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 & Desprѐs, 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. Food insecurity can be experienced at different levels of severity”. Poor food quality is linked to FI which is a contributing factor for obesity (Brown et al., 2019). FI contributes to obesity in adults and especially women while it is linked to 22% increase in child obesity (Anekwe et al., 2020). In the US, FI is observed around the time people get their SNAP (Supplemental Nutritional Assistance Program) but the food intake decreases or people buy cheaper high in calories foods when SNAP is used up – this can contribute to unhealthy eating behaviours and obesity (Berry, 2020). In the US, 11% of the population was food insecure in 2017 (Anekwe et al., 2020). In 2016, 20.7% of adults in England, Northern Ireland and Wales were food insecure and 2.72% experienced severe FI – this affected the economically deprived groups (Loopstra, Reeves & Tarasuk, 2019). Yau, White, Hammond, White and Adams (2020) found 24·3% of the UK population to experience FI (and particularly women) and more likely to report unhealthy diet, poor general health, poor mental health, high stress and being overweight when compared to food secure people. The built environment (housing, transportation, workspace, leisure facilities) also contribute to accessibility or unavailability of quality food and physical activity; neighbourhoods where quality leisure facilities and quality food are accessible have populations with lower BMI (Anekwe et al., 2020; Malik et al., 2013). Obesity is prominent in socially disadvantaged groups such as ethnic/racial minorities, women and those from lower socioeconomic backgrounds (Anekwee et al., 2020; Malik et al., 2013). Obesity may also be a form of socioeconomic disadvantage since obese people have less well-paid jobs and encounter stigmatisation at work (Anekwe et al., 2020). Children from low socioeconomic status and especially girls in developed countries are found to be at higher risk of becoming obese (Ang, Wee, Ph & Ismail, 2013). Noonan (2018) found that UK adolescents at age 14 and especially girls living in poverty were more likely to be obese and overweight; they consumed more often sweetened drinks and fast foods than fresh fruit and vegetables. This is possibly due to the costs involved and availability of healthy food. In addition, elderly living in poverty are more likely to be obese than non-poor elderly (Salmasi & Celidoni, 2017) probably because they are unable to access nutritious food and appropriate physical activity. Low socioeconomic groups eat lower quantities of fruit and vegetables (Bambra et al., 2010). In England, families at the lower end of income would need to spend 70% of their income in order to eat healthy food. Eating of fruits and vegetables was also lowest in low-income countries when compared to high income countries. In 2016-17, 26% of school children in year 6 in the most deprived areas in England were obese when compared with 11% in the least deprived areas. Childhood obesity tends to carry on in adulthood (Marmot & Bell, 2019). Obesity amongst English adults in the most deprived areas is twice (36%) that of adults in the least deprived areas (Adams, 2020; HSE, 2018). Obesity is often described as an issue of ‘quantity’ i.e. high intake of energy v low intake of expenditure. However, it seems to be an issue of ‘quality’ of diet and physical activity (Adams, 2020). Children from lower socioeconomic backgrounds are not less active or eat more than children from higher socioeconomic backgrounds but they do not have access to high-intensity sports and quality food (Love, Adams, Atkin & van Sluijs, 2019). Since healthier foods are more expensive, poor people will look for cheaper lower quality foods (Adams, 2020). Health follows a social gradient i.e. better health with increasing socioeconomic position (Bambra et al., 2010) also, accessibility to resources is dependant on socioeconomic position of the individual (Adams, 2020; Berry, 2020). In the UK, a number of policies have been produced to address obesity over the years. Development of policies, including on obesity, are the product of the government of the day and their ideology (Adams, 2020). The policy on ‘Tackling obesity: empowering adults and children to live healthier lives’ was introduced in July 2020’ (UK Government, 2020). It advises on the government’s intention to focus on public health and prevention of obesity by providing tools to support individuals i.e. information, apps about healthy eating, a BMI calculator, a 12- week weight loss programme, links to private providers for weight loss. It presents the government’s intention to expand weight management services via the NHS for those most at risk, encourage GPs and Local Authorities (LAs) to expand their provision, introduce food labelling for food businesses with more than 250 employees, end promotion on foods high in fat, sugar and salt (HFSS) and ban adverts of HFSS foods before 9pm. Since 2013 the Public Health function in England is the responsibility of the LAs (not the NHS). The central government gives them funding to deliver mandatory and non-mandatory (e.g. obesity) health services which means that they may choose to do nothing about obesity despite being included in central government’s policy (Nobles et al, 2019). This can make redundant the whole endeavour of implementing an obesity policy at community level. It is encouraging that obesity is addressed by the ‘Tackling Obesity’ policy paper but the approach is similar to previous unsuccessful policies. Obesity, a population-wide problem, is presented as an individual’s responsibility: individuals need to change their behaviour and habits to reduce their excess weight (Ulijaszek & McLennan, 2016). The paper implies that the problem lies in people being unable to resist food adverts and promotions - it is will power which lets them down. It locates the issue in the imbalance of energy and makes ‘a call’ to overweight people to achieve a healthier weight absolving the rest of the society. It further suggests that people want more choices to support a healthy lifestyle – presenting obesity as an issue of ‘quantity’ instead of ‘quality’. People need access to quality food choices, something that is not addressed. FI is not acknowledged. In a consumerist society like the UK, the consumer is presented as having the freedom of choice, however, the power lies with the government, media and industry (Ulijaszek & McLennan, 2016). The paper states “we owe it to the NHS to move towards a healthier weight” which inevitably puts the onus and blame on the individual and not on the inadequacies of health policies and failing public services. Such an approach can add to the stigmatisation and marginalisation of overweight and obese people making them reluctant to engage with public health initiatives (Nature Reviews, 2020) The paper recognises the high rates of obesity in the population, its prevalence in deprived groups and especially children in these groups. However, it does not address how this has become an issue for these groups; what has put them in this situation. They are not talking about subsidising healthy food like fruit and vegetables. There is neither a recognition that healthy food is not accessible or available to these groups, nor the recognition of a lack of access to quality physical activity. There is no statement about how to make healthy food accessible and available to deprived people, nor a solution offered to making places conducive to a healthy lifestyle, reducing fast food outlets, improving green spaces and city planning (Malik et al., 2013). There is no intention to impose taxes on less healthy foods or to introduce sports subsidies and better welfare and employment policies (e.g. higher minimum wages, working hours directives and universal basic income) (Adams, 2020). The ‘Tackling Obesity’ policy is produced within the wider health crisis created by the COVID-19 pandemic which has been linked to higher severity and mortality amongst overweight and obese patients (Stefan, Birkenfeld, Schulze & Ludwig, 2020). It is difficult not to see this policy as an attempt to show that the government takes action to address the COVID-19 crisis and conceal their failings in the spread of the pandemic. The policy fails to embrace a whole- systems approach which is more likely to bring improvements by engaging partners in the community and stakeholders. It lacks coordination across the various sectors and government departments (Bagnall et al., 2019). Berry (2020) suggests a nine multilevel responsibility that could inform a successful policy approach: national, food system, education system, medical system, public health, local authority/municipality, society/community, parental and individual.

