Body composition interpretation. Contributions of the fat-free mass index and the body fat mass index.

OBJECTIVE: Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI. METHODS: FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated. RESULTS: FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively. CONCLUSION: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.

Bio-electrical impedance analysis for estimation of fat-free mass and muscle mass in cystic fibrosis patients.

The nutritional status of cystic fibrosis (CF) patients has to be regularly evaluated and alimentary support instituted when indicated. Bio-electrical impedance analysis (BIA) is a recent method for determining body composition. The present study evaluates its use in CF patients without any clinical sign of malnutrition. Thirty-nine patients with CF and 39 healthy subjects aged 6-24 years were studied. Body density and mid-arm muscle circumference were determined by anthropometry and skinfold measurements. Fat-free mass was calculated taking into account the body density. Muscle mass was obtained from the urinary creatinine excretion rate. The resistance index was calculated by dividing the square of the subject's height by the body impedance. We show that fat-free mass, mid-arm muscle circumference and muscle mass are each linearly correlated to the resistance index and that the regression equations are similar for both CF patients and healthy subjects.

Sedentarism affects body fat mass index and fat-free mass index in adults aged 18 to 98 years.

OBJECTIVE: Body mass index does not discriminate body fat from fat-free mass or determine changes in these parameters with physical activity and aging. Body fat mass index (BFMI) and fat-free mass index (FFMI) permit comparisons of subjects with different heights. This study evaluated differences in body mass index, BFMI, and FFMI in physically active and sedentary subjects younger and older than 60 y and determined the association between physical activity, age, and body composition parameters in a healthy white population between ages 18 and 98 y. METHODS: Body fat and fat-free mass were determined in healthy white men (n = 3549) and women (n = 3184), between ages 18 and 98 y, by bioelectrical impedance analysis. BFMI and FFMI (kg/m2) were calculated. Physical activity was defined as at least 3 h/wk of endurance-type activity for at least 2 mo. RESULTS: Physically active as opposed to sedentary subjects were more likely to have a low BFMI (men: odds ratio [OR], 1.4; confidence interval [CI], 0.7-2.5; women: OR 1.9, CI 1.6-2.2) and less likely to have very high BFMI (men: OR, 0.2; CI, 0.1-0.2; women: OR, 0.1; CI, 0.02-0.2), low FFMI (men: OR, 0.5; CI, 0.3-0.9; women: OR, 0.7; CI, 0.6-0.9), or very high FFMI (men: OR, 0.6; CI, 0.4-0.8; women: OR, 0.7; CI, 0.5-1.0). Compared with subjects younger than 60 y, those older than 60 y were more like to have very high BFMI (men: OR, 6.5; CI, 4.5-9.3; women: OR, 14.0; CI, 9.6-20.5), and women 60 y and older were less likely to have a low BFMI (OR, 0.4; CI, 0.2-0.5). CONCLUSIONS: A clear association was found between low physical activity or age and height-normalized body composition parameters (BFMI and FFMI) derived from bioelectrical impedance analysis. Physically active subjects were more likely to have high or very high or low FFMI. Older subjects had higher body weights and BFMI.

Body-mass index and mortality.

Comment on: Prospective Studies Collaboration, Whitlock G, Lewington S et al. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373(9669):1083-96. PMID: 19299006.

Serum Leptin Concentration, Body Mass Index and Incident Heart Failure: The Health, Aging, and Body Composition Study

Background: Leptin is produced primarily by adipocytes. Although originally associated with the central regulation of satiety and energy metabolism, increasing evidence indicates that leptin may be an important factor for congestive heart faire (CHF). In the study, we aimed to test the hypothesis that leptin may influence CHF pathophysiology via a pathway of increasing body mass index (BMI). Methods: We studied 2,389 elderly participants aged 70 and older (M; 1161, F: 1228) without CHF and with serum leptin measures at the Health Aging, and Body Composition study. We analyzed the association between serum leptin level and risk of incident CHF using Cox hazard proportional regression models. Elevated leptin level was defined as more than the highest quartile (Q4) of leptin distribution in the total sample for each gender. Adjusted-covariates included demographic, behavior, lipid and inflammation variables (partially-adjusted models), and further included BMI (fully-adjusted models). Results: In a mean 9-year follow-up, 316 participants (13.2%) developed CHF. The partially-adjusted models indicated that men and women with elevated serum leptin levels (>=9.89 ng/ml in men and >=25 ng/ml in women) had significantly higher risks of developing CHF than those with leptin level of less than Q4. The adjusted hazard ratios (95%CI) for incident CHF was 1.49 (1.04 -2.13) in men and 1.71 (1.12 -2.58) in women. However, these associations became non-significant after adjustment for including BMI for each gender. The fully-adjusted hazard ratios (95%CI) were 1.43 (0.94 -2.18) in men and 1.24 (0.77-1.99) in women. Conclusion: Subjects with elevated leptin levels have a higher risk of CHF. The study supports the hypothesis that the influence of leptin level on risk of CHF may be through a pathway related to increasing BMI.

Body mass index, cigarette smoking, and alcohol consumption and cancers of the oral cavity, pharynx, and larynx: modeling odds ratios in pooled case-control data.

Odds ratios for head and neck cancer increase with greater cigarette and alcohol use and lower body mass index (BMI; weight (kg)/height(2) (m(2))). Using data from the International Head and Neck Cancer Epidemiology Consortium, the authors conducted a formal analysis of BMI as a modifier of smoking- and alcohol-related effects. Analysis of never and current smokers included 6,333 cases, while analysis of never drinkers and consumers of < or =10 drinks/day included 8,452 cases. There were 8,000 or more controls, depending on the analysis. Odds ratios for all sites increased with lower BMI, greater smoking, and greater drinking. In polytomous regression, odds ratios for BMI (P = 0.65), smoking (P = 0.52), and drinking (P = 0.73) were homogeneous for oral cavity and pharyngeal cancers. Odds ratios for BMI and drinking were greater for oral cavity/pharyngeal cancer (P < 0.01), while smoking odds ratios were greater for laryngeal cancer (P < 0.01). Lower BMI enhanced smoking- and drinking-related odds ratios for oral cavity/pharyngeal cancer (P < 0.01), while BMI did not modify smoking and drinking odds ratios for laryngeal cancer. The increased odds ratios for all sites with low BMI may suggest related carcinogenic mechanisms; however, BMI modification of smoking and drinking odds ratios for cancer of the oral cavity/pharynx but not larynx cancer suggests additional factors specific to oral cavity/pharynx cancer.

Chronic exercise preserves lean muscle mass in masters athletes.

Aging is commonly associated with a loss of muscle mass and strength, resulting in falls, functional decline, and the subjective feeling of weakness. Exercise modulates the morbidities of muscle aging. Most studies, however, have examined muscle-loss changes in sedentary aging adults. This leaves the question of whether the changes that are commonly associated with muscle aging reflect the true physiology of muscle aging or whether they reflect disuse atrophy. This study evaluated whether high levels of chronic exercise prevents the loss of lean muscle mass and strength experienced in sedentary aging adults. A cross-section of 40 high-level recreational athletes ("masters athletes") who were aged 40 to 81 years and trained 4 to 5 times per week underwent tests of health/activity, body composition, quadriceps peak torque (PT), and magnetic resonance imaging of bilateral quadriceps. Mid-thigh muscle area, quadriceps area (QA), subcutaneous adipose tissue, and intramuscular adipose tissue were quantified in magnetic resonance imaging using medical image processing, analysis, and visualization software. One-way analysis of variance was used to examine age group differences. Relationships were evaluated using Spearman correlations. Mid-thigh muscle area (P = 0.31) and lean mass (P = 0.15) did not increase with age and were significantly related to retention of mid-thigh muscle area (P < 0.0001). This occurred despite an increase in total body fat percentage (P = 0.003) with age. Mid-thigh muscle area (P = 0.12), QA (P = 0.17), and quadriceps PT did not decline with age. Specific strength (strength per QA) did not decline significantly with age (P = 0.06). As muscle area increased, PT increased significantly (P = 0.008). There was not a significant relationship between intramuscular adipose tissue (P = 0.71) or lean mass (P = 0.4) and PT. This study contradicts the common observation that muscle mass and strength decline as a function of aging alone. Instead, these declines may signal the effect of chronic disuse rather than muscle aging. Evaluation of masters athletes removes disuse as a confounding variable in the study of lower-extremity function and loss of lean muscle mass. This maintenance of muscle mass and strength may decrease or eliminate the falls, functional decline, and loss of independence that are commonly seen in aging adults.

Les préférences alimentaires sont-elles influencées par l'index de masse corporelle, l'âge, le sexe ou le tabac [Are food preferences affected by body mass index, age, sex or tobacco?].

In recent decades the percentage of energy derived from dietary fat has increased. The aim of this study was to explore the relationship between food taste preferences, BMI, age, gender and smoking habits. A computerized questionnaire using a hedonic scale (range 0 to 8) to quantify the liking for sweet and savoury, lean and fat foods, was filled by 233 adults: 171 normal weight (131 women, 40 men) and 62 overweight subjects (BMI > 25 kg/m2 42 women, 20 men). The majority of the subjects had a general preference for savoury lean food irrespective of their BMI or gender. Similarly, preference for sweet lean food was not influenced by the magnitude of the BMI. In contrast, overweight subjects had a preference for sweet fat food (p = 0.05) as well as for savoury fat food (p < 0.05). At any age or BMI, men preferred sweet fat food (p < 0.01). This was not the case for women. Overweight men over forty preferred savoury fat food, in contrast to overweight women of the same age (p < 0.01). The same difference existed between normal weight smokers and non-smokers. This study demonstrates that fat food preference plays a potential role in the development of obesity.

Adiposity indicators and blood pressure in children: nothing beyond body mass index?

Obesity is a major risk factor for elevated blood pressure in children. For instance, in a school-based study of 5207 children aged 10-12 years, the prevalence of hypertension, which is sustained elevated blood pressure over several visits, was 1.5%, 3.9% and 17.5% in normal weight, overweight and obese children, respectively. High body mass index (BMI) is commonly used to define overweight and obesity. However, because BMI is merely a proxy for adiposity, there is a longstanding debate about its performance to predict elevated blood pressure (or any other health conditions associated with adiposity) and whether other adiposity indicators, such as waist circumference, waist-to-hip ratio or hip circumference, should not be preferred... In this study, 7.4% of boys and 6.4% of girls had elevated blood pressure. The adiposity indicators were highly correlated to each other, apart from weight, waist-to-hip ratio and skinfold thickness z-scores. All indicators were associated with blood pressure. The ability to identify children with elevated blood pressure, assessed by the area under the receiver operating curve (AUC) statistic, was superior for BMI, body adiposity index and waist-to-height ratio z-scores compared with other indicators. BMI z-scores had a slightly higher AUC than other indicators. The authors concluded that BMIz-scores could be a better predictor of elevated blood pressure in children than other adiposity indicators.

Lack of metabolic and behavioral adaptations in rural Gambian men with low body mass index.

Energy expenditure was measured by means of a respiratory chamber in two groups of adult rural Gambian men. The first group (n = 29) had a low body mass index (BMI; in kg/m2) < 18.5), whereas the control group (n = 29) had a higher BMI (> 22). This study shows that the energy expenditure of Gambian men with low BMI is not different from that of Gambian men with normal BMI when the results are normalized for fat-free mass or for weight by analysis of covariance. In Gambian men the nutritional status thus does not seem to affect energy metabolism notably. No differences in respiratory quotient, diet-induced thermogenesis, net work efficiency, spontaneous physical activity, heart rate, or urinary catecholamine excretion were observed between the two groups. It is, however, interesting to note that the basal metabolic rate of Gambian men, regardless of their nutritional status, is approximately 10% (range 4-12% depending on the reference value used) lower than that predicted for individuals living in industrialized countries.

Body mass index: comparing mean values and prevalence rates from telephone and examination surveys.

BACKGROUND: Cost effective means of assessing the levels of risk factors in the population have to be defined in order to monitor these factors over time and across populations. This study is aimed at analyzing the difference in population estimates of the mean levels of body mass index (BMI) and the prevalences of overweight, between health examination survey and telephone survey. METHODS: The study compares the results of two health surveys, one by telephone (N=820) and the other by physical examination (N=1318). The two surveys, based on independent random samples of the population, were carried out over the same period (1992-1993) in the same population (canton of Vaud, Switzerland). RESULTS: Overall participation rates were 67% and 53% for the health interview survey (HIS) and the health examination survey (HES) respectively. In the HIS, the reporting rate was over 98% for weight and height values. Self-reported weight was on average lower than measured weight, by 2.2 kg in men and 3.5 kg in women, while self-reported height was on average greater than measured height, by 1.2 cm in men and 1.9 cm in women. As a result, in comparison to HES, HIS led to substantially lower mean levels of BMI, and to a reduction of the prevalence rates of obesity (BMI>30 kg/m(2)) by more than a half. These differences are larger for women than for men. CONCLUSION: The two surveys were based on different sampling procedures. However, this difference in design is unlikely to explain the systematic bias observed between self-reported and measured values for height and weight. This bias entails the overall validity of BMI assessment from telephone surveys.

Influence of CRTC1 Polymorphisms on Body Mass Index and Fat Mass in Psychiatric Patients and the General Adult Population.

IMPORTANCE There is a high prevalence of obesity in psychiatric patients, possibly leading to metabolic complications and reducing life expectancy. The CREB-regulated transcription coactivator 1 (CRTC1) gene is involved in energy balance and obesity in animal models, but its role in human obesity is unknown. OBJECTIVE To determine whether polymorphisms within the CRTC1 gene are associated with adiposity markers in psychiatric patients and the general population. DESIGN, SETTING, AND PARTICIPANTS Retrospective and prospective data analysis and population-based samples at Lausanne and Geneva university hospitals in Switzerland and a private clinic in Lausanne, Switzerland. The effect of 3 CRTC1 polymorphisms on body mass index (BMI) and/or fat mass was investigated in a discovery cohort of psychiatric outpatients taking weight gain-inducing psychotropic drugs (sample 1, n = 152). The CRTC1 variant that was significantly associated with BMI and survived Bonferroni corrections for multiple comparison was then replicated in 2 independent psychiatric samples (sample 2, n = 174 and sample 3, n = 118) and 2 white population-based samples (sample 4, n = 5338 and sample 5, n = 123 865). INTERVENTION Noninterventional studies. MAIN OUTCOME AND MEASURE Difference in BMI and/or fat mass between CRTC1 genotype groups. RESULTS Among the CRTC1 variants tested in the first psychiatric sample, only rs3746266A>G was associated with BMI (Padjusted = .003). In the 3 psychiatric samples, carriers of the rs3746266 G allele had a lower BMI than noncarriers (AA genotype) (sample 1, P = .001; sample 2, P = .05; and sample 3, P = .0003). In the combined analysis, excluding patients taking other weight gain-inducing drugs, G allele carriers (n = 98) had a 1.81-kg/m2 lower BMI than noncarriers (n = 226; P < .0001). The strongest association was observed in women younger than 45 years, with a 3.87-kg/m2 lower BMI in G allele carriers (n = 25) compared with noncarriers (n = 48; P < .0001), explaining 9% of BMI variance. In the population-based samples, the T allele of rs6510997C>T (a proxy of the rs3746266 G allele; r2 = 0.7) was associated with lower BMI (sample 5, n = 123 865; P = .01) and fat mass (sample 4, n = 5338; P = .03). The strongest association with fat mass was observed in premenopausal women (n = 1192; P = .02). CONCLUSIONS AND RELEVANCE These findings suggest that CRTC1 contributes to the genetics of human obesity in psychiatric patients and the general population. Identification of high-risk subjects could contribute to a better individualization of the pharmacological treatment in psychiatry.

Mortality risk of obesity and underweight is overestimated with self-reported body mass index.

Obese persons (those with a body mass index [BMI] ≥30 kg/m2) tend to underestimate their weight, leading to an underestimation of their true (measured) BMI and obesity prevalence.1,2 In contrast, underweight people (BMI <18.5 kg/m2) tend to report themselves heavier, resulting in a higher BMI compared with measured BMI and an underestimation of underweight prevalence.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.