eTable 1. Prevalence of Symptoms of Depression in the CKB and DFTJ Cohorts
eTable 2. Association of Depression With IHD Mortality and Cerebrovascular Disease Mortality
eTable 3. Sensitivity Analysis of the Association of Depression With All-Cause and Cardiovascular Disease Mortality
Customize your JAMA Network experience by selecting one or more topics from the list below.
Identify all potential conflicts of interest that might be relevant to your comment.
Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.
Err on the side of full disclosure.
If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.
Not all submitted comments are published. Please see our commenting policy for details.
Meng R, Yu C, Liu N, et al. Association of Depression With All-Cause and Cardiovascular Disease Mortality Among Adults in China. JAMA Netw Open. 2020;3(2):e1921043. doi:10.1001/jamanetworkopen.2019.21043
Is depression associated with risk of all-cause and cardiovascular disease mortality in Chinese adults?
In this cohort study including 512 712 adults from the China Kadoorie Biobank study and 26 298 adults from the Dongfeng-Tongji study, depression was consistently associated with higher risk of all-cause and cardiovascular disease mortality. However, when stratified by sex, the associations were significant only among men.
These findings suggest that depression is a risk factor for all-cause and cardiovascular disease mortality in adults in China, particularly in men.
Depression is associated with increased disease burden worldwide and with higher risk of mortality in Western populations.
To investigate whether depression is a risk factor for all-cause and cardiovascular disease (CVD) mortality in adults in China.
Design, Setting, and Participants
This cohort study prospectively followed adults aged 30 to 79 years in the China Kadoorie Biobank (CKB) study from June 1, 2004, to December 31, 2016, and adults aged 32 to 104 years in the Dongfeng-Tongji (DFTJ) study from September 1, 2008, to December 31, 2016. Data analysis was conducted from June 1, 2018, to March 31, 2019.
Main Outcomes and Measures
Depression was evaluated using the Chinese version of the World Health Organization Composite International Diagnostic Interview–Short Form in the CKB cohort and a 7-item symptoms questionnaire modified from the Composite International Diagnostic Interview–Short Form in the DFTJ cohort. Multivariable-adjusted Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% CIs for the association of depression with mortality. Covariates in the final models included sociodemographic characteristics, lifestyle factors, and personal and family medical history.
Among 512 712 individuals (mean [SD] age, 52.0 [10.7] years; 302 509 [59.0%] women) in the CKB cohort, there were 44 065 deaths, including 18 273 CVD deaths. The 12-month prevalence of major depressive episode in the CKB cohort was 0.64%, and the 1-month prevalence of clinically significant depressive symptoms was 17.96% in the DFTJ cohort. Among 26 298 individuals (mean [SD] age, 63.6 [7.8] years; 14 508 [55.2%] women) in the DFTJ cohort, there were 2571 deaths, including 1013 CVD deaths. In the multivariable-adjusted model, depression was associated with increased risk of all-cause mortality (CKB cohort: HR, 1.32 [95% CI, 1.20-1.46]; P < .001; DFTJ cohort: HR, 1.17 [95% CI, 1.06-1.29]; P = .002) and CVD mortality (CKB cohort: HR, 1.22 [95% CI, 1.04-1.44]; P = .02; DFTJ cohort: HR, 1.32 [95% CI, 1.14-1.54]; P < .001). In both cohorts, men had statistically significantly higher risk of all-cause mortality (CKB cohort: HR, 1.53 [95% CI, 1.32-1.76]; DFTJ cohort: HR, 1.24 [95% CI, 1.10-1.41]) and CVD mortality (CKB cohort: HR, 1.39 [95% CI, 1.10-1.76]; DFTJ cohort: HR, 1.49 [95% CI, 1.23-1.80]), while the association of depression with mortality among women was only significant for all-cause mortality in the CKB cohort (HR, 1.19 [95% CI, 1.03-1.37]).
Conclusions and Relevance
These findings suggest that depression is associated with an increased risk of all-cause and CVD mortality in adults in China, particularly in men. These findings highlight the importance and urgency of depression management as a measure for preventing premature deaths in China.
Depression has become increasingly common and is associated with increased disease burdens worldwide.1,2 In 2013, the estimated worldwide prevalence of major depressive disorder was 4.7%, and the estimated annual incidence rate was 3.0%.1 The Global Burden of Disease Study 20162 reported that more than 34 million all-age disability-adjusted life-years were associated with depression. A 2013 systematic review3 reported that overall estimations of prevalence of major depressive disorders were 1.6% for current depression, 2.3% for depression in the previous 12 months, and 3.3% for any depression during an individual’s lifetime. It was estimated that more than 10 million disability-adjusted life-years were associated with depressive disorders in China in 2013, and the number was projected to increase by approximately 10% by 2025,4 which highlights the importance of depression prevention and intervention.
