Association of both depressive symptoms scores and specific depressive symptoms with cardiovascular disease among middle-aged and older Chinese adults with chronic pain

doi:10.21203/rs.3.rs-4866554/v1

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Association of both depressive symptoms scores and specific depressive symptoms with cardiovascular disease among middle-aged and older Chinese adults with chronic pain

https://doi.org/10.21203/rs.3.rs-4866554/v1

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Background There are limited studies on the associations of both depressive symptom scores and specific depressive symptoms with cardiovascular disease (CVD) risk. our purpose was to analyze association of both depressive symptom scores and specific depressive symptoms with CVD among Chinese population with chronic pain.

Methods

We collected data from the China Health and Retirement Longitudinal Study (CHARLS) during 2011–2015. The primary endpoint of this study was CVD events, which was defined as heart disease or stroke. COX proportional hazards regression was performed to analyze the association of both depressive symptom scores and specific depressive symptoms with CVD events.

Results

3401 individuals were included when followed up to 2015, including 304 participants with CVD and 3097 participants without CVD, establishing a CVD incidence of 8.94% after an average follow-up of 46.58 months. The adjusted restricted cubic spline (RCS) curves showed a linear relationship between depression symptom scores and CVD events (P for non-linearity > 0.05). Each 1-point increase in the depression symptom score was associated with a 2% increase in the incidence of CVD events (adjusted HR 1.02, 95% CI: 1.01–1.04). Only 2 specific depressive symptoms were significantly associated with CVD events: feeling hopeless (adjusted HR, 1.11, 95% CI: 1.02–1.22) and feeling lonely (adjusted HR, 1.14, 95% CI: 1.03–1.26).

Conclusions

This study revealed a significant positive association between elevated depressive symptom scores and high CVD incidence in individual with chronic pain, only two specific depressive symptoms (feeling hopeless and feeling lonely) were independently associated with the development of CVD.

depressive symptoms scores

specific depressive symptoms

cardiovascular disease

chronic pain

CHARLS

In China, chronic pain is affecting an increasing number of middle-aged and elderly individuals, imposing adversely affects health life and significant economic burden (1–3). Furthermore, studies have shown that patients with chronic pain have a higher risk of cardiovascular disease (CVD) and CVD-related mortality compared to those without chronic pain (4). Therefore, identifying and eliminating the risk factors leading to CVD is of utmost clinical importance for the treatment and management of patients with chronic pain.

Depression, as one of the most common mental illnesses globally, places a significant burden on public health services and has become a public health priority (5–7). Similar to trends in most other parts of the world, the prevalence of depression among the elderly population in China has been rising. Previous studies have shown that the lifetime and 12-month prevalence of depression are 20.6% and 10.4%, respectively, with a higher prevalence in females (26.1%) compared to males (14.7%) (8). A survey of Chinese individuals aged 45 and above found that depressive symptoms are present in approximately 30% of men and 43% of women (9). Furthermore, epidemiological studies have found that depressive symptoms are associated with a range of adverse health outcomes, including stroke, coronary heart disease, and all-cause mortality (10–12).

However, there are limited studies on the associations of both depressive symptom scores and specific depressive symptoms with CVD risk, especially in the Chinese population with chronic pain. Therefore, the purpose of this study was to use the China Health and Retirement Longitudinal Study (CHARLS) database to analyze association of both depressive symptom scores and specific depressive symptoms with CVD among Chinese population with chronic pain.

Study Population

The cohort study data were derived from the China Health and Retirement Longitudinal Study (CHARLS) dataset. The baseline survey was conducted between June 2011 and March 2012, involving 10,257 households. This survey collected data on sociodemographic factors, lifestyle factors, and health-related information. All participants have been followed up every two years since the baseline survey (13).

Firstly, 17707 participants were included in the present study, of which 5662 participants have chronic pain at baseline. In addition, of the remaining 5662 participants, 957 participants were excluded due to pre-existing CVD at baseline. After further excluding 1304 participants, including participants without complete depressive symptom scores at baseline (n = 798), participants who died during follow-up (n = 120), and participants who were lost to follow-up (n = 386), 3401 individuals were finally included when followed up to 2015, including 304 participants with CVD and 3097 participants without CVD, establishing a CVD incidence of 8.94% after an average follow-up of 46.58 months.

