The Relationship between Particulate Matter (PM₁₀) and Hospitalizations and Mortality Of Chronic Obstructive Pulmonary Disease: A Meta-Analysis

Figures & data

Figure 1.  Study selection flow chart. The initial search found 1322 titles, of which 1210 citations were excluded after identification based on abstracts and titles, and there were 31 original studies that met the inclusion criteria for this meta-analysis.

Table 1.  Studies included in the meta-analysis investigating the short term effects between PM₁₀ on COPD

Source	Study Location	Lag days	Study design	OR	95%CI	No. of COPD	Study period	Agesranges	Confounding factors
PM10 and COPD hospitalizations
Chen et al. 2000 (19)	Reno-Sparks Nevada	0	Time–series	1.018	1.004–1.033	3,115	1990–1994	All ages	temperature wind speed, dummies for study, April November
Zanobetti et al. 2000 (20)	10 cities USA	5	Time–series	1.025	1.018–1.033	NAb	1986.10–1994.12	≥65	temperature relative-humidity, pressure
Zanobetti et al. 2000 (9)	Chicago USA	0	Time–series	1.019	1.008–1.030	NA	1986–1994	All ages	sex, race, age group
Anderson et al. 2001 (10)	Birmingham USA	0–1	Time–series	0.993	0.972–1.014	NA	1994.10–1996.12	All ages	temperature humidity
Chen et al. 2004 (21)	Vancouver Canada	0–3	Time–series	1.162	1.068–1.263	4,409	1995.1.1–1999.3.3	≥65	temperature relative-humidity
Yang et al. 2005 (22)	British Canada	7	Time–series	1.157	1.060–1.253	6,027	1994–1998	≥65	temperature relative-humidity
Peel et al. 2005 (23)	Atlanta USA	1	Time–series	1.018	0.994–1.043	NA	1993.1.1–2000.8.1	All ages	temperature dew point
Medina-Ramon et al. 2006 (24)	36 cities USA	1	Time–series	1.015	1.093–1.021	578,006	1986–1999	≥65	days of week, temperature
Ko et al. 2007 (25)	Hong Kong China	0–5	Time–series	1.024	1.021–1.028	119,225	2000–2005	All ages	temperature relative-humidity
Lee et al.2007 (26)	Kaohsiung Taiwan(≥25 °C)	0	Case–crossover	1.044	1.025–1.065	25,108	1996–2003	All ages	temperature humidity
	(<25 °C)			1.081	1.060–1.103
Yang and Chen 2007 (27)	Taipei Taiwan (≥ 20 °C)	0	Case–crossover	1.050	1.037–1.064	46,491	1996–2003	All ages	temperature humidity
	(< 20 °C)			1.013	0.998–1.029
Johnston et al. 2007 (28)	Darwin Australia	0	Time–series	1.21	1.00–1.47	NA	4.1–11.30 2000,2004,2005	All ages	temperature relative-humidity precipitation
Arbex et al. 2009 (29)	Sao-Paulo Brazil	6	Time–series	1.091	1.021–1.174	1,796	2001–2003	>64	Temperature relative humidity
Sauerzapf et al. 2009 (30)	Norwich USA	0–7	Case–crossover	1.079	0.980–1.188	1,050	2006.1.3–2007.2.3	All ages	maximum temperature pollen influenza- infection
David et al. 2009 (31)	7 cities Canada	0	Time–series	0.997	0.984–1.011	NA	1990s–2000s	All ages	weather temporal cycles, day of week and holiday
Belleudi et al. 2010 (32)	Rome Italy	0	Case-crossover	1.003	0.990–1.016	15,087	2001.4.10–2005.12.31	≥35	temperature pressure
Morgan et al. 2010 (33)	Sydney Australia	2	Time-series	1.038	1.014–1.063	36,772	1994.1.1–2002.6.30	≥65	temperature relative-humidity
Tam et al. 2011 (34)	Hong Kong China	2	Case-crossover	1.05	1.01–1.09	111,419	1998–2002	All ages	temperature relative-humidity
PM10 and COPD mortality
Tellez-Rojo et al. 2000 (35)	Mexico city Mexico	3	Time-series	1.041	1.013–1.069	2,294	1994	≥65	Temperature
Moolgavkar 2000 (11)	Cook USA	2	Time-series	1.011	1.00–1.021	NA	1987–1995	All ages	temperature relative humidity
Braga et al. 2001 (36)	10 cities USA	7	Time-series	1.017	1.001–1.033	NA	1986–1993	All ages	temperature relative humidity pressure
Sunyer and Basagana 2001 (37)	Barcelona Spain	0	Case-crossover	1.042	1.00–1.089	2,305	1990–1995	All ages	temperature humidity hot days and influenza days
Wong et al. 2002 (38)	Hong Kong China	0–3	Time-series	1.017	1.002–1.033	NA	1995–1998	All ages	temperature relative humidity
Kan and Chen 2003 (39)	Shanghai China	0	Time-series	1.005	0.999–1.011	NA	2000.6.1– 2001.12.1	All ages	temperature relative-humidity dew point
Fischer et al. 2003 (40)	Dutch Netherland	0–6	Time-series	1.038	0.897–1.317	NA	1986–1994	<45	temperature relative humidity
				1.035	0.958–1.135			45–64
				1.042	0.998–1.093			65–74
				1.017	0.991–1.045			≥75
Kim et al. 2003 (7)	Seoul Korea	0	Time-series	1.010	0.997–1.023	NA	1995–1999	All ages	temperature humidity pressure
Bateson and Schwartz 2004 (12)	Cook USA	0	Case-crossover	1.006	0.992–1.02	16,403	1988–1991	All ages	temperature humidity pressure
Zeka et al. 2005 (41)	20 cities USA	1	Case-crossover	1.004	0.986–1.010	NA	1989–2000	All ages	temperature dew point
Neuberger et al. 2007 (42)	Vienna Austria	0–1	Time-series	1.035	1.004–1.067	2,872	2000–2004	All ages	seasonal temperature relative humidity, pressure day of week influenza
Forastiere et al. 2008 (43)	9 cities Italy	2	Case-crossover	1.008	1.002–1.015	34,627	1997–2004	≥65	temperature pressure
Fischer et al. 2011 (44)	Dutch Netherland	0–6	Time-series	1.018	1.011–1.024	NA	1992–2006	All ages	temperature relative humidity pressure

COPD, chronic obstructive pulmonary disease; OR, odds ratio; NAb, not available.

Figure 2.  Forest plot of COPD hospitalizations and PM₁₀ in the meta-analysis Random-effect models were used to calculate the pooled effect size for OR (chi-squared χ2 = 117.82, [degree of freedom, df = 19], I2 = 83.9%, p < 0.001; and Z = 6.61, p < 0.001). The random pooled effect size (OR) for COPD hospitalizations due to PM₁₀ was 1.03 (95%CI = 1.02–1.04).

Figure 3.  Forest plot of COPD mortality and PM₁₀ in the meta-analysis Fixed effect models were used to calculate the pooled effect size for OR (χ2 = 23.03, df = 15, I2 = 34.9%, p > 0.05; and Z = 7.40, p < 0.001). The pooled effect size (OR) for COPD mortality and PM₁₀ was 1.011 (95%CI = 1.008 –1.014).

Figure 4.  Funnel plot for PM₁₀ and COPD hospitalizations in the meta-analysis. Publication bias was tested by using funnel plots for COPD hospitalization. The combined data obtained from Egger's test for COPD hospitalization (bias = 1.97, P>|t| = 0.250) showed that there was no evidence of publication bias on the association between PM₁₀ and COPD hospitalizations with PM₁₀. The pseudo 95% CI is computed as part of the analysis that produces the funnel plot, and corresponds to the expected 95%CI for a given standard error (SE). OR indicates odds ratio.

Figure 5.  Funnel plot for PM₁₀ and COPD mortality in the meta-analysis. Publication bias was tested by using funnel plots for COPD mortality. The combined data obtained from Egger's test for COPD mortality (bias = 0.16, P>|t| = 0.882) showed that there was no evidence of publication bias on the association between PM₁₀ and COPD mortality with PM10. The pseudo 95% CI is computed as part of the analysis that produces the funnel plot, and corresponds to the expected 95%CI for a given standard error (SE). OR indicates odds ratio.

Table 2.  Studies included in the meta-analysis in different groups between PM₁₀ and COPD hospitalizations and mortality

Groups	References	Amount	OR (95%CI)	P	Heterogeneity		P>|t|
					χ2	I2
Ages
All ages-Hosa	(9,10,19,23,25–28, 30–31,34)	11	1.029 (1.017–1.042)	P<0.001	77.33	85.8%	0.616
≥65-Hos	(20–22,24,29,33)	6	1.038 (1.020–1.056)	P<0.001	27.97	82.1%	0.130
All ages-Morb	(7,11–12,36–39,41–42, 44)	10	1.011 (1.008–1.015)	P<0.001	15.42	41.6%	0.572
≥65-Mor	(35,40,43)	3	1.011 (1.005–1.017)	P<0.001	7.23	58.5%	—
Countries with different socioeconomic status
Developed-Hos	(9,10,19–34)	18	1.027 (1.019–1.036)	P<0.001	117.82	83.9%	0.250
Developing-Hos	—	0	—	—	—	—	—
Developed-Mor	(7,11–12,36–38, 40–44)	11	1.013 (1.009–1.016)	P<0.001	13.87	6.3%	0.900
Developing-Mor	(35,39)	2	1.020 (0.986–1.056)	0.250	6.27	84.0%	—

Hosa, hospitalizations; Morb, mortality; OR, odds ratio.

Chen L, Yang W, Jennison BL, Air particulate pollution and hospital admissions for chronic obstructive pulmonary disease in Reno, Nevada. Inhal Toxicol 2000 Apr; 12(4):281–298.

 PubMed Web of Science ®Google Scholar

Zanobetti A, Schwartz J, Docker DW, Airborne particles are a risk factor for hospital admissions for heart and lung disease. Environ Health Perspect 2000 Nov; 108(11):1071–1077.

 PubMed Web of Science ®Google Scholar

Zanobetti A, Schwartz J, Gold D. Are there sensitive subgroups for the effect of airborne particles? Environ Health Perspect 2000 Sep; 108(9):841–845.

 PubMed Web of Science ®Google Scholar

Anderson HR, Bremner SA, Atkinson RW, Particulate matter and daily mortality and hospital admissions in the west midlands conurbation of the United Kingdom: associations with fine and coarse particles, black smoke and sulphate. Occup Environ Med 2001 Aug; 58(8):504–510.

 PubMed Web of Science ®Google Scholar

Chen Y, Yang Q, Krewski D, Influence of relatively low level of particulate air pollution on hospitalization for COPD in elderly people. Inhal Toxicol 2004 Jan; 16(1): 21–25.

 PubMed Web of Science ®Google Scholar

Yang QY, Chen Y, Krewski D, Effect of short-term exposure to low levels of gaseous pollutants on chronic obstructive pulmonary disease hospitalizations. Environ Res 2005 Sep; 99(1):99–105.

 PubMed Web of Science ®Google Scholar

Peel JL, Tolbert PE, Klein M, Ambient air pollution and respiratory emergency department visits. Epidemiology 2005 Mar; 16(2):164–174.

 PubMed Web of Science ®Google Scholar

Medina-Ramon M, Zanobetti A, Schwartz J. The effect of ozone and PM10 on hospital admissions for pneumonia and chronic obstructive pulmonary disease: a national multicity study. Am J Epidemiol 2006 Mar; 163(6):579–588.

 PubMed Web of Science ®Google Scholar

Ko FW, Tam W, Wong TW, Temporal relationship between air pollutants and hospital admissions for chronic obstructive pulmonary disease in Hong Kong. Thorax 2007 Sep; 62(9):780–785.

 PubMed Web of Science ®Google Scholar

Lee IM, Tsai SS, Chang CC, Air pollution and hospital admissions for chronic obstructive pulmonary disease in a tropical city: Kaohsiung, Taiwan. Inhal Toxicol 2007 May; 19(5): 393–398.

 PubMed Web of Science ®Google Scholar

Yang CY, Chen CJ. Air pollution and hospital admissions for chronic obstructive pulmonary disease in a subtropical city: Taipei, Taiwan. J Toxicol Environ Health 2007 July; 70(14):1214–1219.

 PubMed Web of Science ®Google Scholar

Johnston FH, Bailie R, Pilotto LS, Ambient biomass smoke and cardio-respiratory hospital admissions in Darwin, Australia. BMC Public Health 2007 Sep; 7:240.

 PubMed Web of Science ®Google Scholar

Arbex MA, de Souza Conceicao GM, Cendon SP, Urban air pollution and chronic obstructive pulmonary disease-related emergency department visits. J Epidemiol Community Health 2009 Oct; 63(10):777–783.

 PubMed Web of Science ®Google Scholar

Sauerzapf V, Jones AP, Cross J. Environmental factors and hospitalization for chronic obstructive pulmonary disease in a rural country of England. J Epidemiol Community Health 2009 Apr; 63(4):324–328.

 PubMed Web of Science ®Google Scholar

Stieb DM, Szyszkowicz M, Rowe BH, Air pollution and emergency department visits for cardiac and respiratory conditions: a multi-city time-series analysis. Environ Health 2009 Jun; 8:25.

 PubMed Web of Science ®Google Scholar

Belleudi V, Faustini A, Stefoqqia M, Impact of fine and ultrafine particles on emergency hospital admissions for cardiac and respiratory diseases. Epidemiology 2010 May; 21(3):414–423.

 PubMed Web of Science ®Google Scholar

Morgan G, Sheppeard V, Khalaj B, Effect of bushfire smoke on daily mortality and hospital admission in Sydney, Australia. Epidemiology 2010 Jan; 21(1):47–55.

 PubMed Web of Science ®Google Scholar

Tam WW, Wong TW, Wong AH, Effect of dust storm events on daily emergency admissions for respiratory disease. Respirology 2011 Jan; 17(1):143–148.

 Web of Science ®Google Scholar

Tellez-Rojo MM, Romieu I, Ruiz-Velasco S, Daily respiratory mortality and PM10 pollution in Mexico City importance of considering place of death. Eur Respir J 2000 Sep; 16(3):391–396.

 PubMed Web of Science ®Google Scholar

Moolgavkar SH. Air pollution and daily mortality in three US counties. Environ Health Perspect 2000 Aug; 108(8):777–784.

 PubMed Web of Science ®Google Scholar

Braga AL, Zanobetti A, Schwartz J. The lag structure between particulate air pollution and respiratory and cardiovascular death in 10 US cities. J Occup Environ Med 2001 Nov; 43(11):927–933.

 PubMed Web of Science ®Google Scholar

Sunyer J, Basagana X. Particles, and not gases, are associated with the risk of death in patients with chronic obstructive pulmonary disease. Int J Epidemiol 2001 Oct; 30(5):1138–1140.

 PubMed Web of Science ®Google Scholar

Wong TW, Tam WS, Yu TS, Associations between daily mortalities from respiratory and cardiovascular diseases and air pollution in Hong Kong, China. Occup Environ Med 2002 Jan; 59(1):30–35.

 PubMed Web of Science ®Google Scholar

Kan H, Chen B. Air pollution and daily mortality in Shanghai: a time-series study. Arch Environ Health 2003 Jun; 58(6):360–367.

 PubMedGoogle Scholar

Fischer P, Hoek G, Brunekreef B, Air pollution and mortality in the Netherland: are the elderly more at risk. Eur Respir J 2003 May; 40:34s–38s.

 Google Scholar

Kim H, Kim Y, Hong YC, The lag-effect pattern in the relationship of particulate air pollution to daily mortality in Seoul, Korea. Int J Biometeorol 2003 May; 48(1):25–30.

 PubMed Web of Science ®Google Scholar

Bateson TF, Schwartz J, Who is sensitive to the effects of particulate air pollution on mortality? A case-crossover analysis of effect modifiers. Epidemiology 2004 Mar; 15(2):143–149.

 Google Scholar

Zeka A, Zanobetti A, Schwartz J. Short-term effects of particulate matter on cause specific mortality: effects of lags and modification by city characteristics. Occup Environ Med 2005 Oct; 62(10):718–725.

 PubMed Web of Science ®Google Scholar

Neuberger M, Rabczenko D, Moshammer H. Extended effects of air pollution on cardiopulmonary mortality in Vienna. Atmospheric Environment 2007 Jul; 41:8549–8556.

 Web of Science ®Google Scholar

Forastiere F, Stafoggia M, Berti G, Particulate matter and daily mortality: a case-crossover analysis of individual effect modifiers. Epidemiology 2008 Jul; 19(4):571–580.

 PubMed Web of Science ®Google Scholar

Fischer PH, Marra M, Ameling CB, Trends in relative risk estimates for the association between air pollution and mortality in The Netherlands, 1992–2006. Environ Res 2011 Jan; 111(1):94–100.

 PubMed Web of Science ®Google Scholar