 Now, for today's webinar, again, the title emerging leaders, how trainees are using the CLSA platform for research on health and aging. I'd like to introduce our panelists, Dr. Matilda Saliba, Vrati Mehra, Mehra, it's said that wrong, I'm sorry, and Doha Fareed. So, Dr. Saliba is the CLSA data access officer. She coordinates the feasibility review of data and sample access applications with the CLSA, the release of data sets of approved users, communication of data release updates and responses to access queries from approved users and potential data access applicants. She also ensures providing Canadian and international research community with up to date information on the availability, use and access of CLSA data. She has over 15 years of experience in coordinating health research projects prior to joining the CLSA. And she's been here for 5 months now. She worked as the national access coordinator for the Canadian partnership for tomorrow's project and data harmonization manager with Maelstrom research group at the research institute at McGill University Health Center. Dr. Saliba holds a PhD in epidemiology from London South Bank University in the UK and a master of science and population health from the American University of Beirut in Lebanon. Next, we have Vrati Mehra is currently, she's currently an MD candidate at University of Toronto. She recently completed her master's in epidemiology at York under the supervision of Dr. Hala Tamim. Vrati has won many awards for her research, including the CIHR Canada Graduate Scholarship, Ontario Graduate Scholarship and the LaMarsh Graduate Research Award. And finally, we have Doa Fareed, who is a clinical dietitian and PhD candidate in the Department of Family Medicine and primary healthcare research at McGill. She earned her undergraduate degree in dietetics and human nutrition at McGill and her master's in nutritional epidemiology at Boston University. Her research interests lies in minority health, nutrition predictors of health inequities, obesity and diabetes. Doa has received several awards for her research in inequities of health, such as the Patients Choice Award and Greta Chambers Award. She enjoys exploring different cultures, sports and learning languages during lockdown. So I'll be curious to know how many languages you've actually learned, Doa. So those are our panelists today. I think we've got a great selection and I'm very impressed with the international stature of all of them. So on that note, I will pass it over to Matilda. Yeah, thank you, Jennifer. And thanks to Vati and Doa for presenting at this webinar. So this is a quick overview about what trainees should know before they prepare the CLSA data access application. So, yeah, I will provide a general overview of approved CLSA applications. So here you can see the total number of applications per year where the blue parts can represent the trainees applications. So since 2014, we have more than 300 approved applications where if you notice there's more than one third of those applications are trainees applications. So CLSA is the multidisciplinary data has provided the opportunity to many students and postdocs to use this data to their thesis as well as for the research project as postdoc fellows. So you can check the CLSA website to know more about those approved projects. So as a trainee, what do you need to know? First, you can request the fee waiver if you're eligible. So CLSA provides data at no cost if you're enrolled at a recognized institution in Canada, or if you're a Canadian trainee based at an institution outside Canada but funded to a Canadian source. Bear in mind that the data you request should only be used for your thesis research as part of your master's or PhD program or for your postdoc research project. There is a limit of one waiver per postdoc. So second, it's very important and I stress on this point that you know how to assign the research team roles in your application. So the primary applicant should be the trainees supervisors and not the students or the postdoc. Although this is explicitly explained on Magnolia, so we still get time in Magnolia is by the way our online data access application system. So we still receive applications with students and postdoc as signed as a primary applicant. Although we do have an application in part one section specifically for trainees that all the information should be identified here as well as if you need to request a fee waiver. You need to check the box there. So once we receive like a misassigned research team roles, we have to in this case ask again the supervisor to correct the information review the application and submit again. So this could delay the process too. So you need to know that the supervisor on behalf of the trainee must request a user account on Magnolia. And they need to be responsible for the content of the application as well as submit the application. They also need to follow up on all correspondence with CLSA. Third, you need to be mindful of the application process timeframe. So the application process usually entails several steps. So once you submit, there is the application goes into administrative and feasibility review. So this step usually includes like ensuring that the application is complete as well as the data is available after the application proceeds to the data and access sample committee. Those are independent members that review the application, the scientific background, rational objectives as well as methods. And they provide their recommendations to the CLSA scientific management team. The final decision is granted by the CLSA