Prevalence and Risk Factors of Depression in Rural Chinese Hemodialysis Patients During the COVID-19 Pandemic: A Multicenter Cross-Sectional Study

doi:10.21203/rs.3.rs-5328560/v1

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Prevalence and Risk Factors of Depression in Rural Chinese Hemodialysis Patients During the COVID-19 Pandemic: A Multicenter Cross-Sectional Study

https://doi.org/10.21203/rs.3.rs-5328560/v1

This work is licensed under a CC BY 4.0 License

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Purpose

This study aimed to assess the prevalence and risk factors of depression among maintenance hemodialysis (MHD) patients in rural China during the COVID-19 pandemic.

Methods

A cross-sectional survey was conducted in 14 hemodialysis centers in northern Guangdong Province from April to October 2021. Depression was evaluated using the Self-Rating Depression Scale. Multivariate logistic regression analysis was employed to identify associated factors.

Results

Of the 450 MHD patients enrolled, 160 (35.6%) met the criteria for depression, with 91.8% cases being of mild severity. After adjusting for demographic, dialysis-related, laboratory, pandemic-associated lifestyle changes, and psychological variables, discomfort during dialysis [Odds ratio (OR) 1.654, 95% Confidence Interval (CI) 1.105–2.474] and infection worry (OR 1.719, 95% CI 1.121–2.636) were significantly associated with an increased risk of depression. In contrast, college education was linked to a lower risk (OR 0.456, 95% CI 0.245–0.846).

Conclusion

During the COVID-19 pandemic in rural China, mild depression were common among MHD patients. Mandatory behavioral interventions did not contribute to depression, while discomfort during dialysis and infection worry emerged as risk factors, and college education was associated with a lower risk.

maintenance hemodialysis

COVID-19 pandemic

depression

rural areas

Maintenance hemodialysis (MHD) is a primary treatment for patients with end-stage renal disease. Due to their reliance on hemodialysis equipment and medical care for survival, these patients often have low immune resistance and frequent complications [1, 2]. In addition to suffering numerous physical symptoms, they are prone to emotional disturbances, including a high prevalence of depression [3]. This vulnerability can be exacerbated during major public health events, potentially leading to an increased incidence of mental health issues.

Current evidence suggests that the COVID-19 pandemic has coincided with a widespread increase in psychiatric disorders [4], warranting the attention of the global health community. To combat the COVID-19 pandemic, various countries and governments have implemented mandatory behavioral non-pharmaceutical interventions, such as restrictions on social interactions and mask-wearing. Although these interventions limit free communication, potentially exacerbating depression, compliance with them can make individuals feel safe and help alleviate depressive symptoms. Thus, these measures are a "double-edged sword," and their effects depend on a combination of factors such as medical, social, and cultural context [5].

Considering the health vulnerability of the maintenance hemodialysis (MHD) population, it is generally believed that pandemic-associated psychological stress will have a depressive impact on MHD patients [6–13]. However, studies on dialysis populations have shown inconsistent results. Some research, primarily from countries with advanced healthcare systems, suggests that the pandemic has not significantly affected the mental health of dialysis patients [14, 15]. Other findings focus on mandatory behavioral interventions and indicate that these measures do not impact mental health [16]. A large-scale epidemiological survey from South Korea found that not wearing masks indoors was most strongly associated with depression; those who did not adhere to public health measures were more likely to experience depression [17].

In rural areas, where medical resources are scarce, healthcare systems face increased pressure during major public health events [18]. Additionally, limited educational backgrounds can hinder patients' understanding of the pandemic. In rural America, 43.68% of respondents reported a negative impact on mental health during the pandemic [13]. In Guangdong Province, an economically developed region in China, a province-wide survey among the MHD population indicated that the COVID-19 pandemic had no significant overall impact on mental health. However, it did affect rural areas and low-income populations [19]. Despite these preliminary studies, further research is still lacking on the impact of the pandemic on psychological issues in rural regions. Consequently, our understanding of the unique challenges faced by rural healthcare systems and their impact on vulnerable populations remains limited.

This study utilizes questionnaire data from the multi-hemodialysis center in rural area of China during the COVID-19 pandemic. It aims to investigate the depression prevalence and analyze the association between demographic factors, medical parameters, pandemic-associated lifestyle changes, and depression, thereby exploring the risk factors for depression among the rural MHD population.

