Step-by-Step Guide to Epidemiological Studies

Key Takeaways

Epidemiology in Obesity Research:

Epidemiology plays a critical role in evaluating strategies to prevent illness and manage diseases. Effective research begins with a well-defined question that is feasible, important, and contributes to the scientific landscape.

Study Design and Sampling Techniques:

Informed Consent and Data Collection:

Pilot Studies and Data Quality:

Beyond BMI in Obesity Research:

Next Steps and Future Research

• Enhance training for researchers on selecting appropriate study designs and sampling methods
• Promote the use of alternatives to BMI for more accurate assessments of adiposity and obesity. See the EASO Framework for the Diagnosis, Staging and Management of Obesity in Adults for more on this research area
• Investigate effective recruitment and retention strategies for large-scale studies
• Explore the integration of lifestyle and medical interventions in managing obesity
• Facilitate the development of standardised tools for consistent and reliable data collection

Transcripts are auto generated, if you spot an error, please email enquiries@easo.org

Hello everyone. Hello. Hi Peter, nice to see you all ECN Early Career Network members.

Let’s wait for a minute, everyone will join. And I would like to thank again everyone for joining another regular IASO Early Career Network e-learning hub. Today we have very interesting subjects which will be more interesting, especially interesting for those who are designed to enhance the skills and knowledge in epidemiological research.

This webinar will cover an introduction to epidemiology and its role in obesity research, an overview of the three main types of epidemiological studies, cross-sectional, cohort and case control studies, understanding of the benefits and limitations of each study type, practical examples of how to apply this method in the real world research and later on with great pleasure I will introduce our brilliant speaker, but still I would like to share some news. I would like to remind again that the Novo Nordisk Foundation has provided support to IASO for ECN development activities including this webinar series. The Novo Nordisk Foundation has had no influence over the content.

My name is Dr. Emily Dyatli, I’m ECN board member and also let me introduce my colleague who is together with me today, Dr. Lisa Heiji and together with Lisa we are going to share also some relevant links, information during the today’s speaker’s presentation and I would again kindly remind that today’s webinar is being recorded and the recording and any relevant links will be shared after the event. Also I would like to remind that eLearning Hub, this is online events and IASO ECN promote the knowledge sharing the skills development among the students or earlier career professionals interested in obesity. So please you are all welcome to join ECN.

Remember that ECN is free to join and also these webinars, we are doing these webinars every month. There is some apart from some breaks for summer and or winter and I will like to encourage all attendants to invite also your friends, your colleagues to join the ECN and some short rules about the webinar, we will have 40-45 minutes webinar with very valuable information and at the end last 15 minutes will be devoted to questions and answers. So you can give your questions in two ways, at the end you can raise your hand and switch your microphone on to ask the question but before all the period will kindly ask you to keep your microphones closed and you can also write to the chat your questions and I will handle all them to our speaker and before introducing our speaker I would like to hand over to my colleague Lisa Hagee to give some information about the news about the new projects that you can have in ECN.

Please Lisa. Thanks Emil. Hi everyone, thanks for joining.

I’m just going to quickly run through some of the opportunities available to IASO ECN members and that might be of interest to you. So our next in-person event is going to be the annual European Congress on Obesity and this year it’s held in Malaga, Spain. The date is the 11th to the 14th of 2025 obviously and the ECN activities will be held throughout the congress as well just as last year so we’ll have an ECN lounge so we do invite you to come along and say hello and then play some of the networking games and listen in to some of the professional interviews that are going to be run.

Abstracts, the first round of abstracts have now closed so congratulations if you have handed yours in. There was a record-breaking 1,000 abstracts submitted to the congress already but there is a late breaking deadline so if you would like to still submit an abstract you have until the 28th of February so just be prepared to meet that deadline if you would still like to come otherwise obviously you can still register as a delegate. At the congress we will have two specialist awards ceremonies one being the IASO Novo Nordisk Foundation New Investigator Awards where the four winners will present their research in the different areas so we have basic science, clinical research, childhood obesity and public health and those will be the winners from all of the applications so well done on handing your application in if you did and I’m looking forward to hearing the results.

