Social Support, Coping Strategies, Depression, Anxiety, and Cognitive Function Among People With Type 2 Diabetes Mellitus: A Path Analysis

Wenhang Chen; Rehanguli Maimaitituerxun; Jingsha Xiang; Yu Xie; Fang Xiao; Irene Xinyin Wu; Letao Chen; Jianzhou Yang; Aizhong Liu; Wenjie Dai

doi:10.30773/pi.2024.0024

Psychiatry Investig > Volume 21(9); 2024 > Article

Chen, Maimaitituerxun, Xiang, Xie, Xiao, Wu, Chen, Yang, Liu, and Dai: Social Support, Coping Strategies, Depression, Anxiety, and Cognitive Function Among People With Type 2 Diabetes Mellitus: A Path Analysis

Original Article

Psychiatry Investigation 2024;21(9):1033-1044.

Published online: September 3, 2024

DOI: https://doi.org/10.30773/pi.2024.0024

Social Support, Coping Strategies, Depression, Anxiety, and Cognitive Function Among People With Type 2 Diabetes Mellitus: A Path Analysis

Wenhang Chen¹

, Rehanguli Maimaitituerxun²

, Jingsha Xiang³

, Yu Xie²

, Fang Xiao⁴

, Irene Xinyin Wu²

, Letao Chen⁵

, Jianzhou Yang⁶

, Aizhong Liu²

, Wenjie Dai²

¹Department of Nephrology, Xiangya Hospital, Central South University, Changsha, China

²Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China

³Department of Human Resources, Central Hospital Affiliated to Shandong First Medical University, Jinan, China

⁴Department of Toxicology, Xiangya School of Public Health, Central South University, Changsha, China

⁵Infection Control Center, Xiangya Hospital, Central South University, Changsha, China

⁶Department of Preventive Medicine, Changzhi Medical College, Changzhi, China

Correspondence: Wenjie Dai, MD Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, No. 172 Tongzipo Road, Yuelu District, Changsha, Hunan, China Tel: +86-073189667218, E-mail: m18673965791@163.com

Received January 22, 2024 Revised June 24, 2024 Accepted July 4, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective

To explore the linear associations between social support, coping strategies, depression, anxiety, and cognitive function among people with type 2 diabetes mellitus (T2DM) using a path-analytic method.

Methods

This cross-sectional study enrolled 496 individuals hospitalized due to T2DM. Well-trained investigators conducted face-to-face interviews with the participants using the Social Support Rating Scale, the Chinese version of Medical Coping Modes Questionnaire, the Hospital Anxiety and Depression scale, and the Mini Mental State Examination to measure social support (including objective support, subjective support, and support utilization), coping strategies (including confrontation, avoidance, and acceptance-resignation), depression/anxiety, and cognitive function, respectively. A path analysis was used to elucidate the linear associations between social support, coping strategies, depression, anxiety, and cognitive function.

Results

In the final path model with satisfactory model fit, objective support was found to be associated with cognitive function not only directly but also indirectly through confrontation coping and depression, and acceptance-resignation coping and depression/anxiety. Further, subjective support was found to be associated with cognitive function indirectly through depression/anxiety, as well as serially through acceptance-resignation coping and depression/anxiety. Support utilization was found to be associated with cognitive function indirectly through confrontation coping and depression, as well as through acceptance-resignation coping and depression/anxiety.

Conclusion

Social support, coping strategies, depression, and anxiety were associated with cognitive function among people with T2DM, and these associations were best explained by a serial mediation model from social support, coping strategies, and depression and anxiety to cognitive function.

Keywords: Cognitive function, Social support, Coping strategy, Depression, Anxiety, Type 2 diabetes mellitus

INTRODUCTION

China is one of the countries with the greatest number of adults living with diabetes globally [1], and the overall standardized prevalence of diabetes increased significantly from 10.9% in 2013 to 12.4% in 2018 [2]. Type 2 diabetes mellitus (T2DM) accounts for the majority of diabetes cases [3]. Accumulated evidence has consistently shown that people with T2DM are at increased risk for accelerated cognitive decline and dysfunction that may eventually result in Alzheimer’s disease and vascular dementia [4,5]. Cognitive impairment among people with T2DM is associated with reduced self-care ability and quality of life, as well as increased all-cause mortality [6-9]. Preserving cognitive function has become an increasing priority for care providers as the size of T2DM population is increasing. According to the guideline established by the European geriatric medicine society and the European diabetes working party for older people collaboration, the screening of cognitive impairment is suggested at regular intervals for patients aged 70 years and over in primary care [10].

