Obesity and the environment

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Rush hour in Copenhagen, where 62% of the population commute by bicycle to their work or study places each day

Obesity and the environment aims to look at the different environmental factors that have been determined by researchers to cause and perpetuate obesity. In 1994 in the United States, the percentage of the adult population that was obese was much lower than it is today. In 1994 the percentage of the population in every state that was obese was less than 20%, but by 2008, only one state still had a percentage obese below 20%, six states had a percentage obese of more than 30% while the rest of the states ranged between 20% and 30%.[1]

In 2016, the number of obese people reached an all-time high of about 93 million, which was up 33 percent from 2008 according to the Center for Disease Control (CDC).[2] This may be even more concerning for children and teens who have seen their rate of obesity go up to 18.5%, which is triple the rate in 1980. If current trends continue, as many as 57% of them will end up obese by the time, they reach the age of 35.[3]   This will put them at higher risk for other health conditions such as, Type 2 diabetes, heart disease, and cancer. In response, both federal and local officials have instituted policies to combat obesity as well as promote healthy eating, such as: The Farm Bill, National School Lunch Act and Child Nutrition Act, as well as The Healthy Kid Act.

Environmental obesogens[]

Studies have shown that obesity has become increasingly prevalent in both people and animals such as pets and laboratory animals.[4] There have been no linkages found between this obesity trend and diet and exercise. According to Professor Robert H. Lustig from the University of California, San Francisco, "[E]ven those at the lower end of the body mass index (BMI) curve are gaining weight. Whatever is happening is happening to everyone, suggesting an environmental trigger."[5] The theory of environmental obesogens proposes a different causal facet to obesity – that lifetime exposure to xenobiotic chemicals may change the body's metabolic system. Chemical obesogens are molecules that do not properly regulate lipid metabolism in the body and could therefore promote obesity. Data is scarce, but some in-vitro studies have found this model could be an accurate predictor of future obesity. A study suggested that smoking before and during pregnancy, for example, increases the risk of obesity twofold in children of school age.[6]

Many chemicals that are known or suspected to be obesogens are endocrine disruptors. These obesogens are present in common-use products. In a University at Albany, State University of New York study, organotins were found in a designer handbag, vinyl blinds, wallpaper, tile, and vacuum cleaner dust collected from 20 houses.[7] Phthalates, which have also been linked to obesity, are present in many PVC items in addition to scented items like fresheners, laundry products, and personal care products.[8] Bisphenol A (BPA), is one known environmental obesogen that reduces overall number of fat cells, but makes remaining fat cells larger. Effects of obesogens in animals are the same effects researchers see later in life for low-birth weight babies – glucose intolerance and more abdominal fat.[7] The study concludes that obesogens change an individual's metabolic set points for gaining weight.[7]

What little research has been conducted on the relationship between chemical exposure and body mass index points to obesogens as a likely contributor to the obesity epidemic. Some endocrine disrupting chemicals (EDCs) belong to this class of compounds. Bruce Blumberg, a professor of developmental and cell biology at UC Irvine, has found compelling evidence that exposure to the chemical Tributyltin (TBT), a compound used in pesticides, can trigger fat cell creation.[9] As several cases have confirmed, many farm workers in America have unwillingly or unknowingly worked in fields that had been recently sprayed with TBT and other dangerous chemicals. Among a wide variety of health risks, farm workers may bear a disproportionate risk of exposure to such obesogens. While legislation has been enacted to require a minimum amount of time to pass before workers enter sprayed fields, the lack of legal and political power of many farm workers combined with the fact that enforcing such laws can be difficult, makes exposure to obesogens a possible threat to the livelihood of many farm work

Location[]

Obesity by country[]

The rates of obesity range from country to country due to different environments, lifestyles, and diets. While there is no direct correlation between obesity rates and economic status, wealthier countries have access to more resources to raise awareness and educate people on what they are putting into their bodies.[10] When comparing highest to lowest obesity rates by country Nauru has the highest at 61.0%, while Vietnam has the lowest at 2.1%. Nauru is a Pacific island nation with a population of 10,000. Their diet is mostly made up of canned food due to a drop in their economy. On the other hand Vietnam struggles with their population not receiving enough nutrition. According to World Population Review, the ten countries with the highest obesity rates from highest to lowest, first is Nauru (61.00%), then Cook Islands (55.90%), Palau (55.30%), Marshall Islands (52.90%), Tuvalu (51.60%), Niue (50.00%), Tonga (48.20%), Samoa (47.30%), Kiribati (46.00%), and Micronesia (45.80%).

Race[]

Race and genetics[]

According to the Centers for Disease Control and Prevention (CDC), the obesity have been affecting some groups more than others. Hispanics 47.0% and non-Hispanic blacks 46.8% had the highest age-adjusted prevalence of obesity than the non-Hispanic whites 37.9% and non-Hispanic Asians 12.7%.[11] Many explanations exist to explain the disparity, among which include different behaviors among racial and ethnic groups, differing cultural norms in regards to body weight and size, and unequal access to healthy foods.[12]

Race and genetics are two other dimensions of obesity that have been extensively studied. Some researchers have found that genetics increase the likelihood of occurrence of obesity through higher levels of fat deposition and adipokine secretion.[13] Others think that race itself may affect the way obesity presents itself in individuals. In a recent study of 70,000 men and women of African ancestry, researchers found three new common genetic variants.[14] These single-nucleotide polymorphisms (SNPs) are connected to body mass index (BMI) and obesity. Therefore, individuals who carry these variants are more at risk of becoming obese. Researchers noted that these genetic variants are but a very small determination in most cases of obesity. It is generally agreed upon by many in the medical community that environmental factors and poor health and eating habits are still considered to be the strongest contributors to obesity.[15]

One study found that black men and women have a lower percentage of body fat than white men and women with the same body mass index (BMI).[16] A similar study concluded that obese black adolescents had significantly less dangerous visceral fat than obese white adolescents. Visceral fat is significant because it has been more strongly linked to the risk of disease as compared to fat stored in other parts of the body.[17]

Race and the built environment[]

A multitude of studies show that members of racial and ethnic minority communities are disproportionately obese. A recent study in the American Journal of Public Health found a strong correlation between community demographics and the likelihood of inhabitants being obese. In this study, non-Hispanic Blacks (36.1%) and Hispanics (28.7%) were shown to have higher percentages of obesity than non-Hispanic Whites (24.5%) and non-Hispanic Asians (7.1%).[18] Non-Hispanic Blacks and Hispanics inhabitants often have to rely on cheap calories with little nutritional value. Food deserts are also more likely to be located in these neighborhoods, which limits available food options. Additionally, these communities also tend to have less access to public goods (such as parks). While racial/ethnic minority communities are often impoverished, social standing alone does not explain the disparity between communities. A 2009 study in the Journal of Epidemiology and Community Health found that racial/ethnic minorities have a higher risk of being obese within each observed socioeconomic group.[19] This finding suggests that race may be a key indicator in determining disparities of obesity risk. The study also implies that structural racism may be causing certain racial/ethnic groups to experience a disproportionate risk, as class alone does not determine the likelihood of a person being obese.

