Gender Disparities in the Association of Depression Symptoms and Cardiovascular Disease in US Adult Population
Bibliographic record
Abstract
Context: Depression is a well-known independent risk factor for cardiovascular morbidity, mortality, and poor prognosis for a cardiac event, however, how gender effects this association is not understood. Objective: To identify the effect of gender in the association between depression and cardiovascular disease (CVD) status in the US adult population. Study Design and Analysis: Survey based, unadjusted and adjusted prevalence ratios (PR) were estimated using generalized linear model with Poisson family, and log link function using a cross-sectional survey dataset. Setting or Dataset: Secondary dataset from the National Health and Nutrition Examination Survey (NHANES) conducted during 2013-2018. Population Studied: Community-dwelling, non-institutionalized adults aged 20 years and older (N=14,767). Instruments: The Patient Health Questionnaire (PHQ-9), a nine-item depression screening instrument. This instrument incorporates DSM-IV depression diagnostic criteria, subjects answered each of the nine items scoring points ranging from 0 to 3 on each item. Outcome Measures: CVD event (congestive heart failure, coronary heart disease, angina/angina pectoris, heart attack, or stroke). Results: CVD events were positively associated with higher PHQ-9 scores in unadjusted (PR:1.61, p<0.001 and PR:2.01, p=0.001 for mild/moderate and severe group respectively) and adjusted analysis (PR:1.38, p= 0.002 and PR:1.61, p=0.024 for mild/moderate and severe group respectively). Females were 45% less likely to have a CVD event compared to males. However, more CVDs were reported in females with mild/moderate depression (PR:1.52, p:0.003) and with moderately severe/severe depression (PR:2.22, p=0.002) compared to no/little depression and in males. In a subgroup adjusted analysis, female sex and having depressive symptoms was associated with higher CVD events (PR:2.03, p<0.001 and PR:3.38, p<0.001 for mild/moderate and severe group respectively) as compared to males with depressive symptoms (PR:1.41, p<0.001 and PR:1.66, p<0.001 for mild/moderate and severe group respectively). Conclusion: Females with more severe depressive symptoms are more likely to experience CVD events compared to males. Results highlight the importance of looking at specific risk factors for CVD events, and having a higher suspicion in women should, be considered in primary care settings. Future studies are also needed on the characterization of possible pathophysiological mechanism of these outcomes.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".