Longitudinal associations between risk appraisal of base stations for mobile phones, radio or television and non-specific symptoms.

INTRODUCTION: Studies found that higher risk appraisal of radiofrequency electromagnetic fields is associated with reporting more non-specific symptoms such as headache and back pain. There is limited data available on the longitudinal nature of such associations and what aspects of risk appraisal and characteristics of subjects are relevant. OBJECTIVE: To examine cross-sectional and longitudinal associations between risk appraisal measures and non-specific symptoms, and assess the role of subject characteristics (sex, age, education, trait negative affect) in a general population cohort. METHODS: This study was nested in the Dutch general population AMIGO cohort that was established in 2011/2012, when participants were 31-65 years old. We studied a sample of participants (n = 1720) who filled in two follow-up questionnaires in 2013 and 2014, including questions about perceived exposure, perceived risk, and health concerns as indicators of risk appraisal of base stations, and non-specific symptoms. RESULTS: Perceived exposure, perceived risk, and health concerns, respectively, were associated with higher symptom scores in cross-sectional and longitudinal analyses. Only health concerns (not perceived exposure and perceived risk) temporally preceded high symptom scores and vice versa. Female sex, younger age, higher education, and higher trait negative affect were associated with higher risk appraisal of mobile phone base stations. DISCUSSION: The findings in this study strengthen the evidence base for cross-sectional and longitudinal associations between higher risk appraisal and non-specific symptoms in the general population. However, the directionality of potential causal relations in non-sensitive general population samples should be examined further in future studies, providing information to the benefit of risk communication strategies.

Modeled and perceived RF-EMF, noise and air pollution and symptoms in a population cohort. Is perception key in predicting symptoms?

BACKGROUND: Psychosocial research has shown that perceived exposure can influence symptom reporting, regardless of actual exposure. The impact of this phenomenon on the interpretation of results from epidemiological research on environmental determinants of symptoms is unclear. OBJECTIVE: Our aim was to compare associations between modeled exposures, the perceived level of these exposures and reported symptoms (non-specific symptoms, sleep disturbances, and respiratory symptoms) for three different environmental exposures (radiofrequency electromagnetic fields (RF-EMF), noise, and air pollution). These environmental exposures vary in the degree to which they can be sensorially observed. METHODS: Participant characteristics, perceived exposures, and self-reported health were assessed with a baseline (n = 14,829, 2011/2012) and follow-up (n = 7905, 2015) questionnaire in the Dutch population-based Occupational and Environmental Health Cohort (AMIGO). Environmental exposures were estimated at the home address using spatial models. Cross-sectional and longitudinal regression models were used to examine the associations between modeled and perceived exposures, and reported symptoms. RESULTS: The extent to which exposure sources could be observed by participants likely influenced correlations between modeled and perceived exposure as correlations were moderate for air pollution (rSp = 0.34) and noise (rSp = 0.40), but less so for RF-EMF (rSp = 0.11). Perceived exposures were consistently associated with increased symptom scores (respiratory, sleep, non-specific). Modeled exposures, except RF-EMF, were associated with increased symptom scores, but these associations disappeared or strongly diminished when accounted for perceived exposure in the analyses. DISCUSSION: Perceived exposure has an important role in symptom reporting. When environmental determinants of symptoms are studied without acknowledging the potential role of both modeled and perceived exposures, there is a risk of bias in health risk assessment. However, the etiological role of exposure perceptions in relation to symptom reporting requires further research.

Modeled and Perceived Exposure to Radiofrequency Electromagnetic Fields From Mobile-Phone Base Stations and the Development of Symptoms Over Time in a General Population Cohort.

