Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study

Rina So; Massimo Stafoggia; Kees de Hoogh; Klea Katsouyanni; Danielle Vienneau; Evangelia Samoli; Sophia Rodopoulou; Steffen Loft; Youn-Hee Lim; Rudi G.J. Westendorp; Heresh Amini; Tom Cole-Hunter; Marie Bergmann; Seyed Mahmood Taghavi Shahri; Jiawei Zhang; Matija Maric; Laust H. Mortensen; Mariska Bauwelinck; Jochem Klompmaker; Richard Atkinson; Nicole A.H. Janssen; Bente M. Oftedal; Matteo Renzi; Francesco Forastiere; Maciek Strak; Bert Brunekreef; Gerard Hoek; Zorana Jovanovic Andersen

doi:10.1016/j.envres.2023.115552

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study

Rina So, Massimo Stafoggia, Kees de Hoogh, Klea Katsouyanni, Danielle Vienneau, Evangelia Samoli, Sophia Rodopoulou, Steffen Loft, Youn-Hee Lim, Rudi G.J. Westendorp, Heresh Amini, Tom Cole-Hunter, Marie Bergmann, Seyed Mahmood Taghavi Shahri, Jiawei Zhang, Matija Maric, Laust H. Mortensen, Mariska Bauwelinck, Jochem Klompmaker, Richard AtkinsonNicole A.H. Janssen, Bente M. Oftedal, Matteo Renzi, Francesco Forastiere, Maciek Strak, Bert Brunekreef, Gerard Hoek, Zorana Jovanovic Andersen

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Abstract

Background: Fine particulate matter (PM_2.5) is a well-recognized risk factor for premature death. However, evidence on which PM_2.5 components are most relevant is unclear. Methods: We evaluated the associations between mortality and long-term exposure to eight PM_2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM_2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM_2.5 mass. Results: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03–1.05), RF-Si (1.01; 1.00–1.02), SLR-K (1.03; 1.02–1.04), and RF-K (1.06; 1.05–1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. Conclusions: We present novel results of the relevance of different PM_2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Original language	English
Article number	115552
Number of pages	11
Journal	Environmental Research
Volume	224
Issue number	115552
DOIs	https://doi.org/10.1016/j.envres.2023.115552
Publication status	Published - 1 May 2023

Bibliographical note

Funding Information:
The study presented here was performed under contract with the HEI. The HEI is an organization supported by the United States Environmental Protection Agency (EPA), United States (No. R-82811201 ) and certain motor vehicle and engine manufacturers. The results of this study do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers.

Funding Information:
This work was supported by funding from the Health Effects Institute (HEI) Research Agreement (# 4954-RFA14-3/16-5-3 ), jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R- 82,811,201 ) and certain motor vehicle and engine manufacturers, and by the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (# NNF17OC0027812 ). The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript, and; the decision to submit the manuscript for publication.

Funding Information:
This work was supported by funding from the Health Effects Institute (HEI) Research Agreement (#4954-RFA14-3/16-5-3), jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R- 82,811,201) and certain motor vehicle and engine manufacturers, and by the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (#NNF17OC0027812). The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript, and; the decision to submit the manuscript for publication.The study presented here was performed under contract with the HEI. The HEI is an organization supported by the United States Environmental Protection Agency (EPA), United States (No. R-82811201) and certain motor vehicle and engine manufacturers. The results of this study do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers.

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© 2023

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So, R., Stafoggia, M., de Hoogh, K., Katsouyanni, K., Vienneau, D., Samoli, E., Rodopoulou, S., Loft, S., Lim, Y.-H., Westendorp, R. G. J., Amini, H., Cole-Hunter, T., Bergmann, M., Mahmood Taghavi Shahri, S., Zhang, J., Maric, M., Mortensen, L. H., Bauwelinck, M., Klompmaker, J., ... Andersen, Z. J. (2023). Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study. Environmental Research, 224(115552), Article 115552. https://doi.org/10.1016/j.envres.2023.115552

@article{05137b1cc36142d58cea367003b2d2f9,

title = "Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study",

abstract = "Background: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. Methods: We evaluated the associations between mortality and long-term exposure to eight PM2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM2.5 mass. Results: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03–1.05), RF-Si (1.01; 1.00–1.02), SLR-K (1.03; 1.02–1.04), and RF-K (1.06; 1.05–1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. Conclusions: We present novel results of the relevance of different PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.",

author = "Rina So and Massimo Stafoggia and {de Hoogh}, Kees and Klea Katsouyanni and Danielle Vienneau and Evangelia Samoli and Sophia Rodopoulou and Steffen Loft and Youn-Hee Lim and Westendorp, {Rudi G.J.} and Heresh Amini and Tom Cole-Hunter and Marie Bergmann and {Mahmood Taghavi Shahri}, Seyed and Jiawei Zhang and Matija Maric and Mortensen, {Laust H.} and Mariska Bauwelinck and Jochem Klompmaker and Richard Atkinson and Janssen, {Nicole A.H.} and Oftedal, {Bente M.} and Matteo Renzi and Francesco Forastiere and Maciek Strak and Bert Brunekreef and Gerard Hoek and Andersen, {Zorana Jovanovic}",

