Sandra D Murison

Additional anthropometric measures may improve the predictability of basal metabolic rate in adult subjects

Background:The most commonly used predictive equation for basal metabolic rate (BMR) is the Schofield equation, which only uses information on body weight, age and sex to derive the prediction. However, because body composition is a key influencing factor, there will be error in calculating an individuals basal requirements based on this prediction.Objective:To investigate whether adding additional anthropometric measures to the standard measures can enhance the predictability of BMR and to cross-validate this within a separate subgroup.Design:Cross-sectional study of 150 Caucasian adults from Scotland, with a body mass index range of 16.7–49.3 kg/m2. All subjects underwent measurement of BMR, body composition, and 148 also had basic skinfold and circumference measures taken. The resultant equation was tested in a subgroup of 39 obese males.Results:The average difference between the predicted (Schofield equation) and measured BMR was 502 kJ/day. There was a slight systematic bias in this error, with the Schofield equation underestimating the lowest values. The average discrepancy between predicted and actual BMR was reduced to 452 kJ/day, with the addition of fat mass, fat-free mass, an overall 10% improvement on the Schofield equation (P=0.054). Using an equation derived from principal components analysis of anthropometry measurements similarly decreased the difference to 458 kJ/day (P=0.039). Testing the equation in a separate group indicated a 33% improvement in predictability of BMR, compared to the Schofield equation.Conclusions:In the absence of detailed information on body composition, utilizing anthropometric data provides a useful alternative methodology to improve the predictability of BMR beyond that achieved from the standard Schofield prediction equation. This should be confirmed in more individuals, both within the obese and normal weight category.

Plasma leptin levels are related to body composition, sex, insulin levels and the A55V polymorphism of the UCP2 gene

Objective:Circulating leptin levels show a high degree of individual variability even after the main effect of body fatness is accounted for. We therefore wanted to determine the roles of variation in body composition, age, sex and polymorphisms of the UCP2 gene and promoter region on levels of circulating leptin.Subjects:One hundred and fifty Caucasian subjects, which represented a cross-section of the population from NE, Scotland, were recruited.Measurements:Body composition was measured using dual X-ray absorptiometry. Fasted circulating leptin, insulin, T3 and T4 levels were measured, and all individuals were genotyped for the UCP2 polymorphisms A55V, –866G>A and exon-8 ins/del.Results:The results indicate that circulating leptin was significantly related to sex and principle component (PC) scores representing overall adipose tissue mass and a second representing the contrast of central to peripheral bone mineral content. Residual leptin was associated with the A55V polymorphism (P< 0.001) explaining 11.3% of the residual variance. There was a marginal effect associated with exon-8 ins/del (P=0.045) explaining 4.4% of the residual variance in leptin. Loge transformed circulating fasting insulin was related to PC scores representing general adiposity and sex. Residual Loge insulin was associated with the A55V and exon-8 ins/del polymorphisms explaining 5.7% (P=0.015) and 5% (P=0.026) of the residual variation, respectively. The –866G>A polymorphism was not significantly associated with residual leptin or insulin. Leptin and insulin were significantly (P=0.007) correlated. Statistically removing the effect of insulin on leptin still showed association between leptin and A55V (P=0.002). Removing the effect of leptin on insulin, the A55V polymorphism was no longer significant (P=0.120). After accounting for the correlation between insulin and leptin, the exon-8 ins/del was no longer significant for residual leptin (P=0.119) or Loge insulin (P=0.252).Conclusion:These data suggest that the A55V polymorphism directly affected the levels of leptin but not via an effect on insulin.

Evaluating energy intake measurement in free-living subjects: when to record and for how long?

OBJECTIVE To nutritionally analyse mean energy intake (EI) from different 3 d intervals within a 7 d recording period and to evaluate the seasonal effect on energy and nutrient intake. DESIGN Cross-sectional study of dietary intake collected with 7 d food diaries. SETTING Aberdeen, north-east Scotland, UK, between 2002 and 2004. SUBJECTS Participants from two long-term trials were pooled. These trials, investigating genetic and environmental influences on body weight, were the Genotyping And Phenotyping (GAP) study and a cohort observational study, Rowett Assessment of Childhood Appetite and metaboLism (RASCAL). There were 260 Caucasian adults, BMI range 16.7-49.3 kg/m2, age range 21-64 years. RESULTS Mean EI for Wednesday, Friday and Saturday had the closest approximation to the 7 d mean (0.1 % overestimate). A gender x season interaction (P = 0.019) with a different intake pattern for females and males was observed. For females, lower mean (se) EI was recorded in summer (8117 (610) kJ) and autumn (7941 (699) kJ) compared with spring (8929 (979) kJ) and winter (8132 (1041) kJ). For males, higher mean (se) EI was recorded in summer (10 420 (736) kJ) and autumn (10 490 (1041) kJ) compared with spring (9319 (1441) kJ) and winter (9103 (1505) kJ). CONCLUSIONS The study results indicate that 3 d weighed intakes recorded from Wednesday, Friday and Saturday are most representative of 7 d habitual intake in free-living subjects. They also indicate that seasonality has a limited effect on EI and no effect on macronutrient intake.