine Simard at Laval University and Vanessa Taller at the University of Ottawa. Those are our two French speaking colleagues because we're analyzing the data both in French and English. We have research associates here at the University of Victoria who actually do the work. So we have Stacy Vaughan down here in the front and Helena Cadillac who crunched the data and create many of the graphs that I will show you today to help us move forward to figure out how to deal with 50,000 cases to make sense of it all. And they're very good at that. So the purpose of our research is to examine how Canadians typically perform on measures of cognitive functioning so we can understand the health and lifestyle factors that are affecting cognitive function and as noted earlier there are many non-medical factors that contribute to one's cognitive abilities and must be taken into consideration when assessing cognition. These include things like educational attainment, what language you perform the tests in, your birth cohort which means what point in history you were born and that's reflective of the time when we grew up and so there are different social factors at different points in time that can affect our cognition. So there are many reasons why someone's cognition may change from one point in time to another. I mentioned things like fatigue or illness or medications and we will examine how non-medical factors as well as medical conditions may affect cognition as we determine how Canadians typically perform on these tasks. With this knowledge then we can then develop Canadian comparison standards for both our English and French speaking Canadians as we go forward and this is one of the, I think one of maybe two or three studies where the measures were administered the same way in French and English. So we will be able to have standards that go across both languages in Canada. It's one of the unique features of this study and something that will contribute to our Canadian landscape in a way that no other study has been able to. So with this very large sample that we have we'll be able to take many factors that affect cognitive functioning into consideration that other researchers in the past have not been able to do. Most studies have quite a bit smaller sample size than we have and can't look at as many variables as we can look at. So this will provide us with more accurate standards to be used with other Canadians for identifying when there might be a significant change in cognitive functioning. Okay, so once we've developed our Canadian comparison standards then we plan to create computer algorithms and other tools for interpretation that can be used by health providers in clinical practice. So it's one thing to generate the information and it sits on the shelf in my office that's not particularly useful to the rest of the country. So we're going to be working with clinicians again across the country to see what form they would like this information in so they can use it. Do they want an app for their phones or do they want something on their tablets? How are physicians accessing data these days and can we provide useful information to them that they can use on a daily basis? So this then will lay the foundation for refinement of these comparison standards as new information becomes available over the course of the study. So with the future information we'll then be able to characterize changes in cognitive functioning that are occurring as a function of the normal aging process that we all expect or that are more than that and need further consideration, things like Alzheimer's disease. So why is it so important that we have Canadian comparison standards? Why don't we just use the same standards that they use in the US? Why do we need Canadian standards? So before I go on and tell you about what we're doing with the data it's important to understand why we need to do this. So first of all the existing normative standards, most of them are based on non-Canadian samples and this is particularly important for our French speaking colleagues in where they don't have comparison standards and using English standards when someone is speaking a different language may not be particularly useful or give you very good results. So even for our English speaking people in our country relying on data collected elsewhere in the world may not provide the level of sensitivity to change desired within our healthcare environment. Our healthcare environment is very different from others. The second reason why we need to do this is existing normative standards may be outdated. The collection of data for the creation of normative comparison standards can be expensive and time consuming and for these reasons existing data may be out of date and not relevant to the current population. So if you look in the literature many of these studies are from the 80s and that may not be relevant to the population who is aging today versus the population who is aging back in the 1980s or 70s. The third reason is that existing normative standards for measures may not cover the full spectrum of ages from midlife to later life. So sometimes in previous research the age range of interest has been restricted and didn't cover all age groups. For many years people over the age of 65 weren't even included in research on cognition and then there were other data sets that only included people over the age of 65 and so we had no idea what was going on before or after depending on which set of studies you were looking at. So this limits what data can tell us about changes over time if you start at one place and stop at another. In the CLSA we go from age 45 to 85 and we're going to follow all those people along. So we get the whole midlife to late life spectrum. It gives us a lot more information than previous research has been able to provide us. There's still more reasons why it's important to do this. Existing normative standards often may not take into consideration important health and lifestyle factors. So again when you