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The Other Pandemic: Obesity Anastasia Economou Introduction The other pandemic: Obesity Anastasia Economou Introduction Obesity is defined as “abnormal or excessive fat accumulation that presents a risk to health” (World Health Organisation, [WHO], 2020). The Body Mass Index (BMI), weight is divided by height squared, is used to screen for obesity: a person ≥30 kg/m2 is ‘obese’; between 25 kg/m2 and 30 kg/m2 is ‘overweight’. In 2016, 1.6 billion adults (18 years +), were overweight, of which 650 million were obese. Obesity is a major burden of disease (WHO, 2020) not only in high-income countries, but also in low-income (e.g. Eritrea) and middle income countries (e.g. India) (Malik, Willett & Hu, 2013). Obesity has become a pandemic with projections pointing to 38% of Earth’s population becoming overweight and 20% obese by 2030 (Anekwe et al., 2020). Obesity in the UK is also on the rise: it affects 1 in 4 adults, 1 in 10 children aged 4-5, and 1 in 5 children aged 10-11 (NHS, 2020). 63% of adults and 33% of children leaving primary school are above a healthy weight (Public Health England, [PHE], 2020). Obesity is linked to a number of chronic and debilitating conditions like cardio- metabolic risk (CMR) (i.e. metabolic syndrome, diabetes, hypertension, dyslipidaemia, cardiovascular disease or stroke) and to conditions such as depression which can impact on an individual’s lifecycle. This paper will explore these links and further look at food insecurity and how it could contribute to obesity as well as how socioeconomic inequalities impact on this. It will then seek to evaluate the latest policy of the UK government on ‘Tackling Obesity: empowering adults and children to live healthier lives’ (UK Government, 2020) with a view to exploring whether this policy is appropriate in addressing food insecurity to prevent obesity. It will then conclude with some recommendations. Discussion Obesity imposes risks on cardio-metabolic health i.e. on the chances of developing metabolic syndrome, diabetes, hypertension, dyslipidaemia, cardiovascular disease or stroke (Malik et al., 2009). Four different phenotypes in obesity have been identified: a) Metabolically Healthy Obese (MHO) – have: Low Visceral Fat, High Fat Mass, High Insulin Resistance, High HDL and Low Triglycerides b) Metabolically Healthy – have: Low Visceral Fat, Low BMI, Low Fat Mass, High Lean Body Mass, High Insulin Sensitivity, Low Liver Fat, Low Triglycerides. c) Metabolically Obese Normal Weight (MONW) – have: High Visceral Fat, Low BMI, High Fat Mass, Low Lean Body Mass, Low Insulin Sensitivity, High Liver Fat, High Triglycerides. d) “At risk” obese – have: High Visceral Fat, High BMI, High Fat Mass, Low Insulin Sensitivity, Low HDL, High Triglycerides (Karelis, Brochu, Rabasa‐Lhoret, Garrel, & Poehlman, 2004). In order to identify when an individual runs a CMR, the use of BMI alone is not sufficient because it does not provide information about the fat distribution and concentration. Subcutaneous abdominal adipose tissue (SAAT) and internal (visceral and ectopic deposits i.e. into organs such as liver and pancreas, and around muscles) adipose tissue have been found to have very serious consequences for cardio metabolic health (Piche, Poirier, Lemieux & DesprѐMs, 2018, Thomas, Frost, Taylor-Robinson & Bell, 2012). Some studies have found that increased adiposity, without an increase in liver fat, does not cause metabolic syndrome (Magkos, 2019). Tomiyama, Hunger, Nguyen-Cuu and Wells (2016) found that half of overweight individuals, and 45% of obese individuals, were cardio-metabolically healthy while 30% of the study population who had ‘normal’ BMI were found to be cardio- metabolically unhealthy. 35% of all people with obesity in the world are metabolically healthy (Lin, Zhang Zheng & Zheng, 2017); they have half the risk of developing T2DM and CVD compared with metabolically unhealthy people with obesity but 50-300% increased risk when compared with metabolically healthy normal weight people. 50% of metabolically healthy obese people will become metabolically unhealthy within 10 yrs if they do not make lifestyle changes (Magkos, 2019). MONW is associated with significant cardiometabolic dysregulation (Karelis et al., 2004), including metabolic syndrome and CVD risk factors and increased CVD mortality in women (Romero-Corral et al., 2010). The MONW phenotype has been further investigated using Magnetic Resonance Imaging (MRI) and showed that many thin people carry more visceral adipose tissue (VAT) than overweight or obese people leading to the identification of the TOFI (thin-on-the-outside fat- on-the-inside) sub-phenotype which has been observed to also increase CMR (Thomas et al., 2012). Qualitative aspects of diet, type of foods and dietary patterns, may affect the development and distribution of VAT as well as the SAAT; with VAT being particularly impacted by the quality of diet and physical inactivity (Fischer, Pick, Moewes & Nöthlings, 2015) as well as ageing, sex hormones, dietary composition