Emergency department (ED) crowding is a significant problem in the United States. The number of ED visits rose from 89.8 million in 1992¹ to 115.3 million in 2005, with over 85% of ED visits occurring in nonrural, metropolitan area EDs.² A national survey in 2002 showed that 62% of all surveyed hospitals reported operating at or beyond their designed capacity. Nearly one-third of all hospitals experienced periods of “ED diversion,” that is, times when their EDs could not accept all or specific types of patients by ambulance, especially in urban areas.^3,4 Data from the National Hospital Ambulatory Medical Care Survey² projected that over half a million ambulances were diverted to alternate facilities during 2003, representing approximately 1 ambulance diverted every minute of every day.

Background:Depression remains a major public health problem that is most often evaluated and treated in primary care settings. The objective of this study was to examine the prevalence, treatment, and control of depressive symptoms in a national data sample using a common primary care screening tool for depression. Methods:We analyzed a sample of adults (n = 4836) from 2005 to 2008 National Health and Nutrition Examination Survey data. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9) to determine the overall prevalence, rates of treatment, and antidepressant control of mild, moderate, moderately severe, and severe depressive symptoms. Results:Of the sample, 20.1% reported significant depressive symptoms (PHQ-9) score, ≥5), the majority of whom had mild depressive symptoms (PHQ-9) score, 5–9). Even among individuals with severe depressive symptoms, a large percentage (36.9%) received no treatment from a mental health professional or with antidepressant medication. Of those taking antidepressants, 26.4% reported mild depressive symptoms and 18.8% had moderate, moderately severe, or severe depressive symptoms. Conclusions:Despite greater awareness and treatment of depression in primary care settings, the prevalence of depressive symptoms remains high, treatment levels remain low, and control of depressive symptoms are suboptimal. Primary care providers need to continue to focus their efforts on diagnosing and effectively treating this important disease.

Objectives. We investigated whether race differences in weight gain over 34 years were because of socioeconomic position (SEP) and psychosocial and behavioral factors (physical activity, cigarette smoking, alcohol consumption, depression, marital status, number of children). We used a life-course approach to SEP with 4 measures of SEP (childhood SEP, education, occupation, income) and a cumulative measure of SEP. Methods. We used mixed models and data collected from the Alameda County Study to examine the association between race and weight change slopes and baseline weight in men (n=1186) and women (n=1375) aged 17 to 40 years at baseline (in 1965). Results. All subjects gained weight over time. African American women weighed 4.96 kg (P < .001) more at baseline and gained 0.10 kg/year (P = .043) more weight than White women. Black men weighed 2.41 kg (P= .006) more at baseline but did not gain more weight than White men. The association of race with weight gain in women was largely because of cumulative SEP score. Conclusions. Interventions to prevent overweight and obesity should begin early in life and target the socioeconomically disadvantaged.

ABSTRACT:  Context: Community health centers (CHCs) provide essential access to a primary care medical home for the uninsured, especially in rural communities with no other primary care safety net. CHCs could potentially reduce uninsured emergency department (ED) visits in rural communities. Purpose: We compared uninsured ED visit rates between rural counties in Georgia that have a CHC clinic site and counties without a CHC presence. Methods: We analyzed data from 100% of ED visits occurring in 117 rural (non‐metropolitan statistical area [MSA]) counties in Georgia from 2003 to 2005. The counties were classified as having a CHC presence if a federally funded (Section 330) CHC had a primary care delivery site in that county throughout the study period. The main outcome measure was uninsured ED visit rates among the uninsured (all‐cause ED visits and visits for ambulatory care sensitive conditions). Poisson regression models were used to examine the relationship between ED rates and the presence of a CHC. To ensure that the effects were unique to the uninsured population, we ran similar analyses on insured ED visits. Findings: Counties without a CHC primary care clinic site had 33% higher rates of uninsured all‐cause ED visits per 10,000 uninsured population compared with non‐CHC counties (rate ratio [RR] 1.33, 95% confidence interval [CI] 1.11‐1.59). Higher ED visit rates remained significant (RR 1.21, 95% CI 1.02‐1.42) after adjustment for percentage of population below poverty level, percentage of black population, and number of hospitals. Uninsured ED visit rates were also higher for various categories of diagnoses, but remained statistically significant on multivariate analysis only for ambulatory care sensitive conditions (adjusted RR = 1.22, 95% CI 1.01‐1.47). No such relationship was found for ED visit rates of insured patients (RR 1.06, 95% CI 0.92‐1.22). Conclusions: The absence of a CHC is associated with a substantial excess in uninsured ED visits in rural counties, an excess not seen for ED visit rates among the insured.

Objectives. We sought to describe Black–White differences in HIV disease mortality before and after the introduction of highly active antiretroviral treatment (HAART). Methods. Black–White mortality from HIV is described for the nation as a whole. We performed regression analyses to predict county-level mortality for Black men aged 25–84 years and the corresponding Black:White male mortality ratios (disparities) in 140 counties with reliable Black mortality for 1999–2002. Results. National Black–White disparities widened significantly after the introduction of HAART, especially among women and the elderly. In county regression analyses, contextual socioeconomic status (SES) was not a significant predictor of Black:White mortality rate ratio after we controlled for percentage of the population who were Black and percentage of the population who were Hispanic, and neither contextual SES nor race/ethnicity were significant predictors after we controlled for pre-HAART mortality. Contextual SES, race, and pre-HAART mortality were all significant and independent predictors of mortality among Black men. Conclusions. Although nearly all segments of the Black population experienced widened post-HAART disparities, disparities were not inevitable and tended to reflect pre-HAART levels. Public health policymakers should consider the hypothesis of unequal diffusion of the HAART innovation, with place effects rendering some communities more vulnerable than others to this potential problem.