Welcome to this interdisciplinary course called the Science of Race. Students will walk away from this course being able to define and discuss concepts such as race, racism, group identity, racial passing, reparations for slavery, craniometry, biomedical ethics, segregation, population genetics, affirmative action, and more. In this class, students will read, discuss, debate, and evaluate texts and media focused on core concepts, including early non-western scientific traditions and race as a scientific and social construct. Students can also expect practical exercises or projects related to social justice and change, anthropological concepts of otherness, IQ, health and disease of people of color, and other relevant challenges that we face as a society today. Students who are curious, concerned, interested, or excited about race and race relations in the United States and beyond will be met with opportunities to explore and discuss important issues that we face every day as citizens in the world. If you are a student hoping to have an informed conversation with friends and parents about these issues, then this course is for you. Students from all backgrounds can succeed in this course, though strong active listening and critical thinking skills are especially beneficial for concepts and activities in the Science of Race.


Hello, my name's Mike Stier. I'm the acting research director of Sadi Aquatic Sciences, which is the research arm of Persa. Today I'm gonna be talking about the science behind the giant Australian cuttlefish. Now there's a place up in northern Spencer Gulf called Point Lowly around Waila that has an extensive rocky reef. This reef plays host to an amazing spectacle. Each winter, tens of thousands of giant Australian cuttlefish aggregate on this rocky reef to spawn. They are attracted to this reef because they lay their eggs or attach their eggs to the underside of that reef. This is an incredible natural phenomenon. It's the only place we know of in the world where you get huge numbers of cuttlefish aggregate on a particular site. And as such, it draws the attention of quite a number of visitors, tourists, documentary filmmakers, scientists, and it's along a stretch of coastline that also has a fair bit of coastal industrialization. Over the years, cuttlefish has been approaching iconic status in South Australia. As I said, it's the only place in the world where you get this massive aggregation. And it's starting to achieve an iconic status up there with South Australia's farmers' union ice coffee, frog cakes, and custard tarts. So a really important population. Now, if you look at this cuttlefish population through time and have a look at how it has developed, the first thing we need to consider is the commercial catches because initially this species was, and still is, permitted to be caught by commercial marine scallfish fishes. So you can see back in the early 1980s through to the 90s, there wasn't much of the statewide catch. This has catch landed in all of South Australia. See, it's around about five to 10 tons per year. But in the mid-90s, we saw this really big increase right up to about 250 tons in 1997. Now, the reason why it increased so quickly is because the fishes found the aggregation in a round point lowly and were able to catch quite a lot of cuttlefish in a relatively short time because these species had aggregated. They were using cuttlefish at that stage as bait for snapper. So commercial fishes would come in, catch a heap of cuttlefish and then use them for bait to then go on target snapper later on. Now, clearly this was indicated as a bit of a concern because of fishing on a spawning aggregation. And in the following year, an exclusion zone was put in in 1998, about halfway through the spawning aggregation, which occurs around May, June and July or in peaks in May, June and July. That exclusion zone eventually covered most of that False Bay area from the BHP Jetty all the way across Point Benyton Jetty to the Lighthouse. Around the same time, there was some work done by a PhD student here in South Australia that started to look at the cuttlefish abundance in that area. And she found that around, or in that year, approximately 100,000 cuttlefish were aggregating on that particular spawning area. Now, you can see once that closure was put in place, then the majority of the catch dropped out because most of this catch was coming from that False Bay area. And you can see that that population, well, that catch has rather dropped down to about 10, 15, 20 ton per year and has not really exceeded since then. Now, the corresponding surveys of the cuttlefish abundance were relatively stable in those subsequent years straight after the imposition of that closure. Around about 150 plus thousand animals. So it seemed like that closure was really good in arresting those commercial catches and maintaining that population through time. A couple of years went past and we were asked, well, Sadi was asked to do another survey in 2005 then the Department for Environment and Heritage because there was anecdotal information that that population had declined. We went out and did the survey and it had declined a little bit but it was still relatively high. And you can see in the corresponding time so that the statewide catch was relatively low as well. In 2008, nine and 10, there was some work done with BHP at the time using the same methodology that was described back in the early days here. So we know that all these data are comparable. And then we saw this precipitous decline down to very low levels, around about 13 and a half thousand animals in 2013 which raised quite a lot of concern because that's a pretty considerable decline. As a consequence of that, a broader temporary fishing closure was put in place for Northern Spencer Gulf because that was the only thing at the time that was considered to be able that the government could control. For us to at least have some time to work out what had caused that decline. And it was a fair amount of funding that was given to the state government and Sadi Aquatic Sciences to undertake some research to try and identify the cause of that decline. Since 2013, we've seen that the population has rebounded quite significantly, really identifying how quickly this fishery can respond. And in recent years, it's although