We will also have the best thesis awards so this is for people who have completed their PhD and have handed in their thesis as part of an application to the award and the top applicants will be invited to ECO to present their research as part of a specialist session and the winner will be selected on the day so please do come along to those two sessions in the congress if you can and all of the ECN board members will be there and hosting and I’m sure they’ll be very pleased to see you. We also recently closed and informed the applicants for the ECN exchange programme and this is the very first year we’ve run it so we provide the opportunity for ECN members to visit specialist research centres for three to five days across Europe. If you did receive a place and there was only 10 and there was almost 60 applications so really well done and if you didn’t receive a place please don’t feel disheartened please just apply again next year because we want as many people as we can to have the opportunity to be in the exchange programme so please do keep applying.

That’s really it for now just keep an eye on the bulletin that kind of comes out with the webinar advertisements you’ll see different opportunities like PhD positions available across Europe and also the ECN spotlight where we interview different ECN members and learn about their research. I’ll hand back over to you Emil and thanks again for joining the session. Thank you Lisa and now with great pleasure I would like at last to introduce our speaker.

Please welcome Dr Sara Cushkieri, senior assistant, senior lecturer and researcher at the Faculty of Medicine and Surgery, University of Malta and adjunct assistant professor in the Department of Epidemiology and Biostatistics, Western University Canada. Dr Cushkieri, an expert in epidemiological study design will provide essential insights into conducting effective epidemiological studies. Please hand over to you, the stage is yours Dr Sara.

Thank you very much for your kind introduction. Hello everyone, thank you for joining us. So I’ve been asked to give a very brief step-by-step guide to epidemiological sciences obviously introduction so I won’t really have the time to go into much detail.

So this has been established I’m a medical doctor, my profession epidemiologist, two PhDs under my belt and as noted I have two appointments along with being vice president of the current disease section for the European Public Health Association. So the basic question is what is epidemiology? So for those who don’t have much of a background this is broadly defined as the study of a disease within a population. So epidemiology we’re not looking at an individual level but rather at the population so we can actually see that in epidemiology we are peeping into a health topic.

Now the health topic can be various from chronic diseases to communicable diseases to even undergoing surveillance outbreaks etc and one of the topics that falls under the realm of epidemiology is actually undergoing a study. The importance of epidemiology goes two ways. One is to evaluate strategies to prevent illness and the other is to manage patients who have a disease.

So epidemiology can be used in both scenarios however we cannot undergo any of these management or prevention without proper good epidemiological studies and the crux of any study is establishing a good research question. Without this you cannot proceed. Now a good research question is not you waking up one morning and say I feel like doing something let me do that.

That is not the correct way. In order to achieve a good research question it needs days and sometimes even months to come up with a good strategic question. Reason being it needs to be of importance, feasible to you and scientific literature and this needs to be backed up with literature review.

So in other words something that’s an example that I give my students is you can’t wake up again one morning and say I would like to know how many ants live on the moon. Okay is that feasible? I work with NASA maybe but you know on earth not really. Does it add anything to scientific landscape? Not much.

So you know that’s what I mean being feasible, important and scientific landscape. Now the other question is what if someone has already investigated this research question that I have? Can I proceed further? Well it all depends whether that individual actually has done it in the same locality, in the same characteristics of the population you would like to examine. That is where literature review comes to play because undergoing a very good literature review will back you whether it’s actually a niche or can you learn from someone else? Can you proceed? Once you’ve established this research question in other words what you like to study that will lead you to the study design.

Without a good research question you cannot establish what type of study you can carry out. So they do go hand in hand and that is the biggest hurdle when it comes in a way to designing a study because the proposed and will fall in place once those are well established. Now what are the study designs out there? So these are broadly divided into what you’re seeing on the screen into three descriptive, analytic and experimental.

Experimental among many there are random control trials which I will not be going over in this presentation. Reason being not many of us have the opportunity to be part of those but a descriptive and or analytic study design whatever level of academia or profession you are in you can actually undergo one of them or more across your academic career. So descriptive case studies, case series, descriptive surveys, ecological studies fall in under this category.

Now if we’re talking about publication point of view descriptive tends to get a lower importance when it comes to publishing but something always to keep in mind we do not undergo a study just to publish that is the wrong mentality. We undergo a study to enhance the scientific knowledge. So a descriptive study although might consider it not the most publishable it still can give a lot of quality to scientific community.

