Quality of life in outpatients with depression in China

Journal of Affective Disorders 150 (2013) 513–521

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Research report

Quality of life in outpatients with depression in China Qingzhi Zeng a, Yifeng Xu a,n, Wei Chun Wang b a

Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 600 Wan Ping Nan Road, Shanghai 200030, PR China Centre for Physical Activity & Nutrition Research (C-PAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Hwy, Burwood, VIC 3125, Australia

b

art ic l e i nf o

a b s t r a c t

Article history: Received 7 December 2012 Received in revised form 25 April 2013 Accepted 26 April 2013 Available online 25 May 2013

Background: Quality of life (QOL) is an important outcome measure for patients with depression, but QOL research involving large samples of patients has been uncommon. The purpose of this study was to evaluate the QOL of Chinese outpatients with depression and its determinants. Methods: Using a cross-sectional survey design, data were collected continuously from 19,984 outpatients; 19,950 usable questionnaires were obtained. Along with the QOL index (WHOQOL-BREF), the questionnaire also included participants’ sociodemographic characteristics, outpatient visits, and medication use information. Results: Less than 5% of depressed patients reported “good” or “very good” QOL, while less than 3% were satisfied with their general health. The overall score was low (54.12); four QOL domain (physical health, psychological, social relationships, and environment) scores (range, 35.03–40.10) were significantly lower than in other community population surveys. QOL scores were significantly lower among first-visit than non-first-visit patients. Medication users reported significantly higher QOL scores than non-users, with NaSSA more effective than SSRIs, followed by other types, SNRIs, and no medication, in that order. Limitations: Since this was an observational, cross-sectional survey with continuous outpatient data collection method instead of random sampling, generalization of the results is limited, and causality cannot be determined. However, the “natural” observational design, large sample size, and similarity in findings with other studies reveal the “real world” QOL of depressed outpatients in mainland China. Conclusions: Depressed patients had a low QOL, and the scores of first-visit patients with severe symptoms were significantly lower than non-first-visit patients. Though medication can improve patients’ QOL, different types of medications have different impacts. & 2013 Elsevier B.V. All rights reserved.

Keywords: Outpatients with depression Quality of life First-visit patients Antidepressant

1. Introduction Depression is one of the most common mental illnesses, and it is regarded as a major public health problem worldwide. In the USA, the National Comorbidity Survey Replication (NCS-R) (2003) showed that the life-time and 12-month prevalences of depression were 16.2% and 6.6%, respectively (Kessler et al., 2003). According to the World Health Organization (WHO) (2006), the risks of lifetime depression for men and women were 7–12% and 20–25%, respectively. An epidemiological survey of the four provinces in China (Phillips et al., 2009) showed that the prevalence of major depressive disorder among the general population was 2.07%. He et al. (2009) found that the prevalence of depression in general hospitals was as high as 12.1%. The World Health Organization (WHO) (2001) reported that the burden of depression ranked 4th

n

Corresponding author. Tel.: +86 21 54254051; fax: +86 21 64387986. E-mail address: [email protected] (Y. Xu).

0165-0327/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jad.2013.04.052

among disabling diseases, projected to increase to 2nd in 2020, next to cardiovascular diseases. Previous studies found that patients with depression experienced physical, psychological, and social problems, as well as declines in health-related quality of life, including increased financial pressure, social and family relationship issues, occupational dysfunction, increased days of absence from work, and poor health status (Johnson et al., 1992; Revicki et al., 1998). According to the WHO (The WHOQOL Group, 1998), health-related quality of life refers to individuals’ goals, expectations, standards, and experiences of life within a particular culture and value system. This means that quality of life is rooted in the cultural and social environment within which an individual lives, and it reflects people’s subjective feelings and experiences. Poor quality of life indicates that individuals encounter difficulties in their daily life due to illness or other reasons causing dysfunction or subjective hardship. Therefore, evaluation of health-related quality of life complements the assessment of patients’ physical and mental health status because of its sensitivity to functional status. Thus, it was recommended by Ishak et al. (2011a) that quality of life can be

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used as an outcome assessment in intervention studies among patients with depression. The validity and the reliability of the short version of the quality of life tool (WHOQOL-BREF) developed by the WHO has been tested in many countries. As an approved quality of life assessment tool, the WHOQOL-BREF has been widely used in populations such as communities, patients with chronic illness, and psychiatric outpatients. Numerous studies have been conducted on quality of life among patients with depression in Western countries, while there have been few studies using large samples in Asian countries, especially mainland China. The SF-36 and EQ-5D have been commonly used assessment tools, and relatively few studies used WHOQOL-BREF. For example, Shek (2010) found that if “quality of life” was used as a key word, it came up with 32,331, 145,729, and 15,229 articles from PsycINFO, MEDLINE, and CINAHL databases, respectively. If “quality of life” and “Chinese” were used as key words, the search resulted in 721, 1271, and 314 articles from the same databases. Furthermore, if “quality of life”, “Chinese”, and “WHOQOL-BREF” were used as key words, the search came up with only 27, 40, and 22 papers. If “depression” were added to these key words, the number of papers that would appear in the search results would be far less. While quality of life is culture specific, oriental ethnicity has its own unique background. For example, Confucian ideology represents the personal characteristics of self-control, benevolence, modesty, and harmony. These features may lead to stronger endurance towards pain or illness and less expression of agony among Chinese than other cultural ethnicities. In addition, the outcomes of treatment, patient management, and the treatment effect in clinical practice can only be reflected in the evaluation of patients with depression who live in the communities. However, few studies have assessed the quality of life of outpatients with depression. The aims of the study were to use WHOQOL-BREF as an assessment tool to examine: (1) the quality of life of outpatients with depression; (2) the relationships between the quality of life of outpatients with depression and a number of clinical covariates; and (3) the effects of medication on the quality of life of outpatients with depression.

2. Methods 2.1. Study design and sample Using a cross-sectional survey design, participants were recruited from 30 psychiatric hospitals or psychiatric/psychological outpatient departments in general hospitals (9–2191 patients participated at each study site) in 17 provinces and municipalities, and 23 cities of mainland China. The recruiting sites were located in seven administrative regions in East, North, South, Central, Northeast, Southwest, and Northwest China (see Fig. 1). All patients who met the diagnostic criteria of CCMD-3 depression and were capable and willing to complete the quality of life questionnaire during the study period were included in the study regardless of their first or non-first visit to the study sites and age. The exclusion criteria were: participants with psychotic disorders; participants with depression due to physical illness that may interfere with the study; participants who were unable to complete the study due to severe health issues; and participants with communication problems due to physical disability or language barriers. Ethics approval was obtained from the Shanghai Mental Health Center Ethics Committee. All participants provided their written, informed consent before starting the study.

2.2. Procedure A continuous data collection method was used among outpatients during the period between January 2011 and February 2012. The participants were invited to complete the questionnaires concerning quality of life and related clinical information at their visits. The contents of the questionnaire included information on demographics, quality of life, and medication use. 2.3. Instrument 2.3.1. Demographics Variables included name, sex, age, occupation, and education as reported by the participants 2.3.2. Medical treatment Variables were hospital where the patient received treatment and whether or not it was a first visit (visit status) to the study site, as reported by the participants. 2.3.3. Medication use Information of medication use at the clinical visits was recorded by the psychiatrists in the survey. Six types of medication were included: selective 5-HTs (e.g., SSRIs), 5-HT and NEs (e.g., SNRIs), NE and specific 5-HTs (e.g., NaSSA), other medications, concomitant medications, and medication non-use. 2.3.4. Quality of life The short quality of life index (WHOQOL-BREF) is a simple version of WHOQOL-100, developed by the WHO. There are almost 15 versions in different languages, and it has been used all over the world. The Chinese version of the WHOQOL-BREF was issued by the China Quality of Life Research Collaboration Center in 1999 and has been approved by the WHO (Fang, 2000). Research (Xia et al., 2012) has shown that the Chinese version of the WHOQOL-BREF has high internal reliability, discriminant validity, and construct validity. In addition to the original 26 items, another two items characterizing the Chinese cultural background have been added to the Chinese version of the WHOQOL-BREF. Therefore, the WHOQOL-BREF in Chinese used in the present study comprised 28 items, and the response options ranged from 0 (very poor) to 4 (very good). There were two items in the original WHOQOL-BREF assessing general quality of life (item G1) and general health status (item G2). The remaining 24 items measured four domains of quality of life, including physical health (7 items), psychological (6 items), social relationships (3 items), and environment (8 items). The total scores ranged from 4 to 20 or from 0 to 100, with lower scores representing lower levels of quality of life (Skevington et al., 2004). The two items measuring Chinese cultural background were worded as “has your life been affected by family conflict? (F27)” and “how has your dietary pattern been? (F28)”. Moreover, an additional item (F29) was added following the WHOQOL-BREF, where participants were required to provide a self-evaluation in terms of their general quality of life: would you please give a score to your general quality of life based on your physical, psychological, social relationships, and environment status (use 100% as a full score). Because these additional three items (i.e., F27, F28, & F29) were Chinese culture-specific, they were excluded from the analysis in the cross-cultural comparisons. 2.4. Analysis SPSS version 17.0 was used for the analysis. Means and standard deviations were calculated for the continuous variables, and percentages were used for the categorical variables. Student’s t-tests were used to compare the scores reported by the outpatients with

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Fig. 1. Geographic distribution of the recruiting sites.

depression and the average normal population for the four quality of life domains (i.e., comparisons between sample means and population means). Sample mean quality of life scores were compared between first and non-first visit outpatients. Quality of life scores were compared between two groups: medication user (including SSRIs, SNRIs, NaSSA, concomitant, and others) and medication non-user groups using t-tests. The Bonferroni correction was used to adjust the alpha values for the pairwise comparisons between different medication types (including SSRIs, SNRIs, NaSSA, concomitant, others and no medication).

