A Major Gene for Resting Metabolic Rate Unassociated with Body Composition: Results from the Québec Family Study

A major gene hypothesis for resting metabolic rate (RMR) was investigated using segregation analysis (POINTER) of data on families participating in Phase 2 of the Québec Family Study. Complete analyses were conducted on RMR adjusted for age, and also on RMR adjusted for age and other covariates, primarily fat mass (FM) and fat-free mass (FFM). Prior to adjustment for covariates, support for a major gene hypothesis was equivocal — i.e., there was evidence for either a major gene or a multifactorial component (i.e., polygenic and/or familial environment). The multifactorial model was preferred over the major gene model, although the latter did segregate according to Mendelian expectations. However, after the effects of FM and FFM were accounted for, a major gene effect was unambiguous and compelling. The putative locus accounted for 57% of the variance, affected 7% of the sample, and led to high values of RMR. The lack of a significant multifactorial effect suggested that the familial etiology of RMR adjusted for FM and FFM was likely to be entirely a function of the major locus. Comparing the RMR results from pre- and post-adjustment for FM and FFM suggests a plausible hypothesis. We know from earlier studies in this sample that there is a putative major gene for FM and a major non-Mendelian effect for FFM. The current study leads us to speculate that: (1) the gene(s) affecting body size and body composition also may have an effect on RMR, and further (2) removal of the effect of the major gene(s) for body size and composition allowed for detection of an additional major gene affecting only the RMR. Thus, RMR appears to be an oligogenic trait.     

Familial Clustering of Abdominal Visceral Fat and Total Fat Mass: The Québec Family Study

The evidence for common familial factors underlying total fat mass (estimated from underwater weighing) and abdominal visceral fat (assessed from CT scan) was examined in families participating in phase 2 of the Québec Family Study (QFS) using a bivariate familial correlation model. Previous QFS investigations suggest that both genetic (major and polygenic) and familial environmental factors influence each phenotype, accounting for between 55% to 71% of the phenotypic variance in fat mass, and between 55% to 72% for abdominal visceral fat The current study suggests that the bivariate familial effect ranges from 29% to 50%. This pattern suggests that there may be common familial determinants for abdominal visceral fat and total fat mass, as well as additional familial factors which are specific to each. The relatively high spouse cross-trait correlations usually suggest that a large percent of the bivariate familial effect may be environmental in origin. However, if mating is not random, then the spouse resemblance may reflect either genetic or environmental causes, depending on the source [i.e., through similar genes or cohabitation (environmental) effects]. Finally, there are significant sex differences in the magnitude of the familial cross-trait correlations involving parents, but not offspring, suggesting complex generation (i.e., age) and sex effects. For example, genes may turn on or off as a function of age and sex, and/or there may be an accumulation over time of effects due to the environment which may vary by sex. Whether the common familial factors are genetic (major and/or polygenic), environmental, or some combination of both, and whether the familial expression depends on sex and/or age warrants further investigation using more complex models.     

Major gene effect on body mass index: the role of energy intake and energy expenditure

The evidence for a major gene for body mass index (BMI) was investigated using complex segregation analysis (POINTER) in 1691 individuals belonging to 432 nuclear families residing in the Chittoor district of Andhra Pradesh, India. Since the BMI is significantly correlated with energy intake (EI) and energy expenditure of activity (EEA), the effects of each were removed from the BMI using regression analysis, and the segregation analysis was repeated on the energy-adjusted BMI. For BMI, a putative major locus could not be ruled out, and the effect (q = 0.25, accounting for 37% of the phenotypic variance) was remarkably similar to that reported in Western populations. After adjusting the BMI for EI and EEA, however, no evidence in support of a major gene could be observed, suggesting either that EI and EEA mediate the expression of the major gene effect on BMI, or that the same major gene may influence both traits. The pleiotropy hypothesis was further explored using a simple bivariate familial correlation model, in which the significance of familial cross-trait correlations (e.g., BMI in parents with BMI as predicted from the energy variables in the offspring) was examined. The cross-trait resemblance between the two measures was significant for all biological relatives, verifying the presence of shared heritable determinants (i.e., the same gene[s] and/or familial environments) accounting for 58% of the covariation. The significant cross-trait spouse correlations further suggested that at least part of the cross-trait resemblance may be due to shared environmental factors. Therefore, we conclude that there is strong evidence for shared genetic effects between BMI and the energy variables.     

Pleiotropic Relationships between Cortisol Levels and Adiposity: The HERITAGE Family Study

Objective: To investigate familial basis for the relationship between cortisol adiposity at baseline and their training responses. Research Methods and Procedures: Bivariate correlation and segregation analyses were employed between cortisol and several adiposity measures [body mass index, fat mass (FM), fat-free mass, percentage of body fat (% BF), abdominal visceral fat (AVF), abdominal subcutaneous fat (ASF), and abdominal total fat (ATF)] from 99 white families and 105 black families. Results: In both races, significant inverse phenotypic correlations were generally observed between cortisol and adiposity measures at baseline but not for training responses. Significant cross-trait familial correlations were found for cortisol with abdominal fat (ASF, AVF, ATF) and overall body adiposity (FM, % BF) measures at baseline, which accounted for 14% to 20% of the phenotypic variance in whites. The cross-trait correlations were not significant for baseline phenotypes in blacks, perhaps because of the small sample size. A bivariate segregation analysis showed evidence of polygenic pleiotropy for cortisol with both abdominal fat and overall adiposity measures that accounted for 14% to 17% of the phenotypic covariance, but major gene pleiotropy was not suggested in whites. However, when ASF, AVF, and ATF were additionally adjusted for FM, no familial cross-trait correlations or polygenic pleiotropy between cortisol and the abdominal fat measures remained. Discussion: Evidence was found for polygenic pleiotropy but not for pleiotropic major gene effects between cortisol and overall adiposity in whites. However, the covariation of cortisol with abdominal fat phenotypes is dependent on concomitant polygenic factors for total-body fat.     

The different correlations between obesity and osteoporosis after adjustment of static mechanical loading from weight and fat free mass

Objectives:To explore complex correlations between obesity (OB) and osteoporosis (OP) after adjustment of static mechanical loading from weight and fat free mass (FFM).Methods:A total of 3749 Chinese aged ≥65 years were selected from our ongoing cohort study. OB indices and bone mineral density (BMD) were measured for each subject. Linear regression analyses were performed to explore the correlations between OB indices and OP under three adjustment models (unadjusted, adjusted with weight and adjusted with FFM).Results:Under no adjustment, three general obesity indices (body mass index: BMI, fat mass: FM, and percentage FM: PFM) were positively associated with BMD at three skeletal sites (P<0.001) in the regression analyses. However, after the adjustment with weight, these associations were mostly significant but reverse i.e., negatively in direction. After adjustment with FFM, the three indices were still positively and significantly (P<0.001) associated with BMD but regression coefficients were smaller compared to the unadjusted associations. Similar associations were observed for central adiposity and lower limb adiposity indices.Conclusions:The combined relation of OB to OP due to the physiological factors secreted from adipose tissues and the static mechanical loading from FM is positive in direction.     

Familial resemblance of body composition,physical activity,and resting metabolic rate in pre-school children

Background:

Although parental obesity is a well-established predisposing factor for the development of obesity, associations between regional body compositions, resting metabolic rates (RMR), and physical activity (PA) of parents and their pre-school children remain unknown. The objective of this study was to investigate parent-child correlations for total and regional body compositions, resting energy expenditures, and physical activity.

Methods:

Participants were 89 children aged 2-6 years and their parents, consisting of 61 families. Resting metabolic rate was assessed using indirect calorimetry. Total and regional body compositions were measured by both dual energy X-ray absorptiometry (DXA) and deuterium dilution. Physical activity was assessed by an accelerometer.

Results:

There was a significant parent-offspring regression for total fat free mass (FFM) between children and their mothers (P=0.02), fathers (P=0.02), and mid-parent (average of father and mother value) (P=0.002) when measured by DXA. The same was true for fat mass (FM) between children and mothers (P<0.01), fathers (P=0.02), and mid-parent (P=0.001). There was no significant association between children and parents for physical activity during the entire week, weekend, weekdays, and different parts of days, except for morning activity, which was positively related to the mothers’ morning activities (P<0.01) and mid-parent (P=0.009). No association was found between RMR of children and parents before and after correction for FFM and FM.

Conclusion:

These data suggest a familial resemblance for total body composition between children and their parents. Our data showed no familial resemblance for PA and RMR between children and their parents. Key Words: Obesity, Familial resemblance, Children, Resting metabolic rate, Physical activity     

Factors predicting individual variability in diet-induced weight loss in MF1 mice

The effectiveness of caloric restriction (CR) as a treatment for obesity varies considerably between individuals. Reasons for this interindividual variation in weight loss in response to CR may lie in pre-existing individual differences and/or individual differences in compensatory responses. Here we studied the responses of 127 MF1 mice to 30% CR over four weeks, and investigated whether pre-existing differences or compensatory changes in body temperature, resting metabolic rate (RMR) and behavior explained the variation observed in body mass (BM) and fat mass (FM) changes. Mice showed considerable variation in BM loss (36-1%), and in the type of tissue lost (FM or fat free mass, FFM). About 50% of the variation in BM and FM loss could be predicted by pre-existing differences in food intake, RMR, and general activity, where BM loss was greater when food intake was lower and activity and RMR were higher. Compensatory changes in activity and body temperature together explained ~50% of the variation in BM and FM loss in both sexes. In models incorporating baseline variables and compensatory changes, food intake, and activity were the strongest predictors of weight loss in both sexes; i.e., lower baseline food intake and increased changes in activity resulted in greater BM and FM loss. Interestingly, increased baseline activity was a significant predictor of weight loss independent of compensatory changes in activity. Identifying factors involved in individual variability in weight loss may give insights into the mechanisms that underlie this variability, and is important to develop individually tailored weight-management strategies.     

Tracking of familial resemblance for resting blood pressure over time in the Québec Family Study

The etiology of familial resemblance for systolic (SBP) and diastolic (DBP) blood pressure, both within a single time point as well as across time points, was assessed to determine how familial etiologies underlying a trait may change across time. SBP and DBP measurements were taken roughly 12 years apart in family members participating in the longitudinal Québec Family Study. A longitudinal (bivariate) familial correlation model yields 3 types of correlations: intraindividual cross-time (e.g., father's BP at time 1 with his own BP at time 2); interindividual within-time (e.g., father time 1 with child time 1); and interindividual cross-time (e.g., father time 1 with child time 2). In addition, the change in BP across time (i.e., time 1-time 2) is examined using a univariate family correlation model. This combined method is useful in assessing the degree to which the same familial factors are operating across time (interindividual cross-time correlations), as well as the degree to which different heritable components are involved across time (change score). Maximal heritabilities for SBP were about 70% at each time point, while for DBP the heritability was larger at time 1 (87%) than time 2 (39%). Both the change scores (48% for SBP and 54% for DBP) and the cross-time comparisons (58% to 72% for SBP and 63% to 65% for DBP) evidenced significant familial resemblance. These results illustrate how simple methodologies can be used to specify how familial etiologies underlying a trait may change across time. For BP, the model includes unique familial factors that are specific to each time measurement, and an additional familial factor which is common to both time points. The factors leading to differences in longitudinal familial resemblance for BP (i.e., the unique factors) may be primarily genetic in origin, while those leading to stability across time may include both genetic and familial environmental effects. Sex and/or age interactions with the genotypes are also suggested.     

Does menarche mark a period of elevated resting metabolic rate?

Resting metabolic rate (RMR) and body composition were measured in 44 initially nonoverweight girls at three time points relative to menarche: premenarche (Tanner stage 1 or 2), menarche (+/-6 mo), and 4 yr after menarche. Mean absolute RMR was 1,167, 1,418, and 1,347 kcal/day, respectively. Absolute RMR was statistically significantly higher at menarche than at 4 yr after menarche despite statistically significantly less fat-free mass (FFM) and fat mass (FM), suggesting an elevation in RMR around the time of menarche. The pattern of change in RMR, adjusted for FFM, log transformed FM, age, race, parental overweight, and two interactions (visit by parental overweight, parental overweight by FFM), was also considered. Adjusted RMR did not differ statistically between the visits for girls with two normal-weight parents. For girls with at least one overweight parent, adjusted RMR was statistically significantly lower 4 yr after menarche than at premenarche or menarche. Thus parental overweight may influence changes that occur in RMR during adolescence in girls.     

Differences in daily energy expenditure in lean and obese women: the role of posture allocation

Objective: A low resting metabolic rate (RMR) is considered a risk factor for weight gain and obesity; however, due to the greater fat‐free mass (FFM) found in obesity, detecting an impairment in RMR is difficult. The purposes of this study were to determine the RMR in lean and obese women controlling for FFM and investigate activity energy expenditure (AEE) and daily activity patterns in the two groups. Methods and Procedures: Twenty healthy, non‐smoking, pre‐menopausal women (10 lean and 10 obese) participated in this 14‐day observational study on free‐living energy balance. RMR was measured by indirect calorimetry; AEE and total energy expenditure (TEE) were calculated using doubly labeled water (DLW), and activity patterns were investigated using monitors. Body composition including FFM and fat mass (FM) was measured by dual energy X‐ray absorptiometry (DXA). Results: RMR was similar in the obese vs. lean women (1601 ± 109 vs. 1505 ± 109 kcal/day, respectively, P = 0.12, adjusting for FFM and FM). Obese women sat 2.5 h more each day (12.7 ± 3.2 h vs. 10.1 ± 2.0 h, P < 0.05), stood 2 h less (2.7 ± 1.0 h vs. 4.7 ± 2.2 h, P = 0.02) and spent half as much time in activity than lean women (2.6 ± 1.5 h vs. 5.4 ± 1.9 h, P = 0.002). Discussion: RMR was not lower in the obese women; however, they were more sedentary and expended less energy in activity than the lean women. If the obese women adopted the activity patterns of the lean women, including a modification of posture allocation, an additional 300 kcal could be expended every day.     

Cross-trait familial resemblance for body fat and blood pressure: familial correlations in the Québec Family Study.

Cross-trait resemblance between body fat and blood pressure (BP) was examined among families in the Québec Family Study by using a bivariate familial correlation model assessing both intraindividual (e.g., comparison of father's body fat with his own BP) and interindividual (e.g., comparison of father's body fat with son's BP) cross-trait correlations. Each of six body-fat measures-(i) percent body fat, (ii) body-mass index, (iii) the sum of six skinfolds, (iv) the ratio of the sum of six skinfolds to total fat mass, (v) the ratio of the trunk skinfold sum to the extremity skinfold sum, and (vi) the regression of the trunk-extremity skinfold ratio on the sum of six skinfolds--was analyzed separately with systolic BP and with diastolic BP. Results showed that (1) upper-body fat was the strongest interindividual correlate of BP (especially the correlation of trunk-extremity ratio with diastolic BP), suggesting shared pleiotropic genetic and/or common familial environmental effects; (2) summary body-fat measures either were inconsistent (in the case of both percent body fat and sum of six skinfolds) or gave no evidence of interindividual cross-trait resemblance with BP (in the case of body-mass index); and (3) intraindividual resemblance between the sum of six skinfolds and BP largely vanished once the skinfold sum was adjusted for fat mass, suggesting that the intraindividual association may be mediated largely by the absolute amount of subcutaneous fat rather than by the subcutaneous proportion. Finally, the magnitude of the spouse resemblance for the trunk-extremity ratio with diastolic BP suggests that a significant proportion of the resemblance may be due to environmental influences. In summary, our investigation confirms a heritable link between BP and truncal-abdominal fat as predicted by the metabolic-syndrome hypothesis. That this result is obtained in primarily normotensive, nonobese families, suggests the connection involves normal metabolic paths.     

Factors predicting nongenetic variability in body weight gain induced by a high-fat diet in inbred C57BL/6J mice

Inbred C57BL/6J mice displayed large individual variations in weight gain when fed a high-fat diet (HFD). The objective of this study was to examine whether this predominantly nongenetic variability could be predicted by relevant baseline features and to explore whether variations in these significant features were influenced during pregnancy and/or lactation. Fat mass (FM), fat-free mass (FFM), food intake (FI), resting metabolic rate (RMR), physical activity (PA), and body temperature (T(b)) were all evaluated at baseline in 60 mice (aged 10-12 weeks) before HFD feeding. Regression analyses showed that baseline FM was a strong positive predictor of weight gain between 4 and 16 weeks of HFD. Baseline PA was negatively associated with weight gain at week 8, 12, and 16, and baseline FFM had a positive effect at week 12 and 16. In a second experiment, 40 female mice were mated and litter sizes (LS) were manipulated on day 3 of lactation. Weaning weight and postweaning growth rate (GR) had positive impacts on FM and FFM at age 9 weeks (FM, P = 0.001; FFM, P < 0.001: n = 97). Lactation LS had a negative effect on weaning weight and a positive effect on postweaning GR. In conclusion, our results show that obesity induced by HFD was associated with a higher baseline FM, a higher baseline FFM and a lower baseline PA level before the exposure of HFD. Two of these traits (FM and FFM) were influenced by lactation LS via weaning weight and postweaning GR.     

Relationships Between the Body Mass Index and Body Composition

The aims of this study were to evaluate the Body Mass Index (BMI) (weight/stature²) as a proxy for percent body fat (%BF) and to determine its association with fat-free mass (FFM). Multivariate analysis of variance and partial correlations were used to examine relationships between BMI and %BF and FFM from densitometry for 504 men and 511 women, aged 20 to 45 years. Sensitivity/specificity analyses used cut offs of 28 kg/m² in men and 26 kg/m² in women for BMI, and 25% in men and 33% in women for %BF. Significantly higher associations existed in each gender between BMI and %BF in the upper BMI tertile than in the lower BMI tertiles. In the lower BMI tertiles, correlations between BMI and FFM were approximately twice as large as those between BMI and %BF. The BMI correctly identified about 44% of obese men, and 52% of obese women when obesity was determined from %BF. BMI is an uncertain diagnostic index of obesity. Results of Receiver Operator Characteristic (ROC) analyses using %BF and total body fat, both provided a BMI of 25 kg/m² in men and 23 kg/m² in women as diagnostic screening cut offs for obesity.     

Segmental body composition assessment for obese Japanese adults by single-frequency bioelectrical impedance analysis with 8-point contact electrodes

This study aimed to determine the accuracy of segmental body composition variables estimated by single-frequency BIA with 8-point contact electrodes (SF-BIA8), compared with dual-energy X-ray absorptiometry (DXA). Subjects were 72 obese Japanese adults (43 males and 29 females) aged 30 to 66 years. Segmental body composition variables (fat free mass: FFM, fat mass: FM, and percent fat mass: %FAT) were measured by these techniques. The correlations between impedance values and FFM measured by DXA were calculated. To examine the consistency in predicted values (SF-BIA8) with the reference (DXA), significant mean differences were tested by t-test and the degree of the difference was assessed by effect size. Correlations between the reference and predicted values were calculated. Additionally, the standard error of estimation (SEE) when estimating the reference from the predictor and the relative value of the SEE to the mean value of the DXA measurement (%SEE) were calculated. Systematic error was examined by Bland-Altman plots. High correlations were found between impedance and FFM measured by SF-BIA8. FFM in the extremities showed high correlations with the reference values, but systematic error was found. SF-BIA8 tended to overestimate FFM in the trunk. The consistencies in %FAT and FM with the reference value are inferior to those for FFM, and SEE values in %FAT and FM were greater than those for FFM. The accuracy of the estimated values in the trunk (FFM, %FAT, and FM) are inferior to those of the total body and extremities.     

Maximum-likelihood estimation of familial correlations from multivariate quantitative data on pedigrees: a general method and examples

A general method for maximum-likelihood estimation of familial correlations from pedigree data is presented. The method is applicable to any type of data structure, including pedigrees in which variable numbers of individuals are present within classes of relatives, data in which multiple phenotypic measures are obtained on each individual, and multiple group analyses in which some correlations are equated across groups. The method is applied to data on high-density lipoprotein cholesterol and total cholesterol levels obtained from participants in the Swedish Twin Family Study. Results indicate that there is strong familial resemblance for both traits but little cross-trait resemblance.     

Segregation analysis of fat mass and other body composition measures derived from underwater weighing.

Segregation patterns of three body composition measures which were derived from underwater weighing were evaluated in a random sample of 176 French-Canadian families. Two of the variables can be considered as primary partitions of weight (fat mass [FM] and fat-free mass [FFM]), while the remaining variable (percent body fat [%BF]) is a derived index combining the measures of both fat and fat-free weight. This study represents the first report investigating major gene effects for these measures. Segregation analyses revealed that a major locus hypothesis could not be rejected for two of the three phenotypes. The single exception was FFM, for which nearly 60% of the variance was accounted for by a non-Mendelian major effect, which may reflect environmentally based commingling or may be in part a function of gene-environment interactions or correlations. In contrast to the results for FFM, the results for each of FM and %BF were similar and suggested a major locus which accounted for 45% of the variance, with an additional 22%-26% due to a multifactorial component. Given the similarity of the major gene characteristics for these two phenotypes, the possibility that the same gene underlies both measures warrants investigation. A reasonable hypothesis is to consider genes that may influence nutrient partitioning, as the family of candidate genes to receive the major attention.     

A twin study of the etiology of prolonged fatigue and immune activation.

Risk factors to prolonged fatigue syndromes (PFS) are controversial. Pre-morbid and/or current psychiatric disturbance, and/or disturbed cell-mediated immunity (CMI), have been proposed as etiologic factors. Self-report measures of fatigue and psychologic distress and three in vitro measures of CMI were collected from 124 twin pairs. Crosstwin-crosstrait correlations were estimated for the complete monozygotic (MZ; 79 pairs) and dizygotic (DZ; 45 pairs) twin groups. Multivariate genetic and environmental models were fitted to explore the patterns of covariation between etiologic factors. For fatigue, the MZ correlation was more than double the DZ correlation (0.49 versus 0.16) indicating strong genetic control of familial aggregation. By contrast, for in vitro immune activation measures MZ and DZ correlations were similar (0.49-0.69 versus 0.42-0.53) indicating the etiologic role of shared environments. As small univariate associations were noted between prolonged fatigue and the in vitro immune measures (r = -0.07 to -0.12), multivariate models were fitted. Relevant etiologic factors included: a common genetic factor accounting for 48% of the variance in fatigue which also accounted for 4%, 6% and 8% reductions in immune activation; specific genetic factors for each of the in vitro immune measures; a shared environment factor influencing the three immune activation measures; and, most interestingly, unique environmental influences which increased fatigue but also increased markers of immune activation. PFS that are associated with in vitro measures of immune activation are most likely to be the consequence of current environmental rather than genetic factors. Such environmental factors could include physical agents such as infection and/or psychologic stress.     

Relationship between fat-to-fat-free mass ratio and decrements in leg strength after downhill running.

The purpose of this study was to determine whether greater body fat mass (FM) relative to lean mass would result in more severe muscle damage and greater decrements in leg strength after downhill running. The relationship between the FM-to-fat-free mass ratio (FM/FFM) and the strength decline resulting from downhill running (-11% grade) was investigated in 24 male runners [age 23.4 +/- 0.7 (SE) yr]. The runners were divided into two groups on the basis of FM/FFM: low fat (FM/FFM = 0.100 +/- 0.008, body mass = 68.4 +/- 1.3 kg) and normal fat (FM/FFM = 0.233 +/- 0.020, body mass = 76.5 +/- 3.3 kg, P < 0.05). Leg strength was reduced less in the low-fat (-0.7 +/- 1.3%) than in the normal-fat individuals (-10.3 +/- 1.5%) 48 h after, compared with before, downhill running (P < 0.01). Multiple linear regression analysis revealed that the decline in strength could be predicted best by FM/FFM (r2 = 0.44, P < 0.05) and FM-to-thigh lean tissue cross-sectional area ratio (r2 = 0.53, P < 0.05), with no additional variables enhancing the prediction equation. There were no differences in muscle glycogen, creatine phosphate, ATP, or total creatine 48 h after, compared with before, downhill running; however, the change in muscle glycogen after downhill running was associated with a higher FM/FFM (r = -0.56, P < 0.05). These data suggest that FM/FFM is a major determinant of losses in muscle strength after downhill running.     

Body mass, body composition and sleeping metabolic rate before, during and after endurance training

Metabolic rate, more specifically resting metabolic rate (RMR) or sleeping metabolic rate (SMR), of an adult subject is usually expressed as a function of the fat-free mass (FFM). Chronic exercise is thought to increase FFM and thus to increase RMR and SMR. We determined body mass (BM), body composition, and SMR before, during, and after an endurance training programme without interfering with energy intake. The subjects were 11 women and 12 men, aged 37 (SD 3) years and body mass index 22.3 (SD 1.5) kg · m^–2. The endurance training prepared subjects to run a half marathon competition after 44 weeks. The SMR was measured overnight in a respiration chamber. Body composition was measured by hydrostatic weighing. Measurements were performed at 0, 8, 20, 40, and 90 weeks after the start of the training. The BM had decreased from a mean value of 66.6 (SD 6.9) to 65.6 (SD 6.7) kg (P<0.01), fat mass (FM) had decreased from 17.1 (SD 3.9) to 13.5 (SD 3.6) kg (P<0.001), and FFM had increased from 49.5 (SD 7.3) to 52.2 (SD 7.6) kg (P<0.001) at 40 weeks. Mean SMR before and after 40 weeks training was 6.5 (SD 0.7) and 6.2 (SD 0.6) MJ · day^–1 (P<0.05). The decrease in SMR was related to the decrease in BM (r=0.62,P=0.001). At 90 weeks, when most subjects had not trained for nearly a year, BM and SMR were not significantly different from the initial value while FM and FFM had not changed since week 40 of training. In conclusion, it was found that an exercise induced increase in FFM did not result in an increase in SMR. There was an indication of the opposite effect, a decrease in SMR in the long term during training, possibly as a defence mechanism of the body in the maintenance of BM.     

Body Fat and Fat‐Free Mass and All‐Cause Mortality

Objective: To investigate whether the association between BMI and all‐cause mortality could be disentangled into opposite effects of body fat and fat‐free mass (FFM). Research Methods and Procedures: All‐cause mortality was studied in the Danish follow‐up study “Diet, Cancer and Health” with 27, 178 men and 29, 875 women 50 to 64 years old recruited from 1993 to 1997. By the end of year 2001, the median follow‐up was 5.8 years, and 1851 had died. Body composition was assessed by bioelectrical impedance. Cox regression models were used to estimate the relationships among body fat mass index (body fat mass divided by height squared), FFM index (FFM divided by height squared), and mortality. All analyses were adjusted for smoking habits. Results: Men and women showed similar associations. J‐shaped associations were found between body fat mass index and mortality adjusted for FFM and smoking. The mortality rate ratios in the upper part of body fat mass were 1.12 per kg/m² (95% confidence interval: 1.07, 1.18) in men and 1.06 per kg/m² (95% confidence interval: 1.02, 1.10) in women. Reversed J‐shaped associations were found between FFM index and mortality with a tendency to level off for high values of FFM. Discussion: Our findings suggest that BMI represents joint but opposite associations of body fat and FFM with mortality. Both high body fat and low FFM are independent predictors of all‐cause mortality.