• Component Description
• Eligible Sample
• Protocol and Procedure
• Quality Assurance & Quality Control
• Data Processing and Editing
• Analytic Notes
• References
• Codebook
  • SEQN - Respondent sequence number
  • DXXAGST - Android/gynoid region status
  • DXXVATV - VAT and SAT invalidity code
  • DXXANTV - Android region invalidity code
  • DXXGYTV - Gynoid region invalidity code
  • DXXANFM - Android fat mass
  • DXXANLM - Android lean mass
  • DXXANTOM - Android total mass
  • DXXGYFM - Gynoid fat mass
  • DXXGYLM - Gynoid lean mass
  • DXXGYTOM - Gynoid total mass
  • DXXAGRAT - Android to Gynoid ratio
  • DXXAPFAT - Android percent fat
  • DXXGPFAT - Gynoid percent fat
  • DXXSATA - Subcutaneous fat area
  • DXXSATM - Subcutaneous fat mass
  • DXXSATV - Subcutaneous fat volume
  • DXXTATA - Total abdominal fat area
  • DXXTATM - Total abdominal fat mass
  • DXXTATV - Total abdominal fat volume
  • DXXVFATA - Visceral adipose tissue area
  • DXXVFATM - Visceral adipose tissue mass
  • DXXVFATV - Visceral adipose tissue volume

National Health and Nutrition Examination Survey

2017-2018 Data Documentation, Codebook, and Frequencies

Dual-Energy X-ray Absorptiometry - Android/Gynoid Measurements (DXXAG_J)

Data File: DXXAG_J.xpt

First Published: October 2021

Last Revised: NA

Component Description

Users of the 2017-2018 dual-energy X-ray absorptiometry android/gynoid data (DXXAG_J) are encouraged to read the documentation before accessing the data file. NOTE: missing and invalid android and gynoid data were not multiply imputed.

Dual-energy x-ray absorptiometry (DXA) is the most widely accepted method of measuring body composition, due in part to its speed, ease of use, and low radiation exposure (Baran, 1997; Genant, 1996; Heymsfield, 1989; and Njeh, 1999). In 2017-2018, whole body DXA scans were administered in the NHANES mobile examination center (MEC).

Android and gynoid (A/G) regions were defined by the Hologic APEX software used in the scan analysis. The android area was defined as the lower trunk area bounded by two lines: the pelvic horizontal cut line on its lower side, and a line automatically placed above the pelvic line. The upper gynoid line was placed 1.5 times of the height of android region below the pelvic line and the lower gynoid line was placed such that the distance between the two gynoid lines was twice the height of the android region. All these lines were automatically placed by Hologic software (Shepherd, 2012).

Android obesity is often referred to as the “apple” shape since the increased fat is in the trunk. Gynoid obesity is referred to as the “pear” shape with increased fat in the hip and thigh areas. Fat deposition in the android region is associated with increased risk of cardiovascular disease, hypertension, hyperlipidemia, insulin resistance, and type 2 diabetes (Kissebah, 1994; Folsom, 2000), while gynoid fat deposition is associated with decreased risk of metabolic and cardiovascular diseases (Folsom, 2000; Ashwell, 1994).

Visceral Adipose Tissue (VAT) and subcutaneous Adipose Tissue (SAT) were defined by the Hologic APEX software used in the scan analysis. Visceral adipose tissue area, mass and volume of fat inside abdominal cavity were measured at the approximate interspace location of L4 and L5 vertebra. Subcutaneous adipose tissue area, mass and volume of fat outside abdominal cavity were measured at the approximate interspace location of L4 and L5 vertebra.

The NHANES whole body scans provide nationally representative data on abdominal soft tissue composition and fat distribution overall and for age, gender, and racial/ethnic groups; and data to study the association between abdominal fat distribution and other health conditions and risk factors, such as cardiovascular disease, diabetes, hypertension, and activity and dietary patterns.

