肾移植患者社会支持、生活质量及相关炎性介质的研究
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摘要
目的
1.探讨肾移植患者社会支持的状况；
2.探讨肾移植患者社会支持、医学应对方式、抑郁与生活质量的关系；
3.探讨肾移植患者社会支持与血压、炎性介质的关联。
方法
1.选择2009年9月至2009年12月在中南大学湘雅三医院门诊随诊的肾移植患者,符合入选标准并同意参加者均纳入研究对象,共确定162名患者进行问卷调查。调查问卷包括自编肾移植患者身心健康状况调查表、社会支持评定量表(SSRS)、医学应对问卷(MCMQ)、自评抑郁量表(SDS)和生活质量简表(SF-36)。并对58名参与问卷调查的随诊患者,采集血样检测白介素6(IL-6)、白介素8(IL-8)、C-反应蛋白(CRP)；
2.资料采用SPSS13.0统计软件及AMOS7.0统计软件进行分析,统计方法包括描述性统计分析、单因素分析、多元线性回归分析及结构方程模型分析。
结果
1.本研究共确定162名肾移植患者为研究样本,其中,男性114名(70.4%),女性49名(29.6%)；58名抽血检测患者,男性39名(67.2%),女性19名(32.8%)；
2.162名肾移植患者支持利用度得分与常模比较差异无统计学意义(t=0.400,P>0.05),社会支持总分(t=8.731,P=0.000)、客观支持得分(t=8.379,P=0.00)和主观支持得分(t=8.314,P=0.000)均高于常模；
3.与慢性病常模进行医学应对方式的比较,“面对”(t=8.230,P=0.000)、“回避”(t=14.210,P=0.000))维度得分高于常模；“屈服”屈服维度得分与常模差异无统计学意义(t=0.090,P>0.05),不同性别患者“面对”(t=0.545,P>0.05)、“回避”(t=-0.367,P>0.05)及“屈服”(t=-0.123,P>0.05)三个维度得分差异均无统计学意义；
4.社会支持的单因素分析结果显示：
(1)年龄与客观支持得分(rs=0.219,P<0.01)、主观支持得分(rs=0.243,P<0.01)及社会支持总分(rs=0.240,P<0.01)呈直线相关关系；与支持利用度得分无相关关系(rs=-0.049,P>0.05)；
(2)不同受教育程度患者社会支持总分(F=4.352,P<0.05)及客观支持得分(F=7.605,P<0.05)差异均有统计学意义,主观支持得分(F=0.855,P>0.05)及支持利用度得分(F=2.678,P>0.05)差异均无统计学意义；
(3)有配偶组社会支持总分(F=5.778,P<0.01)、客观支持得分(F=3.504,P<0.01)及主观支持得分(F=7.326,P<0.01)均高于无配偶组,差异有统计学意义；不同配偶组支持利用度得分差异无统计学意义(F=0.186,P>0.05)；
(4)不同职业组的客观支持得分(F=5.290,P<0.05)、主观支持得分(F=2.503,P<0.05)及社会支持总分(F=2.815,P<0.05)差异均有统计学意义；不同职业组的支持利用度得分差异无统计学意义(F=1.342,P>0.05);
(5)有固定经济来源组的客观支持得分(t=4.429,P<0.05)、支持利用度得分(t=2.064,P<0.05)及社会支持总分(t=3.026,P<0.05)均高于无固定经济来源组,差异有统计学意义；有固定经济来源组与无固定经济来源组主观支持得分差异无统计学意义(t=1.088,P>0.05)；
(6)医药费自付比例低于50%组在客观支持得分(t=3.518,P<0.05)、主观支持得分(t=2.589,P<0.05)、支持利用度得分(t=3.286,P<0.05)及社会支持总分(t=3.941,P<0.05)得分均高于自费比例超过50%组,差异均有统计学意义；
(7)对他人支持不同组的患者,其客观支持得分、主观支持得分及社会支持总分(F=5.672,P<0.05；F=3.819,P<0.05;F=6.107,P<0.05)差异均有统计学意义；支持利用度得分差异无统计学意义(F=1.551,P>0.05)；
(8)不同支持感知组的患者客观支持得分、主观支持得分及社会支持总分(F=3.745,P<0.05；F=3.089,P<0.05；F=5.172,P<0.05)差异均有统计学意义；支持利用度得分差异无统计学意义(F=2.978,P>0.05);
