Abstract
Background
Patients with end-stage kidney disease (ESKD) undergoing renal replacement therapy often face significant psychological distress and depression. The social environment of these individuals may influence depressive symptoms, but research on social capital in this group is limited. This study aimed to assess the prevalence of clinically significant depressive symptoms and explore the association between different dimensions of social capital and clinically significant depressive symptoms in ESKD patients.
Methods
A cross-sectional study was conducted involving 819 patients with ESKD who were undergoing peritoneal dialysis or hemodialysis at three medical facilities of the Mexican Institute of Social Security in Aguascalientes, Mexico. Data on patients’ characteristics was collected from April 2023 to January 2024. Depressive symptoms were measured on the Beck Depression Inventory II, considering a score of 17 or higher as indicative of clinically significant depressive symptoms. We utilized a validated Social Capital Questionnaire specifically designed for ESKD patients in Mexico to evaluate structural and cognitive social capital and its dimensions. Multivariable logistic regression analysis was performed to evaluate the association between social capital and clinically significant depressive symptoms.
Results
The prevalence of clinically significant depressive symptoms was 27.2% (95% CI 0.24–0.30). In the structural domain of social capital, “network size” (OR 0.85; 95% CI 0.80–0.91) and “bonding within social groups” (OR 0.85; 95% CI 0.78–0.93) were associated with lower odds of clinically significant depressive symptoms, while “vertical bridging” was associated with higher odds (OR 1.06; 95% CI 1.02–1.10). In the cognitive domain, “norms of reciprocity” (OR 0.97; 95% CI 0.95–0.99), “sense of belonging” (OR 0.92; 95% CI 0.87–0.96), and “social support” (OR 0.85; 95% CI 0.80–0.90) were associated with decreased odds of clinically significant depressive symptoms, while “sense of fairness” was associated with increased odds.
Conclusion
Most social capital dimensions are associated with decreased odds of clinically significant depressive symptoms in patients with ESKD. Our findings emphasize the need for strategies that enhance the protective aspects of social capital, ultimately helping to reduce the prevalence of depressive symptoms among patients with ESKD.
Keywords: Social capital, Depressive symptoms, Chronic kidney disease, Mexico
Background
End-stage kidney disease (ESKD) poses a serious health challenge that creates considerable economic, physical, and emotional strain on patients and their families, reducing the years of healthy life for those affected, increasing their years living with disability, and leading to early mortality [1].
Patients with ESKD who start renal replacement therapy with peritoneal dialysis or hemodialysis face numerous physical, emotional, and social challenges, accompanied by considerable psychosocial impairment that severely affects their quality of life [2].
Depression is common in ESKD patients, with a global prevalence of 26.5%, which is five times higher than in the general population [3–5]. Additionally, the psychological distress experienced by these patients doubles the risk of complications such as cardiovascular disease, infections [6, 7], falls and injuries [8], and the likelihood of death [3–11].
Prior research has indicated that factors such as being female, having a lower educational background, limited income, the presence of comorbidities, an extended duration of chronic kidney disease, low hemoglobin levels, and undergoing hemodialysis are associated with a higher chance of experiencing depression in ESKD patients [11–14]. Moreover, insufficient support for treatment expenses is also connected to depressive symptoms [12].
Social Capital (SC) refers to “elements of social organization, such as networks, norms, and social trust that enable coordination and cooperation for mutual benefit” [15]. SC has been studied as a social determinant of mental health [16] and has been recognized as a protective factor against depressive symptoms. The mechanisms that explain the influence of SC on mental health involve the promotion of healthy behaviors within social groups, facilitating the access to relevant health information, collective efficacy that aids in obtaining material resources, and emotional support that alleviates stress and loneliness, which can trigger depression [17–19].
In the existing literature, several dimensions of SC have been identified as protective factors against depression, including engagement in organizations [20–22], social networks [21, 22], and social ties [23] in the structural domain, as well as trust [21–24] and social support [25] in the cognitive domain. However, not every SC dimension is a protective factor across all studies, as they are conducted in populations characterized by different ages, health conditions, and contexts [26]. Although these studies have shown an association between higher SC and a lower probability of depressive symptoms, we did not find research specifically examining this association in patients with ESKD.
In Mexico, the prevalence of chronic kidney disease (CKD) is on the rise. From 1990 to 2021, the incidence of CKD per 100,000 individuals surged by 188% in men and by 153% in women [27]. In 2021, CKD was responsible for 69,052 deaths in the country, resulting in a national mortality rate of 53.41 per 100,000 individuals across all age groups [28].
