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Cited by 25Physical Activity and HealthObesity, Physical Activity, DietBody Composition Measurement Techniques

Energy costs of standard activities among Indian adults.

Kanade, AN, Gokhale, MK, Rao, S·2001·European Journal of Clinical Nutrition
DOI 10.1038/sj.ejcn.1601211
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Abstract

Objectives To estimate the energy cost of resting (RMR), sitting and standing for urban Indian adults and compare these estimates with the reported values.Design Energy costs were measured using oxylog while body fat was estimated using equipment (HBF300, OMRON Corporation, Japan) that works on the principle of bioelectrical impedance, for 24 men and 40 women, aged 20-50 y, engaged in sedentary activities.Settings Agharkar Research Institute, Pune, India.Results Mean energy cost (kJ/min) of resting (RMR), sitting and standing were significantly (P<0.01, for all) higher for men (4.01+/-0.42, 5.0+/-0.72 and 5.74+/-0.69, respectively) than women (3.54+/-0.28, 4.03+/-0.41 and 4.35+/-0.52, respectively). Gender difference increased with the level of activity, from 13% for RMR to 32% for standing. These differences reduced when adjusted (using analysis of covariance) for body weight and became non-significant on adjusting for fat-free mass (FFM) in the case of RMR and sitting activity. The measured values of energy cost (absolute and per kg weight) for these activities were similar to African subjects but lower compared to Asian or European subjects for both sexes. The stepwise regression analysis done separately by sexes showed weight (29%) in men and body mass index (44%) in women to be the best predictors of RMR, while regression analysis for combined sexes indicated FFM and height as predictors of RMR (r(2)=56%, P<0.01). If means to estimate body fat were not available, RMR could best be predicted with BMI and sex as predictors (r(2)=55%; P<0.01). This was mainly due to the fact that the sex differences in our population were more prominent in FFM than that in BMI. Our observations thus indicate the need to develop prediction equations separately for different populations owing to differences in their body compositions, especially in fat mass (FM) or FFM.Conclusion The energy costs of activities were associated with body composition, especially with absolute fat-free mass, which may vary even with the same body fat percentage. Therefore, there is a need to develop separate prediction equations for different communities.

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  • Resting metabolic rate (kcal kg−1 s−1) was similar among Hadza and Western groups.

    “The metabolic cost of walking (kcal kg−1 m−1) and resting (kcal kg−1 s−1) were also similar among Hadza and Western groups.”

    From Hunter-gatherer energetics and human obesity (2012) · cites this paper as [35]

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Authors
Kanade, A., Gokhale, M., & Rao, S.
Affiliations
Agharkar Research Institute (IN)
Corresponding author
Rao, S
Venue
European Journal of Clinical Nutrition
Publisher
Springer Science and Business Media LLC
Published
2001-07-24
Volume
55
Issue
8
Pages
708-713
ISSN
  • 0954-3007 (ISSN-L)
  • 1476-5640
DOI
10.1038/sj.ejcn.1601211
OpenAlex
W2332200559
Cited by
25
References
32
Citations by year
2022: 1 · 2020: 2 · 2019: 2 · 2018: 2 · 2017: 3 · 2016: 1 · 2015: 1 · 2013: 6 · 2012: 1
FWCI
0.00
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • European Journal of Clinical Nutrition (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Agharkar Research Institute
  • Rocky Mountain Research Station
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
Keywords
energy expenditure, resting metabolic rate, sitting, standing, sedentary activity, sex differences, body composition, fat-free mass, body mass index, prediction equations, Indian adults, urban population
MeSH terms
Adult, Basal Metabolism, Body Composition, Body Weight, Energy Metabolism, Female, Humans, Human Activities, India, Male, Middle Aged, Sex Factors, Urban Population, Body Mass Index

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