Correlation of fourteen subjectively reported adverse mental states with insomnia: Gender differences in a cross-sectional study

Abstract

BACKGROUND

Although numerous studies indicate that adverse mental states negatively affect sleep, few have systematically analyzed the association between various adverse mental states and insomnia. Furthermore, potential gender differences within such associations remain underexplored.

AIM

To investigate gender differences in correlations between adverse mental states and insomnia, and identify gender-specific risk factors for severe insomnia.

METHODS

A multicenter cross-sectional survey method was employed. A total of 2009 adult participants (2019-2021) completed an insomnia clinical assessment form. The form covered sociodemographic information, 14 subjectively reported adverse mental states, core insomnia symptoms, and the Pittsburgh Sleep Quality Index.

RESULTS

Depression, apathy, fatigue, impatience-irritability, grief, forgetfulness, and slow response were significantly associated with insomnia. Timidity, indecision, suspiciousness, catatonia, decreased willpower, taciturnity, and inattention showed no significant association with insomnia. Grief (r = 0.062, P < 0.05), fatigue (r = 0.065, P < 0.05), and slow response (r = 0.080, P < 0.01) were correlated with increased time to fall asleep in women; no mental factors influencing sleep latency were identified in men. Apathy (r = 0.073, P < 0.05) was associated only with increased nocturnal awakenings in men, but not in women. Impatience-irritability was a risk factor for severe insomnia exclusively in men (odds ratio = 1.62, 95%CI: 1.13-2.32, P = 0.009), while grief was a risk factor specifically for women (odds ratio = 1.83, 95%CI: 1.20-2.80, P = 0.005).

CONCLUSION

Not all adverse mental states are significantly associated with insomnia, and the correlation between adverse mental states and insomnia varies according to gender and specific sleep dimensions.

Key Words: Cross-sectional study; Gender differences; Insomnia; Adverse mental states; Risk factors

Core Tip: This cross-sectional study included 2009 adult patients (≥ 18 years old) with insomnia in China. The study used the Pittsburgh Sleep Quality Index and an insomnia clinical assessment form to evaluate the correlation between adverse mental states and insomnia. Results indicated that not all adverse mental states were significantly associated with insomnia. Moreover, the correlation between adverse mental states and insomnia varied significantly by gender and specific sleep parameters. These findings provide valuable insights for developing targeted mental health interventions to manage insomnia.

INTRODUCTION

Insomnia is a sleep disorder characterized by frequent difficulties falling or maintaining sleep, leading to decreased sleep quality. It has high prevalence and relapse rates, making it one of the most common disorders. According to global multicenter cross-sectional data[1], the worldwide prevalence of insomnia ranges from 2.3% to 25.5%, with acute insomnia at 11.3%.

The “3P model of insomnia”[2] is commonly used to explain the pathogenesis of insomnia. The model includes predisposing factors (age, gender, genetics, personality), precipitating factors (life events), and perpetuating factors (anxiety, depression, insomnia-related fear and anxiety, and poor sleep habits). Among these, poor mental state plays a crucial role in maintaining and exacerbating insomnia, a view supported by extensive research. Kapoor et al[3] found that worry, restlessness, irritability, and lack of control in anxiety disorders were independently associated with sleep disturbances. Stahl and Patel[4] indicated that among elderly individuals who have experienced the death of their spouse/Life partner within the previous 12 months, the severity of insomnia was significantly associated with complicated grief. Mohammed Salih et al[5] reported a significant positive relationship between sleep disturbances and depressive symptoms.

Although these studies indicate that adverse mental states negatively affect sleep, few have systematically analyzed the association between various adverse mental states and insomnia. Specifically, there is limited research on gender differences in how adverse mental states affect insomnia, and whether risk factors for severe insomnia vary by gender. These research gaps have limited the effectiveness and precision of psychological interventions for insomnia. Thus, this multicenter cross-sectional study was conducted to analyze the complex relationships between adverse mental states and insomnia, with a special emphasis on gender differences.

MATERIALS AND METHODS

Sample size calculation

Sample size calculation is based on the standard formula for estimating a single population proportion, ultimately determining that a sample size of approximately 2000 insomnia patients should be randomly selected.

Data sources

A total of 2022 cross-sectional questionnaires were collected from 2019 to 2021. After data verification, 2009 insomnia patients were finally included: (1) 500 from Hubei Provincial Hospital of Traditional Chinese Medicine; (2) 500 from Wuhan Hospital of Traditional Chinese Medicine; (3) 522 from Guangdong Provincial Hospital of Traditional Chinese Medicine; and (4) 487 from Gansu University of Traditional Chinese Medicine.

Diagnostic criteria: According to the third edition of the Chinese Classification and Diagnostic Criteria of Mental Disorders[6]: (1) Insomnia as the primary symptom, including difficulty falling asleep, light sleep, dreaminess, early awakening, and daytime fatigue; (2) Extreme anxiety about insomnia consequences; and (3) Exclusion of insomnia caused by other diseases.

