1

Supplementary Material

Contents

Details of studies excluded from meta-analysis for other causes or mortality

Tables

eTable 1 Coding of categorise of cause of death

eTable 2 Study and cohort characteristics

Figures

eFigure 1 All-cause mortality

eFigure 2a All-cause mortality - fixed effects model

eFigure 2b All-cause mortality - random effects model

eFigure 3 All-cause mortality stratification by pre-existing disease on recruitment

eFigure 4 All-cause mortality stratification by age range at cohort recruitment

eFigure 5 Cardiovascular mortality

eFigure 6a Cardiovascular mortality - fixed effects model

eFigure 6b Cardiovascular mortality - random effects model

eFigure 7 Cardiovascular mortality - stratification pre-existing disease on recruitment

eFigure 8 Cardiovascular mortality - stratification by age range at cohort recruitment

eFigure 9 Cardiovascular mortality - stratification by level of confounder control

eFigure 10 Cardiovascular mortality - stratification by spatial resolution of NO2 concentration estimates

eFigure 11 CHD mortality

eFigure 12a CHD mortality - fixed effects model

eFigure 12b CHD mortality - random effects model

eFigure 13 CHD mortality - stratification by age range at cohort recruitment

eFigure 14 CHD mortality - stratification by level of confounder control

eFigure 15 CHD mortality - stratification by spatial resolution of NO2 concentration estimates

eFigure 16 Cerebrovascular mortality

eFigure 17a Cerebrovascular mortality - fixed effects model

eFigure 17b Cerebrovascular mortality - random effects model

eFigure 18 Cerebrovascular mortality - stratification by age range at cohort recruitment

eFigure 19 Cerebrovascular mortality - stratification by level of confounder control

eFigure 20 Cerebrovascular mortality - stratification by spatial resolution of NO2 concentration

eFigure 21 Respiratory mortality

2

eFigure 22a Respiratory mortality - fixed effects model

eFigure 22b Respiratory mortality - random effects model

eFigure 23 Respiratory mortality - stratification by pre-existing disease at cohort recruitment

eFigure 24 Respiratory mortality - stratification by age range at cohort recruitment

eFigure 25 Respiratory mortality - stratification by level of confounder control

eFigure 26 Respiratory mortality - stratification by spatial resolution of NO2 concentration

eFigure 27 COPD mortality

eFigure 28a COPD mortality - fixed effects model

eFigure 28b COPD mortality - random effects model

eFigure 29 COPD mortality - stratification by age range at cohort recruitment

eFigure 30 COPD mortality - stratification by level of confounder control

eFigure 31 COPD mortality - stratification by spatial resolution of NO2 concentration

eFigure 32 Pneumonia mortality

eFigure 33 Lung cancer mortality

eFigure 34a Lung cancer mortality - fixed effects model

eFigure 34b Lung cancer mortality - random effects model

eFigure 35 Lung cancer mortality - stratification by age range at cohort recruitment

eFigure 36 Lung cancer mortality - stratification by level of confounder control

eFigure 37 Lung cancer mortality - stratification by spatial resolution of NO2 concentration

eFigure 38 Diabetes mortality

3

Details of studies excluded from meta-analysis for other causes or mortality (references refer to

main manuscript)

CHD: Twelve studies were meta-analysed after exclusions of one study [53] included in ESCAPE [21]

and 3 analysed in other publications [31, 43, 62].

Cerebrovascular: Seven studies were meta-analysed after exclusions of one study [53] included in

ESCAPE [21]; one study reporting an abnormally high HR (>2.4) from the Shenyang Cohort [63] and 2

studies where the same cohorts were analysed in other publications [31, 62].

COPD: Only a single study [62] analysed in a subsequent publication was excluded.

4

eTable 1 Coding of categorise of cause of death

Mortality Coded

All-causes "All Causes" , "All Cause (after ACS)" , "All Causes (after stroke)" , "All causes" , "Natural Causes" , "Non Accidental"

Cardiovascular "Cardiovascular" , "Circulatory"

Cerebrovascular "Cerebrovascular"

CHD "CHD" , "IHD"

Respiratory "Respiratory" , "Pulmonary" , "Non-malignant Respiratory"

COPD "COPD" , "COPD & allied conditions"

Pneumonia "Pneumonia" , "Pneumonia & Influenza"

Lung cancer "Lung Cancer" , "Trachea, bronchus and lung cancers"

5

eTable 2: Cohort and study characteristics (ordered by cohort/date of publication); citation numbers correspond with main paper

Cohort Name and brief description

Country Enrolment (baseline)

Publication and Date

Number of Subjects

Follow-up Dates / Length

Exposure Period

Exposure assessment

Covariate adjustment includes#:

Mortality Cause

Date Age

European Cohorts

ESCAPE 22 population based cohorts from 13 European Countries

Europe mainly 1990s

all ages [21] Beelen R et al 2014b

367,251

Average 13.9 years

1 year Oct 2008-May 2011 with back-extrapolation to baseline

LUR + back-extrapolation: Address-level

Age, sex, smoking, BMI, occupational and educational factors

All-cause

[22] Beelen R et al 2014a

367,383 Average 13.9 years

1 year Oct 2008-May 2011 with back-extrapolation to baseline

LUR + back-extrapolation: Address-level

Age, sex, smoking, BMI, occupational and educational factors

CV, CHD, MI, Cerebrovascular

[33] Dimakopoulou K et al 2014

307,553 (16 cohorts)

16.3 to 18.6 years

Annual average (baseline)

LUR: Address-level

Age, sex, smoking, BMI, occupational and educational factors

Respiratory

Diet Cancer and Health cohort (DCH) Population based sample with no cancer history living in areas of Copenhagen and Aarhus.

Denmark 1993-1997

50-64 [54] Raaschou-Nielsen O et al 2012

52,061 to end 2009 1971 onwards: Annual mean exposure, time varying

DM: Address-level allowing for change of residence

Age, sex, smoking, BMI, employment status, length of school attendance

All-cause CV, CHD, Cerebrovascular

[55] Raaschou-Nielsen O et al 2013

52,061 to end 2009 1971 onwards: Annual mean exposure, time varying

DM: Address-level allowing for change of residence

Age, sex, smoking, BMI, length of school attendance

Diabetes

[19] Andersen ZI et al 2012

52,215 to June 27th 2006

1971 onwards: Annual mean exposure, time varying

DM: Address-level allowing for change of residence

Age, sex, smoking, BMI, educational level.

Fatal stroke (and sub-types)

6

[58] Sorensen M et al 2014

51,569 1st July 1997 to 30th Nov 2009

1987-2009: 10-years exposure, time varying

DM: Address-level allowing for change of residence

Age, sex, smoking, BMI, length of school attendance

Fatal stroke

Clinical Practice Research Datalink (CPRD) Patients in GP practices participating in CPRD

England 2003 40-89 [25] Carey IM et al 2013

830,429 2003-2007 2002 DM: 1 km grid square-level

Age, sex, smoking, BMI, area-level income

All-cause, CV, CHD, MI, HF, Cerebrovascular, Stroke, Respiratory, COPD, Pneumonia, Lung Cancer

South London Stroke Register (SLSR) Patients in the South London Stroke Register who experienced their first ever stroke between 1995 and 2005.

England 1995-2005

Mean (SD) 70.4 (14.6)

[51] Maheswaren R et al 2010

3,320 to mid-2006 2002 Modelled: 20x20m grid level

Age, sex, smoking, social class but not BMI

All-cause

MINAP (Acute Coronary Syndrome survivors) Patients admitted to hospital in England and Wales with acute coronary syndrome and recorded in MINAP (Myocardial Ischaemia National Audit Project) who are still alive 28 days post admission.

England & Wales

2004-2007

Mean (SD) 68 (13) >25

[59] Tonne C et al 2013

154,204 3.7 years 2004-2010: Annual average, time varying

DM: 1km x 1km level

Age, sex, smoking, area-level income but not BMI

All-cause

Greater London

2003-2007

>25 [65] Tonne C et al 2016

18,138 4.0 years 2003-2010 DM: 20m x 20m level

Age, area-level income deprivation, but not BMI. Smoking, and ethnicity in a sensitivity analysis after imputation of large number of missing values

All-cause

7

Pollution Atmosphérique et Affections Respiratoires Chroniques (PAARC) Adults from French family households resident in 24/18 areas of 7 Cities.

France 1974-1976

25-59 [35] Filleul L et al 2005

14,284 1974-2000 1974-1976 (August excluded)

Monitoring data: Area-level (areas 0.5 to 2.3 km in diameter)

Age, sex, smoking, BMI, educational level

All-cause, Cardio-pulmonary, Lung Cancer

GAZEL Cohort EDF-GDF workers

France 1989-2013

Mean (SD) 43.7 (3.5) 35-50

[23] Bentayeb et al, 2015

20,327 1989-2013 1989-2008 Chemistry Transport Model (resolution 2km) linked to ZIP code, allowing for change in residence

Age, sex, smoking, BMI, highest level of education, occupational level

All-cause, CV, Respiratory, Lung Cancer

German cohort Women sampled at random from cross-sectional studies conducted in North Rhine-Westphalia in the 1980s and 1990s.

Germany 1985-1994

50-59 (92% aged 53-55)

[39] Gehring U et al 2006

4,752 to May 2003 5-year average prior to baseline

Monitoring data: Area-level

Smoking, educational level but not BMI (all female cohort of similar age)

All-cause, Cardio-pulmonary

[57] Schikowski T et al 2007

4,750 to May 2003 5-year average prior to baseline

Monitoring data: Area-level

Smoking, educational level but not BMI (all female cohort of similar age)

CV

[41] Heinrich J et al 2013

4,752 to Oct 2008 1-year average (baseline)

Monitoring data: Nearest monitor to residence

Smoking, educational level but not BMI (all female cohort of similar age)

All-cause, Cardio-pulmonary Respiratory, Lung Cancer

CHD survivors cohort Population based cohort of CHD survivors (Rome)

Italy 1998-2000

35-84 [56] Rosenlund M et al 2008

6,513 29th day after event to end June 2005

1995/1996: Annual mean

LUR: Census block-level

Age, sex, area-based socioeconomic status but not smoking or BMI

All-cause

8

Rome longitudinal study Population based cohort of long-term (5+ years) residents of Rome.

Italy 2001 >=30 [26] Cesaroni G et al 2013

1,265,058 Oct 2001-Dec 2010

Oct 1996-Dec 2010: Cumulative mean exposure, time varying

LUR: Address-level allowing for change of residence

Age, sex, education, occupation but not smoking or BMI

All-cause, CV, CHD, Cerebrovascular, Respiratory, Lung Cancer

[27] Cesaroni G et al 2012

684,204 (subset age 45-80 in 2001)

2001-2006 1995/1996: Annual mean

LUR: Address-level

Age, sex, education, occupation but not smoking or BMI

All-cause

Dutch Environmental Longitudinal Study DUELS Dutch inhabitants who had lived at the same address between 1/1/1999 and 1/1/2004

Nether-lands

2004 >=30 [36] Fisher PH et al 2015

7,218,363 2004-2010 2001 LUR: 100 x 100m level

Age, sex, standardised disposable household income but not smoking or BMI

All-cause, CV, Respiratory, Lung Cancer

Netherlands Cohort Study (NLCS-AIR) Subjects selected from 323 of the 714 municipalities of the Netherlands

Nether-lands

1986 55-69 [20] Beelen et al, 2009

117,528 1987-1996 1987-1996 LUR, Monitoring, GIS: Address-level (baseline address)

Age, sex, smoking, neighbourhood indicators of socioeconomic status but not BMI

CV, CHD, HF, Cerebrovascular, Cardiac Dysrhythmia

[24] Brunekreef B et al 2009

117,528 1987-1996 1987-1996 LUR, Monitoring, GIS: Address-level (baseline address)

Age, sex, smoking, neighbourhood level and COROP area-level percentage of persons with high & low income but not BMI

All-cause, CV, Respiratory, Lung Cancer

[42] Hoek et al 2002

Random sample: 4,492

Sept 1986-Oct 1994

1987-1990 LUR, Monitoring, GIS: Address-level (baseline address)

Age, sex, smoking, BMI, education, occupation

All-cause, Cardio-pulmonary

Oslo cohort Inhabitants of Oslo

Norway 1992 51-90 [53] Naess O et al 2007

143,842 1992-1998 1992-1995 DM: Neighbourhood level

Age, education, occupational class but not smoking or BMI

CV, COPD, Lung Cancer

9

(sex-specific analyses)

North American Cohorts

Adventist Health Study on the Health Effects of Smog (AHSMOG) Sub-sample of the Adventist Health Survey. All subjects, Seventh Day Adventists, white, non-Hispanic and resident in California.

USA 1977 27-95

[29] Chen LH et al 2005

3,239 [1,149 M; 2090 F]

1977-1998 1973-1998: Annual mean, time varying (4-year window)

Monitor data: Interpolation to ZIP code centroid (<50km from monitor), allowing for change of residence

Age, sex, past smoking, BMI, years of education.

CHD

[18] Abbey D et al 1999

5,652 [~3621 F; ~2031 M]

1977-1992 1973-1992: Cumulative monthly mean exposure, time varying

Monitor data: Interpolation to ZIP code centroid (<50km from monitor), allowing for change of residence

Age, sex, past smoking, BMI, years of education (sex-specific analyses)

All-cause, Cardio-pulmonary, Respiratory, Lung Cancer

American Cancer Society Prevention II Study (ACS CSP-II) Friends, neighbours, acquaintances of American Cancer Study (ACS) volunteers

USA 1982 >=30 [61] Turner et al, 2016

669,046 1982-2004 Annual average for 2006

LUR (~30 m): Address-level

Age, sex, smoking, BMI, occupational and educational factors

All-cause, CV, CHD, Cerebrovascular,Respiratory, COPD, Pneumonia, Diabetes, Lung Cancer

[44] Jerrett M et al 2013

73,711 California

1982-2000 1988-2002 LUR: Address-level

Age, sex, smoking, BMI, occupational and educational factors.

All-cause, CV, CHD, Stroke, Respiratory, Lung Cancer

[47] Krewski et al 2009

406,917 1982-2000 1980 Monitoring Data: MSA level

Age, sex, smoking, BMI, occupational and educational factors.

All-cause, Cardio-pulmonary, CHD, Lung Cancer

10

[52] McKean-Cowen et al, 2009

527,123 1982-2000 1982-1998 Monitoring Data: MSA level

Age, sex, smoking, educational level but not BMI

Brain cancer

[43] Krewski et al, 2000

552,138 (295,223 with PM2.5)

1982-1989 1980 Monitoring data: City level

Age, sex, smoking, BMI, educational level

All-cause, Cardio-pulmonary, Lung Cancer

California Teachers Study (CTS) Prospective cohort of female public school professionals living in California.

USA 1995 >=30 [50] Lipset MJ et al 2011

12,336 June 1997-Dec 2005

June 1996-Dec 2005: Cumulative mean exposure, time varying

Monitor data & IDW: 250x250m grid level , allowing for change of residence

Age, smoking, BMI, ecological variables for income, education, unemployment

All-cause, CV, CHD, Cerebrovascular, Respiratory, Lung Cancer

Six Cities Random sample from white subjects in six communities

USA 1974-1977

25-74 [43] Krewski et al, 2000

8,111 1974-1989 1977-1985 Monitor data: City-level

Age, sex, smoking, BMI, education level

All-cause, Cardio-pulmonary, Lung Cancer

US trucking industry cohort Men employed in four trucking companies

USA 1985 15.3-84.9 [40] Hart JE et al 2011

53,814 1985-2000 1985-2000 LUR + spatial smoothing: Address-level

Age, years of work in each of 8 job groups but not smoking or BMI (all male cohort)

All-cause, CV, CHD, Respiratory, COPD, Lung Cancer

Washington University-EPRI Veterans cohort US male veterans with a diagnosis of hypertension

USA 1975-1976

Mean (SD) 51 (12)

[48] Lipfert et al 2006a

~15,200 survivors (1997)

1997-2001 1997-2001 Monitor data: County-level

Age, smoking, BMI, zip code and /or country-level education and income (male only cohort)

All-cause

[49] Lipfert et al 2006b

28,635 survivors (1997)

1997-2001 1999-2001 Monitor data: County-level

Age, smoking, BMI, zip-code level: income, education and poverty status (male only cohort)

All-cause

Canadian Census Health and Environment Cohort (Can CHEC)

Canada 1991 25-89 [32] Crouse DL et al 2015a

735,590 [10 cities]

Jun 1991-Dec 2006

1984-2006: Annual mean exposure, time varying (7-year moving window)

LUR: Post-code level allowing for change in residence

Age, sex, education, employment status, occupational classification,

All-cause, CV, CHD, Cerebrovascular, Respiratory

11

Population based cohort of residents

household income but no direct adjustment for smoking or BMI

[31] Crouse DL et al 2015b

2,521,525 Jun 1991-Dec 2006

1984-2006: Annual mean exposure, time varying (7-year moving window)

LUR: Post-code level allowing for change in residence

Age, sex, education, employment status, occupational classification, household income but no direct adjustment for smoking or BMI

All-cause, CV, CHD, Cerebrovascular, Respiratory, COPD, Diabetes, Lung Cancer

Ontario tax cohort Retrospective cohort study. Random sample from federal family income tax database of subjects living in 3 cities in Ontario.

