This blog was created with the intent of spreading informative, and hopefully at least somewhat interesting, information (I realize it is redundant to say informative information, but I couldn't think of another way to phrase it) about epidemiology and related subjects. Have a look and hopefully you learn something new and interesting!
Courtesy of http://www.ivygateblog.com/2010/11/columbia-mourns-departure-of-four-loko/
As you have probably picked up from my previous posts, epidemiology is a critical part of public health. One important area that epidemiology plays a role in is public policy. Epidemiological studies are important in public policy formulation because they serve as a scientific basis for making the decision, rather than just relying on arbitrary or unproven information. Obesity and its effects have been the focus of several recent epidemiological studies and public policy efforts (for example, requiring certain restaurants to display nutritional information). Cigarette smoking has also been studied extensively, and the results of these studies have led to such public policies as banning smoking in restaurants or even whole campuses.
Alcohol studies have resulted in many changes in public policies through the years. For example, after several studies in the 1970’s showed that lowered drinking age was associated with higher car crash rates, many states raised their minimum legal drinking age to 21. Here is a quick history of the legal drinking age in the United States, for those that are interested. Different policies have been enacted as more studies have been done. A recent example that some people may know about is the FDA ban of alcoholic drinks that also feature caffeine. Specifically, it was aimed at energy drink/alcohol combos such as Four Loko and Joose. The main argument in the ban was that caffeine component of the alcoholic drink masks the effects of the alcohol, causing people (specifically college students) to drink more than they usually do. Several high profile hospitalizations led to the increased attention on these drinks in particular, including one party in which 9 different people had to be rushed to the emergency room for alcohol related reasons. Here is a short video discussing the ban. I would have embedded that video, but CBS News forbids it and what they say goes.
So does the ban come with the backing of epidemiological studies? One of the most commonly cited studies was published by Wake Forest in 2008. The study examines the relationship between alcoholic energy drink use, high-risk drinking behavior, and alcohol-related consequences. The cross-sectional study found students who consumed alcoholic energy drinks had dramatically higher rates of serious alcohol-related consequences. They concluded, “Almost one-quarter of college student current drinkers reported mixing alcohol with energy drinks. These students are at increased risk for alcohol-related consequences, even after adjusting for the amount of alcohol consumed. Further research is necessary to understand this association and to develop targeted interventions to reduce risk.” It is important to note that the study found only associations and no causal relationships. They also admitted that the generalizability of the study was limited by several limitations.
Courtesy of http://www.ivygateblog.com/2010/11/columbia-mourns-departure-of-four-loko/
Another study by the University of Florida, published in 2010, studied associations between energy drink consumption, alcohol intoxication, and intention to drive a motor vehicle in patrons exiting bars at night. They found patrons who had consumed alcohol mixed with energy drinks were at a 3-fold increased risk of leaving a bar highly intoxicated as well as a 4-fold increased risk of intending to drive upon leaving the bar district. They concluded, “These event-level associations provide additional evidence that energy drink consumption by young adults at bars is a marker for elevated involvement in nighttime risk-taking behavior. Further field research is needed to develop sound regulatory policy on alcohol/energy drink sales practices of on-premise establishments.” Again you will notice that associations were found, not causation, and further study was needed before action should be taken in the regard to alcohol/caffeine related drinks.
Other than these two largely cited studies, there has been a lack of scientific focus on the subject. I don’t think anyone would argue that binge drinking has many negative effects on people, physically or otherwise, but does adding caffeine make these adverse effects worse? The studies done so far have done found associations, but they are far from conclusive. Even the authors of the studies admit that further studies need to be undertaken. Many questions remain unanswered. Does consuming these drinks cause the undesired consequence? Are the people who consume these drinks inherently more likely to involve in risky behavior? Just think of all the confounders that could be addressed: age, sex, race, education level, other drinks consumed, period over which drinks were consumed, other drugs consumed, actual alcohol/caffeine drink consumed, different drinking environments, etc, etc, etc.
Regardless, Four Loko and related drinks were banned in their caffeine-included form. Was there a need for further investigation before this move was made? Or was the available epidemiological evidence and the hospitalizations nationwide attributed to the drinks enough?
