Sleep disorders and their associations with anxiety and depression among male detoxification patients under compulsory isolation in Yunnan Province, China

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Methods Data were collected from a cross-sectional health interview and examination survey of 1,021 drug users among male detoxification patients under compulsory isolation in China. Sleep disorders, anxiety, and depressionsymptoms were evaluated using the Pittsburgh Sleep Quality Index (PSQI), Zung’s Self-Rating Anxiety Scale (SAS), and the Self-rating Depression Scale (SDS), respectively. Sleep disorders and anxiety and depression symptoms were evaluated using multivariate logistic regression. Results The prevalence of sleep disorders, anxiety, and depression symptoms were 73.0%, 8.9%, and 6.9%, respectively. Ethnic minorities, participants with a lower level of education, and participants with poor health status by self-assessment had a higher prevalence of sleep disorders than their counterparts ( P <0.05). Participants who consumed ephedrine had the highest prevalence of sleep disorders ( P <0.05), while those who consumed heroin had the highest prevalence of anxiety symptoms ( P <0.001). Multivariate logistic regression analysis uncovered that those with sleep disorders had a greater probability of having anxiety (OR=2.310; 95% CI: 1.116 to 4.783) and depression symptoms (OR=4.683; 95% CI: 1.664 to 13.180). Conclusions Male detoxification patients under compulsory isolation in China experience a high level of sleep disorders, and their sleep disorders are significantly associated with anxiety and depression symptoms. Improving sleep quality may reduce the prevalence of anxiety and depression symptoms in the male detoxification patient population. Sleep disorders anxiety symptoms depression symptoms male detoxification compulsory isolations China Introduction While the number of drug abusers worldwide has been on an upward trend, increasing from 240 million in 2011 to 296 million in 2021[ 1 ], in China the number of illicit drug users has steadily declined over the past five years, from 2.4 million in 2018 to 896,000 in 2023[ 2 , 3 ]. In 2023, a total of 36,000 people were required to undergo compulsory isolated drug detoxification in China, marking a year-on-year decrease of 14.1% [ 4 ]. Previous studies indicate that the prevalence of sleep disorders is higher among substance abusers [ 5 ]. Sleep disorders are often seen in those with substance use disorders during periods of active use as well as during detoxification and recovery [ 6 ]. Meanwhile, there is a growing recognition that psychostimulant abuse (such as methamphetamine and cocaine use) [ 7 , 8 ] as well as narcotics abuse (such as heroin and marijuana use) [ 8 , 9 ] both have adverse impacts on sleep, manifesting as disorders including insomnia, hypersomnia, Circadian rhythm disturbance, and daytime dysfunction[ 8 , 9 ]. Different types of drug abuse have varying impacts on sleep disorders. However, there is a lack of both comparative analyses of sleep disorders between single and polydrug users, as well as a lack of analyses of different types of single drug users among compulsory drug detoxification populations, including in China. Previous research demonstrates that drug abuse increases the risk of developing psychological disorders, and the risk of anxiety and depression rises with increasing dose and duration of drug use[ 10 ]. Globally, approximately 64 million people live with substance use disorders [ 1 ], and major anxiety disorders and depressive disorders are the most common psychiatric complications among those addicted to drugs [ 1 ]. Biologically, several neurotransmitter systems are critically involved in the regulation of sleep, anxiety, and depression[ 11 , 12 ]. While many drugs induce neurotoxic effects on the nervous system, their mechanisms of action differ significantly, and drug withdrawal symptoms vary depending on the specific pharmacological pathways involved[ 13 ]. Quality sleep is essential for the regulation of negative emotion and mental health. The co-occurrence of sleep disorders with various psychiatric conditions, including anxiety and depression, has been established in previous research[ 14 ]. The relationship is bi-directional: not only is sleep disturbance a phenotypic characteristic of various psychiatric illnesses, but it also may induce and exacerbate psychiatric illnesses[ 14 ]. In China, compulsory drug detoxification treatment is the primary method of drug rehabilitation. Previous Chinese studies indicate that prevalence of sleep disorders and anxiety and depression symptoms were higher among individuals under compulsory drug detoxification isolation (19.0%, 5.0%, and 3.6%, respectively) than in the general population [ 15 , 16 ]. These symptoms were most likely to arise during the period of acute withdrawal. However, during the later periods of rehabilitation, a degree of symptom mitigation was likely to occur[ 4 ]. In addition, drug users who are undergoing compulsory detoxification often experience sleep disorders, anxiety, and depression[ 5 , 7 , 17 ]. These conditions may interact to form a vicious cycle, reducing the effectiveness of rehabilitation and increasing the risk of relapse [ 14 , 18 , 19 ]. However, most studies on compulsory drug detoxification populations have focused solely on analyzing the prevalence of sleep disorders or mental health [ 5 , 7 , 17 ]. The interactions of sleep disorders and anxiety and depression symptoms have not been comprehensively examined among this population in China, and the relationships between sleep disorders and the symptoms of anxiety and depression were unclear. Yunnan Province, adjacent to the “Golden Triangle”, a major drug production region, has one of the highest populations of illicit drug users in China[ 20 ]. Although drug-related cross-border criminal activities are active in Yunnan and the problem of polydrug use remains[ 20 ], in recent years, both drug-related crime and the number of illicit drug users have steadily declined, and cross-border drug infiltration risks have been effectively curbed. The current population of drug users has dropped from 81,000 in 2023 to 70,000 in 2024, and the number of drug users under compulsory drug detoxification also decreased from 2023 to 2024[ 21 ]. However, evidence of possible relationships between sleep disorders and the symptoms of anxiety and depression among detoxification patients under compulsory isolation is lacking in China, especially epidemiological studies with large participant populations. Thus, the present study aimed to analyze the prevalence of sleep disorders and associations with anxiety and depression symptoms among male detoxification patients under compulsory isolation in Yunnan Province, China. Methods Data sources and study population This study was conducted in male compulsory isolation sites in Yunnan Province from 2023 to 2024 using a compulsory isolations-based, cross-sectional health interview survey. A two-stage cluster sampling method was applied to select study participants from eighteen male compulsory isolation sites. First, eighteen male compulsory isolation sites in Yunnan were classified into five categories based on geographical location: central, northern, southern, western, and eastern. One compulsory isolation site was chosen by probability proportional to size (PPS) from each of these five categories, for a total of five compulsory isolation sites. Second, cluster sampling method was used to select eligible male detoxification patients from each of the five compulsory isolation sites to participate in this study. Data collection and measurement All consenting participants were interviewed by trained interviewers in person, face-to-face, using a structured, pre-tested questionnaire to collect demographic information (sex, age, ethnicity, residence, marital status, and education level), self-assessment of health status, and types and duration of drug use. Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI) [ 22 ]. PSQI consists of 19 items and seven components, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each component is scored from 0 to 3 points, and the seven components score then summed to obtain a total score, from 0 to 21; a higher PSQI score indicates poorer sleep quality. Anxiety and depression symptoms were evaluated using the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS)[ 23 , 24 ], respectively. Each scale consists of 20 items rated on a 4-point scale ranging from 1 point ("Not at all or a little of the time") to 4 points ("Most or all of the time"), with positively worded items directly scored and reverse-worded items reverse-scored. The raw total score ranges from 20 to 80 points, and the standard score is obtained by multiplying the raw total score by 1.25. Drug abuse was evaluated by Drug Abuse Screening Test-10 (DAST-10), with a total score ranging from 0 to 10 [ 25 ]. Higher total scores indicate a higher level of drug abuse. All information obtained in the interview was recorded based on the self-report of participants. Definitions Sleep disorders were considered PSQI scores of > 7. Anxiety symptoms were defined as SAS standard score of ≥ 50, while depression symptoms were defined as having an SDS standard score of ≥ 53, all scores specific to the Chinese population[ 26 ]. Polydrug use was defined as the consumption of more than one type of drug, according to the WHO definition [ 27 ]. Drug abuse was classified into two levels: low and moderate to severe. Low refers to DAST-10 score ranges from 0 to 2, while moderate to severe was indicated by a DAST-10 score ranging from 3 to 10. Ethnicity was divided into two groups: Han majority and ethnic minority. China officially recognizes 56 distinct ethnic groups under its national classification system. Ethnic minority refers to distinct ethnic groups that exhibit substantial differences with the Han majority population in language, religion, culture, and settlement patterns. In this study, the ethnic minority group included participants of 13 ethnic minorities: Hui, Hani, Dai, Yi, Bai, Bulang, Zang, Jingbo, Lahu, Naxi, Va, Yao, and Zhuang. Ethics approval The Ethics Committee of Kunming Medical University approved this study prior to the commencement of research (Approval No. KMMU2024MEC241). Informed consent was obtained in writing from all study participants. Statistical analysis Data analyses were conducted using SPSS24.0 software. Categorical variables were described as counts and percentages. A chi-squared test was used to compare categorical variables among different groups. Multivariate logistic regression analysis was used to analyze the associations of sleep disorders with anxiety and depression symptoms, after adjusting for age, ethnicity, level of education, self-assessment of health status, and type and duration of drug use. Associations were expressed as odds ratios (OR) with 95% confidence intervals (CI). All of the statistical significance determinations were grounded in two-tailed P values of < 0.05. Results In total, 1040 male detoxification patients under compulsory isolation were invited to participate in the survey. Of these, 1021 consented, resulting in an overall response rate of 98.17%. Table 1 shows general characteristics of the study population. In total, 597 (58.5%) of participants were Han majority ethnicity and 424 (41.5%) were ethnic minorities. Of these study participants, 26.5% were polydrug users and 73.5% were single drug users. The proportion of individuals aged 25–44 years, residing in rural areas, with an education level of primary or below, an unemployed status, and marital status of single, divorced, or widowed was 61.9%, 80.6%, 49.2%, 17.6%, and 66.4%, respectively. Heroin was the most prevalent form of single drug consumption (35.0%), followed by ephedrine (26.6%) and methamphetamine (7.3%). Table 1 General characteristics of the study population Characteristic n % Age group (n, %) 18 ~ 24 45 4.4 25 ~ 34 306 30.0 35 ~ 44 326 31.9 45 ~ 54 240 23.5 55 ~ 64 90 8.8 ≥ 65 14 1.4 Ethnicity (n, %) Han 597 58.5 Minority 424 41.5 Residence (n, %) Rural 823 80.6 Urban 198 19.4 Level of education (n, %) Primary (grade 1–6) or lower 502 49.2 Middle (grade 7–9) or higher 519 50.8 Occupation (n, %) Unemployed 180 17.6 Farmer or other 841 82.4 Marital status (n, %) Unmarried/divorced/widowed 678 66.4 Married or cohabitating 343 33.6 Type of drug use (n, %) Single drug use 750 73.5 Heroin 357 35.0 Ephedrine 272 26.6 Methamphetamine 75 7.3 Other 46 4.5 Polydrug use 271 26.5 Table 2 indicates prevalence of sleep disorders by different characteristics among the study population. Ethnic minorities and individuals with a lower level of education and poor health status by self-assessment had higher prevalence of sleep disorders than their counterparts ( P < 0.05). Furthermore, the highest prevalence of sleep disorders was found among individuals who consumed ephedrine ( P < 0.05). Table 2 Prevalence of sleep disorders among male detoxification patients by different characteristics in Yunnan Province, China Characteristic Sleep disorders n (%) Age group (years) 18–24 36(80.0) 25–34 209(6.3) 35–44 241(73.6) 45–54 179(74.6) 55–64 70(77.8) ≥ 65 11(78.6) Ethnicity Han 411(68.8) ** Minority 334(78.8) Residence Rural 605(73.5) Urban 140(70.7) Level of education Primary (grade 1–6) or lower 382(76.1) * Middle (grade 7–9) or higher 363(69.9) Health status by self-assessment Good 43(52.4) ** Normal 575(72.9) Poor 127(84.7) Level of drug abuse No problem or low level 58(73.4) Moderate to severe level 687(72.9) Type of drug use Single drug use 537(71.6) Heroin 254(71.1) * Ephedrine 209(76.8) Methamphetamine 45(60.0) Other 29(63.0) Polydrug use 208(76.8) Duration of drug use (years) ≤ 5 103(71.0) 6 ~ 15 377(71.4) 16 ~ 25 145(75.9) ≥ 26 120(76.4) All 745(73.0) * P < 0.05, ** P < 0.01 Table 3 presents the prevalence of anxiety and depression symptoms by different characteristics among the study population. Individuals with older age, worse health status by self-assessment, longer duration of drug use, and sleep disorders all had a higher prevalence of anxiety and depression symptoms than their counterparts ( P < 0.05). Furthermore, individuals who consumed heroin had the highest prevalence of anxiety symptoms compared to individuals who consumed any other type of drug(s) ( P < 0.001). Table 3 Prevalence of anxiety and depression symptoms among male detoxification patients by different characteristics in Yunnan Province, China Characteristic Anxiety symptoms (n, %) Depression symptoms (n, %) Age group 18 ~ 24 1(2.2) ** 2(4.4) ** 25 ~ 34 19(6.2) 15(4.9) 35 ~ 44 20(6.1) 18(5.5) 45 ~ 54 29(12.1) 20(8.3) 55 ~ 64 16(17.8) 8(8.9) ≥ 65 6(42.9) 7(50.0) Ethnicity Han 50(8.4) 37(6.2) Minority 41(9.7) 33(7.8) Residence Rural 78(9.5) 59(7.2) Urban 13(6.6) 11(5.6) Level of education Primary (grade 1 ~ 6) or lower 47(9.4) 33(6.6) Middle (grade 7 ~ 9) or higher 44(8.5) 37(7.1) Health status by self-assessment Good 3(3.7) ** 5(6.1) ** Normal 43(5.4) 31(3.9) Poor 45(30.0) 34(22.7) Level of drug abuse No problem or low level 8(10.1) 6(7.6) Moderate to severe levels 83(8.8) 64(6.8) Type of drug use Single drug use 63(8.4) 45(6.0) Heroin 46(12.9) ** 30(8.4) Ephedrine 10(3.7) 9(3.3) Methamphetamine 2(2.7) 4(5.3) Other 5(10.9) 2(4.3) Polydrug use 28(10.3) 25(9.2) Duration of drug use (years) ≤ 5 7(4.8) ** 10(6.9) * 6 ~ 15 43(8.1) 25(4.7) 16 ~ 25 10(5.2) 14(7.3) ≥ 26 31(19.7) 21(13.4) Sleep disorder Yes 76(10.2) * 66(8.9) ** No 15(5.4) 4(1.4) All 91(8.9) 70(6.9) * P < 0.05, ** P < 0.01 Table 4 displays the results of multivariate logistic regression for prevalence of anxiety and depression symptoms. After adjusting for age, ethnicity, level of education, health status by self-assessment, and type and duration of drug use, individuals with sleep disorders had a greater probability of having anxiety (OR = 2.310; 95% CI: 1.116 to 4.783) and depression symptoms (OR = 4.683; 95% CI: 1.664 to 13.180). Table 4 Odds ratios (OR) and 95% confidence intervals (CI) for multi-variable logistic regression for prevalence of anxiety and depression symptoms Characteristic Anxiety symptoms (reference: no) Depression symptoms (reference: no) Adjusted OR (95% CI) † Adjusted OR (95% CI) Sleep disorder (reference: no) 2.310 (1.116, 4.783) * 4.683 (1.664, 13.180) * * P < 0.05, ** P < 0.01, † adjusted for age, ethnicity, level of education, health status by self-assessment, type of drug use, and duration of drug use Discussion The findings indicate prevalence of sleep disorders varied by socioeconomic factors and type of drug use among male detoxification patients under compulsory isolation in Yunnan Province, China. Furthermore, sleep disorders were independently correlated with a higher risk of having anxiety and depression symptoms. In