Regression calibration of self-reported mobile phone use to optimize quantitative risk estimation in the COSMOS study.

The Cohort Study of Mobile Phone Use and Health (COSMOS) has repeatedly collected self-reported and operator-recorded data on mobile phone use. Assessing health effects using self-reported information is prone to measurement error, but operator data were available prospectively for only part of the study population and did not cover past mobile phone use. To optimize the available data and reduce bias, we evaluated different statistical approaches for constructing mobile phone exposure histories within COSMOS. We evaluated and compared the performance of four regression calibration (RC) methods (simple, direct, inverse, and generalized additive model for location, shape, and scale), complete-case (CC) analysis and multiple imputation (MI) in a simulation study with a binary health outcome. We used self-reported and operator-recorded mobile phone call data collected at baseline (2007-2012) from participants in Denmark, Finland, the Netherlands, Sweden, and the UK. Parameter estimates obtained using simple, direct, and inverse RC methods were associated with less bias and lower mean squared error than those obtained with CC analysis or MI. We showed that RC methods resulted in more accurate estimation of the relation between mobile phone use and health outcomes, by combining self-reported data with objective operator-recorded data available for a subset of participants.

Headache in the international cohort study of mobile phone use and health (COSMOS) in the Netherlands and the United Kingdom.

Headache is a common condition with a substantial burden of disease worldwide. Concerns have been raised over the potential impact of long-term mobile phone use on headache due to radiofrequency electromagnetic fields (RF-EMFs). We explored prospectively the association between mobile phone use at baseline (2009-2012) and headache at follow-up (2015-2018) by analysing pooled data consisting of the Dutch and UK cohorts of the Cohort Study of Mobile Phone Use and Health (COSMOS) (N = 78,437). Frequency of headache, migraine, and information on mobile phone use, including use of hands-free devices and frequency of texting, were self-reported. We collected objective operator data to obtain regression calibrated estimates of voice call duration. In the model mutually adjusted for call-time and text messaging, participants in the high category of call-time showed an adjusted odds ratio (OR) of 1.04 (95 % CI: 0.94-1.15), with no clear trend of reporting headache with increasing call-time. However, we found an increased risk of weekly headache (OR = 1.40, 95 % CI: 1.25-1.56) in the high category of text messaging, with a clear increase in reporting headache with increasing texting. Due to the negligible exposure to RF-EMFs from texting, our results suggest that mechanisms other than RF-EMFs are responsible for the increased risk of headache that we found among mobile phone users.

Hearing Loss, Hearing Aid Use, and Risk of Dementia in Older Adults.

Importance: Hearing loss has been suggested as a risk factor for dementia, but there is still a need for high-quality research to better understand the association between these 2 conditions and the underlying causal mechanisms and treatment benefits using larger cohorts and detailed data. Objective: To investigate the association between hearing loss and incident dementia, as well as how hearing aid use contributes to this association. Design, Setting, and Participants: This population-based cohort study was conducted in Southern Denmark between January 2003 and December 2017 and included all residents 50 years and older. We excluded all persons with dementia before baseline as well as those who did not live in the region 5 years before baseline, with incomplete address history, or who had missing covariate information. Exposures: Individual hearing status based on the Hearing Examinations in Southern Denmark database, which contains data on all pure-tone audiometry examinations performed at public hearing rehabilitation clinics in Southern Denmark. Main Outcomes and Measures: Incident cases of dementia and Alzheimer disease as identified from national registries. Results: The study population comprised 573 088 persons (298 006 women [52%]; mean [SD] age, 60.8 [11.3] years) with 23 023 cases of dementia and mean (SD) follow-up of 8.6 (4.3) years. Having a hearing loss was associated with an increased risk of dementia, with an adjusted hazard ratio (HR) of 1.07 (95% CI, 1.04-1.11) compared with having no hearing loss. Severe hearing loss in the better and worse ear was associated with a higher dementia risk, with an HR of 1.20 (95% CI, 1.09-1.32) and 1.13 (95% CI, 1.06-1.20), respectively, compared with having no hearing loss in the corresponding ear. Compared with people without hearing loss, the risk of dementia was higher among people with hearing loss who were not using hearing aids than those who had hearing loss and were using hearing aids, with HRs of 1.20 (95% CI, 1.13-1.27) and 1.06 (95% CI, 1.01-1.10), respectively. Conclusions and Relevance: The results of this cohort study suggest that hearing loss was associated with increased dementia risk, especially among people not using hearing aids, suggesting that hearing aids might prevent or delay the onset and progression of dementia. The risk estimates were lower than in previous studies, highlighting the need for more high-quality longitudinal studies.

