Body composition and all-cause mortality in subjects older than 65 y

The association between android-to-gynoid lean mass ratio and all-cause and specific-cause mortality in US adults: A prospective study

OBJECTIVE

The associations of lean mass distribution with mortality risk are not fully elucidated. We aimed to evaluate the effects of a new lean mass distribution indicator-android/gynoid lean mass ratio (AGLR) evaluated by dual-energy x-ray absorptiometry (DXA) on the risk of all-cause and specific-cause mortality in a NHANES cohort.

METHODS

This was a population-based cohort study, which included 18 542 subjects aged 20 years and older from the US National Health and Nutrition Examination Survey (US NHANES, 2003-2006 and 2011-2018). The primary outcomes of our study were all-cause mortality, cardiovascular (CVD) mortality and cancer mortality, which were obtained from the linkage to registries. Cox proportional hazard regression models were used to investigate the association between lean mass distribution and mortality risk among the US NHANES general population. Restricted cubic spline nested in Cox regression was also used to test whether there was a non-linear association of AGLR as a continuous variable with the risk of mortality.

RESULTS

During a median follow-up of 6.9 years, 1412 participants died, of whom 435 were due to CVD and 340 were due to cancer. The multivariable-adjusted (Model 4) hazard ratios (HRs) for each SD increase in AGLR were 1.53 (95% confidence interval [CI] 1.40-1.67) for all-cause mortality, 1.56 (95% CI 1.30-1.87) for cancer mortality and 1.64 (95% CI 1.47-1.84) for CVD mortality. The associations were robust in sensitivity analyses and present in most subgroups.

CONCLUSIONS

AGLR evaluated by DXA was associated with a higher risk of all-cause and specific-cause mortality among the general population from the US NHANES cohort.

Rapamycin administration causes a decrease in muscle contractile function and systemic glucose intolerance concomitant with reduced skeletal muscle Rictor, the mTORC2 component, expression independent of energy intake in young rats

Emerging evidence suggests the potential of rapamycin, an antibiotic from Streptomyces hygroscopicus that functions as a mechanistic target of rapamycin (mTOR) inhibitor, as a mimetic of caloric restriction (CR) for maintaining skeletal muscle health. Several studies showed that rapamycin administration (RAP) reduced appetite and energy intake. However, the physiological and molecular differences between RAP and CR in skeletal muscle are not fully understood. Here we observed the effects of 4 weeks of RAP administration and CR corresponding to the reduction in energy intake produced by RAP administration (PF, paired feeding) on fast glycolytic and slow oxidative muscle in young adult rats. We found that 4 weeks of RAP demonstrated low fast-glycolytic muscle mass with smaller type I and IIb/x myofiber size independent of the energy intake. In addition, PF improved the contractile function of the plantar flexor muscle, whereas RAP did not improve its function. The suppressing response of mTORC1 signaling to RAP is greater in slow-oxidative muscles than in fast-glycolytic muscles. In addition, systemic glucose tolerance was exacerbated by RAP, with reduced expression of Rictor and hexokinase in skeletal muscle. These observations imply that RAP may have a slight but significant negative impact and it obviously different to CR in young adult skeletal muscle.

Phase angle as a marker of muscle quality: A systematic review and meta-analysis

BACKGROUND & AIMS

Phase angle (PhA) is a biomarker derived from raw bioelectrical impedance analysis (BIA) values: resistance (R) and reactance (Xc). PhA reflects cellular membrane integrity and, as a result, has been considered a marker of fluid distribution, making it a potential prognostic indicator. A growing body of research demonstrates independent associations between PhA and muscle strength, mass, and composition. In this context, PhA has the extra potential to serve as a marker of muscle quality. However, the evidence supporting its use for this purpose is not well established. This study aimed to investigate the relationship between PhA and markers of muscle quality.

METHODS

This systematic review and meta-analysis (Internal Prospective Register of Systematic Reviews - PROSPERO on a registration code: CRD42024507853) focused on observational studies assessing the relationship between PhA and markers of both concepts of muscle quality: the muscle quality index (MQI: strength by a unit of mass) and the muscle composition (i.e., skeletal muscle radiodensity [SMD], muscle echogenicity, muscle fat fraction, inter- and intramuscular adiposity). Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), while the certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Meta-analyses with a random-effects model were conducted.

RESULTS

Seventeen studies were included in this systematic review, encompassing 2710 participants. Meta-analyses demonstrated that PhA had a moderate positive correlation coefficient with SMD (4 studies, 924 participants; r = 0.54, 95 % confidence interval (CI) 0.38 to 0.69, heterogeneity (I2) = 92 %) and good accuracy (85 %) for classifying low SMD (2 studies, 390 participants; Area Under the Curve - AUCpooled 0.85, 95 % CI 0.78 to 0.92, I2 = 0 %). PhA was inversely-moderately correlated with muscle echogenicity (8 studies, 1401 participants; r = - 0.42, 95 % CI - 0.57 to - 0.24, I2 = 82 %) and positively-weakly correlated with MQI (2 studies, 191 participants; r = 0.36, 95 % CI 0.21 to 0.49, I2 = 17 %). All studies had a higher risk of bias. The certainty of evidence ranged from low to very low.

CONCLUSION

Despite technical challenges, this study demonstrates the potential of PhA as a surrogate marker for muscle quality, particularly expressing muscle composition (SMD). Future studies should utilize BIA with standardized protocols to potentially establish specific cutoff values for PhA, thereby enhancing its diagnostic accuracy and clinical applicability. These studies could additionally explore the mechanisms underlying the associations between PhA and muscle quality aspects. In cases where technical factors are not easily controlled, the use of standardized PhA (SPhA), which converts PhA into Z-scores, could be beneficial. Although this warrants investigation, this approach (SPhA) has the potential to account for variables such as age, sex, device differences, and health status.

