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. 2022;112(2):130-142.
doi: 10.1159/000514484. Epub 2021 Jan 18.

Biological and Psychological Stress Correlates Are Linked to Glucose Metabolism, Obesity, and Gender Roles in Women

Affiliations

Biological and Psychological Stress Correlates Are Linked to Glucose Metabolism, Obesity, and Gender Roles in Women

Alexander Kautzky et al. Neuroendocrinology. 2022.

Abstract

Objectives: Psychological stress affects central as well as peripheral metabolism and hormone trafficking via the hypothalamic-pituitary-adrenal axis. Stress thereby plays a decisive role in the etiology and progression of overweight and obesity, leading to several chronic diseases, such as diabetes, and mental health disorders. The interplay of biological and psychometric correlates of stress, anthropometric, immunological, and metabolic parameters and psychosocial factors such as gender roles, however, remains poorly understood.

Methods: In this exploratory study, 43 healthy women were assessed for glucose metabolism by an oral glucose tolerance test and computation of functional parameters for insulin secretion, sensitivity, and resistance. Further, the fatty liver index (FLI) and anthropometric parameters body mass index (BMI), waist-to-hip ratio, body fat, and lean mass were assessed. Psychological stress assessment included the "Brief Symptom Inventory" (BSI), the "Burnout Dimensions Inventory" (BODI), and Perceived Stress Scale (PSS). Biological stress response was evaluated with heart rate variability and cortisol levels. Finally, gender role self-identification was assessed with the "Bem Sex-Role Inventory" (BSRI). Generalized linear models were computed for exploratory association with psychometric outcome. Uncorrected p values are reported.

Results: Burnout and PSS scores were associated with insulin secretion, sputum cortisol, thyroid-stimulating hormone, anthropometric measures, and gender role. BSI ratings for psychiatric symptom dimensions were associated with insulin resistance, sex hormones, anthropometric measures, and gender role. Female self-identification was associated with higher BMI as well as body fat and a higher FLI.

Conclusions: Considering the increased risk of unfavorable metabolic, cardiovascular, and also mental health outcome in obese women, a higher BMI in women with predominant female gender self-identification may be relevant for clinical risk assessment. The broad range of interacting biological, psychological, and gender-related parameters calls for an integrative management of both mental and endocrinological health. However, the exploratory nature of the study requires replication in larger samples before definite conclusion can be drawn.

Keywords: Insulin trafficking; Obesity; Stress.

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Conflict of interest statement

The authors have no conflicts of interest to declare.

Figures

Fig. 1
Fig. 1
Main and interaction effects from the GLMs for metabolic and inflammatory parameters. Only significant (p < 0.05) effects are depicted. For illustration of interaction effects of 2 continuous variables, HOMA-IR was divided into a factor with 3 levels, indicating the likelihood of insulin presence. HOMA-IR, homeostasis model was used for assessment of insulin resistance; GLM, generalized linear model.
Fig. 2
Fig. 2
Main and interaction effects from the GLMs for anthropometric parameters. Only significant (p < 0.05) effects are depicted. For illustration of interaction effects of 2 continuous variables, body fat was divided into a factor with 3 levels by sample distribution (±1 SD). GLM, generalized linear model.
Fig. 3
Fig. 3
Main and interaction effects from the GLMs for hormone parameters. Only significant (p < 0.05) effects are depicted. For illustration of interaction effects of 2 continuous variables, LH was divided into a factor with 3 levels by sample distribution (±1 SD). GLM, generalized linear model.
Fig. 4
Fig. 4
Main and interaction effects from the GLMs for biofeedback parameters. Only significant (p < 0.05) effects are depicted. For illustration of interaction effects of 2 continuous variables, stress HRV was divided into a factor with 3 levels by sample distribution (±1 SD). HRV, heart rate variability; GLM, generalized linear model.

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