In chronic spinal cord injury (SCI), individuals experience dietary inadequacies complicated by an understudied research area. Our objectives were to assess (1) the agreement between methods of estimating energy requirement (EER) and estimated energy intake (EEI) and (2) whether dietary protein intake met SCI-specific protein guidelines. Persons with chronic SCI (n = 43) completed 3-day food records to assess EEI and dietary protein intake. EER was determined with the Long and Institute of Medicine (IOM) methods and the SCI-specific Farkas method. Protein requirements were calculated as 0·8–1·0 g/kg of body weight (BW)/d. Reporting accuracy and bias were calculated and correlated to body composition. Compared with IOM and Long methods (P < 0·05), the SCI-specific method did not overestimate the EEI (P = 0·200). Reporting accuracy and bias were best for SCI-specific (98·9 %, −1·12 %) compared with Long (94·8 %, −5·24 %) and IOM (64·1 %, −35·4 %) methods. BW (r = –0·403), BMI (r = –0·323) and total fat mass (r = –0·346) correlated with the IOM reporting bias (all, P < 0·05). BW correlated with the SCI-specific and Long reporting bias (r = –0·313, P = 0·041). Seven (16 %) participants met BW-specific protein guidelines. The regression of dietary protein intake on BW demonstrated no association between the variables (β = 0·067, P = 0·730). In contrast, for every 1 kg increase in BW, the delta between total and required protein intake decreased by 0·833 g (P = 0·0001). The SCI-specific method for EER had the best agreement with the EEI. Protein intake decreased with increasing BW, contrary to protein requirements for chronic SCI.

Polyplacophoran molluscs (chitons) are phylogenetically ancient and morphologically constrained, yet multiple living species are often found co-occurring within widely overlapping ecological niches. This study used two sets of experiments to compare interspecific variation among co-occurring species in the North Atlantic (Ireland) and separately in the North Pacific (British Columbia, Canada) chiton faunas. A complementary review of historical literature on polyplacophoran physiology provides an overview of the high level of metabolic variability in this group of ‘living fossils’. Species examined in de novo experiments showed significant variation in oxygen consumption both under air-saturated water conditions (normoxia), and in response to decreasing oxygen availability (hypoxia). Some species demonstrate an ability to maintain constant oxygen uptake rates despite hypoxia (oxyregulators), while others oxyconform, with uptake rate dependent on ambient oxygen tension. These organisms are often amalgamated in studies of benthic communities, yet show obvious physiological difference that may impact their response or tolerance to environmental change.

Measurement of energy expenditure in humans is required to assess metabolic needs, fuel utilisation, and the relative thermic effect of different food, drink, drug and emotional components. Indirect and direct calorimetric and non-calorimetric methods for measuring energy expenditure are reviewed, and their relative value for measurement in the laboratory and field settings is assessed. Where high accuracy is required and sufficient resources are available, an open-circuit indirect calorimeter can be used. Open-circuit indirect calorimeters can employ a mask, hood, canopy or room/chamber for collection of expired air. For short-term measurements, mask, hood or canopy systems suffice. Chamber-based systems are more accurate for the long-term measurement of specified activity patterns but behaviour constraints mean they do not reflect real life. Where resources are limited and/or optimum precision can be sacrificed, flexible total collection systems and non-calorimetric methods are potentially useful if the limitations of these methods are appreciated. The use of the stable isotope technique, doubly labelled water, enables total daily energy expenditure to be measured accurately in free-living subjects. The factorial method for combining activity logs and data on the energy costs of activities can also provide detailed information on free-living subjects.

According to the report of the World Health Organization (1985), total energy expenditure (TEE) in human subjects can be calculated as BMR×physical activity level (PAL). However, other reports have pointed out limitations in the suggested procedure related to the % body fat of the subjects. The purpose of the present study was to evaluate the World Health Organization (1985) procedure in thirty-four healthy women with BMI 18–39kg/m2. BMR and TEE were measured using indirect calorimetry (BMRmeas) and the doubly-labelled water method (TEEref) respectively. When assessed using the doubly-labelled water and skinfold-thickness methods, the women had 34 (sd 8) and 33 (sd 6) % body fat respectively. On the basis of guidelines provided by the World Health Organization (1985), 1·64 was selected to represent the average PAL of the women. Furthermore, PAL was also assessed by means of an accelerometer (PALacc), heart-rate recordings (PALHR) and a questionnaire (PALq). These estimates were: PALacc 1·71 (sd 0·17), PALHR 1·76 (sd 0·24), PALq 1·86 (sd 0·27). These values were lower than TEEref/BMRref, which was 1·98 (sd 0·21). BMR assessed using equations recommended by the World Health Organization (1985) (BMRpredicted) overestimated BMR by 594 (sd 431) kJ/24h. However, when TEE was calculated as BMRpredicted×PALacc, BMRpredicted×PALHR and BMRpredicted×PALq respectively, average results were in agreement with TEEref. Furthermore, TEE values based on BMRpredicted and PALacc, PALHR, PALq as well as on PAL=1·64, minus TEEref, were significantly correlated with body fatness. When the same PAL value (1·64) was used for all subjects, this correlation was particularly strong. Thus, the World Health Organization (1985) procedure may give TEE results that are biased with respect to the body fatness of subjects.

The effect of diet quality on basal metabolic rate (BMR) over time was studied in female Octodon degus. Degus fed on a low-quality diet maintained a constant BMR over time, while those fed on a high-quality diet showed an increased BMR after 30 days. After 120 days of dietary acclimation, individuals fed on a high-quality diet exhibited comparatively higher BMRs. Thus, we hypothesize that when environmental food quality is high, degus are able to increase their BMR quickly, allowing high rates of biosynthesis.

A lower BMR of Indians, when compared with Westerners matched for age, sex, and either surface area or body weight, has often been reported in the literature and has been interpreted to reflect an ethnic influence on BMR. To determine the contribution of body composition to these observed differences in BMR, we analysed the data on ninety-six Indians and eighty-one Caucasian Australians of both sexes, aged 18–30 years, studied in Bangalore, India and Melbourne, Australia. Absolute BMR and BMR adjusted for body weight were significantly lower in Indians when compared with Australians of the corresponding sex. However, BMR adjusted for fat-free mass (FFM) in men, and BMR adjusted for FFM and fat mass (FM) in women, were not significantly different between the two groups. Stepwise regression of FFM, FM, sex (0 = women; 1 = men) and ethnicity (0 = Indian; 1 = Australian) on BMR, resulted in the following relationship for the combined data on all subjects: BMR=88.7 × FFM (kg) + 1713 (n 177; r 0.92; r2 0.85; see 425 kJ). The Indian equations of Hayter & Henry (1994), based on body weight, resulted in a significant bias (measured – predicted BMR) of 318 (SE 54) kJ/d in Indian men and -409 (SE 70) kJ/d in Indian women. The equation of Cunningham (1991), based on FFM, accurately predicted the BMR of Indian men, Indian women and Australian men. The small but significant bias of 185 (SE 61)kJ/d in Australian women, may be explained by the significant contribution of FM to BMR in this group. The present study does not provide any evidence for an ethnic influence on basal metabolism. The results strongly support the use of FFM, rather than body weight, for the prediction of BMR in population groups of varying body size and composition. This would allow an accurate estimation of BMR and hence energy requirements in population groups worldwide.

The use of oral contraceptive agents by women may be a factor that contributes to the observed inter-individual variability in the BMR. We, therefore, measured the BMR, body build and composition in two groups of young women and also assessed their self-reported level of physical activity. One group had been using oral contraceptive agents for a period of 6 months or more (OCA, n 24), while the other group had never used oral contraceptives (NOCA, n 22). There were no significant differences in age, body build or composition. The absolute BMR in the two groups were not significantly different when compared using an unpaired t test (OCA: 5841 (SD 471) v. NOCA: 5633 (SD 615)kJ/d). However, using an analysis of covariance, with either body weight or a combination of fat and fat free mass as covariates, the OCA group had a BMR almost 5% higher than that of the NOCA group (OCA: 5871 v. NOCA: 5601 kJ/d; P=0·002). When those subjects with high self-reported levels of physical activity were excluded, the difference in BMR between the two groups persisted (P = 0·001). An ANOVA of oral contraceptives use and phase of menstrual cycle showed significant differences in BMR with use of oral contraceptives (P=0·004) but no difference in BMR between phases of the menstrual cycle. In conclusion, the ose of oral contraceptive agents deserves consideration when conducting and analysing data from studies on energy metabolism in young women, as it results in a significantly higher BMR.

We investigated the relationships between BMR, fat-free mass (FFM) and fat mass in pregnancy. BMR was measured by indirect calorimetry and body composition was assessed by densitometry in seventeen non-pregnant women (79·9 (SD 26·3, range 505−151·4) kg) and sixteen pregnant women (75·7 (SD 20·6, range 545−115·9) kg). The pregnant women were evaluated during weeks 31−35 of gestation. Multiple regression analysis of BMR with FFM and fat mass in the non-pregnant women showed that FFM was a highly significant predictor of BMR (P < 0·0001), but fat mass was not (P = 0·09). In contrast, in the pregnant women, multiple regression analysis revealed that fat mass was a highly significant predictor (P < 0·001), while FFM was not (P = 0·69). Evaluation of the interaction terms in the combined data set confirmed that the relationships of BMR with FFM and fat mass differ significantly in non-pregnant and pregnant women. It is proposed that pregnancy represents a unique condition during which BMR is regulated by maternal adipose reserves. An augmented BMR in overweight pregnant women may be protective, given that excessive weight gain may be detrimental to neonatal and maternal health.

Current recommendations for energy requirements in the elderly are based on assumed levels of physical activity relative to BMR (1.5 x BMR). The main aim of the present study was to establish whether these recommendations might be applicable to a randomly-selected group of free-living elderly men (all over 75 years of age). BMR was measured by indirect calorimetry and total energy expenditure (TEE) by the doubly-labelled-water technique. Further aims included evaluating the applicability of a variety of BMR prediction equations and whether assessed quality of life reflected any measured indices of energy expenditure. The mean value for daily energy requirement was found to be 1.5 x BMR (89 J/kg per min) but with substantial inter-individual variation (SD 0-2 x BMR; 14 J/kg per min). The bias between measured TEE and TEE estimated (1.5 x BMR) from the various BMR predictions varied according to which equation was used (-10-+ 8% of the mean) with substantial 95 YO limits of agreement (28-30%of the mean). TEE and physical activity plus thermogenesis (TEE -BMR) were positively related to activities of daily living, but no relationships were apparent between these and perceived quality of life. It is concluded that, despite considerable inter-individual variability, national recommendations for energy requirements of elderly people are applicable to this randomly-selected group of free-living men over 75 years of age but that substantial variation exists when attempts are made to estimate TEE from measurements or predictions of BMR.

Energy expenditure, and therefore energy requirement, generally decreases with advancing age because of a decrease in basal metabolic rate (BMR) and physical activity. The aim of the present study was to measure total energy expenditure (EE) and activity level in a group of healthy elderly (sixteen men aged 71·3 (SD 4·9) years; ten women aged 67·6 (SD 4·1) years) and young adults (nineteen men aged 30·4 (SD 5·0) years; ten women aged 27·2 (SD 3·9) years) by using the doubly-labelled water method in combination with measurements of BMR. Age-related differences in body composition and their relationship to BMR and activity level were studied. EE was lower in elderly compared with young adults, partly due to a significantly lower BMR. The lower BMR was not fully explained by the lower fat-free mass (FFM) in the elderly. Energy expended (MJ/d) on activity was higher for the younger subjects although there was no significant difference in the physical activity index (PAI = EE/BMR) between the two age groups. The effect of physical activity level is twofold: first it has a positive effect on the BMR, and second it has a positive effect on the FFM. Both effects involve an increase in the total EE with an increased level of physical activity. At energy balance this will lead to increased energy and nutrient intake, making especially the elderly less vulnerable to inadequate energy and nutrient intake.

A large variation in seasonal weight loss between individuals exists in rural communities in developing countries. Therefore, it was investigated whether some individuals show a metabolic adaptation and, through that, prevent large body-weight losses during the preharvest season. Basal metabolic rate (BMR), energy intake and physical activity level (PAL) of rural Beninese women were measured in three seasons. Groups of subjects were: women with a body mass index (BMI) < 18 (n 18), and a BMI > 23 (n 16), and women who had shown small (n 18) and large (n 15) preharvest weight loss. All groups of subjects decreased energy intake during the preharvest season by 0·66–1·09 MJ/d. PAL did not show significant seasonal changes in any of the four groups. Only subjects with a BMI < 18 decreased BMR during the preharvest season with 2·9 (SD 6·7) J/kg per min (P < 0·05), with a decrease of 0·8 (SD 1·4) kg (P < 0·05) in body weight. In very thin women with a BMI < 17 (n 5) BMR expressed per unit body weight decreased even more during the preharvest season (by 12 %).

The objective of the present study was to examine the influence of energy supplementation and its cessation thereafter on the basal metabolic rates (BMR) of chronically undernourished individuals. Seven apparently healthy males were supplemented daily with 3.35 MJ (15 g protein, 35 g fat, 105 g carbohydrate) for 12 weeks. The average gain in body-weight was 1.9 kg (body fat, 58%; fat-free mass (FFM), 42%). The rise in BMR exceeded that accounted for by the increases in FFM during the 12 weeks of supplementation and was attributed to increases in the amount and activity of the visceral tissue as well as to an added cost of lipogenesis. At 12 weeks after cessation of the supplement, body-weights and FFM had decreased to presupplementation levels. BMR at this stage were significantly lower than at the 12th week of supplementation, when expressed per kg FFM or when adjusted for FFM using an analysis of covariance. These results suggest an increase in the metabolic efficiency during this negative energy balance period. The study demonstrates that, in the chronically undernourished, the changes in BMR are reversible and, hence, physiologically important to the process of adaptation to low-energy intakes.