Anxiety and influencing factors of common chronic disease patients in the community based on the perspective of psychosomatic medicine
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摘要:
目的 基于心身医学视角，研究高血压、冠心病、关节炎患者的焦虑情绪情况，为社区慢性病患者的综合管理提供参考依据。 方法 采用分层多阶段随机抽样方法，收集2022年6月—2023年4月于上海市浦东、静安及宝山区3个社区卫生服务中心全科门诊就诊的患有高血压和(或)冠心病和(或)关节炎患者的相关信息，采用汉密尔顿焦虑量表(HAMA)进行评分。采用多因素二元多模型logistic回归分析研究焦虑情绪的影响因素。 结果 415例患者中HAMA评分正常者155例(37.3%)，评分异常者260例(62.7%)，包括可能有焦虑情绪153例(36.9%)与肯定有焦虑情绪107例(25.8%)。不同疾病及不同疾病组合间两两比较，高血压组焦虑评分异常发生率低于高血压合并冠心病组、高血压合并关节炎组和高血压合并冠心病合并关节炎组。中介效应分析显示，慢性病症状在患病数量对焦虑评分异常影响中具有中介效应，占比16.564%。多因素二元多模型logistic回归分析显示，患病数量在3个模型中均为焦虑评分异常的独立影响因素(OR=2.544，95% CI：1.750~3.698；OR=2.426，95% CI: 1.501~3.921；OR=2.266，95% CI: 1.341~3.828，均P＜0.05)。 结论 社区多病共存、伴有症状的患者需注意焦虑情绪评估，进而采取具有针对性的干预措施。 Abstract:Objective To provide a reference for the comprehensive management of chronic disease patients in the community, based on the perspective of psychosomatic medicine. To this end, the study investigates the anxiety levels of patients with hypertension, coronary heart disease (CHD), and knee osteoarthritis. Methods A stratified multi-stage random sampling method was employed to collect relevant information on patients with hypertension and/or coronary heart disease and/or knee osteoarthritis who visited three community health service centers in Pudong, Jing ' an and Baoshan District of Shanghai. The study period was from June 2022 to April 2023. The Hamilton anxiety scale (HAMA) was used to evaluate the patients. Multivariate binary multiple model logistic regression was used to analyze the influencing factors of anxiety. Results Among the 415 patients, 155 cases (37.3%) had normal HAMA scores, while 260 cases (62.7%) had abnormal HAMA scores. Of these, 153 cases (36.9%) had probable anxiety and 107 cases (25.8%) had certain anxiety. The incidence of abnormal anxiety scores in the hypertension group was lower than that in the hypertension combined with CHD group, the hypertension combined with arthritis group and the hypertension combined with CHD combined with arthritis group. The mediation effect analysis revealed that chronic disease symptoms had a mediating effect on the impact of the number of diseases on abnormal anxiety scores, accounting for 16.564%. Multivariate binary multiple model logistic regression analysis demonstrated that the number of illnesses was an independent factor of abnormal anxiety score in all three models (OR=2.544, 95% CI: 1.750-3.698; OR=2.426, 95% CI: 1.501-3.921; OR=2.266, 95% CI: 1.341-3.828, all P < 0.05). Conclusion Patients with multiple coexisting diseases and accompanying symptoms in the community should be evaluated for anxiety and receive targeted intervention measures. -
表 1 汉密尔顿焦虑量表评分正常组与异常组慢性病患者一般资料比较
Table 1. Comparison of general data of chronic disease patients between normal group and abnormal group of Hamilton Anxiety Scale score
组别 例数 性别[例(%)] 年龄(x ±s，岁) BMI(x ±s) 婚姻状况[例(%)] 受教育程度[例(%)] 男性 女性 已婚 离异 丧偶 文盲 小学或初中 高中或中专 大专及以上 正常组 155 87(56.1) 68(43.9) 63.71±8.86 24.26±1.93 143(92.3) 1(0.6) 11(7.1) 12(7.7) 67(43.3) 64(41.3) 12(7.7) 异常组 260 120(46.2) 140(53.8) 68.75±8.77 24.55±2.98 205(78.8) 1(0.4) 54(20.8) 32(12.3) 159(61.2) 60(23.1) 9(3.4) 统计量 3.865a 5.637b 1.093b 13.810a -4.438c P值 0.049 0.001 0.275 0.001 0.001 组别 例数 职业[例(%)] 饮酒[例(%)] 吸烟[例(%)] 国家事业单位 公司、企业职员 工人 农民 离退休 其他 否 是 否 是 正常组 155 2(1.3) 8(5.2) 19(12.2) 46(29.7) 77(49.7) 3(1.9) 111(71.6) 44(28.4) 98(63.2) 57(36.8) 异常组 260 0 6(2.3) 30(11.5) 77(29.6) 146(56.2) 1(0.4) 190(73.1) 70(26.9) 171(65.8) 89(34.2) 统计量 8.923a 0.104a 0.275a P值 0.112 0.747 0.600 组别 例数 同居者[例(%)] 目前年收入[例(%)] 患慢性病数量(x ±s，种) 合并慢性病症状[例(%)] 独居 配偶和(或)子女 其他亲属 保姆 其他 5万元以内 6~10万元 >10~20万元 20万元以上 无 有 正常组 155 12(7.7) 141(91.1) 0 1(0.6) 1(0.6) 93(60.0) 38(24.6) 23(14.8) 1(0.6) 1.37±0.52 127(81.9) 28(18.1) 异常组 260 31(11.9) 223(85.7) 2(0.8) 3(1.2) 1(0.4) 194(74.6) 45(17.3) 18(6.9) 3(1.2) 1.67±0.60 111(42.7) 149(57.3) 统计量 3.527a -3.187c 5.320b 61.141a P值 0.474 0.001 0.001 0.001 注：a为χ2值，b为t值，c为Z值。 
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表 2 不同疾病及不同疾病组合间焦虑情况比较[例(%)]
Table 2. Comparison of anxiety among different diseases and different combinations of diseases [cases (%)]
疾病或疾病组合 焦虑评分 总计 正常 异常 高血压 72(55.8) 57(44.2) 129(100.0) 冠心病 7(31.8) 15(68.2) 22(100.0) 关节炎 21(40.4) 31(59.6) 52(100.0) 高血压合并冠心病a 16(18.2) 72(81.8) 88(100.0) 高血压合并关节炎a 33(34.0) 64(66.0) 97(100.0) 冠心病合并关节炎 3(50.0) 3(50.0) 6(100.0) 高血压合并冠心病合并关节炎a 3(14.3) 18(85.7) 21(100.0) 合计 155(37.3) 260(62.7) 415(100.0) 注：组间整体比较，χ2=38.748，P＜0.001。与高血压比较，aP＜0.05。
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表 3 中介效应显著性Bootstrap检验分析结果
Table 3. Bootstrap test analysis results of the significance of the mediating effect
路径 效应 Bootstrap检验分析结果 统计量 P值 估计值 95% CI SE c 总效应 0.201 0.125~0.278 0.039 5.142a 0.001 C' 直接效应 0.168 0.096~0.240 0.037 4.583a 0.001 a×b 中介效应 0.033 0.005~0.079 0.019 1.798b 0.072 注：统计量中，a为t值，b为Z值。
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表 4 各变量赋值情况
Table 4. Assignment of variables
变量 赋值方法 焦虑评分 正常=0；异常=1 性别 男性=0；女性=1 年龄 连续性变量，以实际值赋值 BMI 连续性变量，以实际值赋值 婚姻状况 以“已婚”为基础水平设置哑变量，已婚=0，0；离异=1，0；丧偶=0，1 受教育程度 文盲=1；小学或初中=2；高中或中专=3；大专及以上=4 职业 以“国家事业单位”为基础水平设置哑变量，国家事业单位=(0，0，0，0，0)；公司、企业职员=(1，0，0，0，0)；工人=(0，1，0，0，0，0)；农民=(0，0，1，0，0)；离退休=(0，0，0，1，0)；其他=(0，0，0，0，0，1) 同居人 以“独居”为基础水平设置哑变量，独居=(0，0，0，0)；配偶和(或)子女=(1，0，0，0)；其他亲属=(0，1，0，0)；保姆=(0，0，1，0)，其他=(0，0，0，1) 目前年收入 5万元以内=1；6~10万元=2；>10~20万元=3；20万元以上=4 吸烟史 否=0；是=1 饮酒史 否=0；是=1 慢性病症状 无=0；有=1 患病个数 连续性变量，以实际值赋值
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表 5 患病数量对焦虑评分异常影响的多因素二元多模型logistic回归分析
Table 5. Multivariate binary multi-model logistic regression analysis of the influence of the number of diseases on abnormal anxiety scores
模型 B SE Waldχ2 P值 OR值 95% CI 模型1 0.934 0.191 23.947 0.001 2.544 1.750~3.698 模型2 0.886 0.245 13.085 0.001 2.426 1.501~3.921 模型3 0.818 0.268 9.347 0.002 2.266 1.341~3.828 注：模型1未调整任何变量；模型2在模型1的基础上，调整性别、年龄、BMI、婚姻状况、受教育程度、职业、同居者、目前年收入、吸烟、饮酒等变量；模型3在模型2的基础上，进一步调整了合并慢性病症状。
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