Ambient Particulate Air Pollution Research Articles

The impacts of reduction in ambient fine particulate air pollution on natural-cause mortality in Taiwan

ABSTRACT Many epidemiologic studies have reported an association between high concentrations of fine particulate matter (PM2.5) and increased mortality rates. Concurrently an association between decreased concentration of these airborne PM2.5 pollutants and a decline in mortality frequency was noted in certain investigations globally; however, only a very few of these studies were conducted in Asia. Taiwan was found to exhibit a 30% decline in ambient PM2.5 levels over the last 20 years. The aim of this ecological investigation was to examine the contribution of annual reductions in ambient PM2.5 to changes in age-standardized natural-cause mortality rates (ASRs) in 65 townships in Taiwan from 2006 to 2020 controlling for lung cancer mortality rate, physician density, and annual household income. Data demonstrated a 0.9/105 fall in adjusted ASR for every 10 ug/m3 reduction in mean annual PM2.5 level in Taiwan during this 14-year period, suggesting a significant association between reductions in ambient PM2.5 levels and decreases in natural-cause mortality rates.

Exposure to source-specific air pollution in residential areas and its association with dementia incidence: a cohort study in Northern Sweden

The aim of this study was to investigate the relationship between source-specific ambient particulate air pollution concentrations and the incidence of dementia. The study encompassed 70,057 participants from the Västerbotten intervention program cohort in Northern Sweden with a median age of 40 years at baseline. High-resolution dispersion models were employed to estimate source-specific particulate matter (PM) concentrations, such as PM10 and PM2.5 from traffic, exhaust, and biomass (mainly wood) burning, at the residential addresses of each participant. Cox regression models, adjusted for potential confounding factors, were used for the assessment. Over 884,847 person-years of follow-up, 409 incident dementia cases, identified through national registers, were observed. The study population’s average exposure to annual mean total PM10 and PM2.5 lag 1–5 years was 9.50 µg/m3 and 5.61 µg/m3, respectively. Increased risks were identified for PM10-Traffic (35% [95% CI 0–82%]) and PM2.5-Exhaust (33% [95% CI − 2 to 79%]) in the second exposure tertile for lag 1–5 years, although no such risks were observed in the third tertile. Interestingly, a negative association was observed between PM2.5-Wood burning and the risk of dementia. In summary, this register-based study did not conclusively establish a strong association between air pollution exposure and the incidence of dementia. While some evidence indicated elevated risks for PM10-Traffic and PM2.5-Exhaust, and conversely, a negative association for PM2.5-Wood burning, no clear exposure–response relationships were evident.

The association between the Canadian active living environments index and glucose metabolism in a Canadian national population study

Biomarkers of glucose metabolism may reflect insulin resistance, a risk factor for diabetes and cardiovascular disease (CVD). Neighborhoods conducive to a physically active lifestyle have the potential to improve these biomarkers. We examined cross-sectional associations between walkability and blood biomarkers of glucose metabolism in 29,649 Canadian Health Measures Survey (CHMS) participants. We used generalized linear mixed models with sampling weights adjusted for province, participants’ age, sex, annual household income and educational attainment, cigarette smoking, environmental tobacco smoke, alcohol consumption, and exposure to ambient fine particulate air pollution (PM2.5). A higher value of the Canadian Active Living Environments Index, a measure of neighborhood walkability, equivalent to the magnitude of its interquartile range (IQR) of 2.4 was significantly associated with percentage differences of −0.48 (95% confidence interval (CI): 0.63, −0.32), −3.17 (95%CI: 5.27, −1.08), −3.88 (95%CI: 6.38, −1.38), and −3.36 (95%CI: 5.25, −1.47) in HbA1C, fasting insulin, HOMA-IR, and HOMA-β, respectively, for all CHMS participants. No significant effects were observed in those ≤16 years old. Canadians living in neighborhoods that facilitate active living have more favorable biomarkers of glucose metabolism, suggesting that the built environment has the potential to improve risk factors for diabetes and CVD in adults.

Causal analysis of air pollution mixtures: estimands, positivity, and extrapolation.

