Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study

Degenerative dementia, of which Alzheimer’s disease is the most common form, is characterized by the gradual deterioration of cognitive function. The events that trigger and promote degenerative dementia are not clear, and treatment options are limited. Experimental and epidemiological studies have revealed chronic noise exposure (CNE) as a potential risk factor for cognitive impairment and degenerative dementia. Experimental studies have indicated that long-term exposure to noise might accelerate cognitive dysfunction, amyloid-β deposition, and tau hyperphosphorylation in different brain regions such as the hippocampus and cortex. Epidemiological studies are increasingly examining the possible association between external noise exposure and dementia. In this review, we sought to construct a comprehensive summary of the relationship between CNE, cognitive dysfunction, and degenerative dementia. We also present the limitations of existing evidence as a guide regarding important prospects for future research.

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“…Another study analyzed both traffic noise and road 470 proximity and reached a similar conclusion [122].…”

mentioning

confidence: 74%

Relationship Between Chronic Noise Exposure, Cognitive Impairment, and Degenerative Dementia: Update on the Experimental and Epidemiological Evidence and Prospects for Further Research

Huang

Zhang

Wang

et al. 2021

JAD

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“…Interestingly, from our result, the risks of PM 2.5 on AD had a nonnegligible decline since 2019. With per 5 g/m 3 PM 2.5 increase, the OR of AD declined 9%, when another indicated that with per 1.54 g/m 3 PM 2.5 increase, the OR of AD dropped 10% [33,37]. We speculated it might result from the low PM 2.5 concentrations in these two countries (regions) (4.1 and 19.7 g/m 3 ) and benign health care services.…”

Section: Mechanisms Of the Association Between Pm And Admentioning

confidence: 86%

Air Pollution and Alzheimer’s Disease: A Systematic Review and Meta-Analysis

Yung

2020

JAD

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Background: Ambient air pollution has been associated with Alzheimer’s disease (AD) in the elderly. However, its effects on AD have not been meta-analyzed comprehensively. Objective: We conducted a systematic review and meta-analysis to assess the associations between air pollution and AD incidence. Methods: We searched PubMed and Web of Science for indexed publications up to March 2020. Odds risk (OR) and confidence intervals (CI) were estimated for particulate matter (PM)10 (PM10), PM2.5, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). The subgroup analysis was conducted based on the pollution levels. Results: Nine studies were included in the meta-analysis and review. The OR per 10μg/m3 increase of PM2.5 was 1.95 (95% CI: 0.88–4.30). The corresponding values per 10μg/m3 increment of other pollutants were 1.03 (95% CI: 0.68–1.57) for O3, 1.00 (95% CI: 0.89–1.13) for NO2, and 0.95 (95% CI: 0.91–0.99) for PM10 (only one study), respectively. Overall OR of the five air pollutants above with AD was 1.32 (95% CI: 1.09–1.61), suggesting a positive association between ambient air pollution and AD incidence. The sub-analysis indicated that the OR (2.20) in heavily polluted regions was notably higher than that in lightly polluted regions (1.06). Although AD risk rate data related to SO2 or CO exposure are still limited, the epidemiologic and toxicological evidence indicated that higher concentration of SO2 or CO exposure increased risks of dementia, implying that SO2 or CO might have a potential impact on AD. Conclusion: Air pollution exposure may exacerbate AD development.

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“…The use of proxies and surrogates is a legitimate and common practice in epidemiological research ( 31 , 32 ), whenever objective data on the exposure and/or outcome of interest is not available, which is the case. On the other hand, in environmental and spatial epidemiology, geographic proximity to emission sources (e.g., major roads, industries) is commonly used as a proxy measure of personal exposure to air pollutants and\noise ( 33 , 34 ), under the assumption that individuals tend to spend their day within the home surroundings. Accordingly, it seems to us legitimate to assume that populations living near railway stations will be more likely to use them (i.e., to be exposed) than populations living far from railway stations.…”

Section: Discussionmentioning

confidence: 99%

Urban Rail Transportation and SARS-Cov-2 Infections: An Ecological Study in the Lisbon Metropolitan Area

Severo

Ribeiro

Lucas

et al. 2021

Front. Public Health

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Introduction: The large number of passengers, limited space and shared surfaces can transform public transportation into a hub of epidemic spread. This study was conducted to investigate whether proximity to railway stations, a proxy for utilization, was associated with higher rates of SARS-CoV-2 infection across small-areas of the Lisbon Metropolitan Area (Portugal).Methods: The number of SARS-CoV-2 confirmed infections from March 2 until July 5, 2020 at the parish-level was obtained from the National Epidemiological Surveillance System. A Geographic Information System was used to estimate proximity to railway stations of the six railway lines operating in the area. A quasi-Poisson generalized linear regression model was fitted to estimate the relative risks (RR) and corresponding 95% confidence intervals (95%CI).Results: Between May 2 and July 5, 2020, there were a total of 17,168 SARS-CoV-2 infections in the Lisbon Metropolitan Area, with wide disparities between parishes. Overall, parishes near any of the railway stations of the Sintra line presented significantly higher SARS-CoV-2 infection rates (RR = 1.42, 95%CI 1.16, 1.75) compared to parishes located farther away from railway stations, while the opposite was observed for parishes near other railway stations (Sado and Fertagus lines), where infection rates were significantly lower than those observed in parishes located farther away from railway stations (RR = 0.66, 95%CI 0.50, 0.87). The associations varied according to the stage of the epidemic and to the mitigation measures enforced. Regression results also revealed an increasing influence of socioeconomic deprivation on SARS-CoV-2 infections.Conclusions: No consistent association between proximity to railway stations and SARS-CoV-2 infection rates in the most affected metropolitan area of Portugal was observed, suggesting that other factors (e.g., socioeconomic deprivation) may play a more prominent role in the epidemic dynamics.

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Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study

Cited by 140 publications

References 74 publications

Relationship Between Chronic Noise Exposure, Cognitive Impairment, and Degenerative Dementia: Update on the Experimental and Epidemiological Evidence and Prospects for Further Research

Relationship Between Chronic Noise Exposure, Cognitive Impairment, and Degenerative Dementia: Update on the Experimental and Epidemiological Evidence and Prospects for Further Research

Air Pollution and Alzheimer’s Disease: A Systematic Review and Meta-Analysis

Urban Rail Transportation and SARS-Cov-2 Infections: An Ecological Study in the Lisbon Metropolitan Area

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