Individual exposure to NO2 in relation to spatial and temporal exposure indices in Stockholm, Sweden: the INDEX study

Characteristics and determinants of personal exposure to typical air pollutants: A pilot study in Beijing and Baoding, China

Personal exposure to fine particulate matter (PM_2.5), nitrogen oxides (NO_x, NO₂ and NO), ozone (O₃) and sulfur dioxide (SO₂) was repeatedly measured among fourteen office workers in Beijing and Baoding, China in summer, autumn and winter of 2019. Time-activity patterns were simultaneously recorded. Determinants of personal air pollution exposure were investigated for each pollutant via a linear mixed effect model. The personal concentrations of PM_2.5, NO₂, NO and O₃ were higher in autumn and winter than those in summer. A decreasing trend was found in the personal PM_2.5 level for a typical indoor population in Beijing, indicating that particulate pollution was effectively controlled in Beijing and its surrounding area. The personal levels of PM_2.5, NO₂, and O₃ were weakly correlated with those monitored at ambient stations and were lower than the respective ambient levels except for PM_2.5 in summer and NO₂ in winter. This pilot study showed that the indoor air environment, ambient pollution, traffic-related variables and temperature were significant exposure sources for office workers. Our study highlighted the significance of controlling traffic emissions and improving the workplace air quality to protect the health of office workers. More importantly, we demonstrated the feasibility of model development for personal air pollution exposure prediction.

Association between exposure to combustion-related air pollution and multiple sclerosis risk

BACKGROUND

Smoking and occupational pulmonary irritants contribute to multiple sclerosis (MS) development. We aimed to study the association between ambient air pollution and MS risk and potential interaction with the human leukocyte antigen (HLA)-DRB1*15:01 allele.

METHODS

Exposure to combustion-related air pollution was estimated as outdoor levels of nitrogen oxides (NOx) at the participants' residence locations, by spatially resolved dispersion modelling for the years 1990-18. Using two population-based case-control studies (6635 cases, 8880 controls), NOx levels were associated with MS risk by calculating odds ratios (OR) with 95% confidence intervals (CI) using logistic regression models. Interaction between high NOx levels and the HLA-DRB1*15:01 allele regarding MS risk was calculated by the attributable proportion due to interaction (AP). In addition, a register study was performed comprising all MS cases in Sweden who had received their diagnosis between 1993 and 2018 (n = 22 173), with 10 controls per case randomly selected from the National Population register.

RESULTS

Residential air pollution was associated with MS risk. NOx levels (3-year average) exceeding the 90th percentile (24.6 µg/m3) were associated with an OR of 1.37 (95% CI 1.10-1.76) compared with levels below the 25th percentile (5.9 µg/m3), with a trend of increasing risk of MS with increasing levels of NOx (P <0.0001). A synergistic effect was observed between high NOx levels (exceeding the lower quartile among controls) and the HLA-DRB1*15:01 allele regarding MS risk (AP 0.26, 95% CI 0.13-0.29).

CONCLUSIONS

Our findings indicate that moderate levels of combustion-related ambient air pollution may play a role in MS development.

Association Between Cardiovascular Disease and Long-term Exposure to Air Pollution With the Risk of Dementia

Question

Does cardiovascular disease play a role in the association between long-term exposure to air pollution and dementia?

Findings

In this cohort study of 2927 participants in the Swedish National Study on Aging and Care in Kungsholmen, air pollution exposure was associated with dementia risk despite comparatively low exposure levels. Heart failure and ischemic heart disease enhanced this association, and the development of stroke seemed to be an important intermediate condition.

Meaning

In this study, virtually all of the association between air pollution and dementia seemed to occur through the presence or the development of cardiovascular disease, which suggests a need to optimize treatment of concurrent cardiovascular disease and risk factor control in older adults at higher risk for dementia and living in polluted urban areas.

Importance

Emerging yet contrasting evidence associates air pollution with incident dementia, and the potential role of cardiovascular disease (CVD) in this association is unclear.

Objective

To investigate the association between long-term exposure to air pollution and dementia and to assess the role of CVD in that association.

Design, Setting, and Participants

Data for this cohort study were extracted from the ongoing Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), a longitudinal population-based study with baseline assessments from March 21, 2001, through August 30, 2004. Of the 5111 randomly selected residents in the Kungsholmen district of Stockholm 60 years or older and living at home or in institutions, 521 were not eligible (eg, due to death before the start of the study or no contact information). Among the remaining 4590 individuals, 3363 (73.3%) were assessed. For the current analysis, 2927 participants who did not have dementia at baseline were examined, with follow-up to 2013 (mean [SD] follow-up time, 6.01 [2.56] years). Follow-up was completed February 18, 2013, and data were analyzed from June 26, 2018, through June 20, 2019.

Exposures

Two major air pollutants (particulate matter ≤2.5 μm [PM_2.5] and nitrogen oxide [NO_x]) were assessed yearly from 1990, using dispersion models for outdoor levels at residential addresses.

Main Outcomes and Measures

The hazard of dementia was estimated using Cox proportional hazards regression models. The potential of CVD (ie, atrial fibrillation, ischemic heart disease, heart failure, and stroke) to modify and mediate the association between long-term exposure to air pollution and dementia was tested using stratified analyses and generalized structural equation modeling.

Results

At baseline, the mean (SD) age of the 2927 participants was 74.1 (10.7) years, and 1845 (63.0%) were female. Three hundred sixty-four participants with incident dementia were identified. The hazard of dementia increased by as much as 50% per interquartile range difference in mean pollutant levels during the previous 5 years at the residential address (hazard ratio [HR] for difference of 0.88 μg/m³ PM_2.5, 1.54 [95% CI, 1.33-1.78]; HR for difference of 8.35 μg/m³ NO_x, 1.14 [95% CI, 1.01-1.29]). Heart failure (HR for PM_2.5, 1.93 [95% CI, 1.54-2.43]; HR for NO_x, 1.43 [95% CI, 1.17-1.75]) and ischemic heart disease (HR for PM_2.5, 1.67 [95% CI, 1.32-2.12]; HR for NO_x, 1.36 [95% CI, 1.07-1.71]) enhanced the dementia risk, whereas stroke appeared to be the most important intermediate condition, explaining 49.4% of air pollution–related dementia cases.

Conclusions and Relevance

This study found that long-term exposure to air pollution was associated with a higher risk of dementia. Heart failure and ischemic heart disease appeared to enhance the association between air pollution and dementia, whereas stroke seemed to be an important intermediate condition between the association of air pollution exposure with dementia.

PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis

BACKGROUND

The use of proxy exposure estimates for PM_2.5 and NO₂ in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest.

OBJECTIVES

We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants.

DATA SOURCES AND ELIGIBILITY CRITERIA

We reviewed the literature (ISI Web of Science, Medline, 2000-2016) for English language studies (in any age group in any location (NO₂) or Europe and North America (PM_2.5)) that reported repeated measurements over time both for personal and ambient PM_2.5 or NO₂ concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures.

RESULTS

Thirty-two papers for PM_2.5 and 24 for NO₂ were identified. Outdoor sources were found to contribute 44% (range: 33-55%) of total personal exposure to PM_2.5 and 74% (range: 57-88%) to NO₂. Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 μg/m³ and 12.0 ppb for PM_2.5 and NO₂ respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 μg/m³ and 7.17 ppb. Our findings indicated also higher error variability for NO₂ than PM_2.5. Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample.

LIMITATIONS, CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO₂ had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO₂ compared with PM_2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models.

Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

Analyzing individual exposure in urban areas offers several challenges where both the individual's activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals' activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual's time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives.

Using smartphones to collect time-activity data for long-term personal-level air pollution exposure assessment

Because of the spatiotemporal variability of people and air pollutants within cities, it is important to account for a person's movements over time when estimating personal air pollution exposure. This study aimed to examine the feasibility of using smartphones to collect personal-level time-activity data. Using Skyhook Wireless's hybrid geolocation module, we developed "Apolux" (Air, Pollution, Exposure), an Android(TM) smartphone application designed to track participants' location in 5-min intervals for 3 months. From 42 participants, we compared Apolux data with contemporaneous data from two self-reported, 24-h time-activity diaries. About three-fourths of measurements were collected within 5 min of each other (mean=74.14%), and 79% of participants reporting constantly powered-on smartphones (n=38) had a daily average data collection frequency of <10 min. Apolux's degree of temporal resolution varied across manufacturers, mobile networks, and the time of day that data collection occurred. The discrepancy between diary points and corresponding Apolux data was 342.3 m (Euclidian distance) and varied across mobile networks. This study's high compliance and feasibility for data collection demonstrates the potential for integrating smartphone-based time-activity data into long-term and large-scale air pollution exposure studies.

