An evaluation of transport mode shift policies on transport-related physical activity through simulations based on random forests

Physical Activity Behaviour and Comparison of GPAQ and Travel Diary Transport-Related Physical Activity in Accra, Ghana

There is a lack of data on physical activity (PA), active travel, and the comparison of measurement instruments in low-resource settings. The objective of this paper is to describe PA behaviour and the agreement of walking estimates from the Global Physical Activity Questionnaire (GPAQ) and the travel diary in a low-resource setting. We used a cross-sectional survey design to capture data from the residents of Accra (Ghana) between May 2020 and March 2021. Of the 863 participants aged 15+ years, 65% were females, and 86% reported PA. The median weekly PA was 18 (interquartile range: 5-75) metabolic equivalent of task hours, with 50% of females and 37% of males achieving low PA levels. In the GPAQ, 80% of participants reported weekly walking; the mean number of days walked was 3.8 (standard deviation (SD): 2.5); hence, 54% of participants reported walking on any day, and the mean daily walking duration was 51 (SD: 82) minutes. In the diary, 56% of participants reported walking for over 24 h, with a mean walking duration of 31 (SD: 65) minutes. The correlation of walking duration between instruments was weak (rho: 0.31; 95% Confidence Interval: 0.25-0.37); the mean bias was 20 min, with GPAQ estimates being 0.1 to 9 times higher than diary estimates. We concluded that low PA is prevalent in Accra, and while the travel diary and GPAQ estimate similar walking prevalence, their walking duration agreement is poor. We recommend accompanying PA questionnaires with objective measures for calibration.

MobiliSense cohort study protocol: do air pollution and noise exposure related to transport behaviour have short-term and longer-term health effects in Paris, France?

INTRODUCTION

MobiliSense explores effects of air pollution and noise related to personal transport habits on respiratory and cardiovascular health. Its objectives are to quantify the contribution of personal transport/mobility to air pollution and noise exposures of individuals; to compare exposures in different transport modes; and to investigate whether total and transport-related personal exposures are associated with short-term and longer-term changes in respiratory and cardiovascular health.

METHODS AND ANALYSIS

MobiliSense uses sensors of location, behaviour, environmental nuisances and health in 290 census-sampled participants followed-up after 1/2 years with an identical sensor-based strategy. It addresses knowledge gaps by: (1) assessing transport behaviour over 6 days with GPS receivers and GPS-based mobility surveys; (2) considering personal exposures to both air pollution and noise and improving their characterisation (inhaled doses, noise frequency components, etc); (3) measuring respiratory and cardiovascular outcomes (smartphone-assessed respiratory symptoms, lung function with spirometry, resting blood pressure, ambulatory brachial/central blood pressure, arterial stiffness and heart rate variability) and (4) investigating short-term and longer-term (over 1-2 years) effects of transport.

ETHICS AND DISSEMINATION

The sampling and data collection protocol was approved by the National Council for Statistical Information, the French Data Protection Authority and the Ethical Committee of Inserm. Our final aim is to determine, for communicating with policy-makers, how scenarios of changes in personal transport behaviour affect individual exposure and health.

Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking

Background

Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes.

Methods

We used data of 285 participants (RECORD MultiSensor Study, 2013–2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken.

Results

Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city.

Conclusions

Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity.

Electronic supplementary material

The online version of this article (10.1186/s12966-019-0841-2) contains supplementary material, which is available to authorized users.

A scoping review of simulation modeling in built environment and physical activity research: Current status, gaps, and future directions for improving translation

Existing reviews have suggested that simulation studies of physical activity and environments are an emerging area, but none have explored findings in this area systematically. We used a scoping review framework to assess the use of simulation modeling to inform decision-making about built environment influences on physical activity. A systematic literature search was conducted in multiple databases in January 2018. Sixteen articles met the inclusion criteria. The studies evaluated interventions and features that were related to neighborhood safety (crime or traffic), active transportation, land use design, and walking and biking infrastructure. All of the studies focused on urban areas and most considered heterogeneity of outcomes based on local context. The majority of studies (70%) did not appear to have engaged or been used by practitioners or policy-makers to inform real-world decisions. There has been a growth of simulation modeling studies, but there remain gaps. The studies evaluated built environment interventions that have been recommended by expert panels, but more were of interventions related to active transportation; few considered recommended interventions to support recreational activity. Furthermore, studies have all focused on urban settings and there is a need to consider non-urban settings and how heterogeneity could reduce or exacerbate health disparities. More work to involve and evaluate practices for engaging stakeholders in model development and interpretation is also needed to overcome the translation of simulation research to practice gap, and realize its potential impact on the built environment and physical activity.

Identification of the potential prognostic genes of human melanoma

The melanoma is one of the most dangerous forms of skin diseases. It may spread to other parts of the body and cause serious illness and death. Early detection and diagnosis are crucial. However, the systemic expression analysis for the different staging of melanoma is still lacking to date. In this study, we analyzed the gene expression profiles of the different staging of melanoma by the differential expression analysis and random forest analysis. First, the results of the principal component analysis showed that the clustering of primary tumor samples, normal samples, and pigment nevus samples got closer, while the clustering of tumor metastatic samples and normal samples was far away. Moreover, the gene expression of tumor metastasis stage and the initial stage had obvious differences. Almost 426 genes identified had differential expression. The functional enrichment of differentially expressed genes was associated with the epidermal cell differentiation, epidermis development, and the keratinocyte differentiation. Taken together, our findings identified the differentially expressed signatures between primary melanoma and metastatic melanoma. Our results would provide the potential mechanisms of melanoma.