5.社会支持的多元线性回归分析显示：影响社会支持总分的因素有：婚姻、年龄、职业、受教育程度、医药费自付比例、感知支持,R2=0.484；影响客观支持得分的因素有：感知支持、家庭人口、婚姻、支持他人情况、“屈服”维度得分、受教育程度及有无固定经济来源,R2=0.345；影响主观支持得分的因素有：感知支持、职业、医学应对总分、婚姻、“屈服”维度得分、受教育程度、有无固定经济来源及医药费自付比例,R2=0.421；影响支持利用度得分的因素有：“屈服”维度得分、年龄、“回避”维度得分及医药费自付比例R2=0.221；
6.患者的抑郁总分为(47.58±9.04)分,高于常模(t=8.02,P<0.01)；
7.患者生活质量简表各维度与常模的比较结果显示：患者生命力维度与常模差异无统计学意义(t=0.009,P>0.05),其他七个维度(躯体功能、躯体角色、肌体疼痛、总健康、社会功能、情感角色、心理健康)的生活质量得分均低于常模(t=8.71,P=0.000；t=12.36,P=0.000；t=10.03,P=0.000；t=7.94,P=0.000；t=4.07,P=0.000；t=6.32,P=0.000；t=3.25,P=0.001)；
8.社会支持、医学应对方式、抑郁、生活质量的相关性：
(1)社会支持的3个维度得分均与抑郁呈负相关(r=-0.229；r=-0.183；r=-0.256；P均<0.05),客观支持得分与生活质量的8个维度得分(除去躯体功能和社会功能)呈正相关(r=0.191;r=0.183；r=0.206；r=0.216；r=0.180；r=0.236；P均<0.05),主观支持得分与生活质量的2个维度得分(总体健康和活力)呈正相关(r=0.208；r=0.205；P均<0.05),支持利用度得分与生活质量的2个维度得分(情感角色和心理健康)呈正相关(r=0.202;r=0.195；P均<0.05)；
(2)“屈服”维度得分与抑郁得分呈正相关(r=0.326,P<0.01),与生活质量的7个维度得分(躯体功能除外)呈负相关(r=-0.181；r=-0.221；r=-0.381；r=-0.388；r=-0.237；r=-0.292；r=-0.246；P均<0.05)；“面对”维度得分与社会支持的3个维度得分呈正相关(r=0.164;r=0.206;r=0.271;P均<0.05)；“屈服”维度得分与客观支持得分、主观支持得分呈负相关(r=-0.277；r=-0.292；P均<0.01)；
(3)抑郁得分与生活质量的7个维度得分(躯体功能除外)呈负相关(r=-0.212;r=-0.222;r=-0.364;r=-0.446;r=-0.233;r=-0.305;r=-0.303;P均<0.05)；
9.结构方程模型结果显示：“面对”的应对方式对社会支持有直接正向效应(β=0.248,P<0.01)；“屈服”的应对方式对社会支持有直接负向效应(β=-0.302,P<0.01)、对生活质量有直接负向效应(β=-0.326,P<0.01)、对抑郁有直接正向效应(β=0.346,P<0.01)；社会支持对生活质量有直接正向效应(β=0.220,P<0.01)、对抑郁有直接负向效应(β=-0.240,P<0.01)；抑郁对生活质量有直接负向效应(β=-0.320,P<0.01)；“面对”的应对方式可通过社会支持路径间接影响生活质量；“屈服”的应对方式可通过社会支持、抑郁、社会支持和抑郁路径间接影响生活质量；
10.对IL-6、IL-8、CRP与社会支持各维度进行Spearman相关分析,CRP与支持利用度得分呈负相关(r=-0.264,P<0.05)；IL-6与客观支持得分呈负相关关系(r=-0.222,P<0.05)；
11.对体重指数在正常范围内的55名患者的血压和社会支持各维度进行Spearman相关分析(双尾),血压与社会支持总分呈负相关关系(r=-0.290，P<0.05；r=-0.281,P<0.05)。
结论
1.肾移植患者的年龄、职业、受教育程度、婚姻、经济状况、抑郁、“屈服”的应对方式等影响社会支持和社会支持的感知；
2.个人期待值与实际获得社会支持的协调程度与客观支持得分、主观支持得分和社会支持总分有关；实际获得的支持少于个人期待值的患者,其客观支持得分、主观支持得分均少于与期望值相当或高于期望值的患者；
