thesis statement junk food

Module: Academic Argument

Argumentative thesis statements.

Below are some of the key features of an argumentative thesis statement.

An argumentative thesis is . . .

An argumentative thesis must make a claim about which reasonable people can disagree. Statements of fact or areas of general agreement cannot be argumentative theses because few people disagree about them.

Junk food is bad for your health is not a debatable thesis. Most people would agree that junk food is bad for your health.

Because junk food is bad for your health, the size of sodas offered at fast-food restaurants should be regulated by the federal government is a debatable thesis.  Reasonable people could agree or disagree with the statement.

An argumentative thesis takes a position, asserting the writer’s stance. Questions, vague statements, or quotations from others are not argumentative theses because they do not assert the writer’s viewpoint.

Federal immigration law is a tough issue about which many people disagree is not an arguable thesis because it does not assert a position.

Federal immigration enforcement law needs to be overhauled because it puts undue constraints on state and local police is an argumentative thesis because it asserts a position that immigration enforcement law needs to be changed.

An argumentative thesis must make a claim that is logical and possible. Claims that are outrageous or impossible are not argumentative theses.

City council members stink and should be thrown in jail is not an argumentative thesis. City council members’ ineffectiveness is not a reason to send them to jail.

City council members should be term limited to prevent one group or party from maintaining control indefinitely is an arguable thesis because term limits are possible, and shared political control is a reasonable goal.

Evidence Based

An argumentative thesis must be able to be supported by evidence. Claims that presuppose value systems, morals, or religious beliefs cannot be supported with evidence and therefore are not argumentative theses.

Individuals convicted of murder will go to hell when they die is not an argumentative thesis because its support rests on religious beliefs or values rather than evidence.

Rehabilitation programs for individuals serving life sentences should be funded because these programs reduce violence within prisons is an argumentative thesis because evidence such as case studies and statistics can be used to support it.

An argumentative thesis must be focused and narrow. A focused, narrow claim is clearer, more able to be supported with evidence, and more persuasive than a broad, general claim.

The federal government should overhaul the U.S. tax code is not an effective argumentative thesis because it is too general (What part of the government? Which tax codes? What sections of those tax codes?) and would require an overwhelming amount of evidence to be fully supported.

The U.S. House of Representative should vote to repeal the federal estate tax because the revenue generated by that tax is negligible is an effective argumentative thesis because it identifies a specific actor and action and can be fully supported with evidence about the amount of revenue the estate tax generates.

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• Argumentative Thesis Statements. Provided by : University of Mississippi. License : CC BY: Attribution

With the alarming rise in obesity rates among Americans in the past few decades, numerous debates have arisen over how (or if) public policy should be changed to help improve this trend. One promising strategy, already adopted by seven states, has been to try and deter consumers from purchasing unhealthy foods through a tax on soda or sugary drinks and junk food (Lohman, 2002). These taxes address the issue that Americans today are consuming almost 20% more calories than they did in the early 1980’s, and those calories are coming from increasingly less-healthy sources, mainly high-fat and high-sugar processed foods (USDA, 2002). Furthermore, processed foods and drinks are increasingly more affordable than the fruits, vegetables, and whole grains needed to sustain a healthy diet (Marsh, 2011). Assuming that cost is a more pertinent factor of food choice than personal taste, increasing the price of soda and junk food through taxes, while using that revenue to subsidize unprocessed fruits and vegetables would entice consumers to choose healthier products as they become more affordable than their unhealthy counterparts.     There is evidence to suggest that cost, more so than preference, influences purchasing choices. A year after New York increased cigarette taxes from $1.25 to $2.75, smoking rates dropped by 12% to a historic low (Harutyunyan, 2009). Although some might argue that smoking is more of a lifestyle choice than eating, it is rather the choice of what foods to eat which will hopefully be affected in the long run. Additionally, this tax might hurt those in areas with little access to fresh produce and whole grains, such as in low-income urban areas; therefore the “junk food tax” would only work if healthy food choices are made not only affordable but easily available to low-income consumers through the use of subsidies (Marsh, 2011). However, if precautions are taken to ensure equal access to healthy food among all citizens, then using the “carrot” of subsidized healthy food and nutrition education along with the “stick” of a food tax, the typical American diet can-- and should-- be changed for the better.

References:

• Harutyunyan, R. (June 6, 2009). “Cigarette Tax Increase Lowered NY Smoking Rates.” EmaxHealth . Retrieved from http://www.emaxhealth.com/2/58/31581/cigarette-tax-increase-lowered-ny-smoking-rates.html
• Lohman, J. (2002). Taxes on junk food. Washington DC: Office of Legislative Research. http://www.cga.ct.gov/2002/olrdata/fin/rpt/2002-r-1004.htm
• Marsh, B. (July 23, 2011). “Bad Food? Tax It, and Subsidize Vegetables.” The New York Times. Retrieved from http://www.nytimes.com/2011/07/24/opinion/sunday/24bittman.html?pagewanted=all
• US Department of Agriculture (2002). Profiling food consumption in America. In Agriculture Factbook: 2001-2002 . Retrieved from http://www.usda.gov/factbook/chapter2.htm

1) What is the author's claim in this piece?

Show Answer? The claim is stated in two places-- at the beginning of the piece, when the author states that the tax is a 'promising' strategy against obesity, and re-stated at the end when the author writes using the carrot of subsidized healthy food and nutrition education along with the stick of a food tax, the typical American diet can,and should, be changed for the better. These two statements condense the main point which the author is trying to impart-- that a junk food tax has a good chance of being successful and should be implemented.

2) Where does the author present evidence in this piece?

Show Answer? The main evidence to support her claim is given in the form of statistics about food consumption in the US to highlight the need for a program encouraging healthy food consumption. Specifically, she states Americans today are consuming almost 20% more calories than they did in the early 1980’s, and those calories are coming from increasingly less-healthy sources, mainly high-fat and high-sugar processed foods. Furthermore, processed foods and drinks are increasingly more affordable than the fruits, vegetables, and whole grains needed to sustain a healthy diet.

3) What is the warrant in this piece? Is it stated explicitly?

Show Answer? Because the author is arguing that a tax on unhealthy food would encourage healthy food consumption, the warrant linking evidence of unhealthy eating to the use of a food tax is that customers make purchasing decisions largely on the basis of cost. This idea is explicitly stated when the author writes mentions that we might assume cost is a more pertinent factor of food choice than personal taste .

4) Where does the author present backing for her warrant?

Show Answer? The author cites backing for the warrant through the effects of cigarette taxes on smoking habits in New York. Specifically, she writes that a year after New York increased cigarette taxes from $1.25 to $2.75, smoking rates dropped by 12% to a historic low (Harutyunyan, 2009).

Show Answer? Yes, the author addresses two possible counterarguments by bringing them up, and then refuting them. She notes that with regard to the legitimacy of comparing smoking to eating habits, some might argue that smoking is more of a lifestyle choice than eating, it is rather the choice of what foods to eat which will hopefully be affected in the long run . She also notes the issue of food deserts by writing additionally, this tax might hurt those in areas with little access to fresh produce and whole grains, such as in low-income urban areas; therefore the “junk food tax” would only work if healthy food choices are made not only affordable but easily available to low-income consumers through the use of subsidies (Marsh, 2011).

Show Answer? The author adds qualification by addressing the issues brought up by lack of access to healthy options in her re-statement of the claim. Specifically, the qualifier appears as the statement "however, if precautions are taken to ensure equal access to healthy food among all citizens, then..." . The claim is again stated as she continues with using the “carrot” of subsidized healthy food and nutrition education along with the “stick” of a food tax, the typical American diet can-- and should-- be changed for the better. .

Show Answer? This answer is dependent upon your own analysis of the argument. However, there are many issues worth noting. The evidence provided does explain that there is a trend in unhealthy eating, but does not give evidence for why this trend is harmful, nor does it provide evidence for why this trend exists. The overall claim that a junk food tax should be implemented would be stronger if evidence were given explaining the consequences of allowing this unhealthy trend to continue; also, the warrant that cost is a primary factor of food purchasing choices would be more valid if evidence was provided outlining other factors in this type of decision-making. Additionally, the rebuttal and qualifier addressing the lack of accessibility to healthy food in low-income areas would be stronger if the author had suggested specific measures by which the accessibility issue would be resolved.

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The Impacts of Junk Food on Health

Energy-dense, nutrient-poor foods, otherwise known as junk foods, have never been more accessible and available. Young people are bombarded with unhealthy junk-food choices daily, and this can lead to life-long dietary habits that are difficult to undo. In this article, we explore the scientific evidence behind both the short-term and long-term impacts of junk food consumption on our health.

Introduction

The world is currently facing an obesity epidemic, which puts people at risk for chronic diseases like heart disease and diabetes. Junk food can contribute to obesity and yet it is becoming a part of our everyday lives because of our fast-paced lifestyles. Life can be jam-packed when you are juggling school, sport, and hanging with friends and family! Junk food companies make food convenient, tasty, and affordable, so it has largely replaced preparing and eating healthy homemade meals. Junk foods include foods like burgers, fried chicken, and pizza from fast-food restaurants, as well as packaged foods like chips, biscuits, and ice-cream, sugar-sweetened beverages like soda, fatty meats like bacon, sugary cereals, and frozen ready meals like lasagne. These are typically highly processed foods , meaning several steps were involved in making the food, with a focus on making them tasty and thus easy to overeat. Unfortunately, junk foods provide lots of calories and energy, but little of the vital nutrients our bodies need to grow and be healthy, like proteins, vitamins, minerals, and fiber. Australian teenagers aged 14–18 years get more than 40% of their daily energy from these types of foods, which is concerning [ 1 ]. Junk foods are also known as discretionary foods , which means they are “not needed to meet nutrient requirements and do not belong to the five food groups” [ 2 ]. According to the dietary guidelines of Australian and many other countries, these five food groups are grains and cereals, vegetables and legumes, fruits, dairy and dairy alternatives, and meat and meat alternatives.

