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Socio-economic Impact of Obesity Management on the US Economy

Info: 9390 words (38 pages) Dissertation
Published: 11th Dec 2019

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Tags: EconomicsInternational StudiesSociology


Obesity is fast becoming a serious epidemic in the United States due partly to eating habits and physical inactivity amongst Americans. According to the Centre for Disease Control, Seventy-three percent of adults and 43 percent of all children in the United States are overweight or obese. Among African-Americans 20 years and over, more than two-thirds are overweight or obese (Gaines, 2010). Generally, the rate of overweight and obesity are higher for African-American and Hispanic women than Caucasian women, higher in the south and Midwest and increases with age (Ogden et al., 2014; Gregg et al., 2009; Sherry et al., 2010). According to the World Health Organization, body mass index (BMI) of an obese person has a value greater than or equal to thirty. Type 2 diabetes and high blood pressure are two diseases that ultimately affect African Americans and this is predominantly caused by an increase in weight as those extra pounds predisposes a person to these diseases (Gaines, 2010). Obesity is one of the primary risk factor for heart diseases, diabetes and a number of cancers and these are major causes of death in American today. The health implication of obesity and the complications associated with it is increasingly becoming more detrimental than cigarette smoking and has therefore become one of the major preventable causes of death worldwide.

This investigation paper focuses on the brief history of obesity; this will take obesity from its discovery over 2000 years to this present day. An understanding of the BMI classification, aetiological determinants, pathophysiology and health effects is important if obesity prevalence will be curtailed. Furthermore, the socio economic impact of obesity management on the United States economy will be looked into. Finally, its treatment options, prevention and trends of the disease will be discussed.


The Ancient Greeks were the first to acknowledge obesity as a health disorder and this was further recognized by the Ancient Egyptians in a similar way. According to Hippocrates, corpulence is not only a disease itself, but the harbinger of other diseases (Haslam & James, 2005). Hippocrates which was the Ancient Greek Father of Western medicine acknowledged obesity in his work and details of various diseases including diabetes was first given by him. Another Indian surgeon Sushruta, also discovered the association between obesity, diabetes and heart diseases and he was the first person to find out the significant signs, symptoms, causes and health implications. In the Ancient days, man always strived for food due to scarcity or famine and this resulted in obesity being regarded as a sign of wealth and good fortune in the middle age. However, all this changed when the scientific society of the 20th century revealed the medical implications of obesity (Caballero B., 2007)

With the inception of the industrial revolution, body size and strength of soldiers and workers became pertinent as this was attributed to the military and economic power of Nations (Caballero, 2007). The increase in the average body mass index from underweight to the normal on the BMI charts played an important role in the development of industrialized societies (Caballero, 2007).  Therefore in the 19th century, there was an increase in weight and height generally. However, during the 20th century, the genetic potentials for height was reached and this resulted to weight increasing more than height in this century and thus resulted in the average increase in BMI (Caballero, 2007). In human evolution, for the first time, the number of adults with excess weight exceeded the number of those who were underweight which further led to obesity (Caballero, 2007).

The perceptions of the public as regards healthy body weight varied from those regarded as normal in the western society, but this perception was changed in the beginning of the 20th century. There was a reduction in the weight seen as normal since 1920s and this was evident by the 2% increase in average height of the Miss America pageant winners and a 12% decrease in weight between year 1922 and 1999 (Rubinstein & Caballero, 2000). Also, the perception of most people as regards healthy weight has changed, for example in Britain the weight at which people regarded themselves to be overweight was considerably higher in 2007 than in 1999 (Johnson & Wardle, 2008). Obesity is still regarded as an indication of wealth and well-being in many parts of Africa and this has become more widespread since the HIV epidemic began (Haslam & James, 2005).


According to the World Health Organization, Body Mass Index (BMI) is a simple index of weight-for-height that is commonly used to classify underweight, normal weight, overweight and obesity in adults. It is defined as the weight in kilograms divided by the square of the height in metres (kg/m2) (W.H.O. 2004). For example, an adult who weighs 60kg and whose height is 1.65m will have a BMI of 22.0.

BMI = 60 kg / (1.65 m2) = 60 / 2.72 = 22.04


Lean Body Mass is a component of body composition, it is calculated by subtracting body fat weight from total body weight. Total body weight is lean plus fat.

In equations: LBM = BW − BF

Lean Body Mass equals Body Weight minus Body Fat


Lean Body Mass plus Body Fat equals Body Weight

Lean Body Weight (men) = (1.10 x Weight(kg)) – 128 ( Weight2/(100 x Height(m))2)

Lean Body Weight (women) = (1.07 x Weight(kg)) – 148 ( Weight2/(100 x Height(m))2)

Ideal Body Weight (men) = 50 + 2.3 ( Height(in) – 60 )

Ideal Body Weight (women) = 45.5 + 2.3 ( Height(in) – 60 )

Body Mass Index = Weight(kg) / Height(m)2

The table below further explains the classification of BMI in relation to the weight and height of an individual.

Table 1: The International Classification of adult underweight, overweight and obesity according to BMI

Classification BMI(kg/m2)
Principal cut-off points Additional cut-off points
Underweight <18.50 <18.50
     Severe thinness <16.00 <16.00
     Moderate thinness 16.00 – 16.99 16.00 – 16.99
     Mild thinness 17.00 – 18.49 17.00 – 18.49
Normal range 18.50 – 24.99 18.50 – 22.99
23.00 – 24.99
Overweight ≥25.00 ≥25.00
     Pre-obese 25.00 – 29.99 25.00 – 27.49
27.50 – 29.99
     Obese ≥30.00 ≥30.00
          Obese class I 30.00 – 34.99 30.00 – 32.49
32.50 – 34.99
          Obese class II 35.00 – 39.99 35.00 – 37.49
37.50 – 39.99
          Obese class III ≥40.00 ≥40.00

Source: Adapted from WHO, 1995, WHO, 2000 and WHO 2004.