Case in point case study for those who are not familiar case study means that maybe you are a doctor or a healthcare professional and you’re taking care of a patient for example and you are taking care of this but you develop a very rare complication or actually has been with something unique and you feel that by giving this case this individual a platform of what happened can actually help other individuals across the world that might meet a similar case. Case series is a bit similar it can either be that you have access to x amount of individuals with a similar disease or similar condition and you would like obviously to relate the story as a case series or as you’re following someone up in time and that can be also a series. Descriptive surveys is you undergoing a questionnaire now I’ll be going into this more detail very soon but these kind of questionnaires all you’re getting is a descriptive result so basically knowledge, awareness, experience that kind of surveys.

Ecological studies in a very simplified manner is when you are investigating a subcategory of individuals and assessing a relation between an exposure and outcome so for example you are investigating a population living in a particular area in a country or with a particular socio-demographic characteristics. Analytic style designs is basically what I’ll be exploring in the next couple of minutes. You are going to have both a descriptive and a more analytic approach to these designs in other words you can undergo statistical analysis and your outcomes obviously will be a bit more robust because you’ve undergone x amount of analysis and statistical equations in a way.

These studies we can broadly put them down as case controls, cross-section and cohort studies. Now this timeline is to give you an idea of how these study designs actually relate to time and it all goes back to your research question so if you would like to investigate let’s say a health status at this point in time so a snapshot in one point in time then what you require is a cross-sectional study. However should you like to follow an individual up either in the future or go back in time then the study design that you require is a cohort study.

Let me just put you in the in the picture of a cohort study it starts with a cross-sectional study meaning a snapshot of what is right now and then you move forward in the future or in the past accordingly. A case control study as can be presented in this picture you’re starting from today and going in the past what is different here is that you’re going to have two different groups that you’re going to investigate. Lastly RCTs it’s an experimental study design there’s actually much more so that we could fall within this category of experimented and as you can see it starts today and it will follow up individual in time because there’s interventions involved.

Now let’s start off with a case control study we’re starting off today and today we’re going to define our study population into two groups. Now let’s take an example just to put you in the picture what we’re trying to achieve a hypothetical research question would be if having had COVID-19 infection leads to developing of type 2 diabetes. So our case our group that falls under the case are individuals with type 2 diabetes.

The control so the other group are actually individuals that do not have type 2 diabetes but it is important that the rest of the characteristics of individuals you’re going to investigate are similar. So in other words if within the case group so those who have diabetes in this example there are 50 males and 50 females between the ages for example between 50 and 60 years it is important that in the control you’re going to have 50 females 50 males between 50 and 60 and other characteristics should also as much as possible be the same so geographical location socioeconomic etc. So in other words you are actually investigating the case and the control meaning diabetes versus not.

The rest of the baseline should ideally be the same. Once that established then you’re going back in time so you’re going to explore for example in this case whether they had COVID-19 infection or not. You will notice that in each case and control there will be x amount of individuals who had been exposed to disease or to the risk factor whatever you are investigating and some that will not.

Once that established then you can move forward to undergo odds ratio. So this is a statistical analysis where you’re going to measure the strength of the link also named as relationship or association between the exposure and the outcome. May I kindly point out that this will give you a probability that there is a link between let’s say COVID and type 2 diabetes.

It will not be proven 100% that it is true that is only can be undergone with a cohort study risk factors identifying. Important when we’re doing this kind of statistics is to undergo confidence intervals to actually have a look at them know because if there are wide confidence there that relationship might not be as strong as you might wish even if the p-value the significance is there. Cross-sectional study.

So this type of study we’re starting off with your target population whatever it is could be the whole population of a country or a region or a hospital or whatever you are investigating and you’re going to take a sample out of them and I’ll be explaining sampling very briefly soon but you will not know what are their characteristics. So an example could be investigating a population x obesity status and their determinants. Once those individuals have been chosen this sampling technique as I said will be explained very soon then you start investigating them so you’re going to undergo maybe questionnaires or examination and start placing them in different groups.

Once that’s done you can as you can see the groups are very similar to the prior study design you can undergo case controls as well within the sub cohorts you are have established and so you can undergo odds ratios as well. What are the benefits of cross-sectional studies? Now I’m giving some more importance here because this is in a way easiest type of study that anyone can undergo whether you are undergrad postgrad level in your career. So first of all it’s relatively easy to conduct if you are strategic with how you go to collect data you can actually collect a lot of different variables which will obviously lead to a number of different outcomes and if we talk about you know as a site publication that also means you might actually have more publications but again it needs to be of scientific quality.