3.支持给予与医学应对方式、经济状况相关；
4.配偶／父母作为肾移植患者日常主要支持者、紧急状况求助者、健康代言人支持提供者身份的一致性较好；
5.社会支持对抑郁有直接负向效应,医学应对方式可通过社会支持间接影响肾移植患者的抑郁；
6.抑郁对生活质量直接负向效应,提示抑郁可降低肾移植患者的生活质量；
7.医学应对方式对肾移植患者生活质量有直接和间接效应；社会支持、抑郁作为中介变量调节医学应对方式与生活质量的关系；
8.肾移植患者中血清IL-6的水平与客观支持得分呈负相关关系；
9.肾移植患者血清CRP水平与患者支持利用度得分呈负相关关系。
10.血压与社会支持总分呈负相关关系。
Objectives
1. To explore the situation of social support in renal transplant recipients;
2. To explore the association between social support, coping modes, depression and quality of life;
3. To explore the associations among social support, blood pressure and inflammatory mediators.
Materials and Methods
1. We chose renal transplant outpatients who were followed up in the Third Xiangya Hospital of Central South University between September and December,2009, who accorded with the inclusion criteria and agreed to participate. Questionnaires were used to investigate 162 registered recipients. Questionnaires contained self-designed renal transplant recipients questionnaire of physical and psychological condition, Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire(MCMQ), Self-rating Depression Scale (SDS) and SF-36; and blood was tested for IL-6,IL-8 and CRP in 58 renal transplant recipients who participated the above study.
2. All data were analyzed by statistical analysis software package of SPSS (version 13.0) and AMOS (Analysis of Moment Structures), including descriptive analysis, single factor analysis, multiple linear regression, and structural equation modeling (SEM) analysis.
Results
1. A total of 162 study objects were chosen, including 114 men (70.4%) and 48 women (29.6%). Among the 58 recipients,39 men (67.2%) and 19 women (32.8%).
2. There was no significant difference between the scores of social support utilization in the 162 renal transplant recipients and the norms (t=0.400, P>0.05), and the scores of total social support (t=8.731, P=0.000), objective support (t=8.379, P=0.000) and subjective support (t=8.314, P=0.000) were higher than the norms.
3. Compared with the norms of chronic diseases on medical coping modes, confrontation (t=8.230,P=0.000) and avoidance (t=14.210, P=0.000) coping scores were higher than the norms, there was no significant difference between resignation coping scores and the norms (t=0.090,P>0.05), and there was no difference between the 3 dimensions of coping modes and gender(t=0.545, P>0.05;t=-0.367, P>0.05; t=-0.123, P>0.05).
4. Single factor analysis for social support showed:
①There was linear correlation between age and the scores of objective support (rs=0.219, P＜0.01), subjective support (rs=0.243, P＜0.01) and total support (rs=-0.240, P<0.01).
②The more education the recipients received, the higher they scored on total support (F=4.352, P＜0.05) and objective support (F=7.605, P＜0.05). There was no difference between education levels and the scores on subjective support (F=0.855, P>0.05), social support utilization (F=2.678, P>0.05).
③The group of recipients with a spouse scored higher on total social support (F=5.778, P＜0.01), objective(F=3.504, P<0.01) and subjective support (F=7.326, P<0.01) than the group without, and there was no difference in recipients'score of social support utilization (F=0.186,P>0.05).
④There was significant difference in recipients'score of objective (F=5.290, P<0.05), subjective (F=2.503, P<0.05) and total support (F=2.815, P<0.05) among different occupaition groups. There was no difference in recipients'score of social support utilization (F=1.342, P>0.05).
⑤The group of recipients having fixed income scored higher on objective (t=4.429, P＜0.05), total support (t=3.026, P<0.05) and social support utilization (t=2.064, P<0.05) than the group without, and there was no difference in recipients'score of subjective support (t= 1.088, P>0.05).
⑥The recipients whose self-paid medical ratio was below 50% scored higher on the 3 dimensions of social support and total support than those above 50%(t=3.518, P<0.05;t=2.589, P<0.05;t=3.286, P<0.05; t=3.941,P<0.05).
⑦There was significant difference in recipients'score of objective (F=5.672, P<0.05), subjective (F=3.819, P<0.05) and total support (F=6.107, P<0.05) among different support offering groups, and there was no difference in recipients'score of social support utilization (F=1.551,P>0.05).
⑧There was significant difference in recipients'score of objective (F=3.745, P<0.05), subjective (F=3.089, P<0.05) and total support (F=5.172, P<0.05) among different received-perceived social support groups,, and there was no difference in recipients'score of social support utilization (F=2.978, P>0.05).
