Prostate cancer screening in Switzerland: 20-year trends and socioeconomic disparities.

BACKGROUND: Despite important controversy in its efficacy, prostate cancer (PCa) screening has become widespread. Important socioeconomic screening disparities have been reported. However, trends in PCa screening and social disparities have not been investigated in Switzerland, a high risk country for PCa. We used data from five waves (from 1992-2012) of the population-based Swiss Health Interview Survey to evaluate trends in PCa screening and its association with socioeconomic indicators. METHODS: We used multivariable Poisson regression to estimate prevalence ratios (PR) and 95% Confidence Intervals (CI) adjusting for demographics, health status, and use of healthcare. RESULTS: The study included 12,034 men aged ≥50 years (mean age: 63.9). Between 1992 and 2012, ever use of PCa screening increased from 55.3% to 70.0% and its use within the last two years from 32.6% to 42.4% (p-value <0.05). Income, education, and occupational class were independently associated with PCa screening. PCa screening within the last two years was greater in men with the highest (>$6,000/month) vs. lowest income (≤$2,000) (46.5% vs. 38.7% in 2012, PR for overall period =1.29, 95%CI: 1.13-1.48). These socioeconomic disparities did not significantly change over time. CONCLUSIONS: This study shows that about half of Swiss men had performed at least one PCa screening. Men belonging to high socioeconomic status are clearly more frequently screened than those less favored. Given the uncertainty of the usefulness of PCa screening, men, including those with high socioeconomic status, should be clearly informed about benefits and harms of PCa screening, in particular, the adverse effect of over-diagnosis and of associated over-treatment.

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

Trabecular bone score in kidney transplant recipients.

UNLABELLED: It is uncertain whether bone mineral density (BMD) can accurately predict fracture in kidney transplant recipients. Trabecular bone score (TBS) provides information independent of BMD. Kidney transplant recipients had abnormal bone texture as measured by lumbar spine TBS, and a lower TBS was associated with incident fractures in recipients. INTRODUCTION: Trabecular bone score (TBS) is a texture measure derived from dual energy X-ray absorptiometry (DXA) lumbar spine images, providing information independent of bone mineral density. We assessed characteristics associated with TBS and fracture outcomes in kidney transplant recipients. METHODS: We included 327 kidney transplant recipients from Manitoba, Canada, who received a post-transplant DXA (median 106 days post-transplant). We matched each kidney transplant recipient (mean age 45 years, 39 % men) to three controls from the general population (matched on age, sex, and DXA date). Lumbar spine (L1-L4) DXA images were used to derive TBS. Non-traumatic incident fracture (excluding hand, foot, and craniofacial) (n = 31) was assessed during a mean follow-up of 6.6 years. We used multivariable linear regression models to test predictors of TBS, and multivariable Cox proportional hazard regression was used to estimate hazard ratios (HRs) per standard deviation decrease in TBS to express the gradient of risk. RESULTS: Compared to the general population, kidney transplant recipients had a significantly lower lumbar spine TBS (1.365 ± 0.129 versus 1.406 ± 0.125, P < 0.001). Multivariable linear regression revealed that receipt of a kidney transplant was associated with a significantly lower mean TBS compared to controls (-0.0369, 95 % confidence interval [95 % CI] -0.0537 to -0.0202). TBS was associated with fractures independent of the Fracture Risk Assessment score including BMD (adjusted HR per standard deviation decrease in TBS 1.64, 95 % CI 1.15-2.36). CONCLUSION: Kidney transplant recipients had abnormal bone texture as assessed by TBS and a lower lumbar spine TBS was associated with fractures in recipients.

