Actigraphic sleep dimensions and associations with academic functioning among adolescents

Mathew, Gina Marie; Reichenberger, David A; Master, Lindsay; Buxton, Orfeu M; Chang, Anne-Marie; Hale, Lauren

doi:10.1093/sleep/zsae062

Abstract

Study Objectives

There is mixed evidence regarding associations of sleep duration with academic functioning in adolescents and a lack of research on other sleep dimensions, particularly using objective sleep measures. We examined associations of multiple actigraphic sleep dimensions with academic functioning among adolescents.

Methods

Data were from the sleep sub-study of the age 15 wave of the Future of Families and Child Wellbeing Study (n = 774–782; 52% female), a national, diverse sample of teens. Adolescents wore wrist-actigraphs for ~1 week and completed a survey reporting academic performance and school-related behavioral problems. Regression models assessed whether average sleep duration, timing, maintenance efficiency, and SD-variability were associated with self-reported academic functioning in cross-sectional analyses adjusted for demographic characteristics, depressive symptoms, and anxious symptoms.

Results

Later sleep timing (hours) and greater sleep variability (SD-hours) were associated with poorer academic outcomes, including sleep onset variability with higher odds of receiving a D or lower (OR = 1.29), sleep onset (β = −.07), sleep offset (β = −.08), and sleep duration variability (β = −.08) with fewer A grades, sleep offset with lower GPA (β = −.07), sleep offset (OR = 1.11), sleep duration variability (OR = 1.31), and sleep onset variability (OR = 1.42) with higher odds of being suspended or expelled in the past 2 years, and sleep duration variability with greater trouble at school (β = .13). Sleep duration, sleep maintenance efficiency, and sleep regularity index were not associated with academic functioning.

Conclusions

Later sleep timing and greater sleep variability are risk factors for certain academic problems among adolescents. Promoting sufficient, regular sleep timing across the week may improve adolescent academic functioning.

Graphical Abstract

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actigraphy, sleep duration, sleep timing, sleep maintenance efficiency, sleep variability, sleep regularity index, academic functioning, adolescence

Statement of Significance

The present study examined associations between different dimensions of actigraphic sleep and several aspects of academic functioning in a large, diverse sample of adolescents in the United States. We found that later sleep timing and greater sleep variability were associated with poorer academic performance and more behavioral issues at school. Sleep duration, maintenance efficiency, and regularity index were not associated with academic functioning. The findings suggest that promoting sufficient, regular sleep timing across the week may help boost academic performance and reduce school-related behavioral issues among adolescents.

Introduction

More than 70% of adolescents in the United States obtain fewer than the 8 to 10 hours of sleep nightly [1] recommended for optimal health and well-being [2]. Short sleep has been linked to suboptimal functioning in adolescents, including poorer cognitive performance [3]. Some studies have demonstrated associations of short sleep duration with poor academic performance [4–13] and school-related behavioral problems among adolescents, including more academic-related anxiety [5], skipping classes [14], and school absences [15]. However, other studies found either no association between sleep duration and academic performance [14, 16–26] or that shorter sleep was linked with better academic performance [27]. The association between sleep and academic functioning among adolescents is therefore unclear but may be explained by other dimensions of sleep health.

Sleep health is a multidimensional construct that in addition to duration includes timing, sleep efficiency, and regularity [28], all of which may also be associated with academic functioning. As children enter adolescence, many experience a shift toward later preferred timing of sleep and other activities (i.e., chronotype) [29]. Later self-reported [19] and actigraphic [25] sleep timing and greater self-reported evening preference [21, 26, 30–32] are associated with poorer academic performance in adolescents. The evidence for sleep efficiency, which represents sleep continuity and may denote better sleep quality, is mixed; some studies demonstrated associations of higher self-reported [8] and actigraphic [26] sleep efficiency with adolescent academic functioning, whereas others found no significant associations when using actigraphy [16, 25]. Additional research is therefore warranted to investigate the associations of objectively measured sleep timing and efficiency with academic functioning in adolescents.

