Hourly step recommendations to achieve daily goals for working and older adults.

ABSTRACT

BACKGROUND: The widespread use of physical activity trackers enables the collection of high-resolution health data, such as hourly step counts, to evaluate health promotion programmes. We aim to investigate how participants meet their daily step goals. METHODS: We used 24-h steps data from the National Steps ChallengeTM Season 3, wherein participants were rewarded with vouchers when achieving specified goals of 5000, 7500, and 10,000 steps per day. We extracted data from 3075 participants' including a total of 52,346 participant-days. We modelled the hourly step counts using a two-part model, in which the distribution for step counts was allowed to depend on the sum of step counts up to the previous hour and participant demographics. RESULTS: Participants have a mean age of 44.2 years (standard deviation = 13.9), and 40.4% are males. We show that on weekdays, the hourly mean step counts among participants aged 60 and above are higher than participants aged 30 to 59 from the start of the day till 6 p.m. We also find that participants who accumulate at least 7000 steps by 7 p.m. are associated with higher success of achieving 10,000 steps. CONCLUSIONS: We provide recommendations on the hourly targets to achieve daily goals, based on different participants' characteristics. Future studies could experimentally test if prompts and nudges at the recommended times of day could promote reaching step goals.

The National Steps ChallengeTM is a nationwide physical activity programme in Singapore that encourages participants to exercise more. We used daily step data from over 3000 adult participants to investigate how different types of participants met their daily step goals. We found that participants who had taken at least 7000 steps by 7 p.m. were more likely to achieve 10,000 steps by the end of the day. Based on our analysis, we propose specific recommendations for hourly targets based on characteristics such as age and sex. Our study provides a better understanding of the population's physical activity levels which will enable people to be given targeted recommendations based on their own characteristics that might facilitate them more easily meeting their exercise goals.