目的：本研究主要目的是建立預測模型來判定矽肺發生的累積風險從而推薦適宜的胸片照射年限並從而評估常規監測和推薦監測策略的成本效益。此外，本研究還評價了常規診斷和驗證性診斷的符合度以及在驗證性診斷中邀請的三位專家之間的符合度。 / 方法：總計有3492男性接塵工人在1964年1月1日到1974年12月31日期間進入本隊列並隨訪至2008年12月31日。不同閱片專家根據中國最新塵肺病診斷標準 （GBZ70-2009））分別閱片總計9084張。對專家之間閱片結果的兩兩比較和兩種診斷結果的比較均采用Cohen’s Kappa檢驗。應用三種篩選方法（強制所有變量同時進入模型，後退逐步篩選，以及Least Absolute Shrinkage and Selection Operator (LASSO)篩選。LASSO模型作為最優模型，以分數量表的方式來表達。根據分數，把工人分成高、中、低危險組，並估計這三組不同危險水平工人的累積危險度。運用0.1% 累積危險度來判定不同危险的工人及不同期別的矽肺病人的射線照射年限。多狀態Markov模型用於計算矽塵暴露工人不同狀態的年轉移概率，並應用Markov成本效益分析方法來估計每獲得一個生命年的成本效益。 / 結果：截至2008年底，本矽塵暴露隊列共計發現298例矽肺病人（累計發病率為8.53%），死亡1347例（死亡比例為38.57%）。本研究發現常規診斷和驗證性診斷有很好的符合度 （Kappa值為0.89， 95%可信區間為0.88-0.91）。基於LASSO模型的分數量表具有很好的診斷識別能力 （ROC曲線下面積為0.83， 95%可信區間為0.81-0.86）。根據0.1%累積危險度標準，我們判定低危險組工人第一次射線照射的時間為第11年，推薦每兩年隨訪一次；中等危險組工人和高危險組工人的第一次射線照射時間分別為第11年和第5年，推薦每年隨訪一次。矽肺病人未晉級到三期以前均一年隨訪一次。矽塵暴露工人的年轉移概率為：從健康狀態向疑似病例轉移的概率為0.0198，從疑似病例向一期矽肺轉移的概率為0.038，從一期矽肺向二期矽肺轉移的概率為0.0516，從二期矽肺向三期矽肺轉移的概率為0.059，從三期矽肺向死亡轉移的概率為0.18。在1964到2008年間，診斷一例矽肺病例平均花費醫療成本為21853.11美元，非醫療成本為5993.30美元。模擬10,000矽塵暴露工人在未來40年按照當前的狀態轉移概率，應用常規的職業健康檢查為手段獲得一個生命年的成本效益為43.60美元，應用推薦的職業健康檢查為手段獲得一個生命年的成本效益為46.99美元。 / 結論：本研究在最優預測模型的基礎上為不同矽肺危險度的矽塵暴露工人首次提供了科學的證據來判定射線照射的適宜年限，亦為未來矽塵暴露工人的職業健康監測提供了科學理論依據，雖然本研究推薦的監測策略獲得同常規策略相類似的成本和效益。 / Objectives: The primary objective was to develop prediction models for determining the optimal intervals of chest radiographic surveillance for workers exposed to silica dust; the second primary objective is to assess the cost per case identification and compare the cost per life year gained under routine medical surveillance program with that under the recommended program for workers exposed to silica dust in China. In addition, the inter-rater agreement amongst three invited radiologists on rereading the chest radiographs and the agreement between the original diagnoses of silicosis (from routine reports) and the verified diagnoses reassessed by the three experts were also evaluated. / Methods: A total of 3492 male workers exposed to silica dust in an iron ore during the period 1964 - 1974 were recruited into this retrospective cohort study. All cohort members were followed up through the end of 2008 to observe the occurrence of silicosis and overall profile of mortality. All 9084 chest X-ray films were reread by three radiologists who had been qualified as experts at the national level according to the Chinese National Diagnostic Criteria of Pneumoconiosis (GBZ70-2009). The diagnosis of silicosis made by the panel of these three invited experts was referred to the “verified diagnosis“. Cohen’s Kappa test was used to test inter-rater agreements of three invited readers on chest radiographs and the agreement on the diagnosis of silicosis obtained from routine medical surveillance (i.e., the original routine diagnosis) was compared with those verified by the 3 qualified readers (i.e., the verified diagnosis). The multivariate Cox’s proportional hazard regression models were developed to predict the silicosis occurrence based on three selection approaches entry of all predictors at the same time, backward stepwise selection, and Least Absolute Shrinkage and Selection Operator (LASSO) selection. The LASSO model showed the best model fit which was thus regarded as the final model for predicting a score chart. / Based on this practically used score chart, we then classified workers into three groups of different risk levels of silicosis (low, moderate, and high). We estimated the cumulative risk of silicosis over years of follow-up for these three groups of workers at different risk levels. We used 1 per thousand of cumulative risk for developing silicosis as a “benchmark“ to determine the intervals of radiologic surveillance for workers with different risks of silicosis. Multi-state Markov model was used to calculate the transition probabilities of different states of silicosis and the analysis on cost and effectiveness was performed. / Results: By the end of 2008, the cumulative incidence rate of silicosis was 8.53% (298 silicosis cases) and a total of 1347 deaths (38.57%) were observed. / Good inter-rater agreements were observed amongst three invited radiologists for rereading all the chest films. Kappa value for the agreement between the original diagnoses and the verified diagnoses was 0.89 (95% confidence interval [95%CI], 0.88-0.91). / The model with the best fit was LASSO Cox model which showed a good discrimination with an area of 0.83 (95%CI, 0.81-0.86) under the receiver operating characteristic (ROC) curve. We classified workers into 3 risk groups according to the score chart obtained from the LASSO Cox model, and found the observed probabilities matched well to the predictions. According to 1 per thousand “benchmark“, we can determine that the initial interval of radiographic surveillance for workers in the low risk group was 11 years and a subsequent biyearly examination was recommended. The initial examination interval was 11 years and 5 years respectively for workers in the middle and high risk group, and then a yearly examination was recommended. For patients with silicosis, an annual radiological surveillance program was recommended regardless of the stage of pneumoconiosis. / According to results from multi-state model, we estimated that the yearly transition probability was 0.0198 for silica dust exposed workers from healthy state to the suspected silicosis cases (sojourn time = 47 years), 0.0338 from suspected silicosis cases to silicosis stage one (sojourn time = 23 years), 0.0516 from silicosis stage one to stage two (sojourn time = 9 years), 0.059 from silicosis stage two to stage three (sojourn time = 6 years), and 0.18 from silicosis stage three to death (sojourn