Amie C. Hayley

So depression is an inflammatory disease, but where does the inflammation come from?

BackgroundWe now know that depression is associated with a chronic, low-grade inflammatory response and activation of cell-mediated immunity, as well as activation of the compensatory anti-inflammatory reflex system. It is similarly accompanied by increased oxidative and nitrosative stress (O&NS), which contribute to neuroprogression in the disorder. The obvious question this poses is ‘what is the source of this chronic low-grade inflammation?’DiscussionThis review explores the role of inflammation and oxidative and nitrosative stress as possible mediators of known environmental risk factors in depression, and discusses potential implications of these findings. A range of factors appear to increase the risk for the development of depression, and seem to be associated with systemic inflammation; these include psychosocial stressors, poor diet, physical inactivity, obesity, smoking, altered gut permeability, atopy, dental cares, sleep and vitamin D deficiency.SummaryThe identification of known sources of inflammation provides support for inflammation as a mediating pathway to both risk and neuroprogression in depression. Critically, most of these factors are plastic, and potentially amenable to therapeutic and preventative interventions. Most, but not all, of the above mentioned sources of inflammation may play a role in other psychiatric disorders, such as bipolar disorder, schizophrenia, autism and post-traumatic stress disorder.

Oxidative & nitrosative stress in depression: Why so much stress?

Many studies support a crucial role for oxidative & nitrosative stress (O&NS) in the pathophysiology of unipolar and bipolar depression. These disorders are characterized inter alia by lowered antioxidant defenses, including: lower levels of zinc, coenzyme Q10, vitamin E and glutathione; increased lipid peroxidation; damage to proteins, DNA and mitochondria; secondary autoimmune responses directed against redox modified nitrosylated proteins and oxidative specific epitopes. This review examines and details a model through which a complex series of environmental factors and biological pathways contribute to increased redox signaling and consequently increased O&NS in mood disorders. This multi-step process highlights the potential for future interventions that encompass a diverse range of environmental and molecular targets in the treatment of depression.

The relationships between insomnia, sleep apnoea and depression: Findings from the American National Health and Nutrition Examination Survey, 2005–2008:

Objective: To determine the association between insomnia, obstructive sleep apnoea (OSA), and comorbid insomnia-OSA and depression, while controlling for relevant lifestyle and health factors, among a large population-based sample of US adults. Method: We examined a sample of 11,329 adults (≥18 years) who participated in the National Health and Nutrition Examination Survey (NHANES) during the years 2005–2008. Insomnia was classified via a combination of self-reported positive physician diagnosis and high-frequency ‘trouble falling asleep’, ‘waking during the night’, ‘waking too early’, and ‘feeling unrested during the day’. OSA was classified as a combination of a positive response to a physician-diagnosed condition, in addition to a high frequency of self-reported nocturnal ‘snoring’, ‘snorting/stopping breathing’ and ‘feeling overly sleepy during the day’. Comorbid insomnia-OSA was further assessed by combining a positive response to either insomnia (all), or sleep apnoea (all), as classified above. Depressive symptomology was assessed by the Patient Health Questionnaire-9 (PHQ-9), with scores of >9 used to indicate depression. Odds ratios (ORs) and 95% confidence intervals (CIs) for sleep disorders and depression were attained from logistic regression modelling adjusted for sex, age, poverty level, smoking status and body mass index (BMI). Results: Those who reported insomnia, OSA or comorbid insomnia-OSA symptoms reported higher rates of depression (33.6%, 22.2%, 27.1%, respectively), and consistently reported poorer physical health outcomes than those who did not report sleep disorders. After adjusting for sex, age, poverty level, smoking status and BMI (kg/m2), insomnia (OR 6.57, 95% CI 3.89-11.11), OSA (OR 5.14, 95% CI 3.14–8.41) and comorbid insomnia-OSA (OR 6.67, 95% CI 4.44–10.00) were associated with an increased likelihood of reporting depression. Conclusions: Insomnia, OSA and comorbid insomnia-OSA are associated with significant depressive symptomology among this large population-based sample of adults.

