The Relationship between Psychological Stress and Anthropometric, Biological Outcomes: A Systematic Review
Bibliographic record
Abstract
Background and Objectives: Challenges and threats to global security and the growing demands of today’s society lead to significantly increased exposure to stress. Stress can negatively affect numerous physiological processes, including metabolic changes. An unhealthy lifestyle might intensify this disruption. The aim of the systematic review was to establish the effect of psychological stress on metabolic and anthropometric factors in healthy individuals. Materials and Methods: The study was conducted according to the PRISMA guidelines; and the risk of bias (ROB) assessment was based on the Newcastle–Ottawa Scale (NOS). A literature search of the MEDLINE/PubMed database was conducted using specific search terms. Results: We identified 32 articles meeting the inclusion criteria for the review with the different experimental designs and aims. Most of the papers were at high ROB. The included studies were conducted in groups of adults and children/teenagers. The most-often-applied tool to measure stress severity was the Perceived Stress Scale (PSS). Twenty-two studies analyzed the connection between stress and body composition, and bioimpedance analysis (BIA) was the most often used method. For biological parameters, the most frequently analyzed was cortisol (n = 9). The other examined factors included glucose, insulin, parameters related to food intake regulation, carbohydrates, lipid metabolism, inflammation, and oxidative stress. The included studies were incompliance in relation to the assessment method and type of assessed biological fluids. Conclusions: The vast majority of studies do not support the effect of chronic distress on anthropometric measurements and biological markers levels. However, many of them suggest adverse, synergistic effects of unhealthy lifestyle patterns and the stress on the examined variables. Further experiments should implement a similar and repeatable methodology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".