Development and application of a multiple linear regression model to consider the impact of weekly waste container capacity on the yield from kerbside recycling programmes

The paper describes the development and application of a multiple linear regression model to identify how the key elements of waste and recycling infrastructure, namely container capacity and frequency of collection affect the yield from municipal kerbside recycling programmes. The overall aim of the research was to gain an understanding of the factors affecting the yield from municipal kerbside recycling programmes in Scotland. The study isolates the principal kerbside collection service offered by 32 councils across Scotland, eliminating those recycling programmes associated with flatted properties or multi occupancies. The results of a regression analysis model has identified three principal factors which explain 80% of the variability in the average yield of the principal dry recyclate services: weekly residual waste capacity, number of materials collected and the weekly recycling capacity. The use of the model has been evaluated and recommendations made on ongoing methodological development and the use of the results in informing the design of kerbside recycling programmes. The authors hope that the research can provide insights for the ongoing development of methods to optimise the design and operation of kerbside recycling programmes.

Association Analysis of Dyslipidemia-Related Genes in Diabetic Nephropathy

Type 1 diabetes (T1D) increases risk of the development of microvascular complications and cardiovascular disease (CVD). Dyslipidemia is a common risk factor in the pathogenesis of both CVD and diabetic nephropathy (DN), with CVD identified as the primary cause of death in patients with DN. In light of this commonality, we assessed single nucleotide polymorphisms (SNPs) in thirty-seven key genetic loci previously associated with dyslipidemia in a T1D cohort using a casecontrol design. SNPs (n = 53) were genotyped using Sequenom in 1467 individuals with T1D (718 cases with proteinuric nephropathy and 749 controls without nephropathy i.e. normal albumin excretion). Cases and controls were white and recruited from the UK and Ireland. Association analyses were performed using PLINK to compare allele frequencies in cases and controls. In a sensitivity analysis, samples from control individuals with reduced renal function (estimated glomerular filtration rate,60 ml/min/1.73 m2) were excluded. Correction for multiple testing was performed by permutation testing. A total of 1394 samples passed quality control filters. Following regression analysis adjusted by collection center, gender, duration of diabetes, and average HbA1c, two SNPs were significantly associated with DN. rs4420638 in the APOC1 region (odds ratio [OR] = 1.51; confidence intervals [CI]: 1.19–1.91; P = 0.001) and rs1532624 in CETP (OR = 0.82; CI: 0.69–0.99; P = 0.034); rs4420638 was also significantly associated in a sensitivity analysis (P = 0.016) together with rs7679 (P = 0.027). However, no association was significant following correction for multiple testing. Subgroup analysis of end-stage renal disease status failed to reveal any association. Our results suggest common variants associated with dyslipidemia are not strongly associated with DN in T1D among white individuals. Our findings, cannot entirely exclude these key genes which are central to the process of dyslipidemia, from involvement in DN pathogenesis as our study had limited power to detect variants of small effect size. Analysis in larger independent cohorts is required.

Aspirin therapy in patients with acute respiratory distress syndrome (ARDS) is associated with reduced intensive care unit mortality: a prospective analysis

INTRODUCTION: Acute respiratory distress syndrome (ARDS) is a common clinical syndrome with high mortality and long-term morbidity. To date there is no effective pharmacological therapy. Aspirin therapy has recently been shown to reduce the risk of developing ARDS, but the effect of aspirin on established ARDS is unknown.

METHODS: In a single large regional medical and surgical ICU between December 2010 and July 2012, all patients with ARDS were prospectively identified and demographic, clinical, and laboratory variables were recorded retrospectively. Aspirin usage, both pre-hospital and during intensive care unit (ICU) stay, was included. The primary outcome was ICU mortality. We used univariate and multivariate logistic regression analyses to assess the impact of these variables on ICU mortality.

RESULTS: In total, 202 patients with ARDS were included; 56 (28%) of these received aspirin either pre-hospital, in the ICU, or both. Using multivariate logistic regression analysis, aspirin therapy, given either before or during hospital stay, was associated with a reduction in ICU mortality (odds ratio (OR) 0.38 (0.15 to 0.96) P = 0.04). Additional factors that predicted ICU mortality for patients with ARDS were vasopressor use (OR 2.09 (1.05 to 4.18) P = 0.04) and APACHE II score (OR 1.07 (1.02 to 1.13) P = 0.01). There was no effect upon ICU length of stay or hospital mortality.

CONCLUSION: Aspirin therapy was associated with a reduced risk of ICU mortality. These data are the first to demonstrate a potential protective role for aspirin in patients with ARDS. Clinical trials to evaluate the role of aspirin as a pharmacological intervention for ARDS are needed.