Young people are often the targets of sneaky advertising tactics by junk food companies, which show our heroes and icons promoting junk foods. In Australia, cricket, one of our favorite sports, is sponsored by a big fast-food brand. Elite athletes like cricket players are not fuelling their bodies with fried chicken, burgers, and fries! A study showed that adolescents aged 12–17 years view over 14.4 million food advertisements in a single year on popular websites, with cakes, cookies, and ice cream being the most frequently advertised products [ 3 ]. Another study examining YouTube videos popular amongst children reported that 38% of all ads involved a food or beverage and 56% of those food ads were for junk foods [ 4 ].

What Happens to Our Bodies Shortly After We Eat Junk Foods?

Food is made up of three major nutrients: carbohydrates, proteins, and fats. There are also vitamins and minerals in food that support good health, growth, and development. Getting the proper nutrition is very important during our teenage years. However, when we eat junk foods, we are consuming high amounts of carbohydrates, proteins, and fats, which are quickly absorbed by the body.

Let us take the example of eating a hamburger. A burger typically contains carbohydrates from the bun, proteins and fats from the beef patty, and fats from the cheese and sauce. On average, a burger from a fast-food chain contains 36–40% of your daily energy needs and this does not account for any chips or drinks consumed with it ( Figure 1 ). This is a large amount of food for the body to digest—not good if you are about to hit the cricket pitch!

• Figure 1 - The nutritional composition of a popular burger from a famous fast-food restaurant, detailing the average quantity per serving and per 100 g.
• The carbohydrates of a burger are mainly from the bun, while the protein comes from the beef patty. Large amounts of fat come from the cheese and sauce. Based on the Australian dietary guidelines, just one burger can be 36% of the recommended daily energy intake for teenage boys aged 12–15 years and 40% of the recommendations for teenage girls 12–15 years.

A few hours to a few days after eating rich, heavy foods such as a burger, unpleasant symptoms like tiredness, poor sleep, and even hunger can result ( Figure 2 ). Rather than providing an energy boost, junk foods can lead to a lack of energy. For a short time, sugar (a type of carbohydrate) makes people feel energized, happy, and upbeat as it is used by the body for energy. However, refined sugar , which is the type of sugar commonly found in junk foods, leads to a quick drop in blood sugar levels because it is digested quickly by the body. This can lead tiredness and cravings [ 5 ].

• Figure 2 - The short- and long-term impacts of junk food consumption.
• In the short-term, junk foods can make you feel tired, bloated, and unable to concentrate. Long-term, junk foods can lead to tooth decay and poor bowel habits. Junk foods can also lead to obesity and associated diseases such as heart disease. When junk foods are regularly consumed over long periods of time, the damages and complications to health are increasingly costly.

Fiber is a good carbohydrate commonly found in vegetables, fruits, barley, legumes, nuts, and seeds—foods from the five food groups. Fiber not only keeps the digestive system healthy, but also slows the stomach’s emptying process, keeping us feeling full for longer. Junk foods tend to lack fiber, so when we eat them, we notice decreasing energy and increasing hunger sooner.

Foods such as walnuts, berries, tuna, and green veggies can boost concentration levels. This is particularly important for young minds who are doing lots of schoolwork. These foods are what most elite athletes are eating! On the other hand, eating junk foods can lead to poor concentration. Eating junk foods can lead to swelling in the part of the brain that has a major role in memory. A study performed in humans showed that eating an unhealthy breakfast high in fat and sugar for 4 days in a row caused disruptions to the learning and memory parts of the brain [ 6 ].

Long-Term Impacts of Junk Foods

If we eat mostly junk foods over many weeks, months, or years, there can be several long-term impacts on health ( Figure 2 ). For example, high saturated fat intake is strongly linked with high levels of bad cholesterol in the blood, which can be a sign of heart disease. Respected research studies found that young people who eat only small amounts of saturated fat have lower total cholesterol levels [ 7 ].

Frequent consumption of junk foods can also increase the risk of diseases such as hypertension and stroke. Hypertension is also known as high blood pressure and a stroke is damage to the brain from reduced blood supply, which prevents the brain from receiving the oxygen and nutrients it needs to survive. Hypertension and stroke can occur because of the high amounts of cholesterol and salt in junk foods.

Furthermore, junk foods can trigger the “happy hormone,” dopamine , to be released in the brain, making us feel good when we eat these foods. This can lead us to wanting more junk food to get that same happy feeling again [ 8 ]. Other long-term effects of eating too much junk food include tooth decay and constipation. Soft drinks, for instance, can cause tooth decay due to high amounts of sugar and acid that can wear down the protective tooth enamel. Junk foods are typically low in fiber too, which has negative consequences for gut health in the long term. Fiber forms the bulk of our poop and without it, it can be hard to poop!

Tips for Being Healthy

One way to figure out whether a food is a junk food is to think about how processed it is. When we think of foods in their whole and original forms, like a fresh tomato, a grain of rice, or milk squeezed from a cow, we can then start to imagine how many steps are involved to transform that whole food into something that is ready-to-eat, tasty, convenient, and has a long shelf life.

For teenagers 13–14 years old, the recommended daily energy intake is 8,200–9,900 kJ/day or 1,960 kcal-2,370 kcal/day for boys and 7,400–8,200 kJ/day or 1,770–1,960 kcal for girls, according to the Australian dietary guidelines. Of course, the more physically active you are, the higher your energy needs. Remember that junk foods are okay to eat occasionally, but they should not make up more than 10% of your daily energy intake. In a day, this may be a simple treat such as a small muffin or a few squares of chocolate. On a weekly basis, this might mean no more than two fast-food meals per week. The remaining 90% of food eaten should be from the five food groups.

In conclusion, we know that junk foods are tasty, affordable, and convenient. This makes it hard to limit the amount of junk food we eat. However, if junk foods become a staple of our diets, there can be negative impacts on our health. We should aim for high-fiber foods such as whole grains, vegetables, and fruits; meals that have moderate amounts of sugar and salt; and calcium-rich and iron-rich foods. Healthy foods help to build strong bodies and brains. Limiting junk food intake can happen on an individual level, based on our food choices, or through government policies and health-promotion strategies. We need governments to stop junk food companies from advertising to young people, and we need their help to replace junk food restaurants with more healthy options. Researchers can focus on education and health promotion around healthy food options and can work with young people to develop solutions. If we all work together, we can help young people across the world to make food choices that will improve their short and long-term health.

Obesity : ↑ A disorder where too much body fat increases the risk of health problems.

Processed Food : ↑ A raw agricultural food that has undergone processes to be washed, ground, cleaned and/or cooked further.

Discretionary Food : ↑ Foods and drinks not necessary to provide the nutrients the body needs but that may add variety to a person’s diet (according to the Australian dietary guidelines).

Refined Sugar : ↑ Sugar that has been processed from raw sources such as sugar cane, sugar beets or corn.

Saturated Fat : ↑ A type of fat commonly eaten from animal sources such as beef, chicken and pork, which typically promotes the production of “bad” cholesterol in the body.

Dopamine : ↑ A hormone that is released when the brain is expecting a reward and is associated with activities that generate pleasure, such as eating or shopping.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

[1] ↑ Australian Bureau of Statistics. 2013. 4324.0.55.002 - Microdata: Australian Health Survey: Nutrition and Physical Activity, 2011-12 . Australian Bureau of Statistics. Available online at: http://bit.ly/2jkRRZO (accessed December 13, 2019).

[2] ↑ National Health and Medical Research Council. 2013. Australian Dietary Guidelines Summary . Canberra, ACT: National Health and Medical Research Council.

[3] ↑ Potvin Kent, M., and Pauzé, E. 2018. The frequency and healthfulness of food and beverages advertised on adolescents’ preferred web sites in Canada. J. Adolesc. Health. 63:102–7. doi: 10.1016/j.jadohealth.2018.01.007

[4] ↑ Tan, L., Ng, S. H., Omar, A., and Karupaiah, T. 2018. What’s on YouTube? A case study on food and beverage advertising in videos targeted at children on social media. Child Obes. 14:280–90. doi: 10.1089/chi.2018.0037

[5] ↑ Gómez-Pinilla, F. 2008. Brain foods: the effects of nutrients on brain function. Nat. Rev. Neurosci. 9, 568–78. doi: 10.1038/nrn2421

[6] ↑ Attuquayefio, T., Stevenson, R. J., Oaten, M. J., and Francis, H. M. 2017. A four-day western-style dietary intervention causes reductions in hippocampal-dependent learning and memory and interoceptive sensitivity. PLoS ONE . 12:e0172645. doi: 10.1371/journal.pone.0172645

[7] ↑ Te Morenga, L., and Montez, J. 2017. Health effects of saturated and trans-fatty acid intake in children and adolescents: systematic review and meta-analysis. PLoS ONE. 12:e0186672. doi: 10.1371/journal.pone.0186672

[8] ↑ Reichelt, A. C. 2016. Adolescent maturational transitions in the prefrontal cortex and dopamine signaling as a risk factor for the development of obesity and high fat/high sugar diet induced cognitive deficits. Front. Behav. Neurosci. 10. doi: 10.3389/fnbeh.2016.00189

Home — Essay Samples — Nursing & Health — Fast Food — Thesis Statement For Fast Food

Thesis Statement for Fast Food

• Categories: Fast Food

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Words: 642 |

Published: Mar 19, 2024

Words: 642 | Page: 1 | 4 min read

Table of contents

I. introduction, ii. health risks of fast food, iii. environmental degradation, iv. economic impact, v. social implications, vi. solutions and recommendations, vii. conclusion.

