Ambient Air Pollution and Socioeconomic Status in China

Estimating neighborhood-based mortality risk associated with air pollution: A prospective study

Effect modification of integrated neighborhood environment on associations of air pollution with mortality remained unclear. We analyzed data from UK biobank prospective study (n = 421,650, median 12.5 years follow-up) to examine disparities of mortality risk associated with air pollution among varied neighborhood settings. Fine particulate matter (PM2.5), PM10 and nitrogen dioxide (NO2) were measured and assigned to each participants' address. Diverse ecological and societal settings of neighborhoods were integrated with principal component analysis and categorized into disadvantaged, intermediate and advantaged levels. We estimated mortality risk associated with air pollution across diverse neighborhoods using Cox regression. We calculated community-level proportions of mortality attributable to air pollutants. There was evidence of higher all-cause and respiratory disease mortality risk associated with PM2.5 and NO2 among those in disadvantaged neighborhoods. In disadvantaged communities, air pollutants explained larger proportions of deaths and such disparities persisted over past decades. Across 2010-2021, reducing PM2.5 and NO2 to 10 μg/m3 (World Health Organization limits) would save 87,000 (52,000-120,000) and 91,000 (37,000-145,000) deaths of populations aged ≥ 40 years, with 150 000 deaths occurred in disadvantaged neighborhood settings. These findings suggested that disadvantaged neighborhoods can exacerbate mortality risk associated with air pollution.

Relationship between exposure to fine particulate matter and cardiovascular risk factors and the modifying effect of socioeconomic status: a cross-sectional study in Beijing, China

Accumulating research suggested that long-term exposure to fine particulate matter (PM2.5) is related to cardiovascular disease (CVD). However, evidence regarding the relationship between PM2.5 and CVD risk factors remains inconsistent. We hypothesized that this association may be partially modified by socioeconomic status (SES). To investigate the relationships and to test the modifying effect of SES, we included baseline data for 21,018 adults from September 2017 to May 2018. PM2.5 concentrations were determined by employing an amalgamation of linear measurements obtained from monitoring stations located near the participants' residential and workplace addresses. We assessed SES across several domains, including income, education, and occupation levels, as well as through a composite SES index. The results indicated that for every 10 μg/m3 increase in PM2.5 exposure, the risk of hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and hyperhomocysteinemia (HHcy) increased by 7.7% [Odds ratio (OR) = 1.077, 95% Confidence Interval (CI) = 1.011, 1.146], 19.6% (OR = 1.196, 95% CI = 1.091, 1.312), 4.2% (OR = 1.042, 95% CI = 1.002, 1.084), and 17.1% (OR = 1.171, 95% CI = 1.133, 1.209), respectively. Compared to the high SES group, those with low SES are more prone to hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and HHcy. Notably, the disparities in SES appear significant in the relationship between PM2.5 exposure and hypercholesterolemia as well as hyperbetalipoproteinemia. But for diabetes and HHcy, the modification effect of SES on PM2.5 shows an inconsistent pattern. In conclusion, the results confirm the association between PM2.5 and cardiovascular risk factors and low SES significantly amplified the adverse PM2.5 effect on dyslipidemia. It is crucial to emphasize a need to improve the socioeconomic inequality among adults in Beijing and contribute to the understanding of the urgency in protecting the health of vulnerable groups.

Associations and attributable burdens in late-life exposure to PM2.5 and its major components and depressive symptoms in middle-aged and older adults: A nationwide cohort study

BACKGROUND

Depression in late life has been associated with reduced quality of life and increased mortality. Whether the chronic fine particular matter (PM2.5) and its components exposure are contributed to the older depression symptoms remains unclear.

METHOD

Middle-aged and older adults (>45 years) were selected from the China Health and Retirement Longitudinal Study during the four waves of interviews. The concentrations of PM2.5 and its major constituents were calculated using near real-time data at a spatial resolution of 10 km during the study period. The depressive symptom was evaluated by the Depression Center for Epidemiologic Studies Depression (CES-D)-10 score. The fix-effect model was applied to evaluate the association between PM2.5 and its major constituents with depressive symptoms. Three three-step methods were used to explore the modification role of sleep duration against the depressive symptoms caused by PM2.5 exposure.

RESULTS

In our study, a total of 52,683 observations of 16,681 middle-aged and older adults were assessed. Each interquartile range (IQR) level of PM2.5 concentration exposure was longitudinally associated with a 2.6 % (95 % confidence interval [CI]: 1.3 %, 4.0 %) increase in the depression CES-D-10 score. Regarding the major components of PM2.5, OM, NO3-, and NH4+ showed the leading toxicity effects, which could increase the depression CES-D-10 score by 2.2 % (95 %CI: 1.0 %, 3.4 %), 2.2 % (0.6 %, 3.9 %), and 2.0 % (95 %CI: 0.6 %, 3.4 %) correspondingly. Besides, males were more susceptible to the worse depressive symptoms caused by PM2.5 and its major components exposure than female subpopulations. Shortened sleep duration might be the mediator of PM2.5-associated depressive symptoms.

CONCLUSION

Our results suggest that long-term exposure to PM2.5 and its major components were associated with an increased risk for depressive symptoms in middle-aged and older adults. Reducing the leading components of PM2.5 may cost-effectively alleviate the disease burden of depression and promote healthy longevity in heavy pollutant countries.

