Abstract
Study Objectives
To determine the prevalence of insomnia, its sociodemographic and clinical correlates, and treatment patterns in Chinese people.
Design
A total of 5,926 subjects were randomly selected in the urban and rural areas of Beijing and interviewed using standardized assessment tools. Basic sociodemographic and clinical data were also collected.
Setting
Urban and rural regions of Beijing municipality, China.
Patients or Participants
Adult residents older than 15 years. Interventions N/A.
Measurements and Results
The prevalence of at least one type of insomnia was 9.2%; the rates of difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), and early morning awakening (EMA) were 7.0%, 8.0%, and 4.9%, respectively. Increased age (age >44 and 24 years in the urban and rural samples, respectively), female sex, married, divorced, separated, or widowed marital status; having a major medical condition; and suffering from a psychiatric disorder were risk factors for all types of insomnia in both the urban and rural samples. A low level of education (primary school or illiteracy) was significantly associated with a higher likelihood of all types of insomnia in the urban sample. Current smokers and current drinkers were less likely to report any type of insomnia in the rural sample. Unemployment was associated with DMS in the urban sample, while it was associated with DIS and DMS in the rural sample. Only 5.4% of the participants with any type of insomnia reported their symptoms to medical practitioners. In contrast, nearly one-third of the subjects with insomnia reported taking benzodiazepines as sleep-enhancing drugs.
Conclusions
Nationwide epidemiologic surveys are needed to further explore the prevalence of insomnia in China. The low percentage of subjects treated for insomnia indicates a major public health problem that should be addressed. Strict controls on use of benzodiazepines are warranted.
Citation:
Xiang YT; Ma X; Cai ZJ; Li SR; Xiang YQ; Guo HL; Hou YZ; Li ZB; Li ZJ; Tao YF; Dang WM; Wu XM; Deng J; Lai KYC; Ungvari GS. The prevalence of insomnia, its sociodemographic and clinical correlates, and treatment in rural and urban regions of Beijing, China: a general population-based survey. SLEEP 2008;31(12):1655–1662.
Keywords: Insomnia, China, epidemiology, community, sleep
INSOMNIA IS AN IMPORTANT PUBLIC HEALTH CHALLENGE BECAUSE OF ITS HIGH PREVALENCE AND ITS ASSOCIATION WITH WORK ABSENTEEISM, considerable impairment of quality of life, and increased medical and societal costs.1–4 It has been reported that nearly one-third of the adult population in the US suffer from sleep problems.5–7 In recent decades, insomnia received increasing attention from policymakers and health care providers, with a large body of studies undertaken.8 To implement appropriate strategies and effective measures to reduce the personal suffering and harmful consequences created by insomnia, it is essential to understand its prevalence and sociodemographic and clinical correlates. However, the frequency of insomnia across different countries varies considerably, ranging from 6% to 76.3%,9,10 due primarily to differences in interview procedures (telephone interviews vs. face-to-face interviews), the definition of criteria for insomnia, and its time frame (e.g., current, past week, past year, or lifetime).8
Several sociodemographic and clinical factors, such as female sex, advanced age, divorced or separated marital status, low income and educational level, and somatic or psychiatric conditions were found to be associated with insomnia in Western countries.7,9,11–13 To date, however, no studies have explored the prevalence of insomnia and its relationship with sociodemographic and clinical correlates in a general population-based survey in China, although previous studies indicate that cultural factors played an important role in insomnia.14,15
In traditional Chinese culture, diligence is highly praised; in contrast, sleep problems are usually minimized.16 Furthermore, the lay public often regards a regular good night's sleep as the manifestation of laziness.16,17 Two famous old sayings frequently quoted to encourage people in China are vivid examples of this attitude: “Pick a light to read for a night” and “Rising up upon hearing the crow of a rooster to practice sword playing”.
The study reported herein set out to investigate (1) the prevalence of various types of DSM-IV-defined insomnia in the general population aged ≥15 years living in the urban and rural areas of Beijing, China; (2) the sociodemographic correlates of insomnia; (3) the relationship of insomnia to major medical and psychiatric disorders; and (4) the treatment of people with insomnia.
METHODS
Subjects and Sampling
The study was part of a large-scale epidemiologic survey of the prevalence of psychiatric disorders in Beijing, China, which was undertaken from April 1 to April 24, 2003. It was based on a stratified, multistage, systematic, and probability sample of permanent residents in Beijing who were ≥15 years, lived with family members, and had the ability to comprehend the contents of the interview. The municipality of Beijing was chosen because it comprises both urban and rural areas.
The study protocol was approved by the Human Research and Ethics Committee of Beijing Anding Hospital. Written consent was obtained from each subject.