1.1 Patient inclusion

We conducted this prospective study in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics committee of our hospital (KY-2021-038). Patients from 14 hemodialysis centers in the northern rural areas of Guangdong Province were selected for this study, conducted from April 2021 to October 2021. The inclusion criteria were as follows: (1) undergoing hemodialysis for 6 months or more; (2) aged 16 years or older; (3) fully conscious and able to complete the questionnaire independently or with assistance; (4) no serious complications in the past one month. Exclusion criteria involved patients who were unwilling to participate.

1.2 Ethical issues

The study protocol was reviewed and approved by the hospital's Ethics Committee. All patients and their family members were informed about the study's details and voluntarily signed the informed consent.

1.3 Data collection

The Self-Rating Depression Scale (SDS), a widely used 20-item self-reported questionnaire, was utilized to assess depression. Upon obtaining informed consent, SDS questionnaires were distributed. Nurses, who were uniformly trained, explained the survey content and the instructions for completing the questionnaire, ensuring patients could complete it independently or with assistance. The SDS scores range from 25 to 100, with a score of 50 or above indicating clinical depression: 50–59 signifies mild depression, 60–69 moderate, and 70 or above severe [20, 21].

Other collected clinical data included: (1) demographic information (age, sex, education level, marital status, and monthly family income); (2) nutritional status (serum albumin levels) and anemia indicators; (3) dialysis details (years on dialysis, frequency of sessions, single-session fluid removal volume and duration, symptoms experienced during dialysis); and (4) pandemic-related information (daily masking duration, discussions with other patients about the pandemic, understanding of pandemic updates).

1.4 Statistical methods

Statistical analyses were performed using SPSS software version 26.0. An independent sample t-test was employed to compare continuous variables between two groups, while the chi-square test was used for categorical data. The Bonferroni correction was used to adjust α value for multiple group comparisons. Multivariate logistic regression analysis was conducted to identify depression-associated risk factors.

2.1 Clinical characteristics

A total of 450 hemodialysis patients completed the survey, of which 238 (52.9%) were male, with an average age of 54.9 ± 13.9 years. The overall SDS score was 45.1 ± 8.8, with emotional and psychological symptoms scoring 7.3 ± 2.3, physical and behavioral symptoms 17.7 ± 3.6, and social and cognitive symptoms 20.1 ± 4.9.

Among the 450 patients, 160 were identified as having depression, including 147 (91.8%) with mild, 11 (6.9%) with moderate, and 2 (1.3%) with severe depression. The clinical characteristics of patients with or without depression are summarized in Table 1. Compared to non-depressed individuals, those with depression were less educated and had lower incomes, and more frequently self-reported worry about COVID-19 infection. No significant differences were found in laboratory indicators or in lifestyle during the pandemic (Table 1).

Table 1

Clinical characteristics of patients without and with depression.
	Non-Depressed N = 290	Depressed N = 160	t/χ²	P value
Demographic indicators
Age	54.5 ± 14.2	55.6 ± 13.4	−0.849	0.396
Male [n (%)]	160 (55.2%)	78 (48.8%)	1.707	0.191
College education	60 (21.3%)	15 (9.6%)	9.624	0.002
Marriage			1.772	0.621
Unmarried	37 (12.8%)	14 (8.8%)
Married	225 (77.6%)	130 (81.3%)
Divorced	12 (4.1%)	6 (3.8%)
Widowed	16 (5.5%)	10 (6.3%)
Monthly income ≥ 5, 000 yuan	127 (43.8%)	44 (27.5%)	11.618	< 0.001
Dialysis parameters
HD vintage			0.556	0.757
< 1 year	67 (23.1%)	42 (26.3%)
1–3 year	55 (19.0%)	29 (18.1%)
≥ 3 year	168 (57.9%)	89 (55.6%)
HD frequency			1.654	0.437
≤ Twice a week	56 (19.3%)	32 (20.0%)
Five times every 2 weeks	219 (75.5%)	115 (71.9%)
Three times a week	15 (5.2%)	13 (8.1%)
Discomfort during dialysis	121 (41.7%)	89 (55.6%)	8.005	0.005
Laboratory parameters
Hemoglobin			3.679	0.159
< 90 g/L	66 (22.8%)	45 (28.1%)
90–129 g/L	212 (73.1%)	104 (65.0%)
≥ 130 g/L	12 (4.1%)	11 (6.9%)
Serum albumin			4.744	0.192
< 30 g/L	15 (5.2%)	14 (8.8%)
30–34 g/L	68 (23.4%)	43 (26.9%)
35–39 g/L	160 (55.2%)	73 (45.6%)
≥ 40 g/L	47 (16.2%)	30 (18.8%)
Lifestyle change
Daily masking time			6.004	0.050
< 2h	100 (34.5%)	41 (25.6%)
2–4h	61 (21.0%)	48 (30.0%)
≥ 4h	129 (44.5%)	71 (44.4%)
Mask discomfort	96 (33.1%)	67 (41.9%)	3.434	0.064
Daily concern for pandemic	212 (73.1%)	126 (78.8%)	1.759	0.185
Reduce outdoor activities	183 (63.1%)	106 (66.3%)	0.444	0.505
Psycho Well-being
Infection worry	166 (57.2%)	113 (70.6%)	7.839	0.005

