The Association of Weight Status with Dental Caries and Trachoma Among School Children in Cities of Changsha and Shenzhen, China
Bibliographic record
Abstract
Dental caries and trachoma are two common diseases among children in developing countries. To examine whether weight status is associated with these two diseases, we used data from two screening surveys conducted in Changsha and Shenzhen, two cities in China. The screening surveys were part of a case-control study examining risk factors related to childhood obesity. Approximately 5,900 children (3,794 from Changsha and 2,193 from Shenzhen) participated in the screening survey in which weight and height were measured. Decayed or filled tooth counts (primary dentition) and trachoma infection status were obtained from school general health examination records (SGER). After excluding those who had missing information on weight, height, and SGER, a total of 4,073 (2,185 boys and 1,888 girls) aged 5-9 years old were included in the analysis. Body mass index (BMI) was calculated as weight (kg) divided by height (m 2 ) and standardized for age and sex, then converted to a BMI z-score. Using BMI z-score, subjects were categorized into 4 groups as underweight (<-2), normal weight (~1.03), overweight (~1.64), or obese (>1.64). Overall, approximately 5.5% of children (6.2% girls and 4.6% boys) were underweight and 18% (11% girls and 23% boys) were overweight or obese. Comparing normal weight to underweight, overweight and obese subjects, after adjusting for age, gender, grade, and city of survey, the odds ratios (OR, [95% CI]) for dental caries were 1.12 (0.84-1.49), 0.70 (0.56-0.86), and 0.62 (0.48-0.79), (p for trends <0.001) while the ORs for trachoma were 1.65 (0.94-2.89), 0.90 (0.52-1.57), and 1. 92 (1.20 -3.06). This suggests that weight status is associated with dental caries and trachoma among these Chinese children. Further study is warranted to explore the underlying mechanism(s).
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".