Frailty prevalence by race and age group.

<p>Frailty prevalence by race and age group.</p

All-cause mortality hazard ratios and 95% confidence intervals by frailty status and demographics.

<p>All-cause mortality hazard ratios and 95% confidence intervals by frailty status and demographics.</p

Concurrent functional measures by frailty group.

<p>Concurrent functional measures by frailty group.</p

Overall survival by initial frailty group, stratified by age at enrollment.

<p>Overall survival by initial frailty group, stratified by age at enrollment.</p

Distribution of demographic variables and health measures by frailty status.

<p>Distribution of demographic variables and health measures by frailty status.</p

Study sample characteristics, NHANES 1999–2000 (N = 3,055).

<p>Study sample characteristics, NHANES 1999–2000 (N = 3,055).</p

Total, direct and indirect effects of Hp_s on iron status, 1-C metabolites and antioxidant status (N = 3,057): NHANES 1999–00.

<p>*p<0.05</p><p>**p<0.01</p><p>***p<0.001.</p><p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121390#pone.0121390.g001" target="_blank">Fig. 1</a> footnote for additional control of exogenous variables.</p><p>Total, direct and indirect effects of Hp_s on iron status, 1-C metabolites and antioxidant status (N = 3,057): NHANES 1999–00.</p

Data reduction and structural equations model.

<p>Data reduction and structural equations model.</p

Serum Nutritional Biomarkers and Their Associations with Sleep among US Adults in Recent National Surveys

<div><p>Background</p><p>The associations between nutritional biomarkers and measures of sleep quantity and quality remain unclear.</p><p>Methods</p><p>Cross-sectional data from the National Health and Nutrition Examination Surveys (NHANES) 2005–2006 were used. We selected 2,459 adults aged 20–85, with complete data on key variables. Five sleep measures were constructed as primary outcomes: (<b>A</b>) Sleep duration; (<b>B</b>) Sleep disorder; (<b>C</b>) Three factors obtained from factor analysis of 15 items and labeled as “Poor sleep-related daytime dysfunction” (<b>Factor 1</b>), “Sleepiness” (<b>Factor 2</b>) and “Sleep disturbance” (<b>Factor 3</b>). Main exposures were serum concentrations of key nutrients, namely retinol, retinyl esters, carotenoids (<i>α</i>-carotene, <i>β</i>-carotene, <i>β</i>-cryptoxanthin, lutein+zeaxanthin, lycopene), folate, vitamin B-12, total homocysteine (tHcy), vitamin C, 25-hydroxyvitamin D (25(OH)D) and vitamin E. Main analyses consisted of multiple linear, logistic and multinomial logit models.</p><p>Results</p><p>Among key findings, independent inverse associations were found between serum vitamin B-12 and sleep duration, 25(OH)D and sleepiness (as well as insomnia), and between folate and sleep disturbance. Serum total carotenoids concentration was linked to higher odds of short sleep duration (i.e. 5–6 h per night) compared to normal sleep duration (7–8 h per night).</p><p>Conclusions</p><p>A few of the selected serum nutritional biomarkers were associated with sleep quantity and quality. Longitudinal studies are needed to ascertain temporality and assess putative causal relationships.</p></div

Monetary Value of Diet Is Associated with Dietary Quality and Nutrient Adequacy among Urban Adults, Differentially by Sex, Race and Poverty Status

<div><p>Objective</p><p>The association between monetary value of the diet (MVD, $/day) with dietary quality was examined using a large sample of urban US adults, differentially by socio-demographic factors.</p><p>Methods</p><p>This was a cross-sectional study of 2,111 participants, aged 30–64y, using data from the Healthy Aging in Neighborhoods of Diversity across the Life Span Study. Dietary quality indices included Healthy Eating Index–2010 (HEI–2010) and Mean Adequacy Ratio (MAR), (two 24-hr recalls). A national food price database was used to estimate MVD. Multiple linear/logistic regression analyses were conducted stratifying separately by sex, race and poverty status.</p><p>Results</p><p>Women had significantly higher HEI-2010 scores than men (43.35 vs 41.57 out of 100, respectively), whereas MAR scores were higher for men (76.8 vs 69.9, out of 100), reflecting energy intake gender differentials. Importantly, a$3/day higher MVD (IQR: $3.70/d (Q1) to$6.62/d (Q4)) was associated with a 4.98±0.35 higher total HEI-2010 and a 3.88±0.37 higher MAR score, after energy-adjustment and control for key confounders. For HEI-2010 and MAR, stronger associations were observed among participants above poverty and among women, whilethe MVD vs. HEI-2010 association was additionally stronger among Whites. Sex and poverty status differentials were observed for many MAR and some HEI-2010 components.</p><p>Conclusions</p><p>Despite positive associations between measures of dietary quality and MVD, particularly above poverty and among women, approaching compliance with the Dietary Guidelines (80 or more for HEI-2010) requires a substantially higher MVD. Thus, nutrition education may further improve people’s decision-making regarding food venues and dietary choices.</p></div