Dataset Information

Poor sleep quality and sleep apnea are associated with higher resting energy expenditure in obese individuals with short sleep duration.

ABSTRACT:

Context

Epidemiological studies reported an inverse or U-shaped relationship between sleep duration and weight. The relationship between sleep and resting energy expenditure (REE) has not been well characterized.

Objective

The aim of the study was to determine the relationship between sleep, REE, and stress hormones.

Design and setting

We conducted a cross-sectional evaluation of a prospective cohort study at a tertiary referral research clinical center.

Subjects

Subjects included 126 obese individuals (30 males, 96 females; age, 40.5 ± 6.9 yr; body mass index, 38.6 ± 6.5 kg/m(2); sleep duration, 360 ± 50 min/night; and sleep efficiency, 79.5 ± 7.5%).

Main outcome measure(s)

REE and respiratory quotient (RQ) were assessed by indirect calorimetry. Sleep duration and sleep efficiency were assessed by actigraphy. Sleep quality was estimated by questionnaires, and sleep apnea was evaluated by respiratory disturbance index (RDI). Morning plasma ACTH, serum cortisol, and 24-h urinary free cortisol and catecholamines were also measured.

Results

RDI was positively correlated with REE adjusted by fat-free mass (r = 0.307; P = 0.003) and RQ (r = 0.377; P < 0.001). Sleep efficiency was inversely correlated with RQ (r = -0.200; P = 0.033). The relationship of RDI score and REE was stronger in men than women (P = 0.03). In women, serum cortisol was positively correlated (r = 0.407; P < 0.001), and Epworth sleepiness score tended to be inversely (r = -0.190; P = 0.086) correlated with adjusted REE. The RQ was positively related to RDI in women, whereas subjective sleep time was related to RQ in men. In a multiple regression model, RDI, serum cortisol, and urinary norepinephrine were directly related to REE, whereas serum cortisol also directly related to adjusted REE.

Conclusion

Poor sleep quality was associated with increased REE, a higher RQ indicating a shift from fat toward carbohydrate oxidation, and activation of the stress system.

SUBMITTER: de Jonge L

PROVIDER: S-EPMC3410277 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Publications

Poor sleep quality and sleep apnea are associated with higher resting energy expenditure in obese individuals with short sleep duration.

de Jonge Lilian L Zhao Xiongce X Mattingly Megan S MS Zuber Samuel M SM Piaggi Paolo P Csako Gyorgy G Cizza Giovanni G

The Journal of clinical endocrinology and metabolism 20120611 8

<h4>Context</h4>Epidemiological studies reported an inverse or U-shaped relationship between sleep duration and weight. The relationship between sleep and resting energy expenditure (REE) has not been well characterized.<h4>Objective</h4>The aim of the study was to determine the relationship between sleep, REE, and stress hormones.<h4>Design and setting</h4>We conducted a cross-sectional evaluation of a prospective cohort study at a tertiary referral research clinical center.<h4>Subjects</h4>Sub ...[more]

PMID: 22689694

Similar Datasets

Project description:Background and Aims:The unique demographic and dietary characteristics of modern Arabic population require development of a new predictive equation for the estimation of resting energy expenditure (REE). This study presented new equations characteristic to Saudi population. Methods:A set of predictive equations for REE was derived for 427 healthy male and female subjects (aged 18-57?±?14 years). REE was measured (REEm) by indirect calorimetry (IC) and predicted (REEp) using nine equations. REEp was compared with REEm to determine the predictive accuracy of these equations. Using IC and anthropometrics for stepwise linear regression analysis, a new set of equations to predict REE of men and women was developed. Accuracy of the new main equations was further tested in an external sample of 48 subjects (men?=?50%). Results:Using a number of parameters (bias, underprediction, overprediction, and % accurate prediction), our results suggested that almost all (9/9 in men and 7/9 in women) equations either underpredicted or overpredicted (2/9) REE. None of the already existing equations showed an acceptable REEp/REEm difference as low as 5% and an accurate prediction (?55%) at the individual level. Based on these findings, a new prediction equation (hereafter referred to as the Almajwal-Abulmeaty (AA) equation) was developed using this study's data, after a rigorous stepwise regression analysis using the following formula: REE?=?3832.955?+?AdjWt (kg)?×?48.037?-?Ht (cm)?×?30.642?+?gender?×?141.268?-?age (years)?×?4.525 [AdjWt is Adjusted body weight?=?(Wt?-?IBW)/4?+?IBW. IBW is Ideal body weight; for men IBW?=?(Ht(cm)?-?152.4)?×?1.0714)?+?45.36 and for women IBW?=?(Ht(cm)-152.4)?×?0.8928)?+?45.36]. The regression model accounted for approximately 70% of the variance in REEm (R 2?=?0.702). Conclusion:Previous equations likely over- or underpredicted REE. Therefore, the new predictive AA equations developed in this study are recommended for the estimation of REE in young to middle-aged Saudi men and women with different body mass indexes. Future research is also required for further clinical and cross-validation of these new equations.

Project description:Background/objectivesThe aim of this study was to compare resting energy expenditure (REE) measured (MREE) by indirect calorimetry (IC) and REE predicted (PREE) from established predictive equations in a large sample of obese Caucasian adults.Subjects/methodsWe evaluated 1851 obese patients (body mass index (BMI)>30 kg m-2) aged between 18a and 65 years. Data were obtained by comparing MREE with PREE, derived from different equations, within and between normal weight and obese groups. The mean differences between PREE and MREE as well as the accuracy prediction within ±10% level were investigated in the whole sample and in three subgroups, classified by BMI (Group 1=30-39.9 kg m-2; Group 2=40-49.9 kg m-2; Group 3>50 kg m-2).ResultsWe observed that FAO, Henry and Muller3 (body composition (BC)) equations provided good mean PREE-MREE (bias -0.7, -0.3 and 0.9%; root mean standard error (RMSE) 273, 263 and 269 kcal per day, respectively); HB and Henry equations were more accurate individually (57 and 56.9%). Only the Muller1 (BC) equation gave the lowest PREE-MREE difference (bias -1.7%; RMSE 228 kcal per day) in females, while Johnstone and De Lorenzo equations were the most accurate (55.1 and 54.8%). When the sample was split into three subgroups according to BMI, no differences were found in males; however, the majority of the equations included in this study failed to estimate REE in severely obese females (BMI>40 kg m-2). Overall, prediction accuracy was low (~55%) for all predictive equations, regardless of BMI.ConclusionsDifferent established equations can be used for estimating REE at the population level in both sexes. However, the accuracy was very low for all predictive equations used, particularly among females and when BMI was high, limiting their use in clinical practice. Our findings suggest that the validation of new predictive equations would improve the accuracy of REE prediction, especially for severely obese subjects (BMI>40 kg m-2).

Dataset Information

Poor sleep quality and sleep apnea are associated with higher resting energy expenditure in obese individuals with short sleep duration.

Context

Objective

Design and setting

Subjects

Main outcome measure(s)

Results

Conclusion

Publications

Poor sleep quality and sleep apnea are associated with higher resting energy expenditure in obese individuals with short sleep duration.

Similar Datasets

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