This release provides raw data from the physical activity monitor (PAM) component for the NHANES National Youth Fitness Survey (NNYFS). Participants were asked to wear the PAM for seven consecutive days to collect objective information on 24-hour movement when awake and asleep. The same PAM component was also included in the main NHANES program in 2011-2014.
Measurement of physical activity with accelerometers had been implemented in NHANES 2003-2006. The PAM used in 2012 NNYFS and NHANES 2011-2014 measured acceleration (i.e., on the x-, y-, and z-axes) every 1/80th of a second (80 Hz). The collected 80 Hz accelerometer measurements have been summed over each minute, hour, and day for each participant and released in separate files for the NNYFS (i.e., Y_PAXHD, Y_PAXMIN, Y_PAXHR, Y_PAXDAY). This release provides the raw data collected through the PAM component, including the following two sets of data files:
A) Accelerometer data files:
Due to the quantity of the data, the 80 Hz accelerometer measurements are organized and stored at the participant level. The data collected for each participant was grouped into one-hour blocks to ease the file management in a cloud or another clustered processing environment. There are up to 194 hourly accelerometer data files for each participant with the number of files corresponding to the length of time the participant wore the monitor with one file for the first ½ hour, one file for each subsequent full hour and one file for the final remaining portion of an hour. Within each hourly accelerometer file, there is one record of the accelerometer measurements data per each 1/80th of a second time point (288,000 records per full hour).
B) Data quality control file:
Visual inspection of graphical data revealed small portions of accelerometer measurements to be implausible and/or unrepresentative of human motion. It is thought that these data irregularities were a result of rare sensor malfunctions or erroneous data translations. Algorithms were developed to automate the checking of these conditions; and subsequent determinations of suspect data were ascribed to one or more of the following reasons:
Across all data collection cycles from NHANES 2011-2014 and 2012 NNYFS, approximately 0.26% of the data were flagged in the quality control checks with most of the suspect data confined to a small percentage of participants. These suspect data detected by the algorithms were released as collected, with their corresponding QC flags documented in the data quality control file for each participant.
To facilitate online access of the data, files included in this release were compressed using the bzip2 format to further reduce file sizes. For each participant, there is one zipped archive file (tar.bz2 format) containing up to 194 hourly accelerometer data files (.csv format) and one data quality control file (.csv format). As bzip2 is a freely available and open-source file compression program, these zipped archive files can be uncompressed using standard compression software (e.g., Winzip) or with common compression utilities available in R and Python.
All participants were asked to wear a PAM for 7 consecutive days.
Participants were asked to wear the PAM starting on the day of their exam in the NHANES Mobile Examination Center (MEC) and to keep wearing the PAM the remainder of the first day, all day and night for the next seven full days (midnight to midnight) and remove it on the morning of the 9th day. The device used in NHANES was the ActiGraph model GT3X+, manufactured by ActiGraph of Pensacola, FL. This model was chosen because of its ability to obtain triaxial measure, its battery life, and its water resistance (ActiGraph, 2013). The devices were programmed to begin detecting and recording the magnitude of acceleration, at 80 Hz sampling intervals, at the end of the participant’s MEC exam session and to stop recording data eight days later (i.e., on the 9th calendar day). The device was placed on a mesh wristband (like a watch), custom fitted for each participant’s wrist and worn on the non-dominant hand, if possible. The participant was told not to do anything with the device except to wear it. If the participant needed to remove it, for any reason, he/she was instructed to put it back on the same wrist in the same orientation, as soon as possible.
A toll-free number and information materials describing the PAM were given to the participant. No activity logs, diaries, or records were kept by the participant. The PAMs were returned by mail in postage-paid padded envelopes provided to each participant.
For further details see the PAM procedures manual.
Survey staff completed an examiner training program that covered the basic operating features of the PAM, equipment operation, subject recruitment strategies, PAM device initialization, and troubleshooting. Field performance and response rates were monitored by NCHS and contractor staff.
Once PAMs were received from participants, data were downloaded from the devices. In 2019, contractors at Northeastern University in Boston, MA, under the direction of PAM component collaborators from the National Cancer Institute (NCI) and staff from the National Center for Health Statistics (NCHS) reviewed these data. The data quality review considered the properties of the raw acceleration measures, which are in units of gravity (g). Raw signals were processed to determine signal patterns that were unlikely to be a result of human movement, such as maximum or minimum values (±6 g) for extended periods of time, spikes in values, and impossible values (e.g., no gravitational acceleration observed, etc.). Refer to the Data Processing and Editing section of this document for more detailed descriptions of the data quality flag code values and descriptions.
Not every eligible NHANES participant has a data file. For example, if a participant refused to wear the PAM, did not return it, or the data could not be retrieved from a damaged PAM, then the participant does not have a data file. Each participant may have up to 194 hours of accelerometer measurement records. Per the protocol, the first day and last day of data collection for each participant are partial days.
As noted previously, grouping the 80 Hz accelerometer data for each participant into multiple hour-long files simplifies file management and data processing. The file names provide important timing information, which permits the file to contain nothing but a header line and accelerometer data, making it easy to concatenate the raw data files into larger files, if desired. The hourly accelerometer files (up to 194 per participant) employ the following naming convention:
GT3XPLUS-AccelerationCalibrated-[FIRMWARE_VERSION].[SENSOR_ID].[YYYY]-[MM]-[DD]-[HH]-[MM]-[SS]-000-P0000.sensor.csv.gz
where
The hourly accelerometer files (up to 194 per participant) contain the following four fields:
HEADER_TIMESTAMP (Date and time stamp)
A datetime in the following format: YYYY-MM-DD HH:MM:SS.MMM, where YYYY-MM-DD represents a date (e.g., “2000-01-03”) and HH:MM:SS.MMM represents a time with MMM indicating the millisecond value (e.g.,
“13:30:00.225” is 13:30:00 + 225 milliseconds).
X (x-axis acceleration value)
Floating-point x-axis acceleration value extracted from the gt3x file, ranging from -6.006 to +6.006 (up to three decimal places). Typically, the value is between -6.000 to +6.000, but values 0.006 higher and lower, respectively, have been observed.
Y (y-axis acceleration value)
Floating-point y-axis acceleration value extracted from the gt3x file, ranging from -6.006 to +6.006 (up to three decimal places). Typically, the value is between -6.000 to +6.000, but values 0.006 higher and lower, respectively, have been observed.
Z (z-axis acceleration value)
Floating-point z-axis acceleration value extracted from the gt3x file, ranging from -6.006 to +6.006 (up to three decimal places). Typically, the value is between -6.000 to +6.000, but values 0.006 higher and lower, respectively, have been observed.
The data quality control files (one per participant) use the following naming convention:
[SEQN]_Logs.csv
where SEQN is the respondent sequence number of the participant.
The data quality control file for each participant contains the following five fields:
DAY_OF_DATA (Ordinal day of data collection)
Integer value (1-9) representing the ordinal day of data (e.g., 1st, 2nd, 3rd, etc.) for this record.
START_TIME (Starting time of this day)
Time in HH:MM:SS.MMM (MMM indicating the millisecond value) format, representing the starting time in the day for this range of suspect data.
END_TIME (Ending time of this day)
Time in HH:MM:SS.MMM (MMM indicating the millisecond value) format, representing the ending time in the day for this range of suspect data.
DATA_QUALITY_FLAG_CODE (Quality control flag triggered)
Codes used to denote data issues that have been identified by the quality control checks for records collected during the time period indicated in the START_TIME and END_TIME columns. More detail about these codes is available at: Data Quality Flag Summary Table for the Physical Activity Monitor (PAM) Data Collected in NHANES 2011-2014 and NNYFS.
DATA_QUALITY_FLAG_VALUE (Frequency count of triggered quality control flag)
Count indicating how often the quality control flag was triggered for records collected during the time period indicated in the START_TIME and END_TIME columns.
NOTE: the same or overlapping time periods may have been flagged for multiple reasons in which case multiple, overlapping records covering the same time period would exist in the data quality control file with one record per reason.
For participants with no accelerometer measurement flagged by the QC checks during the hour, all five fields in the data quality control file for that particular hour group will be blank.
The NNYFS examination sample weights should be used to analyze the PAM data. Please refer to the NNYFS Analytic Guidelines for details on the use of sample weights and other analytic issues.
The PAM component was reintroduced to NHANES in 2011-2014 and was included in the 2012 NHANES National Youth Fitness Survey (NNYFS) as well. A total of 16,417 persons ages 3 years and older wore the PAM during these surveys and had data available for analysis: 2011-2012 NHANES participants 6 years and older (n=6,917); 2013-14 NHANES participants 3 years and older (n=7,776); and 2012 NNYFS participants 3-15 years (1,477). In addition, PAM data were collected for 3-5 years old participants in the 2012 NHANES (n=247) as well. However, due to disclosure concerns, these data are only available in the NCHS Research Data Center (RDC). Overall, 96% of participants with data wore the PAM until the 9th day. About 2% of the participants with PAM data wore it for less than 7 days. On the non-partial days (that is, not the first or last days of wear) the mean number of valid minutes per day was ~1,437 minutes out of a possible 1,440 valid minute. In NHANES and the NNYFS, approximately 99% of the PAMs in each survey were placed on the non-dominant arm of the participant.
In the NNYFS, PAM data is available for 1,477 participants 3 years and older. The current release (Y_PAX80) consists of 1,477 zipped archive files – one for each participant. Due to the very large quantity of the data, these files are stored at the CDC File Transfer Protocol (FTP) Server. To access, please click on the “Y_PAX80 Data” link on the NNYFS Examination Data webpage. This link will take users to the FTP folder containing all 1,477 zip files for Y_PAX80. Users can either click the individual hyperlinks to download selected files manually or write a script in the language of their choice to download all the files together. Please note that the total file size for Y_PAX80 (~245 GB compressed for all 1,477 files) is substantially larger than most traditional NNYFS data files. Users should plan accordingly for storage space and downloading time. Note that due to the files being compressed, the actual storage space required for processing can be expected to increase multiplicatively once the files are uncompressed.
The suspect data that was flagged in the data quality control file for each participant does not constitute an exhaustive list of all possible data errors. Users should be aware that additional, or alternative, error-checking of such high-frequency data may require complex signal visualization and or analysis beyond that presented here. Users should take this information under advice when determining which data to include, or exclude from, analysis.