scientific management team and the applicant will be notified about either it's approved or it requires revisions or it's not approved. So for those that are approved, the next step would be the access agreement phase. So here is where the, I mean, where the access agreements are signed with your institutions and when you need to deal with your own ethics board to get the ethics approval. So we have absolutely no control over the steps and the time might vary from one institution to another. So once the agreement is signed and we receive the ethics approval that then we can prepare and release the data and usually the step takes around one week. So as a student, I'm who wants to use this data for the masters, their masters thesis or PhD or postdoc. It's really important to think about the amount of time it takes. So you should plan on receiving the data about like six months after the submission deadline. Definitely you need to know when are the submission deadlines. So for 2021 we do have two submission deadlines, one for April 14 and another for September 8. And usually you will be notified about the decision like after three months, if it's approved, not approved or requires revisions. Tip number five, you have to be certain of the CLSA variables you would need for your research. So it's important when you start thinking of using CLSA data to explore first the CLSA website, specifically for information under the researchers and data access tab. So you will find there the protocols, which will give you an idea about the study design and the rationale. You'll also find the questionnaires, information on physical assessment there will be there as well as there's data support documents like they describe in details different areas like cognitive data, environment data variables as well as genetic data, etc. So to know what data are currently available, I highly recommend that you consult the CLSA data availability table, which is under the data access section on the CLSA website. Keep in mind that we only accept applications for data that are available at the time of the submission. So along with that, you can also use the data preview portal that we have on our website. So here you can get some like a very high level metadata as well as variable specific information. So this tool is very helpful. I find for if you want to look at a research question, for example, using CLSA data, and you need to make sure you have the numbers available to use so then you can use this tool. So, and there's more, I mean, information on the website that explains in details how to navigate through this data preview portal. Another tab here, we do recommend that you obtain ethics approval the earliest possible. Although it's not required at the time of submission ethical applications can take quite some time for certain institutions. So this could delay the process as we do not we do not release at all data until we receive proof of ethics. And finally, so before you submit ensure your application is complete and includes all necessary information. So please follow the instructions on Magnolia as well as describe well your project by providing the level of details you would normally provide in a grant application. Make sure I mean that you'd select a variable modules in the data checklist that you would need for your research within the corresponding wave. So currently we do have now baseline follow up one. I do emphasize that the primary applicant, which is the student supervisor reviews attentively the application before submitting. We do receive some trainees applications that are incomplete or include inadequate information where they're not sometimes not approved or sent back for revisions and this really could delay the process. So supervisors should use the CSA data access application process as a valuable training tool to guide trainees in preparing the application. And as I said, inadequate information can result in processing delays or refusal of an application. So to know more I mean about our data access process so you can go check the website under the data access section. There's a lot of information there. And then you also I do recommend that you check the part on the FAQ section where there are a lot of questions are answered here too. And definitely I mean, if you have additional questions, you can always email us at access at CLSA dash ELCV dot CA. Thank you. Thank you so much Matilda. So I think we're going to reserve questions to the very end. So we'll put your slide back later. Who I'm not sure actually if it's brought to you or do that's coming up. Next. That's me, Jennifer. Sorry, I was just hoping one of you would just just jump in. Okay, so you are, you are up next. I think you jump slides. Okay. Yeah. Okay. Everybody got a glimpse of my slides. So thank you all for the sales, sales see and sales a and the team and your team for inviting me to speak today. My name is the offer read and I'm a clinical dietician and PhD candidate at McGill University and the department of family medicine and primary healthcare research. And I'm co-supervised by Dr. Elham Rahme and Dr. Cabareg Descupta. And today I'm going to present my analysis of undiagnosed depression persistence, persistent depressive symptoms and seeking mental health care and immigrants and non immigrants using the CLSA data. So I have no conflict of interest this close right now. So before I start, I'm going to share with you a personal story. 