Understanding the response of PM2.5-bound toxic components to source variations under climate change is crucial for public health protection. However, the lack of long-term and multi-site observational data of toxic components limits such efforts. Here, we conducted a five-year PM2.5 measurement (2018-2022) at 10 sites across a Chinese megacity, analyzing 15 polycyclic aromatic hydrocarbons (PAHs), 6 organophosphate esters (OPEs), and 9 potentially toxic elements (PTEs). Using explainable machine learning, we found that source variations from particle matter mass reduction under climate change can impact PM2.5-bound toxic components. Meteorological factors like extreme heat days and max temperature impact most toxic components, while geographic, socioeconomic, and anthropogenic factors mainly affect PTEs, especially Cu. We also designed 10 extreme heat and source variation scenarios to predict the response of toxic components. When comparing scenario 2-1 (source variation without temperature change) with scenario 2-2 and 2-3 (the same source variation but higher temperatures), many PM2.5-bound organics and As show higher reduction rates under climate change, highlighting the need to focus more on gas-phase organics and products of atmospheric process. Benzo[b]fluoranthene (BbF) is most sensitive to traffic source reductions, and Cu, Mn, Zn and Fe are more sensitive to industrial source reductions.

Climate change contributes to warm, dry conditions, which leads to longer and more active fire seasons. Wildland firefighters work long hours in smoky conditions without regulations requiring respiratory protection. Wildfire smoke has many toxic components, including high levels of fine particulate matter (PM2.5). Regular monitoring for short- and long-term health outcomes in wildland firefighter populations is uncommon. However, extrapolating from knowledge about the individual components of smoke, it is likely that the firefighters' health is negatively affected. Firefighters are routinely exposed to dangerous levels of smoke, which may lead to both acute and chronic health consequences. Current guidelines from Occupational Safety and Health Administration (OSHA), the U.S. Forest Service (USFS), and the Interagency Standards for Fire and Fire Aviation Operations do not recommend respirator use for wildland firefighters. The methodologies used to quantify exposure and harm likely underestimate actual risks. Although there are no respirators that can filter all known harmful components of wildfire smoke, this review examines the potential benefit of respirator use by reducing some of the most harmful components of the smoke. Smoke exposure among wildland firefighters needs to be further characterized and quantified. Regulations should be reassessed to accurately reflect the exposure and potential harm that firefighters face. This narrative review gathers information from peer-reviewed scientific literature, government publications, news articles, and personal conversations with both public- and private-sector professionals. The objectives are to describe the likely health effects of wildland firefighting, evaluate the evidence behind current respiratory protection guidelines, and propose potential solutions.

Cardiovascular diseases have been the leading cause of death in the Russian population to date.

Using generalized estimating equations, we examined the links of area-level socio-economic and environmental deprivation with cardiovascular disease risk factors in the adult population as a whole, as well as in men and women separately.

People living in more economically deprived areas had 61 percent higher odds of being obese (Q4: odds ratio (OR) 1.61; 95% confidence interval (CI): 1.20-2.16), 2.32 times higher odds of having chronic kidney disease (OR 2.32; 95% CI: 1.56-3.44), up to 57 percent higher odds of having hyperuricemia (OR 1.57; 95% CI: 1.31-1.88), and up to 80 percent higher odds of having diabetes mellitus (OR 1.80; 95% CI: 1.71-1.89), compared to those in the least deprived areas. Individuals living in the most environmentally deprived areas were associated with higher odds of hypertension (OR 1.37; 95% CI: 1.19-1.57) and these associations persisted for both when considering men (OR 1.38; 95% CI: 1.19-1.61) and women (OR 1.37; 95% CI: 1.14-1.65) separately.

This is the first study to examine the relationship of area characteristics with cardio-metabolic risk factors such as elevated blood pressure and prediabetes, taking into account individual characteristics among the Russian population.

One of the metabolic complications of obesity is known as Metabolic Syndrome (MetS). This narrative review aims to synthesize current research on MetS in young populations, identify knowledge gaps, and guide future studies and funding priorities. It provides evidence-based insights into screening, diagnosis, and treatment, offering practical guidance for healthcare professionals.

A comprehensive search of the literature was conducted to identify relevant studies on obesity in MetS in PubMed and Google Academic electronic database. The search was performed using a combination of "obesity", "complications", "metabolic syndrome", "children", and "adolescents" keywords. Studies were selected based on predefined inclusion and exclusion criteria to ensure relevance and methodological rigor.

The lack of universally accepted diagnostic criteria for MetS in children has led to inconsistencies in its definition across medical literature. Irrespective of the chosen diagnostic approach, the prevalence of MetS in children and adolescents has exhibited a concurrent rise with the increasing rates of obesity in this age group. The pathophysiology of MetS remains incompletely understood, with ongoing discussions on the interplay of genetic, epigenetic, environmental, dietary, and lifestyle factors. Screening for MetS is recommended for overweight and obese children.

Establishing global, consensus-driven criteria that account for ethnicity, gender, and age would enhance diagnostic accuracy and treatment approaches. The prevention of excessive weight among children and adolescents stands as a paramount objective within modern society's healthcare system. Considering the complexity of the disease and the treatment, the team must be multidisciplinary.

This investigation explores the worldwide impact of diabetes burden associated with air pollution, drawing on data from the Global Burden of Disease Study 2021.

