The influence of living conditions and individual behaviors on the oral‐systemic disease connection: a cross‐sectional analysis
Bibliographic record
Abstract
OBJECTIVES: To determine the extent to which living conditions and individual behaviors influence the association between oral health status and systemic disease outcomes in Ontario, Canada's most populated province. METHODS: A secondary data analysis of Ontario data from the Canadian Community. Health Survey 2013/14 was undertaken. Separate analyses were conducted for participants aged 35-59 years (n = 11,858) and 60+ years (n = 11,273). A series of regression models were constructed to examine the association between self-reported oral health status and systemic disease outcomes (arthritis, diabetes, hypertension, heart disease, chronic obstructive pulmonary disease, and stroke). Models were adjusted by proxies of living conditions (income, education, ethnicity, country of birth, employment, and food security) and individual behaviors (smoking status, alcohol use, tooth brushing, life stress, physical activity, sense of belonging). Percent attenuation between models was calculated to determine the extent of the living condition-behavior impact. RESULTS: In both age groups, the prevalence of arthritis and high blood pressure was the highest, followed by heart disease. There was variation in percent attenuation by age group and outcome. Among participants aged 35-59 years, living conditions had a greater impact on the oral-systemic relationship, while individual behaviors played a greater role in this association among adults aged 60+ years. CONCLUSION: There is an association between oral and systemic diseases; however, after accounting for living conditions and individual behaviors, this relationship was attenuated. This highlights the need to address upstream and midstream factors that are common to oral and systemic conditions.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".