I don’t think I need to tell anyone that smoking cigarettes is bad for you. If you don’t realize this in an age where that message is shoved down everyone’s throats pretty consistently and the studies showing the negative impacts of smoking are produced by the boatload, I worry about you. Anyway, I want to talk about a specific type of cigarette: menthols. If you don’t know what a menthol cigarette is, here is a link to the menthol cigarette Wikipedia article:
Why do I care about menthol cigarettes in particular? Well, I got interested in the issue after reading this article. It discusses a federal panel finding that banning menthol cigarettes would benefit public health in the U.S. The main issues that distinguish menthols from regular cigarettes are the IDEAS that the lessened harshness of menthols makes it more attractive to youths and African-Americans, has led to increased use by these groups, and it is harder to quit smoking with menthols. However, the article discusses many confounding factors that could lead to these results (socioeconomic factors, genetic factors, etc.) instead of the menthol itself and raises the concern that there is a lack of evidence at this time linking menthol cigarettes to worse outcomes than regular cigarettes.
Courtesy of http://www.health.com/health/gallery/0,,20388015_8,00.html
Should menthol cigarettes be banned? Would a ban be because of the outcomes related to their use or the perceived effects they have on certain groups? Is there any evidence that menthols are worse for people physically than regular cigarettes? Should they just ban all cigarettes? Lots of questions with this issue. These questions should be addressed and more studies should be done before any decision is made in my opinion. But that’s why we have epidemiologists!
Here is an article from nytimes.com about a study done about the risks about radioactive iodine after the Chernobyl accident. The scariest part is that the exposure to the radioactive material wasn't direct , but through dairy products. The study reveals the exposure leads to increase chance of thyroid cancer. Interesting stuff, especially with what is going on with Japan right now. Hopefully Japan does a better job of protecting people from the potentially harmful effects of radiation.
The title might be a little misleading, but all those are a part of this article in some capacity. Studies are an important part of epidemiology, as you probably have noticed with all the articles based on studies that I have posted so far. Epidemiological studies test whether an exposure has an association with the development of disease (Gordis, 2009). After this, epidemiologists attempt to find whether or not the association is also causal. I'll define/describe some of these words so that makes more sense.
Exposure -think food, sunlight, cigarettes (anything a person can be exposed to) Disease - this includes actual diseases (lupus, cancer, etc.) and also many other outcomes (buying a car, lifting weights, etc.)* Association - some kind of relationship exists between exposure and disease, but it's unclear what that relationship is Causal - the exposure causes the disease
* I know that this is a little confusing but think of a study about whether smoking cigarettes makes a person lift more weights.
It is important to note the difference between association and causation. Just because a study finds an association between eating jelly beans and liver cancer does not mean that eating jelly beans will cause cancer (I just made that up by the way, so no need to be terrified of jelly beans). It is also important when reading an article to be critical of the findings, like whether they are saying an exposure is associated with a disease or if an exposure causes a disease. Big difference. News sites sometimes have a habit of leaving important details out or of making assumptions that the actual study may or may not support. Making bold headlines is a good way to attract viewers, but it is also a good way to send the wrong impression to readers. Take, for example, this article about a breastfeeding study and various headlines that were produced from it:
Can secondhand smoke make you CRAZY?!?!?!? The picture to the left was attached to the article. I love that caption too, which I kept exactly as it appeared in the article. A little sensationalized in my opinion. That's not to say there isn't some validity to the study (notice the epidemiologist who led the study making sure to say that the results do not prove causality), which you can investigate yourself if you wish. What should you look for if you want to know more about the validity of a study? Well I will investigate an article and the associated study and show some things to keep an eye out for.
Keeping on the smoking trend (there is never a shortage of smoking studies and related articles) I chose this article to look at. First, lets take a look at that headline: Study: Quitting smoking raises diabetes risk. If you just read that and are a smoker you might think to yourself, "Well to heck with quitting if it will give me diabetes." If you were a little more critical you might read on and find that the study authors emphasize that quitting benefits far outweigh those of continuing to smoke and the authors associate the increased risk to weight gain often attributed to quitting smoking. Now you might have a different mindset about the topic. Just reading the article is just where you should start to investigate the study. Before you make a life-changing decision to cut out jelly beans (or whatever the exposure is in the study), you should also look at the original study.
Here is a link to the study that the article we are looking at discussing. So lets get some of the basics out of the way.
What is the exposure? = Quiting Smoking What is the disease? = Type 2 diabetes mellitus What is the hypothesis that is being tested? = Smoking cessation increases diabetes risk in the short term, possibly owing to cessation-related weight gain. What kind of study is it? = Prospective cohort study Who was studied? = 10,892 middle-aged adults who initially did not have diabetes
How do you find the answers to these questions? Well luckily in this study they pretty much just lay it out. Some studies may not and you might have to do some reading to figure it out from the article. The exposure, disease, and hypothesis should be fairly easy to pick out. The kind of study might be more difficult to find if it isn't listed. In a cohort study "the investigator selects a group of exposed individuals and a group of nonexposed individuals and follows up both groups [note: can be more than two groups] to compare the incidence of disease" (Gordis, 2009, p. 167). In this case the exposed individuals are smokers who quit and the nonexposed are continuing smokers and individuals who have never smoked. It is prospective because the people studied were identified at the beginning and then assessed later (17 years in this case) to see if they had developed the disease. This differs from a retrospective cohort study which chooses individuals based on whether they have a disease or not and then the researchers look back in time (using past records like surveys, census, etc.) to see whether or not each group being compared has the exposure being tested (Gordis, 2009). So prospective = future, and retrospective = past. Another common type of study is a cross-sectional study which determines exposure rates in the groups being compared at a point in time. So cross-sectional study = present. (Note: There are other types of studies. I just used cross-sectional studies as a comparison to cohort studies.) Prospective cohort studies are good because they allow researchers to follow groups of individuals that they have selected over a period and time and see if an outcome occurs. This is important because it allows researchers to (possibly) determine whether a temporal relationship exists between an exposure and a disease. A temporal relationship means that the exposure preceded the disease. If a cross-sectional study (remember, one point in time) is done the researchers cannot determine if a temporal relationship exists and decide which came first, the exposure or the disease. Temporal relationships are an important part of supporting causation between an exposure and a disease. Prospective studies do have some downsides though. Participants in the study could drop out (or die) at any time during the experiment. There is also a higher chance that more confounding factors are involved.
Okay, lets take a second and discuss confounding factors. Confounding factors are other exposures that could have an association with the disease and thus makes it difficult to ascertain whether the exposure studied or confounding factors led to the outcome. For example in this study, age, race, sex, education, adiposity (huh?), physical activity, lipid levels, blood pressure, and location were all found to be possible confounding factors. These researchers accounted for these particular confounding factors by adjusting their numerical results. So in theory, these factors are not affecting the final results. The problem is that not all confounding factors can be accounted for, but a study that adjusted for as much as possible is preferable to one that doesn't account for confounding factors. Just keep in mind when reviewing studies that these confounding factors are out there and could be affecting the end result.
Back to the study. What should we really be looking for to assess whether what they say is true or not? The most important thing we look for is a valid statistical association. In other words, do the statistics support the hypothesis and can we say that the results can be applied to whole populations (white females, teenagers, Chinese men, etc.). I know statistics are boring to a lot of people, but they are important. This post is already long, so I won't go into details about how to interpret statistical results, because that could get very detailed. But it is important to realize that the results could just be due to chance, confounding factors, or bias on the part of the researchers in selecting study individuals or what data to collect. Some questions you might ask yourself when analyzing a study:
How did the researchers select the study participants?
How did the researchers measure the exposure and the disease?
Do the researchers discuss confounding factors and limitations of the study?
Can you see an apparent bias on the part of the researchers?
Who sponsored the study? (i.e. Are there conflicting interests?)
What assumptions do the researchers make?
Do the statistics support the researchers' conclusion? (Might need a background in statistics to really interpret this.)
Remember, be critical!
So after analyzing the the study, I came up with my own observations. I think that this was a well done study. They were very candid about the different confounding factors and limitations of the study. They make sure to say that there is an association between quitting smoking and development of diabetes, but they cannot prove a causal relationship. I would have liked them to mention that they found that the weight gain many smokers experience after quitting was a major factor in the title, so it doesn't seem like the act of quitting was necessarily at fault in developing diabetes. Same criticism with the news article. However, I think the article and study were responsibly reported and didn't try to sway readers in any way. They both did a very good job of explaining the risk of weight gain and diabetes and ways to alleviate this.All in all, I think this was a well done study that raised awareness of the dangers of weight gain (specifically for those who have recently quit smoking) and its impact on diabetes.
Should you be alarmed if you are a smoker and want to quit? There are a million studies out there trumpeting the benefits of quitting smoking (or even better never starting), so I wouldn't take this as a sign to not stop. To really help yourself avoid an increased risk of diabetes after quitting, the best advice would be to eat healthy and watch your diet.
Well, that's my spiel. I'll finish this post with a little entertainment.
First, an article about some silly experiments you might find amusing. Bad science is out there, so be careful to be critical of what you hear.
And second, Wilford Brimley! (Note: Not laughing at the disease diabetes, I just find this amusing and it somewhat relates to the study I have been talking about.)
I hope this has been another informative and and interesting post. Feel free to leave comments or ask questions. I will do my best with my admittedly limited knowledge to provide an adequate answer.
Oh and lastly, here is a list of sources that I used in this post:
Gordis, L. (2009). Epidemiology (Fourth Edition ed.). Philadelphia: Saunders Elsevier.
