Introduction

Diabetes is a national health problem in many countries. The number of patients with diabetes worldwide was estimated as 537 million in 2021, and this number is expected to rise to 733 million by 2045 (International Diabetes Federation, 2021). Diabetes is associated with several physical complications such as cardiovascular disease and renal disease (American Diabetes Association, 2020). In addition, the complex, multifaceted requirements associated with diabetes care in daily life may also compromise the mental health of patients with diabetes (American Diabetes Association, 2020).

Depression and its symptoms are a common mental health problem in patients with diabetes. The mean prevalence of depressive symptoms in patients with diabetes is 28.3%, with younger patients showing a higher prevalence than older patients (Harding et al., 2019). Previous studies have found the prevalence of depression to be 2–5 times higher in patients with diabetes than in the general population (Bădescu et al., 2016; Deischinger et al., 2020). In addition, the risks of cardiovascular disease and stroke have been shown to be higher in patients with diabetes and depression than in patients with diabetes without depression, which may be mediated by suboptimal self-care and common pathophysiological mechanisms via stress and inflammation (Cummings et al., 2016; Deischinger et al., 2020).

Women with diabetes are more likely to experience depression than men (Deischinger et al., 2020; Sartorius, 2018). In addition, among patients with diabetes, depression is more common in age groups below 65 years (Khaledi et al., 2019). On the basis of the above, women with diabetes younger than 65 years old should be considered at a high risk of comorbid depression. Understanding the factors associated with depression will help design more-timely preventative strategies for this group.

Psychosocial factors that contribute to depression in patients with diabetes, such as personality traits, diabetes-related distress, and role strain, may also contribute to depression in women with diabetes. Personality traits determine individual stress reactivity and psychological adjustment to stress and are generally recognized as being highly correlated with depression (Widiger et al., 2019). Type D personality refers to a set of personality traits that involve high negative affectivity (e.g., gloom and irritability) and high social inhibition (e.g., reticence and lack of self-confidence; Denollet et al., 2010). Individuals with high negative affectivity are inclined to experience negative emotions toward different situations and times, whereas those with high social inhibition tend to exhibit irrational anxiety, insecurity, and alexithymia in social settings (Denollet et al., 2010). Because this personality type leads people to experience low social support, loneliness, and hopelessness, Type D personality involves distressed and neurotic characteristics that tend to promote depression (Al-Qezweny et al., 2016; Shao et al., 2017) and is positively correlated with depressive mood (Conti et al., 2016; Lin et al., 2020). Nevertheless, the relationship between Type D personality and depression in women with diabetes has been inadequately explored.

Self-management is generally a significant burden for patients with diabetes that may elicit negative emotional reactions. Diabetes-related distress refers to the negative emotional response to coexisting with and self-managing the symptoms of diabetes (Kreider, 2017) and includes fearing the pain caused by insulin injections and feeling troubled by the care required to preserve insulin, among other responses. The results of a meta-analysis suggest that 36% of patients with diabetes experience diabetes-related distress (Perrin et al., 2017). Diabetes-related distress is generally thought of as patient suffering and is not considered to be a mental illness.

The findings of many studies support that patients with Type 2 diabetes have higher levels of diabetes-related distress than of depression (Kreider, 2017; Nanayakkara et al., 2018). Fisher et al. (2014) found that 80% of patients with diabetes experience moderate or higher levels of diabetes-related distress rather than from clinical depression. However, there is a high chance of detecting depression in patients untreated for diabetes-related distress (Hermanns et al., 2013). Many previous studies have shown diabetes-related distress as significantly associated with depression in patients with Type 2 diabetes (Al-Ozairi et al., 2020; Roy et al., 2018), although not specifically in women with diabetes. The relationship between diabetes distress and depression in women with diabetes deserves further study.

Role strain occurs when individuals have difficulty meeting their responsibilities and social expectations for a particular role. Traditionally, women take responsibility for family caring and recognize related tasks as obligatory for them (Tavero et al., 2018). Women with diabetes are required to execute additional and complex diabetic self-management activities, which increases their overall role strain while continuing to perform their family care duties. A previous study found that middle-aged women with diabetes were more sensitive to perceived role strain (Park & Kim, 2012). In general, role strain in women is regarded as an adverse condition leading to anxiety and frustration (Goode, 1960) and has been associated with depression (Huang et al., 2020; Park & Kim, 2012). The contribution of role strain should be considered when considering the factors associated with depression in women with diabetes.

In addition, women with diabetes having low educational level, living without spouses, being unemployed, and having a long duration of diabetes with high body mass index (BMI) and HbA1c levels show high prevalence of depression (Ahmad et al., 2018; Al-Ozairi et al., 2020). These demographic and disease characteristics should be considered as covariates when exploring the association between psychosocial factors and depression in this group. Therefore, the aim of this study was to examine the impacts of Type D personality, diabetes-related distress, and diabetes-care-related role strain on depression in women with Type 2 diabetes.

Methods Design and Sampling

This study employed a cross-sectional design and was part of a larger prospective study (Wang et al., 2021). Two hundred ninety-eight women aged 20–64 years were selected using convenience sampling from three outpatient endocrine clinics in Taiwan. The inclusion criteria were being diagnosed with Type 2 diabetes for more than 6 months and having adequate Mandarin Chinese language comprehension. A minimum sample size of 166 was estimated based on an α of .05, a medium effect size of 0.15 in explained variance in depression, a power of .90, and 14 predictors. Thus, the 298 women with Type 2 diabetes enrolled as participants was considered an adequate sample size for this study, which was conducted from October 2018 to May 2019.

Measurement

Data were collected using a self-reported questionnaire administered at a quiet waiting room during participant clinic visits and using patient medical records.

Demographic and disease characteristics

Demographic and disease characteristics including age, educational level, marital status, job status, and duration of diabetes were collected using a self-reported questionnaire. A research assistant transcribed information on insulin for treatment (yes/no), BMI, and HbA1c levels from the medical record of each participant.

Diabetes-care-related role strain

Diabetes-care-related role strain was evaluated using a Chinese-version role strain scale for women with diabetes that was designed to gather information on the subjective experience of diabetes-care-related role conflicts and role guilt (Huang et al., 2020). The scale contained nine items rated from strongly disagree (1) to strongly agree (5), with a total possible score ranging from 9 to 45 and a higher total score indicating higher diabetes-care-related role strain. The Cronbach's α of this scale was .86 in this study.

Type D personality

Type D personality was investigated using the Type D Scale-Taiwanese version, which uses two subscales to respectively measure negative affectivity and social inhibition personality traits (Weng et al., 2013). Each trait was measured using seven items, rated from 0 (false) to 4 (true) points, with higher scores indicating more-significant negative affectivity or social inhibition traits. The Cronbach's α scores for the negative affectivity and social inhibition subscales and the overall scale were .90, .84, and .90, respectively, in this study.

Diabetes-related distress

Diabetes-related distress was assessed using a Chinese-version short-form Problem Areas in Diabetes scale (Hsu et al., 2013). This scale consists of eight items, each rated on a 5-point Likert scale ranging from not a problem (0) to serious problem (4). Total possible scale scores range from 0 to 32, with higher scores associated with higher levels of diabetes-related distress. The Cronbach's α of the Problem Areas in Diabetes scale was .93 in this study.

Depression

A 20-item Chinese version of the Center for Epidemiological Studies-Depression (CES-D) scale was used to assess the symptoms of depression in participants during the past week (Chien & Cheng, 1985). Scale items were scored between 0 (rarely or none of the time) and 3 (most or almost all the time). The item scores were summed to generate the total depression score (range: 0–60), with higher scores indicating greater depressive symptoms. A total score of ≥ 16 was used to indicate being at risk of clinical depression. The CES-D scale has shown good validity and reliability and been widely used in Taiwanese samples (Chien & Cheng, 1985). In this study, the Cronbach's α of this scale was .86.

Ethical Considerations

This study was approved by the institutional review boards of the three participating hospitals (KMUHIRB-E[I]-20180108, YUAN-IRB-20180921B, and TSGHIRB-2-107-05-151). The participants were informed of their right to withdraw from this study at will. To ensure the confidentiality of participant information, self-reported questionnaires were coded and administered to participants after they had signed the consent form. A research assistant transcribed the information related to insulin for treatment (yes/no), BMI, and HbA1c levels from the medical records of the participants. Medical record numbers were not identified in the questionnaire.

Statistical Analysis

IBM SPSS Statistics Version 22.0 (BM Inc., Armonk, NY, USA) was used to perform statistical analyses. Descriptive statistics were used to describe the distributions of the study variables, whereas bivariate correlations among variables were examined using Pearson's correlation coefficient. Furthermore, hierarchical multiple regression analysis was used to investigate the important factors of influence for depression. Blocks of demographic and disease characteristics, negative affectivity, social inhibition, diabetes-care-related role strains, and diabetes-related distress were entered sequentially into the hierarchical multiple regression analysis, with educational level, marital status, family structure, job status, diabetes type, and insulin treatment factors each assigned dummy codes. p Values < .05 were used to determine statistical significance.

Results Distribution of and Associations Among Study Variables

The distributions of demographic and disease characteristics are presented in Table 1. The participants were aged from 21 to 64 (M = 52.56, SD = 9.36) years, and the prevalence of depression (score ≥ 16) was 27.5% (n = 82). As shown in Table 2, Type D personality was significantly and positively correlated with depression (r = .55, p < .001), negative affectivity and social inhibition were significantly and positively correlated (r = .65, p < .001), and negative affectivity (r = .68, p < .001) and social inhibition (r = .50, p < .001) were significantly and positively correlated with depression. Both role strain (r = .41, p < .001) and diabetes-related distress (r = .44, p < .001) were shown to be significantly and positively correlated with depression. Type D personality was found to be significantly and positively correlated with both diabetes-related distress (r = .34, p < .001) and diabetes-care-related role strain (r = .40, p < .001), whereas diabetes-care-related role strain was identified as significantly and positively associated with diabetes-related distress (r = .46, p < .001).

Table 1. - Distribution of Participant Demographic and Disease Characteristics (N = 298) Variable n % Age (years; M and SD) 52.56 9.36 Educational level  Elementary school or below 45 15.1  Junior high school 46 15.4  Senior high school 114 38.3  College or above 93 31.2 Marital status  Unmarried 47 15.8  Divorced/widowed 53 17.8  Married 198 66.4 Job status  None 123 41.3  Full-time 139 46.6  Part-time 36 12.1 Duration of diabetes (years; M and SD) 10.48 8.34 Insulin for treatment  No 209 70.1  Yes 89 29.9 Body mass index (kg/m2; M and SD) 27.17 5.17 HbA1c levels (%; M and SD) 7.66 1.32  Range 5.1–13.0
Table 2. - Distributions of Type D Personality, Role Strain, Diabetes Distress, and Depression and Correlations Among Participants (N = 298) Factor M SD 1 1-1 1-2 2 3 4 1. Type D personality 13.24 11.57 – .64*** .71*** .40*** .34*** .55***  1–1 Negative affectivity 7.02 6.78 – .65*** .37*** .40*** .68***  1–2 Social inhibition 6.23 5.99 – .34*** .36*** .50*** 2. Diabetes-care-related role strain 16.43 7.75 – .46*** .41*** 3. Diabetes-related distress 9.25 7.53 – .44*** 4. Depression 11.82 8.72 –
Important Factors of Depression

