A national study of socioeconomic status and tuberculosis rates by country of birth, United States, 1996–2005
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) in developed countries has historically been associated with poverty and low socioeconomic status (SES). In the past quarter century, TB in the United States has changed from primarily a disease of native-born to primarily a disease of foreign-born persons, who accounted for more than 60% of newly-diagnosed TB cases in 2010. The purpose of this study was to assess the association of SES with rates of TB in U.S.-born and foreign-born persons in the United States, overall and for the five most common foreign countries of origin. METHODS: National TB surveillance data for 1996-2005 was linked with ZIP Code-level measures of SES (crowding, unemployment, education, and income) from U.S. Census 2000. ZIP Codes were grouped into quartiles from low SES to high SES and TB rates were calculated for foreign-born and U.S.-born populations in each quartile. RESULTS: TB rates were highest in the quartiles with low SES for both U.S.-born and foreign-born populations. However, while TB rates increased five-fold or more from the two highest to the two lowest SES quartiles among the U.S.-born, they increased only by a factor of 1.3 among the foreign-born. CONCLUSIONS: Low SES is only weakly associated with TB among foreign-born persons in the United States. The traditional associations of TB with poverty are not sufficient to explain the epidemiology of TB among foreign-born persons in this country and perhaps in other developed countries. TB outreach and research efforts that focus only on low SES will miss an important segment of the foreign-born population.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".