Association between Daily Living Walking Speed and Lifestyle and Physiological Factors in Older, Female Pokémon GO Players

Background: Walking speed is a reliable barometer of adverse health outcomes, particularly among older people. Few studies evaluated factors associated with daily actual walking speed, rather than that measured in a laboratory setting or self-reported data. Methods: In a joint effort with The Pokémon Company, we recruited study participants through a women’s magazine and analyzed data from 63 Pokémon GO players. We measured the true walking speed in daily life among older women using a data-gathering mobile application. Then, using questionnaire survey data collected on these participants in 2019, we estimated the relationship between walking speed and their lifestyle and physiological factors. In the analysis, we employed a bi-directional stepwise linear regression approach, with the Akaike information criterion (AIC) for variable selection. Results: The mean age of the 63 participants was 63.03 years (standard deviation, SD 7.46);the average walking speed was 4.56 km per hour (SD 1.54);and 52 (82.5%) and 55 (87.3%) participants answered that they had excellent/good health physically and mentally, respectively. After adjusted for covariates in a stepwise regression approach, we identified a significant association between −1.33 (95% confidence intervals −2.52 to −0.15) km/hour lower walking speed and the experience of outdoor falls within a year. We also demonstrated that the walking speed was 1.07 (0.33 to 1.81) km/hour faster for those who had played Pokémon GO before the study started. Conclusions: The true walking speed in daily life among older women was measured by a data-gathering mobile application. Although all participants were women recruited on a voluntary basis with an understanding of the purpose of the study, and the surveys were conducted at a cross-sectional setting, a significant relationship with the experience of outdoor falls was demonstrated. We also present evidence suggesting a possible relationship between Pokémon GO play and faster walking speed.

System identification and parameter estimation in mathematical medicine： examples demonstrated for prostate cancer

We review our studies on how to identify the most appropriate models of diseases, and how to determine their parameters in a quantitative manner given a short time series of biomarkers, using intermittent androgen deprivation therapy of prostate cancer as an example. Recently, it has become possible to estimate the specific parameters of individual patients within a reasonable time by employing the information concerning other previous patients as a prior. We discuss the importance of using multiple mathematical methods simultaneously to achieve a solid diagnosis and prognosis in the future practice of personalized medicine.