Effect of comorbid depression on health-related quality of life of patients with chronic diseases: A South Korean nationwide study (2007–2015) (original) (raw)
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Psychiatry investigation, 2018
People with depression often suffer from comorbid, chronic physical diseases. Little is known about how demographic characteristics such as age and sex influence the prevalence of chronic physical diseases comorbid with depression. Therefore, this study aimed to explore the age and sex differences in the prevalence of diverse, chronic physical diseases comorbid with depression. This cross-sectional survey were conducted with the participants (n=45,598) of the Korean National Health and Nutrition Examination Survey (KNHANES). Using log-binomial regression, age adjusted prevalence ratios (APR) of chronic physical diseases of participants with depression and those without depression were estimated for each sex and age group. The APR of most chronic physical diseases were significantly higher among respondents with depression than those without depression. Chronic physical diseases that showed the highest APR were asthma in adult male respondents (APR=3.46) and adult female respondents ...
2007
Background Depression is an important public-health problem, and one of the leading causes of disease burden worldwide. Depression is often comorbid with other chronic diseases and can worsen their associated health outcomes. Few studies have explored the eff ect of depression, alone or as a comorbidity, on overall health status. Methods The WHO World Health Survey (WHS) studied adults aged 18 years and older to obtain data for health, health-related outcomes, and their determinants. Prevalence of depression in respondents based on ICD-10 criteria was estimated. Prevalence values for four chronic physical diseases-angina, arthritis, asthma, and diabetes-were also estimated using algorithms derived via a Diagnostic Item Probability Study. Mean health scores were constructed using factor analysis and compared across diff erent disease states and demographic variables. The relation of these disease states to mean health scores was determined through regression modelling. Findings Observations were available for 245 404 participants from 60 countries in all regions of the world. Overall, 1-year prevalence for ICD-10 depressive episode alone was 3•2% (95% CI 3•0-3•5); for angina 4•5% (4•3-4•8); for arthritis 4•1% (3•8-4•3); for asthma 3•3% (2•9-3•6); and for diabetes 2•0% (1•8-2•2). An average of between 9•3% and 23•0% of participants with one or more chronic physical disease had comorbid depression. This result was signifi cantly higher than the likelihood of having depression in the absence of a chronic physical disease (p<0•0001). After adjustment for socioeconomic factors and health conditions, depression had the largest eff ect on worsening mean health scores compared with the other chronic conditions. Consistently across countries and diff erent demographic characteristics, respondents with depression comorbid with one or more chronic diseases had the worst health scores of all the disease states. Interpretation Depression produces the greatest decrement in health compared with the chronic diseases angina, arthritis, asthma, and diabetes. The comorbid state of depression incrementally worsens health compared with depression alone, with any of the chronic diseases alone, and with any combination of chronic diseases without depression. These results indicate the urgency of addressing depression as a public-health priority to reduce disease burden and disability, and to improve the overall health of populations.
The effect of depression on quality of life of patients with type II diabetes mellitus
Depression and Anxiety, 2008
Diabetes mellitus (DM) is a frequently encountered metabolic disease with chronic features and involves numerous complications throughout its course, which causes severe restriction and disability in an individual's life. It has been reported that the incidence of depression is higher in diabetic patients and that diabetes is one of the risk factors in the development of depression. It has also been reported that co-morbid psychiatric disorders cause further deterioration in the quality of life in diabetic patients. The aim of this study was to investigate the effects of depression on the quality of life in type II DM patients. Sixty patients (30 females and 30 males) with current major depressive episode diagnosed according to DSM-IV criteria, and 48 type II DM patients (30 females and 18 males) without a major depressive episode (non-depressed group) were included in the study. All patients were evaluated with a semi-structured interview form to assess the clinical features of DM, Hamilton Rating Scale for Anxiety (HRSA), Hamilton Rating Scale for Depression (HRSD), and the Turkish version of The World Health Organization Quality of Life Assessment-Brief (WHOQOL-BREF). The HRSD and HRSA scores in the depressed group were 24.8774.83 and 21.0775.44, respectively, whereas those in the nondepressed group were 7.8373.92 and 6.8873.43, respectively. The physical health, psychological health, social relationship, environmental and social pressure domain, general health-related quality of life, overall quality of life, and WHOQOL-BREF total scores were found significantly lower in the depressed group than the non-depressed group. There were significant negative correlations between HRSD and HRSA scores and physical health, psychological health, social relationship, environmental and social pressure domain, general health-related quality of life, overall quality of life, and WHOQOL-BREF total scores. Furthermore, there were significant negative correlations between the HbA1c level and physical health, social relationship, environmental domain, social pressure domain, general health-related quality of life, overall quality of life, and WHOQOL-BREF total scores. However, there was a significant positive correlation between the level of education and physical health, psychological health, social relationship, environmental social pressure domain, overall quality of life, and WHOQOL-BREF total scores. There were significant negative correlations between social relationship domain score, and age and duration of illness. Our study demonstrates that the presence of depression in
The Gerontologist, 1999
We enrolled 543 elderly participants of a managed care organization in a cross-sectional study to test whether the association between self-rated physical health and clinically defined illness differs for persons who are not depressed compared with persons with minor or serious depression. Depression was measured with the Diagnostic Interview Schedule (DIS). Clinically defined illness was measured with the Chronic Disease Score (CDS), a pharmacy-based measure. Additional variables included age, sex, and selfreported pain and physical function. Self-rated physical health was associated with both minor and serious depression, independent of clinically defined illness; minor depression was no longer significant when self-reported pain and physical function were added to the model. A significant negative correlation between self-rated physical health and clinically defined illness was observed for minor and no depression, but no correlation was seen for serious depression. These results confirm the association between depression and selfrated physical health and emphasize that, for persons with serious depression, self-rated health provides a less accurate picture of clinically defined illness at both ends of the spectrum. Also, a diagnosis of minor depression should not forestall investigation of inconsistencies between patient report and clinical evidence.
Journal of Psychosomatic Research, 2013
Aim: To assess to what extent a high physical symptom count influences the effect of treatment for major depressive disorder (MDD), and whether or not actual comorbid medical conditions explain this relationship. Method: Secondary data-analysis on a cluster-randomized trial in primary care, comparing the effectiveness of collaborative care with care as usual (CAU). MDD was measured using the PHQ-9. The Physical Symptoms Questionnaire (PSQ) was filled out at baseline by 115 patients (77.2% of those who entered the trial). Multilevel logistic regression models were used to test whether a high physical symptom count predicted lack of response to treatment, adding interaction terms to test differential effects on collaborative care versus CAU. Results: A high physical symptom count negatively influenced the effect of both collaborative care and care as usual (no interaction). Specifically, a high physical symptom count predicted lack of response in both conditions at 3 (odds ratio=6.8), 6 (OR=4.1), and 9 months follow-up (OR=6.4). This was not explained by chronic physical illness. Conclusion: In this RCT, patients with MDD accompanied by a high physical symptom count benefited less from treatment for MDD in primary care, regardless of the type of treatment (either collaborative care or CAU). This was not explained by the presence of comorbid medical conditions. Further research is needed to improve treatment for MDD accompanied by a high physical symptom count, although collaborative care for depression is still more effective than CAU for this group of patients. Trial registration: Dutch trial register ISRCTN15266438.
Health and Quality of Life Outcomes, 2012
Background: In the US, approximately 53% of adults have at least one chronic condition. Comorbid physical and mental health conditions often have an incremental negative impact on health-related quality of life (HRQL). Primary study objectives were to quantify the impact on HRQL of a) ≥ 1 physical condition , b) ≥ 1 comorbid mental health conditions added to a physical one, c) ≥ 1 mental health condition, and d) ≥ 1 comorbid physical conditions added to at least one related to mental health. Decrements were based on a "Healthy" reference group reporting no chronic conditions. Methods: Participants were sampled (n = 3877) from the US adult population as part of a 2009 normative survey. Demographics, number/ type of chronic conditions, and HRQL data were self-reported. HRQL was defined through SF-36v2 W Physical Component Summary (PCS) scores and Mental Component Summary (MCS) scores. Participant "morbidity" groupings included Healthy; Physical Health Condition only, Mental Health Condition only, and Physical and Mental Health (Comorbid). PCS and MCS scores were also analyzed by physical disease clusters (e.g., cardiovascular, gastrointestinal). Multivariate regression models were used for all analyses.
Rwanda Journal, 2016
Background: Non-communicable diseases are the most common causes of death worldwide. Alongside mortality, noncommunicable diseases also cause high rates of morbidity and disability. The common comorbidity issues of depression worldwide are not a rare occurrence and as depression is chronic in nature it would double or even triple these health threats. Objectives: This paper highlights the epidemiology of the comorbidity of depression as a chronic non-communicable disease, highlighting the health effects of depression and examines specialized tools used to identify depression in patients. Methods: This literature search included the following computerized databases: MEDLINE, Academic Search Premier, Nexus, EBSCOhost, and CINAHL to review articles published from 1991 to 2012. The reviewed articles were quantitative and data were analysed using mostly different versions of SPSS® statistical package. Results and Conclusion: Worldwide established tools were utilized to identify depression in patients with non-communicable diseases. The validated tools include Beck's Depression Inventory, the Patient Health Questionnaire and the Hospital Anxiety and Depression Scale. The prevalence of depression was found to be significantly higher in those with chronic non-communicable diseases in all regions of the world. The health effects of depression found in literature review included a high morbidity and mortality, as well as increased health costs. Conclusion: Significantly higher depression among patients with chronic NCDs suggests that regular screening of depression in this population is warranted. Likewise, the use of validated tool for assessment of depression is essential.
Quality of life among patients with cardiac disease: the impact of comorbid depression
Health and Quality of Life Outcomes
Background: Patients with cardiac disease with or without depression may also have major physical and mental problems. This study assesses and compares the quality of life (QOL) of patients with cardiac disease with and without depression and accompanying comorbidities. Methods: A cross-sectional study was conducted with a convenience sample of 388 patients with cardiac disease. The 12-item Short-Form (SF-12)-patient was used to measure physical component scale (PCS) and mental component scale (MCS) QOL, and the Patient Health Questionnaire (PHQ-9) was used to measure depression. The Charlson Comorbidity Index was used to estimate 10-year survival probability. Descriptive statistics, analysis of covariance (ANCOVA), chi-square tests, and binary logistic regression were used for analysis. Results: The prevalence of minimal to mild depression was 65.7% [(95% CI (60.8, 70.4)] and that of moderate to severe depression was 34.3% [95% CI (29.6, 39.2)]. There was no significant association between the level of PHQcategorised depression and age (p = 0.171), sex (p = 0.079), or ethnicity (p = 0.407). The overall mean PCS and MCS QOL was 32.5 [95% CI (24.4, 40.64)] and 45.4 [95% CI (44.4, 46.4)], respectively, with no significant correlation between PCS and MCS [r (Pearson's) = 0.011; p = 0.830)]. There were QOL differences among the five PHQ categories (PCS: p = 0.028; MCS: p ≤ 0.001) with both MCS and PCS decreasing with increasing depression. ANCOVA (with number of comorbidities as the covariate) showed a significant age × ethnicity interaction for PCS (p = 0.044) and MCS (p = 0.039), respectively. Young Indo-Trinidadians had significantly lower PCS than did Afro-Trinidadians, while the converse was true for MCS. Depression, age, and number of comorbidities were predictors of PCS, while depression, age, and sex were predictors of MCS. Conclusions: Increasing severity of depression worsened both PCS and MCS QOL. Age and level of clinical depression predicted QOL, with number of comorbidities predicting only PCS and sex predicting only MCS. Efforts must be made to treat depression in all age groups of patients with cardiac disease.