A review and analysis of personal and ambient PM2.5 measurements: Implications for epidemiology studies

When and where to exercise: An assessment of personal exposure to urban tropical ambient airborne pollutants in Singapore

BACKGROUND

Physical activity is associated with health benefits and has been shown to reduce mortality risk. However, exposure to high levels of ambient fine particulate matter (PM2.5) during exercise can potentially reduce the health benefits of physical activity. This study aims to assess and compare the PM2.5 concentrations of different exercise venues in Singapore by their location attributes and time of day.

METHODS

Personal PM2.5 exposures (μg/m3) at 24 common outdoor exercise venues in Singapore over 49 sampling days were collected using real-time personal sensors from September 2017 to January 2020. Wilcoxon rank-sum test and Kruskal-Wallis test were used to compare PM2.5 concentrations between different timings (peak (0700-0900; 1800-2000) vs. non-peak (0600-0700; 0900-1800; 2000-2300); weekend vs. weekday), and location attributes (near major roads (<50 m) vs. away from major roads (≥50 m)). Multivariable linear regression models were used to assess the associations between location attributes, timings and ambient PM2.5 with personal PM2.5 concentration, adjusting for potential confounders.

RESULTS

Compared with peak hours, exercising during non-peak hours was associated with a significantly lower PM2.5 exposure (median, 17.8 μg/m3 during peak vs. 14.5 μg/m3 during non-peak; P = 0.006). Exercise venues away from major roads have significantly lower PM2.5 concentrations as compared to those located next to major roads (median, 14.4 μg/m3 away from major roads vs. 18.5 μg/m3 next to major roads; P < 0.001). Individuals who exercised in parks experienced the highest PM2.5 exposure (median, 55.0 μg/m3) levels in the afternoon during 1400-1500. Furthermore, ambient PM2.5 concentration was significantly and positively associated with personal PM2.5 exposure (β = 0.85, P < 0.001).

CONCLUSIONS

Our findings suggest that exercising outdoors in the urban environment exposes individuals to differential levels of PM2.5 at different times of the day. Further research should investigate a wider variety of outdoor exercise venues, explore different types of air pollutants, and consider the varying activity patterns of individuals.

Long-term exposure to air pollution and risk of Sarcopenia in adult residents of Taiwan: a nationwide retrospective cohort study

BACKGROUND

Sarcopenia is an age-related, multifactorial syndrome. Previous studies have shown that air pollutants are associated with inflammation and oxidative stress. However, the association between long-term exposure to air pollution and sarcopenia is not completely understood.

METHODS

The Taiwan National Health Research Database (NHIRD) contains medical records of almost all Taiwanese residents. Daily air pollution data collected by the Taiwan Environmental Protection Agency was used to analyze concentrations of sulfur oxide (SO2), carbon monoxide (CO), nitrogen monoxide (NO), nitrogen dioxide (NO2), and particulate matter (PM2.5, PM10). The databases were merged according to the insurants' living area and the location of the air quality monitoring station. We categorized the pollutants into quartiles (Q1, Q2, Q3, and Q4).

RESULTS

Our study population consisted of 286,044 patients, among whom 54.9% were female and 45.1% were male. Compared to Q1 levels of pollutants, Q4 levels of SO2 (adjusted hazard ratio [aHR] = 8.43; 95% confidence interval [CI] = 7.84, 9.07); CO (aHR = 3.03; 95%CI = 2.83, 3.25); NO (aHR = 3.47; 95%CI = 3.23, 3.73); NO2 (aHR = 3.72; 95%CI = 3.48, 3.98); PM2.5 (aHR = 21.9; 95% CI = 19.7, 24.5) and PM10 (aHR = 15.6; 95%CI = 14.1, 17.4) increased risk of sarcopenia.

CONCLUSIONS

Our findings indicated a significantly increased risk of sarcopenia in both male and female residents exposed to high levels of air pollutants.

Contributions of neighborhood social environment and air pollution exposure to Black-White disparities in epigenetic aging

Racial disparities in many aging-related health outcomes are persistent and pervasive among older Americans, reflecting accelerated biological aging for Black Americans compared to White, known as weathering. Environmental determinants that contribute to weathering are poorly understood. Having a higher biological age, measured by DNA methylation (DNAm), than chronological age is robustly associated with worse age-related outcomes and higher social adversity. We hypothesize that individual socioeconomic status (SES), neighborhood social environment, and air pollution exposures contribute to racial disparities in DNAm aging according to GrimAge and Dunedin Pace of Aging methylation (DPoAm). We perform retrospective cross-sectional analyses among 2,960 non-Hispanic participants (82% White, 18% Black) in the Health and Retirement Study whose 2016 DNAm age is linked to survey responses and geographic data. DNAm aging is defined as the residual after regressing DNAm age on chronological age. We observe Black individuals have significantly accelerated DNAm aging on average compared to White individuals according to GrimAge (239%) and DPoAm (238%). We implement multivariable linear regression models and threefold decomposition to identify exposures that contribute to this disparity. Exposure measures include individual-level SES, census-tract-level socioeconomic deprivation and air pollution (fine particulate matter, nitrogen dioxide, and ozone), and perceived neighborhood social and physical disorder. Race and gender are included as covariates. Regression and decomposition results show that individual-level SES is strongly associated with and accounts for a large portion of the disparity in both GrimAge and DPoAm aging. Higher neighborhood deprivation for Black participants significantly contributes to the disparity in GrimAge aging. Black participants are more vulnerable to fine particulate matter exposure for DPoAm, perhaps due to individual- and neighborhood-level SES, which may contribute to the disparity in DPoAm aging. DNAm aging may play a role in the environment "getting under the skin", contributing to age-related health disparities between older Black and White Americans.

Assessing socioeconomic bias of exposure to urban air pollution: an autopsy-based study in São Paulo, Brazil

Background

The characterisation of individual exposure to air pollution in urban scenarios is a challenge in environmental epidemiological studies. We investigated if the city's pollution monitoring stations over or underestimate the exposure of individuals depending on their socioeconomic conditions and daily commuting times.

Methods

The amount of black carbon accumulated in the lungs of 604 deceased who underwent autopsy in São Paulo was considered as a proxy for PM₁₀. The concentrations of PM₁₀ in the residence of the deceased were estimated by interpolating an ordinary kriging model. These two-exposure metrics allowed us to construct an environmental exposure misclassification index ranging from -1 to 1. The association between the index and daily commuting, socioeconomic context index (GeoSES), and street density as predictors was assessed by means of a multilevel linear regression model.

Findings

With a decrease of 0^.1 units in GeoSES, the index increases, on average, by 0^.028 units and with an increase of 1 h in daily commuting, the index increases, on average, by 0^.022 units indicating that individual exposure to air pollution is underestimated in the lower GeoSES and in people with many hours spent in daily commuting.

Interpretation

Reduction of health consequences of air pollution demands not only alternative fuel and more efficient mobility strategies, but also should include profound rethink of cities.

Funding

São Paulo Research Foundation (FAPESP-13/21728-2) and National Council for Scientific and Technological Development (CNPq-304126/2015-2, 401825/2020-5).

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.

High altitude Relieves transmission risks of COVID-19 through meteorological and environmental factors: Evidence from China

Existing studies reported higher altitudes reduce the COVID-19 infection rate in the United States, Colombia, and Peru. However, the underlying reasons for this phenomenon remain unclear. In this study, regression analysis and mediating effect model were used in a combination to explore the altitudes relation with the pattern of transmission under their correlation factors. The preliminary linear regression analysis indicated a negative correlation between altitudes and COVID-19 infection in China. In contrast to environmental factors from low-altitude regions (<1500 m), high-altitude regions (>1500 m) exhibited lower PM2.5, average temperature (AT), and mobility, accompanied by high SO₂ and absolute humidity (AH). Non-linear regression analysis further revealed that COVID-19 confirmed cases had a positive correlation with mobility, AH, and AT, whereas negatively correlated with SO₂, CO, and DTR. Subsequent mediating effect model with altitude-correlated factors, such as mobility, AT, AH, DTR and SO₂, suffice to discriminate the COVID-19 infection rate between low- and high-altitude regions. The mentioned evidence advance our understanding of the altitude-mediated COVID-19 transmission mechanism.