Conclusion Obesity is a pandemic affecting a large proportion of Earth’s population. It is a major burden of disease worldwide affecting the lives of individuals, their families and communities. Obesity is linked to cardio-metabolic risk, however, excess weight alone does not determine such risk for all individuals; the body composition and more specifically the distribution of VAT plays a key role (like in TOFIs who run cardio-metabolic risk). Depression, which is the predominant mental health disorder worldwide, is also linked to obesity; correlation has been found in either direction as well as reciprocity. These links affect people throughout their lifecycle. There are a number of economic, political, environmental and social factors or determinants that contribute to obesity; one such social factor is FI. People become food insecure when they do not have regular access or availability to nutritious and safe food. FI is found in low-income countries but also in high-income countries like the UK where approximately one quarter of the population worry about having regular access to food. People need quality food and quality physical activity in order to live a healthy life. Those from lower socioeconomic backgrounds are often deprived from both. The UK government policies, like ‘Tackling Obesity’ in 2020, put the responsibility of obesity on the individual and fail to address FI and deprivation. Looking ahead, research should further examine nutrition, physical activity and lifestyle of TOFI individuals to inform our understanding of the detrimental effects of the distribution of VAT. Longitudinal studies can be useful in looking at the links between obesity and depression at different observational points in individuals’ lifecycle so that targeted interventions can take place. Governments should take a whole-systems and multilevel approach in order to address successfully obesity. REFERENCES Adams, J. (2020). Addressing socioeconomic inequalities in obesity: Democratising access to resources for achieving and maintaining a healthy weight. PLoS Med. 17(7): e1003243. https://doi.org/10.1371/journal.pmed.1003243

American Psychiatric Association (APA), 2020: APA_DSM-5-Contents.pdf file:/// C:/Users/ae672/Work%20Folders/Downloads/APA_DSM-5-Contents.pdf downloaded on 6/11/2020

Anekwe, C.V., Jarrell, A.R., Townsend, M.J., Gaudier, G.I., Hiserodt, J.M., Cody Stanford , F. (2020). Socioeconomics of Obesity. Current Obesity Reports . 9:272–279. https://link.springer.com/article/10.1007/s13679-020-00398- 7

Ang, Y.N., Wee, B.S., Poh , B.K., Ismai, M.N. (2013). Multifactorial Influences of Childhood Obesity. Current Obesity Reports . 2:10–22. https://link.springer.com/article/10.1007/s13679-012-0042-7

Bagnall, A., Radley, D., Jones, R., Gately, P., Nobles, J., Van Dijk, M., …. Sahota, P. (2019). Whole systems approaches to obesity and other complex public health challenges: a systematic review. BMC Public Health 19, 8. https://doi.org/10.1186/s12889-018-6274-z

Bambra, C., Gibson, M., Sowden, A., Wright, K., Whitehead, M., Petticrew,M. (2010). Tackling the wider social determinants of health and health inequalities: evidence from systematic reviews. Journal of Epidemiology and Community Health. 64 (2010), 284-291. doi:10.1136/jech.2008.082743 Berry, E.M. (2020). The Obesity Pandemic—Whose Responsibility? No Blame, No Shame, Not More of the Same Front. Nutr. https://doi.org/10.3389/fnut.2020.00002

Blaine (2008). Does Depression Cause Obesity? A Meta-analysis of Longitudinal Studies of Depression and Weight Control. Journal of Health Psychology. Vol 13(8) 1190–1197 DOI: 10.1177/1359105308095977 Brown, A.G.M., Esposito, L.E., Fisher, R.A., Nicastro, H.L., Tabor, D.C., Walker , J.R. (2019). Food insecurity and obesity: research gaps, opportunities, and challenges. Translational Behavioral Medicine. 9(5):980–987. https://doi.org/ 10.1093/tbm/ibz117 Dahlgren, G., & Whitehead, M. (1993). Tackling inequalities in health: What can we learn from what has been tried? Background paper for The King’s Fund International Seminar on Tackling Health Inequalities. Ditchley Park, Oxford: The King’s Fund. https://www.kingsfund.org.uk/projects/time-think-differently/trends- broader-determinants-health de Wit, L., Luppino, F., van Straten, A., Penninx, B., Zitman, F., Cuijpers, P. (2010). Psychiatry Res. 30;178(2):230-5. DOI: 10.1016/j.psychres.2009.04.015 Dhurandhar, E.J. (2016). The food-insecurity obesity paradox: A resource scarcity hypothesis. Physiol Behav. 162:88-92. DOI: 10.1016/j.physbeh.2016.04.025

Di Renzo, L., Gualtieri, P., Cinelli, G., Bigioni, G., Soldat, L., Attinà, A., …. ,De Lorenzo, A. (2020). Psychological Aspects and Eating Habits during COVID-19 Home Confinement: Results of EHLC-COVID-19 Italian Online Survey. Nutrients. 12(7):2152. https://doi.org/10.3390/nu12072152