Social perspective[]

Weight bias and stigma[]

Weight bias is an ongoing field of study that has garnered much more attention in the past few years. There are some studies that focus on obesity-related stigmatization. Multiple academics cite that people who are overweight and obese have been treated differently in almost all aspects of their life because due to the stereotypes commonly attributed to overweight. Laziness, incompetence, weakness of will, sloppiness, and untrustworthiness to name a few of them.[20][21]

In one study of 2,249 obese and overweight women, 54% reported experiencing weight stigma from their colleagues and 43% reported experiencing weight stigma from their superiors. Such weight stigma can be defined as derogatory comments, preferential treatment towards normal-weight colleagues, and denial of employment. In another study of 2,838 nationally representative adults aged 25–74, overweight respondents, obese respondents, and severely obese respondents were 12, 37, and 100 times more likely to report employment discrimination than normal-weight respondents, respectively. Studies show that wages can also be reduced. Data suggests that after controlling for other socioeconomic factors, limitations of health, and other household variables, obese men were expected to see a 0.7 to 3.4% wage depression and obese women were expected to see a wage depression between 2.3 and 6.1%.[22]

Studies have also been conducted showing that physicians are most likely to attribute lack of motivation as the primary cause of obesity, coupled with non-compliance and general laziness. In one United Kingdom study, physicians tended to follow a victim-blaming approach about the causes of obesity, while the obese patients themselves attributed their weight to specific medical causes or other socioeconomic factors, such as low income. Disparities in perceived causation have been seen in some circles as a major hindrance towards physicians and patients abilities to come up with a balanced obesity management plan.[22]

Educational weight bias also persists according to a range of studies conducted observing the effects of obesity and educational attainment. A study of over 700,000 Swedish men found that, after controlling for intelligence and parental socioeconomic levels, those who were obese at the age of 18 had a lower chance of going to college than their peers, who were of normal weight. Similarly, a study based on data gathered by the National Longitudinal Study of Adolescent Health concluded that obese women were 50% less likely to attend college than women who were not obese. It was also found in this study that female students who attended school where most of the females were obese had a relatively similar chance of attending college as non-obese women.[22]

Weight bias, fat stigma, and discrimination are factors that many academics say can contribute to hopelessness and depression that may encourage the same unhealthy habits that initially caused obesity[23]

Relation to mental health[]

One of the most critical lessons the scientific and healthcare communities have cultivated is that obesity and mental illness are directly related. Identifying and causing awareness of this complicated relation between these two diseases is necessary in developing progress and solutions that are not yet accessible. Because these two diseases are so closely related, it is crucial that patients being assessed for obesity be examined and assessed thoughtfully of their mental health status. Public health policies, according to the Charter, should itemize the prevention of mental illness and weight-concerned disorders, and recognize the relationship of both conditions to cultural, gender, socioeconomic, and other health elements. In order to create a type of cultural change, training as well as collaboration of health professionals, focusing on interventions, support, preventions, and collaboration with related specialties is crucial. Health Professionals need be more aware that anyone with one of these health issues, (obesity or mental illness), is automatically more susceptible to develop the other one.

Patients who are assessed for obesity are seen to have a chronic health condition. This is not just in a physical health sense, but extremities in mental health as well. A large variety of (extreme) psychological disorders or mental illnesses such as eating disorders (anorexia, bulimia, binge-eating disorder), Schizophrenia, bipolar disorder, and depression/anxiety, have all been shown to be associated with an increased risk of obesity, as well as other obesity-related illnesses such as diabetes and coronary heart disease. One recent study done to over 10,000 people suffering from schizophrenia, bipolar disorder or depression; showed that the 80% of these people were overweight or obese.[24] Other psychological issues which obesity has been shown to trigger are low self-esteem, distorted body image, and body shaming. People who are obese tend to have more increased rates of depression than those who are not overweight. Research done at the University of Wisconsin-Madison by Dr. David A. Kats and his colleagues shows that out of 2,931 patients who exhibit chronic health conditions, that clinical depression was highest in extreme obese patients (BMI over 35). Other research done by the Swedish Obese Subjects (SOS), have indicated that clinically significant depression is about three to four times higher in severely obese individuals than in those who are not obese. Professor Marianne Sullivan and her team from Sahlgrenska University Hospital noted from their findings and experience that people who are obese have exhibited depression scores just as bad as, or worse than those of patients with chronic (physical) pain. They state in a journal article that "Depression on a level indicating psychiatric morbidity was more often seen in the obese".[25][26]

Class-specific obligations[]

Familial obligations often prevent low-income youth from participating in after-school programs offered in their community. These obligations include, but are not limited to, chores, jobs, family assistance, and household management. A CCLC evaluation found that 50% of non-participating youth could not take part in their programs because of after school responsibilities. Another 28% stated that they could not participate because they were required to take care of their younger siblings after school while their parents were working.[27] As highlighted in a recent brief by the Harvard Family Research Project, "In some evaluations of welfare-to-work programs, the only group of adolescents who experienced gains in participation in formal after school activities were those without younger siblings."[28] Like sibling care, employment is another obstacle that prevents low-income youth from taking advantage of after school programs. Youth from less affluent homes are likely to work longer hours than youth from more affluent homes.[29] According to television broadcast statistics, Hispanic and African-American teen and children are now more targeted by fast food restaurants, Spanish-language advertisement on TV has increased by 8%, and restaurants such as KFC and Burger King have increased their spending on Spanish advertisements from 35% to 41% while decreasing English-language advertising.[30]

Access to space[]

Between the years 1980 and 2000, obesity rates doubled among young children and tripled among teens. Many studies have been conducted to provide insight into whether genetics are to blame, or economic and environmental circumstances. According to the "thrifty gene hypothesis",[31] a common genetic theory for rising obesity rates is that some people are genetically predisposed to more efficiently metabolize food than others. This is a result of years of human evolution. In times of scarcity, these genes were essential in ensuring survival, and in times of abundance, cause obesity. The thrifty genotype is one theory to explain obesity. The tendency to be sedentary and increasing rates of sugar and fat consumption are also linked to obesity prevalence.

