The health impact of nature exposure and green exercise across the life course: a pilot study

Background: Both nature exposure and green exercise (GE) provide numerous health benefits. However, there are no studies examining the impact of childhood GE on adult health. Methods: 45 healthy adults (aged 69.8 ± 8.4 years) took part in the study, wearing a Firstbeat heart rate variability (HRV) monitor for 24 hours. Participants also completed questionnaires assessing childhood and adulthood nature exposure and GE, as well as current connectedness to nature (CN), perceived stress and well-being. Pearson’s correlations and linear regression were used to examine relationships between variables. Results: Childhood nature exposure and GE significantly predicted adult nature exposure and GE (β .317, p < 0.05) as well as CN (β = .831, p < 0.01). After controlling for childhood nature exposure and GE, CN was negatively associated with the percentage of stress over the 24-hour period (r = −.363; p < 0.05) and positively associated with HRV during sleep (r = .415; p < 0.05). Conclusions: CN is important for adult health; however childhood nature exposure and GE are essential to developing this connection

Measuring quality of walkable urban environment through experiential modeling

Smart city design should have one ultimate goal; to improve the human well-being (or quality of life) of its inhabitants. National level planning of economy and societal structures has recently paid more attention to the well-being of citizens. In order to design for well-being and smart communities, it is important to not only understand the dimensions of well-being but also to develop easy to apply measurement methods for city planners. As the first step for creating well-being in smart communities, this study presents two concrete cases where we have measured well-being. These early attempts provide us with only narrow visibility of multidimensional well-being but prove to us that mart well-being measurement systems are possible—and useful—to build. A street imagery tool and an image assessment with a machine learning technique was used for evaluating streetscapes and perceptions of heat wave tweets in Kyojima district and in Tokyo, Japan. Finally, based on our experiences in these two cases, we summarize a measurement framework for a comprehensive multidata well-being assessment system