Evaluation of depressive symptoms

Depressive symptoms among the study participants were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D) (14). This tool evaluates participants' feelings and behaviors over the past week to determine the frequency and severity of various depressive symptoms. The CES-D-10 is an internationally recognized instrument for screening and diagnosing depressive symptoms. Each item is scored on a scale from 0 (rarely or none of the time [< 1 day]) to 3 (most or all of the time [5–7 days]). Items 5 and 8 are reverse scored before summing the item scores. The total CES-D score ranges from 0 to 30, with higher scores indicating more severe depressive symptoms. The 10 items that make up the CES-D: (1) I was bothered by things that don't usually bother me. (2) I had trouble keeping my mind on what I was doing. (3) I felt depressed. (4) I felt everything I did was an effort. (5) I felt hopeful about the future. (6) I felt fearful. (7) My sleep was restless. (8) I was happy. (9) I felt lonely. (10) I could not get "going."

Evaluation of CVD Events

The primary endpoint of this study was the occurrence of CVD) events. The assessment of CVD events was based on the following standardized questions: “Have you been told by a doctor that you have been diagnosed with a heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems?” or “Have you been told by a doctor that you have been diagnosed with a stroke?”. Participants who reported being diagnosed with heart disease or stroke during the follow-up period were classified as having CVD. The date of the last interview before reporting a CVD event was considered the date of CVD diagnosis.

Covariates

The sociodemographic characteristics collected include age, gender, marital status, and educational level. Health-related factors included self-reported smoking and drinking status, physician-diagnosed comorbidities (hypertension, dyslipidemia, diabetes, and chronic kidney disease), and the use of medications for treating diabetes, hypertension, and dyslipidemia. Height, weight, and blood pressure were measured by trained nurses. Body Mass Index (BMI) was calculated by dividing weight (in kilograms) by the square of height (in meters).

About 76% of participants underwent serum metabolic assessments, including blood urea nitrogen, glucose, serum creatinine, total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, C-reactive protein.

Statistical Analysis

Baseline characteristics were summarized according to the presence of CVD after follow-up. Means and standard deviations (SD) were used to represent normally distributed continuous variables, while medians and interquartile ranges (IQR) were used for non-normally distributed continuous variables. Group comparisons for continuous variables were performed using T-tests and Wilcoxon tests. Categorical variables were expressed as percentages and compared between groups using chi-square tests. The proportion of missing values for all included covariates, except serum biomarkers, was less than 10%. Therefore, multiple imputation using the "mi estimate" command in STATA was employed to address missing values for covariates in this study, excluding serum biomarkers.

Restricted cubic spline (RCS) curves were drawn based on the minimum AIC principle to explore the potential linear association between depressive symptom scores and CVD. Meanwhile, unadjusted and adjusted COX regression analysis (P for trend) was used to analyze the relationship between depressive symptom scores and CVD development, as well as to evaluate the association between each tertile of depressive symptom scores and CVD development: Crude model did not adjust for confounding variables. Model 1 adjusted for age, gender, education, marital status, body mass index, systolic blood pressure, diastolic blood pressure, smoking status, drinking status. Model 2 adjusted for age, gender, education, marital status, body mass index, systolic blood pressure, diastolic blood pressure, smoking status, drinking status, diabetes, dyslipidemia, chronic kidney disease, hypertension, lipid-lowering therapy, hypertension medications and diabetes medications. In addition, to analyze the association of specific depressive symptoms with CVD events, ten specific depressive symptoms were added to Model 2, respectively.

Subgroup analyses were conducted to investigate whether the association between depression symptom scores and CVD events was influenced by various demographic and clinical characteristics. These characteristics included age (categorized as ≤ 60 years and > 60 years), sex, educational level, marital status, BMI (categorized as ≤ 30 kg/m² and > 30 kg/m²), smoking status, drinking status, dyslipidemia, chronic kidney disease, hypertension, and diabetes. Additionally, sensitivity analyses were performed by further adjusting for serum biomarkers in Model 2 within the subset of 2568 participants (about 76% of participants) who underwent serum biomarkers assessment. The data were analyzed using Stata version 15 and R Studio (Version 4.1.3), and P-values <0.05 were considered statistically significant.

