Cargando…
The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database
BACKGROUND: Reducing the considerable non-communicable disease (NCD) burden in the aging Japanese population depends on better understanding of the comorbid and temporal relationships between different NCDs. OBJECTIVE: We aimed to identify associations between NCDs and temporal patterns of NCDs in J...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392665/ https://www.ncbi.nlm.nih.gov/pubmed/35780274 http://dx.doi.org/10.1007/s40801-022-00310-w |
_version_ | 1784771114736549888 |
---|---|
author | Higa, Shingo Nozawa, Kazutaka Karasawa, Yusuke Shirai, Chikako Matsuyama, Satoshi Yamamoto, Yuji Laurent, Thomas Asami, Yuko |
author_facet | Higa, Shingo Nozawa, Kazutaka Karasawa, Yusuke Shirai, Chikako Matsuyama, Satoshi Yamamoto, Yuji Laurent, Thomas Asami, Yuko |
author_sort | Higa, Shingo |
collection | PubMed |
description | BACKGROUND: Reducing the considerable non-communicable disease (NCD) burden in the aging Japanese population depends on better understanding of the comorbid and temporal relationships between different NCDs. OBJECTIVE: We aimed to identify associations between NCDs and temporal patterns of NCDs in Japan using data from a large medical claims database. METHODS: The study used three-digit International Classification of Diseases, Tenth Revision codes for NCDs for employees and their dependents included in the MinaCare database, which covers the period since 2010. Associations between pairs of NCDs were assessed by calculating risk ratios. The calculated risk ratios were used to create a network of closely associated NCDs (risk ratio > 15, statistically significant) and to assess temporal patterns of NCD diagnoses (risk ratio ≥ 5). The Infomap algorithm was used to identify clusters of diseases for different sex and age strata. RESULTS: The analysis included 4,200,254 individuals (age < 65 years: 98%). Many of the temporal associations and patterns of the diseases of interest identified in this study were previously known. Regarding the diseases of interest, these associations can be classified as comorbidities, early manifestations initially diagnosed as something else, diseases attributable to or that cause the disease of interest, or caused by pharmacological treatment. International Classification of Diseases, Tenth Revision chapters that were most associated with other chapters included L Diseases of the skin and subcutaneous tissue. In the age-stratified and gender-stratified networks, clusters with the highest numbers of International Classification of Diseases, Tenth Revision codes included I Diseases of the circulatory system and F Mental and behavioral disorders. CONCLUSIONS: Our findings reinforce established associations between NCDs and underline the importance of comprehensive NCD care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40801-022-00310-w. |
format | Online Article Text |
id | pubmed-9392665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-93926652022-08-22 The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database Higa, Shingo Nozawa, Kazutaka Karasawa, Yusuke Shirai, Chikako Matsuyama, Satoshi Yamamoto, Yuji Laurent, Thomas Asami, Yuko Drugs Real World Outcomes Original Research Article BACKGROUND: Reducing the considerable non-communicable disease (NCD) burden in the aging Japanese population depends on better understanding of the comorbid and temporal relationships between different NCDs. OBJECTIVE: We aimed to identify associations between NCDs and temporal patterns of NCDs in Japan using data from a large medical claims database. METHODS: The study used three-digit International Classification of Diseases, Tenth Revision codes for NCDs for employees and their dependents included in the MinaCare database, which covers the period since 2010. Associations between pairs of NCDs were assessed by calculating risk ratios. The calculated risk ratios were used to create a network of closely associated NCDs (risk ratio > 15, statistically significant) and to assess temporal patterns of NCD diagnoses (risk ratio ≥ 5). The Infomap algorithm was used to identify clusters of diseases for different sex and age strata. RESULTS: The analysis included 4,200,254 individuals (age < 65 years: 98%). Many of the temporal associations and patterns of the diseases of interest identified in this study were previously known. Regarding the diseases of interest, these associations can be classified as comorbidities, early manifestations initially diagnosed as something else, diseases attributable to or that cause the disease of interest, or caused by pharmacological treatment. International Classification of Diseases, Tenth Revision chapters that were most associated with other chapters included L Diseases of the skin and subcutaneous tissue. In the age-stratified and gender-stratified networks, clusters with the highest numbers of International Classification of Diseases, Tenth Revision codes included I Diseases of the circulatory system and F Mental and behavioral disorders. CONCLUSIONS: Our findings reinforce established associations between NCDs and underline the importance of comprehensive NCD care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40801-022-00310-w. Springer International Publishing 2022-07-02 /pmc/articles/PMC9392665/ /pubmed/35780274 http://dx.doi.org/10.1007/s40801-022-00310-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Article Higa, Shingo Nozawa, Kazutaka Karasawa, Yusuke Shirai, Chikako Matsuyama, Satoshi Yamamoto, Yuji Laurent, Thomas Asami, Yuko The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database |
title | The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database |
title_full | The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database |
title_fullStr | The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database |
title_full_unstemmed | The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database |
title_short | The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database |
title_sort | use of a network analysis to identify associations and temporal patterns among non-communicable diseases in japan based on a large medical claims database |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392665/ https://www.ncbi.nlm.nih.gov/pubmed/35780274 http://dx.doi.org/10.1007/s40801-022-00310-w |
work_keys_str_mv | AT higashingo theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT nozawakazutaka theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT karasawayusuke theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT shiraichikako theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT matsuyamasatoshi theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT yamamotoyuji theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT laurentthomas theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT asamiyuko theuseofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT higashingo useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT nozawakazutaka useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT karasawayusuke useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT shiraichikako useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT matsuyamasatoshi useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT yamamotoyuji useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT laurentthomas useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase AT asamiyuko useofanetworkanalysistoidentifyassociationsandtemporalpatternsamongnoncommunicablediseasesinjapanbasedonalargemedicalclaimsdatabase |