…beep beep….beep beep….beep beep…
My alarm is telling me that the morning has broken, that I should rise and shine, that I should not be lazy and stay in bed. I thus jump out of bed, and my two feet land on a balance which has been watching over me during my sleep for the past two years. Next, I stretch myself out, take a mountain pose, and slowly bow my head in order to see what my balance is telling me today. 67.8 kilograms. Well done Frankie! You gained 6 kilograms in the past 12 months.
To be honest, I did not really congratulate myself this morning after seeing my current weight. I did, however, think about the fact that exactly one year ago, my balance showed “61.5 kg”. That weight is not very high for a (young?) adult who is 182 centimeters tall, especially taking into account the 10+ hours a week I spent doing endurance sports last Summer. In that regard, my current 67.8 kilograms seem to be much healthier, and I actually would not mind hitting 70 kilograms somewhere in the coming two months.
But wait a minute, how did I reach those 61.5 kilograms?
Well, the COVID-19 crisis affected many lives including mine. Some people gained weight. Other people lost weight. And I did both. My weight before the first lockdown in March 2020 was around 67 kilograms, it had dropped to 65 kilograms by the beginning of June 2020, it dropped quite a bit further in the following four weeks, and it later on started increasing again leading to my current weight.
To zoom in a bit further, my first weight drop can be explained by a significant increase in sports activities (without changing my diet), as I could not do much more than sleeping, working, and exercising during the first lockdown. I did initially deny that I was losing weight, but I could not deny it anymore by the beginning of June 2020, and I soon realized that I needed to do something about it.
After giving it some thought, I reasoned that I needed to better tune my dietary intake to my sports activities, and I downloaded a food coach app to help me with that. This app was quite insightful, and I learned, for example, that my protein intake was way too low for someone who ran and cycled as much as I did. Unfortunately, I became a bit fixated on my caloric intake and decided that I could function well on a 2000-kilocalorie diet. And boy oh boy, how wrong could I be. Fortunately, my body quickly told me that I was on a road to nowhere, and with the help of family and friends I was able to take a timely exit from that road.
Why sharing this story? Well, first of all, I welcome openness with regard to unhealthy eating patterns, and any related stigma should be removed in my opinion. Secondly, I want to place my varying weight in an academic perspective, notably by making a case for the difficult but important work that epidemiologists are doing. Epidemiologists? You know, researchers like those we often see on the television who inform us about trends with regard to the COVID-19 pandemic.
To help me make this case, please imagine that 15 months ago, many researchers wanted to study the impact of the COVID-19 crisis on our fitness levels and lifestyle habits. Such researchers immediately started drafting ideas and protocols for corresponding studies, they requested regulatory approval for carrying out those studies, and they could, maybe, have recruited the first study participants in June 2020. These things take quite some time.
For an imaginative study on young males from the Netherlands who one day would like to own (at least) three donkeys, researchers asked the study participants to fill out all kinds of questionnaires, they performed some baseline measurements on, for example, body weight and height, and they would do the same exactly one year later for comparison purposes. Naturally, I would have voluntarily enrolled in this study, and basic measurements in my case would have shown a significant increase in weight between June 2020 and June 2021 while my height stayed the same. Based on this increase, one might say that my health took a turn for the worse in the past 12 months, especially when solely looking at the numbers and not taking into account that gaining weight was actually a good thing in my case. Here, a lot can thus be learned from my personal context.
Unfortunately, donkeys are popular these days among young males from the Netherlands thus leading to tens of thousands of study participants. Consequently, it is hard for this study’s researchers to take personal contexts into account. It is likely easier for them to hope that the impact of strange subjects like me, so-called ‘outliers’, on the study outcomes will be limited by focusing on general trends, like the average weight difference in the entire study population. Thereby, the researchers make a certain assumption to make their work feasible, but any assumption, of course, could theoretically lead to biased results.
The risk of getting biased results is something that is really hard to circumvent in the field of epidemiology, and epidemiologists accordingly end their research papers with a detailed paragraph on potential strengths and weaknesses of their work. They furthermore stress that their findings and conclusions should be interpreted with caution and that further research is needed.
Such further research is done quite often, also in case of our imaginative study. Specifically, researchers in many different countries carried out similar projects and published their research findings in scientific journals. As a result, it is now possible to combine the findings from all these different studies in a so-called ‘meta-analysis’ based on which conclusions can be drawn a bit more precisely.
Fun fact, outliers can also exist in meta-analyses, but these typically do not reflect individual subjects but individual studies. A possible example in this context could be an observation that the average weight of male donkey enthusiasts increased in ten countries, remained the same in five countries, and decreased in one country. This last country happened to be a country where the government gave every citizen a free treadmill and two kilograms of free fruit and vegetables per week. Clearly, such policy would make the corresponding study an outlier when similar policies do not apply to the other studied populations.
When stretching my imagination a bit further, what if the governments of the ten countries where weight increases were observed, had imposed additional taxes on fruit, vegetables, and sports clothing, while simultaneously removing taxes on fast food and soft drinks. Are we then really looking at the effects of the COVID-19 crisis or do we observe the effects of (idiotic) government policies? I would lean towards the last possible explanation in this hypothetical case.
To wrap it up, epidemiologist have the inspiring but challenging task to study the distribution and determinants of healthy and unhealthy conditions in specified populations, and they aim to apply these studies to (better) control health problems. And just like you and me, epidemiologists are not flawless, and they sometimes stumble upon biased results in spite of doing an excellent job. In this regard, it is important to remember that they are not working under laboratory-controlled conditions where each study participant lives in the exact same way with the exact same exposures. Instead, they are dealing with real-world populations and person-specific contexts which are difficult to control and standardize. And let us be thankful for that.
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