One of the most common mental illnesses in the world is depression (1). Depression is a mental condition characterized by chronic sorrow and a loss of interest. It affects how you feel, think, and behave and can lead to several mental and physical difficulties. It’s also known as major depressive disorder or clinical depression (2, 3). In 2017, 4.4% of the global population suffered from depression, according to the World Health Organization (1). Furthermore, depression is the leading cause of disability, is frequently associated with an increased mortality rate since depressed people are much more likely to commit suicide (4, 5). The urbanization process is among the influencing environmental factors that can cause mental disorders (6–8). Several studies have also shown that mental health issues are likely to unfold in countries with higher rates of urbanization due to their associated socio-demographic transitions (6, 9–11). Individuals living in these areas must adjust to new fast-paced lifestyles, and face intense competition for jobs, commodities, goods, and services, and thus potentially experience increased stress levels (6, 12). Furthermore, urbanization comes with the creation of communities comprising of people who may not know each other well, such communities can undermine friendship, familial connections, and diminish traditional social solidarity, and as a consequence, the local social capital is weakened in the metropolitan setting (9, 13). Understanding mental disorder patterns and identifying appropriate measuring tools thus are necessary for the process of designing contextualized interventions that help improve the well-being state of people living in areas with accelerated urbanization.

Although there is a variety of available instruments to assess depressive symptoms, the nine-item Patient Health Questionnaire (PHQ-9), extensively utilized assessments in multiple research and countries, is one of the most commonly used tools for diagnosis and severity assessment of depression (14–17). It can be used either as a diagnostic algorithm to make a probable diagnosis of major depressive disorder (MDD) or as a continuous measure of the level of depressive symptoms. The PHQ-9 measures the severity of depression by assessing symptoms such as depressed mood, sleep disturbance, fatigue, concentration problems, psychomotor disturbances, and suicidal ideation following the Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition (DSM-IV-TR) (18, 19). Furthermore, the PHQ-9’s psychometric qualities have been tested on various populations, namely mental patients (20, 21), groups of medical patients (22, 23), the elderly (24), general adult population (25, 26). Although the PHQ-9’s internal consistency was demonstrated to be adequate (α = 0.70–0.93) (20–26) and the results of this scale showed moderate-to-strong relationships with the associated measures of depression, investigations of PHQ-9’s underlying component structure were often inconsistent. Several studies revealed that a one-factor model representing the one-dimensionality of the depression construct provided the best fit to the data among different demographic groups (1, 18, 26–28). Nonetheless, other research discovered that the PHQ-9 factor structure was best represented by two-factor models that recognize both somatic and cognitive/affective (20–23, 29). Because of this difference in previous research findings, it is critical to determine whether the PHQ-9 model is the most helpful in explaining depression using different local populations.

In Vietnam, there have been numerous studies on the factors associated with depressive disorder in various groups, such as the elderly, pregnant women, workers, etc. (30–32); however, none of them determined the reliability and tested the validity of PHQ-9 in the community context (30–32). As a result, the goal of this research is to provide data on the psychometric aspects of PHQ9, such as reliability and validity and to determine influencing factors that may affect depression assessment in the community context.

Table 1 summarizes the sociodemographic characteristics of participants. 25.7% of 889 respondents to the survey had at least one of the depressive symptoms. The majority of participants were women (58.9%), lived in rural areas (86.8%), and had primary/secondary school education levels (33.5%). 26.8% of respondents were farmers and 25.2% were freelancers. The mean age of respondents was 42.12 (SD = 13.38), and the average household monthly income was US$ 433.12 (SD = US$ 241.54). The distribution of PHQ-9 scores among depressed and non-depressed patients was described in Appendix Figure A1.

Table 2 shows the health status and risk behaviors of the respondents. More than half of the participants reported at least one symptom indicating health problems (56.8%). The proportion of participants who consumed alcohol and those who smoked were 34.0 and 19.3%, respectively. Healthcare workers (72.5%), friends/relatives (56.4%), and radio/television (43.3%) were the most preferred sources of health information for participants. The mean EQ5D score was 0.92 (SD = 0.12), while the average PHQ-9 score was 2.91 (SD = 3.16). There was a statistical significance of the EQ5D and PHQ-9 scores that differed between depressed and non-depressed patients (p-value < 0.001). The effect size (Cohen’s d) from the EQ5D and PHQ-9 was 0.85 (95% CI = 0.70–1.01) and 2.67 (95% CI = 2.47–2.86), which indicates a large effect size.

Two factors, namely Somatic (five items) and Cognitive or Affective (four items), were identified using the scree plot and parallel analysis (Figure 1) and exploratory factor analysis, with Cronbach’s alphas of 0.84 and 0.80, respectively (Table 3). Furthermore, our CFA results revealed that the model 2 with two factors had better fit indices [TLI = 0.945; CFI = 0.960; RMSEA (90%CI) = 0.074 (0.063–0.086); SRMR = 0.043; p-value = < 0.001] compared to the original instrument (Model 1) [TLI = 0.697; CFI = 0.773; RMSEA (90%CI) = 0.174 (0.163–0.184); SRMR = 0.102; p-value = < 0.001; Figure 2].

