Study Objectives: To estimate genetic and environmental influences on the associations between insomnia and depression symptoms concurrently and longitudinally. Methods: Behavioral genetic analyses were conducted on data from the British longitudinal G1219 twin/sibling study. One thousand five hundred fiftysix twins and siblings participated at Time 1 (mean age = 20.3 years, SD = 1.76). Eight hundred sixty-two participated at Time 2 (mean age = 25.2 years, SD = 1.73 years). Participants completed the Insomnia Symptoms Questionnaire and the Short Mood and Feelings Questionnaire to assess symptoms of insomnia and depression respectively. Results: Genetic effects accounted for 33% to 41% of the variance of the phenotypes. The phenotypic correlations were moderate (r = 0.34 to r = 0.52). The genetic correlations between the variables were high (0.73-1.00). Genetic effects accounted for a substantial proportion of the associations between variables (50% to 90%). Non-shared environmental effects explained the rest of the variance and covariance of the traits. Conclusions: While genetic effects play a modest role in insomnia and depression symptoms separately, they appear to play a more central role in concurrent and longitudinal associations between these phenotypes. This should be acknowledged in theories explaining these common associations.

Research suggests that poor sleep quality is related to the occurrence of sleep paralysis, although the precise relationship between these two variables is unknown. This association has generated interest due to the related possibility that improving sleep quality could help to combat episodes of sleep paralysis. To date, studies examining the association between sleep quality and sleep paralysis have typically measured sleep quality using general measures such as the global score of the Pittsburgh Sleep Quality Index (PSQI). The aim of this study was to increase the precision of our understanding of the relationship between sleep paralysis and other aspects of sleep by investigating associations between different sleep-related variables and sleep paralysis. Using data from the G1219 twin/sibling study, analyses were performed on 860 individuals aged 22-32 years (66% female). Results showed that two components of the PSQI, sleep latency and daytime dysfunction, were predictors of sleep paralysis. In addition, a number of other sleep-related variables were related significantly to sleep paralysis. These were: insomnia symptoms, sleep problems commonly related to traumatic experiences, presleep arousal, cognitions about sleep and excessive daytime sleepiness. There was no relationship with sleep-disordered breathing, diurnal preference or sleeping arrangements. Potential mechanisms underlying these results and suggestions for future research are discussed.

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This study examines the associations between dysfunctional belief about sleep (DBAS), its subtypes and insomnia symptoms and estimates the relative contribution of genetic and environmental influences to these variables and the associations between them. The data came from G1219, a twin/sibling study that comprises 862 individuals (aged 22–32 years, 34% male). The Insomnia Symptoms Questionnaire was used to measure insomnia symptoms and a 10‐item version of the Dysfunctional Beliefs and Attitudes about Sleep Scale was used to assess DBAS. A higher DBAS score was associated with more insomnia symptoms. Overall DBAS showed a mainly non‐shared environmental influence (86%). The genetic correlation between overall DBAS and insomnia symptoms was large but not significant, the shared environmental correlation was very small, negative and not significant, whereas a moderate, significant overlap in the non‐shared environmental influences was evident (non‐shared environmental correlation = 0.32). For the association between the subscales of DBAS and insomnia symptoms no significant overlap for genetic (weak to strong associations) or shared environmental factors (very weak negative to strong associations) was indicated. Most of the non‐shared environmental influences on the four variables were significantly moderately correlated (non‐shared environmental correlation = 0.24–0.46). These findings help to deepen our understanding of cognitive theories of insomnia by dissecting one of its crucial elements and illuminating the factors involved in its association with insomnia symptoms.

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