Comparability and utility of body composition measurement vs. anthropometric measurement for assessing obesity related health risks in Korean men

Relationship between body fat ratio and inflammatory markers in a Chinese population of adult male smokers

Objective

To explore the correlation between changes in the body fat ratio (BFR) and peripheral blood inflammatory markers according to smoking status in the adult Chinese male population.

Methods

A total of 865 participants (aged 20-70 years) were included. All participants underwent a physical health examination at Xiguzhou Central Hospital between October 2015 and July 2016, including measurements of body mass index (BMI), BFR, white blood cell [WBC] count, and neutrophil-lymphocyte ratio [NLR].

Results

WBCs count and NLR were significantly higher in adult male smokers than in non-smokers (P = 0.00). According to the BFR stratification analysis, WBC count and NLR significantly increased in accordance with BFR (P = 0.00). This finding remained significant after adjusting for relevant confounding factors (P < 0.05). Two-factor stratified analysis of smoking status and BFR showed that WBC count and NLR in the smoking population were higher than in nonsmokers, regardless of BFR. The interaction model showed that BFR and smoking status affected WBC count and NLR changes (P < 0.05). A significant positive correlation was found between WBC count, NLR, and BFR in adult male smokers; however, there was no significant correlation with BMI. There was an interaction between smoking and BFR, both of which synergistically affected changes in inflammatory markers, including WBC count and NLR.

Conclusion

WBC count and NLR of smokers with a high BFR were significantly higher than those of nonsmokers with a low BFR. It is important to provide evidence-based medical evidence for social tobacco control and to reduce BFR.

Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study

Background

There is an increasing trend of Metabolic syndrome (MetS) prevalence, which has been considered as an important contributor for cardiovascular disease (CVD), cancers and diabetes. However, there is often a long asymptomatic phase of MetS, resulting in not diagnosed and intervened so timely as needed. It would be very helpful to explore tools to predict the probability of suffering from MetS in daily life or routinely clinical practice.

Objective

To develop models that predict individuals' probability of suffering from MetS timely with high efficacy in general population.

Methods

The present study enrolled 8964 individuals aged 40-75 years without severe diseases, which was a part of the REACTION study from October 2011 to February 2012. We developed three prediction models for different scenarios in hospital (Model 1, 2) or at home (Model 3) based on LightGBM (LGBM) technique and corresponding logistic regression (LR) models were also constructed for comparison. Model 1 included variables of laboratory tests, lifestyles and anthropometric measurements while model 2 was built with components of MetS excluded based on model 1, and model 3 was constructed with blood biochemical indexes removed based on model 2. Additionally, we also investigated the strength of association between the predictive factors and MetS, as well as that between the predictors and each component of MetS.

Results

In this study, 2714 (30.3%) participants suffer from MetS accordingly. The performances of the LGBM models in predicting the probability of suffering from MetS produced good results and were presented as follows: model 1 had an area under the curve (AUC) value of 0.993 while model 2 indicated an AUC value of 0.885. Model 3 had an AUC value of 0.859, which is close to that of model 2. The AUC values of LR model 1 and 2 for the scenario in hospital and model 3 at home were 0.938, 0.839 and 0.820 respectively, which seemed lower than that of their corresponding machine learning models, respectively. In both LGBM and logistic models, gender, height and resting pulse rate (RPR) were predictors for MetS. Women had higher risk of MetS than men (OR 8.84, CI: 6.70-11.66), and each 1-cm increase in height indicated 3.8% higher risk of suffering from MetS in people over 58 years, whereas each 1- Beat Per Minute (bpm) increase in RPR showed 1.0% higher risk in individuals younger than 62 years.

Conclusion

The present study showed that the prediction models developed by machine learning demonstrated effective in evaluating the probability of suffering from MetS, and presented prominent predicting efficacies and accuracies. Additionally, we found that women showed a higher risk of MetS than men, and height in individuals over 58 years was important factor in predicting the probability of suffering from MetS while RPR was of vital importance in people aged 40-62 years.

