Purpose: Children experience excessive weight gain during the summer months, and changes in sleep behaviors may contribute. Children in low-income families are at elevated risk of engaging in poorer health behaviors and health outcomes and may be exposed to greater changes in sleep during summer. The purpose of this study was to assess differences in school-aged children’s sleep health by household income separately while in school and summer. Methods: Children (n=1,007, age range: 5-14yrs, 49% female) wore an Actigraph GT9X for 24 hours per day over 14 days in spring and summer across a maximum of 3 years (6 timepoints). Sleep duration, bedtime, and waketime were calculated using the GGIR (v3.1.2) R package and HDCZA algorithm. Variability of these metrics was calculated as the individual standard deviation across days at each timepoint. Income groups were determined as parent-report of household income, categorized as low-income (3.0 income-to-poverty ratio). We utilized mixed effects models to examine mean levels and variability of sleep metrics to compare income groups in school and summer. Results: Analyses included 34,767 days of accelerometer data. Children had similar sleep duration and timing during school and summer across income groups. However, children in low-income families went to bed significantly later in summer than children in middle (+13.2mins, 95%CI: 5.3, 21.1) and high-income (+21.0mins, 95%CI: 10.1, 31.9) families. Children in low-income families also woke up significantly later in summer than children in high-income families (+12.1mins, 95%CI: 2.4, 21.9). Bedtime was more variable in summer (low vs. middle: +5.2mins; 95%CI: 2.5, 7.9; low vs. high: +8.5mins; 95%CI: 4.8, 12.3), while waketime was more variable in school (low vs. middle: +10.3mins; 95%CI: 7.8, 12.8; low vs. high-income: +13.1mins; 95%CI: 9.6, 16.6) and in summer (low vs. middle: +12.0mins; 95%CI: 9.4, 14.5; low vs. high: +18.7mins; 95%CI: 15.3, 22.2). Conclusions: Children from low-income households had later sleep timing and more sleep variability as compared to their middle and high-income counterparts. Future studies should examine the contextual and behavioral time-use factors associated with sleep health in children across income groups, especially in low-income families, to identify where or when to intervene for effective sleep intervention.
Holmes et al. (2026) studied this question.