The results of the hierarchical multiple regression analysis are presented in Table 3. A diagnostic test was performed before conducting the hierarchical multiple regression to examine collinearity among the independent variables. Multicollinearity was shown to not be a concern, as variance inflation factors ranged between 1.07 and 2.03 and tolerance scores ranged between .52 and .94. As shown in the first step (Model 1) of hierarchical multiple regression, demographic and disease characteristics were put into the regression model, although neither of these characteristics significantly associated with depression. In the second step (Model 2), after negative affectivity was input, an additional 43.4% of the variance in depression was found, with the change in R2 found to be significant, F(9, 288) = 29.71, p < .001. In the third step (Model 3), adding social inhibition explained an additional 0.8% of the variance in depression, with the change in R2 found to be significant, F(10, 287) = 27.48, p < .001. In the fourth step (Model 4), adding diabetes-care-related role strain explained an additional 3% of the variance in depression, with the change in R2 found to be significant, F(11, 286) = 28.13, p < .001. Age was also found to be significantly associated with depression, although social inhibition was not after the variable of diabetes-care-related role strain had been added. In the last step (Model 5), diabetes-related distress explained an additional 2.5% of the variance in depression, with the change in R2 found to be significant, F(12, 285) = 28.386, p < .001. In summary, age (β = .133, p < .01), negative affectivity (β = .517, p < .001), diabetes-care-related role strain (β = .138, p < .01), and diabetes-related distress (β = .194, p < .001) were identified as significant explanatory factors of depression (Table 3).

Table 3. - Hierarchical Multiple Regression of Depression in Participants (N = 298) Demographic and Disease Characteristic Model 1 Model 2 Model 3 Model 4 Model 5 β β β β β Age −.023 .086 .090 .109* .130** Educational level a −.097 .010 .001 .004 −.013 Marriage status b −.102 −.082 −.067 −.074 −.064 Occupational status c −.051 −.007 .001 .005 −.007 Duration of diabetes .127 .026 .028 .027 .038 Treatment d .105 .003 −.002 −.040 −.051 HbA1c levels −.002 .011 .021 .006 −.007 Body mass index −.081 −.039 −.054 −.053 −.057 Type D personality  Negative affectivity .682*** .604*** .564*** .517***  Social inhibition .121* .087 .071 Diabetes-care-related role strains .197*** .138** Diabetes-related distress .194*** R 2 .031 .465 .471 .501 .525 R 2 change – .434 .008 .030 .025 F value 2.194* 29.708*** 27.484*** 28.127*** 28.386*** F for change 2.194* 235.579*** 4.355* 18.140*** 15.526***

Note. β = standardized beta coefficients.

a 0 = junior high school and below, 1 = high school and above. b 0 = no spouse, 1 = have spouse. c 0 = unemployed, 1 = employed. d 0 = only oral medication, 1 = insulin treatment and oral medication.

*p < .05. **p < .01. ***p < .001.

Discussion

In this study, the prevalence of depression in participants was found to be 27.5%, which is similar to a meta-analysis that found a mean prevalence of depression in patients with diabetes of 28.3% (Harding et al., 2019). However, the prevalence of depression in participants was higher than the 15.9% prevalence previously found in the general female population in Taiwan using the same CES-D scale (Tai et al., 2014). The finding of this study supports that women with diabetes experience higher depression than the general female population and that this issue deserves greater attention from healthcare providers.

Higher levels of negative affectivity and social inhibition were shown to be significantly associated with higher levels of depression in this study, which is consistent with previous studies (Nefs et al., 2015; Weng et al., 2013). Of particular note, negative affectivity (but not social inhibition) was identified as an important factor associated with depression after controlling for other variables. In addition, negative affectivity explained 43.4% of the variance in depression. This finding is consistent with the results of previous studies (Spek et al., 2018; van Dooren et al., 2016).

People with high negative affectivity are more prone to experience worry, anger, frustration, and hopelessness. Thus, high levels of negative affectivity contribute to depression in women with diabetes. However, because social inhibition influences the amount of interactivity that individuals engage in with others to release stress, this factor is more weakly associated with depression than either diabetes-care-related role strain or diabetes-related distress, which are more related to diabetes care. A previous meta-analysis identified a significant reduction effect of brief mindfulness training on negative affectivity (Schumer et al., 2018). Nurses may regularly assess negative affectivity using the Type D Scale-Taiwanese version in clinical settings and provide early, brief mindfulness training sessions to reduce negative affectivity to prevent the onset and development of depression in women with Type 2 diabetes.

