Yes, we are back on obesity again, but how can we ignore it when it is only becoming worse and worse in this country. I recently read that 1/3 of all Americans born after the year 2000 will develop diabetes, especially type II diabetes, at some point in their lives (Manning, 2003)! Not only is diabetes devastating by itself, but it can also lead to vascular diseases and other complications of the kidneys and eyes. Diabetes is also a major cause of heart disease and limb amputation (Manning, 2003). I am all too well orientated with diabetes as it is rather prevalent on my mother’s side of the family. My grandfather suffered greatly, from both the pain and the duration of his diabetes, and it eventually took his life. In the last ten years of his life he became legally blind, losing his ability to do what he loved most, driving cars. He also lost the ability to liberally do his next favorite activity, eating…After all, he was Italian! During the last ten years of his life, he also lost the functioning of his kidneys, thereby requiring him to seek hours of dialysis every other day for the rest of his life…An activity which he truly hated…Finally, months before his death, his physician recommended amputating both of his legs below the knee, as he had lost almost all sensation in his lower legs….However, for the sake of my grandfather’s personal dignity, my grandmother demanded that he keep his legs….All this horror, but while his body was shutting down on him, he never lost his clear mind and psychological abilities…What a truly horrible way for a person to die….
This is one of the many reasons why I am a big believer in prevention. With obesity on the rise, this is going to lead to even greater numbers of diabetic Americans. So, if we want to promote the prevention of obesity in this country, where do we start? How about our children! Who has the greatest degree of responsibility in this manner? Their parents! Unfortunately, many parents out there don’t understand themselves how to maintain their health thereby preventing future health episodes. This is one of the many reasons why I am a great supporter of local public health agencies and the different programs that they host helping people learn about healthy eating and cooking strategies.
However, this blog isn’t about what parents need to do. Rather, I would like to talk about health policy in our schools. A major source of obesity in this country is the consumption of soft drinks. So, should schools ban the sale of soft drinks? It is an interesting question as California has already stepped to the plate and done this. In 2003, California banned the sale of soft drinks in all public elementary and middle schools. Later, in 2005, California banned the sale of soft drinks in all public high schools, while also passing legislation on the nutritional requirements of vending machine products and the amount of fruits and vegetables required in school meal planning (Daily News Central, 2005). According to Governor Arnold Schwarzenegger and officials, “over the past decade, Californians have gained 360 million pounds… obesity threatens to surpass tobacco as the leading cause of preventable death in California… it causes more than $20 billion in health-related costs each year” in California alone (Daily News Central, 2005).
So, do laws like these actually help? It’s hard to say, as researchers seem divided on the ban’s effectiveness. However, one thing is not being debated, and that’s the excess sugar and calories found in soft drinks and its relation to obesity. In fact, policy efforts to curb soft drink availability in schools has taken place in at least 30 different countries around the world, as obesity is becoming a world-wide pandemic (Hawkes, 2010). One of the reasons why policy makers are targeting soft drinks in schools is because school time is the one main time when children are away from parents making their own independent decisions, leaving them to the shrewd marketing techniques of the soft drink companies. In fact, it must be noted that soft drink companies have purposely been targeting schools because they have an easy and unprotected target in children, and because of this over 85% of American high schools have soft drink vending machines (Hawkes, 2010). So what’s stopping us from banning soft drinks in schools?
While there is clear evidence that soft drinks are nothing but empty calories and excessive sugar, studies have found soft drink bans in schools are not as effective as first thought. A recent cross-sectional study by Fernandes (2008) looked at the relationship between school bans on soft drinks and overall soft drink consumption by American fifth graders. Thus, in this study the exposure would be attending an elementary school that has banned soft drinks, while the disease or outcome would be the overall decrease in consumption of soft drinks. Over 10,000 fifth graders from 2,300 elementary schools were used for this study. The study found that of the over 10,000 fifth graders that attended an elementary that did not ban soft drinks, about 26% of them purchased and consumed soft drinks at school, with a significant percentage of those fifth graders being low-income and black, non-Hispanic individuals (Fernandes, 2008). Overall, the study found that by banning soft drinks in elementary schools, there was a significant reduction in soft drink consumption of only 4% (Fernandes, 2008). While this reduction in soft drink consumption is relatively low, this is only one study, and every study has its own limitations. For example, in this study, the fifth graders themselves were interviewed, along with the possible presence of recall bias. Fernandes (2008) also warns that the results of this study should not be applied to middle and high school students, as elementary students tend to have less free time and less pocket money relative to middle and high school students. Finally, Fernandes (2008) concluded that additional research is needed on this topic, and emphasized the importance of schools on the personal health of its students.
This policy debate is interesting to me because my high school banned the sale of soft drinks halfway through my years there. When I was younger, I used to love soft drinks, especially Dr. Pepper and Root Beer. Today, I am totally abstinent of soft drinks, with the only exception being sprite or 7-up when my stomach is upset. When they removed the soft drink vending machines from my high school, they replaced them with milk vending machines. These vending machines contained skimmed, 1%, 2%, chocolate and even strawberry milk products. Being someone who is lactose intolerant, I found this rather amusing. While I wasn’t offended of this change, in fact I was a supporter of it, I wished they had installed fruit juice vending machines also, since I couldn’t drink the milk. Nonetheless, in the end, I think it was a good move on the part of my high school.