15 years ago, I immigrated to Canada to study at McGill. This is beautiful McGill under the snow. I got married and got my first child. And as all of you know that in Canada, when you deliver your baby, your first baby, they send you a public health nurse at home to check on you and teach you how to become a mother, let's say. The public health nurse saw me emotional and kind of sad and asked me whether everything was okay. And then I started to list all the things that were going wrong and so on. And to my surprise, she was able to kind of screen me on the spot on having early signs of postpartum depression. In that instance, this nurse saved my life by reassuring me and lifting me up. I realized how screening for depression was so important at that time and devoted my PhD in evaluating depression and seeking help. So here's a question for you guys to vote on your screens. Please vote whether you have on the right on the right side. Please vote whether you have experienced previously symptoms of mental illness or depression. Regardless of COVID-19, let's say. So that's question number one. So, as you will know, depression is a leading cause of disability globally. You know, indeed, we all know depression is serious 6.7 million people in Canada have experienced mental health problem or illness. It seems though that depression often goes undiagnosed and untreated. And this is what studies show. So what happens if depression is left undiagnosed when it can affect it can affect basically your overall quality of life. Your productivity, you know, here we see absenteeism, how much it's affected as well during work, physical illness you get, you know, we get physically ill. It also increases self perceived functional disability. You get to feel paralyzed and it prevents you from seeking help. And sometimes even suicide or suicide attempts. So here's another question for all of you two questions on this. So the next two questions you probably voted already. For those who had symptoms of depression previously, did you seek help or not at that time? The poll is on the right. And you can go ahead and answer question three as well. And why not? Is it because of time? Is it because of stigma? No social support around you or discrimination. You weren't attached to a doctor. You couldn't find a doctor or other reasons. So, so what about immigrants in Canada? What happens to the health of immigrants after arrival? When they arrive, they are relatively healthier than the general population where they have better self reported health, lower use of health services. And this is what they used to call healthy immigrant effect and still call the basic called healthy immigrant effect. However, this healthy immigrant effect declines with years lived in Canada and living more than five years. They are twice as prone to report one of the seven most common chronic analysis. And we see it because of several reasons like unemployment, lack of knowledge, lack of access of services and so on. And because of physical health deteriorates, but what about mental health? A lot of research is missing in this area. So we're looking into that. How about seeking help for immigrants? Well, 20% of immigrants report having barriers in accessing health care services and 12% lower all cause unmet needs than non immigrants. So here's the questions that we're covering in this week in this study, which was published recently, not recently a year ago. I wanted to see among older immigrants and non immigrants who participated in the CLC in the first baseline comprehensive cohort. What is the prevalence of undiagnosed depression and what are the risk factors are our length of residence or age at arrival imported at all. What is the prevalence of persistence and depressive symptoms at the 18 month. And what is the likelihood of seeing a mental health care professional for these symptoms. So I'm going to discuss a bit of the methods as you all know, we use CLC and CLSA and the core selection use the baseline comprehensive cohort, around 30,000 people. And basically we exclude those with any mood disorders in the last year, current and T the present use or and missing information on the outcomes. These are exclusion criteria and at the end we had around 23,000 people. Our primary outcome that we looked at is the current screening of undiagnosed depression and we use CSD 10, which is the center for epidemiological studies short depression scale. And basically it was it's a widely evaluated tool, specifically for older adults. And we can see here the sensitivity and predictive value. This is how the CSD looks like. They ask you a few questions and get to so the first question like I was bothered by things that usually don't bother me. I think everybody's like that during COVID now. I had trouble keeping my mind on what I was doing. You know, I felt depressed and so on. So this was our first outcome. Our second outcome secondary outcome was at 18 months where we looked at a second scale called Kessler psychological distress scale short for K10. Basically measures not specific psychological distress and predict diagnosis for mental illness. This is how the K10 looks like. We use the cutoff of 19 where it was found to balance sensitivity and specificity as well and was used in other studies. So our third under the secondary outcome we looked at a secondary question in the K10 where they asked here in the last before the last question. They asked whether they've seen a doctor for these symptoms of symptoms of, you know, feeling lonely feeling and so on, whether they sought help or not. We also looked at we adjusted for population characteristics and healthy if you're using the Anderson model for utilization for healthcare utilization. So we looked at several characteristics here that we