Protocol - Weight - Measured Weight
- Birth Weight - Birth Weight Abstracted from Medical Records
- Birth Weight - Measured Weight at Birth
- Birth Weight - Proxy Reported Birth Weight
- Body Mass Index
- Ethnicity and Race
- Height - Knee Height
- Height - Recumbent Length
- Height - Self-Reported Height
- Height - Standing Height
- Hip Circumference - Hip Circumference
- Maximum Adult Weight
- Total Pregnancy Weight Gain - Abstracted From Prenatal Charts
- Total Pregnancy Weight Gain - Self-Reported Weight Gain
- Total Pregnancy Weight Gain - Weight Measured During Gestation
- Waist Circumference - Framingham Heart Study
- Waist Circumference - Waist Circumference NCFS
- Waist Circumference - Waist Circumference NHANES
- Weight Loss/Gain
Description
Weight is measured using a digital floor scale. The instrument should be calibrated daily using standardized weights, and a log of calibration results should be maintained.
Specific Instructions
Several overarching, critical issues for high-quality data collection of anthropometric measures that optimize the data in gene-environment etiologic research include (1) the need for training (and retraining) of study staff in anthropometric data collection; (2) duplicate collection of measurements, especially under field conditions; (3) use of more than one person for proper collection of measurements where required; (4) accurate recording of the protocols and the measurement units of data collection; and (5) use of required and properly calibrated equipment.
The notion of recommending replicate measurements comes from the reduction in random errors of measurement and accompanying improved measurement reliability when the mean of multiple measurements is used rather than a single measurement. This improvement in measurement reliability, however, depends on the reliability of a single measurement in the hands of the data collectors in a particular study (Himes, 1989). For example, if a measure such as standing height in a given study has a measurement reliability of 0.95 (expressed as an intraclass correlation coefficient), taking a second measurement and using the mean of the two measurements in analyses will improve the reliability to only 0.97, yielding only a 2% reduction in error variance for the additional effort. If, in the same study, the reliability of a single triceps skinfold measurement was 0.85, using the mean, including a replicate measurement, would raise the reliability to 0.92 and yield a 7% reduction in error variance, more than a three-fold improvement compared with recumbent length.
Because the benefits of taking replicate measurements are so closely linked with the existing measurement reliability, it is recommended that as a part of the training of those who will be collecting anthropometry data, a reliability study be conducted that will yield measurement reliability estimates for the data collectors, protocols, settings, and participants involved in that particular study (Himes, 1989). If the measurement reliability for a single measurement is greater than or equal to 0.95, the recommendation is that replicate measurements are not necessary and will yield little practical benefit. If the measurement reliability is less than 0.95, the recommendation is to include replicate measurements as prescribed.
If replicate measurements are indicated because of relatively low reliability, a second measurement should be taken, including having the participant step off and then back onto the scale. A third measurement should be taken if the first two measurements differ by 0.5 kg. If it is necessary to take a third measurement, the two closest measurements are averaged. Should the third measurement fall equally between the first two measurements, all three should be averaged.
The PhenX Anthropometrics Working Group and Expert Review Panel strongly recommend the assessment of weight using a measured protocol. Self-reported weight should be collected as a last resort only.
NOTE: Self-reported weight values are considered to be less accurate. Self-reported weight is subject to error and is used when measured weight cannot be obtained.
Availability
Protocol
Current Weight - Measured
Note: Detailed videos illustrating the procedure can be found on the National Health and Nutrition Examination Survey (NHANES) website at http://www.cdc.gov/nchs/video/nhanes3_anthropometry/weight/weight.htm.
A digital scale or beam balance is used to weigh participants.
Participants are asked to wear an examination gown and socks or light clothes without shoes. Only undergarments are worn beneath the gown. Infants should wear a clean diaper and t-shirt if they have not been placed in an examination gown. The procedures for obtaining the weight measurement are as follows:
The examiner briefly informs the participant that his/her weight will be measured. Participants are asked to remove objects such as cell phones, wallets, and toys from their pockets.
