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The Indian Journal of Medical Research Nov 2018Body composition is known to be associated with several diseases, such as cardiovascular disease, diabetes, cancers, osteoporosis and osteoarthritis. Body composition... (Review)
Review
Body composition is known to be associated with several diseases, such as cardiovascular disease, diabetes, cancers, osteoporosis and osteoarthritis. Body composition measurements are useful in assessing the effectiveness of nutritional interventions and monitoring the changes associated with growth and disease conditions. Changes in body composition occur when there is a mismatch between nutrient intake and requirement. Altered body composition is observed in conditions such as wasting and stunting when the nutritional intake may be inadequate. Overnutrition on the other hand leads to obesity. Many techniques are available for body composition assessment, which range from simple indirect measures to more sophisticated direct volumetric measurements. Some of the methods that are used today include anthropometry, tracer dilution, densitometry, dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis. The methods vary in their precision and accuracy. Imaging techniques such as nuclear magnetic resonance imaging and computed tomography have become powerful tools due to their ability of visualizing and quantifying tissues, organs, or constituents such as muscle and adipose tissue. However, these methods are still considered to be research tools due to their cost and complexity of use. This review was aimed to describe the commonly used methods for body composition analysis and provide a brief introduction on the latest techniques available.
Topics: Anthropometry; Body Composition; Body Weights and Measures; Dimensional Measurement Accuracy; Humans; Obesity
PubMed: 30666990
DOI: 10.4103/ijmr.IJMR_1777_18 -
Nutrients Aug 2019Anthropometry (from the Greek : human, and : measure) refers to the systematic collection and correlation of measurements of human individuals, including the systematic...
Anthropometry (from the Greek : human, and : measure) refers to the systematic collection and correlation of measurements of human individuals, including the systematic measurement of the physical characteristics of the human body, primarily body weight, body size, and shape [...].
Topics: Adiposity; Anthropometry; Basal Metabolism; Body Composition; Body Mass Index; Humans; Predictive Value of Tests; Reproducibility of Results
PubMed: 31416130
DOI: 10.3390/nu11081891 -
Roczniki Panstwowego Zakladu Higieny 2019Obesity is a global epidemic and belongs to major risk factors for the most prevalent diseases. Anthropometric measures are simple, inexpensive, non-invasive tools to... (Comparative Study)
Comparative Study
BACKGROUND
Obesity is a global epidemic and belongs to major risk factors for the most prevalent diseases. Anthropometric measures are simple, inexpensive, non-invasive tools to diagnosis obesity and to assess the risk of morbidity and mortality. The most widely used are body mass index (BMI), waist circumference (WC), waist-to-hip (WHR) and waist-to-height ratios, visceral fat area (VFA), body fat (BFP) and a new body shape index (ABSI).
OBJECTIVE
The aim of this study was to examine the usefulness of the ABSI in obesity diagnosis compared with other anthropometric parameters like WC, WHR, BMI, VFA, and BFP. We also compared the predictability between ABSI and above mentioned common anthropometric indices.
MATERIAL AND METHODS
The study group was composed of 236 university students. Body height, weight, WC was measured and BMI, WHR, ABSI and ABSI z-score were calculated. The anthropometric measurements were made by using InBody 720 (Biospace Co. Ltd., Seoul, Republic of Korea). Body composition, especially VFA, BFP, FFM was diagnosed by multifrequency bioelectrical impedance analysis. We evaluated the collected data statistically and graphically in Microsoft Office Excel 2010 (Los Angeles, CA, USA). Statistical analyses were performed using the program STATISTICA Cz version 10.
RESULTS
The diagnosis of obesity among participants according to anthropometric measures and indices showed considerable differences. We found that obesity was diagnosed according to waist circumference in 31% of participants. According to BMI 20.3% of subjects were overweight and 5.1% obese. With increasing BMI values, the values of WC, WHR and VFA also increased linearly. According to visceral fat area 11.4% of participants were in the risk obese group and by ABSI mortality risk there were 22% of subjects with high risk (4.8% and 28.3% for men and women, respectively) and 19.1% with very high risk (11.1% and 22% for men and women, respectively). VFA and BFP values increased with increasing risk of mortality, and in men also waist circumference values. When evaluating the ABSI in relation to BMI, the U-shaped curve was confirmed and in the case of WC the J-shaped curve. The FFM evaluation showed that the very low ABSI mortality risk group reached the highest values of this parameter and the lowest values showed the average mortality risk group, not only in the study group but also in male and female groups.
CONCLUSIONS
Our findings suggest the relevance of ABSI to screen at-risk population.
Topics: Adult; Anthropometry; Body Composition; Body Mass Index; Female; Humans; Male; Obesity; Poland; Risk Factors; Students; Waist Circumference; Waist-Height Ratio; Waist-Hip Ratio; Young Adult
PubMed: 31515986
DOI: 10.32394/rpzh.2019.0077 -
The American Journal of Clinical... Jun 2021Calf circumference (CC) is used in geriatric studies as a simple and practical skeletal muscle (SM) marker for diagnosing low SM and sarcopenia. Currently applied CC...
BACKGROUND
Calf circumference (CC) is used in geriatric studies as a simple and practical skeletal muscle (SM) marker for diagnosing low SM and sarcopenia. Currently applied CC cutoff points were developed in samples including older participants; values representative of the full adult lifespan are lacking.
OBJECTIVES
We aimed to develop CC cutoff points and to identify relevant confounding factors from the large and diverse NHANES 1999-2006 population sample.
METHODS
Demographic, anthropometric, and imaging data (DXA, appendicular lean mass) from the adult (age ≥18 y) NHANES sample were partitioned into subgroups according to sex, age, ethnicity, and race. Adults aged 18-39 y and BMI (in kg/m2) 18.5-24.9 were set as a reference population; CC cutoff points were derived at 1 and 2 SDs below the mean.
RESULTS
The sample included 17,789 participants, 51.3% males and 48.7% females, with respective ages (mean ± SD) of 43.3 ± 16.1 y and 45.5 ± 16.9 y. CC was strongly correlated with appendicular lean mass, r = 0.84 and 0.86 for males and females (both P < 0.001), respectively. Significant differences in mean CC were present across sex, ethnic, self-reported race, and BMI groups. Adjusting CC for adiposity using BMI revealed a decrease in CC beginning after the second decade in males and third decade in females. Rounded CC cutoff values for moderately and severely low CC were 34 cm and 32 cm (males), and 33 cm and 31 cm (females), respectively. Our findings support the use of BMI-adjusted CC values for participants outside the normal-weight BMI range (18-24.9).
CONCLUSIONS
This study defined CC values in a diverse population sample along with a BMI-adjustment approach that helps to remove the confounding effects of adiposity and thereby improves CC as a useful clinical estimate of SM mass.
Topics: Adult; Anthropometry; Body Composition; Body Mass Index; Female; Humans; Leg; Male; Middle Aged; Muscle, Skeletal; Nutrition Surveys; Nutritional Status; Sarcopenia
PubMed: 33742191
DOI: 10.1093/ajcn/nqab029 -
Pediatrics Nov 2015Children with Down syndrome (DS) have lower birth weights and grow more slowly than children without DS. Advances in and increased access to medical care have improved...
BACKGROUND AND OBJECTIVES
Children with Down syndrome (DS) have lower birth weights and grow more slowly than children without DS. Advances in and increased access to medical care have improved the health and well-being of individuals with DS; however, it is unknown whether their growth has also improved. Our objective was to develop new growth charts for children with DS and compare them to older charts from the United States and more contemporary charts from the United Kingdom.
METHODS
The Down Syndrome Growing Up Study (DSGS) enrolled a convenience sample of children with DS up to 20 years of age and followed them longitudinally. Growth parameters were measured by research anthropometrists. Sex-specific growth charts were generated for the age ranges birth to 36 months and 2 to 20 years using the LMS method. Weight-for-length and BMI charts were also generated. Comparisons with other curves were presented graphically.
RESULTS
New DSGS growth charts were developed by using 1520 measurements on 637 participants. DSGS growth charts for children <36 months of age showed marked improvements in weight compared with older US charts. DSGS charts for 2- to 20-year-olds showed that contemporary males are taller than previous charts showed. Generally, the DSGS growth charts are similar to the UK charts.
CONCLUSIONS
The DSGS growth charts can be used as screening tools to assess growth and nutritional status and to provide indications of how growth of an individual child compares with peers of the same age and sex with DS.
Topics: Adolescent; Anthropometry; Body Height; Body Mass Index; Body Weight; Child; Child, Preschool; Down Syndrome; Female; Growth Charts; Head; Humans; Infant; Infant, Newborn; Male; Nutritional Status; United States
PubMed: 26504127
DOI: 10.1542/peds.2015-1652 -
European Journal of Clinical Nutrition May 2018Anthropometry, Greek for human measurement, is a tool widely used across many scientific disciplines. Clinical nutrition applications include phenotyping subjects across... (Review)
Review
Anthropometry, Greek for human measurement, is a tool widely used across many scientific disciplines. Clinical nutrition applications include phenotyping subjects across the lifespan for assessing growth, body composition, response to treatments, and predicting health risks. The simple anthropometric tools such as flexible measuring tapes and calipers are now being supplanted by rapidly developing digital technology devices. These systems take many forms, but excitement today surrounds the introduction of relatively low cost three-dimensional optical imaging methods that can be used in research, clinical, and even home settings. This review examines this transformative technology, providing an overview of device operational details, early validation studies, and potential applications. Digital anthropometry is rapidly transforming dormant and static areas of clinical nutrition science with many new applications and research opportunities.
Topics: Absorptiometry, Photon; Anthropometry; Body Composition; Databases, Factual; Humans; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Nutrition Assessment; Principal Component Analysis; Reproducibility of Results; Tomography Scanners, X-Ray Computed
PubMed: 29748657
DOI: 10.1038/s41430-018-0145-7 -
Jornal de Pediatria 2020Validate the accuracy of the Screening Tool for Risk on Nutritional status and Growth (STRONGkids) and estimate the prevalence of malnutrition and nutritional risk in... (Randomized Controlled Trial)
Randomized Controlled Trial
OBJECTIVE
Validate the accuracy of the Screening Tool for Risk on Nutritional status and Growth (STRONGkids) and estimate the prevalence of malnutrition and nutritional risk in hospitalized children.
METHODS
Cross-sectional study of a representative sample of children admitted to ten public pediatric emergency rooms. The sample was randomly estimated in stages, including children older than 30 days and younger than 10 years of age, of both sexes, excluding syndromic children and those in whom it was impossible to directly measure anthropometry. Weight, height, and arm circumference were measured, as well as the Z-scores of the anthropometric indices weight-for-age, height-for-age, weight-for-height, body mass index for age, and arm circumference for age, classified according to the reference curves of the World Health Organization. After the tool was applied, its accuracy tests were performed in comparison with the anthropometric data, with the evaluation of sensitivity, specificity, and positive and negative predictive values.
RESULTS
A total of 271 children were evaluated, 56.46% males and 41.70% younger than 2 years of age. The prevalence rates of malnutrition, nutritional risk assessed by anthropometric measurements, and nutritional risk assessed by the tool were 12.18%, 33.95%, and 78.60%, respectively. Accuracy showed sensitivity of 84.8%, specificity of 26.7%, positive predictive value of 49.8%, and negative predictive value of 67.2%, when the patients at nutritional risk were identified by anthropometry.
CONCLUSION
Validation of the accuracy of STRONGkids was performed, showing high sensitivity, allowing the early identification of nutritional risk in similar populations.
Topics: Anthropometry; Body Mass Index; Body Weight; Child; Child, Preschool; Cross-Sectional Studies; Female; Humans; Infant; Male; Malnutrition; Nutrition Assessment; Nutritional Status
PubMed: 31028746
DOI: 10.1016/j.jped.2018.12.012 -
Nutricion Hospitalaria Sep 2016El sobrepeso y la obesidad se definen como un depósito anormal o excesivo de grasa corporal. El aumento de su prevalencia en las últimas décadas lo convierte en uno...
El sobrepeso y la obesidad se definen como un depósito anormal o excesivo de grasa corporal. El aumento de su prevalencia en las últimas décadas lo convierte en uno de los principales problemas de salud pública que afecta a 42 millones de niños menores de 5 años en el mundo. Su presencia durante la infancia puede ser causa de enfermedades metabólicas hasta ahora consideradas típicas del adulto y mortalidad prematura, por lo que su correcto diagnóstico y tratamiento son fundamentales.
Topics: Absorptiometry, Photon; Adolescent; Anthropometry; Body Composition; Body Mass Index; Child; Child, Preschool; Female; Humans; Infant; Male
PubMed: 27759964
DOI: 10.20960/nh.560 -
International Journal of Environmental... Oct 2022While overeating is considered a cause of the obesity epidemic as quantified by body mass index (BMI), the association of diet with a body shape index (ABSI) and hip...
While overeating is considered a cause of the obesity epidemic as quantified by body mass index (BMI), the association of diet with a body shape index (ABSI) and hip index (HI), which are transformations of waist and hip circumference that are independent of BMI and which predict mortality risk, is poorly known. We used data from the Atherosclerosis Risk in Communities (ARIC) study of about 15,000 middle-aged adults to investigate associations between macronutrient intake (energy, carbohydrate, protein, and fat, the latter two divided into plant and animal sources, all based on self-reported food frequency) with anthropometric indices (BMI, ABSI, and HI). We also analyzed the association of diet and anthropometrics with death rate during approximately 30 years of follow-up. High intake of energy and animal fat and protein was generally associated with higher ABSI and lower HI at baseline, as well as greater mortality hazard. BMI was also positively linked with animal fat and protein intake. In contrast, higher intake of carbohydrates and plant fat and protein was associated with lower ABSI and BMI, higher HI, and lower mortality hazard. For example, after adjustment for potential confounders, each standard deviation of additional plant fat intake (as a fraction of total energy) was associated with a 5% decrease in mortality rate, while animal fat intake was associated with a 5% mortality increase per standard deviation. The directions of the associations between diet and anthropometrics are consistent with those found between anthropometrics and mortality without reference to diet.
Topics: Animals; Anthropometry; Body Composition; Body Mass Index; Carbohydrates; Diet; Obesity; Risk Factors; Waist Circumference
PubMed: 36232184
DOI: 10.3390/ijerph191912885 -
The American Journal of Clinical... Jan 2017
Topics: Anthropometry; History, Ancient
PubMed: 28003202
DOI: 10.3945/ajcn.116.148346