Do you support schools banning the sale of soft drinks? Or is it a waste of time?
Daily News Central. (2005, September 16). Schwarzenegger Bans Soft Drinks in California High Schools. Daily News Central.
Fernandes, M. M. (2008). The Effect of Soft Drink Availability in Elementary Schools on Consumption. Journal of the AMERICAN DIETETIC ASSOCIATION, 108, 1445-1452.
Hawkes, C. (2010). The Worldwide Battle Against Soft Drinks in Schools. American Journal of Preventive Medicine, 38 (4), 457-461.
Manning, A. (2003, June 16). 1/3 of Americans Born in 2000 will get Diabetes- Type 2 Diabetes is on the Rise. USA TODAY.
According to the CDC, in 2009, obesity rates varied from a low in Colorado of 18.6%, to a high of 34.4% in Mississippi (Centers for Disease Control and Prevention, 2011). To make matters worse, obesity has been proven to contribute to heart disease, type II diabetes, stroke, and even some kinds of cancers. On top of that, heart disease, cancer and stroke are the top three killers of Americans. It is no mystery that America is overweight, and that this trend seems to be getting worse with each subsequent generation of Americans. To help combat this issue, and to make some profit along the way, different organizations have developed different dieting techniques. Some diets, like the Atkins Diet, promote the idea of a low-carbohydrate / high-protein diet, designed to burn fat cells quickly by essentially starving the body of its usual carbohydrate intake. On the other hand, other diets require you to buy only the food they create for you, such as Nutrisystem. However, once a person becomes involved and devoted to such diets, how long will she or he stick with their program? When will the excitement wear off? When will the energy to continue the diet become too great? What can we do as a society to change our overweight culture?
The truth is, diets change people’s lifestyles so drastically that they usually tend to be temporary. It is all too common to hear of someone losing a ton of weight and then six months later gaining it all back. Then how do we get Americans to lose weight permanently? We need to find a way to promote weight lose in a manner that is long-term. The changes to one’s lifestyle should happen gradually, so as to ensure long-term success, rather than a “big-bang” approach to dieting that throws a person into a drastically different lifestyle right away. An analogy would be someone trying to quit smoking. If the person decides to stop “cold-turkey” they may go into withdrawal much quicker and more intensively than had she or he gradually cut down on their smoking with the help of nicotine gum or patches. When you cut something out “cold-turkey” that used to be part of your daily routine, you are bound to fall back into that old, comfortable routine.
An interesting study that is being conducted in Minnesota addresses the maintenance of weight loss (Sherwood, et al., 2011). In this randomized clinical trial, researchers from the University of Minnesota and the HealthPartners Research Foundation allocated subjects either into a “guided” treatment group, or a “self-directed” control group, with 209 and 210 subjects respectively. Both groups, which each consisted of subjects who had lost at least 10% of their weight before joining the study, were then enrolled in two different weight loss maintenance interventions. Thus, for this study the exposure would be involvement in the “guided” treatment group, while the disease or outcome would be the maintenance of weight lose. Each intervention consisted of a weight-loss guidebook and log, and a series of phone calls with weight-loss coaches. Whereas the “self-directed” control group had limited access to their coaches, the “guided” treatment group had more extensive and frequent communication with their coaches via the “Keep It Off” program. In the “Keep It Off” program, participants had biweekly calls from their coaches, followed by monthly and then bimonthly phone calls for a total of 24 months. Activities of the “Keep It Off” program include: physical activity review, menu planning, relapse prevention, body image and weight goals, and group sessions while all being integrated with continuous communication with a coach by phone, email and their website (Sherwood, et al., 2011). Since the final version of this article is not yet published, the results cannot be confirmed at this time. Nonetheless, this study proves how important it is to look at dieting, as a component of weight loss, and how it needs to be transcended from a short-term activity to a long-term activity.
As someone who lost 48 lbs one and a half years ago, I know how important it is to keep the weight off once you lose it. It is very easy to fall into old habits because they are comforting and well known. However, I have made a pledge to myself that I would maintain my weight loss and continue my exercise routine as well as my improved eating habits. I am now to the point where I enjoy eating healthy foods. I try my best to keep my meals well-balanced, while avoiding sweets, creams, and soft drinks. In fact, it has been so long since I’ve had any sweets that I don’t crave them anymore. Nowadays, I never tell anyone that I am on a diet, because that sounds temporary to me, but rather I tell others that I made some permanent life changing decisions to improve my health…after all, my life depends upon it.
Centers for Disease Control and Prevention. (2011). U.S. Obesity Trends. Centers for Disease Control and Prevention, Department of Health and Human Services, Atlanta.