adjusted for. In terms of analysis, we did descriptive statistics with means of standard deviation. Multiple logistic regression models were used to examine the situation between immigrant and mental health. With our primary outcome, which is undiagnosed depression with the CSD CSD and the secondary outcome persistent depressive symptom, which will look at model two and seeing a mental health care professional for these symptoms, which is model three. So here's a glimpse of the results, weighted crude results for our primary outcome where that around 10.9% were undiagnosed, the undiagnosed depressed, had undiagnosed depression at baseline 19.1% had immigrated to Canada. And the majority lived in Canada over 20 years ago. So they're actually used to Canada and they've been here, they've been in Canada for a long time. Our secondary outcome 32% had depressive symptoms at 18 months of whom 15.5% only 15.5% had seen a mental health care professional in the previous month, which is a very small number. Here's some more crude results where we actually looked at immigrants versus non-immigrants were more likely to be older, former or non-smoker, married, you know, more educated, unemployed, male to have low income of less than $20,000 and live in urban setting. Immigrants are less likely to have vows disorders, have cancer, overweight, be overweight or obese. So here's our first question in our first model. What is the likelihood of having undiagnosed depression in immigrants and non-immigrants? We found an interaction between immigration status and sex where we found that among men, immigration status was not associated with depression at all. However, among women, immigrants were 50% more likely to have depression. Women were consistently more likely to be depressed than men. And age at arrival or length of residence as a risk factor, we did find that immigrants who arrived at age 40 and above were twice as likely as non-immigrants to have undiagnosed depression. So if they immigrated at a later stage, it's harder for them to adapt. Immigrants who resided in Canada for less than 20 years or above 40 years were more likely than non-immigrants to have undiagnosed depression. In terms of the likelihood of having persistent depressive symptoms after 18 months, we found no difference between immigrants and non-ingrants regardless of undiagnosed depression at baseline. So, and among those without undiagnosed depression, females were at increased risk of having depressive symptoms versus males. But among those with undiagnosed depression at baseline, the risk of depressive symptoms and persistent depressive symptoms was not different between females and males. In terms of the likelihood of seeing a mental health care professional, which is very important to seek help, there was no difference between immigrants and non-immigrants. And females were actually more likely to see mental health care practitioners. And those who had persistence in depressive symptoms, so they had undiagnosed depression at baseline and then we saw them with the K-10 having depressive symptoms at 18 months were three times more likely compared to those with undiagnosed depression at baseline to see a mental health care professional. So here's some take-home messages for you. Screening particularly benefits immigrants who arrived at 40 years of age and older and for everybody. And more specifically, those of female sex. Follow-up screening should query persistence of depressive symptoms and encourage seeking mental health care regardless of immigration status. Here's the results are published in the Epidemiology and Psychiatry Sciences. And we were happy two weeks ago, we were awarded the Rockshaw Award for Best Article of the Year by the Réseau québécois sur le suicide des troubles de l'humeur et les troubles associés. So I switched to French. So I will actually present the results of the poll right now if surely can help us. So yes, 34% of our participants had symptoms of mental illness or depression. And then for those who had symptoms of mental depression, did they seek help? 15% said yes and 15% said no if I'm reading the poll right. And then the last question is that mostly I guess time, finding time to seeking help. So thank you so much everybody for answering the poll questions. I would like to thank my supervisors, Dr. Elham Rahme and Dr. Cabare Descoutta and my thesis committee and the Department of Medicine and Primary Health Care Research. The award I received from the Fond de Recherche Santé Québec and Dialogue Miguel and the Institute for Health and Social Policy for their support as well. If you have any further questions, please do contact me through this email. Thank you. Thank you so much and congratulations on your work both clinically as well as the research work that you've done. It's very exciting. I'm going to think it's a great example of CLSA trainees. So now we'll have another great example of CLSA trainees using data and I'll turn it over to Brati. Thank you, Jennifer. Oops, I'm just trying to navigate to my slides. Okay, perfect. So thank you CLSA for inviting me for this talk. It's an honor. My name is Brati and we used CLSA data for our study to look at the association between diabetes type, age of onset and age of natural menopause and this was a retrospective cohort study. So just to get us started and on the same sort of page, I wanted to go over the three different types of diabetes. So type 1 diabetes is a chronic condition in which your body is no longer able to produce insulin. It's an autoimmune condition type 2 diabetes is when the body becomes unresponsive to the