Analysis of the whole body scans provides abdominal soft tissue measurements for the android and gynoid areas of the trunk, VAT and SAT. These measurements include:

• Total mass (gm)
• Total area (cm²)
• Total volume (cm³)
• Fat mass (gm)
• Lean mass (gm)
• Percent fat (%)

Eligible Sample

DXA whole body scans were administered to eligible survey participants aged 8-59. Pregnant females were ineligible for the DXA examination. Participants who were excluded from the DXA examination for reasons other than pregnancy were considered to be eligible nonrespondents. Reasons for exclusion from the DXA examination were as follows:

• Pregnancy (positive urine pregnancy test and/or self-report at the time of the DXA examination).
• Self-reported history of radiographic contrast material (barium) use in past 7 days.
• Measured weight over 450 pounds or height over 6’5” (DXA table limitation).

The variable DXXAGST indicates the examination status for the android/gynoid region.

The codes for DXXAGST are as follows:
1= Whole body scan completed, android/gynoid region is valid
2= Whole body scan completed, but android or gynoid region is invalid
3= Whole body not scanned, pregnancy
4= Whole body not scanned, weight > 450 lbs
5= Whole body not scanned, height > 6'5”
6= Whole body not scanned, other reason

The main reasons for completed but invalid whole body scans were implants, excessive X-ray “noise” due to obesity, and jewelry not removed. The “Not scanned, other reason” code includes no time to complete the examination, pregnancy test not completed, and participant refusal.

Protocol and Procedure

The whole body scans were acquired on the Hologic Discovery model A densitometers (Hologic, Inc., Bedford, Massachusetts), using software version Apex 3.2. The radiation exposure from DXA whole body scans is extremely low at less than 20 uSv. All scans in the DXXAG_J file were analyzed with Hologic APEX version 4.0 software with NHANES BCA option.

The DXA examinations were administered by trained and certified radiology technologists. Further details of the DXA examination protocol are documented in the Body Composition Procedures Manual located on the NHANES website.

Quality Assurance & Quality Control

A high level of quality control was maintained throughout the DXA data collection and scan analysis, including a rigorous phantom scanning schedule.

Monitoring of Field Staff and Densitometers
Staff from the National Center for Health Statistics (NCHS) and the NHANES data collection contractor monitored technologist acquisition performance through in-person observations in the field. Retraining sessions were conducted with the technologists annually and as needed to reinforce correct techniques and appropriate protocol. In addition, technologist performance codes were recorded by the NHANES quality control center Shepherd Research Lab at the University of California, San Francisco (UCSF), Department of Radiology (2017) and at the University of Hawaii (UH) Cancer Center (2018), during review of participant scans. The codes documented when the technologist had deviated from acquisition procedures and scan quality could have been improved. The performance codes were tracked for each technologist individually and a summary was reported to NCHS on a quarterly basis. Additional feedback on technologist performance was provided by the Shepherd Research Lab when problems were noted during review of the scans. Constant communication was maintained throughout the year among the Shepherd Research Lab, the NCHS, and the data collection contractor regarding any issues that arose.

Hologic service engineers performed all routine densitometer maintenance and repairs. Copies of all reports completed by the manufacturer’s service engineers were sent to the quality control center when the scanners were serviced or repaired so any changes in measurement, as a result of the work, could be assessed.

Scan Analysis
Each participant scan and phantom scan was reviewed and analyzed by the Shepherd Research Lab using standard radiologic techniques and study-specific protocols developed for NHANES. The Hologic software, APEX v4.0 (Hologic) was used to analyze whole body scans acquired in 2017-18. Expert review was conducted by the Shepherd Research Lab on 100% of analyzed participant scans to verify the accuracy and consistency of the results.

Invalidity Codes
Invalidity codes were applied by the Shepherd Research Lab to indicate the reasons regions of the body could not be analyzed accurately. The invalidity codes for the trunk region are provided in the data file (see Analytic Notes for a description of the invalidity codes).

