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Abstract
Objective To examine the relationship between social trust and depressive symptoms among China’s elderly, placing special emphasis on the disparities between urban and rural settings.
Design We employed latent profile analysis to categorise individual patterns of social trust. Subsequently, multiple linear regression analysis was employed to determine if there was an association between these identified social trust patterns and depressive symptoms. Additionally, we examined the potential interactive effects between urban-rural differences and patterns of social trust on depressive symptoms.
Setting The China Family Panel Studies (CFPS) database.
Participants The data was sourced from the CFPS for the years 2018 and 2020, encompassing a total of 5645 participants aged 60 and above.
Outcome measures Depressive symptoms were evaluated employing an eight-item adaptation of the Centre for Epidemiologic Studies Depression Scale. The scores from these eight items were aggregated to create an index of depressive symptoms, which was used to quantify the severity of depressive symptoms.
Results The findings demonstrate a significant link between patterns of social trust and depressive symptoms, with individuals manifesting high social trust (HST) showing a lower propensity for depressive symptoms (Beta=−2.26, 95% CI=−2.62, –1.92). Furthermore, a marked association is apparent between social trust patterns and the changes in depressive symptoms. Additionally, urban dwellers (Beta=−0.67, 95% CI=−1.23, –0.11) demonstrate a more pronounced correlation between patterns of social trust and depressive symptoms, particularly within the HST group.
Conclusion Our findings highlight a strong link between social trust patterns and depressive symptoms, particularly regarding their changes. Urbanites, notably within the HST group, show a lower risk of experiencing depressive symptoms. There is an urgent requirement to establish social trust-specific interventions to decrease susceptibility to depressive symptoms among the rural populace.
- Health
- Aging
- PUBLIC HEALTH
Data availability statement
Data are available in a public, open access repository.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
A large, nationwide representative longitudinal database was used to explore the relationship between social trust and depressive symptoms.
Social trust was categorised using latent profile analysis, and causal inferences were drawn using multivariate linear regression with interaction effects.
Data on depressive symptoms were collected through self-reported measures, which may have introduced some degree of response bias.
Our analysis might not have accounted for all potential confounders, such as comprehensive socioeconomic indicators or tangible metrics of physical health.
Introduction
In numerous countries, there is a discernible uptick in the proportion of the population aged 60 years and above. Amid its swift demographic ageing, China has the globally highest elderly population, posing a significant public health issue, particularly the rising incidence of geriatric depressive symptoms.1 Based on data from China’s Seventh National Population Census in 2020, individuals aged 60 and over comprise 264.02 million or 18.70% of the total population. Meanwhile, those 65 years and older account for 190.64 million, which translates to 13.50% of the overall population.2 Current academic literature suggests that in excess of 39% of the elderly population manifest depressive symptoms. Intriguingly, within the upper age strata of this demographic, the prevalence of depressive symptoms reaches a notable approximation of 45%.3 Depression manifests in more than merely compromised functional capacities and a deterioration in the quality of life; it correspondingly escalates the mortality rate among the elderly.4 Beyond the personal distress, the financial implications of this condition are considerable, imposing a significant economic strain on both the individuals affected and society, as well as overstretching healthcare systems.5 Consequently, diligent efforts to comprehend the aetiology of depression and its potential influencing factors are of paramount importance for public health.
With the advancing understanding of healthy social determinants, there is an amplified acknowledgement of the integral role social capital plays in mental health.6 Social trust is delineated as a cognitive form of social capital, embodying people’s feelings and encompassing both individual and communal trust. Often heralded as a quintessential or prime metric, it sits at the heart of social capital considerations.7 A considerable spectrum of empirical studies underscores the profound association between social trust—a cornerstone of social capital—and the overall health metrics, including depressive symptomatology among adults, women and seniors.8 Specifically, heightened social trust appears to be a catalyst for health-enhancing behaviours, such as outdoor physical activity and enriching social engagements, which potentially mitigate the incidence of depressive symptoms.9 Despite the current academic landscape predominantly focusing on the facets of generalised trust at national, regional or community levels, there exists a notable dearth of studies delving into social trust from an individual perspective.10 Even more conspicuous is the scarcity of research probing the nuances of subjective trust at this individual echelon.