The relationship between excessive daytime sleepiness and depressive and anxiety disorders in women

Objective: Excessive daytime sleepiness (EDS) is a common clinical symptom that affects women more than men. However, the association of excessive sleepiness with depressive and anxiety disorders in the broader population is unclear. The aim of this study was, therefore, to examine the association between excessive daytime sleepiness as measured by the Epworth Sleepiness Scale, and depressive and anxiety disorders in a population-based sample of women. Methods: Using the Structured Clinical Interview for DSM-IV Disorders (Non-Patient) (SCID-I/NP), 944 women aged 20–97 years (median 49 years, IQR 33–65 years) were assessed for depressive and anxiety disorders as part of the Geelong Osteoporosis Study. EDS was assessed using the Epworth Sleepiness Scale (ESS, cut-off > 10). Lifestyle factors were documented by self-report, height and weight were measured, and socioeconomic status categorised according to the Index of Relative Socio-Economic Advantage and Disadvantage. Results: Overall, 125 (13.2%) of the women were identified with EDS. EDS was associated with an increased likelihood for both current (OR = 2.11, 95% CI 1.10–4.06) and lifetime history (OR = 1.95, 95% CI 1.28–2.97) of depressive disorders, but not anxiety disorders, independent of age and alcohol consumption. These findings were not explained by antidepressant or sedative use, body mass index, physical activity, smoking, or socioeconomic status. Conclusions: These results suggest that excessive daytime sleepiness is associated with current and lifetime depressive, but not anxiety disorders. Clinically, this highlights the need to take into account the possible bidirectional relationship between depressive disorders and excessive sleepiness when assessing mental health issues in patients with EDS.

Prevalence of excessive daytime sleepiness in a sample of the Australian adult population

OBJECTIVES Excessive daytime sleepiness (EDS) is associated with significant personal and medical burden. However, there is little indication of the impact of these symptoms in the broader population. PARTICIPANTS AND METHODS We studied 946 men ages 24-92 years (median age, 59.4 [interquartile range {IQR}, 45-73 years]) and 1104 women ages 20-94 years (median age, 50 [IQR, 34-65 years]) who resided in the Barwon Statistical Division, South-Eastern Australia, and participated in the Geelong Osteoporosis Study (GOS) between the years of 2001 and 2008. EDS was defined as an Epworth Sleepiness Scale (ESS) score of ⩾ 10. Lifestyle factors, history of medical conditions, and medication history were documented by self-report. RESULTS For men, the age-specific prevalence of EDS was 5.1% (ages 20-29 years), 6.4% (ages 30-39 years), 9.8% (ages 40-49 years), 15.5% (ages 50-59 years), 12.0% (ages 60-69 years), 12.0% (ages 70-79 years), and 29.0% (ages ⩾ 80 years). For women, the age-specific prevalence of EDS was 14.7% (ages 20-29 years), 8.7% (ages 30-39 years), 15.0% (ages 40-49 years), 16.0% (ages 50-59 years), 12.6% (ages 60-69 years), 13.2% (ages 70-79 years), and 17.0% (ages ⩾ 80 years). Overall standardized prevalence of EDS was 10.4% (95% confidence interval, 9.7-11.2) for men and 13.6% (95% confidence interval, 12.8-14.4) for women. CONCLUSIONS The prevalence of EDS increased with age, affecting approximately one-third of those aged ⩾ 80 years. Because EDS has been associated with poorer health outcomes in the older age strata, these findings suggest that routine screening may be beneficial in ongoing health assessments for these individuals. Overall, more than one-tenth of the Australian adult population has EDS, which is indicative of possible underlying sleep pathology.

Symptoms of depression and difficulty initiating sleep from early adolescence to early adulthood: a longitudinal study

STUDY OBJECTIVES To assess the direction of the relationship and degree of shared associations between symptoms of depression and difficulty initiating sleep (DIS) from early adolescence to early adulthood. DESIGN Cross-sectional and longitudinal assessment of the symptoms of depression-DIS association from early adolescence (age 13 y) to early adulthood (age 23 y). SETTING Hordaland, Norway. PARTICIPANTS There were 1,105 individuals (55% male) who took part in the Norwegian Longitudinal Health Behaviour Study (NLHB) and participated at least once across seven data collection waves during the years 1990-2000. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Characteristic data were obtained during the first assessment. Symptoms of depression and instances of DIS were assessed during each data collection wave. Symptoms of depression and DIS were associated in all data waves, and one-step cross-lagged bivariate correlations were significant and comparatively high for both factors. Structural equation modelling indicated that DIS and symptoms of depression at wave 1 remain relatively stable across waves (all P < 0.001), and a significant and consistent unidirectional cross-lagged effect was noted running from symptoms of depression to DIS from early adolescence to early adulthood. DIS is only marginally and inconsistently associated with the lagged symptoms of depression score across waves. CONCLUSIONS These results suggest that symptoms of depression established in early adolescence are a moderate predictor of difficulty initiating sleep (DIS) in early adulthood, whereas the reverse association of DIS predicting depression was not convincingly supported. These findings are in contrast to previous findings that suggest sleep problems as a risk factor for the later development of depression.