Corbis (2010). She's just trying to stay sane [Photograph] Retrieved from http://theweek.com/article/index/203843/can-secondhand-smoke-make-you-crazy
Not really, but this article discusses a research study that ties cell phone use to changes in the brain. It isn't certain yet whether these changes will have any meaningful impact on overall health. I personally hate talking on the phone, so I'm not too worried. Okay, here's the article:
Here is an interesting article about how allowing pets to sleep in bed with you can cause the spread of disease. Just something to think about, although I know most people won't be kicking Fido off the bed anytime soon.
This seems to be a good place to start. I'm guessing that many people don't know what epidemiology is or maybe haven't even heard of it. It is a surprisingly important part of all our lives, including my own, so I think it is important for people to have at least a simple understanding of what it is. I'll start with some book definitions of epidemiology. Epidemiology by Leon Gordis gives two definitions:
1. "The study of how disease is distributed in populations and the factors that influence or determine this distribution." - Gordis Leon: Epidemiology, 4th ed.Philadelphia, Saunders Elsevier, 2009
2. "The study of the distribution and determinants of health-related states or events in specified populations and the application of this study to control of health problems." - Last JM: A Dictionary of Epidemiology, 4th ed. New York, Oxford University Press, 2000.
You will notice some common language in the two definitions, which I have color-coded to make things a little easier. First, epidemiology deals with disease, or health-related states. Second, it is specific to certain populations, which can be defined in any number of ways.Third, it is concerned with how these diseases are distributed, or spread out, in that population. Finally, epidemiology is concerned with the determinants of the disease, or what factors led to the disease.
Still a little confused? Well basically epidemiology is about better understanding disease and using what we understand to prevent or limit these diseases. If my explanation is still a little weak (which is definitely possible) maybe some examples will help clear things up. How about you check out the Wikipedia link below. Just as a short preface, the link goes to the page about meningitis, which is a disease you may have heard of. If you frequent Wikipedia disease pages, you may have noticed an Epidemiology section. Read this section from the link and maybe that will help give you a better understanding.
Interesting stuff, huh? I may be a little biased (if that's the right word) towards meningitis because I was hospitalized with it a few years back (technically it was meningoenchephalitis.) Seems strange that having a disease would make it interesting to someone, but that seems to be the case. Had any strange diseases of your own? Mumps, measles, chicken pox, something else? Look them up. They all have an epidemiology section, or something closely related. You may also have noticed among all the numbers and statistics a familiar word: epidemic. I'm sure you have heard or used the word before, but do you you really know what an epidemic is? Epidemics are one of the many things that epidemiology is concerned with, and so I think it is important to define it and two related terms.
Epidemic - "The occurrence in a community or region of a group of illnesses of similar nature, clearly in excess of normal expectancy, and derived from a common or from a propagated source."- Gordis Leon: Epidemiology, 4th ed.Philadelphia, Saunders Elsevier, 2009
Endemic - "The habitual presence of a disease within a given geographic area."- Gordis Leon: Epidemiology, 4th ed.Philadelphia, Saunders Elsevier, 2009
Below is a link to an article addressing a disease the author purports to be all three of the above terms. It is of interest to me because I suffer from this disease (I know what you are thinking, "This guy is incredibly unhealthy.") It is hypertension or, more commonly, high blood pressure. It is a pretty interesting (and relatively short), so take a look if you have time.
Starting to see how epidemiology plays into everyday life? Looking to the news is another good example of this. Everyone remembers swine flu not too long ago, and before that SARS was all over televisions and newspapers across the world. These kinds of major news stories about worldwide disease outbreaks are what I would have considered to be epidemiology before I started the class I'm currently in. Although they definitely are part of it, there is much more to epidemiology than SARS. As a big New York Times reader, I've started to see more and more epidemiology related articles with a more clear view of what epidemiology actually entails.Below I have linked a few articles from the last week that are epidemiology related. The first article is about a recently deceased epidemiologist. The second is about how many rare diseases are popping up in New York City because of the diverse travelers common there. The third article is about reasons behind some of the lowered HIV rates in Zimbabwe. The last article addresses Bill Gates' new push to totally eradicate polio.
These are just a few of the articles dealing with epidemiology related news in the past week! I encourage readers to visit nytimes.com and find epidemiology related articles (or whatever else interests you), but I will also be posting epidemiology related articles I find interesting to the blog from time to time.
Well, I hope this has given you some idea of how wide-spread and important epidemiology is, and also just a basic idea of what it is. I personally find epidemiology and disease in general very interesting (and it is very relevant to a seemingly disease-ridden person like myself), and I hope that this blog will get others interested as well. I will finish this post with a video about meningitis, a very serious disease that would be even more serious without the work of epidemiologists.
