Haneen Khreis1, Charlotte Kelly2, James Tate3, Roger Parslow4, Karen Lucas3, Mark Nieuwenhuijsen5. 1. Institute for Transport Studies, University of Leeds, Leeds, United Kingdom. Electronic address: ts12hrk@leeds.ac.uk. 2. Institute for Transport Studies, University of Leeds, Leeds, United Kingdom; Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom. 3. Institute for Transport Studies, University of Leeds, Leeds, United Kingdom. 4. Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom. 5. ISGlobal CREAL, C/Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), C/Dr. Aiguader 88, 08003, Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), C/Monforte de Lemos 3-5, 28029 Madrid, Spain.
Abstract
BACKGROUND AND OBJECTIVE: The question of whether children's exposure to traffic-related air pollution (TRAP) contributes to their development of asthma is unresolved. We conducted a systematic review and performed meta-analyses to analyze the association between TRAP and asthma development in childhood. DATA SOURCES: We systematically reviewed epidemiological studies published until 8 September 2016 and available in the Embase, Ovid MEDLINE (R), and Transport databases. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: We included studies that examined the association between children's exposure to TRAP metrics and their risk of 'asthma' incidence or lifetime prevalence, from birth to age 18years old. STUDY APPRAISAL AND SYNTHESIS METHODS: We extracted key characteristics of each included study using a predefined data items template and these were tabulated. We used the Critical Appraisal Skills Programme checklists to assess the validity of each included study. Where four or more independent risk estimates were available for a continuous pollutant exposure, we conducted overall and age-specific meta-analyses, and four sensitivity analyses for each summary meta-analytic exposure-outcome association. RESULTS: Forty-one studies met our eligibility criteria. There was notable variability in asthma definitions, TRAP exposure assessment methods and confounder adjustment. The overall random-effects risk estimates (95% CI) were 1.08 (1.03, 1.14) per 0.5×10-5m-1 black carbon (BC), 1.05 (1.02, 1.07) per 4μg/m3 nitrogen dioxide (NO2), 1.48 (0.89, 2.45) per 30μg/m3 nitrogen oxides (NOx), 1.03 (1.01, 1.05) per 1μg/m3 Particulate Matter <2.5μm in diameter (PM2.5), and 1.05 (1.02, 1.08) per 2μg/m3 Particulate Matter <10μm in diameter (PM10). Sensitivity analyses supported these findings. Across the main analysis and age-specific analysis, the least heterogeneity was seen for the BC estimates, some heterogeneity for the PM2.5 and PM10 estimates and the most heterogeneity for the NO2 and NOx estimates. LIMITATIONS, CONCLUSIONS AND IMPLICATION OF KEY FINDINGS: The overall risk estimates from the meta-analyses showed statistically significant associations for BC, NO2, PM2.5, PM10 exposures and risk of asthma development. Our findings support the hypothesis that childhood exposure to TRAP contributes to their development of asthma. Future meta-analyses would benefit from greater standardization of study methods including exposure assessment harmonization, outcome harmonization, confounders' harmonization and the inclusion of all important confounders in individual studies. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO 2014: CRD42014015448.
BACKGROUND AND OBJECTIVE: The question of whether children's exposure to traffic-related air pollution (TRAP) contributes to their development of asthma is unresolved. We conducted a systematic review and performed meta-analyses to analyze the association between TRAP and asthma development in childhood. DATA SOURCES: We systematically reviewed epidemiological studies published until 8 September 2016 and available in the Embase, Ovid MEDLINE (R), and Transport databases. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: We included studies that examined the association between children's exposure to TRAP metrics and their risk of 'asthma' incidence or lifetime prevalence, from birth to age 18years old. STUDY APPRAISAL AND SYNTHESIS METHODS: We extracted key characteristics of each included study using a predefined data items template and these were tabulated. We used the Critical Appraisal Skills Programme checklists to assess the validity of each included study. Where four or more independent risk estimates were available for a continuous pollutant exposure, we conducted overall and age-specific meta-analyses, and four sensitivity analyses for each summary meta-analytic exposure-outcome association. RESULTS: Forty-one studies met our eligibility criteria. There was notable variability in asthma definitions, TRAP exposure assessment methods and confounder adjustment. The overall random-effects risk estimates (95% CI) were 1.08 (1.03, 1.14) per 0.5×10-5m-1 black carbon (BC), 1.05 (1.02, 1.07) per 4μg/m3 nitrogen dioxide (NO2), 1.48 (0.89, 2.45) per 30μg/m3 nitrogen oxides (NOx), 1.03 (1.01, 1.05) per 1μg/m3 Particulate Matter <2.5μm in diameter (PM2.5), and 1.05 (1.02, 1.08) per 2μg/m3 Particulate Matter <10μm in diameter (PM10). Sensitivity analyses supported these findings. Across the main analysis and age-specific analysis, the least heterogeneity was seen for the BC estimates, some heterogeneity for the PM2.5 and PM10 estimates and the most heterogeneity for the NO2 and NOx estimates. LIMITATIONS, CONCLUSIONS AND IMPLICATION OF KEY FINDINGS: The overall risk estimates from the meta-analyses showed statistically significant associations for BC, NO2, PM2.5, PM10 exposures and risk of asthma development. Our findings support the hypothesis that childhood exposure to TRAP contributes to their development of asthma. Future meta-analyses would benefit from greater standardization of study methods including exposure assessment harmonization, outcome harmonization, confounders' harmonization and the inclusion of all important confounders in individual studies. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO 2014: CRD42014015448.
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