Sherwood, Crain, Martinson, Hayes, Anderson, Clausen, et al. (2011). Keep it off: A phone-based intervention for long-term weight-loss maintenance. Contemporary Clinical Trials , 10.
In almost every major American city, you can find a Starbucks or a Caribou Coffee shop on just about every street corner. In fact, coffee is the most popular drink in the world only after water, while its trade is worth more than US $10 billion (Butt & Sultan, 2011).
Given the popularity, we thought it would be interesting to examine whether coffee (or any kind of caffeine) has anything to contribute to our student lives. Being in grad school is a lot of work, so any kind of help is welcome 🙂
Therefore, in this case-control study, we are interested in whether the consumption of caffeine has a positive effect on the cognitive abilities of college students, measured in this study by the student’s GPA. We chose to do a case-control study for multiple reasons. We wanted to measure the amount of caffeine consumption to see how it relates to earning a GPA greater than or equal to 3.5. By interviewing graduating students and asking them to recall their caffeine consumption, we don’t have to follow them over a period of years, such as would be the case in a prospective cohort study, thereby eliminating the threat of attrition while saving money, since the study won’t take years to complete. Thus, our hypothesis is that high levels of caffeine bring about greater cognitive ability in college students, thereby reflected and measured in higher GPA scores. Our null hypothesis is that caffeine consumption has no effect on GPA. Such a hypothesis is biologically plausible as many academic articles site caffeine as a deterrent against cognitive declines (Butt & Sultan, 2011; Jarvis, 1993; Nehlig, 2010). Our study is important because if caffeine is found to improve student’s cognitive abilities, witnessed via their GPA scores, this then illuminates benefits of caffeine consumption, thereby promoting its consumption and availability on college campuses. This study is also important because it will spark additional studies around the country revolving around caffeine and its cognitive benefits, and applying it to other fields like worker productivity.
In our case-control study, we are defining case subjects as graduating students with a GPA greater than or equal to 3.5, and we are defining the control subjects as graduating students with a GPA less than 3.5. After starting with our case and control subjects, we will be looking retrospectively at whether these students consumed a great deal of caffeine or not. Therefore, we are defining exposure to high levels of caffeine as at least 1-6 servings per week of a caffeinated drink, while we are defining non-exposure to high levels of caffeine as 1-3 servings per month or less of a caffeinated drink. These stratified measures were developed by Chan, Wang and Holly (2009) from a 131-item food questionnaire obtained and validated by Harvard University.
Methods
For this case-control study, we will interview 500 graduate and undergraduate students. These 500 students will be made up of 100 from the University of Missouri – Columbia, 100 from the University of Washington – Seattle, 100 from the University of Alabama – Birmingham, 100 from the University of Connecticut, and 100 from Harvard University; this is designed to make the results of the study more applicable to the entire United States. The first 50 students from each school will be exclusively case subjects, and then later 50 controls will be selected via group matching and interviewed in the same manner. In this study, we will be group matching for the characteristics of: age, gender, race, BMI, and smoking. We will be conducting one-on-one sound-recorded interviews on all four campuses asking an array of questions that should take about thirty minutes per student, for a total of 250 hours of interviewing. Such an interview process will require a number of interviewees interviewing students simultaneously in different rooms. Each student will be compensated $20 for the thirty-minute interview.
The thirty-minute interview will encompass questions surrounding the students’ GPA scores and their typical behavior or lifestyle over the length of their undergraduate or graduate careers. Questions will specifically address the students’ sleep habits, study time, diet (amount of high-protein foods, high-fiber foods, sweetened foods etc.) credit hours per semester or quarter, major of study, exercise (aerobic and/or anaerobic), and use of other cognitive enhancers (such as Ritalin and Adderall), as we will be accounting for these possible cofounders in the analysis of our results. We will then ask the students about their GPA scores. Finally, we will ask the students about their specific consumption of caffeinated drinks.
With respect to the students’ consumption of caffeine, we will specifically ask them about regular coffee, black tea, green tea, energy drinks, hot cocoa, caffeinated soft drinks, and finally decaf-coffee, decaf/herbal tea and decaf soft drinks for comparison purposes. We will measure caffeine consumption via the number of servings, which will be stratified into the categories of 1 serving per month, 1-3 servings per month, 1-6 servings per week and greater than or equal to 1 serving per day. Again, these stratified measures were developed by Chan, Wang and Holly (2009) from a 131-item food questionnaire obtained and validated by Harvard University. With this information we will be able to determine whether each case and control has had exposure to high levels of caffeine. Furthermore, we will be able to calculate an odds ratio, which will tell us the odds that a case was exposed relative to the odds that a control was exposed. Again, case subjects have GPA scores greater than or equal to 3.5, and exposure is defined in this study as consuming at least 1-6 servings of a caffeinated drink per week (please see the excel template for our layout).
Via our odds ratio calculations, we will be able to determine the strength of the association between the “exposure” and the “disease.” In this case, if the odds ratio is greater than one, with the 95% confidence level consisting of values above the value of one, then we can infer a causal association and determine its strength.