insulin. And so the organs, the primary organs that are responsible for up taking glucose are no longer able to do so. This has both genetic and environmental risk factors. Justational diabetes on the other hand is when a female who was non diabetic develops diabetes during her pregnancy. So some stats just get us started in 2017, more than 476 million people lived with diabetes across the globe in Canada in the same year 2.3 million people reported being diagnosed with diabetes. And although the risk factors among males and females are similar, there are some differences. And so among females, it's actually found that upon diagnosis of diabetes, they have a lower socio economic status, lower education status and higher BMI. And then in terms of the clinical impact of diabetes, it's actually been seen that women have a seven fold greater risk of developing cardiovascular diseases after their diagnosis of diabetes. Compared to just a three fold greater risk in men. And this also translates to greater cardiovascular mortality among females as compared to their male counterparts. So that's what I just reviewed. So menopause. Oh, sorry. Actually, let's go back. So why look at diabetes in women. So with increased prevalence across all age groups, more women are expected to spend a greater portion of their reproductive years living with diabetes. Which then makes it important for us to understand the impact of diabetes on women's long term reproductive health. And one such indicator is actually menopause. So menopause is the age at which a woman experiences age at natural menopause is the age at which a woman experiences 12 consecutive months of amenorrhea. The average age at natural menopause can range anywhere between 46 to 52 years. And so why do we look at menopause? Well, it's been seen that early menopause can actually place women at a greater risk of negative health outcomes, including greater risk of fractures, greater risk of cardiovascular diseases, reduced lung function, post menopausal type 2 diabetes and a greater risk of all cause mortality. And so what we wanted to see was is diabetes a predictor of early menopause. Our rationale was twofold. The first was that the impact of pre menopausal diabetes on age at actual menopause actually currently remains debated in the literature. So while some studies show a reduction, a significant reduction in age at actual menopause among diabetics, some actually show that there's no association there. While others show that this may be a diagnosis based association. So those that are diagnosed with diabetes at a younger age may be more likely to have early menopause. Our second rationale was that there is currently incomplete evidence regarding regarding this association. Many studies have failed to adjust for important socio demographic, behavioral and clinical variables. And many others have been limited by very small sample sizes. And to the best of our knowledge, currently there's no study that looked at the association between gestational diabetes and age at natural menopause. So this leads me to our objective. So we wanted to look at the association between pre menopausal type 1 diabetes type 2 diabetes gestational diabetes and its association with age at natural menopause. Moving into methods. We used CLSA data. So CLSA is one of the largest studies on aging in the world. They have about 50,000 men and women at baseline, which were recruited between 2010 and 2015 aged anywhere between 45 to 85 years. The study has two main cohorts, the tracking cohort and the comprehensive cohort. So the tracking cohort is a telephone based survey wells and it has 20,000 individuals. The comprehensive cohort on the other hand, like its name suggests is more comprehensive. It has 30,000 individuals. And so for comprehensive survey, you have surveyed that is completed at home with a CLSA worker. And participants are recruited from around 11 data collection sites across seven provinces around Canada. And they have to be within 25 to 50 kilometer radius. They then have to go into one of these data collection sites and have their biospecimens collected and have an in depth physical exam. And so for our study, we use the comprehensive cohort. There are some exclusions that I wanted to note that CLSA made. This is very similar to other Canadian surveys. So individuals living on reserves or long term institutions were excluded, full time members of the Canadian Armed Forces, and those that did not speak one of the, either one of the official languages of Canada were excluded. So for our study, we're moving into my study now. So for our study, there are some specific exclusions as well. And so we started with about 15,320 females. We've then excluded women who had a hysterectomy because in people who have their uterus taken out, which is hysterectomy, their menopausal status is unclear. Similarly, for those who had breast ovarian or other female genital organ cancers, we also excluded them because often in their treatment it can mask the age at which they reach menopause because their treatments involve hormones. And then anyone who did not give us enough information about either our exposure variable or our outcome was excluded. This gave us a final sample of 11,436 females. So for our exposure assessment, this was pre-menopausal diabetes, which was assessed via self-report at baseline. We had four main categories that we divided our main exposure variable into type 1 diabetes, type 2 diabetes, gestational diabetes, and no diabetes, which was our reference category. Type 1 and type 2 diabetes were divided based on their age of diagnosis