Faith , M.S., Butryn , M., Wadden , T.A., Fabricatore , A., Nguyen , A.M., Heymsfield , S.B. (2011). Evidence for prospective associations among depression and obesity in population‐based studies. Obesity Reviews. 12(5). https://doi.org/10.1111/j.1467-789X.2010.00843.x Fischer, K., Pick, J.A., Moewes, D., Nöthlings, U. (2015). Qualitative aspects of diet affecting visceral and subcutaneous abdominal adipose tissue: a systematic review of observational and controlled intervention studies. Nutrition Reviews. 73(4):191–215. https://doi.org/10.1093/nutrit/nuu006 Food and Agriculture Organisation of the United Nations (FAO) (2020) http://www.fao.org/hunger/en/ Food Standards Agency (2020);The lived experience of food insecurity under Covid-19https://www.food.gov.uk/sites/default/files/media/document/fsa-food- insecurity-2020_-report-v5.pdf

Food Standards Agency (FSA) (2015) Food we can Trust. https://www.food.gov.uk/sites/default/files/media/document/Food-Standards- Agency-Strategy%20FINAL.pdf Galderisi , S., Heinz ,A., Kastrup , M., Beezhold , J., Sartorius , N. (2015). Toward a new definition of mental health World Psychiatry. 14(2):231-3. doi: 10.1002/wps.20231 Hasler, G., Pine, D.S., Kleinbaum, D.G., Gamma, A., Luckenbaugh, D., Ajdacic, V., Eich, D., Rössler, W., Angst, J. (2005). Depressive symptoms during childhood and adult obesity: the Zurich Cohort Study. Molecular Psychiatry. 10:842–850. https://www.nature.com/articles/4001671

Jeffery, R.W., Linde, J.A., Simon, G.E., Ludman, E.J., Rohde, R. Ichikawa, L.E., Finch, E.A. (2009). Reported food choices in older women in relation to body mass index and depressive symptoms. Appetite. 52(1): 238-240. https://doi.org/10.1016/j.appet.2008.08.008 Jung, S.J., Woo , H. , Cho, S., Park, K., Jeong, S., Lee , Y.J., ….and Shin,A. (2017). Association between body size, weight change and depression: systematic review and meta-analysis. British Journal of Psychiatry. 211 ( 1 ). 14- 21. DOI: 10.1192/bjp.bp.116.186726

Karelis, A. D., Brochu, M., Rabasa‐Lhoret , R., Garrel, D. , Poehlman, E. T. (2004). Clinical markers for the identification of metabolically healthy but obese individuals. Diabetes, obesity and Metabolism. 6(6). https://doi.org/10.1111/j.1462-8902.2004.00377.x

LeMoult, J. (2020). From Stress to Depression: Bringing Together Cognitive and Biological Science. Current Directions in Psychological Science. https://doi.org/10.1177/0963721420964039

Lin, H., Zhang, L., Zheng, R., Zheng, Y. (2017). The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: a PRISMA-compliant article. Medicine (Baltimore). 96(47) doi: 10.1097/MD.0000000000008838 Loopstra, R., Reeves, A., Tarasuk, V. (2019). The rise of hunger among low- income households: an analysis of the risks of food insecurity between 2004 and 2016 in a population-based study of UK adults. J Epidemiol Community Health. 73(7):668–73. https://doi.org/10.1136/jech-2018-211194 PMID: 31036607

Love, R., Adams, J., Atkin, A., van Sluijs, E. (2019). Socioeconomic and ethnic differences in children’s vigorous intensity physical activity: a cross-sectional analysis of the UK Millennium Cohort Study. BMJ Open. 9(5):e027627. pmid:31133593. https://bmjopen.bmj.com/content/9/5/e027627

Luck-Sikorski, C., Schomerus, G., Steffi, T.J., Riedel-Heller, G. (2016). Layered stigma? Co-occurring depression and obesity in the public eye. Journal of Psychosomatic Research.106: 29-33. https://doi.org/10.1016/j.jpsychores.2018.01.003

Luppino, F.S., de Wit, L.M., Bouvy, P.F., Stijnen, T., Cuijpers, P., Penninx, P.W.J.H, Zitman, F.G. (2010). Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 67(3):220- 9. doi: 10.1001/archgenpsychiatry.2010.2