Inclusion criteria: (1) Age ≥ 18 years; (2) Meeting the above insomnia diagnostic criteria; (3) Voluntary participation and signing informed consent; (4) Clear consciousness, no obvious communication barriers or cognitive disorders, and ability to cooperate in completing the questionnaire; and (5) Stable vital signs and absence of severe cardiac, cerebral, digestive, or systemic diseases.

Exclusion criteria: (1) Not meeting diagnostic criteria for insomnia; (2) Severe mental illness or cognitive impairment preventing normal communication; (3) Severe diseases involving other organ systems; and (4) Unstable vital signs.

Research process

The study flowchart is shown in Figure 1.

Figure 1  Flowchart of the study on insomnia and mental states in China.

Measures (general information questionnaire)

Basic information: (1) Name; (2) Gender; (3) Age; (4) Height; (5) Weight; (6) Marital status; and (7) Work arrangement, etc.

Medical history of insomnia: (1) Season; (2) Core insomnia symptoms (time to fall asleep, actual sleep duration, number of nocturnal awakenings, and total waking time during the night); and (3) 14 subjectively reported adverse mental states (depression, apathy, fatigue, impatience-irritability, timidity, indecision, grief, suspiciousness, catatonia, decreased willpower, taciturnity, inattention, forgetfulness, and slow response), etc.

Pittsburgh Sleep Quality Index: The Pittsburgh Sleep Quality Index (PSQI), translated by Liu et al[7], was applied. The PSQI includes 19 self-assessed and 5 other-assessed items, of which 18 items are scored, covering seven dimensions: (1) Subjective sleep quality; (2) Time to fall asleep; (3) Sleep duration; (4) Sleep efficiency; (5) Sleep disturbances; (6) Hypnotic medication usage; and (7) Daytime functioning. Each dimension is scored from 0 to 3, with a total score range of 0 to 21. Higher scores indicate poorer sleep quality. A PSQI score ≥ 16 indicates severe insomnia.

Statistical analysis

The Kolmogorov-Smirnov test was performed to assess normality. Normally distributed measurement data are expressed as mean ± SD, while non-normally distributed data are expressed as median (interquartile range). Count data are described as n. Sleep and mental states between genders were compared using the nonparametric rank-sum test. Bivariate correlation analyses were conducted to evaluate associations between core insomnia symptoms (time to fall asleep, actual sleep duration, number of nocturnal awakenings, total waking time during the night) and 14 subjectively reported adverse mental states (depression, apathy, fatigue, impatience-irritability, timidity, indecision, grief, suspiciousness, catatonia, decreased willpower, taciturnity, inattention, forgetfulness, and slow response).

To examine factors associated with insomnia severity, participants were categorized into non-severe (PSQI < 16) and severe insomnia (PSQI ≥ 16) groups. All candidate variables, including age, season, and the 14 adverse mental states, were first examined using univariate analyses. χ² tests were applied to categorical variables, and Mann-Whitney U tests were used for non-normally distributed continuous variables. Variables demonstrating statistically significant between-group differences (P < 0.05) were subsequently entered as independent variables into gender-stratified binary logistic regression models. Insomnia severity (non-severe = 0; severe = 1) served as the dependent variable. Seasons were coded as dummy variables (spring = 1, summer = 2, autumn = 3, winter = 4).

In our analyses, season was included as an a priori covariate to account for well-documented seasonal variation in sleep patterns and sleep complaints. Multiple epidemiological studies[8,9] have reported that human sleep duration and subjective sleep problems vary across seasons, with longer sleep and increased sleep difficulties often observed in winter compared with summer, and sex and age differences in these seasonal effects have also been described. Moreover, seasonal variation in environmental zeitgebers such as daylight and ambient temperature has been shown to influence circadian regulation, which in turn can affect sleep quality and insomnia symptoms. Therefore, adjustment for season helped control for potential environmental confounding.

Missing data were addressed using multiple imputation under the assumption of missingness at random. Five imputed datasets were generated employing a fully conditional specification. The overall proportion of missing data was low for all variables: (1) Season (1.5%); (2) Sleep latency (3.5%); (3) Actual sleep duration (2.4%); (4) Number of nocturnal awakenings (5.6%); (5) Total nighttime wake time (10.1%); and (6) Age (0.1%). Parameter estimates were pooled across imputed datasets following Rubin’s rules. Sensitivity analyses comparing imputed with complete-case models yielded consistent results regarding direction and magnitude of associations, suggesting the findings were not materially affected by the imputation procedure. Nevertheless, considering the reliance on imputed data, results should be interpreted cautiously.

Given potential conceptual overlap among certain adverse mental states (e.g., depression and grief; fatigue and slowed response), multicollinearity diagnostics were performed prior to regression modeling. Variance inflation factors were calculated for all independent variables, with all values below 5, indicating no problematic multicollinearity. Thus, all variables were retained without requiring dimensionality reduction. Model calibration was evaluated using the Hosmer-Lemeshow goodness-of-fit test, and omnibus likelihood ratio tests were conducted to assess overall model significance. The final gender-stratified models demonstrated acceptable calibration and explanatory capacity. All statistical analyses were conducted using IBM SPSS version 25.0.

