 Today's webinar is the Canadian Lodge-Tunnel Study on Aging, a national platform and infrastructure for researchers and trainees. We have three distinguished speakers who will overview the CLSA for us today. First, Dr. Yves Jonette, a scientific director of the Institute of Aging of the Canadian Institutes of Health Research, who jointly organized this webinar. He received his doctorate in neuroscience from the University of Montreal and completed post-actorial training in neurophysiology and behavioral neuroscience. His principal research interests focus on the aging process and cognitive deficits in the aging. Next, Dr. Laura Griffiths will present on the CLSA platform and infrastructure. She is the associate scientific director of the CLSA and an associate professor at McMaster University in the Department of Health Research Methods, Evidence and Impact. She holds a PhD in epidemiology from the University of Toronto. Her research interests include physical functioning, injury and aging as well as harmonization of longitudinal data. Third, we will have Christy Castanian, a doctoral student of epidemiology from York University School of Kinesiology and Health Science, who will share her experience using the CLSA as a trainee. Finally, remember that there will be a question and answer session at the very end of the webinar, but feel free to add any comments or questions as we go along in the chat box. So first, we welcome Dr. Yves Jonette, who has a couple of words of introduction and welcome. Dr. Jonette. Thank you, Carol. It's really a pleasure to be with you today from Whitehorse, in fact, UConn, where the third pathway for equity for health in the indigenous population is occurring. Another important aspect of the C-I-H-R work, but the CLSA, the Canadian Longitudinal Study on Aging, is really, really something that is very important for C-I-H-R, for all the institutes. It's something that has been prepared since a long time. We've invested approximately $18 million since 2003 to develop the CLSA. It took a long time to develop the protocol to make sure that all the questions and data would be collected in order to answer all the questions on the determinants of healthy aging in a longitudinal perspective. The data are, in fact, not only for the researchers who are traditionally associated with the issue of aging, but all institutes at C-I-H-R, whether it's diabetes, the public health environment, and so on. So this is a unique platform, and in Canada we don't have that much of those platforms. There's other countries, particularly the northern European countries, who have such platforms, such data platform, and they're extremely used and particularly used by trainees and young investigators. Everyone, of course, can have a haxis and ask questions to these data, but I would say trainees and young investigators, you are in a privileged position to ask those questions because you don't need to invest into creating a lab or in research infrastructures. The data are there. They're just there to be used and you will hear about the conditions for trainees that are encouraging trainees to use these data in the next minutes. In fact, out of all the projects that have been approved nearly 48%, nearly 50% of all the applications were submitted by trainees, and since last year or so the data are now available from the first tranche of data, and of course it will become more and more rich as we move forward, because as you will hear every three years these data will be updated with a new point in time. And trainees and young investigators, I would say, you're in a privileged position as well because you will be able to follow this study for the next 20, 23, 25 years, the time it will take to have all these data. So we count on you to make use of these data and to really contribute to identify the optimal conditions to help the aging in Canada, while at the same time looking at the natural occurrences of some health challenges as time goes by. So without any further delay, I would like to just thank the staff at CHR, Dr. Griffith and also Christy Christianian for participating in this webinar this morning, and I'm sure that at the end of the hour you will have all the information, and I hope you'll be convinced that you have a unique platform that you could use for yourself and to help health and wellness of the aging population in Canada. Thank you, Carol. Thank you. So we'll move on to the second part of the presentation, and Dr. Lauren Griffith. Dr. Griffith? Thank you very much, Carol. I'm actually particularly excited to do this talk today, because about 10 years ago I started as a postdoc developing at McMaster University, and part of my postdoc was working on the CLSA in terms of the development. So I see the I'm especially excited in terms of the opportunities for researchers, all researchers, but especially trainees. And I'm presenting this today on behalf of the CLSA Principal Investigators, Dr. Parminder Raina at McMaster, Dr. Christina Wilson at McGill, and Dr. Susan Kirkland at Dalhousie, and of course for all of the CLSA research team across Canada. Okay. Sorry, I'm just having a bit of trouble getting my next slide, but I think I've got it now. So the learning objectives are really twofold, and the first is to understand the CLSA study design and become familiar with the CLSA data access process. But I think even more important is the second objective, and as Dr. Jeanette was saying, I think the CLSA is such an important resource for Canada, and so it's really to be inspired to use the CLSA research platform. So in terms of an overview, I'll talk a bit about the background of the CLSA, the study design, the study content, and data collection, but as well about the current status and something about the demographics of our CLSA sample. And again, part of the big one of the big focuses today is to talk about data access. And here actually you could see on the left hand part of the slides is some of the CLSA teams across the country who are collecting data as part of the CLSA. So the CLSA was a strategic initiative of the CIHR Institute of Aging, and it's been on the Canadian research agenda since 2001. As I said, there's three co-principal investigators, but it's really supported by more than 160 co-investigators from 26 institutions across Canada. And when I show you a bit more about the content, you'll see I think one of the biggest strengths of the CLSA is the multi-disciplinary focus. We have researchers and experts in the areas of biology, genetics, medicine, psychology, sociology, demography, nursing, economics, epidemiology, nutrition, and health services. All of them are helping us design the breadth of data that are needed to answer important interdisciplinary questions. And again, as noted, the CLSA is the largest study of its kind to date in Canada in terms of the breadth and depth. And we're actually following more than 50,000 participants and we'll be following them for over 20 years. The aim of the CLSA is to examine life and health transitions and capture trajectories to enable the identification of modifiable factors