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Junk Food Essay for Students and Children

500+ words essay on junk food.

The term ‘junk food’ itself says a lot about this food. It indicates how it is harmful to our health. Furthermore, junk foods are basically trash which harms our bodies in different ways. They have high levels of cholesterol, sugar, calories and more. We see how nowadays, the younger generation is getting indulging in more and more junk food. This is putting their lives in danger and giving them an unhealthy lifestyle .

Furthermore, junk food does not have a single benefit. It only has ill-effects as they do not contain nutritional value . Parents must teach their kids about the ill-effects of junk food. Moreover, they must provide them with healthy meals at home so they won’t have to go out to eat fast food.

Rising Popularity of Junk Food

We all know that the fast-food industry is increasing by leaps and bounds these days. People these days are more attracted to junk food because it is appealing. Why is that? People are using manipulative ways to entice people to buy their fast food.

Moreover, junk food is prepared very easily. It takes minimum time to prepare it as it does not have any nutritious ingredients. We see how junk food does not have any special ingredients. It just contains common harmful ones in excess like oil, sugar, and more.

Furthermore, junk food is very reasonable. As it does not require any healthy material, it is not that costly. We see how it is available at very reasonable pricing. It is one of the main reasons why people buy it frequently.

Most importantly, junk food has become very accessible now, more than ever. With the onset of numerous food delivery apps, you can now get junk food with a single click. You have a plethora of options now which will deliver all sorts of junk food right at your doorstep.

Get the huge list of more than 500 Essay Topics and Ideas

Ill-effects of Junk Food

The major characteristic of junk food is that it spikes the energy levels instantly. It does not really benefit your body, just satisfies your taste buds. If we intake junk food regularly, we get moody more often.

Moreover, regular consumption of junk food causes a drop in the concentration levels of a person. This is why we see how kids these days are easily distracted. Moreover, you may also notice how obesity becoming common these days. It is a very chronic disease which is only enhanced by eating junk food.

Further, you may also notice how junk food increases blood pressure and sugar. A person gets more prone to heart diseases due to the fattening products used in it. Similarly, junk food is not easy to digest. This may gradually damage your brain function because it creates a lack of oxygen levels.

Junk food does not only damage the heart but the liver as well. It causes diabetes amongst people from an early age. Moreover, the lack of fibers in junk food equals to a damaged digestive system. This may cause constipation as well. Therefore, we see how junk food companies are fooling people. They are deceiving them into consuming their junk food to increase their sales. Thus, we need to realize this fact as soon as possible. Try to replace junk food with healthy food. Prepare your meals at home instead of ordering outside.

FAQ on Junk Food Essay

Q.1 Why is junk food getting popular?

A.1 Junk food is getting popular because it is easily accessible now. It is appealing and fast food companies are fooling the public for increasing their sales.

Q.2 State the ill-effects of junk food.

A.2 Junk food causes a lot of chronic diseases like diabetes, cholesterol, heart diseases. It drops your concentration level and messes with your digestive system.

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Junk Food in Schools and Childhood Obesity

Ashlesha datar.

RAND Corporation, 1776 Main Street, P.O. Box 2138, Santa Monica, CA 90407, USA, gro.dnar@ratad , Phone: 1-310-393-0411 x7367, Fax: 1-310-260-8161

Nancy Nicosia

RAND Corporation, 20 Park Plaza, 7th Floor, Suite 720, Boston, MA 02116, USA, gro.dnar@aisocin , Phone: 1-617-338-2059 x4227

Despite limited empirical evidence, there is growing concern that junk food availability in schools has contributed to the childhood obesity epidemic. In this paper, we estimate the effects of junk food availability on BMI, obesity, and related outcomes among a national sample of fifth-graders. Unlike previous studies, we address the endogeneity of the school food environment by controlling for children’s BMI at school entry and estimating instrumental variables regressions that leverage variation in the school’s grade span. Our main finding is that junk food availability does not significantly increase BMI or obesity among this fifth grade cohort despite the increased likelihood of in-school junk food purchases. The results are robust to alternate measures of junk food availability including school administrator reports of sales during school hours, school administrator reports of competitive food outlets, and children’s reports of junk food availability. Moreover, the absence of any effects on overall food consumption and physical activity further support the null findings for BMI and obesity.

1. Introduction

The prevalence of childhood obesity in the US is at an all-time high with nearly one-third of all children and adolescents now considered overweight or obese ( Ogden et al 2008 ). Considerable attention has been focused on schools in an attempt to identify policy levers that will help reverse the obesity epidemic. In particular, the availability of “competitive foods”, defined as foods and beverages available or sold in schools outside of the school lunch and breakfast programs, has been a much debated issue. On the one hand, opponents question the nutritional value of competitive foods and consider them the primary source of “junk foods” in schools. Indeed, the available evidence suggests that these foods are higher in fat compared with foods sold as part of the school meal programs ( Gordon et al 2007b , Harnack et al 2000 , Wechsler et al 2000, Story, Hayes & Kalina 1996 ). On the other hand, supporters argue that revenues from these food sales provide much-needed funding for schools, especially in times of budgetary pressures ( Gordon et al 2007a ).

The debate draws from largely cross-sectional research that rarely addresses the potential endogeneity of the school food environment. Our paper advances the literature by attempting to isolate the causal effect of junk food availability on children’s food consumption and BMI. We use longitudinal data on BMI for a national sample of fifth graders from the Early Childhood Longitudinal Study – Kindergarten Class (ECLS-K) and an instrumental variables (IV) approach that leverages the well-documented fact that junk foods are significantly more prevalent in middle and high schools relative to elementary schools ( Finkelstein, Hill and Whitaker 2008 ). Plausibly exogenous variation in junk food availability across a cohort of fifth graders is identified using the grade structure in their schools. We argue that a fifth grader attending a combined (e.g. K-8, K-12) or middle school (e.g. 5–8) is more likely to be exposed to junk foods compared to a fifth grader in an elementary school (e.g. K-5, K-6), but that the school’s grade span has no direct effect on a child’s weight. First-stage regressions confirm that combined school attendance is a strong predictor of junk food availability. Further tests for instrument validity including an examination of sorting and peer effects support our use of the instrument.

We find that junk food availability has small positive associations with BMI and obesity in basic OLS models that only control for a limited set of covariates, but those associations become insignificant when controls for BMI at school entry and state fixed effects are added. Our IV models, which address potential bias in the OLS models, generate somewhat larger, albeit less precise, point estimates that are also not statistically significant. Even if the IV point estimates were statistically significant, they would still represent only minor increases in BMI and obesity, generally one-third of one percent. Moreover, reduced form estimates, which are more precisely estimated than IV estimates, provide further support because combined school attendance has no significant effects on 5 th graders’ BMI and obesity. These results are robust to alternative measures of junk food availability and sample restrictions. The models also produce the expected findings on various falsification tests.

While we acknowledge their limitations, ancillary analyses of children’s in-school junk food purchases, total consumption of healthy and unhealthy foods, and physical activity are consistent with our null findings for BMI and obesity. Our estimates suggest that the caloric contributions of in-school junk food purchases are likely to be small. Moreover, we find evidence consistent with substitution between in- and out-of-school consumption. Specifically, the total amount of soda and fast food consumed in- and out-of-school, is not significantly higher among those children with greater exposure to junk food in school (i.e. attending a combined school). And, finally, we find little support for the notion that children substitute calories from healthy foods or increase their physical activity to compensate for increased junk food intake.

The remainder of this paper is organized as follows. We first discuss junk food availability in schools and the findings from the existing literature in Section 2. Section 3 describes our data and relevant analysis variables. In Section 4, we describe our empirical strategy, which leverages longitudinal information on BMI and implements an instrumental variables approach to identify the causal impact of junk food availability. In Section 5, we first discuss our main results for children’s BMI and obesity and then support these findings with robustness checks and falsification tests. We also present supporting evidence from models of in-school purchases of junk food, total consumption of various healthy and unhealthy items, and physical activity. Finally, Section 6 concludes with the policy implications of our findings.

2. Background and Literature

Competitive foods are sold through a la carte lines, vending machines, school canteens/stores, and fundraisers and, in contrast to the federally-reimbursable school meal programs, are not subject to federal nutritional standards. As a result, competitive foods account for much of the variation in the food environment across schools. Competitive foods are available in a large share of schools, although the availability of these foods varies significantly across elementary, middle, and high schools. For example, as many as 97% of high schools and 82% of middle schools have vending machines compared to only 17% of elementary schools ( Gordon et al 2007a ). However, a la carte lines, which are the predominant source of competitive food sales, operate not only in most high (93%) and middle (92%) schools, but also in a large proportion of elementary schools (71%) ( Gordon et al 2007b ).

Sales of competitive foods have the potential to generate significant revenues for schools. During 2005–2006, middle and high schools earned an average of $10,850 and $15,233, respectively, from a la carte sales alone ( Gordon et al 2007a ). In addition, nearly a third of high schools and middle schools earned between $1,000–$9,999 during that same year from vending machines, another ten percent earned between $10,000–$50,000, and a small number earned in excess of $50,000 per year. These revenues may in turn be supplemented by on-site school stores and pouring contracts with beverage companies. While availability and revenues were less common in elementary schools, nearly half of elementary schools had pouring rights contracts, and competitive food sales from fundraising activities were also common.

