Abstract
Objectives
The purpose of this study was to evaluate the prevalence of poor sleep health (ie, poor sleep quality and short sleep duration) in a sample of men who have sex with men (MSM). In addition, this study examined whether poor sleep health was associated with depressive symptoms, substance use, and sexual risk behaviors in this sample.
Design
Cross-sectional survey.
Participants
Broadcast advertisements were placed on a popular smartphone application for MSM in January 2016 to recruit users in the London metropolitan area (n = 202) to complete a Web-based survey, which included validated measures of sleep quality and duration.
Measurements
Poor sleep quality was defined based on self-report as very or fairly bad. Short sleep duration was defined as less than 7 hours each night. Regression models were used to assess associations between sleep variables and self-reported depressive symptoms, substance use, and sexual risk behaviors.
Results
About one-third (34.6%) of the respondents reported poor sleep quality and almost half (43.6%) reported sleeping less than 7 hours every night. Several poor sleep health variables were independently associated with depressive symptoms, substance use (eg, use of alcohol or marijuana), and condomless anal intercourse. For example, typical nightly sleep duration of less than 7 hours was associated with condomless receptive anal intercourse with a higher number of sexual partners (incidence rate ratio, 2.65; 95% confidence interval: 1.63–4.30; P < .001).
Conclusion
Sleep health promotion interventions should be developed for MSM, which may promote positive mental health as well as reduce substance use and sexual risk behaviors in this population.
Keywords: Poor sleep health, Depressive symptoms, Substance use, Sexual risk behaviors, Gay men’s health, Men who have sex with men (MSM)
Introduction
Sleep, like nutrition and physical activity, is a critical determinant of health and well-being.1 Poor sleep health has been implicated in poorer health outcomes across populations. Moreover, research on sleep patterns in the general population suggests that poor sleep quality and short sleep duration are highly prevalent, where only about 1 in 5 Britons (22%) sleep for the recommended 7 to 8 hours each night.2 Despite the large and accumulating evidence on the prevalence and effects of poor seep health, no prior studies have examined sleep health specifically among gay, bisexual, and other men who have sex with men (MSM), who experience multiple health disparities. To illustrate, MSM comprise the largest proportion of people living with HIV in the United Kingdom.3 In addition, MSM often experience syndemics of significant mental health and substance abuse disorders.4
Recent evidence strongly suggests that difficulties falling asleep and sleeping through the night are not only typical symptoms of depression, but also may be independent risk factors for depression and low quality of life long-term.5,6 With regard to substance use, research in otherwise healthy adolescents and adults indicates that poor sleep can influence substance use (eg, use of marijuana, alcohol, cigarettes).7,8 As for sexual behaviors, studies in the general population have yielded conflicting results on the association with sleep health, with some evidence from the United States suggesting that there is a positive relationship between sleep and sexual behaviors in urban adolescents but not in rural adolescents.8,9
Poor sleep health could be implicated in poor mental health because of increased stress due to suboptimal sleep. Laboratory-based studies have shown that sleep deprivation and poor sleep health can impair decision-making skills.10 Therefore, poor sleep health can be associated with increases in alcohol and substance use. Poor sleep health may also lead one to rely on alcohol and other depressants to fall asleep or stay asleep. Conversely, the use of stimulants (eg, cocaine, ecstasy/3,4-methylenedioxymethamphetamine [MDMA]) is associated with poor sleep architecture, suggesting a bidirectional relationship between substance use behaviors and sleep health.11 In the context of MSM and HIV transmission, poor sleep health may impair one’s willingness and/or ability to negotiate condom use with a potential partner. However, no published research has examined whether sleep health is associated with mental health, substance use, or sexual risk behaviors among MSM and very few studies have been conducted investigating associations between sleep health and sexual risk behaviors overall.
