Basic Characteristics
A total of 2,201 subjects completed questionnaires, 45 subjects were excluded as they were incomplete, resulting in 2,156 valid responses and a questionnaire effective recovery rate of 97.96%. There were 1,104 male participants (51.2%). The average age was (71.15±8.04) years, with 1,182 individuals (54.8%) aged 60-70, 630 individuals (29.2%) aged 71-80, and 344 individuals (16.0%) aged over 80. Regarding ethnicity, 1,416 individuals (65.7%) belonged to minority ethnic groups. Concerning education, 1,168 participants (54.2%) were illiterate, 702 (32.6%) had completed primary school, 208 (9.6%) had completed junior high school, and 78 (3.6%) had completed high school or above. There were 1,476 individuals (68.5%) who were married and still living with their partner and 680 individuals (31.5%) with another marital status. The total MUNSH score for rural elderly patients with chronic diseases was (27.17±9.48),PA was (5.02±2.64), NA was (4.06±3.00), , PE was (7.56±3.60) and NE was (5.35±3.67).A total of 512 (23.7%) individuals had high subjective well-being, 1538 (71.3%) had moderate subjective well-being, and 106 (4.9%) had low subjective well-being. Significant differences in MUNSH scores were observed among different marital statuses, living arrangements, whether they had a family doctor, whether they were precision-targeted for poverty alleviation, whether they were with minimum living allowance, different education, family relationships, severity of illness, ability to perform daily activities, and participation in social activities (all P < 0.05) (Table 1).
Associations between Depression, Social Support, and Subjective Well-being in Older Patients with Chronic Diseases
The GDS-15 score for older patients with chronic diseases was (7.23±2.59), with 627 individuals (29.1%) having no depressive symptoms, 1,246 individuals (57.8%) experiencing mild depressive symptoms, and 283 individuals (13.1%) experiencing moderate to severe depressive symptoms. The SRSS total average score was(34.96±7.97), subjective support was (18.80±4.21), objective support was (8.63±3.47), and support utilization was (7.53±2.04). A total of 102 (4.7%) individuals had low social support, 1786 (82.8%) had moderate social support, and 268 (12.4%) had high social support. Significant differences were observed in MUNSH scores and various dimensions among older patients with different degrees of depression and social support levels (all P < 0.05) (Table 2).
Pearson correlation analysis results showed that the GDS-15 score was negatively correlated with MUNSH, PA, and NA score (r = -0.528, -0.139, -0.276, P < 0.01) and positively correlated with PE and NE score (r = 0.546, 0.546, P < 0.05). The SSRS score, subjective support score, objective support score, and support utilization score were all negatively correlated with the GDS-15 score (r = -0.243, -0.256, -0.177, -0.121, P < 0.05). The SSRS score was positively correlated with the MUNSH score, PA score, NA score, subjective support score, objective support score, and support utilization score (r = 0.280, 0.282, 0.173, 0.878, 0.815, 0.708, P < 0.05) and negatively correlated with PE score and NE score (r = -0.245, -0.149, P < 0.05). Subjective support was positively correlated with MUNSH score, PA score, and NA score (r = 0.258, 0.242, 0.124, P < 0.05) and negatively correlated with PE score and NE score (r = -0.222, -0.189, P < 0.05). Objective support was positively correlated with MUNSH score, PA score, NA score (r = 0.204, 0.199, 0.170, P < 0.05) and negatively correlated with PE score and NE score (r = -0.177, -0.071, P < 0.05). Support utilization score was positively correlated with MUNSH score, PA score, and NA score (r = 0.214, 0.264, 0.132, P < 0.05) and negatively correlated with PE score and NE score (r = -0.197, -0.073, P < 0.05) (Table 3).
Multivariate linear regression analysis revealed that mild depression (B = -7.795, 95% CI: -8.437- -7.153, P < 0.001), moderate to severe depression (B = -11.631, 95% CI: -12.623 - -10.639, P < 0.001), moderate social support (B = -2.661, 95% CI: -4.063- -1.259, P < 0.001), primary school education (B = 1.487, 95% CI: 0.854 - 2.12, P < 0.001), junior high school education (B = 1.882, 95% CI: 0.901 - 2.863, P < 0.001), fair family relationships (B = 6.264, 95% CI: 4.560 - 7.968, P < 0.001), relatively good family relationships (B = 6.372, 95% CI: 4.726 - 8.018, P < 0.001), very good family relationships (B = 9.894, 95% CI: 8.225 - 11.562, P < 0.001), moderate severity of illness (B = -0.893, 95% CI: -1.531 - -0.256, P = 0.006), complete self-care ability (B = 1.601, 95% CI: 0.324 - 2.878, P = 0.014), being a precision-targeted poverty alleviation recipient (B = 7.149, 95% CI: 6.552-7.746, P < 0.001), occasional participation in social activities (B = 1.506, 95% CI: 0.714 - 2.299, P < 0.001), frequent participation in social activities (B = 2.352, 95% CI: 1.366 - 3.337, P < 0.001), and consistently participating in social activities (B = 3.643, 95% CI: 2.448 - 4.838, P < 0.001) were independently associated with subjective well-being (Table 4).
Social Support Mediation Analysis of Depression and Subjective Well-being in Older Patients with Chronic Diseases
The SEM results indicated a good model fit (χ2/df=7.672, GFI=0.994, NFI=0.987, RFI=0.967, IFI=0.989, TLI= 0.971,CFI=0.989, RMSEA=0.056). The path coefficients for the impact of depression symptoms on social support and subjective well-being in older patients with chronic diseases were -0.28 and -0.47, respectively. The path coefficient for the impact of social support on subjective well-being was 0.19. All standardized path coefficients in the model were statistically significant (all P < 0.001) (Figure 1).
The bootstrap test results revealed that the total effect of depression symptoms on subjective well-being in older patients with chronic diseases was -0.528, with a direct effect of -0.474 (95% CI: -0.503 to -0.443), accounting for 89.77% of the total effect. The mediating effect of social support on the association between depression and subjective well-being was -0.133 (95% CI: -0.070 to -0.041), constituting 10.23% of the total effect (Table 5).