Canada 1982-1986

35-85 [28] Chen H et al 2013

205,440 1982-2004 1982-2004: 3-year moving average, time varying

LUR: Post-code level allowing for change of residence

Age, sex, annual household income, but not smoking or BMI

CV, CHD, Cerebrovascular

Toronto respiratory cohort Subjects treated at a respiratory disease clinic in Toronto

Canada 1992-1999

Median (IQR) 60 (49-69)

[45] Jerrett M et al 2009

2,360 1992-2002 Average (Autumn 2002 and Spring 2004)

LUR: Address-level

Age, sex, smoking, BMI, EA-level deprivation index

All-cause, CV, Respiratory

Vacouver cohort Long-term (5+ years) residents of Metropolitan

Canada 1999 45-85 [38] Gan WQ et al 2011

452,735 1999-2002 1994-1998 LUR (10m): Address-level allowing for change of residence

Age, sex, neighbourhood socioeconomic status but not smoking or BMI

CHD

12

Vancouver with no CHD history.

[37] Gan WQ et al 2013

467,994 1999-2002 1994-1998 LUR: Address-level allowing for change of residence

Age, sex, neighbourhood socioeconomic status but not smoking or BMI

COPD

Chinese Cohorts

Shenyang cohort Population based retrospective cohort of family members living in 5 urban districts of Shenyang city.

China 2009 35-103 [64] Zhang P et al 2011

9,941 1998-2009 1998-2009: Annual mean exposure, time varying

Monitoring data: District-level

Age, sex, smoking, BMI, educational level, personal income

CV, Cerebrovascular

[34] Dong G-H et al 2012

9,941 1998-2009 1998-2009: Annual mean exposure, time varying

Monitoring data: District-level

Age, sex, smoking, BMI, educational level, household income

Respiratory

Four northern Chinese cities Random sample of neighbourhoods within 1km of a monitor.

China 1998 23-89 [30] Chen et al, 2016

39,054 1998-2009 1998-2009 Annual average, time varying OR 1998 annual average

Monitor data: nearest monitor <1km.

Age, sex, BMI, household income, occupation

All-cause, Lung Cancer

Japanese Cohorts

13

Shizuoka elderly cohort Age-sex - stratification random sample of residents from 74 municipalities of Shizuoka

Japan Dec 1999

65-84 [63] Yorifuji T et al 2010

13,444 Dec 1999-Mar 2006

Apr 2000-Mar 2006

LUR: Address-level

Age, sex, smoking, BMI, financial capability

All-cause, CV, CHD, Cerebrovascular, Cardio-pulmonary, Respiratory, COPD, Pneumonia, Lung Cancer

[62] Yorifuji T et al 2013

13,412 Dec 1999-Jan 2009

Apr 1996-March 2009: Annual mean exposure, time varying

LUR: Address-level

Age, sex, smoking, BMI, financial capability

All-cause, CV, CHD, Cerebrovascular (and sub-types), Cardio-pulmonary, Respiratory, COPD, Pneumonia, Lung Cancer

3 Japanese Prefectures Subjects living in 6 areas in 3 prefectures

Japan 1983-1985

>=40 [46] Katanoda K et al 2011

63,520 10 years (max to Oct 1995)

1974-1983 Monitor data: area-level

Age, sex, smoking, health insurance type / occupational exposure, but not BMI

Respiratory, COPD, Pneumonia, Lung Cancer

Taiwanese Cohort

TCS Civil servants in Greater Taipei area

Taiwan 1989-1992

Employed Mean (SD) 41.3 (10.5)

[60] Tseng et al, 2015

43,227 1992-2008 2000-2008 Monitor data: District-level

Age, sex, smoking, BMI, income, educational level

CV

¶ lung cancer and for female all natural causes not adjusted for BMI; # This is not meant to be a complete list of covariates but focusses only on a few “key” variables.

14

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36. Fischer PH, Marra M, Ameling CB, Hoek G, Beelen R, de Hoogh K, Breugelmans O, Kruize H, Janssen NA, Houthuijs D. Air Pollution and Mortality in Seven Million Adults: The Dutch Environmental Longitudinal Study (DUELS). Environ Health Perspect 2015;123(7):697-704.

37. Gan WQ, FitzGerald JM, Carlsten C, Sadatsafavi M, Brauer M. Associations of ambient air pollution with chronic obstructive pulmonary disease hospitalization and mortality. American Journal of Respiratory and Critical Care Medicine 2013;187(7):721-727.

38. Gan WQ, Koehoorn M, Davies HW, Demers PA, Tamburic L, Brauer M. Long-term exposure to traffic-related air pollution and the risk of coronary heart disease hospitalization and mortality. Environmental Health Perspectives 2011;119(4):501-507.

16

39. Gehring U, Heinrich J, Kramer U, Grote V, Hochadel M, Sugiri D, Kraft M, Rauchfuss K, Eberwein HG, Wichmann HE. Long-term exposure to ambient air pollution and cardiopulmonary mortality in women. Epidemiology 2006;17(5):545-551.

40. Hart JE, Garshick E, Dockery DW, Smith TJ, Ryan L, Laden F. Long-Term Ambient Multipollutant Exposures and Mortality. American Journal of Respiratory and Critical Care Medicine 2011;183(1):73-78.

41. Heinrich J, Thiering E, Rzehak P, Kramer U, Hochadel M, Rauchfuss KM, Gehring U, Wichmann HE. Long-term exposure to NO2 and PM10 and all-cause and cause-specific mortality in a prospective cohort of women. Occupational & Environmental Medicine 2013;70(3):179-86.

42. Hoek G, Brunekreef B, Goldbohm S, Fischer P, Van Den Brandt PA. Association between mortality and indicators of traffic-related air pollution in the Netherlands: A cohort study. Lancet 2002;360(9341):1203-1209.

43. Institute HE. Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and Mortality: A Special Report of the Institute’s Particle Epidemiology Reanalysis Projec. 2000.

44. Jerrett M, Burnett RT, Beckerman BS, Turner MC, Krewski D, Thurston G, Martin RV, van Donkelaar A, Hughes E, Shi Y, Gapstur SM, Thun MJ, Pope CA, 3rd. Spatial analysis of air pollution and mortality in California. Am J Respir Crit Care Med 2013;188(5):593-9.

45. Jerrett M, Finkelstein MM, Brook JR, Arain MA, Kanaroglou P, Stieb DM, Gilbert NL, Verma D, Finkelstein N, Chapman KR, Sears MR. A cohort study of traffic-related air pollution and mortality in Toronto, Ontario, Canada. Environmental Health Perspectives 2009;117(5):772-777.

46. Katanoda K, Sobue T, Satoh H, Tajima K, Suzuki T, Nakatsuka H, Takezaki T, Nakayama T, Nitta H, Tanabe K, Tominaga S. An association between long-term exposure to ambient air pollution and mortality from lung cancer and respiratory diseases in Japan. Journal of Epidemiology 2011;21(2):132-143.

47. Krewski D, Jerrett M, Burnett RT, Ma R, Hughes E, Shi Y, Turner MC, Pope 3rd CA, Thurston G, Calle EE, Thun MJ, Beckerman B, DeLuca P, Finkelstein N, Ito K, Moore DK, Newbold KB, Ramsay T, Ross Z, Shin H, Tempalski B. Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. Research report (Health Effects Institute) 2009(140):5-114; discussion 115-136.

48. Lipfert FW, Baty JD, Miller JP, Wyzga RE. PM2.5 constituents and related air quality variables as predictors of survival in a cohort of U.S. military veterans. Inhalation Toxicology 2006;18(9):645-57.

49. Lipfert FW, Wyzga RE, Baty JD, Miller JP. Traffic density as a surrogate measure of environmental exposures in studies of air pollution health effects: Long-term mortality in a cohort of US veterans. Atmospheric Environment 2006;40(1):154-169.

50. Lipsett MJ, Ostro BD, Reynolds P, Goldberg D, Hertz A, Jerrett M, Smith DF, Garcia C, Chang ET, Bernstein L. Long-term exposure to air pollution and cardiorespiratory disease in the California teachers study cohort. American Journal of Respiratory and Critical Care Medicine 2011;184(7):828-835.

51. Maheswaran R, Pearson T, Smeeton NC, Beevers SD, Campbell MJ, Wolfe CD. Impact of outdoor air pollution on survival after stroke: Population-based cohort study. Stroke 2010;41(5):869-877.

52. McKean-Cowdin R, Calle EE, Peters JM, Henley J, Hannan L, Thurston GD, Thun MJ, Preston-Martin S. Ambient air pollution and brain cancer mortality. Cancer Causes and Control 2009;20(9):1645-1651.

53. Naess O, Nafstad P, Aamodt G, Claussen B, Rosland P. Relation between concentration of air pollution and cause-specific mortality: Four-year exposures to nitrogen dioxide and

17

particulate matter pollutants in 470 neighborhoods in Oslo, Norway. American Journal of Epidemiology 2007;165(4):435-443.

54. Raaschou-Nielsen O, Andersen ZJ, Jensen SS, Ketzel M, Sorensen M, Hansen J, Loft S, Tjonneland A, Overvad K. Traffic air pollution and mortality from cardiovascular disease and all causes: a Danish cohort study. Environmental Health: A Global Access Science Source 2012;11:60.

55. Raaschou-Nielsen O, Sorensen M, Ketzel M, Hertel O, Loft S, Tjonneland A, Overvad K, Andersen ZJ. Long-term exposure to traffic-related air pollution and diabetes-associated mortality: a cohort study. Diabetologia 2013;56(1):36-46.

56. Rosenlund M, Picciotto S, Forastiere F, Stafoggia M, Perucci CA. Traffic-related air pollution in relation to incidence and prognosis of coronary heart disease. Epidemiology 2008;19(1):121-128.

57. Schikowski T, Sugiri D, Ranft U, Gehring U, Heinrich J, Wichmann HE, Kramer U. Does respiratory health contribute to the effects of long-term air pollution exposure on cardiovascular mortality? Respiratory research 2007;8:20.

58. Sorensen M, Luhdorf P, Ketzel M, Andersen ZJ, Tjonneland A, Overvad K, Raaschou-Nielsen O. Combined effects of road traffic noise and ambient air pollution in relation to risk for stroke? Environmental Research 2014;133:49-55.

59. Tonne C, Wilkinson P. Long-term exposure to air pollution is associated with survival following acute coronary syndrome. European Heart Journal 2013;34(17):1306-1311.

60. Tseng E, Ho WC, Lin MH, Cheng TJ, Chen PC, Lin HH. Chronic exposure to particulate matter and risk of cardiovascular mortality: cohort study from Taiwan. BMC Public Health 2015;15:936.

61. Turner MC, Jerrett M, Pope CA, Krewski D, Gapstur SM, Diver WR, Beckerman BS, Marshall JD, Su J, Crouse DL, Burnett RT. Long-Term Ozone Exposure and Mortality in a Large Prospective Study. American Journal of Respiratory and Critical Care Medicine 2016;193(10):1134-1142.

62. Yorifuji T, Kashima S, Tsuda T, Ishikawa-Takata K, Ohta T, Tsuruta K, Doi H. Long-term exposure to traffic-related air pollution and the risk of death from hemorrhagic stroke and lung cancer in Shizuoka, Japan. Science of the Total Environment 2013;443:397-402.

63. Yorifuji T, Kashima S, Tsuda T, Takao S, Suzuki E, Doi H, Sugiyama M, Ishikawa-Takata K, Ohta T. Long-term exposure to traffic-related air pollution and mortality in Shizuoka, Japan. Occupational and Environmental Medicine 2010;67(2):111-117.

64. Zhang PF, Dong GH, Sun BJ, Zhang LW, Chen X, Ma NN, Yu F, Guo HM, Huang H, Lee YL, Tang NJ, Chen J. Long-Term Exposure to Ambient Air Pollution and Mortality Due to Cardiovascular Disease and Cerebrovascular Disease in Shenyang, China. Plos One 2011;6(6).

65. Tonne C, Halonen JI, Beevers SD, Dajnak D, Gulliver J, Kelly FJ, Wilkinson P, Anderson HR. Long-term traffic air and noise pollution in relation to mortality and hospital readmission among myocardial infarction survivors. International Journal of Hygiene & Environmental Health 2016;219(1):72-8.

18

eFigure 1 All-cause mortality

* indicates exclusion from meta-analysis. Refer to methods/results sections of manuscript.

Crouse et al *

Crouse et al

Jerrett et al

HEI *

Krewski et al *

Jerrett et al *

Turner et al

Abbey et al

Lipsett et al

HEI

Hart et al

Lipfert et al *

Lipfert et al

Raaschou-Nielsen et al *

Carey et al

Maheswaren et al

Tonne et al

Beelen et al

Bentayeb et al

Filleul et al

Gehring et al *

Heinrich et al *

Rosenlund et al

Cesaroni et al *

Cesaroni et al

Tonne et al *

Fischer et al

Hoek et al *

Brunekreef et al

Chen et al

Yorifuji et al *

Yorifuji et al

Study

2015a

2015b

2009

2000

2009

2013

2016

1999

2011

2000

2011

2006a

2006b

2012

2013

2010

2013

2014b

2015

2005

2006

2013

2008

2012

2013

2016

2015

2002

2009

2016

2010

2013

Year

CanCHEC

CanCHEC

Toronto respiratory cohort

ACS CPS-II

ACS CPS-II

ACS CPS-II

ACS CPS-II

AHSMOG

CTS

Six Cities

US trucking industry cohort

Washington University-EPRI Veterans cohort

Washington University-EPRI Veterans cohort

DCH

CPRD

SLSR

MINAP (ACS survivors)

ESCAPE

Gazel

PAARC

German cohort

German cohort

CHD survivors cohort

Rome longitudinal study

Rome longitudinal study

MINAP (ACS survivors)

DUELS

NLCS-AIR

NLCS-AIR

Four northern Chinese cities

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

Canada

Canada

USA

USA

USA

USA

USA

USA

USA

USA

USA

USA

Denmark

England

England

England & Wales

Europe

France

France

Germany

Germany

Italy

Italy

Italy

London

Netherlands

Netherlands

Netherlands

China

Japan

Japan

Setting

735,590

2,521,525

2,360

552,138

406,917

73,711

669,046

5,652

12,336

8,111

53,814

~15,200

28,635

52,061

830,429

3,320

154,204

367,251

20,327

14,284

4,752

4,752

6,513

684,204

1,265,058

18,138

7,218,363

2,788

117,528

39,054

13,444

13,412

N

FM

FM

FM

FM

FM

FM

FM

FM

F

FM

M

M

M

FM

FM

FM

FM

FM

FM

FM

F

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

Sex

25-89

25-89

60 (49 69)

>=30

>=30

>=30

>=30

27-95

>=30

25-74

15.3-84.9

51 (12)

51 (12)

50-64

40-89

70.4 (14.6)

>25

All

35-50

25-59

50-59

50-59

35-84

45-80

>=30

>25

>=30

55-69

55-69

23-89

65-84

65-84

Age

Indirect smoking and BMI

Indirect smoking and BMI

No BMI, Smoking

No BMI

No BMI

No BMI, Age

No BMI, Age(?)