Particulate matter pollution, polygenic risk score and mosaic loss of chromosome Y in middle-aged and older men from the Dongfeng-Tongji cohort study

Mosaic loss of chromosome Y (mLOY) is the most common somatic alteration as men aging and may reflect genome instability. PM exposure is a major health concern worldwide, but its effects with genetic factors on mLOY has never been investigated. Here we explored the associations of PM2.5 and PM10 exposure with mLOY of 10,158 males measured via signal intensity of 2186 probes in male-specific chromosome-Y region from Illumina array data. The interactive and joint effects of PM2.5 and PM10 with genetic factors and smoking on mLOY were further evaluated. Compared with the lowest tertiles of PM2.5 levels in each exposure window, the highest tertiles in the same day, 7-, 14-, 21-, and 28-day showed a 0.005, 0.006, 0.007, 0.007, and 0.006 decrease in mLRR-Y, respectively (all P < 0.05), with adjustment for age, BMI, smoking pack-years, alcohol drinking status, physical activity, education levels, season of blood draw, and experimental batch. Such adverse effects were also observed in PM10-mLOY associations. Moreover, the unweighted and weighted PRS presented significant negative associations with mLRR-Y (both P < 0.001). Participants with high PRS and high PM2.5 or PM10 exposure in the 28-day separately showed a 0.018 or 0.019 lower mLRR-Y level [β (95 %CI) = -0.018 (-0.023, -0.012) and - 0.019 (-0.025, -0.014), respectively, both P < 0.001], when compared to those with low PRS and low PM2.5 or PM10 exposure. We also observed joint effects of PM with smoking on exacerbated mLOY. This large study is the first to elucidate the impacts of PM2.5 exposure on mLOY, and provides key evidence regarding the interactive and joint effects of PM with genetic factors on mLOY, which may promote understanding of mLOY development, further modifying and increasing healthy aging in males.

Association of socioeconomic position with sensory impairment among Chinese population: a nationally representative cohort and Mendelian randomization study

Aims

To investigate the association between socioeconomic position (SEP) and sensory impairments (SIs).

Methods

We used data from the China Health and Retirement Longitudinal Study (CHARLS) (2015). Logistic regressions estimated the odds ratio for associations of SEP with SIs. In addition, Mendelian randomization (MR) analysis was conducted to assess the causal relationship between them with the inverse variance weighting (IVW) estimator. MR-Egger, simple median, weighted median, maximum likelihood, and robust adjusted profile score were employed for sensitivity analyses.

Results

In the observational survey, we enrolled 19,690 individuals aged 45 and above. SEP was negatively associated with SIs. Adjusted odds of vision impairment were higher for illiterate (1.50; 95%CI: 1.19, 1.91), less than elementary school diploma (1.76; 95%CI: 1.39, 2.25), middle school diploma (1.53; 95%CI: 1.21, 1.93) and lower income (all p < 0.001). The odds of hearing impairment were significantly higher for people with less than a high school diploma than those with a college degree or higher diploma, for agricultural workers than non-agricultural workers, and for people in low-income families (p < 0.01). The MR analysis also showed that occupation was associated with HI (1.04, 95%CI: 1.01, 1.09, p < 0.05) using IVW.

Conclusion

We found that both observational and causal evidence supports the theory that SEP can result in SIs and that timely discovery, targeted management, and education can prevent SIs among middle-aged and older adults.

Association between metabolic syndrome severity score and cardiovascular disease: results from a longitudinal cohort study on Chinese adults

Objective

This study aimed to quantify the severity of metabolic syndrome(MetS) and investigate its association with cardiovascular disease(CVD) risk on Chinese adults.

Methods

13,500 participants from the Zhejiang Adult Chronic Disease Study were followed up between 2010 and 2021. A continuous MetS severity score derived from the five components of MetS was used to quantify MetS severity, and the association between MetS severity and the risk of incident CVD was assessed using Cox proportional hazard and restricted cubic spline regression.

Results

Both the presence and severity of MetS were strongly associated with CVD risk. MetS was related to an increased risk of CVD (hazard ratio(HR):1.700, 95% confidence interval(CI): 1.380-2.094). Compared with the hazard ratio for CVD in the lowest quartile of the MetS severity score, that in the second, third, and highest quartiles were 1.812 (1.329-2.470), 1.746 (1.265-2.410), and 2.817 (2.015-3.938), respectively. A linear and positive dose-response relationship was observed between the MetS severity and CVD risk (P for non-linearity = 0.437). Similar results were found in various sensitivity analyses.

Conclusion

The MetS severity score was significantly associated with CVD risk. Assessing MetS severity and further ensuring intervention measures according to the different severities of MetS may be more useful in preventing CVD.

Pathogenesis of PM2.5-Related Disorders in Different Age Groups: Children, Adults, and the Elderly

The effects of PM2.5 on human health fluctuate greatly among various age groups, influenced by a range of physiological and immunological reactions. This paper compares the pathogenesis of the disease caused by PM2.5 in people of different ages, focusing on how children, adults, and the elderly are each susceptible to it because of differences in their bodies. Regarding children, exposure to PM2.5 is linked to many negative consequences. These factors consist of inflammation, oxidative stress, and respiratory problems, which might worsen pre-existing conditions and potentially cause neurotoxicity and developmental issues. Epigenetic changes can affect the immune system and make people more likely to get respiratory diseases. On the other hand, exposures during pregnancy can change how the cardiovascular and central nervous systems develop. In adults, the inhalation of PM2.5 is associated with a wide range of health problems. These include respiratory difficulties, reduced pulmonary function, and an increased susceptibility to illnesses such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. In addition, exposure to PM2.5 induces systemic inflammation, cardiovascular diseases, insulin resistance, and neurotoxic consequences. Evident disturbances in the immune system and cognitive function demonstrate the broad impact of PM2.5. The elderly population is prone to developing respiratory and cardiovascular difficulties, which worsen their pre-existing health issues and raise the risk of cognitive decline and neurological illnesses. Having additional medical conditions, such as peptic ulcer disease, significantly increases the likelihood of being admitted to hospital.

Exploring the Modifying Role of GDP and Greenness on the Short Effect of Air Pollutants on Respiratory Hospitalization in Beijing

It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM2.5, PM10, NO2, SO2, O3, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10 μg/m3 increase in PM2.5, PM10, NO2, SO2, and O3 led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1 mg/m3 increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO2 (p < 0.001), SO2 (p < 0.001), O3 (during the warm season, p < 0.001), and CO (p < 0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.

Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions: progress in efficacy and geographic equality

Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs.

Short-term effects of exposure to ambient PM2.5 and its components on hospital admissions for threatened and spontaneous abortions: A multicity case-crossover study in China

BACKGROUND

The adverse effects of short-term exposure to PM2.5 and its components on hospital admissions for threatened and spontaneous abortions (TSAB) are still controversial.

METHODS

Data on daily hospitalizations for TSAB and PM2.5 and its components, including sulfate (SO42-), nitrate (NO3-), ammonium salt (NH4+), organic matter (OM), and black carbon (BC), were collected from January 2015 to December 2021 (total 2,557 days) in five cities in China. Case-crossover analyses were conducted to investigate the short-term associations between PM2.5 and its components and TSAB. Additionally, the modification effects by age (<35 and ≥35 years), season (cold and warm seasons), and the "Three-Year Action Plan to Win the Blue Sky Defense War" (before and after implementation) on the above associations were further conducted.

RESULTS

For each 10 μg/m3 (1 μg/m3 for BC) increase, the strongest relative risks (95% confidence intervals) of hospitalization for TSAB were 1.011 (1.001-1.021) for PM2.5 in lag02, 1.060 (1.003-1.120) for SO42- in lag02, 1.035 (1.000-1.070) for NO3- in lag02, 1.065 (1.009-1.124) for NH4+ in lag02, 1.047 (1.008-1.088) for OM in lag01 and 1.029 (1.005-1.054) for BC in lag02 (all P <0.05). Furthermore, significant modifying effects of age and the Action Plan were found. The effects of NO3- (lag2), NH4+ (lag2), and BC (lag2) were more pronounced in mothers aged ≥35 years and the effects of PM2.5 (lag4), NO3- (lag4), NH4+ (lag4), OM (lag4), and BC (lag4) was more pronounced in the period before the Action Plan was implemented (all P modification <0.05).

CONCLUSION

Short-term exposure to ambient PM2.5 and its components (SO42-, NO3-, NH4+, OM, and BC) was related to increased risks of hospitalization for TSAB. The effects were more pronounced in mothers aged ≥35 years and the period before the Action Plan.

Long-term exposure to air pollution and risk of insulin resistance: A systematic review and meta-analysis

OBJECTIVE

The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR.

METHODS

A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO2, and SO2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR).

RESULTS

This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM2.5 induced a 0.40% change in HOMA-IR (95%CI: -0.03, 0.84; I2 =67.4%, p = 0.009), while PM10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO2 or SO2 exposure concentration was only 0.09% (95%CI: -0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: -0.04, 0.06; I2 =0.0%, p = 0.638), respectively.

CONCLUSIONS

Long-term exposures to PM2.5, PM10, NO2 or SO2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR.

Ethnic and socioeconomic inequalities in air pollution exposure: a cross-sectional analysis of nationwide individual-level data from the Netherlands

BACKGROUND

Air pollution contributes to a large disease burden and some populations are disproportionately exposed. We aimed to evaluate ethnic and socioeconomic differences in exposure to air pollution in the Netherlands.

METHODS

We did a nationwide, cross-sectional analysis of all residents of the Netherlands on Jan 1, 2019. Sociodemographic information was centralised by Statistics Netherlands and mainly originated from the National Population Register, the tax register, and education registers. Concentrations of NO2, PM2·5, PM10, and elemental carbon, modelled by the National Institute for Public Health and the Environment, were linked to the individual-level demographic data. We assessed differences in air pollution exposures across the 40 largest minority ethnic groups. Evaluation of how ethnicity intersected with socioeconomic position in relation to exposures was done for the ten largest ethnic groups, plus Chinese and Indian groups, in both urban and rural areas using multivariable linear regression analyses.

FINDINGS

The total study population consisted of 17 251 511 individuals. Minority ethnic groups were consistently exposed to higher levels of air pollution than the ethnic Dutch population. The magnitude of inequalities varied between the minority ethnic groups, with 3-44% higher exposures to NO2 and 1-9% higher exposures to PM2·5 compared with the ethnic Dutch group. Average exposures were highest for the lowest socioeconomic group. Ethnic inequalities in exposure remained after adjustment for socioeconomic position and were of similar magnitude in urban and rural areas.