The U.S. Department of Agriculture’s regulations on competitive foods in schools had been comprehensive, but in 1983, a successful lawsuit by the National Soft Drink Association limited the scope of these regulations to food service areas during meal hours ( Institute of Medicine 2007 ). In recent years, several states, districts, and schools have enacted competitive food policies that are more restrictive than federal regulations. And, between 2003 and 2005, approximately 200 pieces of legislation were introduced in US state legislatures to establish nutritional standards in schools or to address the availability or quality of competitive foods ( Boehmer et al 2007 ). At the federal level, legislation was passed in 2004 requiring local education agencies to develop a “wellness policy” by 2006 that included nutrition guidelines for all of the foods available in schools. More recently, there has been debate in the US Congress over enacting an amendment to the farm bill that would further restrict the sale of unhealthy foods and beverages in schools ( Black 2007 ). At the local level, two of the largest school districts in the nation, New York City Public School District and Los Angeles Unified School District, imposed a ban on soda vending in schools in 2003 and 2004, respectively.

Despite the growing support for competitive food regulation, it is hard to deny opponents’ claims that the evidence against competitive foods is limited. Existing research does show that competitive food availability is associated with a decline in nutritional quality of meals consumed at school ( Cullen et al 2000 , Cullen & Zakeri 2004 ; Templeton, Marlette & Panemangalore 2005 ). 1 However, less is known about the effects on overall diet quality (consumed both in and out of school) and children’s weight. The literature does provide some evidence of substitution of caloric intake across meals and locations among adults ( Anderson and Matsa 2011 ), but the evidence is less clear regarding children for whom parental oversight can also play a role. Only Kubik and colleagues have examined 24 hour dietary recall (2003) and BMI (2005) among children, however these studies are based on small cross-sectional samples and do not address the potential endogeneity of the school food environment. 2 , 3

The only effort to address endogeneity is in Anderson and Butcher (2006) , who use national data on adolescents aged 14–20 years to examine whether various school food policies influence BMI (based on self-reported height and weight data). In the absence of a single data source containing information on school food policies and BMI among adolescents, the authors use a two-sample IV approach that employs county, state, and regional characteristics as instruments to capture budgetary pressures on schools. They find that a 10 percentage point increase in the proportion of schools in the county that offer junk foods leads to a 1 percent increase in BMI. But this effect is primarily driven by adolescents with an overweight parent, which the authors interpret as a measure of family susceptibility. 4 Their IV approach constitutes an innovation over the literature, but the authors acknowledge that their results may be undermined by a weak first stage.

Our paper adds to the existing literature in its sample, methodology and scope. First, to our knowledge, ours is the only study that addresses the endogeneity of the school food environment among younger children. The focus on fifth graders is useful because junk food regulations are increasingly targeting elementary and middle schools. 5 And our national sample of children provides a larger and more representative sample with significant variation in school environments. Second, our data contain actual measurements of children’s height and weight, unlike the self-reports from other national datasets that have been used to examine this question previously. Third, our approach improves on the common cross-sectional designs by controlling for children’s BMI at school entry and state fixed-effects, and leveraging variation in schools’ grade spans to estimate IV models. Finally, unlike previous studies, we also provide evidence on the underlying mechanisms by examining effects on food consumption and physical activity.

The ECLS-K is a panel dataset on a nationally representative cohort of kindergarteners in the U.S. who entered school in fall 1998. In the fall and spring of kindergarten and the spring of the first, third, and fifth grades, the study collected information from the children and their parents, teachers, and schools on children′s cognitive, social, emotional, physical development (including BMI), and their home, classroom, and school environments. One limitation is that the information on the school food environment and children’s food consumption was collected only in the fifth grade. Our analysis sample includes the approximately 9,380 children attending the fifth grade in public and private schools in the 2003–04 school year. 6 In this section, we describe the key variables for our analyses.

3.1. Dependent Variables Measuring BMI, Food Consumption and Physical Activity

Body mass index (bmi).

A distinct advantage of the ECLS-K is that it collected height and weight measurements from children at kindergarten (school) entry and in the spring of kindergarten and first, third, and fifth grades. Measurements are superior to self- or parent-reported height and weight data that may introduce non-random measurement error. These measurements are used to compute BMI, defined as weight in kilograms divided by height in meters squared. The average BMI in our sample during the fifth grade is 20.4 ( Table 1 ). Approximately 20% of the ECLS-K sample is categorized as obese – this is nearly identical to prevalence rates among 6–11 years olds from the 2007–8 National Health and Nutrition Examination Survey ( Ogden et al 2010 ). 7

Descriptive Statistics in the Fifth Grade

Notes: N=9,380. Means are unweighted. Standard deviation in parentheses.

Junk Food Purchase in School

The food consumption questionnaire collected information on in-school junk food purchase during the fifth grade. These questions asked children about their purchases of sweets, salty snack foods, and sweetened beverages (hereafter, referred to as “soda”) during the previous week. 8 A substantial majority of the children did not purchase junk food in school during the reference week: 77% for sweets, 84% for salty snacks, and 88% for soda (see Appendix Table A1 ). But a large share of these children did not have junk food available in their schools (see Section 3.2). Conditional on availability, about half the sample purchased any of these unhealthy foods at least once a week in school. Among those who did purchase, the modal response was 1 to 2 purchases per week: 68 percent for sweets, 72 percent for salty snacks, and 70 percent for soda. 9

In-School and Total Food Consumption in Fifth Grade

Notes: N=9,380. Percentages are unweighted. Figures in the top panel are not conditional on availability in school.

Total Consumption of Selected Foods and Beverages

The child food consumption questionnaire asked about the frequency of overall consumption of specific food items during the past week. Children were asked to include foods they ate at home, at school, at restaurants, or anywhere else. We examine the consumption of two unhealthy items - soda and fast food, and six healthy food items – milk, green salad, potatoes 10 , carrots, other vegetables, and fruits. The percentage of children not consuming any soda or fast food during the previous week was 16 and 29 percent, respectively, with modal responses at 1 to 3 times per week (see Appendix Table A1 ). Among the healthy foods, green salad, carrots and potatoes were consumed most infrequently with nearly half of children reporting no consumption during the past week. The modal responses for the other healthy foods were 1 to 3 times during the past week.

3.2. Junk Food Availability

Detailed information on junk food availability in schools was collected from the school administrators and from children in the fifth grade. School administrators were asked whether students could purchase 17 individual food and beverage items, either from vending machines, school store, canteen, snack bar or a la carte items from the cafeteria during school hours. From these responses, we constructed an indicator variable of junk food availability in school that equals 1 if the administrator reports that students can purchase food and beverage items containing high sodium and/or sugar, including candy, chocolate, baked foods (e.g. cookies), salty snacks (e.g. potato chips), ice cream or frozen yogurt, or sweetened beverages during school hours, and zero otherwise. 11 Based on these school administrator reports, approximately 61 percent of the children had junk food availability in school. For robustness checks, we also considered two alternative measures of availability. The first is based on whether the modal child at each school reports that foods containing sugar, salty snacks, or sweetened beverages can be purchased at school. Based on this measure, about 75 percent of the children had junk foods available. And the second is based on whether the administrator reports any of the following competitive food outlets operate in the school: vending machines, school stores, canteens, snack bars, and a la carte lines. About 60 percent of the sample had at least one competitive food outlet. 12

4. Empirical Approach

4.1. econometric model.

The relationship between junk food availability and children’s BMI in fifth grade can be estimated cross-sectionally using the following linear regression model.

where, BMI iks , denotes fifth grade BMI for child i attending school k located in state s , JF k captures junk food availability in the child’s school, X i and S k are the vectors of individual/family (gender, age, age interacted with gender, race/ethnicity, mother’s education, household income) and school characteristics (private/public, percent minority, enrollment, urbanicity, state/region), respectively, and ε iks is the error term. The child’s baseline BMI (BBMI i ) is included to address potential heterogeneity that can bias OLS estimates such as student demand for junk foods, genetic susceptibility, and sorting. Because junk food availability is collected only in fifth grade, we do not know the length of exposure during prior school years. Therefore, BMI at school entry is the preferred baseline because it is measured prior to any exposure to the school food environment. Finally, since states differ markedly in terms of obesity prevalence in their populations as well as the policy environment geared towards combating obesity, we include state fixed effects (θ s ) to control for state-specific time-invariant unobserved heterogeneity that may be correlated with school food environments and children’s weight.

The parameter of interest in Equation (1) is β 1 . Obtaining an unbiased estimate of β 1 is challenging because the school food environment is not exogenous to the outcomes of interest. Schools that serve high-fat, energy-dense junk foods may differ on many observable and unobservable factors that are correlated with children’s weight and dietary behavior. In particular, the decision to offer junk foods in schools may be influenced by a variety of factors including budgetary pressures, demands of the student population, parental involvement, and state/district policies. These factors could independently influence children’s weight as well. For example, budgetary pressures may induce schools or districts to scale back or eliminate physical education programs, which might increase children’s weight. As a result, coefficient estimates from the ordinary least squares (OLS) estimation of Equation 1 would be biased.

4.2. Addressing Endogeneity of Junk Food Availability in Schools

We address the potential endogeneity of junk food availability using instrumental variables. Specifically, we estimate the model in Equations (2.1) and (2.2) using Two-Stage Least Squares.

