Fine particulate matter, temperature, and lung function in healthy adults: findings from the HVNR study

Effects of particulate matter on respiratory disease and the impact of meteorological factors in Busan, Korea

BACKGROUND

Both air pollution and weather impact hospitalization for respiratory diseases. However, few studies have investigated the contribution of weather to hospitalization related to the adverse effects of air pollution. This study analyzed the effects of particulate matter (PM) on daily respiratory-related hospital admissions, taking into account meteorological factors.

METHODS

Daily hospital admissions for respiratory diseases (acute bronchitis, allergic rhinitis, and asthma) between 2007 and 2010 were extracted from the National Health Insurance Corporation, Korea. Patients were divided into three age-based groups (0-15, 16-64, and ≥65 years). PM levels were obtained from 19 monitoring stations in Busan.

RESULTS

The mean number of patients admitted for acute bronchitis, allergic rhinitis, and asthma was 5.8 ± 11.9, 4.4 ± 6.1, and 3.3 ± 3.3, respectively. During that time, the daily mean PM₁₀ and PM_2.5 concentrations were 49.6 ± 20.5 and 24.2 ± 10.9 μg/m³, respectively. The mean temperature anomaly was 7.0 ± 2.3 °C; the relative humidity was 62.0 ± 18.0%. Hospital admission rates for respiratory diseases increased with increasing PM and temperature, and with decreasing relative humidity. A multivariate analysis including PM, temperature anomaly, relative humidity, and age showed a significant increase in respiratory-related admissions with increasing PM levels and a decreasing relative humidity. Higher PM_2.5 levels had a greater effect on respiratory-related hospital admission than did PM₁₀ levels. Children and the elderly were the most susceptible to hospital admission for respiratory disease.

CONCLUSIONS

PM levels and meteorological factors impacted hospitalization for respiratory diseases, especially in children and the elderly. The effect of PM on respiratory diseases increased as the relative humidity decreased.

Fine Particulate Matter Concentrations in Urban Chinese Cities, 2005-2016: A Systematic Review

Background: Particulate matter pollution has become a growing health concern over the past few decades globally. The problem is especially evident in China, where particulate matter levels prior to 2013 are publically unavailable. We conducted a systematic review of scientific literature that reported fine particulate matter (PM_2.5) concentrations in different regions of China from 2005 to 2016. Methods: We searched for English articles in PubMed and Embase and for Chinese articles in the China National Knowledge Infrastructure (CNKI). We evaluated the studies overall and categorized the collected data into six geographical regions and three economic regions. Results: The mean (SD) PM_2.5 concentration, weighted by the number of sampling days, was 60.64 (33.27) μg/m³ for all geographic regions and 71.99 (30.20) μg/m³ for all economic regions. A one-way ANOVA shows statistically significant differences in PM_2.5 concentrations between the various geographic regions (F = 14.91, p < 0.0001) and the three economic regions (F = 4.55, p = 0.01). Conclusions: This review identifies quantifiable differences in fine particulate matter concentrations across regions of China. The highest levels of fine particulate matter were found in the northern and northwestern regions and especially Beijing. The high percentage of data points exceeding current federal regulation standards suggests that fine particulate matter pollution remains a huge problem for China. As pre-2013 emissions data remain largely unavailable, we hope that the data aggregated from this systematic review can be incorporated into current and future models for more accurate historical PM_2.5 estimates.

