Using low-cost sensor technologies and advanced computational methods to improve dose estimations in health panel studies: results of the AIRLESS project

Linking environmental risk factors with epigenetic mechanisms in Parkinson's disease

Sporadic Parkinson's disease (PD) is a progressive neurodegenerative disease, with a complex risk structure thought to be influenced by interactions between genetic variants and environmental exposures, although the full aetiology is unknown. Environmental factors, including pesticides, have been reported to increase the risk of developing the disease. Growing evidence suggests epigenetic changes are key mechanisms by which these environmental factors act upon gene regulation, in disease-relevant cell types. We present a systematic review critically appraising and summarising the current body of evidence of the relationship between epigenetic mechanisms and environmental risk factors in PD to inform future research in this area. Epigenetic studies of relevant environmental risk factors in animal and cell models have yielded promising results, however, research in humans is just emerging. While published studies in humans are currently relatively limited, the importance of the field for the elucidation of molecular mechanisms of pathogenesis opens clear and promising avenues for the future of PD research. Carefully designed epidemiological studies carried out in PD patients hold great potential to uncover disease-relevant gene regulatory mechanisms. Therefore, to advance this burgeoning field, we recommend broadening the scope of investigations to include more environmental exposures, increasing sample sizes, focusing on disease-relevant cell types, and recruiting more diverse cohorts.

Integrated assessment of personal monitor applications for evaluating exposure to urban stressors: A scoping review

Urban stressors pose a health risk, and individual-level assessments provide necessary and fine-grained insight into exposure. An ever-increasing amount of research literature on individual-level exposure to urban stressors using data collected with personal monitors, has called for an integrated assessment approach to identify trends, gaps and needs, and provide recommendations for future research. To this end, a scoping review of the respective literature was performed, as part of the H2020 URBANOME project. Moreover, three specific aims were identified: (i) determine current state of research, (ii) analyse literature according with a waterfall methodological framework and identify gaps and needs, and (iii) provide recommendations for more integrated, inclusive and robust approaches. Knowledge and gaps were extracted based on a systematic approach, e.g., data extraction questionnaires, as well as through the expertise of the researchers performing the review. The findings were assessed through a waterfall methodology of delineating projects into four phases. Studies described in the papers vary in their scope, with most assessing exposure in a single macro domain, though a trend of moving towards multi-domain assessment is evident. Simultaneous measurements of multiple stressors are not common, and papers predominantly assess exposure to air pollution. As urban environments become more diverse, stakeholders from different groups are included in the study designs. Most frequently (per the quadruple helix model), civil society/NGO groups are involved, followed by government and policymakers, while business or private sector stakeholders are less frequently represented. Participants in general function as data collectors and are rarely involved in other phases of the research. While more active involvement is not necessary, more collaborative approaches show higher engagement and motivation of participants to alter their lifestyles based on the research results. The identified trends, gaps and needs can aid future exposure research and provide recommendations on addressing different urban communities and stakeholders.

Simulating patterns of life: More representative time-activity patterns that account for context

BACKGROUND

Complex contributions of environment to health are intimately connected to human behavior. Modeling of human behaviors and their influences helps inform important policy decisions related to critical environmental and public health challenges. A typical approach to human behavior modeling involves generating daily schedules based on time-activity patterns of individual humans, simulating 'agents' with these schedules, and interpreting patterns of life that emerge from the simulation to inform a research question. Current behavior modeling, however, rarely incorporates the context that surrounds individuals' truly broad scope of activities and influences on those activities.

OBJECTIVES

We describe in detail a range of elements involved in generating time-activity patterns and connect work in the social science field of behavior modeling with applications in exposure science and environmental health. We propose a framework for behavior modeling that takes a systems approach and considers the broad scope of activities and influences required to simulate more representative patterns of life and thus improve modeling that underlies understanding of environmental contributions to health and associated decisions to promote and protect public health.

METHODS

We describe an agent-based modeling approach reliant on generating a population's schedules, filtering the schedules, simulating behavior using the schedules, analyzing the emergent patterns, and interrogating results that leverages general empirical information in a systems context to inform fit-for-purpose action.

DISCUSSION

We propose a centralized and standardized program to codify behavior information and generate population schedules that researchers can select from to simulate human behavior and holistically characterize human-environment interactions for a variety of public health applications.

Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution

BACKGROUND

Air pollution epidemiology has primarily relied on measurements from fixed outdoor air quality monitoring stations to derive population-scale exposure. Characterisation of individual time-activity-location patterns is critical for accurate estimations of personal exposure and dose because pollutant concentrations and inhalation rates vary significantly by location and activity.

METHODS

We developed and evaluated an automated model to classify major exposure-related microenvironments (home, work, other static, in-transit) and separated them into indoor and outdoor locations, sleeping activity and five modes of transport (walking, cycling, car, bus, metro/train) with multidisciplinary methods from the fields of movement ecology and artificial intelligence. As input parameters, we used GPS coordinates, accelerometry, and noise, collected at 1 min intervals with a validated Personal Air quality Monitor (PAM) carried by 35 volunteers for one week each. The model classifications were then evaluated against manual time-activity logs kept by participants.

RESULTS

Overall, the model performed reliably in classifying home, work, and other indoor microenvironments (F1-score>0.70) but only moderately well for sleeping and visits to outdoor microenvironments (F1-score=0.57 and 0.3 respectively). Random forest approaches performed very well in classifying modes of transport (F1-score>0.91). We found that the performance of the automated methods significantly surpassed those of manual logs.

CONCLUSIONS

Automated models for time-activity classification can markedly improve exposure metrics. Such models can be developed in many programming languages, and if well formulated can have general applicability in large-scale health studies, providing a comprehensive picture of environmental health risks during daily life with readily gathered parameters from smartphone technologies.

Particulate air pollution in the Copenhagen metro part 2: Low-cost sensors and micro-environment classification

In this study fine particulate matter (PM_2.5) levels throughout the Copenhagen metro system are measured for the first time and found to be ∼10 times the roadside levels in Copenhagen. In this Part 2 article, low-cost sensor (LCS) nodes designed for personal-exposure monitoring are tested against a conventional mid-range device (TSI DustTrak), and gravimetric methods. The nodes were found to be effective for personal exposure measurements inside the metro system, with R² values of > 0.8 at 1-min and > 0.9 at 5-min time-resolution, with an average slope of 1.01 in both cases, in comparison to the reference, which is impressive for this dynamic environment. Micro-environment (ME) classification techniques are also developed and tested, involving the use of auxiliary sensors, measuring light, carbon dioxide, humidity, temperature and motion. The output from these sensors is used to distinguish between specific MEs, namely, being aboard trains travelling above- or under- ground, with 83 % accuracy, and determining whether sensors were aboard a train or stationary at a platform with 92 % accuracy. This information was used to show a 143 % increase in mean PM_2.5 concentration for underground sections relative to overground, and 22 % increase for train vs. platform measurements. The ME classification method can also be used to improve calibration models, assist in accurate exposure assessment based on detailed time-activity patterns, and facilitate field studies that do not require personnel to record time-activity diaries.

Radiological risk assessment of the Hunters Point Naval Shipyard (HPNS)

Hunters Point Naval Shipyard in San Francisco, California was deemed a Superfund site by the USEPA in 1989 due to chemical and radiological contamination resulting from U.S. Navy operations from 1939 to 1974. During characterization and remediation efforts, over 50,000 radiological soil samples and 19,000 air samples were collected. This risk assessment, conducted in accordance with federal guidelines, represents the first comprehensive evaluation of past, present, and future health risks associated with radionuclides present at the site. The assessment indicated that before site remediation, most radionuclide soil concentrations were at or near local background concentrations. Had such low remedial goals not been established, significant remediation of surface soils would not have been necessary to protect human health. The pre-remediation lifetime incremental cancer morbidity risks for on-site workers and theoretical on-site residents due to radionuclide contamination were found to be 1.3 × 10^-6 and 3.2 × 10^-6, respectively. The post-remediation risks to future on-site residents were found to be 6.3 × 10^-8 (without durable cover) and 3.7 × 10^-8 (with durable cover), while post-remediation risks to on-site workers were found to be 2.6 × 10^-8 (without durable cover) and 1.6 × 10^-8 (with durable cover). Risk estimates for all scenarios were found to be significantly below the acceptable risk of 3 × 10^-4 approved by regulatory agencies. Upwind and downwind air samples collected during remediation indicate that remediation activities never posed a measurable risk to off-site residents. This risk assessment emphasizes the importance of establishing clear and scientifically rigorous soil remedial goals at sites as well as understanding local radionuclide background concentrations.

The impact of personal and outdoor temperature exposure during cold and warm seasons on lung function and respiratory symptoms in COPD

Rationale

Methodology

Results

Conclusions

Higher temperature, including outdoor exposure during the warm season and personal exposure year-round, may worsen dyspnoea while colder outdoor temperature may trigger cough and phlegm symptoms in COPD patientshttps://bit.ly/3G0bL2c

Air Pollution Exposure and Daily Lung Function in COPD: Effect Modification by Eosinophilia

RATIONALE

Few studies have assessed personal exposure to pollutants and lung function among adults with COPD. Blood eosinophilia may be a biomarker of airway inflammation and pollution susceptibility.

OBJECTIVES

To evaluate if daily pollutant exposures are associated with lung function and if associations are modified by eosinophilia in COPD.

METHODS

We recruited 30 former smokers with moderate-to-severe COPD living in the Boston area and followed them up to 4 non-consecutive months in different seasons. Participants measured morning lung function and carried a portable air quality monitor daily. Previous-day exposure to pollutants (PM2.5, NO2, and ozone) were measured by portable and community monitors. We constructed multi-level linear mixed-effects models with random intercepts for person and observation month, adjusted for temperature, humidity, age, sex, race, height, weight, income, and season, to assess associations of previous-day pollutant exposure with lung function and effect modification by eosinophilia (< vs > 150 cells/µL).

RESULTS

A total of 3,314 observations with exposure and lung function data were collected. Each IQR (5.1 ppb) higher previous-day personal exposure to NO2 was associated with a 11.3 mL (95% CI: -18.7, -4.0) lower FEV1 and a 18.0 mL (95% CI: -32.0, -4.2) lower FVC. Personal and community-level exposure to PM2.5 and community-level NO2 were negatively associated with FEV1 among the 55.2% of participants with eosinophilia (Pinteraction <0.05).

CONCLUSIONS

Our study highlights the need to address air pollution exposure among COPD patients. Future research is needed to verify if eosinophilia is a biomarker for susceptibility to air pollution in COPD.

Features and Practicability of the Next-Generation Sensors and Monitors for Exposure Assessment to Airborne Pollutants: A Systematic Review

In the last years, the issue of exposure assessment of airborne pollutants has been on the rise, both in the environmental and occupational fields. Increasingly severe national and international air quality standards, indoor air guidance values, and exposure limit values have been developed to protect the health of the general population and workers; this issue required a significant and continuous improvement in monitoring technologies to allow the execution of proper exposure assessment studies. One of the most interesting aspects in this field is the development of the "next-generation" of airborne pollutants monitors and sensors (NGMS). The principal aim of this review is to analyze and characterize the state of the art and of NGMS and their practical applications in exposure assessment studies. A systematic review of the literature was performed analyzing outcomes from three different databases (Scopus, PubMed, Isi Web of Knowledge); a total of 67 scientific papers were analyzed. The reviewing process was conducting systematically with the aim to extrapolate information about the specifications, technologies, and applicability of NGMSs in both environmental and occupational exposure assessment. The principal results of this review show that the use of NGMSs is becoming increasingly common in the scientific community for both environmental and occupational exposure assessment. The available studies outlined that NGMSs cannot be used as reference instrumentation in air monitoring for regulatory purposes, but at the same time, they can be easily adapted to more specific applications, improving exposure assessment studies in terms of spatiotemporal resolution, wearability, and adaptability to different types of projects and applications. Nevertheless, improvements needed to further enhance NGMSs performances and allow their wider use in the field of exposure assessment are also discussed.