The propensity for children to be less active can be attributed to the accessibility to safe play areas and after school programs, which differ between different socioeconomic classes. Studies have shown that rates of participation in after school programs is similarly low across all socioeconomic groups. Current research shows that this may be due to external factors other than the willingness or need to participate. Research shows that children that come from high-socioeconomic households typically do not participate in after-school programs because they are already involved in a wide range of other activities not funded by the school. Children that come from low-socioeconomic households, however, typically do not participate because of a lack of ability to participate. Lack of transportation is another obstacle to utilizing play spaces and after-school programs.[32][33][34][27] Parents of low-income and minority youth were less likely to report easy access to conveniently located after-school programs, as compared to high-income and white parents.[35] The child's ability to participate in most after school programs is contingent on the parent's ability to drop them off or pick them up. It's very uncommon for after-school programs to have the resources to provide transportation.[36]

Youth face similar problems as young children from disadvantaged families. Poor youth are less likely to have access to a car, and more likely to live in high crime neighborhoods, making it difficult to take public transportation or walk. The CCLC, an after-school program that targets low-income youth, conducted a survey in which 20% of youth reported that the reason they were not able to enroll was not due to lack of desire, but rather their inability to find adequate transportation.[37]Even so, children from disadvantaged families often have more things to worry about, less free time to exercise or move around. Their families are busy finding ways to put food on the table and meet basic needs, so energy are less focused on children going out to playgrounds, sports, etc. This is the opposite case for more privileged families, they have the financial means to support and time by taking their children to the playgrounds, afterschool places, gym, etc.

Factors of the built environment may contribute to obesity, for example via the availability of unhealthy food or the absence of green spaces, defining the term "obesogenic environment".[38] [39]

Access to technology[]

Children of higher–class families have more access to technology tend to make less use of their provided 'environmental space' of their everyday life. With this, that use of technology takes away from youth outdoor interaction. This issue contradicts with the belief that children who come from high-income homes are less likely to become obese considering they usually have more access to be active in their surrounding 'environmental space'. Children now a day who have more access to technology tend to spend more time indoors behind a computer/television screen. With the ongoing advancement in technology, those who have access- especially children of wealthy working parents- are more likely to spend time sitting still being attentive to either a television or computer screen rather than moving around outdoors. This use and focus on technology not only takes away from physical activity time for a child, but also plays a role in negatively affecting a child's health.

Technology being a direct factor to obesity goes hand in hand amongst children, teens and adults. Not only does the use and increase in technology affect the weight of children who tend to spend more time indoors using this technology rather than being active outdoors, technology advancements also play a role in those adults who spend most of their time working behind and using a computer in general. According to research done by two economists from the Milken Institute, a statistic shows for every 10 percent rise in what a country spends on technology, there's a 1.4 percent increase in obesity rates or approximately 4.2 million people in a country with the same population as The United States.[40][41]

Technology as an obesity factor plays the biggest role in those adults who spend most of their working day at a desk- behind a computer screen.[42] Not only does an increase in time spent behind a computer screen take away from time spent outdoors, it also takes away from time spent on physical activity such as exercise. The more time an individual spends sitting down at a desk working behind a computer, the less time her or she spends outdoors, at the gym, and just moving around in general.[42] The increase in time spent using technology doesn't just take away from time spent being active, it also changes the way people eat. With the time consumption of work many individuals tend to spend more time focusing on their work rather than on their food consumption / everyday diet. According to Ross DeVol—a chief research officer at the Milken Institute claims—'Common sense says if you sit around in front of the screen, don't exercise while you are working, change your diet...you are going to gain weight,'.[42]

Food access[]

Federal and national level studies[]

In 2009, The U.S. Department of Agriculture conducted a "food desert" study to examine access to supermarkets. They found that 23.5 million people within the United States did not have access to a supermarket within a one-mile radius of their residences. More than 113 studies have been conducted to determine if healthy food and supermarkets are equally accessible to every socioeconomic class.[43] 97 of the 113 studies found that supermarkets and healthy food stores are unequally distributed between different socioeconomic groups, 14 of 113 found mixed results, and 2 of 113 found equal distribution. 85% of the studies resulted in the conclusion of unequal distribution between different socioeconomic classes.

Studies in which supermarkets were compared to other food outlets such as small grocery stores and convenience stores were also conducted; in this study supermarkets were used as a proxy for food access, for they provide the most reliable access to a wide variety of nutritious and affordable food. The study showed that low-income and minority communities had less supermarkets and more convenience and small grocery stores as compared to predominantly white and wealthy communities. 89 out of 98 national and local studies have found uneven geographic access to supermarkets in urban areas.

Nationwide studies have concluded that zip codes composed primarily of low-income households are 25% less likely to have a chain supermarket store but contain 1.3 times as many convenient stores when compared to zip codes composed of middle-income households. Zip codes composed of predominantly African-American households have about half the amount of chain supermarkets, as do zip codes composed of predominantly White households.[44] According to an assessment of 685 urban and rural census tracts spanning three states, low-income neighborhoods have approximately half as many supermarkets and four times as many small grocery stores when compared to high-income neighborhoods. The same study also found that predominantly white neighborhoods have four times as many supermarkets as predominantly African-American neighborhoods.[45] Also, a study of 10,763 residents in four states showed that the existence of supermarkets in the surveyed residential area was related with a 24% lower prevalence of obesity and a 9% lower prevalence of overweight.[46]

Local level studies[]

Studies done at the local level demonstrate similar trends to those done at the national level. There are 2.3 times as many supermarkets per household in low-poverty areas in Los Angeles, compared to high-poverty areas. Predominantly white regions have 1.7 times as many supermarkets as Latino regions, and 3.2 times as many as African-American regions.[47] Amongst affluent neighborhoods in Alaska, those composed of predominantly white residents have better access to grocery stores than those composed of predominantly African-American residents, indicating that race may be an element independent of income.[48] West Louisville, Kentucky, a low-income African-American community that suffers from high rates of diabetes, has one supermarket for every 25,000 residents, in comparison to the U.S. average of one supermarket for every 12,500 residents.[49] "In Washington, DC, the city's lowest income wards (Wards 7 and 8) have one supermarket for every 70,000 people while two of the three highest-income wards (Wards 2 and 3) have one for every 11,881 people. One in five of the city's food stamp recipients lives in a neighborhood without a grocery store."[50][51] Twenty-one studies have found that food stores in low-income communities are less likely to stock healthy or fresh food or snacks. These food stores are also more likely to offer lower quality items at higher prices, compared to food stores in predominantly white communities.[52][53][54][55]

Food deserts and obesity[]

Low income families are more vulnerable to becoming overweight and obese due to the low access of high quality, nutritious food in their neighborhoods. Neighborhoods that lack access to nutritious foods are considered to be food deserts.[56]

Low income neighborhoods and communities of color tend to lack full-service grocery stores. A report issued in 2002 by the Urban and Environmental Policy Institute at Occidental College found out that "middle- and upper-income neighborhoods in Los Angeles had 2.26 times as many supermarkets per capita than in low-income neighborhoods."[57] Due to the small amount of grocery stores, low-income residents rely on small corner stores for their food and produce. A study that was conducted in 21 of the nation's largest metropolitan areas found that there are fewer and smaller stores in low-income zip codes than in their wealthier counterparts.[58] Due to the minimal amount of supermarkets located in low-income neighborhoods, people that reside in these neighborhoods have less access to quality food and limited product selection as compared to the selections in wealthier neighborhoods. For example, corner markets in low-income neighborhoods are less likely to offer healthy selections such as whole-grain breads and lower-fat and dairy options.[59]

Low income neighborhoods are burdened with an abundance of fast food outlets. A 2005 study that was conducted in Chicago found that "African-American neighborhoods had 13.7 major fast food restaurants per 100,000 neighborhood residents, while white neighborhoods had 9.4 per 100,000 residents."[60] Fast food restaurants offer inexpensive, calorie-dense food, but that same food is also nutrient-poor and unhealthy, with high levels of sugar, fat, and sodium. According to the USDA recommendation for daily caloric intake, a McDonald's meal has more than half a day's worth of calories.[61][62] In the short term, the residents of these communities are making an economically rational decision when purchasing fast food as it is easily accessible and inexpensive. The alternative would be purchasing low quality groceries at a high cost.[58] In the long-term however, studies show that the consumption of fast food hurts overall health, raising the probability of becoming obese.[63]

Food deserts are described by the Department of Agriculture as neighborhoods without ready access to fresh, healthy, and affordable food. To combat this in the city of Chicago in 2015, then Mayor Emmanuel partnered with Growing Power, which transported affordable fresh fruits and vegetables to food desert areas.[64]  In 2004 Pennsylvania enacted a 100 million dollar economic stimulus package that subsidized grocery stores in food desert areas. Grocery stores could get a low-cost business loan from the (FFFI) when they locate in a food desert.[64] In 2008 New York City, former Mayor Bloomberg introduced the Green Cart amendment which would allow pushcarts vendors to receive a low-cost permit only if they were willing to operate in underserved neighborhoods. The Green Carts program estimated that they would improve the health of 75,000 New Yorkers and save at least 50 lives a year over the long term.[64]

Obesity and School Nutrition Legislation

The National School Lunch Act and Child Nutrition Act of 2004 created the team nutrition network, this nutrition network was assembled to promote healthy eating and physical activity. These teams provided grants to states to create healthy eating programs as well as establish physical activity for children.[65] Along with this act CDC released its own guidelines to promote physical education and health education.[66] Schools should coordinate an approach to develop implement and evaluate healthy eating and physical activity policies and practices. They should create an environment that support both healthy eating and physical activity. School lunches should be healthy and provide appealing healthy food and drink choices outside the meal program. Schools should establish physical education programs as a cornerstone, as well as implement health education ensuring that students gain the proper knowledge necessary for healthy eating and physical activity.  Students should be provided with mental health and social services, as well as schools should partner with families and community members to develop and implement healthy eating and physical activities outside of school. Schools should employ qualified professionals and provide staff with professional development opportunities in areas such as physical education, health education, nutrition services, and mental health.

The 2010 Healthy Kids Act was part of Michelle Obama "Let’s Move" program.  This program authorized the USDA to regulate competitive foods, which references to any food that is not included in a school's lunch program, such as fast food and vending machines. Under the Healthy Kids Act schools required more stringent nutritional standards for meals served in cafeterias. The Healthy Kids Act requires the USDA's nutritional guidelines to be scientifically founded and in compliance with the published Dietary Guidelines for Americans.[67] With this schools began to replace food which were high in fat, sodium and any food that was lacking nutritional value, schools began to implement more fruits, whole grain, vegetables and low or nonfat milk.  As of 2014 kids were beginning to eat more fruits and vegetables, in a study conducted by Harvard it was found that kids age 16% more vegetables and 23% more fruit at lunch.[68] As of 2017 the Healthy Kids Act was still in place but on May 1, 2017 Secretary of Agriculture Sonny Perdue signed a proclamation to make nutrition requirements for school meals more flexible. This includes restoring local control of guidelines on whole grains, sodium and milk.[69]

Agricultural subsidies[]

Every five to seven years, Congress drafts legislation known as the United States Farm Bill. The farm bill is an umbrella that covers different bills affecting America's agriculture and food. It focuses on two major thrusts: "(1) food stamps and nutritional programs and (2) income and price supports for commodity crops."[70]

The farm bill has been touted as one of the biggest contributors to the ongoing obesity epidemic.[71] Over the past decade the government's farm policy focused on the overproduction and the reduction in prices of commodity crops such as corn and soybeans. Low commodity prices offer incentives for firms to create new ways to use the commodity crops. The low prices of corn and soybeans led to the creation of high fructose corn syrup and hydrogenated vegetable oils—ingredients that have been linked to obesity. Throughout the years these ingredients have become a major component of everyday food products. In 1998 over 11,000 food products were introduced to Americans. Out of these products about 75 percent of them were candies, condiments, cereals, and beverages-all foods high in added high fructose corn syrup.[72] Between 1974 and 2004, U.S. consumption of high fructose corn syrup increased over 1,000 percent.[73] Agricultural subsidies in other countries also tend to favor energy-dense crops.[74]

Unhealthy foods tend to be inexpensive when compared to their healthy counterparts. Because fruits and vegetables are not subsidized, the real cost of such crops have risen nearly 40 percent. On the other hand, the prices for soda, sweets, and fats and oils have declined due to the subsidy that the government provides for commodity crops.[75] "Currently the least expensive food available is also the most caloric and the least nutritious: a dollar's worth of cookies or potato chips yields 1200 calories, while a dollar's worth of carrots yields only 250 calories."[76]

The farm bill contributes to the low prices that fast food provides because farmers feed the commodity crops to the cows and livestock that people eventually eat. Essential nutrients are taken away when cows are fed corn and/or soybeans instead of their natural grass diet. "Grass-fed beef has been shown to be higher in health-promoting nutrients, omega-3 fatty acids and cancer-fighting conjugated linoleic acid (cla) than beef that is fed grain."[77] Because the government provides a subsidy for the corn and soybeans that feed the cows, they essentially provide a subsidy for grain-fed livestock. As a result, it becomes difficult for farmers to raise grass-fed livestock due to the fact that they have to compete with livestock producers that have a quicker turn-around.

Another way the federal government has combated obesity is through the Farm Bill of 2008. The farm bill is reauthorized every 5 to 7 years and has been used to improve food security and nutrition since 1933.[78] Throughout the years food security and obesity have been interrelated issues and low-income families have borne the brunt of this problem, often relying on inexpensive, but high-calorie, low-nutrient foods. These diets have contributed to poor nutrition, cardiovascular problems, diabetes, and child development issues. Part of the Farm Bill of 2008 funded community gardens especially in low income neighborhoods to promote healthy eating. A Michigan study of 766 adults in low income neighborhoods showed that community garden participants were 3.5 times more likely to consume fruits and vegetables at least 5 times each day, as well as to consume more than 1.4 times the amount of fruits and vegetables than those who did not participate in community gardening.[1]

This bill has also attempted to lower the cost of purchasing vegetables; researchers found that lowering the cost of vegetables by just 10% would translate into people purchasing at least 7% more produce bought by low income families. Children who participate in a community garden tend to eat healthier and become interested in farming and eating locally grown food which is healthier than buying from a convenience store.[78]

Food movement solutions[]

Food justice[]

The food justice movement works to address the obesity epidemic by promoting access to affordable and healthy food to communities. Underlying this discourse is the belief that healthy food is a right of every person regardless of race, ethnicity, socioeconomic status, or community. The New York-based non-profit organization Just Food defines food justice as "communities exercising their right to grow, sell, and eat healthy food."[79] As a potential remedy for obesity, food justice advocates are in favor of providing affordable, quality food through community supported agriculture and the slow food movement.[80] Proponents of the food justice discourse seek to empower historically disadvantaged communities and groups by advocating equal access to healthy food for all people. Some critics of this discourse commend the movement for making healthy food more accessible but are critical of the fact that it does not call into question the structural dynamics that make obesity a likely risk for many of people.[81] It offers alternative food as a solution to obesity but does not consider how food itself is produced and who is involved in production and consumption decisions.

Food sovereignty[]

The food sovereignty movement seeks to increase empowerment fostered by the food justice movement in addition to addressing structural issues of the food system by advocating for healthy food as a right and for the right of people and countries to actively participate in decisions of food production and consumption (i.e. the food system as a whole). It seeks to empower those most affected and at risk from the obesity epidemic by including them in the process of creating and implementing alternatives to the current food system. Leading food sovereignty organization Via Campesina defines food sovereignty as "the peoples', countries', or State Unions' right to define their agricultural and food policy..."[82] Adopting the food sovereignty discourse is one channel by which to lower the percentage of overweight and obese, particularly in countries that receive food aid and technology from industrialized nations in the form of grain and pesticides containing possible obesogens.

See also[]

Transport:

References[]

