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Allergic diseases such as asthma, atopic dermatitis and hay fever do not cause the onset of mental health conditions or vice versa, a new study has claimed Figures showing the recorded prevalence of conditions including asthma, hypertension, dementia, diabetes and depression have been published for England A World Health Organization vaccination target for five childhood diseases has been met for the tenth consecutive year in England

Environmental factors and mobility predict COVID-19 seasonality

BackgroundWe recently showed that seasonal patterns of COVID-19 incidence and Influenza-Like Illnesses incidence are highly similar, in a country in the temperate climate zone, such as the Netherlands (latitude: 52°N). We hypothesize that in The Netherlands the same environmental factors and mobility trends that are associated with the seasonality of flu-like illnesses are predictors of COVID-19 seasonality as well.MethodsWe used meteorological, pollen/hay fever and mobility data from the Netherlands with its 17.4 million inhabitants. For the reproduction number of COVID-19 (Rt), we used data from the Dutch State Institute for Public Health. This Rt metric is a daily estimate that is based on positive COVID-19 tests in the Netherlands in hospitals and municipalities. For all datasets we selected the overlapping period of COVID-19 and the first allergy season: from February 17, 2020 till September 21, 2020 (total number of measurements: n = 218), the end of pollen season. Backward stepwise multiple linear regression was used to develop an environmental prediction model of the Rt of COVID-19. Next, we studied whether adding mobility trends to an environmental model improved the predictive power.ResultsBy means of stepwise backward multiple linear regression four highly significant (p value < 0.01) predictive factors are selected in our combined model: temperature, solar radiation, hay fever incidence, and mobility to indoor recreation locations. Our combined model explains 87.5% of the variance of Rt of COVID-19 and has a good and highly significant fit: F(4, 213) = 374.2, p-value < 0.00001. The combined model had a better overall predictive performance compared to a solely environmental model, which still explains 77.3% of the variance of Rt, and a good and highly significant fit: F(4, 213) = 181.3, p < 0.00001.ConclusionsWe conclude that the combined mobility and environmental model can adequately predict the seasonality of COVID-19 in a country with a temperate climate like the Netherlands. In this model higher solar radiation, higher temperature and hay fever are related to lower COVID-19 reproduction, and mobility to indoor recreation locations with increased COVID-19 spread.HighlightsThe seasonality of COVID-19 can be well-explained by environmental factors and mobility.A combined model explains 87.5% of the variance of the reproduction number of COVID-19Inhibitors of the reproduction number of COVID-19 are higher solar radiation, and seasonal allergens/allergies.Mobility, especially to indoor recreation locations, increases the reproduction number of COVID-19.Temperature has no direct effect on the reproduction number of COVID-19, but affects mobility and seasonal allergens.Adding mobility trends to an environmental model improves the predictive value regarding the reproduction number of COVID-19.

550Short-term exposure to grass pollen is associated with lower lung function and increased airway inflammation

Background The association between grass pollen exposure and lung function changes and airway inflammation is limited. We investigated these associations in a community-based sample, and whether any such associations were modified by current asthma, current hay fever, pollen sensitization and age. Methods Cross-sectional analyses of data from the Melbourne Atopy Cohort Study (MACS) participants (n = 936). Lung function was assessed using spirometry. Airway inflammation was assessed by fractional exhaled nitric oxide (FeNO), and exhaled breath condensate pH and nitrogen oxides (NOx). Daily pollen counts were collected using a volumetric spore trap. The associations were examined by linear regression. Results Higher ambient levels of grass pollen 2 days before (lag 2) were associated with lower mid-forced expiratory flow (FEF25-75%) and FEV1/FVC ratio (Coef. [95% CI] = -119 [-226, -11] mL/s and -1.0 [-3.0, -0.03] %, respectively) and also 3 days before (lag 3). Increased levels of grass pollen a day before (lag 1) was associated with increased FeNO (4.35 [-0.1, 8.7] ppb) and also at lag 2. Adverse associations between pollen and multiple outcomes were greater in adults with current asthma, hay fever and pollen sensitization. Conclusions Grass pollen exposure was associated with eosinophilic airway inflammation 1-2 days after exposure and airway obstruction 2-3 days after exposure. Key messages There is a more delayed effect on lung function compared to airway inflammation. Adults with current asthma, hay fever and grass pollen sensitisation are especially vulnerable.

Supporting people to self-manage their allergic rhinitis

Allergic rhinitis is common in the UK and can cause significant symptoms and reductions in quality of life. Viv Marsh considers how health professionals can support self-management of these patients Many of us look forward to the spring and summer months with warmer weather, longer days and more opportunity to spend time outdoors. But for hay fever sufferers these months can be truly miserable. For others, the winter months can be equally challenging as, with more time spent indoors, exposure to indoor allergens is greater. Hay fever is the term commonly used to describe seasonal nasal allergy triggered by pollen. It affects many children and adults in the UK, causing significant symptoms and reduction in quality of life. Often, people with allergic rhinitis try to manage the condition themselves using home or over-the-counter remedies to reduce and control symptoms. However, effective management may not be straightforward and guidance from knowledgeable and experienced health professionals can lead to improved outcomes. Taking an evidence-based approach, this article will explore the impact of allergic rhinitis on those who experience it, and will consider how health professionals can support self-management to enable people with the condition to manage their symptoms and minimise its impact on their lives.

The Patient's Hay-fever diary: users feedback can improve pollen information

&lt;p&gt;&lt;em&gt;Background: &lt;/em&gt;Pollen information is crucial for effective preventive behaviour of pollen allergy sufferers. In addition to the results of pollen monitoring and weather conditions, feedback from allergic people plays an important role in generating information for the public. A useful tool that gives us an insight into the burden of pollen allergy is the patient&amp;#8217;s hay fever diary (PHD), developed by the Vienna Medical University. PHD is freely available online, users enter their location, general well-being, pollen symptoms and medication use.&lt;/p&gt;&lt;p&gt;&lt;em&gt;Methods: &lt;/em&gt;This study is based on two databases: 1- PHD data for symptom load index (SLI) calculations, only daily entries from Slovenia were used; 2- National pollen database for three measuring stations: Ljubljana, Maribor and Izola. A five-year period (2014-2018) was analysed. We reviewed the number of monthly entries as an indicator of the time span when most people need pollen information. The focus was on three high allergenic pollen types; birch (Betula), grass (Poaceae) and ragweed (Ambrosia). Annual pollen load (APL) allows us to compare results between years.&lt;/p&gt;&lt;p&gt;&lt;em&gt;Results:&lt;/em&gt; 60 % of yearly entries were recorded from March to May, when users reported the most problems with pollen-induced symptoms. In parallel the monthly pollen totals were high. Birch pollen season typically occurs from late March to end of April with May marked by grass pollen season. The highest SLI values were calculated for birch pollen (4,79 &amp;#8211; 7,68), with the maximum in the year 2016 when the highest APL was also recorded. SLI for grass pollen season varied from 3,92 to 4,80 and is mostly lower than SLI for birch. SLI slowly decreased after May and rose again in August and September, when ragweed pollen occurs. Results for this non-native species show that SLI was increasing from 2,48 (2014) to 4,55 (2018).&lt;/p&gt;&lt;p&gt;&lt;em&gt;Conclusion:&lt;/em&gt; Pollen information is most sought after in the spring, when the highest daily concentrations are recorded. Birch pollen seems to have the highest impact on allergy sufferers, followed by grasses. In the case of ragweed we have noticed that the impact on health was increasing during the analyzed period. A comparison of the calculated SLI with the level of exposure to different pollen types may explain the fluctuations in the occurrence of allergic disease during the course of pollen seasons. Preventive behaviour of allergic persons is only possible with quick and accurate pollen information. Therefore, we started releasing preliminary results with a three-color scale to keep the public informed about the current state of allergens in the atmosphere. &amp;#160;&lt;/p&gt;