CHARLS数据库研究套路汇总

官方
阅读 99 0 收藏 0 2025-06-06 19:01:00

套路 1:生活方式和中介分析

套路精髓:生活方式(包括运动、吸烟、饮酒、睡眠、BMI、社交活动等)

适用场景:老年人群体、心血管疾病、身体多病性、抑郁症等

 案例文章 

标题:Associations of healthy lifestyle and three latent socioeconomic status patterns with physical multimorbidity among middle-aged and older adults in China

期刊:Preventive MedicineIF=4.3

PMID:37660757

标题:Longitudinal association of allostatic load with depressive symptoms among urban adults: Healthy Aging in Neighborhoods of Diversity across the Life Span study

期刊:PsychoneuroendocrinologyIF=3.4

PMID:36640448

标题:The role of lifestyle in the association between long-term ambient air pollution exposure and cardiovascular disease: a national cohort study in China

期刊:BMC MedicineIF=7.0

PMID:38439026

总结:采用中介分析(如竞争性中介、部分中介),验证健康生活方式在“社会/环境暴露-健康结局链中的中介作用,通过改善生活方式缓解健康不平等或环境危害。

套路 2:预测模型与风险因素

套路精髓:

目标:通过构建预测模型识别健康风险

适用场景:视力障碍、虚弱风险、卒中再发风险、高脂血症风险等

 案例文章 

标题:Determinants of Visual Impairment Among Chinese Middle-Aged and Older Adults: Risk Prediction Model Using Machine Learning Algorithms

期刊:JMIR AgingIF=5.0

PMID:39382570

标题:Development and validation of a risk prediction model for frailty in patients with diabetes

期刊:BMC GeriatricsIF=3.4

PMID:36973658

标题:Development and Internal Validation of a Model Predicting the Risk of Recurrent Stroke for Middle-Aged and Elderly Patients: A Retrospective Cohort Study 

期刊:World NeurosurgeryIF=1.9

PMID:36270594

标题:Development and validation of a hyperlipidemia risk prediction model for middle-aged and older adult Chinese using 2015 CHARLS data  

期刊:Front Public HealthIF=3.0

PMID:39906294

总结:通过多维度预测模型揭示了中老年健康问题的复杂性。突破了单一因素分析的局限,为精准预防提供了科学依据,展现了多学科交叉研究在老年健康领域的独特价值。

套路 3:变量之间的交互效应

套路精髓:探讨多种因素之间的交互效应对健康结局的影响

 案例文章 

标题:Interacting and joint effects of triglyceride-glucose index (TyG) and body mass index on stroke risk and the mediating role of TyG in middle-aged and older Chinese adults: a nationwide prospective cohort study

期刊:Cardiovascular DiabetologyIF=8.5

PMID:38218819

标题:CHARLS insights into the impact of dual interactions of chronic diseases on depression in middle-aged and elderly individuals

期刊:Scientific ReportsIF=3.8

PMID:40216835

标题:Air pollution increases the risk of frailty: China Health and Retirement Longitudinal Study (CHARLS)

期刊:Journal of Hazardous MaterialsIF=12.2

PMID:40187242

标题:Interaction of sleep duration and depression on cardiovascular disease: a retrospective cohort study

期刊:BMC Public HealthIF=3.5

PMID:36109743

总结:使用CHARLS数据库,深入探讨多种健康因素之间的交互作用。为理解中老年人群体中健康风险的综合影响提供重要依据有助于揭示疾病发生的多维因素,推动更有效的健康干预方案的制定。

套路 4:疾病的动态变化与长期随访

套路精髓:通过长期随访数据,研究疾病的动态变化及其与不同健康结果的关联

适用场景:慢性疾病、老年人群、健康衰退等

 案例文章 

标题:Changes in sarcopenia and incident cardiovascular disease in prospective cohorts

期刊:BMC MedicineIF=7.0

PMID:39736721

标题:Association between cumulative changes of thetriglyceride glucose index and incidence of stroke in apopulation with cardiovascular-kidney-metabolicsyndrome stage 0-3: a nationwide prospective cohortstudy

期刊:Cardiovascular diabetologyIF=8.5

PMID:40355933

标题:Bidirectional transitions of sarcopenia states in older adults: The longitudinal evidence from CHARLS

期刊:Journal of Cachexia Sarcopenia And MuscleIF=9.4

PMID:39001569

标题:Association between changes in depressive symptoms and falls: The China health and retirement longitudinal study (CHARLS)

期刊:Journal of Affective DisordersIF=4.9

PMID:37683944

标题:Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts

期刊J Cachexia Sarcopenia MuscleIF=9.4

PMID:36575595

总结:利用CHARLS提供的多波数据结构,可构建个体在特定健康状态之间的转变路径,通过Cox模型、多状态马尔可夫模型、混合效应模型等工具,揭示健康状态的动态变化趋势及其对疾病结局的影响。


评论列表

发表评论