pii: jc-00370-13
http://dx.doi.org/10.5664/jcsm.4034
Average Heart Rates of Hispanic and Caucasian Adolescents
during Sleep: Longitudinal Analysis from the TuCASA Cohort
Kristen Hedger-Archbold, Ph.D.1; Seth T. Sorensen, M.A.2; James L. Goodwin, Ph.D.3; Stuart F. Quan, M.D., F.A.A.S.M.3,4
University of Arizona College of Nursing, Tucson, AZ; 2Department of Disability and Psychoeducational Studies, College of
Education, University of Arizona, Tucson, AZ; 3Arizona Respiratory Center, Department of Medicine, University of Arizona College
of Medicine, Tucson, AZ; 4Division of Sleep Medicine, Harvard Medical School, Boston, MA
S C I E N T I F I C I N V E S T I G AT I O N S
1
Objective: The current study describes sleeping heart rate
patterns in an adolescent cohort of Hispanic and Caucasian
children over approximately a 5-year period to determine
how sex, ethnicity, and body mass index (BMI) contribute to
sleeping heart rate patterns over time.
Methods: Participants were recruited from a large urban school
district in the southwest United States as part of the Tucson
Children’s Assessment of Sleep Apnea Study (TuCASA). Heart
rate data was obtained through electrocardiogram (ECG)
recordings during in-home polysomnography, approximately
5 years apart. Second-wave cohort data were analyzed to
determine how age, sex, ethnicity, physical activity, and
BMI contribute to average sleeping heart rates. The same
variables were used to investigate how sleeping heart rate
patterns change longitudinally from school-age (6–11 years) to
adolescence (10–17 years) during sleep.
Results: Female adolescents had significantly faster average
heart rates during sleep. Sleeping heart rate decreased
significantly with increasing age in the adolescent cohort.
Although the Hispanic group had a statistically significant higher
body mass index than Caucasians, there were no significant
differences in heart rate observed between ethnicities or in
those who were classified as obese (BMI ≥ 95th percentile
for age). Longitudinal analysis between the school-aged and
adolescent cohort revealed a significant overall decrease in
heart rate across a 5-year period.
Conclusions: Hispanic and Caucasian adolescents experience
a similar decrease in sleeping heart rate with age. Female
adolescents had significantly faster heart rates than males, and
no significant differences were observed between Caucasians
and Hispanics, or obese vs. nonobese adolescents.
Keywords: adolescents, heart rate, polysomnography
Citation: Hedger-Archbold K, Sorensen ST, Goodwin JL,
Quan SF. Average heart rates of Hispanic and Caucasian
adolescents during sleep: longitudinal analysis from the
TuCASA cohort. J Clin Sleep Med 2014;10(9):991-995.
S
leep parameters in adolescents and school-aged children
have been increasingly characterized in recent years1;
however, despite being regularly recorded during overnight
polysomnography (PSG), limited data on normative heart rate
patterns during sleep have been reported. There are currently
available data for sleeping heart rates in infants2 and schoolaged children,3 as well as heart rates during wakefulness in adolescents,4,5 but there remains a paucity of published information
regarding adolescent heart rates during sleep. The current study
first aimed to describe average heart rates of healthy adolescents during sleep, and to determine the relationships between
age, sex, body mass index (BMI), physical activity, and ethnicity (Caucasian/Hispanic) on nocturnal heart rates. Second, the
study aimed to determine the changes in sleeping heart rates
experienced in a cohort of healthy children over a 5-year time
period, and determine if sex, ethnicity, and BMI during schoolage years contributed to variability in sleeping heart rates for
adolescents.
BRIEF SUMMARY
Current Knowledge/Study Rationale: Little is known about heart
rate patterns during sleep for adolescents and how these patterns may
change over a 5-year period. We aimed to describe and determine the
relationships between age, sex, body mass index (BMI), physical activity and ethnicity on nocturnal heart rate patterns in a cohort of healthy
adolescents.
Study Impact: No significant differences were found between obese
vs. non-obese, Caucasian vs. Hispanic adolescents in nocturnal heart
rates, although female adolescents had significantly faster heart rates
than males at all time points. Levels of physical activity and fitness may
be an important contributor to the observed sex differences in nocturnal
heart rate and should be investigated in future work.
described.6 In brief, the TuCASA cohort includes generally
healthy school-aged children who were recruited from a large
urban school district in the Southwest United States. With the
cooperation of their respective elementary schools, parents of
the students were asked to complete a brief screening questionnaire (N = 2,327) and to provide contact information if they
wanted to see if their child was eligible for the study. Those who
qualified were then studied using a single overnight unattended
in-home polysomnography (PSG) along with completion of a
questionnaire regarding their sleep habits. TuCASA initially recruited 503 participants (ages 6–11 years) who had their PSGs
recorded between the years of 2000 and 2004 (TuCASA 1).
METHODS
Participants
The Tucson Children’s Assessment of Sleep Apnea study
(TuCASA) is a longitudinal cohort that has been previously
991
Journal of Clinical Sleep Medicine, Vol. 10, No. 9, 2014
K Hedger-Archbold, ST Sorensen, JL Goodwin et al.
second. Sleep staging was scored according to Rechtschaffen
and Kales criteria.8 The RDI was defined by the number of apneas and hypopneas per hour of sleep that were also associated
with at least 3% oxygen desaturation (RDI > 3%).
Figure 1—Flow Diagram of Participant Selection
2,327 participants completed TuCASA 1 questionnaire
↓
503 participants (Ages 6-11) underwent PSG TuCASA 1
↓
319 participants (ages 10-17) underwent PSG TuCASA 2
↓
163 participants (TuCASA 2) had valid ECG recordings
↓
(N = 22 excluded RDI ≥ 1 ; 2 outliers high BP) 139 participants
(TuCASA 2) retained in cross sectional analyses
↓
103 participants included (TuCASA 1 & 2) for longitudinal
analyses with valid ECG and RDI ≤ 1 at both time points
Assessment of Physical Activity
As a surrogate for fitness level, the Block Kids Physical Activity Screener was used to assess the children’s daily physical
activity levels (http://www.nutritionquest.com), which is designed for school-age children aged 8–17 years to complete by
themselves. The Screener inquires about frequency and duration of activities in the past week, then computes an estimation
of the average amount of total kilocalories (kcals) expended by
that child on a daily basis.
Data Analysis
BMI percentiles were determined based on height and
weight charts provided online from the Center for Chronic Disease Prevention and Health Promotion.9 Obesity was defined as
having a body mass index (BMI) ≥ 95th percentile compared to
same aged peers. Mean sleeping heart rates were determined
for each stage of sleep and were weighted according to percent
time in each sleep stage to obtain an overall average during the
entire time spent asleep. Parent reports of sleep behavior the
night before and morning after the PSG were used to obtain
estimates of the time the adolescent went to bed and the time
they awoke in the morning.
Independent sample t-tests were used to determine whether
heart rate varied according to sex, ethnicity, physical activity,
and BMI during adolescence (TuCASA 2 PSG). Cohen’s d was
used to measure effect size. t-tests with equal variances not assumed were used to compare Caucasians to Hispanics due to
unequal sample sizes. Least square means analysis of variance
models were used to control for covariates with age. To determine how heart rate changed from baseline to follow-up for
independent variables of gender and ethnicity, a longitudinal
analysis was conducted using repeated measures ANOVA. All
analyses were conducted using SPSS version 20.0 (IBM, SPSS,
Chicago, IL). Data are presented as mean ± SD or percentages
as appropriate.
Approximately 5 years later, researchers attempted to contact the initial 503 participants and were able to obtain valid
in-home PSG recordings with 319 children (TuCASA 2). From
this group of 319 children, 163 (51.1%) had valid recorded
ECG heart rates during PSG. From this group of 163 children
with valid ECG data, 22 were found to have some degree of
sleep disordered breathing (SDB), and so were excluded from
analyses (SDB was defined as the respiratory disturbance index [RDI] ≥ 1 and associated with > 3% oxygen desaturation7).
Two additional outlier cases who had hypertension (142/90 and
134/86, respectively) were also excluded from analyses, yielding a sample size for cross-sectional analyses of N = 139 participants from TuCASA 2 (Figure 1).
For the purposes of longitudinal analysis, we wanted to determine the change over time from sleeping heart rate from TuCASA 1 to TuCASA 2 PSG. Therefore, to create within subject
pairs for analyses, 34 participants with the presence of SDB
at TuCASA 1, and 2 participants with insufficient ECG data
(< 6 h of HR signal recorded) at TuCASA 1 were excluded.
The resulting sample of N = 103 was then used in longitudinal
ANOVA analyses.
Average heart rates were calculated from the PSGs and were
also characterized by body position (supine and other), REM,
and NREM stages.
RESULTS
Polysomnography
Adolescent Sleeping Heart Rates (TuCASA 2)
On the night of the their baseline and follow-up PSG, a
2-member, mixed-sex team came to the participant’s home
approximately an hour prior to the child’s normal bedtime, as
determined by parental report. At this time, informed consent
from the parent or guardian, and assent from the child were
obtained, as well as anthropometric measures of height, weight,
and blood pressure. The single night PSG was recorded on
both occasions using a Compumedics PS-2 system (Abbotsford, Victoria, Australia) with the following channel leads; C3/
A2 and C4/A1 electroencephalogram, right and left electroculogram, bipolar electromyogram, both thoracic and abdominal
plethysmography bands, airflow thermistor, nasal pressure cannula, snoring microphone, body position sensor, ambient light
sensor, finger pulse oximetry, and ECG. The ECG was recorded
using a single bipolar lead sampled at a rate of 64 cycles per
Journal of Clinical Sleep Medicine, Vol. 10, No. 9, 2014
Table 1 reports the demographic and sleep variables for the
3 groups of participants. Sleeping heart rates stratified by age
and gender are shown in Table 2. Results from the independent
sample t-tests within the adolescent group (N = 139) demonstrated that females (N = 69) had significantly faster heart rates
(68.2 ± 9.2) than males (63.1 ± 8.5); t137 = −3.36; p = 0.001,
d = 0.58 (Table 3). Additionally, Hispanic adolescents (N = 54)
had a significantly higher BMI percentile (73.2 ± 24.9) than
Caucasians (58.3 ± 30.7); t137 = −2.984; p = 0.002; d = 0.53)
(Table 4). While the difference in physical activity levels
between males and females was not statistically significant
(729.9 ± 729.9 vs. 527.8 ± 442.7; t106.5 = 1.95; p = 0.056, respectively) a trend in difference was noted. There were no significant differences in age or BMI between males and females,
992
Adolescent Heart Rates during Sleep
Table 1—Demographic and sleep variables across groups
Characteristic
M (SD)
Sex
Male
Female
Ethnicity
Caucasian
Hispanic
Age
BMI %ile
Bedtime
Wake time
N1%
N2%
N3%
N4%
REM%
REM (back) Avg HR
REM (other) Avg HR
NREM (back) Avg HR
NREM (other) Avg HR
Total Average HR
RDI 3% ≥ 1
a
Total PSG data for all Adolescents
(TuCASA 2)
(N = 319)
Cross Sectional Adolescents
(TuCASA 2)
(N = 139)
Longitudinal Adolescents
(TuCASA 1 & 2)
(N = 103)
N = 162 (50.8%)
N = 157 (49.2%)
N = 70 (50.4%)
N = 69 (49.6%)
N = 46 (44.6%)
N = 57 (55.3%)
N = 205 (64.3%)
N = 114 (35.7%)
13.3 (1.7)
63.6 (30.8)
22:01 (1:24)
6:50 (1:05)
3.9 (2.3)
55.4 (6.9)
3.8 (1.8)
14.7 (6.4)
22.7 (4.7)
67.1 (12.2)
66.6 (11.4)
65.6 (9.9)
64.5 (12.6)
66.1 (10.2) a
0.4 (0.6)
N = 86 (61.9%)
N = 53 (38.1%)
13.2 (1.7)
63.5 (29.3)
21:22 (1:05)
6:19 (1:14)
3.6 (1.9)
55.9 (6.6)
3.7 (1.7)
14.0 (5.9)
23.4 (4.2)
66.7 (12.1)
66.6 (10.9)
65.1 (9.6)
64.9 (10.2)
65.8 (9.9)
0.2 (0.3)
N = 64 (62.1%)
N = 39 (37.9%)
13.7 (1.7)
63.6 (29.6)
22:23 (1:08)
7:01 (1.09)
3.7 (2.1)
55.1 (6.2)
3.6 (1.6)
14.2 (5.6)
23.9 (4.1)
67.3 (9.6)
66.6 (9.7)
64.8 (9.4)
64.7 (9.2)
65.8 (9.1)
0.2 (0.2)
HR data derived from N = 163 valid ECG values.
