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Journal articles on the topic 'Anthropometric measures'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 March 2023

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1

Jodeh, Diana S., and S. Alex Rottgers. "High-Fidelity Anthropometric Facial Measurements Can Be Obtained From a Single Stereophotograph From the Vectra H1 3-Dimensional Camera." Cleft Palate-Craniofacial Journal 56, no. 9 (April 7, 2019): 1164–70. http://dx.doi.org/10.1177/1055665619839577.

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Background: Anthropometry is a well-established means of measuring facial morphology. Although reliable, direct anthropometry can be time-consuming and not conducive to a busy clinical practice. The Vectra H1 handheld stereophotogrammetric system requires 3 stereophotographs taken from different perspectives to generate a three-dimensional (3D) surface. The time needed to take the 3 stereophotographs can increase the possibility of involuntary movements, precluding its use to assess young patients. To overcome this limitation, we evaluated if accurate linear facial measurements can be obtained from a single stereophotograph and compare these to the measurements taken by direct anthropometry. Methods: Twenty pediatric patients, aged 0 to 10 years, who were undergoing minor surgical procedures at Johns Hopkins All Children’s Hospital were recruited. Fourteen linear facial distances were obtained from each participant using direct anthropometry under general anesthesia. These same distances were measured using Mirror 3D analysis. Intraclass correlation was used to determine intrarater reliability on duplicate 3D images. Results: Correlation coefficients between 3D imaging in frontal view and direct anthropometric measurements were excellent for 13 measures taken, ranging from 0.8 (subnasale to columella and subnasale to stomion superius) to 0.98 (nasion to subnasale and subnasale to labiale superius). Correlation coefficients between submental view and direct anthropometric measurements were excellent for 13 measures as well, ranging from 0.77 (subnasale to columella) to 0.98 (nasion to subnasale). Conclusions: Linear anthropometric measurements taken from 3D surfaces generated from a single stereophotograph correlate closely with direct anthropometric measures. This improves workflow and applicability of anthropometric studies to our youngest patients.

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Shurtleff, David B., William Otis Walker, Sharon Duguay, Do Peterson, and Diana Cardenas. "Obesity and Myelomeningocele: Anthropometric Measures." Journal of Spinal Cord Medicine 33, no. 4 (January 2010): 410–19. http://dx.doi.org/10.1080/10790268.2010.11689720.

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3

Landi, Francesco, Rosa Liperoti, and Graziano Onder. "The usefulness of anthropometric measures." European Journal of Nutrition 52, no. 6 (July 2, 2013): 1683. http://dx.doi.org/10.1007/s00394-013-0550-6.

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4

Ulijaszek, Stanley J., and Deborah A. Kerr. "Anthropometric measurement error and the assessment of nutritional status." British Journal of Nutrition 82, no. 3 (September 1999): 165–77. http://dx.doi.org/10.1017/s0007114599001348.

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Anthropometry involves the external measurement of morphological traits of human beings. It has a widespread and important place in nutritional assessment, and while the literature on anthropometric measurement and its interpretation is enormous, the extent to which measurement error can influence both measurement and interpretation of nutritional status is little considered. In this article, different types of anthropometric measurement error are reviewed, ways of estimating measurement error are critically evaluated, guidelines for acceptable error presented, and ways in which measures of error can be used to improve the interpretation of anthropometric nutritional status discussed. Possible errors are of two sorts; those that are associated with: (1) repeated measures giving the same value (unreliability, imprecision, undependability); and (2) measurements departing from true values (inaccuracy, bias). Imprecision is due largely to observer error, and is the most commonly used measure of anthropometric measurement error. This can be estimated by carrying out repeated anthropometric measures on the same subjects and calculating one or more of the following: technical error of measurement (TEM); percentage TEM, coefficient of reliability (R), and intraclass correlation coefficient. The first three of these measures are mathematically interrelated. Targets for training in anthropometry are at present far from perfect, and further work is needed in developing appropriate protocols for nutritional anthropometry training. Acceptable levels of measurement error are difficult to ascertain because TEM is age dependent, and the value is also related to the anthropometric characteristics of the group or population under investigation. R > 0·95 should be sought where possible, and reference values of maximum acceptable TEM at set levels of R using published data from the combined National Health and Nutrition Examination Surveys I and II (Frisancho, 1990) are given. There is a clear hierarchy in the precision of different nutritional anthropometric measures, with weight and height being most precise. Waist and hip circumference show strong between-observer differences, and should, where possible, be carried out by one observer. Skinfolds can be associated with such large measurement error that interpretation is problematic. Ways are described in which measurement error can be used to assess the probability that differences in anthropometric measures across time within individuals are due to factors other than imprecision. Anthropometry is an important tool for nutritional assessment, and the techniques reported here should allow increased precision of measurement, and improved interpretation of anthropometric data.

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Giudicelli, Bruno B., Leonardo G. O. Luz, Mustafa Sogut, Hugo Sarmento, Alain G. Massart, Arnaldo C. Júnior, Adam Field, and António J. Figueiredo. "Chronological Age, Somatic Maturation and Anthropometric Measures: Association with Physical Performance of Young Male Judo Athletes." International Journal of Environmental Research and Public Health 18, no. 12 (June 13, 2021): 6410. http://dx.doi.org/10.3390/ijerph18126410.

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Sport for children and adolescents must consider growth and maturation to ensure suitable training and competition, and anthropometric variables could be used as bio-banding strategies in youth sport. This investigation aimed to analyze the association between chronological age, biologic maturation, and anthropometric characteristics to explain physical performance of young judo athletes. Sixty-seven judokas (11.0–14.7 years) were assessed for anthropometric and physical performance. Predicted adult stature was used as a somatic maturation indicator. A Pearson’s bivariate correlation was performed to define which anthropometric variables were associated with each physical test. A multiple linear hierarchical regression was conducted to verify the effects of age, maturity, and anthropometry on physical performance. The regression models were built with age, predicted adult stature, and the three most significantly correlated anthropometric variables for each physical test. Older judokas performed better in most of the physical tests. However, maturation attenuated the age effect in most variables and significantly affected upper body and handgrip strength. Anthropometric variables attenuated age and maturity and those associated with body composition significantly affected the performance in most tests, suggesting a potential as bio-banding strategies. Future studies should investigate the role of anthropometric variables on the maturity effect in young judokas.