3. Results 3.1. Demographic characteristics A total of 19,984 patients participated in the survey, including 52.7% women and 47.3% men, with a mean age of 42 (SD¼13.8) years (range, 6–98 years). The majority of the participants (66.7%) were aged between 31 and 60 years. The percentages of employment status were 75.8% (employed), 12.2% (unemployed), and 12.0% (retired). The majority of the participants (51.6%) completed college education or above, 40.3% completed at least secondary education, and only 8.1% completed the primary level or less (see Table 1).

Table 1 Participants’ demographic characteristics. Demographics Sex (n¼ 18,556) Male Female Age (n¼ 18,448) ≤30 years 31–60 years ≥61years Employment (n¼ 11,711) Employed Unemployed Retired Education (n¼12,726) Primary school or less Secondary school or equivalent College or above

N (%)

8,782 (47.3) 9,774 (52.7) 42.0 7 13.83 (mean7 SD) 4,167 (22.6) 12,311 (66.7) 1,970 (10.7) 8,872 (75.8) 1,427 (12.2) 1,412 (12.0) 1,028 (8.1) 5,134 (40.3) 6,564 (51.6)

Missing data: sex—1428 (7.1%); age—1536 (7.7%); employment—8273 (41.4%); education—7258 (36.4%). SD ¼ standard deviation.

3.2. Clinical characteristics There were 68.9% first-visit patients and 31.1% non-first visit patients. Overall, 8514 patients (48.1%) had never used any antidepressants before; 3370 (19.0%), 1880 (10.6%), 925 (5.2%), and 2463 (13.9%), were on SSRIs, SNRIs, NaSSA, and other antidepressants,

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3.4. Quality of life assessment

respectively, and 552 (3.1%) were using concomitant medications (see Table 2).

“Poor” and “very poor” were reported by 50.5% and 12.7% of the participants, respectively, for the general quality of life items (G1), but less than 5% of the participants reported “good” and “very good”. The general health status item (G2) was “dissatisfied” or “very dissatisfied” in 59.2% and 12.4% of the participants, respectively, and less than 3% reported “satisfaction”. Among the four domains, the average scores of item 1 (physical pain) and item 6 (need medical treatment to function) were greater than 3, while the remaining items were scored lower than 3. The proportions of positive responses were rather low. In addition to pain and discomfort (52.4%), dependency on medication and other medical treatment (48.2%), and negative feelings (18.3%), the remaining items had scores lower than 15%, with the majority lower than 10% towards the positive ends. In terms of the responses to the two items related to Chinese background (F27 & F28), 24.7% of the participants believed that their quality of life was not affected by family conflict, and only 6.1% of the participants reported healthy dietary status. The general quality of life self-assessment item (F29) was scored low, with an average of 54.12 and a standard deviation of 13.05 (see Table 3). Overall, low scores were given by the participants for the four domains including physical health, psychological, social relationships, and environment. With a scoring range between 0 and 100, the physical health domain was scored the highest (mean ¼ 40.10, SD¼ 11.61 for 0–100 scoring; mean ¼ 10.42, SD ¼1.86 for 4–20 scoring), and the psychological domain was scored the lowest (mean¼35.03, SD¼ 13.80 for 0–100 scoring; mean ¼9.61, SD ¼2.21 for 4–20 scoring). The scores of the four domains of quality of life were significantly lower than the averages of the domestic

3.3. General status of the patients who completed the baseline survey A total of 19,950 patients completed the WHO-BREF, representing a response rate of 99.8%. There were 44% men, and 22.6% of the participants were under 30 years old, while 66.7% of the participants were between 31 and 60 years old. The majority of the participants (68.9%) were first-visit patients to the study site. Chi-square tests showed no significant difference between the study sample (n ¼19,950) and the entire recruited outpatient population (N ¼19,984) in relation to sex, age, and visit status. Table 2 Participants’ clinical characteristics. Clinical characteristics Visit status (n¼ 18,451) First visit Non-first visit Medication (n ¼17,704) SSRIs SNRIs NaSSA Others Concomitant No medication

N (%)

12,709 (68.9) 5,742 (31.1) 3,370 1,880 925 2,463 552 8,514

(19.0) (10.6) (5.2) (13.9) (3.1) (48.1)

Missing data: first visit—1533 (7.7%), medication— 2280 (11.4%).

