Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009

Objective High variability has been observed in type 1 diabetes mellitus (DM1) incidence rates (IRs) in childhood. The aim of this study was to characterize DM1 in Aragón and to identify variations in the geographical pattern by gender. Methods A descriptive and ecological study was conducted to det...

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Veröffentlicht in:Pediatric diabetes 2013-02, Vol.14 (1), p.66-76
Hauptverfasser: Compés, Maria Luisa, Feja, Cristina, Niño De Guzman, Ena, Aguilar, Isabel, Conde, Santiago, Alonso, Juan Pablo, Rodrigo, Maria Pilar
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container_end_page 76
container_issue 1
container_start_page 66
container_title Pediatric diabetes
container_volume 14
creator Compés, Maria Luisa
Feja, Cristina
Niño De Guzman, Ena
Aguilar, Isabel
Conde, Santiago
Alonso, Juan Pablo
Rodrigo, Maria Pilar
description Objective High variability has been observed in type 1 diabetes mellitus (DM1) incidence rates (IRs) in childhood. The aim of this study was to characterize DM1 in Aragón and to identify variations in the geographical pattern by gender. Methods A descriptive and ecological study was conducted to determine geographical variations in the DM1 incidence for the period 1991–2009. The source of information was the registry of DM1. To determine data completeness, a capture–recapture analysis was performed. Cases were georeferenced according to the Basic Healthcare Area (BHA) of residence. IRs for both genders, age group, 5 yr of diagnosis, and 95% confidence intervals (95% CIs) were calculated. Geographical pattern was studied applying Bayesian statistical model. The standardized incidence ratios (SIRs), smoothed SIR, and the posteriori risk probability (PRP) were represented cartographically for BHA stratified by gender. Results The completeness was 93.5%. The global IR was 19.2 cases/105 person‐years (95% CI: 17.6–20.8), boys 21.4 (95% CI: 19.0–23.8) and girls 16.8 (95% CI: 14.7–19.1). The age‐specific rates were significantly lower in the 0–4 year age group with respect to the groups of 5–9 and 10–14 years. For boys, areas with a statistically significant excess of risk were found in the north [smoothed SIR: 118–167.9 and PRP of what the smoothed SIR would be greater than 100 (PRP) above 0.8] and below average risk in the south (smoothed SIR: 65.9–79.1 and PRP less than 0.2). Conclusions DM1 IR presented a north–south geographical pattern in boys. This pattern was not observed in girls or when both genders were considered together. Later studies should include gender as an essential variable.
doi_str_mv 10.1111/j.1399-5448.2012.00892.x
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The aim of this study was to characterize DM1 in Aragón and to identify variations in the geographical pattern by gender. Methods A descriptive and ecological study was conducted to determine geographical variations in the DM1 incidence for the period 1991–2009. The source of information was the registry of DM1. To determine data completeness, a capture–recapture analysis was performed. Cases were georeferenced according to the Basic Healthcare Area (BHA) of residence. IRs for both genders, age group, 5 yr of diagnosis, and 95% confidence intervals (95% CIs) were calculated. Geographical pattern was studied applying Bayesian statistical model. The standardized incidence ratios (SIRs), smoothed SIR, and the posteriori risk probability (PRP) were represented cartographically for BHA stratified by gender. Results The completeness was 93.5%. The global IR was 19.2 cases/105 person‐years (95% CI: 17.6–20.8), boys 21.4 (95% CI: 19.0–23.8) and girls 16.8 (95% CI: 14.7–19.1). The age‐specific rates were significantly lower in the 0–4 year age group with respect to the groups of 5–9 and 10–14 years. For boys, areas with a statistically significant excess of risk were found in the north [smoothed SIR: 118–167.9 and PRP of what the smoothed SIR would be greater than 100 (PRP) above 0.8] and below average risk in the south (smoothed SIR: 65.9–79.1 and PRP less than 0.2). Conclusions DM1 IR presented a north–south geographical pattern in boys. This pattern was not observed in girls or when both genders were considered together. Later studies should include gender as an essential variable.