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Skinfold measurement errors and precautions

Skinfold measurement errors and precautions

No Healing vegetable power Skinfold measurement errors and precautions were observed for weight and BMI. Skinfkld individual hand ans of skinfolds vary, MRI SI data resembled the Caliper values 1. Get the most important science stories of the day, free in your inbox. I assumed the discrepancy was due to water fluctuation, is that correct?

Skinfold measurement errors and precautions -

In this case averaging the results would not produce an accurate result. Instead, systematic errors must be reduced by improving methods or equipment. For example, using the displacement method instead of calipers would improve the accuracy of the body fat percentage measurement.

These issues are part of why the caliper method is slowly going out of favor for determining body fat percentage. To summarize: Systematic errors reduce accuracy and increase discrepancy while random errors reduce precision and increase measurement uncertainty.

Random errors also affect accuracy, but the effect can be reduced by averaging more measurements. A stadiometer center photograph is used to measure stature natural height of a person standing upright. method for measuring body fat percentage using specially designed calipers to measure the thickness of skinfolds that are pinched from several specific locations on the body as inputs to empirical equations.

Measurement Error also called Observational Error is the difference between a measured quantity and its true value. It includes random error naturally occurring errors that are to be expected with any experiment and systematic error caused by a mis-calibrated instrument that affects all measurements.

random errors are fluctuations in both directions in the measured data due to the precision limitations of the measurement device. Random errors usually result from the experimenter's inability to take the same measurement in exactly the same way to get exact the same number.

an error having a nonzero mean average , so that its effect is not reduced when many observations are averaged. Usually occurring because there is something wrong with the instrument or how it is used.

Body Physics: Motion to Metabolism Copyright © by Lawrence Davis is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4. Skip to content The Skinfold Method The skinfold caliper method is one way to determine body composition.

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.

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Products Professional Body Composition Analyzer InBody InBody InBody InBody Body Water Analyzer BWA 2. Financing Options. Term Length. She didn't like the result I had, so she asked one of the strength coaches to perform the skinfold. He performs the test, telling me that you have to "wiggle the calipers" when you perform the test which you aren't supposed to do.

Well, all he was doing was wiggling some of the skinfold out from between the calipers, and of course he came up with a lower number than I did simply by using an incorrect technique. Another source of error is in the equation used to predict body density.

The Jackson-Pollock equation is one of the most common equations used with skinfolds. However, an equation is only valid when testing people similar to the people used to develop the equation in the first place. For example, the male version of the Jackson-Pollock equation was developed on men between the ages of 18 and 61 years of age.

Thus, the prediction accuracy falls off when you get outside of this age range. Also, the Jackson-Pollock equations were developed on white men and women; however, as I pointed out in my article on hydrostatic weighing , the density of fat-free mass can change depending upon your race. Thus, there will be greater error when using the Jackson-Pollock equation if you are not white.

Therefore, it is critical that, if you do use skinfolds for body fat estimation, you use an equation that was specifically developed for your race, age, and gender. Another problem we have is similar to the problem we had with BIA.

Like with BIA, skinfold testing is a prediction based off of a prediction. Skinfold testing equations, like the Jackson-Pollock equation, were developed off of hydrostatic weighing measurements which themselves are predictions with error. Finally, we have the same problem that we have with all 2-compartment models the assumption that fat-free mass has a certain density.

As I pointed out in the article on hydrostatic weighing , the density of fat-free mass can change with changes in body weight, which will introduce error when measuring a change in body fat over time.

Skinfolds can have pretty sizeable errors when compared to a 4-compartment model, whether you're looking at group averages or individuals. For men, the error rates were no better. And what about measuring change over time? Similar average and individual error rates were seen in a study on bodybuilders.

Like BIA, skinfolds can be way off when it comes to determining body fat percentage in individuals. When it comes to tracking change over time in groups, then skinfolds do pretty well. Thus, if you are going to use skinfolds for tracking a single person over time, I recommend very long time intervals between measurements minimum of 3 months but 6 months is better ; otherwise, the error rate is higher than the change that you can see.

In fact, I recommend against even calculating a body fat percentage. If skinfold thicknesses are going down, then you are likely losing fat. That sums it up for the most widely used 2-compartment models for testing body fat.

Click here to read Part 6 of this series , where I discuss dual-energy x-ray absorptiometry DEXA , a 3-compartment model for estimating body composition Get Instant Access to Free Research Reviews!

Hi there. Since August I have being dieting hard to prepare for my first body building contest in June.

International Journal of Behavioral Nutrition and Physical Activity snd 7Article measyrement 26 Cite this article. Precaurions details. More knowledge is needed Skinfold measurement errors and precautions the effectiveness of weight gain prevention programmes. The present study tested the and month effectiveness of the 'Netherlands Research programme weight Gain prevention' NHF-NRG -In Balance-project, a worksite-based intervention aimed at the prevention of weight gain. The worksites and employees of the intervention group received individual i.

Skinfold measurement errors and precautions -

Anthropometry in body composition. An overview. Annals of the New York Academy of Science, , Wells, J. Toward Body Composition Reference Data for Infants, Children, and Adolescents. Advances in Nutrition: An International Review Journal, 5 3 , SS. Wohlfahrt-Veje, C.

Main, K. Body fat throughout childhood in healthy Danish children: agreement of BMI, waist circumference, skinfolds with dual X-ray absorptiometry. Body composition defined most broadly refers to the proportions of fat mass FM and fat-free mass FFM or lean body mass LBM but also encompasses a related concept of regional body fatness.

With an increase in FM or adiposity, there may be changes in the relative distribution of fat, for example, toward visceral or dorsal deposits and away from limb fat.

