Epidemiology and associated factors of screening-identified dysphagia risk in psychiatric inpatients

Abstract

BACKGROUND

Dysphagia is a clinically significant but often overlooked issue in psychiatric inpatients, with limited evidence on its associated risk factors.

AIM

To investigate the epidemiology and risk factors of moderate-to-severe risk of dysphagia in psychiatric inpatients.

METHODS

A retrospective analysis of 2414 psychiatric inpatients screened using a standardized assessment was conducted. Patients were stratified into low-risk and moderate-to-severe risk groups. Univariate analysis, multivariate logistic regression, and receiver operating characteristic curve analysis were performed.

RESULTS

In this study, 2.36% of psychiatric inpatients were classified as having moderate-to-severe dysphagia risk. Independent associations with dysphagia risk included age (β = 0.076, P < 0.001), married status (β = -1.389, P = 0.005), schizophrenia (β = 1.714, P = 0.027), intellectual disability (β = 2.119, P = 0.029), thyroid stimulating hormone (β = 0.053, P = 0.009), and length of hospital stay (β = 0.002, P = 0.030). Receiver operating characteristic analysis showed that age demonstrated moderate discriminative ability (area under the curve = 0.715).

CONCLUSION

Among psychiatric inpatients, 2.36% were at moderate-to-severe risk of dysphagia. Factors associated with dysphagia risk included age, schizophrenia, intellectual disability, married status, length of hospital stay, and thyroid stimulating hormone levels.

Key Words: Dysphagia risk; Psychiatric inpatients; Age; Diagnosis; Thyroid stimulating hormone; Marital status; Length of hospital stay

Core Tip: This retrospective study evaluated the risk of dysphagia in 2414 psychiatric inpatients and found that 2.36% were classified as having moderate-to-severe risk of dysphagia. Dysphagia risk was independently associated with older age and those diagnosed with schizophrenia or intellectual disability, with additional associations involving thyroid stimulating hormone levels, marital status, and length of hospital stay. These findings provide epidemiological evidence to support screening-identified risk stratification and underscore the importance of increasing awareness and targeted assessment of dysphagia in psychiatric inpatient settings.

INTRODUCTION

Swallowing is a core physiological process that protects the respiratory system and enables the body to take in nutrients and necessary fluids[1]. Dysphagia is defined as the subjective difficulty in transporting food or liquid from the oral cavity to the stomach[2]. Previous literature has reported a dysphagia prevalence of approximately 9%-10% in the general population[3]. Its adverse consequences include malnutrition, dehydration, aspiration pneumonia, choking, and even death[4,5]. Based on etiology, dysphagia can be classified into three categories: Neurogenic, structural, and psychogenic[6].

Dysphagia in neurological disorders has received significant clinical attention due to its high incidence and potential severe outcomes[7,8]. Stroke is the most common cause. Approximately 42% of patients with acute stroke experience dysphagia[9], and this condition persists in 20% to 43% of them three months later[10]. Furthermore, dysphagia is also frequently observed in other neurological disorders, such as Parkinson's disease[11], Alzheimer’s disease[12], and multiple sclerosis[13]. These figures typically represent clinically diagnosed dysphagia based on instrumental assessments or expert evaluation, and its prevalence is influenced by the disease stage, duration, and assessment methods. The current evidence indicates that age, comorbidity burden, and disease classification are significant determinants of neurogenic dysphagia[14]. Against this backdrop, the continuous innovation in research methods and technologies is driving the improvement of therapeutic strategies[15].

Despite the increasing reports of dysphagia and associated choking incidents among patients with psychiatric disorders in recent years, this serious complication has not received sufficient attention. Previous studies using diverse assessment methods, including clinical diagnosis, bedside examination, and screening scales, have reported prevalence estimates of swallowing abnormalities ranging from 9% to 46%, with mortality rates of 0.7%-6%, approximately twice those of the general population[16,17]. These estimates vary substantially depending on study populations, diagnostic criteria, and assessment instruments. Patients with severe mental illnesses, such as schizophrenia, bipolar disorder, and major depressive disorder, frequently present with severe and persistent dysphagia, which has a reported prevalence of up to 32% among inpatients. The underlying causes are associated with the use of psychotropic medications and behavioral manifestations related to the illnesses themselves[17,18]. Meanwhile, extrapyramidal symptoms induced by antipsychotic medications are also a recognized risk factor for dysphagia[19,20]. Paradoxically, the use of anticholinergic agents to control these symptoms can further compromise swallowing safety and efficiency, as they reduce saliva production and impair cognitive function[20,21]. In clinical practice, especially in large-scale or retrospective studies, dysphagia is often assessed using screening instruments that identify individuals at increased risk rather than providing a definitive clinical diagnosis[22]. Furthermore, the widespread lack of standardized and routinely implemented dysphagia risk screening protocols in psychiatric wards often leads to the oversight or delay in identifying at-risk patients. The resulting complications can prolong hospitalization, increase medical costs, and thereby exacerbate the underlying psychiatric disorder[23,24].

