London time series: mortality and ozone
Creators: name: S. Stanley Young
name: You, Cheng
Publisher: name: F1000Research
Year: 2016

description: London Time Series: Mortality and Ozone<br>S. Stanley Young, genetree@bellsouth.net; Cheng You, cheng1you@gmail.com<br> <br>C1<br>In November of 1952 there was an inversion over London trapping smoke that created a dense smog. Analysis of death data showed that there were thousands of excess deaths over a short period of time. The great London smog has inspired considerable research.<br> <br>C2<br>One of the air components with claimed health effects is ozone. The left figure gives some of the health effects of ozone. It is considered to be causal of acute deaths by the US Environmental Protection Agency. Recently the safe level was changed from 0.075 ppm to 0.070 ppm. The EPA also certifies in room air cleaners that generate ozone. The in room safe level of ozone is given as 0.200 ppm.<br> <br>C3<br>Given are the steps used in Local Control analysis. Covariate variables are selected and used to cluster the observations in a data set. In our case we start with data taken from Bhaskaran et al. International Journal of Epidemiology 2013;42:1187–1195 doi:10.1093/ije/dyt092. We have 1826 daily values for mortality, ozone and weather variables. The records are clustered into 35 clusters and linear regression, mortality versus ozone, is computed within each cluster. The LR intercept and slope are appended to each record in the data set. Attention is directed to the LR slopes. Are the random and centered at zero, i.e. no effect, or can they be considered fixed effects, predictable from the covariates.<br> <br>C4<br>Both mortality and ozone have very strong seasonal effects. Note that the two time series are essentially completely out of phase. As ozone goes up in the summer, deaths go down. The red line in each figure is a moving median fit to the data.<br> <br>C5<br>Our thinking is that acute deaths are due to some local-in-time effects. Literature suggest that local effects can be on the day in question or the previous day. Deviations were computed for each of mortality and ozone from their time series smoothers (moving median). Deviations from a time series smoother were also computed for weather variables.<br> <br>C6<br>In Local Control analysis, variables need to be selected for clustering the data set. Step-wise regression was used for variable selection. Note that ozone is not used in the clustering so it is not allowed to enter into the step-wise regression model. It is noteworthy that neither ozone or the time series smoother for ozone are statistically significant after temperature and relative humidity are entered into the model. The variables selected for the clustering of the data set were D Temp-MM (deviation of temperature from its moving median time series smoother), D Temp -1 (deviation of temperature from its time series smoother lagged by one day) and D RelH-1 (deviation of relative humidity from its time series smoother lagged by one day)<br> <br>C7<br>Given in the histogram is the distribution of the 35 regression slopes. Note that they center at zero.<br> <br>C8<br>The p-values for the 35 slopes are plotted against their expectations. The fact that they track their expectations, the dot dash line, indicates that the variation of the slopes is consistent with randomness.<br> <br>C9<br>An additional check on the slopes is to append them to the original data and compute a recursive partitioning analysis. We are interested in two things. Are the slopes affected by ozone level? Are the slopes predicted by the covariates. The slopes are, in fact, predictable from weather variables. The first split with a very small p-value, 10^-43, points to yesterday’s jump in temperature. A jump in yesterday’s relative humidity also is predictive of the mortality/ozone slope.<br> <br>C10<br>Analysis of the original data (before deviations are computed) gives a negative correlation between mortality and ozone. This negative correlation is usually ignored by environmental epidemiologists. Our analysis finds no association between mortality deviations and ozone deviations. The Local Control analysis via clustering should remove the effects of covariates. We do find that the mortality deviations /ozone deviations regression slopes are a function of weather variables.<br> <br><br><br>