Regional distribution of fat also changes normally with maturation and differentially between sexes; changes that may be aggravated by overweight or obesity. Early identification of patterns of regional fatness that may be associated with risky profiles is also encouraged.

The study of body composition looks at the differences in bone, muscle, organs, and fat. Body composition analysis is an indicator of overall health as determined by a person's percentage of fat and lean mass.

Body composition tests are designed to give a "whole picture" of the body, but measures can also be used to estimate regional fat distribution.

This information is useful to help develop nutrition and exercise programs to benefit the individual and to assess risk for later-life chronic diseases. body composition - triceps skinfold thickness, Anthropometrics, body fat, body mass index, BMI, obesity lean body mass, muscle mass, fat body mass, diabetes, bone density, bone mineral density, BMD, body fat, bone mass, fat mass, skinfold thickness, BIA, metabolic syndrome, DEXA, DXA, NHANES.

Sitarik, A. International Journal of Obesity. Chia, A. Scientific Reports. Aris, I. Int J Epidemiol. Pediatr Obes. Ong, Y. Br J Nutr. Advanced Search. Browse Protocols Browse Tree.

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Home Protocols Browse Protocols Browse Tree. Protocol - Body Composition - Triceps Skinfold Thickness. Related Protocols: Hip Circumference - Hip Circumference Waist Circumference - Framingham Heart Study Waist Circumference - Waist Circumference NCFS Waist Circumference - Waist Circumference NHANES Select Hip Circumference - Hip Circumference Waist Circumference - Framingham Heart Study Waist Circumference - Waist Circumference NCFS Waist Circumference - Waist Circumference NHANES Essential Protocols: Current Age Ethnicity and Race Gender Identity Height - Knee Height Height - Recumbent Length Height - Self-Reported Height Height - Standing Height Sex Assigned at Birth Weight - Measured Weight Weight - Self-Reported Weight Select Current Age Ethnicity and Race Gender Identity Height - Knee Height Height - Recumbent Length Height - Self-Reported Height Height - Standing Height Sex Assigned at Birth Weight - Measured Weight Weight - Self-Reported Weight Studies Using This Protocol: ECHO NHANES ECHO NHANES.

Add to My Toolkit Menu Functions Download Protocol in PDF DCW in Word DD in RTF DD in CSV REDCap Instrument ZIP Download. Protocol Administration Details Source Variables Measure Publications Description Measurement of the study subject subcutaneous fat mass using calipers to measure skinfold thickness over the triceps muscle.

Specific Instructions There are several overarching, critical issues for high-quality data collection of anthropometric measures that optimize the data in gene-environment etiologic research. Upper Arm Length 1. After marking the arm, the participant can relax his or her arm.

Record the result. Remove the caliper jaws first and then release the skinfold. Exhibit 5. Location of triceps skinfold. htm Equipment Needs Skinfold caliper, the type of caliper used should be recorded. Selection Rationale Throughout all of the cycles where skinfolds were collected, National Health and Nutrition Examination Survey NHANES kept to a rigorous training and reliability schedule for their anthropometrists, and the NHANES protocols are consistent with best practices in the field.

Guidance from the ERP includes: • Added a new protocol • New Data Dictionary. Protocol Name from Source National Health and Nutrition Examination Survey NHANES , Anthropometry Procedures Manual, Source Centers for Disease Control and Prevention CDC , National Center for Health Statistics NCHS.

pdf General References Addo, O. show less. right scapula by following the scapula out to the arm until it makes a sharp V-turn to the front of the body, using a cosmetic pencil, was a horizontal line made at the uppermost edge of the posterior border show less.

at the horizontal line mark, was a measurement taken by extending the tape down the posterior surface of the arm to the tip of the olecranon process the bony part of the elbow, exhibit 2?

half, was a horizontal mark made at the mid-point? the nearest 0. circumference mark, were the tips of the calipers placed over the complete skinfold? circumference mark, was the caliper handle released to exert full tension on the skinfold for at least 3 seconds before a measurement was taken?

use of and have access to required and properly calibrated equipment? acquire an accurate recording of the protocols and measurements units of data collection?

fold of skin and subcutaneous adipose tissue grasped approximately 2. upright with weight evenly distributed on both feet, right arm bent 90 degrees at the elbow, and the right palm facing up? upright with weight evenly distributed on both feet, shoulders relaxed, and arms hanging loosely at the sides?

or retraining in anthropometric data collection? Anthropometrics Measure Name Body Composition Release Date October 1, Definition Body composition defined most broadly refers to the proportions of fat mass FM and fat-free mass FFM or lean body mass LBM but also encompasses a related concept of regional body fatness.

Keywords body composition - triceps skinfold thickness, Anthropometrics, body fat, body mass index, BMI, obesity lean body mass, muscle mass, fat body mass, diabetes, bone density, bone mineral density, BMD, body fat, bone mass, fat mass, skinfold thickness, BIA, metabolic syndrome, DEXA, DXA, NHANES Measure Protocols Protocol ID Protocol Name Body Composition - Body Composition by Dual-Energy X-Ray Absorptiometry Body Composition - Triceps Skinfold Thickness Body Composition - Subscapular Skinfold Thickness Body Composition - Suprailiac Skinfold Thickness.

Publications Sitarik, A. View Image ×. caDSR Form. Is the team adequately staffed so that more more than one person is available for proper collection of measurements where required? After locating the end of the spine of the more right scapula by following the scapula out to the arm until it makes a sharp V-turn to the front of the body, using a cosmetic pencil, was a horizontal line made at the uppermost edge of the posterior border show less.

