Body Fat Measurements in Singaporean Adults Using Four Methods

Impact of COVID-19 lockdown on health parameters and muscle strength of older women: A longitudinal study

OBJETIVES

The present study aimed to evaluate the effect of a 13-week COVID-19 lockdown on health-related parameters in women aged 60-70 years.

STUDY DESIGN

Thirty women participated in this longitudinal study. All the assessments were performed before and 13 weeks after the initial phase of the COVID-19 pandemic in Spain (March to June 2020).

MAIN OUTCOME MEASURES

A sociodemographic questionnaire was provided, and tests were performed to assess muscle strength, anthropometric measurements, densitometry, blood pressure, blood parameters, Mediterranean diet adherence, and physical activity levels.

RESULTS

After the lockdown, both healthy and unhealthy lifestyle groups showed a significant worsening of HDL, cholesterol/HDL lipids, and isometric knee extension strength parameters. However, individuals with an unhealthy lifestyle also showed a significant worsening in LDL lipids, Non-HDL lipids, bone mineral density of the femoral neck, fat mass/height (%), truncal fat mass (absolute and percentage), total fat mass (absolute and percentage) and handgrip strength.

CONCLUSIONS

The COVID-19 pandemic had a negative impact on the overall health status of Spanish older women, potentially increasing their susceptibility to comorbidities, such as lipid cholesterol, body fat, and decreased muscle strength.

Predicted fat mass and lean mass in relation to all-cause and cause-specific mortality

BACKGROUND

Studies on the prospective association of body composition with mortality in US general populations are limited. We aimed to examine this association by utilizing data from the National Health and Nutrition Examination Survey (NHANES), a representative sample of US adults, linked with data from the National Death Index.

METHODS

We analysed data of NHANES 1988-1994 and 1999-2014, with 55 818 participants [50.6% female, baseline mean age: 45.0 years (SE, 0.2)]. Predicted fat mass and lean mass were calculated using the validated sex-specific anthropometric prediction equations developed by the NHANES based on individual age, race, height, weight, and waist circumference. Body composition and other covariates were measured at only one time point. Multivariable Cox regression was used to investigate the associations of predicted fat mass and lean mass with overall and cause-specific mortality, adjusting for potential confounders. Interactions between age and body composition on mortality were examined with likelihood ratio testing.

RESULTS

Mean predicted fat mass was 24.1 kg [95% confidence interval (CI): 23.9-24.3) for male participants and 29.9 kg (95% CI: 29.6-30.1) for female participants, while mean predicted lean mass was 59.3 kg (95% CI: 59.1-59.5) for male participants and 41.7 kg (95% CI: 41.5-41.8) for female participants. During a median period of 9.7 years from the survey, 10 408 deaths occurred. When predicted fat and lean mass were both included in the model, predicted fat mass showed a U-shaped association with all-cause mortality, with significantly higher risk at two ends: Quintile 1 (HR, 1.17; 95% CI: 1.05-1.31), Quintile 2 (HR, 1.14; 95% CI: 1.04-1.26) and Quintile 5 (HR, 1.37; 95% CI: 1.12-1.68) compared with Quintile 3. In contrast, predicted lean mass showed a L-shaped association with all-cause mortality, with higher mortality in those with lower lean mass: Quintile 1 (HR, 1.64; 95% CI: 1.46-1.83) and Quintile 2 (HR, 1.29; 95% CI: 1.18-1.42) compared with Quintile 3. Similar results were found for cardiovascular, cancer, and respiratory cause-specific mortality. Age was a significant modifier: There was a monotonic positive association of predicted fat mass with mortality in younger participants (<60 years), but an approximate J-shaped association in older participants (≥60 years) (P interaction <0.001); there was a stronger inverse association between predicted lean mass and mortality in older participants (≥60) compared with those <60 years (P interaction <0.001).

CONCLUSIONS

In this US general population, predicted fat mass and lean mass were independent predictors for overall and cause-specific mortality. Age was a significant modifier on the associations.

