Thursday, October 27, 2011
Saturday, April 30, 2011
Sugar-Sweetened Beverages Tax and childhood obesity in US
Written by: Katherine Wang
Can tax on Sugar-sweetened beverage lower children’s weight?
Epidemiology behind the policy
I searched the Internet and found many papers regarding childhood obesity and consumption of sugar-sweetened beverages (SSBs). Growing epidemiologic studies were conducted to reveal the relationship between consuming SSBs (exposure) and childhood obesity (disease). Lots of researchers used epidemiologic method to design the study and draw a conclusion about SSBs and obesity.
Similarly, there are many researches targeted on this topic. In order to give you a summary of related study, I cite the study synopses here.
( http://www.yaleruddcenter.org/resources/upload/docs/what/policy/SSBtaxes/SSBStudiesChildhoodObesity8.09.pdf )
As the study synopses shown, most researches demonstrate significant association between SSBs consumption and childhood obesity.
Among those articles that indicated significant association, they built a connection between SSBs consumption and childhood obesity. Particularly, some studies revealed the casual relationship, which proved consuming SSBs could lead to children obesity. So, I used a brief picture below to show the main finding of these epidemic studies.
From tax to weight loss--- not that simple.
Let us think about our final goal. What we want to achieve by taking the policy? Yes, we want to decrease the obesity prevalence of children. And where do we start from? That is simple, just begin with raising tax of SSB.
Wow! It appears to be a very short distance between our start step and the goal. Next, I add more detail in this process. Ideally, raising tax on SSBs leads to decrease in SSBs consumption and lower calories intake, thus promote childhood obesity.
Let us check the second link, which is between decreasing SSBs consumption and less calories intake. Assume an obese boy who loves sweet things very much, when he notices the SSBs is expensive, what will he do? We hope he could buy milk instead or buy nothing, however, for many children, that would be too disappointing. Because he is not satisfied by the SSRs, he may seek other sweet things to get psychological balance. Perhaps, this boy will buy some cheap candies or chocolates to still his appetite. The result is, the calories contained in candies and chocolates are not less than SSBs. Thus, the calories intake will not be lowered.
I have seen similar study to test the influence of SSRs-control intervention among children. The study reveals such intervention could promote weight loss. However, we have to consider about the different settings between intervention program and daily life. In other words, children who successfully adhere to the diet rule of intervention may not able to control themselves in everyday life. It is necessary to examine the impact of policy in the life scene.
In general, we must make sure the links between components can be real, rather than imaginary. It is important to critically think about the effectiveness of public policy.
Some other ideas to promote the fitness of Children
In order to impulse people choose healthy food, decreasing the tax of vegetables and fruits may be helpful. When people are conscious of junk food tends to be more expensive and healthy food tends to be cheap, the chance of picking health food will be enhanced.
We could teach schoolchildren to make natural, healthy and tasty juice by themselves. Children may love healthy beverages if it brings fun. In addition, since parents’ decision can often influence children, parents’ participation may help children to build a healthy living habit.
References:
1.http://www.yaleruddcenter.org/resources/upload/docs/what/policy/SSBtaxes/SSBStudiesChildhoodObesity8.09.pdf2.http://www.ncbi.nlm.nih.gov/pubmed/11229668
Sunday, April 17, 2011
What are potential cultural and economic factors lead to high obesity prevalence rate in the United States?