The crux of a cross-sectional is actually to have prevalences and I’m explaining how that is worked very soon as well as analytic analysis such as odds ratio which I just mentioned. It also gives a platform to undergo further research in a particular niche because you might uncover a particular topic or particular area that requires further investigation. As I said before also cross-sectional studies, springboard, cohort study should that be your global agenda.

So what is a prevalence? So prevalence is getting the frequency of a particular disease or a condition and this is worked out by taking the number of cases divided by the total population you’ve studied times 100 and that would be your prevalence. Now when you’re undergoing quite a large study you won’t be collecting data over one day so it will be your prevalence will be what’s called a period prevalence. So if your site takes let’s say a year to undergo it’s still a cross-sectional study because your sample, your total population obviously is what it is, your sample technique was done on day one for example and that hasn’t changed although you have x amount of individuals you need to contact you’re still undergoing a cross-sectional study.

So what you’re going to achieve eventually when you get your results is a period prevalence. If you are undergoing a very small study and maybe you’ve been managed to collect your data within a couple of days or a week then you will have a point prevalence. This is just to give you an idea of potential outcomes coming out from a cross-sectional study.

So this is taken from one of my studies and as you can see this was a national study so we were investigating the obesity status within Malta. So after this study we could classify the different individuals into the different BMI classifications and stratify by males and females and here you’re seeing the different prevalence at that point in time. Something that anyone who understands cross-sectional will be telling you is that we cannot analyze for casual relationships.

In other words what we can find during analysis is there is a relationship, there is a link between one aspect to another with an exposure and an outcome but we cannot say something leads to the other. That cannot be done through a cross-sectional study. We can understand a strength, a probability that there might be a link but not one leads to the other.

That requires a cohort study. Now some practical things to consider if you are thinking of doing a cross-sectional study although these also serve for other study designs with regards to participation, recruitment, data collection and follow-up. So the first thing you need to keep in mind when even designing your research question is who are you targeting? Who would you like to investigate? Is it the whole adult population? Kids maybe? Is it the whole country or particular region or a borough? Whatever is your target population.

At the same time you need to think well the inclusion and exclusion criteria because once you have established your study design and your protocol you can know to go back. So it’s important to have established who will be included and who’s not. For example if you are investigating the adiposity rates within a population it is not really suggestive that you include pregnant women because obviously they are increasing in weight not because of underlying adipose tissue but because there is a baby growing so obviously those should be excluded.

So this kind of inclusion and exclusion criteria should always be kept in mind. Next in line is to think how you’re going to sample your population. So how are you going to achieve the population you would like to investigate? Now it all boils down into do you have access to the whole population meaning let’s take an example if you would like to do a national study then you need to have access to the whole population that lives in that country.

So it could be either through a passport registry maybe or an electoral election list etc. If that is not accessible then probability sampling is not for you. There is non-probability sampling which might be more convenient for you.

Now just as a side note most of these samplings you will not be doing yourself you will be asking help from a statistician or as an epidemiologist to do this for you. However I will be explaining very briefly what each of these sampling is trying to achieve. So here let’s imagine we do have access to the total population that you would like to investigate.

Then comes the decision of how I’m going to pick up my sample population. Simple random sampling as the name implies it’s simple because you’re to put all that list into a software and will ask to randomly select for you x amount of individuals. The x amount will be achieved after using a sample calculator which is something which someone like a statistician will help you achieve.

Here I am just going to tell you you need sampling calculation. So that is sample random so literally randomly selecting let’s imagine hundreds of individuals as established by the sampling calculation. A systemic systematic sampling you are a bit more strategic in how you’re going to pick up your individuals because now you need to meet a research criteria.

Let’s imagine you would like to investigate just females so from this list of the whole population you need a sample just of females let’s imagine hundreds females. A stratified sampling you are adding more criteria to your sampling so let’s imagine you would like not just sampling by gender but also by age groups or by locality or maybe by occupation. So you’re going to get now a more stratified sampling is what you got so a more defined sampling.