High levels of diabetes-related distress were significantly correlated with higher levels of depression in this study, which is consistent with the findings of previous studies (Al-Ozairi et al., 2020; Roy et al., 2018). In addition, high levels of diabetes-care-related role strain were significantly correlated with depression in women with Type 2 diabetes, which is also consistent with the findings of previous studies (Huang et al., 2020; Park & Kim, 2012). Nevertheless, the explained variance in diabetes-related distress and diabetes-care-related role strain on depression in this study was only 2.5% and 3%, respectively, after considering other variables. Compared with negative affectivity, the associations between depression and the two factors of diabetes-related distress and diabetes-care-related role strain were not as high as initially hypothesized in this study, with both factors earning relatively low scores. Their relatively low levels may limit their contribution to depression. Another explanation may be that diabetes-related distress and diabetes-care-related role strain may fluctuate based on the context of diabetes care, whereas negative affectivity is an ingrained trait that constantly affects an individual's response to stress and thus results in its relatively stronger association with depression. Further study is required to adequately clarify and confirm this issue.

Different from previous studies conducted in other countries (Ahmad et al., 2018; Al-Ozairi et al., 2020), demographic and disease characteristic variables with the exception of age were not found to be significantly associated with depression in this study. This discrepancy may reflect cultural and/or healthcare system differences across countries and deserves clarification in future studies. In this study, age was identified as a significant factor affecting depression after controlling for negative affectivity, social inhibition, diabetes-care-related role strain, and diabetes-related distress. Older women with diabetes may be affected by additional stress-inducing factors such as the empty-nest syndrome and menopause, which may exacerbate depression and require further exploratory studies for clarification. However, older women with diabetes should be considered at risk for high levels of depression. Finally, the variables addressed in this study explained 52.5% of the variance in depression. Further studies are needed to explore other associated factors such as social support to increase the explained variance in depression in women with Type 2 diabetes.

Limitations

Several limitations should be considered. The participants were recruited from three outpatient clinics in Taiwan, which limits the generalizability of the conclusions. In future studies, participants should be recruited from a more-diverse pool of hospitals and clinics. In addition, this study selected women aged from 20 to 64 years only, which may not allow the conclusions to be extrapolated to women 65 years and older. Further studies may involve women older than 65 years. Self-reported questionnaires rather than structured diagnostic interviews by clinicians based on established criteria were used to assess the depression status of the participants, which may have biased our identification of depression. Further studies may use a combined self-reported questionnaire/clinical diagnosis approach to objectively assess depression in women with Type 2 diabetes. Causal–effect relationships among the variables in this study could not be confirmed in this study because of the cross-sectional design used. Longitudinal studies measuring Type D personality, diabetes-care-related role strain, and diabetes-related distress at baseline and with follow-up for depression are suggested. In addition, experimental studies investigating the potential influences of Type D personality, diabetes-care-related role strain, and diabetes-related distress on depression are suggested to confirm the causal relationships identified in this study.

Conclusions

The findings of this study support that the negative affectivity associated with the Type D personality has a significantly greater negative impact on depression in women with diabetes than diabetes-related psychosocial factors such as diabetes-related distress and diabetes-care-related role strains. Timely assessment of negative affectivity and providing the brief mindfulness intervention to reduce negative affectivity may be effective in preventing/reducing depression in women with Type 2 diabetes. Moreover, considering the important associations between both diabetes-related distress and diabetes-care-related role strain and depression, these two factors should be appropriately addressed in any comprehensive and timely depression-preventing intervention developed for women with Type 2 diabetes.

Acknowledgments

This work was supported by Yuan's General Hospital under Grant YGH-19-030 and the Ministry of Science and Technology under Grant MOST 107-2629-B-037-001.

Author Contributions

Study conception and design: RHW

Data collection: SYC, HCH, CLH

Data analysis and interpretation: YHC, RHW

Drafting of the article: SYC, HCH, YHC, RHW

Critical revision of the article: SYC, RHW

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