fluctuated on an inter-annual basis, it's been relatively stable. Okay, so there was three hypotheses that we wanted to look at with regards to the decline from the peak of 1999 down to that real low level in 2013. Now, the biggest problem that we had is we had no information of the history of this population. So there's one of three things that could have occurred through time. The first one is, well, perhaps the population has maintained a relatively high level of abundance through time. And what we've seen since that peak in the late nineties of 2000s is a true decline of concern. The other alternative is that perhaps the population just bubbles along at a relatively low level. And then in the late nineties, we saw an ephemeral population explosion and it now subsiding back to those baseline levels. And the third hypothesis is, well, maybe we've got this variation through time with these peaks and troughs in high and low levels of abundance. And we're just conforming to that natural population cycling. So we set out to work to try and identify what was driving this decline. So looking at that first scenario, where we've got a, what we consider a real decline from a large population assessment historically, there's a whole suite of things that we looked at. We tried to pull as much information as we could that was available to us. Information around weather patterns, rain, wind events, coastal pollution, shipping traffic, shipping noise. And then a whole range of biotic effects as well, like the abundance of key predators like dolphins and seals, the impacts of trawling offshore, the catches of cuttlefish from the commercial and recreational fishery. The amount of dive is on site, undertaking tours and snorkeling investigations through that peak spawning area. The prey, cuttlefish tend to predominantly feed upon crustaceans. So we looked at pats and prawns and crabs, the impacts of snapper, which is a key predator for cuttlefish as well. Local aquaculture ventures, disease, changes in the environment, or other cephalopods in the area. So we did a whole suite of analyses and all these analyses are in a report that can be freely accessed by the public and is available on the personal website. And through all of those, there wasn't a real strong signal. We found a signal in rain, so we're at rain in one year. If you had heavy downpours in one year, the subsequent trajectory or the next year's cuttlefish population appeared to decline. So we had this inverse relationship with a lag of about a year. Not too sure whether that was through freshwater inflow, whether it was changes in salinity or whether it was changes in water temperature or turbidity. So there was a whole range of questions that this opened up to us as well. We also saw a positive relationship with prawn trawling activity and effort offshore. We measured the number of cuttlefish in the prawn trawling shots and we found that in periods of high abundance, then you'd get more cuttlefish in those prawn trawlers. So it meant that if they were there, they would catch them. If they weren't, they didn't. We also saw inverse relationships with crabs and calamari. Now, it may be the fact that once the cuttlefish population declines, then the crabs, which are a key diet, key prey item would increase as a function of being predators to control them. And similarly with calamari, if the cuttlefish weren't there, then perhaps that gave the opportunity for calamari to come in and use that area to lay their eggs. So in all, we did quite a lot of investigation and not a lot did stick out at that stage. We clearly saw that fishing didn't have a negative impact or any sort of detectable impact. Diving visitors to the site didn't. And like I said, all that information is in a report that you can freely access. Then we thought, okay, well, if there's a decline here, what is the evidence of that population enduring through history? We looked at some historical information. In 1982, there was a survey done and point lowly looking at, I don't take an environmental impact assessment in relation to the construction of the jetty. Now, this team were looking at indicator species that they could measure in the unlikely event of an oil spill. They went out in the areas that we'd expect to see a large amount of cuttlefish, where the jetty is now. And during winter, when we expect to see high densities of cuttlefish around that time. And the report did not identify large quantities of cuttlefish. I think from memory, only a handful were actually documented. In 1984, there was another survey done in the same area around the same time. And they actually took some video footage and were fortunate enough to get hold of that footage. And we did actually find that there were cuttlefish in those surveys. And we know them to be the right spots because of our understanding of that area, we've actually been able to identify some of the rocks in the footage to verify that they were in an area and time where we would expect large populations or large densities of cuttlefish. They were indeed there, but not in the densities that we would have observed back in the late 90s and early 2000s. And then in about 1986, there was another group that came over from Griffith. They did some work, I think in front of the Santos tanks area and they identified that they saw cuttlefish in those areas, but not at the large densities that were recorded in those late 90s, early 2000s. So it seems like there has been some activity and some cuttlefish in that area through time. However, we can't get a gauge on the relative densities. Although we've spoken to locals that have been there for many years that used to fish from the rocks and have told us that they did indeed catch large quantities of cuttlefish around that point lowly, Fitzgerald Bay, Backey Point area. Okay, so the second hypothesis is, well, was that peak in the late 90s, early 2000s, a population explosion? So did we have low levels of cuttlefish through time and then we saw an event and it's now subsiding back to its natural levels? So concentrating more on the increase rather, the decrease. Now the interesting thing about cuttlefish and other cephalopods including calamari and octopus is they live fast and die young. They typically have what's called a sub annual lifespan and for giant Australian cuttlefish, their maximum age