Volume 183, June 2024, 107969Author links open overlay panel, , , , , , , , Highlights•

Using mobile phone derived daily steps data over three years.

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Negative influence of Covid-19-pandemic on walking steps only exists during the early stage of the pandemic.

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Being younger and having the possibility of working from home are associated with fewer steps per day.

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Individual modeling with meta-analysis is an ideal method for large scale physical activity studies.

AbstractBackground

It has been reported that physical activity levels decreased during the COVID-19 pandemic. Previous studies often relied on self-reported physical activity, which has low accuracy. Studies based on objectively measured physical activity have had short data collection periods, thereby not allowing the consideration of pre-pandemic levels of physical activity or the influence over the different waves of the pandemic.

Methods

In this study, we utilize smartphone-measured step data from a nonprobability sample in Stockholm County, Sweden, where measures to limit the spread of COVID-19 differed from those in many other countries. The results are based on 522 individuals and 532,739 person-days with step data spanning from 2019 to 2021. Generalized additive models were fitted for each individual, and meta-regression was used to combine the results from individual models.

Results

Daily steps decreased during the first wave but increased during the third wave compared to individual pre-pandemic levels. The decrease in daily steps occurred primarily in young individuals and those with occupations allowing remote work. Individuals of retirement age on the contrary increased their daily steps during the same period.

Conclusions

This study reveal that the influence of the COVID-19 pandemic was temporary and that younger age and the possibility of working from home were associated with a decreasing trend in physical activity.

Keywords

COVID-19

Physical activity

Walking step

Time-series analysis

Public health

AbbreviationsGeneral additive model

GAM

Availability of data and materials

The code used for data analysis is available online (Zhou, 2024). Data used for this study are available upon reasonable request (send inquires to [email protected]). Data from Hälsometern is protected by the General Data Protection Regulation of the European Union (GDPR).

© 2024 The Authors. Published by Elsevier Inc.