Food, Eating and Obesity - Theories, Models and Interventions for Health Behaviour Change

Health Psychology: Theory, Research and Practice - David F. Marks 2010

Food, Eating and Obesity
Theories, Models and Interventions for Health Behaviour Change

’Obesity does not imply gluttony; gluttons might escape obesity and, conversely, obesity can arise from a perfectly ordinary level of food intake as the long-term result of a near-imperceptible imbalance in homeostatic mechanisms. Blaming the obese for their obesity is rather like blaming the poor for their poverty; they might be able to do something about their condition, but in practice it is often far from easy.’

Gareth Leng (2014: 1101)


In this chapter, we critically examine the part played by food, diets and dieting in the changing patterns of illnesses and deaths associated with obesity. We review theories, interventions and evidence on effectiveness to explain why the obesity pandemic is so resistant to change. Interventions have commonly used the Energy Surfeit Theory to recommend diets restricting calories of fat. This approach has been unhelpful. More recently, attention has switched to low carbohydrate, vegetarian or vegan diets. There is a need for a scientific approach to obesity prevention rather than the current market-led approach.

Eating and drinking are pleasurable and social activities that provide essential energy to the body. They satisfy hunger and thirst, and are steeped in cultural, moral and symbolic meaning. Food and drink form part of culture itself, a ’food and drink culture’ with its own associated beliefs, values and customs. Food consumption consists of a complex set of processes that includes genetic and environmental factors, conditioning and customs. There are many interesting aspects of food, diets and dieting, enough for many volumes. The central issue here is the phenomenon that is today’s Public Health Problem Number One: the global obesity pandemic. In this chapter, we explain why the obesity pandemic is so resilient and the serious errors and false assumptions that are made in current attempts to eliminate it.

Authorities decree that a ’balanced diet’ with regular physical activity is of crucial importance to a healthy body. Yet in spite of thousands of studies, hundreds of campaigns, and scores of dedicated institutes and journals, there is not a single validated public health intervention able to achieve sustained long-term weight loss. Some basic questions require answers: What is causing the obesity pandemic? Why are current attempts to eliminate the pandemic failing? What is the role, if any, for health psychology?

The obesity pandemic is comparable in importance to the smoking pandemic. It took 50 years of consolidated pressure to reduce the prevalence of smoking-related diseases. It is our contention that there is enough scientific knowledge now to tackle the obesity pandemic. The main obstacle is that our systems of governance are market-led. Food policy and regulation are based as much on economic imperatives as by scientific evidence. If the food chain could be rationally developed on the basis of science rather than profit, the obesity pandemic could be solved right now.

First, let’s consider one government report on the subject. The Foresight Report (2007) referred to a ’complex web of societal and biological factors that have, in recent decades, exposed our inherent human vulnerability to weight gain’. The report presented an obesity map with energy balance at its centre with over 100 variables directly or indirectly influencing energy balance. This complex mapping was divided into seven cross-cutting themes in four categories, which provides a useful framework for the understanding of overweight and obesity (Figure 10.1).

Figure 10.1 Seven influences on overweight and obesity


Source: Foresight Report (2007)

Definition and Prevalence

Obesity has been defined as a chronic, relapsing, neurochemical disease (Bray, 2003). It is manifested by an increase in size and number of fat cells (adipose tissue). One definition of obesity uses a measure known as the body mass index (BMI). The BMI is a person’s weight in kilograms divided by the square of his/her height in metres (kg/m2). A BMI greater than or equal to 25 is classified as overweight; a BMI greater than or equal to 30 is classified as obesity, and 40+ as extreme obesity.

Another indicator of OAO is waist circumference. The correlation between waist circumference and intra-abdominal adipose tissue (IAAT) is 0.8. Abdominal subcutaneous adipose tissue (ASAT), IAAT and the IAAT: ASAT ratio all increase significantly by age and BMI group (Thomas et al., 2012). Belt size may be used as a proxy for waist circumference: >40 inches for males and 35 inches for females indicate excess visceral fat. The body adiposity index (BAI) may also be used: waist circumference as a percentage of height. Another measure, skin fold thickness, is obtained using calipers in different bodily areas.

More than one-third (35.7%) of adults are considered to be obese. More than one in 20 (6.3%) have extreme obesity. Almost three in four men (74%) are considered to be overweight or obese. The prevalence of obesity is similar for both men and women (about 36%) (National Institute of Diabetes and Digestive and Kidney Diseases, 2017).

By 2050, it is predicted that obesity will affect 60% of adult men, 50% of adult women and 25% of children, making Britain a mainly obese society (Butland et al., 2007). Obesity will be the new normal. Similar projections apply to the USA and other European countries. The medical complications of obesity are extensive and lead to higher mortality. Obesity is a marker for insulin resistance, Type 2 diabetes and metabolic syndrome, a collection of cardiovascular risk factors that includes hypertension, dyslipidaemia and insulin resistance (see Figure 10.2).

The Prospective Studies Collaboration (2009) analysed data from almost 1 million people who were followed from middle age in 57 prospective studies. A J-shaped mortality curve was obtained with optimal survival at a BMI level of 22.5—25 kg/m2. Above this range, mortality from several causes — especially vascular diseases — increased. Moderate obesity (BMI 30—35) is associated with three years’ loss of life, while the extremely obese (BMI 40—50) lose ten years of life, equivalent to the years lost by a lifetime of smoking. Obesity is also a risk factor for cancer, cancer recurrence and survival (Boeing, 2013).

There have been many hotly debated controversies about food, diets and dieting. Different dietary interventions for obesity have been extensively explored yet interventions have yielded unexciting results. In this chapter, we attempt to address the issue of why this could be. We begin by considering the issue of measuring obesity (Box 10.1) and then review the many different theories of obesity.

Medical diagnosis is based on cut-offs, e.g., BMI > 30 or body fat > 30%. These cut-offs give different outcomes and have low concordance. For accurate measurement, DXA or MRI, in combination with leptin, should be used. Researchers and physicians who use the proxy measure of BMI as the sole basis for classifying OAO are misclassifying obese patients and putting them at risk. For accurate diagnosis of obesity, DXA and MRI should be used as they provide direct images of adiposity throughout the body. Access to these imaging techniques for researchers is currently restricted.

Figure 10.2 The medical complications of obesity


Source: Yale University Rudd Center for Food Policy and Obesity

Causes of Obesity

In considering causation, we need to bear in mind that obesity has multiple causes. We consider here the main biological theories, the environmental theory, social and developmental factors, and psychological explanations.

Box 10.1 How are Overweight and Obesity Measured?

The BMI is a proxy measure of body fat. It does not measure it directly. Because BMI is easy to calculate, shows high test—retest reliability, is inexpensive and correlates with health risk markers and diseases, it is the measurement of choice for researchers. However, it suffers from serious problems.

Figure 10.3 BMI versus percentage of body fat in scatterplot


Women who fall above the line are obese according to the American Society of Bariatric Physicians (ASBP) criteria (DXA percent body fat: approx. 30%). Men who fall above the horizontal line are obese according to ASBP criteria (DXA percent body fat: approx. 25%). The upper left quadrant bordered by the horizontal line (30% body fat) and vertical line (BMI = 30) demonstrates the large number of women misclassified as ’non-obese’ by BMI yet ’obese’ by percent body fat

Source: Shah and Braverman (2012)

The body consists of four compartments: bone, muscle, subcutaneous fat (about 80% of body fat) and visceral fat (about 20% of body fat). The latter consists of fat in organs such as the liver that causes insulin resistance and metabolic syndrome. The BMI does not distinguish between the four bodily compartments. While some people can have a BMI in the obese range and yet have normal levels of visceral fat (e.g., fit gymnasts), approximately 20% of people with normal BMI have clinical levels of visceral fat.

Studies comparing the BMI to measures of body fat yield show plenty or room for error. Shah and Braverman (2012) compared BMI and body fat scores using dual energy X-ray absorptiometry (DXA) on 1,393 patients from 1998 to 2009. DXA, originally used to measure bone density and total body composition, can alse be used to determine abdominal fat mass. There was agreement for only 60% of the sample, with 39% misclassified as non-obese using BMI. A total of 48% of women and 25% of men were misclassified as non-obese by BMI, but were obese by percentage body fat scores (Figure 10.3). Other researchers using regression suggested that BMI predicts risk markers in white males as well as skin-fold thickness and DXA (Hariri et al., 2013). Yet the scatterplot in Figure 10.3 shows the huge room for error even when the correlation between BMI and body fat percentage is quite strong.

