Sleep Breath DOI 10.1007/s11325-014-1036-3
ORIGINAL ARTICLE
Nocturnal sleep problems among university students from 26 countries Karl Peltzer & Supa Pengpid
Received: 15 April 2014 / Revised: 23 June 2014 / Accepted: 8 July 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Background The aim of this study is to estimate the prevalence of nocturnal sleeping problems and its associated factors among university students in mainly low- and middle-income countries. Methods A cross-sectional survey was conducted with 20,222 undergraduate university students (mean age, 20.8; SD=2. 8) from 27 universities in 26 countries across Asia, Africa and the Americas. Results Overall, 10.4 % reported severe or extreme nocturnal sleeping problems (male, 10.2 %; female, 10.5 %) in the past month. Noctural sleeping problems differed by country, from 32.9 % in Indonesia to 3.0 % in Thailand among Asian countries, from 13.7 % in Mauritius to 7.5 % in South Africa, and from 11.8 % in Jamaica to 6.1 % in Columbia in the Americas. In multivariate logistic regression analysis, coming from a poor family background, staying off campus (on their own or with parents or guardians), stress (history of child sexual abuse), poor mental health (depression and PTSD symptoms), health risk behaviour (tobacco use, heavy internet use, gambling, skipping breakfast and having sustained an injury), lack of social support and poor academic performance were associated with nocturnal sleeping problems. K. Peltzer (*) : S. Pengpid ASEAN Institute for Health Development, Mahidol University, Salaya, Phutthamonthon, Nakhonpathom, Thailand 73170 e-mail: [email protected] S. Pengpid e-mail: [email protected] K. Peltzer : S. Pengpid University of Limpopo, Turfloop Campus, Sovenga 0727, South Africa K. Peltzer HIV, AIDS, TB, and STIs (HAST), Human Sciences Research Council (HSRC), Pretoria 0001, South Africa
Conclusions A significant prevalence of past-month nocturnal sleeping problems was found. Potential factors associated with the risk of reporting sleeping complaints were identified, which may assist in prevention strategies to promote a better quality of sleep. Keywords Sleep problems . Correlates . Mental health . Health risk behaviour . University students . Multi-country
Introduction Sleeping problems across populations may be related to changes in lifestyle, increasing use of technology, increased work, social demands and tertiary stress (changes from secondary school to university such as reduced adult surpervision, new social opportunities and commitments) transition among university students [1–3]. Developing country populations are undergoing rapid demographic, epidemiologic and health transition [4]. Increasing urbanisation results in increased noise and stress providing a poorer physical and mental environment for sleep [5]. Poverty and mental health are negatively associated in developing countries [6]. Societal changes contributing to sleep loss may particularly impact on adolescents and young adults. Technology such as the internet and mobile phones may contribute globally to the problem of sleep loss and mental health [7]. Sleep problems might be an unrecognised public health issue in low- and middle-income and emerging economy countries, especially among young adults and university student populations. The prevalence of sleep disorders, poor sleep quality or sleeping problems or insomnia among university students has mainly been studied in high-income countries such as in the USA (9.5 [8], 15 [9], 22.5 [10], 27 [11], 50.9 [12] and 60 % [13]), Italy (26.7 % [14]), Spain (60 % [15]), Australia (42 % [3]), Korea (36.2–60 % [16, 17]), Hongkong (68.6 % [18]),
Sleep Breath
Taiwan (54.7 % [19]) and Japan (25.6 % [20]) and a few studies from low- and middle-income countries such as Brazil (28.1 % [21]), Ethiopia (55.8 % [22]), India (17.3 % [23]) and Palestine (9.5 % [24]). Some research seems to show an increase in the prevalence of sleep problems among university students over time, e.g. in the USA over two decades from 1978 to 2000, an increase from 24 to 71 % of self-reported dissatisfaction with their sleep was found [25]. Various risk factors for sleeping problems among university students have been identified as follows: \ sociodemographic factors: being a woman [9, 19, 26–28], older age [12, 14], and living away from parents [29]; (2) stress [3, 10, 13, 18, 22, 28] and childhood adversity [10]; (3) poor mental health, including anxiety, depression or minor psychiatric disturbance [3, 10, 14, 18, 23, 26–33]; (4) poor health status [14, 16, 20]; (5) health risk (behaviour): short sleep [34], smoking [20], drinking more alcohol [13], use of stimulants [35], lack of exercise [12, 36], problem gambling [37], tendency toward Internet addition [19], media use [38], skipping breakfast [19], obesity [36, 39], and motor vehicle accidents [2]; (6) lack of social support [19, 26]; and (7) poor academic performance [11, 32, 40]. The aim of this study was to investigate sleeping problems and its associated factors among university students in mainly low- and middle-income countries.
Methods
construction, agriculture, health and welfare and services. Informed consent was obtained from participating students, and the study was conducted in 2013. Participation rates were in most countries over 90 %. Ethics approvals were obtained from all participating institutions. Measures Sleeping problems The prevalence of nocturnal sleeping problems was estimated based on the question: ‘Overall in the last 30 days, how much of a problem did you have with sleeping, such as falling asleep, waking up frequently during the night, or waking up too early in the morning?’ Response options ranged from 1 (none) to 5 (extreme/cannot do). Sleeping problems were defined by the response to this question with ‘severe’ or ‘extreme/cannot do’ [41]. Sociodemographic questions Sociodemographic questions included age, gender, population group, and residence, and socioeconomic background was assessed by rating their family background as wealthy (within the highest 25 % in ‘country’, in terms of wealth), quite well off (within the 50 to 75 % range for their country), not very well off (within the 25 to 50 % range from ‘country’) or quite poor (within the lowest 25 % in their country, in terms of wealth) [42].
Sample and procedure Stress and health status This cross-sectional study was carried out with a network of collaborators in participating countries (see Acknowledgements). The anonymous, self-administered questionnaire used for data collection was developed in English, then translated and back-translated into languages (Arabic, Bahasa, Chinese, French, Lao, Russian, Spanish, Thai and Turkish) of the participating countries. The study was initiated through personal academic contacts of the principal investigators. These collaborators arranged for data to be collected from 400 male and 400 female undergraduate university students aged 16– 30 years by trained research assistants in 2013 in one or two universities in their respective countries. The universities involved were located in the capital cities or other major cities in the participating countries. Research assistants working in the participating universities asked classes of undergraduate students to complete the questionnaire at the end of a teaching class. Classes were recruited according to timetable scheduling in a quasi-random fashion. The students who completed the survey varied in the number of years for which they had attended the university. A variety of majors were involved, including education, humanities and arts, social sciences, business and law, science, engineering, manufacturing and
History of child physical and sexual abuse was assessed with two questions, and subjective health status with one question. Centres for Epidemiologic Studies Depression Scale We assessed depressive symptoms using the ten-item version of the Center for Epidemiologic Studies Depression Scale [43]. Scoring is classified from 0 to 9 as having a mild level of depressive symptoms, 10 to 14 as moderate depressive symptoms and 15 representing severe depressive symptoms [44]. The Cronbach alpha reliability coefficient of this ten-item scale was 0.74 in this study. Post-traumatic stress disorder A seven-item screener was used to identify post-traumatic stress disorder (PTSD) symptoms in the past month [45]. Items asked whether the respondent had experienced difficulties related to a traumatic experience (e.g. ‘Did you begin to feel more isolated and distant from other people?’, ‘Did you become jumpy or get easily startled by ordinary noises or movements?’). Consistent with epidemiological evidence, participants who answered affirmatively to at least four of the questions were considered to have
Sleep Breath
a positive screen for PTSD [45]. The Cronbach alpha reliability coefficient of this seven-item scale was 0.75 in this study.
Health risk (behaviour) Substance use and gambling Tobacco use was assessed with the question: Do you currently use one or more of the following tobacco products (cigarettes, snuff, chewing tobacco, cigars etc.)? Response options were ‘yes’ or ‘no’ [46]. Heavy alcohol consumption was measured by asking participants ‘how often do you have (for men) five or more and (for women) four or more drinks on one occasion?’ The South Oaks Gambling Screen (SOGS), a standardised measure of pathological gambling and gambling behaviours in their lifetime [47] was used to assess nine different gambling behaviours, e.g. ‘Played cards for money’. Response options ranged from 1=not at all to 3=Once a week or more. Students who scored positive (in terms of more than once a week) on any of the nine gambling behaviours were classified as engaged in gambling. Cronbach alpha for this nine-item scale was 0.84 in this sample. Heavy Internet use was assessed with the question how many hours they normally spend on the internet per day. A cutoff of 6 h or more for heavy Internent use was chosen, in line with some previous studies, e.g. [48, 49] Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ) short version, selfadministered last 7 days (IPAQ-S7S). We used the instructions given in the IPAQ manual for reliability and validity, which is detailed elsewhere [50]. To sum up the single indicators to an overall indicator of PA-related energy expenditure (EE; metabolic equivalent (MET) min−1) is a major goal of the IPAQ instruments. We used the recommended, following MET estimates of IPAQ: Vigorous PA=8 METs, moderate PA=4 METs and walking on average=3.3 METs. For calculating the overall METs PA, each category was multiplied with its special MET estimate value. We also used the recommended categorical score, three levels of PA (low, moderate and high) as proposed in IPAQ Scoring Protocol (short form). Low activity represented individuals who do not meet the criteria for moderate and vigorous intensity categories (