2.2 Depressive severity analysis

Given the predominance of mild depression among patients, we utilized the SDS scores to assess its severity across clinically distinct subgroups. Demographic analyses revealed no significant differences in SDS scores based on sex or marital status (Fig. 1A and 1B), but higher educational levels and monthly incomes correlated with lower SDS scores (Fig. 1C and 1D), indicating an education-income link with depression .

SDS scores were unaffected by laboratory results and dialysis parameters, with no variations observed for serum albumin, hemoglobin levels (Fig. 2A, 2B), or dialysis specifics (volume, frequency, session duration, years on dialysis or discomfort during dialysis; Fig. 3A-3E).

Patients experiencing mask discomfort had higher SDS scores than those without (Fig. 4A), while mask duration did not impact scores significantly (Fig. 4B), indicating subjective emotional responses play a role in mask-related distress. Other lifestyle changes due to the pandemic, such as daily pandemic concerns and reduced outdoor activities, did not influence SDS scores (Fig. 4C and 4D). However, anxiety about COVID-19 infection was associated with higher SDS scores (Fig. 4E), emphasizing personal psychological factors' impact on depression over routine activity modifications.

Taken above at all, individuals with low income, limited education, mask discomfort, and heightened COVID-19 anxiety are at increased risk for depression, highlighting the need for integrated psychological and physical health support, especially during crises.

2.3 Depression-associated risk factors

To investigate the independent relationships of above characteristics with depression during the pandemic, we conducted a Wald stepwise multivariate Logistic regression analysis on the variables listed in Table 1. Given a strong association observed between education and income in preliminary analysis (data not shown), only education was included in the modeling as a potential variable. After adjusting for multiple factors, three variables remained significant in the model: college education was associated with a lower risk of depression compared to those without a college education, while discomfort during dialysis and infection worry were linked to an increased risk of depression (Table 2).

Table 2

Independent risk factors for depression
Variables	Odds Ratio	95% Confidential Interval	P value
College education	0.456	0.245–0.846	0.005
Discomfort during dialysis	1.654	1.105–2.474	0.014
Infection concern	1.719	1.121–2.636	0.013

This study provided the epidemiological characteristics of depression in 450 MHD patients during the COVID-19 pandemic in rural areas of northern Guangdong Province, China, and found that about 1/3 of the patients met the criteria for depression with SDS scores of more than 50. After univariate and multivariate analysis, we found that discomfort during dialysis, and infection worry were risk factors associated with depression. Higher education was associated with a lower risk of depression.

This study adopts an SDS score > 50 as the criterion for depression and reveals that the incidence of depression among MHD patients in rural China during the pandemic era is 35.6%, which surpasses the pre-pandemic rate reported by Abdel-Kader K et al. They utilized the Patient Health Questionnaire-9 (PHQ-9) for depression assessment, identifying 25% of MHD patients as depressed based on a PHQ-9 score > 9 threshold [3]. Given the weak correlation between PHQ-9 and SDS scores in the general population, with a mere 0.29 correlation coefficient [22], no direct conversion between these measures is feasible. Consequently, studies employing distinct criteria for depression assessment are not directly comparable. A similar variance due to different assessment methodologies was observed by Ibrahim M et al., who employed the Beck Depression Inventory during a pandemic and found 66.2% of their MHD sample exhibiting depressive symptoms, with 61.4% meeting diagnostic criteria for depression [10]. Another key factor contributing to the discrepancy in reported depression rates is the rural setting of our investigation, which contrasts with the non-rural areas studied by Hao W et al. Using identical depression assessment criteria, they reported a depression detection rate of 32.1% among 321 hemodialysis patients, slightly lower than our findings [8]. This difference may be attributed to demographic variations between the two studies, such as a higher proportion of our subjects with monthly income lower than 5000 yuan (62% compared to 53%) and dialysis vintage more than a year (75.8% versus 67.0%).