We assessed associations between modeled and perceived exposure to radiofrequency electromagnetic fields (RF-EMF) from mobile-phone base stations and the development of nonspecific symptoms and sleep disturbances over time. A population-based Dutch cohort study, the Occupational and Environmental Health Cohort Study (AMIGO) (n = 14,829; ages 31-65 years), was established in 2011/2012 (T0), with follow-up of a subgroup (n = 3,992 invited) in 2013 (T1; n = 2,228) and 2014 (T2; n = 1,740). We modeled far-field RF-EMF exposure from mobile-phone base stations at the home addresses of the participants using a 3-dimensional geospatial model (NISMap). Perceived exposure (0 = not at all; 6 = very much), nonspecific symptoms, and sleep disturbances were assessed by questionnaire. We performed cross-sectional and longitudinal analyses, including fixed-effects regression. We found small correlations between modeled and perceived exposure in AMIGO participants at baseline (n = 14,309; rSpearman = 0.10). For 222 follow-up participants, modeled exposure increased substantially (>0.030 mW/m2) between T0 and T1. This increase in modeled exposure was associated with an increase in perceived exposure during the same time period. In contrast to modeled RF-EMF exposure from mobile-phone base stations, perceived exposure was associated with higher symptom reporting scores in both cross-sectional and longitudinal analyses, as well as with sleep disturbances in cross-sectional analyses.

"These Power Lines Make Me Ill": A Typology of Residents' Health Responses to a New High-Voltage Power Line.

Little attention has been devoted to the potential diversity in residents' health responses when exposed to an uncertain environmental health risk. The present study explores whether subgroups of residents respond differently to a new high-voltage power line (HVPL) being put into operation. We used a quasi-experimental prospective field study design with two pretests during the construction of a new HVPL, and two posttests after it was put into operation. Residents living nearby (0-300 m, n = 229) filled out questionnaires about their health and their perception of the environment. We applied latent class growth models to investigate heterogeneity in the belief that health complaints were caused by a power line. Classes were compared on a wide range of variables relating to negative-oriented personality traits, perceived physical and mental health, and perceptions of the environment. We identified five distinct classes of residents, of which the largest (49%) could be described as emotionally stable and healthy with weak responses to the introduction of a new power line. A considerable minority (9%) responded more strongly to the new line being activated. Residents in this class had heard more about the health effects of power lines beforehand, were more aware of the activation of the new line, and reported a decrease in perceived health afterwards. Based on our findings we can conclude that there is a considerable heterogeneity in health responses to a new HVPL. Health risk perceptions appear to play an important role in this typology, which has implications for risk management.

Cumulative exposure to shift work and sickness absence: associations in a five-year historic cohort.

BACKGROUND: Exposure to shift work has been associated with negative health consequences, although the association between shift work and sickness absence remains unclear. The aim of this study is to investigate associations between cumulative exposure to shift work and sickness absence among ground staff employees of an airline company. METHODS: This study used data from the MORE (Monitoring Occupational Health Risks in Employees) cohort, which is a 5-year historic cohort. The population of the present study consisted of 7562 ground staff employees. For each employee, work schedules and sickness absence days between 2005 and 2009 were obtained from company records. For the exposure to different shift schedule types and to the cumulative number of night shifts, the association with long-term sickness absence (>7 consecutive sickness absence days) and the number of sickness absence episodes during 2009, was calculated using logistic and Poisson regression analyses. Socio-demographic variables, work-related variables, job classification variables, and previous sickness absence days were regarded as confounders. RESULTS: After adjusting for previous sickness absence and job classification variables, only the group of employees that switched into working in a three-shift schedule, showed a significantly increased risk for long-term sickness absence (OR = 1.31, 95%CI 1.02-1.69). Night shift exposure was not significantly associated with long-term sickness absence. Exposure to shift work was negatively associated with more sickness absence episodes. Employees who were exposed to more than 46 night shifts also showed a lower risk for more sickness absence episodes. Subgroup analyses showed that single employees and employees without children had an increased risk for long-term sickness absence when exposed to a three-shift schedule, and when they had changed between shift schedule types. CONCLUSIONS: Cumulative exposure to shift work proved to be negatively associated with more sickness absence episodes, and was not associated with more long-term sickness absence, although selection bias could not be ruled out. Future research should explore the influence of household composition, and take into account both previous sickness absence and psychosocial and physical work factors to obtain a better estimation of the association between shift work and sickness absence.

Risk factors for fatigue among airline pilots.

PURPOSE: The objective of this study is to determine risk factors for fatigue among airline pilots, taking into account person-, work-, health-, sleep-, and lifestyle-related characteristics. METHODS: The study population consisted of 502 pilots who participated in the MORE Energy study. Included risk factors were either measured through an online questionnaire or provided by the company. The outcome of this study, fatigue, was assessed using the Checklist Individual Strength (CIS), and was defined as scoring more than 76 points on this questionnaire. The association of the risk factors with fatigue was determined using univariate and multivariate logistic regression analyses. RESULTS: Of the participating pilots, 29.5 % scored more than 76 points on the CIS and were classified as being fatigued. The fully adjusted regression model showed that person-, work-, health-, and lifestyle-related characteristics were associated with fatigue. Pilots who were aged 31 to 40 (OR 3.36, 95 % CI 1.32-8.53) or 41 to 50 (OR 4.19, 95 % CI 1.40-12.47), an evening type (OR 2.40, 95 % CI 1.38-4.16), scored higher on work-life balance disturbance (OR 1.22, 95 % CI 1.10-1.36), scored higher on need for recovery (OR 1.02, 95 % CI 1.01-1.04), scored lower on general health perception (OR 0.31, 95 % CI 0.20-0.47), were less physically active (OR 0.77, 95 % CI 0.66-0.89), and had a moderate alcohol consumption (OR 3.88, 95 % CI 1.21-12.43), were at higher risk for fatigue. CONCLUSIONS: Higher age, being an evening type, disturbance of the work-life balance, more need for recovery, a lower perceived health, less physical activity, and moderate alcohol consumption were shown to be risk factors for fatigue. Further longitudinal research is needed to elucidate the direction of the associations found and to evaluate the effects of possible countermeasures in airline pilots.

Process evaluation of a tailored mobile health intervention aiming to reduce fatigue in airline pilots.

BACKGROUND: MORE Energy is a mobile health intervention which aims to reduce fatigue and improve health in airline pilots. The primary objective of this process evaluation was to assess the reach, dose delivered, compliance, fidelity, barriers and facilitators, and satisfaction of the intervention. The second objective was to investigate the associations of adherence to the intervention with compliance and with participant satisfaction. Thirdly, we investigated differences between the subgroups within the target population. METHODS: The intervention consisted of a smartphone application, supported by a website. It provided advice on optimal light exposure, sleep, nutrition, and physical activity, tailored to flight and personal characteristics. The reach of the intervention was determined by comparing the intervention group participants and the airline pilots who did not participate. The dose delivered was defined as the total number of participants that was sent an instruction email. Objective compliance was measured through the Control Management System of the application. To determine the fidelity, an extensive log was kept throughout the intervention period. Subjective compliance, satisfaction, barriers, facilitators, and adherence were assessed using online questionnaires. Associations between the extent to which the participants applied the advice in daily life (adherence), compliance, and satisfaction were analysed as well. Finally, outcomes of participants of different age groups and haul types were compared. RESULTS: A total of 2222 pilots were made aware of the study. From this group, 502 pilots met the inclusion criteria and did agree to participate. The reach of the study proved to be 22 % and the dose delivered was 99 %. The included pilots were randomized into the intervention group (n = 251) or the control group (n = 251). Of the intervention group participants, 81 % consulted any advice, while 17 % did this during four weeks or more. Fidelity was 67 %. The participants rated the intervention with a 6.4 (SD 1.6). Adherence was not associated with compliance, but was associated with satisfaction (p ≤ 0.001). Pilots of 35 to 45 year old were significantly more interested in advice regarding physical activity than their colleagues, and short-haul pilots were more interested in advice regarding nutrition compared to long-haul pilots. CONCLUSIONS: The MORE Energy intervention was well received, resulting in an adequate reach and a high dose delivered. The compliance and satisfaction scores indicate that engagement and functionality should be enhanced, and the content and applicability of the advices should be improved to appeal all subgroups of the target population. TRIAL REGISTRATION: Nederlands Trial Register NTR2722 . Registered 27 January 2011.

Residential exposure to RF-EMF from mobile phone base stations: Model predictions versus personal and home measurements.

INTRODUCTION: Geospatial models have been demonstrated to reliably and efficiently estimate RF-EMF exposure from mobile phone base stations (downlink) at stationary locations with the implicit assumption that this reflects personal exposure. In this study we evaluated whether RF-EMF model predictions at the home address are a good proxy of personal 48h exposure. We furthermore studied potential modification of this association by degree of urbanisation. METHOD: We first used an initial NISMap estimation (at an assumed height of 4.5m) for 9563 randomly selected addresses in order to oversample addresses with higher exposure levels and achieve exposure contrast. We included 47 individuals across the range of potential RF-EMF exposure and used NISMap to re-assess downlink exposure at the home address (at bedroom height). We computed several indicators to determine the accuracy of the NISMap model predictions. We compared residential RF-EMF model predictions with personal 48h, at home, and night-time (0:00-8:00AM) ExpoM3 measurements, and with EME-SPY 140 spot measurements in the bedroom. We obtained information about urbanisation degree and compared the accuracy of model predictions in high and low urbanised areas. RESULTS: We found a moderate Spearman correlation between model predictions and personal 48h (rSp=0.47), at home (rSp=0.49), at night (rSp=0.51) and spot measurements (rSp=0.54). We found no clear differences between high and low urbanised areas (48h: high rSp=0.38, low rSp=0.55, bedroom spot measurements: high rSp=0.55, low rSp=0.50). DISCUSSION: We achieved a meaningful ranking of personal downlink exposure irrespective of degree of urbanisation, indicating that these models can provide a good proxy of personal exposure in areas with varying build-up.

Nocebo responses to high-voltage power lines: Evidence from a prospective field study.

BACKGROUND: Experimental studies suggest that nocebo responses might occur after exposure to equipment emitting electromagnetic fields such as high voltage power lines (HVPLs) or mobile phone base stations. OBJECTIVES: The present study investigates to what extent health responses to a new HVPL can be explained by beliefs of residents regarding the health effects of HVPLs. METHODS: We used a quasi-experimental prospective field study design with two pretests during the construction of a new HVPL, and two posttests after it has been put into operation. Residents living near (0-300 m, n=229; 300-500 m, n=489) and farther away (500-2000 m, n=536) filled out questionnaires about their health and their beliefs about the negative health effects of power lines. Longitudinal mediation models were applied to investigate to what extent these beliefs could explain a change in reported symptoms after the new line was put into operation. RESULTS: Significant (p<.01) indirect effects were found for proximity on the increase in reported cognitive (R(2)=0.41) and somatic (R(2)=0.79) symptoms after the power line was put into operation through an increase in the belief that power lines causes health effects. The direct effects of proximity on an increase in reported symptoms were not significant. CONCLUSIONS: Our findings suggest that increases in reported health complaints after a new HVPL has been put into operation can be explained by nocebo mechanisms. Future field studies are needed to know whether our findings extend to other environmental health issues in a community.

Somatic symptom reports in the general population: Application of a bi-factor model to the analysis of change.

OBJECTIVE: To investigate the latent structure of somatic symptom reports in the general population with a bi-factor model and apply the structure to the analysis of change in reported symptoms after the emergence of an uncertain environmental health risk. METHODS: Somatic symptoms were assessed in two general population environmental health cohorts (AMIGO, n=14,829 & POWER, n=951) using the somatization scale of the four-dimensional symptom questionnaire (4DSQ-S). Exploratory bi-factor analysis was used to determine the factor structure in the AMIGO cohort. Multi-group and longitudinal models were applied to assess measurement invariance. For a subsample of residents living close to a newly introduced power line (n=224), we compared a uni- and multidimensional method for the analysis of change in reported symptoms after the power line was put into operation. RESULTS: We found a good fit (RMSEA=0.03, CFI=0.98) for a bi-factor model with one general and three symptom specific factors (musculoskeletal, gastrointestinal, cardiopulmonary). The latent structure was found to be invariant between cohorts and over time. A significant increase (p<.05) was found only for musculoskeletal and gastrointestinal symptoms after the power line was put into operation. CONCLUSIONS: In our study we found that a bi-factor structure of somatic symptoms reports was equivalent between cohorts and over time. Our findings suggest that taking this structure into account can lead to a more informative interpretation of a change in symptom reports compared to a unidimensional approach.

Validity of at home model predictions as a proxy for personal exposure to radiofrequency electromagnetic fields from mobile phone base stations.

BACKGROUND: Epidemiological studies on the potential health effects of RF-EMF from mobile phone base stations require efficient and accurate exposure assessment methods. Previous studies have demonstrated that the 3D geospatial model NISMap is able to rank locations by indoor and outdoor RF-EMF exposure levels. This study extends on previous work by evaluating the suitability of using NISMap to estimate indoor RF-EMF exposure levels at home as a proxy for personal exposure to RF-EMF from mobile phone base stations. METHODS: For 93 individuals in the Netherlands we measured personal exposure to RF-EMF from mobile phone base stations during a 24h period using an EME-SPY 121 exposimeter. Each individual kept a diary from which we extracted the time spent at home and in the bedroom. We used NISMap to model exposure at the home address of the participant (at bedroom height). We then compared model predictions with measurements for the 24h period, when at home, and in the bedroom by the Spearman correlation coefficient (rsp) and by calculating specificity and sensitivity using the 90th percentile of the exposure distribution as a cutpoint for high exposure. RESULTS: We found a low to moderate rsp of 0.36 for the 24h period, 0.51 for measurements at home, and 0.41 for measurements in the bedroom. The specificity was high (0.9) but with a low sensitivity (0.3). DISCUSSION: These results indicate that a meaningful ranking of personal RF-EMF can be achieved, even though the correlation between model predictions and 24h personal RF-EMF measurements is lower than with at home measurements. However, the use of at home RF-EMF field predictions from mobile phone base stations in epidemiological studies leads to significant exposure misclassification that will result in a loss of statistical power to detect health effects.

Symptom reporting after the introduction of a new high-voltage power line: a prospective field study.

BACKGROUND: There is public concern about the potential health effects of exposure to extremely low frequency electromagnetic fields (ELF-EMF) of high-voltage power lines (HVPLs). Some residents living near HVPLs believe ELF-EMF might cause non-specific health complaints. OBJECTIVES: The present study is the first to prospectively investigate whether self-reported health complaints and causal beliefs increase after the construction of a new power line. METHODS: We used a quasi-experimental design with two pretests before and two posttests after a new HVPL was put into operation. Residents living near (0-300m, n=229; 300-500m, n=489) and farther away (500-2000m, n=536) participated in the study. Linear mixed models were fitted to test whether symptom reports and beliefs that power lines caused health complaints increased more in residents living close to the new line compared to residents living farther away. RESULTS: A significantly (p<.05) larger increase from baseline in symptom reports and causal beliefs was found in residents living within 300m from the new power line when compared to residents living farther away. While symptom reports did not differ at baseline, the belief that a power line could cause these symptoms was at baseline already stronger for residents living close compared to residents living farther away. CONCLUSIONS: We found a negative impact of a new HVPL on health perceptions of nearby residents, even before the line was put into operation.

Evaluation of an mHealth intervention aiming to improve health-related behavior and sleep and reduce fatigue among airline pilots.

OBJECTIVES: The aim of this study was to evaluate the effects of an mHealth intervention (intervention using mobile technology) consisting of tailored advice regarding exposure to daylight, sleep, physical activity, and nutrition, and aiming to improve health-related behavior, thereby reducing sleep problems and fatigue and improving health perception of airline pilots. METHODS: A randomized controlled trial was conducted among 502 airline pilots. The intervention group was given access to both the MORE Energy mobile application (app) with tailored advice and a website with background information. The control group was directed to a website with standard information about fatigue. Health-related behavior, fatigue, sleep, and health perception outcomes were measured through online questionnaires at baseline and at three and six months after baseline. The effectiveness of the intervention was determined using linear and Poisson mixed model analyses. RESULTS: After six months, compared to the control group, the intervention group showed a significant improvement on fatigue (ß= -3.76, P<0.001), sleep quality (ß= -0.59, P=0.007), strenuous physical activity (ß=0.17, P=0.028), and snacking behavior (ß= -0.81, P<0.001). No significant effects were found for other outcome measures. CONCLUSIONS: The MORE Energy mHealth intervention reduced self-reported fatigue compared to a minimal intervention. Some aspects of health-related behavior (physical activity and snacking behavior) and sleep (sleep quality) improved as well, but most did not. The results show offering tailored advice through an mHealth intervention is an effective means to support employees who have to cope with irregular flight schedules and circadian disruption. This kind of intervention might therefore also be beneficial for other working populations with irregular working hours.