ORIGINAL ARTICLE
Nocturnal sleep problems among university students from 26 countries Karl Peltzer & Supa Pengpid
Received: 15 April 2014 / Revised: 23 June 2014 / Accepted: 8 July 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Background The aim of this study is to estimate the prevalence of nocturnal sleeping problems and its associated factors among university students in mainly low- and middle-income countries. Methods A cross-sectional survey was conducted with 20,222 undergraduate university students (mean age, 20.8; SD=2. 8) from 27 universities in 26 countries across Asia, Africa and the Americas. Results Overall, 10.4 % reported severe or extreme nocturnal sleeping problems (male, 10.2 %; female, 10.5 %) in the past month. Noctural sleeping problems differed by country, from 32.9 % in Indonesia to 3.0 % in Thailand among Asian countries, from 13.7 % in Mauritius to 7.5 % in South Africa, and from 11.8 % in Jamaica to 6.1 % in Columbia in the Americas. In multivariate logistic regression analysis, coming from a poor family background, staying off campus (on their own or with parents or guardians), stress (history of child sexual abuse), poor mental health (depression and PTSD symptoms), health risk behaviour (tobacco use, heavy internet use, gambling, skipping breakfast and having sustained an injury), lack of social support and poor academic performance were associated with nocturnal sleeping problems. K. Peltzer (*) : S. Pengpid ASEAN Institute for Health Development, Mahidol University, Salaya, Phutthamonthon, Nakhonpathom, Thailand 73170 e-mail: [email protected] S. Pengpid e-mail: [email protected] K. Peltzer : S. Pengpid University of Limpopo, Turfloop Campus, Sovenga 0727, South Africa K. Peltzer HIV, AIDS, TB, and STIs (HAST), Human Sciences Research Council (HSRC), Pretoria 0001, South Africa
Conclusions A significant prevalence of past-month nocturnal sleeping problems was found. Potential factors associated with the risk of reporting sleeping complaints were identified, which may assist in prevention strategies to promote a better quality of sleep. Keywords Sleep problems . Correlates . Mental health . Health risk behaviour . University students . Multi-country
Introduction Sleeping problems across populations may be related to changes in lifestyle, increasing use of technology, increased work, social demands and tertiary stress (changes from secondary school to university such as reduced adult surpervision, new social opportunities and commitments) transition among university students [1–3]. Developing country populations are undergoing rapid demographic, epidemiologic and health transition [4]. Increasing urbanisation results in increased noise and stress providing a poorer physical and mental environment for sleep [5]. Poverty and mental health are negatively associated in developing countries [6]. Societal changes contributing to sleep loss may particularly impact on adolescents and young adults. Technology such as the internet and mobile phones may contribute globally to the problem of sleep loss and mental health [7]. Sleep problems might be an unrecognised public health issue in low- and middle-income and emerging economy countries, especially among young adults and university student populations. The prevalence of sleep disorders, poor sleep quality or sleeping problems or insomnia among university students has mainly been studied in high-income countries such as in the USA (9.5 [8], 15 [9], 22.5 [10], 27 [11], 50.9 [12] and 60 % [13]), Italy (26.7 % [14]), Spain (60 % [15]), Australia (42 % [3]), Korea (36.2–60 % [16, 17]), Hongkong (68.6 % [18]),
Sleep Breath
Taiwan (54.7 % [19]) and Japan (25.6 % [20]) and a few studies from low- and middle-income countries such as Brazil (28.1 % [21]), Ethiopia (55.8 % [22]), India (17.3 % [23]) and Palestine (9.5 % [24]). Some research seems to show an increase in the prevalence of sleep problems among university students over time, e.g. in the USA over two decades from 1978 to 2000, an increase from 24 to 71 % of self-reported dissatisfaction with their sleep was found [25]. Various risk factors for sleeping problems among university students have been identified as follows: \ sociodemographic factors: being a woman [9, 19, 26–28], older age [12, 14], and living away from parents [29]; (2) stress [3, 10, 13, 18, 22, 28] and childhood adversity [10]; (3) poor mental health, including anxiety, depression or minor psychiatric disturbance [3, 10, 14, 18, 23, 26–33]; (4) poor health status [14, 16, 20]; (5) health risk (behaviour): short sleep [34], smoking [20], drinking more alcohol [13], use of stimulants [35], lack of exercise [12, 36], problem gambling [37], tendency toward Internet addition [19], media use [38], skipping breakfast [19], obesity [36, 39], and motor vehicle accidents [2]; (6) lack of social support [19, 26]; and (7) poor academic performance [11, 32, 40]. The aim of this study was to investigate sleeping problems and its associated factors among university students in mainly low- and middle-income countries.