Table 3 WHOQOL-BREF item scores (n¼ 19950). Item

G1.General quality of life G2.General health Domain 1: physical health 1. Physical pain 2. Have enough energy 3. Satisfied with sleep 4. Able to get around? 5. Ability of living activities 6. Need medical treatment to function 7. Capacity for work Domain 2: psychological 8. Enjoy life 9. Able to concentrate 10. Satisfied with yourself 11. Accept bodily appearance 12. Negative feelings 13. Meaningful life Domain 3: social relationships 14. Personal relationships 15. Support from friends 16. Sex life Domain 4: environment 17. Safety of daily life 18. Condition of living place 19. Enough money to meet your needs 20. Accessing to health services 21. Information available in daily life 22. Opportunity for leisure activities 23. Healthy physical environment 24. Transport F27. Family conflict F28. Dietary pattern F29. General quality of life self-assessment

x 7 s:d:

Distribution (%) N

Very poor

Poor

Neither poor nor good

19,725 19,709

12.7 12.4

50.5 59.2

32.0 25.9

4.4 2.3

0.4 0.1

2.29 7 0.76 2.187 0.67

19,939 19,940 19,943 19,941 19,939 19940 19,889

2.4 12.1 26.9 10.0 11.4 4.6 11.8

19.9 56.2 52.5 51.6 41.3 17.0 43.0

25.2 27.8 18.3 28.2 41.9 30.2 39.8

33.4 3.6 2.1 9.8 5.3 33.8 5.3

19.0 0.3 0.1 0.4 0.1 14.4 0.1

3.477 1.08 2.247 0.72 1.96 7 0.74 2.39 7 0.81 2.417 0.77 3.36 7 1.07 2.39 7 0.77

19,928 19,923 19,923 19,938 19,849 19,925 19,939 19,896 19,913 19,531 19,942 19,934 19,927 19,942 19,935 19,933 19,941 19,937 19,924 19,865 19,816 19,896

13.3 12.4 11.2 11.4 11.1 13.3

46.2 48.5 43.3 37.9 45.3 43.6

36.1 35.0 40.2 42.7 25.3 37.8

4.2 3.9 5.2 7.2 14.0 5.1

0.2 0.2 0.1 0.7 4.3 0.2

2.32 7 0.76 2.317 0.74 2.40 7 0.76 2.487 0.82 2.55 7 1.00 2.357 0.78

10.5 9.5 10.8

38.1 33.5 38.8

43.9 45.9 46.5

7.2 10.9 3.7

0.2 0.2 0.1

2.497 0.79 2.59 7 0.81 2.43 7 0.74

12.3 9.5 13.4 9.6 10.6 12.0 10.5 9.0 5.3 9.8

37.9 32.6 36.0 32.8 38.5 44.4 38.5 38.6 33.7 51.7

41.2 44.5 39.7 44.1 39.3 36.1 43.3 39.7 36.3 32.5

8.2 12.9 9.7 13.0 10.5 6.4 7.3 11.9 18.2 5.4

0.4 0.5 1.2 0.6 1.2 1.2 0.5 0.8 6.5 0.7

2.477 0.83 2.62 7 0.84 2.497 0.89 2.62 7 0.85 2.53 7 0.86 2.40 7 0.82 2.497 0.80 2.577 0.84 2.87 70.99 2.357 0.76 54.127 13.05

Good

Very good

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Table 4 Comparisons of the quality of life among patients with depression among countries. City or country Current study (n¼ 19,950) Range 4–20 Range 0–100 Average in Mainland China (n¼ 1431) Fang (2000) Guang Zhou, China (n¼ 1052) Wang et al. (2006) Range 4–20 Range 0–100 Taiwan, China (n ¼13,083) Wang et al. (2006) Worldwide (23 countries) (n¼11,830) Skevington et al. (2004) t1, df1, p1

t2, df2, p2

t3, df3, p3

t4, df4, p4

Physical health

Psychological health

Social relationships

Environment

10.42 7 1.86 40.107 11.61 15.10 72.30

9.617 2.21 35.03713.80 13.89 71.89

10.03 7 2.54 37.687 15.88 13.93 7 2.06

10.107 2.52 38.12 715.73 12.147 2.08

14.56 7 2.00 66.00 712.56 59.127 13.69 16.20 7 2.90 t¼ −356.27, df ¼19949, p¼ 0.000 t¼ −315.20, df ¼19949, p¼ 0.000 t¼ −231.46, df ¼19949, p¼ 0.000 t¼ −439.95, df ¼19949, p¼ 0.000

13.69 72.23 60.55 7 13.96 49.437 15.63 15.007 2.8 t¼ −274.16, df ¼19946, p ¼0.000 t¼ −261.36, df ¼19946, p ¼0.000 t¼ −147.39, df ¼19946, p ¼0.000 t¼ −345.18, df ¼19946, p ¼0.000

14.117 2.23 63.217 13.92 56.517 14.28 14.30 7 3.2 t ¼−216.87, df ¼ 19938, p ¼ 0.000 t ¼−226.88, df ¼ 19938, p ¼ 0.000 t ¼−167.49, df ¼ 19938, p ¼ 0.000 t ¼−237.44, df ¼ 19938, p ¼ 0.000

