Changes in Body Composition Are Associated with Metabolic Changes and the Risk of Metabolic Syndrome

Association of changes in predicted body composition with subsequent risk of dementia

OBJECTIVE

The effect of body composition change on the risk of dementia is not clear. This study analyzed the associations of changes in predicted lean body mass index (pLBMI), predicted appendicular skeletal muscle mass index (pASMI), and predicted body fat mass index (pBFMI) with the risk of dementia.

METHODS

In this nationwide cohort study, data were obtained from the Korean National Health Insurance Service database. The exposure was defined as changes in pLBMI, pASMI, and pBFMI derived from validated prediction equations. The outcome was dementia, defined based on the dementia diagnosis with prescription of anti-dementia medication. Cox proportional hazards regression analyses were performed to obtain the hazard ratio with a 95% confidence interval for risk of dementia according to changes in predicted body composition.

RESULTS

A total of 13,215,208 individuals with no prior record of dementia who underwent health screenings twice between 2009-2010 and 2011-2012 were included. A 1-kg/m2 increase in pLBMI and pASMI had an association with reduced risk of dementia (aHR: 0.85, 95% CI 0.84-0.87; aHR: 0.70, 95% CI 0.69-0.72, respectively for men, and aHR: 0.69, 95% CI 0.67-0.71; aHR: 0.59, 95% CI 0.57-0.61, respectively for women). A 1-kg/m2 increase in pBFMI had an association with a raised risk of dementia (aHR: 1.19, 95% CI 1.17-1.21 for men and aHR: 1.53, 95% CI 1.48-1.57 for women). These results remained consistent regardless of sex or weight change.

INTERPRETATION

Increase in pLBMI or pASMI, or reduction in pBFMI was linked to lower risk of dementia.

Association between body composition and subsequent cardiovascular diseases among 5-year breast cancer survivors

BACKGROUND AND AIMS

Cardiovascular disease (CVD) remain one of the leading causes of mortality in breast cancer survivors. This study aimed to investigate the association between body composition and subsequent CVD in breast cancer survivors.

METHODS AND RESULTS

A retrospective cohort study of more than 70 thousand 5-year breast cancer survivors aged 40 years or older was conducted using data from the National Health Insurance Service of South Korea. Based on the percentage of predicted lean body mass (pLBMP), appendicular skeletal muscle mass (pASMP), and body fat mass (pBFMP), which were calculated using prediction equations with anthropometric data and health habits, groups were equally divided into quartiles. The risk of CVD was evaluated using multivariate Cox proportional hazards regression. Compared to those with the lowest pLBMP and pASMP, those with the highest pLBMP and pASMP had a 38% and 42% lower risk of CVD, respectively. In contrast, those with the highest pBFMP had a 57% higher risk of CVD compared to those with the lowest pBFMP. Each 1 % increase in pLBMP and pASMP was associated with a decreased risk of CVD [pLBMP, adjusted hazard ratio (aHR): 0.96, 95% CI 0.94-0.98, p < 0.05; pASMP, aHR: 0.91, 95% CI 0.87-0.95, p < 0.05] while each 1 % increase in pBFMP was associated with the increased risk of CVD (aHR: 1.05, 95% CI 1.03-1.07, p < 0.01).

CONCLUSION

In this cohort study, a high pLBMP, a high pASMP, and a low pBFMP were associated with a lower risk of CVD.

Effects of different resistance training programmings on the relative strength, body composition, anthropometric variables, and metabolic risk of elderly women