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Abrahams, Zulfa, Gary Maartens, Naomi Levitt, and Joel Dave. "Anthropometric definitions for antiretroviral-associated lipodystrophy derived from a longitudinal South African cohort with serial dual-energy X-ray absorptiometry measurements." International Journal of STD & AIDS 29, no. 12 (June 26, 2018): 1194–203. http://dx.doi.org/10.1177/0956462418778649.

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The development of lipodystrophy is associated with the long-term use of antiretroviral therapy (ART). We assessed agreement between patient-reported lipodystrophy and body composition measures using dual-energy X-ray absorptiometry (DXA) and developed objective measures to define lipoatrophy and lipohypertrophy in black South Africans. One hundred and eighty-seven ART-naïve HIV-infected adults were enrolled in a 24-month longitudinal study. Self-reported information on regional fat loss and fat gain, anthropometry, and DXA measures were collected at baseline, three, six, 12, 18, and 24 months after starting ART. Receiver operating characteristic curves were used to describe the performance of anthropometric variables using change in limb and trunk fat measured by DXA, as the reference standard. The proportion of men and women who developed lipoatrophy and lipohypertrophy increased over the 24-month period, with lipoatrophy occurring more frequently in men (21% versus 10%). In women, lipoatrophy was best determined by thigh skinfold thickness (80.3% correctly classified) and mid-arm circumference (77.6% correctly classified). None of the anthropometric measures performed well for defining lipoatrophy in men. Anthropometric measures performed well for defining lipoatrophy in women, but not lipohypertrophy.

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Wong, Julielynn Y., Albert K. Oh, Eiichi Ohta, Anne T. Hunt, Gary F. Rogers, John B. Mulliken, and Curtis K. Deutsch. "Validity and Reliability of Craniofacial Anthropometric Measurement of 3D Digital Photogrammetric Images." Cleft Palate-Craniofacial Journal 45, no. 3 (May 2008): 232–39. http://dx.doi.org/10.1597/06-175.

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Background: Direct anthropometry performed during a patient examination is the standard technique for quantifying craniofacial dysmorphology, as well as for surgical planning and outcome assessment. Several new technologies have been designed to computerize anthropometric measurements, including three-dimensional (3D) digital photogrammetry. These digital systems have the advantage of acquiring patient craniofacial surface images quickly and noninvasively. Before morphometry using digital photogrammetry can be applied in clinical and research practice, it must be assessed against direct anthropometry. Objective: To evaluate the validity and reliability of facial anthropometric linear distances imaged by 3D digital photogrammetry with respect to direct anthropometry. Design, Setting, Participants, Measures: Standard craniofacial distances were directly measured twice on 20 normal adult volunteers. Craniofacial surfaces were also imaged using the 3dMDface digital photogrammetry system, and distances were digitally measured twice for each subject. Validity measures of accuracy and bias (for direct versus digital measurements) and reproducibility measures of precision and test-retest reliability (for repeated sets of digital measurements) were computed. Results: Seventeen of the 18 direct measurements correlated highly with digital values (mean r = 0.88). The correlation for one measurement (upper prolabial width) was not statistically significant. The overall precision of all 17 digital measurements was less than 1 mm, and the reliability was high (mean r = 0.91). Conclusions: Craniofacial anthropometry using the 3dMDface System is valid and reliable. Digital measurements of upper prolabial width may require direct marking, prior to imaging, to improve landmark identification.

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Pugh, Sarah J., Ana M. Ortega-Villa, William Grobman, Stefanie N. Hinkle, Roger B. Newman, Mary Hediger, Jagteshwar Grewal, Deborah A. Wing, Paul S. Albert, and Katherine L. Grantz. "Longitudinal changes in maternal anthropometry in relation to neonatal anthropometry." Public Health Nutrition 22, no. 5 (February 11, 2019): 797–804. http://dx.doi.org/10.1017/s1368980018003749.

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AbstractObjectiveTo characterize the association of longitudinal changes in maternal anthropometric measures with neonatal anthropometry and to assess to what extent late-gestational changes in maternal anthropometry are associated with neonatal body composition.DesignIn a prospective cohort of pregnant women, maternal anthropometry was measured at six study visits across pregnancy and after birth, neonates were measured and fat and lean mass calculated. We estimated maternal anthropometric trajectories and separately assessed rate of change in the second (15–28 weeks) and third trimester (28–39 weeks) in relation to neonatal anthropometry. We investigated the extent to which tertiles of third-trimester maternal anthropometry change were associated with neonatal outcomes.SettingWomen were recruited from twelve US sites (2009–2013).ParticipantsNon-obese women with singleton pregnancies (n 2334).ResultsA higher rate of increase in gestational weight gain was associated with larger-birth-weight infants with greater lean and fat mass. In contrast, higher rates of increase in maternal anthropometry measures were not associated with infant birth weight but were associated with decreased neonatal lean mass. In the third trimester, women in the tertile of lowest change in triceps skinfold (−0·57 to −0·06 mm per week) had neonates with 35·8 g more lean mass than neonates of mothers in the middle tertile of rate of change (−0·05 to 0·06 mm per week).ConclusionsThe rate of change in third-trimester maternal anthropometry measures may be related to neonatal lean and fat mass yet have a negligible impact on infant birth weight, indicating that neonatal anthropometry may provide additional information over birth weight alone.

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Satır, Benhür, and Filiz Çelikçi Erdoğan. "Comparison of classroom furniture to anthropometric measures of Turkish middle school students." Work 70, no. 2 (October 26, 2021): 493–508. http://dx.doi.org/10.3233/wor-213587.