The effects of poor sleep may be particularly salient for MSM who often use geosocial-networking smartphone applications to meet potential sexual partners for at least 2 reasons. First, previous work has shown that many MSM use these applications across the span of the day, including late night (9:30 PM to 2:30 AM) and early morning (2:30 AM to 6:30 AM).12 These are oftentimes when bars, clubs, and other social venues might be closed. Second, the use of smartphones during these hours has been linked to poor sleep,13 suggesting that MSM who use geosocial-networking smartphone applications may have particularly poor sleep health. As such, the purpose of this study is to evaluate the prevalence of poor sleep health in a sample of MSM residing in London, England, recruited from a popular geosocial-networking smartphone application for MSM. In addition, this study examined whether poor sleep quality and short sleep duration were correlates of mental health, substance use, and sexual risk behaviors in the app-using sample. We note that these applications use global positioning system technology to form connections between users based on their current location.14,15 These geospatial technologies have generated quicker and easier ways for MSM to meet potential partners16 and, consequently, may facilitate users’ ability to have multiple concurrent partners, thereby increasing their risk for acquiring and transmitting HIV17 and other sexually transmitted infections.16
Methods
Sample recruitment
Broadcast advertisements were placed on a popular geosocial-networking smartphone application for gay, bisexual, and other MSM in January 2016. Advertisements were limited to the London metropolitan area. In line with previous research,12 users were shown an advertisement with text encouraging them to click through the advertisement to complete an anonymous Web-based survey. Users were shown this advertisement the first time they logged into the application during four 24-hour periods, which were intentionally not consecutive days. Precautions (eg, use of the “Prevent Ballot Box Stuffing” feature on Qualtrics) were taken to avoid and eliminate duplicate responses as done in previous research18 because participants could have theoretically viewed the advertisement 4 times during the recruitment period, but no duplicate responses were apparent. Participants were told that completing the survey would enter them for a chance to win £50.
At the end of the recruitment period (ie, four 24-hour periods), 1410 users had clicked through the advertisement and reached the landing page of the survey, and 202 users provided informed consent and completed the survey, representing an overall response rate of 14.3%. The survey included 47 items and took an average (SD) of 9.68 (5.65) minutes for users to complete. All protocols were approved by the New York University Committee on Activities Involving Human Subjects before data collection. All respondents reported being at least 18 years old at the time of survey administration, an inclusion criterion.
Measures
Sleep quality
To assess sleep quality, participants were asked, “During the past month, how would you rate your sleep quality overall?”.19 Response options were “very good,” “fairly good,” “fairly bad,” and “very bad.” These 4 options were collapsed into 2 categories—good sleep quality (including responses of very good and fairly good) and poor sleep quality (including responses of very bad and fairly bad) to improve statistical power given the low number of responses in the “very good” and “very bad” categories. Our collapsing approach for the 4-level sleep quality variable has been used in prior epidemiologic research.20
Sleep duration
Self-reported typical sleep duration was measured with an item asking, “During the past month, how many hours of actual sleep did you get each night?”.19 Responses were open-ended but limited to a single integer. Although previous studies have often categorized sleep duration as short (≤6 hours), average (7–8 hours), and long (≥9 hours),21 these 3 categories were collapsed into 2 categories—short (≤6 hours) and average (≥7 hours)—to improve the statistical power given the low number of responses in the “long” category. Our approach to categorizing sleep duration is consistent with previous epidemiologic studies.20
Mental health
The self-reported presence of depressive symptoms was assessed using the Patient Health Questionnaire-2, a reliable and validated screening tool for depressive symptoms.22 A dichotomous variable was created using score on the measure indicating the absence (score: <3) or presence (score: ≥3) of self-reported depressive symptoms.
Substance use
Participants were asked to check off substances they had used with the last 3 months from a list, including alcohol (≥5 drinks in a row), marijuana, acid/lysergic acid diethylamide (LSD), cocaine/crack cocaine, ecstasy/MDMA, ketamine, γ-hydroxybutyric acid/γ-butyrolactone (GHB/GBL), methamphetamine, and nitrite inhalers (poppers). Dichotomous variables were created for alcohol use (use vs nonuse) and for recent drug use for 4 other substances (use vs nonuse of marijuana, cocaine, inhalant nitrite, club drugs, and methamphetamine). A composite variable indicating use and nonuse of club drugs including ecstasy/MDMA, GHB/GBL, ketamine, and LSD/acid was created.23 Sensitivity analyses indicated the robustness of this composite variable. Cocaine and methamphetamine were excluded from this category because these drugs are used in a wider variety of contexts.24
Condomless anal intercourse
First, participants indicated the total number of partners with whom they had had insertive anal intercourse and receptive anal intercourse in the preceding 3 months. For both behaviors, participants were then asked with how many of these partners they did not use a condom, hereafter referred to as condomless insertive anal intercourse and condomless receptive anal intercourse.
Demographic characteristics
Age was measured in a continuous manner and then categorized into 18 to 24 years, 25 to 30 years, 31 to 40 years, 41 to 50 years, and 51 years and older. Self-reported sexual orientation was categorized as gay, bisexual, and other. Ethnic groups were categorized as white/white British, black/black British, Asian/Asian British, and mixed/multiple ethnic groups/other. Employment status was categorized as employed, unemployed, student, and retired. Relationship status was categorized by participants as currently being in a relationship or not. HIV status was assessed based on self-report with 3 response options: HIV positive, HIV negative, and unknown/never tested.
