机构:[1]Center for Data Science in Health and Medicine, Peking University, Beijing, China[2]Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States[3]Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States[4]The Second Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China深圳市中医院深圳医学信息中心
Background: The rise in the number of patients with chronic kidney disease (CKD) and consequent end-stage renal disease necessitating renal replacement therapy has placed a significant strain on health care. The rate of progression of CKD is influenced by both modifiable and unmodifiable risk factors. Identification of modifiable risk factors, such as lifestyle choices, is vital in informing strategies toward renoprotection. Modification of unhealthy lifestyle choices lessens the risk of CKD progression and associated comorbidities, although the lifestyle risk factors and modification strategies may vary with different comorbidities (eg, diabetes, hypertension). However, there are limited studies on suitable lifestyle interventions for CKD patients with comorbidities. Objective: The objectives of our study are to (1) identify the lifestyle risk factors for CKD with common comorbid chronic conditions using a US nationwide survey in combination with literature mining, and (2) demonstrate the potential effectiveness of association rule mining (ARM) analysis for the aforementioned task, which can be generalized for similar tasks associated with noncommunicable diseases (NCDs). Methods: We applied ARM to identify lifestyle risk factors for CKD progression with comorbidities (cardiovascular disease, chronic pulmonary disease, rheumatoid arthritis, diabetes, and cancer) using questionnaire data for 450,000 participants collected from the Behavioral Risk Factor Surveillance System (BRFSS) 2017. The BRFSS is a Web-based resource, which includes demographic information, chronic health conditions, fruit and vegetable consumption, and sugar- or salt-related behavior. To enrich the BRFSS questionnaire, the Semantic MEDLINE Database was also mined to identify lifestyle risk factors. Results: The results suggest that lifestyle modification for CKD varies among different comorbidities. For example, the lifestyle modification of CKD with cardiovascular disease needs to focus on increasing aerobic capacity by improving muscle strength or functional ability. For CKD patients with chronic pulmonary disease or rheumatoid arthritis, lifestyle modification should be high dietary fiber intake and participation in moderate-intensity exercise. Meanwhile, the management of CKD patients with diabetes focuses on exercise and weight loss predominantly. Conclusions: We have demonstrated the use of ARM to identify lifestyle risk factors for CKD with common comorbid chronic conditions using data from BRFSS 2017. Our methods can be generalized to advance chronic disease management with more focused and optimized lifestyle modification of NCDs.
基金:
National Administration of Traditional Chinese Medicine (Pilot Project on Clinical Collaboration of Major and Difficult Diseases); Guangdong Provincial Hospital of Chinese Medicine Program [YN2018ZWB04]
语种:
外文
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2018]版:
大类|2 区医学
小类|1 区卫生保健与服务1 区医学:信息
最新[2025]版:
大类|2 区医学
小类|2 区卫生保健与服务2 区医学:信息
JCR分区:
出版当年[2017]版:
Q1HEALTH CARE SCIENCES & SERVICESQ1MEDICAL INFORMATICS
最新[2023]版:
Q1HEALTH CARE SCIENCES & SERVICESQ1MEDICAL INFORMATICS
第一作者机构:[1]Center for Data Science in Health and Medicine, Peking University, Beijing, China[2]Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States
通讯作者:
通讯机构:[4]The Second Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China[*1]The Second Medical College Guangzhou University of Chinese Medicine No 111 Dade Road Guangzhou, China
推荐引用方式(GB/T 7714):
Peng Suyuan,Shen Feichen,Wen Andrew,et al.Detecting Lifestyle Risk Factors for Chronic Kidney Disease With Comorbidities: Association Rule Mining Analysis of Web-Based Survey Data[J].JOURNAL OF MEDICAL INTERNET RESEARCH.2019,21(12):doi:10.2196/14204.
APA:
Peng, Suyuan,Shen, Feichen,Wen, Andrew,Wang, Liwei,Fan, Yadan...&Liu, Hongfang.(2019).Detecting Lifestyle Risk Factors for Chronic Kidney Disease With Comorbidities: Association Rule Mining Analysis of Web-Based Survey Data.JOURNAL OF MEDICAL INTERNET RESEARCH,21,(12)
MLA:
Peng, Suyuan,et al."Detecting Lifestyle Risk Factors for Chronic Kidney Disease With Comorbidities: Association Rule Mining Analysis of Web-Based Survey Data".JOURNAL OF MEDICAL INTERNET RESEARCH 21..12(2019)