Our study focused on the association between pandemic-associated lifestyle changes and depression. We observed a trend toward an increased depression rate among patients who wore masks for longer periods; however, this increase was not statistically significant when compared to those without depression. Additionally, mask discomfort was not associated with depression. These results suggest that mask-wearing itself does not elevate the risk of depression. After adjusting for multiple variables, the mask-related index remained unassociated with depression. Similarly, other lifestyle changes, such as daily concerns about the pandemic and reduced outdoor activities, were also not linked to depression. These findings support the notion that mandatory behavioral interventions do not contribute to depression in the MHD population in rural areas of China.

Due to the limited educational levels in rural area, it is challenging to precisely quantify the restrictions on social activities during the survey period. As a result, the study design incorporates only a binary measure of whether outdoor activities were reduced. Additional limitation includes incomplete clinical databases in parts of centers, which limit full depression-related laboratory data and comorbidies are not included in the analytical model.

This cross-sectional survey was conducted from March to October 2021, a period that corresponds to the national vaccination campaign stage following the shift from the first large-scale outbreak to sporadic outbreaks in mainland China. Therefore, the interpretation of the study's findings should take into account the sociological context of this specific timeframe.

The multicenter and prospective design is a notable strength of this study, particularly given the difficulties in acquiring data from rural areas during the pandemic. Importantly, the three risk factors for depression that were identified in our research are easily recognizable, thereby highlighting the feasibility of reproducing these results within clinical contexts. Our findings offer persuasive evidence to guide intervention strategies for this demographic in future public health crises.

In conclusion, during the COVID-19 pandemic in rural China, mild depression were common among MHD patients. Mandatory behavioral interventions did not contribute to depression, while discomfort during dialysis and infection worry emerged as risk factors, and college education was associated with a lower risk.

Acknowledgement:

We thank the following hospitals that participated in this research:

Yuebei People's Hospital, Shaoguan City First People's Hospital

Shaozhou People's Hospital

419 Hospital of Ministry of Nuclear Industry

Shaoguan City Kai De Hospital

Shaoguan City Qujiang District People's Hospital

Shaoguan City Women's Hospital

Nanxiong City People's Hospital

Lechang City People's Hospital

Shixing County People's Hospital

Xinfeng County People's Hospital

Ruyuan County People's Hospital

Yingde City Chinese Medicine Hospital

Lechang City Chinese Medicine Hospital

Author contributions

M He, ZQ Liu,JH Lin,ZQ Chen,RG Li,JP Tang,Q Liu,and L Nin designed the study.M He, ZQ Chen, RG Li, ,JP Tang,Q Liu,ZQ Liu,JH Lin,and L Nin collected, analyzed, and interpreted the clinical data. M He, ZQ Chen, RG Li, ,JP Tang,Q Liu,ZQ Liu,JH Lin,and L Nin wrote and revised the manuscript. All authors confirmed the integrity of the data and analysis. All authors read and approved the final manuscript.

Funding

No funding.

Data availability

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

Ethics declarations

Conflict of interest

This manuscript is submitted without conflict of interest and the manuscript is published with the consent of all authors.

Ethical approval

The present study has been approved by the ethics committee of Yuebei People's Hospital (KY-2021-038).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Author information

Authors and Affiliations

Department of Nephrology, Yuebei People's Hospital, Guangdong Medical University, Shaoguan City 512026, Guangdong, China

Min He & Zhaoqi Liu & Juhua Lin

Department of Nephrology, Yuebei People's Hospital,, Shaoguan City 512026, Guangdong, China

Zhiqiang Chen& Rugang Li & Junping Tang & Quan Liu & Ling Nin

Corresponding authors

Correspondence to Min He.

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No competing interests reported.

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Version 1

posted

You are reading this latest preprint version

Prevalence and Risk Factors of Depression in Rural Chinese Hemodialysis Patients During the COVID-19 Pandemic: A Multicenter Cross-Sectional Study

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Methods

1.1 Patient inclusion

1.4 Statistical methods

Results

2.1 Clinical characteristics

2.2 Depressive severity analysis

2.3 Depression-associated risk factors

Discussion

Declarations

References

Additional Declarations

Status:

Version 1