The recruitment of study subjects took place as follows. (1) Neighborhood and village communities (NCs and VCs), in urban and rural regions, respectively, are basic community organizations with several hundred households in China. There were 2,316 NCs and 3,985 VCs in 18 districts and counties in Beijing in early 2003. Following the method of a previous psychiatric epidemiologic survey in Beijing,18 2% of the total NCs and VCs, i.e., 126 NCs and VCs with a total population of 313,356 persons in Beijing were selected using a random number table that took into account the population and the ratio of urban to rural residents in each of the 18 Beijing districts and counties. In Beijing, residents are categorized as either urban or rural dwellers on their household cards, which are kept by the local Public Security Bureau. (2) On the basis of the predetermined sampling interval and random starting points, 6,267 households from the 126 NCs/VCs were selected from the household registry of the local Public Security Bureau. (3) The person in each selected household, aged >15 years, whose date of birth was closest to April 1 was invited to participate in the study. As planned, the subjects of the study accounted for approximately 2% of all the residents living in the 126 NCs and VCs.
Assessment Tools and Procedures
Face-to-face household interviews were conducted. Basic sociodemographic and clinical data including details on insomnia, smoking, drinking, major medical conditions, and their treatment were collected using a 36-item questionnaire designed by the authors. In this study, insomnia was defined according to DSM-IV, targeting the 3 basic forms of sleep disturbances lasting 2 weeks or longer in the past 12 months: difficulties initiating sleep (DIS; “It took you two hours or longer nearly every night before you could fall sleep”); difficulties maintaining sleep (DMS; “You woke up nearly every night and took an hour or more to get back to sleep”); and early morning awakening (EMA; “You woke up nearly every morning at least two hours earlier than you wanted to”). Respondents answered these questions with “yes” or “no.” This definition of insomnia has also been used in other recent studies.7,14 Systematic inquiries were made about major medical conditions affecting the cardiovascular, respiratory, digestive, hematological, endocrine, urinary, connective tissue, and nervous systems. To ensure the accuracy of responses, data collected in the interview were verified by at least one family member. A current smoker was defined as a person who had smoked daily in the past month.19 According to the modern Chinese literature,18 a current drinker has had at least one episode of drinking monthly during the past year, consuming at least 3 standard units of alcohol each time.
The Chinese version of the Composite International Diagnostic Interview-Version 1.0 (CIDI 1.0) that generates DSM-III-R diagnoses was used to identify psychiatric disorders. Both the original and the validated Chinese versions of the CIDI 1.0 have satisfactory psychometric properties.20,21
The interviews were conducted by 102 qualified psychiatrists, selected from 18 mental health services in Beijing. The interviewers underwent training in epidemiological field work at a 10-day workshop given by a trainer (Dr. SR Li) from the Institute of Mental Health, Peking University, who had received training in using CIDI V1.0 from the World Health Organization. The workshop gave an overview of the project and covered the sampling and assessment procedures, techniques for field interviews, potential difficulties in the interviews, mock interviews, and quality assessment. To minimize the failure to identify cases due to false-negative and no responses, the following 2 measures were adopted prior to the interview: (1) public education emphasizing the importance of the project and addressed issues of privacy and confidentiality; and (2) the interviewers were responsible only for participants living in the catchment areas of their respective hospitals, thus capitalizing on the good relationship between psychiatric services and the local NCs/VCs. A detailed manual was devised, and the interview was conducted accordingly.
Statistical Analysis
Data were analyzed using SPSS 13.0 for Windows. The sample was weighted according to the age and sex distribution of Beijing's population in 2002. First, stepwise logistic regression analyses were employed to calculate the crude and adjusted odds ratios for the sociodemographic and clinical variables as potential correlates of each type of insomnia in the urban and rural samples. The crude odds ratios examined the association between insomnia and each of the sociodemographic and clinical variables using single logistic regression analysis. The adjusted odds ratios were used to measure the relationship between insomnia and each variable after controlling for the effects of other variables by using multiple logistic regression analysis. Variables including age, sex, marital and employment status, education level, monthly income, major medical condition(s), psychiatric disorder, and current smoker and drinker status were entered as potential correlates of insomnia. Second, the crude and adjusted odds ratios examined the association between insomnia and major DSM-III-R psychiatric disorders using single and multiple logistic regression analyses, respectively. Insomnia was the dependent variable, and the independent variables were one or more of the sociodemographic and clinical variables, and the diagnosis of major DSM-III-R psychiatric disorders in logistic regression analyses, as appropriate. The level of significance was set at 0.05 (2-tailed).