The validation of contemporary body composition methods in various races and ethnicities

Few investigations have evaluated the validity of current body composition technology among racially and ethnically diverse populations. This study assessed the validity of common body composition methods in a multi-ethnic sample stratified by race and ethnicity. One hundred and ten individuals (55 % female, age: 26·5 (sd 6·9) years) identifying as Asian, African American/Black, Caucasian/White, Hispanic, Multi-racial and Native American were enrolled. Seven body composition models (dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), two bioelectrical impedance devices (BIS, IB) and three multi-compartment models) were evaluated against a four-compartment criterion model by assessing total error (TE) and standard error of the estimate. For the total sample, measures of % fat and fat-free mass (FFM) from multi-compartment models were all excellent to ideal (% fat: TE = 0·94-2·37 %; FFM: TE = 0·72-1·78 kg) compared with the criterion. % fat measures were very good to excellent for DXA, ADP and IB (TE = 2·52-2·89 %) and fairly good for BIS (TE = 4·12 %). For FFM, single device estimates were good (BIS; TE = 3·12 kg) to ideal (DXA, ADP, IB; TE = 1·21-2·15 kg). Results did not vary meaningfully between each race and ethnicity, except BIS was not valid for African American/Black, Caucasian/White and Multi-racial participants for % fat (TE = 4·3-4·9 %). The multi-compartment models evaluated can be utilised in a multi-ethnic sample and in each individual race and ethnicity to obtain highly valid results for % fat and FFM. Estimates from DXA, ADP and IB were also valid. The BIS may demonstrate greater TE for all racial and ethnic cohorts and results should be interpreted cautiously.

Validity of Body-Composition Methods across Racial and Ethnic Populations

Multi-compartment body-composition models that divide the body into its multiple constituents are the criterion method for measuring body fat percentage, fat mass, and fat-free mass. However, 2- and 3-compartment body-composition devices such as air displacement plethysmography (ADP), DXA, and bioelectrical impedance devices [bioelectrical impedance analysis (BIA)] are more commonly used. Accurate measures depend on several assumptions, including constant hydration, body proportion, fat-free body density, and population characteristics. Investigations evaluating body composition in racial and ethnic minorities have observed differences in the aforementioned components between cohorts. Consequently, for racial/ethnic minority populations, estimates of body composition may not be valid. The purpose of this review was to comprehensively examine the validity of common body-composition devices in multi-ethnic samples (samples including >1 race/ethnicity) and in African-American, Hispanic, Asian, and Native American populations. Based on the literature, DXA produces valid results in multi-ethnic samples and ADP is valid for Hispanic and African American males when utilizing race-specific equations. However, for DXA and ADP, there is a need for validity investigations that include larger, more racially diverse samples, specifically including Hispanic/Latinx, Asian, Native American adults, and African-American females. Technology has advanced significantly since initial validity studies were conducted; therefore, conclusions are based on outdated models and software. For BIA, body-composition measures may be valid in a multi-ethnic sample, but the literature demonstrates disparate results between races/ethnicities. For BIA and ADP, the majority of studies have utilized DXA or hydrostatic weighing as the criterion to determine validity; additional studies utilizing a multi-compartment model criterion are essential to evaluate accuracy. Validity studies evaluating more recent technology in larger, more racially/ethnically diverse samples may improve our ability to select the appropriate method to accurately assess body composition in each racial/ethnic population.

Development of Fatty Acid Reference Ranges and Relationship with Lipid Biomarkers in Middle-Aged Healthy Singaporean Men and Women

Dietary fatty acids (FA) are essential for overall human health, yet individual FA reference ranges have yet to be established. Developing individual FA reference ranges can provide context to reported concentrations and whether an individual displays deficient, or excess amounts of FA. Reference ranges of sixty-seven individual FA (μmol/L) were profiled and analyzed using gas chromatography with a flame ionization detector from serum samples collected from 476 middle-aged Singaporean males (BMI:23.3 ± 2.9) and females (BMI:21.8 ± 3.6). Measures of triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and total cholesterol (TC) (mmol/L) were also collected. The mean FA concentration seen in this cohort (11,458 ± 2478 was similar to that of overweight North American cohorts assessed in past studies. Ten biologically relevant FA were compared between sexes, with females exhibiting significantly higher concentrations in four FA (p < 0.05). A multiple regression model revealed the ten FA contributed significantly to nearly all lipid biomarkers (p < 0.05). A majority of participants who had FA concentrations in the ≥95th percentile also exhibited TG, HDL, LDL, and TC levels in the “high” risk classification of developing cardiovascular disease. Future studies profiling individual FA reference ranges in many unique, global cohorts are necessary to develop cut-off values of individual FA concentrations highly related to disease-risk.

Association among Adherence to the Mediterranean Diet, Cardiorespiratory Fitness, Cardiovascular, Obesity, and Anthropometric Variables of Overweight and Obese Middle-Aged and Older Adults

The aim of this study was to evaluate the independent and combined associations between adherence to the Mediterranean diet (AMedDiet), cardiorespiratory fitness (CRF), and different parameters of overweight and obese middle-aged and older adults. Sixty-two participants were enrolled in this cross-sectional study. Fat mass was measured with Dual energy X-ray absorptiometry. AMedDiet and physical activity (PA) were assessed with the PREDIMED and Global PA Questionnaire (GPAQ). Maximal aerobic power was assessed using the 6-min walk test. Systolic (SBP) and diastolic (DBP) blood pressure (BP) were measured with Omron M6, and double product (DP) and mean BP (MBP) were calculated. Kinanthropometry proportionality variables related to obesity were also calculated. Participants with a low CRF as an independent factor or together with a low AMedDiet obtained significantly higher BP, total and trunk fat mass, and proportionality variables (all p ˂ 0.0001). According to the multiple nonlinear regression analysis, Vo2max, AMedDiet, and sex explained 53.4% of SBP, with this formula: 238.611 − (3.63*Vo2max) + (0.044*Vo2max²) − (13.051*AMedDiet) + (0.68*AMedDiet²) + (12.887*sex). SBP and p rediction SBP with the new formula showed a correlation of 0.731 (p ˂ 0.0001); showing a difference between the values of −0.278 (p = 0.883). In conclusion, CRF as an independent factor and combined with AMedDiet can be associated with BP, body composition, and proportionality in overweight and obese middle-aged and older adults.

Body mass index and waist-to-hip ratio misclassification of overweight and obesity in Chinese military personnel

BACKGROUND

The rising prevalence of obesity in military personnel has raised great concerns. Previous studies suggest that body mass index (BMI)- and waist-to-hip ratio (WHR)-based obesity classifications in US military personnel and firefighters have high false negative and subsequently cause obesity misclassification.

OBJECTIVE

To determine whether BMI and WHR could reflect the fat mass of Chinese military personnel.

METHODS

Three hundred fifty-three male Chinese military personnel and 380 age-matched male adults were recruited. Obesity classification was defined by BMI, WHR, and body fat percentage (BFP).

RESULTS

Chinese military personnel had extremely low obesity rate determined by either BFP (0.3%) or BMI (0.6%). By combining overweight and obese individuals, BMI- and WHR-determined prevalence of overweight/obesity was 22.4% and 17.0% compared to BFP-based standard (4.0%) (P < 0.05). In reference to BFP, BMI and WHR have high false-positive rate compared to the control group. Further analysis showed that Chinese military personnel consisted of high percentage of BFP^lowBMI^high and/or BFP^lowWHR^high subpopulations. Eighty-one percent of BMI^high and 78.3% of WHR^high of them were BFP low.

CONCLUSIONS

Chinese military personnel has extremely low obesity rate. BMI and WHR have high false-positive rates in reference to BFP, which cannot accurately reflect the mass of adipose tissue and leads to obesity misclassification.

Brown fat activity determined by infrared thermography and thermogenesis measurement using whole body calorimetry (BRIGHT Study)

To assess BAT activity in humans at a population level, infrared thermography (IRT) represents a safe, readily repeatable and affordable alternative to 18F-FDG-PET. Building upon a previously proposed method by our laboratory, we further refined the image computational algorithm to quantify BAT activation in the cervical-supraclavicular (C-SCV) region of healthy young men under thermo-neutral and cold exposure conditions. Additionally, we validated the whole-body calorimeter (WBC) in reliably measuring cold-induced thermogenesis. The temperature gradient between C-SCV-deltoid regions, and the corresponding difference in heat power output, increased upon cold air exposure relative to thermo-neutral conditions (by 74.88 %, p<0.0001; and by 71.34 %, p<0.0001 respectively). Resting and cumulative energy expenditure (EE) rose significantly (by 13.14 % and 9.12 % respectively, p=0.0001) while positive correlations between IRT measures and EE were found with cold air exposure (percentage change in heat power gradient between ROI and deltoid, cold air: r(2)=0.29, p=0.026, Pearson's correlation). IRT and WBC can be used to study BAT activation. The refined algorithm allows for more automation and objectivity in IRT data analysis, especially under cold air exposures.

Testing Bioimpedance to Estimate Body Fat Percentage across Different Hip and Waist Circumferences

Many studies have validated the use of bioimpedance analysis (BIA) to quantify body fat percentage (BF%). However, it is unknown if some model types (i.e., hand to hand, foot to foot, and hand to foot) are differing in their validity depending on hip and waist circumferences. The purpose of this study was to compare the difference in BF% between three BIA models (i.e., hand to hand, foot to foot, and hand to foot) against the Bod Pod across different hip and waist circumferences. A total of 92 people aged 19-72 years were recruited in this study. After following the pretesting procedures recommended for BIA measures, BF% was estimated using three BIA models and the Bod Pod. Hip and waist circumferences were obtained using standard procedures and tertiles were computed. The Bland-Altman was plotted and 1-sample T-test as well as correlation between the average measure and the difference between the two measures was tested. Within the entire sample, across all BIA models, the Bland-Altman analysis showed significant difference compared to 0 and a significant difference for the proportional. However, when stratified by tertiles, the two measurements were only significant for the highest tertiles of hip and waist for all BIA apparatus (all p <0.01) and the proportional bias was nonsignificant for all tertiles and across all BIA apparatus. For the highest tertile of waist and hip, the average difference was between 1.67% and 3.29% compared with the Bod Pod estimation. In conclusion, the three BIA models offer a BF% measurement agreeing with the estimation obtained with the Bod Pod with the exception of people having a greater waist or greater hip.

Development of an Easy-to-Use Visual Aid for the Prediction of Body Fat Based on Waist Circumference and Height in Asian Chinese Adults

BACKGROUND

Adiposity is a major risk factor for metabolic and cardiovascular diseases. Initial prediction equations to estimate adiposity are complex, requiring skinfold measurements that cannot be obtained conveniently by the general population.

OBJECTIVE

To develop simplified prediction equations to estimate body fat percentage (%BF) in Asian Chinese adults, evaluate the validity of the simplified %BF prediction equations, compare the simplified %BF prediction equations with an existing equation, and create visual charts to enable easy assessment of adiposity by the general public.

DESIGN

Simplified prediction equations were developed and evaluated for validity using anthropometric measurements obtained from a cross-sectional study.

PARTICIPANTS AND SETTING

Healthy participants with no major diseases and not taking long-term medications were recruited in a cross-sectional study conducted at Clinical Nutrition Research Centre, Singapore, between June 2014 and October 2017. A total of 439 participants were used for model building (269 women and 170 men) and another 107 participants were used for evaluating validity (62 women and 45 men).

MAIN OUTCOME MEASURES

Simplified but acceptable prediction models and generation of user-friendly charts.

STATISTICAL ANALYSES PERFORMED

Simplified sex-specific %BF prediction equations were developed using stepwise regression and the model-building dataset. The best models were selected using the Akaike information criterion. The models were further simplified and their performance was compared using the validation dataset before choosing the final prediction equations.

RESULTS

The final selected models for women and men included waist circumference and height with nonsignificant prediction bias in %BF of 0.84%±3.94% (P=0.098, Cohen's d_z=0.21) and -0.98%±3.65% (P=0.079, Cohen's d_z=0.27), respectively. The final equations were split into three height categories from which the sex-specific prediction charts were generated.

CONCLUSIONS

The sex-specific prediction charts provide a good visual guide for estimating %BF using height and waist circumference values that are easy to obtain by the general public.