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BACKGROUND: The match between classroom furniture and students’ anthropometry is an important factor in students’ academic performance. OBJECTIVE: Our aim was to investigate the ergonomic suitability of the classroom furniture to the students, and to propose design suggestions for both desks and chairs. METHODS: We analyzed the ergonomics of classroom furniture that students aged 10–14 years old in Turkey currently use. To this end, we selected Maltepe Primary Education School, one of the largest schools in the Çankaya district of Turkey’s capital city, Ankara, in which to conduct the study. A sample of 119 students was selected, and seven anthropometric measurements were taken for each of these students. We then calculated five relationships between the dimensions of the furniture and the students’ anthropometric measures. RESULTS: We observed high levels of mismatch rates, with an average of 66.6%and high values of over 95%for the relations of two furniture measures, seat depth (related with buttock-popliteal length) and seat-to-desk height (related with elbow height, sitting). Each anthropometric measure was applied a fit probability distribution, and based on those distributions; we suggested the most appropriate classroom furniture dimensions in order to maximize suitability of the furniture to the anthropometric measures in terms of fixed-size (i.e., non-adjustable) classroom furniture. CONCLUSIONS: High mismatch rates can be reduced by 52.0%on average based on the classroom furniture dimensions suggested in this study.

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10

Garimella, Raman, Thomas Peeters, Eduardo Parrilla, Jordi Uriel, Seppe Sels, Toon Huysmans, and Stijn Verwulgen. "Estimating Cycling Aerodynamic Performance Using Anthropometric Measures." Applied Sciences 10, no. 23 (December 2, 2020): 8635. http://dx.doi.org/10.3390/app10238635.

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Aerodynamic drag force and projected frontal area (A) are commonly used indicators of aerodynamic cycling efficiency. This study investigated the accuracy of estimating these quantities using easy-to-acquire anthropometric and pose measures. In the first part, computational fluid dynamics (CFD) drag force calculations and A (m2) values from photogrammetry methods were compared using predicted 3D cycling models for 10 male amateur cyclists. The shape of the 3D models was predicted using anthropometric measures. Subsequently, the models were reposed from a standing to a cycling pose using joint angle data from an optical motion capture (mocap) system. In the second part, a linear regression analysis was performed to predict A using 26 anthropometric measures combined with joint angle data from two sources (optical and inertial mocap, separately). Drag calculations were strongly correlated with benchmark projected frontal area (coefficient of determination R2 = 0.72). A can accurately be predicted using anthropometric data and joint angles from optical mocap (root mean square error (RMSE) = 0.037 m2) or inertial mocap (RMSE = 0.032 m2). This study showed that aerodynamic efficiency can be predicted using anthropometric and joint angle data from commercially available, inexpensive posture tracking methods. The practical relevance for cyclists is to quantify and train posture during cycling for improving aerodynamic efficiency and hence performance.

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Nadadur, Gopal, and Matthew B. Parkinson. "Extrapolation of Anthropometric Measures to New Populations." SAE International Journal of Passenger Cars - Electronic and Electrical Systems 1, no. 1 (June 17, 2008): 567–73. http://dx.doi.org/10.4271/2008-01-1858.

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12

Chen, L.-W., M.-T. Tint, M. V. Fortier, I. M. Aris, L. P.-C. Shek, K. H. Tan, S.-Y. Chan, et al. "Which anthropometric measures best reflect neonatal adiposity?" International Journal of Obesity 42, no. 3 (October 9, 2017): 501–6. http://dx.doi.org/10.1038/ijo.2017.250.

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13

Gross, Michael T., Ennea S. Dailey, Melissa D. Dalton, Angela K. Lee, Tracy L. McKiernan, Wendy L. Vernon, and Ashley C. Walden. "Relationship Between Lifting Capacity and Anthropometric Measures." Journal of Orthopaedic & Sports Physical Therapy 30, no. 5 (May 2000): 237–62. http://dx.doi.org/10.2519/jospt.2000.30.5.237.

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14

Arbogast, K. B., S. Mari-Gowda, E. Houseknecht, and D. A. Mong. "Anthropometric measures of pediatric seat belt fit." Journal of Biomechanics 39 (January 2006): S159. http://dx.doi.org/10.1016/s0021-9290(06)83547-5.

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15

Gallwey, T. J., and M. J. Fitzgibbon. "Some anthropometric measures on an Irish population." Applied Ergonomics 22, no. 1 (February 1991): 9–12. http://dx.doi.org/10.1016/0003-6870(91)90003-z.

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16

Šram, Miroslav, Zvonimir Vrselja, Igor Lekšan, Goran Ćurić, Kristina Selthofer-Relatić, and Radivoje Radić. "Epicardial Adipose Tissue Is Nonlinearly Related to Anthropometric Measures and Subcutaneous Adipose Tissue." International Journal of Endocrinology 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/456293.

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Introduction. Adipose tissue is the largest endocrine organ, composed of subcutaneous (SAT) and visceral adipose tissue (VAT), the latter being highly associated with coronary artery disease (CAD). Expansion of epicardial adipose tissue (EAT) is linked to CAD. One way of assessing the CAD risk is with low-cost anthropometric measures, although they are inaccurate and cannot discriminate between VAT and SAT. The aim of this study is to evaluate (1) the relationship between EAT thickness, SAT thickness and anthropometric measures in a cohort of patients assessed at the cardiology unit and (2) determine predictive power of anthropometric measures and EAT and SAT thickness in establishment of CAD.Methods. Anthropometric measures were obtained from 53 CAD and 42 non-CAD patients. Vascular and structural statuses were obtained with coronarography and echocardiography, as well as measurements of the EAT and SAT thickness.Results. Anthropometric measures showed moderate positive correlation with EAT and SAT thickness. Anthropometric measures and SAT follow nonlinearS curverelationship with EAT. Strong nonlinearpower curverelationship was observed between EAT and SAT thinner than 10 mm. Anthropometric measures and EAT and SAT were poor predictors of CAD.Conclusion. Anthropometric measures and SAT have nonlinear relationship with EAT. EAT thickness and anthropometric measures have similar CAD predictive value.

