Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities

Lina Madaniyazi, Yuming Guo, Renjie Chen, Haidong Kan, Shilu Tong

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)

Abstract

Estimating the burden of mortality associated with particulates requires knowledge of exposureresponse associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μn aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on cityspecific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well.

Original languageEnglish
Pages (from-to)40-47
Number of pages8
JournalEnvironmental Pollution
Volume208
Issue numberPart A SI
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes

Keywords

  • China
  • Mortality
  • Multivariate meta-regression model
  • Particulate matter

Cite this

Madaniyazi, Lina ; Guo, Yuming ; Chen, Renjie ; Kan, Haidong ; Tong, Shilu. / Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities. In: Environmental Pollution. 2016 ; Vol. 208, No. Part A SI. pp. 40-47.
@article{3f6e289079b844908c3715a65333250f,
title = "Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities",
abstract = "Estimating the burden of mortality associated with particulates requires knowledge of exposureresponse associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μn aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on cityspecific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well.",
keywords = "China, Mortality, Multivariate meta-regression model, Particulate matter",
author = "Lina Madaniyazi and Yuming Guo and Renjie Chen and Haidong Kan and Shilu Tong",
year = "2016",
month = "1",
day = "1",
doi = "10.1016/j.envpol.2015.09.011",
language = "English",
volume = "208",
pages = "40--47",
journal = "Environmental Pollution",
issn = "0269-7491",
publisher = "Elsevier",
number = "Part A SI",

}

Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities. / Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu.

In: Environmental Pollution, Vol. 208, No. Part A SI, 01.01.2016, p. 40-47.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities

AU - Madaniyazi, Lina

AU - Guo, Yuming

AU - Chen, Renjie

AU - Kan, Haidong

AU - Tong, Shilu

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Estimating the burden of mortality associated with particulates requires knowledge of exposureresponse associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μn aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on cityspecific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well.

AB - Estimating the burden of mortality associated with particulates requires knowledge of exposureresponse associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μn aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on cityspecific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well.

KW - China

KW - Mortality

KW - Multivariate meta-regression model

KW - Particulate matter

UR - http://www.scopus.com/inward/record.url?scp=84958915718&partnerID=8YFLogxK

U2 - 10.1016/j.envpol.2015.09.011

DO - 10.1016/j.envpol.2015.09.011

M3 - Article

VL - 208

SP - 40

EP - 47

JO - Environmental Pollution

JF - Environmental Pollution

SN - 0269-7491

IS - Part A SI

ER -