because we had that information. So just to make that a little bit more clear here, you can see that for my exposure variable, there are four main categories. So no diabetes, gestational diabetes, type 2 and type 1, but then because we had information on age of diagnosis for type 2 and type 1, we were able to divide it further to see if that had an effect. So type 2 diabetics, we had more of them and so we were able to stratify them a little bit more. So we had less than 30 at age of diagnosis, 30 to 39, 40 to 49, 50 or older. And then for type 1 diabetics, our sample was a little bit smaller, so we were only able to categorize them into each groups, less than 30 and 30 and older. For our outcome assessment, it was basically age of natural menopause, which was treated as a continuous variable. We attained participants menopausal status, sorry, not me. CLSA attained menopausal status first from participants and then their age of natural menopause, which was then used for our outcome. Covariates, we actually adjusted for a lot of covariates. I won't read them all, but there were lots of socio-demographic variables, lifestyle factors and pre-menopausal clinical factors as well that we adjusted for in our analysis. Moving into statistical analysis, we used survival analysis because this allowed us to include participants that had not yet reached menopause, so we were able to take their person years into consideration. So our primary outcome was age of natural menopause for post-menopausal women. And our secondary endpoints included age of interview for women who were not yet menopausal, and for women who had started hormone therapy, it was their age at initiation of hormone therapy because that can often give us inconclusive results on when they actually reach their menopause. So we had Kaplan-Meier curves, which were used to ascertain the median age of natural menopause for different types of diabetes, and Cox proportional hazard regression models where we had bivariate and multivariate exposure association between our exposure variable and our outcome. So moving into results, this is our first table, which is basically highlighting the descriptives. So we had, we were able to add weights, which allowed us to make our study representative to the seven provinces of Canada where the participants were recruited from. So 91% of our sample was non-diabetic. 6.7 had gestational diabetes. This is very similar to the national averages as well. And we had 0.3% that were type 1 diabetics and around 2% at type 2 diabetes. So this is a Kaplan-Meier curve, and as you can see over here, the two curves that you see are non-diabetics and the black and the dashed is people having any type of diabetes. And over here, if you notice, this is the probability that a person will get their menopause, and this is the age. As you can see, the curves look very similar. And so if you were just to see this, you would say there isn't really a big difference there. Rather, if you were to notice the numbers over here, non-diabetics reached menopause at the age of 52, median age of 52, whereas all diabetics had a median age of 53. And so you'd be like, oh, maybe rather all diabetics maybe reached menopause a little bit later. But in our Cox proportional, in our Cox analysis, Cox proportional hazards analysis, we actually saw that those who were diagnosed with type 1 diabetes at an earlier age, so less than 30 years, they reached menopause earlier as compared to their non-diabetics, non-diabetic counterparts. Similarly with those who had type 2 diabetes early on, so between the ages of 30 and 39, they also reached menopause early. And then those who had type 2 diabetes after the age of 50 or at or after the age of 50 were more likely to reach menopause at a later age as compared to non-diabetics. So moving into discussion, why do we see this pattern? And currently, there are very few clinical studies that actually look at this. So a lot of it is hypothesis based. It's actually been seen that in type 1 diabetics, they usually have an autoimmune disorder and people who have an autoimmune disorder, they also tend to have others. And so in type 1 diabetics, it has been seen that they have more ovarian antibodies, self reactive ovarian antibodies. And also in preclinical studies, it's been seen that lower levels of insulin or suboptimal insulin therapy is actually associated with a greater impairment of your egg ovulation and maturation and greater follicular apoptosis. And then type 2 diabetics, it's actually been seen that, you know, creator, you know, having suboptimal glycemic control where you're not taking care of your of your blood sugar can actually be associated with accelerated aging and cause and lead to reduce life expectancy. And so based on all of that, you know, we were thinking that somewhat like a conclusive, sorry, and like a combined effect of bad insulin control, you know, bad glycemic control may be causing this association. However, more studies are needed. Similarly for later diagnosis of type 2 diabetes and later age of natural menopause. We were, we were not sure why this was the case. And so definitely needs additional studies. Additionally, there was one study that was published in 2015 by brand and colleagues that actually showed that age of diagnosis of type 2 diabetes or age of diagnosis of any diabetes. So, lower age of diagnosis is associated with early menopause later diagnosis is associated with later menopause. However, they did not show the different types of diabetes that was in that was an addition that our study has made in the field. So, in terms of strengths and