have very small sample sizes you can't look at very many factors. You can only look at one or two things that may be affecting cognition maybe age and gender. With our sample because it's so large we can look at a lot of things. We can look at age, gender, education, social participation, various medical conditions, etc. etc. And the final reason we have here is that existing normative standards may be available for only individual measures one measure at a time whereas we have a battery of measures. So typically normative standards were developed on individual measures and as I mentioned before it can be very expensive and costly to collect this data so that was one of the reasons they'd only look at one thing at a time. But clinicians typically don't just use one measure at a time. They use batteries of measures. And when your comparison standards are for each measure the possibility of making a mistake is multiplied by the number of measures that you use. And so if you don't correct for that you can be identifying people as impaired when they're really not. And so we will be able to take that into consideration when we're developing our comparison standards because we don't want people making that very costly mistake of identifying people as impaired when they really aren't. So what's our plan? What are we doing? We're not done so I have to tell you the plan and then I can tell you where we are in the plan. So the plan is we need to select a neurologically healthy sub-sample and before anybody does any research they have to have a plan and know what they're going to do and that's what writing research grants is all about is laying out your plan. Here's what we plan to do and here's what it's going to tell us. So first we need to determine how to select a neurologically healthy sample from our overall data set. So we're working on that. I think we've come up with some solutions. We also have to be concerned about well maybe people didn't hear the question and that's why they didn't answer it properly. So we have to take hearing and vision and various other things into consideration. And then we need to examine the performance on each measure and clean the data. Stacey can tell you all about how many hours it takes to clean a data set with 50,000 people and all those variables in it. So sometimes we get impossible scores. Nobody in their right mind can do that task that quickly. Something must have gone wrong with the machine. Not that our machines ever have problems but we live in the real world and sometimes there's a problem. So Stacey's in there looking to see are there any impossible scores and if there are we have to get rid of those. So we're working on that and then we need to combine the measures to minimize that overall error in identification for poor performances. So we want to increase our specificity for typical performances, right? We don't want to be making those errors of identifying people who as impaired who aren't really. So we need to control for that. And then we need to propose user friendly tools for interpretation that can be used by healthcare providers in clinical practice. So what we're then going to do once we get to that point, we're not there yet, then we're going to go to healthcare providers across the country and we're going to present them with some mocked up tools and we're going to say, what do you think? Would you use this tool? If so, great. If not, what would make it easier for you to use in your daily practice? And then we'll rework the tools to address the concerns and maximize their utility for easy access by clinicians. So our findings to date. We've started with three different lines of investigation. First, we began by looking at the performance of you, all the CLSA participants on the measures of cognition. And so I'm going to show you three different sets of analyses we've undertaken. First, I'll share with you some comparisons with other studies that use similar measures. These other studies have much smaller sample sizes and come from other places in the world. But we wanted to see how we're lining up with what has been done elsewhere. Then we wanted to look at the relations between the number of medical conditions reported by people and their performance on cognitive measures. And thirdly, and many studies haven't been able to look at that, again because of sample size. And then I'll report on some observations of how participants, our CLSA participants, remember to remember. So you may remember that there is a task or a couple of tasks where you're told down the road in a little while I want you to do this or that or when the bell goes off I want you to do this or that. So you need to remember to do something in the future. It's like remembering to pick up milk on the way home from work, right? Or remember to mail that letter on your way out. So I'll tell you a little bit about what we've seen there. So the comparison with other studies. We looked at three measures. A word recall task. Most of you don't like that one, but it's important. A task where you generate words. So we have you generate words that start with a letter. And then a switching task where you have to go back and forth between two different tasks. So we looked at the data from the 20,000 telephone interviews for this. So you're off the hook. None of you are in that sample. So we looked at these three measures of cognition. A memory task, a switching task, and a generation of word tasks. And these tasks are similar to tasks that have been used in other research. But most studies don't collect the information over the telephone. They collect the information in person. So we wanted to see did that make a huge difference to how people perform if we're doing it on the telephone or if they're doing it face-to-face. So what did we see? So here's our word recall task. The blue lines are from another study by Mitrashina in 1991. And the red lines are our CLSA data. And these are different age groups across the bottom. 