Association of fat mass and fat-free mass with all-cause and cause-specific mortality in Asian individuals: A prospective cohort study

OBJECTIVE

The study's objective was to investigate the association of fat mass index (FMI) and fat-free mass index (FFMI) with all-cause mortality and cause-specific mortality in the Chinese population.

METHODS

A total of 422,430 participants (48.1% men and 51.9% women) from the Taiwan MJ Cohort with an average follow-up of 9 years were included.

RESULTS

The lowest (Q1) and highest (Q5) quintiles of FMI and FFMI were associated with increased all-cause mortality. Compared with those in the third quintile (Q3) group of FMI, participants in Q1 and Q5 groups of FMI had hazard ratios and 95% CI of 1.32 (1.24-1.40) and 1.13 (1.06-1.20), respectively. Similarly, compared with those in Q3 group of FFMI, people in Q1 and Q5 groups of FFMI had hazard ratios of 1.14 (1.06-1.23) and 1.16 (1.10-1.23), respectively. In the restricted cubic spline models, both FMI and FFMI showed a J-shaped association with all-cause mortality. People in Q5 group of FFMI had a hazard ratio of 0.72 (0.58-0.89) for respiratory disease.

CONCLUSIONS

The mortality risk increases in those with excessively high or low FMI and FFMI, yet the associations between FMI, FFMI, and the risk of death varied across subgroups and causes of death.

Association of body fat distribution with all-cause and cardiovascular mortality in US adults: a secondary analysis using NHANES

OBJECTIVE

To investigate the association of fat and lean mass in specific regions with all-cause and cardiovascular-related mortality.

DESIGN

Population based cohort study.

SETTING

US National Health and Nutrition Examination Survey (2003-2006 and 2011-2018).

PARTICIPANTS

22 652 US adults aged 20 years or older.

EXPOSURES

Fat and lean mass in specific regions obtained from the whole-body dual-energy X-ray absorptiometry.

MAIN OUTCOME MEASURES

All-cause and cardiovascular-related mortality.

RESULTS

During a median of 83 months of follow-up, 1432 deaths were identified. Associations between body composition metrics and mortality risks were evident above specific thresholds. For all-cause mortality, Android fat mass showed elevated HRs above 2.46 kg (HR: 1.17, 95% CI 1.02 to 1.34), while Android lean mass (ALM) had similar trends above 2.75 kg (HR: 1.17, 95% CI 1.03 to 1.33), and Android total mass above 5.75 kg (HR: 1.08, 95% CI 1.01 to 1.16). Conversely, lower HRs were observed below certain thresholds: Gynoid fat mass (GFM) below 3.71 kg (HR: 0.72, 95% CI 0.56 to 0.93), Gynoid lean mass below 6.44 kg (HR: 0.77, 95% CI 0.64 to 0.92), and Gynoid total mass below 11.78 kg (HR: 0.76, 95% CI 0.70 to 0.84). Notably, below 0.722 kg, the HR of visceral adipose tissue mass (VATM) was 1.25 (95% CI 1.04 to 1.48) for all-cause mortality, and above 3.18 kg, the HR of total abdominal fat mass was 2.41 (95% CI 1.15 to 5.05). Cardiovascular-related mortality exhibited associations as well, particularly for Android fat mass (AFM) above 1.78 kg (HR: 1.22, 95% CI 1.01 to 1.47) and below 7.16 kg (HR: 0.50, 95% CI 0.36 to 0.69). HRs varied for Gynoid total mass below and above 10.98 kg (HRs: 0.70, 95% CI 0.54 to 0.93, and 1.12, 95% CI 1.02 to 1.23). Android per cent fat, subcutaneous fat mass (SFM), AFM/GFM, and VATM/SFM were not statistically associated with all-cause mortality. Android per cent fat, Gynoid per cent fat, AFM/GFM, and VATM/SFM were not statistically associated with cardiovascular-related mortality. Conicity index showed that the ALM/GLM had the highest performance for all-cause and cardiovascular-related mortality with AUCs of 0.785, and 0.746, respectively.

CONCLUSIONS

The relationship between fat or lean mass and all-cause mortality varies by region. Fat mass was positively correlated with cardiovascular mortality, regardless of the region in which they located. ALM/GLM might be a better predictor of all-cause and cardiovascular-related mortality than other body components or body mass index.

Muscle distribution in relation to all-cause and cause-specific mortality in young and middle-aged adults

BACKGROUND

The relationship between muscle and prognosis, especially that between muscle distribution across different body parts, and the related prognosis is not well established.

OBJECTIVE

To investigate the relationship between muscle distribution and all-cause and cause-specific mortality and their potential modifiers.

DESIGN

Longitudinal cohort study. C-index, IDI, and NRI were used to determine the best indicator of prognosis. COX regression analysis was performed to explore the relationship between variables and outcomes. Interaction and subgroup analyses were applied to identify the potential modifiers.

PARTICIPANTS

A total of 5052 participants (weighted: 124,841,420) extracted from the NHANES 2003-2006 of median age 45 years and constituting 50.3% men were assessed. For validation, we included 3040 patients from the INSCOC cohort in China.

MAIN MEASURES

Muscle mass and distribution. KEY RESULTS: COX regression analysis revealed that upper limbs (HR = 0.41, 95% CI 0.33-0.51), lower limbs (HR = 0.54, 95% CI 0.47-0.64), trunk (HR = 0.71, 95% CI, 0.59-0.85), gynoid (HR = 0.47, 95% CI 0.38-0.58), and total lean mass (HR = 0.55, 95% CI 0.45-0.66) were all associated with the better survival of participants (P trend < 0.001). The changes in the lean mass ratio of the upper and lower limbs and the lean mass ratio of the android and gynoid attenuated the protective effect of lean mass. Age and sex acted as potential modifiers, and the relationship between lean mass and the prognosis was more significant in men and middle-aged participants when compared to that in other age groups. Sensitive analyses depicted that despite lean mass having a long-term impact on prognosis (15 years), it has a more substantial effect on near-term survival (5 years).

CONCLUSION

Muscle mass and its distribution affect the prognosis with a more significant impact on the near-term than that on the long-term prognosis. Age and sex acted as vital modifiers.

Associations of muscle mass, strength, and quality with all-cause mortality in China: a population-based cohort study

BACKGROUND

It remains unclear about the association of muscle mass, strength, and quality with death in the general Chinese population of diverse economical and geographical backgrounds. The present study aimed to comprehensively examine such associations across different regions in China.

METHODS

Based on the China Kadoorie Biobank study, the present study included 23,290 participants who were aged 38 to 88 years and had no prevalent cardiovascular diseases or cancer. Muscle mass and grip strength were measured using calibrated instruments. Arm muscle quality was defined as the ratio of grip strength to arm muscle mass. Low muscle mass, grip strength, and arm muscle quality were defined as the sex-specific lowest quintiles of muscle mass index, grip strength, and arm muscle quality, respectively. Cox proportional hazards models yielded hazard ratios (HRs) and 95% confidence intervals (CIs) for risks of all-cause mortality in relation to muscle mass, strength, and quality.

RESULTS

During a median follow-up of 3.98 years, 739 participants died. The HR (95% CI) of all-cause mortality risk was 1.28 (1.08-1.51) for low appendicular muscle mass index, 1.38 (1.16-1.62) for low total muscle mass index, 1.68 (1.41-2.00) for low grip strength, and 1.41 (1.20-1.66) for low arm muscle quality in models adjusted for sociodemographic characteristics, lifestyle factors, and medical histories.

CONCLUSION

Low muscle mass, grip strength, and arm muscle quality are all associated with short-term increased risks of mortality, indicating the importance of maintaining normal muscle mass, strength, and quality for general Chinese adults.

Effects of age and gender on body composition indices as predictors of mortality in middle-aged and old people

To determine whether body composition indices interact with age and gender as a predictor of all-cause mortality, 1200 participants at least 40 years of age were recruited in 2009 and 2010. A multi-frequency bioelectrical impedance analysis device was used to measure each participant's body composition indices, including the fat mass index (FMI), fat free mass index (FFMI), skeletal muscle mass index (SMMI), and visceral fat area index (VFAI). A baseline questionnaire was used to collect demographic information about lifestyle habits, socioeconomic status, and medical conditions. All claimed records of death from 2009 to 2018 in the National Health Insurance Research Databank were identified. The all-cause mortality rate was 8.67% after a mean follow-up period of 5.86 ± 2.39 person-years. The Cox proportional hazard model analysis showed significantly negative associations between FFMI or SMMI with all-cause mortality in the total group and those aged ≥ 65 y/o. The FFMI and SMMI were negative predictors of mortality in both genders. The FMI and VFAI were positive predictors of mortality exclusively in females. In conclusion, the SMMI is a better predictor of mortality than the BMI, FMI, and FFMI, especially in older adults. A higher fat mass or visceral fat distribution may predict higher mortality in females.

Influence of changes in body fat on clinical outcomes in a general population: a 12-year follow-up report on the Ansan-Ansung cohort in the Korean Genome Environment Study

BACKGROUND

The impact of the changes in the obesity status on mortality has not been established; thus, we investigated the long-term influence of body fat (BF) changes on all-cause deaths and cardiovascular outcomes in a general population.

METHODS

A total of 8374 participants were observed for 12 years. BF was measured at least two times using a bioimpedance method. The causes of death were acquired from the nationwide database. A major adverse cardiovascular event (MACE) was defined as a composite of myocardial infarction, coronary artery disease, stroke, and cardiovascular death. Standard deviations (SDs) were derived using a local regression model corresponding to the time elapsed between the initial and final BF measurements (SD_T) and were used to standardize the changes in BF (ΔBF/SD_T).

RESULTS

The incidence rates of all-cause death, cardiovascular death, and MACE were the highest in the participants with ΔBF/SD_T <-1 and lowest in the participants with ΔBF/SD_T ≥1. Multivariate Cox proportional hazard models adjusted for relevant covariates, including baseline obesity and physical activity, showed that the risks of all-cause deaths (hazard ratio [HR] 0.58; 95% confidence intervals [CI] 0.53-0.64), cardiovascular deaths (HR 0.63; 95% CI 0.51-0.78) and MACEs (HR 0.68; 95% CI 0.62-0.75) decreased as ΔBF/SD_T increased. Subgroup analyses showed that existing cardiovascular diseases weakened the associations between higher ΔBF/SD_T and better outcomes, while high physical activity and exercise did not impact the associations.

CONCLUSION

Increasing BF was associated with a lower risk of all-cause death, cardiovascular death, and MACE in the general population.Key messagesIncreasing body fat is associated with a lower risk of all-cause death, cardiovascular death, and major cardiovascular adverse events in a low-risk ageing general population, independently of physical activity, underlying cardiovascular disease burden, changes in muscle mass, and baseline obesity status.Fatness measured at baseline requires adjustment for the changes in fatness during the follow-up to reveal its impact on the clinical outcomes.

Association of the fat-free mass index with mortality in patients with cancer: A multicenter observational study

OBJECTIVES

Low fat-free mass index (FFMI) has been related to a higher mortality in community populations. However, information on the relationship between FFMI and mortality is lacking for patients with cancer. The objective of this study was to examine the association between FFMI and all-cause mortality in Chinese cancer patients.

METHODS

This retrospective analysis included data on 1744 patients with cancer from a multicenter cohort study. The restricted cubic splines were used to flexibly model the association of FFMI with all-cause mortality. The association between low FFMI and overall survival was analyzed with the Kaplan-Meier method and a Cox model.

RESULTS

Among all patients, there were 702 men (40.3%) and 1042 women (59.7%). The optimal cutoff point of low FFMI was 16.31 for men and 14.14 for women. The FFMI showed an inverse association with all-cause mortality for men (per standard deviation [SD] increment; hazard ratio [HR]: 0.72; 95% confidence interval [CI], 0.60-0.87; P < 0.001) and a nonlinear relation for women (per SD increment; HR: 0.88; 95% CI, 0.78-0.99; P = 0.048). After adjustment, a low FFMI score was independently associated with an increased risk of mortality for both men and women. In addition, FFMI showed a strong L-shape (per SD increment; HR: 0.59; 95% CI, 0.46-0.76; P < 0.001) relation with all-cause mortality in elderly patients with cancer. For specific tumor type, a low FFMI score was independently associated with worse prognosis in patients with lung and upper gastrointestinal cancer.

CONCLUSIONS

A low FFMI score was associated with all-cause mortality in patients with cancer, especially for elder adults with cancer. These results highlight the usefulness of the FFMI for routine clinical assessment and prognostic estimation in patients with cancer.

Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review

Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations.

Associations of Skeletal Muscle Mass and Fat Mass With Incident Cardiovascular Disease and All-Cause Mortality: A Prospective Cohort Study of UK Biobank Participants

Background There is debate whether body mass index is a good predictor of health outcomes because different tissues, namely skeletal muscle mass (SMM) and fat mass (FM), may be differentially associated with risk. We investigated the association of appendicular SMM (aSMM) and FM with fatal and nonfatal cardiovascular disease (CVD) and all-cause mortality. We compared their prognostic value to that of body mass index. Methods and Results We studied 356 590 UK Biobank participants aged 40 to 69 years with bioimpedance analysis data for whole-body FM and predicted limb muscle mass (to calculate aSMM). Associations between aSMM and FM with CVD and all-cause mortality were examined using multivariable Cox proportional hazards models. Over 3 749 501 person-years of follow-up, there were 27 784 CVD events and 15 844 all-cause deaths. In men, aSMM was positively associated with CVD incidence (hazard ratio [HR] per 1 SD 1.07; 95% CI, 1.06-1.09) and there was a curvilinear association in women. There were stronger positive associations between FM and CVD with HRs per SD of 1.20 (95% CI, 1.19-1.22) and 1.25 (95% CI, 1.23-1.27) in men and women respectively. Within FM tertiles, the associations between aSMM and CVD risk largely persisted. There were J-shaped associations between aSMM and FM with all-cause mortality in both sexes. Body mass index was modestly better at discriminating CVD risk. Conclusions FM showed a strong positive association with CVD risk. The relationship of aSMM with CVD risk differed between sexes, and potential mechanisms need further investigation. Body fat and SMM bioimpedance measurements were not superior to body mass index in predicting population-level CVD incidence or all-cause mortality.

Relation of body fat mass and fat-free mass to total mortality: results from 7 prospective cohort studies

BACKGROUND

Fat mass and fat-free mass may play independent roles in mortality risk but available studies on body composition have yielded inconsistent results.

OBJECTIVE

The aim was to determine the relations of body fat mass and fat-free mass to risk of mortality.

METHODS

In pooled data from 7 prospective cohorts encompassing 16,155 individuals aged 20 to 93 y (median, 44 y), we used Cox regression and restricted cubic splines to estimate HRs and 95% CIs for the relation of body composition, measured by bioelectrical impedance analysis, to total mortality. We adjusted for age, study, sex, ethnicity, history of diabetes mellitus, education, smoking, physical activity, and alcohol consumption.

RESULTS

During a median follow-up period of 14 y (range, 3-21 y), 1347 deaths were identified. After mutual adjustment for fat mass and fat-free mass, fat mass showed a J-shaped association with mortality (overall P value < 0.001; P for nonlinearity = 0.003). Using a fat mass index of 7.3 kg/m2 as the reference, a high fat mass index of 13.0 kg/m2 was associated with an HR of 1.56 (95% CI: 1.30, 1.87). In contrast, fat-free mass showed an inverse association with mortality (overall P value < 0.001; P for nonlinearity = 0.001). Compared with a low fat-free mass index of 16.1 kg/m2, a high fat-free mass of 21.9 kg/m2 was associated with an HR of 0.70 (95% CI: 0.56, 0.87).

CONCLUSIONS

Fat mass and fat-free mass show opposing associations with mortality. Excess fat mass is related to increased mortality risk, whereas fat-free mass protects against risk of mortality. These findings suggest that body composition provides important prognostic information on an individual's mortality risk not provided by traditional proxies of adiposity such as BMI.

Validity of a Single Activity Question for Clinical Assessment of Older Women

Physical activity is an important part of clinical assessment. However, objective measurement can be expensive and burdensome. The current study validated a single activity question for use in clinical assessment. Ninety-seven older women (mean age = 73.7 years, SE = 0.7) completed an activity questionnaire and measurement of anthropometrics, body composition, and strength. Activity level was reported as not active, somewhat active, active, and very active. Activity level was significantly related to hours of light, moderate, and vigorous activity; body mass index (BMI); waist circumference; percent fat and lean mass; and strength (p < 0.05). When activity levels were collapsed into two groups (not active + somewhat active, and active + very active), women in the high activity group (n = 48) were significantly (p < 0.05) more active, had healthier BMI and waist circumference values, less fat and more lean mass, and were stronger than women in the low activity group (n = 49). A single activity question is valid for use in clinical assessment. [Journal of Gerontological Nursing, 46(12), 15-22.].

Nutritional Intervention to Prevent the Functional Decline in Community-Dwelling Older Adults: A Systematic Review

Aging is a global public health concern. From the age of 50, muscle mass, muscle strength and physical performance tend to decline. Sarcopenia and frailty are frequent in community-dwelling older adults and are associated with negative outcomes such as physical disability and mortality. Therefore, the identification of therapeutic strategies to prevent and fight sarcopenia and frailty is of great interest. This systematic review aims to summarize the impact of nutritional interventions alone or combined with other treatment(s) in older community-dwelling adults on (1) the three indicators of sarcopenia, i.e., muscle mass, muscle strength and physical performance; and (2) the hospitalization and readmission rates. The literature search was performed on Medline and included studies published between January 2010 and June 2020. We included randomized controlled trials of nutritional intervention alone or combined with other treatment(s) in community-living subjects aged 65 or older. In total, 28 articles were retained in the final analysis. This systematic review highlights the importance of a multimodal approach, including at least a combined nutritional and exercise intervention, to improve muscle mass, muscle strength and physical performance, in community-dwelling older adults but especially in frail and sarcopenic subjects. Regarding hospitalization and readmission rate, data were limited and inconclusive. Future studies should continue to investigate the effects of such interventions in this population.

Cardiovascular Adaptations to Four Months Training in Middle-Aged Amateur Long-Distance Skiers

Cross-country skiing has a positive effect on health. However, without an individual, thoughtful, and professional plan, it can cause irreversible health problems from overload and injury. The impact of exercise on results is well understood within the group of professional athletes. However, this remains unknown within the group of amateur cross-country skiers and marathon runners—in particular, the impact of the summer preparation period in which training loads performed in the oxygen zone combined with resistance training dominate. The aim of this study was to assess changes in the cardiovascular capacity and body mass composition of male cross-country skiers in the preparation period of their macrocycle. Variables were analyzed using basic descriptive statistics: mean and standard deviation (SD). To compare the results from both measurements (initial and final) the paired Wilcoxon test was used. A statistically significant increase was noted in maximum oxygen uptake and maximum minute ventilation, and a decrease in body fat content, maximum lactate concentration and lactate threshold, and heart rate on anaerobic threshold. Research indicated that in the amateur group increases similar to those in top competitors were achieved in the parameters tested, but the initial level was often significantly lower.

High muscle-to-fat ratio is associated with lower risk of chronic kidney disease development

BACKGROUND

Obesity, a known risk factor for chronic kidney disease (CKD), is generally assessed using body mass index (BMI). However, BMI may not effectively reflect body composition, and the impact of muscle-to-fat (MF) mass balance on kidney function has not been elucidated. This study evaluated the association between body muscle and fat mass balance, represented as the MF ratio, and incident CKD development.

METHODS

Data were retrieved from a prospective community-based cohort study (Korean Genome and Epidemiology Study). Muscle and fat mass were measured using multifrequency bioelectrical impedance analysis. The study endpoint was incident CKD (estimated glomerular filtration rate <60 mL/min/1.73 m2 in at least two or more consecutive measurements during the follow-up period).

RESULTS

Totally, 7682 participants were evaluated. Their mean age was 51.7 ± 8.7 years, and 48% of the subjects were men. During a median follow-up of 140.0 (70.0-143.0) months, 633 (8.2%) subjects developed incident CKD. When the association between body composition and incident CKD was investigated, multivariable Cox proportional hazard analysis revealed that increase in MF ratio was related with a decreased risk of CKD development [per 1 increase in MF ratio: hazard ratio (HR), 0.86; 95% confidence interval (CI), 0.77-0.96; P = 0.008]. This association was also maintained when MF ratio was dichotomized according to sex-specific median values (high vs. low: HR, 0.83; 95% CI, 0.70-0.98; P = 0.031). Analyses preformed in a propensity score matched group also revealed a similar decreased risk of incident CKD in high MF ratio participants (high vs. low: HR, 0.84; 95% CI, 0.71-0.98; P = 0.037). This relationship between MF ratio and incident CKD risk was consistently significant across subgroups stratified by age, sex, hypertension, estimated glomerular filtration rate categories, and proteinuria. Among different BMI groups (normal, overweight, and obese), the relationship between high MF ratio and lower incident CKD risk was significant only in overweight and obese subjects.

CONCLUSIONS

Lower fat mass relative to muscle mass may lower the risk of CKD development in individuals with normal renal function. This relationship seems more prominent in overweight and obese subjects than in normal weight subjects.

Does lean body mass equal health despite body mass index?

OBJECTIVE

To determine the association between having simultaneously high body mass index (BMI) and high relative lean body mass (LBM) and cardio-metabolic risk factors, metabolic syndrome (MetS), and diabetes in adults.

MATERIALS AND METHODS

A cross-sectional analysis was performed on 4982 adults aged 19-85 years that participated in the National Health and Nutrition Examination Survey (cycles 1999-2000-2005-2006). The primary exposure variable was categorization into four groups: (a) Low-BMI/Low-LBM, (b) Low-BMI/High-LBM, (c) High-BMI/Low-LBM, and (d) High-BMI/High-LBM. LBM was assessed using dual-energy X-ray absorptiometry. The primary outcome measures were cardio-metabolic risk factors, MetS based on the ATP III definition; participants were required to have at least three of the following five criteria: high waist circumference, low HDL cholesterol, elevated triglyceride levels, high resting blood pressure, and self-reported diabetes.

RESULTS

Compared to the High-BMI/High-LBM, most cardio-metabolic risk factors were significantly different among groups (P < .05) while no such differences were observed for the High-BMI/Low-LBM (P > .05). Exception of waist circumference (OR [95%]: 21.8 [8.84-53.82]), there was no increased odds of having cardio-metabolic risk factors in the High-BMI/Low-LBM compared with the High-BMI/High-LBM (P > .05). The odds of having MetS and diabetes for the High-BMI/Low-LBM compared with the High-BMI/High-LBM were OR (95% CI): 1.68 (0.84-3.36) and 0.59 (0.26-1.34), respectively.

CONCLUSIONS

Our results suggest that having a high-BMI as well as high relative LBM levels is not associated with cardio-metabolic risk factors, MetS, and diabetes. Therefore, maintaining a BMI below 30 kg/m² appears to be clinically relevant, regardless of LBM levels.

Body composition and mortality in the general population: A review of epidemiologic studies

IMPACT STATEMENT

Current understanding of the association of body composition on mortality in the general population is limited. This review evaluated the available epidemiologic studies on body composition and mortality that leveraged diverse approaches to estimate body composition. Although studies showed inconsistent results, there was evidence suggesting that high fat mass and low lean body mass may be independently associated with mortality in the general population. This review may help partially explain the "obesity paradox" phenomenon and facilitate further studies to advance the understanding of the association of body composition on health in the general and patient populations.

Running performance in a timed city run and body composition: A cross-sectional study in more than 3000 runners

OBJECTIVE

The importance of body composition for running performance is unclear in the general population. The aim of this study was to evaluate whether body composition influences running speed and whether it is a better predictor of running speed than body mass index (BMI).

METHODS

The study included 1353 women (38.2 ± 12.1 y of age) and 1771 men (39.6 ± 12.1 y of age) who underwent, for the first time, a measurement of body composition by bioelectrical impedance analysis between 1999 and 2016, before a timed run occurring annually in Geneva. The running distances and times were converted to average speed (km/h). Body composition was expressed as sex-specific quartiles, where quartile 1 (lowest values) was the reference quartile. The relationships between speed and BMI or body composition were analyzed by multivariate linear regressions.

RESULTS

Multivariate regressions showed that the higher the fat mass index (FMI) quartile, the lower the running speed in women and men (all P < 0.001). In men, a fat-free mass index (FFMI) in quartile 4 (>20 kg/m²) was associated with a poor running performance (r = -0.50, P < 0.001), whereas in women, an FFMI in quartile 2 or 3 (15-16.4 kg/m²) was associated with a higher running speed (r = 0.23, P = 0.04; r = 0.28, P = 0.01, respectively). Body composition predicted speed better than BMI in women (R² = 26.8% versus 14.4%) and men (R² = 29.8% versus 25.4%).

CONCLUSIONS

Running speed is negatively associated with BMI and FMI in both sexes. Body composition is a better predictor of running performance than BMI.

Characteristics and reference values of fat mass index and fat free mass index by bioelectrical impedance analysis in an adult population

BACKGROUND & AIMS

We aim to examine the influence of sex, age, region and ethnicity on fat mass index (FMI) and fat free mass index (FFMI), and to establish FMI and FFMI reference values in Chinese adults.

METHODS

A stratified cluster sampling method was adopted to enroll Chinese participants in this cross-sectional study. Questionnaire surveys and medical examinations were performed to collect data, and body composition parameters were measured by bioelectrical impedance analysis. FMI and FFMI were calculated as the ratio of fat mass and fat free mass to the square of height. Differences in mean values for parameters were tested by Student's t-test or one-way analysis of variance. Reference values of FMI and FFMI were obtained using the percentiles method.

RESULTS

A total of 8959 multiethnic healthy Chinese adults were included in the analysis. Males had higher mean FFMI (males, 18.6 ± 1.6 kg/m²; females, 15.7 ± 1.1 kg/m², P < 0.001) but lower mean FMI (males, 5.1 ± 2.1 kg/m²; females, 7.8 ± 2.8 kg/m², P < 0.001) than did female participants regardless of age and ethnicity. For both sexes, FMI (Male: Bouyei, 4.2 ± 1.8 kg/m²; Uygur, 5.8 ± 2.2 kg/m², P < 0.001; Female: Bouyei, 6.7 ± 2.3 kg/m²; Uygur, 9.0 ± 3.2 kg/m², P < 0.001) and FFMI (Male: Bouyei, 17.8 ± 1.4 kg/m²; Uygur, 19.4 ± 1.6 kg/m², P < 0.001; Female: Bouyei, 15.1 ± 1.0 kg/m²; Uygur, 16.3 ± 1.1 kg/m², P < 0.001) were lowest in Bouyeis and highest in Uygurs. FMI and FFMI values increased with age until they peaked in the 30-39 year age group in males and after the age of 40 years in females for all ethnic groups. Reference values (5th-95th percentile) of FMI and FFMI were presented according to gender, age, region and ethnicity.

CONCLUSION

The body composition of Chinese population differs in different age, sex, ethnicity and region subgroups. Practitioners and future studies may need to consider different reference values for FMI and FFMI in Chinese adults among Han, Bouyei and Uygur populations; these values can serve as indices for evaluating nutrition status and identifying abnormalities in body composition.

Severe central obesity or diabetes can replace weight loss in the detection of frailty in obese younger elderly - a preliminary study

Purpose

Unwanted weight loss is one of the established criteria for the diagnosis of frailty. However, the relevance of this criterion to detect frailty in obese older adults has not been assessed. In particular, with the exception of malignancy, unwanted weight loss is not commonly seen in older obese subjects. Therefore, we tested the possibility that some obesity phenotypes and/or diabetes might be more useful in the detection of frailty in this setting.

Patients and methods

A preliminary cross-sectional study of 50 consecutive subjects was conducted at The Institute of Endocrinology, Metabolism and Hypertension, Tel-Aviv Sourasky Medical Center. Inclusion criteria were: young elderly (aged 65–75 years), with general and/or abdominal obesity, without cancer. Frailty was assessed directly using the Fried model, the five-item fatigue, resistance, ambulation, illnesses, and loss of weight (FRAIL) scale. Eventually, in the assessment of frailty, the weight loss criterion was replaced by one or several of obesity/diabetes-related variables each time: severity of obesity by body mass index, waist circumference (and their interaction), body fat, and diabetes. The receiver operating characteristic curves for functional impairment indices were plotted to compare the usefulness of the frailty accepted and adjusted models.

Results

The prevalence of frailty and pre-frailty in this cohort were 7/50 (14%) and 27/50 (54%), respectively, but unwanted weight loss was seen in three subjects (6%) only. The level of abdominal obesity had the strongest correlation with functional score (r=0.292, P<0.05). Frailty models which included either severe abdominal obesity or diabetes in lieu of unwanted weight loss had good sensitivity rates per each frailty score as compared with the original Fried model.

Conclusion

For detecting and/or screening for the frailty syndrome in obese young elderly, the level of abdominal obesity or diabetes may provide a useful marker.

Overweight Without Central Obesity, Cardiovascular Risk, and All-Cause Mortality

OBJECTIVE

To assess the association of overweight without central obesity with risks of mortality.

PATIENTS AND METHODS

We included 14,299 participants in the Third National Health and Nutrition Examination Survey (from October 18, 1988, through October 15, 1994). According to their body mass index and waist circumference, participants were categorized into 7 anthropometric groups. Logistic regression models were used to assess the relation of cardiovascular risk factors (hypertension, diabetes, or hypercholesterolemia) and 10-year cardiovascular risk to anthropometric groups. Cox proportional hazards models were used to assess the risk of all-cause mortality, and competing-risks regression models were used for calculating cardiovascular and noncardiovascular mortality.

RESULTS

Compared with those with normal body mass index and waist circumference, overweight men without central obesity were more likely to have all 3 cardiovascular risk factors and a high cardiovascular risk, whereas women in this anthropometric group were more likely to have hypercholesterolemia. In proportional hazards models, overweight without central obesity was associated with lower all-cause mortality among men in the population with cardiovascular risk factors (hazard ratio, 0.71; 95% CI, 0.56-0.89; P=.004) and the general population (hazard ratio, 0.72; 95% CI, 0.60-0.87; P=.001), whereas results of these comparisons among women were not significant (P>.05). In competing risk analyses, overweight men without central obesity had a lower risk of noncardiovascular mortality, but not cardiovascular mortality.

CONCLUSION

Although overweight without central obesity was associated with cardiovascular risk factors and a high cardiovascular risk among men, men in this anthropometric group had a lower mortality risk.

Nutritional Status and Nutritional Treatment Are Related to Outcomes and Mortality in Older Adults with Hip Fracture

Malnutrition is very prevalent in geriatric patients with hip fracture. Nevertheless, its importance is not fully recognized. The objective of this paper is to review the impact of malnutrition and of nutritional treatment upon outcomes and mortality in older people with hip fracture. We searched the PubMed database for studies evaluating nutritional aspects in people aged 70 years and over with hip fracture. The total number of studies included in the review was 44, which analyzed 26,281 subjects (73.5% women, 83.6 ± 7.2 years old). Older people with hip fracture presented an inadequate nutrient intake for their requirements, which caused deterioration in their already compromised nutritional status. The prevalence of malnutrition was approximately 18.7% using the Mini-Nutritional Assessment (MNA) (large or short form) as a diagnostic tool, but the prevalence was greater (45.7%) if different criteria were used (such as Body Mass Index (BMI), weight loss, or albumin concentration). Low scores in anthropometric indices were associated with a higher prevalence of complications during hospitalization and with a worse functional recovery. Despite improvements in the treatment of geriatric patients with hip fracture, mortality was still unacceptably high (30% within 1 year and up to 40% within 3 years). Malnutrition was associated with an increase in mortality. Nutritional intervention was cost effective and was associated with an improvement in nutritional status and a greater functional recovery. To conclude, in older people, the prevention of malnutrition and an early nutritional intervention can improve recovery following a hip fracture.

Relation of Disease with Standardized Phase Angle among Older Patients

BACKGROUND

A low phase angle (PA) has been associated with negative outcome in specific diseases. However, many patients suffer from several co-morbidities. This study aims at identifying the impact of the type and the severity of diseases on PA in a retrospective cohort study of older people.

METHODS

We included all people ≥65 years who underwent a PA measurement (Nutriguard®) between 1990 and 2011 at the Geneva University Hospitals. PA was standardized for gender, age and body mass index according to German reference values. Co-morbidities were reported in form of the Cumulative Illness Rating Scale which considers 14 different organs/systems (disease categories), each rated from 0 (healthy) to 4 (severe illness) (severity grades). The association between the diseases categories and standardized PA was evaluated by a multivariate linear regression. For each significant disease category, we performed univariate regression models. The adjusted R2 was used to identify the best predictors of standardized PA. We considered that the severity grade affected standardized PA if there was a progressive decrease in the regression coefficients.

RESULTS

We included 1181 people (37% women). The multivariate regression model showed that the disease categories explain 17% of the variance of standardized PA. Many disease categories affect standardized PA and the ones best associated with standardized PA were the hematopoietic and vascular (R2 7.4%), the musculo-skeletal (R2 5.5%) and the respiratory (R2 4.0%) diseases. The regression coefficients in the univariate linear regression model decreased progressively with higher severity grades in respiratory (-0.15, -0.27, -0.55, -0.67) and musculo-skeletal diseases (-0.09, -0.46, -0.85, -0.86).

CONCLUSIONS

Many different diseases affect standardized PA. The higher the severity grade in musculo-skeletal and respiratory diseases, the lower is the standardized PA.

Association of mortality and phase angle measured by different bioelectrical impedance analysis (BIA) devices

PURPOSE

A high phase angle measured by the Nutriguard^® bioelectrical impedance analysis device is associated with a reduced mortality risk in older people. This retrospective study aims to analyze whether this association persists with the other devices that have been used in our hospital.

METHODS

This study encompasses all people 65 yrs and older who underwent a phase angle measurement between 1990 and 2011 at the Geneva University Hospitals, with the RJL-101^® (RJL Systems), Xitron 4000B^® (Xitron Technologies), Eugedia^® (Eugédia-Spengler) and Bio-Z^® (Spengler). Diseases at the time of phase angle measurement were reported in the form of the Cumulative Illness Rating Scale. Date of death was retrieved until December 2012. Phase angle values were categorized into sex- and device-specific quartiles, where quartile 1 represents the lowest quartile and reference value. Cox regressions were performed to evaluate the association between phase angle quartiles and mortality.

RESULTS

We considered 1878 people (969 women), of whom 1151 had died. In univariate sex-specific Cox regressions, the death risk decreased progressively as the phase angle quartile measured by the Bio-Z^® or RJL-101^® increased. The HR (95% CI) in quartile 4 was 0.36 (0.26, 0.50) and 0.38 (0.29, 052) in women and men measured with the Bio-Z^® (both p < 0.001), and 0.23 (0.14, 0.39) and 0.19 (0.10, 0.36) in women and men measured with the RJL-101^® (both p < 0.001). The association between phase angle and mortality persisted when adjusted for age, body mass index or co-morbidities. The small number of deaths in people who underwent a measurement by Eugedia^® (n = 93) or Xitron 4000B^® (n = 56) did not allow performing multivariate Cox regressions.

CONCLUSIONS

Phase angle quartiles are associated with mortality in people aged ≥65 years when using the RJL-101^® or Bio-Z device^®.

Association of Dynamics in Lean and Fat Mass Measures with Mortality in Frail Older Women

OBJECTIVE

The relationship between body composition and mortality in frail older people is unclear. We used dual-x-ray absorptiometry (DXA) data to examine the association between dynamics in whole-body composition and appendicular (4 limbs) and central (trunk) compartments and all-cause mortality in frail older women.

DESIGN

Prospective study with up to 19 years of follow up.

SETTING

Community dwelling older (≥65) women.

PARTICIPANTS

876 frail older participants of the Women's Health Initiative Observational Study with a single measure of body composition and 581 participants with two measures.

MEASUREMENTS

Frailty was determined using modified Fried's criteria. All-cause mortality hazard was modeled as a function of static (single-occasion) or dynamic changes (difference between two time points) in body composition using Cox regression.

RESULTS

Analyses adjusted for age, ethnicity, income, smoking, cardiovascular disease, diabetes, stroke, number of frailty criteria and whole-body lean mass showed progressively decreased rates of mortality in women with higher appendicular fat mass (FM) (P for trend=0.01), higher trunk FM (P for trend=0.03) and higher whole-body FM (P for trend=0.01). The hazard rate ratio for participants with more than a 5% decline in FM between two time points was 1.91; 1.67 and 1.71 for appendicular, trunk and whole-body compartment respectively as compared to women with relatively stable adiposity (p<0.05 for all). Dynamics of more than 5% in lean mass were not associated with mortality.

CONCLUSION

Low body fat or a pronounced decline in adiposity is associated with increased risks of mortality in frail older women. These results indicate a need to re-evaluate healthy weight in persons with frailty. .

Prevalence of low muscle mass according to body mass index in older adults

OBJECTIVE

Low muscle mass has been associated with increased morbi-mortality and should be identified for optimizing preventive and therapeutic strategies. This study evaluates the prevalence of bioelectrical impedance analysis (BIA)-derived low muscle mass in older persons using definitions found through a systematic literature search and determines the link between body mass index (BMI) and low muscle mass.

METHODS

We performed a systematic search of trials involving ≥100 persons that derived low muscle mass from BIA and reported cut-offs for low muscle mass normalized for body height or weight. These cut-offs were applied to all adults ≥65 y who underwent a BIA measurement at Geneva University Hospital between 1990 and 2011 (N = 3181). The association between BMI and low muscle mass was evaluated through multivariate logistic regressions.

RESULTS

We identified 15 cut-offs based on the fat-free mass index (FFMI), skeletal muscle index (SMI), or skeletal muscle percentage (SMP). Depending on the definition, the prevalence of low muscle mass was 17% to 68% in women and 17% to 85% in men. The risk of low muscle mass increased with a BMI <18.5 kg/m² when using cut-offs based on FFMI (odds ratio [OR] ♀ 14.28-24.04/♂ 25.42-50.64) or SMI (OR ♀ 3.56-4.56/♂ 7.07-8.87) and decreased with a BMI ≥25 kg/m² (FFMI: OR ♀ 0.03-0.04/♂ 0.01-0.04; SMI: OR ♀ 0.18-0.25/♂ 0.14-0.18). The opposite association appeared between BMI and cut-offs based on SMP.

CONCLUSION

The prevalence of low muscle mass varies widely depending on the definition, especially in persons with BMI <18.5 or ≥25 kg/m².

BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants

OBJECTIVE

To conduct a systematic review and meta-analysis of cohort studies of body mass index (BMI) and the risk of all cause mortality, and to clarify the shape and the nadir of the dose-response curve, and the influence on the results of confounding from smoking, weight loss associated with disease, and preclinical disease.

DATA SOURCES

PubMed and Embase databases searched up to 23 September 2015.

STUDY SELECTION

Cohort studies that reported adjusted risk estimates for at least three categories of BMI in relation to all cause mortality.

DATA SYNTHESIS

Summary relative risks were calculated with random effects models. Non-linear associations were explored with fractional polynomial models.

RESULTS

230 cohort studies (207 publications) were included. The analysis of never smokers included 53 cohort studies (44 risk estimates) with >738 144 deaths and >9 976 077 participants. The analysis of all participants included 228 cohort studies (198 risk estimates) with >3 744 722 deaths among 30 233 329 participants. The summary relative risk for a 5 unit increment in BMI was 1.18 (95% confidence interval 1.15 to 1.21; I(2)=95%, n=44) among never smokers, 1.21 (1.18 to 1.25; I(2)=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33; I(2)=89%, n=11) among healthy never smokers with exclusion of early follow-up, and 1.05 (1.04 to 1.07; I(2)=97%, n=198) among all participants. There was a J shaped dose-response relation in never smokers (Pnon-linearity <0.001), and the lowest risk was observed at BMI 23-24 in never smokers, 22-23 in healthy never smokers, and 20-22 in studies of never smokers with ≥20 years' follow-up. In contrast there was a U shaped association between BMI and mortality in analyses with a greater potential for bias including all participants, current, former, or ever smokers, and in studies with a short duration of follow-up (<5 years or <10 years), or with moderate study quality scores.

CONCLUSION

Overweight and obesity is associated with increased risk of all cause mortality and the nadir of the curve was observed at BMI 23-24 among never smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of follow-up. The increased risk of mortality observed in underweight people could at least partly be caused by residual confounding from prediagnostic disease. Lack of exclusion of ever smokers, people with prevalent and preclinical disease, and early follow-up could bias the results towards a more U shaped association.