is around about 12, 18 months. So they grow from an embryo in an egg. That egg undertakes embryonic development for a number of months. The animal hatches out as a miniature version of an adult. So there's no vulnerable planktonic phase. It grows relatively quickly, feeds copious amounts of crustaceans, gets to a size of reproductive age and then comes back to mate and spawn and the whole cycle continues. So the interesting thing here is that the population that we see in one year, the spawning population in one year does not endure for two spawning years. So once they've spawned, then they may spawn multiple times over a short spawning season, they tend to die. And in a couple of months after the peak spawning, that's when you start to see large amounts of dead cuttlefish wash up on the shore, particularly in northern Spencer Gulf. There's large washups of dead cuttlefish as they've just expired from spawning. They've then successfully laid all those eggs and those eggs then hatch and then contribute to the next population. And we've seen booms and busts of cephalopods around the world. And there's a good example off the coast of California where the jumbo Humboldt squid, they tend to boom and bust on the result of good environmental or favorable environmental conditions. And from this article it says what's behind the territorial expansion has yet to be determined, but through some observation, they believe a gradual warming of the ocean pollution and overfishing of large predators could be contributing factors. So the key things I want to pull out there is the gradual warming of water and the overfishing of large predators. Because these guys live so fast, their growth trajectory is highly, highly governed by environmental temperature. The warmer the temperature, the faster they grow. And of course, if there's no large predators through removal of fishing, for example, in the case of the Humboldt squid, it creates a situation for that species to proliferate. So what came out of that too was that perhaps cephalopods in general could be the key beneficiaries of global warming. And we've seen that in multiple species around the world. But another interesting thing that was mentioned here was that the Californian Humboldt squid appeared to expand its territory or shift its territory. We thought maybe the same thing was happening with giant Australian cuttlefish. Now we know in Northern Spencer Gulf the giant Australian cuttlefish is pretty much a separate species or separate subspecies or subpopulation to the rest of the state. There's very little mixing of the Southern Spencer Gulf cuttlefish and the Northern Spencer Gulf cuttlefish, even though giant Australian cuttlefish do occur throughout the entire Southern Australian range. But anyway, we know that the population that we are interested in is confined to that Northern Spencer Gulf. We also know that the region up around Waila is where we see large densities of cuttlefish, okay? So what we thought we'd do is look at other areas in and around Spencer Gulf that had similar habitat, similar rocks, similar substrate to allow the female cuttlefish to lay their eggs. And we undertook an extensive survey in these four zones and we found nothing actually. Now granted, we were looking at a time around 2013 when the population was really low. But we didn't see a shift in that population. And what that did tell us, however, is that population up in Northern Spencer Gulf, around the Point Lola, that Point Lola spawning aggregation is incredibly important to the overall population of the Northern Spencer Gulf cuttlefish. Then if you look at the third scenario where we have this fluctuation where you go in peaks and troughs and booms and busts and population abundance through time. And that's something that's consistently seen in the cephalopod literature. You see these big peaks and troughs in a range of cuttlefish, squid and octopus species. Now, like I said before, it's really driven by a number of environmental processes. One could be related to the amount of prey or predators that are available or in the area at that time. If there's not very many predators, then cuttlefish, for example, would increase. And then vice versa, if the predators, the levels of predation increases, then it tends to cap the abundance of prey. And the other thing we've seen with cephalopods in general is that temperature is a real key driver in the rate of how these species grow and proliferate. Now, the trophic web of cuttlefish or where it fits in is quite complex. We understand that seals and dolphins and snapper and other large fish, salmon, kingfish, et cetera, natural predators of cuttlefish.  So we can see very complex relationships there. So we may be seeing some changes in that population on the basis of shifts in predator and prey availability. So when we weighed up all that information, we seemed to take a weight of evidence approach that indicated that this third scenario, third hypothesis was the most likely scenario where we're seeing these peaks and troughs and population abundance through time. But at this stage, we still had very little information to support. But if we look what's happened in subsequent years, so we can see where we've had or no surveys back in the early, or the 80s and early 90s. We've seen our surveys in the late 90s. This one here was where we were impacted by fishing. These ones were after the immediate closure. We've seen that decline down to about 13 and a half thousand animals in 2013. And we've seen this rapid increase. And now a population that's pretty much returned back to historically healthy levels. Now, remember I said that the cuttlefish embryos take a long time to develop. And the reason why cuttlefish aggregate around that point lowly area is because of the rocks. They need to attach these eggs to those rocks. Now it can take a couple of months for these embryos to develop into hatchlings. And what they tend to do is hatch, maintain, live within the rocks until they get a certain age and size and they migrate or disperse out of the area into the Gulf. And once they achieve sexual maturity, they come back. But what we did is we've got some temperature loggers out there and we've just been looking at trends in temperature during that embryonic developmental phase. So we're looking over an 18-week period here. And