BMI values are age dependent and are the same for both males and females (WHO, 2000). The health risks associated with increasing BMI are many and the interpretation of BMI values in relation to risk may vary for different populations in different geographical locations (WHO, 2004).


Obesity is a heterogeneous group of conditions with numerous causes, it is not merely a single disorder and it is predominantly expressed phenotypically (Susan A.J, 1997). Obesity is hereditary, but the genetic component does not follow simple Mendelian principles and the effect of the genotype on the aetiology of obesity may be decreased or increased by factors that are non-genetic (Susan A.J, 1997). Several factors determine the body weight, and these are interactions of genetic, environmental and psychosocial factors which are in relation to the amount of energy consumed and the amount of energy expended and the resulting acting through the physiological mediators of energy intake and energy expenditure and the resulting equilibrium between both (Susan A.J, 1997).


Certain endocrinological disorders may lead to obesity, but this applies to a very small percentage of the total number of cases (Susan A.J, 1997). The endocrinological determinants of obesity have been reviewed recently (Bouchard C., Perusse L., Leblanc C., Tremblay A, & Theriault, 1988). The single disorder that causes obesity in this group is hypothyroidism in which increased weight occurs largely as a result of reduced energy expenditure (Susan A.J, 1997). Other endocrinological factors contributing to obesity include Cushing’s syndrome and disorders of corticosteroid metabolism, where weight gain is typically accompanied by a distinctive prototype of fat deposition in the trunk, sex hormone disorders including hypogonadism in men and ovariectomy in women, insulinoma and growth hormone deficiency (Susan A.J, 1997). The key causes of weight gain in these cases are the amount of energy intake. Certain hypothalamic tumors or damage to the hypothalamic part of the brain as a result of excessive exposure to radiation, infectious agents or head trauma can also lead to obesity with defect in appetite control and hyperphagia (Susan A.J, 1997). A hypothalamic disorder is also believed to be the foundation of a number of congenital abnormalities which could also result in obesity, e.g. Prader-Willi syndrome, which is an abnormality that could be a primary cause of obesity (Susan A.J, 1997).


At a population level, the genetic influence of obesity is expressed in terms of heritability (Susan A.J, 1997). This refers to the percentage of the total difference in a character which is attributable to genetic factors (Susan A.J, 1997). The heritability of obesity may be considered either in terms of the total fatness of an individual or the distribution of body fat in an individual (Susan A.J, 1997). Several discoveries have been made over the years regarding the influence of genetics on chronic diseases like cardiovascular disease and obesity (R. C. Whitaker, J.A. Wright, M.S. Pepe, K.D. Seidel, &W.H. Dietz., 1997). Recent reports indicate that at least 32 genes contribute to common forms of obesity. Many of these genes are thought to be related to the development of obesity through the deregulation metabolic hormones in the body (Susan A J, 1997).

The obesity related variant in the fat mass and obesity-associated protein also known as alpha-ketoglutarate-dependent dioxygenase FTO, has aroused interest in pediatrics due to its relationship with increased weight and ponderal index at 2 weeks of age (A. Lopez-Bermejo, C.J. Petry, M. Diaz, et al., 2008). FTO is located on the long arm of the chromosome 16 and is expressed in the brain, specifically the hypothalamic nuclei (Khung E. Rhee et al. 2012). Those who are homogenous for the at-risk allele have been found to be 3kg heavier than those who do not have the allele (T.M. Frayling, N. J. Timpson, M. N. Weedon et al. 2007). This weight gain is likely due to the gene’s involvement in the regulation of energy intake (Khung E. Rhee et al. 2012). According to recent studies, individuals carrying the at-risk allele prefer dense energy foods (J.E Cecil, R. Tavendale, P. Watt, M. M. Hetherington, & C.N.A Palmer, 2008), have reduced feeling of satiety (J. Wardle, S. Carnell, C.M.A. Haworth, I.S. Farooqi, S. O’Rahilly, & R. Plomin, 2008), display loss of control over eating (M. Tanofsky-Kraff, J.C. Han, K. Anandalingam et al. 2009), consume more fat and calories (even after adjusting for BMI) (N. J. Timpson, P.M. Emmett, T.M. Frayling, et al. 2008) and display a greater tendency towards consuming palatable foods after eating a meal (J. Wardle, C.Llewellyn, S. Sanderson, & R. Plomin, 2009). Therefore, FTO isn’t associated with energy expenditure, but it increases the susceptibility of individuals to higher calorie consumption and decreased satisfaction. A meta- analysis of 45 studies found that adults who were physically active attenuate the odds of obesity associated with FTO by almost 30% (T.O. Kilpelainen, L. Qi, S. Brage, et al. 2011). Thus carrying a gene for obesity does not necessarily predestine one to be obese (D. Meyre, K. Proulx, H. Kawagoe-Takaki et al. 2010), but rather increases the risk in the face of an obesogenic environment (Khung E. Rhee et al. 2012).