with the potential to inform interventions for prevention, treatment, and impact to improve the health of populations as they age. And as you can see here, the aim is a fairly high-level aim. In terms of the CLSA, our funding is really to collect data that are made available then to researchers. So it's not a specific study that would have very specific aims and research questions. It's one that is collected so that we can and that we can answer a number of research questions. And that really falls in line with our vision, which is to create a research platform infrastructure to enable state-of-the-art interdisciplinary population-based research and evidence-based decision making that will lead to the better health and quality of life of Canadians as they age. And this slide tells you a little bit about the journey so far. And again, I think this really underscores the utility of using CLSA data when you think about the amount of time to create a cohort and a data resource, a rich resource like this that is available now to all Canadian researchers and trainees. So as I said before, it started in a call for proposals in 2001. There was a protocol development phase. There was a set of feasibility studies. There was validation work and pilot work. But one of the really important points is this orange bar, which is funding that was received from the Canada Foundation for Innovation. And this funding really enabled an important aspect of the CLSA. And that is one that was allowed us to create our infrastructure. So we were allowed to construct data collection sites across the country that had standardized equipment. We were also able to create our enabling units. So we have the National Coordinating Center and the Biorepository and Bioanalysis Center at McMaster. We have the Statistical Analysis Center at McGill. We have a genetic and epigenetic center in Vancouver. And we also were able to create the infrastructure to conduct computer-assisted telephone interviewing. So the next phase, so before we even got to the data collection phase, there's clearly a decade of work done. But the recruitment happened and is completed over a five-year period. And here you can see that we're in the, well we're about two-thirds of the way through our first follow-up data collection. So in terms of the study design, the target was to recruit 50,000 women and men age 45 to 85 at baseline. And of that 50,000, 20,000 were targeted to be a random sample from within the 10 provinces. And these participants would provide data via telephone through computer-assisted telephone interviewing. And then about 60% of the CLSA sample or 30,000 were to be randomly selected from geographically restricted areas, but essentially within 25 to 50 kilometers of one of the 11 data collection sites. And the geographic restriction was required because these people provided questionnaire data but through a face-to-face in-home interview, as well as attending one of our data collection sites, whether there was clinical and physical test done, and if they consented to provide biological samples, both blood and urine. And over I think about 93% of participants were consented to provide biological samples. At the bottom of this slide you can see as well kind of where we are in terms of our data collection. So the idea was that we had five years to recruit our sample, but then every three years we have a new wave of data collection. So as I said, we're about two-thirds of waves through our first follow-up, and in 2018 we'll start into our second follow-up. And so there's actually seven full waves of data planned, and that's our active follow-up, which is done every three years. But there's also then a plan to do data linkage to augment our data with passive follow-up. And essentially, part of both the people who conducted the interviews by telephone and in person were asked whether they would be willing to provide their health insurance number and allow us to link with administrative databases. And again, over 90% of participants were willing to do this. So we are in the process of developing and negotiating how we are going to do this administrative data linkage, which you can imagine is quite a complex undertaking, but that is what we plan to have as part of the data that will be available as part of the COSA. And this next slide is meant to give you an idea of what our population looks like. So the purple dots represent the people who are part of our telephone interview cohort. They are from the 10 provinces. The red circles identify where our data collection sites are. So although, again, it's not a random sample of the Canadian population, you could see that it represents both the Pacific, the Prairies, Ontario, Quebec, and the Atlantic provinces where we have our data collection sites. In terms of defining the cohorts, as I said before, we included Canadians that are 45 to 85 years old at recruitment. And the idea here was to capture baby boomers, so the people who are between 46 and 64, as well as members of what we call the silent generation. And the idea here is that the healthy aging and aging may differ a fair bit in terms of the baby boomer cohort than cohorts before. The other thing that this really allows us to do that is different than many of the aging cohorts is many of them focus on the aged yet or they look at aging issues in the older just focused on older age groups, say 65 and older. Here looking at 45 to 85 lets us really look at healthy aging interjectories, not only of diseases, but also how people move along with aging and all the certain, all the specific, you know, physical, social, and psychological aspects of that. In terms of the recruitment, we had three main sampling frames. Our first one was part of a partnership with Statistics Canada. And I'm sure many of you have heard of the Canadian Community Health Survey. And the healthy aging CCHS was done in 2008 and 2009. And this was actually a collaboration between Statistics Canada and CLSA researchers in terms of developing the content of the CCHS healthy aging. But one of the things that is unique to this survey and had never been done before is Statistics Canada also allowed us to use it as a sampling frame. So CCHS participants in the healthy aging survey who would be eligible to take part in the CLSA were asked if they would be willing to provide content or their contact information to the CLSA researchers so that we could reach out to them and see if they would be interested in participating in the CLSA. We also had partnerships with Provincial Ministries of Health. So in in provinces where we were able to do this, we used health card registration databases. And for those of you who are familiar with this, it's a fairly complete sampling frame. It's usually about 98 percent of the population of a province is included in these databases. And so here we would ask the ministries, we'd give them age and sex strata, the number of people that we wanted to have invitation sent to. The invitations would come directly from the ministry and then if people were interested in the CLSA they would return a consent