26
Influence of sleep on obesity
ORIGINAL ARTICLE
Short sleep time increases lipid intake in obese
adolescents
Menor tempo de sono aumenta a ingestão de lipídios em adolescentes obesos
Flávia Campos Corgosinho3, Ana Raimunda Dâmaso2,3,4, Aline de Piano Ganen3,
Raquel Munhoz da Silveira Campos3, Patricia Leão Silva3, Priscila de Lima Sanchez3, Carolina Ackel-D’Elia3,
June Carnier5, Lian Tock3, Monica Levy Andersen1, Sergio Tufik1, Marco Túlio de Mello1
ABSTRACT
Objectives: The aims of the present study were to verify
whether sleep pattern could influence the food intake profile
as well as to examine the impact of body composition on sleep
pattern in obese adolescents. Methods: This is a cross-sectional
study comprised of 55 post-puberty adolescents (15 to 19 years
of age) with body mass indices greater than the 95th percentile.
The anthropometric variables analysed were waist circumference,
body weight, height, body mass index and body composition.
Nutritional data were obtained throughout a 3-day dietary
record, and sleep parameters were recorded using a 7-day sleep
diary. Statistical analyses were performed using multiple linear
regressions with significance set at p < 0.05, and the effect size
(r) was calculated for both models. Results: The models models
of multiple linear regression analyses adjusted by gender revealed
that body fat mass (kg) was an independent predictor of greater
influence of sleep latency and the total sleep time on lipid intake.
It was observed that a reduction in sleep time might contribute to
the development and maintenance of obesity through an increase
in fat intake. Furthermore, the data suggest that the total fat mass
might be associated with higher sleep latency, contributing with
a reduction in sleep duration, confirmed by an expressive effect
size. Conclusion: The results indicate that an association between
reduced sleep duration and irregular eating habits can promote a
vicious cycle difficult obesity control in adolescents.
Keywords: adolescent, body fat distribution, lipids, obesity, sleep,
sleep disorders.
RESUMO
Objetivos: Os objetivos do presente estudo foram verificar se o
padrão de sono poderia influenciar no perfil de ingestão alimentar,
assim como examinar o impacto da composição corporal no
padrão de sono de adolescentes obesos. Métodos: Estudo
transversal composto por 55 adolescentes pós-púberes (com idade
entre 15 e 19 anos), com Índice de massa Corporal (IMC) maior
que o percentil 95. As variáveis antropométricas analisadas foram a
circunferência da cintura, peso corporal, altura, IMC e composição
corporal. Os dados nutricionais foram obtidos através do registro
alimentar de 3 dias; e o padrão de sono foi obtido usando um
diário do sono de 7 dias. Análises estatísticas foram feitas usando
regressões lineares múltiplas, adotando p < 0,05 como significância.
O tamanho do efeito foi calculado para ambos os modelos.
Resultados: Ambos os modelos de regressão ajustados por gênero
mostraram que a gordura corporal (kg) foi um fator independente
para a latência do sono; e o tempo total de sono apresentou-se
como fator independente para ingestão de lipídios. Foi observado
que a redução no tempo total de sono pode contribuir para o
desenvolvimento e manutenção da obesidade, através de um
possível aumento da ingestão lipídica. Além disso, os dados
sugerem que a gordura corporal total pode estar associada com uma
maior latência pro sono, contribuindo com a redução do tempo
total de sono, confirmado pelo expressivo tamanho do efeito.
Conclusão: Os resultados indicam uma associação entre menor
tempo de sono e hábitos alimentares irregulares, levando à um ciclo
vicioso, dificultando o controle da obesidade em adolescentes
Descritores: adolescente, distribuição da gordura corporal, lipídeos,
obesidade, sono, transtornos do sono.
