My name's Jennifer Boyko. For those of you who haven't attended a webinar before, I'm the manager of scientific operations with the Canadian Longitudinal Study on Aging or CLSA for short. Thanks for joining us today for the webinar that's entitled The Impact of Urban Greenness on Aging Physical and Mental Health Among CLSA Participants. Before we begin, I would like to acknowledge that the CLSA National Coordinating Centre and McMaster University are located on the traditional territories of the Mississauga and Haudenosaunee Nations and within the land protected by the Dish with One Spoon Wampum Agreement. Queen's University is situated on traditional Anishinaabe and Haudenosaunee Territory. The Ontario Tech University acknowledges the lands and people of the Mississaugas and Spudown Island First Nation, a branch of the greater Anishinaabe Nation. To acknowledge this traditional territory is to recognize its longer history when predating the establishment of the earliest European colonies. It is also to acknowledge this territory significance for the indigenous peoples who lived and continue to live upon it. As attendees of this webinar today, I do encourage you to continue your learning following the webinar and to acknowledge the original inhabitants of the lands where we currently have the privilege to research, live, and work wherever that may be for you. We'll now move to an introduction with some standard housekeeping points for today. Everyone but the presenters will be muted throughout the webinar. If you need to change or test your audio during the webinar at all, you can click Audio Settings and this is in the left of the bottom toolbar. Today's webinar will consist of two presentations where you get a two-for-one deal today. At the end of both presentations, there will be a question and answer session. If you have a question about the webinar, then at any time where you can post the question by typing it into the Q&A box that's located in the bottom toolbar, the questions will be addressed at the very end of the webinar. Questions will be visible to all attendees. If you have any technical trouble concerning the webinar, you can use the chat box to communicate with our webinar team. So again, Q&A box for the questions to the presenters and chat box for technical issues, please. A feedback survey will be launched at the end of the webinar and we invite you to complete this after exiting your Zoom session today. This brief evaluation survey provides us with important feedback that we can use to plan future SPLSA webinars. Now onto the webinar. Again, the title is The Impact of Urban Grimness on Aging, Physical and Mental Health among CLSA participants. This webinar will be presented by Irmina Klichnik and Susanna Abraham-Potagiri. Irmina is a third year PhD candidate in health science. She's working under the supervision of Dr. Shilpa Dovra. Her dissertation focus is on the topic of active living and that's as defined as the intersection between social participation and movement behavior. Irmina has published two papers utilizing data from the CLSA and she's especially interested in exploring the role of neighborhood factors as they relate to active living, active aging. Susanna is a second year PhD candidate in epidemiology at Queen University in Kingston. For her thesis, she is looking at cancer incidents in the vicinity of Canadian nuclear power plant using the Canadian Census of Health and Environment cohorts. Her supervisors are Dr. Paul Villanue from Carleton University and Dr. Will King from Queen's University. Now I will pass it on to Irmina who will be presenting for us today. Okay, can you see that? Is that visible? Yes, okay. Okay, so thank you. And first of all, inviting me to the sub in our series. I've attended a few myself and I've enjoyed learning from these. So I'm really happy to have an opportunity to present some of our work that we've done with the CLSA. So, and again, thank you for that introduction as well. So today I'll be talking about greenness and health among CLSA participants and I'll be highlighting a couple of the studies that we've done using this data as well as one that's currently under review for publication as well. Is it, there we go. So I'll thank you also for the land acknowledgement. I just wanted to also include that this area where we're at in Oshawa is covered under the Williams treaties as well. That's an important part for us. So greenness is essentially an indicator quantity of green vegetation on the ground which is derived from satellite imagery kind of like you see in this image. It's used when examining relationship between environment and health and to access the environmental variables from the CLSA, we actually use the pre-linked data set that includes like a variety of environmental data from the canoe data set which is the Canadian Urban Environment Health Consortium. So before I go into some of my studies I just want to give you a few examples of how greenness has been used in previous research and a little bit about how it's measured. So as I said, it's an image like a satellite image of how much greenness reflects back into the image from the ground. And so usually within a certain postal code or a geographic area we would look at a buffer like a circular buffer for example 250, 500 meters or 1,000 meters buffer. So it's been studied for a lot of kind of traditional health outcomes like mortality and physical outcomes. The first study that I want to highlight is sometime 2017 which looked at the like association between greenness and mortality risk. So on the left there you can see hazard ratio going from one to zero and across the bottom we've got greenness within a 250 meter buffer. So kind of a smaller area but essentially you can see that as greenness increases sorry the risk of mortality decreases quite a bit as that increases. So this