Holding the zero end of the measuring tape more at the horizontal line mark, was a measurement taken by extending the tape down the posterior surface of the arm to the tip of the olecranon process the bony part of the elbow, exhibit 2? After dividing the taken measurement in more half, was a horizontal mark made at the mid-point?

What was the thickness of the skinfold to more the nearest 0. While holding the skinfold 2. Has the staff been properly trained in the more use of and have access to required and properly calibrated equipment? Has the staff been properly trained to more acquire an accurate recording of the protocols and measurements units of data collection?

Using the thumb and index finger, was the more fold of skin and subcutaneous adipose tissue grasped approximately 2.

Was the participant instructed to stand more upright with weight evenly distributed on both feet, right arm bent 90 degrees at the elbow, and the right palm facing up? Then, pinch the skin between your thumb and index finger, and attach the jaws of the calipers to the area.

Next, press down on the calipers where indicated with your thumb until you hear a click, which means the measurement has been recorded. You should repeat this process 3 times in each spot for accuracy and write down each result. For tips on how to use the measurements to calculate your body fat, keep reading!

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wikiHow Account. No account yet? Create an account. wikiHow is where trusted research and expert knowledge come together. Learn why people trust wikiHow. Categories Health Nutrition and Food Health Weight Management How to Use Body Fat Calipers.

Download Article Explore this Article parts. Tips and Warnings. Things You'll Need. Related Articles. Article Summary. Co-authored by Michele Dolan Last Updated: February 11, Fact Checked. Part 1. Enlist professional help to get the most accurate results. Experience counts when using skinfold calipers because the accuracy of the test depends on precision of measurement.

Ask a friend to help. If a professional is not administering your test, keep in mind that collecting measurements from certain points, such as your back, may be difficult — if not impossible — on your own.

Learn how calipers work. Body fat calipers do not measure body fat percentage directly. The accuracy of skinfold calipers for measuring body fat percentage depends on both the experience of the person using the calipers and the formula used to compute the results.

Select a sensible formula. There are over equations used to calculate body fat percentage from a pinch test. Each is specific to groups of people according to characteristics such as age, gender, race, and fitness level, which affect where bodies tend to store adipose fat.

Plugging in the same data to several different equations can return results that vary by several percentage points. To choose a formula that makes sense for you, work with a fitness professional and use it as a benchmark of your progress.

Or, forgo the formula completely and just keep track of the skinfold measurements. Track your progress. At the start of a fitness regimen to reduce your body fat percentage, it is useful to get a baseline measurement. Keep this information in a log personal training journals and fitness apps are good options along with your exercise routine e.

Recommended ranges for a healthy percentage of body fat differ according to gender, age, and fitness level. If you want to maintain your current body fat composition, monthly measurements may be more useful. Get a set of skinfold calipers. There are many types of calipers available on the consumer market.

Ideally, an experienced examiner is administering the pinch test for you and has good-quality calipers.

If you are administering the test yourself, you can purchase calipers at many different price points from a few dollars to a couple hundred and from many different retailers. You may want to invest in high-quality calipers, which will be more expensive.

Cheap calipers may not exert the appropriate amount of constant pressure necessary to provide adequate tension control and reliable results.

Some highly recommended calipers include Harpenden Skinfold Calipers, Lafayette Skinfold Calipers, Lange Calipers, Slim Guide Skinfold Calipers, and Accu-Measure Body Fat Calipers.

Part 2. Choose a test. Pinch tests measure skinfolds at three, four, seven, and even ten points on the body. Taking measurements from more points does not ensure accuracy of the body fat percentage calculation.

That depends on the precision used when taking the measurements and the formula used to calculate body fat. Identify the points at which you'll take measurements.

The key is to be consistent with the exact locations as well as pinch-type vertical vs. In general, the right side of the body on a standing subject is used when obtaining measurements. Common areas to measure skinfolds include: [10] X Research source Triceps — Have the subject bend the elbow to 90 degrees and mark the point midway between the top of the shoulder and elbow.

Iliac crest — Have the subject hold their right arm across the body. Use a horizontal pinch to take this measurement right above the hip bone on the side of the body. Calf — With the foot resting on a chair or platform at approximately 90 degrees, take the measurement as a vertical fold on the inside of the calf at the point with the largest circumference.

A measurement here should be taken as a vertical fold directly under the center of the armpit and perpendicular to the nipple.

The PhenX Measjrement uses cookies to offer you the best Skinfold measurement errors and precautions online. By Insulin pump features to use our website, Measudement agree to the use of cookies. If you would like to know more about cookies and how to manage them please view our Privacy Policy. Home » Protocols » Body Composition - Triceps Skinfold Thickness. Measurement of the study subject subcutaneous fat mass using calipers to measure skinfold thickness over the triceps muscle.

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Skin Fold Measurements

In this precautoins series on body abd testingyou've Skinfold measurement errors and precautions that it can be highly inaccurate in individuals, whether for a one-time measurement, or when measuring Targeted fat distribution over time.

So far you've errora about hydrostatic weighingthe Bod Pod Fitness motivation, and BIA. Now Green tea anti-inflammatory talk about skinfolds.

Measuremetn testing involves taking xnd device known as erorrs caliper, pinching the skin Organic athletic supplements fat underneath the skin known as subcutaneous fat Skijfold, pulling the skinfold away Herbal medicine for longevity the Hydration solutions for long flights muscle, and measuring the thickness of precautinos skinfold with the caliper.

This is done at numerous sites Skinfolv the body Belly fat burner for postpartum separate sites. The skinfold thicknesses are Skihfold added together, and plugged into an equation along with your precaufions.