to contact form to us and then the CLSA would follow up with that. The third sampling frame that we used was random digit dialing. And we did that through a marketing firm, but we also developed our own infrastructure eventually in the CLSA through our computer assisted telephone interviewing sites to actually do some of this random digit dialing recruitment as well. So in terms of the exclusion criteria, and this is at baseline of the CLSA, essentially it was driven by our first sampling frame which was the CCHS, Healthy Aging. And Healthy Aging excluded residents of the three territories, people living in an institution, living on First Nation reserves and full-time members of the armed forces and temporary visa holders. And the CLSA added two criteria. One was cognitive impairment at baseline again. And this was because we needed to get signed informed consent to be in the study over 20 years. And those that were unable to communicate in French and English because we had we were only able to have our validated questionnaires available in both French and English. Now again it's underlined here these are the exclusion criteria at baseline. Clearly in a study of aging we're very much interested in for example, although it's a community living population at baseline, we're very much interested in transitions in living arrangements for example in into long-term care into other institutions as well as as well as transitions that may make it so that people are not able to participate actively on their own. So for example cognitive impairment where we're developing proxy interviews as we move forward. So although they're excluded at baseline the intention is to be as inclusive as possible as we move along in our 20 years. Just a bit of terminology and I may have already used these terms before in the talk because we're so used to it in our CLSA. But we call the cohort where we do the telephone interviewing where we targeted the 20,000 out of tracking cohort. And we targeted 20,000 we actually ended up recruiting 21,241. The 30,000 who had an in-home interview and came to one of the data collection sites across the country is our comprehensive cohort. Again we targeted 30,000 but we actually recruited over 30,097. So I'm going to talk a little bit about the study content and data collection and I'm going to spend just a few moments on this slide because I realized that there is a lot to look at here. But I think this is really again underscores when you look at these three pillars it underscores one of the great strengths of the CLSA in that the breadth and depth of information because although you could see the clearly the breadth of information here most of these dots actually represent a model module that is used to collect information in all of these areas. So in terms of doing interdisciplinary research the CLSA is really quite an amazing resource. So in the first pillar we have demographic and lifestyle variables. We have most of the socio-demographic variables that you would think that are in those studies. We also have a veteran identifier. In terms of the lifestyle we have smoking and alcohol consumption. We have nutritional risk in both the tracking and the comprehensive cohort. In the people where we do the in-home interview the comprehensive we actually also have a short diet questionnaire which is kind of a food frequency screener. So we have more in-depth information there. We collect information on physical activity health care utilization and medication supplement use. And again in the comprehensive because we're in the people's homes we actually ask them to bring out all of their prescription and non-prescription medications supplements that they're taking in regularly and we record specifically the drug information numbers from those products. So we have extremely rich information about medications that we're in the process of cleaning now. In terms of physical and psychological health again you can see that there's general health women's health chronic conditions and then again in the comprehensive cohort when they come to our data collection site there's extensive more extensive information collected about symptoms of different diseases. We collect information about sleep oral health injuries falls mobility pain and discomfort functional status and again in the tracking we have self-reported functional status in the comprehensive we actually have performance measures that are done at the data collection site. We collect information on activities of daily living both basic and instrumental cognition depression post-traumatic stress disorder and life satisfaction. In terms of social health again it's quite extensive information in this pillar. We collect information on social networks social support social participation and inequality in online caregiving or online communications in care receiving both formal and informal and caregiving and there's quite an extensive amount of information as you can imagine when we have our baseline cohort from 45 to 85 on labor force participation as well as retirement planning and retirement status. We also have information on transportation, mobility, migration, built environments and home ownership. For those people that come to the data collection site on top of that questionnaire assessment they also have physical assessments so we collect anthropometric data as well as you can see the picture in the middle that's actually our DEXA so we we collect information on bone density body composition and aortic calcification blood pressure ECG. We also do a carotid ultrasound and collect information where we can measure the carotid into the media thickness. We do spirometry vision and hearing as well as collect information. We have an image or a retinal image from all of our participants and we do the performance testing so gate speed balance and grip strength for example. In the data collection site we do also an enhanced cognitive battery so we look at prospective memory as well as additional executive function measures and we look at reaction time and for those people who consent we collect biological specimens so we collect blood and urine and again I think over 90% of the participants in CLSA consented to give biological samples. And here again is again there's a lot of information in this slide but if you look at the top row the green row that is what is currently available in terms of the hematology data. So these data are actually collected at the time of the visit so there's some processing that is done of the blood and then it's aliquoted and frozen and then stored at our biorepository McMaster. As well there's additional biomarker data that will be available in mid 2018. There's some clinical chemistry biomarkers that will be available for all participants who provided biological samples and you could see that these biomarkers were specifically collected as ones that are important to the study of aging. Within those people that have the clinical biochemistry biomarkers there's also a sample of 10 000 so these people are selected to essentially be a representative sample of the CLSA