BACKGROUND
Arthritis is a common, debilitating, chronic medical condition associated with pain, functional limitation, and reduced quality of life.1 The estimated lifetime risk of osteoarthritis is approximately 40% in men and 47% in women, rising to nearly 60% among individuals with a body mass index (BMI) greater than 30.2 Furthermore, around 50% of arthritis cases are managed by primary care physicians, and up to 38% of cases seen by rheumatologists could be managed by family physicians.3,4 Depression is likewise highly prevalent in primary care settings and is a leading cause of global disability, often co-occurring with chronic medical illness and contributing to worse clinical outcomes, greater healthcare utilization, and impaired functioning.5 Given that family physicians are often consulted first-line for the management of both chronic musculoskeletal disease and mental health conditions, understanding the relationship between arthritis and depression is clinically important.
Prior systematic reviews and large epidemiologic studies have reported elevated rates of depression among patients with rheumatoid arthritis and other chronic joint diseases, likely reflecting the combined effects of chronic pain, reduced physical functioning, and psychosocial stressors.6 National surveillance data have similarly shown a higher prevalence of anxiety and depressive symptoms among adults with arthritis compared with those without arthritis.7 Retrospective cohort studies further suggest that arthritis may increase the risk of developing depressive symptoms over time.8 However, the extent to which this association is independent of key demographic and socioeconomic factors remains uncertain.
Age appears to be a particularly important, yet incompletely understood, factor that modifies this relationship. While arthritis prevalence increases with age, younger adults with arthritis may face distinct psychosocial challenges, disruption of work and social roles, and altered life trajectories that may heighten vulnerability to depression. National data indicate that symptoms of anxiety and depression among adults with arthritis are often more prevalent in younger than in older individuals, and age-stratified analyses in rheumatoid arthritis cohorts suggest stronger associations between arthritis and depression in younger adults.7,9 Despite these observations, relatively few population-based studies have explicitly examined whether age modifies the association between arthritis and depression in U.S. adults, and the degree to which this relationship persists after accounting for sociodemographic characteristics remains unclear.
Accordingly, this study aims to clarify the independent association between arthritis and depression in a nationally representative sample of U.S. adults using recent NHANES data and to evaluate whether this relationship varies across age groups. By addressing this gap, this study aims to better characterize age-related differences in the association between arthritis and depressive symptoms, informing future hypothesis-driven and longitudinal research in primary care settings.
METHODS
A cross-sectional analysis was conducted using publicly available data from the National Health and Nutrition Examination Survey (NHANES) 2021–2023 cycle. Adults aged 18 years and older with complete data on arthritis status, depression screening, and demographic variables were included in the analysis.
Arthritis status was defined by self-reported clinician diagnosis of arthritis (NHANES variable MCQ195). Depression was assessed using the Patient Health Questionnaire (PHQ-9), derived from questionnaire items DPQ010 through DPQ090, with depression defined as a total PHQ-9 score ≥10, consistent with established NHANES scoring conventions.
Demographic covariates included age (RIDAGEYR), sex (RIAGENDR), educational attainment (DMDEDUC2), and income-to-poverty ratio (INDFMPIR). The analytic sample included adults across a broad age range and represented both sexes and varying levels of educational attainment and socioeconomic status. Age was analyzed as a continuous variable to evaluate changes in the arthritis–depression association across the age spectrum. Participants with missing data for any model covariates were excluded from adjusted analyses.
STATISTICAL ANALYSIS
All analyses were performed using Python in Jupyter Notebook. Descriptive statistics were used to summarize participant characteristics. Multivariable logistic regression models were constructed to evaluate the independent association between arthritis and depression while adjusting for demographic covariates. A secondary model included an interaction term between arthritis and age to assess effect modification across the age spectrum.
Odds ratios (ORs) with 95% confidence intervals (CIs) and p-values were reported, with statistical significance defined as p < 0.05. NHANES sampling weights were not applied, and results should be interpreted as associative rather than nationally weighted estimates.
RESULTS
A total of 1,119 participants met inclusion criteria for adjusted analyses. As seen in Figure 1, in unadjusted analyses, no statistically significant association was observed between arthritis and depression. In the multivariable logistic regression model adjusting for age, sex, education, and income, arthritis was not independently associated with depression (OR 0.76, 95% CI 0.51–1.14, p = 0.19). Higher educational attainment (OR 0.75, 95% CI 0.62–0.90, p = 0.002) and higher income-to-poverty ratio (OR 0.75, 95% CI 0.66–0.86, p < 0.001) were independently associated with lower odds of depression alone. Sex was not significantly associated with depression alone in the adjusted model.
The association between arthritis and depression was found to be significantly modified by age (p = 0.014), suggesting that age moderates the relationship between these conditions. Specifically, arthritis was associated with a higher likelihood of depression among younger adults, with this effect gradually diminishing as age increased. This finding suggests that younger adults with arthritis experience a greater relative risk of depression compared to older adults.
DISCUSSION
In this nationally representative sample of U.S. adults from the 2021–2023 NHANES cycle, we found no independent association between arthritis and depression in the general adult population after adjusting for demographic factors. However, a significant interaction between arthritis and age was identified, indicating that the association between arthritis and depression is age-dependent. Specifically, younger adults with arthritis experienced significantly higher odds of depression, with this association diminishing progressively with increasing age.
These findings highlight an important nuance in the relationship between physical and mental health that may be particularly relevant in primary care and family medicine settings. While arthritis is commonly perceived as a condition affecting older adults, its presence in younger individuals may carry disproportionate psychological burdens. Younger adults may be more affected by the functional limitations imposed by arthritis due to greater occupational, educational, and social demands during early and middle adulthood. The diagnosis of a chronic, potentially disabling condition during this life stage may interfere with career development, social roles, and the ability to engage in physical activities typically enjoyed by peers, contributing to feelings of isolation or decreased self-worth.
In contrast, older adults may perceive arthritis as a more expected consequence of aging and may have developed coping strategies, social support systems, or adjusted expectations that buffer against depressive symptoms. Additionally, older individuals may have greater access to medical care and may already be under treatment for arthritis-related pain and disability, potentially mitigating the impact on mental health.
The finding that higher educational attainment and income were independently associated with lower odds of depression aligns with broader literature on the social determinants of mental health.10,11 These variables likely reflect greater access to healthcare, health literacy, social resources, and coping mechanisms that can mediate psychological resilience, even in the presence of chronic illness.
LIMITATIONS
This study has several limitations. First, the cross-sectional nature of NHANES limits causal inference; while associations between arthritis and depression are described, the directionality of these relationships cannot be determined. Second, both arthritis and depression were based on self-reported data, which may be subject to recall or reporting bias. Third, residual confounding may exist, as other potential mediators (e.g., pain severity, physical functioning, or access to care) were not included in the analysis. Fourth, although NHANES is a nationally representative dataset, the exclusion of participants with incomplete data may have introduced selection bias and reduced the generalizability of the findings. Fifth, arthritis was assessed as a single self-reported condition, without differentiation by subtype (e.g., osteoarthritis versus rheumatoid arthritis), which may obscure subtype-specific associations. Lastly, NHANES sampling weights were not applied, so results should be interpreted as associative and may not be generalizable to the broader U.S. population.
CONCLUSION
These results suggest that screening for depression in patients with arthritis may be particularly important among younger adults, who may be at elevated risk but are less likely to be identified by traditional age-based screening paradigms. Clinicians should consider incorporating age-specific mental health assessment and counseling into the care of younger patients with arthritis, as well as ensuring timely referrals to mental health services when needed. These findings have important implications for family medicine, highlighting the need for heightened depression screening and psychosocial support among younger patients presenting with arthritis. Incorporating age-sensitive mental health assessment into routine musculoskeletal care may improve holistic management and patient outcomes in primary care settings.
AI AND TOOL USAGE STATEMENT
ChatGPT (OpenAI) was used to assist with statistical coding, data interpretation, and drafting/editing the manuscript. Additionally, NotebookLM (Google) was used to help generate and format figures for presentation. All analyses and interpretations were independently reviewed and verified by the study authors.