we can see that during that time, you can get periods of increasing temperature towards the end of their development and periods of decreasing temperature. Now, if you look at both of those, you can see that in the warm years, we've got 2013, 2014, 2015 and 2017. And in the cool years, 2009, 2010, 2011 and 2016. Now if you overlay those temperature years, all those cool years with the population, you can clearly see that while we've seen a decline in that cuttlefish abundance and currently it appears that the temperature or the incubation temperature for these embryos is the best indication that we've got so far for that declining population. And if we look at the warming years, we can see while we're starting to see a population increase. Now, it sort of makes sense because if the animals are accelerating through that embryonic phase, they will grow faster and accelerate through that period of being vulnerable to production. So it suggests that they've got an increase or the hypothesis is they've got an increased probability of survival. And if they survive that earlier phase, then there's a greater chance that they'll contribute to that subsequent spawning population.  Now, if you look at 2016, that was a cool year and you can see that the subsequent population had declined. 2017 was relatively warm and well, the population had increased. So there is some signal there worth exploring in more detail in future research. Now, the issue with trying to get a handle on population dynamics on cephalopods and undertaking the appropriate management for them has been very difficult. And there's numerous texts on cephalopod fisheries biology that says that the significance of the effect of stochastic variables on annual species is really extreme. So this means that the populations can bounce around quite largely on an annual basis. And it's the main reason why it has proven difficult to establish a reliable assessment and management procedures for cephalopods. Now, this is a continual challenge for cephalopod fisheries biologists and fishery scientists throughout the world. So in summary of this presentation, point lowly is clearly a very important spawning ground as an essential component of that population. And particularly that area that is permanently closed. In the analysis that we've done to date through looking at all lines of evidence both in the marine scale fish fishery, the prawn fishery, et cetera, we found no clear impact of commercial fishing on the protected spawning population. And of course, we've got a lack of historical information, although there's some information to suggest that the population has been there in various levels of abundance through time. Clearly, as we've seen with the rapid rebound in that population since its low in 2013 that the population is highly responsive and variable. And so far, incubation temperature with the embryo the embryos appears to have the strongest influence. So knowing this information, it's really important that we continue to maintain those annual population surveys so we can track that population through time. And it's equally important that we monitor commercial and recreational catches both within the area and throughout the state to make sure that they're operating in parallel and not having or not providing any sustainability risks to what we consider an iconic population in South Australia. And clearly protecting those known spawning grounds along that Point Lely Stretch, False Bay Area is the most appropriate approach to maximizing the supply of eggs to buffer against that unpredictability of the environment. So hopefully the information I've pulled together today has provided you with a bit more knowledge about the species. And like I said before, there's a whole suite of reports science and literature that is publicly available on the PERSA website. Thanks very much for enduring the time and listening to me for about half an hour. Thank you.


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.  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.  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 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?  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.


NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Bruce Gachuk The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep, an aged crone sat on the beach and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore! And a poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Bill Turnes The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep, an aged crone sat on the beach and pointed to the ship. She'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Caitlin Buckley The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep, an aged crone sat on the beach and pointing to the ship. She'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Chad Horner The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep, an aged crone sat on the beach. And pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by David Lawrence The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Newgate Novelist The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Julian Pratley The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Kevin S. The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Leanne Howlett The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Larry Wilson The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Neema The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Paul Fleishman The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Phil Shampf The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by Tavaresh The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain. NIGHT AND MORNING by Charles Sangster Red for LibriVox.org by V. M. Nielsen The winds are piping loud to night, and the waves roll strong and high. God pity the watchful Mariner, who toils neath yonder sky! I saw the vessel speed away with a free majestic sweep. That evening, as the sun went down to his palace in the deep. An aged crone sat on the beach, and pointing to the ship, she'll never return again, she said, with a scorn upon her lip. The morning rose tempestuous, the winds blew to the shore. There were corpses on the sands that mourn, but the ship came, nevermore. End of poem. This recording is in the public domain.