Physical activity and sedentary behavior surveillance using accelerometers in Japanese urban adults: A descriptive study of participation and adherence

Background Representative data collection in accelerometer-based physical activity and sedentary behavior surveys is challenging. Although in-person protocols and monetary incentives are recommended to enhance recruitment, the participation outcomes of such methods have not been thoroughly examined. This study aimed to (1) quantify response and adherence rates for an in-person, incentivized accelerometer survey; (2) assess participant representativeness; and (3) characterize reasons and factors associated with participation. Methods This cross-sectional study randomly selected 650 Japanese adults aged 20–79 from resident registers in three major metropolitan areas. Trained investigators delivered and retrieved accelerometers and questionnaires. A 5000-yen incentive was provided upon completion. Primary outcomes were response and adherence rates (≥ 4 valid wear days). Participants’ representativeness was evaluated by comparing sociodemographic characteristics with national census data, and reasons for participation and non-participation were summarized. Results The response rate was 31.5%, and the adherence rate was 29.1%. Compared to census data, participants were older and more likely to be employed and living with others; however, gender distribution was comparable. Motivations for participation differed by age: older adults were mainly motivated by health-consciousness, whereas younger adults cited the monetary incentive. Non-contact at home was a major reason for non-participation among younger adults. Conclusions The in-person, incentivized protocol achieved a higher response rate than typical mail-based methods in Japan and produced a gender-balanced sample, although some selection bias remains. These findings suggest that while this resource-intensive protocol can enhance overall recruitment, future strategies tailored to participant sociodemographic characteristics are warranted to maximize accelerometer-based data collection.