The influence of air pollution on diabetes burden was analyzed at global, regional, and national levels. The study considered variations across age groups and genders and explored the relationship between disease impact and the Socio-Demographic Index (SDI). Additionally, an ARIMA model was employed to predict the future incidence of diabetes burden related to air pollution until 2050.

In 2021, approximately 281.91 thousand fatalities and 12.90 million disability-adjusted life years were attributed to diabetes burden due to air pollution, featuring an age-standardized mortality rate (ASMR) of 3.3234 (95% UI, 1.9549-4.6634) and an age-standardized DALY rate (ASDR) of 148.9167 (95% UI, 86.5013-224.9116) per 100,000 individuals. There was a noticeable escalation in the disease burden over the period studied. The most severe effects were noted in individuals aged 60 and above. The data also revealed a higher disease burden among males. Forecasting suggests that while low SDI regions might see a decrease in death rates, lower-middle SDI areas could face an increase in standardized mortality rates. On a national scale, Russia, Mexico, and several African nations are predicted to experience rising diabetes burden attributable to air pollution mortality rates and age-standardized mortality rates from now to 2050. South Asia and Africa are anticipated to witness substantial growth in age-standardized death rates compared to other areas.

The results provide essential insights for developing preventive strategies for diabetes burden and measures to mitigate air pollution.

Despite numerous meta-analyses showing an association between air pollutants and diabetes, there is considerable heterogeneity between studies.

This study aims to evaluate the cumulative evidence regarding the association between air pollution and type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM) through systematic reviews and meta-analyses.

Following the PRISMA 2020 guidance, a comprehensive review across three databases, including Web of Science, Embase, and PubMed, from inception to September 30, 2024. The quality of the included systematic reviews was assessed using the AMSTAR 2 tool. The research protocol has been registered in PROSPERO (CRD42024594953).

A total of 19 meta-analyses were identified in this review, including two articles investigating the impact of air pollution on T1DM, nine on T2DM, and ten on GDM. Due to limited data, no significant relationship between air pollution and T1DM was found. There is evidence that exposure to particulate matter (PM2.5 and PM10) may significantly increase the risk of T2DM. However, meta-analyses concerning GDM exhibit a less consistent association between air pollution and GDM risk, which varies by pollutant and duration of exposure.

Results suggest that exposure to air pollution may increase diabetes risk to some extent, particularly for T2DM. However, due to limited available studies, further prospective cohort studies are warranted to elucidate the role of air pollutants in diabetes, particularly for T1DM. Additionally, understanding potential mechanisms by which air pollution affects diabetes is crucial for future investigations.

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.

Despite the growing evidence pointing to the detrimental effects of air pollution on diabetes mellitus (DM), the relationship remains poorly explored, especially in desert-adjacent areas characterized by high aridity and pollution.

We conducted a cross-sectional study with health examination data from more than 2.9 million adults in 2 regions situated in the southern part of the Taklamakan Desert, China.

We assessed 3-year average concentrations (2018-2020) of particulate matter (PM1, PM2.5, and PM10), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) through a space-time extra-trees model. After adjusting for various covariates, we employed generalized linear mixed models to evaluate the association between exposure to air pollutants and DM.

The odds ratios for DM associated with a 10 µg/m3 increase in PM1, PM2.5, PM10, CO, and NO2 were 1.898 (95% CI, 1.741-2.070), 1.07 (95% CI, 1.053-1.086), 1.013 (95% CI, 1.008-1.018), 1.009 (95% CI, 1.007-1.011), and 1.337 (95% CI, 1.234-1.449), respectively. Notably, men, individuals aged 50 years or older, those with lower educational attainment, nonsmokers, and those not engaging in physical exercise appeared to be more susceptible to the adverse effects of air pollution. Multiple sensitivity analyses confirmed the stability of these findings.

Our study provides robust evidence of a correlation between prolonged exposure to air pollution and the prevalence of DM among individuals living in desert-adjacent areas. This research contributes to the expanding knowledge on the relationship between air pollution exposure and DM prevalence in desert-adjacent areas.

Air pollution exposure has become an international health issue that poses many risks to life and health. The bidirectional regulatory network, known as the oral-gut-brain axis connects the oral cavity, intestine, and central nervous system, as well as its influence on health outcomes from exposure to air pollution is receiving increased attention. This article systematically details the epidemiological evidence linking air pollutants to diseases affecting the oral, respiratory, intestinal, and nervous systems, while also explaining the route of air pollutants via the oral-gut-brain axis. The oral-gut-brain axis anomalies resulting from air pollution and their underlying molecular processes are also covered. The study provides a fresh viewpoint on how exposure to air pollution affects health and investigates cutting-edge preventative and therapeutic techniques.

The field of political economics in health has a significant and far-reaching impact on public health. It encompasses a diverse range of interconnected domains, including the economy, welfare, the environment, food and drug safety, pollution emissions, occupational safety, the quality of medical services, consumer rights, public health policy, healthcare policy, scientific research, and marketing management. In this review, we examine the global influence of political economics on health outcomes and delineate the impact of prevalent neurosurgical conditions on individual and collective healthcare resources. This review will discuss the effects of political-economic factors on the prevalence and treatment of neurosurgical diseases, including stroke, traumatic brain injury (TBI), intracerebral hemorrhage (ICH), and brain malignant tumors. Furthermore, the current challenges and future directions will be discussed. We intend this review to facilitate the exchange and integration of political economics, public health, and neurosurgery, provide a foundation for policy development, enhance the prevention, diagnosis, and treatment of neurosurgical diseases, and ultimately promote public health.