12.337 2.32 52.047 14.53 42.38 7 14.92 13.50 72.60 t¼ −114.49, df ¼19941, p ¼0.000 t¼ −125.15, df ¼19941, p ¼0.000 t¼ −38.25, df ¼19941, p ¼0.000 t¼ −190.78, df ¼19941, p ¼0.000

Scoring range: 0–100 for Taiwan； 4–20 for Worldwide. After adjusted for age and sex, 4–20 for the average in Mainland China；t1, df1, p1, t2, df2, p2, t3, df3, p3 and t4, df4, p4 are the results when the current sample is compared with the average in Mainland China, Guang Zhou, Taiwan, and worldwide samples.

Table 5 Quality of life in first and non-first visit patients (x 7 SD). Domain & item

Domain 1：Physical health Domain 2：Psychological health Domain 3：Social relationships Domain 4：Environment G1.General quality of life G2.General health F27.Family conflict F28.Dietary pattern F29.General quality of life self-assessment

First visit

Non-first visit

N

Score

N

Score

12687 12685 12678 12682 12528 12519 12644 12607 12662

39.777 11.59 34.45 7 13.55 36.92 7 15.87 37.50 7 15.20 2.22 7 0.75 2.137 0.67 2.85 7 0.97 2.32 7 0.75 52.56 7 13.20

5732 5734 5732 5732 5697 5693 5703 5695 5712

41.517 11.00 37.42 7 13. 72 40.247 15.41 39.96 7 15.36 2.447 0.76 2.29 7 0.67 3.067 0.96 2.46 7 0.76 57.077 12.12

t

P

−9.81 −13.69 −13.42 −10.12 −18.18 −14.39 −13.49 −11.61 −22.71

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

The four domains range from 0 to 100.

population in 1999 (Fang, 2000), in Taiwan, and worldwide (Skevington et al., 2004) (see Table 4). 3.5. First and non-first-visit patients First-visit patients reported significantly lower scores than non-first-visit patients on the four domains of the quality of life scale (including physical health, psychological, social relationships, and environment), general quality of life and general health status (G1 & G2), items of family conflict (F27) and dietary status (F28), and the general quality of life self-assessment (see Table 5). 3.6. Quality of life among the different medication user groups The scores of the medication user groups were significantly higher than the scores of the medication non-user group, with the greatest differences in the psychological domain and the smallest differences in the physical domain. The remaining quality of life items were also scored significantly differently between the medication user groups and the medication non-user group. Differences in quality of life were also reported between different types of medication users. The scoring orders (from high to low) are presented as follows. In the physical health domain, NaSSA 4 SSRIs and concomitant 4SNRIs, the others, and non-

medication. In the psychological domain, NaSSA and concomitant4 SSRIs, SNRIs, and the others 4non-medication. In the social relationship domain, NaSSA and concomitant 4SSRIs 4SNRIs, the others, and non-medication. In the environment domain, concomitant4NaSSA4SSRIs and the others4SNRIs and non-medication. For the general quality of life item (G1), NaSSA and concomitant4SSRIs4SNRIs, the others, and non-medication. With the general health status item (G2), NaSSA and concomitant4SSRIs and SNRIs4the others4non-medication. Moreover, for the family conflict item (F27), NaSSA and the others4SSRIs, SNRIs, and concomitant4non-medication. For the dietary item (F28), NaSSA4concomitant4SSRIs4SNRIs and the others4non-medication. Finally, in terms of the general quality of life self-assessment (F29), NaSSA and concomitant4SSRIs4SNRIs, the others, and non-medication (see Table 6).

4. Discussion The sample size of the present study was larger than any previous study using the WHOQOL-BREF to assess the quality of life among outpatients with depression. Clinical and epidemiological research (Berlim et al., 2003; Zaratiegui, 2007; Sobocki et al., 2007; Reed et al., 2009; ten Doesschate et al., 2010; Zikic et al., 2010; Winter et al., 2012) has shown that the quality of life in a

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Table 6 The relationships between quality of life and the type of medication used ðx 7 s:d:Þ. Domain & Item

①SSRIs (n¼3367)

②SNRIs (n¼ 1878)

③NaSSA (n¼ 919)

④Others (n¼2462)

Domain 1： Physical health

40.107 11.68 39.52 7 10.71 44.30 7 11.36 39.747 9.99

Domain 2： Psychological health

I:Medication t, P1 group (n¼17.689)

⑤Concomitant (n¼552)

II:No medication (n¼8513)

41.137 11.71

39.09 7 12.38 40.377 11.10

F, P2

7.21, 0.000

33.56, 0.000 ③4①,⑤4②,④,II

34.79 7 14.71 34.82 7 12.35 42.75 7 14.03 35.197 12.79 40.63 7 13.05

33.407 13.50 36.05 7 13.83 12.87, 0.000

102.32, 0.000 ③,⑤ 4①,②,④4 II

Domain 3：Social relationships

37.577 16.26 36.647 14.09 44.417 14.94 36.26 7 15.96 43.217 14.17

36.197 15.00 38.05 7 15.72 8.06, 0.000

68.30, 0.000 ③,⑤ 4①4②,④,II

Domain 4： Environment

37.81 7 16.44 36.067 13.87 45.077 15.51 37.88 7 15.16

36.717 15.51 38.82 7 15.68 9.02, 0.000

104.51, 0.000 ⑤4③4①,④4 ②,II.

48.207 13.08

G1.General quality of life

2.377 0.70

2.22 7 0.69

2.687 0.89

2.20 7 0.81

2.58 7 0.78

2.22 7 .71

2.34 7 0.77

10.33, 0.000

100.25, 0.000 ③,⑤ 4①4②,④,II.

G2.General health

2.25 7 0.65

2.247 0.59

2.39 7 0.72

2.167 0.62

2.39 7 0.69

2.117 .68

2.25 7 0.64

13.64, 0.000

60.23, 0.000 ③,⑤ 4①,②4④4II

F27.Family conflict

2.90 7 0.90

2.94 7 1.10

3.337 0.88

3.337 1.17

2.93 7 0.87

2.677 0.93

3.077 1.04

26.55, 0.000

219.07, 0.000 ③,④ 4①,②,⑤4 II

F28.Dietary pattern

2.377 0.74

2.25 7 0.69

2.85 7 0.79

2.20 7 0.76

2.60 7 0.73

2.317 0.73

2.36 7 0.77

3.97, 0.000

129.23, 0.000 ③4⑤4① 4②,④,II

F29.General quality of life self-assessment

54.79 7 13.03 53.417 11.04 60.53 7 13.27 53.117 13.28 62.017 11.34

53.23 7 13.23 55.067 12.93 9.30, 0.000

99.67, 0.000 ③,⑤ 4①4②,④,II

The four domain scoring range: 0–100. t and P1 are comparison results between medication use(I) and medication non-use(II), F and P2 are the comparison results among the six types of medications (①—SSRIs, ②—SNRIs, ③—NaSSA, ④—Others, ⑤—Concomitant, and II-no medication). Pairwise comparisons were adjusted using the Bonferroni correction.

number of aspects was significantly lower among patients with depression than among patients without depression or patients with other chronic diseases. The present study found that less than 5% of the patients reported their quality of life as “good” or “very good”, and less than 3% were “satisfied” or “very satisfied” with their health status, which is consistent with previous findings. The scores of the four quality of life domains including physical, psychological, social relationships, and environment were lower than 40, especially the scores of the psychological domain, which was significantly lower than the average scores from the large community surveys in the domestic population (Fang, 2000) and the populations of Guang Zhou (Xia et al., 2012), Taiwan, and worldwide. The general quality of life scores were also low, with an average of 54.1. It is possible that patient’s actual quality of life may be lower than their self-reported data because of the Chinese Confucian cultural characteristics. The low levels of quality of life among patients with depression may be related to the disease itself, such as depression and low self-esteem, as well as psychological distress and decreased social function. A large survey among outpatients with depression using the WHO-QOL (BREF) to assess the quality of life is rare in either China or other countries. Zikic et al. (2010) found that, for the four domains of quality of life, the score (36.0–48.0) reported by 84 patients with depression was significantly lower than the score (64.0–76.7) reported by 30 normal individuals. Research in Taiwan (Sung and Yeh, 2007) showed that the scores for the four domains of quality of life were 10.2–12.0 among 181 outpatients with depression. The findings are close between the present study and the research in Taiwan based on the scores obtained, although the quality of life cannot be directly compared due to the differences in culture and sampling methods. Among a number of factors that affect the quality of life of patients with depression, the severity of depressive symptoms is

one of the important determinants. Nuevo et al. (2010) found that there was no significant relationship between quality of life and the severity of depressive symptoms. However, he believes that the significant relationships were distorted by the inappropriate severity grading of the ICD-10. Several studies (Sung and Yeh, 2007; Chan et al., 2009; Jung et al., 2012) found that the severer the depressive symptoms, the poorer the quality of life. The present study showed that the overall quality of life of first-visit patients was lower than that of non-first-visit patients. In general, severe symptoms usually push the patients (first-visit) to seek medical attention, while with non-first-visit patients, their symptoms have improved after a period of medical treatment. Therefore, the findings of differences in quality of life between first and non-first-visit patients support the relationships between quality of life and the severity of depressive symptoms, although the severity of symptoms was not assessed in the present study. In addition to severity, medication also determines the quality of life of patients with depression. Ishak et al. (2011b) examined the effects of antidepressants on quality of life during 1984–2010 between treatment and control groups and found that patients’ quality of life was significantly improved after receiving drug treatment including SSRIs, SNRIs, and norepinephrine–dopamine reuptake inhibitors. More effective improvement in quality of life was found among patients with severe depressive symptoms. The present study examined medication use at clinic visits. Overall, quality of life was better among medication users than among medication non-users, and differences in quality of life remained between different medication user groups. Based on the four domains and the general quality of life scores, the influences of types of medication on quality of life can be summarized in the following order: NaSSA ≥ concomitant ≥ SSRIs ≥ the others ≥ SNRIs ≥ no medication. More research has compared the effects of antidepressants and placebo (Demyttenaere et al., 2008; Kornstein et al.,

