Autonomic Nervous System Response to Psychosocial Stress in Anorexia Nervosa: A Cross-Sectional and Controlled Study.

To foster understanding in the psychopathology of patients with anorexia nervosa (PAN) at the psychological and physiological level, standardized experimental studies on reliable biomarkers are needed, especially due to the lack of disorder-specific samples. To this end, the autonomic nervous system (ANS) response to a psychosocial stressor was investigated in n = 19 PAN (BMI: 18.7 ± 3.3 kg/m2), age, and gender-matched to n = 19 healthy controls (HC; BMI: 24.23 ± 3.0 kg/m2). For this purpose, heart rate (HR) and heart rate variability (HRV) parameters were assessed in a cross-sectional study design under two experimental conditions: (1) rest and (2) stress (Trier Social Stress Test). In addition, psychological indicators of stress were assessed. An 2 × 2 × 8 ANOVA demonstrated similar HR and HRV patterns (except LF-HRV) between PAN and HC at rest. Under stress, PAN (vs. HC) demonstrated a blunted HR [condition*time*group: F (2.91, 104.98) = 9.326, p = 0.000, η2 = 0.206] and an attenuated HRV response (reduced SNS/PNS reactivity). Significant effects of stress appraisal (SA) and BMI on HRV-reactivity were revealed. SA on SDNN = Condition*time*SA = F (4.12, 140.15) = 2.676, p = 0.033, η2 = 0.073. BMI on LF/HF-Ratio = Condition*time*BMI = F (3.53, 60.16) = 3.339, p = 0.019, η2 = 0.164. Psychological indices suggested higher levels of chronic and appraised stress in PAN relative to HC. Additional analyses demonstrated that ED-symptoms are highly correlated with the latter constructs, as well as with psychological burden, but not with weight. Further, it was shown that abnormalities in reactivity persisted despite normalized ANS activity. Overall, we suggested that besides weight recovery, improvement in stress appraisal could be beneficial for cardiac health. In this light, a combination of therapy (e.g., development and activation of coping skills, cognitive reappraisal) and biofeedback training may improve treatment outcomes and regulate stress reactivity.

Effects of stress on chewing and food intake in patients with anorexia nervosa.

OBJECTIVE: The present study investigates the impact of psychosocial stress on chewing and eating behavior in patients with anorexia nervosa (PAN ). METHOD: The eating and chewing behavior of PAN were examined in a standardized setting by means of a chewing sensor. These procedures encompassed n = 19 PAN , age, and gender matched to n = 19 healthy controls (HC). Food intake and chewing frequency were assessed in two experimental conditions: rest versus stress (via Trier Social Stress Test). To verify stress induction, two appraisal scales were employed. In addition, chronic stress, psychological distress and eating disorder symptoms were assessed. RESULTS: In terms of food intake and chewing frequency, the results of the 2x2 ANOVA demonstrated a significant effect of condition and group. During stress, all participants demonstrated a higher chewing frequency and a decreased ingestion. In general, patients ate less at a lower chewing frequency (vs. HC). However, sample specific analyses demonstrated that the eating and chewing behavior of PAN remained unchanged regardless of the condition, except for their drinking. Food choices were comparable between the groups, but appetite values significantly differed. DISCUSSION: The increase in chewing frequency in all participants during stress suggests that chewing might impact affect regulation, however, not specifically in PAN . Future research should clarify to what extent the normalization of chewing behavior could ameliorate ED-symptoms (incl. food intake) in PAN . The application of a chewing sensor could support this aim and future interventions.

Cortisol reactivity in patients with anorexia nervosa after stress induction.

There is a need of experimental studies on biomarkers in patients with anorexia nervosa (PAN), especially in the context of stress, in order to foster understanding in illness maintenance. To this end, the cortisol response to an acute stressor was investigated in n = 26 PAN (BMI: 19.3 ± 3.4 kg/m2), age, and gender matched to n = 26 healthy controls (HC; BMI: 23.08 ± 3.3 kg/m2). For this purpose, salivary cortisol parameters were assessed in two experimental conditions: (1) rest/no intervention and (2) stress intervention (TSST; Trier Social Stress Test). In addition, psychological indicators of stress were assessed (Primary Appraisal Secondary Appraisal, Visual Analogue Scale, and Trier Inventory for the assessment of Chronic Stress), as well as psychological distress, depression, and eating disorder (ED) symptoms. A 2 × 2 × 8 ANOVA demonstrated elevated cortisol levels in PAN in the resting condition. In the stress intervention no significant group effect in terms of cortisol (F (1, 50) = 0.69; p = 0.410; [Formula: see text]). A significant condition (F (1, 50) = 20.50; p = 0.000; [Formula: see text]) and time effect (F(2.71, 135.44) = 11.27; p = 0.000; [Formula: see text]) were revealed, as well as two significant interaction effects. First: Condition × group (F (1, 50) = 4.17, p = 0.046; [Formula: see text]) and second: Condition × time (F (2.71, 135.44) = 16.07, p = 0.000, [Formula: see text]). In terms of AUCG, no significant differences between both groups were exhibited. Regardless, significant results were evinced in terms of an increase (AUCi: F(1, 50) = 20.66, p = 0.015, [Formula: see text]), baseline to peak (+20 min post-TSST: t5 = 16.51 (9.02), p = 0.029) and reactivity (MPAN = 0.73 vs. MHC = 4.25, p = 0.036). In addition, a significant correlation between AUCG and BMI: r (24) = -0.42, p = 0.027 was demonstrated, but not between AUCi and BMI (r (24) = -0.26, p = 0.20). Psychological indices suggested higher levels of chronic and perceived stress in PAN relative to HC. However, stress perception in the stress condition (VAS) was comparable. Additional analyses demonstrated that ED-symptoms are highly correlated with psychological distress and depression, but not with BMI. In addition, it could be demonstrated that reactivity is rather related to ED-symptoms and psychological burden than to BMI. In conclusion, PAN showed elevated basal cortisol levels at rest and exhibited a blunted cortisol reactivity to the TSST as evinced by salivary cortisol parameters. Further, it was shown that weight recovery influences reversibility of hypercortisolemia, i.e., cortisol levels normalize with weight gain. However, HPAA (hypothalamus-pituitary-adrenal axis) irregularities in terms of reactivity persist even at a BMI ≤ 19.3 (±3.4). Our data suggest that pronounced psychological burden in PAN, have a greater impact on the HPAA functionality (secondary to the ED) than BMI itself.