Causal inference for air pollution mixtures is an increasingly important issue with appreciable challenges. When the exposure is a multivariate mixture, there are many exposure contrasts that may be of nominal interest for causal effect estimation, but the complex joint mixture distribution often renders observed data extremely limited in their ability to inform estimates of many commonly defined causal effects. We use potential outcomes to (1) define causal effects of air pollution mixtures, (2) formalize the key assumption of mixture positivity required for estimation, and (3) offer diagnostic metrics for positivity violations in the mixture setting that allow researchers to assess the extent to which data can actually support estimation of mixture effects of interest. For settings where there is limited empirical support, we redefine causal estimands that apportion causal effects according to whether they can be directly informed by observed data versus rely entirely on model extrapolation, isolating key sources of information on the causal effect of an air pollution mixture. The ideas are deployed to assess the ability of a national US data set on the chemical components of ambient particulate matter air pollution to support estimation of a variety of causal mixture effects. This article is part of a Special Collection on Environmental Epidemiology.

Accumulation of Ambient Black Carbon Particles Within Key Memory-Related Brain Regions

Ambient air pollution is a worldwide problem, not only related to respiratory and cardiovascular diseases but also to neurodegenerative disorders. Different pathways on how air pollutants could affect the brain are already known, but direct evidence of the presence of ambient particles (or nanoparticles) in the human adult brain is limited. To examine whether ambient black carbon particles can translocate to the brain and observe their biodistribution within the different brain regions. In this case series a label-free and biocompatible detection technique of nonincandescence-related white light generation was used to screen different regions of biobanked brains of 4 individuals from Belgium with neuropathologically confirmed Alzheimer disease for the presence of black carbon particles. The selected biological specimens were acquired and subsequently stored in a biorepository between April 2013 and April 2017. Black carbon measurements and data analysis were conducted between June 2020 and December 2022. The black carbon load was measured in various human brain regions. A Kruskal-Wallis test was used to compare black carbon loads across these regions, followed by Dunn multiple comparison tests. Black carbon particles were directly visualized in the human brain of 4 individuals (3 women [75%]; mean [SD] age, 86 [13] years). Screening of the postmortem brain regions showed a significantly higher median (IQR) number of black carbon particles present in the thalamus (433.6 [289.5-540.2] particles per mm3), the prefrontal cortex including the olfactory bulb (420.8 [306.6-486.8] particles per mm3), and the hippocampus (364.7 [342.0-448.7] particles per mm3) compared with the cingulate cortex (192.3 [164.2-277.5] particles per mm3), amygdala (217.5 [147.3-244.5] particles per mm3), and the superior temporal gyrus (204.9 [167.9-236.8] particles per mm3). This case series provides evidence that ambient air pollution particles are able to translocate to the human brain and accumulate in multiple brain regions involved in cognitive functioning. This phenomenon may contribute to the onset and development of neurodegenerative disorders.

Improving consistency in estimating future health burdens from environmental risk factors: Case study for ambient air pollution

Future changes in exposure to risk factors should impact mortality rates and population. However, studies commonly use mortality rates and population projections developed exogenously to the health impact assessment model used to quantify future health burdens attributable to environmental risks that are therefore invariant to projected exposure levels. This impacts the robustness of many future health burden estimates for environmental risk factors. This work describes an alternative methodology that more consistently represents the interaction between risk factor exposure, population and mortality rates, using ambient particulate air pollution (PM2.5) as a case study. A demographic model is described that estimates future population based on projected births, mortality and migration. Mortality rates are disaggregated between the fraction due to PM2.5 exposure and other factors for a historic year, and projected independently. Accounting for feedbacks between future risk factor exposure and population and mortality rates can greatly affect estimated future attributable health burdens. The demographic model estimates much larger PM2.5-attributable health burdens with constant 2019 PM2.5 (∼10.8 million deaths in 2050) compared to a model using exogenous population and mortality rate projections (∼7.3 million), largely due to differences in mortality rate projection methods. Demographic model-projected PM2.5-attributable mortality can accumulate substantially over time. For example, ∼71 million more people are estimated to be alive in 2050 when WHO guidelines (5 µg m−3) are achieved compared to constant 2019 PM2.5 concentrations. Accounting for feedbacks is more important in applications with relatively high future PM2.5 concentrations, and relatively large changes in non-PM2.5 mortality rates.

