Association of Particulate Matter Exposure With Lung Function and Mortality Among Patients With Fibrotic Interstitial Lung Disease Article Swipe
G.C. Goobie
,
Christopher Carlsten
,
Kerri A. Johannson
,
Nasreen Khalil
,
Veronica Marcoux
,
Deborah Assayag
,
H. Manganas
,
Jolene H. Fisher
,
Martin Kolb
,
Kathleen O. Lindell
,
James P. Fabisiak
,
Xiaoping Chen
,
Kevin F. Gibson
,
Yingze Zhang
,
Daniel J. Kass
,
Christopher J. Ryerson
,
Mehdi Nouraie
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1001/jamainternmed.2022.4696
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1001/jamainternmed.2022.4696
Importance Particulate matter 2.5 μm or less in diameter (PM 2.5 ) is associated with adverse outcomes in idiopathic pulmonary fibrosis, but its association with other fibrotic interstitial lung diseases (fILDs) remains unclear. Objective To investigate the association of PM 2.5 exposure with mortality and lung function among patients with fILD. Design, Setting, and Participants In this multicenter, international, prospective cohort study, patients were enrolled in the Simmons Center for Interstitial Lung Disease Registry at the University of Pittsburgh in Pittsburgh, Pennsylvania (Simmons cohort); 42 sites of the Pulmonary Fibrosis Foundation Registry (PFF cohort); and 8 sites of the Canadian Registry for Pulmonary Fibrosis (CARE-PF cohort). A total of 6683 patients were included (Simmons, 1424; PFF, 1870; and CARE-PF, 3389). Data were analyzed from June 1, 2021, to April 3, 2023. Exposures Exposure to PM 2.5 and its constituents was estimated with hybrid models, combining satellite-derived aerosol optical depth with chemical transport models and ground-based PM 2.5 measurements. Main Outcomes and Measures Multivariable linear regression tested associations of exposures with baseline forced vital capacity (FVC) and diffusion capacity for carbon monoxide (D L CO), and linear mixed models tested associations with lung function decline. Multivariable Cox models tested associations of 5-year time-varying exposures from enrollment to censoring with mortality or lung transplant. Multiconstituent analyses were performed with quantile-based g-computation. Models were adjusted for age, sex, smoking history, self-reported race, a socioeconomic covariate, and site (for PFF and CARE-PF only). Cohort effect estimates were meta-analyzed with clustering by cohort. Results Median follow-up across the 3 cohorts was 2.9 years (IQR, 1.5-4.5 years), with death for 28% of patients and lung transplant for 10% of patients. Of 6683 patients, 3653 were men (55%), 205 were Black (3.1%), and 5609 were White (84.0%). Median (IQR) age at enrollment was 66 (58-73) years. In Simmons, each 1-μg/m 3 increase in 5-year preenrollment PM 2.5 was associated with a lower estimated percentage baseline FVC, and each 1-μg/m 3 increase in 5-year precensoring PM 2.5 was associated with decreasing FVC and D L CO, but these associations were not observed in PFF or CARE-PF. In PFF, each 1-μg/m 3 increase in 5-year preenrollment PM 2.5 was associated with lower percentage baseline D L CO. In cohort-specific analyses, each 1-μg/m 3 increase in 5-year time-varying PM 2.5 exposure was associated with higher mortality or transplant rates in Simmons (hazard ratio [HR], 1.05 [95% CI, 1.01-1.09]; P = .02), but not the other cohorts (PFF HR, 1.02 [95% CI, 0.98-1.06]; P = .38; CARE-PF HR, 0.98 [95% CI, 0.96-1.01]; P = .16). Meta-analysis of pooled individual patient data from the 3 cohorts demonstrated an HR of 1.09 (95% CI, 1.05-1.13; P < .001) for each 1-μg/m 3 increase in PM 2.5 . Increasing exposures to sulfate, ammonium, and black carbon PM 2.5 constituents were also associated with higher rate