Association between anxiety, depression, and fatigue in elderly patients with Parkinson’s disease

Abstract

BACKGROUND

Parkinson’s disease (PD) is a common neurodegenerative disorder in the elderly population. Non-motor symptoms such as anxiety and depression are often subtle, hindering early detection and intervention, yet they markedly affect quality of life and clinical outcomes.

AIM

To investigate the prevalence of anxiety and depression in elderly PD patients, identify associated risk factors, and assess their relationship with fatigue severity.

METHODS

A cross-sectional analysis was conducted in 123 elderly PD patients treated at The Second Rehabilitation Hospital of Shanghai between January 2023 and December 2024. Demographic and clinical data were obtained using standardized questionnaires. Anxiety, depression, and fatigue were assessed using the Beck Anxiety Inventory (BAI), Geriatric Depression Scale (GDS), and Fatigue Scale-14 (FS-14), respectively. Binary logistic regression identified risk factors for anxiety and depression, whereas Spearman’s correlation assessed associations with fatigue.

RESULTS

Anxiety and depression prevalence rates were 64.2% (mean BAI score: 19.59 ± 10.92) and 56.1% (mean GDS score: 12.82 ± 6.37), respectively. The mean FS-14 total score was 9.46 ± 1.89, comprising physical (5.77 ± 1.51) and mental (3.69 ± 1.20) fatigue components. Significant positive correlations were observed between fatigue scores (total, physical, and mental) and both anxiety and depression (all P < 0.05). Univariate analysis revealed statistically significant associations between anxiety/depression and monthly income, disease duration, and disease severity (all P < 0.05). Multivariate logistic regression indicated higher anxiety risk in patients with lower monthly income, prolonged disease duration, advanced disease severity, or multimorbidity. Depression risk was elevated in patients with lower monthly income and severe disease, whereas longer disease duration unexpectedly served as a protective factor.

CONCLUSION

Elderly PD patients show high rates of anxiety and depression, both of which are significantly correlated with fatigue severity. These findings highlight the importance of psychological monitoring and targeted mental health interventions in PD management among the elderly.

Key Words: Parkinson’s disease; Anxiety; Depression; Elderly; Fatigue severity; Psychological status

Core Tip: Parkinson’s disease (PD) predominantly affects middle-aged and elderly individuals, with an increasing incidence in aging populations. Anxiety and depression are major psychological symptoms that intensify caregiver dependence and impose heavy burdens on patients and families. Fatigue, another disabling but underrecognized non-motor symptom, further compounds disease impact. However, few studies have addressed its relationship with anxiety and depression in PD. This study assessed the prevalence of anxiety and depression, identified related factors, and analyzed their correlation with fatigue severity.

INTRODUCTION

Parkinson’s disease (PD), historically termed paralysis agitans, is a progressive neurodegenerative disorder predominantly affecting middle-aged and elderly populations[1]. The cardinal motor features include resting tremor, bradykinesia, muscular rigidity, and postural instability. Pathologically, PD is characterized by selective loss of dopaminergic and other pigmented neurons within key brainstem nuclei – most notably the substantia nigra pars compacta, locus coeruleus, raphe nuclei, and dorsal motor nucleus of the vagus – along with the presence of distinctive eosinophilic cytoplasmic inclusions (Lewy bodies) in surviving neurons[2,3]. Although diagnosis is primarily based on dopaminergic motor symptoms, emerging evidence implicates multiple neurotransmitter systems, explaining the wide range of motor and non-motor manifestations in PD pathogenesis[4,5]. As neurodegeneration advances, non-motor features such as depression, cognitive impairment, autonomic dysfunction, and sleep disturbances progressively dominate the clinical presentation, often becoming the primary determinants of patients’ quality of life[6,7]. Indeed, recent research emphasizes that the cumulative non-motor symptoms may exceed those of classical motor impairments[8].

Approximately 50% of patients with PD develop psychological comorbidities, most commonly anxiety and depression. Their reported prevalence is 40% and 28%, respectively[9], and symptoms may appear 2-10 years before PD diagnosis, significantly impairing patients’ quality of life[10]. These manifestations should therefore be recognized as early non-motor indicators of PD pathophysiology rather than mere psychological reactions to chronic illness[10]. Depression, in particular, is highly prevalent, emerging in the prodromal stage and persisting throughout the disease course[11]. Both motor and non-motor impairments correlate with depressive symptoms, further worsening functional decline and quality of life. A meta-analysis of 129 studies (n = 38304) estimated the pooled prevalence of depression in patients with PD at 38%[12]. Anxiety disorders also impose substantial burden yet remain understudied despite their clinical significance. Up to 40% of patients with PD experience generalized anxiety disorder, panic attacks, or social phobia, with some studies reporting rates as high as 68%[13]. Despite their impact, major knowledge gaps remain regarding the etiopathogenesis, standardized diagnostic criteria, and management of these conditions. Importantly, co-occurring anxiety and depression in PD may accelerate disease progression, heighten suffering, increase disability, and elevate suicide risk[14], underscoring the urgent need for systematic characterization of their clinical phenotypes and modifiable risk factors.

Besides mood disturbances, fatigue represents another debilitating yet poorly understood non-motor symptom. It is defined by pervasive exhaustion and energy depletion and affects nearly half of all patients[15-17]. For many PD patients, fatigue is among the most disabling symptoms, severely limiting daily activities and quality of life.

However, its clinical heterogeneity, overlapping manifestations, and multiple confounders complicate both mechanistic understanding and therapeutic management. Previous studies have largely focused on fatigue in relation to PD-specific features, yet growing evidence suggests strong associations with other non-motor symptoms of PD, including cognitive impairment, depression, anxiety, and autonomic dysfunction[18-20]. Together, these factors amplify the overall disease burden. Given these interconnections, the potential interplay between affective symptoms (anxiety and depression) and fatigue severity warrants further investigation. Accordingly, this study aimed to: (1) Determine the prevalence and determinants of anxiety and depression in patients with PD; and (2) Examine their association with fatigue severity. The ultimate goal is to support the early identification of high-risk patients and inform tailored preventive and therapeutic strategies.

MATERIALS AND METHODS

Study population

We enrolled consecutive elderly patients with PD who received treatment at The Second Rehabilitation Hospital of Shanghai between January 2023 and December 2024. Eligibility was determined as follows.

Inclusion criteria: (1) Age ≥ 60 years at enrollment; (2) Diagnosis of idiopathic PD according to the 2015 International Movement Disorder Society clinical diagnostic criteria; (3) Preserved cognitive and communicative ability, with intact auditory and visual function, permitting complete neuropsychological assessment (a normal score on the Simple Intelligence Scale confirmed adequate cognition and communication); and (4) Availability of comprehensive baseline clinical data and follow-up records.

Exclusion criteria: (1) Essential tremor, PD secondary to cerebrovascular diseases, encephalitis, trauma, or drugs, or PD-plus syndromes; (2) Recent exposure to major personal or familial stressors likely to affect mood; (3) A history of psychiatric disorders or family history of major mental illness; (4) Severe visual or auditory impairment, deficits in emotional expression, or comorbid psychiatric conditions that hindered participation; (5) Recent use of psychoactive medications influencing neuropsychiatric status; (6) Significant language barriers or dementia preventing questionnaire completion; (7) Comorbidities affecting psychological status (e.g., epilepsy, hypothyroidism); (8) Antidepressant or anxiolytic use within the past month; and (9) Incomplete demographic or clinical data. Based on these criteria, 123 patients were included.

Data collection

General demographic data: Information extracted from electronic medical records included age, sex, occupation, household income, education level, living arrangement, marital status, multimorbidity, disease duration, and disease severity.

Disease severity assessment: Disease severity was evaluated using the modified Hoehn and Yahr Staging Scale, which categorizes progression into seven stages (higher stages indicating greater severity): (1) Stage 1: Unilateral limb involvement (e.g., unilateral hand tremor, bradykinesia); (2) Stage 1.5: Unilateral limb plus trunk involvement (e.g., shoulder stiffness, postural abnormality); (3) Stage 2: Bilateral limb involvement without balance impairment; (4) Stage 2.5: Mild bilateral disease with recoverable posterior pull test (e.g., slight postural instability corrected with support); (5) Stage 3: Mild-moderate bilateral disease with balance impairment but independent living possible (e.g., difficulty turning, unsteady gait); (6) Stage 4: Severe disability with ability to stand or walk independently; and (7) Stage 5: Complete dependence on wheelchair or bed. Patients were classified as mild (stages 1, 1.5, 2), moderate (stages 2.5, 3), or severe (stages 4, 5).