According to the country rankings 2010 regarding global prevalence of adult obesity (http://www.allcountries.org/ranks/global_prevalence_of_adult_obesity.html ), in 2010, the United States had the 18th highest obesity prevalence rates among male and female adults. The total number of included country was 153 and the ranking of China was 136. We can see the adult obesity prevalence was much higher in the United States than in China. What are the reasons that lead to such big difference? Comparisons between various aspects in America and in China would be helpful to interpret obesity rates disparity between two countries. Besides significant genetic disparity, cultural and economic factors may also provide interesting explanations. For example, did the short lunch time (exposure) contribute to high obesity (disease; BMI≥30) rate in America? In China, the afternoon working schedule often starts from 1pm (in winter) or 2pm (in summer), so most people have 1.5-2.5 hour to have lunch and to have a rest. Sufficient lunch time allow people to eat healthy lunch in a relaxing way. While, in the United States, the lunch hour is relatively short. Oftentimes, people are pushed to finish the lunch rapidly in order to go back to office on time. The fast food, which contains high calories and fat, is favored by most Americans since it can save their time. Also, people may want to consume more calories at evening if they were dissatisfied with poor lunch. So, should we conduct a prospective cohort study to explore the link between lunch time and obesity? In this study, investigators can follow subjects with several years, and measure their lunch time and weight status. What about other possible factors besides the lunch time? Perhaps we can consider economic factors behind the fact. Let us think about the food market in China and in America. China is a low-income country and America is a high-income country, however, the food prices in these two countries are almost the same. This means most Chinese would have much concern about money when they purchase food, thus, Chinese may purchase less food than Americans do. Moreover, in China, vegetables and fruits are much cheaper and more available than meat and western fast food, so, Chinese may consume more vegetables and fruits to save more money. The food choice, which is closely related to weight status, could be driven by food market.
Reference:
1. http://www.allcountries.org/ranks/global_prevalence_of_adult_obesity.html
Friday, April 8, 2011
How does preference of clothing style affect your weight status?
Written by: Christine, Mary and Katherine
How does preference of clothing style affect your weight status?
Background
According to Healthy People 2020, reducing the prevalence of obesity is still a priority objective. [1] The increasing prevalence of obesity is a serious health-related problem, which could cause a lot of serious diseases, such as heart disease, stroke, diabetes, and cancers. [2] Especially, since these are all in the list of top ten leading causes of death in United States. [3] There is a recent study which shows how obese children like to wear loose-fit clothing. [4] There is also additional research that indicates that there is a link between wearing loose-fit clothing and eating disorders. [5] Based on those conclusions, we suspect wearing loose-fit clothing might also be a predictor of becoming overweight or obese. Therefore, we design a prospective cohort study to test the following hypothesis: is there an association between wearing loose-fit clothing and becoming overweight and/or obese.
Study Design
Study Design
In our study, the exposure is wearing loose-fit clothing and the disease is whether our sample becomes overweight or obese. We chose prospective cohort study design for our topic. Firstly, we will interview underweight or normal weight sample population by asking “Do you prefer to buy loose-fit clothing or tight-fit clothing?” The response options would be “loose-fit clothing”, “tight-fit clothing”, or “don’t know”. Then, we will divide our sample into three different groups based on our participants’ response. Later on, we plan to assess their weight status at every year follow-up assessment by calculating their Body Mass Index (BMI) and determining if they become overweight or obese. The duration of our first phase study will be 7 years. If we discover meaningful preliminary study results, we are planning to extend this study to the next 15 years. Figure 1 shows the process of this study design.
Figure 1. the process of the study design.
Methods
Study Population
This study interviewed 20,000 adolescents between the ages of 15-25. The participants were randomly selected in order to avoid selection bias. To be considered eligible all participants had to be between the ages of 15-25. However, participants were ineligible if they were already obese or overweight. In order to make our sample more representative of the population as a whole in Missouri, we randomly selected our target schools (Booker T Middle School, Standford Middle School, Academy Achievement Middle School, Center High School, RayPeck High School, and Central Senior High School) and students. Before the study commenced prior approval and consent was obtained from each participant’s parent if they were under the age of 18.The students’ medical records were obtained from the school nurse and based off of that data we predetermined if the student was eligible (i.e. underweight or normal weight). However, all students were weighed at the time of the interview and BMI measures were obtained. To reduce psychological harm and stress we conducted a blind study sharing only pertinent information with the participants about the study, as we did not want to inflict any type of harm or embarrassment on our participants. In order to maintain contact with our participants we updated their contact information every year.
