Table 1.
Summary of the 26 articles
| Study | Study Location |
years | Population | Outcome | Exposure Assessment |
PM2.5 mean (25%, 75%) or range |
Method of analysis |
Method for dose- response |
Findings |
|---|---|---|---|---|---|---|---|---|---|
| Studies conducted at low levels | |||||||||
| Crouse [12] | Canada | 2001-2010 | CanCHEC | total mortality | PM25 spatio-temporal predictions, annual | 8.3; (5.6-10.8) | Cox proportional hazards models | Low levels | significant positive associations |
| Weichenthal [13] | Canada | 2001-2011 | CanCHEC | total, cardiovascular, and respiratory mortality | PM25 spatio-temporal predictions, annual | 7.4; (5.4, 9.1) | Cox proportional hazards models | Low levels | significant positive associations |
| Jerrett [31] | US | 1982-2004 | ACS-CPS-II | Circulatory and ischemic heart disease mortality | 10 exposures models, annual | Across all methods: mean ~12; (~10 ,~13.5) | Cox proportional hazards models | Low levels | significant positive associations with every exposure model tested |
| Pun [23] | US | 2000-2008 | Medicare and National Death Index | cause-specific mortality | EPA monitors, annual | 12.5 (10.3, 14.3) | Log-linear regression models on 5 years counts | Low levels | significant positive associations |
| Garcia [30] | US, California | 2000-2006 | Death Statistical Master File from the California Department of Public Health. | cause-specific mortality: CVD, IHD, and CPD | 5 exposure prediction models, annual | rural areas mean=10.5; urban areas mean =15.5 | Poisson regression | Low levels | Significant positive associations, with larger effects in rural vs urban areas, except for IHD mortality |
| Schwartz [28] | US, Boston MA | 2004–2009 | total mortality | Harvard supersite monitor, daily | median 7.8; (6, 11) | Instrumental variables, propensity score and Poisson | Low levels | significant positive associations | |
| Yoo [20] | US, Buffalo-Niagara region | 2011 | New York State Department of Health | cause specific admissions | EPA down-scaler model, daily | 9.5; (5.9, 12.0) | Bayesian hierarchical spatial Poisson model with and without spatial random effects | Low levels | positive non significant |
| Hao [21] | US | 2007–2008 | National Center for Health Statistics | Chronic lower respiratory disease (CLRD) mortality | EPA down-scaler model, daily | 10.7; (8.7-12.5) | Bayesian hierarchical spatial Poisson models | Low levels | positive non significant |
| Rodopoulou [24] | US, Little Rock, Arkansas | 2002-2012 | UAMS Medical Center | cause specific emergency room visits: CVD, respiratory | EPA monitors, daily | 12.4; (8.0, 15.6) | Time series | Low levels | positive significant and non |
| DeVries [25] | US, Worcester county, MA | 2011-2012 | medical practice located in Worcester County, Ma | COPD visits | EPA monitors, daily | 8.6; min= 0.5, max=37 | Conditional logistic regression | Low levels | Non significant associations |
| Studies that restrict analyses at low levels | |||||||||
| Makar [14] | US | 2002-2010 | Medicare and MCBS | total mortality; total, CVD and resp hospitalizations | PM25 spatio-temporal predictions, annual | 12; | Cox proportional hazards models with IPW | Restrict to annual PM2.5<12 | significant positive associations with higher effects at low doses |
| Di [2] | US | 2000-2012 | Medicare | total mortality | PM25 spatio-temporal predictions, annual | 11; (5%: 6.21, 95%: 15.64) | Cox proportional hazards models | Restrict to annual PM2.5<12, C-R curve: Spline | significant positive associations with higher effects at low doses, C-R linear |
| Wang [15] | US, 7 Southeastern states | 2000-2013 | Medicare | total mortality | PM25 spatio-temporal predictions, annual | median=10.7; (9.1, 12.9) | Cox proportional hazards models | Restrict to annual PM2.5<12 | significant positive associations with higher effects at low doses |
| Schwartz [26] | US 135 U.S. cities. | 1999 - 2006 | National Center for Health Statistics (NCHS) | total mortality | EPA monitors, daily | 12.8; (7.5, 16.1) | Marginal Structural Models and intrumental variable | Restrict to daily PM2.5<25 | significant positive associations with higher effects at low doses |
| Schwartz [29] | US, Boston MA | 2000-2009 | Massachusetts Department of Public Health | total mortality | Harvard supersite monitor, daily | 9.8; min=0.2, max=67.2 | Causal models, instrumental vars | Restrict to daily PM2.5<30 | significant positive associations with higher effects at low doses |
| Lee [16] | US, 7 Southeastern states | 2007 - 2011 | states departments of public health | cause specific mortality | PM25 spatio-temporal predictions, daily | 11; (0.02, 86.2) | case-crossover | Restrict to daily PM2.5<35 | significant positive associations with higher effects at low doses |
| Di [3] | US | 2000-2012 | medicare | total mortality | PM25 spatio-temporal predictions, daily | 11.6, min=0, max=50 | case-crossover | Restrict to daily PM2.5<25, C-R curve: thin-plate spline | significant positive associations with higher effects at low doses, C-R supralinear |
| Shi [17] | US, New England | 2003–2008 | Medicare | total mortality | PM25 spatio-temporal predictions, daily | lag01: 8.2; (4.60, 10.7); annual: 8.1; (6.2, 10) | Poisson survival analysis | Restrict to daily PM2.5<30, annual <10, C-R curve: penalized spline | significant positive associations, C-R linear |
| Studies that estimate exposure-response functions | |||||||||
| Crouse [18] | Canada | 1998–2006 | CanCHEC | cause-specific mortality | PM25 spatio-temporal predictions, annual | 8.9; (6-11.8) | Cox proportional hazards models | Natural Spline with 2 df | Supralinear |
| Pinault [19] | Canada | 2000-2008 | CanCHEC | total, respiratory, and cardiovascular mortality | PM25 spatio-temporal predictions, annual | 6.3; (4.2, 8.3) | Cox proportional hazards models | spline-based HR curves and threshold | Supralinear, with large CI. No threshold |
| Pinault [7] | Canada | 2001-2011 | CanCHEC | cause-specific mortality: CVD, Cerebrovascular, diabete, resp, copd, pneumonia | PM25 spatio-temporal predictions, annual | 7.4; (5.4, 9.1) | Cox proportional hazards models | Shape Constrained Health Impact Function | Supralinear |
| Weichenthal [27] | Canada, 3 regions of British Columbia | 2008-2015 | Canadian Institute for Health Information | Myocardial Infarction (MI) hospital admissions | Fixed site monitors, 3 days mean | 8.8; min=0, max=10 | case-crossover | cubic spline with three equally spaced knots | Supralinear |
| Villeneuve [8] | Canada | 1980-2005 | Canadian Mortality Database linked to Canadian National Breast Screening Study | cause specific mortality: CVD resp ihd stroke total | PM25 spatio-temporal predictions, annual | 9.1; (6.4, 12.4) | Cox proportional hazards models | natural cubic spline with 3df and threshold analyses | Linear for CVD and heart disease and no threshold, U-shaped for nonaccidental mortality with threshold at 11mg/m3 |
| Thurston [9] | US, 6 states | 2000–2009 | NIH-AARP Study | cause-specific mortality: CVD, resp | PM25 spatio-temporal predictions, annual | ~13; (~12,~15) | Cox proportional hazards models | natural spline 4 df | Linear |
| Lim [10] | US, 6 states | 1995–2011 | NIH-AARP Diet and Health Study | diabetes mortality | PM25 spatio-temporal predictions, annual | 11; min=2.8 to max=21.2 | Cox proportional hazards models | natural spline with 2df | Linear |
| Hart [11] | US | 2000-2006 | Nurses’ Health Study | Total mortality | PM25 spatio-temporal predictions and nearest monitor, annual | s-t model: 12.0; nearest monitoring: 12.7 | Cox proportional hazards models | restricted cubic spline with and without measurement error correction | linear for both PM2.5 measurements and with and without measurement error correction |