INTRODUCTION
Sleep curtailment is a very common occurrence in the current
today, especially among adolescents who are involved in many
activities such as school-related duties and recreational activities,
such as sports, social networking, and language course(1). It is
well documented that adolescents require more sleep than adults
and elderly people, and a minimum of 9 hours of sleep has been
recommended(2-4). Recently, studies have shown that sleep loss is associated with many health issues such as obesity and its co-morbidities(5-7). For instance, Gupta et al.(8) showed that each additional hour
of sleep decreased the odds of obesity by 80%. In agreement with
these findings, another study highlighted that obese individuals with
less sleep per night presented greater obesity severity, indicating the
importance of sleep for body weight homeostasis(9).
Concomitantly, obesity is a multifactorial disease that
affects millions of people worldwide, and one of the main
Study carried out at Departamento de Psicobiologia.
1
Departamento de Psicobiologia - Universidade Federal de São Paulo.
2
Departamento de Biociências - Universidade Federal de São Paulo.
3
Programa de Pós-Graduação em Nutrição - Universidade Federal de São Paulo.
4
Programa de Pós-Graduação em Ciências da Saúde - Universidade Federal de São Paulo.
5
Departamento de Nutrição - Universidade Federal de São Paulo.
Corresponding author: F.C. Corgosinho. Departamento de Biociências - Universidade Federal de São Paulo. Rua Prof. Francisco de Castro, nº 93. São Paulo - SP.
Brazil. CEP: 04020-050. Phone/Fax: 55 (11) 5572-0177. E-mail: [email protected]
Received: October 02, 2012; Accepted: February 23, 2013.
Sleep Sci. 2013;6(1):26-31
Corgosinho FC, Dâmaso AR, Ganen AP, Campos RMS, Silva PL, Sanchez PL, et al.
causes of obesity is the imbalance between energy intake and
expenditure. The incidence of obesity during adolescence
increases the chances of obesity in adulthood, which can reduce
the individual’s quality and duration of life and cause sleep
disorders(10-12).
Epidemiological data have shown a significant association
between weight gain and short sleep time(8). Furthermore, an
association between reduced sleep duration and irregular eating
habits, snacking between meals, excessive food seasoning and
low consumption of vegetables has been demonstrated(13-15).
In a recent study of South Korean adolescents, sleep time was
inversely associated with body mass index (BMI) levels, and
reduced sleep was strongly correlated with a greater risk of being
overweight and becoming obese(16). In fact, some studies have
suggested that altered pattern of the sleep-wake cycle and feeding
behaviour were associated with changes in body weight, although
the mechanisms by which short sleep contributes to increased
adiposity remain unclear(9,17). Moreover, emerging evidence
suggests that sleep-deprived humans have preferences for
energy-dense foods(18-20), although only a single study has tested
this hypothesis on teenagers and found a positive association
between less hours of sleep and increased carbohydrate intake(21).
Because sleep impairment can lead to nutritional
imbalance and obese adolescents already have detrimental
control of the energy balance(22), it is important to investigate
whether the total sleep time results in undesirable changes in
the food intake profile that underlies the connection between
insufficient sleep and obesity.
A single study showed that adult obese individuals have
longer sleep latency when compared with non-obese however,
it was not evaluated the possible association with adiposity
measures(23). In addition, it remains unknown the relationship
of sleep latency and body composition in obese adolescents.
Thus, the purpose of this current study was to verify whether
sleep time could exert a significant influence on the food intake
profile as well as determine the impact that body composition
has on latency of sleep among obese adolescents.
MATERIALS AND METHODS
Subjects
A total of 55 obese adolescents (15 to 19 years of age)
presenting simple obesity based on a body mass index (BMI)
> 95th percentile (Centers for Disease Control and Prevention)
entered the Interdisciplinary Obesity Program of the
Universidade Federal de São Paulo (UNIFESP) between January
2009 and 2010. The inclusion criteria for the post-pubescent
stage were based on the Tanner scale(24) stage 5 for both
boys and girls. Non-inclusion criteria were as follows: other
metabolic or endocrine diseases such as hypothyroidism
and Cushing Syndrome; chronic alcohol consumption;
previous use of drugs, such as anabolic-androgenic steroids,
psychotropics, anorectics, or hypoglycaemic, which may affect
appetite regulation; and pregnancy.
The study was conducted in accordance with the
principles of the declaration of Helsinki and was approved
by the Ethical Committee of the Universidade Federal de
São Paulo (# 0135/04) and registered in ClinicalTrials.gov
(NCT01358773). Informed consent was obtained from all
subjects and/or their parents.
Anthropometric variables and body composition
Subjects were weighed on a scale to the nearest 0.1 kg while
wearing light clothing but not shoes. Height was measured to the
nearest 0.5 cm with a wall-mounted stadiometer (Sanny, model
ES 2030), and waist circumference was measured with a nonstretchable tape measure and recorded to the nearest 0.1 cm.
The BMI was calculated as body weight divided by height
squared. Body composition was measured by plethysmography
in a BOD POD body composition system (version 1.69; Life
Measurement Instruments, Concord, CA, USA)(25).
Food variables
Energy intake was calculated based on a 3-day dietary record.
Because most obese people under-report their food consumption,
each adolescent was asked to record their diet with help from their
parents. Trained nutritionist instructed the subjects to record in as
detailed a manner as possible every item that they either drank or
ate, the time they ingested it, the amount consumed, and how the
food was prepared. The degree of under-reporting may still be
substantial; however, this is a validated method for the assessment
of dietary consumption(26). Portions were measured in terms of
familiar volumes and sizes. The dietician taught the parents and
adolescents how to record food consumption. The same dietician
transferred these dietary data to a computer, and the nutrient composition was analysed by a PC program developed at the Universidade
Federal de São Paulo (Nutwin software, for Windows, version 1.5)
that used data from western and local food tables. Parents were also
encouraged by a dietician to call if they needed extra information.
The distributions of the nutrients were analysed using the values
recommended by Dietary References Intakes (DRI)(27).
Sleep parameters
Sleep can be evaluated through many ways, and whereas the
polysomnography is the gold standard instrument, it requires
a high investment. Also, considering that polysomnographic
measurements are cumbersome and expensive, it was necessary
to select a suitable method for the sleep assessment(28). The
sleep diary is a validated subjective methodology in which the
patient takes notes of specific sleep variables during a week
that allows the calculation of important information such as
total sleep time, sleep latency, sleep efficiency, total time in bed,
awakenings, and the subject’s own perception of sleep(29). In
spite of its limitation, the sleep diary tends to be correlated with
objective measure of sleep(30). Therefore, a 7-day sleep diary was
used to record the following variables: nocturnal sleep time,
night awakenings, sleep efficiency, total time in bed, sleep latency
and how the volunteer perceived their sleep. Sleep efficiency
was determinated by the percentage of time spent asleep over
time from sleep onset (sleep latency) to last awakening, thus an
increased latency time can impair total sleep time.
Sleep Sci. 2013;6(1):26-31
27
28
Influence of sleep on obesity
Statistical analysis
The Gaussian distribution of variables was verified with a
Shapiro-Wilk’s W test, and variables with normal distribution
were expressed as mean ± standard deviation (SD) while
non-parametric variables were expressed as median (minimum
and maximum) in a descriptive table. The z-score of the
non-parametric variables was also obtained. A correlation study
was performed, but just as an exploratory method. Comparisons
between girls and boys were made using the independent t - test.
Two models of multiple regression analyses were performed.
In the first model the sleep latency was set as dependent model
while gender and fat mass (kg) were the independent variables
to verify how they could affect it. In the second model the total
sleep time was chosen as a dependent variable and gender as
well lipid intake (%) were the independent variables, to verify
how total sleep time could influence food patterns. The
magnitude of effect size was calculated in both models to
evaluate the reliability of the analyses (√t2/t2+df), considering
as an expressive result values above 0.3. The results with p
values < 0.05 were considered statistically significant. Statistical
analyses were performed using SPSS (version 18 for Windows).
RESULTS
The sample population totalled 55 volunteers of both genders
(35 girls and 20 boys) with a mean age of 17 years. The
descriptions of the analysed variables are shown in Table 1. All
anthropometric variables portray pathogenic obesity, including
a high percentile of fat mass, waist circumference higher than
recommended by the World Health Organization (WHO) and
reduction in the proportion of lean mass(31). Based on the
average BMI (37.26 kg/m2), most of the teenagers presented
class II obesity. Significant differences were found in the body
compositions based on gender, whereas boys presented greater
lean body mass (kg) and less percentage of fat mass. Boys also
presented higher values of waist circumference.
Table 1. Anthropometric characteristics of obese adolescents.
Variables
Entire group
(n = 55)
Girls
(n = 35)
Boys
(n = 20)
Body mass (Kg)
107.25 ± 17.02
104.40 ±
13.98
112.22 ± 20.80
BMI (Kg/m2)
37.26 ± 4.4
37.49 ± 4.39
36.81 ± 4.5
Fat mass (%)
46.25 ± 5.0
47.44 ± 4.7†
44.17 ± 5.1†
Lean mass (%)
53.4 ± 8.2
53.21 ± 7.97
53.92 ± 9.0
Fat mass (Kg)
50.4 ± 8.7
49.7 ± 7.3
51.85 ± 11.0
Lean mass (Kg)
57.48 ± 9.0
54.66 ± 7.30†
62.28 ± 10.65†
Waist circumference (cm)
101.8 ± 10.5
99.4 ± 9.4†
107.12 ± 10.56†
BMI: body mass index; † test t significant difference.
Regarding the food parameters, the mean distribution
of the macronutrients was within the Dietary Reference Intake
(DRI) recommendations: carbohydrates (52.8%), protein
(18.9%) and lipids (28.7%). Despite the mean of lipid intake
being within the recommendations, when we fractionated the
lipid profile by the percentage of Energy Intake (EI), the mean
Sleep Sci. 2013;6(1):26-31
values of saturated fat (9.73%), monounsaturated fat (7.3%)
or polyunsaturated fat (3.5%) did not reach the recommended
values(27). When it was analysed the food intake according to
gender, it was observed that boys showed a significantly higher
energy intake.
The data obtained from the sleep diary showed that
most of the adolescents (63.3%) slept less than 8 hours/night,
and 87.27% of them reported sleep latency lower than 30
minutes. The sleep efficiency was an important variance among
the teenagers; however, the differences in the sleep variables
between boys and girls were not statistical significant. Sleep
variables and dietary patterns are disclosed in Table 2.
Table 2. Sleep variables and dietary patterns of obese adolescents.
Entire group
Girls
Boys
Variables
(n = 55)
(n = 35)
(n = 20)
Total energy
intake
1824.61 ± 590.3
1693 ± 466.88†
2048.25 ± 719.64†
Lipid intake (%)
28.7 ± 5.3
28.62 ± 5.55
28.97 ± 4.97
Saturated fat
(%)
9.7 ± 2.7
9.77 ± 2.95
9.66 ± 2.55
Monounsaturated
fat (%)
7.3 ± 2.6
7,28 ± 2.95
7.33 ± 2.92
Polyunsaturated
fat (%)
3.5 ± 1.4
3.5 ± 1.26
3.65 ± 1.7
Carbohydrates
intake (%)
52.80 ±7.4
54.17 ± 6.66
50.47 ± 8.3
Protein Intake
(%)
18.9 ± 4.8
17.78 ± 3.51†
20.99 ± 6.08†
Total time
in bed (h)
8 ± 1.3
7.95 ± 1.26
8.10 ± 1.4
Total sleep time
(h)
7.5 ± 1.2
7.44 ± 1.20
7.6 ± 1.41
Sleep latency
(minutes)*
12.14 (3.4 - 46.4)
12.57 (3.4 - 37.1) 11.42 (4.85 - 46.42)
Sleep efficiency
(%)*
94.2 (41.0 - 97.7)
93.82 (41 - 97.7)
94.57 (86.65 - 97.34)
Well-being on
awakening (%)
72.04 ± 16.23
69.41 ± 15.57
76.8 ± 16.72
Sleep
satisfaction (%)
75.28 ± 16.23
73.5 ± 17.48
78.57 ± 17.25
* non-parametric data presented as median and minimum and maximum values, † test t significant
difference.
Two multiple linear regression analyses were performed
and in the first model adjusted by gender with sleep latency as
a dependent variable revealed that body fat mass (kg) was an
independent predictor (β = 0.48; p = 0.003) (r = 0.95) (Table 3).
In the second model, having the lipid intake (%) as a dependent
variable, demonstrated that total sleep time was a predictor
factor (β = -1.32; p = 0.02) (r = 0.91) (Table 4).
A negative association was discovered between total
sleep time and lipid intake (%), indicating that a reduced sleep
time increases lipid consumption. Additionally, a higher fat mass
was associated with longer time required for the volunteers to
fall asleep. The main findings of this study are illustrated and
hypothesized in Figure 1.
Corgosinho FC, Dâmaso AR, Ganen AP, Campos RMS, Silva PL, Sanchez PL, et al.
Table 3. Multiple regression analysis for sleep latency.
Sleep Latency
Regression Coefficient β
p
Gender
0.02
0.99
Body fat mass (kg)
0.48
0.003
Effect Size = (0.95).
Table 4. Multiple regression analysis for lipid intake (%).
Lipid intake (%)
Regression Coefficient β
p
Gender
0.45
0.76
Total sleep time
-1.32
0.02
Effect Size = (0.91).
Figure 1. The influence of sleep debt on lipid intake, suggesting a vicious cycle of
obesity maintenance.
DISCUSSION
In the present investigation, we demonstrate that fewer hours
of sleep can predict a higher consumption of lipids in obese
adolescents. Moreover, total fat mass might influence sleep
duration due to greater sleep latency, suggesting an intrinsic
pathway that can lead to a perpetuation of obesity and its
co-morbidities (Table 4 and Figure 1).
Emerging evidence suggests that short sleep time may
alter the balance between energy intake and energy expenditure.
Indeed, most researches have focused on the link between sleep
time and carbohydrate metabolism. However, analyses of the
influence of high fat intake upon sleep have demonstrated a
trend of reducing sleep duration between the highest and lowest
quartiles of fat intake in adults(32,33).
For the best of our knowledge, we showed for the first
time, an inverse association between total sleep time and lipid
consumption in adolescents, suggesting that obese teenagers with
less hours of sleep might prefer high-fat foods. This finding is in
agreement with a previous study, which also showed influence of
less hours of sleep on food behaviour, in which teenager girls with
short sleep duration presented higher carbohydrate consumption(21).
However, the authors did not find any association between sleep
patterns and body fat. Alteration in both lipid and carbohydrate
intake can change the lipid pathway and induce a positive energy
balance leading to obesity and its co-morbidities(34,35).
Increased lipid consumption and less hours of sleep
has been linked in the adult population, especially among shift
workers(6,14,36). In fact, a study performed with Greek women
showed an association between sleep duration and saturated
fat(37). High levels of fat intake are related to the development of
non-alcoholic fatty liver disease, atherosclerosis and dyslipidemia, in
addition to the increase of body weight through a positive energetic
balance(38-41). Collectively, these results reinforce the importance
of early nutritional strategies to prevent and control metabolic
diseases, especially in adolescents.
Additionally, short sleep time may affect orexigenic
and anorexigenic hormones, thus altering satiety and appetite.
Previously, Spiegel et al.(19) showed that sleep deprivation reduced
by 18% and increased by 28% the concentrations of leptin and
ghrelin, respectively. In the same study, it was demonstrated that
sleep debt was associated with an increase in hunger ratings by
24% on the 10-cm visual analogue scale and appetite ratings
by 23%. Thus, all these mentioned factors might explain the
alterations on food behaviour among those who sleep less.
In the present study, a vicious cycle can be hypothesized
(Figure 1), since less hours of sleep could influence fat
consumption, which could lead to a weight gain and apparently
reducing sleep time through higher sleep latency. This hypothesis
could be reinforced by an expressive effect size obtained in both
multiple linear regression models (Tables 3 and 4). In agreement,
recent evidence suggests that adipose tissue has an important
role in endocrine system regulation, energy homeostasis, satiety
signalling, and the biological clock, suggesting the link between
sleep and obesity as causes and consequences(42).
A possible explanation for increased sleep latency in
those with higher fat mass could be the effects of excess weight,
especially on the respiratory system. Considering that severe
obesity is associated with an anatomically narrowed pharynx,
which would constitute a resistive load that might contribute
to sleep disruption(43). Although, we did not find an association
between abdominal obesity and sleep changes, some studies
with adults have shown that this kind of obesity was related to
a reduction of sleep time and sleep efficiency(7,44). In addition,
a single report showed that obese adults without obstructive
sleep apnea had higher sleep latency and presented more sleep
fragmentation and less REM sleep than did control subjects(23).
Our results contribute to better understanding the
perpetuation of obesity through feeding behaviours induced
by fewer hours of sleep and how it can promote modifications
in this highly complex mechanism of energy balance in obese
adolescents. We can conclude that sufficient hours of sleep
may be essential for maintaining metabolism, even though the
mechanisms involved in this process are not yet well defined.
Sleep Sci. 2013;6(1):26-31
29
30
Influence of sleep on obesity
Figure 1 hypothesized how obesity and total sleep time can
corroborate each other, worsening the pathology.
Our data suggest a tendency of reduced sleep time
among obese adolescents (Table 2), which is consistent with
previous studies(45,46). Many hypotheses have been proposed
to address the question of sleep loss in adolescents, being the
syndrome of the sleep phase delay (a tendency to stay up later
at night and to sleep later in the morning) and the morning
school period some of the mainly causes(3,47). Moreover, a recent
study showed that a school time delay of 30 minutes was able
to increase 45 minutes of sleep, and the number of students
that slept at least 8 hours increased from 16.4% to 54.7%(48).
Therefore, schools should consider a later time of study for
adolescents. In the current study, 80% of the students started
school activities in the morning (data not shown).
Although sleep has fundamental functions in energy
conservation, immunity, metabolism regulation, neural
maintenance, memory consolidation and behaviour, the total sleep time has decreased in past years(49). Sleep debt has
been associated with many complications, with obesity and
eating disorders being the main factors, which reflects on the
worldwide obesity epidemy(6,50). However, some obese patients
can have adequate consumption, like those in the present study,
and present an altered energy balance due to the neuroendocrine
dysfunction caused by obesity(22).
The small sample size, a lack of control group and
subjective assessments represent the limitations of this study.
However, our data were empowered by an expressive effect size,
suggesting that the vicious cycle between short sleep time, an
increased lipid intake, fat mass deposition and sleep latency may
occur in obese teenagers. Further investigations with objective
analyses and larger sample sizes should be performed for a
better understanding of the mechanisms and to extend the
results to the general teenage population.
CONCLUSION
The results indicate that less hours of sleep might contribute to
the maintenance of obesity in adolescents through an increase
in fat intake. Furthermore, we show that the total fat mass is
associated with higher sleep latency, contributing to a reduction
in sleep time. These data suggest a vicious cycle between
eating disorders, obesity and reduced sleep, which can lead to a
diminished quality of life in teenagers.
COMPETING INTERESTS
The authors declare that they have no competing interests.
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