P5 Halitosis and related factors in a Chinese general population
Bibliographic record
Abstract
The purpose of this study was to estimate the distribution of halitosis in a general Chinese population and assess the relationship between halitosis and oral health status and other social or behavioral factors. The subjects were 1000 males and 1000 females aged from 15 to 64 years in urban and rural area of Beijing, China. Questionnaire survey and oral examination was conducted. Questionnaire items included socio‐economic status (income and education), oral habits (brushing), knowledge for oral health, dental attendance, life habits (smoking), medical history and self‐assessment of halitosis. Oral examination comprised of DMFT, plaque index (PI), calculus index (CI), pocket depth (PD), modified sulcus bleeding index (mSBI) and tongue coating score (TCS). Volatile sulfur compounds (VSC) concentrations in mouth air were assessed by Halimeter. If VSC was 75 ppb and above, the subject was diagnosed halitosis. As a result, the prevalence of halitosis was 35.4% for the total population. Age and area of residence did not related to the VSC value. The levels of VSC were different among the period of assessment time. In the 15–24, 25–34 and 55–64‐year‐old groups, VSC values were significantly higher in the late afternoon. DMFT was not related with VSC. General health, social and behavioral factors did not relate to VSC. According to the logistic regression analysis, TCS, gender, CI and mSBI was significantly correlated with VSC. TCS had the highest OR value among them. The prevalence of halitosis was high in this population. Tongue coating played the most important role in determining VSC level, followed by periodontal status. However DMFT, smoking, social economic status, oral habits, general health and other social factors did not contribute to the level of VSC. The effective oral health promotion programs would be necessary to improve the poor oral health status and decrease the level of VSC for this study population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".