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An array of cognitive traits impacts the behaviour of free-living animals, including perception, attention, learning, memory, decision-making and executive functions (flexibility, categorization, problem-solving [20]). Individual variation in cognitive performance is well documented in the animal kingdom [21,22], yet the evolutionary significance of cognitive variation remains poorly understood [23]. Cognitive performance can vary within and among species [24,25] because of the influence of environmental factors and is underpinned by selection for cognitive traits associated with fitness outcomes [26]. One approach to understand the link between cognition and fitness is to first measure cognitive performance in individuals and then correlate this with a fitness metric [27], such as reproductive success and/or survival [28,29]. For example, pioneering studies in birds showed a positive relationship between problem-solving performance and reproductive success, measured as clutch size or mating success [29,30].

Direct selection for cognitive traits is associated with greater innovation rates and brain size, which predict colonization and survival success in birds [35] and mammals [36]. Yet, most of these studies did not specifically test whether general intelligence in animals is directly related to survival success in the natural environment, and there is no evidence for a link between a g factor and reproductive success in wild birds [6,13]. Furthermore, it has been suggested that general intelligence results from a cluster of cognitive traits that are linked together and are elicited by evolutionary conditions and factors that create a set of selection pressures [37]. However, cognitive arrays are the result of species-typical adaptations to their whole ecological and social environments [3]. Thus, it raises the question of whether a g factor or specific cognitive traits instead better correlates with fitness in free-living animals with a specific ecological and social environment.

Tulane Law School conference to feature top media experts - September 21, 2018Media scholars, legal minds and reporters for The New York Times and The Washington Post are among more than two dozen experts who will serve as panelists at a freedom of the press conference Sept. 27-28 at Tulane University School of Law.Titled...

Well good morning everybody I hope you can all hear me well my name is Sue Higgins and thank you for joining us for the path to accessing health data in Montana it's at first in what we hope will be many health research related webinars hosted by the Center for American Indian and Rural Health Equity, Montana INBRE, and the American Indian/Alaskan Native Clinical and Translational Research Program these are three Montana based NIH funded health research programs I'd like to thank our two wonderful speakers Heather Zimmerman and Helen Tesfai they will speak back-to-back hopefully with a short time for questions at the end during which you can ask questions using the chat function on your screen you're all muted right now but this chat function should work if we don't get to those questions we'll record them and get back to you with answers as well as copies of our speakers presentations in a post webinar email that we'll send to everybody one final note please bear with us as we troubleshoot our new webinar system we hope it runs seamlessly for you and now to introduce our speakers while Heather loads for presentation I've got to transfer that to you Heather and hopefully that worked Heather Zimmerman earned her master of public health and epidemiology from Saint Louis University in 2007 she's been working for the Montana Department of Public Health and Human Services for the past nine years first managing the Montana behavioral risk factor surveillance system data her face and then working with a variety of chronic disease programs her current position is with the Montana cancer control programs managing the central tumor registry which he started in November of 2006 Palin Tesfaye Montana she's an mph is a senior epidemiologist with Rocky Mountain tribal epidemiological Center she worked in public health field for over five years in Eritrea in East Africa where she worked as a biologist and a researcher in a mosquitoes lab processing data and helping publish research manuscripts before coming to the United States Helen also has a diploma in software applications and information technology in 2009 she earned her mph degree in epidemiology and international health and development at Tulane School of Public Health and Tropical Medicine goals she tutored SAS a statistical program while at Tulane and also worked as a Data Manager at the Louisiana Public Health Institute with that I'll turn things over to Heather and if any of you have problems seeing or hearing please send a chat to me thanks so much Heather go for it good morning thank you so much for that introduction I will go through today some of the public health data sources that are managed by the Department of Public Health and Human Services and could be very good resources for all of you doing health research so this is just a list of all the data sources I'm going to go through it's it's a lengthy list so I'm going to go through each data source fairly quickly but I have included a good amount of detail on the slides that will be sent out for your reference later on especially contact information for each of the people who manage these data sources and will be able to answer questions or deal with data requests so without further ado I will get started first of all we have available population estimates from the National Center for Health Statistics and this is data that is produced nationally but it is we make it available to you specifically for Montana because it's the population data that we at the department use whenever we're calculating rates so it's fairly comprehensive and and malleable it's derived from census and American Community Survey estimates which I'm sure you're all familiar with and provided to us by the National Center for Health Statistics and it's useful because we have county level data let me slip to the next slide we have county level data for single years of age through the year through age 85 and then after that it just says 85 plus so you're able to put together age groupings any way that you like which is obviously very helpful and much more convenient for then using traditional census queries and you can get at the county level you can also stratify by sex and we have single years from 1990 through 2017 and so every year we added a new data set a new year the kody Custis is the person who manages this and you can get the data on our data query system called ibis which i will go through at the end of all of this next we'll talk about vital statistics so this is death data and also birth data which I'll get to later and the death data comes from the death certificate so it is a complete counting of all deaths among people who lived in the state and also people who died while there they were just physically in Montana it has cause of death location of residents down to the county level location of the death not like an address but just a hospital home nursing homes that kind of thing and also demographic data so that can be very useful as a health outcome obviously birth data it comes from birth certificates so similar to the death certificates it includes all births among women who reside in Montana and also births that occur in the state even if the residence is elsewhere it has parental characteristics the location of the birth data about prenatal care smoking and alcohol use during pregnancy method of delivery birth outcomes and breastfeeding status at discharge so this is obviously a very rich data set that is available for any kind of infant or maternal outcomes and all of that is managed by the vital statistics office Todd Cooke runs that here's his contact information the death data and the birth day are also on Ibis but you can see sort of canned reports and different analysis that's just done routinely and put on the website at the webpage that is here next we'll go through the hospital and emergency department discharge data so this data comes from the Montana Hospital Association it is de-identified records of all inpatient admissions and II D our emergency department encounters it's based on the billing data for these encounters and so we get all of the information that would be submitted to an insurance company for reimbursement it is a voluntary system so hospitals do not have to be part of this data set but it does have very wide coverage and as I said before it is de-identified so we have no way of identifying the individual who was admitted or encountered so there is possibility for multiple admissions among this the same person if like for example if a person is admitted to one hospital and then ultimately just determined that they need to be transferred to another hospital the admission to the second hospital would be counted twice and there would be no way to know that those two admissions were linked to each other so that's just important to remember when you're looking at this data the main data that's useful is age sex length of stay date of admission primary diagnosis secondary diagnosis and that's up to eight secondary diagnosis procedure codes ecoute are codes that are used for injuries mostly they code the manner and the place of the injury so so the diagnosis code might be you know broken humerus right humerus that might be the diagnosis code but then the e codes would be fell off of the slide at school and broke the arm so that's what e codes are total charges but it does not say how much was reimbursed just how much was charged and then it does have county of residence of the of the person but in a lot of cases we're not able to release county-level data for the emergency or impatient emissions because one of the stipulations of our being able to use this data from the Hospital Association is that we don't identify individual facilities so many counties only have one facility so it's it gets a little bit tricky Cody Custis also manages the Montana hospital discharge data program so again he's your contact for that our next data set is the Montana central tumor registry which I manage and it is a registry for information on all new cancer cases among Montana residents and also just people that are treated for cancer in Montana so it is state law that all new diagnoses and and tumors that are treated in Montana facilities must be reported to the central registry I was established in 1979 and it's very complete we estimated at least 95% complete data is available on demographics treatment information cancer site and type stage at diagnosis it's a standardized we follow a standard data standards that are nationwide and established by the North American Association for central cancer registries so it's easily comparable to other states and it is not duplicated so we do have identifying information for all of the tumor registry data we we do know that this specific person had this specific cancer and if that person were to have a second cancer we would know that still the same person with their second cancer and be able to track that so it is not duplicated and here is my contact information if you have any questions about cancer statistics I would be happy to help you and again the tumor registry data and the hospital discharge data are available on our online query system which I'll go through at the end I also wanted to let you all know that there's a very good national resource for cancer statistics on the United States cancer statistics statistics website which is put together by the Centers for Disease Control and they have put together a nationwide data set that includes both registries in like Montana that are funded through CDC and also the seer program which is part of the National Cancer Institute and so it does have a complete 100% of the nation are at least 99 percent of the u.s. population is covered by it and you can get state-level statistics you can get national level statistics and it's all calculated in the same way so you know the statistics will be comparable go through the behavioral risk factor surveillance system it is a random digit dial telephone survey BRFSS is conducted nationwide but it's a state-based survey so it's designed specifically to do state level estimates it is conducted annually so actually it's conducted continuously the FSS question telephone surveys are always out in the field but we get a data set for each calendar year and it is acts adults about chronic conditions and health related behaviors so as a survey it has some strengths and limitations it's the only source for many chronic disease and payroll risk prevalence estimates because unlike cancer most chronic diseases don't have any sort of registry it does it is designed for state level estimates it is weighted to be representative of non institutionalized adults in Montana and also because it's a designed for a state level survey there are room to add questions to it that are specific to Montana so every state adds ask asks sorry a set of core questions that are consistent across all states and then each state also has the opportunity to add questions the limitations are direct estimates are not usually possible for County or smaller areas just because we're limited by sample size especially in the more rural counties it's not able to get enough sample size even with combining several years of data together it is a telephone survey so there are some populations that are missed it includes both cell phone and landline surveys but people that don't have either of those would not be included and also there's less representation for people that might live in like a group setting I think college dormitories are included now that they didn't use tune I think homes are not included that's why it's non-institutionalized adult and of course this is all self-report data so all the limitations that come with that so there are some small area estimation that is available using BRFSS data so you might have heard county level estimates of the prevalence of diabetes or obesity or physical inactivity or other things from County Health Rankings or other kind of sites like that and I just wanted to let you all know that for most of that kind of data where it's a county level estimate and it's either a behavior or chronic disease probably it's derived from small area estimation test amasian which is a probabilistic analysis and so they take the survey data and create a model that uses demographic information to predict the prevalence of certain conditions and then using the population data for that specific county they're able to use the model to derive the prevalence and so it's useful especially when you're talking about burden but not necessarily useful for like program evaluation and the Beerfest contact is helic open here's her information on that and then I also wanted to point you to the CDC website for BRFSS it's very useful I like it probably the best if you're going to just do state statewide estimates but if you want anything more specific to different regions in Montana or any sub state stuff you'll probably need to go to Ibis which I will go through at the end and then I wanted to talk a little bit about the youth risk behavior surveillance system which is sort of like the teenage version of BRFSS even though the Montana Department of Health and Human Services does not administer this survey it's actually administered by the Office of Public Instruction but it is a pretty important resource if you're interested in adolescent health or any sort of measures associated among that age group so it's a school-based survey of high school students it's done every two years and it asks about a lot of the similar behavior that that it's BRFSS s about but a lot more detail with Alcohol Tobacco and other drug use sexual behavior and nutrition physical activity injury and violence and as I mentioned that survey is run by the Office of Public Instruction and the coordinator is Susan Cort here is her information and you can also look up nationwide and state-level estimates from the CDC website that's listed here for YRBS and now the most important exciting part is how you actually get to all of these data sources aside from doing direct data requests to the contacts that I already gave you all that's always allowed but also we can go through the montana's indicator based information system which is a web-based query we call it Ibis not to be confused with the bird I didn't even know there was a bird named Ibis until we got this data system but if you google it you might get bird websites too and this is what the page looks like I'm going to switch over to the actual website in just a minute so montana ibis has multiple rules first of all it's a database query system which is what i'm going to focus on but it also it has indicator query system which where we put together indicator reports on a certain topic and then sort of put together these hand reports that have lots of different data sources all on one topic together and it also is the place where we are putting together our community health assessments for county level analysis of several different topics together and like I said it's all of the data sources that I went through already are available in the database query system we're always trying to add more and so hopefully there will be more in the future as we're going now I'm going to switch over to the website hold on just them there we go so this is what the website homepage looks like ibis mt gov this is really good I'm like I said I'm going to focus mostly on presenting the data queries but I encourage you to also look at these health topics that's where the indicator reports are publications is doesn't have a lot on there now but we will begin to fill that in as we start to put together this website more and then community profiles has indicator data for individual counties that we've put together right now let's look at the data