Environmental exposure and sensitization patterns in a Swiss alpine pediatric cohort

Background The level of environmental exposure throughout life may contribute to the prevalence of allergic sensitization and allergic disease. The alpine climate has been considered a healthy climate with little allergen exposure and pollution. We conducted a cross-sectional study to investigate local environmental exposure and concomitant prevalence of allergic sensitization among local school children born and raised in an alpine environment. Methods Clinical and demographic data were collected with a questionnaire. Allergen content was assessed in residential settled dust samples, lifetime exposure to pollen and air pollution was calculated using data from national pollen and air pollution monitoring stations, and the allergic sensitization profile was determined with component resolved diagnostics (ISAC®). Univariate and multivariate regression models were used to estimate the relation between exposure and sensitization. Results In a cohort of children born and raised in an alpine environment, sensitization to aeroallergens is quite common (38%), especially to grass (33%) and cat (16%). House dust mite allergen was detected in up to 38% of residential dust samples, but sensitization to HDM was low (2.5%). Pollutant levels were low, but an increasing trend was observed in the amount of ozone and PM10. Living close to a busy road was associated with increased odds OR (95% CI) for being sensitized to any allergen 2.7 (1.0–7.2), to outdoor allergens 2.8 (1.1–7.1) and being sensitized plus reporting symptoms of rhinoconjunctivitis 4.4 (1.3–14.8) and asthma 5.5 (1.4–21). Indoor living conditions, including the presence of visible mold, increased the odds of being sensitized to indoor allergens (1.9 (1.1–3.2) and being sensitized plus reporting symptoms of rhinoconjunctivitis 1.9 (1.0–3.6) and asthma 2.1 (1.0–4.1). Conclusion In a healthy alpine environment, pollution might still be an important factor contributing to allergic sensitization

Predicting the main pollen season of Broussonetia Papyrifera (paper mulberry) tree

Paper mulberry pollen, declared a pest in several countries including Pakistan, can trigger severe allergies and cause asthma attacks. We aimed to develop an algorithm that could accurately predict high pollen days to underpin an alert system that would allow patients to take timely precautionary measures. We developed and validated two prediction models that take historical Nov 15, 2023 2/18 pollen and weather data as their input to predict the start date and peak date of the pollen season in Islamabad, the capital city of Pakistan. The first model is based on linear regression and the second one is based on phenological modelling. We tested our models on an original and comprehensive dataset from Islamabad. The mean absolute errors (MAEs) for the start day are 2.3 and 3.7 days for the linear and phenological models, respectively, while for the peak day, the MAEs are 3.3 and 4.0 days, respectively. These encouraging results could be used in a website or app to notify patients and healthcare providers to start preparing for the paper mulberry pollen season. Timely action could reduce the burden of symptoms, mitigate the risk of acute attacks and potentially prevent deaths due to acute pollen-induced allergy

Environmental exposure and sensitization patterns in a Swiss alpine pediatric cohort

BACKGROUND The level of environmental exposure throughout life may contribute to the prevalence of allergic sensitization and allergic disease. The alpine climate has been considered a healthy climate with little allergen exposure and pollution. We conducted a cross-sectional study to investigate local environmental exposure and concomitant prevalence of allergic sensitization among local school children born and raised in an alpine environment. METHODS Clinical and demographic data were collected with a questionnaire. Allergen content was assessed in residential settled dust samples, lifetime exposure to pollen and air pollution was calculated using data from national pollen and air pollution monitoring stations, and the allergic sensitization profile was determined with component resolved diagnostics (ISAC®). Univariate and multivariate regression models were used to estimate the relation between exposure and sensitization. RESULTS In a cohort of children born and raised in an alpine environment, sensitization to aeroallergens is quite common (38%), especially to grass (33%) and cat (16%). House dust mite allergen was detected in up to 38% of residential dust samples, but sensitization to HDM was low (2.5%). Pollutant levels were low, but an increasing trend was observed in the amount of ozone and PM$_{10}$. Living close to a busy road was associated with increased odds OR (95% CI) for being sensitized to any allergen 2.7 (1.0-7.2), to outdoor allergens 2.8 (1.1-7.1) and being sensitized plus reporting symptoms of rhinoconjunctivitis 4.4 (1.3-14.8) and asthma 5.5 (1.4-21). Indoor living conditions, including the presence of visible mold, increased the odds of being sensitized to indoor allergens (1.9 (1.1-3.2) and being sensitized plus reporting symptoms of rhinoconjunctivitis 1.9 (1.0-3.6) and asthma 2.1 (1.0-4.1). CONCLUSION In a healthy alpine environment, pollution might still be an important factor contributing to allergic sensitization

Effects of climate change on Platanus flowering in Western Mediterranean cities: current trends and future projections

Ornamental trees can reduce some of the negative impacts of urbanization on citizens but some species, such as Platanus spp., produce pollen with high allergenic potential. This can exacerbate the symptomatology in allergic patients, being a public health problem. Therefore, it would be relevant to determine the environmental conditions regulating the flowering onset of the Platanus species. The aims of this study were to use aerobiological records for modelling the thermal requirements of Platanus flowering and to make future projections based on the effects that climate change could have on it under several possible future scenarios. This study was conducted in Badajoz and Malaga, two Western Mediterranean cities with different climate conditions. In the first step, several main pollen season definitions were applied to the aerobiological data and their onset dates were compared with in situ phenological observations. The main pollen season definition that best fitted the Platanus flowering onset was based on the 4th derivative of a logistic function. This definition was used as a proxy to model the thermal requirements of the Platanus flowering onset by applying the PhenoFlex statistical framework. The errors obtained by this model during the external validation were 3.2 days on average, so it was fed with future temperature estimations to determine possible future trends. According to the different models, the flowering onset of Platanus in Badajoz will show heterogeneous responses in the short and medium term due to different balances in the chilling-forcing compensation, while it will clearly delay in Malaga due to a significant delay in the chilling requirement fulfilment. This may increase the chances of cross-reactivity episodes with other pollen types in the future, increasing its impact on public health.Funding for open Access charge: Universidad de Málaga / CBUA. This work was partially financed by the Ministry of Science and Innovation of Spain and FEDER funding inside the Operational Plurirregional Program of Spain 2014-2020 and the Operational Program of Smart Growing (Project Environmental and Biodiversity Climate Change Lab, EnBiC2-Lab), by the Regional Government of Extremadura (IB20081 and GR21027), and by the University of Málaga under its program for projects led by young researchers (I Plan Propio de Investigación y Transferencia; B1-2021_24). A. Picornell was supported by a postdoctoral grant financed by the Ministry of Economic Transformation, Industry, Knowledge and Universities of the Junta de Andalucía (POSTDOC_21_00056). We acknowledge the E-OBS dataset from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://www.ecad.eu)

The optimal parameter values along with mean average errors (MAEs) for phenological modelling under the 5% and 2.5% criteria.

Note that the optimal parameter values were derived from the training years while the MAEs indicate model performance on the test years.</p

Annual paper mulberry pollen count time-series for the years 2004–2018.

Each line represents a separate year. The main pollen seasons (periods with the highest pollen concentrations) are recorded between 10th and 31st March. Pollen concentrations rise again slightly between July and August during and after the summer rain.</p

The box plot of candidate heat units for the peak day after all filtration has been performed including removal of the entries whose relative standard deviation is higher than 50% across years.

The red dots show M, the mean values that will be used as the required heat units.</p

Mean Absolute Error (MAE) values for various durations of meteorological data for the peak day prediction under the 2.5% and 5% start day criteria.

This was done only for the training years as the testing years were reserved to evaluate the performance of the algorithm.</p