Stress as a common risk factor for obesity and addiction

Rajita Sinha, Ania M Jastreboff, Rajita Sinha, Ania M Jastreboff

Abstract

Stress is associated with obesity, and the neurobiology of stress overlaps significantly with that of appetite and energy regulation. This review will discuss stress, allostasis, the neurobiology of stress and its overlap with neural regulation of appetite, and energy homeostasis. Stress is a key risk factor in the development of addiction and in addiction relapse. High levels of stress changes eating patterns and augments consumption of highly palatable (HP) foods, which in turn increases incentive salience of HP foods and allostatic load. The neurobiological mechanisms by which stress affects reward pathways to potentiate motivation and consumption of HP foods as well as addictive drugs is discussed. With enhanced incentive salience of HP foods and overconsumption of these foods, there are adaptations in stress and reward circuits that promote stress-related and HP food-related motivation as well as concomitant metabolic adaptations, including alterations in glucose metabolism, insulin sensitivity, and other hormones related to energy homeostasis. These metabolic changes in turn might also affect dopaminergic activity to influence food motivation and intake of HP foods. An integrative heuristic model is proposed, wherein repeated high levels of stress alter the biology of stress and appetite/energy regulation, with both components directly affecting neural mechanisms contributing to stress-induced and food cue-induced HP food motivation and engagement in overeating of such foods to enhance risk of weight gain and obesity. Future directions in research are identified to increase understanding of the mechanisms by which stress might increase risk of weight gain and obesity.

Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1
Figure 1
Total stress scores for cumulative adverse life events and chronic stress associated with (a) current smoking status (X2 = 31.66, df=1, P < 0.0001; Odds Ratio =1.196 {95%CI: 1.124–1.273}); (b) current alcohol use as categorized by NIAAA alcohol use criteria for regular, binge and heavy levels of consumption and DSM-IVR diagnosis for alcohol dependence (X2 =15.37, df=1, P < 0.0001; OR =1.113 {95%CI: 1.055–1.173}); and (c) current body mass index (BMI) groups for lean (206), overweight (199) and obese (183) (X2 = 25.47, df=1, P < 0.0001, OR =1.146 (95%CI: 1.087–1.208)) assessed in a community sample of 588 participants.
Figure 2
Figure 2
Greater total cumulative stress significantly predicts log transformed (a) fasting plasma glucose levels (adjusted R2 = 0.0189; t=2.88. p<.004), (b) fasting insulin (adjusted R2 = 0.016; t=2.74, p<.007), and, (c) HOMA-IR (adjusted R2 = 0.0210, t=3.02, p<.0027) in a subsample of the 380 healthy non-diabetic subjects. Figures show raw data for FPG, insulin and HOMA-IR comparing the low, medium and high total stress groups (p values corrected for multiple comparisons using Tukey tests).
Figure 3
Figure 3
Axial brain slices in the obese and lean groups of neural activation differences observed in contrasts comparing favorite-food cue vs. neutral-relaxing conditions (A) and stress versus neutral-relaxing conditions (B) (threshold of p

Figure 4

A heuristic model is proposed…

Figure 4

A heuristic model is proposed of how HP foods, food cues and stress…

Figure 4
A heuristic model is proposed of how HP foods, food cues and stress exposure may increase subjective (emotions, hunger) and also activate metabolic, stress and motivation systems in the brain and body to promote HP food motivation and intake (A). Stress-responsive hormones (ACTH, cortisol) and metabolic factors (insulin, ghrelin, leptin) influence brain limbic and striatal reward regions (emotion and signaling) to influence dopaminergic signaling, activate hypothalamic and midbrain arousal regions and prefrontal cortical circuits involved in reward prediction, self control and decision making (B). With weight-related adaptations in metabolic, neuroendocrine and subjective/behavioral responses, a vulnerable individual becomes highly susceptible to food cues-related and stress-related HP food craving which predicts HP food intake in these susceptible individuals (C). Such a sensitized process with increased HP food motivation and intake would in turn also promote weight gain (D), thereby potentiating the cycle of weight-related adaptations in stress and metabolic pathways (E), and increased sensitization of brain motivation pathways, to promote HP food motivation and intake, especially under conditions of food cue or stress exposure. Individual differences variables may further moderate these relationships as shown in F.
Figure 4
Figure 4
A heuristic model is proposed of how HP foods, food cues and stress exposure may increase subjective (emotions, hunger) and also activate metabolic, stress and motivation systems in the brain and body to promote HP food motivation and intake (A). Stress-responsive hormones (ACTH, cortisol) and metabolic factors (insulin, ghrelin, leptin) influence brain limbic and striatal reward regions (emotion and signaling) to influence dopaminergic signaling, activate hypothalamic and midbrain arousal regions and prefrontal cortical circuits involved in reward prediction, self control and decision making (B). With weight-related adaptations in metabolic, neuroendocrine and subjective/behavioral responses, a vulnerable individual becomes highly susceptible to food cues-related and stress-related HP food craving which predicts HP food intake in these susceptible individuals (C). Such a sensitized process with increased HP food motivation and intake would in turn also promote weight gain (D), thereby potentiating the cycle of weight-related adaptations in stress and metabolic pathways (E), and increased sensitization of brain motivation pathways, to promote HP food motivation and intake, especially under conditions of food cue or stress exposure. Individual differences variables may further moderate these relationships as shown in F.

Source: PubMed

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