Associations of eating speed with fat distribution and body shape vary in different age groups and obesity status

Background

Eating speed has been reported to be associated with energy intake, body weight, waist circumference (WC), and total body fat. However, no study has explored the association between eating speed and body fat distribution, especially its difference among different age or body mass index (BMI) groups.

Methods

4770 participants aged 18–80 years were recruited from the baseline survey of the Lanxi Cohort Study. They were categorized into three groups according to meal duration. Linear regression analyses were performed among all participants and separately by age group and obesity status to evaluate the associations of WC and total and regional fat mass percentages (FM%) with eating speed.

Results

After adjusting for confounding factors, eating slowly was significantly related to lower WC, lower total, trunk, and android FM%, lower android-to-gynoid fat mass ratio, and higher leg and gynoid FM%. After stratification by age or obesity status, the associations were especially prominent among participants aged 18–44 years or those with BMI < 24 kg/m². No significant trends were found for participants aged 65–80 years or those who were overweight/obese.

Conclusions

Eating slowly is closely related with better fat distribution among Chinese adults, especially for those aged 18–44 years and those with BMI < 24 kg/m². If confirmed prospectively, it might be a potential efficient approach to improve fat distribution.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12986-022-00698-w.

Cardiometabolic Profile of Different Body Composition Phenotypes in Children

CONTEXT

Cardiometabolic profiles of different body composition phenotypes are poorly characterized in young children, where it is well established that high adiposity is unfavorable, but the role of lean mass is unclear.

OBJECTIVE

We hypothesized that higher lean mass attenuates cardiometabolic risk in children with high fat mass.

METHODS

In 6-year-old children (n = 377) from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) prospective birth cohort, whole-body composition was measured by quantitative magnetic resonance, a novel validated technology. Based on fat mass index (FMI) and lean mass index (LMI), 4 body composition phenotypes were derived: low FMI-low LMI (LF-LL), low FMI-high LMI (LF-HL), high FMI-low LMI (HF-LL), high FMI-high LMI (HF-HL).

MAIN OUTCOME MEASURES

Body mass index (BMI) z-score, fasting plasma glucose, insulin resistance, metabolic syndrome risk score, fatty liver index, and blood pressure.

RESULTS

Compared with the LF-HL group, children in both high FMI groups had increased BMI z-score (HF-HL: 1.43 units 95% CI [1.11,1.76]; HF-LL: 0.61 units [0.25,0.96]) and metabolic syndrome risk score (HF-HL: 1.64 [0.77,2.50]; HF-LL: 1.28 [0.34,2.21]). The HF-HL group also had increased fatty liver index (1.15 [0.54,1.77]). Girls in HF-HL group had lower fasting plasma glucose (-0.29 mmol/L [-0.55,-0.04]) and diastolic blood pressure (-3.22 mmHg [-6.03,-0.41]) than girls in the HF-LL group. No similar associations were observed in boys.

CONCLUSION

In a multi-ethnic Asian cohort, lean mass seemed to protect against some cardiometabolic risk markers linked with adiposity, but only in girls. The FMI seemed more important than lean mass index in relation to cardiometabolic profiles of young children.

Using open source accelerometer analysis to assess physical activity and sedentary behaviour in overweight and obese adults

Background

Physical activity and sedentary behaviour are difficult to assess in overweight and obese adults. However, the use of open-source, raw accelerometer data analysis could overcome this. This study compared raw accelerometer and questionnaire-assessed moderate-to-vigorous physical activity (MVPA), walking and sedentary behaviour in normal, overweight and obese adults, and determined the effect of using different methods to categorise overweight and obesity, namely body mass index (BMI), bioelectrical impedance analysis (BIA) and waist-to-hip ratio (WHR).

Methods

One hundred twenty adults, aged 24–60 years, wore a raw, tri-axial accelerometer (Actigraph GT3X+), for 3 days and completed a physical activity questionnaire (IPAQ-S). We used open-source accelerometer analyses to estimate MVPA, walking and sedentary behaviour from a single raw accelerometer signal. Accelerometer and questionnaire-assessed measures were compared in normal, overweight and obese adults categorised using BMI, BIA and WHR.

Results

Relationships between accelerometer and questionnaire-assessed MVPA (Rs = 0.30 to 0.48) and walking (Rs = 0.43 to 0.58) were stronger in normal and overweight groups whilst sedentary behaviour were modest (Rs = 0.22 to 0.38) in normal, overweight and obese groups. The use of WHR resulted in stronger agreement between the questionnaire and accelerometer than BMI and BIA. Finally, accelerometer data showed stronger associations with BMI, BIA and WHR (Rs = 0.40 to 0.77) than questionnaire data (Rs = 0.24 to 0.37).

Conclusions

Open-source, raw accelerometer data analysis can be used to estimate MVPA, walking and sedentary behaviour from a single acceleration signal in normal, overweight and obese adults. Our data supports the use of WHR to categorise overweight and obese adults. This evidence helps researchers obtain more accurate measures of physical activity and sedentary behaviour in overweight and obese populations.

Optimal Cutoff Points for Anthropometric Variables to Predict Insulin Resistance in Polycystic Ovary Syndrome

BACKGROUND

Insulin resistance (IR) is a major cardiometabolic risk factor in females with polycystic ovary syndrome (PCOS). The euglycemic clamp is the gold standard method to measure IR. However, considering the time and cost that it takes, surrogate markers of IR are now widely used. The current study aimed at evaluating the cutoff points of even less invasive anthropometric and body composition variables to predict IR in females with PCOS.

METHODS

The current cross sectional study selected 224 females with PCOS, using Rotterdam criteria, referred to reproductive endocrinology research center; 88 of which were diagnosed with insulin resistance. Receiver operating characteristics curve was used to explore the best cutoff values of each anthropometric and body composition measures. IR was defined as homeostasis model assessment formula greater or equal to 2.6: HOMA-IR = fasting insulin (mU/L) × fasting plasma glucose (mM/L)/22.5.

RESULTS

The highest area under the curve (0.751) was for the multiplication of waist circumference (WC) by body mass index (BMI), as a single index. The highest sensitivity and specificity were for body water (BW) percentage (82% for values greater than 32.85%) and WC (79% for values greater than 88 cm), respectively.

CONCLUSIONS

It was concluded that there were simple anthropometric variables; e.g., WC × BMI, percentage of BW, and WC that could help to estimate IR in clinical settings especially when the gold standard or surrogate markers of IR were unavailable.

Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students

High body fat is related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF%) and fat mass index (FMI) for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years). Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA) and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC) analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC), sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001). BF% and FMI were positively correlated to MetS components (p < 0.05). ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m² in men, and 38.95% and 11.86 kg/m² in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes’ thresholds seem to be good tools to identify university students with unfavorable metabolic profiles.

Definition of new cut-offs of BMI and waist circumference based on body composition and insulin resistance: differences between children, adolescents and adults

Objective

This study aims to determine associations between anthropometric traits, regional fat depots and insulin resistance in children, adolescents and adults to define new cut‐offs of body mass index (BMI) or waist circumference (WC).

Design

Cross‐sectional data were assessed in 433 children, adolescents and adults (aged: 6–60 years, BMI: 23.6 [21.0–27.7] kg m⁻²). Total adipose tissue (TAT), regional subcutaneous adipose tissue (SAT_total, SAT_trunk) and visceral adipose tissue (VAT) were determined by whole‐body magnetic resonance imaging, fat mass by air‐displacement plethysmography. Insulin resistance was evaluated by homeostasis model assessment of insulin resistance (HOMA‐IR). Bivariate as well as partial correlations and regression analyses were used. Cut‐off values of BMI and WC related to regional fat depots and HOMA‐IR were analysed by receiver operating characteristics curve.

Results

In adults, TAT, SAT_total and SAT_trunk increased linearly with increasing BMI and WC, whereas they followed a cubic function in children and adolescents with a steep increase at BMI and WC ≥1 standard deviation score and VAT at WC ≥2 standard deviation score. Sex differences were apparent in adults with women having higher masses of TAT and SAT and men having higher VAT. Using established BMI or WC cut‐offs, correspondent masses of TAT, SAT_total, SAT_trunk and VAT increased from childhood to adulthood. In all age groups, there were positive associations between BMI, WC, SAT_trunk, VAT and HOMA‐IR. When compared with normative cut‐offs of BMI or WC, HOMA‐IR‐derived cut‐offs of regional fat depots were lower in all age groups.

Conclusions

Associations between BMI, WC and regional fat depots varied between children, adolescents, young and older adults. When compared with BMI‐derived and WC‐derived values, an insulin resistance‐derived cut‐off corresponded to lower masses of regional fat depots. Thus, established BMI and WC cut‐offs are not appropriate to assess metabolic disturbances associated with obesity; therefore, new cut‐offs of BMI and WC are needed for clinical practice.

Relation between metabolic syndrome and body compositions among Chinese adolescents and adults from a large-scale population survey

Background

Few nationally representative surveys regarding body composition and metabolic syndrome (MetS) have been done in a large-scale representative Chinese population to explore the prediction of body composition indicators for MetS. The objective of this study was to examine the relation of body composition and MetS and to determine the optimal cut-off values of body composition indicators that predict MetS in a large representative Chinese sample based on multiple provinces and ethnicities, covering a broad age range from 10 to 80 years old.

Methods

The subjects came from a large-scale population survey on Chinese physiological constants and health conditions conducted in six provinces. 32,036 subjects completed all blood biochemical testing and body composition measure. Subjects meeting at least 3 of the following 5 criteria qualify as having MetS: elevated blood pressure, lower high density lipoprotein cholesterol level, higher triglyceride level, higher fasting glucose level and abdominal obesity.

Results

The total prevalence rate of MetS for males (9.29%) was lower than for females (11.58%). The prevalence rates were 12.03% for male adults and 15.57% for female adults respectively. The risk of MetS increased 44.6% (OR = 1.446, 95%CI: 1.414–1.521) for males and 53.4% (OR = 1.534, 95%CI: 1.472–1.598) for females with each 5% increase of percentage of body fat. The risk of MetS increased two-fold (OR = 2.020, 95%CI: 1.920–2.125 for males; OR = 2.047, 95%CI: 1.954–2.144 for females respectively) with each 5% increase of waist-hip ratio. The risk of MetS increased three-fold (OR = 2.915, 95%CI: 2.742–3.099 for males; OR = 2.950, 95%CI: 2.784–3.127 for females respectively) with each 5% increase of Waist-to-Height Ratio (WHtR). Areas under the receiver operating curve (AUC) of most body composition indicators were larger than 0.70 and the sensitivities and the specificities of most cut-off values were larger than 0.65. AUCs of WHR and WHtR were the largest. The optimal cut-off values of WHtR were 0.51 for males and 0.53 for females.

Conclusion

MetS has become a serious public health challenge in China. Body composition variables were closely related to MetS and they were reliable indicators in the screening of the presence of MetS.

Waist-to-Height Ratio as an Indicator of High Blood Pressure in Urban Indian School Children

OBJECTIVE

To examine the utility of waist-to-height ratio to identify risk of high blood pressure when compared to body mass index and waist circumference in South Indian urban school children.

DESIGN

Secondary data analysis from a cross-sectional study.

SETTING

Urban schools around Bangalore, India.

PARTICIPANTS

1913 children (58.1% males) aged 6-16 years with no prior history of chronic illness (PEACH study).

METHODS

Height, weight, waist circumference and of blood pressure were measured. Children with blood pressure ?90th percentile of age-, sex-, and height-adjusted standards were labelled as having high blood pressure.

RESULTS

13.9% had a high waist-to-height ratio, 15.1% were overweight /obese and 21.7% had high waist circumference. High obesity indicators were associated with an increased risk of high blood pressure. The adjusted risk ratios (95% CI) of high systolic blood pressure with waist-to-height ratio, body mass index and waist circumference were 2.48 (1.76, 3.47), 2.59 (1.66, 4.04) and 2.38 (1.74, 3.26), respectively. Similar results were seen with high diastolic blood pressure.

CONCLUSION

Obesity indicators, especially waist-to-height ratio due to its ease of measurement, can be useful initial screening tools for risk of high blood pressure in urban Indian school children.

Comparison of waist to height ratio and body indices for prediction of metabolic disturbances in the Korean population: the Korean National Health and Nutrition Examination Survey 2008-2011

BACKGROUND

The aim of the present study of the general population was to identify the best predictor of metabolic risk among the body index variables evaluated with dual-energy X-ray absorptiometry (DEXA) or anthropometric indices including the waist to height ratio (WHtR).

PATIENTS AND METHODS

Data from the Korean National Health and Nutrition Examination Survey 2008-2011 were used for the analyses. As a result, 15,965 participants were included in this study. The body mass (BM) index was calculated as the body weight divided by the height squared. The WHtR was calculated as the waist circumference divided by height. Body composition indices such as lean mass (LM), fat mass (FM), trunk fat mass (TFM), and bone mineral content (BMC) were determined by using DEXA. Skeletal muscle mass (SM) was defined as the sum of the lean soft masses of both extremities. The LM, FM, BMC, TFM, and SM indices were calculated by dividing the total LM, total FM, total BMC, TFM, or SM by the height squared.

RESULTS

The WHtR had the highest area under the curve (AUC) and was the best predictor of metabolic syndrome for both sexes. In addition, the WHtR had the highest AUCs for components of metabolic syndrome (male: AUC 0.823, 95 % confidence interval [CI] 0.814-0.832; female: AUC 0.870, 95 % CI 0.863-0.877). There was a small statistically significant difference in AUC between WHtR and the other indices. Multivariate logistic regression showed that male participants in the second, third, and fourth quartiles had a 4.0 (95 % CI, 3.1-5.2), 9.6 (95 % CI, 7.5-12.3), and 36.1 (95 % CI, 28.0-46.4) times increased risk of metabolic syndrome compared with patients in the first quartile and female participants in the second, third, and fourth quartiles had a 4.3 (95 % CI, 3.1-6.0), 18.0 (95 % CI, 13.3-24.5), and 58.5 (95 % CI, 42.9-79.9) times increased risk of metabolic syndrome compared with patients in the first quartile.

CONCLUSION

Among the BM, FM, LM, SM, TFM, and WHtR indices, WHtR is most useful to predict the presence of metabolic syndrome and insulin resistance in the Korean population.

Associations of the uric acid related genetic variants in SLC2A9 and ABCG2 loci with coronary heart disease risk

Background

Multiple studies investigated the associations between serum uric acid and coronary heart disease (CHD) risk. However, further investigations still remain to be carried out to determine whether there exists a causal relationship between them. We aim to explore the associations between genetic variants in uric acid related loci of SLC2A9 and ABCG2 and CHD risk in a Chinese population.

Results

A case–control study including 1,146 CHD cases and 1,146 controls was conducted. Association analysis between two uric acid related variants (SNP rs11722228 in SLC2A9 and rs4148152 in ABCG2) and CHD risk was performed by logistic regression model. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Compared with subjects with A allele of rs4148152, those with G allele had a decreased CHD risk and the association remained significant in a multivariate model. However, it altered to null when BMI was added into the model. No significant association was observed between rs11722228 and CHD risk. The distribution of CHD risk factors was not significantly different among different genotypes of both SNPs. Among subjects who did not consume alcohol, the G allele of rs4148152 showed a moderate protective effect. However, no significant interactions were observed between SNP by CHD risk factors on CHD risk.

Conclusions

There might be no association between the two uric acid related SNPs with CHD risk. Further studies were warranted to validate these results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0162-7) contains supplementary material, which is available to authorized users.

Cut-Off Values of Visceral Adiposity to Predict NAFLD in Brazilian Obese Adolescents

Objectives. The present study aimed at determining cut-off points of visceral fat to predict NAFLD and analyzed metabolic disorders of obese adolescents. Methods. Cross-sectional study involved 165 obese adolescents ranged in age from 15 to 19 years. Glycemia, hepatic transaminases, lipid profile, and insulin resistance were analyzed. Visceral and subcutaneous fat were measured by ultrasound and body composition by plesthysmography. Results. The NAFLD adolescents had significantly higher values for body mass, BMI-for-age, BMI, total fat, waist circumference, and visceral fat when compared with non-NAFLD obese adolescents in both genders. Moreover, there were significant positive correlations between visceral fat with the variables BMI-for-age (r = 0.325,), TG (r = 0.277), AST (r = 0.509), ALT (r = 0.519), WC (r = 0.390), and visceral/subcutaneous ratio (r = 0.790) for NAFLD group. Total fat, triglycerides, and visceral fat were the independent predictors to NAFLD. Analysis of the ROC curves revealed cut-off points of visceral fat of 4.47 cm for girls and 4.21 cm for boys. Conclusions. The results may suggest that abdominal ultrasonography procedure may be a safe alternative method of assessing visceral adiposity aiming to be considered to the development of preventive and treatment strategies in obese individuals. This clinial trial is registered with ClinicalTrial.gov (NCT01358773).

The utility of fat mass index vs. body mass index and percentage of body fat in the screening of metabolic syndrome

Background

It has been well documented that obesity is closely associated with metabolic syndrome (MetS). Although body mass index (BMI) is the most frequently used method to assess overweightness and obesity, this method has been criticized because BMI does not always reflect true body fatness, which may be better evaluated by assessment of body fat and fat-free mass. The objective of this study was to investigate the best indicator to predict the presence of MetS among fat mass index, BMI and percentage of body fat (BF %) and determine its optimal cut-off value in the screening of MetS in practice.

Methods

A cross-sectional study of 1698 subjects (aged 20–79 years) who participated in the annual health check-ups was employed. Body composition was measured by bioelectrical impedance analysis (BIA). Fat mass index (FMI) was calculated. Sex-specific FMI quartiles were defined as follows: Q1: <4.39, Q2:4.39- < 5.65, Q3:5.65- < 7.03, Q4:≥7.03,in men; and Q1:<5.25, Q2:5.25- < 6.33, Q3:6.33- < 7.93,Q4:≥7.93, in women. MetS was defined by National Cholesterol Education Program/Adult Treatment Panel III criteria. The association between FMI quartiles and MetS was assessed using Binary logistic regression. Receiver operating curve(ROC) analysis was used to determine optimal cutoff points for BMI,BF% and FMI in relation to the area under the curve(AUC),sensitivity and specificity in men and women.

Results

The adjusted odds ratios (95% CI) for the presence of MetS in the highest FMI quartile versus lowest quartile were 79.143(21.243-294.852) for men( P < 0.01) and 52.039(4.144-653.436) for women( P < 0.01) after adjusting age, BMI, BF%, TC, LDL, CRP, smoking status and exercise status, and the odds ratios were 9.166(2.157-38.952) for men( P < 0.01) and 25.574(1.945-336.228) for women( P < 0.05) when WC was also added into the adjustment. It was determined that BMI values of 27.45 and 23.85 kg/m², BF% of 23.95% and 31.35% and FMI of 7.00 and 7.90 kg/m² were the optimal cutoff values to predict the presence of MetS among men and women according to the ROC curve analysis. Among the indicators used to predict MetS, FMI was the index that showed the greatest area under the ROC curve in both sexes.

Conclusions

Higher FMI levels appear to be independently and positively associated with the presence of MetS regardless of BMI and BF%. FMI seems to be a better screening tool in prediction of the presence of metabolic syndrome than BMI and percentage of body fat in men and women.