Fine Particulate Constituents and Lung Dysfunction: A Time-Series Panel Study

The evidence is quite limited regarding the constituents of fine particulate matter (PM_2.5) responsible for lung dysfunction. We designed a time-series panel study in 28 patients to examine the effects of 10 major constituents of PM_2.5 on lung function with repeated daily measurements from December 2012 to May 2013 in Shanghai, China. We applied a linear mixed-effect model combined with a distributed lag model to estimate the cumulative effects of PM_2.5 constituents on morning/evening forced expiratory volume in 1-s (FEV₁) and peak expiratory flow (PEF) over a week. The cumulative decreases in morning FEV₁, evening FEV₁, morning PEF and evening PEF associated with an interquartile range (35.8 μg/m³) increase in PM_2.5 concentrations were 33.49 [95% confidence interval(CI):2.45,54.53] mL, 16.80 (95%CI:3.75,29.86) mL, 4.48 (95%CI:2.30,6.66) L/min, and 1.31 (95%CI:-0.85,3.47) L/min, respectively. These results were not substantially changed after adjusting for gases in two-pollutant models. The associations of elemental carbon (EC) and nitrates with morning/evening FEV₁, and the associations of EC and sulfates with morning PEF were robust after controlling for PM_2.5. This study demonstrated that short-term exposure to PM_2.5 was associated with reduced pulmonary function. Some constituents (EC, sulfate and nitrate) may be responsible for the detrimental effects.

The interactive effects between high temperature and air pollution on mortality: A time-series analysis in Hefei, China

Recent evidence suggests that there may be an interaction between air pollution and heat on mortality, which is pertinent in the context of global climate change. We sought to examine this interaction in Hefei, a hot and polluted Chinese city. We conducted time-series analyses using daily mortality, air pollutant concentration (including particulate matter with aerodynamic diameter <10μm (PM₁₀), sulphur dioxide (SO₂) and nitrogen dioxide (NO₂)), and temperature data from 2008 to 2014. We applied quasi-Poisson regression models with natural cubic splines and examined the interactive effects using temperature-stratified models. Subgroup analyses were conducted by age, gender, and educational levels. We observed consistently stronger associations between air pollutants and mortality at high temperatures than at medium temperatures. These differences were statistically significant for the associations between PM₁₀ and non-accidental mortality and between all pollutants studied and respiratory mortality. Mean percentage increases in non-accidental mortality per 10μg/m³ at high temperatures were 2.40% (95% confidence interval: 0.64 to 4.20) for PM₁₀, 7.77% (0.60 to 15.00) for SO₂, and 6.83% (-1.37 to 15.08) for NO₂. The estimates for PM₁₀ were 3.40% (0.96 to 5.90) in females and 4.21% (1.44 to 7.05) in the illiterate, marking them as more vulnerable. No clear trend was identified by age. We observed an interaction between air pollutants and high temperature on mortality in Hefei, which was stronger in females and the illiterate. This may be due to differences in behaviours affecting personal exposure to high temperatures and has potential policy implications.

Short-term exposure to high ambient air pollution increases airway inflammation and respiratory symptoms in chronic obstructive pulmonary disease patients in Beijing, China

BACKGROUND

Few studies have investigated the short-term respiratory effects of ambient air pollution in chronic obstructive pulmonary disease (COPD) patients in the context of high pollution levels in Asian cities.

METHODS

A panel of 23 stable COPD patients was repeatedly measured for biomarkers of airway inflammation including exhaled nitric oxide (FeNO) and exhaled hydrogen sulfide (FeH2S) (215 measurements) and recorded for daily respiratory symptoms (794person-days) in two study periods in Beijing, China in January-September 2014. Daily ambient air pollution data were obtained from nearby central air-monitoring stations. Mixed-effects models were used to estimate the associations between exposures and health measurements with adjustment for potential confounders including temperature and relative humidity.

RESULTS

Increasing levels of air pollutants were associated with significant increases in both FeNO and FeH2S. Interquartile range (IQR) increases in PM2.5 (76.5μg/m(3), 5-day), PM10 (75.0μg/m(3), 5-day) and SO2 (45.7μg/m(3), 6-day) were associated with maximum increases in FeNO of 13.6% (95% CI: 4.8%, 23.2%), 9.2% (95% CI: 2.1%, 16.8%) and 34.2% (95% CI: 17.3%, 53.4%), respectively; and the same IQR increases in PM2.5 (6-day), PM10 (6-day) and SO2 (7-day) were associated with maximum increases in FeH2S of 11.4% (95% CI: 4.6%, 18.6%), 7.8% (95% CI: 2.3%, 13.7%) and 18.1% (95% CI: 5.5%, 32.2%), respectively. Increasing levels of air pollutants were also associated with increased odds ratios of sore throat, cough, sputum, wheeze and dyspnea.

