London Hybrid Exposure Model: Improving Human Exposure Estimates to NO2 and PM2.5 in an Urban Setting.

Here we describe the development of the London Hybrid Exposure Model (LHEM), which calculates exposure of the Greater London population to outdoor air pollution sources, in-buildings, in-vehicles, and outdoors, using survey data of when and where people spend their time. For comparison and to estimate exposure misclassification we compared Londoners LHEM exposure with exposure at the residential address, a commonly used exposure metric in epidemiological research. In 2011, the mean annual LHEM exposure to outdoor sources was estimated to be 37% lower for PM2.5 and 63% lower for NO2 than at the residential address. These decreased estimates reflect the effects of reduced exposure indoors, the amount of time spent indoors (∼95%), and the mode and duration of travel in London. We find that an individual's exposure to PM2.5 and NO2 outside their residential address is highly correlated (Pearson's R of 0.9). In contrast, LHEM exposure estimates for PM2.5 and NO2 suggest that the degree of correlation is influenced by their exposure in different transport modes. Further development of the LHEM has the potential to increase the understanding of exposure error and bias in time-series and cohort studies and thus better distinguish the independent effects of NO2 and PM2.5

Contribution of smoking and air pollution exposure in urban areas to social differences in respiratory health

<p>Abstract</p> <p>Background</p> <p>Socio-economic status, smoking, and exposure to increased levels of environmental air pollution are associated with adverse effects on respiratory health. We assessed the contribution of occupational exposures, smoking and outdoor air pollution as competing factors for the association between socio-economic status and respiratory health indicators in a cohort of women from the Ruhr area aged 55 at the time of investigation between 1985 and 1990.</p> <p>Methods</p> <p>Data of 1251 women with spirometry and complete questionnaire information about respiratory diseases, smoking and potential confounders were used in the analyses. Exposure to large-scale air pollution was assessed with data from monitoring stations. Exposure to small-scale air pollution was assessed as traffic-related exposure by distance to the nearest major road. Socio-economic status was defined by educational level. Multiple regression models were used to estimate the contribution of occupational exposures, smoking and outdoor air pollution to social differences in respiratory health.</p> <p>Results</p> <p>Women with less than 10 years of school education in comparison to more than 10 years of school education were more often occupationally exposed (16.4% vs. 10.1%), smoked more often (20.3% vs. 13.9%), and lived more often close to major roads (26.0% vs. 22.9%). Long-term exposure to increased levels of PM₁₀was significantly associated with lower school education. Women with low school education were more likely to suffer from respiratory symptoms and had reduced lung function. In the multivariate analysis the associations between education and respiratory health attenuated after adjusting for occupational exposure, smoking and outdoor air pollution. The crude odds ratio for the association between the lung function indicator FEV₁less than 80% of predicted value and educational level (<10 years vs. >10 years of school education) was 1.83 (95% CI: 1.22–2.74). This changed to 1.56 (95% CI: 1.03–2.37) after adjusting for occupational exposure, smoking and outdoor air pollution.</p> <p>Conclusion</p> <p>We found an association between socio-economic status and respiratory health. This can partly be explained by living conditions indicated by occupational exposure, smoking behaviour and ambient air pollution. A relevant part of the social differences in respiratory health, however, remained unexplained.</p

A comparison of self reported air pollution problems and GIS-modeled levels of air pollution in people with and without chronic diseases

<p>Abstract</p> <p>Objective</p> <p>To explore various contributors to people's reporting of self reported air pollution problems in area of living, including GIS-modeled air pollution, and to investigate whether those with respiratory or other chronic diseases tend to over-report air pollution problems, compared to healthy people.</p> <p>Methods</p> <p>Cross-sectional data from the Oslo Health Study (2000–2001) were linked with GIS-modeled air pollution data from the Norwegian Institute of Air Research. Multivariate regression analyses were performed. 14 294 persons aged 30, 40, 45, 60 or 75 years old with complete information on modeled and self reported air pollution were included.</p> <p>Results</p> <p>People who reported air pollution problems were exposed to significantly higher GIS-modeled air pollution levels than those who did not report such problems. People with chronic disease, reported significantly more air pollution problems after adjustment for modeled levels of nitrogen dioxides, socio-demographic variables, smoking, depression, dwelling conditions and an area deprivation index, even if they had a non-respiratory disease. No diseases, however, were significantly associated with levels of nitrogen dioxides.</p> <p>Conclusion</p> <p>Self reported air pollution problems in area of living are strongly associated with increased levels of GIS-modeled air pollution. Over and above this, those who report to have a chronic disease tend to report more air pollution problems in area of living, despite no significant difference in air pollution exposure compared to healthy people, and no associations between these diseases and NO₂. Studies on the association between self reported air pollution problems and health should be aware of the possibility that disease itself may influence the reporting of air pollution.</p

ICE COLD ERIC – International collaborative effort on chronic obstructive lung disease: exacerbation risk index cohorts – Study protocol for an international COPD cohort study

<p>Abstract</p> <p>Background</p> <p>Chronic Obstructive Pulmonary Disease (COPD) is a systemic disease; morbidity and mortality due to COPD are on the increase, and it has great impact on patients' lives. Most COPD patients are managed by general practitioners (GP). Too often, GPs base their initial assessment of patient's disease severity mainly on lung function. However, lung function correlates poorly with COPD-specific health-related quality of life and exacerbation frequency. A validated COPD disease risk index that better represents the clinical manifestations of COPD and is feasible in primary care seems to be useful. The objective of this study is to develop and validate a practical COPD disease risk index that predicts the clinical course of COPD in primary care patients with GOLD stages 2–4.</p> <p>Methods/Design</p> <p>We will conduct 2 linked prospective cohort studies with COPD patients from GPs in Switzerland and the Netherlands. We will perform a baseline assessment including detailed patient history, questionnaires, lung function, history of exacerbations, measurement of exercise capacity and blood sampling. During the follow-up of at least 2 years, we will update the patients' profile by registering exacerbations, health-related quality of life and any changes in the use of medication. The primary outcome will be health-related quality of life. Secondary outcomes will be exacerbation frequency and mortality. Using multivariable regression analysis, we will identify the best combination of variables predicting these outcomes over one and two years and, depending on funding, even more years.</p> <p>Discussion</p> <p>Despite the diversity of clinical manifestations and available treatments, assessment and management today do not reflect the multifaceted character of the disease. This is in contrast to preventive cardiology where, nowadays, the treatment in primary care is based on patient-specific and fairly refined cardiovascular risk profile corresponding to differences in prognosis. After completion of this study, we will have a practical COPD-disease risk index that predicts the clinical course of COPD in primary care patients with GOLD stages 2–4. In a second step we will incorporate evidence-based treatment effects into this model, such that the instrument may guide physicians in selecting treatment based on the individual patients' prognosis.</p> <p>Trial registration</p> <p>ClinicalTrials.gov Archive NCT00706602</p

Impacts of highway traffic exhaust in alpine valleys on the respiratory health in adults: a cross-sectional study

BACKGROUND: Most studies having shown respiratory health effects from traffic exhaust were conducted in urban areas with a complex mixture of air pollution sources. This study has investigated the potential impact of traffic exhaust on respiratory symptoms among adults living along a Swiss alpine highway corridor, where traffic exhaust from the respective trans-Alpine highway is the predominant source of air pollution. METHODS: In summer 2005, we recruited 1839 adults aged 15 to 70 from a random sample of 10 communities along the Swiss alpine highway corridors. Subjects answered a questionnaire on respiratory health (asthmatic and bronchitic symptoms), risk factors, and potential confounding variables. We used logistic regression models to assess associations between respiratory symptoms and traffic exposure being defined a) as living within 200 m of the highway, and b) as a bell-shaped function simulating the decrease of pollution levels with increasing distance to the highway. RESULTS: Positive associations were found between living close to a highway and wheezing without cold (OR = 3.10, 95%-CI: 1.27-7.55) and chronic cough (OR = 2.88, 95%-CI: 1.17-7.05). The models using a bell-shaped function suggested that symptoms reached background levels after 400-500 m from the highway. The association with chronic cough was driven by a subgroup reporting hay fever or allergic rhinitis. CONCLUSIONS: Highway traffic exhaust in alpine highway corridors, in the absence of other industrial sources, showed negative associations with the respiratory health of adults, higher than those previously found in urban areas

Pregnancy related anxiety and general anxious or depressed mood and the choice for birth setting:A secondary data-analysis of the DELIVER study

BACKGROUND: In several developed countries women with a low risk of complications during pregnancy and childbirth can make choices regarding place of birth. In the Netherlands, these women receive midwife-led care and can choose between a home or hospital birth. The declining rate of midwife-led home births alongside the recent debate on safety of home births in the Netherlands, however, suggest an association of choice of birth place with psychological factors related to safety and risk perception. In this study associations of pregnancy related anxiety and general anxious or depressed mood with (changes in) planned place of birth were explored in low risk women in midwife-led care until the start of labour. METHODS: Data (n = 2854 low risk women in midwife-led care at the onset of labour) were selected from the prospective multicenter DELIVER study. Women completed the Pregnancy Related Anxiety Questionnaire-Revised (PRAQ-R) to assess pregnancy related anxiety and the EuroQol-6D (EQ-6D) for an anxious and/or depressed mood. RESULTS: A high PRAQ-R score was associated with planned hospital birth in nulliparous (aOR 1.92; 95% CI 1.32–2.81) and parous women (aOR 2.08; 95% CI 1.55–2.80). An anxious or depressed mood was associated with planned hospital birth (aOR 1.58; 95% CI 1.20–2.08) and with being undecided (aOR 1.99; 95% CI 1.23–2.99) in parous women only. The majority of women did not change their planned place of birth. Changing from an initially planned home birth to a hospital birth later in pregnancy was, however, associated with becoming anxious or depressed after 35 weeks gestation in nulliparous women (aOR 4.17; 95% CI 1.35–12.89) and with pregnancy related anxiety at 20 weeks gestation in parous women (aOR 3.91; 95% CI 1.32–11.61). CONCLUSION: Low risk women who planned hospital birth (or who were undecided) more often reported pregnancy related anxiety or an anxious or depressed mood. Women who changed from home to hospital birth during pregnancy more often reported pregnancy related anxiety or an anxious or depressed mood in late pregnancy. Anxiety should be adequately addressed in the process of informed decision-making regarding planned place of birth in low risk women

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC