Prevalence and associated factors of disorders of gut‐brain interaction in the United States: Comparison of two nationwide Internet surveys
Bibliographic record
Abstract
BACKGROUND: No comprehensive assessment of disorders of gut-brain interaction (DGBI) in the United States (US) national population has been published in the past three decades. We aimed to provide an updated picture of DGBI in the United States and associated factors, using data from two national Internet surveys. METHODS: Data were analyzed from 1949 people surveyed in 2015, and 2023 people surveyed in 2017 as a part of the Rome Foundation Global Epidemiology Study (RFGES). The surveys had nearly identical methodology and included the Rome IV Diagnostic Questionnaire and questions on demographics, quality of life (QoL), emotional symptoms, and healthcare utilization. KEY RESULTS: The prevalence of having any DGBI was 36.0% and 39.9% in the two surveys. Prevalence estimates for the 22 DGBI assessed were broadly comparable between the surveys, as their 95% confidence intervals overlapped for every disorder. Females had DGBI more commonly than males in both surveys (odds ratios 1.66 and 1.52), and people of age 65 and older had lower DGBI prevalence than younger age groups. Having DGBI was associated in both surveys with significant QoL impairment, elevated anxiety, depression and somatization symptoms, and increased doctor visits. CONCLUSIONS AND INFERENCES: Approximately 4 out of every 10 US adults have a DGBI; more commonly women and people under the age of 65. DGBI adversely affect QoL and emotional well-being and increase healthcare needs. The similarity of findings between the two surveys supports the reliability of DGBI prevalence estimates obtained with the Internet survey method used globally in the RFGES.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".