time = 5 years). / During the period 1964 to 2008, the average direct medical cost spent on identifying one silicosis case was US$ 21853.11 and the non-medical cost for identifying one case was US$ 5993.30 per case. The estimated medical cost regarding per life year gained was US$ 43.60 under the routine medical surveillance program and it would be US$ 46.99 if the newly recommended surveillance program is adopted. / Conclusion: This study is the first to provide scientific evidence on determining the optimal intervals of radiographic surveillance for workers at different risk levels of silicosis based on the ‘best’ prediction model. Although our study revealed similar cost and effectiveness for using the recommended occupational health examination strategy compared with the routine program, this study is the first to provide scientific theory for guiding evidence-based occupational medical surveillance on workers exposed to silica dust in the world. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Chen, Minghui. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 195-210). / Abstract also in Chinese. / Abstract (English) --- p.i / Abstract (Chinese) --- p.v / Acknowledgements --- p.vii / List of contents --- p.ix / List of tables --- p.xv / List of figures --- p.xviii / List of main abbreviations --- p.xx / Chapter Section I --- Introduction and Literature Review --- p.1 / Chapter Chapter 1 --- Introduction --- p.2 / Chapter Chapter 2 --- Literature Review of Medical Examination, Prediction model and Economic Evaluation in Silicosis --- p.7 / Chapter 2.1 --- The aims of this literature review --- p.7 / Chapter 2.2 --- Search strategies and selection criteria --- p.7 / Chapter 2.3 --- Searching results --- p.8 / Chapter 2.4 --- Critical appraisal criteria and quality of selected studies --- p.9 / Chapter 2.4.1 --- Critical appraisal criteria --- p.9 / Chapter 2.4.2 --- Quality of selected studies --- p.10 / Chapter 2.5 --- Overview of effectiveness of chest radiography in medical surveillance of silicosis for workers exposed to silica dust --- p.15 / Chapter 2.5.1 --- Occupational medical surveillance for workers exposed to silica dust --- p.15 / Chapter 2.5.2 --- Comparison of CT or HRCT and chest radiography --- p.16 / Chapter 2.5.3 --- Comparison of digital radiography (DR) and chest radiography --- p.17 / Chapter 2.5.4 --- Other tests to be relevant to silicosis diagnosis --- p.23 / Chapter 2.5.5 --- The effectiveness of chest radiography in medical surveillance and diagnosis of silicosis --- p.24 / Chapter 2.5.6 --- Comparison between the ILO Classification and the Chinese Diagnostic criteria of pneumoconiosis --- p.25 / Chapter 2.6 --- Overview of application of prediction model in silicosis and a review on methodology in prediction model --- p.32 / Chapter 2.6.1 --- Application of prediction model in occupational diseases --- p.32 / Chapter 2.6.2 --- Overview of application of predicting model in pneumoconiosis including silicosis in China in recent 10 years --- p.34 / Chapter 2.6.3 --- Development of prediction model and the applications from practical perspectives --- p.35 / Chapter 2.7 --- A review on economic evaluation in occupational diseases and the screening interval analyses --- p.42 / Chapter 2.7.1 --- An overview on economic evaluation in pneumoconiosis --- p.42 / Chapter 2.7.2 --- Overview of economic evaluation in occupational health and safety and screening interval analyses --- p.44 / Chapter 2.7.3 --- Overview for methodology of performing CEA --- p.45 / Chapter 2.8 --- Research gaps were found from this literature review --- p.52 / Chapter Section II --- Objectives and Methods --- p.53 / Chapter Chapter 3 --- General aims and objectives --- p.54 / Chapter 3.1 --- General aims --- p.54 / Chapter 3.2 --- Primary objectives --- p.54 / Chapter 3.3 --- Secondary objective --- p.54 / Chapter Chapter 4 --- Methodology and Research Plans --- p.55 / Chapter 4.1 --- Study Design --- p.55 / Chapter 4.2 --- The cohort --- p.55 / Chapter 4.3 --- Follow-up --- p.58 / Chapter 4.4 --- Data Collection --- p.58 / Chapter 4.4.1 --- Baseline information --- p.58 / Chapter 4.4.2 --- Diagnosis of silicosis and the verification --- p.59 / Chapter 4.4.3 --- Occupational hygiene monitoring data --- p.60 / Chapter 4.4.4 --- Cost data of medical examination --- p.61 / Chapter 4.5 --- Data Entry and Data Analyses --- p.62 / Chapter Section III --- Results and Discussions --- p.65 / Chapter Chapter 5 --- Description of the cohort --- p.66 / Chapter 5.1 --- Cohort recruitment --- p.66 / Chapter 5.2 --- Baseline characteristics --- p.69 / Chapter 5.3 --- Change of respirable silica dust concentration over time --- p.71 / Chapter 5.5 --- Occurrence of silicosis --- p.73 / Chapter 5.5.1 --- Basic characteristics of silicosis patients --- p.73 / Chapter 5.5.2 --- Trend of silicosis occurrence with calendar year --- p.78 / Chapter 5.5.3 --- Trend of silicosis occurrence with age of entering the cohort --- p.78 / Chapter 5.5.4 --- Trend of silicosis occurrence with cumulative exposure to respirable silica dust --- p.78 / Chapter 5.6 --- Survival distribution at different respirable silica dust exposure levels --- p.79 / Chapter 5.7 --- A summary of the results in Chapter 5 --- p.82 / Chapter Chapter 6 --- Agreement between the routine diagnosis of silicosis and the verified ‘new panel’ diagnosis --- p.83 / Chapter [Summary] --- p.83 / Chapter 6.1 --- Background --- p.85 / Chapter 6.2 --- Methodology --- p.86 / Chapter 6.2.1 --- The routine and the verified diagnosis of silicosis --- p.86 / Chapter 6.2.2 --- Inter-rater agreement --- p.87 / Chapter 6.3 --- Results --- p.89 / Chapter 6.3.1 --- Technical