Long-Term Association of Air Pollution and Hospital Admissions Among Medicare Participants Using a Doubly Robust Additive Model

Long-Term Exposure to Air Pollution and Risk of Acute Lower Respiratory Infections in the Danish Nurse Cohort

Rationale: Air pollution is a major risk factor for chronic cardiorespiratory diseases, affecting the immune and respiratory systems' functionality, but epidemiological evidence in respiratory infections remains sparse. Objectives: We aimed to assess the association of long-term exposure to ambient air pollution with the risk of developing new and recurrent acute lower respiratory infections (ALRIs), characterized by persistently severe symptoms necessitating hospital contact, and identify the potential susceptible populations by socioeconomic status, smoking, physical activity status, overweight, and comorbidity with chronic lung disease. Methods: We followed 23,912 female nurses from the Danish Nurse Cohort (age >44 yr) from baseline (1993 or 1999) until 2018 for incident and recurrent ALRIs defined by hospital contact (inpatient, outpatient, and emergency room) data from the National Patient Register. Residential annual mean concentrations of fine particulate matter, nitrogen dioxide (NO2), and black carbon were modeled using the Danish Eulerian Hemispheric Model/Urban Background Model/Air Geographic Information System. We used marginal Cox models with time-varying exposures to assess the association of 3-year running mean air pollution level with incident and recurrent ALRIs and examined effect modification by age, socioeconomic status, smoking, physical activity, body mass index, and comorbidity with asthma or chronic obstructive pulmonary disease (COPD). Results: During a 21.3-year mean follow-up, 4,746 ALRIs were observed, of which 2,553 were incident. We observed strong positive associations of all three pollutants with incident ALRIs, with hazard ratios and 95% confidence intervals of 1.19 (1.08-1.31) per 2.5 μg/m3 for fine particulate matter, 1.17 (1.11-1.24) per 8.0 μg/m3 for NO2, and 1.09 (1.05-1.12) per 0.3 μg/m3 for black carbon, and slightly stronger associations with recurrent ALRIs. Associations were strongest in patients with COPD and nurses with low physical activity. Conclusions: Long-term exposure to air pollution at low levels was associated with risks of new and recurrent ALRIs, with patients with COPD and physically inactive subjects most vulnerable.

Risk of stroke admission after long-term exposure to PM1: Evidence from a large cohort in South China

BACKGROUND

Limited attention has been paid to the health effects of long-term PM1 exposure on stroke admission. Current investigations exploring the long-term PM exposure effect are largely based on observational studies, and PM generally is not allocated randomly to participants. Using traditional regression models might confuse messaging and hinder policy recommendations for pollution control and disease prevention policies.

METHODS

We conducted a cohort study among 36,271 adults from one of the largest cities in China in 2015 and followed up through 2020. Hazard ratios of stroke admissions following long-term PM1 exposure were estimated via a causal inference approach, marginal structural time-varying Cox proportional hazard model, accounting for multiple confounders. Additionally, several sensitivity analyses and impact modification analyses were carried out.

RESULTS AND DISCUSSION

Associations with 1 μg/m3 increase in long-term PM1 were identified for total (HR, 1.079; 95 %CI, 1.012-1.151) and ischemic stroke admissions (HR, 1.092; 95 %CI, 1.018-1.171). The harmful associations varied with exposure duration, initially increasing and then decreasing. The 2-3 years cumulative exposure was associated with a 3.3-5.4 % raised risk for total stroke. For every 1 μg/m³ increase in long-term PM1 exposure, females exhibited a higher risk of both total and ischemic stroke (13 % and 16 %) than men (4 % and 5 %). Low-exposure individuals (whose annual PM1 concentrations were under the third quartile among the annual concentrations for all the participants) exhibited greater sensitivity to PM1 effects (total stroke: 1.079 vs. 1.107; ischemic stroke: 1.092 vs. 1.116). The results underline the importance of safeguarding low-exposed people in highly polluted areas and suggest that long-term PM1 exposure may increase stroke admission risk, warranting attention to vulnerable groups.

Air pollution accelerates the development of obesity and Alzheimer's disease: the role of leptin and inflammation - a mini-review

Air pollution is an urgent concern linked to numerous health problems in low- and middle-income countries, where 92% of air pollution-related deaths occur. Particulate matter 2.5 (PM2.5) is the most harmful component of air pollutants, increasing inflammation and changing gut microbiota, favoring obesity, type 2 diabetes, and Alzheimer's Disease (AD). PM2.5 contains lipopolysaccharides (LPS), which can activate the Toll-like receptor 4 (TLR4) signaling pathway. This pathway can lead to the release of pro-inflammatory markers, including interleukins, and suppressor of cytokine signaling-3 (SOCS3), which inhibits leptin action, a hormone that keeps the energy homeostasis. Leptin plays a role in preventing amyloid plaque deposition and hyperphosphorylation of tau-protein (p-tau), mechanisms involved in the neurodegeneration in AD. Approximately 50 million people worldwide are affected by dementia, with a significant proportion living in low-and middle-income countries. This number is expected to triple by 2050. This mini-review focuses on the potential impact of PM2.5 exposure on the TLR4 signaling pathway, its contribution to leptin resistance, and dysbiosis that exacerbates the link between obesity and AD.

Residential greenness and chronic obstructive pulmonary disease in a large cohort in southern China: Potential causal links, risk trajectories, and mediation pathways

INTRODUCTION

Residential greenness may influence COPD mortality, but the causal links, risk trajectories, and mediation pathways between them remain poorly understood.

OBJECTIVES

We aim to comprehensively identify the potential causal links, characterize the dynamic progression of hospitalization or posthospital risk, and quantify mediation effects between greenness and COPD.

METHODS

This study was conducted using a community-based cohort enrolling individuals aged ≥ 18 years in southern China from January 1, 2009 to December 31, 2015. Greenness was characterized by normalized difference vegetation index (NDVI) around participants' residential addresses. We applied doubly robust Cox proportional hazards model, multi-state model, and multiple mediation method, to investigate the potential causal links, risk trajectories among baseline, COPD hospitalization, first readmission due to COPD or COPD-related complications, and all-cause death, as well as the multiple mediation pathways (particulate matter [PM], temperature, body mass index [BMI] and physical activity) connecting greenness exposure to COPD mortality.

RESULTS

Our final analysis included 581,785 participants (52.52% female; average age: 48.36 [Standard Deviation (SD): 17.56]). Each interquartile range (IQR: 0.06) increase in NDVI was associated with a reduced COPD mortality risk, yielding a hazard ratio (HR) of 0.88 (95 % CI: 0.81, 0.96). Furthermore, we observed per IQR (0.04) increase in NDVI was inversely associated with the risk of multiple transitions (baseline - COPD hospitalization, baseline - death, and readmission - death risks), especially a declined risk of all-cause death after readmission (HR = 0.66 [95 %CI: 0.44, 0.99]). Within the observed association between greenness and COPD mortality, three mediators were identified, namely PM, temperature, and BMI (HR for the total indirect effect: 0.773 [95 % CI: 0.703, 0.851]), with PM showing the highest mediating effect.

CONCLUSIONS

Our findings revealed greenness may be a beneficial factor for COPD morbidity, prognosis, and mortality. This protective effect is primarily attributed to the reduction in PM concentration.

Associations of fine particulate matter with incident cardiovascular disease; comparing models using ZIP code-level and individual-level fine particulate matter and confounders

BACKGROUND

PM2.5 has been positively associated with cardiovascular disease (CVD) incidence. Most evidence has come from cohorts and administrative databases. Cohorts typically have extensive information on potential confounders and residential-level exposures. Administrative databases are usually more representative but typically lack information on potential confounders and often only have exposures at coarser geographies (e.g., ZIP code). The weaknesses in both types of studies have been criticized for potentially jeopardizing the validity of their findings for regulatory purposes.

METHODS

We followed 101,870 participants from the US-based Nurses' Health Study (2000-2016) and linked residential-level PM2.5 and individual-level confounders, and ZIP code-level PM2.5 and confounders. We used time-varying Cox proportional hazards models to examine associations with CVD incidence. We specified basic models (adjusted for individual-level age, race and calendar year), individual-level confounder models, and ZIP code-level confounder models.

RESULTS

Residential- and ZIP code-level PM2.5 were strongly correlated (Pearson r = 0.88). For residential-level PM2.5, the hazard ratio (HR, 95 % confidence interval) per 5 μg/m3 increase was 1.06 (1.01, 1.11) in the basic and 1.04 (0.99, 1.10) in the individual-level confounder model. For ZIP code-level PM2.5, the HR per 5 μg/m3 was 1.04 (0.99, 1.08) in the basic and 1.02 (0.97, 1.08) in the ZIP code-level confounder model.

CONCLUSION

We observed suggestive positive, but not statistically significant, associations between long-term PM2.5 and CVD incidence, regardless of the exposure or confounding model. Although differences were small, associations from models with individual-level confounders and residential-level PM2.5 were slightly stronger than associations from models with ZIP code-level confounders and PM2.5.

Could the association between ozone and arterial stiffness be modified by fish oil supplementation?

BACKGROUND

Arterial stiffness (AS) is an important predicting factor for cardiovascular disease. However, no epidemiological studies have ever explored the mediating role of biomarkers in the association between ozone and AS, nor weather fish oil modified such association.

METHODS

Study participants were drawn from the UK biobank, and a total of 95,699 middle-aged and older adults were included in this study. Ozone was obtained from Community Multiscale Air Quality (CMAQ) model matched to residential addresses, fish oil from self-reported intake, and arterial stiffness was based on device measurements. First, we applied a double robust approach to explore the association between ozone or fish oil intake and arterial stiffness, adjusting for potential confounders at the individual and regional levels. Then, how triglycerides, apolipoprotein B (Apo B)/apolipoprotein A (ApoA) and non-high-density lipoprotein cholesterol (Non-HDL-C) mediate the relationship between ozone and AS. Last, the modifying role of fish oil was further explored by stratified analysis.

RESULTS

The mean age of participants was 55 years; annual average ozone exposure was associated with ASI (beta:0.189 [95%CI: 0.146 to 0.233], P < 0.001), and compared to participants who did not consume fish oil, fish oil users had a lower ASI (beta: 0.061 [95%CI: -0.111 to -0.010], P = 0.016). The relationship between ozone exposure and AS was mediated by triglycerides, ApoB/ApoA, and Non-HDL-C with mediation proportions ranging from 10.90% to 18.30%. Stratified analysis showed lower estimates on the ozone-AS relationship in fish oil users (P = 0.011).

CONCLUSION

Ozone exposure was associated with higher levels of arterial stiffness, in contrast to fish oil consumption, which showed a protective association. The association between ozone exposure and arterial stiffness was partially mediated by some biomarkers. In the general population, fish oil consumption might provide protection against ozone-related AS.

Long-term PM1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China

Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.

Chronic inhalation of H2S in low concentration induces immunotoxicity and inflammatory effects in lung tissue of rats

Hydrogen sulfide (H2S) is a typical odour compound mainly causing respiratory and central nervous system symptoms. However, the immunotoxicity of inhaled H2S and the underlying mechanisms remain largely unknown. In this study, a low-dose inhalation exposure to H2S was arranged to observe inflammatory response and immunotoxicity in lung tissue of rats. Low concentrations of H2S exposure affected the immune level of pulmonary tissue and peripheral blood. Significant pathological changes in lung tissue in the exposure group were observed. At low concentration, H2S not only induced the upregulation of AQP-4 and MMP-9 expression but also stimulated immune responses, initiating various anti-inflammatory and inflammatory factors, altering tissue homeostatic environments. The TNF and chemokine signaling pathway played an important role which can promote the deterioration of pulmonary inflammatory processes and lead to lung injury and fibrosis. Excessive immune response causes an inflammatory effect and blood-gas barrier damage. These data will be of value in evaluating future occupational health risks and providing technical support for the further development of reliable, sensitive, and easy-to-use screening indicators of exposure injury.

Co-exposure to multiple air pollutants, genetic susceptibility, and the risk of myocardial infarction onset: a cohort analysis of the UK Biobank participants

AIMS

The relationship between the long-term joint exposure to ambient air pollution and incidence of myocardial infarction (MI) and modification by genetic susceptibility remain inconclusive.

METHODS AND RESULTS

We analysed 329 189 UK Biobank participants without MI at baseline. Exposure concentrations to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were obtained. Air pollution score assessing the joint exposure was calculated, and its association with MI was evaluated via Cox model under the P value aggregation framework. Genetic susceptibility to MI was evaluated by incorporating polygenic risk score (PRS) into models. Risk prediction models were also established. During a median follow-up of 13.4 years, 9993 participants developed MI. Per interquartile range increase of PM2.5, PM10, NO2, and NOx resulted in 74% [95% confidence intervals (CIs) 69%-79%], 67% (63%-72%), 46% (42%-49%), and 38% (35%-41%) higher risk of MI. Compared with the lowest quartile (Q1) of air pollution score, the multivariable adjusted hazard ratio (HR) (95%CIs) of Q4 (the highest cumulative air pollution) was 3.50 (3.29-3.72) for MI. Participants with the highest PRS and air pollution score possessed the highest risk of incident MI (HR = 4.88, 95%CIs 4.35-5.47). Integrating PRS, air pollution exposure, and traditional factors substantially improved risk prediction of MI.

CONCLUSION

Long-term joint exposure to air pollutants including PM2.5, PM10, NO2, and NOx is substantially associated with increased risk of MI. Genetic susceptibility to MI strengthens such adverse joint association. Air pollutions together with genetic and traditional factors enhance the accuracy of MI risk prediction.

Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM2.5 exposure and cardiovascular emergency department visits in Missouri

INTRODUCTION

Ambient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures of socioeconomic position (SEP) modify the relationship between PM2.5 exposure and CVDM in Missouri at the census-tract (CT) level.

METHODS

We use individual level Missouri emergency department (ED) admissions data (n=3 284 956), modelled PM2.5 data, and yearly CT data from 2012 to 2016 to conduct a two-stage analysis. Stage one uses a case-crossover approach with conditional logistic regression to establish the baseline risk of ED visits associated with IQR changes in PM2.5. In the second stage, we use multivariate metaregression to examine how CT-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM.

RESULTS

We find that overall, ambient PM2.5 exposure is associated with increased risk for CVDM. We test effect modification in statewide and urban CTs, and in the warm season only. Effect modification results suggest that among SEP measures, poverty is most consistently associated with increased risk for CVDM. For example, across Missouri, the highest poverty CTs are at an elevated risk for CVDM (OR=1.010 (95% CI 1.007 to 1.014)) compared with the lowest poverty CTs (OR=1.004 (95% CI 1.000 to 1.008)). Other SEP modifiers generally display an inconsistent or null effect.

CONCLUSION

Overall, we find some evidence that area-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM, and suggest that the relationship between air-pollution, area-level SEP and CVDM may be sensitive to spatial scale.

Long-term exposure to PM2.5 species and all-cause mortality among Medicare patients using mixtures analyses

BACKGROUND

The relationship between long-term exposure to PM2.5 and mortality is well-established; however, the role of individual species is less understood.

OBJECTIVES

In this study, we assess the overall effect of long-term exposure to PM2.5 as a mixture of species and identify the most harmful of those species while controlling for the others.

METHODS

We looked at changes in mortality among Medicare participants 65 years of age or older from 2000 to 2018 in response to changes in annual levels of 15 PM2.5 components, namely: organic carbon, elemental carbon, nickel, lead, zinc, sulfate, potassium, vanadium, nitrate, silicon, copper, iron, ammonium, calcium, and bromine. Data on exposure were derived from high-resolution, spatio-temporal models which were then aggregated to ZIP code. We used the rate of deaths in each ZIP code per year as the outcome of interest. Covariates included demographic, temperature, socioeconomic, and access-to-care variables. We used a mixtures approach, a weighted quantile sum, to analyze the joint effects of PM2.5 species on mortality. We further looked at the effects of the components when PM2.5 mass levels were at concentrations below 8 μg/m3, and effect modification by sex, race, Medicaid status, and Census division.

RESULTS

We found that for each decile increase in the levels of the PM2.5 mixture, the rate of all-cause mortality increased by 1.4% (95% CI: 1.3%-1.4%), the rate of cardiovascular mortality increased by 2.1% (95% CI: 2.0%-2.2%), and the rate of respiratory mortality increased by 1.7% (95% CI: 1.5%-1.9%). These effects estimates remained significant and slightly higher when we restricted to lower concentrations. The highest weights for harmful effects were due to organic carbon, nickel, zinc, sulfate, and vanadium.

CONCLUSIONS

Long-term exposure to PM2.5 species, as a mixture, increased the risk of all-cause, cardiovascular, and respiratory mortality.

Air pollution and human health: a phenome-wide association study

OBJECTIVES

To explore the associations of long-term exposure to air pollution with onset of all human health conditions.

DESIGN

Prospective phenome-wide association study.

SETTING

Denmark.

PARTICIPANTS

All Danish residents aged ≥30 years on 1 January 2000 were included (N=3 323 612). After exclusion of individuals with missing geocoded residential addresses, 3 111 988 participants were available for the statistical analyses.

MAIN OUTCOME MEASURE

First registered diagnosis of every health condition according to the International Classification of Diseases, 10th revision, from 2000 to 2017.

RESULTS

Long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were both positively associated with the onset of more than 700 health conditions (ie, >80% of the registered health conditions) after correction for multiple testing, while the remaining associations were inverse or insignificant. As regards the most common health conditions, PM2.5 and NO2 were strongest positively associated with chronic obstructive pulmonary disease (PM2.5: HR 1.06 (95% CI 1.05 to 1.07) per 1 IQR increase in exposure level; NO2: 1.14 (95% CI 1.12 to 1.15)), type 2 diabetes (PM2.5: 1.06 (95% CI 1.05 to 1.06); NO2: 1.12 (95% CI 1.10 to 1.13)) and ischaemic heart disease (PM2.5: 1.05 (95% CI 1.04 to 1.05); NO2: 1.11 (95% CI 1.09 to 1.12)). Furthermore, PM2.5 and NO2 were both positively associated with so far unexplored, but highly prevalent outcomes relevant to public health, including senile cataract, hearing loss and urinary tract infection.

CONCLUSIONS

The findings of this study suggest that air pollution has a more extensive impact on human health than previously known. However, as this study is the first of its kind to investigate the associations of long-term exposure to air pollution with onset of all human health conditions, further research is needed to replicate the study findings.

Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study

OBJECTIVE

To estimate exposure-response associations between chronic exposure to fine particulate matter (PM2.5) and risks of the first hospital admission for major cardiovascular disease (CVD) subtypes.

DESIGN

Population based cohort study.

SETTING

Contiguous US.

PARTICIPANTS

59 761 494 Medicare fee-for-service beneficiaries aged ≥65 years during 2000-16. Calibrated PM2.5 predictions were linked to each participant's residential zip code as proxy exposure measurements.

MAIN OUTCOME MEASURES

Risk of the first hospital admission during follow-up for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, valvular heart disease, thoracic and abdominal aortic aneurysms, or a composite of these CVD subtypes. A causal framework robust against confounding bias and bias arising from errors in exposure measurements was developed for exposure-response estimations.

RESULTS

Three year average PM2.5 exposure was associated with increased relative risks of first hospital admissions for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, and thoracic and abdominal aortic aneurysms. For composite CVD, the exposure-response curve showed monotonically increased risk associated with PM2.5: compared with exposures ≤5 µg/m3 (the World Health Organization air quality guideline), the relative risk at exposures between 9 and 10 µg/m3, which encompassed the US national average of 9.7 µg/m3 during the study period, was 1.29 (95% confidence interval 1.28 to 1.30). On an absolute scale, the risk of hospital admission for composite CVD increased from 2.59% with exposures ≤5 µg/m3 to 3.35% at exposures between 9 and 10 µg/m3. The effects persisted for at least three years after exposure to PM2.5. Age, education, accessibility to healthcare, and neighborhood deprivation level appeared to modify susceptibility to PM2.5.

CONCLUSIONS

The findings of this study suggest that no safe threshold exists for the chronic effect of PM2.5 on overall cardiovascular health. Substantial benefits could be attained through adherence to the WHO air quality guideline.

Weekly prenatal PM2.5 and NO2 exposures in preterm, early term, and full term infants: Decrements in birth weight and critical windows of susceptibility

BACKGROUND

Previous studies have observed associations between birth weight and prenatal air pollution exposure, but there is not consensus on timing of critical windows of susceptibility.

OBJECTIVE

We estimated the difference in birth weight among preterm, early term and full term births associated with weekly exposure to PM2.5 and NO2 throughout gestation.

METHODS

We included all singleton live births in the Lower Peninsula of Michigan (United States) between 2007 and 2012 occurring at or after 32 weeks gestational age (n = 497,897). Weekly ambient PM2.5 and NO2 concentrations were estimated at maternal residences using 1-km gridded data from ensemble-based models. We utilized a distributed lag nonlinear model to estimate the difference in birth weight associated with weekly exposures from the last menstrual period (week 0) through 31 weeks gestation for preterm births; through 36 weeks gestation for early term births; and through 38 weeks gestation for full term births.

RESULTS

In single-pollutant models, a 5 μg/m3 increase in PM2.5 exposure was associated with a reduction in birth weight among preterm births (-37.1 g [95% confidence interval [CI]: 60.8 g, -13.5 g]); early term births (-13.5 g [95% CI: 26.2 g, -0.67 g]); and full term births (-8.23 g [95% CI: 15.8 g, -0.68 g])]. In single-pollutant models, a 10 ppb increase in NO2 exposure was associated with a -11.7 g (95% CI: 14.46 g, -8.92 g) decrement in birth weight among full term births only. In models co-adjusted for PM2.5 and NO2, PM2.5 exposure was associated with reduced birth weight among preterm births (-36.9 g [95% CI: 61.9 g, -11.8 g]) and NO2 exposure was associated with reduced birth weight among full term births (-11.8 g [95% CI: 14.7 g, -8.94 g]). The largest decrements in birth weight were associated with PM2.5 exposure between approximately 10 and 26 weeks of pregnancy; for NO2 exposure, the largest decrements in birth weight in full term births were associated with exposure between weeks 6-18.

CONCLUSION

We observed the largest and most persistent adverse associations between PM2.5 exposure and birth weight in preterm infants, and between NO2 exposure and birth weight in full term infants. Exposure during the first half of pregnancy had a greater impact on birthweight.

Short-term air pollution exposure and mortality in Brazil: Investigating the susceptible population groups

This is the first study to examine the association between ambient air pollution (PM2.5, O3, and NO2) and mortality (in different population groups by sex and age) based on a nationwide death record across Brazil over a 15-year period (2003-2017). We used a time-series analytic approach with a distributed lag model. Our study population includes 2,872,084 records of deaths in Brazil between 2003 and 2017. Men accounted for a higher proportion of deaths, with 58% for all-cause mortality, 54% for respiratory mortality, and 52% for circulatory mortality. Most individuals were over 65 years of age. Our results suggest an association between air pollution and mortality in Brazil. The direction, statistical significance, and effect size of these associations varied considerably by type of air pollutant, region, and population group (sex and age group). In particular, the older population group (>65 years) was most affected. The national meta-analysis for the entire data set (without stratification by sex and age) showed that for every 10 μg/m3 increase in PM2.5 concentration, the risk of death from respiratory diseases increased by 2.93% (95%CI: 1.42; 4.43). For every 10 ppb increase in O3, there is a 2.21% (95%CI: 0.59; 3.83) increase in the risk of all-cause mortality for the group of all people between 46 and 65 years old, and a 3.53% (95%CI: 0.34; 6.72) increase in the risk of circulatory mortality for the group of women, all ages. For every 10 ppb increase in NO2, the risk of respiratory mortality increases by 17.56% (95%CI: 4.44; 30.64) and the risk of all-cause mortality by 5.63% (95%CI: 1.83; 9.44). The results of our study provide epidemiological evidence that air pollution is associated with a higher risk of cardiorespiratory mortality in Brazil. Given the lack of nationwide studies on air pollution in Brazil, our research is an important contribution to the local and international literature that can provide better support to policymakers to improve air quality and public health.

Short-term exposure to sulfur dioxide and daily mortality in Brazil: A nationwide time-series study between 2003-2017

Sulfur dioxide (SO2), despite its ubiquitousness, there is relatively less epidemiological evidence regarding the health risks associated with SO2 compared to other pollutants, especially in low-income countries where there are high levels of SO2 emissions. In this study, we estimated the association between ambient SO2 exposure and daily mortality in Brazil over a period of 15 years (2003-2017). We used an extension of the two-stage time-series design in a time-series analytic approach with a distributed lag model. The study population consisted of 2,872,084 death records, with a higher proportion of male deaths observed across all-cause mortality (58%). The majority of the individuals were aged above 65 years. The mean SO2 concentration across the study period was 1.5 μg/m³ (range: 0.0 to 71.0). The national meta-analysis for the whole dataset (without stratification by sex and age) showed an uncertain association, in which a 10 μg/m3 increase in daily SO2 was associated with an RR of mortality of 1.015 (95%CI: 0.992; 1.037). Robust associations were observed only for the subgroup analysis of people 46-65 years old [RR = 1.050 (95%CI: 1.004; 1.096)] and men 46-65 years old [RR = 1.064 (95%CI: 1.005; 1.122)]. We found moderate heterogeneity in the national analysis, with an I2 of 21% for the subgroup of people 46-65 years old. Excess mortality fraction for people between 46 and 65 years old attributable to per 10 μg/m3 increase in SO2 was 2.93% (95% eCI: 0.29%-6.78%). These results highlight the need for targeted air pollution control policies to reduce the health burden of SO2 exposure in Brazil. Further research is needed to fully understand the mechanisms behind the age-specific and regional effects of SO2 on mortality.

The mediation of the placenta on the association between maternal ambient temperature exposure and birth weight

Studies have indicated that exposure to low and high temperatures during pregnancy negatively affects fetal development. The placenta plays vital functions in fetal development and could also be impacted by suboptimal temperatures. However, whether the placenta mediates the association between suboptimal temperature and birth weight is unknown. Our study aims to evaluate the association between ambient temperature and birth weight as well as the mediation effect of the placenta. A prospective birth cohort study was conducted during 2017-2020 in Guangzhou, China (n = 3349 participants). We defined extreme temperature exposure during the whole pregnancy by using different thresholds, including low temperatures (< 25th, < 15th, < 10th, < 5th percentiles), and high temperatures (> 75th, > 85th, > 90th, > 95th percentiles). Three different approaches (generalized linear model, inverse probability weighting, and doubly robust model) were applied to estimate the effects of low/high temperatures on birth weight and placental indicators, including placental weight, placental volume, and placental-to-birth weight ratio (PFR), respectively. We observed that both low and high ambient temperatures during the whole pregnancy were associated with lower birth weight and negative changes in placental indicators. The estimated lower mean birth weight ranged from -158 g (95 % CI: -192 g, -123 g) to -363 g (95 % CI: -424 g, -301 g) for low temperatures and from -97 g (95 % CI: -135 g, -59 g) to -664 g (95 % CI: -742 g, -585 g) for high temperatures. In mediation analyses, placental weight mediated 28.79 % to 40.47 % and 48.22 % to 54.38 % of the association of low and high temperatures with birth weight, respectively. The findings suggest that placental weight may mediate the association between ambient temperature exposure and birth weight.

Long-Term Exposure to Air Pollution Below Regulatory Standards and Cardiovascular Diseases Among US Medicare Beneficiaries: A Double Negative Control Approach

Growing evidence suggests that long-term air pollution exposure is a risk factor for cardiovascular mortality and morbidity. However, few studies have investigated air pollution below current regulatory limits, and causal evidence is limited. We used a double negative control approach to examine the association between long-term exposure to air pollution at low concentrations and three major cardiovascular events among Medicare beneficiaries aged ≥ 65 years across the contiguous United States between 2000 and 2016. We derived ZIP code-level estimates of ambient fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and warm-season ozone (O 3 ) from high-resolution spatiotemporal models. The outcomes of interest were hospitalizations for stroke, heart failure (HF), and atrial fibrillation and flutter (AF). The analyses were restricted to areas with consistently low pollutant levels on an annual basis (PM 2.5 <10 µg/m³, NO 2  < 45 or 40 ppb, warm-season O 3  < 45 or 40 ppb). For each 1 µg/m 3 increase in PM 2.5 , the hospitalization rates increased by 2.25% (95% confidence interval (CI): 1.96%, 2.54%) for stroke and 3.14% (95% CI: 2.80%, 3.94%) for HF. Each ppb increase in NO 2 increased hospitalization rates for stroke, HF, and AF by 0.28% (95% CI: 0.25%, 0.31%), 0.56% (95% CI: 0.52%, 0.60%), and 0.45% (95% CI: 0.41%, 0.49%), respectively. For each ppb increase in warm-season O 3 , there was a 0.32% (95% CI: 0.21%, 0.44%) increase in hospitalization rate for stroke. The associations for NO 2 and warm-season O 3 became stronger under a more restrictive upper threshold. Using an approach robust to omitted confounders, we concluded that long-term exposure to low-level PM 2.5 , NO 2 , and warm-season O 3 was associated with increased risks of cardiovascular diseases in the US elderly. Stricter national air quality standards should be considered.

Long-term association of air pollution and incidence of lung cancer among older Americans: A national study in the Medicare cohort

BACKGROUND

Despite strong evidence of the association of fine particulate matter (PM2.5) exposure with an increased risk of lung cancer mortality, few studies had investigated associations of multiple pollutants simultaneously, or with incidence, or using causal methods. Disparities were also understudied.

OBJECTIVES

We investigated long-term effects of PM2.5, nitrogen dioxide (NO2), warm-season ozone, and particle radioactivity (PR) exposures on lung cancer incidence in a nationwide cohort.

METHODS

We conducted a cohort study with Medicare beneficiaries (aged ≥ 65 years) continuously enrolled in the fee-for-service program in the contiguous US from 2001 to 2016. Air pollution exposure was averaged across three years and assigned based on ZIP code of residence. We fitted Cox proportional hazards models to estimate the hazard ratio (HR) for lung cancer incidence, adjusted for individual- and neighborhood-level confounders. As a sensitivity analysis, we evaluated the causal relationships using inverse probability weights. We further assessed effect modifications by individual- and neighborhood-level covariates.

RESULTS

We identified 166,860 lung cancer cases of 12,429,951 studied beneficiaries. In the multi-pollutant model, PM2.5 and NO2 exposures were statistically significantly associated with increased lung cancer incidence, while PR was marginally significantly associated. Specifically, the HR was 1.008 (95% confidence interval [CI]: 1.005, 1.011) per 1-μg/m3 increase in PM2.5, 1.013 (95% CI: 1.012, 1.013) per 1-ppb increase in NO2, and 1.005 (0.999, 1.012) per 1-mBq/m3 increase in PR. At low exposure levels, all pollutants were associated with increased lung cancer incidence. Men, older individuals, Blacks, and residents of low-income neighborhoods experienced larger effects of PM2.5 and PR.

DISCUSSION

Long-term PM2.5, NO2, and PR exposures were independently associated with increased lung cancer incidence among the national elderly population. Low-exposure analysis indicated that current national standards for PM2.5 and NO2 were not restrictive enough to protect public health, underscoring the need for more stringent air quality regulations.

Exposure to urban nanoparticles at low PM[Formula: see text] concentrations as a source of oxidative stress and inflammation

Exposures to fine particulate matter (PM[Formula: see text]) have been associated with health impacts, but the understanding of the PM[Formula: see text] concentration-response (PM[Formula: see text]-CR) relationships, especially at low PM[Formula: see text], remains incomplete. Here, we present novel data using a methodology to mimic lung exposure to ambient air (2[Formula: see text] 60 [Formula: see text]g m[Formula: see text]), with minimized sampling artifacts for nanoparticles. A reference model (Air Liquid Interface cultures of human bronchial epithelial cells, BEAS-2B) was used for aerosol exposure. Non-linearities observed in PM[Formula: see text]-CR curves are interpreted as a result of the interplay between the aerosol total oxidative potential (OP[Formula: see text]) and its distribution across particle size (d[Formula: see text]). A d[Formula: see text]-dependent condensation sink (CS) is assessed together with the distribution with d[Formula: see text] of reactive species . Urban ambient aerosol high in OP[Formula: see text], as indicated by the DTT assay, with (possibly copper-containing) nanoparticles, shows higher pro-inflammatory and oxidative responses, this occurring at lower PM[Formula: see text] concentrations (< 5 [Formula: see text]g m[Formula: see text]). Among the implications of this work, there are recommendations for global efforts to go toward the refinement of actual air quality standards with metrics considering the distribution of OP[Formula: see text] with d[Formula: see text] also at relatively low PM[Formula: see text].

Is COPD mortality in South China causally linked to the long-term PM1 exposure? Evidence from a large community-based cohort

BACKGROUND

Long-term ambient particulate matter (PM) exposure has been found associated with chronic obstructive pulmonary disease (COPD) mortality in an increasing body of research. However, limited evidence was available on the potential causal links between PM1 and COPD mortality, especially in highly exposed areas.

OBJECTIVES

To examine the COPD mortality risk following long-term ambient PM1 exposure in south China.

METHODS

The cohort included 580,757 participants recruited during 2009-2015. Satellite-based annual concentrations of PM1 were estimated at a spatial resolution of 1 km × 1 km and assigned to each participant based on their residential addresses. We analyzed the potential causal links between time-varying PM1 exposure and COPD mortality using marginal structural cox models within causal frameworks. Stratified analyses were also performed to identify the potential susceptible groups.

RESULTS

The annual average PM1 concentration continuously decreased over time. After adjusting for confounders, each 1 μg/m3 increase in PM1 concentration corresponded to an 8.1 % (95% confidence interval: 6.4-9.9 %) increment in the risk of COPD mortality. The impact of PM1 was more pronounced among the elderly and those with low exercise frequency, with a 1.9-6.9 % higher risk than their counterparts. We further observed a 0.1-9.7 % greater risk among those who lived in lower greenness settings. Additionally, we observed higher effect estimates in participants with long-term low PM1 exposure compared to the general population.

CONCLUSIONS

COPD mortality risk significantly increased following long term ambient PM1 exposure, particularly among groups with certain demographics or long-term low exposure.

Retrospective cohort study investigating synergism of air pollution and corticosteroid exposure in promoting cardiovascular and thromboembolic events in older adults

OBJECTIVE

To evaluate the synergistic effects created by fine particulate matter (PM2.5) and corticosteroid use on hospitalisation and mortality in older adults at high risk for cardiovascular thromboembolic events (CTEs).

DESIGN AND SETTING

A retrospective cohort study using a US nationwide administrative healthcare claims database.

PARTICIPANTS

A 50% random sample of participants with high-risk conditions for CTE from the 2008-2016 Medicare Fee-for-Service population.

EXPOSURES

Corticosteroid therapy and seasonal-average PM2.5.

MAIN OUTCOME MEASURES

Incidences of myocardial infarction or acute coronary syndrome (MI/ACS), ischaemic stroke or transient ischaemic attack, heart failure (HF), venous thromboembolism, atrial fibrillation and all-cause mortality. We assessed additive interactions between PM2.5 and corticosteroids using estimates of the relative excess risk due to interaction (RERI) obtained using marginal structural models for causal inference.

RESULTS

Among the 1 936 786 individuals in the high CTE risk cohort (mean age 76.8, 40.0% male, 87.4% white), the mean PM2.5 exposure level was 8.3±2.4 µg/m3 and 37.7% had at least one prescription for a systemic corticosteroid during follow-up. For all outcomes, we observed increases in risk associated with corticosteroid use and with increasing PM2.5 exposure. PM2.5 demonstrated a non-linear relationship with some outcomes. We also observed evidence of an interaction existing between corticosteroid use and PM2.5 for some CTEs. For an increase in PM2.5 from 8 μg/m3 to 12 μg/m3 (a policy-relevant change), the RERI of corticosteroid use and PM2.5 was significant for HF (15.6%, 95% CI 4.0%, 27.3%). Increasing PM2.5 from 5 μg/m3 to 10 μg/m3 yielded significant RERIs for incidences of HF (32.4; 95% CI 14.9%, 49.9%) and MI/ACSs (29.8%; 95% CI 5.5%, 54.0%).

CONCLUSION

PM2.5 and systemic corticosteroid use were independently associated with increases in CTE hospitalisations. We also found evidence of significant additive interactions between the two exposures for HF and MI/ACSs suggesting synergy between these two exposures.

Effects of low-level air pollution exposures on hospital admission for myocardial infarction using multiple causal models

Myocardial infarctions have been associated with PM2.5, and more recently with NO2 and O3, however counterfactual designs have been lacking and argument continues over the extent of confounding control. Here we introduce a doubly robust, counterfactual-based approach that deals with nonlinearity and interactions in associations between confounders and both outcome and exposure, as well as a double negative controls approach that capture omitted confounders. We used data from over 4 million admissions for myocardial infarction in the US Medicare population between 2000 and 2016 and linked them by ZIP code of residence to high resolution predictions of annual PM2.5, NO2, and O3. We computed the counts of admissions for each ZIP code-year. In the doubly robust approach, we divided each pollutant into deciles, and for each decile, we fitted a gradient boosting machine model to estimate the effects of covariates, including the co-pollutants, on the counts. We used these models to predict, for all ZIP code-years, the expected counts had everyone be exposed in that decile. We also estimated the probability of being in that decile given all covariates, again with a gradient boosting machine, and used inverse probability weights to compute the weighted average rate of MI admission in each decile. In the negative control approach, for each pollutant, we fitted a quasi-Poisson model to estimate the exposure effect, adjusting for covariates including the co-pollutants, and negative exposure and outcome controls to control for unmeasured confounding. Each 1-μg/m3 increase in annual PM2.5 increased the admission for MI by 1.37 cases per 10,000 person-years (95% CI: 1.20, 1.54) in the doubly robust approach, and by 0.69 cases (95% CI 0.60, 0.78) using the negative control approach. Elevated risks were seen even below annual PM2.5 level of 8 μg/m3. Results for NO2 and O3 were inconsistent.

Air Pollution and Cardiovascular and Thromboembolic Events in Older Adults With High-Risk Conditions

Little epidemiologic research has focused on pollution-related risks in medically vulnerable or marginalized groups. Using a nationwide 50% random sample of 2008-2016 Medicare Part D-eligible fee-for-service participants in the United States, we identified a cohort with high-risk conditions for cardiovascular and thromboembolic events (CTEs) and linked individuals with seasonal average zip-code-level concentrations of fine particulate matter (particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5)). We assessed the relationship between seasonal PM2.5 exposure and hospitalization for each of 7 CTE-related causes using history-adjusted marginal structural models with adjustment for individual demographic and neighborhood socioeconomic variables, as well as baseline comorbidity, health behaviors, and health-service measures. We examined effect modification across geographically and demographically defined subgroups. The cohort included 1,934,453 individuals with high-risk conditions (mean age = 77 years; 60% female, 87% White). A 1-μg/m3 increase in PM2.5 exposure was significantly associated with increased risk of 6 out of 7 types of CTE hospitalization. Strong increases were observed for transient ischemic attack (hazard ratio (HR) = 1.039, 95% confidence interval (CI): 1.034, 1.044), venous thromboembolism (HR = 1.031, 95% CI: 1.027, 1.035), and heart failure (HR = 1.019, 95% CI: 1.017, 1.020). Asian Americans were found to be particularly susceptible to thromboembolic effects of PM2.5 (venous thromboembolism: HR = 1.063, 95% CI: 1.021, 1.106), while Native Americans were most vulnerable to cerebrovascular effects (transient ischemic attack: HR = 1.093, 95% CI: 1.030, 1.161).

Intermediate and long-term exposure to air pollution and temperature and the extracellular microRNA profile of participants in the normative aging study (NAS)

BACKGROUND

The molecular effects of intermediate and long-term exposure to air pollution and temperature, such as those on extracellular microRNA (ex-miRNA) are not well understood but may have clinical consequences.

OBJECTIVES

To assess the association between exposure to ambient air pollution and temperature and ex-miRNA profiles.

METHODS

Our study population consisted of 734 participants in the Normative Aging Study (NAS) between 1999 and 2015. We used high-resolution models to estimate four-week, eight-week, twelve-week, six-month, and one-year moving averages of PM2.5, O3, NO2, and ambient temperature based on geo-coded residential addresses. The outcome of interest was the extracellular microRNA (ex-miRNA) profile of each participant over time. We used a longitudinal quantile regression approach to estimate the association between the exposures and each ex-miRNA. Results were corrected for multiple comparisons and ex-miRNAs that were still significantly associated with the exposures were further analyzed using KEGG pathway analysis and Ingenuity Pathway Analysis.

RESULTS

We found 151 significant associations between levels of PM2.5, O3, NO2, and ambient temperature and 82 unique ex-miRNAs across multiple quantiles. Most of the significant results were associations with intermediate-term exposure to O3, long-term exposure to PM2.5, and both intermediate and long-term exposure to ambient temperature. The exposures were most often associated with the 75th and 90th percentile of the outcomes. Pathway analyses of significant ex-miRNAs revealed their involvement in biological pathways involving cell function and communication as well as clinical diseases such as cardiovascular disease, respiratory disease, and neurological disease.

CONCLUSION

Our results show that intermediate and long-term exposure to all our exposures of interest were associated with changes in the ex-miRNA profile of study participants. Further studies on environmental risk factors and ex-miRNAs are warranted.

Short-term effects of individual exposure to PM2.5 on hospital admissions for myocardial infarction and stroke: a population-based case-crossover study in Guangzhou, China

Some studies have investigated the effects of PM_2.5 on cardiovascular diseases based on the population-average exposure data from several monitoring stations. No one has explored the short-term effect of PM_2.5 on cardiovascular hospitalizations using individual-level exposure data. We assessed the short-term effects of individual exposure to PM_2.5 on hospitalizations for myocardial infarction (MI) and stroke in Guangzhou, China, during 2014-2019. The population-based data on cardio-cerebrovascular events were provided by Guangzhou Center for Disease Control and Prevention. Average annual percent changes (AAPCs) were used to describe trends in the hospitalization rates of MI and stroke. The conditional logistic regression model with a time-stratified case-crossover design was applied to estimate the effects of satellite-retrieved PM_2.5 with 1-km resolution as individual-level exposure. Furthermore, we performed stratified analyses by demographic characteristics and season. There were 28,346 cases of MI, 188,611, and 36,850 cases of ischemic stroke (IS) and hemorrhagic stroke (HS), respectively, with an annual average hospitalization rate of 37.2, 247, and 48.4 per 100,000 people. Over the six-year study period, significant increasing trends in the hospitalization rates were observed with AAPCs of 12.3% (95% confidence interval [CI]: 7.24%, 17.6%), 13.1% (95% CI: 9.54%, 16.7%), and 9.57% (95% CI: 6.27%, 13.0%) for MI, IS, and HS, respectively. A 10 μg/m³ increase in PM_2.5 was associated with an increase of 1.15% (95% CI: 0.308%, 1.99%) in MI hospitalization and 1.29% (95% CI: 0.882%, 1.70%) in IS hospitalization. A PM_2.5-associated reduction of 1.17% (95% CI: 0.298%, 2.03%) was found for HS hospitalization. The impact of PM_2.5 was greater in males than in females for MI hospitalization, and greater effects were observed in the elderly (≥ 65 years) and in cold seasons for IS hospitalization. Our study added important evidence on the adverse effect of PM_2.5 based on satellite-retrieved individual-level exposure data.

Association Between the Incidence of Hospitalizations for Acute Cardiovascular Events, Weather, and Air Pollution

Background

The incidence of hospitalizations for cardiovascular events has been associated with specific weather conditions and air pollution. A comprehensive model including the interactions between various environmental factors remains to be developed.

Objectives

The purpose of this study was to develop a comprehensive model of the association between weather patterns and the incidence of cardiovascular events and use this model to forecast near-term spatiotemporal risk.

Methods

We present a spatiotemporal analysis of the association between atmospheric data and the incidence rate of hospital admissions related to heart failure (922,132 episodes), myocardial infarction (521,988 episodes), and ischemic stroke (263,529 episodes) in ∼24 million people in Canada between 2007 and 2017. Our hierarchical Bayesian model captured the spatiotemporal distribution of hospitalizations and identified weather and air pollution-related factors that could partially explain fluctuations in incidence.

Results

Models that included weather and air pollution variables outperformed models without those covariates for most event types. Our results suggest that environmental factors may interact in complex ways on human physiology. The impact of environmental factors was magnified with increasing age. The weather and air pollution variables included in our models were predictive of the future incidence of heart failure, myocardial infarction, and ischemic strokes.

Conclusions

The increasing importance of environmental factors on cardiovascular events with increasing age raises the need for the development of educational materials for older patients to recognize environmental conditions where exacerbations are more likely. This model could be the basis of a forecasting system used for local, short-term clinical resource planning based on the anticipated incidence of events.

Source-Specific Air Pollution Including Ultrafine Particles and Risk of Myocardial Infarction: A Nationwide Cohort Study from Denmark

BACKGROUND

Air pollution is negatively associated with cardiovascular health. Impediments to efficient regulation include lack of knowledge about which sources of air pollution contributes most to health burden and few studies on effects of the potentially more potent ultrafine particles (UFP).

OBJECTIVE

The authors aimed to investigate myocardial infarction (MI) morbidity and specific types and sources of air pollution.

METHODS

We identified all persons living in Denmark in the period 2005-2017, age >50 y and never diagnosed with MI. We quantified 5-y running time-weighted mean concentrations of air pollution at residencies, both total and apportioned to traffic and nontraffic sources. We evaluated particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5), <0.1μm (UFP), elemental carbon (EC), and nitrogen dioxide (NO2). We used Cox proportional hazards models, with adjustment for time-varying exposures, and personal and area-level demographic and socioeconomic covariates from high-quality administrative registers.

RESULTS

In this nationwide cohort of 1,964,702 persons (with 18 million person-years of follow-up and 71,285 cases of MI), UFP and PM2.5 were associated with increased risk of MI with hazard ratios (HRs) per interquartile range (IQR) of 1.040 [95% confidence interval (CI): 1.025, 1.055] and 1.053 (95% CI: 1.035, 1.071), respectively. HRs per IQR of UFP and PM2.5 from nontraffic sources were similar to the total (1.034 and 1.051), whereas HRs for UFP and PM2.5 from traffic sources were smaller (1.011 and 1.011). The HR for EC from traffic sources was 1.013 (95% CI: 1.003, 1.023). NO2 from nontraffic sources was associated with MI (HR=1.048; 95% CI: 1.034, 1.062) but not from traffic sources. In general, nontraffic sources contributed more to total air pollution levels than national traffic sources.

CONCLUSIONS

PM2.5 and UFP from traffic and nontraffic sources were associated with increased risk of MI, with nontraffic sources being the dominant source of exposure and morbidity. https://doi.org/10.1289/EHP10556.

Air pollution and stroke; effect modification by sociodemographic and environmental factors. A cohort study from Denmark

OBJECTIVES

Air pollution increases the risk of stroke, but the literature on identifying susceptible subgroups of populations is scarce and inconsistent. The aim of this study was to investigate if the association between air pollution and risk of stroke differed by sociodemographic factors, financial stress, comorbid conditions, and residential road traffic noise, population density and green space.

METHODS

We assessed long-term exposure to air pollution with ultrafine particles, PM_2.5, elemental carbon and NO₂ for a cohort of 1,971,246 Danes aged 50-85 years. During follow-up from 2005 to 2017, we identified 83,211 incident stroke cases. We used Cox proportional hazards model (relative risk) and Aalen additive hazards models (absolute risk) to estimate associations and confidence intervals (CI) between 5-year running means of air pollution at the residence and risk of stroke in population strata.

RESULTS

All four pollutants were associated with higher risk of stroke. The association between air pollution and stroke was strongest among individuals with comorbidities, with shorter education, lower income and being retired. The results also indicated stronger associations among individuals living in less populated areas, and with low noise levels and more green space around the residence. Estimates of absolute risk seemed better suited to detect such interactions than estimates of relative risk. For example for PM_2.5 the hazard ratio for stroke was 1.28 (95%CI: 1.22-1.34) and 1.26 (95%CI: 1.16-1.37) among those with mandatory and medium/long education respectively. The corresponding rate difference estimates per 100,000 person years were 568 (95%CI: 543-594) and 423(95%CI: 390-456) CONCLUSION: The associations between air pollution and risk of stroke was stronger among individuals of lower socioeconomic status or with pre-existing comorbid conditions. Absolute risk estimates were better suited to identify such effect modification.

Air pollution and myocardial infarction; effect modification by sociodemographic and environmental factors. A cohort study from Denmark

Air pollution is associated with increased risk of myocardial infarction (MI), but it is unresolved to what extent the association is modified by factors such as socioeconomic status, comorbidities, financial stress, residential green space, or road traffic noise. We formed a cohort of all (n = 1,964,702) Danes, aged 50-85 years, with 65,311 cases of MI during the followed-up period 2005-2017. For all participants we established residential five-year running average exposure to particulate matter <2.5  μm (PM_2.5), ultrafine particles (UFP, <0.1  μm), elemental carbon (EC) and nitrogen dioxide (NO₂). We evaluated risk in population strata, using Aalen additive hazards models to estimate absolute risk and Cox proportional hazards models to estimate relative risk of MI with 95% confidence intervals (CI). PM_2.5 and the other pollutant were associated with MI. Lower education and lower income were associated with higher absolute risks of MI from air pollution, whereas no clear effect modification was apparent for relative risk estimates. For example, 5 μg/m³ higher PM_2.5 was associated with HR for MI of 1.16 (95% CI: 1.10-1.22) among those with only mandatory education and 1.13 (95% CI: 1.03-1.24) among those with long education. The corresponding rate differences per 100,000 person years were 243 (95% CI: 216-271) and 358 (95% CI: 338-379), respectively. Higher level of comorbidity was consistently across all four pollutants associated with both higher absolute and relative risk of MI. In conclusion, people with comorbid conditions or of lower SES appeared more vulnerable to long-term exposure to air pollution and more cases of MI may be prevented by focused interventions in these groups.

Disparities in ambient nitrogen dioxide pollution in the United States

Average ambient concentrations of nitrogen dioxide (NO2), an important air pollutant, have declined in the United States since the enactment of the Clean Air Act. Despite evidence that NO2 disproportionately affects racial/ethnic minority groups, it remains unclear what drives the exposure disparities and how they have changed over time. Here, we provide evidence by integrating high-resolution (1 km × 1 km) ground-level NO2 estimates, sociodemographic information, and source-specific emission intensity and location for 217,740 block groups across the contiguous United States from 2000 to 2016. We show that racial/ethnic minorities are disproportionately exposed to higher levels of NO2 pollution compared with Whites across the United States and within major metropolitan areas. These inequities persisted over time and have worsened in many cases, despite a significant decrease in the national average NO2 concentration over the 17-y study period. Overall, traffic contributes the largest fraction of NO2 disparity. Contributions of other emission sources to exposure disparities vary by location. Our analyses offer insights into policies aimed at reducing air pollution exposure disparities among races/ethnicities and locations.

Potential causal links between long-term ambient particulate matter exposure and cardiovascular mortality: New evidence from a large community-based cohort in South China

BACKGROUND

Cardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited.

AIMS

We examined the potential causal links between PM exposure and the CVD mortality in South China.

METHODS

580,757 participants were recruited during 2009-2015 and followed up through 2020. Satellite-based annual concentrations of PM_2.5, PM₁₀, and PM_coarse (i.e., PM₁₀ - PM_2.5) at 1 km² spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality.

RESULTS

For overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 μg/m³ increase in the annual average concentration of PM_2.5, PM₁₀, and PM_coarse were 1.033 (1.028-1.037), 1.028 (1.024-1.032), and 1.022 (1.012-1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM_2.5 and PM₁₀. Significant association between PM_coarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM₁₀ concentrations below 70 μg/m³ were more vulnerable to PM_2.5-, PM₁₀- and PM_coarse-CVD mortality risks.

CONCLUSION

This large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.

Associations Between Long-Term Air Pollutant Exposure and 30-Day All-Cause Hospital Readmissions in US Patients With Stroke

BACKGROUND

Long-term exposure to air pollutants is associated with increased stroke incidence, morbidity, and mortality; however, research on the association of pollutant exposure with poststroke hospital readmissions is lacking.

METHODS

We assessed associations between average annual carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), particulate matter 2.5, and sulfur dioxide (SO2) exposure and 30-day all-cause hospital readmission in US fee-for-service Medicare beneficiaries age ≥65 years hospitalized for ischemic stroke in 2014 to 2015. We fit Cox models to assess 30-day readmissions as a function of these pollutants, adjusted for patient and hospital characteristics and ambient temperature. Analyses were then stratified by treating hospital performance on the Centers for Medicare and Medicaid Services risk-standardized 30-day poststroke all-cause readmission measure to determine if the results were independent of performance: low (Centers for Medicare and Medicaid Services rate for hospital <25th percentile of national rate), high (>75th percentile), and intermediate (all others).

RESULTS

Of 448 148 patients with stroke, 12.5% were readmitted within 30 days. Except for tropospheric NO2 (no national standard), average 2-year CO, O3, particulate matter 2.5, and SO2 values were below national limits. Each one SD increase in average annual CO, NO2, particulate matter 2.5, and SO2 exposure was associated with an adjusted 1.1% (95% CI, 0.4-1.9%), 3.6% (95% CI, 2.9%-4.4%), 1.2% (95% CI, 0.2%-2.3%), and 2.0% (95% CI, 1.1%-3.0%) increased risk of 30-day readmission, respectively, and O3 with a 0.7% (95% CI, 0.0%-1.5%) decrease. Associations between long-term air pollutant exposure and increased readmissions persisted across hospital performance categories.

CONCLUSIONS

Long-term air pollutant exposure below national limits was associated with increased 30-day readmissions after stroke, regardless of hospital performance category. Whether air quality improvements lead to reductions in poststroke readmissions requires further research.

Estimating a Causal Exposure Response Function with a Continuous Error-Prone Exposure: A Study of Fine Particulate Matter and All-Cause Mortality

Numerous studies have examined the associations between long-term exposure to fine particulate matter (PM2.5) and adverse health outcomes. Recently, many of these studies have begun to employ high-resolution predicted PM2.5 concentrations, which are subject to measurement error. Previous approaches for exposure measurement error correction have either been applied in non-causal settings or have only considered a categorical exposure. Moreover, most procedures have failed to account for uncertainty induced by error correction when fitting an exposure-response function (ERF). To remedy these deficiencies, we develop a multiple imputation framework that combines regression calibration and Bayesian techniques to estimate a causal ERF. We demonstrate how the output of the measurement error correction steps can be seamlessly integrated into a Bayesian additive regression trees (BART) estimator of the causal ERF. We also demonstrate how locally-weighted smoothing of the posterior samples from BART can be used to create a more accurate ERF estimate. Our proposed approach also properly propagates the exposure measurement error uncertainty to yield accurate standard error estimates. We assess the robustness of our proposed approach in an extensive simulation study. We then apply our methodology to estimate the effects of PM2.5 on all-cause mortality among Medicare enrollees in New England from 2000-2012.

Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study

Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-months ozone (O3) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 μg/m3 increase in PM2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO2, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O3. Both for NO2 and PM2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO2 ≤ 36 ppb, PM2.5 ≤ 8.2 μg/m3). Furthermore, associations remained in the restricted low-level cohorts. The O3-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM2.5 and NO2 are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.

Using Parametric g-Computation to Estimate the Effect of Long-Term Exposure to Air Pollution on Mortality Risk and Simulate the Benefits of Hypothetical Policies: The Canadian Community Health Survey Cohort (2005 to 2015)

BACKGROUND

Numerous epidemiological studies have documented the adverse health impact of long-term exposure to fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter (PM2.5)] on mortality even at relatively low levels. However, methodological challenges remain to consider potential regulatory intervention's complexity and provide actionable evidence on the predicted benefits of interventions. We propose the parametric g-computation as an alternative analytical approach to such challenges.

METHOD

We applied the parametric g-computation to estimate the cumulative risks of nonaccidental death under different hypothetical intervention strategies targeting long-term exposure to PM2.5 in the Canadian Community Health Survey cohort from 2005 to 2015. On both relative and absolute scales, we explored the benefits of hypothetical intervention strategies compared with the natural course that a) set the simulated exposure value at each follow-up year to a threshold value if exposure was above the threshold (8.8 μg/m3, 7.04 μg/m3, 5 μg/m3, and 4 μg/m3), and b) reduced the simulated exposure value by a percentage (5% and 10%) at each follow-up year. We used the 3-y average PM2.5 concentration with 1-y lag at the postal code of respondents' annual mailing addresses as their long-term exposure to PM2.5. We considered baseline and time-varying confounders, including demographics, behavior characteristics, income level, and neighborhood socioeconomic status. We also included the R syntax for reproducibility and replication.

RESULTS

All hypothetical intervention strategies explored led to lower 11-y cumulative mortality risks than the estimated value under the natural course without intervention, with the smallest reduction of 0.20 per 1,000 participants (95% CI: 0.06, 0.34) under the threshold of 8.8 μg/m3, and the largest reduction of 3.40 per 1,000 participants (95% CI: -0.23, 7.03) under the relative reduction of 10% per interval. The reductions in cumulative risk, or numbers of deaths that would have been prevented if the intervention was employed instead of maintaining the status quo, increased over time but flattened toward the end of the follow-up period. Estimates among those ≥65 years of age were greater with a similar pattern. Our estimates were robust to different model specifications.

DISCUSSION

We found evidence that any intervention further reducing the long-term exposure to PM2.5 would reduce the cumulative mortality risk, with greater benefits in the older population, even in a population already exposed to low levels of ambient PM2.5. The parametric g-computation used in this study provides flexibilities in simulating real-world interventions, accommodates time-varying exposure and confounders, and estimates adjusted survival curves with clearer interpretation and more information than a single hazard ratio, making it a valuable analytical alternative in air pollution epidemiological research. https://doi.org/10.1289/EHP11095.

Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study

Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and warm-months ozone (O₃) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 μg/m³ increase in PM_2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO₂, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O₃. Both for NO₂ and PM_2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO₂ ≤ 36 ppb, PM_2.5 ≤ 8.2 μg/m³). Furthermore, associations remained in the restricted low-level cohorts. The O₃-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM_2.5 and NO₂ are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.

Long-term Exposure to Ambient Air Pollutants and Increased Risk of Pneumonia in the UK Biobank

BACKGROUND

Short-term exposure to air pollution has been linked to pneumonia risk. However, evidence on the long-term effects of air pollution on pneumonia morbidity is scarce and inconsistent. We investigated the associations of long-term air pollutants exposure with pneumonia and explored the potential interactions with smoking.

RESEARCH QUESTION

Is long-term exposure to ambient air pollution associated with the risk of pneumonia, and does smoking modify the associations?

STUDY DESIGN AND METHODS

We analyzed data in 445,473 participants without pneumonia within 1 year before baseline from the UK Biobank. Annual average concentrations of particulate matter (particulate matter with a diameter < 2.5 μm [PM_2.5] and particulate matter with a diameter < 10 μm [PM₁₀]), nitrogen dioxide (NO₂), and nitrogen oxides (NO_x) were estimated using land-use regression models. Cox proportional hazards models were used to assess the associations between air pollutants and pneumonia incidence. Potential interactions between air pollution and smoking were examined on both additive and multiplicative scales.

RESULTS

The hazard ratios of pneumonia for each interquartile range increase in PM_2.5, PM₁₀, NO₂, and NO_x concentrations were 1.06 (95% CI, 1.04-1.08), 1.10 (95% CI, 1.08-1.12), 1.12 (95% CI, 1.10-1.15), and 1.06 (95% CI, 1.04-1.07), respectively. There were significant additive and multiplicative interactions between air pollution and smoking. Compared with never smokers with low air pollution exposure, ever smokers with high air pollution exposure had the highest pneumonia risk (PM_2.5: HR, 1.78; 95% CI, 1.67-1.90; PM₁₀: HR, 1.94; 95% CI, 1.82-2.06; NO₂: HR, 2.06; 95% CI, 1.93-2.21; NO_x: HR, 1.88; 95% CI, 1.76-2.00). The associations between air pollutants and pneumonia risk persisted in participants exposed to air pollutants concentrations meeting the European Union limits.

INTERPRETATION

Long-term exposure to air pollutants was associated with an increased risk of pneumonia, especially in smokers.

Effects of Air Pollution on the Health of Older Adults during Physical Activities: Mapping Review

Atmospheric pollutants present environmental threats to health and have been investigated in different environments, such as highways, squares, parks, and gyms. These environments are frequented by older adults, who are considered fragile to the harmful impacts of pollution present in the air. The aim was to analyze the state of the art on the effects of air pollution on the health of older adults during physical activities (PAs) through a mapping review. The search was performed in PubMed, Web of Science, Scopus, and Cinahl databases until June 2022. Of the 10,109 studies initially identified, 58 met the inclusion criteria. The most investigated health outcome was cardiovascular disease, followed by respiratory outcomes. Particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) were the most investigated pollutants. Of the 75 health outcomes investigated, in 29, air pollution had harmful effects on the health of the older adults during the practice of PA, more frequently in cardiovascular diseases. In 25 outcomes, the beneficial effects of PA to the health of the older adults remained, despite exposure to high and low concentrations of pollutants, most often in terms of mental disorders. We conclude that poor air quality is a harmful factor for the health of older adults during the practice of PAs, more frequently in cardiovascular and respiratory diseases. On the other hand, for mental-health-related outcomes (depression and cognition), in most studies, the beneficial effects of PA in older adults were maintained, even after exposure to pollutants.

Impact of air pollution on running performance

Air pollution exposures during training may impact race preformances. We aggregated data on 334 collegiate male track & field athletes from 46 universities across the United States over 2010-2014. Using distributed lag non-linear models, we analyzed the relationship between race time and PM2.5, ozone, and two versions of the Air Quality Index (AQI) exposures up to 21 days prior to the race. We observed a 12.8 (95% CI: 1.3, 24.2) second and 11.5 (95% CI: 0.8, 22.1) second increase in race times from 21 days of PM2.5 exposure (10.0 versus 5.0 μg/m3) and ozone exposure (54.9 versus 36.9 ppm), respectively. Exposure measured by the two-pollutant threshold (PM2.5 and ozone) AQI was not significantly associated with race time; however, the association for summed two-pollutant AQI (PM2.5 plus ozone) was similar to associations observed for the individual pollutants (12.4, 95% CI: 1.8, 23.0 s). Training and competing at elevated air pollution levels, even at exposures within AQI's good-to-moderate classifications, was associated with slower race times. This work provides an initial characterization of the effect of air pollution on running performance and a justification for why coaches should consider approaches to reduce air pollution exposures while training.

Association of Long-term Exposure to Air Pollution With Late-Life Depression in Older Adults in the US

IMPORTANCE

Emerging evidence has suggested harmful associations of air pollutants with neurodegenerative diseases among older adults. However, little is known about outcomes regarding late-life mental disorders, such as geriatric depression.

OBJECTIVE

To investigate if long-term exposure to air pollution is associated with increased risk of late-life depression diagnosis among older adults in the US.

DESIGN, SETTING, AND PARTICIPANTS

This population-based longitudinal cohort study consisted of US Medicare enrollees older than 64 years. Data were obtained from the US Centers for Medicare and Medicaid Services Chronic Conditions Warehouse. The participants were continuously enrolled in the Fee-for-Service program and both Medicare Part A and Part B. After the 5-year washout period at entry, a total of 8 907 422 unique individuals were covered over the study period of 2005 to 2016, who contributed to 1 526 690 late-onset depression diagnoses. Data analyses were performed between March 2022 and November 2022.

EXPOSURES

The exposures consisted of residential long-term exposure to fine particulate matter (PM2.5), measured in micrograms per cubic meter; nitrogen dioxide (NO2), measured in parts per billion; and ozone (O3), measured in parts per billion.

MAIN OUTCOMES AND MEASURES

Late-life depression diagnoses were identified via information from all available Medicare claims (ie, hospital inpatient, skilled nursing facility, home health agency, hospital outpatient, and physician visits). Date of the first occurrence was obtained. Hazard ratios and percentage change in risk were estimated via stratified Cox proportional hazards models accounting for climate coexposures, neighborhood greenness, socioeconomic conditions, health care access, and urbanicity level.

RESULTS

A total of 8 907 422 Medicare enrollees were included in this study with 56.8% being female individuals and 90.2% being White individuals. The mean (SD) age at entry (after washout period) was 73.7 (4.8) years. Each 5-unit increase in long-term mean exposure to PM2.5, NO2, and O3 was associated with an adjusted percentage increase in depression risk of 0.91% (95% CI, 0.02%-1.81%), 0.61% (95% CI, 0.31%- 0.92%), and 2.13% (95% CI, 1.63%-2.64%), respectively, based on a tripollutant model. Effect size heterogeneity was found among subpopulations by comorbidity condition and neighborhood contextual backgrounds.

CONCLUSIONS AND RELEVANCE

In this cohort study among US Medicare enrollees, harmful associations were observed between long-term exposure to air pollution and increased risk of late-life depression diagnosis.

Short-term air pollution exposure and hospital admissions for cardiorespiratory diseases in Brazil: A nationwide time-series study between 2008 and 2018

The established evidence associating air pollution with health is limited to populations from specific regions. Further large-scale studies in several regions worldwide are needed to support the literature to date and encourage national governments to act. Brazil is an example of these regions where little research has been performed on a large scale. To address this gap, we conducted a study looking at the relationship between daily PM_2.5, NO₂, and O₃, and hospital admissions for circulatory and respiratory diseases across Brazil between 2008 and 2018. A time-series analytic approach was applied with a distributed lag modeling framework. We used a generalized conditional quasi-Poisson regression model to estimate relative risks (RRs) of the association of each air pollutant with the hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. Our study population includes 23, 791, 093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. Our findings suggest significant associations of ambient air pollution (PM_2.5, NO₂, and O₃) with respiratory and circulatory hospital admissions in Brazil. The national meta-analysis for the whole population showed that for every increase of PM_2.5 by 10 μg/m³, there is a 3.28% (95%CI: 2.61; 3.94) increase in the risk of hospital admission for respiratory diseases. For O₃, we found positive associations only for some sub-group analyses by age and sex. For NO₂, our findings suggest that a 10 ppb increase in this pollutant, there was a 35.26% (95%CI: 24.07; 46.44) increase in the risk of hospital admission for respiratory diseases. This study may better support policymakers to improve the air quality and public health in Brazil.

Residential greenness and dyslipidemia risk: Dose-response relations and mediation through BMI and air pollution

BACKGROUND

Evidence on associations of residential greenness with dyslipidemia is limited, particularly regarding dose-response relations and mediation.

OBJECTIVES

To investigate associations between greenness and dyslipidemia, non-linear dose-response relationships and mediators.

METHODS

This cross-sectional study draws on the 2018 Fujian Behavior and Disease Surveillance (FBDS) cohort that used multi-stage stratified random sampling from the general population of Fujian Province, China. Participants with one or more abnormities in total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), or low-density lipoprotein cholesterol (LDL-C) were classified as having dyslipidemia. Residential greenness was operationalized as 3-year average of the normalized difference vegetation index (NDVI_500m) and enhanced vegetation index (EVI_500m). A doubly robust approach was used for effect quantification. Dose-response relations were studied with natural cubic splines. Mediation via physical activity (PA), body mass index (BMI), PM_2.5, PM₁₀, SO₂, and NO₂ was also examined.

RESULTS

Data from 43,183 participants were analyzed. Increases in NDVI_500m and EVI_500m residential greenness were associated with decreased dyslipidemia risk and improved blood lipids. Non-linear dose response relationships were discovered. Significant reduction of dyslipidemia risk was observed at levels of EVI_500m > 0.48 and NDVI_500m > 0.65. Joint mediation effects of PA, BMI, PM_2.5, PM₁₀, NO₂, and SO₂ on the associations of NDVI_500m and EVI_500m with dyslipidemia risk were 49.74% and 44.64%, respectively.

CONCLUSIONS

Increased residential exposure to greenness was associated with decreased risk of dyslipidemia. A non-linear dose-response relationship between greenness and dyslipidemia suggests that specific thresholds of greenness need to be reached in order to achieve effects. BMI, PM_2.5, and PM₁₀ partially mediated the association.

Real-World Trends in the Evaluation of Medical Products

There is a compelling need to evaluate the real-world health effects of medical products outside of tightly controlled preapproval clinical trials. This is done through pharmacoepidemiology, which is the study of the health effects of medical products (including drugs, biologicals, and medical devices and diagnostics) in populations, often using nonrandomized designs. Recent developments in pharmacoepidemiology span changes in the focus of research questions, research designs, data used, and statistical analysis methods. Developments in these areas are thought to improve the value of the evidence produced by such studies, and are prompting greater use of real-world evidence to inform clinical, regulatory, and reimbursement decisions.

Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China

BACKGROUND

The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM₁ which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas.

METHODS

A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM₁, PM_2.5, and PM₁₀ at 1 km² spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels.

RESULTS

37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m³ increase in PM₁, PM_2.5, and PM₁₀ concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM₁, PM_2.5, and PM₁₀ tend to be higher in the low-exposure group than in the general population.

CONCLUSIONS

We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM₁compared to large particles and among certain vulnerable subgroups.

Short-term air pollution and temperature exposure and changes in the extracellular microRNA profile of Normative Aging Study (NAS) participants

BACKGROUND

While the health effects of air pollution and temperature are widely studied, the molecular effects are poorly understood. Extracellular microRNAs (ex-miRNAs) have the potential to serve as diagnostic or prognostic biomarkers and/or to act as intercellular signaling molecules that mediate the effects of environmental exposures on health outcomes.

METHODS

We examined the relationship between short-term exposure to air pollution and ambient temperature and the ex-miRNA profiles of participants in the Normative Aging Study (NAS) from 1999 to 2015. Our exposures were defined as same-day, two-day, three-day, one-week, two-week, and three-week moving averages of PM2.5, NO2, O3, and temperature which were derived from high-resolution spatio-temporal models. The ex-miRNA profiles of the subjects were obtained during follow-up visits. We analyzed the data using a longitudinal quantile regression model adjusted for individual covariates, batch effects, and time trends. We adjusted for multiple comparisons using a false discovery rate (FDR) correction. Ex-miRNAs that were significantly associated with exposures were further investigated using pathway analyses.

RESULTS

We found that all the examined exposures were associated with changes in ex-miRNA profiles in our study, particularly PM2.5 which was responsible for most of the statistically significant results. We found 110 statistically significant exposure-outcome relationships that revealed associations with the levels of 52 unique ex-miRNAs. Pathway analyses showed these ex-miRNAs have been linked to target mRNAs, genes, and biological mechanisms that could affect virtually every organ system, and as such may be linked to multiple clinical disease presentations such as cardiovascular disease, respiratory disease, and neurological disease.

CONCLUSIONS

Air pollution and temperature exposures were significantly associated with alterations in the ex-miRNA profiles of NAS subjects with possible biological consequences.

Short-term associations between ambient air pollution and emergency department visits for Alzheimer's disease and related dementias

Dementia is a seriously disabling illness with substantial economic and social burdens. Alzheimer's disease and its related dementias (AD/ADRD) constitute about two-thirds of dementias. AD/ADRD patients have a high prevalence of comorbid conditions that are known to be exacerbated by exposure to ambient air pollution. Existing studies mostly focused on the long-term association between air pollution and AD/ADRD morbidity, while very few have investigated short-term associations. This study aims to estimate short-term associations between AD/ADRD emergency department (ED) visits and three common air pollutants: fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and warm-season ozone.

Methods

For the period 2005 to 2015, we analyzed over 7.5 million AD/ADRD ED visits in five US states (California, Missouri, North Carolina, New Jersey, and New York) using a time-stratified case-crossover design with conditional logistic regression. Daily estimated PM_2.5, NO_2, and warm-season ozone concentrations at 1 km spatial resolution were aggregated to the ZIP code level as exposure.

Results

The most consistent positive association was found for NO₂. Across five states, a 17.1 ppb increase in NO₂ concentration over a 4-day period was associated with a 0.61% (95% confidence interval = 0.27%, 0.95%) increase in AD/ADRD ED visits. For PM_2.5, a positive association with AD/ADRD ED visits was found only in New York (0.64%, 95% confidence interval = 0.26%, 1.01% per 6.3 µg/m³). Associations with warm-season ozone levels were null.

Conclusions

Our results suggest AD/ADRD patients are vulnerable to short-term health effects of ambient air pollution and strategies to lower exposure may reduce morbidity.

Associations between long-term air pollution exposure and the incidence of cardiovascular diseases among American older adults

BACKGROUND & AIM

Numerous studies have linked air pollution with cardiovascular diseases. Fewer studies examined the associations at low concentration levels or assessed potential modifiers. Some investigations only examined hospitalizations, which can miss incident cases. This study aims to address these gaps through a nationwide cohort study of Medicare enrollees.

METHODS

Our study cohort comprise all Medicare enrollees (≥65 years old) continuously enrolled in the fee-for-service program and both Medicare part A and B across the contiguous U.S. from 2000 to 2016. We examined the associations of population-weighted ZIP code-level annual average PM_2.5, NO₂, and warm-season O₃ (May-October), with the first diagnoses of atrial fibrillation (AF), congestive heart failure (CHF), and stroke. We fit multi-pollutant Cox proportional hazards models adjusted for individual demographic characteristics and area-level covariates. We further examined these associations at low pollutant concentration levels and the potential effect modifications by race/ethnicity and comorbidities (diabetes, hypertension, hyperlipidemia).

RESULTS

Elevated PM_2.5 and NO₂ levels were associated with increased incidence of AF, CHF, and stroke. For each 1 μg/m³ increase in annual PM_2.5, hazard ratios (HRs) were 1.0059 (95%CI: 1.0054-1.0064), 1.0260 (95%CI: 1.0256-1.0264), and 1.0279 (95%CI: 1.0274-1.0284), respectively. For each1 ppb increase in annual NO₂, HRs are 1.0057 (95%CI: 1.0056-1.0059), 1.0112 (95%CI: 1.0110-1.0113), and 1.0095 (95%CI: 1.0093-1.0096), respectively. For warm-season O₃, each 1 ppb increase was associated with increased incidence of CHF (HR=1.0035, 95%CI: 1.0033-1.0037) and stroke (HR=1.0026, 95%CI: 1.0023-1.0028). Larger magnitudes of HRs were observed when restricted to pollutants levels lower than NAAQS standards. Generally higher risks were observed for Black people and diabetics.

CONCLUSIONS

Long-term exposure to PM_2.5, NO₂, and warm-season O₃ were associated with increased incidence of cardiovascular diseases, even at low pollutant concentration levels. Black people and people with diabetes were found to be vulnerable populations.

The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America

BACKGROUND

Air pollution is speculated to increase the risks of COVID-19 spread, severity, and mortality.

OBJECTIVES

We systematically reviewed studies investigating the relationship between air pollution and COVID-19 cases, non-fatal severity, and mortality in North America and Europe.

METHODS

We searched PubMed, Web of Science, and Scopus for studies investigating the effects of harmful pollutants, including particulate matter with diameter ≤2.5 or 10 μm (PM_2.5 or PM₁₀), ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and carbon monoxide (CO), on COVID-19 cases, severity, and deaths in Europe and North America through to June 19, 2021. Articles were included if they quantitatively measured the relationship between exposure to air pollution and COVID-19 health outcomes.

RESULTS

From 2,482 articles screened, we included 116 studies reporting 355 separate pollutant-COVID-19 estimates. Approximately half of all evaluations on incidence were positive and significant associations (52.7%); for mortality the corresponding figure was similar (48.1%), while for non-fatal severity this figure was lower (41.2%). Longer-term exposure to pollutants appeared more likely to be positively associated with COVID-19 incidence (63.8%). PM_2.5, PM₁₀, O₃, NO₂, and CO were most strongly positively associated with COVID-19 incidence, while PM_2.5 and NO₂ with COVID-19 deaths. All studies were observational and most exhibited high risk of confounding and outcome measurement bias.

DISCUSSION

Air pollution may be associated with worse COVID-19 outcomes. Future research is needed to better test the air pollution-COVID-19 hypothesis, particularly using more robust study designs and COVID-19 measures that are less prone to measurement error and by considering co-pollutant interactions.

Long-term air pollution exposure and incident stroke in American older adults: A national cohort study

Aims

Stroke is a leading cause of death and disability for Americans, and growing evidence suggests that air pollution may play an important role. To facilitate pollution control efforts, the National Academy of Sciences and the World Health Organization have prioritized determining which air pollutants are most toxic. However, evidence is limited for the simultaneous effects of multiple air pollutants on stroke.

Methods and results

We constructed a nationwide population-based cohort study, using the Medicare Chronic Conditions Warehouse (2000-2017) and high-resolution air pollution data, to investigate the impact of long-term exposure to ambient PM2.5, NO2, and ground-level O3 on incident stroke. Hazard ratios (HR) for stroke incidence were estimated using single-, bi-, and tri-pollutant Cox proportional hazards models. We identified ~2.2 million incident stroke cases among 17,443,900 fee-for-service Medicare beneficiaries. Per interquartile range (IQR) increase in the annual average PM2.5 (3.7 μg/m3), NO2 (12.4 ppb), and warm-season O3 (6.5 ppb) one-year prior to diagnosis, the HRs were 1.022 (95% CI: 1.017-1.028), 1.060 (95% CI: 1.054-1.065), and 1.021 (95% CI: 1.017-1.024), respectively, from the tri-pollutant model. There was strong evidence of linearity in concentration-response relationships for all three air pollutants in single-pollutant models. This linear relationship remained robust for NO2 and O3 in tri-pollutant models while the effect of PM2.5 attenuated at the lower end of concentrations.

Conclusion

Using a large nationwide cohort, our study suggests that long-term exposure to PM2.5, NO2, and O3 may independently increase the risk of stroke among the US elderly, among which traffic-related air pollution plays a particularly crucial role.