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Gómez-Carrascosa, Inmaculada, María L. Sánchez-Ferrer, Ernesto de la Cruz-Sánchez, Julián J. Arense-Gonzalo, María T. Prieto-Sánchez, Emilia Alfosea-Marhuenda, Miguel A. Iniesta, Jaime Mendiola, and Alberto M. Torres-Cantero. "Analysis and Reliability of Anthropometric Measurements during Pregnancy: A Prospective Cohort Study in 208 Pregnant Women." Journal of Clinical Medicine 10, no. 17 (August 31, 2021): 3933. http://dx.doi.org/10.3390/jcm10173933.

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Anthropometric assessment during pregnancy is a widely used, low-technology procedure that has not been rigorously evaluated. Our objective is to investigate fat mass distribution during pregnancy by examining changes in anthropometrics measures, in order to evaluate the reliability of these measures. An observational, longitudinal, prospective cohort study was performed in 208 pregnant women. Anthropometric measurements were taken following the ISAK protocol during the three trimesters and a generalized linear model for repeated measures was used to evaluate differences. Variability was assessed using the coefficient of variation, and Propagated Error (PE) was used to sum of skinfold thicknesses (SFT). SFT showed a general increase in fat mass during the three trimesters of pregnancy (∑SFT7 p = 0.003), and was observed in specific anatomical locations as well: arms (∑Arm SFT, p = 0.046), trunk (∑Trunk SFT, p = 0.019), legs (∑Leg SFT, p = 0.001) and appendicular (∑Appendicular SFT, p = 0.001). Anthropometric measures for skinfold thickness were taken individually during pregnancy and were reliable and reproducible during the three trimesters, which could help to prevent adverse pregnancy outcomes.

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Sumpor, Davor. "Anthropometric measures important for control panel design in locomotive or railcar." Tehnicki vjesnik - Technical Gazette 22, no. 1 (2015): 1–10. http://dx.doi.org/10.17559/tv-20140206135045.

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Ye, Ming, Paula J. Robson, Dean T. Eurich, Jennifer E. Vena, Jian-Yi Xu, and Jeffrey A. Johnson. "Anthropometric changes and risk of diabetes: are there sex differences? A longitudinal study of Alberta’s Tomorrow Project." BMJ Open 9, no. 7 (July 2019): e023829. http://dx.doi.org/10.1136/bmjopen-2018-023829.

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ObjectivesTo characterise the sex-specific difference in the association between anthropometric changes and risk of diabetes in the general population in Canada.Setting and participantsFrom 2000 to 2008, Alberta’s Tomorrow Project (ATP) invited Alberta’s residents aged 35–69 years to a prospective cohort study. A total of 19 655 diabetes-free ATP participants having anthropometrics measured at the baseline and follow-ups were included.Design and outcome measuresA longitudinal study design was used to examine the association between anthropometric changes and risk of diabetes and the sex difference in this association. Changes in weight, body mass index (BMI), waist circumference (WC) and waist-hip-ratio (WHR) were calculated as the difference between baseline and follow-up measures. Diabetes cases were identified using the Canadian National Diabetes Surveillance System algorithm with administrative healthcare data (2000–2015) linked to the ATP cohort. The sex-specific association between anthropometric changes and incidence of diabetes were examined by multivariable Cox regression models.ResultsChanges in weight, BMI, WC and WHR over time were positively associated with incidence of diabetes in both men and women. The sex difference in risk of diabetes associated with 1 standard deviation (SD) increase in anthropometrics was 0.07 (95% CI −0.02 to 0.14) for weight, 0.08 (95% CI −0.03 to 0.17) for BMI, 0.07 (95% CI −0.02 to 0.15) for WC and 0.09 (95% CI 0.03 to 0.13) for WHR. Similar results were found in sex difference in the associations with changes per 5% and changes per categories (5% loss, ±5%, 5% gain).ConclusionsThe positive association between anthropometric changes and risk of diabetes was generally stronger in men than in women. However, this sex-specific difference of approximately 10% of the total risk associated with anthropometric changes had limited significance. For population-based public health programmes aiming to control obesity and incidence of diabetes, it may not be necessary to set up sex-specific goals for anthropometric reduction.

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Closs, Vera Elizabeth, Patricia Klarmann Ziegelmann, João Henrique Ferreira Flores, Irenio Gomes, and Carla Helena Augustin Schwanke. "Anthropometric Measures and Frailty Prediction in the Elderly: An Easy-to-Use Tool." Current Gerontology and Geriatrics Research 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/8703503.

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Purpose. Anthropometry is a useful tool for assessing some risk factors for frailty. Thus, the aim of this study was to verify the discriminatory performance of anthropometric measures in identifying frailty in the elderly and to create an easy-to-use tool. Methods. Cross-sectional study: a subset from the Multidimensional Study of the Elderly in the Family Health Strategy (EMI-SUS) evaluating 538 older adults. Individuals were classified using the Fried Phenotype criteria, and 26 anthropometric measures were obtained. The predictive ability of anthropometric measures in identifying frailty was identified through logistic regression and an artificial neural network. The accuracy of the final models was assessed with an ROC curve. Results. The final model comprised the following predictors: weight, waist circumference, bicipital skinfold, sagittal abdominal diameter, and age. The final neural network models presented a higher ROC curve of 0.78 (CI 95% 0.74–0.82) (P<0.001) than the logistic regression model, with an ROC curve of 0.71 (CI 95% 0.66–0.77) (P<0.001). Conclusion. The neural network model provides a reliable tool for identifying prefrailty/frailty in the elderly, with the advantage of being easy to apply in the primary health care. It may help to provide timely interventions to ameliorate the risk of adverse events.

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Barnett, Lisa M., Avigdor Zask, Lauren Rose, Denise Hughes, and Jillian Adams. "Three-Year Follow-Up of an Early Childhood Intervention: What About Physical Activity and Weight Status?" Journal of Physical Activity and Health 12, no. 3 (March 2015): 319–21. http://dx.doi.org/10.1123/jpah.2013-0419.

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Background:Fundamental movement skills are a correlate of physical activity and weight status. Children who participated in a preschool intervention had greater movement skill proficiency and improved anthropometric measures (waist circumference and BMI z scores) post intervention. Three years later, intervention girls had retained their object control skill advantage. The study purpose was to assess whether at 3-year follow up a) intervention children were more physically active than controls and b) the intervention effect on anthropometrics was still present.Methods:Children were assessed at ages 4, 5, and 8 years for anthropometric measures and locomotor and object control proficiency (Test of Gross Motor Development-2). At age 8, children were also assessed for moderate to vigorous physical activity (MVPA) (using accelerometry). Several general linear models were run, the first with MVPA as the outcome, intervention/control, anthropometrics, object control and locomotor scores as predictors, and age and sex as covariates. The second and third models were similar, except baseline to follow-up anthropometric differences were the outcome.Results:Overall follow-up rate was 29% (163/560), with 111 children having complete data. There were no intervention control differences in either MVPA or anthropometrics.Conclusion:Increased skill competence did not translate to increased physical activity.

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Overend, Tom J., David A. Cunningham, Donald H. Paterson, and Michael S. Lefcoe. "Anthropometric and Computed Tomographic Assessment of the Thigh in Young and Old Men." Canadian Journal of Applied Physiology 18, no. 3 (September 1, 1993): 263–73. http://dx.doi.org/10.1139/h93-023.

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Anthropometric (AP) and computed tomographic (CT) methods of determining limb and muscle-plus-bone cross-sectional area (CSA) and volume (Vol) were compared in 13 young (M = 24.5 yrs) and 11 old (M = 71.0 yrs) men. CSA of total thigh, muscle-plus-bone, quadriceps, and hamstring muscle compartments and muscle were measured from CT scans. Corresponding muscle Vol were estimated from anthropometric equations. Prediction equations for CT measures were developed from AP measures using multiple linear regression. AP and CT techniques produced different values for thigh component CSA and Vol, especially in the old men. AP overestimated muscle-plus-bone CSA and Vol (4-6%) and underestimated skin and subcutaneous tissue CSA and Vol (17-33%). Prediction equations for quadriceps CSA and Vol (R2 = 80-96%) were more accurate than equations for hamstrings (R2 = 42-65%). Specific thigh muscle CSA and Vol can be predicted from AP measures (SEE 5-15%). These findings may have clinical significance when normalizing strength per unit of muscle size. Key words: computed tomography, anthropometry, cross-sectional area, limb volume, ageing

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Correia, Igor Massari, Anderson Marliere Navarro, Jéssica Fernanda Corrêa Cordeiro, Euripedes Barsanulfo Gonçalves Gomide, Lisa Fernanda Mazzonetto, Alcivandro de Sousa Oliveira, Emerson Sebastião, et al. "Bone Mineral Content Estimation in People Living with HIV: Prediction and Validation of Sex-Specific Anthropometric Models." International Journal of Environmental Research and Public Health 19, no. 19 (September 28, 2022): 12336. http://dx.doi.org/10.3390/ijerph191912336.

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People living with HIV (PWH) experience an accelerated reduction in bone mineral content (BMC), and a high risk of osteopenia and osteoporosis. Anthropometry is an accurate and low-cost method that can be used to monitor changes in body composition in PWH. To date, no studies have used anthropometry to estimate BMC in PWH. To propose and validate sex-specific anthropometric models to predict BMC in PWH. This cross-sectional study enrolled 104 PWH (64 males) aged >18 years at a local university hospital. BMC was measured using dual energy X-ray absorptiometry (DXA). Anthropometric measures were collected. We used linear regression analysis to generate the models. Cross-validations were conducted using the “leave one out”, from the predicted residual error sum of squares (PRESS) method. Bland–Altman plots were used to explore distributions of errors. We proposed models with high coefficient of determination and reduced standard error of estimate for males (r2 = 0.70; SEE = 199.97 g; Q2PRESS = 0.67; SEEPRESS = 208.65 g) and females (r2 = 0.65; SEE = 220.96 g; Q2PRESS = 0.62; SEEPRESS = 221.90 g). Our anthropometric predictive models for BMC are valid, practical, and a low-cost alternative to monitoring bone health in PWH.

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Reese, Tyler O., Pascal Bovet, Candice Choo-Kang, Kweku Bedu-Addo, Terrence Forrester, Jack A. Gilbert, Julia H. Goedecke, et al. "Utility of silhouette showcards to assess adiposity in three countries across the epidemiological transition." PLOS Global Public Health 2, no. 5 (May 19, 2022): e0000127. http://dx.doi.org/10.1371/journal.pgph.0000127.

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The Pulvers’ silhouette showcards provide a non-invasive and easy-to-use way of assessing an individual’s body size perception using nine silhouette shapes. However, their utility across different populations has not been examined. This study aimed to assess: 1) the relationship between silhouette perception and measured anthropometrics, i.e., body mass index (BMI), waist circumference (WC), waist-height-ratio (WHtR), and 2) the ability to predict with silhouette showcards anthropometric adiposity measures, i.e., overweight and obesity (BMI ≥ 25 kg/m2), obesity alone (BMI ≥ 30 kg/m2), elevated WC (men ≥ 94 cm; women ≥ 80 cm), and WHtR (> 0.5) across the epidemiological transition. 751 African-origin participants, aged 20–68 years old, from the United States (US), Seychelles, and Ghana, completed anthropometrics and selected silhouettes corresponding to their perceived body size. Silhouette performance to anthropometrics was examined using a least-squares linear regression model. A receiver operator curve (ROC) was used to investigate the showcards ability to predict anthropometric adiposity measures. The relationship between silhouette ranking and BMI were similar between sexes of the same country but differed between countries: 3.65 [95% CI: 3.34–3.97] BMI units/silhouette unit in the US, 3.23 [2.93–3.74] in Seychelles, and 1.99 [1.72–2.26] in Ghana. Different silhouette cutoffs predicted obesity differently in the three countries. For example, a silhouette ≥ five had a sensitivity/specificity of 77.3%/90.6% to predict BMI ≥ 25 kg/m2 in the US, but 77.8%/85.9% in Seychelles and 84.9%/71.4% in Ghana. Ultimately, silhouettes predicted BMI, WC, and WHtR similarly within each country and sex but not across countries. Our data suggest that Pulvers’ silhouette showcards may be a helpful tool to predict anthropometric and adiposity measures in different populations when direct measurement cannot be performed. However, no universal silhouette cutoff can be used for detecting overweight or obesity status, and population-specific differences may stress the need to calibrate silhouette showcards when using them as a survey tool in different countries.

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Zaki, Moushira Erfan. "Effects of Whole Body Vibration and Resistance Training on Bone Mineral Density and Anthropometry in Obese Postmenopausal Women." Journal of Osteoporosis 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/702589.

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Objective. The aim of this study was to evaluate the impact of two exercise programs, whole body vibration and resistance training on bone mineral density (BMD) and anthropometry in obese postmenopausal women.Material and Methods. Eighty Egyptian obese postmenopausal women were enrolled in this study; their age ranged from 50 to 68 years. Their body mass index ranged (30–36 kg/m2). The exercise prescription consisted of whole body vibration (WBV) and resistance training. Bone mineral density (BMD) and anthropometrical parameters were measured at the beginning and at the end of the study. Changes from baseline to eight months in BMD and anthropometric parameters were investigated.Results. BMD at the greater trochanter, at ward's triangle, and at lumbar spine were significantly higher after physical training, using both WBV and resistive training. Moreover, both exercise programs were effective in BMI and waist to the hip ratio. Simple and multiple regression analyses showed significant associations between physical activity duration and BMD at all sites. The highest values ofR2were found for the models incorporating WBV plus BMI.Conclusion. The study suggests that both types of exercise modalities had a similar positive effect on BMD at all sites in obese postmenopausal women. Significant association was noted between physical activity and anthropometric variables and BMD measures at all sites.

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Tian, Yu-Feng, Chi-Hong Chu, Mei-Hsuan Wu, Chia-Lin Chang, Tsan Yang, Yu-Ching Chou, Giu-Cheng Hsu, Cheng-Ping Yu, Jyh-Cherng Yu, and Chien-An Sun. "Anthropometric measures, plasma adiponectin, and breast cancer risk." Endocrine-Related Cancer 14, no. 3 (September 2007): 669–77. http://dx.doi.org/10.1677/erc-06-0089.

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Adiponectin is a peptide hormone secreted exclusively by adipocytes, and obesity is an established risk factor for breast cancer. We have, thus, evaluated the associations of anthropometric measures of adiposity and adiponectin with the development of breast cancer in a case–control study. Questionnaire information, anthropometric measures, and blood samples were taken before treatment from 244 incident cases with breast cancer, including 141 premenopausal and 103 postmenopausal cases, and 244 controls admitted for health examination at the Tri-Service General Hospital, Taipei between 2004 and 2005. Plasma levels of adiponectin were measured by RIA. The relationship between anthropometric measures of adiposity and breast cancer risk was modified by menopausal status, with a significant increase in risk observed in postmenopausal but not premenopausal women. Moreover, a fairly robust inverse association of adiponectin with the risk was observed only in postmenopausal women (adjusted odds ratio (OR), 0.55; 95% confidence interval (CI), 0.23–0.97), but not in premenopausal women. Additionally, the plasma adiponectin levels tended to be inversely associated with estrogen receptor (ER)-positive (adjusted OR, 0.53; 95% CI, 0.27–0.98) but not ER-negative breast tumors. Furthermore, the associations of adiponectin with breast cancer risk overall and by menopausal and ER status remained after adjustment for obesity indices. These results suggest that adiponectin may have an independent role in breast carcinogenesis, particularly in the postmenopausal and ER-positive breast cancer risk.

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Navaneethan, Sankar D., John P. Kirwan, Susana Arrigain, Martin J. Schreiber, Mark J. Sarnak, and Jesse D. Schold. "Obesity, Anthropometric Measures and Chronic Kidney Disease Complications." American Journal of Nephrology 36, no. 3 (2012): 219–27. http://dx.doi.org/10.1159/000341862.

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Farber, Scott J., Dennis C. Nguyen, Gary B. Skolnick, Sybill D. Naidoo, Matthew D. Smyth, and Kamlesh B. Patel. "Anthropometric Outcome Measures in Patients With Metopic Craniosynostosis." Journal of Craniofacial Surgery 28, no. 3 (May 2017): 713–16. http://dx.doi.org/10.1097/scs.0000000000003495.

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Moser, Deise Cristiane, Isabela de Carlos Back Giuliano, Ana Cláudia Kapp Titski, Anelise Reis Gaya, Manuel João Coelho-e-Silva, and Neiva Leite. "Anthropometric measures and blood pressure in school children." Jornal de Pediatria (Versão em Português) 89, no. 3 (May 2013): 243–49. http://dx.doi.org/10.1016/j.jpedp.2012.11.003.

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Kimmel, P. L. "Anthropometric measures, cytokines and survival in haemodialysis patients." Nephrology Dialysis Transplantation 18, no. 2 (February 1, 2003): 326–32. http://dx.doi.org/10.1093/ndt/18.2.326.

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Hunsaker, Darrell H., and Robert H. Riffenburgh. "Impact of Snoring on Anthropometric Measures of OSA." Otolaryngology–Head and Neck Surgery 137, no. 2 (August 2007): 362–63. http://dx.doi.org/10.1016/j.otohns.2007.05.004.

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Moser, Deise Cristiane, Isabela de Carlos Back Giuliano, Ana Cláudia Kapp Titski, Anelise Reis Gaya, Manuel João Coelho-e-Silva, and Neiva Leite. "Anthropometric measures and blood pressure in school children." Jornal de Pediatria 89, no. 3 (May 2013): 243–49. http://dx.doi.org/10.1016/j.jped.2012.11.006.

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Harke, Shubhangi M., Suresh P. Khadke, Abhijit A. Ghadge, Ashwini S. Manglekar, Shashank S. Shah, Arundhati G. Diwan, and Aniket A. Kuvalekar. "Adipocytokines and anthropometric measures in type 2 diabetics." Diabetes & Metabolic Syndrome: Clinical Research & Reviews 11 (November 2017): S273—S276. http://dx.doi.org/10.1016/j.dsx.2016.12.043.

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Burgess, Helen A. "Anthropometric Measures as a Predictor of Cephalopelvic Disproportion." Tropical Doctor 27, no. 3 (July 1997): 135–38. http://dx.doi.org/10.1177/004947559702700305.

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Lund, Eiliv, Hans-Olov Adami, Reinhold Bergstr�m, and Olav Meirik. "Anthropometric measures and breast cancer in young women." Cancer Causes and Control 1, no. 2 (September 1990): 169–72. http://dx.doi.org/10.1007/bf00053169.

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Arslan, Alan A. "Anthropometric Measures, Body Mass Index, and Pancreatic Cancer." Archives of Internal Medicine 170, no. 9 (May 10, 2010): 791. http://dx.doi.org/10.1001/archinternmed.2010.63.

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Ghosh, Arnab. "Discriminant analysis by anthropometric measures in elderly Bengalee Hindus of Calcutta, India." Anthropologischer Anzeiger 64, no. 1 (March 24, 2006): 91–96. http://dx.doi.org/10.1127/anthranz/64/2006/91.

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Edefonti, Alberto, Marina Picca, Beatrice Damiani, Rosanna Garavaglia, Silvana Loi, Gianluigi Ardissino, Giuseppina Marra, and Luciana Ghio. "Prevalence of Malnutrition Assessed by Bioimpedance Analysis and Anthropometry in Children on Peritoneal Dialysis." Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis 21, no. 2 (March 2001): 172–79. http://dx.doi.org/10.1177/089686080102100211.

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Objective To evaluate the sensitivity of anthropometry and bioelectrical impedance analysis (BIA) in detecting alterations in body composition of children treated with peritoneal dialysis (PD), and to determine the prevalence of malnutrition in this population, in short- and long-term PD duration, using anthropometric and BIA-derived indices. Patients Eighteen children treated with automated PD (11 males, 7 females; mean age 8.7 ± 4.7 years). Design Eighteen patients were studied using anthropometry and BIA at the start (t0) and after 6 months (t1) of PD, 15 of these patients at 12 months (t2), and 8 at 24 months (t3) of PD. Midarm muscle circumference (MAMC), arm muscle area (AMA), and arm fat area (AFA) were calculated from anthropometric measures according to Frisancho (FrisanchoAR. New norms of upper limb fat and muscle areas for assessment of nutritional status. Am J Clin Nutr 1981; 34:2540–5.). The bioelectrical measures of resistance (R) and reactance (Xc) were obtained directly from the impedance signal; phase angle (PA) and distance (D) were calculated using mathematical formulas. Nutritional status was assessed by anthropometric measurements and BIA-derived indices, expressed as standard deviation scores (SDS), and by a score system based on BIA and anthropometric parameters. The percentage of children with values of anthropometric and BIA-derived indices below the 3rd percentile or between the 3rd and 25th percentiles, and the percentage of children with scores of 7 – 12 and 4 – 6 were calculated in order to detect patients with severe or moderate derangement of nutritional status. Results The mean SDS values of Xc, PA, and D significantly improved ( p = 0.05, p = 0.001, p = 0.02) during the first 6 months of PD and remained almost stable during the following months. The SDS values of the anthropometric indices were less compromised than those of the BIA-derived indices, particularly at the start of dialysis. By 6 months, the percentages of children with values of BIA and anthropometric indices below the 3rd percentile had decreased. The percentages of patients with moderate and severe derangement of BIA and anthropometric indices remained substantially unchanged after 12 months. However, at 24 months, the percentage of patients with moderate derangement of BIA indices increased. All these findings were confirmed by the nutritional score system. Conclusion BIA is more sensitive than anthropometry in detecting alterations in body composition of children on PD. The prevalence of malnutrition, high at the commencement of PD, decreases during the first year of treatment but not over the long term.

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Detregiachi, Cláudia Rucco Penteado, Karina Quesada, Sandra M. Barbalho, Ricardo José Tofano, Jéssica Cambui Andreasi, and Laura Bergo Cantarim. "Relationship between obstructive sleep Apnea Syndrome and Anthropometric Measures." International Journal of Advanced Engineering Research and Science 6, no. 6 (2019): 43–46. http://dx.doi.org/10.22161/ijaers.6.6.4.

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Armbruster, Debra, Jonathan Slaughter, Michael Stenger, and Patrick Warren. "Neonatal Anthropometric Measures and Peripherally Inserted Central Catheter Depth." Advances in Neonatal Care 21, no. 4 (January 7, 2021): 314–21. http://dx.doi.org/10.1097/anc.0000000000000817.

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41

Abdelhamid, Enas R., Alyaa H. Kamhawy, Alshaimaa A. Elkhatib, Amr S. Megawer, Amal I. El Shafie, Yasmin G. El Gendy, and Dina E. A. Rabie. "Breast Milk Macronutrients in Relation to Infants’ Anthropometric Measures." Open Access Macedonian Journal of Medical Sciences 8, B (June 25, 2020): 845–50. http://dx.doi.org/10.3889/oamjms.2020.4980.

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BACKGROUND: Breast milk (BM) is the main nutritional source for newborns before they are capable to eat and consume other foods. BM has carbohydrates, lipids, complex proteins, and other biologically active components which have a direct effect on infant growth. AIM: The aim of the study was to correlate anthropometric data of the infant to macronutrients in BM (fat, protein, and carbohydrates) and to find some modifiable issues affecting macronutrient contents of BM for the benefits of upcoming infants. METHODS: One hundred breastfeeding mothers participated in the study, they were recruited from the outpatient clinic, El Demerdash Hospital, Ain Shams University, from September 2019, to December 2019. BM was expressed by an electric pump, macronutrient content was assessed. Anthropometric data of the babies and mothers were obtained, gestational age, parity, age of the women, and the route of birth were recorded. RESULTS: For the macronutrients content of milk, a positive significant correlation was observed between BM fat, protein, and lactose. Infants’ body mass index (BMI) was negatively related to the fat content of BM, while no relation was found between BMI and protein or lactose content of the milk. BM fat content was negatively correlated with gestational age and maternal age. Positive correlations were found between BMI and protein, lactose and infant age. Protein content was negatively correlated with parity. No impact of infant’s sex on BM composition and as regards maternal diet, high protein consumption leading to increase BM protein content. CONCLUSIONS: The current study confirms that BM macronutrient composition has a wide variability; this variability is associated with each macronutrient, respectively. To improve BM composition, one could aim for improving the nutritional balance in lactating women, especially for protein intake. More well-designed longitudinal studies about factors that influence human milk compositions are warranted.

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Kok Grouleff, Magnus, Maria Wielsøe, Dina Berthelsen, Gert Mulvad, Silvia Isidor, Manhai Long, and Eva Cecilie Bonefeld-Jørgensen. "Anthropometric measures and blood pressure of Greenlandic preschool children." International Journal of Circumpolar Health 80, no. 1 (January 1, 2021): 1954382. http://dx.doi.org/10.1080/22423982.2021.1954382.

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Preethi, B. L., and K. M. Prasannakumar. "Prediction of Insulin Resistance with Anthropometric Measures in Adolescence." International Journal of Physiology 5, no. 2 (2017): 43. http://dx.doi.org/10.5958/2320-608x.2017.00052.x.

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44

Fidelis, OP, B. Ogunlade, and SA Adelakun. "Anthropometric measures of young Nigerians for ergonomic furniture design." Journal of Biology and Medicine 3, no. 1 (September 20, 2019): 055–61. http://dx.doi.org/10.17352/jbm.000017.

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45

Beck, Stephanie R., W. Mark Brown, Adrienne H. Williams, June Pierce, Stephen S. Rich, and Carl D. Langefeld. "Age-Stratified QTL Genome Scan Analyses for Anthropometric Measures." BMC Genetics 4, Suppl 1 (2003): S31. http://dx.doi.org/10.1186/1471-2156-4-s1-s31.

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46

ITO, MASAK, KUNIAKI HAYASHI, MASATAKA UETANI, MIHO YAMADA, MASAFUMI OHKI, and TAKASHI NAKAMURA. "Association between Anthropometric Measures and Spinal Bone Mineral Density." Investigative Radiology 29, no. 9 (September 1994): 812–16. http://dx.doi.org/10.1097/00004424-199409000-00002.

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47

Durán-Agüero, Samuel, Ricardo Sepulveda, and Marion Guerrero-Wyss. "Sleep disorders and anthropometric measures in Chilean university students." Revista Española de Nutrición Humana y Dietética 23, no. 3 (March 9, 2020): 153. http://dx.doi.org/10.14306/renhyd.23.3.646.

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Introducción: El objetivo del estudio es comparar los hábitos de sueño, el insomnio y la somnolencia diurna en estudiantes universitarios según las medidas antropométricas.Material y métodos: Diseño del estudio: un estudio transversal, se llevó a cabo en estudiantes universitarios utilizando la escala de somnolencia de Epworth, el índice de calidad del sueño de Pittsburgh y el índice de severidad del insomnio. Además, se determinaron las variables antropométricas; peso, altura y circunferencia de la cintura.Resultados: Fueron evaluados 1275 estudiantes universitarios (74% mujeres). Los estudiantes en promedio dormían a la medianoche y en promedio 6,4 horas, el 77,9% dormía menos de lo recomendado, el 34,2% tenía somnolencia diurna y el 68,5% tenía insomnio. Con respecto al insomnio, se observó que el grupo de bajo peso presentaba la puntuación más alta de insomnio que contrastaba significativamente con el grupo de peso normal (p = 0,04). En el caso de la somnolencia diurna al comparar por IMC, se observa que los estudiantes con obesidad son las que presentan la mayor somnolencia (p <0.01). Hay una asociación entre menos horas de sueño con mayor IMC (OR: 1,12 (IC95%1,01-1,991)) y presencia de insomnio (OR: 2,734 (IC95%:1,324-5,645).Conclusión: los estudiantes universitarios duermen menos de lo recomendado, tienen una alta prevalencia de insomnio y somnolencia diurna excesiva, además, son las mujeres con obesidad presentan esta alteración con mayor frecuencia y se identifica el puntaje más alto de insomnio en estudiantes con bajo peso. Tanto un IMC elevado como el insomnio se asocian a sueño de corta cantidad.

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Borch, Knut H., Sigrid K. Brækkan, Ellisiv B. Mathiesen, Inger Njølstad, Tom Wilsgaard, Jan Størmer, and John-Bjarne Hansen. "Anthropometric Measures of Obesity and Risk of Venous Thromboembolism." Arteriosclerosis, Thrombosis, and Vascular Biology 30, no. 1 (January 2010): 121–27. http://dx.doi.org/10.1161/atvbaha.109.188920.

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Wong, E., K. Backholer, K. Pasupathi, C. Stevenson, H. Mannan, R. Freak-Poli, A. Hodge, and A. Peeters. "Anthropometric measures as predictors of long term physical disability." Obesity Research & Clinical Practice 5 (October 2011): 47. http://dx.doi.org/10.1016/j.orcp.2011.08.146.

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Santos, R. D. S., F. G. Carvalho, V. M. M. Suen, A. M. Navarro, J. S. Marchini, and O. Iannetta. "PP125 BETTER THE OSTEOSONOGRAPHIC RESULTS, BETTER THE ANTHROPOMETRIC MEASURES." Clinical Nutrition Supplements 5, no. 2 (January 2010): 72. http://dx.doi.org/10.1016/s1744-1161(10)70201-5.

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