Evolutionary Hypothesis

The genetic make-up of humans is adapted to a nomadic existence of hunting and gathering in which the body stores fat. Early humans have been traced to sites in Africa dating approximately 2.5 million years ago; the tool-making Homo habilis (’handy man’) lived in the Olduvai Gorge in Tanzania. These Olduvai hominids were hunter-gatherers, killing and processing their food with weapons and tools fashioned from pieces of volcanic obsidian (Lamb and Sington, 1998). Allowing 25 years for each generation, 100,000 generations of humans separate contemporary Homo sapiens from Homo habilis. In evolutionary terms, this is not long enough for any significant evolutionary change.

Natural ecosystems provide a diet of wild plant-based foods that is both varied and plentiful. For example, North American Indians used hundreds of plants in their diets, including the stinging nettle, common purslane, milkweed, clover, pond-lily, dandelions and fiddleheads (Fieldhouse, 1996). In addition, hunter-gatherers would harvest insects and fish, and hunt for meat. Over 13,000 insects have been classified as edible. This diet was adequate both in quality of nutrients and quantity of energy supplied. Cordain et al. (2000) suggested that whenever ecologically possible, hunter-gatherers would have consumed high amounts (45—65% of total energy) of animal food. Most (73%) hunter-gatherer societies worldwide derived more than 50% (56—65%) of their subsistence from animal foods, whereas only 13.5% of these societies derived more than half (56—65%) of their subsistence from gathered plant foods. Until human beings settled in villages and towns around 10,000 years ago, humans consumed only wild and unprocessed food collected from their environment. They would likely have walked or run 5—10 miles daily searching for their food, drinking only fresh water, yielding a healthful diet of lean protein, poly-unsaturated fats (especially omega-3 fatty acids), mono-unsaturated fats, fibre, vitamins, minerals, antioxidants and other beneficial phytochemicals (O’Keefe and Cordain, 2004). The ’diseases of affluence’ of the modern age would have been almost unknown.

For a few million years the capacity to store fat was advantageous. Ice Age hunter-gatherers needed to store fat to survive the winters and long journeys. When the ice retracted and temperatures increased, agriculture developed and foods became more accessible. A metabolic feature to promote survival became a risk factor for diseases.

Genetic Pedisposition

Body size, whether large or small, runs in families. This observation has led to many studies of the heritability of excess weight in twins and adoptees. Heritability is the proportion of observed differences in a trait among individuals that is due to genetic differences. Evidence from studies indicates that the tendency to put on weight is inherited and beyond any individual’s personal control.

A systematic review explored genetic studies on BMI in pre-adolescence, young adulthood and late adulthood (Nan et al., 2012). Nan et al. searched for studies reporting intra-pair correlations of healthy twin pairs who were raised together, finding data on 8,179 monozygotic (MZ, i.e., identical) and 9,977 dizygotic (DZ, non-identical) twin pairs from 12 studies in addition to data for 629 MZ and 594 DZ pairs from four twin registries. Heritability scores of BMI ranged from 61% to 80% for male and female participants combined, while unique environmental influences increased from 14% to 40% with increasing age.

Genetic predisposition to develop overweight and obesity is a biological fact. However, the human genome has not altered in the last few thousand years and so genetic predisposition is insufficient to explain the increase in obesity over the last few decades.

The fundamental biological process of homeostasis operates to preserve stability and equilibrium within all systems of the human organism (Marks, 2015). Homeostasis can be disturbed by gradual changes in the environment. It is popularly assumed that changes in body weight reflect the choices an individual makes about what food to eat, how much to eat and how much to exercise. However, the long-term balance between energy intake and energy output is mainly determined by unconscious physiological systems (Leng, 2014). We turn to discuss how these ’unconscious physiological systems’ have been theorized in different approaches to the understanding food, eating and obesity.

The Energy Surfeit Theory

The Energy Surfeit Theory (EST) has dominated obesity research over the last 50 years. The EST has been the founding assumption of countless studies, reports and interventions aimed towards breaking the obesity pandemic. All attempts to break the pandemic using the EST concept have been a disastrous failure. In this section, we analyse how this disaster could have happened.

According to the EST, obesity is caused by an imbalance between energy intake and energy expenditure. The energy balance equation (EBE) states:

energy intake = internal heat produced + external work + energy stored

Energy is consumed in the diet through intake of three macronutrients: protein, carbohydrate (CHO) and fat. In the presence of excess food, the body will convert and store nutrients as triglycerides in adipose tissue. Translating the EBE in terms of fat, the equation becomes:

rate of change of fat stores in the body = rate of fat intake — rate of fat oxidation

First, consider energy intake. The standard unit of energy, the calorie, is defined as the energy needed to increase the temperature of 1 kg of water by 1°C, which is about 4.184 kJ. Fat contributes 9 calories per gram, alcohol 7 calories per gram and carbohydrates 4 calories per gram. The fat content of a food item is the sum of four different fats: saturated, trans-saturated (trans), poly-unsaturated and mono-unsaturated. For sedentary adults, every 22 kcal per day increase in energy intake will increase body weight by roughly 1 kg after several years. Energy can be expended in several ways.

Eating itself expends calories, the ’thermic effect’ of food, which is the energy expended in order to consume (bite, chew and swallow) and process (digest, transport, metabolize and store) food. Processing protein, CHO and fat requires 20—35%, 5—15% and 2—3% of energy consumed, respectively. A gram of fat not only gives you more calories, but a smaller percentage is burned off by the thermic effect.

The majority of diets are based on counting calories. Diet designers assume that diets of equal caloric content result in identical weight change independent of macronutrient composition. ’A calorie is a calorie’, so the saying goes. This assumption is actually false because it violates the second law of thermodynamics. Feinman and Fine (2004) proposed that a misunderstanding of the second law accounts for the controversy about the role of macronutrients on weight loss: ’Attacking the obesity epidemic will involve giving up many old ideas that have not been productive. “A calorie is a calorie” might be a good place to start’ (Feinman and Fine, 2004). All calories are not equal. If you eat an equal number of calories of protein, fat and carbohydrates, the metabolic processes are different and calories in the fat are more likely to end up on your waist as fewer calories are burned off by the thermic effect.

Against the energy surfeit model of obesity, recent evidence suggests that increasing energy expenditure may be more effective for reducing body fat than caloric restriction, the most commonly recommended treatment for obesity. This could happen because homeostatic regulation of body weight is more effective when energy intake and expenditure are both high (high energy flux), implying that low energy flux should predict weight gain. Hume et al. (2016) examined whether energy balance or energy flux predicted future weight gain in two independent samples consisting of adolescents (n = 154) and college-aged women (n = 75). Measures of objective doubly labelled water, resting metabolic rate, and percentage of body fat were taken at baseline. Percentage of body fat was measured annually for three years of follow-up for the adolescent sample and for two years of follow-up for the young adult sample. Low energy flux, not energy surfeit, predicted future increases in body fat in both samples. In addition, high energy flux appeared to prevent fat gain in part because it was associated with a higher resting metabolic rate.

Almost all authorities subscribe to the dictum that obesity is caused by an energy surfeit, i.e., eating too many calories (gluttony) and failing to burn off enough calories (sloth). This assumption has been the rationale for thousands of failed interventions and created victim-blaming and stigmatization, which have done little to reduce the incidence of overweight and obesity. There are serious defects with this theory. It is wrong in principle and it doesn’t work in practice.


Let’s turn to the energy expenditure, the other half of the energy—balance equation. It is alleged by almost all authorities and experts that one of the principal causes of obesity is inactivity/lack of exercise. Energy loss in exercise is measured in joules. One joule in everyday life represents approximately the energy required to lift a small apple (with a mass of approximately 100 g) vertically through 1 metre. Do this a million times and you have used 1 megajoule (MJ) of energy or 239 calories. There are, of course, many quicker ways of burning energy than lifting an apple.

The use of exercise is a recommended part of any weight loss programme. It’s almost universally recommended by everybody, but the scientific evidence indicates that exercise interventions actually provide an ineffective procedure for losing weight. The impact of increased activity on body weight is slow-acting and hard to sustain. Simple mathematics suggest that the amount of exercise necessary for significant long-term weight loss maintenance far exceeds the capacity of most people.

Hall et al. (2011) mathematically simulated energy expenditure adaptations during weight loss. A persistent daily energy imbalance between intake and expenditure of about 30 kJ per day underlies the observed average weight gain in the US population. In addition, a heavier person expends more energy to move a certain distance. They calculated that the average increase of energy intake needed to sustain the increased weight (the maintenance energy gap) amounted to about 0.9 MJ per day. To reverse the trend and lose weight, a person would need to burn off at least 0.9 MJ per day, for example 1.0 or 1.2 MJ per day. Let’s consider what losing 1.2 MJ per day would actually involve.

A 100 kg man would need to run about 20 km, almost a half-marathon each week, to burn off 1.2 MJ per day in order to reach a weight of around 85 kg. This would take approximately five years using exercise alone. To lose 15 kg, a 100 kg person would need to run 5,000 km over five years. It’s hardly surprising that obese people find exercise an ineffective method of losing weight, and that attrition rates in exercise programmes are so very high.

Similar conclusions have been reached in several systematic reviews (SRs), e.g., Loveman et al. (2011) and the Swedish Council on Health Technology Assessment (2013). The latter concluded:

adding physical activity to a dietary intervention for obese individuals has a marginal — if any — effect on weight loss at group level. The lack of effect can be explained by compensatory mechanisms, such as a lower degree of physical activity throughout the rest of the day or increased hunger and less of a sense of satiety in connection with meals. (Swedish Council on Health Technology Assessment, 2013: 40)

There is also a safety issue: harm can result from inappropriate levels of exercise (Cooper et al., 2007; Barg et al., 2011). In spite of all the advice coming from health authorities to exercise more to lose weight, the obesity pandemic would never be reversed by obese individuals increasing their daily amount of exercise. To lose a significant amount of weight, it is necessary for people living with obesity to make major dietary changes.

Dietary change to reduce obesity may require more than calorie reductions. Critics of calorie counting argue that it is not excess calories that cause obesity, but the quantity and quality of carbohydrates consumed (Taubes, 2012). We turn to this theory next.

The Insulin Theory

The insulin theory claims that obesity is caused by a chronic elevation in insulin in a diet that contains too much carbohydrate (Taubes, 2009):

This alternative hypothesis of obesity constitutes three distinct propositions. First is the basic proposition that obesity is caused by a regulatory defect in fat metabolism, and so a defect in the distribution of energy rather than an imbalance of energy intake and expenditure. The second is that insulin plays a primary role in this fattening process, and the compensatory behaviours of hunger and lethargy. The third is that carbohydrates, and particularly refined carbohydrates — and perhaps the fructose content as well, and thus perhaps the amount of sugars consumed — are the prime suspects in the chronic elevation of insulin; hence, they are the ultimate cause of common obesity. (Taubes, 2009: 359)

CHO is a high glycaemic index (GI) food that produces insulin that, in turn, causes the body to store fat. Carbohydrates include starch, which is found in rice, wheat, maize, potatoes and cassava, and all sources of sugar, specifically natural sugars and added sugars and fibre. Sugary beverages including alcohol, sweets, sugary cereals, dried fruits, low-fat crackers, rice cakes, potato crisps, flour, cakes, cookies, jams, preserves, potato products, pickles, sauces, salad dressings and pizzas are all high in carbohydrates.

According to the insulin theory, the CHO content of a person’s diet must be rectified to restore health (Taubes, 2012). This is because blood levels of insulin are mainly determined by CHO intake, and insulin regulates fat accumulation. The more digestible the carbohydrates that we eat (i.e., the higher their glycaemic index) and the sweeter they are (the higher their fructose content), the higher our blood insulin level goes and the more fat we accumulate in our bodies.

Food consumption data from the National Health and Nutrition Examination Survey (NHANES) between 1971 and 2004 indicate that the observed increase in energy intake in the USA is accounted for almost completely by increased CHO consumption, with a 67.7 g increase per day in men and a 62.4 g increase per day in women within that time frame (Lim et al., 2010). Meals composed predominantly of high GI foods induce hormonal events that stimulate hunger and cause overeating in adolescents. A high GI diet has been linked with risk for central adiposity, cardiovascular disease and Type 2 diabetes (Ebbeling et al., 2002). Low-CHO diets show a metabolic advantage. An isocaloric diet, which has a fixed number of calories, can be used to compare diets that vary in the percentage of CHO that they contain. If a calorie really was a calorie, then the weight loss obtained in a low-CHO isocaloric diet would be identical to that in a high CHO isocaloric diet. However, in nine out of ten studies, more weight loss occurred in the low-carb diet (Fine and Feinman, 2004). This research led to the conclusion that a good way to take off weight is to switch to a low-carb diet.

Ketosis is a metabolic state in which some of the body’s energy supply comes from ketone bodies in the blood. Ketonic diets are very low CHO diets (VLCDs) that restrict the daily intake of carbohydrates but encourage the consumption of fats. Brehm et al. (2013) conducted a randomized controlled trial to determine the effects of a VLCD on body composition and cardiovascular risk factors. A total of 42 healthy, obese female volunteers were randomly allocated to a VLCD or to a calorie-restricted low-fat diet. Women on both diets reduced their calorie consumption by similar amounts at three and six months. However, the VLCD group lost more weight (8.5 ± 1.0 vs. 3.9 ± 1.0 kg) and more body fat (4.8 ± 0.67 vs. 2.0 ± 0.75 kg) than the low-fat diet group.

A systematic review by Gibson et al. (2015) concluded that the true benefit of VLCD is in preventing an increase in appetite, which helps the dieter to severely restrict food intake to achieve substantial weight losses, rather than the absence of hunger altogether. Ketosis provides a plausible explanation for the suppression of appetite during a ketogenic diet.

There can be little doubt that a major contributor to obesity is the consumption of sugar. New guidelines on sugar consumption were proposed by the World Health Organization in 2014 (WHO, 2014a). This was a highly controversial step in the attempt to influence diet by the use of policy and regulation. Box 10.2 summarizes the new WHO guidelines on sugar.

Box 10.2 WHO Guidelines on Sugar

The consumption of sugar has grown continuously over the last 200 years and continues to grow. In 2014 the WHO launched a new draft guideline on sugars intake in light of scientific studies on the consumption of sugars and its impact on excess weight gain and tooth decay (World Health Organization, 2014a). Systematic reviews were carried out by Te Morenga et al. (2013), who showed that sugar is a determinant of body weight, and Moynihan and Kelly (2014), who found that 47 of 55 studies reported a positive association between sugars and calories. Yang et al. (2014) examined time trends of added sugar consumption as percentage of daily calories in the USA. They observed a significant relationship between added sugar consumption and increased risk for cardiovascular disease (CVD) mortality. The highest sugar group had a risk of death from a cardiovascular event almost three times higher than those whose sugar consumption was 10% or lower of daily calories.

The WHO’s previous recommendation from 2002 was that sugars should make up less than 10% of total energy intake per day. The new guideline proposes that a reduction to below 5% of total energy intake per day would be beneficial. A 5% of total energy intake is equivalent to around 25 grams (around six teaspoons) of sugar per day for an adult with normal BMI.

Sugar includes monosaccharides (such as glucose or fructose) and disaccharides (such as sucrose or table sugar) that are added by the manufacturer, cook or consumer, and naturally present sugars in honey, syrups, fruit juices and fruit concentrates. Much of the sugars consumed today are ’hidden’ in processed foods that are not usually viewed as sweets. For example, 1 tablespoon of ketchup contains around 4 grams (around 1 teaspoon) of sugars. A single can of sugar-sweetened soda contains up to 40 grams (around 10 teaspoons). A Yeo Valley Family Farm 0% Fat Vanilla Yogurt contains 20.9 grams (around 5 teaspoons).

Sugar has become a new watchword, along with fat.

The dangers of sugar were highlighted by John Yudkin in Pure, White and Deadly (1972). Following this publication, there should have been a reduction of sugar in the diet. However, Yudkin was ignored. Food consumption and diets do not follow reason or evidence and consumption of sugar-sweetened beverages has risen rapidly ever since.

While a low-CHO diet provides a helpful method of reducing body fat, the insulin hypothesis has not been confirmed in scientific studies (Guyenet, 2012).

Developmental Hypothesis

Obesity starts in the womb. The baby is highly sensitive to the environment experienced within the womb. A relationship has been observed between the weight of a mother-to-be and her child. For example, Modi et al. (2011) used MRI to monitor fat levels in 105 unborn babies and found that 30% had more abdominal adipose tissue than expected. The amount of fat was proportional to the mother-to-be’s BMI. These findings were reinforced by Schellong et al. (2012), who found that infants with a birthweight in excess of 4 kg were twice as likely to suffer from obesity in later life than normal-weight babies. Preventing in utero over-nutrition by avoiding maternal over-nutrition, overweight and/or diabetes during pregnancy would be a promising strategy to prevent overweight and obesity globally. It’s a ’chicken-and-egg’ problem.

Risk of obesity continues to develop in the crib and accelerates in the first few years of life. A consistent association occurs between faster infant weight gain (from birth to age 1 year) and later overweight or obesity. Druet et al. (2012) assessed the association between infant weight gain and subsequent obesity by meta-analysing individual-level data on 47,661 participants from ten cohort studies. Each unit increase in weight SD scores between 0 and 1 year conferred a two-fold higher risk of childhood obesity and a 23% higher risk of adult obesity (Figure 10.4).

Childhood and adolescence are critical periods for the adoption of a healthy lifestyle. By age 15 many adolescents show consistent behaviour patterns that influence their chances of OAO in later years. Clark et al. (2007) studied how parents’ child-feeding behaviours influence child weight. Parents reported using a wide range of child-feeding behaviours, including monitoring, pressure to eat and restriction. Interestingly, a restriction of childrens eating has most frequently and consistently been associated with child weight gain. The authors found evidence for a causal relationship between parental restriction and childhood overweight, indicating that, inadvertently, parents may promote excess weight gain in childhood by using inappropriate child-feeding behaviours.

Figure 10.4 Odds ratios for childhood obesity by infant weight gain, 0—1 year, adjusted for sex, age and birthweight


Source: Druet et al. (2012)

Early parental attachment plays a critical role in the regulation of emotion and in the formation of drinking habits, substance abuse and food consumption (Marks, 2015; Figure 10.7). Emotion regulation, associated with attachment patterns, plays a critical role in causation of ill health. DeSteno, Gross and Kubzansky (2013) observed that chronic childhood distress at age 7 or 8 years is associated with adult physical health outcomes such as obesity, number of physical illnesses and inflammation. Dietary habits from childhood persist into adulthood once formed, and parental influences are internalized and enacted throughout life. Goossens et al. (2012) examined attachment towards mothers and fathers as a predictor of eating pathology and weight gain among 8—11-year-old boys and girls. Insecure attachment to mothers was predictive of increases in dietary restraint, eating concerns, weight concerns and shape concerns, and adjusted BMI in children one year later. Insecure attachments to fathers was predictive of persistence in children’s subjective binge eating episodes. Faber and Dubé (2015) investigated the role of caregiver—child attachment quality and its associations with high caloric food consumption in middle socio-economic status children and adults. Data from 213 children and 216 parents showed that an insecure parental attachment, whether actual or recalled, significantly and positively predicted high calorific food consumption in both samples. Faber and Dubé (2015: 521) concluded that: ’From an intervention standpoint, parents-to-be could receive a short information sheet teaching them that responding to a child’s attention-seeking does not make the child needy, but rather teaches him or her to become trusting and independent. From a counselling and clinical standpoint, children and parents of children with eating issues could benefit greatly from developing secure and trusting relationships’.

Knowledge about child-feeding is one aspect of parenting and childcare that could benefit from training. Training could be designed to increase provider knowledge and self-efficacy and remove misconceptions as well as educate providers about feeding, nutrition education and family communication.

Sleeping Patterns

Another area of concern is children’s sleeping patterns. Patel and Hu (2008) found a consistent body of evidence that short sleep duration in childhood is predictive of weight gain. A meta-analysis of cross-sectional studies has shown that there is an almost two-fold higher prevalence of obesity in children and adults who have a short sleep duration (Miller et al., 2014). Padez et al. (2009) studied the association between sleep duration, overweight and body fat in a sample of Portuguese children. Prevalence of overweight decreased with longer night sleep times. Laboratory and epidemiological studies point to short sleep duration and poor sleep quality as factors associated with obesity (Beccuti and Pannain, 2011).

Perhaps there is a simple explanation. Obstructive sleep apnoea (OSA), which is associated with sleep fragmentation, is more common with OAO. Increased visceral adiposity tends to reduce the airway size while lying down. OSA is also known to trigger hypertension, insulin resistance, Type 2 diabetes and, possibly, metabolic syndrome. OSA causes daytime sleepiness and impaired memory and concentration (Dempsey et al., 2010). Sleep deprivation makes a person less attentive and careful in their food choices, reducing their fruit and vegetable consumption but increasing their consumption of fast food (Kruger et al., 2014). In these circumstances, daytime sleepiness and OAO form a vicious circle: OAO - > OSA - > daytime sleepiness - > poor diet - > OAO. This hypothesis warrants further study.

Food Reward Theory

This theory is based on the fact that food has a reward or reinforcement value that strengthens the desire to eat. The food reward theory of obesity argues that the reward value of food influences food intake and body fatness, contributing to the development of obesity (Guyenet, 2012). Cues such as the sight or smell of food stimulate appetite and promote higher consumption. Studies of conditioning carried out by Pavlov and many others show that animals and people learn to associate non-food cues with eating. Exposure to the conditioned stimuli then elicits salivation and changes in blood glucose, and can initiate food intake even in people who are already sated.

To help explain obesity, the food reward theory is paired with the idea that a breakdown can occur in the brain’s ability to switch off eating when the stomach is full. As early as 1840, a German physician, Bernard Mohr, suggested that obesity is associated with abnormalities of the basal hypothalamus. The food reward theory hypothesizes that obese people may have impairments in the dopaminergic pathways of their brains that regulate neuronal systems associated with reward sensitivity, conditioning and control (Volkow et al., 2011). Dopamine is involved in reward functions, and is a major regulator of food intake and body fatness. Dopamine signalling in the striatum regulates the motivation to obtain food (wanting), but not the enjoyment or palatability of food (liking). The theory suggests that neuropeptides responsible for regulating energy balance through the hypothalamus also modulate the activity of dopamine cells and their projections into regions involved in the reward process in food intake. Volkow et al. hypothesize that the breakdown of feedback mechanisms and increased resistance to homoeostatic signals in obese people impairs the function of circuits involved in reward sensitivity, conditioning and cognitive control.

Thaler et al. (2012) studied the effect of hypothalamic injury in rodents and humans to look for an association with the development of obesity. MRI was used to image and quantify gliosis, a process leading to scars in the central nervous system, in the brains of 34 young humans undergoing clinical examination. Thaler et al. found evidence of increased gliosis in the mediobasal hypothalamus of obese humans and concluded that, in both humans and rodent models, obesity is associated with neuronal injury in a brain area crucial for body weight control. The food reward theory has implications for obesity prevention and treatment via decreasing the reward value of food and enhancing the reward value of alternative activity.

The Obesogenic Environment

We all eat what tastes good and is easy to obtain. When human beings started using agriculture and farming instead of hunting and gathering, diets became less varied, fat consumption increased, and activity levels decreased. Today’s modern food environment contains large amounts of processed food that has been engineered to maximize food reward. Producers have influenced the palatability of foods by increasing quantities of sugar and salt in combination with fats and flavourings. Consumers buy foods for their palatability, convenience and cost. Such palatable and cheap convenience foods are typically obesogenic, i.e., they contain sufficient sugar and fat to produce overweight and obesity when consumed over months or years.

A summary of overall food intake is the number of calories consumed in the daily diet. Data for the USA on calories consumed and obesity prevalence over the period 1960—2010 show a 17% increase in daily calories over the 50-year period that corresponds almost perfectly with the increase in obesity prevalence. However, as always, it would be a serious mistake to assume causation when all we have is a correlation. But when the environment contains all the necessary ’ingredients’ for obesity to happen, then we should not be surprised at the outcome. After all, it is already established that the human body is genetically wired to store fat.

Obesity could well be the inevitable end-product of the ’obesogenic’ environment. This is an environment engineered by a food and drinks industry that promotes fattening, unhealthful food and drink almost without restriction (Swinburn et al., 1999). Obesity can be classified as a non-communicable disease (NCD), a category that also includes cancer, heart disease, diabetes and dementia. Through the sale of unhealthy commodities — tobacco, alcohol and ultra-processed food and drink — transnational corporations are major drivers of global epidemics of NCDs, of which obesity is just one.

Highly profitable industries and supermarket chains will not curb their activities unless required to do so by legislation. In a capitalist society this simply ain’t going to happen. There has been a rise in sales of unhealthy commodities in low-income and middle-income countries compared to high-income countries where sales tended to level off between 1997 and 2009 (Moodie et al., 2013). There is a high concentration in these industries of processed foods and relatively few companies are dominating the market. For example, 75% of world food sales are of processed foods, the largest manufacturers of which control more than a third of the global market.

Common strategies by the transnational corporations deliberately undermine NCD prevention and control. Companies hire doctors to ghost-write scientific papers that cast doubt about findings linking unhealthy products to illness. They also infiltrate governmental committees responsible for regulation. It is evident that unhealthy commodity industries should not have any role in the formation of national or international NCD policy, yet they are often involved in government advisory bodies on food and drinks policies. Only public regulation and intervention can be effective in preventing harm caused by obesity and other NCDs that are the direct result of unhealthy commodity industries.