The comparison of baseline characteristics of between the CVD group and the non-CVD group are summarized in Table 1. Overall, there were no significant differences between the two groups in terms of demographic characteristics and serum biochemical indicators, except for age, educational level, systolic blood pressure, diastolic blood pressure, BMI, and triglycerides. However, there were no significant differences between the two groups in the presence of diabetes and history of diabetes medications, except for other comorbidities and medication histories. Specifically, participants in CVD group were older and had a higher educational level compared to those in the non-CVD group (mean [SD], 60.11 [9.45] vs. 58.39 [9.32]; P-value = 0.002). Participants in the CVD group had higher systolic (mean [SD], 134.21 [22.59] vs. 128.73 [22.45]; P-value < 0.001) and diastolic (mean [SD], 77.05 [12.66] vs. 75.02 [12.27]; P-value = 0.006) blood pressure levels. Additionally, the BMI (mean [SD], 24.01 [4.42] vs. 23.24 [4.09]; P-value = 0.002) and triglyceride (median [IQR], 111.51 [82.30] vs. 104.43 [74.78]; P-value = 0.048) levels of participants in CVD group were higher compared to those in the non-CVD group.

Table 1

Baseline characteristics.
Characteristics	CVD			P-value
	Total Sample	No	Yes
	3401	3097	304
Age, mean (SD), years	58.55 (9.35)	58.39 (9.32)	60.11 (9.45)	0.002
Female, (%)	2086 (61.3)	1894 (61.2)	192 (63.2)	0.534
Married, (%)	2809 (82.6)	2563 (82.8)	246 (80.9)	0.467
Education, (%)				0.004
Primary school or lower	2642 (77.7)	2416 (78.0)	226 (74.3)
Secondary school	709 (20.8)	642 (20.7)	67 (22.0)
Higher	50 (1.5)	39 (1.3)	11 (3.6)
blood pressure, mean (SD), mmHg
Systolic	129.22 (22.51)	128.73 (22.45)	134.21 (22.59)	< 0.001
Diastolic	75.20 (12.32)	75.02 (12.27)	77.05 (12.66)	0.006
BMI, kg/cm2	23.31 (4.13)	23.24 (4.09)	24.01 (4.42)	0.002
Smoking status, (%)				0.944
Never	2220 (65.3)	2019 (65.2)	201 (66.1)
Former	236 (6.9)	215 (6.9)	21 (6.9)
Current	945 (27.8)	863 (27.9)	82 (27.0)
Drinking status, (%)				0.768
Never	2172 (63.9)	1975 (63.8)	197 (64.8)
Former	470 (13.8)	426 (13.8)	44 (14.5)
Current	759 (22.3)	696 (22.5)	63 (20.7)
Serum biomarkers*
Blood urea nitrogen, mean (SD), mg/dl	15.75 (4.56)	15.75 (4.54)	15.78 (4.79)	0.938
Glucose, mean (SD), mg/dl	107.93 (32.78)	107.67 (32.40)	110.39 (36.30)	0.220
Serum creatinine, mean (SD), mg/dl	0.76 (0.18)	0.76 (0.18)	0.77 (0.19)	0.379
Total Cholesterol, mean (SD), mg/dl	192.82 (36.89)	193.09 (37.03)	190.23 (35.50)	0.252
Triglycerides, median (IQR), mg/dl	105.32 (76.11)	104.43 (74.78)	111.51 (82.30)	0.048
HDL Cholesterol, mean (SD), mg/dl	51.76 (15.21)	51.86 (15.17)	50.73 (15.64)	0.271
LDL Cholesterol, mean (SD), mg/dl	115.65 (34.13)	115.85 (34.05)	113.72 (34.92)	0.358
C-reactive protein, median (IQR), mg/L	0.97 (1.59)	0.99 (1.55)	0.91 (2.03)	0.700
History of comorbidities, (%)
Hypertension	746 (21.9)	637 (20.6)	109 (35.9)	< 0.001
Diabetes	185 (5.4)	161 (5.2)	24 (7.9)	0.065
Dyslipidemia	297 (8.7)	257 (8.3)	40 (13.2)	0.006
Chronic kidney disease	308 (9.1)	270 (8.7)	38 (12.5)	0.037
History of medication use, (%)
Lipid-lowering therapy	296 (8.7)	256 (8.3)	40 (13.2)	0.005
Hypertension medications	774 (22.8)	663 (21.4)	111 (36.5)	< 0.001
Diabetes medications	187 (5.5)	163 (5.3)	24 (7.9)	0.074
*Missing data: Blood urea nitrogen (820 of 3401 [24.1%]), Glucose (827 of 3401 [24.3%]), Serum creatinine (827 of 3401 [24.3%]), Total Cholesterol (822 of 3401 [24.2%]), Triglycerides (821 of 3401 [24.1%]), HDL Cholesterol (819 of 3401 [24.1%]), LDL Cholesterol (825 of 3401 [24.3%]), C-reactive protein (820 of 3401 [24.1%]).
Abbreviation: BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein; IQR, interquartile range (75th quartile minus 25th quartile); SD, standard deviation.

Association of both depressive symptoms scores and specific depressive symptoms with cardiovascular disease

A total of 304 participants developed CVD after an average follow-up of 46.58 months. The adjusted RCS plot with 3-knots showed a linear relationship between depression symptom scores and CVD events (P for non-linearity > 0.05) (Fig. 1). Furthermore, we used Cox regression analysis to quantify this relationship. In Model 2, where depression symptom scores were treated as a continuous variable, each 1-point increase in the depression symptom score was associated with a 2% increase in the incidence of CVD events (adjusted HR 1.02, 95% CI: 1.01–1.04). Additionally, when depression symptom scores were analyzed as a categorical variable (tertiles), the incidence of CVD events increased with higher tertiles (P for trend < 0.001). Compared to the first tertile group of depression symptom scores, the adjusted HR (95% CI) for CVD events for the second and third tertiles group were 1.54 (1.14, 2.06) and 1.67 (1.24, 2.24), respectively (Table 2). Among specific depressive symptoms, when the 10 symptoms measured by the CES-D scale were included in Model 2, only 2 symptoms were significantly associated with CVD events: feeling hopeless (adjusted HR, 1.11, 95% CI: 1.02–1.22) and feeling lonely (adjusted HR, 1.14, 95% CI: 1.03–1.26) (Table 3).

Table 2

Association of depressive symptoms scores with cardiovascular diseases.
Variables	N	Crude model		Model 1		Model 2
Variables	N	HR 95%CI	P-value	HR 95%CI	P-value	HR 95%CI	P-value
Depressive symptoms scores	3401	1.02(1.01,1.04)	0.010	1.03(1.01,1.04)	0.004	1.02(1.01, 1.04)	0.010
Depressive symptoms scores tertiles
Q1	1169	Ref.		Ref.		Ref.
Q2	1261	1.49(1.12,2.00)	0.01	1.57(1.17,2.11)	0.003	1.54(1.14, 2.06)	0.005
Q3	971	1.6(1.20,2.13)	0.001	1.72(1.28,2.31)	< 0.001	1.67(1.24, 2.24)	< 0.001
P for trend			0.001		< 0.001		< 0.001

Table 3

Association Between specific depressive symptoms and cardiovascular diseases
Items ^a	Cardiovascular disease
Items ^a	HR (95% CI) ^b	P-value
Bothered by little things	1.10(0.99, 1.21)	0.065
Had trouble concentrating	1.05(0.95, 1.16)	0.325
Felt depressed	1.05(0.95, 1.17)	0.312
Everything was an effort	1.03(0.93, 1.13)	0.596
Did not feel hopeful	1.11(1.02, 1.22)	0.022
Felt fearful	1.10(0.98, 1.23)	0.105
Sleep was restless	1.07(0.97, 1.17)	0.155
Did not feel happy	1.10(1.00, 1.21)	0.061
Felt lonely	1.14(1.03, 1.26)	0.011
Could not get going	1.06(0.95, 1.19)	0.280
^a Measured by the 10-item Center for Epidemiologic Studies Depression Scale.
^b Model adjusted for age, gender, education, marital status, body mass index, systolic blood pressure, diastolic blood pressure, smoking status, drinking status, diabetes, dyslipidemia, chronic kidney disease, hypertension, lipid-lowering therapy, hypertension medications and diabetes medications.

Subgroup and sensitivity analyses

Figure 2 shows the association of depression symptom scores with CVD events, stratified by potential risk factors. Compared to those with higher education levels at baseline, the association between depression symptom scores and CVD events was more pronounced in participants with lower education levels (adjusted HR, 1.04, 95% CI: 1.02–1.06) (P for interaction = 0.01). In addition, about 76% of CHARLS participants underwent serum biomarkers. After excluding all missing serum metabolic markers, sensitivity analyses were performed by further adjusting for metabolic biomarkers in Model 2 within the subset of 2568 participants who underwent serum biomarkers. The results did not significantly change after further adjusting for blood urea nitrogen, glucose, serum creatinine, total cholesterol, triglycerides, HDL cholesterol, LDL cholesterol, and C-reactive protein levels, respectively (Table 4).

Table 4

Association of depressive symptoms scores with cardiovascular diseases in subpopulations of 2568 participants with chronic pain with metabolic biomarkers measurements.
Model	HR 95%CI	P-value
Model 2	1.03(1.01, 1.05)	0.003
Model adjusted as model 2 plus
Blood urea nitrogen, mg/dl	1.03(1.01, 1.05)	0.003
Glucose, mg/dl	1.03(1.01, 1.05)	0.003
Serum creatinine, mg/dl	1.03(1.01, 1.05)	0.002
Total Cholesterol, mg/dl	1.03(1.01, 1.05)	0.003
Triglycerides, mg/dl	1.03(1.01, 1.05)	0.003
HDL Cholesterol, mg/dl	1.03(1.01, 1.05)	0.003
LDL Cholesterol, mg/dl	1.03(1.01, 1.05)	0.003
C-reactive protein, mg/L	1.03(1.01, 1.05)	0.003
Model 2 adjusted for age, gender, education, marital status, body mass index, systolic blood pressure, diastolic blood pressure, smoking status, drinking status, diabetes, dyslipidemia, chronic kidney disease, hypertension, lipid-lowering therapy, hypertension medications and diabetes medications were adjusted.
Abbreviation: HDL, high-density lipoprotein; LDL, low-density lipoprotein.

This study aimed to evaluate the association of between depressive symptoms scores and specific depressive symptoms with CVD incidence in participants with chronic pain. The results showed that elevated depressive symptoms scores were significantly positively associated with higher CVD incidence (HR 1.02, 95%CI: 1.01, 1.04) in participants with chronic pain. And the presence of two specific depressive symptoms (did not feel hopeful: HR 1.11, 95%CI: 1.02–1.22 and felt lonely: HR 1.14, 95%CI: 1.03–1.26) was independently associated with the development of CVD. These findings help to understand the complex relationship between chronic pain, depression, and CVD.

Previous research indicated that depressive symptoms are prevalent among patients with chronic pain (15). This prevalence might be attributed to the long-term stress and decreased quality of life associated with chronic pain (16, 17). Chronic pain could trigger a range of psychological responses, such as feelings of helplessness, hopelessness, and anxiety, which may further develop into depressive symptoms (17, 18). Conversely, depressive symptoms could exacerbate the perception of pain, trapping patients in a vicious cycle of "pain-depression-pain. Zhu et al. study found depression and chronic pain was mutually causal, with sleep disorder as a mediator (19). In addition, Bisby et al. found that there was high rates of depression and anxiety symptoms among adults with chronic pain (20). In terms of mechanism, the relationship between chronic pain and depression might be attributed to the Insula→Amygdala and Insula→Thalamus pathways (21). Therefore, for chronic pain patients suffering from depression, we need to provide them with psychological intervention and pay attention to whether depression affects the clinical prognosis of chronic pain patients.

