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Supplemental material, sj-docx-2-eab-10.1177_00139165231182686 for Is Neighborhood Nature an Ecological Precursor of Parenting Practices, Infant-Parent Bonding, and Infant Socioemotional Function? by Lærke Mygind, Christopher Greenwood, Primrose Letcher, Suzanne Mavoa, Kate Lycett, Yichao Wang, Trine Flensborg-Madsen, Peter Bentsen, Jacqui A. Macdonald, Kimberly Thomson, Delyse Hutchinson, Craig A. Olsson and Peter G. Enticott in Environment and Behavior

Supplemental material, sj-docx-3-eab-10.1177_00139165231182686 for Is Neighborhood Nature an Ecological Precursor of Parenting Practices, Infant-Parent Bonding, and Infant Socioemotional Function? by Lærke Mygind, Christopher Greenwood, Primrose Letcher, Suzanne Mavoa, Kate Lycett, Yichao Wang, Trine Flensborg-Madsen, Peter Bentsen, Jacqui A. Macdonald, Kimberly Thomson, Delyse Hutchinson, Craig A. Olsson and Peter G. Enticott in Environment and Behavior

Supplemental material, sj-docx-1-eab-10.1177_00139165231182686 for Is Neighborhood Nature an Ecological Precursor of Parenting Practices, Infant-Parent Bonding, and Infant Socioemotional Function? by Lærke Mygind, Christopher Greenwood, Primrose Letcher, Suzanne Mavoa, Kate Lycett, Yichao Wang, Trine Flensborg-Madsen, Peter Bentsen, Jacqui A. Macdonald, Kimberly Thomson, Delyse Hutchinson, Craig A. Olsson and Peter G. Enticott in Environment and Behavior

openaire: EC/H2020/856602/EU//FINEST TWINS Funding Information: KH is supported by Academy of Finland as part of PLANhealth Project (13297753). KH would also like to acknowledge FinEst (H2020 grant 856602) for supporting this study. SM was supported by an Australian National Health and Medical Research Council Early Career Fellowship (#1121035) and a University of Melbourne Faculty of Medicine, Dentistry and Health Sciences Research Fellowship. EI is supported by the Medical Research Council [MC_UU_12015/7, MC_UU_00006/5]. MS is supported by a Health Research Council of New Zealand Sir Charles Hercus Research Fellowship (Grant number 17/013). Neighbourhoods for Active Kids was funded by the Health Research Council of New Zealand (grant number 14/436). Authors would like to acknowledge prof. Marketta Kyttä her contribution to this research. Publisher Copyright: © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Measures of individual mobility, such as activity space, have been previously used to help improve our understanding of individuals’ interactions with their everyday environments. However, such methods have rarely been adopted in studying children's physical activity and active travel behavior. In this study, we use a combination of participatory mapping and accelerometer data collected from children aged 8–13 years living in Tāmaki Makaurau/Auckland, Aotearoa/New Zealand, to describe children's travel behavior and explore associations of active travel, physical activity, and socio-demographic characteristics with environmental attributes. The results from this study reveal complex associations between these different layers. Density of cycling routes was consistently associated with higher levels of physical activity captured via moderate-to-vigorous physical activity (MVPA), prevalence of active travel, and total activity space exposure. Nevertheless, population density, greenspace, and land-use mix revealed varying associations across different activity behaviors including MVPA, number of steps, and prevalence of active travel. The results from this study not only reassert the complexity of person–environment relationships, but also highlight the potential impacts of measurement and analytical methods on the study results. The novel combination of participatory mapping and accelerometer data together with activity space analysis provided new analytical insights which we discuss in this paper. This study concludes by reporting its observations and envisioning future research directions.

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisions to be based on the strongest science possible, transparency and clarity in reporting in spatial lifecourse epidemiologic studies is essential. A task force supported by the International Initiative on Spatial Lifecourse Epidemiology (ISLE) identified a need for guidance in this area and developed a Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) Statement. The aim is to provide a checklist of recommendations to improve and make more consistent reporting of spatial lifecourse epidemiologic studies. The STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement for cohort studies was identified as an appropriate starting point to provide initial items to consider for inclusion. Reporting standards for spatial data and methods were then integrated to form a single comprehensive checklist of reporting recommendations. The strength of our approach has been our international and multidisciplinary team of content experts and contributors who represent a wide range of relevant scientific conventions, and our adherence to international norms for the development of reporting guidelines. As spatial, location-based, and artificial intelligence technologies used in spatial lifecourse epidemiology continue to evolve at a rapid pace, it will be necessary to revisit and adapt the ISLE-ReSt at least every 2–3 years from its release.

Table S2. GIS data sources and calculations for neighborhood environmental features. This table provides detail regarding the geographical information systems data sources and the calculations performed to determine objective neighborhood environmental features to be assessed. (DOCX 15 kb)

Additional file 1: Table S1. Baseline characteristics of stayers, movers, and drop-outs, AusDiab study (1999-2012); Material S1. Active Australia Survey Items Used to Measure Physical Activity; Material S2. Calculating Changes Using Values Measured at Three Observation Points; Material S3. Details of the Three-Level Linear Growth Model Used in the Study

Table S1. Potential ecological correlates of activity-related health behaviors. This table provides detail regarding variables that were assessed as potential correlates of activity-related health behaviors including the survey items used and data reduction for use of the variables. (DOCX 26 kb)