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Exposure to ultrafine particles and cognitive decline among older people in the United States
Abstract
Background:
Some 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.
Methods:
This 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 e4 status, race, education, smoking status, history of diabetes, and quartiles of neighborhood median household income.
Results:
This 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 statistically significant differences in annual decline of each cognitive function across the five exposure groups.
Conclusions:
This 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.
... Limited work done so far has reported negative health implications of UFPs. Some recent studies have suggested an association between human neurodegenerative diseases and UFPs (Amouei Torkmahalleh et al., 2022;Calderón-Garcidueñas & Ayala, 2022;Flood-Garibay et al., 2023;Gan et al., 2023). Amouei Torkmahalleh et al. (2022) studied the effect of UFPs emitted from a gas stove on healthy adults using electroencephalography for brain response. ...
Previous toxicological research has suggested the potential neurotoxicity of ultrafine particulate matter (UFP, particles ≤0.1 μm in diameter). However, evidence from human beings, particularly regarding the neurodevelopmental impacts of UFP, is still limited. We enrolled 11,230 children aged 3–5.5 years from Shanghai, China. Residential UFP exposure was assessed by a land use regression model with a spatial resolution of 50 m. The neurodevelopment of preschoolers was assessed using the Ages & Stages Questionnaires, Third Edition. Generalized linear mixed models were used to examine the associations of UFP exposure with risk of suspected neurodevelopmental delay. For our participants, the median of UFP exposure was 24,478 [interquartile range (IQR): 22,773–27,657] number per cubic centimeter. We observed that each IQR increase in UFP was associated with 8% [odds ratio (OR), 1.08; 95% CI, 1.02–1.15] and 12% (OR, 1.12; 95% CI, 1.02–1.22) higher odds of suspected neurodevelopmental delay in gross and fine motor skills, respectively. These associations show a monotonically upward dose–response manner across overall UFP concentrations. Our findings suggest that UFP exposure during early childhood is associated with an increased risk of neurodevelopmental delay among Chinese preschoolers.
Over the past few decades, numerous environmental chemicals from solvents to pesticides have been suggested to be involved in the development and progression of neurodegenerative diseases. Most of the evidence has accumulated from occupational or cohort studies in humans or laboratory research in animal models, with a range of chemicals being implicated. What has been missing is a systematic approach analogous to genome-wide association studies, which have identified dozens of genes involved in Alzheimer's disease, Parkinson's disease and other neurodegenerative diseases. Fortunately, it is now possible to study hundreds to thousands of chemical features under the exposome framework. This Perspective explores how advances in mass spectrometry make it possible to generate exposomic data to complement genomic data and thereby better understand neurodegenerative diseases.
Little is known about the impact of long-term ambient air pollution (AP) and noise exposure on change in cognitive function over years in the elderly. In this study, we wanted to examine the association between long-term exposure to AP and noise with the rate of cognitive decline in a population aged 50 and older and susceptible groups with mild cognitive impairment or at a genetically higher risk of Alzheimer's disease (Apolipoprotein E ε4 positive). Participants in the German population-based Heinz Nixdorf Recall study carried out five neuropsychological tests. Individual tests scores at the first (T1 = 2006-2008) and second (T2 = 2011-2015) follow-up for each test were used as outcomes after standardization using predicted means adjusted for age and education. Global cognitive score (GCS) was defined as sum of five standardized scores of individual tests. Long-term exposures to particulate matter (PM2.5, PM10, PM2.5 absorbance), accumulation mode particle number (PNacc), a proxy of ultrafine particles, and nitrogen dioxide were estimated by the land-use regression and chemistry transport models. Noise exposures were assessed as outdoor weighted nighttime road traffic noise (Lnight) means. We performed linear regression analyses adjusted for sex, age, individual and neighborhood socio-economic status, and lifestyle variables. Effect modification in vulnerable groups was estimated using multiplicative interaction terms between exposure and a modifier. Overall, 2554 participants (49.5% men, median age is 63 (IQR = 12)) were included. We found weak associations between higher exposure to PM10 and PM2.5 with faster decline in the immediate verbal memory test. Adjustment for potential confounders and for co-exposures did not change the results. We saw no effects on GCS, and no effect of noise exposure. In susceptible groups, higher AP and noise exposure were tended to be associated with faster decline in GCS. Our results suggest that AP exposure may accelerate cognitive decline in older ages, particularly in susceptible groups.
Background
Growing epidemiological evidence suggests an adverse relationship between exposure to air pollutants and cognitive decline. However, there is still some heterogeneity in the findings, with inconsistent results depending on the pollutant and the cognitive domain considered. We wanted to determine whether air pollution was associated with global and domain-specific cognitive decline.
Methods
This analysis used data from the French Three-City prospective cohort (participants aged 65 and older at recruitment and followed for up to 12 years). A battery of cognitive tests was administered at baseline and every 2 years, to assess global cognition (Mini Mental State Examination, MMSE), visual memory (Benton Visual Retention Test), semantic fluency (Isaacs Set Test) and executive functions (Trail Making Tests A and B). Exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and black carbon (BC) at the participants’ residential address during the 5 years before the baseline visit was estimated with land use regression models. Linear mixed models and latent process mixed models were used to assess the association of each pollutant with global and domain-specific cognitive decline.
Results
The participants’ (n = 6380) median age was 73.4 years (IQR: 8.0), and 61.5% were women. At baseline, the median MMSE score was 28 (IQR: 3). Global cognition decline, assessed with the MMSE, was slightly accelerated among participants with higher PM2.5 exposure: one IQR increment in PM2.5 (1.5 µg/m³) was associated with accelerated decline (β: −0.0060 [−0.0112; −0.0007] standard unit per year). Other associations were inconsistent in direction, and of small magnitude.