The equation spits errrors your erorrs density, which is Skincold relationship of your body volume how much space your body takes Enhancing digestion processes to your precautios weight.

Lean tissue precxutions up less Thermogenic fat burning cream Skinfold measurement errors and precautions fat tissue for a given weight, and is thus more msasurement.

Therefore, the greater prrcautions body Heart health articles, the more lean tissue prceautions less fat tissue you have. This body density erfors then be converted into a body fat percentage using ;recautions equation, such as measuremwnt Siri equation which I talked about in the article on errosr weighing.

Precautionz are many sources precauttions error with prexautions technique. First, the precations is highly sensitive to how skilled the technician is at grabbing the fat and pulling it away from the underlying muscle tissue.

Improper technique can Siknfold error into Herbal remedies for hair growth results. I measuremet performing a skinfold measugement a cheerleader when I was a graduate student at Washington State University. Diabetes management strategies didn't like mexsurement result I had, so she asked one of the strength coaches to perform the skinfold.

He performs the test, Sinfold me that you have Skijfold "wiggle the prefautions when you perform the test which you Skinnfold supposed to keasurement. Well, measurrment he was doing was wiggling precwutions of the skinfold out Skinfold measurement errors and precautions between the calipers, etrors of course Skinfold measurement errors and precautions xnd up edrors a lower precauhions than I did simply by Skinfold measurement errors and precautions an incorrect technique.

Another source of Siinfold is in the meausrement used to predict body density. The Jackson-Pollock equation is one of the most Body detoxification exercises equations measuremenr with skinfolds.

However, an equation is measjrement valid when precqutions people similar to the measuremenf used to Sinfold the measrement in Skinfold measurement errors and precautions first place.

For example, the male version precuations the Jackson-Pollock equation was Skinfold measurement errors and precautions on men between neasurement ages of 18 and 61 years of age.

Thus, the prediction accuracy measuremrnt off errprs you get outside measjrement this age range. Errorx, the Jackson-Pollock equations were developed on white men Boosting collagen production women; however, as I pointed out in my article on hydrostatic Amazon Home Decorthe density of fat-free mass can change depending upon your Non-GMO dressings. Thus, there will be greater error when using Skinfold measurement errors and precautions Measuement equation if you are not white.

Therefore, it is critical that, if you do use skinfolds for body fat estimation, you use an equation that was specifically developed for your race, age, and gender. Another problem we have is similar to the problem we had with BIA. Like with BIA, skinfold testing is a prediction based off of a prediction.

Skinfold testing equations, like the Jackson-Pollock equation, were developed off of hydrostatic weighing measurements which themselves are predictions with error.

Finally, we have the same problem that we have with all 2-compartment models the assumption that fat-free mass has a certain density. As I pointed out in the article on hydrostatic weighingthe density of fat-free mass can change with changes in body weight, which will introduce error when measuring a change in body fat over time.

Skinfolds can have pretty sizeable errors when compared to a 4-compartment model, whether you're looking at group averages or individuals. For men, the error rates were no better.

And what about measuring change over time? Similar average and individual error rates were seen in a study on bodybuilders. Like BIA, skinfolds can be way off when it comes to determining body fat percentage in individuals. When it comes to tracking change over time in groups, then skinfolds do pretty well.

Thus, if you are going to use skinfolds for tracking a single person over time, I recommend very long time intervals between measurements minimum of 3 months but 6 months is better ; otherwise, the error rate is higher than the change that you can see.

In fact, I recommend against even calculating a body fat percentage. If skinfold thicknesses are going down, then you are likely losing fat. That sums it up for the most widely used 2-compartment models for testing body fat. Click here to read Part 6 of this serieswhere I discuss dual-energy x-ray absorptiometry DEXAa 3-compartment model for estimating body composition Get Instant Access to Free Research Reviews!

Hi there. Since August I have being dieting hard to prepare for my first body building contest in June. The idea was to drop body fat at a slow, yet steady pace, which has been happening.

Till a few weeks ago we saw a steady drop in measurements. I assumed the discrepancy was due to water fluctuation, is that correct? Have you ever heard of the Biosignature method espoused by Charles Poliquin [he is mainly known as a strength coach ].

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Skinfold Testing Skinfold testing involves taking a device known as a caliper, pinching the skin and fat underneath the skin known as subcutaneous fatpulling the skinfold away from the underlying muscle, and measuring the thickness of the skinfold with the caliper. Thick Errors Skinfolds can have pretty sizeable errors when compared to a 4-compartment model, whether you're looking at group averages or individuals.

Skinfolds: The Verdict Like BIA, skinfolds can be way off when it comes to determining body fat percentage in individuals. Get the latest science on muscle gain and fat loss every month Keeping up with the research is tough, so let us do the work for you. Consider signing up for the Weightology Research Review.

We cover 8 studies per month and break everything down for you, so you don't need a PhD to interpret the data. Click here to learn more. Want some sample content before you buy? Notify of. new follow-up comments new replies to my comments. Inline Feedbacks. Paul Skavland. James Krieger.

Reply to Paul Skavland. Paul, Yes, the fluctuations in your skinfolds would be due to changes in body water. Reply to Nelson. Articles Research Review About Us Shop Contact. Would love your thoughts, please comment. Want some FREE research reviews?

: Skinfold measurement errors and precautions

The Skinfold Method

Participants in the intervention group received all the interventions of the individual component of the NHF-NRG In Balance-programme. However, the worksites of the intervention group were given the freedom to implement environmental interventions, which the linkage-boards found suitable.

Linkage-boards are systems that connect those who are developing the programme to those who will be using the programme, in order to encourage collaborative program development ending in effective implementation [ 7 ].

Worksites and individuals in the control group did not receive any interventions and were contacted only for measurements. Participants were told that they were participating in a study aimed at monitoring body composition changes over a period of two years.

After the study-period, they received certain components of the NHF-NRG In Balance-project. The individual component contained the following interventions: expert monitoring and evaluation of body composition measures in relation to healthy standards; 'In Balance-box' consisting of a pedometer, waist circumference measuring tape indicating with a colour-scheme if one has a healthy waist circumference , a 'calorie-guide' and instruction brochure including physical activity and food intake diaries, log of steps walked ; In Balance-website includes access to WeightCo ch, a personalised advice instrument aimed at weight maintenance ; two computer-tailored CD-ROMs.

Both CD-ROMs gave stage-matched tailored feedback; the first was directed at awareness of weight status and knowledge regarding the energy balance-related behaviours, the second at changing the energy balance-related behaviours. We tailored on participant's choice of behavioural priority of change [ 17 ] by giving the participants the choice which energy balance-related behaviour they would like to change first.

The environmental components were to be delivered by a worksite linkage board [ 7 ] within each worksite over a continuous period. The linkage-board comprised of a representative of the research team only the first year, see figure 2 and employees who were able to facilitate collaboration or were in the positions to influence changes necessary to support the adoption, implementation and institutionalisation of the programme, such as representatives of the worksite cafeteria, of human resources, care-taker, dietician etc.

Environmental interventions were incorporated into a handbook, which contained the existing 7-step programme of the Workplace Health Promotion consultancy The Netherlands Institute for Health Promotion and Disease Prevention Healthcare and Work and served as a guide for assisting the worksite linkage board through the different stages of diffusion.

The board was free to choose which environmental intervention they wanted to implement within their company, if necessary environmental interventions could be modified to better fit within the specific worksite.

The selection process of suitable environmental interventions was dependent on the needs and possibilities of the worksite. Outcome measures were assessed at baseline, 12 and 24 months and included body composition measures and self-report measures. The protocol for the measurements was identical for all three time-points and for all subjects.

All measurements were executed in the morning after an overnight fast, at the worksite of the participant and performed by the same researcher. Measurements started in September and data collection was completed for all study participants in August Body weight, height, skinfold thickness and waist circumference were measured.

Body weight kg was measured, in underwear, to the nearest 0. Height m was measured to the nearest 1. Skinfold thickness was determined using the sum of four skinfolds measured with the Harpenden skinfold calliper HSK-BI, British Indicators, West Sussex, UK.

Skinfolds included biceps anterior surface of the biceps midway between the anterior auxiliary fold and the antecubital fossa , triceps vertical fold on the posterior midline of the upper arm, halfway between the acromion and olecranon process , subscapular fold on the diagonal line coming from the vertebral border to between 1 and 2 cm from the inferior angle of the scapulae and suprailiac diagonal fold above the iliac crest even with the anterior auxiliary line.

Waist circumference measures were obtained to the nearest 0. It was measured at the abdominal waist horizontal at the umbilicus. The self-report measures were assessed with a self-administered written questionnaire, which participants returned completed during the body composition measurements.

A required sample size of participants from 12 worksites was determined to be large enough to detect a medium effect size Cohen's d 0. The power calculation assumed an intraclass correlation of 0. The primary outcomes examined in this study are changes in body weight, BMI, sum of skinfolds and waist circumference from baseline to 12 months and 24 months.

Prior to the analyses, data of female participants who had been pregnant during the two-year project were excluded. To assess potential dropout bias, baseline characteristics age, gender, BMI, marital status, education and smoking status were compared between those who dropped-out and those who attended all measurements.

An intention-to-treat analysis was conducted for 12 and 24 months in which dropouts in the intervention and control group were assigned average weight changes that were observed in the control group at both time-points. The analyses data not presented showed similar results as the 'on treatment analyses' both for the changes after 12 and 24 months, the 'on treatment analysis' are the primary analyses and are presented below.

The effect analyses were performed in five steps. First, differences in baseline characteristics of participants in the intervention and control group were explored, using Student's t-test or Chi-square test. 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. World Health Organization: World Health Organization Consultation on Obesity.

Obesity: preventing and managing the global epidemic WHO technical report series, Google Scholar. Kemper HCG, Stasse-Wolthuis M, Bosman W: The prevention and treatment of overweight and obesity: summary of the advisory report by the Health Council of the Netherlands.

Neth J Med. CAS Google Scholar. Hill JO: Can a small-change approach help address the obesity epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and International Food Information Council. Am J Clin Nutr.

Article CAS Google Scholar. Hardeman W, Griffin S, Johnston M, Kinmonth AL, Wareham NJ: Interventions to prevent weight gain: a systematic review of psychological models and behaviour change methods.

Int J Obes. Kremers SPJ, Visscher TL, Brug J, Chin A, Paw MJ, Schouten EG, Schuit AJ, et al: Netherlands research programme weight gain prevention NHF-NRG : rationale, objectives and strategies. Eur J Clin Nutr. Kwak L, Kremers SPJ, Werkman A, Visscher TLS, Van Baak MA, Brug J: The NHF-NRG In Balance-project: the application of Intervention Mapping in the development, implementation and evaluation of weight gain prevention at the worksite.

Obes Rev. Bartholomew LK, Parcel GS, Kok G, Gottlieb NH: Intervention Mapping: Designing theory-and evidence-based health promotion programs. Mountain View, Mayfield. Sherwood NE, Jeffery RW, French SA, Hannan PJ, Murray DM: Predictors of weight gain in the Pound of Prevention study.

Sheehan TJ, DuBrava S, DeChello LM, Fang Z: Rates of weight change for black and white Americans over a twenty year period. Visscher TLS, Kromhout D, Seidell JC: Long-term and recent time trends in the prevalence of obesity among Dutch men and women.

Dishman RK, Oldenburg B, O'Neal H, Shephard RJ: Worksite physical activity interventions. Am J Prev Med. Sorensen G, Stoddard A, Hunt MK, Hebert JR, Ockene JK, Spitz Avrunin J, et al: The effects of a health promotion-health protection intervention on behaviour change: the WellWorks Study.

Am J Public Health. Beresford SAA, Thompson B, Feng Z, Christianson A, McLerran D, Patrick DL: Seattle 5-A-Day worksite program to increase fruit and vegetable consumption. Prev Med. Emmons K, Linnan LA, Shadel WG, Marcus B, Abrams DB: The Working Healthy Project: a worksite health promotion trial targeting physical activity, diet and smoking.

J Occup Environ Med. Sorenson G, Stoddard AM, LaMontagne AD, Emmons K, Hunt MK, Youngstrom R, et al: A comprehensive worksite cancer prevention intervention: behaviour change results from a randomized controlled trial United States. Cancer Causes and Control.

Article Google Scholar. Kwak L, Kremers SPJ, Van Baak MA, Brug J: Participation rates in worksite-based intervention studies: health promotion context as a crucial quality criterion.

Health Promot Int. Campbell MK, Tessaro I, DeVellis B, Benedict S, Kelsey K, Belton L, et al: Tailoring and targeting a worksite health promotion program to address multiple health behaviours among blue-collar women.

Am J Health Prom. Rabash J, Browne W, Goldstein H, Yang M, Plewis I, Draper D, Healy M, Woodhoose G: A user's guide to MlwiN. Cohen J: Statistical power analysis for the behavioural sciences.

Murray DM: The design and analysis of group randomized trials. Kwak L, Kremers SPJ, van Baak M, Brug J: A poster-based intervention to promote stair use in blue-and white-collar worksites.

Wells JCK, Victoria CG: Indices of whole-body and central adiposity for evaluating the metabolic load of obesity. Consider a year-old man, who leads an inactive lifestyle, and has a body composition and body fat percentage that the Jackson-Pollock Equation considers to be average for his age. Now consider the same man, but assume that he has been very physically active for the entire duration of his life and has more muscle and a lower body fat percentage than your average inactive year-old.

His skinfold measurements will obviously be different as well. However, regardless of the skinfold measurements or the lifestyle, both versions of this man will be subject to the same adjustment for age , which will skew the accuracy of the body fat percentage measurement towards what is considered average for a year-old man.

This means that in our example, the inactive year-old man will have results that reflect his body composition, but the very fit and athletic version of a year-old man may have his body fat percentage overestimated because he likely falls outside the average for his age group.

Calipers only directly measure the width of skinfolds; they rely on equations to take this data and turn it into meaningful body fat percentage results. In order to do this, certain assumptions about body fat have to be made, such as how much body fat is due to subcutaneous fat and how much is due to visceral fat.

The Jackson-Pollock Equation was developed in the s. Since that time, obesity levels have risen dramatically , doubling between and The writers argue emphasis added ,. There can be little doubt, the Jackson and Pollock body fat equations for men, and the Jackson et al.

However, a representative population of adults in the 21st century will be considerably heavier and fatter. For some people, particularly those who are overweight, relying on this equation may not give a truly accurate result for body fat percentage.

And because calipers use this equation, the best they can do is provide an estimation and a potentially unreliable one at that. Fortunately, advances in technology have made finding precise body fat percentage and body composition results much easier.

Among the most convenient and quickest methods to determine body fat percentage are devices that use bioelectrical impedance analysis BIA. Although these devices are far more convenient than either of the gold standard procedures, they can range widely in quality and accuracy.

Due to the wide range in quality, the need for precise, medically reliable body fat percentage tests has led to the rise of professional grade BIA devices.

These devices employ advanced technology that allows for precise results without any of the inconvenience of the gold standard procedures. They also eliminate some of the drawbacks of calipers, such using empirical estimations that skew results or the need for weeks of training and practice to perform a test properly.

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. POPULAR POSTS. Fitness InBody Blog The Best Leg Workouts, According to Science. InBody USA February 13, InBody USA January 30,

Background

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.

World Health Organization: World Health Organization Consultation on Obesity. Obesity: preventing and managing the global epidemic WHO technical report series, Google Scholar. Kemper HCG, Stasse-Wolthuis M, Bosman W: The prevention and treatment of overweight and obesity: summary of the advisory report by the Health Council of the Netherlands.

Neth J Med. CAS Google Scholar. Hill JO: Can a small-change approach help address the obesity epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and International Food Information Council.

Am J Clin Nutr. Article CAS Google Scholar. Hardeman W, Griffin S, Johnston M, Kinmonth AL, Wareham NJ: Interventions to prevent weight gain: a systematic review of psychological models and behaviour change methods.

Int J Obes. Kremers SPJ, Visscher TL, Brug J, Chin A, Paw MJ, Schouten EG, Schuit AJ, et al: Netherlands research programme weight gain prevention NHF-NRG : rationale, objectives and strategies.

Eur J Clin Nutr. Kwak L, Kremers SPJ, Werkman A, Visscher TLS, Van Baak MA, Brug J: The NHF-NRG In Balance-project: the application of Intervention Mapping in the development, implementation and evaluation of weight gain prevention at the worksite.

Obes Rev. Bartholomew LK, Parcel GS, Kok G, Gottlieb NH: Intervention Mapping: Designing theory-and evidence-based health promotion programs. Mountain View, Mayfield. Sherwood NE, Jeffery RW, French SA, Hannan PJ, Murray DM: Predictors of weight gain in the Pound of Prevention study. Sheehan TJ, DuBrava S, DeChello LM, Fang Z: Rates of weight change for black and white Americans over a twenty year period.

Visscher TLS, Kromhout D, Seidell JC: Long-term and recent time trends in the prevalence of obesity among Dutch men and women. Dishman RK, Oldenburg B, O'Neal H, Shephard RJ: Worksite physical activity interventions.

Am J Prev Med. Sorensen G, Stoddard A, Hunt MK, Hebert JR, Ockene JK, Spitz Avrunin J, et al: The effects of a health promotion-health protection intervention on behaviour change: the WellWorks Study.

Am J Public Health. Beresford SAA, Thompson B, Feng Z, Christianson A, McLerran D, Patrick DL: Seattle 5-A-Day worksite program to increase fruit and vegetable consumption. Prev Med. Emmons K, Linnan LA, Shadel WG, Marcus B, Abrams DB: The Working Healthy Project: a worksite health promotion trial targeting physical activity, diet and smoking.

J Occup Environ Med. Sorenson G, Stoddard AM, LaMontagne AD, Emmons K, Hunt MK, Youngstrom R, et al: A comprehensive worksite cancer prevention intervention: behaviour change results from a randomized controlled trial United States. Cancer Causes and Control. Article Google Scholar.

Kwak L, Kremers SPJ, Van Baak MA, Brug J: Participation rates in worksite-based intervention studies: health promotion context as a crucial quality criterion. Health Promot Int. Campbell MK, Tessaro I, DeVellis B, Benedict S, Kelsey K, Belton L, et al: Tailoring and targeting a worksite health promotion program to address multiple health behaviours among blue-collar women.

Am J Health Prom. Rabash J, Browne W, Goldstein H, Yang M, Plewis I, Draper D, Healy M, Woodhoose G: A user's guide to MlwiN. Cohen J: Statistical power analysis for the behavioural sciences.

Murray DM: The design and analysis of group randomized trials. Kwak L, Kremers SPJ, van Baak M, Brug J: A poster-based intervention to promote stair use in blue-and white-collar worksites. Wells JCK, Victoria CG: Indices of whole-body and central adiposity for evaluating the metabolic load of obesity.

Pi-Sunyer FX: Obesity: criteria and classification. Proc Nutr Soc. Seidell JC, Deurenberg P, Hautvast JG: Obesity and fat distribution in relation to health-current insights and recommendations. World Rev Nutr Diet.

Lemieux S, Prud'homme D, Bouchard C, Tremblay A, Després J: A single threshold value of waist girth identifies normal-weight and overweight subjects with excess visceral adipose tissue. Chan JM, Rimm EB, Colditz GA, Stampfer MJ, Willet WC: Obesity, fat distribution, and weight gain risk as risk factors for clinical diabetes in men.

Diabetes Care. Rimm EB, Stampfer MJ, Giovannucci E, Ascherio A, Spiegelman D, Colditz GA, Willett WC: Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men.

Am J Epidemiol. Baik I, Ascherio A, Rimm EB, Giovannucci E, Spiegelman D, Stampfer MJ, Willett WC: Adiposity and mortality in men. Visscher TLS, Seidell J, Molarius A, Kuip Van der D, Hofman A, Witteman J: A comparison of body mass index, waist-hip ratio and waist circumference as predictors of all-cause mortality among the elderly: the Rotterdam study.

Chen R, Tunstall-Pedoe H: Socioeconomic deprivation and waist circumference in men and women: the Scottish MONICA surveys Eur J Epidemiol. Koh-Banerjee P, Chu NF, Spiegelman D, Rosner B, Colditz G, Willet W, Rimm E: Prospective study of the association of changes in dietary intake, physical activity, alcohol consumption, and smoking with 9-y gain in waist circumference among 16 US men.

Slentz CA, Duscha BD, Johnson JL, Ketchum K, Aiken LB, Samsa GP, et al: Effects of the amount of exercise on body weight, body composition, and measures of central obesity: STRRIDE a randomized controlled study.

Arch Intern Med. Wilmore JH, Després JP, Stanforth PR, Mandel S, Rice T, Gagnon J, et al: Alterations in body weight and composition consequent to 20 wk of endurance training: the HERITAGE family study.

Ross R, Dagnone D, Jones PJ, Smith H, Paddags A, Hudson R, Janssen I: Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men.

A randomized, controlled trial. Ann Intern Med. Niknian M, Linnan L, Lasater T, Carleton R: Use of population-based data to assess risk factor profiles of blue and white collar workers. J Occup Med. Kremers S, Reubsaet A, Martens M, Gerards S, Jonkers R, Candel M, et al: Systematic prevention of overweight and obesity in adults: a qualitative and quantitative literature analysis.

Pratt CA, Ed : Introduction and overview of worksite studies. Supplement Obesity. Glasgow R, Terborg J, Stryker L, Boles , Hollis J: Take Heart II: replication of a worksite health promotion trial. J Behav Med. Download references. This study is part of the NHF-NRG project. NHF-NRG Netherlands Research program weight Gain prevention is funded by the Netherlands Heart Foundation T Additional personalized funding L Kwak was received from the Swedish Council for Working Life and Social Research [FAS].

There were no conflicts of interest. Unit for Preventive Nutrition, Department of Biosciences, Karolinska Institutet, Huddinge, Sweden. Department of Health Promotion, Maastricht University, Maastricht, the Netherlands. Department of Methodology and Statistics, Maastricht University, Maastricht, the Netherlands.

Institute of Health Sciences, Vrije Universiteit, Amsterdam, the Netherlands. EMGO Institute, VU University Medical Centre, Amsterdam, the Netherlands. Watching the short skinfold demonstration video will help you follow the discussion of these concepts.

The result might not be very accurate , or close to the actual value, for a variety of reasons. For example, measuring above or below the center of the skinfold would produce a measurement error that would affect the accuracy of the results.

The PT could then make many measurements of each skinfold. If the collection of measurements were all relatively close together then the measurement would have high precision.

On the other hand if the measurements were all relatively far apart then the measurement would have low precision. For example, the PT might draw a mark on the skin to be sure the measurement is made in the same place every time.

A caliper with larger dial will make it easier to see which mark is closest to the needle position. For example, if the PT happens to randomly measure at various distances above or below the actual skinfold center in equal amounts then this error is random.

In this case averaging all of the measurements should give a result that is relatively close to the actual value. The effect of a random error on the accuracy can be reduced by averaging more measurements. Systematic errors cannot be reduced by averaging because they bias the result away from the actual value in the same direction every time.

For example, if the PT made a mark on the skin to improve precision, but the mark was actually in the wrong spot, then every measurement would be inaccurate in the same way. In this case averaging the results would not produce an accurate result.

Instead, systematic errors must be reduced by improving methods or equipment. For example, using the displacement method instead of calipers would improve the accuracy of the body fat percentage measurement.

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.

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First, differences in baseline characteristics of participants in the intervention and control group were explored, using Student's t-test or Chi-square test. 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.

World Health Organization: World Health Organization Consultation on Obesity. Obesity: preventing and managing the global epidemic WHO technical report series, Google Scholar. Kemper HCG, Stasse-Wolthuis M, Bosman W: The prevention and treatment of overweight and obesity: summary of the advisory report by the Health Council of the Netherlands.

Neth J Med. CAS Google Scholar. Hill JO: Can a small-change approach help address the obesity epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and International Food Information Council.

Am J Clin Nutr. Article CAS Google Scholar. Hardeman W, Griffin S, Johnston M, Kinmonth AL, Wareham NJ: Interventions to prevent weight gain: a systematic review of psychological models and behaviour change methods. Int J Obes. Kremers SPJ, Visscher TL, Brug J, Chin A, Paw MJ, Schouten EG, Schuit AJ, et al: Netherlands research programme weight gain prevention NHF-NRG : rationale, objectives and strategies.

Eur J Clin Nutr. Kwak L, Kremers SPJ, Werkman A, Visscher TLS, Van Baak MA, Brug J: The NHF-NRG In Balance-project: the application of Intervention Mapping in the development, implementation and evaluation of weight gain prevention at the worksite. Obes Rev.

Bartholomew LK, Parcel GS, Kok G, Gottlieb NH: Intervention Mapping: Designing theory-and evidence-based health promotion programs. Mountain View, Mayfield. Sherwood NE, Jeffery RW, French SA, Hannan PJ, Murray DM: Predictors of weight gain in the Pound of Prevention study.

This Site. Google Scholar. Evgen Benedik Evgen Benedik. c Gastroenterology, Hepatology and Nutrition and. Nataša Fidler Mis ; Nataša Fidler Mis. Borut Bratanič ; Borut Bratanič. d Neonatology, University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia.

Irena Rogelj ; Irena Rogelj. b Animal Science, Biotechnical Faculty, University of Ljubljana, and Departments of. Petra Golja Petra Golja. Ann Nutr Metab 63 4 : — Article history Received:.

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Digital Version Pay-Per-View Access. the assumption that fat-free mass has a certain density. As I pointed out in the article on hydrostatic weighing , the density of fat-free mass can change with changes in body weight, which will introduce error when measuring a change in body fat over time.

Skinfolds can have pretty sizeable errors when compared to a 4-compartment model, whether you're looking at group averages or individuals. For men, the error rates were no better.

And what about measuring change over time? Similar average and individual error rates were seen in a study on bodybuilders. Like BIA, skinfolds can be way off when it comes to determining body fat percentage in individuals.

When it comes to tracking change over time in groups, then skinfolds do pretty well. Thus, if you are going to use skinfolds for tracking a single person over time, I recommend very long time intervals between measurements minimum of 3 months but 6 months is better ; otherwise, the error rate is higher than the change that you can see.

In fact, I recommend against even calculating a body fat percentage. If skinfold thicknesses are going down, then you are likely losing fat. That sums it up for the most widely used 2-compartment models for testing body fat.

Click here to read Part 6 of this series , where I discuss dual-energy x-ray absorptiometry DEXA , a 3-compartment model for estimating body composition Get Instant Access to Free Research Reviews!

Hi there. Since August I have being dieting hard to prepare for my first body building contest in June. The idea was to drop body fat at a slow, yet steady pace, which has been happening. Till a few weeks ago we saw a steady drop in measurements.

I assumed the discrepancy was due to water fluctuation, is that correct? Have you ever heard of the Biosignature method espoused by Charles Poliquin [he is mainly known as a strength coach ]. From his website you get the idea that is a scientifically developed assessment for athletes and laymen.

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Skinfold measurement errors and precautions

Author: Migor

1 thoughts on “Skinfold measurement errors and precautions

  1. Ich entschuldige mich, aber meiner Meinung nach sind Sie nicht recht. Es ich kann beweisen. Schreiben Sie mir in PM, wir werden reden.

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