Comorbidity and Associated Severity of Borderline Personality Disorder and Physical Health Conditions in a Nationally Representative Sample
Bibliographic record
Abstract
Objective: To investigate the comorbidity and severity of borderline personality disorder and physical health conditions in a nationally representative sample. Despite the recent trend of examining the relationship between physical and mental health, there has been limited research examining the association of physical health conditions and personality disorders, in particular, borderline personality disorder. Methods: The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Wave 2 (n = 34,653; cumulative response rate, 70.2%; age, ≥20 years) was used in the current study. The Alcohol Use Disorder and Associated Disabilities Interview Schedule-Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition was used to assess mental disorders, and self-reports were used to assess physical health conditions. Multiple logistic regression models examined the comorbidity of physical health conditions with borderline personality disorder and associated suicide attempts. Results: After adjusting for sociodemographic variables, common Axis I mental disorders, and Axis II personality disorders, the presence of borderline personality disorder was significantly associated with arteriosclerosis or hypertension, hepatic disease, cardiovascular disease, gastrointestinal disease, arthritis, venereal disease, and “any assessed medical condition” (adjusted odds ratios, range 1.46–2.80). In the most stringent adjusted model, diabetes, stroke, and obesity were not associated with borderline personality disorder. Furthermore, a greater likelihood of suicide attempts was associated with cardiovascular disease, venereal disease, and “any assessed medical condition” with comorbid borderline personality disorder than borderline personality disorder alone. Conclusion: Careful screening and treatment of physical health conditions among people with borderline personality disorder are warranted. BPD = borderline personality disorder; DSM-IV = Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; NESARC = National Epidemiological Survey on Alcohol and Related Conditions; AUDADIS-IV = Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV Version; BMI = body mass index; HRQOL = health-related quality of life; MCS = mental health-related quality of life component score; PCS = physical health-related quality of life component score.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".