within the 30 000 who have genome wide genotyping and this is actually done with the same chip that is used in the UK Biobank. Of the 10 1500 we'll have information on DNA methylation from and epigenetics and of the 1500 and 1000 again we'll have information on the tabloid mix and these data will be available the data in the blue rows will be available in mid 2018. So just to give you an idea of what our sample looks like the target was to have about 60 percent of the sample 45 to 64 because again we want to follow them for 20 years and 40 percent in the older teenage groups and you can see here that is essentially what we were able to to achieve. We were having the plan was to have about 50 50 males and females we have 50 almost 51 percent females but again very even distribution and in terms of the language of administration it's about 81 percent is in English 18.6 percent of the interviews were conducted in French and about 84 percent of the sample was born in Canada. Again here looking at the participants by province you could see that in the tracking cohort essentially the allocation of the sample so we wanted to have about 20 000 but it was essentially done based on the size of the province so you could see Ontario and Quebec have the biggest sample as part of the tracking but having said that we also wanted to make sure there was a minimum number in each of the age sex strata so in PDI they were a little bit over sampled. In the comprehensive the target was to have about 3 000 at each of the data collection sites so you could see the provinces that had two data collection sites have a little over 6 000 the provinces that had one data collection site has about 3 000 and Newfoundland because of the population available had a little bit of a smaller sample size but that was taken up then in terms of the other data collection sites so we have again the total is still over 30 000. In terms of data access and I'm going to again specifically talk about the baseline data the CLSA was designed as a research study but it's funded as a research platform and our success is really if we get Canadian researchers and researchers internationally who are interested in using this resource it's extremely important that these data be used because it is such an important resource and that is available to researchers that can be part of many different programs of research. So who can apply for these data? Researchers based in an academic setting and research institutes in Canada and elsewhere can apply and there's a little asterisk with elsewhere because as yet biospecimens cannot be released to Canadian or to researchers outside of Canada and what's important as well for the trainees listening today is that graduate students and postdoctoral fellows based in Canadian institutions or trainees studying elsewhere but funded by a Canadian agency are able to apply for these data. What do you get? So there's the alphanumeric data on all 51,338 participants. There's additional raw data that are very that are available upon request so there's some additional data from the cognitive battery for the ECG spiramity for example. There's also de-identified open text for selected variables and here one thing that that the CLSA collected there wasn't a lot of open text but one thing that's collected was asking people what they thought healthy agent was so that is available to researchers as well as some additional de-identified open text for example in terms of occupation and industry. Sampling weights are available. We have sampling weights for the tracking cohort for the comprehensive cohort and for the combined CLSA full cohort and there's also additional some additional data as I said that we are working on creating linkages with data from the CLSA and we currently have some linked data on air pollution and meteorologic data that have been linked using with the collaboration with Health Canada and there's information there is the forward quotation areas or the first three characters of the postal codes that are available upon request. In terms of the steps this access at our access at clsa-dlcd.ca is very important. This is where you can apply for the data as well as if you have specific questions about the application process so you submit the application at preset deadlines and there's actually one deadline that's coming up in a little over two weeks. The first thing that happens is there's an administrative and statistical review to make sure that the application is complete it's then reviewed by our data and biospecimen access committee and the application their recommendations are approved by or reviewed by the senior management team. The the applicants are then notified and then there is a step in creating access agreements that are made between McMaster University who's the custodian of the data and researchers institution and so the preparation of that and signatures are required as well as ethics approval. And the reason that this is important is because unlike many of the other data sets that are available for examples who stats can and the non-public use datasets you have to go to research data center the CLSA data you actually will receive the raw data it is provided to the applicant so it can go on your computer but clearly then the agreement has to spell out the security confidentiality and scientific requirements of making these data available. So in terms of the data access timeline you could see here about how long each of the steps takes but the important one that we have absolutely no control over is the one in the middle the yellow one. So that is where the access agreements are signed so that is a negotiation between the institutions to get the signatures as well as the researcher dealing with their own research ethics board to get their ethics approval and again that is really where the time frame is quite variable. So especially in terms of people thinking about using these data for a master's or a PhD product project it's really important to think about this in terms of the amount of time so you should plan on receiving the data about six months after the submission deadline. In terms of the cost it's a partial cost recovery model. The alphanumeric data are a $3,000 straight fee and that is for alphanumeric data only. The important thing to note especially for trainees is that graduate students there's no cost for a data set if it's used solely for thesis research and for postdocs there's no cost for one data set used solely for a postdoctoral project. Again I was saying that the biospecimen data will be available sometime in 2018 and the costing of this is still in development. In terms of resources I cannot stress more how useful it is when you start thinking about using the CLSA data to come look at the CLSA website and specifically under the researchers and data access tabs what you'll find there under the researchers tabs is the protocol so you get a real idea about you know the very particulars about the study design and the rationale for the the different instruments chosen citations for those instruments as well as the data collection