ORIGINAL ARTICLE
Gender differences in the relationship of sleep pattern and body composition in healthy adults Diferenças do gênero na relação entre o padrão de sono e a composição corporal em adultos saudáveis Ioná Zalcman Zimberg1, Cibele Aparecida Crispim1,2, Rafael Marques Diniz1, Murilo Dattilo1, Bruno Gomes dos Reis1, Daniel Alves Cavagnolli1, Alexandre Paulino de Faria1, Sérgio Tufik1, Marco Túlio de Mello1
Abstract de composição corporal foram feitas na manhã seguinte, após 12 horas Objective: To investigate the gender differences in relationship be- de jejum. Protocolos validados foram usados para avaliar o sono (po- tween body composition and sleep pattern in healthy subjects. Meth- lissonografia) e antropometria (massa corporal, altura, dobras cutâneas ods: Fifty-two healthy volunteers (27 women) participated in this e circunferências corporais). Resultados: Correlação positiva entre study. Subjects underwent overnight polysomnography and measure- porcentagem de sono de ondas lentas e massa corporal magra (r=0,46; ments of body composition were taken in the following morning af- p=0,016) foram encontradas em mulheres. Em homens, desperta- ter a 12-hour fast. Validated protocols were used to evaluate sleep res durante o sono foram positivamente correlacionados com índices (polysomnography) and anthropometry (body mass, height, skinfolds como índice de massa corporal (r=0,62, p<0,01), massa gorda (kg) and body circumferences). Results: A positive correlation between (r=0,61, p<0,01), percentual de gordura (r=0,56, p<0.01), circunfe- percentage of slow-wave sleep and percentage of lean body mass rência de cintura (r=0,58, p<0.01), circunferência de quadril (r=0,45, (r=0.46, p=0.016) was found in women. In men, awakenings during p<0.01) e relação cintura-quadril (r=0,50, p=0,01). Índice de massa sleep were correlated positively with indices such as body mass in- corporal, percentual de gordura, circunferência de cintura e relação dex (r=0.62, p<0.01), fat mass (kg) (r=0.61, p<0.01), fat percentage cintura quadril foram correlacionadas com o índice de apneia e hipop- (r=0.56, p<0.01), waist circumference (r=0.58, p<0.01), hip circum- neia (r=0,40, p=0,03; r=0,46, p<0,01; r=0,49, p<0,01; e r=0,56, ference (r=0.45, p<0.01), and waist-to-hip ratio (r=0.50, p=0.01). p<0,01) em ambos os gêneros. Conclusões: Este estudo demonstrou Body mass index, body fat percentage, waist circumference, and waist- importantes associações estatísticas entre diferentes variáveis de sono to-hip ratio were correlated with apnea-hypopnea index (r=0.40, e características antropométricas em indivíduos saudáveis, sugerindo p=0.03; r=0.46, p<0.01; r=0.49, p<0.01; and r=0.56, p<0.01) in uma possível relação entre maior deposição de gordura e diminuição both genders. Conclusion: This study showed important statistical na qualidade de sono. Ademais, atesta-se que essas associações diferem associations between different sleep variables and anthropometric entre gêneros e incitam investigações mais aprofundadas. characteristics in healthy subjects, suggesting a possible relationship between greater body fat deposition and impairment of sleep quality. Palavras-chave: sono/fisiologia; transtornos do sono/diagnostico; In addition, it was noticed that these associations differ between gen- índice de massa corporal; composição corporal; distribuição da gor- ders and deserve further exploration. dura corporal; polissonografia; humanos; feminino.
Keywords: sleep/physiology; sleep disorders/diagnosis; body mass INTRODUCTION index; body composition; body fat distribution; polysomnography; Sleep has been increasingly recognized for its contribution human; female. to physical and psychological health1. Moreover, sleep loss due to voluntary curtailment of time in bed has become a Resumo hallmark of modern society2. Studies show that most people Objetivo: Investigar as diferenças de gênero na relação entre compo- sição corporal e padrão de sono em indivíduos saudáveis. Métodos: need between 7 and 8 hours of daily sleep, however, over less Cinquenta e dois voluntários saudáveis (27 mulheres) participaram do than 50 years, a reduction of sleep duration by 1.5 to 2 hours estudo. Os sujeitos foram submetidos à polissonografia e mensurações seems to have occurred2-4.
Study carried out at Centro de Estudos em Psicobiologia e Exercício (CEPE), São Paulo (SP), Brazil. 1Departamento de Psicobiologia, Universidade Federal de São Paulo (UNIFESP), São Paulo (SP), Brazil. 2Universidade Federal de Uberlândia (UFU), Uberlândia (MG), Brazil. Financial support: AFIP, Sleep Institute, CEDIP/FAPESP (#998/14303-3), CEPE, UNIFESP, FADA, CAPES and CEMSA. Conflict of interests: nothing to declare. Corresponding author: Marco Túlio de Mello – Rua Professor Francisco de Castro, 93 – CEP 04020-050 – São Paulo (SP), Brazil – E-mail: [email protected] Received: February 2, 2011 – Accepted: July 2, 2011
Sleep Sci. 2011;4(2):�����–��44 40 Relationship between sleep pattern and body composition
Several studies have observed an association between eters were recorded in one night of PSG in the laboratory. short sleep duration and increased body mass index (BMI) The PSG consisted of the simultaneous and continuous or increased risk for being overweight5-13. Compared with registration of the electroencephalogram (C4-A1, C3-A2, sleeping 7 to 8 hours per night, Patel et al.14 found that O2-A1, and O1-A2), left and right electrooculogram, sub- sleeping less than 5 hours was associated with a BMI that mentonian and tibialis anterior muscles electromyography, was, on average, more than 2.5 kg/m2 in men and 1.8 kg/m2 electrocardiogram, nasal and oral airflow, thoracic cage and in women, after adjustments were made for multiple poten- abdominal respiratory motion, oxyhemoglobin saturation tially confounding variables. Moreover, measures of adipos- (SaO2), snoring and body positioning. All data were col- ity also have been associated with time of sleep, showing lected and stored using an EMBLA S7000® and recordings that short sleep duration is associated with higher body fat were taken in 30-second epochs. PSGs were scored by a percentage and waist circumference15-17. blinded, experienced sleep technician and staged according However few studies that examined the association be- to standard criteria21. Analyses included measures of total tween sleep quality and body composition in health indi- sleep time (TST), sleep efficiency, stages 1, 2,3 (slow wave viduals are available in the literature17 as well as gender sleep – SWS), rapid eye movement (REM) sleep, REM differences in these variables18. In front of this, the aim of sleep latency, wake time after sleep onset (WASO), AHI, this study was to investigate whether sleep architecture is oxygen saturation and PLM. associated with body composition in healthy adults and if Arousals were defined according to guidelines of the this association is influenced by gender. Sleep Disorders Atlas Task Force of the American Sleep Dis- orders Association22, and respiratory events classified using METHODS criteria of the American Academy of Sleep Medicine19. Epi- sodes of apnea were defined as complete cessation of airflow Participants and study design for 10 seconds or more, and hypopnea was scored if there Fifty-two non-obese, healthy volunteers (27 women), between was at least a 50% reduction in airflow for 10 seconds or a 19 and 45 years old (men: 27.3±6.0; women: 28.8±6.7), discernable decrement in airflow for 10 seconds in associa- were recruited from the community and from the medical tion with either an oxyhemoglobin desaturation of at least and technical staff and students of Universidade Federal de 3% or an arousal. Apnea/hypopnea events were classified as São Paulo (UNIFESP) and Associação Fundo de Incentivo a obstructive, central or mixed according to the presence or Pesquisa (AFIP). All individuals were sedentary (according the absence of breathing efforts and the AHI was calculated to International Physical Activity Questionnaire – IPAQ), considering number of episodes of apnea and hypopnea per did not work in shift work, featured no abnormalities in a hour of sleep. clinical electrocardiogram at rest and under physical strain, and did not have any health problems according to medical Body composition evaluation evaluation. After clinical evaluation, all subjects underwent Measurements of body mass, height, skinfolds, and body overnight polysomnography (PSG). Subjects who presented circumferences were taken in the following morning of the values of apnea-hypoapnea index (AHI) >1519, and those PSG exam after a 12-hour fast. Height was measured with a who presented periodic leg movements (PLM) >520, assessed Sanny estadiometer (American Medical do Brasil Ltda., Bra- by means of PSG were excluded. Enrollment was voluntary zil) with a 0.1 cm precision. Body weight was measured to after being informed about the procedures and objectives of the nearest 0.1 kg using a Filizola scale (Star model, Filizola, the study. Brazil). Body mass (kg) divided by the square height (m²) The research was performed in Sleep Institute and Cen- was used to calculate BMI. tro de Estudos em Psicobiologia e Exercício/Associação Fundo de Three measurements of triceps, subscapular, midaxillary, Incentivo à Pesquisa (CEPE/AFIP) in 2007, situated in São chest, suprailiac, abdominal, and thigh skinfolds were taken Paulo city (SP), Brazil. It was approved by the Committee using a Lange skinfold caliper (Beta Technology Incorpo- of Ethics of Universidade Federal de São Paulo (#0018/08) rated, USA) with a 0.1 mm precision. The mean value was and the volunteers were informed about all the stages of used to estimate the body fat percentage according to Jack- the study and signed a written and informed consent be- son & Pollock23 and Jackson et al.24, equations for men and fore participation. women, respectively. A Sanny measuring tape (American Medical do Bra- Sleep evaluation sil Ltda., São Paulo) with a 10 mm precision was used to Volunteers arrived at the sleep laboratory at 21h30 for measure the waist (WC) and hip (HP) circumferences. WC electrode attachment and went to bed at 23h. Sleep param- divided by HP was used to calculate the waist-to-hip ratio
Sleep Sci. 2011;4(2):�����–��44 41 Zimberg IZ, Crispim CA, Diniz RM, Dattilo M, Reis BG, Cavagnolli DA, Faria AP, Tufik S, Mello MT
(WHR). The WC and WHR were considered central obe- mass, fat mass, WC, and WHR (r=0.43; r=0.46; r=0.29; sity indices. r=0.50; r=0.55). All measurements were taken by trained professional and When genders were separately analyzed, a positive sig- all protocols were previously validated. nificant correlation between SWS percentage and lean mass percentage was found in women (Figure 1), but not in men Statistical analyses (r=0.08, p=0.33). Only women presented a negative corre- Student’s t-test for independent samples was used for gen- lation between fat mass percentage (r=-0.46, p=0.016) and der comparisons between individuals’ characteristics of sleep SWS percentage. and body composition. Pearson’s correlation was used to as- sess the association between sleep parameters and variables Table 1. Body composition and sleep characteristics of volunteers. of body composition. Data were analyzed using Statistica Men (n=25) Women (n=27) p value 6.0 (StatSoft, Inc., Tulsa, OK, USA). All values were ex- Body composition variables pressed as mean±standard deviation (SD). Statistical tests Age (yr) 27.3±6.0 28.7±6.8 0.45 were accepted as significant when p≤0.05. Body Mass (kg) 76.9±14.9 58.2±8.5 0.00 Height (m) 1.75±0,1 1.61±0.1 0.00 RESULTS BMI (kg/m²) 25.0±4.3 22.4±2.6 0.01 Lean mass (kg) 61.1±7.8 44.9±4.9 0.00 The characteristics of the volunteers are described in Table 1 Fat mass (kg) 15.9±8.9 13.4±4.5 0.21 and, in general, they were young adults, non-obese, with Body fat (%) 19.5±7.8 22.5±4.9 0.11 normal body fat percentage, and waist circumference. When WC (cm) 85.1±12.1 72.2±6.7 0.00 compared by gender, men presented significantly higher val- HC (cm) 99.0±10.5 95.9±6.1 0.20 ues of body mass, height, BMI, lean mass, WC and WHR WHR 0.9±0.1 0.7±0.1 0.00 than women, as expected. Sleep variables Regarding the sleep variables, women had reduced total TST (min) 369.3±40.3 353.6±78.7 0.38 sleep time (≤6 hours) in comparison with normative data21. Sleep latency (min) 16.6±15.5 11.3±11.3 0.16 Men had a significantly higher percentage of stage 1 sleep Sleep efficiency (%) 87.3±6.9 87.8±7.9 0.83 Stage 1 (%) 3.8 2.2 2.6 1.8 0.03 and AHI than did women. AHI in men were higher when ± ± Stage 2 (%) 55.1±6.6 53.1±7.9 0.34 compared to normative data. Although there were no statis- SWS (%) 23.1±6.5 24.6±6.3 0.41 tically significant differences between genders, the percent- REM (%) 17.9±4.6 19.7±5.1 0.20 age of waking after sleep onset was higher, and REM sleep WASO (min) 37.3±25.7 38.0±28.7 0.92 was lower when compared to normative data21. AHI (events/hr) 8.4±7.5 2.6±2.5 0.00 The correlations of sleep pattern with BMI and body PLM (events/hr) 0.6±1.5 1.8±5.2 0.27 composition are described in Table 2. Stage 1 of sleep was Epworth Sleepiness Scale 8.3±2.5 8.4±3.6 0.91 positively correlated to lean mass and WHR (r=0.29). Stage In bold p≤0.05; Student’s t test. 2 of sleep was also correlated to WHR (r=0.28 and r=-0.36, BMI: body mass index; WC: waist circumference; HC: hip respectively). WASO showed a significant correlation with circumference; WHR: waist-to-hip ratio; TST: total sleep time; SWS: slow-wave sleep (stage 3 of sleep); REM: rapid eye movement; WASO: weight and adiposity measures as BMI, fat mass, WC, and wake after sleep onset; AHI: apnea-hypoapnea index; PLM: periodic leg HC (r=0.35; r=0.42; r=0.40; r=0.29; r=0.31, respectively). movements. Furthermore, AHI positively correlated with BMI, lean
