中老年人疼痛和抑郁症状的关系：一项交叉滞后的纵向分析

夏红红; 旺姆; 张红霞; 付铭; 万洋; 邱培媛

doi:10.12182/20260760603

中老年人疼痛和抑郁症状的关系：一项交叉滞后的纵向分析

Relationship Between Pain and Depressive Symptoms in Middle-aged and Older Chinese Adults: A Cross-Lagged Longitudinal Analysis

摘要

摘要:
目的探究我国中老年人疼痛与抑郁症状之间的纵向关联，为中老年人疼痛与抑郁的管理提供科学依据。
方法利用中国健康与养老追踪调查（China Health and Retirement Longitudinal Study, CHARLS）2011-2020年共5次随访数据，纳入年龄≥45岁且完整参与5次调查的中老年人7 876例。采用随机截距交叉滞后面板模型（random intercept cross-lagged panel model, RI-CLPM）分析疼痛与抑郁症状在5个时间点的纵向关系。模型分步控制了以下混杂因素：非时变因素包括性别、户口和婚姻状况；时变因素包括年龄、共病、日常生活活动能力评分、吸烟、饮酒及体力活动情况。
结果 RI-CLPM模型拟合良好（CFI=0.906，TLI=0.879，RMSEA=0.036，SRMR=0.060）。在控制个体间差异后，RI-CLPM结果显示疼痛对抑郁症状的滞后效应在T1→T5各时间段均具有统计学意义〔T1→T2：β=0.043（95% CI：0.020～0.067）；T2→T3：β=0.047（95% CI：0.023～0.070）；T3→T4：β=0.056（95% CI：0.034～0.078）；T4→T5：β=0.050（95% CI：0.028～0.071）〕；抑郁症状对疼痛的滞后效应在T2→T5阶段有统计学意义，且抑郁症状对疼痛的预测作用更大〔T2→T3：β=0.121（95% CI：0.099～0.143）；T3→T4：β=0.112（95% CI：0.091～0.134）；T4→T5：β=0.070（95% CI：0.049～0.090）〕。
结论疼痛与抑郁症状在时间上存在双向预测关系，疼痛对抑郁症状的预测效应稳定存在，而抑郁症状对疼痛的预测效应更强，提示在疼痛患者的诊疗过程中应注重抑郁症状的筛查。

Abstract:
Objective To investigate the longitudinal association between pain and depressive symptoms in middle-aged and older adults in China, and to provide a scientific basis for the management of pain and depression in this population.
Methods Data from 5 follow-up waves (conducted between 2011 and 2020) of the China Health and Retirement Longitudinal Study (CHARLS) were used in the study. A total of 7876 middle-aged and older adults aged 45 years or older who completed all 5 surveys were enrolled. A Random Intercept Cross-Lagged Panel Model (RI-CLPM) was applied to analyze the longitudinal relationship between pain and depressive symptoms across the 5 time points. The potential confounders controlled for in the model in a stepwise manner included time-invariant variables (sex, marital status, and household registration) and time-varying covariates (age, comorbidity, activities of daily living scores, smoking, drinking, and physical activity).
Results The RI-CLPM demonstrated a good model fit (Comparative Fit Index CFI = 0.906, Tucker and Lewis Index TLI = 0.879, Root Mean Square Error of Approximation RMSEA = 0.036, and Standardized Root Mean Square Residual SRMR = 0.060). After controlling for between-person differences, the RI-CLPM results showed that the lagged effects of pain on depressive symptoms were statistically significant across all time points from T1 to T5 (T1 to T2: β = 0.043, 95% CI 0.020–0.067; T2 to T3: β = 0.047, 95% CI 0.023–0.070; T3 to T4: β = 0.056, 95% CI 0.034–0.078; T4 to T5: β = 0.050, 95% CI 0.028–0.071). Additionally, the lagged effects of depressive symptoms on pain were statistically significant from T2 to T5 (T2 to T3: β = 0.121, 95% CI 0.099–0.143; T3 to T4: β = 0.112, 95% CI 0.091–0.134; T4 to T5: β = 0.070, 95% CI 0.049–0.090), and the predictive effects of depressive symptoms on pain were greater.
Conclusion Pain and depressive symptoms have a bidirectional predictive relationship over time. The predictive performance of pain for depressive symptoms remains stable over time, while the predictive performance of depressive symptoms for pain is stronger. These findings suggest that screening for depressive symptoms should be emphasized in the diagnosis and treatment of patients presenting with pain.

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