Outdoor artificial light at night and risk of early-onset dementia: A case-control study in the Modena population, Northern Italy.

Background: Dementia is a neurological syndrome characterized by severe cognitive impairment with functional impact on everyday life. It can be classified as young onset dementia (EOD) in case of symptom onset before 65, and late onset dementia (LOD). The purpose of this study is to assess the risk of dementia due to light pollution, and specifically outdoor artificial light at night (LAN). Methods: Using a case-control design, we enrolled dementia patients newly-diagnosed in the province of Modena in the period 2017-2019 and a referent population from their caregivers. We geo-referenced the address of residence on the date of recruitment, provided it was stable for the previous five years. We assessed LAN exposure through 2015 nighttime luminance satellite images from the Visible Infrared Imaging Radiometer Suite (VIIRS). Using a logistic regression model adjusted for age, sex, and education, we calculated the risk of dementia associated with increasing LAN exposure, namely using <10 nW/cm2/sr as reference and considering ≥10-<40 nW/cm2/sr intermediate and ≥40 nW/cm2/sr high exposure, respectively We also implemented non-linear assessment using a spline regression model. Results: We recruited 58 EOD cases, 34 LOD cases and 54 controls. Average LAN exposure levels overlapped for EOD cases and controls, while LOD cases showed higher levels. Compared with the lowest exposure, the risk of EOD associated with LAN was higher in the intermediate exposure (OR = 1.36, 95% CI 0.54-3.39), but not in the high exposure category (OR = 1.04, 95% CI 0.32-3.34). In contrast, the risk of LOD was positively associated with LAN exposure, with ORs of 2.58 (95% CI 0.26-25.97) and 3.50 (95% CI 0.32-38.87) in the intermediate and high exposure categories, respectively. The spline regression analysis showed substantial lack of association between LAN and EOD, while almost linear although highly imprecise association emerged for LOD. Conclusions: Although the precision of the estimates was affected by the limited sample size and the study design did not allow us to exclude the presence of residual confounding, these results suggest a possible role of LAN in the etiology of dementia, particularly of its late-onset form.

Residential proximity to petrol stations and risk of childhood leukemia.

Petrol stations emit benzene and other contaminants that have been associated with an increased risk of childhood leukemia. We carried out a population-based case-control study in two provinces in Northern Italy. We enrolled 182 cases of childhood leukemia diagnosed during 1998-2019 and 726 age- and sex-matched population controls. We geocoded the addresses of child residences and 790 petrol stations located in the study area. We estimated leukemia risk according to distance from petrol stations within a 1000 m buffer and amount of supplied fuel within a buffer of 250 m from the child's residence. We used conditional logistic regression models to approximate risk ratios (RRs) and 95% confidence intervals (CIs) for associations of interest, adjusted for potential confounders. We also modeled non-linear associations using restricted cubic splines. In secondary analyses, we restricted to acute lymphoblastic leukemia (ALL) cases and stratifed by age (<5 and ≥5 years). Compared with children who lived≥1000 m from a petrol station, the RR was 2.2 (95% CI 0.5-9.4) for children living<50 m from nearest petrol station. Associations were stronger for the ALL subtype (RR=2.9, 95% CI 0.6-13.4) and among older children (age≥5 years: RR=4.4, 95% CI 0.6-34.1; age<5 years: RR=1.6, 95% CI 0.1-19.4). Risk of leukemia was also greater (RR=1.6, 95% CI 0.7-3.3) among the most exposed participants when assigning exposure categories based on petrol stations located within 250 m of the child's residence and total amount of gasoline delivered by the stations. Overall, residence within close proximity to a petrol station, especially one with more intense refueling activity, was associated with an increased risk of childhood leukemia, though associations were imprecise.

The influence of meteorological factors on COVID-19 spread in Italy during the first and second wave.

The relation between meteorological factors and COVID-19 spread remains uncertain, particularly with regard to the role of temperature, relative humidity and solar ultraviolet (UV) radiation. To assess this relation, we investigated disease spread within Italy during 2020. The pandemic had a large and early impact in Italy, and during 2020 the effects of vaccination and viral variants had not yet complicated the dynamics. We used non-linear, spline-based Poisson regression of modeled temperature, UV and relative humidity, adjusting for mobility patterns and additional confounders, to estimate daily rates of COVID-19 new cases, hospital and intensive care unit admissions, and deaths during the two waves of the pandemic in Italy during 2020. We found little association between relative humidity and COVID-19 endpoints in both waves, whereas UV radiation above 40 kJ/m2 showed a weak inverse association with hospital and ICU admissions in the first wave, and a stronger relation with all COVID-19 endpoints in the second wave. Temperature above 283 K (10 °C/50 °F) showed a strong non-linear negative relation with COVID-19 endpoints, with inconsistent relations below this cutpoint in the two waves. Given the biological plausibility of a relation between temperature and COVID-19, these data add support to the proposition that temperature above 283 K, and possibly high levels of solar UV radiation, reduced COVID-19 spread.

Particulate matter exposure from motorized traffic and risk of conversion from mild cognitive impairment to dementia: An Italian prospective cohort study.

BACKGROUND: Based on epidemiologic and laboratory studies, exposure to air pollutants has been linked to many adverse health effects including a higher risk of dementia. In this study, we aimed to evaluate the effect of long-term exposure to outdoor air pollution on risk of conversion to dementia in a cohort of subjects with mild cognitive impairment (MCI). METHODS: We recruited 53 Italian subjects newly-diagnosed with MCI. Within a geographical information system, we assessed recent outdoor air pollutant exposure, by modeling air levels of particulate matter with equivalent aerodynamic diameter ≤10 µm (PM10) from motorized traffic at participants' residence. We investigated the relation of PM10 concentrations to subsequent conversion from MCI to any type of dementia. Using a Cox-proportional hazards model combined with a restricted cubic spline model, we computed the hazard ratio (HR) of dementia with its 95% confidence interval (CI) according to increasing PM10 exposure, adjusting for sex, age, and educational attainment. RESULTS: During a median follow up of 47.3 months, 34 participants developed dementia, in 26 cases diagnosed as Alzheimer's dementia. In non-linear restricted spline regression analysis, mean and maximum annual PM10 levels positively correlated with cerebrospinal fluid total and phosphorylated tau proteins concentrations, while they were inversely associated with ß-amyloid. Concerning the risk of dementia, we found a positive association starting from above 10 µg/m3 for mean PM10 levels and above 35 µg/m3 for maximum PM10 levels. Specific estimates for Alzheimer's dementia were substantially similar. Adding other potential confounders to the multivariable model or removing early cases of dementia onset during the follow-up had little effect on the estimates. CONCLUSIONS: Our findings suggest that exposure to outdoor air pollutants, PM10 in particular, may non-linearly increase conversion from MCI to dementia above a certain ambient air concentration.

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study.

(1) Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with still unknown etiology. Some occupational and environmental risk factors have been suggested, including long-term air pollutant exposure. We carried out a pilot case-control study in order to evaluate ALS risk due to particulate matter with a diameter of ≤10 µm (PM10) as a proxy of vehicular traffic exposure. (2) Methods: We recruited ALS patients and controls referred to the Modena Neurology ALS Care Center between 1994 and 2015. Using a geographical information system, we modeled PM10 concentrations due to traffic emissions at the geocoded residence address at the date of case diagnosis. We computed the odds ratio (OR) and 95% confidence interval (CI) of ALS according to increasing PM10 exposure, using an unconditional logistic regression model adjusted for age and sex. (3) Results: For the 132 study participants (52 cases and 80 controls), the average of annual median and maximum PM10 concentrations were 5.2 and 38.6 µg/m3, respectively. Using fixed cutpoints at 5, 10, and 20 of the annual median PM10 levels, and compared with exposure <5 µg/m3, we found no excess ALS risk at 5-10 µg/m3 (OR 0.87, 95% CI 0.39-1.96), 10-20 µg/m3 (0.94, 95% CI 0.24-3.70), and ≥20 µg/m3 (0.87, 95% CI 0.05-15.01). Based on maximum PM10 concentrations, we found a statistically unstable excess ALS risk for subjects exposed at 10-20 µg/m3 (OR 4.27, 95% CI 0.69-26.51) compared with those exposed <10 µg/m3. However, risk decreased at 20-50 µg/m3 (OR 1.49, 95% CI 0.39-5.75) and ≥50 µg/m3 (1.16, 95% CI 0.28-4.82). ALS risk in increasing tertiles of exposure showed a similar null association, while comparison between the highest and the three lowest quartiles lumped together showed little evidence for an excess risk at PM10 concentrations (OR 1.13, 95% CI 0.50-2.55). After restricting the analysis to subjects with stable residence, we found substantially similar results. (4) Conclusions: In this pilot study, we found limited evidence of an increased ALS risk due to long-term exposure at high PM10 concentration, though the high statistical imprecision of the risk estimates, due to the small sample size, particularly in some exposure categories, limited our capacity to detect small increases in risk, and further larger studies are needed to assess this relation.

Living near waterbodies as a proxy of cyanobacteria exposure and risk of amyotrophic lateral sclerosis: a population based case-control study.

BACKGROUND: Epidemiological studies highlighted the possibility that exposure to cyanotoxins leads to the development of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). METHODS: We devised a population-based case-control study in two Italian populations. We used residential proximity of the residence to water bodies as a measure of possible exposure to cyanotoxins. RESULTS: Based on 703 newly-diagnosed ALS cases and 2737 controls, we calculated an ALS odds ratio (OR) of 1.41 (95% CI: 0.72-2.74) for current residence in the vicinity of water bodies, and a slightly lower estimate for historical residence (OR: 1.31; 95% CI: 0.57-2.99). Subjects <65 years and people living in the Northern Italy province of Modena had higher ORs, especially when historical residence was considered. CONCLUSIONS: Overall, despite some risk of bias due to exposure misclassification and unmeasured confounding, our results appear to support the hypothesis that cyanotoxin exposure may increase ALS risk.

A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas.

Gaussian dispersion models are widely used to simulate the concentrations and deposition fluxes of pollutants emitted by source areas. Very often, the calculation time limits the number of sources and receptors and the geometry of the sources must be simple and without holes. This paper presents CAREA, a new GIS-based Gaussian model for complex source areas. CAREA was coded in the Python language, and is largely based on a simplified formulation of the very popular and recognized AERMOD model. The model allows users to define in a GIS environment thousands of gridded or scattered receptors and thousands of complex sources with hundreds of vertices and holes. CAREA computes ground level, or near ground level, concentrations and dry deposition fluxes of pollutants. The input/output and the runs of the model can be completely managed in GIS environment (e.g. inside a GIS project). The paper presents the CAREA formulation and its applications to very complex test cases. The tests shows that the processing time are satisfactory and that the definition of sources and receptors and the output retrieval are quite easy in a GIS environment. CAREA and AERMOD are compared using simple and reproducible test cases. The comparison shows that CAREA satisfactorily reproduces AERMOD simulations and is considerably faster than AERMOD.

Pesticide exposure assessed through agricultural crop proximity and risk of amyotrophic lateral sclerosis.

BACKGROUND: Epidemiologic studies have raised the possibility that some pesticide compounds induce the neurodegenerative disease amyotrophic lateral sclerosis (ALS), though the available evidence is not entirely consistent. METHODS: We conducted a population-based case-control study in two Italian populations to assess the extent to which residence in the vicinity of agricultural crops associated with the application of neurotoxic pesticides is a risk factor for ALS, using crop acreage in proximity to the residence as an index of exposure. RESULTS: Based on 703 cases and 2737 controls, we computed an ALS odds ratio of 0.92 (95% confidence interval 0.78-1.09) for those in proximity to agricultural land. Results were not substantially different when using alternative exposure categories or when analyzing specific crop types, with the exception of a higher risk related to exposure to citrus orchards and olive groves in Southern Italy, though based on few exposed subjects (N = 89 and 8, respectively). There was little evidence of any dose-response relation between crop proximity and ALS risk, and using long-term residence instead of current residence did not substantially change our estimates. CONCLUSIONS: Though our index of exposure is indirect and subject to considerable misclassification, our results offer little support for the hypothesis that neurotoxic pesticide exposure increases ALS risk.

Passive exposure to agricultural pesticides and risk of childhood leukemia in an Italian community.

BACKGROUND: Exposure to pesticides has been suggested as a risk factor for childhood leukemia, but definitive evidence on this relation and the specific pesticides involved is still not clear. OBJECTIVE: We carried out a population-based case-control study in a Northern Italy community to assess the possible relation between passive exposure to agricultural pesticides and risk of acute childhood leukemia. METHODS: We assessed passive pesticide exposure of 111 childhood leukemia cases and 444 matched controls by determining density and type of agricultural land use within a 100-m radius buffer around children's homes. We focused on four common crop types, arable, orchard, vineyard and vegetable, characterized by the use of specific pesticides that are potentially involved in childhood induced leukemia. The use of these pesticides was validated within the present study. We computed the odds ratios (OR) of the disease and their 95% confidence intervals (CI) according to type and density of crops around the children's homes, also taking into account traffic pollution and high-voltage power line magnetic field exposure. RESULTS: Childhood leukemia risk did not increase in relation with any of the crop types with the exception of arable crops, characterized by the use of 2.4-D, MCPA, glyphosate, dicamba, triazine and cypermethrin. The very few children (n=11) residing close to arable crops had an OR for childhood leukemia of 2.04 (95% CI 0.50-8.35), and such excess risk was further enhanced among children aged <5 years. CONCLUSIONS: Despite the null association with most crop types and the statistical imprecision of the estimates, the increased leukemia risk among children residing close to arable crops indicates the need to further investigate the involvement in disease etiology of passive exposure to herbicides and pyrethroids, though such exposure is unlikely to play a role in the vast majority of cases.

Increased incidence of childhood leukemia in urban areas: a population-based case-control study.

OBJECTIVE: We carried out a population-based case-control study to assess the possibility of an excess risk of childhood leukemia in urban areas, independently from road traffic pollution. METHODS: Study subjects were the 111 cases of childhood leukemia diagnosed from 1998 to 2011 among residents of two provinces of the northern Italian Emilia-Romagna region, and 444 controls matched by age and sex. Through mapping of the region carried out by remote sensing, we examined the percentage of urban or rural area in the 100-meter circular buffer around each child's house. We also modeled annual average exposure to benzene and PM10 from vehicular traffic at each residence. RESULTS: In a multivariate model adjusting for benzene and PM10, the odds ratio of leukemia associated with residence in a highly urbanized area and residential area (≥95% land use of this type near the child's home) was 1.4 (95% confidence intervals 0.8-2.4) and 1.3 (0.8-2.2), respectively. An increased risk was also found in association with the proximity to «dumps, scrap yards, and building sites¼. No association emerged with residence in rural areas or near industrial plants. CONCLUSIONS: These results indicate that children living in urban areas experience an excess leukemia risk, independently from exposure to pollutants from vehicles.