Meanwhile, data regarding the prevalence of clinically significant depressive symptoms among CKD patients in Mexico is scarce and drawn from small studies involving fewer than 200 patients, which indicated that the prevalence of depressive symptoms varied from 25 to 76% [29–31]. Notably, the role of social capital in patients with CKD in Mexico is currently unknown. This gap in knowledge is relevant given the potential consequences that SC may have on health outcomes. Gaining information on the dimensions of SC that influence depressive symptoms in patients with ESKD could offer valuable insights. Such information could guide the design and implementation of targeted interventions aimed at enhancing SC and ultimately improving patients’ psychological well-being by addressing the interplay between social capital and mental health. Therefore, the objective of this study was to evaluate the prevalence of clinically significant depressive symptoms and analyze the association between social capital and these symptoms in dialysis patients with ESKD.
Methods
Design and setting of the study
We conducted a cross-sectional study at three medical facilities of the Mexican Institute of Social Security (IMSS) in Aguascalientes, Mexico: one Zone General Hospital, one Nephrology outpatient clinic, and one subrogated hemodialysis unit. Data was collected from April 2023 to January 2024.
Sample size
To address the first study objective, we determined that a minimum sample size of 247 patients is necessary to assess the prevalence of clinically significant depressive symptoms. This estimation was based on an expected 26% prevalence[32] of depressive symptoms among ESKD patients, a total population size of 1,505 patients, a margin of error of 5%, and a confidence level of 95%.
For the second objective, we utilized the Freeman 10 * (k + 1) method to estimate the minimal sample size needed to detect associations of social capital with clinically significant depressive symptoms. This method consists of adding a minimum of 10 patients for each variable included in the multivariable analysis [33]. In our research, we considered a total of 43 variables, which encompassed both independent variables and confounders, including dummies for categorical variables, resulting in a minimum of 431 patients. To account for potential non-response rates and missing data, and to ensure that our analysis achieves 90% power for both study objectives we decided to Double the sample size, inviting 866 patients to take part in the study.
Participants
The inclusion criteria encompass diagnosis of ESKD and renal replacement therapy with peritoneal dialysis or hemodialysis, being over 18 years of age, and agreeing to participate in the study. Patients with a medical diagnosis or self-reported cognitive impairment were not included.
Participants were identified through the State Registry of Chronic Kidney Disease in Aguascalientes. At the beginning of 2023, this registry had information on 1,956 patients with ESKD, of whom 1,505 were enrolled in the IMSS. A total of 866 patients was selected through a systematic sampling method that involved inviting every even-numbered patient with ESKD from the state registry. These patients receive healthcare in three IMSS medical facilities (Zone General Hospital, Nephrology outpatient clinic, and a subrogated hemodialysis unit). Six trained interviewers approached patients to participate in the study while they were waiting for hemodialysis sessions or consultations with nephrology specialists. The interviewers provided detailed information about the study, obtained signed informed consent from the patients, and administered the questionnaire.
Questionnaire
The questionnaire consisted of three parts: the first part included inquiries about the patients’ socioeconomic and clinical details; the second consisted of the Social Capital Questionnaire specifically designed and validated for ESKD patients in Mexico [34] and the third part comprised the Beck Depression Inventory II [35].
Variables
Demographic and Clinical Characteristics
The demographic characteristics of the patients included age, sex, marital status, education, occupation, and socioeconomic status (SES). The SES was defined according to the Mexican Association of Market Intelligence and Opinion Agencies, reflecting the quality of life within a household based on education, housing, connectivity, and technology use. The letters A-E denote the seven socioeconomic levels: A/B for the upper class with high purchasing power; C + for the upper-middle class with above-average access to goods and services; C for the middle class with average living conditions; C- for the lower-middle class with limited access; D + for the lower class with significant restrictions; D for the very low class with minimal access to services; and E for extreme poverty, lacking resources to meet basic needs [36].
The clinical characteristics encompassed the CKD duration since the diagnosis and the initiation of renal replacement therapy. Additionally, we registered whether the patient participated in the kidney transplant protocol, had any comorbidities, had a history of a prior diagnosis of depression or anxiety, or was currently undergoing treatment for depression. Information was also collected regarding the history of kidney transplant and the timing of appointments. All clinical information obtained from patients was verified in the participants’ clinical records. We also obtained recent laboratory results (within the past year) for hemoglobin levels, plasma albumin, parathyroid hormone, and phosphorus levels from the laboratory database. These biomarkers were included due to their association with worsened health outcomes in patients with advanced chronic kidney disease, including adverse neuropsychiatric effects [37, 38].
Social capital
We used previously developed and validated in Mexico, the Social Capital Questionnaire for ESKD patients. This questionnaire assesses SC across two domains: the structural Domain, which includes seven dimensions and 28 questions, and the cognitive Domain, consisting of six dimensions and 38 questions. Responses to the questions are given on a Likert scale, with scores ranging from 1 to 5; a higher score indicates a greater level of social capital. In the structural domain, the summary scores for the dimensions of “participation in organizations,” “links with institutions,” and “collective action” range from a minimum of 3 to a maximum of 15. For the dimension of “network size,” the summary scores range from 6 to 30. The scores for “group diversity” and “bonding within social groups” range from 4 to 20, while for “vertical bridging,” the score range is from 5 to 25. In the cognitive domain, the summary scores for the dimensions of “norms of reciprocity,” “sense of fairness,” and “social trust” range from 8 to 40. The score for “social harmony” ranges from 3 to 15, for “sense of belonging” from 5 to 25, and for “social support” from 6 to 30 [34].