Dose-Response Association
Via comparing the amount of caffeine consumption and the students’ GPA scores, we may be able to determine a dose-response relationship.
Coffee has been proven to enhance cognitive performance in a dose-response relationship (Jarvis, 1993).
Biologic Plausibility
Caffeine is well known to enhance concentration and alertness (Nehlig, 2010), which may hence directly or indirectly enhance cognitive abilities.
Caffeine and its metabolites have been proven to enhance human cognitive functionality (Butt & Sultan, 2011).
Challenges and Limitations
There are several challenges we expect – some are the nature of the case-control study and some are more specific to our approach and topic. First of all, how will we account for different concentrations of caffeine in all those drinks? Some are standardized (soda drinks, coffee from coffee-shops like Starbucks, etc.), but many people make their own coffee. And some people also add sugar (and different amounts of it), which is another stimulant.
Going further with this, will people remember how much of each drink they consumed? And how high the caffeine levels were in their home-made coffees and how much sugar they added? These issues, known as recall bias, are one of the characteristic weaknesses of case-control studies.
The next set of issues will come from what is known as selection bias. We have decided to spread the research and include universities from various parts of the USA to minimize the effect of the geographical area, but the question remains – can we generalize our results and say they are valid for all universities? We have decided to include Harvard because it is one of the best universities in the world. It will be interesting to see what kind of caffeine consumption they have and whether that has anything to do with their outstanding results. However, a broader study (including more colleges, like community colleges, and even high schools) might improve our understanding of whether there is a connection between caffeine consumption and attending college in the first place.
Continuing with selection bias issues, we have to be careful when selecting people for the interview. We might get a sample that is not representative of that particular university. For example, if people who agree to participate have something in common (for example, an interest in research, such as the one we are doing with this study), we might end up with a higher GPA sample. Or maybe the people who refuse to participate have something significant in common… These issues can be called non-response bias and we should keep them in mind when selecting our cases. Controls are going to be matched to the cases anyway; however this will bring some more problems into the picture. Namely, the factors we choose for matching the groups cannot be accounted for in the analysis (because we will artificially establish proportions that will be equal between cases and controls).
There are some other issues we see that could potentially affect the validity of our study. What are the risks connected with high caffeine consumption? There are known health risks (for example cardiovascular issues), but what about developing tolerance? This might lead to even higher caffeine consumption, which then disrupts the sleeping pattern and can lead to a decrease in cognitive performance. There might be other issues, such as combining caffeine with other cognitive enhancers, or even medications. And then is a whole set of issues connected to differences in culture and socio-economic status. Not only do these differences account for different caffeine consumption (quantity and quality), but they introduce other behavioral differences and we cannot control for everything.
And last, but not least, where will we get the money for our research? If we interview 500 students and give $20 each, that is $10,000 already (and we do not even get paid ourselves…)! Coffee companies (Starbucks, Caribou, etc) might be interested in sponsoring this, however this will introduce another possible bias – will this stimulate us to find a positive connection between caffeine consumption and GPA? This is definitely worth considering.
Designing a study is tough! There are so many different things to think about that it can become overwhelming. After we had decided on what we wanted to study, we had to agree on a study design. Each type of study has its own set of upsides and downsides, so we really had to sit down and decide which downsides we could live with and which upsides were the most important for our results. We had originally decided on a prospective cohort study, but this proved to be a less than optimal option. If this type of study was to be undertaken, we would have to follow participants for some time. This could affect the use of caffeine for participants, which we didn’t want. Another difficulty with cohort studies (both retrospective and prospective) is that we start with the exposure and participants are separated by this. We decided that this would be difficult considering the varying amounts of exposure (caffeine consumption). An intervention study would provide stronger evidence, but is probably unethical to make people drink coffee. So, we finally decided on a case-control study. While it lacks some of the strengths of other studies (temporality, lower recall bias, etc.), we decided a case-control study would be the most manageable study to perform. Another problem we came across was how detailed to go with GPA. Should we have just two GPA groups or more than two GPA groups? What GPA should be the cutoff for the GPA groups? We finally decided that to keep it simple and easier to analyze we would use just two groups. Thinking of all the possibly confounders was also difficult (we obviously didn’t think of all of them), and there were many challenges and limitations to address (discussed earlier). Overall, we realized that designing a study to accurately portray what the researchers are looking for (without too much outside interference) is really difficult, and some sacrifices and tradeoffs have to be made.
So What?
Why is this study worth doing and what could come from positive results? Well, let’s just assume that there is a correlation between caffeine consumption and GPA. For one, this will lead to increased research on caffeine’s affect on cognitive abilities. We understand the limitations of our study and that causation cannot be proven from just our study, but if positive results are found perhaps causation will be found in a later study. Looking at this from a limited prospective, we could maybe eventually say that caffeine helps students more efficiently learn and therefore increase their GPA’s. From a broader prospective, we may one day be able to say that caffeine helps people in general work and learn more effectively. This of course would likely have many effects, some unwanted. Companies may encourage caffeine use without thinking about the additional effects on people cause by other factors (what type of caffeine, amount, etc.). Companies producing sodas or similar products high in caffeine may market themselves as “good for the mind,” even though they could have other negative health effects. With obesity being a major issue, promoting sodas as “good for you” may not be something we as a country would want. However, there could be positive results as well. Students and other individuals could use caffeine to help themselves become better in the classroom and better in the workplace. Caffeine could also be used as a safer option than other, illegal options that some students use for help in school (i.e. Ritalin, Adderall). At this juncture, it is difficult to say what kinds of changes could occur with a discovery of a positive correlation between caffeine and GPA, but it may lead to further studies that could benefit students and workers (and yes, possibly companies selling caffeine products) in their professional lives.
Butt, M., & Sultan, M. (2011). Coffee and Its Consumption: Benefits and Risks. Critical reviews in food science and nutrition, 51 (4), 363-373.
Chan, J., Wang, F., & Holly, E. (2009). Sweets, Sweetened Beverages, and Risk of Pancreatic Cancer in a Large Population-Based Case-Control Study. Cancer Causes Control, 20, 835-846.
That’s right folks, it is time to fiber up! Take up those whole grain cereals and those bran muffins, and be proud to be regular!
In all seriousness, dietary fiber, or edible parts of plants or analogous carbohydrates that are resistant to digestion and absorption in the human small intestine (Park, Subar, Hollenbeck, & Schatzkin, 2011, p. 1), has been proven to provide countless benefits to the human body. According to the Mayo Clinic (2009), dietary fiber has the following benefits:
Normalizes bowel movement (in the words of my father: “Keeps you regular!”)
Maintains bowel integrity and health
Lowers blood cholesterol levels
Helps control blood sugar levels
Assists in weight loss
Lowers the chance of colorectal cancer (studies on this are mixed however)
A recent study was released (2/14/2011) by the Archives of Internal Medicine titled Dietary Fiber Intake and Mortality in the NIH-AARP Diet and Health Study, as to the health benefits of dietary fiber intake (Park, Subar, Hollenbeck, & Schatzkin, 2011). More precisely, the article demonstrates an inverse association between dietary fiber intake and mortality, especially with respect to cardiovascular, infectious, and respiratory diseases. The New York Times then made the article public (2/21/2011) by summarizing the article in the Health section of their newspaper. The New York Times article was titled Diet: High Fiber to Combat Death and Disease (Rabin, 2011).
The study conducted was a prospective cohort study. We know this because the researchers started with individuals that were categorized as being either exposed (consumes a high amount of dietary fiber) or non-exposed (consumes a low amount of dietary fiber), and thus our independent variables, in order to determine the dependent variable, or the disease, which in this case is mortality.
(Image Removed)
To the left is a diagram outlining the logic behind a prospective cohort study design. As mentioned before, exposed in this study indicates high dietary fiber, non-exposed indicates low dietary fiber, disease indicates death, and no disease indicates vitality.
This specific cohort study was set up by sending mailed questionnaires to 567,169 AARP members aged 50 to 71 years of age between 1995 and 1996. The mailed questionnaires were self-administered 124-item food-frequency questionnaires, or what are known as FFQs. Participants were each asked to record their usual consumption and portion size over the past 12 months. After numerous participants were excluded from the study (mostly due to the presence of chronic diseases, which were thought to be potential risk factors), the cohort study contained a total of 219,123 men and 168,999 women. During a total of nine years of follow-up (until 12/31/2005), there were 20,126 deaths in men and 11,330 deaths in women. Person-years were used to quantify the total follow-up time, which was calculated from the baseline questionnaire until death or the end of that specific individual’s follow-up time, for a combined 100,000 person-years for the entire study.
With this design and set-up, there are already a number of issues that need to be addressed. Usually with a cohort study, there are a number of subjects who drop out of the study, whether it is simply quitting the study or dying. We do know the number of individuals that died, as it is directly a part of the study itself, we however are not given the exact number of subjects who quit the study and were not included in the entire nine years of follow-up. Therefore, we are unable to determine the percentage of attrition. Next, questionnaires of this nature can be potentially troublesome. Depending on how each question is worded, each question could be interpreted differently from person to person. Additionally, there are issues with reporting biases. A bias by definition is “any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the risk of a disease” (Gordis, 2009, p. 247). In this case, a reporting bias is when “a subject may be reluctant to report an exposure (or non-exposure in this study) he is aware of because of attitudes, beliefs, and perceptions” (Gordis, 2009, p. 250). Also, the fact that subjects were required to recall their average fiber intake over the last 12 months may be troublesome, as some people become forgetful of such matters, which only gets worse with age.
There is also a form of information bias that is present here as a result of the long questionnaire (124 items) that may result in survey fatigue. Information bias is “when the means for obtaining information about the subjects in the study are inadequate (too long) so that as a result some of the information gathered regarding exposures is incorrect” (Gordis, 2009, p. 249). Finally, only AARP members were used in the study, which in itself may provide a source of bias. AARP is a nonpartisan, nonprofit, organization that lobbies on behalf of the interests of its members, all of whom are age 50 and over. Thus, members of AARP may on average be more educated, and may be more aware of current events and research surrounding individuals of their age group, including the many benefits of a healthy lifestyle (all relative to the general population).