Early morning obligations such as school [33] shorten the opportunity between when adolescents prefer to go to sleep and when they must wake up, promoting misalignment of sleep timing across the week and sleep variability [34]. There is limited research on the associations of variability in sleep duration, variability in sleep timing, and sleep regularity index (SRI) with adolescent academic functioning. One study in 315 Icelandic adolescents demonstrated an association between actigraphic variability in sleep duration and poorer academic performance [25], and another study in 265 US adolescents found an association between actigraphic SRI and better grades [35]. In another study of 542 Italian adolescents, actigraphic social jetlag was associated with lower GPA [4], but actigraphic sleep timing and variability were not associated with school grades in another study of 80 Canadian adolescent girls [10]. Therefore, the evidence for an association between sleep variability and poorer academic functioning in adolescents is mixed.

There is moreover a lack of research on the associations between dimensions of sleep and aspects of academic functioning other than performance, such as skipping school, suspensions and expulsions, and trouble getting along with teachers and other students. Additionally, most studies that examine sleep and academic functioning in adolescents rely on self-reported sleep [5–9, 11, 13–15, 17–24, 27, 30–32, 36–38], which can deviate from objective measures such as actigraphy [39]. To the best of our knowledge, six studies [4, 10, 16, 25, 26, 35] have examined associations between actigraphic sleep and academic performance in adolescents, with sample sizes ranging from 36 [26] to 542 [4]; none of these examined school-related behavioral issues. Four of these six [4, 10, 25, 35] examined whether dimensions of sleep variability were associated with academic performance, with sample sizes ranging from 80 [10] to 542 [4]. Therefore, additional research that examines the link between different dimensions of sleep and several aspects of academic functioning, including behavioral issues, in a large sample of adolescents is warranted.

The present study examined whether several dimensions of actigraphic sleep were associated with academic functioning, including academic performance and behavioral issues in school, among a large, diverse sample of nearly 800 US adolescents. We hypothesized that shorter sleep duration, later sleep timing, lower sleep efficiency, and greater sleep variability would be associated with poorer academic functioning.

Materials and Methods

Participants

Data for the present analyses come from the Future of Families (named Fragile Families at the time of data collection) and Child Wellbeing Study (FFCWS; ffcws.princeton.edu), a longitudinal birth cohort oversampled for nonmarital births, which resulted in a greater proportion of racial/ethnic minority mothers and those of lower socioeconomic status and education level compared to the national US population. More details regarding the sample and design may be found elsewhere [40]. This study was conducted according to the guidelines established in the Declaration of Helsinki of 1975 (revised 1983), and all procedures involving human participants were approved by the Princeton University and Stony Brook University (CORIHS B; FWA #00000125) Institutional Review Boards. Written (for in-home interviews) or recorded verbal (for phone interviews) informed consent was obtained from primary caregivers (91% biological mother, 6% biological father, and 3% nonbiological parent), and assent was obtained from adolescents.

The research survey firm Westat^® communicated with the participants, obtained informed consent, distributed the actigraphy devices, and compensated the participants. Westat paid participants through pre-paid gift cards sent through postal mail. Parents received $100 USD for completion of the one-time parent survey. Adolescents received $50 USD for completion of the one-time youth survey and $50 for wearing the actigraphy device.

The original FFCWS birth cohort consists of 4898 children born from 1998 to 2000 in 20 large US cities [41]. Families were recruited from local hospitals at the time of the child’s birth. Study staff maintained records about the participants and their families for follow-up at subsequent waves, when participants were approximately ages 1, 3, 5, 9, and 15 years of age. Families were eligible for inclusion in the year 15 follow-up wave if the child was alive, not legally adopted by another family, and participated in the year 9 wave. Data in the present cross-sectional analyses were collected from February 2014 to February 2016. During the year 15 wave of the FFCWS (wave 6), 3444 adolescents and their primary caregivers completed separate surveys querying household and demographic characteristics, administered either over the phone or in person at the participant’s place of residence. A randomly selected subsample (n = 1090) were asked to participate in a FFCWS sub-study [42]. Adolescents who assented to participation (n = 1049) were administered the survey and given wrist-worn accelerometers to measure sleep for seven consecutive days at their in-person interview. Out of 1049 assenting adolescents, n = 237 were excluded due to providing fewer than three valid nights of actigraphy recordings (refer to the “Wrist actigraphy” section; present sample M ± SD = 6.6 ± 2.0 nights per adolescent; range 3–16; interquartile range, IQR 5–8), n = 3 were excluded due to not providing complete demographic and household data, n = 27 were excluded due to not reporting grades for at least two of the four subjects, n = 0–7 were excluded due to not answering survey questions on academic functioning outcomes (number varies depending on the specific outcome), and n = 1 was excluded from SRI analyses only due to an invalid SRI, leaving a sample of n = 774–782 adolescents (73.8%–74.5% of the subsample; participant flow chart in Supplementary Figure S1). Sex, race/ethnicity, and income were not associated with missingness from the largest analytical sample of n = 782 versus the n = 1049 who assented to the sub-study (all p ≥ .05). Study method and results are reported following the Strengthening of the Reporting of Observational Studies in Epidemiology (STROBE) statement for cross-sectional studies in Supplementary Table S1 [43].

