Air pollution modelling for birth cohorts: a time-space regression model

Proietti, Elena; Delgado-Eckert, Edgar; Vienneau, Danielle; Stern, Georgette; Tsai, Ming-Yi; Latzin, Philipp; Frey, Urs; Röösli, Martin

doi:10.1186/s12940-016-0145-9

Environmental Health

Table 1 Final model for the rural region

From: Air pollution modelling for birth cohorts: a time-space regression model

Variables	Percentile			Estimate per IQR^a	95 % CI lower	95 % CI upper	Cumulative Adj. R²
Variables	25	50	75	Estimate per IQR^a	95 % CI lower	95 % CI upper	Cumulative Adj. R²
Total length of major roads in 100 m buffer * season^b	0	294	563	−0.363	−0.382	−0.345	0.278
Vehicles in 50 m buffer N	67068	862600	1730503	0.146	0.141	0.150	0.334
High density residential land use in 200 m buffer percent area	0	0	0	0.410	0.389	0.430	0.372
Log (NO₂ from AQM Payerne) log(NO ₂ concentration)	2.28	2.62	2.98	0.250	0.239	0.262	0.406
Log (NO₂ from dispersion model) log(NO ₂ concentration)	2.94	3.08	3.21	0.028	0.022	0.035	0.510
Total length of major roads in 100 m buffer m	0	197	238	0.474	0.456	0.492	0.563
Season (summer = 1, mid-season = 2, winter = 3)^b	1	2	3	0.181	0.158	0.203	0.578
Sqrt(Traffic in the nearest road) sqrt(N)	0.0	12.5	67.3	0.098	0.092	0.104	0.591
Industrial land use in 300 m buffer percent area	0	0	0	0.321	0.300	0.342	0.603
Population in 100 m buffer N	13.5	103.3	156.1	0.051	0.045	0.057	0.611
Linear time trend year	2001.7	2004.3	2007.1	0.529	0.499	0.558	0.614
Linear time trend ^2 (year^2)	2001.7²	2004.3²	2007.1²	−0.559	−0.593	−0.525	0.618
Total length of major roads in 1000 m buffer m	0	197	238	0.038	0.030	0.046	0.622
Temperature Celsius	3.65	9.75	16.14	−0.102	−0.115	−0.090	0.625
Altitude m	460	535	561	−0.032	−0.036	−0.028	0.628
Low density residential land use in 200 m buffer percent area	0.301	0.999	0.999	0.108	0.094	0.122	0.631
Boundary layer height m	126.2	319.7	656.2	−0.022	−0.030	−0.014	0.632
Total length of major roads in 500 m buffer m	0	197	238	0.012	0.004	0.020	0.632

Model developed without an intercept term. The R² is not provided in the regression output when the intercept is suppressed; we thus manually calculated the R². The predictors are ordered per decreasing relevance on the basis of incremental R². All p-values were <0.001
* indicates multiplication of variables
^aFor land use data (high and low density residential land use and industrial land use) we report the estimate per increase from 0 to 100 % of used area instead of per increase of IQR because data distribution is skewed and IQR would be 0
^bSeason categorised as 1: summer (May to August), 2: mid-season (March, April, September, October), 3: winter (November to February)

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ISSN: 1476-069X

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