A cluster sampling is you have your population this whole population is going to be clustered in a particular category for example ages or gender and then you’re going to sample from each of the different clusters that you have developed that is a sublime version of how these occur and as I said before these will require a sample calculation to understand the size the amount of people in other words that you required in order to get a representative study. Now if you don’t have access to these large datasets of individuals then it’s not the end of the world for you. You need to try to get sampling through another mode which is a non-probability sampling.

Here it is very important to keep in mind that you will not get a national representative or a regional representative sample so your study will not you can’t say it is representative of those individuals. It might be that you get a very good response and it will be similar you know you can say yeah you know with some probability it does reflect but you cannot say it reflects that you cannot do. So again here we’re seeing four examples so convenient sampling would be again after discussing the amount of individuals you require with an expert let’s imagine he or she will tell you listen you need 50 individuals living in that particular area.

So convenient sampling would occur let’s imagine you set up shop in the middle of the high street or in a prominent area and the first individual you see ask them to participate they obviously fall within the criteria that you have and as soon as you reach your 100th mark or 50 mark whatever it was then you stop and you say this is it that is my convenient sampling. When it comes to permissive sampling now you’re being a bit more strategic so again go to set up shop and say the first hundreds let’s say females that I come across and they accept I will obviously take them on board and I will stop. This is obviously a simplified version of what happens.

A quota sampling very similar but now you have a quota you need let’s say five percent being males ten being between particular age whatever your research question is. So here you’re putting a quota to the amount of individuals you need from your target population. Snowball sampling is a bit different so in this type of sampling technique you’re starting off with someone and you’re going to ask this someone to kindly disseminate your study this is mostly used on social media for example you have a survey have a questionnaire and you put a post on social media and ask your followers and your friends can you kindly share it for me and ask your friends and followers to also fill it in.

So this is called sampling because this means snowball sampling because it starts from one person and it’s there’s a ripple effect. Now what about recruitment methods? Some pointers. There are different methods how to recruit an individual again it all depends on what you’re trying to achieve from your research question it could be from clinics or hospitals could be online via email social media or community groups you know these all can be done through direct invitations. There you can even do advertisements on newspapers websites and public postings or else you can engage local organisations or community leaders to help you out.

Again, this depends on your research question so if you are to undergo a nationally representative study you cannot really play around that very perspective because the sample you get you need to stick to it but if you’re especially following the non-probability sampling then these are different recruitment methods that you can employ. What about data collection what you should keep in mind first of all we can broadly define different type of modality how to collect data into three interview surveys questionnaires health records and health examination health records is the easiest in a way out of them provided you get permission because accessing health records you require not just ethics but data protection as well as informed consent from the individual that you are going to access the on however as the name implies once you get the permission you’re going to go over those records and get the data that you require. When it comes to interview survey this is a bit more strategically planned out why because ideally what you’re going to ask the individuals so the questionnaire used what are called validated questions so these are questions that are already being used and tested that they will actually give you meaningful answers once they are used so a question should never be invented by your good self but rather that question should have undergone a process of validation to ensure that whoever answers that question will actually give you the type of outcome that you require.

There are a lot of different validated questionnaires out there, most of them are open access so you can use them provided you reference accordingly on different aspects of health and even beyond. Now sometimes you might come into a bit of a dilemma because you found x amount of questionnaires that you can use, but maybe you need to add one question just so you know. Ask a particular specific question – can I do that or not, if possible, and you can get away without using it. That is the best way, however sometimes we do use at least one question after being, you know, reviewed by different researchers to make sure that it does make sense, you know put it out there but with caution it shouldn’t really exceed a lot of questions. This we had unfortunately to do so especially in according excuse me during the pandemic. During the pandemic there was a matter of validated questions so we had to try to use what’s out there and maybe add a couple of questions which are specific to that question of line of questioning at the time.

