| Objectives1. 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 Methods1. 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.Results1. 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).Conclusion1. 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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