Ethnic differences in diurnal cortisol profiles in healthy adults: A meta‐analysis
Bibliographic record
Abstract
PURPOSE: Cortisol is a well-known biomarker of the physiological stress system; atypical cortisol patterns have been linked to many psychological and physiological illnesses. Previous studies have found vast health disparities among ethnic groups; however, studies examining the relationship between cortisol and ethnicity have found mixed results. This meta-analysis investigated whether there are differences in diurnal cortisol outcomes among ethnic groups, while considering the moderating roles of various individual factors and methodological approaches. METHODS: Search phrases were entered into MEDLINE, PsycINFO, EMBASE, Cochrane Library, CINAHL, Scopus, and Web of Science. Effect sizes were extracted for ten diurnal cortisol outcomes, including waking, 30 min after waking, cortisol awakening response, slope, area under the curve, urinary twenty-four-hour secretion, total cortisol output, and midday, evening, and bedtime concentrations, for eight ethnic group comparisons, including Asians, Blacks, Hispanics, Indigenous people, Whites, Minority and Majority groups, and Multiethnic groups. Moderator analyses, including variables such as gender, age, and number of cortisol collection time points, were conducted. RESULTS: There were significant ethnic differences in diurnal cortisol profiles, including cortisol awakening responses, with more robust differences in ethnic comparisons that included White participants. Differences in diurnal cortisol profiles were also moderated by gender, mean age, and sample size. CONCLUSIONS: This meta-analysis supports the notion that ethnic groups exhibit distinct diurnal cortisol profiles, which, according to the biopsychosocial model of health, may be a result of unique sociocultural experiences. The limitations of this meta-analysis and future directions for stress research with various ethnic groups are discussed. Statement of contribution What is already known on this subject? Studies have found vast health disparities among ethnic groups. Psychological and physiological illnesses and atypical diurnal cortisol profiles are strongly correlated. Studies have examined the relationship between diurnal cortisol rhythms and ethnicity, but findings are mixed. What does this study add? This study is a systematic examination of the relationship between diurnal cortisol rhythm and ethnicity. Psychosocial and methodological factors moderate the relationship between diurnal cortisol output and ethnicity. This study provides insight on factors that contribute to health disparities among ethnic groups.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".