tool so all of the questionnaires are available and I would highly recommend that you take a look at the questionnaires. The physical assessments is information on that and as well under this tab there's data support documentation so there's documents on different areas such as the weights such as the cognitive variables and for example the the linked air pollution data there's additional information about that that will allow you to understand what we've what we've what we've collected and what is available as well as giving you some you know information that you really need to use these data effectively. In collaboration kind of along with that I would recommend that you look at the data preview portal and generally when I use this I use it in well I have the questionnaire in front of me because I think there are two different parts of information but extremely important so here in the data preview portal you can get metadata which is very high level on variable specific information so it gives you some information about how the how the variable is collected how the question is asked sometimes there's a little bit information about the coding but it also gives you an idea of how many people have endorsed different different variables so for example if you want to look at satisfaction with life you could look up the different variables that we've collected in terms of looking at the area of the information you could look at the instrument you could also look at specific variables so it's very helpful in terms of thinking about if you want to look at a research question using CLSA data you need to make sure that you have the numbers that would be available to you and it can really be quite helpful in terms of thinking about what your research question might be the other thing that is extremely useful is the FAQ so there's FAQs in the area of data access the data preview portal I just gave you a very kind of high level overview but there's a lot of information about how to navigate that and application questions and as well if you still have questions after looking at that you can email at access at clsa.elcd.ca just to give you a quick idea of the approved training projects from 2017 you could see they're quite diverse looking at model of health looking at metabolic and functional benefits looking at multi morbidity but as well here if you look at this word cloud the keywords again I think this really underscores the utility of the clsa in that you could see very strongly represented is physical health psychological health social health and really looking at these together in kind of a multi disciplinary way so the really the take home message that I'd like to leave with you is that this is a large cohort it was designed assembled at data collection is ongoing the baseline data and biospecimens have been collected and the alphanumeric data from questionnaires physical assessments and the basic hematology results are available on all 51,338 clsa participants and again underscoring that these are free for student thesis research and for postdoc projects and I would just like to take a moment to thank our funders and recognize our partners and I will pass the the mic over to one of the trainees who's actually used our data hello everyone thank you Dr. Griffiths for your presentation my name is Christy and I will be sharing with you today my experience with accessing clsa data and using clsa data um I'm just okay sorry about that so the outline of my talk will be as follows a bit of background on myself of the project objectives and I will go into more details on how to specifically access the data and go through the timeline to order the data that's specific for my case and I'll present the outputs from our project and lastly some take-home messages for you and I apologize if anything is redundant to Dr. Griffiths' talk so I'm being currently trained as a chronic disease epidemiologist after dabbling a bit in maternal child health epidemiology my research interests include a combination of aging health behavior and women's health I hold degrees in biology and epidemiology from the American University of Beirut and I'm currently in my fourth year of doctoral studies in epidemiology at York University under the supervision of Dr. Haletamin so my dissertation specifically focuses on understanding how various factors such as socioeconomic health behavior health related variables influence hormone therapy use and age at natural monopause in Canada this information is important for the prevention and risk reduction of future morbidity among older women now I would like to take this opportunity to acknowledge the mentorship and guidance of the following people who have been very supportive for my graduate career there are Dr. Zabla Sibai, Haletamin, Chris Ardern, Heather Ejel and my informal mentor Adina Zekiaz-Hazuri so just a bit of a background on my previous work my MSP thesis examines the burden and correlates of type 2 diabetes in Lebanon using a large national dataset also this study has been published in diabetes research and clinical practice during my masters I also worked on a paper on physical activity among the diabetics that was published in BMC public health as you can see from the screenshots here now these two papers have been most cited and present a cornerstone of my work so far so why did I choose to use the CLSA platform for my dissertation it is also a large nationwide population-based dataset and includes rich information on different aspects of aging chronic disease in women's health as you saw and this really enables my project to be completed so what is my project about so the project tackles the epidemiology of menopause in Canada and included two studies study one examined the prevalence and factors associated with hormone therapy use while study two and to provide an estimate of the median age at natural menopause and assess the association of various factors with age at natural menopause in Canada I'm sure I don't know why study two title isn't appearing but it's okay so I will go through this schematic diagram here with you in details but first just an overall summary of the process of ordering the data and accessing CLSA data so there are five major steps required to gain access to the data and there are one submitting an application to the access at CLSA email two the application will be reviewed by the different CLSA properties three there is the step of completing and signing the data access agreement by the different parties four datasets preparation and delivery and lastly preparing the final report after using the data so I will go through this diagram step by step and remember this is the timeline that you see are tailored to my experience so it might differ for you if you order the data before you submit the application it is important to really keep in mind the following while preparing it so it's important to one clearly assign the research team members and distinguish the roles so who's the PI who's the trainee so because the PI is the one who has to submit the application and correspond with the CLSA team throughout the study duration so fun story I made the mistake of sending in my application as a PI because I'm thinking this is for my situation it's my project one actually I'm the trainee so we had to submit the application a second time with the PI being my supervisor and she was the one who sent the first email to the email address access at CLSA and she was the one who's doing all the correspondence it is also important to obtain ethics approval for your project from your institution before submitting the application and I emphasize on before because this takes more time than you think next comes actually well oh while preparing the application it's pretty straightforward but you have to be mindful of the following you have to you have to make sure which variables are needed when completing the data checklist so it's useful to go to the data portal and look up the variables and make sure you know the ones that you need now the application is paper based with a three-page description of the project and just be sure that the application is complete and signed before submitting to the CLSA. Next comes submitting the application so our application was submitted by the PI on March 9, 2016 before getting a final decision on our application it had to undergo three reviews from three distinct subcommittees of the CLSA the administrative committee the statistical review committee and the data and biospecimen access committee reviewed our application and on July 2016 our application was approved with some recommendation which were mostly a depression very complicated one because there are a number of parties involved with lots of administrative procedures to be done and we all know these take a while and it was during the summertime when this process occurred in my case and many people were on vacation so trying to hold off them was not so easy so next we revised the application and revised the application and sent it to the CLSA email address again next we heard from the admin administrative coordinator who is Roxanne Cheeseman who then sent the data access agreement to the PI and this is to be reviewed and completed by the approved users institution so a bit of terminology so once your application is approved the PI becomes the approved user so the PI then completed the relevant section of the agreement and then forward the agreement to the office of research services at York for the institution signature and this was done by July 25 so the PI's and the institution signatures were then obtained on the data access agreement and this signed access agreement was then forwarded to McMaster via Roxanne Cheeseman and this data access agreement was then signed by McMaster more specifically the research office and Dr. Reina on September 22, 2016 so step four we hear from the data access officer who is Dr. Ishbhan Monar-Sakhach who is here today with us very thankfully to answer any questions you might have so Ishbhan as he is known shared the download link for the data set folder so this link contains the data in CSV format and it's literally in Excel format and he shared this within the very next day upon signing the data access agreement now it's important to note that the link expires in seven days and the folder which contains the data can be downloaded as many times as the number of research members there are on the access agreement so if there are 10 people who sign the data access agreement then the data can be downloaded 10 times within seven days now the data dictionary is very clear and the data is pretty straightforward again but it might be useful for you to label the variables with your own study names in order to personalize the data set and make it easier for you to analyze it so for example HRT use duration was labeled in the following way by the CLSA so WHO HRT year what what not so I then labeled it in order to make it more helpful and clear for me to use as HRT use duration so just a small tip for you okay so once you have the data you will have a specified time period within which the analyses have to be completed and this is usually within a year of the date that the data was sent and this can go up to two years after that you will have to submit a final report outlining what variables you recoded, did you derive any new variables and whatnot so in my case data handling and cleaning an analysis took me from December 2016 to June 2017 now while analyzing the data it is helpful to be aware of the changes that occur to the data during the time that you're working on it because these might affect your analysis so in my case what happened on February 17 2017 there was a data release update that was sent to the PI saying we have added sampling weights data variables to be used in conjunction with the existing weights as outlined in the sampling weights documentation available on our website so to make this clear we had ordered baseline data from the tracking cohort and we were given like the sample weights for that sample the tracking cohort the variable for the sampling strata weights however was not available at the time that we had first ordered the data but they were made available by February 17 2017 so since this data release update contained the variable that was important for the active completion of the analysis we contacted the data officer data access officer again ish on February 25 2017 and then he provided those sampling strata variables as a data release update within the same week so it is also important to note that output from the project once the analysis is done so any manuscripts you have for publication have to be first reviewed and selected by the scientific management team prior to sending them off for publication so output one in my case was the following paper which was published in menopause and output two is also done and dusted and it will also be published in menopause we'll take home messages to keep in mind one it's important to ensure that the research teams roles are clearly known and assigned and it's also important to follow up on data release update emails and it's important to also ensure that ethics approval is valid throughout the study duration it be also mindful of project time frame and deadlines on which to submit the final report last year i'd like to add that the health plsa is a great platform to use and a very rewarding training experience and i'm very delighted to share this experience with you today and i'd like to thank the following people and teams who were very helpful throughout this process and thank you for listening any questions please let me know well thank you very much and thank you all to our distinguished speakers for your excellent presentations so we have some time maybe take maybe 10 minutes go into the next hour to open it up for questions just a reminder that muting remains on so you can enter your questions and we'll go ahead and read through them and try to address them as they come up so a couple people have asked about if the slides are available but it seems like they will be posted on the clsa website and you'll receive a notification when they're available so there is that all right the first question what opportunities are there currently and in the future to study immigrants ethnic minorities maybe uh dr griffith you might want to chime in on on kind of future opportunities for for vulnerable populations certainly um one thing that we have i wasn't able to really go into exactly all of the variables that are collected but we do collect information on ethnicity and on cultural background that are available as well as whether a person was born in canada and if they did immigrate what was the year of immigration and so that data is available having said that you do have to recognize that the two of the or at least one of the inclusion criteria was being able to speak or be able to conduct the interview in either French or English so there may be some limitations there in terms of depending if you want to study recent immigrants but i would definitely encourage who anyone that is interested in this area to look at the data preview portal and you can kind of get an idea for the numbers of people that we would have in these areas thank you so i also want to point out that as i um as somebody here who can field questions we do have ish fund ulnar salt tax who is our data access officer he's somebody you'll work with closely if you're requesting data access and a very good resource here so another question is it possible to just request numeric data without the biospecimens ish do you want to field that one hi everyone um hope you can hear me all right um yes so uh the question i'm trying to find it here just so that i have it well is it possible just to request numeric data without biospecimens currently we we have alphanumeric data from the baseline cohort available to researchers biospecimens are not yet available so actually all current currently approved projects are using alphanumeric data only the data checklist that details what data are currently available can be found on our website and you can download it take a look in combination with using the data preview portal to see if there are modules and variables of interest to you but yes absolutely you can you can request alphanumeric data without biospecimens thank you the next question do you plan on adding more physiologic measures or questionnaires in the future um so i guess this might be kind of a future planning or future opportunities for the clsa platform lauren do you want to do you want to talk about kind of future possibilities of directions or how things might be added or taken away in the future certainly um when i focused on the on the content i was focusing only on the baseline and so for example in follow-up one we had modules on childhood maltreatment elder abuse epilepsy unmet healthcare needs and a couple of additional areas that were included so what we try and do is we try and balance on the importance of having the data collected in a similar way so we could look at transitions and trajectories over time with also including new and interesting areas so the way that we do this is we have a number of working groups in all different areas who review our content before every wave and suggest what might be interesting and new content and if there is new content what might we either not collect just for one wave or stop collecting if we don't need it to have that information every three years because essentially it's a big thing for us and because of a 20-year study we really want to do everything to keep people in the study and to reduce as much the burden on the participants so as much as we'd love to have you know a million things in the study we have to be very cognizant of you know the the most important thing is being able to keep people in the study our participant retention so we do have a mechanism to add new content and but again we have to balance that with participant burden thank you so another question is it mandatory to obtain ethics approval before submission of application and I might ask as well if you need to have financial funding secured before apply maybe if you can answer that sure so I did post a quick reply also in the chat box for anyone who's following along ethics approval is not required at the time of application to use clsa data we do however highly recommended because sometimes for different institutions ethical applications can take a varying amount of time and this could hold up your approval process because we do not release data until proof of ethics has been received by the clsa should your institution not require a full ethical review we just need a letter from your institutional review board to to this effect similarly for funding you do not need to have funding secured at the time of application of course as Dr Griffith had mentioned in the presentation for eligible trainees and postdoctoral fellows there are fee waivers available for the data set if you are an approved user who does have to pay the the fee you do not have to have the funding at the time you apply for access to the data and can government employees access the data from Andrea one yes government employees can access the data we do have several approved projects that are being led by government employees in in various agencies yes I think this one's for you as well so if you're approved for projects and you publish more than one manuscript it has to be only one per data request please do the clsa would be would be more than happy if you publish more than one manuscript of course we we encourage knowledge translation and the the dissemination of results based on the clsa data set as much as possible including of course presentations at conferences posters public talks at community centers for example as well as peer reviewed publications so you can answer what more than one question per data set as long as it's been overviewed in your data access proposal thanks carol for the for the position so yes as as long as your aims have been approved by the data and sample access committee you can answer more than one question and sometimes these projects evolve as you are doing the research and a new aim pops into the picture we do have a mechanism to add another aim or a new aim or change an existing aim using an amendment form that you can request through the access email and it will be reviewed by the DCAC committee and you should be able to incorporate it into an already approved project thank you so we have another question what would be the procedure for getting biomarkers measured that are not on your hemispology or chemistry list Dr. Griffith do you want to talk about spa assessments certainly I think that in terms of the process for this I would recommend that that if someone is interested in this that they contact the the biorepository and bioanalysis center there are some restrictions to this in terms of you know where these where the biomarker analysis can be it take place and and not necessarily where it can take place but more specifically about the process and the quality indicators that need to be involved with that and and really to understand that more fully I would recommend contacting the biorepository