Materials and measures

Wrist actigraphy and nightly sleep predictors

Sleep measures were collected with a wrist-worn accelerometer with off-wrist detection (Actiwatch Spectrum; Philips-Respironics, Murrysville, PA), and study participants were asked to wear the watch on their nondominant wrist for 1 week. Accelerometer devices measure movements, from which patterns of sleep and wake may be estimated [44]. Device data were downloaded with Philips Actiware software (Version 6.0.4, Philips Respironics, 2017). At least two independent scorers (blinded to each other) determined cut-point (i.e., start and end time that define a 24-hour day), validity of days, and sleep intervals with a duration of ≥ 30 minutes using a validated procedure [45]. Differences between the scorers in the determination of the number of valid days, cut-point, number of sleep intervals, and any >15-minute differences in duration or wake after sleep onset for each recording were compared and adjudicated, with a third scorer adjudicating any remaining discrepancies. The scorers determined sleep intervals using a decrease in activity levels (medium-activity threshold of 40 activity counts/minutes) and the aid of light levels for sleep onset and offset [46], and a nighttime sleep interval was split into two intervals (main sleep and nap) if there was an awakening ≥ 1 hour during this interval. Sleep measures within the present study were based on data from the main nighttime sleep interval and did not include naps (except SRI, which was based on 24-hour sleep-wake patterns). No sleep intervals were set if the duration was less than 30 minutes. A sleep actigraphy day was determined invalid and no sleep interval was set if there were ≥ 4 total hours of off-wrist time, with the exception of the first and last day (device should have been worn at least 2 hours on the first day). Other invalidation criteria were constant false activity due to battery failure, data unable to be retrieved or recovered, or an off-wrist period of ≥ 60 minutes within 10 minutes of the scored beginning or end of the main sleep period for that day. Nights were excluded from present analyses if the adolescent had an all-nighter (i.e., no sleep interval was set within that 24-hour day; n = 2 days). The distribution of the month of actigraphic data collection per adolescent (first sleep period’s wake date/time) is presented in Supplementary Table S2.

Nighttime sleep onset and sleep offset were the person-average start and end of the main nighttime sleep interval (i.e., when an adolescent fell asleep at night and woke up the next morning, respectively) calculated in hours from midnight. Nighttime sleep duration was calculated as the person-average number of hours between sleep onset and sleep offset of the main nighttime sleep interval. Nighttime sleep maintenance efficiency represents the person-average percentage of sleep duration that the individual spent asleep during the main nighttime sleep interval and was calculated as 1−(WASO in hours / sleep duration in hours) and multiplied by 100 to produce a percentage [47–50]. The term “sleep maintenance efficiency” is used instead of the more common “sleep efficiency” due to exclusion of sleep onset latency in the calculation, which is typically represented in calculations of sleep efficiency. Variability in nighttime sleep duration, onset, and offset across the monitoring period were each represented by the person-standard deviation (SD) per adolescent. Another type of sleep variability was the SRI [51]. SRI was calculated per person based on the formula from Phillips et al. [51] from 24-hour sleep/wake patterns and ranges from 0 (low regularity) to 100 (high regularity). The score encapsulates within-person sleep patterns and represents the percentage probability that an individual is in the same state (sleeping or awake) at any two-time points 24 hours apart, averaged across all days. A score of 0 indicates the individual is sleeping and waking totally at random, whereas a score of 100 indicates the individual is sleeping and waking at exactly the same times each day.

Academic functioning outcomes

Academic functioning was assessed on the year 15 survey, which was administered once to adolescents and their primary caregivers in person.

Adolescents reported their academic performance as letter grades in the subjects of English, mathematics, history or social studies, and science with the question, “At the {most recent grading period/last grading period in the spring} what was your grade in …” with the answer options of “A” (1), “B” (2), “C” (3), “D or lower” (4), or “No grade or pass/fail” (5). The answer for each subject was recoded to correspond to a grade point average on the 0–4 scale, with A recoded to 4, B to 3, C to 2, and D or lower to 0.5 (representing the average between D and F). An answer of “5” was recoded as missing. Variables of interest included the odds of receiving a D or lower in any course; the percent of courses one received an A; and average GPA (0.5–4) across all four courses (Cronbach's alpha = .69).

Adolescents were also asked about behavioral academic functioning. Skipped school during the last school year was assessed with the question, “{During this school year/During the last school year}, did you ever skip school for a full day without an excuse?” Been suspended or expelled in the past 2 years was assessed with the question, “Have you been suspended or expelled from school in the past 2 years?” Both questions also had options “Yes” (1) and “No” (2), with “No” recoded to 0. Adolescents were also asked four questions related to general trouble in school modeled after questions in the National Longitudinal Study of Adolescent Health (Add Health) Wave I In-School Questionnaire. They were presented with the prompt, “{Since school started this year/During the last school year}, how often {have you had/did you have} trouble … Would you say never, sometimes, or often?” with the items “Paying attention in school,” “Getting along with your teachers,” “Getting your homework done,” and “Getting along with other students.” The answer options were “Never” (1), “Sometimes” (2), and “Often” (3), and a trouble in school score was calculated as the average across all four items (Cronbach's alpha = .62).

Covariates

Depressive and anxious symptoms were assessed on the adolescent survey through five items derived from the Center for Epidemiologic Studies Depression Scale [52] and anxious symptoms were assessed through six items selected from the 18-item version of the Brief Symptom Inventory [53], both of which were created by the larger FFCWS team at Princeton University and Columbia University [42]. Adolescents selected their level of agreement with six statements expressing depressive or anxious symptoms: “strongly agree” (1) “somewhat agree” (2), “somewhat disagree” (3), and “strongly disagree” (4). A symptoms score was calculated as the average of item ratings (Cronbach's alpha: depressive symptoms = .76; anxious symptoms = .74) and reverse scored, with greater composite score indicating greater symptomology (i.e., 0 = strongly disagree, 3 = strongly agree).

Most demographic and household characteristics were reported on the year 15 adolescent or primary caregiver survey. Race/ethnicity was reported on the youth survey and grouped into exclusive categories of white/Caucasian (not Hispanic or Latino), black/African (not Hispanic or Latino), Hispanic and/or Latino (any race), or a category with other (including Asian, Central American/Caribbean, Native American/Alaska Native, and/or Native Hawaiian/Pacific Islander), multi-racial, and no reported race/ethnicity (all not Hispanic or Latino). The adolescent’s living arrangements (living with biological mother and father; not living with biological mother and father) were also reported on the youth survey. Annual household income (in USD) and the primary caregiver’s highest education level (did not complete high school, completed high school, completed some college, or college graduate) were reported on the primary caregiver survey. Missing income values were imputed by the FFCWS staff at Princeton University through the Stata statistical software regression-based impute command with the following covariates: original sample city, total adults in the household, and primary caregiver age, years of education, race/ethnicity, earnings, immigrant status, employed last year, hours worked, welfare receipt, and marital status. Sex information was collected at birth, and age was reported at the in-person year 15 interview.

Statistical analyses

Analyses were conducted in SAS 9.4 software (SAS Institute, Cary, North Carolina). Most variables met standards for normality (skew < |3| and kurtosis < |10|) [54]. The SDs of sleep onset and offset were positively skewed (skew ≥ 3) and/or leptokurtotic (kurtosis ≥ 10) and were winsorized (i.e., values 3 SDs above or below the mean were replaced with the nearest value that was within 3 SDs of the mean). Of 782 adolescents in the largest analytical sample, 15 sleep onset SD values and 11 sleep offset SD values were winsorized, after which they also met criteria for normality.

Main analyses

We used bivariate Pearson correlations to test associations among the dimensions of sleep and academic functioning. Logistic (for binary outcomes) or linear (for continuous outcomes) regression models were used to test whether each dimension of sleep (sleep duration, sleep onset, sleep offset, sleep maintenance efficiency, SD-variability in sleep duration, SD-variability in sleep onset, SD-variability in sleep offset, and SRI) separately predicted each academic outcome. In addition to a linear term for sleep duration, we also included a quadratic term (sleep duration × sleep duration) within the same model to test whether curvilinear associations existed between sleep duration and academic functioning outcomes. Age, sex, race/ethnicity, household income, primary caregiver education level, adolescent living arrangements, depressive symptoms, anxious symptoms, and the number of courses for which letter grades were reported were included as covariates in all analyses. Adolescents reporting grades for fewer than two courses (n = 27) were excluded from all analyses. Alpha < .05 (two-sided) was deemed statistically significant. Adjusted p-values were calculated within each set of similar sleep and academic measures based on the Benjamini-Hochberg adaptive false discovery rate (aFDR) [55] and presented in Supplementary Material.

