Ambient air pollution associated with incidence and dynamic progression of type 2 diabetes: a trajectory analysis of a population-based cohort

Air pollution, metabolic signatures, and the risk of idiopathic pulmonary fibrosis

Air pollution has been associated with a higher incidence of idiopathic pulmonary fibrosis (IPF), yet this metabolic mechanism remains unclear. 185,865 participants were included in the UK Biobank. We estimated air pollution exposure using the bilinear interpolation approach, including fine particle matter with diameter < 2.5 μm (PM2.5), particle matter with diameter < 10 μm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx). We identified metabolites and established the metabolic signature with air pollutants using an elastic net regularized regression. Cox proportional hazards models combined with generalized propensity score (GPS) were conducted to evaluate the relationships between metabolic signatures and incident IPF, and mediation analysis was performed to evaluate potential mediators. During a median follow-up of 12.3 years, 1239 IPF cases were ascertained. We identified multi-metabolite profiles comprising 87 metabolites for PM2.5, 65 metabolites for PM10, 71 metabolites for NO2, and 76 metabolites for NOx. Metabolic signatures were associated with incident IPF, with HRs of 1.20 (95 % CI: 1.13, 1.27), 1.09 (95 % CI: 1.03, 1.15), 1.23 (95 % CI: 1.16, 1.31), and 1.24 (95 % CI: 1.17, 1.31) per standard deviation (SD) increase in metabolic profiles associated with PM2.5, PM10, NO2, and NOx, respectively. Furthermore, metabolic signatures of PM2.5, PM10, NO2 and NOx significantly mediated 5.71 %, 3.98 %, 4.21 %, and 4.58 % of air pollution on IPF. Long-term air pollution was associated with a higher risk of IPF, with metabolites potentially playing a mediating role. The findings emphasize the significance of improving metabolic status for the prevention of IPF.

Beverage consumption modifies the risk of type 2 diabetes associated with ambient air pollution exposure

BACKGROUND

Evidence on how beverage consumption modifies associations between air pollution (AP) exposure with the type 2 diabetes (T2D) risk remains scarce, which we aimed to investigate in this study.

METHODS

A total of 77,278 adults from the UK Biobank cohort were enrolled. Annual average concentrations of fine particulate matter (PM2.5 and PM10) and nitrogen oxides (NO2 and NOX) were estimated to represent the long-term AP exposure using the land use regression model. The consumption of beverages (alcoholic beverages, juice, sugar-sweetened beverages [SSB], coffee, and tea) was estimated with the 24-hour dietary assessment. The AP-T2D and beverage-T2D risks were assessed using Cox regression models. Modifying effects of beverage consumption on AP-T2D associations were evaluated through stratified analysis and heterogeneity test.

RESULTS

During a median follow-up of 12.19 years, 1486 T2D events were recorded. One interquartile range increase of PM2.5, NO2, and NOX raised the T2D risk with the hazard ratios (HR) and 95 % confidence intervals (95 % CI) being 1.09 (1.03, 1.16), 1.14 (1.06, 1.21), and 1.09 (1.04, 1.15), respectively. For beverages, compared with non-consumption, daily consumption (>0 cup) of red wine, > 0-3 cups of white wine, ground coffee, and herbal tea, and > 0-1 cup of spirits were associated with a 13 %-37 % reduced T2D risk, while > 0 cup of SSB were associated with a 21 %-122 % elevated T2D risk. Beverage consumption modified AP-T2D associations, as compared with non-consumption, > 0-3 cups of red wine, white wine, ground coffee, and herbal tea had a lower attenuated T2D risk associated with NO2 and/or NOX. Conversely, those with > 1 cup of SSB had a higher T2D risk associated with both NO2 and NOX (Pheter <0.05).

CONCLUSIONS

This study highlights the significant role of beverage consumption in mitigating or exacerbating the T2D risk associated with long-term NO2 and NOX exposure.

Outdoor air pollution exposure and the risk of type 2 diabetes mellitus: A systematic umbrella review and meta-analysis

The association between different air pollutants and Type 2 Diabetes Mellitus (T2DM) is a growing topic of interest in public health research. This umbrella review and meta-analysis aimed to consolidate current literature on the association between various outdoor air pollutants and T2DM. Subgroups and dose-response relationships were also analyzed to further quantify the association, especially by the factors such as the type of pollutants, duration of exposure, and geographical variation, etc. A thorough literature search of three databases revealed a total of 71 records for umbrella review and 1524 records for meta-analysis where 8 studies were included in the final review of umbrella review and 46 studies for meta-analysis. The evaluation of the study's quality in umbrella review and meta-analysis were conducted using the AMSTAR 2 criteria and the Newcastle-Ottawa Scale (NOS), respectively. Exposure to Particulate Matter (PM) 2.5, PM10, Nitrogen dioxides (NO2) and Ozone (O3) were significantly associated with the risk of T2DM [OR = 1.12 (95% Confidence Interval (CI): 1.09, 1.15), 1.12 (95% CI: 1.06, 1.18), 1.09 (95%CI: 1.07, 1.12), 1.05 (95%CI: 1.03, 1.08), respectively] and subgroup analysis further revealed that PM2.5, PM10, and NO2 associations were confounded by factors such as ages, study design, regions of exposure and air pollution concentration levels. Lastly, only exposure to PM10 had a significant dose-response relationship with the risk of T2DM (p-value = 0.000). These findings further emphasized the need for standardized methods in conducting air pollution research and additional research on other air pollutants to further explore the relationships between these air pollutants and T2DM.

Outdoor light at night, air pollution and risk of incident type 2 diabetes

BACKGROUND

Air pollution and outdoor light at night (LAN) have been reported to be related to type 2 diabetes (T2D). However, their interaction with risk of T2D remains uncertain. Therefore, our study aimed to explore the relationship between outdoor LAN, air pollution and incident T2D.

METHODS

Our study included a cohort of 24,147 subjects recruited from 2015 to 2018 in Ningbo, China. Land use regression models were used to evaluate particulate matter with a diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10) and nitrogen dioxide (NO2). Satellite images data with a spatial resolution of 500m was used to estimate outdoor LAN levels. T2D new cases were identified by medical records based on health information system. Cox proportional hazards models were used to estimate Hazard ratios (HRs) and 95% confidence intervals (CIs). Moreover, we investigated the multiplicative and additive interactions between air pollution and outdoor LAN.

RESULTS

During 108,908 person-years of follow-up period, 1016 T2D incident cases were identified. The HRs (95% CIs) were 1.22 (1.15, 1.30) for outdoor LAN, 1.20 (1.00, 1.45) for PM2.5, 1.23 (1.11, 1.35) for PM10 and 1.19 (1.04, 1.37) for NO2 in every interquartile range increase, respectively. Furthermore, significant interactions were observed between outdoor LAN and NO2.

CONCLUSIONS

Our findings indicated that air pollution and outdoor LAN were positively associated with T2D. Moreover, we observed an interaction between outdoor LAN and NO2 suggesting that stronger associations for outdoor LAN and T2D in areas with higher levels of NO2, and for NO2 and T2D in areas with higher levels of outdoor LAN.

Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

Associations of ambient air pollution with incidence and dynamic progression of atrial fibrillation

The influence of air pollution on dynamic changes in clinical state from healthy to atrial fibrillation (AF), further AF-related complications and ultimately, death are unclear. We aimed to investigate the relationships between air pollution and the occurrence and progression trajectories of AF. We retrieved 442,150 participants free of heart failure (HF), myocardial infarction (MI), stroke and dementia at baseline from UK Biobank. Exposures to air pollution for each transition stage were estimated at the geocoded residential address of each participant using the bilinear interpolation approach. The outcomes were incident AF, complications, and death. Multi-stage models were used to evaluate the associations between air pollution and dynamic progression of AF. Over a 12.6-year median follow-up, a total of 21,670 incident AF patients were identified, of whom, 4103 developed complications and 1331 died. PM2.5, PM10, NOx and NO2 were differentially positively associated, while O3 was negatively associated with risks of progression trajectories of AF. PM2.5 exposure was significantly associated with an increased risk of progression. The associations of PM2.5, PM10, NOx, and NO2 on incident AF were generally more pronounced compared to other transitions. The cumulative transition probabilities were generally higher in individuals with higher exposure levels of PM2.5, PM10, NOx, and NO2 and lower exposure to O3. Air pollution could potentially have a role in increasing the risk of both the occurrence and progression of AF, emphasizing the significance of air pollution interventions in both the primary prevention of AF and the management of AF-related outcomes.

Air pollution associated with cardiopulmonary disease and mortality among participants with preserved ratio impaired spirometry

BACKGROUND

Epidemiological evidence regarding the association between air pollutants and cardiopulmonary disease, mortality in individuals with preserved ratio impaired spirometry (PRISm), and their combined effects remains unclear.

METHODS

We followed 36,149 participants with PRISm in the UK Biobank study. Annual concentrations of PM2.5, PM10, NO2, NOx, and SO2 at residential addresses were determined using a bilinear interpolation method, accounting for address changes. A multistate model assessed the dynamic associations between air pollutants and cardiopulmonary diseases and mortality in PRISm. Quantile g-computation was used to investigate the joint effects of air pollutants.