Statistical analyses
First, descriptive statistics (eg, frequencies) were calculated. Next, bivariable and multivariable models were constructed to examine associations between poor sleep health (defined as poor sleep quality and short sleep duration as the 2 exposure variables) and the studied health outcomes—depressive symptoms, substance use, and the numbers of partners with whom they had insertive or receptive anal intercourse, with and without condoms. Log-binomial models (yielding prevalence ratios [PRs]) were fit for associations between sleep quality and sleep duration and the presence of depressive symptoms and alcohol, club drug, cocaine, inhalant nitrite, marijuana, and methamphetamine use. Although the most common method of modeling dichotomous outcomes is binary logistic regression, the odds ratios derived from these models may overestimate the PRs if outcomes are common.25 Negative binomial regression models (yielding incidence rate ratios [IRRs]) were used to assess associations between sleep health variables and sexual intercourse. This modeling approach was selected as the numbers of partners for each behavior were count variables and overdispersed with regard to the mean.26 In all multivariable models, demographic characteristics as well as the other outcomes were controlled for to more actually estimate the association of interest. Statistical significance was determined at P < .05.
Results
Sample demographics
Demographic characteristics of the sample are shown in Table 1. The average (SD) age in the sample was 36.2 (11.5) years, where 38.7% of respondents were between 18 and 30 years old. Most (97.5%) described their sexual orientation as gay or bisexual. Almost three-fourths (71.8%) of the sample identified their ethnic group as white or white British. Most (85.2%) were either currently employed or enrolled in school. One-fifth (19.3%) reported currently being in a relationship with another man. Most (83.7%) self-reported their HIV status as negative and 11.4% reported their HIV status as positive.
Table 1.
Sample demographics (n = 202)
| % (n) | |
|---|---|
| Age (y) | |
| 18–24 | 14.9 (30) |
| 25–30 | 23.8 (48) |
| 31–40 | 30.7 (62) |
| 41–50 | 18.8 (38) |
| ≥51 | 11.9 (24) |
| Sexual orientation | |
| Gay | 87.1 (176) |
| Bisexual | 10.4 (21) |
| Other | 2.5 (5) |
| Ethnic group | |
| White/White British | 71.8 (145) |
| Black/Black British | 5.4 (11) |
| Asian/Asian British | 7.9 (16) |
| Mixed/Multiple ethnic groups/other | 13.9 (28) |
| Employment status | |
| Employed | 73.1 (147) |
| Unemployed | 10.9 (22) |
| Student | 12.4 (25) |
| Retired | 3.5 (7) |
| Current relationship | |
| Yes | 19.3 (39) |
| No | 80.7 (163) |
| Self-reported HIV status | |
| Positive | 11.4 (23) |
| Negative | 83.7 (169) |
| Unknown/Never tested | 5.0 (10) |
Poor sleep health
About one-third (34.6%) of the respondents reported poor sleep quality and almost half (43.6%) reported sleeping less than 7 hours every night, with an average (SD) of 6.65 (1.69) hours of reported sleep each night (Table 2). The minimum amount of self-reported sleep duration was 2 hours, while the maximum amount was 15 hours.
Table 2.
Self-reported sleep health, mental health, substance use, and sexual risk behaviors
| % (n) | |
|---|---|
| Sleep quality | |
| Very good | 10.9 (22) |
| Fairly good | 54.5 (110) |
| Fairly bad | 27.7 (56) |
| Very bad | 6.9 (14) |
| Sleep durationa(h) | |
| <5 | 7.9 (16) |
| 5–6 | 35.7 (72) |
| 7–8 | 46.5 (94) |
| >8 | 6.4 (13) |
| Depressive symptoms | |
| Absent | 77.7 (157) |
| Present | 22.3 (45) |
| Alcohol (>5 drinks) | 38.6 (78) |
| Club drugs | 23.3 (47) |
| Ecstasy/MDMA | 14.9 (30) |
| GHB/GBL | 14.9 (30) |
| Ketamine | 4.5 (9) |
| LSD/Acid | 1.0 (2) |
| Cocaine | 14.4 (29) |
| Inhalant nitrites | 36.6 (74) |
| Marijuana | 19.8 (40) |
| Methamphetamine use | 13.9 (28) |
| Insertive anal intercourse | |
| 0 partners | 24.6 (48) |
| ≥1partners | 75.4 (147) |
| Receptive anal intercourse | |
| 0 partners | 34.4 (67) |
| ≥1partners | 65.6 (128) |
| Condomless insertive anal intercourse | |
| 0 partners | 55.0 (111) |
| ≥1partners | 45.0 (91) |
| Condomless receptive anal intercourse | |
| 0 partners | 62.9 (127) |
| ≥1partners | 37.1 (75) |
Abbreviations: MDMA, 3,4-methylenedioxymethamphetamine; GHB/GBL, γ-hydroxybutyric acid/γ-butyrolactone; LSD, lysergic acid diethylamid.
Nightly.
Poor sleep health and mental health
More than a fifth (22.3%) of the sample reported experiencing depressive symptoms (Table 3). In multivariable models, both poor sleep quality (PR, 4.48; 95% confidence interval [CI], 1.85–10.88; P = .001) and short sleep duration (PR, 2.49; 95% CI, 1.06–5.81; P = .036) were significantly associated with the presence of depressive symptoms when controlling for demographic variables, substance use, and sexual intercourse.
Table 3.
Multivariable associations between poor sleep health and depressive symptoms
| Depressive symptoms, PR (95% CI) | |
|---|---|
| Poor sleep quality | 4.48**(1.85–10.88) |
| Short sleep duration | 2.49*(1.06–5.81) |
Adjusted for age, sexual orientation, ethnic group membership, employment status, relationship status, HIV status, alcohol use, club drug use, cocaine use, inhalant nitrite use, marijuana use, methamphetamine use, and engagement in condomless insertive and receptive anal intercourse.
Abbreviations: PR, prevalence ratio; CI, confidence interval.
P < .05.
P < .01.
P < .001.
Poor sleep health and substance use
More than half (53.0%) of respondents reported use of at least one substance in the last 3 months; 38.6% reported binge drinking. The most commonly used substances were reported to be inhalant nitrites (36.6%), marijuana (19.8%), GHB or GBL (14.9%), ecstasy or MDMA (14.9%), power cocaine or crack cocaine (14.4%), and methamphetamine (13.9%). Smaller portions of the sample reported recent use of ketamine (4.5%) or LSD/acid (1.0%).
In multivariable models (Table 4), poor sleep quality was associated with increased odds of marijuana use in the preceding 3 months (PR, 3.06; 95% CI, 1.27–7.36; P = .013) and poor sleep duration was associated with methamphetamine use in the preceding 3 months (PR, 2.84; 95% CI, 1.02–7.90; P = .046). Furthermore, poor sleep quality was associated with an increase in odds of reporting alcohol use (PR, 2.34; 95% CI, 1.11–4.91; P = .025).
Table 4.
Multivariable associations between poor sleep health and substance use: log-binomial regression
| Alcohol use, PR (95% CI) | Club drug use, PR (95% CI) | Cocaine use, PR (95% CI) | Inhalant nitrite use, PR (95% CI) | Marijuana use, PR (95% CI) | Methamphetamine use, PR (95% CI) | |
|---|---|---|---|---|---|---|
| Poor sleep quality | 2.34*(1.11–4.91) | 1.04 (0.46–2.40) | 1.13 (0.41–3.09) | 1.38 (0.66–2.90) | 3.06* (1.27–7.36) | 1.52 (0.53–4.38) |
| Short sleep duration | 1.96 (0.95–4.04) | 1.09 (0.50–2.39) | 1.11 (0.43–2.87) | 1.26 (0.62–2.53) | 1.22 (0.53–2.77) | 2.84*(1.02–7.90) |
Adjusted for age, sexual orientation, ethnic group membership, employment status, relationship status, HIV status, presence of depressive symptoms, engagement in condomless insertive anal intercourse, and engagement in condomless receptive anal intercourse.
Abbreviations: PR, prevalence ratio; CI, confidence interval.
P < .05.
P < .01;
P < .001
Poor sleep health and condomless sex
Three quarters (75.2%) of respondents reported having engaged in insertive anal intercourse with one or more partners, with an average (SD) of 4.6 (8.3) partners. Almost half (45.0%) of the sample reported engaging in condomless insertive anal intercourse with one or more partners, with an average (SD) of 2.3 (5.8) partners. Almost two-thirds (64.9%) of respondents reported engaging in receptive anal intercourse with one or more partners, with an average (SD) of 3.3 (7.8) partners. More than one-third (37.1%) of the sample reported engaging in condomless receptive anal intercourse with one or more partners, with an average (SD) of 1.8 (6.9) partners. In multi-variable models, poor sleep quality was associated with reporting having condomless insertive anal sex with fewer partners (IRR, 0.52; 95% CI, 0.34–0.97; P = .010).
In addition, in multivariable models (Table 5), poor sleep quality was associated with reporting receptive anal intercourse with a greater number of partners (IRR, 1.54; 95% CI, 1.01–2.35; P = .043) and condomless receptive anal intercourse with a greater number of partners (IRR, 2.36; 95% CI, 1.45–3.84; P = .011). Likewise, typical sleep duration of less than 7 hours was associated with receptive anal intercourse with a greater number of sexual partners (IRR, 1.71; 95% CI, 1.14–2.56; P = .010). Typical sleep duration of less than 7 hours was also associated with reporting condomless receptive anal sex with a higher number of partners in multivariable models (IRR, 2.65; 95% CI, 1.63–4.30; P < .001).
Table 5.
Multivariable associations between poor sleep health and number of sexual partners: negative-binomial regression
| Insertive anal intercourse, IRR (95% CI) | Condomless insertive anal intercourse, IRR (95% CI) | Receptive anal intercourse, IRR (95% CI) | Condomless receptive anal intercourse, IRR (95% CI) | |
|---|---|---|---|---|
| Poor sleep quality | 0.71 (0.48–1.07) | 0.54*(0.340–0.87) | 1.54*(1.013–2.35) | 2.36*(1.450–3.84) |
| Short sleep duration | 0.88 (0.61–1.26) | 0.81 (0.532–1.24) | 1.71*(1.139–2.56) | 2.65***(1.634–4.30) |
Adjusted for age, sexual orientation, ethnic group membership, employment status, relationship status, HIV status, presence of depressive symptoms, alcohol use, club drug use, cocaine use, inhalant nitrite use, marijuana use, and methamphetamine use.
P < .05.
P < .01.
P < .001.
Discussion
This is the first study to examine sleep health in a sample of gay, bisexual, and other MSM on geosocial networking apps. In addition, this study is the first to examine poor sleep health variables as correlates of mental health, substance use, and condomless anal sex among MSM. Therefore, this study provides a meaningful contribution to the literature in a high-risk sample of MSM: app-using MSM. About one-third reported poor sleep quality and about half of respondents reported typically sleeping less than 7 hours each night, meaning a large portion of the sample receives an insufficient amount of sleep each night. In this study, poor sleep quality and short sleep duration were associated with depressive symptoms, substance use (eg, alcohol, marijuana, methamphetamine), and some condomless anal intercourse behaviors among MSM. No previous studies have examined sleep health among MSM, so these findings cannot be directly compared with those of other studies. However, multiple studies found that poor sleep health is a robust predictor of poor health outcomes,27,28 including mental health, substance use and sexual risk behaviors in general populations.5–10
There are a number of potential explanations for these findings. Via increased stress, poor sleep health can influence depression and, subsequently, substance use. This, in turn, can lead to sexual risk behaviors such as condomless sex. As for substance use, individuals may rely on alcohol and other depressant substances to fall asleep or stay asleep29; at the same time, it is generally acknowledged that substance use exerts an adverse physiological impact on sleep quality and duration. As stated previously, poor sleep health may impair one’s ability to make decisions10 and to negotiate condom use with a potential sexual partner. In addition, poor sleep health may also reduce one’s self-efficacy30 for engaging in safer sexual practice. Paradoxically, though, we found that poor sleep quality was associated with reporting having condomless insertive anal sex with fewer partners. This was an unexpected finding and requires further investigation. It is possible, however, that this is due to differences in physical exertion of individuals who are insertive partners vs receptive partners—perhaps when insertive sexual partners have poor sleep they are too tired to engage in sexual intercourse.
Future research directions
Future empirical research should aim to investigate the unidirectional and potentially bidirectional causal mechanisms linking poor sleep to mental health, substance use, and sexual risk behaviors, including pathophysiologic mechanisms. Prospective study designs could be used to assess longitudinal changes in these variables. In addition, given the conflicting findings regarding sleep quality and condomless insertive and receptive intercourse, future research should differentiate between main and casual partners, the HIV status of each partner, and the number of sex events per partner, which may reveal more nuanced associations between sleep and sexual risk behaviors. Moreover, studies should examine sleep health among large samples of MSM and samples not recruited only through geosocial-networking smartphone applications and MSM samples across different geographic locations. In addition, the use of objective measures of sleep and health behaviors would advance the science by going beyond self-reported measures. For example, sleep can be measured using accelerometers,31 and mental health, substance use and sexual risk behaviors could be assessed using ecological momentary assessment methods to minimize recall bias.32 Finally, given that our sample of sexual minority men often suffered from poor sleep health, future research can also examine correlates of poor sleep health in sexual minority men, such as psychosocial stress.33,34 Although such research has not been conducted among sexual minority men, it is well known that sexual minorities experience increased stress and related anxiety,35 which could contribute to sleep difficulties.
Study implications
Although the extent to which lesbian, gay, bisexual and transgender health disparities extend to the field of sleep health is rarely examined, this study clearly suggests that a large proportion of MSM in this sample has poor health, including sleeping less than 7 to 9 hours, the recommended sleep duration for adults.36 Given its associations with adverse health behaviors and outcomes, promotion of sleep health should be considered in guidelines for lesbian, gay, bisexual and transgender–affirmative healthcare practice and as part of public health campaigns targeted to MSM. Such campaigns can use both “traditional” and smartphone-based interventions using geosocial-networking smartphone applications such as Grindr, Jack’d, and Scruff, applications commonly used by MSM.12 Although no existing public health interventions that directly address sleep health in MSM, sexual health promotion interventions targeted to MSM have leveraged these applications.37
Study limitations
The findings of this study are subject to several limitations. First, variable cutoff points for sleep duration have been used and in this study were derived from self-reported measures rather than objective accelerometer data, which may be less biased by poor recall. Second, in this study, other health behaviors and outcomes were analyzed based on self-reported data. Same-source bias could thus be an issue, as the exposure and outcomes were all examined via self-report. Furthermore, residual confounding (eg, omitted variable bias) might be a concern. It is possible that the survey excluded important confounding variables associated with both the independent variable and the dependent variable (eg, self-regulation, health consciousness). Consequently, these variables cannot be controlled in the multivariable regression analyses. In addition, this study used a cross-sectional design, therefore precluding any causal inference, given that reverse causation is possible. In addition, the incongruence between the 3-month recall period for substance use and sexual behaviors and 1-month recall period for sleep quality and duration is an additional limitation of this study.
Given that this sample was recruited from a geosocial-networking smartphone application in the London metropolitan area, these findings may only be generalizable to MSM who use geosocial-networking smartphone applications in London. Indeed, these relationships could be different in MSM who do not use these applications and in MSM in different rural and urban settings in England and beyond. In addition, there might be seasonal variation in sleep quality and duration among Londoners,38 which was not captured in this survey conducted in January 2016; however, the evidence on such seasonal variation in sleep among adults in the United Kingdom is conflicting.39 Lastly, the sample was recruited from a single geosocial-networking smartphone application and given that there are many applications commonly used by MSM,12 these findings may not be generalizable to MSM who use other applications or non-app using MSM (as there was no comparison group in this study). We note, though, that we specifically selected this location because it has the highest number of users of this application worldwide.40
Conclusion
Poor sleep health was common among this sample of MSM who use geosocial-networking smartphone applications in London. In addition, poor sleep health was associated with the presence of depressive symptoms, substance use, and condomless anal sex. Sleep health promotion should be targeted to MSM, as it may reduce adverse sleep-related health behaviors and outcomes in this vulnerable population.
Acknowledgments
We thank Jermaine Blakley and Gina Leipertz for conducting and summarizing some of the background research, and we thank Jace Morganstein for commenting on an early version of the manuscript. We also thank the participants of this study who contributed to the project.
Disclosure
Dr Dustin Duncan is a scholar in the National Heart, Lung, and Blood Institute–funded PRIDE Behavioral Medicine and Sleep Disorders Research Program (Grant: 2R25HL105444-06; Principal Investigators: Drs Girardin Jean-Louis and Gbenga Ogedegbe) and a scholar in the HIV Prevention Trials Network (HPTN) Scholars Program (Program Directors: Drs Darrell Wheeler and Sten Vermund). Drs Kenneth Mayer and Steven Safren were supported by the Harvard University Center for AIDS Research (Grant: P30AI060354). Dr Safren was also supported by Grant K24MH094214. Dr Joseph Palamar was supported by Grant K01DA038800. This work was supported by the New York University College of Arts and Science Dean’s Undergraduate Research Fund (Principal Investigator: William C. Goedel) and Dr Dustin Duncan’s New York University School of Medicine Start-Up Research Fund.
References
- 1.Institute of Medicine. Committee on Sleep Medicine and Research Sleep disorders and sleep deprivation: an unmet public health problem. Washington, DC: National Academies Press; 2006. [PubMed] [Google Scholar]
- 2.The Sleep Council. The great British bedtime report. Chapel Hill, England: The Sleep Council; 2013. [Google Scholar]
- 3.Public Health England. HIV in the United Kingdom, 2014. London, England: Public Health England; 2015. [Google Scholar]
- 4.Stall R, Friedman M, Catania JA. Interacting epidemics and gay men’s health: a theory of syndemic production among urban gay men. In: Wolitski RJ, Stall R, Valdiserri RO, editors. Unequal opportunity: health disparities affecting gay and bisexual men in the United States. New York, NY: Oxford University Press; 2008. pp. 251–274. [Google Scholar]
- 5.Tsuno N, Besset A, Ritchie K. Sleep and depression. J Clin Psychiatry. 2005 doi: 10.4088/jcp.v66n1008. [DOI] [PubMed] [Google Scholar]
- 6.Roane BM, Taylor DJ. Adolescent insomnia as a risk factor for early adult depression and substance abuse. Sleep. 2008;31(10):1351–1356. [PMC free article] [PubMed] [Google Scholar]
- 7.Peltzer K, Pengpid S. Nocturnal sleep problems among university students from 26 countries. Sleep Breath. 2015;19(2):499–508. doi: 10.1007/s11325-014-1036-3. [DOI] [PubMed] [Google Scholar]
- 8.McKnight-Eily LR, Eaton DK, Lowry R, Croft JB, Presley-Cantrell L, Perry GS. Relationships between hours of sleep and health-risk behaviors in US adolescent students. Prev Med. 2011;53(4):271–273. doi: 10.1016/j.ypmed.2011.06.020. [DOI] [PubMed] [Google Scholar]
- 9.O’Brien EM, Mindell JA. Sleep and risk-taking behavior in adolescents. Behav Sleep Med. 2005;3(3):113–133. doi: 10.1207/s15402010bsm0303_1. [DOI] [PubMed] [Google Scholar]
- 10.Harrison Y, Horne JA. The impact of sleep deprivation on decision making: a review. J Exp Psychol Appl. 2000;6(3):236–239. doi: 10.1037//1076-898x.6.3.236. [DOI] [PubMed] [Google Scholar]
- 11.Schierenbeck T, Riemann D, Berger M, Hornyak M. Effect of illicit recreational drugs upon sleep: cocaine, ecstasy and marijuana. Sleep Med Rev. 2008;12(5):381–389. doi: 10.1016/j.smrv.2007.12.004. [DOI] [PubMed] [Google Scholar]
- 12.Goedel WC, Duncan DT. Geosocial-networking app usage patterns of gay, bisexual, and other men who have sex with men: survey among users of Grindr, a mobile dating app. JMIR Public Health Surveill. 2015;1(1):e4. doi: 10.2196/publichealth.4353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Lanaj K, Johnson RE, Barnes CM. Beginning the workday yet already depleted? Consequences of late-night smartphone use and sleep. Organ Behav Hum Decis Process. 2014;124(1):11–23. [Google Scholar]
- 14.Landovitz RJ, Tseng C-H, Weissman M, Haymer M, Mendenhall B, Rogers K, et al. Epidemiology, sexual risk behavior, and HIV prevention practices of men who have sex with men using GRINDR in Los Angeles. Calif J Urban Health. 2013;90(4):729–739. doi: 10.1007/s11524-012-9766-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Phillips G, II, Magnus M, Kuo I, Rawls A, Peterson J, Jia Y, et al. Use of geosocial networking (GSN) mobile phone applications to find men for sex by men who have sex with men (MSM) in Washington, DC. AIDS Behav. 2014;18(9):1630–1637. doi: 10.1007/s10461-014-0760-9. [DOI] [PubMed] [Google Scholar]
- 16.Beymer MR, Weiss RE, Bolan RK, Rudy ET, Bourque LB, Rodriguez JP, et al. Sex on demand: geosocial networking phone apps and risk of sexually transmitted infections among a cross-sectional sample of men who have sex with men in Los Angeles county. Sex Transm Infect. 2014;90(7):567–572. doi: 10.1136/sextrans-2013-051494. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Morris M, Kretzschmar M. Concurrent partnerships and the spread of HIV. AIDS. 1997;11(5):641–648. doi: 10.1097/00002030-199705000-00012. [DOI] [PubMed] [Google Scholar]
- 18.Goedel WC, Halkitis PN, Greene RE, Hickson DA, Duncan DT. HIV risk behaviors, perceptions, and testing and preexposure prophylaxis (PrEP) awareness/use in Grindr-using men who have sex with men in Atlanta, Georgia. J Assoc Nurses AIDS Care. 2016;27(2):133–142. doi: 10.1016/j.jana.2015.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
- 20.Ruff RR, Ng J, Jean-Louis G, Elbel B, Chaix B, Duncan DT. Neighborhood stigma and sleep: findings from a pilot study of low-income housing residents in New York City. Behav Med. doi: 10.1080/08964289.2016.1203754. [in press] [DOI] [PubMed] [Google Scholar]
- 21.Kant AK, Graubard BI. Association of self-reported sleep duration with eating behaviors of American adults: NHANES 2005–2010. Am J Clin Nutr. 2014;100(3):938–947. doi: 10.3945/ajcn.114.085191. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Arroll B, Goodyear-Smith F, Crengle S, Gunn J, Kerse N, Fishman T, et al. Validation of PHQ-2 and PHQ-9 to screen for major depression in the primary care population. Ann Fam Med. 2010;8(4):348–353. doi: 10.1370/afm.1139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Halkitis PN, Palamar JJ, Mukherjee PP. Poly-club-drug use among gay and bisexual men: a longitudinal analysis. Drug Alcohol Depend. 2007;89(2):153–160. doi: 10.1016/j.drugalcdep.2006.12.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Palamar JJ, Mukherjee PP, Halkitis PN. A longitudinal investigation of powder cocaine use among club-drug using gay and bisexual men. J Stud Alcohol Drugs. 2008;69(6):806–813. doi: 10.15288/jsad.2008.69.806. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Petersen MR, Deddens JA. A comparison of two methods for estimating prevalence ratios. BMC Med Res Methodol. 2008;8(1):9. doi: 10.1186/1471-2288-8-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Hilbe JM. Negative binomial regression. New York, NY: Cambridge University Press; 2011. [Google Scholar]
- 27.Zizi F, Jean-Louis G, Brown CD, Ogedegbe G, Boutin-Foster C, McFarlane SI. Sleep duration and the risk of diabetes mellitus: epidemiologic evidence and pathophysiologic insights. Curr Diab Rep. 2010;10(1):43–47. doi: 10.1007/s11892-009-0082-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Jean-Louis G, Williams NJ, Sarpong D, Pandey A, Youngstedt S, Zizi F, et al. Associations between inadequate sleep and obesity in the US adult population: analysis of the National Health Interview Survey (1977–2009) BMC Public Health. 2014;14(1):290. doi: 10.1186/1471-2458-14-290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kales A, Bixler EO, Tan T-L, Scharf MB, Kales JD. Chronic hypnotic-drug use: ineffectiveness, drug-withdrawal insomnia, and dependence. JAMA. 1974;227(5):513–517. [PubMed] [Google Scholar]
- 30.Nielsen K, Yarker J, Randall R, Munir F. The mediating effects of team and self-efficacy on the relationship between transformational leadership, and job satisfaction and psychological well-being in healthcare professionals: a cross-sectional questionnaire survey. Int J Nurs Stud. 2009;46(9):1236–1244. doi: 10.1016/j.ijnurstu.2009.03.001. [DOI] [PubMed] [Google Scholar]
- 31.Jean-LouisG, Kripke DF, Cole RJ, Assmus JD, Langer RD. Sleep detection with an accelerometer actigraph: comparisons with polysomnography. Physiol Behav. 2001;72(1):21–28. doi: 10.1016/s0031-9384(00)00355-3. [DOI] [PubMed] [Google Scholar]
- 32.Shiffman S. Ecological momentary assessment (EMA) in studies of substance use. Psychol Assess. 2009;21(4):486–497. doi: 10.1037/a0017074. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Johnson D, Lisabeth L, Lewis T, Sims M, Hickson D, Samdarshi T, et al. The contribution of psychosocial stressors to sleep among African Americans in the Jackson Heart Study. Sleep. 2016;39(7):1411–1419. doi: 10.5665/sleep.5974. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Cunningham TJ, Wheaton AG, Giles WH. The association between psychological distress and self-reported sleep duration in a population-based sample of women and men. Sleep Disord. 2015;2015:172064. doi: 10.1155/2015/172064. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Meyer IH. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychol Bull. 2003;129(5):674–697. doi: 10.1037/0033-2909.129.5.674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health. 2015;1(1):40–43. doi: 10.1016/j.sleh.2014.12.010. [DOI] [PubMed] [Google Scholar]
- 37.Su JY, Holt J, Payne R, Gates K, Ewing A, Ryder N. Effectiveness of using Grindr to increase syphilis testing among men who have sex with men in Darwin, Australia. Aust N Z J Public Health. 2015;39(3):293–294. doi: 10.1111/1753-6405.12342. [DOI] [PubMed] [Google Scholar]
- 38.Golder SA, Macy MW. Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science. 2011;333(6051):1878–1881. doi: 10.1126/science.1202775. [DOI] [PubMed] [Google Scholar]
- 39.O’Connell SE, Griffiths PL, Clemes SA. Seasonal variation in physical activity, sedentary behaviour and sleep in a sample of UK adults. Ann Hum Biol. 2014;41(1):1–8. doi: 10.3109/03014460.2013.827737. [DOI] [PubMed] [Google Scholar]
- 40.Grindr. Grindr Fact Sheet. 2015 [Available from:] http://www.grindr.com/press/