Sensitivity and supplementary analyses

In sensitivity analyses, all models were further adjusted for the per-person percentage of nighttime actigraphy recordings that preceded a nonschool day (range: 0%–100%), defined as a wake day that was Saturday or Sunday, during the month of July or August, a federal holiday, the day after Thanksgiving, and/or during the winter break taken by most US schools. Supplementary analyses examined whether free night catch-up sleep (average sleep duration on nonschool nights − average sleep duration on school nights) and social jetlag, a misalignment of sleep timing on school versus nonschool nights (| average sleep midpoint on nonschool nights − average sleep midpoint on school nights | [34]), predicted academic outcomes. Only adolescents with at least one school and nonschool actigraphy night each were included, resulting in n = 568–572 adolescents in free night catch-up sleep and social jetlag analyses.

Results

Participant characteristics

The analytical sample ranged from 774 to 782 depending on the outcome. In n = 782, 52% (n = 405) were female with a mean age ± SD of 15.4 ± 0.6 years (range 15.0–18.0). Ethnoracial composition of the full sample was 45% black/African American (n = 352), 26% Hispanic or Latino (n = 201), 16% white/Caucasian (n = 126), and 13% other, multi-racial, or none (n = 103). Other sample information, including descriptive statistics for sleep variables, academic functioning outcomes, and covariates, is in Table 1. Refer to Supplementary Table S3 for correlations among types of sleep variability and Supplementary Table S4 for associations among aspects of academic functioning.

Table 1.

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Descriptive Statistics (n = 775–782)

Variable	n	Min–max	Mean or %		(SD or n)
Demographic and household characteristics
Age	782	15.00–18.00	15.35		(0.56)
Sex (female)^a	782	—	51.8	%	(405)
Race/ethnicity	782	—
Black/African American	782	—	45.0	%	(352)
Hispanic and/or Latino	782	—	25.7	%	(201)
White/Caucasian	782	—	16.1	%	(126)
Other,^b multi-racial, or none			13.2	%	(103)
Household income^c	782	$0–$530 000	$60 442		($59 306)
Primary caregiver’s education level
Did not graduate high school	782	—	17.1	%	(134)
Completed high school	782	—	17.9	%	(140)
Completed some college	782	—	45.5	%	(356)
Graduated from college	782	—	19.4	%	(152)
Lives with biological mother and father	782	—	29.4	%	(230)
Emotional health
Depressive symptoms (CES-D score)^d	782	0.00–3.00	0.61		(0.59)
Anxious symptoms (BSI-18 score)^e	782	0.00–3.00	0.81		(0.62)
Nighttime sleep % nonschool nights		0–100.00	49.08		(31.50)
Dimensions of nighttime sleep
Sleep duration (hours)	782	4.22–12.18	7.75		(1.01)
Sleep onset	782	16:30–06:19	0:30		(1:40)
Sleep offset	782	04:03–16:08	8:20		(1:45)
Sleep maintenance efficiency %	782	75.86–96.80	90.71		(2.93)
Variability in sleep duration (SD-hours)	782	0.20–5.40	1.64		(0.80)
Variability in sleep onset (SD-hours)	782	0.09–3.58	1.35		(0.71)
Variability in sleep offset (SD-hours)	782	0.00–4.64	1.60		(0.89)
Sleep regularity index^f	781	4.86–82.85	48.00		(13.60)
Academic functioning^g
Received a D or lower in any course	782	—	21.2	%	(166)
Percent of courses received an A	782	0.00–100.00	29.22		(31.25)
Average GPA^h	782	0.50–4.00	2.85		(0.73)
Skipped school during last school year	780	—	11.9	%	(93)
Was suspended/expelled in the past 2 years	778	—	25.3	%	(197)
Trouble in school scale (average score)ⁱ	775	1.00–3.00	1.82		(0.47)