Penalized distributed lag interaction model: Air pollution, birth weight, and neighborhood vulnerability

AbstractMaternal exposure to air pollution during pregnancy has a substantial public health impact. Epidemiological evidence supports an association between maternal exposure to air pollution and low birth weight. A popular method to estimate this association while identifying windows of susceptibility is a distributed lag model (DLM), which regresses an outcome onto exposure history observed at multiple time points. However, the standard DLM framework does not allow for modification of the association between repeated measures of exposure and the outcome. We propose a distributed lag interaction model that allows modification of the exposure‐time‐response associations across individuals by including an interaction between a continuous modifying variable and the exposure history. Our model framework is an extension of a standard DLM that uses a cross‐basis, or bi‐dimensional function space, to simultaneously describe both the modification of the exposure‐response relationship and the temporal structure of the exposure data. Through simulations, we showed that our model with penalization out‐performs a standard DLM when the true exposure‐time‐response associations vary by a continuous variable. Using a Colorado, USA birth cohort, we estimated the association between birth weight and ambient fine particulate matter air pollution modified by an area‐level metric of health and social adversities from Colorado EnviroScreen.

Association between Ambient Particulate Air Pollution and Soluble Biomarkers of Endothelial Function: A Meta-Analysis.

The burden of cardiovascular diseases caused by ambient particulate air pollution is universal. An increasing number of studies have investigated the potential effects of exposure to particulate air pollution on endothelial function, which is one of the important mechanisms for the onset and development of cardiovascular disease. However, no previous study has conducted a summary analysis of the potential effects of particulate air pollution on endothelial function. To summarize the evidence for the potential effects of short-term exposure to ambient particulate air pollution on endothelial function based on existing studies. A systematic literature search on the relationship between ambient particulate air pollution and biomarkers of endothelial function including endothelin-1 (ET-1), E-selectin, intercellular cell adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1) was conducted in PubMed, Scopus, EMBASE, and Web of Science up to 20 May 2023. Subsequently, a meta-analysis was conducted using a random effects model. A total of 18 studies were included in this meta-analysis. A 10 μg/m3 increase in short-term exposure to ambient PM2.5 was associated with a 1.55% (95% CI: 0.89%, 2.22%) increase in ICAM-1 and a 1.97% (95% CI: 0.86%, 3.08%) increase in VCAM-1. The associations of ET-1 (0.22%, 95% CI: -4.94%, 5.65%) and E-selectin (3.21%, 95% CI: -0.90% 7.49%) with short-term exposure to ambient PM2.5 were statistically insignificant. Short-term exposure to ambient PM2.5 pollution may significantly increase the levels of typical markers of endothelial function, including ICAM-1 and VCAM-1, suggesting potential endothelial dysfunction following ambient air pollution exposure.

The effects of ambient particulate matter air pollution on platelets and hemostasis.

Elevated ambient pollution exposure is potentially linked to thromboembolism. However, the mechanisms by which particulate matter (PM) interferes with the balance of hemostatic system remain unclear. This study investigates PM-mediated hemostatic changes in individuals across unique seasonal variations of ambient pollution. This prospective study was conducted between February and July 2020 during alterations in ambient pollution in Chiang Mai, Thailand. Blood tests from 30 healthy subjects were assessed at four-week intervals, four times in total. Various coagulation tests, including prothrombin time (PT), activated partial thromboplastin time (aPTT), von Willebrand factor (vWF), platelet count, and platelet functions, were evaluated. A mixed-effects model was used to analyze the impact of high PM2.5 and PM10 on hemostatic parameters. Thirty male subjects with mean age of 38.9 ± 8.2 years, were included. High levels of PM2.5 and PM10 were significantly associated with PT shortening, with no such effect observed in aPTT. PM2.5 and PM10 values also positively correlated with vWF function, while vWF antigen levels remained unchanged. Soluble P-selectin showed a strong positive association with PM2.5 and PM10 levels. Platelet function analysis revealed no correlation with PM values. Short-term exposure to elevated PM2.5 and PM10 concentrations was linked to shortened PT and enhanced vWF function in healthy individuals. Exploring the impact of these changes on clinically relevant thrombosis is crucial. Additional studies on the pathogenesis of pollution-related thrombosis are warranted for maintaining good health.

Metabolic profiles associated with exposure to ambient particulate air pollution: findings from the Betula cohort.

