Effects of air pollution on dementia over Europe for present and future climate change scenarios

Association Between Long-Term Exposure to Ambient Air Pollution and the Risk of Mild Cognitive Impairment in a Chinese Urban Area: A Case-Control Study

Background

As a prodromal stage of dementia, significant emphasis has been placed on the identification of modifiable risks of mild cognitive impairment (MCI). Research has indicated a correlation between exposure to air pollution and cognitive function in older adults. However, few studies have examined such an association among the MCI population inChina.

Objective

We aimed to explore the association between air pollution exposure and MCI risk from the Hubei Memory and Aging Cohort Study.

Methods

We measured four pollutants from 2015 to 2018, 3 years before the cognitive assessment of the participants. Logistic regression models were employed to calculate odds ratios (ORs) to assess the relationship between air pollutants and MCI risk.

Results

Among 4,205 older participants, the adjusted ORs of MCI risk for the highest quartile of PM2.5, PM10, O3, and SO2 were 1.90 (1.39, 2.62), 1.77 (1.28, 2.47), 0.56 (0.42, 0.75), and 1.18 (0.87, 1.61) respectively, compared with the lowest quartile. Stratified analyses indicated that such associations were found in both males and females, but were more significant in older participants.

Conclusions

Our findings are consistent with the growing evidence suggesting that air pollution increases the risk of mild cognitive decline, which has considerable guiding significance for early intervention of dementia in the older population. Further studies in other populations and broader geographical areas are warranted to validate these findings.

The use of environmental scenarios to project future health effects: a scoping review

Environmental risks are a substantial factor in the current burden of disease, and their role is likely to increase in the future. Model-based scenario analysis is used extensively in environmental sciences to explore the potential effects of human activities on the environment. In this Review, we examine the literature on scenarios modelling environmental effects on health to identify the most relevant findings, common methods used, and important research gaps. Health outcomes and measures related to climate change (n=106) and air pollution (n=30) were most frequently studied. Studies examining future disease burden due to changes or policies related to dietary risks were much less common (n=10). Only a few studies assessed more than two environmental risks (n=3), even though risks can accumulate and interact with each other. Studies predominantly covered high-income countries and Asia. Sociodemographic, vulnerability, and health-system changes were rarely accounted for; thus, assessing the full effect of future environmental changes in an integrative way is not yet possible. We recommend that future models incorporate a broader set of determinants of health to more adequately capture their effect, as well as the effect of mitigation and adaptation efforts.

High-risk spatiotemporal patterns of cutaneous leishmaniasis: a nationwide study in Iran from 2011 to 2020

BACKGROUND

Cutaneous leishmaniasis (CL) is a wide-reaching infection of major public health concern. Iran is one of the six most endemic countries in the world. This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020, detecting high-risk zones, while also noting the movement of high-risk clusters.

METHODS

On the basis of clinical observations and parasitological tests, data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education. Utilizing spatial scan statistics, we investigated the disease's purely temporal, purely spatial, spatial variation in temporal trends and spatiotemporal patterns. At P = 0.05 level, the null hypothesis was rejected in every instance.

RESULTS

In general, the number of new CL cases decreased over the course of the 9-year research period. From 2011 to 2020, a regular seasonal pattern, with peaks in the fall and troughs in the spring, was found. The period of September-February of 2014-2015 was found to hold the highest risk in terms of CL incidence rate in the whole country [relative risk (RR) = 2.24, P < 0.001)]. In terms of location, six significant high-risk CL clusters covering 40.6% of the total area of the country were observed, with the RR ranging from 1.87 to 9.69. In addition, spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency. Finally, five space-time clusters were found. The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period affecting many regions of the country.

CONCLUSIONS

Our study has revealed significant regional, temporal, and spatiotemporal patterns of CL distribution in Iran. Over the years, there have been multiple shifts in spatiotemporal clusters, encompassing many different parts of the country from 2011 to 2020. The results reveal the formation of clusters across counties that cover certain parts of provinces, indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries. Such analyses, at a finer geographical scale, such as county level, might provide more precise results than analyses at the scale of the province.

Health risk assessment for particulate matter: application of AirQ+ model in the northern Caribbean region of Colombia

Air pollution is considered the world's most important environmental and public health risk. The annual exposure for particulate matter (PM) in the northern Caribbean region of Colombia between 2011 and 2019 was determined using PM records from 25 monitoring stations located within the area. The impact of exposure to particulate matter was assessed through the updated Global Burden of Disease health risk functions using the AirQ+ model for mortality attributable to acute lower respiratory disease (in children ≤ 4 years); mortality in adults aged > 18 years old attributable to chronic obstructive pulmonary disease, ischaemic heart disease, lung cancer, and stroke; and all-cause post-neonatal infant mortality. The proportions of the prevalence of bronchitis in children and the incidence of chronic bronchitis in adults attributable to PM exposure were also estimated for the population at risk. Weather Research and Forecasting-California PUFF (WRF-CALPUFF) modeling systems were used to estimate the spatiotemporal trends and calculate mortality relative risk due to prolonged PM_2.5 exposure. Proportions of mortality attributable to long-term exposure to PM_2.5 were estimated to be around 11.6% of ALRI deaths in children ≤ 4 years of age, 16.1% for COPD, and 26.6% for IHD in adults. For LC and stroke, annual proportions attributable to PM exposure were estimated to be 9.1% and 18.9%, respectively. An estimated 738 deaths per year are directly attributed to particulate matter pollution. The highest number of deaths per year is recorded in the adult population over 18 years old with a mean of 401 events. The mean risk in terms of the prevalence of bronchitis attributable to air pollution in children was determined to be 109 per 100,000 inhabitants per year. The maximum RR values for mortality (up 1.95%) from long-term PM_2.5 exposure were predicted to correspond to regions downwind to the industrial zone.

Supplementary information

The online version contains supplementary material available at 10.1007/s11869-023-01304-5.

Mitigating the impact of air pollution on dementia and brain health: Setting the policy agenda

BACKGROUND

Emerging research suggests exposure to high levels of air pollution at critical points in the life-course is detrimental to brain health, including cognitive decline and dementia. Social determinants play a significant role, including socio-economic deprivation, environmental factors and heightened health and social inequalities. Policies have been proposed more generally, but their benefits for brain health have yet to be fully explored.

OBJECTIVE AND METHODS

Over the course of two years, we worked as a consortium of 20+ academics in a participatory and consensus method to develop the first policy agenda for mitigating air pollution's impact on brain health and dementia, including an umbrella review and engaging 11 stakeholder organisations.

RESULTS

We identified three policy domains and 14 priority areas. Research and Funding included: (1) embracing a complexities of place approach that (2) highlights vulnerable populations; (3) details the impact of ambient PM_2.5 on brain health, including current and historical high-resolution exposure models; (4) emphasises the importance of indoor air pollution; (5) catalogues the multiple pathways to disease for brain health and dementia, including those most at risk; (6) embraces a life course perspective; and (7) radically rethinks funding. Education and Awareness included: (8) making this unrecognised public health issue known; (9) developing educational products; (10) attaching air pollution and brain health to existing strategies and campaigns; and (11) providing publicly available monitoring, assessment and screening tools. Policy Evaluation included: (12) conducting complex systems evaluation; (13) engaging in co-production; and (14) evaluating air quality policies for their brain health benefits.

CONCLUSION

Given the pressing issues of brain health, dementia and air pollution, setting a policy agenda is crucial. Policy needs to be matched by scientific evidence and appropriate guidelines, including bespoke strategies to optimise impact and mitigate unintended consequences. The agenda provided here is the first step toward such a plan.

The role of geographic information system and global positioning system in dementia care and research: a scoping review

Background

Geographic Information System (GIS) and Global Positioning System (GPS), vital tools for supporting public health research, provide a framework to collect, analyze and visualize the interaction between different levels of the health care system. The extent to which GIS and GPS applications have been used in dementia care and research is not yet investigated. This scoping review aims to elaborate on the role and types of GIS and GPS applications in dementia care and research.

Methods

A scoping review was conducted based on Arksey and O’Malley’s framework. All published articles in peer-reviewed journals were searched in PubMed, Scopus, and Web of Science, subject to involving at least one GIS/GPS approach focused on dementia. Eligible studies were reviewed, grouped, and synthesized to identify GIS and GPS applications. The PRISMA standard was used to report the study.

Results

Ninety-two studies met our inclusion criteria, and their data were extracted. Six types of GIS/GPS applications had been reported in dementia literature including mapping and surveillance (n = 59), data preparation (n = 26), dementia care provision (n = 18), basic research (n = 18), contextual and risk factor analysis (n = 4), and planning (n = 1). Thematic mapping and GPS were most frequently used techniques in the dementia field.

Conclusions

Even though the applications of GIS/GPS methodologies in dementia care and research are growing, there is limited research on GIS/GPS utilization in dementia care, risk factor analysis, and dementia policy planning. GIS and GPS are space-based systems, so they have a strong capacity for developing innovative research based on spatial analysis in the area of dementia. The existing research has been summarized in this review which could help researchers to know the GIS/GPS capabilities in dementia research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00308-1.

Catastrophic PM2.5 emissions from Siberian forest fires: Impacting factors analysis

With increased forest fires due to climate change, PM_2.5 emissions also intensified. Record PM_2.5 emissions according to Copernicus Atmosphere Monitoring Service in Russia amounted to 8 megatons (Mt) in 2021, which is 78% higher than the average level of 2004-2021 (4.5 Mt). Seven federal subjects (the constituent entities) with vast forest areas without fire protection produced 86% of emissions (6.8 Mt) in 2021, the major losses (6.1 Mt) in Yakutia (Sakha Republic). The ambient temperature in Eastern Siberia is increasing, especially in months of winter and spring seasons (up to +3.6 °C) in 1990-2020 compared to 1901-2020 (CEDA Archive); climate change has affected meteorological conditions leading to increased forest fires. The results of the SARIMAX model study for PM_2.5 emissions considering meteorological factors using ERA5 and burnt forest area using MODIS (MCD64A1), establishing a significant dependence of PM_2.5 emissions on the lack of precipitation and the associated parameters of complete and potential evaporation. This influence long before the fire season (up to 9 months), as it affects the snow cover and the dryness of the fuel by the beginning of forest fires. In turn, high PM_2.5 emission values are accompanied by a drop in 2 m air temperature and surface solar radiation downwards due to the aerosol saturation with suspended particles. The average COR for seven federal subjects was 0.79, with the highest forecast result in Yakutia (0.95), indicating the maximum propensity for record emissions due to weather conditions. In combination with forest management without fire protection, meteorological parameters have caused an increase in PM_2.5 emissions in recent years in Siberia. The forest needs other ways to manage under the pressures of climate change to reduce environmental pollution associated with PM_2.5 emissions from vast Siberian fires.

An Empirical Study for Senior Citizens Using a Customized Medical Informatics System for Dementia Diagnosis and Analysis

The treatment of dementia-related diseases is a global issue. Taiwan is facing a more serious dementia problem due to the combination of an aging society and a declining birthrate. A great portion of healthcare resources has been utilized for dementia among the aged population. In order to understand how dementia develops in rural areas in Taiwan, a cooperated effort between the university and a regional hospital was formed to develop a customized medical information system to collect and track dementia patients. This efficient customized system compiled information on 768 patients with dementia-released diseases. Big data technology and data mining approaches were then applied to analyze the relevant information. Using statistical analysis, we then extracted useful medical findings from the large amounts of collected medical data. Some of the findings indicate that the patients’ education level and care practices have a major effect on the dementia severity in these local senior populations.

Climate change and COVID-19: shared challenges, divergent perspectives, and proposed collaborative solutions

Pandemics leave their mark quickly. This is true for all pandemics, including COVID-19. Its multifarious presence has wreaked havoc on people's physical, economic, and social life since late 2019. Despite the need for social science to save lives, it is also critical to ensure future generations are protected. COVID-19 appeared as the world grappled with the epidemic of climate change. This study suggests policymakers and practitioners address climate change and COVID-19 together. This article offers a narrative review of both pandemics' impacts. Scopus and Web of Science were sought databases. The findings are reported analytically using important works of contemporary social theorists. The analysis focuses on three interconnected themes: technology advancements have harmed vulnerable people; pandemics have macro- and micro-dimensions; and structural disparities. To conclude, we believe that collaborative effort is the key to combating COVID-19 and climate change, while understanding the lessons learnt from the industrialised world. Finally, policymakers can decrease the impact of global catastrophes by addressing many socioeconomic concerns concurrently.

What Are the Sectors Contributing to the Exceedance of European Air Quality Standards over the Iberian Peninsula? A Source Contribution Analysis

The Iberian Peninsula, located in southwestern Europe, is exposed to frequent exceedances of different threshold and limit values of air pollution, mainly related to particulate matter, ozone, and nitrous oxide. Source apportionment modeling represents a useful modeling tool for evaluating the contribution of different emission sources or sectors and for designing useful mitigation strategies. In this sense, this work assesses the impact of various emission sectors on air pollution levels over the Iberian Peninsula using a source contribution analysis (zero-out method). The methodology includes the use of the regional WRF + CHIMERE modeling system (coupled to EMEP emissions). In order to represent the sensitivity of the chemistry and transport of gas-phase pollutants and aerosols, several emission sectors have been zeroed-out to quantify the influence of different sources in the area, such as on-road traffic or other mobile sources, combustion in energy generation, industrial emissions or agriculture, among others. The sensitivity analysis indicates that large reductions of precursor emissions (coming mainly from energy generation, road traffic, and maritime-harbor emissions) are needed for improving air quality and attaining the thresholds set in the European Directive 2008/50/EC over the Iberian Peninsula.

The pathogenic effects of particulate matter on neurodegeneration: a review

The increasing amount of particulate matter (PM) in the ambient air is a pressing public health issue globally. Epidemiological studies involving data from millions of patients or volunteers have associated PM with increased risk of dementia and Alzheimer’s disease in the elderly and cognitive dysfunction and neurodegenerative pathology across all age groups, suggesting that PM may be a risk factor for neurodegenerative diseases. Neurodegenerative diseases affect an increasing population in this aging society, putting a heavy burden on economics and family. Therefore, understanding the mechanism by which PM contributes to neurodegeneration is essential to develop effective interventions. Evidence in human and animal studies suggested that PM induced neurodenegerative-like pathology including neurotoxicity, neuroinflammation, oxidative stress, and damage in blood–brain barrier and neurovascular units, which may contribute to the increased risk of neurodegeneration. Interestingly, antagonizing oxidative stress alleviated the neurotoxicity of PM, which may underlie the essential role of oxidative stress in PM’s potential effect in neurodegeneration. This review summarized up-to-date epidemiological and experimental studies on the pathogenic role of PM in neurodegenerative diseases and discussed the possible underlying mechanisms.