Prevalence and risk factors for intestinal parasitic infections in pregnant women residing in three districts of Bogotá, Colombia
Bibliographic record
Abstract
BACKGROUND: Intestinal parasitic infections (IPI) lead to significant morbidity and mortality in pediatric and adult populations worldwide. Intestinal parasitism during pregnancy is of interest as it may affect the health of pregnant women and their offspring. This study determined the prevalence of IPI in pregnant women living in substandard conditions in three urban districts of Bogotá, Colombia. Associations between prevalence and sociodemographic factors, housing, and living conditions were also evaluated. METHODS: In a cross-sectional and community-based study, pregnant women were recruited from three districts of Bogotá. A total of 550 participants answered a questionnaire; 331 of these also provided stool samples, with 233 providing one and 98 providing two stool samples. Questionnaire responses were associated with the presence of intestinal parasites, which was determined using a standard combined microscopy technique including direct wet mount and formol-ether concentration. Results were verified by supplementary examination of 48 stool samples by quantitative polymerase chain reaction (qPCR). RESULTS: Among pregnant women who lived in selected poor residential areas in Bogotá, the overall prevalence of intestinal parasitism was 41% with 9% polyparasitism. Pathogenic parasites were present in 1.2% of the 331 participants including Giardia lamblia and Ascaris lumbricoides. Higher prevalence was found for parasites with debated pathogenicity, including Blastocystis hominis (25%), Endolimax nana (15%), Entamoeba coli (8%), and Iodamoeba butschlii (2%). Entamoeba histolytica/dispar complex was also detected (1.5%). When comparing a subset of stool samples using the combined microscopy technique and qPCR, the latter detected a higher 58.3% overall IPI prevalence. Higher prevalence of infections by any intestinal parasite was found in participants who had never been dewormed (p = 0.01). Higher but not statistically significant associations were found between any parasite and women living with a partner, and intestinal polyparasitism and being from a minority group and not having a water sink. CONCLUSIONS: This first study of the prevalence of intestinal parasitism in Bogotá focused on pregnant women living in poverty, found a high prevalence of intestinal parasites of debated pathogenicity, and confirmed a low prevalence of pathogenic intestinal parasites. These results highlight the need for educational interventions to disrupt transmission routes for prevalent parasites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".