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.

Prevalence of low fat-free mass index and high and very high body fat mass index following lung transplantation.

The aim of this study was to determine the prevalence of low fat-free mass index (FFMI) and high and very high body fat mass index (BFMI) after lung transplantation (LTR). A total of 37 LTR patients were assessed prior to and at 1 month, 1 year and 2 years for FFM and compared to 37 matched volunteers (VOL). FFM was calculated by the Geneva equation and normalized for height (kg/m(2)). Subjects were classified as FFMI "low", <or=17.4 in men and <or=15.0 in women; BFMI "high", 5.2-8.1 in men and 8.3-11.7 in women; or "very high" >8.2 kg/m(2) in men and >11.8 kg/m(2) in women. In 23 M/14 F, body mass index (BMI) was 22.3+/-4.4 and 20.1+/-4.9 kg/m(2), respectively. The prevalence of low FFMI was 80% at 1 month and 33% at 2 years after LTR. Prevalence of very high BFMI increased and was higher in patients than VOL after LTR. The prevalence of low FFMI was high prior to and remained important 2 years after LTR, whereas BFMI was lower prior to and higher 2 years after LTR.

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.

Fat-free mass index and fat mass index percentiles in Caucasians aged 18-98 y.

OBJECTIVE: To determine reference values for fat-free mass index (FFMI) and fat mass index (FMI) in a large Caucasian group of apparently healthy subjects, as a function of age and gender and to develop percentile distribution for these two parameters. DESIGN: Cross-sectional study in which bioelectrical impedance analysis (50 kHz) was measured (using tetrapolar electrodes and cross-validated formulae by dual-energy X-ray absorptiometry in order to calculate FFMI (fat-free mass/height squared) and FMI (fat mass/height squared). SUBJECTS: A total of 5635 apparently healthy adults from a mixed non-randomly selected Caucasian population in Switzerland (2986 men and 2649 women), varying in age from 24 to 98 y. RESULTS: The median FFMI (18-34 y) were 18.9 kg/m(2) in young males and 15.4 kg/m(2) in young females. No difference with age in males and a modest increase in females were observed. The median FMI was 4.0 kg/m(2) in males and 5.5 kg/m(2) in females. From young to elderly age categories, FMI progressively rose by an average of 55% in males and 62% in females, compared to an increase in body mass index (BMI) of 9 and 19% respectively. CONCLUSIONS: Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in fat-free mass with or without excess fat mass (sarcopenic obesity) for a given age category, complementing the classical concept of body mass index (BMI) in a more qualitative manner. In contrast to BMI, similar reference ranges seems to be utilizable for FFMI with advancing age, in particular in men.

Obesity markers and blood pressure in a sample of Portuguese children and adolescents.

Little information exists regarding the effect of several obesity markers on blood pressure (BP) levels in youth. Transverse study including 2494 boys and 2589 girls. Height, weight and waist were measured according to the international criteria and body fat (BF) by bioimpedance. BP was measured by an automated device. Hypertension was defined using sex-specific, age-specific and height-specific observation-points. Body mass index (BMI) and waist were positively related with systolic blood pressure (SBP) and diastolic blood pressure (DBP) and heart rate in both sexes, whereas the relationships with BF were less consistent. Stepwise linear regression analysis showed that BMI was positively related with SBP and DBP in both sexes, whereas BF was negatively related with SBP in both sexes and with heart rate in boys only; finally, waist was positively related with SBP in boys and heart rate in girls. Age and heart rate-adjusted values of SBP and DBP increased with BMI: for SBP, 117+/-1, 123+/-1 and 124+/-1 mmHg in normal, overweight and obese boys, respectively; corresponding values for girls were 111+/-1, 114+/-1 and 116+/-2 mmHg (mean+/-SE, P<0.001). Overweight and obese boys had an odds ratio for being hypertensive of 2.26 (95% confidence interval: 1.79-2.86) and 3.36 (2.32-4.87), respectively; corresponding values for girls were 1.58 (confidence interval 1.25-1.99) and 2.31 (1.53-3.50). BMI, not BF or waist, is consistently and independently related to BP levels in children; overweight and obesity considerably increase the risk of hypertension.

Obese and fit adolescents have lower blood pressure levels than obese and unfit counterparts.

The aim of the study was to assess the effects of physical fitness on the relationships between body mass index (BMI) and body fat (BF) on blood pressure (BP) levels. Cross-sectional study conducted in 25 schools of Lisbon (Portugal), including 2041 boys and 1995 girls aged 10-18. BF was assessed by bioimpedance. Cardiovascular fitness was assessed by the 20-meter shuttle run and classified as fit/unfit. Obesity (BMI or BF defined) was defined according to international criteria. In both sexes, BMI was positively related with systolic and diastolic BP, while BF was only positively related with diastolic BP z-scores. No interaction was found between fitness and BMI categories regarding BP levels, while for BF a significant interaction was found. Being fit reduced the BF-induced increase in the Odds ratio (OR) of presenting with high BP: OR (95% confidence interval) 1.01 (0.73-1.40) and 0.99 (0.70-1.38) for overweight and obese fit boys, respectively, the corresponding values for unfit overweight and obese boys being 1.33 (0.94-1.90) and 1.75 (1.34-2.28), respectively. The values were 0.88 (0.57-1.35) and 1.66 (0.98-2.80) for overweight and obese fit girls, respectively, the corresponding values for unfit overweight and obese being 1.63 (1.12-2.37) and 1.90 (1.32-2.73) respectively. No interaction was found between fitness and BMI-defined overweight and obesity. Being fit reduces the negative impact of BF on BP levels and high BP status in adolescents. This protective effect was not found with BMI.

Identifying the best body mass index metric to assess adiposity change in children.

OBJECTIVE: Although dual-energy X-ray absorptiometry (DEXA) is the preferred method to estimate adiposity, body mass index (BMI) is often used as a proxy. However, the ability of BMI to measure adiposity change among youth is poorly evidenced. This study explored which metrics of BMI change have the highest correlations with different metrics of DEXA change. METHODS: Data were from the Quebec Adipose and Lifestyle Investigation in Youth cohort, a prospective cohort of children (8-10 years at recruitment) from Québec, Canada (n=557). Height and weight were measured by trained nurses at baseline (2008) and follow-up (2010). Metrics of BMI change were raw (ΔBMIkg/m(2) ), adjusted for median BMI (ΔBMIpercentage) and age-sex-adjusted with the Centers for Disease Control and Prevention growth curves expressed as centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of DEXA change were raw (total fat mass; ΔFMkg), per cent (ΔFMpercentage), height-adjusted (fat mass index; ΔFMI) and age-sex-adjusted z-scores (ΔFMz-score). Spearman's rank correlations were derived. RESULTS: Correlations ranged from modest (0.60) to strong (0.86). ΔFMkg correlated most highly with ΔBMIkg/m(2) (r = 0.86), ΔFMI with ΔBMIkg/m(2) and ΔBMIpercentage (r = 0.83-0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations with ΔBMIcentile were consistently among the lowest. CONCLUSIONS: In 8-10-year-old children, absolute or per cent change in BMI is a good proxy for change in fat mass or FMI, and BMI z-score change is a good proxy for FM z-score change. However change in BMI centile and change in per cent fat mass perform less well and are not recommended.

Role of reactive hyperreninemia in blood pressure changes induced by sodium depletion in patients with refractory hypertension

Sixteen patients with refractory hypertension were submitted to vigorous sodium depletion while cardiovascular homeostasis was monitored with measurements of hormonal and hemodynamic parameters and repeat saralasin tests. This regimen resulted in a negative sodium balance by an average of 300 mEq. The loss of sodium closely correlated to the decrease of body weight (r = 0.70, p less than 0.005). Blood pressure (BP) decreased from 176/166 +/- 8/3 to 155/109 +/-6/3 mm Hg. There was a significant correlation between percent increments in plasma renin activity (PRA) and the rise in plasma norepinephrine (r = 0.68, p less than 0.05) and a close negative correlation between percent increase in PRA and the ratio of fall in mean blood pressure (MAP) per unit of weight loss (r = -0.73, p less than 0.005). Thus, patients with the least percent increase in PRA demonstrated the greatest fall in BP per unit of weight loss, indicating that relative rather than absolute elevation of renin may be the factor limiting antihypertensive efficacy of sodium depletion. Sodium depletion induced increase in peripheral resistance and decrease in cardiac output, both mostly attributable to relative hyperreninemia. Indeed, the adverse hemodynamic changes were reversed by angiotensin inhibition, during which BP normalized. It is concluded that vigorous sodium depletion complemented by angiotensin blockade or suppression with sympatholytic agents improves management of otherwise refractory hypertension.

Body mass index, abdominal adiposity and blood pressure: consistency of their association across developing and developed countries.

BACKGROUND: Obesity is increasing worldwide because developing countries are adopting Western high-fat foods and sedentary lifestyles. In parallel, in many of them, hypertension is rising more rapidly, particularly with age, than in Western countries. OBJECTIVE: To assess the relationship between adiposity and blood pressure (BP) in a developing country with high average BP (The Seychelles, Indian Ocean, population mainly of African origin) in comparison to a developed country with low average BP (Switzerland, population mainly of Caucasian origin). DESIGN: Cross-sectional health examination surveys based on population random samples. SETTING: The main Seychelles island (Mahé) and two Swiss regions (Vaud-Fribourg and Ticino). SUBJECTS: Three thousand one hundred and sixteen adults (age range 35-64) untreated for hypertension. MEASUREMENTS: Body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), systolic and diastolic blood pressure (SBP and DBP, mean of two measures). METHODS: Scatterplot smoothing techniques and gender-specific linear regression models. RESULTS: On average, SBP and DBP were found to increase linearly over the whole variation range of BMI, WHR and WC. A modest, but statistically significant linear association was found between each indicator of adiposity and BP levels in separate regression models controlling for age. The regression coefficients were not significantly different between the Seychelles and the two Swiss regions, but were generally higher in women than in men. For the latter, a gain of 1.7 kg/m(2) in BMI, of 4.5 cm in WC or of 3.4% in WHR corresponded to an elevation of 1 mmHg in SBP. For women, corresponding figures were 1.25 kg/m(2), 2.5 cm and 1.8% respectively. Regression coefficients for age reflected a higher effect of this variable on both SBP and DBP in the Seychelles than in Switzerland. CONCLUSION: These findings suggest a stable linear relation of adiposity with BP, independent of age and body fat distribution, across developed and developing countries. The more rapid increase of BP with age observed in the latter countries are likely to reflect higher genetic susceptibility and/or higher cumulative exposure to another risk factor than adiposity.

Inflammatory markers and blood pressure: sex differences and the effect of fat mass in the CoLaus Study.

Several studies have reported high levels of inflammatory biomarkers in hypertension, but data coming from the general population are sparse, and sex differences have been little explored. The CoLaus Study is a cross-sectional examination survey in a random sample of 6067 Caucasians aged 35-75 years in Lausanne, Switzerland. Blood pressure (BP) was assessed using a validated oscillometric device. Anthropometric parameters were also measured, including body composition, using electrical bioimpedance. Crude serum levels of interleukin-6 (IL-6), tumor necrosis factor α (TNF-α) and ultrasensitive C-reactive protein (hsCRP) were positively and IL-1β (IL-1β) negatively (P<0.001 for all values), associated with BP. For IL-6, IL-1β and TNF-α, the association disappeared in multivariable analysis, largely explained by differences in age and body mass index, in particular fat mass. On the contrary, hsCRP remained independently and positively associated with systolic (β (95% confidence interval): 1.15 (0.64; 1.65); P<0.001) and diastolic (0.75 (0.42; 1.08); P<0.001) BP. Relationships of hsCRP, IL-6 and TNF-α with BP tended to be stronger in women than in men, partly related to the difference in fat mass, yet the interaction between sex and IL-6 persisted after correction for all tested confounders. In the general population, the associations between inflammatory biomarkers and rising levels of BP are mainly driven by age and fat mass. The stronger associations in women suggest that sex differences might exist in the complex interplay between BP and inflammation.

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.

No use for waist-for-height ratio in addition to body mass index to identify children with elevated blood pressure.

Abstract Background. In children, waist-for-height ratio (WHtR) has been proposed to identify subjects at higher risk of cardiovascular diseases. The utility of WHtR to identify children with elevated blood pressure (BP) is unclear. Design. Cross-sectional population-based study of schoolchildren. Methods. Weight, height, waist circumference and BP were measured in all sixth-grade schoolchildren of the canton de Vaud (Switzerland) in 2005/06. WHtR was computed as waist [cm]/height [cm]. Elevated BP was defined according to sex-, age- and height-specific US reference data. The area under the receiver operating characteristic curve (AUC) statistic was computed to compare the ability of body mass index (BMI) z-score and WHtR, alone or in combination, to identify children with elevated BP. Results. 5207 children participated (76% response) [2621 boys, 2586 girls; mean (± SD) age, 12.3 ± 0.5 years; range: 10.1-14.9]. The prevalence of elevated BP was 11%. Mean WHtR was 0.44 ± 0.05 (range: 0.29- 0.77) and 11% had high WHtR (> 0.5). BMI z-score and WHtR were strongly correlated (Spearman correlation coefficient r = 0.76). Both indices were positively associated with elevated BP. AUCs for elevated BP was relatively low for BMI z-score (0.62) or for WHtR (0.62), and was not substantially improved when both indices were considered together (0.63). Conclusions. The ability of BMI z-score or WHtR to identify children aged 10-14 with elevated BP was weak. Adding WHtR did not confer additional discriminative power to BMI alone. These findings do not support the measurement of WHtR in addition to BMI to identify children with elevated BP.

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.