RESULTS
Of the 6,251 subjects who were approached and screened, 5,926 met study criteria and were interviewed. The reasons for failing to participate in the study included living or working far away, no interest in the study, lack of time, or difficulty in comprehending the interview questions. Each participant answered all items on the questionnaire. Table 1 shows the sociodemographic and clinical characteristics of the participants. The prevalence of DIS, DMS, and EMA by sex, age group, and rural and urban regions are shown in Table 2. The prevalence of at least one of the 3 types of insomnia in the past 12 months was 9.2% in the whole sample. Specifically, the rates of DIS, DMS, and EMA were 7.0%, 8.0%, and 4.9%, respectively. The overall female/male ratio for any insomnia was 1.6%; the ratio increased with age after 45 years ranging between 1.7 (the above 65-year age group) and 2.1 (the 45 to 54-year age group). The prevalence of at least one of the 3 types of insomnia was 9.7% and 8.8% in the rural and urban samples, respectively. The estimated prevalence rates of DIS, DMS, and EMA, and any type of insomnia in the urban sample were lower than those in the rural sample, but the difference did not reach a statistically significant level. A higher proportion of subjects reported all 3 types of insomnia (4.0%) than either one (2.4%) or 2 (2.9%).
Table 1.
Sociodemographic Characteristics of the Study Population (n=5,926)
| Unweighted |
||
|---|---|---|
| n | % | |
| Age (years) | ||
| 15–24 | 579 | 9.8 |
| 25–34 | 764 | 12.9 |
| 35–44 | 1369 | 23.1 |
| 45–54 | 1217 | 20.5 |
| 55–64 | 838 | 14.1 |
| 65–74 | 821 | 13.9 |
| ≥ 75 | 338 | 5.7 |
| Men | 2735 | 46.2 |
| Married | 4520 | 76.3 |
| Education level | ||
| College or above | 786 | 13.3 |
| Senior high school | 1461 | 24.7 |
| Junior high school | 2039 | 34.4 |
| Primary school | 959 | 16.2 |
| Illiterate | 681 | 11.5 |
| Unemployed | 3108 | 52.4 |
| Monthly income (RMB)a | ||
| >2000 | 238 | 4.0 |
| 1000–2000 | 1508 | 25.4 |
| 500–999 | 1722 | 29.1 |
| <500 | 2458 | 41.4 |
| Urban residence | 3445 | 58.1 |
| Major medical disorder(s) | 1929 | 32.6 |
| Current smoker | 1455 | 24.6 |
| Current drinker | 811 | 13.7 |
US$1 = RMB6.90
Table 2.
Prevalence of Insomnia by Age, Sex, and Region
| Age (years) | DIS |
DMS |
EMA |
At least one of the three types of insomnia |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (years) | Male % (SE) | Female % (SE) | Total % (SE) | Male % (SE) | Female % (SE) | Total % (SE) | Male % (SE) | Female % (SE) | Total % (SE) | Male % (SE) | Female % (SE) | Total % (SE) | |
| Whole sample | |||||||||||||
| 15–24 | 1.9 (0.5) | 1.8 (0.6) | 1.9 (0.4) | 1.6 (0.5) | 2.5 (0.7) | 2.0 (0.4) | 0.9 (0.4) | 1.1 (0.4) | 1.0 (0.3) | 1.9 (0.5) | 2.9 (0.8) | 2.3 (0.4) | |
| 25–34 | 6.5 (1.0) | 5.1 (1.0) | 5.8 (0.7) | 7.3 (1.0) | 4.8 (1.0) | 6.2 (0.7) | 5.6 (0.9) | 2.9 (0.7) | 4.4 (0.6) | 9.0 (1.1) | 6.0 (1.1) | 7.7 (0.8) | |
| 35–44 | 4.8 (0.8) | 7.8 (1.1) | 6.2 (0.7) | 5.5 (0.9) | 10.2 (1.3) | 7.7 (0.7) | 3.4 (0.7) | 5.8 (1.0) | 4.5 (0.6) | 6.6 (1.0) | 10.2 (1.3) | 8.3 (0.8) | |
| 45–54 | 7.0 (1.1) | 12.5 (1.5) | 9.6 (0.9) | 6.6 (1.1) | 15.0 (1.7) | 10.7 (1.0) | 3.8 (0.8) | 9.6 (1.4) | 6.7 (0.8) | 8.1 (1.2) | 16.9 (1.7) | 12.4 (1.0) | |
| 55–64 | 7.8 (1.8) | 16.2 (2.2) | 12.4 (1.5) | 10.7 (2.1) | 19.0 (2.4) | 15.3 (1.6) | 5.6 (1.5) | 11.3 (1.9) | 8.7 (1.2) | 12.1 (2.2) | 21.2 (2.5) | 17.1 (1.7) | |