Epidemiological studies prove that type II diabetes, characterized by insulin resistance (IR), may be caused by fine particulate matter 2.5 (PM2.5). However, underlying mechanisms whereby PM2.5, particularly during short-term exposure, induces liver dysfunction leading to IR remains poorly understood. In the present study, HepG2 cells and the BALB/c mouse model were used to explore how PM2.5 affects insulin sensitivity. The effects of subacute PM2.5 exposure on glucose metabolism were examined using commercial kits. Oxidative stress and inflammation were detected by fluorescent staining and RT-qPCR. The phosphorylation of PI3K/AKT was examined by Western blot. Subacute PM2.5 exposure induced IR, as reflected by increased glucose levels in cell supernatants, elevated insulin levels, and the impaired intraperitoneal glucose tolerance test in mice. PM2.5 induced oxidative stress, as evidenced by increased reactive oxygen species, cytochrome P450 2E1, and malondialdehyde, along with reduced superoxide dismutase 1/2 and silent information regulator 1. IL-6 and TNF-α were found to be upregulated using RT-qPCR. Western blot showed that PM2.5 inhibited the PI3K-AKT signaling pathway, indicated by the decreased phosphorylation of PI3K/AKT in HepG2 cells. Additionally, H&E staining showed only mild hepatic injury in mice liver. These results firmly suggest that subacute PM2.5 exposure induces insulin resistance through oxidative stress, inflammation, and the inhibition of the PI3K-AKT signaling pathway.

Exposure to air pollution is associated with worldwide morbidity and mortality. Diesel exhaust (DE) emissions are important contributors which induce vascular inflammation and metabolic disturbances by unknown mechanisms. We aimed to determine molecular pathways activated by DE in the liver that could be responsible for its cardiometabolic toxicity.

Apolipoprotein E knockout (ApoE KO) mice were exposed to DE or filtered air (FA) for two weeks, or DE for two weeks followed by FA for 1 week. Expression microarrays and global metabolomics assessment were performed in the liver. An integrated transcriptomic and metabolomic analytical strategy was employed to dissect critical pathways and identify candidate genes that could dissect DE-induced pathogenesis. HepG2 cells were treated with an organic extract of DE particles (DEP) vs. vehicle control to test candidate genes.

DE exposure for 2 weeks dysregulated 658 liver genes overrepresented in whole cell metabolic pathways, especially including lipid and carbohydrate metabolism, and the respiratory electron transport pathway. DE exposure significantly dysregulated 118 metabolites, resulting in increased levels of triglycerides and fatty acids due to mitochondrial dysfunction as well as increased levels of glucose and oligosaccharides. Consistently, DEP treatment of HepG2 cells led to increased gluconeogenesis and glycogenolysis indicating the ability of the in-vitro approach to model effects induced by DE in vivo. As an example, while gene network analysis of DE livers identified phosphoenolpyruvate carboxykinase 1 (Pck1) as a key driver gene of DE response, DEP treatment of HepG2 cells resulted in increased mRNA expression of Pck1 and glucose production, the latter replicated in mouse primary hepatocytes. Importantly, Pck1 inhibitor mercaptopicolinic acid suppressed DE-induced glucose production in HepG2 cells indicating that DE-induced elevation of hepatic glucose was due in part to upregulation of Pck1 and increased gluconeogenesis.

Short-term exposure to DE induced widespread alterations in metabolic pathways in the liver of ApoE KO mice, especially involving carbohydrate and lipid metabolism, together with mitochondrial dysfunction. Pck1 was identified as a key driver gene regulating increased glucose production by activation of the gluconeogenesis pathway.

Environmental factors have been identified as primary risk factors for type 2 diabetes mellitus (T2DM). However, studies on the association between environmental factors and T2DM have mainly focused on morbidity and mortality, which do not fully reflect the disease burden stemming from air pollution. Therefore, we aimed to evaluate the correlation between air pollution and T2DM, including hospital length of stay (LOS) and costs.

We collected data on patients with T2DM from three healthcare institutions in Xinxiang from 2016-2021. Data on particulate and gaseous pollutants in Xinxiang and daily meteorological data were collected from national databases. The distribution lag nonlinear model was used to evaluate the correlation between air pollution and the number of inpatients with T2DM, LOS, and hospital costs. Subgroup analyses were conducted to identify potential modifying factors.

Overall, 13,797 patients with T2DM were included in our analysis. Within the cumulative lag of 7 days, with every increase of 1 mg/m3 of carbon monoxide (CO) and 10 μg/m3 of 2.5 microns particulate matter, nitrogen dioxide and ozone exhibited significant associations with an increase in diabetes hospitalization risk. CO exhibited adverse effects on LOS on most lag days. Moreover, hospital costs were significantly associated with the attributable fraction of LOS and hospital costs attributed to diabetes.

Exposure to air pollutants increased T2DM risk, imposing significant economic and social burdens in Xinxiang, China. Implementing policies to reduce air pollutant exposure may decrease T2DM admissions, costs, and LOS.

