Mismatch of Biological and Social Time in Cocaine-Addicted Men

Intact circadian rhythmicity is a critical determinant of wellbeing and general health [1, 2]. It is well known that drugs of abuse, including alcohol, disrupt circadian rhythmicity, but the effects of cocaine remain unclear [3, 4]. Yet, this understanding could provide a novel avenue to mitigate the observed problems in mental and physical health among regular cocaine users [5‒7]. As a potent stimulant drug, cocaine acutely disrupts sleep and may cause a shift in functioning from morning to evening, resulting in a misalignment of circadian timing [8‒10]. This may recover during cocaine withdrawal, but chronic cocaine use is likely to induce a more profound dysregulation [8, 10]. Animal models further suggest that cocaine directly interacts with circadian clock genes, which are responsible for circadian timing of the body on a molecular level [11‒13]. Given cocaine’s strong neurochemical effects on the brain and the body, it is possible that variation in the usage pattern of the drug, including the quantity and time of use, may alter the alignment of users’ circadian clock, otherwise known as chronotype, but to the best of our knowledge, this has not yet been investigated.

Chronotype refers to the personal preference for falling asleep and waking up at specific times of the day [14], which affects an individual’s activity pattern throughout the day. Chronotype is thought to be influenced by the calibration of an individual’s circadian clock, and it can be measured by the timing of midsleep on non-working days [15]. Chronotype varies considerably throughout the population, with individuals with early behavioural patterns termed early chronotypes, or early larks, and those with later behavioural patterns being termed late chronotypes, or night owls. This has considerable clinical relevance as differences in chronotype, particularly later chronotype, across the population have been associated with adverse health outcomes [16‒18]. Importantly, an individual’s chronotype is not fixed but can be determined by intrinsic factors, such as age or genetic influences, and extrinsic factors (“Zeitgebers”), such as working patterns, light exposure [19], and possibly by drugs of abuse [3, 13, 20]. Variations in chronotype are associated with differences in the effects of drugs of abuse on mental health [21], possibly through changes in reward signalling [13, 22, 23]. This may also explain the altered wellbeing and increased behavioural problems observed in late chronotypes [24‒26]. Chronotype has mostly been investigated as a potential risk factor for drug use, e.g., cross-sectional studies have repeatedly shown associations between late chronotype and increased drug use [22, 27, 28], including increased stimulant drug use [29]. There have been speculations as to whether this relationship might be bidirectional [30, 31] and whether regular cocaine use might even induce changes in chronotype [4, 8, 32]. It is thus surprising how little is known about the chronotype of adults with cocaine use disorder (CUD), whose lives are dominated by the drug [33]. It is also of note that when a person’s biological time (i.e., chronotype) is not in line with their social time (i.e., working hours, social life, and light exposure), this may lead to disruptions, with implications for this person’s psychological functioning and wellbeing. This misalignment has been described by the term social jetlag [34], which has also been associated with increased drug use [31, 35, 36] and poor health outcomes [37‒39].

The present study aimed to shed light on variations in chronotype in patients with CUD and their possible clinical implications. We hypothesised that patients with CUD fall predominantly in the late chronotype category, have greater social jetlag and poorer health compared with their healthy peers, which is reflected by the severity of their cocaine use and the status of their mental and physical health.

As CUD is more prevalent in men than in women [40], we recruited 90 men from the local community using advertisements and word of mouth. There were forty-eight men who met the diagnostic criteria for moderate-to-severe CUD, as ascertained by the Diagnostic and Statistical Manual of Mental Disorders, Version 5 [33], and forty-two healthy men with no personal history of substance use disorder. All participants had to be at least 18 years of age and able to read and write in English. Exclusion criteria included a lifetime history of a psychotic disorder, neurological illness, or a traumatic head injury. All participants were psychiatrically screened using the Mini-International Neuropsychiatric Inventory [41] and provided urine samples, which were screened for undeclared drugs. All samples provided by CUD patients tested positive for cocaine (suggesting that they had used the drug in the past 72 hours), and all samples provided by control participants tested negative. All 90 participants completed the Munich Chronotype Questionnaire (MCTQ) to measure chronotype. As sleep duration is influenced by the use of an alarm clock (even on work-free days), chronotype can only be assessed in participants, who do not use an alarm clock [42]. Consequently, data from 16 participants had to be excluded from the analysis, leaving the final sample at 74 participants (42 CUD patients and 32 controls). The demographics of participants whose data had to be excluded did not significantly differ from the remainder sample. All the questionnaires were administered by oral interview, with verbal responses from the participant being recorded, collecting information regarding chronotype, mental health, and drug use. All participants provided informed consent prior to study participation, and the study protocol was approved by the Cambridge Research Ethics Committee [PRE.2018.062]. Unrelated data of the sample have been published elsewhere [43‒45].

The present sample was representative of the national average in ethnicity, with most participants being of Caucasian origin in both groups (75% CUD, 85% controls). CUD patients reported starting using cocaine during early adulthood (mean age of onset: 21 years (±5.8 standard deviation [SD]) and have been using regularly for an average of 13 years (±7.7 SD). Most CUD patients (86%) reported using cocaine daily, mainly intranasally or by inhalation, but 60% of users also reported having used cocaine intravenously at least once in their lives. They further indicated on the Obsessive-Compulsive Drug Use Scale (OCDUS) [46] moderate-to-high levels of cocaine-related compulsivity (mean: 35.4 [±9.5 SD], range: [18–52]). As shown in Figure 1, half of the CUD patients reported not to have a preferred time of using the drug (50%), while 29% reported preferably using cocaine in the evening, 17% in the afternoon, and 5% in the morning. All CUD patients were tobacco smokers, and the majority also met the diagnostic criteria for another substance (52% opiates, 18% cannabis, 7% alcohol). Participants with comorbid opiate use disorder were either prescribed methadone (n = 14) or buprenorphine (n = 6). Some CUD patients reported taking prescribed medication, including antidepressants (7%), painkillers (8%), benzodiazepines (4%), or antibiotics (2%). Healthy control participants were also screened for drug and alcohol use, but none of them met lifetime criteria for substance use disorders. About a quarter of control participants (26%) were either past or current tobacco smokers, and more than half of them (57%) reported having used cannabis at least once in their lives but never on a regular basis.

Chronotype and social jetlag: we used the Munich Chronotype Questionnaire (MCTQ) to assess individual variation in chronotype – a widely used tool that has been cross-validated against other chronotype measures [15, 47]. The MCTQ is a 19-item instrument that considers timing of sleep patterns on both weekdays (i.e. work days or days with appointments) and work free days (i.e. weekends or holidays). Midsleep on free days (MSF) is the measure used as an indicator of chronotype. Given that sleep debt from weekdays is compensated for by increased sleep duration, sleep recovery on work free days, sleep-corrected MSF (MSF_sc) was calculated using the formula: MSF_sc = MSF −(SD_f −SD_week)/2 [48]. Social jetlag was calculated from the difference between midsleep on weekdays and work free days. We divided the sample into three chronotype categories based on individual variation of MSF_sc: early, intermediate, and late. Tertile splits were applied to the whole sample to generate these categories, as used in the literature [49, 50], but we acknowledge that there are also other ways of categorising chronotype that are based on quartiles and percentiles, respectively [51, 52]. Information on sleep duration was gathered from the MCTQ. Additional questions about participants’ chronotype during childhood and the chronotypes of their spouses and first-degree relatives were also collected in the structured interview [15].

General and mental health: all participants were asked to rate their general health status on a 5-point Likert scale (0 = poor, 4 = excellent) and completed the Depression, Anxiety and Stress Scale (DASS-21) to assess current symptoms of depression, anxiety, and stress [53]. The DASS-21 total score was used as an indicator for participants’ current mental health status. Participants also completed the Daily Fatigue Impact Scale [54] to evaluate their subjective daily experience of fatigue.

Cocaine use: we used several indicators to assess CUD patients’ history of cocaine use, including the age at which they started using cocaine, the duration of regular use, the frequency of use, and their preferred time of day when they use cocaine. We also administered the Obsessive-Compulsive Drug Use Scale (OCDUS) to assess how much cocaine consumption interfered with CUD patients’ social life as well as their resistance and drive to use cocaine [46]. As compulsive patterns of drug use are a hallmark of drug addiction, we used the OCDUS score as an indicator of addiction severity.

Statistical analyses were conducted using the IBM Statistical Package for the Social Sciences (SPSS) version 27. If appropriate, data were square root transformed in preparation for parametric analysis, but untransformed values are shown in the figures and tables. All tests were two-tailed, and an effect was deemed significant at p < 0.05. We first investigated group differences in demographics and chronotype using independent t tests and Fisher’s exact tests. To investigate group differences in health-related variables, we used analyses of variance with group (two levels: control, CUD) and chronotype (three levels: early, intermediate, late) as between-subject factors. A linear regression model was used to investigate the influence of CUD and comorbid substance use disorder, employment status, and light exposure on social jetlag. Substance dependency status was entered as four separate dichotomous variables (D1: not cocaine-dependent, cocaine-dependent; D2: not opiate-dependent, opiate-dependent; D3: not cannabis-dependent, cannabis-dependent; D4: not alcohol-dependent, alcohol-dependent). χ² or Fisher’s exact tests were used for the analysis of categorical data.

As shown in Table 1, the two diagnostic groups were well-matched for age (t_52.8 = −0.64, p = 0.507), biological sex (100% male), sexual orientation (Fisher’s exact p = 0.116), handedness (Fisher’s exact p = 0.862), and ethnicity (Fisher’s exact p = 0.193). CUD patients, however, had spent less time in formal education (t_51.8 = 9.57, p < 0.001), were less likely to be in employment at the time of the study (χ² = 16.53, p < 0.001), and had a lower disposable monthly income compared with their healthy peers (t₇₂ = 3.35, p = 0.001). As shown in Figure 1a, chronotype distribution differed significantly between the groups (Fisher’s exact p = 0.001) such that late chronotype was predominant in the CUD group, whereas the control group was predominated by the early chronotype. Significantly more CUD patients (38%) compared with control participants (10%) reported a change to later chronotype from childhood to adulthood (Fisher’s exact p = 0.019), see also Figure 1b, c, 2. Although both groups reported sleeping on average 8 h per night during the week (t₇₂ = 0.12, p = 0.906), they did differ significantly on their weekly light exposure (t_52.9 = −2.28, p = 0.027), as CUD patients reported on average 3.2 h more light exposure compared with control participants. Circadian disruption is also reflected by social jetlag, which was significantly increased in CUD patients (Mann-Whitney U = 562.5, p < 0.001). Linear regression revealed that employment status accounted for 11% of the variance of social jetlag (R² = 0.11, F_1,72 = 8.94, p = 0.004). Interestingly, alcohol, cannabis, opiate, and cocaine consumption did not account for any of the variance of social jetlag (all p > 0.05). Social jetlag was not associated with any health-related variables in either group (all p > 0.05).

Self-reported mental health status (F_1,68 = 72.23, p < 0.001), daily fatigue (F_1,68 = 15.71, p < 0.001), and general health (F_1,67 = 41.31, p < 0.001) were significantly different between diagnostic groups but not between chronotypes (all p > 0.05). No group-by-chronotype interactions were identified (all p > 0.05). Experienced daily fatigue was not associated with the average sleep duration either in CUD patients (r = −0.002, p = 0.988) or in control participants (r = −0.005, p = 0.979).

Late chronotypes tended to initiate cocaine use at a younger age (mean: 18 years [±3.1 SD]) compared with early (mean: 21 years [±5.5 SD]) or intermediate chronotypes (mean: 23 years [±7.7 SD]) (F_2,37 = 3.0, p = 0.062); a finding that was not seen for the age of initiation of tobacco (F_2,37 = 0.01, p = 0.987), cannabis (F_2,37 = 0.37, p = 0.693), or alcohol use (F_2,37 = 0.08, p = 0.928). Furthermore, we did not find any differences across chronotypes with respect to the duration of cocaine use (F_2,39 = 0.89, p = 0.419), the pattern of cocaine-related compulsivity (as measured by the OCDUS score [F_2,39 = 0.90, p = 0.415]), or the time of day when cocaine is typically used (Fisher’s exact p = 0.821).

The present study supports prior observations in substance-using populations of an increased prevalence of late chronotype. Additionally, we found that more CUD patients than healthy control participants reported a change to later chronotype from childhood to adulthood. However, contrary to widely held beliefs, we could not find evidence for relationships between chronotype and addiction severity, mental health, or wellbeing in patients with CUD. Although there was a trend that CUD patients who started using cocaine at an earlier age were more likely to be of late chronotype – and this trend was not seen for the initiation of drugs such as tobacco, alcohol, or cannabis – severity of cocaine use did not differ across the three chronotypes. Self-reported mental and physical health in our participants was also evenly distributed across chronotypes. In fact, our data suggest that changes in health-related variables were associated with diagnostic group rather than with chronotype. We did, however, find evidence for circadian disruption in terms of greater social jetlag in CUD patients, as reflected by a mismatch between their biological and social time (see Fig. 2). Interestingly, this mismatch was not influenced by drug and alcohol use but, in part, by employment status (i.e., most CUD patients were not in employment).

As shown in Figure 1a, late chronotype was more prevalent in patients with CUD, as a larger proportion of CUD patients than control participants reported shifting to a later chronotype from childhood to adulthood. These findings are clinically relevant, given the plethora of additional ailments that have been associated with late chronotype, ranging from decreased subjective wellbeing to increased all-cause mortality [16, 24, 55]. Although our study does not completely explain this relationship, there are two possible scenarios: (i) cocaine use facilitates the change to late chronotype, or (ii) the change in chronotype represents a risk factor for an increase in cocaine use. Our findings that patients who were of late chronotype showing a trend to initiate cocaine, but not other drugs of abuse, at a younger age, are interesting and invite speculations as to whether cocaine use during adolescence might influence the individual’s chronotype. A possible mechanism for this might lie in cocaine’s neuromodulatory effects. Prior work points towards dysregulated circadian clock gene expression and thus dopamine and melatonin signalling following chronic drug use [3, 56, 57] – systems that are known to be influenced by cocaine [8, 58, 59]. Chronotype is likely to vary throughout lifetime, especially during the period of development (i.e., changes from early to late chronotype in the period from childhood to late adolescence), whereas during adulthood, chronotype has generally been considered to remain stable [57]. This pattern was reflected in our control sample, who showed stable pattern of chronotype, whereas the increase in self-reported late shifts from childhood to adulthood in CUD patients might be due to extrinsic influencing factors on chronotype (i.e., cocaine) that may have induced the aforementioned mechanisms [3, 8, 59]. It is of note that late chronotype (or eveningness) has also been associated with a number of other risk factors for drug use such as risk-taking behaviour and conduct problems in adolescents [25, 60, 61] and poor sleep quality [62, 63]. Indeed, chronotype and substance use may also interact with one another [23, 31, 64] and may further exacerbate the maladaptive behaviour frequently seen in CUD patients.

Interestingly, CUD patients in our study report a similar sleep duration as their healthy peers. This may seem surprising because chronic cocaine use is known to reduce total sleep time and sleep quality [4, 8, 10]. However, many CUD participants in this study were unemployed; the freedom afforded by this may allow for compensatory additional sleep time to meet the adequate daily sleep duration. Interestingly, despite a similar duration of sleep as their healthy peers, CUD reports higher levels of daily fatigue. This may suggest that either their sleep quality is poor or that another mechanism, other than sleep, may cause their high levels of fatigue, for example, chronic inflammation [65]. Unfortunately, our study design did not include objective sleep data, information about sleep quality, or inflammation; further research is therefore warranted.

Contrary to prior studies suggesting the presence of a direct relationship between chronotype and drug use severity [22, 23, 66], our findings do not support this assertion. It is, however, of note that there are differences in sample composition and assessment methods. Prior work often included psychiatric outpatients or investigated those that consumed a wide range of substances and rarely included cocaine consumption [22, 66, 67], yet the present study particularly focussed on community-dwelling men whose primary drug of dependence was cocaine. We also used the MCTQ, which collects more information than other chronotype measures such as the Morningness-Eveningness Questionnaire [68] or the Composite Scale of Morningness [69]. For example, the MCTQ provides information such as midpoint sleep, sleep onset/duration/loss for weekdays and weekends, as well as light exposure (see Table 2), which allows to calculate the mismatch between biological and social time. As shown in Figure 2, patients with CUD are, to a much greater degree, affected by this mismatch than their healthy peers. Although tobacco and alcohol have also been shown to contribute to social jetlag [48], neither these drugs nor cocaine were responsible for any variance in the present study, whereas employment status did. Given that most of our CUD patients were unemployed, it is tempting to speculate whether employment may, besides other benefits, also provide a temporal anchor for CUD patients to improve their circadian rhythm. Although further research is still warranted, the beneficial effects of employment for the circadian rhythm of CUD patients highlight the need for the reintegration of addicted patients into wider society. It is likely that the beneficial effects of employment may also improve drug users’ poorer health more generally.

The present study has several strengths, including use of the MCTQ for the assessment of chronotype, in-person assessments (rather than anonymous assessments online), and detailed information about participants' patterns of cocaine use (e.g., preferred time of cocaine use). Yet there are also limitations to be considered. Firstly, as in most studies, the present study has a cross-sectional design, which is suitable to identify relationships but does not allow inferences on causality or directionality. Consequently, the shift from early to late chronotype, as reported by a higher number of CUD patients than control participants, requires further verification from a longitudinal design. Secondly, we did not measure sleep quality, which has been suggested to be influenced by unemployment [70] and has even been shown to impact on the likelihood of drug use, including the use of cocaine [43, 44]. Finally, employment status may influence people’s lives in many ways, psychologically and socially. Patients with CUD are more often affected by unemployment compared with their healthy peers [71], and this was also reflected in the present study.

The present study provides new insight into variations in chronotype in patients with CUD, which has received growing interest in recent years in the field of addiction. Although the influence of drugs of abuse on circadian rhythmicity is undisputed, the implications on drug-addicted patients’ poor health and wellbeing are still elusive. Our findings challenge the prevailing view that the predominantly late chronotype in addicted patients is associated with addiction severity – a finding not supported by our data, but we acknowledge that more research is needed. The study also draws attention to the significant increase in social jetlag in CUD patients, as reflected by two different sleeping patterns on weekdays and weekends (as shown in Fig. 2), which affects their health and wellbeing, and may therefore present a target for treatment.

The authors thank all participants for their contribution to this study and Dr. Tsen Vei Lim, Eva Groot, Ibtisam Abdi, and Dr. Roderick Lumsden for their assistance with data collection, quality control, and data management.

The study protocol was reviewed and approved by the Cambridge Research Ethics Committee (PRE2018.062). All participants provided written informed consent prior to study participation.

K.D.E. is the recipient of an Alexander von Humboldt Fellowship for senior researchers (GBR 1202805 HFST-E) and receives editorial honoraria from Karger. Both authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The study was funded by the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014) and NIHR Applied Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

K.D.E. is responsible for the concept, the funding and the design of the study, data acquisition, and data integrity. J.F. wrote the first draft of the manuscript. Both authors had full access to the data, took responsibility for the accuracy of the data analysis, and contributed equally to the interpretation of the data and the writing up.

All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.