Cross‐sectional analysis of role of socioeconomic status in the association between depression and periodontitis
Bibliographic record
Abstract
BACKGROUND: Numerous studies have reported an association between depression and periodontitis, though results are inconsistent and highly heterogeneous. The present study aimed to examine the potential confounding role of poor socioeconomic status (SES) in the association between depression and periodontitis by performing a secondary analysis of the National Health and Nutrition Examination Survey (NHANES) data. METHODS: Among participants of the 2009-2014 NHANES cycles, those who fulfilled sociodemographic (education level, household income, ethnicity, marital status), medical, and depression questionnaires, and underwent full-mouth periodontal examination were selected. Periodontitis (mild, moderate, and severe) was assessed based on the Centers for Disease Control and Prevention/American Academy of Periodontology (CDC/AAP) criteria. Depression was defined by a Patient Health Questionnaire (PHQ-9) total score ≥10. Weighted multivariable regressions for complex design models were used to assess the association between periodontitis and depression accounting for the role of SES. Adjusted odds ratio (OR) with 95% confidence intervals (CIs) were provided. RESULTS: Among 9537 participants [mean age: 51.9 years (SD: 14.1), 50.1% females], 4768 (41.2%) and 830 (7.3%) presented with periodontitis and depression, respectively. Depression was significantly associated with periodontitis (weighted OR [95% CI]: 1.26 [1.01-1.56]). However, this association was no longer significant when adjusting for SES indicators (0.94 [0.75-1.18]), especially poverty (91.4% of OR reduction when adjusting for poverty only). CONCLUSION: The association between depression and periodontitis may largely be explained by SES, which should thus be considered at both the population- and individual levels in preventive and management strategies. PLAIN LANGUAGE SUMMARY: Depression and periodontitis are two common health problems, and some studies suggest they might be linked. But could this connection actually be due to other factors, like low income or education levels? To find out, we analyzed data from a national US health survey involving over 9500 adults who answered questions about their mental health, income, education, and lifestyle, and who also underwent a full-mouth periodontal examination. We found that depression and periodontitis appeared to be connected at first glance. However, when we considered socioeconomic factors-especially low income-the link between the two disappeared. This suggests that financial challenges and limited access to resources might play a bigger role than previously thought. Our findings highlight the need for health professionals to look beyond individual conditions and consider a person's broader life circumstances when providing care. At a public health level, addressing social inequalities could help improve both mental and oral health outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".