Table 4 shows the results of the descriptive analysis for each PHQ-9 item. All of the nine items had a range of scores from 0 to 3. The Skewness and Kurtosis coefficients ranged from 0.97–6.71 to 3.84–51.76, respectively. Nine out of nine items had Kurtosis coefficients greater than 3.0, indicating that these data distribution had long and fat tails as well as high and shape peaks. The mean and standard deviation of each item in PHQ-9 scale were also reported in this table. Moreover, most of the nine items showed high correlation coefficients with other items in the respective factor (r > 0.6).

Table 5 summarizes the factor of the PHQ-9 instrument score based on various socio-economic characteristics. The mean Somatic factor and Cognitive/Affective factor scores were 0.49 (SD = 0.48) and 0.11 (SD = 0.29), with the statistically higher score for people living in urban areas. Notable differences in these factors in terms of living location, level of education, and leisure-time exercise were observed (p < 0.01).

Table 6 indicates the factors associated with depression of participants. The PHQ-9 score of older participants was statistically higher, as was the somatic factor. While female participants had a statistically higher PHQ-9 score and were more prone to experience depressive symptoms and somatic characteristics, those residing in rural regions had a statistically lower score. In terms of health behavior and health status, people with health issues had statistically higher PHQ-9 scores and were more likely to experience depressive symptoms; somatic factors; or cognitive/affective factors. Those who engaged in moderate leisure-time exercise had a statistically significant association with lower cognitive/affective variables, whereas those who engaged in heavy drinking were more inclined to have depressive symptoms, somatic factors, and a higher PHQ-9 score. Individuals who obtained health information via radio/television, newspaper, health care workers, or social networks were less likely to suffer from depression in comparison to those who listened through the loudspeaker.

The results of the study reveal that those individuals who were females and residents of urban areas had a higher prevalence of depressive symptoms. Associations between level of depressive symptoms and individual characteristics, such as age, gender, health status, drinking behavior, level of physical activity, and access to information sources were also found. Furthermore, the study provided insights into the measuring features of the PHQ-9 instrument in assessing depression for the general population in Vietnam. The two-factor model, which includes factor 1 “Somatic” and factor 2 “Cognitive/Affective,” was shown to have better fit indices than the theoretical one-factor model, according to the performed factor analysis. Results of this study can potentially promote the initial mental health status assessment, usage of psychological therapy, and thus life quality enhancement.

Consistent with prior studies, our findings suggest that Vietnamese people were more likely to register their depression under the two-factor model instead of the one-factor of the original PHQ-9 (21, 40, 41). The first factor was “Somatic” with five items (Anhedonia, Depressed mood, Sleep disturbance, Fatigue, and Appetite changes) and the other was “Cognitive/Affective” with four items (Low Self-esteem, Concertation difficulties, Psychomotor disturbances, and Suicidal ideation). The unidimensional structure of the PHQ-9 has been corroborated in the majority of studies that look into its factor structure (26, 42–44). Other authors, on the other hand, suggest that the PHQ-9’s two-factor structure may be more interpretable in light of depression conceptual frameworks (20, 45, 46). The disparity between these research findings might be attributed to the participation of distinctive subgroups. Studies that indicated the superiority of the two-factor model, which is characterized by somatic and non-somatic (affective) symptoms, have been carried out on a number of clinical populations, namely those with concomitant physical conditions such as spinal cord injury (20) or cancer (45, 46). As a result, the somatic factor loading is probably induced by the confounding effects of physical and mental illness (43). However, Lamela et al. suggested that a two-factor model yielded fit in a general population sample (44), which is consistent with other empirical studies (36). Furthermore, our investigation found that for most people with moderate depression in a suburban environment, the two-factor model had greater fit indices compared to the theoretical one-factor from previous findings (36, 45). CFA results supported EFA findings when our two-factor model produced satisfactory fit indicators.

These two factors were given names based on the variables that made up the factors, as well as prior literature and the DSM-IV-TR (19). In comparison to the theoretical one-factor model used in earlier research, our two-factor model with factor 1 “Somatic” and factor 2 “Cognitive/Affective” had superior fit indices (40, 47) when two variables Q1 Anhedonia “Little interest or pleasure in doing things” and Q2 Depressed mood “Feeling gloomy, dejected, or hopeless” were added to factor 1 (40, 47). The cognitive-affective dimension of symptoms includes negative mood or negative affect, while the somatic dimension includes symptoms such as fatigue or loss of energy (48). Although several studies have shown that both two variables Q1 and Q2 suitable in factor 2 “Cognitive/Affective”, our findings showed that anhedonia or depressed mood could be characteristics to recognize somatic symptom disorder. Patients may experience a near-complete lack of happiness, desire, and interest in working because of these symptoms. However, more research is still needed to determine the items in each factor and the best PHQ-9 model for participants of different subgroups.

In addition, a significant link between the number of health problems and the risk of depression was found; this is consistent with the findings of previous studies (49, 50). People with health issues are concerned not only about their health but also about their family and socioeconomic status. In the context of accelerated urbanization, suburban people are often under financial pressure and in fear of getting ill since the expenditure on health care services can have detrimental effects on their financial health (51, 52).

Although only a small number of individuals reported smoking or alcohol consumption, those behaviors were linked to the somatic symptoms of depression. A possible rationale is that people tend to smoke or drink alcohol as a coping mechanism to deal with stress and depression (53). This consequently gives a potentially false impression of depressive symptoms relief (54, 55). The influence of stimulant usage on psychological discomfort, whether increased or lessened, is, nevertheless, still debatable. Moreover, in line with previous research, female gender is strongly associated with somatization (56–58); compared to males, females are more likely to report (59) somatic symptoms (e.g., eating disorder, headache, low body image confidence, insomnia, and exhaustion) in early adolescence (58, 60, 61).

In consonance with previous studies, moderate regular exercise can improve the cognitive and affective aspects of depression (62–64) and can aid in the prevention and cure of health problems such as high blood pressure, diabetes, and arthritis, and enhancing mood, eliminating anxiety, boosting confidence, and promoting social engagement (65, 66). In addition, people are likely to have reduced depressive symptoms if they obtain health information via radio/television, newspapers, health care workers or social network as these formal sources provide useful and reliable information about how to prevent such health problems and to raise awareness of health protection for themselves and their families (67–69).

A number of implications can be drawn from our study. Firstly, the PHQ-9 can be applied in clinical practice in Vietnam as a screening instrument. Potential patients in rural areas can fill the PHQ-9 before seeing a psychiatrist. Then the psychiatrist can use the scores to determine if the patient’s score is higher than the cut-off for depressive disorder, and it is determined that the symptoms are predominately somatic or cognitive/affective. If predominately somatic, the psychiatrists can consider providing psychotherapy to address somatic symptoms and provides symptomatic relief. In contrast, if the symptoms are predominately cognitive/affective and moderate to severe, the psychiatrists should consider antidepressants and cognitive training. This will enhance the efficiency of psychiatric services in Vietnam, which is characterized by a high volume of patient load. Severe depression can also be identified for more intense treatment. Furthermore, health and risk behavior education programs should be implemented to raise people’s health awareness of depression and how to treat it. Regulating health monitoring, encouraging people to exercise, and reducing substance use have a significant impact on the mental health of Vietnamese in suburban areas.

However, the limitation of this study should not be overlooked. The sampling may affect the generalizability of our findings. In order to demonstrate the consistency of the empirical findings, future studies should be performed on a larger and more diversified population. The inclusion of structured questionnaires like the one used in this study would allow for replication and could serve as a reference point for future research. In addition, our findings might be susceptible to recollection bias due to participants’ self-reporting process. Missing responses might also affect the result interpretation and reliability. Besides, the study did not use other reliability measures such as nomological validity and test-retest reliability. In addition, the need for a gold standard validation study, as well as a study exploring psychometric approaches such as item response theory, should be explored in future research in Vietnam. Lastly, prior research finds that the summed PHQ-9 has better diagnostic properties than the algorithm (70). In some studies, the application of the diagnostic algorithm score of the PHQ-9 as a method of validation includes the involvement of psychiatrists, and it is challenging for Vietnam as it is a developing country and does not have enough psychiatrists. In Vietnam, there are only 0.91 psychiatrists were available per 100,000 people. As a result, we do not have enough of a clinical workforce to use the PHQ-9 diagnostic algorithm.

This study provided evidence that the PHQ-9 scale is a valid and internally reliable instrument to assess depression in the Vietnam population. The PHQ-9 has a stable two-factor structure. Both factors were found to be significantly associated with gender, health behavior, and health status in the suburban community in Vietnam. This scale can be a useful screening tool for depression, and further validation studies in other populations are recommended.

The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

This research project was reviewed and managed by the Vietnam Ministry of Health under Decision 850/QD-BYT. Ethical approval was granted by the IRB committee at Hanoi Medical University and the Ministry of Health. The patients/participants provided their written informed consent to participate in this study.

TV, TL, CL, and CH: conceptualization. ADa, LL, SN, ADo, and ND: data curation. LV, ADa, SN, and TV: formal analysis. SN, TV, TL, RH, and CH: investigation. ADa, LL, TT, ADo, and ND: methodology. TT, RH, and CH: supervision. LV, TT, ADo, TL, and CL: writing – original draft. LV, LL, ND, TL, CL, and RH: writing – review and editing. All authors contributed to the article and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.