Oral Health Status and Dental Services Utilisation Among a Vulnerable Sample of Pregnant Women
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Oral health conditions during pregnancy can negatively impact both mother and fetus, highlighting the importance of maintaining dental care. In Canada, significant disparities exist between general and dental healthcare access, with limited evidence on oral health status and dental care utilisation among pregnant women. This study aimed to provide initial insights into self-perceived oral health status and dental utilisation patterns among a vulnerable sample of pregnant women in southwestern Ontario. METHODS: This cross-sectional study recruited a convenient sample of pregnant women referred to the Family Medicine and Obstetrics Clinic, serving those without a family physician. Data were collected using a self-administered questionnaire adapted from the Canadian Health Measure Survey, the Canadian Community Health Survey, and the Survey of Maternal Health. Andersen and Newman's framework for health service utilisation was used as the theoretical framework. Descriptive and univariable analyses were conducted, followed by a forward stepwise selection of variables with p-values < 0.1 from the univariable analyses. RESULTS: One-hundred-fifty patients were approached and 130 (86.7%) completed the questionnaire. Of these, 96 (73.9%) reported their oral health as good/excellent while 34 (26.2%) reported having poor/fair oral health. Education level and quality of life were the strongest predictors of oral health status. While 101 (77.7%) visited a dentist within the last 2 years, only 35 (26.9%) had a dental visit during pregnancy. Toothbrushing frequency was the main predictor of time since last dental visit, with no other predictive factors once toothbrushing was considered. CONCLUSION: The study sample showed relatively positive self-perceived oral health and dental visit patterns. However, the low rate of dental visits during pregnancy highlights the need for better integration of dental care into prenatal care. To ensure maternal and child health, pregnant women should be a high priority in policies aimed at improving access to dental care.
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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 | 0.000 | 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".