CONCLUSIONS

FeH2S may serve as a novel biomarker to detect adverse respiratory effects of air pollution. Our results provide potential important public health implications that ambient air pollution may pose risk to respiratory health in the context of high pollution levels in densely-populated cities in the developing world.

Association between children's forced vital capacity and long-term exposure to local ambient temperature in China: A national cross-sectional survey

It is well documented that short-term exposure to extreme ambient temperature is associated with respiratory disorder. However, few studies have assessed the long-term effect of temperature on children's lung function. The present study aimed to investigate the association between long-term exposure to local ambient temperature and children's forced vital capacity (FVC) in China. We analyzed the FVC data of 71,768 children from the 2010 Chinese National Survey on Students' Construction and Health (CHNSCH), and local annual average ambient temperature, relative humidity, air pollutants data from China Meteorological Administration and Ministry of Environment Protection of China. Generalized additive model (GAM) with non-linear function was used to examine the effect of ambient temperature on children's FVC. The results showed that low temperature was significantly associated with decrease of FVC in Chinese children within certain temperature range while adjusting for individual characteristics, socioeconomic conditions, air pollutants and relative humidity. The largest alteration of FVC related to the annual average temperature difference among cities from 20.4°C to 4.5°C was observed, being 242.7ml (95%CI: 220.0, 265.3) decrease in FVC. The similar association was found in both physically active and inactive children, while the largest alteration of FVC related to the temperature difference reached 329.1ml (95%CI: 296.7, 361.6) in physically active children and 290.5ml (95%CI: 255.7, 325.3) in physically inactive ones. Public health policy should be developed for protecting children's respiratory health during growth and development in some areas with cold weather. Key message What is the key question? Few studies have assessed the long-term effect of temperature on children's forced vital capacity (FVC). We analyzed the Chinese national survey data to clarify the association between children's forced vital capacity and long-term exposure to local ambient temperature. What is the bottom line? Our study found that low temperature was significantly associated with decrease of forced vital capacity in children of 30 cities in China. The largest alteration of FVC related to the temperature difference from 20.4°C to 4.5°C was observed, being 242.7ml (95%CI: 220.0, 265.3) decrease in FVC. Why read on? The presented study provide some evidence about long-term effect of temperature on children's respiratory health and public health policy should be developed for protecting children from adverse effects of low temperature on their respiratory health during growth and development in some areas with cold weather.

The effect of pollutional haze on pulmonary function

Detrimental health effects of atmospheric exposure to ambient particulate matter (PM) have been investigated in numerous studies. Exposure to pollutional haze, the carrier of air pollutants such as PM and nitrogen dioxide (NO2) has been linked to lung and cardiovascular disease, resulting increases in both hospital admissions and mortality. This review focuses on the constituents of pollutional haze and its effects on pulmonary function. The article presents the available information and seeks to correlate pollutional haze and pulmonary function.

The exposure metric choices have significant impact on the association between short-term exposure to outdoor particulate matter and changes in lung function: Findings from a panel study in chronic obstructive pulmonary disease patients

BACKGROUND

The use of ambient air pollution data obtained from central air-monitoring stations as surrogates for participants' exposures to outdoor air pollutants in previous studies may have introduced bias in the estimation of exposure-response associations.

OBJECTIVES

We investigated and compared the effects of short-term exposure to outdoor particulate matter (PMout) and outdoor-originated equivalent personal PM (PMeq) on lung function in chronic obstructive pulmonary disease (COPD) patients.

METHODS

A total of 33 doctor-diagnosed stable COPD patients were recruited and repeatedly measured for lung function (totally 170 measurements) in 2013-2014. Daily PMout concentrations were obtained from central-monitoring stations, and daily time-weighted average PMeq concentrations were estimated based on PMout over the study. Associations of PM with lung function were estimated using mixed-effects models.