Q. Zeng et al. / Journal of Affective Disorders 150 (2013) 513–521

2006) on quality of life, while few studies compared the effects of different antidepressants on quality of life. For example, Versiani et al. (2005) found that mirtazapine (NaSSA) was more effective than fluoxetine (SSRI) for severely depressed patients. Moreover, mirtazapine users’ sleeping was significantly more improved than that of fluoxetine users, though significant differences in quality of life were not found between the two types of medications. Lonnqvist et al. (1994) found that moclobemide was more effective than fluoxetine in improving depressive symptoms and quality of life. There is insufficient evidence from the research on the effects of medication on quality of life. However, improvement of quality of life was shown in the early stage of drug treatment. Quality of life is correlated with depressive symptoms. That is, the higher the degree of symptom improvement, the better the quality of life. Furthermore, improvement of quality of life is reflected in psychological health, as well as in the other domains. The present study showed that not only psychological health but also the other aspects of quality of life, including general quality of life, health status, physical health, social relationships, environment, two additional items measuring Chinese characteristics, and the general self-assessment scores were significantly better in the medication user groups than in the medication non-user group, which is consistent with the literature. Though only the influences of severity of depression and medication were examined in the present study, a great number of other determinants have been found in similar studies that affect quality of life in populations with depression. For example, studies have shown that somatic symptoms, education and occupational status, number of previous depressions and current episode duration, suicidal tendency, and drug addiction, are associated with HRQol outcomes (Sobocki et al., 2007; Reed et al., 2009; Winter et al., 2012). With population aging, the world is paying more attention to aging-related diseases. Not surprisingly, a high prevalence of depression is found among the elderly with chronic illnesses or disabilities. The findings of Winter et al. (2011) indicate that depression is one of the determinants of reduced HRQol in the elderly with neurodegenerative diseases, and as age increases, HRQol decreases. Studies provide evidence and caution in relation to the necessity of early prevention and intervention for depression.

5. Limitations The present study was a natural observational investigation involving outpatients with depression regardless of age, patients’ visit (first or non-first), and medication use. Moreover, the study used continuous data collection within outpatient settings instead of a random sampling method. Thus, the findings may not reflect the full perspective on the quality of life of outpatients with depression in different stages and different courses of disease. Since the study was cross-sectional, causal relationships among visit status, medication, and quality of life cannot be determined. The depressive disorder was assessed by the psychiatrists based on the CCMD-3 criteria. Unfortunately, due to the operability and feasibility of administering such a large sample in a limited time at many study sites, information on the severity of depression was not provided in the case report form, which could induce a selection bias. Generally, there is a relatively low possibility for patients with mild depression or at an early stage of depression to visit a psychiatrist because of the associated stigma, particularly among Chinese. Therefore, the number of patients with severe depressive symptoms may be higher in the present study. However, the findings from this most “natural” observational method may better reflect the “real world” of quality of life among outpatients with depression. Furthermore, the findings of the present study were similar to those from other studies. Future

519

research could use prospective designs to explore causal relationships with more objective measures.

Name

Beijing Anding Hospital Peking University Sixth Hospital The Third People’s Hospital of Foshan, Foshan Mental Mental Health Center The First Affiliated Hospital of Fujian Medical University Huashan Hospital, Fudan University Guangdong General Hospital Guangzhou Brain Hospital Center of the First Affiliated Hospital of Harbin Medical University Henan Provincial Mental Health Center Hubei General Hospital Hu Zhou Third People’s Hospital Beijing Huilongguan Hospital The First Affiliated Hospital of Nanchang University Nanjing Brain Hospital, affiliated to Nanjing Medical University Ningbo Kangning Hospital Shandong Provincial Hospital Shanghai Mental Health Center Tongji Hospital, affiliated to Shanghai Tongji University Corning Hospital, Shenzhen City Beijing Chao-yang Hospital West China Hospital, Sichuan University Tianjin Anding Hospital

n (%)

City

Province/ municipality

1090 (5.5)

Beijing

Beijing

2191 (11.0)

Beijing

Beijing

389 (1.9)

Foshan

Guangdong

70 (0.4)

Fuzhou

Fujian

Shanghai

Shanghai

1218 (6.1) 720 (3.6)

