Cargando…
Investigating spousal concordance of diabetes through statistical analysis and data mining
OBJECTIVE: Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5560637/ https://www.ncbi.nlm.nih.gov/pubmed/28817654 http://dx.doi.org/10.1371/journal.pone.0183413 |
_version_ | 1783257692487286784 |
---|---|
author | Wang, Jong-Yi Liu, Chiu-Shong Lung, Chi-Hsuan Yang, Ya-Tun Lin, Ming-Hung |
author_facet | Wang, Jong-Yi Liu, Chiu-Shong Lung, Chi-Hsuan Yang, Ya-Tun Lin, Ming-Hung |
author_sort | Wang, Jong-Yi |
collection | PubMed |
description | OBJECTIVE: Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. METHODS: A total of 22,572 individuals identified from the 2002–2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics. RESULTS: High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001). CONCLUSIONS: A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions. |
format | Online Article Text |
id | pubmed-5560637 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55606372017-08-25 Investigating spousal concordance of diabetes through statistical analysis and data mining Wang, Jong-Yi Liu, Chiu-Shong Lung, Chi-Hsuan Yang, Ya-Tun Lin, Ming-Hung PLoS One Research Article OBJECTIVE: Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. METHODS: A total of 22,572 individuals identified from the 2002–2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics. RESULTS: High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001). CONCLUSIONS: A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions. Public Library of Science 2017-08-17 /pmc/articles/PMC5560637/ /pubmed/28817654 http://dx.doi.org/10.1371/journal.pone.0183413 Text en © 2017 Wang 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wang, Jong-Yi Liu, Chiu-Shong Lung, Chi-Hsuan Yang, Ya-Tun Lin, Ming-Hung Investigating spousal concordance of diabetes through statistical analysis and data mining |
title | Investigating spousal concordance of diabetes through statistical analysis and data mining |
title_full | Investigating spousal concordance of diabetes through statistical analysis and data mining |
title_fullStr | Investigating spousal concordance of diabetes through statistical analysis and data mining |
title_full_unstemmed | Investigating spousal concordance of diabetes through statistical analysis and data mining |
title_short | Investigating spousal concordance of diabetes through statistical analysis and data mining |
title_sort | investigating spousal concordance of diabetes through statistical analysis and data mining |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5560637/ https://www.ncbi.nlm.nih.gov/pubmed/28817654 http://dx.doi.org/10.1371/journal.pone.0183413 |
work_keys_str_mv | AT wangjongyi investigatingspousalconcordanceofdiabetesthroughstatisticalanalysisanddatamining AT liuchiushong investigatingspousalconcordanceofdiabetesthroughstatisticalanalysisanddatamining AT lungchihsuan investigatingspousalconcordanceofdiabetesthroughstatisticalanalysisanddatamining AT yangyatun investigatingspousalconcordanceofdiabetesthroughstatisticalanalysisanddatamining AT linminghung investigatingspousalconcordanceofdiabetesthroughstatisticalanalysisanddatamining |