50 to 65, 66 to 70, 71 to 75, 76 to 85. And basically we're getting very similar results to what they showed in the Mitrashina study. That's good because that means that doing it over the telephone doesn't make a huge difference. And so that was good for us to know. We've published this paper. It's in the clinical neuropsychologist. And some of the studies did differ from CLSA. This one didn't. But we wanted to see what the factors were that might be contributing to differences if there are differences. So we've looked at that. Then we looked at the word generation. So that's generating a number of words that begin with a particular letter. Again, we've got age groups across the bottom here. And we compared it to a study by Tombow in 1999. Tom Tombow trained with me many years ago. So it's nice to be comparing ourselves to people we know. And again, we see that there... Where am I? Here I am. So there are significant differences between our sample and that of Tombow for the older two age groups. So you see there's a difference there and a difference there. For both the Tombow and the CLSA participants though are performing slightly better than Tombow's sample. And there's good reasons for that because his sample was from a study of... They were normal controls in a study of dementia. And so it's a very different sample selection process than what we go through. So we're not particularly perturbed by the fact there was a significant difference there. In both CLSA and Tombow, you see there's a decrease over the age groups. And that's quite consistent with other literature. So we saw some differences, but we also saw some similarities. And this is our switching task. And this here we're looking between languages. This task has not been used very much in the literature. So there's not very much other literature to compare ourselves to. And where it has been used, they have very, very small sample sizes. So it's not really fair to compare 20,000 people to 15 people. Doesn't give for great stats. But what we did here, we looked at French and English. So is there any reason why we should suspect a difference between English speakers and French speakers on this task? So again, we see a decrease across age groups in both French and English samples. We also see a very small difference, particularly up at the upper age ranges between the French and English speakers. These are new findings because this task hasn't been used very much in the literature before. So we're very interested to speak with our French speaking colleagues and see if there's some reasons why we might see these differences in language on this task between the two languages. So we're contributing something new to the literature that no one has looked at before. The second thing we looked at was do medical conditions affect scores on the measures of cognition? There's good reasons to suspect that medical conditions do affect your cognition and maybe the more medical conditions you have, the more it affects your cognitive functioning. We know from smaller studies that are more focused on particular specific medical conditions we know that certain things can affect cognition. So we also know that inclusion of an examination of medical conditions when developing comparison standards like we want to do is often recommended in the literature but nobody has had the data to do it before. So we wanted to look and see is this something we should be controlling for when we're developing our normative standards because we've got the data to do it. So first we looked at the relation between self-reported medical conditions and measures of cognition. So the first thing you do here is you estimate what the level of functioning should be or here we're talking about very low scores. So the percentage of people with very low scores on our cognitive measures. We estimate how many low scores we would expect. Then we look at our data, our actual data to see if there are more things happening than we would expect and there aren't. There are fewer things happening than we would expect by chance. And this tells us that the number of medical conditions doesn't affect cognition. Again lots of people have suspected they do and want it to be looked at so we've looked at it. Now the caveat here is this is the baseline, right? These are fairly healthy people. This may change over time as people start to have more medical problems that may change but right now we don't have to control for that in our comparison standards. The number of medical conditions isn't affecting how people perform. So then we wanted to just check our stats because when you're doing stats you always have to check your stats to make sure you did it right. So we said well we know that age makes, has an effect on cognition. So let's do the same procedure only this time we'll look at age. So again we estimated how many low scores we would expect on the basis of age. And then we looked at, oops this way, estimated is the blue and the red are the actual. And you see here we estimated more than had low scores but here in the older age group we see that age is affecting cognitive functioning. So we checked our stats and our stats are good. We know that age affects it so we have to control for age in our comparison standards but medical conditions don't affect. So that's a new thing that other people haven't been able to look at before. So the third thing we then have looked at. So that paper is under review. Well it came back. We submitted it. They wanted revisions. We've submitted the revisions. Fingers crossed that will be published within the next month or so. Okay now the third area we're looking at is remembering to remember. How do people perform on that? We know that remembering to remember is an important thing, right? We all have to remember to do things in the future. Cell phones are helping a lot. We can set our timers that will remind us oh we got to go and take the soup off or whatever but we still need to remember to remember. And there are not many large studies like ours that have been able to