and bioanalysis center thank you maybe Dr. Griffith you're probably the best person to talk about how we base questionnaire information on how it was developed are we talking about the determinants of health being really the pushing background on what questions got entered included certainly there was as I as I kind of alluded to before there was working groups that had experts in many different areas including there's a clinical working group psychological health working group social working group there's a lifestyle working group as well as others and so essentially each working group identified the questionnaires that were most appropriate to include in the CLSA at baseline and essentially what we wanted was to have instruments that were well validated ones that could be administered by telephone or face-to-face ones that were applicable to the age group that we had at baseline so 45 to 85 and essentially ones that were including important areas and including novel areas of research that have not yet been really fully understood and that was the working groups were tasked with that and then the the senior management team then worked with that to try and devise the final content so it was really quite a it was a long term in a collaborative process in terms of identifying the content and as you kind of saw those pillars in one of the slides it was really important to make sure that there was at least a reasonable representation of many different areas of health especially and including the social determinants of health. Thank you and from Andrea Wang thanks for bringing up the the question back to the front here can we talk about why First Nations were excluded from the study as a baseline exclusion and perhaps maybe also territorial? Sure again that was based on our first sampling frame which was the Canadian Community Health Study on Healthy Aging and that was essentially that was their exclusion criteria and so that became the CLSA's exclusion criteria because those were that was the first sampling frame. Having said that there certainly is interest in in researching these populations and you know at least personally I would hope that there may be some opportunities to collect some CLSA like data it may be done in a very different way in terms of collecting it from some of these areas but it would be I think ideal to get some some additional maybe sub-cohorts as we as we move along but that's you know that would be certainly in the future. Future opportunities perhaps yeah absolutely. Christy maybe you can actually address a couple of these questions about how what it's like to go through a couple of these review processes. ASHA asked about the pre-journal submission review what kind of components are reviewed and how long that takes and Andrea Wang also asked about the statistical review that happened during the proposal process. Okay for the first question before submitting the your product to for bedding so basically you just submit the draft of the paper that you plan to submit for publication to the CLSA scientific committee mainly Dr. Skirkland, Raina and Dr. Wilson for them to review a draft of your paper to see the results of your analysis and to approve of what you've done before submitting this paper for publication and this usually takes up two or three weeks maximum for you to hear back on the status. Regarding statistical review so this step entails basically reviewing whether the proposed plan of analysis so how do you plan to answer your research question is specifically sound so whether the techniques that will be applied are relevant and whether they fully answer the research question. Thank you and then I think a very important question are there any funding opportunities to import new investigators to access the CLSA data Dr. Griffith? Certainly there actually was a recent catalyst competition to use CLSA data but in addition to that it should be I should emphasize that the the funds required to access CLSA data is an allowable expense for Canadian funding so if even if you're doing you're proposing a whole different project if a component of it is to use CLSA data that is an allowable expense for CIHR. Thank you so that was 15 minutes of Q&A I'm sure that everybody for our presenters will stay on the line and answer all the questions but I just want to remind everyone that CLSA data access request applications are ongoing the next deadline for applications is October 16th as our presenters mentioned visit our CLSA website under data access to review the available data for further information and for details about the application process you can also contact basically all of our presenters particularly particularly ish and myself for any of the presenters for more information about how to do data access also our next webinar scheduled for October 12th 2017 at noon eastern time we'll be welcoming Dr. Elizabeth Badley and Dr. Anthony Perusio to discuss osteoarthritis not just a nuisance condition of old age and overview of findings from the Canadian Unstable Study on Aging so please register soon and join us for our next month webinar so going back to the questions can data access be refused and based on what criteria ish do you want to field that sure we we try to work with applicants as far as possible to enable data access to the CLSA platform data access can be refused in cases for example where an application is too early to ask the question that it's proposing to ask for example we only have baseline data available no longitudinal question can be answered at this stage when further data points for follow-up one follow-up to data become available longitudinal questions may be asked for example sometimes a very specific population or segment of the population is proposed to be studied and perhaps the statistical review determines that the sample size for that particular segment of the population is not large enough to allow a valid response to the proposed question in that case also for example the the access to the data could be refused so those are some situations but each each application is considered based on its own own merits and so as I said if you if you we try to work with researchers even before the application as much as possible to enable data access so please if you have any questions before you submit your application don't hesitate to email us on the access email and again these these slides as well as the recording will be available on the CLSA website soon and feel free to distribute and share those. Another question how many applications are there annually application deadlines are there annually and what are they if maybe that's for you again there are three application deadlines annually so the last application deadline for 2017 is October 16th and the 2018 application deadlines are already posted on our website they are January 29th June 11th and September 24th. Okay so I'm going to thank everybody for joining us today and if you have any further questions please send them to our access at clsaelcd.ca website and we'll be happy to respond. Thank you everybody for joining today's webinar.