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Epidemiology and Population Health

Timing of objectively-collected physical activity in relation to body weight and metabolic health in sedentary older people: a cross-sectional and prospective analysis

Abstract

Background

Little is known about the impact of timing as opposed to frequency and intensity of daily physical activity on metabolic health. Therefore, we assessed the association between accelerometery-based daily timing of physical activity and measures of metabolic health in sedentary older people.

Methods

Hourly mean physical activity derived from wrist-worn accelerometers over a 6-day period was collected at baseline and after 3 months in sedentary participants from the Active and Healthy Ageing study. A principal component analysis (PCA) was performed to reduce the number of dimensions (e.g. define periods instead of separate hours) of hourly physical activity at baseline and change during follow-up. Cross-sectionally, a multivariable-adjusted linear regression analysis was used to associate the principal components, particularly correlated with increased physical activity in data-driven periods during the day, with body mass index (BMI), fasting glucose and insulin, HbA1c and the homeostatic model assessment for insulin resistance (HOMA-IR). For the longitudinal analyses, we calculated the hourly changes in physical activity and change in metabolic health after follow-up.

Results

We included 207 individuals (61.4% male, mean age: 64.8 [SD 2.9], mean BMI: 28.9 [4.7]). Higher physical activity in the early morning was associated with lower fasting glucose (−2.22%, 95% CI: −4.19, −0.40), fasting insulin (−13.54%, 95%CI: −23.49, −4.39), and HOMA-IR (−16.07%, 95%CI: −27.63, −5.65). Higher physical activity in the late afternoon to evening was associated with lower BMI (−2.84%, 95% CI: −4.92, −0.70). Higher physical activity at night was associated with higher BMI (2.86%, 95% CI: 0.90, 4.78), fasting glucose (2.57%, 95% CI: 0.70, 4.30), and HbA1c (2.37%, 95% CI: 1.00, 3.82). Similar results were present in the prospective analysis.

Conclusion

Specific physical activity timing patterns were associated with more beneficial metabolic health, suggesting particular time-dependent physical activity interventions might maximise health benefits.

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Fig. 1: Characteristics in (changes in) physical activity in the study population.
Fig. 2: The associations between the individual variables of metabolic health and the principal components (PC) representing the baseline physical activity.
Fig. 3: The associations between the individual variables of metabolic health and the longitudinal principal components (PC) representing change in timing of physical activity.

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Funding

The AGO study was financially supported by Philips Consumer Lifestyle, and the Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research (NGI/NOW) (grant numbers: 05040202 and 050–060–810). DvH and RN were supported by the VELUX Stiftung (grant number 1156). RN was supported by an innovation grant from the Dutch Heart Foundation [grant number 2019T103]. The funders had no role in the design, analyses and interpretation of the results of the study.

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Contributions

GA, MS, DvH, and RN conceptualised the study. GA performed the data analysis. GA, MS, DvH, and RN contributed to the interpretation of the data. CAW, SPM, FvdO, DvH, and PES contributed to the study design and CAW and SPM performed the data collection. PES, FvdO, SPM, DvH, and RN contributed to the funding acquisition. The drafting of the initial version of the paper was done by GA and RN. All authors critically revised the paper for important intellectual content. All authors read and approved the final paper.

Corresponding author

Correspondence to Gali Albalak.

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Albalak, G., Stijntjes, M., Wijsman, C.A. et al. Timing of objectively-collected physical activity in relation to body weight and metabolic health in sedentary older people: a cross-sectional and prospective analysis. Int J Obes 46, 515–522 (2022). https://doi.org/10.1038/s41366-021-01018-7

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