</description><identifier>ISSN: 1399-543X</identifier><identifier>EISSN: 1399-5448</identifier><identifier>DOI: 10.1111/j.1399-5448.2012.00892.x</identifier><identifier>PMID: 22816867</identifier><language>eng</language><publisher>Former Munksgaard: John Wiley &amp; Sons A/S</publisher><subject>Adolescent ; Bayes Theorem ; Child ; Child, Preschool ; Diabetes Mellitus, Type 1 - epidemiology ; DM1 ; ecological studies ; Female ; geoepidemiology ; Geography ; Humans ; Incidence ; Infant ; Infant, Newborn ; Male ; Spain - epidemiology ; Time Factors</subject><ispartof>Pediatric diabetes, 2013-02, Vol.14 (1), p.66-76</ispartof><rights>2012 John Wiley &amp; Sons A/S</rights><rights>2012 John Wiley &amp; Sons A/S.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3382-602e4e7369e0da28c65afd8d39e78e6539880017cadb242c4da43a4e06e12b633</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1399-5448.2012.00892.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1399-5448.2012.00892.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22816867$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Compés, Maria Luisa</creatorcontrib><creatorcontrib>Feja, Cristina</creatorcontrib><creatorcontrib>Niño De Guzman, Ena</creatorcontrib><creatorcontrib>Aguilar, Isabel</creatorcontrib><creatorcontrib>Conde, Santiago</creatorcontrib><creatorcontrib>Alonso, Juan Pablo</creatorcontrib><creatorcontrib>Rodrigo, Maria Pilar</creatorcontrib><title>Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009</title><title>Pediatric diabetes</title><addtitle>Pediatr Diabetes</addtitle><description>Objective High variability has been observed in type 1 diabetes mellitus (DM1) incidence rates (IRs) in childhood. The aim of this study was to characterize DM1 in Aragón and to identify variations in the geographical pattern by gender. Methods A descriptive and ecological study was conducted to determine geographical variations in the DM1 incidence for the period 1991–2009. The source of information was the registry of DM1. To determine data completeness, a capture–recapture analysis was performed. Cases were georeferenced according to the Basic Healthcare Area (BHA) of residence. IRs for both genders, age group, 5 yr of diagnosis, and 95% confidence intervals (95% CIs) were calculated. Geographical pattern was studied applying Bayesian statistical model. The standardized incidence ratios (SIRs), smoothed SIR, and the posteriori risk probability (PRP) were represented cartographically for BHA stratified by gender. Results The completeness was 93.5%. The global IR was 19.2 cases/105 person‐years (95% CI: 17.6–20.8), boys 21.4 (95% CI: 19.0–23.8) and girls 16.8 (95% CI: 14.7–19.1). The age‐specific rates were significantly lower in the 0–4 year age group with respect to the groups of 5–9 and 10–14 years. For boys, areas with a statistically significant excess of risk were found in the north [smoothed SIR: 118–167.9 and PRP of what the smoothed SIR would be greater than 100 (PRP) above 0.8] and below average risk in the south (smoothed SIR: 65.9–79.1 and PRP less than 0.2). Conclusions DM1 IR presented a north–south geographical pattern in boys. This pattern was not observed in girls or when both genders were considered together. Later studies should include gender as an essential variable.</description><subject>Adolescent</subject><subject>Bayes Theorem</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Diabetes Mellitus, Type 1 - epidemiology</subject><subject>DM1</subject><subject>ecological studies</subject><subject>Female</subject><subject>geoepidemiology</subject><subject>Geography</subject><subject>Humans</subject><subject>Incidence</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Male</subject><subject>Spain - epidemiology</subject><subject>Time Factors</subject><issn>1399-543X</issn><issn>1399-5448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo9Uc1u1DAQthCIlsIrIB85kOC_OPaBAy2lVKwKEkVws2bj2dZLNkntBDYnuPKaPAnJbtm5zMjfj8bzEUI5y_lUr9Y5l9ZmhVImF4yLnDFjRb59QI4PwMPDLL8dkScprRnjpZXqMTkSwnBtdHlMfp3CiClAQ6GBekwh0XZF-1ukN9jeROhuQwU1_QExQB_aZoeOHVJOfYAl9pjoBus69EOioaFD4zFSXvz9_WeMtK397rVp42QJqaefOwjNS8qt5ZlgzD4lj1ZQJ3x230_Il3fn12fvs8XHi8uzN4usktKITDOBCkupLTIPwlS6gJU3XlosDepCWmPm71Xgl0KJSnlQEhQyjVwstZQn5MXet4vt3YCpd5uQqmlxaLAdkuPCCKYKy_VEfX5PHZYb9K6LYQNxdP-PNhFe7wk_Q43jAefMzeG4tZvv7uYM3ByO24Xjtu7T-dvLaZr02V4fUo_bgx7idze5l4X7enXhrrSw1x9OF66U_wAISJFf</recordid><startdate>201302</startdate><enddate>201302</enddate><creator>Compés, Maria Luisa</creator><creator>Feja, Cristina</creator><creator>Niño De