North–South Disparities in Multimorbidity Revealed by Association Rule and Sequential Pattern Mining: Evidence From the China National Health Survey (CNHS)
7 affiliations
- 1Department of Epidemiology and Statistics, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- 2State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
- 3Sleep Center, Department of Respiratory and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- 4Department of Epidemiology and Biostatistics, School of Public Health of Jilin University, Changchun, China
- 5Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, China
- 6Precision and Intelligence Medical Imaging Lab, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- 7School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Abstract
Background: North-south differences in context and lifestyle may shape multimorbidity patterns in China. We compared multimorbidity between two northern (Liaoning, Jilin) and two southern (Guangdong, Jiangsu) CNHS provinces in eastern China using association rule mining (ARM) and sequential pattern mining (SPM).
Methods: We analyzed 19,067 adults (≥20 years) and 20 chronic conditions. ARM identified co-occurrence rules and reported support (proportion with the combination), confidence (P(consequent|antecedent)), and lift (observed/expected co-occurrence; >1 indicates positive association). SPM summarized common diagnosis-order sequences using sequence support (percentage of participants exhibiting an ordered sequence). Sensitivity analyses were restricted to self-reported physician diagnoses.
Results: Multimorbidity prevalence was 37.85% (age-standardized 32.84%), higher in northern than southern provinces (41.39% vs 34.08%; standardized 35.41% vs 31.04%). Hypertension, hyperuricemia, and diabetes were most common. Cardiovascular/cerebrovascular conditions were more frequent in the north, whereas anemia and kidney stones were more common in the south. ARM suggested metabolic–renal clustering in the south (eg, CKD→gout, support = 1.18%, confidence = 26.14%, lift = 2.60; gout+anemia→CKD, support = 0.55%, confidence = 38.89%, lift = 3.71) and musculoskeletal–cardiovascular links in the north (eg, osteoarthritis→spinal disease, support = 0.52%, confidence = 24.69%, lift = 2.22; CTRD→CHD, support = 0.63%, confidence = 28.24%, lift = 1.26). Common SPM sequences included hypertension→hyperuricemia (24.22%) and hypertension→diabetes→hyperuricemia (5.32%); hypertension→hyperuricemia→CKD was more frequent in the south (2.28%), while hypertension→CHD→hyperuricemia was more frequent in the north (5.70%). Sensitivity analyses showed broadly consistent regional contrasts.
Conclusion: Multimorbidity burden and structure differed between the northern and southern provinces, supporting province-tailored prevention and integrated care.
Related
- Longitudinal sleep duration trajectories and their association with cardio-renal-metabolic multimorbidity risk in postmenopausal women: evidence from the CHARLS study.
- Independent association of the CHG index with cardiometabolic multimorbidity: real-world evidence from community and clinical datasets.
- Physical activity, sleep duration, and multimorbidity: a cross-sectional study of prevalence associations and association rule mining of multimorbidity patterns
- Hyperlocal PM2.5 Exposure and Health Burden Disparities Revealed by a Taxi-Based Mobile Monitoring Platform in Shenzhen
- Estimated cardiorespiratory fitness and incident cardiometabolic multimorbidity: evidence from the CHARLS cohort
BibTeX
@article{chen2026northsouth,
title = {{North–South Disparities in Multimorbidity Revealed by Association Rule and Sequential Pattern Mining: Evidence From the China National Health Survey (CNHS)}},
author = {Zhili Chen and Yaoda Hu and Huijing He and Qiong Ou and Yawen Liu and Tan Xu and Ji Tu and Zhiming Lu and Zichao Wang and Da Xu and Qing Wang and Zhujie Ran and Mengwei Zhang and Guangliang Shan},
journal = {Journal of Epidemiology},
year = {2026},
month = nov,
doi = {10.2188/jea.je20260009},
url = {https://doi.org/10.2188/jea.je20260009},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - North–South Disparities in Multimorbidity Revealed by Association Rule and Sequential Pattern Mining: Evidence From the China National Health Survey (CNHS)
AU - Zhili Chen
AU - Yaoda Hu
AU - Huijing He
AU - Qiong Ou
AU - Yawen Liu
AU - Tan Xu
AU - Ji Tu
AU - Zhiming Lu
AU - Zichao Wang
AU - Da Xu
AU - Qing Wang
AU - Zhujie Ran
AU - Mengwei Zhang
AU - Guangliang Shan
PY - 2026
DA - 2026/11/05
JO - Journal of Epidemiology
DO - 10.2188/jea.je20260009
UR - https://doi.org/10.2188/jea.je20260009
AB - Background: North-south differences in context and lifestyle may shape multimorbidity patterns in China. We compared multimorbidity between two northern (Liaoning, Jilin) and two southern (Guangdong, Jiangsu) CNHS provinces in eastern China using association rule mining (ARM) and sequential pattern mining (SPM). Methods: We analyzed 19,067 adults (≥20 years) and 20 chronic conditions. ARM identified co-occurrence rules and reported support (proportion with the combination), confidence (P(consequent|antecedent)), and lift (observed/expected co-occurrence; >1 indicates positive association). SPM summarized common diagnosis-order sequences using sequence support (percentage of participants exhibiting an ordered sequence). Sensitivity analyses were restricted to self-reported physician diagnoses. Results: Multimorbidity prevalence was 37.85% (age-standardized 32.84%), higher in northern than southern provinces (41.39% vs 34.08%; standardized 35.41% vs 31.04%). Hypertension, hyperuricemia, and diabetes were most common. Cardiovascular/cerebrovascular conditions were more frequent in the north, whereas anemia and kidney stones were more common in the south. ARM suggested metabolic–renal clustering in the south (eg, CKD→gout, support = 1.18%, confidence = 26.14%, lift = 2.60; gout+anemia→CKD, support = 0.55%, confidence = 38.89%, lift = 3.71) and musculoskeletal–cardiovascular links in the north (eg, osteoarthritis→spinal disease, support = 0.52%, confidence = 24.69%, lift = 2.22; CTRD→CHD, support = 0.63%, confidence = 28.24%, lift = 1.26). Common SPM sequences included hypertension→hyperuricemia (24.22%) and hypertension→diabetes→hyperuricemia (5.32%); hypertension→hyperuricemia→CKD was more frequent in the south (2.28%), while hypertension→CHD→hyperuricemia was more frequent in the north (5.70%). Sensitivity analyses showed broadly consistent regional contrasts. Conclusion: Multimorbidity burden and structure differed between the northern and southern provinces, supporting province-tailored prevention and integrated care.
SN - 0917-5040
SN - 1349-9092
ER -