Safety and efficacy of the peptide-based therapeutic vaccine for HIV-1, Vacc-4x: a phase 2 randomised, double-blind, placebo-controlled trial.

BACKGROUND: Present combination antiretroviral therapy (cART) alone does not cure HIV infection and requires lifelong drug treatment. The potential role of HIV therapeutic vaccines as part of an HIV cure is under consideration. Our aim was to assess the efficacy, safety, and immunogenicity of Vacc-4x, a peptide-based HIV-1 therapeutic vaccine targeting conserved domains on p24(Gag), in adults infected with HIV-1. METHODS: Between July, 2008, and June, 2010, we did a multinational double-blind, randomised, phase 2 study comparing Vacc-4x with placebo. Participants were adults infected with HIV-1 who were aged 18-55 years and virologically suppressed on cART (viral load <50 copies per mL) with CD4 cell counts of 400 × 10(6) cells per L or greater. The trial was done at 18 sites in Germany, Italy, Spain, the UK, and the USA. Participants were randomly assigned (2:1) to Vacc-4x or placebo. Group allocation was masked from participants and investigators. Four primary immunisations, weekly for 4 weeks, containing Vacc-4x (or placebo) were given intradermally after administration of adjuvant. Booster immunisations were given at weeks 16 and 18. At week 28, cART was interrupted for up to 24 weeks. The coprimary endpoints were cART resumption and changes in CD4 counts during treatment interruption. Analyses were by modified intention to treat: all participants who received one intervention. Furthermore, safety, viral load, and immunogenicity (as measured by ELISPOT and proliferation assays) were assessed. The 52 week follow-up period was completed in June, 2011. For the coprimary endpoints the proportion of participants who met the criteria for cART resumption was analysed with a logistic regression model with the treatment effect being assessed in a model including country as a covariate. This study is registered with ClinicalTrials.gov, number NCT00659789. FINDINGS: 174 individuals were screened; because of slow recruitment, enrolment stopped with 136 of a planned 345 participants and 93 were randomly assigned to receive Vacc-4x and 43 to receive placebo. There were no differences between the two groups for the primary efficacy endpoints in those participants who stopped cART at week 28. Of the participants who resumed cART, 30 (34%) were in the Vacc-4x group and 11 (29%) in the placebo group, and percentage changes in CD4 counts were not significant (mean treatment difference -5·71, 95% CI -13·01 to 1·59). However, a significant difference in viral load was noted for the Vacc-4x group both at week 48 (median 23 100 copies per mL Vacc-4x vs 71 800 copies per mL placebo; p=0·025) and week 52 (median 19 550 copies per mL vs 51 000 copies per mL; p=0·041). One serious adverse event, exacerbation of multiple sclerosis, was reported as possibly related to study treatment. Vacc-4x was immunogenic, inducing proliferative responses in both CD4 and CD8 T-cell populations. INTERPRETATION: The proportion of participants resuming cART before end of study and change in CD4 counts during the treatment interruption showed no benefit of vaccination. Vacc-4x was safe, well tolerated, immunogenic, seemed to contribute to a viral-load setpoint reduction after cART interruption, and might be worth consideration in future HIV-cure investigative strategies. FUNDING: Norwegian Research Council GLOBVAC Program and Bionor Pharma ASA.

Two Signatures For A New Blood-Based Test For Colorectal Cancer Screening

Background: Detection rates for adenoma and early colorectal cancer (CRC) are unsatisfactory due to low compliance towards invasive screening procedures such as colonoscopy. There is a large unmet screening need calling for an accurate, non-invasive and cost-effective test to screen for early neoplastic and pre-neoplastic lesions. Our goal is to identify effective biomarker combinations to develop a screening test aimed at detecting precancerous lesions and early CRC stages, based on a multigene assay performed on peripheral blood mononuclear cells (PBMC).Methods: A pilot study was conducted on 92 subjects. Colonoscopy revealed 21 CRC, 30 adenomas larger than 1 cm and 41 healthy controls. A panel of 103 biomarkers was selected by two approaches: a candidate gene approach based on literature review and whole transcriptome analysis of a subset of this cohort by Illumina TAG profiling. Blood samples were taken from each patient and PBMC purified. Total RNA was extracted and the 103 biomarkers were tested by multiplex RT-qPCR on the cohort. Different univariate and multivariate statistical methods were applied on the PCR data and 60 biomarkers, with significant p-value (< 0.01) for most of the methods, were selected.Results: The 60 biomarkers are involved in several different biological functions, such as cell adhesion, cell motility, cell signaling, cell proliferation, development and cancer. Two distinct molecular signatures derived from the biomarker combinations were established based on penalized logistic regression to separate patients without lesion from those with CRC or adenoma. These signatures were validated using bootstrapping method, leading to a separation of patients without lesion from those with CRC (Se 67%, Sp 93%, AUC 0.87) and from those with adenoma larger than 1cm (Se 63%, Sp 83%, AUC 0.77). In addition, the organ and disease specificity of these signatures was confirmed by means of patients with other cancer types and inflammatory bowel diseases.Conclusions: The two defined biomarker combinations effectively detect the presence of CRC and adenomas larger than 1 cm with high sensitivity and specificity. A prospective, multicentric, pivotal study is underway in order to validate these results in a larger cohort.