I feel you-monitoring environmental variables related to asthma in an integrated real-time frame

The study of asthma and other complex diseases has proven to be a "moving target" for researchers due to its complex aetiology, difficulty in definition, and immeasurable environmental effects. A large number of studies regarding the contribution of both genetic and environmental factors often result in contradictory results, in part due to the highly heterogeneous nature of asthma. Recent literature has focused on the epigenetic signatures of asthma caused by environmental factors, highlighting the importance of environment. However, unlike the genetic techniques, environmental assessment still lacks accuracy. A plausible solution for this problem would be an individual-based environmental exposure assessment, relying on new technologies such as personal real-time environmental sensors. This could prove to enable the assessment of the whole environmental exposure-or exposome-matching in terms of precision the genome that is emphasized in most studies so far. In addition, the measurement of the whole array of biological molecules, in response to the environment action, could help understand the context of the disease. The current perspective comprises a beyond-genetics integrated vision of omics technology coupled with real-time environmental measures targeting to enhance our comprehension of the disease genesis.

The relevance of commuter and work/school exposure in an epidemiological study on traffic-related air pollution

Exposure during transport and at non-residential locations is ignored in most epidemiological studies of traffic-related air pollution. We investigated the impact of separately estimating NO2 long-term outdoor exposures at home, work/school, and while commuting on the association between this marker of exposure and potential health outcomes. We used spatially and temporally resolved commuter route data and model-based NO2 estimates of a population sample in Basel, Switzerland, to assign individual NO2-exposure estimates of increasing complexity, namely (1) home outdoor concentration; (2) time-weighted home and work/school concentrations; and (3) time-weighted concentration incorporating home, work/school and commute. On the basis of their covariance structure, we estimated the expectable relative differences in the regression slopes between a quantitative health outcome and our measures of individual NO2 exposure using a standard measurement error model. The traditional use of home outdoor NO2 alone indicated a 12% (95% CI: 11-14%) underestimation of related health effects as compared with integrating both home and work/school outdoor concentrations. Mean contribution of commuting to total weekly exposure was small (3.2%; range 0.1-13.5%). Thus, ignoring commute in the total population may not significantly underestimate health effects as compared with the model combining home and work/school. For individuals commuting between Basel-City and Basel-Country, ignoring commute may produce, however, a significant attenuation bias of 4% (95% CI: 4-5%). Our results illustrate the importance of including work/school locations in assessments of long-term exposures to traffic-related air pollutants such as NO2. Information on individuals' commuting behavior may further improve exposure estimates, especially for subjects having lengthy commutes along major transportation routes.

Determinants of personal exposure to some carcinogenic substances and nitrogen dioxide among the general population in five Swedish cities

Environmental levels of airborne carcinogenic and related substances are comparatively better known than individual exposure and its determinants. We report on a personal monitoring program involving five Swedish urban populations. The aim of the program was to investigate personal exposure to benzene, 1,3-butadiene, formaldehyde, and nitrogen dioxide (NO2). The measurements were performed among 40 inhabitants during seven consecutive days, in one urban area each year, during 2000-2008. The estimated population exposure levels were 1.95 μg/m(3) for benzene, 0.56 μg/m(3) for 1,3-butadiene, 19.4 μg/m(3) for formaldehyde, and 14.1 μg/m(3) for NO2. Statistical analysis using a mixed-effects model revealed that time spent in traffic and time outdoors contributed to benzene and 1,3- butadiene exposure. For benzene, refueling a car was an additional determinant influencing the exposure level. Smoking or environmental tobacco smoke were significant determinants of exposure to NO2, benzene, and 1,3-butadiene. Those with a gas stove had higher NO2 exposure. Living in a single-family house increased the exposure to formaldehyde significantly. In a variance component model, the between-subject variance dominated for 1,3-butadiene and formaldehyde, whereas the between-city variance dominated for NO2. For benzene, the between-subject and between-cities variances were similar.