BACKGROUND: The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association. METHODS: We used data from >35 million Medicare enrollees from 207 US cities (2000-2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5-mortality association. RESULTS: We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 μg/m increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents. CONCLUSIONS: To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5-survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.
BACKGROUND: The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association. METHODS: We used data from >35 million Medicare enrollees from 207 US cities (2000-2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5-mortality association. RESULTS: We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 μg/m increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents. CONCLUSIONS: To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5-survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.
Authors: Rob Beelen; Ole Raaschou-Nielsen; Massimo Stafoggia; Zorana Jovanovic Andersen; Gudrun Weinmayr; Barbara Hoffmann; Kathrin Wolf; Evangelia Samoli; Paul Fischer; Mark Nieuwenhuijsen; Paolo Vineis; Wei W Xun; Klea Katsouyanni; Konstantina Dimakopoulou; Anna Oudin; Bertil Forsberg; Lars Modig; Aki S Havulinna; Timo Lanki; Anu Turunen; Bente Oftedal; Wenche Nystad; Per Nafstad; Ulf De Faire; Nancy L Pedersen; Claes-Göran Östenson; Laura Fratiglioni; Johanna Penell; Michal Korek; Göran Pershagen; Kirsten Thorup Eriksen; Kim Overvad; Thomas Ellermann; Marloes Eeftens; Petra H Peeters; Kees Meliefste; Meng Wang; Bas Bueno-de-Mesquita; Dorothea Sugiri; Ursula Krämer; Joachim Heinrich; Kees de Hoogh; Timothy Key; Annette Peters; Regina Hampel; Hans Concin; Gabriele Nagel; Alex Ineichen; Emmanuel Schaffner; Nicole Probst-Hensch; Nino Künzli; Christian Schindler; Tamara Schikowski; Martin Adam; Harish Phuleria; Alice Vilier; Françoise Clavel-Chapelon; Christophe Declercq; Sara Grioni; Vittorio Krogh; Ming-Yi Tsai; Fulvio Ricceri; Carlotta Sacerdote; Claudia Galassi; Enrica Migliore; Andrea Ranzi; Giulia Cesaroni; Chiara Badaloni; Francesco Forastiere; Ibon Tamayo; Pilar Amiano; Miren Dorronsoro; Michail Katsoulis; Antonia Trichopoulou; Bert Brunekreef; Gerard Hoek Journal: Lancet Date: 2013-12-09 Impact factor: 79.321
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