The utility of automated measures of ocular metrics for detecting driver drowsiness during extended wakefulness.

Slowed eyelid closure coupled with increased duration and frequency of closure is associated with drowsiness. This study assessed the utility of two devices for automated measurement of slow eyelid closure in a standard poor performance condition (alcohol) and following 12-h sleep deprivation. Twenty-two healthy participants (mean age=20.8 (SD 1.9) years) with no history of sleep disorders participated in the study. Participants underwent one baseline and one counterbalanced session each over two weeks; one 24-hour period of sleep deprivation, and one daytime session during which alcohol was consumed after a normal night of sleep. Participants completed a test battery consisting of a 30-min simulated driving task, a 10-min Psychomotor Vigilance Task (PVT) and the Karolinska Sleepiness Scale (KSS) each in two baseline sessions, and in two randomised, counterbalanced experimental sessions; following sleep deprivation and following alcohol consumption. Eyelid closure was measured during both tasks using two automated devices (Copilot and Optalert™). There was an increase in the proportion of time with eyelids closed and the Johns Drowsiness Score (incorporating relative velocity of eyelid movements) following sleep deprivation using Optalert (p<0.05 for both). These measures correlated significantly with crashes, PVT lapses and subjective sleepiness (r-values 0.46-0.69, p<0.05). No difference between the two sessions for PERCLOS recorded during the PVT or the driving task as measured by the Copilot. The duration of eyelid closure predicted frequent lapses following sleep deprivation (which were equivalent to the average lapses at a blood alcohol concentration of 0.05% - area under curve for ROC curve 0.87, p<0.01). The duration of time with slow eyelid closure, assessed by the automated devices, increased following sleep deprivation and was associated with deterioration in psychomotor performance and subjective sleepiness. Comprehensive algorithms inclusive of ocular parameters may be a better indicator of performance impairment following sleep loss.

Excessive daytime sleepiness and falls among older men and women: cross-sectional examination of a population-based sample

BackgroundExcessive daytime sleepiness (EDS) has been associated with an increased risk for falls among clinical samples of older adults. However, there is little detailed information among population-representative samples. The current study aimed to assess the relationship between EDS and falls among a cohort of population-based older adults.MethodsThis study assessed 367 women aged 60-93years (median 72, interquartile range 65-79) and 451 men aged 60-92years (median 73, interquartile range 66-80) who participated in the Geelong Osteoporosis Study between the years 2001 and 2008. Falls during the prior year were documented via self-report, and for men, falls risk score was obtained using an Elderly Fall Screening Test (EFST). Sleepiness was assessed using the Epworth Sleepiness Scale (ESS), and scores of ≥ 10 indicated EDS. Differences among those with and without EDS in regard to falls were tested using logistic regression models.ResultsAmong women, 50 (13.6 %) individuals reported EDS. Women with EDS were more likely to report a fall, and were more likely to report the fall occurring outside. EDS was similarly associated with an increased risk of a fall following adjustment for use of a walking aid, cases of nocturia and antidepressant medication use (adjusted OR = 2.54, 95 % CI 1.24-5.21). Multivariate modelling revealed antidepressant use (current) as an effect modifier (p < .001 for the interaction term). After stratifying the data by antidepressant medication use, the association between EDS and falls was sustained following adjustment for nocturia among antidepressant non-users (adjusted OR = 2.63, 95 % CI 1.31-5.30). Among men, 72 (16.0 %) individuals reported EDS. No differences were detected for men with and without EDS in regard to reported falls, and a trend towards significance was noted between EDS and a high falls risk as assessed by the EFST (p = 0.06), however, age explained this relationship (age adjusted OR = 2.20, 95 % CI 1.03-1.10).ConclusionsFor women, EDS is independently associated with at least one fall during the previous year, and this is more likely to occur whilst located outside. Amelioration of EDS may assist in improving functional outcomes among these individuals by reducing the risk for falls.

