Validity of using annual mean particulate matter concentrations as measured at fixed site in assessing personal exposure: an exposure assessment study in Japan

Early-life exposure to ambient air pollutants and kidney function in adolescents: a cohort study based on the 'Children of 1997' Hong Kong birth cohort

OBJECTIVES

Air pollution is increasingly linked to impaired kidney function in adults. However, little is known about how early-life exposure to air pollutants affects kidney function in adolescents.

STUDY DESIGN

Cohort study.

METHODS

We leveraged data from the 'Children of 1997' Hong Kong population-representative birth cohort (N = 8327). Residential exposure to average ambient levels of four air pollutants, including inhalable particle (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and nitrogen monoxide (NO), during in utero, infancy, and childhood periods was estimated using the inverse distance weighting. Kidney function was assessed using estimated glomerular filtration rate (eGFR) calculated from age-adjusted equations for adolescents. Generalized linear regression was used to examine the association of air pollutant exposure in each period with kidney function at 17.6 years. Two-pollutant models tested the robustness of the association.

RESULTS

Of the 3350 participants included, 51.4% were boys. Exposure to PM10 was associated with poorer kidney function. Each interquartile range increment in PM10 was inversely associated with eGFR (β: -2.933, 95% confidence interval -4.677 to -1.189) in utero, -2.362 (-3.992 to -0.732) infancy, -2.708 (-4.370 to -1.047) childhood, and -2.828 (-4.409 to -1.247) overall. Exposure to PM10 and SO2in utero had a stronger inverse association with kidney function in males. The associations were robust to PM10 exposure in two-pollutant models.

CONCLUSIONS

Our findings suggest that early-life exposure to ambient PM10 and SO2 is associated with reduced kidney function in adolescents, especially exposure in utero.

Validity of using ambient concentrations as surrogate exposures at the individual level for fine particle and black carbon: A systematic review and meta-analysis

Exposure measurement error is an important source of bias in epidemiological studies. We assessed the validity of employing ambient (outdoor) measurements as proxies of personal exposures at individual levels focusing on fine particles (PM_2.5) and black carbon (BC)/elemental carbon (EC) on a global scale. We conducted a systematic review and meta-analysis and searched databases (ISI Web of Science, Scopus, PubMed, Ovid MEDLINE®, Ovid Embase, and Ovid BIOSIS) to retrieve observational studies in English language published from 1 January 2006 until 5 May 2021. Correlation coefficients (r) between paired ambient (outdoor) concentration and personal exposure for PM_2.5 or BC/EC were standardized as effect size. We used random-effects meta-analyses to pool the correlation coefficients and investigated the causes of heterogeneity and publication bias. Furthermore, we employed subgroup and meta-regression analyses to evaluate the modification of pooled estimates by potential mediators. This systematic review identified thirty-two observational studies involving 1744 subjects from ten countries, with 28 studies for PM_2.5 and 11 studies for BC/EC. Personal PM_2.5 exposure is more strongly correlated with ambient (outdoor) concentrations (0.63, 95% confidence interval [CI]: 0.57-0.68) than personal BC/EC exposure (0.49, 95% CI: 0.38-0.59), with significant differences in ṝ (0.14, 95% CI: 0.03-0.25; p < 0.05). The results demonstrated that the health status of participants was a significant modifier of pooled correlations. In addition, the personal to ambient (P/A) ratio for PM_2.5 and average ambient BC/EC levels were potential effect moderators of the pooled ṝ. The funnel plots and Egger's regression test indicated inevident publication bias. The pooled estimates were robust through sensitivity analyses. The results support the growing consensus that the validity coefficient of proxy measures should be addressed when interpreting results from epidemiological studies to better understand how strong health outcomes are affected by different levels of PM_2.5 and their components.

Personal PM2.5-bound PAH exposure, oxidative stress and lung function: The associations and mediation effects in healthy young adults

