Psychological Factors that Link Socioeconomic Status to Depression/Anxiety in Patients with Systemic Lupus Erythematosus

Azizoddin, Desiree R.; Zamora-Racaza, Geraldine; Ormseth, Sarah R.; Sumner, Lekeisha A.; Cost, Chelsie; Ayeroff, Julia R.; Weisman, Michael H.; Nicassio, Perry M.

doi:10.1007/s10880-017-9505-z

Cited by 38 publications

(32 citation statements)

References 54 publications

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“…These results were supported by previous studies (23)(24)(25). Also, socioeconomic status was significantly related to the depression, which is consistent with several previous pieces of evidence, including studies by Freeman et al (26), Domenech-Abella et al (27), Hoebel et al (28), and Azizoddin et al (29).…”

Section: Discussionsupporting

confidence: 90%

Spatial Modeling of Depression and Its Related Factors Using a Spatial Generalized Linear Mixed Model in Mashhad, Iran: A Cross-Sectional Study

et al. 2019

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Background: Depression is one of the most common mental disorders and it has the third rank of the cause of disability and has been considered to increase the years of life with disability in Iran. Objectives: The purpose of this study was to map the geographical distribution and find hot spots of depression and its relation to demographic and socioeconomic factors in Mashhad. Methods: A population-based cross-sectional study was conducted in Mashhad in 2010. In this study, 9704 individuals aged 35 to 65 years old were evaluated using Beck's depression inventory-II. A generalized linear mixed model with a logit link was fitted for the spatial modeling of depression. R and GIS software was used for spatial analysis and disease mapping, respectively. Results: The prevalence of depression was different in geographical areas, ranging from 13.29% to 26.67%. The spatial correlation in the prevalence of depression was significant. The fitted spatial model showed that the spatial adjusted associations between gender (P < 0.001), marital status (P < 0.001), socioeconomic status (P < 0.001), and depression were significant. Conclusions: The significant spatial correlation shows that depression is spatially contagious and it is important to find its hot spots in the population. Thus developing health policy for prevention, early diagnostics, and treatment programs is preferred in these resource-limited areas.

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Section: Discussionsupporting

confidence: 90%

Spatial Modeling of Depression and Its Related Factors Using a Spatial Generalized Linear Mixed Model in Mashhad, Iran: A Cross-Sectional Study

et al. 2019

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“…In 1 previous longitudinal analysis, the data failed to demonstrate the contribution of baseline depression to fatigue at follow‐up (18). To understand predictors of depressed mood that may better explain fatigue, Azizoddin et al (42) examined 124 lupus patients and identified the fact that the relationships between socioeconomic status and depressed mood and anxiety were mediated by stress, social support, and low self‐esteem, above and beyond disease factors. Such findings illuminate the strength of psychological factors and their impact on depressive symptomatology and consequently fatigue, as seen in this study.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal Study of Fatigue, Stress, and Depression: Role of Reduction in Stress Toward Improvement in Fatigue

Azizoddin

Jolly

Arora

et al. 2020

Arthritis Care & Research

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Objective Fatigue is common among individuals with systemic lupus erythematosus (SLE), but the causes are not well understood. Our objective was to examine perceived stress and depressive symptoms as predictors of fatigue in SLE. Methods Data from 2 years of the Lupus Outcomes Study (n = 650 patients), obtained through annual structured interviews, were used. Fatigue was measured with the Short Form 36 (SF‐36) vitality scale along with a variety of self‐report measures of disease, depression, and stress. Multivariate linear regression models examined predictors of changes in fatigue. Model 1 tested the association of time 1 (T1) depression with time 2 (T2) fatigue; model 2 added T1 perceived stress to model 1, and final models added T1‐to‐T2 decrease in stress. All analyses controlled for T1 fatigue, age, sex, self‐report of fibromyalgia, pain, and SLE duration, activity, and damage. Results Mean ± SD age was 51 ± 12 years, 92% of participants were women, and 68% were white. The mean ± SD SF‐36 fatigue score was 55 ± 24. T1 depression significantly predicted T2 fatigue. When T1 stress was added, stress (β = 1.7 [95% confidence interval (95% CI) 1.1, 2.2]; P < 0.0001) significantly predicted T2 fatigue, but depression was no longer significant. The addition of T1‐to‐T2 decrease in stress was associated with a clinically meaningful decline in fatigue (β = –11.8 [95% CI –15.6, –8.9]; P < 0.0001). Conclusion While depressive symptoms initially predicted subsequent fatigue, the effects were mediated by stress. A decrease in stress, in addition, was associated with a clinically meaningful decrease in fatigue. These results suggest that perceived stress plays an important role in SLE fatigue and may be an important focus of interventions for fatigue.

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“…The calculation of scores was based on previous studies. 14,15,22 The total depression subscale was divided into normal (0-9), mild depression (10)(11)(12), moderate depression (13)(14)(15)(16)(17)(18)(19)(20), severe depression (21-27) and extremely severe depression symptoms (28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42). The total anxiety subscale score was divided into normal (0-6), mild anxiety (7-9), moderate anxiety (10)(11)(12)(13)(14), severe anxiety (15)(16)(17)(18)(19) and extremely severe anxiety symptoms (20-42).…”

Section: Measures and Outcomesmentioning

confidence: 99%

“…[25][26][27][28] The 22-item IES-R questionnaire was composed of three subscales that measured mean avoidance, intrusion and hyperarousal. The total IES-R score was multiplied by two and interpreted as normal (0-23), mild psychological impact (24-32), moderate psychological impact (33)(34)(35)(36) and severe psychological impact (>37). Both the DASS-21 and IES-R tools have been previously used for their psychometric properties in research related to the COVID-19 outbreak.…”

Section: Measures and Outcomesmentioning

confidence: 99%

<p>Psychological State and Associated Factors During the 2019 Coronavirus Disease (COVID-19) Pandemic Among Filipinos with Rheumatoid Arthritis or Systemic Lupus Erythematosus</p>

Tee¹,

Salido²,

Reyes³

et al. 2020

OARRR

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Background: Patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are perceived to be more vulnerable to worse COVID-19 infection outcome. Furthermore, severe shortage in hydroxychloroquine supply was experienced. Objective: We presented the psychological responses of Filipino SLE and RA patients to the COVID-19 pandemic and shortage of hydroxychloroquine supply. Methods: A total of 512 completed online surveys from SLE and RA patients were gathered from May 19 to 26, 2020. The online survey collected data on socio-demographics, health status, contact history, health service utilization, use of hydroxychloroquine, COVID-19 knowledge and concerns, precautionary measures, information needs, the validated Impact of Events Scale-Revised (IES-R) and Depression, Anxiety and Stress Scales (DASS-21) ratings. Results: The psychological impact of COVID-19 outbreak was at least moderate in 20%. The mean IES-R score was higher among SLE (22.34, SD=14.39) than RA (18.85, SD=13.24) patients. Stress, anxiety and depression were moderate to severe in 12.3%, 38.7%, and 27.7% of respondents. The mean stress subscale score was 10.11 (SD=7.95), mean anxiety subscale score was 6.79 (SD=6.57) and mean depression subscale score was 9.03 (SD=8.77). The risk factors for adverse mental health during the COVID-19 pandemic include the presence of comorbidity of hypertension and asthma; being a healthcare worker; and presence of specific symptoms of myalgia, cough, breathing difficulty, dizziness and sore throat. The protective factors for mental health during the pandemic include satisfaction with available health information and wearing of face masks. Conclusion: In the third month of the pandemic in the Philippines, 20% of the respondents with lupus and RA experienced moderate to severe psychological impact. There was moderate to severe anxiety in 38.7% and moderate to severe depression in 27%. Identification of factors that affect mental health in lupus and RA is useful in implementation of effective psychological support strategies.

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Psychological Factors that Link Socioeconomic Status to Depression/Anxiety in Patients with Systemic Lupus Erythematosus

Cited by 38 publications

References 54 publications

Spatial Modeling of Depression and Its Related Factors Using a Spatial Generalized Linear Mixed Model in Mashhad, Iran: A Cross-Sectional Study

Spatial Modeling of Depression and Its Related Factors Using a Spatial Generalized Linear Mixed Model in Mashhad, Iran: A Cross-Sectional Study

Longitudinal Study of Fatigue, Stress, and Depression: Role of Reduction in Stress Toward Improvement in Fatigue

<p>Psychological State and Associated Factors During the 2019 Coronavirus Disease (COVID-19) Pandemic Among Filipinos with Rheumatoid Arthritis or Systemic Lupus Erythematosus</p>

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