Conclusion
In this large population-based cohort, higher PM2.5 exposure was associated with accelerated global cognition decline. We did not detect any significant association for the specific cognitive domains or the other pollutants. Evidence concerning PM2.5 effects on cognition is growing, but more research is needed on other ambient air pollutants.
Background
Late-life exposure to ambient air pollution is a modifiable risk factor for dementia, but epidemiological studies have shown inconsistent evidence for cognitive decline. Air quality (AQ) improvement has been associated with improved cardiopulmonary health and decreased mortality, but to the best of our knowledge, no studies have examined the association with cognitive function. We examined whether AQ improvement was associated with slower rate of cognitive decline in older women aged 74 to 92 years.
Methods and findings
We studied a cohort of 2,232 women residing in the 48 contiguous US states that were recruited from more than 40 study sites located in 24 states and Washington, DC from the Women’s Health Initiative (WHI) Memory Study (WHIMS)-Epidemiology of Cognitive Health Outcomes (WHIMS-ECHO) study. They were predominantly non-Hispanic White women and were dementia free at baseline in 2008 to 2012. Measures of annual (2008 to 2018) cognitive function included the modified Telephone Interview for Cognitive Status (TICSm) and the telephone-based California Verbal Learning Test (CVLT). We used regionalized universal kriging models to estimate annual concentrations (1996 to 2012) of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) at residential locations. Estimates were aggregated to the 3-year average immediately preceding (recent exposure) and 10 years prior to (remote exposure) WHIMS-ECHO enrollment. Individual-level improved AQ was calculated as the reduction from remote to recent exposures. Linear mixed effect models were used to examine the associations between improved AQ and the rates of cognitive declines in TICSm and CVLT trajectories, adjusting for sociodemographic (age; geographic region; race/ethnicity; education; income; and employment), lifestyle (physical activity; smoking; and alcohol), and clinical characteristics (prior hormone use; hormone therapy assignment; depression; cardiovascular disease (CVD); hypercholesterolemia; hypertension; diabetes; and body mass index [BMI]). For both PM2.5 and NO2, AQ improved significantly over the 10 years before WHIMS-ECHO enrollment. During a median of 6.2 (interquartile range [IQR] = 5.0) years of follow-up, declines in both general cognitive status (β = −0.42/year, 95% CI: −0.44, −0.40) and episodic memory (β = −0.59/year, 95% CI: −0.64, −0.54) were observed. Greater AQ improvement was associated with slower decline in TICSm (βPM2.5improvement = 0.026 per year for improved PM2.5 by each IQR = 1.79 μg/m³ reduction, 95% CI: 0.001, 0.05; βNO2improvement = 0.034 per year for improved NO2 by each IQR = 3.92 parts per billion [ppb] reduction, 95% CI: 0.01, 0.06) and CVLT (βPM2.5 improvement = 0.070 per year for improved PM2.5 by each IQR = 1.79 μg/m³ reduction, 95% CI: 0.02, 0.12; βNO2improvement = 0.060 per year for improved NO2 by each IQR = 3.97 ppb reduction, 95% CI: 0.005, 0.12) after adjusting for covariates. The respective associations with TICSm and CVLT were equivalent to the slower decline rate found with 0.9 to 1.2 and1.4 to 1.6 years of younger age and did not significantly differ by age, region, education, Apolipoprotein E (ApoE) e4 genotypes, or cardiovascular risk factors. The main limitations of this study include measurement error in exposure estimates, potential unmeasured confounding, and limited generalizability.
Conclusions
In this study, we found that greater improvement in long-term AQ in late life was associated with slower cognitive declines in older women. This novel observation strengthens the epidemiologic evidence of an association between air pollution and cognitive aging.
Background Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors.
Background
Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors.
Methods
We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis.
Findings
We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4–65·1) million cases globally in 2019 to 152·8 (130·8–175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [–7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64–1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52–1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41–67]) and western Europe (74% [58–90]), and the largest in north Africa and the Middle East (367% [329–403]) and eastern sub-Saharan Africa (357% [323–395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia.
Interpretation
Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia.
Background:
Recently, it has been suggested that up to a third of the dementia cases might be preventable. While prevention is always better than cure, this is particularly important in the field of dementia, as current interventions are not able to modify the disease. This article revises the evidence "for" and "against" dementia primary prevention.
Discussion:
Evidence "for" is sustained by the Lancet Commission on Dementia Prevention, Intervention and Care that noted a reduction of age-related incidence of dementia in high-income countries. Based on results from large cohort studies and using population attributable risk, the commission concluded that up to 35% of dementia cases could be prevented by modifying nine risk factors: low education, midlife hearing loss, obesity, hypertension, late-life depression, smoking, physical inactivity, diabetes, and social isolation. In this life course conceptual framework, modifications of risk factors can influence dementia decades before clinical disease onset. However, evidence "against" is supported by large randomized controlled trials (RCT, > 250 participants per arm, minimum of 6 months follow-up), primarily set to prevent dementia using lifestyle interventions that have shown modest or negative results. The 2017 National Academy of Medicine report concluded that the current evidence is limited and there are no specific interventions to warrant a public health recommendation for dementia prevention. Multiple pathological pathways are involved in the development of dementia which are theoretically treatable by managing midlife hearing loss and hypertension, and with physical exercise and education, as suggested by robust observational studies. However, evidence from large clinical trials is not conclusive to support that a third of dementia cases might be prevented. Current initiatives testing the effect of lifestyle interventions in larger clinical trials may help to settle this debate.
Ultrafine particles (PM0.1), which are present in the air in large numbers, pose a health risk. They generally enter the body through the lungs but translocate to essentially all organs. Compared to fine particles (PM2.5), they cause more pulmonary inflammation and are retained longer in the lung. Their toxicity is increased with smaller size, larger surface area, adsorbed surface material, and the physical characteristics of the particles. Exposure to PM0.1 induces cough and worsens asthma. Metal fume fever is a systemic disease of lung inflammation most likely caused by PM0.1. The disease is manifested by systemic symptoms hours after exposure to metal fumes, usually through welding. PM0.1 cause systemic inflammation, endothelial dysfunction, and coagulation changes that predispose individuals to ischemic cardiovascular disease and hypertension. PM0.1 are also linked to diabetes and cancer. PM0.1 can travel up the olfactory nerves to the brain and cause cerebral and autonomic dysfunction. Moreover, in utero exposure increases the risk of low birthweight. Although exposure is commonly attributed to traffic exhaust, monitored students in Ghana showed the highest exposures in a home near a trash burning site, in a bedroom with burning coils employed to abate mosquitos, in a home of an adult smoker, and in home kitchens during domestic cooking. The high point-source production and rapid redistribution make incidental exposure common, confound general population studies and are compounded by the lack of global standards and national reporting. The potential for PM0.1 to cause harm to health is great, but their precise role in many illnesses is still unknown and calls for more research.
Introduction:
In 2015, the US Alzheimer's Disease Centers (ADC) implemented Version 3 of the Uniform Data Set (UDS). This paper describes the history of Version 3 development and the UDS data that are freely available to researchers.
Methods:
UDS Version 3 was developed after years of coordination between the National Institute on Aging-appointed Clinical Task Force (CTF), clinicians from ∼30 ADCs, and the National Alzheimer's Coordinating Center (NACC). The CTF recognized the need for updates to align with the state of the science in dementia research, while being flexible to the diverse needs and diseases studied at the ADCs. Version 3 also developed a nonproprietary neuropsychological battery.
Results:
This paper focuses on the substantial Version 3 changes to the UDS forms related to clinical diagnosis and characterization of clinical symptoms to match updated consensus-based diagnostic criteria. Between March 2015 and March 2018, 4820 participants were enrolled using UDS Version 3. Longitudinal data were available for 25,337 of the 37,568 total participants using all UDS versions.
Discussion:
The results from utilization of the UDS highlight the possibility for numerous research institutions to successfully collaborate, produce, and use standardized data collection instruments for over a decade.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.
Observational studies have shown consistently increased likelihood of dementia or mild cognitive impairment diagnoses in people with higher air pollution exposure history, but evidence has been less consistent for associations with cognitive test performance. We estimated the association between baseline neighbourhood-level exposure to airborne pollutants (particulate matter and nitrogen oxides) and (1) cognitive test performance at baseline and (2) cognitive score change between baseline and 2.8-year follow-up, in 86,759 middle- to older-aged adults from the UK Biobank general population cohort. Unadjusted regression analyses indicated small but consistent negative associations between air pollutant exposure and baseline cognitive performance. Following adjustment for a range of key confounders, associations were inconsistent in direction and of very small magnitude. The largest of these indicated that 1 interquartile range higher air pollutant exposure was associated on average with 0.35% slower reaction time (95% CI: 0.13, 0.57), a 2.92% higher error rate on a visuospatial memory test (95% CI: 1.24, 4.62), and numeric memory scores that were 0.58 points lower (95% CI: -0.96, -0.19). Follow-up analyses of cognitive change scores did not show evidence of associations. The findings indicate that in this sample, which is five-fold larger than any previous cross-sectional study, the association between air pollution exposure and cognitive performance was weak. Ongoing follow-up of the UK Biobank cohort will allow investigation of longer-term associations into old age, including longitudinal tracking of cognitive performance and incident dementia outcomes.
Background:
Few longitudinal studies have examined the association between ultrafine particulate matter (UFP, particles < 0.1 μm aerodynamic diameter) exposure and cardiovascular disease (CVD) risk factors. We used data from 791 adults participating in the longitudinal Boston Puerto Rican Health Study (Massachusetts, USA) between 2004 and 2015 to assess whether UFP exposure was associated with blood pressure and high sensitivity C-reactive protein (hsCRP, a biomarker of systemic inflammation).
Methods:
Residential annual average UFP exposure (measured as particle number concentration, PNC) was assigned using a model accounting for spatial and temporal trends. We also adjusted PNC values for participants' inhalation rate to obtain the particle inhalation rate (PIR) as a secondary exposure measure. Multilevel linear models with a random intercept for each participant were used to examine the association of UFP with blood pressure and hsCRP.
Results:
Overall, in adjusted models, an inter-quartile range increase in PNC was associated with increased hsCRP (β = 6.8; 95% CI = - 0.3, 14.0%) but not with increased systolic blood pressure (β = 0.96; 95% CI = - 0.33, 2.25 mmHg), pulse pressure (β = 0.70; 95% CI = - 0.27, 1.67 mmHg), or diastolic blood pressure (β = 0.55; 95% CI = - 0.20, 1.30 mmHg). There were generally stronger positive associations among women and never smokers. Among men, there were inverse associations of PNC with systolic blood pressure and pulse pressure. In contrast to the primary findings, an inter-quartile range increase in the PIR was positively associated with systolic blood pressure (β = 1.03; 95% CI = 0.00, 2.06 mmHg) and diastolic blood pressure (β = 1.01; 95% CI = 0.36, 1.66 mmHg), but not with pulse pressure or hsCRP.
Conclusions:
We observed that exposure to PNC was associated with increases in measures of CVD risk markers, especially among certain sub-populations. The exploratory PIR exposure metric should be further developed.
Introduction:
The neuropsychological battery of the Uniform Data Set (UDSNB) was implemented in 2005 by the National Institute on Aging (NIA) Alzheimer Disease Centers program to measure cognitive performance in dementia and mild cognitive impairment due to Alzheimer Disease. This paper describes a revision, the UDSNB 3.0.
Methods:
The Neuropsychology Work Group of the NIA Clinical Task Force recommended revisions through a process of due diligence to address shortcomings of the original battery. The UDSNB 3.0 covers episodic memory, processing speed, executive function, language, and constructional ability. Data from 3602 cognitively normal participants in the National Alzheimer Coordinating Center database were analyzed.
Results:
Descriptive statistics are presented. Multivariable linear regression analyses demonstrated score differences by age, sex, and education and were also used to create a normative calculator available online.
Discussion:
The UDSNB 3.0 neuropsychological battery provides a valuable non proprietary resource for conducting research on cognitive aging and dementia.
Increasing evidence points to an association of airborne pollutant exposure with respiratory, cardiovascular, and neurological pathology. We examined whether or not ground-level ozone or fine particulate matter ≤ 2.5 μm in diameter (PM2.5) was associated with accelerated cognitive decline. Using repeated measures mixed regression modeling, we analyzed cognitive performance of a geographically diverse sampling of individuals from the National Alzheimer’s Coordinating Center between 2004–2008. Ambient air concentrations of ozone and PM2.5 were established using a space-time Hierarchical Bayesian Model that statistically merged air monitor data and modeled air quality estimates. We then compared the ambient regional concentrations of ozone and PM2.5 with the rate of cognitive decline in residents within those regions. Increased levels of ozone correlated with an increased rate of cognitive decline, following adjustment for key individual and community-level risk factors. Furthermore, individuals harboring one or more APOE4 alleles exhibited a faster rate of cognitive decline. The deleterious association of ozone was confined to individuals with normal cognition who eventually became cognitively impaired as opposed to those who entered the study with baseline impairment. In contrast to ozone, we did not observe any correlation between ambient PM2.5 and cognitive decline at regulatory limits set by the Environmental Protection Agency. Our findings suggest that prolonged exposure to ground-level ozone may accelerate cognitive decline during the initial stages of dementia development.
Associations between long-Term exposure to ambient air pollution and cognitive function have been observed in a few longitudinal studies. Our aim was to investigate the association between long-Term exposure to air pollution and episodic memory, a marker of early cognitive decline. We used data from the Betula study in Northern Sweden, and included participants 60 to 85 of age at inclusion, 1,469 persons in total. The participants were followed for up to 22 years, five years apart between 1988 and 2010. A composite of five tasks was used as a measure of episodic memory measure (EMM), and the five-year change in EMM score (ΔEMM) was calculated such that a participant could contribute with up to four measurement pairs. A Land Use Regression Model was used to estimate cumulative annual mean of NOx at the residential address of the participants (a marker for long-Term exposure to traffic-related air pollution). There did not seem to be any association between exposure to traffic air pollution and episodic memory change, with a ΔEMM estimate of per 1 μg/m3 increase in NOx of 0.01 (95% Confidence Interval:-0.02,0.03). This is in contrast to a growing body of evidence suggesting associations between air pollution and cognitive function.
Background:
Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels.
Methods:
We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure-response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure-response functions spanning the global range of exposure.
Findings:
Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000-422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015.
Interpretation:
Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction.
Funding:
Bill & Melinda Gates Foundation and Health Effects Institute.
Background
Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health. MethodsZIP-code level estimates of exposure for six pollutants (CO, NOx, EC, PM2.5, SO4, O3) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error.Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs. ResultsSubstantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3–85% for population error, and 31–85% for total error. When CO, NOx or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate. Conclusions
The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.
Background:
Long-term exposure to fine particulate matter has been linked to cardiovascular disease and systemic inflammatory responses; however, evidence is limited regarding the effects of long-term exposure to ultrafine particulate matter (UFP, <100nm). We used a cross-sectional study design to examine the association of long-term exposure to near-highway UFP with measures of systemic inflammation and coagulation.
Methods:
We analyzed blood samples from 408 individuals aged 40-91years living in three near-highway and three urban background areas in and near Boston, Massachusetts. We conducted mobile monitoring of particle number concentration (PNC) in each area, and used the data to develop and validate highly resolved spatiotemporal (hourly, 20m) PNC regression models. These models were linked with participant time-activity data to determine individual time-activity adjusted (TAA) annual average PNC exposures. Multivariable regression modeling and stratification were used to assess the association between TAA-PNC and single peripheral blood measures of high-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor-necrosis factor alpha receptor II (TNFRII) and fibrinogen.
Results:
After adjusting for age, sex, education, body mass index, smoking and race/ethnicity, an interquartile-range (10,000particles/cm(3)) increase in TAA-PNC had a positive non-significant association with a 14.0% (95% CI: -4.6%, 36.2%) positive difference in hsCRP, an 8.9% (95% CI: -0.4%, 10.9%) positive difference in IL-6, and a 5.1% (95% CI: -0.4%, 10.9%) positive difference in TNFRII. Stratification by race/ethnicity revealed that TAA-PNC had larger effect estimates for all three inflammatory markers and was significantly associated with hsCRP and TNFRII in white non-Hispanic, but not East Asian participants. Fibrinogen had a negative non-significant association with TAA-PNC.
Conclusions:
Our findings suggest an association between annual average near-highway TAA-PNC and subclinical inflammatory markers of CVD risk.
Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time.Journal of Exposure Science and Environmental Epidemiology advance online publication, 1 April 2015; doi:10.1038/jes.2015.11.
Background: Air pollution is hypothesized to be a risk factor for diabetes. Epidemiological evidence is inconsistent and has not been systematically evaluated.
Objectives: We systematically reviewed epidemiological evidence on the association between air pollution and diabetes, and synthesized results of studies on type 2 diabetes (T2DM).
Methods: We systematically searched electronic literature databases (last search 29 April 2014) for studies reporting the association between air pollution (particle concentration or traffic exposure) and diabetes (type 1, type 2 or gestational). We systematically evaluated risk of bias and role of potential confounders in all studies. We synthesized reported associations with T2DM in meta-analyses using random effect models and conducted various sensitivity analyses.
Results: We included 13 studies (eight on T2DM, two on type 1, three on gestational diabetes), all conducted in Europe or North-America. Five studies were longitudinal, five cross-sectional, two case-control and one ecologic. Risk of bias, air pollution assessment, and confounder control varied across studies. Dose-response effects were not reported. Meta-analyses of three studies on PM2.5 (particulate matter <2.5 µm in diameter) and four studies on NO2 (nitrogen dioxide) showed increased risk of T2DM by 8-10% per 10 µg/m3 increase in exposure [PM2.5: 1.10 (95% CI: 1.02, 1.18); NO2: 1.08 (95% CI: 1.00, 1.17)]. Associations were stronger in females. Sensitivity analyses showed similar results.
Conclusion: Existing evidence indicates a positive association of air pollution and T2DM risk albeit there is high risk of bias. High quality studies assessing dose-response effects are needed. Research should be expanded to developing countries where outdoor and indoor air pollution are high.
Maximum likelihood or restricted maximum likelihood (REML) estimates of the
parameters in linear mixed-effects models can be determined using the lmer
function in the lme4 package for R. As for most model-fitting functions in R,
the model is described in an lmer call by a formula, in this case including
both fixed- and random-effects terms. The formula and data together determine a
numerical representation of the model from which the profiled deviance or the
profiled REML criterion can be evaluated as a function of some of the model
parameters. The appropriate criterion is optimized, using one of the
constrained optimization functions in R, to provide the parameter estimates. We
describe the structure of the model, the steps in evaluating the profiled
deviance or REML criterion, and the structure of classes or types that
represents such a model. Sufficient detail is included to allow specialization
of these structures by users who wish to write functions to fit specialized
linear mixed models, such as models incorporating pedigrees or smoothing
splines, that are not easily expressible in the formula language used by lmer.
Studies of the effect of air pollution on cognitive health are often limited to populations living near cities that have air monitoring stations. Little is known about whether the estimates from such studies can be generalized to the U.S. population, or whether the relationship differs between urban and rural areas. To address these questions, we used a satellite-derived estimate of fine particulate matter (PM2.5) concentration to determine whether PM2.5 was associated with incident cognitive impairment in a geographically diverse, biracial US cohort of men and women (n = 20,150). A 1-year mean baseline PM2.5 concentration was estimated for each participant, and cognitive status at the most recent follow-up was assessed over the telephone using the Six-Item Screener (SIS) in a subsample that was cognitively intact at baseline. Logistic regression was used to determine whether PM2.5 was related to the odds of incident cognitive impairment. A 10 µg/m(3) increase in PM2.5 concentration was not reliably associated with an increased odds of incident impairment, after adjusting for temperature, season, incident stroke, and length of follow-up [OR (95% CI): 1.26 (0.97, 1.64)]. The odds ratio was attenuated towards 1 after adding demographic covariates, behavioral factors, and known comorbidities of cognitive impairment. A 10 µg/m(3) increase in PM2.5 concentration was slightly associated with incident impairment in urban areas (1.40 [1.06-1.85]), but this relationship was also attenuated after including additional covariates in the model. Evidence is lacking that the effect of PM2.5 on incident cognitive impairment is robust in a heterogeneous US cohort, even in urban areas.
In metropolitan areas, road traffic is a major contributor to ambient air pollution and the dominant source of community noise. The authors investigated the independent and joint influences of community noise and traffic-related air pollution on risk of coronary heart disease (CHD) mortality in a population-based cohort study with a 5-year exposure period (January 1994-December 1998) and a 4-year follow-up period (January 1999-December 2002). Individuals who were 45-85 years of age and resided in metropolitan Vancouver, Canada, during the exposure period and did not have known CHD at baseline were included (n = 445,868). Individual exposures to community noise and traffic-related air pollutants, including black carbon, particulate matter less than or equal to 2.5 μm in aerodynamic diameter, nitrogen dioxide, and nitric oxide, were estimated at each person's residence using a noise prediction model and land-use regression models, respectively. CHD deaths were identified from the provincial death registration database. After adjustment for potential confounders, including traffic-related air pollutants or noise, elevations in noise and black carbon equal to the interquartile ranges were associated with 6% (95% confidence interval: 1, 11) and 4% (95% confidence interval: 1, 8) increases, respectively, in CHD mortality. Subjects in the highest noise decile had a 22% (95% confidence interval: 4, 43) increase in CHD mortality compared with persons in the lowest decile. These findings suggest that there are independent effects of traffic-related noise and air pollution on CHD mortality.
Chronic exposure to particulate air pollution may accelerate cognitive decline in older adults, although data on this association are limited. Our objective was to examine long-term exposure to particulate matter (PM) air pollution, both coarse ([PM 2.5-10 μm in diameter [PM(2.5-10)]) and fine (PM <2.5 μm in diameter [PM(2.5)]), in relation to cognitive decline.
The study population comprised the Nurses' Health Study Cognitive Cohort, which included 19,409 US women aged 70 to 81 years. We used geographic information system-based spatiotemporal smoothing models to estimate recent (1 month) and long-term (7-14 years) exposures to PM(2.5-10), and PM(2.5) preceding baseline cognitive testing (1995-2001) of participants residing in the contiguous United States. We used generalized estimating equation regression to estimate differences in the rate of cognitive decline across levels of PM(2.5-10) and PM(2.5) exposures. The main outcome measure was cognition, via validated telephone assessments, administered 3 times at approximately 2-year intervals, including tests of general cognition, verbal memory, category fluency, working memory, and attention.
Higher levels of long-term exposure to both PM(2.5-10) and PM(2.5) were associated with significantly faster cognitive decline. Two-year decline on a global score was 0.020 (95% CI, -0.032 to -0.008) standard units worse per 10 μg/m(3) increment in PM(2.5-10) exposure and 0.018 (95% CI, -0.035 to -0.002) units worse per 10 μg/m(3) increment in PM(2.5) exposure. These differences in cognitive trajectory were similar to those between women in our cohort who were approximately 2 years apart in age, indicating that the effect of a 10-μg/m(3) increment in long-term PM exposure is cognitively equivalent to aging by approximately 2 years.
Long-term exposure to PM(2.5-10) and PM(2.5) at levels typically experienced by many individuals in the United States is associated with significantly worse cognitive decline in older women.
Epidemiologic studies have demonstrated that exposure to road traffic is associated with adverse cardiovascular outcomes.
We aimed to identify specific traffic-related air pollutants that are associated with the risk of coronary heart disease (CHD) morbidity and mortality to support evidence-based environmental policy making.
This population-based cohort study included a 5-year exposure period and a 4-year follow-up period. All residents 45-85 years of age who resided in Metropolitan Vancouver during the exposure period and without known CHD at baseline were included in this study (n=452,735). Individual exposures to traffic-related air pollutants including black carbon, fine particles [aerodynamic diameter ≤ 2.5 µm (PM(2.5))], nitrogen dioxide (NO(2)), and nitric oxide were estimated at residences of the subjects using land-use regression models and integrating changes in residences during the exposure period. CHD hospitalizations and deaths during the follow-up period were identified from provincial hospitalization and death registration records.
An interquartile range elevation in the average concentration of black carbon (0.94 × 10(-5)/m filter absorbance, equivalent to approximately 0.8 µg/m(3) elemental carbon) was associated with a 3% increase in CHD hospitalization (95% confidence interval, 1-5%) and a 6% increase in CHD mortality (3-9%) after adjusting for age, sex, preexisting comorbidity, neighborhood socioeconomic status, and copollutants (PM(2.5) and NO(2)). There were clear linear exposure-response relationships between black carbon and coronary events.
Long-term exposure to traffic-related fine particulate air pollution, indicated by black carbon, may partly explain the observed associations between exposure to road traffic and adverse cardiovascular outcomes.
Background:
Dementia is a devastating neurologic condition that is common in older adults. We previously reviewed the epidemiological evidence examining the hypothesis that long-term exposure to air pollution affects dementia risk. Since then, the evidence base has expanded rapidly.
Objectives:
With this update, we collectively review new and previously identified epidemiological studies on air pollution and late-life cognitive health, highlighting new developments and critically discussing the merits of the evidence.
Methods:
Using a registered protocol (PROSPERO 2020 CRD42020152943), we updated our literature review to capture studies published through 31 December 2020, extracted data, and conducted a bias assessment.
Results:
We identified 66 papers (49 new) for inclusion in this review. Cognitive level remained the most commonly considered outcome, and particulate matter (PM) remained the most commonly considered air pollutant. Since our prior review, exposure estimation methods in this research have improved, and more papers have looked at cognitive change, neuroimaging, and incident cognitive impairment/dementia, though methodological concerns remain common. Many studies continue to rely on administrative records to ascertain dementia, have high potential for selection bias, and adjust for putative mediating factors in primary models. A subset of 35 studies met strict quality criteria. Although high-quality studies of fine particulate matter with aerodynamic diameter ≤2.5μm (PM2.5) and cognitive decline generally supported an adverse association, other findings related to PM2.5 and findings related to particulate matter with aerodynamic diameter ≤10μm (PM10, NO2, and NOx) were inconclusive, and too few papers reported findings with ozone to comment on the likely direction of association. Notably, only a few findings on dementia were included for consideration on the basis of quality criteria.
Discussion:
Strong conclusions remain elusive, although the weight of the evidence suggests an adverse association between PM2.5 and cognitive decline. However, we note a continued need to confront methodological challenges in this line of research. https://doi.org/10.1289/EHP8716.
The United States Postal Service (USPS) assigns unique identifiers for postal service areas known as ZIP codes which are commonly used to identify cities and regions throughout the United States in datasets. Despite the widespread use of ZIP codes, there are challenges in using them for geospatial analysis in the social sciences. This paper presents zipcodeR, an R package that facilitates analysis of ZIP code-level data by providing an offline database of ZIP codes and functions for geocoding, normalizing and retrieving data about ZIP codes and relating them to other geographies in R without depending on any external services.
Objective
To evaluate the association between long-term exposure to ambient air pollution and cognitive decline in older adults residing in an urban area.
Methods
Data for this study were obtained from 2 prospective cohorts of residents in the northern Manhattan area of New York City: the Washington Heights–Inwood Community Aging Project (WHICAP) and the Northern Manhattan Study (NOMAS). Participants of both cohorts received in-depth neuropsychological testing at enrollment and during follow-up. In each cohort, we used inverse probability weighted linear mixed models to evaluate the cross-sectional and longitudinal associations between markers of average residential ambient air pollution (nitrogen dioxide [NO 2 ], fine particulate matter [PM 2.5 ], and respirable particulate matter [PM 10 ]) levels in the year prior to enrollment and measures of global and domain-specific cognition, adjusting for sociodemographic factors, temporal trends, and censoring.
Results
Among 5,330 participants in WHICAP, an increase in NO 2 was associated with a 0.22 SD lower global cognitive score at enrollment (95% confidence interval [CI], −0.30, −0.14) and 0.06 SD (95% CI, −0.08, −0.04) more rapid decline in cognitive scores between visits. Results were similar for PM 2.5 and PM 10 and across functional cognitive domains. We found no evidence of an association between pollution and cognitive function in NOMAS.
Conclusion
WHICAP participants living in areas with higher levels of ambient air pollutants have lower cognitive scores at enrollment and more rapid rates of cognitive decline over time. In NOMAS, a smaller cohort with fewer repeat measurements, we found no statistically significant associations. These results add to the evidence regarding the adverse effect of air pollution on cognitive aging and brain health.
Objectives
Due to their small size, ultrafine particles (UFP) are believed to exert higher toxicity than larger particles. As numerous studies on health effects of UFP have been published since the last systematic review in 2013, we aim to systematically review the new literature.
Methods
We searched MEDLINE and the specialized LUDOK database for studies published between 01.01.2011 and 11.05.2017 investigating health effects of ambient air pollution-related UFP. We included epidemiologic studies containing UFP measures and quantifiable measures of associations. Relevant data were extracted on the basis of previously developed evaluation criteria.
Results
We identified 85 original studies, conducting short-term (n = 75) and long-term (n = 10) investigations. Panel (n = 32), scripted exposure with predefined settings (n = 16) or time series studies (n = 11) were most frequent. Thirty-four studies adjusted for at least one other pollutant. Most consistent associations were identified for short-term effects on pulmonary/systemic inflammation, heart rate variability and blood pressure.
Conclusions
The evidence suggests adverse short-term associations with inflammatory and cardiovascular changes, which may be at least partly independent of other pollutants. For the other studied health outcomes, the evidence on independent health effects of UFP remains inconclusive or insufficient.
The incidence of dementia is expected to double in the next 20 years and will contribute to heavy social and economic burden. Dementia is caused by neuronal loss that leads to brain atrophy years before symptoms manifest. Currently, no cure exists and extensive efforts are being made to mitigate cognitive impairment in late life in order to reduce the burden on patients, caregivers, and society. The most common type of dementia, Alzheimer's disease ( AD ), and vascular dementia (VaD) often co‐exists in the brain and shares common, modifiable risk factors, which are targeted in numerous secondary prevention trials. There is a growing need for non‐pharmacological interventions and infrastructural support from governments to encourage psychosocial and behavioral interventions. Secondary prevention trials need to be redesigned based on the risk profile of individual subjects, which require the use of validated and standardized clinical, biological, and neuroimaging biomarkers. Multi‐domain approaches have been proposed in high‐risk populations that target optimal treatment; clinical trials need to recruit individuals at the highest risk of dementia before symptoms develop, thereby identifying an enriched disease group to test preventative and disease modifying strategies. The underlying aim should be to reduce microscopic brain tissue loss by modifying vascular and lifestyle risk factors over a relatively short period of time, thus optimizing the opportunity for preventing dementia in the future. Collaboration between international research groups is of key importance to the optimal use and allocation of existing resources, and the development of new techniques in preventing dementia.
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This article is part of the Special Issue “Vascular Dementia” .
Purpose of the review:
Air pollution continues to be a major public health concern affecting nine out of 10 individuals living in urban areas worldwide. Exposure to air pollution is the ninth leading risk factor for cardiopulmonary mortality. The aim of this review is to examine the current literature for the most recent updates on health effects of specific air pollutants and their impact on asthma, chronic obstructive pulmonary disease, lung cancer, and respiratory infection.
Recent findings:
A total of 53 publications were reviewed to establish new insights as to how air pollution is associated with pulmonary morbidity and mortality. Considerable past evidence suggests that air pollution is an important factor that enhances pulmonary disease, while also causing greater harm in susceptible populations, such as children, the elderly, and those of low socio-economic status worldwide. Asthma, chronic obstructive pulmonary disease, lung cancer, and respiratory infections all seem to be exacerbated because of exposure to a variety of environmental air pollutants with the greatest effects because of particulate matter, ozone, and nitrogen oxides. New publications reviewed reaffirm these findings.
Summary:
Continued vigilance will be essential to lessen the effects of air pollution on human health and pulmonary disease. Cooperation at a multinational level will be required on the part of governments, industry, energy-based enterprises, and the public working together to solve our air quality issues at the local, national, and global level.
Rationale:
Ambient air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD). However, there is a lack of longitudinal studies to support this assertion.
Objectives:
To investigate the associations of long-term exposure to elevated traffic-related air pollution and woodsmoke pollution with the risk of COPD hospitalization and mortality.
Methods:
This population-based cohort study included a 5-year exposure period and a 4-year follow-up period. All residents aged 45-85 years who resided in Metropolitan Vancouver, Canada, during the exposure period and did not have known COPD at baseline were included in this study (n = 467,994). Residential exposures to traffic-related air pollutants (black carbon, particulate matter <2.5 μm in aerodynamic diameter, nitrogen dioxide, and nitric oxide) and woodsmoke were estimated using land-use regression models and integrating changes in residences during the exposure period. COPD hospitalizations and deaths during the follow-up period were identified from provincial hospitalization and death registration databases.
Measurements and main results:
An interquartile range elevation in black carbon concentrations (0.97 × 10(-5)/m, equivalent to 0.78 μg/m(3) elemental carbon) was associated with a 6% (95% confidence interval, 2-10%) increase in COPD hospitalizations and a 7% (0-13%) increase in COPD mortality after adjustment for covariates. Exposure to higher levels of woodsmoke pollution (tertile 3 vs. tertile 1) was associated with a 15% (2-29%) increase in COPD hospitalizations. There were positive exposure-response trends for these observed associations.
Conclusions:
Ambient air pollution, including traffic-related fine particulate pollution and woodsmoke pollution, is associated with an increased risk of COPD.
Despite increasing regulatory attention and literature linking roadside air pollution to health outcomes, studies on near roadway air quality have not yet been well synthesized. We employ data collected from 1978 as reported in 41 roadside monitoring studies, encompassing more than 700 air pollutant concentration measurements, published as of June 2008. Two types of normalization, background and edge-of-road, were applied to the observed concentrations. Local regression models were specified to the concentration-distance relationship and analysis of variance was used to determine the statistical significance of trends. Using an edge-of-road normalization, almost all pollutants decay to background by 115-570 m from the edge of road; using the more standard background normalization, almost all pollutants decay to background by 160-570 m from the edge of road. Differences between the normalization methods arose due to the likely bias inherent in background normalization, since some reported background values tend to underpredict (be lower than) actual background. Changes in pollutant concentrations with increasing distance from the road fell into one of three groups: at least a 50% decrease in peak/edge-of-road concentration by 150 m, followed by consistent but gradual decay toward background (e.g., carbon monoxide, some ultrafine particulate matter number concentrations); consistent decay or change over the entire distance range (e.g., benzene, nitrogen dioxide); or no trend with distance (e.g., particulate matter mass concentrations).
In 2004, the first American Heart Association scientific statement on "Air Pollution and Cardiovascular Disease" concluded that exposure to particulate matter (PM) air pollution contributes to cardiovascular morbidity and mortality. In the interim, numerous studies have expanded our understanding of this association and further elucidated the physiological and molecular mechanisms involved. The main objective of this updated American Heart Association scientific statement is to provide a comprehensive review of the new evidence linking PM exposure with cardiovascular disease, with a specific focus on highlighting the clinical implications for researchers and healthcare providers. The writing group also sought to provide expert consensus opinions on many aspects of the current state of science and updated suggestions for areas of future research. On the basis of the findings of this review, several new conclusions were reached, including the following: Exposure to PM <2.5 microm in diameter (PM(2.5)) over a few hours to weeks can trigger cardiovascular disease-related mortality and nonfatal events; longer-term exposure (eg, a few years) increases the risk for cardiovascular mortality to an even greater extent than exposures over a few days and reduces life expectancy within more highly exposed segments of the population by several months to a few years; reductions in PM levels are associated with decreases in cardiovascular mortality within a time frame as short as a few years; and many credible pathological mechanisms have been elucidated that lend biological plausibility to these findings. It is the opinion of the writing group that the overall evidence is consistent with a causal relationship between PM(2.5) exposure and cardiovascular morbidity and mortality. This body of evidence has grown and been strengthened substantially since the first American Heart Association scientific statement was published. Finally, PM(2.5) exposure is deemed a modifiable factor that contributes to cardiovascular morbidity and mortality.
A Clinical Task Force, composed of clinical leaders from Alzheimer's Disease Centers (ADC), was convened by the National Institute on Aging to develop a uniform set of assessment procedures to characterize individuals with mild Alzheimer disease and mild cognitive impairment in comparison with nondemented aging. The resulting Uniform Data Set (UDS) defines a common set of clinical observations to be collected longitudinally on ADC participants in accordance with standard methods. The UDS was implemented at all ADCs on September 1, 2005. Data obtained with the UDS are submitted to the National Alzheimer's Coordinating Center and represent a unique and valuable source of data to support and stimulate collaborative research.
The National Alzheimer's Coordinating Center (NACC) is responsible for developing and maintaining a database of participant information collected from the 29 Alzheimer's Disease Centers (ADCs) funded by the National Institute on Aging (NIA). The NIA appointed the ADC Clinical Task Force to determine and define an expanded, standardized clinical data set, called the Uniform Data Set (UDS). The goal of the UDS is to provide ADC researchers a standard set of assessment procedures, collected longitudinally, to better characterize ADC participants with mild Alzheimer disease and mild cognitive impairment in comparison with nondemented controls. NACC implemented the UDS (September 2005) by developing data collection forms for initial and follow-up visits based on Clinical Task Force definitions, a relational database, and a data submission system accessible by all ADCs. The NIA requires ADCs to submit UDS data to NACC for all their Clinical Core participants. Thus, the NACC web site (https://www.alz.washington.edu) was enhanced to provide efficient and secure access data submission and retrieval systems.
Outdoor concentrations of soot and nitrogen dioxide (NO2) outside of schools have been associated with children's respiratory and eye symptoms. We assessed how adjustments for measurement error affect these associations.
Concentrations of air pollutants outside children's schools were validated by personal measurements of exposure to traffic-related air pollution. We estimated prevalence ratios of 4 health outcomes (current wheeze, conjunctivitis, phlegm, and elevated total serum immunoglobulin E) using school outdoor measurements, and then adjusted for measurement error using the personal exposure data and applying a regression calibration method. The analysis adjusting for measurement error was carried out using a main study/external validation design.
Adjusting for measurement error produced effect estimates related to soot and NO2 that were 2 to 3 times higher than in the original study. The adjusted prevalence ratio for current phlegm was 5.3 (95% confidence interval = 1.2-23) for a 9.3 microg/m3 increase in soot, and 3.8 (1.0-14), for a 17.6 microg/m3 increase in NO2, compared with the original results of 2.2 (1.3-3.9) and 1.8 (1.1-2.8), respectively. Corrections were of similar magnitude for the prevalence of current wheeze, current conjunctivitis, and total elevated total immunoglobulin E.
The estimated effects of outdoor air pollution on respiratory and other health effects in children may be substantially attenuated when based on exposure measurements outside schools instead of personal exposure.