Numerous studies in different ethnic groups suggest that the familial correlation in the total body fatness, expressed as body mass index, (BMI; kg/m2) from parent to offspring is about 0.2 and for sibling-sibling relationships about 0.25 (Bouchard C, Perusse L, Leblanc C, Tremblay A, Theriault G. 1988). As would be expected, studies of twins show a much higher concentration, particularly in monozygotic pairs (Susan A.J, 1997). However, these findings do not segregate the independent effects of genetic transmission and a shared environment (Susan A.J, 1997). Further studies of twins reared apart attribute 50-70% of the difference in BMI in later life to genetic factors (Stunkard A, Harris J, Pedersen N, McClearn G. 1990). Adoption studies, where an individual is compared both to their biological parent and their adopted parents, have also demonstrated the importance of genetic influences (Susan A.J, 1997). There is a strong relationship between the BMI of the adoptee and their biological parents across the entire range of fatness, but no relationship between the adoptee and their adoptive parents (Stunkard A, Sorensen T, Hanis C. et al. 1986).

Studies of fat distribution have considered both the ratio of subcutaneous to total fat mass and the distribution of subcutaneous fat in the trunk relative to the limbs (Susan A.J, 1997). Data from the Quebec Family Study, suggest that the size of the internal fat stores are more strongly influenced by genetic factors than subcutaneous depots (Bouchard C., Perusse L., Leblanc C., Tremblay A, Theriault, 1988). Familial clustering suggests that genetic factors may account for 37% of the variance in the trunk to extremity skin fold thickness ratio (Rice T, Bouchard C, Perusse L, Rao D. 1995). These combined evidence from these genetic analysis suggests that obesity is a polygenic disorder and that a considerable proportion of the variance is non-additive (Susan A.J, 1997). This would explain the higher correlations between siblings than those between parent and offspring, and the 2-fold greater correlation between monozygotic than dizygotic twins (Susan A.J, 1997). These genetic influences seem to operate through susceptible genes; the occurrence of the gene increases the risk of developing a characteristic but not essential for its expression nor is it, in itself, sufficient to explain the development of the disease (Susan A.J, 1997). Unlike animal models, where a number of single genes can lead to obesity, no human obesity gene has yet been characterized, but the heterogeneous nature of human obesity does not preclude the identification of small number of individuals with a single defect which leads to obesity (Susan A.J, 1997). In man, a number of genetically determined conditions result in excess body weight or fatness (e.g Prader-Willi syndrome or Bardet-Biedl syndrome), but these account for only a very small proportion of the obese population (Susan A.J, 1997).


Energy expenditure

Studies in animals have postulated that at the time of overfeeding, a remarkable increase in metabolic rate may deplete the excess energy thus reducing the rate of weight gain below theoretical values (Rothwell N., Stock M., 1983). Genetically obese animals tend to gain more weight than their lean controls even when they are pair-fed, thus implying a greater metabolic rate (Thurby P., Trayhurn P., 1979). One possible explanation for this effect is the decrease in diet-induced thermogenesis which is lessened in animal models of obesity due to a decrease in the sympathetic activation of brown adipose tissue (Rothwell N., Stock M., 1983). These unequivocal effects on energy expenditure in obese animals contrast with the paucity of evidence in humans (Susan A Jebb, 1997). Susan A.J (1997) stated that in obese humans, there have been constant reports of abnormally low energy intake which indirectly imply that there must be a defect in energy expenditure. There are three basic elements to energy expenditure which have each been the focus of extensive research.

Basal Metabolic Rate

In 1997, Susan A Jebb defined basal or resting metabolic rate as the energy expended by an individual at rest, following an overnight fast and at a comfortable environmental temperature in the thermo neutral range. Several studies of basal metabolic rate have concluded that obese subjects have a higher BMR compared to their lean counterparts. Researchers like Swinburn B. & Ravussin E, reported that approximately 80% of the inter- individual variance in BMR can be accounted for by age, fat-free mass, fat mass and gender. Nevertheless, this still gives room for some likelihood that inter-individual difference in BMR which may influence individuals with a relatively low BMR to become obese (Susan A. Jebb, 1997).

Diet induced thermogenesis

A number of studies have suggested that the post-prandial increase in energy expenditure is attenuated in obese subjects, perhaps due to decreased Sympathetic Nervous System activity (Astrup A. 1996). Similar effects have also been demonstrated in the post-obese. However this is not a consistent finding, even among studies from the same laboratory. A recent review by Ravussin E. & Swinburn B. (1993) identified 28 studies in favour of a defect in thermogenesis in humans and 17 against. However, since thermogenesis accounts for only a fraction of total energy expenditure (approximately 10%), the potential for a significant effect on total energy expenditure is insufficient (Susan A. Jebb 1997).

Physical activity

The most significant component of energy expenditure is physical activity which may represent 20-50% of total energy expenditure. Studies of fidgeting movements in Pima Indians within a whole-body calorimeter have shown significant inter-individual variations in the daily energy cost of these actions from 400-3000 kJ/day, with low levels predictive of subsequent weight gain at least in males but not females (Zurlo F., Ferraro R., Fontvielle A. et. al. 1988). However, in free-living conditions, the freedom to undertake conscious physical activity or exercise increases the inter-individual variability even further (Susan A Jebb). Research in this area has been hampered by imprecision in the methods to measure physical activities which have included various actometers, heart rate monitoring, activity diaries and direct observation (Susan A. Jebb, 1997).