this study, the prevalence of sleep disorders among male detoxification patients under compulsory isolation was significantly higher than in the general Chinese population [ 15 ], among detoxification patients under compulsory isolation centers in Changsha and Beijing [ 5 , 28 ], and among drug users in residential centers for the treatment of drug use in Iran, Jordan, and Vietnam[ 29 – 31 ]. However, it was lower than among drug users undergoing treatment or recovery in the United States, Taiwan, Germany, and Thailand [ 32 – 35 ]. This result possibly can be attributed to disparities in drug control policies, demographic characteristics, types of drug use, and detoxification and rehabilitation methodologies across nations, leading to differential outcomes in sleep quality among the drug use population. Furthermore, the prevalence of sleep disorders varied among single drug use groups, consistent with previous studies[ 5 , 7 ]. This may be related to disparities in neurotransmitter dysregulation and structural and functional impairments caused by different drugs [ 36 ]. The results of the study reveal that ethnic minority male detoxification patients and those with a lower level of education had a higher prevalence of sleep disorders than their counterparts. This may result from the fact that ethnic minorities may face pressures from family conflicts, poorer social adaptability, and intensified job-seeking stress, which may cumulatively exacerbate sleep disorders[ 37 ]. Meanwhile, individuals with lower educational attainment demonstrate diminished health awareness, greater economic pressure, disadvantaged sleep environments, and elevated prevalence of sleep disorders[ 38 ]. Consistent with previous research[ 39 ], poor health status by self-assessment correlated with sleep disorders, potentially mediated by somatic discomfort, anxiety, and depression symptoms, which are associated with a higher prevalence of sleep disorders. In this study, the prevalence of anxiety and depression was slightly higher than in the general population in China[ 16 ], but lower than found in previous research on detoxification patients in five compulsory isolation centers in China[ 40 ], and among drug users undergoing treatment or recovery in the United States, Saudi Arabia, India and Myanmar[ 41 – 44 ]. This possibly relates to the effects of intervention strategies in the study population and the extension of services of compulsory drug rehabilitation centers in recent years. Measures such as providing vocational training, regular family visitation and guidance, and psychological intervention to individuals undergoing compulsory detoxification have substantially enhanced reintegration into society, concurrently contributing to the alleviation of anxiety and depression symptoms[ 4 , 21 , 45 ]. Our study found that heroin users had the highest prevalence of anxiety symptoms. This result is inconsistent with a previous study that found that methamphetamine users had higher anxiety scores than heroin users[ 46 ]. This possibly results from the fact that heroin users tend to be of older age and tend to have a longer duration of drug use, whereas ephedrine and methamphetamine users are predominantly younger with shorter duration of drug use[ 2 , 3 ]. The abuse of heroin, ephedrine, and methamphetamine is linked to drug-induced psychosis[ 46 ], but the differences in their neurobiological mechanisms remain poorly understood. Individuals with drug use disorders have varying degrees of emotional regulation impairments depending on the drug involved, and are more prone to develop anxiety and other negative emotions compared to the general population[ 40 ]. Consistent with previous research, the findings of this study indicated that the prevalence of anxiety and depression increased with age as well as the duration of drug use [ 10 , 47 ]. Chronic drug use may lead to altered cerebral hemodynamics, reduced density of brain dopamine transporter, and neurobiological disturbance, potentially contributing to the neurobiological vulnerability underlying drug induced psychotic disorders[ 48 ]. Poor health status by self-assessment has been demonstrated to have significant associations with symptoms of anxiety [ 49 ]. Those with poor health status by self-assessment may demonstrate a cluster of risk factors, including older age, extended duration of drug use, a suboptimal physical health profile, reduced health-rated quality of life, and compromised psychosocial functioning. These interrelated risk factors may synergistically predispose individuals to heightened vulnerability to anxiety symptoms or aggravate pre-existing symptomatology. Our data also showed that the prevalence of anxiety and depression was higher among individuals with sleep disorders. The association between sleep disorders and mental health symptoms remained significant even after adjusting for other potential confounding factors. Sleep disorders can impair emotional regulation, increasing the risk of anxiety and depression[ 50 ]. Meanwhile, in this study, sleep disorders were more common among individuals undergoing compulsory drug detoxification. As sleep disorders exacerbate the effects of anxiety and depression, future psychological interventions should integrate sleep disorder treatments into mental health services, while concurrently mitigating sleep-related adverse impacts on psychological well-being. The findings are limited in several respects. First, the level of drug abuse was evaluated using DAST-10, which lacks an objective measure of drug use frequency and dosage levels. Second, the assessment of sleep disorders and anxiety and depression symptoms relied exclusively on subjective reports, lacking an objective monitoring and evaluation of sleep patterns and of psychological symptoms. Third, the study was cross-sectional in design, so causal relationships cannot be determined. Finally, this study lacks comparative analysis with non-drug using populations in the local region, which limits the generalizability of the research findings. Conclusion Sleep disorders have strong impacts on anxiety and depression symptoms among male detoxification patients under compulsory isolation in Yunnan Province, China. Our findings highlight that future anxiety and depression interventions should take sleep quality into account. Declarations Ethical approval and consent to participate This study was approved by the Ethics Committee of Kunming Medical University prior to the commencement of research. Written informed consent was obtained from all individuals participating in the study, and the Ethics Committee of Kunming Medical University approved this consent procedure. This study was performed in accordance with the Declaration of Helsinki. Consent for publication Not applicable. Competing interests The authors declare that there are no conflicts of interest. Clinical trial number Not applicable Funding The data collection and analysis of this study was supported by a grant from NHC Key Lab of Drug Addiction Medicine(Kunming Medical University)Open Projects Fund (KN202419); First-Class Discipline Team of Kunming Medical University (2024XKTDTS16) and Master’s Education Innovation Fund of Kunming Medical University (2025S155). The funders had no role in the study design, decision to publish, or preparation of the manuscript. Author Contribution XML carried out the study and drafted the manuscript. LC designed the study and revised the manuscript. GHL, CYR, QRB, RMS, and FG collected the data. ARG provided comments on the paper during the writing process. All authors have read and approved the manuscript. Acknowledgements Not applicable. Availability of data and material The datasets used and/or analyzed in this study are available from the corresponding author on reasonable request. 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Xu C, Acevedo P, Wang L, Wang N, Ozuna K, Shafique S, Karithara A, Padilla V, Mao C, Xie X et al. Sleep Apnea and Substance Use Disorders Associated with Co-Occurrence of Anxiety Disorder and Depression among U.S. Adults: Findings from the NSDUH 2008–2014. Brain Sci 2023, 13(4). Kar H, Gania AM, Bandy A, Ud Din Dar N, Rafiq F. Psychiatric comorbidities and concurrent substance use among people who inject drugs: a single-centre hospital-based study. Sci Rep. 2023;13(1):19053. Kyaw KWY, Platt L, Bijl M, Rathod SD, Naing AY, Roberts B. The effect of different types of migration on symptoms of anxiety or depression and experience of violence among people who use or inject drugs in Kachin State, Myanmar. Harm Reduct J. 2023;20(1):45. Lin W, Zhou W. Factors associated with the physical and mental health of drug users participating in community-based drug rehabilitation programmes in China. Health Soc Care Community. 2020;28(2):584–90. Li W, Wang L, Lyu Z, Chen J, Li Y, Sun Y, Zhu J, Wang W, Wang Y, Li Q. Difference in topological organization of white matter structural connectome between methamphetamine and heroin use disorder. Behav Brain Res. 2022;422:113752. Belov OO, Pshuk NG. Age and gender features of depressive and anxiety symptomatics of depressive disorders. Wiad Lek. 2020;73(7):1476–9. Iyo M, Sekine Y, Mori N. Neuromechanism of developing methamphetamine psychosis: a neuroimaging study. Ann N Y Acad Sci. 2004;1025:288–95. Juarez Padilla J, Singleton CR, Pedersen CA, Lara-Cinisomo S. Associations between Self-Rated Health and Perinatal Depressive and Anxiety Symptoms among Latina Women. Int J Environ Res Public Health 2022, 19(19). Palmer CA, Oosterhoff B, Bower JL, Kaplow JB, Alfano CA. Associations among adolescent sleep problems, emotion regulation, and affective disorders: Findings from a nationally representative sample. J Psychiatr Res. 2018;96:1–8. 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Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":false,"prefix":"","firstName":"Guo-hui","middleName":"","lastName":"LI","suffix":""},{"id":502149581,"identity":"a7e73612-26c7-4d3a-af06-964fcf71404e","order_by":2,"name":"Chun-yi RUAN","email":"","orcid":"","institution":"NHC Key Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":false,"prefix":"","firstName":"Chun-yi","middleName":"","lastName":"RUAN","suffix":""},{"id":502149582,"identity":"5d38b378-a776-4393-9efe-b85b64c3a34a","order_by":3,"name":"Qing-rou BAO","email":"","orcid":"","institution":"NHC Key Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":false,"prefix":"","firstName":"Qing-rou","middleName":"","lastName":"BAO","suffix":""},{"id":502149583,"identity":"6bca714d-dc48-469f-b25a-0f53dcfd8d36","order_by":4,"name":"Rui-min SHI","email":"","orcid":"","institution":"NHC Key Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":false,"prefix":"","firstName":"Rui-min","middleName":"","lastName":"SHI","suffix":""},{"id":502149584,"identity":"a793db45-76a9-4fd3-858c-fe9b1843d877","order_by":5,"name":"Fan GU","email":"","orcid":"","institution":"NHC Key Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"GU","suffix":""},{"id":502149585,"identity":"d847e649-e516-40a9-9ab5-72dc81762d9f","order_by":6,"name":"Allison Rabkin GOLDEN","email":"","orcid":"","institution":"NHC Key Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":false,"prefix":"","firstName":"Allison","middleName":"Rabkin","lastName":"GOLDEN","suffix":""},{"id":502149586,"identity":"4f0ffc45-8378-4abd-be9f-a43745a60d91","order_by":7,"name":"Le CAI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYFACxsYDDAYScvwSYJ6EDDFaGg4wVNgYS84AsoBaeIiy5wDDmbTEDTfAWhgIa+FvP9xw4GPbYcbNt5uPP7pRY8HDwH746AZ8WiTOJDYcnNl2mNnszrHE5pxjQIfxpKXdwKfFgCGx4TBv22E2sxs5hs05bEAtEjxm+LXwP2w4/LftMI/xDJCWf8RokQDaAvS+hIEEUEtuGxFaJG48bDjYU2FjIHEjLXF2bp8EDxshv/D3pz988MNAor5/RvKBzznf6uT42Q8fw6sFE7CRpnwUjIJRMApGATYAAMIoTc+WawYbAAAAAElFTkSuQmCC","orcid":"","institution":"NHC Key Laboratory of Drug Addiction Medicine, Kunming Medical University, Kunming 650500","correspondingAuthor":true,"prefix":"","firstName":"Le","middleName":"","lastName":"CAI","suffix":""}],"badges":[],"createdAt":"2025-06-30 10:08:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7009295/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7009295/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89570151,"identity":"cd0e7b9d-0cb5-487d-be8b-29a37aee332e","added_by":"auto","created_at":"2025-08-21 12:02:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":854767,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7009295/v1/c8bbbd8a-a62a-4ab2-8668-7c57965cdf15.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sleep disorders and their associations with anxiety and depression among male detoxification patients under compulsory isolation in Yunnan Province, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWhile the number of drug abusers worldwide has been on an upward trend, increasing from 240\u0026nbsp;million in 2011 to 296\u0026nbsp;million in 2021[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], in China the number of illicit drug users has steadily declined over the past five years, from 2.4\u0026nbsp;million in 2018 to 896,000 in 2023[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In 2023, a total of 36,000 people were required to undergo compulsory isolated drug detoxification in China, marking a year-on-year decrease of 14.1% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious studies indicate that the prevalence of sleep disorders is higher among substance abusers [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Sleep disorders are often seen in those with substance use disorders during periods of active use as well as during detoxification and recovery [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Meanwhile, there is a growing recognition that psychostimulant abuse (such as methamphetamine and cocaine use) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] as well as narcotics abuse (such as heroin and marijuana use) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] both have adverse impacts on sleep, manifesting as disorders including insomnia, hypersomnia, Circadian rhythm disturbance, and daytime dysfunction[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDifferent types of drug abuse have varying impacts on sleep disorders. However, there is a lack of both comparative analyses of sleep disorders between single and polydrug users, as well as a lack of analyses of different types of single drug users among compulsory drug detoxification populations, including in China.\u003c/p\u003e\u003cp\u003ePrevious research demonstrates that drug abuse increases the risk of developing psychological disorders, and the risk of anxiety and depression rises with increasing dose and duration of drug use[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Globally, approximately 64\u0026nbsp;million people live with substance use disorders [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and major anxiety disorders and depressive disorders are the most common psychiatric complications among those addicted to drugs [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Biologically, several neurotransmitter systems are critically involved in the regulation of sleep, anxiety, and depression[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While many drugs induce neurotoxic effects on the nervous system, their mechanisms of action differ significantly, and drug withdrawal symptoms vary depending on the specific pharmacological pathways involved[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Quality sleep is essential for the regulation of negative emotion and mental health. The co-occurrence of sleep disorders with various psychiatric conditions, including anxiety and depression, has been established in previous research[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The relationship is bi-directional: not only is sleep disturbance a phenotypic characteristic of various psychiatric illnesses, but it also may induce and exacerbate psychiatric illnesses[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn China, compulsory drug detoxification treatment is the primary method of drug rehabilitation. Previous Chinese studies indicate that prevalence of sleep disorders and anxiety and depression symptoms were higher among individuals under compulsory drug detoxification isolation (19.0%, 5.0%, and 3.6%, respectively) than in the general population [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These symptoms were most likely to arise during the period of acute withdrawal. However, during the later periods of rehabilitation, a degree of symptom mitigation was likely to occur[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In addition, drug users who are undergoing compulsory detoxification often experience sleep disorders, anxiety, and depression[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These conditions may interact to form a vicious cycle, reducing the effectiveness of rehabilitation and increasing the risk of relapse [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, most studies on compulsory drug detoxification populations have focused solely on analyzing the prevalence of sleep disorders or mental health [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The interactions of sleep disorders and anxiety and depression symptoms have not been comprehensively examined among this population in China, and the relationships between sleep disorders and the symptoms of anxiety and depression were unclear.\u003c/p\u003e\u003cp\u003eYunnan Province, adjacent to the “Golden Triangle”, a major drug production region, has one of the highest populations of illicit drug users in China[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Although drug-related cross-border criminal activities are active in Yunnan and the problem of polydrug use remains[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], in recent years, both drug-related crime and the number of illicit drug users have steadily declined, and cross-border drug infiltration risks have been effectively curbed. The current population of drug users has dropped from 81,000 in 2023 to 70,000 in 2024, and the number of drug users under compulsory drug detoxification also decreased from 2023 to 2024[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, evidence of possible relationships between sleep disorders and the symptoms of anxiety and depression among detoxification patients under compulsory isolation is lacking in China, especially epidemiological studies with large participant populations. Thus, the present study aimed to analyze the prevalence of sleep disorders and associations with anxiety and depression symptoms among male detoxification patients under compulsory isolation in Yunnan Province, China.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eData sources and study population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study was conducted in male compulsory isolation sites in Yunnan Province from 2023 to 2024 using a compulsory isolations-based, cross-sectional health interview survey. A two-stage cluster sampling method was applied to select study participants from eighteen male compulsory isolation sites. First, eighteen male compulsory isolation sites in Yunnan were classified into five categories based on geographical location: central, northern, southern, western, and eastern. One compulsory isolation site was chosen by probability proportional to size (PPS) from each of these five categories, for a total of five compulsory isolation sites. Second, cluster sampling method was used to select eligible male detoxification patients from each of the five compulsory isolation sites to participate in this study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData collection and measurement\u003c/b\u003e\u003c/p\u003e\u003cp\u003e All consenting participants were interviewed by trained interviewers in person, face-to-face, using a structured, pre-tested questionnaire to collect demographic information (sex, age, ethnicity, residence, marital status, and education level), self-assessment of health status, and types and duration of drug use. Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. PSQI consists of 19 items and seven components, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each component is scored from 0 to 3 points, and the seven components score then summed to obtain a total score, from 0 to 21; a higher PSQI score indicates poorer sleep quality. Anxiety and depression symptoms were evaluated using the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], respectively. Each scale consists of 20 items rated on a 4-point scale ranging from 1 point (\"Not at all or a little of the time\") to 4 points (\"Most or all of the time\"), with positively worded items directly scored and reverse-worded items reverse-scored. The raw total score ranges from 20 to 80 points, and the standard score is obtained by multiplying the raw total score by 1.25. Drug abuse was evaluated by Drug Abuse Screening Test-10 (DAST-10), with a total score ranging from 0 to 10 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Higher total scores indicate a higher level of drug abuse. All information obtained in the interview was recorded based on the self-report of participants.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDefinitions\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eSleep disorders were considered PSQI scores of \u0026gt; 7. Anxiety symptoms were defined as SAS standard score of ≥ 50, while depression symptoms were defined as having an SDS standard score of ≥ 53, all scores specific to the Chinese population[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePolydrug use was defined as the consumption of more than one type of drug, according to the WHO definition [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Drug abuse was classified into two levels: low and moderate to severe. Low refers to DAST-10 score ranges from 0 to 2, while moderate to severe was indicated by a DAST-10 score ranging from 3 to 10.\u003c/p\u003e\u003cp\u003eEthnicity was divided into two groups: Han majority and ethnic minority. China officially recognizes 56 distinct ethnic groups under its national classification system. Ethnic minority refers to distinct ethnic groups that exhibit substantial differences with the Han majority population in language, religion, culture, and settlement patterns. In this study, the ethnic minority group included participants of 13 ethnic minorities: Hui, Hani, Dai, Yi, Bai, Bulang, Zang, Jingbo, Lahu, Naxi, Va, Yao, and Zhuang.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e The Ethics Committee of Kunming Medical University approved this study prior to the commencement of research (Approval No. KMMU2024MEC241). Informed consent was obtained in writing from all study participants.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData analyses were conducted using SPSS24.0 software. Categorical variables were described as counts and percentages. A chi-squared test was used to compare categorical variables among different groups. Multivariate logistic regression analysis was used to analyze the associations of sleep disorders with anxiety and depression symptoms, after adjusting for age, ethnicity, level of education, self-assessment of health status, and type and duration of drug use. Associations were expressed as odds ratios (OR) with 95% confidence intervals (CI). All of the statistical significance determinations were grounded in two-tailed \u003cem\u003eP\u003c/em\u003e values of \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn total, 1040 male detoxification patients under compulsory isolation were invited to participate in the survey. Of these, 1021 consented, resulting in an overall response rate of 98.17%.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows general characteristics of the study population. In total, 597 (58.5%) of participants were Han majority ethnicity and 424 (41.5%) were ethnic minorities. Of these study participants, 26.5% were polydrug users and 73.5% were single drug users. The proportion of individuals aged 25\u0026ndash;44 years, residing in rural areas, with an education level of primary or below, an unemployed status, and marital status of single, divorced, or widowed was 61.9%, 80.6%, 49.2%, 17.6%, and 66.4%, respectively. Heroin was the most prevalent form of single drug consumption (35.0%), followed by ephedrine (26.6%) and methamphetamine (7.3%).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneral characteristics of the study population\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u0026thinsp;~\u0026thinsp;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026thinsp;~\u0026thinsp;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e306\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026thinsp;~\u0026thinsp;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026thinsp;~\u0026thinsp;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55\u0026thinsp;~\u0026thinsp;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinority\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e424\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidence (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of education (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary (grade 1\u0026ndash;6) or lower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle (grade 7\u0026ndash;9) or higher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupation (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFarmer or other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e841\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e82.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmarried/divorced/widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried or cohabitating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of drug use (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle drug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeroin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e357\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEphedrine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e272\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethamphetamine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolydrug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e indicates prevalence of sleep disorders by different characteristics among the study population. Ethnic minorities and individuals with a lower level of education and poor health status by self-assessment had higher prevalence of sleep disorders than their counterparts (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, the highest prevalence of sleep disorders was found among individuals who consumed ephedrine (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrevalence of sleep disorders among male detoxification patients by different characteristics in Yunnan Province, China\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSleep disorders\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36(80.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e209(6.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e241(73.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e179(74.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e70(77.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11(78.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e411(68.8)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinority\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e334(78.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e605(73.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e140(70.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary (grade 1\u0026ndash;6) or lower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e382(76.1)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle (grade 7\u0026ndash;9) or higher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e363(69.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth status by self-assessment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43(52.4)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e575(72.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e127(84.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of drug abuse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo problem or low level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58(73.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate to severe level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e687(72.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of drug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle drug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e537(71.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeroin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e254(71.1)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEphedrine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e209(76.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethamphetamine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45(60.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29(63.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolydrug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e208(76.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of drug use (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e103(71.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026thinsp;~\u0026thinsp;15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e377(71.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u0026thinsp;~\u0026thinsp;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e145(75.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e120(76.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAll\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e745(73.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the prevalence of anxiety and depression symptoms by different characteristics among the study population. Individuals with older age, worse health status by self-assessment, longer duration of drug use, and sleep disorders all had a higher prevalence of anxiety and depression symptoms than their counterparts (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, individuals who consumed heroin had the highest prevalence of anxiety symptoms compared to individuals who consumed any other type of drug(s) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrevalence of anxiety and depression symptoms among male detoxification patients by different characteristics in Yunnan Province, China\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnxiety symptoms\u003c/p\u003e\u003cp\u003e(n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDepression symptoms\u003c/p\u003e\u003cp\u003e(n, %)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u0026thinsp;~\u0026thinsp;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1(2.2)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2(4.4)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026thinsp;~\u0026thinsp;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19(6.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15(4.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026thinsp;~\u0026thinsp;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20(6.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18(5.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026thinsp;~\u0026thinsp;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29(12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20(8.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55\u0026thinsp;~\u0026thinsp;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16(17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8(8.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6(42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7(50.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50(8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37(6.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinority\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41(9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33(7.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e78(9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59(7.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13(6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11(5.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary (grade 1\u0026thinsp;~\u0026thinsp;6) or lower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47(9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33(6.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle (grade 7\u0026thinsp;~\u0026thinsp;9) or higher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44(8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37(7.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth status by self-assessment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3(3.7)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5(6.1)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43(5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31(3.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45(30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34(22.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of drug abuse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo problem or low level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8(10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6(7.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate to severe levels\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83(8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64(6.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of drug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle drug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e63(8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45(6.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeroin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46(12.9)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30(8.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEphedrine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10(3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9(3.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethamphetamine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2(2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4(5.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5(10.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2(4.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolydrug use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28(10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25(9.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of drug use (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(4.8)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10(6.9)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026thinsp;~\u0026thinsp;15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43(8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25(4.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u0026thinsp;~\u0026thinsp;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10(5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14(7.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31(19.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21(13.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep disorder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e76(10.2)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66(8.9)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15(5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4(1.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAll\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e91(8.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70(6.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displays the results of multivariate logistic regression for prevalence of anxiety and depression symptoms. After adjusting for age, ethnicity, level of education, health status by self-assessment, and type and duration of drug use, individuals with sleep disorders had a greater probability of having anxiety (OR\u0026thinsp;=\u0026thinsp;2.310; 95% CI: 1.116 to 4.783) and depression symptoms (OR\u0026thinsp;=\u0026thinsp;4.683; 95% CI: 1.664 to 13.180).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOdds ratios (OR) and 95% confidence intervals (CI) for multi-variable logistic regression for prevalence of anxiety and depression symptoms\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnxiety symptoms\u003c/p\u003e\u003cp\u003e(reference: no)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDepression symptoms\u003c/p\u003e\u003cp\u003e(reference: no)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdjusted OR (95% CI) \u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep disorder (reference: no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.310 (1.116, 4.783)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.683 (1.664, 13.180)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u0026dagger; adjusted for age, ethnicity, level of education, health status by self-assessment, type of drug use, and duration of drug use\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings indicate prevalence of sleep disorders varied by socioeconomic factors and type of drug use among male detoxification patients under compulsory isolation in Yunnan Province, China. Furthermore, sleep disorders were independently correlated with a higher risk of having anxiety and depression symptoms.\u003c/p\u003e\u003cp\u003eIn this study, the prevalence of sleep disorders among male detoxification patients under compulsory isolation was significantly higher than in the general Chinese population [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], among detoxification patients under compulsory isolation centers in Changsha and Beijing [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and among drug users in residential centers for the treatment of drug use in Iran, Jordan, and Vietnam[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, it was lower than among drug users undergoing treatment or recovery in the United States, Taiwan, Germany, and Thailand [\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This result possibly can be attributed to disparities in drug control policies, demographic characteristics, types of drug use, and detoxification and rehabilitation methodologies across nations, leading to differential outcomes in sleep quality among the drug use population. Furthermore, the prevalence of sleep disorders varied among single drug use groups, consistent with previous studies[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This may be related to disparities in neurotransmitter dysregulation and structural and functional impairments caused by different drugs [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe results of the study reveal that ethnic minority male detoxification patients and those with a lower level of education had a higher prevalence of sleep disorders than their counterparts. This may result from the fact that ethnic minorities may face pressures from family conflicts, poorer social adaptability, and intensified job-seeking stress, which may cumulatively exacerbate sleep disorders[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Meanwhile, individuals with lower educational attainment demonstrate diminished health awareness, greater economic pressure, disadvantaged sleep environments, and elevated prevalence of sleep disorders[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Consistent with previous research[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], poor health status by self-assessment correlated with sleep disorders, potentially mediated by somatic discomfort, anxiety, and depression symptoms, which are associated with a higher prevalence of sleep disorders.\u003c/p\u003e\u003cp\u003eIn this study, the prevalence of anxiety and depression was slightly higher than in the general population in China[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], but lower than found in previous research on detoxification patients in five compulsory isolation centers in China[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], and among drug users undergoing treatment or recovery in the United States, Saudi Arabia, India and Myanmar[\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This possibly relates to the effects of intervention strategies in the study population and the extension of services of compulsory drug rehabilitation centers in recent years. Measures such as providing vocational training, regular family visitation and guidance, and psychological intervention to individuals undergoing compulsory detoxification have substantially enhanced reintegration into society, concurrently contributing to the alleviation of anxiety and depression symptoms[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur study found that heroin users had the highest prevalence of anxiety symptoms. This result is inconsistent with a previous study that found that methamphetamine users had higher anxiety scores than heroin users[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This possibly results from the fact that heroin users tend to be of older age and tend to have a longer duration of drug use, whereas ephedrine and methamphetamine users are predominantly younger with shorter duration of drug use[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The abuse of heroin, ephedrine, and methamphetamine is linked to drug-induced psychosis[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], but the differences in their neurobiological mechanisms remain poorly understood. Individuals with drug use disorders have varying degrees of emotional regulation impairments depending on the drug involved, and are more prone to develop anxiety and other negative emotions compared to the general population[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsistent with previous research, the findings of this study indicated that the prevalence of anxiety and depression increased with age as well as the duration of drug use [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Chronic drug use may lead to altered cerebral hemodynamics, reduced density of brain dopamine transporter, and neurobiological disturbance, potentially contributing to the neurobiological vulnerability underlying drug induced psychotic disorders[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Poor health status by self-assessment has been demonstrated to have significant associations with symptoms of anxiety [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Those with poor health status by self-assessment may demonstrate a cluster of risk factors, including older age, extended duration of drug use, a suboptimal physical health profile, reduced health-rated quality of life, and compromised psychosocial functioning. These interrelated risk factors may synergistically predispose individuals to heightened vulnerability to anxiety symptoms or aggravate pre-existing symptomatology.\u003c/p\u003e\u003cp\u003eOur data also showed that the prevalence of anxiety and depression was higher among individuals with sleep disorders. The association between sleep disorders and mental health symptoms remained significant even after adjusting for other potential confounding factors. Sleep disorders can impair emotional regulation, increasing the risk of anxiety and depression[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Meanwhile, in this study, sleep disorders were more common among individuals undergoing compulsory drug detoxification. As sleep disorders exacerbate the effects of anxiety and depression, future psychological interventions should integrate sleep disorder treatments into mental health services, while concurrently mitigating sleep-related adverse impacts on psychological well-being.\u003c/p\u003e\u003cp\u003eThe findings are limited in several respects. First, the level of drug abuse was evaluated using DAST-10, which lacks an objective measure of drug use frequency and dosage levels. Second, the assessment of sleep disorders and anxiety and depression symptoms relied exclusively on subjective reports, lacking an objective monitoring and evaluation of sleep patterns and of psychological symptoms. Third, the study was cross-sectional in design, so causal relationships cannot be determined. Finally, this study lacks comparative analysis with non-drug using populations in the local region, which limits the generalizability of the research findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSleep disorders have strong impacts on anxiety and depression symptoms among male detoxification patients under compulsory isolation in Yunnan Province, China. Our findings highlight that future anxiety and depression interventions should take sleep quality into account.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003cp\u003e This study was approved by the Ethics Committee of Kunming Medical University prior to the commencement of research. Written informed consent was obtained from all individuals participating in the study, and the Ethics Committee of Kunming Medical University approved this consent procedure. This study was performed in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare that there are no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe data collection and analysis of this study was supported by a grant from NHC Key Lab of Drug Addiction Medicine(Kunming Medical University)Open Projects Fund (KN202419); First-Class Discipline Team of Kunming Medical University (2024XKTDTS16) and Master\u0026rsquo;s Education Innovation Fund of Kunming Medical University (2025S155). The funders had no role in the study design, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXML carried out the study and drafted the manuscript. LC designed the study and revised the manuscript. GHL, CYR, QRB, RMS, and FG collected the data. ARG provided comments on the paper during the writing process. All authors have read and approved the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAvailability of data and material\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed in this study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUnited Nations Office on Drugs and Crime, Vienna. 2024. World drug report 2024. 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Ann N Y Acad Sci. 2004;1025:288\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJuarez Padilla J, Singleton CR, Pedersen CA, Lara-Cinisomo S. Associations between Self-Rated Health and Perinatal Depressive and Anxiety Symptoms among Latina Women. Int J Environ Res Public Health 2022, 19(19).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePalmer CA, Oosterhoff B, Bower JL, Kaplow JB, Alfano CA. Associations among adolescent sleep problems, emotion regulation, and affective disorders: Findings from a nationally representative sample. J Psychiatr Res. 2018;96:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sleep disorders, anxiety symptoms, depression symptoms, male detoxification, compulsory isolations, China","lastPublishedDoi":"10.21203/rs.3.rs-7009295/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7009295/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to evaluate the prevalence of sleep disorders and examine its associations with anxiety and depression symptoms among male detoxification patients under compulsory isolation in Yunnan Province, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were collected from a cross-sectional health interview and examination survey of 1,021 drug users among male detoxification patients under compulsory isolation in China. Sleep disorders, anxiety, and depressionsymptoms were evaluated using the Pittsburgh Sleep Quality Index (PSQI), Zung’s Self-Rating Anxiety Scale (SAS), and the Self-rating Depression Scale (SDS), respectively. Sleep disorders and anxiety and depression symptoms were evaluated using multivariate logistic regression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of sleep disorders, anxiety, and depression symptoms were 73.0%, 8.9%, and 6.9%, respectively. Ethnic minorities, participants with a lower level of education, and participants with poor health status by self-assessment had a higher prevalence of sleep disorders than their counterparts (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). Participants who consumed ephedrine had the highest prevalence of sleep disorders (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), while those who consumed heroin had the highest prevalence of anxiety symptoms (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). Multivariate logistic regression analysis uncovered that those with sleep disorders had a greater probability of having anxiety (OR=2.310; 95% CI: 1.116 to 4.783) and depression symptoms (OR=4.683; 95% CI: 1.664 to 13.180).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale detoxification patients under compulsory isolation in China experience a high level of sleep disorders, and their sleep disorders are significantly associated with anxiety and depression symptoms. Improving sleep quality may reduce the prevalence of anxiety and depression symptoms in the male detoxification patient population.\u003c/p\u003e","manuscriptTitle":"Sleep disorders and their associations with anxiety and depression among male detoxification patients under compulsory isolation in Yunnan Province, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 11:45:59","doi":"10.21203/rs.3.rs-7009295/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-08-13T18:28:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-07T16:56:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-04T16:17:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-04T16:16:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2025-06-30T10:06:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"621840aa-e9a5-4d62-a2e7-cba5baa7e128","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-21T11:45:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-21 11:45:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7009295","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7009295","identity":"rs-7009295","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}