INTERPRETATION

The variability in air pollution exposure across ethnic and socioeconomic subgroups in the Netherlands indicates environmental injustice at the intersection of social characteristics. The health consequences of the observed inequalities and the underlying processes driving them warrant further investigation.

FUNDING

The Gravitation programme of the Dutch Ministry of Education, Culture, and Science, the Netherlands Organization for Scientific Research, the Netherlands Organisation for Health Research and Development, and Amsterdam University Medical Center.

Effects of long-term exposure to ambient fine particulate air pollution on all-cause mortality in Taiwan

According to the US Environmental Protection Agency's Integrated Science Assessment (ISA), there is a causal relationship between fine particulate matter (PM2.5) exposure and increased mortality rates. A similar association was also reported by the International Agency for Research on Cancer (IARC). While many studies are available on this relationship between PM exposure and elevated mortality frequency in Europe and North America, there are limited investigations in Asia. Thus, the aim of this study was to perform an ecological investigation to determine the relationship between exposure to ambient PM2.5 levels and all-cause mortality in 66 in Taiwan municipalities. To undertake this investigation, annual PM2.5 levels and age-standardized all-cause mortality rates were calculated for male and female residents of these areas from 2010 to 2020. Weighted-multiple regression analyses were used to obtain adjusted risk ratio (RR) controlling for possible confounding by urbanization level, physician density, and annual mean household income. Annual PM2.5 levels of each municipality were divided into tertiles. Data demonstrated that men residing in areas with intermediate tertile PM2.5 levels (21.06 to 27.29 µg/m3) and the highest tertiles levels (27.30-33.11 µg/m3) exhibited adjusted RRs of 1.06 (95% CI = 1.03-1.08) and 1.13 (95% CI = 1.10-1.16), respectively. Women in these locations displayed a similar risk, 1.03 (0.99-1.06) and 1.07 (1.04-1.11), respectively. These findings indicate that ambient exposure to PM2.5 increased risk for all-cause mortality rates in both men and women in Taiwan during this time period.

Atmospheric elemental carbon pollution and its regional health disparities in China

Previous studies have reported that atmospheric elemental carbon (EC) may pose potentially elevated toxicity when compared to total ambient fine particulate matter (PM2.5). However, most research on EC has been conducted in the US and Europe, whereas China experiences significantly higher EC pollution levels. Investigating the health impact of EC exposure in China presents considerable challenges due to the absence of a monitoring network to document long-term EC levels. Despite extensive studies on total PM2.5 in China over the past decade and a significant decrease in its concentration, changes in EC levels and the associated mortality burden remain largely unknown. In our study, we employed a combination of satellite remote sensing, available ground observations, machine learning techniques, and atmospheric big data to predict ground EC concentrations across China for the period 2005-2018, achieving a spatial resolution of 10 km. Our findings reveal that the national average annual mean EC concentration has remained relatively stable since 2005, even as total PM2.5 levels have substantially decreased. Furthermore, we calculated the all-cause non-accidental deaths attributed to long-term EC exposure in China using baseline mortality data and pooled mortality risk from a cohort study. This analysis unveiled significant regional disparities in the mortality burden resulting from long-term EC exposure in China. These variations can be attributed to varying levels of effectiveness in EC regulations across different regions. Specifically, our study highlights that these regulations have been effective in mitigating EC-related health risks in first-tier cities. However, in regions characterized by a high concentration of coal-power plants and industrial facilities, additional efforts are necessary to control emissions. This observation underscores the importance of tailoring environmental policies and interventions to address the specific challenges posed by varying emission sources and regional contexts.

Evolution in disparity of PM2.5 pollution in China

The spatial disparity of air pollutants is one of the key influential factors for environmental inequality. We quantitatively evaluated the evolution of PM2.5 spatial disparity in China during 2013-2020, and investigated the associations between PM2.5 spatial disparity and economic indicators. Differences in PM2.5 between more- and less-polluted cities declined over time, suggesting decreased absolute disparity. However, the more polluted cities in 2013 remained so in 2017 and 2020, and vice versa, indicating persistent relative disparity. PM2.5 pollution levels increased with higher GDP per capita in less-developed areas of China, but such negative effects weakened over time, while economic development tended to promote cleaner air in developed areas of China. Therefore, policies to improve air quality and promote economic development simultaneously are needed in China to reduce the disparity of air pollution and promote all people to enjoy environmental equality.

Examining the geographical distribution of air pollution disparities across different racial and ethnic groups: Incorporating workplace addresses

BACKGROUND

Most previous studies on air pollution exposure disparities among racial and ethnic groups in the US have been limited to residence-based exposure and have given little consideration to population mobility and spatial patterns of residences, workplaces, and air pollution. This study aimed to examine air pollution exposure disparities by racial and ethnic groups while explicitly accounting for both the work-related activity of the population and localized spatial patterns of residential segregation, clustering of workplaces, and variability of air pollutant concentration.

METHOD

In the present study, we assessed population-level exposure to air pollution using tabulated residence and workplace addresses of formally employed workers from LEHD Origin-Destination Employment Statistics (LODES) data at the census tract level across eight Metropolitan Statistical Areas (MSAs). Combined with annual-averaged predictions for three air pollutants (PM2.5, NO2, O3), we investigated racial and ethnic disparities in air pollution exposures at home and workplaces using pooled (i.e., across eight MSAs) and regional (i.e., with each MSA) data.