RESULTS

Long-term exposure to PM2.5, PM10, NO2, NOx, and SO2 was significantly associated with the risk of cardiopulmonary disease in PRISm. The corresponding hazard ratios (HRs) [95 % confidence intervals (95 % CIs)] per interquartile range (IQR) were 1.49 (1.43, 1.54), 1.52 (1.46, 1.57), 1.34 (1.30, 1.39), 1.30 (1.26, 1.34), and 1.44 (1.41, 1.48), respectively. For mortality, the corresponding HRs (95 % CIs) per IQR were 1.36 (1.25, 1.47), 1.35 (1.24, 1.46), 1.27 (1.18, 1.36), 1.23 (1.15, 1.31), and 1.29 (1.20, 1.39), respectively. In PRISm, quantile g-computation analysis demonstrated that a quartile increase in exposure to a mixture of all air pollutants was positively associated with the risk of cardiopulmonary disease and mortality, with HRs (95 % CIs) of 1.84 (1.76, 3.84) and 1.45 (1.32, 1.57), respectively.

CONCLUSION

Long-term individual and joint exposure to air pollutants (PM2.5, PM10, NO2, NOx, and SO2) might be an important risk factor for cardiopulmonary disease and mortality in high-risk populations with PRISm.

Associations between cooking method of food and type 2 diabetes risk: A prospective analysis focusing on cooking method transitioning

Cooking process for food significantly impacts household air and increases exposure to endocrine disruptors such as acrylamide, consequently affecting human health. In the past 30 years, the transformation of cooking methods to high-temperature thermal processing has occurred widely in China. Yet the transition of cooking methods on the onset of type 2 diabetes (T2D) remains unclear, which may hinder health-based Sustainable Development Goals. We aimed to estimate the associations between dietary intake with different cooking methods and T2D risk. We included 14,745 participants (>20 y) from the China Health and Nutrition Survey (1991-2015). Food consumption was calculated using three consecutive 24-h dietary recalls combined with both individual participant level and household food inventory. Cooking methods, including boiling, steaming, baking, griddling, stir-frying, deep-frying, and raw eating, were also recorded. The consumption of baked/griddled and deep-fried foods was positively associated with 39% and 35% higher of T2D risk by comparing the highest with the lowest category of food consumption, respectively. The use of unhealthy cooking methods for processing foods including baked/griddled and deep-fried foods was attributable for 15 million T2D cases of the total T2D burden in 2011, resulting in a medical cost of $2.7 billion and was expected to be attributable for 39 million T2D cases in 2030, producing a medical cost of $223.8 billion. Replacing one serving of deep-fried foods and baked/griddle foods with boiled/steamed foods was related to 50% and 20% lower risk of T2D, respectively. Our findings recommend healthy driven cooking methods for daily diet for nourishing sustainable T2D prevention in China.

Perspective on using non-human primates in Exposome research

The physiological and pathological changes in the human body caused by environmental pressures are collectively referred to as the Exposome. Human society is facing escalating environmental pollution, leading to a rising prevalence of associated diseases, including respiratory diseases, cardiovascular diseases, neurological disorders, reproductive development disorders, among others. Vulnerable populations to the pathogenic effects of environmental pollution include those in the prenatal, infancy, and elderly stages of life. Conducting Exposome mechanistic research and proposing effective health interventions are urgent in addressing the current severe environmental pollution. In this review, we address the core issues and bottlenecks faced by current Exposome research, specifically focusing on the most toxic ultrafine nanoparticles. We summarize multiple research models being used in Exposome research. Especially, we discuss the limitations of rodent animal models in mimicking human physiopathological phenotypes, and prospect advantages and necessity of non-human primates in Exposome research based on their evolutionary relatedness, anatomical and physiological similarities to human. Finally, we declare the initiation of NHPE (Non-Human Primate Exposome) project for conducting Exposome research using non-human primates and provide insights into its feasibility and key areas of focus. SYNOPSIS: Non-human primate models hold unique advantages in human Exposome research.

Causal associations of ambient particulate matter 10 and Alzheimer's disease: result from a two-sample multivariable Mendelian randomization study

Introduction

Alzheimer's disease (AD) and ambient particulate matter 10 (PM10) have been associated in epidemiological studies. However, the relationship between PM10 and risk of AD has not been proven to be causal. Thus we used two-sample multivariable Mendelian randomization (MR) to examine this relationship.

Material and methods

Genome-wide association studies (GWAS) for PM10 from UK Biobank, AD from EBI GWAS and IEU OpenGWAS were used for discovery and replication, respectively. Pooled meta-analysis of the inverse variance weighted (IVW) method was the main method. Sensitivity analyses included MR-Egger regression, weighted median, weighted mode and leave-one-out methods. The multivariable MR model adjusted for education. The MR estimates of causality association were expressed as odds ratios (OR) and corresponding 95% confidence intervals (CI).

Results

There were in total 17 and 19 genetic variants associated with PM10 in the discovery and replication steps, respectively. In the univariate MR, pooled meta-analysis of genetically predicted PM10 was associated with a 99% increased risk of AD (95% CI: 1.25, 3.15, p = 0.004) per 1 standard deviation (SD) increment of PM10 by IVW, and in the multivariable MR with pooled meta-analysis, we found that each SD increase in PM10 was associated with a 127% increase in the risk of AD (95% CI: 1.33, 3.86, p = 0.002) after accounting for education levels.

Conclusions

Increased PM10 levels were found to be significantly related to an increased risk of AD. This study provided evidence of genetic prediction of a causal relationship between PM10 and the risk of AD, suggesting that air pollution control may have significant implications for the prevention of AD.

PM2.5 Exposure as a Risk Factor for Optic Nerve Health in Type 2 Diabetes Mellitus

(1) Objective: This study investigated the relationship between long-term particulate matter (PM2.5) exposure and optic disc parameters-vertical cup-to-disc ratio (vCDR), vertical optic disc diameter (vDD), and vertical optic cup diameter (vCD)-in patients with type 2 diabetes mellitus (T2DM). (2) Methods: A cross-sectional analysis was conducted using data from 65,750 T2DM patients in the 2017-2018 Shanghai Cohort Study of Diabetic Eye Disease (SCODE). Optic disc parameters were extracted from fundus images, and PM2.5 exposure was estimated using a random forest model incorporating satellite and meteorological data. Multivariate linear regression models were applied, adjusting for confounders including age, gender, body mass index, blood pressure, glucose, time of T2DM duration, smoking, drinking, and physical exercise. (3) Results: A 10 μg/m3 increase in PM2.5 exposure was associated with significant reductions in vCDR (-0.008), vDD (-42.547 μm), and vCD (-30.517 μm) (all p-values < 0.001). These associations persisted after sensitivity analyses and adjustments for other pollutants like O3 and NO2. (4) Conclusions: Long-term PM2.5 exposure is associated with detrimental changes in optic disc parameters in patients with T2DM, suggesting possible optic nerve atrophy. Considering the close relationship between the optic nerve and the central nervous system, these findings may also reflect broader neurodegenerative processes.

Long-term effects of air quality on hospital readmission for heart failure in patients with acute myocardial infarction

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization.

METHODS

We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups.

RESULTS

After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 μg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 μg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064).

CONCLUSION

NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 μg/m3 and PM10 exceeds 55 μg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Association of residential air pollution and green space with all-cause and cause-specific mortality in individuals with diabetes: an 11-year prospective cohort study

BACKGROUND

To assess the long-term impact of residential air pollution and green space exposure on cause-specific mortality in individuals with type 2 diabetes mellitus (T2DM).

METHODS

This study includes 174,063 participants newly diagnosed with T2DM from a prospective cohort in Shanghai, China, enrolled between 2011 and 2013. Residential annual levels of air pollutants, including fine (PM2.5) and coarse (PM2.5-10) particulate matter, nitrogen dioxide (NO2), along with the normalized difference vegetation index (NDVI), were derived from satellite-based exposure models.

FINDINGS

During a median follow-up of 7.9 years (equivalent to 1,333,343 person-years), this study recorded 22,205 deaths. Higher exposure to PM2.5 was significantly associated with increased risks for all mortality outcomes, whilst PM2.5-10 showed no significant impacts. The strongest associations of PM2.5 were observed for diabetes with peripheral vascular diseases [hazard ratio (HR): 2.70; per 10 μg/m3 increase] and gastrointestinal cancer (2.44). Effects of NO2 became significant at concentrations exceeding approximately 45 μg/m³, with the highest associations for lung cancer (1.20) and gastrointestinal cancer (1.19). Conversely, each interquartile range increase in NDVI (0.10) was linked to reduced mortality risks across different causes, with HRs ranging from 0.76 to 1.00. The association between greenness and mortality was partly and significantly mediated by reduced PM2.5 (23.80%) and NO2 (26.60%). There was a significant and negative interaction between NO2 and greenness, but no interaction was found between PM2.5 and greenness.

INTERPRETATION

Our findings highlight the vulnerability of individuals with T2DM to the adverse health effects of air pollution and emphasise the potential protective effects of greenness infrastructure.