To assess social capital, we defined social groups as “social entities composed of two or more individuals who interact with one another, share a sense of identity, and are bound by a common purpose” [39]. Based on this general definition, we subsequently defined particular groups. For instance, we defined “Social media groups” as networks of individuals that connect through digital platforms such as Facebook, Twitter, Snapchat, Telegram, Instagram, WeChat, TikTok, Messenger, and other social networks accessible via smartphones or computers. We defined “Groups of people with chronic illnesses” as those formed within healthcare settings to provide support and education to patients on self-care strategies and to share their experiences.
The Beck Depression Inventory II
This is one of the most widely used tools to assess depressive symptoms in patients with ESKD [40–45]. It consists of 21 Questions, each with four response options ranging from 0 to 3 and a summary score ranging from 0 to 63. According to Preljevic et al. recommendations for screening depression in dialysis patients, a score of 17 or higher indicates clinically significant depressive symptoms in Line with the criteria for major depression set in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. This cutoff score has a sensitivity of 0.82 and a specificity of 0.89 [45].
Statistical analysis
For the descriptive analysis, we first evaluated the distribution of the data using the Kolmogorov-Smirnov test. For variables with a normal distribution, we reported the mean as the measure of central tendency and the standard deviation to indicate dispersion. For variables lacking a normal distribution, we used the median and minimum and maximum values [46].
We then conducted a bivariate analysis to compare the characteristics of participants with and without clinically significant depressive symptoms. The Student’s t-test was applied for continuous variables that followed a normal distribution, while the Mann-Whitney U test was used for those with a non-normal distribution. For categorical variables, the chi-square test was employed.
To assess the association between social capital and clinically significant depressive symptoms, we performed multiple logistic regression with robust variance, which is recommended for analyzing cross-sectional studies with a dichotomous dependent variable [47]. We estimated both crude and adjusted odds ratios (ORs) with 95% confidence intervals (95% CI). We included all relevant sociodemographic and clinical variables in this analysis, regardless of their statistical significance, in line with the recommendations of VanderWeele and Shpitser [48]. The covariates used to adjust the structural and cognitive domains in multivariable logistic regression model were age, sex, marital status, occupation, education, diabetes and hypertension, previous diagnosis of depression, current treatment for depression, previous diagnosis of anxiety, socioeconomic status, treatment modality, time since CKD diagnosis, time since initiation of renal replacement therapy, kidney transplant protocol, hemoglobin, albumin, parathyroid hormone, and phosphorus. We also considered the effect of clustering within the health facilities through hierarchical clustering analysis. Finally, based on insights from the Literature review, we tested but did not find an interaction between social capital and sex. The analysis was conducted using STATA version 18, developed by StataCorp LLC, College Station, TX, USA.
Results
Out of 1,505 IMSS ESKD patients registered in the State Registry of Chronic Kidney Disease in Aguascalientes, 866 were invited to participate in the study. Of those invited, 27 (3%) declined to participate. Interviews were conducted with 839 patients; however, 20 (2.4%) were excluded due to incomplete information, resulting in the sample of 819 participants. This incomplete data occurred because some interviews were suspended due to fatigue or discomfort experienced by the participants during the process.
Two hundred and twenty-three participants (27.2%, 95% CI 0.24–0.30) had clinically significant depressive symptoms, as indicated by a Beck II scale score of 17 or higher. Table 1 presents the sociodemographic characteristics of patients with and without clinically significant depressive symptoms. Those with clinically significant depressive symptoms were more likely to be women (p < 0.001) and engaged in housework or retired, whereas those without symptoms were more often employed (p = 0.003).
Table 1.
Sociodemographic characteristics of participants with and without clinically significant depressive symptoms (n = 819)
| Covariates | Total n = 819 n (%) |
Without clinically significant depressive symptoms n = 596 n (%) |
With clinically significant depressive symptoms n = 223 n (%) |
p* |
|---|---|---|---|---|
| Age in years | ||||
| Median (min-max) | 41 (18–86) | 40 (18–86) | 42(19–81) | NS |
| Sex | ||||
| Men | 459 (56.0) | 362 (60.74) | 97 (43.5) | < 0.001 |
| Women | 360 (44.0) | 234 (39.26) | 126 (56.5) | |
| Marital status | ||||
| Single | 304 (37.1) | 228 (38.3) | 76 (34.1) | NS |
| Married or in a civil partnership | 515 (62.9) | 368 (61.7) | 147 (65.9) | |
| Schooling | ||||
| None or incomplete primary school | 105 (12.8) | 76 (12.8) | 29 (13.0) | NS |
| Primary school | 151 (18.4) | 115 (19.3) | 36 (16.1) | |
| Secondary school | 299 (36.5) | 213 (35.7) | 86 (38.6) | |
| High school | 176 (21.5) | 125 (21.0) | 51 (22.9) | |
| University education with or without postgraduate degree | 88 (10.7) | 67 (11.2) | 21 (9.4) | |
| Occupation | ||||
| Paid job | 265 (33.4) | 211 (35.4) | 54 (24.2) | 0.003 |
| Household activities | 231 (28.2) | 152 (25.5) | 79 (35.4) | |
| Retiree | 216 (26.4) | 151 (25.3) | 65 (29.2) | |
| Unemployed/student | 107 (13.0) | 82 (13.8) | 25 (11.2) | |
| Socioeconomic level | ||||
| A/B, upper class | 64 (7.8) | 50 (8.4) | 14 (6.3) | NS |
| C+, upper-middle class | 130 (15.9) | 102 (17.1) | 28 (12.6) | |
| C, middle class | 191 (23.3) | 143 (24.0) | 48 (21.5) | |
| C-, middle-low class | 179 (21.9) | 124 (20.8) | 55 (24.7) | |
| D+, lower class | 108 (13.2) | 82 (13.8) | 26 (11.7) | |
| D, very lower class | 133 (16.2) | 86 (14.4) | 47 (21.1) | |
| E, extreme poverty | 14 (1.7) | 9 (1.5) | 5 (2.2) | |
NS not significant p > 0.05
* The results of the p-values represent a bivariate comparison between individuals with and without clinically significant depressive symptoms. The Chi-squared test was used to analyze categorical variables, while the Mann-Whitney U test was employed to compare the ages of those with and without clinically significant depressive symptoms
The clinical characteristics of participants are presented in Table 2. Patients with clinically significant depressive symptoms had lower enrollment in the kidney transplant protocol (p = 0.003) and were more likely to have hypertension (p = 0.011). They also had a higher rate of previously diagnosed depression or anxiety and were treated for depression (p < 0.001). No other significant differences were observed between patients with and without clinically significant depressive symptoms.
Table 2.
Clinical characteristics of patients with and without clinically significant depressive symptoms (n = 819)
| Covariates | Total n = 819 n (%) |
Without clinically significant depressive symptoms n = 596 n (%) |
With clinically significant depressive symptoms n = 223 n (%) |
p* |
|---|---|---|---|---|
| Cause of CKD | ||||
| Diabetes/hypertension | 264 (32.2) | 186 (31.2) | 78 (35.0) | NS |
| Other causesπ | 299 (36.5) | 220 (36.9) | 79 (35.4) | |
| Unknown | 256 (31.3) | 190 (31.9) | 66 (29.6) | |
| Type of replacement therapy | ||||
| Peritoneal dialysis | 115 (14.0) | 89 (14.9) | 26 (11.7) | NS |
| Hemodialysis | 704 (86.0) | 507 (85.1) | 197 (88.3) | |
| Previous kidney transplant | 96 (11.7) | 76 (12.8) | 20 (9.0) | NS |
| Enrolment in the kidney Transplant protocol | 268 (37.7) | 213 (35.7) | 55 (24.7) | 0.003 |
| Diabetes | 279 (34.1) | 195 (32.7) | 84 (37.7) | NS |
| Hypertension | 633 (77.3) | 447 (75.0) | 186 (83.4) | 0.011 |
| Diabetes and hypertension | 249 (30.4) | 170 (28.5) | 79 (35.4) | 0.056 |
| History of diagnosis of depression | 123 (15.0) | 61 (10.2) | 62 (27.8) | < 0.001 |
| Undergoing treatment for depression | 57 (7.0) | 24 (4.0) | 33 (14.8) | < 0.001 |
| Previous diagnosis of anxiety | 134 (16.4) | 59 (10.1) | 64 (27.2) | < 0.001 |
| Hemodialysis or peritoneal dialysis location | ||||
| ZGH | 261 (31.9) | 180 (30.2) | 81 (36.3) | NS |
| OMCU | 52 (6.4) | 37 (6.2) | 15 (6.7) | |
| Subrogated HD unit | 391 (47.7) | 290 (48.7) | 101 (45.3) | |
| Home (PD) | 115 (14.0) | 89 (14.9) | 26 (11.7) | |
| Blood test results | (Mean, SD) | (Mean, SD) | (Mean, SD) | |
| Hemoglobin | 10.7±2.5 | 10.8±2.5 | 10.5±2.7 | NS |
| Albumin | 3.9±0.7 | 3.9±0.8 | 3.9±0.7 | NS |
|
Median (min-max) |
Median (min-max) |
Median (min-max) |
||
| Parathyroid hormone | 340 (6.1–2217) | 340 (7.7–2217) | 339 (6.1–1704) | NS |
| Phosphorus | 4.9 (1.1–15.8) | 4.9 (1.1–15.8) | 4.9 (1.2–10.8) | NS |
| Time since CKD diagnosis (years) | 5 (0–51) | 5 (0–51) | 5 (0–36) | NS |
| Time since peritoneal dialysis/hemodialysis initiation (years) | 3 (0–23) | 3 (0–23) | 3 (0–19) | NS |
CKD Chronic kidney disease, HD hemodialysis, PD Peritoneal dialysis, NS not significant p > 0.05, ZGH Zone General Hospital, OMCU Outpatient Medical Care Unit. πOther causes of CKD included anatomical abnormalities of the urinary tract, glomerulopathies or polycystic kidney disease
*The results of the p-values represent a bivariate comparison between individuals with and without clinically significant depressive symptoms. We used the Chi-squared test for categorical variables, the Student’s T-test for normally distributed hemoglobin and albumin levels, and the Mann-Whitney U test for non-normally distributed parathyroid hormone and phosphorus levels, as well as time since CKD diagnosis and time since peritoneal dialysis/hemodialysis initiation
Table 3 illustrates social groups of patients with and without clinically significant depressive symptoms. Patients experiencing clinically significant depressive symptoms less frequently had family members (p = 0.030), belong to groups of friends (p < 0.001), neighbors (p < 0.001), coworkers (p < 0.001), retirees (p = 0.002), and senior citizens (p = 0.002), sports groups (p < 0.001), schools (p = 0.008), and trade unions (p = 0.035).
Table 3.
Social groups of patients with and without clinically significant depressive symptoms (n = 819)
| Covariates | Total n = 819 n (%) |
Without clinically significant depressive symptoms n = 596 n (%) |
With clinically significant depressive symptoms n = 223 n (%) |
p* |
|---|---|---|---|---|
| Family | 806 (98.4) | 590 (99.0) | 216 (96.9) | 0.030 |
| Friends | 535 (65.3) | 420 (70.5) | 115 (51.6) | < 0.001 |
| Neighbors | 431 (52.6) | 339 (56.9) | 92 (41.3) | < 0.001 |
| Co-workers | 327 (39.9) | 264 (44.3) | 63 (28.2) | < 0.001 |
| Group of retirees or pensioners | 161 (19.7) | 133 (22.3) | 28 (12.6) | 0.002 |
| Senior citizens group | 102 (12.4) | 87 (14.6) | 15 (6.7) | 0.002 |
| Sports groups | 125 (15.3) | 108 (18.1) | 17 (7.6) | < 0.001 |
| School | 188 (22.9) | 151 (25.3) | 37 (16.6) | 0.008 |
| Trade unions | 24 (2.9) | 22 (3.7) | 2 (0.9) | 0.035 |
| Group of people with chronic illnesses | 390 (47.6) | 286 (48.0) | 104 (46.6) | NS |
| Social-media groups | 594 (75.5) | 439 (73.7) | 155 (69.5) | NS |
| Political party | 22 (2.7) | 17 (2.8) | 5 (2.2) | NS |
| Non-governmental institution | 24 (2.9) | 20 (3.4) | 4 (1.8) | NS |
| Religious group | 349 (42.6) | 259 (43.5) | 90 (40.4) | NS |
| Citizen endorsement group | 5 (0.6) | 4 (0.7) | 1 (0.4) | NS |
*The results of the p-values represent a bivariate comparison between individuals with and without clinically significant depressive symptoms. We used the Chi-squared test to compare categorical variables in this table
NS not significant p > 0.05
Table 4 shows the scores of patients with and without clinically significant depressive symptoms in various dimensions of SC. Those with clinically significant depressive symptoms scored lower in the structural domain, specifically in “participation in organizations” (p = 0.003), “size of networks,” “collective action,” “diversity,” and “bonding within social groups” (p < 0.001 each). Additionally, in the cognitive domain, patients with clinically significant depressive symptoms had lower scores in “social harmony,” “sense of belonging,” “social support,” and “social trust” (p < 0.001 each) (see Table 4). *The results of the p-values represent a bivariate comparison between individuals with and without clinically significant depressive symptoms. We used the Mann-Whitney U test to compare non-normally distributed SC variables
Table 4.
Social capital in patients with and without clinically significant depressive symptoms (n = 819)
| Domains and Dimensions | Total n = 819 n (%) |
Without clinically significant depressive symptoms n = 596 n (%) |
With clinically significant depressive symptoms n = 223 n (%) |
p* |
|---|---|---|---|---|
| STRUCTURAL DOMAIN |
Median (min-max) |
Median (min-max) |
Median (min-max) |
|
| Participation in organizations | 9 (3–15) | 9 (3–15) | 8 (3–15) | 0.003 |
| Links with institutions | 3 (3–14) | 3 (3–14) | 3 (3–12) | NS |
| Networks size | 22 (6–30) | 22 (6–30) | 18 (6–30) | <0.001 |
| Collective action | 8 (3–15) | 9 (3–15) | 6 (3–15) | <0.001 |
| Diversity | 16 (4–20) | 16 (4–20) | 14 (4–20) | <0.001 |
| Vertical bridging of social groups | 5 (5–25) | 5 (5–25) | 5 (5–22) | NS |
| Bonding within social groups | 7 (4–20) | 8 (4–20) | 6 (4–20) | <0.001 |
| Total structural domain score | 72 (28–119) | 74 (28–119) | 65 (29–118) | <0.001 |
| COGNITIVE DOMAIN | ||||
| Norms of reciprocity | 35 (8–40) | 36 (8–40) | 34 (14–40) | NS |
| Social harmony | 12 (3–15) | 12 (3–15) | 12 (3–15) | <0.001 |
| Sense of belonging | 20 (5–25) | 21 (5–25) | 20 (5–25) | <0.001 |
| Sense of fairness | 32 (8–40) | 32 (8–40) | 32 (8–40) | NS |
| Social support | 24 (6–30) | 24 (6–30) | 23 (6–30) | <0.001 |
| Social trust | 32 (8–40) | 32 (8–40) | 31 (14–40) | <0.001 |
| Total cognitive domain score | 152 (42–190) | 153 (42–190) | 148 (56–190) | <0.001 |
NS not significant p > 0.05
The associations between SC dimensions and depressive symptoms are summarized in Table 5 and illustrated in Fig. 1. After controlling for confounding variables described in Tables 1 and 2, the findings reveal that in the structural domain, the dimensions “network size” and “bonding within social groups” were associated with lower odds of clinically significant depressive symptoms, with each point increase reducing the odds of depressive symptoms by 15% (OR 0.85; 95% CI: 0.80-0.91 and OR 0.85; 95% CI: 0.78-0.93). In contrast, “vertical bridging of social groups” dimension increased the odds of clinically significant depressive symptoms by 6% with each point increase.
Table 5.
Association of social capital with clinically significant depressive symptoms
| SOCIAL CAPITAL DIMENSIONS | Crude OR (95%CI) | Adjusted OR (95%CI) |
|---|---|---|
| STRUCTURAL DOMAIN | ||
| Participation in organizations | 0.94 (0.89–0.98) | 1.03 (0.99-1.09) |
| Links with institutions | 0.99 (0.91–1.08) | 1.09 (0.85-1.40) |
| Networks size | 0.89 (0.86–0.92) | 0.85 (0.80-0.91) |
| Collective action | 0.88 (0.84–0.92) | 1.01 (0.88-1.16) |
| Diversity | 0.93 (0.89–0.96) | 1.07 (0.95-1.21) |
| Vertical bridging of social groups | 0.97 (0.92–1.02) | 1.06 (1.02-1.10) |
| Bonding within social groups | 0.90 (0.86–0.94) | 0.85 (0.78-0.93) |
| COGNITIVE DOMAIN | ||
| Norms of reciprocity | 0.98 (0.96–1.01) | 0.97 (0.95–0.99) |
| Social harmony | 0.80 (0.74–0.86) | 0.89 (0.79–1.02) |
| Sense of belonging | 0.86 (0.82–0.90) | 0.92 (0.87–0.96) |
| Sense of fairness | 0.99 (0.97–1.01) | 1.06 (1.04–1.08) |
| Social support | 0.88 (0.85–0.91) | 0.85 (0.80–0.90) |
| Social trust | 0.93 (0.90–0.96) | 1.05 (0.95–1.16) |
This table displays the findings from the bivariate and multivariable logistic regression analyses. The assessed associations were adjusted by study covariates reported in the statistical analysis section
OR odds ratio
Fig. 1.
Association between social capital dimensions and clinically significant depressive symptoms. A Structural domain. aOR: adjusted odds ratio; cOR: crude odds ratio; CI: confidence interval; BO: bonding within social groups; BR: vertical bridging of social groups; CA: collective action; DI, diversity; NZ: network size; LI: Links with institutions and PO: participation in organizations. The assessed associations were adjusted for study covariates.B Cognitive domain. ST: social trust; SS: social support; SF: Sense of fairness; SB: sense of belonging; SH: social harmony; and NR: norms of reciprocity. The assessed associations were adjusted for study covariates
In the cognitive domain, increases in “norms of reciprocity,” “sense of belonging,” and “social support” were associated with 3% lower odds of depressive symptoms (OR 0.97; 95% CI: 0.95-0.99), 8% (OR 0.92; 95% CI: 0.87-0.96), and 15% (OR 0.85; 95% CI: 0.80-0.90), respectively. Additionally, higher scores in “sense of fairness” were associated with a 6% increased odds of depressive symptoms (OR 1.06; 95% CI: 1.04-1.08).
Discussion
This study identified a high prevalence of clinically significant depressive symptoms in patients with ESKD and showed that several dimensions of social capital are associated with decreased or increased odds of clinically significant depressive symptoms.
We found that approximately three in ten ESKD patients in Mexico present symptoms of clinically significant depressive symptoms. This prevalence aligns with the overall findings of Adejumo’s meta-analysis [5]; however, it is higher than the 19.9% reported for the Americas region in patients with CKD at all stages. Notably, when looking specifically at patients undergoing renal replacement therapy, the prevalence of depressive symptoms increased to 30.6%. Additionally, the meta-analysis revealed variability in depressive symptoms rates across different studies, which could be attributed to the use of different measurement tools, the large variability in sample size, and the geopolitical differences among the regions included in the study [5].
Our study found that larger social networks and strong bonding within social groups are associated with lower odds of clinically significant depressive symptoms. This suggests that having more connections and close relationships increases the likelihood of receiving emotional and instrumental support [18]. A study in China had similar results, showing that individuals with a lower social network size had a higher probability of depressive symptoms, with odds ratios of 2.84 for men and 2.78 for women, but it only included older adults without ESKD [21]. In contrast, another study of hypertensive patients found no association between network size and depressive symptoms [23], indicating that population characteristics and study context can impact results. Additionally, the possible protection of bonding within social groups was supported by two studies, which showed that when individuals have strong horizontal group connections, the prevalence of depressive symptoms tends to decrease. This phenomenon can be explained by the fact that relationships with people who share similar characteristics—such as family, friends, or neighbors—help shield individuals from feelings of isolation and prevent mental health affectations [18, 49].
Our findings indicate that vertical bridging of social groups, reflected in group connections that are differentiated by factors like influence or wealth, can increase the odds of experiencing clinically significant depressive symptoms. This contrasts with the results reported by Shin Nakamine et al. in Japan, who found no association between bridging and depressive symptoms [50]. Similarly, a study by Tianyao Qu conducted in a North American population indicated that while there may be an association between bridging and depressive symptoms, this association became insignificant when adjusting for factors such as social support and conflictual relationships [51]. This suggests that social relationships among diverse groups can also be influenced by the quality of those relationships and the perceived benefits involved. It was previously found that joining vertical groups is often characterized by weak ties, as it typically involves interactions among individuals from different social classes, ideologies, and professions [52]. While such connections can provide access to resources that are not available within close-knit social groups, they can also lead to feelings of inferiority, discrimination, or a lack of understanding. When individuals feel misunderstood, they may experience subjective isolation or even conflictual relationships, which can further increase the risk of depressive symptoms [53].
In our study, we identified certain aspects of the cognitive domain of social capital that decreased the odds of clinically significant depressive symptoms, including norms of reciprocity (also referred to as mutual support), a sense of belonging, and social support. Our findings align with previous research, which has shown that these dimensions were associated with health benefits. For instance, a study conducted in China found that older adults with comorbidities who reported low levels of reciprocity had 1.77 times higher odds of rating their health poorly (OR 1.77; 95% CI: 1.17-2.68) [54]. Another study in China involving older adults demonstrated that high levels of reciprocity were associated with a reduced risk of depressive symptoms (coefficient: 0.30; 95% CI: 0.11, 0.48) [55]. However, when the researchers analyzed data by province, they found that this protective effect was significant only in provinces with lower socioeconomic status [55]. A similar observation was obtained in a Japanese study, which identified reciprocity as protective against depressive symptoms (cOR 0.95; 95% CI: 0.92-0.99).[56] Nevertheless, after adjusting for confounding variables in their multivariable model, the significance of this finding diminished. It is essential to recognize that socioeconomic and contextual differences can lead to variations in reciprocity [55]. Greater levels of reciprocity are generally found in communities with close social ties and strong cohesion [54, 55]. Conversely, in more heterogeneous communities, inequality can diminish the strength of reciprocity [55].
The possible protective effect of a sense of belonging was highlighted in studies from both China [57] and the United States [58]. A strong sense of belonging fosters social identity, enhances self-esteem, encourages community bonds and participation, and promotes social cohesion; all of these contribute to resilience and the ability to handle challenges. This can act as a protective factor against depressive symptoms [19].
Our study found that social support is associated with lower odds of clinically significant depressive symptoms. Two U.S. studies also indicate that higher social support is linked to lower depressive symptoms risk (gamma coefficient = − 0.065, p < 0.001) [58]. Additionally, individuals in social groups with strong connections reported better self-perceived health outcomes (OR 0.65; 95% CI 0.44-0.98) [59]. The association between social support can be understood through neurobiological mechanisms, as it may lower cortisol levels and reduce chronic inflammation associated with depressive symptoms [60]. Psychosocial factors also play a significant role—receiving support from a social group helps alleviate the emotional burden during stressful events. Having someone to talk to, ask for help, or share worries can diminish the intensity of negative emotions, ultimately leading to a reduction in depressive symptoms [60].
Finally, our research indicates that a sense of fairness is associated with a greater likelihood of experiencing clinically significant depressive symptoms. The sense of fairness dimension of the SC questionnaire assesses whether patients feel that their social groups provide equal opportunities for all members to access medical care, consult with dietitians or nephrologists, receive dialysis, and obtain medications and recommended food. Although in the general population, a greater sense of fairness boosts well-being in the general population [61], this may not be true for patients with ESKD. Our results suggest that feeling equal to the general population in terms of health resource access may be associated with increased odds of depressive symptoms in the highly vulnerable ESKD population [62]. Therefore, it is advisable to prioritize ESKD patients’ access to medical care, specialists, and medications due to the severity of their condition.
Given the associations between several aspects of social capital and depressive symptoms in ESKD patients, it is important for healthcare providers to evaluate the social capital of these patients and encourage the involvement of their families and significant others in their healthcare. They should also foster an emotionally healthy and supportive atmosphere. Additionally, healthcare providers need to include patients in the decision-making process regarding their care and motivate them to establish connections with others who are experiencing similar health issues, thereby enhancing social relationships, gaining emotional support, and identifying solutions to everyday challenges. Moreover, healthcare providers ought to advocate for initiatives and policies that strengthen community resources available to individuals with ESKD, which include access to mental health professionals like psychologists or psychiatrists. By adopting these approaches, healthcare providers can significantly contribute to enhancing the social capital of ESKD patients, with the ultimate goal of improving their mental well-being. [63]
This study has several strengths. One notable strength is that Aguascalientes, where the study was conducted, has one of the highest global prevalence rates of patients with ESKD. [64] The study accounted for over half of the individuals registered with ESKD in Aguascalientes who were selected through systematic sampling from the Chronic Kidney Disease Registry. Another strength is that we used validated SC questionnaires specifically designed for Mexican patients with ESKD. This ensured a thorough and robust assessment of the structural and cognitive dimensions of social capital, enabling us to understand its association with clinically significant depressive symptoms better.
However, our study also has some Limitations. Firstly, the cross-sectional design Limits our ability to determine causal relationships between social capital and clinically significant depressive symptoms. Secondly, there may be selection bias, as the study focused on a population with social security. However, in Aguascalientes, the Mexican Social Security Institute serves approximately 75% of individuals with ESKD. Finally, caution is advised when comparing our findings to ESKD patients in other countries, as social capital can vary significantly across different contexts worldwide.
Conclusion
Most social capital dimensions are associated with decreased odds of clinically significant depressive symptoms in patients with ESKD. Our findings emphasize the need for strategies that enhance the protective aspects of social capital, ultimately helping to reduce the prevalence of clinically significant depressive symptoms among patients with ESKD.
It is advisable for future research to investigate the relationship between social capital and anxiety in individuals with ESKD, since anxiety is also a prevalent mental health concern for those affected by ESKD.
Acknowledgements
AAO is a doctoral student from Programa de Doctorado en Ciencias Médicas, Odontológicas y de la Salud, Universidad Nacional Autónoma de México and received CONAHCYT fellowship (CVU 706900). The authors would like to thank IMSS Aguascalientes for allowing this research to be carried out with their patients. They also extend thanks to Dra. Guadalupe Ricalde Ríos, Dr. Chew Wong Alfredo and Daniela Jaffer Gutiérrez for their participation in the logistics of accessing hemodialysis rooms and peritoneal dialysis patients.
Abbreviations
- CKD
Chronic kidney disease
- ESKD
End-stage kidney disease
- HD
Hemodialysis
- IMSS
Mexican Institute of Social Security
- PD
Peritoneal dialysis
- SC
Social capital
Authors’ contributions
Conceptualization: AAO, SVD. Methodology: AAO, SVD, JMAG, AM, JPL, CAPA, CQV. Investigation: AAO, SVD, JMAG, AM, JPL, CAPA, CQV. Funding acquisition: AAO, SVD. Formal analysis: AAO, HMB. Data curation: AAO, HMB. Project administration: AAO, SVD. Writing-original draft: AAO, SVD. Writing-review and editing: AAO, SVD, JMAG, AM, HMB, JPL, CAPA, CQV. All authors reviewed and approved the final version of the manuscript and agreed to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Funding
This work was supported by the grant from the Research Funding Program of the Mexican Institute of Social Security as part of the 2023 IMSS Call for funding research projects focus on Priority Health issues, Vulnerable Populations and Emerging Issues. (R-2022-785-053; grant-recipient-AAO) The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data availability
The datasets generated and/or analyzed during the current study are not publicly available but are available from the first author Dr. Alicia Alanis-Ocádiz (E-mail: alanisdr@hotmail.com) upon reasonable request.
Declarations
Ethics approval and consent to participate
The Instituto Mexicano del Seguro Social National Scientific Research and Ethics Committee approved the research protocol under registration number R-2022-785-053. The study was conducted in accordance with the Declaration of Helsinki. All patients who participated in the study signed informed consent before completing the survey.
Consent for publication
Consent for publication was not required by the IMSS National Scientific Research and Ethics Committee.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available but are available from the first author Dr. Alicia Alanis-Ocádiz (E-mail: alanisdr@hotmail.com) upon reasonable request.