RESULTS

Descriptive data for male and female participants

The study included 724 males (36.04%) and 1285 females (63.96%) (Table 1). Among participants, 79.04% were married, 67.04% worked day shifts, and insomnia occurred most frequently in spring (34.79%).

Table 1 Descriptive data for male and female participants, n (%)/median (interquartile range).

Variables	Total (n = 2009)	Men (n = 724)	Women (n = 1285)
Age	48.00 (33.00, 58.00)	46.00 (32.00, 58.00)	48.00 (35.00, 58.00)
Height	165.00 (160.00, 171.00)	172.00 (169.00, 176.00)	161.00 (158.00, 165.00)
Weight	60.00 (55.00, 65.00)	66.00 (61.00, 70.00)	56.50 (52.00, 60.00)
Marriage
Unmarried	378 (18.82)	155 (21.41)	223 (17.35)
Married	1588 (79.04)	562 (77.62)	1026 (79.84)
Get divorced	12 (0.60)	3 (0.41)	9 (0.70)
Widowed spouse	31 (1.54)	4 (0.55)	27 (2.10)
Season
Spring	699 (34.79)	265 (36.60)	434 (33.77)
Summer	365 (18.17)	111 (15.33)	254 (19.77)
Autumn	551 (27.43)	184 (25.41)	367 (28.56)
Winter	363 (18.07)	145 (20.03)	218 (16.96)
Uncertain	31 (1.54)	19 (2.62)	12 (0.93)
Work arrangement
Day shift	1347 (67.05)	490 (67.68)	857 (66.69)
Shift work	88 (4.38)	35 (4.83)	53 (4.12)
Night shift	21 (1.05)	11 (1.52)	10 (0.78)
Uncertain	553 (27.53)	188 (25.97)	365 (28.40)

Comparison of sleep states between male and female insomnia patients

Table 2 shows significant differences between male and female insomnia patients in time to fall asleep, actual sleep duration, and total waking time during the night (P < 0.05). No significant difference existed in the number of nocturnal awakenings (P > 0.05).

Table 2 Comparison of sleep condition in male and female insomnia patients, median (interquartile range).

Variables	Total (n = 2009)	Men (n = 724)	Women (n = 1285)	Statistic	P value
Time to fall asleep (minutes)	60.00 (30.00, 120.00)	60.00 (30.00, 120.00)	60.00 (30.00, 120.00)	-3.39	< 0.001c
Actual sleep duration (hours)	5.00 (4.00, 6.00)	5.00 (4.00, 6.00)	5.00 (4.00, 6.00)	-2.1	0.036a
Number of nocturnal awakenings	2.00 (1.00, 3.00)	2.00 (1.00, 3.00)	2.00 (1.00, 3.00)	-0.66	0.507
Total waking time during the night	60.00 (30.00, 120.00)	60.00 (20.00, 120.00)	60.00 (30.00, 120.00)	-2.83	0.005b

^aP < 0.05.

^bP < 0.01.

^cP < 0.001.

Comparison of mental states during insomnia in male and female patients

Table 3 indicates differences in mental states between male and female insomnia patients. Depression, timidity, grief, and catatonia were more common among females (P < 0.05), while apathy, fatigue, and decreased willpower were more prevalent among males (P < 0.05).

Table 3 Comparison of mental status during insomnia in male and female patients, n (%).

Variables	Total (n = 2009)	Men (n = 724)	Women (n = 1285)	Statistic	P value
Depression	369 (18.37)	103 (14.23)	266 (20.70)	12.94	< 0.001c
Apathy	181 (9.01)	82 (11.33)	99 (7.70)	7.41	0.006b
Fatigue	1175 (58.49)	455 (62.85)	720 (56.03)	8.86	0.003b
Impatience-irritability	644 (32.06)	239 (33.01)	405 (31.52)	0.47	0.491
Timidity	201 (10.00)	55 (7.60)	146 (11.36)	7.29	0.007b
Indecision	122 (6.07)	39 (5.39)	83 (6.46)	0.93	0.334
Grief	117 (5.82)	20 (2.76)	97 (7.55)	19.34	< 0.001c
Suspiciousness	155 (7.72)	54 (7.46)	101 (7.86)	0.1	0.746
Catatonia	421 (20.96)	132 (18.23)	289 (22.49)	5.07	0.024a
Decreased willpower	637 (31.71)	253 (34.94)	384 (29.88)	5.48	0.019a
Taciturnity	145 (7.22)	63 (8.70)	82 (6.38)	3.72	0.054
Inattention	223 (11.10)	91 (12.57)	132 (10.27)	2.48	0.116
Forgetfulness	1038 (51.67)	384 (53.04)	654 (50.89)	0.85	0.356
Slow response	539 (26.83)	209 (28.87)	330 (25.68)	2.4	0.122

^aP < 0.05.