Table 2. Correlations between body composition measurements and sleep variables. Sleep effic Stage Stage TST (min) SWS (%) REM (%) WASO (min) AHI (%) 1 (%) 2 (%) BMI (kg/m²) -0.01 -0.24 0.18 0.10 -0.06 -0.15 0.35 0.43 Lean mass (kg) -0.02 -0.16 0.30 0.09 -0.07 -0.19 0.11 0.46 Fat mass (kg) -0.02 -0.23 0.13 0.10 -0.08 -0.09 0.42 0.29 Body fat (%) -0.01 -0.16 -0.02 0.08 -0.10 0.02 0.40 0.06 WC (cm) 0.03 -0.20 0.25 0.19 0.06 -0.15 0.29 0.50 HC (cm) 0.01 -0.09 0.13 0.02 -0.18 -0.07 0.31 0.17 WHR 0.09 -0.15 0.29 0.28 -0.22 -0.11 0.14 0.55 In bold characters: p<0.05; Pearson’s correlation. TST: total sleep time; Sleep effic: sleep efficiency; SWS: slow-wave sleep (stage 3 of sleep); REM: rapid eye movement; WASO: wake after sleep onset; AHI: apnea-hypoapnea index; BMI: body mass index; WC: waist circumference; HC: hip circumference; WHR: waist-to-hip ratio.
Sleep Sci. 2011;4(2):�����–��44 42 Relationship between sleep pattern and body composition
Only in men, WASO was positively correlated with (r=0.50, p=0.01), as shown in Figure 2. Furthermore, a BMI (r=0.62, p<0.01), fat mass (r=0.61, p<0.01), lean positive correlation between WHR and AHI (r=0.51, mass (r=0.41¸ p=0.04), fat percentage (r=0.56, p<0.01), p=0.01) was also found (Figure 3). All these correlations WC (r=0.58, p<0.01), HC (r=0.45, p=0.02), and WHR were not found in women.
DISCUSSION In the present study, several significant correlations be- 40 r=0.46, p=0.02 35 tween anthropometric variables and sleep were found, in- 30 dicating that these aspects can be associated. It is impor- 25 tant to highlight that a bidirectional influence can occur 20 between sleep and anthropometric variables, that is, sleep 15 may influence body composition and body composition can 10 influence sleep pattern. The first is well demonstrated in
Slow Wave Sleep (%) Slow Wave 5 0 the literature, but little is known about how parameters 60 65 70 75 80 85 90 like body fat percentage, waist and hip circumferences can Lean body mass (%) affect sleep pattern. Figure 1. Correlation between slow-wave sleep percentage and lean body Although our results indicated expected differences in mass percentage in women. A corresponding best-fit line along with the anthropometric variables between the genders, the same oc- Person’s correlation coefficient (r) and its p value was shown. curred with sleep pattern which evidenced a higher stage 1 and AHI in men, a finding previously reported by our group. 0,70 Previously, Silva et al.18, demonstrated in a large group of 0,60 Brazilian patients that men had higher stage 1, stage 2, and 0,50 AHI than women, whereas women had significantly more 0,40 SWS than men. 0,30 Given the speculative nature of these results and the 0,20 lack of evidence in this area, it is difficult to compare these
WASO correlation WASO results with other researches. One of the few studies that 0,10 analyzed the relationship between body composition and
0,00 ) 2 sleep was done by Rontoyanni et al.16. Their results dem-
WHR onstrated a negative correlation between sleep duration
HC (cm) and fat percentage in healthy women, supporting the idea BM (kg/m Body fat (%) Fat mass (kg) that sleep duration is significantly associated with body Lean mass (kg) fat. On the other hand, in a study conducted by Stranges WASO: wake after sleep onset; BMI: body mass index; WC: waist circum- WC (cm) 15 ference; HC: hip circumference; WHR: Waist-to-hip ratio. et al. , negative correlations between sleep duration and Figure 2. Significant correlations between body composition measure- body mass and central adiposity were observed. In our ments and wake after sleep onset in men. study no association between sleep duration and greater body mass and/or adiposity was found. Nevertheless, we 35 verified an association between body composition and sleep r=0.51, p=0.01 30 quality variables. Rao et al.17 published the first large scale study to exam- 25 ine the relationship of sleep architecture, specifically SWS, 20 with measures of body composition such as BMI, waist cir- AHI 15 cumference and percentage body fat. This study showed 10 that older men in the lowest quartile of SWS had an average 2 5 BMI of 27.4kg/m , compared to 26.8 for those in the high- 0 est quartile of SWS. Furthermore, participants in the lowest 0,7 0,75 0,8 0,85 0,9 0,95 1 quartile of SWS had a 1.4-fold increased odds for obesity WHR (p=0.03, 95%CI: 1.0-1.8) compared to those in the highest Figure 3. Correlation between apnea-hypoapnea index and waist-to-hip quartile. Authors concluded that independent of sleep dura- ratio in men. A corresponding best-fit line along with the Person’s correla- tion, percentage time in SWS is inversely associated with tion coefficient (r) and its p value was shown. BMI and other measures of body composition. The authors
Sleep Sci. 2011;4(2):�����–��44 43 Zimberg IZ, Crispim CA, Diniz RM, Dattilo M, Reis BG, Cavagnolli DA, Faria AP, Tufik S, Mello MT did not found a relationship between adiposity variables and groups6,14,15,33-36. Future metabolic studies should be done in SWS. In our study we observed in women a negative correla- different genders to determine if they have a different hor- tion between percentage of SWS sleep and percentage of fat monal response to short sleep duration. mass. It also was observed that the WHR correlates nega- A limitation of the present study was the single night tively with the percentage of stage 4 sleep and positively of PSG. An adaptation to the laboratory could potentially with stage 1 sleep in both genders. According to Rao et al.17, influence the response to sleep. Another limitation is that it is possible that increased BMI may alter sleep architecture we did not control menstrual cycle phase of women involved and decrease SWS. in the study. The alteration of the ideal sleep architecture can bring This study demonstrated an important association be- about harmful effects. As an example, Tasali et al.25, in a tween different sleep variables and adiposity measurements recent study demonstrated that the reduction of the SWS in healthy individuals, suggesting that a greater deposition was related to a greater insulin resistance, indicating its role of body fat can be associated with an impairment of sleep in glucose homeostasis. These data suggest that a smaller quality and not only the inverse, as shown in several studies. amount of SWS (which occurs in obese individuals) can con- However, more studies are necessary to elucidate the real tribute to an increased risk of type 2 diabetes. influence of sleep and its disturbances on several factors re- Although in our study it was not possible to demonstrate sponsible for the control of body mass. a cause-effect relationship between body composition and apnea, some positive correlations between AHI and anthro- Acknowledgments pometric variables were found especially in men, demon- This study was supported by AFIP, CEPE, Centro de Estudo strating that body fat distribution can be associated with Multidisciplinar em Sonolência e Acidentes (CEMSA), Centro de a higher risk for apnea. Some studies show that obesity is a Pesquisa, Inovação e Difusão-Fundação de Amparo à Pesquisa do pathogenic factor in apnea26-29 and that approximately 70% Estado de São Paulo (CEPID/SONO-FAPESP) (#98/14303-3), of the patients with sleep apnea are obese30. This association National Counsel of Technological and Scientific Develop- occurs because excessive weight can lead to a pharyngeal ment (CNPq), Coordenação de Aperfeiçoamento de Pessoal de narrowing due to the fat deposition on the pharynx walls or Nível Superior (CAPES), FAPESP, UNIFESP, Fonte de Auxílio on parapharyngeal structures, such as tongue, soft palate and UNIFESP. We thank all volunteers uvula30,31. Still, the risk of apnea development is more asso- aos Docentes e Alunos of ciated with the accumulation of fat in the central region32, a and researchers involved in this study. fact also observed in the present study. The role of sleep fragmentation in the relationship be- References 1. Taheri S. The link between short sleep duration and obesity: we tween sleep duration and obesity it is not clear yet. In the should recommend more sleep to prevent obesity. Arch Dis Child. Rotterdam Study, whereas actigraphy was used to assess 2006;91(11):881-4. sleep, the degree of sleep fragmentation was a stronger pre- 2. National Sleep Foundation. Sleep in America 2011 Poll [Internet]. dictor of adiposity than reduced sleep duration33. Persons Washington: National Sleep Foundation; 2002. [cited 2010 Nov. 12]. with more fragmented sleep had a higher BMI and more Available from
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