FUNDING

The 6th Three-year Action Program of Shanghai Municipality for Strengthening the Construction of Public Health System (GWVI-11.1-22), the National Key Research and Development Program (2022YFC3702701), and the National Natural Science Foundation of China (82030103, 82373532).

Exposure to Air Pollutants and Myocardial Infarction Incidence: A UK Biobank Study Exploring Gene-Environment Interaction

BACKGROUND

Unraveling gene-environment interaction can provide a novel insight into early disease prevention. Nevertheless, current understanding of the interplay between genetic predisposition and air pollution in relation to myocardial infarction (MI) risk remains limited. Furthermore, the potential long-term influence of air pollutants on MI incidence risk warrants more conclusive evidence in a community population.

OBJECTIVE

We investigated interactions between genetic predisposition and exposure to air pollutants on MI incidence.

METHODS

This study incorporated a sample of 456,354 UK Biobank participants and annual mean air pollution (PM 2.5 , PM 10 , NO 2 , and NO x ) from the UK Department for Environment, Food and Rural Affairs (2006-2021). The Cox proportional hazards model was employed to explore MI incidence after chronic air pollutants exposure. By quantifying genetic risk through the calculation of polygenic risk score (PRS), this study further examined the interactions between genetic risk and exposure to air pollutants in the development of MI on both additive and multiplicative scales.

RESULTS

Among 456,354 participants, 9,114 incident MI events were observed during a median follow-up of 12.08 y. Chronic exposure to air pollutants was linked with an increased risk of MI occurrence. Specifically, the hazard ratios (per interquartile range) were 1.12 (95% CI: 1.10, 1.13) for PM 2.5 , 1.20 (95% CI: 1.19, 1.22) for PM 10 , 1.13 (95% CI: 1.12, 1.15) for NO 2 , and 1.12 (95% CI: 1.11, 1.13) for NO x . In terms of the joint effects, participants with high PRS and high level of air pollution exposure exhibited the greatest risk of MI among all study participants (∼ 255 % to 324%). Remarkably, both multiplicative and additive interactions were detected in the ambient air pollutants exposure and genetic risk on the incidence of MI.

DISCUSSION

There were interactions between exposure to ambient air pollutants and genetic susceptibility on the risk of MI onset. Moreover, the joint effects of these two exposures were greater than the effect of each factor alone. https://doi.org/10.1289/EHP14291.

Air Pollution, Genetic Susceptibility, and Risk of Incident Systemic Lupus Erythematosus: A Prospective Cohort Study

OBJECTIVE

There are few existing studies that investigate the risk of systemic lupus erythematosus (SLE) associated with long-term exposure to air pollutants. This study aimed to explore associations between long-term exposure to air pollutants and incident SLE and further evaluate interactions and joint effects of genetic risk and air pollutants.

METHODS

A total of 459,815 participants were included from UK Biobank. The concentrations of air pollutants (fine particulate matter with diameter ≤2.5 μm [PM2.5], particulate matter diameter ≤10 μm [PM10], nitrogen dioxide [NO2], and nitrogen oxides [NOx]) were estimated by land-use regression model. We applied Cox proportional hazards model to explore linkages of air pollutants and incident SLE. The polygenic risk score (PRS) was used for further assessing the interactions and joint effects of genetic risk and air pollutants.

RESULTS

A total of 399 patients with SLE were identified during a median follow-up of 11.77 years. There were positive associations between air pollutant exposure and incident SLE, as the adjusted hazard ratios were 1.18 (95% confidence interval [95% CI] 1.06-1.32), 1.23 (1.10-1.39), 1.27 (1.14-1.41), and 1.13 (1.03-1.23) for each interquartile range increase in PM2.5, PM10, NO2, and NOx, respectively. Moreover, participants with high genetic risk and high air pollution exposure had the highest risk of incident SLE compared with those with low genetic risk and low air pollution exposure (adjusted hazard ratio: PM2.5, 4.16 [95% CI 2.67-6.49]; PM10, 5.31 [95% CI 3.30,-8.55]; NO2, 5.61 [95% CI 3.45-9.13]; and NOx, 4.80 [95% CI 3.00-7.66]). There was a significant multiplicative interaction between NO2 and PRS.

CONCLUSION

Long-term exposure to air pollutants (PM2.5, PM10, NO2, and NOx) may increase the risk of developing SLE.

Healthy lifestyle associated with dynamic progression of type 2 diabetes: A multi-state analysis of a prospective cohort

Background

Although the association of a healthy lifestyle with type 2 diabetes (T2D) has been extensively studied, its impact on the dynamic trajectory, including progression, onset and prognosis, of T2D has not been investigated.

Methods

Using data from the UK Biobank, 461 168 participants without diabetes or diabetes-related events were included. We incorporated four lifestyle factors to construct the healthy lifestyle score (HLS). We employed a multi-state model to examine the relationship between a healthy lifestyle and transition in T2D progression, including transitions from baseline to diabetes, complications, and further to death. The cumulative probability of above transitions based on the health lifestyle score was calculated.

Results

The results indicated that adhering to 3-4 healthy lifestyles had an inverse association with the risk of transition from baseline to diabetes (hazard ratio (HR) = 0.966; 95% confidence interval (CI) = 0.935-0.998, P = 0.038), diabetes to complications (HR = 0.869; 95% CI = 0.818-0.923, P = 5.2 × 10-6), baseline to death (HR = 0.528; 95% CI = 0.502-0.553, P < 2 × 10-16, and diabetes to death (HR = 0.765; 95% CI = 0.591-0.990, P = 0.041) compared with maintaining 0-1 healthy lifestyles. In addition, the transition probability of the above transitions can be lower with maintaining 3-4 healthy lifestyles.

Conclusions

Healthy lifestyles are negatively associated with the risk of multiple outcomes during the dynamic progression of T2D. Adherence to 3-4 healthy lifestyle behaviours before diabetes onset can lower the risk of developing T2D, further reducing the risk of diabetes complications and death in patients with T2D.

Exposure to ambient air pollutants during circadian syndrome and subsequent cardiovascular disease and its subtypes and death: A trajectory analysis

BACKGROUND

The association between exposure to air pollutants and cardiovascular disease (CVD) trajectory in individuals with circadian syndrome remains inconclusive.

METHODS

The individual exposure levels of air pollutants, including particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM2.5), PM with aerodynamic diameter ≤ 10 μm (PM10), PM2.5 absorbance, PM with aerodynamic diameter between 2.5 μm and 10 μm, nitrogen dioxide (NO2), nitrogen oxides (NOx), and air pollution score (overall air pollutants exposure), were estimated for 48,850 participants with circadian syndrome from the UK Biobank. Multistate regression models were employed to estimate associations between exposure to air pollutants and trajectories from circadian syndrome to CVD/CVD subtypes (including coronary heart disease [CHD], atrial fibrillation [AF], heart failure [HF], and stroke) and death. Mediation roles of CVD/CVD subtypes in the associations between air pollutants and death were evaluated.

RESULTS

After a mean follow-up time over 12 years, 12,570 cases of CVD occurred, including 8192 CHD, 1693 AF, 1085 HF, and 1600 stroke cases. In multistate model, per-interquartile range increment in PM2.5 (hazard ratio: 1.08; 95 % confidence interval: 1.06, 1.10), PM10 (1.04; 1.01, 1.06), PM2.5 absorbance (1.04; 1.02, 1.06), NO2 (1.07; 1.03, 1.11), NOx (1.08; 1.04, 1.12), or air pollution score (1.06; 1.03, 1.08) was associated with trajectory from circadian syndrome to CVD. Significant associations between the above-mentioned air pollutants and trajectories from circadian syndrome and CVD to death were observed. CVD, particularly CHD, significantly mediated the associations of PM2.5, NO2, NOx, and air pollution score with death.

CONCLUSIONS

Long-term exposure to air pollutants during circadian syndrome was associated with subsequent CVD and death. CHD emerged as the most prominent CVD subtype in CVD progression driven by exposure to air pollutants during circadian syndrome. Our study highlights the importance of controlling air pollutants exposure and preventing CHD in people with circadian syndrome.

Air pollution exposure during preconception and first trimester of pregnancy and gestational diabetes mellitus in a large pregnancy cohort, Hebei Province, China

Objective

To explore the relationship between the exposure level of particulate matter 2.5 (PM2.5) and particulate matter 10 (PM10) in the air of pregnant women during preconception and first trimester of pregnancy and the risk of gestational diabetes mellitus (GDM).

Methods

The data of pregnant women delivered in 22 monitoring hospitals in Hebei Province from 2019 to 2021 were collected, and the daily air quality data of their cities were used to calculate the exposure levels of PM2.5 and PM10 in different pregnancy stages, and logistic regression model was used to analyze the impact of exposure levels of PM2.5 and PM10 on GDM during preconception and first trimester of pregnancy.