No BMI, Smoking

No BMI, Smoking

No BMI, Smoking

No BMI

No BMI, Smoking

No BMI

Adjustment

Confounder

1.05 (1.03, 1.07)

1.03 (1.03, 1.04)

1.23 (1.00, 1.51)

0.99 (0.99, 1.00)

1.00 (0.99, 1.00)

1.04 (1.01, 1.07)

1.02 (1.01, 1.03)

1.00 (0.98, 1.02)

0.98 (0.95, 1.02)

1.08 (1.02, 1.14)

1.05 (1.03, 1.08)

1.02 (0.98, 1.07)

1.03 (0.99, 1.07)

1.08 (1.02, 1.15)

1.02 (1.00, 1.05)

1.41 (1.14, 1.75)

1.01 (0.98, 1.04)

1.01 (0.99, 1.03)

1.07 (1.00, 1.15)

1.14 (1.03, 1.26)

1.12 (1.01, 1.23)

1.11 (1.04, 1.18)

0.95 (0.89, 1.02)

1.06 (1.04, 1.08)

1.03 (1.02, 1.03)

1.05 (0.98, 1.12)

1.03 (1.02, 1.03)

1.08 (0.94, 1.23)

1.03 (1.00, 1.05)

0.93 (0.90, 0.95)

1.02 (0.96, 1.08)

1.12 (1.07, 1.18)

ES (95% CI)

1.05 (1.03, 1.07)

1.03 (1.03, 1.04)

1.23 (1.00, 1.51)

0.99 (0.99, 1.00)

1.00 (0.99, 1.00)

1.04 (1.01, 1.07)

1.02 (1.01, 1.03)

1.00 (0.98, 1.02)

0.98 (0.95, 1.02)

1.08 (1.02, 1.14)

1.05 (1.03, 1.08)

1.02 (0.98, 1.07)

1.03 (0.99, 1.07)

1.08 (1.02, 1.15)

1.02 (1.00, 1.05)

1.41 (1.14, 1.75)

1.01 (0.98, 1.04)

1.01 (0.99, 1.03)

1.07 (1.00, 1.15)

1.14 (1.03, 1.26)

1.12 (1.01, 1.23)

1.11 (1.04, 1.18)

0.95 (0.89, 1.02)

1.06 (1.04, 1.08)

1.03 (1.02, 1.03)

1.05 (0.98, 1.12)

1.03 (1.02, 1.03)

1.08 (0.94, 1.23)

1.03 (1.00, 1.05)

0.93 (0.90, 0.95)

1.02 (0.96, 1.08)

1.12 (1.07, 1.18)

ES (95% CI)

1.9 1 1.1 1.2

19

eFigure 2a All-cause mortality – fixed effects model

eFigure 2b All-cause mortality - random effects model

Overall (I-squared = 83.9%, p = 0.000)

Crouse et al

Jerrett et al

Carey et al

HEI

Fischer et al

Lipsett et al

Lipfert et al

Yorifuji et al

Abbey et al

Study

Filleul et al

Maheswaren et al

Bentayeb et al

Cesaroni et al

Chen et al

Tonne et al

Beelen et al

Hart et al

Turner et al

Brunekreef et al

Rosenlund et al

2015b

2009

2013

2000

2015

2011

2006b

2013

1999

Year

2005

2010

2015

2013

2016

2013

2014b

2011

2016

2009

2008

CanCHEC

Toronto respiratory cohort

CPRD

Six Cities

DUELS

CTS

Washington University-EPRI Veterans cohort

Shizuoka elderly cohort

AHSMOG

Cohort

PAARC

SLSR

Gazel

Rome longitudinal study

Four northern Chinese cities

MINAP (ACS survivors)

ESCAPE

US trucking industry cohort

ACS CPS-II

NLCS-AIR

CHD survivors cohort

Canada

Canada

England

USA

Netherlands

USA

USA

Japan

USA

Setting

France

England

France

Italy

China

England & Wales

Europe

USA

USA

Netherlands

Italy

2,521,525

2,360

830,429

8,111

7,218,363

12,336

28,635

13,412

5,652

N

14,284

3,320

20,327

1,265,058

39,054

154,204

367,251

53,814

669,046

117,528

6,513

1.03 (1.02, 1.03)

1.03 (1.03, 1.04)

1.23 (1.00, 1.51)

1.02 (1.00, 1.05)

1.08 (1.02, 1.14)

1.03 (1.02, 1.03)

0.98 (0.95, 1.02)

1.03 (0.99, 1.07)

1.12 (1.07, 1.18)

1.00 (0.98, 1.02)

ES (95% CI)

1.14 (1.03, 1.26)

1.41 (1.14, 1.75)

1.07 (1.00, 1.15)

1.03 (1.02, 1.03)

0.93 (0.90, 0.95)

1.01 (0.98, 1.04)

1.01 (0.99, 1.03)

1.05 (1.03, 1.08)

1.02 (1.01, 1.03)

1.03 (1.00, 1.05)

0.95 (0.89, 1.02)

100.00

15.10

0.01

1.00

0.22

51.16

0.50

0.47

0.27

1.23

Weight

0.06

0.01

0.11

13.49

0.73

0.67

1.69

1.10

11.08

%

0.96

0.13

1.03 (1.02, 1.03)

1.03 (1.03, 1.04)

1.23 (1.00, 1.51)

1.02 (1.00, 1.05)

1.08 (1.02, 1.14)

1.03 (1.02, 1.03)

0.98 (0.95, 1.02)

1.03 (0.99, 1.07)

1.12 (1.07, 1.18)

1.00 (0.98, 1.02)

ES (95% CI)

1.14 (1.03, 1.26)

1.41 (1.14, 1.75)

1.07 (1.00, 1.15)

1.03 (1.02, 1.03)

0.93 (0.90, 0.95)

1.01 (0.98, 1.04)

1.01 (0.99, 1.03)

1.05 (1.03, 1.08)

1.02 (1.01, 1.03)

1.03 (1.00, 1.05)

0.95 (0.89, 1.02)

100.00

15.10

0.01

1.00

0.22

51.16

0.50

0.47

0.27

1.23

Weight

0.06

0.01

0.11

13.49

0.73

0.67

1.69

1.10

11.08

%

0.96

0.13

1.9 1 1.1 1.2

NOTE: Weights are from random effects analysis

. (0.99, 1.06)with estimated predictive interval

Overall (I-squared = 83.9%, p = 0.000)

Lipsett et al

Rosenlund et al

Maheswaren et al

Chen et al

Beelen et al

Carey et al

Abbey et al

Yorifuji et al

Filleul et al

HEI

Hart et al

Lipfert et al

Brunekreef et al

Turner et al

Study

Bentayeb et al

Tonne et al

Cesaroni et al

Jerrett et al

Crouse et al

Fischer et al

2011

2008

2010

2016

2014b

2013

1999

2013

2005

2000

2011

2006b

2009

2016

Year

2015

2013

2013

2009

2015b

2015

CTS

CHD survivors cohort

SLSR

Four northern Chinese cities

ESCAPE

CPRD

AHSMOG

Shizuoka elderly cohort

PAARC

Six Cities

US trucking industry cohort

Washington University-EPRI Veterans cohort

NLCS-AIR

ACS CPS-II

Cohort

Gazel

MINAP (ACS survivors)

Rome longitudinal study

Toronto respiratory cohort

CanCHEC

DUELS

USA

Italy

England

China

Europe

England

USA

Japan

France

USA

USA

USA

Netherlands

USA

Setting

France

England & Wales

Italy

Canada

Canada

Netherlands

12,336

6,513

3,320

39,054

367,251

830,429

5,652

13,412

14,284

8,111

53,814

28,635

117,528

669,046

N

20,327

154,204

1,265,058

2,360

2,521,525

7,218,363

1.02 (1.01, 1.03)

0.98 (0.95, 1.02)

0.95 (0.89, 1.02)

1.41 (1.14, 1.75)

0.93 (0.90, 0.95)

1.01 (0.99, 1.03)

1.02 (1.00, 1.05)

1.00 (0.98, 1.02)

1.12 (1.07, 1.18)

1.14 (1.03, 1.26)

1.08 (1.02, 1.14)

1.05 (1.03, 1.08)

1.03 (0.99, 1.07)

1.03 (1.00, 1.05)

1.02 (1.01, 1.03)

ES (95% CI)

1.07 (1.00, 1.15)

1.01 (0.98, 1.04)

1.03 (1.02, 1.03)

1.23 (1.00, 1.51)

1.03 (1.03, 1.04)

1.03 (1.02, 1.03)

100.00

4.31

1.60

0.19

5.26

7.28

6.06

6.58

2.90

%

0.86

2.45

6.31

4.17

5.97

9.65

Weight

1.45

5.07

9.76

0.21

9.81

10.12

1.02 (1.01, 1.03)

0.98 (0.95, 1.02)

0.95 (0.89, 1.02)

1.41 (1.14, 1.75)

0.93 (0.90, 0.95)

1.01 (0.99, 1.03)

1.02 (1.00, 1.05)

1.00 (0.98, 1.02)

1.12 (1.07, 1.18)

1.14 (1.03, 1.26)

1.08 (1.02, 1.14)

1.05 (1.03, 1.08)

1.03 (0.99, 1.07)

1.03 (1.00, 1.05)

1.02 (1.01, 1.03)

ES (95% CI)

1.07 (1.00, 1.15)

1.01 (0.98, 1.04)

1.03 (1.02, 1.03)

1.23 (1.00, 1.51)

1.03 (1.03, 1.04)

1.03 (1.02, 1.03)

100.00

4.31

1.60

0.19

5.26

7.28

6.06

6.58

2.90

%

0.86

2.45

6.31

4.17

5.97

9.65

Weight

1.45

5.07

9.76

0.21

9.81

10.12

1.9 1 1.1 1.2

20

eFigure 3 All-cause mortality - stratification by pre-existing disease on recruitment

NOTE: Weights are from random effects analysis

.

.

General

Crouse et al

Hart et al

Lipsett et al

Abbey et al

HEI

Turner et al

Carey et al

Beelen et al

Filleul et al

Bentayeb et al

Cesaroni et al

Fischer et al

Brunekreef et al

Chen et al

Yorifuji et al

Subtotal (I-squared = 86.1%, p = 0.000)

Preexisting

Jerrett et al

Lipfert et al

Maheswaren et al

Tonne et al

Rosenlund et al

Subtotal (I-squared = 76.3%, p = 0.002)

Study

2015b

2011

2011

1999

2000

2016

2013

2014b

2005

2015

2013

2015

2009

2016

2013

2009

2006b

2010

2013

2008

Year

CanCHEC

US trucking industry cohort

CTS

AHSMOG

Six Cities

ACS CPS-II

CPRD

ESCAPE

PAARC

Gazel

Rome longitudinal study

DUELS

NLCS-AIR

Four northern Chinese cities

Shizuoka elderly cohort

Toronto respiratory cohort

Washington University-EPRI Veterans cohort

SLSR

MINAP (ACS survivors)

CHD survivors cohort

Cohort

Canada

USA

USA

USA

USA

USA

England

Europe

France

France

Italy

Netherlands

Netherlands

China

Japan

Canada

USA

England

England & Wales

Italy

Setting

2,521,525

53,814

12,336

5,652

8,111

669,046

830,429

367,251

14,284

20,327

1,265,058

7,218,363

117,528

39,054

13,412

2,360

28,635

3,320

154,204

6,513

N

FM

M

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

M

FM

FM

FM

Sex

25-89

15.3-84.9

>=30

27-95

25-74

>=30

40-89

All

25-59

35-50

>=30

>=30

55-69

23-89

65-84

60 (49 69)

51 (12)

70.4 (14.6)

>25

35-84

Age

1.03 (1.03, 1.04)

1.05 (1.03, 1.08)

0.98 (0.95, 1.02)

1.00 (0.98, 1.02)

1.08 (1.02, 1.14)

1.02 (1.01, 1.03)

1.02 (1.00, 1.05)

1.01 (0.99, 1.03)

1.14 (1.03, 1.26)

1.07 (1.00, 1.15)

1.03 (1.02, 1.03)

1.03 (1.02, 1.03)

1.03 (1.00, 1.05)

0.93 (0.90, 0.95)

1.12 (1.07, 1.18)

1.02 (1.01, 1.03)

1.23 (1.00, 1.51)

1.03 (0.99, 1.07)

1.41 (1.14, 1.75)

1.01 (0.98, 1.04)

0.95 (0.89, 1.02)

1.04 (0.98, 1.10)

ES (95% CI)

11.34

7.01

4.69

7.34

2.62

11.14

6.72

8.18

0.91

1.53

11.28

11.74

6.62

5.78

3.11

100.00

6.73

31.07

6.23

32.14

23.84

100.00

Weight

%

1.03 (1.03, 1.04)

1.05 (1.03, 1.08)

0.98 (0.95, 1.02)

1.00 (0.98, 1.02)

1.08 (1.02, 1.14)

1.02 (1.01, 1.03)

1.02 (1.00, 1.05)

1.01 (0.99, 1.03)

1.14 (1.03, 1.26)

1.07 (1.00, 1.15)

1.03 (1.02, 1.03)

1.03 (1.02, 1.03)

1.03 (1.00, 1.05)

0.93 (0.90, 0.95)

1.12 (1.07, 1.18)

1.02 (1.01, 1.03)

1.23 (1.00, 1.51)

1.03 (0.99, 1.07)

1.41 (1.14, 1.75)

1.01 (0.98, 1.04)

0.95 (0.89, 1.02)

1.04 (0.98, 1.10)

ES (95% CI)

11.34

7.01

4.69

7.34

2.62

11.14

6.72

8.18

0.91

1.53

11.28

11.74

6.62

5.78

3.11

100.00

6.73

31.07

6.23

32.14

23.84

100.00

Weight

%

1.9 1 1.1 1.2

21

eFigure 4 All-cause mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Crouse et al

Hart et al

Lipsett et al

Abbey et al

HEI

Turner et al

Carey et al

Beelen et al

Cesaroni et al

Fischer et al

Chen et al

Subtotal (I-squared = 87.6%, p = 0.000)

Restricted

Filleul et al

Bentayeb et al

Brunekreef et al

Yorifuji et al

Subtotal (I-squared = 78.9%, p = 0.003)

Study

2015b

2011

2011

1999

2000

2016

2013

2014b

2013

2015

2016

2005

2015

2009

2013

Year

CanCHEC

US trucking industry cohort

CTS

AHSMOG

Six Cities

ACS CPS-II

CPRD

ESCAPE

Rome longitudinal study

DUELS

Four northern Chinese cities

PAARC

Gazel

NLCS-AIR

Shizuoka elderly cohort

Cohort

Canada

USA

USA

USA

USA

USA

England

Europe

Italy

Netherlands

China

France

France

Netherlands

Japan

Setting

2,521,525

53,814

12,336

5,652

8,111

669,046

830,429

367,251

1,265,058

7,218,363

39,054

14,284

20,327

117,528

13,412

N

FM

M

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

Sex

25-89

15.3-84.9

>=30

27-95

25-74

>=30

40-89

All

>=30

>=30

23-89

25-59

35-50

55-69

65-84

Age

1.03 (1.03, 1.04)

1.05 (1.03, 1.08)

0.98 (0.95, 1.02)

1.00 (0.98, 1.02)

1.08 (1.02, 1.14)

1.02 (1.01, 1.03)

1.02 (1.00, 1.05)

1.01 (0.99, 1.03)

1.03 (1.02, 1.03)

1.03 (1.02, 1.03)

0.93 (0.90, 0.95)

1.02 (1.01, 1.03)

1.14 (1.03, 1.26)

1.07 (1.00, 1.15)

1.03 (1.00, 1.05)

1.12 (1.07, 1.18)

1.08 (1.02, 1.15)

ES (95% CI)

13.36

7.73

4.99

8.12

2.70

13.09

7.38

9.18

13.27

13.92

6.25

100.00

17.45

22.27

32.27

28.01

100.00

Weight

%

1.03 (1.03, 1.04)

1.05 (1.03, 1.08)

0.98 (0.95, 1.02)

1.00 (0.98, 1.02)

1.08 (1.02, 1.14)

1.02 (1.01, 1.03)

1.02 (1.00, 1.05)

1.01 (0.99, 1.03)

1.03 (1.02, 1.03)

1.03 (1.02, 1.03)

0.93 (0.90, 0.95)

1.02 (1.01, 1.03)

1.14 (1.03, 1.26)

1.07 (1.00, 1.15)

1.03 (1.00, 1.05)

1.12 (1.07, 1.18)

1.08 (1.02, 1.15)

ES (95% CI)

13.36

7.73

4.99

8.12

2.70

13.09

7.38

9.18

13.27

13.92

6.25

100.00

17.45

22.27

32.27

28.01

100.00

Weight

%

1.9 1 1.1 1.2

22

eFigure 5 Cardiovascular mortality

* indicates exclusion from meta-analysis. Refer to methods/results section of manuscript.

Chen et al

Crouse et al *

Crouse et al

Jerrett et al

Hart et al

Jerrett et al *

Lipsett et al

Turner et al

Zhang et al *

Raaschou-Nielsen et al *

Carey et al

Beelen et al

Bentayeb et al

Schikowski et al *

Cesaroni et al

Beelen et al *

Brunekreef et al

Fischer et al

Naess et al

Tseng et al

Yorifuji et al *

Yorifuji et al

Study

2013

2015a

2015b

2009

2011

2013

2011

2016

2011

2012

2013

2014a

2015

2007

2013

2009

2009

2015

2007

2015

2010

2013

Year

Ontario tax cohort

CanCHEC

CanCHEC

Toronto respiratory cohort

US trucking industry cohort

ACS CPS-II

CTS

ACS CPS-II

Shenyang cohort

DCH

CPRD

ESCAPE

Gazel

German cohort

Rome longitudinal study

NLCS-AIR

NLCS-AIR

DUELS

Oslo cohort

TCS

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

Canada

Canada

Canada

USA

USA

USA

USA

China

Denmark

England

Europe

France

Germany

Italy

Netherlands

Netherlands

Netherlands

Norway

Taiwan

Japan

Japan

Setting

205,440

735,590

2,521,525

2,360

53,814

73,711

12,336

669,046

9,941

52,061

830,429

367,383

20,327

4,750

1,265,058

117,528

117,528

7,218,363

143,842

43,227

13,444

13,412

N

FM

FM

FM

FM

M

FM

F

FM

FM

FM

FM

FM

FM

F

FM

FM

FM

FM

FM

FM

FM

FM

Sex

35-85

25-89

25-89

60 (49 69)

15.3-84.9

>=30

>=30

>=30

35-103

50-64

40-89

All

35-50

50-59

>=30

55-69

55-69

>=30

51-90

41.3 (10.5)

65-84

65-84

Age

Indirect Smoking, No BMI

Indirect smoking and BMI

Indirect smoking and BMI

No BMI, Smoking

No BMI, Age

No BMI, Smoking

No BMI

No BMI

No BMI, Smoking

No BMI, Smoking

Adjustment

Confounder

1.08 (1.03, 1.12)

1.04 (1.02, 1.07)

1.03 (1.02, 1.04)

1.64 (1.13, 2.37)

1.04 (1.00, 1.09)

1.06 (1.01, 1.11)

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

2.46 (2.31, 2.62)

1.16 (1.03, 1.31)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

1.00 (0.76, 1.30)

1.40 (1.14, 1.72)

1.03 (1.02, 1.04)

1.03 (0.98, 1.08)

1.02 (0.98, 1.07)

1.00 (0.99, 1.01)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.15 (1.03, 1.28)

1.24 (1.15, 1.33)

ES (95% CI)

1.08 (1.03, 1.12)

1.04 (1.02, 1.07)

1.03 (1.02, 1.04)

1.64 (1.13, 2.37)

1.04 (1.00, 1.09)

1.06 (1.01, 1.11)

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

2.46 (2.31, 2.62)

1.16 (1.03, 1.31)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

1.00 (0.76, 1.30)

