Traffic-related air pollution and cognitive function in a cohort of older men

Fine particulate matter components associated with exacerbated depressive symptoms among middle-aged and older adults in China

Growing awareness acknowledges ambient fine particulate matter (PM2.5) as an environmental risk factor for mental disorders, especially among older people. However, there remains limited evidence regarding which specific chemical components of PM2.5 may be more detrimental. This nationwide prospective cohort study included 22,126 middle-aged and older adult participants of the China Health and Retirement Longitudinal Study (CHARLS, 2011-2016), to explore the individual and joint associations between long-term exposure to various PM2.5 components (sulfate, nitrate, ammonium, organic matter, and black carbon) and depressive symptoms. The depressive symptoms were assessed using the 10-item Center for Epidemiological Studies-Depression Scale (CES-D-10). Using the novel quantile-based g-computation for multi-pollutant mixture analysis, we found that exposure to the mixture of major PM2.5 components was significantly associated with aggravating depressive symptoms, with the exposure-response curve exhibiting consistent linear or supra-linear shape without a lower threshold. The estimated weight index indicated that, among major PM2.5 components, only nitrate, sulfate, and black carbon significantly contributed to the exacerbation of depressive symptoms. Given the expanding aging population, stricter regulation on the emissions of particularly toxic PM2.5 components may mitigate the escalating disease burden of depression.

Investigation of the expression of Cis P-tau and Pin1 proteins following air pollution induction in the brain tissue of C57BL/6 mice

Alzheimer's disease (AD) is a multifactorial disease in which environmental factors play a role. Among environmental factors, air pollution is a vital issue in modern life. Despite extensive considerations, it remains uncertain how pollution mediates neurodegeneration in AD. Beta-amyloids and hyperphosphorylated tau proteins are the two main pathological markers that have been studied in AD so far. Tau protein is basically a phosphoprotein whose functions are controlled by phosphorylation. The function of tau protein is to be located on the surface of microtubules and stabilize them. Studies have shown that phosphorylated tau protein (p-tau) exists in cis and trans conformations at Thr231, among which cis is highly neurotoxic. The Pin1 enzyme performs the conversion of cis to trans or vice versa. In this study, an experimental mouse model was designed to investigate the formation of cis p-tau by inducing air pollution. In this way, mice were randomly exposed to pollution at 2-week, 1-month, and 2-month intervals. We investigated the formation of phosphorylated cis tau form during air pollution on mouse brains using Western blots and immunofluorescence. The fluorescent imaging results and Western blotting analysis of mouse brains revealed a significant accumulation of cis p-tau in pollution-treated mice models compared to the healthy control mice. According to Western blot results, air pollution induction caused a significant decrease in Pin1 protein. The results clearly show that the tauopathy observed during air pollution is mediated through the formation of cis tau. Our findings unravel tauopathy mysteries upon pollution and would help find a possible therapeutic target to fight the devastating disorder caused by modern life.

Assessing the risks associated with indoor and outdoor air quality in relation to the geographic placement of nursing home

Indoor air quality significantly impacts the well-being and health of elderly residents in nursing homes. This study was conducted to explore the connection between indoor and outdoor PM (Particulate Matter) concentrations in nursing homes and their association with the facilities' location and construction characteristics. The findings revealed that indoor PM2.5 and PM10 concentrations ranged from 0.2 to 124 μg/m3 and 2-188.4 μg/m3, respectively, which were approximately 12.67 and 1.25 times higher than their outdoor counterparts. A strong correlation (P < 0.05) was identified between indoor PM levels and various factors, including proximity to parks, passenger terminals, and gas stations, as well as building attributes such as single-glazed windows, ceramic floor coverings, and the use of radiators. The risk assessment indicated that carcinogenic risk factors were well within acceptable limits for all nursing homes. However, it's important to note that certain PM components, particularly polycyclic aromatic hydrocarbons (PAH), may have long-term adverse effects on the health of nursing home residents. Even though indoor PM levels met the standards established by the U.S. Environmental Protection Agency (USEPA) for particulate matter risk assessments, the study emphasized that even low levels of indoor air pollutants can affect the health and well-being of older adults, particularly considering the increased vulnerability associated with aging. Consequently, the study underscores the importance of nursing home location selection and the regular monitoring of particulate matter concentrations. These measures are essential for enhancing air quality within nursing homes, ultimately contributing to the improved well-being and health of their residents.

Climate change effects in older people's health: A scoping review

BACKGROUND

Climate change has serious consequences for the morbidity and mortality of older adults.

OBJECTIVE

To identify the effects of climate change on older people's health.

METHODS

A scoping review was conducted following the Joanna Briggs Institute guidelines and the PRISMA-ScR checklist. Quantitative research and reports from organizations describing the effects of climate change on older people were selected.

RESULTS

Sixty-three full-text documents were selected. Heat and air pollution were the two factors that had the most negative effects on cardiovascular and respiratory morbidity and mortality in older people. Mental health and cognitive function were also affected.

CONCLUSIONS

Climate change affects several health problems in older individuals, especially high temperatures and air pollution. Nursing professionals must have the necessary skills to respond to the climate risks in older adults. More instruments are required to determine nursing competencies on climate change and the health of this population group.

PATIENT OF PUBLIC CONTRIBUTION

No patient or public contribution.

Source-Specific Air Pollution and Loss of Independence in Older Adults Across the US

Importance

Air pollution is a recognized risk factor associated with chronic diseases, including respiratory and cardiovascular conditions, which can lead to physical and cognitive impairments in later life. Although these losses of function, individually or in combination, reduce individuals' likelihood of living independently, little is known about the association of air pollution with this critical outcome.

Objective

To investigate associations between air pollution and loss of independence in later life.

Design, Setting, and Participants

This cohort study was conducted as part of the Environmental Predictors Of Cognitive Health and Aging study and used 1998 to 2016 data from the Health and Retirement Study. Participants included respondents from this nationally representative, population-based cohort who were older than 50 years and had not previously reported a loss of independence. Analyses were performed from August 31 to October 15, 2023.

Exposures

Mean 10-year pollutant concentrations (particulate matter less than 2.5 μm in diameter [PM2.5] or ranging from 2.5 μm to 10 μm in diameter [PM10-2.5], nitrogen dioxide [NO2], and ozone [O3]) were estimated at respondent addresses using spatiotemporal models along with PM2.5 levels from 9 emission sources.

Main Outcomes and Measures

Loss of independence was defined as newly receiving care for at least 1 activity of daily living or instrumental activity of daily living due to health and memory problems or moving to a nursing home. Associations were estimated with generalized estimating equation regression adjusting for potential confounders.

Results

Among 25 314 respondents older than 50 years (mean [SD] baseline age, 61.1 [9.4] years; 11 208 male [44.3%]), 9985 individuals (39.4%) experienced lost independence during a mean (SD) follow-up of 10.2 (5.5) years. Higher exposure levels of mean concentration were associated with increased risks of lost independence for total PM2.5 levels (risk ratio [RR] per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.10), PM2.5 levels from road traffic (RR per 1-IQR of 10-year mean, 1.09; 95% CI, 1.03-1.16) and nonroad traffic (RR per 1-IQR of 10-year mean, 1.13; 95% CI, 1.03-1.24), and NO2 levels (RR per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.08). Compared with other sources, traffic-generated pollutants were most consistently and robustly associated with loss of independence; only road traffic-related PM2.5 levels remained associated with increased risk after adjustment for PM2.5 from other sources (RR per 1-IQR increase in 10-year mean concentration, 1.10; 95% CI, 1.00-1.21). Other pollutant-outcome associations were null, except for O3 levels, which were associated with lower risks of lost independence (RR per 1-IQR increase in 10-year mean concentration, 0.94; 95% CI, 0.92-0.97).

Conclusions and Relevance

This study found that long-term exposure to air pollution was associated with the need for help for lost independence in later life, with especially large and consistent increases in risk for pollution generated by traffic-related sources. These findings suggest that controlling air pollution could be associated with diversion or delay of the need for care and prolonged ability to live independently.

Associations between solar and geomagnetic activity and cognitive function in the Normative Aging study

BACKGROUND

Studies show that changes in solar and geomagnetic activity (SGA) influence melatonin secretion and the autonomic nervous system. We evaluated associations between solar and geomagnetic activity and cognitive function in the Normative Aging Study from 1992 to 2013.

METHODS

We used logistic and linear generalized estimating equations and regressions to evaluate the associations between moving averages of sunspot number (SSN) and Kp index (a measure of geomagnetic activity) and a binary measure for Mini-Mental State Examination (MMSE) scores (≤25 or > 25) and six other cognitive tests as continuous measures, combined into one global composite score and considered separately.

RESULTS

A one-IQR increase in same-day SSN and Kp index were associated with 17% (95% CI: 3%, 34%) and 19% (95% CI: 4%, 36%) increases in the odds of low MMSE score. We observed small increases in the global cognitive score with increasing SSN, although we observed decreases specifically in relation to the backwards digit span test.

CONCLUSIONS

Periods of high SGA were associated with cognitive function. SGA may not equally impact all aspects of cognitive function, as evidenced by differences in associations observed for the MMSE, global cognitive score, and individual cognitive tests. Given that much of the pathology of cognitive decline in the elderly remains unexplained, studies specifically targeting decline and with longer follow-up periods are warranted.

Long-term exposure to fine particulate matter constituents and cognitive impairment among older adults: An 18-year Chinese nationwide cohort study

BACKGROUND

Although growing evidence has shown independent links of long-term exposure to fine particulate matter (PM2.5) with cognitive impairment, the effects of its constituents remain unclear. This study aims to explore the associations of long-term exposure to ambient PM2.5 constituents' mixture with cognitive impairment in Chinese older adults, and to further identify the main contributor.

METHODS

15,274 adults ≥ 65 years old were recruited by the Chinese Longitudinal Healthy Longevity Study (CLHLS) and followed up through 7 waves during 2000-2018. Concentrations of ambient PM2.5 and its constituents (i.e., black carbon [BC], organic matter [OM], ammonium [NH4+], sulfate [SO42-], and nitrate [NO3-]) were estimated by satellite retrievals and machine learning models. Quantile-based g-computation model was employed to assess the joint effects of a mixture of 5 PM2.5 constituents and their relative contributions to cognitive impairment. Analyses stratified by age group, sex, residence (urban vs. rural), and region (north vs. south) were performed to identify vulnerable populations.

RESULTS

During the average 3.03 follow-up visits (89,296.9 person-years), 4294 (28.1%) participants had developed cognitive impairment. The adjusted hazard ratio [HR] (95% confidence interval [CI]) for cognitive impairment for every quartile increase in mixture exposure to 5 PM2.5 constituents was 1.08 (1.05-1.11). BC held the largest index weight (0.69) in the positive direction in the qg-computation model, followed by OM (0.31). Subgroup analyses suggested stronger associations in younger old adults and rural residents.

CONCLUSION

Long-term exposure to ambient PM2.5, particularly its constituents BC and OM, is associated with an elevated risk of cognitive impairment onset among Chinese older adults.

Indoor air pollution and cognitive function among older adults in India: a multiple mediation approach through depression and sleep disorders

BACKGROUND

Studies across multiple countries reveal that depression and sleep disorders can lead to cognitive decline. This study aims to speculate on the effect of different sources of indoor air pollution on cognition and to explore the mediation effect of depression and sleep disorders on cognition when exposed to indoor air pollution. We hypothesize that an older adult experiences higher cognitive decline from indoor pollution when mediated by depression and sleep disorders.

METHODS

We use data from Longitudinal Aging Study in India (LASI), 2017-2018, and employ a multiple mediation model to understand the relationship between indoor air pollution and cognition through sleep disorders and depression while adjusting for possible confounders. Sensitivity analysis was applied to see the effect of different sources of indoor pollution (cooking fuel, indoor smoke products, and secondhand smoke) on cognitive performance.

RESULTS

The effect of three sources of indoor pollutants on cognition increased when combined, indicating stronger cognitive decline. Unclean cooking practices, indoor smoke (from incense sticks and mosquito coils), and secondhand smoke were strongly associated with sleep disorders and depression among older adults. Indoor air pollution was negatively associated with cognitive health (β= -0.38) while positively associated with depression (β= 0.18) and sleep disorders (β= 0.038) acting as mediators. Sensitivity analysis explained 45% variability while adjusting for confounders.

CONCLUSION

The study lays a foundation for future investigations into the nexus of indoor pollution and mental health. It is essential to formulate policies to reduce exposure to varying sources of indoor air pollutants and improve screening for mental health services as a public health priority.

Traffic-related air pollution and dementia incidence in the Adult Changes in Thought Study

BACKGROUND

While epidemiologic evidence links higher levels of exposure to fine particulate matter (PM2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence.

OBJECTIVE

To evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO2]) and late-life dementia incidence.

METHODS

We ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM2.5, and APOE genotype. We ran sensitivity analyses where we did not adjust for PM2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others.

RESULTS

We identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92-1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89-1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91-1.02) for every 2 ppb increment in NO2. These findings were consistent across sensitivity and secondary analyses.

DISCUSSION

We did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study.

Particulate Matter in Human Elderly: Higher Susceptibility to Cognitive Decline and Age-Related Diseases

This review highlights the significant impact of air quality, specifically particulate matter (PM), on cognitive decline and age-related diseases in the elderly. Despite established links to other pathologies, such as respiratory and cardiovascular illnesses, there is a pressing need for increased attention to the association between air pollution and cognitive aging, given the rising prevalence of neurocognitive disorders. PM sources are from diverse origins, including industrial activities and combustion engines, categorized into PM10, PM2.5, and ultrafine PM (UFPM), and emphasized health risks from both outdoor and indoor exposure. Long-term PM exposure, notably PM2.5, has correlated with declines in cognitive function, with a specific vulnerability observed in women. Recently, extracellular vesicles (EVs) have been explored due to the interplay between them, PM exposure, and human aging, highlighting the crucial role of EVs, especially exosomes, in mediating the complex relationship between PM exposure and chronic diseases, particularly neurological disorders. To sum up, we have compiled the pieces of evidence that show the potential contribution of PM exposure to cognitive aging and the role of EVs in mediating PM-induced cognitive impairment, which presents a promising avenue for future research and development of therapeutic strategies. Finally, this review emphasizes the need for policy changes and increased public awareness to mitigate air pollution, especially among vulnerable populations such as the elderly.

Relationships of Residential Distance to Major Traffic Roads with Dementia Incidence and Brain Structure Measures: Mediation Role of Air Pollution

Background: Uncertainty exists regarding the operating pathways between near-roadway exposure and dementia incidence. We intend to examine relationships between proximity to major roadways with dementia incidence and brain MRI structure measures, and potential mediation roles of air and noise pollution. Methods: The cohort study was based on the UK Biobank. Baseline survey was conducted from 2006 to 2010, with linkage to electronic health records conducted for follow-up. Residential distance to major roadways was ascertained residential address postcode. A land use regression model was applied for estimating traffic-related air pollution at residence. Dementia incidence was ascertained using national administrative databases. Brain MRI measures were derived as image-derived phenotypes, including total brain, white matter, gray matter, and peripheral cortical gray matter. Results: We included 460,901 participants [mean (SD) age: 57.1 (8.1) years; men: 45.7%]. Compared with individuals living >1,000 m from major traffic roads, living ≤1,000 m was associated with a 13% to 14% higher dementia risk, accounting for 10% of dementia cases. Observed association between residential distance and dementia was substantially mediated by traffic-related air pollution, mainly nitrogen dioxide (proportion mediated: 63.6%; 95% CI, 27.0 to 89.2%) and PM2.5 (60.9%, 26.8 to 87.0%). The shorter residential distance was associated with smaller volumes of brain structures, which was also mediated by traffic-related air pollutants. No significant mediation role was observed of noise pollution. Conclusions: The shorter residential distance to major roads was associated with elevated dementia incidence and smaller brain structure volumes, which was mainly mediated by traffic-related air pollution.

Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US

Importance

Emerging evidence indicates that exposure to fine particulate matter (PM2.5) air pollution may increase dementia risk in older adults. Although this evidence suggests opportunities for intervention, little is known about the relative importance of PM2.5 from different emission sources.

Objective

To examine associations of long-term exposure of total and source-specific PM2.5 with incident dementia in older adults.

Design, Setting, and Participants

The Environmental Predictors of Cognitive Health and Aging study used biennial survey data from January 1, 1998, to December 31, 2016, for participants in the Health and Retirement Study, which is a nationally representative, population-based cohort study in the US. The present cohort study included all participants older than 50 years who were without dementia at baseline and had available exposure, outcome, and demographic data between 1998 and 2016 (N = 27 857). Analyses were performed from January 31 to May 1, 2022.

Exposures

The 10-year mean total PM2.5 and PM2.5 from 9 emission sources at participant residences for each month during follow-up using spatiotemporal and chemical transport models.

Main Outcomes and Measures

The main outcome was incident dementia as classified by a validated algorithm incorporating respondent-based cognitive testing and proxy respondent reports. Adjusted hazard ratios (HRs) were estimated for incident dementia per IQR of residential PM2.5 concentrations using time-varying, weighted Cox proportional hazards regression models with adjustment for the individual- and area-level risk factors.

Results

Among 27 857 participants (mean [SD] age, 61 [10] years; 15 747 [56.5%] female), 4105 (15%) developed dementia during a mean (SD) follow-up of 10.2 [5.6] years. Higher concentrations of total PM2.5 were associated with greater rates of incident dementia (HR, 1.08 per IQR; 95% CI, 1.01-1.17). In single pollutant models, PM2.5 from all sources, except dust, were associated with increased rates of dementia, with the strongest associations for agriculture, traffic, coal combustion, and wildfires. After control for PM2.5 from all other sources and copollutants, only PM2.5 from agriculture (HR, 1.13; 95% CI, 1.01-1.27) and wildfires (HR, 1.05; 95% CI, 1.02-1.08) were robustly associated with greater rates of dementia.

Conclusion and Relevance

In this cohort study, higher residential PM2.5 levels, especially from agriculture and wildfires, were associated with higher rates of incident dementia, providing further evidence supporting PM2.5 reduction as a population-based approach to promote healthy cognitive aging. These findings also indicate that intervening on key emission sources might have value, although more research is needed to confirm these findings.

Impact of air pollution on the health of the older adults during physical activity and sedentary behavior: A systematic review

BACKGROUND

Air pollution, in addition to presenting health risks, can impact the practice of physical activity (PA) and sedentary behavior (SB) in older adults. This study analyzed the impact of air pollution on the health of older adults during PA and SB, through a systematic review.

METHODS

A keyword and reference search was performed in PubMed, SCOPUS, SPORTDiscus, and Web of Science. Predetermined selection criteria included study designs: interventions or experiments, retrospective or prospective cohort studies, cross-sectional studies and case-control studies; population: older adults aged 60 years or older; exposures: specific air pollutants (particulate matter (PM), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), black carbon (CN), ultrafine particles (PU), nitrogen oxides (NOx) and biomass fuels) indoors and outdoors; and outcomes: physical activity and/or sedentary behavior.

RESULTS

The beneficial effects of PA were attenuated or harmed in 11 studies, showing negative impacts on the health of the older adults, mainly by PM2.5 pollutants. On the other hand, in 10 studies the effects of PA were greater than the negative effects of air pollutants, with a greater frequency in relation to PM2.5. In general, even the articles presenting controversial results suggest that practicing PA in polluted environments is more favorable to the health of older adults than remaining in SB.

DISCUSSION AND CONCLUSIONS

On the one hand, air pollution negatively impacted the health of the older adults during PA practices, while on the other hand, PA can mitigate the negative effects of pollutants on the health of older adults during the practices. Evidence shows that practicing PA in environments with low concentrations of pollutants can provide gains and reduce health risks. Remaining in SB in environments with high levels of air pollution worsens the health of older adults.

Correlation between air pollution and cognitive impairment among older individuals: empirical evidence from China

BACKGROUND

Little information is available regarding the impact of air pollution on cognitive impairment in older individuals in developing countries. This study empirically tested the impacts of the air quality index (AQI), air pollution intensity (quantified by the number of days of extreme air pollution in a year), and different pollutants on the cognitive abilities of older Chinese individuals.

METHODS

A panel of 28,395 participants spanning 122 cities in 2015 and 2018 was used, based on 3-year follow-up survey data from the China Health and Retirement Longitudinal Study (CHARLS) database. Data from the two phases of the CHARLS microsurvey were combined with relevant statistical data on air pollution in each region in the current year. These two surveys were used to investigate changes in basic health and macro-environmental indicators in older individuals in China, and a mean difference test was conducted. We then reduced the sample selection error by controlling for environmental migration and used two-way fixed and instrumental variable methods for endogenous treatment to avoid the estimation error caused by missing variables.

RESULTS

Air pollution had a significantly negative effect on the cognitive abilities of older individuals (odds ratio [OR]: 1.4633; 95% confidence interval [95% CI]: 1.20899-1.77116). Different pollution intensities(only AQI value is greater than 200 or more) had apparent effects on cognitive impairment, with an OR of approximately 1.0. Sulfur dioxide had significantly negative effects on cognitive ability, with OR of 1.3802 (95% CI: 1.25779-1.51451). Furthermore, air pollution impact analysis showed heterogeneous results in terms of age, sex, education, and regional economic development level. In addition, social adaptability (calculated using social participation, learning, adaptability, and social support) not only had a significant positive effect on the cognitive abilities of older individuals, but also regulated the cognitive decline caused by air pollution.

CONCLUSIONS

Air pollution affects cognitive impairment in older individuals, especially in those with lower education levels, and living in economically underdeveloped areas. This effect is synchronous and has a peak at an AQI of > 200.

Effect of indoor air quality on the association of long-term exposure to low-level air pollutants with cognition in older adults

BACKGROUND

How indoor air quality affects the temporal associations of long-term exposure to low-level air pollutants with cognition remains unclear.

METHODS

This cohort study (2011-2019) included 517 non-demented older adults at baseline with four repeated cognitive assessments. The time-varying exposure to PM2.5, PM10, NO2, SO2, CO, and O3 was estimated for each participant from 1994 to 2019. Indoor air quality was determined by ventilation status and daily indoor time. Generalized linear mixed models were used to analyze the association of air pollutants, indoor air quality, and cognition adjusting for important covariates.

RESULTS

Over time, per 2.97 μg/m3 (i.e., an interquartile range) increment of PM2.5 was associated with the poor performance of memory (Z score of a cognitive test, βˆ:-0.14), attention (βˆ:-0.13), and executive function (βˆ:-0.20). Similarly, per 2.05 μg/m3 increase in PM2.5-10 was associated with poor global cognition [adjusted odds ratio (aOR): 1.48, βˆ:-0.28], attention (βˆ:-0.07), and verbal fluency (βˆ:-0.09); per 4.94 μg/m3 increase in PM10 was associated with poor global cognition (aOR: 1.78; βˆ:-0.37). In contrast, per 2.74 ppb increase in O3 was associated with better global cognition (βˆ:0.36 to 0.47). These associations became more evident in participants with poor ventilation or short daily indoor time (<12.5 h/day). For global cognition, the exposure to a 10-μg/m3 increment in PM2.5, PM2.5-10, and PM10 corresponded to 1.4, 5.8, and 2.8 years of aging, respectively.

CONCLUSION

This study demonstrated how indoor air quality in areas using clean fuels differentially affected the associations of long-term exposure to low-level air pollutants with cognition. Tightening air quality standards may help prevent dementia.

Global rural health disparities in Alzheimer's disease and related dementias: State of the science

INTRODUCTION

Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place-based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators.

METHODS

An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: "What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?" In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings.

RESULTS

A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions.

DISCUSSION

A location dynamics model and ADRD-focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities.

HIGHLIGHTS

Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities. Defining the unique rural barriers and facilitators to cognitive health yields insight. The strengths and resilience of rural residents can mitigate ADRD-related challenges. A novel "location dynamics" model guides assessment of rural-specific ADRD issues.

Exposure to quasi-ultrafine particulate matter accelerates memory impairment and Alzheimer's disease-like neuropathology in the AppNL-G-F knock-in mouse model

Exposure to traffic-related air pollution consisting of particulate matter (PM) is associated with cognitive decline leading to Alzheimer's disease (AD). In this study, we sought to examine the neurotoxic effects of exposure to ultrafine PM and how it exacerbates neuronal loss and AD-like neuropathology in wildtype (WT) mice and a knock-in mouse model of AD (AppNL-G-F/+-KI) when the exposure occurs at a prepathologic stage or at a later age with the presence of neuropathology. AppNL-G-F/+-KI and WT mice were exposed to concentrated ultrafine PM from local ambient air in Irvine, California, for 12 weeks, starting at 3 or 9 months of age. Particulate matter-exposed animals received concentrated ultrafine PM up to 8 times above the ambient levels, whereas control animals were exposed to purified air. Particulate matter exposure resulted in a marked impairment of memory tasks in prepathologic AppNL-G-F/+-KI mice without measurable changes in amyloid-β pathology, synaptic degeneration, and neuroinflammation. At aged, both WT and AppNL-G-F/+-KI mice exposed to PM showed a significant memory impairment along with neuronal loss. In AppNL-G-F/+-KI mice, we also detected an increased amyloid-β buildup and potentially harmful glial activation including ferritin-positive microglia and C3-positive astrocytes. Such glial activation could promote the cascade of degenerative consequences in the brain. Our results suggest that exposure to PM impairs cognitive function at both ages while exacerbation of AD-related pathology and neuronal loss may depend on the stage of pathology, aging, and/or state of glial activation. Further studies will be required to unveil the neurotoxic role of glial activation activated by PM exposure.

The pollutome-connectome axis: a putative mechanism to explain pollution effects on neurodegeneration

The study of pollutant effects is extremely important to address the epochal challenges we are facing, where world populations are increasingly moving from rural to urban centers, revolutionizing our world into an urban world. These transformations will exacerbate pollution, thus highlighting the necessity to unravel its effect on human health. Epidemiological studies have reported that pollution increases the risk of neurological diseases, with growing evidence on the risk of neurodegenerative disorders. Air pollution and water pollutants are the main chemicals driving this risk. These chemicals can promote inflammation, acting in synergy with genotype vulnerability. However, the biological underpinnings of this association are unknown. In this review, we focus on the link between pollution and brain network connectivity at the macro-scale level. We provide an updated overview of epidemiological findings and studies investigating brain network changes associated with pollution exposure, and discuss the mechanistic insights of pollution-induced brain changes through neural networks. We explain, in detail, the pollutome-connectome axis that might provide the functional substrate for pollution-induced processes leading to cognitive impairment and neurodegeneration. We describe this model within the framework of two pollutants, air pollution, a widely recognized threat, and polyfluoroalkyl substances, a large class of synthetic chemicals which are currently emerging as new neurotoxic source.

A Longitudinal Analysis of the Association Between Long-Term Exposure to Air Pollution and Cognitive Function Among Adults Aged 45 and Older in China

OBJECTIVES

Evidence suggests long-term exposure to fine particulate matter air pollution (PM2.5) is associated with a higher risk of cognitive impairment, especially among older adults. This study examines the relationship between PM2.5 exposure and cognitive function in China's aging population.

METHODS

We used longitudinal data from the China Health and Retirement Longitudinal Study (2011-2015) linked with historical PM2.5 concentrations (2000-2015) from remotely sensed satellite data. Growth curve models were applied to estimate associations between PM2.5 exposure (measured in intensity, duration, and a joint variable of intensity with duration for cumulative exposure) and cognitive function.

RESULTS

Relative to the lowest exposure group, exposure in the second group of PM2.5 intensity (35-50 μg/m3) is associated with poorer cognitive function, but higher levels of PM2.5 appear to be associated with better cognitive function, indicating a U-shaped association. Similar patterns are seen for fully adjusted models of PM2.5 duration: the second group (13-60 months) is associated with worse cognitive function than the first group (0-12 months), but coefficients are nonsignificant in longer duration groups. Joint analysis of PM2.5 intensity with duration suggests that duration may play a more detrimental role in cognitive function than intensity. However, we do not find a statistically significant association between PM2.5 exposure and the rate of cognitive decline.

DISCUSSION

Our findings are mixed and suggest that some categories of higher and longer exposure to PM2.5 are associated with poorer cognitive function, while that exposures do not hasten cognitive decline. However, more work is necessary to disentangle PM2.5 exposure from individuals' background characteristics, particularly those jointly associated with cognitive function and urban living.

Air pollution and human cognition: A systematic review and meta-analysis

BACKGROUND

This systematic review summarises and evaluates the literature investigating associations between exposure to air pollution and general population cognition, which has important implications for health, social and economic inequalities, and human productivity.

METHODS

The engines MEDLINE, Embase Classic+Embase, APA PsycInfo, and SCOPUS were searched up to May 2022. Our inclusion criteria focus on the following pollutants: particulate matter, NOx, and ozone. The cognitive abilities of interest are: general/global cognition, executive function, attention, working memory, learning, memory, intelligence and IQ, reasoning, reaction times, and processing speed. The collective evidence was assessed using the NTP-OHAT framework and random-effects meta-analyses.

RESULTS

Eighty-six studies were identified, the results of which were generally supportive of associations between exposures and worsened cognition, but the literature was varied and sometimes contradictory. There was moderate certainty support for detrimental associations between PM_2.5 and general cognition in adults 40+, and PM_2.5, NOx, and PM₁₀ and executive function (especially working memory) in children. There was moderate certainty evidence against associations between ozone and general cognition in adults age 40+, and NOx and reasoning/IQ in children. Some associations were also supported by meta-analysis (N = 14 studies, all in adults aged 40+). A 1 μg/m³ increase in NO₂ was associated with reduced performance on general cognitive batteries (β = -0.02, p < 0.05) as was a 1 μg/m³ increase in PM_2.5 exposure (β = -0.02, p < 0.05). A 1μgm³ increase in PM_2.5 was significantly associated with lower verbal fluency by -0.05 words (p = 0.01) and a decrease in executive function task performance of -0.02 points (p < 0.001).

DISCUSSION

Evidence was found in support of some exposure-outcome associations, however more good quality research is required, particularly with older teenagers and young adults (14-40 years), using multi-exposure modelling, incorporating mechanistic investigation, and in South America, Africa, South Asia and Australasia.

Long-term exposure to ambient air pollution and cognitive function in older US adults: The Multi-Ethnic Study of Atherosclerosis

Air pollution effects on cognitive function have been increasingly recognized. Little is known about the impact of different sources of fine particulate (PM2.5). We aim to evaluate the associations between long-term air pollution exposure, including source-specific components in PM2.5, and cognition in older adults.

Methods

Cognitive assessment, including the Cognitive Abilities Screening Instrument (CASI), Digit Symbol Coding (DSC), and Digit Span (DS), was completed in 4392 older participants in the United States during 2010-2012. Residence-specific air pollution exposures (i.e., oxides of nitrogen [NO2/NOx], PM2.5 and its components: elemental carbon [EC], organic carbon [OC], sulfur [S], and silicon [Si]) were estimated by geo-statistical models. Linear and logistic regression models were used to estimate the associations between each air pollutants metric and cognitive function.

Results

An interquartile range (IQR) increase in EC (0.8 μg/m3) and Si (23.1 ng/m3) was associated with -1.27 (95% confidence interval [CI]: -0.09, -2.45) and -0.88 (95% CI: -0.21, -1.54) lower CASI scores in global cognitive function. For each IQR increase in Si, the odds of low cognitive function (LCF) across domains was 1.29 times higher (95% CI: 1.04, 1.60). For other tests, NO X was associated with slower processing speed (DSC: -2.01, 95% CI: -3.50, -0.52) and worse working memory (total DS: -0.4, 95% CI: -0.78, -0.01). No associations were found for PM2.5 and two PM2.5 components (OC and S) with any cognitive function outcomes.

Conclusion

Higher exposure to traffic-related air pollutants including both tailpipe (EC and NO x ) and non-tailpipe (Si) species were associated with lower cognitive function in older adults.

Curcumin Ameliorates Neurobehavioral Deficits in Ambient Dusty Particulate Matter-Exposure Rats: The Role of Oxidative Stress

It has been consistently found that exposure to ambient air pollution, such as particulate matter (PM), results in cognitive impairments and mental disorders. This study aimed to investigate the possible neuroprotective effects of curcumin, a polyphenol compound, on the neurobehavioral deficits and to identify the role of oxidative stress in dusty PM exposure rats. Rats received curcumin (50 mg/kg, daily, gavage, 2 weeks) 30 min before placing animals in a clean air chamber (≤ 150 µg/m³, 60 min daily, 2 weeks) or ambient dusty PM chamber (2000-8000 µg/m³, 60 min daily, 2 weeks). Subsequently, the cognitive and non-cognitive functions of the animals were evaluated using standard behavioral tests. Moreover, blood-brain barrier (BBB) permeability, brain water content (BWC), oxidative-antioxidative status, and histological changes were determined in the cerebral cortex and hippocampal areas of the rats. Our results showed that curcumin administration in dusty PM exposure rats attenuates memory impairment, decreases anxiety-/depression-like behaviors, and improves locomotor/exploratory activities. These findings were accompanied by reduced BBB permeability and BWC, decreasing oxidative stress, and lessening neuronal loss in the cerebral cortex and different hippocampal areas. The results of this study suggest that curcumin's antioxidant properties may contribute to its efficacy in improving neurobehavioral deficits and preventing neuronal loss associated with dusty PM exposure.

Haze and inbound tourism: Empirical evidence from China

The impact of climate change on tourism has always been an important topic for research in the field of international tourism, and haze has been widely recognized as the primary negative factor affecting the development of inbound tourism in China. In this study, we first conduct a theoretical analysis of the mechanism through which haze influences the tourism industry, and then we empirically analyze the impact on China's inbound tourism using surface particulate matter (PM2.5) concentrations as a proxy for haze, based on provincial panel data from 1998 to 2016. The empirical results show that haze not only has an inhibitory effect on inbound tourism, but also significantly reduces the average length of stay of international tourists. In addition, while there are significant regional differences in the crowding-out effect of haze pollution on inbound tourism, the effect varies depending on the origin of inbound tourists, exhibiting the greatest negative impact on inbound tourism from Taiwan and the smallest from foreign countries. Our research highlights that haze pollution can led to the change of human tourism behavior which enrich the literature on tourism and haze.

Incident dementia and long-term exposure to constituents of fine particle air pollution: A national cohort study in the United States

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO3-), sulfate (SO42-), ammonium (NH4+), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer's disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration-response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO42-, and NH4+ for both end points (even after adjustments of other constituents), among which BC and SO42- showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO42-, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

Neighbourhood walkability in relation to cognitive functioning in patients with disorders along the heart-brain axis

This study examined associations of neighbourhood walkability with cognitive functioning (i.e., global cognition, memory, language, attention-psychomotor speed, and executive functioning) in participants without or with either heart failure, carotid occlusive disease, or vascular cognitive impairment. Neighbourhood walkability at baseline was positively associated with global cognition and attention-psychomotor speed. These associations were stronger in patients with vascular cognitive impairment. Individuals who live in residential areas with higher walkability levels were less likely to have impairments in language and executive functioning at two-year follow-up. These findings highlight the importance of the built environment for cognitive functioning in healthy and vulnerable groups.

Alzheimer's disease-like cortical atrophy mediates the effect of air pollution on global cognitive function

Little is known about the effect of air pollution on Alzheimer's disease (AD)-specific brain structural pathologies. There is also a lack of evidence on whether this effect leads to poorer cognitive function. We investigated whether, and the extent to which, AD-like cortical atrophy mediated the association between air pollution exposures and cognitive function in dementia-free adults. We used cross-sectional data from 640 participants who underwent brain magnetic resonance imaging and the Montreal Cognitive Assessment (MoCA). Mean cortical thickness (as the measure of global cortical atrophy) and machine learning-based AD-like cortical atrophy score were estimated from brain images. Concentrations of particulate matter with diameters ≤ 10 μm (PM₁₀) and ≤ 2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) were estimated based on each participant's residential address. Following the product method, a mediation effect was tested by conducting a series of three regression analyses (exposure to outcome; exposure to mediator; and exposure and mediator to outcome). A 10 μg/m³ increase in PM₁₀ (β = -1.13; 95 % CI, -1.73 to -0.53) and a 10 ppb increase in NO₂ (β = -1.09; 95 % CI, -1.40 to -0.78) were significantly associated with a lower MoCA score. PM₁₀ (β = 0.27; 95 % CI, 0.06 to 0.48) and NO₂ (β = 0.35; 95 % CI, 0.25 to 0.45) were significantly associated with an increased AD-like cortical atrophy score. Effects of PM₁₀ and NO₂ on MoCA scores were significantly mediated by mean cortical thickness (proportions mediated: 25 %-28 %) and AD-like cortical atrophy scores (13 %-16 %). The findings suggest that air pollution exposures may induce AD-like cortical atrophy, and that this effect may lead to poorer cognitive function in dementia-free adults.

Exposure to indoor air pollution and the cognitive functioning of elderly rural women: a cross-sectional study using LASI data, India

BACKGROUND

The majority of people in rural developing counties still rely on unclean and solid fuels for cooking, putting their health at risk. Adult and elderly women are most vulnerable due to prolonged exposure in cooking areas, and Indoor Air Pollution (IAP) may negatively impact their health and cognitive function. This study examines the effect of IAP on the cognitive function of middle-aged and elderly rural women in India.

METHODS

The study utilized the data from the Longitudinal Ageing Study in India (LASI 2017-18, Wave-1). Bivariate analysis and multilevel linear regression models were applied to show the association between IAP and the cognitive abilities of rural women and results from regression were presented by beta coefficient (β) with 95% confidence interval (CI). Confounding factors such as age, education, health risk behaviours, marital status, monthly per capita consumption expenditure (MPCE), religion etc. were adjusted in the final model.

RESULTS

The study found that 18.71 percent of the rural women (n = 3,740) lived in Indoor Air Pollution exposed households. IAP was significantly found to be associated with the cognitive functional abilities among the middle and older aged rural women. Middle and older aged rural women exposed to IAP had lower cognitive functional abilities than non-exposed women. Comparing to the non-exposed group, the cognitive score was worse for those exposed to IAP in both the unadjusted (β = -1.96; 95%CI: -2.22 to -1.71) and the adjusted (β = -0.72; 95%CI: -0.92 to -0.51) models. Elderly rural women from lower socioeconomic backgrounds were more likely to have cognitive impairment as a result of IAP.

CONCLUSION

Findings revealed that IAP from solid fuels could significantly affect the cognitive health of elderly rural women in India, indicating the need for immediate intervention efforts to reduce the use of solid fuels, IAP and associated health problems.

Exposure to a real traffic environment impairs brain cognition in aged mice

Traffic-related air pollution (TRAP) has been a common public health problem, which is associated with central nervous system dysfunction according to large-scale epidemiological studies. Current studies are mostly limited to artificial laboratory exposure environments and specific genetic mechanisms remain unclear. Therefore, we chose a real-world transportation environment to expose aged mice, transporting them from the laboratory to a 1-m-high dry platform inside the campus and tunnel, and the mice were exposed daily from 7 a.m. to 7 p.m. for 2, 4 and 12 weeks respectively. Compared with the control group (in campus), the memory function of mice in the experimental group (in tunnel) was significantly impaired in the Morris water maze test. TRAP exposure increased the number of activated microglia in the hippocampal DG, CA1, CA3 regions and dorsolateral prefrontal cortex (dPFC). And neuroinflammation and oxidative stress levels were up-regulated in both hippocampus and dPFC of aged mice. By screening the risk genes of Alzheimer's disease, we found the mRNA and protein levels of ABCA7 were down-regulated and those of PYK2 were up-regulated. The DNA methylation ratios increased in four CpG sites of abca7 promoter region and decreased in one CpG site of pyk2 promoter region, which were consistent with the altered expression of ABCA7 and PYK2. In conclusion, exposure to the real traffic environment impaired memory function and enhanced neuroinflammation and oxidative stress responses, which could be relevant to the altered expression and DNA methylation levels of ABCA7 and PYK2. Our work provides a new and promising understanding of the pathological mechanisms of cognitive impairment caused by traffic-related air pollution.

Carbonaceous Nanoparticle Air Pollution: Toxicity and Detection in Biological Samples

Among the different air pollutants, particulate matter (PM) is of great concern due to its abundant presence in the atmosphere, which results in adverse effects on the environment and human health. The different components of PM can be classified based on their physicochemical properties. Carbonaceous particles (CPs) constitute a major fraction of ultrafine PM and have the most harmful effects. Herein, we present a detailed overview of the main components of CPs, e.g., carbon black (CB), black carbon (BC), and brown carbon (BrC), from natural and anthropogenic sources. The emission sources and the adverse effects of CPs on the environment and human health are discussed. Particularly, we provide a detailed overview of the reported toxic effects of CPs in the human body, such as respiratory effects, cardiovascular effects, neurodegenerative effects, carcinogenic effects, etc. In addition, we also discuss the challenges faced by and limitations of the available analytical techniques for the qualitative and quantitative detection of CPs in atmospheric and biological samples. Considering the heterogeneous nature of CPs and biological samples, a detailed overview of different analytical techniques for the detection of CPs in (real-exposure) biological samples is also provided. This review provides useful insights into the classification, toxicity, and detection of CPs in biological samples.

Air pollution and refraining from visiting health facilities: a cross-sectional study of domestic migrants in China

BACKGROUND

Local environmental factors are associated with health and healthcare-seeking behaviors. However, there is a paucity in the literature documenting the link between air pollution and healthcare-seeking behaviors. This study aimed to address the gap in the literature through a cross-sectional study of domestic migrants in China.

METHODS

Data were extracted from the 2017 China Migrants Dynamic Survey (n = 10,051) and linked to the official air pollution indicators measured by particulate matter (PM_2.5 and PM₁₀) and air quality index (AQI) in the residential municipalities (n = 310) of the study participants over the survey period. Probit regression models were established to determine the association between air pollution and refraining from visiting health facilities after adjustment for variations in the predisposing, enabling and needs factors. Thermal inversion intensity was adopted as an instrumental variable to overcome potential endogeneity.

RESULTS

One unit (µg/m³) increase in monthly average PM_2.5 was associated with 1.8% increase in the probability of refraining from visiting health facilities. The direction and significance of the link remained unchanged when PM_2.5 was replaced by AQI or PM₁₀. Higher probability of refraining from visiting health facilities was also associated with overwork (β = 0.066, p = 0.041) and good self-related health (β = 0.171, p = 0.006); whereas, lower probability of refraining from visiting health facilities was associated with short-distance (inter-county) migration (β=-0.085, p = 0.048), exposure to health education (β=-0.142, p < 0.001), a high sense of local belonging (β=-0.082, p = 0.018), and having hypertension/diabetes (β=-0.169, p = 0.005).

CONCLUSION

Air pollution is a significant predictor of refraining from visiting health facilities in domestic migrants in China.

Quantifying the multiple environmental, health, and economic benefits from the electrification of the Delhi public transport bus fleet, estimating a district-wise near roadway avoided PM2.5 exposure

This study investigates the co-benefits from the utilization of the battery-electric bus (BEB) fleet in the Delhi public transportation system as a part of the Delhi electric vehicles policy 2020. To this aim, an integrated quantitative assessment framework is developed to estimate the expected environmental, health, and economic co-benefits from replacing the currently existing public bus fleet with the new BEBs in Delhi. First, the model estimates the avoided emissions from deploying the BEB fleet, using a detailed battery energy simulation model, considering the impact of the battery capacity loss on the annual operational time (hours of service) of the BEB. The annual operational time of the BEB is greatly affected by its battery degradation, which results in time lost due to charging the battery. This indicates that the annual passenger-kilometer (PKM) delivered by the BEB is less than the regular bus, under the same traveling condition. Second, considering fine particles (PM_2.5) as the most health-harming pollutant, the model calculates the near roadway avoided PM_2.5 exposure in the selected traffic zones of 11 major districts of Delhi, using a Gaussian dispersion model. Third, the near roadway avoided PM_2.5 exposure is further used in a health impact assessment model, which considers concentration-response functions for several diseases to evaluate the public health benefits from introducing the BEB fleet in Delhi. The research findings indicate that, the utilization of the new BEB fleet leads to a 74.67% reduction in the total pollutant emissions from the existing bus fleet in Delhi. The results of the integrated co-benefits assessment reveal a significant reduction in PM_2.5 emissions (44 t/y), leading to avoidance of mortality (1370 cases) and respiratory diseases related hospital admissions (2808 cases), respectively, and an annual savings of about USD 383 million from the avoided mortality and morbidity cases in Delhi.

Long-term Traffic-related Air Pollutant Exposure and Amyotrophic Lateral Sclerosis Diagnosis in Denmark: A Bayesian Hierarchical Analysis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Limited evidence suggests ALS diagnosis may be associated with air pollution exposure and specifically traffic-related pollutants.

METHODS

In this population-based case-control study, we used 3,937 ALS cases from the Danish National Patient Register diagnosed during 1989-2013 and matched on age, sex, year of birth, and vital status to 19,333 population-based controls free of ALS at index date. We used validated predictions of elemental carbon (EC), nitrogen oxides (NO x ), carbon monoxide (CO), and fine particles (PM 2.5 ) to assign 1-, 5-, and 10-year average exposures pre-ALS diagnosis at study participants' present and historical residential addresses. We used an adjusted Bayesian hierarchical conditional logistic model to estimate individual pollutant associations and joint and average associations for traffic-related pollutants (EC, NO x , CO).

RESULTS

For a standard deviation (SD) increase in 5-year average concentrations, EC (SD = 0.42 µg/m 3 ) had a high probability of individual association with increased odds of ALS (11.5%; 95% credible interval [CrI] = -1.0%, 25.6%; 96.3% posterior probability of positive association), with negative associations for NO x (SD = 20 µg/m 3 ) (-4.6%; 95% CrI = 18.1%, 8.9%; 27.8% posterior probability of positive association), CO (SD = 106 µg/m 3 ) (-3.2%; 95% CrI = 14.4%, 10.0%; 26.7% posterior probability of positive association), and a null association for nonelemental carbon fine particles (non-EC PM 2.5 ) (SD = 2.37 µg/m 3 ) (0.7%; 95% CrI = 9.2%, 12.4%). We found no association between ALS and joint or average traffic pollution concentrations.

CONCLUSIONS

This study found high probability of a positive association between ALS diagnosis and EC concentration. Further work is needed to understand the role of traffic-related air pollution in ALS pathogenesis.

A review of respirable fine particulate matter (PM2.5)-induced brain damage

Respirable fine particulate matter (PM_2.5) has been one of the most widely publicized indicators of pollution in recent years. Epidemiological studies have established a strong association between PM_2.5, lung disease, and cardiovascular disease. Recent studies have shown that PM_2.5 is also strongly associated with brain damage, mainly cerebrovascular damage (stroke) and neurological damage to the brain (changes in cognitive function, dementia, psychiatric disorders, etc.). PM_2.5 can pass through the lung–gas–blood barrier and the “gut–microbial–brain” axis to cause systemic oxidative stress and inflammation, or directly enter brain tissue via the olfactory nerve, eventually damaging the cerebral blood vessels and brain nerves. It is worth mentioning that there is a time window for PM_2.5-induced brain damage to repair itself. However, the exact pathophysiological mechanisms of brain injury and brain repair are not yet fully understood. This article collects and discusses the mechanisms of PM_2.5-induced brain injury and self-repair after injury, which may provide new ideas for the prevention and treatment of cerebrovascular and cerebral neurological diseases.

Extracellular microRNA and cognitive function in a prospective cohort of older men: The Veterans Affairs Normative Aging Study

BACKGROUND

Aging-related cognitive decline is an early symptom of Alzheimer's disease and other dementias, and on its own can have substantial consequences on an individual's ability to perform important everyday functions. Despite increasing interest in the potential roles of extracellular microRNAs (miRNAs) in central nervous system (CNS) pathologies, there has been little research on extracellular miRNAs in early stages of cognitive decline. We leverage the longitudinal Normative Aging Study (NAS) cohort to investigate associations between plasma miRNAs and cognitive function among cognitively normal men.

METHODS

This study includes data from up to 530 NAS participants (median age: 71.0 years) collected from 1996 to 2013, with a total of 1,331 person-visits (equal to 2,471 years of follow up). Global cognitive function was assessed using the Mini-Mental State Examination (MMSE). Plasma miRNAs were profiled using small RNA sequencing. Associations of expression of 381 miRNAs with current cognitive function and rate of change in cognitive function were assessed using linear regression (N = 457) and linear mixed models (N = 530), respectively.

RESULTS

In adjusted models, levels of 2 plasma miRNAs were associated with higher MMSE scores (p < 0.05). Expression of 33 plasma miRNAs was associated with rate of change in MMSE scores over time (p < 0.05). Enriched KEGG pathways for miRNAs associated with concurrent MMSE and MMSE trajectory included Hippo signaling and extracellular matrix-receptor interactions. Gene targets of miRNAs associated with MMSE trajectory were additionally associated with prion diseases and fatty acid biosynthesis.

CONCLUSIONS

Circulating miRNAs were associated with both cross-sectional cognitive function and rate of change in cognitive function among cognitively normal men. Further research is needed to elucidate the potential functions of these miRNAs in the CNS and investigate relationships with other neurological outcomes.

Machine Learning for Prediction of Cognitive Health in Adults Using Sociodemographic, Neighbourhood Environmental, and Lifestyle Factors

The environment we live in, and our lifestyle within this environment, can shape our cognitive health. We investigated whether sociodemographic, neighbourhood environment, and lifestyle variables can be used to predict cognitive health status in adults. Cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (34-97 years) (n = 4141) was used. Cognitive function was measured using processing speed and memory tests, which were categorized into distinct classes using latent profile analysis. Sociodemographic variables, measures of the built and natural environment estimated using geographic information system data, and physical activity and sedentary behaviours were used as predictors. Machine learning was performed using gradient boosting machine, support vector machine, artificial neural network, and linear models. Sociodemographic variables predicted processing speed (r2 = 0.43) and memory (r2 = 0.20) with good accuracy. Lifestyle factors also accurately predicted processing speed (r2 = 0.29) but weakly predicted memory (r2 = 0.10). Neighbourhood and built environment factors were weak predictors of cognitive function. Sociodemographic (AUC = 0.84) and lifestyle (AUC = 0.78) factors also accurately classified cognitive classes. Sociodemographic and lifestyle variables can predict cognitive function in adults. Machine learning tools are useful for population-level assessment of cognitive health status via readily available and easy-to-collect data.

Association between Long-Term Air Pollution, Chronic Traffic Noise, and Resting-State Functional Connectivity in the 1000BRAINS Study

BACKGROUND

Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown.

OBJECTIVE

This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks.

METHODS

Data from 574 participants (44.1% female, 56-85 years of age) in the German 1000BRAINS study (2011-2015) were analyzed. Exposure to particulate matter (PM10, PM2.5, and PM2.5 absorbance), accumulation mode particle number (PNAM), and nitrogen dioxide (NO2) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h (Lden) and nighttime (Lnight) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables.

RESULTS

Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, -0.006 (95% CI: -0.021, 0.009) per 0.3 ×10-5/m increase in PM2.5 absorbance and -0.004 (95% CI: -0.006, -0.002) per 1-y age increase].

CONCLUSION

High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737.

Effects of air pollution on human health - Mechanistic evidence suggested by in vitro and in vivo modelling

Airborne particulate matter (PM) comprises both solid and liquid particles, including carbon, sulphates, nitrate, and toxic heavy metals, which can induce oxidative stress and inflammation after inhalation. These changes occur both in the lung and systemically, due to the ability of the small-sized PM (i.e. diameters ≤2.5 μm, PM_2.5) to enter and circulate in the bloodstream. As such, in 2016, airborne PM caused ∼4.2 million premature deaths worldwide. Acute exposure to high levels of airborne PM (eg. during wildfires) can exacerbate pre-existing illnesses leading to hospitalisation, such as in those with asthma and coronary heart disease. Prolonged exposure to PM can increase the risk of non-communicable chronic diseases affecting the brain, lung, heart, liver, and kidney, although the latter is less well studied. Given the breadth of potential disease, it is critical to understand the mechanisms underlying airborne PM exposure-induced disorders. Establishing aetiology in humans is difficult, therefore, in-vitro and in-vivo studies can provide mechanistic insights. We describe acute health effects (e.g. exacerbations of asthma) and long term health effects such as the induction of chronic inflammatory lung disease, and effects outside the lung (e.g. liver and renal change). We will focus on oxidative stress and inflammation as this is the common mechanism of PM-induced disease, which may be used to develop effective treatments to mitigate the adverse health effect of PM exposure.

Protecting playgrounds: local-scale reduction of airborne particulate matter concentrations through particulate deposition on roadside ‘tredges’ (green infrastructure)

Exposure to traffic-related particulate air pollution has been linked with excess risks for a range of cardiovascular, respiratory and neurological health outcomes; risks likely to be exacerbated in young children attending schools adjacent to highly-trafficked roads. One immediate way of reducing airborne PM concentrations at the local (i.e., near-road community) scale is installation of roadside vegetation as a means of passive pollution abatement. Roadside vegetation can decrease airborne PM concentrations, through PM deposition on leaves, but can also increase them, by impeding airflow and PM dispersion. Critical to optimizing PM removal is selection of species with high particle deposition velocity (Vd) values, currently under-parameterised in most modelling studies. Here, the measured amounts of leaf-deposited magnetic PM after roadside greening (‘tredge’) installation, and measured reductions in playground PM, particle number and black carbon concentrations demonstrate that air quality improvements by deposition can be achieved at the local, near-road, community/playground scale. PM deposition on the western red cedar tredge removed ~ 49% of BC, and ~ 46% and 26% of the traffic-sourced PM_2.5 and PM₁, respectively. These findings demonstrate that roadside vegetation can be designed, installed and maintained to achieve rapid, significant, cost-effective improvement of air quality by optimising PM deposition on plant leaves.

Long-term exposure to low-level air pollution, genetic susceptibility and risk of dementia

BACKGROUND

We aimed to assess the association between low-level air pollution and the risk of dementia, and examine the modification effect by genetic susceptibility on the relationship.

METHODS

A total of 164 447 participants who were free of dementia at baseline and aged ≥60 years were included. Annual average concentrations of particulate matter (PM) with diameters of ≤2.5 μm (PM2.5), between 2.5 and 10 μm (PMcoarse), PM2.5 absorbance and nitrogen dioxides (NO2) were evaluated using the Land Use Regression models. Cox proportional hazards regression was used to estimate the association between air pollutants and incident dementia.

RESULTS

The adjusted hazard ratio (HR) of dementia for a 5-μg/m3 increase in NO2 was 1.09 (95% CI, 1.05-1.14); the adjusted HR of dementia for a 1-μg/m3 increase in PM2.5 was 1.10 (1.04-1.17). Such significant associations were present even within concentration ranges well below the present World Health Organization, US and European annual mean limit values. In addition, higher PM2.5 absorbance, a marker closely related to motorized traffic, was associated with higher risk of dementia. We found the risk of dementia associated with a combination of air pollutants (NO2 or PM2.5) and high genetic susceptibility (APOE-ε4 alleles or overall genetic susceptibility) was greater than the addition of the risk associated with each individual factor, indicating significant interactions on an additive scale (all P-interaction < 0.05).

CONCLUSION

Long-term exposure to PM2.5 or NO2, even at relatively low levels, is associated with a higher risk of dementia. Air pollution may additively interact with the genetic susceptibility on dementia risk.

Association between cognitive function and ambient particulate matters in middle-aged and elderly Chinese adults: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Increasing studies have discussed how ambient air pollution affects cognitive function, however, the results are inconsistent, and such studies are limited in developing countries. To fill the gap, in this study, we aimed to explore the effect of ambient particulate matters (PM₁, PM_2.5, PM₁₀) on cognitive function of middle-aged and elderly Chinese adults. A total of 7928 participants older than 45 were included from CHARLS collected in 2011, 2013, and 2015. Cognitive function was evaluated with two dimensions, the first one was episodic memory and the second dimension was mental status. The total score of cognitive function was the sum of above two dimensions (0-31 points). Participants' exposure to ambient particulate matters was estimated by using a satellite-based spatiotemporal model. Linear mixed models were applied to analyze the impact of PM₁, PM_2.5, and PM₁₀ on cognition function. Further interaction analyses were applied to examine the potential effect modifications on the association. After adjusting for confounding factors, we found an IQR increase in all three ambient particulate matters was significantly associated with a decrease in cognitive function score, with the greatest effect in the 90-day exposure window for PM₁ (β = -0.227, 95%CI: -0.376, -0.078) and PM_2.5 (β = -0.220, 95%CI: -0.341, -0.099). For ambient PM₁₀, the most significant exposure window was 60-day (β = -0.158, 95%CI: -0.274, -0.042). Interaction analyses showed that the PM-cognitive function association could be modified by gender, region, alcohol consumption, smoking, education level, chronic diseases, and depressive symptoms. In conclusion, exposure to ambient particulate matter for a certain period would significantly decrease cognitive function among middle-aged and elderly Chinese. Furthermore, individuals who were female, or lived in the midland of China were more susceptible to the adverse effect of particulate matters.

Neuroinflammation in Low-Level PM2.5-Exposed Rats Illustrated by PET via an Improved Automated Produced [18F]FEPPA: A Feasibility Study

Background

[¹⁸F]FEPPA is a potent TSPO imaging agent that has been found to be a potential tracer for imaging neuroinflammation. In order to fulfill the demand of this tracer for preclinical and clinical studies, we have developed a one-pot automated synthesis with simplified HPLC purification of this tracer, which was then used for PET imaging of neuroinflammation in fine particulate matter- (PM2.5-) exposed rats.

Results

Using this automated synthesis method, the RCY of the [¹⁸F]FEPPA was 38 ± 4% (n = 17, EOB) in a synthesis time of 83 ± 8 min from EOB. The radiochemical purity and molar activities were greater than 99% and 209 ± 138 GBq/μmol (EOS, n = 15), respectively. The quality of the [¹⁸F]FEPPA synthesized by this method met the U.S. Pharmacopoeia (USP) criteria. The stability test showed that the [¹⁸F]FEPPA was stable at 21 ± 2°C for up to 4 hr after the end of synthesis (EOS). Moreover, microPET imaging showed that increased tracer activity of [¹⁸F]FEPPA in the brain of PM2.5-exposed rats (n = 6) were higher than that of normal controls (n = 6) and regional-specific.

Conclusions

Using the improved semipreparative HPLC purification, [¹⁸F]FEPPA has been produced in high quantity, high quality, and high reproducibility and, for the first time, used for PET imaging the effects of PM2.5 in the rat brain. It is ready to be used for imaging inflammation in various clinical or preclinical studies, especially for nearby PET centers without cyclotrons.

A review on factors influencing fog formation, classification, forecasting, detection and impacts

With the changing climate and environment, the nature of fog has also changed and because of its impact on humans and other systems, study of fog becomes essential. Hence, the study of its controlling factors such as the characteristics of condensation nuclei, microphysics, air–surface interaction, moisture, heat fluxes and synoptic conditions also become crucial, along with research in the field of prediction and detection. The current review expands for the period between 1976 to 2021, however, especially focused on the research articles published in the last two decades. It considers 250 research papers/research letters, 24 review papers, four book chapters/manuals, five news articles, 15 reports, six conference papers and five other online readings. This review is a compilation of the pros and cons of the techniques used to determine the factors influencing fog formation, its classification, tools and techniques available for its detection and forecast. Some recent advanced are also discussed in this review: role of soil properties on fogs, application of microwave communication links in the detection of fog, new class of smog, and how the cognitive abilities of humans are affected by fog. Recently India and China are facing an emergence and repetitions of fog haze/smog and thus their policies initiatives are also briefly discussed. It is concluded that the complexity in fog forecasting is high due to multiple factors playing a role at multiple levels. Most of the researchers have worked upon the role of humidity, temperature, wind, and boundary layer to predict fogs. However, the role of global wind circulations, soil properties, and anthropogenic heat requires further investigations. Literature shows that fog is being harnessed to address water insecurity in various countries, however, coastal areas of Angola, Namibia and South Africa, Kenya, Eastern Yemen, Oman, China, India, Sri Lanka, Mexico, along with the mountainous regions of Peru, Chile, and Ecuador, are some of the potential sites that can benefit from the installation of fog water harvesting systems.

Applied Machine Learning in Industry 4.0: Case-Study Research in Predictive Models for Black Carbon Emissions

Industry 4.0 constitutes a major application domain for sensor data analytics. Industrial furnaces (IFs) are complex machines made with special thermodynamic materials and technologies used in industrial production applications that require special heat treatment cycles. One of the most critical issues while operating IFs is the emission of black carbon (EoBC), which is due to a large number of factors such as the quality and amount of fuel, furnace efficiency, technology used for the process, operation practices, type of loads and other aspects related to the process conditions or mechanical properties of fluids at furnace operation. This paper presents a methodological approach to predict EoBC during the operation of IFs with the use of predictive models of machine learning (ML). We make use of a real data set with historical operation to train ML models, and through evaluation with real data we identify the most suitable approach that best fits the characteristics of the data set and implementation constraints in real production environments. The evaluation results confirm that it is possible to predict the undesirable EoBC well in advance, by means of a predictive model. To the best of our knowledge, this paper is the first approach to detail machine-learning concepts for predicting EoBC in the IF industry.

Possible association between PM2.5 and neurodegenerative diseases: A systematic review

Air pollution is one of the most serious environmental problems that afflict our planet and one of the greatest risk factors for human health. In particular, PM_2.5 is able to cross the blood-alveolar and blood-brain barriers, thus increasing the onset of respiratory, cardiovascular and neurodegenerative diseases. Neurodegenerative disease is a progressive neuronal dysfunction that leads to neuronal lesions in both structure and function, and includes several diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), vascular dementia (VaD), multiple sclerosis (MS), and others. We carried out a systematic review using PRISMA approach to investigate on the possible association between exposure to PM_2.5 and neurodegenerative diseases. The international databases (PubMed, Science Direct, Web of Sciences) were used to find published studies on the topic. The search period was between January 2011 and June 2021. About 2000 full research articles were selected, and finally, we included 20 full-research articles. Selected studies have highlighted how PM_2.5 exposure can be associated with the onset of neurodegenerative diseases (AD, PD, MS, VaD). This association depends not only on age, PM_2.5 levels and exposure time, but also on exposure to other air pollutants, proximity to areas with high vehicular traffic, and the presence of comorbidities. Exposure to PM_2.5 promotes neuroinflammation processes, because through breathing the particles can reach the nasal epithelial mucosa and transferred to the brain through the olfactory bulb. Furthermore, exposure to PM_2.5 has been associated with an increased expression of markers of neurodegenerative diseases (e.g. alpha-synuclein or beta-amyloid), which can contribute to the etiopathogenesis of neurodegenerative diseases. Although many studies have revealed the pathological relationship between PM_2.5 exposure and cognitive impairment, the potential cellular and molecular mechanisms of PM_2.5 leading to neurodegenerative disease remain not entirely clear, and then, further studies need to be carried out on the topic.

Diesel Aerosols in an Underground Coal Mine

The case study was conducted in an underground coal mine to characterize submicron aerosols at a continuous miner (CM) section, assess the concentrations of diesel aerosols at the longwall (LW) section, and assess the exposures of selected occupations to elemental carbon (EC) and total carbon (TC). The results show that aerosols at the CM sections were a mixture of aerosols freshly generated at the outby portion of the CM section and those generated in the main drifts that supply "fresh air" to the section. The relatively low ambient concentrations and personal exposures of selected occupations suggest that currently applied control strategies and technologies are relatively effective in curtailing exposures to diesel aerosols. Further reductions in EC and TC concentrations and personal exposures to those would be possible by more effective curtailment of emissions from high-emitting light duty (LD) vehicles.

Role of brain extracellular vesicles in air pollution-related cognitive impairment and neurodegeneration

A relationship between environmental exposure to air pollution and cognitive impairment and neurological disorders has been described. Previous literature has focused on the direct effects of the air pollution components on neuronal and glial cells, as well as on involvement of oxidative stress and neuroinflammation on microglia and astrocyte reactivity. However, other mechanisms involved in the air pollution effects on central nervous system (CNS) toxicity can be playing critical roles. Increasingly, extracellular vesicle's (EVs) mediated intercellular communication is being recognized as impacting the development of cognitive impairment and neurological disorders like Alzheimer's disease and others. Here we describe the available evidence about toxic air pollutants and its components on brain, an involvement of brain cells specific and EVs types (based in the origin or in the size of EVs) in the initiation, exacerbation, and propagation of the neurotoxic effects (inflammation, neurodegeneration, and accumulation of neurotoxic proteins) induced by air pollution in the CNS. Additionally, we discuss the identification and isolation of neural-derived EVs from human plasma, the most common markers for neural-derived EVs, and their potential for use as diagnostic or therapeutic molecules for air pollution-related cognitive impairment and neurodegeneration.

Association between indoor ventilation frequency and cognitive function among community-dwelling older adults in China: results from the Chinese longitudinal healthy longevity survey

Backgrounds

Emerging evidence suggested that indoor air pollution caused long-term adverse effects on cognitive function among older adults who spend more than 85% of their time indoors. Although high indoor ventilation can mitigate the effect of indoor air pollution on cognition among the younger population, limited evidence revealed the association between indoor ventilation and cognition among older adults.

Methods

A total of 11,853 participants aged 65 and over (female, 54.5%; mean age, 83.6 years) were included from the 2017–2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Indoor ventilation frequency was measured by the self-reported frequency of opening windows per week in each season. Cognitive function was evaluated by the Mini-Mental State Examination (MMSE). Multivariate Poisson regression with robust error variance was applied to assess the association between overall indoor ventilation frequency and cognitive function. We fitted in two adjusted models: Model 1 was adjusted for demographic; model 2 was further adjusted for lifestyle, socioeconomic status, health conditions, and environmental factors. The same models were also applied to measure the association between seasonal indoor ventilation frequency and cognitive function.

Results

Of 11,853 older adults, 3035 (25.6%) had cognitive impairment. A high overall indoor ventilation frequency (indoor ventilation frequency: 6–8) was significantly associated with a 9% lower likelihood of cognitive impairment than low overall indoor ventilation frequency (indoor ventilation frequency: 0–3) among Chinese older adults [Relative risk (RR): 0.91, 95% Confidential Interval (CI): 0.83–0.99] in the full adjusted model. In the subgroup analysis in four seasons, high and intermediate indoor ventilation frequency in winter were significantly associated with 8% (RR: 0.92; 95%CI: 0.86–0.99) and 16% (RR: 0.84; 95%CI: 0.78–0.90) lower probability of cognitive impairment than low indoor ventilation frequency in the fully adjusted model among Chinese older adults, respectively.

Conclusions

In this nationally representative cohort, a higher frequency of house ventilation by opening windows was significantly associated with a lower risk of cognitive impairment among Chinese older adults aged 65 and over. These results offered robust evidence for policymaking and health intervention to prevent older adults from cognitive impairment or dementia in developing regions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02805-1.

Physical activity attenuates negative effects of short-term exposure to ambient air pollution on cognitive function

BACKGROUND

As physical activity benefits brain health whereas air pollution damages it, the cognitive response to these exposures may interact.

PURPOSE

This study aimed to assess the short-term joint effect of physical activity and air pollution on cognitive function in a panel of healthy young adults.

METHODS

We followed ninety healthy subjects aged around 22 years from September 2020 to June 2021 and measured their personal exposure to fine particulate matter (PM_2.5) (μg/m³) and daily accelerometer-based moderate-to-vigorous physical activity (MVPA) (min/day) in 4 one-week-long sessions over the study period. At the end of each measurement session, we assessed executive function using Stroop color-word test and collected resting-state electroencephalogram (EEG) signals.

RESULTS

We found short-term PM_2.5 exposure damaged executive function (β_PM25 = 0.0064, p = 0.039) but physical activity could counterbalance it (β_MVPA = -0.0047, p = 0.048), whereby beta-3 wave played as a potential mediating role. MVPA-induced improvement on executive function was larger in polluted air (β_MVPA = -0.010, p = 0.035) than that in clean air (β_MVPA = -0.003, p = 0.45). To offset the negative effect of air pollution on cognitive function, individuals should do extra 13.6 min MVPA every day for every 10 μg/m³ increase in daily PM_2.5.

CONCLUSION

This study implies that physical activity could be used as a preventive approach to compensate the cognitive damages of air pollution.

Childhood Abuse and Cognitive Function in a Large Cohort of Middle-Aged Women

Cognitive function at middle age is of particular public health interest, as it strongly predicts later dementia. Children who have experienced abuse subsequently have worse cognitive function than those who have not. However, it remains unclear whether the association of abuse with cognitive function persists into middle age. In 2014-2016, 14,151 women ages 49-69 years who had previously responded to a childhood abuse questionnaire completed a cognitive battery. In models adjusted for childhood socioeconomic status and head trauma, combined physical, emotional, and sexual abuse was associated with lower scores on both Learning/Working Memory (severe abuse, lower scores similar to that observed in women 4.8 years older in our data) and Psychomotor Speed/Attention (severe abuse, lower scores similar to that observed in women to 2.9 years older in our data). Adjustment for adulthood socioeconomic status and health factors (e.g., smoking, hypertension) slightly attenuated associations. In exploratory analyses further adjusted for psychological distress, associations were attenuated. Women exposed versus unexposed to childhood abuse had poorer cognitive function at mid-life. Associations were particularly strong for learning and working memory and were not accounted for by adulthood health factors. Childhood abuse should be investigated as a potential risk factor for cognitive decline and dementia in old age.