limitations, we do have a lot of strengths and we had a large sample size. We carefully adjusted for a lot of covariates. It is 1 of the 1st studies to look at gestational diabetes and age of natural menopause. We did not find an association there. But definitely 1 of the 1st studies, according to our, our search to look at this association. And then we adjusted for a lot of free menopausal health conditions, which again permitted for more clarity on a temporal sequence of events and their impact on age at natural menopause. Having said that, there are some limitations. We did not have information on age of diagnosis for gestational diabetes. So, it's possible that if you were to divide gestational diabetics on the basis of their age of diagnosis, you may see a similar effect. And both diabetes and age of natural menopause was based on self report. So, so it is susceptible to misclassification. And then finally, CLSA did not collect information on oral contraceptive use age of monarchy. So, 1st period, parody and breastfeeding. So, we were not able to include those variables, even though they have been shown to be important in previous studies. And so, the significance of our study is that we hope that we've made the 1st step towards understanding the association between diabetes and age at menopause. And we hope that, you know, this can help clinicians in Canada and around the world direct more early and focused care towards at-risk patients. I would like to thank my supervisor, Dr. Halitani, my lab members, and also Q, who was my statistician and he supported me a lot during my thesis who was in the audience right now. Thank you. And that would be the end. I can take some questions. Great. Thank you so much, Rati. And we've lost Doa's video. Perhaps she has a little one at home who was pulling on her leg. No, okay. That seems to always happen during these webinars these days. So, so I welcome everyone to put questions into the chat box. If you have any, either about the content of presentations, the research or about the process for applying for data, which Matilda can speak to. So, there is a question from Chris Wolfson. My question to both trainee presenters is, was there information that you would have liked to have that was not included in the CLSA? I can start, Rati. Sure. Thank you, Chris, for the question. It's a very important question. When I first submitted my proposal, I thought there would be more of a bigger percentage of non-whites in the CLSA. I think it's 2% non-whites, racial minorities and so on, and 98% whites. So even my, my immigrants are, they report that they're white and maybe we have like, I don't know, 300 people that like look different. I'm just saying that I would have loved more diversity in the CLSA. I don't know if they can change that, but I don't think so. And the other thing is, I was, I was planning to look at IBD, I think, in my first analysis, irritable bowel syndrome, and that they haven't, you know, difference related between Crohn's disease and so on. And I think they changed the questionnaire when we commented on that for the next few years, I think. Thank you. Yeah, thank you for that question, Chris. Sorry, Jennifer. I believe I did mention this at the end of my presentation and to Doa's point, I think that's a very good point. It would be nice to have a more diverse population for sure. And for my particular study, we did not have information on menarche, parity, breastfeeding. Some of these variables have been shown to be quite important when it comes to age and natural menopause. And so it would have been, it would have been nice to have that information for sure. Great. Yes, there's always more information that people are requesting of the CLSA, but I, we have the sample and the diversity is something that we have heard before. As well. So, but that's, that's great feedback just before people start to, we're not done yet. So don't worry about that. But the poll, the evaluation poll was put up. So if you have before you leave, if you have to leave before one o'clock, if you can please take a few minutes to complete that feedback poll. So, there is a another question from Teresa Pauley. Some other national panel data such such as HRS allow for researchers to submit ideas for experimental modules or the addition of questionnaires. Is that possible at the CLSA as well? Matilda, do you want to take that or do you want me to take that? Yeah, go ahead, Jennifer to be better. She's answered this. Yeah, I mean, I think really from, from my perspective, the answer is, you know, we, we have a process where we have working groups come together at during each of our waves to identify. Areas and our questionnaires and our data collection procedures that are either not being used or have become less important or there could also be areas that could become important as well. So, I think if you have any, I think in terms of experimental modules, I think that idea hasn't, I can't speak to it specifically, but that hasn't been. Used, but the idea of adding different modules and questionnaires definitely has been and this the CLSA questionnaires have changed from wave to wave. For example, adding elder abuse module, which was early on in baseline was removed and is now being put back in. And so I think anything's possible. And I think if you have those sorts of questions, you can address them either, if you know, one of the PIs, you could address it that way. Or of course, through our data access officer who would get that filtered to the right place. So it all starts with a question, right? So hopefully that answers that question. One