Taking a look at the pros and cons of each method can help personal trainers make prudent decisions as to which one is best to use based on their capabilities, proficiency, client needs and limitations, as well as assessment environment.

Circumference Measurements Implementing circumference measurement protocol involves measuring the circumference of designated locations and then calculating body density based on the positive linear relationship between the circumference values.

Note that simply measuring waist circumference alone has been shown to be one of the best predictors of disease risk as it examines the accumulation of visceral adipose tissue. PROS Circumference measurements are relatively non-invasive providing a lower psychological impact. It is also considered useful for elderly clients due to fat re-distribution during the aging process subcutaneous to visceral.

Many people think in inches and look at being able to fit into in-fashion clothing or those that once fit , so looking at circumference values can be a tangible way to easily perceive progression and success of a program aimed at weight loss.

Circumference measurements provide regional fat storage data which takes a look at disease risk, and is very easy to perform making it one of the preferred methods for larger clients and is a great option for new and inexperienced personal trainers. CONS Circumference measurements have a reduced level of accuracy for lean and muscular clients.

The assessment will over-predict muscular individuals as the assessment does not differentiate between muscle and adipose tissue directly. A reference value such as the neck or elbow breadth is often used for genetic size prediction.

Skinfold Measurements The sum of skinfold measurements taken at a varying number of designated sites 3, 4, or 7 based on gender is placed in a population specific regression equations to predict body density and body fat.

It assumes that subcutaneous fat is predictive of overall body fat percentage. PROS Skinfold measurements have been shown to be fairly accurate for leaner subjects with a standard estimate of error of 3. Limited and economical equipment is needed, and the assessment can be performed quickly once the trainer is proficient in the protocol in almost any environment.

Even with reduced accuracy when compared to the gold standard of hydrostatic weighing, skinfold asessment can be a reliable method to look at progression of weight loss.

CONS Skinfold measurements are not an optimal or even appropriate choice for obese clients. However, measurements of bioelectric impedance indicate that they may vary depending on the time of day when measurements are carried out.

Moreover, if food intake has been increased before measurements, the final value may also be higher. As food can affect the result it is the same with caffeine and alcohol. Another important aspect is physical activity which can lead to changes in water content of the body as well as to dehydration.

These methods are some of the most commonly used methods for simple field measurements. Although both methods have their shortcomings there is no need to exclude these methods from the measurement program. If the protocol is followed and the measurer is experienced both methods can give satisfactory results.

Blog Post. by Filip Sabol October 31, MEASURING SKIN FOLDS Measuring body composition with caliper can be done in several ways. Related Posts. Each method has its own limitations and applicability, but both are uncomplicated, practical, inexpensive and easy to administer particularly in epidemiological studies.

The paper was presented at 53 rd IDACON — Virtual International Conference of Indian Dietetic Association. HT was supported by a Junior Research Fellowship from the University Grants Commission, Government of India.

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Close Current Research in Nutrition and Food Science - An open access, peer reviewed international journal covering all aspects of Nutrition and Food Science Register for an account. Sayyad 3 1 Symbiosis School of Biological Sciences, Symbiosis International Deemed University , Pune, India.

Article Metrics PDF Downloads: Introduction Body composition measurements are quantitative methods of nutritional assessment in humans. Materials and Methods This report is a part of the PMS study which investigated association of premenstrual syndrome with various lifestyle factors among young women.

Statistical Analysis Statistical analysis was carried out in SPSS software v. Results In total female students participated in the study.

Table 1: Anthropometric Measurements and Body Composition Parameters. Measurement Mean SD Range Anthropometric measurements Height cm Click here to view Figure Discussion Currently adiposity is used as a marker to define the obesity rather than relation of body weight to body height which is BMI.

Acknowledgment The paper was presented at 53 rd IDACON — Virtual International Conference of Indian Dietetic Association. Funding Source HT was supported by a Junior Research Fellowship from the University Grants Commission, Government of India.