Variable	n	Min–max	Mean or %		(SD or n)
Demographic and household characteristics
Age	782	15.00–18.00	15.35		(0.56)
Sex (female)^a	782	—	51.8	%	(405)
Race/ethnicity	782	—
Black/African American	782	—	45.0	%	(352)
Hispanic and/or Latino	782	—	25.7	%	(201)
White/Caucasian	782	—	16.1	%	(126)
Other,^b multi-racial, or none			13.2	%	(103)
Household income^c	782	$0–$530 000	$60 442		($59 306)
Primary caregiver’s education level
Did not graduate high school	782	—	17.1	%	(134)
Completed high school	782	—	17.9	%	(140)
Completed some college	782	—	45.5	%	(356)
Graduated from college	782	—	19.4	%	(152)
Lives with biological mother and father	782	—	29.4	%	(230)
Emotional health
Depressive symptoms (CES-D score)^d	782	0.00–3.00	0.61		(0.59)
Anxious symptoms (BSI-18 score)^e	782	0.00–3.00	0.81		(0.62)
Nighttime sleep % nonschool nights		0–100.00	49.08		(31.50)
Dimensions of nighttime sleep
Sleep duration (hours)	782	4.22–12.18	7.75		(1.01)
Sleep onset	782	16:30–06:19	0:30		(1:40)
Sleep offset	782	04:03–16:08	8:20		(1:45)
Sleep maintenance efficiency %	782	75.86–96.80	90.71		(2.93)
Variability in sleep duration (SD-hours)	782	0.20–5.40	1.64		(0.80)
Variability in sleep onset (SD-hours)	782	0.09–3.58	1.35		(0.71)
Variability in sleep offset (SD-hours)	782	0.00–4.64	1.60		(0.89)
Sleep regularity index^f	781	4.86–82.85	48.00		(13.60)
Academic functioning^g
Received a D or lower in any course	782	—	21.2	%	(166)
Percent of courses received an A	782	0.00–100.00	29.22		(31.25)
Average GPA^h	782	0.50–4.00	2.85		(0.73)
Skipped school during last school year	780	—	11.9	%	(93)
Was suspended/expelled in the past 2 years	778	—	25.3	%	(197)
Trouble in school scale (average score)ⁱ	775	1.00–3.00	1.82		(0.47)

Sleep was measured with nightly actigraphy (mean number of valid actigraphy nights per youth was 6.6 ± 2.0, range 3–16). Academic functioning was reported on a one-time year 15 survey administered to adolescents.

^aData collected at birth.

^bAsian, Central American/Caribbean, Native American/Alaska Native, and/or Native Hawaiian/Pacific Islander.

^cMissing values imputed by the Future of Families and Child Wellbeing Study staff at Princeton University through the Stata statistical software regression-based impute command with covariates original sample city, total adults in the household, and primary caregiver age, years of education, race/ethnicity, earnings, immigrant status, employed last year, hours worked, welfare receipt, and marital status.

^dBased on Center for Epidemiologic Studies Depression score; ranges from 0 (low) to 3 (high) [52]; Cronbach’s alpha = .76.

^eBased on 18-item Brief Symptom Inventory score; ranges from 0 (low) to 3 (high) [53]; Cronbach’s alpha = 74.

^fCalculated based on formula from Phillips et al.; ranges from 0 (low) to 100 (high) [51]. Includes 24-hour sleep.

^gCalculated from reported grades in English, mathematics, history or social studies, and science.

^hAverage of letter grades across courses, where A = 4, B = 3, C = 2, and D or F = 0.5; Cronbach’s alpha = .69.

ⁱItems in scale modeled after questions in the National Longitudinal Study of Adolescent Health (Add Health) Wave I In-School Questionnaire. Includes trouble "paying attention,” “getting along with teachers,” “getting homework done,” and “getting along with other students”; ranges from 1 (low) to 3 (high); Cronbach’s alpha = .62.

BSI-18, Brief Symptom Inventory-18; CES-D, Center for Epidemiologic Studies Depression scale; GPA, grade point average; max, maximum; min, minimum; n, number in sample; SD, standard deviation.

Table 1.

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Descriptive Statistics (n = 775–782)

Variable	n	Min–max	Mean or %		(SD or n)
Demographic and household characteristics
Age	782	15.00–18.00	15.35		(0.56)
Sex (female)^a	782	—	51.8	%	(405)
Race/ethnicity	782	—
Black/African American	782	—	45.0	%	(352)
Hispanic and/or Latino	782	—	25.7	%	(201)
White/Caucasian	782	—	16.1	%	(126)
Other,^b multi-racial, or none			13.2	%	(103)
Household income^c	782	$0–$530 000	$60 442		($59 306)
Primary caregiver’s education level
Did not graduate high school	782	—	17.1	%	(134)
Completed high school	782	—	17.9	%	(140)
Completed some college	782	—	45.5	%	(356)
Graduated from college	782	—	19.4	%	(152)
Lives with biological mother and father	782	—	29.4	%	(230)
Emotional health
Depressive symptoms (CES-D score)^d	782	0.00–3.00	0.61		(0.59)
Anxious symptoms (BSI-18 score)^e	782	0.00–3.00	0.81		(0.62)
Nighttime sleep % nonschool nights		0–100.00	49.08		(31.50)
Dimensions of nighttime sleep
Sleep duration (hours)	782	4.22–12.18	7.75		(1.01)
Sleep onset	782	16:30–06:19	0:30		(1:40)
Sleep offset	782	04:03–16:08	8:20		(1:45)
Sleep maintenance efficiency %	782	75.86–96.80	90.71		(2.93)
Variability in sleep duration (SD-hours)	782	0.20–5.40	1.64		(0.80)
Variability in sleep onset (SD-hours)	782	0.09–3.58	1.35		(0.71)
Variability in sleep offset (SD-hours)	782	0.00–4.64	1.60		(0.89)
Sleep regularity index^f	781	4.86–82.85	48.00		(13.60)
Academic functioning^g
Received a D or lower in any course	782	—	21.2	%	(166)
Percent of courses received an A	782	0.00–100.00	29.22		(31.25)
Average GPA^h	782	0.50–4.00	2.85		(0.73)
Skipped school during last school year	780	—	11.9	%	(93)
Was suspended/expelled in the past 2 years	778	—	25.3	%	(197)
Trouble in school scale (average score)ⁱ	775	1.00–3.00	1.82		(0.47)

Variable	n	Min–max	Mean or %		(SD or n)
Demographic and household characteristics
Age	782	15.00–18.00	15.35		(0.56)
Sex (female)^a	782	—	51.8	%	(405)
Race/ethnicity	782	—
Black/African American	782	—	45.0	%	(352)
Hispanic and/or Latino	782	—	25.7	%	(201)
White/Caucasian	782	—	16.1	%	(126)
Other,^b multi-racial, or none			13.2	%	(103)
Household income^c	782	$0–$530 000	$60 442		($59 306)
Primary caregiver’s education level
Did not graduate high school	782	—	17.1	%	(134)
Completed high school	782	—	17.9	%	(140)
Completed some college	782	—	45.5	%	(356)
Graduated from college	782	—	19.4	%	(152)
Lives with biological mother and father	782	—	29.4	%	(230)
Emotional health
Depressive symptoms (CES-D score)^d	782	0.00–3.00	0.61		(0.59)
Anxious symptoms (BSI-18 score)^e	782	0.00–3.00	0.81		(0.62)
Nighttime sleep % nonschool nights		0–100.00	49.08		(31.50)
Dimensions of nighttime sleep
Sleep duration (hours)	782	4.22–12.18	7.75		(1.01)
Sleep onset	782	16:30–06:19	0:30		(1:40)
Sleep offset	782	04:03–16:08	8:20		(1:45)
Sleep maintenance efficiency %	782	75.86–96.80	90.71		(2.93)
Variability in sleep duration (SD-hours)	782	0.20–5.40	1.64		(0.80)
Variability in sleep onset (SD-hours)	782	0.09–3.58	1.35		(0.71)
Variability in sleep offset (SD-hours)	782	0.00–4.64	1.60		(0.89)
Sleep regularity index^f	781	4.86–82.85	48.00		(13.60)
Academic functioning^g
Received a D or lower in any course	782	—	21.2	%	(166)
Percent of courses received an A	782	0.00–100.00	29.22		(31.25)
Average GPA^h	782	0.50–4.00	2.85		(0.73)
Skipped school during last school year	780	—	11.9	%	(93)
Was suspended/expelled in the past 2 years	778	—	25.3	%	(197)
Trouble in school scale (average score)ⁱ	775	1.00–3.00	1.82		(0.47)