question that I think I'll just pose since we were, you know, we wanted to highlight. Some of the trainee projects that are completed successfully, but also the four trainees, what, what it looks like to actually apply for and use CLSA data. So I'm wondering if you can, and then I have a follow up question for you Matilda. So you're not going to get off scot-free. You know, just like how, what was your experience like in terms of applying for the data? You know, was it, you know, just what was your general experience? What would you say to other trainees? And then of course, if you have any advice, feel free to provide that as well. Yeah, I think I want to go first. I can go first. That's okay. My experience was actually great. I knew from the beginning that I wanted to get data from CLSA. It's so nice to have a Canadian study that that is looking at, you know, aging. So it was great. And I thought the instructions are very clear. I think what Matilda said in the beginning of the presentation, which was, you know, take six months before like, say, tell yourself that you're going to have six months till the time you're going to get your data fully in your hand. And then take that into consideration when you're writing your proposal and you're thinking about your study and you're coming up with your objective and your stats. It's very good to know that, you know, that time it took me less than that, but it's good to give yourself that much time. And then the data is very well displayed and very easy to work with. So, yeah. Yeah, that's, that's all I would say. I can say the same thing as well. I would like to thank all the support from the CLSA team. They answered the emails quite fast. And I think I think most of my PhD on CLSA data, even though I did work on NHANES data before NHANES was much more complicated different types of, you know, have to download several ones and so on. So, yeah, I'm proud. I'm proud that it's like that. And I hope the future we get a more diverse. Okay. Great. Thanks for that feedback. And Matilda, one question that I had had for you, I'm totally putting it on the spot for this one, but I know we've talked about the data access a lot and how trainees can and others of course can apply for data. I'm wondering if you can just speak very briefly to what it means when so people get their data, researchers get their data, you use it, you publish, but what does the, the tail end of the process look like in terms of requirements for data use? For example, final report. Yeah, I can go to this. Or did I, did I, did I miss something? No, actually. Yeah, actually. Yeah. So the data, I mean, once we release the data, so it depends on the timeframe that was agreed in the access agreement. So. By the end of the access agreement, definitely they should all researchers, including trainees, they need to submit a final report. I think we may have lost Matilda. Unless it's me, that's a glitching at this point. Yeah, I think it's probably Matilda. So yeah, I'll just jump in here. I don't know now the slides are all moving around. But yeah, so I, I probably shouldn't try to finish because I'm. No, very little about Matilda's role, but there is depends on timelines and there are requirements as part of the data access agreements that we hope that all researchers, whether trainee or. You know, non-trainee can abide by in that we do ask for some sort of a very brief final report and that that also helps us to understand what research outputs are being created from the data that is being made available for the CLSA. So it's very useful to sort of, so we sort of try to follow projects all through that process. So yeah. I don't see any final questions, but if you do have any final questions, you can reach out to either of the either of the 3 presenters today. So I'd like to, including thank every, thank our presenters again. We appreciate your participation in the CLSA using the CLSA data as well as participating in this webinar series. I'd like to remind everyone that CLSA data access request applications are ongoing. And as Matilda noted, the next deadline is April 14 of this year. And you can visit the CLSA website under data access to review the available data. And further information on the data access process. I'd also like to remind everyone to complete their survey if possible under the polling option. If you don't see it under the chat button, you can, you can click the drop down arrow. That's in the same place. Today is the last day to apply for the summer program in aging, which is spa 2021 for short grad students and postdocs interested in longitudinal studies on aging are encouraged to apply for this. You can get more information by visiting the research net website. And for upcoming CLSA web webinar, which will be in March, the following up on Joe's presentation. It's mental health outcomes among men and without a history of prostate cancer diagnosis in Canada. A silent epidemic and cancer survivorship. And this will be presented by Louise Moody and Dr. Gabriela, Leah of Dalhousie University. And you can visit our CLSA website under webinars to find out more about that. And finally, the CLSA promotes the webinar series using the hashtag CLSA webinar. And we invite you to follow us on Twitter and also tweet these sorts of things out. So thank you again for attending today's presentation and webinar. And we look forward to seeing you in March. And Matilda is back. So thank you, all of you. That's okay. I'm sorry that internet was off. I'm really sorry for this. It was bound to happen. Right. Okay. Thank you. Thank you everyone. Thank you everyone.