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Depression is associated with significant morbidity and human capital costs globally. Early screening for depressive symptoms and timely depressive disorder case identification and intervention may improve health outcomes and cost-effectiveness among affected individuals. China’s public and academic communities have reached a consensus on the need to improve access to early screening, diagnosis, and treatment of depression.
This study aims to estimate the screening prevalence and associated factors of subthreshold depressive symptoms among Chinese residents enrolled in the cohort study using a mobile app–based integrated mental health care model and investigate the 12-month incidence rate and related factors of major depressive disorder (MDD) among those with subthreshold depressive symptoms.
Data were drawn from the Depression Cohort in China (DCC) study. A total of 4243 community residents aged 18 to 64 years living in Nanshan district, Shenzhen city, in Guangdong province, China, were encouraged to participate in the DCC study when visiting the participating primary health care centers, and 4066 (95.83%) residents who met the DCC study criteria were screened for subthreshold depressive symptoms using the Patient Health Questionnaire-9 at baseline. Of the 4066 screened residents, 3168 (77.91%) with subthreshold depressive symptoms were referred to hospitals to receive a psychiatric diagnosis of MDD within 12 months. Sleep duration, anxiety symptoms, well-being, insomnia symptoms, and resilience were also investigated. The diagnosis of MDD was provided by trained psychiatrists using the Mini-International Neuropsychiatric Interview. Univariate and multivariate logistic regression models were performed to explore the potential factors related to subthreshold depressive symptoms at baseline, and Cox proportional hazards models were performed to explore the potential factors related to incident MDD.
Anxiety symptoms (adjusted odds ratio [AOR] 1.63, 95% CI 1.42-1.87) and insomnia symptoms (AOR 1.13, 95% CI 1.05-1.22) were associated with an increased risk of subthreshold depressive symptoms, whereas well-being (AOR 0.93, 95% CI 0.87-0.99) was negatively associated with depressive symptoms. During the follow-up period, the 12-month incidence rate of MDD among participants with subthreshold depressive symptoms was 5.97% (189/3168). After incorporating all significant variables from the univariate analyses, the multivariate Cox proportional hazards model reported that a history of comorbidities (adjusted hazard ratio [AHR] 1.49, 95% CI 1.04-2.14) and anxiety symptoms (AHR 1.13, 95% CI 1.09-1.17) were independently associated with an increased risk of incident MDD. The 5-item World Health Organization Well-Being Index was associated with a decreased risk of incident MDD (AHR 0.90, 95% CI 0.86-0.94).
Elevated anxiety symptoms and unfavorable general well-being were significantly associated with subthreshold depressive symptoms and incident MDD among Chinese residents in Shenzhen. Early screening for subthreshold depressive symptoms and related factors may be helpful for identifying populations at high risk of incident MDD.
Mental disorders account for significant illness-associated disability globally, and major depressive disorder (MDD, also called clinical depression) is one of the leading causes [
It is well documented that subthreshold depressive symptoms (ie, not meeting the minimum diagnostic threshold for a major depressive episode) could predispose and portend incident MDD, and previous evidence suggests that individuals manifesting subthreshold depressive symptoms have an approximately 2-fold higher risk of incident MDD than those without [
During the past 30 years across China, rapid economic development and social change (eg, urbanization) have exposed citizens to changing factors. These rapid changes may be a determinant of adverse mental health problems (eg, subthreshold depressive symptoms and MDD) [
Although 6 types of serious mental health disorders (including schizophrenia, schizoaffective disorder, persistent delusional disorder, bipolar disorder, mental disorders caused by epilepsy, and mental retardation accompanied by mental disorders) are recognized in community-based mental health management programs in China, MDD is not included. Previous evidence suggests that factors such as stigma-induced stress contribute to the unwillingness to seek professional help among individuals with depressive symptoms or MDD [
Data were derived from the Depression Cohort in China (DCC) study (Chinese Clinical Trial Registry ChiCTR 1900022145), which is an ongoing longitudinal, population-based study for early identification, treatment, prevention, and management of subthreshold depressive symptoms and MDD [
The study procedures were carried out in accordance with the Declaration of Helsinki. This study received ethics approval from the institutional review board of the School of Public Health, Sun Yat-sen University (L2017044), and the study protocol was approved by the ethics review boards of all the participating centers.
The DCC study used a BRIDGES health care model, which used the BRIDGES model, a project of the University of Toronto’s departments of medicine and family and community medicine, as a reference [
The study data were drawn from an ongoing cohort study that began in early 2019 in which community residents are screened when they visit primary health care centers. Approximately 90,000 residents in Nanshan district walk through the doors of 34 primary health care centers a year. Among all the people visiting these centers, GPs selectively screen those who have mental health–related physical complaints (eg, sleep problems and chronic somatic pain) or are more likely to have mental health issues based on the GPs’ clinical experience and our study training. Our study aimed to screen individuals with subthreshold depressive symptoms and identify patients with MDD within limited medical resources and periods. Therefore, a total of 4243 community residents aged 18 to 64 years living in Nanshan were encouraged to participate in the DCC study when visiting the 34 participating primary health care centers at baseline, of which 177 (4.17%) residents were excluded (n=5, 2.8%, with incomplete information on depressive symptoms; n=133, 75.1%, with diagnostic depressive disorder; and n=39, 22%, with other psychiatric disorders;
In this study, of the 4066 residents who met the study criteria, 3168 (77.91%) screened positive with subthreshold depressive symptoms at baseline at the primary health care centers and were referred to the general or specialized mental health hospitals to receive the psychiatric diagnoses within 12 months through the BRIDGES health care model. Psychiatric diagnoses were provided by the trained psychiatrists using the Mini-International Neuropsychiatric Interview (MINI; Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria). Among the patients with subthreshold depressive symptoms, 5.97% (189/3168) were first diagnosed with MDD during the follow-up period after the baseline screening (
The integrated mental health care model in Nanshan, Shenzhen, in Guangdong province, China. MDD: major depressive disorder; MINI: Mini-International Neuropsychiatric Interview; PHQ-9: Patient Health Questionnaire-9.
In the DCC study, subthreshold depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9), a widely used self-report measure in clinical and research settings that screens for depressive symptoms over the past 2 weeks [
Participants with subthreshold depressive symptoms were referred to hospitals to receive the diagnosis of MDD within 12 months. The MINI, a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision–based validated structured diagnostic psychiatric interview, was used by psychiatrists to diagnose a current MDD and exclude other diagnoses [
Sleep duration was assessed by the question,
Well-being was measured using the 5-item World Health Organization Well-Being Index (WHO-5), which is a positively worded scale designed to measure the level of subjective well-being over the past 2 weeks on a 6-point scale ranging from 0 (not present) to 5 (constantly present), leading to a raw score ranging from 0 (absence of well-being) to 25 (maximal well-being) [
Insomnia symptoms were assessed with the Insomnia Severity Index, which consists of 7 items, with each item scored from 0 to 4, for a maximum of 28 points. Higher scores represent greater insomnia levels [
Adverse life events were measured using the Stressful Life Events Screening Questionnaire (SLESQ), which has been validated in Chinese studies [
Resilience was measured using the Connor-Davidson Resilience Scale (CD-RISC), which comprises 25 items, with each rated on a 5-point scale ranging from 0 (not at all true) to 4 (true nearly all of the time). The Cronbach
The sociodemographic variables included in this study were age, sex (1=male and 2=female), ethnicity (1=Han Chinese and 2=Chinese minorities), education level (1=junior high school or below, 2=senior high school, and 3=college or above), living arrangement (1=living alone, 2=living with family, and 3=living with others), marital status (1=unmarried, 2=married, 3=divorced, and 4=widowed), lifetime smoking (assessed by the question,
Data were described as means (SDs) for normally distributed continuous variables and as medians (IQRs) for nonnormally distributed continuous variables, and frequency with percentage was used to describe categorical variables. Baseline characteristics were summarized according to baseline depressive symptoms. Mann-Whitney
The sample characteristics of all included participants at baseline are shown in
Baseline characteristics of participants according to subthreshold depressive symptom status (N=4066).
Variable | Participants | |||||
|
Total | PHQ-9 score<5 (n=898) | PHQ-9 score≥5 (n=3168) |
|
||
Age (years), mean (SD) | 38.19 (11.46) | 38.35 (10.74) | 38.14 (11.66) | .64 | ||
|
.67 | |||||
|
Male | 1541 (37.9) | 346 (38.53) | 1195 (37.72) |
|
|
|
Female | 2525 (62.1) | 552 (61.47) | 1973 (62.28) |
|
|
|
.76 | |||||
|
Han Chinese | 3922 (96.46) | 869 (96.77) | 3053 (96.37) |
|
|
|
Chinese minorities | 140 (3.44) | 29 (3.23) | 111 (3.50) |
|
|
|
Missing | 4 (0.1) | —b | — |
|
|
|
<.001 | |||||
|
Junior high school or below | 576 (14.17) | 84 (9.35) | 492 (15.53) |
|
|
|
Senior high school | 966 (23.76) | 198 (22.05) | 768 (24.24) |
|
|
|
College or above | 2516 (61.88) | 615 (68.49) | 1901 (60) |
|
|
|
Missing | 8 (0.2) | — | — |
|
|
|
<.001 | |||||
|
Living alone | 484 (11.9) | 83 (9.24) | 401 (12.66) |
|
|
|
Living with family | 3018 (74.23) | 723 (80.51) | 2295 (72.44) |
|
|
|
Living with others | 447 (11) | 69 (7.68) | 378 (11.93) |
|
|
|
Missing | 117 (2.88) | — | — |
|
|
|
<.001 | |||||
|
Unmarried | 997 (24.52) | 178 (19.82) | 819 (25.85) |
|
|
|
Married | 2927 (72) | 704 (78.4) | 2223 (70.17) |
|
|
|
Divorced | 117 (2.88) | 13 (1.45) | 104 (3.28) |
|
|
|
Widowed | 25 (0.61) | 3 (0.33) | 22 (0.69) |
|
|
Lifetime smoking (yes), n (%) | 1080 (26.56) | 225 (25.06) | 855 (27) | .27 | ||
Onset age of smoking (years), mean (SD) | 19.50 (5.39) | 19.52 (6.20) | 19.49 (5.15) | .93 | ||
Lifetime drinking (yes), n (%) | 2424 (59.61) | 566 (63.02) | 1858 (58.65) | .02 | ||
Onset age of drinking (years), mean (SD) | 19.23 (4.93) | 19.72 (4.90) | 19.09 (4.94) | .008 | ||
|
974 (23.95) | 189 (21.05) | 785 (24.78) | .02 | ||
|
Hypertension | 396 (9.74) | 84 (9.35) | 312 (9.85) | .70 | |
|
Diabetes | 168 (4.13) | 37 (4.12) | 131 (4.14) | .99 | |
|
Heart disease | 45 (1.11) | 8 (0.89) | 37 (1.17) | .59 | |
|
Stroke | 13 (0.32) | 1 (0.11) | 12 (0.38) | .32 | |
|
Thyroid disease | 129 (3.17) | 26 (2.9) | 103 (3.25) | .67 | |
|
Tumor | 33 (0.81) | 4 (0.45) | 29 (0.91) | .21 | |
|
Other | 313 (7.7) | 52 (5.79) | 261 (8.24) | .02 | |
Sleep duration (hours per day), mean (SD) | 6.67 (4.68) | 7.25 (6.54) | 6.50 (3.99) | <.001 | ||
Anxiety symptoms, mean (SD) | 5.24 (4.88) | 1.37 (1.86) | 6.34 (4.91) | <.001 | ||
Adverse life events, mean (SD) | 0.48 (1.15) | 0.18 (0.65) | 0.56 (1.24) | <.001 | ||
Well-being, mean (SD) | 13.75 (6.05) | 12.45 (5.80) | 18.35 (4.49) | <.001 | ||
Insomnia symptoms, mean (SD) | 8.25 (6.54) | 3.45 (3.47) | 9.61 (6.56) | <.001 | ||
Resilience, mean (SD) | 59.05 (23.50) | 68.56 (26.36) | 56.05 (21.69) | <.001 |
aMann-Whitney
bNot available.
Univariate logistic regression models reported that participants with education levels of junior high school or below (OR 1.26, 95% CI 1.05-1.50) and senior high school (OR 1.90, 95% CI 1.48-2.43) had higher risks of having subthreshold depressive symptoms than those with education level of college or above. Participants living with family (OR 0.66, 95% CI 0.51-0.84) were less likely to report subthreshold depressive symptoms than those living alone. Lifetime drinking (OR 1.20, 95% CI 1.03-1.40) and a history of comorbidities (OR 1.24, 95% CI 1.03-1.48) were positively associated with subthreshold depressive symptoms, as were anxiety symptoms (OR 1.78, 95% CI 1.70-1.87), insomnia symptoms (OR 1.30, 95% CI 1.27-1.32), and adverse life events (OR 1.73, 95% CI 1.52-1.96). The onset age of drinking (OR 0.98, 95% CI 0.96-0.99), sleep duration (OR 0.88, 95% CI 0.83-0.94), general well-being (OR 0.81, 95% CI 0.79-0.82), and resilience (OR 0.98, 95% CI 0.97-0.98) were negatively associated with subthreshold depressive symptoms.
After incorporating all significant variables from the univariate analyses, the multivariate logistic regression model demonstrated that only anxiety symptoms (adjusted OR [AOR] 1.63, 95% CI 1.42-1.87) and insomnia symptoms (AOR 1.13, 95% CI 1.05-1.22) were associated with an increased risk of subthreshold depressive symptoms. General well-being (AOR 0.93, 95% CI 0.87-0.99) was negatively associated with the risk of subthreshold depressive symptoms. Moreover, these factors were still significantly associated with subthreshold depressive symptoms after correcting for multiple testing (
Factors associated with subthreshold depressive symptoms among baseline participants.
Variable | Model 1a | Model 2b | |||||
|
ORc (95% CI) | Adjusted OR (95% CI) |
|
||||
Age (1-year increase) | 1.00 (0.99-1.01) | .64 | N/Ae | N/A | N/A | ||
Male (reference=female) | 0.97 (0.83-1.13) | .66 | N/A | N/A | N/A | ||
Ethnicity (reference=Chinese minorities) | 0.92 (0.61-1.39) | .69 | N/A | N/A | N/A | ||
|
|||||||
|
Junior high school or below | 1.26 (1.05-1.50) | .01 | 1.48 (0.57-3.88) | .43 | .78 | |
|
Senior high school | 1.90 (1.48-2.43) | <.001 | 1.13 (0.54-2.38) | .75 | .89 | |
|
|||||||
|
Living with family | 0.66 (0.51-0.84) | .001 | 0.92 (0.30-2.84) | .89 | .96 | |
|
Living with others | 1.13 (0.80-1.61) | .48 | 0.54 (0.24-1.21) | .13 | .39 | |
|
|||||||
|
Unmarried | 0.63 (0.19-2.12) | .45 | N/A | N/A | N/A | |
|
Married | 0.43 (0.13-1.44) | .17 | N/A | N/A | N/A | |
|
Divorced | 1.09 (0.29-4.15) | .90 | N/A | N/A | N/A | |
Lifetime smoking (reference=no smoking) | 1.11 (0.93-1.31) | .25 | N/A | N/A | N/A | ||
Onset age of smoking (1-year increase) | 1.00 (0.97-1.03) | .93 | N/A | N/A | N/A | ||
Lifetime drinking (reference=no drinking) | 1.20 (1.03-1.40) | .02 | 1.33 (0.39-4.59) | .65 | .89 | ||
Onset age of drinking (1-year increase) | 0.98 (0.96-0.99) | .009 | 0.96 (0.91-1.01) | .15 | .39 | ||
History of comorbidities (reference=no comorbidities) | 1.24 (1.03-1.48) | .02 | 1.26 (0.67-2.36) | .48 | .78 | ||
Sleep duration (1-hour increase) | 0.88 (0.83-0.94) | <.001 | 0.98 (0.94-1.02) | .33 | .71 | ||
Anxiety symptoms (increase in score by 1) | 1.78 (1.70-1.87) | <.001 | 1.63 (1.42-1.87) | <.001 | <.001 | ||
Well-being (increase in score by 1) | 0.81 (0.79-0.82) | <.001 | 0.93 (0.87-0.99) | .02 | .09 | ||
Insomnia symptoms (increase in score by 1) | 1.30 (1.27-1.32) | <.001 | 1.13 (1.05-1.22) | .001 | .007 | ||
Adverse life events (increase in score by 1) | 1.73 (1.52-1.96) | <.001 | 0.96 (0.74-1.24) | .76 | .89 | ||
Resilience (increase in score by 1) | 0.98 (0.97-0.98) | <.001 | 1.00 (0.99-1.01) | .99 | .99 |
aThe univariate logistic regression models were the unadjusted models.
bThe multivariate logistic regression models incorporated all significant variables from the univariate analyses.
cOR: odds ratio.
dThe false discovery rate–adjusted
eN/A: not applicable.
Of the 3168 residents screened with subthreshold depressive symptoms at baseline, 189 (5.97%) met the first major depressive episode criterion between March 2019 and March 2020; the 12-month incidence rate of MDD among participants with subthreshold depressive symptoms was 5.97% (189/3168;
In addition, we used restricted cubic splines to flexibly model and visualize the associations of anxiety symptoms and well-being with the risk of incident MDD (
Factors associated with incident major depressive disorder among participants with subthreshold depressive symptoms.
Variable | Model 1a | Model 2b | |||||
HRc (95% CI) | Adjusted HR (95% CI) |
|
|||||
Age (1-year increase) | 1.00 (0.99-1.02) | .73 | N/Ae | N/A | N/A | ||
Male (reference=female) | 0.77 (0.56-1.05) | .10 | N/A | N/A | N/A | ||
Ethnicity (reference=Chinese minorities) | 0.73 (0.36-1.50) | .40 | N/A | N/A | N/A | ||
|
|||||||
|
Junior high school or below | 0.86 (0.55-1.33) | .50 | N/A | N/A | N/A | |
|
Senior high school | 1.00 (0.70-1.42) | .99 | N/A | N/A | N/A | |
|
|||||||
|
Living with families | 0.70 (0.46-1.06) | .01 | N/A | N/A | N/A | |
|
Living with others | 1.00 (0.59-1.71) | .99 | N/A | N/A | N/A | |
|
|||||||
|
Unmarried | 0.48 (0.14-1.67) | .25 | N/A | N/A | N/A | |
|
Married | 0.33 (0.08-1.12) | .07 | N/A | N/A | N/A | |
|
Divorced | 0.73 (0.19-2.78) | .64 | N/A | N/A | N/A | |
Lifetime smoking (reference=no smoking) | 1.02 (0.73-1.40) | .93 | N/A | N/A | N/A | ||
Onset age of smoking (1-year increase) | 1.00 (0.96-1.04) | .98 | N/A | N/A | N/A | ||
Lifetime drinking (reference=no drinking) | 1.51 (1.10-2.06) | .01 | 0.98 (0.68-1.42) | .92 | .92 | ||
Onset age of drinking (1-year increase) | 0.99 (0.96-1.02) | 0.39 | N/A | N/A | N/A | ||
History of comorbidities (reference=no comorbidities) | 2.05 (1.44-2.91) | <.001 | 1.49 (1.04-2.14) | .03 | .07 | ||
Sleep duration (1-hour increase) | 1.01 (0.99-1.03) | .36 | N/A | N/A | N/A | ||
Anxiety symptoms (increase in score by 1) | 1.24 (1.21-1.27) | <.001 | 1.13 (1.09-1.17) | <.001 | <.001 | ||
Well-being (increase in score by 1) | 0.80 (0.78-0.83) | <.001 | 0.90 (0.86-0.94) | <.001 | <.001 | ||
Insomnia symptoms (increase in score by 1) | 1.15 (1.13-1.18) | <.001 | 1.03 (1.00-1.07) | .05 | .07 | ||
Adverse life events (increase in score by 1) | 1.37 (1.28-1.47) | <.001 | 1.09 (1.00-1.19) | .05 | .07 | ||
Resilience (increase in score by 1) | 0.98 (0.97-0.99) | <.001 | 1.00 (0.99-1.02) | .67 | .78 |
aThe univariate logistic regression models were the unadjusted models.
bThe multivariate logistic regression models incorporated all significant variables from the univariate analyses.
cHR: hazard ratio.
dThe false discovery rate–adjusted
eN/A: not applicable.
This prospective cohort study used a mobile app–based integrated mental health care model to link mental health care delivery among primary health care centers, a general hospital, and a mental health hospital in Nanshan, Shenzhen, and identify populations at high risk and factors contributing to elevated risks of subthreshold depressive symptoms and incident MDD among Chinese residents in Nanshan.
Of the 4066 community residents meeting the DCC study criteria, 3168 (77.91%) screened positive for subthreshold depressive symptoms at baseline in evaluations by GPs using the PHQ-9 at primary health care centers [
The univariate logistic regression models demonstrated that a lower level of education, lifetime drinking, a history of comorbidities, anxiety symptoms, insomnia symptoms, and adverse life events were positively associated with subthreshold depressive symptoms. In contrast, residents living with family, having an older onset age of drinking, having longer sleep duration, and having higher resilience were less likely to experience subthreshold depressive symptoms [
Regarding the situation of MDD in China, Huang et al [
Moreover, the univariate Cox proportional hazards models showed that lifetime drinking, a history of comorbidities, anxiety symptoms, insomnia symptoms, and adverse life events might predict an increased risk of incident MDD. A higher level of subjective well-being and resilience may predict a decreased risk of incident MDD. Findings from the univariate analyses may provide evidence for identifying populations at high risk for incident MDD and modifiable factors among individuals with subthreshold depressive symptoms. In addition, after accounting for all significant variables, the multivariate analyses indicated that only a history of comorbidities and anxiety symptoms were associated with an increased risk of incident MDD among populations with subthreshold depressive symptoms; a higher level of well-being significantly predicted decreased incident MDD risk. Furthermore, restricted cubic spline models demonstrated a linear and positive association between anxiety symptoms and the risk of incident MDD. Well-being was negatively associated with incident MDD in a nonlinear fashion, meaning that although individuals with lower general well-being might be at a higher risk of incident MDD, whereas those with a higher level of well-being might be less likely to develop MDD, the HR for incident MDD did not linearly decrease by the level of well-being. These findings suggest that recognizing and preventing individuals with a history of comorbidities or anxiety symptoms from developing MDD may be the focus of targeted intervention efforts, and a strategy of cultivating well-being might be a promising first step. A possible explanation for the association between a history of comorbidities and incident MDD is that depressive disorder is prevalent in patients with a physical disorder (particularly in those with severe conditions such as diabetes and stroke), and this comorbidity largely contributes to a poorer quality of life, worsening outcomes, higher medical costs, and more significant disability of the physical disorders [
Several limitations need to be addressed. First, only community residents in Nanshan, Shenzhen, were involved in this study; thus, the findings may not be fully generalizable to other regions. Second, the study sample was drawn from the DCC study, which recruited participants from the participating primary health care centers, and the study sample was not randomly selected. Therefore, this study had selection and sampling bias and the estimated screening prevalence of depressive symptoms among adults in Shenzhen might be overestimated. Third, we did not estimate the 12-month incidence rate of MDD among individuals without subthreshold depressive symptoms. Although it may be rare for individuals without depressive symptoms to exhibit a 12-month incidence of MDD, these populations may present different illness characteristics in the presence of MDD. Fourth, the variable of PHQ-9 was used as a dichotomous variable (ie, having or not having depressive symptoms) in this study, and we would like to use a different method to estimate the severity of depressive symptoms (ie, the polytomous variable of PHQ-9) in our future study. To reduce the risk of developing MDD, early screening of vulnerable populations and implementation of effective interventions targeting these symptoms are highly recommended. The strengths of this study included the longitudinal design, the large representative community-based sample, and the use of a clinically validated diagnostic interview (ie, MINI) to diagnose MDD.
Using a mobile app–based integrated mental health care model, this study found that the screened prevalence of subthreshold depressive symptoms among community residents in Nanshan, Shenzhen, was high. More specifically, we reported that 5.97% (189/3168) of the individuals with subthreshold depressive symptoms developed MDD within 12 months. In addition, anxiety symptoms were associated with an increased risk of subthreshold depressive symptoms and incident MDD among the community residents, and the presence of a history of comorbidities may predict the elevated risk of incident MDD. Moreover, a higher level of general well-being might decrease the risks of subthreshold depressive symptoms and incident MDD. The results from our study highlight the following: (1) the 12-month incidence rate of MDD among populations with subthreshold depressive symptoms is high, and screening earlier on in the illness trajectory of individuals with subthreshold depressive symptoms and recognizing high-risk factors may lead to earlier detection and treatment of MDD; (2) more attention should be paid to vulnerable populations with adverse characteristics (eg, anxiety symptoms, insomnia symptoms, or adverse life events); and (3) the implementation of an integrated mental health care model (ie, linking community, primary health care centers, and hospitals) in China might be helpful for training GPs to provide essential mental health services, improving community residents’ access to mental health care as well as the timely referral and management of patients with MDD.
The characteristics of each item of the Patient Health Questionnaire-9 among participants at baseline.
Incidence of the first diagnosis of depressive disorder among participants with subthreshold depressive symptoms.
Restricted cubic spline models for the associations of (A) anxiety symptoms and (B) well-being with the risk of incident major depressive disorder.
Building Bridges to Integrate Care
Connor-Davidson Resilience Scale
Depression Cohort in China
general practitioner
hazard ratio
low- and middle-income countries
major depressive disorder
Mini-International Neuropsychiatric Interview
odds ratio
Patient Health Questionnaire-9
Stressful Life Events Screening Questionnaire
World Health Organization
5-item World Health Organization Well-Being Index
This work was supported by the National Key Research and Development Program of China (2018YFC2000705) and the National Natural Science Foundation of China (81761128030 and 81903339). The authors wish to give particular thanks to all participating primary health care centers, hospitals, and community residents who made the study possible and gratefully acknowledge technical support from the School of Public Health, Sun Yat-sen University.
LG and CL had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. All authors were responsible for the concept and design of the study as well as the acquisition, analysis, and interpretation of data. HZ, Y Liao, and XH drafted the manuscript. Critical revision of the manuscript for important intellectual content was carried out by LG, CL, Y Lee, Y Liu, LMWL, MS, LL, and RSM. HZ was responsible for the statistical analysis. LG and CL obtained funding. Administrative, technical, or material support was provided by LG, CL, BF, and RSM. The study was supervised by LG, CL, BF, and RSM.
RSM has received research grant support from Canadian Institutes of Health Research (CIHR)/Global Alliance for Chronic Diseases (GACD)/National Natural Science Foundation of China (NSFC); speaker and consultation fees from Lundbeck, Janssen, Alkermes, Neumora Therapeutics, Mitsubishi Tanabe, Purdue, Pfizer, Otsuka, Takeda, Neurocrine, Sunovion, Bausch Health, Axsome, Novo Nordisk, Kris, Sanofi, Eisai, Intra-Cellular, NewBridge Pharmaceuticals, Abbvie, and Atai Life Sciences. RSM is a CEO of Braxia Scientific Corp..