Air pollution is a significant contributor to morbidity and mortality globally and has been linked to an increased risk of dementia. Previous studies within the Betula cohort in Northern Sweden have demonstrated associations between air pollution and dementia, as well as distinctive metabolomic profiles in dementia patients compared to controls. This study aimed to investigate whether air pollution is associated with quantitative changes in metabolite levels within this cohort, and whether future dementia status would modify this association. Both short-term and long-term exposure to air pollution were evaluated using high spatial resolution models and measured data. Air pollution from vehicle exhaust and woodsmoke were analyzed separately. Metabolomic profiling was conducted on 321 participants, including 58 serum samples from dementia patients and a control group matched for age, sex, and education level, using nuclear magnetic resonance spectroscopy. No statistically significant associations were found between any metabolites and any measures of short-term or long-term exposure to air pollution. However, there were trends potentially suggesting associations between both long-term and short-term exposure to air pollution with lactate and glucose metabolites. Notably, these associations were observed despite the lack of correlation between long-term and short-term air pollution exposure in this cohort. There were also tendencies for associations between air pollution from woodsmoke to be more pronounced in participants that would later develop dementia, suggesting a potential effect depending on urban/rural factors. While no significant associations were found, the trends observed in the data suggest potential links between air pollution exposure and changes in lactate and glucose metabolites. These findings provide some new insights into the link between air pollution and metabolic markers in a low-exposure setting. However, addressing existing limitations is crucial to improve the robustness and applicability of future research in this area. The pronounced associations in participants who later developed dementia may indicate an influence of urban/rural factors, warranting further investigation.

Abstract 12441: Ambient Fine Particulate Matter Air Pollution but Not Ozone is Associated With Elevated Risk of All-Cause Hospitalization in Patients With a Prior Diagnosis of Atrial Fibrillation

Introduction: Short-term increases (days to weeks) in fine particulate matter (PM 2.5 ) air pollution are associated with atrial fibrillation (AF) episodes. We previously reported that PM 2.5 was not associated with severe AF measured as emergency or inpatient hospitalization for the primary diagnosis of AF. Mild AF, though, may influence all-cause hospitalizations. This study evaluated if short-term increases in PM 2.5 and ozone were associated with all-cause hospitalization at 11 Intermountain Health hospitals in patients with AF, and if this differed between wildfire (June-Oct.) and winter inversion (Nov.-March) seasons. Methods: Patients carrying an AF diagnosis (N=347,157) were evaluated for all-cause hospitalization and, secondarily, AF hospitalization (N=25,601) and first AF diagnosis (N=77,893). PM 2.5 levels were measured from January 1, 1999 to March 31, 2022 (ozone: 2006-2022) in subjects residing on Utah’s Wasatch Front. Using the case-crossover design that matched individual-level characteristics, Poisson regression also adjusted for weather variables. Results: Mean age was 72±15 years and 51.0% were female. Overall, PM 2.5 increases at a lag of 0 days, 1 day, 3-day moving average (mAvg) (days 0-2), and 7-day mAvg (days 0-6) were associated with all-cause hospitalization [respectively: odds ratio (OR)=1.010, 1.008, 1.011, 1.009 per +10 μg/m 3 ; p=0.0004, 0.006, 0.0004, 0.028]. Associations differed by seasons (Figure). Regressions entering both ozone and PM 2.5 mildly increased PM 2.5 ORs for all-cause hospitalization. PM 2.5 was not associated with first AF diagnosis. Increases in ozone were not associated with higher risk of any outcome. Conclusions: Short-term increases in PM 2.5 air pollution were associated with all-cause hospitalization in patients with a prior AF diagnosis. Lag structure varied for wildfire and inversion seasons, with greater effect sizes in wildfire season. Increases in ozone did not associate with elevated risk.

Long-term exposure to air pollution and incidence of mental disorders. A large longitudinal cohort study of adults within an urban area