  1. ^ a b Alaimo, Katherine; Packnett, Elizabeth; Miles, Richard A.; Kruger, Daniel J. (March 2008). "Fruit and Vegetable Intake among Urban Community Gardeners". Journal of Nutrition Education and Behavior. 40 (2): 94–101. doi:10.1016/j.jneb.2006.12.003. ISSN 1499-4046. PMID 18314085.
  2. ^ CDC (2020-02-27). "Obesity is a Common, Serious, and Costly Disease". Centers for Disease Control and Prevention. Retrieved 2020-05-01.
  3. ^ Stoll, Basil A. (1989), "Does the Mind Affect Cancer Risk?", Social Dilemmas in Cancer Prevention, Macmillan Education UK, pp. 103–114, doi:10.1007/978-1-349-10708-7_10, ISBN 978-1-349-10710-0
  4. ^ Klimentidis, Y. C.; Beasley, T. M.; Lin, H.-Y.; Murati, G.; Glass, G. E.; Guyton, M.; Newton, W.; Jorgensen, M.; Heymsfield, S. B.; Kemnitz, J.; Fairbanks, L.; Allison, D. B. (24 November 2010). "Canaries in the coal mine: a cross-species analysis of the plurality of obesity epidemics". Proceedings of the Royal Society B: Biological Sciences. 278 (1712): 1626–1632. doi:10.1098/rspb.2010.1890. PMC 3081766. PMID 21106594.
  5. ^ Lustig, Robert H (August 2006). "Childhood obesity: behavioral aberration or biochemical drive? Reinterpreting the First Law of Thermodynamics". Nature Clinical Practice Endocrinology & Metabolism. 2 (8): 447–458. doi:10.1038/ncpendmet0220. PMID 16932334. S2CID 6282659.
  6. ^ Grün, Felix; Blumberg, Bruce (June 2006). "Environmental Obesogens: Organotins and Endocrine Disruption via Nuclear Receptor Signaling". Endocrinology. 147 (6): s50–s55. doi:10.1210/en.2005-1129. PMID 16690801.
  7. ^ a b c Holtcamp, Wendee (1 February 2012). "Obesogens: An Environmental Link to Obesity". Environmental Health Perspectives. 120 (2): a62–a68. doi:10.1289/ehp.120-a62. PMC 3279464. PMID 22296745.
  8. ^ Stahlhut, Richard W.; van Wijngaarden, Edwin; Dye, Timothy D.; Cook, Stephen; Swan, Shanna H. (14 March 2007). "Concentrations of Urinary Phthalate Metabolites Are Associated with Increased Waist Circumference and Insulin Resistance in Adult U.S. Males". Environmental Health Perspectives. 115 (6): 876–882. doi:10.1289/ehp.9882. PMC 1892109. PMID 17589594.
  9. ^ Guthman, Julie (2011). Weighing in obesity, food justice, and the limits of capitalism. Berkeley, CA: University of California Press. pp. 105–106. ISBN 978-0-520-26625-4.
  10. ^ "Obesity Rates By Country 2021". worldpopulationreview.com. Retrieved 2021-10-20.
  11. ^ "Adult Obesity Facts | Overweight & Obesity | CDC". www.cdc.gov. 2019-01-31. Retrieved 2019-11-18.
  12. ^ "Compared with whites, Blacks had 51% higher and Hispanics had 21% higher obesity rates". Centers for Disease Control and Prevention. Retrieved 8 April 2014.
  13. ^ Khan, Unab I.; Wang, Dan; Sowers, Maryfran R.; Mancuso, Peter; Everson-Rose, Susan A.; Scherer, Philipp E.; Wildman, Rachel P. (September 2012). "Race–ethnic differences in adipokine levels: the Study of Women's Health Across the Nation (SWAN)". Metabolism. 61 (9): 1261–1269. doi:10.1016/j.metabol.2012.02.005. PMC 3404256. PMID 22444780.
  14. ^ Monda, Keri L; Chen, Gary K; Taylor, Kira C; Palmer, Cameron; Edwards, Todd L; Lange, Leslie A; Ng, Maggie C Y; Adeyemo, Adebowale A; Allison, Matthew A; Bielak, Lawrence F; Chen, Guanjie; et al. (14 April 2013). "A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry". Nature Genetics. 45 (6): 690–696. doi:10.1038/ng.2608. PMC 3694490. PMID 23583978.
  15. ^ "Genetic discovery found to influence obesity in people of African ancestry". Retrieved 8 April 2014.
  16. ^ Burke, Mary A.; Heiland, Frank (2008). "Race, Obesity, and the Puzzle of Gender Specificity" (PDF). doi:10.2139/ssrn.1324342. S2CID 154273450. Cite journal requires |journal= (help)
  17. ^ Bacha, F; Saad, R; Gungor, N; Janosky, J; Arslanian, SA (Jun 2003). "Obesity, regional fat distribution, and syndrome X in obese black versus white adolescents: race differential in diabetogenic and atherogenic risk factors". The Journal of Clinical Endocrinology and Metabolism. 88 (6): 2534–40. doi:10.1210/jc.2002-021267. PMID 12788850.
  18. ^ Kirby, James; Lan Liang; Hsin-Jen Chen; Youfa Wang (2012). "Race, place, and obesity: the complex relationships among community racial/ethnic composition, individual race/ethnicity, and obesity in the United States". American Journal of Public Health. 102 (8): 1572–1578. doi:10.2105/ajph.2011.300452. PMC 3464818. PMID 22698012.
  19. ^ Scharoun-Lee, M; JS Kaufman; BM Popkin; P Gordon-Larsen (February 2009). "Obesity, race/ethnicity and life course socioeconomic status". Journal of Epidemiology and Community Health. 63 (2): 133–139. doi:10.1136/jech.2008.075721. PMC 2627789. PMID 18977809.
  20. ^ Chernov, Andrea E. "Weight Discrimination: The Effects of Obesity on Employment and Promotion". University of Hawaii at Hilo. 4 (23).
  21. ^ Carels, R. A.; Hinman, N. G.; Burmeister, J. M.; Hoffmann, D. A.; Ashrafioun, L.; Koball, A. M. (2013). "Stereotypical images and implicit weight bias in overweight/Obese people". Eating and Weight Disorders. 18 (4): 10.1007/s40519-013–0072–5. doi:10.1007/s40519-013-0072-5. PMC 3864577. PMID 24057679.
  22. ^ a b c Puhl, Rebecca M.; Heuer, Chelsea A. (May 2009). "The Stigma of Obesity: A Review and Update". Obesity. 17 (5): 941–964. doi:10.1038/oby.2008.636. PMID 19165161. S2CID 152352.
  23. ^ Sutin, Angelina R.; Terracciano, Antonio; Newton, Robert L. (24 July 2013). "Perceived Weight Discrimination and Obesity". PLOS ONE. 8 (7): e70048. Bibcode:2013PLoSO...870048S. doi:10.1371/journal.pone.0070048. PMC 3722198. PMID 23894586.
  24. ^ Bradshaw, Tim; Mairs, Hilary (2014). "Obesity and Serious Mental III Health: A Critical Review of the Literature". Healthcare. 2 (2): 166–182. doi:10.3390/healthcare2020166. PMC 4934464. PMID 27429268.
  25. ^ Collingwood, J. (2016, December 17). Obesity and Mental Health | Psych Central. Retrieved December 06, 2016, from http://psychcentral.com/lib/obesity-and-mental-health/
  26. ^ Magazine, C. (2012). Obesity and Mental Illness: Addressing a Double Epidemic. Retrieved December 06, 2016, from http://www.obesitynetwork.ca/Obesity-and-Mental-Illness-Addressing-a-Double-Epidemic-322
  27. ^ a b Walker, Karen E.; Amy J.A. Arbreton (March 1, 2004). After-School Pursuits: An Examination of outcomes in San Francisco Beacon Initiative (PDF). Philadelphia: Public/Private Ventures – via City of Madison.
  28. ^ Lauver, Sherri; Priscilla M.D. Little; Heather B. Weiss (July 2004). "Moving Beyond the Barriers: Attracting and Sustaining Youth Participation in Out-of-School Time Programs". Harvard Family Research Project. 6. Cite journal requires |journal= (help)
  29. ^ Lerman, Robert I. "Are Teens in Low-Income and Welfare Families Working Too Much". An Urban Institute Program to Assess Changing Social Policies. Retrieved 9 April 2014.
  30. ^ "Fast Food FACTS in Brief". Fast Food F.a.c.t.s Food Advertising to Children and Teens Score. Retrieved 7 May 2014.
  31. ^ "Obesity & Genetics". Centers for Disease Control and Prevention. 19 Jan 2010. Retrieved 6 May 2014.
  32. ^ Bhanpuri, Hoor (October 2005). Gahala, Jan (ed.). "ENSURING EQUITY, ACCESS, AND QUALITY IN 21ST CENTURY COMMUNITY LEARNING CENTERS". Learning Point Associates. Naperville, IL (19).
  33. ^ Beckett, Susan Bodilly, Megan (2005). Making out-of-school-time matter : evidence for action agenda (PDF) ([Online-Ausg.] ed.). Santa Monica, CA: Rand Corp. ISBN 0-8330-3734-X.
  34. ^ Halpern, Robert (Fall 1999). "After-School Programs for Low-Income Children: Promise and Challenges". The Future of Children. 9 (2): 81–95. doi:10.2307/1602708. JSTOR 1602708. PMID 10646261.
  35. ^ Duffett, Ann; Jean Johnson (2004). Teaching interrupted : do discipline policies in today's public schools foster the common good?. with Steve Farkas, Susanna Kung and Amber Ott. New York, NY: Public Agenda. ISBN 1-889483-85-0.
  36. ^ Grossman, Jean Baldwin; Karen Walker; Rebecca Raley. "Challenges and Opportunities in After-School Programs: Lessons for Policymakers and Funders" (PDF). Public/Private Ventures. Retrieved 9 April 2014.
  37. ^ James-Burdumy, Susane; Mark Dynarski; Mary Moore; John Deke; Wendy Mansfield (April 2005). "When Schools Stay Open Late: The National Evaluation of the 21st Century Community Learning Centers Program". Final Report. U.S. Department of Education/ Institute of Education Science National Center for Education Evaluation and Regional Assistance (NCEE).
  38. ^ Swinburn, Boyd; Egger, Gerry; Raza, Fezeela (1999). "Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity". Preventive Medicine. 29 (6): 563–570. doi:10.1006/pmed.1999.0585. PMID 10600438.
  39. ^ Präger, Maximilian; Kurz, Christoph; Böhm, Julian; Laxy, Michael; Maier, Werner (7 June 2019). "Using data from online geocoding services for the assessment of environmental obesogenic factors: a feasibility study". International Journal of Health Geographics. 18 (13): 13. doi:10.1186/s12942-019-0177-9. PMC 6555943. PMID 31174531.
  40. ^ Brewis, A. A. (2011). Obesity and Human Development. Rutgers University Press.
  41. ^ News, Maggie Fox NBC (2012-08-23). "Spending on technology equals more obesity, study shows". msnbc.com. Retrieved 2019-11-08.
  42. ^ a b c Fox, M. (2013, August 23). Spending Money On Technology Equals More Obesity, Study Shows. Retrieved November 29, 2016, from http://www.nbcnews.com/id/48757019/ns/health-fitness/t/spending-technology-equals-more-obesity-study-shows/#.WEcQ_1zMzjQ
  43. ^ Kaiser, Carla (January 2009). "Healthy Food Access in Minneapolis: Initial Conversations with Residents" (PDF). Institute for Agriculture and Trade Policy. Minneapolis, Minnesota. Retrieved 9 April 2014.
  44. ^ Powell, Lisa M.; Slater, Sandy; Mirtcheva, Donka; Bao, Yanjun; Chaloupka, Frank J. (2007). "Food Store Availability and Neighborhood Characteristics in the United States". Preventive Medicine. 44 (3): 189–195. doi:10.1016/j.ypmed.2006.08.008. PMID 16997358 – via Elsevier ScienceDirect.
  45. ^ Moore, Latetia V; Ana V. Diez Roux (February 2006). "Associations of Neighborhood Characteristics With the Location and Type of Food Stores". American Journal of Public Health. 96 (2): 325–331. doi:10.2105/AJPH.2004.058040. PMC 1470485. PMID 16380567.
  46. ^ Ghosh-Dastidar, Bonnie; Cohen, Deborah; Hunter, Gerald; Zenk, Shannon N.; Huang, Christina; Beckman, Robin; Dubowitz, Tamara (November 2014). "Distance to Store, Food Prices, and Obesity in Urban Food Deserts". American Journal of Preventive Medicine. 47 (5): 587–595. doi:10.1016/j.amepre.2014.07.005. ISSN 0749-3797. PMC 4205193. PMID 25217097.
  47. ^ Shaffer, Amanda; Robert Gottlieb (May 2002). "The Persistence of L.A.'s Grocery Gap: The Need for a New Food Policy and Approach to Market Development". Center for Food and Justice. Retrieved 9 April 2014.
  48. ^ Helling, Amy; David Sawicki (2003). "Race and Residential Accessibility to Shopping and Services". Housing Policy Debate. 14 (1–2): 69–102. doi:10.1080/10511482.2003.9521469. S2CID 154045870.
  49. ^ "Bridging the Divide: Growing Self-Sufficiency in Our Food Supply" (PDF). Community Food Assessment, A Regional Approach for Food Sysyems in Louisville, Kentucky. Louisville, Kentucky: Community Farm Alliance. Retrieved 9 April 2014.
  50. ^ "Healthy Food, Healthy Communities: An Assessment and Scorecard of Community Food Security In the District of Columbia" (PDF). D.C. Hunger Solutions. Retrieved 9 April 2014.