Numerous studies have been performed regarding the association of depression with increased risk of all-cause and cause-specific mortality in general populations and various patient groups, as summarized in a 2014 meta-analysis5 that included 293 studies with 1 813 733 participants from 35 countries. That meta-analysis by Cuijpers et al5 found that depression was associated with a 52% increased risk of all-cause mortality. However, the causal relationship between depression and mortality is still questionable, and a 2017 analysis6 of 293 studies with 3 604 005 participants indicated that the positive association of depression with mortality was largely based on low-quality studies (eg, studies with small sample sizes and short follow-up durations or with inadequate adjustment of potential confounding factors, particularly comorbid mental disorders and health behaviors). Therefore, more high-quality research is still needed to examine the association of depression with mortality.
Very few prospective cohort studies have been conducted on this topic among adults in China, to our knowledge. We found 4 studies7-10 in adults in China, including 3 studies in adults 65 years and older and 1 study in adults 55 years and older. Three studies7,9,10 found that the association of depressive symptoms with all-cause mortality was stronger among men than women. However, studies in younger adults in China are lacking, and 1 meta-analysis11 found that depression was also associated with excess mortality in women, although not as much as in men. Therefore, more studies are needed to examine the associations of depression with all-cause and cardiovascular disease (CVD) mortality in Chinese populations.
In this study, we used data from 2 large, well-established prospective cohort studies in mainland China to investigate whether depression was associated with all-cause and CVD mortality in middle-aged and elderly Chinese populations. We also tested whether the associations would be modified by age and sex.
The study design and baseline characteristics of the 2 cohorts have been reported in detail previously.12,13 Briefly, the China Kadoorie Biobank (CKB) cohort is a prospective study with more than 500 000 individuals aged 30 to 79 years recruited from 10 areas in China between June 1, 2004, and July 31, 2008. The Dongfeng-Tongji (DFTJ) cohort was established from September 1, 2008, to June 1, 2010, with a total of 27 009 workers from Dongfeng Motor Corporation with an age range of 32 to 104 years (most participants were retired workers). At baseline in the CKB cohort,12 the estimated population response rate was approximately 30% (26%-38% in 5 rural areas and 16%-50% in 5 urban areas), and the baseline response rate was 87% in the DFTJ cohort.13 In the CKB study, a detailed data collection protocol was developed in Chinese by experts from the University of Oxford and local, regional, and national Centers for Disease Control and Prevention (CDC) in China as part of a robust training program for field workers and interviewers. Within a few weeks of the initial baseline survey, approximately 3% of participants were randomly selected to repeat selected items (depression was not included) and measures in the questionnaire as a quality control (QC) procedure. There was good agreement between baseline and QC surveys for several common variables.12 Regular central monitoring and periodical on-site monitoring visits were undertaken by provincial CDC staff and staff from the coordinating centers of Peking University and the University of Oxford. In the DFTJ cohort, all interviewers received unified training and assessment before field work, and they administered questionnaires during face-to-face interviews. On-site QC teams checked all questionnaires for missing and incorrect items every day, and the QC supervision team randomly checked 10% of the questionnaires every week, but a QC resurvey was not conducted in the DFTJ cohort. In the CKB cohort, we excluded participants with unreliable information on death date (n = 1) and individuals without information on body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) (n = 2). In the DFTJ cohort, we excluded individuals without sufficient information on depression (n = 1), individuals with unreliable information on death date (n = 1), and individuals who were lost to follow-up (n = 709). The CKB study protocol was approved by the Oxford University Tropical Research Ethics Committee and the China CDC Ethical Review Committee, and the DFTJ cohort was approved by the medical ethics committee of the Tongji Medical College, Huazhong University of Science and Technology, and Dongfeng General Hospital, Dongfeng Motor Corporation. All participants provided written informed consent before enrollment in the study. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
In the CKB cohort at baseline, participants were first asked whether they had the following symptoms for 2 weeks in a row or longer during the past 12 months: (1) feeling much more sad or depressed than usual; (2) loss of interest in most things, such as hobbies or activities, that usually give them pleasure; (3) felt so hopeless that they had no appetite to eat even their favorite food; and (4) feeling worthless and useless, that everything that went wrong was their fault, that life was very difficult, and that there was no way out. If they answered yes to any of these questions, they were further evaluated for major depression using a modified Chinese version of the World Health Organization Composite International Diagnostic Interview–Short Form (CIDI-SF)14 in a face-to-face interview performed by trained health workers. In the CIDI-SF questionnaire, 7 additional yes-or-no questions were asked about symptoms during that 2 weeks (ie, losing interest in things, feeling tired or low on energy, weight change, difficulty in sleeping, trouble concentrating, thoughts about death, or feeling worthless). Participants who responded yes to 3 or more of the 7 depressive symptoms were classified as having major depression. A 2015 study15 reported that the CIDI-SF questionnaire for major depression had a sensitivity of 69.6% and a specificity of 96.7% in a Chinese population.