BackgroundRecent epidemiological evidence suggests associations between air pollution exposure and major depressive disorders, but the literature is inconsistent for other mental illnesses. We investigated the associations of several air pollutants and road traffic noise with the incidence of different categories of mental disorders in a large population-based cohort. MethodsWe enrolled 1,739,277 individuals 30 + years from the 2011 census in Rome, Italy, and followed them up until 2019. In detail, we analyzed 1,733,331 participants (mean age 56.43 +/- 15.85 years; 54.96 % female) with complete information on covariates of interest. We excluded subjects with prevalent mental disorders at baseline to evaluate the incidence (first hospitalization or co-pay exemption) of schizophrenia spectrum disorders, bipolar, anxiety, personality, or substance use disorders. In addition, we studied subjects with first prescriptions of antipsychotics, antidepressants, and mood stabilizers. Annual average concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO₂), Black Carbon (BC), ultrafine particles (UFP), and road traffic noise were assigned to baseline residential addresses. We applied Cox regression models adjusted for individual and area-level covariates. ResultsEach interquartile range (1.13 µg/m3) increase in PM2.5 was associated with a hazard ratio (HR) of 1.070 (95 % confidence interval [CI]: 1.017, 1.127) for schizophrenia spectrum disorder, 1.135 (CI: 1.086, 1.186) for depression, 1.097 (CI: 1.030, 1.168) for anxiety disorders. Positive associations were also detected for BC and UFP, and with the three categories of drug prescriptions. Bipolar, personality, and substance use disorders did not show clear associations. The effects were highest in the age group 30–64 years, except for depression. ConclusionsLong-term exposure to ambient air pollution, especially fine and ultrafine particles, was associated with increased risks of schizophrenia spectrum disorder, depression, and anxiety disorders. The association of the pollutants with the prescriptions of specific drugs increases the credibility of the results.

Ambient particulate matter air pollution exposure and ovarian cancer incidence in the USA: An ecological study.

To investigate associations between air particulate matter of ≤2.5 μm in diameter (PM2.5 ) and ovarian cancer. County-level ecological study. Surveillance, epidemiology, and end results from a collection of state-level cancer registries across 744 counties. Data from the Environmental Protection Agency's network for PM2.5 monitoring was used to calculate trailing 5- and 10-year PM2.5 county-level values. County-level data on demographic characteristics were obtained from the American Community Survey. A total of 98 751 patients with histologically confirmed ovarian cancer as a primary malignancy from 2000 to 2016. Generalised linear regression models were developed to estimate the association between PM2.5 and PM10 levels, over 5- and 10-year periods of exposure, and ovarian cancer risk, after accounting for county-level covariates. Risk ratios for associations between ovarian cancer (both overall and specifically epithelial ovarian cancer) and PM2.5 levels. For the 744 counties included, the average PM2.5 level from 1990 through 2018 was 11.75 μg/m3 (SD = 3.7) and the average PM10 level was 22.7 μg/m3 (SD = 5.7). After adjusting for county-level covariates, the overall annualised ovarian cancer incidence was significantly associated with increases in 5-year PM2.5 (RR = 1.11 per 10 units (μg/m3 ) increase, 95% CI 1.06-1.16). Similarly, when the analysis was limited to epithelial cell tumours and adjusted for county-level covariates there was a significant association with trailing 5-year PM2.5 exposure models (RR = 1.12 per 10 units increase, 95% CI 1.08-1.17). Likewise, 10-year PM2.5 exposure was associated with ovarian cancer overall and with epithelial ovarian cancer. Higher county-level ambient PM2.5 levels are associated with 5- and 10-year incidences of ovarian cancer, as measurable in an ecological study.

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

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

The impacts of reduction in ambient fine particulate (PM2.5) air pollution on life expectancy in Taiwan

The impacts of reduction in ambient fine particulate (PM2.5) air pollution on life expectancy in Taiwan

Residential wood burning in two Swedish cohorts: Public health implications of source-specific particulate ambient air pollution

Residential wood burning in two Swedish cohorts: Public health implications of source-specific particulate ambient air pollution

Pre-admission ambient air pollution and blood soot particles predict hospitalisation outcomes in COVID-19 patients.