Table 2—Healthy cross-sectional adolescent cohorts sleeping heart rate according to age and gender (N = 139).
Age-Group
10 – 11
12
13
14
15
16 – 17
Sample (N = 139)
(N = 27)
70.8 (9.4) [67.2, 74.5]
(N = 20)
67.1 (6.9) [63.7, 70.4]
(N = 33)
66.7 (9.8) [63.2, 70.2]
(N = 24)
63.4 (8.6) [59.8, 66.9]
(N = 24)
63.1 (7.1) [59.9, 66.1]
(N = 11)
59.3 (9.6) [53.2, 65.4]
Male (N = 70)
(N = 12)
67.7 (9.3) [61.5, 73.9]
(N = 13)
67.3 (8.7) [61.8, 72.9]
(N = 13)
64.4 (9.1) [58.6, 70.2]
(N = 13)
59.8 (6.1) [56.2, 63.9]
(N = 13)
62.1 (5.8) [58.5, 65.8]
(N = 6)
54.3 (5.6) [49.1, 59.5]
Female (N = 69)
(N = 15)
72.9 (9.1) [68.2, 77.6]
(N = 7)
66.7 (2.4) [64.4, 68.9]
(N = 20)
68.1 (10.1) [63.4, 72.8]
(N = 11)
67.2 (9.6) [61.1, 73.3]
(N = 11)
64.1 (8.5) [58.4, 69.8]
(N = 5)
66.3 (10.0) [53.8, 78.7]
Values presented as mean, (SD) [95% confidence interval].
and no significant differences in age, physical activity, or average sleeping heart rates between Caucasian and Hispanic
adolescents.
Since no significant differences in average heart rates were
observed between the Caucasian and Hispanic groups, both
groups were combined in the least square means analysis of
variance models. Results from these analysis revealed that
overall sample heart rates decreased with age (F = 12.905,
p < 0.001) and female adolescents had significantly faster heart
rates than males through the adolescent years when controlling for age (F = 14.738, p < 0.001). There were no significant
differences observed in average heart rates in adolescents who
were classified as obese (N = 26) vs. nonobese (N = 115). A
small but significant difference was observed within individuals
comparing average heart rates during REM (66.7 ± 9.6) to
NREM (65.1 ± 9.3); t136 = 4.447; p < 0.001; d = 0.36. However,
when physical activity was entered into the model along with
gender, age, and BMI percentile, the difference between male
and female nocturnal heart rate was attenuated (66.6 ± 14.4 vs.
63.9 ± 14.3, p = 0.12, respectively), and failed to achieve statistical significance.
Change in Heart Rates 5 Years Later (TuCASA 1 & 2)
Longitudinal analysis of heart rates was conducted on N = 103
participants with an average duration of 4.5 (0.8) (min 2.7, max
7.3) years between PSG studies. Average change in body mass
index was an increase of 3.1%. There were no significant relationships found between change in BMI and change in overall
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Journal of Clinical Sleep Medicine, Vol. 10, No. 9, 2014
K Hedger-Archbold, ST Sorensen, JL Goodwin et al.
Table 3—Age, BMI, and heart rate stratified by gender
(N = 139)
Age
BMI %ile
HR
Physical Activities
(kcal/day)
Male
(N = 70)
13.7 (1.8)
62.4 (29.7)
63.1 (8.5)
729.9 (729.9)
Female
(N = 69)
13.6 (1.7)
65.6 (29.3)
68.2 (9.2)
527.8 (442.7)
Table 4—Age, BMI, and heart rate stratified by ethnicity
(N = 139)
p value
0.579
0.527
0.001
0.056
Age
BMI %ile
HR
Physical Activity
(kcals/day)
Caucasian
(N = 85)
13.5 (1.8)
58.3 (30.7)
65.9 (9.8)
558.7 (628.3)
Hispanic
(N = 54)
13.8 (1.7)
73.2 (24.9)
65.7 (10.6)
735.8 (562.9)
p value
0.288
0.002
0.424
0.100
p values from independent samples t-tests comparing males vs. female
adolescents.
p values from independent samples t-test comparing Hispanic and
Caucasian adolescents.
heart rate, REM heart rate, or NREM heart rate (p > 0.05). Similarly, no significant relationships were observed between duration of time between time points on any heart rate measure. As
a result, neither was entered as a covariate in analysis.
Results from the ANOVA investigating changes in overall
heart rate over time revealed a significant decrease between
baseline (76.8) and follow-up (65.8) of 11 BPM in overall heart
rate (F1, 99 = 92.60, p < 0.001, η2 = 0.48). There were no significant main effects or interactions for gender (p = 0.73) and/
or ethnicity (p = 0.07) on change in overall average heart rates.
Significant decreases between time points were also observed
for average heart rates during REM between baseline (79.1)
and follow-up (66.9); F1, 98 = 54.12, p < 0.001, η2 = 0.36. Similar to overall heart rates, there were no main effects or interaction with gender (p = 0.99) and/or ethnicity (p = 0.13). Lastly,
changes in average heart rates during NREM sleep also significantly decreased from baseline (74.7) to follow-up (64.8);
F1, 99 = 105.6; p < 0.001; η2 = 0.52. Consistent with overall and
REM heart rates, there was no main effect observed on gender
(p = 0.68); however, a significant main effect was observed on
ethnicity (F1, 99 = 4.45, p = 0.04, η2 = 0.04), with Hispanic youth
demonstrating an accelerated decrease in NREM heart rate
from school-aged years (76.8) to adolescence (64.2) compared
to Caucasian youth (73.4 to 65.1).
had no health problems and were free from cardiorespiratory
morbidity using a single in-lab nocturnal PSG. Findings from
the study highlighted a significant decrease in heart rate during
both wakefulness and sleep at each of the age groups studied,
and found females to have significantly faster heart rates during
sleep. Corroborating findings from our current study, the investigators also found that heart rates during REM were significantly
faster than NREM. Our results extend these previous findings by
documenting them in a home environment, demonstrating their
occurrence in a longitudinal cohort containing Hispanics, and
exploring the role of fitness as an explanatory variable.
Compared to waking heart rates, sleeping heart rates observed in Hispanic and Caucasian adolescents in the present
study appear to be approximately 15% to 20 % slower than
published normative heart rates during wakefulness.4 Similar
to our previous study when this cohort was younger, there were
no significant differences found between sleeping heart rates in
Hispanics and Caucasians; however, it should be noted that this
is a finding that does not apply to all ethnic groups, as there is
evidence that African American children may have faster heart
rates during sleep.3
In contrast to findings in the adult and pediatric literature,
obese participants in our study did not have comparably faster
heart rates.11 One explanation for this may be due to our sample
having a relatively high average BMI compared to equal aged
peers. Average BMI observed in our sample was at the 66th percentile, suggesting that even though otherwise healthy, the adolescents in our study were heavier than same-aged peers, and
may have had elevated heart rates compared to a more representative sample. Additionally, numerous participants approached
and exceeded the 85th percentile classifying them as overweight9; thus the 95th percentile for classifying obese subjects in
our sample may not discriminate differences when applying this
clinical cutoff to the groups’ average sleeping heart rates.
Resting daytime pulse rate is generally accepted as a marker
of underlying physical fitness in children.12 In our study we
assessed physical activity using a validated self-administered
questionnaire as a surrogate for fitness in our cohort. We found a
nonsignificant trend for higher physical activity levels in males
than females (p = 0.056) and when included in our multivariate
models explained much of the difference in sleeping heart rates
between genders. Resting daytime heart rate in adolescents has
been shown to be inversely correlated with fitness levels.13 Our
results extend these previous observations to heart rate during
sleep. They also suggest that some of the differences in sleeping
DISCUSSION
Consistent with sleeping heart rates in school-aged children,
Hispanic and Caucasian adolescents ages 10 to 17 years old had
sleeping rates that decreased significantly as age increased. Females in this cohort had consistently faster average heart rates
than males. On average, healthy female heart rates were approximately 5 beats per minute faster than males, and heart rate
decreased with each advancing year during adolescence. There
was also a significant difference between average recorded
heart rates between sleep stages, with ECG recordings during
REM yielding higher rates than NREM. Furthermore, level of
fitness appeared to explain some of the differences in heart rate
between genders.
Although reports of normative values for heart rate during sleep are rare in the literature, the findings in the current
study appear to be consistent with a recently described cohort
by Scholle and colleagues investigating healthy German youth
of Caucasian ancestry.10 The researchers investigated children
and adolescents between the ages of 1 and 18 years old who
Journal of Clinical Sleep Medicine, Vol. 10, No. 9, 2014
994
Adolescent Heart Rates during Sleep
heart rate between genders in adolescents may be explained by
fitness levels rather than inherent differences between males
and females. However, further studies will be needed to confirm these observations.
Although our study utilized a generally healthy cohort of
children and adolescents to minimize the impact comorbid
symptoms and cardiorespiratory problems would have on ECG
recordings, the study has some limitations. First, the extent
heart rate parameters during sleep differ between unattended
in-home and in-lab PSGs remains unknown. Scholle and colleagues found that there was a first-night effect on sleeping
heart rates in comparison to the second night in lab recordings
with second-night recordings having slower heart rates by approximately 1 to 2 beats per minute.10
Secondly, in the current study our sample initially consisted
of 319 participants who underwent PSGs, yet only 163 (51.1%)
of our participants had valid recorded heart rates during the inhome PSG, suggesting the possibility that the ECG lead may
be more easily dropped during in-home PSGs than in-lab recordings. Thirdly, fitness level in this study was ascertained by
questionnaire. Thus, there may be greater variability than if a
cardiopulmonary exercise test had been performed. However,
we believe that any error would be non-differential, and thus
unlikely to alter our findings.
Lastly, although bedtime and wake time were available to
investigate sleep routine, there was no known information regarding alternative bed time behaviors such as playing video
games14 or consuming caffeinated beverages,15 which may have
an impact on sleeping heart rates.
The current study presents data from a generally healthy
prospective cohort of Hispanic and Caucasian children and
adolescents that allowed for exclusion of children and adolescents who have evidence of sleep disordered breathing. In
adult patients with sleep apnea, there is evidence that they may
have lower heart rate variability and higher heart rates in comparison with controls matched for age, gender, and BMI,16 and
an increase in sympathetic drive may be present in those with
OSA even during wakefulness.17 Future research should further
investigate potential racial differences, physical activity or fitness levels, and the impact BMI and sleep apnea have on heart
parameters during sleep.
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rate patterns during sleep are altered in preterm-born infants: implications for
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rate parameters during sleep for children aged 6 to 11 years. J Clin Sleep Med
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12. Peters H, Whincup PH, Cook DG, Law C, Li L. Trends in resting pulse rates
in 9-11 year-old children in the UK 1980-2008. Arch Dis Child 2014;99:10-14.
13. Tell GS, Vellar OD. Physical fitness, physical activity, and cardiovascular disease
risk factors in adolescents: The Oslo Youth Study. Prev Med 1988;17:12-24.
14. Ivarsson M, Anderson M, Akerstedt T, Lindblad F. Playing a violent television
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SUBMISSION & CORRESPONDENCE INFORMATION
Submitted for publication October, 2013
Submitted in final revised form April, 2014
Accepted for publication April, 2014
Address correspondence to: Kristen Hedger Archbold, R.N., Ph.D., College of
Nursing, University of Arizona, 1305 N., Martin P.O. Box 210203, Tucson, AZ 85721;
Tel: (520) 626-0828; E-mail:[email protected]
DISCLOSURE STATEMENT
REFERENCES
This was not an industry supported study. TuCASA was supported by HL62373.
The authors have indicated no financial conflicts of interest.
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Journal of Clinical Sleep Medicine, Vol. 10, No. 9, 2014