Depression in Teenager Pregnant Women in a Public Hospital in a Northern Mexican City: Prevalence and Correlates
Bibliographic record
Abstract
BACKGROUND: Very little is known about prenatal depression in teenagers in Mexico. We determined the prevalence and correlates of prenatal depression in teenager women attending a public hospital in Durango City, Mexico. METHODS: We performed a cross-sectional study to assess depression in 181 teenager pregnant women who attended a public hospital for prenatal care. We used a validated Mexican version of the Edinburg postnatal depression scale (EPDS) to screen depression. Women with EPDS scores suggestive of depression were further examined to confirm depression by a psychiatric evaluation using the DSM-IV criteria. Bivariate and multivariate analyses were used to evaluate the prevalence association with socio-demographic, clinical and psychosocial characteristics of the pregnant women. RESULTS: Of the 181 teenager pregnant women studied, 61 (33.7%) had EPDS equal to or higher than 8 (range 8 - 23), and 37 of them were confirmed to have prenatal depression by the psychiatric evaluation. The general prevalence of prenatal depression in the teenager pregnant women studied was 20.4%. Of the 37 women with depression, 34 suffered from minor depression and three suffered from major depression. Thus, the prevalence of minor and major depression in the women studied was 18.8% and 1.7%, respectively. Multivariate analysis of the socio-demographic, clinical and psychosocial characteristics of the teenager pregnant women showed that prenatal depression was associated with a previous episode of depression during pregnancy (odds ratio (OR) = 6.12; 95% confidence interval (CI): 1.68 - 22.30; P = 0.006), and borderline associations with big fetal size (OR = 9.9; 95% CI: 0.94 - 104.24; P = 0.05) and family problems (OR = 3.83; 95% CI: 0.99 - 14.84; P = 0.05). CONCLUSIONS: Results demonstrate that prenatal depression is common in pregnant teenagers in Durango City, Mexico. The history of an episode of depression during pregnancy should alert physicians for further depression episodes during pregnancy in teenagers. Further research to elucidate the association of prenatal depression with size of the fetus and family problems in pregnant teenagers is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".