The energy requirements of an individual encompass the summation of basal expenditure, thermogenesis and physical activity. A whole-body calorimeter can be used to measure the total energy expenditure of an individual. The analysis of total energy expenditure in 319 obese subjects clearly demonstrates a significant increase in energy expenditure with increasing body weight such that individuals with a BMI in excess of 35 kg/m2 have energy expenditure approximately 30% higher than those with BMI less than 25 kg/m2 (Susan A Jebb, 1997). The outstanding difficulty with these studies , as stated by Susan A. Jebb in 1997 is that the increase in energy expenditure seen in obese subjects as a result of their increased body size may mask pre-existing metabolic defects in the pre-obese state which exposes the individual to excessive weight gain. However, in experimental overfeeding researches, there is no remarkable difference in the degree of weight gain between lean and obese subjects when matched for their excess energy intake (Diaz E. Prentice A. M et. al. 1992).  Studies of total energy expenditure in post-obese subjects have not arrived at a definite conclusion; some studies show no difference in energy expenditure in the post-obese relative to never-obese controls (Goldberg G.R., et. al. 1991), whilst others show a modest suppression of energy expenditure (Geissler C. Miller D., Shah M. 1987). In general, there is little evidence to support the hypothesis that human obesity may be due to a specific defect in energy expenditure in predisposed individuals (Susan A Jebb, 1997). Susan A Jebb further stated that advocates of a metabolic basis to obesity, argue that only very small differences in energy expenditure are neccessary to produce significant weight gain over many years, and this difference may be lower than the limits of precision of even the most advanced methodology.

Energy Intake

The failure to identify a defect in the metabolic control of energy expenditure and the contrary observation of high levels of energy expenditure, and the contrary observation of high levels of energy expenditure in obese subjects has led to a focus on food intake to explain the aetiology of obesity (Susan A Jebb, 1997). The increase in energy expenditure associated with the development of obesity should automatically help to prevent continued weight gain; hence the failure of this auto-regulatory system suggests that there must be a considerable error in the regulation of food intake (Susan A Jebb, 1997). Furthermore, habitually lean individuals are able to regulate intake to match energy requirements over a wide range of energy requirements yet those who become obese seem unable to achieve this balance (Susan A Jebb, 1997).

Breakthrough in discerning the role of energy intake in the aetiology of obesity has been critically disconcerted by under-reporting which is now largely recognized as a feature of obesity (Susan A Jebb, 1997). Comparisons of energy intake and energy expenditure indicate consistent shortfalls in self-reported intake, averaging approximately 30% of energy requirements in obese subjects (Prentice A.M., Black A.E., Coward W.A., 1986; Lichtman S., Pisarska K., Berman E., et al., 1993). This phenomenon also extends to post-obese subjects and to others who may be very weight conscious (Susan A Jebb, 1997).

Under-reporting may be cause by several factors and it is natural for individuals to change their eating pattern when they are to record their food intake.  This is usually associated with a reduction in intake as subjects consciously or sub-consciously adopt a self-imposed ‘diet’. (Susan A Jebb, 1997). Therefore they might give accurate results about their intake for that duration, but it may not be a true representation of their habitual pattern. Forgetfulness, underestimation of meal size and lack of basic knowledge of food consumption can also lead to under-reporting. Although, it is possible to have falsification and fabrication of dietary records, there are also instances of self-deception or deliberate manipulation of dietary records.

Recent research into the appetite control system by Blundell J.; Bouchard C., Bray G. (1996), has identified a network of synchronous interactions which govern eating behavior. These effects are mediated through the central nervous system particularly the hypothalamus, where a number of neuropeptides appear to regulate feeding behavior via effects on hunger and satiety (Susan A Jebb, 1997). Laboratory studies of feeding behavior by Spiegel T., et al., in 1989, proposed that, following a convert energy preload, obese subject may be less able to accurately compensate for the energy content of the preload at a subsequent meal than lean subjects. However, these studies are usually of short duration in laboratory settings and may not accurately reflect eating behavior in a naturalistic setting, where knowledge of foods consumed and conditioned learning may invoke other regulatory processes (Susan A Jebb, 1997).

There is also significant evidence that the individual macronutrients (protein, fat, carbohydrate and alcohol) have different influences on eating behavior, majorly due to their effects on satiety (Stubbs R., 1995). Experimental studies of manipulated foods and retrospective analyses of dietary records suggest that protein is the most satiating (DeCastro J., 1987; Hill A., Blundell J., 1990). Carbohydrate is also an efficient inhibitor of later food consumption, at least in the short terms, meal-to-meal context (Rolls B., et al. 1994). Fat seems to have a satiating capacity (Lawton C., Burley V., 1993). Fat hyperphagia occurs during a single meal due to subjects overeating high fat foods and is also known as passive over consumption. In 1994, Poppitt S., stated that fat has two times the energy per gram of carbohydrate or protein which may be due to the level of energy density and not necessarily a characteristic of dietary fat. Appetite is said to be stimulated by alcohol and according to DeCastro J & Orozco (1990), in free living circumstances, alcohol consumption with meals is associated with higher energy intakes, but this may also reflect that alcohol is more likely to be consumed on special occasions which in themselves are associated with increased food intake.

Basically, taste preference can have an effect on the amount of food consumed and the kind of food.  The individual preference for certain meals would make them more likely to consume more of that meal. Therefore, sensory preferences plays a role on energy balance since is it associated with energy intake. According to Witherley S, Pangborn R & Stern J (1980), several reports of sensory preferences for particular food groups in association with obesity, but inter-subject variability is so great as to obscure any underlying obese-lean differences. The relationship between sensory preference for fat versus sugar and BMI was pinpointed by Drewnowski in 1992. Obese women had preference for foods with high fat to sugar ratio while women with low BMI had preference for high sugar to fat ratio, therefore increase in weight is closely related to increase for fatty foods.