The purpose of this study was to analyze the effect of two different programming models of resistance training (RT) on metabolic risk, anthropometric variables, and relative strength in elderly women. The research was a prospective and comparative longitudinal study with a non-probabilistic random sample. Twenty-two elderly women (64 ± 3 years) was divided into two experimental groups being the Linear programming (LP, n = 12) and Daily undulatory programming (DUP, n = 10), with 3 sessions/week for 12 weeks. Submaximal strength (10RM) was evaluated in the horizontal leg press (HL), pulldown (PD), leg curl (LC), vertical bench press (BP), and leg extension (LE). Anthropometric variables, food intake (R24h) and submaximal strength (10RM) was analyzed. Participants were initially classified as overweight or obese evaluated by body mass index (BMI) and percentual of fat mass (%FM) and with moderate to high risk to develop metabolic diseases evaluated by hip-waist ratio (HWR), waist-height ratio (WHR) and waist circumference (WC). There is no change for metabolic risk and anthropometric variables after the intervention period. There was a significant improvement for relative strength accessed by 10RM and body weight (10RM/BW), and lean body mass (10RM/LBM) (p < 0.05), with large or medium effect size for most of variables after 12 weeks of RT. As a conclusion, both programmings increased relative strength after 12 weeks of RT with attenuated change in body composition and metabolic risk in elderly women in both programming groups and all those strategies can be used in elderly women to improve strength.

Deep learning imaging phenotype can classify metabolic syndrome and is predictive of cardiometabolic disorders

BACKGROUND

Cardiometabolic disorders pose significant health risks globally. Metabolic syndrome, characterized by a cluster of potentially reversible metabolic abnormalities, is a known risk factor for these disorders. Early detection and intervention for individuals with metabolic abnormalities can help mitigate the risk of developing more serious cardiometabolic conditions. This study aimed to develop an image-derived phenotype (IDP) for metabolic abnormality from unenhanced abdominal computed tomography (CT) scans using deep learning. We used this IDP to classify individuals with metabolic syndrome and predict future occurrence of cardiometabolic disorders.

METHODS

A multi-stage deep learning approach was used to extract the IDP from the liver region of unenhanced abdominal CT scans. In a cohort of over 2,000 individuals the IDP was used to classify individuals with metabolic syndrome. In a subset of over 1,300 individuals, the IDP was used to predict future occurrence of hypertension, type II diabetes, and fatty liver disease.

RESULTS

For metabolic syndrome (MetS) classification, we compared the performance of the proposed IDP to liver attenuation and visceral adipose tissue area (VAT). The proposed IDP showed the strongest performance (AUC 0.82) compared to attenuation (AUC 0.70) and VAT (AUC 0.80). For disease prediction, we compared the performance of the IDP to baseline MetS diagnosis. The models including the IDP outperformed MetS for type II diabetes (AUCs 0.91 and 0.90) and fatty liver disease (AUCs 0.67 and 0.62) prediction and performed comparably for hypertension prediction (AUCs of 0.77).

CONCLUSIONS

This study demonstrated the superior performance of a deep learning IDP compared to traditional radiomic features to classify individuals with metabolic syndrome. Additionally, the IDP outperformed the clinical definition of metabolic syndrome in predicting future morbidities. Our findings underscore the utility of data-driven imaging phenotypes as valuable tools in the assessment and management of metabolic syndrome and cardiometabolic disorders.

Four-years change of BMI and waist circumference are associated with metabolic syndrome in middle-aged and elderly Chinese

The purpose of the study was to determine whether changes in body mass index (BMI) and waist circumference (WC) in middle-aged and elderly Chinese are associated with metabolic syndrome. In this cohort investigation, 3697 middle-aged and elderly people aged 45 or over were recruited from the China Health and Retirement Longitudinal Study (CHARLS). The National Cholesterol Education Program Adult Treatment Panel III (2005) defined metabolic syndrome (MetS). With Cox regression analysis, we calculated hazard ratio (HR) and 95% confidence intervals (CIs) for MetS based on BMI-WC change categories. To assess the prevalence of MetS, the changes in BMI and WC levels were classified into four quartiles based on their relative and absolute changes. In subjects whose BMI and WC decreased (HR = 0.338; 95% CIs 0.264, 0.433) as well as those whose BMI increased and their WC decreased (HR = 0.375; 95% CIs 0.228, 0.499), metabolic syndrome risk was significantly lower compared with those with increases in both BMI and WC. Regarding the absolute changes in BMI, the lowest percentile of BMI was significantly lower in both males (HR = 0.302; 95% CIs 0.204, 0.448) and females (HR = 0.486; 95% CIs 0.354, 0.667) for the risk of metabolic syndrome. Similar results were observed in the absolute changes in WC, with the lowest quantile of WC having a significant impact on MetS risk in males (HR = 0.170; 95% CIs 0.107, 0.270) and females (HR = 0.303; 95% CIs 0.217, 0.424). The risk of metabolic syndrome was significantly associated with changes in BMI and WC in middle-aged and elderly Chinese. A reduced BMI and WC are associated with lower metabolic syndrome risks in middle-aged and elderly people.