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Compositional Data Analysis in Forensic Geoscience

Statistics are regularly used to make some form of comparison between trace evidence or deploy the exclusionary principle (Morgan and Bull, 2007) in forensic investigations. Trace evidence are routinely the results of particle size, chemical or modal analyses and as such constitute compositional data. The issue is that compositional data including percentages, parts per million etc. only carry relative information. This may be problematic where a comparison of percentages and other constraint/closed data is deemed a statistically valid and appropriate way to present trace evidence in a court of law. Notwithstanding an awareness of the existence of the constant sum problem since the seminal works of Pearson (1896) and Chayes (1960) and the introduction of the application of log-ratio techniques (Aitchison, 1986; Pawlowsky-Glahn and Egozcue, 2001; Pawlowsky-Glahn and Buccianti, 2011; Tolosana-Delgado and van den Boogaart, 2013) the problem that a constant sum destroys the potential independence of variances and covariances required for correlation regression analysis and empirical multivariate methods (principal component analysis, cluster analysis, discriminant analysis, canonical correlation) is all too often not acknowledged in the statistical treatment of trace evidence. Yet the need for a robust treatment of forensic trace evidence analyses is obvious. This research examines the issues and potential pitfalls for forensic investigators if the constant sum constraint is ignored in the analysis and presentation of forensic trace evidence. Forensic case studies involving particle size and mineral analyses as trace evidence are used to demonstrate the use of a compositional data approach using a centred log-ratio (clr) transformation and multivariate statistical analyses.

HDAC1 and HDAC2 independently predict mortality in hepatocellular carcinoma by a competing risk regression model in a Southeast Asian population

Histone deacetylases (HDACs) are enzymes involved in transcriptional repression. We aimed to examine the significance of HDAC1 and HDAC2 gene expression in the prediction of recurrence and survival in 156 patients with hepatocellular carcinoma (HCC) among a South East Asian population who underwent curative surgical resection in Singapore. We found that HDAC1 and HDAC2 were upregulated in the majority of HCC tissues. The presence of HDAC1 in tumor tissues was correlated with poor tumor differentiation. Notably, HDAC1 expression in adjacent non-tumor hepatic tissues was correlated with the presence of satellite nodules and multiple lesions, suggesting that HDAC1 upregulation within the field of HCC may contribute to tumor spread. Using competing risk regression analysis, we found that increased cancer-specific mortality was significantly associated with HDAC2 expression. Mortality was also increased with high HDAC1 expression. In the liver cancer cell lines, HEP3B, HEPG2, PLC5, and a colorectal cancer cell line, HCT116, the combined knockdown of HDAC1 and HDAC2 increased cell death and reduced cell proliferation as well as colony formation. In contrast, knockdown of either HDAC1 or HDAC2 alone had minimal effects on cell death and proliferation. Taken together, our study suggests that both HDAC1 and HDAC2 exert pro-survival effects in HCC cells, and the combination of isoform-specific HDAC inhibitors against both HDACs may be effective in targeting HCC to reduce mortality.

Reduced risk of pancreatic cancer associated with asthma and nasal allergies

OBJECTIVE: Studies indicate an inverse association between ductal adenocarcinoma of the pancreas (PDAC) and nasal allergies. However, controversial findings are reported for the association with asthma. Understanding PDAC risk factors will help us to implement appropriate strategies to prevent, treat and diagnose this cancer. This study assessed and characterised the association between PDAC and asthma and corroborated existing reports regarding the association between allergies and PDAC risk.

DESIGN: Information about asthma and allergies was collated from 1297 PDAC cases and 1024 controls included in the PanGenEU case-control study. Associations between PDAC and atopic diseases were studied using multilevel logistic regression analysis. Meta-analyses of association studies on these diseases and PDAC risk were performed applying random-effects model.

RESULTS: Asthma was associated with lower risk of PDAC (OR 0.64, 95% CI 0.47 to 0.88), particularly long-standing asthma (>=17 years, OR 0.39, 95% CI 0.24 to 0.65). Meta-analysis of 10 case-control studies sustained our results (metaOR 0.73, 95% CI 0.59 to 0.89). Nasal allergies and related symptoms were associated with lower risk of PDAC (OR 0.66, 95% CI 0.52 to 0.83 and OR 0.59, 95% CI 0.46 to 0.77, respectively). These results were supported by a meta-analysis of nasal allergy studies (metaOR 0.6, 95% CI 0.5 to 0.72). Skin allergies were not associated with PDAC risk.

CONCLUSIONS: This study shows a consistent inverse association between PDAC and asthma and nasal allergies, supporting the notion that atopic diseases are associated with reduced cancer risk. These results point to the involvement of immune and/or inflammatory factors that may either foster or restrain pancreas carcinogenesis warranting further research to understand the molecular mechanisms driving this association.

Validation of a method for the analysis of volatile organic compounds in water

Dissertação de mestrado, Qualidade em Análises, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Impact of job insecurity on sexual desire: an exploratory analysis.

To explore, for the first time, the impact of job insecurity on sexual desire. Cross-sectional analysis of a nationally representative sample of 7247 individuals aged 20-64 years working as full or part-time employees in Switzerland. The logistic regression analysis showed that workers aged 20-49 years perceiving high levels of job insecurity are exposed to a significantly higher risk of decrease of sexual desire compared to the reference group. The risk is 53% higher among men (OR 1.53; 95% CI 1.16-2.01) and 47% for woman (OR 1.47; 1.13-1.91). No increased risk was found for employees aged 50-64 years old. An increasing fear of job loss is associated with a deterioration in sexual desire. These first preliminary findings should promote further epidemiological and clinical prospective studies on the impact of job insecurity on intimate relationships and sexual dysfunction.

Statistical Analysis of Diabetes Mellitus

Diabetes mellitus is a disease where the glucosis-content of the blood does not automatically decrease to a ”normal” value between 70 mg/dl and 120 mg/dl (3,89 mmol/l and 6,67 mmol/l) between perhaps one hour (or two hours) after eating. Several instruments can be used to arrive at a relative low increase of the glucosis-content. Besides drugs (oral antidiabetica, insulin) the blood-sugar content can mainly be influenced by (i) eating, i.e., consumption of the right amount of food at the right time (ii) physical training (walking, cycling, swimming). In a recent paper the author has performed a regression analysis on the influence of eating during the night. The result was that one ”bread-unit” (12g carbon-hydrats) increases the blood-sugar by about 50 mg/dl, while one hour after eating the blood-sugar decreases by about 10 mg/dl per hour. By applying this result-assuming its correctness - it is easy to eat the right amount during the night and to arrive at a fastening blood-sugar (glucosis-content) in the morning of about 100 mg/dl (5,56 mmol/l). In this paper we try to incorporate some physical exercise into the model.

Factores de riesgo para sobrepeso y obesidad en escolares en una población bogotana

Introducción: con las recientes tendencias de estilo de vida, no está claro qué factores son los contribuyentes más importantes en niños escolares para desarrollar sobrepeso- obesidad. Objetivo. Evaluar el impacto de los factores prenatales, perinatales y ambientales sobre el desarrollo de sobrepeso y obesidad en niños de 5 a 10 años en una población bogotana. Materiales y métodos: se realizó un estudio de casos y controles no pareado, empleando una encuesta a 528 niños, en quienes se identificaron los factores de riesgo. Se utilizó la prueba chi-cuadrado para evaluar las diferencia entre los niños normales y con sobrepeso-obesidad. Se realizó un modelo de regresión logística para evaluar los factores relevantes. Se determinaron los (OR) y sus intervalos de confianza (IC) del 95%. Resultados: se obtuvo una muestra de 528 niños. Se encontró que existen diferencias significativas en la ingesta calórica (p<0,001). El sobrepeso materno pregestacional fue de 23,2% en las madres de los casos y 16,5% en los controles (p<0,001). No hubo diferencias estadísticamente significativas con otros factores. La regresión logística arrojó datos significativos en dieta hipercalórica p =0,002 (OR =5,27; IC 95% 1,79-1,54) y el peso materno p =0,005 (OR =1,03, IC 95% 1,01-1,05). Se realizó una curva ROC para el cálculo de la capacidad predictiva del modelo y el área bajo la curva es de 0.64 (IC 95% 0.59-0.69). Conclusiones: se identificó como factores de riesgo para el desarrollo de sobrepeso-obesidad infantil en niños escolares, una dieta hipercalórica y sobrepeso materno pregestacional.

Aislamiento de venas pulmonares en el Centro Internacional de Arritmias ‘Andrea Natale’ - Fundación Cardio infantil

Introducción: El Aislamiento de Venas Pulmonares (AVP) es un procedimiento de alto costo al cual son sometidos pacientes con riesgo cardiovascular elevado. Requiere un alto grado de especialización en el personal médico y paramédico que lo ejecuta, con curvas de aprendizaje que sobrepasan los dos años de formación académica y entrenamiento específico. Metodología: Se realizó un estudio de cohorte retrospectivo, donde se incluyeron 88 sujetos sometidos al procedimiento en el lapso comprendido entre el 1º de enero y el 31 de diciembre de 2013, con el objetivo de evaluar su proceso de atención en el Centro Internacional de Arritmias ‘Andrea Natale’ de la FCI – Instituto de Cardiología. Se realizó análisis de regresión lineal y logística múltiple. Resultados: Se encontró que en el 97,73%% de los pacientes el diagnóstico principal era algún tipo de Fibrilación Auricular (FA); a su vez, la comorbilidad más frecuente fue HTA en el 30,68% y ningún paciente presentaba enfermedad coronaria, no hubo diferencias significativas por sexo. La complicación peri operatoria tuvo una incidencia del 3,41%, el 22,73% requirió ingreso a UCI con un promedio de días estancia 0,25+0,51. El 98,86% de la población estudiada recibió educación pos procedimiento acerca de sus cuidados y signos de alarma. Los factores encontrados en el estudio que afectan la duración del procedimiento y la estancia hospitalaria son las interconsultas pre procedimiento, el manejo médico de la cardiomiopatía de base y el uso de anti agregantes plaquetarios pre procedimiento; los cuales, son puntos por mejorar previo al ingreso o programación del paciente para ser llevado a AVP. Discusión: Como recomendaciones específicas se destacan: La necesidad de incluir en el protocolo de preparación para ablación de venas pulmonares la realización de interconsultas a las especialidades requeridas, antes de su ingreso para la realización del procedimiento. Es importante que el paciente que lo amerite haga parte de un programa de falla cardiaca previamente al procedimiento