Based on these considerations, this retrospective study aimed to investigate the proportion of screening-identified dysphagia risk among psychiatric inpatients using a standardized screening tool and to explore its associated factors. Previous studies have indicated that prevalence estimates derived from screening instruments are often lower than those based on clinical diagnosis or instrumental assessments. Therefore, we hypothesized that the proportion of psychiatric inpatients identified as having dysphagia risk would be lower than previously reported prevalence estimates based on clinical diagnosis. In addition, we further hypothesized that older age (≥ 60 years), comorbid somatic diseases, psychiatric diagnostic categories, and indicators of illness chronicity would be associated with an increased risk of dysphagia.

MATERIALS AND METHODS

Study design and patients

This retrospective study included patients who were admitted to Shandong Daizhuang Hospital between January 2020 and August 2024. During routine inpatient care, patients with clinically suspected swallowing difficulties were screened for dysphagia risk using a standardized scale. All enrolled patients were selected through a systematic search of electronic medical records within the inpatient database.

A total of 8528 inpatients with suspected dysphagia were screened during the study period. After excluding 267 patients with incomplete data on key variables, the remaining missing values were handled using multiple imputation, a widely recommended method to minimize bias and ensure robust statistical estimates. Additionally, 5847 patients were excluded due to a primary diagnosis of neurological disorder or neurological comorbidities. The final study cohort included 2414 patients who met all the inclusion criteria and had complete data available for analysis. Details of the patient selection process are shown in Figure 1.

Figure 1  Flowchart of the patient selection process.

The study population encompassed the following categories of mental disorders: Depression (F32/F33), schizophrenia (F20), bipolar disorder (F31), intellectual disabilities (F70-F79), dissociative disorders (F44), anxiety disorders (F41), mental and behavioral disorders due to use of alcohol (F10), as well as other psychiatric conditions including but not limited to sleep disorders (F51), somatization disorder (F45), and behavioral and emotional disorders with onset usually occurring in childhood and adolescence (F90-F98).

Clinical assessment

Demographic and clinical data were collected from patients’ medical records, including sex, age, occupation, marital status, age of onset, duration of illness, length of hospital stay, medication history, and comorbid physical illnesses. All data were extracted from admission notes and hospitalization records. Consistent with age stratification approaches commonly used in clinical epidemiological studies, participants were categorized into four age groups: Children (0-17 years), young adults (18-44 years), middle-aged adults (45-59 years), and older adults (≥ 60 years)[25].

The Choking Risk Assessment Scale (CRA) employed in this study is a structured screening tool routinely used in psychiatric nursing practice. Nurse-administered swallowing screening tools based on observable clinical risk factors have demonstrated acceptable reliability and discriminative ability in identifying patients at increased risk of dysphagia, supporting the use of such screening approaches in clinical research[26]. All CRA results completed during hospitalization were extracted from medical records.

The content of the scale includes history of choking during eating, difficulty swallowing, compulsive eating and binge eating, extrapyramidal side effects of antipsychotic medications, organic brain disease, history of seizures, intellectual disability, age ≥ 80 years, and consciousness impairment. The CRA uses a cumulative scoring system to stratify risk severity. A total score ≤ 3 indicates low risk, scores of 4-6 indicate moderate risk, and scores ≥ 7 indicate high risk.

Blood sample collection

Peripheral blood samples were collected at the assessment time point in the morning after an overnight fast and analyzed by the clinical laboratory department to obtain complete blood count data. The following cellular counts were retrieved: Neutrophils, monocytes, lymphocytes and platelets. Five inflammation-related ratios were then calculated: Platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, neutrophil-to-monocyte ratio, monocyte-to-lymphocyte ratio, systemic immune-inflammation index[27-29]. Serum thyroid function parameters were also measured, including triiodothyronine (T3), thyroxine (T4), free T4, free T3, and thyroid stimulating hormone (TSH).

