Literature DB >> 31446684

Prevalence of Depression in Ankylosing Spondylitis: A Systematic Review and Meta-Analysis.

Lijuan Zhang1, Yaping Wu2, Shiguang Liu1, Weiyi Zhu3.   

Abstract

The aim of this study was to provide a summary estimate of depression prevalence among people with ankylosing spondylitis (AS) in comparison to those without AS. A systematic literature search was conducted using PubMed, Embase, PsycINFO, Web of Science, the Cochrane database library, China National Knowledge Infrastructure, and Wanfang Database from their inception to December 2016. The results showed that thirty-one eligible studies involving 8,106 patients were analyzed. Fifteen methods of defining depression were reported. The overall pooled prevalence of depression was 35% (95% CI, 28-43%), with high between-study heterogeneity (I2=98.8%, p<0.001). The relative risk of depression among people with AS was 1.76 (95% CI: 1.21-2.55, eight studies, n=3,006) compared with people without AS. The depression score [standardized mean difference (SMD)=0.43, 95% CI: 0.19-0.67, seven studies, n=549] was higher in AS patients than in controls. The main influence on depression prevalence was the sample size and country of origin. In conclusion, one-third of people with AS experience symptoms of depression. Depression was more prevalent in AS patients than in controls. Further research is needed to identify effective strategies for preventing and treating depression among AS patients.

Entities:  

Keywords:  Ankylosing spondylitis; Depression; Meta-analysis; Systematic review

Year:  2019        PMID: 31446684      PMCID: PMC6710421          DOI: 10.30773/pi.2019.06.05

Source DB:  PubMed          Journal:  Psychiatry Investig        ISSN: 1738-3684            Impact factor:   2.505


INTRODUCTION

Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease with significant effects on patients’ physical function and psychological status [1,2]. It has become increasingly clear that psychological distress, such as depression or anxiety, is common in patients with including osteoarthritis [3], lupus [4] and rheumatic arthritis [5,6]. Individuals with AS are more likely to be depressed than healthy individuals [7]. Depression is a chronic, prevalent condition, and is a leading cause of disability, affecting at least 120 million people worldwide [8]. In a population based study, doctor-diagnosed depression was found to be increased 1.81 and 1.49 fold respectively in women and men with AS [9]. It may be explained that AS is related to inflammation of depression because it is an inflammatory disease. Depressed AS patients tended to have poor long-term outcomes, including increased disease activity [10,11], fatigue [12], decreased functionality [13], sleep disturbances [14], impaired quality of life [15], and high medical costs [16]. However, estimates of the prevalence of depression in AS patients varied across studies, from 3% [17] to 66% [18]. Such discrepancy could be explained by the differences in time frames when these studies were performed, study quality, or tools used for assessing depression. It is important for rheumatologists to establish reliable estimate of depression prevalence, in order to prevent, treat, and identify causes of depression in people with AS. Recent reviews have suggested that depression was highly prevalent among people with rheumatoid arthritis [19], osteoarthritis [3], and systemic lupus erythematosus [20]. Another systematic review found that the prevalence of neuropsychiatric damage in chronic rheumatic diseases such as lupus has been significantly increasing over the past 5 decades [21]. This finding is not surprising due to reduction in white matter and grey matter volumes in the very early stage of lupus [22]. As yet no systematic review has provided pooled prevalence estimates of depression in AS. Our goal was to fill this gap. We aimed to 1) describe the pooled prevalence of depression in people with AS; 2) compare depression prevalence and score in AS patients versus healthy controls; 3) explore the influence of study characteristics on prevalence estimates.

METHODS

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard [23] and followed a predetermined registered protocol (PROSPERO: 42016052590).

