Development trajectory of depression in diabetes patients in middle-aged and elderly Chinese
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摘要:
目的 研究旨在识别我国中老年糖尿病患者的抑郁发展轨迹，检验其抑郁轨迹是否存在性别和城乡差异，为糖尿患者抑郁症状的预防与管理提供依据。 方法 采用中国健康与养老追踪调研中2011—2018年4期纵向数据，选择≥45岁确诊糖尿病患者数据进行分析。 应用增长混合模型开展潜类别模型拟合性评估，分析男性与女性、城市与农村中老年糖尿病患者抑郁症状的发展轨迹。 结果 共481名中老年人纳入数据分析，男性（7.17～7.81）和城市（7.50～8.38）糖尿病患者在各阶段抑郁症状得分均值普遍低于女性（9.07～10.27）和农村（9.06～10.11）患者。 男性糖尿病患者抑郁症状轨迹可划分为高–降组与低–升组，女性患者可划分为恒高组和低–升组；城市患者抑郁症状轨迹可划分为高–降组和低–升组，农村患者可划分为恒低组和低–升组。 结论 我国中老年糖尿病患者抑郁症状整体有增长趋势，不同群体抑郁症状轨迹具有异质性。 女性和农村糖尿病患者抑郁症状更为严重，是心理干预措施的重点关注对象。 Abstract:Objective To identify the development trajectory of depression of diabetes patients in middle-aged and elderly Chinese, explore the possible gender, urban-rural area specific differences in the development trajectory of depression in this population, and provide evidence for the prevention and management of depression in diabetes patients. Methods The data from four phases of a longitudinal health study in elderly population in China from 2011 to 2018 were used to analyze the development trajectory of depression of diabetes patients aged ≥45 years. The Growth Mix Model was used to evaluate the fitness of the potential models, and the development trajectories of depression in men and women, in urban and rural residents in this population were analyzed. Results A total of 481 middle-aged and elderly diabetes patients were included in the analysis. The results showed that the mean depressive symptom scores of men (7.17–7.81) and urban residents (7.50–8.38) were generally lower than those of women (9.07–10.27) and rural residents (9.06–10.11). The development trajectory of depression showed high-decreasing and low-increasing patterns in men, high-stable and low-increasing patterns in women, high-decreasing and low-increasing patterns in urban residents and low-stable and low-increasing patterns in rural residents. Conclusion The incidence of depressive symptoms in middle-aged and elderly diabetes patients in China showed an increasing trend, and the development trajectories of depression in different groups were heterogeneous. Women and rural residents had more severe depressive symptoms, suggesting the necessity of psychological intervention in this group. -
Key words:
- Middle-aged and elderly people /
- Diabetes /
- Depressive trajectory /
- Depressive symptom
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表 1 481例中老年糖尿病患者基本特征
Table 1. Basic characteristics of 481 cases of middle-aged and elderly diabetes patients
人口学变量 类别 糖尿病患者（例） 构成比（%） 性别 男性 210 43.66 女性 271 56.34 居住地 城镇 254 52.81 农村 227 47.19 婚姻 在婚 435 90.44 不在婚姻 46 9.56 学历 初中及以下 407 84.61 高中 58 12.06 大学及以上 16 3.33 
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表 2 481例中老年糖尿病患者各时间点抑郁症状得分以及相关性分析
Table 2. Depression scores and its correlation analysis at each stage in 481 middle-aged and elderly diabetes patients
变量 2011年 2013年 2015年 2018年 性别划分 T1 – 0.51a 0.49a 0.43a T2 0.56a – 0.49a 0.43a T3
T40.48a
0.45a0.53a
0.39a–
0.50a0.52a
–男性
（均数±标准差）7.50±5.99 7.17±5.32 7.44±6.39 7.81±5.88 女性
（均数±标准差）9.28±6.48 9.07±6.07 9.97±6.50 10.27±6.95 城乡划分 T1 – 0.47a 0.46a 0.46a T2 0.59a – 0.49a 0.42a T3
T40.53a
0.42a0.54a
0.43a–
0.50a0.52a
–城市b