and genetic factors (Thomas et al., 2012). Depression has also been linked to obesity. Depression is “a common mental disorder that causes people to experience depressed mood, loss of interest or pleasure, feelings of guilt or low self-esteem, disturbed sleep or appetite, low energy and poor concentration” (MHF, 2016). Depression is the predominant mental health disorder – 3.4% world wide (out of 10.7% people with mental health disorder). In the UK, it affects 3% of males and 3.8% of females (MHF, 2016). In 2013, depression was the second leading cause for years lived with disability (WHO, 2018). Mental unwellness is the second-largest source of burden of disease in England (Mental Health First Aid England, 2020). Obesity can raise twice the risk of becoming depressed (Roberts, Deleger, Strawbridge & Kaplan, 2003) especially for women (Tyrrell et al., 2019; Pereira- Miranda, Costa, Queiroz, Pereira-Santos & Santana , 2016; Jung et al., 2017; Roberts et al., 2003), those of older age and those who have financial difficulties (Jung et al., 2017; Roberts et al., 2003). Obesity may lead to negative self- perception, restrictive diets and a vicious circle of weight loss and gain, binge eating and depression. Obese people can feel guilty and ashamed and may isolate themselves which enhances the risk of depression (Pereira-Miranda et al. 2016). They may experience stigmatisation in the community, by health professionals and in job settings which can exacerbate the negative feelings they already experience and lead to depression (Puhl, Himmelstein & Pearl, 2020; Puhl & Heuer, 2009). Eating foods high in saturated fat and glycaemic index may affect the function of the brain (Ouakinin, Barreira & Gois, 2018; Pereira-Miranda et al., 2016). It seems that women with obesity and depression experience more devaluation compared to women with only one condition. Individuals with a higher level of internalized stigma, ingrained in the public stigma, may face great health obstacles (Luck-Sikorski, Schomerus, Steffi & Riedel-Heller, 2016). Depression also has been found to increase the risk of obesity. Blaine (2008) report 1.8 times increase in the risk while De Wit et al. (2010) found an 18% increase and that the risk is more pronounced in women. Adolescent girls have 2.5 times increase in the risk of becoming obese adults. (Blaine, 2008; Hasler et al., 2005). Low mood and low energy can lead to less activity and thus, excess energy intake which leads in itself to obesity. Lack of energy and inability to concentrate on tasks (like cooking) may also lead to the consumption of low quality diet. Depression may lead to comfort food (Di Renzo et al., 2020; Jeffery et al., 2009) which is often high in refined sugars, saturated fat and calories and can lead to weight gain. There also has been found a reciprocal association between obesity and depression. The findings regarding the risk vary. Luppino et al., (2010) found the risk for people with obesity to develop depression was 55% while the risk for people with depression to develop obesity was 58%. Mannan, Mamun, Doi and Clavarino (2016) found that depressed people had a 37% increased risk of being obese while 18% of obese people had an increased risk of being depressed and that in 10 year follow-up, the bi-directional relationship was even stronger for both men and women perhaps due to lifestyle and environmental influences. The bi-directional association is more likely in women (Rajan & Menon, 2017). Pan et al. (2012) found this in middle-aged and older women while Mannan et al., (2016) observed it in women aged 18-49. Women seem to be more vulnerable across their lifecycle than men to depression and obesity possibly due to biological, sociocultural, psychosocial and environmental influences (Morssinkhofa et al., 2020; Mannan et al., 2016). Stress can lead to depression (Le Moult, 2020) but stress is also linked to obesity (Tomiyama, 2019). It may be that there is a link between social and biological factors. The length of time may impact as well as strengthen the association between depression and obesity (Luppino et al., 2010). Mediouni, Madiouni and Kaczor-Urbanowicz (2020) propose the term ‘‘depreobesity’’ pointing to a modern epidemic characterised by the co- occurrence of depression and obesity. The relationship between obesity and depression is very complex and yet to be fully unravelled. There are social determinants of health and thus obesity (Marmot & Bell, 2019). These are the circumstances in which people are born, grow, live, work and age, and they “are influenced by the distribution of money, power and resources operating at global, national and local levels” WHO (2014, p.1). Food insecurity (FI) is a social determinant. The Food and Agriculture Organisation of the UN (2020) states that “A person is food insecure when they lack regular access to enough safe and nutritious food for normal growth and development and an active and healthy life. This may be due to unavailability of food and/or lack of resources to obtain food.
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