Urban-rural disparities may exert a moderating influence on the nexus between elderly individuals’ social trust patterns and their depressive symptoms. Prior research suggests that seniors in urban settings typically enjoy a richer tapestry of social support, a broader social connectivity, superior access to societal resources, and consequently, elevated levels of social trust.11 This might lead to a diminished likelihood of developing depressive symptoms compared with their rural peers. Thus, the connection between social trust and depressive manifestations might be more pronounced among urban seniors. Yet, some research posits that the magnitude of the association between social trust and depression remains relatively consistent across both urban and rural settings.10 Despite the extensive exploration of the interplay between social trust and depressive symptoms, the precise moderating role of urban-rural differentials, especially among the senior demographic, is not yet fully elucidated. Furthermore, with the swift march of global urbanisation, especially pronounced in low to middle-income nations, discerning the urban nuances in social trust and their ramifications for depression could unveil the root causes of the palpable urban-rural variances in depression rates.12 Such understanding could equip policymakers with insights to devise more bespoke intervention approaches.
Thus, in the present study, we aimed to investigate the association between patterns of social trust perception and depressive symptoms and to examine the interactive effect of urban-rural disparities on this relationship using a nationally representative sample of Chinese older adults.
Methods
Data sources and sample composition
The data for this study was sourced from the China Family Panel Studies (CFPS), a nationally representative longitudinal survey conducted by the Institute of Social Science Survey (ISSS) at Peking University. This biennial survey encompasses 16 000 households and spans 25 out of China’s 31 provinces, inclusive of municipalities and autonomous regions.13 14 Owing to its expansive sample size and geographical coverage, the CFPS offers robust national representation. Data collection for the CFPS was conducted using a mixed-method approach, which included both computer-assisted personal interviewing and traditional face-to-face interviews. Comprehensive details on the sampling methodology and procedural aspects of the study are documented in previously published works.1 14 To safeguard the anonymity of participants, the CFPS assigns each respondent a consistent, unique identification number across different survey years. This facilitates the formation of cohorts using data spanning multiple years. Inclusion criteria for this study encompassed: (1) individuals aged 60 and above; (2) individuals who completed the survey in both 2018 and 2020. The exclusion criteria were: (1) individuals aged 60 below; (2) the variables of interest in this study were missing. After meticulous screening and pairing based on unique identification numbers, a total of 5645 respondents, surveyed comprehensively in both 2018 and 2020, were included in this study, yielding a total of 11 290 data points. A flowchart of the study method is shown in figure 1.
Flow chart of study method.
The data collection for CFPS employed a blend of computer-assisted personal interviewing and direct face-to-face methods.14 To ensure data integrity, experienced teams meticulously oversaw the questionnaire development, data collation and database formation, upholding stringent quality control measures.
Main outcome measures: Depressive symptoms
The eight-item Centre for Epidemiologic Studies Depression Scale (CES-D-8) questionnaire, developed by Radloff, stands as one of the predominant self-assessment tools for depressive symptoms.15 A condensed version was incorporated into CFPS2018 to optimise survey length and enhance response rates. Research attests to the reliability and validity of the CES-D-8 scale in depression screening.16 17 Specifics of the eight-item CES-D scale can be found in online supplemental appendix table S1.
Supplemental material
In our study, the primary outcome measures were depressive symptoms recorded in 2018 and 2020. Respondents detailed their symptoms from the preceding week using a scale of 0 to 3: 0 signifying ‘rarely’, 1 as ‘a little’, 2 for ‘occasionally’, and 3 denoting ‘often’. Scores for negatively phrased questions ranged from 0 to 3; whereas, positively phrased questions were scored inversely from 3 to 0. Within the CES-D-8 framework, depression symptoms were gauged on a scale from 0 to 24, with elevated scores indicating more severe symptoms. The internal consistency of the scale, as measured by Cronbach’s alpha, was 0.764 for the 2018 wave and 0.776 for the 2020 wave in our study.
Main measures of independent variables: Social trust
In both CFPS2018 and CFPS2020, the questionnaire probed six items related to perceptions of social trust (detailed in online supplemental table S2). Responses were gauged on a scale ranging from 0 to 10, where 0 denotes ‘extremely distrustful’ and 10 signifies ‘extremely trustworthy’. These choices capture the respondents’ perceptual attitudes towards societal trust in domains including parents, neighbours, physicians, Americans, strangers and the government. To discern distinct patterns in the perception of social trust, this study employed latent profile analysis (LPA) to classify respondents.
Potential confounders
We examined the distribution of diverse characteristics within the study sample from 2018, encompassing both demographic and socioeconomic facets. These included: region (west, central, east, northeast); gender (female, male); marital status (married, unmarried); chronic diseases (yes or no); alcohol abuse (yes or no); smoking (yes or no). Existing literature indicates a correlation between depressive symptoms and various demographic, socioeconomic and health attributes.18 19
Statistical analysis
To describe the distribution of variables in the study, descriptive statistics (mean, SD; n, %) were used. LPA classified individuals according to their patterns of response to episodic items, which was realised by checking the distribution of different groups in the data and determining whether these distributions are meaningful or not.20 In the application of LPA, the observed variables were continuous. In this study, Mplus V.8.3 was used for LPA to check the number of unobserved categories (potential features of social trust), describe the characteristics of categories and calculate the probability that each individual belongs to a given category. Generally, Bayesian Information Criterion (BIC), Sample-size Adjustment BIC (SABIC), Akaike Information Criterion (AIC) and entropy were used for reference in LPA. The lower the values of AIC, BIC and SABIC in a model, it indicated that this model was more fitting than another model.21 Similarly, entropy can also be used as statistical data to judge the fitting degree of the model. Entropy showed how accurate the classification of this model was, and the value of entropy higher than 0.8 was acceptable.22 Additionally, in order to further compare different models, Lo-Mendell-Rubin likelihood ratio test (LMR) and bootstrap likelihood ratio test (BLRT) were used as significance tests. When LMR or BLRT was significant, it indicated that the classification of this model was better than that of previous models (p<0.05). To compare the differences of social trust patterns, the Pearson’s χ² test was used.
Multiple linear regression analysis was conducted to identify whether social trust patterns were associated with depressive symptoms. In addition, an interaction effect was also examined between township of resident (compared with the ‘Urban’ cases) and the social trust patterns, on depressive symptoms. The effect of confounding factors mentioned above on the outcome variables was controlled in the multiple linear regression model. Stata V.15.0 was used for data analysis. The statistical significance level was set at p<0.05.
Results
Descriptive statistical analysis
The descriptive analysis of the main variables in our study was presented in table 1. Among 5645 respondents in wave 2018, females (n=2897, 51.32%), individuals with agricultural Hukou status (n=2997, 53.09%) and individuals lived in the urban areas of East China (n=2018, 35.75%) were accounted for the majority. From 2018 to 2020, the average score of depression symptoms among residents decreased significantly. Additionally, more than half of the respondents were unemployed (n=2871, 50.86%), married (n=4023, 71.27%), and had a middle-income status (n=2904, 51.44%), no alcohol drinking (n=4805, 85.12%) and no smoking (n=4232, 74.97%). In wave 2020, most of these variables essentially maintained the similarity.
Sample characteristics
Model selection
The fitting statistics of various potential profile patterns were displayed in online supplemental appendix table S3. A two-class model which had favourable AIC, BIC, SABIC values and the acceptable entropy values was found to be the most appropriate model based on exploratory LPA surveys conducted in wave 2018 and wave 2020.
According to the percentages of each category reported by LPA, we can obtain the proportions of interviewees with different social trust patterns: high social trust (HST, 76.0%) and low social trust (LST, 24.0%). As shown in figure 2, individuals with high social trust are most likely to trust their parents, neighbours, doctors and the government, the probability of which is significantly higher than that of the respondents with low trust. They are least likely to trust Americans and strangers. In contrast, respondents with low social trust have a higher likelihood of trusting doctors and the government, and the lowest likelihood of trusting strangers, yet the probability is significantly higher than that of respondents with high social trust.