Guzman, Ena</creator><creator>Aguilar, Isabel</creator><creator>Conde, Santiago</creator><creator>Alonso, Juan Pablo</creator><creator>Rodrigo, Maria Pilar</creator><general>John Wiley &amp; Sons A/S</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope></search><sort><creationdate>201302</creationdate><title>Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009</title><author>Compés, Maria Luisa ; Feja, Cristina ; Niño De Guzman, Ena ; Aguilar, Isabel ; Conde, Santiago ; Alonso, Juan Pablo ; Rodrigo, Maria Pilar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3382-602e4e7369e0da28c65afd8d39e78e6539880017cadb242c4da43a4e06e12b633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adolescent</topic><topic>Bayes Theorem</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Diabetes Mellitus, Type 1 - epidemiology</topic><topic>DM1</topic><topic>ecological studies</topic><topic>Female</topic><topic>geoepidemiology</topic><topic>Geography</topic><topic>Humans</topic><topic>Incidence</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Male</topic><topic>Spain - epidemiology</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Compés, Maria Luisa</creatorcontrib><creatorcontrib>Feja, Cristina</creatorcontrib><creatorcontrib>Niño De Guzman, Ena</creatorcontrib><creatorcontrib>Aguilar, Isabel</creatorcontrib><creatorcontrib>Conde, Santiago</creatorcontrib><creatorcontrib>Alonso, Juan Pablo</creatorcontrib><creatorcontrib>Rodrigo, Maria Pilar</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><jtitle>Pediatric diabetes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Compés, Maria Luisa</au><au>Feja, Cristina</au><au>Niño De Guzman, Ena</au><au>Aguilar, Isabel</au><au>Conde, Santiago</au><au>Alonso, Juan Pablo</au><au>Rodrigo, Maria Pilar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009</atitle><jtitle>Pediatric diabetes</jtitle><addtitle>Pediatr Diabetes</addtitle><date>2013-02</date><risdate>2013</risdate><volume>14</volume><issue>1</issue><spage>66</spage><epage>76</epage><pages>66-76</pages><issn>1399-543X</issn><eissn>1399-5448</eissn><abstract>Objective High variability has been observed in type 1 diabetes mellitus (DM1) incidence rates (IRs) in childhood. The aim of this study was to characterize DM1 in Aragón and to identify variations in the geographical pattern by gender. Methods A descriptive and ecological study was conducted to determine geographical variations in the DM1 incidence for the period 1991–2009. The source of information was the registry of DM1. To determine data completeness, a capture–recapture analysis was performed. Cases were georeferenced according to the Basic Healthcare Area (BHA) of residence. IRs for both genders, age group, 5 yr of diagnosis, and 95% confidence intervals (95% CIs) were calculated. Geographical pattern was studied applying Bayesian statistical model. The standardized incidence ratios (SIRs), smoothed SIR, and the posteriori risk probability (PRP) were represented cartographically for BHA stratified by gender. Results The completeness was 93.5%. The global IR was 19.2 cases/105 person‐years (95% CI: 17.6–20.8), boys 21.4 (95% CI: 19.0–23.8) and girls 16.8 (95% CI: 14.7–19.1). The age‐specific rates were significantly lower in the 0–4 year age group with respect to the groups of 5–9 and 10–14 years. For boys, areas with a statistically significant excess of risk were found in the north [smoothed SIR: 118–167.9 and PRP of what the smoothed SIR would be greater than 100 (PRP) above 0.8] and below average risk in the south (smoothed SIR: 65.9–79.1 and PRP less than 0.2). Conclusions DM1 IR presented a north–south geographical pattern in boys. This pattern was not observed in girls or when both genders were considered together. Later studies should include gender as an essential variable.</abstract><cop>Former Munksgaard</cop><pub>John Wiley &amp; Sons A/S</pub><pmid>22816867</pmid><doi>10.1111/j.1399-5448.2012.00892.x</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
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source MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects Adolescent
Bayes Theorem
Child
Child, Preschool
Diabetes Mellitus, Type 1 - epidemiology
DM1
ecological studies
Female
geoepidemiology
Geography
Humans
Incidence
Infant
Infant, Newborn
Male
Spain - epidemiology
Time Factors
title Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009
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