**Inadequate Coping Attitudes, Disordered Eating Behaviours and Eating Disorders in Type 1 Diabetic Patients**

Ricardo V. García-Mayor and Alejandra Larrañaga *Eating Disorders Section, Endocrinology, Diabetes, Nutrition and Metabolism Department, University Hospital of Vigo Spain*

#### **1. Introduction**

94 Type 1 Diabetes – Complications, Pathogenesis, and Alternative Treatments

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Diabetes mellitus has been found to be the sixth leading cause of death for those living in the United States affecting the young and old at an alarming rate (National Center for Health Statistics, 2011). Type 1 diabetes typically has an early onset in life, but can occur at any age. It primarily develops when the body's own immune system attacks and destroys pancreatic beta cells, which produce the hormone insulin that regulates blood glucose levels. This type of diabetes accounts for 5 to 10 % of all diagnosed cases. Type 2 diabetes affects mainly adult subjects, its prevalence around the world has increased in relationship with the increase of the prevalence of overweight and obesity, attributed to lifestyle changes such as sedentary habits and overeating. Consequently, diabetes is one of the most challenging and burdensome chronic diseases of the 21st century, and it is a growing threat to the world's public health (King et al, 1995; King et al, 1998). Diabetes mellitus, especially type 1 form represent a very hard experience that requires subsequent psychological adaptation. Unfortunately, this often does not occur and it is followed by frustration and the nonacceptance of the disease. Problems with coping are one of the important consequences of the disease and the cause of uncountable problems in the future.

The management of type1 diabetes and its associated health-risk factors are often complex and require considerable patient education and frequent medical monitoring (Koopmanschap, 2002). The participation of the patients is basic in order to obtain a correct degree of metabolic control; however, this carries as a consequence considerable amount of stress. People on insulin must learn how to regulate their blood sugars by monitoring blood glucose levels daily while carefully attending to their food intake and an exercise regimen. Careful blood glucose monitoring is necessary to prevent wide variations in blood sugars that affect both short term and long term health and functioning. Hypoglycaemia reactions are a concern in the short run not only because they are frightening and disruptive, but also because, when severe, they can lead to unconsciousness, coma and death (Cox & Gonder-Frederick, 1992). The constant stress of maintaining tight glycaemia control can result in two types of psychological distress (a) subclinical emotional distress, and (b) diagnosable psychological disorders (Rubin & Payrot, 2001). Additionally, psychiatric conditions can

Inadequate Coping Attitudes, Disordered Eating

(Bombardier et al, 1990).

of confidence.

Behaviours and Eating Disorders in Type 1 Diabetic Patients 97

chronic illness yields the following outcomes: successful performance of adaptive tests, absence of psychological disorders, low experience of negative affect, improved functional

Coping can generally be defined as cognitive and/or behavioral attempts to manage and tolerate situations that are appraised as stressful to an individual. No single coping strategy or dimension can be considered maladaptive. The quality of the coping strategy and process is evaluated according to its impact on the outcome of interest. From the previous conceptual definition, Folkman and Lazarus (Folkman & Lazaruz, 1980; Folkman & Lazaruz, 1985; Folkman & Lazaruz, 1988) distinguished two primary dimensions of coping (or categories): emotion-focused (composed of individual coping strategies such as seeking emotional support) and problem-focused (composed of individual coping strategies such as making a plan of action). These coping categories described efforts to either alleviate the personal emotional stress induced by the stressor or alter the source of stress in the environment. Use of problem-focused coping has been found to be associated with better metabolic control, emotional status, and better adjustment overall in patients with diabetes (Lundman & Norberg, 1993); use of emotion-focused coping has been found to be associated with poor adjustment and adherence to health regimens in chronically ill samples