The first interview was conducted in August 2003 as baseline. They were all proctored by trained health professionals. During the interview the participants were asked if they preferred to wear loose or tight fitting clothing. We also interviewed for age, gender, genetic disposition of obesity, lifestyle choices (i.e. did the individual live a sedentary lifestyle- little to no exercise; lightly active- light exercise 1-3 days per week; moderate lifestyle- 3-5 days per week; or very active lifestyle- 6-7 days per week) [6], eating habits, and socioeconomic status of parents. Based on their clothing preference, we grouped them into three groups: “loose-fit clothing”, “tight-fit clothing”, or “don’t know”. Each year the participants were interviewed to see if their preference of clothing style changed based on their increase, decrease, or consistency of weight. We followed the participants for 7 years.
Discussion
As mentioned previously, the purpose of this study is to determine if there is an association between adolescents’ preference of clothing style and weight status. We would like to determine if adolescents and/or young adults that wear loose fitting clothing, while they are underweight or at normal rate are more likely to be overweight or obese in the future. We think that people who wear loose fit clothing are less sensitive about their weight gain. Therefore, they are more likely to become overweight or obese because they cannot monitor their weight change. Additionally, individuals who wear loose clothes could be ashamed of their body and/or have low self-esteem. One common problem of people who usually undergo this behavior is eating disorders; where they tend to purge or starve themselves; they are also less likely to eat healthy and exercise, while often trying to find “comfort” in food. [7] In this case, those people are at higher risk of becoming overweight or obese. Thus, we feel that clothing preferences could predict if the individual will become overweight or obese. A hypothesis is appropriate for this type of study design since the study is prospective it is essential to know what will be measured and the purpose of the study. Then, we will feed a statistical model to test this hypothesis.
Challenges
This study may face several challenges:
1. Non-compliance: some participants may not feel comfortable discussing their clothing preferences, which could result in false information; and some parents may not want their children to participate in the study or pull their children out of the study, which could create follow up bias;
2. Bias in assessment of outcome: because we used BMI as the only measurement of their weight status it may not be a precise reflection of their body shape.
3. Information bias: since the responses of their clothing preferences were subjective, the categories were limited in that they only consisted of three choices.
4. Unmeasured confounders: if women become pregnant it may change their clothing preferences, stress, drug or alcohol abuse, side effects of medications, and social norm may influence eating behaviors (i.e. adolescents may mimic the eating habits of their peers, which could have an impact on their weight).
5. There may not be a direct association between weight gain and clothing preference.
Strengths
The first strength of this study is the big sample size. Our sample includes a big part of students in Missouri because the participants come from six different schools in urban and suburban areas of Missouri. The large sample could increase the accuracy of study result. Secondly, since the participants were selected randomly and the selection criterion is not strict, the potential selection bias was reduced to a lower level. Thirdly, the contact information of participants was updated every year to ensure that we maintained contact with our participants so that we could follow up with them in the future. Fourthly, the measurements of variables are easy to take and cost effective. Fifthly, because most people have a clear idea about their preference of clothing (loose fitting or tight fitting), the recall bias of this study is expected to be small. Finally, in this study, we conducted interviews to obtain the data. Those interviews are conducted by trained health professionals, which may reduce unclear and/or unanswered responses and increase the accuracy of data.
Weaknesses and impacts
First of all, the sample only comes from the state of Missouri. The conclusion of this study could not be generalized to the people who lived in other states because of potential differences between states. Secondly, the participants may give dishonest answers in this study since it is a self-report process. Thirdly, some unmeasured confounders may be involved in this study since there are various factors that can lead to overweight or obesity problems. It is also possible that the overweight or obesity is caused by the co-influence of various factors (e.g. poor diet and lack of physical exercise). Some potential unmeasured confounders are mentioned in the challenge session, such as stress, drug or alcohol abuse, side effects of medications, and social norm. Failing to consider these confounders could decrease the credibility of our research results. However, we use randomized selection for our sample population, which could rule out some potential unmeasured confounders by having them equally distributed in all groups. Fourthly, as mentioned in the challenge session above, higher BMI does not necessarily mean that an individual is overweight or obese. If the bigger portion of one’s body is mostly muscle, the weight would tend to be higher since muscle weighs more than fat. [8] However, the person may still be still in good shape. Thus, BMI may not be a very ideal measurement of obesity or overweightness. Fifthly, this study followed the sample for seven years. Thus, we may miss data during such a long period of time. For instance, some students might move to other states, and some may refuse to take part in the interview at various time points throughout the study. Besides loss of data, the accuracy of data should be considered. The students who were interviewed several times throughout the course of the study, may guess the possible objective of this study, and give some biased answers, intentionally. Thus, the credibility will be lower.
