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Phenotyping asthma, rhinitis and eczema in MeDALL population-based birth cohorts: an allergic comorbidity cluster

(2015) ALLERGY. 70(8). p.973-984
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Ghent researchers on unfolded proteins in inflammatory disease (GROUP-ID)
Abstract
Background: Asthma, rhinitis and eczema often co-occur in children, but their interrelationships at the population level have been poorly addressed. We assessed co-occurrence of childhood asthma, rhinitis and eczema using unsupervised statistical techniques. Methods: We included 17209 children at 4years and 14585 at 8years from seven European population-based birth cohorts (MeDALL project). At each age period, children were grouped, using partitioning cluster analysis, according to the distribution of 23 variables covering symptoms ever' and in the last 12months', doctor diagnosis, age of onset and treatments of asthma, rhinitis and eczema; immunoglobulin E sensitization; weight; and height. We tested the sensitivity of our estimates to subject and variable selections, and to different statistical approaches, including latent class analysis and self-organizing maps. Results: Two groups were identified as the optimal way to cluster the data at both age periods and in all sensitivity analyses. The first (reference) group at 4 and 8years (including 70% and 79% of children, respectively) was characterized by a low prevalence of symptoms and sensitization, whereas the second (symptomatic) group exhibited more frequent symptoms and sensitization. Ninety-nine percentage of children with comorbidities (co-occurrence of asthma, rhinitis and/or eczema) were included in the symptomatic group at both ages. The children's characteristics in both groups were consistent in all sensitivity analyses. Conclusion: At 4 and 8years, at the population level, asthma, rhinitis and eczema can be classified together as an allergic comorbidity cluster. Future research including time-repeated assessments and biological data will help understanding the interrelationships between these diseases.
Keywords
eczema, rhinitis, LATENT CLASS ANALYSIS, ATOPIC-DERMATITIS, CHILDHOOD ASTHMA, ASSOCIATIONS, PREVENTION, COUGH, SENSITIZATION, ORGANIZATION, MECHANISMS, SYMPTOMS, cluster analysis, asthma, allergy

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Citation

Please use this url to cite or link to this publication:

Chicago
Garcia-Aymerich, J, M Benet, Yvan Saeys, M Pinart, X Basagaña, HA Smit, V Siroux, et al. 2015. “Phenotyping Asthma, Rhinitis and Eczema in MeDALL Population-based Birth Cohorts: An Allergic Comorbidity Cluster.” Allergy 70 (8): 973–984.
APA
Garcia-Aymerich, J., Benet, M., Saeys, Y., Pinart, M., Basagaña, X., Smit, H., Siroux, V., et al. (2015). Phenotyping asthma, rhinitis and eczema in MeDALL population-based birth cohorts: an allergic comorbidity cluster. ALLERGY, 70(8), 973–984.
Vancouver
1.
Garcia-Aymerich J, Benet M, Saeys Y, Pinart M, Basagaña X, Smit H, et al. Phenotyping asthma, rhinitis and eczema in MeDALL population-based birth cohorts: an allergic comorbidity cluster. ALLERGY. 2015;70(8):973–84.
MLA
Garcia-Aymerich, J, M Benet, Yvan Saeys, et al. “Phenotyping Asthma, Rhinitis and Eczema in MeDALL Population-based Birth Cohorts: An Allergic Comorbidity Cluster.” ALLERGY 70.8 (2015): 973–984. Print.
@article{6971542,
  abstract     = {Background: Asthma, rhinitis and eczema often co-occur in children, but their interrelationships at the population level have been poorly addressed. We assessed co-occurrence of childhood asthma, rhinitis and eczema using unsupervised statistical techniques.
Methods: We included 17209 children at 4years and 14585 at 8years from seven European population-based birth cohorts (MeDALL project). At each age period, children were grouped, using partitioning cluster analysis, according to the distribution of 23 variables covering symptoms ever' and in the last 12months', doctor diagnosis, age of onset and treatments of asthma, rhinitis and eczema; immunoglobulin E sensitization; weight; and height. We tested the sensitivity of our estimates to subject and variable selections, and to different statistical approaches, including latent class analysis and self-organizing maps.
Results: Two groups were identified as the optimal way to cluster the data at both age periods and in all sensitivity analyses. The first (reference) group at 4 and 8years (including 70\% and 79\% of children, respectively) was characterized by a low prevalence of symptoms and sensitization, whereas the second (symptomatic) group exhibited more frequent symptoms and sensitization. Ninety-nine percentage of children with comorbidities (co-occurrence of asthma, rhinitis and/or eczema) were included in the symptomatic group at both ages. The children's characteristics in both groups were consistent in all sensitivity analyses.
Conclusion: At 4 and 8years, at the population level, asthma, rhinitis and eczema can be classified together as an allergic comorbidity cluster. Future research including time-repeated assessments and biological data will help understanding the interrelationships between these diseases.},
  author       = {Garcia-Aymerich, J and Benet, M and Saeys, Yvan and Pinart, M and Basaga{\~n}a, X and Smit, HA and Siroux, V and Just, J and Momas, I and Ranci{\`e}re, F and Keil, T and Hohmann, C and Lau, S and Wahn, U and Heinrich, J and Tischer, CG and Fantini, MP and Lenzi, J and Porta, D and Koppelman, GH and Postma, DS and Berdel, D and Koletzko, S and Kerkhof, M and Gehring, U and Wickman, M and Mel{\'e}n, E and Hallberg, J and Bindslev-Jensen, C and Eller, E and Kull, I and L{\o}drup Carlsen, KC and Carlsen, K-H and Lambrecht, Bart and Kogevinas, M and Sunyer, J and Kauffmann, F and Bousquet, J and Ant{\'o}, JM},
  issn         = {0105-4538},
  journal      = {ALLERGY},
  keyword      = {eczema,rhinitis,LATENT CLASS ANALYSIS,ATOPIC-DERMATITIS,CHILDHOOD ASTHMA,ASSOCIATIONS,PREVENTION,COUGH,SENSITIZATION,ORGANIZATION,MECHANISMS,SYMPTOMS,cluster analysis,asthma,allergy},
  language     = {eng},
  number       = {8},
  pages        = {973--984},
  title        = {Phenotyping asthma, rhinitis and eczema in MeDALL population-based birth cohorts: an allergic comorbidity cluster},
  url          = {http://dx.doi.org/10.1111/all.12640},
  volume       = {70},
  year         = {2015},
}

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