Previous research suggested that depressive symptoms might increase the risk of CVD through multiple mechanisms (22). Firstly, depressive symptoms were linked to overactivation of the sympathetic nervous system (23), which could lead to increased heart rate, elevated blood pressure, and heightened cardiac load, thereby raising the risk of CVD. Secondly, depressive symptoms were often accompanied by unhealthy lifestyle choices (24, 25), such as smoking, excessive alcohol consumption, lack of exercise, and poor diet, all of which were risk factors for CVD. Additionally, depressive symptoms might lead to increased inflammatory responses and endothelial dysfunction (26, 27), physiological changes that could contribute to the development of atherosclerosis and other CVD. Krittanawong et al. found that depression increased the risk of CVD (HR 1.16; 95% CI, 1.04–1.30) and CVD mortality (HR 1.44; 95% CI, 1.27–1.63) (28). Similar to the results of this study, we found depressive symptoms scores increase the risk of CVD incidence in participants with chronic pain, and the above association was more likely to be found among people with low education levels. Liu et al. found that High education level reduces the incidence of various CVD (29). Therefore, for individuals with low education levels, we need to pay attention to their mental health. In addition, most previous studies had divided the population into healthy or depressed, ignoring the heterogeneity of depressive symptoms and the important differences between individuals with depression (30, 31). In this study, we found that two specific depressive symptoms (feeling hopeless: HR 1.11, 95%CI: 1.02–1.22 and feeling lonely: HR 1.14, 95%CI: 1.03–1.26) were independently associated with the development of CVD. These findings might provide new ideas for personalized treatment of patients with depression.

The results of this study suggested that special attention should be paid to the assessment and management of depressive symptoms in patients with chronic pain. Effective psychological interventions and antidepressant treatments might not only help alleviate depressive symptoms but also reduce the risk of CVD. Additionally, it was crucial to enhance the monitoring and preventive measures for cardiovascular health in chronic pain patients. A comprehensive management strategy, including psychological support, lifestyle interventions, and pharmacological treatments, might be an effective approach to reducing the incidence of CVD in these patients.

Despite the valuable insights provided by this study, several limitations exist. Firstly, the study could not establish a causal relationship between depression and CVD in patients with chronic pain. Additionally, the study did not analyze in detail the specific impact of different types of chronic pain (such as neuropathic pain and musculoskeletal pain) on depressive symptoms and CVD. Future research should consider the differences between various pain types. Moreover, the physiological mechanisms of between depressive symptoms and CVD were not investigated in this study.

Conflicts of Interest

All patients have no competing interests.

Funding

This work was supported by Shanghai Jinshan District Medical and Health Science and Technology Innovation Funding Project (grant number: 2022-WS-02).

Ethics Statement

The CHARLS study received approval from the Institutional Review Board of Peking University. Written informed consent was obtained from all participants. Therefore, the present study does not require additional ethical review and approval. Due to the free availability of the CHARLS database, the present study does not require additional ethical review and approval.

Data Availability Statement

The data of the present study come from https://charls.pku.edu.cn/. The data supporting the findings of the present paper could be provided by contacting the corresponding author (E-mail: [email protected]), without reservation.

Author contributions

Dingzhong Tang: Investigation, Methodology, Formal analysis, Conceptualization, and Writing-Original Draft; Weiwei Wang: Methodology, Software, Validation; Hong Chen, Xiayan Song, and Guojun Luo: Conceptualization, Investigation and Resources; Chunli Yu: Conceptualization, Supervision, Project administration and Funding.

Acknowledgement

Thanks to the National Development Research Institute of Peking University and the Chinese Social Science Research Center of Peking University for providing CHARLS data.

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No competing interests reported.

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Association of both depressive symptoms scores and specific depressive symptoms with cardiovascular disease among middle-aged and older Chinese adults with chronic pain

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Abstract

Figures

Introduction

Methods

Study Population

Evaluation of depressive symptoms

Evaluation of CVD Events

Covariates

Statistical Analysis

Results

Association of both depressive symptoms scores and specific depressive symptoms with cardiovascular disease

Subgroup and sensitivity analyses

Discussion

Conclusion

Declarations

References

Additional Declarations

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