ICRP workshop on the review and revision of the system of radiological protection: a focus on research priorities-feedback from the international community.

In September 2022, the International Commission on Radiological Protection (ICRP) organised a workshop in Estoril, Portugal, on the 'Review and Revision of the System of Radiological Protection: A Focus on Research Priorities'. The workshop, which was a side event of the European Radiation Protection Week, offered an opportunity to comment on a recent paper published by ICRP on areas of research to support the System of Radiological Protection. Altogether, about 150 individuals participated in the workshop. After the workshop, 16 of the 30 organisations in formal relations with ICRP provided written feedback. All participants and organisations followed ICRP's view that further research in various areas will offer additional support in improving the System in the short, medium, and long term. In general, it was emphasised that any research should be outcome-focused in that it should improve protection of people or the environment. Many research topics mentioned by the participants were in line with those already identified by ICRP in the paper noted above. In addition, further ideas were expressed such as, for example, that lessons learned during the COVID-19 pandemic with regards to the non-radiological social, economic and environment impacts, should be analysed for their usefulness to enhance radiological protection, and that current protection strategies and application of current radiological protection principles may need to be adapted to military scenarios like those observed recently during the military conflict in the Ukraine or the detonation of a nuclear weapon. On a broader perspective, it was discussed how radiation research and radiological protection can contribute towards the Sustainable Development Goals announced by the United Nations in 2015. This paper summarises the views expressed during the workshop and the major take home messages identified by ICRP.

Completeness and representativeness of small area socioeconomic data linked with the UK Clinical Practice Research Datalink (CPRD).

BACKGROUND: The Clinical Practice Research Datalink (CPRD) holds primary care electronic healthcare records for 25% of the UK population. CPRD data can be linked via practice postcode in the UK, and additionally via patient postcode in England, to area-level socioeconomic status (SES) data including the Index of Multiple Deprivation (IMD), the Carstairs Index and the Townsend Deprivation Index; as well as rural-urban classification (RUC). This study aims to describe the completeness and representativeness of CPRD-linked SES and RUC data. METHODS: Patients currently registered at general practices contributing data to the May 2021 snapshots of CPRD GOLD (n=445 587) and CPRD Aurum (n=13 278 825) were used to assess the completeness and representativeness of CPRD-linked SES and RUC data against the UK general population. RESULTS: All currently registered patients had complete SES and RUC data at practice level across the UK. Most English patients in CPRD GOLD (78%), CPRD Aurum (94%) and combined (93%) had SES and RUC data at patient level. Patient-level SES data in CPRD for England were comparable to England's general population (average IMD decile in CPRD 5.52±0.00 vs 5.50±0.02). CPRD UK practices were on average in more deprived areas than the UK general population (6.06±0.07 vs 5.50±0.02). A slightly higher proportion of CPRD patients and practices were from urban areas (85%) as compared with the UK general population (82%). CONCLUSION: Completeness of CPRD-linked SES and RUC data is high. The CPRD populations were broadly representative of the general populations in the UK in terms of SES and RUC.

Associations of private residential gardens versus other greenspace types with cardiovascular and respiratory disease mortality: Observational evidence from UK Biobank.

BACKGROUND: Longitudinal evidence linking urban greenspace to reduced rates of all-cause and cause-specific mortality has mostly been established using greenness measures of limited specificity such as vegetation indices. Evidence on specific green space types, including private residential gardens is less well established. METHODS: We examined associations of greenspace with all-cause, non-injury, cardiovascular disease (CVD) and respiratory disease deaths in UK Biobank - a national prospective cohort of adults with linked Office for National Statistics mortality records. We included private residential gardens and other greenspace types, e.g., public parks, sport facilities, using categories from Ordnance Survey MasterMap™ Greenspace. We used Cox proportional hazards models, adjusted for individual and area-level covariates, and stratified analyses by sex, household income, and area-level deprivation. In sensitivity analyses, we further adjusted for air pollution, road-traffic noise, indirect tobacco smoke exposure, and physical activity, and restricted analyses to non-movers. RESULTS: In 232,926 participants, we observed 13,586 all-cause, 13,159 non-injury, 2,796 cardiovascular (CVD), and 968 respiratory disease deaths. Private residential garden cover showed inverse associations with all-cause, non-injury, CVD, and chronic respiratory disease mortality, after adjustment for covariates and other types of greenspace, with hazard ratios and 95 % confidence intervals of 0.94 (0.91, 0.97), 0.95 (0.92, 0.97), 0.92 (0.86, 0.98) and 0.87 (0.78, 0.98), respectively, per interquartile range (IQR) increase in private residential garden cover (IQR = 21.6 % increase within 100 m buffer). Other greenspace types showed weaker inverse associations with CVD and chronic respiratory disease mortality than private residential gardens. Sex, household income, and area level deprivation modified associations. Findings were robust to sensitivity analyses. CONCLUSION: Our finding that private residential gardens substantially contributed to inverse associations of total greenspace with premature mortality has implications for public health and urban planning. Inequities in access, ownership, views and use of private residential gardens, and potential health inequities, should be addressed.

Green Walkability and Physical Activity in UK Biobank: A Cross-Sectional Analysis of Adults in Greater London.

Urban greenspace provides opportunities for outdoor exercise and may increase physical activity, with accompanying health benefits. Areas suitable for walking (walkability) are also associated with increased physical activity, but interactions with greenspace are poorly understood. We investigated associations of walkability and green walkability with physical activity in an urban adult cohort. We used cross-sectional data from Greater London UK Biobank participants (n = 57,726) and assessed walkability along roads and footpaths within 1000 m of their residential addresses. Additionally, we assessed green walkability by integrating trees and low-lying vegetation into the walkability index. Physical activity outcomes included self-reported and accelerometer-measured physical activity and active transport. We assessed associations using log-linear, logistic and linear regression models, adjusted for individual- and area-level confounders. Higher green walkability was associated with favourable International Physical Activity Questionnaire responses and achievement of weekly UK government physical activity guideline recommendations. Participants living in the highest versus lowest quintile of green walkability participated in 2.41 min (95% confidence intervals: 0.22, 4.60) additional minutes of moderate-and-vigorous physical activity per day. Higher walkability and green walkability scores were also associated with choosing active transport modes such as walking and cycling. Our green walkability approach demonstrates the utility in accounting for walkability and greenspace simultaneously to understand the role of the built environment on physical activity.

Exploring the translational challenge for medical applications of ionising radiation and corresponding radiation protection research.

BACKGROUND: Medical applications of ionising radiation and associated radiation protection research often encounter long delays and inconsistent implementation when translated into clinical practice. A coordinated effort is needed to analyse the research needs for innovation transfer in radiation-based high-quality healthcare across Europe which can inform the development of an innovation transfer framework tailored for equitable implementation of radiation research at scale. METHODS: Between March and September 2021 a Delphi methodology was employed to gain consensus on key translational challenges from a range of professional stakeholders. A total of three Delphi rounds were conducted using a series of electronic surveys comprised of open-ended and closed-type questions. The surveys were disseminated via the EURAMED Rocc-n-Roll consortium network and prominent medical societies in the field. Approximately 350 professionals were invited to participate. Participants' level of agreement with each generated statement was captured using a 6-point Likert scale. Consensus was defined as median ≥ 4 with ≥ 60% of responses in the upper tertile of the scale. Additionally, the stability of responses across rounds was assessed. RESULTS: In the first Delphi round a multidisciplinary panel of 20 generated 127 unique statements. The second and third Delphi rounds recruited a broader sample of 130 individuals to rate the extent to which they agreed with each statement as a key translational challenge. A total of 60 consensus statements resulted from the iterative Delphi process of which 55 demonstrated good stability. Ten statements were identified as high priority challenges with ≥ 80% of statement ratings either 'Agree' or 'Strongly Agree'. CONCLUSION: A lack of interoperability between systems, insufficient resources, unsatisfactory education and training, and the need for greater public awareness surrounding the benefits, risks, and applications of ionising radiation were identified as principal translational challenges. These findings will help to inform a tailored innovation transfer framework for medical radiation research.

Lessons being learned from the Covid-19 pandemic for radiological emergencies and vice versa: report from expert discussions.

In order to examine what lessons radiological emergency management may offer for the management of the Covid-19 pandemic, and vice versa, a series of three online webinars were conducted with leading experts, scholars and practitioners from a wide range of disciplines essential for emergency management and long-term risk governance. The first webinar debated the lessons we are learning from the Covid-19 pandemic for radiological risk communication, the second explored issues around longer-term outcomes of a crisis and how to balance these with short-term actions whilst the third focused on the key challenges of the 'transition phase', using lessons learned from the Chernobyl (1986) and Fukushima Daichii (2011) accidents. This paper reviews the discussions and provides valuable lessons for the radiation protection community. Results of the discussions indicated that: (a) non-radiological and non-epidemiological consequences of emergencies, for example psychological (mental health), societal and economic, should not be underestimated; (b) multidisciplinary expertise is imperative for communication efforts and for effective emergency management, including decision-making in the application of protective measures; (c) stakeholder engagement, including the involvement of the potentially affected population, should be encouraged from an early stage; and (d) trust is increased if policy-makers and the main science agencies show a unified voice.

Trimester effects of source-specific PM10 on birth weight outcomes in the Avon Longitudinal Study of Parents and Children (ALSPAC).

BACKGROUND: Evidence suggests that exposure to particulate matter with aerodynamic diameter less than 10 µm (PM10) is associated with reduced birth weight, but information is limited on the sources of PM10 and exposure misclassification from assigning exposures to place of residence at birth. METHODS: Trimester and source-specific PM10 exposures (PM10 from road source, local non-road source, and total source) in pregnancy were estimated using dispersion models and a full maternal residential history for 12,020 births from the Avon longitudinal study of parents and children (ALSPAC) cohort in 1990-1992 in the Bristol area. Information on birth outcomes were obtained from birth records. Maternal sociodemographic and lifestyle factors were obtained from questionnaires. We used linear regression models for continuous outcomes (birth weight, head circumference (HC), and birth length (BL) and logistic regression models for binary outcomes (preterm birth (PTB), term low birth weight (TLBW) and small for gestational age (SGA)). Sensitivity analysis was performed using multiple imputation for missing covariate data. RESULTS: After adjustment, interquartile range increases in source specific PM10 from traffic were associated with 17 to 18% increased odds of TLBW in all pregnancy periods. We also found odds of TLBW increased by 40% (OR: 1.40, 95%CI: 1.12, 1.75) and odds of SGA increased by 18% (OR: 1.18, 95%CI: 1.05, 1.32) per IQR (6.54 µg/m3) increase of total PM10 exposure in the third trimester. CONCLUSION: This study adds to evidence that maternal PM10 exposures affect birth weight, with particular concern in relation to exposures to PM10 from road transport sources; results for total PM10 suggest greatest effect in the third trimester. Effect size estimates relate to exposures in the 1990s and are higher than those for recent studies - this may relate to reduced exposure misclassification through use of full residential history information, changes in air pollution toxicity over time and/or residual confounding.

Short-term effects of air pollution on daily asthma-related emergency department visits in an industrial city.

BACKGROUND: Epidemiological studies from Europe and North America have provided evidence that exposure to air pollution can aggravate symptoms in asthmatic patients. METHODS: Daily number of AEDv, air pollution levels (PM10, PM2.5, SO2, NO2 and CO) and meteorological variables was obtained from Jubail Industrial City, Saudi Arabia, for the period of 2007-11. Data were analyzed using a time-series approach. Relative risks (RRs) were estimated using Poisson regression. RESULTS: The associations between AEDv and PM10, PM2.5, SO2 and NO2 remained positive and statistically significant after mutual adjustment in the multi-pollutant model.The RR of AEDv increased by 5.4, 4.4, 3.4 and 2.2% per an inter-quartile range increase in SO2 (2.0 ppb), PM2.5 (36 µg/m3), NO2 (7.6 ppb) and PM10 (140 µg/m3), respectively. No significant associations between AEDv and CO were found. CONCLUSIONS: Current levels of ambient air pollution are associated with AEDv in this industrial setting in the Middle East. Greater awareness of environmental health protection and the implementation of effective measures to improve the quality of air in such settings would be beneficial to public health.

Impact of road traffic noise on obesity measures: Observational study of three European cohorts.

BACKGROUND: Environmental stressors such as transport noise may contribute to development of obesity through increased levels of stress hormones, sleep deprivation and endocrine disruption. Epidemiological evidence supporting an association of road traffic noise with obesity markers is still relatively scant and confined to certain geographical regions. We aimed to examine the cross-sectional associations between road traffic noise and obesity markers in three large European cohorts involving nearly 500,000 individuals. METHODS: Three population-based cohorts (UK Biobank, Lifelines, HUNT3) were established between 2006 and 2013 in the UK, the Netherlands and Norway respectively. For all three cohorts, residential 24-h road traffic noise (Lden) for 2009 was modelled from a standardised European noise assessment framework. Residential exposures to NO2 for 2007 and PM2.5 for 2010 were estimated from Europe-wide land use regression models. Obesity markers including body mass index and waist circumference were measured at recruitment. Obesity and central obesity status were subsequently derived. Regression models were fitted in each cohort, adjusting for a harmonised set of demographic and lifestyle covariates, with further adjustments for air pollution in the main model. RESULTS: The main analyses included 412,934 participants of UK Biobank, 61,032 of Lifelines and 30,305 of HUNT3, with a mean age of 43-56 years and Lden ranging 42-89 dB(A) across cohorts. In UK Biobank, per 10 dB(A) higher of Lden: BMI was higher by 0.14kg/m2 (95%CI: 0.11-0.18), waist circumference higher by 0.27 cm (95%CI: 0.19-0.35), odds of obesity was 1.06 (95%CI: 1.04-1.08) and of central obesity was 1.05 (95%CI: 1.04-1.07). These associations were robust to most other sensitivity analyses but attenuated by further adjustment of PM2.5 or area-level socioeconomic status. Associations were more pronounced among women, those with low physical activity, higher household income or hearing impairment. In HUNT3, associations were observed for obesity or central obesity status among those exposed to Lden greater than 55 dB(A). In contrast, no or negative associations were observed in the Lifelines cohort. CONCLUSIONS: This largest study to date providing mixed findings on impacts of long-term exposure to road traffic noise on obesity, which necessitates future analyses using longitudinal data to further investigate this potentially important epidemiological link.

Advances in mapping population and demographic characteristics at small-area levels.

Temporally and spatially highly resolved information on population characteristics, including demographic profile (e.g. age and sex), ethnicity and socio-economic status (e.g. income, occupation, education), are essential for observational health studies at the small-area level. Time-relevant population data are critical as denominators for health statistics, analytics and epidemiology, to calculate rates or risks of disease. Demographic and socio-economic characteristics are key determinants of health and important confounders in the relationship between environmental contaminants and health. In many countries, census data have long been the source of small-area population denominators and confounder information. A strength of the traditional census model has been its careful design and high level of population coverage, allowing high-quality detailed data to be released for small areas periodically, e.g. every 10 years. The timeliness of data, however, becomes a challenge when temporally and spatially highly accurate annual (or even more frequent) data at high spatial resolution are needed, for example, for health surveillance and epidemiological studies. Additionally, the approach to collecting demographic population information is changing in the era of open and big data and may eventually evolve to using combinations of administrative and other data, supplemented by surveys. We discuss different approaches to address these challenges including (i) the US American Community Survey, a rolling sample of the US population census, (ii) the use of spatial analysis techniques to compile temporally and spatially high-resolution demographic data and (iii) the use of administrative and big data sources as proxies for demographic characteristics.

Availability, access, analysis and dissemination of small-area data.

In this era of 'big data', there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualizations, allowing small-area data to be seen and understood by non-expert audiences, are revolutionizing public and researcher interactions with data. The UK Small Area Health Statistics Unit's Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and 'mash-ups', and user-generated inputs from social media, mobile devices and wearable tech are new data streams that will find utility in future studies, and bring novel dimensions with respect to ethical use of small-area data.

Small-area methods for investigation of environment and health.

Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographical scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast-growing computational capabilities, permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but has also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.

Childhood type 1 diabetes: an environment-wide association study across England.

AIMS/HYPOTHESIS: Type 1 diabetes is an autoimmune disease affecting ~400,000 people across the UK. It is likely that environmental factors trigger the disease process in genetically susceptible individuals. We assessed the associations between a wide range of environmental factors and childhood type 1 diabetes incidence in England, using an agnostic, ecological environment-wide association study (EnWAS) approach, to generate hypotheses about environmental triggers. METHODS: We undertook analyses at the local authority district (LAD) level using a national hospital episode statistics-based incident type 1 diabetes dataset comprising 13,948 individuals with diabetes aged 0-9 years over the period April 2000 to March 2011. We compiled LAD level estimates for a range of potential demographic and environmental risk factors including meteorological, land use and environmental pollution variables. The associations between type 1 diabetes incidence and risk factors were assessed via Poisson regression, disease mapping and ecological regression. RESULTS: Case counts by LAD varied from 1 to 236 (median 33, interquartile range 24-46). Overall type 1 diabetes incidence was 21.2 (95% CI 20.9, 21.6) per 100,000 individuals. The EnWAS and disease mapping indicated that 15 out of 53 demographic and environmental risk factors were significantly associated with diabetes incidence, after adjusting for multiple testing. These included air pollutants (particulate matter, nitrogen dioxide, nitrogen oxides, carbon monoxide; all inversely associated), as well as lead in soil, radon, outdoor light at night, overcrowding, population density and ethnicity. Disease mapping revealed spatial heterogeneity in type 1 diabetes risk. The ecological regression found an association between type 1 diabetes and the living environment domain of the Index of Multiple Deprivation (RR 0.995; 95% credible interval [CrI] 0.991, 0.998) and radon potential class (RR 1.044; 95% CrI 1.015, 1.074). CONCLUSIONS/INTERPRETATION: Our analysis identifies a range of demographic and environmental factors associated with type 1 diabetes in children in England.

Industrial Biotechnology: To What Extent Is Responsible Innovation on the Agenda?

The UK Industrial Biotechnology (IB) Strategy presents a consistent plan to develop the IB sector but fails to endorse an innovation process that allows for input from multiple publics. This could be disadvantageous for the bioeconomy: there are notable cases where negligence to address societal dimensions has caused innovation failure.

Towards a strategic research agenda for social sciences and humanities in radiological protection.

Reflecting a change in funding strategies for European research projects, and a commitment to the idea of responsible research and innovation in radiological protection (RP), a collective of research institutes and universities have developed a prospective Strategic Research Agenda (SRA) for Social Sciences and Humanities (SSH) in radiological protection. This is the first time such a research agenda has been proposed. This paper identifies six research lines of interest and concern: (1) Effects of social, psychological and economic aspects on RP behaviour; (2) Holistic approaches to the governance of radiological risks; (3) Responsible research and innovation in RP; (4) Stakeholder engagement and participatory processes in RP research, development, policy and practice; (5) Risk communication; and (6) RP cultures. These topics were developed through broad stakeholder consultation, in conjunction with activities carried out in the framework of various projects and initiatives (EU H2020 CONCERT programme, the EU FP7 projects OPERRA, PREPARE and EAGLE, the 2015-2018 RICOMET series of conferences, and the 2014 and 2016 International Symposia on Ethics of Environmental Health); as well as through dialogues with members of the European radiation protection research communities. The six research lines open opportunities to integrate a range of key social and ethical considerations into RP, thereby expanding research opportunities and programmes and fostering collaborative approaches to research and innovation.

Role of patient and public involvement in implementation research: a consensus study.

BACKGROUND: Patient and public involvement (PPI) is often an essential requirement for research funding. Distinctions can be drawn between clinical research, which generally focuses on patients, and implementation research, which generally focuses on health professional behaviour. There is uncertainty about the role of PPI in this latter field. We explored and defined the roles of PPI in implementation research to inform relevant good practice guidance. METHODS: We used a structured consensus process using a convenience sample panel of nine experienced PPI and two researcher members. We drew on available literature to identify 21 PPI research roles. The panel rated their agreement with roles independently online in relation to both implementation and clinical research. Disagreements were discussed at a face-to-face meeting prior to a second online rating of all roles. Median scores were calculated and a final meeting held to review findings and consider recommendations. RESULTS: Ten panellists completed the consensus process. For clinical research, there was strong support and consensus for the role of PPI throughout most of the research process. For implementation research, there were eight roles with consensus and strong support, seven roles with consensus but weaker support and six roles with no consensus. There were more disagreements relating to PPI roles in implementation research compared with clinical research. PPI was rated as contributing less to the design and management of implementation research than for clinical research. CONCLUSIONS: The roles of PPI need to be tailored according to the nature of research to ensure authentic and appropriate involvement. We provide a framework to guide the planning, conduct and reporting of PPI in implementation research, and encourage further research to evaluate its use.

Road traffic noise, air pollution and incident cardiovascular disease: A joint analysis of the HUNT, EPIC-Oxford and UK Biobank cohorts.

BACKGROUND: This study aimed to investigate the effects of long-term exposure to road traffic noise and air pollution on incident cardiovascular disease (CVD) in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. METHODS: In pooled complete-case sample of the three cohorts from Norway and the United Kingdom (N = 355,732), 21,081 incident all CVD cases including 5259 ischemic heart disease (IHD) and 2871 cerebrovascular cases were ascertained between baseline (1993-2010) and end of follow-up (2008-2013) through medical record linkage. Annual mean 24-hour weighted road traffic noise (Lden) and air pollution (particulate matter with aerodynamic diameter ≤ 10 µm [PM10], ≤2.5 µm [PM2.5] and nitrogen dioxide [NO2]) exposure at baseline address was modelled using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU) and European-wide Land Use Regression models. Individual-level covariate data were harmonised and physically pooled across the three cohorts. Analysis was via Cox proportional hazard model with mutual adjustments for both noise and air pollution and potential confounders. RESULTS: No significant associations were found between annual mean Lden and incident CVD, IHD or cerebrovascular disease in the overall population except that the association with incident IHD was significant among current-smokers. In the fully adjusted models including adjustment for Lden, an interquartile range (IQR) higher PM10 (4.1 µg/m3) or PM2.5 (1.4 µg/m3) was associated with a 5.8% (95%CI: 2.5%-9.3%) and 3.7% (95%CI: 0.2%-7.4%) higher risk for all incident CVD respectively. No significant associations were found between NO2 and any of the CVD outcomes. CONCLUSIONS: We found suggestive evidence of a possible association between road traffic noise and incident IHD, consistent with current literature. Long-term particulate air pollution exposure, even at concentrations below current European air quality standards, was significantly associated with incident CVD.

Residential Air Pollution and Associations with Wheeze and Shortness of Breath in Adults: A Combined Analysis of Cross-Sectional Data from Two Large European Cohorts.

BACKGROUND: Research examining associations between air pollution exposure and respiratory symptoms in adults has generally been inconclusive. This may be related in part to sample size issues, which also preclude analysis in potentially vulnerable subgroups. OBJECTIVES: We estimated associations between air pollution exposures and the prevalence of wheeze and shortness of breath using harmonized baseline data from two very large European cohorts, Lifelines (2006-2013) and UK Biobank (2006-2010). Our aim was also to determine whether the relationship between air pollution and respiratory symptom prevalence differed between individuals with different characteristics. METHODS: Cross-sectional analyses explored associations between prevalence of self-reported wheeze and shortness of breath and annual mean particulate matter with aerodynamic diameter <2.5µm, 2.5-10µm, and <10µm (PM2.5, PMcoarse, and PM10, respectively) and nitrogen dioxide (NO2) concentrations at place of residence using logistic regression. Subgroup analyses and tests for interaction were performed for age, sex, smoking status, household income, obesity status, and asthma status. RESULTS: All PM exposures were associated with respiratory symptoms based on single-pollutant models, with the largest associations seen for PM2.5 with prevalence of wheezing {odds ratio (OR)=1.16 per 5µg/m³ [95% confidence interval (CI): 1.11, 1.21]} and shortness of breath [OR=1.61 per 5µg/m³ (95% CI: 1.45, 1.78)]. The association between shortness of breath and a 5-µg/m³ increment in PM2.5 was significantly higher for individuals from lower-[OR=1.73 (95% CI: 1.52, 1.97)] versus higher-income households [OR=1.31 (95% CI: 1.11, 1.55); p-interaction=0.005), whereas the association between PM2.5 and wheeze was limited to lower-income participants [OR=1.30 (95% CI: 1.22, 1.38) vs. OR=1.02; (95% CI: 0.96, 1.08); p-interaction<0.001]. Exposure to NO2 also showed positive associations with wheeze and shortness of breath. CONCLUSION: Exposure to PM and NO2 air pollution was associated with the prevalence of wheeze and shortness of breath in this large study, with stronger associations between PM2.5 and both outcomes among lower- versus higher-income participants. https://doi.org/10.1289/EHP1353.

Long-term exposure to road traffic noise, ambient air pollution, and cardiovascular risk factors in the HUNT and lifelines cohorts.

AIMS: Blood biochemistry may provide information on associations between road traffic noise, air pollution, and cardiovascular disease risk. We evaluated this in two large European cohorts (HUNT3, Lifelines). METHODS AND RESULTS: Road traffic noise exposure was modelled for 2009 using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU). Annual ambient air pollution (PM10, NO2) at residence was estimated for 2007 using a Land Use Regression model. The statistical platform DataSHIELD was used to pool data from 144 082 participants aged ≥20 years to enable individual-level analysis. Generalized linear models were fitted to assess cross-sectional associations between pollutants and high-sensitivity C-reactive protein (hsCRP), blood lipids and for (Lifelines only) fasting blood glucose, for samples taken during recruitment in 2006-2013. Pooling both cohorts, an inter-quartile range (IQR) higher day-time noise (5.1 dB(A)) was associated with 1.1% [95% confidence interval (95% CI: 0.02-2.2%)] higher hsCRP, 0.7% (95% CI: 0.3-1.1%) higher triglycerides, and 0.5% (95% CI: 0.3-0.7%) higher high-density lipoprotein (HDL); only the association with HDL was robust to adjustment for air pollution. An IQR higher PM10 (2.0 µg/m3) or NO2 (7.4 µg/m3) was associated with higher triglycerides (1.9%, 95% CI: 1.5-2.4% and 2.2%, 95% CI: 1.6-2.7%), independent of adjustment for noise. Additionally for NO2, a significant association with hsCRP (1.9%, 95% CI: 0.5-3.3%) was seen. In Lifelines, an IQR higher noise (4.2 dB(A)) and PM10 (2.4 µg/m3) was associated with 0.2% (95% CI: 0.1-0.3%) and 0.6% (95% CI: 0.4-0.7%) higher fasting glucose respectively, with both remaining robust to adjustment for air/noise pollution. CONCLUSION: Long-term exposures to road traffic noise and ambient air pollution were associated with blood biochemistry, providing a possible link between road traffic noise/air pollution and cardio-metabolic disease risk.