Decreased lung function is an early hazard of respiratory damage from fine particulate matter (PM_2.5) exposure. Limited studies have explored the association between PM_2.5-bound polycyclic aromatic hydrocarbons (PAHs) and lung function, but studies at the personal level in healthy young adults are scarce. Here, we assessed personal PM_2.5 and PM_2.5-bound PAH levels in a panel of 45 healthy young adults by a time-weighted model. The aims were to investigate the relationship between personal exposure and lung function by a linear mixed effect model, and to explore the mediating effects of oxidative stress in this association. The results showed that personal exposure to PM_2.5 and PAHs had the greatest negative effect on forced expiratory volume in 1 s (FEV₁), peak expiratory flow rate (PEF) and forced expiratory flow between 25% and 75% vital capacity (FEF_25-75) at lag 3 days. An IQR increase in personal PM_2.5 exposure was associated with a change of 0.35% (95% CI: 0.27%, 0.42%) in FEV₁, 0.39% (95% CI: 0.29%, 0.47%) in PEF and 0.36% (95% CI: 0.27%, 0.45%) in FEF_25-75. An IQR increase in personal PAH exposure was associated with a decrease of 0.63% (95% CI: 0.55%, 0.69%) in FEV₁, 0.69% (95% CI: 0.61%, 0.75%) in PEF and 0.66% (95% CI: 0.57%, 0.72%) in FEF_25-75. Additionally, exposure to PM_2.5 and PAHs resulted in the strongest positive effects on urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) and 8-iso-prostaglandin-F_2α (8-iso-PGF_2α). Of these, 8-OHdG mediated 10.33%, 8.87% and 9.45% of the associations of personal PM_2.5 exposure with FEV₁, PEF and FEF_25-75, respectively. Our results revealed that personal exposure to PM_2.5 and PAHs was associated with lung function decline in healthy young adults, and urinary 8-OHdG mediated the association between personal PM_2.5 and lung function.

Evaluating carbon content in airway macrophages as a biomarker of personal exposure to fine particulate matter and its acute respiratory effects

It remains unclear whether carbon content in airway macrophages (AM) can predict personal short-term exposure to fine particulate matter (PM_2.5) air pollution and its respiratory health effects. We aimed to evaluate the pathway from personal PM_2.5 exposure to adverse respiratory outcomes through AM carbon content. We designed a longitudinal panel study with 3 scheduled follow-ups among 113 non-smoking patients of chronic obstructive pulmonary disease in Shanghai, China, from April 2017 to January 2019. We quantified AM carbon content from induced sputum by image analysis, tested lung function and measured sputum levels of 4 pro-inflammatory cytokines and 2 anti-inflammatory cytokines. We applied the "meet in the middle" approach incorporating linear mixed-effect models to evaluate the associations from external PM_2.5 exposure to respiratory outcomes through AM carbon content. Our results indicated that personal exposure to PM_2.5 within 24 h was significantly associated with decreased forced expiratory volume in 1s and anti-inflammatory cytokines, as well as increased macrophages and pro-inflammatory cytokines. These changes were accompanied by increased areas of AM carbon and higher percentage of AM area occupied by carbon, both of which were associated with increased levels of pro-inflammatory cytokines and decreased levels of anti-inflammatory cytokines. Exposure to ambient black carbon and organic carbon in PM_2.5 within 2 days was significantly associated with increased AM carbon area and percentage of AM area occupied by carbon. Our findings reinforced the causality in respiratory health effects of PM_2.5 in which increased AM carbon content might serve as a valid exposure biomarker.

Indoor air quality of 5,000 households and its determinants. Part A: Particulate matter (PM2.5 and PM10-2.5) concentrations in the Japan Environment and Children's Study

Exposure to particulate matter (PM) is one of the important risk factors for morbidity and mortality. Although PM concentrations have been assessed using air quality monitoring stations or modelling, few studies have measured indoor PM in large-scale birth cohorts. The Japan Environment and Children's Study (JECS) measured indoor and outdoor air quality in approximately 5000 households when the participating children were aged 1.5 and 3 years. PM was collected using portable pumps for 7 days (total of 24 h), inside and outside each home. Prediction models for indoor PM concentrations were built using data collected at age 1.5 years and post-validated against data collected at age 3 years. Median indoor/outdoor PM_2.5 and PM_10-2.5 concentrations at age 1.5 years [3 years] were 12.9/12.7 [12.5/11.3] μg/m³ and 5.0/6.3 [5.1/6.1] μg/m³, respectively. Random forest regression analysis found that the major predictors of indoor PM_2.5 were indoor PM_10-2.5, outdoor PM_2.5, indoor smoking, observable smoke and indoor/outdoor temperature. Indoor PM_2.5, outdoor PM_10-2.5, indoor humidity and opening room windows were important predictors of indoor PM_10-2.5 concentrations. Indoor benzene, acetaldehyde, ozone and nitrogen dioxide concentrations were also found to predict indoor PM_2.5 and PM_10-2.5 concentrations, possibly due to the formation of secondary organic aerosols. These findings demonstrate the importance of reducing outdoor PM concentrations, avoiding indoor smoking, using air cleaner in applicable and diminishing sources of VOCs that could form secondary organic aerosols, and the resulting models can be used to predict indoor PM concentrations for the rest of the JECS cohort.

