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Sleep Med Res > Volume 14(4); 2023 > Article
Andishmand, Amini, Naderi, Garmabi, Sharifnezhad, Darrudi, and Gholami: Is Sleep Duration Associated With Depression and Anxiety? A Cross-Sectional Study on Medical Students in Iran

Abstract

Background and Objective

As the quantity of sleep can influence our mental health, this study examined the association of sleep duration with depression and anxiety in freshman students of Neyshabur University of Medical Sciences (NUMS).

Methods

This study was conducted on 471 freshman students who enrolled at NUMS in the academic years of 2019 and 2020. Data collection and evaluation of sleep duration, depression, and anxiety were done using the Persian versions of the Pittsburgh Sleep Quality Index, Beck Depression Inventory-II, and Beck Anxiety Inventory. The association between sleep duration with depression and anxiety was analyzed using the multinomial logistic regression models.

Results

The prevalence of inadequate and excessive sleep duration in the participants was 41.8% and 6.4%, respectively. More than 20% of the students reported depression (mild = 10.2%, moderate = 7.0%, and severe = 4.2%), and approximately one-third reported anxiety (mild = 20.6%, moderate = 7.9%, and severe = 3.4%). The analytical results showed that the odds of moderate and severe depression in individuals with inadequate sleep were three times higher compared to the individuals with adequate sleep (p < 0.05). Further, the odds of moderate anxiety in individuals with inadequate sleep was relatively three times higher compared to individuals with adequate sleep (p < 0.05).

Conclusions

Inadequate sleep predisposes students to mental disorders such as depression and anxiety. Therefore, policymakers and educators should develop psychological interventions to prevent anxiety and depression in students and help students live a healthy lifestyle such as improving sleep.

INTRODUCTION

Sleep helps to rehabilitate and restore both physical and mental health. It allows the body to control cellular growth and maintain hormone-focused metabolism [1]. The quantity of a person’s sleep can influence their behavior and health-related traits [2]. Age, sex, local residency, higher socioeconomic status leading to more than 24-hour entertainment at home with social networks or watching television, and lengthy working hours are associated with inadequate sleep [3,4]. However, it is still unclear how much sleep every individual needs. The amount of time required every 24 hours for best performance differs from person to person. A short sleep duration is defined as sleep lasting less than 6 or 7 hours on average over 24 hours. Long sleeping, on the other hand, is defined as sleeping for at least 9 hours [5]. Due to the adverse effects of irregular sleep patterns, the amount of sleep is likely to be associated with health-related outcomes, such as depression and anxiety. Notably, young individuals, such as students, are more likely to experience inadequate sleep, which can negatively affect learning, mood, and ordinary activities, leading to poor academic performance and healthcare costs [6]. Tapping more on niches, we can state that sleep deprivation has been shown to have an important effect on cognitive functions and motor activity. Especially, for medical students, these aspects are more important. This could be attributed to the demanding course contents and lengthy working hours. Healthcare students put in long hours at practice, hence are prone to inadequate sleep and its effects [7,8]. Ultimately, inadequate sleep might affect the community through accidents and medical errors [9]. This underlines the need for research on the effects of sleep quantity on students’ mental health. Therefore, the purpose of this study was to examine the relationship between sleep duration and depression and anxiety in first-year medical students at Neyshabur University of Medical Sciences (NUMS).

METHODS

Design and Study Population

A longitudinal survey for first-year medical students at NUMS was conducted. The survey collected information about students’ lifestyles and examined their relationship with academic success and health markers. The baseline data were collected in 2019 and 2020. For each year, data was collected during the enrollment period (late September to early October). The follow-up data were collected at the end of each academic year (annual follow-up). An informed consent, which involved informing the participants about their rights, the study’s goals, and the procedures used, was obtained from the participants [10]. All first-year students (n = 471) were asked to complete several questionnaires requesting demographic, socioeconomic, general health, and lifestyle data along with academic information.
The Declaration of Helsinki’s guiding principles were followed when conducting this study. The NUMS Ethics Committee gave their approval (Date: 05.10.2019/No: IR.NUMS. REC.1398.018).

Depression and Anxiety (Dependent Variables)

The research population’s level of depression was evaluated using the Persian version of the Beck Depression Inventory-II (BDI-II), which was validated in the Iranian population by Ghassemzadeh et al. [7]. Based on BDI-II, four categories (without depression, mild depression, moderate depression, and severe depression) are created. In this study, the categories of mild, moderate, and severe depression were compared to the category of no depression. The study population’s level of anxiety was assessed using the Persian version of the Beck Anxiety Inventory (BAI), which has been validated for the Iranian population by Kaviani and Mousavi [8]. Similar to the depression questionnaire, four groups (without anxiety, mild anxiety, moderate anxiety, and severe anxiety) were developed, and likewise, the categories of mild, moderate, and severe anxiety were compared to the category of no anxiety.

Sleep Duration (Independent Variable)

A question from the Pittsburgh Sleep Quality Index (PSOI) was used to measure the average number of hours that the students slept each night over 1 month. Three categories of sleep duration were established: inadequate (less than 7 hours), adequate (≥ 7 to < 9 hours), and excessive (equal to or more than 9 hours). Alimirzaei et al. [9] validated the Persian version of the PSOI in the students of Kerman University of Medical Sciences (a province in southeast Iran).

Covariates

In this study, factors such as sex (female vs. male), age (≤ 20 years old vs. > 20 years old), marital status (single vs. married), family residency (urban vs. rural), family size (≤ 4 vs. > 4), ethnicity (Fars vs. other), smoking (no vs. yes), body mass index (BMI) (< 25 vs. ≥ 25 kg/m2), physical activity (low vs. moderate vs. high), and family wealth index (WI) (poorest vs. poor vs. moderate vs. rich vs. richest) were included as covariates. In this study, WI evaluated the family’s economic situation, and it was calculated using principal component analysis based on the student’s family’s ownership of some assets.

Statistical Analysis

The variables’ frequencies, percentages, means, and standard deviations (SDs) were calculated using the descriptive analysis. At the univariate level, the association between the study population’s characteristics and different levels of dependent variables (depression and anxiety) was evaluated using the chi-square test. The independent associations of sleep duration with depression and anxiety were assessed using multinomial logistic regression models. The significance level was set at p < 0.05, and Stata 14 (StataCorp LLC., College Station, TX, USA) was used for all statistical analyses

RESULTS

The mean age of the students who participated in the study was approximately 22 years, and most of them were female (62.4%). More than 78% of the participants lived in urban areas, and less than 16% of them were married. Table 1 lists other characteristics of the study participants. The prevalence of inadequate and excessive sleep duration was 41.8% and 6.4% of the students, respectively, while approximately 52% of the students reported adequate sleep duration. As shown in Table 1, more than 20% of the students reported depression (mild = 10.2%, moderate = 7.0%, and severe = 4.2%). Also, approximately one-third of the students reported anxiety (mild = 20.6%, moderate = 7.9%, and severe = 3.4%) (Table 1). Fig. 1 presents the mean sleep duration based on different levels of depression and anxiety. As shown in Fig. 1A, the mean sleep duration in students with moderate and severe depression was lower than in students with no depression. Also, the mean sleep duration in students with mild, moderate, and severe anxiety is lower than in students with no anxiety (Fig. 1B).

Association of Sleep Duration and Depression

The results of the unadjusted and adjusted associations between sleep duration and depression are shown in Tables 1 and 2, respectively. Significant associations were observed between sleep duration and depression in the unadjusted (p = 0.005) and some of the adjusted (p < 0.05) models (Table 2). As shown in Table 2, in the adjusted models, comparison results of the inadequate sleep category with the adequate sleep category showed a significant association with moderate and severe depression. In this setting, after adjusting for all covariates (model 3), we observed that the odds of moderate and severe depression in individuals with inadequate sleep were three times higher compared to individuals with adequate sleep. In individuals with mild depression, there was no significant association observed between sleep duration and depression in all the adjusted models (p > 0.05). There was no association observed between excess sleep duration and depression in all the adjusted models (p > 0.05).