Eating frequency has effect on weight gain, because people who eat several small meals at intervals have less weight than those that eat fewer meals in larger quantity and therefore large quantity of food consumed at a time may be a risk factor for obesity, however, studies as regards this, showed no remarkable relationship (Bellisle F, McDevitt R, Prentice A.M. 1997). Research in this area is contradicted by under-reporting of food consumption in obese subjects and by post-hoc variations in eating patterns as a result of obesity and efforts to control weight (Susan A Jebb, 1997). Eating frequency in obese subjects is however an unreliable blueprint to the eating patterns involved in the aetiology of obesity (Susan A Jebb, 1997).


Obesogenic environment which was first coined in the 1990s, in a bid to explain the present obesity epidermic. According to King D (2007), obesogenic environment is the sum of the influences that the surroundings, opportunities or conditions of life have on promoting obesity in individuals and populations. This encompasses the cultural, social and infrastructural conditions that affect the ability of a person to embrace a healthy lifestyle. Individuals in a population respond to unhealthy environment and the more urbanized the environment, the more individuals are pressurized to adopt unhealthy habits. The pressure from the surrounding makes it difficult for individuals to change their lifestyle and practice healthy habits when the environment itself is unhealthy. Environmental factors may have a critical effect in the development of obesity by unmasking genetic or metabolic susceptibilities (Susan A.J, 1997). Environmental influences on diet involve a wide range of factors including accessibility to food and high calorie drinks. Eating habits are commonly influenced by the availability and accessibility of unhealthy food, which is an important consideration in the effect on obesity. Studies in the United States recommend that the availability of high quality, affordable ‘healthy’ food is limited for people who reside in low-income communities and such scarcity is associated with unhealthy diet and obesity (White 2007) .However despite several epidemiological studies that shows environmental influences play an important role in the aetiology of obesity, it is a fact that some people within the same ‘unhealthy environment’ still managed to maintain a healthy weight (Susan A.J, 1997).


Food is sometimes used as a coping mechanism by individuals with weight issues, especially when they are unhappy, nervous, stressed, bored and depressed. In many obese individuals there seems to be a perpetual cycle of mood disturbance, overeating, and weight gain (Jennifer C. Collins & Jon E. Bentz 2009). When they feel frustrated, they rely on food for comfort, even though this coping mechanism may pacify their mood, the resultant weight gain that results may cause a dysphoric mood due to their inability to control their stress (Jennifer C. Collins & Jon E. Bentz, 2009). Eventually a guilty feeling may restart the cycle and might steer a habitual pattern of eating food to get comfort. This habitual pattern is specifically significant if there is a genetic risk factor for obesity or an ‘obesogenic’ environment where foods high in calorie & density are readily accessible and sedentary lifestyle is present. Regrettably, these situations are popular in America.

In addition to depression and anxiety, other risk factors include problematic eating behaviors such as “mindless eating,” frequent snacking on high calories foods, overeating, and night eating (Glinski J., Wetzler S., Goodman E.2001). American Psychiatric Association has currently included Binge eating disorder (BED) in an appendix of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) and is characterized by: recurrent episodes of eating during a discrete period of time (at least 2 days a week over a 6 month period); eating large quantity of food than majority of the people would eat at the same time; a feeling of loss of control during the episodes; and guilt or distress following the episodes (Jennifer C. Collins & Jon E. Bentz, 2009). According to Wadden T.A., Sarwer D. B., Fabricatore A. N., Jones L., Stack R., & Williams N.S (2007), BED is estimated to occur in approximately 2% of the general population and between 10% and 25% of the bariatric population. An important differentiation pointed out by the American Psychiatric Association, between BED and bulimia/anorexia is that BED is not associated with any regular compensatory behaviors, such as purging, fasting, or excessive exercise. It can therefore be implied that the majority of individuals with BED are overweight.

Night eating, which was first identified in 1955 as another disorder that can lead to remarkable weight gain, though night eating syndrome (NES) is not currently recognized by the American Psychiatric Association as a distinct diagnosis in the DSM-IV-TR. Night eating syndrome is characterized by excessive late night consumption (> 35% of daily calories after the evening meal), unhealthy eating patterns, “morning anorexia,” insomnia, and distress (Stunkard A. J., Grace W. J. & Wolff H. G. 1955). NES occurs in approximately 1% of the general population and an estimated 5-20% of the bariatric population (Wadden T.A., Sarwer D. B., Fabricatore A. N., Jones L., Stack R., & Williams N.S. 2007). More recently, NES has been seen as a disorder of circadian rhythm that includes a delay of appetite in the mornings and the continuation of appetite and over consumption of food during the night (Jennifer C. Collins & Jon E. Bentz, 2009).


There are several possible pathophysiological mechanisms involved in the advancement and prolongation of obesity. This field of research had been almost unapproached until the leptin gene was discovered in 1994 by J. M. Friedman’s laboratory (Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L., Friedman, J.M., 1994). These researchers proposed that leptin was a satiety element. However, soon after J. F. Caro’s laboratory could not ascertain any mutations in the leptin gene in humans with obesity. In 1995, Considine, RV; Considine, EL; Williams, CJ; Nyce, MR; Magosin, SA; Bauer, TL; Rosato, EL; Colberg, J., & Caro, J.F. proposed a contrary view that Leptin expression was increased, postulating the possibility of Leptin-resistance in human obesity. Since the discovery of leptin, insulin, ghrelin, orexin, cholecystokinin, adipokines, peptide tyrosine tyrosine, as well as many other mediators have been researched. The adipokines are intermediators produced by adipose tissue; their action is thought to revise many obesity-related diseases. Leptin and ghrelin are considered to be interrelated in their effect on appetite, with ghrelin produced by the stomach regulating short-term appetitive control (i.e. hunger pangs when the stomach is empty and satiety when the stomach is stretched). Leptin is created by adipose tissue to signal fat storage reservoirs in the body, and mediates long-term appetitive controls (i.e. to eat more when fat storages are low and less when fat storages are high). Although administration of leptin may be effective in a small subset of obese humans who have deficiency in leptin, most obese humans are considered to be leptin resistant and have been found to have high levels of leptin (Hamann A., & Matthaei S. 1996). This resistance is thought to explain in part why administration of leptin has not been shown to be effective in suppressing appetite in most obese people (Flier J.S. 2004).

Leptin and ghrelin act on the hypothalamus and are produced peripherally. They control appetite through their actions on the central nervous system. They act on the hypothalamus, a region of the brain central to the coordination of food consumption and energy expenditure. There are several circuits within the hypothalamus that contribute to its performance in integrating appetite, the melanocortin pathway being the most well understood (Flier J.S. 2004). The circuit starts with an region of the hypothalamus, the arcuate nucleus, that has outputs to the lateral hypothalamus (LH) and ventromedial hypothalamus (VMH), the brain’s feeding and satiety centers, respectively (Boulpaep, Emile L., Boron, & Walter F. 2003).

According to Flier J.S. (2004), the arcuate nucleus contains two distinct groups of neurons; the first group co expresses neuropeptide Y (NPY) and agouti-related peptide (AgRP) and has stimulatory inputs to the LH and inhibitory inputs to the VMH and the second group coexpresses pro-opiomelanocortin (POMC) and cocaine- and amphetamine-regulated transcript (CART) and has stimulatory inputs to the VMH and inhibitory inputs to the LH (Flier J.S. 2004). Consequently, NPY/AgRP neurons stimulate feeding and inhibit satiety, while POMC/CART neurons stimulate satiety and inhibit feeding (Flier J.S. 2004). Both groups of arcuate nucleus neurons are regulated in part by leptin. Leptin inhibits the NPY/AgRP group while stimulating the POMC/CART group (Flier J.S. 2004).  Researches done by Flier J.S., 2004, thus concluded that a deficiency in leptin signaling, either via leptin deficiency or leptin resistance, leads to overfeeding and may account for some genetic and acquired forms of obesity.


Obesity is a severe medical condition and a chronic health issue worldwide. The association between body weight and mortality is a subject of concern, especially in regards to the optimal weight for longevity (JoAnn E. Manson, M.D., Walter C. Willett, M.D., et al, 1995). The significance of understanding the true relationship between weight and mortality is underlined by the increasing prevalence of obesity in the United States (Kuczmarski RJ, et al, 1994) especially women (Harlen WR, et al, 1988). Obesity is a major risk factor for cardiovascular diseases (e.g., heart disease, stroke and high blood pressure), diabetes (e.g. type 2 diabetes), musculoskeletal disorders (e.g., osteoarthritis), some cancers (e.g., endometrial, breast, and colon cancer), high total cholesterol or high levels of triglycerides, liver and gallbladder diseases, sleep apnea and respiratory problems, reproductive health complications such as infertility and mental health conditions (WHO, 2012).

Obesity and Cancer

Obese people are more vulnerable to cancer and their prognosis is extremely worse when diagnosed. Men that are obese are 33% more likely to die from cancer and obese women also have a 50% higher likelihood of dying from breast cancer (Weight Management Centre, 2010). Additional to obesity, cancer has recently been linked to diet and physical activity status (Bray 2004, Barnard 2004, Wiseman 2008). The cancers most significantly associated with obesity in women are cervical, uterine, kidney, breast and endometrial cancer and in men are colon, pancreatic and liver cancer (Calle, Rodriguez, Walker-Thurmond & Thun 2003). One study, using National Cancer Institute Surveillance, Epidemiology, and End Results data, estimated that in 2007 in the United States, about 34,000 new cases of cancer in men (4 percent) and 50,500 in women (7 percent) were due to obesity. The percentage of cases attributed to obesity varied widely for different cancer types but was as high as 40 percent for some cancers, particularly endometrial cancer and esophageal adenocarcinoma (National Cancer Institute, 2012).

Obesity and cardiovascular disorders

Cardiovascular disease (CVD) is one of the major cause of death in U.S. Obese people are more liable to die from CVD largely due to accelerated atherosclerosis, hyperlipidaemia, loss of glyceamic control and hypertension. Until recently the relationship between obesity and coronary heart disease was viewed as indirect, i.e., through covariates related to both obesity and coronary heart disease risk (Lew E.A., Garfinkel L., 1979) including hypertension; dyslipidemia, particularly reductions in HDL cholesterol; and impaired glucose tolerance or non–insulin-dependent diabetes mellitus. Insulin resistance and accompanying hyperinsulinemia are typically associated with these comorbidities (Reaven G.M., 1988). Although most of the comorbidities linking obesity to coronary artery disease increase as BMI increases, they also relate to the total distribution of body fat. Long-term longitudinal studies, however, indicate that obesity as such not only relates to but independently predicts coronary atherosclerosis (Manson J.E., et al., 1995; Garrison R. J., et al. 1985; Rabkin S.W., 1977). Messerli F. H. (1982) stated that left ventricular hypertrophy is mostly seen in patients with obesity and is related to systemic hypertension and may be related to the severity of obesity. Hypertension is approximately three times more commonly found in obese individuals than normal-weight persons (Van Itallie T.B., 1985). This relationship may be directly related such that when weight increases, there is an increase in blood pressure (Kannel W.B., Brand N., et al., 1967) and when weight decreases, blood pressure also decreases (Reisin E., Frohlich E.D., et al., 1983).

Obesity and mental health

Individuals diagnosed with obesity tend to be less favorable on all levels of the psychological assessment and may exhibit several symptoms ranging from mere sadness to chronic depression. Evident are more episodes of mood swings, anxiety, personality and eating disorders, basically related to or associated with obesity experienced by individuals with obesity (Pickering, Grant, Chou, Compton 2007). Obesity may be an inception of psychiatric manifestations and vice versa and is related to psychosocial deterioration and bias based on weight. This comprises of loss of self-worth, and reduced self-esteem associated with stigmatization. Stigmatization can further lead to desolation and withdrawal and thus many obese individuals seek solace in binge eating, thereby gaining more weight. Based on reports from Roberts, Deleger, Strawbridge & Kaplan 2003; Herva, Laitinen, Miettunen, Veijola, Karvonen & Lasky 2006; Kasen, Cohen, Chen &Must 2008, concern, shame and guilt associated with low self-worth, which is finally related to excessive food consumption completes the obesity-mental disorder circle.

There is bias and discrimination associated with obesity. They generally report reduced quality of life and functional wellbeing, collectively called Health-related quality of life (HRQOL) (Puhl & Brownell 2001; Wadden & Phelan 2002). This relationships is majorly expressed by women (Fontaine 2001) and for people with severe obesity (Hudson, Hiripi, Pope & Kessler 2007; Scott, Bruffaerts, Siomn, Alonso, Angermeyer, de Girolamo et al. 2008).

Obesity and diabetes

Diabetes is usually a terminal illness. i.e. it is a lifelong chronic disease characterized by high levels of sugar in the blood. One of the major risk factors for diabetes is obesity. Obesity is directly associated with Diabetes 2. The association between obesity and type 2 diabetes are firmly established and without the intervention of a healthy diet and proper exercise, obesity can lead to type 2 diabetes over a very short period of time.  In fact, obesity is believed to account for 80-85% of the risk of developing type 2 diabetes, while recent research suggests that obese people are up to 80 times more likely to develop type 2 diabetes than those with a BMI of less than 22 (National Health Service, 2014). It is a known fact that obesity carries a greater risk of developing type 2 diabetes, especially if you have excess weight around your abdomen. Studies postulates that abdominal fat causes fat cells to releases ‘pro-inflammatory’ chemicals, which can reduce the body’s sensitivity to the insulin, this can also disrupt the function of insulin responsive cells and their ability to react to insulin. This is known as insulin resistance  which is a primary activator for type 2 diabetes. Excess abdominal fat is a major high-risk form of obesity.


In 1999-2000, nearly 65 percent of U.S. adults were either obese or overweight. Obesity accounts for $117 billion a year in direct and indirect economic costs. Obesity is associated with 300,000 deaths per year, and is fast becoming the leading cause of preventable deaths” (Mancino, Lin, and Ballenger, 2004). Certainly, obesity has become a large problem in America. Recent increase in meal portions and reduction in availability of natural food production may propose why people find it challenging to maintain a healthy diet. Although, certain People have been successful at maintaining a healthy nutritional status and avoiding this unhealthy situation. Gary Becker’s human capital theory is a groundwork that helps to clarify the effect of weight status on the economy in terms of the labor market outcomes for the individual. Human capital is the educational qualification, job experience/training, and the health condition that workers devote their time in to boost their capacity and skills to be “rented out” to employers (Ehrenberg and Smith, 2005). Healthy weight status in relation to labour is a type of human capital investment. According to Robert Pindyck and Daniel Rubinfeld (2004), “When an investment decision is made, the investor commits to a current outlay of expenses in return for a  stream of expected future benefits.” These stated costs for a healthy weight may include buying of food with high nutritional values and creating time for physical activities. As an investment, the individual sacrifices money, time and other resources to attain a healthy weight to become more productive in the future and, hence, earn higher income. Obese workers miss more days of work and inflict more cost on employers especially in medical and disability claims and also workers compensation claims. As a result, firms end up with extra costs associated with obesity, this is one of the economic effects of obesity.

Obesity places significant burden on the society through health care expenditures and disability payments combined through group health insurance and public programs. The estimated annual medical cost of obesity in the U.S. was $147 billion in 2008 U.S. dollars; the medical costs for people who are obese were $1,429 higher than those of normal weight (CDC, 2011). Obesity there has direct and indirect effect on the Nation’s resources, as more money is spent on the obese due to the high risk of comorbidity with other life threatening diseases like type 2 diabetes, osteoarthritis and cardiovascular diseases.


There are several weight-loss schemes available but many are ineffectual and short-term, especially for those who are morbidly obese. The strategies for weight loss with non-surgical programs usually involve a combination of diet modification, behavior modification therapy and appropriate exercise.

Dietary Modification

Dietary modifications for obesity are designed to create a negative energy intake-energy expenditure balance (i.e., calories consumed < calories expended) by reducing daily energy intake below the required level. The required energy varies by weight, sex and level of physical exercise such individuals with higher weights, more activity have greater energy needs, including men (Melanson K. & Dwyer J. 2002). Uniformly, higher energy deficits results in higher weight losses. Low calorie diet is recommended for obese individuals and they are advised to check calorie content of meals before consumption. Very low calorie diet is recommended for morbidly obese individuals with little or no success in low diet consumption.

Behaviour Therapy

The oldest report of the use of behavioral therapy in the management of obesity occurred in 1967. Since then, it has been widely used in the management of obesity (Gupta R. & Misra A. 2007). Behavior therapy involves setting out goals and principles to patients to aid their adherence to the diet modification and activity goals for weight loss. Conventional tactics include self-monitoring of food intake and exercise, reduced portion of meals and number of times of food intake, intellective restructuring, problem solving, and prevention of regression. The primary aim of behavior modification therapy is to change eating pattern and exercise practices to promote weight loss (CDC, 2011).

Components of behavioral therapy

  1. Self-monitoring: This is one of the main elements of behavior therapy in obesity. Self-monitoring includes maintaining food dairies and activity logs (Guare J.C., et. Al., 1989).
  2. Stimulus Control: This is the second key element in behavior therapy. In this element, focus is placed on altering the environment that initiates eating and modifying it to help prevent overeating. Stimulus control includes proper purchase of food items, excluding energy-dense processed food and introducing more fruits and vegetables (Wing R.R., 2004)
  3. Slower eating: Reducing the speed of eating so as to allow signals for fullness come into play.
  4. Goal setting: Setting realistic goals for one’s self or setting goals for patients as appropriate (Bandura A. & Simon K.M., 1977).
  5. Behavioral contracting: Reinforcing of successful outcomes or rewarding good behaviors plays a key role (Volpp K. G., et. al., 2008).
  6. Education: Nutritional education is a necessary component of a successful behavior therapy for obesity. A structured meal plan in conjunction with consultation with a dietician will be helpful (Pedersen S. D., et. al., 2007).
  7. Social support: Behavioral modification is more sustainable in the long term when there is social support. Enhancing social support is essential for behavioral therapy (Avenell A. et. al., 2004).

Physical activity

Physical activity is the third component of non-surgical weight loss interventions and lifestyle modification. The advantages of physical activities include promoting negative energy balance by maximizing calorie expenditure, preserving fat-free part during weight loss, and improving cardiovascular fitness. Physical activity, however, is ineffective in weight loss in the absence of diet modification. The greatest benefit of physical activity is in facilitating the maintenance of weight loss (Pronk N.P & Wing R.R. 1992). Case studies have shown that people who exercise regularly are more successful in maintaining weight losses than are those who do not exercise. Kayman S., Bruvold W., Stern J.S. 1990; Klem M.L., Wing R.R., McGuire M.T., Seagle H.M., Hill J.O.1997). Additional evidence comes from randomized trials. Participants who receive diet plus exercise maintain greater weight losses 1 year after treatment than do those who receive diet alone, although the differences are not always statistically significant (Wing, R.R. 1999).


Obesity is a long-lasting medical condition, which is linked with several debilitating and life-threatening conditions. The increasing rate of obesity globally is a public health concern (Srinivas N., et. al., 2004). Hence an effective way to control obesity requires strategies that would tackle the major issues relating to prevention (Srinivas N., et. al., 2004). The treatment and prevention of obesity are interrelated. The prevention of obesity involves several levels i) Primary ii) Secondary iii) Tertiary (Timothy P.G., 1997).

  1. Primary prevention: The goal of primary prevention is to reduce the number of new cases. Diet modification/ healthy diet habits is a primary way of preventing obesity. Sedentary life style which is one of the causes of obesity can be prevented by appropriate exercises and activities that help burn out excess calories in the body and also prevent accumulation of fat. Simple habits ranging from 30 minutes walk in a day to weekly work out at the gymnasium can go a long way in maintaining a healthy weight. Health education is also very important in this aspect because some individuals in the community are unaware of the health implications of their habits. Appropriate health education programs should be organized to increase awareness. Accessibility to healthy food is also an important factor in the prevention of obesity. Formulations of policies that would facilitate healthy eating habit should be adopted by the Government; this would go a long way in reducing the economic effects of obesity and the burden on the Nation’s resources. Policy and environmental approaches that make healthy choices available, affordable and easy can be used to extend the propagation of strategies designed to raise awareness and support people who would like to make healthy lifestyle changes (CDC, 2011).
  2. Secondary prevention: Secondary prevention is to lower the rate of established cases in the community (Srinivas N., et. al., 2004). Secondary prevention includes strategies to diagnose and treat an existing medical condition in its early stage to avoid complications. (Jeffery G.K., 2014).
  3. Tertiary prevention: Tertiary prevention is to stabilize or reduce the amount of disability related to obesity ((Srinivas N., et. al., 2004). For those who are already obese and showing signs and symptoms of complications, there are clinical preventive maintenance and treatment regimes (Srinivas N., et. al., 2004). These treatment includes medications and increase in fruit and vegetable consumption. Some extreme cases may include surgery and this is used usually when BMI exceeds 30kg/m2 or 40 kg/m2 and when other treatment options have failed. Examples of surgical procedures to treat obesity and its complications includes gastric partitioning and gastric by-pass (Srinivas N., et. al., 2004).


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