Longitudinal research on the bidirectional association between depression and arthritis

A predictive model for depression in elderly people with arthritis based on the TRIPOD guidelines

OBJECTIVE

Through machine learning algorithms, a prediction model for depression in arthritis patients was established to provide a basis for related interventions.

METHODS

Data from 4240 patients with arthritis were collected from the National Health and Nutrition Examination Survey database and divided into a training set (70 %) and a test set (30 %). LASSO Regression was employed for feature variable selection, and predictive models were constructed using five machine learning algorithms: Random Forest (RF), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), Gaussian Naive Bayes (GNB), and Gradient Boosting Decision Tree (GBDT). Model performance was evaluated through various metrics, including the Area Under the Receiver Operating Characteristic Curve (AUC), accuracy, sensitivity, cutoff, recall, Kappa, Positive Predictive Value(PPV) and Negative Predictive Value(NPV). Additionally, Shapley Additive Explanations (SHAP) analysis was conducted for personalized risk assessment.

RESULT

The predictive performance of the random forest model was the highest,with an area under curve (AUC) of 0.811 (SD:0.000) for the training set and 0.780 (SD:0.001) for the test set. The model identified eight significant variables associated with the occurrence of arthritis depression, including health status, difficulty standing for extended periods, difficulty getting in and out of bed, difficulty sitting for prolonged durations, education, gender, difficulty managing finances, and race. DCA demonstrated that the nomogram was clinically beneficial.

CONCLUSION

The predictive model developed for identifying depression in patients with arthritis exhibits high predictive ability, and good clinical applicability. This model can aid healthcare providers in the early detection of depression, thereby enabling timely interventions that can enhance patient prognosis and promote healthy aging. Future research should incorporate real-time biomarker monitoring to refine dynamic risk assessment.

Associations of arthritis with functional disability and depressive symptoms in general US adults: NHANES 1988-1994 and 1999-2018

Objectives

This study aimed to examine the associations of arthritis with functional disability and depressive symptoms among general US adults. Additionally, it explored the relationship between radiographic knee osteoarthritis (assessed by X-ray examination) and functional disability. Above findings seek to highlight the need for comprehensive physical and mental health management in individuals with arthritis.

Methods

We designed a cross-sectional study utilizing multivariable logistic regression models to examine the associations. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were documented in a crude model and three adjusted models. Participants were from the National Health and Nutrition Examination Survey (NHANES) 1988-1994 and 1999-2018. Arthritis was self-reported or graded by the Kellgren-Lawrence score after an objective X-ray examination. Functional disability included disability in activities of daily living (ADL disability), instrumental activities of daily living (IADL disability), and mobility disability. Depressive symptom was assessed using the Patient Health Questionnaire (PHQ).

Results

We included 22,566 older adults (≥60 years; 10,961 had self-reported arthritis) for functional disability analysis (2377 older adults with data on X-ray examination; 1012 had radiographic knee osteoarthritis) and 32,056 adults (≥20 years; 9175 had self-reported arthritis) for depressive symptom analysis. After controlling for all covariates, self-reported arthritis was associated with ADL disability (odds ratios [OR]: 2.677; 95% confidence interval [CI]: 2.499-2.868), IADL disability (OR: 2.064; 95% CI: 1.940-2.196), and mobility disability (OR: 2.954; 95% CI: 2.778-3.142), and depressive symptom (OR: 2.177; 95% CI: 1.979-2.395). In participants with data on X-ray examination, radiographic knee osteoarthritis was only associated with mobility disability (OR: 1.437; 95% CI: 1.183-1.744).

Conclusions

Self-reported arthritis was associated with ADL disability, IADL disability and mobility disability, and depressive symptoms. Among participants with X-ray data, radiographic knee osteoarthritis was only associated with mobility disability in general US adults. Appropriate managements of both physical and mental health are needed for individuals with arthritis.

Development of machine learning models for predicting depressive symptoms in knee osteoarthritis patients

Knee osteoarthritis (KOA) combined with depressive symptoms is prevalent and leads to poor outcomes and significant financial burdens. However, practical tools for identifying at-risk patients remain limited. A robust prediction model is needed to address this gap. This study aims to develop and validate a predictive model to identify KOA patients at risk of developing depressive symptoms. The China Health and Retirement Longitudinal Survey (CHARLS) data were used for model development and the Osteoarthritis Initiative (OAI) for external validation. 18 potential predictors were selected using LASSO regression. 4 machine learning models-logistic regression, decision tree, random forest, and artificial neural network-were developed. Model performance was assessed using the area under the operating characteristic curve (AUC), calibration curves, and decision curve analysis. The most important features were extracted from the optimal model on external validation. A total of 469 individuals were included, with 70% used for training and 30% for testing. The random forest model achieved the best performance, with an AUC of 0.928 in the test set, outperforming logistic regression (AUC 0.622), decision tree (AUC 0.611), and neural network models (AUC 0.868). External validation revealed an AUC of 0.877 (95% CI: 0.864-0.889) for the adjusted random forest model. Pain severity was the most significant predictor, followed by the five-time sit-to-stand test (FTSST) and sleep problems. This study is the first in China to apply a predictive model for depressive symptoms in KOA patients, offering a practical tool for early risk identification using routinely available data.

Association of improvement and worsening of depressive symptoms with arthritis

PURPOSE

The longitudinal association between changes in depressive symptoms (improvement/worsening) and arthritis is unclear.

METHODS

Study data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) 2011-2018. The 10-item Center for Epidemiological Studies Depression Scale (CES-D-10) was used to examine participant depressive symptoms and data on self-reported history of arthritis were collected. Depressive symptoms improving is defined as depression at baseline and no depression at follow-up. Similarly, depressive symptoms worsening is defined as no depression at baseline and depression at follow-up. Cox proportional hazards models were used to evaluate the effects of improvement or deterioration in depressive symptoms on arthritis. Participants with missing data on depression and arthritis, having arthritis in 2011 CHARLS and lost to follow-up was excluded.

RESULTS

A total of 8556 participants free of arthritis were included from 2011 to 2018. After adjustment for confounders, depressive symptoms were associated with a 54% increased risk of developing arthritis. Each 1-point increase in CES-D-10 score was associated with a 4% higher risk of arthritis. Participants with depressive symptoms at baseline but improved symptoms (without depressive symptoms) at follow-up had a 25% lower rate of arthritis, and a 1-point reduction in CES-D-10 score during 8 years of follow-up was associated with a 5% lower risk of developing arthritis. Participants with no depressive symptoms at baseline but depression at follow-up had a 66% higher rate of arthritis, and a 1-point increase in CES-D-10 score during 8 years of follow-up was associated with a 5% higher risk of arthritis.

CONCLUSIONS

Improvement in depressive symptoms was associated with lower risk of arthritis and worsening of depression was associated with higher risk of arthritis. These findings suggest that the relationship between depression and arthritis is complex.

Association of Depression With the Progression of Multimorbidity in Older Adults: A Population-Based Cohort Study

BACKGROUND

The relationship between depression and the risk of multimorbidity progression has rarely been studied in older adults. This study was aimed to determine whether depression is associated with progression in the severity and complexity of multimorbidity, considering the influence of depression's severity and subtype.

METHODS

As a part of the Korean Longitudinal Study on Cognitive Aging and Dementia, this population-based cohort study followed a random sample of community-dwelling Koreans aged 60 and older for 8 years at 2-year intervals starting in 2010. Participants included those who completed mood and multimorbidity assessments and did not exhibit complex multimorbidity at the study's outset. Depression was assessed using the Geriatric Depression Scale, while multimorbidity was evaluated using the Cumulative Illness Rating Scale. The study quantified multimorbidity complexity by counting affected body systems and measured multimorbidity severity by averaging scores across 14 body systems.

FINDINGS

The 2,486 participants (age = 69.1 ± 6.5 years, 57.6% women) were followed for 5.9 ± 2.4 years. Linear mixed models revealed that participants with depression had a faster increase in multimorbidity complexity score (β = .065, SE = 0.019, p = 0.001) than those without depression, but a comparable increase in multimorbidity severity score (β = .001, SE = .009, p = 0.870) to those without depression. Cox proportional hazard models revealed that depression was associated with the risk of developing highly complex multimorbidity affecting five or more body systems, particularly in severe or anhedonic depression.

INTERPRETATION

Depression was associated with the worsening of multimorbidity in Korean older adults, particularly when severe or anhedonic. Early screening and management of depression may help to reduce the burden of multimorbidity in older adults.

Depressive symptoms and associated factors among older patients with arthritis: evidence from a community-based study in eastern China

Introduction

Depressive symptoms are often experienced by patients with arthritis and are correlated with poor health outcomes. However, the association between depressive symptoms and multidimensional factors (sociodemographic characteristics, health conditions, health behaviors, and social support) among older patients with arthritis in China remains poorly understood. This study aimed to explore the prevalence of depressive symptoms in older patients with arthritis in eastern China and identify the associated factors.

Methods

We analyzed data of 1,081 older patients with arthritis using secondary data from 2014 to 2020 from a community-based ongoing study initiated in 2014 in eastern China. The prevalence of depressive symptoms was calculated, and univariate and multilevel logistic regression analyses were used to identify the associated factors.

Results

The mean age of older patients with arthritis was 69.16 ± 7.13 years; 42.92% were men and 57.08% were women. The prevalence of depressive symptoms in older patients with arthritis was 14.99% (95% confidence interval: 12.91-17.26%), about 1.8 times higher than that in older adults without arthritis (8.49%, p < 0.001). Multilevel logistic regression identified perception of poor economic status (odds ratio [OR] = 5.52, p < 0.001), multimorbidity (OR = 1.96, p = 0.001), limitations in activities of daily living (OR = 2.36, p = 0.004), and living alone (OR = 3.13, p = 0.026) as factors positively associated with depressive symptoms. Patients diagnosed with arthritis at an older age had lower odds of experiencing depressive symptoms (OR = 0.67, p = 0.046).

Conclusion

Screening for depressive symptoms is essential among older patients with arthritis, especially those who perceive themselves as having a poor economic status, are diagnosed at an earlier age, have multimorbidity, have limitations in activities of daily living, and live alone. The associations of age at arthritis diagnosis and dietary behaviors with depressive symptoms require further research.

Quantifying depressive symptoms on incidence of common chronic diseases and multimorbidity patterns in middle-aged and elderly Chinese adults

BACKGROUND

Depressive symptoms are highly prevalent and increase risks of various morbidities. However, the extent to which depressive symptoms could account for incidence of these chronic conditions, in particular multimorbidity patterns, remains to be examined and quantified.

METHODS

For this cohort analysis, we included 9024-14,093 participants aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the longitudinal associations between depressive symptoms and 13 common chronic diseases and 4 multimorbidity patterns. Population attributable fractions (PAFs) combining the information on both exposure prevalence and risk association were estimated to quantify the magnitude of the burden of these conditions attributable to depressive symptoms.

RESULTS

Depressive symptoms were associated with increased risks of liver disease, stroke, heart problem, asthma, diabetes, arthritis, kidney disease, chronic lung disease, digestive disease, dyslipidemia, and memory-related disease, and the adjusted HRs (95% CIs) and PAFs (95% CIs) ranged from 1.15 (1.05-1.26) to 1.64 (1.38-1.96) and 5% (0-10%) to 17% (6-28%), respectively. In addition, individuals with depressive symptoms had elevated risks of the cardiometabolic-cancer pattern, the cerebrovascular-memory pattern, the articular-visceral organ pattern, and the respiratory pattern, with respective HRs (95% CIs) of 1.26 (1.11-1.42), 1.34 (1.07-1.69), 1.45 (1.29-1.63), and 2.01 (1.36-2.96), and respective PAFs (95% CIs) of 5% (0-10%), 8% (-4-21%), 12% (7-17%), and 20% (5-35%).

CONCLUSION

Depressive symptoms contribute substantially to the burden across a broad range of chronic diseases as well as different multimorbidity patterns in middle-aged and older Chinese.

Hospital Length of Stay and Associated Factors in Patients with Osteoarthritis from Germany: A Cross-Sectional Study

Objective: There is a scarcity of data on hospital length of stay (LOS) in the osteoarthritis population. Therefore, this study aimed to investigate hospital LOS and associated factors in patients with osteoarthritis from Germany. Methods: The present cross-sectional study included patients hospitalized for osteoarthritis in one of fourteen hospitals in Germany between 2018 and 2023 (hospital database; IQVIA). The study outcome was the duration of hospital stay in days. Study covariables included age, sex, hospital department, osteoarthritis type, co-diagnosis, and hospitalization-related procedure. Associations between covariables and hospital LOS were analyzed using hierarchical linear regression models. Results: There were 8770 patients included in the study (mean [standard deviation] age 68.7 [10.8] years; 60.2% women). The mean (standard deviation) hospital LOS was 8.5 (5.0) days. Factors positively and significantly associated with hospital LOS were older age, female sex, orthopedic surgery and other medical specialty departments (compared with other surgery departments), knee and other and unspecified osteoarthritis (compared with hip osteoarthritis), multiple co-diagnoses (e.g., acute posthemorrhagic anemia, other disorders of fluid, electrolyte, and acid-base balance, and disorders of purine and pyrimidine metabolism), and several hospitalization-related procedures (i.e., geriatric rehabilitation, hip arthroplasty, and knee arthroplasty). Conclusions: The mean hospital LOS was higher than eight days in this osteoarthritis population from Germany, with a spectrum of demographic, clinical, and hospitalization-related factors associated with this hospital LOS. In this context, interventions are needed to reduce the LOS of hospitalizations for osteoarthritis in Germany.

The relationship between frailty, walking ability, and depression in elderly Chinese people

To explore the relationship between depression symptoms, frailty, and walking ability in Chinese elderly people, and to provide new evidence for research on the prevention and treatment of depression in Chinese elderly people. The data of this study is sourced from the 2018 CHARLS data (China Health and Retirement Longitudinal Study). Z-test, logistic regression, and linear stratified regression were used to analyze the walking ability, frailty, and depressive symptoms of 2927 participants. Good walking ability and non frailty were significantly negatively correlated with depression symptoms in the elderly (P < .05). This important negative association persists even after adjusting for demographic, health condition, and lifestyle factors. (P < .05). Elderly women are at a higher risk of developing depression than men, while elderly people with good walking ability and no frailty are at a lower risk of developing depression. At the same time, elderly people with disabilities, hypertension, arthritis, and low levels of physical activity are more likely to experience depressive symptoms. It is recommended that elderly people pay attention to maintaining walking ability and avoiding frailty to reduce the risk of depression.

Depressive symptom trajectories and new-onset arthritis in a middle-aged and elderly Chinese population

OBJECTIVE

Previous studies reported that depression was associated with a high risk of arthritis. However, the effect of different long-term depressive symptom trajectory patterns on the risk of arthritis has not been evaluated. Our study aimed to explore the association between depressive symptom trajectories and the risk of arthritis.

METHODS

A total of 5583 participants from the China Health and Retirement Longitudinal Study from 2011 to 2018 were included in this analysis. Group-based trajectory modeling was used to identify depressive symptom trajectories, and a multivariable competitive Cox regression model was used to examine the association of depressive symptom trajectories with arthritis during follow-up.

RESULTS

Five depressive symptom trajectories were identified in our research: stable-high, decreasing, increasing, stable-moderate and stable-low. Compared with participants in the stable-low trajectory group, those in the stable-moderate, increasing, decreasing and stable-high trajectory groups had a higher cumulative risk of arthritis, with HRs (95% CIs) for arthritis of 1.64 (1.30, 2.07), 1.86 (1.30, 2.66), 1.99 (1.41, 2.80) and 2.19 (1.38, 3.48), respectively. Participants with the stable-high symptoms trajectory had the highest cumulative risk of arthritis. There was still a high risk of arthritis, although the depression state was reduced and remained at a level that is generally considered reasonable.

CONCLUSIONS

The higher depressive symptoms trajectories were significantly associated with the increased risk of arthritis, and the long-term depressive symptoms trajectories may be a strong predictor of having arthritis.

Influence of chronic diseases on the occurrence of depression: A 13-year follow-up study from the Survey of Health, Ageing and Retirement in Europe

The causal association between chronic diseases and depression remains unclear. This study aimed to explore the effects of types and number of chronic diseases on the risk of depression using data from the Survey of Health, Ageing and Retirement in Europe (SHARE). A self-admitted questionnaire was used to obtain data on 14 predefined chronic diseases and the European-Depression Scale (EURO-D) was used to assess depression. Among the 16,080 baseline depression-free participants aged 50+, 31.29% (5032) developed depression over 13 years. Multivariate Cox regression models showed that individuals with any chronic diseases were at higher risk of new onset depression compared to disease-free participants. The risk of new onset depression increased with an increasing number of diseases among both younger (50-64) and older (65+) adults. Individuals with heart attack, stroke, diabetes, chronic lung disease, and arthritis were at increased risk of depression across age groups. However, some age-specific associations were observed, with cancer increasing depression risk among younger- and peptic ulcer, Parkinson's disease and cataracts increasing depression risk among older adults. These findings highlight the importance of managing chronic diseases, especially among those with more than two diseases, to prevent the development of depression among middle-aged and older adults.

Prevalence and associated factors of cross-sectional and incident self-reported arthritis or rheumatism among a national community sample of middle-aged and older adults in Thailand

Background

The study aimed to assess the prevalence and associated factors of cross-sectional and incident arthritis or rheumatism among a national community sample of middle-aged and older adults in Thailand.

Methods

We analyzed cross-sectional and longitudinal data from two consecutive waves (2015 and 2017) of the Health, Aging, and Retirement in Thailand (HART) study. Arthritis or rheumatism (SRA) was assessed by self-reported health care provider diagnosis.

Results

The cross-sectional (baseline) sample included 5,616 participants (≥45 years, median age 66 years, interquartile range 57 to 76 years) and the incident (follow-up) sample included 3,545 participants. The prevalence of SRA in the cross-sectional sample (baseline) was 4.0% and in the incident (follow-up) sample 5.3%. In the cross-sectional multivariable model, obesity class I (aOR: 1.78, 95% CI: 1.19 to 2.67), obesity class II (aOR: 1.82, 95% CI: 1.02 to 3.25), hypertension (aOR: 1.90, 95% CI: 1.35 to 2.66), brain disease and/or psychiatric problems (aOR: 4.79, 95% CI: 2.27 to 10.62), sleep problem (aOR: 1.45, 95% CI: 1.01 to 2.07) and prescription drug use (aOR: 1.63, 95% CI: 1.14 to 2.33) were positively associated, and not in the labor force (aOR: 0.53, 95% CI: 0.34 to 0.84), and employed (aOR: 0.63, 95% CI: 0.41 to 0.99) were negatively associated with SRA. In the incident multivariable model, obesity class I (aOR: 1.78, 95% CI: 1.17 to 3.61), obesity class II (aOR: 2.01, 95% CI: 1.12 to 3.61), poor mental health (aOR: 1.69, 95% CI: 1.19 to 2.41), and functional disability (aOR: 2.04, 95% CI: 1.01 to 4.13) were positively associated, and current alcohol use (aOR: 0.50, 95% CI: 0.25 to 0.99) was negatively associated with SRA.

Conclusion

The middle and older Thai adults had a low prevalence and incidence of SRA, and several physical and mental risk factors for cross-sectional and/or incident SRA were identified.

Visual impairment and depression in China: a 7-year follow-up study from national longitudinal surveys

OBJECTIVES

To explore the longitudinal association between visual impairment (VI) and depression among adults 45 years and older in China based on a nationally representative follow-up dataset.

SETTING

Participants in China from the China Health and Retirement Longitudinal Study were included.

PARTICIPANTS

A total of 6748 participants from two waves of the China Health and Retirement Longitudinal Study 2011-2018 were included for analysis by age group.

PRIMARY AND SECONDARY OUTCOME MEASURES

VI and depression were defined by self-diagnosis and the Center for Epidemiological Studies Depression Scale-10, respectively. Lagged dependent variable regression models with ordinary least squares estimation were used to evaluate the association between VI and depression. Age was divided into three groups, that is, 45-54, 55-64, and 65 years and older, to explore the relationship between VI and depression in different age groups.

RESULTS

In our study sample, VI remarkably predicted an increase in depressive scores. The magnitude of depressive scores increased among those with VI points greater than 3.517 (β=3.517; 95% CI=2.697 to 4.331) points than those without VI in the 7-year follow-up. Significant relationships were also found between VI and depression in the three age groups in the sensitivity analysis.

CONCLUSION

VI was associated with an increase in depression scores over a 7-year period. Female respondents, low educational attainment and high alcohol intake significantly predicted an increase in depressive status.

Bidirectional Association Between Depression and Hearing Loss: Evidence From the China Health and Retirement Longitudinal Study

The relationship between depression and age-related hearing loss (ARHL) is not fully understood. This study tested the bidirectional associations between clinically significant depressive symptoms (CSDSs) and ARHL in middle-aged and older adults using data from the China Health and Retirement Longitudinal Study. Among 3,418 participants free of baseline ARHL, baseline CSDS was associated with an increased odds of incident ARHL (odds ratio [OR]: 1.51). Cognitive decline, BMI, and arthritis partially mediated the longitudinal CSDS-ARHL association and explained 24% of the variance in the total effect. Among 4,921 participants without baseline CSDS, baseline ARHL was associated with an increased odds of incident CSDS (OR: 1.37). The bidirectional associations remained significant after adjustments for baseline demographic factors, comorbidities, and other health-related covariates. Depression may contribute to the development of ARHL, and vice versa. Interventions in depression, cognitive decline, and arthritis may delay the onset of ARHL and break the vicious circle between them.