The Most Damaging Impact Caused by Obesity and Weight Bias

Causes

Obesity is characterized as a chronic condition as the result of an excess amount of body fat and it is defined by body mass index (BMI). A person’s BMI is determined by their height and weight (Balentine, 2019). However, to properly understand the impact of obesity, we need to look at what actually causes obesity in the first place:

One of the main causes is genetic influence. Several genes contribute to weight gain and body fat distribution; in fact, over 400 different genes are connected to being overweight or obese – they affect appetite, satiety, metabolism and even the tendency to use eating as a way to cope with stress (Harvard Medical School, 2009). The genetic causes of obesity can be broadly classified into different sections. Monogenic obesity is caused by a single gene mutation (Thaker, 2017). For example, mutations in the genes encoding leptin and leptin receptors were found in two severely obese cousins, and further research showed that leptin and leptin receptor – deficient patients exhibited severe weight gain, which resulted in severe obesity (Farooqi & O'Rahilly, 2006). This result is understandable as leptin is a hormone that regulates appetite, food intake and satiety, and so clearly, an absence would lead to constant hunger and weight gain. Another section is syndromic obesity, which is obesity that is associated with clinical phenotypes, which can include organ-system specific abnormalities and intellectual disability. The two most common forms of syndromic obesity are Bardet-Biedl syndrome and Prader Willi syndrome (Thaker, 2017). Bardet-Biedl syndrome is a genetic condition where mutations damage the structure and function of cilia and can cause vision loss, learning difficulties and abnormal weight gain. (Genetics Home Reference, 2020). Prader Willi syndrome is a genetic disorder due to the loss of function of specific genes and causes restricted growth and constant hunger, ultimately leading to type 2 diabetes and obesity (Genetics Home Reference, 2020). However, whilst genes do play a significant role in the development of the body, the Harvard School of Public Health (HSPH) claim that genes associated with obesity play a small part in the overall risk (Legg, 2016). This means that even if a person carries a gene linked to obesity, they do not necessarily become obese, and vice versa, leading to the belief that genetics have a smaller role in obesity compared to others such as environmental.

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There are also many environmental influences on obesity. For example, urbanization has a large role in an obesogenic environment. Studies have shown that in communities that have low economic infrastructure and unsafe/inaccessible play areas, children are unable to perform the physical activity required for healthy development and so obese individuals are more prevalent in these areas (Pirgon & Aslan, 2015). It is common knowledge that physical activity is a must in order to live a healthy and balanced lifestyle, and so by not having the adequate structures for this, adults and children alike are practically being denied the right to live healthily, especially if they cannot afford luxuries such as a gym membership or a nearby leisure centre. Moreover, areas that have been highly urbanized, for example some major cities in Turkey, have diminished access to physical and sporting activities, and this leads to more people living a sedentary lifestyle, which increases the risk of obesity – in the UK , people are 20% less active now than in the 1960s, which is correlated with the increase of obesity over the past years (Fenton, 2017). This is in opposition to areas that have more parks and walking areas, where it is easier for children to lose weight (Pirgon & Aslan, 2015), showing that in order to help prevent an increase in obesity, consideration of public health and activity needs to be taken in urban planning of communities.

Obesity can also be linked to economic disparities as obesity is not evenly distributed across socio-demographic groups. In the UK, obesity rates are highest for children from the most deprived areas (Fenton, 2017). In these areas (which happen to be situated in a highly obesogenic environment), calorie-rich foods are available all around: meal deals in supermarkets, cheap sweets at the corner store and most importantly, fast food restaurants. Public Health England (PHE) has found that 17% of all fast food outlets are in the top 10% most deprived areas in the UK, similar to results showing that areas with the lowest earnings, such as Huddersfield, have the highest density of fast food restaurants (Magrini, 2018). This increase in consumption of out-of-home meals that have a high fat, sugar and salt content lead to an increase in obesity, especially in socially deprived areas, which would also probably not have any proper access to a form a physical activity.