Malik, V.S., Willett, W.C., Hu F.B. (2013). Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol, 9, 13-27. doi: 10.1038/nrendo.2012.199. Magkos , F. (2019). Metabolically healthy obesity: what's in a name? The American Journal of Clinical Nutrition. Volume 110, Issue 3. 533–539. https://doi.org/10.1093/ajcn/nqz133 Mannan, M., Mamun, A., Doi, S., Clavarino, A. (2016). Is there a bi-directional relationship between depression and obesity among adult men and women? Systematic review and bias-adjusted meta analysis. Asian Journal of Psychiatry. 21. 51-66. https://doi.org/10.1016/j.ajp.2015.12.008 Marmot, M. and Bell, R. (2019). Social determinants and non-communicable diseases: time for integrated action. BMJ. 364:l251. doi: https://doi.org/10.1136/bmj.l251

Mediouni, M., Madiouni, R. and Kaczor-Urbanowicz , K.E. (2020). COVID-19: How the quarantine could lead to the depreobesity. Obes Med. 19: 100255. doi: 10.1016/j.obmed.2020.100255 Mental Health Foundation (MHF) (2020). https://www.mentalhealth.org.uk/statistics/mental-health-statistics- depression Retrieved 10/11/20 . Mental Health Foundation (MHF) (2016) https://www.mentalhealth.org.uk/statistics accessed 3/11/20 Morssinkhofa, M.W.L., van Wylickb, D.W., Priester-Vinkc, S. , van der Werfd, Y.D., den Heijere, M., van den Heuvelb, O.A., Broekmana,B.F.P. (2020). Associations between sex hormones, sleep problems and depression: A systematic. Neuroscience & Biobehavioral Reviews. 118: 669-680. https://doi.org/10.1016/j.neubiorev.2020.08.006

National Health System (NHS) (2020): https://www.nhs.uk/conditions/obesity/1/11/20 Nature Reviews. (2020). Editorial: UK policy targeting obesity during a pandemic — the right approach? Nature Reviews Endocrinology. 16:609. h ttps://www.nature.com/articles/s41574-020-00420-x .

Ng, M., Fleming, T., Robinson, M., Thomson, B., Graetz, N., Margono, C., ….. Gakidou, E. (2014). Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study. The Lancet. 384 (9945 ). 766-781. doi: 10.1016/ S0140-6736(14)60460-8.

Nobles, J., Christensen, A., Butler, M., Radley, D. Pickering, K. Saunders, J., … Gately, P. (2019). Understanding how local authorities in England address obesity: A wider determinants of health perspective. Health Policy Volume 123, Issue 10, 998-1003. https://doi.org/10.1016/j.healthpol.2019.07.016

Noonan, R.J. (2018). Poverty, Weight Status, and Dietary Intake among UK Adolescents. Int J Environ Res Public Health. 2018 Jun; 15(6): 1224. doi: 10.3390/ijerph15061224

Obesity Health Alliance (2020). Briefing: How are COVID-19 measures affecting the food environment? http://obesityhealthalliance.org.uk/wp-content/uploads/2020/05/OHA-polling-data- summary-final.pdf.

Ouakinin, S.R.S., Barreira, D.P.,Gois, C.J. (2018). Depression and Obesity: Integrating the Role of Stress, Neuroendocrine Dysfunction and Inflammatory Pathways. Front. Endocrinol. https://doi.org/10.3389/fendo.2018.00431

Pan, A., Sun, Q., Czernichow, S., Kivimaki, M., Okereke, O.I., Lucas, M., …. Hu , F.B. (2012). Bidirectional association between depression and obesity in middle-aged and older women. International Journal of Obesity . 36:595–602. https://www.nature.com/articles/ijo2011111

