Prevalence and Associated Factors of Insomnia in Adult Psychiatric Patients: A Hospital-Based Study

Article information

Sleep Med Res. 2025;16(2):121-128
Publication date (electronic) : 2025 June 26
doi : https://doi.org/10.17241/smr.2025.02824
1Department of Psychiatry, Chittagong Medical College, Chittagong, Bangladesh
2Department of Psychiatry, National Institute of Mental Health (NIMH), Dhaka, Bangladesh
3Department of Child & Adolescent Psychiatry, National Institute of Mental Health (NIMH), Dhaka, Bangladesh
4Department of Psychiatry, Pabna Mental Hospital, Pabna, Bangladesh
5Department of Psychiatry, Cumilla Medical College, Cumilla, Bangladesh
6Department of Psychiatry, Chandpur Medical College, Chandpur, Bangladesh
Corresponding Author Ahsan Aziz Sarkar, FCPS Department of Psychiatry, Pabna Mental Hospital, Pabna 6602, Bangladesh Tel +88-02-5888-46231 Fax +88-02-5888-05212 E-mail ahsan.psychiatry@gmail.com
Received 2025 March 31; Revised 2025 May 2; Accepted 2025 May 14.

Abstract

Background and Objective

Insomnia is highly prevalent in psychiatric disorders, yet its patterns and predictors vary across diagnoses and cultural contexts. This study examined the prevalence and associations of insomnia in adult psychiatric patients in an outpatient setting.

Methods

A cross-sectional study was conducted among 380 adult psychiatric patients at a tertiary hospital. Insomnia was assessed using the Structured Clinical Interview for DSM-5 Sleep Disorders–Revised. Sociodemographic, clinical, and lifestyle variables were assessed, and logistic regression analyses were used to identify predictors of insomnia.

Results

The prevalence of insomnia was 44.2%, with the highest rates observed in trauma-and stressor-related disorders, followed by depressive disorders. Schizophrenia spectrum disorders, obsessive compulsive disorder, and conversion disorder showed significantly lower odds of insomnia compared to depressive disorders. Key predictors of insomnia included lower educational level (0–5 years: adjusted odds ratio [aOR]=5.60, p=0.015), low socioeconomic status (aOR=6.57, p=0.044), comorbid physical illness (aOR=3.81, p=0.005), and prolonged screen time (aOR=8.17, p<0.001).

Conclusions

Insomnia affects nearly half of adult psychiatric patients, with considerable variation across diagnostic categories. These findings underscore the need for targeted sleep assessment and interventions within psychiatric services, especially in low resource settings.

INTRODUCTION

Insomnia is a state of dissatisfaction with sleep, often manifesting as frequent and persistent difficulties in initiating sleep, maintaining sleep, or experiencing early morning awakenings. To be classified as a disorder, these symptoms have to persist for at least 3 months in the absence of contributing physical, mental, or substance-related conditions [1]. It is a common feature of various psychiatric disorders, with estimates suggesting that 50% to 80% of individuals with psychiatric illnesses experience insomnia [2]. Given its widespread occurrence, the relationship between insomnia and psychiatric disorders is intricate and bidirectional. There is ongoing debate regarding its status—whether it should be considered a symptom of psychiatric disorders or a comorbid condition, appears first or second, a causative or risk factor for psychiatric illness, or a consequence of another underlying condition [3]. Insomnia was classified as primary and secondary types in the Diagnostic and Statistical Manual of Mental Disorders, 4th ed (DSM-IV); however, in the DSM-5, it was changed into insomnia disorder and insomnia disorder with comorbidity [1]. Regardless of its classification, insomnia has been shown to have a detrimental impact on patients, contributing to greater severity of psychiatric symptoms, triggering illness episodes, imparting poor treatment response, persisting as a residual syndrome, and leading to functional impairment, emotional dysregulation, cognitive deficits, and an increased risk of suicide [4,5]. The shared neurobiological mechanisms underlying sleep and mental health disorders further explain their frequent co-occurrence. Sleep-regulating neurotransmitters, including acetylcholine, noradrenaline, serotonin, histamine, orexin, hypocretin, gamma-aminobutyric acid, and glycine, as well as associated neural structures, are often disrupted in various psychiatric conditions, physical illnesses, and following use of many substances and medications [6]. These intricate interactions highlight the need for a comprehensive understanding of insomnia in psychiatric populations.

Hospital-based studies on insomnia in patients with psychiatric disorders are essential, as they typically involve individuals with more severe and complex conditions and guides intervention strategies. While comparisons with the normal population are common, studies comparing insomnia across different psychiatric disorders remain relatively scarce. Cultural differences influence insomnia reporting, with studies indicating that Asians tend to report fewer sleep complaints compared to other ethnic groups [7]. Moreover, since the majority of existing studies have been conducted in high-income countries, their findings may not be fully generalizable to populations with different cultural, environmental, and lifestyle contexts. For example, a systematic review of sleep problems among firefighters reported a higher prevalence of sleep disorders in low-income countries compared to high-income countries (41.1% vs. 29.4%), which was attributed to differences in occupational facilities and available resources [8]. Supporting this, data from the World Health Organization’s Study on Global Ageing and Adult Health showed that Bangladesh, one of the poorest among the eight countries studied, had the highest reported proportion of sleep problems [9]. Although a meta-analysis by Simonelli et al. [10] found no significant difference in the prevalence of poor sleep quality between high- and low-income countries, the authors highlighted technological, geographic, social, demographic, and health-related factors as possible explanations for the wide variability in findings across countries. Given the significant impact of insomnia on patients’ quality of life, along with the substantial direct and indirect costs associated with the condition, this study was designed to determine the prevalence of insomnia in psychiatric disorders and identify the demographic, lifestyle, and other associated risk factors.

METHODS

Study Design and Participants

This cross-sectional study was conducted in 2021 at a tertiary care psychiatric hospital in Bangladesh. A total of 380 adult patients (aged 18 years and older) attending the outpatient service were consecutively enrolled until the required sample size was reached. Patients were included if they had a DSM-5 psychiatric disorder diagnosed by consultant psychiatrists, were in a stable clinical condition, and were able to provide informed written consent. Patients with intellectual disabilities, pregnant females, and those with serious medical conditions were excluded.

Tools

A semi-structured questionnaire was used to collect sociodemographic, clinical, and lifestyle-related information, along with the patients’ clinical diagnoses. Diagnoses were taken from the clinical notes of the consultant psychiatrists and only the principal diagnosis was considered. Insomnia was assessed using the insomnia module of the Structured Clinical Interview for DSM-5 Sleep Disorders–Revised (SCISD-R) [11], a semi-structured interview designed to diagnose insomnia and other sleep-wake disorders based on DSM-5 criteria. The insomnia module consists of seven questions assessing sleep disruption patterns, functional impact, frequency, duration, and exclusion of secondary causes. Each question was rated on a four-point scale: 0= insufficient information, 1=absent, 2=subthreshold, and 3=threshold, with a rating of 3 on all seven items required for an insomnia diagnosis. A psychiatrist conducted face-to-face interviews using a paper-and-pencil method to collect data. In addition, body mass index (BMI) of each patient was calculated by measuring height and weight of the patient.

Study Definitions

Patients were classified into four BMI categories: underweight (<18.5 kg/m2), normal (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), and obese (>30 kg/m2). Socioeconomic status was determined by the World Bank’s monthly income-based categorization. Substance use was defined as the consumption of any DSM-5-defined substance for more than two weeks within the past month. Patient was considered exercising if he was engaged in at least 150 minutes of moderate-intensity aerobic or at least 75 minutes of vigorous-intensity aerobic physical or sports activity in the week preceding the interview. Regular use of a mobile phone or television was defined as daily usage. Tea, coffee intake was classified as daily consumption, regardless of the amount.

Ethical Consideration

Ethical approval was obtained from the Institutional Review Board (IRB) of NIMH (Ref. NIMH/19/2307/02). Informed written consent was obtained from all participants after explaining the study’s purpose, procedures, potential benefits, and related considerations. Ethical principles were strictly maintained throughout the study.

Data Analysis

Data analysis was conducted using IBM SPSS Statistics version 27 (IBM Corp.). Descriptive statistics, including frequencies and percentages, were used to summarize demographic, clinical, and lifestyle-related variables. The overall prevalence of insomnia among psychiatric outpatients was reported as a percentage. Univariate logistic regression analyses were first performed to compare the odds of insomnia across different psychiatric diagnoses, using depressive disorders as the reference category. Due to issues of complete separation, where all patients with insomnia disorder and trauma- and stressor-related disorders had insomnia and none with personality disorders had insomnia, these three diagnostic groups were excluded from the regression model to avoid unstable estimates. Additional univariate logistic regression analyses were conducted to assess associations between insomnia and other study variables. Finally, variables found to be associated with insomnia in the univariate analyses (p<0.10) were included in a multivariate logistic regression model to identify independent predictors of insomnia.

RESULTS

Demographic, Clinical, and Lifestyle Information

A total of 380 adult patients with psychiatric disorders were enrolled in this study. Mean age of the patients was 35.8 years (standard deviation [SD]=±12.0) and mean duration of psychiatric illness was 44.2 months (SD=±49.0). Schizophrenia spectrum disorders (27.4%), bipolar and related disorders (22.4%) and depressive disorders (11.8%) were the most common diagnoses of the enrolled patients. Table 1 presents their demographic, clinical, and lifestyle characteristics. The majority (62.1%) were aged 18–39 years, with a higher proportion of males (57.6%). Comorbid physical illness was reported by 37.9% of patients.

Demographic, clinical, and lifestyle characteristics of adult psychiatric patients (n=380)

Prevalence of Insomnia

Overall, 44.2% patients with psychiatric disorders had insomnia. Among the insomnia patients (n=168), the most common complaints were difficulty initiating sleep (69.6%), followed by maintaining sleep (56.5%) and early morning awakening (30.9%). Over half (57.1%) reported impact on multiple modalities (i.e., initiation, maintenance, early morning waking). Table 2 presents the psychiatric diagnoses, the proportion of patients with insomnia for each disorder, and the odds of having insomnia relative to depressive disorder. Insomnia was most prevalent in patients with insomnia disorder (100%) and trauma- and stressor-related disorders (100%), though their odds ratios (ORs=1.35×109, p=0.999) were unstable due to small sample sizes. Compared to depressive disorder (reference), schizophrenia spectrum disorder was significantly associated with lower odds of insomnia (OR=0.44, 95% confidence interval [CI]: 0.21–0.90, p=0.025) along with obsessive compulsive disorder (OCD) and conversion disorder (OR=0.27, 95% CI: 0.07–0.99, p=0.049 for both). Other disorders, including bipolar disorder, anxiety disorder, OCD, and somatic symptom disorder, did not show statistically significant differences in insomnia prevalence compared to depressive disorders.

Psychiatric diagnosis, proportion of patients with insomnia for each disorder, and odds of having insomnia in reference to depressive disorders

Associations of Insomnia

Table 3 presents the predicted odds of having insomnia based on demographic, clinical, and lifestyle factors among adult psychiatric patients. In the multivariate analysis, lower education (0–5 years: adjusted OR [aOR]=5.60, p=0.015), low socioeconomic status (aOR= 6.57, p=0.044), comorbid physical illness (aOR=3.81, p=0.005), and prolonged screen time (aOR=8.17, p<0.001) remained significant independent predictors of insomnia.

Predicted probability of having insomnia by demographic, clinical, and lifestyle factors in adult psychiatric patients

In univariate analysis, factors such as being married, residing in an urban area, being on psychotropic medication, engaging in regular exercise, and not consuming tea or coffee were significantly associated with lower odds of insomnia; however, these associations did not remain significant in the multivariate model. Other variables, including age, sex, employment status, BMI, substance use, and duration of psychiatric illness, were not significantly associated with insomnia in either univariate or multivariate analyses.

DISCUSSION

The study found that 44.2% of adult psychiatric patients experienced insomnia. While patients with trauma- and stressorrelated disorders exhibited the highest prevalence, nearly half of the patients with depressive disorders, bipolar disorders, and anxiety disorders also reported insomnia. In contrast, patients with schizophrenia spectrum disorders, OCD, and conversion disorder showed relatively lower insomnia prevalence. These findings are comparable to those reported by Okuji et al. [2], who documented higher insomnia rates across various psychiatric conditions, including schizophrenia (50%), mood disorders (69%), anxiety disorders (63%), dissociative disorder (54%), and somatoform disorder (78%). While they estimated 50% to 80% prevalence for different psychiatric disorders, Mondal et al. [12] reported somewhat lower rates in a study of 500 psychiatric outpatients, where 73.4% had insomnia symptoms, but only 29.2% had clinically significant insomnia. Their study also found lower insomnia prevalence in schizophrenia (27.9%) and generalized anxiety disorder (34.5%), while major depressive episodes showed a higher rate (59.1%). Moreover, a meta-analysis of polysomnographic studies reinforces the widespread presence of sleep disturbances across psychiatric disorders, consistently reporting reduced total sleep time, decreased sleep efficiency, and prolonged sleep latency, regardless of whether the disorder is affective or non-affective in nature [13].

Depression is one of the most common psychiatric disorders in which insomnia is both a core symptom and a diagnostic criterion. The strong association between depressive disorders and sleep disturbances has led some experts to suggest that diagnosing depression in the absence of sleep problems may be inappropriate [14]. Given this well-established relationship, depressive disorder was chosen as the reference category for comparing insomnia prevalence across other psychiatric diagnoses. Our findings indicate that the odds of insomnia were comparable across most psychiatric disorders when compared to depressive disorder, except for schizophrenia spectrum disorder, OCD, and conversion disorder, which exhibited significantly lower odds of insomnia. This aligns with the study by Mondal et al. [12], who also reported lower odds of insomnia in schizophrenia. Further support comes from the meta-analysis by Benca et al. [13], which found that sleep disturbances are more pronounced and widespread in affective disorders compared to schizophrenia based on polysomnographic findings. In contrast, insomnia prevalence was markedly high in trauma- and stressor-related disorders, which is consistent with existing literature. The hyperarousal state of the brain, heightened vigilance, and frequent nightmares in these conditions are key contributors to persistent sleep disturbances [15].

Lower educational attainment was strongly associated with insomnia, and individuals with lower socioeconomic status also exhibited a higher likelihood of sleep disturbances. This finding is consistent with research on socioeconomic disparities in sleep health [7]. Limited education and lower income may correlate with poorer health literacy, reduced access to healthcare, and increased psychosocial stressors, all of which can contribute to disrupted sleep patterns. Consistent with previous studies [16], the presence of comorbid physical illnesses was associated with higher rates of insomnia. These associations may be attributed to distressing physical symptoms, the psychological burden of chronic illness, side effects of medications, and physiological changes affecting sleep regulation. Additionally, prolonged mobile phone or television use emerged as a strong predictor of insomnia. This finding supports growing evidence that excessive screen exposure disrupts sleep through multiple mechanisms, including bright light-induced melatonin suppression, cognitive arousal, and reduction of time available for sleep [17]. Paradoxically, individuals with insomnia may engage in increased screen use, especially at night, as a coping mechanism for sleep difficulties, which in turn can further disrupt sleep and perpetuate the insomnia cycle.

Although the multivariate analysis provides the most robust estimates by adjusting for potential confounders, some noteworthy associations were observed in the univariate analysis that merit discussion. These findings, while not statistically significant after adjustment, align with existing literature and may reflect underlying patterns that warrant further investigation in larger or more targeted studies. For example, urban residency was associated with significantly lower odds of insomnia in the univariate analysis. While previous studies have often reported higher insomnia rates among urban populations, attributed to environmental factors such as light and noise pollution, greater lifestyle stressors, and overcrowded living conditions [18,19], our findings may reflect the benefits of improved access to healthcare services in urban areas. Such access could facilitate earlier diagnosis and management of sleep problems, potentially reducing insomnia prevalence among urban dwellers. Similarly, regular tea or coffee consumption was linked with higher odds of insomnia, aligning with the known stimulant effects of caffeine on sleep. Caffeine can delay sleep onset and reduce total sleep time by up to 45 minutes [20], and its impact may be further compounded by individuals increasing their intake in response to fatigue caused by poor sleep. Marital status also showed a protective effect, with married individuals experiencing lower odds of insomnia compared to others. This is in line with previous findings that associate sleep disturbances with separation, divorce, or strained relationships [7,21]. Emotional support, shared responsibilities, and structured daily routines in marital relationships may all contribute to better sleep quality. The use of psychotropic medication was another factor linked to reduced odds of insomnia in univariate analysis. This may reflect the therapeutic effects of pharmacological treatment on underlying psychiatric symptoms or the sedative properties of certain medications, such as specific antidepressants and antipsychotics. Finally, regular physical activity appeared to have a protective association with insomnia. Prior meta-analyses have shown that exercise can improve sleep latency, duration, and quality through physiological and psychological mechanisms, including stress reduction, mood regulation, melatonin modulation, and thermoregulatory processes [22,23].

Contrary to some prior research, age, sex, BMI, and substance use were not significantly associated with insomnia in this study. While older age is well-documented as a risk factor for sleep disturbances, including insomnia, this finding may be attributed to the relatively young age cohort in the present sample (mean age: 35.8 years). Additionally, a meta-analysis reported no significant differences in slow-wave sleep patterns across age groups in psychiatric patients [13], suggesting that the impact of aging on sleep may be less pronounced in this population. Similarly, no significant sex differences in insomnia prevalence were observed, aligning with a previous finding that discussed comparable proportions of sleep complaints between men and women with psychiatric disorders [2]. However, some meta-analyses have suggested higher sleep problems in females with affective disorders and males with schizophrenia, indicating that sex differences in sleep disturbances may be disorder-specific rather than universal [13]. While obesity is a known contributor to insomnia, primarily due to its association with obstructive sleep apnea, physical discomfort, gastric reflux, and hormonal dysregulation [24], BMI was not significantly linked to insomnia in this study. This may be because the highest BMI category in the sample was overweight rather than obese, potentially limiting the degree of sleep disruption. Substance use also did not emerge as a significant predictor of insomnia, despite substantial evidence linking various substances to insomnia. One possible explanation is the short reference period (1 month) used to define substance use, which may not capture its long-term effects on sleep. Additionally, certain substances, such as cannabinoids and alcohol, have sedative effects that some individuals use to self-medicate for sleep difficulties, potentially confounding the association [25].

This study’s strengths include the use of the SCISD-R clinical version for insomnia diagnosis, recruitment of a diverse psychiatric patient sample, and consideration of multiple demographic and lifestyle factors influencing insomnia. Additionally, it provides insights from a low- and middle-income country, where cultural, socioeconomic, and healthcare access factors differ from high-income settings. This study has several methodological limitations that should be acknowledged to ensure transparency and support accurate interpretation of the findings. First, the study focused exclusively on insomnia disorder, assessed using the insomnia module of the SCISD-R. Other clinically relevant sleep disorders such as hypersomnolence disorder, obstructive sleep apnea, restless legs syndrome, circadian rhythm sleep-wake disorders, etc. were not evaluated. Consequently, comorbid or alternative sleep disorders may have gone undetected, and some cases of sleep difficulties may have been misclassified or underdiagnosed. Second, the study employed a cross-sectional design, which precludes any inference of causality between psychiatric diagnoses, lifestyle factors, and insomnia. Although associations have been identified, causal pathways cannot be established, and the temporal direction of relationships remains unclear. Third, participants were recruited from a tertiary-level psychiatric hospital, which may introduce selection bias. Patients attending such facilities may present with more severe, treatment-resistant, or complex psychiatric conditions compared to those in primary care or community settings. Therefore, the findings may not be generalizable to broader psychiatric or general populations, especially in non-specialized clinical environments. Fourth, the presence of comorbid psychiatric disorders was not formally adjusted for in the analysis. While data principal diagnosis was used to estimate disorder-specific prevalence and odds ratios, many patients in psychiatric settings often present with multiple comorbid diagnoses. This overlap may have influenced the observed relationships between specific psychiatric conditions and insomnia, potentially inflating or confounding the associations. Future studies should more systematically account for comorbidity, either through stratified analysis or multivariate modeling, to ensure robust and disorder- specific estimates. Finally, the study was also limited by an overrepresentation of certain diagnostic categories and small sample sizes in others. In particular, insomnia disorder, trauma-and stressor-related disorders, and personality disorders were excluded from regression models due to issues of complete separation, where all or none of the patients in these categories had insomnia, resulting in unstable estimates. This imbalance in diagnostic representation may have limited the statistical power and precision of subgroup comparisons.

In conclusion, this study underscores the high prevalence of insomnia among adults with psychiatric disorders, affecting nearly half of the sample. Multivariate analysis identified lower education, low socioeconomic status, comorbid physical illness, and prolonged screen exposure as independent risk factors, highlighting the role of social disadvantage, physical health burden, and behavioral patterns in sleep disturbances. Given these findings, clinicians should adopt a comprehensive approach to insomnia assessment in psychiatric care, considering not only diagnostic categories but also socioeconomic background, physical health, and daily lifestyle habits.

Notes

Availability of Data and Material

The research data supporting this study can be obtained by contacting the corresponding author upon justified request.

Author Contributions

Conceptualization: Jhowhar Datta. Formal analysis: Jhowhar Datta. Funding acquisition: Jhowhar Datta. Investigation: Jhowhar Datta, Taiyeb Ibna Zahangir, Sadia Afrin. Methodology: Ahsan Aziz Sarkar. Supervision: Mohammad Tariqul Alam. Writing—original draft: Jhowhar Datta, Ahsan Aziz Sarkar. Writing—review & editing: Md Shariful Haque, A. M. Fariduzzaman, Bijoy Kumar Dutta.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Funding Statement

This work was partially supported by a research grant from the BSMMU, Dhaka.

Acknowledgements

We gratefully acknowledge all study participants for their valuable time and contributions to this research.

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Article information Continued

Table 1.

Demographic, clinical, and lifestyle characteristics of adult psychiatric patients (n=380)

Characteristic n (%)
Age group (yr)
 18–39 236 (62.1)
 ≥40 144 (37.9)
Sex
 Male 219 (57.6)
 Female 161 (42.4)
Education (yr)
 0–5 99 (26.1)
 6–10 103 (27.6)
 >10 176 (46.3)
Marital status
 Married 239 (62.9)
 Unmarried 117 (30.8)
 Others 24 (6.3)
Residence
 Urban 237 (62.4)
 Rural 143 (37.6)
Employment status
 Employed 312 (82.1)
 Unemployed 68 (17.9)
Socioeconomic status
 Low 83 (21.8)
 Lower-middle 265 (69.7)
 Upper-middle 32 (8.4)
Body mass index (kg/m2)
 Underweight 32 (8.4)
 Normal 243 (63.9)
 Overweight 105 (27.7)
Physical illness
 Present 144 (37.9)
On psychotropic medication
 Yes 237 (62.6)
Substance use
 Yes 138 (36.4)
Regular exercise
 Yes 127 (33.4)
Taking tea, coffee
 Yes 293 (77.1)
Using mobile, TV
 Yes 241 (63.4)

Table 2.

Psychiatric diagnosis, proportion of patients with insomnia for each disorder, and odds of having insomnia in reference to depressive disorders

Diagnosis Psychiatric disorder (n=380) Insomnia (n=168) Odds ratio (95% CI) p-value
Schizophrenia spectrum disorders 104 (27.4) 37 (35.5) 0.44 (0.21–0.90) 0.025*
Bipolar and related disorders 85 (22.4) 45 (52.9) 0.91 (0.44–1.90) 0.816
Depressive disorders 45 (11.8) 25 (55.5) 1 (ref.) -
Anxiety disorders 33 (8.7) 17 (51.5) 0.83 (0.33–2.07) 0.695
Obsessive compulsive disorders 16 (4.2) 4 (25.0) 0.27 (0.07–0.99) 0.049*
Conversion disorder 15 (3.9) 4 (26.6) 0.27 (0.07–0.99) 0.049*
Somatic symptom disorder 16 (4.2) 7 (43.7) 0.83 (0.26–2.62) 0.755
Sexual dysfunctions 10 (2.6) 3 (30.0) 0.41 (0.10–1.59) 0.200
Substance related disorders 27 (7.1) 8 (29.6) 0.41 (0.14–1.17) 0.098
Neurocognitive disorders 13 (3.4) 5 (38.4) 0.41 (0.10–1.59) 0.200
Overall 380 (100) 168 (44.2)

Insomnia disorder (n=9), trauma- and stressor-related disorders (n=4), and personality disorders (n=3) were excluded.

*

p<0.05.

CI, confidence interval; -, not applicable.

Table 3.

Predicted probability of having insomnia by demographic, clinical, and lifestyle factors in adult psychiatric patients

Characteristic Univariate regression
Multivariate regression
Unadjusted odds ratio (95% CI) p-value Adjusted odds ratio (95% CI) p-value
Age group (yr)
 18–39 0.82 (0.54–1.24) 0.356 NA
 ≥40 1 (ref.)
Sex
 Male 0.94 (0.62–1.42) 0.792 NA
 Female 1 (ref.)
Education (yr)
 0–5 3.81 (2.72–6.38) <0.001*** 5.60 (1.39–22.57) 0.015*
 6–10 1.83 (1.11–3.02) 0.017* 1.59 (0.53–4.75) 0.403
 >10 1 (ref.) 1 (ref.)
Marital status
 Married 0.35 (0.14–0.86) 0.023* 0.36 (0.08–1.60) 0.183
 Unmarried 0.40 (0.16–1.02) 0.056 0.91 (0.19–4.25) 0.906
 Others 1 (ref.) 1 (ref.)
Residence
 Urban 0.43 (0.28–0.66) <0.001*** 2.00 (0.60–6.65) 0.257
 Rural 1 (ref.) 1 (ref.)
Employment status
 Unemployed 1.53 (0.90–2.59) 0.111 NA
 Employed 1 (ref.)
Socioeconomic status
 Low 2.22 (0.96–5.12) 0.061 6.57 (1.05–40.88) 0.044*
 Lower-middle 1.15 (0.54–2.45) 0.711 4.19 (0.96–18.23) 0.056
 Upper-middle 1 (ref.) 1 (ref.)
Body mass index (kg/m2)
 Underweight 0.87 (0.38–1.96) 0.743 NA
 Normal 1.27 (0.80–2.01) 0.304
 Overweight 1 (ref.)
Physical illness
 Present 0.68 (0.44–1.04) 0.081 3.81 (1.49–9.70) 0.005**
 Absent 1 (ref.) 1 (ref.)
On psychotropic medication
 Yes 0.63 (0.41–0.95) 0.031* 1.05 (0.42–2.62) 0.916
 No 1 (ref.) 1 (ref.)
Substance use
 Yes 1.32 (0.86–2.01) 0.192 NA
 No 1 (ref.)
Regular exercise
 Yes 0.66 (0.42–0.99) 0.048* 0.68 (0.27–1.73) 0.426
 No 1 (ref.) 1 (ref.)
Taking tea, coffee
 Yes 2.22 (1.35–3.57) 0.002** 0.50 (0.20–1.26) 0.145
 No 1 (ref.) 1 (ref.)
Using mobile, TV
 Yes 0.75 (0.49–1.15) 0.192 NA
 No 1 (ref.)
Duration of psychiatric illness (mon) 0.99 (0.99–1.00) 0.221 NA
Time spent each day on mobile and TV (hr) 7.38 (4.48–12.10) <0.001*** 8.17 (4.42–15.10) <0.001***
*

p<0.05;

**

p<0.01;

***

p<0.001.

Ref., reference category; CI, confidence interval; NA, not applicable; variables such as age group, sex, employment status, body mass index, substance use, duration of psychiatric illness, use of mobile, TV, and psychiatric diagnoses were excluded from the multivariate analysis.