Contribution of multimorbidity to overall mortality in the population-based CoLaus study

Introduction : Multimorbidity (MM) is currently a major health concern for hospitalized patients but little is known about the relative importance of MM in the general population. Accordingly we assessed whether MM could be a good predictor of overall mortality. Method : Data from the population based CoLaus Study: 3239 participants (1731 women, mean age 50+/-9 years) followed for a median time of 5.4 years (range 0.4 to 8.5 years). MM was defined as presenting >=2 morbidities according to Barnett et al. (27 items, measured data). Survival analysis was conducted using Cox regression. Results : During follow-up, 53 (1.6%) participants died. Participants who died had a higher number of morbidities (2.4 +/- 1.6 vs. 1.9 +/- 1.5, p<0.05) and had a higher prevalence of MM (69.8% vs. 55.9%, p<0.05). On bivariate analysis, presence of MM (defined as a yes/no variable) was significantly related with overall mortality: relative risk (RR) of 1.84, 95% confidence interval [1.02; 3.31], p<0.05 (see figure), but this association became non-significant after adjusting for age, gender and smoking: RR=1.68 [0.93; 3.04], p=0.09. Similar results were obtained when using the number of morbidities: RR for an extra morbidity 1.22 [1.05; 1.44], p<0.02; after adjusting for age, gender and smoking, RR=1.16 [0.99; 1.37], p=0.07. Conclusion : During a short 5 year observation period, measured MM in the general population is associated with overall mortality. This association becomes borderline significant after multivariate adjustment. These observations will have to be confirmed during a longer follow-up period. This increased mortality in MM patients may require developing specific strategies of screening and prevention.

Epidemiology of congenital diaphragmatic hernia in Europe: a register-based study.

INTRODUCTION: Published prevalence rates of congenital diaphragmatic hernia (CDH) vary. This study aims to describe the epidemiology of CDH using data from high-quality, population-based registers belonging to the European Surveillance of Congenital Anomalies (EUROCAT). METHODS: Cases of CDH delivered between 1980 and 2009 notified to 31 EUROCAT registers formed the population-based case series. Prevalence over time was estimated using multilevel Poisson regression, and heterogeneity between registers was evaluated from the random component of the intercept. RESULTS: There were 3373 CDH cases reported among 12 155 491 registered births. Of 3131 singleton cases, 353 (10.4%) were associated with a chromosomal anomaly, genetic syndrome or microdeletion, 784 (28.2%) were associated with other major structural anomalies. The male to female ratio of CDH cases overall was 1:0.69. Total prevalence was 2.3 (95% CI 2.2 to 2.4) per 10 000 births and 1.6 (95% CI 1.6 to 1.7) for isolated CDH cases. There was a small but significant increase (relative risk (per year)=1.01, 95% credible interval 1.00-1.01; p=0.030) in the prevalence of total CDH over time but there was no significant increase for isolated cases (ie, CDH cases that did not occur with any other congenital anomaly). There was significant variation in total and isolated CDH prevalence between registers. The proportion of cases that survived to 1 week was 69.3% (1392 cases) for total CDH cases and 72.7% (1107) for isolated cases. CONCLUSIONS: This large population-based study found an increase in total CDH prevalence over time. CDH prevalence also varied significantly according to geographical location. No significant association was found with maternal age.

An integer-based score to predict functional outcome in acute ischemic stroke: The ASTRAL score.

OBJECTIVE: To develop and validate a simple, integer-based score to predict functional outcome in acute ischemic stroke (AIS) using variables readily available after emergency room admission. METHODS: Logistic regression was performed in the derivation cohort of previously independent patients with AIS (Acute Stroke Registry and Analysis of Lausanne [ASTRAL]) to identify predictors of unfavorable outcome (3-month modified Rankin Scale score >2). An integer-based point-scoring system for each covariate of the fitted multivariate model was generated by their β-coefficients; the overall score was calculated as the sum of the weighted scores. The model was validated internally using a 2-fold cross-validation technique and externally in 2 independent cohorts (Athens and Vienna Stroke Registries). RESULTS: Age (A), severity of stroke (S) measured by admission NIH Stroke Scale score, stroke onset to admission time (T), range of visual fields (R), acute glucose (A), and level of consciousness (L) were identified as independent predictors of unfavorable outcome in 1,645 patients in ASTRAL. Their β-coefficients were multiplied by 4 and rounded to the closest integer to generate the score. The area under the receiver operating characteristic curve (AUC) of the score in the ASTRAL cohort was 0.850. The score was well calibrated in the derivation (p = 0.43) and validation cohorts (0.22 [Athens, n = 1,659] and 0.49 [Vienna, n = 653]). AUCs were 0.937 (Athens), 0.771 (Vienna), and 0.902 (when pooled). An ASTRAL score of 31 indicates a 50% likelihood of unfavorable outcome. CONCLUSIONS: The ASTRAL score is a simple integer-based score to predict functional outcome using 6 readily available items at hospital admission. It performed well in double external validation and may be a useful tool for clinical practice and stroke research.

Hirschsprung's disease prevalence in Europe: A register based study.

BACKGROUND: Hirschsprung's disease is a congenital gut motility disorder, characterised by the absence of the enteric ganglion cells along the distal gut. The aim of this study was to describe the epidemiology of Hirschsprung's disease, including additional congenital anomalies, total prevalence, trends, and association with maternal age. METHODS: Cases of Hirschsprung's disease delivered during 1980 to 2009 notified to 31 European Surveillance of Congenital Anomaly registers formed the population-based case-series. Prevalence rates and 95% confidence intervals were calculated as the number of cases per 10,000 births. Multilevel Poisson regression was performed to investigate trends in prevalence, geographical variation and the association with maternal age. RESULTS: There were 1,322 cases of Hirschsprung's disease among 12,146,210 births. The total prevalence was 1.09 (95% confidence interval, 1.03-1.15) per 10,000 births and there was a small but significant increase in prevalence over time (relative risk = 1.01; 95% credible interval, 1.00-1.02; p = 0.004). There was evidence of geographical heterogeneity in prevalence (p < 0.001). Excluding 146 (11.0%) cases with chromosomal anomalies or genetic syndromes, there were 1,176 cases (prevalence = 0.97; 95% confidence interval, 0.91-1.03 per 10,000 births), of which 137 (11.6%) had major structural anomalies. There was no evidence of a significant increased risk of Hirschsprung's disease in cases born to women aged ≥35 years compared with those aged 25 to 29 (relative risk = 1.09; 95% credible interval, 0.91-1.31; p = 0.355). CONCLUSION: This large population-based study found evidence of a small increasing trend in Hirschsprung's disease and differences in prevalence by geographic location. There was also no evidence of an association with maternal age. Birth Defects Research (Part A), 100:695-702, 2014. © 2014 Wiley Periodicals, Inc.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Epidemiology of Masked and White-Coat Hypertension: The Family-Based SKIPOGH Study.

OBJECTIVE: We investigated factors associated with masked and white-coat hypertension in a Swiss population-based sample. METHODS: The Swiss Kidney Project on Genes in Hypertension is a family-based cross-sectional study. Office and 24-hour ambulatory blood pressure were measured using validated devices. Masked hypertension was defined as office blood pressure<140/90 mmHg and daytime ambulatory blood pressure≥135/85 mmHg. White-coat hypertension was defined as office blood pressure≥140/90 mmHg and daytime ambulatory blood pressure<135/85 mmHg. Mixed-effect logistic regression was used to examine the relationship of masked and white-coat hypertension with associated factors, while taking familial correlations into account. High-normal office blood pressure was defined as systolic/diastolic blood pressure within the 130-139/85-89 mmHg range. RESULTS: Among the 652 participants included in this analysis, 51% were female. Mean age (±SD) was 48 (±18) years. The proportion of participants with masked and white coat hypertension was respectively 15.8% and 2.6%. Masked hypertension was associated with age (odds ratio (OR) = 1.02, p = 0.012), high-normal office blood pressure (OR = 6.68, p<0.001), and obesity (OR = 3.63, p = 0.001). White-coat hypertension was significantly associated with age (OR = 1.07, p<0.001) but not with education, family history of hypertension, or physical activity. CONCLUSIONS: Our findings suggest that physicians should consider ambulatory blood pressure monitoring for older individuals with high-normal office blood pressure and/or who are obese.

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.

Association between Inflammatory and Obesity Markers in a Swiss Population-Based Sample (CoLaus Study).

Objective: To assess the associations between obesity markers (BMI, waist circumference and %body fat) and inflammatory markers (interleukin-1β (IL-1β); interleukin-6 (IL-6); tumor necrosis factor-α (TNF-α) and high-sensitivity C-reactive protein (hs-CRP)). Methods: Population sample of 2,884 men and 3,201 women aged 35-75 years. Associations were assessed using ridge regression adjusting for age, leisure-time physical activity, and smoking. Results: No differences were found in IL-1β levels between participants with increased obesity markers and healthy counterparts; multivariate regression showed %body fat to be negatively associated with IL-1β. Participants with high %body fat or abdominal obesity had higher IL-6 levels, but no independent association between IL-6 levels and obesity markers was found on multivariate regression. Participants with abdominal obesity had higher TNF-α levels, and positive associations were found between TNF-α levels and waist circumference in men and between TNF-α levels and BMI in women. Obese participants had higher hs-CRP levels, and these differences persisted after multivariate adjustment; similarly, positive associations were found between hs-CRP levels and all obesity markers studied. Conclusion: Obesity markers are differentially associated with cytokine levels. %Body fat is negatively associated with IL-1β; BMI (in women) and waist circumference (in men) are associated with TNF-α; all obesity markers are positively associated with hs-CRP. Copyright © 2012 S. Karger GmbH, Freiburg.

Reference values and factors associated with renal resistive index in a family-based population study.

Increased renal resistive index (RRI) has been recently associated with target organ damage and cardiovascular or renal outcomes in patients with hypertension and diabetes mellitus. However, reference values in the general population and information on familial aggregation are largely lacking. We determined the distribution of RRI, associated factors, and heritability in a population-based study. Families of European ancestry were randomly selected in 3 Swiss cities. Anthropometric parameters and cardiovascular risk factors were assessed. A renal Doppler ultrasound was performed, and RRI was measured in 3 segmental arteries of both kidneys. We used multilevel linear regression analysis to explore the factors associated with RRI, adjusting for center and family relationships. Sex-specific reference values for RRI were generated according to age. Heritability was estimated by variance components using the ASSOC program (SAGE software). Four hundred women (mean age±SD, 44.9±16.7 years) and 326 men (42.1±16.8 years) with normal renal ultrasound had mean RRI of 0.64±0.05 and 0.62±0.05, respectively (P<0.001). In multivariable analyses, RRI was positively associated with female sex, age, systolic blood pressure, and body mass index. We observed an inverse correlation with diastolic blood pressure and heart rate. Age had a nonlinear association with RRI. We found no independent association of RRI with diabetes mellitus, hypertension treatment, smoking, cholesterol levels, or estimated glomerular filtration rate. The adjusted heritability estimate was 42±8% (P<0.001). In a population-based sample with normal renal ultrasound, RRI normal values depend on sex, age, blood pressure, heart rate, and body mass index. The significant heritability of RRI suggests that genes influence this phenotype.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Comparisons of Estimates of Annual Exceedance-Probability Discharges for Small Drainage Basins in Iowa, Based on Data through Water Year 2013, TR-678, 2015

Traditionally, the Iowa Department of Transportation has used the Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa. Twenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart. For the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013). For drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias. An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1–4 from the 1987 single-variable RREs and for flood regions 1–3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.

Gender and socioeconomic disparities in BMI trajectories in the Seychelles using birth cohorts generated from serial population-based surveys.

ABSTRACT: BACKGROUND: The relationship between body mass index (BMI) and socioeconomic status (SES) tends to change over time and across populations. In this study, we examined, separately in men and women, whether the association between BMI and SES changed over successive birth cohorts in the Seychelles (Indian Ocean, African region). METHODS: We used data from all participants in three surveys conducted in 1989, 1994 and 2004 in independent random samples of the population aged 25-64 years in the Seychelles (N= 3'403). We used linear regression to model mean BMI according to age, cohort, SES and smoking status, allowing for a quadratic term for age to account for a curvilinear relation between BMI and age and interactions between SES and age and between SES and cohorts to test whether the relation between SES and BMI changed across subsequent cohorts. All analyses were performed separately in men and women. RESULTS: BMI increased with age in all birth cohorts. BMI was lower in men of low SES than high SES but was higher in women of low SES than high SES. In all SES categories, BMI increased over successive cohorts (1.24 kg/m2 in men and 1.51 kg/m2 for a 10-year increase in birth cohorts, p <0.001). The difference in BMI between men or women of high vs. low SES did not change significantly across successive cohorts (the interaction between SES and year of birth of cohort was statistically not significant). Smoking was associated with lower BMI in men and women (respectively -1.55 kg/m2 and 2.46 kg/m2, p <0.001). CONCLUSIONS: Although large differences exist between men and women, social patterning of BMI did not change significantly over successive cohorts in this population of a middle-income country in the African region.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.