Self-reflection
Due to the increasing incidence rate of overweight and obesity among American youth and children, obesity has been a serious health issue threatening our next generation; we would like to study a potential factor of becoming overweight and/or obese in order to help with controlling youths’ weight status. Both overweight and obesity are mainly caused by lack of physical activities and poor diet. Besides these two factors, we pondered if there were any other factors that might also result in weight gain. To explore other factors of overweight and obese youth, we conduct this research to study whether peoples’ clothing preferences influence their weight gain.
In order to get strong causal association, we decided to track our sample population for 7 years starting with normal weight/underweight students. Therefore, our study is a prospective cohort study. And as a pilot study of this research, we will first focus on the students in Missouri. Because of the large number of total students in Missouri, we use randomized selection to choose our sample, which makes the study more general for the whole population of Missouri students. Also, in order to have valid association, we would test some potential confounders.
As we mentioned before, this is a pilot study, there are some limitations in our study design as following:
1. The sample:
We selected the sample only from six schools in Missouri; this may result in the limitation of the sample selection. We know the conclusion cannot be generalized to the entire American youth group. However, we want to study the Missouri students as a pilot study, as it would not be very expensive or time-consuming. If we targeted samples from different states worldwide, it would take a considerable amount of time, money, and resources to conduct such a study. So, we only used participants in Missouri.
2. Body Mass Index (BMI) :
In this study, we got access to the medical records in advance, and then, measured the BMI during the interview. It is possible that these two BMI values conflict with each other. For example, a student may be overweight in the medical record, but be normal during the interview. If this is the case, we would use the data collected in the interview process, because it would reflect the most recent weight status of the participants.
Although the BMI may not be the most accurate measurement of weight status, we choose this measurement because it provides weight status in a basic, cost effective form. Moreover, the health professionals checked the appearance of each participant to estimate whether he/she was overweight or obese. If the health professionals found that someone looked fit but had a high BMI, they would take note of this on the participant’s record.
3. Unmeasured confounders:
Although there are other involved confounders in this study, we only measure the key confounders. We do not want to measure too many confounders because it will increase the complexity of our interview. Some unmeasured confounders, such as the stress and side effect of medication, would make the interview last longer and could decrease the compliance of participants.
Also, having considered the health literacy level of our sample, we do not measure the variables that participants are unable to give clear answers to based on their knowledge.
4. Follow-up:
We follow the participants for seven years to obtain the data. This is a long period of time and can result in some problems regarding data collection. We design some strategies to reduce the chance of loss of data or nonresponse. To avoid the loss of data, we also record the contact information of participants and their relatives. If the participants move to another state, we will still stay in contact with them, if possible, through email. To increase the response rate, we gave rewards to participants, such as gift cards and coupons to various restaurants.
What will change?
In modern society, weight status is considered to be an increasingly important issue by the general population. Many people would like to try different methods of weight management. This study may provide a new way to control weight. If the clothing preference can significantly affect the weight status, many people may adjust their clothing preference in order to achieve or maintain ideal weight status. So, our study might influence lots of people to think about their clothing preference and make adjustments for the future. For the people who have weight problems, this study offers an interesting way to possibly help them.
Moreover, this study may change the social norms about weight management and clothing preference. In recent time, most people do not notice the association between clothing preference and weight issues. Given the information of this study, they may change their perspectives, because clothing preference is not only related to comfort and beauty, but could also relate to weight status.
