Psychological distress and unmet mental health needs of low-income food assistance recipients who smoke.

Children of parents with a mood disorder, including major depressive disorder and bipolar disorder, are at an increased risk of developing a mood disorder (Uher et al., ). Although mood disorders typically emerge in late adolescence to early adulthood, onset often occurs in early to mid-adolescence in high-risk youth (Uher et al., ). Children at high risk of mood disorders frequently display mood-related symptoms, such as anxiety and irritability, consistent with early manifestations of mood vulnerability (Harrison et al., ; Weissman et al., ; Whelan, Leibenluft, Stringaris, & Barker, ). Sleep dysregulation is a core feature of mood disorders, including irregular sleep–wake patterns, prolonged sleep onset latency, insomnia, and circadian rhythm disruptions (Verkhratsky, Nedergaard, Steardo, & Li, ; Walker, Walton, DeVries, & Nelson, ). Sleep disturbances not only accompany existing mood disorders but also precede them, with longitudinal studies showing that disturbed sleep predicts later development of mood disorders (Alvaro, Roberts, Harris, & Bruni, ; Uher et al., ). Previous studies comparing self-reported sleep between offspring with at least one parental diagnosis of a mood disorder (FHR) and offspring with no parental diagnosis of a mood disorder (CO) indicate that FHR youth experience greater sleep disturbances (Hamilton et al., ; Maoz et al., ). However, these findings provide limited insight into the nature of sleep disturbance, as most studies rely on global sleep scores or binary classifications of ‘sleep problems’, which obscure specific patterns of dysregulation. Only a few studies have examined specific self-reported sleep characteristics in FHR compared to CO. Levenson et al. () found that FHR youth in early adolescence slept significantly earlier than CO, though no differences in sleep duration were observed. Another study by Soehner et al. () found no differences in either sleep timing or sleep duration between FHR and CO youth in middle adolescence. These inconsistent findings may partly reflect the limitations of self-report, as such measures often overestimate actual sleep duration and timing, limiting their utility for estimating circadian parameters (Lauderdale et al., ). Actigraphy is an objective sleep measure, which provides estimates of sleep–wake states comparable to those from polysomnography in pediatric populations (Ancoli-Israel et al., ; Schneider, Fárková, & Bakštein, ). Because actigraphy can reliably estimate sleep–wake states, it enables assessment of three key sleep domains: sleep duration, sleep timing, and regularity of sleep. To our knowledge, three studies have examined objectively measured sleep duration, timing, and regularity of sleep in youth at FHR compared to CO. For sleep duration, two studies reported no group differences in middle childhood and early adolescence (Estrada-Jaramillo et al., ; Sebela, Novak, Kemlink, & Goetz, ), whereas one study found that FHR youth slept longer than controls in late adolescence (Scott et al., ). For sleep timing, two studies reported no group differences in timing of sleep in early and late adolescence (Estrada-Jaramillo et al., ; Scott et al., ). Only one study has examined regularity of sleep, also reporting no differences between groups in middle childhood (Sebela, Novak, Kemlink, & Goetz, ). One possible explanation for the inconsistency between self-report and actigraphy findings is that the effects of familial risk on sleep may not be evident in early development but instead emerge later in adolescence or young adulthood. All previous studies relied on linear models when evaluating age-related differences in sleep, despite well-established nonlinear changes in sleep across the lifespan. For example, sleep duration is highest in childhood and declines steeply with age, while sleep timing shifts later during adolescence before advancing again in older adulthood (Colrain & Baker, ; Hirshkowitz et al., ; Li, Vitiello, & Gooneratne, ; Ohayon, Carskadon, Guilleminault, & Vitiello, ). Such approaches may lack sensitivity to detect age-specific or developmentally dynamic effects of familial risk.