Comparing meta-analysis and ecological-longitudinal analysis in time-series studies. A case study of the effects of air pollution on mortality in three Spanish cities.
OBJECTIVE
The objective of this paper is to introduce a different approach, called the ecological-longitudinal, to carrying out pooled analysis in time series ecological studies. Because it gives a larger number of data points and, hence, increases the statistical power of the analysis, this approach, unlike conventional ones, allows the complementation of aspects such as accommodation of random effect models, of lags, of interaction between pollutants and between pollutants and meteorological variables, that are hardly implemented in conventional approaches.


METHODS
The approach is illustrated by providing quantitative estimates of the short-term effects of air pollution on mortality in three Spanish cities, Barcelona, Valencia and Vigo, for the period 1992-1994. Because the dependent variable was a count, a Poisson generalised linear model was first specified. Several modelling issues are worth mentioning. Firstly, because the relations between mortality and explanatory variables were non-linear, cubic splines were used for covariate control, leading to a generalised additive model, GAM. Secondly, the effects of the predictors on the response were allowed to occur with some lag. Thirdly, the residual autocorrelation, because of imperfect control, was controlled for by means of an autoregressive Poisson GAM. Finally, the longitudinal design demanded the consideration of the existence of individual heterogeneity, requiring the consideration of mixed models.


RESULTS
The estimates of the relative risks obtained from the individual analyses varied across cities, particularly those associated with sulphur dioxide. The highest relative risks corresponded to black smoke in Valencia. These estimates were higher than those obtained from the ecological-longitudinal analysis. Relative risks estimated from this latter analysis were practically identical across cities, 1.00638 (95% confidence intervals 1.0002, 1.0011) for a black smoke increase of 10 microg/m(3) and 1.00415 (95% CI 1.0001, 1.0007) for a increase of 10 microg/m(3) of sulphur dioxide. Because the statistical power is higher than in the individual analysis more interactions were statistically significant, especially those among air pollutants and meteorological variables.


CONCLUSIONS
Air pollutant levels were related to mortality in the three cities of the study, Barcelona, Valencia and Vigo. These results were consistent with similar studies in other cities, with other multicentric studies and coherent with both, previous individual, for each city, and multicentric studies for all three cities.
Saez
M
M
Statistics and Econometrics, Department of Economics, University of Girona, Spain. msaez@gnomics.udg.es
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D000393:Air Pollutants / Q000009:adverse effects; D000397:Air Pollution / Q000009:adverse effects*; D006801:Humans; D008137:Longitudinal Studies; D015201:Meta-Analysis as Topic; D009026:Mortality; D015337:Multicenter Studies as Topic; D016012:Poisson Distribution; D012906:Smoke / Q000009:adverse effects; D013030:Spain / Q000453:epidemiology; D013458:Sulfur Dioxide / Q000009:adverse effects; D013696:Temperature; D014504:Urban Health / Q000706:statistics & numerical data*
D000393:Air Pollutants; D012906:Smoke; D013458:Sulfur Dioxide