Political stringency, infection rates, and higher education students' adherence to government measures in the Nordic countries and the UK during the first wave of the COVID-19 outbreak.

Understanding predictors of adherence to governmental measures to prevent the spread of the COVID-19 is fundamental to guide health communication. This study examined whether political stringency and infection rates during the first wave of the pandemic were associated with higher education students' adherence to COVID-19 government measures in the Nordic countries (Denmark, Finland, Norway, Iceland, and Sweden) and the United Kingdom. Both individual- and country-level data were used in present study. An international cross-sectional subsample (n = 10,345) of higher-education students was conducted in May-June 2020 to collect individual-level information on socio-demographics, study information, living arrangements, health behaviors, stress, and COVID-19-related concerns, including adherence to government measures. Country-level data on political stringency from the Oxford COVID-19 Government Response Tracker and national infection rates were added to individual-level data. Multiple linear regression analyses stratified by country were conducted. Around 66% of students reported adhering to government measures, with the highest adherence in the UK (73%) followed by Iceland (72%), Denmark (69%), Norway (67%), Finland (64%) and Sweden (49%). Main predictors for higher adherence were older age, being female and being worried about getting infected with COVID-19 (individual-level), an increase in number of days since lockdown, political stringency, and information about COVID-19 mortality rates (country-level). However, incidence rate was an inconsistent predictor, which may be explained by imperfect data quality during the onset of the pandemic. We conclude that shorter lockdown periods and political stringency are associated with adherence to government measures among higher education students at the outset of the COVID-19 pandemic.

Fever and infections during pregnancy and psychosis-like experiences in the offspring at age 11. A prospective study within the Danish National Birth Cohort.

BACKGROUND: Maternal exposures to fever and infections in pregnancy have been linked to subsequent psychiatric morbidity in the child. This study examined whether fever and common infections in pregnancy were associated with psychosis-like experiences (PLEs) in the child. METHODS: A longitudinal study of 46 184 children who participated in the 11-year follow-up of the Danish National Birth Cohort was conducted. Pregnant women were enrolled between 1996 and 2002 and information on fever, genitourinary infections, respiratory tract infection, and influenza-like illness during pregnancy was prospectively collected in two interviews during pregnancy. PLEs were assessed using the seven-item Adolescent Psychotic-Like Symptom Screener in a web-based questionnaire completed by the children themselves at age 11. RESULTS: PLEs were reported among 11% of the children. Multinomial logistic regression models with probability weights to adjust for potential selection bias due to attrition suggested that maternal fever, genitourinary infections and influenza-like illness were associated with a weak to moderate increased risk of subclinical psychosis-like symptoms in the offspring, whereas respiratory tract infections were not. No clear pattern was observed between the strengths of the associations and the timing of exposure, or the type of psychosis-like symptom. CONCLUSIONS: In this study, maternal exposures to fevers and common infections in pregnancy were generally associated with a subtle excess risk of PLEs in the child. A more pronounced association was found for influenza-like illness under an a priori definition, leaving open the possibility that certain kinds of infections may constitute important risk factors.

[Data protection in rehabilitation research]. / Datenschutz in der Rehabilitationsforschung.

Data protection is regulated by legislation and has to be adhered to by scientists, too. This overview shows where aspects of data protection have to be considered in rehabilitation research. Important legal sources are the code of social law X, the German Federal Data Protection Act and the data protection acts of the German states. Specific recommendations about patient information sheet and written informed consent are given for research based on interviews with study participants. Furthermore, operations such as collecting, processing, using, storing, publishing and archiving of personal data are explained, taking into account the requirements of data protection. A practical example (URL: www.thieme-connect.de/ejournals/toc/rehabilitation) shows how to separate personal data and research data using the services of an external data custodian.

Residential characteristics and radiofrequency electromagnetic field exposures from bedroom measurements in Germany.

The objectives of this study were to assess total exposure to radiofrequency electromagnetic fields (RF-EMF) in bedrooms and the contribution of different radioservices (FM radio, analogue TV and DVB-T, TETRA, GSM900 downlink, GSM1800 downlink, UMTS downlink, DECT, and wireless LAN and blue tooth) to the total exposure. Additional aims were to describe the proportion of measuring values above the detection limit of the dosimeters and to characterize the differences in exposure patterns associated with self-reported residential characteristics. Exposure to RF sources in bedrooms was measured using Antennessa(®) EME Spy 120 dosimeters in 1,348 households in Germany; 280 measures were available for each frequency band per household. Mean electrical field strengths and power flux densities were calculated. Power flux densities allow the calculation of proportions of different radioservices on total exposure. Exposure was often below the detection limit (electrical field strength: 0.05 V/m) of the dosimeter. Total exposure varied, depending on residential characteristics (urban vs. rural areas and floor of a building the measurement took place). Major sources of exposure were cordless phones (DECT standard) and wireless LAN/blue tooth contributing about 82% of total exposure (20.5 µW/m(2)). Exposure to RF-EMF is ubiquitous, but exposure levels are-if at all measurable-very low and far below the ICNIRP's exposure reference levels.

Quality control for exposure assessment in epidemiological studies.

In the framework of an epidemiological study, dosemeters were used for the assessment of radio frequency electromagnetic field exposure. To check the correct dosemeter's performance in terms of consistency of recorded field values over the entire study period, a quality control strategy was developed. In this paper, the concept of quality control and its results is described. From the 20 dosemeters used, 19 were very stable and reproducible, with deviations of a maximum of +/-1 dB compared with their initial state. One device was found to be faulty and its measurement data had to be excluded from the analysis. As a result of continuous quality control procedures, the confidence in the measurements obtained during the field work was strengthened significantly.

Occupation and risk of glioma, meningioma and acoustic neuroma: results from a German case-control study (interphone study group, Germany).

BACKGROUND: Several epidemiological studies have investigated the association between occupation and brain tumour risk, but results have been inconclusive. We investigated the association between six occupational categories defined a priori: chemical, metal, agricultural, construction, electrical/electronic and transport, and the risk of glioma, meningioma and acoustic neuroma. METHODS: In a population-based case-control study involving a total of 844 cases and 1688 controls conducted from 2000 to 2003, detailed information on life-long job histories was collected during personal interviews and used to create job calendars for each participant. Job title, job activity, job number, and the starting and ending dates of the activity were recorded for all activities with duration of at least 1 year. Reported occupational activities were coded according to the International Standard Classification of Occupations 1988 (ISCO 88). For the analyses we focused on six a priori defined occupational sectors, namely chemical, metal, agricultural, construction, electrical/electronic and transport. Multiple conditional logistic regression analysis was used to estimate odds ratios and their 95% confidence intervals. RESULTS: Most of the observed odds ratios were close to 1.0 for ever having worked in the six occupational sectors and risk of glioma, meningioma and acoustic neuroma. Sub-group analyses according to duration of employment resulted in two elevated odds ratios with confidence intervals excluding unity. CONCLUSIONS: We did not observe an increased risk of glioma or meningioma for occupations in the agricultural, construction, transport, chemical, electrical/electronic and metal sectors. The number of 'significant' odds ratios is consistent with an overall 'null-effect'.

Determinants of mobile phone output power in a multinational study: implications for exposure assessment.

OBJECTIVES: The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure for epidemiological studies, we assessed determinants of mobile phone output power in a multinational study. METHODS: More than 500 volunteers in 12 countries used Global System for Mobile communications software-modified phones (GSM SMPs) for approximately 1 month each. The SMPs recorded date, time, and duration of each call, and the frequency band and output power at fixed sampling intervals throughout each call. Questionnaires provided information on the typical circumstances of an individual's phone use. Linear regression models were used to analyse the influence of possible explanatory variables on the average output power and the percentage call time at maximum power for each call. RESULTS: Measurements of over 60,000 phone calls showed that the average output power was approximately 50% of the maximum, and that output power varied by a factor of up to 2 to 3 between study centres and network operators. Maximum power was used during a considerable proportion of call time (39% on average). Output power decreased with increasing call duration, but showed little variation in relation to reported frequency of use while in a moving vehicle or inside buildings. Higher output powers for rural compared with urban use of the SMP were observed principally in Sweden where the study covered very sparsely populated areas. CONCLUSIONS: Average power levels are substantially higher than the minimum levels theoretically achievable in GSM networks. Exposure indices could be improved by accounting for average power levels of different telecommunications systems. There appears to be little value in gathering information on circumstances of phone use other than use in very sparsely populated regions.

Mobile phone base stations and adverse health effects: phase 2 of a cross-sectional study with measured radio frequency electromagnetic fields.

OBJECTIVE: The aim of the cross-sectional study was to test the hypothesis that exposure to continuous low-level radio frequency electromagnetic fields (RF-EMFs) emitted from mobile phone base stations was related to various health disturbances. METHODS: For the investigation people living mainly in urban regions were selected from a nationwide study in 2006. In total, 3526 persons responded to a questionnaire (response rate 85%). For the exposure assessment a dosimeter measuring different RF-EMF frequencies was used. Participants answered a postal questionnaire on how mobile phone base stations affected their health and they gave information on sleep disturbances, headaches, health complaints and mental and physical health using standardised health questionnaires. Information on stress was also collected. Multiple linear regression models were used with health outcomes as dependent variables (n = 1326). RESULTS: For the five health scores used, no differences in their medians were observed for exposed versus non-exposed participants. People who attributed adverse health effects to mobile phone base stations reported significantly more sleep disturbances and health complaints, but they did not report more headaches or less mental and physical health. Individuals concerned about mobile phone base stations did not have different well-being scores compared with those who were not concerned. CONCLUSIONS: In this large population-based study, measured RF-EMFs emitted from mobile phone base stations were not associated with adverse health effects.

Mobile phone base stations and adverse health effects: phase 1 of a population-based, cross-sectional study in Germany.

OBJECTIVE: The aim of this first phase of a cross-sectional study from Germany was to investigate whether proximity of residence to mobile phone base stations as well as risk perception is associated with health complaints. METHODS: The researchers conducted a population-based, multi-phase, cross-sectional study within the context of a large panel survey regularly carried out by a private research institute in Germany. In the initial phase, reported on in this paper, 30,047 persons from a total of 51,444 who took part in the nationwide survey also answered questions on how mobile phone base stations affected their health. A list of 38 health complaints was used. A multiple linear regression model was used to identify predictors of health complaints including proximity of residence to mobile phone base stations and risk perception. RESULTS: Of the 30,047 participants (response rate 58.6%), 18.7% of participants were concerned about adverse health effects of mobile phone base stations, while an additional 10.3% attributed their personal adverse health effects to the exposure from them. Participants who were concerned about or attributed adverse health effects to mobile phone base stations and those living in the vicinity of a mobile phone base station (500 m) reported slightly more health complaints than others. CONCLUSIONS: A substantial proportion of the German population is concerned about adverse health effects caused by exposure from mobile phone base stations. The observed slightly higher prevalence of health complaints near base stations can not however be fully explained by attributions or concerns.

Applicability of an exposure model for the determination of emissions from mobile phone base stations.

Applicability of a model to estimate radiofrequency electromagnetic field (RF-EMF) strength in households from mobile phone base stations was evaluated with technical data of mobile phone base stations available from the German Net Agency, and dosimetric measurements, performed in an epidemiological study. Estimated exposure and exposure measured with dosemeters in 1322 participating households were compared. For that purpose, the upper 10th percentiles of both outcomes were defined as the 'higher exposed' groups. To assess the agreement of the defined 'higher' exposed groups, kappa coefficient, sensitivity and specificity were calculated. The present results show only a weak agreement of calculations and measurements (kappa values between -0.03 and 0.28, sensitivity between 7.1 and 34.6). Only in some of the sub-analyses, a higher agreement was found, e.g. when measured instead of interpolated geo-coordinates were used to calculate the distance between households and base stations, which is one important parameter in modelling exposure. During the development of the exposure model, more precise input data were available for its internal validation, which yielded kappa values between 0.41 and 0.68 and sensitivity between 55 and 76 for different types of housing areas. Contrary to this, the calculation of exposure-on the basis of the available imprecise data from the epidemiological study-is associated with a relatively high degree of uncertainty. Thus, the model can only be applied in epidemiological studies, when the uncertainty of the input data is considerably reduced. Otherwise, the use of dosemeters to determine the exposure from RF-EMF in epidemiological studies is recommended.