Now when it comes to mode of dissemination again this depends on what you’re trying to achieve in my opinion and what I’ve used and tried to get even my students to actually do is undergo an interviewer-led questionnaire. Yes it is time-consuming it requires that an individual is across so face-to-face with the participant or with the patient but it will get the best results, out of all reason being you are asking the individual and even if he doesn’t understand that question you can explain up to a limit without influencing the individual you know with regards to the so there’s no prompting there you can’t kind of try to hint or try to help the individual. There’s a whole training process how to do you know proper interviewing but once that is established the information that you get is much more accurate than if you use post or email or telephone or social media. The reason being although the others are a bit more convenient even easier to conduct social media and emails the response you get you cannot be 100 percent sure that they are one accurate that all the questions have been answered correctly that the individual has have actually understood what you’re trying to ask, because they can’t ask you back although on telephone. This can be done but you know let’s be honest how many individuals would like to spend 30 minutes on the telephone trying to answer a questionnaire, not much. So you have to think about that having said all of this interview survey although it is you know a very good source to get information you cannot preclude that there are a number of biases that might affect your data one being that it is self-reported so individual even he or she have understood that question doesn’t mean that the answer is fully correct because an individual might feel uncomfortable telling you something even if you know you are in front of him or her so the answer might be a bit skewed or even and you might have forgotten something maybe his medical history or his drug consent might invent and you don’t have you know 100 accuracy when it comes to a survey kind of study.

In fact, one can say there are advantages, yes, because effect is it can maintain the anonymity because if you don’t ask any person questions you know no one will know what the background is etc and it is easier to do undergo data analysis. However disadvantages would be as I said the bias and subjectivity to the data that you get and if you’re not doing an interview led then obviously a clarification of any doubts in in the questions cannot really be satisfied and there can be low response rates, because you know, let’s be honest if you get an email undergoing you know please do the survey for me unless you really want to help or you like the the theme of that question most likely you will just ignore so that will be a low response rate. Unfortunately so having had said that the best type of study design in a way which to employ is health examination if your research question permits it.

So what is a health examination, so this means that you are going to undergo examination on the participant however it does mean that there’s going to be a lot of logistic and planning as well as training to whoever is carrying out the study. But let’s take an example, let’s imagine you would like to assess how many of in the community have type 2 diabetes or obesity or any other type of condition so that would be the aim you need to think how you’re going to equip your participant. Now it’s not just sending a letter or calling them or inviting them you know to undergo a survey but now you need to have a place where you’re going to you know be comfortable yourself and the participant to undergo an examination.

The examination can be you know from taking blood pressure to taking height, weight, waist circumference or even taking blood so that is things that you need to keep in mind not just to logistically you know plan this out but also where you’re going to have these kind of examinations be performed and how the results like the blood tests are going to work out within a particular timeline because once you take your blood you can’t really leave the blood there lying, it needs to be taken to the lab within a time period something else to always consider this is relevant for any type of study is how you’re going to input the data are you going to handwrite the data or you’re going to directly input on your laptop or tablet whatever you’re using. I mean all of them have their pro and cons obviously immediately inputting on a laptop is easier because it’s easier to translate to when you are analyzing but you need to make sure that errors are of minimum occurrence. In fact data quality control is extremely important whichever type of study design would like to carry out you need to make sure that the data you are collecting from the start of the study up to the end is you know the same so you need to constantly monitor how data is being collected whether it’s on the field or online and then the protocols that you’ve established on day one are adhered to throughout and if you’re especially undergoing any kind of data collection with individuals or you have other people helping you out it’s important that training is ongoing so interviewers even whoever is examining if that’s what you’re doing is the same you cannot have any variations because that will affect your outcome eventually.

Now when you come to data entry it is essential to double check for errors now if you have a written questionnaire for example and you’re inputting obviously there can be errors for inputting people you know we are humans, you can do any type of errors so it is worth to double check, you know take random questionnaires and double check with. Also online if you’re using online platform to input your your survey or even your data collected from the health examination part it’s important to ensure that you do automate the error check so you know if you are asking an individual about something and the responses are already set there so the interviewer just chooses the correct answer like another automatic check would be. If you’re doing let’s say age and the age was between 18 and 70 so an individual can only write the age between 8 and 70 so no one can do 700 for example you know with an added zero that kind of things.

Some tips pilot study it is extremely important especially if you’re undergoing a large study. Now you might be saying one what is a pilot study well this is basically a small study that test runs your method although you might have you know been reading your method you’ve passed it through a number of senior colleagues and they’re saying it reads well it should work well etc unless you test it out through a pilot study so you know test run it across very few participants doesn’t have to be thousands could be you know 15 individuals or 15 it depends on your total sample. It is essential because what works on paper doesn’t mean it will really work when you are on the field and from personal experience yeah when i had to do the study i was not so happy because it means that i’m going to waste time i’m going to waste participants because once a participant has taken part in a pilot study you can’t really use them in a way the correct term but you know you can’t use that data for your actual study that is you know just for pilot study and that’s it so in a way they are lost. However after the study i realized that although the method appeared to be you know functioning brilliantly the timings for appointments were too vast so we had a lot of waiting time you know which is not really sustainable and something else for example that we realized that appointments that were being set up randomly across the population that we needed to examine were not really efficient so the elderly individuals actually enjoy coming early whereas the more younger individuals wanted a later appointment and that we learned after the pilot study so you know when we actually started the big field work we gave the timing of the appointment strategically you know according to age because that is what appeared to have worked you know much more efficiently and indeed we had a very good response when we followed this strategy and again we wouldn’t have known it unless a pilot study had been done.

Something else that can help you is sending reminder emails calls or texts this is mostly when we’re talking about examination because individuals might tell you yes i’ll come on yes i accept your invitation but then close to the day they might forget or something comes up and you know it’s very important to remind an individual to come for the appointment and always be flexible don’t be rigid, so if you said yes this is the appointment time take it or leave it that will not work. You know if you need individuals and you need to accommodate them so it’s very important to be as flexible as possible place your examination your interview or whatever you’re doing in a convenient location, don’t expect people living in a remote area to travel x amount of kilometers unless you are going to offer them some transport. If not make it as easy for them to attend to help you out to achieve your study outcome as possible. Now as already stated i come from a very small country we are very you know everyone is very close by however still i went to each and every town in a local health center for every individual to be you know very convenient to come and do their health examination and study so it helps people will make will you know have more encouragement if all they need to do is walk a couple of blocks rather than take the bus or even go you know with other modes of transport.

Now when it comes to incentives you need to be careful not every ethical board will allow that you give incentives especially when it comes to financial incentives because there are a lot of ethical concerns you’re kind of buying individuals to take part etc however there’s always you need to check with your local scenario. However offering like a gift card or even if you’re doing a health examination what you’re doing is actually giving them a free health checkup it’s very important that what you find you give it to them because it’s theirs you know so their blood pressure readings etc and that will boost the participation rates so it’s very important to keep that in mind but make sure that you are ethically sound as well and the most important thing is never give up you know these things sometimes turn a bit south you know not everything goes according to plan however never give up and you can always obviously ask senior help to to actually give you a hand if need be now time is running.

So if anyone would like to read more about this this was a very very brief introduction to epidemiology actually written a whole book about this it’s a guideline if you are not certain about doing a phd or not another book which i’ve done i’ve written and if you think about successfully publishing again there’s something else. And last and not least if you are postdoc and you are into chronic disease epidemiology we are actually looking for fellows and with that i would like to thank you very much for your attention and if you have any questions obviously we have some time. Yeah dear dr Sarah thank you very much for the brilliant and very interesting presentation and i would like to use opportunity to read the questions we have get and now as an EASO especially also including ECN members we talk about that we are going in obesity diagnostic beyond BMI we should find the ways to go beyond BMI. So how do you address the limitations of BMI as a measure of adiposity in population-based studies? This is the first question so as you know this week there was actually a whole lancet paper which it was a consortium about this you know it’s a very interesting read and they actually you know we knew that BMI is off you know it’s but it’s been used over and over again because for epidemiological studies and they even say it themselves that it’s still in a way reliable however what we’ve done although we didn’t show it we used waist circumference and waist hip ratio to try as much as possible to understand the real obesity status from epidemiological point of view ideally and if you have the resources. We actually do an MRI because that will determine clinically even as well as epidemiologically the amount of adiposity however it all depends on the resources that you are in because we need to be realistic not everyone is financially capable to do you know an MRI however as pointed out also in in this recent publication if you use waist circumference or waist ratio it is much better than a BMI however when the study that I showed you was carried out the whole debate hadn’t really started but I agree with you the BMI shouldn’t to be the only metric we use because it’s definitely and I also would like to remind all participants that also last year EIASO also published a new framework the study where we also talk about this and now the Lancet also do something similar.

So another question, what are the key challenges in designing epidemiological studies to investigate obesity as a chronic disease, it’s also very important to chronic to highlight every time that it’s chronic relapsing deceit well and that is a very interesting and challenging question because this is a chicken and egg situation obviously comes first or did something else come you know develop first and then obviously comes in play so it’s very important that when you are designing your study try to go back in time meaning it ideally you have access to medical records if they’re available if weight and height and waist circumference has been available in most cases it’s not so you have to kind of depend on the history of the individual which again as we said it’s a self-report it might not be ideal so it’s highly difficult to say you know how to interpret. You need to set the protocol so your design protocol well are you going to consider you know examination from day one today and what happens so you’re going to get what are considered as healthy individuals and I know in inverted commas because you need to define healthy as well because is it healthy because the weight appears to be normal or did you undergo blood tests and physical examination to ensure that all the different metabolic characters are normal and then you move forward so ideally the answer that question would be a cohort study so you start with the more minigame inverted commas individuals and you move in time and then you can actually see if obviously it’s a chronic disease. If you’re starting from current today having someone have a high adiposity it will be a bit more difficult to determine if it’s the primary cause of a disease or not unless you do a lot of investigation or medical history etc. So thank you very much.

Now I have one technical question, personally I’m a medical doctor practitioner but here this will be more interesting regarding the subject reverse the question about reverse causality in longitudinal studies how do you manage reverse causation particularly when studying obesity related health outcomes and another question – do you have any examples in the area of this question owner the research RCT evidence indicates that sweetener intake has no effect on adiposity whereas longitudinal studies often indicate sweeteners are associated with adiposity increases. So let’s start with the last question – I’ve never went into the sweetener so I can’t really answer the question. I haven’t gone into any research of that so I’m not the right person to answer that with regards to reverse causality that is again a Pandora’s box as previous answer it’s very difficult to say what you know is affecting and what’s not ideally as I said before and it is very difficult to avoid all the aspects is to start from a let’s say and and a young age where there is no health conditions ideally and you see what’s going to happen because you know once a metabolic disease it is obesity or whatever the current zero investigating sets in it is very difficult to try to see you know was it the chicken or the egg that came first you know which is reverse causality etc. So the best way I find is to really be very specific when you start so put a definition of what you what is considered as the starting point and what you’re looking for but there is it there is no single way to tell you this is the right way to do so you know, it’s very difficult to do. In fact this is always a study limitation of any study that we do you know you can’t eliminate it but the best way is to define what you start with you know who’s your you know initial population what you’re really looking for and try your best you know taking a good amount of variables from from what you’re investigating and to try to compensate for that. It will be difficult it’s there’s no one-trip pony you know and I guess the time is running we will take one the last question so one of the challenge with epidemiology of obesity is that the general public as controls are hard to recruit without bias can you suggest any type and any tips or clues on this well you can’t really change individual and their and their opinion and their insight so that’s this number one but it’s very difficult to avoid bias let’s put it like so however if you are going to do a randomized stratified sampling so you’re going to choose an individual not based on their clinical you know characteristics or not if they have an obesity or any other current disease but rather on other stratifying like you know age gender living conditions or maybe occupation and then investigate them like equals then it is easier to kind of eliminate the the responses because if you are going to say I’m going to set up shop in a clinic that’s you know it’s an obesity clinic or another current disease clinic then the bias is going to be much higher so try to level the feed where your sample population by ensuring that what you’re searching for isn’t the kind of the key.

So we have you know different backgrounds basic but different metabolic background so you try to say compare okay so the response of someone to have a high bmi or a high waist circumference as against someone who isn’t is it similar yes or no because if they are similar then possibly it’s not their you know higher deposit is affecting whatever they are recalling or whatever you are searching for rather than you know having a concrete you know all of the individuals already prime that you’re asking them instead because they have a particular disease that obviously is going to bias the output so that would be think trying to level the playing field yet again it’s always certain limitations we cannot really control how individual and response they might tell okay it’s undergoing a metabolic study so I think she wants to hear this from me x y and z.

Um thank you very much dr Sara and I would like to remind again all  attendees to complete the feedback forms that appears after the webinar and stress your comments they are well-evaluated for us in order to support the development of future webinars. So please give us feedback and I would like to sum up again on behalf of all participants we thank you dr Sara for a time for being here. All participants you are also are invited to join our next monthly webinars, please feel free to share the links to invite all your friends and other scientists who want to join ECN. I want to remind that ECN is for free so join us and be close for obesity subject in professional manner. Thank you very much Lisa, do you want to add something? That was perfect, just thank you everyone for attending and thanks very much Sara for sharing with us. Thank you very much. Thank you everyone. Bye bye see you, thank you.