1. The health technician directs participants to stand in the center of the scale platform with hands at their sides and looking straight ahead.
2. The weight measurement is recorded in kilograms.
3. Special situations:
- Small children: Infants and toddlers who cannot stand alone on the scale will be weighed with an adult, or with an infant’s scale. If an adult is holding the child, then the adult guardian or the health technician will stand alone on the scale so the scale can be tared. This sets the scale readout to zero. The child is then handed to the adult and the child’s weight is measured.
- If the participant is wearing a cast or medical prosthesis, make a note in the record of the location and place.
- If the participant wore street clothes instead of the examination gown, make a note of this in the record. It is acceptable for infants to wear diapers or underpants and a t-shirt.
- Participants should not be weighed if they are wearing shoes.
- Note that special consideration may be needed for participants whose weight exceeds the capacity of the study scale. For example, weight can be obtained using two portable scales:
- Have the participant stand with one foot on each portable scale.
- Combine the two results to approximate the weight.
- Record the weight.
- If the weight equals the capacity of both portable scales, note that the weight Equals Capacity (EC) of the scales.
Record current weight in kilograms.
Repeat weight measurement.
Personnel and Training Required
Technicians should be trained in the basic techniques of anthropometric measurements.
Equipment Needs
Digital scale or beam balances. Portable scales have also been used in the National Health and Nutrition Examination Survey. A standard weight is used to calibrate the scale. A tare function is used when weighing infants and children. The tare function is a feature found in clinical scale equipment.
Requirements
| Requirement Category | Required |
|---|---|
| Major equipment | No |
| Specialized training | No |
| Specialized requirements for biospecimen collection | No |
| Average time of greater than 15 minutes in an unaffected individual | No |
Mode of Administration
Physical Examination
Lifestage
Infant, Toddler, Child, Adolescent, Adult, Senior
Participants
All ages. Adult participants who cannot stand unassisted are excluded.
Selection Rationale
The National Health and Nutrition Examination Survey 2007-2008 protocols were selected as best practice methodology and are the most widely used protocols to assess weight. Weight measurements are used to calculate body mass index, assess nutritional status, and predict morbidity and mortality.
Language
Chinese, English, Spanish
Standards
| Standard | Name | ID | Source |
|---|---|---|---|
| Logical Observation Identifiers Names and Codes (LOINC) | Measured weight proto | 62297-7 | LOINC |
| Human Phenotype Ontology | Abnormality of body weight | HP:0004323 | HPO |
| caDSR Form | PhenX PX021501 - Measured Weight | 5806000 | caDSR Form |
Derived Variables
Ponderal index (PI, neonates and infants), weight for length (birth to 36 months), Body Mass Index (BMI; 2 years to adults, but some references from birth) BMI
| Measurement Units | Formula and Calculation |
| Kilograms and meters (or centimeters) | Formula: weight (kg)/[height (m)]2 With the metric system, the formula for BMI is weight in kilograms divided by height in meters squared. Because height is commonly measured in centimeters, divide height in centimeters by 100 to obtain height in meters. Example: Weight = 68 kg, Height = 165 cm (1.65 m) Calculation: 68 ÷ (1.65)2 = 24.98 |
Centers for Disease Control and Prevention. (2015). Body Mass Index. Retrieved from http://www.cdc.gov/healthyweight/assessing/bmi/
Process and Review
The Expert Review Panel #1 reviewed the measures in the Anthropometrics, Diabetes, Physical Activity and Physical Fitness, and Nutrition and Dietary Supplements domains.
Guidance from the ERP includes:
• Added replicate measure language
• Changed unit of measurement
Back-compatible: no changes to Data Dictionary
Previous version in Toolkit archive (link)
Protocol Name from Source
National Health and Nutrition Examination Survey (NHANES), Anthropometry Procedures Manual, 2007
Source
Centers for Disease Control and Prevention, National Center for Health Statistics. (2007-2008). National Health and Nutrition Examination Survey (NHANES) Anthropometry Procedures Manual. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention.
Certification for the Spanish translation can be found here.
General References
None
Protocol ID
21501
Variables
Export Variables| Variable Name | Variable ID | Variable Description | dbGaP Mapping | |
|---|---|---|---|---|
| PX021501_Cast_Or_Medical_Prosthesis | ||||
| PX021501010100 | Record whether the participant is wearing a more | N/A | ||
| PX021501_Cast_Or_Medical_Prosthesis_Location | ||||
| PX021501010200 | If the participant is wearing one, record more | N/A | ||
| PX021501_Measured_Weight_1_Kilograms | ||||
| PX021501030500 | Measured weight in kg, first measurement | N/A | ||
| PX021501_Measured_Weight_1_Pounds | ||||
| PX021501030100 | Measured weight in lbs, first measurement | N/A | ||
| PX021501_Measured_Weight_2_Kilograms | ||||
| PX021501030600 | Measured weight in kg, second measurement | N/A | ||
| PX021501_Measured_Weight_2_Pounds | ||||
| PX021501030200 | Measured weight in lbs, second measurement | N/A | ||
| PX021501_Measured_Weight_3_Kilograms | ||||
| PX021501030700 | Measured weight in kg, third measurement | N/A | ||
| PX021501_Measured_Weight_3_Pounds | ||||
| PX021501030300 | Measured weight in lbs, third measurement | N/A | ||
| PX021501_Measured_Weight_Average_Kilograms | ||||
| PX021501030800 | Measured weight in kg, average | N/A | ||
| PX021501_Measured_Weight_Average_Pounds | ||||
| PX021501030400 | Measured weight in lbs, average | Variable Mapping | ||
| PX021501_Street_Clothes | ||||
| PX021501020000 | Record whether or not the participant is more | N/A | ||
Measure Name
Weight
Release Date
March 27, 2009
Definition
Current Weight - Measured Current measured weight is the weight of the participant in kilograms. Current Weight - Self-Reported* Self-reported weight is the weight in kilograms or pounds as reported by the participant.
*NOTE: Self-reported weight values are considered to be less accurate and are used only when measured weight cannot be obtained.
Purpose
Current weight is used to assess a child’s growth and development and an adult’s current health status. Overweight and obese status is associated with several serious comorbidities, including type 2 diabetes, cardiovascular disease, hypertension, and obstructive sleep apnea.
Keywords
Anthropometrics, body mass index, BMI, obesity, ponderal index, weight for length, NHANES
Measure Protocols
| Protocol ID | Protocol Name |
|---|---|
| 21501 | Weight - Measured Weight |
| 21502 | Weight - Self-Reported Weight |
Publications
Dahl, A., et al. (2024) Genetic and brain similarity independently predict childhood anthropometrics and neighborhood socioeconomic conditions Developmental Cognitive Neuroscience. 2024 February; 65(1). doi: 10.1016/j.dcn.2023.101339
Kringle, E. A., et al. (2023) Associations between daily step count trajectories and clinical outcomes among adults with comorbid obesity and depression. Mental Health and Physical Activity. 2023 March; 24: 9. doi: 10.1016/j.mhpa.2023.100512
Ross, J. M., et al. (2022) The effects of cannabis use on physical health: A co-twin control study. Drug and Alcohol Dependence. 2022 January; 230: 109200. doi: 10.1016/j.drugalcdep.2021.109200
Schettini, E., et al. (2021) Internalizing-externalizing comorbidity and regional brain volumes in the ABCD study. Development and Psychopathology. 2021 December; 33(5): 1620-1633.
Barch, D. M., et al. (2021) Demographic and mental health assessments in the adolescent brain and cognitive development study: Updates and age-related trajectories. Developmental Cognitive Neuroscience. 2021 December; 52: 101031. doi: 10.1016/j.dcn.2021.101031
Lv, N., et al. (2021) Problem-solving therapy–induced amygdala engagement mediates lifestyle behavior change in obesity with comorbid depression: a randomized proof-of-mechanism trial. American Journal of Clinical Nutrition. 2021 September; 114(6): 2060-2073. doi: 10.1093/ajcn/nqab280
Barbirou, M., et al. (2020) Western influenced lifestyle and Kv2.1 association as predicted biomarkers for Tunisian colorectal cancer. BMC Cancer. 2020 November; 20: Article Number: 1086. doi: 10.1186/s12885-020-07605-7
Sitarik, A. R., et al. (2020) Association between cesarean delivery types and obesity in preadolescence. International Journal of Obesity. 2020 September; 44(10): 2023-2034. doi: 10.1038/s41366-020-00663-8
Lv, N., et al. (2020) The ENGAGE-2 study: Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes in a randomized controlled trial (Phase 2). Contemporary Clinical Trials. 2020 August; 95(Aug:106072). doi: 10.1016/j.cct.2020.106072
Wu, Y., et al. (2020) Short-term exposure to air pollution and its interaction effects with two ABO SNPs on blood lipid levels in northern China: A family-based study. Chemosphere. 2020 June; 249: 8. doi: 10.1016/j.chemosphere.2020.126120
Barch, D. M., et al. (2018) Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Dev Cogn Neurosci. 2018 August; 32: 55-66. doi: 10.1016/j.dcn.2017.10.010
Lee, S., et al. (2018) Peer Group and Text Message-Based Weight-Loss and Management Intervention for African American Women. West J Nurs Res. 2018 August; 40(8): 1203-1219. doi: 10.1177/0193945917697225
Aris, I. M., et al. (2017) Infant body mass index peak and early childhood cardio-metabolic risk markers in a multi-ethnic Asian birth cohort. Int J Epidemiol. 2017 April; 46(2): 513-525. doi: 10.1093/ije/dyw232
Kwok, R. K., et al. (2017) The GuLF STUDY: A Prospective Study of Persons Involved in the Deepwater Horizon Oil Spill Response and Clean-Up. Environ Health Perspect. 2017 April; 125(4): 570-578. doi: 10.1289/EHP715
Ong, Y. L., et al. (2016) The association of maternal vitamin D status with infant birth outcomes, postnatal growth and adiposity in the first 2 years of life in a multi-ethnic Asian population: the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort study. Br J Nutr. 2016 August; 116(4): 621-31. doi: 10.1017/S0007114516000623
Rosas, L. G., et al. (2016) Evaluation of a culturally-adapted lifestyle intervention to treat elevated cardiometabolic risk of Latino adults in primary care (Vida Sana): A randomized controlled trial. Contemp Clin Trials. 2016 May; 48: 30-40. doi: 10.1016/j.cct.2016.03.003
Ma, J., et al. (2016) Pilot randomised trial of a healthy eating behavioural intervention in uncontrolled asthma. Eur Respir J. 2016 January; 47(1): 122-32. doi: 10.1183/13993003.00591-2015
Schifferdecker, K. E., et al. (2016) Translation of an Action Learning Collaborative Model Into a Community-Based Intervention to Promote Physical Activity and Healthy Eating. Health Promot Pract. 2016 January; 17(1): 70-9. doi: 10.1177/1524839915601371
Hitz, M.M., Conway, P.G, Palcher, J.A., McCarty, C.A. (2014) Using PhenX toolkit measures and other tools to assess urban/rural differences in health behaviors: recruitment methods and outcomes. BMC Research Notes. 2014 November; 7(847). doi: 10.1186/1756-0500-7-847
McCarty, C.A., Berg, R., Rottscheit, C.M., Waudby, C.J., Kitchner, T., Brilliant, M., Ritchie, M.D. (2014) Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies. BMC Med Genomics. 2014 January; 7: 3. doi: 10.1186/1755-8794-7-3