The Effect of Resistance Training with Outdoor Fitness Equipment on the Body Composition, Physical Fitness, and Physical Health of Middle-Aged and Older Adults: A Randomized Controlled Trial

This study examined the effect of outdoor-fitness-equipment-based resistance training on the health parameters of middle-aged and older adults, as well as analyzing the effect of age on the results found. A total of 149 volunteers were randomly assigned to the training (TG) and control (CG) groups. The TG performed two weekly sessions of resistance training for 8 weeks using outdoor fitness equipment, while the CG continued with their regular daily activities. Body composition was measured using DXA, and the maximal isometric voluntary contraction in knee extension, elbow flexion, and hand grip were assessed, along with the 4 m walk test, the Timed Up and Go Test, and the Short Form 36 Health Survey Questionnaire. The TG showed a significant increase in the lean mass index (p = 0.002) and maximal isometric voluntary contraction in both legs (p < 0.001) and arms (p < 0.001), as well as in physical functioning (p < 0.001) and the role physical dimension (p = 0.006) of the Short Form 36 Health Survey Questionnaire, compared to the CG, which showed a decrease in all these variables. In addition, the TG showed a greater decrease in fat mass (p < 0.001), fat mass index (p = 0.003), and the Timed Up and Go Test (p < 0.001) than the CG. Age conditioned the evolution of most of the variables analyzed (p < 0.05). In conclusion, resistance training with outdoor fitness equipment may be useful for improving the health of middle-aged and older adults, although age is a factor that could influence the adaptations found.

Muscle mass and chronic dizziness: a cross-sectional study of a Korean population

BACKGROUND AND OBJECTIVES

Weight gain is associated with imbalance in older people. In contrast, overweightness or mild obesity is less common in patients with chronic dizziness. This paradox may be, at least in part, related to differences in the body composition indices adopted in the previous studies. This study aimed to determine any association between the predicted body composition and chronic dizziness or imbalance of unknown causes.

METHODS

We measured the lean body mass, body fat mass, and appendicular skeletal mass in 9243 people who participated in the Korean National Health and Nutrition Examination Survey 2019-2021. Sarcopenia was defined according to the Asian Working Group for Sarcopenia's guidelines. Obesity was defined as a body fat percentage of ≥ 25% for men and ≥ 35% for women.

RESULTS

The participants with chronic dizziness had a lower body mass index than those without (p = 0.001). Furthermore, sarcopenia was more common in those with chronic dizziness. In contrast, the degree of obesity was comparable in both groups. Multiple logistic regression analysis showed that sarcopenia was associated with a higher risk of chronic dizziness (odds ratio = 1.6, 95% confidence interval: 1.1-2.5; p = 0.026).

DISCUSSION

Given the association of sarcopenia with chronic dizziness or imbalance, muscle mass may play a role in maintaining balance and stability. Physical exercise could be recommended to increase muscle mass in patients with chronic dizziness/imbalance and sarcopenia. Additional research is required to establish a causal relationship between chronic dizziness and sarcopenia.

Risk of Obesity and Unhealthy Central Adiposity in Adolescents Born Preterm With Very Low Birthweight Compared to Term-Born Peers