Equation 2.1 represents the first-stage regression where junk food availability (JF k ) is regressed on the combined school attendance instrument (CS k ), individual (X i ) and school (S k ) characteristics, baseline BMI (BBMI i ), and state fixed effects (θ s ). Equation 2.2 represents the second stage where children’s BMI (or obesity) is regressed on the predicted availability of junk foods from the first stage (ĴF k ) in addition to the common covariates.

We also report results from the reduced form, which regresses BMI or obesity directly on the instrument ( Equation 3 ). These results have the advantage of being unbiased and providing evidence of whether a causal relationship exists in the regression of interest. 13

4.2.1. Instrument

Our sample consists of a single cohort of 5 th graders attending schools with a variety of grade spans. Given that junk food availability is significantly higher in middle and high schools compared to elementary schools, a potentially useful instrument for junk food availability is whether the 5 th grader attends a combined school (defined as the highest grade is seventh or higher) or whether the 5 th grader is in an elementary school (defined as highest grade is 5 th or 6 th ). Our instrument considers only this dichotomy of school type: elementary versus combined. Over 70 percent of our sample attends elementary schools while the remainder attends combined schools usually with grade spans of K-8, K-12 and 5–8 (see Appendix Table A2 ).

Variation in Grade Span in Fifth Grade

Notes: N=9380. “Combined” schools are defined as schools with highest grade equal to 7 or higher.

For combined school attendance to be a valid instrument, it must be the case that the school’s grade span has no direct effect on children’s weight except through the junk food environment. One potential concern is that there may be unobserved factors that are correlated with both the likelihood of combined school attendance as well as BMI. For example, it is well known that states differ markedly in the prevalence of childhood obesity. But, states are also likely to differ in terms of factors that contribute to school grade span such as: (1) the size of the school-age population, (2) its distribution within the state, (3) differences in the educational systems and policies, as well as (4) education budgets. Similarly, school grade span can vary across urban versus rural areas (even within states), with the latter more likely to have combined schools largely because of a smaller school-age population. The inclusion of state and urbanicity dummies in our regressions controls for unobserved differences across states and across rural/urban areas that may be correlated with combined school attendance (or grade span, more generally) and BMI.

Another potential concern with this identification strategy is that variation in grade span exposes children to older peers who may influence obesogenic behaviors. Peers, defined broadly, have been shown to influence a wide range of adolescent behaviors and outcomes. 14 However, of particular relevance to our identification strategy is the literature examining a specific type of peer effect, namely, the effect of exposure to older peers due to school grade span.

Several studies have examined peer effects on academic, social-behavioral and substance use outcomes by leveraging variation in school grade span ( Clark and Folk 2007 ; Clark and Loheac 2007 ; Eisenberg 2004 ; Bedard and Do 2005 ; Cook et al 2008 ). Most studies compare students in the same grade who attend middle versus combined schools or middle versus elementary schools . 15 These studies generally find that 6 th or 7 th graders who attend middle school fare poorly compared to those who attend elementary or combined schools. 16 However, we are not aware of any studies that compare children in the same grade level who attend elementary versus combined schools . The exception is Rickles (2005) , whose findings suggest inconsistent effects of elementary versus combined schools attendance on achievement.

Furthermore, there is very limited evidence on the influence of older peers on food choices. Cullen and Zakeri (2004) compared changes in food consumption of 4 th graders who transitioned to middle school in 5 th grade and gained access to school snack bars to changes in food consumption of 5 th graders who were already in middle school. Fourth graders who transitioned to middle school consumed fewer healthy foods compared with the previous school year, but it is not clear whether this was due to the presence of older peers or the change in school food environment.

Overall, the literature suggests that the presence of older peers may adversely affect academic and social behavioral outcomes, but there is less evidence to support effects on their eating behaviors. Nevertheless, if such an effect exists, the potential bias in our IV estimates due to peer effects is likely to be upward. That is, 5 th graders might emulate older peers who are more likely to consume junk foods in school and would therefore tend to be overweight, independent of the school food environment. In that case, an insignificant finding is unlikely to be undermined.

4.2.2. Checks for Instrument Validity

Identification in our IV models relies on the assumption that, conditional on state and urbanicity dummies, the school’s grade span does not influence BMI except through differences in the availability of junk foods. Districts typically determine the grade span at the time of the schools’ opening based on a number of factors including transportation costs, length of bus ride, desired number of transitions, population size, site availability, preferred school size, and likelihood of parental involvement ( Paglin and Fager 1997 ) rather than children’s health outcomes. Changes in grade span over time are possible, but infrequent and similarly-motivated. For example, in our ECLS-K sample, less than 4 percent of the children who remained in the same school between kindergarten and fifth grade experienced a grade-span change from combined to elementary school or vice-versa. While unlikely, it is nevertheless possible that schools may change grade span in response to children’s physical size. Therefore, below we report results from several tests that support the validity of our instruments. These analyses are based on our preferred specification, which controls for the full set of covariates, including state and urbanicity dummies and baseline BMI.

First, we report first-stage estimates of the effect of our instrument – combined school attendance – on junk food availability in school. The first-stage estimates show that combined school attendance significantly increases the likelihood of junk food availability with an F-statistic on the instrument that exceeds 22 ( Table 2 ).

First Stage Regression Estimates of Junk Food Availability in Fifth Grade

Notes: Figures in brackets are robust standard errors clustered at the school level. Other covariates in the model include male, age (months), male*age, race/ethnicity, kindergarten BMI, mother’s education, income, private school dummy, categories for percent minority in school and school enrollment, and state and urbanicity dummies.

Second, since our instrument leverages across school variation we might be concerned that selection into different schools (or communities) might undermine the validity of our instrument. To test for differential selection into combined versus elementary schools, we regress BMI, obesity, test scores, social-behavioral outcomes, and parental involvement measured in kindergarten on combined school attendance in 5 th grade ( Table 3 ). 17 Because these outcomes are determined prior to exposure to school, these comparisons allow us to test for selection. The results suggest that, conditional on observed characteristics, combined school attendance is uncorrelated with pre-exposure BMI, obesity, test scores, social-behavioral outcomes and parental involvement.

Effect of Attending a Combined School on Kindergarten Outcomes

Notes: Each estimate represents a separate regression. Other covariates in the models include age, male, age*male, race/ethnicity, kindergarten BMI (not in model in Columns 1 and 2), mother’s education, income, private school dummy, categories for percent minority in school and school enrollment, and state and urbanicity dummies. Robust standard errors clustered at school level are shown in brackets. For reading, math, self control, and interpersonal skills, higher skills indicate better outcomes. For externalizing and internalizing behavior problems, higher scores indicate worse outcomes. Parent involvement is measured as the sum of the number of times/week that the parent engages in 9 activities with the child (e.g. reading books, talk about nature, do science projects, tell stories).

Third, another concern is that combined school attendance might generate peer effects on BMI, obesity, food consumption and physical activity, independent of junk food availability. We test for the presence of peer effects by regressing these outcomes on combined school attendance using only the sample of schools that do not offer junk foods ( Table 4 ). The results do not provide any support for peer effects on BMI, obesity, food consumption or physical activity. 18

Effect of Combined School Attendance on BMI, Obesity and Related Behaviors Without Junk Food Availability in Fifth Grade

Notes: Each estimate represents a separate regression. All models control for the full set of covariates. Robust standard errors clustered at school level are shown in brackets.

Overall, the instrument appears to be strongly predictive of junk food availability and there is no evidence that selection or peer effects threaten its validity.

We now turn to our main results, which examine the effects of junk food availability on BMI and other outcomes. We first estimate basic OLS models of BMI and obesity, then augment with state fixed effects and baseline BMI to address omitted variable bias and selection, and finally estimate the IV and reduced form specifications (Section 5.1). In Section 5.2, we examine the sensitivity of our results to alternate measures of junk food availability and various sample restrictions. We also report findings from falsification tests. And finally, in Section 5.3, we describe results from ancillary regressions that explore the potential mechanisms underlying our BMI findings. In particular, we examine in-school and total consumption of selected foods and beverages and the availability of and participation in physical activity.

5.1. BMI and Obesity

Our main results focus on whether the availability of junk foods increases BMI and obesity among 5 th graders ( Table 5 ). Columns 1 and 4 in Panel A show the results of basic OLS regressions of log BMI and obesity, respectively, on junk food availability controlling for child, household, and school characteristics. 19 These regressions yield a statistically significant increase in both BMI and obesity when junk food is available, although the point estimates are small. The inclusion of state fixed effects and urbanicity dummies (Panel A, columns 2 and 5) and then baseline BMI measured in kindergarten (Panel A, columns 3 and 6) eliminates the significant coefficients. The fully-specified OLS models have very small, precisely estimated, and statistically insignificant point estimates.

Effects of Junk Food Availability on BMI and Obesity in Fifth Grade

Notes: N=9,380. Robust standard errors clustered at school level are shown in brackets. Other covariates in the model include male, age (months), male*age, race/ethnicity, kindergarten BMI, mother’s education, income, private school dummy, categories for percent minority in school and school enrollment, and state and urbanicity dummies. First stage results are shown in Table 2 .

However, the coefficients from these OLS models may be biased if junk food availability is related to unobserved determinants of children’s BMI. For example, districts with a large population of students at risk for obesity may adopt more stringent nutritional policies that reduce the availability of junk foods in school. In such situations, OLS regressions may show no significant relationship or even a negative relationship between junk food availability and BMI. OLS estimates might also suffer from attenuation bias due to the presence of measurement error in the junk food availability measures.