Another thing that may prevent people from being physically active is technology. Research has shown that there is a relationship between screen media exposure and obesity. One example is a longitudinal study of a sample of US 10 – 15 year-olds, where there was a strong relationship between the number of hours that television was watched per day and the prevalence of overweight (Gortmaker, et al., 1996). The reason for this effect on obesity is that technology displaces physical activity as it takes up people’s time, especially if they work jobs that require them to be sitting around computers for most of the day, leading them to a sedentary lifestyle. However, it is difficult to accurately measure the relationship between screen time and physical activity – studies where screen time is reduced have only increased the amount of physical activity by a small portion (Ramsey Buchanan, et al., 2016), suggesting that displacement of physical activity is not a strong enough link between screen time and obesity. In fact, there is more evidence to support that screen media increases energy intake as children consume up to a third of their daily calorie intake in front of the screen (Robinson, et al., 2017). This could be because of how foods, especially more calorie-dense foods, are marketed on television advertisements, movies and social media etc., which encourages children to consume more food, and this, with the addition of less physical activity, would eventually result in obesity.

There are many other causes of obesity such as psychological trauma, where overeating is used as a coping mechanism to deal with events from the past (Leon & Roth, 1977), the side effects of medication such as antidepressants and some oral contraceptives, and hormone levels. Nevertheless, by covering some of the main causes of obesity, it will be much easier to be able to understand and evaluate its effects along with the effects of weight bias.

Costs

It is obvious that one of the largest impacts that obesity has on society is its costs. Obesity itself does not have a large impact on the costs, but rather it is the obesity and overweight – related health issues that do. In 2014/2015, the NHS spent around £6.1 billion on these issues (Fenton, 2017), which includes diabetes, coronary heart disease and even cancer. Cancer itself costs £9.4 billion (NHS, 2011), and so an increase in obesity (and eventually cancer) would lead to an increase of costs for the NHS. Data shows that there was an 18% increase in admissions for obesity treatment such as sleeve gastrectomy (reducing stomach size by 15%) or conditions or even complicated by obesity, including heart disease and cancer (Boseley, 2018) and with the NHS already under so much pressure due to being understaffed, an ageing population and the lack of beds, the increase in obesity-related health illnesses will put even more of a strain on the NHS, possibly even taking them into further debt. The most shocking (possibly even upsetting) element of all this is that obesity is a highly preventable disease; although there are genetic elements to becoming overweight, like we saw before, it is mostly due to the obesogenic environment that a majority of the world’s urban population lives in, and therefore there could have been the possibility that the cost of obesity and overweight-related issues could have been reduced, placing less pressure on the NHS and using some of these funds on other segments of healthcare and society e.g. the police service.

It is also shown that the amount spent on the treatment of obesity and diabetes is greater than amount spent on police, fire service and judicial system combined (Fenton, 2017). This clearly would lead to a rise in crime, the chance that calls do not get answered as quickly and officers are not as fast as responding to emergencies (Dodd, 2018) causing fewer crimes such as thefts from being investigated and so fewer offenders are brought to justice, making some areas less safe. We can therefore clearly see how this large economic cost can even lead to societal impacts, showing the damaging impact obesity has on society in relation to its costs, yet this estimate may not be entirely true.

On one hand, it is possible that the costs of obesity on the NHS have been largely miscalculated. The estimates may not be balanced cost-effective analyses, where £3.6 billion is saved on pensions and healthcare from the 7.1% of early deaths attributable to high BMIs (Owens, 2019) which means that the costs may actually be £2.47 billion per year – 2.3% of the estimated budget. The almost “exaggeration” of the estimate could be seen as propaganda put out by public health campaigners and politicians in order to gain media attention and cause an uproar, and though their intentions are good, these tactics incite a climate of resentment against obese people (BBC, 2015), which evidently enforces weight bias within society. However, on the other, there is not much research to back these claims up, and so the NHS’s original £6.1 billion spent on obesity-related illnesses estimate is considered to be the correct one.

Not only would the cost of obesity include the NHS’s estimate, but also the approaches to reducing obesity. One major example is the sugar tax, officially named the “Soft Drinks Industry Levy”, which was introduced to the UK in 2018 as part of the government’s obesity strategy which aims to reduce sugar consumption by persuading companies to reformulate their high sugar brands and avoid paying the levy. There are obviously many benefits of the sugar tax as it provides incentive to reduce the consumption on sugary drinks, which enables higher spending on health care as it raises revenue and encourages companies to produce healthier snacks, but some economists see it as a regressive tax, where a higher percentage is taken from low-income groups and can also lead to job losses (Pettinger, 2019). However, these arguments are weak as people do not need to buy sugary drinks, they can always switch to alternatives to avoid the tax. Also, everyone, including those on low incomes, will benefit from the increased spending on healthcare and a better quality of life. Between April and October of 2018, £154 million was raised to fund school sports programs and breakfast clubs to help combat childhood obesity (Rathbone Greenbank Investments, 2019). The sugar tax provides strong social and economic benefits and will encourage a healthier lifestyle to help reduce the increase of obesity with minimal economic disruption. From this, we can conclude that there are efforts being put in place in order to reduce the economic impacts of obesity.

There are also many other techniques that the government is putting in place to reduce obesity as it is suggested that obesity prevention could result in cost savings. For example, food labels are clearer and more consistent so that people are able to understand what are in the products they are consuming (Diabetes UK, n.d.). They are restricting price promotions on unhealthy foods so as to convince the public that unhealthy food is not the cheaper option; this is significantly important for those in low income families as they are then able to buy healthier foods instead of opting to buy what is on a deal. There are many more incentives put in place to reduce the costs, and although it is not a cure for increasing health expenditures, obesity prevention could possibly be a cost-effective way of improving mental health. We can then clearly see that since there are efforts put in place to reduce the costs, and so in the near future, the cost of obesity-related illnesses could be reduced.

Overall, we can see that obesity costs a lot on the NHS, and due to the increase of overweigh-related diseases, more pressure will be placed on the NHS. As shown in Figure 1, along with smoking and war, obesity is one of the most expensive manmade burdens that needs to be confronted before allowing the costs to become insurmountable as it is already 3% of the UK’s GDP. Weight bias, however, does not really have an impact on the economy and costs, but it does have an impact on other parts of society.

Physical Health

It is common knowledge that obesity impacts physical health and leads to many illnesses. One example of this is obstructive sleep apnea (OSA), which is a breathing problem that happens during sleep where the throat closes completely and the airway collapses, stopping air from travelling to and from the lungs for ten seconds or more, at least a hundred times a night. Research shows that there is a linear correlation between OSA and obesity (Jehan, et al., 2017) and that at least 45% of obese subjects suffer from it (Young, et al., 1993), showing that as weight increases, the risk for obstructive sleep apnea also increases. The narrowing of the upper respiratory muscles in obese individuals occurs due to the accumulation of fatty tissues, and the obstruction of breathing due to the narrowing of the upper airway leads to a marked increase of pressure in the thorax, triggering apnea. OSA interferes with a person’s life, causing them to become more tired and fatigued throughout the day, making it more difficult to concentrate on work and can even make people feel moody and quick-tempered, which can damage people’s relationships with their peers. A lack of sleep weakens the immune system, leaving those with OSA more vulnerable to illness. However, the most significant danger of OSA is that it could lead to metabolic syndrome, a disorder that includes high blood pressure, abnormal cholesterol levels and high blood sugar, all of which would lead to a higher risk of heart disease. Having OSA increases the risk of high blood pressure as sudden drops in blood oxygen levels that occur during sleep apnea increase the blood pressure and can strain the cardiovascular system (Mayo Clinic Staff, 2018). All of this evidence is important in demonstrating how obesity can lead to many other conditions that can have grave impact on a person’s life.

There is also a link between obesity and asthma. Epidemiological studies of asthma and obesity have clearly shown that obesity is more likely to occur in obese patients, and this does not differ between the sexes (Sutherland, 2014). There is also evidence of a dose-responsive relationship, with the odds of developing asthma increasing as BMI increases (Beuther & Sutherland, 2011). There are also physiological mechanisms e.g. obesity alters lung mechanics, leading to symptoms of dyspnea, which is shortness of breath. The reduced airflow and a change in the compliance of the respiratory system is linked to a combination of excess soft-tissue weight compressing on the rib cage and fatty infiltration of the chest wall. These alterations lead obese individuals to breathe in reduced lung volumes, which may be one cause in the increase of dyspnea as there is an increase work of breathing (Sutherland, 2014). The asthma and dyspnea, like the obstructive sleep apnea, can have a very negative effect on a person’s life, as even simple activities such as walking up the stairs become a daily challenge. However, there is data that suggests that asthma might be over diagnosed in the obese population. Obese patients report more dyspnea and asthma-like symptoms than non-obese patients, which leads to misdiagnosis. Consequently, over diagnosis leads to an increase in the prevalence of asthma in developed countries (Aaron, et al., 2008), meaning that more healthcare services and money is spent on asthma, even though it is not required.