Stress-related laboratory eating behavior in adults with obesity and healthy weight.

Stress is an important factor in the progression of irregular eating patterns and has an additional exacerbating impact in people with overweight and obesity. Therefore, in this study, the chewing and food intake was observed after standardized acute stress induction, as well as resting, in people with obesity and healthy weight controls. Twenty-eight women and men with obesity (BMI: 32.76 ±â€¯2.25 kg/m2) were matched with regard to sex and age to 28 people with healthy weight (BMI: 22.58 ±â€¯2.04 kg/m2). After two conditions (Trier Social Stress Test vs. resting condition) the chewing frequency and food intake were measured during a standardized laboratory meal on two separate days. Additionally, for manipulation check of stress induction salivary cortisol and two appraisal questionnaires (Primary Appraisal Secondary Appraisal, Visual Analogue Scale) were used. People with obesity showed after stress and resting condition a lower chewing frequency in contrast to healthy weight controls (F(1, 54) = 12.816, p ≤ .001). Thereby, both groups demonstrated a higher chewing frequency after the stress induction than after the resting condition (F(1, 54) = 7.436, p ≤ .01). There was no difference between the healthy weight controls and the people with obesity in food intake. In conclusion, the present data indicate a possible 'obese eating style' with regard to chewing performance. Furthermore, the demonstrated higher chewing frequency after stress induction, in people with obesity and people with healthy weight, might be a stress reduction strategy.

Chewing after stress: psychosocial stress influences chewing frequency, chewing efficacy, and appetite.

BACKGROUND: Psychosocial stress is accompanied by an increase in the activity of the hypothalamic-pituitary-adrenocortical (HPA)-axis and by an increase in food intake. At present, no studies have been conducted to examine the impact of a potent laboratory stress test on the chewing frequency. METHODS: Thirty-one healthy participants (14 females, mean age 27.13) were compared after they had fulfilled the protocol of a standardized psychosocial stress test, the Trier Social Stress Test (TSST), and after a resting condition of silent reading in reference to their chewing frequency, chewing efficacy, food intake, and eating preferences. As part of the design free salivary cortisol levels and heart rate variability were measured repeatedly before and after the TSST and the resting condition. RESULTS: After the TSST, the participants exhibited a significantly higher mean chewing frequency than after the resting condition (F(2,60)=3.600, p=.035, η(2)=.107). The testing condition had no influence on the amount of food intake. Following the psychosocial stress, however, the participants reported a significantly less general appetite (Z=-3.921, p<.001) and less of an appetite for eggs (Z=-2.023, p=.043) than after their resting condition. No correlation was found between the salivary cortisol response and the chewing frequency. CONCLUSION: The results indicated that psychosocial stress is associated with an increase in chewing frequency, as measured with a sound-based apparatus, and with a decrease in appetite.

Food intake monitoring: automated chew event detection in chewing sounds.

The analysis of the food intake behavior has the potential to provide insights into the development of obesity and eating disorders. As an elementary part of this analysis, chewing strokes have to be detected and counted. Our approach for food intake analysis is the evaluation of chewing sounds generated during the process of eating. These sounds were recorded by microphones applied to the outer ear canal of the user. Eight different algorithms for automated chew event detection were presented and evaluated on two datasets. The first dataset contained food intake sounds from the consumption of six types of food. The second dataset consisted of recordings of different environmental sounds. These datasets contained 68,094 chew events in around 18 h recording data. The results of the automated chew event detection were compared to manual annotations. Precision and recall over 80% were achieved by most of the algorithms. A simple noise reduction algorithm using spectral subtraction was implemented for signal enhancement. Its benefit on the chew event detection performance was evaluated. A reduction of the number of false detections by 28% on average was achieved by maintaining the detection performance. The system is able to be used for calculation of the chewing frequency in laboratory settings.

Food intake monitoring: an acoustical approach to automated food intake activity detection and classification of consumed food.

Obesity and nutrition-related diseases are currently growing challenges for medicine. A precise and timesaving method for food intake monitoring is needed. For this purpose, an approach based on the classification of sounds produced during food intake is presented. Sounds are recorded non-invasively by miniature microphones in the outer ear canal. A database of 51 participants eating seven types of food and consuming one drink has been developed for algorithm development and model training. The database is labeled manually using a protocol with introductions for annotation. The annotation procedure is evaluated using Cohen's kappa coefficient. The food intake activity is detected by the comparison of the signal energy of in-ear sounds to environmental sounds recorded by a reference microphone. Hidden Markov models are used for the recognition of single chew or swallowing events. Intake cycles are modeled as event sequences in finite-state grammars. Classification of consumed food is realized by a finite-state grammar decoder based on the Viterbi algorithm. We achieved a detection accuracy of 83% and a food classification accuracy of 79% on a test set of 10% of all records. Our approach faces the need of monitoring the time and occurrence of eating. With differentiation of consumed food, a first step toward the goal of meal weight estimation is taken.