To address these issues, we estimate instrumental variables (IV) and reduced form regressions using grade span as the instrument: whether the 5 th grader attends a combined school with older peers. 20 The IV point estimates are relatively larger than the OLS estimates, but less precisely estimated rendering them statistically insignificant ( Table 5 , Panel B). 21 , 22 IV estimates from models that do not control for state and urbanicity dummies and baseline BMI (columns 1 and 4) are much larger than those in our preferred specification (Columns 3 and 6), although they are not statistically significantly different from each other. Even if the IV point estimates in our preferred specification (columns 3 and 6) were significant, they would represent only small increases in BMI and obesity of less than one-third of one percent. Hausman tests that check for the endogeneity of junk food availability by comparing estimates from the fully-specified OLS regression with the IV cannot reject the null hypothesis that both estimates are consistent. Therefore, we also report the reduced form estimates of BMI and obesity regressed directly on our instrument ( Table 5 , Panel C). The coefficients on the instrument are close to zero and very precisely estimated, which further confirm the null findings. Given concerns about unobserved heterogeneity in the OLS specifications and the larger standard errors in the IV specifications, the reduced form estimates are preferred.

5.2. Sensitivity and Falsification Checks

We conducted a number of sensitivity analyses to test the robustness of our findings. In this section, we report results from a few key analyses and then turn to falsification tests. 23 These analyses control for the full set of covariates, including state and urbanicity dummies and baseline BMI.

For the sensitivity analyses, we first re-estimate our BMI and obesity regressions with the two alternate measures of junk food availability ( Table 6 ). Both the child-reported measure of junk food availability and the school-administrator reported measure of competitive food outlet show no effect of junk food availability on BMI or obesity. Next, we re-estimate the models with the exclusion of three particular groups that might confound our instrument ( Table 7 ). First, because combined schools are much more likely to be private, our instruments may simply capture variation across public versus private schools students, even though the regressions control for private school attendance. We re-estimate the models on a sample that excludes children who attend private schools ( Table 7 , Panel A) and find no effects on BMI and obesity. 24 Second, even though Section 4.2.2 suggests there are no peer effects on BMI and related behaviors, we test the sensitivity of our results to exclusion of the oldest peers (e.g., grade 9 or higher), but still find no evidence of an effect on BMI and obesity ( Table 7 , Panel B). Finally, children who switch schools for unobservable reasons potentially related to junk food availability may bias our estimates, but estimates from models that exclude children who changed schools between kindergarten and fifth grade confirm no effects ( Table 7 , Panel C). The point estimates from the OLS, IV and reduced form regressions for these sensitivity checks are essentially zero, though less precisely estimated in the IV models. 25

Effects of Alternate Measures of Junk Food Availability on BMI and Obesity in Fifth Grade

Notes: N=9,380

Effects of Junk Food Availability on BMI and Obesity in Fifth Grade with Alternate Sample Restrictions

Notes: All models include the full set of covariates. Robust standard errors clustered at school level are shown in brackets. Hausman tests for consistency of OLS estimates could not be rejected in any case. The tests are not reported in the table.

As falsification tests, we examined whether junk food availability in the fifth grade influenced children’s height in the fifth grade and their pre-exposure BMI. Height should clearly be unrelated. And indeed, the coefficients are essentially zero and insignificant ( Table 8 ). Because BMI and obesity in kindergarten is measured prior to exposure to junk foods in school, any effects would suggest unobserved heterogeneity. The OLS, IV and reduced form point estimates are close to zero (though the IV estimates are less precise) and the reduced form specifications also show no relationship ( Table 9 , Panel A). Results for BMI and obesity measured in first and third grade likewise confirm insignificant effects of junk food availability during fifth grade ( Table 9 , Panels B and C). However, because our data do not contain information on junk food availability prior to 5 th grade, these results are also consistent with the absence of junk foods in earlier grades.

Effect of Junk Food Availability in School on Height in Fifth Grade

Note: N=9,380. Robust standard errors clustered at school level are shown in brackets.

Effects of Junk Food Availability on BMI and Obesity in Kindergarten, First, and Third Grade

Notes: Each estimate represents a separate regression. All models include the full set of covariates. Robust standard errors clustered at school level are shown in brackets.

5.3. Effects of Junk Food Availability on Food Consumption and Physical Activity

The consistent lack of significant findings for BMI and obesity raises questions regarding how the energy balance equation is affected by junk food availability. While we cannot measure children’s energy intake and expenditure explicitly with these data, we can examine whether junk food availability influences general food consumption patterns and physical activity. Unlike BMI and obesity, the consumption and physical activity measures are based on parents’ and children’s reports . As a result, they are subject to measurement error and consequently produce noisier estimates particularly for the IV models. Nevertheless, they represent our best opportunity for understanding important mechanisms underlying our null finding. Therefore, for the in-school junk food purchases, total consumption, and physical activity analyses, we focus mainly on the reduced form results (though we provide OLS results for comparison). 26

5.3.1 In-School Purchases and Overall Consumption

One potential explanation for our null findings for BMI and obesity may be that availability does not impact overall food consumption. This may happen for several different reasons. First, young children may not purchase significant amounts of junk food in school either due to limited access to such foods or fewer discretionary resources to purchase them. Second, children may not change their total consumption of junk food because junk food purchased in school simply substitutes for junk food brought from home. Or third, children may not change their overall consumption during the day, but simply substitute between junk food consumed in-school and out-of-school.

Unfortunately, we cannot completely separate out these possible explanations because the ECLS-K does not provide us with full information about the daily dietary intake of each child. However, we do have information about in-school purchases of foods with sugar, salty snacks, and sweetened beverages for those children with in-school availability. We also have total (in-school plus out-of-school) consumption of soda, fast food, and a variety of healthy foods for all children in the sample. While not definitive, we can use this information to gain some insight into underlying eating behaviors and lend support for our BMI and obesity findings.

Not surprisingly, our analysis of in-school consumption of junk foods does confirm that children purchase junk food when it is available. 27 The OLS estimates show a significant relationship for purchases of all types of junk food when junk foods are available in schools ( Table 10 , Panel A). And the reduced form estimates show that children in combined schools are between 5 and 9 percentage points more likely to purchase junk foods compared to those in elementary schools Table 10 , Panel B).

Effect of Junk Food Availability on In-School Junk Food Purchases in Fifth Grade

Notes: N=9380. Each estimate represents a separate regression. Dependent variables in columns (1)–(3) are dichotomous and capture whether any purchase of that item was made in school during the last week. All regressions include the full set of covariates. Robust standard errors clustered at school level are shown in brackets.

To provide a sense of the caloric contribution of these purchases, we multiplied the increase in the probability of purchase from attending a combined school by the median number of times that food was purchased among children who purchased at least once, by the number of the calories per unit. 28 Summing across the three junk food groups yields 50 calories per week (7 calories per day) from in-school junk food purchases. The caloric contribution of in-school purchases is much higher (435 calories per week or 62 calories per day for the median child) among children who purchase these foods (as opposed to merely having them available). But even the 62 calories per day represents less than a quarter (23 percent) of the daily discretionary calorie allowance (267 calories) for a moderately active fifth grader. 29

It is possible that children substitute in-school purchases for snacks brought from home or eaten at home either due to satiation or parental monitoring. With our simple dietary recall measures, we cannot explicitly test the nature of potential substitution. We can, however, examine the total intake of soda and fast food consumed in and out of school. Soda is of particular interest because it is the only item for which children were asked about both their in-school and total consumption separately. Fast food, on the other hand, does not correspond exactly to the in-school snack food consumption categories. We find that junk food availability is not associated with significant increases in children’s total consumption of soda or fast foods ( Table 11 , Columns 1 and 2). 30 The OLS regressions show negative, though generally insignificant, estimates. 31 More importantly, the reduced form estimates confirm that there is no relationship between combined school attendance and total consumption of soda and fast food. The fact that children who consume soda and other junk food in schools show no evidence of an increase in total consumption provides support for the substitution hypothesis. This finding is also consistent with the literature, which indicates that only 27 percent of soda and sweetened drinks consumed in elementary schools are bought at school compared to 67 percent brought from home ( Briefel et al 2009 ).

Effect of Junk Food Availability on Total Consumption of Selected Unhealthy and Healthy Foods in Fifth Grade

Notes: N=9380. Each estimate represents a separate regression. Dependent variable captures the number of times the food or beverage item was consumed during the last 7 days. All models include the full set of covariates. Robust standard errors clustered at school level are shown in brackets.

While BMI is a widely-used outcome measure, it does not capture nutritional changes. Just because children are not gaining weight does not mean that their diets are not adversely affected by junk food availability. If children are consuming junk food in lieu of healthy foods, there may still be concerns about their nutrition. Columns 3 through 8 of Table 11 examine whether children with in-school availability of junk foods consume less milk, green salad, carrots, potatoes, other vegetables, and fruit. The OLS results show no significant associations with junk food availability. Moreover, reduced form regressions also show that combined school attendance does not significantly impact total consumption of the healthy foods. 32

Physical Activity

The absence of any effects of junk food availability on BMI despite the in-school purchases of junk food also raises questions regarding potential compensatory changes in the availability of and participation in physical activity. For example, revenues from junk food sales may be used to fund playgrounds or pay for physical education instructors. Or it may be that combined schools simply offer more opportunities for physical activity due to their scale and organization relative to elementary schools. Another possibility is that parents or children may increase children’s physical activity to balance junk food intake. If physical activity is greater, then we may find no change in BMI or obesity despite an increase in caloric intake.

OLS and reduced form estimates for school- and parent-reported physical activity measures are reported in Table 12 . OLS estimates show no relationship between junk food availability and minutes per week of physical education at school, minutes per week of recess at school, and parent-reported participation in physical activity (measured as the number of days per week that the child engaged in exercise that causes rapid heart beat for 20 continuous minutes or more). The reduced form regressions show no significant effects of combined school attendance on minutes per week of physical education instruction. Children attending combined school have fewer minutes of recess ( Table 12 , Column 2), but slightly higher days of parent-reported physical activity ( Table 12 , Column 3) though neither finding is statistically significant at.conventional levels. Overall, the regressions do not provide consistent evidence that increased energy expenditure explains the null finding for BMI and obesity.

Effects of Junk Food Availability on Physical Education, Recess and Physical Activity in Fifth Grade

Notes: Each estimate represents a separate regression. All models include the full set of covariates as well as the baseline (kindergarten) measure of the dependent variable. Robust standard errors clustered at school level are shown in brackets.

6. Conclusion

Junk food availability is a prominent issue for middle and high schools in the U.S. However, there is also widespread legislation and regulation targeting junk foods even in elementary school ( Trust for American’s Health 2009 ). Young children’s access to junk foods in school is an important concern due to the strong correlation between childhood overweight and obesity in adolescence and adulthood ( Institute of Medicine 2005 ). In this paper, we examined whether junk food availability increased BMI and obesity among a national sample of 5th graders. Those 5th graders who attend a combined school are much more likely to have junk food availability relative to those in elementary school. While estimates from naïve models that only control for a limited set of covariates suggest a positive association between junk foods in school and BMI and obesity, fully-specified OLS models that control for BMI at school entry and state fixed-effects demonstrate no statistically or economically significant relationships among these young children. Likewise, the IV and reduced form models, which are not subject to the potential bias undermining OLS models, confirm the null findings for BMI and obesity. These results are not sensitive to various robustness checks including alternate measures of junk food availability and sample restrictions.

Finally, we provide further support for the null findings by examining in-school and overall food consumption patterns as well as physical activity. The null effects on BMI and obesity cannot be explained entirely by limited access or limited discretionary resources among young children because 5 th graders do purchase junk food when it is available in schools. However, our results suggest that the caloric contribution of in-school purchases is likely to be small. Moreover, we find no evidence of significant changes in the overall frequency of consumption of soda and fast food, which is consistent with children substituting in-school purchases of junk food for that taken from or eaten at home. Alternative explanations such as compensatory changes children’s consumption of healthy foods and in their opportunities for and participation in physical activity do not appear to play a significant role in explaining our null findings for BMI and obesity.

Our findings may have implications in the current economic environment. Half of the states are projecting budget shortfalls that threaten staffing, compensation, extracurricular activities, and policy initiatives such as mandated limits on class size. 33 Many schools subsidize their funding with revenue from the sale of junk foods. In total, elementary schools earn approximately $442 million annually from junk food sales ( Institute of Medicine 2007 ). In light of our findings, certain policy measures, such as outright bans on junk food sales (at least among elementary school children), might appear premature given that they remove a key source of discretionary funds.

While our results are robust, we caution that we could not consider the full range of consequences of junk food availability. Not only are the dietary intake measures in the ECLS-K limited, but we are also not able to examine whether related health outcomes such as diet quality or dental caries are influenced by junk food availability. Also, we are unable to examine the generalizability of our findings to older children who may have greater junk food access and intake both in and outside school. And finally, we could not consider whether exclusive contracts between schools and beverage/snack companies influence students’ food choices in the longer run through product or brand recognition. Additional research is necessary to fully understand the potential consequences before costly legislation is implemented. Such research might also consider the consequences of junk food regulations on school finances and the extent to which these financial consequences could be mitigated by the sale of more nutritious alternatives or through alternative financing mechanisms.

Means by Attendance in Elementary Versus Combined School and by Private/Public

Notes: N=9,380.

Effect of Grade-Span on Academic and Social-Behavioral Outcomes Among Schools Without Junk Food Availability in Fifth Grade

Acknowledgments

This research was funded by grants from the Robert Wood Johnson Foundation’s Healthy Eating Research Program, NIH R01 HD057193, the Bing Center for Health Economics at RAND, and the RAND Labor and Population Program. All opinions are those of the authors and do not represent opinions of the funding agencies.

1 Other studies have examined the effects of price reductions, increases in availability, and promotion of low-fat foods in secondary schools on sales and purchases of these foods ( French et al 2004 , 2001 , 1997a , 1997b , Jeffery et al 1994 ) as well as their consumption ( Perry et al 2004 ) within experimental settings and found positive effects.

2 Kubik et al (2003) find that a la carte availability in school is negatively associated with overall intake of fruits and vegetables and positively associated with total and saturated fat intake among 7 th graders attending 16 Minneapolis-St Paul schools. Using the same data, Kubik et al (2005) show that using competitive foods as rewards and incentives is positively associated with BMI.

3 Also, using the ECLS-K, Fernandes (2008) found small positive associations between soda availability in schools and both in-school and overall soda consumption of fifth graders.

4 Their results for the other school policies, pouring rights contracts, and food and beverage advertisements are smaller and less precise.

5 For example, California’s first nutrition policy (SB 677) implemented beverage standards for elementary and middle schools, not high schools.

6 All sample sizes have been rounded to the nearest 10 per the ECLS-K’s restricted-use data agreement.

7 Obesity is defined as BMI greater than the 95 th percentile for age and gender on the Center for Disease Control growth charts.

8 Sweets include candy, ice cream, cookies, brownies or other sweets; salty snack foods include potato chips, corn chips, Cheetos, pretzels, popcorn, crackers or other salty snacks, and sweetened beverages include soda pop, sports drinks or fruit drinks that are not 100 percent juice.

9 To validate the ECLS-K estimates, we examined the Third School Nutrition and Dietary Assessment Study (SNDA-III), which collected 24-hour dietary recall from 2,300 children attending a nationally representative sample of public schools in 2005. Similar to the ECLS-K, eighty percent of elementary school children reported no competitive food purchases. Among children who made a purchase, the median daily caloric intake from these foods was 185 calories. The SNDA estimate is higher than our ECLS-K estimates (62 calories reported in Section 5) because it includes healthy foods purchased from competitive food venues: for example, milk was by far the most popular item purchased from competitive food venues and yogurt also ranked highly.

10 The “potatoes” category excluded French fries, fried potatoes, and potato chips.

11 The questionnaire separately asked about availability of high- and low-fat options for baked foods, salty snacks, and ice cream/frozen yogurt/sherbert. We include both the low- and high-fat options in our measure, however, in sensitivity analyses, we used only the high-fat versions to construct our school-administrator based measure of junk food availability and found results to be similar.

12 We rely mainly on the first measure of junk food availability because it is the most specific with respect to the quality of foods and because school-level policies regarding junk food availability are frequently set by school principals and staff ( Gordon et al 2007a ). We prefer this measure over the simple dichotomy of having any (unregulated) competitive food outlets because the outlet-based measure does not differentiate the type of foods sold (e.g. milk vs. soda). We also prefer it over the child-report because children who do not consume junk foods are less likely to accurately report availability and because children reported only the availability of any sweets, salty snacks, or sweetened beverages, but did not differentiate specific items (e.g. low-fat vs. high-fat).

13 The value of reduced form regressions has been highlighted by Angrist and Krueger (2001) and, more recently, Chernozhukov and Hansen (2008) formally show that the test for instrument irrelevance in the reduced form regression can be viewed as a weak-instrument-robust test of the hypothesis that the coefficient on the endogenous variable in the structural equation is zero.

14 This literature examines peer effects on a wide range of outcomes including substance use ( Lundborg 2006 ; Eisenberg 2004 ; Case and Katz 1991 ; Gaviria and Raphael 2001 ), crime ( Case and Katz 1991 ; Glaeser, Sacerdote, and Scheinkman 1996 ; Regnerus 2002 ), teenage pregnancy ( Crane 1991 ; Evans, Oates and Schwab 1992 ), discipline ( Cook et al 2008 ), academic achievement ( Hanushek et al 2003 ; Cook et al 2008 ), adolescent food choices ( Perry, Kelder, Komro 1993 ; Cullen et al 2001 ; French et al 2004 ) and weight ( Trogdon, Nonnemaker and Pais 2008 ).

15 However, Clark and Loheac (2007) estimate how substance use behavior of students within the same school who are one year older influences adolescent substance use and find a positive relationship.

16 One exception is Eisenberg (2004) who finds that 7 th and 8 th graders who attend schools with older peers are no more likely to use substances relative to those who attend schools with younger peers.

17 We also examined unadjusted differences in children’s individual, family and school characteristics during the 5 th grade (see Appendix Table A3 ). There were slight differences for some of the covariates. However, there was no overall pattern in the socioeconomic factors that would threaten the validity of the IV approach: that is, some differences imply better BMI outcomes for one group and others worse. For example, in our sample, elementary school students are more likely to be Hispanic and Asian while combined school students are more likely to be white. There are no differences in the share that are Black. Similarly, there is no consistent pattern in maternal education. Elementary school students are more likely to have poorly and highly educated mothers (less than high school, more than Bachelors).

18 To check whether these null findings are merely due to lack of power instead of absence of peer effects, we estimated the same models using social-behavioral outcomes and test scores as dependent variables because the literature finds evidence of peer effects on these outcomes. We were able to identify statistically significant peer effects on social-behavioral outcomes (but not test scores), which suggests that lack of power is an unlikely explanation for the finding of null peer effects on BMI and related outcomes.

19 In all models, we estimate robust standard errors clustered at the school level.

20 In alternate analyses, we used continuous measures of the highest and lowest grades in the school as instruments. In these over-identified models, both instruments had a strong positive association with junk food availability (i.e. increases in the highest and lowest grades available at the school were strongly predictive of junk food availability). This approach yielded qualitatively similar results as the exactly-identified models (available upon request).