RESULTS

Interquartile range increases in PM2.5out (111.0 μg/m(3), 5-day) and PM10out (112.0 μg/m(3), 3-day) were associated with a 3.3% (95% confidence interval [CI]: -5.8%, -0.8%) reduction and a 2.1% (95%CI: -3.9%, -0.3%) reduction in forced vital capacity (FVC), respectively. Similar results were found for forced expiratory volume in 1s (FEV1). An interquartile range increase in PM2.5eq (45.3 μg/m(3), 3-day), but not PM10eq, was still associated with a 1.7% (95%CI: -3.3%, -0.1%) reduction in FVC.

CONCLUSIONS

Our study may provide a novel approach to assess the association of ambient PM with health observations with improved accuracy.

PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.

Effect of Personal Exposure to PM2.5 on Respiratory Health in a Mexican Panel of Patients with COPD

Background: Air pollution is a problem, especially in developing countries. We examined the association between personal exposure to particulate matter with an aerodynamic diameter less than 2.5 µm (PM_2.5) on respiratory health in a group of adults with chronic obstructive pulmonary disease (COPD). Methods: All participants resided in Mexico City and during follow-up, personal exposure to PM_2.5, respiratory symptoms, medications, and daily activity were registered daily. Peak expiratory flow (PEF) was measured twice daily, from February through December, 2000, in 29 adults with moderate, severe, and very severe COPD. PEF changes were estimated for each 10 µg/m³ increment of PM_2.5, adjustment for severity of COPD, minimum temperature, and day of the sampling. Results: For a 10-µg/m³ increase in the daily average of a two-day personal exposure to PM_2.5, there was a significant 33% increase in cough (95% CI, range, 5‒69%), and 23% in phlegm (95% CI, range, 2‒54%), a reduction of the PEF average in the morning of −1.4 L/min. (95% CI , range, −2.8 to −0.04), and at night of −3.0 L/min (95% CI, range, −5.7 to −0.3), respectively. Conclusions: Exposure to PM_2.5 was associated with reductions in PEF and increased respiratory symptoms in adults with COPD. The PEF reduction was observed both at morning and at night.

Short-Term Effects of Fine Particulate Matter and Temperature on Lung Function among Healthy College Students in Wuhan, China

Ambient fine particulate matter (PM) has been associated with impaired lung function, but the effect of temperature on lung function and the potential interaction effect between PM and temperature remain uncertain. To estimate the short-term effects of PM2.5 combined with temperature on lung function, we measured the daily peak expiratory flow (PEF) in a panel of 37 healthy college students in four different seasons. Meanwhile, we also monitored daily concentrations of indoor and outdoor PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm), ambient temperature and relative humidity of the study area, where the study participants lived and attended school. Associations of air pollutants and temperature with lung function were assessed by generalized estimating equations (GEEs). A 10 μg/m3 increase of indoor PM2.5 was associated with a change of -2.09 L/min in evening PEF (95%CI: -3.73 L/min--0.51 L/min) after adjusting for season, height, gender, temperature and relative humidity. The changes of -2.17 L/min (95%CI: -3.81 L/min- -0.52 L/min) and -2.18 L/min (95%CI: -3.96 L/min--0.41 L/min) in evening PEF were also observed after adjusting for outdoor SO2 and NO2 measured by Environmental Monitoring Center 3 kilometers away, respectively. An increase in ambient temperature was found to be associated with a decrease in lung function and our results revealed a small but significant antagonistic interactive effect between PM2.5 and temperature. Our findings suggest that ambient PM2.5 has an acute adverse effect on lung function in young healthy adults, and that temperature also plays an important role.