quality of chest X-ray films --- p.89 / Chapter 6.3.2 --- Inter-rater agreement amongst readers --- p.89 / Chapter 6.3.3 --- Agreement between the routine and the verified diagnosis of silicosis --- p.93 / Chapter 6.3.4 --- Agreement of the progression of silicosis between the routine and verified diagnosis --- p.95 / Chapter 6.4 --- Discussion --- p.97 / Chapter Chapter 7 --- Developing prediction model for determining the optimal intervals of chest radiographic examinations for workers at different risks of silicosis --- p.100 / Chapter [Summary] --- p.100 / Chapter 7.1 --- Background --- p.102 / Chapter 7.2 --- Methods --- p.104 / Chapter 7.2.1 --- The cohort and outcome determination --- p.104 / Chapter 7.2.2 --- Developing prediction models for silicosis --- p.107 / Chapter 7.2.3 --- Coding of Predictors --- p.113 / Chapter 7.3 --- Results --- p.118 / Chapter 7.3.1 --- Model Specifications --- p.118 / Chapter 7.3.2 --- Stepwise Selection and LASSO selection --- p.119 / Chapter 7.3.3 --- Model Validations: Stability and Optimism --- p.119 / Chapter 7.3.4 --- Model Presentations --- p.126 / Chapter 7.3.5 --- Cut-off point of follow up year for determining examination intervals --- p.130 / Chapter 7.4 --- Discussions --- p.136 / Chapter Chapter 8 --- Transition probabilities of multi-states for workers with silica dust exposure --- p.141 / Chapter [Summary] --- p.141 / Chapter 8.1 --- Background --- p.143 / Chapter 8.2 --- Methodology of multi-state model --- p.145 / Chapter 8.2.1 --- Survival data and multi-state model --- p.145 / Chapter 8.2.2 --- Markov model and transition states --- p.151 / Chapter 8.2.3 --- Model assessment --- p.153 / Chapter 8.3 --- Results --- p.154 / Chapter 8.3.1 --- Initial values specification and estimates of intensity matrix --- p.154 / Chapter 8.3.2 --- Transition probability matrix, mean sojourn times, and survival situation --- p.159 / Chapter 8.3.3 --- Observed and expected prevalence of each state for Model assessment --- p.163 / Chapter 8.4 --- Discussion --- p.165 / Chapter Chapter 9 --- Cost effectiveness analysis of occupational medical surveillance for workers exposed to silica dust --- p.168 / Chapter [Summary] --- p.168 / Chapter 9.1 --- Background --- p.170 / Chapter 9.2 --- Methodologies --- p.171 / Chapter 9.2.1 --- Costs and effectiveness --- p.171 / Chapter 9.2.2 --- Cost per silicosis identification estimation in the iron ore during 1964 to 2008 --- p.172 / Chapter 9.2.3 --- Cost effectiveness analysis in the Markov model --- p.173 / Chapter 9.3 --- Results --- p.176 / Chapter 9.3.1 --- Cost estimation and cost per silicosis identification in the iron ore cohort --- p.176 / Chapter 9.3.2 --- Cost effectiveness analysis in the Markov model --- p.181 / Chapter 9.4 --- Discussion --- p.187 / Chapter Section IV --- Conclusions and Implications --- p.191 / Chapter Chapter 10 --- Conclusions, implications, and recommendations --- p.192 / Chapter 10.1 --- Conclusions --- p.192 / Chapter 10.2 --- Implications and recommendations --- p.193 / Reference list --- p.195 / Chapter Appendix I --- Chest Radiographic Imaging of Different Diagnostic Criteria for Pneumoconiosis in China --- p.211 / Chapter Appendix II --- Diagnosis Stages among Different Diagnostic Criteria for Pneumoconiosis in China --- p.212 / Chapter Appendix III --- Publications in journals and international conferences during the PhD study --- p.213 / Chapter Supplement I --- Syntax for test proportionality of Cox model in R survival package and LASSO model in R penalized package --- p.215 / Chapter Supplement II --- Guideline of applying the prediction model in practice --- p.216 / Chapter Supplement III --- Syntax for multi-state model in R msm package --- p.221 / Chapter Supplement IV --- An example for cost estimation of adjusting inflation and exchanging --- p.222 / Chapter Supplement V --- Cost estimation of workers, suspected silicosis cases and silicosis patients in the iron ore during 1964 - 2008 --- p.223 / Chapter Supplement V (Continued) --- Cost estimation of workers, suspected silicosis cases and silicosis patients in the iron ore during 1964 - 2008 --- p.224 / Chapter Supplement VI --- Number of deaths for all cause of death in the iron ore cohort until 2008 --- p.225 / Chapter Supplement VII --- Decision tree of Markov model in the study --- p.226 / Chapter Supplement VII (Continued) --- Decision tree of Markov model in the study --- p.227

Objetivos: Avaliar a influência da exposição a fatores ambientais inalatórios durante a gravidez e o diagnóstico de dermatomiosite juvenil (DMJ). Métodos: Um estudo caso-controle incluiu 20 casos de DMJ e 56 controles, pareados por idade e sexo, residentes na região metropolitana de São Paulo. Através de um questionário foram obtidos os dados demográficos e os dados de exposição ambiental durante a gravidez: a exposição ocupacional (poeira causada por demolições, construções ou pedreiras, poeira de giz, tintas, verniz, vapor de combustível e fluídos de bateria), a existência de fontes de poluentes inalatórios próximas à residência da mãe e a exposição materna ao tabaco. As concentrações diárias de material particulado (PM10), dióxido de enxofre (SO2), dióxido de nitrogenio (NO2), ozônio (O3) e monóxido de carbono (CO) inalados foram avaliadas durante o período gestacional. Resultados: A exposição ocupacional materna a poeira de giz escolar e a resíduo volátil de gasolina ou diesel no grupo de DMJ foi significantemente maior comparada ao grupo controle (50% vs. 2,3%, p=0,004). Mães fumantes e exposição passiva ao cigarro na residência durante a gravidez foram significantemente maior no grupo de DMJ (20% vs. 1,7%, p=0,01; 35% vs. 16%, p=0,07, respectivamente). No modelo de regressão logística univariada, o fumo materno durante a gravidez, a exposição ocupacional a agentes inalados e a exposição ao CO troposférico no tercil mais elevado (3.2-5.4 ppm) no terceiro trimestre foram significantemente associados com DMJ (p < 0,05). Na análise multivariada, o fumo materno (OR=13,26, IC 95% 1,21-144,29, p=0,03), a exposição ocupacional (OR=35,39, IC 95%1,97-632,80, p=0,01) e a exposição ao CO (terceiro tercil) no terceiro trimestre de gestação (OR=12,21, IC 95%1,28- 115,96, p=0,03) permaneceram como fator de risco para DMJ. Conclusão: A exposição a poluentes inalatórios ambientais e fumaça de cigarro durante o desenvolvimento fetal podem contribuir para o aparecimento de DMJ / Objective: To evaluate the influence of exposures to inhaled environmental factors during pregnancy on juvenile dermatomyositis (JDM) diagnosis. Methods: A case-control study included 20 JDM and 56 healthy controls matched by age and gender residents in the metropolitan region of São Paulo city. A questionnaire assessed demographic data and environmental inhalation exposure during pregnancy (occupational exposure to demolition, chalk, construction and/or quarry dust, paints, varnish, fuel vapor and/or battery fluids, stationary sources of inhaled pollution near the mother\'s home and maternal tobacco exposure). Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) were evaluated throughout the gestational period. Results: Maternal occupational exposure to chalk dust/gasoline vapor in JDM group was significantly higher compared to controls (50% vs. 2. 3%, p=0.004). Smoking mothers and secondhand smoke exposure at home during pregnancy were significantly higher in JDM group (20% vs. 1.7%, p=0.01; 35% vs. 16%, p=0.07; respectively). In univariate logistic regression models, maternal smoking, occupational exposure to inhaled agents and the higher tertile of trospospheric CO (3.2-5.4 ppm) in the third trimester were significantly associated with JDM (p < 0.05). In multivariate analysis, smoking mother (OR=13.26, 95% CI 1.21-144.29, p=0.03), occupational exposure (OR=35.39, 95% CI 1.97-632.80, p=0.01) and CO (third tertile) exposure in the third trimester of gestation (OR=12.21, 95% CI 1.28-115.96, p=0.03) remained risk factors for JDM. Conclusion: Inhaled pollutants and tobacco smoking during fetal development may contribute to JDM

Objetivos: Avaliar a influência da exposição a fatores ambientais inalatórios durante a gravidez e o diagnóstico de dermatomiosite juvenil (DMJ). Métodos: Um estudo caso-controle incluiu 20 casos de DMJ e 56 controles, pareados por idade e sexo, residentes na região metropolitana de São Paulo. Através de um questionário foram obtidos os dados demográficos e os dados de exposição ambiental durante a gravidez: a exposição ocupacional (poeira causada por demolições, construções ou pedreiras, poeira de giz, tintas, verniz, vapor de combustível e fluídos de bateria), a existência de fontes de poluentes inalatórios próximas à residência da mãe e a exposição materna ao tabaco. As concentrações diárias de material particulado (PM10), dióxido de enxofre (SO2), dióxido de nitrogenio (NO2), ozônio (O3) e monóxido de carbono (CO) inalados foram avaliadas durante o período gestacional. Resultados: A exposição ocupacional materna a poeira de giz escolar e a resíduo volátil de gasolina ou diesel no grupo de DMJ foi significantemente maior comparada ao grupo controle (50% vs. 2,3%, p=0,004). Mães fumantes e exposição passiva ao cigarro na residência durante a gravidez foram significantemente maior no grupo de DMJ (20% vs. 1,7%, p=0,01; 35% vs. 16%, p=0,07, respectivamente). No modelo de regressão logística univariada, o fumo materno durante a gravidez, a exposição ocupacional a agentes inalados e a exposição ao CO troposférico no tercil mais elevado (3.2-5.4 ppm) no terceiro trimestre foram significantemente associados com DMJ (p < 0,05). Na análise multivariada, o fumo materno (OR=13,26, IC 95% 1,21-144,29, p=0,03), a exposição ocupacional (OR=35,39, IC 95%1,97-632,80, p=0,01) e a exposição ao CO (terceiro tercil) no terceiro trimestre de gestação (OR=12,21, IC 95%1,28- 115,96, p=0,03) permaneceram como fator de risco para DMJ. Conclusão: A exposição a poluentes inalatórios ambientais e fumaça de cigarro durante o desenvolvimento fetal podem contribuir para o aparecimento de DMJ / Objective: To evaluate the influence of exposures to inhaled environmental factors during pregnancy on juvenile dermatomyositis (JDM) diagnosis. Methods: A case-control study included 20 JDM and 56 healthy controls matched by age and gender residents in the metropolitan region of São Paulo city. A questionnaire assessed demographic data and environmental inhalation exposure during pregnancy (occupational exposure to demolition, chalk, construction and/or quarry dust, paints, varnish, fuel vapor and/or battery fluids, stationary sources of inhaled pollution near the mother\'s home and maternal tobacco exposure). Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) were evaluated throughout the gestational period. Results: Maternal occupational exposure to chalk dust/gasoline vapor in JDM group was significantly higher compared to controls (50% vs. 2. 3%, p=0.004). Smoking mothers and secondhand smoke exposure at home during pregnancy were significantly higher in JDM group (20% vs. 1.7%, p=0.01; 35% vs. 16%, p=0.07; respectively). In univariate logistic regression models, maternal smoking, occupational exposure to inhaled agents and the higher tertile of trospospheric CO (3.2-5.4 ppm) in the third trimester were significantly associated with JDM (p < 0.05). In multivariate analysis, smoking mother (OR=13.26, 95% CI 1.21-144.29, p=0.03), occupational exposure (OR=35.39, 95% CI 1.97-632.80, p=0.01) and CO (third tertile) exposure in the third trimester of gestation (OR=12.21, 95% CI 1.28-115.96, p=0.03) remained risk factors for JDM. Conclusion: Inhaled pollutants and tobacco smoking during fetal development may contribute to JDM

Wong, Yun Sze. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 142-162). / Abstracts in English and Chinese. / Abstract (in English) --- p.ii / Abstract (in Chinese) --- p.vi / Acknowledgement --- p.ix / Statement of Work --- p.x / Table of Contents --- p.xi / List of Tables --- p.xiv / List of Figures --- p.xvi / Glossary of Terms and Abbreviations --- p.xviii / Chapter Section I: --- Introduction --- p.1 / Chapter Chapter 1: --- General Overview of Asthma --- p.2 / Chapter 1.1 --- Asthma definition and its phenotype --- p.2 / Chapter 1.2 --- Asthma epidemiology and its prevalence in past decades --- p.4 / Chapter 1.3 --- Hygiene hypothesis and asthma development --- p.8 / Chapter 1.4 --- Asthma pathogenesis and innate immunity --- p.12 / Chapter 1.5 --- The environmental factors and genetic makeup in relation with asthma --- p.17 / Chapter Chapter 2: --- Study Plan and Obj ective --- p.21 / Chapter Section II: --- Literature Review --- p.24 / Chapter Chapter 3: --- Indoor Environmental factors of Asthma --- p.25 / Chapter 3.1 --- Overview of the indoor environmental factors --- p.25 / Chapter 3.2 --- House dust endotoxin --- p.27 / Chapter 3.2.1 --- Determinants of endotoxin exposure in home environment --- p.21 / Chapter 3.2.2 --- Protective role of endotoxin in allergy and asthma development --- p.29 / Chapter 3.2.3 --- Deleterious effect of endotoxin exposure in asthma: the dark side --- p.31 / Chapter 3.3 --- Allergen --- p.34 / Chapter 3.3.1 --- Allergens: an update --- p.34 / Chapter 3.3.2 --- Determinants of allergens in home environment --- p.35 / Chapter 3.3.3 --- Allergens avoidance: environmental intervention --- p.36 / Chapter 3.4 --- Nitrogen dioxide --- p.40 / Chapter 3.4.1 --- Determinants of indoor nitrogen dioxide and its relation with gas cooking --- p.40 / Chapter 3.4.2 --- The adverse effects of nitrogen dioxide on respiratory symptoms --- p.41 / Chapter 3.4.3 --- Reactive nitrogen species and nitrosative stress in asthma --- p.42 / Chapter Chapter 4: --- CD14 Single Nucleotide Polymorphisms and Asthma --- p.45 / Chapter 4.1 --- Overview of CD14 receptor --- p.45 / Chapter 4.2 --- Action of CD14 receptor in endotoxin response --- p.47 / Chapter 4.3 --- Relation of CD14 with asthma --- p.48 / Chapter 4.3.1 --- Associations between CD14 polymorphisms and asthma phenotypes --- p.48 / Chapter 4.3.2 --- Endotoxin switch concept: from gene to gene - environment --- p.52 / Chapter Section III: --- Study Core --- p.55 / Chapter Chapter 5: --- Methodology in indoor environment investigation and its result --- p.57 / Chapter 5.1 --- Study Population --- p.57 / Chapter 5.2 --- Home Visiting Protocol --- p.60 / Chapter 5.2.1 --- The International Study of Asthma and Allergies in Childhood (ISAAC) --- p.60 / Chapter 5.2.2 --- ISAAC questionnaire --- p.61 / Chapter 5.2.3 --- House dust collection procedures --- p.62 / Chapter 5.2.4 --- Indoor nitrogen dioxide measurements --- p.65 / Chapter 5.2.4.1 --- Ogawa passive sampler --- p.65 / Chapter 5.2.4.2 --- Preparation and measurement procedures --- p.66 / Chapter 5.2.4.3 --- Indoor nitrogen dioxide quantification --- p.67 / Chapter 5.3 --- House dust extraction --- p.69 / Chapter 5.4 --- House dust endotoxin measurement --- p.70 / Chapter 5.5 --- Allergen measurement --- p.72 / Chapter 5.6 --- Statistical Analysis --- p.75 / Chapter 5.7 --- Results --- p.77 / Chapter 5.7.1 --- Demographic data and subjects characteristics --- p.77 / Chapter 5.7.2 --- "Dust weight, endotoxin and allergen levels and their determinants in household" --- p.82 / Chapter 5.7.3 --- Indoor NO〕2levels and its determinant in household --- p.95 / Chapter 5.7.4 --- Associations between indoor environmental factors and respiratory health --- p.96 / Chapter 5.7.4.1 --- Clinical symptoms --- p.96 / Chapter 5.7.4.2 --- Exhaled NO levels --- p.101 / Chapter 5.7.4.3 --- Spirometric indices --- p.103 / Chapter Chapter 6： --- Methodology in genotyping CD14 polymorphisms and its result --- p.105 / Chapter 6.1 --- Study population --- p.105 / Chapter 6.2 --- Serum Total and allergen-specific IgE measurement --- p.106 / Chapter 6.3 --- CD14 Genotyping s --- p.107 / Chapter 6.3.1 --- Genotyping promoter SNPs ofCD14/-159 and -1359 --- p.107 / Chapter 6.3.2 --- Genotyping promoter SNP of CD14/-1619 --- p.109 / Chapter 6.3.3 --- Validation of genotyping by sequencing --- p.111 / Chapter 6.4 --- Statistical Analysis --- p.112 / Chapter 6.5 --- Results --- p.113 / Chapter 6.5.1 --- Subjects characteristics and clinical features. --- p.113 / Chapter 6.5.2 --- Associations between CD14 SNPs and asthma phenotypes --- p.114 / Chapter Chapter 7: --- Discussion --- p.120 / Chapter 7.1 --- Influence of indoor factors on asthmatic children --- p.120 / Chapter 7.2 --- CD14 polymorphisms in modifying asthma phenotypes --- p.135 / Chapter Chapter 8: --- Conclusion and Further Works --- p.138 / References --- p.141 / Appendix 1 Questionnaire / Appendix 2 Publications

Submitted by Rosina Valeria Lanzellotti Mattiussi Teixeira (rosina.teixeira@unisantos.br) on 2018-01-15T12:20:11Z No. of bitstreams: 1 Macerlane de Lira Silva.pdf: 2428419 bytes, checksum: c28794e7f59ddaa54f5dda87a02337be (MD5) / Made available in DSpace on 2018-01-15T12:20:12Z (GMT). No. of bitstreams: 1 Macerlane de Lira Silva.pdf: 2428419 bytes, checksum: c28794e7f59ddaa54f5dda87a02337be (MD5) Previous issue date: 2017-06-12 / Introduction: Birth weight is one of the main factors of neonatal morbidity, being determinant for survival conditions in early childhood. Studies have shown correlations between exposure to air pollution and low birth weight (LBW). Objective: To analyze the relationship between air pollution and LBW from the information contained in the Birth Information System that occurred in the city of São Paulo, SP, between 2011 and 2015. Method: The present ecological study with an individual, retrospective base. Data about air pollutants and climatic variables were obtained from Environment Company of the State of São Paulo (CETESB). For data analyses, it was used the software SPSS. Quantitative variables were presented in terms of their values (media) and dispersion (standard deviation) values and the qualitative variables were presented in terms of their absolute and relative values. To verify the association between birth weight (normal or LW), maternal age (aging rate), marital status, education, type of pregnancy, number of prenatal consultations, type of delivery, gender of the newborn it was used the Square QI-test. Aiming to verify the relationship between LW at birth and air pollution, it was used the logistic regression model, adjusted for mean humidity, minimum temperature, maternal schooling, maternal age, number of prenatal consultations, type of pregnancy and type of delivery. The level of significance was 5%. Results: During the study period, the results showed that 327,675 births were recorded in SINASC. From these, 31,161 (9.5%) were born with LW and 296,514 (90.5%) with adequate weight. It was observed a prevalence of males (51.1%), born with adequate gestational age (87.2%), by a cesarean delivery (54.0%), having the pregnant women attended 7 or more prenatal consultations (74,9%). The majority of mothers had 7 years or more of studies (86.4%). Data analysis revealed that mothers under 20 and over 35 years old had 1.15 (CI95%: 1.11-1.20) and 1.16 (CI95%: 1.12-1.20) more chances to have newborns with LW than mothers aged between 20 and 35 years, pregnant women who performed less than 7 prenatal visits had 1.16 (CI95%: 1.12-1.21), as did non-married pregnant-women presented 1.14 (CI95%: 1.11-1.18) times more of chances of having a new born with LW. Prematurity appears with a predictive value of birth with LW of 25.74 (CI95%: 25.04-26.46). Only SO2 had a significant effect with the low weight presented. For each increase of an interquartile at the level of SO2 within the three trimesters of gestation, an increase in the occurrence of LW of newborns. Conclusion: There are many deleterious health effects due to pollution, especially the exposure of women in the gestational period, leading to LWB. / Introdução: O peso ao nascer é um dos principais fatores de morbidades neonatais, sendo determinante para as condições de sobrevivência na primeira infância. Estudos revelam correlações entre a exposição a poluição do ar e Baixo Peso ao Nascer (BPN). Objetivo: Analisar a relação entre a poluição do ar e o BPN, a partir das informações contidas no Sistema de Informação de Nascimentos, ocorridos no município de São Paul/SP entre 2011 e 2015. Método: O presente estudo é do tipo ecológico de base individual, retrospectivo. Os dados de poluentes do ar e vaiáveis climáticas foram obtidos junto a Companhia Ambiental do Estado de São Paulo (CETESB). Para analise dos dados utilizou-se o software SPSS. As variáveis quantitativas foram apresentadas em termos de seus valores de tendência central (média) e de dispersão (desvio padrão) e as variáveis qualitativas foram apresentadas em termos de seus valores absolutos e relativos. Para verificação de associação entre peso ao nascer (normal ou BP), idade materna (faixa etária), estado civil, escolaridade, tipo de gravidez, número de consultas pré-natal, tipo de parto, sexo do RN foi utilizado o teste de Qui-quadrado. Visando a verificação da relação existente entre BP ao nascer e a poluição do ar, foi utilizado o modelo de regressão logística, ajustado por umidade média, temperatura mínima, escolaridade materna, idade materna, número de consultas pré-natal, tipo de gravidez e tipo de parto. O nível de significância foi de 5%. Resultados: No período de estudo, os resultados evidenciaram que foram registrados, no SINASC 327.675 nascimentos. Destes, 31.161 (9,5%) nasceram com BP e 296.514 (90,5%) com peso adequado. Observou-se maior ocorrência de RN do sexo masculino (51,1%), nascidos com idade gestacional adequada (87,2%), através de parto cesárea (54,0%), tendo as gestantes comparecido à 7 ou mais consultas pré-natais (74,9%). A maioria das mães, tinham 7 anos ou mais de estudos (86,4%). A análise dos dados revelou que mães com menos de 20 anos e mais de 35 anos tem, respectivamente, 1,15 (IC95%: 1,11-1,20) e 1,16 (IC95%: 1,12-1,20), mais chance ter recém-nascido com BP do que mães com idade entre 20 a 35 anos. Gestante que realizaram menos de 7 consultas pré-natais tem 1,16 (IC95%: 1,12-1,21) assim como, mulheres não casadas apresentam 1,14 (IC95%: 1,11-1,18) vezes mais chance de ter filho de BP. A prematuridade aparece com valor preditivo de nascimento com BP de 25,74 (IC95%: 25,04-26,46). Apenas o SO2 apresentou efeito significativo com o baixo peso apresentando, para cada aumento de um interquartil no nível de SO2 em cada um dos três trimestres de gestação. Observa-se, ainda, um aumento na ocorrência de Recém-nascido de BP. Conclusão: Muitos são os efeitos deletérios a saúde, decorrentes da poluição, em especial a exposição de mulheres no período gestacional, acarretando o BPN.

Objetivo: Avaliar os efeitos de diferentes níveis de exposição ambiental sobre a superfície ocular, por meio da análise histológica da superfície ocular e da avaliação de parâmetros clínicos. Métodos: Etapa 1: Foram selecionados 29 voluntários, em duas localidades diferentes: São Paulo (n=13) e Divinolândia (n=16). Foram avaliadas medidas individuais de exposição ao dióxido de Nitrogênio (NO2) atmosférico e a citologia de impressão de conjuntiva tarsal inferior. Avaliou-se a exposição individual ao NO2 por 7 dias consecutivos, usando um sistema de medida passivo. Foram coletados espécimes de citologia de impressão de conjuntiva tarsal inferior. Foram realizados comparações entre o número de células caliciformes e os níveis de NO2 entre os dois grupos e individualmente. Etapa 2: Foram avaliados 55 voluntários, residentes em São Paulo. Foram medidos os níveis de exposição individual ao NO2, e foi realizada uma avaliação subjetiva de sintomas oculares (OSDI e freqüência de sintomas de desconforto ocular); teste de Schirmer I, biomicroscopia, coloração com fluoresceína e rosa bengala, e medida do TRFL, que foram comparados posteriormente por meio de análise estatística. Resultados: Etapa 1: Os níveis de exposição individual ao NO2 em São Paulo(média=32,47 ± 9,83 g/m3) foram 68% mais altos do que em Divinolândia (média =19,33± 5,24 g/m3); (p = 0,005), e houve uma correlação entre o número de células caliciformes e os níveis de NO2 (=0,566, p=0,001), tendo sido observado um padrão dose-resposta relativo à exposição. Etapa 2: Houve associação entre os níveis de NO2 e os escores do OSDI (p<0,05), a freqüência de irritação ocular (p<0,05), e os valores do TRFL (p<0,05, = -0,316). Conclusões: Houve uma associação significativa entre exposição à poluição atmosférica e a hiperplasia de células caliciformes conjuntivais, sintomas de desconforto ocular e maior instabilidade do filme lacrimal. Observou-se uma repercussão tanto clínica quanto histológica da exposição a níveis mais elevados de NO2, o que sugere que essas medidas podem ser usadas como biomarcadores dos efeitos adversos da poluição atmosférica sobre a superfície ocular / The purpose of this study was to assess the effects of different levels of ambient air pollution on the ocular surface, combining determinations of individual exposure with clinical and histological parameters. Methods: Stage 1: A total of 29 volunteers from two locations - São Paulo (n=13) and Divinolândia (n=16) were selected. We assessed mean individual levels of NO2 exposure for 7 days, using a passive sampler. Impression cytology samples were obtained from inferior tarsal conjunctiva. Goblet cell counts and NO2 exposure level were compared between the two groups, and between individual values. Stage 2: A total of 55 volunteers, who lived in São Paulo, were selected. The mean individual levels of nitrogen dioxide (NO2) exposure were assessed, as in Stage 1. All subjects answered the Ocular Symptom Disease Index (OSDI) and a symptoms inventory. Subsequently, subjects underwent Schirmer I test, biomicroscopy, vital staining and tear break-up time (TBUT) assessment. OSDI scores, symptoms frequency and clinical data were compared to individual NO2 exposure values by statistical analysis. Results: Stage 1: The NO2 exposure levels were 68% higher for individuals living in São Paulo (mean = 32.47, SD = ± 9.83) than for those living in Divinolândia (mean 19.33, SD ± 5.24) (p = 0,005). There was a steady increase in goblet cell counts, proportional to NO2 exposure (=0.566, p=0.001). Stage 2: There was a significant association between NO2 levels and OSDI scores (p<0.05), reported ocular irritation (p<0.05) and TBUT (p<0.05, = -0.316). Conclusions: An association between exposure to higher levels of air pollution, goblet cell hyperplasia, ocular discomfort symptoms and tear film instability was detected; indicating that there are clinical and histological effects of NO2 exposure, and that these measurements may be used as biomarkers of the adverse effects of air pollution on the ocular surface

It is now generally acknowledged that particulate air pollution can cause respiratory symptoms and that indoor dust particles may be associated with mucous membrane irritation and odour annoyance. One reason for this may be that dust particles adsorb large quantities of gases and other volatile compounds. It is therefore important to be able to determine the chemical compounds adsorbed onto indoor dust particles. In this thesis, a new technique was developed that can analyse chemical compounds in indoor dust particles in a simple yet accurate way. In its basic configuration, it comprises a one stage thermal desorption oven, a gas flow cell with a miniaturized GC column, and a nitrogen-flushed photo diode array (PDA) detector for fast UV spectra recording. The dust sample is thermally desorbed in the oven and the released compounds are flushed onto the GC column by means of a carrier gas stream; the separated compounds are then registered by the PDA detector and identified by their characteristic gas-phase UV spectra. Using this set-up, a number of volatile organic as well as inorganic compounds were identified in indoor dust particles, e.g. nitric oxide, ammonia, hydrogen sulphide, pyridine, 2-furaldehyde, 2-methylfuran, and isoprene. Moreover, acrylate monomers were identified in dust samples from a secondary school with problems due to powdering floor polish. An instrumental set-up with higher performance was achieved by interfacing the gas flow cell to a capillary GC column. When airborne indoor dust samples were analysed by this system and by GC-MS under similar conditions of thermal desorption (150 °C) and GC separation, the two analytical systems were found to be complementary. GC-UV together with GC-MS was thus demonstrated to be considerably more powerful than GC-MS alone for the analysis of volatile organic compounds (VOC) in indoor dust. When airborne dust samples from damp (n=9) and control (n=9) residences were analysed for VOC and microorganisms, identifications made by culture and microscopy of the major moulds found, i.e. Aspergillus, Cladosporium and Penicillum, coincided with the identification of VOC known to be produced by these species. A number of additional VOC were also found, some of which may be irritating to the skin, eyes or respiratory tract if present at higher concentrations. Quantitative GC-UV analysis of indoor dust from 389 residences in Sweden showed that the VOC found at the highest concentrations were saturated aldehydes (C5-C10), furfuryl alcohol, 2,6-di-tert-butyl-4-methylphenol, 2-furaldehyde, and benzaldehyde. Alkenals were also found, notably 2-butenal (crotonaldehyde), 2-methyl-propenal (methacrolein), hexenal, heptenal, octenal, and nonenal. GC-UV was also applied (together with GC-MS) to determine VOC in dust from residences of 198 children with symptoms of asthma and/or allergy (cases) and from residences of 202 children without symptoms (controls). The mean concentration of nicotine was found to be significantly higher in dust from case residences, while the mean concentrations of hexane, nonanal, octane, 2-pentylfuran and tridecanol were significantly higher in dust from control residences. In a stepwise logistic regression model, nicotine, hexanal, furfuryl alcohol, nonane, butanol, and octenal showed increased relative risks, expressed as odds ratios comparing cases with controls. By contrast, benzaldehyde, nonanal, butenal, hexane, tridecanol, and pentylfuran showed decreased relative risks. These findings point to the possibility that not only environmental tobacco smoke but also other emissions in the indoor environment may be linked to the increased prevalence of asthma and/or allergy in children. It is concluded that GC-UV may be used as an alternative or complement to GC-MS for measuring chemicals in indoor dust, thus improving the survey and control of human exposure to particle-bound toxicants and other chemicals. / Copyright Agreement: Figure 3 included in the PDF file abowe is the exclusive property of SAGE Publications (http://www.sagepublications.com/), or its licensors and is protected by copyright and other intellectual property laws. The download of the file(s) is intended for the User's personal and noncommercial use. Any other use of the download of the Work is strictly prohibited. User may not modify, publish, transmit, participate in the transfer or sale of, reproduce, create derivative works (including coursepacks) from, distribute, perform, display, or in any way exploit any of the content of the file(s) in whole or in part. Permission may be sought for further use from Sage Publications Ltd, Rights and Permissions Department, 1 Oliver's Yard, 55 City Road, London EC1Y 1SP Fax: +44 (020) 7324-8600. By downloading the file(s), the User acknowledges and agrees to these terms.

Diss. (sammanfattning) Umeå : Umeå universitet, 2009. / Härtill 5 uppsatser. Även tryckt utgåva.

Diss. (sammanfattning) Umeå : Umeå universitet, 2010. / Härtill 4 uppsatser.

Benzene is an important toxic chemical in urban air and known human carcinogen released substantially by mobile sources. It's important to understand the spatial variation of benzene concentrations in order to understand exposures of susceptible sub-populations such as children and minority groups. Current monitoring networks use large and expensive air samplers that require electricity and restrict the location and number of samplers, not allowing for fine spatial resolution data. The goals of this study are to develop and evaluate protocols for passive sampling and analysis of ambient benzene concentrations, and conduct a pilot study investigating small-scale variations over an area where children are likely to be exposed. Protocols were developed for the use and analysis of the Radiello RAD130 passive sampler for field sampling over the spatial scale of a city park adjacent to an elementary school. A pilot study was conducted from 4/27/11-5/4/11, where 11 samplers were exposed for a seven day sampling period at the park. After sampler exposure, benzene concentrations were determined through solvent desorption followed by analysis using a Varian gas chromatograph with mass spectrometer. Co-location with the existing regulatory active sampler in the county and of two samplers at the same site was done to evaluate the accuracy and precision of the methods, respectively. Health risk estimates were calculated using risk assessment guidance from the U.S. and California Environmental Protection Agencies. Concentrations over the park were found to range from 0.23 0.34 µg m^-3 with a coefficient of variation of 11%. A relative percent difference of 3% was found between the co-located sampler and the active sampler, and a 14% relative percent difference was found between the two duplicate samplers. The variation in health risk from concentration variation due to sampler placement contributed less to the overall uncertainty in the estimates than the uncertainty built in to the calculation parameters of inhalation unit risk and cancer potency factor, as estimated by the U.S. EPA and California EPA, respectively. These results suggest that the exposure of an individual at the park would be characterized sufficiently for standard health risk analysis through the use of one sampler. Further research is necessary into using passive samplers over both the same spatial scale in other areas, as well as on a larger scale to determine intra-urban benzene concentration distributions. The protocols developed here will be used in a future planned study of benzene concentration measurements to characterize neighborhood-scale exposures in Hillsborough County.