Resting and Physical Activity Energy Expenditure Across an Altitudinal Gradient: An Adjusted Analysis
Abstract
1. Introduction
2. Materials and Methods
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- Ethical aspects: Participants voluntarily agreed to take part in the study after each procedure and the potential usefulness of the results had been thoroughly explained, and they subsequently signed an informed consent authorizing the corresponding measurements.This study followed the guidelines of the Declaration of Helsinki on research involving human subjects and was approved by the USMP Ethics Committee with the International Registry Federalwide Assurance (FWA) for the Protection of Human Subjects for International No. 00015320. U.S. Department of Health and Human Services (HHS) Registration of an Institutional Review Board (IRB) IRB No. 00003251.
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- Study Population: The study population consisted of 141 healthy subjects: 70 women and 71 men. 40 subjects (20 women and 20 men) were residing in Lima, 40 (20 women and 20 men) in Arequipa, 42 (21 women and 21 men) in Puno, and 19 (9 women and 10 men) in La Rinconada. The age range of participants was between 18 and 38 years old. They were selected according to predefined inclusion criteria: individuals in apparent good health who had resided in their respective localities for at least one year, thereby ensuring chronic exposure to local environmental and hypoxic conditions. To estimate the level of habitual physical activity (sedentary, light, moderate, or intense), the Spanish short version of the International Physical Activity Questionnaire (IPAQ-SF) was administered, selecting for the study those classified as having moderate physical activity [18,19,20]. Thus, all participants were able to complete the six-minute walk test (6MWT), undergo basal metabolic and vital sign measurements, and supply the required demographic information. Exclusion criteria included refusal to participate; any limitation preventing engagement in light-to-moderate physical activity; the onset of discomfort leading to withdrawal during assessments; or inability to complete the full set of required measurements.Procedure: The assessments were conducted in a controlled environment between 8:00 and 10:00 a.m. [21]. Similar environmental conditions were maintained in all the study cities, and participants wore light clothing. Specifically, the ambient temperature was kept between 10 and 20 °C, and the terrain was completely flat.Before the assessment, subjects were required to: refrain from vigorous exercise for 24 h and moderate exercise for at least 2 h prior to the evaluation; observe a 5- to 6-h fast to minimize the thermic effect of food; and completely abstain from stimulants (caffeine, nicotine) and alcohol for 12 to 24 h [22,23]. Finally, a 10-min period of absolute rest was mandated in a quiet environment before measurement to ensure stability in oxygen consumption (VO2) and reduce emotional stress [24].Body weight was recorded using a Tanita BC 545N segmental body analysis scale (Tanita, Tokyo, Japan), which employs the bioelectrical impedance method [25]. Height was measured with a DETECTO 2391 stadiometer (Cardinal/Detecto Scale, Webb City, MO, USA) [26].To determine Hb and hematocrit (Hct) levels, blood samples were obtained from the middle fingertip. A capillary puncture was performed using a sterile lancet, the first two drops were discarded, and the third drop was then collected to fill the microcuvette. Hb levels were assessed using a portable Hb 201+ hemoglobinometer (HemoCue AB, Ängelholm, Sweden) employing the azidimethemoglobin method within a measurement range of 0 to 25.60 g/dL. Hct measurements were performed using a Hemata Stat II microcentrifuge (EKF Diagnostics, Boerne, TX, USA).The Kalenji HR500 smartwatch (Decathlon, Villeneuve-d’Ascq, France), worn on the right wrist in contact with the skin, was employed to measure chronotropic response (CR) and EE. To determine REE, a continuous 5-min period of physiological stability, or steady state, was first identified after acclimatization. This steady state was confirmed if the heart rate’s (HR) coefficient of variation (CV) was ≤10%, calculated using the formula presented in Equation (1).where represents the standard deviation and the mean HR within that interval. The mean heart rate obtained during this steady-state period was subsequently used as the reference value for analysis.REE was assessed over a 20-min period after participants reached a physiological steady-state while resting, with no physical exertion. Caloric expenditure was calculated in Kcal/min. For the measure of physical exertion, the 6MWT was administered following the American Thoracic Society (ATS) protocol. Participants were instructed to cover the greatest possible distance on a 60-m, obstacle-free course [27]. Continuous HR monitoring at the wrist was performed using the watch’s PPG sensor, allowing for REE immediate estimation upon completion of this test.For kilocalorie consumption calculation, the device’s algorithm combines the chronotropic response with the subject’s anthropometric variables (age, sex, weight, and height) to estimate basal metabolic rate and EE from physical activity [28].Vital signs were measured before and after REE and PAEE measurements. Systolic and diastolic blood pressure (SBP and DBP) and HR were measured using a Riester Ri-Champion adult digital upper arm sphygmomanometer (Rudolf Riester GmbH, Jungingen, Germany), with a measurement range of 30 to 280 mm Hg and an HR range of 40 to 200 beats per minute. SpO2 was measured using a Nellcor® Oximax® N-65 portable pulse oximeter (DigiCare Biomedical, Boynton Beach, FL, USA) with a saturation resolution of 1% and an HR range of 30 to 235 beats per minute.EE = gender × (−55.0969 + 0.6309 × heart rate + 0.1988 × weight + 0.2017 × age) + (1 − gender) × (−20.4022 + 0.4472 × heart rate − 0.1263 × weight + 0.074 × age)
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- Statistical Analysis: Data normality was verified using the Kolmogorov–Smirnov test. Descriptive statistics were expressed using measures of central tendency and dispersion. Bivariate comparisons across altitude groups were performed using Student’s t-test, one-way ANOVA, and Kruskal–Wallis tests, with Tukey’s Honestly Significant Difference (HSD) applied for post-hoc analyses. Associations between physiological variables were assessed using Pearson correlation coefficients and simple linear regression models. To account for potential confounders and isolate the independent effect of altitude on EE, an analysis of covariance (ANCOVA) was employed, adjusting for age, sex, and body mass index (BMI) as covariates. All statistical analyses were performed using Python version 3.0 and the threshold for statistical significance was set at p < 0.05.
3. Results
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Women | Men | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Lima N = 40 | Arequipa N = 20 | Puno N = 21 | La Rinconada N = 09 | p Value | Lima N = 20 | Arequipa N = 20 | Puno N = 21 | La Rinconada N = 10 | p Value | |
| Age (years) | 21.9 ± 1.6 | 22.3 ± 2.5 | 23.6 ± 1.9 | 27.6 ± 5.3 | 0.000 * | 20.9 ± 2.4 | 22.8 ± 2.1 | 24.1 ± 2.6 | 34.2 ± 2.6 | 0.000 * |
| BMI (kg/m2) | 24.7 ± 2.8 | 24.8 ± 2.1 | 24.1 ± 3.1 | 25.9 ± 5.8 | 0.523 | 24.4 ± 2.9 | 25.6 ± 2.8 | 24.7 ± 3.9 | 28.0 ± 4.2 | 0.043 * |
| Women | Men | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Lima | Arequipa | Puno | La Rinconada | p Value | Lima | Arequipa | Puno | La Rinconada | p Value | |
| SpO2 (%) | 98.6 ± 0.4 | 95.6 ± 0.4 | 93.0 ± 0.4 | 81.9 ± 0.6 | <0.001 * | 98.0 ± 0.4 | 95.0 ± 0.4 | 92.4 ± 0.4 | 81.3 ± 0.7 | <0.001 * |
| HR (bpm) | 72.2 ± 1.6 | 80.1 ± 1.5 | 77.0 ± 1.5 | 83.3 ± 2.7 | <0.001 * | 69.1 ± 1.5 | 77.0 ± 1.5 | 73.9 ± 1.4 | 80.2 ± 2.8 | 0.350 * |
| Hb (g/dL) | 13.2 ± 0.3 | 13.7 ± 0.2 | 15.4 ± 0.2 | 18.3 ± 0.4 | <0.001 * | 15.0 ± 0.2 | 15.5 ± 0.2 | 17.2 ± 0.2 | 20.1 ± 0.4 | <0.001 * |
| Hct (%) | 39.4 ± 0.7 | 41.3 ± 0.7 | 46.0 ± 0.7 | 55.1 ± 1.2 | <0.001 * | 45.0 ± 0.7 | 46.8 ± 0.7 | 51.6 ± 0.7 | 60.7 ± 1.3 | <0.001 * |
| SBP (mmHg) | 103.3 ± 2.2 | 99.2 ± 2.0 | 102.2 ± 1.9 | 104.9 ± 3.6 | 0.096 | 114.7 ± 2.1 | 110.6 ± 2.0 | 113.6 ± 1.9 | 116.4 ± 3.8 | 0.970 |
| DBP (mmHg) | 71.6 ± 2.0 | 64.8 ± 1.9 | 65.9 ± 1.8 | 71.8 ± 3.3 | 0.003 * | 77.7 ± 1.9 | 70.9 ± 1.8 | 72.0 ± 1.8 | 77.9 ± 3.4 | 0.688 |
| MAP (mmHg) | 82.2 ± 1.9 | 76.3 ± 1.7 | 78.0 ± 1.7 | 82.9 ± 3.0 | 0.006 * | 90.0 ± 1.8 | 84.1 ± 1.7 | 85.9 ± 1.6 | 90.7 ± 3.2 | 0.786 |
| Sex | Lima Median (IR) | Arequipa Median (IR) | Puno Median (IR) | La Rinconada Median (IR) | p-Value |
|---|---|---|---|---|---|
| Men | 1040 (850–1250) | 1060 (870–1230) | 1050 (840–1260) | 1030 (860–1240) | 0.997 |
| Women | 940 (750–1100) | 950 (760–1120) | 930 (740–1130) | 960 (770–1100) |
| City | Women (Mean ± SD) | Men (Mean ± SD) | p Value (t-Test) |
|---|---|---|---|
| Lima | 1.04 ± 0.26 | 1.11 ± 0.27 | 0.393 |
| Arequipa | 1.65 ± 0.50 | 1.27 ± 0.58 | 0.029 * |
| Puno | 1.46 ± 0.58 | 1.25 ± 0.66 | 0.278 |
| La Rinconada | 2.08 ± 0.82 | 2.48 ± 0.97 | 0.348 |
| Source of Variation | df | F | p-Value |
|---|---|---|---|
| Adjusted Model | 15 | 4.966 | <0.001 |
| City | 3 | 0.400 | 0.753 |
| Age | 1 | 0.483 | 0.488 |
| Sex | 1 | 0.059 | 0.808 |
| BMI | 1 | 0.200 | 0.656 |
| Source of Variation | df | F | p-Value |
|---|---|---|---|
| Overall Model | 15 | 8.050 | <0.001 |
| City | 3 | 2.403 | 0.071 |
| Age | 1 | 1.509 | 0.222 |
| Sex | 1 | 0.124 | 0.726 |
| BMI | 1 | 0.097 | 0.756 |
| City | 6MWT | HR After Physical Activity | Energy Expenditure During Physical Activity | ||||
|---|---|---|---|---|---|---|---|
| Distance (m) | p | HR (beats/min) | p | Women (kcal/min) | Men (kcal/min) | p Value | |
| Lima | 339.8 ± 20.1 | 0.830 | 92.1 ± 9.3 | 0.001 * | 4.44 ± 0.86 | 4.70 ± 1.02 | 0.391 |
| Arequipa | 342.1 ± 14.8 | 97.7 ± 13.6 | 5.54 ± 1.35 | 5.13 ± 1.45 | 0.363 | ||
| Puno | 338.5 ± 18.2 | 102.4 ± 12.0 | 6.46 ± 0.97 | 6.17 ± 1.82 | 0.520 | ||
| La Rinconada | 340.2 ± 15.5 | 107.6 ± 9.8 | 6.80 ± 0.87 | 8.43 ± 1.69 | 0.018 * | ||
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Bernedo-Itusaca, M.E.; Cutipa-Tinta, S.; Merma-Valero, J.M.; Cruz-Riquelme, T.M.; Flores-Coila, S.T.; Coa-Coila, M.A.; Coriman-Cuentas, C.A.; Condori-Apaza, M.A.; Pérez-Flores, R.K.; Ramos Allazo, R.d.R.; et al. Resting and Physical Activity Energy Expenditure Across an Altitudinal Gradient: An Adjusted Analysis. Oxygen 2026, 6, 19. https://doi.org/10.3390/oxygen6030019
Bernedo-Itusaca ME, Cutipa-Tinta S, Merma-Valero JM, Cruz-Riquelme TM, Flores-Coila ST, Coa-Coila MA, Coriman-Cuentas CA, Condori-Apaza MA, Pérez-Flores RK, Ramos Allazo RdR, et al. Resting and Physical Activity Energy Expenditure Across an Altitudinal Gradient: An Adjusted Analysis. Oxygen. 2026; 6(3):19. https://doi.org/10.3390/oxygen6030019
Chicago/Turabian StyleBernedo-Itusaca, Margot Evelin, Shantal Cutipa-Tinta, Judith Marie Merma-Valero, Tatiana Milagros Cruz-Riquelme, Sintia Tatiana Flores-Coila, Mahely Adriana Coa-Coila, Claudia Alejandra Coriman-Cuentas, Mayra Anay Condori-Apaza, Ruth Karina Pérez-Flores, Rocío del Rosario Ramos Allazo, and et al. 2026. "Resting and Physical Activity Energy Expenditure Across an Altitudinal Gradient: An Adjusted Analysis" Oxygen 6, no. 3: 19. https://doi.org/10.3390/oxygen6030019
APA StyleBernedo-Itusaca, M. E., Cutipa-Tinta, S., Merma-Valero, J. M., Cruz-Riquelme, T. M., Flores-Coila, S. T., Coa-Coila, M. A., Coriman-Cuentas, C. A., Condori-Apaza, M. A., Pérez-Flores, R. K., Ramos Allazo, R. d. R., Abollaneda Amao, M. S., Salazar Granara, A. A., Pacheco-Barrios, K., Yang, M., Viscor, G., & Hancco Zirena, I. (2026). Resting and Physical Activity Energy Expenditure Across an Altitudinal Gradient: An Adjusted Analysis. Oxygen, 6(3), 19. https://doi.org/10.3390/oxygen6030019

