Single slice vs. volumetric MR assessment of visceral adipose tissue: reliability and validity among the overweight and obese.

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Visceral adipose tissue (VAT) is associated with abnormal cardiovascular and metabolic profiles. Total VAT volume of the abdominal compartment by magnetic resonance imaging (MRI) is the gold-standard measurement for VAT but is costly and time consuming. Prior studies suggest VAT area on a single slice MR image may serve as a surrogate for total VAT volume but it is unknown if this relationship is maintained in overweight and obese men and women. Untreated sleep apnea subjects enrolled into the Icelandic Sleep Apnea Cohort (ISAC) underwent abdominal MRI. VAT area and subcutaneous adipose tissue (SAT) area at the L2-L3 and L4-L5 interspaces and total VAT and SAT volumes were determined by manual examination using image analysis software; 539 men and 129 women with mean ages of 54.1 and 58.8 years and mean BMI of 32.2 kg/m(2) and 33.7 kg/m(2), respectively, were studied. Mean total VAT volume was 40% smaller and mean total SAT was 25% larger among females compared with males. The correlation with VAT volume was significantly larger for L2-L3 VAT area (r = 0.96) compared to L4-L5 VAT area (r = 0.83). The difference in correlation coefficients was statistically significant (nonparametric bootstrap P < 0.001 with 95% confidence interval (CI) for the difference from 0.11 to 0.15. VAT area at L2-L3 was also significantly better correlated with VAT volume than traditional anthropometric variables. Linear regression analyses demonstrated that L2-L3 area alone was sufficient for predicting total VAT volume and that the nature of the linear association was maintained across all levels of obesity and in both genders.NIH HL070267 HL09430

"Sleep disparity" in the population: poor sleep quality is strongly associated with poverty and ethnicity

<p>Abstract</p> <p>Background</p> <p>Little is known about the social determinants of sleep attainment. This study examines the relationship of race/ethnicity, socio-economic status (SES) and other factors upon sleep quality.</p> <p>Methods</p> <p>A cross-sectional survey of 9,714 randomly selected subjects was used to explore sleep quality obtained by self-report, in relation to socioeconomic factors including poverty, employment status, and education level. The primary outcome was poor sleep quality. Data were collected by the Philadelphia Health Management Corporation.</p> <p>Results</p> <p>Significant differences were observed in the outcome for race/ethnicity (African-American and Latino versus White: unadjusted OR = 1.59, 95% CI 1.24-2.05 and OR = 1.65, 95% CI 1.37-1.98, respectively) and income (below poverty threshold, unadjusted OR = 2.84, 95%CI 2.41-3.35). In multivariable modeling, health indicators significantly influenced sleep quality most prominently in poor individuals. After adjusting for socioeconomic factors (education, employment) and health indicators, the association of income and poor sleep quality diminished, but still persisted in poor Whites while it was no longer significant in poor African-Americans (adjusted OR = 1.95, 95% CI 1.47-2.58 versus OR = 1.16, 95% CI 0.87-1.54, respectively). Post-college education (adjusted OR = 0.47, 95% CI 0.31-0.71) protected against poor sleep.</p> <p>Conclusions</p> <p>A "sleep disparity" exists in the study population: poor sleep quality is strongly associated with poverty and race. Factors such as employment, education and health status, amongst others, significantly mediated this effect only in poor subjects, suggesting a differential vulnerability to these factors in poor relative to non-poor individuals in the context of sleep quality. Consideration of this could help optimize targeted interventions in certain groups and subsequently reduce the adverse societal effects of poor sleep.</p

Daytime sleepiness and napping in nursing-home eligible community dwelling older adults : A mixed methods study

Objectives: To describe perceptions and beliefs about daytime sleepiness and napping along with subjective and objective daytime sleep characteristics in nursing-home eligible community dwelling older adults. Methods: A mixed methods study; we conducted semi-structured interviews and measured sleep variables via Actigraphy, sleep diary, and Epworth Sleepiness Scale (ESS). Napping was defined as >10 minutes; anything less was considered dozing. Results: Final sample (n = 40) was primarily female (85%), Black (100%), with a mean age of 72 ± 9.5 years. Few (25%) reported daytime sleepiness (ESS >10). However, average duration of napping per day was 33.1 ± 11.5 minutes with a nap frequency of 2.5 ± 1.5 naps. Conclusion: Our sample napped frequently throughout the day, yet the majority reported no daytime sleepiness. These older adults did not always recognize napping or how much they napped

Afternoon napping and cognition in chinese older adults: Findings from the China Health and Retirement Longitudinal Study Baseline Assessment

Objectives: To examine the cross-sectional associations between self-reported postlunch napping and structured cognitive assessments in Chinese older adults. Design: Cross-sectional cohort study. Setting: China. Participants: Individuals aged 65 and older from the baseline national wave of the China Health and Retirement Longitudinal Study (CHARLS) (N = 2,974). Measurements: Interview-based cognitive assessments of orientation and attention, episodic memory, visuospatial abilities, and a combined global cognition score incorporating these assessments. Other self-reported or interview-based assessments included postlunch napping duration, nighttime sleep duration, demographic characteristics, health habits, comorbidities, functional status and social activities. According to reported napping duration, older adults were categorized as non-nappers (0 minutes), short nappers ( 90 minutes). Results: Postlunch napping was reporting in 57.7% of participants for a mean of 63 minutes. Cognitive function was significantly associated with napping (P < .001). Between-group comparisons showed that moderate nappers had better overall cognition than nonnappers (P < .001) or extended nappers (P = .01). Nonnappers also had significantly poorer cognition than short nappers (P = .03). In multiple regression analysis, moderate napping was significantly associated with better cognition than non- (P = .004), short (P= .04), and extended napping (P = .002), after controlling for demographic characteristics, body mass index, depression, instrumental activities of daily living, social activities, and nighttime sleep duration. Conclusion: A cross-sectional association was found between moderate postlunch napping and better cognition in Chinese older adults. The cross-sectional design and self-reported measures of sleep limited the findings. Longitudinal studies with objective napping measures are needed to further test this hypothesis