Illustration of measurement error models for reducing biases in nutrition and obesity research using 2D body composition data

DOI

The files required to reproduce the results of our manuscript entitled, “Illustration of measurement error models for reducing biases in nutrition and obesity research using 2D body composition data” published in Obesity are provided. The data and data dictionary for the Photobody Study and codes corresponding to this manuscript are in this folder.

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The inclusion criteria were: adults aged 19 to 80 years, living in Birmingham, Alabama.  The exclusion criteria were: 1) weight greater than 450 lbs (weight limit of DXA equipment); 2) presence of health conditions that would prevent participants from lying down for DXA scans or standing for taking photographs or that may alter body composition (e.g., cancer, cachexia, or rheumatoid arthritis); 3) missing body parts (except a finger or toe); and 4) pregnant individuals.Smallest Geographic Unit: N/A

other~~Specific details about the recruitment and study design can be found in the Methods section in our publication or one of the original papers:

1.      Pradhan, L., et al. Feature extraction from 2D images for body composition analysis. in Multimedia (ISM), 2015 IEEE International Symposium on. 2015. IEEE.

2.      Capers, P.L., et al., Visual Representation of Body Shape in African-American and European American Women: Clinical Considerations. Clinical medicine insights. Women's health, 2016. 9(Suppl 1): p. 63.3.       Affuso, O., et al., A method for measuring human body composition using digital images. PloSOne (in press, 2018). 

Identifier
DOI https://doi.org/10.3886/E106966V1
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:658568
Provenance
Creator Affuso, Olivia
Publisher ICPSR - Interuniversity Consortium for Political and Social Research
Contributor United States Department of Health and Human Services. National Institutes of Health. National Heart Lung and Blood Institute; United States Department of Health and Human Services. National Institutes of Health. National Institute of Diabetes and Digestive and Kidney Diseases; United States Department of Health and Human Services. National Institutes of Health. National Center for Advancing Translational Sciences; United States Department of Health and Human Services. National Institutes of Health. National Cancer Institute
Publication Year 2018
Rights Download
OpenAccess true
Contact ICPSR - Interuniversity Consortium for Political and Social Research
Representation
Resource Type Dataset; clinical data
Discipline Social Sciences