look at this kind of behavior. So remembering to remember. So we mentioned the tasks before. There's the task when a timer goes off you're supposed to do something. That's an event-based task. Or at a specific time you're supposed to do something. So that's a time-based task. So there's two different tasks. It's a relatively new measure. Hasn't been used very often. And we've had the opportunity to take a look at performance of our neurologically healthy sample both in English and French. We examined the performance for men versus women. For different age groups. For language of administration. And for educational attainment. So when we look at men and women. No difference between men and women. That's a good thing. Some of us might not believe that. But that's what the data says. So here we're looking at the event-based task. So then we look at English and French. And similarly we saw that English and French speakers don't really differ on these tasks at all. And that's a good thing too. And then we looked at age and language. So here we have language. Red being French. Blue being English. Across the different age groups. And what we see here. Is that there is a decrease by age across the age groups for both languages. But we see that difference is greater here at the upper age groups for the French speakers. Greater than for the English speakers. So that's a significant interaction of age by language. So that's going to take us some time to figure out why that's happening. But again there's absolutely no data available on this task for French speakers anywhere. And very little available for English speakers. So we're contributing something new to the literature that as we go over time we may be able to see what's underlying these differences between the French and English samples. Then we looked at level of education. So here we have less than secondary. Secondary education. Some post secondary and post secondary education. Again English is the blue. French is the red. So here again we see English speaking groups differed in educational attainment. Performed differently on the tasks. Okay so that goes up. But our French speakers go up and down and up. Why? I don't know. But we have this inconsistent finding. So we'll have to see if there's something else contributing to that finding. But again on this particular measure we don't know very much about it. So we're starting to find out some information about what might be going on and what are the factors that are affecting performance on that specific measure. Okay so to summarize then our measures are generally comparable with similar measures used in other studies even when we administer them over the telephone. When there were differences our sample performs better than other smaller samples. We demonstrated that the number of self-reported medical conditions does not appear to affect scores on cognitive measures in our relatively healthy CLSA sample. Using a similar approach to that used for the medical conditions we demonstrated again as has been demonstrated many times in the literature that age affects performance on cognitive measures and this is consistent with the previous literature. And then some of our measures are relatively new like our switching task and our remembering to remember task. And we're able to provide emerging information about performance on them for people of different ages, for English and French speakers and to look at various other factors like educational attainment, gender, those kinds of things. So I want to emphasize that these are preliminary data. For the data from the telephone interviews the medical information is self-reported information and we have no information about the severity of these health conditions just that they're there. From these analyses we've selected a neurologically healthy sample from our overall CLSA data set. Only a relatively small number of participants reported neurological conditions and were removed from the analyses as it's well known that neurological conditions can affect cognitive functioning. We're currently examining information from data collection sites so what I showed you was from the tracking cohort, the telephone interviews. We're now doing the same kinds of analyses on the data collection site data. That's all of you. So now we're going to know how you perform on these things. And we can look at much more other information about factors that may affect cognitive functioning for our participants. So we have much more to do to realize our goal of characterizing how Canadians typically perform on measures of cognitive functioning and developing easily accessible comparison standards for use by clinicians. So our steps from here is to continue with what we're doing to develop the comparison standards to create our tools that can be used for interpretation by our colleagues in the healthcare field and to lay the foundation for refinement of this information as your longitudinal comes in. We can refine it and make it better and better over time. So our funding goes until June 2018 and we anticipate sharing this information as we're moving forward and rolling out new pieces of it. We wish to share this information with researchers, clinicians, and other interested parties including people like yourselves as we take each step in the process of exploring this current extensive collection of information on Canadians. So thank you for supporting the Canadian Longitudinal Study on Aging and I'd also like to thank our funders, the Canadian Institutes of Health Research and the Canadian Canada Foundation for Innovation and the funders of our project, the Alzheimer Society and the Pacific Alzheimer Research Foundation. And all of you for supporting the CLSA and this and other research from the study will be a benefit to all Canadians. Thank you. Questions? I have one. Where's the... Hi, my name is Alice Howes. Just recently on TV there was the Lieutenant Governor of Alberta and I'm sure a lot of people saw it on TV where he was diagnosed with Alzheimer's