of mortality or transplant in the meta-analysis, and multiconstituent models demonstrated that black carbon and sulfate were the primary drivers of the adverse mortality rates associated with the PM 2.5 mixture. Conclusions and Relevance In this cohort study, exposure to PM 2.5 was associated with worse lung function and mortality or transplant among some but not all patients with fILD. Sulfate, ammonium, and black carbon constituents were associated with the most potential risk, highlighting the need for reductions in human-derived sources of pollution.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1001/jamainternmed.2022.4696
- https://jamanetwork.com/journals/jamainternalmedicine/articlepdf/2797557/jamainternal_goobie_2022_oi_220062_1670009033.7659.pdf
- OA Status
- hybrid
- Cited By
- 96
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4306663539
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Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4306663539Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1001/jamainternmed.2022.4696Digital Object Identifier
- Title
-
Association of Particulate Matter Exposure With Lung Function and Mortality Among Patients With Fibrotic Interstitial Lung DiseaseWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-10-17Full publication date if available
- Authors
-
G.C. Goobie, Christopher Carlsten, Kerri A. Johannson, Nasreen Khalil, Veronica Marcoux, Deborah Assayag, H. Manganas, Jolene H. Fisher, Martin Kolb, Kathleen O. Lindell, James P. Fabisiak, Xiaoping Chen, Kevin F. Gibson, Yingze Zhang, Daniel J. Kass, Christopher J. Ryerson, Mehdi NouraieList of authors in order
- Landing page
-
https://doi.org/10.1001/jamainternmed.2022.4696Publisher landing page
- PDF URL
-
https://jamanetwork.com/journals/jamainternalmedicine/articlepdf/2797557/jamainternal_goobie_2022_oi_220062_1670009033.7659.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://jamanetwork.com/journals/jamainternalmedicine/articlepdf/2797557/jamainternal_goobie_2022_oi_220062_1670009033.7659.pdfDirect OA link when available
- Concepts
-
Medicine, Idiopathic pulmonary fibrosis, Cohort, Vital capacity, Interstitial lung disease, Internal medicine, Pulmonary function testing, Cohort study, Proportional hazards model, Hazard ratio, Diffusing capacity, Lung, Lung function, Confidence intervalTop concepts (fields/topics) attached by OpenAlex
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-
96Total citation count in OpenAlex
- Citations by year (recent)
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2025: 38, 2024: 38, 2023: 19, 2022: 1Per-year citation counts (last 5 years)
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33Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.function | 46, 192, 518 |
| abstract_inverted_index.history, | 226 |
| abstract_inverted_index.included | 112 |
| abstract_inverted_index.increase | 304, 323, 353, 374, 449 |
| abstract_inverted_index.mixture. | 501 |
| abstract_inverted_index.monoxide | 180 |
| abstract_inverted_index.observed | 343 |
| abstract_inverted_index.outcomes | 16 |
| abstract_inverted_index.patients | 48, 62, 110, 266, 528 |
| abstract_inverted_index.sulfate, | 457 |
| abstract_inverted_index.unclear. | 32 |
| abstract_inverted_index.(Simmons, | 113 |
| abstract_inverted_index.Exposures | 131 |
| abstract_inverted_index.Objective | 33 |
| abstract_inverted_index.Pulmonary | 88, 102 |
| abstract_inverted_index.Relevance | 504 |
| abstract_inverted_index.ammonium, | 458, 532 |
| abstract_inverted_index.analyses, | 370 |
| abstract_inverted_index.censoring | 206 |
| abstract_inverted_index.combining | 144 |
| abstract_inverted_index.diffusion | 176 |
