Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2021 Jun 1.
Published in final edited form as: Diabetes Educ. 2020 May 8;46(3):242–251. doi: 10.1177/0145721720916179

Facilitators and Barriers of Sleep in Young Adults with Type 1 Diabetes

Stephanie Griggs 1, Robin Whittemore 2, Nancy S Redeker 3, Margaret Grey 4
PMCID: PMC7329586  NIHMSID: NIHMS1592598  PMID: 32383625

Abstract

Purpose:

The purpose of this study was to explore the perceived facilitators and barriers for obtaining sufficient sleep in young adults with T1D.

Methods:

A qualitative descriptive approach was used to generate data. In-depth semi-structured interviews with 30 young adults with T1D (66.7% female, mean age 22.1 years) were conducted. Interviews were transcribed verbatim and coded using NVivo™.

Results:

Young adults with T1D reported feeling challenged at bedtime and overnight by the demands of a complex disease management regimen. General and diabetes-specific barriers and facilitators to obtaining sufficient sleep were the over-arching themes in the present study. Young adults perceived that electronic device use was a facilitator for relaxation before bed and a barrier to sleep by some participants. Delays in bedtime or disruptions in sleep were common diabetes-specific barriers.

Conclusions:

When designing sleep-promoting interventions for young adults with T1D, researchers should consider diabetes-specific challenges and solutions in addition to those present in the general young adult population.

Keywords: Type 1 diabetes, sleep, young adults, barriers, facilitators

Type 1 diabetes (T1D) is one of the most common chronic conditions in young adulthood, and adults represent 85% of the total T1D population.1,2 Young adulthood is a critical period in which individuals must assume responsibility for their diabetes self-management while moving out of their parent’s home to attend college or enter the workforce.1 Only 14% to 30% of young adults ages 18–30 meet glycemic targets (< 7% HbA1c or < 53 mmol/mol).3 Up to 50% of young adults develop diabetes-related complications in their 20’s (e.g., retinopathy, neuropathy, and hypertension).4,5

Sleep deficiency, defined as less than 6.5 hours total sleep time and variability in total sleep time, is common in young adults ages 18–30 with T1D, associated with poorer glycemic control,6,7 and is a barrier to physical activity8 and self-management.9 Conditions that accompany T1D, such as hypoglycemia, hyperglycemia, and glucose variability, often disrupt nocturnal sleep.6,10 In one study, over half of adults ages 18–89 with T1D (n =145) woke at least once overnight to manage their diabetes.10

Both children11 and young adults12 with T1D exhibit more awakenings overnight compared to matched controls. Osmotic diuresis associated with hyperglycemia may disrupt sleep due to nocturia.13 Hyperglycemia is also associated with difficulty initiating sleep (longer sleep onset latency) and more sleep disruption (higher awakenings index).6 In a pilot study of 23 young adults with T1D, glucose fluctuations were associated with multiple awakenings during sleep over a 60-hour period of monitoring via polysomnography (PSG).14

Hypoglycemic events among young and middle-aged adults with T1D are associated with reduced rapid eye movement or light sleep,15 impaired declarative memory,16,17 poorer general alertness and motor speed,16 and electroencephalography changes18 compared to people without diabetes. Fear of hypoglycemia is associated with poorer self-reported sleep quality.19,20 Young adults with T1D also have poorer objective sleep quality (e.g., poorer sleep efficiency, less time in deep stage N3 sleep), more variability in total sleep time, report sleep that is less restorative,12,21 and have an impaired awakening response to hypoglycemia compared to matched controls.22,23 Failure to awaken from sleep increases the risk of prolonged and potentially fatal hypoglycemia.24

There are limited qualitative studies on perceived barriers and facilitators of sleep in adolescents and young adults without chronic conditions.25–28 Feeling stressed, watching television,26 being unable to fall asleep,27 homework,25,26 and socializing with friends26,27 were reported to be perceived barriers of sufficient sleep, total sleep time between 7–9 hours, in adolescents without chronic conditions. Barriers to modifying sleep behavior were time demands, technology use, difficulty switching off their brains, and unpredictable habits, and enablers to modifying sleep behavior reported were advancing bedtimes and minimizing phone use in one study of adolescents and young adults without chronic conditions.28

The perceived barriers to sufficient sleep among adolescents with T1D (n = 25) were sleep disturbances related to diabetes management, use of electronics, homework, and neighborhood noise.29 In the same study, caregivers identified enforcing bedtimes and limiting distractions as facilitators of sleep, while adolescents identified the use of electronics as the most common facilitator to fall asleep more quickly; however, 50% of the adolescents in the study could not identify a facilitator.29 Both fear of hypoglycemia and device alarms were identified as a cause of waking during the night in young adults with T1D in one study10 and in parents of 549 younger children (Mean age 5.2) with T1D in another study.30 In a mixed-methods study where free text responses were analyzed from adults with T1D (18–89 years), only causes of waking were identified, not other barriers or facilitators.10 Therefore, it is important to gain a better understanding of the modifiable factors contributing to sleep deficiency in young adults with T1D to design appropriate sleep improvement interventions. Thus, the purpose of this study was to explore the perceived facilitators and barriers for obtaining sufficient sleep in young adults with T1D.

Methods

Design

A qualitative descriptive approach31 was used to explore the perceived barriers and facilitators of sleep among young adults ages 18–30 with T1D. A goal of a qualitative description is to allow researchers to stay close to the data and to events.

Sample and setting

Young adults with T1D were recruited from the Yale-New Haven Health System who were: (1) between the ages of 18–30 years; (2) diagnosed with T1D for at least 6 months; (3) with no other major health problems (e.g., chronic medical conditions or major psychiatric illness); (4) not participating in any intervention studies; (4) currently had a CGM or were willing to wear a CGM; and (5) read/spoke English. Those with a previous Obstructive Sleep Apnea (OSA) diagnosis, night shift workers, and those who were pregnant were excluded. The age range was chosen as it captures a key developmental stage when young adults are transitioning into either college or their careers. Young adults who had been diagnosed with diabetes for less than 6 months were excluded to avoid the confounding effects of the initial adjustment period after diagnosis.

The Berlin Questionnaire BQ (Cronbach’s α = 0.86–0.92),32 a 9-item scale, was used to identify patients at high risk for sleep apnea (e.g., OSA). The BQ items address the presence and frequency of snoring, wake time sleepiness or fatigue, and history of obesity or hypertension.32 Participants with persistent and frequent symptoms in any two of these three domains are considered to be at high risk for sleep apnea.32 Participants were referred for treatment and not included in the study if they scored at high risk for OSA.

Variables and measures

Demographic and clinical characteristics.

A questionnaire and the Electronic Medical Record (EMR) were used to collect clinical and demographic data. The following data were extracted from the EMR: age, body mass index (BMI, kg/m2), duration of diabetes, most recent A1C, and medical history (diabetes, sleep, other comorbidities, last menstrual period for females). The following data were collected by self-report survey: ethnicity, education, insulin therapy regimen (e.g., insulin injections or pump), CGM pump brand (if applicable), last menstrual period for females, and sleep duration from the Pittsburgh Sleep Quality Index.33 Participants were asked: During the past month, how many hours of actual sleep did you get at night? (this may be different than the number of hours you spent in bed) for the sleep duration item from the Pittsburgh Sleep Quality Index.33

Procedures

Approval was obtained from the University Institutional Review Board. Informed consent, demographic data, A1C levels, and self-reported sleep quality data were obtained at time of recruitment. Participants received a $40 gift card for the interview.

A total of 134 were invited to participate. Of these, 47 responded with interest and were screened over the phone, four additional people were excluded with two screening high risk for sleep apnea, and the other two self-identifying as in early pregnancy. Those who declined to participate did so due to the time commitment of the study, a lack of interest, or refusal/inability to wear a CGM.

Data collection procedures

The data for this study were drawn from exit interviews and surveys from a multi-method descriptive study designed to characterize sleep (actigraphy and questionnaires), neurocognitive function, and glycemia (A1C and continuous glucose monitoring [CGM]). An in-depth, semi-structured telephone interview consisting of the following open-ended questions and probes was used for this analysis: Describe your bedtime routine; What helps you get a good night’s sleep?; Can you think back to a night where you had a good night’s sleep?; What were some things that helped you sleep well?; What prevents you from getting a good night’s sleep? Can you think back to a night where you didn’t sleep well? What were some things that prevented you from sleeping well?

Data management and analysis

Demographic data were analyzed using SPSS version 26 for Mac. Interviews were audio-recorded and transcribed verbatim. All transcripts were organized and coded with NVivo 12 for Mac.34 An audit trail was used to track decision-making and triangulate the data. Interview data were analyzed and coded for themes using qualitative content analysis.35 The analysis was inductive and began during the data collection process to allow for ongoing modification of the interview guide. Interviews were coded using an in vivo approach.36 Sampling continued until data redundancy was reached.

Transcripts were first read in their entirety to get a sense of the whole. Meaning units were identified and condensed. The condensed meaning units were then abstracted based on codes that emerged from the data. Two authors (SG, RW) used a conceptual coding method to develop the final coding structure by synthesizing and collapsing the preliminary 113 in vivo codes until consensus was reached.37 The final coding structure included 52 codes that were mutually exclusive. Codes were then collapsed into categories, and categories were collapsed into themes and subthemes. Conceptual mapping, field notes, and memos were used to help refine the themes and subthemes. Participant profiles were used to connect themes with interviews once the themes were finalized.38

Criteria for determining validity in qualitative research described by Whittemore, Chase, and Mandle (2001) were used.39 As depicted in Table 1, the four main strategies of trustworthiness were used throughout the systematic process: credibility, transferability, dependability, and confirmability.40

Table 1.

Lincoln & Guba (1985) Framework for Trustworthiness of Data

Criterion Specific Strategy Used
Credibility (internal validity) Data collected with both interviews and audio-recording. Demographic and clinical data collected via interview, survey, and chart review.
Confirmation of findings done with member checking throughout interview.
Dependability (reliability) Field notes, audio-recordings were transcribed verbatim.
Transferability (external validity) Thick description of methods and findings reported to 2nd researcher.
Effort made to recruit participants from varied backgrounds (age, gender, and ethnicity).
Confirmability (objectivity) Audit trail, memos, conceptual mapping.
Open in a new tab

Results

The participant demographic and clinical characteristics are presented in Table 2. The three participants who did not identify as white identified as Asian (n = 1, 3.3%), Native Hawaiian (n = 1, 3.3%), and Hispanic (n = 1, 3.3%). Self-reported sleep duration ranged from 5 to 10 hours with a mean of 7.4 ± 1.2 hours. The mean A1C was 7.0 ± 1.2% (53 mmol/mol), which is slightly lower than the T1D Exchange cohort currently using CGM technology (A1C 7.4 ± 1.0 – 8.3 ± 1.5 % or 57 – 67 mmol-mol).3

Table 2.

Sample characteristics (N = 30)

Demographic Characteristics Mean ± SD or N (%)
Age (years) 22.1 ± 3.1
Gender
 Female 20 (66.7)
 Male 10 (33.3)
BMI kg/m2 26.8 ± 4.7
Race/ethnicity
 White, Non-Hispanic 27 (90.0)
 Non-White 3 (10.0)
Able to meet monthly expenses (% yes) 29 (96.7)
College student (% yes) 15 (50.0)
Type 1 Diabetes Profile
T1D duration (years) 11.6 ± 6.0
A1C (%) 7.0 ± 1.1
Insulin Pump (% yes) 24 (80.0)
Continuous Glucose Monitor (% yes) 26 (86.6)
Open in a new tab

Note:The Systéme International d’Unités (SI units) conversion for 7% HbA1C is 53 mmol/mol

Two overarching themes related to sleep in the young adults with T1D were identified in the current study: general and diabetes-specific barriers and general and diabetes-specific facilitators to obtaining sufficient sleep. The themes, subthemes, and sample quotes are presented in Table 3.

Table 3.

Themes and Subthemes of Facilitators and Barriers with Sample Quotes

Type Theme Subtheme Sample Quote/s (participant #, age)
Barriers General barriers of sufficient sleep Stress or anxiety
…if there is a night that I can’t fall asleep it’s usually because I’m really anxious about something, like maybe something that happened that day, or maybe I have to do something important the next day and maybe I’m trying to run down what I have to do that day and it keeps me up for a while and I can’t just fall asleep because I have to get up and do this and that. Usually just being anxious about pleasing the teacher or something that happened in the past
(Participant 14, age 19).
Uncomfortable sleep environment
…when there’s…noises happening, if there is any kind of light… flashing, or just presently in the room…if I’m…too hot or too cold
(Participant 4, age 21).
Sleep hygiene practices
…watching Netflix too much before bed…losing track of time. But I guess…taking naps during the day and feeling not tired
(Participant 15, age 20).
Diabetes specific delays in bedtime Manage hyper or hypo glycemia
I think sometimes my blood sugar - I really don’t like going to bed with it either trending up or trending down, so I’ll often stay up just to make sure and manage that it’s ok
(Participant 5, age 28).
Fear of hypoglycemia
… I don’t love going to bed high after giving myself insulin because sometimes I drop then I wake up low and I don’t love that
(participant 10, age 19).
Diabetes specific sleep disruptions Hyper/hypoglycemia
I know when my blood sugar is high or my blood sugar is low I wake up throughout the night. Also, if my blood sugar is high I have to go to the bathroom which makes me actually get up.
(Participant 16, age 22).
Equipment alarms
So not timing my eating right, so my blood sugar is out of range and then more likely to alarm
(Participant 13, age 19).
Facilitators General facilitators Regular relaxing bedtime routine
I try to…relax before bed. So I put my pajamas on, I wash my face, brush my teeth, brush my hair, and then I hop into bed and I’ll probably go on my phone between..45 minutes or between 30 and 45 minutes and just like scroll through…Netflix videos or YouTube videos…that’s why I go on my phone to just relax and do whatever and not really think about what’s going on this day or what I have to do tomorrow
(Participant 14, age 19).
.…if I actively try to fall asleep, like doing a little bit of meditation and relaxing my muscles, helps me keep my eyes closed and from there it’s easier to fall asleep
(Participant 3, age 23).
Comfortable sleep environment
…being comfortable. Like, I wake up like, sometimes when I wake up its because I’m too hot or something, so just being like a comfortable temperature, you know there’s not any kind of light flashing…So you know, and like quiet. I can’t fall asleep to, you know, TV or music. I need dark and quiet and, you know, a good temperature
(Participant 4, age 21).
Physical activity
Having busy days…always doing things, going to the gym, always moving, studying, class, tiring me out
(Participant 1, age 21).
Being tired
If I’m really tired from another night I can usually get to sleep pretty easily.
(Participant 10, age 19).
Diabetes specific facilitators Euglycemia
Eating a good dinner, making sure I’m full, making sure my blood sugar is in range before I go to bed
(Participant 2, age 22).
…because the better my blood sugar is, the better I sleep
(Participant 7, age 24).
Managing diabetes equipment
Making sure my Dexcom is calibrated for the next 12 hours
(Participant 7, age 24)
Probably like 5 or 10 minutes before I decide ok it’s time to go to bed, I lower my basal rate to my night-time basal
(Participant 12, age 22).
Open in a new tab

Barriers to Obtaining Sufficient Sleep

General Barriers.

Young adults described a variety of general barriers to obtaining sufficient sleep. The most common barriers were related to their sleep hygiene practices (60%), stress or anxiety (30%), or an uncomfortable sleep environment (26.7%). Less common barriers were related to physical symptoms from having a respiratory illness (3.3%) or pain in the leg from swimming (3.3%).

A majority of participants described screen use (53.3%) either from watching TV on their phone or a TV as part of their bedtime routine. For some participants, technology was a barrier to sleep as “watching too much TV, being on their phone too long, getting into a TV show, or getting into a story” delayed their bedtime (13.3%). One participant specified that “more than 30–45 minutes” on their phone was too long (Participant 14, age 19). Less common barriers related to sleep hygiene practices included: caffeine use (10%), having a full stomach/heavy meal (6.7%), naps (6.7%), going to bed before being tired or having energy (6.7%), having variability in bedtime (3.3%), a late bedtime/early waketime (3.3%), having less sleep the prior night (3.3%), or staying up too late (3.3%).

Several participants reported that feeling stressed, anxious, or emotional from something that happened that day or in the past or worrying about what they had to do the following day kept them awake and that is was difficult to “shut [their] brain down”.

An uncomfortable sleep environment was described as the temperature being too cold or too hot or when there was noise, light or sunlight coming into the room. One participant mentioned that lack of comfort was a barrier but could not pinpoint whether this lack of comfort was related to the temperature or the bed itself (Participant 24, age 19).

Diabetes-Specific Bedtime Delays or Disruptions in Sleep.

All participants reported that diabetes affected their sleep and included the need to delay their bedtime to manage their diabetes (60%) sometimes related to a fear of hypoglycemia (13.3%), being awoken from hyper or hypoglycemia (66.7%), and being awoken by sensor/pump alarms (20%) with some noting that the alarms were sometimes false (6.7%). Participants delayed their bedtimes to manage either hyper or hypoglycemia or to set up equipment for the night (e.g., treat with insulin, replace an expired sensor, lower an insulin pump rate to a nighttime basal rate, check settings on pumps, etc.). For example, one participant stated, “if I have like high blood sugar, I feel like it normally takes me longer to go to bed” (Participant 29, age 23). Several brought up the need to see how their blood sugar would react to treatment before they were able to go to bed. To illustrate, one participant stated: “If I start with a high blood sugar before I go to bed – high blood sugar takes a lot longer to correct than low blood sugar – I mean I don’t see an effect for a half hour after I bolus, so there’s a half hour after I’m stuck waiting and just not feeling well” (Participant 3, age 23).

One trend that emerged, though not always explicitly stated, was a fear of hypoglycemia. One participant stated: “And then, I think there might be somewhat of an innate worry that it won’t go down, or it will drop too far, so I think having a high blood sugar beforehand kind of hurts” (Participant 3, age 23). Others reported an implied fear of hypoglycemia with mention of it being better to be “trending high” than “trending low” or that they would either “eat a snack” despite being in range or stay a little on the “high” side to prevent lows overnight.

Sleep disruptions were caused by high (66.7%) or low blood glucose (63.3%) or both (53.3%). One participant reported: “Good glucose control. If it’s high, I tend to be restless, or if it’s low I have to get up.” (Participant 20, age 27). Another reported: “I think when my sugar is out of whack, like out of control, it really affects me because I notice that if I’m up all night with a low blood sugar or high blood sugar I’m really tired the whole next day, so that’s definitely one thing that affects my sleep” (Participant 9, age 24).

The sensor or pump was another source of sleep disruption for some participants with one describing flashing lights from an expired sensor and several describing high or low glucose alarms. One participant noted: “I had to change my sensor last night. It expired very late at night. So, I had to change it, and it was flashing, so I put it under a towel so I wouldn’t have to keep seeing it” (Participant 4, age 21).

Facilitators to Obtaining Sufficient Sleep

General Facilitators of Sufficient Sleep.

Young adults offered multiple facilitators and strategies for obtaining sufficient sleep. While participants provided responses unique to their situations, similar strategies were used including having a regular relaxing bedtime routine (73.3%), physical activity during the day (30%), a comfortable sleep environment (quiet, dark, warm, and cozy) (26.7%), and being tired (23.3%). Less common facilitators were related to dietary practices such as avoiding caffeine (3.3%), staying well hydrated (3.3%), or drinking alcohol (3.3%).

Most young adults used some form of distraction (66.7%) most commonly from electronics (TV or phone) (46.7%) or reading (20%) as part of their bedtime routine to help them relax and to fall asleep more quickly. One participant shared:

“I try to like relax before bed. That’s why I go on my phone to just relax and do whatever and not really think about what’s going on this day or what I have to do tomorrow because if I’m really anxious before I fall asleep it takes me a few hours to fall asleep so, definitely like relax and not think about anything.”

(Participant 14, age 19).

Other aspects related to a regular relaxing bedtime routine were some form of meditation or light exercise (20%), feeling accomplished/next day planning (13.3%), having time between dinner and bedtime (10%), an early bedtime (6.7%), or a shower at night (3.3%).

Diabetes-Specific Facilitators of Sufficient Sleep.

Maintaining blood glucose within range as close to bedtime as possible was the most common facilitator of sleep (43.3%). One participant stated: “making sure my blood sugar is in range before I go to bed” (Participant 2, age 22). Strategies to maintain blood glucose in range included having a snack or light meal (13.3%), not eating two hours before bedtime (3.3%), or eating closer to bedtime (3.3%). One example offered by a participant was: “Depending on what my blood-sugar is at that point if I’m already on the lower side I’ll eat a snack then. If I’m not I will stretch. But you know my blood-sugar dictates whether I stretch first and then eat a snack or whether I eat a snack and then stretch” (Participant 12, age 22). Another offered: “Not eating 2 hours before bed. You see if I don’t eat my blood sugar is more stable and I’m not needing to correct before bed” (Participant 13, age 19). Another diabetes-specific facilitator was managing diabetes equipment (10%), either by ensuring the sensor for a CGM was not expired or calibrated for the night or that the basal rate was lowered for an insulin pump.

Discussion

Sleep habits are an important factor for improving diabetes outcomes, given the accumulating evidence that sleep deficiency is a risk factor for difficulty with diabetes management and meeting glycemic targets in young adults with T1D.6,7 In the current study, the perceived barriers and facilitators of sleep in young adults with T1D varied in important ways from the general population.26–28 Of note, the young adults with T1D in the current study needed to manage general barriers (e.g., stress or anxiety and uncomfortable environment) and promote facilitators (e.g., regular relaxing bedtime) in addition to barriers and facilitators specific to their diabetes. Specifically, they were challenged with managing glycemia at bedtime and overnight and having glucose fluctuations or associated alarms disrupt their sleep. The findings of the current study support the reasons that young adults with T1D have more sleep deficiency than the general population.

A majority of the young adults with T1D perceived that electronic device use (e.g., smartphone, television, and movies, etc.) for entertainment was an important part of their bedtime ritual with only a few noting this electronic device use as a barrier to sleep (13.3%). This perception that electronic devices could be either a facilitator or barrier has varied in previous studies of adolescents and young adults with T1D and without chronic conditions.26,28,29 Electronic device use was seen as a facilitator in two studies of adolescents, one without chronic conditions26 and one with T1D.29 In the present study young adults perceived this electronic device use for entertainment as a distractor from stress and rumination. On the other hand, some participants in the present study and in a previous study of young adults without chronic conditions acknowledged that electronic devices were a barrier to sleep.28

Young adults with T1D may rely on electronic devices or other technology to support their diabetes management (e.g., smartphones connected to CGM) or need to delay bedtime to manage glycemia, with many noting a fear of hypoglycemia. Fear of hypoglycemia was a barrier of sleep noted in the current study and a consistent theme in previous research.10,30 Due to the life-threatening nature of hypoglycemia in T1D, there is a need to closely monitor and optimize glycemia before bedtime. This need leads to challenges with the use of technology. While technology to manage diabetes can be beneficial in terms of providing continuous glucose monitoring, it also poses challenges. Young adults with T1D must balance safety of high/low alert settings with the nuisance of false alarms.41 Having the alarm also may ease their fear and allow them to sleep knowing they will be awakened if there is a problem.

Technologies such as linked CGMs and insulin pumps that can sense and stop insulin infusions when blood glucose is low have the potential to reduce the fear of hypoglycemia and actual hypoglycemia. Closed-loop systems that use computer-based algorithms for insulin therapy have been reported to demonstrate reductions in sleep disturbances for caregivers and adolescents with T1D;42 however in a study of 16 middle aged adults and 12 adolescents, no differences were noted in self-reported sleep quality for those with T1D using a closed-loop system or insulin pump.43 Although there is potential for better outcomes with these recent advancements, diabetes devices disrupt sleep with alarms and there is a need to acclimate to this technology.

There are a number of important practice implications to help improve sleep in young adults with T1D. Providers can assess for potential modifiable challenges specific to diabetes (e.g., delaying bedtime to manage glycemia and disruptions) and strategies specific to diabetes to promote sleep, such as timing of eating and managing both glycemia and diabetes equipment in addition to general barriers and facilitators of sleep. An important consideration related to technology is that screens emit blue light and that suppresses melatonin,44 therefore recommending that the young adult decrease screen use 1/2 −1 hour before bed or adjusting the settings on a smart device to decrease blue light exposure may help to improve sleep. Brainstorming other strategies to facilitate falling asleep such as reading or writing on paper based on their interests may also be helpful. If technology (CGM or insulin pumps) is used to manage their diabetes, the provider can work with the young adult to incorporate this technology into their bedtime routine by considering daytime vs. nighttime settings and whether adjustments can be made to facilitate sleep (e.g., adjusting settings on CGM, replacing sensors if false alarms are noted).

Strengths of this study include the sampling of a narrower age range of young adults with T1D who are currently understudied in the literature despite having difficulty with achieving glycemic control. The use of in-depth interviews to assess factors salient to this population is another strength. The design and sampling are meant to complement existing large-scale survey and objective sleep monitoring research using actigraphy and PSG and to identify modifiable challenges and solutions to healthy sleep unique to young adults with T1D.

Limitations of this study should also be noted. This was a secondary analysis of a primary study where sleep and glucose were measured concurrently, therefore all participants in the current study had a CGM or were willing to use a CGM, and only 13.3% who did not currently have one were recruited. Although estimates for CGM use increased in this population nationally from 7% in 2010–2012 to 30% in 2016–2018,3 CGMs are still not used by the majority. Young adults who do not use a CGM and/or an insulin pump may experience different diabetes-specific barriers and facilitators. Another factor is that the current sample had slightly better glycemic control compared to the T1D Exchange cohort. The high use of CGM in the current study may have contributed to better glycemic control compared to the T1D Exchange cohort. Nevertheless, important clinical and research implications for addressing sleep in young adults with T1D are provided.

Further research is needed to understand the role of general and diabetes-specific barriers in sleep in those in and outside of target glycemic range. A diabetes-specific sleep disturbance measure may be warranted considering that current measures only address general sleep disturbances.47 A diabetes-specific measure would be able to capture the need to delay bedtime to manage hyper or hypoglycemia or a nocturnal fear of hypoglycemia and sleep disruptions related to hyperglycemia and related symptoms (e.g., nocturia, awakenings, polydipsia, etc.), hypoglycemia and related symptoms (awakenings or irritability, etc.) and pump alarms. Research on facilitators and barriers of sleep in young adults with T1D who do not use CGMs and/or insulin pumps is also needed.

Conclusion

The young adults with T1D in the current study were challenged at bedtime and overnight by the demands of the complex diabetes regimen. Although several strategies to facilitate sleep were noted, such as eating one to two hours before bed, or keeping glycemia in the target range or higher before bed, it is not surprising that sleep deficiency is highly prevalent in these young adults. Keeping glucose levels higher than the recommended range is a risk factor for premature micro and macrovascular complications.5 The consequences of sleep deficiency are detrimental for young adults with T1D given the association with poorer glycemic control and poorer management of T1D. There are potentially modifiable general environmental and psychosocial factors in addition to those specific to T1D to consider. Further, young adults with T1D can improve sleep by engaging in good sleep hygiene practices such as avoiding caffeine or naps and avoiding or limiting electronics prior to bedtime. When designing sleep-promoting interventions for young adults with T1D, it will be important to consider diabetes-specific challenges and solutions in addition to those present in the general young adult population.

Funding:

Funding was provided by the National Institute for Nursing Research (NINR), T32 NR0008346 and Sigma Theta Tau International. Dexcom provided continuous glucose monitors (G4) free of charge to be used in the study for participants who did not have their own device. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIH.

Footnotes

Conflict of interest: The authors have no conflicts of interest to disclose.

Contributor Information

Stephanie Griggs, Instructor of Nursing, Case Western Reserve University, Frances Payne Bolton School of Nursing, Cleveland, Ohio 44106.

Robin Whittemore, Professor of Nursing, Yale University, School of Nursing, West Haven, Connecticut 06477.

Nancy S. Redeker, Beatrice Renfield Term Professor of Nursing & Professor of Medicine, Yale University, School of Nursing and School of Medicine, West Haven, Connecticut 06477.

Margaret Grey, Annie Goodrich Professor of Nursing and Professor of Pediatrics, Yale University, School of Nursing and School of Medicine, West Haven, Connecticut 06477.

References

  • 1.American Diabetes Association (2020). Standards of Medical Care in Diabetes. Diabetes Care, 42(Supplement 1), S37–S47. doi: 10.2337/dc20-S004 [DOI] [PubMed] [Google Scholar]
  • 2.Centers for Disease Control and Prevention (2017). National Diabetes Statistics Report, 2017: Estimates of diabetes and its burden in the United States. [Internet]. US Department of Health and Human Services, 2017. [Google Scholar]
  • 3.Foster NC, Beck RW, Miller KM, et al. State of type 1 diabetes management and outcomes from the T1D Exchange in 2016–2018. Diabetes Technol & Ther. 2019;21(2):66–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Bryden KS, Dunger DB, Mayou RA, Peveler RC, Neil HA. Poor prognosis of young adults with type 1 diabetes: a longitudinal study. Diabetes Care. 2003;26(4):1052–1057. [DOI] [PubMed] [Google Scholar]
  • 5.Monaghan M, Helgeson V, Wiebe D. Type 1 diabetes in young adulthood. Curr Diabetes Rev. 2015;11(4):239–250. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Borel AL, Benhamou PY, Baguet JP, et al. Short sleep duration is associated with a blood pressure nondipping pattern in type 1 diabetes: the DIAPASOM study. Diabetes Care. 2009;32(9):1713–1715. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Matejko B, Skupien J, Mrozińska S, et al. Factors associated with glycemic control in adult type 1 diabetes patients treated with insulin pump therapy. Endocrine. 2015;48(1):164–169. [DOI] [PubMed] [Google Scholar]
  • 8.Sabharwal M Perceived Barriers of Young Adults for Participation in Physical Activity. Curr Res in Nutr Food Sc. 2018;6(2):437–449. [Google Scholar]
  • 9.Datye K, Bonnet K, Schlundt D, Jaser S. Experiences of Adolescents and Emerging Adults Living With Type 1 Diabetes. Diabetes Educ. 2019;45(2):194–202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Barnard K, James J, Kerr D, Adolfsson P, Runion A, Serbedzija G. Impact of chronic sleep disturbance for people living with t1 diabetes. J Diabetes Sci Technol. 2016;10(3):762–767. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Matyka KA, Crawford C, Wiggs L, Dunger DB, Stores G. Alterations in sleep physiology in young children with insulin-dependent diabetes mellitus: relationship to nocturnal hypoglycemia. J Pediatr. 2000;137(2):233–238. [DOI] [PubMed] [Google Scholar]
  • 12.Barone MTU, Wey D, Schorr F, et al. Sleep and glycemic control in type 1 diabetes. Arch of Endocrinol and Metab. 2015;59(1):71–78. [DOI] [PubMed] [Google Scholar]
  • 13.Maahs DM, West NA, Lawrence JM, Mayer-Davis EJ. Epidemiology of type 1 diabetes. Endocrinol and Metab Clin North Am. 2010;39(3):481–497. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Farabi SS, Carley DW, Quinn L. Glucose Variations and Activity Are Strongly Coupled in Sleep and Wake in Young Adults With Type 1 Diabetes. Biol Res Nurs 2017;19(3):249–257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Jauch-Chara K, Schmid SM, Hallschmid M, Born J, Schultes B. Altered neuroendocrine sleep architecture in patients with type 1 diabetes. Diabetes Care. 2008;31(6):1183–1188. [DOI] [PubMed] [Google Scholar]
  • 16.Inkster BE, Zammitt NN, Ritchie SJ, Deary IJ, Morrison I, Frier BM. Effects of Sleep Deprivation on Hypoglycemia-Induced Cognitive Impairment and Recovery in Adults With Type 1 Diabetes. Diabetes Care. 2016;39(5):750–756. [DOI] [PubMed] [Google Scholar]
  • 17.Jauch-Chara K, Hallschmid M, Gais S, et al. Hypoglycemia during sleep impairs consolidation of declarative memory in type 1 diabetic and healthy humans. Diabetes Care. 2007;30(8):2040–2045. [DOI] [PubMed] [Google Scholar]
  • 18.Farabi SS, Carley DW, Quinn L. EEG power and glucose fluctuations are coupled during sleep in young adults with type 1 diabetes. Clin Neurophysiol. 2016;127(8):2739–2746. [DOI] [PubMed] [Google Scholar]
  • 19.Beléndez M, Hernández-Mijares A. Beliefs about insulin as a predictor of fear of hypoglycaemia. Chronic Illn. 2009;5(4):250–256. [DOI] [PubMed] [Google Scholar]
  • 20.Suteau V, Saulnier PJ, Wargny M, et al. Association between sleep disturbances, fear of hypoglycemia and psychological well-being in adults with type 1 diabetes mellitus, data from cross-sectional VARDIA Study. Diabetes Res Clin Pract. 2019:107988. [DOI] [PubMed] [Google Scholar]
  • 21.Jauch‐Chara K, Hallschmid M, Schmid SM, et al. Plasma glucagon decreases during night‐time sleep in Type 1 diabetic patients and healthy control subjects. Diabet Med. 2007;24(6):684–687. [DOI] [PubMed] [Google Scholar]
  • 22.Banarer S, Cryer PE. Sleep-related hypoglycemia-associated autonomic failure in type 1 diabetes: reduced awakening from sleep during hypoglycemia. Diabetes. 2003;52(5):1195–1203. [DOI] [PubMed] [Google Scholar]
  • 23.Schultes B, Jauch-Chara K, Gais S, et al. Defective awakening response to nocturnal hypoglycemia in patients with type 1 diabetes mellitus. PLoS Medicine. 2007;4(2):e69. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Weston PJ, Gill GV. Is undetected autonomic dysfunction responsible for sudden death in Type 1 diabetes mellitus? The ‘dead in bed’syndrome revisited. Diabetic Med 1999;16(8):626–631. [DOI] [PubMed] [Google Scholar]
  • 25.Gaarde J, Hoyt LT, Ozer EJ, Maslowsky J, Deardorff J, Kyauk CK. So Much to Do Before I Sleep: Investigating Adolescent-Perceived Barriers and Facilitators to Sleep. Youth & Society. 2018:0044118X18756468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Noland H, Price JH, Dake J, Telljohann SK. Adolescents’ Sleep Behaviors and Perceptions of Sleep. J of Sch Health. 2009;79(5):224–230. [DOI] [PubMed] [Google Scholar]
  • 27.Owens JA, Stahl J, Patton A, Reddy U, Crouch M. Sleep practices, attitudes, and beliefs in inner city middle school children: a mixed-methods study. Behav Sleep Med. 2006;4(2):114–134. [DOI] [PubMed] [Google Scholar]
  • 28.Paterson JL, Reynolds AC, Duncan M, Vandelanotte C, Ferguson SA. Barriers and Enablers to Modifying Sleep Behavior in Adolescents and Young Adults: A Qualitative Investigation. Behav Sleep Med. 2019;17(1):1–11. [DOI] [PubMed] [Google Scholar]
  • 29.Bergner EM, Williams R, Hamburger ER, et al. Sleep in Teens With Type 1 Diabetes: Perspectives From Adolescents and Their Caregivers. Diabetes Educ. 2018;44(6):541–548. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Van Name MA, Hilliard ME, Boyle CT, et al. Nighttime is the worst time: Parental fear of hypoglycemia in young children with type 1 diabetes. Pediatr Diabetes. 2018;19(1):114–120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Sandelowski M What’s in a name? Qualitative description revisited. Res Nurs Health 2010;33(1):77–84. [DOI] [PubMed] [Google Scholar]
  • 32.Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999;131(7):485–491. [DOI] [PubMed] [Google Scholar]
  • 33.Buysse DJ, Reynolds CF 3rd, 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] [PubMed] [Google Scholar]
  • 34.Richards L Handling qualitative data : a practical guide. 2nd ed London: SAGE; 2009. [Google Scholar]
  • 35.Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today. 2004;24(2):105–112. [DOI] [PubMed] [Google Scholar]
  • 36.Thomas DR. A General Inductive Approach for Analyzing Qualitative Evaluation Data. Am J of Eval. 2006;27(2):237–246. [Google Scholar]
  • 37.Saldaña J The coding manual for qualitative researchers. Third edition ed. Los Angeles: SAGE; 2016. [Google Scholar]
  • 38.Ayres L, Kavanaugh K, Knafl KA. Within-case and across-case approaches to qualitative data analysis. Qual Health Res. 2003;13(6):871–883. [DOI] [PubMed] [Google Scholar]
  • 39.Whittemore R, Chase SK, Mandle CL. Validity in qualitative research. Qual Health Res. 2001;11(4):522–537. [DOI] [PubMed] [Google Scholar]
  • 40.Lincoln YS, Guba EG. Naturalistic inquiry. Beverly Hills, Calif: Sage Publications; 1985. [Google Scholar]
  • 41.Kamath A, Mahalingam A, Brauker J. Methods of evaluating the utility of continuous glucose monitor alerts. J Diabetes Sci Technol. 2010;4(1):57–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Schierloh U, Aguayo GA, Fichelle M, et al. Effect of predicted low suspend pump treatment on improving glycaemic control and quality of sleep in children with type 1 diabetes and their caregivers: the QUEST randomized crossover study. Trials. 2018;19(1):665. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Sharifi A, De Bock MI, Jayawardene D, et al. Glycemia, treatment satisfaction, cognition, and sleep quality in adults and adolescents with type 1 diabetes when using a closed-loop system overnight versus sensor-augmented pump with low-glucose suspend function: a randomized crossover study. Diabetes Technol Ther. 2016;18(12):772–783. [DOI] [PubMed] [Google Scholar]
  • 44.Tähkämö L, Partonen T, Pesonen AK. Systematic review of light exposure impact on human circadian rhythm. Chronobiol Int. 2019;36(2):151–170. [DOI] [PubMed] [Google Scholar]
  • 45.Cella D, Riley W, Stone A, et al. The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. J Clin Epidemiol. 2010;63(11):1179–1194. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES