Relationship between Enviromental Factors and Infant Mortality in Madrid 1986 – 1997

1. Relationship between Enviromental Factors and Infant Mortality in Madrid 1986 – 1997 Julio Díaz Jiménez (1), César López Santiago (1), Cristina Linares Gil (1) Ricardo García Herrera (2) (1) Centro Universitario de Salud Pública. Madrid. (2) Facultad de Ciencias Físicas. Universidad Complutense de Madrid.

2. OBJECTIVE To analyse the effects of extreme temperatures and main air pollutants on daily mortalityof children up to 10 years of age. Madrid (Spain) since 1986 to 1997.

3. MATERIALS & METHODS • DEPENDENT VARIABLE: • Daily mortality data from1/01/1986 to 31/12/1997: children residents in Madrid under ten years of age. • All mortality causes were considered, except accidents ICD-9 (1-799). • Age groups have considered: • from 0 to 9 years old • less than 1 year old • from 1 to 5 years old • from 5 to 9 years old.

4. MATERIALS & METHODS • INDEPENDENT VARIABLES: • Daily temperature: average, maximum and minimum • Relative Humidity • Air pollution: daily average concentrations of SO2, NOx, TSP, NO2, O3) . • CONTROL VARIABLES: • Influenza epidemics. • Day of the week

5. MATERIALS & METHODS • Poisson regression was used to model the association between infant mortality in Madrid and the environmental risk factor considered. • The independent variables impact on mortality was assessed through the atributable risk (AR), with the assumption that the whole population could be exposed to its effect. • Attributable risk can be easily computed as follows: AR = (RR-1)/RR (23), where RR is the relative risk obtained by Poisson models. • The analysis was carried out using statistic pack S-Plus 2000.

6. Descriptive statistics for children mortality, air pollution and meteorological variables series

7. RESULTS Lags in which are established significant associations between the children sample (0-9 years old) mortality and the independent variables (outcome of the pre-whitening series residuals CCF analysis).

8. RESULTS Poisson Regression Models for Children (0-9 years old) mortality and air pollutants.

9. 2,2 2,0 1,8 1,6 1,4 1,2 1,0 ,8 ,6 ,4 0 20 40 60 80 100 120 140 160 10 30 50 70 90 110 130 150 TSP concentration (/m3) RESULTS Scatter-plot of TSP concentration and mortality in the group of 0-9 years old. Daily mortality

10. 1,4 1,2 1,0 Daily mortality in the group of 0-9 years old ,8 ,6 ,4 ,2 0 4 8 12 16 20 24 28 32 36 40 2 6 10 14 18 22 26 30 34 38 42 Maximun Temperature (ºC) RESULTS Scatter-plot of Tmax and mortality in the group of 0-9 years old.

11. V-SHAPED RELATIONS Scatter-plot of TSP concentration and mortality for the whole population in Madrid (same period) 120 115 110 105 mortality 100 95 causes 90 All 85 80 75 70 0 4 8 12 16 20 24 28 32 36 40 44 48 2 6 10 14 18 22 26 30 34 38 42 46 50 Maximum daily temperature (ºC)

12. RESULTS Statistically significant variables. Poisson Regression for all the variables considered and mortality in the group of 0-9 years old. * RR for an increase of 25 micg/m3 ** RR for each degree of Tmax under 30ºC. *** RR for each 1% that realative humidity increases.

13. 1,4 1,3 1,2 1,1 1,0 ,9 Daily mortality in the group of 0-9 years old ,8 ,7 ,6 ,5 ,4 0 2 4 6 8 10 12 14 16 18 20 22 1 3 5 7 9 11 13 15 17 19 21 Daily Tmax. 7 days lag. RESULTS Scatter Plot Diagram for Tmax lagged 7 days with mortality in winter.

14. RESULTS Extremely cold days influence on mortality of the different children age groups considered. * for each degree in which daily Tmax is under 6ºC.

15. MAIN CONCLUSIONS • 1. TSP presents an association with mortality in the very short term, while SO2 and NOx present the association lagged one day. • 2.There is no association found between mortality and troposphere ozone. • 3. The maximum daily temperature shows a significant relationship with child mortality, but not the minimum daily temperature.