Abstract

BackgroundDespite a global call for action and growing burden of non-communicable diseases (NCD) associated with physical inactivity, effective interventions to increase community-wide physical activity (PA) remain few. NCDs accounted for 80% of Singapore’s disease burden (2015) and yet 40% of Singaporeans did not meet minimum recommended weekly PA despite evidence of the benefits to cardiorespiratory health, diabetes and cancer prevention.MethodsA large-scale public health intervention was initiated in 2015 to increase population-level PA through incidental daily walking. Intervention components included fitness trackers, redeemable rewards and gamification, implemented in a mutually-reinforcing manner within an eco-system supportive of PA and informed by real-time data analytics. Mean daily step count at baseline and post-intervention were compared across periods, and the influence of participant sub-groups characteristics on overall results, using significance tests. Standards for Reporting on Implementation Studies (StaRI) were adhered to.ResultsIntervention reach increased fourfold from 129,677 participants in wave 1 (2015–16) to 690,233 in wave 3 (2017–18) amounting to a total of 1,184,410 Step Challenge participations. Mean days of fitness tracker use increased from 2.4 to 5.0 days/week among participants completing the Challenge in wave 1 and from 5.3 to 6.0 days/week in wave 3. The mean number of daily steps between pre-Challenge and Challenge periods increased by 4163 (sd=1360; p< 0.001) in wave 1, by 2242 (sd=334; p< 0.001) in wave 2 and by 1645 steps/day (sd=54; p< 0.001) in wave 3. Mean daily step increases between wave 1 and 3 also suggest that incidental PA was maintained, a finding supported by a 2017 national population survey showing that incidental PA among adults increased from 5% in 2010 to 14% in 2017 while moderate-intensity PA increased from 5 to 10% over the same period.ConclusionPopulation-level PA was effectively increased through multi-level interventions integrating technology, behavioural economics, gamification, marketing, communications and community linkages within a supportive context- and climate-appropriate environment. Responsive data analytics were instrumental to strengthen implementation by tailoring modalities that maximise effectiveness at population-level. Further analyses are needed to explore potential barriers, challenges or unmet needs in sub-groups with lower uptake to tailor future interventions for greater reach and impact.

Highlights

  • Despite a global call for action and growing burden of non-communicable diseases (NCD) associated with physical inactivity, effective interventions to increase community-wide physical activity (PA) remain few

  • Study population The eligibility criteria to participate in this intervention were residing in Singapore, being 17 years or older, able to provide consent to readiness for PA and to the use of aggregated data for analysis by Health Promotion Board (HPB)

  • The proportion of participants reporting < 150 min of weekly PA at baseline increased from 15% in wave 1 to 21% in wave 3 but remained lower than the overall Singapore population (26%)

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Summary

Methods

A large-scale public health intervention was initiated in 2015 to increase population-level PA through incidental daily walking. Intervention components included fitness trackers, redeemable rewards and gamification, implemented in a mutually-reinforcing manner within an eco-system supportive of PA and informed by real-time data analytics. Mean daily step count at baseline and post-intervention were compared across periods, and the influence of participant sub-groups characteristics on overall results, using significance tests. Study population The eligibility criteria to participate in this intervention were residing in Singapore, being 17 years or older, able to provide consent to readiness for PA and to the use of aggregated data for analysis by HPB. Conceptual approach and design The overall design, data collection, planning and execution adopted an implementation science approach using real-time data analytics [27,28,29]. The implementation strategy was grounded in a socio-ecological framework approach that built on HPB’s ground presence and supportive social, economic and structural environment to enable individual and population-level PA [30,31,32,33,34]

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