The 20-Year Trends in Caries and Associated Determinants among Adults in Post-Soviet Lithuania: Repeated Cross-Sectional Studies
Bibliographic record
Abstract
AIM: The aim of the study was to examine the 20-year trend in dental caries and associated determinants among adults in Lithuania after the country restored its independence. MATERIAL AND METHODS: Data from two cross-sectional national surveys included samples of 35-44-year-olds (adults) and 65-74-year-olds (early elderly). The 1997/1998 survey (first survey) recruited a stratified random sample of 569 individuals from 10 selected areas in Lithuania (response rate 52%), and the 2017/2019 survey (second survey) recruited a stratified random sample of 723 individuals from 5 biggest Lithuanian cities and one randomly selected peri-urban/rural area from each of 10 Lithuanian counties (response rate 53%). The information about the social (sex, residence, education) and behavioral (toothbrushing frequency, use of fluoridated toothpaste, and last dental visit) determinants was collected via self-reports using the World Health Organization (WHO) Oral Health Questionnaire for Adults questions. Information about the fluoride level in the drinking water was retrieved from the water suppliers. Dental caries was recorded at the surface level following the WHO criteria by two calibrated examiners, one at each of the national surveys. Bivariate and multivariate analyses were used. RESULTS: According to multivariable negative binomial regression analysis, in adults, 67% lower DS scores (IRR 0.33, 95% CI 0.26-0.42) and in early elderly 47% lower DS scores (IRR 0.53, 95% CI 0.38-0.74) were observed in the second survey. Adults in the second survey (vs. first survey) had 62% lower MT scores (IRR 0.38, 95% CI 0.32-0.46), and the early elderly had 19% lower MT scores (IRR 0.81, 95% CI 0.72-0.92). Adults in the second survey had 21% lower DMFT scores (IRR 0.79, 95% CI 0.73-0.85). The changes in behavioral determinants were observed over the 20-year period. CONCLUSION: An improvement in dental health during the 20-year period, mainly related to reduction in untreated caries and missing teeth, was observed in adults and early elderly. However, early elderly still had high numbers of missing teeth. The decrease in total caries experience during the 20 years was significant only in adults. Our findings support an urgent need to design and implement national oral health promotion and prevention programs with increased focus on oral self-care and fluoridated toothpaste use.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".