The shortage of time, and the endless selection of food products can lead people to eat regardless of their hunger and energy needs and consume fast and fat food (Broussard & Van Cauter, 2016; Rey-Lopez et al., 2014; Siep et al., 2012). Research shows that the appearance of appetizing food products attracts attention and may be enough to trigger a person's food intake for pleasure only, regardless of existential needs (Dietrich, 2017; Siep et al., 2012), which can lead to obesity.
Obesity and disturbed eating
While the global average of obese people stands at 10.7% of men and 15.2% of women over the age of 18, in Israel the picture is even more bleak. Over 23% of men and 27% of women in Israel (age 18 and up) are considered overweight (World Health Organization, 2015). Obesity increases the risk of diseases such as diabetes, various types of cancer and heart disease and is now considered a global epidemic (Nabavi et al., 2015; Rey‐Lopez et al., 2014). This study examines a possible way of coping with Food Attention Bias (FAB) that, together with other factors, may lead to obesity. The study examines the impact of a cognitive strategy based on a stimulus re-evaluation technique, on people's susceptibility to FAB to tempting food stimuli, aiming to promote the development of a tool for coping with obesity.
Obesity is defined as a condition of abnormal or excessive fat accumulation in adipose tissue, to the extent that health is impaired (Ogden et al., 2007). The most widely used tool for measuring and diagnosing obesity is the body mass index (BMI) due to its simplicity and low cost (Mei et al., 2002). A value of 30 or higher is considered obese, 25-29.9 is overweight and values that are in between 18.5-24.9 indicate normal weight (Mei et al., 2002; Ogden et al., 2007).
Many factors contribute to the ever-growing epidemic of obesity. High-calorie and high-fat food is accessible because of its low cost and immediate availability (Wright & Aronne, 2012). Genetic factors also impact obesity (Pinto et al., 2019) as well as various hormonal problems such as hypothyroidism, and external factors affecting the endocrine system (such as food or industrial drugs consumed by humans) (Barness et al., 2007). Social factors also contribute to the risk of obesity. Research shows that people are more likely to be obese if they have a friend, brother or spouse who has gained weight to the extent of obesity (Wright & Aronne, 2012). Thus, it is evident that the origin of obesity consists of interactions between environmental, biological, and genetic factors.
Obesity may be related to disturbed eating which involves a variety of unbalanced eating behaviors. Some of these behaviors are diet-related, such as an unsupervised diet that includes strict calorie intake, while other behaviors include unhealthy eating, such as consuming a large amount of high-fat foods while skipping meals. In addition, anorectic or bulimic behaviors such as taking laxatives or diet pills, vomiting, and periodicity of binge eating and dieting are also considered to be disturbed eating behaviors (Littleton & Ollendick, 2003).
It appears there is a phenomenological overlap between substance-related and addictive disorders and feeding and eating disorders, in that the need for ‘control’ plays a prominent role in the criteria for disorders within these two categories (Hebebrand et al., 2014). The response to food stimulates reward-related brain pathways, much like brain activity when consuming alcohol, drugs, and tobacco. These pathways include the dopamine system and the opiate system. The cerebral causes of overeating and craving for food are similar to those of consuming addictive substances in that both stimulate intrusive thoughts and direct our attention to the desired goal, such as consuming addictive substances or consuming high calorie foods while a person is not hungry (Kavanagh et al., 2005; May et al., 2004).
Furthermore, brain imaging studies have shown an association between the Mesocorticolimbic pathways, associated with providing rewards and various cognitive processes, and overeating (Alcaro et al., 2007; Kelley & Berridge, 2002). This pathway has been previously linked to the term 'appetitive motivation', which means increasing behavioral orientation toward goals that have pleasant and positive hedonistic effects such as eating, drinking alcohol or having sex. The hedonistic effects can be related to one's subjective experience and emotional impact of action (Bozarth, 1994).
Previous studies have found that overweight individuals show greater brain activity in more extensive reward areas than thin individuals, and reduced brain activity in inhibitory areas in response to food images, especially high-calorie food (Yokum & Stice, 2013). Accordingly, it has been suggested that the tension between appetitive motivation and cognitive inhibition leads to a person's eating behavior, so that lack of control and goal-directed behavior of food consumption, especially calorie-rich food, which is of greater hedonistic value, will lead to weight gain, overweight and obesity (Appelhans, 2009; Nederkoorn et al., 2010; Nederkoorn et al., 2006).
Cognitive strategies for intervention in eating behaviors
Due to the many negative effects of obesity noted above, and the expansion of the phenomenon to the point of being defined as an epidemic in recent years, the need to develop weight loss treatment methods and maintain proper body weight has increased (Wadden, & Stunkard, 2002). One of these ways, which addresses the uncontrollable desire to eat foods of great calorific value, is a cognitive reappraisal (CR) exercise. CR interventions involve the person's conscious cognitive change of the meaning of the situation aiming to consequently change the emotional response to it (Giuliani et al., 2013). Hence, it may strengthen one's cognitive control when encountering high-calorie food, thereby weakening the appetitive motivation. This strategy has previously been supported by findings demonstrating that cognitive interventions contribute to a decrease in food cravings through active control of one's way of thinking about food (Giuliani et al., 2013; Werrij et al., 2009).
CR aims to change how one thinks about emotionally stimulating cues, such as high-calorie food cues. In most studies using brain imaging, the instructions for practicing this strategy are not detailed, however, Giuliani et al., 2013 describes the following procedures: (1) "Imagine that currently you are very replete, (2) focus on the negative consequences of eating this food (stomach ache or weight gain for example), (3) Remind yourself that you can keep this dish for later, (4) Imagine something bad happened to the dish (let's say someone sneezed on it)." Each participant had to choose one of this proposed CR strategies or create an alternative strategy that would be applicable in the real world and use it throughout the experiment. Subsequently, the researchers found that there was a decrease in the desire to eat high-calorie food, with no significant difference between the strategies proposed by the research team and those created by the participants themselves (Giuliani et al., 2013).
Functional Magnetic Resonance Imaging (fMRI) studies of smokers and studies of people with normal BMI found that using CR when given the long-term negative effects of eating high-fat food has reduced the desire for high-fat food (Kober et al., 2010; Siep et al., 2012). In addition, using CR has been shown to increase activity in inhibitory areas (such as the Gyrus and Ventrolateral Prefrontal Cortex) in exposure to high-fat or sugar-rich food, and attenuate activity in attentional areas (such as the Precuneus and Posterior Cingulate Cortex). These findings suggest that CR can suppress appetitive motivation and reduce unhealthy food intake in overweight individuals (Stice et al., 2015; Yokum & Stice, 2013).
Changes in attentional bias as a measure of the impact of cognitive strategies
Attentional Bias (AB) is a state of automatic and excessive attention to specific stimulation (MacLeod & Matthews, 2012). Attention bias towards food is a specific case of AB, called Food Attentional Bias. Berridge (1996) proposed the model of food reward, which holds that unhealthy eating is a behavioral response to such FAB. According to this model, unhealthy food cues capture more attention as they are perceived as more attractive, rewarding, and tasteful (Polivy et al., 2008). FAB has been linked to people's inability to resist the temptation of food (Graham et al., 2011) suggesting that obese people will have greater FAB. FAB leads to faster processing of food-related information in obese individuals relative to non-obese individuals (Hendrikse et al., 2015).
In this study, we used the Visual Dot Probe (VDP) to assess FAB. This procedure is commonly used to measure AB toward various stimuli, such as smoking and alcohol (Ehrman et al., 2002; Townshend & Duka, 2001; See Methods section). A study that used the VDP procedure as an indicator of FAB, found that all participants exhibited FAB, but obese individuals showed an increased FAB compared to participants without obesity (Nijs et al., 2010a, 2010b). This suggests that the VDP task provides a sensitive measure of FAB (Hendrikse et al., 2015).
The main goal of the current study was to examine in what ways FAB is modulated by cognitive-behavioral procedures used for regulating food consumption. To this end we tested participants' FAB before and after they performed a CR or a control procedure and analyzed their effects on FAB. Participants were divided into two groups: In the CR group, they performed a cognitive reappraisal procedure and in the control group they performed a neutral task (CN). All groups performed a computerized VDP task before and after the intervention. In this task, two stimuli were briefly presented on the screen and participants only watched them. These stimuli included the target stimulus – either a word or a picture of food, and a neutral stimulus, either a word or a picture of an animal. Immediately after the word or picture disappeared, a dot appeared on the screen where either the target or the neutral stimulus had been presented. Participants were asked to press a key to indicate the location of the dot, and their reaction time (RT) was recorded. The difference between RT on compatible (the dot appeared in the same position as the food stimulus) and incompatible (the dot did not appear in the same position as the food stimulus) trials served as the FAB score.
Following Giuliani et al.'s (2013) study, in the intervention procedure, participants were required to write and memorize five sentences, while they were watching a set of pictures that included high-calorie appetizing food products. Participants in the CR group were instructed to write sentences about the negative consequences of eating high-calorie foods whereas participants in the CN group were required to write and memorize five neutral sentences about their day. Following the intervention procedure, all participants performed the VDP task again, with a different set of stimuli. In the last phase of the study the participants self-reported on demographics and eating behaviors.
We hypothesized that:
In the CR group, post intervention FAB scores will be lower than pre-intervention scores. In addition, following the intervention, the CR intervention group would show reduced FAB compared to the control group.
The CR intervention will have a greater impact on FAB levels among participants with higher disturbed eating behaviors than participants with lower disturbed eating behaviors.