Early childhood growth trajectories and periodontal health among 8-10 year-old Quebec children at risk of obesity
Bibliographic record
Abstract
Background: Anthropometric measures including birth weight and body mass index have been associated with adult periodontal disease. However, there is limited evidence regarding the role of childhood growth in subsequent periodontal inflammation. Objectives: We estimate the extent to which childhood growth trajectories between age 0 to 2 years are associated with indicators of periodontal health among 8-10 year old children participating in the QUALITY Cohort.Methods: We used baseline data from an ongoing prospective study, the QUALITY (Quebec Adipose Lifestyle Investigation in Youth) cohort investigating the natural history of obesity among 8-10-year-old Caucasian children living in Quebec, Canada. This analysis included 244 boys and 186 girls for whom data were available on anthropometric measures and periodontal health, namely concentration levels of TNFα-GCF and gingival bleeding on probing. Anthropometric measures at birth and up to 2 years of age were collected retrospectively from the Quebec health booklets. GCF samples were collected from the gingival sulcus using a paper strip and the concentration of TNFα-GCF was determined by enzyme-linked immunosorbent assay and the presence of gingival bleeding was measured in buccal and lingual surfaces of the Community Periodontal Index (CPI). Growth analysis of weight-for-length z-score by age was done using the ‘lcmm’ (Latent Class Mixed Model) package in R and the indicators of periodontal health were regressed on the resultant growth trajectories using a regression analysis adjusting for body mass index (BMI) of the child and mother, parental income, education status of mother, maternal age, child’s age, breastfed.Results: The mean age of the children was 9.1 years (SD=0.9) and majority of them were males (n= 244, 56.7%). Most children did not have excess weight (62%) and the average gestational age was around 40 weeks. The mean age of the children’s mother was 30.27 (SD=4.7) years and 18% of them had history of gestational diabetes. The mean family income was 42,727 CAD$. The median TNFα-GCF was 215 (IQR: 33, 517), and the median proportion of gingival bleeding sites was 75 (50, 83.33). We identified a three-class quadratic solution in the data analysis and defined as follows: Growth of the children that started out at a lower than average weight for length at birth but grew rapidly were named as Class 1; children who had a higher than average weight for length at birth but had a dip in growth were named as Class 2; while Class 3 denoted expected growth in a child who was born at the average weight for length and initially rose rapidly and then became steady. In the adjusted linear model, having a class 1 or class 2 type trajectory, compared to class 3, showed no association with concentration levels of TNFα-GCF on average [0.49 (95% CI:-10.80, 11.79) or 0.18(95% CI: -10.29, 10.64)], respectively. Also, another adjusted linear model having a class 1 or class 2 type trajectory, compared to class 3, showed no association with proportion of sites with gingival bleeding on probing [2.11 % (95% CI :-4.75, 8.98) or 1.13 % (95% CI: -5.23, 7.49)] respectively( table 3).Conclusions: The expected growth trajectory showed no association with either TNFα-GCF levels nor proportion of sites with gingival bleeding
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".