21 The IV regressions were also estimated without baseline BMI. The point estimates, first-stage F-statistics, and Hausman tests yield similar results (available upon request).

22 A concern with our IV specification estimated via two-stage least-squares is that our first stage models do not account for the dichotomous nature of the treatment variable ( Maddala 1983 ). Estimates from binary treatment effect IV models confirm that the effects of junk food availability on BMI are neither substantive nor significant (available upon request).

23 We also conducted additional sensitivity analyses not reported here. First, given that we do not know the exposure to junk food in previous grades and given concerns that genetic susceptibility may not have a constant proportional effect on BMI at every point in the life cycle, we controlled for 1 st or 3 rd grade BMI instead of BMI in Kindergarten and obtained similar results. Second, inclusion of controls for school meal participation did not change our findings. Third, we used BMI z-scores as the dependent variable to accurately control for age and gender influences on BMI and obtained qualitatively similar results. Fourth, we estimated quantile regressions to test whether the effects of junk food availability varied across the BMI distribution, but found no evidence for heterogeneous effects. Finally, we also re-estimated our BMI and obesity models separately for each gender. The results for junk food availability mirrored those for the full sample. The OLS, IV, and RF models show no significant effects of junk food availability for either boys or girls. Still we may be concerned about differential peer effects, for example, if girls are influenced by older peers’ concerns about body image, which would bias our IV estimates downward. Restricting the sample to those boys and girls attending schools without junk food availability, the coefficients from the reduced form were nearly identical to those based on the full sample of boys and girls, which suggests that peer effects are not an issue even when regressions are gender-specific.

24 Estimates based only on the sample of private schools yield small and statistically insignificant effects of competitive food availability on BMI in both OLS and IV specifications, although the F-statistics for the instrument in the first stage were smaller (Results available upon request).

25 Hausman tests cannot reject the consistency of fully-specified OLS estimates in any of our sensitivity checks.

26 Although not shown, the IV (Wald) estimates are easily calculated by dividing the reduced form estimates in Table 10 – Table 12 by 0.2 (first stage estimate from Table 2 ). The IV coefficients are never significant in part due to the larger standard errors in the regressions of reported eating behaviors and physical activity.

27 We dichotomize the in-school purchase variables and estimate linear probability models since much of the variation in junk food purchases at school occurs on the extensive margin.

28 The median number of times an item is purchased in school among children who purchase at least once is 1.5 times (1–2 times per week). We assume that salty snacks add 140 calories (typical calories from a bag of potato chips), sweets add 200 calories (typically calories from a candy bar), and soda adds 150 calories. Given the limitations of the consumption data in the ECLS-K, we caution the reader to treat these caloric intake calculations as approximations.

29 Discretionary calories are the difference between an individual’s total energy requirement and the energy necessary to meet nutrient requirements. According to Dietary Guidelines for Americans, the discretionary allowance for a 2000 calorie diet is 267 calories. See: http://www.health.gov/dietaryguidelines/dga2005/document/html/chapter2.htm#table3 accessed August 22, 2008.

30 The total consumption variables are not dichotomized because there is sufficient variation on the intensive margin.

31 Negative binomial models with a binary treatment variable to account for the count-data distribution of the total consumption variable and the binary nature of junk food availability produced qualitatively similar results. (Results available upon request).

32 Given the limitations of the ECLS-K’s consumption variables, we again examined the SNDA-III data and found no evidence that combined school attendance increases total caloric intake.

33 “Schools expect budget cuts as economy sours: State problems, decline in property values eat away at district funds”. Available at: http://www.msnbc.msn.com/id/23116409/ (Accessed February 10, 2009).

Contributor Information

Ashlesha Datar, RAND Corporation, 1776 Main Street, P.O. Box 2138, Santa Monica, CA 90407, USA, gro.dnar@ratad , Phone: 1-310-393-0411 x7367, Fax: 1-310-260-8161.

Nancy Nicosia, RAND Corporation, 20 Park Plaza, 7th Floor, Suite 720, Boston, MA 02116, USA, gro.dnar@aisocin , Phone: 1-617-338-2059 x4227.

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Good Essay About Should Junk Food Be Banned In Schools

Type of paper: Essay

Topic: Nutrition , Social Issues , Eating , Health , Education , Children , Food , Students

Words: 1200

Published: 03/27/2020

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(A Persuasive or Argumentative Essay) I. Introduction of the Problem Junk food (e.g., French fries, soda pop, ice cream, etc.) tastes good and has high calories, but only has little nutritional value. Some, if not most, schools sell junk food to students because they are affordable to students who have small pocket money. On the other hand, other students whose taste buds became accustomed to eating junk food, even though they have the financial means, also find time to eat this kind of snack. In US public schools alone, as children move to higher grade levels, the food they consumed becomes less healthy because only less nutritional values are obtained from consuming a variety of junk food (Finkelstein, Hill and Whitaker). Junk food consumption is a problem that needs solution that is why the USDA advised schools that school-aged children (aged 2 years and over) should have a healthful and balanced, daily dietary nutrition (USDA: Center for Nutrition Policy and Promotion). Don’t let the taste of junk food fool you as it will be harmful to your health later in your life. II. Solution Many US school districts nationwide planned to curtail unhealthy menu items of its secondary school students (Racette). So, if you are the parent, teacher, principal, politician, manufacturer, and/or stakeholder, would you be persuaded that junk food should be banned in schools? III. Development of Solution: Why eating junk food is a health issue? Junk food is a health issue in schools because of the little nutritional value that students can obtain from it. In addition, students become prone to health problems such as obesity, high blood pressure, low energy levels, heart diseases, and so on. Studies reveal that students become obese due to their large quantity of junk food consumptions, easiness to buy junk food in schools, persuasiveness of ads about junk food, lack of activity, etc. (Beil). According to Beil, regular consumptions of junk food and other high-processed, high-calorie foods have negative effects on the brains of children. Instead of eating junk food, there are other more affordable yet balanced/nutritional food available in the market today. Moreover, politicians, parents, school heads and other stakeholders should make it a point that the school canteen will not sell any junk food. Students also should not be allowed to eat junk food inside the school; instead, there should be policies, rules and regulations to combat its sale in school (such as use instead of junk-food free vending machines). IV. Refutation The controversy surrounding the banning of junk food in schools is also met with oppositions. There are students who believe that it is up to them whether to eat junk food or not. They have the right to choose which food to eat as long as it will not do them harm such that eating one small pack of junk food a day will not cause students to become obese. Instead, they say that schools should focus more on more pressing and persistent education issues such as school gangs, bullying, etc. On the contrary, some students state categorically that junk food is not good for one’s health. Various research findings point to the fact that junk food will cause more harm than good (Beil; USDA: Center for Nutrition Policy and Promotion). Schools, for the most part, decide and act for the wellbeing of its students. Hence, when schools include in its policy the banning of junk food, students should comply. There is really nothing wrong if students in schools will abstain from eating unhealthy food. V. My Personal Stance Personally, I agree with the students who favor the banning of junk food consumption in schools. Apparently, based on evidences, junk food will not do us good. Aside from the awareness drive, schools should constantly be vigilant regarding violations of school rules such as eating junk food. Students caught bringing and eating junk food should be twice warned with a penalty to render civic service. If a particular student run afoul the third time, he/she has to be kicked out from the school. This way, instead of suspending the students, other students will realize how serious schools are in helping them to become not just healthy individuals, but as disciplined persons. Another effort toward solving the health issue on junk food is for schools to provide free nutritional food to students who are undernourished and malnourished. Each school district should include in its budget food for students who have health problems, too. If this is done on a regular basis, schools are way near from becoming not just learning institutions, but more importantly, who also look after the health of its students. VI. Conclusion There is nothing wrong in eating foods. However, when one eats unhealthy food, there will always be adverse repercussions – whether immediately or in the long run. Hence, people in authorities should guard individuals from making unsound decisions and actions. The same holds true in terms of consuming junk food. Junk food, as stated earlier, is not good because it deposits many calories inside the body while only benefitting less from having the required nutrition. Hence, I am strongly in favor of junking junk food in schools. Reality bites! Junk food will remain as junk food. We should never have a second thought banning junk food in schools. If we do not do any action, then when is the right time to do so? I think students should learn the importance of being healthy while they are still young. They are not old enough not to learn and start while they are still young. Being aware that what you eat is what will make you in the end is not far from the truth. Although eating unhealthy food may not affect you instantly or give a bad return immediately, it will. Hence, in order for schools to ban junk food from students, it is good to provide information dissemination, look-out regularly (that is, being vigilant) against violators, and offer free nutritional food. All of these will turn the schools’ objectives of having healthy students – both minds and bodies. It is never late to strive for what is best for students. If we act now, we can see the immediate results. Thus, we have to ban junk food in our schools. Don’t let the taste of junk food fool you.

Works Cited

Beil, Laura. "The Snack-Food Trap." Newsweek 160.19 (2012): 44-47. Web. 18 February 2014. Finkelstein, Daniel, Elaine Hill and Robert Whitaker. "School Food Environments And Policies In US Public Schools." Pediatrics 122.1 (2008): e251-e259. Web. 17 February 2014. Racette, Kellie. "Trimming the Fat." Teacher Magazine 16.1 (2004): 21-25. Web. 18 February 2014. USDA: Center for Nutrition Policy and Promotion. Dietary Guidelines for Americans. 7 March 2013. USDA: Center for Nutrition Policy and Promotion. Web. 18 February 2014. <http://www.cnpp.usda.gov/dietaryguidelines.htm>.

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