This study investigated the effect of household air pollution on pregnant women with GDM, and assessed the modifying effect of a healthy lifestyle on this relationship. Household solid fuel exposure was defined as using solid fuels (coal, crop residue, and wood) for cooking and heating. Four individually modifiable lifestyle factors were assessed in early pregnancy: body mass index, diet, sleep, and vitamin D supplementation. Multifactorial logistic regression modeling was used to assess the relationship between household air pollution and GDM. A stratified analysis and additive interaction tested the effects of healthy lifestyle scores. After adjusting for potential confounders, we found that using solid fuels for heating was significantly associated with an increased risk of GDM (adjusted OR = 1.60, 95% CI 1.18-2.18). GDM risk showed a decreasing trend in the medium versus the high score group when compared to the low score group, with a consistent trend regardless of household fuel type used (adjusted OR = 0.39, 95% CI 0.27-0.57) (adjusted OR = 0.12, 95% CI 0.05-0.28), respectively. Importantly, when the healthy lifestyle score increased, exposure to household air pollution was no longer associated with a higher GDM risk. There was a negative additive interaction between exposure to household solid fuels exposure and a healthy lifestyle (FERI: -5.10 [-16.48, -2.04]; AP: -1.29 [-2.80, -0.39]; SI: -0.37 [-0.20, -0.67]). We determined that exposure to household air pollution may be an important GDM risk factor. In addition, A healthy lifestyle may have a protective effect on women with GDM exposed to indoor fuel air pollution.

Valid, high-resolution estimates of population-level exposure to air pollutants are necessary for accurate estimation of the association between air pollution and the occurrence or exacerbation of adverse health outcomes such as Chronic Obstructive Pulmonary Disease (COPD).

We produced fine-scale individual-level estimates of ambient concentrations of multiple air pollutants (fine particulate matter [PM2.5], NOX, NO2, and O3) at residences of participants in the Subpopulations and Intermediate Outcomes in COPD Air Pollution (SPIROMICS Air) study, located in seven regions in the US. For PM2.5, we additionally integrated modeled estimates of particulate infiltration based on home characteristics and measured total indoor concentrations to provide comprehensive estimates of exposure levels.

To estimate ambient concentrations, we used a hierarchical high-resolution spatiotemporal model that integrates hundreds of geographic covariates and pollutant measurements from regulatory and study-specific monitors, including ones located at participant residences. We modeled infiltration efficiency based on data on house characteristics, home heating and cooling practices, indoor smoke and combustion sources, meteorological factors, and paired indoor-outdoor pollutant measurements, among other indicators.

Cross-validated prediction accuracy (R2) for models of ambient concentrations was above 0.80 for most regions and pollutants. Particulate matter infiltration efficiency varied by region, from 0.51 in Winston-Salem to 0.72 in Los Angeles, and ambient-source particles constituted a substantial fraction of total indoor PM2.5.

Leveraging well-validated fine-scale approaches for estimating outdoor, ambient-source indoor, and total indoor pollutant concentrations, we can provide comprehensive estimates of short and long-term exposure levels for cohorts undergoing follow-up in multiple different regions.

The intricate connections between health and the environment are often overlooked globally, yet they play a pivotal role in shaping our well-being.

Astonishingly, environmental risk factors contribute to nearly 24% of the global disease burden, underscoring the critical impact of our surroundings on health. At the crossroads of this issue lies Diabetes, a rapidly growing non-communicable disease that highlights the delicate balance between human health and environmental sustainability. This epidemic offers a unique lens through which to explore how environmental factors contribute to the prevalence of Diabetes, revealing the complex interplay at work. Despite growing awareness, healthcare systems worldwide face challenges integrating environmental threats into more effective diabetes care strategies CONCLUSIONS: This perspective highlights the urgent need for collaborative efforts and innovative solutions that address the environmental dimensions of diabetes management. Doing so can build healthier communities and pave the way for a more sustainable future.

Increasing air pollution could undermine human health, but the causal link between air pollution and eye and ear health has not been well-studied. Based on four-week-level records of eye and ear health over 1991-2015 provided by the China Health and Nutrition Survey, we estimate the causal effect of air pollution on eye and ear health. Using two-stage least squares estimation, we find that eye or ear disease possibility rises 1.48% for a 10 μg/m3 increase in four-week average PM2.5 concentration. The impacts can last about 28 weeks and will be insignificant afterward. Females, individuals aged 60 years and over, with high exposure environments, relatively poor economic foundations, and low knowledge levels are more vulnerable to such negative influences. Behavioral channels like more smoking activities and less sleeping activities could partly explain this detrimental effect. Our findings enlighten how to minimize the impact of air pollution and protect public health.

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).

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.

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.

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 is a major health risk factor. Ports might be an understudied source of air pollution.

We conducted a spatial health impact assessment (HIA) of port-sourced air pollution for Barcelona for 2017 at the neighbourhood level. Total NO2 and PM10 and port-sourced NO2, PM10 and PM2.5 concentrations were available through the ADMS-Urban model. Population data, mortality and morbidity data, and risk estimates were obtained. We followed standard HIA methodologies and calculated relative risks and impact fractions for 1.35 million adults living in 73 neighbourhoods.

The city-wide mean total NO2 and PM10 concentrations were 37.88 μg/m3 (range: 19.61-52.17 μg/m3) and 21.68 μg/m3 (range: 17.33-26.69 μg/m3), respectively, of which 7% (range: 2-36%) and 1% (range: 0-7%) were port-sourced, respectively. The mean port-sourced PM2.5 concentration was 0.19 μg/m3 (range: 0.06-1.38 μg/m3). We estimated that 1,123 (PI: 0-3,060) and 1,230 (95% CI: 0-2,566) premature deaths were attributable to total NO2 and PM10, respectively, of which 8.1% (91; PI: 0-264) and 1.1% (13; 95% CI 0-29) were attributable to port-sourced NO2 and PM10, respectively. 20 (95% CI: 15-26) premature deaths were attributable to port-sourced PM2.5. Additionally, a considerable morbidity burden and losses in life expectancy were attributable to port-sourced air pollution. Neighbourhoods closest to the port in the south-east were most adversely affected, gradually decreasing towards the north-west.