Statistical analysis

Statistical analysis was performed using IBM SPSS Statistics, version 27.0. Descriptive statistics were used to summarize demographic and clinical data, presented as mean ± SD for continuous variables and as n (%) for categorical variables. Between-group comparisons were conducted using the independent-samples t-test or the Mann-Whitney U test for continuous variables, and the χ² test or Fisher’s exact test for categorical variables, as appropriate. Given the retrospective and exploratory nature of this study, all variables were included in univariate logistic regression analysis to explore potential associations with dysphagia risk and ensure that relevant factors were not omitted. Subsequently, variables with statistical significance were included in the multivariate logistic regression model to identify independent factors associated with dysphagia risk. The receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of these independent factors, and the area under the curve (AUC) was calculated. The significance of results was defined as P < 0.05.

RESULTS

Demographic information

A total of 2414 patients were analyzed based on the CRA. Patients were divided into two groups: Those with scores of 3 or less were classified into the low-risk group (n = 2357), while those with scores of 4 or above were combined into the moderate-to-severe risk group (n = 57) because of the small number of patients in the high-risk group. Based on this grouping, the proportion of patients classified as having moderate-to-severe dysphagia risk was calculated to be 2.36%. This proportion reflects a screening-identified risk classification, rather than the prevalence or incidence of clinically diagnosed dysphagia.

There were significant between-group differences regarding age (Z = -5.56, P < 0.001), age groups (χ² = 34.37, P < 0.001), occupation (χ² = 15.61, P = 0.008), marital status (χ² = 12.24, P = 0.007), and education (χ² = 9.65, P = 0.047). In addition, no significant differences were found between the two groups in terms of sex (χ² = 0.06, P = 0.812) and BMI (Z = -0.33, P = 0.745). Detailed demographic characteristics are presented in Table 1.

Table 1 Clinical and demographic characteristics of the low-risk group and moderate-to-severe risk group, n (%).

Characteristics	Low-risk group (n = 2357)	Moderate-to-severe risk group (n = 57)	Z/χ2	P value
Sex			0.06	0.812
Male	905 (38.4)	21 (36.8)
Female	1452 (61.6)	36 (63.2)
Age (year), mean ± SD	42.38 ± 18.40	58.81 ± 21.66	-5.56	< 0.001a
Age group (years)			34.37	< 0.001a
0-17	239 (10.1)	2 (3.5)
18-44	1072 (45.5)	12 (21.1)
45-59	612 (26.0)	16 (28.1)
≥ 60	434 (18.4)	27 (47.4)
Marital status			12.24	0.007a
Unmarried	658 (27.9)	10 (17.5)
Married	1588 (67.4)	43 (75.4)
Divorced	87 (3.7)	1 (1.8)
Widowed	24 (1.0)	3 (5.3)
Occupation			15.61	0.008a
Student	324 (13.7)	2 (3.5)
Worker	63 (2.7)	2 (3.5)
Farmer	321 (13.6)	10 (17.5)
Employee	216 (9.2)	10 (17.5)
Unemployed person	1337 (56.7)	27 (47.4)
Retiree	96 (4.1)	6 (10.5)
Education			9.65	0.047a
Illiteracy	332 (14.1)	16 (28.1)
Elementary school	529 (22.4)	12 (21.1)
Junior high school	808 (34.3)	18 (31.6)
Senior high school	410 (17.4)	7 (12.3)
University	278 (11.8)	4 (7.0)
BMI (kg/m2)	24.49 ± 6.08	24.50 ± 3.51	-0.33	0.745
Length of hospital stay (days), mean ± SD	59.81 ± 85.55	98.12 ± 220.49	-1.10	0.271
Duration of illness (months), mean ± SD	109.92 ± 125.85	138.22 ± 143.62	-0.96	0.337
Number of episodes, mean ± SD	2.64 ± 2.11	3.05 ± 2.52	-1.35	0.177
Diagnosis			10.02	0.187
Depression	523 (22.2)	17 (29.8)
Schizophrenia	529 (22.4)	18 (31.6)
Bipolar disorder	519 (22.0)	11 (19.3)
Intellectual disabilities	124 (5.3)	3 (5.3)
Dissociative disorders	161 (6.8)	3 (5.3)
Anxiety disorders	51 (2.2)	2 (3.5)
Mental and behavioral disorders due to use of alcohol	286 (12.1)	2 (3.5)
Other mental disorders	164 (7.0)	1 (2.2)
Medication
Antipsychotics	1827 (77.5)	47 (82.5)	0.78	0.376
Antidepressants	936 (39.7)	22 (38.6)	0.29	0.865
Anxiolytics	280 (11.9)	11 (19.3)	2.89	0.089
Mood stabilizers	937 (39.8)	16 (28.1)	3.18	0.075
Antiepileptic drugs	509 (21.6)	12 (21.1)	0.01	0.922
Benzodiazepines	862 (36.6)	22 (38.6)	0.10	0.754
Somatic comorbidity
Hypertension	341 (14.5)	13 (22.8)	3.08	0.079
Coronary heart disease	181 (7.7)	14 (24.6)	21.33	< 0.001a
Myocardial ischemia	379 (16.1)	11 (19.3)	0.43	0.514
Inflammatory indicators, mean ± SD
NLR	2.32 ± 1.84	2.08 ± 1.20	-1.01	0.311
PLR	145.85 ± 85.11	135.06 ± 60.83	-0.91	0.365
MLR	0.27 ± 0.20	0.24 ± 0.12	-0.70	0.483
NMR	9.84 ± 6.20	9.85 ± 5.34	-0.06	0.949
SII	522.48 ± 490.67	474.87 ± 299.28	-1.24	0.215
Thyroid function, mean ± SD
T3	1.58 ± 0.40	1.54 ± 0.31	-0.75	0.457
T4	96.18 ± 28.53	104.00 ± 28.22	-2.09	0.036a
FT4	16.12 ± 3.96	16.46 ± 3.34	-1.42	0.156
FT3	4.78 ± 1.06	4.56 ± 0.63	-1.56	0.118
TSH	2.54 ± 3.05	6.80 ± 22.04	-1.06	0.291

^aP < 0.05.

BMI: Body mass index; PLR: Platelet-lymphocyte ratio; NLR: Neutrophil-lymphocyte ratio; NMR: Neutrophil-monocyte ratio; MLR: Monocyte-lymphocyte ratio; SII: Systemic immune-inflammation index; T3: Triiodothyronine; T4: Thyroxine; FT4: Free thyroxine; FT3: Free triiodothyronine; TSH: Thyroid stimulating hormone.

Clinical characteristics and medication use

In terms of somatic comorbidity, there were significant differences in coronary heart disease (χ² = 21.33, P < 0.001), but no significant differences were observed in hypertension (χ² = 3.08, P = 0.079) or myocardial ischemia (χ² = 0.43, P = 0.514). No significant differences between groups were observed regarding length of hospital stay (Z = -1.10, P = 0.271), duration of illness (Z = -0.96, P = 0.337), number of episodes (Z = -1.35, P = 0.177), or diagnostic categories (χ² = 10.02, P = 0.187). No significant differences were found between the two groups in medication use (all P > 0.05; Table 1).

Inflammatory indicators and thyroid function

Regarding thyroid function, there were significant between-group differences regarding T4 (Z = -2.09, P = 0.036). No significant differences were observed between the two groups in T3 (Z = -0.75, P = 0.457), free T4 (Z = -1.42, P = 0.156), free T3 (Z = -1.56, P = 0.118), or TSH (Z = -1.06, P = 0.291).

Inflammatory indicators showed no significant differences between groups, including neutrophil-to-lymphocyte ratio (Z = -1.01, P = 0.311), platelet-to-lymphocyte ratio (Z = -0.91, P = 0.365), monocyte-to-lymphocyte ratio (Z = -0.70, P = 0.483), neutrophil-to-monocyte ratio (Z = -0.06, P = 0.949), and systemic immune-inflammation index (Z = -1.24, P = 0.215). Comprehensive data on inflammatory indicators and detailed thyroid function are provided in Table 1.

Univariate logistic regression analysis

Univariate logistic regression analysis revealed that among demographic variables, age (β = 0.047, P < 0.001), age over 60 years (β = 2.006, P = 0.007), widowed status (β = 2.107, P = 0.002), and occupations including farmer (β = 1.619, P = 0.038), employee (β = 2.015, P = 0.010), and retiree (β = 2.315, P = 0.005) were significantly associated with dysphagia risk. In terms of educational attainment, junior high school (β = -0.772, P = 0.027), senior high school (β = -1.038, P = 0.024), and university education (β = -1.209, P = 0.032) also showed significant correlations. In contrast, no significant associations were observed for sex or body mass index (all P > 0.05).

Regarding clinical characteristics, prolonged hospital stays (β = 0.002, P = 0.005), as well as diagnoses of depression (β = 1.536, P = 0.041), schizophrenia (β = 1.582, P = 0.035), and comorbid coronary heart disease (β = 1.364, P < 0.001), were associated with a higher dysphagia risk. However, disease duration, number of episodes, medication therapy, and other physical comorbidities did not demonstrate statistically significant associations (P > 0.05).