Foods that Make us Fat

Research on eating behaviour has shown that calorie consumption is higher when meals consist of a variety of foods compared with a single food type, when the food is more palatable, and when it is presented in more energy-dense formulations. More palatable and energy-dense diets result in greater weight gain (Wardle, 2007). Opinions about the optimum macronutrient composition of a healthful diet have been strongly divided. However, three macronutrients have been linked to OAO: fats, sugars and proteins. One of the biggest changes associated with the increase in calories consumed has been the increasing availability of snack and fast foods. These contain high amounts of fat, sugar, protein and salt. In addition to changes in eating habits, portion sizes of main meals have increased substantially. ’Supersizing’ increases consumption: doubling of portion size increases consumption by 35% (Zlatevska et al., 2014).

Epidemiological studies show an association between dietary fat and body fat (adiposity). Hooper et al. (2012) reviewed studies that compared lower with usual total fat intake on body fatness. Low-fat diets were associated with lower relative body weight, but the difference in weight was fairly slight — only 1.6 kg. Moreover, the prevalence of obesity has greatly increased, despite an apparent decrease in the proportion of total calories consumed as fat in the diet of US children (Ebbeling et al., 2002).

In prospective studies, Mozaffarian et al. (2011) studied data from 120,877 US women and men with follow-up periods from 1986 to 2006. Within each four-year period, participants gained an average of 1.52 kg, which would be 7.60 kg over 20 years. Four-year weight change was most strongly associated with the intake of potato chips (0.76 kg), potatoes (0.58 kg), sugar-sweetened beverages (0.45 kg), unprocessed red meats (0.43 kg) and processed meats (0.42 kg). Weight gain was inversely associated with the intake of vegetables (—0.10 kg), whole grains (—0.17 kg), fruits (—0.22 kg), nuts (—0.26 kg) and yogurt (—0.37). ’Lifestyle’ factors associated with weight change included physical activity (—0.80 kg), alcohol use (0.19 kg per drink per day), smoking (new quitters, 2.35 kg; former smokers, 0.06 kg), sleep (more weight gain with < 6 or > 8 hours of sleep) and television watching (0.14 kg per hour per day).

Mozaffarian et al.’s data lead to an interesting inference. If the ’couch potato diet’ of red meat, potatoes, chips and cola (+2.31 kg) is replaced by a ’hairy shirt’ diet of vegetables, grains, fruits, nuts and yogurt (-1.12) plus some physical activity (—0.80) there could be an average weight reduction of 4.15 kg every four years. That comes to a massive 20.4 kg over 20 years. With this rate of change, the obesity pandemic could be solved. Unfortunately, the human tendency to ’go with the flow’ is a more attractive option than to be a lean and restrained spartan. Until the first heart attack, that is.

Food producers have used fats, sugars and salts to tinker with our taste buds while playing havoc with public health. They have experimented with trans fats (a partially hydrogenated oil, PHO), sugars, corn syrup and salt. In 2013, the US Centers for Disease Control and Prevention estimated that a reduction of trans fat could prevent 7,000 deaths from heart disease and up to 20,000 heart attacks each year in the USA. The high risks associated with PHOs led the Food and Drug Administration (FDA) to suggest that PHOs are no longer ’generally recognized as safe’ (GRAS). With the removal of GRAS status, trans fats will all but disappear from the US food chain.

High-fructose corn syrup (HFCS) accounts for 40% of sweeteners used in the USA. The product is in sodas, ketchups and condiments, salad dressings, canned soups, bread, and many other places you possibly don’t expect to find it. Consumption of HFCS increased to 27 kg per person per year between 1970 and 2000, a trend mirrored by the figures for obesity. Studies in endocrinology have suggested a causal relationship between sugar intake and weight gain (e.g., Lustig, 2013).

To summarize the obesity story thus far, a complex array of genetic, nutritional, developmental and environmental factors influence overweight and obesity. None ’tells the whole story’ on its own. Obesity is a clear case of multiple causation. We need to explain not only how obesity can develop in a susceptible individual, but why some individuals develop it and not others. We turn now to consider social and psychological explanations for obesity.

Social Influences: Thin Ideal, Body Dissatisfaction and Stigmatization

Society places a high value on the ’thin ideal’, a body image that is slim and slender with a narrow waist and little body fat. Yet for many, the thin ideal is in direct opposition to both a natural predisposition to become obese and to an obesogenic food environment. Psychologist Kelly Brownell (1992) discussed the search for the perfect body as an instance where physiology and culture collide:

Modern society breeds a search for the perfect body. Today’s aesthetic ideal is extremely thin, and now, superimposed on this, is the need to be physically fit. People seek the ideal, not only because of expected health benefits, but because of what the ideal symbolizes in our culture (self-control, success, acceptance). … Research has shown that biological variables, particularly genetics, are influential in the regulation of body weight and shape. Hence, there are limits to how much a person can change. This places culture in conflict with physiology. In addition, the rewards of being attractive are less than most would expect. There are serious consequences of seeking the ideal and falling short, some psychological and others physiological (e.g. increased health risk for weight cycling). (Brownell, 1992: 1)

The psychological impact of OAO can be measured in terms of the stigma, lowered self-esteem and reduced well-being. The size of the thin ideal is decreasing as the rate of obesity is increasing, making the thin ideal difficult to maintain (Pinhas et al., 1998). Depending on the degree to which the thin body ideal is internalized, the perceived gap between the actual body and the thin ideal can have serious psychological effects (Ahern et al., 2011). Thin ideal internalization is associated with body image and eating disturbances, especially in conjunction with dieting and negative affect (Thompson and Stice, 2001). The thin ideal is a global phenomenon. The influence of the media, especially the representation of the female body on magazine covers, is huge.

Rodgers et al. (2010: 89—95) noted that: ’In Western society, body image concerns are so prevalent among young women they have been called normative, with body dissatisfaction appearing in girls as young as 5 years old.’ The thin ideal is ’transmitted’ from mother to child. Yamazaki and Omori (2014) asked early adolescents (175 girls and 198 boys) in Japan to complete a questionnaire to assess their drive for thinness and perceptions of mothers’ attitudes and behaviours related to body shape. The questionnaire for mothers (n = 206) measured mothers’ thin ideal internalization. The authors found that mothers’ thin ideal internalization was associated with girls’ drive for thinness through the perception of mothers’ attitudes directed to the girls, and with boys’ drive for thinness through observation of their mothers’ weight-loss behaviour.

Bojorquez et al. (2013) examined the bodily experiences of Mexican women to investigate their acceptance of the thin ideal and body dissatisfaction. The interviewees accepted the thin body ideal, but experienced their bodies as ’signifiers of motherhood’ that protected them from body dissatisfaction. Thus perception of overweight may predict body dissatisfaction and weight loss intentions better than weight status itself.

Fredrickson et al. (2015) examined the association of weight perception and weight satisfaction with body change intentions and weight-related behaviours in 928 overweight adolescents (aged 11—18; 44% female). Accurate perception of weight and dissatisfaction with weight were associated with trying to lose weight, but were negatively associated with some healthy weight-related behaviours. Awareness of overweight and body dissatisfaction may be detrimental to the adoption of healthy weight control behaviours. The authors concluded that interventions with overweight adolescents should encourage body satisfaction. Overweight and obesity are rarely, if ever, a deliberate or conscious choice. Yet the blaming, shaming and stigmatization of people with OAO is very common; it heightens the stress of OAO individuals that, in turn, leads to increased eating. People with OAO are openly stigmatized and often incur more open forms of prejudice and discrimination than other stigmatized social groups (Brochu and Esses, 2011). Obesity is often the butt of jokes and cartoons. Puhl and Brownell (2004: 69) stated:

… obese individuals are highly stigmatized. … Given that half the [US] population is overweight, the number of people potentially faced with discrimination and stigmatization is immense. The consequences of being denied jobs, disadvantaged in education, or marginalized by health care professionals because of one’s weight can have a profound impact on family life, social status, and quality of life.

Puhl and Heuer (2009) found no evidence that negative attitudes towards obesity were less prevalent, and concluded that weight bias will remain a social injustice and public health issue, impairing the quality of life for both present and future generations of obese individuals.

Pearl et al. (2015) investigated the effects of weight bias experiences and internalization on exercise among 177 women with OAO in a cross-sectional study. Participants completed questionnaires assessing exercise behaviour, self-efficacy and motivation, experiences of weight stigmatization, weight bias internalization and weight-stigmatizing attitudes towards others. Pearl et al. found that weight stigma experiences positively correlated with exercise behaviour, but weight bias internalization was negatively associated with all exercise variables.

Seacat et al. (2016) studied daily diaries to assess female weight stigmatization. They recruited 50 overweight/obese women from public weight forums to complete week-long daily diaries. A total of 1,077 weight-stigmatizing events were reported. Results indicated that body mass index, education, age, daily activities and interpersonal interactions can all can influence individual levels of stigmatization.

Stigma-based bullying is associated with significant negative mental and physical health outcomes. In a longitudinal study, Rosenthal et al. (2015) used surveys and physical assessments with mostly black and Latino, socio-economically disadvantaged, urban students. Rosenthal et al. reported greater weight- and race-based bullying as being indirectly associated with increased blood pressure and BMI. Bullying was associated with decreased self-rated health across two years.

Public health campaigns designed to prevent or reduce obesity might not be universally helpful and could have detrimental consequences. Simpson et al. (2017) explored the effects of obesity prevention campaigns. Participants viewed either weight-focused or weight-neutral campaigns. Assessments occurred at three time points (pre-, post- and follow-up). Compared with weight-neutral campaigns, weight-focused campaigns were associated with increases in negative perceptions of obesity and decreases in self-efficacy for health behaviour change. People don’t like being preached to with scare tactics.

We turn now to consider some of the main psychological processes associated with obesity.

Emotion, Personality, Body Dissatisfaction and Depression

One hypothesis to explain obesity has been to attribute overeating to emotionality. People are said to eat to calm themselves, assuage sadness or guilt or reduce feelings of loneliness. In spite of its intuitive appeal, the evidence for this theory is positive but inconsistent.

Rodin (1973) studied the effects of distraction on performance of obese and normal-weight participants. Male undergraduates worked on tasks requiring concentration, while competing; irrelevant material was also used to distract them. Rodin found that overweight students were more disrupted than normal-weight students by interesting, emotionally toned material, while they performed better than normals when there were no distracting events. Rodin suggested that obese people may have a heightened responsiveness to external cues. This finding led to a theory that obese people were not only more responsive to external cues, but also ate more when feeling anxious, bored or depressed (Schachter and Rodin, 1974). This is the theory that obesity is related to emotional eating.

Polivy et al. (1978) compared the emotional responsiveness of dieters and non-dieters in a sample of male college students. Dieters were found to be more extreme emotional responders. When an internal source of arousal (i.e., caffeine) was provided, non-dieters became more emotional and dieters became less emotional.

Lowe and Fisher (1993) compared the emotional reactivity and emotional eating of normal-weight and overweight female college students in a natural environment. Their participants self-monitored food intake and pre-eating mood at each episode of eating for 12 consecutive days. The obese students were more emotionally reactive and more likely to engage in emotional eating than normal-weight individuals with snacks but not with meals. Emotional distress was associated with snack eating, and emotional eating was related to their percentage overweight.

Other studies explored emotional eating and regulation in obese young people from non-student populations and in adults. They have also looked at family and peer relational factors as a source of the emotion and feeling. Vandewalle et al. (2014) explored the association between parental rejection and emotional eating in 110 obese young people aged 10 and 16 years attending a Belgian treatment centre for obesity. Maladaptive emotion regulation strategies mediated the relation between maternal rejection and emotional eating. Paternal rejection itself was not associated with emotion regulation or with emotional eating in the young people.

Personality traits can contribute to unhealthy weight increases and difficulties with weight management. Sutin et al. (2011) studied the association between personality and obesity across the adult lifespan. Their data came from a longitudinal study with 1,988 participants who spanned more than 50 years to investigate personality associations with adiposity and fluctuations in BMI. Participants with higher neuroticism or extraversion or lower conscientiousness had higher BMI, more body fat, and larger waist and hip circumferences. The strongest association was found for impulsivity. Participants who scored in the top 10% of impulsivity weighed, on average, 11 kg more than those in the bottom 10% (Figure 10.5).

Figure 10.5 Estimated BMI for participants one Standard Deviation above and below the mean on impulsiveness


Source: Sutin et al. (2011)

Another psychological factor is dietary restraint, the attempt to hold back from eating. Restraint can create a rebound effect in the form of binge eating. In a cross-sectional study, Marcus et al. (1985) determined the prevalence and severity of binge eating among 432 women seeking behavioural treatment for obesity and to assess the relationship between binge eating and dietary restraint; 46% of women reported serious binge eating, especially younger and heavier women, in whom binge eating severity was related to overall dietary restraint. A prospective study by Johnson and Wardle (2005), however, found no evidence that dietary restraint causes bulimic binge eating. A survey of 1,177 adolescent girls explored whether emotional eating, binge eating, abnormal attitudes to eating and weight, low self-esteem, stress and depression are associated with dietary restraint or body dissatisfaction. Restraint was associated only with more negative attitudes to eating, whereas body dissatisfaction was significantly associated with all adverse outcomes, casting doubt on the hypothesis that restrained eating is a primary cause of bulimic symptoms and emotional eating. Many studies have shown that body dissatisfaction is associated with depression (e.g., Paxton et al., 2006).

Psychiatric studies indicate a reliable association between depression and obesity both in cross-sectional and prospective studies. Onyike et al. (2003) studied rates of depression in the past month for both men and women as a function of BMI (Figure 10.6). The data came from 9,997 respondents to the National Health and Nutrition Examination Survey (NHANES), an interview survey of the US population.

Obesity was associated with increased rates of depression. Being severely obese (BMI ≥ 40) resulted in markedly higher rates of depression. This study provides no evidence on causation. However, it seems likely from other evidence that causation runs in both directions, which is confirmed in prospective studies.

Figure 10.6 The relationship between depression and BMI


Source: Onyike et al. (2003)

Luppino et al. (2010) conducted a systematic review and meta-analysis on the longitudinal relationship between depression, overweight and obesity to identify possible influencing factors. They reviewed studies examining the longitudinal relationship between depression and overweight (BMI 25—29.99) or obesity (BMI ≥ 30). Obesity at baseline increased the risk of onset of depression at follow-up by 55%. Overweight also increased the risk of onset of depression at follow-up by 27%. Depression increased the odds for developing obesity by 58%. Luppino et al. (2010: 220) concluded that the meta-analysis confirmed a reciprocal link between depression and obesity.

The evidence on the psychological influences on obesity suggests a homeostatic system, a ’circle of discontent’ (Figure 10.7). Empirical evidence of this ’vicious circle’ in adolescents and obese women is present in the literature (e.g., Wardle et al., 2001; Chaiton et al., 2009; Goldfield et al., 2010; Sonneville et al., 2012). This ’circle of discontent’ requires systematic investigation using prospective studies (Marks, 2015).

Figure 10.7 A theory linking body dissatisfaction, depression, emotional eating, and overweight and obesity


Source: Marks (2015)


Dietary Guidelines

One of the main strategies for preventing obesity and overweight at a societal or population level is the publication of dietary guidelines. The Dietary Guidelines for Americans (DGA) is updated every five years as a blueprint for nutrition policies such as School Lunch. The guidelines are intended to reduce coronary heart disease (CHD) mortality by reducing dietary fat intake. On 7 January 2016, the US Department of Health and Human Services and the Department of Agriculture released the DGA 2015—2020. What if those guidelines are wrong? Evidence from epidemiology suggests that they probably are. The controversy surrounding the 2015 DGA was unprecedented. Critics claimed the DGA was not based on a comprehensive review of the most rigorous and recent science (Teicholz, 2015). The research ignored in the DGA included recent findings on saturated fats and low CHO diets.

Box 10.3 The Dietary Guidelines for Americans 2015—2020

Key recommendations

1. Consume a healthy eating pattern that accounts for all foods and beverages within an appropriate calorie level.

2. A healthy eating pattern includes:

1. A variety of vegetables from all of the subgroups—dark green, red and orange, legumes (beans and peas), starchy, and other

2. Fruits, especially whole fruits

3. Grains, at least half of which are whole grains

4. Fat-free or low-fat dairy, including milk, yogurt, cheese, and/or fortified soy beverages

5. A variety of protein foods, including seafood, lean meats and poultry, eggs, legumes (beans and peas), and nuts, seeds, and soy products

6. Oils

7. A healthy eating pattern limits: Saturated fats and trans fats, added sugars, and sodium

3. Key Recommendations that are quantitative are provided for several components of the diet that should be limited. These components are of particular public health concern in the United States, and the specified limits can help individuals achieve healthy eating patterns within calorie limits:

o viii. Consume less than 10 percent of calories per day from added sugars

o ix. Consume less than 10 percent of calories per day from saturated fats

o x. Consume less than 2,300 milligrams (mg) per day of sodium

4. If alcohol is consumed, it should be consumed in moderation—up to one drink per day for women and up to two drinks per day for men—and only by adults of legal drinking age.

5. In tandem with the recommendations above, Americans of all ages—children, adolescents, adults, and older adults—should meet the Physical Activity Guidelines for Americans to help promote health and reduce the risk of chronic disease. Americans should aim to achieve and maintain a healthy body weight. The relationship between diet and physical activity contributes to calorie balance and managing body weight. As such, the Dietary Guidelines includes a Key Recommendation to Meet the Physical Activity Guidelines for Americans.