（均数±标准差）7.87±6.37 7.50±5.50 7.96±6.32 8.38±6.36 农村b
（均数±标准差）9.22±6.22 9.06±6.09 9.89±6.70 10.11±6.76 注：a. P<0.01；b, T1～T4. 2011、2013、2015、2018年4个时间点中老年糖尿患者的抑郁症状得分。“—”的连线形成相关系数的对角线。性别部分对角线以下为男性抑郁的相关系数，对角线以上为女性抑郁的相关系数；城乡部分对角线以下为城市抑郁的相关系数，对角线以上为农村抑郁的相关系数；−表示无数据
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表 3 以性别划分的增长混合模型拟合信息
Table 3. Gender specific fitting information of Growth Mixture Model
类别 K Log（L） AIC BIC aBIC Entropy LMR BLRT 分类概率 男性 类别1 9 −2 565.68 5 149.36 5 179.48 5 150.97 − − − − 类别2 12 −2 549.97 5 123.94 5 164.11 5 126.09 0.83 0.001 0.000 0.148/0.852 类别3 15 −2 542.44 5 114.88 5 165.09 5 117.56 0.87 0.318 0.010 0.128/0.848/0.024 类别4 18 −2 532.09 5 100.17 5 160.42 5 103.38 0.89 0.102 0.000 0.029/0.033/0.100/0.838 类别5 21 −2 527.88 5 097.75 5 168.04 5 101.50 0.82 0.333 0.190 0.015/0.090/0.028/0.153/0.714 女性 类别1 9 −3 418.79 6 855.59 6 888.01 6 859.47 − − − − 类别2 12 −3 404.72 6 833.44 6 876.66 6 838.61 0.74 0.097 0.000 0.236/0.764 类别3 15 −3 396.22 6 822.44 6 876.47 6 828.91 0.75 0.294 0.010 0.103/0.768/0.129 类别4 18 −3 390.33 6 816.67 6 881.51 6 824.43 0.79 0.235 0.040 0.188/0.018/0.731/0.063 类别5 21 −3 381.72 6 805.45 6 881.09 6 814.51 0.80 0.356 0.005 0.070/0.059/0.317/0.465/0.089 注：类别1～5分别表示将男性或女性群体划分为1～5个组，既类别1表示将群体划分为1个组，类别2表示将群体划分为2个组，依此类推。K为模型中自由估计的参数个数，Log（L）. 对数似然比，AIC. 艾凯克信息准则，BIC. 贝叶斯信息准则，aBIC. 调整后的贝叶斯信息准则，Entropy. 信息熵，LMR. 似然比检验指标Lo-Mendell-Rubin的缩写，BLRT. 基于Bootstrap的似然比检验；−表示无数据
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表 4 以城乡划分的增长混合模型拟合信息
Table 4. Urban-rural area specific fitting information of Growth Mixture Model
类别 K Log（L） AIC BIC aBIC Entropy LMR BLRT 分类概率 城市 类别1 9 −3128.85 6275.71 6307.54 6279.01 − − − − 类别2 12 −3100.49 6224.97 6267.42 6229.38 0.90 0.000 0.000 0.114/0.886 类别3 15 −3095.18 6220.36 6273.42 6225.86 0.88 0.280 0.045 0.036/0.114/0.850 类别4 18 −3085.64 6207.28 6270.95 6213.89 0.82 0.505 0.005 0.095/0.035/0.665/0.205 类别5 21 −3073.04 6188.08 6262.37 6195.79 0.88 0.297 0.000 0.035/0.028/0.606/0.075/0.256 农村 类别1 9 −2861.70 5741.39 5772.22 5743.69 − − − − 类别2 12 −2846.35 5716.70 5757.80 5719.77 0.80 0.000 0.000 0.841/0.159 类别3 15 −2840.21 5710.41 5761.79 5714.25 0.78 0.126 0.020 0.093/0.568/0.339 类别4 18 −2835.88 5707.77 5769.42 5712.37 0.77 0.400 0.145 0.167/0.119/0.075/0.639 类别5 21 −2831.12 5704.23 5776.16 5709.60 0.81 0.356 0.005 0.013/0.106/0.084/0.194/0.603 注：类别1～5分别表示将城市或农村群体划分为1～5个组，类别1表示将群体划分为1个组，类别2表示将群体划分为2个组，依此类推。K. 模型中自由估计的参数个数，Log（L）. 对数似然比，AIC. 艾凯克信息准则，BIC. 贝叶斯信息准则，aBIC. 调整后的贝叶斯信息准则，Entropy. 信息熵，LMR. 似然比检验指标Lo-Mendell-Rubin的缩写，BLRT. 基于Bootstrap的似然比检验；−表示无数据
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表 5 糖尿病患者抑郁症状的增长混合模型截距和斜率
Table 5. Intercepts and slopes from Growth Mixture Model for depression in diabetes patients
潜在类别 截距（α） 斜率（β） 参数估计值 $s\bar x$ t值 P值 参数估计值 $ s\bar x $ t值 P值 男性 高–降组 16.75 1.14 14.67 0.000 −0.79 0.23 −3.43 0.001 低–升组 5.63 0.39 14.64 0.000 0.20 0.07 3.11 0.002 女性 恒高组 16.44 1.36 12.10 0.000 −0.10 0.37 −0.27 0.791 低–升组 6.71 0.40 16.96 0.000 0.25 0.11 2.29 0.022 城市 高–降组 19.01 1.07 17.78 0.000 −0.82 0.26 −3.11 0.002 低–升组 5.97 0.31 19.59 0.000 0.22 0.06 3.57 0.000 农村 恒低组 8.60 0.42 20.55 0.000 −0.08 0.07 −1.14 0.256 低–升组 11.44 1.09 10.48 0.000 1.29 0.22 5.85 0.000
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