The association between ambient temperature and children's lung function in Baotou, China

The objective of this study is to examine the association between ambient temperature and children's lung function in Baotou, China. We recruited 315 children (8-12 years) from Baotou, China in the spring of 2004, 2005, and 2006. They performed three successive forced expiratory measurements three times daily (morning, noon, and evening) for about 5 weeks. The highest peak expiratory flow (PEF) was recorded for each session. Daily data on ambient temperature, relative humidity, and air pollution were monitored during the same period. Mixed models with a distributed lag structure were used to examine the effects of temperature on lung function while adjusting for individual characteristics and environmental factors. Low temperatures were significantly associated with decreases in PEF. The effects lasted for lag 0-2 days. For all participants, the cumulative effect estimates (lag 0-2 days) were -1.44 (-1.93, -0.94) L/min, -1.39 (-1.92, -0.86) L/min, -1.40 (-1.97, -0.82) L/min, and -1.28 (-1.69, -0.88) L/min for morning, noon, evening, and daily mean PEF, respectively, associated with 1 °C decrease in daily mean temperature. Generally, the effects of temperature were slightly stronger in boys than in girls for noon, evening, and daily mean PEF, while the effects were stronger in girls for morning PEF. PM2.5 had joint effects with temperature on children's PEF. Higher PM2.5 increased the impacts of low temperature. Low ambient temperatures are associated with lower lung function in children in Baotou, China. Preventive health policies will be required for protecting children from the cold weather.

Air pollution and COPD in China

Recently, many researchers paid more attentions to the association between air pollution and chronic obstructive pulmonary disease (COPD). Haze, a severe form of outdoor air pollution, affected most parts of northern and eastern China in the past winter. In China, studies have been performed to evaluate the impact of outdoor air pollution and biomass smoke exposure on COPD; and most studies have focused on the role of air pollution in acutely triggering symptoms and exacerbations. Few studies have examined the role of air pollution in inducing pathophysiological changes that characterise COPD. Evidence showed that outdoor air pollution affects lung function in both children and adults and triggers exacerbations of COPD symptoms. Hence outdoor air pollution may be considered a risk factor for COPD mortality. However, evidence to date has been suggestive (not conclusive) that chronic exposure to outdoor air pollution increases the prevalence and incidence of COPD. Cross-sectional studies showed biomass smoke exposure is a risk factor for COPD. A long-term retrospective study and a long-term prospective cohort study showed that biomass smoke exposure reductions were associated with a reduced decline in forced expiratory volume in 1 second (FEV1) and with a decreased risk of COPD. To fully understand the effect of air pollution on COPD, we recommend future studies with longer follow-up periods, more standardized definitions of COPD and more refined and source-specific exposure assessments.

A hybrid model for PM₂.₅ forecasting based on ensemble empirical mode decomposition and a general regression neural network

Exposure to high concentrations of fine particulate matter (PM₂.₅) can cause serious health problems because PM₂.₅ contains microscopic solid or liquid droplets that are sufficiently small to be ingested deep into human lungs. Thus, daily prediction of PM₂.₅ levels is notably important for regulatory plans that inform the public and restrict social activities in advance when harmful episodes are foreseen. A hybrid EEMD-GRNN (ensemble empirical mode decomposition-general regression neural network) model based on data preprocessing and analysis is firstly proposed in this paper for one-day-ahead prediction of PM₂.₅ concentrations. The EEMD part is utilized to decompose original PM₂.₅ data into several intrinsic mode functions (IMFs), while the GRNN part is used for the prediction of each IMF. The hybrid EEMD-GRNN model is trained using input variables obtained from principal component regression (PCR) model to remove redundancy. These input variables accurately and succinctly reflect the relationships between PM₂.₅ and both air quality and meteorological data. The model is trained with data from January 1 to November 1, 2013 and is validated with data from November 2 to November 21, 2013 in Xi'an Province, China. The experimental results show that the developed hybrid EEMD-GRNN model outperforms a single GRNN model without EEMD, a multiple linear regression (MLR) model, a PCR model, and a traditional autoregressive integrated moving average (ARIMA) model. The hybrid model with fast and accurate results can be used to develop rapid air quality warning systems.