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

The causal factors of international inequality in CO2 emissions per capita: a regression-based inequality decomposition analysis

This paper uses the possibilities provided by the regression-based inequality decomposition (Fields, 2003) to explore the contribution of different explanatory factors to international inequality in CO2 emissions per capita. In contrast to previous emissions inequality decompositions, which were based on identity relationships (Duro and Padilla, 2006), this methodology does not impose any a priori specific relationship. Thus, it allows an assessment of the contribution to inequality of different relevant variables. In short, the paper appraises the relative contributions of affluence, sectoral composition, demographic factors and climate. The analysis is applied to selected years of the period 1993–2007. The results show the important (though decreasing) share of the contribution of demographic factors, as well as a significant contribution of affluence and sectoral composition.

The association between obesity and back pain in nine countries: a cross-sectional study

BACKGROUND: The association between obesity and back pain has mainly been studied in high-income settings with inconclusive results, and data from older populations and developing countries are scarce. The aim of this study was to assess this association in nine countries in Asia, Africa, Europe, and Latin America among older adults using nationally-representative data. METHODS: Data on 42116 individuals ≥50 years who participated in the Collaborative Research on Ageing in Europe (COURAGE) study conducted in Finland, Poland, and Spain in 2011-2012, and the World Health Organization's Study on Global Ageing and Adult Health (SAGE) conducted in China, Ghana, India, Mexico, Russia, and South Africa in 2007-2010 were analysed. Information on measured height and weight available in the two datasets was used to calculate Body Mass Index (BMI). Self-reported back pain occurring in the past 30 days was the outcome. Multivariable logistic regression analysis was used to assess the association between BMI and back pain. RESULTS: The prevalence of back pain ranged from 21.5% (China) to 57.5% (Poland). In the multivariable analysis, compared to BMI 18.5-24.9 kg/m(2), significantly higher odds for back pain were observed for BMI ≥35 kg/m(2) in Finland (OR 3.33), Russia (OR 2.20), Poland (OR 2.03), Spain (OR 1.56), and South Africa (OR 1.48); BMI 30.0-34.0 kg/m(2) in Russia (OR 2.76), South Africa (OR 1.51), and Poland (OR 1.47); and BMI 25.0-29.9 kg/m(2) in Russia (OR 1.51) and Poland (OR 1.40). No significant associations were found in the other countries. CONCLUSIONS: The strength of the association between obesity and back pain may vary by country. Future studies are needed to determine the factors contributing to differences in the associations observed.

Optimization of wood flour acetylation by factorial design and partial least squares regression

Acetylation was performed to reduce the polarity of wood and increase its compatibility with polymer matrices for the production of composites. These reactions were performed first as a function of acetic acid and anhydride concentration in a mixture catalyzed by sulfuric acid. A concentration of 50%/50% (v/v) of acetic acid and anhydride was found to produced the highest conversion rate between the functional groups. After these reactions, the kinetics were investigated by varying times and temperatures using a 3² factorial design, and showed time was the most relevant parameter in determining the conversion of hydroxyl into carbonyl groups.

Least squares regression with errors in both variables: case studies

Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.

Adjust of regression models to estimate the rectal temperature of broilers for the first 14 days of life

The broiler rectal temperature (t rectal) is one of the most important physiological responses to classify the animal thermal comfort. Therefore, the aim of this study was to adjust regression models in order to predict the rectal temperature (t rectal) of broiler chickens under different thermal conditions based on age (A) and a meteorological variable (air temperature - t air) or a thermal comfort index (temperature and humidity index -THI or black globe humidity index - BGHI) or a physical quantity enthalpy (H). In addition, through the inversion of these models and the expected t rectal intervals for each age, the comfort limits of t air, THI, BGHI and H for the chicks in the heating phase were determined, aiding in the validation of the equations and the preliminary limits for H. The experimental data used to adjust the mathematical models were collected in two commercial poultry farms, with Cobb chicks, from 1 to 14 days of age. It was possible to predict the t rectal of conditions from the expected t rectal and determine the lower and superior comfort thresholds of broilers satisfactorily by applying the four models adjusted; as well as to invert the models for prediction of the environmental H for the chicks first 14 days of life.

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i