was in this study the kind of biggest effect were for respiratory disease and the lowest for three-brow vascular disease. So there is quite a bit of range but we're seeing this pattern on a very large scale because this study actually used participants from the Canadian Census Health and Environment cohort which is over 1.2 million participants. So if we're seeing something like this on such a large scale we know there's something going on in there. This next study by Tuyig, Bennett and Jones they included 103 observational studies and 40 interventional studies and they looked at over 100 health outcomes. So for this collection here this is six studies that they included in this meta-analysis and they found that higher greenness is associated with a decreased incidence of type two diabetes across these studies. And they also found that higher greenness is associated with decreased blood pressure across 12 studies. So that is pretty, that's something it's not nothing and there's something definitely there. So it definitely requires further investigation. And then in this study here by Perino et al in 2019 this image here is right from the paper they used greenness, they broke it up into turtiles whereas in the CLSA we usually use quartiles or quintiles to separate out the data. In the top, the lowest turtile you can see there's hardly any greenness in there it's like a very cement urban type of neighborhood. And then in the highest you can see a lot more greenness and it is like I said it's a snapshot of this small buffer area but just to give you an idea of what the satellite images are looking at. So after adjusting for comorbidities in the sample there was a relationship between greenness and the odds of, I'm sorry the likelihood of depression. So there was a lower likelihood of depression in the medium versus the low greenness which is actually called NDVI here it's the normalized difference vegetation index it's the technical term for it. And then a 12% or sorry 16% lower likelihood in the higher greenness versus the lowest. So people who are living in these areas they're experiencing better mental health. So this kind of leads up to the question of, we're coming to show evidence that greenness results in health but how exactly does this happen? Is it enough to plant a few trees in your yard and all of a sudden your diabetes disappears? Probably not. So in our lab we're kind of interested more in these mediating factors or these kind of intermediaries such as movement behavior. So one area of focus in the study of older adults is age-friendly environments. So creating communities that are supportive of social activity, physical activity and which provide access to like healthcare transportation and other services. And so two important aspects of age-friendly environments are the built environment. So whether we have sidewalks and parks and libraries nearby where people can gather as well as the natural environment. So I mean, you could argue that building a park or putting a park in could be a part of built environment but usually these kind of more natural environments are considered as greenness. So this one other study that I just wanna highlight because it kind of shows this relationship really well greenness exposure contributes to all these in the middle column, all these outcomes like stress reduction, air pollution, filtration, regulation of heat and humidity. These are kind of like the obvious measurable things but right there highlighted is increased physical activity. So we've seen that quite a bit and I'll talk a little bit about that when I get into our papers. But essentially, we see this connection but I want you to look to the right of that and see how many connections we have between greenness exposure, physical activity and then all of these health outcomes. So it's like the role of physical activity or movement behavior definitely needs to be considered when we're looking at greenness and health. The other thing that some of these studies don't really show is, let me just not clicking for me. There we go. Our geriatric syndrome. So this image is adapted from actually another webinar presentation by one of my committee members, Dr. Copeland. So she kind of outlined geriatric syndrome as these other syndromes that impact quality of life and independence. So things like pain, frailty, falls and things like that. They impact our functional limitations and our kind of stronger predictors of self-rated health and mortality than chronic disease actually is sometimes. Because as you know, and maybe you felt this way too, you might be diagnosed with a chronic condition but that doesn't necessarily mean that you're going to have poor self-rated health outcomes. You might have arthritis but you still do what you want when you want every day. So it might not impact you the same. So these syndromes are kind of more of a, coming at it from a self-rated type of your own experience of the actual condition rather than yes or no, do you have a condition? So that leads me to our three papers. So the purpose of our first paper was to look at movement behavior. So we discussed that as physical activity and sedentary time across different neighborhood environments. Let me get into the variables a little bit later but we started with this one to kind of establish that connection with using the CLSA data because we have all this wonderful environmental data here and it's a beautiful large sample. So we wanted to take advantage of that to see where we can build this story. This is the purpose of our second study was to look at the same neighborhood factors. So again, Greenis, I'll also mention walkability a little bit but since the focus of this talk is more on Greenis, I'll focus more on that. So we looked at the associations between those factors and self-rated measures of health. So like general health, self-rated mental health and self-rated healthy aging as well as chronic condition count. So the actual yes or no of whether you've been diagnosed with something in the last 12 months or ever. And then for our third paper which is hopefully going to be approved for publication very shortly as we've just finished our revision. The purpose of this study was to assess for a moderating effect between each of physical activity and neighborhood factors and geriatric relevant health outcomes. So for us from the CLSA data, we were looking at a physical impairment, pain, medication use and depression as these geriatric relevant health outcomes. Okay. So overall, the first study differs a little bit from the next two because in the first one we included the entire sample. So we had about 36,000 participants in that first study but we excluded participants who didn't have complete data for outcomes. So we got a little bit wiser in study two and three and decided to use multiple imputation to counter that a little bit because we were only using participants 65 and older at baseline for the next two studies. All of our environmental exposures were from baseline because the canoe data set is only linked with the baseline data set for CLSA. And total physical activity ranged quite a bit from five to eight hours per week across the different studies just depending on the age and things like that. And just to kind of just a little bit finer detail into some of our variables for our first study, we looked at total physical activity. So we use the pace scale, the physical activity scale for the elderly. It's a self-rated instrument. So essentially people are asked how many days did you participate in light intensity physical activity in the past week and how many hours per day? So we use that information to figure out essentially hours per week. And then we developed a semi continuous, I guess it was more of a count scale. And then for sedentary time, which was continuous also, we just had the one question about how many, how much time do you spend in sitting activities per week? So again, it's, we know from the research that that is not the best way to get at sedentary time because sometimes we under report how much we sit or we don't know if something is sitting and something is not sitting or sometimes we over report. We think we're just sitting the whole time but really we are getting up and moving it around. So just keep that little caveat in mind as we go through. For study two, we looked at for the chronic conditions count. It was just, it was based on the D-Drix framework which has 10 kind of like most common chronic conditions for people over the age of 65. And the questions in the CLSA were, have you been diagnosed with one of these in the last 12 months and yes or no? And then for self-rated health, we had the general health, mental health and healthy aging which was kind of rated from excellent to poor. And then for our third study, our geriatric relevant health outcomes, the physical impairment outcome was from the older American resources and services scale. So it was just, it was asking people if they have like one or two or three or more or none impairments that kind of prevent them from being independent throughout the day. Pain severity rating, medication use which was listed as one, two or three plus prescription medication. And then we used the depression question using the CSD depression scale. So for our exposure variables, again, these are from baseline because that is where our environmental data is available. The first one was the ALE. So the ALE stands for Active Living Environments. We use index or a Z score depending on the study, but essentially it looks like dwelling density, intersection density and points of interest within your neighborhood essentially. So we use this as a measure of walkability. You can just put that at the back of your mind because we won't be talking much about it, but I just want you to kind of consider it. And then for greenness, the normalize difference vegetation index, again the NDVI, we looked at these values as quartiles because the main purpose is that it's really difficult and I don't want to say meaningless, but it is not as meaningful to interpret 0.49 greenness versus 0.45 greenness. So when we look at it in quartiles, it's a bit more conducive to interpretation. For our first study, we actually use the max of the annual mean at 1,000 meters because we wanted to use a larger buffer and this is more of a conservative method, but we change it to the mean of the annual mean for the second and third study because the distribution was a lot better after we were able to impute some of the missing data. So a few of the results from our study, this is from study one. This graph just shows the odd ratios for greenness. So these are compared with the first quartile of greenness. So in this, you see my mouse there, the first section here, this is the second quartile of greenness compared to the first. So when you think about those numbers, we have access to zero to one, a range of zero to one for greenness, zero indicates barren land. We don't have many people living in barren land in Canada and then the highest values we had was around 0.74, our kind of denser bush type of area or more rural areas. So as greenness goes up, we're seeing increases in physical activity as well, especially the younger males and females and the males that are kind of middle age 65 to 74. So it's almost like it's going up a little bit here from second to third and then in the fourth it levels up a little bit. These areas are quite rural. So the built environment in this area would be a lot lower and so that's why we considered built environment in this study as well. And then for that, for the sedentary time, higher levels of greenness also had higher levels of sedentary time for the younger males and