RESUMO
Background: The characterisation of individual exposure to air pollution in urban scenarios is a challenge in environmental epidemiological studies. We investigated if the city's pollution monitoring stations over or underestimate the exposure of individuals depending on their socioeconomic conditions and daily commuting times. Methods: The amount of black carbon accumulated in the lungs of 604 deceased who underwent autopsy in São Paulo was considered as a proxy for PM10. The concentrations of PM10 in the residence of the deceased were estimated by interpolating an ordinary kriging model. These two-exposure metrics allowed us to construct an environmental exposure misclassification index ranging from -1 to 1. The association between the index and daily commuting, socioeconomic context index (GeoSES), and street density as predictors was assessed by means of a multilevel linear regression model. Findings: With a decrease of 0.1 units in GeoSES, the index increases, on average, by 0.028 units and with an increase of 1 h in daily commuting, the index increases, on average, by 0.022 units indicating that individual exposure to air pollution is underestimated in the lower GeoSES and in people with many hours spent in daily commuting. Interpretation: Reduction of health consequences of air pollution demands not only alternative fuel and more efficient mobility strategies, but also should include profound rethink of cities. Funding: São Paulo Research Foundation (FAPESP-13/21728-2) and National Council for Scientific and Technological Development (CNPq-304126/2015-2, 401825/2020-5).
RESUMO
Residuals are frequently used to evaluate the validity of the assumptions of statistical models and may also be employed as tools for model selection. For standard (normal) linear models, for example, residuals are used to verify homoscedasticity, linearity of effects, presence of outliers, normality and independence of the errors. Similar uses may be envisaged for three types of residuals that emerge from the fitting of linear mixed models. We review some of the residual analysis techniques that have been used in this context and propose a standardization of the conditional residual useful to identify outlying observations and clusters. We illustrate the procedures with a practical example.
Assuntos
Modelos Lineares , Estudos Longitudinais , Pré-Escolar , Placa Dentária/prevenção & controle , Humanos , Escovação Dentária/métodosRESUMO
The determination of the post mortem interval (PMI) is important in many instances, especially in criminal investigations. So, we consider post mortem tomographic evaluation of intra-cardiac hypostasis as an additional method for such purpose. Tomographic images of the thoraces of the corpses of 23 patients who died in a hospital were obtained sequentially at one hour intervals to allow the analysis of changes in density due to hypostasis over time. The right and left atria, which appear in the mediastinal window, were selected for measurements of the average organ density. An exponential model was used to relate the difference between the attenuation coefficients of the anterior segment of the right atrium and the posterior segment of the left atrium to the PMI. In spite of the large variability of the data from this observational study, PMI estimates during the first 12 h after death can be estimated with a margin of error smaller than two hours. The results suggest that the difference between the attenuation coefficients stabilizes around 12 h post mortem and may be used as an additional method to estimate the PMI.