Population-level risks of physical activity: Saving bones and screening hearts

Documented risks of physical activity include reduced bone mineral density at high activity volume, and sudden cardiac death among adults and adolescents. Further illumination of these risks is needed to inform future public health guidelines. The present research seeks to 1) quantify the association between physical activity and bone mineral density (BMD) across a broad range of activity volume, 2) assess the utility of an existing pre-screening questionnaire among US adults, and 3) determine if pre-screening risk stratification by questionnaire predicts referral to physician among Texas adolescents. ^ Among 9,468 adults 20 years of age or older in the National Health and Nutrition Examination Survey (NHANES) 2007-2010, linear regression analyses revealed generally higher BMD at the lumbar spine and proximal femur with greater reported activity volume. Only lumbar BMD in women was unassociated with activity volume. Among men, BMD was similar at activity beyond four times the minimum volume recommended in the Physical Activity Guidelines. These results suggest that the range of activity reported by US adults is not associated with low BMD at either site. ^ The American Heart Association / American College of Sports Medicine Preparticipation Questionnaire (AAPQ) was applied to 6,661 adults 40 years of age or older from NHANES 2001-2004 by using NHANES responses to complete AAPQ items. Following AAPQ referral criteria, 95.5% of women and 93.5% of men would be referred to a physician before exercise initiation, suggesting little utility for the AAPQ among adults aged 40 years or older. Unnecessary referral before exercise initiation may present a barrier to exercise adoption and may strain an already stressed healthcare infrastructure. ^ Among 3181 athletes in the Texas Adolescent Athlete Heart Screening Registry, 55.2% of boys and 62.2% of girls were classified as high-risk based on questionnaire answers. Using sex-stratified contingency table analyses, risk categories were not significantly associated with referral to physician based on electrocardiogram or echocardiogram, nor were they associated with confirmed diagnoses on follow-up. Additional research is needed to identify which symptoms are most closely related to sudden cardiac death, and determine the best methods for rapid and reliable assessment. ^ In conclusion, this research suggests that the volume of activity reported by US adults is not associated with low BMD at two clinically relevant sites, casts doubts on the utility of two existing cardiac screening tools, and raises concern about barriers to activity erected through ineffective screening. These findings augment existing research in this area that may inform revisions to the Physical Activity Guidelines regarding risk mitigation.^

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^

Predicting smokeless tobacco cessation in a blue -collar population

The use of smokeless tobacco products is undergoing an alarming resurgence in the United States. Several national surveys have reported a higher prevalence of use among those employed in blue-collar occupations. National objectives now target this group for health promotion programs which reduce the health risks associated with tobacco use.^ Drawn from a larger data set measuring health behaviors, this cross-sectional study tested the applicability of two related theories, the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB), to smokeless tobacco (SLT) cessation in a blue-collar population of gas pipeline workers. In order to understand the determinants of SLT cessation, measures were obtained of demographic and normative characteristics of the population and specific constructs. Attitude toward the act of quitting (AACT) and subjective norm (SN) are constructs common to both models, perceived behavioral control (PBC) is unique to the TPB, and the number of past quit attempts is not contained in either model. In addition, a self-reported measure was taken of SLT use at two-month follow-up.^ The study population was comprised of all male SLT users who were field employees in a large gas pipeline company with gas compressor stations extending from Texas to the Canadian border. At baseline, 199 employees responded to the SLT portion of the survey, 118 completed some portion of the two-month follow-up, and 101 could be matched across time.^ As hypothesized, significant correlations were found between constructs antecedent to AACT and SN, although crossover effects occurred. Significant differences were found between SLT cessation intenders and non-intenders with regard to their personal and normative beliefs about quitting as well as their outcome expectancies and motivation to comply with others' beliefs. These differences occurred in the expected direction, with the mean intender score consistently higher than that of the non-intender.^ Contrary to hypothesis, AACT predicted intention to quit but SN did not. However, confirmatory of the TPB, PBC, operationalized as self-efficacy, independently contributed to the prediction of intention. Statistically significant relationships were not found between intention, perceived behavioral control, their interactive effects, and use behavior at two-month follow-up. The introduction of number of quit attempts into the logistic regression model resulted in insignificant findings for independent and interactive effects.^ The findings from this study are discussed in relation to their implications for program development and practice, especially within the worksite. In order to confirm and extend the findings of this investigation, recommendations for future research are also discussed. ^

Subjective well -being as predictor of mortality, heart disease, and obesity: Prospective evidence from the Alameda County Study

Based on the World Health Organization's (1965) definition of health, understanding of health requires understanding of positive psychological states. Subjective Well-being (SWB) is a major indicator of positive psychological states. Up to date, most studies of SWB have been focused on its distributions and determinants. However, study of its consequences, especially health consequences, is lacking. This dissertation research examined Subjective Well-being, as operationally defined by constructs drawn from the framework of Positive Psychology, and its sub-scores (Positive Feelings and Negative Feelings) as predictors of three major health outcomes—mortality, heart disease, and obesity. The research used prospective data from the Alameda County Study over 29 years (1965–1994), based on a stratified, randomized, representative sample of the general public in Alameda County, California (Baseline N = 6928). ^ Multivariate analyses (Survival analyses using sequential Cox Proportional Hazard models in the cases of mortality and heart disease, and sequential Logistic Regression analyses in the case of obesity) were performed as the main methods to evaluate the associations of the predictors and the health outcomes. The results revealed that SWB reduced risks of all-cause mortality, natural-cause mortality, and cardiovascular mortality. Positive feelings not only had an even stronger protective effect against all-cause, natural-cause and cardiovascular mortality, but also predicted decreased unnatural-cause mortality which includes deaths from suicide, homicide, accidents, mental disorders, drug dependency, as well as alcohol-related liver diseases. These effects were significant even after adjusted for age, gender, education, and various physical health measures, and, in the case of cardiovascular mortality, obesity and health practices (alcohol consumption, smoking, and physical activities). However, these two positive psychological indicators, SWB and positive feelings, did not predict obesity. And negative feelings had no significant effect on any of the health outcomes evaluated, i.e., all-cause mortality, natural- and unnatural-cause mortality, cardiovascular mortality, or obesity, after covariates were controlled. These findings were discussed (1) in comparison with relevant existing studies, (2) in terms of their implications in health research and promotion, (3) in terms of the independence of positive and negative feelings, and (4) from a Positive Psychology perspective and its significance in Public Health research and practice. ^

Toxoplasma gondii seroprevalence in ringed seals (Pusa hispida) from the Canadian Arctic

Toxoplasmosis is a significant public health threat for Inuit in the Canadian Arctic. This study aimed to investigate arctic seals as a possible food-borne source of infection. Blood samples collected from 828 seals in 7 Canadian Arctic communities from 1999 to 2006 were tested for Toxoplasma gondii antibodies using a direct agglutination test. Polymerase chain reaction (PCR) was used to detect T. gondii DNA in tissues of a subsample of seals. Associations between seal age, sex, species, diet, community and year of capture, and serological test results were investigated by logistic regression. Overall seroprevalence was 10.4% (86/828). All tissues tested were negative by PCR. In ringed seals, seroprevalence was significantly higher in juveniles than in adults (odds ratio = 2.44). Overall, seroprevalence varied amongst communities (P = 0.0119) and by capture year (P = 0.0001). Our study supports the hypothesis that consumption of raw seal meat is a significant source of infection for Inuit. This work raises many questions about the mechanism of transfer of this terrestrial parasite to the marine environment, the preponderance of infection in younger animals and the natural course of infection in seals. Further studies to address these questions are essential to fully understand the health risks for Inuit communities.

Advanced methodologies for the dendrogeomorphic analysis of past floods and related risks

This communication presents an overview of their first results and innovate methodologies, focused in their possibilities and limitations for the reconstruction of recent floods and paleofloods over the World.

Economic analysis of drought risks: an application to irrigated agriculture in Spain

Abstract This paper describes a two-part methodology for managing the risk posed by water supply variability to irrigated agriculture. First, an econometric model is used to explain the variation in the production value of irrigated agriculture. The explanatory variables include an index of irrigation water availability (surface storage levels), a price index representative of the crops grown in each geographical unit, and a time variable. The model corrects for autocorrelation and it is applied to 16 representative Spanish provinces in terms of irrigated agriculture. In the second part, the fitted models are used for the economic evaluation of drought risk. In flow variability in the hydrological system servicing each province is used to perform ex-ante evaluations of economic output for the upcoming irrigation season. The model?s error and the probability distribution functions (PDFs) of the reservoirs? storage variations are used to generate Monte Carlo (Latin Hypercube) simulations of agricultural output 7 and 3 months prior to the irrigation season. The results of these simulations illustrate the different risk profiles of each management unit, which depend on farm productivity and on the probability distribution function of water in flow to reservoirs. The potential for ex-ante drought impact assessments is demonstrated. By complementing hydrological models, this method can assist water managers and decisionmakers in managing reservoirs.

Stabilization in a two-species chemotaxis system with logistic source

We study a system of three partial differential equations modelling the spatiotemporal behaviour of two competitive populations of biological species both of which are attracted chemotactically by the same signal substance. For a range of the parameters the system possesses a uniquely determined spatially homogeneous positive equilibrium (u?, v?) globally asymptotically stable within a certain nonempty range of the logistic growth coefficients.

Regularized logistic regression and multi-objective variable selection for classifying MEG data

This paper addresses the question of maximizing classifier accuracy for classifying task-related mental activity from Magnetoencelophalography (MEG) data. We propose the use of different sources of information and introduce an automatic channel selection procedure. To determine an informative set of channels, our approach combines a variety of machine learning algorithms: feature subset selection methods, classifiers based on regularized logistic regression, information fusion, and multiobjective optimization based on probabilistic modeling of the search space. The experimental results show that our proposal is able to improve classification accuracy compared to approaches whose classifiers use only one type of MEG information or for which the set of channels is fixed a priori.

Assessment of self-combustion risks for solid fuels (POSTER)

Every solid fuel has a tendency to react with oxygen, a fact that constitutes the basis of their ability to oxidation and energy intake for combustion, but that poses a risk when it occurs in an uncontrolled manner. When the slow oxidation phenomenon produces more heat than can be evacuated, the result is a heating process, which promotes combustion reactions, primarily fuel oxidation, and a progressive increase in temperature.

Use of decision trees algorithm for the territorial logistic planning.

Data mining, and in particular decision trees have been used in different fields: engineering, medicine, banking and finance, etc., to analyze a target variable through decision variables. The following article examines the use of the decision trees algorithm as a tool in territorial logistic planning. The decision tree built has estimated population density indexes for territorial units with similar logistics characteristics in a concise and practical way.

Analyzing climate change adaptation in the agriculture and water sectors: screening risks and opportunities.

As part of the Mediterranean area, the Guadiana basin in Spain is particularly exposed to increasing water stress due to climate change. Future warmer and drier climate will have negative implications for the sustainability of water resources and irrigation agriculture, the main socio- economic sector in the region. This paper illustrates a systematic analysis of climate change impacts and adaptation in the Guadiana basin based on a two-stage modeling approach. First, an integrated hydro-economic modeling framework was used to simulate the potential effects of regional climate change scenarios for the period 2000-2069. Second, a participatory multi-criteria technique, namely the Analytic Hierarchy Process (AHP), was applied to rank potential adaptation measures based on agreed criteria. Results show that, in the middle-long run and under severe climate change, reduced water availability, lower crop yields and increased irrigation demands might lead to water shortages, crop failure, and up to ten percent of income losses to irrigators. AHP results show how private farming adaptation measures, including improving irrigation efficiency and adjusting crop varieties, are preferred to public adaptation measures, such as building new dams. The integrated quantitative and qualitative methodology used in this research can be considered a socially-based valuable tool to support adaptation decision-making.

Identifying Potential Risks and Benefits of Using Cloud in Distributed Software Development.

Cloud-based infrastructure has been increasingly adopted by the industry in distributed software development (DSD) environments. Its proponents claim that its several benefits include reduced cost, increased speed and greater productivity in software development. Empirical evaluations, however, are in the nascent stage of examining both the benefits and the risks of cloud-based infrastructure. The objective of this paper is to identify potential benefits and risks of using cloud in a DSD project conducted by teams based in Helsinki and Madrid. A cross-case qualitative analysis is performed based on focus groups conducted at the Helsinki and Madrid sites. Participants observations are used to supplement the analysis. The results of the analysis indicated that the main benefits of using cloud are rapid development, continuous integration, cost savings, code sharing, and faster ramp-up. The key risks determined by the project are dependencies, unavailability of access to the cloud, code commitment and integration, technical debt, and additional support costs. The results revealed that if such environments are not planned and set up carefully, the benefits of using cloud in DSD projects might be overshadowed by the risks associated with it.

Methodological issues of LCA application to building sector: challenges, risks and opportunities

Methodological issues of LCA application to building sector: challenges, risks and opportunities