Long-term exposure to ambient air pollution and risk of leukemia and lymphoma in a pooled European cohort.

Leukemia and lymphoma are the two most common forms of hematologic malignancy, and their etiology is largely unknown. Pathophysiological mechanisms suggest a possible association with air pollution, but little empirical evidence is available. We aimed to investigate the association between long-term residential exposure to outdoor air pollution and risk of leukemia and lymphoma. We pooled data from four cohorts from three European countries as part of the "Effects of Low-level Air Pollution: a Study in Europe" (ELAPSE) collaboration. We used Europe-wide land use regression models to assess annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) at residences. We also estimated concentrations of PM2.5 elemental components: copper (Cu), iron (Fe), zinc (Zn); sulfur (S); nickel (Ni), vanadium (V), silicon (Si) and potassium (K). We applied Cox proportional hazards models to investigate the associations. Among the study population of 247,436 individuals, 760 leukemia and 1122 lymphoma cases were diagnosed during 4,656,140 person-years of follow-up. The results showed a leukemia hazard ratio (HR) of 1.13 (95% confidence intervals [CI]: 1.01-1.26) per 10 µg/m3 NO2, which was robust in two-pollutant models and consistent across the four cohorts and according to smoking status. Sex-specific analyses suggested that this association was confined to the male population. Further, the results showed increased lymphoma HRs for PM2.5 (HR = 1.16; 95% CI: 1.02-1.34) and potassium content of PM2.5, which were consistent in two-pollutant models and according to sex. Our results suggest that air pollution at the residence may be associated with adult leukemia and lymphoma.

Concomitant exposure to air pollution, green space and noise, and risk of myocardial infarction: a cohort study from Denmark.

AIMS: The three correlated environmental exposures (air pollution, road traffic noise, and green space) have all been associated with the risk of myocardial infarction (MI). The present study aimed to analyse their independent and cumulative association with MI. METHODS AND RESULTS: In a cohort of all Danes aged 50 or older in the period 2005-17, 5-year time-weighted average exposure to fine particles (PM2.5), ultrafine particles, elemental carbon, nitrogen dioxide (NO2), and road traffic noise at the most and least exposed façades of residence was estimated. Green space around residences was estimated from land use maps. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence interval (CI), and cumulative risk indices (CRIs) were calculated. All expressed per interquartile range. Models were adjusted for both individual and neighbourhood-level socio-demographic covariates. The cohort included 1 964 702 persons. During follow-up, 71 285 developed MI. In single-exposure models, all exposures were associated with an increased risk of MI. In multi-pollutant analyses, an independent association with risk of MI was observed for PM2.5 (HR: 1.026; 95% CI: 1.002-1.050), noise at most exposed façade (HR: 1.024; 95% CI: 1.012-1.035), and lack of green space within 150 m of residence (HR: 1.018; 95% CI: 1.010-1.027). All three factors contributed significantly to the CRI (1.089; 95% CI: 1.076-1.101). CONCLUSION: In a nationwide cohort study, air pollution, noise, and lack of green space were all independently associated with an increased risk of MI. The air pollutant PM2.5 was closest associated with MI risk.

The present study aimed to analyse their independent and cumulative association of the three correlated environmental exposures: air pollution, road traffic noise, and green space with MI. Air pollution, noise, and lack of green space were all independently associated with MI.Risk estimates for air pollution, noise, and lack of green space were similar, indicating that all may be equally relevant targets for regulatory measures.

Source-Specific Air Pollution Including Ultrafine Particles and Risk of Myocardial Infarction: A Nationwide Cohort Study from Denmark.

BACKGROUND: Air pollution is negatively associated with cardiovascular health. Impediments to efficient regulation include lack of knowledge about which sources of air pollution contributes most to health burden and few studies on effects of the potentially more potent ultrafine particles (UFP). OBJECTIVE: The authors aimed to investigate myocardial infarction (MI) morbidity and specific types and sources of air pollution. METHODS: We identified all persons living in Denmark in the period 2005-2017, age >50 y and never diagnosed with MI. We quantified 5-y running time-weighted mean concentrations of air pollution at residencies, both total and apportioned to traffic and nontraffic sources. We evaluated particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5), <0.1µm (UFP), elemental carbon (EC), and nitrogen dioxide (NO2). We used Cox proportional hazards models, with adjustment for time-varying exposures, and personal and area-level demographic and socioeconomic covariates from high-quality administrative registers. RESULTS: In this nationwide cohort of 1,964,702 persons (with 18 million person-years of follow-up and 71,285 cases of MI), UFP and PM2.5 were associated with increased risk of MI with hazard ratios (HRs) per interquartile range (IQR) of 1.040 [95% confidence interval (CI): 1.025, 1.055] and 1.053 (95% CI: 1.035, 1.071), respectively. HRs per IQR of UFP and PM2.5 from nontraffic sources were similar to the total (1.034 and 1.051), whereas HRs for UFP and PM2.5 from traffic sources were smaller (1.011 and 1.011). The HR for EC from traffic sources was 1.013 (95% CI: 1.003, 1.023). NO2 from nontraffic sources was associated with MI (HR=1.048; 95% CI: 1.034, 1.062) but not from traffic sources. In general, nontraffic sources contributed more to total air pollution levels than national traffic sources. CONCLUSIONS: PM2.5 and UFP from traffic and nontraffic sources were associated with increased risk of MI, with nontraffic sources being the dominant source of exposure and morbidity. https://doi.org/10.1289/EHP10556.

Long-term exposure to residential transportation noise and mortality: A nationwide cohort study.

Studies have indicated that transportation noise is associated with higher cardiovascular mortality, whereas evidence of noise as a risk factor for respiratory and cancer mortality is scarce and inconclusive. Also, knowledge on effects of low-level noise on mortality is very limited. We aimed to investigate associations between road and railway noise and natural-cause and cause-specific mortality in the Danish population. We estimated address-specific road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades for all residential addresses in Denmark from 1990 to 2017 using high-quality exposure models. Using these data, we calculated 10-year time-weighted mean noise exposure for 2.6 million Danes aged >50 years, of whom 600,492 died from natural causes during a mean follow-up of 11.7 years. We analyzed data using Cox proportional hazards models with adjustment for individual and area-level sociodemographic variables and air pollution (PM2.5 and NO2). We found that a 10-year mean exposure to road LdenMax and road LdenMin per 10 dB were associated with hazard ratios (95% confidence intervals) of, respectively, 1.09 (1.09; 1.10) and 1.10 (1.10; 1.11) for natural-cause mortality, 1.09 (1.08; 1.10) and 1.09 (1.08; 1.10) for cardiovascular mortality, 1.13 (1.12; 1.14) and 1.17 (1.16; 1.19) for respiratory mortality and 1.03 (1.02; 1.03) and 1.06 (1.05; 1.07) for cancer mortality. For LdenMax, the associations followed linear exposure-response relationships from 35 dB to 60-<65 dB, after which the function levelled off. For LdenMin, exposure-response relationships were linear from 35 dB and up, with some levelling off at high noise levels for natural-cause and cardiovascular mortality. Railway noise did not seem associated with higher mortality in an exposure-response dependent manner. In conclusion, road traffic noise was associated with higher mortality and the increase in risk started well below the current World Health Organization guideline limit for road traffic noise of 53 dB.

Air pollution and myocardial infarction; effect modification by sociodemographic and environmental factors. A cohort study from Denmark.

Air pollution is associated with increased risk of myocardial infarction (MI), but it is unresolved to what extent the association is modified by factors such as socioeconomic status, comorbidities, financial stress, residential green space, or road traffic noise. We formed a cohort of all (n = 1,964,702) Danes, aged 50-85 years, with 65,311 cases of MI during the followed-up period 2005-2017. For all participants we established residential five-year running average exposure to particulate matter <2.5 µm (PM2.5), ultrafine particles (UFP, <0.1 µm), elemental carbon (EC) and nitrogen dioxide (NO2). We evaluated risk in population strata, using Aalen additive hazards models to estimate absolute risk and Cox proportional hazards models to estimate relative risk of MI with 95% confidence intervals (CI). PM2.5 and the other pollutant were associated with MI. Lower education and lower income were associated with higher absolute risks of MI from air pollution, whereas no clear effect modification was apparent for relative risk estimates. For example, 5 µg/m3 higher PM2.5 was associated with HR for MI of 1.16 (95% CI: 1.10-1.22) among those with only mandatory education and 1.13 (95% CI: 1.03-1.24) among those with long education. The corresponding rate differences per 100,000 person years were 243 (95% CI: 216-271) and 358 (95% CI: 338-379), respectively. Higher level of comorbidity was consistently across all four pollutants associated with both higher absolute and relative risk of MI. In conclusion, people with comorbid conditions or of lower SES appeared more vulnerable to long-term exposure to air pollution and more cases of MI may be prevented by focused interventions in these groups.

Air pollution and stroke; effect modification by sociodemographic and environmental factors. A cohort study from Denmark.

OBJECTIVES: Air pollution increases the risk of stroke, but the literature on identifying susceptible subgroups of populations is scarce and inconsistent. The aim of this study was to investigate if the association between air pollution and risk of stroke differed by sociodemographic factors, financial stress, comorbid conditions, and residential road traffic noise, population density and green space. METHODS: We assessed long-term exposure to air pollution with ultrafine particles, PM2.5, elemental carbon and NO2 for a cohort of 1,971,246 Danes aged 50-85 years. During follow-up from 2005 to 2017, we identified 83,211 incident stroke cases. We used Cox proportional hazards model (relative risk) and Aalen additive hazards models (absolute risk) to estimate associations and confidence intervals (CI) between 5-year running means of air pollution at the residence and risk of stroke in population strata. RESULTS: All four pollutants were associated with higher risk of stroke. The association between air pollution and stroke was strongest among individuals with comorbidities, with shorter education, lower income and being retired. The results also indicated stronger associations among individuals living in less populated areas, and with low noise levels and more green space around the residence. Estimates of absolute risk seemed better suited to detect such interactions than estimates of relative risk. For example for PM2.5 the hazard ratio for stroke was 1.28 (95%CI: 1.22-1.34) and 1.26 (95%CI: 1.16-1.37) among those with mandatory and medium/long education respectively. The corresponding rate difference estimates per 100,000 person years were 568 (95%CI: 543-594) and 423(95%CI: 390-456) CONCLUSION: The associations between air pollution and risk of stroke was stronger among individuals of lower socioeconomic status or with pre-existing comorbid conditions. Absolute risk estimates were better suited to identify such effect modification.

'Source-specific' air pollution and risk of stroke in Denmark.

BACKGROUND: Long-term air pollution is a risk factor for stroke. Which types and sources of air pollution contribute most to stroke in populations is unknown. We investigated whether risk of stroke differed by type and source of air pollution. METHODS: We selected all persons aged >50 years and living in Denmark in the period 2005-17. We estimated running 5-year mean residential air-pollution concentrations of particulate matter <2.5 µm (PM2.5), ultrafine particles (UFP), elemental carbon (EC) and nitrogen dioxide (NO2). Pollutants were modelled as total air pollution from all emission sources, as well as apportioned into contributions from non-traffic and traffic sources. Hazard ratios (HRs) and CIs were estimated by using Cox proportional hazards models, adjusting for area-level and personal demographic and socio-economic covariates. We identified all primary strokes from hospital and mortality registers. RESULTS: The cohort numbered 2 million people and 94 256 cases of stroke. Interquartile ranges (IQR) of air pollution were associated with risk of stroke with HRs of 1.077 (95% CI: 1.061-1.094, IQR: 1.85 µg/m3) for PM2.5, 1.039 (1.026-1.052, IQR: 4248 particles/cm3) for UFP, 1.009 (1.001-1.018, IQR: 0.28 µg/m3) for EC and 1.028 (1.017-1.040, IQR: 7.15 µg/m3) for NO2. Traffic sources contributed little to the total exposure. HRs associated with air pollution from traffic were close to the null, whereas non-traffic sources tended to be associated with HRs higher than those for total air pollution, e.g. for non-traffic PM2.5, the HR was 1.091 (1.074-1.108). CONCLUSIONS: Air pollution, including UFP, was associated with risk of stroke. The risk appeared attributable mainly to air pollution from non-traffic sources.

Effects of Sociodemographic Characteristics, Comorbidity, and Coexposures on the Association between Air Pollution and Type 2 Diabetes: A Nationwide Cohort Study.

BACKGROUND: Exposure to air pollution has been associated with a higher risk of type 2 diabetes (T2D), but studies investigating whether deprived groups are more susceptible to the harmful effects of air pollution are inconsistent. OBJECTIVES: We aimed to investigate whether the association between air pollution and T2D differed according to sociodemographic characteristics, comorbidity, and coexposures. METHODS: We estimated residential exposure to PM2.5, ultrafine particles (UFP), elemental carbon, and NO2 for all persons living in Denmark in the period 2005-2017. In total, 1.8 million persons 50-80 y of age were included for main analyses of whom 113,985 developed T2D during follow-up. We conducted additional analyses on 1.3 million persons age 35-50 y. Using Cox proportional hazards model (relative risk) and Aalens additive hazard model (absolute risk), we calculated associations between 5-y time-weighted running means of air pollution and T2D in strata of sociodemographic variables, comorbidity, population density, road traffic noise, and green space proximity. RESULTS: Air pollution was associated with T2D, especially among people age 50-80 y, with hazard ratios of 1.17 [95% confidence interval (CI): 1.13, 1.21] per 5 µg/m3 PM2.5 and 1.16 (95% CI: 1.13, 1.19) per 10,000 UFP/cm3. In the age 50-80 y population, we found higher associations between air pollution and T2D among men in comparison with women, people with lower education vs. individuals with high education, people with medium income vs. those with low or high income, people cohabiting vs. those living alone, and people with comorbidities vs. those without comorbidities. We observed no marked changes according to occupation, population density, road noise, or surrounding greenness. In the age 35-50 y population, similar tendencies were observed, except in relation to sex and occupation, where we observed associations with air pollution only among women and blue-collar workers. DISCUSSION: We found stronger associations between air pollution and T2D among people with existing comorbidities and weaker associations among people with high socioeconomic status in comparison with those with lower socioeconomic status. https://doi.org/10.1289/EHP11347.

Transportation Noise and Risk of Tinnitus: A Nationwide Cohort Study from Denmark.

BACKGROUND: There is a growing body of evidence linking residential exposure to transportation noise with several nonauditory health outcomes. However, auditory outcomes, such as tinnitus, are virtually unexplored. OBJECTIVES: We aimed to investigate the association between residential transportation noise and risk of incident tinnitus. METHODS: We conducted a nationwide cohort study including all residents in Denmark age ≥30y, of whom 40,692 were diagnosed with tinnitus. We modeled road traffic and railway noise at the most (Ldenmax) and least (Ldenmin) exposed façades of all Danish addresses from 1990 until 2017. For all participants, we calculated 1-, 5-, and 10-y time-weighted mean noise exposure and retrieved detailed information on individual- and area-level socioeconomic covariates. We conducted analyses using Cox proportional hazards models. RESULTS: We found positive associations between exposure to road traffic noise and risk of tinnitus, with hazard ratios of 1.06 [95% confidence interval (CI): 1.04, 1.08] and 1.02 (95% CI: 1.01, 1.03) per 10-dB increase in 10-y Ldenmin and Ldenmax, respectively. Highest risk estimates were found for women, people without a hearing loss, people with high education and income, and people who had never been in a blue-collar job. The association with road Ldenmin followed a positive, monotonic exposure-response relationship. We found no association between railway noise and tinnitus. DISCUSSION: To our knowledge, this is the first study to show that residential exposure to road traffic noise may increase risk of tinnitus, suggesting noise may negatively affect the auditory system. If confirmed, this finding adds to the growing evidence of road traffic noise as a harmful pollutant with a substantial health burden. https://doi.org/10.1289/EHP11248.

Long-term exposure to transportation noise and risk of type 2 diabetes: A cohort study.

BACKGROUND: Some studies have found transportation noise to be associated with higher diabetes risk. This includes studies based on millions of participants, relying entirely on register-based confounder adjustment, which raises concern about residual lifestyle confounding. We aimed to investigate associations between noise and type 2 diabetes (T2D), including investigation of effects of increasing confounder adjustment for register-data and lifestyle. METHODS: In a cohort of 286,151 participants randomly selected across Denmark in 2010-2013 and followed up until 2017, we identified 7574 incident T2D cases. Based on residential address-history for all participants linked with exposure assessment of high spatial resolution, we calculated 10-year time-weighted mean road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades and air pollution (PM2.5). We used Cox models to calculate hazard ratios (HR) with increasing adjustment for individual- and area-level register-based sociodemographic covariates, self-reported lifestyle and air pollution. RESULTS: We found that a 10 dB increase in 10-year mean road LdenMin was associated with HRs (95% CI) of 1.06 (1.02-1.10) after adjustment for age, sex and year, 1.08 (1.04-1.13) after further adjustment for register-based sociodemographic covariates, 1.07 (1.03-1.12) after further lifestyle adjustment (e.g. smoking, diet and alcohol) and 1.06 (1.02-1.11) after further PM2.5 adjustment. For road LdenMax, the corresponding HRs were 1.07 (1.04-1.10), 1.05 (1.02-1.08), 1.04 (1.01-1.07) and 1.03 (1.00-1.06). Railway noise was associated with HRs of 1.04 (0.98-1.11) for LdenMax and 1.02 (0.92-1.12) for LdenMin after adjustment for sociodemographic and lifestyle covariates and PM2.5. CONCLUSIONS: Long-term exposure to road traffic noise was associated with T2D, which together with previous literature indicates that T2D should be considered when calculating health impacts of noise. After sociodemographic adjustment, further lifestyle adjustment only changed HRs slightly, suggesting that large register-based studies with adjustment for key sociodemographic covariates can produce reliable results.

Exposure to ambient air pollution and lipid levels and blood pressure in an adult, Danish cohort.

BACKGROUND: Air pollution is a well-recognized risk factor for cardiovascular disease. However, the mechanistic pathways underlying the association are not completely understood. Hence, further studies are required to shed light on potential mechanisms, through which air pollution may affect the development from subclinical to clinical cardiovascular disease. OBJECTIVES: To investigate associations between short-term exposure to air pollution and high-density lipoprotein (HDL), non-high density lipoprotein (non-HDL), systolic and diastolic blood pressure. METHODS: The study was conducted among 32,851 Danes from the Diet, Cancer and Health - Next Generations cohort, who had a blood sample taken and blood pressure measured. We measured HDL and non-HDL in the blood samples. We modelled exposure to fine particulate matter (PM2.5), ultrafine particles (UFP), elemental carbon (EC) and nitrogen dioxide (NO2) in time-windows from 24 h up to 90 days before blood sampling. Pollutants were modelled as total air pollution from all sources, and apportioned into contributions from non-traffic and traffic sources. We analyzed data using linear and logistic regression, with adjustment for socio-economic and lifestyle factors. RESULTS: Air pollution exposure over 24 h to 30 days was generally adversely associated with lipid profile and blood pressure, e.g. for 30-day UFP-exposure, adjusted ß-estimates were: -0.025 (-0.043; -0.006) for HDL, 0.086 (0.042; 0.130) for non-HDL, 2.45 (1.70; 3.11) for systolic and 1.56 (1.07; 20.4) for diastolic blood pressure, per 10,000 particles/cm3. The strongest associations were found for the non-traffic components of air pollution, and among those who were overweight/obese. DISCUSSION: In this large study of air pollution and lipid levels and blood pressure, we found that 24-h to 30-day PM2.5, UFP, EC and NO2 concentrations were generally adversely associated with lipid profile and blood pressure, two important cardiovascular risk factors. The study suggests potential pathways, through which air pollution could affect the development of cardiovascular disease.

Air pollution with NO2, PM2.5, and elemental carbon in relation to risk of breast cancer- a nationwide case-control study from Denmark.

Air pollution with particulate matter is an established lung carcinogen. Studies have suggested an association with breast cancer, but the evidence is inconsistent. METHODS: From nationwide registers, we identified all breast cancer cases (n = 55 745) in Denmark between 2000 and 2014. We matched one control for each case on age and year of birth. We used a multi-scale dispersion model to estimate outdoor concentrations of particulate matter <2.5 µm (PM2.5), elemental carbon (EC) and nitrogen dioxide (NO2) as time-weighted average over all addresses up to 20 years prior to diagnosis. We calculated odds ratios (OR) and 95% confidence intervals (CI) by conditional logistic regression with adjustment for marital status, educational level, occupational status, personal income, region of origin, medication and area-level socio-economic indicators. RESULTS: A 10 µg/m3 higher PM2.5 was associated with an OR for breast cancer of 1.21 (95% CI: 1.11-1.33). The corresponding ORs for EC (per 1 µg/m3) and NO2 (per 10 µg/m3) were 1.03 (95% CI: 1.00-1.07) and 1.03 (95% CI: 1.01-1.06), respectively. In multi-pollutant models, the OR for PM2.5 changed only little, whereas ORs for EC or NO2 approached the null. In an analysis of persons below 55 years, PM2.5 was associated with an OR of 1.32 (95% CI: 1.09-1.60) per 10 µg/m3 increase. CONCLUSION: We found evidence of an association between the investigated air pollutants and breast cancer, especially PM2.5. There were indications that the association differed by age at diagnosis. We were not able to include all potential confounders and thus, results should be interpreted with caution.

Time trends in mobile phone use and glioma incidence among males in the Nordic Countries, 1979-2016.

INTRODUCTION: In the Nordic countries, the use of mobile phones increased sharply in the mid-1990s especially among middle-aged men. We investigated time trends in glioma incidence rates (IR) with the perspective to inform about the plausibility of brain tumour risks from mobile phone use reported in some case-control studies. METHODS: We analysed IR of glioma in Denmark, Finland, Norway, and Sweden among men aged 40-69 years, using data from national cancer registries and population statistics during 1979-2016, using log-linear joinpoint analysis. Information on regular mobile phone use and amount of call-time was obtained from major studies of mobile phones in these countries. We compared annual observed incidence with that expected under various risk scenarios to assess which of the reported effect sizes are compatible with the observed IR. The expected numbers of cases were computed accounting for an impact of other factors besides mobile phone use, such as improved cancer registration. RESULTS: Based on 18,232 glioma cases, IR increased slightly but steadily with a change of 0.1% (95 %CI 0.0%; 0.3%) per year during 1979-2016 among 40-59-year-old men and for ages 60-69, by 0.6 % (95 %CI 0.4; 0.9) annually. The observed IR trends among men aged 40-59 years were incompatible with risk ratios (RR) 1.08 or higher with a 10-year lag, RR ≥ 1.2 with 15-year lag and RR ≥ 1.5 with 20-year lag. For the age group 60-69 years, corresponding effect sizes RR ≥ 1.4, ≥2 and ≥ 2.5 could be rejected for lag times 10, 15 and 20 years. DISCUSSION: This study confirms and reinforces the conclusions that no changes in glioma incidence in the Nordic countries have occurred that are consistent with a substantial risk attributable to mobile phone use. This particularly applies to virtually all reported risk increases reported by previous case-control studies with positive findings.

Occupational noise exposure and risk of incident stroke: a pooled study of five Scandinavian cohorts.

OBJECTIVES: To investigate the association between occupational noise exposure and stroke incidence in a pooled study of five Scandinavian cohorts (NordSOUND). METHODS: We pooled and harmonised data from five Scandinavian cohorts resulting in 78 389 participants. We obtained job data from national registries or questionnaires and recoded these to match a job-exposure matrix developed in Sweden, which specified the annual average daily noise exposure in five exposure classes (LAeq8h): <70, 70-74, 75-79, 80-84, ≥85 dB(A). We identified residential address history and estimated 1-year average road traffic noise at baseline. Using national patient and mortality registers, we identified 7777 stroke cases with a median follow-up of 20.2 years. Analyses were conducted using Cox proportional hazards models adjusting for individual and area-level potential confounders. RESULTS: Exposure to occupational noise at baseline was not associated with overall stroke in the fully adjusted models. For ischaemic stroke, occupational noise was associated with HRs (95% CI) of 1.08 (0.98 to 1.20), 1.09 (0.97 to 1.24) and 1.06 (0.92 to 1.21) in the 75-79, 80-84 and ≥85 dB(A) exposure groups, compared with <70 dB(A), respectively. In subanalyses using time-varying occupational noise exposure, we observed an indication of higher stroke risk among the most exposed (≥85 dB(A)), particularly when restricting analyses to people exposed to occupational noise within the last year (HR: 1.27; 95% CI: 0.99 to 1.63). CONCLUSIONS: We found no association between occupational noise and risk of overall stroke after adjustment for confounders. However, the non-significantly increased risk of ischaemic stroke warrants further investigation.

Long-term exposure to ambient air pollution and bladder cancer incidence in a pooled European cohort: the ELAPSE project.

BACKGROUND: The evidence linking ambient air pollution to bladder cancer is limited and mixed. METHODS: We assessed the associations of bladder cancer incidence with residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3) and eight PM2.5 elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in a pooled cohort (N = 302,493). Exposures were primarily assessed based on 2010 measurements and back-extrapolated to the baseline years. We applied Cox proportional hazard models adjusting for individual- and area-level potential confounders. RESULTS: During an average of 18.2 years follow-up, 967 bladder cancer cases occurred. We observed a positive though statistically non-significant association between PM2.5 and bladder cancer incidence. Hazard Ratios (HR) were 1.09 (95% confidence interval (CI): 0.93-1.27) per 5 µg/m3 for 2010 exposure and 1.06 (95% CI: 0.99-1.14) for baseline exposure. Effect estimates for NO2, BC and O3 were close to unity. A positive association was observed with PM2.5 zinc (HR 1.08; 95% CI: 1.00-1.16 per 10 ng/m3). CONCLUSIONS: We found suggestive evidence of an association between long-term PM2.5 mass exposure and bladder cancer, strengthening the evidence from the few previous studies. The association with zinc in PM2.5 suggests the importance of industrial emissions.

The effect of adjustment to register-based and questionnaire-based covariates on the association between air pollution and cardiometabolic disease.

OBJECTIVE: Recent studies on air pollution and disease have been based on millions of participants within a region or country, relying entirely on register-based confounder adjustment. We aimed to investigate the effects of increasing adjustment for register- and questionnaire-based covariates on the association between air pollution and cardiometabolic diseases. METHODS: In a population-based cohort of 246,766 eligible participants randomly selected across Denmark in 2010 and 2013 and followed up until December 31, 2017, we identified 3,247 myocardial infarction (MI) cases, 4,166 stroke cases and 6,366 type 2 diabetes cases. Based on historical address-information, we calculated 5-year time-weighted exposure to PM2.5 and NO2 modelled using a validated air pollution model. We used Cox proportional hazards models to calculate hazard ratios (HR) with increasing adjustment for a number of individual- and area-level register-based covariates as well as lifestyle covariates assessed through questionnaires. RESULTS: We found that a 5 µg/m3 higher PM2.5 was associated with HRs (95% CI) for MI, stroke and diabetes, of respectively, 1.18 (0.91-1.52), 1.11 (0.88-1.40) and 1.24 (1.03-1.50) in the fully adjusted models. For all three diseases, adjustment for either individual-level, area-level or lifestyle covariates, or combinations of these resulted in higher HRs compared to HRs adjusted only for age, sex and calendar-year, most marked for MI and diabetes. Further adjustment for lifestyle in models with full register-based individual- and area-level adjustment resulted in only minor changes in HRs for all three diseases. CONCLUSIONS: Our findings suggest that in studies of air pollution and cardiometabolic disease, which use an adjustment strategy with a broad range of register-based socioeconomic variables, there is no effect on risk estimates from subsequent lifestyle adjustment.