Personal exposure to particulate matter in peri-urban India: predictors and association with ambient concentration at residence

Scalable exposure assessment approaches that capture personal exposure to particles for purposes of epidemiology are currently limited, but valuable, particularly in low-/middle-income countries where sources of personal exposure are often distinct from those of ambient concentrations. We measured 2 × 24-h integrated personal exposure to PM_2.5 and black carbon in two seasons in 402 participants living in peri-urban South India. Means (sd) of PM_2.5 personal exposure were 55.1(82.8) µg/m³ for men and 58.5(58.8) µg/m³ for women; corresponding figures for black carbon were 4.6(7.0) µg/m³ and 6.1(9.6) µg/m³. Most variability in personal exposure was within participant (intra-class correlation ~20%). Personal exposure measurements were not correlated (R_spearman < 0.2) with annual ambient concentration at residence modeled by land-use regression; no subgroup with moderate or good agreement could be identified (weighted kappa ≤ 0.3 in all subgroups). We developed models to predict personal exposure in men and women separately, based on time-invariant characteristics collected at baseline (individual, household, and general time-activity) using forward stepwise model building with mixed models. Models for women included cooking activities and household socio-economic position, while models for men included smoking and occupation. Models performed moderately in terms of between-participant variance explained (38-53%) and correlations between predictions and measurements (R_spearman: 0.30-0.50). More detailed, time-varying time-activity data did not substantially improve the performance of the models. Our results demonstrate the feasibility of predicting personal exposure in support of epidemiological studies investigating long-term particulate matter exposure in settings characterized by solid fuel use and high occupational exposure to particles.

Occupational exposure to particulate matter from air pollution in the outdoor workplaces in Almaty during the cold season

Background

A large fraction of population in Almaty and other Kazakhstan cities is employed in the outdoor jobs and likely exposed to high levels of particulate matter (PM) during the cold season. The magnitude of such occupational exposure remains unknown; therefore, the aim was to quantify the levels of exposure to PM₁₀ in the outdoor workplaces in Almaty in order to guide future interventions of primary prevention.

Study Design and Participants’ Profile in the Sub-Cohort Study in the Japan Environment and Children’s Study (JECS)

Background

The Japan Environment and Children’s Study (JECS) is a nationwide birth cohort study investigating environmental effects on children’s health and development. A Sub-Cohort Study has begun, conducting extended exposure and outcome measurements by targeting a subgroup randomly selected from the JECS Main Study. We report the Sub-Cohort Study methodology and participants’ baseline profiles.

Methods

Of 100,148 children in the JECS Main Study, children born after April 1, 2013 who met eligibility criteria ([1] all questionnaire and medical record data from children and their mothers collected from the first trimester to 6 months of age, [2] biospecimens [except umbilical cord blood] from children and their mothers collected at first to second/third trimester and delivery) were randomly selected for each Regional Centre at regular intervals. Face-to-face assessment of neuropsychiatric development, body measurement, paediatrician’s examination, blood/urine collection for clinical testing and chemical analysis, and home visits (ambient and indoor air measurement and dust collection) are conducted. Participants are followed up at 1.5 and 3 years old for home visits, and 2, 4, 6, and 8 years old for developmental/medical examination. The details of protocols after age 10 are under discussion.

Results

Of 10,302 selected children, 5,017 participated. The profiles of the participating mothers, fathers and children did not substantially differ between the Main Study and Sub-Cohort Study.

Conclusion

The JECS Sub-Cohort Study offers a platform for investigating associations between environmental exposure and outcomes.

Different relationships between personal exposure and ambient concentration by particle size

Ambient particulate matter (PM) concentrations at monitoring stations were often used as an indicator of population exposure to PM in epidemiological studies. The correlation between personal exposure and ambient concentrations of PM varied because of diverse time-activity patterns. The aim of this study was to determine the relationship between personal exposure and ambient concentrations of PM₁₀ and PM_2.5 with minimal impact of time-activity pattern on personal exposure. Performance of the MicroPEM, v3.2 was evaluated by collocation with central ambient air monitors for PM₁₀ and PM_2.5. A field technician repeatedly conducted measurement of 24 h personal exposures to PM₁₀ and PM_2.5 with a fixed time-activity pattern of office worker over 26 days in Seoul, Korea. The relationship between the MicroPEM and the ambient air monitor showed good linearity. Personal exposure and ambient concentrations of PM_2.5 were highly correlated with a fixed time-activity pattern compared with PM₁₀. The finding implied a high infiltration rate of PM_2.5 and low infiltration rate of PM₁₀. The relationship between personal exposure and ambient concentrations of PM₁₀ and PM_2.5 was different for high level episodes. In the Asian dust episode, staying indoors could reduce personal exposure to PM₁₀. However, personal exposure to PM_2.5 could not be reduced by staying indoors during the fine dust advisory episode.