^bP < 0.01.

^cP < 0.001.

Correlation of 14 subjectively reported adverse mental states with core insomnia symptoms in women

Table 4 shows correlations between adverse mental states and sleep symptoms in women. Fatigue (r = 0.065, P < 0.05), grief (r = 0.062, P < 0.05), and slow response (r = 0.080, P < 0.01) were positively correlated with time to fall asleep. Depression (r = -0.094, P < 0.01), fatigue (r = -0.070, P < 0.05), impatience-irritability (r = -0.096, P < 0.01), and forgetfulness (r = -0.122, P < 0.01) negatively affected actual sleep duration. Forgetfulness (r = 0.092, P < 0.01) and slow response (r = 0.077, P < 0.01) were positively correlated with number of nocturnal awakenings. Depression (r = 0.104, P < 0.01) was positively associated with total waking time during the night (Figure 2A).

Figure 2 Analysis of the correlation. A: Correlation of 14 subjectively reported adverse mental states with core insomnia symptoms in women; B: Correlation of 14 subjectively reported adverse mental states with core insomnia symptoms in men. ^aP < 0.05, ^bP < 0.01.

Table 4 Correlation of 14 subjectively reported adverse mental states with core insomnia symptoms in women.

Variables	Time to fall asleep (minutes)	Actual sleep duration (hours)	Number of nocturnal awakenings	Total waking time during the night (minutes)
Depression	0.04	-0.094b	0	0.104b
Apathy	-0.042	0.03	0.001	-0.072a
Fatigue	0.065a	-0.070a	0.032	-0.023
Impatience-irritability	0.047	-0.096b	0.052	0.03
Timidity	-0.007	0.022	0.047	-0.033
Indecision	-0.045	0.075b	-0.015	-0.054
Grief	0.062a	-0.048	0.009	-0.016
Suspiciousness	-0.007	0.028	-0.022	-0.023
Catatonia	-0.028	0.004	-0.012	-0.051
Decreased willpower	-0.028	0.069a	-0.045	-0.146b
Taciturnity	-0.041	0.081b	-0.009	-0.087b
Inattention	-0.05	0.053	-0.005	-0.070a
Forgetfulness	0.070a	-0.122b	0.092b	0.027
Slow response	0.080b	-0.035	0.077b	-0.013

^aP < 0.05.

^bP < 0.01.

Correlation of 14 subjectively reported adverse mental states with core insomnia symptoms in men

Table 5 shows correlations between adverse mental states and sleep symptoms in men. No mental factors influencing time to fall asleep were identified. However, fatigue (r = -0.132, P < 0.01), impatience-irritability (r = -0.083, P < 0.05), and forgetfulness (r = -0.129, P < 0.01) negatively affected actual sleep duration. Depression (r = 0.080, P < 0.05), apathy (r = 0.073, P < 0.05), and forgetfulness (r = 0.153, P < 0.01) were positively correlated with number of nocturnal awakenings. Forgetfulness (r = 0.134, P < 0.01) was positively correlated with total waking time during the night (Figure 2B).

Table 5 Correlation of 14 subjectively reported adverse mental states with core insomnia symptoms in men.

Variables	Time to fall asleep (minutes)	Actual sleep duration (hours)	Number of nocturnal awakenings	Total waking time during the night (minutes)
Depression	0.057	-0.042	0.080a	0.011
Apathy	-0.054	0.011	0.073a	-0.078a
Fatigue	-0.01	-0.132b	0.072	0.067
Impatience-irritability	0.047	-0.083a	-0.021	-0.022
Timidity	0.053	-0.02	0.01	-0.012
Indecision	0.031	-0.001	-0.088a	-0.084a
Grief	0.026	-0.048	-0.039	0.055
Suspiciousness	-0.021	0.037	-0.004	-0.042
Catatonia	-0.001	-0.012	-0.057	-0.075a
Decreased willpower	0.011	-0.01	-0.01	-0.118b
Taciturnity	-0.068	0.114b	-0.101b	-0.131b
Inattention	-0.109b	0.096b	-0.036	-0.106b
Forgetfulness	-0.035	-0.129b	0.153b	0.134b
Slow response	0.051	0.002	0.047	-0.037

^aP < 0.05.

^bP < 0.01.

Analysis of risk factors for severe insomnia in women

Results in Table 6 indicate that age, season, depression, indecision, grief, forgetfulness, and slow response were associated with severe insomnia in women. The risk of severe insomnia increases with age in women [odds ratio (OR) = 1.05, 95%CI: 1.04-1.06, P < 0.001]. Compared to spring, summer was associated with severe insomnia in women (OR = 1.43, 95%CI: 1.02-2.01, P = 0.038). Compared to spring, autumn was associated with severe insomnia in women (OR = 1.22, 95%CI: 0.89-1.67, P = 0.209). Compared to spring, winter was associated with severe insomnia in women (OR = 1.52, 95%CI: 1.06-2.17, P = 0.021). Depression increases the risk of severe insomnia in women (OR = 1.79, 95%CI: 1.35-2.38, P < 0.001). Grief increases the risk of severe insomnia in women (OR = 1.83, 95%CI: 1.20-2.80, P = 0.005). Forgetfulness increases the risk of severe insomnia in women (OR = 1.34, 95%CI: 1.05-1.71, P = 0.018). Slow response increases the risk of severe insomnia in women (OR = 1.53, 95%CI: 1.17-2.00, P = 0.002).

Table 6 Binary logistic regression analysis of factors influencing severe insomnia in women.

Variables	β	SE	Z	P value	Odds ratio	95%CI
Age	0.05	0	10.11	< 0.001c	1.05	1.04-1.06
Season
Spring						1.00 (reference)
Summer	0.36	0.17	2.07	0.038a	1.43	1.02-2.01
Autumn	0.2	0.16	1.25	0.209	1.22	0.89-1.67
Winter	0.42	0.18	2.3	0.021a	1.52	1.06-2.17
Depression	0.58	0.14	4.02	< 0.001c	1.79	1.35-2.38
Indecision	-0.64	0.29	-2.18	0.029a	0.53	0.30-0.94
Grief	0.61	0.22	2.8	0.005b	1.83	1.20-2.80
Forgetfulness	0.29	0.12	2.36	0.018a	1.34	1.05-1.71
Slow response	0.43	0.14	3.13	0.002b	1.53	1.17-2.00

^aP < 0.05.

^bP < 0.01.

^cP < 0.001.

β: Unstandardized regression coefficient; Z: The ratio of the regression coefficient to its standard error.

Analysis of risk factors for severe insomnia in men

The results in Table 7 show that age, season, depression, impatience-irritability, forgetfulness, and slow response were significantly associated with severe insomnia in men. The risk of severe insomnia increases with age in men (OR = 1.04, 95%CI: 1.03-1.05, P < 0.001). Compared to spring, summer was associated with severe insomnia in men (OR = 1.47, 95%CI: 0.85-2.54, P = 0.173). Compared to spring, autumn was associated with severe insomnia in men (OR = 1.48, 95%CI: 0.92-2.37, P = 0.105). Compared to spring, winter was associated with severe insomnia in men (OR = 2.80, 95%CI: 1.75-4.49, P < 0.001). Depression increases the risk of severe insomnia in men (OR = 1.72, 95%CI: 1.08-2.72, P = 0.021). Impatience-irritability increases the risk of severe insomnia in men (OR = 1.62, 95%CI: 1.13-2.32, P = 0.009). Forgetfulness increases the risk of severe insomnia in men (OR = 2.20, 95%CI: 1.52-3.18, P < 0.001). Slow response increases the risk of severe insomnia in men (OR = 2.60, 95%CI: 1.81-3.75, P < 0.001).

Table 7 Binary logistic regression analysis of factors influencing severe insomnia in men.

Variables	β	SE	Z	P value	Odds ratio	95%CI
Age	0.04	0.01	6.84	< 0.001c	1.04	1.03-1.05
Season
Spring						1.00 (reference)
Summer	0.38	0.28	1.36	0.173	1.47	0.85-2.54
Autumn	0.39	0.24	1.62	0.105	1.48	0.92-2.37
Winter	1.03	0.24	4.29	< 0.001c	2.80	1.75-4.49
Depression	0.54	0.23	2.31	0.021a	1.72	1.08-2.72
Impatience-irritability	0.48	0.18	2.62	0.009b	1.62	1.13-2.32
Indecision	-0.48	0.45	-1.05	0.294	0.62	0.26-1.51
Forgetfulness	0.79	0.19	4.17	< 0.001c	2.20	1.52-3.18
Slow response	0.96	0.19	5.13	< 0.001c	2.60	1.81-3.75

^aP < 0.05.

^bP < 0.01.

^cP < 0.001.

β: Unstandardized regression coefficient; Z: The ratio of the regression coefficient to its standard error.

Model diagnostics indicated adequate performance of the gender-stratified logistic regression models. All variance inflation factors were below 5 for both women and men, indicating no evidence of problematic multicollinearity among independent variables. The omnibus tests of model coefficients were statistically significant (women: P = 0.022; men: P < 0.001), suggesting the models had meaningful explanatory power. Moreover, Hosmer-Lemeshow goodness-of-fit tests were non-significant (all P > 0.05), confirming acceptable agreement between observed and predicted probabilities, thus demonstrating adequate model calibration.

DISCUSSION

Overview of main findings

In this study, a representative clinical sample of the Chinese population revealed a significantly higher proportion of insomnia among females compared with males, consistent with previous epidemiological reports[10,11]. We systematically examined associations between 14 subjectively reported adverse mental states and multiple insomnia dimensions. Depression, apathy, fatigue, impatience-irritability, grief, forgetfulness, and slow response were significantly associated with insomnia. In contrast, timidity, indecision, suspiciousness, catatonia, decreased willpower, taciturnity, and inattention showed no significant associations. Importantly, the correlation between adverse mental states and insomnia varied according to gender and specific sleep dimensions. Grief, apathy, and impatience-irritability demonstrated clear gender specificity. Meanwhile, fatigue, forgetfulness, slow response, and depression showed broader associations with insomnia, although their manifestations differed between men and women.

Gender-specific associations between adverse mental states and insomnia

Apathy in men: Previous neuroimaging studies[12] have demonstrated gender differences in regional brain activity among patients with insomnia, suggesting potential sex-related variation in neural circuits involved in sleep-emotion regulation. Consistent with this perspective, our results showed that apathy was associated with an increased number of nocturnal awakenings in men, whereas no such association was observed in women, indicating a gender-specific pattern at the level of symptom co-occurrence.

Rather than implying a causal effect, this finding suggests that apathetic symptoms and sleep fragmentation may coexist in men through shared physiological or psychological correlates. From a physiological standpoint, neural networks related to motivation and emotional regulation that are implicated in apathy may overlap with arousal-related systems relevant to sleep maintenance, particularly in men, although this interpretation requires further experimental validation. From a psychological perspective, men may be less likely to externalize emotional distress, which could be accompanied by daytime apathetic features and heightened nocturnal arousal.

From a motivational and reward-processing framework, apathy represents a motivational syndrome closely related to anhedonia, characterized by reduced engagement in physical, cognitive, and emotional activities. Liu et al[13] reported that the association between anhedonia and insomnia was significantly stronger in men than in women, suggesting sex-related differences in the linkage between reward processing and sleep. Similarly, Wu et al[14] found that insomnia was associated with reduced reward responsiveness. Taken together, these findings support a potential bidirectional association in which apathetic or anhedonic traits are linked to sleep fragmentation, while disrupted sleep may in turn be associated with impaired reward-related functioning. However, given the cross-sectional design of the present study, the observed relationships should be interpreted as associative rather than causal.

Grief and depressive traits in women: In contrast, grief was specifically associated with prolonged sleep latency and a higher likelihood of severe insomnia in women, whereas depressive traits were associated with longer total nighttime wakefulness in this group. These associations may reflect sex-related differences in emotional processing styles, including greater tendencies toward self-critical perfectionism and rumination among women[15]. From adolescence onward, women are more likely to exhibit internalized emotional responses, such as brooding and worry, which may become particularly salient during nighttime periods of reduced external distraction.

Previous studies have reported that women tend to show heightened sensitivity to grief-related emotional stress, and such emotional experiences are frequently linked to sleep-onset difficulties[16]. In the present study, grief was also more prevalent among women than men (82.81%), which may help to explain its gender-specific association with insomnia severity observed in our analyses. Importantly, even when similar emotional states are present, their sleep-related correlates appear to differ by gender. For example, depressive traits in women were associated with prolonged nighttime wakefulness and shorter sleep duration, whereas in men, depressive symptoms were more strongly linked to increased nocturnal awakenings.

Taken together, these patterns suggest that adverse emotional states may be differentially associated with specific insomnia dimensions across genders. Such differences may be related to sex-associated variation in cognitive styles[17], brain structure[18], and emotional perception[19]. However, these interpretations remain speculative, and the observed relationships should be understood as associative rather than indicative of distinct causal pathways.

Fatigue, cognitive symptoms, and bidirectional relationships with insomnia

Beyond gender-specific patterns, fatigue, forgetfulness, and slowed responses were consistently associated with insomnia severity and distinct sleep parameters across both men and women. In particular, forgetfulness was associated with difficulties in sleep maintenance and shorter sleep duration, whereas fatigue showed a stronger association with prolonged sleep latency and reduced total sleep time. Traditionally, cognitive and somatic symptoms such as forgetfulness[20], fatigue[21], and slow response have often been conceptualized as consequences of insomnia. However, the present findings suggest a more complex pattern of co-occurrence, consistent with a potentially bidirectional association between these symptoms and insomnia.

Several previous studies provide context for this interpretation. Guo et al[22] reported that daytime fatigue in individuals with insomnia was correlated with altered thalamic network activity after sleep onset. Ishikura et al[23] observed that fatigue was associated with varying degrees of insomnia symptoms, while cross-sectional evidence further indicates a higher prevalence of insomnia among individuals reporting fatigue[24]. In addition, longitudinal findings suggest that improvements in chronic fatigue are accompanied by reductions in insomnia severity over time[25]. Taken together, these studies support the possibility of reciprocal associations between fatigue-related symptoms and sleep disturbance, although causal direction cannot be determined.

Notably, in the present study, fatigue was specifically associated with prolonged sleep latency in women. Population-based survey data have shown that women report higher levels of perceived stress than men[26]. Following periods of high-intensity or stressful work[27], heightened stress sensitivity may coexist with subjective fatigue and sustained physiological arousal. Neurobiological studies have linked such patterns to altered amygdala function and cortical hyperarousal[28]. While these responses may represent adaptive correlates of prolonged stress exposure[29], their association with sleep-onset difficulties suggests a pattern of co-occurring stress, fatigue, and insomnia symptoms rather than a unidirectional pathway.