Air pollution exposure is one of the major risk factors for aggravation of respiratory diseases. We investigated whether exposure to air pollution and accumulated black carbon (BC) particles in blood were associated with coronavirus disease 2019 (COVID-19) disease severity, including the risk for intensive care unit (ICU) admission and duration of hospitalisation. From May 2020 until March 2021, 328 hospitalised COVID-19 patients (29% at intensive care) were recruited from two hospitals in Belgium. Daily exposure levels (from 2016 to 2019) for particulate matter with aerodynamic diameter <2.5 µm and <10 µm (PM2.5 and PM10, respectively), nitrogen dioxide (NO2) and BC were modelled using a high-resolution spatiotemporal model. Blood BC particles (internal exposure to nano-sized particles) were quantified using pulsed laser illumination. Primary clinical parameters and outcomes included duration of hospitalisation and risk of ICU admission. Independent of potential confounders, an interquartile range (IQR) increase in exposure in the week before admission was associated with increased duration of hospitalisation (PM2.5 +4.13 (95% CI 0.74-7.53) days, PM10 +4.04 (95% CI 1.24-6.83) days and NO2 +4.54 (95% CI 1.53-7.54) days); similar effects were observed for long-term NO2 and BC exposure on hospitalisation duration. These effect sizes for an IQR increase in air pollution on hospitalisation duration were equivalent to the effect of a 10-year increase in age on hospitalisation duration. Furthermore, for an IQR higher blood BC load, the OR for ICU admission was 1.33 (95% CI 1.07-1.65). In hospitalised COVID-19 patients, higher pre-admission ambient air pollution and blood BC levels predicted adverse outcomes. Our findings imply that air pollution exposure influences COVID-19 severity and therefore the burden on medical care systems during the COVID-19 pandemic.

The influence of ambient air pollution on the transmission of tuberculosis in Jiangsu, China.

In this paper, based on the statistical data, we investigate the effects of long-term exposure to ambient particulate air pollution on the transmission dynamics of tuberculosis (TB) in Jiangsu, China by studying the threshold dynamics of the TB epidemic model via the statistical data analytically and numerically. The basic reproduction number reveals that TB in Jiangsu, China is an endemic disease and will persist for a long time. And the numerical results show that, in order to control the TB in Jiangsu effectively, we must decrease the depuration coefficient of PM10 in the body, the proportion of TB symptomatic infectious by direct transmission, the reactivation rate of the pre-symptomatic infectious and the effect coefficient of PM10 and MTB inhaled of TB transmission, and increase the uptake coefficient, the recovery rate of the symptomatic/pre-symptomatic infectious and the influence coefficient of PM10 on the body of mortality. Our study shows that PM10 is closely related to the incidence of TB, and the effective control efforts are suggested to focus on increasing close-contact distance and wearing protective mask to decrease the influence of PM10 on the TB transmission, which may shed a new light on understanding the environmental drivers to TB.

Exposure to ultrafine particles and cognitive decline among older people in the United States

BackgroundSome studies suggest that ambient particulate air pollution is associated with cognitive decline. However, the findings are mixed, and there is no relevant research examining the influences of ultrafine particles (UFP), which may have more toxicity than larger particles. We therefore conducted this study to investigate whether residential UFP exposure is associated with cognitive decline using data from the Alzheimer's Disease Research Centers in the United States. MethodsThis is a longitudinal study of participants who were aged 65 years and older and had normal cognitive status at baseline. Residential UFP exposure, expressed as particle number concentrations (PNC), was assessed in 2016–2017 using a nationwide land use regression model, and was assigned to each participant using their 3-digit residential ZIP codes. Cognitive functions including memory, attention, language, executive function, and global function were assessed annually using 15 neuropsychological tests from March 2015 to February 2022. Linear mixed-effects models were used to examine the associations after adjustment for covariates including baseline age, sex, APOE ε4 status, race, education, smoking status, history of diabetes, quartiles of neighborhood median household income, and interaction terms of follow-up time with each covariate. ResultsThis study included 5646 participants (mean age 76 years, 65% female). On average, each participant had 4 annual visits. When PNC was treated as a continuous variable, there were no statistically or clinically significant changes in annual decline of each cognitive function in relation to an interquartile range elevation in PNC (4026 particles/cm3). Similarly, when PNC was treated as a categorical variable including five exposure groups, there were no linear exposure-response trends in annual decline of each cognitive function across the five exposure groups. ConclusionsThis study found no meaningful associations between residential UFP exposure and cognitive decline in global and domain-specific functions. There is a need for further research that assigns UFP exposure at a finer geographic scale.

Global burden of type 2 diabetes in adolescents and young adults, 1990-2019: systematic analysis of the Global Burden of Disease Study 2019

ObjectiveTo estimate the global burden of type 2 diabetes in adolescents and young adults (aged 15-39 years) from 1990 to 2019.DesignSystematic analysis.Data sourceGlobal Burden of Disease Study 2019. Participants aged...