Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-13T04:22:21.725Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessing sleeping energy expenditure in children using heart-rate monitoring calibrated against open-circuit indirect calorimetry: a pilot study

Published online by Cambridge University Press:  09 March 2007

L. Beghin ,
L. Michaud ,
D. Guimber ,
G. Vaksmann ,
D. Turck  and
F. Gottrand
L. Beghin
Affiliation:
Unité de Gastroentérologie, Hépatologie et Nutrition, Clinique de Pédiatrie, Hôpital Jeanne de Flandre et Faculté de Médecine, Lille, France Centre d'Investigation Clinique, CIC-9301-INSERM-CHU, Hôpital Cardiologique, Lille, France
L. Michaud
Affiliation:
Unité de Gastroentérologie, Hépatologie et Nutrition, Clinique de Pédiatrie, Hôpital Jeanne de Flandre et Faculté de Médecine, Lille, France
D. Guimber
Affiliation:
Unité de Gastroentérologie, Hépatologie et Nutrition, Clinique de Pédiatrie, Hôpital Jeanne de Flandre et Faculté de Médecine, Lille, France
G. Vaksmann
Affiliation:
Service de Maladies Cardiovasculaires Infantiles et Congénitales, Hôpital Cardiologique, Lille, France
D. Turck
Affiliation:
Unité de Gastroentérologie, Hépatologie et Nutrition, Clinique de Pédiatrie, Hôpital Jeanne de Flandre et Faculté de Médecine, Lille, France
F. Gottrand*
Affiliation:
Unité de Gastroentérologie, Hépatologie et Nutrition, Clinique de Pédiatrie, Hôpital Jeanne de Flandre et Faculté de Médecine, Lille, France
*
*Corresponding author:Professor F. Gottrand, fax +33 3 20 44 59 63, email fgottrand@chru-lille.fr
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Total energy expenditure (EE) can be assessed in children by the heart-rate (HR) monitoring technique calibrated against open-circuit indirect calorimetry (IC). In this technique, sleeping EE is usually estimated as the lowest value of a 30 min resting EE measurement×0·90 to give an average for the total sleeping period. However, sleeping is a dynamic process in which sleeping EE is modulated by the effect of factors such as body movement and different sleep stages. The aim of the present study was to determine a new method to improve the sleeping EE measurement by taking into account body movements during sleep. Twenty-four non-obese children participated in the present study. All subjects passed through a calibration period. HR and EE measured by IC were simultaneously collected during resting, the postprandial period, and during different levels of activity. Different methods for computing sleeping EE (resting EE×0·90 with different breakpoints (‘flex point’ HR with linear regression or ‘inflection point’ (IP) HR with the third order polynomial regression equation (P3)) were compared with EE measured for least 2·0 h in eight sleeping children. The best method of calculation was then tested in sixteen children undergoing HR monitoring and with a body movement detector. In a subset of eight children undergoing simultaneous sleeping EE measurement by IC and HR, the use of the equation resting EE×0·8 when HR<IP and P3 when HR>IP during the sleeping period gave the lowest difference (1 (SD 5·4) %) compared with other methods (linear or polynomial regressions). The new formula was tested in an independent subset of sixteen other children. The difference between sleeping ee computed with the formula resting EE×0·90 and sleeping EE computed with resting EE×0·8 when HR<IP and the P3 equation when HR>IP during sleeping periods was significant (13 (sd 5·9)%) only for active sleeping subjects (n 6 of 16 subjects). The correlation between the difference in the results from the two methods of calculation and body movements was close (r 0·63, P<0·005, Spearman test) as well as computed sleeping EE (Spearman test, r 0·679, P<0·001), indicating that this new method is reliable for computing sleeping EE with HR monitoring if children are moving during sleep and improves the total EE assessment.

Keywords

ChildrenSleeping energy expenditureHeart-rate monitoringIndirect calorimetry
Type
Research Article
Information
British Journal of Nutrition , Volume 88 , Issue 5 , November 2002 , pp. 533 - 543
Copyright
Copyright © The Nutrition Society 2002

References

Astrup, A, Thorbek, G, Lind, J & Isaksson, B (1990) Prediction of 24-h energy expenditure and its components from physical characteristics and body composition in normal-weight humans. American Journal of Clinical Nutrition 52, 777–783.CrossRefGoogle ScholarPubMed
Azaz, Y, Fleming, PJ, Levine, M, McCabe, R, Stewart, A & Johnson, P (1992) The relationship between environmental temperature, metabolic rate, sleep state and evaporative water loss in infants from birth to three months. Pediatric Research 32, 417–423.Google Scholar
Beghin, L, Budniok, T, Vaksmann, G, Boussard-Delbecque, L, Michaud, L, Turck, D & Gottrand, F (2000) Simplification of the method of assessing daily and nightly energy expenditure in children, using heart rate monitoring calibrated against open circuit indirect calorimetry. Clinical Nutrition 19, 425–435.CrossRefGoogle ScholarPubMed
Benedict, FG (1919) Energy requirements of children from birth to puberty. Boston Medical and Surgical Journal 6, 107–138.CrossRefGoogle Scholar
Bitar, A, Vermorel, M, Fellmann, N, Bedu, M, Chamoux, A & Coudert, J (1996) Heart rate recording method validated by whole-body indirect calorimetry in 10-yr-old children. Journal of Applied Physiology 81, 1169–1173.Google Scholar
Bitar, A, Vernet, J, Coudert, J & Vermorel, M (2000) Longitudinal changes in body composition, physical capacities and energy expenditure in boys and girls during the onset of puberty. European Journal of Clinical Nutrition 39, 157–163.CrossRefGoogle ScholarPubMed
Bitar, A, Vermorel, M, Fellmann, N & Coudert, J (1995) Twenty-four-hour energy expenditure and its components in prepubertal children as determined by whole-body indirect calorimetry and compared with young adults. American Journal of Clinical Nutrition 62, 308–315.Google Scholar
Bland, JM & Altman, DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1, 307–310.CrossRefGoogle ScholarPubMed
Bouten, CVC, Koekkoek, KTM, Verduin, M, Kodde, R & Janssen, JD (1997) A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity. IEEE Biomedical Engineering 38, 211–229.Google Scholar
Bouten, CVC, Westerterp, KR, Verduin, M, Kodde, R & Janssen, JD (1994) Assessment of energy expenditure for physical activity using a triaxial accelerometer. Medicine and Science in Sports and Exercise 26, 1516–1523.CrossRefGoogle ScholarPubMed
Bracco, D, Morin, O, Liang, H, Jéquier, E, Borger, AG & Schutz, Y (1996) Changes in sleeping and basal energy expenditure and substrate oxidation induced by short term thyroxin administration in man. Obesity Research 4, 213–219.Google Scholar
Brebbia, DR & Altshuler, KZ (1965) Oxygen consumption rate and electroencephalographic stage of sleep. Science 150, 1621–1623.CrossRefGoogle ScholarPubMed
Brebbia, DR & Altshuler, KZ (1968) Stage-related patterns and nightly trends of energy exchange during sleep. In Computers and Electronics Devices in Psychiatry, pp. 319–335 [Kline, NS and Luska, E, editors]. New York: Grune & StrattonGoogle Scholar
Butte, NF, Jensen, CL, Moon, JK, Glaze, DG & Frost, JD (1992) Sleep organisation and energy expenditure of breast-fed and formula-fed infants. Pediatric Research 32, 514–519.Google Scholar
Coleman, KJ, Saelens, BE, Wiedrich-Smith, MD, Finn, JD & Epstein, LH (1997) Relationships between TriTrac-R3D vectors, heart rate, and self-report in obese children. Medicine and Science in Sports and Exercise 29, 1535–1542.Google Scholar
Eccles, MP, Cole, TJ & Whitehead, RG (1989) Factors influencing sleeping metabolic rate in infants. European Journal of Clinical Nutrition 43, 485–492.Google ScholarPubMed
Emons, HJG, Gronenboom, DC, Westerterp, KR & Saris, WHM (1992) Comparison of heart rate monitoring combined with indirect calorimetry and the doubly labelled water (2H218O) method for the measurement of energy expenditure in children. European Journal of Applied Physiology 65, 99–103.CrossRefGoogle ScholarPubMed
Fontvieille, AM, Harper, IT, Ferraro, RT, Spraul, M & Ravussin, E (1993) Daily energy expenditure by five-year-old children, measured by doubly labeled water. Journal of Pediatrics 123, 200–207.CrossRefGoogle ScholarPubMed
Fontvieille, AM, Rising, R, Spraul, M, Larson, DE & Ravussin, E (1994) Relationship between sleep stage and metabolic rate in humans. American Journal of Physiology 267, E732–E737.Google Scholar
Geissler, CA, Dzumbira, TMO & Noor, M (1986) Validation of a field technique for the measurement of energy expenditure: factorial method versus continuous respirometry. American Journal of Clinical Nutrition 44, 496–502.CrossRefGoogle ScholarPubMed
Goldberg, GR, Prentice, AM, Davies, HL & Murgatroyd, PR (1988) Overnight and basal metabolic rate in men and women. European Journal of Clinical Nutrition 42, 137–144.Google ScholarPubMed
Haskell, EH, Palca, JW, Walker, JM, Berger, RJ & Heller, HC (1981) Metabolism and thermoregulation during stages of sleep in humans exposed to heat and cold. Journal of Applied Physiology 51, 948–954.CrossRefGoogle ScholarPubMed
Hull, D, McArthur, AJ, Pritchard, K & Goodall, M (1996) Metabolic rate of sleeping infants. American Journal of Disease in Childhood 75, 282–287.Google Scholar
Jakicic, JM, Winters, C, Lagally, K, Ho, J, Robertson, RJ & Wing, RR (1999) The accuracy of the TriTrac-R3D accelerometer to estimate energy expenditure. Medicine and Science in Sports and Exercise 31, 747–753.CrossRefGoogle ScholarPubMed
Karlberg, P (1952) Determination of standard energy metabolism (basal metabolism) in normal infants. Acta Paediatrica Scandinavica 41, 89–92.Google ScholarPubMed
Klausen, B, Toubro, S & Astrup, A (1997) Age and sex effects on energy expenditure. American Journal of Clinical Nutrition 65, 895–907.Google Scholar
Livingstone, MBE, Coward, WA, Prentice, AM, Davies, PSW, Strain, JJ, McKenna, PG, Mahonet, CA, White, JA, Stewart, CM & Kerr, MJJ (1992) Daily energy expenditure in free-living children: comparison of heart-rate monitoring with the (2H218O) doubly labelled water method. American Journal of Clinical Nutrition 56, 343–352.Google Scholar
Maffeis, C, Pinelli, L, Zaffanello, M, Schena, F, Iacumin, P & Schutz, Y (1995) Daily energy expenditure in free living conditions in obese and non-obese children: comparison of doubly labelled water (2H218O) method and heart-rate monitoring. International Journal of Obesity 19, 671–677.Google Scholar
Masse, LC, Fulton, JE, Watson, KL, Heesch, KC, Kohl, HW 3rd, Blair, SN & Tortolero, SR (1999) Detecting bouts of physical activity in a field setting. Research Quarterly for Exercise and Sport 70, 212–219.Google Scholar
Palca, JW, Walker, JM & Berger, RJ (1986) Thermoregulation, metabolism, and stages of sleep in cold-exposed men. Journal of Applied Physiology 61, 940–947.Google Scholar
Panter-Brick, C, Todd, A, Baker, R & Worthman, C (1996a) Comparative study of flex heart rate in three samples of Nepali boys. American Journal of Human Biology 8, 653–660.Google Scholar
Panter-Brick, C, Todd, A, Baker, R & Worthman, C (1996b) Heart rate monitoring of physical activity among village school, and homeless Nepali boys. American Journal of Human Biology 8, 661–672.3.0.CO;2-K>CrossRefGoogle ScholarPubMed
Rechtschaffen, A & Kales, A (1968) A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. National Institutes of Health Publication 204. Washington, DC: US Government Printing Office.Google Scholar
Ryan, T, Mlynczak, S, Erickson, T, Man, SFP & Man, GCW (1989) Oxygen consumption during sleep: Influence of sleep stage and time of night. Sleep 12, 201–210.Google Scholar
Schaefer, F, Georgi, M, Zieger, A & Scharer, K (1994) Usefulness of bioelectric impedance and skinfold measurements in predicting fat-free mass derived from total body potassium in children. Pediatric Research 35, 617–624.Google Scholar
Schofield, WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Human Nutrition: Clinical Nutrition 39 Suppl. 1, 5–41.Google Scholar
Schutz, Y & Deurenberg, P (1996) Energy metabolism: overview of recent methods used in human studies. Annals of Nutrition and Metabolism 40, 183–193.CrossRefGoogle ScholarPubMed
Sempé, M, Pedron, G & Roy-Pernot, MP (1979) Auxologie: methods et sequences pp. 25–49. Paris: Théraplix.Google Scholar
Spurr, GB, Reina, JC & Barac-Nieto, M (1986) Marginal malnutrition in school-aged Colombian boys: metabolic rate and estimated daily energy expenditure. American Journal of Clinical Nutrition 44, 113–126.Google Scholar
Stothers, JK & Warner, RM (1978) Oxygen consumption and neonatal sleep states. Journal of Physiology 278, 435–440.CrossRefGoogle ScholarPubMed
Stothers, JK & Warner, RM (1984) Thermal balance and sleep state in the newborn. Early Human Development 9, 313–322.Google Scholar
Talbot, FB (1921) Standards of basal metabolism in normal infants in children. American Journal of Disease in Childhood 21, 519–528.Google Scholar
Torun, B, Davies, PSW, Livingtone, MBE, Paolisso, M, Sackett, R & Spurr, GB (1996) Energy requirements and dietary energy recommendations for children and adolescents 1 to 18 years old. European Journal of Clinical Nutrition 50 Suppl. 1, S37–S81.Google Scholar
Treuth, MS, Adolph, AL & Butte, NF (1998) Energy expenditure in children predicted from heart rate and activity calibrated against respiration calorimetry. American Journal of Physiology 275, E12–E18.Google Scholar
Van Mil, EA, Westerterp, KR, Gerver, WJ, Curfs, LM, Schrande-Stumplel, CT, Kester, AD & Saris, WH (2000) Energy expenditure at rest and during sleep in children with Prader-Willi syndrome is explained by body composition. American Journal of Clinical Nutrition 71, 752–756.CrossRefGoogle ScholarPubMed
Wareham, NJ, Hennings, SJ, Prenctice, AM & Day, NE (1997) Feasibility of heart-rate monitoring to estimate total level and pattern of energy expenditure in a population-based epidemiological study: the Ely young cohort feasibility study 1994–5. British Journal of Nutrition 78, 889–900.CrossRefGoogle Scholar
Webb, P & Hiestand, M (1975) Sleep metabolism and age. Journal of Applied Physiology 38, 257–262.Google Scholar
Weir, JB (1949) New methods for calculating metabolic rate with special reference to protein metabolism. Journal of Physiology 109, 1–9.CrossRefGoogle ScholarPubMed
Welk, GJ & Corbin, CB (1995) The validity of the TriTrac-R3D activity monitor for the assessment of physical activity in children. Research Quarterly for Exercise and Sport 66, 1–8.CrossRefGoogle ScholarPubMed
Wells, JCK & Davies, PSW (1995a) Sleeping metabolic rate and body size in 12-week-old infants. European Journal of Clinical Nutrition 49, 323–328.Google ScholarPubMed
Wells, JCK & Davies, PSW (1995b) The effect of diet and sex on sleeping metabolic rate in 12-week-old infants. European Journal of Clinical Nutrition 49, 329–335.Google Scholar
Westerterp, KR (1999) Physical activity assessment with accelerometers. International Journal of Obesity and Related Metabolic Disorders 23, 45–49.CrossRefGoogle ScholarPubMed
White, DP, Weil, JV & Zwillich, CW (1985) Metabolic rate and breathing during sleep. Journal of Applied Physiology 59, 384–391.Google Scholar
World Health Organization (1985) Energy and Protein Requirements. Report of a Joint Food and Agriculture Organization/World Health Organization/United Nations University Expert Consultation. World Health Organization Technical Report Series no. 724. Geneva: WHO.Google Scholar
Zhang, K, Sun, M, Werner, P, Kovera, AJ, Albu, J, Pi-Sunyer, FX & Boozer, CN (2002) Sleeping metabolic rate in relation to body mass index and body composition. International Journal of Obesity 26, 376–383.CrossRefGoogle ScholarPubMed