Conflict of Interest The authors declare no conflict of interest. References Kuriyan R. Body composition techniques.

Indian Journal of Medical Research. CrossRef Thibault R, Genton L, Pichard C. Body composition: why, when and for who?. Clinical Nutrition.

CrossRef Andreoli A, Garaci F, Cafarelli FP, Guglielmi G. Body composition in clinical practice. European Journal of Radiology. CrossRef Chahar PS. Comparison of Skinfold Thickness Measurement and Bioelectrical Impedance Method for Assessment of Body Fat.

World Applied Sci J. Bhat D. Body fat measurement in Indian men: comparison of three methods based on a two-compartment model. International Journal of Obesity. DOI: CrossRef World Health Organization.

Waist circumference and waist-hip ratio: report of a WHO expert consultation, Geneva. Accessed on 24 January Durnin J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on men and women aged from 16 to 72 years.

British Journal of Nutrition. CrossRef Borga M. Advanced body composition assessment: from body mass index to body composition profiling. Journal of Investigative Medicine. CrossRef Brand R. Editorial: Standards of Reporting: The CONSORT, QUORUM, and STROBE Guidelines.

Clin Orthop Relat Res. CrossRef Bland J. Statistical methods for assessing agreement between two methods of clinical measurement. CrossRef WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies [published correction appears in Lancet.

CrossRef Lavie CJ, Milani RV, Ventura HO, De Schutter A, Romero-Corral A. Use of body fatness cutoff points—reply—I. InMayo Clinic Proceedings 1;85 11 : CrossRef Alvero-Cruz J. Body fat assessment by bioelectrical impedance and its correlation with anthropometric indicators.

Nutricion Hospitalaria. Gibson RS. Anthropometric assessment of body composition. In: Principles of nutritional assessment.

And not only can they measure body fat percentage, but some devices give a complete body composition analysis. These medical BIA devices give important metrics like visceral fat, skeletal muscle mass, muscle distribution, BMR, and more. This body composition test was taken on the InBody Click here for more information.

Hopefully, this helps you understand a little more about calipers. Although they can be so quick and simple to use, they do have significant drawbacks when accurate results are essential. Disclaimer: Please be aware that your actual monthly payment liability is subject to change based on the amount financed, which is at the financer's discretion and that the amount shown here is merely an estimate and does not include applicable federal and sales tax.

Hit enter to search or ESC to close. Close Search. Health InBody Blog 4 Reasons Calipers Fail to Give Accurate Body Fat Results By InBody USA August 8, October 14th, No Comments. It was originally published on July 2, The 7 sites on the body are shown here: Each of these sites must be located precisely on the body, and an X should be drawn on the skin to ensure proper jaw placement.

Today these assumptions can be quite large. The writers argue emphasis added , There can be little doubt, the Jackson and Pollock body fat equations for men, and the Jackson et al.

Alternatives Fortunately, advances in technology have made finding precise body fat percentage and body composition results much easier. Tags: Calipers. Love 1 Share Tweet Share Pin.

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Anthropometrica: A Textbook of Body Measurement for Sports and Health Courses. Australian Sport Commission, Ed. Sydney, Australia. a, de Oliveira, G. Technical error of measurement in anthropometry.

Revista Brasileira de Medicina Do Esporte , 11 , 81— A physical profile of elite female ice hockey players from the USA. Body fat measurement in elite sport climbers: Comparison of skinfold thickness equations with dual energy X-ray absorptiometry.

Journal of Sports Sciences , 27 5 , — com Follow up your progress using a technique to measure the muscle cross-sectional area. Retrieved from www. php on March 31, Schmidt, P. Static and Dynamic Differences among Five Types of Skinfold Calipers Author s : Paul K.

Schmidt and J. Journal of Human Biology , 62 3 , — Siri, W. Body composition from fluid spaces and density: analysis of methods. Techniques for Measuring Body Composition.

Washington: National Academy of Sciences , — Stewart, A. International Standards for Anthropometric Assessment. International Society for the Advancement of Kinanthropometry.

Souffir, C. Évaluation de la mesure de la graisse viscérale abdominale dans les rhumatismes inflammatoires chroniques polyarthrite rhumatoïde et spondyloarthropathies. Médecine humaine et pathologie.

Tanda, G. Marathon performance in relation to body fat percentage and training indices in recreational male runners. Open Access Journal of Sports Medicine , 4 , —9. S Topend Sports Skinfold Caliper Guide.

htm on March 31, Wang, J. Anthropometry in Body Composition: An Overview. Annals of the New York Academy of Sciences , 1 , — x Wells, J. Measuring body composition. Archives of Disease in Childhood , 91 7 , — Body fat throughout childhood in healthy Danish children: agreement of BMI, waist circumference, skinfolds with dual X-ray absorptiometry.

European Journal of Clinical Nutrition , 68 6 , — More content by Carla. Access our course on Agility for FREE! Get Instant Access.

Why we exist Our mission is to improve the performance of athletes and teams around the world by simplifying sports science and making it practical. Second, differences between the intervention and control group in changes in body weight, BMI, skinfold thickness and waist circumference at 12 and 24 months were examined using linear regression analyses adjusting for various baseline characteristics age, gender, BMI, marital status, education and smoking status.

The measurements were repeatedly obtained for the same subjects, nested within several worksites, yielding a three level design. To deal with possible dependencies in the measurements across time due to being obtained for the same worksites and persons, the multilevel linear regression analyses were conducted in MlwiN employing a random intercept that varies both at the level of worksites and at the level of persons [ 18 ].

By including the baseline measurement of the outcome variable in the analysis as one of the measurements at the lowest level, combined with a specific coding for the effect of time, differences of outcomes with baseline are analysed, in this way correcting for differences between the intervention groups at baseline.

In this analysis the unstandardized regression coefficient B for the interaction between time and the intervention factor represents the intervention effect on such change scores.

The analysis model is comparable to a repeated measures ANOVA adjusted for baseline for follow-ups at 12 months and at 24 months, however there being no random interaction effects with time. Adjustments for the baseline value of age, gender, BMI, marital status, education and smoking status were made, by including these variables as covariates in the analysis.

Thirdly, Cohen's d effect sizes were calculated in order to calculate the magnitude of the intervention effect; d is defined as the difference between two means divided by the pooled standard deviation in the population.

Fourth, potential interaction effects of the intervention group with gender, age and BMI were explored. If significant interactions occurred analyses were repeated with stratification by gender, age, or BMI.

Fifth, two types of intraclass correlation coefficients ICCs were calculated for each of the four outcome measures. The ICC on worksite-level is the random intercept variance at worksite-level divided by the total variance and thus reflects the degree to which differences on outcome measures can be explained by random effects of the worksites.

The ICC on person level is the random intercept variance at worksite level plus the random intercept variance at person level divided by the total variance, thus reflecting to what extent differences on outcome measures can be explained by random effects of worksites and individuals [ 20 ].

The number of participants who were not measured at 12 and 24 months was 71 The most common reasons for discontinuation were change of occupation, conflict with workload and stress-related issues.

The dropout analyses revealed some selective dropout. Baseline characteristics of the control and intervention group are described in table 1. Participants from the intervention group were older and had a higher BMI than participants from the control group Apart from these differences groups did not differ in terms of baseline characteristics.

Changes in skinfold thickness, waist circumference, body weight and BMI for the two groups over 12 and 24 months are depicted in table S1 additional file 1.

A greater reduction in sum of skinfolds was observed for participants in the intervention group than for participants in the control group. Participants from the intervention group reduced their waist circumferences over time in comparison to an increase in the control group.

Changes in weight and BMI however did not differ significantly between the two groups neither at 12 nor at 24 months. Although changes in weight and BMI were not statistically significant, they were in favour of the intervention group. The corresponding Cohen's d 's were all smaller than 0.

Significant interaction terms were found for the changes in skinfold thickness table 2. No significant effects were observed among men.

Data collected by observation and registration of activities revealed that four of the six worksites implemented environmental interventions.

All four worksites placed posters near the elevators and stairs to stimulate stair use over a 3-week period [ 21 ] and provided general information on the project. Two hospital, paper-factory of these four worksites formed worksite linkage boards and implemented more environmental interventions, which included making the NHF-NRG In Balance-project visible through articles in the worksite personnel magazine or through intranet.

The hospital organized several special events: a 1-week placement of an 'information wall' containing information on the balance between food intake and physical activity in addition to the presence of a health professional who took waist circumference measurements and gave advice.

This worksite also handed out free apples during National Health Week, together with information booklets and maps and walking routes that were located around the hospital.

Moreover, they made their personnel aware of the hospitals physical activity facilities, e. squash, aerobic classes, bikes to borrow. After the 2-year period the hospital was in negotiation regarding a specific bike-scheme. The paper-factory organized a series of workshops given by a dietician on healthy eating, distributed pamphlets on physical activity and information regarding special offers at local sports facilities.

The present study was designed to test the and month effectiveness of the NHF-NRG In Balance-project, with regard to changes in body weight, BMI, sum of skinfolds and waist circumference.

The results indicate that with regard to changes in sum of skinfolds and waist circumference the project was indeed effective at both 12 and 24 months. Even though changes in weight and BMI between the intervention and control group were not significantly different, they did change in the desired direction.

Overall, the intervention of the NHF-NRG In Balance-project had a positive effect on the body composition measures of the individuals in the intervention group.

The interpretation of effect sizes of Cohen's d imply effects of medium magnitude for the changes in skinfold thickness and waist circumference both after 12 and 24 months Cohen's d between 0.

Such changes in body composition indicators may have important health implications, as it has been demonstrated that the health risks associated with obesity derive primarily from fat rather than weight [ 22 ].

Moreover, it is not only the total amount of fat that is important, but also the distribution of fat in the body [ 23 ], with central fatness being most related to health risks [ 24 ]. The reduction in skinfold thickness and waist circumference observed in the present study reflects a reduction in central fatness [ 22 , 25 ].

The decrease in waist circumference is most relevant, as a large waist circumference is independently associated with health risks [ 26 , 27 ] and mortality [ 28 , 29 ].

On a population level it has even been shown that there is a more significant trend of increases in waist circumference over time than BMI [ 30 ]. With regard to changes in waist circumference it has been demonstrated that an increase in fibre intake was associated with a reduction in waist circumference in men [ 31 ].

A strong dose-response relationship has also been observed between the amount of exercise and measures of central obesity [ 32 ]. Interestingly, changes in physical activity can lead to changes in body composition, which may be reflected in changes in waist circumference, while body weight remains stable through increased muscle mass [ 33 , 34 ].

This is in line with the findings of the present study. Stratified outcome analyses were interesting.

It appeared that the intervention only had an effect on the changes in skinfold thickness in women and not in men. It would be interesting to see if this is a result of the engagement in different energy balance-related behaviours of men and women.

The process evaluation of the environmental interventions showed that two worksites formed a worksite linkage-board, who implemented several environmental interventions throughout the two year period. When taking baseline characterises into consideration, the individuals in these two worksites appeared to show better results with regard to changes in waist circumference and sum of skinfolds than individuals in worksites with fewer components to the intervention both after 12 and 24 months data not shown.

Although the study was not powered to significantly detect these between-worksite differences, this finding does underscore the importance of intervening on both the individual and the environmental level.

Moreover, it showed that the context of the worksites did not affect the uptake of the intervention, as one of these two worksites had predominantly white-collar workers and the other blue-collar.

This finding as worksite-health promotion programs are often less likely to result in health behaviour change in blue-collar workers [ 35 ]. The NHF-NRG In Balance-project is one of few worksite obesity prevention programmes, which 1 is primarily aimed at weight gain prevention through changes in both food intake and physical activity, 2 contains both individual and environmental components and 3 assesses longer-term follow-up effectiveness.

A recent review of papers on lifestyle interventions aimed at prevention of overweight and obesity, with primary programme objective weight management, prevention of weight gain or moderate weight loss among adults, included four additional studies to the present study, in which workplace interventions were evaluated.

Two of these studies included behavioural goals that were aimed at both diet and physical activity; three included both cognitive and environmental goals and two studies assessed effectiveness after a 12 month follow-up. Significantly smaller increases in BMI in the intervention conditions were observed in one study; no treatment effect for weight or BMI changes was found in the others.

Two of the studies also included measurements on percent body fat, both of which observed significantly positive effects [ 36 ]. These findings are in line with those observed in the present study. To date, there has been an increase in the number of worksite obesity prevention studies that are testing environmental or combined environmental-and individual-level worksite interventions over a longer period of time, e.

However results regarding effectiveness have not yet been published. In the present study, we perceived several benefits of implementing the intervention within a worksite setting. Firstly, the worksites provided access to a large number of adults with different educational backgrounds.

Moreover, the employees within the worksites are able to play an important role in diffusing the intervention throughout the worksite by impacting social norms, which in the long-term may influence the behaviours of co-workers who did not change their behaviour initially [ 38 ].

Difficulties were perceived with regard to enhancing facilitators of environmental changes, as only two of the six worksites set up a worksite-linkage board. As the linkage boards play a crucial role in the adoption, implementation and institutionalization of the environmental components, strategies should be developed to mobilize support and commitment for the formation of such boards.

There are a number of limitations of this study, including those concerning the generalizability. An important reason for companies not to participate in the NHF-NRG In Balance-project proved to be the randomized evaluation design of the programme, implying that companies were not willing to take the risk of being excluded from the intervention [ 16 ].

We were therefore forced to drop the original randomization design of the programme and assign worksites to the experimental and control group based on matching. As a result of which it is possible that selection bias occurred, weakening the internal validity of the results. Moreover, external validity was weakened by the fact that participating worksites were most likely not representative of the average worksite, in that the participating worksites probably showed a higher interest in health promotion than worksites in general.

Implementing the project in less interested worksites might not have generated the same results. A second limitation of the present study is the recruitment of participants.

Even though the aim of the project was to prevent weight gain in young adults, there was a relatively high response of older and overweight individuals, in line with observations of other studies [ 27 , 28 ].

This may have resulted in a selection bias, in which individuals who were more interested to change the targeted behaviours were oversampled. Moreover, there was a high response of participants with a tertiary education. The third limitation concerns the statistical analysis, although sophisticated multilevel analyses were executed in this study, the statistical procedures may not fully account for all potential dependencies that were introduced as a result of the research design.

For example, our statistical model contained only one random component for worksite, implying that every worksite is assumed to have exactly the same response to the intervention if in intervention or to the control situation if in the control condition.

The fourth limitation pertains to the process evaluation; unfortunately we were unable to perform an in-depth analysis regarding the uptake of interventions by the individuals. The fifth limitation is related to the absence of a significant difference in weight changes over time between both groups.

However, weight changes observed in the control group were smaller than those expected, with smaller weight change differences between the groups 0. The smaller increase in weight in the control group is most likely a result of measurement effects.

However, it could also be a result of a selection bias; the control group might have consisted of more motivated individuals who are susceptible to change.

Moreover, it is possible that those individuals who dropped-out were those with a higher BMI. The findings presented here show the effectiveness of the NHF-NRG In Balance-project and support the value of using workplace settings for maintenance of behavioural changes in the area of weight gain prevention.

Additionally, it underscores the importance of systematically developing an intervention that contains both individual and environmental components and is directed at changing both physical activity and dietary behaviour.

Furthermore, the results support the notion that more attention needs to be given to generating interest in weight management both among worksites and among individuals who are at risk of weight gain.

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