Adverse Childhood Experiences and the Co‐occurrence of Poor Oral Health and Multimorbidity: Findings From the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVES: To investigate the extent of the association of adverse childhood experiences (ACEs) with co-occurring poor self-reported oral health (SROH) and multimorbidity in middle-aged and older adults, and whether these associations differ by age and sex. METHODS: This cross-sectional study used data from 27 765 adults aged 45-85 years from the first follow-up wave (2015-2018) of the Canadian Longitudinal Study on Aging (CLSA). Four categories were generated to assess co-occurring SROH and multimorbidity: (i) good SROH, no multimorbidity; (ii) poor SROH, no multimorbidity; (iii) good SROH, multimorbidity and (iv) poor SROH and multimorbidity. Age-and sex-stratified multinomial logistic regressions were used to examine associations of ACEs (e.g. childhood maltreatment, neglect, parental death, serious illness or separation) with co-occurring poor SROH and multimorbidity, adjusted for the confounders race/ethnicity, income, level of education, smoking status and alcohol consumption. RESULTS: Over a third of participants reported having multimorbidity (35.3%), 10.4% reported poor SROH, and almost 30% of participants had experienced at least one ACE. There was a gradient in the association between higher ACEs and each of the health outcome categories, with the greater odds being for the co-occurrence of poor SROH and multimorbidity (OR = 1.37, 95% CI: 1.30, 1.44). The associations between ACEs and adverse health outcomes in later life were significant across age groups and sexes, with middle-aged females demonstrating the strongest associations. CONCLUSIONS: ACEs are linked to an increased non-communicable chronic disease burden and poor oral health among middle-aged and older Canadians, highlighting the importance of prevention in early life and the focus on psychosocial factors over the life course for healthy aging.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".