Distal and Proximal Influences on Self-Reported Oral Pain and Self-Rated Oral Health Status in Saudi Arabia: Retrospective Study Using a 2017 Nationwide Database
Bibliographic record
Abstract
BACKGROUND: Oral health significantly influences overall well-being, health care costs, and quality of life. In Saudi Arabia, the burden of oral diseases, such as dental caries and periodontal disease, has increased over recent decades, driven by various lifestyle changes. OBJECTIVE: To explore the associations between proximal (direct) and distal (indirect) influences that affect oral pain (OP) and self-rated oral health (SROH) status in the Kingdom of Saudi Arabia (KSA) using an adapted conceptual framework. METHODS: This retrospective cross-sectional study used data from a national health survey conducted in KSA in 2017. The sample included adults (N=29,274), adolescents (N=9910), and children (N=11,653). Sociodemographic data, health characteristics, and access to oral health services were considered distal influences, while frequency and type of dental visits, tooth brushing frequency, smoking, and consumption of sweets and soft drinks were considered proximal influences. Path analysis modeling was used to estimate the direct, indirect, and total effects of proximal and distal influences on OP and SROH status. RESULTS: The mean age of adult respondents was 42.2 years; adolescents, 20.4 years; and children, 10.58 years. Despite OP reports from 39% of children, 48.5% of adolescents, and 47.1% of adults, over 87% across all groups rated their oral health as good, very good, or excellent. A higher frequency of tooth brushing showed a strong inverse relationship with OP and a positive correlation with SROH (P<.001). Frequent dental visits were positively associated with OP and negatively with SROH (P<.001). Sweet consumption increased OP in adolescents (β=0.033, P=.007) and negatively affected SROH in children (β=-0.086, P<.001), adolescents (β=-0.079, P<.001), and adults (β=-0.068, P<.001). Soft drink consumption, however, was associated with lower OP in adolescents (β=-0.034, P=.005) and improved SROH in adolescents (β=0.063, P<.001) and adults (β=0.068, P<.001). Smoking increased OP in adults (β=0.030, P<.001). Distal influences like higher education were directly linked to better SROH (β=0.046, P=.003) and less OP (indirectly through tooth brushing, β=-0.004, P<.001). For children, high household income correlated with less OP (β=-0.030, P=.02), but indirectly increased OP through other pathways (β=0.024, P=.003). Lack of access was associated with negative oral health measures (P<.001). CONCLUSIONS: Among the KSA population, OP and SROH were directly influenced by many proximal and distal influences that had direct, indirect, or combined influences on OP and SROH status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".