Diabetic patients initially experience high levels of depression and anxiety (Lustman et al, 1997; Tuncay, 2008). Anderson et al. (Anderson et al, 2001) found that adults with diabetes have twice the odds of comorbid depression. It was also found that this prevalence was much higher in women than in men. Within their sample, one in every three individuals had a level of depression that impaired their ability to function on a daily basis which in turn affected quality of life, regimen adherence, and blood glucose control. Regarding to coping strategies, it has been shown that problem-focused coping was positively associated with glycaemia control and negatively associated with anxiety and depression (Maes et al, 1996). Smari and Valtysdottir (Smari & Valtysdottir, 1997) also found that problem-focused coping was associated with lower blood glucose levels—indicative of better adjustment. On the contrary, individuals who engaged in more emotion-focused types of coping experienced more anxiety, depression, and higher levels of glycaemia. It is obvious that any deviation from a normal routine or health status serves as a continual source of stress that leads to the individuals' inability to care for themselves (White et al, 1992). Therefore, management of

this stress via coping strategies is crucial for psychological and physical health.

An author found that treating depression through therapy is effective for individuals with diabetes so they may regain confidence and abilities to control the disease, leading to improved quality of life and social and physiological functioning (Eisenberg, 1992). The treatment includes the development of coping skills through training programs (Grey & Berry, 2004) as well as patient empowerment (Anderson et al, 1995). DeRidder and Schreurs (DeRidder & Schreurs, 2001) observed that diabetic patients in particular are inclined to use coping strategies that are aimed at reducing the negative emotions surrounding the disease and its maintenance. If this suggestion was found to be empirically true across diabetes studies and patients, it may portend a particularly problematic issue since these strategies were generally viewed as less adaptive. It is apparent that stress permeates the management of diabetes and thus use of effective coping skills is imperative not only in illness management but general stress management as well. At present, there is no systematic quantitative review of the stress and coping literature in diabetes that links coping strategies to indices of adjustment. Thus, a summary statement of the adaptive versus maladaptive strategies identified for these coping-adjustment relations cannot be made with any degree

status, and appraisals of well-being in varying life domains (Stanton et al, 2001).

occur independently without being a consequence of diabetes. It has been shown that individuals with diabetes have a disproportionately higher rate of psychiatric disorders (Bogner et al, 2007; Llorente & Urrutia, 2006), with affective and anxiety disorders being more commonly diagnosed than in the general population (De Mont-Marin et al, 1995). This is evidenced by research showing high rates of psychiatric disorders, particularly depression and anxiety, for example, Fettahoglu et al., (Fettahoglu et al, 2007) found over 40% increased risk in having any type of psychiatric disorder in patients with diabetes, and Gülseren et al. (Gülseren et al, 2001) found that depression and anxiety account for 45% of psychiatric disorders in patients with diabetes. These results show the negative impact that diabetes can have on an individual's psychosocial adjustment, and the need for research to determine the most appropriate and common coping strategies to deal with the stress of illness.

Other psychological problems of these patients are Eating Disorders (ED). The classical ED are anorexia nervosa (AN) and bulimia nervosa (BN), but recently another entity was recognized, the so called eating disorders not otherwise specified (EDNOS), which are incomplete forms of classical ED that are diagnosed when patients did not fulfill the classical ED diagnostic criteria. Type 1 diabetic patients have a high risk of suffering from ED due to these patients have to select the food they eat carefully in an early period of their development and because both entities, type 1 diabetes and ED, often affect adolescents and young adults. Furthermore, type 1 diabetic patients suffer from other eating behavior anomalies, which mainly appear in girls, that consist in spliting insulin doses or restricting food intake in order to reduce their body weight, but with the high price of the metabolic disturbance and subsequent chronic vascular complications if such behavior persists over time.

In this chapter we will review these psychological anomalies suffered by type 1 diabetic patients, especially problems with coping attitudes, disordered eating behaviors (DEB) and eating disorders (ED), and also discuss some aspects of their forms of presentation, management and prevention.


*2.5. D-STATCOM*

The D-STATCOM is commonly regarded as a shunt compensator which supplies reactive power in PFAs. The voltage magnitude at the D-STATCOM bus can be controlled by adjusting the reactive power injection of D-STATCOM.

