Otitis media (OM) is a very common disease in children, which results in a significant economic burden to the healthcare system for hospital-based outpatient departments, emergency departments (EDs), unscheduled medical examinations, and antibiotic prescriptions. The aim of this retrospective observational study is to investigate the association between climate variables, air pollutants, and OM visits observed in the 2007-2010 period at the ED of Cuneo, Italy. Measures of meteorological parameters (temperature, humidity, atmospheric pressure, wind) and outdoor air pollutants (particulate matter, ozone, nitrous dioxide) were analyzed at two statistical stages and in several specific steps (crude and adjusted models) according to Poisson's regression. Response variables included daily examinations for age groups 0-3, 0-6, and 0-18. Control variables included upper respiratory infections (URI), flu (FLU), and several calendar factors. A statistical procedure was implemented to capture any delayed effects. Results show a moderate association for temperature (T), age 0-3, and 0-6 with P < 0.05, as well as nitrous dioxide (NO) with P < 0.005 at age 0-18. Results of subsequent models point out to URI as an important control variable. No statistical association was observed for other pollutants and meteorological variables. The dose-response models (DLNM-final stage) implemented separately on a daily and hourly basis point out to an association between temperature (daily model) and RR 1.44 at age 0-3, CI 1.11-1.88 (lag time 0-1 days) and RR 1.43, CI 1.05-1.94 (lag time 0-3 days). The hourly model confirms a specific dose-response effect for T with RR 1.20, CI 1.04-1.38 (lag time range from 0 to 11 to 0-15 h) and for NO with RR 1.03, CI 1.01-1.05 (lag time range from 0 to 8 to 0-15 h). These results support the hypothesis that the clinical context of URI may be an important risk factor in the onset of OM diagnosed at ED level. The study highlights the relevance of URI as a control variable to be included in the statistical analysis in association with meteorological factors and air pollutants. The study also points out to a moderate association of OM with low temperatures and NO, with specific risk factors for this variable early in life. Further studies are needed to confirm these findings, particularly with respect to air pollutants in larger urban environments.

No abstract

Shift work can lead to circadian desynchronization due to temporary misalignment between working hours and physiological and behavioral functioning, resulting in compromised health, insomnia, worsening of sleep quality, reduced ability to work during waking hours, and increased cardiovascular risk. We evaluated the effects of shift work on the rest-activity circadian rhythm (RAR) and health status of Italian orthopaedic nurses. The study population was 59 nurses: 44 worked the night shift and 15 worked the day shift. All carried out continuous 5-day actigraphic monitoring to assess RAR, including both the working and the rest period. The rhythmometric analysis showed that, during the working period, the night shift nurses had a significantly lower amplitude than the day shift nurses (p < 0.001), and the acrophase was significantly different between the two groups (p < 0.01). When we stratified the two groups by median body mass index (<25 kg/m2 normal weight and ≥25 kg/m2 overweight), during the working period, we noted a significantly lower amplitude for both the normal weight and the overweight nurses who worked the night shift (p < 0.01 and p < 0.001, normal weight and overweight respectively). The current findings suggest the need for further study of the relationship between activity levels and shift work.

The incidence of nephrolithiasis is rising worldwide, especially in women and with increasing age. Incidence and prevalence of kidney stones are affected by genetic, nutritional, and environmental factors. The aim of this study is to investigate the link between various meteorological factors (independent variables) and the daily number of visits to the Emergency Department (ED of the S. Croce and Carle Hospital of Cuneo for renal colic (RC) and urinary stones (UC) as the dependent variable over the years 2007-2010.The Poisson generalized regression models (PGAMs) have been used in different progressive ways. The results of PGAMs (stage 1) adjusted for seasonal and calendar factors confirmed a significant correlation (p < 0.03) with the thermal parameter. Evaluation of the dose-response effect [PGAMs combined with distributed lags nonlinear models (DLNMs)-stage 2], expressed in terms of relative risk (RR) and cumulative relative risk (RRC), indicated a relative significant effect up to 15 lag days of lag (RR > 1), with a first peak after 5 days (lag ranges 0-1, 0-3, and 0-5) and a second weak peak observed along the 5-15 lag range days. The estimated RR for females was significant, mainly in the second and fourth age group considered (19-44 and >65 years): RR for total ED visits 1.27, confidence interval (CI) 1.11-1.46 (lag 0-5 days); RR 1.42, CI 1.01-2.01 (lag 0-10 days); and RR 1.35, CI 1.09-1.68 (lag 0-15 days). The research also indicated a moderate involvement of the thermal factor in the onset of RC caused by UC, exclusively in the female sex. Further studies will be necessary to confirm these results.

Citizen science has shown great potential for bringing large groups of people closer to science, thanks in part to cooperation with universities and research centers. In this context, amateur weather networks played a major role in the last few decades thanks to a constant growth in technology. An example is given by the Meteonetwork association, born in 2002, and mainly composed by atmospheric science enthusiasts, who built up in time a huge weather station network in Italy. In recent years, they have enlarged their horizons over Europe, displaying real time observations and daily maps coming from both personal weather stations and official networks. This study described how Meteonetwork has set up an open crowdsourced weather data system, how data are validated, and which products are generated and freely accessible for scientists and stakeholders for their own purposes. Two concrete use cases were described as examples: the Weatherness Project, which selects a subnet of Meteonetwork data for biometeorological and health purposes and the data assimilation process implemented to improve the initial conditions into the WRF meteorological model for daily weather forecasts.