Results

108,429 singleton live deliveries were included in the study, of which 12,967 (12.0%) women had a GDM diagnosis. The prevalence of GDM increased over the course of the study from 10.2% (2019) to 14.9% (2021). From 2019 to 2021, the average exposure of PM2.5 and PM10 was relatively 56.67 and 103.08μg/m3 during the period of preconception and first trimester of pregnancy in Hebei Province. Handan, Shijiazhuang, and Xingtai regions had the most severe exposure to PM2.5 and PM10, while Zhangjiakou, Chengde, and Qinhuangdao had significantly lower exposure levels than other regions. The GDM group had statistically higher exposure concentrations of PM2.5 and PM10 during the period of preconception, first trimester, preconception and first trimester (P<0.05). Multivariate logistic regression analysis showed that the risk of GDM increases by 4.5%, 6.0%, and 10.6% for every 10ug/m3 increase in the average exposure value of PM2.5 in preconception, first trimester, preconception and first trimester, and 1.7%, 2.1%, and 3.9% for PM10. Moreover, High exposure to PM2.5 in the first, second, and third months of preconception and first trimester is associated with the risk of GDM. And high exposure to PM10 in the first, second, and third months of first trimester and the first, and third months of preconception is associated with the risk of GDM.

Conclusion

Exposure to high concentrations of PM2.5 and PM10 during preconception and first trimester of pregnancy can significantly increase the risk of GDM. It is important to take precautions to prevent exposure to pollutants, reduce the risk of GDM, and improve maternal and fetal outcomes.

Air pollution and risk of 32 health conditions: outcome-wide analyses in a population-based prospective cohort in Southwest China

BACKGROUND

Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions.

METHODS

A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD.

RESULTS

Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62-1.89), hypertensive diseases (1.49, 1.38-1.62), cardiac arrests (1.52, 1.30-1.77), arrhythmia (1.76, 1.44-2.15), cerebrovascular diseases (1.86, 1.65-2.10), stroke (1.77, 1.54-2.03), ischemic stroke (1.85, 1.61-2.12), atherosclerosis (1.77, 1.57-1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15-1.51), pneumonia (1.37, 1.16-1.61), inflammatory bowel diseases (1.34, 1.16-1.55), liver diseases (1.59, 1.43-1.77), type 2 diabetes (1.48, 1.26-1.73), lipoprotein metabolism disorders (2.20, 1.96-2.47), purine metabolism disorders (1.61, 1.38-1.88), anemia (1.29, 1.15-1.45), sleep disorders (1.54, 1.33-1.78), renal failure (1.44, 1.21-1.72), kidney stone (1.27, 1.13-1.43), osteoarthritis (2.18, 2.00-2.39), osteoporosis (1.36, 1.14-1.61). OM had max weights for joint effects of AP on many conditions.

CONCLUSIONS

Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

Associations between Changes in Exposure to Air Pollutants due to Relocation and the Incidence of 14 Major Disease Categories and All-Cause Mortality: A Natural Experiment Study

BACKGROUND

Though observational studies have widely linked air pollution exposure to various chronic diseases, evidence comparing different exposures in the same people is limited. This study examined associations between changes in air pollution exposure due to relocation and the incidence and mortality of 14 major diseases.

METHODS

We included 50,522 participants enrolled in the UK Biobank from 2006 to 2010. Exposures to particulate matter with a diameter ≤ 2.5 μ m (PM 2.5 ), particulate matter with a diameter ≤ 10 μ m (PM 10 ), nitrogen oxides (NO x ), nitrogen dioxide (NO 2 ), and sulfur dioxide (SO 2 ) were estimated for each participant based on their residential address and relocation experience during the follow-up. Nine exposure groups were classified based on changes in long-term exposures due to residential mobility. Incidence and mortality of 14 major diseases were identified through linkages to hospital inpatient records and death registries. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incidence and mortality of the 14 diseases of interest.

RESULTS

During a median follow-up of 12.6 years, 29,869 participants were diagnosed with any disease of interest, and 3,144 died. Significantly increased risk of disease and all-cause mortality was observed among individuals who moved from a lower to higher air polluted area. Compared with constantly low exposure, moving from low to moderate PM 2.5 exposure was associated with increased risk of all 14 diseases but not for all-cause mortality, with adjusted HRs (95% CIs) ranging from 1.18 (1.05, 1.33) to 1.48 (1.30, 1.69); moving from low to high PM 2.5 areas increased risk of all 14 diseases: infections [1.37 (1.19, 1.58)], blood diseases [1.57 (1.34, 1.84)], endocrine diseases [1.77 (1.50, 2.09)], mental and behavioral disorders [1.93 (1.68, 2.21)], nervous system diseases [1.51 (1.32, 1.74)], ocular diseases [1.76 (1.56, 1.98)], ear disorders [1.58 (1.35, 1.86)], circulatory diseases [1.59 (1.42, 1.78)], respiratory diseases [1.51 (1.33, 1.72)], digestive diseases [1.74 (1.58, 1.92)], skin diseases [1.39 (1.22, 1.58)], musculoskeletal diseases [1.62 (1.45, 1.81)], genitourinary diseases [1.54 (1.36, 1.74)] and cancer [1.42 (1.24, 1.63)]. We observed similar associations for PM 10 and SO 2 with 14 diseases (but not with all-cause mortality); increases in NO 2 and NO x were positively associated with 14 diseases and all-cause mortality.

CONCLUSIONS

This study supports potential associations between ambient air pollution exposure and morbidity as well as mortality. Findings also emphasize the importance of maintaining consistently low levels of air pollution to protect the public's health. https://doi.org/10.1289/EHP14367.

Association between birth weight/joint exposure to ambient air pollutants and type 2 diabetes: a cohort study in the UK Biobank

Early life events and environmental factors are associated with type 2 diabetes (T2D) development. We assessed the combined effect of birth weight andambient air pollutants, and effect of their interaction on T2D risk. Totally, 6,474 T2D incidents were recorded over an 8.7-year follow-up period. The adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were 1.31 (1.26, 1.36) for each kilogram decrease in birth weight, and 1.08 (1.05, 1.11) for each standard deviation increase in air pollution score (APS). Birth weight<3000 g amplified the T2D risk associated with high APS. A combination of the lowest birth weight (<2500 g) and the highest quintile of APS led to over two-fold increase in T2D risk (aHR: 2.17; 95% CI: 1.79-2.64). There was a significant additive interaction between them. In conclusion, ambient air pollutants increase the risk for T2D, particularly in populations with low birth weight.

Diabetes mellitus-Progress and opportunities in the evolving epidemic

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

County Rurality and Incidence and Prevalence of Diagnosed Diabetes in the United States

OBJECTIVE

To examine differences in the incidence and prevalence of diagnosed diabetes by county rurality.

PATIENTS AND METHODS

This observational, cross-sectional study used US Centers for Disease Control and Prevention data from 2004 through 2019 for county estimates of incidence and prevalence of diagnosed diabetes. County rurality was based on 6 levels (large central metro counties [most urban] to noncore counties [most rural]). Weighted least squares regression was used to relate rurality with diabetes incidence rates (IRs; per 1000 adults) and prevalence (percentage) in adults aged 20 years or older after adjusting for county-level sociodemographic factors (eg, food environment, health care professionals, inactivity, obesity).

RESULTS

Overall, in 3148 counties and county equivalents, the crude IR and prevalence of diabetes were highest in noncore counties. In age and sex ratio-adjusted models, the IR of diabetes increased monotonically with increasing rurality (P<.001), whereas prevalence had a weak, nonmonotonic but statistically significant increase (P=.002). Further adjustment for sociodemographic factors including food environment, health care professionals, inactivity, and obesity attenuated differences in incidence across rurality levels, and reversed the pattern for prevalence (prevalence ratios [vs large central metro] ranged from 0.98 [95% CI, 0.97 to 0.99] for large fringe metro to 0.94 [95% CI, 0.93 to 0.96] for noncore). In region-stratified analyses adjusted for sociodemographic factors including inactivity and obesity, increasing rurality was inversely associated with incidence in the Midwest and West only and inversely associated with prevalence in all regions.

CONCLUSION

The crude incidence and prevalence of diagnosed diabetes increased with increasing county rurality. After accounting for sociodemographic factors including food environment, health care professionals, inactivity, and obesity, county rurality showed no association with incidence and an inverse association with prevalence. Therefore, interventions targeting modifiable sociodemographic factors may reduce diabetes disparities by region and rurality.

Exposure to Air Pollution, Genetic Susceptibility, and Psoriasis Risk in the UK

Importance

Psoriasis is a common autoinflammatory disease influenced by complex interactions between environmental and genetic factors. The influence of long-term air pollution exposure on psoriasis remains underexplored.

Objective

To examine the association between long-term exposure to air pollution and psoriasis and the interaction between air pollution and genetic susceptibility for incident psoriasis.

Design, Setting, and Participants

This prospective cohort study used data from the UK Biobank. The analysis sample included individuals who were psoriasis free at baseline and had available data on air pollution exposure. Genetic analyses were restricted to White participants. Data were analyzed between November 1 and December 10, 2023.

Exposures

Exposure to nitrogen dioxide (NO2), nitrogen oxides (NOx), fine particulate matter with a diameter less than 2.5 µm (PM2.5), and particulate matter with a diameter less than 10 µm (PM10) and genetic susceptibility for psoriasis.

Main Outcomes and Measures

To ascertain the association of long-term exposure to NO2, NOx, PM2.5, and PM10 with the risk of psoriasis, a Cox proportional hazards model with time-varying air pollution exposure was used. Cox models were also used to explore the potential interplay between air pollutant exposure and genetic susceptibility for the risk of psoriasis incidence.

Results

A total of 474 055 individuals were included, with a mean (SD) age of 56.54 (8.09) years and 257 686 (54.36%) female participants. There were 9186 participants (1.94%) identified as Asian or Asian British, 7542 (1.59%) as Black or Black British, and 446 637 (94.22%) as White European. During a median (IQR) follow-up of 11.91 (11.21-12.59) years, 4031 incident psoriasis events were recorded. There was a positive association between the risk of psoriasis and air pollutant exposure. For every IQR increase in PM2.5, PM10, NO2, and NOx, the hazard ratios (HRs) were 1.41 (95% CI, 1.35-1.46), 1.47 (95% CI, 1.41-1.52), 1.28 (95% CI, 1.23-1.33), and 1.19 (95% CI, 1.14-1.24), respectively. When comparing individuals in the lowest exposure quartile (Q1) with those in the highest exposure quartile (Q4), the multivariate-adjusted HRs were 2.01 (95% CI, 1.83-2.20) for PM2.5, 2.21 (95% CI, 2.02-2.43) for PM10, 1.64 (95% CI, 1.49-1.80) for NO2, and 1.34 (95% CI, 1.22-1.47) for NOx. Moreover, significant interactions between air pollution and genetic predisposition for incident psoriasis were observed. In the subset of 446 637 White individuals, the findings indicated a substantial risk of psoriasis development in participants exposed to the highest quartile of air pollution levels concomitant with high genetic risk compared with those in the lowest quartile of air pollution levels with low genetic risk (PM2.5: HR, 4.11; 95% CI, 3.46-4.90; PM10: HR, 4.29; 95% CI, 3.61-5.08; NO2: HR, 2.95; 95% CI, 2.49-3.50; NOx: HR, 2.44; 95% CI, 2.08-2.87).

Conclusions and Relevance

In this prospective cohort study of the association between air pollution and psoriasis, long-term exposure to air pollution was associated with increased psoriasis risk. There was an interaction between air pollution and genetic susceptibility on psoriasis risk.

Influence of cognitive reserve on risk of depression and subsequent dementia: A large community-based longitudinal study

BACKGROUND

Cognitive reserve (CR) has been linked to dementia, yet its influence on the risk of depression and related outcomes remains unknown. We aimed to examine the association of CR with depression and subsequent dementia or death, and to assess the extent to which CR is related to depression-free survival.

METHODS

Within the UK Biobank, 436,232 participants free of depression and dementia were followed. A comprehensive CR indicator (low, moderate, and high) was created using latent class analysis based on information on education, occupation, mentally passive sedentary behavior, social connection, confiding with others, and leisure activities. Depression, dementia, and survival status were ascertained through self-reported medical history and/or linkages to medical records. Data were analyzed using multi-state Markov model and Laplace regression.

RESULTS

Over a median follow-up of 12.96 years, 16,560 individuals developed depression (including 617 with subsequent dementia) and 28,655 died. In multivariable multi-state models, compared with low CR, high CR was associated with lower risk of depression (hazard ratio 0.53 [95% confidence interval 0.51-0.56]) and lower risk of post-depression dementia (0.55 [0.34-0.88]) or death (0.69 [0.55-0.88]) in middle-aged adults (aged <60 years). In Laplace regression, the depression-free survival time was prolonged by 2.77 (2.58-2.96) years in participants with high compared to low CR.

CONCLUSIONS

High CR is associated with lower risks of depression and subsequent transitions to dementia and death, particularly in middle age. High CR may prolong depression-free survival. Our findings highlight the importance of enhancing CR in the prevention and prognosis of depression.

Regular use of fish oil supplements and course of cardiovascular diseases: prospective cohort study

Objective

To examine the effects of fish oil supplements on the clinical course of cardiovascular disease, from a healthy state to atrial fibrillation, major adverse cardiovascular events, and subsequently death.

Design

Prospective cohort study.

Setting

UK Biobank study, 1 January 2006 to 31 December 2010, with follow-up to 31 March 2021 (median follow-up 11.9 years).

Participants

415 737 participants, aged 40-69 years, enrolled in the UK Biobank study.

Main outcome measures

Incident cases of atrial fibrillation, major adverse cardiovascular events, and death, identified by linkage to hospital inpatient records and death registries. Role of fish oil supplements in different progressive stages of cardiovascular diseases, from healthy status (primary stage), to atrial fibrillation (secondary stage), major adverse cardiovascular events (tertiary stage), and death (end stage).

Results

Among 415 737 participants free of cardiovascular diseases, 18 367 patients with incident atrial fibrillation, 22 636 with major adverse cardiovascular events, and 22 140 deaths during follow-up were identified. Regular use of fish oil supplements had different roles in the transitions from healthy status to atrial fibrillation, to major adverse cardiovascular events, and then to death. For people without cardiovascular disease, hazard ratios were 1.13 (95% confidence interval 1.10 to 1.17) for the transition from healthy status to atrial fibrillation and 1.05 (1.00 to 1.11) from healthy status to stroke. For participants with a diagnosis of a known cardiovascular disease, regular use of fish oil supplements was beneficial for transitions from atrial fibrillation to major adverse cardiovascular events (hazard ratio 0.92, 0.87 to 0.98), atrial fibrillation to myocardial infarction (0.85, 0.76 to 0.96), and heart failure to death (0.91, 0.84 to 0.99).

Conclusions

Regular use of fish oil supplements might be a risk factor for atrial fibrillation and stroke among the general population but could be beneficial for progression of cardiovascular disease from atrial fibrillation to major adverse cardiovascular events, and from atrial fibrillation to death. Further studies are needed to determine the precise mechanisms for the development and prognosis of cardiovascular disease events with regular use of fish oil supplements.

Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China

BACKGROUND

The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome.

METHODS AND RESULTS

A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05).

CONCLUSIONS

Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.

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.

Long-Term Exposure to Low Concentrations of Ambient Benzene and Mortality in a National English Cohort

Background: Benzene affects human health through environmental exposure in addition to occupational contact. However, few studies have examined the associations between long-term exposure to low concentrations of ambient benzene and mortality risks in nonoccupational settings.Methods: This prospective cohort study consists of 393,042 participants without stroke, myocardial infarction, or cancer at baseline from the UK Biobank. Annual average concentrations of benzene for each year during follow-up were measured using air dispersion models. The main outcomes were all-cause mortality and mortality from specific causes. Cox proportional-hazards models with time-varying exposure measurements were used to estimate the hazard ratios and 95% confidence intervals (CIs) for mortality risks. Restricted cubic spline models were used to estimate exposure-response relationships.Measurements and Main Results: With each interquartile range increase in the average annual concentration of benzene, the adjusted hazard ratios of mortality risk from all causes, cardiovascular disease, cancer, and respiratory disease were 1.26 (95% CI, 1.24-1.27), 1.24 (95% CI, 1.21-1.28), 1.27 (95% CI, 1.25-1.29), and 1.25 (95% CI, 1.20-1.30), respectively. The monotonically increasing exposure-response curves showed no threshold and plateau within the observed concentration range. Furthermore, the effect of benzene exposure on mortality persisted across different subgroups and was somewhat stronger in younger and White people (P for interaction < 0.05).Conclusions: Long-term exposure to low concentrations of ambient benzene significantly increases mortality risk in the general population. Ambient benzene represents a potential threat to public health, and further investigations are needed to support timely pollution regulation and health protection.

Elevated blood remnant cholesterol and triglycerides are causally related to the risks of cardiometabolic multimorbidity

The connection between triglyceride-rich lipoproteins and cardiometabolic multimorbidity, characterized by the concurrence of at least two of type 2 diabetes, ischemic heart disease, and stroke, has not been definitively established. We aim to examine the prospective associations between serum remnant cholesterol, triglycerides, and the risks of progression from first cardiometabolic disease to multimorbidity via multistate modeling in the UK Biobank. We also evaluate the causality of these associations via Mendelian randomization using 13 biologically relevant SNPs as the genetic instruments. Here we show that elevated remnant cholesterol and triglycerides are significantly associated with gradually higher risks of cardiometabolic multimorbidity, particularly the progression of ischemic heart disease to the multimorbidity of ischemic heart disease and type 2 diabetes. These results advocate for effective management of remnant cholesterol and triglycerides as a potential strategy in mitigating the risks of cardiometabolic multimorbidity.