Guangzhou Guangdong

1023 (5.1)

Guangzhou Guangdong

1097 (5.5)

Harbin

Heilongjiang

Xinxiang

Henan

29 (0.1)

Wuhan

Hubei

717 (3.6)

Huzhou

Zhejiang

1318 (6.6)

Beijing

Beijing

1107 (5.5)

Nanchang

Jiangxi

1189 (5.9)

Nanjing

Jiangsu

269 (1.3)

Ningbo

Zhejiang

660 (3.3)

Jinan

Shandong

1543 (7.7)

Shanghai

Shanghai

1017 (5.1)

Shanghai

Shanghai

138 (0.7)

Shenzhen

Guangdong

904( 4.5)

Beijing

Beijing

123 (0.6)

9 (0.0004) Chengdu

45 (0.2)

Tianjin

Sichuan

Tianjin

520

75 The First affiliated Hospital of Wenzhou Medical College Xi Jing Hospital 19 Yangzhou 774 Wutaishan Hospital 164 The Second Affiliated Hospital of Zhejiang University School of Medicine Chinese PLA 14 General Hospital Shengjing Hospital 528 of China Medical University 1396 The Second Xiangya Hospital of Central South University 148 The First Affiliated Hospital of Chongqing Medical University Total 19984

Q. Zeng et al. / Journal of Affective Disorders 150 (2013) 513–521

(0.4)

Wenzhou

Zhejiang

(0.1) (3.9)

Xi’an Yangzhou

Shaanxi Jiangsu

(0.8)

Hangzhou

Zhejiang

(0.1)

Beijing

Beijing

(2.6)

Shenyang

Liaoning

(7.0)

Changsha

Hunan

(0.7)

Chongqing Chongqing

(100.0)

Role of funding source This study was initiated and sponsored by the Chinese Medical Doctor Association (CMDA), with a funding from Hangzhou MSD Pharmaceutical Company.

Conflict of interest The authors declare that they have no conflict of interests.

Acknowledgements The authors would like to gratefully acknowledge colleagues from the 30 study sites for their support and assistance in this survey: Beijing Anding Hospital, Beijing (Dr. Wang Gang); Peking University Sixth Hospital, Beijing (Dr. Yu Xin); The Third People’s Hospital of Foshan, Foshan Mental Mental Health Center, Foshan, Guangdong (Dr. Li Xuesong); The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian (Dr. Zheng Jianmin); Huashan Hospital, Fudan University, Shanghai (Dr. Shi Shenxun); Guangdong General Hospital, Guangzhou, Guangdong (Dr. Jia Fujun); Guangzhou Brain Hospital, Guangzhou, Guangdong (Dr. Ning Yuping); Center of the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang (Dr. Hu Jian); Henan Provincial Mental Health Center, Xinxiang, Henan (Dr. Chen Zuoming); Hubei General Hospital, Wuhan, Hubei (Dr. Wang Xiaoping); Hu Zhou Third People’s Hospital, Huzhou, Zhejiang (Dr. Qian Mincai); Beijing Huilongguan Hospital, Beijing (Dr. Yang Fude); The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi (Dr. Yuan Yefeng); Nanjing Brain Hospital, affiliated to Nanjing Medical University, Nanjing, Jiangsu (Dr. Zhang Ning); Ningbo Kangning Hospital, Ningbo, Zhejiang (Dr. Chen Zhongming); Shandong Provincial Hospital, Jinan, Shandon (Dr. Jiao Zhian); Shanghai Mental Health Center, Shanghai (Dr. Xu Yifeng); Tongji Hospital, affiliated to Shanghai Tongji University, Shanghai (Dr. Lu Zheng); Corning Hospital, Shenzhen City, Shenzhen, Guangdong (Dr. Liu Tiebang); Beijing Chao-yang Hospital, Beijing (Dr. Hu Yongdong); West China Hospital, Sichuan University, Sichuan (Dr. Li Tao); Tianjin Anding Hospital, Tianjin (Dr. Tian Hongjun); The First affiliated Hospital of Wenzhou Medical College, Wenzhou, Zhejiang (Dr. Zhao Yongzhong); Xi Jing Hospital, Xi’an, Shaanxi (Dr. Tan Qingrong); Yangzhou Wutaishan Hospital, Yangzhou, Jiangsu (Dr. Gu Xiaoyang); The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang (Dr. Li Huichun); Chinese PLA General Hospital, Beijing (Dr. Lang Senyang); Shengjing Hospital of China Medical University, Shenyang, Liaoning (Dr. Wang Xumei); The Second Xiangya Hospital of Central South University, Changsha, Hunan (Dr. Li Lingjiang); The First Affiliated Hospital of Chongqing Medical University, Chongqing (Dr. Meng Huaqing). The investigators are also particularly indebted to the patients who participated in this study.

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