The port is an understudied air pollution source in Barcelona with strong health impacts. Cities need local insight into health risk factors, their sources, attributable burdens and distributions for defining targeted policies.

In Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public health problem, the empirical understanding of the actual risks remains limited. We hypothesized that increased exposure to heat and dust, independently and jointly, exacerbates the risk of hospitalization for diabetes patients.

We placed custom-designed particle samplers in Kuwait to collect daily dust samples for 2 years from 2017 to 2019. Samples were analyzed for elemental concentrations to identify and quantify dust pollution days. Temperature data were collected from meteorological stations. We then collected hospitalization data for unplanned diabetic admissions in all public hospitals in Kuwait. We used a case-crossover study design and conditional quasi-Poisson models to compare hospitalization days to control days within the same subject. Finally, we fitted generalized additive models to explore the smoothed interaction between temperature and dust days on diabetes hospitalization.

There were 11 155 unplanned diabetes hospitalizations over the study period. We found that each year, there was an excess of 282 diabetic admissions attributed to hot days (95% CI: -14 to 473). Additionally, for every 10 µg/m3 increase in dust levels, there were about 114 excess diabetic admissions annually (95% CI: 11 to 219). Compared with mild non-dusty days (33°C (0 µg/m3)), hot-dusty days jointly increased the relative risk of diabetic admissions from 1.11 at 42°C (85 µg/m3) to 1.36 at 42°C (150 µg/m3).

Both heat and dust seem to contribute to the increased diabetes morbidity, with combined hot-dusty conditions exacerbating these risks even further.

Ambient particulate matter (PM2.5) is a potential risk factor for metabolic damage to the liver. Epidemiological studies suggest that elevated PM2.5 concentrations cause changes in hepatic metabolism, but there is a lack of laboratory evidence. Here, we aimed to evaluate the effects of PM2.5 exposure on liver metabolism in C57BL/6j female mice (10 months old) and to explore the mechanisms underlying metabolic alterations and differential gene expressions by combining metabolomics and transcriptomics analyses. The metabolomics results showed that PM2.5 exposure notably affected the metabolism of amino acids and organic acids and caused hepatic lipid and bile acid accumulation. The transcriptomic analyses revealed that PM2.5 exposure led to a series of metabolic pathway abnormalities, including steroid biosynthesis, steroid hormone biosynthesis, primary bile acid biosynthesis, etc. Among them, the changes in the bile acid pathway might be one of the causes of liver damage in mice. In conclusion, this study clarified the changes in liver metabolism in mice caused by PM2.5 exposure through combined transcriptomic and metabolomic analyses, revealed that abnormal bile acid metabolism is the key regulatory mechanism leading to metabolic-associated fatty liver disease (MAFLD) in mice, and provided laboratory evidence for further clarifying the effects of PM2.5 on body metabolism.

Diabetes mellitus, a metabolic condition affecting around 537 million individuals worldwide, poses significant challenges, particularly among the elderly population. The etiopathogenesis of type 2 diabetes (T2D) depends on a combination of the effects driven by advancing age, genetic background, and lifestyle habits, e.g. overnutrition. These factors influence the development of T2D differently in men and women, with an obvious sexual dimorphism possibly underlying the diverse clinical features of the disease in different sexes. More recently, environmental pollution, estimated to cause 9 million deaths every year, is emerging as a novel risk factor for the development of T2D. Indeed, exposure to atmospheric pollutants such as PM2.5, O3, NO2, and Persistent Organic Pollutants (POP)s, along with their combination and bioaccumulation, is associated with the development of T2D and obesity, with a 15 % excess risk in case of exposure to very high levels of PM2.5. Similar data are available for plasticizer molecules, e.g. bisphenol A and phthalates, emerging endocrine-disrupting chemicals. Even though causality is still debated at this stage, preclinical evidence sustains the ability of multiple pollutants to affect pancreatic function, promote insulin resistance, and alter lipid metabolism, possibly contributing to T2D onset and progression. In addition, preclinical findings suggest a possible role also for plastic itself in the development of T2D. Indeed, pioneeristic studies evidenced that micro- or nanoplastics (MNP)s, particles in the micro- or nano- range, promote cellular damage, senescence, inflammation, and metabolic disturbances, leading to insulin resistance and impaired glucose metabolism in animal and/or in vitro models. Here we synthesize recent knowledge relative to the association between air-related or plastic-derived pollutants and the incidence of T2D, discussing also the possible mechanistic links suggested by the available literature. We then anticipate the need for future studies in the field of candidate therapeutic strategies limiting pollution-induced damage in preclinical models, such as SGLT-2 inhibitors. We finally postulate that future guidelines for T2D prevention should consider pollution and sex an additional risk factors to limit the diabetes pandemic.

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.

Evidence of the associations between fine particulate matter (PM2.5) and diabetes risk from women of reproductive age, in whom diabetes may have adverse long-term health effects for both themselves and future generations, remains scarce. We therefore examined the associations of long-term PM2.5 exposure with fasting blood glucose (FBG) level and diabetes risk in women of reproductive age in China.

This study included 20,076,032 women age 20-49 years participating in the National Free Preconception Health Examination Project in China between 2010 and 2015. PM2.5 was estimated using a satellite-based model. Multivariate linear and logistic regression models were used to examine the associations of PM2.5 exposure with FBG level and diabetes risk, respectively. Diabetes burden attributable to PM2.5 was estimated using attributable fraction (AF) and attributable number.

PM2.5 showed monotonic relationships with elevated FBG level and diabetes risk. Each interquartile range (27 μg/m3) increase in 3-year average PM2.5 concentration was associated with a 0.078 mmol/L (95% CI 0.077, 0.079) increase in FBG and 18% (95% CI 16%, 19%) higher risk of diabetes. The AF attributed to PM2.5 exposure exceeding 5 μg/m3 was 29.0% (95% CI 27.5%, 30.5%), corresponding to an additional 78.6 thousand (95% CI 74.5, 82.6) diabetes cases. Subgroup analyses showed more pronounced diabetes risks in those who were overweight or obese, age >35 years, less educated, of minority ethnicity, registered as a rural household, and residing in western China.

We found long-term PM2.5 exposure was associated with higher diabetes risk in women of reproductive age in China.

PM2.5, a known public health risk, is increasingly linked to intestinal disorders, however, the mechanisms of its impact are not fully understood.

This study aimed to explore the impact of chronic PM2.5 exposure on intestinal barrier integrity and to uncover the underlying molecular mechanisms.

C57BL/6 J mice were exposed to either concentrated ambient PM2.5 (CPM) or filtered air (FA) for six months to simulate urban pollution conditions. We evaluated intestinal barrier damage, microbial shifts, and metabolic changes through histopathology, metagenomics, and metabolomics. Analysis of the TLR signaling pathway was also conducted.

The mean concentration of PM2.5 in the CPM exposure chamber was consistently measured at 70.9 ± 26.8 μg/m³ throughout the study period. Our findings show that chronic CPM exposure significantly compromises intestinal barrier integrity, as indicated by reduced expression of the key tight junction proteins Occludin and Tjp1/Zo-1. Metagenomic sequencing revealed significant shifts in the microbial landscape, identifying 35 differentially abundant species. Notably, there was an increase in pro-inflammatory nongastric Helicobacter species and a decrease in beneficial bacteria, such as Lactobacillus intestinalis, Lactobacillus sp. ASF360, and Eubacterium rectale. Metabolomic analysis further identified 26 significantly altered metabolites commonly associated with intestinal diseases. A strong correlation between altered bacterial species and metabolites was also observed. For example, 4 Helicobacter species all showed positive correlations with 13 metabolites, including Lactate, Bile acids, Pyruvate and Glutamate. Additionally, increased expression levels of TLR2, TLR5, Myd88, and NLRP3 proteins were noted, and their expression patterns showed a strong correlation, suggesting a possible involvement of the TLR2/5-MyD88-NLRP3 signaling pathway.

Chronic CPM exposure induces intestinal barrier dysfunction, microbial dysbiosis, metabolic imbalance, and activation of the TLR2/5-MyD88-NLRP3 inflammasome. These findings highlight the urgent need for intervention strategies to mitigate the detrimental effects of air pollution on intestinal health and identify potential therapeutic targets.

This study aims to examine the association between the occurrence of diabetic foot and air quality (SO2, CO, NO2, O3). Open data were collected to conduct a big data study. Patient information was gathered from the National Health Insurance Service, and the National Institute of Environmental Science's air quality data were used. A total study population of 347,543 cases were reviewed (case = 13,353, control = 334,190). The lag period from air quality changes to the actual amputation operation was calculated for each factor. The frequency of diabetic foot amputation in each region was identified and analyzed using a distributed lag non-linear model. Gangwon-do showed the highest relative risks (RRs) for SO2 and CO, while Chungcheongnam-do exhibited the highest RR for NO2. Jeju had the highest RR for O3. Regions like Incheon, Busan, and the capital region also showed significant risk increases. These findings emphasize the importance of tailored air quality management to address diabetic foot complications effectively.

Long-term exposure to air pollution has been linked to cancer incidence. However, the evidence is limited regarding the effect of short-term exposure to air pollution on cancer mortality.

This study aimed to investigate associations between short-term exposure to air pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter <10 mm (PM10) and PM2.5) and cancer daily mortality.

This study used air quality, meteorological and daily cancer death data from 2014 to 2019 in Hangzhou, China. Generalised additive models (GAM) with quasi-Poisson regression were used to analyse the associations between air pollutants and cancer mortality with adjustment for confounding factors including time trends, day of week, temperature and humidity. Then, we conducted stratified analyses by sex, age, season and education. In addition, stratified analyses of age, season and education were performed within each sex to determine whether sex difference was modified by such factors.

After adjusting for potential confounders, the GAM results indicated a statistically significant relationship between increased cancer mortality and elevated air pollution concentrations, but only in the female population. For every 10 μg/m3 rise in pollutant concentration, the increased risk of cancer death in females was 6.82% (95% CI 3.63% to 10.10%) for SO2 on lag 03, and 2.02% (95% CI 1.12% to 2.93%) for NO2 on lag 01 and 0.89% (95% CI 0.46% to 1.33%) for PM10 on lag 03 and 1.29% (95% CI 0.64% to 1.95%) for PM2.5 on lag 03. However, no statistically significant association was found among males. Moreover, the differences in effect sizes between males and females were more pronounced during the cold season, among the elderly and among subjects with low levels of education.