1.40 (1.14, 1.72)

1.03 (1.02, 1.04)

1.03 (0.98, 1.08)

1.02 (0.98, 1.07)

1.00 (0.99, 1.01)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.15 (1.03, 1.28)

1.24 (1.15, 1.33)

ES (95% CI)

1.9 1 1.11.2

23

eFigure 6a Cardiovascular mortality – fixed effects model

eFigure 6b Cardiovascular mortality – random effects model

Overall (I-squared = 83.4%, p = 0.000)

Yorifuji et al

Carey et al

Tseng et al

Hart et al

Brunekreef et al

Turner et al

Cesaroni et al

Beelen et al

Fischer et al

Lipsett et al

Jerrett et al

Crouse et al

Naess et al

Chen et al

Bentayeb et al

Study

2013

2013

2015

2011

2009

2016

2013

2014a

2015

2011

2009

2015b

2007

2013

2015

Year

Shizuoka elderly cohort

CPRD

TCS

US trucking industry cohort

NLCS-AIR

ACS CPS-II

Rome longitudinal study

ESCAPE

DUELS

CTS

Toronto respiratory cohort

CanCHEC

Oslo cohort

Ontario tax cohort

Gazel

Cohort

Japan

England

Taiwan

USA

Netherlands

USA

Italy

Europe

Netherlands

USA

Canada

Canada

Norway

Canada

France

Setting

13,412

830,429

43,227

53,814

117,528

669,046

1,265,058

367,383

7,218,363

12,336

2,360

2,521,525

143,842

205,440

20,327

N

1.03 (1.02, 1.03)

1.24 (1.15, 1.33)

1.00 (0.97, 1.03)

0.95 (0.75, 1.21)

1.04 (1.00, 1.09)

1.02 (0.98, 1.07)

1.04 (1.03, 1.05)

1.03 (1.02, 1.04)

1.01 (0.97, 1.06)

1.00 (0.99, 1.01)

0.99 (0.94, 1.05)

1.64 (1.13, 2.37)

1.03 (1.02, 1.04)

1.02 (1.00, 1.05)

1.08 (1.03, 1.12)

1.00 (0.76, 1.30)

ES (95% CI)

100.00

0.33

2.24

0.03

1.09

1.00

29.69

18.67

%

0.89

17.60

0.57

0.01

22.97

4.00

0.87

0.03

Weight

1.03 (1.02, 1.03)

1.24 (1.15, 1.33)

1.00 (0.97, 1.03)

0.95 (0.75, 1.21)

1.04 (1.00, 1.09)

1.02 (0.98, 1.07)

1.04 (1.03, 1.05)

1.03 (1.02, 1.04)

1.01 (0.97, 1.06)

1.00 (0.99, 1.01)

0.99 (0.94, 1.05)

1.64 (1.13, 2.37)

1.03 (1.02, 1.04)

1.02 (1.00, 1.05)

1.08 (1.03, 1.12)

1.00 (0.76, 1.30)

ES (95% CI)

100.00

0.33

2.24

0.03

1.09

1.00

29.69

18.67

%

0.89

17.60

0.57

0.01

22.97

4.00

0.87

0.03

Weight

1.9 1 1.11.2

NOTE: Weights are from random effects analysis

. (0.98, 1.08)with estimated predictive interval

Overall (I-squared = 83.4%, p = 0.000)

Tseng et al

Crouse et al

Turner et al

Yorifuji et al

Jerrett et al

Hart et al

Chen et al

Brunekreef et al

Naess et al

Cesaroni et al

Bentayeb et al

Beelen et al

Lipsett et al

Study

Carey et al

Fischer et al

2015

2015b

2016

2013

2009

2011

2013

2009

2007

2013

2015

2014a

2011

Year

2013

2015

TCS

CanCHEC

ACS CPS-II

Shizuoka elderly cohort

Toronto respiratory cohort

US trucking industry cohort

Ontario tax cohort

NLCS-AIR

Oslo cohort

Rome longitudinal study

Gazel

ESCAPE

CTS

Cohort

CPRD

DUELS

Taiwan

Canada

USA

Japan

Canada

USA

Canada

Netherlands

Norway

Italy

France

Europe

USA

Setting

England

Netherlands

43,227

2,521,525

669,046

13,412

2,360

53,814

205,440

117,528

143,842

1,265,058

20,327

367,383

12,336

N

830,429

7,218,363

1.03 (1.02, 1.05)

0.95 (0.75, 1.21)

1.03 (1.02, 1.04)

1.04 (1.03, 1.05)

1.24 (1.15, 1.33)

1.64 (1.13, 2.37)

1.04 (1.00, 1.09)

1.08 (1.03, 1.12)

1.02 (0.98, 1.07)

1.02 (1.00, 1.05)

1.03 (1.02, 1.04)

1.00 (0.76, 1.30)

1.01 (0.97, 1.06)

0.99 (0.94, 1.05)

ES (95% CI)

1.00 (0.97, 1.03)

1.00 (0.99, 1.01)

100.00

0.34

12.37

12.50

2.96

0.15

6.38

5.66

6.08

10.12

12.24

0.28

5.74

%

4.36

Weight

8.64

12.19

1.03 (1.02, 1.05)

0.95 (0.75, 1.21)

1.03 (1.02, 1.04)

1.04 (1.03, 1.05)

1.24 (1.15, 1.33)

1.64 (1.13, 2.37)

1.04 (1.00, 1.09)

1.08 (1.03, 1.12)

1.02 (0.98, 1.07)

1.02 (1.00, 1.05)

1.03 (1.02, 1.04)

1.00 (0.76, 1.30)

1.01 (0.97, 1.06)

0.99 (0.94, 1.05)

ES (95% CI)

1.00 (0.97, 1.03)

1.00 (0.99, 1.01)

100.00

0.34

12.37

12.50

2.96

0.15

6.38

5.66

6.08

10.12

12.24

0.28

5.74

%

4.36

Weight

8.64

12.19

1.9 1 1.11.2

24

eFigure 7 Cardiovascular mortality - stratification by pre-existing disease on recruitment

NOTE: Weights are from random effects analysis

.

.

General

Chen et al

Crouse et al

Hart et al

Lipsett et al

Turner et al

Carey et al

Beelen et al

Bentayeb et al

Cesaroni et al

Fischer et al

Brunekreef et al

Naess et al

Tseng et al

Yorifuji et al

Subtotal (I-squared = 83.3%, p = 0.000)

Preexisting

Jerrett et al

Subtotal (I-squared = .%, p = .)

Study

2013

2015b

2011

2011

2016

2013

2014a

2015

2013

2015

2009

2007

2015

2013

2009

Year

Ontario tax cohort

CanCHEC

US trucking industry cohort

CTS

ACS CPS-II

CPRD

ESCAPE

Gazel

Rome longitudinal study

DUELS

NLCS-AIR

Oslo cohort

TCS

Shizuoka elderly cohort

Toronto respiratory cohort

Cohort

Canada

Canada

USA

USA

USA

England

Europe

France

Italy

Netherlands

Netherlands

Norway

Taiwan

Japan

Canada

Setting

205,440

2,521,525

53,814

12,336

669,046

830,429

367,383

20,327

1,265,058

7,218,363

117,528

143,842

43,227

13,412

2,360

N

FM

FM

M

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

Sex

35-85

25-89

15.3-84.9

>=30

>=30

40-89

All

35-50

>=30

>=30

55-69

51-90

41.3 (10.5)

65-84

60 (49 69)

Age

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

1.00 (0.76, 1.30)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.02 (0.98, 1.07)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.24 (1.15, 1.33)

1.03 (1.02, 1.04)

1.64 (1.13, 2.37)

1.64 (1.13, 2.37)

ES (95% CI)

5.54

12.59

6.27

4.23

12.74

8.60

5.62

0.27

12.45

12.40

5.97

10.16

0.32

2.85

100.00

100.00

100.00

Weight

%

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

1.00 (0.76, 1.30)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.02 (0.98, 1.07)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.24 (1.15, 1.33)

1.03 (1.02, 1.04)

1.64 (1.13, 2.37)

1.64 (1.13, 2.37)

ES (95% CI)

5.54

12.59

6.27

4.23

12.74

8.60

5.62

0.27

12.45

12.40

5.97

10.16

0.32

2.85

100.00

100.00

100.00

Weight

%

1.7 .8 .9 1 1.11.21.3

25

eFigure 8 Cardiovascular mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Chen et al

Crouse et al

Hart et al

Lipsett et al

Turner et al

Carey et al

Beelen et al

Cesaroni et al

Fischer et al

Naess et al

Tseng et al

Subtotal (I-squared = 80.8%, p = 0.000)

Restricted

Bentayeb et al

Brunekreef et al

Yorifuji et al

Subtotal (I-squared = 90.2%, p = 0.000)

Study

2013

2015b

2011

2011

2016

2013

2014a

2013

2015

2007

2015

2015

2009

2013

Year

Ontario tax cohort

CanCHEC

US trucking industry cohort

CTS

ACS CPS-II

CPRD

ESCAPE

Rome longitudinal study

DUELS

Oslo cohort

TCS

Gazel

NLCS-AIR

Shizuoka elderly cohort

Cohort

Canada

Canada

USA

USA

USA

England

Europe

Italy

Netherlands

Norway

Taiwan

France

Netherlands

Japan

Setting

205,440

2,521,525

53,814

12,336

669,046

830,429

367,383

1,265,058

7,218,363

143,842

43,227

20,327

117,528

13,412

N

FM

FM

M

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

Sex

35-85

25-89

15.3-84.9

>=30

>=30

40-89

All

>=30

>=30

51-90

41.3 (10.5)

35-50

55-69

65-84

Age

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.02 (1.01, 1.04)

1.00 (0.76, 1.30)

1.02 (0.98, 1.07)

1.24 (1.15, 1.33)

1.10 (0.93, 1.29)

ES (95% CI)

5.20

14.95

6.01

3.82

15.21

8.88

5.29

14.70

14.62

11.06

0.26

100.00

19.65

41.28

39.07

100.00

Weight

%

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.02 (1.01, 1.04)

1.00 (0.76, 1.30)

1.02 (0.98, 1.07)

1.24 (1.15, 1.33)

1.10 (0.93, 1.29)

ES (95% CI)

5.20

14.95

6.01

3.82

15.21

8.88

5.29

14.70

14.62

11.06

0.26

100.00

19.65

41.28

39.07

100.00

Weight

%

1.7 .8 .9 1 1.1 1.2 1.3

26

eFigure 9 Cardiovascular mortality - stratification by level of adjustment for smoking and BMI

NOTE: Weights are from random effects analysis

.

.

Individual

Lipsett et al

Turner et al

Carey et al

Beelen et al

Tseng et al

Subtotal (I-squared = 68.0%, p = 0.014)

None/Indirect

Chen et al

Crouse et al

Hart et al

Cesaroni et al

Fischer et al

Naess et al

Subtotal (I-squared = 82.4%, p = 0.000)

Study

2011

2016

2013

2014a

2015

2013

2015b

2011

2013

2015

2007

Year

CTS

ACS CPS-II

CPRD

ESCAPE

TCS

Ontario tax cohort

CanCHEC

US trucking industry cohort

Rome longitudinal study

DUELS

Oslo cohort

Cohort

USA

USA

England

Europe

Taiwan

Canada

Canada

USA

Italy

Netherlands

Norway

Setting

12,336

669,046

830,429

367,383

43,227

205,440

2,521,525

53,814

1,265,058

7,218,363

143,842

N

F

FM

FM

FM

FM

FM

FM

M

FM

FM

FM

Sex

>=30

>=30

40-89

All

41.3 (10.5)

35-85

25-89

15.3-84.9

>=30

>=30

51-90

Age

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

0.95 (0.75, 1.21)

1.01 (0.99, 1.04)

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.02 (1.00, 1.05)

1.03 (1.01, 1.04)

ES (95% CI)

15.41

36.27

27.39

19.57

1.35

100.00

7.52

22.74

8.74

22.33

22.20

16.48

100.00

Weight

%

0.99 (0.94, 1.05)

1.04 (1.03, 1.05)

1.00 (0.97, 1.03)

1.01 (0.97, 1.06)

0.95 (0.75, 1.21)

1.01 (0.99, 1.04)

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.02 (1.00, 1.05)

1.03 (1.01, 1.04)

ES (95% CI)

15.41

36.27

27.39

19.57

1.35

100.00

7.52

22.74

8.74

22.33

22.20

16.48

100.00

Weight

%

1.7 .8 .9 1 1.1 1.2

27

eFigure 10 Cardiovascular mortality - stratification by spatial resolution of NO2 concentration estimates

NOTE: Weights are from random effects analysis

.

.

LUR Address

Chen et al

Crouse et al

Hart et al

Turner et al

Beelen et al

Cesaroni et al

Fischer et al

Subtotal (I-squared = 87.1%, p = 0.000)

Area

Lipsett et al

Carey et al

Naess et al

Tseng et al

Subtotal (I-squared = 0.0%, p = 0.429)

Study

2013

2015b

2011

2016

2014a

2013

2015

2011

2013

2007

2015

Year

Ontario tax cohort

CanCHEC

US trucking industry cohort

ACS CPS-II

ESCAPE

Rome longitudinal study

DUELS

CTS

CPRD

Oslo cohort

TCS

Cohort

Canada

Canada

USA

USA

Europe

Italy

Netherlands

USA

England

Norway

Taiwan

Setting

205,440

2,521,525

53,814

669,046

367,383

1,265,058

7,218,363

12,336

830,429

143,842

43,227

N

FM

FM

M

FM

FM

FM

FM

F

FM

FM

FM

Sex

35-85

25-89

15.3-84.9

>=30

All

>=30

>=30

>=30

40-89

51-90

41.3 (10.5)

Age

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

1.04 (1.03, 1.05)

1.01 (0.97, 1.06)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.03 (1.01, 1.04)

0.99 (0.94, 1.05)

1.00 (0.97, 1.03)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.01 (1.00, 1.03)

ES (95% CI)

7.06

19.50

8.15

19.81

7.18

19.20

19.10

100.00

8.34

32.81

58.41

0.44

100.00

Weight

%

1.08 (1.03, 1.12)

1.03 (1.02, 1.04)

1.04 (1.00, 1.09)

1.04 (1.03, 1.05)

1.01 (0.97, 1.06)

1.03 (1.02, 1.04)

1.00 (0.99, 1.01)

1.03 (1.01, 1.04)

0.99 (0.94, 1.05)

1.00 (0.97, 1.03)

1.02 (1.00, 1.05)

0.95 (0.75, 1.21)

1.01 (1.00, 1.03)

ES (95% CI)

7.06

19.50

8.15

19.81

7.18

19.20

19.10

100.00

8.34

32.81

58.41

0.44

100.00

Weight

%

1.7 .8 .9 1 1.1 1.2 1.3

28

eFigure 11 CHD mortality

* indicates exclusion from meta-analysis. Refer to methods/results sections of manuscript.

