Common oral conditions and correlates: an oral health survey in Kwara State Nigeria
Bibliographic record
Abstract
BACKGROUND: Oral diseases are one of the most prevalent health problems today with distribution and severity varying in different parts of the world and within the same country. Oral health surveys are needed to determine prevalence of oral conditions and the nature and urgency of oral health interventions. A modified version of World Health Organisation pathfinder survey methods was used to determine prevalence of oral conditions amongst 150 respondents in two local government areas in Kwara State, Nigeria. This involved a stratified cluster sampling technique which identified the subgroups; location and certain age groups 5-6, 12 and 35-44 years age groups respectively. Clinical oral examination was carried out to determine the presence and types of common oral conditions among the respondents. Data analysis was done using descriptive statistics and Chi square analysis at 5% level of significance. RESULTS: Among all the selected subjects 91.3% had an oral condition, while for the rural and urban population it was 93.3 and 89.3% respectively (p > 0.05). The most prevalent oral conditions were plaque and surface calculus found in 66.0% of the respondents respectively. Others are gingivitis (30.0%), enamel wear (15.0%) and dental caries (13.0%). The mean decayed missing filled teeth index was 0.26. The decayed missing filled teeth index did not show any significant difference between the rural and urban areas or male and female gender. The presence of calculus (p = 0.005) and gingivitis (0.015) was more in males than females. The presence of plaque (0.001) and calculus (0.006) was significantly more among the skilled workforce. The 12 year age group had significantly more cases of plaque, calculus and gingivitis while there were more cases of enamel wear among the 35-44 year olds compared with other age groups. There were more cases of trauma (87.5%) seen in urban than rural location (p = 0.029). CONCLUSION: Oral health in selected communities of Kwara State is suboptimal requiring intervention. The presence of oral conditions is influenced by age, occupation, location and gender.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".