Also, our study may have an impact on the clothing industry. For instance, if a manager of clothing company knew that wearing tight-fit clothes could help weight loss, this company could try to design more tight style clothes to cater to customers who intend to lose weight. It is possible smaller size clothing would become popular in the United States, like other countries such as Europe, China, and Japan.
References:
1. Healthy People 2020.
2. Overweight and Obesity: Health Consequences.
3. FastStats: Leading Causes of Death. http://www.cdc.gov/nchs/fastats/lcod.htm
4. Peter G. Kopelman, Ian D. Caterson, William H. Dietz, Kate Steinbeck. Chapter 29. Childhood Obesity: Consequences and Complications. Published Online:11 MAY 2010. DOI:10.1002/9781444307627.ch29.http://onlinelibrary.wiley.com/doi/10.1002/9781444307627.ch29/summary
5. Trautmann J, Worthy SL, Lokken KL. Body dissatisfaction, bulimic symptoms, and clothing practices among college women. J Psychol. 2007 Sep; 141(5):485-98. http://www.ncbi.nlm.nih.gov/pubmed/17933403
6. Life Span Fitness
7. Gordis, L. (2009). Epidemiology. Philadelphia, PA: Saunders
8. Centers for Disease Control and Prevention http://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/
Wednesday, March 2, 2011
Basic Knowledge About Study Design
Define:
Exposure: The exposure means the subjects were exposed to certain thing that we are interested in the given study. For example, if we want to investigate the reason of the food poisoning event occurred after a big party, we will collect the information about the food type people consumed during that party. In other words, the exposure in this case is eating or drinking the food.
Causality: In epidemiology, the causality is the association between exposure and disease. If the exposure results in the disease, they have the causality relationship.
Bias: Bias is an inclination to present or hold a partial perspective at the expense of (possibly equally valid) alternatives. Bias can come in many forms.
(This is the quotation from http://en.wikipedia.org/wiki/Bias.)
Cross-sectional study:
The cross-sectional study is used to determine the association between exposure and the disease or health-related characteristics among a interested population in a specific time. The hallmark of cross-sectional study is the snapshot, which means researchers collecting the data of exposure and disease simultaneously.
The cross-sectional study is best for quantifying the prevalence of disease (or health risk) and for quantifying the accuracy of a diagnostic test.
Strengths: The cross-sectional study is not expensive, easy to conduct and ethically safe.
Weaknesses: Only examine the association between variables, not causality.
The recall bias exist in this type of study.
The group size may vary.
Confounders may be unequally distributed.
Case-Control study:
The case-control study starts with identifying the case group and the control group. The case group are the individuals who have the certain disease or health outcome. By contrast, the control group are individuals who do not have the certain disease or health outcome. The control group should be appropriate to make sure the research accuracy. Afterword, we examine the exposure and non-exposure in case group and control group respectively. Based on these data, we can calculate the proportion of exposure and non-exposure in case and control group, thus, the conclusion about association between exposure and disease can be drawn.
Strengths: Quick and cheap, fewer subjects than cross-sectional study, only feasible method for rare disease and for the subjects who have long time interval between exposure and outcome.
Weaknesses: Recall bias, selection bias, difficulties in selection of control group, and the effect of confounders.
Cohort Study:
Compared with the case-control study, the cohort study begins with the exposure and non-exposure. Data were collect from the people who are exposed and not exposed, followed by obtaining the data about disease and non-disease in each group. The corhort study if best for the effect of predictive factors on disease.
Strengths: We can matching the subjects, can establish timing and directionality of events, ethically safe, we can standardise the eligibility criteria and outcome assessment.
Weaknesses: Difficulties in defining control group, binding is difficult, exposure may related to confounders that we do not know.
If we want to study the rare disease, the corhort study needs long time to follow up and large sample size.
References:
1.http://www.cebm.net/index.aspx?o=1039
Tuesday, March 1, 2011
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