Pereira-Miranda , E. , Costa , P. , Queiroz , V. , Pereira-Santos , M. , Santana, M. (2017). Overweight and Obesity Associated with Higher Depression Prevalence in Adults: A Systematic Review and Meta-Analysis. Journal of the American College of Nutrition. 36(3). https://doi.org/10.1080/07315724.2016.1261053 Piché, M., Poirier, P. Lemieux, I., & Després, J. (2018). Overview of epidemiology and contribution of obesity and body fat distribution to cardiovascular disease: An Update. Progress in Cardiovascular Diseases, 61, 103–113. https://doi.org/10.1016/j.pcad.2018.06.004

Pilgrim , A. , Barker, M., Jackson, A., Ntani, G., Crozier, S., Inskip, H., …. Robinson, S. (2012). SWS Study Group : Does living in a food insecure household impact on the diets and body composition of young children? Findings from the Southampton Women's Survey. J Epidemiol Community Health. 66(6). doi: 10.1136/jech.2010.125476

Public Health England (2019). Health Matters; Whole systems approach to obesity. Retrieved from https://publichealthmatters.blog.gov.uk/2019/07/25/health-matters-whole- systems-approach-to-obesity/

Puhl, R., & Brownell, K. (2006). Confronting and coping with weight stigma: An investigation of overweight and obese adults. Obesity. 14. 1802–1815. DOI: 10.1038/oby.2006.208

Puhl, M. and Heuer, C.A. (2009). The Stigma of Obesity: A Review and Update, Obesity. 17: 941–964. doi:10.1038/oby.2008.636 Puhl, R. M., Himmelstein, M. S., & Pearl, R. L. (2020). Weight stigma as a psychosocial contributor to obesity. American Psychologist, 75(2), 274– 289. https://doi.org/10.1037/amp0000538 Rajan, T.M. and Menon, V. (2017). Psychiatric disorders and obesity: A review of association studies. J Postgrad Med. 63(3): 182–190. doi: 10.4103/jpgm.JPGM_712_16

Richie, H. and Rocher, M. (2018). Our world in data: mental health. https://ourworldindata.org/mental-health? fbclid=IwAR25JQXJiVc_adD8gX2b0jH1tToBApxZXeaDIH- anaeiiMaa3CN4Avcekns Roberts, R., Deleger, S., Strawbridge, W., & Kaplan, G. (2003). Prospective association between obesity and depression: evidence from the Alameda County Study International Journal of Obesity. Volume 27. 514–521. https://journals.sagepub.com/doi/abs/10.1177/1359105308095977

Romero-Corral, A., Somers, V.K., Sierra-Johnson, J., Korenfeld, Y., Boarin, S., Korinek, J., Jensen, M.D., Parati, G., Lopez-Jimenez, F. (2010). Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. European Heart Journal, 31(6):737- 746. https://doi.org/10.1093/eurheartj/ehp487

Salmasi, L. and Celidoni, M. (2017). Investigating the poverty-obesity paradox in Europe. Economics & Human Biology . 26 :70-85. https://doi.org/10.1016/j.ehb.2017.02.005

Stefan, N., Birkenfeld, A.L., Schulze, M.B., Ludwig, D.S. (2020). Obesity and impaired metabolic health in patients with COVID-19. Nature Reviews Endocrinology. 16:341–342. https://www.nature.com/articles/s41574-020-0364-6

Stefan, N., Schick, F., Haring, H.U. (2017). Causes, characteristics, and consequences of metabolically unhealthy normal weight in humans. Cell Metab. 26:292–300. DOI: 10.1016/j.cmet.2017.07.008

Stunkard , A.J., Faith , M.S., Allison , K.C. (2003). Depression and obesity. Biol Psychiatry. 1;54(3):330-7. doi: 10.1016/s0006-3223(03)00608-5