Health responses to a new high-voltage power line route: design of a quasi-experimental prospective field study in the Netherlands.

BACKGROUND: New high-voltage power transmission lines will be introduced due to increasing demand for reliable and renewable energy supplies. Some residents associate non-specific health complaints with exposure to electromagnetic fields from nearby power lines. This study protocol describes the design and rationale of a prospective study investigating whether the introduction of a new power line triggers health responses in residents living nearby. METHODS/DESIGN: The study is designed as a quasi-experimental field study with two pretests during the construction of a new power line route, and two posttests after it has been put into operation. Key outcomes are self-reported non-specific somatic and cognitive health complaints, and attribution of these health complaints to a power line. The main determinant is proximity to the new power line route. One member of every household (n=2379) residing in close proximity (0-500 meters) to the overhead parts of a new power line route in the Netherlands is invited to participate, as well as a sample of household members (n=2382) residing farther away (500-2000 meters). Multilevel analysis will be employed to test whether an increase in key outcome measures is related to proximity to the line. Longitudinal structural equation models will be applied to test to what extent health responses are mediated by psychosocial health mechanisms and moderated by negative oriented personality traits. DISCUSSION: This is the first study to investigate health responses to a new power line route in a prospective manner. The results will provide theoretical insight into psychosocial mechanisms operating during the introduction of an environmental health risk, and may offer suggestions to policymakers and other stakeholders for minimizing adverse health responses when introducing new high-voltage power lines.

Symptom attribution and risk perception in individuals with idiopathic environmental intolerance to electromagnetic fields and in the general population.

AIM: To investigate differences in health perception and electromagnetic fields (EMF) between people within the general population reporting sensitivity or non-sensitivity to EMF, and people who registered themselves as sensitive to EMF at a non-governmental organisation (NGO). METHODS: Correlations and regression analysis to compare a sample of the general population recruited via internet panel to individuals with idiopathic environmental intolerance to EMF (IEI-EMF) recruited via an interest group. RESULTS: The general population sensitive group was more similar to the non-sensitive group in personal characteristics than to the NGO sensitive group. They experienced more - and more frequent - non-specific symptoms, reported higher perceived risk of EMF, and attributed their symptoms more to EMF than the non-sensitive group, but less than the NGO sensitive group. There was a positive association between attribution of symptoms to EMF and reported intensity of non-specific symptoms, which was stronger for the NGO sensitive subjects than for the general population. CONCLUSIONS: People sensitive to EMF and recruited via an internet panel differ from people sensitive to EMF and recruited via an NGO, who reported a higher frequency of non-specific symptoms. Attribution of symptoms to EMF is one of the predictors of the intensity of physical symptoms. Changing the perceived association between EMF and health problems in individuals with IEI-EMF might contribute to a better health experience.

Development and evaluation of an intervention aiming to reduce fatigue in airline pilots: design of a randomised controlled trial.

BACKGROUND: A considerable percentage of flight crew reports to be fatigued regularly. This is partly caused by irregular and long working hours and the crossing of time zones. It has been shown that persistent fatigue can lead to health problems, impaired performance during work, and a decreased work-private life balance. It is hypothesized that an intervention consisting of tailored advice regarding exposure to daylight, optimising sleep, physical activity, and nutrition will lead to a reduction of fatigue in airline pilots compared to a control group, which receives a minimal intervention with standard available information. METHODS/DESIGN: The study population will consist of pilots of a large airline company. All pilots who posses a smartphone or tablet, and who are not on sick leave for more than four weeks at the moment of recruitment, will be eligible for participation.In a two-armed randomised controlled trial, participants will be allocated to an intervention group that will receive the tailored advice to optimise exposure to daylight, sleep, physical activity and nutrition, and a control group that will receive standard available information. The intervention will be applied using a smartphone application and a website, and will be tailored on flight- and participant-specific characteristics. The primary outcome of the study is perceived fatigue. Secondary outcomes are need for recovery, duration and quality of sleep, dietary and physical activity behaviours, work-private life balance, general health, and sickness absence. A process evaluation will be conducted as well. Outcomes will be measured at baseline and at three and six months after baseline. DISCUSSION: This paper describes the development of an intervention for airline pilots, consisting of tailored advice (on exposure to daylight and sleep-, physical activity, and nutrition) applied into a smartphone application. Further, the paper describes the design of the randomised controlled trial evaluating the effect of the intervention on fatigue, health and sickness absence. If proven effective, the intervention can be applied as a new and practical tool in fatigue management. Results are expected at the end of 2013. TRIAL REGISTRATION: Netherlands Trial Register: NTR2722.

Flight schedules and occupational accidents among cabin crew: a longitudinal study.

BACKGROUND: Flight schedules of cabin crew involve early starts, long working hours, night flights, and the crossing of time zones, all of which might contribute to the risk of onboard occupational accidents. Because it is unclear if cumulative flight schedule exposure affects the incidence of occupational accidents, the objective of this study is to examine this association among cabin crewmembers. METHODS: Data from the 5-yr historic MORE cohort was used. The study population consisted of 6311 cabin crewmembers. For each employee, all flight schedules from 2005 to 2008 and registered occupational accidents in 2009 were collected. The association between the cumulative exposure to different types of flights and the occurrence of occupational accidents was determined using logistic regression analyses. RESULTS: In 2009, 289 cabin crewmembers reported at least 1 occupational accident. The adjusted logistic regression models showed that the number of short-haul flights during the period 2005-2008 was positively associated with the occurrence of occupational accidents in 2009. Less exposure to long-haul flights was also associated with reporting an occupational accident. DISCUSSION: The results of this study suggest that cumulative exposure to short-haul flights is associated with an increased risk for occupational accidents among cabin crewmembers. This increased risk may be caused by the specific characteristics of short-haul flights. Future research should focus on possible underlying mechanisms, such as fatigue accumulation, and on the influence of adjustments to short-haul schedules. Airline companies can increase their focus on the short-haul operation in order to reduce onboard accidents.

Perception of health risks of electromagnetic fields by MRI radiographers and airport security officers compared to the general Dutch working population: a cross sectional analysis.

BACKGROUND: The amount of exposure to electromagnetic fields (EMF) at work is mainly determined by an individual's occupation and may differ from exposure at home. It is, however, unknown how different occupational groups perceive possible adverse health effects of EMF. METHODS: Three occupational groups, the general Dutch working population (n = 567), airport security officers who work with metal detectors (n = 106), and MRI radiographers who work with MRI (n = 193), were compared on perceived risk of and positive and negative feelings towards EMF in general and of different EMF sources, and health concerns by using analyses of variances. Data were collected via an internet survey. RESULTS: Overall, MRI radiographers had a lower perceived risk, felt less negative, and more positive towards EMF and different sources of EMF than the general working population and the security officers. For security officers, feeling more positive about EMF was not significantly related to perceived risk of EMF in general or EMF of domestic sources. Feeling positive about a source did not generalize to a lower perceived risk, while negative feelings were stronger related to perceived risk. MRI radiographers had fewer health concerns regarding EMF than the other two groups, although they considered it more likely that EMF could cause physical complaints. CONCLUSIONS: These data show that although differences in occupation appear to be reflected in different perceptions of EMF, the level of occupational exposure to EMF as such does not predict the perceived health risk of EMF.

Effectiveness of phone and e-mail lifestyle counseling for long term weight control among overweight employees.

OBJECTIVES: To determine the effectiveness of a weight-management program with personal counseling by phone or e-mail. METHODS: A randomized controlled trial of a 6-month program comparing two modes of intervention delivery (phone, n = 462; Internet, n = 464) with self-directed materials (control, n = 460), among overweight employees. Change in body weight after 2 years was the main outcome. RESULTS: Among complete cases, weight loss in the Internet group was 1.2 kg (95% confidence interval [CI], -1.9 to -0.4) and in the phone group 0.8 kg (95% CI, -1.5 to 0.03), compared with the control group. Multiple imputation of missing body weight resulted in comparative weight losses of -0.9 kg (95% CI, -2.0 to 0.3) and -0.4 kg (95% CI, -1.4 to 0.7). CONCLUSIONS: Among complete cases, the Internet intervention showed modest long-term weight loss, but among all participants neither program version was more effective than self-help.