Source: Dietary Guidelines Advisory Committee (2015—2020:

Attempts by health authorities to promote healthy eating through guidelines has sometimes led to public anger and confusion about portion sizes, dietary fat, percentage energy and certain nutrients. Nutritional messages in public health and commercial sources are perceived as conflicting and food guides are used minimally by consumers (Boylan et al., 2013). To be usefully applied as a guide to eating behaviour, guidelines need clearly and consistently to inform people what, when and where to eat, not only how much they should consume. De Ridder et al. (2013) argued that people’s ability to regulate their eating is compromised by a lack of clear, shared standards that guide eating behaviour.

Harcombe et al. (2016) carried out a systematic review to examine the epidemiological evidence concerning the dietary guideline to reduce the consumption of fat. They found no support for the recommendations to restrict dietary fat. The epidemiological evidence suggested no significant association between CHD mortality and total fat or saturated fat intake and thus does not support the present dietary fat guidelines.

Nissen (2016b) questions why the committee responsible for the DGA 2015—2020 took a U-turn on cholesterol. The preliminary report (February 2015) had reversed ’decades of dogma’ with the statement that ’cholesterol is not a nutrient of concern for overconsumption’. In the final 2015 report this statement had been removed, instead suggesting that ’individuals should eat as little dietary cholesterol as possible’. Quite reasonably, Nissen (2016b: 588) wonders how, for decades, the US medical establishment had ’erroneously advised the population to severely limit cholesterol intake and to consider whether other conventional dietary advice will eventually prove faulty’.

Guidelines that are unreliable and based on dogma will not be trusted and we should not be surprised if people choose not to follow them.

Vegetarianism and Veganism

One underutilized intervention for overweight and obesity is a vegetarian or vegan diet. Vegetarian diets include eggs and/or dairy but no other foods derived from animal sources. Vegan diets exclude all animal-based foods. Such diets can be motivated by ethical beliefs against animal cruelty, by concerns for the environment or by an interest in improved health, including the desire to lose weight. Total consumption of meat and dairy by meat eaters is striking. Each year a US meat eater consumes 130 shellfish, 40 fish, 26 chickens, one turkey, nearly half a pig and a little more than a tenth of a cow. That’s nearly 200 animals a year or 16,000 animals over a lifetime (Mohr, 2012). Ruminants (cattle, water buffalo, sheep and goats) use 86% of the world’s agricultural land and consume 71% of its total biomass, yet produce only 8% of its food (Smith et al., 2013).

Key et al. (1998) compared the mortality rates of vegetarians and non-vegetarians among 76,000 men and women who had participated in five prospective studies. This meta-analysis collated the entire body of evidence collected in prospective studies in Western countries from 1960 to 1981. The original studies were conducted in California (2), Britain (2) and Germany (1) and provided data concerning 16—89-year-olds for whom diet and smoking status information was available. Vegetarians were defined as those who did not eat any meat or fish (n = 27,808). Participants were followed for an average of 10.6 years when 8,330 deaths occurred. The results showed that vegetarians as a group contained a lower proportion of smokers and current alcohol drinkers but a higher proportion of high exercisers, and had a consistently lower BMI. The death rate ratio for ischaemic heart disease for vegetarians versus non-vegetarians across the five studies was 0.76 (95% CI 0.62—0.94). The all-cause mortality ratio was 0.95 (95% CI 0.82—1.11). When non-vegetarians were subdivided into regular meat eaters and semi-vegetarians who ate fish only or ate meat less than once a week, there was evidence of a significant dose-response. The death rate ratio for ischaemic heart disease, caused by a narrowing of the arteries, for semi-vegetarians and vegetarians compared to regular meat eaters was 0.78 and 0.66 respectively. Vegetarians have a lower risk of dying from ischaemic heart disease than non-vegetarians.

A meta-analysis with over 120,000 participants reported a 29% lower risk of death from cardiovascular disease in vegetarians (those eating meat or fish less than once a week) and an 18% lower incidence of cancer overall in vegetarians (Huang et al., 2012). Vegetarians have a lower risk of hospitalization or death from ischaemic heart disease (Crowe et al., 2013); lower blood pressure and a lower risk of having hypertension (Pettersen et al., 2012; Yokoyama et al., 2014); lower risk of developing metabolic syndrome (Rizzo et al., 2011); and a lower risk of some cancers than do meat eaters. Vegetarians and fish eaters had a lower risk of cancer compared to meat eaters (Key et al., 2009). They have a lower risk of diverticular disease compared to meat eaters or fish eaters; vegans have an even lower risk (Crowe et al., 2011). Vegetarians, especially vegans, have a lower risk of developing Type 2 diabetes (Tonstad et al., 2009, 2013). However, vegans require dietary supplements of vitamin B12, B6, D and iodine.

A neglected factor has been fibre. The Seven Countries study found fibre intake was inversely related to body weight (Menotti et al., 1989). Large-scale studies by the European Prospective Investigation into Cancer and Nutrition (EPIC) produced data that could be applied to the study of obesity. For example, Fogelholm et al. (2012) examined the role of dietary macronutrient composition, food consumption and dietary patterns in predicting weight or waist circumference change, with and without prior weight reduction. The results show that dietary fibre, especially cereal fibre, fruit/vegetable intake and the Mediterranean dietary pattern, were inversely associated with weight or waist change. A mechanism for the protective effect of fibre was elucidated in 2014 (De Vadder et al., 2014). It involves the intestinal flora and the ability of the intestine to produce glucose between meals.

Nath (2011) explored the impact of hegemonic masculinity upon the adoption of meatless diets. The evidence suggested that the belief that meat provides strength and vigour to men and the enforcement of meat-eating as a social norm help to explain why vegetarianism is not viewed as an appealing choice for men. However, evidence suggests that this concern is becoming less evident as vegetarianism is gaining in popularity among both men and women.

Vegetarian and vegan diets are affordable and environmentally friendly. One UK study has shown that changing from a non-vegetarian to a vegetarian or vegan diet could reduce greenhouse gas emissions by 22% and 26%, respectively. Any of these changes would be less expensive than the average diet in the UK and would have adequate protein (Berners-Lee et al., 2012). On current evidence, vegetarian and vegan diets provide a sustainable and effective means for achieving healthful levels of nutrition and body weight.

Drug Therapies and Bariatric Surgery

Long-term safety concerns limit the use of drugs to bring about weight loss. Five major drugs have been withdrawn owing to safety concerns. The two remaining drugs are phentermine, a derivative of amphetamine (an appetite suppressant), and orlistat, which reduces the amount of fat absorbed from food eaten. Orlistat has negative side effects that have resulted in poor tolerability, low adherence and varied effectiveness. Orlistat is currently available over the counter in European countries and elsewhere.

An average weight loss of 5% is regarded as the minimum threshold for approval guidelines issued by regulatory authorities, yet the majority of patients will often set much higher targets of 10—15%. Modest efficacy is offered by current drug therapies for obesity, but a history of poor tolerability and a lack of safety, a paucity of novel therapies, and a lack of reimbursement have substantially constrained developers of new drugs for obesity (Wong et al., 2012).

At least 25% of people in the UK are obese, yet only 1.3% (2.1% of females, 0.6% of males) received anti-obesity medication (Patterson et al., 2014). The relationship between medication rates and age differs by gender, with prescriptions higher in younger females and older males. While the prevalence of obesity worsens with age, younger females are more likely to be prescribed anti-obesity medication, suggesting an element of patient demand.

Medication gives patients an imperfect solution to OAO while perpetuating feelings of learned helplessness. Hollywood and Ogden (2014), using thematic analysis, studied ten participants’ experiences of gaining weight after taking orlistat. They found that the participants attributed their failure to lose weight to the medication and emphasized a medical model of obesity. Their weight gain was fatalistically considered an inevitable part of their self-identity, that of a perpetual dieter.

Bariatric surgical procedures forcibly induce a drastic lifestyle change and can elicit up to 20% weight loss, but carry inherent medical risks and high cost. Bariatric surgery is the most effective treatment for the severely obese but it does not work for everyone (Husted and Ogden, 2014). MackSense (2014) reported a huge jump in the number of NHS-funded bariatric procedures in England, from 261 in 2000—2001 to 8,087 in 2010—2011. It estimated that for 2001—2011 less than 1% of people eligible for bariatric surgery received the treatment, i.e., 5,000—10,000 (MackSense, 2014). In the USA, the incidence of bariatric surgery plateaued by 2010 at approximately 113,000 cases per year (Livingston, 2010). Complication rates fell from 10.5% in 1993 to 7.6% of cases in 2006. Bariatric surgery costs the health economy at least $1.5 billion annually.

Another study suggests that a significant variable in predicting the success of bariatric surgery is a person’s investment in the operation — i.e., the extent to which they are committed and also their undertaking, in time, finance, emotion, or physical and behavioural effort. In an RCT, Husted and Ogden (2014) found that success following surgery was related to individuals’ sense of investment in the surgery, with failure being linked to hedonic motivation to consume food and greater susceptibility to food in the environment. The intervention raised the salience of personal investment in having weight-loss surgery by reducing automatic hedonic thoughts about food to aid weight loss. After three months, the intervention group had a mean weight loss of 6.77 kg compared to 0.91 kg for the control participants. This simple, cost-effective psychological intervention facilitated weight loss and changed hedonic thoughts about food in bariatric patients.

Jumbe et al. (2017) discuss the literature on the psychological impact of bariatric surgery, exploring whether the procedure addresses underlying psychological conditions that can lead to morbid obesity and the effect on eating behaviour postoperatively. Their findings show that this literature suggests some persisting disorder in psychological outcomes like depression and body image for patients at longer-term follow-up, compared to control groups. The authors state that understanding the reasons behind these findings is limited due to a lack of postoperative psychological monitoring and theoretical mapping. Jumbe et al. (2017: 71) conclude that ’Reframing of bariatric approaches to morbid obesity to incorporate psychological experience postoperatively would facilitate understanding of psychological aspects of bariatric surgery and how this surgical treatment maps onto the disease trajectory of obesity’.

Significant weight loss after bariatric surgery creates a high demand for body contouring surgery. In a qualitative study, Gilmartin et al. (2013) observed two major quality-of-life perception changes for patients who had undergone contouring surgery after dramatic weight loss: ’identity transformation’, which embraced improved physical function and enhanced self-esteem, confidence and quality of life, and a ’changed lifestyle’. The participants talked about ’discarding stigmatized identities’ and transitioning towards new identity meanings that are perceived as ’normal’ in comparison to their former stigmatized ’fat/ugly’ categorization. One female 58-year-old explained: ’A new powerful self emerged. I am happy with my body shape and self-perception. The surgery dramatically altered my physical appearance and my inner world too. The journey has birthed a new personality and identity’ (Gilmartin et al., in press).

Behavioural Interventions and the Raising of False Hopes

A variety of interventions have been tried at the individual level of influence. The quality of the research used to evaluate the interventions is of varied quality but mostly poor. Sample sizes are small, power analyses are rarely if ever carried out, and designs are poor overall. Systematic reviews on effectiveness will briefly illustrate the crisis situation that exists in dealing with obesity using behavioural methods.

Traditional approaches have used diets and exercise. Behavioural programmes have produced weight losses of 10 kg on average at the end of six months (Wing, 2004). Adherence to such programmes is low and attrition high. Those most in need of reducing weight show least adherence. For example, there is an association between waist circumference percentile and non-adherence. Long-term follow-up show gradual weight regain such that four years after treatment only a modest amount of weight loss remains (M = 1.8 kg) (Perri et al., 2004).

The use of temporary diets and activity programmes produce only temporary effects. People who wish to maintain a lower weight over their entire lifetime need to commit to permanent lifestyle change. Only a small percentage of people are willing to make such a commitment. There is no magic bullet.

Lifestyle modifications remain the safest means of prevention and treatment of OAO but they are also the least effective. The Energy Surfeit Theory and dietary guidelines have proven to be a poor basis for interventions. Stice et al. (2006), in a meta-analytic review of obesity prevention programmes for children and adolescents, reported mediocre results: most (79%) did not produce statistically reliable weight gain prevention effects. The average intervention effect size was an r of 0.04, a trivial result. Dozens of SRs have evaluated the effectiveness of behavioural interventions with a multiplicity of OAO groups. Universally, outcomes have been modest, with average weight loss rarely exceeding 5% of body weight. Follow-up over a few years suggests that maintenance of weight loss is almost non-existent.

The basis for dietary interventions often appears to be the existing dietary guidelines themselves. Hafekost et al. (2013) suggested that reliance on dietary guidelines to inform interventions may be holding back progress as few interventions are testing alternative models. They point out that alternative interventions, such as CHO restricted, low glycaemic index and low fructose, have a more plausible rationale than energy balance.

As early as 1991, therapists’ competence to help obese patients lose weight was being questioned:

Although millions seek treatments for obesity, the benefits of treatment have been overstated. For most people, treatment is not effective; the majority of the obese struggle in vain to lose weight and blame themselves for relapses. … Many therapists may be contributing to this psychologic damage by giving their patients false hope for success… (Wooley and Garner, 1991: 1248)

Hafekost et al. (2013) questioned whether ’the public health message’ matches scientific knowledge of obesity. They examined the models of energy balance underpinning current research about weight-loss intervention from the field of public health, and determined whether they are consistent with the model provided by basic science. Most public health interventions were based on the energy balance theory, and attempted to reduce caloric consumption and/or increase physical activity in order to create a negative energy balance. Hafekost et al. (2013: 41) concluded that: ’Public health weight-loss interventions seem to be based on an outdated understanding of the science. … Instead of asking why people persist in eating too much and exercising too little, the key questions of obesity research should address those factors (environmental, behavioural or otherwise) that lead to dysregulation of the homeostatic mechanism.’

They also raise an important ethical point: Is it right to offer interventions that have not worked in the past?

Despite the extensive literature on their long-term ineffectiveness, interventions based on this simplistic understanding of energy balance continue to be advocated under the assumption that previous interventions have not been pursued sufficiently vigorously or that participants have failed to follow the prescriptions of the intervention. … Continuing to promote a model that is unlikely to be successful in the longer term, and may result in individuals becoming discouraged, is both unproductive and wasteful of resources that could be better spent on investigating more plausible alternatives to improving weight control. (Hafekost et al., 2013: 5)

The evidence of effectiveness of behavioural interventions is so weak, we can only hope the old dictum ’prevention is better than cure’ will one day be acted on. This requires legislation to make healthful foods more affordable and fatty foods and sugary drinks less attractive (Marks, 2015).

Future Research

1. There is an urgent need for the design of science-based dietary guidelines without any interference from industry to provide effective guidance of eating behaviour.

2. Research is needed into finding ways of making food labelling accessible, clear, transparent, usable and accurate.

3. Research is needed for methods of facilitating long-term dietary change towards reduced consumption of sugars, processed foods and red meats.

4. The insulin theory claims that obesity is caused by a chronic elevation of insulin in a diet that contains too much CHO. The homeostasis theory explains obesity as a ’circle of discontent’. Further research is required to enable these theories to be empirically evaluated.


1. Human beings are endowed by evolution to store excess food energy as fat. This natural endowment has led to an evolutionary ’hiccough’ called the obesity pandemic.

2. The food and drinks industries, with the tacit approval of state bodies, have successfully promoted a large variety of cheap, popular and unhealthy products consisting of snacks, ready meals, junk food and fizzy drinks, together creating an ’obesogenic’ environment with excessive sugars, salt and fats.

3. Obesity is an excessive increase in the size and number of fat cells. By 2050, it is predicted that the majority of adults and 25% of children will be obese.

4. According to the Energy Surfeit Theory (EST), obesity is caused by an excess of calories. Interventions based on the EST have failed to break the epidemic and have led to a ’blame and shame’ culture in which victims are blamed for their condition and, in some places, health services are withdrawn.

5. Lack of progress and stagnation with the EST approach requires new evidence-based approaches to tackle obesity. The insulin theory claims that obesity is caused by a chronic elevation of insulin in a diet that contains too much carbohydrate. The homeostasis theory explains obesity as a vicious ’circle of discontent’, involving body dissatisfaction, negative affect and emotional consumption.

6. Obesity begins in the womb, develops in the crib and accelerates in early life. Attachment patterns, body dissatisfaction and negative affect influence eating and food preferences in early adolescence and these patterns continue into adulthood.

7. In spite of high prevalences of overweight and obesity almost everywhere, the ’thin ideal’ pervades popular culture with narratives and images of thinness. This influence can have nothing but a negative effect on both young and adult people the world over.

8. Diets that are low in carbohydrates and plant-based diets containing low amounts of sugar, little or no red meat and the minimum of fats promote weight loss and help prevent obesity, diabetes, metabolic syndrome, coronary heart disease and cancer.

9. Drug therapies have poor outcomes. The most effective treatment, bariatric surgery, is costly and inaccessible to the majority of people who would benefit from it. There also can be unwanted, long-term effects from surgery.

10. Governmental actions, guidelines and programmes independent of corporate interests are required at all levels of society to reduce the prevalence of obesity and other chronic, diet-based conditions.