  51. ^ Manjarrez, Carlos A.; Jessica Cigna (June 2006). "Food Stamp Participation and Market Access in the District of Columbia" (PDF). The Urban Institute (3). Retrieved 9 April 2014.
  52. ^ Bodor, J Nicholas; Donald Rose; Tomas A Farley; Christopher Swalm; Susanna K Scott (April 2008). "Neighborhood Fruit and Vegetable Availability and Consumption: The Role of Small Food Stores in an Urban Environment". Public Health Nutrition. 11 (4): 413–420. doi:10.1017/S1368980007000493. PMID 17617930.
  53. ^ CHUNG, CHANJIN; MYERS, SAMUEL L. (December 1999). "Do the Poor Pay More for Food? An Analysis of Grocery Store Availability and Food Price Disparities". Journal of Consumer Affairs. 33 (2): 276–296. doi:10.1111/j.1745-6606.1999.tb00071.x. S2CID 154911489.
  54. ^ Hosler, Akiko S.; Deepa Varadarajulu; Adrienne E. Ronsani; Bonnie L. Fredrick; Brian Fisher (November–December 2006). "Low-Fat Milk and High-Fiber Bread Availability in Food Stores in Urban and Rural Communities". Journal of Public Health Management and Practice. 12 (6): 556–562. doi:10.1097/00124784-200611000-00009. PMID 17041304.
  55. ^ Sloane, David C.; Diamant, Allison L.; Lewis, LaVonna B.; Yancey, Antronette K.; Flynn, Gwendolyn; Nascimento, Lori Miller; McCarthy, William J.; Guinyard, Joyce Jones; Cousineau, Michael R. (July 2003). "Improving the nutritional resource environment for healthy living through community-based participatory research". Journal of General Internal Medicine. 18 (7): 568–575. doi:10.1046/j.1525-1497.2003.21022.x. PMC 1494887. PMID 12848840.
  56. ^ Russ, Lopez (2007). Lopez, Russ P.. "Neighborhood Risk Factors For Obesity. Obesity. pp. 2111–2119.
  57. ^ Shaffer, Amanda (2002). The Persistence of L.A's Grocery Gap: The Need for a New Food Policy and Approach to Market Development.
  58. ^ a b Feldstein, Lisa (2010). You Eat Where You are. Cognella. San Diego, CA. pp. 1–28.
  59. ^ Jetter, K, 30.1 (2006): 38-44. Print.
  60. ^ "Chain Reaction: Income, Race, and Access to Chicago's Major Player Grocers". Metropolitan Chicago Information Center. Retrieved 29 April 2014.
  61. ^ "Center for Nutrition Policy and Promotion" (PDF). USDA. Retrieved 25 April 2014.
  62. ^ "McDonald's USA". Retrieved 24 April 2014.
  63. ^ Ford, Paula B (2008). "Disparities in obesity prevalence due to variation in the retail food environment: three testable hypotheses". Nutrition Reviews. 66 (4): 216–228. doi:10.1111/j.1753-4887.2008.00026.x. PMID 18366535.
  64. ^ a b c Plough, Alonzo L. (August 2013), "Promoting Social Justice Through Public Health Policies, Programs, and Services", Social Injustice and Public Health, Oxford University Press, pp. 421–435, doi:10.1093/med/9780199939220.003.0023, ISBN 978-0-19-993922-0
  65. ^ Duggleby, R. G.; Kaplan, H. (1975-11-18). "A competitive labeling method for the determination of the chemical properties of solitary functional groups in proteins". Biochemistry. 14 (23): 5168–5175. doi:10.1021/bi00694a023. ISSN 0006-2960. PMID 42.
  66. ^ "School Health Guidelines | Healthy Schools | CDC". www.cdc.gov. 2019-09-23. Retrieved 2020-05-01.
  67. ^ "- HeinOnline.org". heinonline.org. Retrieved 2020-05-01.
  68. ^ Berger, Aaron T.; Widome, Rachel; Erickson, Darin J.; Laska, Melissa N.; Harnack, Lisa J. (2019-09-08). "Changes in association between school meals and children's dietary quality during implementation of the Healthy, Hunger-Free Kids Act of 2010". medRxiv. doi:10.1101/19005579. S2CID 203813028.
  69. ^ Campbell, John L. (2018-05-24). "Make America Great Again". Oxford Scholarship Online. doi:10.1093/oso/9780190872434.003.0002.
  70. ^ ; (2012). Food fight: the citizen's guide to the next food and farm bill. Healdsburg, Calif.: Watershed Media.
  71. ^ Foster, Julie (2011). "SUBSIDIZING FAT: HOW THE 2012 FARM BILL CAN ADDRESS AMERICA'S OBESITY EPIDEMIC". Comment. 160 (1): 235–276.
  72. ^ Nestle, Marion (2002). Food politics: how the food industry influences nutrition and health. Berkeley: University of California Press. ISBN 978-0-520-22465-0.
  73. ^ Bray, George A; Samara Joy Nielsen; Barry M Popkin (2004). "Consumption of high-fructose corn syrup in beverages may play a role in the epidemic of obesity". American Journal of Clinical Nutrition. 79 (4): 537–543. doi:10.1093/ajcn/79.4.537. PMID 15051594.
  74. ^ "FRAC Food Research and Action Center". frac.org. Archived from the original on 14 September 2012. Retrieved 7 April 2018.
  75. ^ "Converted to real dollars". Data from USDA ERS FoodReview. 25 (3).
  76. ^ Drewnowski, Adam; SE Specter (2004). "Poverty and obesity: the role of energy density and energy costs". American Society for Clinical Nutrition. 79 (1): 6–16. doi:10.1093/ajcn/79.1.6. PMID 14684391.
  77. ^ Severe, J. "Grass-Fed vs. Conventionally Fed Beef" (PDF). Utah State University. Retrieved 1 May 2014.
  78. ^ a b Kaiser, Michelle L. (August 2013). "Prioritizing Health and Community Food Security Through the Farm Bill". Social Work in Public Health. 28 (5): 509–519. doi:10.1080/19371918.2011.592088. ISSN 1937-1918. PMID 23805805. S2CID 21176073.
  79. ^ "Archived copy". Archived from the original on 2014-04-08. Retrieved 2014-05-07.CS1 maint: archived copy as title (link)
  80. ^ Holt-Gimenez, Eric; Yi Wang (2011). "Reform or transformation? The pivotal role of Food Justice in the movement". Race/Ethnicity: Multidisciplinary Global Contexts. 5 (1). doi:10.2979/racethmulglocon.5.1.83. S2CID 4223765.
  81. ^ Guthman, Julie (2011). Weighing in obesity, food justice, and the limits of capitalism. Berkeley, CA: University of California Press. p. 141. ISBN 978-0-520-26625-4.
  82. ^ Patel, Raj (2008). Stuffed and starved : the hidden battle for the world food system. Brooklyn, N.Y.: Melville House Pub. ISBN 978-1-933633-49-7.
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