The Relationship Between Periodontal Disease and Public Health: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Periodontal diseases, such as periodontitis, are considered the main cause of tooth loss in the elderly.The present study is aimed to determine the relationship between periodontal condition and quality of life. Quality of life consists of a range of people's objective needs related to the self-perception of well-being. METHODS: This study was done from January 2014 to June 2015 in a healthcare clinic in Zahedan, southeast Iran. Using the random sampling method, the researchers enrolled 700 individuals over 35 years of age. The participants initially completed a demographic questionnaire consisting of data, such as age, sex, educational level, and smoking habit. Then, the periodontal chart was completed. Moreover, patients, based on the number of their natural teeth, were divided into two groups (≥10 teeth in both maxillary and mandible arches and <10 teeth in at least one arch). The body mass index (BMI) was also measured.To assess the participants' general health, the WHO's quality of life questionnaire (WHOQOL-BREF) was used. RESULTS: Of the 700 enrolled individuals, 53.3% were womenand 47.7% were men. Moreover, most of the participants (63.71%) had BMI of less than 25 and 68% did not smoke.We found that as the people's periodontal status deteriorated, their quality of life also declined and the total mean score in all four health domains decreased (P<0.001).Moreover, people with more than 10 teeth in both arches scored higher with respect to life quality than those with less than 10 teeth in at least one arch (P<0.001). CONCLUSION: This studyindicates a decrease in the general quality of life in patients with periodontal disease.The authors suggest performing studies with larger sample sizes andcohort studies for more reliable results.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".