Chen et al

Crouse et al *

Crouse et al

Gan et al

Chen et al

Hart et al

Jerrett et al *

Krewski et al *

Lipsett et al

Turner et al

Raaschou-Nielsen et al *

Carey et al

Beelen et al

Cesaroni et al

Beelen et al

Yorifuji et al *

Yorifuji et al

Study

2013

2015a

2015b

2011

2005

2011

2013

2009

2011

2016

2012

2013

2014a

2013

2009

2010

2013

Year

Ontario tax cohort

CanCHEC

CanCHEC

Vancouver Cohort

AHSMOG

US trucking industry cohort

ACS CPS-II

ACS CPS-II

CTS

ACS CPS-II

DCH

CPRD

ESCAPE

Rome longitudinal study

NLCS-AIR

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

Canada

Canada

Canada

USA

USA

USA

USA

USA

USA

Denmark

England

Europe

Italy

Netherlands

Japan

Japan

Setting

205,440

735,590

2,521,525

452,735

3,239

53,814

73,711

406,917

12,336

669,046

52,061

830,429

367,383

1,265,058

117,528

13,444

13,412

N

FM

FM

FM

FM

FM

M

FM

FM

F

FM

FM

FM

FM

FM

FM

FM

FM

Sex

35-85

25-89

25-89

45-85

27-95

15.3-84.9

>=30

>=30

>=30

>=30

50-64

40-89

All

>=30

55-69

65-84

65-84

Age

Indirect Smoking, No BMI

Indirect smoking and BMI

Indirect smoking and BMI

No BMI, Smoking

No BMI, Smoking

No BMI, Smoking

No BMI

Adjustment

Confounder

1.09 (1.02, 1.15)

1.05 (1.02, 1.09)

1.04 (1.03, 1.05)

1.05 (1.01, 1.09)

1.09 (1.00, 1.17)

1.00 (0.95, 1.06)

1.09 (1.02, 1.16)

1.02 (1.01, 1.03)

1.04 (0.96, 1.12)

1.07 (1.06, 1.09)

1.08 (0.89, 1.31)

0.99 (0.95, 1.04)

1.00 (0.91, 1.09)

1.05 (1.04, 1.07)

0.99 (0.93, 1.06)

1.27 (1.02, 1.58)

1.29 (1.12, 1.48)

ES (95% CI)

1.09 (1.02, 1.15)

1.05 (1.02, 1.09)

1.04 (1.03, 1.05)

1.05 (1.01, 1.09)

1.09 (1.00, 1.17)

1.00 (0.95, 1.06)

1.09 (1.02, 1.16)

1.02 (1.01, 1.03)

1.04 (0.96, 1.12)

1.07 (1.06, 1.09)

1.08 (0.89, 1.31)

0.99 (0.95, 1.04)

1.00 (0.91, 1.09)

1.05 (1.04, 1.07)

0.99 (0.93, 1.06)

1.27 (1.02, 1.58)

1.29 (1.12, 1.48)

ES (95% CI)

1.9 1 1.1 1.2

29

eFigure 12a CHD mortality - fixed effects model

eFigure 12b CHD mortality - random effects model

Overall (I-squared = 67.3%, p = 0.000)

Hart et al

Crouse et al

Chen et al

Cesaroni et al

Study

Beelen et al

Turner et al

Chen et al

Yorifuji et al

Gan et al

Carey et al

Lipsett et al

Beelen et al

2011

2015b

2013

2013

Year

2009

2016

2005

2013

2011

2013

2011

2014a

US trucking industry cohort

CanCHEC

Ontario tax cohort

Rome longitudinal study

Cohort

NLCS-AIR

ACS CPS-II

AHSMOG

Shizuoka elderly cohort

Vancouver Cohort

CPRD

CTS

ESCAPE

USA

Canada

Canada

Italy

Setting

Netherlands

USA

USA

Japan

Canada

England

USA

Europe

53,814

2,521,525

205,440

1,265,058

N

117,528

669,046

3,239

13,412

452,735

830,429

12,336

367,383

1.05 (1.04, 1.06)

1.00 (0.95, 1.06)

1.04 (1.03, 1.05)

1.09 (1.02, 1.15)

1.05 (1.04, 1.07)

ES (95% CI)

0.99 (0.93, 1.06)

1.07 (1.06, 1.09)

1.09 (1.00, 1.17)

1.29 (1.12, 1.48)

1.05 (1.01, 1.09)

0.99 (0.95, 1.04)

1.04 (0.96, 1.12)

1.00 (0.91, 1.09)

100.00

1.88

39.77

1.37

23.49

Weight

1.14

24.72

0.78

0.25

3.04

2.19

0.78

0.59

%

1.05 (1.04, 1.06)

1.00 (0.95, 1.06)

1.04 (1.03, 1.05)

1.09 (1.02, 1.15)

1.05 (1.04, 1.07)

ES (95% CI)

0.99 (0.93, 1.06)

1.07 (1.06, 1.09)

1.09 (1.00, 1.17)

1.29 (1.12, 1.48)

1.05 (1.01, 1.09)

0.99 (0.95, 1.04)

1.04 (0.96, 1.12)

1.00 (0.91, 1.09)

100.00

1.88

39.77

1.37

23.49

Weight

1.14

24.72

0.78

0.25

3.04

2.19

0.78

0.59

%

1.9 1 1.1 1.2

NOTE: Weights are from random effects analysis

. (1.00, 1.10)with estimated predictive interval

Overall (I-squared = 67.3%, p = 0.000)

Carey et al

Study

Turner et al

Yorifuji et al

Chen et al

Beelen et al

Cesaroni et al

Chen et al

Gan et al

Hart et al

Beelen et al

Crouse et al

Lipsett et al

2013

Year

2016

2013

2013

2009

2013

2005

2011

2011

2014a

2015b

2011

CPRD

Cohort

ACS CPS-II

Shizuoka elderly cohort

Ontario tax cohort

NLCS-AIR

Rome longitudinal study

AHSMOG

Vancouver Cohort

US trucking industry cohort

ESCAPE

CanCHEC

CTS

England

Setting

USA

Japan

Canada

Netherlands

Italy

USA

Canada

USA

Europe

Canada

USA

830,429

N

669,046

13,412

205,440

117,528

1,265,058

3,239

452,735

53,814

367,383

2,521,525

12,336

1.05 (1.03, 1.06)

0.99 (0.95, 1.04)

ES (95% CI)

1.07 (1.06, 1.09)

1.29 (1.12, 1.48)

1.09 (1.02, 1.15)

0.99 (0.93, 1.06)

1.05 (1.04, 1.07)

1.09 (1.00, 1.17)

1.05 (1.01, 1.09)

1.00 (0.95, 1.06)

1.00 (0.91, 1.09)

1.04 (1.03, 1.05)

1.04 (0.96, 1.12)

100.00

7.92

Weight

17.22

1.41

5.84

5.13

17.11

3.83

%

9.50

7.20

3.05

17.99

3.80

1.05 (1.03, 1.06)

0.99 (0.95, 1.04)

ES (95% CI)

1.07 (1.06, 1.09)

1.29 (1.12, 1.48)

1.09 (1.02, 1.15)

0.99 (0.93, 1.06)

1.05 (1.04, 1.07)

1.09 (1.00, 1.17)

1.05 (1.01, 1.09)

1.00 (0.95, 1.06)

1.00 (0.91, 1.09)

1.04 (1.03, 1.05)

1.04 (0.96, 1.12)

100.00

7.92

Weight

17.22

1.41

5.84

5.13

17.11

3.83

%

9.50

7.20

3.05

17.99

3.80

1.9 1 1.1 1.2

30

eFigure 13 CHD mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Gan et al

Chen et al

Crouse et al

Hart et al

Lipsett et al

Chen et al

Turner et al

Carey et al

Beelen et al

Cesaroni et al

Subtotal (I-squared = 59.4%, p = 0.008)

Restricted

Beelen et al

Yorifuji et al

Subtotal (I-squared = 91.2%, p = 0.001)

Study

2011

2013

2015b

2011

2011

2005

2016

2013

2014a

2013

2009

2013

Year

Vancouver Cohort

Ontario tax cohort

CanCHEC

US trucking industry cohort

CTS

AHSMOG

ACS CPS-II

CPRD

ESCAPE

Rome longitudinal study

NLCS-AIR

Shizuoka elderly cohort

Cohort

Canada

Canada

Canada

USA

USA

USA

USA

England

Europe

Italy

Netherlands

Japan

Setting

452,735

205,440

2,521,525

53,814

12,336

3,239

669,046

830,429

367,383

1,265,058

117,528

13,412

N

FM

FM

FM

M

F

FM

FM

FM

FM

FM

FM

FM

Sex

45-85

35-85

25-89

15.3-84.9

>=30

27-95

>=30

40-89

All

>=30

55-69

65-84

Age

1.05 (1.01, 1.09)

1.09 (1.02, 1.15)

1.04 (1.03, 1.05)

1.00 (0.95, 1.06)

1.04 (0.96, 1.12)

1.09 (1.00, 1.17)

1.07 (1.06, 1.09)

0.99 (0.95, 1.04)

1.00 (0.91, 1.09)

1.05 (1.04, 1.07)

1.05 (1.03, 1.06)

0.99 (0.93, 1.06)

1.29 (1.12, 1.48)

1.12 (0.87, 1.45)

ES (95% CI)

9.09

5.10

22.11

6.51

3.17

3.19

20.62

7.28

2.50

20.43

100.00

52.82

47.18

100.00

Weight

%

1.05 (1.01, 1.09)

1.09 (1.02, 1.15)

1.04 (1.03, 1.05)

1.00 (0.95, 1.06)

1.04 (0.96, 1.12)

1.09 (1.00, 1.17)

1.07 (1.06, 1.09)

0.99 (0.95, 1.04)

1.00 (0.91, 1.09)

1.05 (1.04, 1.07)

1.05 (1.03, 1.06)

0.99 (0.93, 1.06)

1.29 (1.12, 1.48)

1.12 (0.87, 1.45)

ES (95% CI)

9.09

5.10

22.11

6.51

3.17

3.19

20.62

7.28

2.50

20.43

100.00

52.82

47.18

100.00

Weight

%

1.8 1 1.2 1.4

31

eFigure 14 CHD mortality - stratification by level of adjustment for smoking and BMI

NOTE: Weights are from random effects analysis

.

.

Individual

Lipsett et al

Chen et al

Turner et al

Carey et al

Beelen et al

Subtotal (I-squared = 67.7%, p = 0.015)

None/Indirect

Gan et al

Chen et al

Crouse et al

Hart et al

Cesaroni et al

Subtotal (I-squared = 13.4%, p = 0.329)

Study

2011

2005

2016

2013

2014a

2011

2013

2015b

2011

2013

Year

CTS

AHSMOG

ACS CPS-II

CPRD

ESCAPE

Vancouver Cohort

Ontario tax cohort

CanCHEC

US trucking industry cohort

Rome longitudinal study

Cohort

USA

USA

USA

England

Europe

Canada

Canada

Canada

USA

Italy

Setting

12,336

3,239

669,046

830,429

367,383

452,735

205,440

2,521,525

53,814

1,265,058

N

F

FM

FM

FM

FM

FM

FM

FM

M

FM

Sex

>=30

27-95

>=30

40-89

All

45-85

35-85

25-89

15.3-84.9

>=30

Age

1.04 (0.96, 1.12)

1.09 (1.00, 1.17)

1.07 (1.06, 1.09)

0.99 (0.95, 1.04)

1.00 (0.91, 1.09)

1.04 (1.00, 1.08)

1.05 (1.01, 1.09)

1.09 (1.02, 1.15)

1.04 (1.03, 1.05)

1.00 (0.95, 1.06)

1.05 (1.04, 1.07)

1.04 (1.03, 1.06)

ES (95% CI)

15.31

15.38

32.51

23.67

13.13

100.00

6.12

2.82

51.23

3.84

35.99

100.00

Weight

%

1.04 (0.96, 1.12)

1.09 (1.00, 1.17)

1.07 (1.06, 1.09)

0.99 (0.95, 1.04)

1.00 (0.91, 1.09)

1.04 (1.00, 1.08)

1.05 (1.01, 1.09)

1.09 (1.02, 1.15)

1.04 (1.03, 1.05)

1.00 (0.95, 1.06)

1.05 (1.04, 1.07)

1.04 (1.03, 1.06)

ES (95% CI)

15.31

15.38

32.51

23.67

13.13

100.00

6.12

2.82

51.23

3.84

35.99

100.00

Weight

%

1.9 1 1.1 1.2

32

eFigure 15 CHD mortality - stratification by spatial resolution of NO2 concentration estimates

NOTE: Weights are from random effects analysis

.

.

LUR Address

Gan et al

Chen et al

Crouse et al

Hart et al

Turner et al

Beelen et al

Cesaroni et al

Subtotal (I-squared = 61.1%, p = 0.017)

Area

Lipsett et al

Chen et al

Carey et al

Subtotal (I-squared = 49.5%, p = 0.138)

Study

2011

2013

2015b

2011

2016

2014a

2013

2011

2005

2013

Year

Vancouver Cohort

Ontario tax cohort

CanCHEC

US trucking industry cohort

ACS CPS-II

ESCAPE

Rome longitudinal study

CTS

AHSMOG

CPRD

Cohort

Canada

Canada

Canada

USA

USA

Europe

Italy

USA

USA

England

Setting

452,735

205,440

2,521,525

53,814

669,046

367,383

1,265,058

12,336

3,239

830,429

N

FM

FM

FM

M

FM

FM

FM

F

FM

FM

Sex

45-85

35-85

25-89

15.3-84.9

>=30

All

>=30

>=30

27-95

40-89

Age

1.05 (1.01, 1.09)

1.09 (1.02, 1.15)

1.04 (1.03, 1.05)

1.00 (0.95, 1.06)

1.07 (1.06, 1.09)

1.00 (0.91, 1.09)

1.05 (1.04, 1.07)

1.05 (1.03, 1.07)

1.04 (0.96, 1.12)

1.09 (1.00, 1.17)

0.99 (0.95, 1.04)

1.03 (0.97, 1.09)

ES (95% CI)

9.61

5.18

26.93

6.70

24.68

2.48

24.40

100.00

27.68

27.80

44.51

100.00

Weight

%

1.05 (1.01, 1.09)

1.09 (1.02, 1.15)

1.04 (1.03, 1.05)

1.00 (0.95, 1.06)

1.07 (1.06, 1.09)

1.00 (0.91, 1.09)

1.05 (1.04, 1.07)

1.05 (1.03, 1.07)

1.04 (0.96, 1.12)

1.09 (1.00, 1.17)

0.99 (0.95, 1.04)

1.03 (0.97, 1.09)

ES (95% CI)

9.61

5.18

26.93

6.70

24.68

2.48

24.40

100.00

27.68

27.80

44.51

100.00

Weight

%

1.9 1 1.1 1.2

33

eFigure 16 Cerebrovascular mortality

* indicates exclusion from meta-analysis. Refer to methods/results sections of manuscript.

Chen et al

Crouse et al *

Crouse et al

Lipsett et al

Turner et al

Zhang et al *

Raaschou-Nielsen et al *

Beelen et al

Cesaroni et al

Beelen et al

Yorifuji et al *

Yorifuji et al

Study

2013

2015a

2015b

2011

2016

2011

2012

2014a

2013

2009

2010

2013

Year

Ontario tax cohort

CanCHEC

CanCHEC

CTS

ACS CPS-II

Shenyang cohort

DCH

ESCAPE

Rome longitudinal study

NLCS-AIR

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

Canada

Canada

USA

USA

China

Denmark

Europe

Italy

Netherlands

Japan

Japan

Setting

205,440

735,590

2,521,525

12,336

669,046

9,941

52,061

367,251

1,265,058

117,528

13,444

13,412

N

FM

FM

FM

F

FM

FM

FM

FM

FM

FM

FM

FM

Sex

35-85

25-89

25-89

>=30

>=30

35-103

50-64

All

>=30

55-69

65-84

65-84

Age

Indirect Smoking, No BMI

Indirect smoking and BMI

Indirect smoking and BMI

No BMI, Smoking

No BMI

Adjustment

Confounder

0.96 (0.89, 1.04)

1.01 (0.96, 1.07)

1.00 (0.99, 1.02)

0.93 (0.83, 1.03)

1.00 (0.98, 1.01)

2.44 (2.27, 2.62)

1.09 (0.83, 1.43)

1.01 (0.93, 1.10)

1.01 (0.99, 1.03)

1.15 (1.02, 1.29)

1.09 (0.94, 1.27)

1.19 (1.06, 1.34)

ES (95% CI)

0.96 (0.89, 1.04)

1.01 (0.96, 1.07)

1.00 (0.99, 1.02)

0.93 (0.83, 1.03)

1.00 (0.98, 1.01)

2.44 (2.27, 2.62)

1.09 (0.83, 1.43)

1.01 (0.93, 1.10)

1.01 (0.99, 1.03)

1.15 (1.02, 1.29)

1.09 (0.94, 1.27)

1.19 (1.06, 1.34)

ES (95% CI)

1.9 1 1.1 1.2

34

eFigure 17a Cerebrovascular mortality - fixed effects model

eFigure 17b Cerebrovascular mortality - random effects model

Overall (I-squared = 61.5%, p = 0.011)

Lipsett et al

Chen et al

Yorifuji et al

Crouse et al

Beelen et al

Turner et al

Beelen et al

Study

Cesaroni et al

2011

2013

2013

2015b

2014a

2016

2009

Year

2013

CTS

Ontario tax cohort

Shizuoka elderly cohort

CanCHEC

ESCAPE

ACS CPS-II

NLCS-AIR

Cohort

Rome longitudinal study

USA

Canada

Japan

Canada

Europe

USA

Netherlands

Setting

Italy

12,336

205,440

13,412

2,521,525

367,251

669,046

117,528

N

1,265,058

1.00 (0.99, 1.02)

0.93 (0.83, 1.03)

0.96 (0.89, 1.04)

1.19 (1.06, 1.34)

1.00 (0.99, 1.02)

1.01 (0.93, 1.10)

1.00 (0.98, 1.01)

1.15 (1.02, 1.29)

ES (95% CI)

1.01 (0.99, 1.03)

100.00

0.99

1.88

0.83

33.67

1.62

31.07

0.88

Weight

29.07

%

1.00 (0.99, 1.02)

0.93 (0.83, 1.03)

0.96 (0.89, 1.04)

1.19 (1.06, 1.34)

1.00 (0.99, 1.02)

1.01 (0.93, 1.10)

1.00 (0.98, 1.01)

1.15 (1.02, 1.29)

ES (95% CI)

1.01 (0.99, 1.03)

100.00

0.99

1.88

0.83

33.67

1.62

31.07

0.88

Weight

29.07

%

1.9 1 1.1 1.2

NOTE: Weights are from random effects analysis

. (0.95, 1.07)with estimated predictive interval

Overall (I-squared = 61.5%, p = 0.011)

Beelen et al

Study

Turner et al

Cesaroni et al

Yorifuji et al

Crouse et al

Beelen et al

Lipsett et al

Chen et al

2014a

Year

2016

2013

2013

2015b

2009

2011

2013

ESCAPE

Cohort

ACS CPS-II

Rome longitudinal study

Shizuoka elderly cohort

CanCHEC

NLCS-AIR

CTS

Ontario tax cohort

Europe

Setting

USA

Italy

Japan

Canada

Netherlands

USA

Canada

367,251

N

669,046

1,265,058

13,412

2,521,525

117,528

12,336

205,440

1.01 (0.98, 1.03)

1.01 (0.93, 1.10)

ES (95% CI)

1.00 (0.98, 1.01)

1.01 (0.99, 1.03)

1.19 (1.06, 1.34)

1.00 (0.99, 1.02)

1.15 (1.02, 1.29)

0.93 (0.83, 1.03)

0.96 (0.89, 1.04)

100.00

6.18

Weight

25.17

24.88

3.52

25.50

3.70

4.11

6.94

%

1.01 (0.98, 1.03)

1.01 (0.93, 1.10)

ES (95% CI)

1.00 (0.98, 1.01)

1.01 (0.99, 1.03)

1.19 (1.06, 1.34)

1.00 (0.99, 1.02)

1.15 (1.02, 1.29)

0.93 (0.83, 1.03)

0.96 (0.89, 1.04)

100.00

6.18

Weight

25.17

24.88

3.52

25.50

3.70

4.11

6.94

%

1.9 1 1.1 1.2

35

eFigure 18 Cerebrovascular mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Chen et al

Crouse et al

Lipsett et al

Turner et al

Beelen et al

Cesaroni et al

Subtotal (I-squared = 0.0%, p = 0.457)

Restricted

Beelen et al

Yorifuji et al

Subtotal (I-squared = 0.0%, p = 0.659)

Study

2013

2015b

2011

2016

2014a

2013

2009

2013

Year

Ontario tax cohort

CanCHEC

CTS

ACS CPS-II

ESCAPE

Rome longitudinal study

NLCS-AIR

Shizuoka elderly cohort

Cohort

Canada

Canada

USA

USA

Europe

Italy

Netherlands

Japan

Setting

205,440

2,521,525

12,336

669,046

367,251

1,265,058

117,528

13,412

N

FM

FM

F

FM

FM

FM

FM

FM

Sex

35-85

25-89

>=30

>=30

All

>=30

55-69

65-84

Age

0.96 (0.89, 1.04)

1.00 (0.99, 1.02)

0.93 (0.83, 1.03)

1.00 (0.98, 1.01)

1.01 (0.93, 1.10)

1.01 (0.99, 1.03)

1.00 (0.99, 1.01)

1.15 (1.02, 1.29)

1.19 (1.06, 1.34)

1.17 (1.08, 1.27)

ES (95% CI)

1.91

34.26

1.01

31.61

1.65

29.57

100.00

51.38

48.62

100.00

Weight

%

0.96 (0.89, 1.04)

1.00 (0.99, 1.02)

0.93 (0.83, 1.03)

1.00 (0.98, 1.01)

1.01 (0.93, 1.10)

1.01 (0.99, 1.03)

1.00 (0.99, 1.01)

1.15 (1.02, 1.29)

1.19 (1.06, 1.34)

1.17 (1.08, 1.27)

ES (95% CI)

1.91

34.26

1.01

31.61

1.65

29.57

100.00

51.38

48.62

100.00

Weight

%

1.9 1 1.1 1.2

36

eFigure 19 Cerebrovascular mortality - stratification by level of adjustment for smoking and BMI

NOTE: Weights are from random effects analysis

.

.

Individual

Lipsett et al

Turner et al

Beelen et al

Subtotal (I-squared = 0.0%, p = 0.391)

None/Indirect

Chen et al

Crouse et al

Cesaroni et al

Subtotal (I-squared = 0.0%, p = 0.433)

Study

2011

2016

2014a

2013

2015b

2013

Year

CTS

ACS CPS-II

ESCAPE

Ontario tax cohort

CanCHEC

Rome longitudinal study

Cohort

USA

USA

Europe

Canada

Canada

Italy

Setting

12,336

669,046

367,251

205,440

2,521,525

1,265,058

N

F

FM

FM

FM

FM

FM

Sex

>=30

>=30

All

35-85

25-89

>=30

Age

0.93 (0.83, 1.03)

1.00 (0.98, 1.01)

1.01 (0.93, 1.10)

0.99 (0.98, 1.01)

0.96 (0.89, 1.04)

1.00 (0.99, 1.02)

1.01 (0.99, 1.03)

1.01 (0.99, 1.02)

ES (95% CI)

2.94

92.25

4.80

100.00

2.90

52.11

44.99

100.00

Weight

%

0.93 (0.83, 1.03)

1.00 (0.98, 1.01)

1.01 (0.93, 1.10)

0.99 (0.98, 1.01)

0.96 (0.89, 1.04)

1.00 (0.99, 1.02)

1.01 (0.99, 1.03)

1.01 (0.99, 1.02)

ES (95% CI)

2.94

92.25

4.80

100.00

2.90

52.11

44.99

100.00

Weight

%

1.9.9 1 1.1 1.2

37

eFigure 20 Cerebrovascular mortality - stratification by spatial resolution of NO2 concentration

NOTE: Weights are from random effects analysis

.

.

LUR Address

Chen et al

Crouse et al

Turner et al

Beelen et al

Cesaroni et al

Subtotal (I-squared = 0.0%, p = 0.638)

Area

Lipsett et al

Subtotal (I-squared = .%, p = .)

Study

2013

2015b

2016

2014a

2013

2011

Year

Ontario tax cohort

CanCHEC

ACS CPS-II

ESCAPE

Rome longitudinal study

CTS

Cohort

Canada

Canada

USA

Europe

Italy

USA

Setting

205,440

2,521,525

669,046

367,251

1,265,058

12,336

N

FM

FM

FM

FM

FM

F

Sex

35-85

25-89

>=30

All

>=30

>=30

Age

0.96 (0.89, 1.04)

1.00 (0.99, 1.02)

1.00 (0.98, 1.01)

1.01 (0.93, 1.10)

1.01 (0.99, 1.03)

1.00 (0.99, 1.01)

0.93 (0.83, 1.03)

0.93 (0.83, 1.03)

ES (95% CI)

1.93

34.60

31.93

1.66

29.87

100.00

100.00

100.00

Weight

%

0.96 (0.89, 1.04)

1.00 (0.99, 1.02)

1.00 (0.98, 1.01)

1.01 (0.93, 1.10)

1.01 (0.99, 1.03)

1.00 (0.99, 1.01)

0.93 (0.83, 1.03)

0.93 (0.83, 1.03)

ES (95% CI)

1.93

34.60

31.93

1.66

29.87

100.00

100.00

100.00

Weight

%

1.9 1 1.1 1.2

38

eFigure 21 Respiratory mortality

* indicates exclusion from meta-analysis. Refer to methods/results sections of manuscript.

NOTE: Weights are from random effects analysis

Crouse et al *

Crouse et al

Jerrett et al

Abbey et al

Hart et al

Jerrett et al *

Lipsett et al

Turner et al

Dong et al *

Carey et al

Dimakopoulou K

Heinrich et al *

Cesaroni et al

Brunekreef et al

Fischer et al

Katanoda et al

Yorifuji et al *

Yorifuji et al

Study

2015a

2015b

2009

1999

2011

2013

2011

2016

2012

2013

2014

2013

2013

2009

2015

2011

2010

2013

Year

CanCHEC

CanCHEC

Toronto respiratory cohort

AHSMOG

US trucking industry cohort

ACS CPS-II

CTS

ACS CPS-II

Shenyang cohort

CPRD

ESCAPE

German cohort

Rome longitudinal study

NLCS-AIR

DUELS

3 Japanease Prefectures

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

Canada

Canada

USA

USA

USA

USA

USA

China

England

Europe

Germany

Italy

Netherlands

Netherlands

Japan

Japan

Japan

Setting

735,590

2,521,525

2,360

5,652

53,814

73,711

12,336

669,046

9,941

830,429

307,553

4,752

1,265,058

117,528

7,218,363

63,520

13,444

13,412

N

FM

FM

FM

FM

M

FM

F

FM

FM

FM

FM

F

FM

FM

FM

FM

FM

FM

Sex

25-89

25-89

60 (49 69)

27-95

15.3-84.9

>=30

>=30

>=30

35-103

40-89

All

50-59

>=30

55-69

>=30

>=40

65-84

65-84

Age

Indirect smoking and BMI

Indirect smoking and BMI

No BMI, Smoking

No BMI, Age(?)

No BMI, Smoking

No BMI

No BMI, Smoking

No BMI

Adjustment

Confounder

1.04 (1.00, 1.09)

1.02 (1.00, 1.04)

1.08 (0.64, 1.84)

0.98 (0.93, 1.03)

1.04 (0.95, 1.14)

1.00 (0.91, 1.10)

0.96 (0.86, 1.08)

1.02 (1.00, 1.04)

2.97 (2.69, 3.27)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.08 (0.81, 1.44)

1.03 (1.00, 1.06)

1.11 (1.00, 1.23)

1.02 (1.01, 1.03)

1.08 (1.06, 1.10)

1.19 (1.02, 1.38)

1.19 (1.06, 1.34)

ES (95% CI)

1.04 (1.00, 1.09)

1.02 (1.00, 1.04)

1.08 (0.64, 1.84)

0.98 (0.93, 1.03)

1.04 (0.95, 1.14)

1.00 (0.91, 1.10)

0.96 (0.86, 1.08)

1.02 (1.00, 1.04)

2.97 (2.69, 3.27)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.08 (0.81, 1.44)

1.03 (1.00, 1.06)

1.11 (1.00, 1.23)

1.02 (1.01, 1.03)

1.08 (1.06, 1.10)

1.19 (1.02, 1.38)

1.19 (1.06, 1.34)

ES (95% CI)

1.9 1 1.11.2

39

eFigure 22a Respiratory mortality - fixed effects model

eFigure 22b Respiratory mortality - random effects model

Overall (I-squared = 75.5%, p = 0.000)

Katanoda et al

Carey et al

Fischer et al

Turner et al

Brunekreef et al

Abbey et al

Dimakopoulou K

Cesaroni et al

Lipsett et al

Hart et al

Yorifuji et al

Study

Jerrett et al

Crouse et al

2011

2013

2015

2016

2009

1999

2014

2013

2011

2011

2013

Year

2009

2015b

3 Japanease Prefectures

CPRD

DUELS

ACS CPS-II

NLCS-AIR

AHSMOG

ESCAPE

Rome longitudinal study

CTS

US trucking industry cohort

Shizuoka elderly cohort

Cohort

Toronto respiratory cohort

CanCHEC

Japan

England

Netherlands

USA

Netherlands

USA

Europe

Italy

USA

USA

Japan

Setting

Canada

Canada

63,520

830,429

7,218,363

669,046

117,528

5,652

307,553

1,265,058

12,336

53,814

13,412

N

2,360

2,521,525

FM

FM

FM

FM

FM

FM

FM

FM

F

M

FM

Sex

FM

FM

>=40

40-89

>=30

>=30

55-69

27-95

All

>=30

>=30

15.3-84.9

65-84

Age

60 (49 69)

25-89

No BMI

No BMI, Smoking

No BMI

No BMI, Smoking

No BMI, Smoking

Adjustment

Indirect smoking and BMI

Confounder

1.03 (1.02, 1.04)

1.08 (1.06, 1.10)

1.08 (1.04, 1.13)

1.02 (1.01, 1.03)

1.02 (1.00, 1.04)

1.11 (1.00, 1.23)

0.98 (0.93, 1.03)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

0.96 (0.86, 1.08)

1.04 (0.95, 1.14)

1.19 (1.06, 1.34)

ES (95% CI)

1.08 (0.64, 1.84)

1.02 (1.00, 1.04)

100.00

10.88

2.54

48.73

10.96

0.43

2.03

0.69

5.52

0.38

0.59

0.34

Weight

0.02

16.89

%

1.03 (1.02, 1.04)

1.08 (1.06, 1.10)

1.08 (1.04, 1.13)

1.02 (1.01, 1.03)

1.02 (1.00, 1.04)

1.11 (1.00, 1.23)

0.98 (0.93, 1.03)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

0.96 (0.86, 1.08)

1.04 (0.95, 1.14)

1.19 (1.06, 1.34)

ES (95% CI)

1.08 (0.64, 1.84)

1.02 (1.00, 1.04)

100.00

10.88

2.54

48.73

10.96

0.43

2.03

0.69

5.52

0.38

0.59

0.34

Weight

0.02

16.89

%

1.9 1 1.1 1.2

NOTE: Weights are from random effects analysis

. (0.97, 1.10)with estimated predictive interval

Overall (I-squared = 75.5%, p = 0.000)

Cesaroni et al

Hart et al

Study

Abbey et al

Yorifuji et al

Carey et al

Katanoda et al

Jerrett et al

Lipsett et al

Turner et al

Fischer et al

Brunekreef et al

Crouse et al

Dimakopoulou K

2013

2011

Year

1999

2013

2013

2011

2009

2011

2016

2015

2009

2015b

2014

Rome longitudinal study

US trucking industry cohort

Cohort

AHSMOG

Shizuoka elderly cohort

CPRD

3 Japanease Prefectures

Toronto respiratory cohort

CTS

ACS CPS-II

DUELS

NLCS-AIR

CanCHEC

ESCAPE

Italy

USA

Setting

USA

Japan

England

Japan

Canada

USA

USA

Netherlands

Netherlands

Canada

Europe

1,265,058

53,814

N

5,652

13,412

830,429

63,520

2,360

12,336

669,046

7,218,363

117,528

2,521,525

307,553

FM

M

Sex

FM

FM

FM

FM

FM

F

FM

FM

FM

FM

FM

>=30

15.3-84.9

Age

27-95

65-84

40-89

>=40

60 (49 69)

>=30

>=30

>=30

55-69

25-89

All

No BMI, Smoking

No BMI, Smoking

Adjustment

No BMI

Confounder

No BMI, Smoking

No BMI

Indirect smoking and BMI

1.03 (1.01, 1.05)

1.03 (1.00, 1.06)

1.04 (0.95, 1.14)

ES (95% CI)

0.98 (0.93, 1.03)

1.19 (1.06, 1.34)

1.08 (1.04, 1.13)

1.08 (1.06, 1.10)

1.08 (0.64, 1.84)

0.96 (0.86, 1.08)

1.02 (1.00, 1.04)

1.02 (1.01, 1.03)

1.11 (1.00, 1.23)

1.02 (1.00, 1.04)

0.97 (0.89, 1.05)

100.00

11.60

3.67

Weight

8.06

2.37

8.92

13.28

0.13

2.62

13.30

%

15.02

2.87

14.03

4.13

1.03 (1.01, 1.05)

1.03 (1.00, 1.06)

1.04 (0.95, 1.14)

ES (95% CI)

0.98 (0.93, 1.03)

1.19 (1.06, 1.34)

1.08 (1.04, 1.13)

1.08 (1.06, 1.10)

1.08 (0.64, 1.84)

0.96 (0.86, 1.08)

1.02 (1.00, 1.04)

1.02 (1.01, 1.03)

1.11 (1.00, 1.23)

1.02 (1.00, 1.04)

0.97 (0.89, 1.05)

100.00

11.60

3.67

Weight

8.06

2.37

8.92

13.28

0.13

2.62

13.30

%

15.02

2.87

14.03

4.13

1.9 1 1.1 1.2

40

eFigure 23 Respiratory mortality - stratification by pre-existing disease

NOTE: Weights are from random effects analysis

.

.

General

Crouse et al

Hart et al

Lipsett et al

Abbey et al

Turner et al

Carey et al

Dimakopoulou K

Cesaroni et al

Fischer et al

Brunekreef et al

Yorifuji et al

Katanoda et al

Subtotal (I-squared = 77.5%, p = 0.000)

Preexisting

Jerrett et al

Subtotal (I-squared = .%, p = .)

Study

2015b

2011

2011

1999

2016

2013

2014

2013

2015

2009

2013

2011

2009

Year

CanCHEC

US trucking industry cohort

CTS

AHSMOG

ACS CPS-II

CPRD

ESCAPE

Rome longitudinal study

DUELS

NLCS-AIR

Shizuoka elderly cohort

3 Japanease Prefectures

Toronto respiratory cohort

Cohort

Canada

USA

USA

USA

USA

England

Europe

Italy

Netherlands

Netherlands

Japan

Japan

Canada

Setting

2,521,525

53,814

12,336

5,652

669,046

830,429

307,553

1,265,058

7,218,363

117,528

13,412

63,520

2,360

N

FM

M

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

FM

Sex

25-89

15.3-84.9

>=30

27-95

>=30

40-89

All

>=30

>=30

55-69

65-84

>=40

60 (49 69)

Age

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.02 (1.00, 1.04)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.11 (1.00, 1.23)

1.19 (1.06, 1.34)

1.08 (1.06, 1.10)

1.03 (1.01, 1.05)

1.08 (0.64, 1.84)

1.08 (0.64, 1.84)

ES (95% CI)

13.98

3.72

2.66

8.11

13.27

8.96

4.18

11.61

14.95

2.92

2.41

13.25

100.00

100.00

100.00

Weight

%

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.02 (1.00, 1.04)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.11 (1.00, 1.23)

1.19 (1.06, 1.34)

1.08 (1.06, 1.10)

1.03 (1.01, 1.05)

1.08 (0.64, 1.84)

1.08 (0.64, 1.84)

ES (95% CI)

13.98

3.72

2.66

8.11

13.27

8.96

4.18

11.61

14.95

2.92

2.41

13.25

100.00

100.00

100.00

Weight

%

1.7 .8 .9 1 1.1 1.2 1.3

41

eFigure 24 Respiratory mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Crouse et al

Hart et al

Lipsett et al

Abbey et al

Turner et al

Carey et al

Dimakopoulou K

Cesaroni et al

Fischer et al

Katanoda et al

Subtotal (I-squared = 77.9%, p = 0.000)

Restricted

Brunekreef et al

Yorifuji et al

Subtotal (I-squared = 0.0%, p = 0.391)

Study

2015b

2011

2011

1999

2016

2013

2014

2013

2015

2011

2009

2013

Year

CanCHEC

US trucking industry cohort

CTS

AHSMOG

ACS CPS-II

CPRD

ESCAPE

Rome longitudinal study

DUELS

3 Japanease Prefectures

NLCS-AIR

Shizuoka elderly cohort

Cohort

Canada

USA

USA

USA

USA

England

Europe

Italy

Netherlands

Japan

Netherlands

Japan

Setting

2,521,525

53,814

12,336

5,652

669,046

830,429

307,553

1,265,058

7,218,363

63,520

117,528

13,412

N

FM

M

F

FM

FM

FM

FM

FM

FM

FM

FM

FM

Sex

25-89

15.3-84.9

>=30

27-95

>=30

40-89

All

>=30

>=30

>=40

55-69

65-84

Age

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.02 (1.00, 1.04)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.08 (1.06, 1.10)

1.03 (1.01, 1.05)

1.11 (1.00, 1.23)

1.19 (1.06, 1.34)

1.15 (1.06, 1.24)

ES (95% CI)

15.15

3.62

2.56

8.24

14.27

9.20

4.08

12.26

16.38

14.25

100.00

55.80

44.20

100.00

Weight

%

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.02 (1.00, 1.04)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.08 (1.06, 1.10)

1.03 (1.01, 1.05)

1.11 (1.00, 1.23)

1.19 (1.06, 1.34)

1.15 (1.06, 1.24)

ES (95% CI)

15.15

3.62

2.56

8.24

14.27

9.20

4.08

12.26

16.38

14.25

100.00

55.80

44.20

100.00

Weight

%

1.9 1 1.1 1.2 1.3

42

eFigure 25 Respiratory mortality - stratification by level of adjustment for smoking and BMI

NOTE: Weights are from random effects analysis

.

.

Individual

Lipsett et al

Abbey et al

Turner et al

Carey et al

Dimakopoulou K

Subtotal (I-squared = 69.4%, p = 0.011)

None/Indirect

Crouse et al

Hart et al

Cesaroni et al

Fischer et al

Katanoda et al

Subtotal (I-squared = 84.9%, p = 0.000)

Study

2011

1999

2016

2013

2014

2015b

2011

2013

2015

2011

Year

CTS

AHSMOG

ACS CPS-II

CPRD

ESCAPE

CanCHEC

US trucking industry cohort

Rome longitudinal study

DUELS

3 Japanease Prefectures

Cohort

USA

USA

USA

England

Europe

Canada

USA

Italy

Netherlands

Japan

Setting

12,336

5,652

669,046

830,429

307,553

2,521,525

53,814

1,265,058

7,218,363

63,520

N

F

FM

FM

FM

FM

FM

M

FM

FM

FM

Sex

>=30

27-95

>=30

40-89

All

25-89

15.3-84.9

>=30

>=30

>=40

Age

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.02 (1.00, 1.04)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.01 (0.97, 1.05)

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.08 (1.06, 1.10)

1.04 (1.01, 1.06)

ES (95% CI)

9.45

22.44

30.36

23.97

13.77

100.00

24.56

5.91

19.90

26.52

23.11

100.00

Weight

%

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.02 (1.00, 1.04)

1.08 (1.04, 1.13)

0.97 (0.89, 1.05)

1.01 (0.97, 1.05)

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.08 (1.06, 1.10)

1.04 (1.01, 1.06)

ES (95% CI)

9.45

22.44

30.36

23.97

13.77

100.00

24.56

5.91

19.90

26.52

23.11

100.00

Weight

%

1.9 1 1.1

43

eFigure 26 Respiratory mortality - stratification by spatial resolution of NO2 concentration

NOTE: Weights are from random effects analysis

.

.

LUR Address

Crouse et al

Hart et al

Turner et al

Dimakopoulou K

Cesaroni et al

Fischer et al

Subtotal (I-squared = 0.0%, p = 0.826)

Area

Lipsett et al

Abbey et al

Carey et al

Katanoda et al

Subtotal (I-squared = 83.2%, p = 0.000)

Study

2015b

2011

2016

2014

2013

2015

2011

1999

2013

2011

Year

CanCHEC

US trucking industry cohort

ACS CPS-II

ESCAPE

Rome longitudinal study

DUELS

CTS

AHSMOG

CPRD

3 Japanease Prefectures

Cohort

Canada

USA

USA

Europe

Italy

Netherlands

USA

USA

England

Japan

Setting

2,521,525

53,814

669,046

307,553

1,265,058

7,218,363

12,336

5,652

830,429

63,520

N

FM

M

FM

FM

FM

FM

F

FM

FM

FM

Sex

25-89

15.3-84.9

>=30

All

>=30

>=30

>=30

27-95

40-89

>=40

Age

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

1.02 (1.00, 1.04)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.02 (1.01, 1.03)

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.08 (1.04, 1.13)

1.08 (1.06, 1.10)

1.04 (0.98, 1.10)

ES (95% CI)

20.26

0.70

13.15

0.82

6.62

58.45

100.00

14.18

26.50

27.61

31.71

100.00

Weight

%

1.02 (1.00, 1.04)

1.04 (0.95, 1.14)

1.02 (1.00, 1.04)

0.97 (0.89, 1.05)

1.03 (1.00, 1.06)

1.02 (1.01, 1.03)

1.02 (1.01, 1.03)

0.96 (0.86, 1.08)

0.98 (0.93, 1.03)

1.08 (1.04, 1.13)

1.08 (1.06, 1.10)

1.04 (0.98, 1.10)

ES (95% CI)

20.26

0.70

13.15

0.82

6.62

58.45

100.00

14.18

26.50

27.61

31.71

100.00

Weight

%

1.9 1 1.1

44

eFigure 27 COPD mortality

* indicates exclusion from meta-analysis. Refer to methods/results sections of manuscript.

Crouse et al

Gan et al

Hart et al

Turner et al

Carey et al

Naess et al

Katanoda et al

Yorifuji et al *

Yorifuji et al

Study

2015b

2013

2011

2016

2013

2007

2011

2010

2013

Year

CanCHEC

Vancouver Cohort

US trucking industry cohort

ACS CPS-II

CPRD

Oslo cohort

3 Japanease Prefectures

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

Canada

USA

USA

England

Norway

Japan

Japan

Japan

Setting

2,521,525

467,994

53,814

669,046

830,429

143,842

63,520

13,444

13,412

N

FM

FM

M

FM

FM

FM

FM

FM

FM

Sex

25-89

45-85

15.3-84.9

>=30

40-89

51-90

>=40

65-84

65-84

Age

Indirect smoking and BMI

No BMI, Smoking

No BMI, Smoking

No BMI, Smoking

No BMI

Adjustment

Confounder

1.03 (1.01, 1.06)

1.05 (0.95, 1.15)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.11 (0.78, 1.57)

0.98 (0.75, 1.29)

ES (95% CI)

1.03 (1.01, 1.06)

1.05 (0.95, 1.15)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.11 (0.78, 1.57)

0.98 (0.75, 1.29)

ES (95% CI)

1.9 1 1.1 1.2

45

eFigure 28a COPD mortality - fixed effects model

eFigure 28b COPD mortality - random effects model

Overall (I-squared = 0.0%, p = 0.492)

Gan et al

Katanoda et al

Study

Carey et al

Yorifuji et al

Hart et al

Turner et al

Crouse et al

Naess et al

2013

2011

Year

2013

2013

2011

2016

2015b

2007

Vancouver Cohort

3 Japanease Prefectures

Cohort

CPRD

Shizuoka elderly cohort

US trucking industry cohort

ACS CPS-II

CanCHEC

Oslo cohort

Canada

Japan

Setting

England

Japan

USA

USA

Canada

Norway

467,994

63,520

N

830,429

13,412

53,814

669,046

2,521,525

143,842

FM

FM

Sex

FM

FM

M

FM

FM

FM

45-85

>=40

Age

40-89

65-84

15.3-84.9

>=30

25-89

51-90

No BMI, Smoking

No BMI

Adjustment

No BMI, Smoking

Confounder

Indirect smoking and BMI

No BMI, Smoking

1.03 (1.01, 1.04)

1.05 (0.95, 1.15)

1.02 (0.96, 1.08)

ES (95% CI)

1.07 (0.99, 1.14)

0.98 (0.75, 1.29)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.03 (1.01, 1.06)

1.05 (1.01, 1.09)

100.00

2.18

6.43

Weight

4.18

0.28

1.71

%

30.62

39.72

14.88

1.03 (1.01, 1.04)

1.05 (0.95, 1.15)

1.02 (0.96, 1.08)

ES (95% CI)

1.07 (0.99, 1.14)

0.98 (0.75, 1.29)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.03 (1.01, 1.06)

1.05 (1.01, 1.09)

100.00

2.18

6.43

Weight

4.18

0.28

1.71

%

30.62

39.72

14.88

1.9 1 1.1 1.2

NOTE: Weights are from random effects analysis

. (1.01, 1.05)with estimated predictive interval

Overall (I-squared = 0.0%, p = 0.492)

Hart et al

Crouse et al

Katanoda et al

Gan et al

Turner et al

Study

Yorifuji et al

Carey et al

Naess et al

2011

2015b

2011

2013

2016

Year

2013

2013

2007

US trucking industry cohort

CanCHEC

3 Japanease Prefectures

Vancouver Cohort

ACS CPS-II

Cohort

Shizuoka elderly cohort

CPRD

Oslo cohort

USA

Canada

Japan

Canada

USA

Setting

Japan

England

Norway

53,814

2,521,525

63,520

467,994

669,046

N

13,412

830,429

143,842

M

FM

FM

FM

FM

Sex

FM

FM

FM

15.3-84.9

25-89

>=40

45-85

>=30

Age

65-84

40-89

51-90

No BMI, Smoking

Indirect smoking and BMI

No BMI

No BMI, Smoking

Adjustment

No BMI, Smoking

Confounder

1.03 (1.01, 1.04)

0.99 (0.88, 1.10)

1.03 (1.01, 1.06)

1.02 (0.96, 1.08)

1.05 (0.95, 1.15)

1.00 (0.98, 1.03)

ES (95% CI)

0.98 (0.75, 1.29)

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

100.00

1.71

39.72

6.43

2.18

30.62

Weight

0.28

4.18

14.88

%

1.03 (1.01, 1.04)

0.99 (0.88, 1.10)

1.03 (1.01, 1.06)

1.02 (0.96, 1.08)

1.05 (0.95, 1.15)

1.00 (0.98, 1.03)

ES (95% CI)

0.98 (0.75, 1.29)

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

100.00

1.71

39.72

6.43

2.18

30.62

Weight

0.28

4.18

14.88

%

1.9 1 1.1 1.2

46

eFigure 29 COPD mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Gan et al

Crouse et al

Hart et al

Turner et al

Carey et al

Naess et al

Katanoda et al

Subtotal (I-squared = 4.8%, p = 0.390)

Restricted

Yorifuji et al

Subtotal (I-squared = .%, p = .)

Study

2013

2015b

2011

2016

2013

2007

2011

2013

Year

Vancouver Cohort

CanCHEC

US trucking industry cohort

ACS CPS-II

CPRD

Oslo cohort

3 Japanease Prefectures

Shizuoka elderly cohort

Cohort

Canada

Canada

USA

USA

England

Norway

Japan

Japan

Setting

467,994

2,521,525

53,814

669,046

830,429

143,842

63,520

13,412

N

FM

FM

M

FM

FM

FM

FM

FM

Sex

45-85

25-89

15.3-84.9

>=30

40-89

51-90

>=40

65-84

Age

1.05 (0.95, 1.15)

1.03 (1.01, 1.06)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.03 (1.01, 1.04)

0.98 (0.75, 1.29)

0.98 (0.75, 1.29)

ES (95% CI)

2.42

38.07

1.90

30.35

4.60

15.66

7.01

100.00

100.00

100.00

Weight

%

1.05 (0.95, 1.15)

1.03 (1.01, 1.06)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.03 (1.01, 1.04)

0.98 (0.75, 1.29)

0.98 (0.75, 1.29)

ES (95% CI)

2.42

38.07

1.90

30.35

4.60

15.66

7.01

100.00

100.00

100.00

Weight

%

1.8 .9 1 1.1 1.2

47

eFigure 30 COPD mortality - stratification by level of adjustment for smoking and BMI

NOTE: Weights are from random effects analysis

.

.

Individual

Turner et al

Carey et al

Subtotal (I-squared = 56.8%, p = 0.128)

None/Indirect

Gan et al

Crouse et al

Hart et al

Naess et al

Katanoda et al

Subtotal (I-squared = 0.0%, p = 0.764)

Study

2016

2013

2013

2015b

2011

2007

2011

Year

ACS CPS-II

CPRD

Vancouver Cohort

CanCHEC

US trucking industry cohort

Oslo cohort

3 Japanease Prefectures

Cohort

USA

England

Canada

Canada

USA

Norway

Japan

Setting

669,046

830,429

467,994

2,521,525

53,814

143,842

63,520

N

FM

FM

FM

FM

M

FM

FM

Sex

>=30

40-89

45-85

25-89

15.3-84.9

51-90

>=40

Age

1.00 (0.98, 1.03)

1.07 (0.99, 1.14)

1.02 (0.97, 1.08)

1.05 (0.95, 1.15)

1.03 (1.01, 1.06)

0.99 (0.88, 1.10)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.03 (1.02, 1.05)

ES (95% CI)

66.39

33.61

100.00

3.36

61.18

2.64

22.92

9.91

100.00

Weight

%

1.00 (0.98, 1.03)

1.07 (0.99, 1.14)

1.02 (0.97, 1.08)

1.05 (0.95, 1.15)

1.03 (1.01, 1.06)

0.99 (0.88, 1.10)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.03 (1.02, 1.05)

ES (95% CI)

66.39

33.61

100.00

3.36

61.18

2.64

22.92

9.91

100.00

Weight

%

1.9 1 1.1

48

eFigure 31 COPD mortality - stratification by spatial resolution of NO2 concentration

NOTE: Weights are from random effects analysis

.

.

Area

Carey et al

Naess et al

Katanoda et al

Subtotal (I-squared = 0.0%, p = 0.524)

LUR Address

Gan et al

Crouse et al

Hart et al

Turner et al

Subtotal (I-squared = 9.5%, p = 0.346)

Study

2013

2007

2011

2013

2015b

2011

2016

Year

CPRD

Oslo cohort

3 Japanease Prefectures

Vancouver Cohort

CanCHEC

US trucking industry cohort

ACS CPS-II

Cohort

England

Norway

Japan

Canada

Canada

USA

USA

Setting

830,429

143,842

63,520

467,994

2,521,525

53,814

669,046

N

FM

FM

FM

FM

FM

M

FM

Sex

40-89

51-90

>=40

45-85

25-89

15.3-84.9

>=30

Age

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.04 (1.01, 1.07)

1.05 (0.95, 1.15)

1.03 (1.01, 1.06)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.02 (1.00, 1.04)

ES (95% CI)

16.40

58.37

25.23

100.00

3.64

51.51

2.87

41.98

100.00

Weight

%

1.07 (0.99, 1.14)

1.05 (1.01, 1.09)

1.02 (0.96, 1.08)

1.04 (1.01, 1.07)

1.05 (0.95, 1.15)

1.03 (1.01, 1.06)

0.99 (0.88, 1.10)

1.00 (0.98, 1.03)

1.02 (1.00, 1.04)

ES (95% CI)

16.40

58.37

25.23

100.00

3.64

51.51

2.87

41.98

100.00

Weight

%

1.9 1 1.1

49

eFigure 32 Pneumonia mortality

Turner et al

Carey et al

Yorifuji et al

Yorifuji et al

Katanoda et al

Study

2016

2013

2013

2010

2011

Year

ACS CPS-II

CPRD

Shizuoka elderly cohort

Shizuoka elderly cohort

3 Japanease Prefectures

Cohort

USA

England

Japan

Japan

Japan

Setting

669,046

830,429

13,412

13,444

63,520

N

FM

FM

FM

FM

FM

Sex

>=30

40-89

65-84

65-84

>=40

Age

1.06 (1.02, 1.09)

1.08 (1.03, 1.15)

1.15 (0.98, 1.34)

1.18 (0.96, 1.45)

1.08 (1.06, 1.10)

ES (95% CI)

1.06 (1.02, 1.09)

1.08 (1.03, 1.15)

1.15 (0.98, 1.34)

1.18 (0.96, 1.45)

1.08 (1.06, 1.10)

ES (95% CI)

11 1.1 1.2 1.3

50

eFigure 33 Lung cancer mortality

* indicates exclusion from meta-analysis. Refer to methods/results sections of manuscript.

NOTE: Weights are from random effects analysis

Crouse et al

HEI *

Krewski et al *

Jerrett et al *

Turner et al

Abbey et al

Lipsett et al

HEI

Hart et al

Chen et al

Carey et al

Filleul et al

Heinrich et al

Cesaroni et al

Fischer et al

Brunekreef et al

Naess et al

Katanoda et al

Yorifuji et al *

Yorifuji et al

Study

2015b

2000

2009

2013

2016

1999

2011

2000

2011

2016

2013

2005

2013

2013

2015

2009

2007

2011

2010

2013

Year

CanCHEC

ACS CPS-II

ACS CPS-II

ACS CPS-II

ACS CPS-II

AHSMOG

CTS

Six Cities

US trucking industry cohort

Four northern Chinese cities

CPRD

PAARC

German cohort

Rome longitudinal study

DUELS

NLCS-AIR

Oslo cohort

3 Japanease Prefectures

Shizuoka elderly cohort

Shizuoka elderly cohort

Cohort

Canada

USA

USA

USA

USA

USA

USA

USA

USA

China

England

France

Germany

Italy

Netherlands

Netherlands

Norway

Japan

Japan

Japan

Setting

2,521,525

552,138

406,917

73,711

669,046

5,652

12,336

8,111

53,814

39,054

830,429

14,284

4,752

1,265,058

7,218,363

117,528

143,842

63,520

13,444

13,412

N

FM

FM

FM

FM

FM

FM

F

FM

M

FM

FM

FM

F

FM

FM

FM

FM

FM

FM

FM

Sex

25-89

>=30

>=30

>=30

>=30

27-95

>=30

25-74

15.3-84.9

23-89

40-89

25-59

50-59

>=30

>=30

55-69

51-90

>=40

65-84

65-84

Age

Indirect smoking and BMI

No BMI, Smoking

No BMI, Age(?)

No BMI, Smoking

No BMI, Smoking

No BMI

No BMI, Smoking

No BMI

Adjustment

Confounder

1.04 (1.02, 1.06)

0.99 (0.97, 1.01)

1.00 (0.98, 1.01)

1.15 (1.03, 1.28)

1.00 (0.97, 1.02)

1.23 (1.06, 1.42)

1.00 (0.86, 1.16)

1.05 (0.86, 1.27)

1.04 (0.98, 1.10)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.48 (1.06, 2.07)

1.27 (0.95, 1.69)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

0.97 (0.90, 1.05)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

0.95 (0.78, 1.16)

1.20 (1.03, 1.40)

ES (95% CI)

1.04 (1.02, 1.06)

0.99 (0.97, 1.01)

1.00 (0.98, 1.01)

1.15 (1.03, 1.28)

1.00 (0.97, 1.02)

1.23 (1.06, 1.42)

1.00 (0.86, 1.16)

1.05 (0.86, 1.27)

1.04 (0.98, 1.10)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.48 (1.06, 2.07)

1.27 (0.95, 1.69)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

0.97 (0.90, 1.05)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

0.95 (0.78, 1.16)

1.20 (1.03, 1.40)

ES (95% CI)

1.9 1 1.1 1.2

51

eFigure 34a Lung cancer mortality - fixed effects model

eFigure 34b Lung cancer mortality - random effects model

Overall (I-squared = 88.1%, p = 0.000)

Katanoda et al

Brunekreef et al

Yorifuji et al

Carey et al

Turner et al

Lipsett et al

Naess et al

Filleul et al

Fischer et al

HEI

Hart et al

Abbey et al

Study

Chen et al

Heinrich et al

Crouse et al

Cesaroni et al

2011

2009

2013

2013

2016

2011

2007

2005

2015

2000

2011

1999

Year

2016

2013

2015b

2013

3 Japanease Prefectures

NLCS-AIR

Shizuoka elderly cohort

CPRD

ACS CPS-II

CTS

Oslo cohort

PAARC

DUELS

Six Cities

US trucking industry cohort

AHSMOG

Cohort

Four northern Chinese cities

German cohort

CanCHEC

Rome longitudinal study

Japan

Netherlands

Japan

England

USA

USA

Norway

France

Netherlands

USA

USA

USA

Setting

China

Germany

Canada

Italy

63,520

117,528

13,412

830,429

669,046

12,336

143,842

14,284

7,218,363

8,111

53,814

5,652

N

39,054

4,752

2,521,525

1,265,058

FM

FM

FM

FM

FM

F

FM

FM

FM

FM

M

FM

Sex

FM

F

FM

FM

>=40

55-69

65-84

40-89

>=30

>=30

51-90

25-59

>=30

25-74

15.3-84.9

27-95

Age

23-89

50-59

25-89

>=30

No BMI

No BMI

Confounder

No BMI, Smoking

No BMI, Smoking

No BMI, Smoking

Adjustment

No BMI, Age(?)

Indirect smoking and BMI

No BMI, Smoking

1.07 (1.06, 1.08)

1.08 (1.03, 1.12)

0.97 (0.90, 1.05)

1.20 (1.03, 1.40)

1.06 (1.00, 1.11)

1.00 (0.97, 1.02)

1.00 (0.86, 1.16)

1.08 (1.03, 1.12)

1.48 (1.06, 2.07)

1.10 (1.09, 1.11)

1.05 (0.86, 1.27)

1.04 (0.98, 1.10)

1.23 (1.06, 1.42)

ES (95% CI)

0.90 (0.82, 0.98)

1.27 (0.95, 1.69)

1.04 (1.02, 1.06)

1.04 (1.02, 1.07)

100.00

2.72

0.78

0.20

%

1.69

10.18

0.22

3.06

0.04

57.57

0.13

1.37

0.23

Weight

0.59

0.06

12.86

8.31

1.07 (1.06, 1.08)

1.08 (1.03, 1.12)

0.97 (0.90, 1.05)

1.20 (1.03, 1.40)

1.06 (1.00, 1.11)

1.00 (0.97, 1.02)

1.00 (0.86, 1.16)

1.08 (1.03, 1.12)

1.48 (1.06, 2.07)

1.10 (1.09, 1.11)

1.05 (0.86, 1.27)

1.04 (0.98, 1.10)

1.23 (1.06, 1.42)

ES (95% CI)

0.90 (0.82, 0.98)

1.27 (0.95, 1.69)

1.04 (1.02, 1.06)

1.04 (1.02, 1.07)

100.00

2.72

0.78

0.20

%

1.69

10.18

0.22

3.06

0.04

57.57

0.13

1.37

0.23

Weight

0.59

0.06

12.86

8.31

1.9 1 1.1 1.2

NOTE: Weights are from random effects analysis

. (0.94, 1.17)with estimated predictive interval

Overall (I-squared = 88.1%, p = 0.000)

Yorifuji et al

Abbey et al

Crouse et al

Hart et al

Fischer et al

Lipsett et al

Chen et al

HEI

Carey et al

Naess et al

Cesaroni et al

Study

Katanoda et al

Heinrich et al

Brunekreef et al

Turner et al

Filleul et al

2013

1999

2015b

2011

2015

2011

2016

2000

2013

2007

2013

Year

2011

2013

2009

2016

2005

Shizuoka elderly cohort

AHSMOG

CanCHEC

US trucking industry cohort

DUELS

CTS

Four northern Chinese cities

Six Cities

CPRD

Oslo cohort

Rome longitudinal study

Cohort

3 Japanease Prefectures

German cohort

NLCS-AIR

ACS CPS-II

PAARC

Japan

USA

Canada

USA

Netherlands

USA

China

USA

England

Norway

Italy

Setting

Japan

Germany

Netherlands

USA

France

13,412

5,652

2,521,525

53,814

7,218,363

12,336

39,054

8,111

830,429

143,842

1,265,058

N

63,520

4,752

117,528

669,046

14,284

FM

FM

FM

M

FM

F

FM

FM

FM

FM

FM

Sex

FM

F

FM

FM

FM

65-84

27-95

25-89

15.3-84.9

>=30

>=30

23-89

25-74

40-89

51-90

>=30

Age

>=40

50-59

55-69

>=30

25-59

Indirect smoking and BMI

No BMI, Smoking

No BMI, Smoking

No BMI, Smoking

No BMI, Smoking

Adjustment

No BMI

No BMI, Age(?)

No BMI

Confounder

1.05 (1.02, 1.08)

1.20 (1.03, 1.40)

1.23 (1.06, 1.42)

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.10 (1.09, 1.11)

1.00 (0.86, 1.16)

0.90 (0.82, 0.98)

1.05 (0.86, 1.27)

1.06 (1.00, 1.11)

1.08 (1.03, 1.12)

1.04 (1.02, 1.07)

ES (95% CI)

1.08 (1.03, 1.12)

1.27 (0.95, 1.69)

0.97 (0.90, 1.05)

1.00 (0.97, 1.02)

1.48 (1.06, 2.07)

100.00

2.85

3.10

10.39

7.68

10.75

3.00

5.55

2.00

8.12

9.15

10.16

Weight

8.98

0.99

6.26

10.28

0.75

%

1.05 (1.02, 1.08)

1.20 (1.03, 1.40)

1.23 (1.06, 1.42)

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.10 (1.09, 1.11)

1.00 (0.86, 1.16)

0.90 (0.82, 0.98)

1.05 (0.86, 1.27)

1.06 (1.00, 1.11)

1.08 (1.03, 1.12)

1.04 (1.02, 1.07)

ES (95% CI)

1.08 (1.03, 1.12)

1.27 (0.95, 1.69)

0.97 (0.90, 1.05)

1.00 (0.97, 1.02)

1.48 (1.06, 2.07)

100.00

2.85

3.10

10.39

7.68

10.75

3.00

5.55

2.00

8.12

9.15

10.16

Weight

8.98

0.99

6.26

10.28

0.75

%

1.9 1 1.1 1.2

52

eFigure 35 Lung cancer mortality - stratification by age range at cohort recruitment

NOTE: Weights are from random effects analysis

.

.

Adult

Crouse et al

Hart et al

Lipsett et al

Abbey et al

HEI

Turner et al

Chen et al

Carey et al

Heinrich et al

Cesaroni et al

Fischer et al

Naess et al

Katanoda et al

Subtotal (I-squared = 89.5%, p = 0.000)

Restricted

Filleul et al

Brunekreef et al

Yorifuji et al

Subtotal (I-squared = 81.1%, p = 0.005)

Study

2015b

2011

2011

1999

2000

2016

2016

2013

2013

2013

2015

2007

2011

2005

2009

2013

Year

CanCHEC

US trucking industry cohort

CTS

AHSMOG

Six Cities

ACS CPS-II

Four northern Chinese cities

CPRD

German cohort

Rome longitudinal study

DUELS

Oslo cohort

3 Japanease Prefectures

PAARC

NLCS-AIR

Shizuoka elderly cohort

Cohort

Canada

USA

USA

USA

USA

USA

China

England

Germany

Italy

Netherlands

Norway

Japan

France

Netherlands

Japan

Setting

2,521,525

53,814

12,336

5,652

8,111

669,046

39,054

830,429

4,752

1,265,058

7,218,363

143,842

63,520

14,284

117,528

13,412

N

FM

M

F

FM

FM

FM

FM

FM

F

FM

FM

FM

FM

FM

FM

FM

Sex

25-89

15.3-84.9

>=30

27-95

25-74

>=30

23-89

40-89

50-59

>=30

>=30

51-90

>=40

25-59

55-69

65-84

Age

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.00 (0.86, 1.16)

1.23 (1.06, 1.42)

1.05 (0.86, 1.27)

1.00 (0.97, 1.02)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.27 (0.95, 1.69)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

1.05 (1.02, 1.08)

1.48 (1.06, 2.07)

0.97 (0.90, 1.05)

1.20 (1.03, 1.40)

1.15 (0.92, 1.42)

ES (95% CI)

11.65

8.47

3.22

3.33

2.14

11.51

6.04

8.98

1.05

11.37

12.07

10.18

9.98

100.00

21.45

42.12

36.43

100.00

Weight

%

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.00 (0.86, 1.16)

1.23 (1.06, 1.42)

1.05 (0.86, 1.27)

1.00 (0.97, 1.02)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.27 (0.95, 1.69)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

1.05 (1.02, 1.08)

1.48 (1.06, 2.07)

0.97 (0.90, 1.05)

1.20 (1.03, 1.40)

1.15 (0.92, 1.42)

ES (95% CI)

11.65

8.47

3.22

3.33

2.14

11.51

6.04

8.98

1.05

11.37

12.07

10.18

9.98

100.00

21.45

42.12

36.43

100.00

Weight

%

1.8 1 1.2 1.4 1.6

53

eFigure 36 Lung cancer mortality - stratification by level of adjustment for smoking and BMI

NOTE: Weights are from random effects analysis

.

.

Individual

Lipsett et al

Abbey et al

HEI

Turner et al

Chen et al

Carey et al

Subtotal (I-squared = 71.5%, p = 0.004)

None/Indirect

Crouse et al

Hart et al

Heinrich et al

Cesaroni et al

Fischer et al

Naess et al

Katanoda et al

Subtotal (I-squared = 86.0%, p = 0.000)

Study

2011

1999

2000

2016

2016

2013

2015b

2011

2013

2013

2015

2007

2011

Year

CTS

AHSMOG

Six Cities

ACS CPS-II

Four northern Chinese cities

CPRD

CanCHEC

US trucking industry cohort

German cohort

Rome longitudinal study

DUELS

Oslo cohort

3 Japanease Prefectures

Cohort

USA

USA

USA

USA

China

England

Canada

USA

Germany

Italy

Netherlands

Norway

Japan

Setting

12,336

5,652

8,111

669,046

39,054

830,429

2,521,525

53,814

4,752

1,265,058

7,218,363

143,842

63,520

N

F

FM

FM

FM

FM

FM

FM

M

F

FM

FM

FM

FM

Sex

>=30

27-95

25-74

>=30

23-89

40-89

25-89

15.3-84.9

50-59

>=30

>=30

51-90

>=40

Age

1.00 (0.86, 1.16)

1.23 (1.06, 1.42)

1.05 (0.86, 1.27)

1.00 (0.97, 1.02)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.02 (0.96, 1.08)

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.27 (0.95, 1.69)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

1.06 (1.03, 1.10)

ES (95% CI)

10.71

11.01

7.43

28.64

18.02

24.20

100.00

19.23

11.20

0.95

18.37

20.61

15.08

14.57

100.00

Weight

%

1.00 (0.86, 1.16)

1.23 (1.06, 1.42)

1.05 (0.86, 1.27)

1.00 (0.97, 1.02)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.02 (0.96, 1.08)

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.27 (0.95, 1.69)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

1.06 (1.03, 1.10)

ES (95% CI)

10.71

11.01

7.43

28.64

18.02

24.20

100.00

19.23

11.20

0.95

18.37

20.61

15.08

14.57

100.00

Weight

%

1.8 1 1.2 1.4

54

eFigure 37 Lung cancer mortality - stratification by spatial resolution of NO2 concentration

NOTE: Weights are from random effects analysis

.

.

Area

Lipsett et al

Abbey et al

HEI

Chen et al

Carey et al

Heinrich et al

Naess et al

Katanoda et al

Subtotal (I-squared = 65.3%, p = 0.005)

LUR Address

Crouse et al

Hart et al

Turner et al

Cesaroni et al

Fischer et al

Subtotal (I-squared = 95.7%, p = 0.000)

Study

2011

1999

2000

2016

2013

2013

2007

2011

2015b

2011

2016

2013

2015

Year

CTS

AHSMOG

Six Cities

Four northern Chinese cities

CPRD

German cohort

Oslo cohort

3 Japanease Prefectures

CanCHEC

US trucking industry cohort

ACS CPS-II

Rome longitudinal study

DUELS

Cohort

USA

USA

USA

China

England

Germany

Norway

Japan

Canada

USA

USA

Italy

Netherlands

Setting

12,336

5,652

8,111

39,054

830,429

4,752

143,842

63,520

2,521,525

53,814

669,046

1,265,058

7,218,363

N

F

FM

FM

FM

FM

F

FM

FM

FM

M

FM

FM

FM

Sex

>=30

27-95

25-74

23-89

40-89

50-59

51-90

>=40

25-89

15.3-84.9

>=30

>=30

>=30

Age

1.00 (0.86, 1.16)

1.23 (1.06, 1.42)

1.05 (0.86, 1.27)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.27 (0.95, 1.69)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

1.05 (1.00, 1.11)

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.00 (0.97, 1.02)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

1.04 (1.00, 1.09)

ES (95% CI)

7.78

8.02

5.27

13.83

19.50

2.64

21.66

21.30

100.00

21.08

15.66

20.86

20.62

21.79

100.00

Weight

%

1.00 (0.86, 1.16)

1.23 (1.06, 1.42)

1.05 (0.86, 1.27)

0.90 (0.82, 0.98)

1.06 (1.00, 1.11)

1.27 (0.95, 1.69)

1.08 (1.03, 1.12)

1.08 (1.03, 1.12)

1.05 (1.00, 1.11)

1.04 (1.02, 1.06)

1.04 (0.98, 1.10)

1.00 (0.97, 1.02)

1.04 (1.02, 1.07)

1.10 (1.09, 1.11)

1.04 (1.00, 1.09)

ES (95% CI)

7.78

8.02

5.27

13.83

19.50

2.64

21.66

21.30

100.00

21.08

15.66

20.86

20.62

21.79

100.00

Weight

%

1.8 1 1.2 1.4

55

eFigure 38 Diabetes associated mortality – random effects model

NOTE: Weights are from random effects analysis

. (0.75, 1.44)with estimated predictive interval

Overall (I-squared = 38.2%, p = 0.198)

Study

Raaschou-Nielsen et al

Turner et al

Crouse et al

Year

2013

2016

2015b

Cohort

DCH

ACS CPS-II

CanCHEC

Setting

Denmark

USA

Canada

N

52,061

669,046

2,521,525

Sex

FM

FM

FM

Age

50-64

>=30

25-89

1.04 (1.00, 1.07)

ES (95% CI)

1.31 (0.98, 1.76)

1.05 (1.01, 1.09)

1.03 (1.00, 1.05)

100.00

Weight

1.35

%

40.83

57.82

1.04 (1.00, 1.07)

ES (95% CI)

1.31 (0.98, 1.76)

1.05 (1.01, 1.09)

1.03 (1.00, 1.05)

100.00

Weight

1.35

%

40.83

57.82

1.8 1 1.2 1.4