Radon and lung cancer in the pooled uranium miners analysis (PUMA): highly exposed early miners and all miners.

OBJECTIVES: Radon is a ubiquitous occupational and environmental lung carcinogen. We aim to quantify the association between radon progeny and lung cancer mortality in the largest and most up-to-date pooled study of uranium miners. METHODS: The pooled uranium miners analysis combines 7 cohorts of male uranium miners with 7754 lung cancer deaths and 4.3 million person-years of follow-up. Vital status and lung cancer deaths were ascertained between 1946 and 2014. The association between cumulative radon exposure in working level months (WLM) and lung cancer was modelled as the excess relative rate (ERR) per 100 WLM using Poisson regression; variation in the association by temporal and exposure factors was examined. We also examined analyses restricted to miners first hired before 1960 and with <100 WLM cumulative exposure. RESULTS: In a model that allows for variation by attained age, time since exposure and annual exposure rate, the ERR/100 WLM was 4.68 (95% CI 2.88 to 6.96) among miners who were less than 55 years of age and were exposed in the prior 5 to <15 years at annual exposure rates of <0.5 WL. This association decreased with older attained age, longer time since exposure and higher annual exposure rate. In analyses restricted to men first hired before 1960, we observed similar patterns of association but a slightly lower estimate of the ERR/100 WLM. CONCLUSIONS: This new large, pooled study confirms and supports a linear exposure-response relationship between cumulative radon exposure and lung cancer mortality which is jointly modified by temporal and exposure factors.

Low emission zones reduced PM10 but not NO2 concentrations in Berlin and Munich, Germany.

Low emission zones (LEZs) aiming at improving the air quality in urban areas have been implemented in many European cities. However, studies are limited in evaluating the effects of LEZ, and most of which used simple methods. In this study, a general additive mixed model was utilized to account for confounders in the atmosphere and validate the effects of LEZ on PM10 and NO2 concentrations in two German cities. In addition, the effects of LEZ on elemental carbon (EC) and total carbon (TC) in Berlin were also evaluated. The LEZ effects were estimated after taking into account air pollutant concentrations at a reference site located in the regional background, and adjusting for hour of the week, public holidays, season, and wind direction. The LEZ in Berlin, and the LEZ in combination with the heavy-duty vehicle (HDV) transit ban in Munich significantly reduced the PM10 concentrations, at both traffic sites (TS) and urban background sites (UB). The effects were greater in LEZ stage 3 than in LEZ stages 2 and 1. Moreover, compared with PM10, LEZ was more efficient in reducing EC, a component that is considered more toxic than PM10 mass. In contrast, the LEZ had no consistent effect on NO2 levels: no effects were observed in Berlin; in Munich, the combination of the LEZ and the HDV transit ban reduced NO2 at UB site in LEZ stage 1, but without further reductions in subsequent stages of the LEZ. Overall, our study indicated that LEZs, which target the major primary air pollution source in the highly populated city center could be an effective way to improve urban air quality such as PM mass concentration and EC level.

STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2-More complex methods of adjustment and advanced topics.

We continue our review of issues related to measurement error and misclassification in epidemiology. We further describe methods of adjusting for biased estimation caused by measurement error in continuous covariates, covering likelihood methods, Bayesian methods, moment reconstruction, moment-adjusted imputation, and multiple imputation. We then describe which methods can also be used with misclassification of categorical covariates. Methods of adjusting estimation of distributions of continuous variables for measurement error are then reviewed. Illustrative examples are provided throughout these sections. We provide lists of available software for implementing these methods and also provide the code for implementing our examples in the Supporting Information. Next, we present several advanced topics, including data subject to both classical and Berkson error, modeling continuous exposures with measurement error, and categorical exposures with misclassification in the same model, variable selection when some of the variables are measured with error, adjusting analyses or design for error in an outcome variable, and categorizing continuous variables measured with error. Finally, we provide some advice for the often met situations where variables are known to be measured with substantial error, but there is only an external reference standard or partial (or no) information about the type or magnitude of the error.

STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Measurement error and misclassification of variables frequently occur in epidemiology and involve variables important to public health. Their presence can impact strongly on results of statistical analyses involving such variables. However, investigators commonly fail to pay attention to biases resulting from such mismeasurement. We provide, in two parts, an overview of the types of error that occur, their impacts on analytic results, and statistical methods to mitigate the biases that they cause. In this first part, we review different types of measurement error and misclassification, emphasizing the classical, linear, and Berkson models, and on the concepts of nondifferential and differential error. We describe the impacts of these types of error in covariates and in outcome variables on various analyses, including estimation and testing in regression models and estimating distributions. We outline types of ancillary studies required to provide information about such errors and discuss the implications of covariate measurement error for study design. Methods for ascertaining sample size requirements are outlined, both for ancillary studies designed to provide information about measurement error and for main studies where the exposure of interest is measured with error. We describe two of the simpler methods, regression calibration and simulation extrapolation (SIMEX), that adjust for bias in regression coefficients caused by measurement error in continuous covariates, and illustrate their use through examples drawn from the Observing Protein and Energy (OPEN) dietary validation study. Finally, we review software available for implementing these methods. The second part of the article deals with more advanced topics.

How short is too short? A randomised controlled trial evaluating short-term existential behavioural therapy for informal caregivers of palliative patients.

BACKGROUND: Informal caregivers of palliative patients show higher levels of depression and distress compared with the general population. Fegg's (2013) existential behavioural therapy was shortened to two individual 1-h sessions (short-term existential behavioural therapy). AIM: Testing the effectiveness of sEBT on psychological symptoms of informal caregivers in comparison with active control. DESIGN: Randomised controlled trial. SETTING/PARTICIPANTS: Informal caregivers of palliative in-patients. METHODS: The primary outcome was depression; secondary outcomes were anxiety, subjective distress and minor mental disorders, positive and negative affect, satisfaction with life, quality of life and direct health care costs. General linear mixed models allow several measurements per participant and change over time. Reasons for declining the intervention were investigated by Rosenstock's Health Belief Model. RESULTS: Overall inclusion rate was 41.0%. Data of 157 caregivers were available (63.1% females; mean age: 54.6 years, standard deviation (SD): 14.1); 127 participants were included in the main analysis. Participation in sEBT or active control was not significantly associated with post-treatment depression. Outcomes showed prevailingly significant association with time of investigation. Self-efficacy, scepticism of benefit of the intervention, belief of better coping alone and support by family and friends were significant factors in declining participation in the randomised controlled trial. CONCLUSION: Inclusion rate was tripled compared with a previously evaluated longer EBT group intervention. By shortening the intervention, inclusion rate was traded for effectiveness and the intervention could not impact caregivers' psychological state. Early integration of sEBT and combination of individual and group setting and further study of the optimal length for caregiver interventions are suggested.

Mixtures of Berkson and classical covariate measurement error in the linear mixed model: Bias analysis and application to a study on ultrafine particles.

The ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual-specific measurement error; Berkson-type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual-specific error components, autocorrelated errors, and a mixture of classical and Berkson error. Theoretical considerations and simulation results show, that autocorrelation may severely change the attenuation of the effect estimations. Furthermore, unbalanced designs and the inclusion of confounding variables influence the degree of attenuation. Bias correction with the method of moments using data with mixture measurement error partially yielded better results compared to the usage of incomplete data with classical error. Confidence intervals (CIs) based on the delta method achieved better coverage probabilities than those based on Bootstrap samples. Moreover, we present the application of these new methods to heart rate measurements within the Augsburger Umweltstudie: the corrected effect estimates were slightly higher than their naive equivalents. The substantial measurement error of ultrafine particle measurements has little impact on the results. The developed methodology is generally applicable to longitudinal data with measurement error.

Individual meaning in life assessed with the Schedule for Meaning in Life Evaluation: toward a circumplex meaning model.

OBJECTIVE: The experience of "meaning in life" (MiL) is a major aspect of life satisfaction and psychological well-being. To assess this highly individual construct, idiographic measures with open-response formats have been developed. However, it can be challenging to categorize these individual experiences for interindividual comparisons. Our study aimed to derive MiL categories from individual listings and develop an integrative MiL model. METHOD: University students were asked to rate 58 MiL providing aspects recently found in a nationwide study using the Schedule for Meaning in Life Evaluation (SMiLE), an MiL instrument allowing for open responses. Pearson's correlations and factor analyses were used to test the unidimensionality of subsequently derived higher-order MiL categories. Multidimensional scaling, cluster analysis, and factor analysis were performed to further analyze a latent MiL structure. RESULTS: A total of 340 students participated in the study. Some 11 unidimensional categories consisting of 34 meaning-providing aspects were summarized into a circumplex model with four MiL domains: leisure/health, work/finances, culture/spirituality, and relationships (family, partnership, social relations). SIGNIFICANCE OF RESULTS: This model seems to incorporate a major portion of individual respondent-generated MiL listings. It may be useful for future idiographic MiL studies to help organize individual experiences of MiL and allow for higher-level interindividual comparisons. Further studies including different samples are necessary to confirm this model or derive other MiL domains, for example, in palliative care patients or patients who are confronted with a loss of meaning.

Lung Cancer and Radon: Pooled Analysis of Uranium Miners Hired in 1960 or Later.

BACKGROUND: Despite reductions in exposure for workers and the general public, radon remains a leading cause of lung cancer. Prior studies of underground miners depended heavily upon information on deaths among miners employed in the early years of mine operations when exposures were high and tended to be poorly estimated. OBJECTIVES: To strengthen the basis for radiation protection, we report on the follow-up of workers employed in the later periods of mine operations for whom we have more accurate exposure information and for whom exposures tended to be accrued at intensities that are more comparable to contemporary settings. METHODS: We conducted a pooled analysis of cohort studies of lung cancer mortality among 57,873 male uranium miners in Canada, Czech Republic, France, Germany, and the United States, who were first employed in 1960 or later (thereby excluding miners employed during the periods of highest exposure and focusing on miners who tend to have higher quality assessments of radon progeny exposures). We derived estimates of excess relative rate per 100 working level months (ERR/100 WLM) for mortality from lung cancer. RESULTS: The analysis included 1.9 million person-years of observation and 1,217 deaths due to lung cancer. The relative rate of lung cancer increased in a linear fashion with cumulative exposure to radon progeny (ERR/100 WLM=1.33; 95% CI: 0.89, 1.88). The association was modified by attained age, age at exposure, and annual exposure rate; for attained ages <55 y, the ERR/100 WLM was 8.38 (95% CI: 3.30, 18.99) among miners who were exposed at ≥35 years of age and at annual exposure rates of <0.5 working levels. This association decreased with older attained ages, younger ages at exposure, and higher exposure rates. DISCUSSION: Estimates of association between radon progeny exposure and lung cancer mortality among relatively contemporary miners are coherent with estimates used to inform current protection guidelines. https://doi.org/10.1289/EHP10669.

Mortality in Underground Miners in a Former Uranium Ore Mine­Results of a Cohort Study Among Former Employees of Wismut AG in Saxony and Thuringia.

BACKGROUND: From 1946 to 1990, more than 400 000 people were employed by Wismut AG, a Soviet/Soviet-German corporation (German abbreviation: SAG/ SDAG), in the East German states of Saxony and Thuringia. In the early years in particular, employees were exposed to large amounts of radon and respirable crystalline silica. METHODS: In a cohort of 35 204 former underground employees of Wismut AG, mortality was analyzed in comparison to the general male population of East Germany, and the pertaining standardized mortality ratios (SMRs) were calculated. RESULTS: 18 510 persons in the study cohort died in the follow-up period 1960-2013. Mortality from lung cancer was 2.36 higher in the study cohort than in the general population (95% confidence interval, [2.28; 2.45]); the associated SMRs rose markedly with increasing radon exposure. Mortality from silicosis and other types of pneumoconiosis was elevated by a factor of 22.62 [21.20; 24.11], and the associated SMRs rose exponentially with increasing exposure to respirable crystalline silica. Mortality from both of these causes was still markedly elevated more than 20 years after Wismut AG had ceased its activities. Mortality from a wide range of other diseases was elevated as well, with the following SMRs: stomach cancer, 1.28 [1.17; 1.40]; liver cancer, 1.34 [1.15; 1.55]; all tumors other than lung cancer, 1.06 [1.02; 1.09]; infections, 1.18 [1.01; 1.38]; cerebrovascular diseases, 1.33 [1.26; 1.41]; and influenza/pneumonia, 1.13 [1.01; 1.27]. Mortality from a small number of other causes was found to be markedly lowered in the study cohort (mental illness, renal diseases, and nervous system diseases). The role of occupational risk factors, lifestyle differences and other reasons for the latter results is unclear. CONCLUSION: Underground miners employed by Wismut AG displayed marked excess mortality due to silicosis/other pneumoconiosis and lung cancer. The contribution of individual occupational risk factors for these and other causes of death with increased SMR are being further investigated in analyses within the study cohort.

Epidemiologic analyses with error-prone exposures: review of current practice and recommendations.

PURPOSE: Variables in observational studies are commonly subject to measurement error, but the impact of such errors is frequently ignored. As part of the STRengthening Analytical Thinking for Observational Studies Initiative, a task group on measurement error and misclassification seeks to describe the current practice for acknowledging and addressing measurement error. METHODS: Task group on measurement error and misclassification conducted a literature survey of four types of research studies that are typically impacted by exposure measurement error: (1) dietary intake cohort studies, (2) dietary intake population surveys, (3) physical activity cohort studies, and (4) air pollution cohort studies. RESULTS: The survey revealed that while researchers were generally aware that measurement error affected their studies, very few adjusted their analysis for the error. Most articles provided incomplete discussion of the potential effects of measurement error on their results. Regression calibration was the most widely used method of adjustment. CONCLUSIONS: Methods to correct for measurement error are available but require additional data regarding the error structure. There is a great need to incorporate such data collection within study designs and improve the analytical approach. Increased efforts by investigators, editors, and reviewers are needed to improve presentation of research when data are subject to error.

Personal exposure to ultrafine particles: Two-level statistical modeling of background exposure and time-activity patterns during three seasons.

Personal exposure to air pollution is associated with time- and location-specific factors including indoor and outdoor air pollution, meteorology and time activities. Our investigation aims at the description and identification of factors determining personal exposure to particle number concentration (PNC) in everyday situations. Ten volunteers recorded their personal exposure to PNC and kept an activity diary in three different seasons besides stationary measurements of ambient air pollution and meteorology. Background exposure to PNC was modelled using the most predictive variables. In a second step, the effects of the activities were calculated adjusted for the background exposure. The average personal PNC level was highest in winter and was three times higher than the mean stationary PNC level while staying indoors and two times higher while staying outdoors. Personal indoor PNC levels were significantly increased during the use of candles, cooking and the occurrence of smell of food. High stationary outdoor PNC levels and low dew point temperatures were associated with increased personal outdoor PNC levels. Times spent in public transport were associated with lower personal PNC levels than other times spent in transportation. Personal PNC levels in everyday situations exhibited a large variability because of seasonal, microenvironment-specific and activity-specific influences.