Understanding the factors that shape daily mobility during pregnancy is essential for inclusive transportation planning that promotes active travel for all. Using smartphone-based Global Positioning System data from 860 pregnant women in Barcelona, Spain, we evaluated the correlates of active and passive travel in early and late pregnancy. We identified 33 correlates from 48 candidate variables including personal characteristics, the residential physical environment, the social environment, and temporal factors. The most important correlate across pregnancy was non-European ethnic origin, being associated with 10–15 min less daily active travel. In early pregnancy, commuting distance was the most important correlate, being positively associated with passive travel, while the COVID-19 pandemic was associated with less passive travel. In late pregnancy, residential walkability and having a university degree were positively associated with active travel. The neighbourhood education level was associated with more active travel, particularly during weekends. We discuss key priorities for supporting active travel during pregnancy.

Health implications of mobility during pregnancy entail a need to understand pregnant women's activity spaces. We present ActMAP, a framework for quantifying multiple aspects of activity spaces from distinct trips and stays derived from GPS data. We applied ActMAP to data from 238 pregnant women in Barcelona, Spain (2018–2020) and explored weekday, weekend and intraday associations between pregnancy trimester and activity spaces. Activities were more centred around the home later in pregnancy. However, the number of visited places and daily trips remained largely constant throughout pregnancy. By constructing activity spaces from individual trips and stays, ActMAP could provide a framework for GPS-based holistic assessments of mobility.

Greenspace can promote health via diverse pathways. A common approach to assessing greenspace exposure is to estimate vegetation availability within buffers surrounding locations where people reside or spend time. However, no clear framework for informed buffer selection exists, and choices made show considerable heterogeneity, impeding evidence synthesis and causal inference. In this Personal View conducted by an interdisciplinary panel of experts, we aimed to establish a framework for informed buffer selection for epidemiological studies on greenspace. We began by reviewing available approaches for the selection of buffer types, which range from single fixed-location approaches to high-resolution mobility-based activity-space approaches, as well as different buffer sizes. We then summarised the determinants of buffer type and size selection including health outcomes and underlying mechanisms, study population, contextual factors, and data characteristics. Finally, based on these determinants, we developed recommendations for future research. Buffer type and size selection should be hypothesis driven, reflecting presumed greenspace–health mechanisms. Buffer selection should target activity-based approaches where feasible, and multiple buffer sizes should be tested. Overall, the assessment of greenspace exposure should shift from ad-hoc approaches to personalised, multiscale, and context-specific methods. We call for standardising and reporting the rationale for buffer selection to minimise bias and enhance comparability and evidence synthesis across studies.