| abstract_inverted_index.estimated | 140, 315 |
| abstract_inverted_index.estimates | 241 |
| abstract_inverted_index.exposures | 168, 202, 455 |
| abstract_inverted_index.fibrosis, | 20 |
| abstract_inverted_index.follow-up | 250 |
| abstract_inverted_index.mortality | 43, 208, 385, 472, 494, 520 |
| abstract_inverted_index.patients, | 276 |
| abstract_inverted_index.patients. | 273 |
| abstract_inverted_index.performed | 215 |
| abstract_inverted_index.potential | 542 |
| abstract_inverted_index.pulmonary | 19 |
| abstract_inverted_index.transport | 151 |
| abstract_inverted_index.1.05-1.13; | 441 |
| abstract_inverted_index.Foundation | 90 |
| abstract_inverted_index.Importance | 0 |
| abstract_inverted_index.Increasing | 454 |
| abstract_inverted_index.Pittsburgh | 78 |
| abstract_inverted_index.University | 76 |
| abstract_inverted_index.associated | 13, 311, 330, 360, 382, 467, 496, 514, 538 |
| abstract_inverted_index.clustering | 245 |
| abstract_inverted_index.covariate, | 231 |
| abstract_inverted_index.decreasing | 332 |
| abstract_inverted_index.enrollment | 204, 294 |
| abstract_inverted_index.idiopathic | 18 |
| abstract_inverted_index.individual | 427 |
| abstract_inverted_index.percentage | 316, 363 |
| abstract_inverted_index.pollution. | 553 |
| abstract_inverted_index.reductions | 548 |
| abstract_inverted_index.regression | 164 |
| abstract_inverted_index.transplant | 269, 387, 474, 522 |
| abstract_inverted_index.0.96-1.01]; | 420 |
| abstract_inverted_index.0.98-1.06]; | 411 |
| abstract_inverted_index.1.01-1.09]; | 397 |
| abstract_inverted_index.Conclusions | 502 |
| abstract_inverted_index.Particulate | 1 |
| abstract_inverted_index.Pittsburgh, | 80 |
| abstract_inverted_index.association | 23, 37 |
| abstract_inverted_index.investigate | 35 |
| abstract_inverted_index.prospective | 59 |
| abstract_inverted_index.transplant. | 211 |
| abstract_inverted_index.&amp;lt; | 443 |
| abstract_inverted_index.Interstitial | 70 |
| abstract_inverted_index.Participants | 54 |
| abstract_inverted_index.Pennsylvania | 81 |
| abstract_inverted_index.associations | 166, 189, 198, 340 |
| abstract_inverted_index.constituents | 138, 464, 536 |
| abstract_inverted_index.demonstrated | 434, 481 |
| abstract_inverted_index.ground-based | 154 |
| abstract_inverted_index.highlighting | 544 |
| abstract_inverted_index.interstitial | 27 |
| abstract_inverted_index.multicenter, | 57 |
| abstract_inverted_index.precensoring | 326 |
| abstract_inverted_index.time-varying | 201, 377 |
| abstract_inverted_index.Meta-analysis | 424 |
| abstract_inverted_index.Multivariable | 162, 194 |
| abstract_inverted_index.human-derived | 550 |
| abstract_inverted_index.measurements. | 157 |
| abstract_inverted_index.meta-analyzed | 243 |
| abstract_inverted_index.preenrollment | 307, 356 |
| abstract_inverted_index.self-reported | 227 |
| abstract_inverted_index.socioeconomic | 230 |
| abstract_inverted_index.g-computation. | 218 |
| abstract_inverted_index.international, | 58 |
| abstract_inverted_index.meta-analysis, | 477 |
| abstract_inverted_index.quantile-based | 217 |
| abstract_inverted_index.cohort-specific | 369 |
| abstract_inverted_index.Multiconstituent | 212 |
| abstract_inverted_index.multiconstituent | 479 |
| abstract_inverted_index.satellite-derived | 145 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5081815232 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 17 |
| corresponding_institution_ids | https://openalex.org/I141945490, https://openalex.org/I170201317 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.8399999737739563 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.99435634 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |