Table 3.
Adjusted OR |
95% CI | |
---|---|---|
Non-employment in Adults | ||
| ||
Race | ||
Asian vs. White | 2.67 | [1.18,6.04] |
Other vs. White | 1.26 | [0.42,3.78] |
| ||
Chelation Status: DFO or L1 | ||
Not Regular vs. Regular | 6.67 | [1.96, 25.0] |
| ||
Liver Failure | ||
Yes vs. No | 7.86 | [2.14,28.8] |
| ||
HIV | ||
Positive vs. Negative | 9.45 | [1.61, 55.5] |
| ||
Education in Adults | ||
| ||
Age (in 10 year increments) | 1.61 | [1.10,2.35] |
| ||
Gender | ||
Female vs.Male | 2.38 | [1.37,4.17] |
| ||
Chelation Status: DFO or L1 | ||
Regular vs. Not regular | 3.87 | [1.36, 11.0] |
| ||
Most recent serum ferritin Level | ||
>= 2500 vs. < 2500 | 0.71 | [0.40, 1.27] |
Possible predictors were age, gender, race/ethnicity, nationality, transfusion and chelation status, serum ferritin, and clinical complications(heart disease, liver failure or cirrhosis, lung disease, pulmonary hypertension, arthralgia or arthritis, HIV, osteoporosis/fracture, hypogonadism, thyroid disease, parathyroid disease, diabetes, Hep C ,stature). Predictors found significant in univariate analyses were entered into multivariatemodels. A logistic regression model was used for employment and a proportional odds model for education. OR = odds ratio. CI = confidence interval. The OR models the odds of non-employment (vs. employment) or higher education (post-college vs. college vs. high school vs. < high school). Significance at level 0.05 is indicated in bold type.