note = "Funding Information: The study presented here was performed under contract with the HEI. The HEI is an organization supported by the United States Environmental Protection Agency (EPA), United States (No. R-82811201 ) and certain motor vehicle and engine manufacturers. The results of this study do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Funding Information: This work was supported by funding from the Health Effects Institute (HEI) Research Agreement (# 4954-RFA14-3/16-5-3 ), jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R- 82,811,201 ) and certain motor vehicle and engine manufacturers, and by the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (# NNF17OC0027812 ). The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript, and; the decision to submit the manuscript for publication. Funding Information: This work was supported by funding from the Health Effects Institute (HEI) Research Agreement (#4954-RFA14-3/16-5-3), jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R- 82,811,201) and certain motor vehicle and engine manufacturers, and by the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (#NNF17OC0027812). The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript, and; the decision to submit the manuscript for publication.The study presented here was performed under contract with the HEI. The HEI is an organization supported by the United States Environmental Protection Agency (EPA), United States (No. R-82811201) and certain motor vehicle and engine manufacturers. The results of this study do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Publisher Copyright: {\textcopyright} 2023",

year = "2023",

month = may,

day = "1",

doi = "10.1016/j.envres.2023.115552",

language = "English",

volume = "224",

journal = "Environmental Research",

issn = "0013-9351",

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So, R, Stafoggia, M, de Hoogh, K, Katsouyanni, K, Vienneau, D, Samoli, E, Rodopoulou, S, Loft, S, Lim, Y-H, Westendorp, RGJ, Amini, H, Cole-Hunter, T, Bergmann, M, Mahmood Taghavi Shahri, S, Zhang, J, Maric, M, Mortensen, LH, Bauwelinck, M, Klompmaker, J, Atkinson, R, Janssen, NAH, Oftedal, BM, Renzi, M, Forastiere, F, Strak, M, Brunekreef, B, Hoek, G & Andersen, ZJ 2023, 'Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study', Environmental Research, vol. 224, no. 115552, 115552. https://doi.org/10.1016/j.envres.2023.115552

TY - JOUR

T1 - Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study

AU - So, Rina

AU - Stafoggia, Massimo

AU - de Hoogh, Kees

AU - Katsouyanni, Klea

AU - Vienneau, Danielle

AU - Samoli, Evangelia

AU - Rodopoulou, Sophia

AU - Loft, Steffen

AU - Lim, Youn-Hee

AU - Westendorp, Rudi G.J.

AU - Amini, Heresh

AU - Cole-Hunter, Tom

AU - Bergmann, Marie

AU - Mahmood Taghavi Shahri, Seyed

AU - Zhang, Jiawei

AU - Maric, Matija

AU - Mortensen, Laust H.

AU - Bauwelinck, Mariska

AU - Klompmaker, Jochem

AU - Atkinson, Richard

AU - Janssen, Nicole A.H.

AU - Oftedal, Bente M.

AU - Renzi, Matteo

AU - Forastiere, Francesco

AU - Strak, Maciek

AU - Brunekreef, Bert

AU - Hoek, Gerard

AU - Andersen, Zorana Jovanovic

N1 - Funding Information: The study presented here was performed under contract with the HEI. The HEI is an organization supported by the United States Environmental Protection Agency (EPA), United States (No. R-82811201 ) and certain motor vehicle and engine manufacturers. The results of this study do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Funding Information: This work was supported by funding from the Health Effects Institute (HEI) Research Agreement (# 4954-RFA14-3/16-5-3 ), jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R- 82,811,201 ) and certain motor vehicle and engine manufacturers, and by the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (# NNF17OC0027812 ). The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript, and; the decision to submit the manuscript for publication. Funding Information: This work was supported by funding from the Health Effects Institute (HEI) Research Agreement (#4954-RFA14-3/16-5-3), jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R- 82,811,201) and certain motor vehicle and engine manufacturers, and by the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (#NNF17OC0027812). The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript, and; the decision to submit the manuscript for publication.The study presented here was performed under contract with the HEI. The HEI is an organization supported by the United States Environmental Protection Agency (EPA), United States (No. R-82811201) and certain motor vehicle and engine manufacturers. The results of this study do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Publisher Copyright: © 2023

PY - 2023/5/1

Y1 - 2023/5/1

N2 - Background: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. Methods: We evaluated the associations between mortality and long-term exposure to eight PM2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM2.5 mass. Results: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03–1.05), RF-Si (1.01; 1.00–1.02), SLR-K (1.03; 1.02–1.04), and RF-K (1.06; 1.05–1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. Conclusions: We present novel results of the relevance of different PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

AB - Background: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. Methods: We evaluated the associations between mortality and long-term exposure to eight PM2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM2.5 mass. Results: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03–1.05), RF-Si (1.01; 1.00–1.02), SLR-K (1.03; 1.02–1.04), and RF-K (1.06; 1.05–1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. Conclusions: We present novel results of the relevance of different PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

UR - http://www.scopus.com/inward/record.url?scp=85148951110&partnerID=8YFLogxK

U2 - 10.1016/j.envres.2023.115552

DO - 10.1016/j.envres.2023.115552

M3 - Article

SN - 0013-9351

VL - 224

JO - Environmental Research

JF - Environmental Research

IS - 115552

M1 - 115552

ER -

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study

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