Prevalence of cardiovascular risk factors among racial and ethnic minorities with schizophrenia spectrum and bipolar disorders: a critical literature review.

OBJECTIVE: People with serious mental illness (SMI) die at least 11 years earlier than the general U.S. population, on average, due largely to cardiovascular disease (CVD). Disparities in CVD morbidity and mortality also occur among some U.S. racial and ethnic minorities. The combined effect of race/ethnicity and SMI on CVD-related risk factors, however, remains unclear. To address this gap, we conducted a critical literature review of studies assessing the prevalence of CVD risk factors (overweight/obesity, diabetes mellitus, metabolic syndrome, hypercholesterolemia, hypertension, cigarette smoking, and physical inactivity) among U.S. racial/ethnic groups with schizophrenia-spectrum and bipolar disorders. METHODS AND RESULTS: We searched MEDLINE and PsycINFO for articles published between 1986 and 2013. The search ultimately yielded 40 articles. There was great variation in sampling, methodology, and study populations. Results were mixed, though there was some evidence for increased risk for obesity and diabetes mellitus among African Americans, and to a lesser degree for Hispanics, compared to non-Hispanic Whites. Sex emerged as an important possible effect modifier of risk, as women had higher CVD risk among all racial/ethnic subgroups where stratified analyses were reported. CONCLUSIONS: Compared to general population estimates, there was some evidence for an additive risk for CVD risk factors among racial/ethnic minorities with SMI. Future studies should include longitudinal assessment, stratification by sex, subgroup analyses to clarify the mechanisms leading to potentially elevated risk, and the evaluation of culturally appropriate interventions to eliminate the extra burden of disease in this population.

Adolescent crash rates and school start times in two central Virginia counties, 2009-2011: a follow-up study to a southeastern Virginia study, 2007-2008.

BACKGROUND AND OBJECTIVE: Early high school start times (EHSST) may lead to sleep loss in adolescents ("teens"), thus resulting in higher crash rates. (Vorona et al., 2011). In this study, we examined two other adjacent Virginia counties for the two years subsequent to the above-mentioned study. We again hypothesized that teens from jurisdictions with EHSST (versus later) experience higher crash rates. METHODS: Virginia Department of Motor Vehicles supplied de-identified aggregate data on weekday crashes and time-of-day for 16-18 year old (teen) and adult drivers for school years 2009-2010 and 2010-2011 in Henrico and Chesterfield Counties. Teen crash rates for counties with early versus later school start-times were compared using two-sample Z-tests and these compared to adult crash rates using pair-wise tests. RESULTS: Henrico teens manifested a statistically higher crash rate of 48.8/1000 licensed drivers versus Chesterfield's 37.9/1000 (p = 0.04) for 2009-2010. For 2010-2011, HC 16-17 year old teens demonstrated a statistically significant higher crash rate (53.2/1000 versus 42.0/1000), while for 16-18 teens a similar trend was found, albeit nonsignificant (p = 0.09). Crash peaks occurred 1 hour earlier in the morning and 2 hours earlier in the afternoon in Chesterfield, consistent with commute times. Post hoc analyses found significantly more run-off road crashes to the right (potentially sleep-related) in Chesterfield teens. Adult crash rates and traffic congestion did not differ between counties. CONCLUSIONS: Higher teen crash rates occurred in jurisdictions with EHSST, as in our prior study. This study contributes to and extends existing data on preventable teen crashes and high school start times.

Actigraphy: analyzing patient movement.

BACKGROUND: Actigraphic data during simulated participant movements were evaluated to differentiate among patient behavior states. METHODS: Arm and leg actigraphic data were collected on 30 volunteers who simulated 3 behavioral states (calm, restless, agitated) for 10 minutes; counts of observed participant movements (head, torso, extremities) were documented. RESULTS: The mean age of participants was 34.7 years, and 60% were female. Average movement was significantly different among the states (P < .0001; calm [mean = .48], restless [mean = 2.16], agitated [mean = 3.75]). Mean actigraphic measures were significantly different among states for both arm (P < .0001; calm [mean = 6.8], restless [mean = 28.5], agitated [mean = 52.6]) and leg (P < .0001; calm [mean = 3.5], restless [mean = 18.7], agitated [mean = 37.7]). CONCLUSION: Distinct levels of behavioral states were successfully simulated. Actigraphic data can provide an objective indicator of patient activity over a variety of behavioral states, and these data may offer a standard for comparison among these states.