A. Psyllidis
Please Note
37 records found
1
Transport-related social exclusion in Latin America
A multilingual scoping review of modal choice and travel behaviour
Population-specific factors of pedestrian accessibility
Bridging practitioner insights and accessibility metrics
Mobility Futures
Four scenarios for the Dutch mobility system in 2050
CTwalk
A tool for mapping potential inter-population encounters In X-minute neighborhoods
Bridging or separating?
Co-accessibility as a measure of potential place-based encounters
Children’s access to urban greenspace
A survey of factors and measures
Recent evidence underscores the importance of greenspace exposure in promoting physical activity, and in having a positive impact on mental health and cognitive development. Accessibility has been identified to be the primary motivating factor when it comes to encouraging greenspace use and, correspondingly, exposure. Existing quantitative approaches to measuring greenspace accessibility predominantly focus on the areas surrounding home locations, often disregarding access from other settings such as schools or workplaces, exposures while on the move, and mobility differences among different population age groups. This article introduces a novel method to measure greenspace accessibility that considers access from different activity settings (i.e., homes, schools, and the commutes between them) for children and adolescents, while accounting for the dependency of human access on the road network. We use Amsterdam, Rotterdam, and The Hague in the Netherlands as case studies to illustrate the utility of our method. Compared to conventional measures of greenspace accessibility, we show that accounting for school and commuting settings, in addition to residences, captures previously untapped accessibility aspects for both children and adolescents. Our approach can be replicated in other cities worldwide, with the aspiration to provide planners and public health policy-makers with a methodological tool that can help in evaluating access and use of greenspaces when designing health-promoting interventions.
“Eyes on the Street”
Estimating Natural Surveillance Along Amsterdam’s City Streets Using Street-Level Imagery
Is it safe to be attractive?
Disentangling the influence of streetscape features on the perceived safety and attractiveness of city streets
Points of Interest (POI)
A commentary on the state of the art, challenges, and prospects for the future
Early environmental quality and life-course mental health effects
The Equal-Life project
There is increasing evidence that a complex interplay of factors within environments in which children grows up, contributes to children’s suboptimal mental health and cognitive development. The concept of the life-course exposome helps to study the impact of the physical and social environment, including social inequities, on cognitive development and mental health over time.
Methods:
Equal-Life develops and tests combined exposures and their effects on children’s mental health and cognitive development. Data from eight birth-cohorts and three school studies (N = 240.000) linked to exposure data, will provide insights and policy guidance into aspects of physical and social exposures hitherto untapped, at different scale levels and timeframes, while accounting for social inequities. Reasoning from the outcome point of view, relevant stakeholders participate in the formulation and validation of research questions, and in the formulation of environmental hazards. Exposure assessment combines GIS-based environmental indicators with omics approaches and new data sources, forming the early-life exposome. Statistical tools integrate data at different spatial and temporal granularity and combine exploratory machine learning models with hypothesis-driven causal modeling.
Conclusions:
Equal-Life contributes to the development and utilization of the exposome concept by (1) integrating the internal, physical and social exposomes, (2) studying a distinct set of life-course effects on a child’s development and mental health (3) characterizing the child’s environment at different developmental stages and in different activity spaces, (4) looking at supportive environments for child development, rather than merely pollutants, and (5) combining physical, social indicators with novel effect markers and using new data sources describing child activity patterns and environments. ...
There is increasing evidence that a complex interplay of factors within environments in which children grows up, contributes to children’s suboptimal mental health and cognitive development. The concept of the life-course exposome helps to study the impact of the physical and social environment, including social inequities, on cognitive development and mental health over time.
Methods:
Equal-Life develops and tests combined exposures and their effects on children’s mental health and cognitive development. Data from eight birth-cohorts and three school studies (N = 240.000) linked to exposure data, will provide insights and policy guidance into aspects of physical and social exposures hitherto untapped, at different scale levels and timeframes, while accounting for social inequities. Reasoning from the outcome point of view, relevant stakeholders participate in the formulation and validation of research questions, and in the formulation of environmental hazards. Exposure assessment combines GIS-based environmental indicators with omics approaches and new data sources, forming the early-life exposome. Statistical tools integrate data at different spatial and temporal granularity and combine exploratory machine learning models with hypothesis-driven causal modeling.
Conclusions:
Equal-Life contributes to the development and utilization of the exposome concept by (1) integrating the internal, physical and social exposomes, (2) studying a distinct set of life-course effects on a child’s development and mental health (3) characterizing the child’s environment at different developmental stages and in different activity spaces, (4) looking at supportive environments for child development, rather than merely pollutants, and (5) combining physical, social indicators with novel effect markers and using new data sources describing child activity patterns and environments.