Thomas, E.L., Frost, G.S., Taylor-Robinson, S.D. and Bell, J.D. (2012). Excess body fat in obese and normal-weight subjects. Nutrition Research Reviews. 1 -12. doi:10.1017/S0954422412000054 Tomiyama, A.J., Hunger, J.M., Nguyen-Cuu, J., Wells, C. (2016). Misclassification of cardiometabolic health when using body mass index categories in NHANES 2005-2012. Int J Obes (Lond). 40(5):883-6. doi: 10.1038/ ijo.2016.17 Tomiyama, J. (2019). Stress and Obesity. Annual Review of Psychology. Vol. 70:703-718. https://doi.org/10.1146/annurev-psych-010418-102936 Tyrrell, J., Mulugeta, A., Wood, A.R., Zhou, A., Beaumont, R.N., Tuke, M.A., … Sharp , S. (2019). International Journal of Epidemiology. 48 (3). 834–848. https://doi.org/10.1093/ije/dyy223 Ulijaszek,S. & McLennan, A. (2016). Framing obesity in UK policy from the Blair years, 1997–2015: the persistence of individualistic approaches despite overwhelming evidence of societal and economic factors, and the need for collective responsibility. Obesity Reviews, 17, 397-411. doi: 10.1111/obr.12386 UK Government (2007). Foresight Report, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/ attachment_data/file/287937/07-1184x-tackling-obesities-future-choices- report.pdf UK Government (2020). Tackling obesity: empowering adults and children to live healthier lives. https://www.gov.uk/government/publications/tackling-obesity- government-strategy/tackling-obesity-empowering-adults-and-children-to-live- healthier-lives

UK Government (2020). Press release on Tackling obesity. https://www.gov.uk/government/news/major-new-campaign-encourages-millions- to-lose-weight-and-cut-covid-19-ris

Ul-Haq, Z., Smith, D.J., Nicholl, B.I., Cullen, B., Martin, D., Gill, J.M.R., …. Pell , J.P. (2014). Gender differences in the association between adiposity and probable major depression: a cross-sectional study of 140,564 UK Biobank participants. BMC Psychiatry. 153 (2014). doi:10.1186/1471-244X-14-153

United Nations (UN), 2020: Policy Brief: COVID-19 and the Need for Action on Mental Health 13 MAY 2020 , United Nations: https://www.un.org/sites/un2.un.org/files/un_policy_brief- covid_and_mental_health_final.pdf Whitlock, G., Lewington, S., Sherliker, P., Clarke, R., Emberson, J., Halsey, J., ….. Peto, R. (2009). Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet, 373:1083–96. DOI: 10.1016/S0140-6736(09)60318-4

Wildman, R.P., Muntner, P., Reynolds, K., McGinn, A.P., Rajpathak, S., Wylie- Rosett, J., Sowers, M.R. (2008). The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999–2004). Arch Intern Med.168:1617–24. DOI: 10.1001/archinte.168.15.1617

World Health Organisation (WHO) (2020): https://www.who.int/news-room/fact- sheets/detail/obesity-and- overweight#:~:text=Overweight%20and%20obesity %20are%20defined,overweight%20and%20obesity%20in%20adults. Downloaded 1/11/20 World Health Organisation (WHO) (2018). https://www.who.int/mental_health/evidence/guidelines_severe_mental_disorders _web_note_2018/en/ accessed 3/11/20

World Health Organisation (WHO) (2014). Social Determinants of Mental Health.

Retrieved from apps.who.int/iris/

bitstream/10665/112828/1/9789241506809_eng.pdf?ua=1 [Accessed 12/09/16].

World Health Organization (WHO) (2004). Promoting mental health. Concepts,

emerging evidence, practice. Retrieved from

https://www.who.int/mental_health/evidence/en/promoting_mhh.pdf

World Health Organisation (WHO) (2001) - Strengthening mental health promotion. Geneva, World Health Organization (Fact sheet, No. 220). https://mindyourmindproject.org/wp-content/uploads/2014/11/WHO-Statement- on-Mental-Health-Promotion.pdf. Yau, A., White, M., Hammond, D., White, C., Adams, J. (2020). Socio- demographic characteristics, diet and health among food insecure UK adults: cross-sectional analysis of the International Food Policy Study. Public Health Nutr. 2020:1–13. https://doi.org/10.1017/S1368980020000087 PMID: 32336313

Zhang , Q. , Wang, Y., (2004). Trends in the association between obesity and socioeconomic status in U.S. adults: 1971 to 2000. Obes Res. 12(10):1622- 32. doi: 10.1038/oby.2004.202