Neither boom nor bust: how Houston's housing market differs from nation's

The ongoing housing downturn has served as a significant headwind for the U.S. economy, subtracting nearly a percentage point from the country's gross domestic product growth in each of the past six quarters. However, this downturn has not been uniform across the country. Houston is an example of a metropolitan area that was seemingly immune to the trend until its housing market began slowing significantly in mid-2007. ; Houston did not share in the rapid price appreciation seen by some large metros in the early 2000s or the sharp downturn of late 2006 and early 2007. But the tightening of credit standards since August has affected Houston disproportionately. Mortgage and housing markets have seen wide variations in performance as a result of the downturn, and this is Houston's story in the context of the national housing market turmoil.Housing ; Texas

Recent data indicate that black women are at greater risk of severe morbidity and mortality from postpartum haemorrhage, both before and after adjusting for comorbidity.

Recent data indicate that black women are at greater risk of severe morbidity and mortality from postpartum haemorrhage, both before and after adjusting for comorbidity. Causes of increased risk of severe morbidity and mortality related to postpartum haemorrhage in black women in the USA are poorly understood and warrant further research. There is a need for tailored maternity services and improved access to care for women from ethnic minorities

Protocol of a test of hearing health education programs for farm and rural youth

Abstract Background Farm and rural youth have frequent exposure to hazardous noise on the farm and recreationally, and have an increased prevalence of noise-induced hearing loss. There is a lack of programs to prepare this high-risk population to use hearing conservation strategies. Methods The purpose of this project is to test innovative hearing health education programs delivered to a large target group and to determine the effectiveness and sustainability of these programs in promoting hearing health among farm and rural youth. Specifically, this project includes: a) an interactive face-to-face informational program alone, b) an interactive face-to-face informational program followed by an Internet-based booster, and c) a no-intervention control. Sites will include selected affiliates of a major farm youth safety education organization. Data will be collected at baseline, 3, and 12 months. A linear mixed model will be used to compare the effectiveness of the three interventions over time. Descriptive statistics will be used to compare program costs and sustainability ratings. Discussion Outcomes of this project will provide knowledge necessary to implement quality and cost-effective services to farm and rural youth, a high-risk and underserved population, that can be implemented and sustained after the study is completed. Trial registration Clinicaltrials.gov NCT02472821 Registered 09 Jun, 2015.http://deepblue.lib.umich.edu/bitstream/2027.42/115460/1/12889_2015_Article_2393.pd

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Predictors of use of hearing protection among a representative sample of farmers

Farmers experience higher rates of noise-induced hearing loss (NIHL) than workers in most other industries. We developed a model of farmers' use of hearing protection, and tested it with a random sample ( n  = 532) of farmers from the upper Midwest. Barriers to using hearing protection (e.g., difficulty communicating; OR  = .44, p  < .003) were negatively related to use. Greater access/availability of hearing protectors ( OR  = 1.75, p  < .010) and male gender ( OR  = .43, p  < .019) were positively related to use. The model correctly predicted use of hearing protection for 74% of the cases. Overall, farmers demonstrated low hearing protector use, and results were similar to those from previous studies of non-farm workers. Findings from this study will be useful in designing interventions to increase farmers' hearing protector use and decrease their rates of NIHL. © 2010 Wiley Periodicals, Inc. Res Nurs Health 33:528–538, 2010Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78292/1/20410_ftp.pd

The influence of heavy goods vehicle traffic on accidents on different types of Spanish interurban roads

This paper illustrates a methodology developed to analyze the influence of traffic conditions, i.e. volume and composition on accidents on different types of interurban roads in Spain, by applying negative binomial models. The annual average daily traffic was identified as the most important variable, followed by the percentage of heavy goods vehicles, and different covariate patterns were found for each road type. The analysis of hypothetical scenarios of the reduction of heavy goods vehicles in two of the most representative freight transportation corridors, combined with hypotheses of total daily traffic mean intensity variation, produced by the existence or absence of induced traffic gives rise to several scenarios. In all cases a reduction in the total number of accidents would occur as a result of the drop in the number of heavy goods transport vehicles, However the higher traffic intensity, resulting of the induction of other vehicular traffic, reduces the effects on the number of accidents on single carriageway road segments compared with high capacity roads, due to the increase in exposure. This type of analysis provides objective elements for evaluating policies that encourage modal shifts and road safety enhancements