| ≥ 65 | 8.2 (1.5) | 13.6 (1.8) | 11.0 (1.2) | 8.4 (1.5) | 15.6 (1.9) | 12.1 (1.2) | 5.5 (1.2) | 9.8 (1.6) | 7.7 (1.0) | 10.2 (1.7) | 17.6 (2.0) | 14.0 (1.3) | |
| Total | 5.5 (0.4) | 8.7 (0.5) | 7.0 (0.3) | 6.0 (0.4) | 10.4 (0.6) | 8.0 (0.3) | 3.8 (0.3) | 6.2 (0.4) | 4.9 (0.3) | 7.2 (0.4) | 11.5 (0.6) | 9.2 (0.4) | |
| Rural sample | |||||||||||||
| 15–24 | 1.2 (0.6) | 0.8 (0.6) | 1.1 (0.4) | 1.2 (0.6) | 0.8 (0.6) | 1.1 (0.4) | 1.2 (0.6) | 0 | 0.7 (0.3) | 1.2 (0.6) | 1.6 (0.9) | 1.4 (0.5) | |
| 25–34 | 5.9 (1.4) | 6.1 (1.5) | 6.0 (1.0) | 6.5 (1.4) | 5.6 (1.5) | 6.1 (1.0) | 5.9 (1.4) | 4.2 (1.3) | 5.1 (0.9) | 8.3 (1.6) | 7.1 (1.6) | 7.7 (1.1) | |
| 35–44 | 5.5 (1.3) | 9.0 (1.7) | 7.3 (1.1) | 6.2 (1.4) | 11.7 (1.9) | 8.9 (1.2) | 4.4 (1.2) | 7.4 (1.5) | 5.9 (1.0) | 7.2 (1.5) | 11.7 (1.9) | 9.4 (1.2) | |
| 45–54 | 6.5 (1.8) | 14.6 (2.5) | 10.7 (1.5) | 8.0 (2.0) | 16.5 (2.6) | 12.4 (1.7) | 4.0 (1.4) | 11.7 (2.2) | 8.0 (1.4) | 8.5 (2.0) | 18.7 (2.7) | 13.8 (1.7) | |
| 55–64 | 9.9 (3.5) | 21.0 (4.0) | 16.4 (2.8) | 14.0 (4.1) | 22.7 (4.2) | 19.1 (3.0) | 6.6 (2.9) | 13.6 (3.4) | 10.7 (2.3) | 14.8 (4.2) | 25.5 (4.3) | 21.1 (3.1) | |
| ≥ 65 | 11.9 (3.4) | 19.2 (3.8) | 15.8 (2.6) | 10.7 (3.2) | 22.4 (4.0) | 16.9 (2.6) | 6.2 (2.5) | 15.5 (3.5) | 11.2 (2.2) | 13.2 (3.5) | 24.4 (4.2) | 19.2 (2.8) | |
| Total | 5.4 (0.6) | 10.0 (0.9) | 7.6 (0.5) | 6.1 (0.6) | 11.3 (0.9) | 8.6 (0.5) | 4.2 (0.5) | 7.5 (0.7) | 5.8 (0.4) | 7.1 (0.7) | 12.6 (0.9) | 9.7 (0.6) | |
| Urban sample | |||||||||||||
| 15–24 | 2.6 (0.9) | 2.6 (1.0) | 2.6 (0.6) | 1.9 (0.8) | 4.0 (1.5) | 2.9 (0.7) | 0.6 (0.4) | 2.0 (0.8) | 1.2 (0.4) | 2.6 (0.9) | 4.0 (1.2) | 3.2 (0.7) | |
| 25–34 | 7.0 (1.4) | 4.0 (1.3) | 5.7 (1.0) | 8.1 (1.5) | 4.0 (1.3) | 6.3 (1.0) | 5.4 (1.3) | 1.5 (0.8) | 3.7 (0.8) | 9.7 (1.7) | 5.0 (1.4) | 7.7 (1.1) | |
| 35–44 | 4.2 (1.0) | 6.5 (1.5) | 5.2 (0.9) | 5.0 (1.1) | 8.5 (1.7) | 6.5 (1.0) | 2.5 (0.8) | 4.0 (1.2) | 3.1 (0.7) | 6.2 (1.3) | 8.5 (1.7) | 7.2 (1.0) | |
| 45–54 | 7.3 (1.5) | 10.8 (1.9) | 8.9 (1.2) | 5.7 (1.3) | 13.8 (2.2) | 9.4 (1.2) | 3.8 (1.1) | 7.9 (1.7) | 5.7 (1.0) | 7.9 (1.5) | 15.4 (2.3) | 11.3 (1.3) | |
| 55–64 | 6.8 (2.0) | 13.4 (2.6) | 10.2 (1.7) | 9.2 (2.3) | 16.8 (2.9) | 13.2 (1.9) | 5.2 (1.8) | 9.9 (2.3) | 7.7 (1.5) | 10.8 (2.5) | 18.5 (3.0) | 14.9 (2.0) | |
| ≥ 65 | 6.7 (1.6) | 11.0 (2.0) | 8.9 (1.3) | 7.5 (1.7) | 12.5 (2.1) | 10.0 (1.4) | 5.2 (1.4) | 7.2 (1.7) | 6.2 (1.1) | 8.8 (1.9) | 14.6 (2.3) | 11.7 (1.5) | |
| Total | 5.6 (0.5) | 7.7 (0.6) | 6.6 (0.4) | 5.9 (0.5) | 9.6 (0.7) | 7.6 (0.4) | 3.5 (0.3) | 5.2 (0.5) | 4.3 (0.3) | 7.3 (0.6) | 10.6 (0.8) | 8.8 (0.5) | |
SE: standard error
Tables 3 and 4 depict the crude and adjusted odds ratios for the relationship between sociodemographic and clinical variables and insomnia in the urban and rural samples. In the urban cohort, age >44 years, female sex, married, divorced, separated or widowed marital status, low level of education (primary school or illiteracy), and the presence of a major medical or psychiatric disorder were all risk factors of DIS, DMS, and EMA, while unemployment was associated with more frequent DMS. In the rural cohort, age >24 years, female sex, married, divorced, separated or widowed marital status, and the presence of a major medical or psychiatric disorder were all risk factors of DIS, DMS, and EMA, while unemployment was associated with more frequent DIS and DMS. Current smokers and drinkers were less likely to report any type of insomnia in the rural sample.
Table 3.
Sociodemographic Correlates for Insomnia in Urban Areas (Logistic Regression Analysis)
| DIS |
DMS |
EMA |
||||
|---|---|---|---|---|---|---|
| Crude OR (95% CI) | Adjust OR (95% CI) | Crude OR (95% CI) | Adjust OR (95% CI) | Crude OR (95% CI) | Adjust OR (95% CI) | |
| Age (years) | ||||||
| 15–24 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 25–34 | 2.1 (0.9–4.8) | 1.7 (0.7–3.9) | 2.0 (0.9–4.5) | 1.6 (0.7–3.5) | 2.6 (0.8–8.0) | — |
| 35–44 | 2.0 (0.9–4.5) | 1.6 (0.7–3.6) | 2.3 (1.1–4.9)* | 1.9 (0.9–3.9) | 2.5 (0.8–7.3) | — |
| 45–54 | 3.7 (1.7–7.8)* | 2.8 (1.3–6.1)* | 3.7 (1.8–7.5)* | 2.7 (1.3–5.7)* | 4.8 (1.7–13.6)* | — |
| 55–64 | 4.2 (1.9–9.0)* | 2.8 (1.3–6.0)* | 4.9 (2.4–10.1)* | 3.2 (1.5–6.8)* | 6.2 (2.2–17.6)* | — |
| ≥ 65 | 3.6 (1.7–7.6)* | 1.9 (1.3–2.3) | 3.6 (1.8–7.4)* | 2.1 (1.01–4.6)* | 5.0 (1.7–14.0)* | — |
| Sex | ||||||
| Men | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Women | 1.5 (1.2–2.0)* | 1.7 (1.3–2.3)* | 1.8 (1.4–2.3)* | 2.3 (1.7–3.1)* | 1.5 (1.2–2.1)* | 1.9 (1.4–2.8)* |
| Marital status | ||||||
| Single | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Married | 1.5 (1.04–2.2)* | — | 1.5 (1.1–2.2)* | — | 2.1 (1.2–3.7)* | — |
| Divorced/separated/widowed | 2.6 (1.5–4.5)* | — | 2.6 (1.6–4.4)* | — | 3.7 (1.9–7.4)* | — |
| Education level | ||||||
| College or above | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Senior high school | 0.7 (0.5–1.1) | — | 0.6 (0.4–0.9)* | 0.7 (0.5–1.1) | 0.9 (0.5–1.5) | 1.01 (0.6–1.6) |
| Junior high school | 1.2 (0.8–1.8) | — | 1.04 (0.7–1.9) | 0.8 (0.6–1.2) | 1.1 (0.6–1.7) | 0.7 (0.4–1.3) |
| Primary school | 1.9 (1.1–3.1)* | — | 1.8 (1.2–2.9)* | 1.1 (0.7–1.7) | 2.5 (1.4–4.5)* | 1.3 (0.7–2.3) |
| Illiterate | 2.3 (1.3–4.1)* | — | 1.9 (1.1–1.3)* | 0.4 (0.2–0.7)* | 2.1 (1.1–4.4)* | 0.4 (0.2–0.9)* |
| Employment status | ||||||
| Unemployed | — | — | 1.4 (1.1–1.9)* | — | — | — |
| Employed | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Major medical condition(s) | ||||||
| Yes | 2.2 (1.6–3.0)* | — | 2.5 (1.9–3.3)* | — | 2.6 (1.8–3.8)* | — |
| No | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Psychiatric disorder | ||||||
| Yes | 6.4 (4.7–8.6)* | 5.9 (4.5–7.7)* | 6.1 (4.6–8.1)* | 6.8 (5.0–8.6)* | 6.7 (4.6–9.7)* | 7.4 (5.3–10.4)* |
| No | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Significant at the 0.05 level, two-sided test
Only significant OR(s) and 95% CI(s), and variables entered the final model are reported
Table 4.
Sociodemographic Correlates for Insomnia in Rural Areas (Logistic Regression Analysis)
| DIS |
DMS |
EMA |
||||
|---|---|---|---|---|---|---|
| Crude OR (95% CI) | Adjust OR (95% CI) | Crude OR (95% CI) | Adjust OR (95% CI) | Crude OR (95% CI) | Adjust OR (95% CI) | |
| Age (years) | ||||||
| 15–24 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 25–34 | 5.7 (2.3–14.4)* | 3.8 (1.1–13.2)* | 5.8 (2.3–14.7)* | 4.0 (1.1–13.6)* | 6.9 (2.3–20.5)* | — |
| 35–44 | 7.0 (2.8–17.4)* | 3.7 (1.1–12.5)* | 8.8 (3.6–21.9)* | 5.2 (1.6–17.0)* | 8.1 (2.8–23.6)* | — |
| 45–54 | 10.8 (4.3–26.7)* | 4.7 (1.4–15.7)* | 12.8 (5.2–31.3)* | 6.2 (1.9–20.3)* | 11.2 (3.8–32.8)* | — |
| 55–64 | 17.6 (6.9–44.8)* | 7.3 (2.2–24.4)* | 21.2 (8.4–53.4)* | 9.8 (2.9–32.4)* | 15.3 (5.0–46.9)* | — |
| ≥ 65 | 16.9 (6.7–42.7)* | 3.2 (0.9–10.9) | 18.3 (7.3–46.1)* | 4.0 (1.2–13.5)* | 16.2 (5.4–48.6)* | — |
| Sex | ||||||
| Men | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Women | 1.9 (1.4–2.6)* | 2.2 (1.6–3.0)* | 2.0 (1.4–2.6)* | 2.2 (1.6–3.0)* | 1.8 (1.3–2.6)* | 2.8 (1.9–4.2)* |
| Marital status | ||||||
| Single | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Married | 4.3 (2.3–8.1)* | — | 4.5 (2.5–8.1)* | — | 4.5 (2.1–9.2)* | — |
| Divorced/separated/widowed | 9.9 (4.8–20.3)* | — | 9.7 (4.8–19.2)* | — | 10.5 (4.6–24.0)* | — |
| Employment status | ||||||
| Unemployed | 1.4 (1.1–1.9)* | — | 1.5 (1.1–2.0)* | — | — | — |
| Employed | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Major medical condition(s) | ||||||
| Yes | 3.6 (2.6–4.9) * | — | 3.3 (2.5–4.5) * | — | 4.1 (2.9–5.9)* | — |
| No | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Psychiatric disorder | ||||||
| Yes | 10.5 (7.4–14.9)* | 9.6 (6.9–13.5)* | 9.2 (6.7–12.7)* | 7.9 (5.8–10.7)* | 15.2 (9.8–23.5)* | 17.1 (11.1–26.4)* |
| No | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Current smoker | ||||||
| Yes | 0.6 (0.4–0.8)* | — | 0.5 (0.4–0.7)* | — | 0.6 (0.4–0.8)* | — |
| No | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Current drinker | ||||||
| Yes | 0.5 (0.3–0.8)* | — | 0.6 (0.4–0.9)* | — | 0.5 (0.3–0.9)* | — |
| No | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Significant at the 0.05 level, two-sided test
Only significant OR(s) and 95% CI(s), and variables entered the final model are reported
Table 5 presents the relationships of major DSM-III-R psychiatric disorders with insomnia. Major depressive episode (MDE) was significantly associated with more frequent insomnia, followed by anxiety disorders, schizophrenia, and alcohol dependence. A dose-response relationship between the number of psychiatric disorders and insomnia was also observed.
Table 5.
The Relationship Between Insomnia and DSM-III-R Psychiatric Disorders (Logistic Regression Analysis)
| Disorder categories | Insomnia |
|
|---|---|---|
| Crude OR (95% CI) | Adjust OR (95% CI) | |
| Alcohol dependence | 3.5 (1.3–9.3)* | 4.1 (1.3–13.1)* |
| Schizophrenia | 5.7 (2.5–12.9)* | 4.8 (2.1–11.0)* |
| Major depressive episode | 25.1 (19.2–32.7)* | 19.7 (15.2–25.5)* |
| Anxiety disorders | 8.8 (6.0–12.9)* | 6.4 (4.4–9.2)* |
| Psychiatric disorders | ||
| No psychiatric disorder | 1.0 | 1.0 |
| One psychiatric disorder | 5.5 (4.4–6.8)* | 4.8 (3.8–5.9)* |
| Two psychiatric disorders | 17.1 (12.1–24.0)* | 17.0 (12.0–24.2)* |
| Three or more psychiatric disorders | 17.4 (8.9–33.9)* | 15.7 (7.6–30.2)* |
Significant at the 0.05 level, two-sided test
Only 5.4% of the participants with any type of insomnia (“insomniacs”) complained of insomnia symptoms to medical practitioners, and only 2.1% of them consulted mental health specialists. In contrast, however, 32.4% of the insomniacs reported taking “sleep-enhancing drugs.” Specifically, 29.8% of the insomniacs took benzodiazepines; 1.7% used alcoholic beverages or herbal medications (1.7%); 0.6% reported mixed use of benzodiazepines and barbiturates; and 0.3% used barbiturates only.
DISCUSSION
To the best of our knowledge, this is the first epidemiological survey of insomnia and its sociodemographic and clinical correlates using stringent methods in a large, random sample including both rural and urban regions in China.
The prevalence of any type of insomnia (9.2%) found in this study was within the range (6%–76.3%) reported by studies from other countries.8,10 However, differing definitions of insomnia and various timeframes used in the literature prevent direct comparison. To date, 2 surveys have used the same definition of insomnia and the time frame as this study. Roth et al.7 investigated 9,282 subjects in the National Comorbidity Survey Replication (NCS-R) in the USA and reported rates for DIS, DMS, and EMA of 16.4%, 19.9%, and 16.7%, respectively; the frequency of at least one type of insomnia was 36.3%. These figures are considerably higher than the corresponding 7.0%, 8.0%, 4.9%, and 9.2% in this study. In contrast, our findings are essentially consistent with those in a Nigerian investigation of 6,752 subjects, in which the prevalence of DIS, DMS, EMA, and any type of insomnia were 7.7%, 8.5%, 5.4%, and 11.8%.14 Similar to the findings of Gureje et al,14 the type of insomnia most frequently reported by insomniacs in our study was DMS, followed by DIS and EMA.
Any potential biases related to diagnostic criteria, interviewing techniques or other aspects of the methods could hardly account for the gaping discrepancy between the findings of our study and those of Roth et al.7 because the questions on insomnia used in both surveys were quite simple and unequivocal. In addition, questions about insomnia could not raise fear of discrimination or stigmatization, resulting in false-negative responses. Consequently, it can be safely assumed that socioeconomic, cultural, and racial factors could have a major impact on insomnia.14,15
Subjects in the 55 to 64-year age group had the highest rate of at least one type of insomnia (17.1%) overall, and in both the urban (14.9%) and rural samples (21.1%). Possible reasons for the high rate of insomnia may include stressful life events related to retirement, supporting children and taking care of parents, and a higher risk of medical conditions.22 The finding that the rate of insomnia rose with age is similar to results of Western studies.12,15,23
Unlike the higher prevalence of psychiatric disorders and suicide in rural areas of China,24–27 there was no significant difference between the rural and urban samples in any type of insomnia. We have no clear explanation for this unexpected finding and the reasons need to be explored in future studies. Four percent, 2.9% and 2.4% of subjects in this study reported 3 types, 2 types, and 1 type of simultaneously occurring insomnia, respectively. In contrast, the corresponding figures were 7.4%, 9.0%, and 12.8% in the US,7 suggesting that cooccurrence of different types of insomnia in a Chinese population was less frequent than in the mixed-race population of the United States.
In keeping with previous findings in Western countries,9,13,14 women were more likely to have at least one type of insomnia in both rural and urban areas. The female/male ratios for insomnia reached their peak after 45 years of age, with menopause and increased chronic physical conditions usually being regarded as explanations.8,28
Married, divorced, separated, and widowed marital status were more associated with insomnia in both urban and rural areas. The association between insomnia and divorced, separated and widowed marital status is consistent with the results of previous surveys in Western countries.9,29 However, no significant association between married status and insomnia was reported from Western settings. In today's fast-changing Chinese society, complex personal relationships, social stress, the gradual dissolution of the traditional family structure and marriage-related problems may have contributed to the higher likelihood of insomnia in the married/divorced/widowed group. These issues need to be investigated further.
In agreement with Western studies,9,30 insomnia was associated with major medical conditions in Chinese people. Low education level (illiteracy and primary school) was significantly associated with insomnia in the urban sample, which is also in line with several previous studies.2,23,31 As this association did not hold true in the rural sample, it could be that a low education level is more often associated with greater work-related stress and thus insomnia in urban areas in China. Unemployment was associated with DMS in the urban sample and with DIS and DMS in the rural sample, confirming previous findings.23,32
Smoking and drinking have been found to be risk factors for insomnia,33,34 but were not so in our rural sample. We hypothesize that the rather liberal definition of smoking and drinking status used in the Chinese literature may be partially responsible for the lack of connection between these habits and insomnia in this study. The impact of smoking and drinking on insomnia in Chinese populations needs to be further explored.
In multivariate analyses, the significant associations between insomnia and married/divorced/separated/widowed marital status, major medical conditions, unemployment, and current smoking and drinking were eliminated in both the urban and rural samples after other sociodemographic and clinical variables were controlled. However, these results must be evaluated with caution because the potential confounding influence of collinearity that exists between any 2 variables, or between a variable and a combination of other variables, cannot be entirely ruled out. These findings need to be confirmed in future studies.
As expected, insomnia was significantly associated with psychiatric disorders in both the urban and rural samples, and higher prevalence of insomnia was found with increasing number of comorbid psychiatric disorders in the whole sample. In line with other studies,7–9 MDE was the most frequent psychiatric illness co-occurring with insomnia. An unusually high rate of psychiatric disorders (60%) was found among insomniacs in this study, way above the corresponding figures reported in Western studies (40%33; 15.6%9). Different definitions of insomnia and interview measures (telephone vs. face-to-face interview) might partly explain the discrepancy. The co-occurrence of insomnia and psychiatric disorders in China needs to be further investigated.
Only 5.4% of the subjects with insomnia in this study reported their symptoms to medical practitioners; of them, a mere 2.1% attended mental health specialists. The low treatment rate may have the following reasons: first, many Chinese people may hesitate to consult clinicians only for insomnia because they do not regard it as a medical condition35; second, there is limited access to the few existing sleep clinics in Beijing and all over China36; and third, clinicians in China less frequently ask patients about their sleeping habits probably due to the inadequate emphasis on sleep disturbances in the medical curriculum.37 The establishment of easily accessible sleep clinics, more attention to sleep in undergraduate and postgraduate medical education, and a massive awareness campaign addressing the recognition and treatment of insomnia are urgently needed in China.
Another unexpected finding was that nearly one third of the insomniacs in this study were taking benzodiazepines. Given the limited access to expert advice, most resorted to self-medication and purchased benzodiazepines over the counter, although these substances are supposed to be restricted and available only by prescription in China. The off-label use of benzodiazepines could increase the risk of secondary dependence38 and other adverse effects, and their use should be more strictly controlled in China.
The major strengths of this study were the careful planning and design, sound methods, large sample, and the involvement of clinician interviewers. However, the results should be treated with caution due to certain limitations. First, the study involved only registered permanent residents of Beijing, one of the most developed metropolitan areas of the country. The results may not be applicable to other regions of China because the study population obviously cannot represent the entire population (1.3 billion) of the country. In addition, China has 56 ethnic groups living in its territory, with significant differences in socio-cultural and economic contexts across the country. Because of the inadequate funding for sleep research and the limited number of well-trained interviewers, a nation-wide epidemiological survey on sleep disturbances is not scheduled in the foreseeable future. Instead, regional epidemiological surveys on insomnia, such as this study, appear to be more logistically feasible at this stage. Second, the study was cross-sectional; hence the causality of the relationships between the occurrence of insomnia and sociodemographic and psychiatric illness-related variables could not be explored. Third, our analyses did not employ a specialized statistical software package to account for the complex sampling design, which could have affected our results. Also, more information on variables that were not significantly associated with insomnia in the multivariate analyses could not be provided due to the limitations of SPSS. Fourth, the definition of insomnia used in this study captures a relatively high level of severity compared to some previous studies. Different specifiers of insomnia have been used in the literature; for example, insomnia with or without timeframe,39 or insomnia symptoms with daytime consequences,30 or dissatisfaction with sleep quality or quantity.12 As part of a large-scale psychiatric epidemiologic survey, DSM-IV-specified sleep problems were used in this study.
In conclusion, given the harmful consequences of insomnia and the low treatment rate reported in this survey, serious attempts should be made to improve access to treatment and to conduct further national surveys to explore the situation in areas other than Beijing. Longitudinal studies should also be carried out to investigate the sociodemographic and clinical predictors of insomnia.
DISCLOSURE STATEMENT
This was not an industry supported study. The authors have indicated no financial conflicts of interest.
ACKNOWLEDGMENTS
This study was supported by a grant from the Beijing Municipal Science and Technology Commission (No. H010910130112-200100528). The authors would like to express their gratitude to all the mental health professionals and participants involved in the project. The authors also express their gratitude to the two anonymous reviewers for their constructive comments and recommendations.
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