and it wasn't Alzheimer's. His doctor took a video of him the way he walked and he was noticing when he was in the legislature that he was slurring his words or forgetting. But he wasn't slurring his words as much as he was forgetting and he talked to his wife about it. They went to see the doctor and apparently they discovered that it was something pressing on that part of his brain and they did the surgery and he's walking quite fine now. Now have you looked into this? There are many different reasons why someone's behavior and cognition may change while memory may change. Alzheimer's is only one of those reasons. There's at least 36 other reasons and some of them have to do with remediable pressures on the brain, things like normal pressure hydrocephalus or a bump on the head can create a little bleed inside the... between the skull and the brain tissue that can affect behavior and that can be relieved and change a person's trajectory altogether. So yes, any change in cognition there are many different reasons why that can happen and so one needs to go and have all the scans and the blood tests and all the different medical work up to try to figure out which of those reasons is causing the change. That's our physician and I think it should be. Part of the reason for that is we don't know what the data means yet because we're still researching it. For example, if I release the data on the remembering to remember there are no comparison standards. So to release that to your doctor what's he going to do with it? He doesn't know what it means because we don't know what it means. So you do get some information that the study provides to you. But we certainly can't release all of that information because much of it we don't know what the meaning of that is in the context of your situation. I'm just going to have one of these guys here address that because I know about the cognitive tests. I can't tell you about whether the other tests would give useful information to your doctor. So Joanne or Deborah could one of you address that comment? Yeah, we don't actually get all those results they're sent directly to McMaster. And again we don't interpret them. It's a research study and there's guidelines but we're not your clinician and your physician if he's concerned about osteoporosis will be doing a scan himself. So we're trying to gather this big information to make sense out of it but it's a research study and not a clinical study. So I'm sorry, I know that's a frustration for many people. Just to add to that you will or you should have got a letter or you will be getting a letter that for that particular measure that gives you your risk of developing a fracture in the next 10 years. It's a frack score. If you have not got the letter yet it will be coming from the baseline. If you've come through the clinic recently that information will be down the road but your baseline measure will come to you. I'm just wondering why you take out all the neurological diseases. For our purposes we want to look at how healthy people perform on cognitive tests. Neurological conditions will affect cognitive tests and so we take those out so we're only looking at the people who don't have those problems. But if somebody has Alzheimer's that is a neurological problem. But we're not trying to identify Alzheimer's. We're trying to create comparison standards on healthy people that can then be used to identify people with neurological conditions. So if you take somebody out of the study and not out of the study only out of our data analysis we will still be in the study and will be used for other purposes. Our purpose is very specific to develop the comparison standards. Thank you. Yes. In all of your mentions of age you said that you're going up to 85. Those of us that are 85 are we now aging out of your study? No we will follow people that come into the study from 45 to 85 and then we follow those people for 20 years. So we'll be following you until you're 105. Okay. I was intrigued by your graph around the relationship between medical conditions and performance on cognitive tasks. As I read the graph it was not self-evident to me that there was no relationship. Could you go over that material again or I apologize because I know it's just repeating what you said very clearly. Your statement is clear the graph didn't seem to show it. Okay. It's complicated to show it in a graph. Where are we? There we are. So here are the estimates of how many poor scores the data should be giving. It's an estimate based on the correlations between the measures. Okay. And here's the actual occurrence of low scores. So it's way less whether you have zero medical conditions one medical condition or two medical conditions it's way less than we would expect. We collapse them. Two plus. Two plus because as you go more than two you get two people, three people, one person it goes out in a small tail so we collapse them to two plus. So no matter how many whoops back up here we're still actually getting fewer low scores on cognition than we would expect just by chance. We haven't got the medication data yet it's possible that medication also severity of medical condition we don't have that data for the telephone interviews. We will have that data with you guys data we will be able to look at severity as well as this is all self-report and so we'll actually have measured health as well as self-report. So we'll be able to take this another step further but from this data on self-report that's what it's telling us. But again it's a very healthy sample we're not going back to see anything at this point in time. I was curious about why the normal level of sexual functioning wasn't included in your data gathering. Normal level of? Sexual functioning? Like normal? I don't know. Do you think that's something we should be collecting? I think it is in one of the coming up modules. That should be. Okay. Added in future years and we're considering but of course it's tricky getting accurate measures, right? Your study is for 20 years. Is that because you hope that funding will continue it? Or why just 20 years? 20 years? That's what was proposed if we can get funding for 40 years I'm sure they'll keep going. I won't be involved but I'm sure the others would keep going if they could. But that was the period of time to follow those 45 year olds up to 65. That was the reason why that 20 year period was picked but if we can get funding for 40 years I'm sure they'll do it. I just won't be involved. Yes. Hi. What I wanted to ask is have they taken into consideration hereditary things? My grandfather had dementia and my mother's just recently been diagnosed with dementia. So I wanted to know how if that was part of the study so that I could understand what the progression is with the family. So we aren't collecting any family history like that. We are collecting genetic information that may be useful in that regard down the road. Data won't be available for analysis for quite a long time but again with a study like this as was mentioned at the beginning it took us 10 years from 2001 to 2011 to design the study to arm wrestle over which measures were going to go in and which measures were going to go out. If we had gone with our first design you would be down at the data collection site for weeks on end with us collecting data. So we had to pare down all the myriad of things that we could ask about to what was felt to be the fundamental core for healthy independent functioning. So it's not a study of disease it's a study of healthy functioning and what predicts healthy functioning so we had to leave some things out and believe me there are very many sad people in the country that we had to leave out certain things. Excuse me. Speaking of being left out it appears that I am in the telephone group and I live in Victoria I've always lived in Victoria and I understood from your selection explanation that you people who lived in the major centers would be part of the face-to-face group. Okay we got some tracking people how did that happen? Okay. So we were a tracking data site a phone we were both for a while. I mean individual? No. We began the study in 2011. 2011 was the first round of data collection. Yeah there are many many studies going on there are many nationwide studies going on so you were probably in the telephone cohort. Yeah. Can she contact McMaster? We don't have any names attached to data we can't answer that we can't answer that question. Can McMaster answer that question? I don't know. I'll have to find out. Contact me. Debra Sheet School of Nursing UVic I'll find that answer for you if you could repeat the questions. Great. A couple more questions and then I think we're going to have to wrap it up. Oh. They've got the microphones. The question about neurological effects the data was removed. What neurological conditions were you looking at? Okay so what types of neurological conditions did we remove for our data analysis? Not from the study they're still in the study but just for our data analysis? Oh here's Stacey with the answer right here. Parkinson's disease, Alzheimer's disease, epilepsy, MS, stroke and TIAs many strokes and cancers. Not all cancers. Central nervous system cancer so brain cancer. Is there any data regarding mental health conditions with cognition? We haven't looked at that data yet but we do have mental health conditions self-reported mental health conditions in there. We did look at depression and anxiety. Okay thank you. And when I look at this map of Canada our north is not represented at all. There was a decision again it's a fiscal decision. This study cost millions and millions of dollars to do to only do the ten provinces not the territories and not what's the correct term. Not the reservations. So that would be there's been talk about doing a separate sub-study for those areas but the overall study for the baseline did not do the territories. Yes but as I say they are planning a smaller sub-study to deal with some of the things that had to be left out of the original data collection. Good question. In many cultures the elderly are kept in the homes and an extended family is established in Canada and really a lot of extended care and assisted living. So many facilities now are being developed and it's a growing thing. Has the study been considered to look at the effect of this on the elderly when they are either put into a home or... Okay at baseline everyone was living in the community so at the baseline data we don't have anyone living in those types of environments. Over time people will be moving into those types of environments and then there will be an opportunity to ask those research questions but for the baseline data everyone was living in the community. So down the road yes but right now no. Of the results when I got the results of the first data collection I was interested but mildly interested. When I got the results three years later of the second one I found it very interesting to compare hearing sight all those things were interesting but what I would really like to compare is the cognition data of the first and the second and I think many people would feel that way. Is there no way that you can let us know something about that? Not until we know what it means. I understand that but even if you told us that we were significantly worse. We can't tell you that because we don't know what significantly worse is yet. But you can but if my remembering to remember is certainly something you can statistically measure from one test to the other. But we don't for that test in particular we're developing the normative standard right now. So we don't know what a bad performance is right now. We couldn't tell you what the change what a significantly bigger change than normal would be until we do the analysis and we're not there yet. There will be a point in time where we will have that information but we don't have it available right now. Okay. Thank you all. I think we should get to the if you could give Holly Dr. Tucho a big hand again. Thank you.