Search strategy

The systematic literature search was conducted by two investigators independently through the PubMed, Embase, PsycINFO, Web of Science, Cochrane database library, China National Knowledge Infrastructure (CNKI), and Wanfang Database for pertinent studies published in English or Chinese from their inception to December 2016. The computer-based searches combined terms related to AS patients [(depress* or depress* disorder$ or affective disorder$ or mood disorder$ or adjustment disorder$ or affective symptom$ or dysthymi*) AND (Ankylosing spondylitis or AS)] (Supplementary Material 1 in the online-only Data Supplement). The search was restricted to studies in humans. In addition, the reference lists of all identified relevant publications were reviewed. Finally, where published information was unclear or inadequate, we contacted the corresponding authors for more information.

Inclusion and exclusion criteria

Studies were eligible if they met the following criteria: 1) observational studies (cross-sectional and prospective studies) and baseline data of randomized controlled trials with or without a comparison group without AS; 2) depression was measured by self-reported symptom scales, physician/clinician diagnosis, or structured clinical diagnostic interview. Table 1 presented a full list of the eligible methods of detecting depression, alongside the numbers of participants assessed.
Table 1.

Overview of prevalence studies of depression in AS patients

Study IDCountryParticipantsMen, %Age, mean±SD/median (range), yearsDisease duration, mean±SD/median (range), yearsCriteria for detection of depression (cutoff)Prevalence, %NOS
Aissaoui 2012Morocco11068.238.52±12.629 (0–40)HADS (≥8)55.52
Altan 2003NS63NSNSNSHADS (≥8)33.31
Anyfanti 2012Greece4468.8NSNSZung SDS (≥50)18.21
Arisoy 2013Turkey988.939.4±10.110.6±7.6HADS (≥7)332
Aydin 2016Turkey3762.334.67±7.907.16±2.49HADS (≥8)48.53
Baysal 2011Turkey24386.434.65±10.366.02±6.60HADS (≥7)39.83
Cakar 2007Turkey5210032.85±12.119.09±7.3621 Item-BDI (≥14/25)50/13.52
Cooksey 2015UK34877.056.0±13.022.0±15.0HADS (≥11)7.54
Demir 2013Turkey22039.34±6.283.3±2.621 Item-BDI (≥14)45.52
Dhakad 2015India10010034.42±9.784.84±0.06HADS (≥8)662
Durmus 2015Turkey8063.839.33±10.9810.88±10.0821 Item-BDI (>17)22.52
Ertenli 2012Turkey1681.236.4 ±10.312.8±9.5HADS (≥8)43.82
Ersözlü-Bozkirli 2015Turkey2979.334.4±10.34.1±6.221 Item-BDI (≥30)37.92
Fallahi 2014Iran16379.137.74±9.8814.49±8.47Structured interview29.42
Günaydin 2009Turkey6283.939.6±10.310.3±7.9Zung SDS (≥50)27.42
Hakkou 2011Morocco11068.238.5±12.610.3±8.1HADS (≥8)55.52
Healey 2009UK61271.650.8±12.210.3±8.1HADS (≥8)32.45
Hyphantis 2013Greece5585.542.9±10.915.3±11.5PHQ-9 (≥5/10)40.7/14.82
Jiang 2015China68380.427.33±8.676.47±6.47Zung SDS (NS)644
Li 2012China31474.527.65±8.346.07±4.90Zung SDS (≥50)41.44
Lian 2003China6078.036.0±12.0>5 years (68%)Zung SDS (≥41)43.32
Martindale 2006UK8983.150 (18–77)18 (12–29)HADS (≥11)12.43
Meesters 2014Sweden1,7386554.5±14.3NSStructured interview, ICD-10103
Rodríguez-Lozano 2012Spain1907548.4±11.720.2±11HADS (≥11)112
Rostom 2013Morocco11010038.5±12.69 (0–40)HADS (≥8)55.53
Schneeberger 2015Argentina6489.144 (33–53)17 (10.3–25)CES-D (≥16)39.12
Shen 2016China2,33164.936.50 (27.25–48.18)NSStructured interview, ICD-93.13
Xu 2016China10375.732.9±10.7NSZung SDS (≥53)36.92

NS: not stated, ID: identification, SD: standard deviation, AS: ankylosing spondylitis, HADS: Hospital Anxiety and Depression Scale, SDS: Self-rating Depression Scale, BDI: Beck Depression Inventory, PHQ: Patient Health Questionnaire, ICD: International Classification of Diseases, CES-D: Centre for Epidemiological Studies Depression Scale, NOS: Newcastle-Ottawa Scale

Studies were excluded if: 1) the study was not published as the full reports, such as case reports, commentaries, conference abstracts and letters to editors; 2) the study had a retrospective design; and 3) participants with depression at baseline were not excluded for the analysis.