females with those age 65 or younger. So that was kind of interesting for us, a surprising result. And then for study two, which was looking at the chronic condition count and the self-rated health outcomes where we saw that there was an increase, well, this looks like a decrease, but that's because excellent is one and poor is five. There's 10% higher odds of higher self-rated general health and 12% higher odds of better self-rated mental health for higher levels of greenness. So we're seeing this for the self-rated variables, but not so much the actual chronic condition count. And then for our third study, which hopefully will be up soon enough and you all can read and enjoy that, we were looking at moderation effects here. So there's an additional effect on top of those known associations that we already are aware of between physical activity and geriatric outcomes and the greenness or neighborhood environment and the geriatric outcomes. So we know there's an association between those two things, but there is an additive effect when you consider both of those things together. So overall kind of our overall conclusions in study one, we were able to show that movement behavior is different across different neighborhood environments. So it's definitely something that needs to be considered. And then for study two, neighborhood factors are associated with general health and mental health of self-rated, but not chronic condition count. And then for our third study, there is a moderating effect between, in the relationship between each of physical activity, neighborhood factors and those geriatric relevant health outcomes. So the association between these outcomes and our exposure variable are affected beyond just the individual relationship. So overall, the positive association between neighborhood greenness and self-rated measures of health could be due to a lot of factors. But what we are kind of showing with all of this data and all of these findings is that greenness might be an important factor to consider when promoting healthy aging in older adults. So the next step is to consider other mechanisms by which this is happening. So for me, for my PhD, I'll be looking at another mechanism as a social interaction and social engagement and considering that active aging. So I've defined active aging as physical activity and social participation because we know those things are related. So I'll be looking at how environment exposure like greenness, walkability, other neighborhood factors kind of go through this funnel of activating to result in some measurable health outcomes. And that is it for me. Okay, well, thank you very much. That was very informative. And I think a great first half to our webinar today. I had sent you a message, Ramina, but maybe if you wanted to type any responses to the questions, if you're able. Okay, in the Q&A? Yeah, I'm just actually thinking that we may have ended up with a lot of questions. So it might save being able to get through some while Suzanne is presenting, but I will turn it over to Suzanne now and we'll definitely try to get to all the questions that aren't answered. Thank you, Jennifer. Can everybody see my screen okay? Good, okay. Thank you for the opportunity to present today. I'm going to be sharing some of our findings from a recent paper that we published in environmental research on urban greenness and mental health among adults in the CLSAC cohort. So there might be some overlapping themes where they mean as presentation, especially regarding the exposure. So please bear with me. So I'm going to start with a causal diagram that shows green space in the context of built environments and how it can prevent chronic conditions. So there are two primary pathways from built environment to chronic conditions. So one is through behaviors that encourage or discourage us to behave in certain ways that can affect adults. So this would include participation in physical activity and opportunities to increase your social interactions. The other is through exposure to harmful substances such as air pollution and extreme temperature. Now these exposures and behaviors can lead to an increase or decrease in intermediate events such as systemic inflammation and stress, which then if an address could lead to the development of chronic conditions. So I would also like to highlight that these pathways are not exhaustive and they have varying degrees of influence. The generally environment exposures tend to be very complex and interlinked. Today I will be focusing on green space and its association with various indicators of mental health. So now a little bit about mental health in Canada. Annually we have about one in 10 Canadians who use health services to manage mood and anxiety disorders. Here on the right I have a graph showing the prevalence of mood and anxiety disorders among different age groups. Individuals, 45 and over, carry a substantial burden of this disease. Additionally we have a rapidly aging Canadian population and a large proportion of these people are reporting on mental health needs. Now researchers and policy makers in the last decade have advocated for novel approaches such as improving your natural environments. Now we have a lot of recent studies that suggest links between green space and improved health. But very few studies have focused on older adults. Additionally, we know very little about the variable impacts on economic strata, especially in the Canadian context and how this association varies with how often people interact with their neighbourhoods. So our main research question was to assess if urban greenness was associated with mental health among Canadian middle and older age adults. We also wanted to know if green space had the potential to reduce socioeconomic disparities in mental health among Canadians. So this is because we have several European studies that show pronounced benefits of greenness for those in the lower socioeconomic groups. And we wanted to know if maybe in the Canadian context this could be true. And we also wanted to check effect modification by sex, age, household income and how often people interact with their neighbourhood. So we did a cross-section analysis of the CLSA comprehensive cohort baseline to look at the previously mentioned questions. We restricted our sample size to the comprehensive cohort. This is because the availability of detailed data such as frequency of interaction with neighbourhood was only available in the comprehensive cohort. So here I have a flow chart showing our final sample size. We excluded participants who did not live in urban areas. This is because Canadian postal codes and rural areas are not spatially resolved. That means in a rural area, a postal code could cover a large land area such as an entire town or a village. Now to assess green space, we used NDVI, the Normalized Difference Vegetation Index. So very briefly, if I had to define the NDVI, these are satellite images from which we can and for the density of greenness. So Irmina had a really nice picture in one of our beginning slides of what it looks like. So the index ranges from minus one to one with negative values representing water and values around zero bare soil and higher positive values means dense green vegetation. So we restricted our NDVI to the positive values to isolate the effects of blue space. Now, can you compile NDVI values for Canada on an annual basis? The CLSA team assigned greenness using the centroid location of each participant, six-character residential postal code. So for our analysis, we used the maximum of surrounding annual mean NDVI within a 500-meter buffer of the participant's place of residence. So we also conducted sensitivity analysis with 250,000-meter buffers. So the CLSA had the comprehensive cohort had very rich data on various mental health outcomes. We used four self-reported measures of mental health, the Centre for Epidemiological Studies Depression Scale. So this is the short form scale which has 10 questions and participants answer these 10 questions and they have a score from anywhere zero to 30. Then we had self-reported clinical depression. This was a yes or no question. The perception of mental health was on a likered scale which range from excellent to poor and satisfaction of life scale was again a scale that ranged from extremely satisfied to dissatisfied. So for our analysis, we ran a multivariable logistic regression model to describe the association between greenness and mental health outcomes. And we ran a cubic spline analysis to evaluate the shape of the dose response function between greenness and CESD10 scores. So that's the depression on the continuous scale. We ran stratified analysis to evaluate the variations across social demographic stages and frequency of interaction with neighbourhood. For all of the above mentioned analysis, confounders were identified using review of literature. Then we used the distinctive cost criterion approach with the liberal value of 0.2 to select confounders that went into the model. Here we use the relationship with the exposure. So this is our main table. We have risk estimates in three different models. The first set of estimates were minimally adjusted for age group and sex alone. This was extended to include race, household income, mobility issues, alcohol consumption, smoking status and physical activity in model two. And the third set of estimates are the fully adjusted models that include all of the previously mentioned covariates plus the frequency of interaction with neighbourhood, region, perceived noise disturbance and NO2 concentrations. So I just want you to look at the little red boxes there. So in our fully adjusted models, we observed a 5% reduction of reduced odds of depressive symptoms in relation to an interportal range increase within a 500-metre buffer of the participants' residence. So we similarly found an inverse association with the other three indicators that we looked at.  So this is one of our spline graphs by household income. So we have the CESD10 scores on the x-axis and the maximum of annual mean and DVI within a 500-metre on the y-axis. These graphs again are adjusted for socioeconomic factors, health behaviours and air pollution. So if we look at the less than 550,000 yearly household income, we see that as greenness increases, their depression scores show a steeper decrease. So for the other two groups, there is a decrease, but it's not as steep. So this is suggestive that greenness could help in reducing socioeconomic disparities in mental health. So this is our second spline graph. This one is by how often people interacted with their neighbourhoods. Again, these are adjusted for socioeconomic factors, health behaviours, indicators and air pollution. So if we look at the greater than or equal to four interactions per week group and compare it to the other graph, we see that those who interacted more with their neighbourhood had an overall lower score of depression. So this is suggestive that greenness, the effect of the beneficial effects of greenness tends to be stronger for people who interact more with their neighbourhoods. Now I want to highlight some of our strengths and limitations. So we had a large number of participants from various Canadian urban areas. We were able to adjust for confounders that were not available in the past. So this includes how often people interacted with their neighbourhood and perceived noise disturbance. Additionally, we see consistency of findings in terms of protective association for all four of the mental health indicators that we looked at in the adjusted models and across household income categories. Now, some of the limitations that I want to highlight is a possibility