Air pollution and health: bridging the gap from sources to health outcomes: conference summary

Air Pollution and Health: Bridging the Gap from Sources to Health Outcomes, an international specialty conference sponsored by the American Association for Aerosol Research, was held to address key uncertainties in our understanding of adverse health effects related to air pollution and to integrate and disseminate results from recent scientific studies that cut across a range of air pollution-related disciplines. The Conference addressed the science of air pollution and health within a multipollutant framework (herein "multipollutant" refers to gases and particulate matter mass, components, and physical properties), focusing on five key science areas: sources, atmospheric sciences, exposure, dose, and health effects. Eight key policy-relevant science questions integrated across various parts of the five science areas and a ninth question regarding findings that provide policy-relevant insights served as the framework for the meeting. Results synthesized from this Conference provide new evidence, reaffirm past findings, and offer guidance for future research efforts that will continue to incrementally advance the science required for reducing uncertainties in linking sources, air pollutants, human exposure, and health effects. This paper summarizes the Conference findings organized around the science questions. A number of key points emerged from the Conference findings. First, there is a need for greater focus on multipollutant science and management approaches that include more direct studies of the mixture of pollutants from sources with an emphasis on health studies at ambient concentrations. Further, a number of research groups reaffirmed a need for better understanding of biological mechanisms and apparent associations of various health effects with components of particulate matter (PM), such as elemental carbon, certain organic species, ultrafine particles, and certain trace elements such as Ni, V, and Fe(II), as well as some gaseous pollutants. Although much debate continues in this area, generation of reactive oxygen species induced by these and other species present in air pollution and the resulting oxidative stress and inflammation were reiterated as key pathways leading to respiratory and cardiovascular outcomes. The Conference also underscored significant advances in understanding the susceptibility of populations, including the role of genetics and epigenetics and the influence of socioeconomic and other confounding factors and their synergistic interactions with air pollutants. Participants also pointed out that short-and long-term intervention episodes that reduce pollution from sources and improve air quality continue to indicate that when pollution decreases so do reported adverse health effects. In the limited number of cases where specific sources or PM2.5 species were included in investigations, specific species are often associated with the decrease in effects. Other recent advances for improved exposure estimates for epidemiological studies included using new technologies such as microsensors combined with cell phone and integrated into real-time communications, hybrid air quality modeling such as combined receptor-and emission-based models, and surface observations used with remote sensing such as satellite data.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Basic assistance for mental health in Northeast Brazil

Introduction: Brazilian northeast region is historically affected by socioeconomic problems that made this region more needful for strategies regarding to psychiatric disorders assistance. Methods: This study includes original analysis based on data of secondary level health assistance, extracted from Brazil's Hospitalar Information System, Basic Assistance Information System and Brazilian Institute of Geographic and Statistics. Results: Between 2008 and 2010, more than two hundred million dollars were spent by Brazilian federal government to achieve better quality in the assistance for mental health in Northeast. The service network responsible for the treatment of mental disorders in primary care involves a wide range of professionals and establishments. Conclusion: In northeastern Brazil, socioeconomic and geographic conditions contribute to a particular state of vulnerability for the development of psychopathologies. The association of primary care and an integrated network of public health, however, have improved the attention to mental disordersin this region.

Parent psychopathology and offspring mental disorders: results from the WHO World Mental Health Surveys

Background Associations between specific parent and offspring mental disorders are likely to have been overestimated in studies that have failed to control for parent comorbidity. Aims To examine the associations of parent with respondent disorders. Method Data come from the World Health Organization (WHO) World Mental Health Surveys (n = 51 507). Respondent disorders were assessed with the Composite International Diagnostic Interview and parent disorders with informant-based Family History Research Diagnostic Criteria interviews. Results Although virtually all parent disorders examined (major depressive, generalised anxiety, panic, substance and antisocial behaviour disorders and suicidality) were significantly associated with offspring disorders in multivariate analyses, little specificity was found. Comorbid parent disorders had significant sub-additive associations with offspring disorders. Population-attributable risk proportions for parent disorders were 12.4% across all offspring disorders, generally higher in high- and upper-middle-than low-/lower-middle-income countries, and consistently higher for behaviour (11.0-19.9%) than other (7.1-14.0%) disorders. Conclusions Parent psychopathology is a robust non-specific predictor associated with a substantial proportion of offspring disorders.