An additional bias that is common with cohort studies is bias in assessment of the outcomes (Gordis, 2009, p. 174). This form of bias, however, is not a problem in this study, because since researchers have preconceptions as to what they believe the results to be, based on their hypothesis, they may be biased in their interpretation of the diagnosis of a disease. But, in this study, the outcome is death, and dead is dead….not much argument there…we hope. On the other hand, since researchers do indeed have preconceptions about the results, there will always be some degree of analytic bias, which results in the “unintentional introduction of their biases into their data analyses and into their interpretation” (Gordis, 2009, p. 174).
At this point, you may be thinking to yourself: “Wow, this guy is really picky! How will any study measure up to his expectations!” Yes, I am being critical here, but the truth is no study is perfect, and every study is bound to have flaws. This doesn’t mean that we have to throw the study out, but we do need to be aware of the biases that are possible and present, as they help to determine the strength of the association being hypothesized in the study.
(Image Removed)
With a study such as this, involving dietary fiber and its association with mortality rates, there are many potential confounders that can affect the results. A confounder is an additional variable that may be different between the study groups thereby potentially resulting in a biased result. Put another way, it is possible that the effect of the exposure on the disease, which in our example would be the effect of dietary fiber on specific forms of mortality, is actually due to the effect of a confounder. A confounder could be age, sex, occupation, urbanization, etc. In order to control confounding, researchers will either stratify the results or adjust for specific confounder variables in a multivariate manner.
(Image Removed)
Above is table 1 from the original article. This table displays various selected characteristics of all the subjects used in the study that were later adjusted for to avoid the influence of them as confounders. First, men and women were stratified into two groups to avoid any gender biases in the data. Then, the amount of dietary fiber intake was stratified into quintiles based on the amount consumed. This “dose-response relationship” helps to establish an inverse association between dietary fiber intake and specific mortality rates. The median amount of dietary fiber consumption for the lowest quintile was 12.6 g/d (grams/day) for men and 10.8 g/d for women, while for the highest quintile was 29.4 g/d for men and 25.8 g/d for women. Things to notice in table 1 is that college and post-college, health status, physical status, alcohol consumption, smoking status and red meat intake all seem to correspond with the specific fiber quintiles, with better results moving hand-in-hand with increased fiber intake. This is why these variables are considered confounders. People who intake a lot of fiber are probably very health conscious, and thus probably smoke less, exercise more, etc.
(Image Removed)
In table 2, the authors show all five quintiles, for both men and women. Most of the information provided in this table is in the form of relative risks. Relative risk is the risk of developing the disease among exposed individuals relative to individuals not exposed. In our case, it would be the risk of death among those individuals with a relatively high intake of fiber relative to those with a relatively low intake of fiber. Relative risk is a powerful tool because it estimates the strength of an association between the disease and exposure. Next to all the relative risk calculations is an interval, this is the confidence interval, which at 95% tells us you can be 95% confident that the true value is within this range. In our case, if the lowest quintile is our “reference” or “base” to measure all the other risks with, the relative risk of 0.78 for the highest quintile would tell us those individuals had a 22% lower risk of total death relative to the lowest quintile individuals.
In fact, in general, if relative risk calculations are over one, this indicates that the risk of disease in greater in exposed individuals than in non-exposed individuals. If the relative risk is exactly one, this indicates that risk is equal between exposed and non-exposed individuals, and thus no association exists between the exposure and disease. In our case, the relative risk amounts are mostly under one, which indicates the risk of disease (death in our case) is lower in exposed individuals (high fiber) relative to non-exposed (low fiber), thereby indicating a possible protective quality of the exposure (high fiber). With this in mind, we can determine if the relative risk value is significant or not via studying the confidence interval. If the confidence interval contains one, then there is a possibility that the true relative risk is really one, and thus nullifying the association between exposure and disease.
Getting back to confounders, in order to control for age, the authors decided to first analyze relative risk calculations with the results age-adjusted. To adjust for age means to nullify age as a factor that differs between different quintiles. Next, the authors decided to adjust for multiple factors at once, via two different multivariate analyses. The first multivariate analysis, controls for numerous stratifications of smoking. The second multivariate analysis, controls for all the characteristics listed in table one. Then, the authors took the results from the second multivariate analysis and stratified it via smoking status and via BMI figures. Since the overall study is so large participant-wise, the stratifications didn’t hurt the power of the study. Power in a statistical sense means “the probability of obtaining a statistically significant p-value when the null hypothesis is truly false” (Machin, Campbell, & Walters, 2007, p. 109).
(Image Removed)
From table 2, we can see from the stratified analysis that the association was not changed and thus is equally as strong as the non-stratified results, thus indicating no significant interaction from smoking and BMI levels on the death rates relative to the already adjusted multivariate analyses.
(Image Removed)
(Image Removed)
From tables 3 and 4, we can see that for both men and women, the risk of death from cardiovascular, infectious, and respiratory diseases was lowered by greater fiber intake. Furthermore, we observe a similar association between fiber and cancer, but in this circumstance, the results for cancer deaths were only significant for men. On this note, the authors stated that the difference may be due to chance, and that further research would be necessary. For “deaths from accidents,” we would not expect fiber intake to reduce the risk of accidental death, and that is exactly what we see, as the p-values and confidence intervals indicate the relative risk calculations are insignificant statistically. Due to convention, p-values above 0.05 are considered insignificant. The p-value is the probability of obtaining the observed statistic, or one more extreme, given that the null hypothesis is true.
(Image Removed)
Finally, in the above figure, the authors compared the different types of fibers and their respective relative risk factors. The fibers compared were grains, fruits, vegetables, and beans. Grains appeared to have the greatest association with decreased risk of death for both men and women, while fruits and vegetables did not. Beans on the other hand, appeared to have an overall significant association with reduced risk of death for women, but not for men.
In the end, the authors were able to conclude that dietary fiber has the potential to reduce the risk of death from all causes, but especially from cardiovascular, infectious and respiratory diseases. With respect to the lower cardiovascular death risk, the authors credited fiber’s ability to “improve serum lipid levels, postprandial absorption and insulin resistance, and lower blood pressure” (Park, Subar, Hollenbeck, & Schatzkin, 2011, p. 5). With respect to the lower infectious and respiratory death risk, the authors credited fiber’s anti-inflammatory properties.
After a thorough analysis of this study, I think it was a very well-designed study. The sample size is in the hundreds of thousands, and the authors attempted to adjust for almost every important potential confounder. My only reservation with this, is the general confounder of a healthy lifestyle overall. People with a healthy lifestyle are more likely to consume large amounts of dietary fiber, and are more likely to live longer lives. Nonetheless, I think the study design was excellent and well thought out. The New York Times article, on the other hand, was not responsibly reported in my opinion. While the NYT article did summarize the main points accurately, the author failed to explain the details of why the results occurred. While the general public would probably not be able to appreciate the full scientific article without a statistical and epidemiological background, I still feel the NYT article is an insult to the real article and all the hard work that was put into it, in both money and time. After reading just the NYT article, I was not convinced at all, as it just read like any other random health article. However, after reading the scientific article, I am fully convinced of the benefits of dietary fiber.
I chose this article because I have a fondness for nutrition, especially fiber. After being educated thoroughly by my colorectal specialist as to the importance of fiber (and water) I have taken my fiber intake seriously. Also, in the last year and a half, I have lost over 40 pounds of weight due to a changed and improved lifestyle, but not a diet. Diets are temporary, lifestyle changes are permanent. I take this subject both seriously and personally. I had one grandfather die from diabetes, and another die from heart disease, so I take my personal lifestyle seriously now, as everyone should. Both nutrition and exercise are important to me, especially my dietary fiber intake. I only eat 100% whole wheat bread, I love beans, vegetables high in fiber like corn, peas and carrots, raisin bran cereal, and dried fruit. Thus, I think this article is really important, as fiber has multiple benefits as outlined in this blog post, and we all need to stop and think about what we are and are not putting into our bodies. From reading this article, I feel like I have grown in my love and interest for nutritional health, and its potential implications on future public policy. Thank you.
Machin, D., Campbell, M. J., & Walters, S. J. (2007). Medical Statistics: A Textbook for the Health Sciences (4th Edition ed.). England, UK: John Wiley & Sons.
Mayo Foundation for Medical Education and Research. (2009, November 19). Dietary fiber: Essential for a healthy diet. Retrieved February 28, 2011, from Mayo Clinic: http://www.mayoclinic.com/health/fiber/NU00033
Park, Y., Subar, A. F., Hollenbeck, A., & Schatzkin, A. (2011, February 14). Dietary Fiber Intake and Mortality in the NIH-AARP Diet and Health Study. Archives of Internal Medicine , 1-8.
Rabin, R. C. (2011, February 21). Diet: High Fiber to Combat Death and Disease. The New York Times , p. D6.
According to the World Health Organization (WHO), epidemiology can be defined as:
“The study of the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems” (WHO, 2011).
Overall, epidemiology has five main goals (Gordis, 2009, p. 3):
Identify the cause and risk factors behind a disease
Determine how widespread the disease is in a society
Analyze the natural history of a disease
Evaluate preventive measures, different forms of medical treatment, and types of health care delivery
To provide assistance and insight for composing public policy affecting health promotion and disease prevention
Before I started my studies in epidemiology, I simply thought it was concerned solely with diseases and their effects on populations. However, the study and profession of epidemiology reaches a much greater spectrum than this. As someone who is deeply interested and passionate about health policy, I was pleasantly surprised to discover the importance of epidemiology in shaping and influencing public policy. This fact makes the study incredibly important and powerful in the world of health care. In truth, epidemiology is all around us. From investigating food outbreaks, to determining the source of epidemic outbreaks, to ensuring that our drinking water is pure and free of pathogens, to distributing and promoting different forms of prevention, such as vaccination campaigns (see H1N1 Flu Outbreak of 2009 below), epidemiology is everywhere keeping us safe.
Being such an important aspect of the broader specialty of public health, epidemiology has done more to extend the average human life expectancy and improve human life quality overall than any single cure or treatment. As someone who is passionate about health policy, one area that I am particularly fond of is preventive medicine and practices. Epidemiology is very involved with preventive medicine, as its scientists are always looking for ways to make preventive care smarter and more efficient by using empirical evidence gathered throughout communities, states, or even countries. After all, as Hippocrates, the father of medicine, once stated:
“It is always better to prevent a disease than it is to cure one.”
This image displays the top 10 leading causes of death in the USA from 1900 and 1997. Notice the large prevalence of infectious diseases in 1900 and the emergence of chronic diseases in recent years. This image demonstrates how the power of epidemiology has changed our world. Whereas infectious diseases are spread from the environment (such as a swimming pool in the early 20th century), thus allowing the agent (for instance Poliomyelitis, or the polio virus) to be spread either directly to the host (the person) or indirectly via a vector (for instance, a mosquito transmitting malaria). Chronic diseases on the other hand, are an entirely different type of problem. Many times they are a direct result of lifestyle, including a sedentary lifestyle, poor nutrition, excessive alcohol consumption and tobacco use (Department of Health and Human Services, 2010).
An example of preventive medicine via epidemiology from my (our) world:
The H1N1 Flu Outbreak of 2009
When the H1N1 flu outbreak took place in 2009, I was an undergraduate student at the University of Washington. At this time, I was also a part-time volunteer in the trauma surgery unit of the Harborview Medical Center in downtown Seattle. As people became concerned, as did I, it was soon discovered that there was a low supply of H1N1 vaccine available for the general public. With the supply low, this meant that the remaining vaccine had to be rationed intelligently, with the most susceptible individuals coming first.
Some of the first people to receive the vaccine were government employees, and I know this because I have a close friend in the FBI, and I remember her and her family being vaccinated before anyone else was at that time. I remember thinking that it was unfair that they had preference over the rest of us, but I soon realized that they were vaccinated first to protect and serve the rest of us if the flu outbreak got out of control.
Being both a college student and especially a hospital volunteer moved me up the priority list to receive the vaccination, which made me very happy. Being a volunteer always pays off, life has a funny way of rewarding us with good deeds sometimes. I am a huge believer in prevention, especially when it comes to the promotion of vaccination programs, and I am always eager to receive my flu shot as soon as it is available in the fall. Technically, from an epidemiologist’s point of view, I would be referring to solely primary prevention. In fact, there are three forms of prevention, all of which are essential to the promotion of health and the prevention of disease.
Primary Prevention: Preventing the initial development of a disease in an individual who is currently well (for instance vaccinations).
Secondary Prevention: Early detection of existing disease to reduce severity and complication (for instance mammograms).
Tertiary Prevention: Reducing the impact of the disease in individuals who have already been diagnosed with the respective disease (for instance rehabilitation services).
(Gordis, 2009, p. 6)
However, something that really upsets me is when individuals fail to get vaccinated due to ignorance and apathy. I have a friend who refuses to get the flu shot because he is convinced that it is a waste of time. He claims that the shot gives you the flu disease (which is impossible since the various versions of the virus within the vaccine are all inactivated or killed) and always references older relatives. First of all, if a person is having a bad reaction to the shot, it is probably because the person is allergic to the many chemicals in the vaccine, or the person is allergic to eggs, since the virus is grown in chicken eggs (a technique that hasn’t changed or been improved upon greatly since its inception). However, my friend just refuses to be responsible and get the vaccine, partly out of ignorance and stubbornness, and partly due to distrust of the medical community. Nonetheless, by obtaining the vaccine, he would be protecting both herself and others around her.
Granted, thanks to the phenomenon known as herd immunity, which states that as long as a large proportion of a community is immunized to a specific disease, the spread of that communicable disease should be minimized, and this should be enough to protect the community as a whole. However, I still think it is our responsibility as members of society to get vaccinated for both our and society’s sake (assuming that the person doesn’t have negative reactions to vaccinations).
Also, I am in favor of the recent Patient Protection and Affordable Care Act and its intention to make certain evidence-based preventive services, including vaccinations, free of charge under most new health insurance policies. To see more details on this click HERE.
What do you think about this? Are people being irresponsible socially and personally when they fail to get immunized? Any suggestions on how we as a nation can further promote the use and many benefits of vaccinations?
Department of Health and Human Services. (2010, July 7). Chronic Disease Prevention and Health Promotion. Retrieved February 9, 2011, from Centers for Disease Control and Prevention: http://www.cdc.gov/chronicdisease/overview/index.htm
Epidemiology...it's everywhere! 
