Gender and Age Disparities in the Prevalence of <i>Chlamydia</i> Infection Among Sexually Active Adults in the United States
Bibliographic record
Abstract
BACKGROUND: Chlamydia trachomatis (CT) causes a costly and potentially recurrent bacterial infection that accounts for a considerable proportion of sexually transmitted infections (STIs) in the United States. Disparities by gender and age group in CT prevalence have been reported previously. The current study evaluates demographic, socioeconomic, and behavioral risk and protective factors that may account for gender/age disparities in CT infections among sexually active young adults in the United States. METHODS: Secondary analyses were performing using the 1999-2006 National Health and Nutrition Examination Survey (NHANES) data. RESULTS: A total sample of 5611 adults, 20-39 years of age, who participated in the 1999-2006 NHANES, reported lifetime sexual experience, and had valid laboratory-based CT status, was analyzed. CT prevalence did not differ significantly by gender and was estimated to be 1.6%. It was slightly higher for people <25 years vs. those ≥25 years of age; age disparities were reduced after controlling for demographic, socioeconomic, and behavioral characteristics. Among those <25 years, non-Hispanic blacks had a higher odds of CT infection compared with other groups. Among those ≥25 years of age, not having had unprotected sex in the past month reduced the odds for CT infection, whereas non-Hispanic black race and never married status increased the odds for CT infection. CONCLUSIONS: Among sexually active adults, no gender disparities were observed in CT prevalence. Age group disparities were partly explained by personal characteristics associated with risk of STIs.
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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 | 0.001 |
| 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) | 0.002 | 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".