Psychological assessment: Anxiety was assessed using the Beck Anxiety Inventory (BAI), a 21-item self-report scale in which symptoms experienced during the past week were rated on a 4-point Likert scale [from 0 (not at all) to 3 (severely)]. Total score was 0-63 and interpreted as follows: (1) 0-10: Minimal/no anxiety; (2) 11-15: Mild anxiety; (3) 16-25: Moderate anxiety; and (4) 26-63: Severe anxiety. Leentjens et al[21] confirmed the reliability and validity of the BAI in patients with PD. Depression was assessed using the Geriatric Depression Scale-30 (GDS-30), which comprises 30 yes/no items addressing emotional and behavioral symptoms (e.g., emptiness, hopelessness, excessive worry, and frequent crying). Responses indicating depressive symptoms scored 1 point, whereas non-depressive responses scored 0 points. The total score (0-30) reflects depression severity, with the following cutoffs: (1) 0-10: Normal; (2) 11-20: Mild depression; and (3) 21-30: Moderate–severe depression. The GDS-30 demonstrates strong validity with sensitivity/specificity of 0.84/0.95 (cutoff = 11) and 0.80/1.00 (cutoff = 14).

Fatigue assessment: Fatigue was assessed using the Fatigue Scale-14 (FS-14), which includes 8 items on physical fatigue and 6 items on mental fatigue. Total score is 0-14, with higher totals indicating greater fatigue severity.

Data processing

The questionnaire survey was administered by trained interns at our hospital. Before data collection, all investigators completed standardized training covering the study objectives, research components, proper questionnaire administration procedures, and the importance of informed consent. After participants provided written consent, the scales were administered at admission. Each question was posed sequentially, with responses recorded only after confirmation of accuracy. The investigators emphasized respectful and effective communication throughout the process. Data were entered into Excel, with each questionnaire double-entered and cross-checked to minimize entry errors and preserve data integrity.

Statistical analysis

Statistical analyses were performed using Statistical Package for the Social Sciences 25.0. Continuous variables, expressed as mean ± SD, were compared using independent t-tests for normally distributed data or nonparametric tests for non-normally distributed data. Categorical variables were summarized as frequencies (percentages) and compared using the χ² test. Binary logistic regression was used to identify factors associated with anxiety and depression, while Pearson’s correlation coefficient assessed associations between anxiety, depression, and fatigue severity. P < 0.05 was considered statistically significant.

RESULTS

Sociodemographic characteristics of the patients

Among the 123 participants, 52.8% were male and 47.2% were female, with a mean age of 65.54 ± 3.87 years. Educational attainment included 25.2% with a college degree or higher, 43.1% with senior high school, secondary school, or vocational college, and 31.7% with junior high school or below. Geographically, 67.5% resided in urban areas and 32.5% in rural areas. Monthly income was below 5000 RMB for 64.2% of the participants. Most patients were married (49.6%), and disease duration was ≤ 5 years in 71.5% of cases. Based on clinical severity, 22.8% of patients were classified as advanced stage. The full demographic characteristics are presented in Table 1.

Table 1 Sociodemographic characteristics of participants.

	Number of cases (n = 123)	Constituent ratio (%)
Gender
Male	65	52.8
Female	58	47.2
Age	65.54 ± 3.87	-
Body mass index	22.93 ± 2.14	-
Education level
Junior high school or below	39	31.7
Senior high school, secondary school, or college	53	43.1
University or above	31	25.2
Marital status
Single	24	19.5
Married	61	49.6
Divorced or widowed	38	30.9
Residence
Urban	83	67.5
Rural	40	32.5
Monthly income (yuan)
≤ 5000	79	64.2
> 5000	44	35.8
Disease duration (years)
≤ 5	88	71.5
> 5	35	28.5
Disease severity (Hoehn and Yahr grading)
Mild	30	24.4
Moderate	65	52.8
Severe	28	22.8
Multimorbidity
Yes	88	71.5
No	35	28.5
Family medical history
Yes	10	8.1
No	113	91.9

Anxiety and depression scores

Psychometric evaluation revealed considerable psychological morbidity. The mean BAI score was 19.59 ± 10.92, and the GDS score was 12.82 ± 6.37. Using a cutoff score of 10, clinically significant anxiety was identified in 64.2% (79/123) and depression in 56.1% (69/123) of the participants. Detailed comparisons are provided in Table 2.

Table 2 Comparison of anxiety and depression scores.

	Total score (n = 123)		Score
Beck Anxiety Inventory	19.59 ± 10.92	Anxiety (n = 79)	26.38 ± 7.39
		Non-anxiety (n = 44)	7.41 ± 1.57
Geriatric Depression Scale	12.82 ± 6.37	Depression (n = 69)	17.65 ± 3.76
		Non-depression (n = 54)	6.65 ± 2.48

Fatigue severity scores

A comprehensive fatigue assessment revealed a notable fatigue burden. The mean total FS-14 score was 9.46 ± 1.89, comprising a physical fatigue score of 5.77 ± 1.51 and a mental fatigue score of 3.69 ± 1.20. These findings suggest a moderate-to-severe fatigue syndrome in this cohort. The detailed results are presented in Table 3.

Table 3 Fatigue severity of patients.

Category	Number of items	Score
Fatigue severity	14	9.46 ± 1.89
Physical fatigue	8	5.77 ± 1.51
Mental fatigue	6	3.69 ± 1.20

Univariate analysis of clinical characteristics in patients with or without anxiety

Of the 123 enrolled patients, 79 exhibited anxiety symptoms. Univariate analysis revealed statistically significant differences between anxious and non-anxious groups in education level, monthly income, disease duration, disease severity, and multimorbidity (all P < 0.05). No significant differences were observed for gender, age, body mass index (BMI), marital status, residence, or family medical history (P > 0.05; Table 4).

Table 4 Univariate analysis of clinical characteristics in patients with or without anxiety.

	Anxiety (n = 79)	Non-anxiety (n = 44)	χ2/t	P value
Gender			0.223	0.637
Male	43	22
Female	36	22
Age	65.09 ± 3.58	66.36 ± 4.26	1.760	0.081
Body mass index	23.10 ± 2.19	22.61 ± 2.05	1.216	0.226
Education level			9.179	0.010
Junior high school or below	21	18
Senior high school, secondary school, or college	42	11
University or above	16	15
Marital status			0.353	0.838
Single	14	10
Married	39	22
Divorced or widowed	26	12
Residence			0.078	0.781
Urban	54	29
Rural	25	15
Monthly income (yuan)			16.211	< 0.0001
≤ 5000	61	18
> 5000	18	26
Disease duration (years)			9.830	0.002
≤ 5	49	39
> 5	30	5
Disease severity (Hoehn and Yahr grading)			7.313	0.026
Mild	17	13
Moderate	38	27
Severe	24	4
Multimorbidity			9.424	0.002
Yes	64	24
No	15	20
Family medical history			0.158	0.691
Yes	7	3
No	72	41

Analysis of influencing factors for anxiety

All variables showing significant differences in the univariate analysis (P < 0.05) among the 123 patients were entered into a multivariate logistic regression model. Anxiety status (0: Absent, 1: Present) was set as the dependent variable, with significant univariate predictors were included as covariates. The analysis identified monthly income ≤ 5000 RMB and disease duration of > 5 years as independent risk factors for anxiety (P = 0.001). Compared with mild disease severity, severe disease was associated with a markedly higher risk of anxiety [hazard ratio (HR) = 6.636, P = 0.022]. Multimorbidity also independently predicted elevated anxiety risk (HR = 2.826, P = 0.040). Details are provided in Table 5.

Table 5 Factors associated with anxiety in elderly patients with Parkinson’s disease.

Variable	β	SE	Wald	P value	Hazard ratio	95%CI
Constant	-2.073	0.716	8.393	0.004	0.126	-
Education level (0: Junior high school or below)	-	-	3.618	0.164	-	-
1: Senior high school, secondary school, or college	0.701	0.561	1.563	0.211	2.016	0.672-6.050
2: University or above	-0.421	0.620	0.461	0.497	0.656	0.195-2.214
Monthly income (0: > 5000, 1: ≤ 5000)	1.684	0.504	11.149	0.001	5.372	2.003-14.414
Disease duration (0: ≤ 5, 1: > 5)	2.281	0.690	10.931	0.001	9.784	2.531-37.820
Disease severity (0: Mild)	-	-	6.836	0.033	-	-
1: Moderate	0.004	0.545	0.000	0.995	1.004	0.345-2.923
2: Severe	1.893	0.824	5.279	0.022	6.636	1.321-33.346
Multimorbidity (0: No, 1: Yes)	1.039	0.506	4.214	0.040	2.826	1.048-7.622

Univariate analysis of clinical characteristics in patients with or without depression

Depressive symptoms were identified in 69 patients. Univariate analysis revealed significant between-group differences (P < 0.05) in marital status, monthly income, disease duration, and disease severity. No significant associations were observed for gender, age, BMI, education level, residence, multimorbidity, or family medical history (P > 0.05; Table 6).

Table 6 Univariate analysis of clinical characteristics in patients with or without depression.

	Depression (n = 69)	Non-depression (n = 54)	χ2/t	P value
Gender			2.726	0.099
Male	41	24
Female	28	30
Age	66.09 ± 3.98	64.85 ± 3.63	1.782	0.077
Body mass index	22.69 ± 2.23	23.23 ± 2.01	0.388	0.167
Education level			1.223	0.543
Junior high school or below	24	15
Senior high school, secondary school, or college	30	23
University or above	15	16
Marital status			8.504	0.014
Single	8	16
Married	34	27
Divorced or widowed	27	11
Residence			0.895	0.344
Urban	49	34
Rural	20	20
Monthly income (yuan)			10.831	0.001
≤ 5000	53	26
> 5000	16	28
Disease duration (years)			11.351	0.001
≤ 5	41	47
> 5	28	7
Disease severity (Hoehn and Yahr grading)			13.880	0.001
Mild	12	18
Moderate	33	32
Severe	24	4
Multimorbidity			0.022	0.883
Yes	49	39
No	20	15
Family medical history			1.145	0.285
Yes	4	6
No	65	48

Analysis of influencing factors for depressive symptoms

Variables with significant differences in univariate comparisons were included in a multivariate logistic regression, with depression status (0: Absent, 1: Present) as the dependent variable. A monthly income ≤ 5000 RMB was identified as a significant risk factor for depression (HR = 3.038, P = 0.013). Severe disease, compared with mild disease, was also strongly associated with higher depression risk (HR = 7.289, P = 0.005). Interestingly, a disease duration of > 5 years served as a protective factor against depression (HR = 0.264, P = 0.006). The results are summarized in Table 7.

Table 7 Analysis of influencing factors for depression in elderly patients with Parkinson's disease.

Variable	β	SE	Wald	P value	Hazard ratio	95%CI
Constant	-0.038	0.610	0.004	0.950	0.963	-
Marital status (0: Single)	-	-	4.123	0.127	-	-
1: Married	-1.202	0.620	3.761	0.052	0.300	0.089-1.013
2: Divorced or widowed	-0.750	0.495	2.263	0.132	0.472	0.178-1.255
Monthly income (0: > 5000, 1: ≤ 5000)	1.111	0.449	6.129	0.013	3.038	1.260-7.322
Disease duration (0: ≤ 5, 1: > 5)	-1.333	0.486	7.527	0.006	0.264	0.102-0.683
Disease severity (0: Mild)	-	-	8.620	0.013	-	-
1: Moderate	0.360	0.506	0.507	0.477	1.434	0.532-3.864
2: Severe	1.986	0.705	7.929	0.005	7.289	1.829-29.049

Association between anxiety, depression, and fatigue severity

Significant positive correlations were observed between anxiety/depression scores and fatigue severity (P < 0.05). Both physical and mental fatigue subscales demonstrated strong associations with higher anxiety and depression scores, indicating that psychological distress was associated with increased fatigue severity (Table 8).

Table 8 Correlation between anxiety, depression, and fatigue severity.

	Beck Anxiety Inventory		Geriatric Depression Scale
	r value	P value	r value	P value
Fatigue severity	0.319	0.0003	0.376	< 0.0001
Physical fatigue	0.263	0.003	0.256	0.004
Mental fatigue	0.227	0.011	0.337	0.0001

DISCUSSION

PD predominantly affects middle-aged and elderly populations, with the incidence steadily rising in aging societies[22]. Anxiety and depression represent major neuropsychiatric manifestations in patients with PD, increasing caregiver dependence and placing heavy burdens on both patients and their families. Current evidence links these mood disturbances to dysregulation of cerebral neurotransmitters. Importantly, patients with PD exhibit substantially higher rates of comorbid anxiety and depression than the general population, with symptoms emerging at any disease stage[23]. In our study cohort of 123 patients, 79 (64.2%) and 69 (56.1%) patients exhibited anxiety and depression, respectively, underscoring the significant psychological morbidity in this population.

The pathophysiological mechanisms underlying anxiety and depression in PD remain incompletely understood although research continues to advance. Evidence increasingly supports shared neurobiological pathways linking PD-related mood disturbances with motor symptoms. Our univariate and multivariate analyses identified low monthly income and greater disease severity as independent risk factors for both anxiety and depression. Socioeconomic advantage likely facilitates access to specialized care, advanced therapeutics, and comprehensive disease management, which collectively reduce symptom burden, improve quality of life, and mitigate psychological distress. Conversely, progressive disease severity strongly correlates with worsening anxiety and depression, reflecting a bidirectional relationship between motor and neuropsychiatric manifestations. This interaction is consistent with findings that PD-associated depression correlates with impaired executive and multi-domain cognitive performance, particularly in subcortical functions, including verbal fluency, executive control, visuospatial processing, and memory retrieval, while orientation, memory storage, and core language abilities are relatively preserved[24,25]. Depression in patients with PD is also associated with accelerated cognitive decline and motor deterioration[26]. Growing evidence suggests that neuropsychiatric complications – including depression, anxiety, and cognitive impairment – are linked to neurochemical imbalances and structural changes in the brain of patients with PD. Specifically, PD patients with comorbid depression exhibit marked reductions in dopaminergic and noradrenergic innervation within key limbic and cognitive regulatory regions, including the anterior cingulate cortex, thalamus, ventral striatum, amygdala, and locus coeruleus. These disruptions likely underlie the observed correlation between cognitive dysfunction severity and the presence of anxiety and depressive symptoms, mediated by complex, synergistic mechanisms[27,28]. Interestingly, our analysis revealed that longer disease duration paradoxically served as a protective factor against depression while simultaneously increasing the risk of anxiety. Generally, disease progression – with tremors, rigidity, and bradykinesia – impairs independence, fosters caregiver reliance, and intensifies psychological distress such as loneliness and helplessness. Over time, the cumulative disease burden – encompassing physical disability, declining social function, and reduced quality of life – would theoretically heighten the vulnerability to mood disorders. The protective effect of longer duration on depression in our cohort may instead reflect sampling bias, limited statistical power, or unmeasured confounders. Additionally, multimorbidity emerged as a significant risk factor for anxiety. Older PD patients frequently present with comorbidities, such as hypertension, dyslipidemia, and diabetes, each with distinct prognostic implications. The additive psychological burden of managing multiple chronic illnesses likely amplifies health-related anxiety, further compromising the emotional well-being of this population.

Our investigation into fatigue revealed that all PD patients experienced varying degrees of fatigue, attributable to multiple factors. Elderly individuals often present with chronic comorbidities, whereas age-related organ decline reduces tolerance to physical stress. Progressive neurodegeneration in patients with PD is irreversible, producing persistent physical, psychological, and social distress throughout the disease course. Accordingly, chronic fatigue has been recognized as a hallmark symptom[29]. A significant positive correlation was observed between fatigue severity and anxiety and depression severity. One study reported that patients in advanced Hoehn and Yahr stages exhibited greater fatigue and higher depressive symptoms[30]. Similarly, assessments using the Hospital Anxiety and Depression Scale and the Non-Motor Symptoms Scale confirmed that elevated anxiety and depression levels were strongly associated with fatigue[31]. Notably, a bidirectional relationship exists between fatigue and emotional state: Persistent fatigue provokes emotional instability, whereas emotional distress intensifies physical fatigue. Physical fatigue disrupts neurotransmitter balance by reducing serotonin secretion – critical for mood regulation – and elevating cortisol, a stress hormone. These physiological changes heighten reactivity to external stimuli, thereby predisposing individuals to emotional fluctuations. Conversely, sustained negative emotions, such as anxiety and depression, impair sleep, weaken immune function, and increase energy demands. For example, sleep deprivation compromises prefrontal cortex activity, the brain region governing emotional regulation, thereby intensifying fatigue.

This study has several limitations. First, this was a single-center study with a small sample size, limiting generalizability to the wider PD population, particularly in rural or economically disadvantaged groups. Second, the retrospective design precluded the collection of additional clinical variables, introducing potential bias. Third, the absence of long-term follow-up prevented the assessment of emotional changes over time. Further multicenter studies with a multi-center, larger cohort and extended follow-up are warranted to validate these findings.

CONCLUSION

In conclusion, patients with PD exhibit heightened susceptibility to anxiety and depression, both of which correlate positively with fatigue severity. These results highlight the need for enhanced psychological support in clinical care to strengthen emotional resilience and reduce fatigue-related burden in elderly PD patients.