A latent class approach:characterizing the willingness to share personal health information in Finland

Abstract. BACKGROUND: With the fast advances in technology, the aging populations, and the climate change, the amount of data in our hands has become enormous, and the ways of handling it has become better. There has been large amount of privacy concerns as well due to the fast-growing data that are spread everywhere. This study focuses on health data to find out whether personal characteristics can be associated with the willingness to consent it for secondary purposes. METHODS: A sample data (n=2338) concerning the Finnish populations attitudes towards secondary uses of health data was acquired and analyzed. The questionnaire included 14 questions regarding the willingness to consent data for different purposes. The dimensionality of this issue was reduced with a latent class analysis, and the information was condensed into one latent variable with 5 classes. After that a latent class regression was performed to find out whether the willingness could be explained with the help of other background information. RESULTS: A statistically significant association between the willingness to consent health data and the following characteristics; Gender, Age, Education, Perception of health, Number of visits to health or social care, and Financial situation. Political orientation had a high value of estimate, but no significance. CONCLUSIONS: Secondary uses of health data can achieve improvements in public health and welfare and health equality. Therefore, it is important that we make sure that the privacy concerns of using and sharing health data are taken care of. Methods for increasing the citizens willingness to consent their health data could be done through education and by building mutual trust between the health care system and the patients

Ambient particulate air pollution and daily stock market returns and volatility in 47 cities worldwide

Abstract We studied globally representative data to quantify how daily fine particulate matter (PM2.5) concentrations influence both daily stock market returns and volatility. Time-series analysis was applied on 47 city-level environmental and economic datasets and meta-analysis of the city-specific estimates was used to generate a global summary effect estimate. We found that, on average, a 10 μg/m³ increase in PM2.5 reduces same day returns by 1.2% (regression coefficient: − 0.012, 95% confidence interval: − 0.021, − 0.003) Based on a meta-regression, these associations are stronger in areas where the average PM2.5 concentrations are lower, the mean returns are higher, and where the local stock market capitalization is low. Our results suggest that a 10 μg/m³ increase in PM2.5 exposure increases stock market volatility by 0.2% (regression coefficient 0.002, 95% CI 0.000, 0.004), but the city-specific estimates were heterogeneous. Meta-regression analysis did not explain much of the between-city heterogeneity. Our results provide global evidence that short-term exposure to air pollution both reduces daily stock market returns and increases volatility

Regular exercise improves asthma control in adults:a randomized controlled trial

Abstract We conducted a randomized controlled trial to test the hypothesis that a 24-week exercise intervention improves asthma control in adults. Adults with mild or moderate asthma were randomly assigned to either the exercise intervention group (IG) or the reference group (RG). Participants in IG received an individualized exercising program, including aerobic exercise at least three times a week for ≥30 minutes, muscle training, and stretching. The primary outcome was asthma control, measured by Asthma Control Test (ACT), asthma-related symptoms, and peak expiratory flow (PEF) variability. We estimated the risk (i.e. probability) of improvement in asthma control and the risk difference (RD) between IG and RG. Of 131 subjects (67 IG/64 RG) entered, 105 subjects (51/54) completed the trial (80%), and 89 (44/45) were analysed (68%). The ACT became better among 26 (62%) participants in IG and among 17 (39%) participants in RG. The effect of intervention on improving asthma control was 23% (RD = 0.23, 95% CI 0.027–0.438; P = 0.0320). The intervention also reduced shortness of breath by 30.1% (RD = 0.301, 95% CI 0.109–0.492; P = 0.003). The change in PEF variability was similar in both groups. Regular exercise improves asthma control measured by the ACT, while has little effect on PEF variability

Airborne pollen concentrations and daily mortality from respiratory and cardiovascular causes

Abstract We conducted a time-series analysis of the relations between daily levels of allergenic pollen and mortality in the Helsinki Metropolitan Area with 153 378 deaths; 9742 from respiratory and 57 402 from cardiovascular causes. Daily (average) pollen counts of alder, birch, mugwort and grass were measured. In quasi-Poisson regression analysis, abundant alder pollen increased the risk of non-accidental deaths with an adjusted cumulative mortality rate ratio (acMRR) of 1.10 (95% CI 1.01–1.19) and of deaths from respiratory-diseases with acMRR of 1.78 (95% CI 1.19–2.65). Abundant mugwort pollen increased cardiovascular mortality (1.41, 1.02–1.95). These findings identify an important global public health problem

Towards a Comprehensive Evaluation of the Environmental and Health Impacts of Shipping Emissions

We present a new concept for marine research, applied in the EU-funded project EMERGE, “Evaluation, control and Mitigation of the EnviRonmental impacts of shippinG Emissions” (2020–2024; https://emerge-h2020.eu/). For the first time, both the various marine and atmospheric impacts of the shipping sector have been and will be comprehensively analyzed, using a concerted modelling and measurements framework. The experimental part of the project focuses on five European geographical case studies in different ecologically vulnerable regions, and a mobile onboard case study. The EMERGE consortium has also developed a harmonised and integrated modelling framework to assess the combined impacts of shipping emissions, both (i) on the marine ecosystems and (ii) the atmospheric environment. The first results include substantial refinements of a range of models to be applied, especially those for the STEAM and OpenDrift models. In particular, the STEAM (Ship Traffic Emission Assessment Model) model has been extended to allow for the effects of atmospheric and oceanographic factors on the fuel consumption and emissions of the ships. The OpenDrift model has been improved to take into account the partitioning, degradation, and volatilization of pollutants in water. The predicted emission and discharge values have been used as input for both regional scale atmospheric dispersion models, such as WRF-CMAQ (Weather Research and Forecasting—Community Multiscale Air Quality Model) and SILAM (System for Integrated modeLling of Atmospheric composition), and water quality and circulation models, such as OpenDrift (Open source model for the drifting of substances in the ocean) and Delft3D (oceanographic model). The case study regions are Eastern Mediterranean, Northern Adriatic Sea, the Lagoon of Aveiro, the Solent Strait and the Öresund Strait. We have also conducted a substantial part of the experimental campaigns scheduled in the project. The final assessment will include the benefits and costs of control and mitigation options affecting water quality, air pollution exposure, health impacts, climate forcing, and ecotoxicological effects and bioaccumulation of pollutants in marine biota