Association of Sleep Duration and Anxiety

The association between sleep duration and anxiety is shown in Tables 1 and 3. The sleep duration was not significantly associated with anxiety in the unadjusted (p = 0.053) (Table 1) and most of the adjusted (p > 0.05) models (Table 3). As presented in Table 3, in the adjusted models, comparison results of the inadequate sleep category with the adequate sleep category showed a significant association with moderate anxiety in the study population. In this regard, when the models were adjusted for studied covariates, we observed that the odds of moderate anxiety in individuals with inadequate sleep was three times higher than in individuals with adequate sleep. In individuals with mild and severe anxiety, there was no significant association observed between sleep duration and anxiety in all the adjusted models (p > 0.05). Moreover, there was no association observed between excess sleep duration and anxiety in all the adjusted models (p > 0.05).

DISCUSSION

Sleep takes approximately one-third of our lives and hence is an integral aspect of life. Adequate sleep is essential for physical and mental development and stability. Therefore, inadequate sleep not only devitalizes physical and mental functions, and leads to weaker work productivity, but may also cause mental disorders like depression and anxiety [11]. Consequently, inadequate sleep can have deleterious effects on society and individuals.
According to our results, more than 40% of the students in this study had inadequate sleep duration. Similarly, in a study conducted at King Abdulaziz University, Ibrahim et al. [12] found that the students who enrolled in the basic educational years suffered higher rates of inadequate sleep compared to the comparative groups. Also, findings from an investigation on medical students in Egypt in 2017 indicated that students in their first years (preclinical years) reported higher scores of inadequate and poor sleep compared to the counter groups [13]. Looking at the binary pole of findings, the present study is inconsistent with some findings [14,15]. For instance, Yazdi et al. [16] showed that senior students suffered higher levels of inadequate sleep. Also, Frank et al. [17] observed that the mean night sleep duration in freshman students was more than in the other students.
Using multinomial logistic regression models and after adjusting for studied covariates, the results of this study showed that the odds of moderate and severe depression in individuals with inadequate sleep were three times higher than in individuals with adequate sleep. Depression is considered the greatest contributor to global disability and accounted for 5% of disability rates in 2016 [18]. Previous studies have shown that depression is associated with genetics, behavioral, physical, and socioeconomic factors [19,20]; in line with these contributing factors, duration and pattern of sleep have been found to be risk factors for depression [21,22].
Inadequate sleep among healthcare students has been documented and with trivial differences in the results, the current study is a corroborating trace for the previous findings [23,24]. Previous literature has reported that inadequate sleep is tied with depressive and anxiety symptoms. Johnson et al. [25] propounded that sleep duration is a robust predictor of successive affective disorders. At one-year follow-ups in university, it was asserted that abatement in sleep duration potentially leads to a reduction of depression incidence [26]. Consistent with our study findings, Choi et al. [27] found that inadequate sleep was associated with depression; that is, individuals with severe depressive disorders suffer short sleep duration and low sleep efficiency. To further support our finding, stretches of evidence advocate that sleep problems mostly occur prior to depressive and anxiety symptoms and hence might be threatening bells for subsequent mental problems. Therefore, prompt and convenient interventions for sleep problems might deter the ensuing onset or aggravation of anxiety and depressive symptoms [28].
In the second part of multinomial logistic regression models, the analysis revealed that the odds of moderate anxiety in individuals with inadequate sleep were three times higher than in individuals with adequate sleep. In this study, in individuals with mild and severe anxiety, there was no significant association between sleep duration and anxiety in all the adjusted models. Inadequate and poor sleep has been one of the persistent predictors of enhanced anxiety levels in college students [29]. The relationship between sleep duration and anxiety in the current study is consistent with the previous literature. For instance, the results of two previous studies showed that inadequate sleep exacerbates the severity of anxiety symptoms and hence concluded that inadequate sleep and anxiety might facilitate probing treatment strategies [30,31]. The high reported value in moderate anxiety and inadequate sleep can be justified by the association between mental health and sleep quality. While the results of this study showed that sleeping for less than 7 hours increases anxiety severity by up to 14%, this finding is not statistically significant; therefore, we cannot rely on it. As shown in Table 1, the number of individuals in this range was small (n = 16); thus, generalizing these results should be done with care.

Strengths and Limitations

Despite the contributions of the study, it has several shortcomings. First, since this is a cross-sectional study, we are unable to conclude the causes. Second, we recruited students from only one university and there was a potential for recall bias from the study population; therefore, the findings might not be generalizable to all non-healthcare students’ samples. Third, additional confounding factors may have impacted the study’s data. Therefore, it is necessary to conduct a study with a larger sample size that takes into consideration other variables as well. Fourth, the self-reported instrument was employed to capture sleep duration, which could in turn cause bias. Lastly, the current study failed to take into account a clinical diagnosis of anxiety and depression. Despite these limitations, this study has several advantages. First, the effect of numerous confounding factors was controlled when we used multinomial logistic regression models to analyze the association between sleep duration with depression and anxiety in this study. Second, recruiting a sample of students at NUMS that is typical of both clinical and nonclinical medical students, is considered another edge. Last, although the current study recruited a sufficient sample size, the researchers had their centralization only on specific groups of students (freshmen students).

Conclusions

The findings of this study confirmed that sleep duration is significantly associated with depression and anxiety among freshmen students at NUMS. Therefore, evaluating sleep duration and its association with depression and anxiety in medical students might lend a hand in the early diagnosis and management of mental health. Therefore, to improve medical students’ sleep problems and consequently prevent depression and anxiety, it is essential for the concerned officials to develop and implement interventional programs.

NOTES

Availability of Data and Material
The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.
Author Contributions
Conceptualization: Ali Gholami, Zahra Andishmand. Data curation: Ali Gholami. Formal analysis: Ali Gholami. Investigation: Zahra Andishmand, Fatemeh Naderi, Maryam Garmabi, Ahmad Sharifnezhad, Fatemeh Darrudi. Methodology: Ali Gholami. Project administration: Ali Gholami, Ahmad Sharifnezhad. Software: Ali Gholami. Supervision: Ali Gholami, Ahmad Sharifnezhad. Visualization: Ali Gholami. Writing—original draft: Ali Gholami, Zahra Andishmand, Asieh Amini. Writing— review & editing: Ali Gholami, Asieh Amini.
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Funding Statement
Funding for the present work was provided by Neyshabur University of Medical Sciences (Grant number: 9801118).

ACKNOWLEDGEMENTS

To all the students who took part in this study, we would like to say thank you. We also acknowledge NUMS for their financial support.

REFERENCES

1. Leproult R, Van Cauter E. Role of sleep and sleep loss in hormonal release and metabolism. Endocr Dev 2010;17:11-21.
crossref pmid pmc
2. Reis C, Dias S, Rodrigues AM, Sousa RD, Gregório MJ, Branco J, et al. Sleep duration, lifestyles and chronic diseases: a cross-sectional population-based study. Sleep Sci 2018;11:217-30.
crossref pmid pmc
3. Madrid-Valero JJ, Martínez-Selva JM, Ribeiro do Couto B, Sánchez-Romera JF, Ordoñana JR. Age and gender effects on the prevalence of poor sleep quality in the adult population. Gac Sanit 2017;31:18-22.
crossref pmid
4. Fuligni AJ, Arruda EH, Krull JL, Gonzales NA. Adolescent sleep duration, variability, and peak levels of achievement and mental health. Child Dev 2018;89:e18-28.
crossref pmid pmc
5. Tan X, Chapman CD, Cedernaes J, Benedict C. Association between long sleep duration and increased risk of obesity and type 2 diabetes: a review of possible mechanisms. Sleep Med Rev 2018;40:127-34.
crossref pmid
6. Chaput JP, Gray CE, Poitras VJ, Carson V, Gruber R, Olds T, et al. Systematic review of the relationships between sleep duration and health indicators in school-aged children and youth. Appl Physiol Nutr Metab 2016;41(6 Suppl 3):S266-82.
crossref pmid
7. Ghassemzadeh H, Mojtabai R, Karamghadiri N, Ebrahimkhani N. Psychometric properties of a Persian-language version of the Beck Depression Inventory--second edition: BDI-II-PERSIAN. Depress Anxiety 2005;21:185-92.
crossref pmid
8. Kaviani H, Mousavi AS. Psychometric properties of the Persian version of Beck Anxiety Inventory (BAI). Tehran Univ Med J 2008;66:136-40.

9. Alimirzaei R, Azizzadeh Forouzi M, Abazari F, Mohammadalizadeh S, Haghdoost A. Sleep quality and some associated factors in Kerman students of nursing and midwifery. Health Dev J 2015;4:146-57.

10. Sharifnezhad A, Garmabi M, Naderi F, Darrudi F, Andishmand Z, Gholami A. Association of sleep duration and quality with health-related quality of life in fresher university students. Sleep Med Res 2023;14:50-7.
crossref
11. Yu Y, Liu J, Skokauskas N, Liu F, Zhang L, Teng T, et al. Prevalence of depression and anxiety, and associated factors, among Chinese primary and high school students: a cross‐sectional, epidemiological study. Asia Pac Psychiatry 2023;15:e12523.
crossref pmid
12. Ibrahim NK, Badawi FA, Mansouri YM, Ainousa AM, Jambi SK, Fatani AN, et al. Sleep quality among medical students at King Abdulaziz University: a cross-sectional study. J Community Med Health Educ 2017;7:561.

13. Fawzy M, Hamed SA. Prevalence of psychological stress, depression and anxiety among medical students in Egypt. Psychiatry Res 2017;255:186-94.
crossref pmid
14. Angelone AM, Mattei A, Sbarbati M, Di Orio F. Prevalence and correlates for self-reported sleep problems among nursing students. J Prev Med Hyg 2011;52:201-8.
pmid
15. Kabrita CS, Hajjar-Muça TA, Duffy JF. Predictors of poor sleep quality among Lebanese university students: association between evening typology, lifestyle behaviors, and sleep habits. Nat Sci Sleep 2014;6:11-8.
crossref pmid pmc
16. Yazdi Z, Loukzadeh Z, Moghaddam P, Jalilolghadr S. Sleep hygiene practices and their relation to sleep quality in medical students of Qazvin University of Medical Sciences. J Caring Sci 2016;5:153-60.
crossref pmid pmc
17. Frank E, Carrera JS, Elon L, Hertzberg VS. Basic demographics, health practices, and health status of U.S. medical students. Am J Prev Med 2006;31:499-505.
crossref pmid
18. Sun Y, Shi L, Bao Y, Sun Y, Shi J, Lu L. The bidirectional relationship between sleep duration and depression in community-dwelling middle-aged and elderly individuals: evidence from a longitudinal study. Sleep Med 2018;52:221-9.
crossref pmid
19. World Health Organization. Depression and other common mental disorders [Internet]. Geneva: World Health Organization; 2017 [cited 2022 Dec 5]. Availiable from: https://www.who.int/publications/i/item/depression-global-health-estimates.

20. Kendler KS, Gatz M, Gardner CO, Pedersen NL. A Swedish national twin study of lifetime major depression. Am J Psychiatry 2006;163:109-14.
crossref pmid
21. Cole MG, Dendukuri N. Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. Am J Psychiatry 2003;160:1147-56.
crossref pmid
22. Bao YP, Han Y, Ma J, Wang RJ, Shi L, Wang TY, et al. Cooccurrence and bidirectional prediction of sleep disturbances and depression in older adults: meta-analysis and systematic review. Neurosci Biobehav Rev 2017;75:257-73.
crossref pmid
23. Zhai L, Zhang H, Zhang D. Sleep duration and depression among adults: a meta‐analysis of prospective studies. Depress Anxiety 2015;32:664-70.
crossref pmid
24. Wolkove N, Elkholy O, Baltzan M, Palayew M. Sleep and aging: 1. Sleep disorders commonly found in older people. CMAJ 2007;176:1299-304.
crossref pmid pmc
25. Johnson EO, Roth T, Breslau N. The association of insomnia with anxiety disorders and depression: exploration of the direction of risk. J Psychiatr Res 2006;40:700-8.
crossref pmid
26. Lukowski AF, Karayianis KA, Kamliot DZ, Tsukerman D. Undergraduate student stress, sleep, and health before and during the COVID-19 pandemic. Behav Med; 2022 Jun 28 [Epub]. Available from: https://doi.rog/10.1080/08964289.2022.2085651.
crossref
27. Choi YH, Yang KI, Yun CH, Kim WJ, Heo K, Chu MK. Impact of insomnia symptoms on the clinical presentation of depressive symptoms: a cross-sectional population study. Front Neurol 2021;12:716097.
crossref pmid pmc
28. Eaton WW, Badawi M, Melton B. Prodromes and precursors: epidemiologic data for primary prevention of disorders with slow onset. Am J Psychiatry 1995;152:967-72.
crossref pmid
29. Basudan S, Binanzan N, Alhassan A. Depression, anxiety and stress in dental students. Int J Med Educ 2017;8:179-86.
crossref pmid pmc
30. Zhang Y, Peters A, Chen G. Perceived stress mediates the associations between sleep quality and symptoms of anxiety and depression among college nursing students. Int J Nurs Educ Scholarsh 2018;15:20170020.
crossref
31. Cox RC, Olatunji BO. A systematic review of sleep disturbance in anxiety and related disorders. J Anxiety Disord 2016;37:104-29.
crossref pmid

Fig. 1.
Mean of sleep duration in students based on different state of depression (A) and anxiety (B).
smr-2023-01865f1.jpg
Table 1.
Univariate analyses for the association of studied variables with depression and anxiety
Total (n = 471) Depression
p-value Anxiety
p-value
No (n = 370, 78.6%) Mild (n = 48, 10.2%) Moderate (n = 33, 7.0%) Severe (n = 20, 4.2%) No (n = 321, 68.1%) Mild (n = 97, 20.6%) Moderate (n = 37, 7.9%) Severe (n = 16, 3.4%)
Sex 0.316 < 0.001
 Female 294 (62.4) 223 (75.8) 33 (11.2) 24 (8.2) 14 (4.8) 179 (60.9) 73 (24.8) 28 (9.5) 14 (4.8)
 Male 177 (37.6) 147 (83.0) 15 (8.5) 9 (5.1) 6 (3.4) 142 (80.2) 24 (13.6) 9 (5.1) 2 (1.1)
Age 0.810 0.571
 ≤ 20 yrs 276 (58.6) 219 (79.3) 25 (9.1) 20 (7.2) 12 (4.4) 185 (67.0) 58 (21.0) 21 (7.6) 12 (4.4)
 > 20 yrs 195 (41.4) 151 (77.4) 23 (11.8) 13 (6.7) 8 (4.1) 136 (69.7) 39 (20) 16 (8.2) 4 (2.1)
Marital status 0.218 0.697
 Single 399 (84.7) 311 (77.9) 39 (9.8) 29 (7.3) 20 (5.0) 273 (68.4) 80 (20.0) 31 (7.8) 15 (3.8)
 Married 72 (15.3) 59 (81.9) 9 (12.5) 4 (5.6) 0 (0.0) 48 (66.7) 17 (23.6) 6 (8.3) 1 (1.4)
Family residency 0.862 0.150
 Urban 370 (78.6) 292 (78.9) 36 (9.7) 27 (7.3) 15 (4.1) 249 (67.3) 78 (21.1) 33 (8.9) 10 (2.7)
 Rural 101 (21.4) 78 (77.2) 12 (11.9) 6 (5.9) 5 (5.0) 72 (71.3) 19 (18.8) 4 (4.0) 6 (5.9)
Family size 0.542 0.017
 ≤ 4 186 (39.5) 147 (79.0) 22 (11.8) 10 (5.4) 7 (3.8) 111 (59.7) 48 (25.8) 19 (10.2) 8 (4.3)
 > 4 285 (60.5) 223 (78.2) 26 (9.1) 23 (8.1) 13 (4.6) 210 (43.7) 49 (17.2) 18 (6.3) 8 (2.8)
Ethnicity 0.147 0.413
 Fars 404 (85.8) 322 (79.7) 36 (8.9) 28 (6.9) 18 (4.5) 276 (68.3) 86 (21.3) 30 (7.4) 12 (3)
 Other 67 (14.2) 48 (71.6) 12 (17.9) 5 (7.5) 2 (3) 45 (67.2) 11 (16.4) 7 (10.4) 4 (6.0)
Smoking < 0.001 < 0.001
 No 446 (94.7) 359 (80.5) 43 (9.6) 29 (6.5) 15 (3.3) 312 (70.0) 89 (20.0) 30 (6.7) 15 (3.3)
 Yes 25 (5.3) 11 (44.0) 5 (20.0) 4 (16.0) 5 (20.0) 9 (36.0) 8 (32.0) 7 (28.0) 1 (4.0)
BMI 0.321 0.776
 < 25 kg/m2 361 (76.6) 279 (77.3) 36 (10.0) 29 (8.0) 17 (4.7) 248 (68.7) 74 (20.5) 26 (7.2) 13 (3.6)
 ≥ 25 kg/m2 110 (23.4) 91 (82.7) 12 (10.9) 4 (3.6) 3 (2.7) 73 (66.4) 23 (20.9) 11 (10.0) 3 (2.7)
Physical activity 0.594 0.133
 Low 218 (46.3) 167 (76.6) 24 (11.0) 19 (8.7) 8 (3.7) 147 (67.4) 49 (22.5) 18 (8.3) 4 (1.8)
 Moderate 135 (28.7) 104 (77.0) 15 (11.1) 8 (5.9) 8 (5.9) 85 (63.0) 28 (20.7) 14 (10.4) 8 (5.9)
 High 118 (25.0) 99 (83.9) 9 (7.6) 6 (5.1) 4 (3.4) 89 (75.4) 20 (16.9) 5 (4.2) 4 (3.4)
Family WI 0.790 0.787
 Poorest 102 (21.7) 84 (82.3) 8 (7.8) 7 (6.9) 3 (2.9) 71 (69.6) 19 (18.6) 9 (8.8) 3 (2.9)
 Poor 98 (20.8) 79 (80.6) 6 (6.1) 8 (8.2) 5 (5.1) 68 (69.4) 19 (19.4) 6 (6.1) 5 (5.1)
 Moderate 84 (17.9) 67 (79.8) 10 (11.9) 5 (6.0) 2 (2.3) 57 (67.9) 20 (23.8) 7 (8.3) 0 (0.0)
 Rich 93 (19.8) 68 (73.1) 11 (11.8) 8 (8.6) 6 (6.5) 65 (69.9) 15 (16.1) 9 (9.7) 4 (4.3)
 Richest 93 (19.8) 71 (76.3) 13 (14.0) 5 (5.4) 4 (4.3) 60 (64.5) 23 (24.7) 6 (6.5) 4 (4.3)
Sleep duration 0.005 0.053
 < 7 h 197 (41.8) 142 (72.1) 20 (10.1) 20 (10.7) 14 (7.1) 121 (61.4) 44 (22.3) 24 (12.2) 8 (4.1)
 ≥ 7 to < 9 h 244 (51.8) 206 (84.4) 23 (9.4) 9 (3.7) 6 (2.5) 178 (72.9) 46 (18.9) 12 (4.9) 8 (3.3)
 ≥ 9 h 30 (6.4) 22 (73.3) 5 (16.7) 3 (10.0) 0 (0.0) 22 (73.3) 7 (23.3) 1 (3.3) 0 (0.0)

Values are presented as n (%).

BMI, body mass index; WI, wealth index; CI, confidence interval; h, hour.

Table 2.
Adjusted association of sleep duration with depression (using multinomial logistic regression model)
Variables Category Models* Depression
Mild
Moderate
Severe
OR 95% CI p-value OR 95% CI p-value OR 95% CI p-value
Sleep duration ≥ 7 to < 9 h - 1 - - 1 - - 1 - -
< 7 h Model 1 1.24 0.65, 2.36 0.509 3.63 1.60, 8.22 0.002 3.68 1.37, 9.91 0.01
Model 2 1.15 0.60, 2.20 0.682 3.86 1.69, 8.81 0.001 3.86 1.42, 10.47 0.008
Model 3 1.10 0.56, 2.14 0.784 3.61 1.56, 8.36 0.003 3.16 1.12, 8.93 0.03
≥ 9 h Model 1 2.05 0.70, 5.98 0.188 2.88 0.72, 11.54 0.135 < 0.001 - -
Model 2 1.90 0.64, 5.63 0.245 3.02 0.75, 12.23 0.121 < 0.001 - -
Model 3 1.73 0.57, 5.27 0.337 2.39 0.57, 10.09 0.234 < 0.001 - -

* Model 1: adjusted for sex, age, and marital status. Model 2: adjusted for sex, age, marital status, family residency, family number, and ethnicity. Model 3: adjusted for sex, age, marital status, family residency, family number, ethnicity, smoking, BMI, physical activity, and WI.

OR, odds ratio; CI, confidence interval; BMI, body mass index; WI, wealth index; h, hour.

Table 3.
Adjusted association of sleep duration with anxiety (using multinomial logistic regression model)
Variables Category Models* Anxiety
Mild
Moderate
Severe
OR 95% CI p-value OR 95% CI p-value OR 95% CI p-value
Sleep duration ≥ 7 to < 9 h - 1 - - 1 - - 1 - -
< 7 h Model 1 1.51 0.93, 2.45 0.096 3.14 1.50, 6.59 0.002 1.54 0.55, 4.31 0.411
Model 2 1.46 0.89, 2.39 0.130 3.07 1.45, 6.5 0.003 1.25 0.43, 3.62 0.675
Model 3 1.35 0.82, 2.24 0.241 2.74 1.26, 5.96 0.011 1.14 0.38, 3.41 0.811
≥ 9 h Model 1 1.16 0.45, 2.94 0.755 0.62 0.08, 5.04 0.653 < 0.001 - -
Model 2 1.12 0.44, 2.87 0.816 0.61 0.07, 5.03 0.645 < 0.001 - -
Model 3 1.09 0.42, 2.83 0.866 0.46 0.05, 4.06 0.487 < 0.001 - -

* Model 1: adjusted for sex, age, and marital status; Model 2: adjusted for sex, age, marital status, family residency, family number, and ethnicity; Model 3: adjusted for sex, age, marital status, family residency, family number, ethnicity, smoking, BMI, physical activity, and family WI.

OR, odds ratio; CI, confidence interval; BMI, body mass index; WI, wealth index; h, hour.