Trajectories and stability of self-reported short sleep duration from adolescence to adulthood

The trajectories and stability of self‐reported sleep duration recorded at ages 13, 15, and 23 years on reported sleep duration at age 30 years among 1105 students (55% male) who participated in the Norwegian Longitudinal Health and Behaviour Study were examined. Questionnaire data were used to obtain demographic and sleep variables. Dichotomised short sleep duration was based on normative values and set as ≤8.5 h (age 13 years), ≤8 h (age 15 years) and ≤7 h (ages 23 and 30 years). Results indicated a significant overall reduction in total sleep duration (h per night) across age groups. Sleep duration (continuous) at age 15 and 23 years (whole group) was moderately but positively correlated with sleep duration at age 30 years (P < 0.01). When split by sex, at age 15 years, this association was present among females only (P < 0.01); however, at age 23 years, this association was present in both male and females (both P < 0.001). Categorical short sleep at age 23 years (whole group) was associated with short sleep at age 30 years (unadjusted odds ratio = 3.67, 95% confidence interval 2.36–5.69). Following sex stratification, this effect was significant for both males (unadjusted odds ratio = 3.77, 95% confidence interval: 2.22–6.42) and females (unadjusted odds ratio = 2.71, 95% confidence interval: 1.46–5.04). No associations were noted for categorical short sleep at ages 13 or 15 years, and subsequent short sleep at 30 years. Habitual short sleep duration during middle adulthood is not sustained from the time of early adolescence. Rather, these trends appear to be formed during early adulthood.

Excessive daytime sleepiness and metabolic syndrome: a cross-sectional study

OBJECTIVE Excessive daytime sleepiness (EDS) has been associated with singular independent symptoms of metabolic syndrome, such as insulin resistance and diabetes. The aim of this study was to assess whether this relationship is sustained among individuals who meet criteria for the whole syndrome. MATERIALS/METHODS 994 Women aged 21-94 years (median 50.2 years, IQR 34-65) and 840 men aged 24-92 years (median 60.4 years, IQR 47-73) who resided in the Barwon Statistical Division, South-Eastern Australia, and participated in the Geelong Osteoporosis Study (GOS) between the years of 2001 and 2008. Anthropometric measurements, lifestyle, mood, demographic and health-related factors were obtained. Sleep duration was categorized as short (<6 h), average (6-9 h) and long (>9 h). Sleepiness was assessed using the Epworth Sleepiness Scale (ESS), and scores of ≥ 10 indicated EDS. The presence of metabolic syndrome was assessed using a modified version of criteria as outlined by the International Diabetics Federations recommendations (2005). RESULTS Women: 138 (14.0%) of the women reported EDS; those with EDS were heavier, had a greater body mass index (BMI) and were more likely to have metabolic syndrome. The association between EDS and metabolic syndrome was sustained following adjustment for age and hours sleep (adjusted OR=1.90, 95% CI 1.16-3.09), however BMI attenuated the relationship (adjusted OR=1.64, 95% CI =1.05-2.57). These findings were independent of smoking status, alcohol intake, medication use, socioeconomic status, physical activity and current diagnosis of a depressive illness. Men: 111 (13.2%) of the men reported EDS; those with EDS had a greater waist circumference and were more likely to have metabolic syndrome. Analysis of age-stratified data (<60 years vs. ≥60 years) revealed that the older men with EDS were more likely to have metabolic syndrome (OR=1.71, 95% CI 1.01-2.92), however, age explained this association (age adjusted OR=1.51, 95% CI 0.88-2.60). In the younger age group, no association was detected between EDS and metabolic syndrome. For both men and women, the prevalence of combined EDS and metabolic syndrome increased progressively with age. CONCLUSION For women, the association between EDS and metabolic syndrome appears to be driven by adiposity measures; while for men, the association is somewhat attributed to older age. Additional research is required to assess temporal associations with underlying sleep pathology.