Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

Revisiting the synthetic control estimator

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. The SC relies on the assumption that there is a weighted average of the control units that reconstruct the potential outcome of the treated unit in the absence of treatment. If these weights were known, then one could estimate the counterfactual for the treated unit using this weighted average. With these weights, the SC would provide an unbiased estimator for the treatment effect even if selection into treatment is correlated with the unobserved heterogeneity. In this paper, we revisit the SC method in a linear factor model where the SC weights are considered nuisance parameters that are estimated to construct the SC estimator. We show that, when the number of control units is fixed, the estimated SC weights will generally not converge to the weights that reconstruct the factor loadings of the treated unit, even when the number of pre-intervention periods goes to infinity. As a consequence, the SC estimator will be asymptotically biased if treatment assignment is correlated with the unobserved heterogeneity. The asymptotic bias only vanishes when the variance of the idiosyncratic error goes to zero. We suggest a slight modification in the SC method that guarantees that the SC estimator is asymptotically unbiased and has a lower asymptotic variance than the difference-in-differences (DID) estimator when the DID identification assumption is satisfied. If the DID assumption is not satisfied, then both estimators would be asymptotically biased, and it would not be possible to rank them in terms of their asymptotic bias.

Asymptotic Change-Point Analysis of the Dependencies in Time Series

In recent papers, Wied and his coauthors have introduced change-point procedures to detect and estimate structural breaks in the correlation between time series. To prove the asymptotic distribution of the test statistic and stopping time as well as the change-point estimation rate, they use an extended functional Delta method and assume nearly constant expectations and variances of the time series. In this thesis, we allow asymptotically infinitely many structural breaks in the means and variances of the time series. For this setting, we present test statistics and stopping times which are used to determine whether or not the correlation between two time series is and stays constant, respectively. Additionally, we consider estimates for change-points in the correlations. The employed nonparametric statistics depend on the means and variances. These (nuisance) parameters are replaced by estimates in the course of this thesis. We avoid assuming a fixed form of these estimates but rather we use "blackbox" estimates, i.e. we derive results under assumptions that these estimates fulfill. These results are supplement with examples. This thesis is organized in seven sections. In Section 1, we motivate the issue and present the mathematical model. In Section 2, we consider a posteriori and sequential testing procedures, and investigate convergence rates for change-point estimation, always assuming that the means and the variances of the time series are known. In the following sections, the assumptions of known means and variances are relaxed. In Section 3, we present the assumptions for the mean and variance estimates that we will use for the mean in Section 4, for the variance in Section 5, and for both parameters in Section 6. Finally, in Section 7, a simulation study illustrates the finite sample behaviors of some testing procedures and estimates.

Anomaly Detection in Noisy Images

Finding rare events in multidimensional data is an important detection problem that has applications in many fields, such as risk estimation in insurance industry, finance, flood prediction, medical diagnosis, quality assurance, security, or safety in transportation. The occurrence of such anomalies is so infrequent that there is usually not enough training data to learn an accurate statistical model of the anomaly class. In some cases, such events may have never been observed, so the only information that is available is a set of normal samples and an assumed pairwise similarity function. Such metric may only be known up to a certain number of unspecified parameters, which would either need to be learned from training data, or fixed by a domain expert. Sometimes, the anomalous condition may be formulated algebraically, such as a measure exceeding a predefined threshold, but nuisance variables may complicate the estimation of such a measure. Change detection methods used in time series analysis are not easily extendable to the multidimensional case, where discontinuities are not localized to a single point. On the other hand, in higher dimensions, data exhibits more complex interdependencies, and there is redundancy that could be exploited to adaptively model the normal data. In the first part of this dissertation, we review the theoretical framework for anomaly detection in images and previous anomaly detection work done in the context of crack detection and detection of anomalous components in railway tracks. In the second part, we propose new anomaly detection algorithms. The fact that curvilinear discontinuities in images are sparse with respect to the frame of shearlets, allows us to pose this anomaly detection problem as basis pursuit optimization. Therefore, we pose the problem of detecting curvilinear anomalies in noisy textured images as a blind source separation problem under sparsity constraints, and propose an iterative shrinkage algorithm to solve it. Taking advantage of the parallel nature of this algorithm, we describe how this method can be accelerated using graphical processing units (GPU). Then, we propose a new method for finding defective components on railway tracks using cameras mounted on a train. We describe how to extract features and use a combination of classifiers to solve this problem. Then, we scale anomaly detection to bigger datasets with complex interdependencies. We show that the anomaly detection problem naturally fits in the multitask learning framework. The first task consists of learning a compact representation of the good samples, while the second task consists of learning the anomaly detector. Using deep convolutional neural networks, we show that it is possible to train a deep model with a limited number of anomalous examples. In sequential detection problems, the presence of time-variant nuisance parameters affect the detection performance. In the last part of this dissertation, we present a method for adaptively estimating the threshold of sequential detectors using Extreme Value Theory on a Bayesian framework. Finally, conclusions on the results obtained are provided, followed by a discussion of possible future work.

Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

Understanding Red Blood Cell Parameters In The Context Of The Frailty Phenotype: Interpretations Of The Fibra (frailty In Brazilian Seniors) Study.

Frailty and anemia in the elderly appear to share a common pathophysiology associated with chronic inflammatory processes. This study uses an analytical, cross-sectional, population-based methodology to investigate the probable relationships between frailty, red blood cell parameters and inflammatory markers in 255 community-dwelling elders aged 65 years or older. The frailty phenotype was assessed by non-intentional weight loss, fatigue, low grip strength, low energy expenditure and reduced gait speed. Blood sample analyses were performed to determine hemoglobin level, hematocrit and reticulocyte count, as well as the inflammatory variables IL-6, IL-1ra and hsCRP. In the first multivariate analysis (model I), considering only the erythroid parameters, Hb concentration was a significant variable for both general frailty status and weight loss: a 1.0g/dL drop in serum Hb concentration represented a 2.02-fold increase (CI 1.12-3.63) in an individual's chance of being frail. In the second analysis (model II), which also included inflammatory cytokine levels, hsCRP was independently selected as a significant variable. Each additional year of age represented a 1.21-fold increase in the chance of being frail, and each 1-unit increase in serum hsCRP represented a 3.64-fold increase in the chance of having the frailty phenotype. In model II reticulocyte counts were associated with weight loss and reduced metabolic expenditure criteria. Our findings suggest that reduced Hb concentration, reduced RetAbs count and elevated serum hsCRP levels should be considered components of frailty, which in turn is correlated with sarcopenia, as evidenced by weight loss.

Micronutrient And Physiologic Parameters Before And 6 Months After Rygb.

Bariatric surgery is considered an effective method for sustained weight loss, but may cause various nutritional complications. The aim of this study was to evaluate the nutritional status of minerals and vitamins, food consumption, and to monitor physiologic parameters in patients with obesity before and 6 months after Roux-en-Y gastric bypass surgery (RYGB). Thirty-six patients who had undergone RYGB were prospectively evaluated before and 6 months after surgery. At each phase their weight, height, body mass index (BMI), Electro Sensor Complex (ES Complex) data, food consumption, and total protein serum levels, albumin, prealbumin, parathyroid hormone (PTH), zinc (Zn), B12 vitamin (VitB12), iron (Fe), ferritin, copper (Cu), ionic calcium (CaI), magnesium (Mg), and folic acid were assessed. The mean weight loss from baseline to 6 months after surgery was 35.34±4.82%. Markers of autonomic nervous system balance (P<.01), stiffness index (P<.01), standard deviation of normal-to-normal R-R intervals (SDNN) (P<.01), and insulin resistance (P<.001) were also improved. With regard to the micronutrients measured, 34 patients demonstrated some kind of deficiency. There was a high percentage of Zn deficiency in both pre- (55.55%) and postoperative (61.11%) patients, and 33.33% of the patients were deficient in prealbumin postoperatively. The protein intake after 6 months of surgery was below the recommended intake (<70 g/d) for 88.88% of the patients. Laboratory analyses demonstrated an average decrease in total protein (P<.05), prealbumin (P = .002), and PTH (P = .008) between pre- and postsurgery, and a decrease in the percentage of deficiencies for Mg (P<.05), CaI (P<.05), and Fe (P = .021). Despite improvements in the autonomic nervous system balance, stiffness index markers and insulin resistance, we found a high prevalence of hypozincemia at 6 months post-RYGB. Furthermore, protein supplements were needed to maintain an adequate protein intake up to 6 months postsurgery.

Intrahippocampal Infusion Of Crotamine Isolated From Crotalus Durissus Terrificus Alters Plasma And Brain Biochemical Parameters.

Crotamine is one of the main constituents of the venom of the South American rattlesnake Crotalus durissus terrificus. Here we sought to investigate the inflammatory and toxicological effects induced by the intrahippocampal administration of crotamine isolated from Crotalus whole venom. Adult rats received an intrahippocampal infusion of crotamine or vehicle and were euthanized 24 h or 21 days after infusion. Plasma and brain tissue were collected for biochemical analysis. Complete blood count, creatinine, urea, glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT), creatine-kinase (CK), creatine kinase-muscle B (CK-MB) and oxidative parameters (assessed by DNA damage and micronucleus frequency in leukocytes, lipid peroxidation and protein carbonyls in plasma and brain) were quantified. Unpaired and paired t-tests were used for comparisons between saline and crotamine groups, and within groups (24 h vs. 21 days), respectively. After 24 h crotamine infusion promoted an increase of urea, GOT, GPT, CK, and platelets values (p ≤ 0.01), while red blood cells, hematocrit and leukocytes values decreased (p ≤ 0.01). Additionally, 21 days after infusion crotamine group showed increased creatinine, leukocytes, TBARS (plasma and brain), carbonyl (plasma and brain) and micronucleus compared to the saline-group (p ≤ 0.01). Our findings show that crotamine infusion alter hematological parameters and cardiac markers, as well as oxidative parameters, not only in the brain, but also in the blood, indicating a systemic pro-inflammatory and toxicological activity. A further scientific attempt in terms of preserving the beneficial activity over toxicity is required.

Evaluation Of Red Cell And Reticulocyte Parameters As Indicative Of Iron Deficiency In Patients With Anemia Of Chronic Disease.

The purpose of this study was to evaluate the effectiveness of mature red cell and reticulocyte parameters under three conditions: iron deficiency anemia, anemia of chronic disease, and anemia of chronic disease associated with absolute iron deficiency. Peripheral blood cells from 117 adult patients with anemia were classified according to iron status, and inflammatory activity, and the results of a hemoglobinopathy investigation as: iron deficiency anemia (n=42), anemia of chronic disease (n=28), anemia of chronic disease associated with iron deficiency anemia (n=22), and heterozygous β thalassemia (n=25). The percentage of microcytic red cells, hypochromic red cells, and levels of hemoglobin content in both reticulocytes and mature red cells were determined. Receiver operating characteristic analysis was used to evaluate the accuracy of the parameters in differentiating between the different types of anemia. There was no significant difference between the iron deficient group and anemia of chronic disease associated with absolute iron deficiency in respect to any parameter. The percentage of hypochromic red cells was the best parameter to discriminate anemia of chronic disease with and without absolute iron deficiency (area under curve=0.785; 95% confidence interval: 0.661-0.909, with sensitivity of 72.7%, and specificity of 70.4%; cut-off value 1.8%). The formula microcytic red cells minus hypochromic red cells was very accurate in differentiating iron deficiency anemia and heterozygous β thalassemia (area under curve=0.977; 95% confidence interval: 0.950-1.005; with sensitivity of 96.2%, and specificity of 92.7%; cut-off value 13.8). The indices related to red cells and reticulocytes have a moderate performance in identifying absolute iron deficiency in patients with anemia of chronic disease.

Relationship Between Aerobic And Anaerobic Parameters From 3-minute All-out Tethered Swimming And 400-m Maximal Front Crawl Effort.

The main aim of this investigation was to verify the relationship of the variables measured during a 3-minute all-out test with aerobic (i.e., peak oxygen uptake [(Equation is included in full-text article.)] and intensity corresponding to the lactate minimum [LMI]) and anaerobic parameters (i.e., anaerobic work) measured during a 400-m maximal performance. To measure force continually and to avoid the possible influences caused by turns, the 3-minute all-out effort was performed in tethered swimming. Thirty swimmers performed the following tests: (a) a 3-minute all-out tethered swimming test to determine the final force (equivalent to critical force: CF3-MIN) and the work performed above CF3-MIN (W'3-MIN), (b) a LMI protocol to determine the LMI during front crawl swimming, and (c) a 400-m maximal test to determine the (Equation is included in full-text article.)and total anaerobic contribution (WANA). Correlations between the variables were tested using the Pearson's correlation test (p ≤ 0.05). CF3-MIN (73.9 ± 13.2 N) presented a high correlation with the LMI (1.33 ± 0.08 m·s; p = 0.01) and (Equation is included in full-text article.)(4.5 ± 1.2 L·min; p = 0.01). However, the W'3-MIN (1,943.2 ± 719.2 N·s) was only moderately correlated with LMI (p = 0.02) and (Equation is included in full-text article.)(p = 0.01). In summary, CF3-MIN determined during the 3-minute all-out effort is associated with oxidative metabolism and can be used to estimate the aerobic capacity of swimmers. In contrast, the anaerobic component of this model (W'3-MIN) is not correlated with WANA.

Reference Values For High-density Lipoprotein Particle Size And Volume By Dynamic Light Scattering In A Brazilian Population Sample And Their Relationships With Metabolic Parameters.

Current data indicate that the size of high-density lipoprotein (HDL) may be considered an important marker for cardiovascular disease risk. We established reference values of mean HDL size and volume in an asymptomatic representative Brazilian population sample (n=590) and their associations with metabolic parameters by gender. Size and volume were determined in HDL isolated from plasma by polyethyleneglycol precipitation of apoB-containing lipoproteins and measured using the dynamic light scattering (DLS) technique. Although the gender and age distributions agreed with other studies, the mean HDL size reference value was slightly lower than in some other populations. Both HDL size and volume were influenced by gender and varied according to age. HDL size was associated with age and HDL-C (total population); non- white ethnicity and CETP inversely (females); HDL-C and PLTP mass (males). On the other hand, HDL volume was determined only by HDL-C (total population and in both genders) and by PLTP mass (males). The reference values for mean HDL size and volume using the DLS technique were established in an asymptomatic and representative Brazilian population sample, as well as their related metabolic factors. HDL-C was a major determinant of HDL size and volume, which were differently modulated in females and in males.

Efeitos da ingestão de cafeína Em exercício aeróbio de alta intensidade em hipóxia : parâmetros fisiológicos e perceptuais = Effects of caffeine ingestion on high-intensity aerobic exercise in hypoxia : physiological and perceptual parameters

Universidade Estadual de Campinas . Faculdade de Educação Física

Monitoramento de parâmetros imunológicos em atletas adolescentes de basquetebol durante e após a temporada esportiva= : Monitoring of immunological parameters in adolescent basketball athletes during and after a sports season

Universidade Estadual de Campinas . Faculdade de Educação Física

Análise transversal da estrutura óssea e parâmetros hematológicos em futebolistas profissionais = : Cross-sectional analysis of bone structure and hematological parameters in professional soccer players

Universidade Estadual de Campinas. Faculdade de Educação Física

Comparison of periodontal parameters in individuals with syndromic craniosynostosis

Craniosynostosis syndromes are characterized by premature closure of one or more cranial sutures, associated with other malformations, the most frequent of which are the Crouzon and Apert syndromes. Few studies in the literature have addressed the oral health of these individuals. The purpose of this study was to compare the periodontal status of individuals with Apert, Crouzon, Pfeiffer and Saethre-Chotzen syndromes before toothbrushing and compare the efficiency of plaque removal before and after mechanical toothbrushing. The probing depth, plaque index (according to Löe and O'Leary), clinical attachment level, gingival index (according to Silness and Löe) and amount of keratinized mucosa were evaluated before toothbrushing, and the O'Leary plaque index was assessed before and immediately after toothbrushing, on the same day, in 27 individuals aged 11 to 36 years. There was statistically significant difference in the mean probing depth and clinical attachment level among regions (p=0.00; p=0.01, respectively). The gingival index did not reveal statistically significant differences. With regard to the plaque index, the left region exhibited higher plaque index values than the right and anterior regions. No significant results were found in the analysis of keratinized mucosa. Comparison of the O'Leary plaque index before and after toothbrushing revealed statistically significant difference for all syndromes except for the Pfeiffer syndrome (p<0.05). In conclusion, there was no difference in the periodontal status among individuals with syndromic craniosynostosis. The posterior region was more affected than the anterior region as to the presence of plaque, loss of insertion and probing depth. Individuals with Pfeiffer syndrome exhibited greater toothbrushing efficiency than individuals with the other craniosynostosis syndromes.