Cargando…

Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study

BACKGROUND: Variations in the prevalence and pattern of multimorbidity might be attributable to lifestyle and environmental factors. This study was performed to determine the prevalence of common chronic diseases and to reveal multimorbidity patterns among adults in Guangdong province with Chaoshan,...

Descripción completa

Detalles Bibliográficos
Autores principales: Hu, Yaoda, He, Huijing, Ou, Qiong, Nai, Jing, Pan, Li, Chen, Xingming, Tu, Ji, Zeng, Xuejun, Pei, Guo, Wang, Longlong, Lin, Binbin, Liu, Qihang, Shan, Guangliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192874/
https://www.ncbi.nlm.nih.gov/pubmed/37213602
http://dx.doi.org/10.3389/fpubh.2023.1163791
_version_ 1785043720702263296
author Hu, Yaoda
He, Huijing
Ou, Qiong
Nai, Jing
Pan, Li
Chen, Xingming
Tu, Ji
Zeng, Xuejun
Pei, Guo
Wang, Longlong
Lin, Binbin
Liu, Qihang
Shan, Guangliang
author_facet Hu, Yaoda
He, Huijing
Ou, Qiong
Nai, Jing
Pan, Li
Chen, Xingming
Tu, Ji
Zeng, Xuejun
Pei, Guo
Wang, Longlong
Lin, Binbin
Liu, Qihang
Shan, Guangliang
author_sort Hu, Yaoda
collection PubMed
description BACKGROUND: Variations in the prevalence and pattern of multimorbidity might be attributable to lifestyle and environmental factors. This study was performed to determine the prevalence of common chronic diseases and to reveal multimorbidity patterns among adults in Guangdong province with Chaoshan, Hakka, and island cultures. METHODS: We used data collected at the baseline survey (April–May 2021) of the Diverse Life-Course Cohort study and included 5,655 participants aged ≥20 years. Multimorbidity was defined as the presence of two or more of the 14 chronic diseases collected by self-reports, physical examinations, and blood tests. Multimorbidity patterns were explored by association rule mining (ARM). RESULTS: Overall, 40.69% of participants had multimorbidity, and the prevalence among coastland (42.37%) and mountain residents (40.36%) was higher than that among island residents (37.97%). The prevalence of multimorbidity increased rapidly with higher age groups and showed an inflection point at 50 years, beyond which >50% of the middle-aged and older adults had multimorbidity. The proportion of people with two chronic diseases accounted for most cases of multimorbidity, and the strongest association was found between hyperuricemia and gout (lift of 3.26). The most prevalent multimorbidity pattern was dyslipidemia and hyperuricemia in the coastland areas and dyslipidemia combined with hypertension in the mountain and island areas. Furthermore, the most common triad combination consisted of cardiovascular diseases, gout, and hyperuricemia, which was verified in the mountain and coastal areas. CONCLUSION: These observations of multimorbidity patterns, including the most frequent multimorbidity and associations, will help healthcare providers develop healthcare plans that improve the effectiveness of multimorbidity management.
format Online
Article
Text
id pubmed-10192874
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-101928742023-05-19 Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study Hu, Yaoda He, Huijing Ou, Qiong Nai, Jing Pan, Li Chen, Xingming Tu, Ji Zeng, Xuejun Pei, Guo Wang, Longlong Lin, Binbin Liu, Qihang Shan, Guangliang Front Public Health Public Health BACKGROUND: Variations in the prevalence and pattern of multimorbidity might be attributable to lifestyle and environmental factors. This study was performed to determine the prevalence of common chronic diseases and to reveal multimorbidity patterns among adults in Guangdong province with Chaoshan, Hakka, and island cultures. METHODS: We used data collected at the baseline survey (April–May 2021) of the Diverse Life-Course Cohort study and included 5,655 participants aged ≥20 years. Multimorbidity was defined as the presence of two or more of the 14 chronic diseases collected by self-reports, physical examinations, and blood tests. Multimorbidity patterns were explored by association rule mining (ARM). RESULTS: Overall, 40.69% of participants had multimorbidity, and the prevalence among coastland (42.37%) and mountain residents (40.36%) was higher than that among island residents (37.97%). The prevalence of multimorbidity increased rapidly with higher age groups and showed an inflection point at 50 years, beyond which >50% of the middle-aged and older adults had multimorbidity. The proportion of people with two chronic diseases accounted for most cases of multimorbidity, and the strongest association was found between hyperuricemia and gout (lift of 3.26). The most prevalent multimorbidity pattern was dyslipidemia and hyperuricemia in the coastland areas and dyslipidemia combined with hypertension in the mountain and island areas. Furthermore, the most common triad combination consisted of cardiovascular diseases, gout, and hyperuricemia, which was verified in the mountain and coastal areas. CONCLUSION: These observations of multimorbidity patterns, including the most frequent multimorbidity and associations, will help healthcare providers develop healthcare plans that improve the effectiveness of multimorbidity management. Frontiers Media S.A. 2023-05-04 /pmc/articles/PMC10192874/ /pubmed/37213602 http://dx.doi.org/10.3389/fpubh.2023.1163791 Text en Copyright © 2023 Hu, He, Ou, Nai, Pan, Chen, Tu, Zeng, Pei, Wang, Lin, Liu and Shan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Hu, Yaoda
He, Huijing
Ou, Qiong
Nai, Jing
Pan, Li
Chen, Xingming
Tu, Ji
Zeng, Xuejun
Pei, Guo
Wang, Longlong
Lin, Binbin
Liu, Qihang
Shan, Guangliang
Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study
title Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study
title_full Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study
title_fullStr Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study
title_full_unstemmed Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study
title_short Prevalence of common chronic disease and multimorbidity patterns in Guangdong province with three typical cultures: analysis of data from the Diverse Life-Course Cohort study
title_sort prevalence of common chronic disease and multimorbidity patterns in guangdong province with three typical cultures: analysis of data from the diverse life-course cohort study
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192874/
https://www.ncbi.nlm.nih.gov/pubmed/37213602
http://dx.doi.org/10.3389/fpubh.2023.1163791
work_keys_str_mv AT huyaoda prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT hehuijing prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT ouqiong prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT naijing prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT panli prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT chenxingming prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT tuji prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT zengxuejun prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT peiguo prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT wanglonglong prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT linbinbin prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT liuqihang prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy
AT shanguangliang prevalenceofcommonchronicdiseaseandmultimorbiditypatternsinguangdongprovincewiththreetypicalculturesanalysisofdatafromthediverselifecoursecohortstudy