English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We used a biomarker of activity-related energy expenditure (AREE) to assess measurement properties of self-reported physical activity and to determine the usefulness of AREE regression calibration equations in the Women's Health Initiative. Biomarker AREE, calculated as the total energy expenditure from doubly labeled water minus the resting energy expenditure from indirect calorimetry, was assessed in 450 Women's Health Initiative participants (2007-2009). Self-reported AREE was obtained from the Arizona Activity Frequency Questionnaire (AAFQ), the 7-Day Physical Activity Recall (PAR), and the Women's Health Initiative Personal Habits Questionnaire (PHQ). Eighty-eight participants repeated the protocol 6 months later. Reporting error, measured as log(self-report AREE) minus log(biomarker AREE), was regressed on participant characteristics for each instrument. Body mass index was associated with underreporting on the AAFQ and PHQ but overreporting on PAR. Blacks and Hispanics underreported physical activity levels on the AAFQ and PAR, respectively. Underreporting decreased with age for the PAR and PHQ. Regressing logbiomarker AREE on logself-reported AREE revealed that self-report alone explained minimal biomarker variance (R(2) = 7.6, 4.8, and 3.4 for AAFQ, PAR, and PHQ, respectively). R(2) increased to 25.2, 21.5, and 21.8, respectively, when participant characteristics were included. Six-month repeatability data adjusted for temporal biomarker variation, improving R(2) to 79.4, 67.8, and 68.7 for AAFQ, PAR, and PHQ, respectively. Calibration equations "recover" substantial variation in average AREE and valuably enhance AREE self-assessment.

Physical Activity Assessment: Biomarkers and Self-Report of Activity-Related Energy Expenditure in the WHI