RESULTS

We found that non-White groups consistently had the highest levels of exposure to all three air pollutants, at both their residential and workplace locations. Narrower exposure disparities were found at workplaces than residences across all three air pollutants in the pooled estimates, due to substantially lower workplace segregation than residential segregation. We also observed that racial disparities in air pollution exposure and the effect of considering work-related activity in the exposure assessment varied by region, due to both the levels and patterns of segregation in the environments where people spend their time and the local heterogeneity of air pollutants.

CONCLUSIONS

The results indicated that accounting for workplace activity illuminates important variation between home- and workplace-based air pollution exposure among racial and ethnic groups, especially in the case of NO2. Our findings suggest that consideration of both activity patterns and place-based exposure is important to improve our understanding of population-level air pollution exposure disparities, and consequently to health disparities that are closely linked to air pollution exposure.

Associations of healthy lifestyle and three latent socioeconomic status patterns with physical multimorbidity among middle-aged and older adults in China

BACKGROUND

Multimorbidity is an emerging global public health concern. However, complex associations of healthy lifestyle and socioeconomic status (SES) with multimorbidity have not been identified.

METHODS

This population-based prospective cohort study used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) to explore these relationships. Physical multimorbidity was measured using 12 non-communicable diseases. Latent class analysis (LCA) was conducted to determine the optimal SES patterns based on annual per-capita household expenditure, occupation, education level, and health insurance. The healthy lifestyle score (0-5) was constructed comprising information on smoking, drinking, physical activity, sleep, and body shape.

RESULTS

Of 17,708 participants in the CHARLS, 7776 were eligible for inclusion in our analysis (13.3% with high SES, 26.1% with medium SES, and 60.6% with low SES). Compared with high SES participants, those with low SES had higher risks of incident physical multimorbidity (OR 1.22, 95% CI 1.05, 1.42), which was competitively mediated by lifestyle (mediation proportion, -10.17%, 95% CI -19.12%, -1.23%). Significant interactions were observed between lifestyle factors and SES in patients with incident diabetes. Participants with low SES and no or one healthy lifestyle factor had a higher risk of incident physical multimorbidity than those with high SES and four to five healthy lifestyle factors (OR 2.19, 95% CI 1.57, 3.04).

CONCLUSION

Healthy lifestyles competitively mediate a fractional proportion of socioeconomic inequity in incident physical multimorbidity. Furthermore, healthy lifestyles were associated with lower multimorbidity risk in the SES subgroups, supporting the important role of lifestyle in reducing physical multimorbidity burden.

Ambient air pollution and the health-related quality of life of older adults: Evidence from Shandong China

Ambient air pollution is a major public health concern impacting all aspects of human health. There is a lack of studies on the impact of ambient air pollution on health-related quality of life (HRQoL) of older Chinese adults. Our study answers two questions: How concentrations of ambient air pollutants are associated with HRQoL among older adults in China and, second, what are the possible mechanisms through which ambient air pollution affects HRQoL. From the 2018 National Health Service Survey, we sampled 5717 aged 65 years or older residents for the eastern province of Shandong, China. Data on individual exposures to PM_2.5 and PM₁₀ (particulate matter with diameter less than or equal to 2.5 μm and 10 μm) and sulfur dioxide (SO₂) were collected from the ChinaHighAirPollutants (CHAP) datasets. Mixed-effects Tobit regression models and mixed-effects ordered Probit regression models were employed to examine the associations of long-term exposure to ambient air pollution with the European Quality of Life 5 Dimensions 3 Level Version (EQ-5D-3L) scale comprising mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Socioeconomic, demographic and behavioral factors relating to HRQoL were also examined. The results show that for each 1 μg/m³ increase, EQ-5D-3L scores fell 0.002 for PM_2.5; 0.001 for PM₁₀ and 0.002 for SO₂. Long term exposure to PM_2.5, PM₁₀ and SO₂ were also associated with increased prevalence of pain/discomfort and anxiety/depression. The reduced HRQoL effects of ambient air pollution were exacerbated by higher socioeconomic status (affluent, urban and higher level of education). Our findings suggested that HRQoL of older Chinese adults was not only associated with demographic, socioeconomic, and health-related factors, but also negatively correlated with air pollution, especially through increased pain/discomfort and anxiety/depression. The paper proposes policy recommendations.

The interactive effects of extreme temperatures and PM2.5 pollution on mortalities in Jiangsu Province, China

Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM2.5 pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM2.5 pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.

Exposure to ambient air pollution with depressive symptoms and anxiety symptoms among adolescents: A national population-based study in China

BACKGROUND

Air pollution threatens adolescents' physical health and adversely affects adolescents' mental health. Previous studies mostly focused on the effects of air pollution on physical health, but there were few studies on the effects of air pollution on mental health.

METHODS

We collected scores of depressive symptoms and anxiety symptoms from 15,331 adolescents from 43 schools in eleven provinces in September and November 2017. The data on air pollution comes from the China High Air Pollutants dataset, which included concentrations of particulate matter with diameters of ≤1.0 μm (PM₁), diameters of ≤2.5 μm (PM_2.5), and diameters of ≤10 μm (PM₁₀), as well as nitrogen dioxide (NO₂). The associations between air pollution and depressive and anxiety symptoms among adolescents were estimated using generalized linear mixed models.

RESULTS

Depressive and anxiety symptoms among Chinese adolescents were 16% and 32%, respectively. In the adjusted model, an interquartile range (IQR) increase from PM_2.5 was associated with the odds of anxiety symptoms [odds ratio (OR) = 1.01; 95% confidence interval (CI): 1.00, 1.01, P = 0.002]. Also, an IQR increase in PM₁₀ was significantly associated with the odds of anxiety symptoms (OR = 1.01; 95% CI: 1.00, 1.01, P = 0.029). Compared with the lowest quartile, the adjusted OR of anxiety symptoms for the highest quartile of PM_2.5 and PM₁₀ were 1.29 (1.15, 1.44) and 1.23 (1.06, 1.42), respectively. In addition, the association between PM_2.5 and depressive symptoms was significant. The robustness of the results was also confirmed by stratification and sensitivity analyses.

CONCLUSIONS

Exposure values for airborne particulate matter were associated with depressive symptoms and anxiety symptoms in adolescents, particularly for PM_2.5 and PM₁₀ with anxiety symptoms among adolescents.

Ambient Air Pollution and All-Cause and Cause-Specific Mortality in an Analysis of Asian Cohorts

INTRODUCTION

Much of what is currently known about the adverse effects of ambient air pollution comes from studies conducted in high-income regions, with relatively low air pollution levels. The aim of the current project is to examine the relationship between exposure to ambient air pollution (as predicted from satellite-based models) and all-cause and cause-specific mortality in several Asian cohorts.

METHODS

Cohorts were recruited from the Asia Cohort Consortium (ACC). The geocoded residences of participants were assigned levels of ambient particulate material with aerodynamic diameter of 2.5 μm or less (PM2.5) and nitrogen dioxide (NO2) utilizing global satellite-derived models and assigned for the year of enrollment (or closest available year). The association between ambient exposure and mortality was established with Cox proportional hazard models, after adjustment for common confounders. Both single- and two-pollutant models were generated. Model robustness was evaluated, and hazard ratios were calculated for each cohort separately and combined via random effect meta-analysis for pooled risk estimates.

RESULTS

Six cohort studies from the ACC participated: the Community-based Cancer Screening Program (CBCSCP, Taiwan), the Golestan Cohort Study (Iran), the Health Effects for Arsenic Longitudinal Study (HEALS, Bangladesh), the Japan Public Health Center-based Prospective Study (JPHC), the Korean Multi-center Cancer Cohort Study (KMCC), and the Mumbai Cohort Study (MCS, India). The cohorts represented over 340,000 participants.

Mean exposures to PM2.5 ranged from 8 to 58 μg/m3. Mean exposures to NO2 ranged from 7 to 23 ppb. For PM2.5, a positive, borderline nonsignificant relationship was observed between PM2.5 and cardiovascular mortality. Other relationships with PM2.5 tended toward the null in meta-analysis. For NO2, an overall positive relationship was observed between exposure to NO2 and all cancers and lung cancer. A borderline association between NO2 and nonmalignant lung disease was also observed. The findings within individual cohorts remained consistent across a variety of subgroups and alternative analyses, including two-pollutant models.

CONCLUSIONS

In a pooled examination of cohort studies across Asia, ambient PM2.5 exposure appears to be associated with an increased risk of cardiovascular mortality and ambient NO2 exposure is associated with an increased cancer (and lung cancer) mortality. This project has shown that satellite-derived models of pollution can be used in examinations of mortality risk in areas with either incomplete or missing air pollution monitoring.

Economic and racial disparities of the weather impact on air quality in Brazil

Several studies have quantified the air pollution exposure disparities across racial and income groups. However, there is still a lack of investigations assessing disparities related to the impacts of weather on air pollution, which could indicate target air pollution reduction strategies under different climate scenarios. Our study aims to address this gap by estimating the economic and racial disparities of the weather impact on air quality in Brazil between 2003 and 2018. First, we used a generalized additive approach to estimate the weather-related changes in PM_2.5. This framework derived "weather penalty", which a positive penalty suggests that an increase in PM_2.5 was associated with long-term weather changes in the study period. Then, we estimated the population-weighted weather penalty for racial and income groups. Average penalty for the White population (the most-exposed group) was 31% higher than that of the Pardo population (the least-exposed group, mainly people of light brown skin color) in Brazil. In the stratification analysis by region, the Midwest and South were the regions where the black population was the most-exposed group. For the income group, our results indicate that the high-income population group was the most-exposed group in all analyses, including the national and the regional analyses. These findings are somewhat surprising, as previous studies have shown that minority and low-income populations tend to be more exposed to air pollution, than white and higher-income populations. However, our study suggests that disparities in exposure to air pollution may be more complex and nuanced than previously thought. Further research is needed to better understand the underlying drivers of these environmental disparities, and to develop targeted interventions to reduce exposures.

Premature mortality attributable to NO2 exposure in cities and the role of built environment: A global analysis

BACKGROUND

Environmental risks accumulate in cities, including polluted air and health disparities, but these risks can be reduced through scientific city planning. The purpose of this study was to investigate the global burden of premature mortality attributable to NO₂ exposure in urban areas and the role of the built environment in this regard.

METHODS

An approach based on health impact assessment was used to estimate the premature mortality burdens associated with NO₂ exposure in 13,169 urban areas around the world using globally gridded NO₂ and population estimates, baseline mortality, and epidemiologically derived exposure-response functions. We used the most recent WHO recommended value (i.e.,10 μg/m³) as a counterfactual concentration. Finally, the relationship between the characteristics of the built environment at the city level and the burden of NO₂-related mortality was evaluated.

RESULTS

Worldwide, 549,715(95%CI: 276204-815,023) cases of death attributable to NO₂ exposure in urban areas could be prevented if compliance with the latest WHO guideline, accounting for 2.7 % (95%CI:1.4 %-4.0 %) of total mortalities in 2019. Across cities around the world, the age-standardized mortality rate (per 100,000 people) attributable to NO₂ exposure ranged from 51.3 (95%CI:25.8-76.0) in Central Asia to 3.4(95%CI: 1.7-5.1) in Oceania. Although there was a significant decrease in premature mortality attributable to NO₂ exposure globally, considerable regional heterogeneity exists, with cities in Central Asia and Andean Latin America in particular exhibiting an upward trend. Further, we discovered a positive association between population density and street connectivity with mortality attributable to NO₂. While the increase in green and blue space were significantly associated with a lower NO₂-associated mortality.

CONCLUSION

The findings of this study provided a comprehensive understanding of the premature mortality burden due to NO₂ in cities throughout the world and the role that urban planning policies can play in reducing the health burden associated with air pollution.

Socio-demographic characteristics and inequality in exposure to PM2.5: A case study in the Sichuan basin, China

The Chengyu Metropolitan Area (CYMA), located in the Sichuan Basin, is an unevenly developed region with high PM_2.5 concentrations and a population of approximately 100 million. Although exposure inequality in air pollution has received increasing concern, no related research has been carried out in the CYMA to date. In this work, we used the concentration index to assess inequality of PM_2.5 population-weighted exposure in the CYMA among different subgroups, including age, education, gender, occupation and GDP per capita in the city of residence. Our findings revealed that the non-disadvantaged subgroups (people aged 15-64, people with senior and higher education, people with high-income occupations and residents of cities with high GDP per capita) had a higher PM_2.5 exposure in the CYMA, with the concentration indices of -0.03 (95% CI: 0.064, -0.001), -0.14 (95% CI: 0.221, -0.059), -0.15 (95% CI: 0.238, -0.056) and -0.27 (95% CI: 0.556, 0.012), opposite to previous studies in developed countries such as the United States and France. In addition, exposure differences among cities were much larger than those among populations in the CYMA. These findings may benefit the government in identifying disproportionately exposed subgroups in developing regions, and suggest that related measures should initially be carried out for cities exposed to high PM_2.5 concentrations rather than for populations exposed to high PM_2.5 concentrations.

Accumulation of Black Carbon Particles in Placenta, Cord Blood, and Childhood Urine in Association with the Intestinal Microbiome Diversity and Composition in Four- to Six-Year-Old Children in the ENVIRONAGE Birth Cohort

BACKGROUND

The gut microbiome plays an essential role in human health. Despite the link between air pollution exposure and various diseases, its association with the gut microbiome during susceptible life periods remains scarce.

OBJECTIVES

In this study, we examined the association between black carbon particles quantified in prenatal and postnatal biological matrices and bacterial richness and diversity measures, and bacterial families.

METHODS

A total of 85 stool samples were collected from 4- to 6-y-old children enrolled in the ENVIRonmental influence ON early AGEing birth cohort. We performed 16S rRNA gene sequencing to calculate bacterial richness and diversity indices (Chao1 richness, Shannon diversity, and Simpson diversity) and the relative abundance of bacterial families. Black carbon particles were quantified via white light generation under femtosecond pulsed laser illumination in placental tissue and cord blood, employed as prenatal exposure biomarkers, and in urine, used as a post-natal exposure biomarker. We used robust multivariable-adjusted linear models to examine the associations between quantified black carbon loads and measures of richness (Chao1 index) and diversity (Shannon and Simpson indices), adjusting for parity, season of delivery, sequencing batch, age, sex, weight and height of the child, and maternal education. Additionally, we performed a differential relative abundance analysis of bacterial families with a correction for sampling fraction bias. Results are expressed as percentage difference for a doubling in black carbon loads with 95% confidence interval (CI).

RESULTS

Two diversity indices were negatively associated with placental black carbon [Shannon: -4.38% (95% CI: -8.31%, -0.28%); Simpson: -0.90% (95% CI: -1.76%, -0.04%)], cord blood black carbon [Shannon: -3.38% (95% CI: -5.66%, -0.84%); Simpson: -0.91 (95% CI: -1.66%, -0.16%)], and urinary black carbon [Shannon: -3.39% (95% CI: -5.77%, -0.94%); Simpson: -0.89% (95% CI: -1.37%, -0.40%)]. The explained variance of black carbon on the above indices varied from 6.1% to 16.6%. No statistically significant associations were found between black carbon load and the Chao1 richness index. After multiple testing correction, placental black carbon was negatively associated with relative abundance of the bacterial families Defluviitaleaceae and Marinifilaceae, and urinary black carbon with Christensenellaceae and Coriobacteriaceae; associations with cord blood black carbon were not statistically significant after correction.

CONCLUSION

Black carbon particles quantified in prenatal and postnatal biological matrices were associated with the composition and diversity of the childhood intestinal microbiome. These findings address the influential role of exposure to air pollution during pregnancy and early life in human health. https://doi.org/10.1289/EHP11257.

Acute and chronic maternal exposure to fine particulate matter and prelabor rupture of the fetal membranes: A nation-wide survey in China

BACKGROUND

Prelabor rupture of the fetal membranes (PROM) is a major contributor to adverse perinatal outcomes. Some epidemiologic studies explored the association between maternal PM_2.5 exposure and PROM but failed to treat the labor induction and prelabor cesarean section as censored observations.

OBJECTIVE

We aimed to evaluated whether acute and chronic maternal ambient PM_2.5 exposure may increase the risk of PROM in China.

METHODS

This study was based on the China Labor and Delivery Survey, a nationwide multicenter investigation. Included in the current analysis were 45,879 singleton spontaneous births in 96 hospitals in mainland China from 2015 to 2017. Outcomes were PROM, preterm PROM (<37 weeks' gestation) and term PROM (≥37 weeks' gestation). Daily concentration of PM_2.5 at 1 km spatial resolution was estimated by gap-filling model. Generalized linear mixed model and mixed effects Cox model were applied to assess the associations of acute (from 0 to 4 days before delivery) and chronic (average gestational and trimester-specific) ambient PM_2.5 exposure with outcomes, respectively.

RESULTS

Significant associations were found between acute PM_2.5 exposures (per interquartile range increase) and the risk of preterm PROM (OR = 1.11; 95 % CI: 1.03, 1.19 for PM_2.5 on delivery day; OR = 1.10; 95 % CI: 1.02, 1.18 for PM_2.5 1 day before delivery) but not for term PROM. An interquartile range increase in PM_2.5 during the second trimester was associated with elevated risks of PROM (HR = 1.14; 95 % CI: 1.07, 1.22), preterm PROM (HR = 1.22; 95 % CI: 1.02, 1.45) and term PROM (HR = 1.13; 95 % CI: 1.06, 1.22), respectively. Women who were less educated, obese, or gave birth in a cold season appeared to be more sensitive to ambient PM_2.5 exposure.

CONCLUSION

Our findings suggest that both acute and chronic maternal exposures to ambient PM_2.5 during pregnancy are risk factors for PROM.

Ca Minerals and Oral Bioavailability of Pb, Cd, and As from Indoor Dust in Mice: Mechanisms and Health Implications

BACKGROUND

Elevating dietary calcium (Ca) intake can reduce metal(loid)oral bioavailability. However, the ability of a range of Ca minerals to reduce oral bioavailability of lead (Pb), cadmium (Cd), and arsenic (As) from indoor dust remains unclear.

OBJECTIVES

This study evaluated the ability of Ca minerals to reduce Pb, Cd, and As oral bioavailability from indoor dust and associated mechanisms.

METHODS

A mouse bioassay was conducted to assess Pb, Cd, and As relative bioavailability (RBA) in three indoor dust samples, which were amended into mouse chow without and with addition of CaHPO4,  CaCO3, Ca gluconate, Ca lactate, Ca aspartate, and Ca citrate at 200-5,000μg/g Ca. The mRNA expression of Ca and phosphate (P) transporters involved in transcellular Pb, Cd and As transport in the duodenum of mice was quantified using real-time polymerase chain reaction. Serum 1,25-Dihydroxyvitamin D3 [1,25(OH)2D3], parathyroid hormone (PTH), and renal CYP27B1 activity controlling 1,25(OH)2D3 synthesis were measured using ELISA kits. Metal(loid) speciation in the feces of mice was characterized using X-ray absorption near-edge structure (XANES) spectroscopy.

RESULTS

In general, mice exposed to each of the Ca minerals exhibited lower Pb-, Cd-, and As-RBA for three dusts. However, RBAs with the different Ca minerals varied. Among minerals, mice fed dietary CaHPO4 did not exhibit lower duodenal mRNA expression of Ca transporters but did have the lowest Pb and Cd oral bioavailability at the highest Ca concentration (5,000μg/g Ca; 51%-95% and 52%-74% lower in comparison with the control). Lead phosphate precipitates (e.g., chloropyromorphite) were observed in feces of mice fed dietary CaHPO4. In comparison, mice fed organic Ca minerals (Ca gluconate, Ca lactate, Ca aspartate, and Ca citrate) had lower duodenal mRNA expression of Ca transporters, but Pb and Cd oral bioavailability was higher than in mice fed CaHPO4. In terms of As, mice fed Ca aspartate exhibited the lowest As oral bioavailability at the highest Ca concentration (5,000μg/g Ca; 41%-72% lower) and the lowest duodenal expression of P transporter (88% lower). The presence of aspartate was not associated with higher As solubility in the intestine.

DISCUSSION

Our study used a mouse model of exposure to household dust with various concentrations and species of Ca to determine whether different Ca minerals can reduce bioavailability of Pb, Cd, and As in mice and elucidate the mechanism(s) involved. This study can contribute to the practical application of optimal Ca minerals to protect humans from Pb, Cd, and As coexposure in the environment. https://doi.org/10.1289/EHP11730.

Location-specific strategies for eliminating US national racial-ethnic [Formula: see text] exposure inequality

Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.