5. Multiple linear regression for social support showed that marriage, age, career, education level, self-paid medical ratio, support for others and perceived social support were influencing factors for total social support (R2=0.484); Perceived social support, number of family members, marriage, support for others, resignation, education level and fixed income were influencing factors for objective social support (R2=0.345); Perceived social support, career, medical coping scores, marriage, resignation, education level, fixed income and self-paid medical ratio were influencing factors for subjective social support (R2=0.421); Resignation, age, avoidance and self-paid medical ratio were influencing factors for social support utilization (R2=0.221).
6. The total score of SDS was (47.58-9.04) points, higher than the norms (t=8.02, P＜0.01).
7. Compared with the norms, SF-36 showed that there was no difference between VT scores of the recipients and the norms (t=0.009, P>0.05). The other 7 dimension scores of the quality of life were lower than the norms (t=8.71,P=0.000; t=12.36, P=0.000; t=10.03,P=0.000; t=7.94, P=0.000;t=4.07, P=0.000; t=6.32, P=0.000; t=3.25, P=0.001).
8. The association between social support, coping modes, depression and quality of life was indicated as follows.
①The 3 dimensions of social support had a negative correlation with depression (r=-0.229; r=-0.183;r=-0.256; P values all<0.05). Objective support had a positive correlation with 8 dimensions (PF and SF excluded) of quality of life (r=0.191;r=0.183;r=0.206; r=0.216; r=0.180; r=0.236; P values all<0.05). Subjective support had a positive correlation with 2 dimensions of quality of life (r=0.208; r=0.205; P values all<0.05). Social support utilization had a positive correlation with 2 dimensions (RE and MH) of quality of life (r=0.202; r=0.195; P all<0.05).
②Resignation had a positive correlation with depression (r=0.326, P＜0.01) and a negative correlation with 7 dimensions (PF excluded) of quality of life (r=-0.181; r=-0.221; r=-0.381; r=-0.388; r=-0.237; r=-0.292; r=-0.246; P values all<0.05). There was a positive correlation between confrontation and the 3 dimensions of social support (r=0.164; r=0.206; r=0.271; P values all<0.05). There was negative correlation among resignation, objective and subjective support (r=-0.277; r=-0.292; P values all＜0.01).
③Depression had a negative correlation with 7 dimensions (PF excluded) of quality of life (r=-0.212;r=-0.222; r=-0.364;r=-0.446; r=-0.233;r=-0.305;r=-0.303; P values all<0.05).
9. SEM showed that confrontation had direct positive effect on social support (β=0.248,P<0.01). Resignation had direct negative effect on social support (β=-0.302, P＜0.01) and quality of life (β=-0.326, P<0.01),and direct positive effect on depression (β=0.346,P<0.01). Social support had direct positive effect on quality of life (β=0.220, P＜0.01) and negative effect on depression(β=-0.240, P<0.01). Depression had direct negative effect on quality of life (β=-0.320, P<0.01). Confrontation had indirect effect on quality of life via social support; Resignation had indirect effect on quality of life via social support, depression, and support-depression.
10. Spearman correlation analysis was processed among IL-6, IL-8, CRP and social support, and there was a negative correlation between CRP and social support utilization (r=-0.264, P＜0.05). There was a negative correlation between IL-6 and objective support (r=-0.222, P<0.05).
11. Spearman correlation analysis (two-tailed) was processed among Bp and all dimensions of social support in 55 recipients whose BMI was in the normal range, and there was a negative correlation between SBp and the total social support (r=-0.290, P＜0.05) and a negative correlation between DBp and total social support (r=-0.281, P<0.05).
Conclusion
1. Renal transplant recipients'age, career, education level, marriage, economic conditions, depression and the surrender dimension of coping modes are influencing factors for social support and received-perceived social support.
2. The coordination degree of the expected and the actual obtaining of individuals correlated with the scores of objective, subjective and total support. The scores of objective and subjective support in recipients who get actual support far less than expected is lower than those who get actual support no less or even higher than expected.
3. Support offering has a correlation with coping modes and economic conditions.
4. The roles of primary support, emergency contact and health care provided by spouses or parents are consistent.
5. Social support has direct negative effect on depression while coping modes has indirect effect on depression of recipients via social support.
6. Depression has direct negative effect on quality of life, indicating that depression may lower the quality of life of recipients.
7. Coping modes has direct and/or indirect effect on quality of life of recipients. Social support and depression, as mediated variables, can mediate the relationship between coping modes and quality of life.
8. IL-6 is negatively related to the scores of objective support among renal transplant recipients.
9. CRP is negatively related to the scores of social support utilization among renal transplant recipients.
10. Bp has negative correlation with total social support among renal transplant recipients.
1.探讨肾移植患者社会支持的状况；
2.探讨肾移植患者社会支持、医学应对方式、抑郁与生活质量的关系；
3.探讨肾移植患者社会支持与血压、炎性介质的关联。
方法
1.选择2009年9月至2009年12月在中南大学湘雅三医院门诊随诊的肾移植患者,符合入选标准并同意参加者均纳入研究对象,共确定162名患者进行问卷调查。调查问卷包括自编肾移植患者身心健康状况调查表、社会支持评定量表(SSRS)、医学应对问卷(MCMQ)、自评抑郁量表(SDS)和生活质量简表(SF-36)。并对58名参与问卷调查的随诊患者,采集血样检测白介素6(IL-6)、白介素8(IL-8)、C-反应蛋白(CRP)；
2.资料采用SPSS13.0统计软件及AMOS7.0统计软件进行分析,统计方法包括描述性统计分析、单因素分析、多元线性回归分析及结构方程模型分析。
结果
1.本研究共确定162名肾移植患者为研究样本,其中,男性114名(70.4%),女性49名(29.6%)；58名抽血检测患者,男性39名(67.2%),女性19名(32.8%)；
2.162名肾移植患者支持利用度得分与常模比较差异无统计学意义(t=0.400,P>0.05),社会支持总分(t=8.731,P=0.000)、客观支持得分(t=8.379,P=0.00)和主观支持得分(t=8.314,P=0.000)均高于常模；
3.与慢性病常模进行医学应对方式的比较,“面对”(t=8.230,P=0.000)、“回避”(t=14.210,P=0.000))维度得分高于常模；“屈服”屈服维度得分与常模差异无统计学意义(t=0.090,P>0.05),不同性别患者“面对”(t=0.545,P>0.05)、“回避”(t=-0.367,P>0.05)及“屈服”(t=-0.123,P>0.05)三个维度得分差异均无统计学意义；
4.社会支持的单因素分析结果显示：
(1)年龄与客观支持得分(rs=0.219,P<0.01)、主观支持得分(rs=0.243,P<0.01)及社会支持总分(rs=0.240,P<0.01)呈直线相关关系；与支持利用度得分无相关关系(rs=-0.049,P>0.05)；
(2)不同受教育程度患者社会支持总分(F=4.352,P<0.05)及客观支持得分(F=7.605,P<0.05)差异均有统计学意义,主观支持得分(F=0.855,P>0.05)及支持利用度得分(F=2.678,P>0.05)差异均无统计学意义；
(3)有配偶组社会支持总分(F=5.778,P<0.01)、客观支持得分(F=3.504,P<0.01)及主观支持得分(F=7.326,P<0.01)均高于无配偶组,差异有统计学意义；不同配偶组支持利用度得分差异无统计学意义(F=0.186,P>0.05)；
(4)不同职业组的客观支持得分(F=5.290,P<0.05)、主观支持得分(F=2.503,P<0.05)及社会支持总分(F=2.815,P<0.05)差异均有统计学意义；不同职业组的支持利用度得分差异无统计学意义(F=1.342,P>0.05);
(5)有固定经济来源组的客观支持得分(t=4.429,P<0.05)、支持利用度得分(t=2.064,P<0.05)及社会支持总分(t=3.026,P<0.05)均高于无固定经济来源组,差异有统计学意义；有固定经济来源组与无固定经济来源组主观支持得分差异无统计学意义(t=1.088,P>0.05)；
(6)医药费自付比例低于50%组在客观支持得分(t=3.518,P<0.05)、主观支持得分(t=2.589,P<0.05)、支持利用度得分(t=3.286,P<0.05)及社会支持总分(t=3.941,P<0.05)得分均高于自费比例超过50%组,差异均有统计学意义；
(7)对他人支持不同组的患者,其客观支持得分、主观支持得分及社会支持总分(F=5.672,P<0.05；F=3.819,P<0.05;F=6.107,P<0.05)差异均有统计学意义；支持利用度得分差异无统计学意义(F=1.551,P>0.05)；
(8)不同支持感知组的患者客观支持得分、主观支持得分及社会支持总分(F=3.745,P<0.05；F=3.089,P<0.05；F=5.172,P<0.05)差异均有统计学意义；支持利用度得分差异无统计学意义(F=2.978,P>0.05);
5.社会支持的多元线性回归分析显示：影响社会支持总分的因素有：婚姻、年龄、职业、受教育程度、医药费自付比例、感知支持,R2=0.484；影响客观支持得分的因素有：感知支持、家庭人口、婚姻、支持他人情况、“屈服”维度得分、受教育程度及有无固定经济来源,R2=0.345；影响主观支持得分的因素有：感知支持、职业、医学应对总分、婚姻、“屈服”维度得分、受教育程度、有无固定经济来源及医药费自付比例,R2=0.421；影响支持利用度得分的因素有：“屈服”维度得分、年龄、“回避”维度得分及医药费自付比例R2=0.221；
6.患者的抑郁总分为(47.58±9.04)分,高于常模(t=8.02,P<0.01)；
7.患者生活质量简表各维度与常模的比较结果显示：患者生命力维度与常模差异无统计学意义(t=0.009,P>0.05),其他七个维度(躯体功能、躯体角色、肌体疼痛、总健康、社会功能、情感角色、心理健康)的生活质量得分均低于常模(t=8.71,P=0.000；t=12.36,P=0.000；t=10.03,P=0.000；t=7.94,P=0.000；t=4.07,P=0.000；t=6.32,P=0.000；t=3.25,P=0.001)；
8.社会支持、医学应对方式、抑郁、生活质量的相关性：
(1)社会支持的3个维度得分均与抑郁呈负相关(r=-0.229；r=-0.183；r=-0.256；P均<0.05),客观支持得分与生活质量的8个维度得分(除去躯体功能和社会功能)呈正相关(r=0.191;r=0.183；r=0.206；r=0.216；r=0.180；r=0.236；P均<0.05),主观支持得分与生活质量的2个维度得分(总体健康和活力)呈正相关(r=0.208；r=0.205；P均<0.05),支持利用度得分与生活质量的2个维度得分(情感角色和心理健康)呈正相关(r=0.202;r=0.195；P均<0.05)；
(2)“屈服”维度得分与抑郁得分呈正相关(r=0.326,P<0.01),与生活质量的7个维度得分(躯体功能除外)呈负相关(r=-0.181；r=-0.221；r=-0.381；r=-0.388；r=-0.237；r=-0.292；r=-0.246；P均<0.05)；“面对”维度得分与社会支持的3个维度得分呈正相关(r=0.164;r=0.206;r=0.271;P均<0.05)；“屈服”维度得分与客观支持得分、主观支持得分呈负相关(r=-0.277；r=-0.292；P均<0.01)；
(3)抑郁得分与生活质量的7个维度得分(躯体功能除外)呈负相关(r=-0.212;r=-0.222;r=-0.364;r=-0.446;r=-0.233;r=-0.305;r=-0.303;P均<0.05)；
9.结构方程模型结果显示：“面对”的应对方式对社会支持有直接正向效应(β=0.248,P<0.01)；“屈服”的应对方式对社会支持有直接负向效应(β=-0.302,P<0.01)、对生活质量有直接负向效应(β=-0.326,P<0.01)、对抑郁有直接正向效应(β=0.346,P<0.01)；社会支持对生活质量有直接正向效应(β=0.220,P<0.01)、对抑郁有直接负向效应(β=-0.240,P<0.01)；抑郁对生活质量有直接负向效应(β=-0.320,P<0.01)；“面对”的应对方式可通过社会支持路径间接影响生活质量；“屈服”的应对方式可通过社会支持、抑郁、社会支持和抑郁路径间接影响生活质量；
10.对IL-6、IL-8、CRP与社会支持各维度进行Spearman相关分析,CRP与支持利用度得分呈负相关(r=-0.264,P<0.05)；IL-6与客观支持得分呈负相关关系(r=-0.222,P<0.05)；
11.对体重指数在正常范围内的55名患者的血压和社会支持各维度进行Spearman相关分析(双尾),血压与社会支持总分呈负相关关系(r=-0.290，P<0.05；r=-0.281,P<0.05)。
结论
1.肾移植患者的年龄、职业、受教育程度、婚姻、经济状况、抑郁、“屈服”的应对方式等影响社会支持和社会支持的感知；
2.个人期待值与实际获得社会支持的协调程度与客观支持得分、主观支持得分和社会支持总分有关；实际获得的支持少于个人期待值的患者,其客观支持得分、主观支持得分均少于与期望值相当或高于期望值的患者；
3.支持给予与医学应对方式、经济状况相关；
4.配偶／父母作为肾移植患者日常主要支持者、紧急状况求助者、健康代言人支持提供者身份的一致性较好；
5.社会支持对抑郁有直接负向效应,医学应对方式可通过社会支持间接影响肾移植患者的抑郁；
6.抑郁对生活质量直接负向效应,提示抑郁可降低肾移植患者的生活质量；
7.医学应对方式对肾移植患者生活质量有直接和间接效应；社会支持、抑郁作为中介变量调节医学应对方式与生活质量的关系；
8.肾移植患者中血清IL-6的水平与客观支持得分呈负相关关系；
9.肾移植患者血清CRP水平与患者支持利用度得分呈负相关关系。
10.血压与社会支持总分呈负相关关系。
Objectives
1. To explore the situation of social support in renal transplant recipients;
2. To explore the association between social support, coping modes, depression and quality of life;
3. To explore the associations among social support, blood pressure and inflammatory mediators.
Materials and Methods
1. We chose renal transplant outpatients who were followed up in the Third Xiangya Hospital of Central South University between September and December,2009, who accorded with the inclusion criteria and agreed to participate. Questionnaires were used to investigate 162 registered recipients. Questionnaires contained self-designed renal transplant recipients questionnaire of physical and psychological condition, Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire(MCMQ), Self-rating Depression Scale (SDS) and SF-36; and blood was tested for IL-6,IL-8 and CRP in 58 renal transplant recipients who participated the above study.
2. All data were analyzed by statistical analysis software package of SPSS (version 13.0) and AMOS (Analysis of Moment Structures), including descriptive analysis, single factor analysis, multiple linear regression, and structural equation modeling (SEM) analysis.
Results
1. A total of 162 study objects were chosen, including 114 men (70.4%) and 48 women (29.6%). Among the 58 recipients,39 men (67.2%) and 19 women (32.8%).
2. There was no significant difference between the scores of social support utilization in the 162 renal transplant recipients and the norms (t=0.400, P>0.05), and the scores of total social support (t=8.731, P=0.000), objective support (t=8.379, P=0.000) and subjective support (t=8.314, P=0.000) were higher than the norms.
3. Compared with the norms of chronic diseases on medical coping modes, confrontation (t=8.230,P=0.000) and avoidance (t=14.210, P=0.000) coping scores were higher than the norms, there was no significant difference between resignation coping scores and the norms (t=0.090,P>0.05), and there was no difference between the 3 dimensions of coping modes and gender(t=0.545, P>0.05;t=-0.367, P>0.05; t=-0.123, P>0.05).
4. Single factor analysis for social support showed:
①There was linear correlation between age and the scores of objective support (rs=0.219, P＜0.01), subjective support (rs=0.243, P＜0.01) and total support (rs=-0.240, P<0.01).
②The more education the recipients received, the higher they scored on total support (F=4.352, P＜0.05) and objective support (F=7.605, P＜0.05). There was no difference between education levels and the scores on subjective support (F=0.855, P>0.05), social support utilization (F=2.678, P>0.05).
③The group of recipients with a spouse scored higher on total social support (F=5.778, P＜0.01), objective(F=3.504, P<0.01) and subjective support (F=7.326, P<0.01) than the group without, and there was no difference in recipients'score of social support utilization (F=0.186,P>0.05).
④There was significant difference in recipients'score of objective (F=5.290, P<0.05), subjective (F=2.503, P<0.05) and total support (F=2.815, P<0.05) among different occupaition groups. There was no difference in recipients'score of social support utilization (F=1.342, P>0.05).
⑤The group of recipients having fixed income scored higher on objective (t=4.429, P＜0.05), total support (t=3.026, P<0.05) and social support utilization (t=2.064, P<0.05) than the group without, and there was no difference in recipients'score of subjective support (t= 1.088, P>0.05).
⑥The recipients whose self-paid medical ratio was below 50% scored higher on the 3 dimensions of social support and total support than those above 50%(t=3.518, P<0.05;t=2.589, P<0.05;t=3.286, P<0.05; t=3.941,P<0.05).
⑦There was significant difference in recipients'score of objective (F=5.672, P<0.05), subjective (F=3.819, P<0.05) and total support (F=6.107, P<0.05) among different support offering groups, and there was no difference in recipients'score of social support utilization (F=1.551,P>0.05).
⑧There was significant difference in recipients'score of objective (F=3.745, P<0.05), subjective (F=3.089, P<0.05) and total support (F=5.172, P<0.05) among different received-perceived social support groups,, and there was no difference in recipients'score of social support utilization (F=2.978, P>0.05).
5. Multiple linear regression for social support showed that marriage, age, career, education level, self-paid medical ratio, support for others and perceived social support were influencing factors for total social support (R2=0.484); Perceived social support, number of family members, marriage, support for others, resignation, education level and fixed income were influencing factors for objective social support (R2=0.345); Perceived social support, career, medical coping scores, marriage, resignation, education level, fixed income and self-paid medical ratio were influencing factors for subjective social support (R2=0.421); Resignation, age, avoidance and self-paid medical ratio were influencing factors for social support utilization (R2=0.221).
6. The total score of SDS was (47.58-9.04) points, higher than the norms (t=8.02, P＜0.01).
7. Compared with the norms, SF-36 showed that there was no difference between VT scores of the recipients and the norms (t=0.009, P>0.05). The other 7 dimension scores of the quality of life were lower than the norms (t=8.71,P=0.000; t=12.36, P=0.000; t=10.03,P=0.000; t=7.94, P=0.000;t=4.07, P=0.000; t=6.32, P=0.000; t=3.25, P=0.001).
8. The association between social support, coping modes, depression and quality of life was indicated as follows.
①The 3 dimensions of social support had a negative correlation with depression (r=-0.229; r=-0.183;r=-0.256; P values all<0.05). Objective support had a positive correlation with 8 dimensions (PF and SF excluded) of quality of life (r=0.191;r=0.183;r=0.206; r=0.216; r=0.180; r=0.236; P values all<0.05). Subjective support had a positive correlation with 2 dimensions of quality of life (r=0.208; r=0.205; P values all<0.05). Social support utilization had a positive correlation with 2 dimensions (RE and MH) of quality of life (r=0.202; r=0.195; P all<0.05).
②Resignation had a positive correlation with depression (r=0.326, P＜0.01) and a negative correlation with 7 dimensions (PF excluded) of quality of life (r=-0.181; r=-0.221; r=-0.381; r=-0.388; r=-0.237; r=-0.292; r=-0.246; P values all<0.05). There was a positive correlation between confrontation and the 3 dimensions of social support (r=0.164; r=0.206; r=0.271; P values all<0.05). There was negative correlation among resignation, objective and subjective support (r=-0.277; r=-0.292; P values all＜0.01).
③Depression had a negative correlation with 7 dimensions (PF excluded) of quality of life (r=-0.212;r=-0.222; r=-0.364;r=-0.446; r=-0.233;r=-0.305;r=-0.303; P values all<0.05).
9. SEM showed that confrontation had direct positive effect on social support (β=0.248,P<0.01). Resignation had direct negative effect on social support (β=-0.302, P＜0.01) and quality of life (β=-0.326, P<0.01),and direct positive effect on depression (β=0.346,P<0.01). Social support had direct positive effect on quality of life (β=0.220, P＜0.01) and negative effect on depression(β=-0.240, P<0.01). Depression had direct negative effect on quality of life (β=-0.320, P<0.01). Confrontation had indirect effect on quality of life via social support; Resignation had indirect effect on quality of life via social support, depression, and support-depression.
10. Spearman correlation analysis was processed among IL-6, IL-8, CRP and social support, and there was a negative correlation between CRP and social support utilization (r=-0.264, P＜0.05). There was a negative correlation between IL-6 and objective support (r=-0.222, P<0.05).
11. Spearman correlation analysis (two-tailed) was processed among Bp and all dimensions of social support in 55 recipients whose BMI was in the normal range, and there was a negative correlation between SBp and the total social support (r=-0.290, P＜0.05) and a negative correlation between DBp and total social support (r=-0.281, P<0.05).
Conclusion
1. Renal transplant recipients'age, career, education level, marriage, economic conditions, depression and the surrender dimension of coping modes are influencing factors for social support and received-perceived social support.
2. The coordination degree of the expected and the actual obtaining of individuals correlated with the scores of objective, subjective and total support. The scores of objective and subjective support in recipients who get actual support far less than expected is lower than those who get actual support no less or even higher than expected.
3. Support offering has a correlation with coping modes and economic conditions.
4. The roles of primary support, emergency contact and health care provided by spouses or parents are consistent.
5. Social support has direct negative effect on depression while coping modes has indirect effect on depression of recipients via social support.
6. Depression has direct negative effect on quality of life, indicating that depression may lower the quality of life of recipients.
7. Coping modes has direct and/or indirect effect on quality of life of recipients. Social support and depression, as mediated variables, can mediate the relationship between coping modes and quality of life.
8. IL-6 is negatively related to the scores of objective support among renal transplant recipients.
9. CRP is negatively related to the scores of social support utilization among renal transplant recipients.
10. Bp has negative correlation with total social support among renal transplant recipients.
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