Cargando…

The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna

BACKGROUND: Online pollen diaries and mobile applications nowadays allow easy and fast documentation of pollen allergy symptoms. Such crowd-sourced symptom data provides insights into the development and the onset of a pollen allergy. Hitherto studies of the symptom load index (SLI) showed a discrep...

Descripción completa

Detalles Bibliográficos
Autores principales: Bastl, Katharina, Kmenta, Maximilian, Berger, Markus, Berger, Uwe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190540/
https://www.ncbi.nlm.nih.gov/pubmed/30349618
http://dx.doi.org/10.1186/s40413-018-0203-6
_version_ 1783363593254731776
author Bastl, Katharina
Kmenta, Maximilian
Berger, Markus
Berger, Uwe
author_facet Bastl, Katharina
Kmenta, Maximilian
Berger, Markus
Berger, Uwe
author_sort Bastl, Katharina
collection PubMed
description BACKGROUND: Online pollen diaries and mobile applications nowadays allow easy and fast documentation of pollen allergy symptoms. Such crowd-sourced symptom data provides insights into the development and the onset of a pollen allergy. Hitherto studies of the symptom load index (SLI) showed a discrepancy between the SLI and the total pollen amount of a season, but did not analyze the daily data. METHODS: The Patient’s Hayfever Diary (PHD) was used as data pool for symptom data. Symptom data of Vienna (Austria) was chosen as a large and local sample size within the study period of 2013 until 2017. The city was divided into three different areas based on equal population densities and different environmental factors. Correlation factors, regression lines, locally weighted smoothing (LOESS) curves and line plots were calculated to examine the data. RESULTS: Daily SLI and pollen concentration data correlates well and the progress of the SLI within a pollen season is mirrored by the pollen concentrations. The LOESS curves do not deviate much from the regression line and support the linearity of the symptom-pollen correlation on a daily basis. Seasonal SLI data does not follow the same pattern as the respective seasonal pollen indices. Results did not vary in the three areas within Vienna or when compared with the Eastern region of Austria showing no significant spatial variation of the SLI. DISCUSSION: Results indicate a linear relationship of the SLI and pollen concentrations/seasonal polllen index (SPIn) on a daily basis for both in general and throughout the season, but not on a seasonal basis. These findings clarify the frequent misinterpretation of the SLI as index that is tightly connected to pollen concentrations, but reflects as well the seasonal variation of the burden of pollen allergy sufferers. CONCLUSION: More than just the seasonal pollen index has to be considered when the SLI of a selected pollen season has to be explained. Cross-reactivity to other pollen types, allergen content and air pollution could play a considerable role. The similar behavior of the SLI in Vienna and a whole region indicate the feasibility of a possible symptom forecast in future and justifies the use of a single pollen monitoring station within a city of the size of Vienna.
format Online
Article
Text
id pubmed-6190540
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-61905402018-10-22 The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna Bastl, Katharina Kmenta, Maximilian Berger, Markus Berger, Uwe World Allergy Organ J Original Research BACKGROUND: Online pollen diaries and mobile applications nowadays allow easy and fast documentation of pollen allergy symptoms. Such crowd-sourced symptom data provides insights into the development and the onset of a pollen allergy. Hitherto studies of the symptom load index (SLI) showed a discrepancy between the SLI and the total pollen amount of a season, but did not analyze the daily data. METHODS: The Patient’s Hayfever Diary (PHD) was used as data pool for symptom data. Symptom data of Vienna (Austria) was chosen as a large and local sample size within the study period of 2013 until 2017. The city was divided into three different areas based on equal population densities and different environmental factors. Correlation factors, regression lines, locally weighted smoothing (LOESS) curves and line plots were calculated to examine the data. RESULTS: Daily SLI and pollen concentration data correlates well and the progress of the SLI within a pollen season is mirrored by the pollen concentrations. The LOESS curves do not deviate much from the regression line and support the linearity of the symptom-pollen correlation on a daily basis. Seasonal SLI data does not follow the same pattern as the respective seasonal pollen indices. Results did not vary in the three areas within Vienna or when compared with the Eastern region of Austria showing no significant spatial variation of the SLI. DISCUSSION: Results indicate a linear relationship of the SLI and pollen concentrations/seasonal polllen index (SPIn) on a daily basis for both in general and throughout the season, but not on a seasonal basis. These findings clarify the frequent misinterpretation of the SLI as index that is tightly connected to pollen concentrations, but reflects as well the seasonal variation of the burden of pollen allergy sufferers. CONCLUSION: More than just the seasonal pollen index has to be considered when the SLI of a selected pollen season has to be explained. Cross-reactivity to other pollen types, allergen content and air pollution could play a considerable role. The similar behavior of the SLI in Vienna and a whole region indicate the feasibility of a possible symptom forecast in future and justifies the use of a single pollen monitoring station within a city of the size of Vienna. BioMed Central 2018-10-16 /pmc/articles/PMC6190540/ /pubmed/30349618 http://dx.doi.org/10.1186/s40413-018-0203-6 Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Original Research
Bastl, Katharina
Kmenta, Maximilian
Berger, Markus
Berger, Uwe
The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna
title The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna
title_full The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna
title_fullStr The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna
title_full_unstemmed The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna
title_short The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna
title_sort connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in vienna
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190540/
https://www.ncbi.nlm.nih.gov/pubmed/30349618
http://dx.doi.org/10.1186/s40413-018-0203-6
work_keys_str_mv AT bastlkatharina theconnectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT kmentamaximilian theconnectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT bergermarkus theconnectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT bergeruwe theconnectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT bastlkatharina connectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT kmentamaximilian connectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT bergermarkus connectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna
AT bergeruwe connectionofpollenconcentrationsandcrowdsourcedsymptomdatanewinsightsfromdailyandseasonalsymptomloadindexdatafrom2013to2017invienna