Socioeconomic status moderate the relationship between mental health literacy, social participation, and active aging among Chinese older adults: evidence from a moderated network analysis

Abstract

Objective: The aging population represents a formidable global challenge, with China experiencing an accelerated demographic shift. While previous research has established a directional link between mental health literacy, social participation, and active aging, the moderating effect of socioeconomic status (SES) on these associations remains underexplored. This study sought to address this gap by employing moderated network analysis, in contrast to the total score approaches commonly used in prior literature.

Methods: A cross-sectional design was implemented, involving 1,032 Chinese individuals aged 60 and above, who completed the Mental Health Literacy Questionnaire, Active Aging Scale, Social Participation Questionnaire, and Socioeconomic Status Index Scale. The moderated network method was applied to explore the bidirectional relationships between mental health literacy, social participation, and active aging, while examining the moderating role of SES.

Results: The analysis identified the strongest bidirectional relationships between attitudes toward mental illness and the development of spiritual wisdom. Seven interaction terms emerged involving mental health literacy, social participation, and active aging, moderated by SES. Notably, the most significant interaction terms were found between attitudes toward mental illness and engagement in active learning.

Conclusions: These results contribute novel insights into the bidirectional relationships among mental health literacy, social participation, and active aging, as well as the role of SES in moderating these relationships. The findings highlight the need for targeted policy interventions to address socioeconomic inequalities in later life, thereby fostering active aging.

Keywords: Active aging; Mental health literacy; Moderated network analysis; Social participation; Socioeconomic status.

Fig. 1

Heatmap of the Spearman correlation matrix. The number in each box is the Spearman correlation coefficient. In the upper triangular matrix, only significant coefficients are presented after Bonferroni correction test (p < 0.05), and the blank box indicates coefficients do not survive this correction

Fig. 2

Plot showing the point estimates from each model, along with confidence intervals based on the estimated standard errors

Fig. 3

Plot the confidence intervals associated with interaction terms based on the MNMs

Fig. 4

A indicates MNMs of the network. Green lines indicate a positive relationship between two variables. Red lines indicate negative relationships at p < .05. The dashed line indicates that only one of the interactive relationships between two nodes is moderated by the SES variable at p < .05 (i.e., AND rule). Conversely, the solid line indicates that both nodewise regressions between two nodes are significant at p < .05 (i.e., AND rule). The light blue shading represents the R² for each nodewise regression

Fig. 5

Moderated network model with the exogenous moderator plotted with the AND rule. Green lines indicate a positive relationship between two variables at p < .05. Red lines indicate negative relationships at p < .05. The dashed line indicates that both of the interactive relationships between two nodes are moderated by the SES variable at p < .05 (i.e., AND rule). Conversely, the solid line indicates that both nodewise regressions between two nodes are significant at p < .05 (i.e., AND rule). The square represents SES along with arrows directly denoting its links to the other variables

Fig. 6

Conditional network models at the values of the mean ± SD of SES. Plotted with the AND rule and a significance threshold of p < 0.05

Fig. 7

Plots of conditional marginal effects. Each plot represents average values across both relevant interaction terms. In (A), the plot shows the conditional marginal effects of MHL1 × SES on SP4. In (B), the plot shows the conditional marginal effects of SP1 × SES on MHL4. In (C), the plot shows the conditional marginal effects of MHL6 × SES on AAS2. In (D), the plot shows the conditional marginal effects of MHL4 × SES on AAS2. In (E), the plot shows the conditional marginal effects of AAS2 × SES on MHL4. In (F), the plot shows the conditional marginal effects of SP4 × SES on AAS3.In (G), the plot shows the conditional marginal effects of SP5 × SES on AAS3.In (H), the plot shows the conditional marginal effects of AAS7 × SES on SP2

Fig. 8

The Expected Influence (centrality) value (standardized Z scores) of the MHL, SP, and AAS

Fig. 9

Average correlations were plotted with 95% coverage intervals for each subsample size. There were 1000 interactions for cease-dropping