In the DFTJ cohort at baseline, participants were directly asked about the 7 depressive symptoms in the past month without inquiry of the screening questions. Participants who reported 3 or more symptoms during the past month were defined as having clinically significant depressive symptoms. Thereafter, depression was used to simplify the terminology in the 2 cohorts.
In the CKB study, cause-specific mortality was monitored regularly through official residential records and death certificates reported to China CDC’s Disease Surveillance Points system. The vital status of the participants was also checked annually against medical and health insurance records and supplemented by local street committees or village administrators, and if necessary, a verbal autopsy was conducted.12 In the DFTJ cohort, each participant had a unique medical insurance card number and was tracked through the medical insurance system provided by Dongfeng Motor Corporation for the cause-specific mortality.13 Causes of death were coded according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10)16 by trained staff. The deaths related to CVD were classified as those coded I00-99.
Information on the covariates in the 2 cohorts was collected by trained health workers through questionnaires and physical measurements at the baseline survey, including demographic or socioeconomic characteristics (ie, age, sex, education, and marital status for both cohorts and region and household income for the CKB cohort), lifestyle factors (ie, drinking and smoking status, physical activity, and consumption of red meat, fresh fruits, and vegetables), and health status. The physical examinations included body weight and height, blood pressures, and blood glucose level (random blood glucose level in the CKB cohort and fasting blood glucose level in the DFTJ cohort). Participants were asked about their history of chronic diseases, and a health index score was created by counting the number of chronic diseases, including chronic obstructive pulmonary disease or asthma, hypertension (defined as measured blood pressure ≥140/90 mm Hg, self-reported diagnosis of hypertension, or use of antihypertensive drugs at baseline), coronary heart disease (CHD), stroke, diabetes (defined as self-reported diagnosis or medication use, fasting glucose level ≥126 mg/dL [to convert to millimoles per liter, multiply by 0.0555], or random glucose level ≥200 mg/dL), and cancer. The health index variable was categorized into 4 groups based on the number of chronic diseases: 0, 1, 2, and 3 or more. Physical activity was quantified as metabolic equivalent task hours per day spent on activities related to occupation, commuting, housework, and nonsedentary leisure-time activities in the CKB study17 but only on nonsedentary leisure-time activities in the DFTJ cohort.18
Baseline characteristics of the respondents in our study are presented as means with SDs for continuous variables, with differences calculated using t test, or percentages for categorical variables, with differences calculated using χ2 test. Survival time was defined as the period from the date of baseline interview to the date of death, loss to follow-up, or December 31, 2016, whichever came first. The association of depression with mortality was estimated using Cox proportional hazards regression model, which yielded hazard ratios (HRs) and 95% CIs. The proportional hazards assumption was tested by adding an interaction term of follow-up duration and depression variable in the models, and no violation was found. We adjusted the sociodemographic characteristics, lifestyle factors, and personal and family medical history as confounders in the multivariable-adjusted Cox models. The potential confounders included age (continuous variable); sex; education level (less than primary school, middle school, high school, or college or higher); BMI (continuous variable); marital status (married, widowed, separated or divorced, or never married); drinking status (never, occasionally, or monthly; former or reduced intake; or current); smoking status (never or occasional, former, or current); consumption frequency of meat (daily, 4-6 days per week, 1-3 days per week, or <1 day per week), vegetables (daily or <1 per day), and fruits (daily, 4-6 days per week, 1-3 days per week, or <1 day per week); health index score (0, 1, 2, or ≥3); and family history of CVD. In the CKB cohort, study site (10 sites) and household income (categorized as <¥10 000 [<US $1435.89], ¥10 000-¥19 999 [US $1435.89-$2871.65], ¥20 000-¥34 999 [US $2871.79-$5025.49], or ≥¥35 000 [≥US $5025.63] per year) were also included in the model. The confounders were selected based on a priori knowledge of underlying biological mechanisms and previous reports.5,6 We also examined the associations of depression with ischemic heart disease mortality and cerebrovascular disease mortality. Additionally, we conducted stratified analyses by sex and age (≥65 years vs <65 years) and tested the significance of interaction by including a 2-way interaction term in the final model.
We performed a series of sensitivity analyses to test the robustness of the results: (1) the individuals who died within the first 2 years of follow-up were excluded to minimize the chance of reverse associations; (2) participants with baseline history of cancer, CHD, or stroke were excluded to examine the associations in relatively healthy individuals; (3) participants in the DFTJ cohort 80 years or older were excluded to reduce the potential selection bias; and (4) we adjusted for each chronic disease instead of the health index score to fully account for potential confounding by disease status. In addition, we defined depression as having 5 or more symptoms in both cohorts to examine whether the associations could be changed by applying a more strict cutoff.
We conducted all analyses separately in each cohort. We used SAS statistical software version 9.3 (SAS Institute) for all analyses. P values were 2-tailed, and statistical significance was set at .05. Data analysis was conducted from June 1, 2018, to March 31, 2019.
We included 512 712 participants (mean [SD] age, 52.0 [10.7] years; 302 509 [59.0%] women) in the CKB cohort and 26 298 individuals (mean [SD] age, 63.6 [7.8] years; 14 508 [55.2%] women) in the DFTJ cohort. The 12-month prevalence of major depressive episode in the CKB cohort was 0.64%, and the 1-month prevalence of clinically significant depressive symptoms was 17.96% in the DFTJ cohort. Table 1 presents the distribution of baseline characteristics based on depression status. Compared with participants without depression, those with depression were more likely to be women (CKB cohort: 300 178 participants [58.9%] vs 2331 participants [71.7%]; P < .001; DFTJ cohort: 11 517 participants [53.4%] vs 2991 participants [63.3%]; P < .001), be never or occasional smokers (CKB cohort: 344 209 participants [67.6%] vs 2424 participants [73.9%]; P < .001; DFTJ cohort: 15 089 participants [69.9%] vs 3410 participants [72.2%]; P < .001), have 3 or more comorbidities (CKB cohort: 4906 participants [0.9%] vs 59 participants [1.8%]; P < .001; DFTJ cohort: 1906 participants [8.8%] vs 819 participants [17.3%]; P < .001), and have a family history of CVD (CKB cohort: 104 208 participants [20.5%] vs 847 [25.8%]; P < .001; DFTJ cohort: 1939 participants [9.0%] vs 7171 participants [15.2%]; P < .001); however, they were less likely to be married (CKB cohort: 462 025 participants [90.7%] vs 2437 participants [74.3%]; P < .001; DFTJ cohort: 18 971 participants [87.9%] vs 4002 participants [84.7%]; P < .001), be current drinkers (CKB cohort: 75 816 participants [14.9%] vs 1324 participants [9.9%]; P < .001; DFTJ cohort: 4606 participants [21.3%] vs 894 participants [18.9%]; P < .001), or report daily consumptions of red meat (CKB cohort: 149 407 participants [29.3%] vs 610 participants [18.6%]; P < .001; DFTJ cohort: 5843 participants [27.1%] vs 1152 participants [24.4%]; P < .001) or fresh fruits (CKB cohort: 96 162 participants [18.9%] vs 420 participants [12.8%]; P < .001; DFTJ cohort: 10 715 participants [49.6%] vs 2232 participants [47.3%]; P = .03). In the CKB study, compared with participants without depression, those with depression were more likely to be younger (mean [SD] age, 52.0 [10.7 years vs 51.5 [10.0] years; P < .001), less active (mean [SD], 21.1 [13.9] metabolic equivalent task–hours per day vs 19.9 [14.1] metabolic equivalent task–hours per day; P < .001), and never, occasional, or monthly drinkers (412 858 participants [80.5%] vs 2762 participants [84.2%]; P < .001) and to have less than primary school education level (258 480 participants [50.7%] vs 1875 participants [57.1%]; P < .001), lower BMI (mean [SD], 23.7 [3.4] vs 23.2 [3.4]), and household income less than ¥10 000 (US $1435.89) (143 395 participants [28.1%] vs 1339 participants [40.8%]; P < .001).
In the CKB study, the 3 most commonly reported symptoms reported by participants with depression were losing interest in things (2952 participants [90.0%]), feeling tired or low on energy (2676 participants [81.6%]), and having trouble concentrating (2653 participants [80.9%]). The 3 most commonly reported symptoms reported by participants with depression in the DFTJ cohort were having trouble concentrating (4322 participants [91.5%]), feeling tired or low on energy (4212 participants [89.2%]), and having difficulty sleeping (3626 participants [76.8%]) (eTable 1 in the Supplement).
In the CKB study, we documented 44 065 deaths, including 17 501 CVD deaths, during 5 088 810 person-years of follow-up. In the DFTJ cohort, we documented 2571 deaths, including 1013 CVD deaths, during 208 403 person-years of follow-up. The incidence rates of all-cause and CVD mortality among participants with depression were significantly higher than that among those without depression in both cohorts (Table 2). In the multivariable-adjusted model, depression was associated with an increased risk of all-cause mortality (CKB cohort: HR, 1.32 [95% CI, 1.20-1.46]; P < .001; DFTJ cohort: HR, 1.17 [95% CI, 1.06-1.29]; P = .002) and CVD mortality (CKB cohort: HR, 1.22 [95% CI, 1.04-1.44]; P = .02; DFTJ cohort: HR, 1.32 [95% CI, 1.14-1.53]; P < .001). In the partially adjusted model 1, depression was associated with ischemic heart disease mortality and cerebrovascular disease mortality, but when we adjusted for all covariates, the association only remained significant for depression and cerebrovascular mortality in the DFTJ cohort (HR, 1.56 [95% CI, 1.24-1.96]; P < .001) (eTable 2 in the Supplement).
In the stratified analysis by sex (Table 3), the HR for all-cause mortality was 1.53 (95% CI, 1.32-1.76) in men and 1.19 (95% CI, 1.03-1.37) in women (P for interaction = .005) in the CKB cohort, while the HR for CVD mortality was 1.39 (95% CI, 1.10-1.76) in men and 1.11 (95% CI, 0.89-1.40) in women (P for interaction = .19). In the DFTJ cohort, the HR for all-cause mortality was 1.24 (95% CI, 1.10-1.41) in men and 1.06 (95% CI, 0.91-1.24) in women (P for interaction = .21), while the HR for CVD mortality was 1.49 (95% CI, 1.23-1.80) in men and 1.09 (95% CI, 0.86-1.39) in women (P for interaction = .06) (Table 3).
In the stratified analysis by age (Table 4), the associations were only significant in people 65 years or older compared with participants younger than 65 years in the DFTJ cohort for all-cause mortality (HR, 1.21 [95% CI, 1.08-1.35] vs 1.06 [95% CI, 0.88-1.28]) and CVD mortality (HR, 1.33 [95% CI, 1.12-1.58] vs 1.27 [95% CI, 0.94-1.71]), although the P values for interactions were not significant. However, the associations were only significant in the CKB cohort for participants younger than 65 years compared with those 65 years or older for all-cause mortality (HR, 1.45 [95% CI, 1.28-1.64] vs 1.08 [95% CI, 0.91-1.29]; P for interaction < .001) and CVD mortality (HR, 1.34 [95% CI, 1.09-1.65] vs 1.01 [95% CI, 0.78-1.32]; P for interaction = .02).
The association of depression with mortality remained unchanged in the sensitivity analyses excluding participants who died during the first 2 years of follow-up (CKB cohort: 5261 participants [1.0%]; DFTJ cohort: 1204 participants [4.6%]); participants with baseline history of cancer, CHD, or stroke (CKB cohort: 25 514 participants [5.0%]; DFTJ cohort: 6633 participants [25.2%]); or participants 80 years or older in the DFTJ cohort (533 participants [2.0%]); or by using 5 or more symptoms as the cutoff to define depression. The associations were slightly attenuated when adjusting for 6 specific diseases instead of the health index score but did not change materially (eTable 3 in the Supplement).
In this large prospective cohort study of adults in China, we found that depression was associated with a significantly elevated risk of all-cause and CVD mortality, and the associations were independent of sociodemographic factors, lifestyle factors, and health status. Furthermore, we found that the associations were only significant in men. To our knowledge, this is the first and largest study in mainland China to evaluate the associations of depression with all-cause and CVD mortality.
A large body of evidence has suggested that depression is a risk factor for all-cause mortality. Many studies have been performed on this topic in the general population as well as specific patient groups, and a 2014 meta-analysis of 293 studies with 1 813 733 participants from 35 countries5 reported that depression was associated with a 52% increased risk of all-cause mortality. However, most of the investigations were performed in Western countries, and high-quality studies in Chinese populations are lacking, to our knowledge. In an early study among 280 adults 65 years or older living in a rural community in Taiwan, Fu et al8 reported that depressive symptoms, defined as a score of 15 or higher on the 20-item Center for Epidemiological Studies–Depression Scale (CES-D), were associated with higher mortality risk during 12 years of follow-up. In another cohort study of 2416 men and women in Taiwan 65 years or older, Teng et al9 reported that depressive symptoms, defined as a score of 10 or higher on the 10-item CES-D, were associated with higher mortality risk during 8 years of follow-up only in men and not in women. Similarly, in a cohort study of 56 088 men and women in Hong Kong 65 years or older, Sun et al7 reported that depressive symptoms, defined as a score of 8 or higher on the 15-item Geriatric Depression Scale, were associated with higher mortality risk during 8 years of follow-up only in men and not in women. A 2018 study10 among 1999 participants in Beijing reported that time-dependent depressive symptoms, defined as a score of 16 or higher on the 20-item CES-D, were associated with higher mortality risk in men and women. Therefore, this study, the largest cohort study on this topic in mainland China to our knowledge, is generally consistent with the literature. The previous 4 studies in Chinese populations were all in people 55 years or older, and our study also included people younger than 55 years. In the stratified analysis by age, we did not find consistent associations of age with all-cause or CVD mortality. The exact reasons for this disparity are unknown, and more prospective studies are needed to explore whether age-specific associations exist for depression and mortality.
We also observed that the association of depression with mortality was more evident in men. This is consistent with 3 previous studies in elderly Chinese populations in Taiwan,9 Hong Kong,7 and Beijing, China.10 In a 2017 meta-analysis, Miloyan and Fried6 evaluated sex differences in the association of depression with mortality. They found 33 estimates in men and 29 in women and reported that the association was slightly stronger in men than women.6 Therefore, the evidence suggests that there may be a sex difference in the association of depression with mortality. Although the exact reasons for the sex difference are unclear, there are several potential biological and psychosocial explanations. First, depression-associated oxidative stress19-21 may play a role: mounting evidence suggests that men express lower levels of antioxidants (eg, superoxide dismutase22 and glutathione23) in mitochondria than women do, which would lead to greater oxidative damage in men. Second, although the prevalence of depression is generally higher in women than men, the strategies to overcome depression might be different. Compared with women, men may be culturally less inclined to report mild depression or seek help until depression is severe.24,25 In addition, emotional processing in the brain may be generally different in men compared with women, as indicated in 2 studies using functional magnetic resonance imaging.26,27 Finally, 2 previous studies28,29 have examined a number of risk factors associated with CHD and stroke that might be different in men and women, and the underlying biological, behavioral, or social mechanisms are still unclear.
We also found that depression was associated with significantly higher risk of CVD mortality. Mounting evidence has suggested that depression is a risk factor of CVD mortality in the general population and in patients with known CVDs, and a 2017 meta-analysis of 92 studies with 116 295 136 participants30 reported that depression was associated with a 63% higher risk of CVD mortality. A 2016 meta-analysis of myocardial infarction and coronary events from 19 cohort studies with 323 709 participants and 8447 events31 reported that depression was associated with a significantly increased risk of deaths of myocardial infarction and coronary events. Another meta-analysis of stroke morbidity and mortality among 317 540 participants from 28 prospective cohort studies32 reported depression was associated with a 55% increase risk of stroke mortality. Similar to all-cause mortality, most of the studies on CVD mortality were conducted in Western countries, and high-quality studies in Chinese populations are lacking. In a 2013 cohort study of 62 839 participants in Hong Kong 65 years or older, Sun et al33 reported that depressive symptoms, defined as a score of 8 or higher on the 15-item Geriatric Depression Scale, were associated with higher CHD mortality risk in men but not in women. In a cohort study among 1999 participants in Beijing, China, Li et al10 reported that time-dependent depressive symptoms were associated with higher CVD mortality risk in men but not in women. Therefore, our study is generally consistent with previous studies in this field. In addition, our previous analyses of the CKB study found that depression was associated with higher risks of incident ischemic heart disease34 and stroke.35 The results of this analysis of the association of depression with CVD mortality were consistent with these results.
Previous studies had proposed several potential mechanisms for the association of depression with mortality, but there is no consensus yet.5,36 Biologically, depression may cause dysregulation of central biological stress systems, including hypothalamic-pituitary-adrenal axis hyperactivity37 and neuroimmune and sympathoadrenergic dysregulation,38 which may all play a role in the association of depression with mortality. In addition, people with depression often have unhealthy lifestyles,36 including physical inactivity, smoking, heavy alcohol consumption, and poor diet, and low adherence to treatment, and those factors have been consistently shown to be risk factors for premature death. As for CVD mortality, previous studies have reported that depression is associated with vascular endothelial dysfunction,39 a prolonged QT interval,40 lower heart rate variability,36 and increased platelet aggregation,39 which would accelerate the deterioration of the condition.
Several strengths should be noted in this study. To our knowledge, this is the largest study to investigate the association of depression with mortality in Chinese populations. Participants from the CKB study were recruited from 10 areas (5 urban and 5 rural) across China, while participants from the DFTJ cohort were mostly recruited among retired workers from a large company, and most of whom were living in Shiyan City in central China. The characteristics of the participants in the 2 cohorts were different in many ways. The consistent results from the 2 cohort studies indicate that the findings might not be due to random error. Furthermore, we collected detailed information on outcomes, had a relatively long follow-up period and high follow-up rate, and adjusted for a number of potential confounding factors.
Several limitations should also be noted in our study. First, the DFTJ cohort is an occupational cohort, and the healthy worker effect might be possible. However, the prevalence of clinically relevant depressive symptoms was similar to that in a 2014 meta-analysis of Chinese adults with a similar age range.41 In the CKB study, the 12-month prevalence of depression detected by CIDI-SF was low (0.61%) compared with findings from previous studies in Western and Chinese populations,42-44 which may be owing to different depression measurement tools, procedures, and study populations. The CKB study only recruited individuals who volunteered to participate; therefore, depressed patients may have been less likely to be included because of their loss of interest in most things. In addition, the questions regarding symptoms were asked differently, which may also cause misclassifications (ie, 2-week duration in the past 12 months in the CKB vs any time in the past 1 month in the DFTJ), and participants in the DFTJ cohort were not asked the depression screening questions before giving answers regarding symptoms of depression. Despite the difference in the depression measurement and substantial differences in the prevalence of depression in the 2 cohorts, the consistent results in the 2 cohorts reduced the possibility of chance findings. Second, we did not have information on clinical diagnoses of depression and its subtypes in our studies and did not measure depression status during the follow-up; thus, misclassifications of depression status were possible. Further studies are also needed to investigate the long-term associations of different types of depression (eg, melancholic and atypical depression) with health outcomes.45 We used 2 different criteria to define depression in our analyses (having ≥3 symptoms in the main analysis and having ≥5 symptoms in the sensitivity analysis), but the results remained similar, indicating that the cutoffs to detect depression did not change our findings. Furthermore, misclassifications were more likely to be nondifferential and were unrelated to the outcome; thus, they may underestimate the associations. Third, we did not collect detailed information of use of antidepressant medications among people with depression. However, previous analysis of the CKB study46 and an epidemiological survey in Chinese populations43 have suggested that the proportion of people with depression who received treatment is low. Therefore, the influence of antidepressant treatment on our results would be minimal. Fourth, residual confounding is still possible, although we have adjusted for various established and potential risk factors for mortality.
The findings of this cohort study suggest that depression is an independent risk factor of all-cause and CVD mortality in adults in China, especially in men. More studies with clinically diagnosed depression and repeated measures of depression in Chinese populations are still needed to confirm our findings and clarify the potential underlying mechanisms. Given the high disease burdens associated with depression and CVD in the general population and the low treatment rate in Chinese population,46 our findings have significant clinical and public health importance, and more efforts are needed in China to increase awareness and improve treatment strategies for individuals with depression.
Accepted for Publication: December 12, 2019.
Published: February 12, 2020. doi:10.1001/jamanetworkopen.2019.21043
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Meng R et al. JAMA Network Open.
Corresponding Author: An Pan, PhD, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (firstname.lastname@example.org); Liming Li, MD, Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China (email@example.com).
Author Contributions: Drs Pan and Li had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Meng and Yu contributed equally to this work.
Concept and design: Meng, Yu, Guo, Zhang, Z. Chen, Wu, Pan.
Acquisition, analysis, or interpretation of data: Meng, Yu, Liu, He, Lv, Bian, Yang, Y. Chen, Z. Chen, Pan, Li.
Drafting of the manuscript: Meng.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Meng, Liu, Pan.
Obtained funding: Guo, Z. Chen, Pan, Li.
Administrative, technical, or material support: Yu, He, Lv, Guo, Bian, Yang, Y. Chen, Zhang, Z. Chen, Pan, Li.
Supervision: Z. Chen, Wu, Pan, Li.
Conflict of Interest Disclosures: None reported.
Funding/Support: This study was specifically supported by the National Key Research and Development Program of China (grant 2017YFC0907504) and the National Natural Science Foundation of China (grant 81202266). The Dongfeng-Tongji cohort was supported by the National Key Research and Development Program of China (grants 2016YFC0900800, 2016YFC0900801, 2017YFC0907500, and 2017YFC0907501), and the National Natural Science Foundation of China (grants 91643202 and 81230069). The China Kadoorie Biobank (CKB) baseline survey and the first repeated survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up of CKB was supported by grants from the UK Wellcome Trust (grants 202922/Z/16/Z, 088158/Z/09/Z, and 104085/Z/14/Z), the National Natural Science Foundation of China (grants 81390540, 81390541, and 81390542), the National Key Research and Development Program of China (grants 2016YFC0900500, 2016YFC0900501, and 2016YFC0900504), and the Chinese Ministry of Science and Technology (grant 2011BAI09B01).
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Group Information: The members of the China Kadoorie Biobank Collaborative Group are as follows:
International Steering Committee: Junshi Chen, Zhengming Chen (principal investigator), Rory Collins, Liming Li (principal investigator), and Richard Peto.
International Coordinating Center, Oxford: Daniel Avery, Ruth Boxall, Derrick Bennett, Yumei Chang, Yiping Chen, Zhengming Chen, Robert Clarke, Huaidong Du, Simon Gilbert, Alex Hacker, Mike Hill, Michael Holmes, Andri Iona, Christiana Kartsonaki, Rene Kerosi, Ling Kong, Om Kurmi, Garry Lancaster, Sarah Lewington, Kuang Lin, John McDonnell, Iona Millwood, Qunhua Nie, Jayakrishnan Radhakrishnan, Sajjad Rafiq, Paul Ryder, Sam Sansome, Dan Schmidt, Paul Sherliker, Rajani Sohoni, Becky Stevens, Iain Turnbull, Robin Walters, Jenny Wang, Lin Wang, Neil Wright, Ling Yang, and Xiaoming Yang.
National Coordinating Center, Beijing, China: Zheng Bian, Yu Guo, Xiao Han, Can Hou, Jun Lv, Pei Pei, Yunlong Tan, and Canqing Yu.
Qingdao, China, Centers for Disease Control and Prevention (CDC) Regional Coordinating Center: Zengchang Pang, Ruqin Gao, Shanpeng Li, Shaojie Wang, Yongmei Liu, Ranran Du, Yajing Zang, Liang Cheng, Xiaocao Tian, Hua Zhang, Yaoming Zhai, Feng Ning, Xiaohui Sun, and Feifei Li.
Licang, China, CDC Regional Coordinating Center: Silu Lv, Junzheng Wang, and Wei Hou.
Heilongjiang Province, China, CDC Regional Coordinating Center: Mingyuan Zeng, Ge Jiang, and Xue Zhou.
Nangang, China, CDC Regional Coordinating Center: Liqiu Yang, Hui He, Bo Yu, Yanjie Li, Qinai Xu, Quan Kang, and Ziyan Guo.
Hainan Province, China, CDC Regional Coordinating Center: Dan Wang, Ximin Hu, Hongmei Wang, Jinyan Chen, Yan Fu, Zhenwang Fu, and Xiaohuan Wang.
Meilan, China, CDC Regional Coordinating Center: Min Weng, Zhendong Guo, Shukuan Wu, Yilei Li, Huimei Li, and Zhifang Fu.
Jiangsu Province, China, CDC Regional Coordinating Center: Ming Wu, Yonglin Zhou, Jinyi Zhou, Ran Tao, Jie Yang, and Jian Su.
Suzhou, China, CDC Regional Coordinating Center: Fang Liu, Jun Zhang, Yihe Hu, Yan Lu, Liangcai Ma, Aiyu Tang, Shuo Zhang, Jianrong Jin, and Jingchao Liu.
Guangxi Province, China, CDC Regional Coordinating Center: Zhenzhu Tang, Naying Chen, and Ying Huang.
Liuzhou, China, CDC Regional Coordinating Center: Mingqiang Li, Jinhuai Meng, Rong Pan, Qilian Jiang, Jian Lan, Yun Liu, Liuping Wei, Liyuan Zhou, Ningyu Chen Ping Wang, Fanwen Meng, Yulu Qin, and Sisi Wang.
Sichuan Province, China, CDC Regional Coordinating Center: Xianping Wu, Ningmei Zhang, Xiaofang Chen, and Weiwei Zhou.
Pengzhou, China, CDC Regional Coordinating Center: Guojin Luo, Jianguo Li, Xiaofang Chen, Xunfu Zhong, Jiaqiu Liu, and Qiang Sun.
Gansu Province, China, CDC Regional Coordinating Center: Pengfei Ge, Xiaolan Ren, and Caixia Dong.
Maiji, China, CDC Regional Coordinating Center: Hui Zhang, Enke Mao, Xiaoping Wang, Tao Wang, and Xi Zhang.
Henan Province, China, CDC Regional Coordinating Center: Ding Zhang, Gang Zhou, Shixian Feng, Liang Chang, and Lei Fan.
Huixian, China, CDC Regional Coordinating Center: Yulian Gao, Tianyou He, Huarong Sun, Pan He, Chen Hu, Xukui Zhang, Huifang Wu, and Pan He.
Zhejiang Province, China, CDC Regional Coordinating Center: Min Yu, Ruying Hu, and Hao Wang.
Tongxiang, China, CDC Regional Coordinating Center: Yijian Qian, Chunmei Wang, Kaixu Xie, Lingli Chen, Yidan Zhang, Dongxia Pan, and Qijun Gu.
Hunan Province, China, CDC Regional Coordinating Center: Yuelong Huang, Biyun Chen, Li Yin, Huilin Liu, Zhongxi Fu, and Qiaohua Xu.
Liuyang, China, CDC Regional Coordinating Center: Xin Xu, Hao Zhang, Huajun Long, Xianzhi Li, Libo Zhang, and Zhe Qiu.
Additional Contributions: Judith Mackay, FRCP (Chinese University of Hong Kong); Yu Wang, PhD, Gonghuan Yang, PhD, Zhengfu Qiang, MD, Lin Feng, MSc, Maigeng Zhou, PhD, Wenhua Zhao, PhD, and Yan Zhang, BD (China CDC); Lingzhi Kong, MD, Xiucheng Yu, MD, and Kun Li, MD (Chinese Ministry of Health); and Sarah Clark, DPhil, Martin Radley, BSc, Michael Hill, DPhil, Hongchao Pan, PhD, and Jill Boreham, PhD (Clinical Trial Service Unit, Oxford University), assisted with the design, planning, organization, and conduct of the study. None of these individuals received compensation for their contributions.
Create a personal account or sign in to: