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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: Diabetes Educ. 2020 Sep 18;46(6):540–551. doi: 10.1177/0145721720958396

Age-related differences in mood, diabetes-related distress, and functional outcomes in adults with type 2 diabetes mellitus and comorbid obstructive sleep apnea and insomnia

Bomin Jeon 1, Susan M Sereika 2, Judith A Callan 3, Faith S Luyster 4, Monica M DiNardo 5, Eileen R Chasens 6
PMCID: PMC7769961  NIHMSID: NIHMS1641521  PMID: 32948109

Abstract

Purpose

The purpose of this study was to examine age-related differences in mood, diabetes-related distress, and functional outcomes in activities sensitive to impaired sleep in adults with type 2 diabetes mellitus (T2DM) and comorbid obstructive sleep apnea (OSA) and insomnia. This study also evaluated the associations of age, insomnia severity, and OSA severity on outcome variables.

Methods

This study was a secondary analysis of pooled baseline data from 2 randomized controlled trials among adults with T2DM with symptoms of sleep disorders (N = 145, 109 younger adults, 36 older adults; 46.2% male; 67.6% White). Comorbid OSA and insomnia was defined as Apnea-hypopnea Index ≥ 5 events per hour and Insomnia Severity Index ≥ 10. Outcome variables included mood, diabetes-related distress, and functional outcomes.

Results

Older adults reported better mood, lower diabetes-related distress, and higher functional outcomes relative to younger adults (all Ps < .05). Insomnia severity was associated with worse mood (b = 2.59, P < .001) and diabetes-related distress (b = 1.40, P < .001), and lower functional outcome (b = −0.22, P < .001). Older age was associated with lower diabetes-related distress (b = −0.44, P = .040).

Conclusion

Older age was a protective factor of mood disturbance, diabetes-related distress, and functional impairment in adults with T2DM and comorbid OSA and insomnia. Insomnia severity was associated with greater mood disturbance, diabetes-related distress, and functional impairment when OSA and insomnia coexist. The results suggest that diabetes care and education specialists should assess patients for impaired sleep.

Keywords: Comorbid obstructive sleep apnea and insomnia, Mood, Diabetes-related distress, Functional outcome, Type 2 diabetes mellitus

Introduction

Type 2 diabetes mellitus (T2DM) is the seventh leading cause of death in the United States.1 Older age is a risk factor for developing T2DM, with a higher prevalence rate (27%) in adults over 65 years old compared to adults ages 18 to 64 years (22%).1 In addition to the metabolic effects of T2DM, persons with T2DM more frequently experience mood disturbances (i.e. increased depressive symptoms) and major depression compared to persons without T2DM.2,3 Diabetes-related distress, emotional distress in response to the burden of diabetes management,4 is estimated to affect up to 49% of persons with T2DM.5-9 In addition to being a risk factor for developing T2DM, advancing age is also a risk factor for greater mood disturbance.10,11 However, it is unclear whether older adults with T2DM may be at higher risk of having impaired mood and diabetes-related distress.

Growing evidence suggests that sleep disorders, including obstructive sleep apnea (OSA) and insomnia, are common comorbidities in T2DM and are associated with older age.12-17 OSA is a sleep-related breathing disorder characterized by repetitive upper airway obstruction causing apnea (cessation of breathing) or hypopnea (reduction of airflow) during sleep.18,19 The estimated prevalence of OSA in persons with T2DM is approximately 36%, which is significantly higher than in persons without T2DM.20-22 Insomnia is defined as sleep-specific complaints that include difficulty initiating sleep, difficulty maintaining sleep, and early morning awakenings with an inability to return to sleep.23 An estimated 40.6% of persons with T2DM report insomnia symptoms.22 In population-based epidemiological studies, nearly half of persons over 60 years old have at least one insomnia symptom.24,25 Data from a large study (N = 5615) of community-dwelling adults ages 39 to 99 years found that after controlling for age, sex, race, snoring and breath-holding, for each 10-year increase in age, there was a 52% increased risk of having moderate to severe OSA (odds ratio [OR] = 1.52, 95% CI, 1.4 – 1.65).26 Up to 60% of older adults with insomnia had concurrent OSA.27,28

OSA and insomnia are both associated with mood disturbance and sleep disturbances are the common causes of excessive daytime sleepiness.29 Older adults with insomnia or OSA report severe depressive symptoms and have a higher risk of developing depression.30-33 Excessive daytime sleepiness in older adults is associated with impaired physical function and poor daytime functional outcome.34,35 In addition, older adults having comorbid OSA and insomnia experience greater excessive daytime sleepiness and function impairment than those having neither OSA nor insomnia.36 In summary, OSA and insomnia, which frequently coexist, are highly prevalent in older adults and in persons with T2DM, and these sleep disorders are associated with mood disturbances and excessive daytime sleepiness and may result in functional impairment in older adults.

Despite the high prevalence and adverse consequences of T2DM and sleep disorders in older adults, little is known about the impact of age on mood, diabetes-related distress, and functional outcomes associated with daytime sleepiness for T2DM patients with comorbid OSA and insomnia. The purpose of this study was to examine age-related differences in mood, diabetes-related distress, and functional outcomes in activities sensitive to impaired sleep in adults with T2DM and comorbid OSA and insomnia. This study also evaluated the association of age, insomnia severity, and OSA severity on mood, diabetes-related distress, and functional outcomes in activities sensitive to impaired sleep in adults with T2DM and comorbid OSA and insomnia while controlling for potential covariates.

Methods

Research Design

This study was a descriptive comparative secondary analysis of pooled baseline data from 2 randomized controlled trials with similar eligibility criteria and instrumentation: the Diabetes Sleep Treatment Trial (DSTT; R01-DK096023; NCT01901055) and the Diabetes Sleep Treatment Trial: Insomnia (DSTT-I; K24 NR016685; NCT03064321).

The DSTT was a multi-site study that compared the efficacy of treatment of OSA with continuous positive airway pressure (CPAP) versus sham-CPAP on outcomes of glucose control and diabetes self-management. The DSTT-I was a single site pilot/feasibility study that compared the efficacy of online cognitive behavioral treatment for insomnia versus information control on glucose control and diabetes self-management. Further details on the premise, design, and methodology of DSTT have been published.37 Institutional review boards at each of the sites in the parent studies approved the protocols. The current study was approved by a separate institutional review board submission to combine the data from the 2 independent studies for secondary analysis; it is the first to analyze the combined dataset from 2 parent studies.

Participants

Participants in the parent studies were recruited from endocrinology clinics and sleep medicine clinics. E-mails describing the study were sent to potential participants identified through approved electronic medical review, research registries, focused mailings to persons with diabetes, flyers within the community, and social media advertisement. Potential participants completed a brief interview (in-person or telephone) to screen for initial eligibility. Initial eligibility criteria for both DSTT and DSTT-I were: (1) self-reported T2DM; (2) age ≥ 18 years; (3) not involved in any sleepiness-related near-miss or automobile accident, and (4) willing to be randomized in the respective clinical trials. Following written informed consent, baseline assessments were completed for those who met the initial eligibility. For this analysis, baseline data that measured OSA severity based on an Apnea-Hypopnea Index (AHI) and insomnia severity using Insomnia Severity Index (ISI) were used to determine comorbid OSA and insomnia status.38 The eligibility criteria for the secondary analysis included (1) complete baseline data on OSA severity and insomnia severity; (2) AHI ≥5 events per hour and ISI ≥10; (3) no other sleep disorders (e.g., restless leg syndrome); and (4) complete baseline data on outcome variables of mood, diabetes-related distress, and daytime functional outcomes. Among the participants (N = 415) who met initial inclusion criteria in both the DSTT and the DSTT-I, 145 participants met the eligibility criteria for this secondary analysis (Figure 1).

Figure 1.

Figure 1.

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Participant flow for inclusion in the study.

Abbreviations: ISI, insomnia severity index; OSA, obstructive sleep apnea.

Measures

OSA Severity

Presence of OSA and OSA severity were determined by AHI, which was measured by an ApneaLinkPlus, an approved level III device for unattended portable in-home sleep studies that monitors 4 channels information (respiratory effort, nasal flow, pulse, oxygen saturation).39 Participants wore the ApneaLinkPlus for a single night in the parent studies; repeat assessments were performed when a participant had inadequate data (i.e., <4 hours of data, if AHI <10 events per hour; or <2 hours of data, if AHI >10 events per hour). All sleep study data were reviewed by trained polysomnography (PSG) technicians according to the current published standards of America Academy of Sleep Medicine for scoring apneas and hypopneas.40 In this study, OSA was defined as AHI ≥5 events per hour, and OSA severity was evaluated by the value of AHI. OSA severity is frequently classified as mild (AHI = 5-14), moderate (AHI = 15-29), or severe (AHI = ≥30).19,40 A single channel home-based ApneaLink had a good sensivitiy (67.5%) and specificity (76.9%) of an AHI of ≥5 compared to in-laboraory PSG for detecting persons with OSA.41

Insomnia Severity

The ISI is a 7-item self-report measure with a 5-point Likert scale from 0 = no problems to 4 = very severe problem that evaluates the severity, and impact of insomnia symptoms.38 The ISI total score ranges from 0 to 28, with higher scores indicating worse insomnia symptoms.38 Internal consistency for the ISI was excellent for community (Cronbach α = .90) and clinical samples (Cronbach α = .91). The cutoff score of 10 has high sensitivity (86%) and specificity (88%) for detecting insomnia in community-dwelling adults.38 In this study, insomnia was defined as ISI ≥10, and insomnia severity was evaluated by the ISI total score.

Mood

The Profile of Mood States (POMS) is a self-report measure with 5-point Likert scale from 0 = not at all to 4 = extremely that evaluates mood during the previous week.42 The POMS consists of a set of 65 adjectives or phrases that are related to the 6 subscales (Tension-Anxiety, Depression-Dejection, Anger-Hostility, Vigor-Activity, Fatigue-Inertia, and Confusion-Bewilderment).42 The Total Mood Disturbance (TMD) score is calculated by subtracting the Vigor-Activity score from the sum total of the other 5 subscales. Higher scores indicate greater mood impairment.42 Internal consistency for the 6 POMS subscales was excellent (Cronbach α = .87 for Confusion-Bewilderment to .95 for Depression-Dejection), and the POMS subscale scores reported high correlation with other concurrent measures of mood (e.g. depression, anxiety, anger).43 The POMS has been validated to be sensitive to changes associated with treatment for OSA and insomnia patients.44,45

Diabetes-Related Distress

The Problem Areas in Diabetes (PAID) is a 20-item self-report measure with 5-point Likert scale from 0 = not a problem to 4 = serious problem that evaluates unique areas of diabetes-related emotional distress in diabetes patients.46,47 A total PAID score is calculated by summing the responses and multiplying those scores by 1.25; potential scores range from 0 to 100, with higher scores indicating greater diabetes-related distress.46,47 A total PAID score ≥40 is indicative of severe diabetes-related distress.48,49 Internal consistency for the PAID was excellent (Cronbach α = .95), and the PAID had moderate to high correlation with other relevant measures of coping and distress.46,47 The PAID has been validated to be sensitive to changes associated with educational and psychosocial interventions.46

Daytime Functional Outcomes

The Functional Outcomes of Sleep Questionnaire (FOSQ) is a 30-item self-report measure with 4-point Likert scaling from 1 = yes, extreme difficulty to 4 = no difficulty that evaluates the impact of daytime sleepiness on activities of daily living.50 The FOSQ is comprised of 5 subscales: General Productivity, Social Outcome, Activity Level, Vigilance, and Intimacy and Sexual Relationships.50 The response score of 0 (I don’t do this activity for other reasons) for each item is coded as a missing response. Lower scores indicate poorer functional outcomes on activities sensitive to daytime sleepiness.50 Internal consistency for the FOSQ total score was excellent (Cronbach α = .95). The FOSQ has been validated to discriminate between normal subjects and those with sleep problems that require treatment.50

Daytime Sleepiness

Daytime sleepiness was measured by the Epworth Sleepiness Scale (ESS), an 8-item self-report measure that asks to rate the likelihood of falling asleep in common situations of daily living using 4-point Likert scaling from 0 = never dozing to 3 = high chance of dozing.51 The sum of all items represents the total ESS score.51 Potential scores range from 0 to 24; ESS scores greater than 10 indicate significant daytime sleepiness.52 Internal consistency for the ESS was good (Cronbach α = .88), and the ESS has been validated to discriminate normal sleepers from OSA patients.51,53

Sleep Quality

The Pittsburgh Sleep Quality Index (PSQI) is a validated 19-item self-report instrument that uses 4-point Likert scaling from 0 = not during the past month or very good to 3 = three or more times week or very bad to measure sleep quality and disturbances.54 The PSQI evaluates 7 components including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction.54 The sum of the component scores yields a global score that ranges from 0 to 24, with higher scores indicating poorer sleep quality.54 Internal consistency for the PSQI was good (Cronbach α = .83). A global PSQI score >5 has high sensitivity (89.6%) and specificity (86.5%) to differentiate poor and good sleep quality.54 The PSQI also has been validated in OSA and insomnia patients.55,56

Demographic/Clinical information

Demographic information collected included age, sex, race (nonwhite vs white), marital status (single/divorced/widowed vs married/partnered), education (<2-year degree of college or technical training vs ≥2-year degree of college or technical training), and financial difficulty (no financial difficulty vs some to extreme financial difficulty). Age was dichotomized into 2 groups: younger adults (i.e., persons <65 years old) and older adults (i.e., persons ≥65 years old). Participants were asked about insulin use (no vs yes) and the duration of T2DM. The parent study conducted a clinical assessment where a venipuncture was accomplished to obtain A1c, which is considered to be an accurate index of average level of blood sugar over the past 2 to 3 months. Body mass index (BMI; kg/m2) was calculated from measured height and weight.

Statistical Analysis

IBM SPSS Statistics (version 25; IBM Corp., Armonk, NY) was used for statistical analysis. A total of 145 participants identified who met eligible criteria for this secondary analysis. Prior to data analysis, the amount and patterns of missing data and the statistical assumptions underlying multiple hierarchical regression including linearity, normality, homoscedasticity of the model residuals, and no serious multicollinearity were assessed among these 145 participants. Descriptive statistics of frequencies and percentage for nominal-level variables or means and standard deviations were computed. Independent 2-sample t-test and chi-square test of independence were used to compare demographic, clinical information, severity of impaired mood, diabetes-related distress, and functional outcomes between younger and older adults. Multiple hierarchical linear regression analyses were applied with outcome variables of (1) mood, (2) diabetes-related distress, and (3) daytime functional outcomes. Bivariate correlations and linear regression were conducted to identify covariates. In addition, variables that were differed between younger and older adults were controlled for in the final multiple hierarchical linear regression models. Main predictors were OSA severity, insomnia severity, and age as continuous variables. The level of statistical significance was set at P < .05.

Results

Participant Characteristics

Demographic, clinical, and sleep characteristics of the total sample and by age group are summarized in Table 1. The sample was primarily white (67.6%), denied financial difficulty (64.8%), and received more than a 2-year degree of college or had technical training (63.4%). Sex (male; 46.2%), marital status (married/partnered; 49.7%), and insulin use (yes; 43.5%) were evenly distributed in this sample. The sample was obese (mean BMI= 35.16 ± 7.01), had excessive daytime sleepiness (mean ESS = 10.48 ± 4.44), and reported poor sleep quality (mean PSQI = 10.48 ± 3.52).

Table 1.

Demographic, Clinical and Sleep Characteristics in Total Sample and Comparison of Younger and Older Adults with T2DM and Comorbid OSA and insomnia

Characteristic Total Sample
(N = 145)		 Adults < 65y
(n = 109)		 Adults ≥ 65y
(n = 36)		 P Value
Demographics
  Sex, male, n (%) 67 (46.2) 48 (44.0) 19 (52.8) .441
  Race, white, n (%) 98 (67.6) 68 (62.4) 30 (83.3) .024
  Married/partnered, n (%) 72 (49.7) 51 (46.8) 21 (58.3) .253
  Education, ≥2-year degree of college or technical training, n (%) 92 (63.4) 65 (59.6) 27 (75.0) .113
  Some to extreme financial difficulty, n (%) 51 (35.2) 67 (62.0) 26 (72.2) .268
Clinical information
  Insulin use status, yes, n (%) 64 (44.1) 46 (42.2) 18 (50.0) .444
  Duration of T2DM, y 11.00 ± 9.64 8.91 ± 8.10 17.34 ± 11.19 <.001
  A1C (%) 7.95 ± 1.61 8.10 ± 1.69 7.51 ± 1.26 .057
  BMI (kg/m2) 35.16 ± 7.01 35.87 ± 7.20 33.00 ± 6.00 .033
Daytime sleepiness
  Epworth Sleepiness Scale 10.48 ± 4.44 11.01 ± 4.65 8.86 ± 3.32 .011
Sleep quality
  Pittsburgh Sleep Quality Index 10.48 ± 3.52 10.47 ± 3.46 10.50 ± 3.73 .967
OSA severity
  Apnea-Hypopnea Index 19.07 ± 15.01 19.07 ± 15.85 19.08 ± 12.31 .999
Insomnia severity
  Insomnia Severity Index 15.62 ± 4.55 15.87 ± 4.52 14.86 ± 4.62 .250
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Abbreviations: BMI, body mass index; OSA, obstructive sleep apnea; T2DM, type 2 diabetes mellitus.

The majority of the sample was adults younger than 65 years (n = 109, 75.2%). Older adults had a significantly longer duration of T2DM (P < .001) and a lower BMI (P = .033) compared to younger adults. Younger adults experienced more daytime sleepiness (P = .011) than older adults. There were no significant differences between older and younger adults in sleep quality, OSA severity, or insomnia severity.

Age-Related Differences in Mood, Diabetes-Related Distress, and Functional Outcomes

Table 2 presents results from the comparison of mood disturbance, diabetes-related distress, and functional outcomes between the 2 age groups. Adults ≥65 years had significantly lower scores on the POMS subscales of Tension-Anxiety, Depression-Dejection, Anger-Hostility, and Confusion-Bewilderment and on POMS TMD score. Higher scores on the POMS subscale of Vigor-Activity were found in adults ≥65 years compared to adults <65 years (all Ps < .05). There were no statistically significant differences between younger and older adults on the POMS Fatigue-Inertia subscale. Older adults had a significantly lower diabetes-related distress based on the PAID compared to younger adults (P = .001). In addition, older adults had significantly higher scores on functional outcomes sensitive to impaired sleep (General Productivity, Social Outcomes, Activity, Vigilance, and FOSQ total score; all Ps < .05) compared to adults younger than 65 years. There was no significant difference between the 2 groups on the FOSQ subscale of the Intimacy and Sexual Relationships.

Table 2.

Comparison Mood, Diabetes-Related Distress, and Sleep-Related Daytime Function Between Younger and Older Adults With T2DM and Comorbid OSA and insomnia

Variables Total
(N = 145)		 Adults < 65y
(n = 109)		 Adults ≥ 65y
(n = 36)		 P Value
POMS scores
   Tension-anxiety 9.15 ± 6.13 9.95 ± 6.37 6.75 ± 4.67 .006
   Depression-dejection 7.75 ± 9.08 8.64 ± 9.91 5.06 ± 5.10 .039
   Anger-hostility 6.76 ± 6.81 7.45 ± 7.22 4.67 ± 4.90 .033
   Vigor-activity 15.22 ± 6.21 14.60 ± 6.25 17.11 ± 5.77 .035
   Fatigue-inertia 10.85 ± 6.03 11.22 ± 6.02 9.72 ± 6.02 .197
   Confusion-bewilderment 6.75 ± 4.78 7.28 ± 4.94 5.17 ± 3.91 .021
   Total mood disturbance 26.04 ± 31.67 29.94 ± 33.34 14.25 ± 22.52 .010
Diabetes-related distress
   PAID 30.37 ± 19.95 33.57 ± 20.16 20.69 ± 16.00 .001
FOSQ scores
   General productivity 3.34 ± 0.55 3.26 ± 0.57 3.60 ± 0.41 .001
   Social outcomes 3.50 ± 0.66 3.43 ± 0.70 3.72 ± 0.48 .021
   Activity level 2.99 ± 0.62 2.93 ± 0.61 3.20 ± 0.61 .022
   Vigilance 3.09 ± 0.63 3.02 ± 0.64 3.31 ± 0.54 .014
   Intimacy and Sexual Relationshipsa 3.06 ± 0.96 3.04 ± 0.94 3.12 ± 1.02 .729
   FOSQ total 15.98 ± 2.60 15.64 ± 2.64 17.02 ± 2.23 .005
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Abbreviations: FOSQ, Functional Outcomes of Sleep Questionnaire; OSA, obstructive sleep apnea; PAID, Problem Areas in diabetes Questionnaire; POMS, Profile of Mood States; T2DM, type 2 diabetes mellitus.

a

n = 118 (adults <65y = 87, adults ≥65y = 31) of participants were included due to nonapplicable and missing cases.

Associations of Age, Insomnia, and OSA Severity on Outcome Variables

Unadjusted association was obtained with linear regression between the 3 predictors (age, insomnia, and OSA severity) and each outcome (POMS TMD score, PAID, and FOSQ total scores). The overall models were significant to predict each outcome (POMS TMD score, F = 9.72, df = 3, P < .001; PAID, F = 16.81, df = 3, P < .001; FOSQ total scores, F = 12.20, df = 3, P < .001). Insomnia severity was significantly associated with higher POMS TMD score (P < .001), higher PAID (P < .001), and higher FOSQ total scores (P < .001). Age was associated with lower POMS TMD score (P = .002), lower PAID (P = .001), and lower FOSQ total scores (P = .001). OSA severity had no association with any outcomes.

Table 3 summarizes the results of multiple hierarchical linear regression analyses for the outcomes of POMS TMD score, PAID, and FOSQ total scores with the predictor variables of age, insomnia severity, and OSA severity controlling for daytime sleepiness, duration of T2DM, BMI, and race. The overall models were significant to predict POMS TMD score (F = 5.91, df = 7, P < .001), PAID (F = 4.29, df = 7, P < .001), and FOSQ total score (F = 16.74, df = 7, P < .001).

Table 3.

The Association of Age, Insomnia, and OSA Severity on Impaired Mood, Diabetes-Related Distress, and Sleep-Related Daytime Function in Adults With T2DM and Comorbid OSA and insomnia

b b 95% CI β t P Value Semipartial
correlation		 Fit
POMS total mood disturbance score
   (Constant) 6.31 [−45.59, 58.20] 0.24 .810
Control
   Epworth Sleepiness Scale 1.20 [0.05, 2.35] 0.17 2.06 .041 .16
   Duration of T2DM −0.01 [−0.55, 0.53] −0.00 −0.04 .970 −.00
   BMI 0.01 [−0.77, 0.80] 0.00 0.03 .975 .00
   Race, whitea 1.60 [−8.80, 11.99] 0.02 0.30 .762 .02
Main
   Insomnia Severity Index 2.59 [1.52, 3.67] 0.38 4.78 < .001 .36
   Apnea-Hypopnea Index −0.12 [−0.45, 0.21] −0.06 −0.73 .466 −.06
   Age −0.58 [1.18, 0.03] −0.18 −1.90 0.06 −.14
R2 = .154,
P < .001
PAID
   (Constant) 29.19 [−5.00, 63.38] 1.69 .094
Control
   Epworth Sleepiness Scale 0.49 [−0.27, 1.25] 0.11 1.27 .206 .10
   Duration of T2DM 0.01 [−0.35, 0.36] 0.00 0.03 .973 .00
   BMI 0.02 [−0.50, 0.53] 0.05 0.06 .953 .01
   Race, whitea −2.43 [−9.27, 4.42] −0.06 −0.70 .484 −.06
Main
   Insomnia Severity Index 1.40 [0.69, 2.10] 0.32 3.90 < .001 .31
   Apnea-Hypopnea Index −0.03 [−0.25, 0.18] −0.03 −0.31 0.756 −.02
   Age −0.44 [−0.81, −0.02] −0.20 −2.07 0.040 −.16
R2 = .116
P = .001
FOSQ total score
   (Constant) 20.96 [17.32, 24.59] 11.40 < .001
Control
   Epworth Sleepiness Scale −0.26 [−0.35, −0.18] −0.45 −6.49 < .001 −.41
   Duration of T2DM 0.04 [0.01, 0.08] 0.16 2.32 .022 .15
   BMI 0.00 [−0.05, 0.06] 0.01 0.13 .899 .01
   Race, whitea −0.56 [−1.29, 0.17] −0.10 −1.53 .129 −.10
Main
   Insomnia Severity Index −0.22 [−0.30, −0.14] −0.38 −5.77 < .001 −.37
   Apnea-Hypopnea Index −0.01 [−0.03, 0.02] −0.05 −0.73 .465 −.05
   Age 0.02 [−0.02, 0.06] 0.07 0.91 .364 .06
R2 = .134
P < .001
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Abbreviations: FOSQ, Functional Outcomes of Sleep Questionnaire; OSA, obstructive sleep apnea; PAID, Problem Areas in Diabetes Questionnaire; POMS, Profile of Mood States; T2DM, type 2 diabetes mellitus.

a

Reference of race is nonwhite.

Insomnia severity based on the ISI (P < .001) was found to be a significant predictor of poorer mood based on the POMS TMD score while controlling for covariates (P = .041). Specifically, greater insomnia severity and daytime sleepiness were independently associated with higher POMS TMD scores. Insomnia severity (P < .001) and age (P = .040) were found to be significant predictors of diabetes-related distress (PAID scores). Greater insomnia severity was associated with higher levels of diabetes-related distress (higher PAID score), whereas older age was associated with lower levels of diabetes-related distress (lower PAID scores). In addition, greater insomnia severity (P < .001) was significantly associated with lower functional outcomes (FOSQ total score); greater daytime sleepiness (P < .001) and longer duration of T2DM (P = .002) were also significant in this model. However, OSA severity (i.e., AHI) was not significantly associated with changes in mood, diabetes-related distress, or functional outcomes.

Discussion

The findings in this study suggest that younger, not older, adults with T2DM and coexisting OSA and insomnia experienced poorer mood, higher diabetes-related distress, and worse daytime functional outcomes. After controlling for covariates (i.e., daytime sleepiness, duration of T2DM, BMI, and race), insomnia severity was significantly associated with worse mood, increased diabetes-related distress, and poorer daytime function. Conversely, greater age was associated with lower diabetes-related distress.

Although previous studies reported that older adults are at a higher risk for T2DM and sleep disorders, mood disturbances, and daytime sleepiness than younger adults33,57-59, the findings of this study suggested that younger adults who were less than 65 years had worse mood and higher diabetes-related distress compared to older adults who were older than 65 years. In addition, older adults with T2DM and comorbid OSA and insomnia had better daytime functional outcomes than younger adults. These findings indicate that the associations between sleep disorders and mood, diabetes-related distress, and daytime functional outcomes are different between younger and older adults with T2DM.

The transactional stress model from Lazarus and Folkman60 explains that persons individually appraise specific events to determine whether the events have the potential to increase distress dependent on their possible ability to cope. Consistent with the content of this model, the study by Berg and Upchurch61 reported that older adults cope better with stress related with chronic disease and show better emotional regulation strategies because they are likely to experience chronic stress for a longer period of time than younger adults.62 That is, older adults may have better coping strategies to help reduce their overall perception of detrimental outcomes associated with chronic diseases because of their experience. Research about the relationship between age and distress in T2DM suggests that older age is associated with less psychological distress, such as depressive symptoms and diabetes-related distress.63,64 Therefore, in patients with T2DM, the relationship between sleep disorders and mood, diabetes-related distress, and daytime function may be attenuated in older adults with more prolonged experience with T2DM. However, the construct of experience with T2DM in older adults as it relates to coping with detrimental outcomes in relation to sleep disorders needs to be further evaluated.

The analysis examined the associations of age and the severity of 2 common sleep disorders, insomnia and OSA, in predicting mood, diabetes-related distress, and daytime functional outcomes in persons with T2DM. A 1-unit increase in insomnia severity was associated with a 2.59-unit increase in mood disturbance, a 1.40-unit increase in diabetes-related distress, and a 0.22-unit decrease in daytime function. However, OSA severity did not have any statistically significant relationship with these 3 outcomes. These results suggest that when insomnia and OSA coexist, insomnia may be more influential for psychological distress, including impaired mood, diabetes-related distress, and impaired daytime function, although previous studies report that insomnia and OSA are independently or jointly associated with mood disturbance, and daytime sleepiness.15,17,29,33,65-67

This study found that a 1-unit increase in age was related to a 0.44-unit decrease in diabetes-related distress, which supports a hypothesis that older age is associated with better coping strategies to stress related with chronic disease.61 However, age was not related to mood and daytime functional outcomes. The FOSQ is designed to assess the impact of excessive daytime sleepiness on the ability to conduct daily activities.50 Excessive daytime sleepiness is a common symptom of persons with mood disturbances68-70 and in this study, daytime sleepiness was significantly associated with higher levels of impaired mood. This suggests that when daytime sleepiness is considered, the association between age and impaired mood and daytime functional outcomes is greatly diminished. Therefore, it is necessary to examine the role of daytime sleepiness between sleep disorders and mood and daytime functional outcomes in persons with T2DM in the future.

The study has several limitations. It was a secondary analysis using cross-sectional data with a relatively modest sample size that precludes the inference of causality. In addition, the exclusion of those subjects who did not have adequate quantified sleep data from the home-based sleep studies may have biased the sample. Although persons may gain benefit from home-based sleep study because they may have less difficulty initiating sleep than those in in-patient PSG, the ApneaLinkPlus device does not collect EEG waveforms, which verify the actual sleep status of individual. This can be a significant problem in the evaluation of potential persons with comorbid OSA and insomnia. The objective measures of sleep such as in-patient PSG, or the concurrent use of actigraphy would provide a more reliable measure of comorbid OSA and insomnia. The limited number of responses in the Intimate and Sexual Relationship subscale score of FOSQ may affect the results of the comparison between younger and older adults. However, as this subscale contains sensitive questions, it is plausible that the participants indicated ‘non-applicable’ because they did not connect sleepiness to changes in sexual function. It was found in another study to have more missing data than other subscales in the FOSQ.71 Finally, although daytime sleepiness was controlled in the regression analyses, it remained a significant factor in the prediction of impaired mood and daytime functional impairment. There remains a need to explore the role of daytime sleepiness in the relationship between severity of sleep disorders and mood and daytime functional outcomes in persons with T2DM.

Conclusions

In conclusion, this study suggested that older age in persons with T2DM and comorbid OSA and insomnia had better mood, lower diabetes-related distress, and higher level of daytime function relative to younger adults. Increased insomnia severity was associated with impaired mood, a higher level of diabetes-related distress, and daytime function impairment, but OSA severity had no relationship with these variables when covariates were controlled.

Implications

Diabetes care and education specialists need to recognize the effect that OSA and insomnia may have on mood, diabetes-related distress, and functional outcomes in their patients with diabetes. In addition, it is important to screen for excessive daytime sleepiness because sleep disorders are the most common causes of it. Importantly, daytime sleepiness should not be considered benign because daytime sleepiness may significantly worsen mood and reduce daytime function, which decreases health-related quality of life in persons with diabetes. Moreover, it is important that clinicians recognize that older age is not synonymous with impaired mood and high levels of diabetes-related distress because age may actually increase the older adults’ ability to cope with the negative effects of sleep disturbances because of their longer experience of T2DM. However, impaired mood and diabetes-related distress have a significant negative effect on glucose management and health-related quality of life. Therefore, sleep as well as other potential factors need to be considered as modifiable factors for mood disturbances in care of the patient with T2DM.

Acknowledgements

Funding: This research is supported by the National Institue of Diabetes and Digestive and Kidney Diseases (R01-DK096023) and the National Institute of Nursing Research (K24 NR016685).

Footnotes

Conflict of interest: No conflicts of interest have been declared by the authors.

Contributor Information

Bomin Jeon, University of Pittsburgh, School of Nursing, Pittsburgh, PA.

Susan M. Sereika, University of Pittsburgh, School of Nursing, Pittsburgh, PA.

Judith A. Callan, University of Pittsburgh, School of Nursing, Pittsburgh, PA.

Faith S. Luyster, University of Pittsburgh, School of Nursing, Pittsburgh, PA.

Monica M. DiNardo, VA Pittsburgh Healthcare System, Pittsburgh, PA.

Eileen R. Chasens, University of Pittsburgh, School of Nursing, Pittsburgh, PA.

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