Joint Exposure to Multiple Air Pollutants, Genetic Susceptibility, and Incident Dementia: A Prospective Analysis in the UK Biobank Cohort

Objectives: This study aimed to evaluate the joint effects of multiple air pollutants including PM2.5, PM10, NO2, and NOx with dementia and examined the modifying effects of genetic susceptibility. Methods: This study included 220,963 UK Biobank participants without dementia at baseline. Weighted air pollution score reflecting the joint exposure to multiple air pollutants were constructed by cross-validation analyses, and inverse-variance weighted meta-analyses were performed to create a pooled effect. The modifying effect of genetic susceptibility on air pollution score was assessed by genetic risk score and APOE ε4 genotype. Results: The HR (95% CI) of dementia for per interquartile range increase of air pollution score was 1.13 (1.07∼1.18). Compared with the lowest quartile (Q1) of air pollution score, the HR (95% CI) of Q4 was 1.26 (1.13∼1.40) (P trend = 2.17 × 10-5). Participants with high air pollution score and high genetic susceptibility had higher risk of dementia compared to those with low air pollution score and low genetic susceptibility. Conclusion: Our study provides evidence that joint exposure to multiple air pollutants substantially increases the risk of dementia, especially among individuals with high genetic susceptibility.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study

BACKGROUND AND AIMS

Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown.

METHODS

This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset.

RESULTS

Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx.

CONCLUSIONS

In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Effect modification of dietary diversity on the association of air pollution with incidence, complications, and mortality of type 2 diabetes: Results from a large prospective cohort study

BACKGROUND

It remains unknown whether the dietary diversity score (DDS) could modify the association of long-term exposure to individual air pollutants and the mixture of various pollutants with the incidence, complications, and mortality of type 2 diabetes (T2D).

METHODS

We included 162,579 participants from the UK Biobank who had ≥ one 24-h dietary assessment and were free of diabetes or diabetes complications before their last response date of the 24-h dietary assessment. Exposure to benzene, NOx, NO2, SO2, PM10, and PM2.5 was estimated at each participant's residential location using a bilinear interpolation algorithm based on air dispersion models on a 1 km × 1 km grid. The DDS was calculated based on repeated 24-h dietary assessments. The outcomes were the incidence, complications, and mortality of T2D. Associations of individual pollutants and multiple pollutants mixtures with outcomes were assessed using Cox proportional hazards regression models and the quantile g-computation approach, respectively. We further stratified these analyses by DDS.

RESULTS

During a median of 10.1 years of follow-up, 2978 participants developed incident T2D, 1181 developed T2D complications, and 242 died due to T2D. Long-term single-pollutant and multi-pollutant exposure were associated with elevated risk of incidence, complications, and mortality of T2D. For example, for incident T2D, the hazard ratio and 95 % confidence interval for each quantile increase were 1.155 (1.095, 1.215) for the air pollution mixture. We observed significant interactions between air pollution (benzene, NOx, NO2, PM10, PM2.5, and the air pollution mixture) and DDS (P-interaction <0.05), with the corresponding associations being significantly weaker in adults with high DDS than in those with low DDS.

CONCLUSION

Higher dietary diversity may attenuate the harmful impacts of air pollution on T2D-related outcomes. A higher diversity diet could be used to prevent the onset and progression of T2D induced by long-term exposure to various air pollutants.

Genetic Susceptibility Modifies Relationships Between Air Pollutants and Stroke Risk: A Large Cohort Study

BACKGROUND

The extent to which genetic susceptibility modifies the associations between air pollutants and the risk of incident stroke is still unclear. This study was designed to investigate the separate and joint associations of long-term exposure to air pollutants and genetic susceptibility on stroke risk.

METHODS

The participants of this study were recruited by the UK Biobank between 2006 and 2010. These participants were followed up from the enrollment until the occurrence of stroke events or censoring of data. Hazard ratios (HRs) and 95% CIs for stroke events associated with long-term exposure to air pollutants were estimated by fitting both crude and adjusted Cox proportional hazards models. Additionally, the polygenic risk score was calculated to estimate whether the polygenic risk score modifies the associations between exposure to air pollutants and incident stroke.

RESULTS

A total of 502 480 subjects were included in this study. After exclusion, 452 196 participants were taken into the final analysis. During a median follow-up time of 11.7 years, 11 334 stroke events were observed, with a mean age of 61.60 years, and men accounted for 56.2% of the total cases. Long-term exposures to particulate matter with an aerodynamic diameter smaller than 2.5 µm (adjusted HR, 1.70 [95% CI, 1.43-2.03]) or particulate matter with an aerodynamic diameter smaller than 10 µm (adjusted HR, 1.50 [95% CI, 1.36-1.66]), nitrogen dioxide (adjusted HR, 1.10 [95% CI, 1.07-1.12]), and nitrogen oxide (adjusted HR, 1.04 [95% CI, 1.02-1.05]) were pronouncedly associated with increased risk of stroke. Meanwhile, participants with high genetic risk and exposure to high air pollutants had ≈45% (31%, 61%; particulate matter with an aerodynamic diameter smaller than 2.5 µm), 48% (33%, 65%; particulate matter with an aerodynamic diameter smaller than 10 µm), 51% (35%, 69%; nitrogen dioxide), and 39% (25%, 55%; nitrogen oxide) higher risk of stroke compared with those with low genetic risk and exposure to low air pollutants, respectively. Of note, we observed additive and multiplicative interactions between genetic susceptibility and air pollutants on stroke events.

CONCLUSIONS

Chronic exposure to air pollutants was associated with an increased risk of stroke, especially in populations at high genetic risk.

Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review

PURPOSE OF REVIEW

The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs.

RECENT FINDINGS

CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.

Long-term influence of air pollutants on morbidity and all-cause mortality of cardiometabolic multi-morbidity: A cohort analysis of the UK Biobank participants

BACKGROUND

The effects of air pollutants on cardiometabolic diseases (CMDs) have been widely explored, whereas their influences on cardiometabolic multi-morbidity (CMM) were not clear.

METHODS

We employed the UK Biobank cohort (N = 317,160) to study the association between six air pollutants (PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx) and four CMDs including type II diabetes (T2D), coronary artery disease (CAD), stroke and hypertension. CMM was defined as occurrence of two or more of the four diseases. Multi-state Cox models were performed to estimate hazard ratio (HR) and its 95% confidence interval (95%CI).

RESULTS

During a median follow-up of 12.8 years, 52,211 participants developed only one CMD, 15,446 further developed CMM, and 16,861 ultimately died. It was demonstrated that per interquartile range increase (IQR) increases in PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx would increase 12% (9%-15%), 4% (1%-7%), 3% (1%-6%), 7% (4%-10%), 11% (8%-15%) and 10% (7%-13%) higher risk of developing one CMD from health baseline; 7% (2%-12%), 8% (3%-13%), 6% (2%-11%), 10% (5%-15%), 13% (7%-18%) and 10% (5%-15%) greater risk of occurring CMM from one CMD baseline; and 11% (-2%∼26%), 22% (7%-38%), 17% (3%-32%), 31% (16%-49%), 33% (17%-51%) and 32% (17%-50%) larger risk of causing death from CMM baseline, respectively.

CONCLUSIONS

We revealed that people living in areas with high air pollution suffered from higher hazard of CMD, CMM and all-cause mortality; our findings implied keeping clean air was an effective approach to prevent or mitigate initiation, progression, and death from healthy to CMDs and from CMDs to CMM.

The effects of long-term exposure to air pollution on incident mental disorders among patients with prediabetes and diabetes: Findings from a large prospective cohort

BACKGROUND

The association between air pollution and mental disorders has been widely documented in the general population. However, the evidence among susceptible populations, such as individuals with prediabetes or diabetes, is still insufficient.

METHODS

We analyzed data from 48,515 participants with prediabetes and 24,393 participants with diabetes from the UK Biobank. Annual pollution data were collected for fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), and nitrogen dioxides (NOx) during 2006-2021. The exposure to air pollution and temperature for each participant were estimated by the bilinear interpolation approach and time-weighted method based on their geocoded home addresses and time spent at each address. We employed the generalized propensity score model based on the generalized estimating equation and the time-varying covariates Cox model to assess the effects of air pollution.

RESULTS

We observed causal links between air pollutants and mental disorders among both prediabetic and diabetic participants, with stronger effects among those with diabetes than prediabetes. The hazard ratios were 1.18 (1.12, 1.24), 1.15 (1.10, 1.20), 1.18 (1.13, 1.23), and 1.15 (1.11, 1.19) in patients with prediabetes, and 1.21 (1.13, 1.29), 1.17 (1.11, 1.24), 1.19 (1.13, 1.25), and 1.17 (1.12, 1.23) in patients with diabetes per interquartile range elevation in PM2.5, PM10, NO2, and NOx. Furthermore, the effects were more pronounced among people who were older, alcohol drinkers, and living in urban areas.

CONCLUSIONS

Our study indicates the potential causal links between long-term exposure to air pollution and incident mental disorders among those with prediabetes and diabetes. Reducing air pollution levels would significantly benefit this vulnerable population by reducing the incidence of mental disorders.

Association between exposure to air pollution during preconception and risk of gestational diabetes mellitus: The role of anti-inflammatory diet

BACKGROUND

Regarding the association between the sensitive time-windows of air pollution (AP) exposure and gestational diabetes mellitus (GDM), epidemiological findings are inconsistent. The dietary inflammatory potential has been implicated in the development of GDM, but it is unclear whether an anti-inflammatory diet during pregnancy reduces the association between AP and GDM.

OBJECTIVE

We aimed to characterize the sensitive time-windows of AP to GDM risk. Further, to verify whether a maternal anti-inflammatory diet can reduce the risk of AP-induced GDM, by inhibiting inflammation.

METHODS

A total of 8495 pregnant women were included between 2015 and 2021 in the Maternal & Infants Health in Hefei study. Weekly mean AP exposure to fine particles (PM2.5 and PM10), SO2, and NO2 was estimated from the data of Hefei City Ecology and Environment Bureau. High-sensitivity C-reactive protein (hs-CRP) concentrations were measured to evaluate systemic inflammation. The empirical dietary inflammatory pattern (EDIP) score based on a validated food frequency questionnaire was used to assess the dietary inflammatory potential of pregnant women. Logistic regression models with distributed lags were used to identify the sensitive time-window for the effect of AP on GDM. Mediation analysis estimated the mediated effect of hs-CRP, linking AP with GDM. Stratified analysis was used to investigate the potential effect of anti-inflammatory diet on GDM risk.

RESULTS

The increased risks of GDM were found to be positively associated with exposure to PM2.5 (OR = 1.11, 95% CI:1.07-1.15), PM10 (OR = 1.12, 95% CI:1.09-1.16), and SO2 (OR = 1.42, 95% CI:1.25-1.60) by distributed lag models, and the critical exposure windows were 21st to 28th weeks of preconception. The proportion of association between PM2.5, PM10, and SO2 with GDM mediated by hs-CRP was 25.9%, 21.1%, and 19.4%, respectively, according to mediation analysis. In the stratified analyses by EDIP, the association between AP and GDM was not statistically significant among women those with anti-inflammatory diets.

CONCLUSIONS

Exposure to AP, especially in 21st to 28th week of preconception, is associated with risk of GDM, which is partly mediated by hs-CRP. Adherence to the anti-inflammatory dietary pattern may reduce the risk of AP-induced GDM.

Criteria air pollutants and diabetes mortality classified by different subtypes and complications: A nationwide, case-crossover study

The associations between air pollution and diabetes mortality of different subtypes and complications were largely unclear. We performed an individual-level, time-stratified case-crossover study among over 0.9 million diabetes deaths from all administrative regions of Chinese mainland during 2013-2019. Daily concentrations of fine particles (PM2.5), coarse particles (PM2.5-10), nitrogen dioxide (NO2) and ozone (O3) were obtained for each decedent using high-resolution prediction models. Conditional logistic regression models were utilized to analyze the data. Each interquartile range increment in PM2.5, PM2.5-10, NO2 and O3 concentrations on lag 0-2 d increased the risks of overall diabetes mortality by 2.81 %, 1.92 %, 3.96 % and 2.15 %, respectively. Type 2 diabetes had stronger associations with air pollution than type 1 diabetes. Air pollutants were associated with diabetic ketoacidosis and diabetic nephropathy, but not other complications. The exposure-response curves were approximately linear with a plateau at higher concentrations of PM2.5, PM2.5-10, and NO2, while the associations for O3 appear to be statistically significant beyond 60 μg/m3. This nationwide study reinforces the evidence of higher risks of acute diabetic events following short-term air pollution exposure. We identified differential effects of air pollutants on various subtypes and complications of diabetes, which require further mechanistic investigations.

Ambient air pollution associated with incident asthma, subsequent cardiovascular disease and death: A trajectory analysis of a national cohort

No previous study has examined the impact of air pollution on the cardiovascular disease (CVD) trajectory, especially among asthmatic subjects. Based on the UK Biobank cohort, we retrieved 292,227 adults free of asthma and CVD aged 37-73 years at recruitment (2006-2010). Annual mean concentrations of particulate matter (PM10 and PM2.5) and nitrogen oxides (NO2 and NOx) were assessed at each individual's addresses. We used multi-state models to estimate the associations of air pollution with the trajectory from healthy to incident asthma, subsequent CVD, and death. During a median follow-up of 11.7 years, a total of 6338 (2.2%) participants developed asthma, among which, 638 (10.1%) subsequently proceeded to CVD. We observed significant impacts of various air pollutants on the CVD dynamic transitions, with a more substantial effect of particulate matter pollutants than gaseous air pollutants. For example, the hazard ratios (95% confidence intervals) for per interquartile range increase in PM2.5 and PM10 were 1.28 (1.13, 1.44) and 1.27 (1.13, 1.43) for transitions from incident asthma to subsequent CVD. In conclusion, long-term air pollution exposure could affect the CVD trajectory. Distinguishing the effect of air pollutants on CVD transition stages has great significance for CVD health management and clinical prevention, especially among asthma patients.

Associations of Life's Essential 8 and fine particulate matter pollution with the incidence of atrial fibrillation

Both unhealthy lifestyle factors and ambient air pollution have been closely linked with the risk of atrial fibrillation (AF). We retrieved 250,898 participants without AF at baseline from UK Biobank. LE8 was determined by 8 metrics, and was characterized as low, moderate and high cardiovascular health (CVH). Exposure to PM2.5 was estimated at the geocoded residential address of each participant. During a median follow-up of 12.46 years, we identified 14,743 (5.9%) incident AF cases. Participants with moderate and high CVH showed a decreased risk of incident AF compared to those with low CVH. Of the LE8 metrics, ideal body mass index (BMI) and blood pressure (BP) were associated with a decrease of 11.57% and 11.46% AF cases. High PM2.5 exposure was associated with an 8% increased risk of AF as compared to low PM2.5 exposure. Compared with those who had low CVH and high PM2.5 exposure, participants with a high CVH and low PM2.5 exposure had the lower AF incidence. Our study found higher CVH is protective, while higher PM2.5 might be one risk factor of AF. Adherence to the LE8 guidelines may help reduce the incidence of AF, especially in those with lower PM2.5 exposure.

Low-level ambient sulfur dioxide exposure and genetic susceptibility associated with incidence of idiopathic pulmonary fibrosis: A national prospective cohort study

BACKGROUND

The association between long-term air pollution exposure and the development of idiopathic pulmonary fibrosis (IPF) has been established, but the evidence regarding the effect of low levels of air pollution, especially ambient sulfur dioxide (SO2), is limited. Besides, the combined effect and interaction between genetic susceptibility and ambient SO2 on IPF remain uncertain.

METHODS

This study retrieved data from 402,042 participants who were free of IPF at baseline in the UK Biobank. The annual mean concentration of ambient SO2 was estimated for each participant based on their residential addresses using a bilinear interpolation method. Cox proportional hazard models were used to examine the relationship between ambient SO2 and incident IPF. We further generated a polygenic risk score (PRS) for IPF and estimated the combined effects of genetic susceptibility and ambient SO2 on incident IPF.

RESULTS

After a median follow-up of 11.78 years, 2562 cases of IPF were identified. The results indicated that each 1 μg/m3 increase in ambient SO2 was associated with a hazard ratio (HR) (95% confidence interval [CI]) of 1.67 (1.58, 1.76) for incident IPF. The study found statistically significant synergistic additive interaction between genetic susceptibility and ambient SO2. Individuals with high genetic risk and high ambient SO2 exposure had a higher risk of developing IPF (HR = 7.48, 95% CI:5.66, 9.90).

CONCLUSION

The study suggests that long-term exposure to ambient SO2, even at concentrations lower than current air quality guidelines set by the Word Health Organization and European Union, may be an important risk factor for IPF. This risk is more pronounced among people with a high genetic risk. Therefore, these findings emphasize the need to consider the potential health effects of SO2 exposure and the necessity for stricter air quality standards.

Long-term exposure to ambient air pollution, genetic susceptibility, and the incidence of bipolar disorder: A prospective cohort study

There is mounting recent evidence showing that air pollution exposure may be related to the risk of mental health, yet the association between long-term exposure to air pollution and the risk of incident bipolar disorder (BD) remains unclear. Thus we aim to identify associations between air pollution and the incidence of BD in a prospective population-based cohort. In total, 482,726 participants who were free of BD from the UK Biobank were included in this prospective study. We applied time-varying Cox proportional hazards models, accounting for relevant confounders, and used annual-year moving averages of air pollution as time-varying exposures. The genetic risk for BD was categorized into three categories (low, intermediate, and high) according to the tertiles of polygenic risk score. During a median of 10.79-year follow-up, 923 incident BD events were recorded. Long-term exposures to PM2.5, PM10, NO2, and NOx were associated with increased BD risk. Estimated HRs (95% CIs) for each interquartile range increase in PM2.5, PM10, NO2, and NOx concentrations were 1.31 (1.18-1.45), 1.19 (1.09-1.31), 1.19 (1.08-1.30), and 1.16 (1.07-1.26), respectively. Associations were still observed and even stronger at pollutant concentrations lower than WHO air quality guideline. In subgroup analysis stratified by genetic risk, we observed consistent associations between all pollutants and BD risk in intermediate and high genetic risk groups, but not in low genetic risk group. For example, the HRs (95% CIs) for PM2.5 were 1.00 (0.94-1.53), 1.30 (1.06-1.59), and 1.34 (1.16-1.54) in low, intermediate, and high genetic groups, respectively. In conclusion, long-term exposure to air pollution was significantly associated with an elevated risk of BD. Associations of air pollution with BD occurred only within intermediate and high genetic risk categories and were even stronger at the pollutants levels below WHO air quality guidelines. These findings could help inform policy makers regarding ambient air quality standards and BD management.

Air pollution, genetic susceptibility, and the risk of atrial fibrillation: A large prospective cohort study

To date, no study has explored the extent to which genetic susceptibility modifies the effects of air pollutants on the risk of atrial fibrillation (AF). This study was designed to investigate the separate and joint effects of long-term exposure to air pollutants and genetic susceptibility on the risk of AF events. This study included 401,251 participants without AF at baseline from UK Biobank. We constructed a polygenic risk score and categorized it into three categories. Cox proportional hazards models were fitted to assess the separate and joint effects of long-term exposure to air pollutants and genetics on the risk of AF. Additionally, we further evaluated the effect modification of genetic susceptibility. The hazard ratios and corresponding 95% confidence intervals of incident AF for per interquartile range increase in particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5) or 10 µm (PM10), nitrogen dioxide (NO2), and nitrogen oxide (NOx) were 1.044 (1.025, 1.063), 1.063 (1.044, 1.083), 1.061 (1.042, 1.081), and 1.039 (1.023, 1.055), respectively. For the combined effects, participants exposed to high air pollutants levels and high genetic risk had approximately 149.2% (PM2.5), 181.7% (PM10), 170.2% (NO2), and 157.2% (NOx) higher risk of AF compared to those with low air pollutants levels and low genetic risk, respectively. Moreover, the significant additive interactions between PM10 and NO2 and genetic risk on AF risk were observed, with around 16.4% and 35.1% of AF risk could be attributable to the interactive effects. In conclusion, long-term exposure to air pollutants increases the risk of AF, particularly among individuals with high genetic susceptibility.

Air pollution associated with incidence and progression trajectory of chronic lung diseases: a population-based cohort study

BACKGROUND

No prior study has examined the effects of air pollution on the progression from healthy to chronic lung disease, subsequent chronic lung multimorbidity and further to death.

METHODS

We used data from the UK Biobank of 265 506 adults free of chronic lung disease at recruitment. Chronic lung multimorbidity was defined as the coexistence of at least two chronic lung diseases, including asthma, chronic obstructive pulmonary disease and lung cancer. The concentrations of air pollutants were estimated using land-use regression models. Multistate models were applied to assess the effect of air pollution on the progression of chronic lung multimorbidity.

RESULTS

During a median follow-up of 11.9 years, 13 863 participants developed at least one chronic lung disease, 1055 developed chronic lung multimorbidity and 12 772 died. We observed differential associations of air pollution with different trajectories of chronic lung multimorbidity. Fine particulate matter showed the strongest association with all five transitions, with HRs (95% CI) per 5 µg/m3 increase of 1.31 (1.22 to 1.42) and 1.27 (1.01 to 1.57) for transitions from healthy to incident chronic lung disease and from incident chronic lung disease to chronic lung multimorbidity, and 1.32 (1.21 to 1.45), 1.24 (1.01 to 1.53) and 1.91 (1.14 to 3.20) for mortality risk from healthy, incident chronic lung disease and chronic lung multimorbidity, respectively.

CONCLUSION

Our study provides the first evidence that ambient air pollution could affect the progression from free of chronic lung disease to incident chronic lung disease, chronic lung multimorbidity and death.

Dynamic association of ambient air pollution with incidence and mortality of pulmonary hypertension: A multistate trajectory analysis

BACKGROUND

There is little evidence regarding the association between ambient air pollution and incidence and the mortality of pulmonary hypertension (PH).

METHODS

We included 494,750 participants at baseline in the UK Biobank study. Exposures to PM2.5, PM10, NO2, and NOx were estimated at geocoded participants' residential addresses, utilizing pollution data provided by UK Department for Environment, Food and Rural Affairs (DEFRA). The outcomes were the incidence and mortality of PH. We used multivariate multistate models to investigate the impacts of various ambient air pollutants on both incidence and mortality of PH.

RESULTS

During a median follow-up of 11.75 years, 2517 participants developed incident PH, and 696 died. We observed that all ambient air pollutants were associated with increased incidence of PH with different magnitudes, with adjusted hazard ratios (HRs) [95% confidence intervals (95% CIs)] for each interquartile range (IQR) increase of 1.73 (1.65, 1.81) for PM2.5, 1.70 (1.63, 1.78) for PM10, 1.42 (1.37, 1.48) for NO2, and 1.35 (1.31, 1.40) for NOx. Furthermore, PM2.5, PM10, NO2 and NO2 influenced the transition from PH to death, and the corresponding HRs (95% CIs) were 1.35 (1.25, 1.45), 1.31 (1.21, 1.41), 1.28 (1.20, 1.37) and 1.24 (1.17, 1.32), respectively.

CONCLUSION

The results of our study indicate that exposure to various ambient air pollutants might play key but differential roles in both the incidence and mortality of PH.

Dietary Diversity and Inflammatory Diet Associated with All-Cause Mortality and Incidence and Mortality of Type 2 Diabetes: Two Prospective Cohort Studies

A higher dietary diversity score (DDS) and a lower energy-adjusted dietary inflammatory index (E-DII) may be associated with lower risks of type 2 diabetes (T2D) and mortality. This cohort study aimed to investigate the associations of DDS and E-DII with all-cause mortality, incidence of T2D, and mortality of T2D, as well as the joint effects of these two dietary factors. A total of 181,360 participants without all types of diabetes at baseline from the UK Biobank and 42,139 participants from the US NHANES were included. Cox proportional hazards models were used to assess the associations of DDS and E-DII with outcomes. In the UK Biobank data, 8338 deaths, 3416 incident T2D cases, and 353 T2D deaths occurred during a median follow-up of 12.5 years. In the US NHANES data, 6803 all-cause deaths and 248 T2D-specific deaths were recorded during a median follow-up of 9.6 years. We observed that higher DDS and lower E-DII were significantly associated with lower risks of total mortality and incident T2D. Compared with low DDS, the hazard ratios (HRs) and 95% confidence intervals (CIs) of high DDS were 0.69 (0.64, 0.74) for all-cause mortality, 0.79 (0.70, 0.88) for incident T2D in the UK Biobank, and 0.69 (0.61, 0.78) for all-cause mortality in the US NHANES. Compared with participants in tertile 3 of E-DII, those in tertile 1 had a lower risk of overall death [HR 0.86 (95% CI: 0.81, 0.91) in UK Biobank; 0.83 (0.77, 0.88) in US NHANES] and incident T2D [0.86 (0.79, 0.94)] in UK Biobank. No evidence was observed of the interactive effects of DDS and E-DII on either all-cause mortality or the incidence and mortality of T2D. There was no significant association found between any exposure and T2D mortality in this study. In conclusion, our results revealed that higher DDS and lower E-DII were associated with both total mortality and incident T2D in UK and US adults.

Ambient air pollution associated with incidence and progression trajectory of cardiometabolic diseases: A multi-state analysis of a prospective cohort

BACKGROUND

Previous studies on the association between ambient air pollution and cardiometabolic diseases (CMDs) focused on a single disease, without considering cardiometabolic multimorbidity (CMM) and the progression trajectory of CMDs.

METHODS

Based on the UK Biobank cohort, we included 372,530 participants aged 37-73 years at baseline (2006-2010) with follow-up until September 2021. Incident CMDs cases were identified based on self-reported information and multiple health-related records in the UK Biobank. CMM was defined as the occurrence of at least two CMDs, including ischemic heart disease (IHD), stroke and type 2 diabetes (T2D). Exposure to ambient air pollutants, including particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), and nitrogen oxides (NO_x) were estimated at participants' geocoded residential addresses based on the high-resolution (1 × 1 km) pollution data from 2001 to 2021 provided by UK Department for Environment, Food and Rural Affairs. Multi-state models with adjustment for potential confounders were used to examine the impact of long-term exposure to ambient air pollution on transitions from healthy to first CMD (FCMD), subsequently to CMM, and further to death.

RESULTS

During a median follow-up of 12.6 years, 40,112 participants developed at least one CMD, 3896 developed CMM, and 21,739 died. Among the four pollutants, PM_2.5 showed the strongest associations with all transitions from healthy to FCMD, to CMM, and then to death [hazard ratios (95 % confidence intervals) per interquartile range (IQR) increment: 1.62 (1.60, 1.64) and 1.68 (1.61, 1.76) for transitions from healthy to FCMD and from FCMD to CMM, and 1.62 (1.59, 1.66), 1.67 (1.61, 1.73), and 1.52 (1.38, 1.67) for death risk from healthy, FCMD, and CMM, respectively]. After dividing FCMDs into three specific CMDs, we found that ambient air pollution had differential impacts on disease-specific transitions within the same transition phase.

CONCLUSIONS

Our findings indicate that there is potential for air pollution mitigation in contributing to the prevention of the development and progression of CMDs.