An Epidemiologic Study of Psychotropic Medication and Obesity-Related Chronic Illnesses in Older Psychiatric Patients
Bibliographic record
Abstract
OBJECTIVE: Adverse effects from medication vary with age. Weight gain with several psychotropics is well known in adults but less information is available related to extent and complications of psychotropic-induced weight gain in older psychiatric patients. We determined the relative incidence of 2 obesity-related conditions (diabetes and hypertension) in older psychiatric patients receiving antipsychotics, antidepressants, and mood stabilizers. METHOD: A population-based case-control study of all psychiatric patients aged 67 years or older in contact with either specialist services or primary care using administrative data from Nova Scotia. RESULTS: We identified incident cases of diabetes (n = 608) and of hypertension (n = 1056), as well as an equal number of control subjects for each condition. Amitryptiline, selective serotonin reuptake inhibitors (SSRIs), and olanzapine were associated with an increased risk of presenting with hypertension 6 months after initial prescription. By contrast, conventional antipsychotics were associated with a reduced incidence of hypertension. Olanzapine was also significantly associated with diabetes after 6 months (OR adj = 2.58, 95% CI 1.12 to 5.92). The findings for SSRIs and olanzapine remained significant after adjusting for potential confounders such as sociodemographic characteristics, schizophrenia, beta blockers, thiazide diuretics, and corticosteroids. CONCLUSIONS: Our results suggest that the association of psychotropics and 2 obesity-related conditions, hypertension and diabetes, applies to older psychiatric patients as well as younger populations. Within drug classes, there are drugs that have a greater association than others, and this may be a factor when choosing a specific agent.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".