Previous studies have associated ambient particulate chemical constituents with adverse cardiopulmonary health effects. However, specific pollution sources behind the cardiopulmonary health effects of ambient particles are uncertain. We examined the cardiopulmonary health effects of fine particles (PM2.5) from different pollution sources in Beijing, China, among a panel of 40 healthy university students. Study subjects were repeatedly examined for a series of cardiopulmonary health indicators during three 2-month-long study periods (suburban period, urban period 1, and urban period 2) in 2010-2011 before and after relocating from a suburban campus to an urban campus with changing air pollution levels and contents. Daily ambient PM2.5 mass samples were collected over the study and measured for 29 chemical constituents in the laboratory. Source appointment for ambient PM2.5 was performed using Positive Matrix Factorization, and mixed-effects models were used to estimate the cardiopulmonary effects associated with source-specific PM2.5 concentrations. Seven PM2.5 sources were identified as traffic emissions (12.0%), coal combustion (22.0%), secondary sulfate/nitrate (30.2%), metallurgical emission (0.4%), dust/soil (12.4%), industry (6.9%), and secondary organic aerosol (9.9%). Ambient PM2.5 in the suburban campus had larger contributions from secondary sulfate/nitrate (41.8% vs. 22.9%-26.0%) and metallurgical emission (0.7% vs. 0.3%) as compared to that in the urban campus), whereas PM2.5 in the urban campus had larger contributions from traffic emissions (13.0%-16.3% vs. 5.1%), coal combustion (21.0%-30.7% vs. 10.7%), and secondary organic aerosol (9.7%-12.0% vs. 8.7%) as compared to that in the suburban campus. Potential key sources were identified for PM2.5 effects on inflammatory biomarkers (secondary sulfate/nitrate and dust/soil), blood pressure (coal combustion and metallurgical emission), and pulmonary function (dust/soil and industry). Analyses using another source appointment tool Unmix yielded a similar pattern of source contributions and associated health effects. In conclusion, ambient PM2.5 in Beijing suburban and urban areas has two distinct patterns of source contributions, and PM2.5 from different sources may play important roles on different aspects of PM2.5-related cardiopulmonary health effects.

These findings suggest that outdoor NO(2) air pollution may be particularly important for the development of wheeze and asthma among children. Indoor NO(2) concentrations were associated with the prevalence of respiratory symptoms only among girls. Girls may be more susceptible to indoor air pollution than boys.

BackgroundAmbient air pollution has been associated with activation of systemic inflammation and hypercoagulability and increased plasma homocysteine, but the chemical constituents behind the association are not well understood. We examined the relations of various chemical constituents of fine particles (PM2.5) and biomarkers of inflammation, coagulation and homocysteine in the context of traffic-related air pollution.MethodsA panel of 40 healthy college students underwent biweekly blood collection for 12 times before and after their relocation from a suburban campus to an urban campus with changing air pollution contents in Beijing. Blood samples were measured for circulatory biomarkers of high-sensitivity C reactive protein (hs-CRP), tumor necrosis factor alpha (TNF-α), fibrinogen, plasminogen activator inhibitor type 1 (PAI-1), tissue-type plasminogen activator (t-PA), von Willebrand factor (vWF), soluble platelet selectin (sP-selectin), and total homocysteine (tHcy). Various air pollutants were measured in a central air-monitoring station in each campus and 32 PM2.5 chemical constituents were determined in the laboratory. We used three different mixed-effects models (single-constituent model, constituent-PM2.5 joint model and constituent residual model) controlling for potential confounders to estimate the effects of PM2.5 chemical constituents on circulatory biomarkers.ResultsWe found consistent positive associations between the following biomarkers and PM2.5 chemical constituents across different models: TNF-α with secondary organic carbon, chloride, zinc, molybdenum and stannum; fibrinogen with magnesium, iron, titanium, cobalt and cadmium; PAI-1 with titanium, cobalt and manganese; t-PA with cadmium and selenium; vWF with aluminum. We also found consistent inverse associations of vWF with nitrate, chloride and sodium, and sP-selectin with manganese. Two positive associations of zinc with TNF-α and of cobalt with fibrinogen, and two inverse associations of nitrate with vWF, and of manganese with sP-selectin, were independent of the other constituents in two-constituent models using constituent residual data. We only found weak air pollution effects on hs-CRP and tHcy.ConclusionsOur results provide clues for the potential roles that PM2.5 chemical constituents may play in the biological mechanisms through which air pollution may influence the cardiovascular system.

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BackgroundNo standardised method has been adopted for measuring toe-grip strength (TGS), and no reference values have been established for evaluating it. The present study investigated age-related changes in TGS and the association of TGS with various descriptive characteristics.MethodsTGS was measured in both feet of 1842 community-dwelling individuals aged 20–79 years using a toe-grip dynamometer. The participants were classified by decade into six age groups: 20–29, 30–39, 40–49, 50–59, 60–69, and 70–79 years. Correlations for TGS between the dominant and non-dominant sides were analysed according to decade and sex using Pearson’s correlation coefficient. The mean TGS and TGS-to-weight ratio (TGS/Wt%) were compared between sexes by each decade and among all decades by sex using two-way analysis of variance with post-hoc tests. To assess relationships between mean TGS and various descriptive characteristics, we determined Pearson’s correlation coefficient by sex and performed a stepwise multiple-regression analysis. Significance was set at 5%.ResultsCorrelations for TGS between the dominant and non-dominant sides were significant in all decades by sex, ranging from 0.73 for men in their 70s to 0.91 for women in their 50s. Mean TGS and TGS/Wt% significantly differed between the sexes in all decades and in all decades except the 40s, respectively. In men, the mean TGS and TGS/Wt% significantly decreased with aging after the 50s and 60s, respectively. In women, both the mean TGS and TGS/Wt% significantly decreased between the 40s and 50s and between the 60s and 70s. TGS significantly correlated with age, height, and weight in both sexes. The stepwise multiple-regression analysis revealed TGS was significantly associated with sex, age, height, and weight (adjusted R2 = 0.31).ConclusionsTGS was closely correlated between the dominant and non-dominant sides. TGS and TGS/Wt were significantly reduced with aging after the 50s in men and significantly reduced between the 40s and 50s and between the 60s and 70s in women. Age, sex, height, and weight accounted for only 30.8% of the variance in TGS. Therefore, other factors (e.g. toe flexibility, structural characteristics) should be considered for improving the accuracy of predicting TGS.