Comparison between air pollution concentrations measured at the nearest monitoring station to the delivery hospital and those measured at stations nearest the residential postal code regions of pregnant women in Fukuoka

BACKGROUND

Numerous earlier studies examining the association of air pollution with maternal and foetal health estimated maternal exposure to air pollutants based on the women's residential addresses. However, residential addresses, which are personally identifiable information, are not always obtainable. Since a majority of pregnant women reside near their delivery hospitals, the concentrations of air pollutants at the respective delivery hospitals may be surrogate markers of pollutant exposure at home. We compared air pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital with those measured at the closest monitoring stations to the respective residential postal code regions of pregnant women in Fukuoka.

METHODS

Aggregated postal code data for the home addresses of pregnant women who delivered at Kyushu University Hospital in 2014 was obtained from Kyushu University Hospital. For each of the study's 695 women who resided in Fukuoka Prefecture, we assigned pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital and pollutant concentrations measured at the nearest monitoring station to their respective residential postal code regions.

RESULTS

Among the 695 women, 584 (84.0%) resided in the proximity of the nearest monitoring station to hospital or one of the four other stations (as the nearest stations to their respective residential postal code region) in Fukuoka city. Pearson's correlation for daily mean concentrations among the monitoring stations in Fukuoka city was strong for fine particulate matter (PM_2.5), suspended particulate matter (SPM), and photochemical oxidants (Ox) (coefficients ≥0.9), but moderate for coarse particulate matter (the result of subtracting the PM_2.5 from the SPM concentrations), nitrogen dioxide, and sulphur dioxide. Hospital-based and residence-based concentrations of PM_2.5, SPM, and Ox were comparable.

CONCLUSIONS

For PM_2.5, SPM, and Ox, exposure estimation based on the delivery hospital is likely to approximate that based on the home of pregnant women.

Comparison of Highly Resolved Model-Based Exposure Metrics for Traffic-Related Air Pollutants to Support Environmental Health Studies

Human exposure to air pollution in many studies is represented by ambient concentrations from space-time kriging of observed values. Space-time kriging techniques based on a limited number of ambient monitors may fail to capture the concentration from local sources. Further, because people spend more time indoors, using ambient concentration to represent exposure may cause error. To quantify the associated exposure error, we computed a series of six different hourly-based exposure metrics at 16,095 Census blocks of three Counties in North Carolina for CO, NO_x, PM_2.5, and elemental carbon (EC) during 2012. These metrics include ambient background concentration from space-time ordinary kriging (STOK), ambient on-road concentration from the Research LINE source dispersion model (R-LINE), a hybrid concentration combining STOK and R-LINE, and their associated indoor concentrations from an indoor infiltration mass balance model. Using a hybrid-based indoor concentration as the standard, the comparison showed that outdoor STOK metrics yielded large error at both population (67% to 93%) and individual level (average bias between −10% to 95%). For pollutants with significant contribution from on-road emission (EC and NO_x), the on-road based indoor metric performs the best at the population level (error less than 52%). At the individual level, however, the STOK-based indoor concentration performs the best (average bias below 30%). For PM_2.5, due to the relatively low contribution from on-road emission (7%), STOK-based indoor metric performs the best at both population (error below 40%) and individual level (error below 25%). The results of the study will help future epidemiology studies to select appropriate exposure metric and reduce potential bias in exposure characterization.

Scavenging of PM2.5 by precipitation and the effects of precipitation pattern changes on health risks related to PM2.5 in Tokyo, Japan

Fine particulate matter (aerodynamic diameter<2.5 μm; PM2.5) poses risks to human health. While precipitation is the main process for decreasing ambient pollutant concentrations, scavenging of PM2.5 by precipitation remains to be investigated. Here we formulated the processes of PM2.5 scavenging by precipitation from observed PM2.5 concentrations ([PM2.5]) and precipitation intensities. Then we analyzed how changes in precipitation patterns would affect health risks related to PM2.5 on the basis of a Monte Carlo simulation. Tokyo, the capital of Japan, was selected as the target for this study because of its social significance. We found that [PM2.5] decreased significantly through scavenging of PM2.5 from the atmosphere by precipitation. In contrast, we found no significant correlation between reduction of [PM2.5] and precipitation intensity. Our model for estimating the reduction of PM2.5 and the Monte Carlo simulation showed good agreement with observations. Among various changes in potential precipitation patterns, changes in the arithmetic mean of the number of events and/or in precipitation duration were more influential on reduction of [PM2.5] than changes in their standard deviations. Health risks due to PM2.5 will increase with decreases in precipitation duration and occurrence.