Analysis of Indoor Air Pollutants and Guidelines for Space and Physical Activities in Multi-Purpose Activity Space of Elementary Schools

Owing to the recent increase in the number of warning reports and alerts on the dangers of fine dusts, there has been an increasing concern over fine dusts among citizens. In spaces with poor ventilation, the occupants are forced to open the window to initiate natural ventilation via the direct introduction of the outside air; however, this may pose a serious challenge if the external fine-dust concentration is high. The lack of natural ventilation increases the indoor carbon dioxide (CO2) concentration, thus necessitating the installation of mechanical ventilation systems. This study analyzed the frequency of the application of mechanical ventilation systems in the Multi-purpose activity space of elementary schools, which are spaces where children require a higher indoor air quality than adults owing to the rapid increase in the CO2 concentration of the Multi-purpose activity space during activities. In addition, the architectural and equipment factors of the Multi-purpose activity spaces of nine elementary schools were characterized. The results revealed that five out of the nine elementary schools installed mechanical ventilation systems, whereas the remaining four schools installed jet air turnover systems. The indoor air quality of the Multi-purpose activity space of D elementary school, which had the minimum facility volume among the schools investigated in this study (564.2 m3), with up to 32 participants for each activity, was investigated. The results revealed that the ultrafine-dust (PM2.5) concentration of the facility was as high as 4.75 µg/m3 at a height of 1.2 m, and the CO2 concentration was as high as 3183 ppm. The results of the analysis of three elementary schools with different volumes were compared and analyzed using CONTAM simulation. This study determined the required volume per occupant and the optimum number of occupants for a given volume and presented guidelines for the optimum number of occupants, activities, and volume to reduce the high concentration of pollutants in the analyzed Multi-purpose activity space. The guideline proposed in this study is aimed at maintaining the CO2 concentration of the Multi-purpose activity space below 1000 ppm, as prescribed by the Indoor Air Quality Control in Public-Use Facilities, Etc. Act in South Korea.

Activity Space and Functional Outcomes in Frail Older Persons Using GPS analysis

With increasing age, walking becomes a main functional ability to participate in activities of daily living and supports independence and mobility. Frailty in older, multimorbid patients has a negative impact on physical activity and may reduce the personal activity space (AS). In this pilot study, GPS data were used to identify walking tracks to define individual AS and to compare functional performance in frail older persons. GPS data of 20 community-dwelling adults (84.5(±5.2)years, 85% women, mean frailty phenotype 1.9 (70% ≥2)points) were analyzed using a customized software to assess individual AS over a ten-months period. A geriatric home assessment including Short Physical Performance Battery (SPPB), gait speed (GS) and Timed-up-and-Go (TUG) was conducted monthly. GPS analysis revealed three different walking types presenting AS similarities: Type A walkers prefer smaller short walks nearby the home while Type B can be characterized by taking larger regular walks. Type C presents the widest AS using different transportation modes, but only a moderate number of walks. Mean group difference in functional performance of Type A walkers showed significantly reduced GS (0.45(±0.1)m/s), TUG (23.4s(±4.9)) and SPPB scores (3.8(±0.8) points; p<0.05) compared to Type C (0.82(±0.1)m/s (GS); 13.2(±1.4)s (TUG); 7.0(±1.3) points (SPPB)). Functional performance of Type B walkers (0.63(±0.2)m/s (GS); 17.1(±4.4)s (TUG); 6.5(±2.4)points (SPPB)) revealed significantly higher SPPB scores compared to Type A (p<0.05). Walks and individual AS can be mapped via GPS under everyday conditions. High heterogeneity within frail older people was observed. Persons with lower functional performance showed a reduced AS and physical activity.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals’ activity space and twin siblings’ shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

Association between physical activity and activity space in different farming seasons among rural Lao PDR residents

Background Southeast Asia is experiencing a health transition, where non-communicable diseases (NCD) are exceeding communicable diseases. Despite NCDs accounting for roughly 60–85% of deaths in the region, many developing Southeast Asian countries are beginning to address the impacts of a physically inactive lifestyle for the first time. Our study aims to bridge this gap by objectively measuring physical activity in rural Lao PDR to reveal the association among physical activity, activity space, and seasonal variation. Methods Multiple waves of survey data were collected in Songkhon District, Lao PDR between March 2010 and March 2011. Adults aged between 18 and 65 were recruited (n = 48). A portable GPS recorded participants’ activity and farmland locations and an accelerometer recorded participants’ physical activity level and daily steps for seven consecutive days. Using a directional distribution tool in ArcGIS 10.5, the activity space area of each participant in each wave was calculated. Concurrently, participants recorded time spent on each daytime activity. Linear mixed models with the fixed effects as the observations from different waves and the random effects as individual participants were developed to identify factors associated with areas of activity space and counts of daily steps, respectively. Results A total of 48 respondents aged between 19 and 57 took part in the study. Half of the participants were females. Walking was found to be the most frequent travel mode. Females were physically less active, with a smaller activity space, and were more overweight than the males in the study. Participants were physically less active during the off-farming seasons. Conclusions Findings contribute to the surveillance of risk factors needed to create healthy living environments. Our research is also one of the first to use empirical evidence demonstrating seasonal variations of rural residents’ activities in mainland Southeast Asia.