Effect of Daily Water Intake on Periodontal Health and Dental Caries: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Water is crucial for maintenance of human body health. Objective: The study aimed to determine the effect of water intake on oral health and to compare the water intake behaviors in people of different age groups, genders, and professions. Study Design: Cross-sectional study. Settings: Study was conducted in the outpatient department of Punjab Dental Hospital through systemic random sampling. Duration: November 02, 2022 to January 03, 2023. Methods: A close-ended questionnaire was designed and administered; the later clinical examination was performed, and findings were recorded. Data were analyzed using SPSS version 23. Results: DMFT score was highest among those aged between 45 to 54 years, males, having elementary school education, unemployed, and having sedentary job activity level. Males (33.6%) were consuming more water. Respondents drinking adequate water had coral pink gingiva (25.6%), whereas those who were consuming less water had red gingiva (25.6%), bleeding on probing (37.6%), and supra gingival calculus (33.6%). The main reasons for not drinking adequate water were forgetfulness, followed by adipsia and fear of polyuria. Most respondents (72.8%) preferred drinking water at home rather than at work. Most respondents (72.8%) do not drink water at their workplace as they preferred (32%) to drink home-filtered water. Most respondents (83.2%) used only water for oral cleaning. Conclusion: Those consuming less than 1 liter of water daily had an increased prevalence of supragingival calculus, bleeding gums, and dark red gingiva. The mode of intervention should be mass education regarding water consumption, as per guidelines of WHO and ADA.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".