Background: Early-life factors such as preterm birth or very low birthweight (VLBW) are associated with increased cardiovascular disease risk. However, it remains unknown whether this is due to an increased risk of obesity (unhealthy central adiposity) because studies have predominantly defined obesity based on BMI, an imprecise adiposity measure. Objective: Investigate if adolescents born preterm with VLBW have a higher risk of unhealthy central adiposity compared to term-born peers. Study Design: Cross-sectional analysis of data from a prospective cohort study of 177 individuals born preterm with VLBW (<1500 g) and 51 term-born peers (birthweight ≥2500 g). Individuals with congenital anomalies, genetic syndromes, or major health conditions were excluded. Height, weight, waist circumference, skin fold thickness, and dual energy X-ray absorptiometry body composition were measured at age 14 years. We calculated BMI percentiles and defined overweight/obesity as BMI ≥85th percentile for age and sex. We estimated the preterm-term differences in overweight/obesity prevalence and adiposity distribution with multivariable generalized linear models. Results: There was no difference in small for gestational age status or overweight/obesity prevalence. Compared to term, youth born preterm with VLBW had lower BMI z-score [β -0.38, 95% confidence limits (CL) -0.75 to -0.02] but no differences in adiposity apart from subscapular-to-triceps ratio (STR; β 0.18, 95% CL 0.08 to 0.28). Conclusions: Adolescents born preterm with VLBW had smaller body size than their term-born peers and had no differences in central adiposity except greater STR.

Relationships between Circulating Biomarkers and Body Composition Parameters in Patients with Metabolic Syndrome: A Community-Based Study

Metabolic syndrome (MetS) is a complex disease involving multiple physiological, biochemical, and metabolic abnormalities. The search for reliable biomarkers may help to better elucidate its pathogenesis and develop new preventive and therapeutic strategies. In the present population-based study, we looked for biomarkers of MetS among obesity- and inflammation-related circulating factors and body composition parameters in 1079 individuals (with age range between 18 and 80) belonging to an ethnically homogeneous population. Plasma levels of soluble markers were measured by using ELISA. Body composition parameters were assessed using bioimpedance analysis (BIA). Statistical analysis, including mixed-effects regression, with MetS as a dependent variable, revealed that the most significant independent variables were mainly adipose tissue-related phenotypes, including fat mass/weight (FM/WT) [OR (95% CI)], 2.77 (2.01-3.81); leptin/adiponectin ratio (L/A ratio), 1.50 (1.23-1.83); growth and differentiation factor 15 (GDF-15) levels, 1.32 (1.08-1.62); inflammatory markers, specifically monocyte to high-density lipoprotein cholesterol ratio (MHR), 2.53 (2.00-3.15), and a few others. Additive Bayesian network modeling suggests that age, sex, MHR, and FM/WT are directly associated with MetS and probably affect its manifestation. Additionally, MetS may be causing the GDF-15 and L/A ratio. Our novel findings suggest the existence of complex, age-related, and possibly hierarchical relationships between MetS and factors associated with obesity.

Relationship between Body Composition and Gait Characteristics in Patients with Cerebral Small Vessel Disease

BACKGROUND

This study aims to explore the correlation between body composition, encompassing factors such as muscle mass and fat distribution, and gait performance during both single-task walking (STW) and dual-task walking (DTW) in patients diagnosed with cerebral small vessel disease (CSVD).

METHODS

The data of hospitalized patients diagnosed with CSVD, including cadence, stride time, velocity and stride length, as well as information on variability, asymmetry and coordination during both STW and DTW, were assessed. The number of falls reported by each participant was also assessed.

RESULTS

A total of 95 CSVD patients were assessed, and the results showed that individuals with low appendicular skeletal muscle mass (ASM), which includes both the low ASM group and the combination of low ASM and high body fat (BF) group, had reduced velocity or cadence, shortened stride length, and prolonged stride time across all walking modalities compared to the control group. Only the combination of the low ASM and high BF group exhibited a deterioration in the coefficient of variation (CV) for all basic parameters and the Phase Coordination Index (PCI) compared to the control group across all walking patterns. Conversely, patients in the high BF group displayed a decline in basic parameters, primarily during cognitive DTW. Concurrently, the high BF group showed a significant increase in the CV and the PCI compared to the control group only during cognitive DTW. Furthermore, regardless of gender, both ASM and BF independently correlated with the occurrence of falls.

CONCLUSIONS

CSVD patients with varying body compositions could allocate different levels of attention to their daily walking routines.

The dynamic nexus: exploring the interplay of BMI before, during, and after pregnancy with Metabolic Syndrome (MetS) risk in Chinese lactating women

BACKGROUND AND AIM

The health implications of BMI and MetS in lactating women are significant. This study aims to investigate the relationship between risk of Mets in lactation and BMI in four stages: pre-pregnancy, prenatal period, 42 days postpartum, and current lactation.

METHODS AND RESULTS

A total of 1870 Lactating Women within 2 years after delivery were included from "China Child and Lactating Mother Nutrition Health Surveillance (2016-2017)". Logistic regression model and Restricted cubic spline (RCS) were used to estimate the relationship between BMI and risk of MetS. ROC analysis was used to determine the threshold for the risk of MetS. Chain mediating effect analysis was used to verify the mediating effect. BMI of MetS group in all stages were higher than non-MetS group (P < 0.0001). There were significant positive correlations between BMI in each stage and ORs of MetS during lactation (P < 0.05). The best cut-off values for BMI in the four stages were 23.47, 30.49, 26.04 and 25.47 kg/m2. The non-linear spline test at BMI in 42 days postpartum, current and MetS in lactation was statistically significant (P non-linear = 0.0223, 0.0003). The mediation effect of all chains have to work through lactation BMI. The total indirect effect accounted for 80.95% of the total effect.

CONCLUSIONS

The risk of MetS in lactating women is due to a high BMI base before pregnancy and postpartum. High BMI in all stages of pregnancy and postpartum were risk factors for MetS in lactation. BMI during lactation plays a key role in the risk of MetS.

Associations between eating behaviors and metabolic syndrome severity in young adults

Metabolic syndrome (MetS), a precursor to cardiovascular disease and type II diabetes, is rapidly increasing in young adults. Accordingly, earlier interventions aimed at combating the onset of MetS in young adults are required. However, current behavioral interventions have failed to consider the eating behaviors that precede disease development, likely contributing to the consistently high failure rates of these interventions. The purpose of this cross-sectional study was to evaluate the associations between eating behaviors and MetS severity (MetSindex) in a sample of young adults. A sample of 104 (non-Hispanic White: 45; non-Hispanic Black: 49; Hispanic White: 5; Asian: 5) young adult (age: 23.1 ± 4.4) males and females (F:61, M:43) completed anthropometric, blood pressure, blood glucose, and blood lipid assessments; each of which were used to calculate a continuous MetSindex score. Participants also completed the revised version of the 18-item Three-factor Eating Questionnaire to measure emotional eating (EmE), uncontrolled eating (UE), and cognitive restraint (CR). EmE was positively associated with MetSindex for young adult females (p = 0.033) and non-Hispanic Black participants (p = 0.050), but not male (p = 0.506) or non-Hispanic White participants (p = 0.558). Additionally, MetSindex was greater in the highest EmE tertile compared to the lowest EmE tertile for the total sample (p = 0.037) and young adult females (p = 0.015). UE and CR were not associated with MetSindex. These data suggest a potential link between EmE and MetS severity in young adults, and that behavioral interventions aimed at MetS prevention should focus on treating the underlying EmE behaviors common in young adults, particularly for young female and Black adults at the greatest risk.

Changes in body composition and subsequent cardiovascular disease risk among 5-year breast cancer survivors

Introduction

Cardiovascular disease (CVD) remains a leading cause of death in breast cancer survivors, a growing population. The aim of this study was to determine whether changes in body composition, commonly observed in breast cancer survivors, is associated with subsequent CVD risk.

Methods

This cohort study used the Korean National Health Insurance Service database. The study population included 73,271 5-year breast cancer survivors aged 40 years or above. To assess changes in body composition and its effect on the risk of CVD, validated prediction equations and multivariate Cox proportional hazards regression were used. Changes in metabolic markers (blood pressure, total cholesterol, and fasting serum glucose) according to changes in body composition were calculated by multiple linear regression.

Results

Having persistently high predicted lean body and appendicular skeletal muscle mass percentages (LBMP and ASMP, respectively) among breast cancer survivors was associated with 32% and 40% lower CVD risks than a persistently low predicted LBMP or ASMP, respectively. Conversely, persistently high predicted body fat mass percentage (BFMP) was associated with a higher CVD risk than persistently low predicted BFMP. Additionally, those with a low to high change in predicted BFMP had a higher risk of CVD than those with persistently low predicted BFMP. Changes in body composition were accompanied by changes in metabolic markers.

Discussion

Maintaining high percentages of lean body and appendicular skeletal muscle mass and preventing an increase in fat mass may be beneficial in preventing CVD in breast cancer survivors.

Association of the amount of alcohol consumption with change in skeletal muscle and fat mass among Korean adults

The association between changes in alcohol consumption and body composition remains unclear. We investigated the association between changes in drinking habits and muscle mass and fat mass in adults. From the Health Examinees in Korea, the study population (N = 62 094) was categorized according to alcohol consumption (g of ethanol/day) and the changes in drinking habits between the baseline and follow-up periods were determined. Predicted muscle mass index (pMM), lean mass index, and fat mass index (pFM) were also calculated using age, sex, weight, height, and waist circumference. The β coefficient and adjusted means were then calculated using multiple linear regression analysis after adjusting for covariates, including follow-up duration, calorie intake, and protein intake. Compared to the almost-unchanged drinking group (reference; adjusted mean: -0.030 [95% confidence intervals: -0.048, -0.011]), there was no statistical difference or tendency of change in the pMMs of the most-decreased (-0.024 [-0.048, 0.000]) and the most-increased (-0.027 [-0.059, -0.013]) alcohol-consumed groups. The pFM decreased at those with less alcohol consumption (0.053 [-0.011, 0.119]) and increased with increased alcohol consumption (0.125 [0.063, 0.187]), compared to the no-change group (reference; 0.088 [0.036, 0.140]). Thus, changes in alcohol consumption were not significantly associated with changes in muscle mass. Increased alcohol consumption was associated with increased fat mass. Reducing the amount of alcohol consumption may improve body composition in terms of fat mass.

Metabolic Flexibility and Inflexibility: Pathology Underlying Metabolism Dysfunction

Metabolic flexibility can be defined as the ability of the skeletal muscle to adjust its utilization of substrate pathways [...].

The paradox of obesity with normal weight; a cross-sectional study

Objective

To evaluate the prevalence of excessive adiposity among normal-weight individuals, and their cardiometabolic risk.

Methods

This cross-sectional study included 3,001 participants (ages 20-95, 52% men, BMI 28.0 ± 5.5 kg/m²) who completed an anthropometric evaluation, dual x-ray absorptiometry (DXA) scan to measure body composition, and cardiometabolic blood markers. Excess adiposity was defined as ≥25% for men and ≥ 35% for women.

Results

Of the entire study participants, 967 were in normal BMI (18.5-24.9 kg/m²) with a wide body fat distribution (4-49%). Of them, 26% of men and 38% of women were classified with excess adiposity. As compared to normal-weight lean participants, normal-weight obese men and women had higher triglycerides (76.5 ± 37.3 vs. 101.2 ± 50.3 mg/dL, p = 0.004 and 84 ± 44.2 vs. 101.4 ± 91.1 mg/dL, p = 0.030; respectively) and elevated low-density lipoprotein cholesterol (103.3 ± 31.7 vs. 119.6 ± 45.5 mg/dL, p = 0.011) and total cholesterol (171.5 ± 40.3 vs. 190.2 ± 39 mg/dL, p = 0.007) for men only. Among NWO, abdominal circumference was prevalent in 60% of the females with NWO (≥88 cm), but only in 4% of males (≥102 cm).

Conclusion

Higher adiposity, even within normal weight, increases cardiometabolic risk, and abdominal waist circumference misclassified obesity in normal-weight individuals. This study highlights the need for a body composition evaluation to determine cardiometabolic risk for adults with normal body weight.

Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation

Metabolic health is increasingly implicated as a risk factor across conditions from cardiology to neurology, and efficiency assessment of body composition is critical to quantitatively characterizing these relationships. 2D low dose single slice computed tomography (CT) provides a high resolution, quantitative tissue map, albeit with a limited field of view. Although numerous potential analyses have been proposed in quantifying image context, there has been no comprehensive study for low-dose single slice CT longitudinal variability with automated segmentation. We studied a total of 1816 slices from 1469 subjects of Baltimore Longitudinal Study on Aging (BLSA) abdominal dataset using supervised deep learning-based segmentation and unsupervised clustering method. 300 out of 1469 subjects that have two year gap in their first two scans were pick out to evaluate longitudinal variability with measurements including intraclass correlation coefficient (ICC) and coefficient of variation (CV) in terms of tissues/organs size and mean intensity. We showed that our segmentation methods are stable in longitudinal settings with Dice ranged from 0.821 to 0.962 for thirteen target abdominal tissues structures. We observed high variability in most organ with ICC<0.5, low variability in the area of muscle, abdominal wall, fat and body mask with average ICC≥0.8. We found that the variability in organ is highly related to the cross-sectional position of the 2D slice. Our efforts pave quantitative exploration and quality control to reduce uncertainties in longitudinal analysis.

Epidemiological, mechanistic, and practical bases for assessment of cardiorespiratory fitness and muscle status in adults in healthcare settings

Given their importance in predicting clinical outcomes, cardiorespiratory fitness (CRF) and muscle status can be considered new vital signs. However, they are not routinely evaluated in healthcare settings. Here, we present a comprehensive review of the epidemiological, mechanistic, and practical bases of the evaluation of CRF and muscle status in adults in primary healthcare settings. We highlight the importance of CRF and muscle status as predictors of morbidity and mortality, focusing on their association with cardiovascular and metabolic outcomes. Notably, adults in the best quartile of CRF and muscle status have as low as one-fourth the risk of developing some of the most common chronic metabolic and cardiovascular diseases than those in the poorest quartile. The physiological mechanisms that underlie these epidemiological associations are addressed. These mechanisms include the fact that both CRF and muscle status reflect an integrative response to the body function. Indeed, muscle plays an active role in the development of many diseases by regulating the body's metabolic rate and releasing myokines, which modulate metabolic and cardiovascular functions. We also go over the most relevant techniques for assessing peak oxygen uptake as a surrogate of CRF and muscle strength, mass, and quality as surrogates of muscle status in adults. Finally, a clinical case of a middle-aged adult is discussed to integrate and summarize the practical aspects of the information presented throughout. Their clinical importance, the ease with which we can assess CRF and muscle status using affordable techniques, and the availability of reference values, justify their routine evaluation in adults across primary healthcare settings.

Do Body Composition and Values of Selected Nutritional Status Indices Influence the Glycaemic Index Values of Vegetarian Dishes? A Pilot Study in a Group of Older Women

An ageing population brings with it the need for public policy to respond to the demands and health needs of this group of people. The ageing process has been shown to be associated with changes in body composition. These mainly concern a decrease in muscle mass and an increase in body fat. Body composition and other indicators of nutritional status are important factors differentiating carbohydrate management. Glycaemic index (GI) values may be affected by differences resulting from individual metabolism. The rate of carbohydrate digestion is also influenced by a number of factors, including the degree to which the product is processed, the structure of the starch, and the presence of protein, fat and dietary fibre. Available studies do not provide information on the glycaemic response following the consumption of specific products by older people with varying BMI and body composition. Therefore, the aim of this study was to evaluate the effect of the body mass index (BMI) values of women aged 50-80 years on the glycaemic response after eating vegetarian meals and the influence of selected indices of nutritional status on their GI values. It has been shown that the areas under the glycaemic curves after the consumption of the tested foods, both traditional and modified, are higher in the group of overweight and obese women. Nevertheless, the GI of meals consumed by those with a BMI ≥ 25.0 kg/m² is lower than that of foods consumed by women with normal values of this index. In the group of women with BMI 18.5-24.9 kg/m², on the basis of an analysis of the obtained correlations, it was observed that the GI value of modified products depends on the percentage of body fat (FM%) (p = 0.0363) and the percentage of fat free mass (FFM%) (p = 0.0363), and, in the case of traditional products, also on the percentage of total body water (%) (p = 0.0133). In the group of women with a BMI ≥ 25.0 kg/m², significant correlations were only found between the GI of modified foods and the waist-to-hip ratio (WHR) (p = 0.0363) and the ratio of waist circumference to height (WHtR) (p = 0.0369) indices. The GI values of food set solely with the participation of young, healthy people should not be the basis for the nutrition planning of all groups of people.

Three-dimensional optical body shape and features improve prediction of metabolic disease risk in a diverse sample of adults

OBJECTIVE

This study examined whether body shape and composition obtained by three-dimensional optical (3DO) scanning improved the prediction of metabolic syndrome (MetS) prevalence compared with BMI and demographics.

METHODS

A diverse ambulatory adult population underwent whole-body 3DO scanning, blood tests, manual anthropometrics, and blood pressure assessment in the Shape Up! Adults study. MetS prevalence was evaluated based on 2005 National Cholesterol Education Program criteria, and prediction of MetS involved logistic regression to assess (1) BMI, (2) demographics-adjusted BMI, (3) 85 3DO anthropometry and body composition measures, and (4) BMI + 3DO + demographics models. Receiver operating characteristic area under the curve (AUC) values were generated for each predictive model.

RESULTS

A total of 501 participants (280 female) were recruited, with 87 meeting the criteria for MetS. Compared with the BMI model (AUC = 0.819), inclusion of age, sex, and race increased the AUC to 0.861, and inclusion of 3DO measures further increased the AUC to 0.917. The overall integrated discrimination improvement between the 3DO + demographics and the BMI model was 0.290 (p < 0.0001) with a net reclassification improvement of 0.214 (p < 0.0001).

CONCLUSIONS

Body shape measures from an accessible 3DO scan, adjusted for demographics, predicted MetS better than demographics and/or BMI alone. Risk classification in this population increased by 29% when using 3DO scanning.

Changes in predicted lean body mass, appendicular skeletal muscle mass, and body fat mass and cardiovascular disease

BACKGROUND

Little is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.

METHODS

This nationwide, population-based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20-39 years without a previous history of CVD who underwent two health screening examinations during 2009-2010 and 2011-2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.

RESULTS

The mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person-years of follow-up. Each 1 kg/m² increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82-0.91; aHR: 0.76, 95% CI 0.69-0.82, respectively] and women (aHR: 0.77, 95% CI 0.63-0.95; aHR: 0.75, 95% CI 0.59-0.96). Each 1 kg/m² increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10-1.22) and women (aHR: 1.32, 95% CI 1.06-1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between -1 and +1 kg/m² also had a decreased risk of CVD per 1 kg/m² increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80-0.92; aHR: 0.85, 95% CI 0.76-0.95) and women (aHR: 0.62, 95% CI 0.47-0.83; aHR: 0.59, 95% CI 0.44-0.80) and had a greater risk of CVD per 1 kg/m² increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10-1.25) and women (aHR: 1.64, 95% CI 1.20-2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.

CONCLUSIONS

Among young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.

Impact of training modes on fitness and body composition in women with obesity: A systematic review and meta-analysis

OBJECTIVE

This study aimed to assess the effectiveness of different exercise modalities and determine the optimal exercise prescription for improving cardiorespiratory fitness, body composition, and metabolic health of women with obesity.

METHODS

A systematic review of randomized controlled trials (RCTs) published between January 1988 and October 2020 was conducted. The RCTs were screened using the following inclusion criteria: 1) participants: women aged 18 to 65 years with BMI > 30 kg/m² and without comorbidities; 2) intervention: exercise; 3) comparison: non-intervention control; and 4) outcomes measures: cardiorespiratory fitness (maximal oxygen consumption), body composition (i.e., body weight, percentage body fat), and/or metabolic measures (i.e., blood pressure, cholesterol).

RESULTS

A total of 20 RCTs with a total of 2,062 participants were included. Although the results showed that any form of exercise was more effective than control, improvements in fitness and body composition were modest. Aerobic exercise (vigorous and moderate intensity) appeared most promising for improving fitness and body weight, whereas low-load resistance training resulted in the largest improvements in body fatness.

CONCLUSIONS

In women living with obesity, aerobic exercise was consistently effective in improving fitness and body composition. Although both resistance training and combined exercise interventions appear promising, more research is needed to evaluate their efficacy and determine an optimal exercise prescription for this population.