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Table 4 Estimates effects of long-term PM2.5 exposure in quartile and Temperature on COVID-19 mortality rate using the negative binomial regression model, adjusted for all potential confounders (From 01May to 31 December, 2020)

From: Impact of long-term exposure to PM2.5 and temperature on coronavirus disease mortality: observed trends in France

Independent variables 01 May 01 June 01 July 01 August 01 September 01 October 01 November 01 December 31 December
Annual average Long-term PM2.5 exposure (μg/m3) in quartile (ref. = Q1 (7.2 μg/m3))
Q2
(9.0 μg/m3)
1.134 (0.758–1.699) 1.144 (0.779–1.680) 1.134 (0.775–1.660) 1.127 (0.771–1.649) 1.126 (0.773–1.640) 1.144 (0.796–1.643) 1.105 (0.807–1.513) 1.142 (0.876–1.490) 1.190 (0.922–1.535)
Q3
(10.7 μg/m3)
2.408b (1.508–3.845) 2.302b (1.474–3.597) 2.307b (1.484–3.586) 2.295b (1.476–3.568) 2.317b (1.498–3.582) 2.234b (1.467–3.404) 1.624b (1.129–2.336) 1.366a (1.007–1.853) 1.469b (1.099–1.963)
Q4
(13.4 μg/m3)
2.797b (1.439–5.436) 2.678b (1.414–5.070) 2.697b (1.433–5.074) 2.682b (1.424–5.052) 2.680b (1.433–5.012) 2.596b (1.416–4.760) 1.712a (1.013–2.893) 1.141 (0.734–1.776) 1.140 (0.749–1.736)
Annual average Temperature over 12 years 0.919 (0.835–1.012) 0.914 (0.835–1.001) 0.914a (0.836–1.000) 0.915 (0.837–1.001) 0.918 (0.841–1.003) 0.921 (0.846–1.004) 0.903b (0.839–0.972) 0.867b (0.814–0.923) 0.855b (0.805–0.908)
Number of intensive care and resuscitation beds (per 100,000) 1.015 (0.991–1.039) 1.010 (0.988–1.033) 1.009 (0.987–1.031) 1.008 (0.986–1.031) 1.008 (0.986–1.030) 1.006 (0.985–1.027) 1.006 (0.987–1.024) 1.000 (0.984–1.015) 1.001 (0.986–1.017)
Medical density (per 100,000) 0.998 (0.996–1.001) 0.999 (0.997–1.001) 0.999 (0.997–1.001) 0.999 (0.997–1.002) 0.999 (0.997–1.002) 1.000 (0.998–1.002) 1.000 (0.998–1.002) 1.001 (0.999–1.002) 1.001 (0.999–1.002)
% People aged 60 or more 1.073a (1.009–1.140) 1.078a (1.017–1.144) 1.080b (1.019–1.145) 1.083b (1.021–1.148) 1.079a (1.018–1.143) 1.079b (1.020–1.141) 1.032 (0.986–1.081) 1.017 (0.977–1.059) 1.013 (0.975–1.053)
% Males 1.436 (0.986–2.092) 1.494a (1.040–2.147) 1.530a (1.068–2.191) 1.561a (1.091–2.235) 1.559a (1.093–2.223) 1.543a (1.092–2.180) 1.456a (1.080–1.963) 1.308a (1.010–1.694) 1.278 (0.997–1.637)
% Unemployment 1.027 (0.889–1.186) 1.014 (0.884–1.163) 1.015 (0.886–1.163) 1.015 (0.886–1.164) 1.020 (0.891–1.167) 0.989 (0.870–1.126) 0.997 (0.891–1.115) 1.008 (0.914–1.111) 1.014 (0.924–1.114)
Rate of Poverty (per cent) 1.000 (0.910–1.100) 1.000 (0.914–1.094) 1.002 (0.917–1.096) 1.002 (0.916–1.095) 1.000 (0.916–1.093) 1.018 (0.935–1.109) 1.017 (0.944–1.095) 1.006 (0.944–1.072) 1.003 (0.944–1.065)
% Urban population (proportion of people living in the great urban areas) 1.025b (1.009–1.040) 1.024b (1.009–1.039) 1.024b (1.010–1.039) 1.025b (1.010–1.040) 1.024b (1.010–1.039) 1.025b (1.011–1.039) 1.014a (1.003–1.026) 1.009 (0.999–1.019) 1.006 (0.996–1.015)
Population density (inhab/square) 1.000b (1.000–1.000) 1.000b (1.000–1.000) 1.000b (1.000–1.000) 1.000b (1.000–1.000) 1.000b (1.000–1.000) 1.000a (1.000–1.000) 1.000a (1.000–1.000) 1.000a (1.000–1.000) 1.000a (1.000–1.000)
Standardized Prevalence of Diabetes (%) 1.191 (0.831–1.708) 1.235 (0.879–1.735) 1.247 (0.890–1.745) 1.253 (0.895–1.753) 1.250 (0.897–1.741) 1.244 (0.901–1.717) 1.288 (0.973–1.705) 1.353a (1.066–1.716) 1.352b (1.077–1.698)
Criteria for assessing goodness of fit:
Deviance 1.1782 1.2091 1.2114 1.2134 1.2086 1.2147 1.1827 1.1982 1.1927
Scaled Deviance 1.1782 1.2091 1.2114 1.2134 1.2086 1.2147 1.1827 1.1982 1.1927
Pearson Chi-Square 1.2419 1.2275 1.2168 1.2148 1.2164 1.1875 1.1898 1.1747 1.1834
Scaled Pearson X2 1.2419 1.2275 1.2168 1.2148 1.2164 1.1875 1.1898 1.1747 1.1834
BIC (smaller is better) 733.6727 769.6559 775.9792 779.4617 781.455 789.3626 813.6141 885.5104 927.3749
  1. (a) Significance at 5%, (b) Significance at 1%