Increased cancer mortality was only observed in females with rising concentrations of air pollutants. Further research is required to confirm this sex difference. Advocate for the reduction of air pollutant emissions to protect vulnerable groups.

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Although recent advancements in cancer therapies have extended the lifespan of patients with cancer, they have also introduced new challenges, including chronic health issues such as cardiovascular disease arising from pre-existing risk factors or cancer therapies. Consequently, cardiovascular disease has become a leading cause of non-cancer-related death among cancer patients, driving the rapid evolution of the cardio-oncology field. Environmental factors, particularly air pollution, significantly contribute to deaths associated with cardiovascular disease and specific cancers, such as lung cancer. Despite these statistics, the health impact of air pollution in the context of cardio-oncology has been largely overlooked in patient care and research. Notably, the impact of air pollution varies widely across geographic areas and among individuals, leading to diverse exposure consequences. This review aims to consolidate epidemiologic and preclinical evidence linking air pollution to cardio-oncology while also exploring associated health disparities and environmental justice issues.

We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai.

A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods.

In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 μg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders.

Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.

Epidemiological studies on air pollution, diabetes, and hypertension conflict. This study examined air pollution, diabetes, and hypertension in adults in 11 metropolitan areas of Iran (2012-2016). Local environment departments and the Tehran Air Quality Control Company provided air quality data. The VIZIT website and Stepwise Approach to Chronic Disease Risk Factor Surveillance study delivered chronic disease data. Multiple logistic regression and generalized estimating equations evaluated air pollution-related diabetes and hypertension. In Isfahan, Ahvaz, and Tehran, PM2.5 was linked to diabetes. In all cities except Urmia, Yasuj, and Yazd, PM2.5 was statistically related to hypertension. O3 was connected to hypertension in Ahvaz, Tehran, and Shiraz, whereas NO2 was not. BMI and gender predict hypertension and diabetes. Diabetes, SBP, and total cholesterol were correlated. Iran's largest cities' poor air quality may promote diabetes and hypertension. PM2.5 impacts many cities' outcomes. Therefore, politicians and specialists have to control air pollution.

PM2.5, NO2, and O3 contribute to the development of adverse pregnancy complications. While studies have investigated the independent effects of these exposures, literature on their combined effects is limited. Our objective was to study the multipollutant effects of PM2.5, NO2, and O3 on maternal systemic C-reactive protein (CRP) levels.

We used data from 1170 pregnant women enrolled in the Maternal-Infant Research on Environmental Chemicals Study (MIREC) study in Canada. Air pollution exposures were assigned to each participant based on residential location. CRP was measured in third-trimester blood samples. We fit multipollutant linear regression models and evaluated the effects of air pollutant mixtures (14-day averages) using repeated-holdout Weighted Quantile Sum (WQS) regression and by calculating the Air Quality Health Index (AQHI).

In multipollutant models adjusting for NO2, O3, and green space, each interquartile range (IQR) increase in 14-day average PM2.5 (IQR: 6.9 µg/m3) was associated with 27.1% (95% confidence interval [CI] = 6.2, 50.7) higher CRP. In air pollution mixture models adjusting for green space, each IQR increase in AQHI was associated with 37.7% (95% CI = 13.9, 66.5) higher CRP; and an IQR increase in the WQS index was associated with 78.6% (95% CI = 29.7, 146.0) higher CRP.

PM2.5 has the strongest relationship of the individual pollutants examined with maternal blood CRP concentrations. Mixtures incorporating all three pollutants, assessed using the AQHI and WQS index, showed stronger relationships with CRP compared with individual pollutants and illustrate the importance of conducting multipollutant analyses.

Diabetic retinopathy (DR), one of the most common microvascular complications of diabetes mellitus (DM), is a major contributor of vision impairment and blindness worldwide. Studies have shown that air pollution exposure is adversely associated with DM. However, evidence is scarce regarding how air pollution exposure affects DR. This study aimed to investigate the association between ambient air pollution exposure and DR risk.

The study population was based on the Fujian Eye Study (FJES), an ophthalmologic, epidemiologic survey investigating the eye health condition of residents in Fujian Province from 2018 to 2019. Daily average concentrations of ambient air pollutants (PM2.5, PM10, SO2, NO2, and O3) were acquired from a high-resolution air quality dataset in China from 2013 to 2018. We used a logistic regression model to examine the associations between DR risk and long-term air pollution at various exposure windows.

A total of 2405 out of the 8211 participants were diagnosed with diabetes, among whom 183 had DR. Ambient air pollution, especially particulate matter (i.e., PM2.5 and PM10) and NO2 were positively associated with DR prevalence among all the study subjects. Ambient SO2 and O3 concentrations were not associated with DR prevalence. PM2.5 and NO2 seemed to be borderline significantly associated with increased prevalence of DR in subjects with DM, especially under the model adjusted for sex, age, BMI, SBP, and DBP.

These findings showed that long-term exposure to ambient particulate matter and NO2 was associated with a high DR risk in Fujian province, where ambient air pollution is relatively low.

Diabetes poses a global public health challenge and our understanding of its temporal evolution in China relative to the rest of the world is limited. Our study aims to comprehensively examine the temporal trend of diabetes DALYs in China from a global perspective.

We analyzed data on diabetes incidence, prevalence, and mortality for individuals aged ≥20 years in China and globally from the Global Burden of Disease (GBD) 2019 study. We assessed trends in age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of diabetes in China and globally by estimating annual percentage changes (EAPCs). We employed decomposition analysis to reveal factors driving the trend of diabetes DALYs in China.

During 1990-2019, the number of diabetes patients increased by 160% from 35.14 million to 91.70 million in China. The ASIR of diabetes increased from 249 per 100,000 to 329 per 100,000 in China, which was lower than the global rate (419 per 100,000 in 2019). The EAPC of diabetes incidence was also lower in China compared to the global rate (1.02% vs. 1.57%). Consistently, the age-standardized prevalence rate of diabetes increased from 4788 per 100,000 to 8170 per 100,000 during 1990-2019 in China, which remained lower than the corresponding global rate (8827 per 100,000 in 2019). Further, the ASMR of diabetes increased from 9 per 100,000 to 15 per 100,000 during 1990-2019 in China, which was lower than the corresponding global rate (30 per 100,000 in 2019). However, EAPC of diabetes mortality in China was much higher than the global level (1.75% vs. 1.07%). Globally, the rising diabetes DALYs was predominantly attributed to population growth (55.2%) and epidemiologic changes (24.6%). In comparison, population growth (48.9%) also played an important role in the increasing diabetes DALYs in China, but aging (43.7%) was second major contributor.

Our findings show that diabetes DALYs in China followed a global increasing trend during 1990-2019. Notably, aging has a very substantial contribution to the increase in diabetes DALYs in China in addition to population growth. .

Background: Growing evidence has demonstrated the role of ambient air pollutants in driving diabetes incidence. However, epidemiological evidence linking ozone (O3) exposure to diabetes risk has been scarcely studied in Zhuang adults in China. We aimed to investigate the associations of long-term exposure to O3 with diabetes prevalence and fasting plasma glucose (FPG) and estimate the mediating role of liver enzymes in Zhuang adults. Methods: We recruited 13 843 ethnic minority adults during 2018-2019 based on a cross-sectional study covering nine districts/counties in Guangxi. Generalized linear mixed models were implemented to estimate the relationships between O3 exposure and diabetes prevalence and FPG. Mediation effect models were constructed to investigate the roles of liver enzymes in the associations of O3 exposure with diabetes prevalence and FPG. Subgroup analyses were conducted to identify potential effect modifications. Results: Long-term exposure to O3 was positively associated with diabetes prevalence and FPG levels in Zhuang adults, with an excess risk of 7.32% (95% confidence interval [CI]: 2.56%, 12.30%) and an increase of 0.047 mmol L-1 (95% CI: 0.032, 0.063) for diabetes prevalence and FPG levels, respectively, for each interquartile range (IQR, 1.18 μg m-3) increment in O3 concentrations. Alanine aminotransferase (ALT) significantly mediated 8.10% and 29.89% of the associations of O3 with FPG and diabetes prevalence, respectively, and the corresponding mediation proportions of alkaline phosphatase (ALP) were 8.48% and 30.00%. Greater adverse effects were observed in females, obese subjects, people with a low education level, rural residents, non-clean fuel users, and people with a history of stroke and hypertension in the associations of O3 exposure with diabetes prevalence and/or FPG levels (all P values for interaction < 0.05). Conclusion: Long-term exposure to O3 is related to an increased risk of diabetes, which is partially mediated by liver enzymes in Chinese Zhuang adults. Promoting clean air policies and reducing exposure to environmental pollutants should be a priority for public health policies geared toward preventing diabetes.

Air pollution is an environmental stimulus that may predispose pregnant women to preterm rapture of membrane (PROM). However, the relationship of maternal exposure to air pollutants and PROM is still unclear. To investigate the relationship between the long-term and short-term maternal exposure to air pollution and PROM. We searched all studies published in PubMed, Embase and Web of Science up to February 2024. The studies provided quantitative effect estimates with 95% confidence intervals, for the impact of short-term (<30 days) or long-term (≥30 days) maternal exposure to air pollutants on PROM, preterm PROM (PPROM) or term PROM (TPROM). The odds ratio (OR), risk ratio (RR), or hazard ratio (HR), with 95% confidence intervals was extracted, and RR or HR were deemed as OR because of the low prevalence of PROM. Fixed- or random-effects meta-analyses performed. In total, 17 relevant studies were included. Maternal exposure to PM2.5 in the second trimester increases the risk of PROM (pooled OR = 1.15, 95%CI: 1.05-1.26). Maternal exposure to PM10, NO2, NO, CO and SO2 during pregnancy and short-term maternal exposure to PM2.5, NO2, SO2 and O3 also associate with PROM occurrence. The results of the study show that both long-term maternal exposure in the second or third trimester and short-term maternal exposure to ambient air pollution can increase the risk of PROM.

Type 2 diabetes (T2D) is a major public health concern, and various environmental factors have been associated with the development of this disease. This study aimed to investigate the longitudinal effects of multiple environmental exposures on the risk of incident T2D in a German population-based cohort.

We used data from the KORA cohort study (Augsburg, Germany) and assessed exposure to air pollutants, traffic noise, greenness, and temperature at the participants' residencies. Cox proportional hazard models were used to analyze the associations with incident T2D, adjusting for potential confounders.

Of 7736 participants included in the analyses, 10.5% developed T2D during follow-up (mean: 15.0 years). We found weak or no association between environmental factors and the risk of T2D, with sex and education level significantly modifying the effects of air pollutants.

Our study contributes to the growing body of literature investigating the impact of environmental factors on T2D risks and suggests that the impact of environmental factors may be small.

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.