T4 (β = 0.008, P = 0.039) and TSH (β = 0.042, P < 0.001) in thyroid function tests were identified as significant predictors. However, inflammatory indicators showed no significant relationship with dysphagia risk. The complete univariate analysis results are presented in Table 2.

Table 2 Univariate logistic regression analysis of variables associated with moderate-to-severe dysphagia risk.

Characteristics	β	SE	OR	95%CI	P value
Sex	0.066	0.278	1.068	0.620-1.842	0.812
Age	0.047	0.008	1.048	1.033-1.064	< 0.001a
Age groups
0-17	-	-	-	1.00	-
18-44	0.291	0.767	1.338	0.297-6.016	0.704
45-59	1.139	0.754	3.124	0.713-13.691	0.131
≥ 60	2.006	0.737	7.434	1.753-31.534	0.007a
Marital status
Unmarried	-	-	-	1.00	-
Married	0.578	0.354	1.782	0.890-3.567	0.103
Divorced	-0.279	1.055	0.756	0.090-5.980	0.791
Widowed	2.107	0.690	8.225	2.126-31.822	0.002a
Occupation
Student	-	-	-	1.00	-
Worker	1.638	1.009	5.143	0.711-37.191	0.105
Farmer	1.619	0.779	5.047	1.097-23.214	0.038a
Employ	2.015	0.780	7.500	1.627-34.564	0.010a
Unemployed person	1.185	0.735	3.272	0.774-13.828	0.107
Retiree	2.315	0.825	10.125	2.011-50.980	0.005a
Education
Illiteracy	-	-	-	1.00	-
Elementary school	-0.754	0.388	0.471	0.220-1.007	0.052
Junior high school	-0.772	0.350	0.462	0.233-0.917	0.027a
Senior high school	-1.038	0.459	0.354	0.144-0.871	0.024a
University	-1.209	0.565	0.299	0.099-0.903	0.032a
BMI	< 0.001	0.022	1.000	0.958-1.044	0.989
Length of hospital stay	0.002	0.001	1.002	1.001-1.003	0.005a
Disease duration	0.002	0.001	1.002	1.000-1.003	0.096
Number of episodes	0.073	0.050	1.075	0.975-1.186	0.144
Diagnosis
Mental and behavioral disorders due to use of alcohol	-	-	-	1.00	-
Depression	1.536	0.751	4.648	1.066-20.261	0.041a
Schizophrenia	1.582	0.749	4.866	1.121-21.119	0.035a
Bipolar disorder	1.109	0.772	3.031	0.667-13.768	0.151
Intellectual disabilities	1.241	0.919	3.460	0.571-20.963	0.177
Dissociative disorders	0.980	0.918	2.665	0.441-16.113	0.286
Anxiety disorders	1.724	1.011	5.608	0.772-40.717	0.088
Other mental disorders	-0.137	1.229	0.872	0.078-9.690	0.911
Medication
Antipsychotics	0.310	0.352	1.363	0.684-2.717	0.378
Antidepressants	-0.047	0.275	0.954	0.556-1.637	0.865
Anxiolytics	0.573	0.342	1.774	0.908-3.465	0.093
Mood stabilizers	-0.525	0.298	0.591	0.330-1.060	0.078
Antiepileptic drugs	-0.032	0.329	0.968	0.508-1.844	0.922
Benzodiazepines	0.086	0.275	1.090	0.635-1.870	0.754
Somatic comorbidity
Hypertension	0.557	0.321	1.745	0.930-3.274	0.083
Coronary heart disease	1.364	0.317	3.911	2.100-7.283	< 0.001a
Myocardial ischemia	0.222	0.340	1.248	0.641-2.431	0.515
Inflammatory indicators
NLR	-0.105	0.102	0.900	0.737-1.100	0.900
PLR	-0.002	0.002	0.998	0.994-1.002	0.337
MLR	-1.105	0.984	0.331	0.048-2.276	0.261
NMR	< 0.001	0.022	1.000	0.959-1.044	0.987
SII	-0.001	< 0.001	0.999	0.999-1.000	0.214
Thyroid function
T3	-0.288	0.365	0.750	0.367-1.532	0.429
T4	0.008	0.004	1.008	1.000-1.016	0.039a
FT4	0.019	0.030	1.020	0.961-1.082	0.522
FT3	-0.300	0.176	0.741	0.525-1.045	0.087
TSH	0.042	0.012	1.043	1.019-1.068	< 0.001a

^aP < 0.05.

BMI: Body mass index; PLR: Platelet-lymphocyte ratio; NLR: Neutrophil-lymphocyte ratio; NMR: Neutrophil-monocyte ratio; MLR: Monocyte-lymphocyte ratio; SII: Systemic immune-inflammation index; T3: Triiodothyronine; T4: Thyroxine; FT4: Free thyroxine; FT3: Free triiodothyronine; TSH: Thyroid stimulating hormone; OR: Odds ratio; CI: Confidence interval.

Multivariate logistic regression analysis

Based on the results of the univariate logistic regression analysis, significant variables, including age, age group, marital status, occupation, education, length of hospital stay, diagnosis, coronary heart disease, T4 and TSH were included in the multivariate logistic regression analysis to explore their influence on the dysphagia risk. Collinearity diagnostics indicated that age group was excluded due to a variance inflation factor > 5. Among the remaining variables, the minimum variance inflation factor was 1.003 and the maximum was 2.233, indicating that there was no multicollinearity among the independent variables.

Multivariate logistic regression analysis was performed using forward stepwise selection with an entry criterion of P < 0.05. Only variables retained in the final model are presented. The regression model indicated that age, marital status, length of hospital stay, diagnosis, and TSH were independently associated with dysphagia risk, whereas occupation, education level, coronary heart disease, and T4 were not significantly associated with this risk. Each one-year increase in age was associated with a 7.9% higher risk [odds ratio (OR) = 1.079, 95% confidence interval (CI): 1.055-1.104; β = 0.076; P < 0.001]. Regarding marital status, compared with unmarried patients, those who were married had a significantly lower risk (OR = 0.259, 95%CI: 0.095-0.652; β = -1.389; P = 0.005), while divorced (P = 0.113) and widowed (P = 0.071) showed no significant association. Each additional day of hospital stay was associated with a slight increase in dysphagia risk (OR = 1.002, 95%CI: 1.000-1.003; β = 0.002; P = 0.030). Regarding diagnostic categories, compared with mental and behavioral disorders due to use of alcohol, schizophrenia (OR = 5.550, 95%CI: 1.214-25.384; β = 1.714; P = 0.027) and intellectual disabilities (OR = 8.319, 95%CI: 1.247-55.477; β = 2.119; P = 0.029) were independently associated with an elevated risk. Depression (P = 0.219), bipolar disorder (P = 0.099), dissociative disorders (P = 0.462), anxiety disorders (P = 0.968), and other mental disorders (P = 0.570) showed no significant association. Each 1 mIU/L increment in TSH was associated with a 5.4% increase in dysphagia risk (OR = 1.054, 95%CI: 1.013-1.097; β = 0.053; P = 0.009) (Table 3).

Table 3 Multivariate logistic regression analysis of variables associated with moderate-to-severe dysphagia risk.

Characteristics	β	SE	OR	95%CI	P value
Age	0.076	0.012	1.079	1.055-1.104	< 0.001a
Marital status
Unmarried	-	-	-	1.00	-
Married	-1.389	0.490	0.259	0.095-0.652	0.005a
Divorced	-1.749	1.104	0.174	0.020-1.516	0.113
Widowed	-1.728	0.955	0.178	0.027-1.156	0.071
Length of hospital stay	0.002	0.001	1.002	1.000-1.003	0.030
Diagnosis
Mental and behavioral disorders due to use of alcohol	-	-	-	1.00	-
Depression	0.964	0.785	2.622	0.563-12.206	0.219
Schizophrenia	1.714	0.776	5.550	1.214-25.384	0.027a
Bipolar disorder	1.308	0.793	3.700	0.783-17.493	0.099
Intellectual disabilities	2.119	0.968	8.319	1.247-55.477	0.029a
Dissociative disorders	0.699	0.950	2.012	0.313-12.943	0.462
Anxiety disorders	-0.048	1.195	0.953	0.091-9.920	0.968
Other mental disorders	-0.717	1.262	0.488	0.041-5.791	0.570
Thyroid function
TSH	0.053	0.02	1.054	1.013-1.097	0.009a

^aP < 0.05.

The bold values indicate statistically significant associations (P < 0.05). OR: Odds ratio; CI: Confidence interval; TSH: Thyroid stimulating hormone.

In the between-group analyses, TSH levels and diagnostic categories were not significantly different (P = 0.291 and P = 0.187), but both were significantly associated with dysphagia risk in univariable logistic regression (P < 0.05). This difference reflects the distinct focus of the two approaches: Group comparisons assess crude distributional differences, whereas logistic regression evaluates risk associations with a binary outcome. Accordingly, variables may be non-significant in group comparisons yet remain eligible for inclusion in multivariable models. In contrast, coronary heart disease was significant in univariable regression but not after multivariable adjustment, indicating a confounding effect.

