Later sleep timing was associated with higher estimated insulin resistance across all groups. Some associations between sleep timing and metabolic measures may be age-dependent.

Individuals with favorable levels of all readily measured major CVD risk factors (low CV risk) during middle age incur lower cardiovascular morbidity and mortality, lower all-cause mortality, and lower Medicare costs at older ages compared to adults with one or more unfavorable CVD risk factors. Studies on predictors of low CV risk in Hispanics/Latinos have focused solely on Mexican-Americans. The objective of this study was to use data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL; enrolled 2008 to 2011) to assess relationships of nativity and length of residence in the US, a commonly used proxy for acculturation, with low CV risk (not currently smoking; no diabetes; untreated total cholesterol <200mg/dL; untreated blood pressure <120/<80; body mass index <25 kg/m2; and no major ECG abnormalities) in 15,047 Central American, South American, Cuban, Dominican, Mexican, Puerto Rican men and women, and Hispanic/Latino men and women identifying as other or >1 heritage. We also tested whether associations varied by Hispanic/Latino background. Women living in the US<10 years were 1.96 (95% confidence interval: 1.37, 2.80) times more likely to be low CV risk than US-born women after adjusting for sociodemographic characteristics, diet, physical activity, and self-reported experiences of ethnic discrimination. Findings varied in men by Hispanic/Latino background, but length of residence was largely unrelated to low CV risk. These findings highlight the role acculturative processes play in shaping cardiovascular health in Hispanics/Latinos.

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OBJECTIVEType 2 diabetes mellitus (DM) has been associated with lung dysfunction, but this association has not been explored in Hispanics/Latinos. The relation between diabetic nephropathy and lung function and symptoms has not been explored.RESEARCH DESIGN AND METHODSThe Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a large, multicenter, observational study, recruited 16,415 participants aged 18–74 years (14,455 with complete data on variables of interest), between 2008 and 2011 from four U.S. communities through a two-stage area household probability design. Baseline measurements were used for analyses. Forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and dyspnea score were compared between individuals with and without DM, overall, and stratified by albuminuria. The analyses were performed separately for those with and without preexisting lung disease (chronic bronchitis, emphysema, asthma). Linear regression with sampling weights was used for all analyses.RESULTSAmong Hispanics/Latinos without lung disease, those with DM had lower mean FEV1 and FVC values and a higher mean dyspnea score than those without DM (mean [95% CI] FEV1 3.00 [2.96–3.04] vs. 3.10 [3.09–3.11] L, P < 0.01; FVC 3.62 [3.59–3.66] vs. 3.81 [3.79–3.83] L, P < 0.001; dyspnea score 0.60 [0.49–0.71] vs. 0.41 [0.34–0.49], P < 0.001). Hispanics/Latinos with DM and macroalbuminuria showed 10% lower FVC (P < 0.001), 6% lower FEV1 (P < 0.001), and 2.5-fold higher dyspnea score (P = 0.04) than those without DM and with normoalbuminuria. Similar findings but with higher impairment in FVC were found in Hispanics/Latinos with lung disease.CONCLUSIONSHispanics/Latinos with DM have functional and symptomatic pulmonary impairment that mirror kidney microangiopathy. The progression of pulmonary impairment in adults with DM needs to be investigated further.

Genome-wide detection of quantitative trait loci (QTL) hotspots underlying variation in many molecular and phenotypic traits has been a key step in various biological studies since the QTL hotspots are highly informative and can be linked to the genes for the quantitative traits. Several statistical methods have been proposed to detect QTL hotspots. These hotspot detection methods rely heavily on permutation tests performed on summarized QTL data or individual-level data (with genotypes and phenotypes) from the genetical genomics experiments. In this article, we propose a statistical procedure for QTL hotspot detection by using the summarized QTL (interval) data collected in public web-accessible databases. First, a simple statistical method based on the uniform distribution is derived to convert the QTL interval data into the expected QTL frequency (EQF) matrix. And then, to account for the correlation structure among traits, the QTL for correlated traits are grouped together into the same categories to form a reduced EQF matrix. Furthermore, a permutation algorithm on the EQF elements or on the QTL intervals is developed to compute a sliding scale of EQF thresholds, ranging from strict to liberal, for assessing the significance of QTL hotspots. With grouping, much stricter thresholds can be obtained to avoid the detection of spurious hotspots. Real example analysis and simulation study are carried out to illustrate our procedure, evaluate the performances and compare with other methods. It shows that our procedure can control the genome-wide error rates at the target levels, provide appropriate thresholds for correlated data and is comparable to the methods using individual-level data in hotspot detection. Depending on the thresholds used, more than 100 hotspots are detected in GRAMENE rice database. We also perform a genome-wide comparative analysis of the detected hotspots and the known genes collected in the Rice Q-TARO database. The comparative analysis reveals that the hotspots and genes are conformable in the sense that they co-localize closely and are functionally related to relevant traits. Our statistical procedure can provide a framework for exploring the networks among QTL hotspots, genes and quantitative traits in biological studies. The R codes that produce both numerical and graphical outputs of QTL hotspot detection in the genome are available on the worldwide web http://www.stat.sinica.edu.tw/chkao/ .