The Widening Health Care Gap Between High- and Low-Wage Workers

Compares the changes in insurance status, out-of-pocket costs, access to care, use of prescription drugs, and health-related outcomes of low-wage workers and high-wage workers between 1996 and 2003. Discusses the implications of the growing disparities

Who Pays for Health Care When Workers Are Uninsured?

Quantifies the costs to the public, in taxpayer bills to fund public insurance or uncompensated care programs, of employers not insuring workers. Compares public costs for uninsured employees of small, multi-location, and large firms and their families

Socioeconomic status as an independent predictor of physiological biomarkers of cardiovascular disease: Evidence from NHANES

Background C-reactive protein, homocysteine, cholesterol, and fibrinogen are known to vary by socioeconomic status (SES). Using a nationally representative study, we examined whether these factors vary independently of all other known risk factors, such as diet, exercise, and genetic predisposition. Methods We analyzed the 1999–2002 National Health Examination and Nutrition Survey using logistic regression models. Results We found that high-density lipoprotein cholesterol blood levels increase with income and educational attainment after controlling all known risk factors for elevated cholesterol (e.g., diet, exercise, and family history). Blood levels of C-reactive protein are inversely associated with income and education. Homocysteine blood levels are inversely associated with income even after controlling for blood folate level. A non-significant inverse relationship between homocysteine levels and educational attainment was also observed. Blood levels of low-density lipoprotein cholesterol and fibrinogen were not significantly associated with income or education. Conclusions Levels of “good” (high density lipoprotein) cholesterol increase with income and education even after controlling for factors known to place people at risk of high cholesterol. Stress differences by social class may play a role

Rite of Passage? Why Young Adults Become Uninsured and How New Policies Can Help, 2008 Update

Assesses the increase in young adults without health insurance -- their demographics and income levels, causes and implications, and federal and state actions taken -- and suggests targeted policy options to cover students and recent graduates

Rite of Passage? Why Young Adults Become Uninsured and How New Policies Can Help

Assesses the scope of the health insurance problem facing young adults, its causes and implications, and offers policy changes that could help them stay insured as they make the transition to independent living

Rite of Passage? Why Young Adults Become Uninsured and How New Policies Can Help, 2009 Update

Provides an annual assessment of the uninsurance of 19- to 29-year-olds and their demographics, incomes, and health status. Outlines federal and state actions to expand access to coverage and suggests policy options to address the impact of the recession

Addition of 25-hydroxyvitamin D levels to the Deyo-Charlson Comorbidity Index improves 90-day mortality prediction in critically ill patients

Background: The Deyo-Charlson Comorbidity Index (DCCI) has low predictive value in the intensive care unit (ICU). Our goal was to determine whether addition of 25-hydroxyvitamin D (25OHD) levels to the DCCI improved 90-day mortality prediction in critically ill patients. Methods: Plasma 25OHD levels, DCCI, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were assessed within 24 h of admission in 310 ICU patients. Receiver operating characteristic curves of the prediction scores, without and with the addition of 25OHD levels, for 90-day mortality were constructed and the areas under the curve (AUC) were compared for equality. Results: Mean (standard deviation) plasma 25OHD levels, DCCI, and APACHE II score were 19 (SD 8) ng/mL, 4 (SD 3), and 17 (SD 9), respectively. Overall 90-day mortality was 19 %. AUC for DCCI vs. DCCI + 25OHD was 0.68 (95 % CI 0.58–0.77) vs. 0.75 (95 % CI 0.67–0.83); p < 0.001. AUC for APACHE II vs. APACHE II + 25OHD was 0.81 (95 % CI 0.73–0.88) vs. 0.82 (95 % CI 0.75–0.89); p < 0.001. There was a significant difference between the AUC for DCCI + 25OHD and APACHE II + 25OHD (p = 0.04) but not between the AUC for DCCI + 25OHD and APACHE II (p = 0.12). Conclusions: In our cohort of ICU patients, the addition of 25OHD levels to the DCCI improved 90-day mortality prediction compared to the DCCI alone. Moreover, the predictive capability of DCCI + 25OHD was comparable to that of APACHE II. Future prospective studies are needed to validate our findings and to determine whether the use of DCCI + 25OHD can influence clinical decision-making