Interpretation of non-significant associations

Certain adverse mental states, including timidity, indecision, suspiciousness, catatonia, decreased willpower, taciturnity, and inattention, did not exhibit significant associations with insomnia. These results should not be interpreted as evidence that such mental states lack relevance to sleep regulation. Instead, these findings may reflect differences in underlying neural mechanisms, relevance to particular insomnia subtypes, or specific contextual and cultural factors.

Insomnia is primarily characterized by dysregulated arousal and sleep-controlling mechanisms, including overactivation of cortical-limbic circuits, elevated hypothalamic-pituitary-adrenal axis activity, and autonomic imbalance. Mental states such as depression, grief, fatigue, and irritability are closely associated with emotional arousal and stress reactivity. In contrast, traits like timidity or indecision may reflect more stable personality features, less closely tied to acute arousal processes. Clinically, such traits could become significant in specific insomnia subtypes or at advanced stages of insomnia severity, not individually assessed here. Additionally, binary subjective measures may lack sensitivity to detect subtle relationships. Cultural context could further attenuate detectable associations, as traits like timidity or taciturnity might be considered normative rather than distress-related within Chinese clinical settings.

Several methodological and interpretive considerations must be noted regarding the current findings. First, logistic regression models examining severe insomnia (PSQI ≥ 16) were designed primarily to identify associative patterns rather than predictive accuracy or causality. Formal assessments of model fit and interaction terms were not the central objectives; thus, gender-specific results should be viewed as stratified associations rather than confirmed statistical interactions. Future research with larger and more balanced samples is needed to formally assess gender × mental state interactions. Second, although seasonal variation was included as a covariate, it serves as a proxy for broader environmental influences, such as photoperiod changes and circadian rhythm shifts, rather than a direct biological determinant. The lack of direct measures of light exposure or vitamin D levels limits mechanistic interpretations but does not diminish the contextual relevance of seasonality in population-based sleep studies. Third, while gender differences were identified, the observed effect sizes were modest (r = 0.062-0.153), indicating relatively small individual-level effects. Thus, these findings should not be considered as robust or deterministic gender differences. Rather, their clinical relevance arises from consistent patterns across multiple sleep parameters and alignment with known gender-related differences in emotional processing and sleep regulation. From a population health perspective, even minor effects can have meaningful implications given insomnia’s high prevalence. Finally, the gender-specific link between grief and insomnia likely involves combined neurobiological and sociocultural pathways. Women demonstrate heightened sensitivity within limbic and stress-related neural circuits and exhibit differences in hypothalamic-pituitary-adrenal axis regulation and hormonal fluctuations, potentially amplifying grief-related emotional arousal effects on sleep initiation. Concurrently, gendered coping behaviors, such as women’s stronger propensity toward rumination and emotional internalization, may further contribute to prolonged pre-sleep arousal. These combined mechanisms offer a plausible framework explaining the observed gender-specific relationship, while acknowledging that direct mechanistic examination exceeded the scope of this study.

Risk factors for severe insomnia

Consistent with previous research[30], age emerged as an independent risk factor for severe insomnia in both men and women. Seasonal variation was also observed, with the highest risk occurring in winter, in line with findings from Norway[31,32], although this pattern is not universally reported across regions[10]. Gender-specific psychiatric risk factors further differentiated severe insomnia profiles, with impatience and irritability predominating in men and grief in women. These differences may reflect gender-related temperament characteristics, highlighting their potential value as clinical indicators of severe insomnia.

Clinical implications

The identification of gender-specific psychological risk factors has important implications for personalized insomnia interventions. In men, interventions focusing on emotion regulation, irritability control, and arousal reduction, such as anger management training, stress coping strategies, and relaxation-based approaches, may be particularly effective. In women, grief-focused counseling, cognitive-behavioral techniques targeting rumination and pre-sleep worry, and supportive psychotherapy that promotes emotional expression may help reduce sleep-onset difficulties. Importantly, intervention strategies should be matched to the predominant sleep domain affected, such as targeting sleep latency in grief-related insomnia or sleep continuity in irritability-related insomnia.

Methodological considerations and interpretive scope

The present study used a cross-sectional and symptom-focused design and relied on subjective self-reported assessments of mental states and sleep quality. Therefore, the findings should be interpreted as descriptive associations, not causal or independent effects. Self-reported data may be affected by recall bias and social desirability. Unmeasured confounders, including medication use, physical comorbidities, and socioeconomic status, may also influence the observed relationships. Nevertheless, the consistent gender-specific patterns across multiple sleep dimensions support the internal consistency of the findings and suggest that the results are unlikely to reflect random reporting bias alone.

The analyses did not comprehensively adjust for several potentially important confounders, such as medication use (e.g., antidepressants, benzodiazepines, or hypnotics), physical comorbidities, and socioeconomic factors. These variables may independently affect both adverse mental states and sleep outcomes and could partly explain the observed associations. For example, psychotropic medications may alter emotional states while directly influencing sleep architecture and continuity. Accordingly, the findings should be interpreted as symptom-level associations rather than independent effects of specific mental states on insomnia. The primary contribution of this study lies in identifying clinically relevant co-occurrence patterns between adverse mental states and sleep disturbances, rather than in establishing etiological mechanisms. Future studies with comprehensive adjustment for pharmacological, medical, and socioeconomic factors are required to further clarify causal pathways.

Adverse mental states were assessed using subjective self-reports rather than standardized psychometric instruments such as the Patient Health Questionnaire-9 (PHQ-9) or the Generalized Anxiety Disorder-7 (GAD-7). This approach may introduce recall bias and limit direct comparability with studies using validated diagnostic scales. However, the study was designed within a symptom-oriented and dimensional approach, aiming to capture subjectively reported mental states commonly observed in clinical insomnia settings rather than to establish formal psychiatric diagnoses. Similarly, sleep outcomes were evaluated using the PSQI, a well-validated instrument for subjective sleep assessment. Nevertheless, the absence of objective sleep measures, such as actigraphy or polysomnography, limits the ability to verify self-reported sleep parameters and to distinguish perceptual from physiological aspects of sleep disturbance. Accordingly, the findings should be interpreted as associations between perceived mental states and subjective sleep quality, rather than objective sleep architecture. Future studies that integrate standardized psychometric instruments with objective sleep assessments are needed to triangulate these relationships and improve cross-study comparability.

Research limitations

Several limitations of this study should be acknowledged. First, the cross-sectional study design inherently limits the ability to establish temporal or causal relationships between insomnia and adverse mental states. Although significant associations were identified, it remains unclear whether adverse mental states contribute to insomnia onset or exacerbation, whether insomnia worsens mental health, or whether these associations reflect bidirectional interactions or common underlying pathways. Future studies employing longitudinal methods with repeated assessments over longer follow-up periods (e.g., 6-12 months), or well-designed case-control studies with matched non-insomnia controls, are required to clarify causal directions.

Second, adverse mental states were measured using subjective self-reporting rather than standardized psychometric scales, such as the Patient Health Questionnaire-9 or Generalized Anxiety Disorder-7. Although this symptom-focused approach mirrors real-world clinical insomnia practice, it might introduce measurement bias and limit comparability with studies using validated diagnostic instruments. Future research should integrate standardized assessments and perform cross-validation analyses comparing psychometric scale scores with subjective symptom reports to enhance measurement accuracy and data credibility.

Third, the gender distribution within the sample was unbalanced, with a higher proportion of female than male participants. Although this distribution aligns broadly with epidemiological data indicating higher insomnia prevalence among women, it might affect statistical power and the generalizability of gender-stratified findings. To mitigate this issue, analyses were conducted separately for men and women using gender-specific regression models. Nevertheless, future studies should aim to recruit larger male samples, potentially through collaboration with clinical settings predominantly attended by men, or employ gender-weighted analytical methods to enhance the robustness of gender comparisons.

Fourth, missing data due to unclear or incomplete questionnaire responses were addressed using multiple imputation. Although this approach reduces bias related to missingness, it may introduce uncertainty into parameter estimates. Future studies focusing on improved data completeness and prospective data collection could further enhance the reliability of findings.

Finally, excluding participants with severe mental illness or substantial cognitive impairment, though necessary to ensure questionnaire reliability and data quality, may limit the representativeness of the sample. Given the significant comorbidity between insomnia and severe psychiatric or cognitive conditions, the current study population may be biased towards relatively healthier insomnia sufferers. Consequently, the generalizability of these findings to more complex clinical groups may be restricted. Future research should consider including broader clinical populations or performing stratified analyses incorporating patients with comorbid psychiatric or cognitive disorders to better represent the full clinical spectrum of insomnia and improve external validity.

CONCLUSION

This study systematically analyzed correlations between 14 adverse mental states and insomnia through a cross-sectional survey of the Chinese population with insomnia. The results indicated that not all mental states correlated with insomnia. Depression, apathy, fatigue, impatience-irritability, grief, forgetfulness, and slow response were significantly associated with insomnia. Timidity, indecision, suspiciousness, catatonia, decreased willpower, taciturnity, and inattention showed no significant correlation. Moreover, the impact of identical mental states on insomnia varied significantly by gender and sleep dimension. For instance, grief specifically affected women’s sleep onset, whereas apathy specifically impacted men’s sleep continuity. These findings demonstrate complex patterns between insomnia and adverse mental states, offering substantial clinical value for assessing insomnia and developing targeted psychological interventions. Importantly, our findings also suggest potential gender-specific differences in the emotion-sleep neural circuitry. Future studies could expand on this research using neuroimaging techniques and other methods to explore gender-specific mechanisms, thereby advancing sleep medicine toward more precise and personalized approaches.

ACKNOWLEDGEMENTS

We sincerely thank all staff members for their dedicated efforts in this research. We are also deeply grateful to all participants for providing accurate data.