The interface of the D-STATCOM at ith bus shown in Figure 2a, and its traditional modelling for PFAs is shown in Figure 2b. The specified reactive power of the load is combined with the reactive power output of D-STATCOM, so that reactive power varies as magnitude of Vi varies. This is absolutely a PV bus modelling with the real power output of the D-STATCOM set to zero [27,28]. The hypothesis in this model is that losses in the D-STATCOM and its connection are ignored. The D-STATCOMs have low harmonic content, so the harmonic current injected by the D-STATCOM is considered as zero for HPFA.

**Figure 2.** (**a**) D-STATCOM interface at ith bus 2 (**b**) Traditional modelling of D-STATCOM as PV bus.


**1. Introduction**

116 Current Topics in Tropical Medicine

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**10. References**

Until recently, very few physicians in industrialized countries had heard the word "Chikungunya", and fewer knew how to spell it. Chikungunya, a viral infection transmitted by mosquitoes, derives its name from Makonde, a language spoken in south Tanzania, and means "that which bends up", referring to the posture of patients afflicted with severe joint paints characterizing this infection. Chikungunya virus (CHIKV) was first isolated in Tanzania in 1952 (Robinson, 1955) and has come to the world attention recently, when it caused a massive outbreak in the Indian Ocean region and India (Enserik, 2006). Since 1952, CHIKV has caused a number of epidemics, both in Africa and Southeast Asia, many of them having involved hundreds-of-thousands people. In 2005 the largest Chikungunya fever epidemic on record occurred. The most affected region was La Reunion Island, where CHIKV infected more than a third of the population and killed hundred of people. The 2005/2006 outbreak, started from Comoro Islands, rapidly spread to several countries in the Indian Ocean and India (Enserik, 2006; Mavalankar et al., 2007). Compared to earlier outbreaks, this episode was massive, occurred in highly medicalized areas such as La Reunion, and had very significant economic and social impact. More than 1000 imported CHIKV cases have been detected among European and American travellers returning from the affected areas since the beginning of the outbreak in the Indian Ocean region (Fusco et al., 2006; Taubiz et al., 2007), giving rise, in 2007, to the first autochthonous European outbreak in Italy (Charrel & de Lambellerie, 2008; Rezza et al., 2007). Since 2006, the Regional Office of the French Institute For Public Health Surveillance in the Indian Ocean has conducted epidemiological and biological surveillance for CHIKV infection. During the period December 2006-july 2009, no confirmed case was detected on Reunion Island and Mayotte, but new outbreak were reported in Madacascar. After few years of relative dormancy in Réunion Island, CHIKV transmission has restarted in 2009 and 2010, with one case imported in France (May 2010) (D'Ortenzio et al., 2010). This episode has refreshed the concerns about the possibility of renewed autochthonous transmission in Mediterranean countries.

\* Meschi Silvia1, Selleri Marina1, Lalle Eleonora1, Castilletti Concetta1, Carletti Fabrizio2, Di Caro Antonino2 and Capobianchi Maria Rosaria1

1*Laboratory of Virology, National Institute for Infectious Diseases "L. Spallanzani", Rome, Italy*

*2Laboratory of Microbiology and Infectious Disease Biorepository, National Institute for Infectious Diseases "L. Spallanzani", Rome, Italy*

The Re-Emergence of an Old Disease: Chikungunya Fever 119

they can become perfect "incubators" for mosquito eggs, where the ideal conditions of

Human beings serve as the Chikungunya virus reservoir during epidemic periods. In Africa some animals (monkeys, rodents, and birds) constitute the virus reservoir during not-epidemic periods, sustaining virus circulation in the environment in the absence of human cases. Outbreaks might occur in monkeys when herd immunity is low; the animals develop viraemia but no pronounced physical manifestations (Inoue et al., 2003; Wolfe et al., 2001). An animal

After infection with Chikungunya virus, there is a silent incubation period lasting 2–4 days on average (range 1–12 days) (Lam et al., 2001). Clinical onset is abrupt, with high fever, headache, back pain, myalgia, and arthralgia; the latter can be intense, affecting mainly the extremities (ankles, wrists, phalanges) but also the large joints (Hochedez et al., 2006; Lam et al., 2001; Quatresous, 2006; Robinson, 1955; Saxena et al., 2006). Skin involvement present in about 40–50% of cases, and consists of (1) a pruriginous maculopapular rash predominating on the thorax, (2) facial oedema, or (3) in children, a bullous rash with pronounced sloughing, and (4) localised petechiae and gingivorrhagia (mainly in children) (Brighton et al., 1983; Fourie & Morrison, 1979). Radiological findings are normal, and biological markers of inflammation (erythrocyte sedimentation rate and C-reactive protein) are normal or moderately elevated (Fourie & Morrison, 1979; Kennedy et al., 1980). Iridocyclitis and retinitis are the most common ocular manifestations associated with Chikungunya fever; less frequent ocular lesions include episcleritis. All ocular manifestations have a benign course with complete resolution and preservation of vision. Retinitis shows gradual resolution over a period of 6 to 8 weeks (Mahendradas et al., 2008). CHIKV infection seems to elicit long-lasting protective immunity, and experiments performed using animal models have shown a partial cross-protection among CHIKV and other alphaviruses (Edelman et

Erratic, relapsing, and incapacitating arthralgia is the hallmark of Chikungunya, although it rarely affects children. These manifestations are normally migratory and involve small joints of hands, wrists, ankles, and feet with pain on movement. Symptoms generally resolve within 7–10 days, except for joint stiffness and pain: up to 12% of patients still have chronic arthralgia three years after onset of the illness. Arthralgia experienced by CHIKF patients closely resembles the symptoms induced by other viruses like Ross River Virus (RRV) and Barmah Forest virus (BFV) (Jacups et al, 2008; Mahalingam et al., 2002). Such alphavirusinduced arthralgia mirrors rheumatoid arthritis, a condition which is characterised by severe joint pains due to inflammation and tissue destruction caused by inflammatory cytokines such as IL-1b, IL-6 and TNF-a (Barksby et al., 2007). It is thus plausible that CHIKV infection induces similar pro-inflammatory cytokines that cause arthralgia, explaining why joint pains are constant ailments of many patients infected with CHIKV even years after recovery from the initial febrile phase (Lakshmi et al., 2008). More recently, global analyses on the specific involvement of cytokines and chemokines have showed that IL-1b, IL-6, and RANTES were associated with disease severity (Ng et al.,

reservoir has not been identified in Asia, where humans appear to be the only host.

temperature and humidity are achieved easily and naturally.

**4. Clinical manifestation**

al., 2000; Hearn Jr. & Rainey, 1963).

**4.2 Arthralgia**

**4.1 General features**


*6.1. Feature Extraction from Tactile Data and Classification by Convolutional Neural Networks*

In the first approach we train two separate convolutional neural networks (CNN) to learn the features from the video of tactile images (cutaneous cues) and the sequence of normal vectors to the surface (kinesthetic cues). All tactile images captured by the virtual FSR sensor, are 32 × 32 grayscale images and 25 frames are considered for each exploration (contour).

The first CNN (dedicated to cutaneous cues) takes benefit from two convolution layers with 3D kernels followed by a batch normalization layer speeding up the learning process. No pooling layer is added as the size of tactile images is not so large to require down sampling. Two fully connected layers are then exploited to learn the relationship between the extracted features through the filters in the convolution layers. A SoftMax layer finally outputs the probability distribution values over predicted output classes. The network is trained for 50 epochs.

The second CNN (dedicated to cutaneous cues) has 25 × 3 × 1 data in its input layer. Thus, it can be implemented with 2D kernels in convolution layers. We set up a similar architecture for the second CNN, i.e., two convolution layers with a batch normalization in between followed by two fully connected layers, and a SoftMax layer generating the probability distribution results predicted for the output layer.

Each of these CNNs are applied after training to tactile data captured over identical contours as a test sample and output the probabilities that the sample belongs to each of the eight object classes. The winning class has the highest probability among all. In order to integrate the results obtained by cutaneous and kinesthetic cues, for each probing sequence from the test data, we sum up the obtained probability values computed by the two CNNs for each class and choose the class with the highest probability as the winning class, as illustrated in Figure 7.

**Figure 7.** The two convolutional neural network (CNN) structures and the decision on output class.