Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study.


Journal

Annals of nutrition & metabolism
ISSN: 1421-9697
Titre abrégé: Ann Nutr Metab
Pays: Switzerland
ID NLM: 8105511

Informations de publication

Date de publication:
2020
Historique:
received: 19 06 2019
accepted: 25 01 2020
pubmed: 17 3 2020
medline: 29 5 2021
entrez: 16 3 2020
Statut: ppublish

Résumé

Evaluation of total energy expenditure (TEE) and physical activity level (PAL) is important for treatment of patients with type 2 diabetes mellitus (T2DM). However, the validity of accelerometers (ACC) and physical activity questionnaires (PAQ) for estimating TEE and PAL remains unknown in elderly populations with T2DM. We evaluated the accuracy of TEE and PAL results estimated by an ACC (TEEACC and PALACC) and a PAQ (TEEPAQ and PALPAQ) in elderly patients with T2DM. Fifty-one elderly patients with T2DM (aged 61-79 years) participated in this study. TEEACC was calculated with PALACC using a triaxial ACC (Active style Pro HJA-750c) over 2 weeks and predicted basal metabolic rate (BMR) by Ganpule's equation. TEEPAQ was estimated using predicted BMR and the PALPAQ from the -Japan Public Health Center Study-Long questionnaire. We compared the results to TEEDLW measured with the doubly labeled water (DLW) method and PALDLW calculated with BMR using indirect calorimetry. TEEDLW was 2,165 ± 365 kcal/day, and TEEACC was 2,014 ± 339 kcal/day; TEEACC was strongly correlated with TEEDLW (r = 0.87, p < 0.01) but significantly underestimated (-150 ± 183 kcal/day, p < 0.05). There was no significant difference in TEEPAQ and TEEDLW (-49 ± 284 kcal/day), while the range of difference seemed to be larger than TEEACC. PALDLW, PALACC, and PALPAQ were calculated to be 1.71 ± 0.17, 1.69 ± 0.16, and 1.78 ± 0.24, respectively. -PALACC was strongly correlated with PALDLW (r = 0.71, p < 0.01), and there was no significant difference between the 2 values. PALPAQ was moderately correlated with PALDLW (r = 0.43, p < 0.01) but significantly overestimated. Predicted BMR was significantly lower than the BMR -measured by indirect calorimetry (1,193 ± 186 vs. 1,262 ± 155 kcal/day, p < 0.01). The present ACC and questionnaire showed acceptable correlation of TEE and PAL compared with DLW method in elderly patients with T2DM. Systematic errors in estimating TEE may be improved by the better equation for predicting BMR.

Identifiants

pubmed: 32172232
pii: 000506223
doi: 10.1159/000506223
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

62-72

Informations de copyright

© 2020 S. Karger AG, Basel.

Auteurs

Yuki Nishida (Y)

Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.

Shigeho Tanaka (S)

Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan, tanakas@nibiohn.go.jp.

Satoshi Nakae (S)

Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.
Division of Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.

Yosuke Yamada (Y)

Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.
Section of Healthy Longevity Research, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.

Katsutaro Morino (K)

Department of Medicine, Shiga University of Medical Science, Shiga, Japan.

Keiko Kondo (K)

Department of Public Health, Shiga University of Medical Science, Shiga, Japan.

Kaori Nishida (K)

Division of Clinical Nutrition, Shiga University of Medical Science, Shiga, Japan.

Akiko Ohi (A)

Division of Clinical Nutrition, Shiga University of Medical Science, Shiga, Japan.

Mika Kurihara (M)

Division of Clinical Nutrition, Shiga University of Medical Science, Shiga, Japan.

Masaya Sasaki (M)

Division of Clinical Nutrition, Shiga University of Medical Science, Shiga, Japan.

Satoshi Ugi (S)

Department of Medicine, Shiga University of Medical Science, Shiga, Japan.

Hiroshi Maegawa (H)

Department of Medicine, Shiga University of Medical Science, Shiga, Japan.

Naoyuki Ebine (N)

Faculty of Health and Sports Science, Doshisha University, Kyoto, Japan.

Satoshi Sasaki (S)

Department of Social and Preventive Epidemiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Fuminori Katsukawa (F)

Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan.

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