Literature DB >> 7827002

The influence of exercise on the energy requirements of adult males in the UK.

P Haggarty1, G McNeill, M K Manneh, L Davidson, E Milne, G Duncan, J Ashton.   

Abstract

Energy expenditure was measured over 10 d using the doubly-labelled water (DLW) and activity diary methods in summer and winter in subjects with 'light' occupations but leisure activities which ranged from 'non-active' to 'very active'. The basal metabolic rate (BMR) and the energy cost of activities were determined by indirect calorimetry. The Department of Health (1991) predicted BMR for the group (6.89 (SD 0.30) MJ/d; n 18) was not significantly different from the measured value (7.17 (SD 0.70) MJ/d; n 18). The range of DLW-derived expenditure values within the group was BMR x 1.41 to 2.41. The largest seasonal change within individuals was BMR x 0.5. The energy expenditure of the group as a whole was lower in winter (BMR x 1.88; SD 0.33; n 9) than summer (BMR x 2.01; SD 0.30; n 9) though the difference was not statistically significant. The average summer and winter DLW-derived expenditure was BMR x 1.96 (SD 0.31; n 17). The activity diary estimate of expenditure was BMR x 1.79 (SD 0.32; n 17). In a subset of the group who were representative of the most active 26% of all adult males in the UK, the DLW-derived expenditure was BMR x 2.08 (SD 0.24; n 11). This is higher than the highest Department of Health (1991) estimate of BMR x 1.6 for individuals in light occupations. The measured energy costs of low-intensity activities were similar to those presented in the Department of Health (1991) report but the value determined for running (BMR x 13.08; SD 2.4; n 6) was higher than the highest value in the report (BMR x 6 to 8). The results indicate that the recent Department of Health (1991) reference values for energy may underestimate the expenditure of a significant proportion of the UK population largely because the energy costs of activity used in the report to calculate expenditure do not accurately reflect those achieved during active leisure in individuals who take regular exercise.

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Mesh:

Year:  1994        PMID: 7827002     DOI: 10.1079/bjn19940086

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  11 in total

1.  Meteorology and the physical activity of the elderly: the Nakanojo Study.

Authors:  Fumiharu Togo; Eiji Watanabe; Hyuntae Park; Roy J Shephard; Yukitoshi Aoyagi
Journal:  Int J Biometeorol       Date:  2005-07-26       Impact factor: 3.787

2.  Seasonal variation in food intake, physical activity, and body weight in a predominantly overweight population.

Authors:  Y Ma; B C Olendzki; W Li; A R Hafner; D Chiriboga; J R Hebert; M Campbell; M Sarnie; I S Ockene
Journal:  Eur J Clin Nutr       Date:  2006-04       Impact factor: 4.016

3.  Lack of Seasonal Differences in Basal Metabolic Rate in Humans: A Cross-Sectional Study.

Authors:  Pimjai Anthanont; James A Levine; Shelly K McCrady-Spitzer; Michael D Jensen
Journal:  Horm Metab Res       Date:  2016-07-13       Impact factor: 2.936

Review 4.  Seasonal variations in physical activity and implications for human health.

Authors:  Roy J Shephard; Yukitoshi Aoyagi
Journal:  Eur J Appl Physiol       Date:  2009-07-16       Impact factor: 3.078

5.  Steps per day: the road to senior health?

Authors:  Yukitoshi Aoyagi; Roy J Shephard
Journal:  Sports Med       Date:  2009       Impact factor: 11.136

6.  Seasonal changes in amount and patterns of physical activity in women.

Authors:  Maciej S Buchowski; Leena Choi; Karen M Majchrzak; Sari Acra; Charles E Mathews; Kong Y Chen
Journal:  J Phys Act Health       Date:  2009-03

Review 7.  Assessing the effects of weather conditions on physical activity participation using objective measures.

Authors:  Catherine B Chan; Daniel A Ryan
Journal:  Int J Environ Res Public Health       Date:  2009-10-12       Impact factor: 3.390

8.  Year-round high physical activity levels in agropastoralists of Bolivian Andes: results from repeated measurements of DLW method in peak and slack seasons of agricultural activities.

Authors:  Hiroshi Kashiwazaki; Kazuhiro Uenishi; Toshio Kobayashi; Jose Orias Rivera; William A Coward; Antony Wright
Journal:  Am J Hum Biol       Date:  2009 May-Jun       Impact factor: 1.937

9.  Seasonal variation in the distribution of daily stepping in 11-13 year old school children.

Authors:  P R W McCrorie; E Duncan; M H Granat; B W Stansfield
Journal:  Int J Exerc Sci       Date:  2015

10.  Seasonal Variation and Global Public Interest in the Internet Searches for Osteoporosis.

Authors:  Chao Wang; Xiong Shu; Jianfeng Tao; Yanzhuo Zhang; Yue Yuan; Chengai Wu
Journal:  Biomed Res Int       Date:  2021-06-04       Impact factor: 3.411

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