Data extraction and quality assessment

Two trained investigators independently extracted data and assess quality of the studies included in this meta-analysis. Any disagreements in data extraction and quality assessment were resolved through discussion between the two investigators or adjudication with a third reviewer. We used a standardized form to record data on the authors, year of publication, country of study, participants, percentage of male participants, average age of participants, mean disease duration, criteria for detection of depression, and reported the prevalence or score of depression. If duplicate publications from the same study were identified, we would include the result with the largest number of individuals from the study. Wherever possible, we extracted the number affected and not affected by depression in each sample (using the authors’ cut-off points for each outcome measure). If this was not available, we extracted the mean and standard deviation of the depression assessment scale. The investigators independently fulfilled the quality assessment using a modified version of the Newcastle-Ottawa Scale (NOS) in line with previous study [24]. Studies were judged to be at low risk of bias (≥3 points) or high risk of bias (<3 points).

Outcome measures

The outcomes of interest were major depression diagnosed with a structured clinical assessment [e.g., International Classification of Diseases (ICD)-10] or depression assessed with a validated assessment tool or screening measure [e.g., the Hospital Anxiety and Depression Scale (HADS), Beck Depression Inventory (BDI)].

Statistical analyses

Three analyses were undertaken. First, we pooled studies reporting the prevalence of depression in the AS sample using a random-effects models [25,26]. Second, we used a pooled relative risk (RR) analysis with random-effect model. Third, we conducted a pooled standardized mean difference (SMD) analysis to investigate differences between those with and without AS. Statistical heterogeneity among studies was evaluated with I2 statistics with the values of 25%, 50%, and 75% respectively denoted cut-off points for low, moderate and high degrees of heterogeneity [27]. The influence of individual studies on the overall prevalence estimate was explored by serially excluding each study in a sensitivity analysis. Subgroup analyses were planned by overall study quality, sample size, country of origin and publication year to explore the sources of potential heterogeneity. Finally, we used Pearson’s and Spearman’s correlation analyses to assess the association between variables and prevalence of depression in people with AS. Potential publication bias was evaluated with a funnel plot [28] and the Egger’s test [29]. Statistical analyses were all conducted on Statistical analyses were all conducted on STATA version 12.0 (Stata Corp, College Station, TX, USA).

RESULTS

Search results

A total of 598 citations were identified. After removal of duplicates, titles and then abstracts were screened for potential eligibility. From this, 59 were potentially eligible and considered in the full-text review. Twenty-eight articles were excluded; thus, 31 records met the eligibility criteria and were included (Figure 1), and a full reference list was shown in Supplementary Material 2 (in the online-only Data Supplement). Inter-observer agreement (κ) between two investigators was 0.89.
Figure 1.

Search results and study selection.

Study characteristics

Table 1 and 2 presented the characteristics of the included studies. Thirty-one eligible studies consisted of 8,106 patients were reported. Nineteen studies were conducted in Asia, 7 studies in Europe, 3 studies in Africa, and 1 study in South America. The mean age was 39.2 years, and the mean percentage of males represented in the sample was 75.9%. In addition, the mean number of participants per study was 261, and the mean disease duration was 10.64 years. Table 3 described the methods defined depression and the frequency of their use. Depression was assessed in 15 different ways. Thirteen studies assessed for depression using the HADS; three different cut-off points were presented, the most commonly used being 8. Five studies assessed for depression using the 21 Item-BDI, with four different thresholds were presented in the articles. Six used the Zung Self-rating Depression Scale (SDS), and three used other screening tools. Three assessed for depression using structured interview (e.g., ICD). Supplementary Table 1 (in the online-only Data Supplement) summarized the quality assessment using a modified version of the NOS, which indicated that 1 study received 5 points, 3 studies received 4 points, 6 studies received 3 points, 18 studies received 2 points, and 3 studies received 1 point.
Table 2.

Overview of studies of depression in AS patients and control group

Study IDCountryStudy designParticipants% of male in AS group% of male in control groupMean/median age (years) in AS group±SD (range)Mean/median age (years) in control group±SD (range)Mean disease duration of AS (years)±SDDepression measuresNOS
Altan 2003NSCase control63 AS and 60 controlNSNSNSNSNSHADS1
Baysal 2011TurkeyCross-sectional243 AS and 118 control86.478.834.65±10.3636.53±9.266.02±6.60HADS3
Demir 2013TurkeyCase control22 AS and 27 control0039.34±6.2837.58±9.583.3±2.621 Item-BDI2
Dhakad 2015IndiaCase control100 AS and 100 control10010034.42±9.7836.39±8.074.84±0.06HADS2
Dincer 2007TurkeyCase control68 AS and 45 control10010032.9±11.030.1±6.24NS21 Item-BDI1
Durmus 2015TurkeyCase control80 AS and 80 control63.871.239.33±10.9836.41±10.8410.88±10.0821 Item-BDI2
Ortancil 2010TurkeyCase control29 AS and 20 control696042.0±9.738.2±12.59.4±7.7SCL-90-R2
Ozkorumak 2011TurkeyCase control43 AS and 43 control10010036.25±8.7636.53±6.547.51±7.2221 Item-BDI2
Schneeberger 2015ArgentinaCase control64 AS and 95 control89.189.544 (33–53)40 (32–53)17 (10.3–25)CES-D2
Shen 2016ChinaCohort2,331 AS and 9324 control64.964.936.50 (27.25–48.18)36.50 (27.25–48.18)NSICD-93
Xu 2016ChinaCross-sectional103 AS and 121 control75.760.332.9±10.737.0±12.5NSZung SDS2

NS: not stated, ID: identification, SD: standard deviation, AS: ankylosing spondylitis, HADS: Hospital Anxiety and Depression Scale, BDI: Beck Depression Inventory, SCL-90-R: Symptoms Checklist-90-Revised, CES-D: Centre for Epidemiological Studies Depression Scale, ICD: International Classification of Diseases, SDS: Self-rating Depression Scale, NOS: Newcastle-Ottawa Scale

Table 3.

Methods of detecting depression and summary of prevalence and heterogeneity findings

ToolDefinition/cutoffNo. of studiesNo. of participantsPrevalence, % (95% CI)Heterogeneity I2, %
HADS≥7225240 (34–46)0
≥881,15842 (39–45)91.1
≥1136279 (6–12)29.6
21 Item-BDI≥1427449 (34–60)0
>1718022 (13–32)-
≥2515214 (4–23)-
≥3012938 (20–56)-
Zung SDS>4116043 (31–56)-
≥50342030 (15–44)87.0
≥53110337 (28–46)-
NS168364 (60–68)-
Structured interview (e.g., ICD)34,23213 (6–20)98.4
 CES-D≥1616439 (27–51)-
 PHQ-9≥515541 (28–54)-
≥1015515 (5–24)-

NS: not stated, HADS: Hospital Anxiety and Depression Scale, BDI: Beck Depression Inventory, SDS: Self-rating Depression Scale, ICD: International Classification of Diseases, CES-D: Centre for Epidemiological Studies Depression Scale, PHQ: Patient Health Questionnaire

Prevalence of depression among AS patients

Prevalence estimates of depression varied from 3% to 66% in individual studies (Table 1). The overall pooled prevalence of depression was 35% (95% CI, 28–43%), with high betweenstudy heterogeneity (I2=98.8%, p<0.001) (Figure 2). Table 3 presented the summary of meta-analyses and heterogeneity assessments. Prevalence estimates ranged from 9% (95% CI, 6–12%, I2=29.6%) according to the Hospital Anxiety and Depression Scale with thresholds of 11% to 49% (95% CI, 34–60%, I2=0%) for the 21-Item Beck Depression Inventory with a cutoff of 14 or more. Prevalence of major depressive disorder to be 13% (95% CI, 6–20%) according to the structured interview, with high heterogeneity (I2=98.4%).
Figure 2.

Prevalence of depression in ankylosing spondylitis patients.

Depression in AS versus non-AS cohorts

Eight studies included data on the prevalence estimates of depression for people with AS compared with those without AS. A pooled RR of 1.76 (95% CI: 1.21–2.55, n=3006) (Figure 3). Seven studies (n=549) presented data comparing depression scores for people with AS compared with those without AS. The depression score (SMD=0.43, 95% CI: 0.19–0.67) was higher in AS patients than in controls (Figure 4).
Figure 3.

Association between prevalence of depression in ankylosing spondylitis patients versus control group.

Figure 4.

Association between score of depression in ankylosing spondylitis patients versus control group.

Sensitivity and subgroup analyses

Table 4 showed the prevalence estimates of depression according to each sensitivity and subgroup analysis, in comparison with the primary analysis. Sensitivity analyses found that the exclusion of studies with less sample representativeness tended to decrease depression prevalence estimates according to structured interview. The pooled SMD tended to decrease in AS patients verse controls by exclusion of studies only using male sample. The subgroup analyses were conducted by sample size, overall quality, publication year, and country of origin. The results showed that studies with sample size <200 had higher depression prevalence estimates [52% (95% CI, 44–60%) vs. 42% (95% CI, 39–45%)] compared with primary analysis according to the HADS with thresholds of 8, and higher pooled RR [3.72 (95% CI, 1.33–10.38) vs. 1.48 (95% CI, 1.06–2.06)] in AS patients verse controls compared with the studies with sample size ≥200. When evaluated by Newcastle-Ottawa Scale (NOS), studies with lower total overall quality scores yielded higher depression estimates [52% (95% CI, 41–63%) vs. 45% (95% CI, 28–62%)] according to the HADS with thresholds of 8, and higher pooled RR [3.72 (95% CI, 1.33–10.38) vs. 1.48 (95% CI, 1.06–2.06)] compared with the studies with higher total overall quality scores. More recent publications and developing country tended to yield higher depression prevalence estimates according to the HADS with a cutoff of 8 or more. There was no particular trend or pattern in any other sensitivity analyses or subgroup analyses.
Table 4.

Impact of study characteristics on prevalence estimates for depression in AS: sensitivity and subgroup analyses

Prevalence estimates for depression in AS patients
Prevalence of depression in AS patients versus control group (RR)Scores of depression in AS patients versus control group (SMD)
HADS (≥8)HADS (≥11)Zung SDS (≥50)Structured interview
Primary analysis42 (39, 45)9 (6, 12)30 (15, 44)13 (6, 20)1.76 (1.21, 2.55)0.43 (0.19, 0.67)
I2=91.1%I2=29.6%I2=87.0%I2=98.4%I2=75.8%I2=64.7%
8 studies3 studies3 studies3 studies8 studies7 studies
1,158 AS627 AS420 AS4,232 AS3,006 AS/9,925 control549 AS/428 control
Sensitivity analyses
 Excluding studies with less sample representativeness---7 (0, 13)--
I2=98.6%
2 studies
4,069 AS
 Excluding studies with less comparable respondent and non-respondent comparability45 (28, 62)9 (5, 13)----
I2=91.3%I2=40.9%
3 studies2 studies
759 AS437 AS
 Excluding studies only using male sample45 (34, 56)9 (6, 12)30 (15, 44)13 (6, 20)1.85 (1.24, 2.75)0.28 (0.13, 0.43)
I2=87.0%I2=29.6%I2=87.0%I2=98.4%I2=64%I2=0%
6 studies3 studies3 studies3 studies7 studies5 studies
948 AS627 AS358 AS4,232 AS2,906 AS/9,825 control438 AS/340 control
Subgroup analyses
 Sample size
  <20052 (44, 60)11 (8, 15)23 (14, 32)-3.72 (1.33, 10.38)0.49 (0.22, 0.75)
I2=70.0%I2=0%I2=22.1%I2=87%I2=59%
7 studies2 studies2 studies6 studies6 studies
546 AS279 AS108 AS432 AS/483 control306 AS/310 control
  ≥200---7 (0, 13)1.48 (1.06, 2.06)-
I2=98.6%I2=40%
2 studies2 studies
4,069 AS2574 AS/9442 control
Overall quality
 <3 points (low quality)52 (41, 63)-23 (14, 32)-3.72 (1.33, 10.38)0.49 (0.22, 0.75)
I2=79.4%I2=22.1%I2=87%I2=59%
5 studies2 studies6 studies6 studies
399 AS108 AS432 AS/483 control306 AS/310 control
 ≥3 points (high quality)45 (28, 62)9 (5, 13)-7 (0, 13)1.48 (1.06, 2.06)-
I2=91.3%I2=40.9%I2=98.6%I2=40%
3 studies2 studies2 studies2 studies
759 AS437 AS4,069 AS2,574 AS/9,442 control
Publication year
 2000s32 (29, 32)-----
I2=0%
2 studies
675 AS
 2010–57 (52, 62)9 (5, 12)30 (8, 53)7 (0, 13)2.98 (1.47, 6.06)0.43 (0.15, 0.70)
I2=18.2%I2=41.7%I2=92.3%I2=98.6%I2=88%I2=70%
6 studies2 studies2 studies2 studies7 studies6 studies
483 AS538 AS358 AS4,069 AS2,943 AS/9,865 control481 AS/383 control
Country of origin
 Asia55 (41, 70)-35 (22, 49)16 (-10, 12)3.27 (1.41, 7.58)0.44 (0.15, 0.72)
I2=62.0%I2=79.7%I2=98.1%I2=90%I2=70%
3 studies2 studies2 studies6 studies6 studies
153 AS376 AS2,494 AS2,879 AS/9,770 control485 AS/333 control
 Europe-9 (6, 12)----
I2=29.6%
3 studies
627 AS
 Africa56 (50, 61)-----
I2=0%
3 studies
330 AS

AS: ankylosing spondylitis, HADS: Hospital Anxiety and Depression Scale, SDS: Self-rating Depression Scale, RR: relative risk, SMD: standardized mean difference

Associated study variables

Pearson’s and Spearman’s correlation analyses were employed to examine the relationship between variables including proportion of male participants, mean/medium age, mean/medium disease duration, sample size, representativeness, comparability, overall quality, country of origin, publication year, and the prevalence of depression. We found that small sample size (r=-0.45, p=0.016) and developing country (r=0.613, p=0.001) of the sample were significantly associated with increased depression prevalence (Table 5).
Table 5.

Pearson’s and Spearmen’s correlation between study characteristics and prevalence estimates

Study characteristicDepression prevalence estimate
No. of studiesrp
Male, %270.1530.445
Mean/medium age, year27-0.0540.790
Mean/medium disease duration, year27-0.0350.861
Sample size28-0.450[*]0.016
Representativeness28-0.2150.272
Comparability28-0.0660.737
Overall quality28-0.0550.780
Country of origin27-0.613[]0.001
Publication year280.1080.585

p<0.05,

p<0.01

Assessment of publication bias

According to the Egger’s test, assessment of publication bias suggested significant publication bias in studies reporting depression [Egger: bias=7.87 (95% CI: 4.77–10.97), p<0.001] (Supplementary Figure 1 in the online-only Data Supplement).

DISCUSSION

This is the first systematic review and meta-analysis on the prevalence of depression in AS. This study indicated that depression were more prevalent in AS patients than in controls. In this study, the pooled prevalence of depression in AS patients is 35% and higher than other chronic medical illnesses such as asthma (27%) [30], chronic obstructive lung disease (24.6%) [31], lupus (24%) [20] and rheumatoid arthritis (15%) [32]. This meta-analysis also revealed that small sample size and developing country of the studies conducted were significantly associated with increased depression prevalence, which might be explained that small studies often led to high prevalence estimates, and people with low socio-economic status (SES) in developing country was associated with increased susceptibility to depression [19]. Our sensitivity analyses indicated that depression prevalence estimates were relatively stable. Apart from the measurement tool used to ascertain depression, study quality and study population had impacts on the estimates detected. Our subgroup analyses found that variation in study sample size contributed importantly to the observed heterogeneity in the data. Studies with sample size <200 had higher depression estimates according to the HADS with a cutoff of 8 or more. Study quality might be a further explanation for the variance in prevalence estimates. Studies with lower total overall quality scores yielded higher depression estimates using the HADS with thresholds of 8. We used rigorous methods to conduct the review and a reproducible, structured approach to data extraction and synthesis. The gold standard method was diagnostic interviews using ICD criteria, which were often time consuming and expensive, therefore, it was not ideal for investigating patients in a busy hospital environment [33]. Alternatively, self-report screening tools might be used. Although such self-reported questionnaires were quick and easy to complete and cheaper to use than diagnostic interviews in psychiatric practices, the different scales and cutoffs used to define the presence or the absence of depression could vary [33]. Such nature would lead to information bias and methodological heterogeneity when combining these data in a meta-analysis. It indicated that the rheumatologists should report prevalence at conventional cut-points, and screen for depression among AS patients according to the social and cultural contexts of the rheumatologists and patients in clinical practice. However, this study still had some limitations. Firstly, a substantial amount of the heterogeneity among the studies remained unexplained by the variables examined. And there was inadequate data to conduct subgroup analyses according to variables of interest such as gender, disease duration and impact of age. A better understanding of social and cultural contexts of AS patients may help elucidate some of the root causes of depressive symptoms. Secondly, the data were derived from studies that used different designs and involved different groups of patients (e.g., different countries and years of publication), which might result in heterogeneity among the studies. Thirdly, the analysis relied on aggregated published data, which might result in potential publication bias.

CONCLUSIONS

One-third of people with AS experienced symptoms of depression. Depression was more prevalent in AS patients than in controls. Further research is needed to identify effective strategies for preventing and treating depression among AS patients.
  33 in total

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Review 2.  Treat-to-target in axial spondyloarthritis - what about physical function and activity?

Authors:  Jürgen Braun; Xenofon Baraliakos; Uta Kiltz
Journal:  Nat Rev Rheumatol       Date:  2021-07-26       Impact factor: 20.543

3.  Effects of traditional qigong exercise on ankylosing spondylitis: a protocol for systematic reviews and meta-analysis.

Authors:  Wei Liu; Yihua Fan; Renhong Wan; Longmei Zhao; Hang Lu; Rongjun Liao; Zhining Zhuang; Xiaoping Guo
Journal:  BMJ Open       Date:  2021-04-21       Impact factor: 2.692

4.  Efficacy of warming needle moxibustion in the treatment of ankylosing spondylitis: A protocol of a randomized controlled trial.

Authors:  Weizhong Ding; Shirong Chen; Xuexiang Shi; Yang Zhao
Journal:  Medicine (Baltimore)       Date:  2021-05-21       Impact factor: 1.817

5.  Depression and anxiety in individuals with axial spondyloarthritis and nonspecific low back pain who are interested in non-pharmacological therapy options: Cross-sectional study.

Authors:  Markéta Hušáková; Andrea Levitová; Daniela Domluvilová; Klára Dad'ová; Karel Pavelka
Journal:  Medicine (Baltimore)       Date:  2022-09-30       Impact factor: 1.817

  5 in total

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