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European journal of clinical nutrition
Jan, 2024;78 (1): 27-33.

Investigation of seasonality of human spontaneous physical activity and energy expenditure in respiratory chamber in Phoenix, Arizona.

Beyza N Aydin, Emma J Stinson, Tomás Cabeza De Baca, Takafumi Ando, Katherine T Travis, Paolo Piaggi, Jonathan Krakoff, Douglas C Chang
Author Information
  1. Beyza N Aydin: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA. beyza.aydin@nih.gov. ORCID
  2. Emma J Stinson: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA. ORCID
  3. Tomás Cabeza De Baca: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA. ORCID
  4. Takafumi Ando: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA.
  5. Katherine T Travis: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA.
  6. Paolo Piaggi: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA. ORCID
  7. Jonathan Krakoff: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA. ORCID
  8. Douglas C Chang: Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA.
PMID: 37833567 DOI: 10.1038/s41430-023-01347-y

Abstract

OBJECTIVE: The existence of seasonal changes in energy metabolism is uncertain. We investigated the relationship between the seasons and spontaneous physical activity (SPA), energy expenditure (EE), and other components measured in a respiratory chamber.
METHODS: Between 1985-2005, 671 healthy adults (aged 28.8 ± 7.1 years; 403 men) in Phoenix, Arizona had a 24-hour stay in the respiratory chamber equipped with radar sensors; SPA (expressed as a percentage over the time interval), the energy cost of SPA, EE, and respiratory exchange ratio (RER) were measured.
RESULTS: In models adjusted for known covariates, SPA (%) was lower during summer (7.2 ± 2.9, p = 0.0002), spring (7.5 ± 2.9, p = 0.025), and fall (7.6 ± 3, p = 0.038) compared to winter (8.3 ± 3.5, reference). Conversely, energy cost of SPA (kcal/h/%) was higher during summer (2.18 ± 0.83, p = 0.0008), spring (2.186 ± 0.83, p = 0.017), and fall (2.146 ± 0.75, p = 0.038) compared to winter (2.006 ± 0.76). Protein (292 ± 117 kcal/day, β = -21.2, p = 0.08) oxidation rates was lower in the summer compared to winter. Carbohydrate and lipid oxidation rates (kcal/day) did not differ across seasons. RER and 24-h EE did not differ by season.
CONCLUSION: SPA, representing fidgeting-like behavior in the chamber, demonstrated a winter peak and summer nadir in humans living in a desert climate. These findings indicate that the physiological propensity for movement may be affected by seasonal factors.
CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT00340132, NCT00342732.

Associated Data

ClinicalTrials.gov | NCT00342732; NCT00340132

References

  1. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet. 2011;377:557–67. https://doi.org/10.1016/S0140-6736(10)62037-5 [DOI: 10.1016/S0140-6736(10)62037-5]
  2. Hales CM, National Center for Health S. Prevalence of obesity and severe obesity among adults: United States, 2017–2018, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics: Hyattsville, MD, 2020.
  3. Garland T Jr., Schutz H, Chappell MA, Keeney BK, Meek TH, Copes LE, et al. The biological control of voluntary exercise, spontaneous physical activity and daily energy expenditure in relation to obesity: human and rodent perspectives. J Exp Biol. 2011;214:206–29. https://doi.org/10.1242/jeb.048397 [DOI: 10.1242/jeb.048397]
  4. Salmon J, Owen N, Crawford D, Bauman A, Sallis JF. Physical activity and sedentary behavior: a population-based study of barriers, enjoyment, and preference. Health Psychol. 2003;22:178–88. https://doi.org/10.1037//0278-6133.22.2.178 [DOI: 10.1037//0278-6133.22.2.178]
  5. Hut RA, Beersma DG. Evolution of time-keeping mechanisms: early emergence and adaptation to photoperiod. Philos Trans R Soc Lond B Biol Sci. 2011;366:2141–54. https://doi.org/10.1098/rstb.2010.0409 [DOI: 10.1098/rstb.2010.0409]
  6. Foster RG, Roenneberg T. Human responses to the geophysical daily, annual and lunar cycles. Curr Biol. 2008;18:R784–R794. https://doi.org/10.1016/j.cub.2008.07.003 [DOI: 10.1016/j.cub.2008.07.003]
  7. Lovegrove BG. The influence of climate on the basal metabolic rate of small mammals: a slow-fast metabolic continuum. J Comp Physiol B. 2003;173:87–112. https://doi.org/10.1007/s00360-002-0309-5 [DOI: 10.1007/s00360-002-0309-5]
  8. Storey KB, Storey JM. Aestivation: signaling and hypometabolism. J Exp Biol. 2012;215:1425–33. https://doi.org/10.1242/jeb.054403 [DOI: 10.1242/jeb.054403]
  9. Kitada K, Daub S, Zhang Y, Klein JD, Nakano D, Pedchenko T, et al. High salt intake reprioritizes osmolyte and energy metabolism for body fluid conservation. J Clin Invest. 2017;127:1944–59. https://doi.org/10.1172/JCI88532 [DOI: 10.1172/JCI88532]
  10. Gutman R, Yosha D, Choshniak I, Kronfeld-Schor N. Two strategies for coping with food shortage in desert golden spiny mice. Physiol Behav. 2007;90:95–102. https://doi.org/10.1016/j.physbeh.2006.08.033 [DOI: 10.1016/j.physbeh.2006.08.033]
  11. Bronson FH. Are humans seasonally photoperiodic? J Biol Rhythms. 2004;19:180–92. https://doi.org/10.1177/0748730404264658 [DOI: 10.1177/0748730404264658]
  12. Tucker P, Gilliland J. The effect of season and weather on physical activity: a systematic review. Public Health. 2007;121:909–22. https://doi.org/10.1016/j.puhe.2007.04.009 [DOI: 10.1016/j.puhe.2007.04.009]
  13. Beighle A, Alderman B, Morgan CF, Le Masurier G. Seasonality in children’s pedometer-measured physical activity levels. Res Q Exerc Sport. 2008;79:256–60. https://doi.org/10.1080/02701367.2008.10599488 [DOI: 10.1080/02701367.2008.10599488]
  14. Kolle E, Steene-Johannessen J, Andersen LB, Anderssen SA Seasonal variation in objectively assessed physical activity among children and adolescents in Norway: a cross-sectional study. Int J Behav Nutr Phy 2009; 6. https://doi.org/10.1186/1479-5868-6-36
  15. Hjorth MF, Chaput JP, Michaelsen K, Astrup A, Tetens I, Sjodin A. Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8-11 year-old Danish children: a repeated-measures study. BMC Public Health. 2013;13:808. https://doi.org/10.1186/1471-2458-13-808 [DOI: 10.1186/1471-2458-13-808]
  16. Atkin AJ, Sharp SJ, Harrison F, Brage S, Van Sluijs EM. Seasonal Variation in Children’s Physical Activity and Sedentary Time. Med Sci Sports Exerc. 2016;48:449–56. https://doi.org/10.1249/MSS.0000000000000786 [DOI: 10.1249/MSS.0000000000000786]
  17. Baranowski T, Thompson WO, DuRant RH, Baranowski J, Puhl J. Observations on physical activity in physical locations: age, gender, ethnicity, and month effects. Res Q Exerc Sport. 1993;64:127–33. https://doi.org/10.1080/02701367.1993.10608789 [DOI: 10.1080/02701367.1993.10608789]
  18. Goran MI, Nagy TR, Gower BA, Mazariegos M, Solomons N, Hood V, et al. Influence of sex, seasonality, ethnicity, and geographic location on the components of total energy expenditure in young children: implications for energy requirements. Am J Clin Nutr. 1998;68:675–82. https://doi.org/10.1093/ajcn/68.3.675 [DOI: 10.1093/ajcn/68.3.675]
  19. Plasqui G, Westerterp KR. Seasonal variation in total energy expenditure and physical activity in Dutch young adults. Obes Res. 2004;12:688–94. https://doi.org/10.1038/oby.2004.80 [DOI: 10.1038/oby.2004.80]
  20. Humpel N, Owen N, Leslie E. Environmental factors associated with adults’ participation in physical activity - A review. Am J Prev Med. 2002;22:188–99. https://doi.org/10.1016/S0749-3797(01)00426-3 [DOI: 10.1016/S0749-3797(01)00426-3]
  21. Travis KT, Ando T, Stinson EJ, Krakoff J, Gluck ME, Piaggi P, et al. Trends in spontaneous physical activity and energy expenditure among adults in a respiratory chamber, 1985 to 2005. Obesity (Silver Spring). 2022;30:645–54. https://doi.org/10.1002/oby.23347 [DOI: 10.1002/oby.23347]
  22. Xi B, Liang Y, He T, Reilly KH, Hu Y, Wang Q, et al. Secular trends in the prevalence of general and abdominal obesity among Chinese adults, 1993-2009. Obes Rev. 2012;13:287–96. https://doi.org/10.1111/j.1467-789X.2011.00944.x [DOI: 10.1111/j.1467-789X.2011.00944.x]
  23. Piaggi P, Thearle MS, Bogardus C, Krakoff J. Lower energy expenditure predicts long-term increases in weight and fat mass. J Clin Endocrinol Metab. 2013;98:E703–707. https://doi.org/10.1210/jc.2012-3529 [DOI: 10.1210/jc.2012-3529]
  24. Ravussin E, Lillioja S, Knowler WC, Christin L, Freymond D, Abbott WG, et al. Reduced rate of energy expenditure as a risk factor for body-weight gain. N Engl J Med. 1988;318:467–72. https://doi.org/10.1056/NEJM198802253180802 [DOI: 10.1056/NEJM198802253180802]
  25. Zurlo F, Lillioja S, Espositodelpuente A, Nyomba BL, Raz I, Saad MF, et al. Low Ratio of Fat to Carbohydrate Oxidation as Predictor of Weight-Gain - Study of 24-H Rq. American Journal of Physiology. 1990;259:E650–E657. [PMID: 2240203]
  26. Piaggi P, Thearle MS, Krakoff J, Votruba SB. Higher Daily Energy Expenditure and Respiratory Quotient, Rather Than Fat-Free Mass, Independently Determine Greater ad Libitum Overeating. J Clin Endocrinol Metab. 2015;100:3011–20. https://doi.org/10.1210/jc.2015-2164 [DOI: 10.1210/jc.2015-2164]
  27. Pannacciulli N, Salbe AD, Ortega E, Venti CA, Bogardus C, Krakoff J. The 24-h carbohydrate oxidation rate in a human respiratory chamber predicts ad libitum food intake. Am J Clin Nutr. 2007;86:625–32. https://doi.org/10.1093/ajcn/86.3.625 [DOI: 10.1093/ajcn/86.3.625]
  28. Salbe AD, Tschop MH, DelParigi A, Venti CA, Tataranni PA. Negative relationship between fasting plasma ghrelin concentrations and ad libitum food intake. J Clin Endocr Metab. 2004;89:2951–6. https://doi.org/10.1210/jc.2003-032145 [DOI: 10.1210/jc.2003-032145]
  29. Ferraro R, Boyce VL, Swinburn B, De Gregorio M, Ravussin E. Energy cost of physical activity on a metabolic ward in relationship to obesity. Am J Clin Nutr. 1991;53:1368–71. https://doi.org/10.1093/ajcn/53.6.1368 [DOI: 10.1093/ajcn/53.6.1368]
  30. Genuth S, Alberti KG, Bennett P, Buse J, Defronzo R, Kahn R, et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care. 2003;26:3160–7. https://doi.org/10.2337/diacare.26.11.3160 [DOI: 10.2337/diacare.26.11.3160]
  31. Tataranni PA, Ravussin E. Use of dual-energy X-ray absorptiometry in obese individuals. Am J Clin Nutr. 1995;62:730–4. https://doi.org/10.1093/ajcn/62.4.730 [DOI: 10.1093/ajcn/62.4.730]
  32. Guo Y, Franks PW, Brookshire T, Antonio Tataranni P. The intra- and inter-instrument reliability of DXA based on ex vivo soft tissue measurements. Obes Res. 2004;12:1925–9. https://doi.org/10.1038/oby.2004.241 [DOI: 10.1038/oby.2004.241]
  33. Ravussin E, Lillioja S, Anderson TE, Christin L, Bogardus C. Determinants of 24-hour energy expenditure in man. Methods and results using a respiratory chamber. J Clin Invest. 1986;78:1568–78. https://doi.org/10.1172/JCI112749 [DOI: 10.1172/JCI112749]
  34. Abbott WG, Howard BV, Christin L, Freymond D, Lillioja S, Boyce VL, et al. Short-term energy balance: relationship with protein, carbohydrate, and fat balances. Am J Physiol. 1988;255:E332–337. https://doi.org/10.1152/ajpendo.1988.255.3.E332 [DOI: 10.1152/ajpendo.1988.255.3.E332]
  35. Lusk G. Animal calorimetry. Twenty-fourth paper. Analysis of the oxidation of mixtures of carbohydrate and fat. A correction. J Biol Chem. 1924;59:41–42. [DOI: 10.1016/S0021-9258(18)85293-0]
  36. Jequier E, Acheson K, Schutz Y. Assessment of energy expenditure and fuel utilization in man. Annu Rev Nutr. 1987;7:187–208. https://doi.org/10.1146/annurev.nu.07.070187.001155 [DOI: 10.1146/annurev.nu.07.070187.001155]
  37. Basolo A, Shah MH, Parthasarathy V, Parrington S, Walter M, Votruba SB, et al. Thigh Adipocyte Size is Inversely Related to Energy Intake and Respiratory Quotient in Healthy Women. Obesity (Silver Spring). 2020;28:1129–40. https://doi.org/10.1002/oby.22804 [DOI: 10.1002/oby.22804]
  38. Piaggi P, Krakoff J, Bogardus C, Thearle MS. Lower “awake and fed thermogenesis” predicts future weight gain in subjects with abdominal adiposity. Diabetes. 2013;62:4043–51. https://doi.org/10.2337/db13-0785 [DOI: 10.2337/db13-0785]
  39. Menne MJ, I Durre, B Korzeniewski, S McNeal, K Thomas, X Yin, et al. Global Historical Climatology Network - Daily (GHCN-Daily), Version 3. In: Center NNCD, (ed), 2012.
  40. Ellis BJ, Figueredo AJ, Brumbach BH, Schlomer GL. Fundamental Dimensions of Environmental Risk : The Impact of Harsh versus Unpredictable Environments on the Evolution and Development of Life History Strategies. Hum Nat. 2009;20:204–68. https://doi.org/10.1007/s12110-009-9063-7 [DOI: 10.1007/s12110-009-9063-7]
  41. Chang DC, Basolo A, Piaggi P, Votruba SB, Krakoff J. Hydration biomarkers and copeptin: relationship with ad libitum energy intake, energy expenditure, and metabolic fuel selection. Eur J Clin Nutr. 2020;74:158–66. https://doi.org/10.1038/s41430-019-0445-6 [DOI: 10.1038/s41430-019-0445-6]
  42. Ho JY, Goggins WB, Mo PKH, Chan EYY. The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities. Int J Behav Nutr Phys Act. 2022;19:68 https://doi.org/10.1186/s12966-022-01285-1 [DOI: 10.1186/s12966-022-01285-1]
  43. Tendler A, Bar A, Mendelsohn-Cohen N, Karin O, Korem Kohanim Y, Maimon L et al. Hormone seasonality in medical records suggests circannual endocrine circuits. Proc Natl Acad Sci USA 2021; 118. https://doi.org/10.1073/pnas.2003926118
  44. Berglund L, Berne C, Svardsudd K, Garmo H, Melhus H, Zethelius B. Seasonal variations of insulin sensitivity from a euglycemic insulin clamp in elderly men. Ups J Med Sci. 2012;117:35–40. https://doi.org/10.3109/03009734.2011.628422 [DOI: 10.3109/03009734.2011.628422]
  45. Ockene IS, Chiriboga DE, Stanek EJ 3rd, Harmatz MG, Nicolosi R, Saperia G, et al. Seasonal variation in serum cholesterol levels: treatment implications and possible mechanisms. Arch Intern Med. 2004;164:863–70. https://doi.org/10.1001/archinte.164.8.863 [DOI: 10.1001/archinte.164.8.863]
  46. Dopico XC, Evangelou M, Ferreira RC, Guo H, Pekalski ML, Smyth DJ, et al. Widespread seasonal gene expression reveals annual differences in human immunity and physiology. Nat Commun. 2015;6:7000 https://doi.org/10.1038/ncomms8000 [DOI: 10.1038/ncomms8000]
  47. Kirsz K, Szczesna M, Molik E, Misztal T, Wojtowicz AK, Zieba DA. Seasonal changes in the interactions among leptin, ghrelin, and orexin in sheep. J Anim Sci. 2012;90:2524–31. https://doi.org/10.2527/jas.2011-4463 [DOI: 10.2527/jas.2011-4463]
  48. Boddum K, Hansen MH, Jennum PJ, Kornum BR. Cerebrospinal Fluid Hypocretin-1 (Orexin-A) Level Fluctuates with Season and Correlates with Day Length. PLoS One. 2016;11:e0151288 https://doi.org/10.1371/journal.pone.0151288 [DOI: 10.1371/journal.pone.0151288]
  49. Amati F, Dube JJ, Shay C, Goodpaster BH. Separate and combined effects of exercise training and weight loss on exercise efficiency and substrate oxidation. J Appl Physiol (1985). 2008;105:825–31. https://doi.org/10.1152/japplphysiol.90384.2008 [DOI: 10.1152/japplphysiol.90384.2008]
  50. Wucher V, Sodaei R, Amador R, Irimia M, Guigo R Day-night and seasonal variation of human gene expression across tissues. bioRxiv 2022. e-pub ahead of print 20220111; https://doi.org/10.1101/2021.02.28.433266
  51. Levine JA, Schleusner SJ, Jensen MD. Energy expenditure of nonexercise activity. Am J Clin Nutr. 2000;72:1451–4. https://doi.org/10.1093/ajcn/72.6.1451 [DOI: 10.1093/ajcn/72.6.1451]
  52. Zurlo F, Ferraro RT, Fontvielle AM, Rising R, Bogardus C, Ravussin E. Spontaneous physical activity and obesity: cross-sectional and longitudinal studies in Pima Indians. Am J Physiol. 1992;263:E296–300. https://doi.org/10.1152/ajpendo.1992.263.2.E296 [DOI: 10.1152/ajpendo.1992.263.2.E296]
  53. Snitker S, Tataranni PA, Ravussin E. Spontaneous physical activity in a respiratory chamber is correlated to habitual physical activity. Int J Obesity. 2001;25:1481–6. https://doi.org/10.1038/sj.ijo.0801746 [DOI: 10.1038/sj.ijo.0801746]

Grants

  1. DK069015-36/U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
  2. DK069091-12/U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)

MeSH Term

Adult
Male
Humans
Arizona
Energy Metabolism
Exercise
Oxidation-Reduction
Seasons
Journal Article

Word Cloud

Created with Highcharts 10.0.0p = 0SPAenergy2respiratorychambersummerwinterEE7comparedseasonalseasonsspontaneousphysicalactivityexpendituremeasuredPhoenixArizonacostRERlower9springfall03883oxidationratesdifferOBJECTIVE:existencechangesmetabolismuncertaininvestigatedrelationshipcomponentsMETHODS:1985-2005671healthyadultsaged288 ± 71years403men24-hourstayequippedradarsensorsexpressedpercentagetimeintervalexchangeratioRESULTS:modelsadjustedknowncovariates%2 ± 200025 ± 20256 ± 383 ± 35referenceConverselykcal/h/%higher18 ± 00008186 ± 0017146 ± 075006 ± 076Protein292 ± 117 kcal/dayβ = -2108Carbohydratelipidkcal/dayacross24-hseasonCONCLUSION:representingfidgeting-likebehaviordemonstratedpeaknadirhumanslivingdesertclimatefindingsindicatephysiologicalpropensitymovementmayaffectedfactorsCLINICALTRIALREGISTRATION:ClinicalTrialsgovidentifiers:NCT00340132NCT00342732Investigationseasonalityhuman

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