Organ donation in Switzerland - an analysis of factors associated with consent rate

BACKGROUND AND AIM Switzerland has a low post mortem organ donation rate. Here we examine variables that are associated with the consent of the deceased's next of kin (NOK) for organ donation, which is a prerequisite for donation in Switzerland. METHODS AND ANALYSIS During one year, we registered information from NOK of all deceased patients in Swiss intensive care units, who were approached for consent to organ donation. We collected data on patient demographics, characteristics of NOK, factors related to the request process and to the clinical setting. We analyzed the association of collected predictors with consent rate using univariable logistic regression models; predictors with p-values <0.2 were selected for a multivariable logistic regression. RESULTS Of 266 NOK approached for consent, consent was given in 137 (51.5%) cases. In multivariable analysis, we found associations of consent rates with Swiss nationality (OR 3.09, 95% CI: 1.46-6.54) and German language area (OR 0.31, 95% CI: 0.14-0.73). Consent rates tended to be higher if a parent was present during the request (OR 1.76, 95% CI: 0.93-3.33) and if the request was done before brain death was formally declared (OR 1.87, 95% CI: 0.90-3.87). CONCLUSION Establishing an atmosphere of trust between the medical staff putting forward a request and the NOK, allowing sufficient time for the NOK to consider donation, and respecting personal values and cultural differences, could be of importance for increasing donation rates. Additional measures are needed to address the pronounced differences in consent rates between language regions.

Statistical analysis of personal radiofrequency electromagnetic field measurements with nondetects

Exposimeters are increasingly applied in bioelectromagnetic research to determine personal radiofrequency electromagnetic field (RF-EMF) exposure. The main advantages of exposimeter measurements are their convenient handling for study participants and the large amount of personal exposure data, which can be obtained for several RF-EMF sources. However, the large proportion of measurements below the detection limit is a challenge for data analysis. With the robust ROS (regression on order statistics) method, summary statistics can be calculated by fitting an assumed distribution to the observed data. We used a preliminary sample of 109 weekly exposimeter measurements from the QUALIFEX study to compare summary statistics computed by robust ROS with a naïve approach, where values below the detection limit were replaced by the value of the detection limit. For the total RF-EMF exposure, differences between the naïve approach and the robust ROS were moderate for the 90th percentile and the arithmetic mean. However, exposure contributions from minor RF-EMF sources were considerably overestimated with the naïve approach. This results in an underestimation of the exposure range in the population, which may bias the evaluation of potential exposure-response associations. We conclude from our analyses that summary statistics of exposimeter data calculated by robust ROS are more reliable and more informative than estimates based on a naïve approach. Nevertheless, estimates of source-specific medians or even lower percentiles depend on the assumed data distribution and should be considered with caution.

Temporal and spatial variability of personal exposure to radio frequency electromagnetic fields

BACKGROUND: Little is known about the population's exposure to radio frequency electromagnetic fields (RF-EMF) in industrialized countries. OBJECTIVES: To examine levels of exposure and the importance of different RF-EMF sources and settings in a sample of volunteers living in a Swiss city. METHODS: RF-EMF exposure of 166 volunteers from Basel, Switzerland, was measured with personal exposure meters (exposimeters). Participants carried an exposimeter for 1 week (two separate weeks in 32 participants) and completed an activity diary. Mean values were calculated using the robust regression on order statistics (ROS) method. RESULTS: Mean weekly exposure to all RF-EMF sources was 0.13 mW/m(2) (0.22 V/m) (range of individual means 0.014-0.881 mW/m(2)). Exposure was mainly due to mobile phone base stations (32.0%), mobile phone handsets (29.1%) and digital enhanced cordless telecommunications (DECT) phones (22.7%). Persons owning a DECT phone (total mean 0.15 mW/m(2)) or mobile phone (0.14 mW/m(2)) were exposed more than those not owning a DECT or mobile phone (0.10 mW/m(2)). Mean values were highest in trains (1.16 mW/m(2)), airports (0.74 mW/m(2)) and tramways or buses (0.36 mW/m(2)), and higher during daytime (0.16 mW/m(2)) than nighttime (0.08 mW/m(2)). The Spearman correlation coefficient between mean exposure in the first and second week was 0.61. CONCLUSIONS: Exposure to RF-EMF varied considerably between persons and locations but was fairly consistent within persons. Mobile phone handsets, mobile phone base stations and cordless phones were important sources of exposure in urban Switzerland.