Quality Control Scans
The quality control phantoms were scanned according to a predetermined schedule. The Hologic Anthropomorphic Spine Phantom associated with each MEC was scanned daily as required by the manufacturer to ensure accurate calibration of the densitometer. Other MEC-specific phantoms, such as the Hologic Whole Body Slim-line Phantom and Hologic Tissue Step Phantom, were scanned 1 to 3 times weekly. Another set of phantoms, the Hologic Spine (HSP-Q96), Hologic Block, and Hologic Whole Body Phantoms, circulated among the MECs and was scanned at the start of operations at each survey site.

Air scans, which are phantom-less scans using the whole body scan mode, were used to describe and monitor the systems’ radiographic uniformity across the entire scan field. Poor uniformity could be caused by poor aperture alignment, incorrect gantry rotation, non-uniform gain in detectors, etc., that result in localized inaccuracies in the attenuation values.

The complete phantom scanning schedule is described in the Body Composition Procedures Manual located on the NHANES website.

In 2017-2018, longitudinal monitoring was conducted through the daily spine phantom scans as required by the manufacturer, 3 times weekly whole body slim-line phantom scans, and weekly air scans in order to correct any scanner-related changes in participant data. The circulating HSP-Q96, block, and whole body phantoms, which were scanned at the start of operations at each site, provided additional data for use in longitudinal monitoring and cross calibration. The cross-comparability of the data from each MEC was critical so the data could be pooled for analysis.

The Shepherd Research Lab used the Cumulative Statistics method (CUSUM) and the MEC-specific phantom data to determine breaks in the calibration of the densitometers over the course of the survey (Lu, 1996). Multiplicative correction factors were used to correct the phantom data back to the baseline calibration. The type, frequency, and magnitude of calibration problems detected in the NHANES data were similar to those in other studies using stationary densitometers that were being monitored by Shepherd Research Lab.

After applying the correction factors developed by Shepherd Research Lab from the cross-calibration and longitudinal phantom data to the NHANES participant data, the adjusted participant data were compared to unadjusted data. The magnitude of the changes and reduction in standard errors between the adjusted and unadjusted data were found to be small and correction of the participant data was not required.

A number of data quality issues were addressed through the quality control program. Direct feedback given to the technologists regarding acquisition problems affecting the quality of the scans and yearly refresher training resulted in improved technologist performance. The rigorous schedule of quality control scans provided continuous monitoring of machine performance. The expert review procedures helped to ensure that scan analysis was accurate and consistent.

Data Processing and Editing

During the editing process, data were reviewed for completeness, consistency, and outliers. Back-end edits of the data were performed when errors were identified. The NHANES BCA option was enabled for whole body scan analysis, this option adds 5% of lean mass to the fat mass. The correction is based on the results of an analysis of QDR-4500A DXA data from seven research laboratories indicating that the QDR-4500A algorithm underestimated fat mass and overestimated lean mass (Schoeller, 2005).

Invalidity Codes
Invalidity codes were included in the data file to indicate the reasons regions could not be analyzed accurately. Invalidity codes were applicable to completed scans only (DXXAGST =1 or 2). If a participant was not scanned, all invalidity codes are missing. Objects found in the upper portion of the trunk such as pacemakers or breast implants did not invalidate the scan validity for the android gynoid data.

Values for DXXVATV(VAT and SAT), DXXANTV (Android region) and DXXGYTV (Gynoid region) invalidity codes
0 = Valid
1 = Invalid

The percentage of eligible survey participants in 2017-2018 with valid DXA data is in android/gynoid region shown by age group in Table 1. The percentage of participants with valid data decreases with increasing age. The decrease in valid data with age was due primarily to an increase in the number of participants with implants, such as stents and hip replacements and higher rates of obesity resulting in invalid truncal data from “obesity noise.” The percentage of participants with valid DXA data in android/gynoid region also decreases with increasing BMI due to weight over 450 pounds and “obesity noise” (Table 2).

Table 1. Percentages of interviewed and examined participants aged 8-59 years with valid DXA data in android/gynoid region by age group, NHANES 2017-2018

Age group (years)	Interviewed and examined *	Eligible for DXA †		%100 valid DXA data‡
	N	N	%	N	%
8-11	731	731	100	616	84
12-15	573	573	100	452	79
16-19	563	563	100	460	82
20-29	776	750	97	614	82
30-39	813	788	97	612	78
40-49	778	774	99	618	80
50-59	880	880	100	676	77
Total	5,114	5,059	99	4,048	80

* The number interviewed and examined is the total number of participants in the data file with a SEQN variable. This number includes pregnant females.
† The total number eligible for DXA does not include pregnant women.
‡ Of those eligible for DXA who successfully completed a scan.

Table 2. Percentages of participants aged 20-59 years with valid DXA data in android/gynoid region by body mass index (BMI) ^* category, NHANES 2017-18

BMI group	Interviewed and Examined (N)	Eligible for DXA (N) †	Eligible for DXA (%) †	100% valid DXA data (N) ‡	100% valid DXA data (%) ‡
<18	42	42	100	29	70
18-24.9	839	830	99	724	87
25-29.9	959	942	98	794	84
30-34.9	675	663	98	533	80
35-39.9	353	343	97	250	73
≥ 40	344	337	98	181	54
Total	3,247	3,192	98	2,520	79

*Measured weight in kilograms divided by measured height in meters squared.
†The total number eligible for DXA does not include pregnant women.
‡ Of those eligible for DXA who successfully completed a scan.

Analytic Notes

The NHANES examination sample weight should be used for any analyses using the DXXAG_H data. Please refer to the NHANES Analytic Guidelines and the online NHANES Tutorial for further details on the use of sample weights and other analytic issues.

References

• Ashwell M. Obesity in men and women. Int J Obes Relat Metab Disord 1994; 18(supple): S1-S7.
• Baran DT, Faulkner KG, Genant HK, Miller PD, Pacifici R. Diagnosis and management of osteoporosis: guidelines for the utilization of bone densitometry.Calcif Tissue Int 1997:62:433-440.
• Fan B, Lewiecki EM, Sherman M, Lu Y, Miller PD, Genant HK, Shepherd JA. Improved precision with Hologic Apex software. Osteoporos Int. 2008; 19:1597-602.
• Folsom AR, Kushi LH, Anderson KE et al. Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women’s Health Study. Arch Intern Med 2000; 160:2117-28.
• Genant HK, Engelke K, Fuerst T, Güer C-C, Grampp S, Harris ST, Jergas M, Lang T, Lu Y, Majumdar S, Mathur A, Takada M. Noninvasive assessment of bone mineral and structure: state of the art. J Bone Miner Res 1996; 11:707-30.
• Heymsfield SB, Wang J, Heshka S, Kehayias JJ, Pierson RN Jr. Dual-photon absorptiometry: comparison of bone mineral and soft tissue measurements in vivo with established methods. Am J Clin Nutr 1989; 49:1283-9.
• Kissebah AH, Krakower GR. Regional adiposity and morbidity. Physiol Rev 1994; 74:761-811
• Lu Y, Mathur AK, Blunt BA, et al. Dual X-ray absorptiometry quality control: comparison of visual examination and process-control charts. JBMR 1996; 11:626-37.
• Njeh CF, Fuerst T, Hans D, Blake GM, Genant HK. Radiation exposure in bone mineral density assessment. Appl Radiat Isot 1999; 50:215-36.
• Schoeller DA, Tylavsky FA, Baer DJ, Chumlea WC, Earthman CP, Fuerst T, Harris TB, Heymsfield SB, Horlick M, Lohman TG, Lukaski HC, Shepherd J, Siervogel RM, Borrud LG. QDR 4500A dual-energy X-ray absorptiometer underestimates fat mass in comparison with criterion methods in adults. Am J Clin Nutr. 2005; 81:1018-25.
• Shepherd JA, Fan B, Lu Y, Wu XP, Wacker WK, Ergun DL, Levine MA. A multinational study to develop universal standardization of whole-body bone density and composition using GE Healthcare Lunar and Hologic DXA systems. Journal of Bone and Mineral Research. 2012; 27(10): 2208-16.

Codebook and Frequencies