Social trust patterns detected among people aged over 60. Note. The social trust patterns were determined by the estimated probability of respondents from each latent class answering from 1 to 10 in six items (V1–V6). The solid black line refers to the type with high social trust (HST) and the dotted black line refers to the type with low social trust (LST).
Results of chi-square test
Online supplemental appendix table S4 displays the results of the χ² test analysis. We found that gender, township, region, working status, education, self-evaluated income status, marital status, chronic diseases, alcohol abuse and smoking were related to respondents’ social trust patterns (p<0.05).
Multiple linear regression analysis
Table 2 presents the results of the multiple linear regression analysis assessing the related factors for depressive symptoms. With confounding variables controlled, social trust patterns were significantly associated with depressive symptoms in 2018 and 2020. Specifically, higher social trust pattern was associated with fewer depressive symptoms (B=−2.26, 95% CI=−2.62, –1.92). Compared with rural older adults, urban older adults (B=−1.06, 95% CI=−1.33, –0.79) were less likely to develop depressive symptoms.
Multiple linear regression of the relationship between social trust patterns and depressive symptoms (n=5645)
Table 2 and figure 3 show the regression results after introducing the interaction of urban-rural disparities and social trust patterns on depressive symptoms. Compared with the elderly who lived in rural, significant interaction effects were observed for urban HST group (B=−0.67, 95% CI=−1.22, –0.11). Urban older adults demonstrated a stronger association between social trust patterns and depressive symptoms. Online supplemental appendix table S5 demonstrated a significant correlation between social trust and the changes in depressive symptoms.
Results of multiple linear regression with interactions.
Discussion
This study focused on depressive symptoms among Chinese adults, and examined the relationship between social trust patterns and depressive symptoms, and further examined the interaction effect of urban-rural differentials and social trust patterns on depressive symptoms in this population, using data from the CFPS. In this study, we found social trust patterns are significantly associated with depressive symptoms either in short term and long term, especially for those who are highly social trust elderly. In addition, the results of this study reveal that urban-rural differentials may play a moderator role in the relationship between social trust patterns and depressive symptoms.
Our investigation reveals a notable inverse association between social trust, which encompasses the spectrum of trust individuals place in parents, neighbours, doctors, governmental bodies, strangers, and the populace at large, and depressive symptoms. This aligns with the continuum of findings extant in prior research.23 A significant corpus of contemporary research delineates social trust as an essential facet of social capital, inversely associated with mental maladies and the prevalence of depressive symptoms among the elderly.6 Moreover, stress is postulated as a putative mechanism bridging trust and health outcomes. Individuals who exhibit higher levels of social trust are less predisposed to stress in comparison to their more sceptical counterparts, consequently mitigating their susceptibility to adverse health outcomes.24 Residing within a familial or communal environment characterised by elevated levels of social trust may attenuate stress and augment overall well-being, thereby leading to a reduction in the prevalence of depressive symptoms.25 Empirical evidence from a South Korean study elucidates that interpersonal trust within familial contexts can engender more favourable outcomes in the management of depression.26 Complementary research emanating from Japan intimates that fostering amicable neighbourly relations may serve as a potential strategy in averting depressive symptoms in older populations.27 Given these insights, it is imperative to accord attention to the multifaceted dimensions of trust within elderly populations, particularly within familial, neighbourhood, and broader social contexts, as a vital measure for the prophylaxis of depressive symptoms in this demographic.
