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Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases

BACKGROUND: The incidence of Type 1 Diabetes (T1D) in children varies dramatically between countries. Part of the explanation must be sought in environmental factors. Increasingly, public databases provide information on country-to-country environmental differences. METHODS: Information on the incid...

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Autores principales: Diaz-Valencia, Paula Andrea, Bougnères, Pierre, Valleron, Alain-Jacques
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338253/
https://www.ncbi.nlm.nih.gov/pubmed/25706995
http://dx.doi.org/10.1371/journal.pone.0118298
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author Diaz-Valencia, Paula Andrea
Bougnères, Pierre
Valleron, Alain-Jacques
author_facet Diaz-Valencia, Paula Andrea
Bougnères, Pierre
Valleron, Alain-Jacques
author_sort Diaz-Valencia, Paula Andrea
collection PubMed
description BACKGROUND: The incidence of Type 1 Diabetes (T1D) in children varies dramatically between countries. Part of the explanation must be sought in environmental factors. Increasingly, public databases provide information on country-to-country environmental differences. METHODS: Information on the incidence of T1D and country characteristics were searched for in the 194 World Health Organization (WHO) member countries. T1D incidence was extracted from a systematic literature review of all papers published between 1975 and 2014, including the 2013 update from the International Diabetes Federation. The information on country characteristics was searched in public databases. We considered all indicators with a plausible relation with T1D and those previously reported as correlated with T1D, and for which there was less than 5% missing values. This yielded 77 indicators. Four domains were explored: Climate and environment, Demography, Economy, and Health Conditions. Bonferroni correction to correct false discovery rate (FDR) was used in bivariate analyses. Stepwise multiple regressions, served to identify independent predictors of the geographical variation of T1D. FINDINGS: T1D incidence was estimated for 80 WHO countries. Forty-one significant correlations between T1D and the selected indicators were found. Stepwise Multiple Linear Regressions performed in the four explored domains indicated that the percentages of variance explained by the indicators were respectively 35% for Climate and environment, 33% for Demography, 45% for Economy, and 46% for Health conditions, and 51% in the Final model, where all variables selected by domain were considered. Significant environmental predictors of the country-to-country variation of T1D incidence included UV radiation, number of mobile cellular subscriptions in the country, health expenditure per capita, hepatitis B immunization and mean body mass index (BMI). CONCLUSIONS: The increasing availability of public databases providing information in all global environmental domains should allow new analyses to identify further geographical, behavioral, social and economic factors, or indicators that point to latent causal factors of T1D.
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spelling pubmed-43382532015-03-04 Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases Diaz-Valencia, Paula Andrea Bougnères, Pierre Valleron, Alain-Jacques PLoS One Research Article BACKGROUND: The incidence of Type 1 Diabetes (T1D) in children varies dramatically between countries. Part of the explanation must be sought in environmental factors. Increasingly, public databases provide information on country-to-country environmental differences. METHODS: Information on the incidence of T1D and country characteristics were searched for in the 194 World Health Organization (WHO) member countries. T1D incidence was extracted from a systematic literature review of all papers published between 1975 and 2014, including the 2013 update from the International Diabetes Federation. The information on country characteristics was searched in public databases. We considered all indicators with a plausible relation with T1D and those previously reported as correlated with T1D, and for which there was less than 5% missing values. This yielded 77 indicators. Four domains were explored: Climate and environment, Demography, Economy, and Health Conditions. Bonferroni correction to correct false discovery rate (FDR) was used in bivariate analyses. Stepwise multiple regressions, served to identify independent predictors of the geographical variation of T1D. FINDINGS: T1D incidence was estimated for 80 WHO countries. Forty-one significant correlations between T1D and the selected indicators were found. Stepwise Multiple Linear Regressions performed in the four explored domains indicated that the percentages of variance explained by the indicators were respectively 35% for Climate and environment, 33% for Demography, 45% for Economy, and 46% for Health conditions, and 51% in the Final model, where all variables selected by domain were considered. Significant environmental predictors of the country-to-country variation of T1D incidence included UV radiation, number of mobile cellular subscriptions in the country, health expenditure per capita, hepatitis B immunization and mean body mass index (BMI). CONCLUSIONS: The increasing availability of public databases providing information in all global environmental domains should allow new analyses to identify further geographical, behavioral, social and economic factors, or indicators that point to latent causal factors of T1D. Public Library of Science 2015-02-23 /pmc/articles/PMC4338253/ /pubmed/25706995 http://dx.doi.org/10.1371/journal.pone.0118298 Text en © 2015 Diaz-Valencia et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Diaz-Valencia, Paula Andrea
Bougnères, Pierre
Valleron, Alain-Jacques
Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases
title Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases
title_full Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases
title_fullStr Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases
title_full_unstemmed Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases
title_short Covariation of the Incidence of Type 1 Diabetes with Country Characteristics Available in Public Databases
title_sort covariation of the incidence of type 1 diabetes with country characteristics available in public databases
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338253/
https://www.ncbi.nlm.nih.gov/pubmed/25706995
http://dx.doi.org/10.1371/journal.pone.0118298
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