ROC analysis

ROC analysis was conducted for each continuous variable associated with moderate-to-severe dysphagia risk (Table 4). Age demonstrated a moderate discriminative ability, with an AUC of 0.715 (95%CI: 0.641-0.789, P < 0.001). The optimal cut-off value for age was 49.50 years, with a sensitivity of 70.2% and a specificity of 62.9%.

Table 4 Receiver operating characteristic analysis of variables associated with moderate-to-severe dysphagia risk.

Indicator	Optimal cut-off value	Sensitivity (%)	Specificity (%)	AUC	95%CI	P value
Age	49.50	70.2	62.9	0.715	0.641-0.789	< 0.001a
Length of hospital stay	33.50	57.5	57.9	0.543	0.460-0.625	0.310
Thyroid function
TSH	1.47	77.2	33.1	0.541	0.465-0.617	0.291

^aP < 0.05.

Area under the curve values closer to 0.5 indicate limited discriminative ability. AUC: Area under the curve; CI: Confidence interval; TSH: Thyroid stimulating hormone.

In contrast, length of hospital stay and TSH showed limited discriminative performance when evaluated as single predictors. The AUC for length of hospital stay was 0.543 (95%CI: 0.460-0.625, P = 0.310), with an optimal cut-off value of 33.50 days. Similarly, TSH yielded an AUC of 0.541 (95%CI: 0.465-0.617, P = 0.291), with an optimal cut-off value of 1.47 mIU/L (Figure 2).

Figure 2 Receiver operating characteristic curves for continuous predictors of moderate-to-severe dysphagia risk. TSH: Thyroid stimulating hormone.

DISCUSSION

This retrospective study observed that 2.36% of psychiatric inpatients were classified as having moderate-to-severe dysphagia risk based on a standardized screening tool. This proportion represents risk stratification based on screening thresholds, not the prevalence or incidence of clinically diagnosed dysphagia. In multivariable analyses, we identified several factors independently associated with higher risk classification, including older age, longer length of hospital stay, a primary diagnosis of schizophrenia or intellectual disability, and higher serum TSH levels. Moreover, married status emerged as a protective factor. In this context, risk-based screening may help to identify psychiatric inpatients who warrant closer attention with respect to swallowing safety.

Dysphagia has consistently been a major concern among the elderly, affecting approximately 10% to 33% of this population[30,31], and is associated with increased mortality and morbidity[32]. This study identified age as a significant predictor of moderate-to-severe dysphagia risk. Univariate regression demonstrated a significantly increased risk in individuals over 60 years old, while ROC analysis based on age as a continuous variable further suggested an age threshold for increased risk at 49.5 years. However, this cut-off should be interpreted as a statistical indicator rather than a clinical boundary. Research indicates that even in the absence of other diseases, older age itself is associated with a significant decline in swallowing function[33]. With advancing age, there is a gradual decline in both sensory sensitivity and muscular motor coordination within the oral and pharyngeal regions[31,33]. According to statistics, nearly half of nursing home residents with dysphagia develop aspiration pneumonia within 12 months, with a mortality rate as high as 45%[34-37]. Furthermore, dysphagia has been shown to prolong hospital stays (by approximately 3.8 days), increase medical costs by 33%, and substantially impair patients’ quality of life[33,38].

In terms of disease diagnosis, patients with schizophrenia and intellectual disabilities demonstrate a significantly higher independent risk of moderate-to-severe dysphagia compared with those with mental and behavioral disorders due to use of alcohol. Patients with mental and behavioral disorders due to alcohol use were selected as the reference group because this diagnosis is common in psychiatric inpatient settings and represents a clinically relevant comparison group. Research indicates that the prevalence of dysphagia is approximately 23% among individuals with schizophrenia, rising significantly to 31% in inpatient populations[39]. The increased risk of dysphagia in patients with schizophrenia is thought to be related to both disease-related factors and medication-associated adverse effects[40]. Cognitive decline associated with schizophrenia, particularly impairments in executive function and memory, may adversely affect the coordination of eating behaviors and swallowing safety, thereby reducing feeding efficiency[41-43]. At the same time, adverse effects of pharmacological treatments, such as drug-induced parkinsonism, dystonia, dry mouth, and excessive sedation, may further compromise swallowing function[44,45].

Dysphagia is also a common yet frequently overlooked serious health issue among individuals with intellectual disabilities. It is estimated that the prevalence of dysphagia in this population ranges from 8% to 11%[46]. The prevalence of dysphagia among older adults with intellectual disabilities has been reported to be as high as 43.8%[47]. Intellectual disability typically stems from congenital or early acquired brain injury. Such neurological damage not only impairs cognitive function but may also involve key regions responsible for swallowing regulation, including the brainstem, resulting in oral motor dysfunction, impaired neural control, and related neurobehavioral abnormalities[48,49]. Moreover, dysphagia in patients with intellectual disability is closely related to various factors, such as malnutrition, growth and development retardation, muscle and bone structure abnormalities[50-52].

In multivariate analysis, serum TSH remained an independent factor associated with moderate-to-severe dysphagia risk. However, ROC analysis did not demonstrate a significant discriminative ability of TSH, suggesting that its predictive value as a standalone marker is limited. Elevated TSH levels typically indicate overt or subclinical hypothyroidism. Research has suggested that thyroid dysfunction may be associated with neuromuscular abnormalities affecting muscle strength and coordination, thereby disrupting the complex sensorimotor integration required for swallowing[53,54]. In addition, some studies have reported improvement in dysphagia following thyroid hormone replacement therapy, further supporting neuromuscular incoordination as a potential underlying mechanism[53,55]. Endocrine and metabolic disturbances may also contribute to dysphagia through their effects on peripheral nerves and skeletal muscle function[56,57]. However, detailed information regarding thyroid disease diagnoses and treatment was not systematically collected in the present study; therefore, the observed association between elevated TSH levels and dysphagia risk should be regarded as a preliminary finding rather than evidence of a causal relationship.

Marital status remained statistically associated with moderate-to-severe dysphagia risk in the multivariable model, suggesting that it may partly reflect differences in social support and daily caregiving resources relevant to swallowing-related outcomes. Research indicates that higher marital quality is associated with better physical and mental health in individuals, and that older adults without a spouse have a higher risk of cognitive impairment than those with a spouse[58,59]. Marital status and social support may influence cognitive function by reducing psychological stress and promoting healthy behaviors, thereby affecting health-seeking behaviors, symptom awareness, and adherence to recommended management strategies[60-63]. Therefore, marital status may be associated with differences in dysphagia risk. Given that marital status is a categorical variable and largely represents social-context factors, its standalone predictive value is likely limited; it is better interpreted as an adjustment covariate or proxy indicator within a multivariable model.

The length of hospital stay was significantly associated with the risk of moderate-to-severe dysphagia in the multivariable analysis. Previous studies have reported that dysphagia is associated with an average extension of hospital stay by approximately 3.8 days, as well as increased healthcare utilization among hospitalized patients[23,38]. Furthermore, delayed identification and management of dysphagia may increase the risk of complications, further prolonging hospitalization[64]. Conversely, a longer duration of hospitalization may enhance the likelihood of dysphagia recognition ultimately contributing to improved management of the condition[23]. Therefore, the observed association between length of hospital stay and dysphagia risk is likely bidirectional.

In this study, the proportion of patients classified as having moderate-to-severe dysphagia risk was relatively lower than that reported in previous studies, which is consistent with our study hypothesis. Prior research has indicated that screening instruments generally identify fewer cases than diagnostic or instrumental assessments and therefore primarily reflect risk stratification rather than confirmed dysphagia[65]. In addition, patients with primary or comorbid neurological disorders, who typically carry a higher risk of swallowing function impairment, were excluded from the present study, a criterion that may have reduced the yield of dysphagia risk detection to some extent. The retrospective study design and reliance on a single screening tool may also have limited the identification of milder or transient swallowing problems[56,65]. Moreover, information on psychiatric symptom severity, psychotropic medication dosage, and cognitive function was not systematically available in the medical records, which may have limited the identification of other potential predictors of dysphagia risk. Future prospective studies with more rigorous designs are needed to further validate these findings and to provide stronger evidence for clinical dysphagia risk assessment.

CONCLUSION

This study found that 2.36% of psychiatric inpatients were classified as having moderate-to-severe risk of dysphagia based on the screening assessment. Statistical analysis identified age, primary diagnosis, TSH level, marital status, and length of hospital stay as independent risk factors for dysphagia in this population. Based on these findings, dysphagia risk screening may be prioritized among older psychiatric inpatients, particularly those diagnosed with schizophrenia or intellectual disability. Further prospective studies are needed to verify these associations and explore the underlying mechanisms.

ACKNOWLEDGEMENTS

The authors thank Ms. Xia Liu for her biostatistical review of this manuscript and for providing the certificate of biostatistical review.