More precisely, the elderly populace characterised by elevated trust paradigms exhibits a diminished propensity for depressive symptomatology in contrast to their counterparts with lower levels of trust. This observation is in substantial alignment with the corpus of extant research findings.27 Viewing through the lens of social capital, an augmented degree of trust, indicative of fortified trust relations with family, neighbours, medical practitioners and governmental entities, is poised to cultivate a more resilient social network and bolster social support mechanisms.11 Historical studies have elucidated that a robust framework of trust and mutual reciprocity enhances social connections and support systems, a role that has been widely acknowledged for its efficacy in mitigating depressive symptoms among the senior demographic.23 Moreover, the nexus between social trust and mental health may be intricately tied to the facet of social participation, with the prevailing body of research corroborating that active social engagement is conducive to improved health statuses.12 Crucially, the research conducted by Chen Li et al has substantiated that social trust exerts a salutary influence on levels of satisfaction and self-esteem among the elderly, which may in turn facilitate the amelioration of depressive symptoms.28 Consequently, an emphasis on the social trust status of the elderly, in conjunction with the associated social relational networks, social support systems and social participation, could potentially elevate the Social Trust Index among this demographic, thereby mitigating instances of depressive symptoms.
An additional intriguing discovery from our investigation is the moderating effect of urban-rural disparities on the nexus between social trust and depressive symptoms. This finding does not completely resonate with those of Sasaki et al, whose research failed to detect a pronounced interaction among urban-rural differentials, social trust and symptoms of depression.10 Contrastingly, our analysis indicates that urban elderly individuals, notably those within elevated trust brackets, are less susceptible to depressive symptoms than their rural counterparts. This divergence could be ascribed to the pronounced socioeconomic chasm segregating urban and rural zones in China. Elderly residents in urban areas generally enjoy superior socioeconomic standing relative to their rural equivalents, a factor demonstrated to substantially bolster social trust and mitigate depressive symptoms among the aged.29 Additionally, rural elderly individuals face inferior conditions in public transportation, housing, education, healthcare, mental health services and pension benefits. China’s swift urbanisation only magnifies this inequity, potentially relegating rural elderly individuals to a disadvantaged position in terms of social trust and susceptibility to depression.30 Additionally, the hastening exodus of the younger populace from rural to urban locales exacerbates the ‘empty nest’ phenomenon, eroding the familial support traditionally accessible to the rural aged.31 Prior studies imply that this transition might likewise impinge on the degrees of social trust and depressive symptoms within these rural elderly cohorts.12 Hence, a holistic attention to the living conditions and economic strata of rural elderly citizens, amalgamated with the enactment of proactive social trust initiatives, might bear significant ramifications for fostering an equitable regional advancement of mental well-being among the elderly demographic. However, it is important to acknowledge that due to data limitations, the sample size in this study is relatively modest, and the analysis is based on publicly available data. Consequently, the findings may be influenced by certain biases, such as temporal selection bias. Therefore, careful consideration is required when assessing the representativeness of the sample, as well as the applicability and generalisability of the results.
Conclusion
Our findings highlight a strong link between social trust patterns and depressive symptoms. The results of this study reveal that urban-rural differentials may play a moderator role in the relationship between social trust and depressive symptoms. Compared with their rural counterparts, older adults residing in urban areas, particularly those within the HST group, exhibited a lower susceptibility to depressive symptoms. Given these findings, there is a pressing need to design and implement intervention measures pertinent to enhancing individual-level social trust among the elderly, thereby reducing the risk of depressive symptoms among those with a low social trust status. Specifically, those residing in rural areas, particularly individuals with low levels of social trust, warrant close attention and provision of pro-active, effective health guidance to ameliorate their circumstances.
Data availability statement
Data are available in a public, open access repository.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and was approved by the Institutional Review Board of Peking University (IRB00001052-14010), Beijing, China. All participants gave consent after being informed to the aim of the survey and their rights to refuse to participate. The planning, conduct and reporting of human research are in accordance with the Helsinki Declaration as revised in 2013. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
Thanks to CFPS group for their excellent sharing of CFPS database, makes it possible for us to explore the mental health impacts of union formation patterns in Chinese adults.
References
Footnotes
X @2111110172@bjmu.edu.cn
Contributors TW: Conceptualisation, formal analysis, writing—original draft, writing—review and editing. QL: Conceptualisation, data curation, writing—review and editing. SZ: Data curation, writing—review and editing. YW: Formal analysis, writing—review and editing. WJ: Conceptualisation, supervision, writing—review and editing. TW is responsible for the overall content as the guarantor.
Funding This work was supported by the National Natural Science Foundation of China (Grant Number: 72174007) to Weiyan Jian. The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.