Methods
construction, agriculture, health and welfare and services. Informed consent was obtained from participating students, and the study was conducted in 2013. Participation rates were in most countries over 90 %. Ethics approvals were obtained from all participating institutions. Measures Sleeping problems The prevalence of nocturnal sleeping problems was estimated based on the question: ‘Overall in the last 30 days, how much of a problem did you have with sleeping, such as falling asleep, waking up frequently during the night, or waking up too early in the morning?’ Response options ranged from 1 (none) to 5 (extreme/cannot do). Sleeping problems were defined by the response to this question with ‘severe’ or ‘extreme/cannot do’ [41]. Sociodemographic questions Sociodemographic questions included age, gender, population group, and residence, and socioeconomic background was assessed by rating their family background as wealthy (within the highest 25 % in ‘country’, in terms of wealth), quite well off (within the 50 to 75 % range for their country), not very well off (within the 25 to 50 % range from ‘country’) or quite poor (within the lowest 25 % in their country, in terms of wealth) [42].
Sample and procedure Stress and health status This cross-sectional study was carried out with a network of collaborators in participating countries (see Acknowledgements). The anonymous, self-administered questionnaire used for data collection was developed in English, then translated and back-translated into languages (Arabic, Bahasa, Chinese, French, Lao, Russian, Spanish, Thai and Turkish) of the participating countries. The study was initiated through personal academic contacts of the principal investigators. These collaborators arranged for data to be collected from 400 male and 400 female undergraduate university students aged 16– 30 years by trained research assistants in 2013 in one or two universities in their respective countries. The universities involved were located in the capital cities or other major cities in the participating countries. Research assistants working in the participating universities asked classes of undergraduate students to complete the questionnaire at the end of a teaching class. Classes were recruited according to timetable scheduling in a quasi-random fashion. The students who completed the survey varied in the number of years for which they had attended the university. A variety of majors were involved, including education, humanities and arts, social sciences, business and law, science, engineering, manufacturing and
History of child physical and sexual abuse was assessed with two questions, and subjective health status with one question. Centres for Epidemiologic Studies Depression Scale We assessed depressive symptoms using the ten-item version of the Center for Epidemiologic Studies Depression Scale [43]. Scoring is classified from 0 to 9 as having a mild level of depressive symptoms, 10 to 14 as moderate depressive symptoms and 15 representing severe depressive symptoms [44]. The Cronbach alpha reliability coefficient of this ten-item scale was 0.74 in this study. Post-traumatic stress disorder A seven-item screener was used to identify post-traumatic stress disorder (PTSD) symptoms in the past month [45]. Items asked whether the respondent had experienced difficulties related to a traumatic experience (e.g. ‘Did you begin to feel more isolated and distant from other people?’, ‘Did you become jumpy or get easily startled by ordinary noises or movements?’). Consistent with epidemiological evidence, participants who answered affirmatively to at least four of the questions were considered to have
Sleep Breath
a positive screen for PTSD [45]. The Cronbach alpha reliability coefficient of this seven-item scale was 0.75 in this study.
Health risk (behaviour) Substance use and gambling Tobacco use was assessed with the question: Do you currently use one or more of the following tobacco products (cigarettes, snuff, chewing tobacco, cigars etc.)? Response options were ‘yes’ or ‘no’ [46]. Heavy alcohol consumption was measured by asking participants ‘how often do you have (for men) five or more and (for women) four or more drinks on one occasion?’ The South Oaks Gambling Screen (SOGS), a standardised measure of pathological gambling and gambling behaviours in their lifetime [47] was used to assess nine different gambling behaviours, e.g. ‘Played cards for money’. Response options ranged from 1=not at all to 3=Once a week or more. Students who scored positive (in terms of more than once a week) on any of the nine gambling behaviours were classified as engaged in gambling. Cronbach alpha for this nine-item scale was 0.84 in this sample. Heavy Internet use was assessed with the question how many hours they normally spend on the internet per day. A cutoff of 6 h or more for heavy Internent use was chosen, in line with some previous studies, e.g. [48, 49] Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ) short version, selfadministered last 7 days (IPAQ-S7S). We used the instructions given in the IPAQ manual for reliability and validity, which is detailed elsewhere [50]. To sum up the single indicators to an overall indicator of PA-related energy expenditure (EE; metabolic equivalent (MET) min−1) is a major goal of the IPAQ instruments. We used the recommended, following MET estimates of IPAQ: Vigorous PA=8 METs, moderate PA=4 METs and walking on average=3.3 METs. For calculating the overall METs PA, each category was multiplied with its special MET estimate value. We also used the recommended categorical score, three levels of PA (low, moderate and high) as proposed in IPAQ Scoring Protocol (short form). Low activity represented individuals who do not meet the criteria for moderate and vigorous intensity categories (