of self-selection that could have happened. This could have happened in two ways. So individuals of higher socioeconomic status might be able to select where they want to live so they might choose greener areas. And secondly, people with severe mental health issues might be less likely to use their neighbourhoods. So both of these factors could have attenuated odds ratios to the null. Now, because we're looking at a cross-sectional nature, we data, we have limited ability to draw causal inferences. Lastly, I also want to highlight that the NDVI is a really amazing indicator, but it's unable to capture the type of vegetation, biodiversity, and if the green space is actually accessible to you. In summary, our findings suggest that residential greenness is protective for mental health among Canadians, Canadian adults and the CLSC cohort. Now, greening interventions can be used as a strategy to mitigate socioeconomic disparities in mental health. And we see stronger associations between greenness and mental health outcomes for lower SES populations and for those who frequently interact with their neighbourhoods. I would like to thank all of my co-authors, especially my supervisor, Dr. Paul Villeneuve, our collaborators for providing us with such a rich, amazing data set, the CLSA team and the CanU, and our funder, the CIHR. Thank you for listening. Happy to answer any questions that you might have. Great. Thank you, Susanna. And again, thank you to Irmina as well. And Irmina, you did a great job answering those initial questions. I'm sure there's going to be a few more. There's always a few more that pop up, but I'm just going to... I'll give Susanna a little bit of a pause for a second. And I think there was one question that there was a follow-up question to Irmina. And that was... It was, was breedness not associated with physical activity of females, 55 to 75 years, and you had said it wasn't a significant association, but do you have a hypothesis for why not? Irmina. Whoops. Okay. So thank you, everybody, for all the questions. So in terms of why it's not significant, I think it would come down to the statistical analysis. Like I'm not sure exactly why it wasn't significant, but in terms of how older adults do physical activity and social activity at those ages, 65 to 74 is usually considered after retirement for men. So of that age group, kind of in general, males, I should say, they retire. So their life changes a little bit. There's, we expect to see some differences between those age groups. For females in that cohort, it's a little bit different. Not all females of that cohort would be working. Many are, especially in the CLSA data set. Many would have that retirement time, but we know from other research that women and men, like men do more physical activity, but they're also more sedentary than women at that age. So there's still more nuance to tease out from there. And it definitely requires further investigation, I think. That's why we're gonna keep at it with some of this data. Great. And actually I'm gonna go to a question that was asked. Maybe Susanna might have a comment on it. It was the question from home about how greenest environment or community improved the holistic healing and wellness for adults with dementia for both indigenous and non-indigenous. I thought given the focus on mental health in your work, you might have, I know in the CLSA, I mean, it's right, the CLSA doesn't have, specifically have a cohort of indigenous people living on reserves. But have you come across differences in mental health in terms of greenness for people with Alzheimer's disease either? With or either indigenous or non-indigenous or sort of unpacking that all of it? So in the paper that we did, we didn't have, we didn't look at people with memory issues or older adults. The focus was more on 45 to 85. So like an overall picture of what mental health looks like when your greenness increases. But there is research out there that says as greenness increases, it increases your restorative capacity. You're able to cope more, you're able to put this lesser stress. So there is some evidence out there, but it was not teased out in the paper that we did. Great. And now we have, we do have a question from Ellen. And it is, how do you consider using electronic devices such as watches to track physical activity? I presume this is more one for Amina. We would love to do that, but that's just not available with the CLSA dataset. So we've used, we've actually used, we use accelerometers actually, they, we attach them onto our Patricia Pintz leg or to calculate kind of their 24 hour movement behavior. So we get a good sense of how much they are sitting and walking at a higher speed or just getting up and down. So we would love, if that was available in the CLSA, oh my gosh, like that's my prayer. That's a question for the people to say.  Oh, are they gonna be doing it in the next follow up or? Yeah, actually, we've actually just, the CLSA has just recently, our follow up three started using wearable devices for some of our participants. So that data won't be obviously ready or released for probably early follow up four, but yeah, we are using mobility trackers as well as sleep trackers. And you can find some information about that, I believe on our website. Look under the participant material section. I think it's under that. That'll just give you a sense of what will be captured next. Yeah, that would be great because you're right. Whoever asked the question, like having the objective measures certainly adds to the subjective measure that we're collecting like with the pace because, you know, there's pros and cons to both of course, but it's very helpful to have both. Okay, so now we have a question. Do you think that greening of nursing homes will have the same effect? I don't know. Effect on mental health or physical activity, maybe you can both answer that from your own perspective. So for me, I haven't done any work in long-term care, but I have done some work in assisted living and I do work with an inpatient population in a hospital. Definitely any environment that is conducive to social and physical activity is going to help regardless of, you know, what level of greenness it has or anything. I used to actually work at a retirement home where they had courtyards that were accessible from any exit with a ramp. Like it was just so easy for people to move in and out of the building. There were lots of places to rest, but also, you know, trees and plants and things that they could go outside and enjoy and it made them want to be outside and maybe join a physical activity group that was taking place out there. So in terms of studies that have been done in this area, I'm not very familiar with, from a long-term care perspective, but from my personal experience, certainly having an outside environment is helpful for people who, especially with dementia. And did you have anything to follow up with, Susanna? So in a live person or animal there or something? Yeah, so that's, I'm so sorry. That's my dog. So for my research, we looked at, we had, so I can share a graph that might show that this doesn't relate to older, younger group, but so we have, we did this blind graphs for depression by 45 to 60 year old and 60 plus years old. What we saw is that the older group had an increased protective effect.  So this could be suggestive that if they, you have increased greenness, maybe for older people, it might be even more protective than for younger people, because you have increased opportunities for social interaction and physical participation. But I wouldn't be able to infer that to long-term care, though, if that makes sense. Yep. Okay, so next question. Rather than overall physical activity, have you looked at different types of physical activity from the pace that may be more impacted by green space? Or did you re-answer that one, Stephanie? Yes, you did. Okay. Let's, let's get started. I think that was just a followup to her first question, but what I wanted to just note is that we mentioned this in our limitations as well, is that for the actual frequency and intensity of the activities, we don't, there's no, it doesn't tell us like if it's outside or inside. So that's one of the things that's kind of missing from there in terms of looking at physical activities that are listed and specific, because the CLSA, the pace does actually ask for, you know, like it'll ask no golfing or soccer or other like actual activities. But again, it's not clear from that data, from those questions, whether it's inside or outside. So that's kind of a limitation that we have because people might be very physically active, but it could be all inside. So the greenness has nothing to do with how physically active they are.  Yeah, and I guess that touches on the question that I was gonna note next, and which is green spaces, maybe white spaces in winter, can you keep the seasonal factors? And so that's interesting. So if one of you wants to touch on that, that would be great. So I can go first. So the NDVI, so the measure NDVI in Canada, they measure it during the summer season. So it's an average they take from when the cloud cover is less than 10%. So we only infer this when it's actually, when your vegetation is actually green. So in our analysis, we try to look at season. So when the month the participant answered the survey, we tried to do a sensitivity analysis with that, but none of our results changed. So eventually we didn't add that variable, but that is a factor that needs to be considered when you're doing research with greenness. Great. Maybe we'll go on to Sandra's question, which is good sort of knowledge translation, research update question. Are you open to sharing your work with city planning departments and ecology centers? I can go first for this one. So my lab, I guess, and my supervisor for sure are, we're going to be using this information to kind of bolster some of our other studies that we have going on right now. Currently my supervisor is leading a study about like older artists experience of their neighborhoods. So they're doing walking interviews with them, which is really cool. And we're going to be presenting that information to our like regional counselors. Because in OSHA, we have quite a strong, like we have the OSHA Senior Citizen Center, which is a very big group. And they're, you know, they're very motivated to make sure that older adults are getting what they need and that their voices are heard. So we will be using some of this information to to present when we when we end up showing them the study results from our actual like in-person study that we've done in OSHA. So yeah, definitely we'll be sharing that information. Anything to add about knowledge translation in general related to your work, Suzana? So we haven't, so me, my supervisor and our team, we present when we're asked to fall within like the research team and the academic team. We haven't been able to go further than that, but that's something we have been talking about. But, yeah. Sorry to put you on the spot there. No, no, that's okay. One of my favorite topics. So I like making sure we address it. Okay, so with a few more questions before we wrap up, is there a type of greenness that provides a greater impact for personal property greenness versus public greenness have different impacts? Not sure who wants to jump in on that one. Yeah, so I can go first. So the disadvantage with NDVI is you can tell how dense the green is, but you can tell if a person has access to it, if it's your garden or what kind of vegetation it is. We don't know that yet because the NDVI is not able to capture those minute differences and those details. But there are other measures that, other satellite measures that are being researched where you can actually, the AI can identify, okay, this is your personal garden, this is your park. So when we have data like that, maybe in the next few years, we will be able to tell what type of greenness actually affects your mental and physical health. The other thing that I'll add is for our study, because we're using a larger buffer, we're trying to incorporate just outside of your, maybe your property. So if we're, ideally we would have a 1000 meter buffer of the mean, that would be really helpful in kind of figuring out a kilometer of where you live. Because the idea of, for instance, we're considering walkability as well. It's a completely different story if you've got people who, like where I live in North Oshawa where it's very residential, a lot of people that I know will drive up to Uxbridge to enjoy the parks and the trails up there. So, my neighborhood greenness doesn't necessarily impact my physical activity outside, but this would differ across age groups of course, right? But for now, using a larger buffer, I think would really be the only way to mitigate for that. And I like this question. The findings on greenness and health are interesting and mostly refer to outdoor plants. Any knowledge and comments about indoor plants and health? Outside of the environmental things like air purification, I don't have enough knowledge in that area, unfortunately. Especially as it relates to physical activity. Yeah, I would have to say the same because we haven't been able to make any inferences for indoor plants. And I don't think the CLSA had any questions regarding that, but maybe that's a question that could be added, like in the future. Okay, and so a question from Stephanie. Month was indicated as a factor investigated with latitude also investigated. I believe this would be for Amina, but. So because the CLSA data collection sites are like the range of latitude is pretty small because it's mostly from the kind of higher, highest populated areas of Canada. So in terms of like, if you think about, I don't know if you've ever, if you're a gardener or if you know anything about like plant zones, most of the data collection sites are within one or two plant zones. So it's kind of homogenous that way. So we didn't account for it definitely, but absolutely, like people who live in Northern Quebec will have a very different experience than those of us in Southern Ontario. Okay, so last couple of questions from Kathy for Cork Fuller. This one is about inclusiveness. Walking and talking or listening or challenging for people with hearing or vision loss. So it might not be a great idea to interview people while walking in terms of inclusiveness.  I think that might be related to the comment I made about our walking interviews study. So for that, we're definitely, it's not like we're walking and talking and snapping pictures and writing all at once. It's more that the participants will take us through their neighborhood, like where they go to the park or just to show us, oh, we don't have any sidewalk here. So I have to walk on the road or however they access their environment, but they're welcome to use their walkers. If they use them so far, I think we've only had a few people with canes and walkers who actually do go outside. The point is for us to, like we want them to show us what it is. If their walking interview takes us to the end of their driveway because they can't get anywhere, that's important for us to know. So we haven't run into that as far as I know. I'm not directly involved with the study, but as far as I'm aware, we haven't come up against that, but we do have a lot of variability in how much people are taking us for these walks. So we would try to accommodate any participants if they wanted to be part of it, but they can't even access their neighborhood. We would meet with them on their porch. It's just more so that we can have their lived experience, like through their own words. All right, and I think we'll have time for this one last question before we wrap up. Are there also benefits of being around water, such as the lake or ocean? Have either of you come across that? Maybe Susanna can- Yeah, so there's plenty of research on blue space as well. So the beneficial effects of blue space on mental health, physical health are quite similar. So the NDVI values around zero, zero to a little bit over 0.1 tends to be blue space. So we isolated that because we had only 28 participants around that value. So, but definitely research around blue space is out there, and they show similar protective effect for mental health. Okay, well, I think we will wrap it up now. We are right on time. Thank you to both of you today. I think you did a fantastic job and you had lots of questions and lots of really interesting questions too that hopefully challenged you as you complete your PhD study. I'd like to remind everyone that the next deadline for data access applications if you're interested in using the CLSA data is July 12th of 2023. You can visit the CLSA website under data access to review what data is available as well as details about the application process. I'd also like to remind everyone to complete your survey upon exiting the Zoom session today. For the next CLSA webinar, it will be entitled The Impact of Retirement on Cognitive Decline, findings from the CLSA, and it will be on May 23rd at 1pm by PhD student Catherine Goslin and registration for details for the next CLSA webinar will be posted on our website and social media as well. And then finally, a last final thank you to everyone for attending today and to our presenters. And remember that the CLSA does promote the webinar series using the hashtag feelasdaywebinar. So we invite you to follow us on Twitter at CLSA underscore ELDB.  Thanks. Thank you. Thank you, bye.