Social support, generally defined as the support accessible to an individual through social ties to other individuals, groups, and the larger community [11], is a potentially modifiable protective factor against cognitive impairment. Previous studies have linked social support to cognitive function in the older adults [12-16], and to people with T2DM [17-19], suggesting that increased social support may contribute to improved cognitive function. However, the mechanistic processes underlying this proposed relationship are still unknown among people with T2DM. One possibility is that social support may affect later-life cognitive function by modifying the acquisition of coping strategies, which is defined as ongoing behavioral and cognitive efforts to manage specific internal and/or external demands that are appraised as taxing or exceeding the resources of the individual from a process standpoint [20]. Specifically, social support received from one’s family, friends, and community can be an antecedent factor that reduces the use of avoidance coping, which is also linked to cognitive deficits [21,22]. For example, Hall et al. [21] found that more acquisition of behavioral/avoidant coping strategies was associated with poorer performance on tests of verbal ability and executive function among people with multiple functional somatic symptoms. Similarly, Zhu et al. [22] found that reducing negative coping may be a crucial intervention target to prevent further impairment of working memory among people with schizophrenia suffering from great stress.

Depression and anxiety symptoms are well-recognized internalized symptoms influenced by coping strategies [23-25]. Additionally, emerging evidence suggests that depression and anxiety symptoms are correlated with cognitive function, regardless of the study population [25,26]. For instance, Oyeyemi et al. [27] found that greater severity of depression and anxiety was associated with poorer cognitive performance both before and 6 weeks after major non-cardiac surgery among older adults. Also, Lindert et al. [28] found that depression and anxiety symptoms were both associated with changes in episodic memory and executive function. Furthermore, Guerrero-Berroa et al. [29] found that among the elderly with T2DM, depression was associated with worse performance on tasks of executive function, language/semantic categorization, and overall cognition. Therefore, it can be hypothesized that the effects of coping strategies on cognitive function may be at least partially explained by the outcomes of depression and anxiety symptoms.

No prior study has examined the associations of social support, coping strategies, and depression and anxiety symptoms with cognitive function among people with T2DM, and the direct and indirect effects of these factors on cognitive function have not yet been elucidated in this population. Lack of such research has not only limited our understanding of the protective mechanisms against cognitive function, but also negatively affected the development of effective interventions to improve cognitive function among people with T2DM. In this cross-sectional study conducted among people with T2DM, a path-analytic approach was used to test the following hypotheses: 1) social support is associated with the acquisition of coping strategies which eventually affect cognitive function, 2) the effects of coping strategies on cognitive function are mediated by depression and anxiety symptoms, and 3) social support contributes to cognitive function by affecting depression and anxiety symptoms through modifying the acquisition of coping strategies. This hypothesis is also graphically presented in Figure 1.

METHODS

Ethical approval

This study was approved by the ethical committee of Xiangya School of Public Health of Central South University (No. XYGW-2021-27). Written informed consent was obtained from all participants before interviewing.

Study design and participants

This study used a cross-sectional study design. People hospitalized due to T2DM [30] in the department of endocrinology of Xiangya Hospital of Central South University were invited to participate in this study between March 1, 2021 and December 31, 2021. Those with clinical dementia were excluded.

Data collection

Well-trained investigators, who underwent unified training before interviewing and were blinded to the hypothesized model, conducted face-to-face survey using questionnaires to collect data about socio-demographic characteristics (including age, sex, educational level, and household income), T2DM related information (including duration of diabetes, family history of diabetes, and diabetic comorbidities and complications), social support, coping strategies, and depression and anxiety symptoms. Cognitive function was assessed by experienced physicians using the Mini Mental State Examination (MMSE) [31]. All data were collected upon hospitalization and imported to a spreadsheet using the Questionnaire Star electronic questionnaire system (https://www.wjx.cn/).

Measures

Social support

The Social Support Rating Scale was applied to explore the level of social support [32]. It consists of 10 items that comprehensively measure the levels of objective support (3 items including “I often live with my family members”; “I often get economic assistance from my family members, friends, neighbors, relatives, or others when facing economic difficulties”; and “I often get consultation from my family members, friends, neighbors, relatives, or others when facing trouble”), subjective support (4 items including “I often communicate with my neighbors”; “I often communicate with my colleagues”; “my friends will help me when things go wrong”; and “my family members will help me when things go wrong”), and support utilization (3 items including “I often seek assistance positively when facing difficulties”; “I often communicate with others when in distress”; and “I often participate in social activity”). Its total score ranges from 1 to 22, 8 to 32, and 3 to 12 for the domain of objective support, subjective support, and support utilization, respectively, and a higher total score in each domain indicates a higher level of the corresponding kind of social support. This scale has been widely used in China, and the reliability and construct validity were well-validated [33].

Coping strategies

The Chinese version of Medical Coping Modes Questionnaire (MCMQ) was used to assess the coping strategies. It was initially developed by Feifel et al. [34] and specifically designed for use in medical settings. The items in the MCMQ measure coping responses to a current illness. Its Chinese version was modified by Shen and Jiang in 2000 [35]. The Chinese version of MCMQ consists of 20 items of 4-point Likert response format evaluating three types of coping strategies (confrontation, avoidance, and acceptance-resignation). Its total score ranges from 8 to 32, 7 to 28, and 5 to 20 for the domain of confrontation, avoidance, and acceptance-resignation, respectively, and a higher total score in each domain indicates more likely to apply this type of coping strategy. The Cronbach’s α coefficient for the domain of confrontation, avoidance, and acceptance-resignation was 0.69, 0.60, and 0.76, respectively; and the test-retest reliability was 0.64, 0.85, and 0.67, respectively [35].

Depression and anxiety symptoms

The Hospital Anxiety and Depression scale (HADS), one of the most frequently used scale in medical settings, was used to assess depression and anxiety symptoms in this study [36]. This scale consists of two subscales: HADS-A, designed to evaluate anxiety symptoms, and HADS-D, designed to evaluate depression symptoms. Each subscale consists of 7 items with a 4-point Likert response format. Its total score ranges from 0 to 21 in each subscale, with higher scores indicating greater severity of anxiety or depression symptoms. The Cronbach’s α coefficient for the subscale of depression and anxiety was 0.86 and 0.89, respectively [36].

Cognitive function

The MMSE was used to assess cognitive function. This scale was initially developed by Folstein et al. [31], and its Chinese version was adjusted by Li et al. [37]. This widely used tool comprehensively evaluates cognitive function including memory, registration, recall, calculation, language, ability to draw a complex polygon, and attention and orientation. Its total score ranges from 0 to 30 with lower score suggesting worse cognitive function. The Chinese version of MMSE has high reliability and validity, with an interrater correlation coefficient of 0.998 and a test-retest reliability of 0.90 after 2 to 6 days in a sample of 1,331 subjects aged 60 in an urban area of Beijing [37].

Statistical analyses

Data were analyzed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). All statistical hypotheses tests were two-tailed at the 5% significance level. Categorical variables were described using frequencies and percentages (%). Continuous variables were described using mean and standard deviation (SD), or median and inter-quartile range. Bivariate correlations between social support, coping strategies, depression, anxiety and cognitive function were examined by Pearson correlation analyses.

Before conducting the path analysis, the acceptability, construct validity and the reliability of the scales used in this study should be tested. Acceptance was evaluated by analysis of missing items, with <5% missing values per item was interpreted as satisfactory [38]. Confirmatory factor analyses (CFA) were conducted to assess the construct validity, and goodness-of-fit of the CFA models was tested using the full-information maximum likelihood method by Amos 21.0 software (IBM Corporation Software Group, Somers, NY, USA). Adequacy of the CFA models was examined using the chi-square degrees of freedom ratio (χ²/df), the standardized root mean square residual (SRMR), the Tucker-Lewis index (TLI), and the comparative fit index (CFI). In general, a χ²/df value of ≤3, a SRMR value of ≤0.08, and TLI and CFI values of ≥0.95 are indicative of good fit [39]. McDonald’s omega (ω) coefficients were computed to assess the internal consistency reliability, and a McDonald’s ω value of <0.50, 0.50 to <0.60, 0.60 to <0.70, 0.70 to <0.80, 0.80 to 0.90 and >0.90 indicates unacceptable, poor, questionable, acceptable, good, and excellent internal consistency [40]. The scales with unacceptable reliability were removed from further path analysis.

A path analysis, performed using the maximum likelihood method by Amos 21.0 software (IBM Corporation Software Group, Somers, NY, USA), was used to test the hypothesized model on the relationships between social support, coping strategies, depression, anxiety, and cognitive function among people with T2DM. Standardized regression coefficients (β) were calculated, and the direct, indirect and total effects were determined. The following indicators were used to examine the goodness of model fit: χ²/df, the goodness of fit index (GFI), the incremental fit index (IFI), CFI, the normed fit index (NFI), the root mean square error of approximation (RMSEA), and SRMR. Satisfactory model fit was indicated by χ²/df ≤3, RMSEA and SRMR values ≤0.06, and GFI, IFI, NFI and CFI values ≥0.95. When necessary, the hypothesized model was modified by removing insignificant pathways based on the principle of parsimony (also known as ‘Occam’s razor’) or pathways with the largest modification indices. The modified and bootstrap based test statistics were used for scaling corrections in covariance structure analysis, and the results were considered reliable if the 95% confidence interval (CI) for Bias-Corrected/Percentile did not overlap zero [41].

RESULTS

Characteristics of participants

A total of 530 eligible individuals were invited, of which 496 agreed to participate and provided complete data. Their mean (SD) age was 59.6 (9.9) with a range of 40 to 96, and their mean (SD) duration of diabetes was 11.2 (7.8) years. Among the 496 participants, 284 (57.3%) were males, 173 (34.9%) had an education level of middle school, and 225 (45.4%) had a family history of diabetes. In terms of diabetic complications, 262 (52.8%) and 226 (45.6%) were complicated with diabetic nephropathy and diabetic retinopathy, respectively. The characteristics of the sample are shown in Table 1.

Description of the observed variables

Table 2 shows the number of items, mean (SD), range, and the fit of every observed variable. All McDonald’s ω values and goodness-of-fit of the CFA models yielded acceptable internal consistency reliability and construct validity except for the subscale of avoidance coping (McDonald’s ω=0.297, χ²/df=6.142, SRMR=0.116, TLI=0.052, CFI=0.368). Therefore, all pathways connected to avoidance coping in the hypothesized model were removed from further path analysis.

Correlation matrix of the observed variables

Table 3 shows the correlation matrix of the observed variables included in the path analysis. All domains of social support including subjective support (r=0.15, p<0.01), objective support (r=0.25, p<0.01), support utilization (r=0.14, p<0.01), and confrontation coping (r=0.21, p<0.01) were significantly positively correlated with cognitive function. Additionally, acceptance-resignation coping (r=-0.44, p<0.01), depression (r=-0.48, p<0.01), and anxiety (r=-0.51, p<0.01) were significantly negatively correlated with cognitive function.

Path analysis

The modified path model (Figure 2) was developed after removing avoidance coping pathways due to the low internal consistency reliability. This modified path model fit was unsatisfactory (χ²/df=7.374, GFI=0.996, RMSEA=0.113, SRMR=0.096, CFI=0.995, NFI=0.995, and IFI=0.995). The standardized path coefficients (β) of subjective support to confrontation coping, subjective support to cognitive function, objective support to depression, objective support to anxiety, support utilization to anxiety, support utilization to cognitive function, confrontation coping to anxiety, and acceptance-resignation coping to cognitive function were insignificant (p>0.05), thus these pathways were removed to generate a final path model.

The final path model is shown in Figure 3. This model fit had all of its standardized path coefficients (β) significant (p<0.05), and was satisfactory (χ²/df=2.105, GFI=0.990, RMSEA=0.048, SRMR=0.053, CFI=0.992, NFI=0.986, and IFI=0.992). In addition, the overall R2 was 0.301, indicating that 30.1% of the variability in the cognitive function was explained by social support, coping strategies, and depression and anxiety symptoms.

The direct effects of variables entered into the final path model are shown in Table 4. The total, direct, and indirect effects of variables entered into the final path model are shown in Table 5. Acceptance-resignation coping to depression performed the strongest total effect (β=0.65) and the largest direct effect (β=0.65). Acceptance-resignation coping to cognitive function performed the strongest indirect effect (β=-0.32).

Table 6 shows the standardized bootstrap mediated effects, indicating that the results in the final path model were reliable because the bias corrected 95% CI and percentile 95% CI did not overlap zero.

DISCUSSION

Previous studies found a protective effect of social support against cognitive impairment in diabetic populations [18,19]. Additionally, in a previous systematic review and meta-analysis of 51 eligible longitudinal studies, Evans et al. [42] found that low levels of social isolation characterized by high engagement in social activity and large social networks were associated with better late-life cognitive function (r=0.054, 95% CI: 0.043-0.065). However, the exact nature of this association remains unclear among people with T2DM. This study found that objective support was associated with cognitive function among people with T2DM not only directly but also indirectly through confrontation coping and depression, and acceptance-resignation coping and depression/anxiety. Furthermore, subjective support was associated with cognitive function among people with T2DM indirectly through depression/anxiety, as well as serially through acceptance-resignation coping and depression/anxiety. Support utilization was associated with cognitive function indirectly through confrontation coping and depression, as well as through acceptance-resignation coping and depression/anxiety. The foregoing findings suggest that cognitive function of people with T2DM can be maintained or even improved not only directly through offering more objective support to people with T2DM by family members, neighbors, friends and community, but also indirectly by encouraging people with T2DM to adopt more confrontation coping styles, or by alleviating the symptoms of depression and anxiety in people with T2DM.

Few studies have evaluated the association between coping strategies and cognitive function, and among these limited studies, Prussien et al. [43] found that secondary control coping was significantly positively associated with verbal comprehension in a special sample of 44 children and adolescents with sickle cell disease, and Paans et al. [44] found that more active coping was significantly positively associated with better executive functioning among 90 euthymic individuals with bipolar disorder. However, this is the first study to explore the relationship between coping strategies and cognitive function among people with T2DM. The results showed that confrontation coping was associated with cognitive function among people with T2DM not only directly but also indirectly (partially mediated by depression). Also, acceptance-resignation coping was associated with cognitive function indirectly by a fully mediated model through depression/anxiety. Therefore, interventions or treatment plans targeting these modifiable factors associated with cognitive function would ensure better cognitive function for people with T2DM.

Considering depression and anxiety, this study found a significant negative correlation between the severity of depression and anxiety symptoms and cognitive function. Thus, depression and anxiety could be intervention targets for improving cognitive function among people with T2DM. This is consistent with a recent randomized, double-blinded, placebo-controlled trial [45], whose findings indicated that the traditional Chinese medicine KaiXinSan, which has been used to treat people with depression for a long time, had a beneficial effect on cognitive function related to working memory. Moreover, vortioxetine, a generally efficacious and well tolerated antidepressant agent approved in the European and the United States of America for the treatment of major depressive disorder in adults, was found to be effective in improving a broad range of cognitive domains, including executive function, attention, processing speed, learning and memory [46]. Additionally, in the animal models, it was found that chronic estradiol replacement to aged female rats reduced anxiety-like and depression-like behavior, and eventually enhanced cognitive performance [47]. Furthermore, Apium graveolens extract could influence depression and cognition in healthy mice [48].

Though this study recruited a large sample of 496 participants with complete data, there were potential limitations. Firstly, it should be noted that the model established in this study was fully based on theoretical basis from previous research which aimed to elaborate the relationships between social support, coping strategies, depression and anxiety symptoms, and cognitive function among people with T2DM. Other factors that may affect cognitive function (such as age, educational level, and diabetes complications) were not considered in this study. However, this study still added significantly to the existing body of knowledge by explaining 30.1% of the variability in cognitive function using the established model. Secondly, this was a cross-sectional study which recruited the participants from March 1, 2021 to December 31, 2021. Therefore, potential bias may be introduced. Additionally, it has been suggested that without a time-lagged design, the direction of effects is exchangeable [49]. Therefore, the potential bi-directional nature of the final path model and the exploratory nature of the present study should be particularly noted. Thirdly, this study used the MMSE to assess cognitive function. Though the MMSE was designed for cognitive deficits, especially regarding attention, memory, and language function [31], due to the high percentage of ceiling effects, it is controversial whether the MMSE can detect the early stage of cognitive decline [50]. Therefore, it is suggested for future studies to measure cognitive function using multiple instruments such as the Montreal Cognitive Assessment and the Addenbrooke’s Cognitive Examination-III to test the sensitivity of the established model. Last but not the least, this study was a hospital-based study with individuals aged at least 40. Therefore, whether the findings could be generalized to other T2DM patient settings remains unclear.

In conclusion, this study established a path model to elaborate the relationships between social support, coping strategies, depression and anxiety symptoms, and cognitive function among people with T2DM. Though social support, coping strategies, depression, and anxiety have been regarded as central not only to understanding cognitive function but also maintaining cognitive function, no prior work has examined their relationships among people with T2DM. This study found that their relationships were explained best through a serial mediation model. Specifically, objective support was associated with cognitive function not only directly but also indirectly through confrontation coping and depression, as well as through acceptance-resignation coping and depression/anxiety. Furthermore, subjective support was associated with cognitive function indirectly through depression/anxiety, as well as through acceptance-resignation coping and depression/anxiety. Also, support utilization was associated with cognitive function indirectly through confrontation coping and depression, as well as through acceptance-resignation coping and depression/anxiety. Therefore, in clinical practice, a system-based treatment plan integrating social support, coping strategies, depression, and anxiety should be implemented for improving cognitive function among people with T2DM, and depression and anxiety could be efficient intervention targets to prevent cognitive decline among people with T2DM.

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Wenjie Dai. Data curation: Rehanguli Maimaitituerxun, Jingsha Xiang, Yu Xie, Fang Xiao, Irene Xinyin Wu, Letao Chen. Formal analysis: Wenhang Chen. Funding acquisition: Wenjie Dai, Irene Xinyin Wu. Investigation: Rehanguli Maimaitituerxun, Jingsha Xiang, Yu Xie, Fang Xiao, Irene Xinyin Wu, Letao Chen. Methodology: Wenhang Chen, Wenjie Dai. Project administration: Wenjie Dai, Irene Xinyin Wu. Resources: Wenjie Dai. Software: Wenhang Chen. Supervision: Jianzhou Yang, Aizhong Liu. Validation: Rehanguli Maimaitituerxun, Jingsha Xiang, Yu Xie, Fang Xiao, Irene Xinyin Wu, Letao Chen, Jianzhou Yang, Aizhong Liu. Visualization: Wenhang Chen. Writing—original draft: Wenhang Chen. Writing—review & editing: all authors.

Funding Statement

This study was supported by the National Natural Science Foundation of China (grant number 82103939), the National Natural Science Foundation of Hunan Province (grant number 2021JJ40805), the start-up research fund of Central South University (grant number 202044003), and the National Key R&D Program of China (grant number 2020YFC2008600).

ACKNOWLEDGEMENTS

We are grateful to all participants enrolled in this study and all staff involved at the Xiangya Hospital of Central South University.

Figure 1.

Hypothesized model for the relationships between social support, coping strategies, depression, anxiety, and cognitive function among people with T2DM. T2DM, type 2 diabetes mellitus.

Figure 2.

Modified path model depicting the relationships between social support, coping strategies, depression, anxiety, and cognitive function among people with T2DM. All the coefficients were standardized path coefficient β. Significant pathways were indicated by solid lines and insignificant pathways were indicated by dashed lines. *p<0.05; **p<0.01. T2DM, type 2 diabetes mellitus.

Figure 3.

Final path model depicting the relationships between social support, coping strategies, depression and anxiety symptoms, and cognitive function among people with T2DM. All the coefficients were standardized path coefficient β.**p<0.01. T2DM, type 2 diabetes mellitus.

Table 1.

Characteristics of participants (N=496)

Variables	Value
Age (yr)	59.6±9.9
40-59	271 (54.6)
60-96	225 (45.4)
Sex
Male	284 (57.3)
Female	212 (42.7)
Educational level
Elementary school or below	106 (21.4)
Middle school	173 (34.9)
High or secondary school	101 (20.4)
College or above	116 (23.4)
Per capita monthly household income (RMB)
≤3,000	213(42.9)
3,001-5,000	128 (25.8)
≥5,001	155 (31.3)
Duration of diabetes (yr)	11.2±7.8
<5	129 (26.0)
5-9	95 (19.2)
≥10	272 (54.8)
Family history of diabetes
Yes	225 (45.4)
No	271 (54.6)
Hypertension
Yes	314 (63.3)
No	182 (36.7)
Hyperlipidemia
Yes	138 (27.8)
No	358 (72.2)
Diabetic nephropathy
Yes	262 (52.8)
No	234 (47.2)
Diabetic retinopathy
Yes	226 (45.6)
No	270 (54.4)
Diabetic foot
Yes	49 (9.9)
No	447 (90.1)
Diabetes treatment
OHA	104 (21.0)
Insulin	35 (7.1)
OHA+insulin	339 (68.3)
None or diet	18 (3.6)

Values are presented as mean±standard deviation or number (%).

RMB, renminbi; OHA, oral hypoglycemic agent

Table 2.

Descriptive statistics and internal consistency reliability analysis of scales and subscales

Variables	M±SD	Range	Number of items	McDonald’s ω	Cronbach’s α	KMO
Social support (SSRS)	42.14±7.55	12-62	10	0.76	0.79	0.72
Objective support	11.04±2.85	1-19	3	0.54	0.76	0.64
Subjective support	13.37±2.63	4-16	4	0.72	0.69	0.68
Support utilization	6.59±2.37	3-12	3	0.66	0.57	0.63
Confrontation coping	17.18±4.26	8-32	8	0.76	0.72	0.77
Avoidance coping	14.57±2.72	8-25	7	0.30	0.23	0.56
Acceptance-resignation coping	8.75±3.66	5-20	5	0.84	0.83	0.84
Depression (HADS-D)	5.45±4.64	0-21	7	0.85	0.84	0.88
Anxiety (HADS-A)	4.64±3.94	0-21	7	0.82	0.81	0.86
Cognitive function (MMSE)	26.53±4.17	1-30	30	0.88	0.88	0.84

M, Mean; SD, Standard deviation; KMO, Kaiser-Meyer-Olkin; SSRS, Social Support Rating Scale; HADS-D, the Depression subscale of Hospital Anxiety and Depression scale; HADS-A, the Anxiety subscale of Hospital Anxiety and Depression scale; MMSE, Mini Mental State Examination

Table 3.

Correlation matrix of the observed variables used in the path model

	1	2	3	4	5	6	7
1. Subjective support	1.00
2. Objective support	0.50^**	1
3. Support utilization	0.29^**	0.31^**	1
4. Confrontation coping	0.18^**	0.21^**	0.33^**	1
5. Acceptance-resignation coping	-0.25^**	-0.26^**	-0.29^**	-0.23^**	1
6. Depression	-0.30^*	-0.25^*	-0.34^**	-0.25^**	0.71^**	1
7. Anxiety	-0.26^**	-0.21^**	-0.21^**	-0.14^**	0.65^**	0.75^**	1
8. Cognitive function	0.15^**	0.25^**	0.14^**	0.21^**	-0.44^**	-0.48^**	-0.51^**

^* p<0.05;

^** p<0.01

Table 4.

Direct effects of variables entered into the final path model

Pathway	B	β	SE	p
Objective support → Confrontation coping	0.18	0.12	0.07	0.008
Objective support → Acceptance-resignation coping	-0.17	-0.13	0.06	0.008
Subjective support → Acceptance-resignation coping	-0.17	-0.12	0.07	0.012
Support utilization → Acceptance-resignation coping	-0.33	-0.22	0.07	<0.001
Support utilization → Confrontation coping	0.53	0.30	0.08	<0.001
Subjective support → Anxiety	-0.16	-0.11	0.05	0.002
Support utilization → Depression	-0.19	-0.10	0.06	<0.001
Subjective support → Depression	-0.17	-0.10	0.06	0.003
Acceptance-resignation coping → Depression	0.82	0.65	0.04	<0.001
Confrontation coping → Depression	-0.07	-0.07	0.03	0.018
Acceptance-resignation coping → Anxiety	0.67	0.62	0.04	<0.001
Objective support → Cognitive function	0.17	0.12	0.06	0.003
Confrontation coping → Cognitive function	0.09	0.09	0.04	0.016
Depression → Cognitive function	-0.16	-0.17	0.05	0.003
Anxiety → Cognitive function	-0.36	-0.34	0.06	<0.001

B, unstandardized path coefficient; β, standardized path coefficient; SE, standard error

Table 5.

Total, direct, and indirect effects of variables entered into the final path model

	Support utilization	Subjective support	Objective support	Acceptance-resignation coping	Confrontation coping	Depression	Anxiety
Total effects
Acceptance-resignation coping	-0.22	-0.12	-0.13	-	-	-	-
Confrontation coping	0.30	-	0.12	-	-	-	-
Depression	-0.26	-0.18	-0.09	0.65	-0.07	-	-
Anxiety	-0.14	-0.19	-0.08	0.62	-	-	-
Cognitive function	0.12	0.09	0.17	-0.32	0.11	-0.17	-0.34
Direct effects
Acceptance-resignation coping	-0.22	-0.12	-0.13	-	-	-	-
Confrontation coping	0.30	-	0.12	-	-	-	-
Depression	-0.10	-0.10	-	0.65	-0.07	-	-
Anxiety	-	-0.11	-	0.62	-	-	-
Cognitive function	-	-	0.12	-	0.09	-0.17	-0.34
Indirect effects
Acceptance-resignation coping	-	-	-	-	-	-	-
Confrontation coping	-	-	-	-	-	-	-
Depression	-0.16	-0.08	-0.09	-	-	-	-
Anxiety	-0.14	-0.08	-0.08	-	-	-	-
Cognitive function	0.12	0.09	0.06	-0.32	0.01	-	-

All the coefficients were standardized path coefficient β

Table 6.

The standardized bootstrap mediated effects

Pathway	Effects	SE	Bias corrected 95% CI			Percentile 95% CI
Pathway	Effects	SE	Lower bounds	Upper bounds	p	Lower bounds	Upper bounds	p
Direct effects
Objective support → Confrontation coping	0.12	0.05	0.02	0.20	0.012	0.03	0.21	0.009
Objective support → Acceptance-resignation coping	-0.14	0.05	-0.23	-0.04	0.006	-0.23	-0.04	0.005
Subjective support → Acceptance-resignation coping	-0.16	0.05	-0.24	-0.20	0.017	-0.23	-0.02	0.023
Support utilization → Acceptance-resignation coping	-0.13	0.04	-0.30	-0.14	0.002	-0.31	-0.14	0.002
Support utilization → Confrontation coping	0.30	0.04	0.22	0.38	0.002	0.22	0.38	0.002
Subjective support → Anxiety	-0.11	0.04	-0.19	-0.04	0.003	-0.18	-0.04	0.003
Support utilization → Depression	-0.07	0.04	-0.17	-0.03	0.006	-0.17	-0.03	0.006
Subjective support → Depression	-0.10	0.04	-0.19	-0.03	0.006	-0.18	-0.03	0.008
Acceptance-resignation coping → Depression	0.65	0.03	0.59	0.70	0.002	0.59	0.70	0.002
Confrontation coping → Depression	-0.06	0.04	-0.13	-0.05	0.041	-0.13	-0.05	0.041
Acceptance-resignation coping → Anxiety	0.62	0.03	0.55	0.67	0.002	0.57	0.67	0.002
Objective support → Cognitive function	0.12	0.04	0.05	0.21	0.002	0.04	0.20	0.002
Confrontation coping → Cognitive function	0.10	0.04	0.02	0.18	0.010	0.02	0.17	0.015
Depression → Cognitive function	-0.17	0.07	-0.31	-0.04	0.008	-0.31	-0.03	0.009
Anxiety → Cognitive function	-0.35	0.06	-0.47	-0.22	0.002	-0.47	-0.22	0.002
Indirect effects
Objective support → Confrontation coping→ Cognitive function	0.06	0.02	0.02	0.09	0.002	0.02	0.09	0.002
Objective support → Acceptance-resignation coping → Anxiety	-0.08	0.03	-0.14	-0.03	0.006	-0.14	-0.03	0.005
Objective support → Acceptance-resignation coping → Depression	-0.09	0.03	-0.16	-0.03	0.005	-0.16	-0.03	0.004
Subjective support → Anxiety/Depression → Cognitive function	0.10	0.03	0.05	0.15	0.001	0.05	0.15	0.002
Subjective support → Acceptance-resignation coping → Anxiety	-0.08	0.03	-0.15	-0.02	0.014	-0.15	-0.01	0.023
Subjective support → Acceptance-resignation coping → Depression	-0.08	0.04	-0.16	-0.02	0.014	-0.15	-0.01	0.023
Support utilization → Confrontation coping/Depression → Cognitive function	0.12	0.02	0.08	0.17	0.001	0.08	0.17	0.002
Support utilization → Acceptance-resignation coping → Anxiety	-0.14	0.03	-0.19	-0.09	0.002	-0.19	-0.09	0.002
Support utilization → Acceptance-resignation coping → Depression	-0.16	0.03	-0.22	-0.10	0.002	-0.22	-0.11	0.002
Acceptance-resignation coping → Anxiety/Depression → Cognitive function	-0.33	0.03	-0.39	-0.26	0.002	-0.39	-0.26	0.002
Confrontation coping → Depression → Cognitive function	0.01	0.01	0.03	0.08	0.089	0.03	0.08	0.035
Total effects
Objective support → Cognitive function	0.18	0.04	0.10	0.27	0.002	0.10	0.26	0.002
Subjective support → Cognitive function	0.10	0.03	0.05	0.15	0.001	0.05	0.15	0.002
Support utilization → Cognitive function	0.12	0.02	0.08	0.17	0.001	0.08	0.17	0.002

SE, standard error; CI, confidence interval

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