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Geary RS, Thompson DA, Garrett JK, Mizen A, Rowney FM, Song J, White MP, Lovell R, Watkins A, Lyons RA, Williams S, Stratton G, Akbari A, Parker SC, Nieuwenhuijsen MJ, White J, Wheeler BW, Fry R, Tsimpida D, Rodgers SE. Green-blue space exposure changes and impact on individual-level well-being and mental health: a population-wide dynamic longitudinal panel study with linked survey data. PUBLIC HEALTH RESEARCH 2023; 11:1-176. [PMID: 37929711 DOI: 10.3310/lqpt9410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023] Open
Abstract
Background Cross-sectional evidence suggests that living near green and blue spaces benefits mental health; longitudinal evidence is limited. Objectives To quantify the impact of changes in green and blue spaces on common mental health disorders, well-being and health service use. Design A retrospective, dynamic longitudinal panel study. Setting Wales, UK. Participants An e-cohort comprising 99,682,902 observations of 2,801,483 adults (≥ 16 years) registered with a general practice in Wales (2008-2019). A 5312-strong 'National Survey for Wales (NSW) subgroup' was surveyed on well-being and visits to green and blue spaces. Main outcome measures Common mental health disorders, general practice records; subjective well-being, Warwick-Edinburgh Mental Well-being Scale. Data sources Common mental health disorder and use of general practice services were extracted quarterly from the Welsh Longitudinal General Practice Dataset. Annual ambient greenness exposure, enhanced vegetation index and access to green and blue spaces (2018) from planning and satellite data. Data were linked within the Secure Anonymised Information Linkage Databank. Methods Multilevel regression models examined associations between exposure to green and blue spaces and common mental health disorders and use of general practice. For the National Survey for Wales subgroup, generalised linear models examined associations between exposure to green and blue spaces and subjective well-being and common mental health disorders. Results and conclusions Our longitudinal analyses found no evidence that changes in green and blue spaces through time impacted on common mental health disorders. However, time-aggregated exposure to green and blue spaces contrasting differences between people were associated with subsequent common mental health disorders. Similarly, our cross-sectional findings add to growing evidence that residential green and blue spaces and visits are associated with well-being benefits: Greater ambient greenness (+ 1 enhanced vegetation index) was associated with lower likelihood of subsequently seeking care for a common mental health disorder [adjusted odds ratio (AOR) 0.80, 95% confidence interval, (CI) 0.80 to 0.81] and with well-being with a U-shaped relationship [Warwick-Edinburgh Mental Well-being Scale; enhanced vegetation index beta (adjusted) -10.15, 95% CI -17.13 to -3.17; EVI2 beta (quadratic term; adj.) 12.49, 95% CI 3.02 to 21.97]. Those who used green and blue spaces for leisure reported better well-being, with diminishing extra benefit with increasing time (Warwick-Edinburgh Mental Well-being Scale: time outdoors (hours) beta 0.88, 95% CI 0.53 to 1.24, time outdoors2 beta -0.06, 95% CI -0.11 to -0.01) and had 4% lower odds of seeking help for common mental health disorders (AOR 0.96, 95% CI 0.93 to 0.99). Those in urban areas benefited most from greater access to green and blue spaces (AOR 0.89, 95% CI 0.89 to 0.89). Those in material deprivation benefited most from leisure time outdoors (until approximately four hours per week; Warwick-Edinburgh Mental Well-being Scale: time outdoors × in material deprivation: 1.41, 95% CI 0.39 to 2.43; time outdoors2 × in material deprivation -0.18, 95% CI -0.33 to -0.04) although well-being remained generally lower. Limitations Longitudinal analyses were restricted by high baseline levels and limited temporal variation in ambient greenness in Wales. Changes in access to green and blue spaces could not be captured annually due to technical issues with national-level planning datasets. Future work Further analyses could investigate mental health impacts in population subgroups potentially most sensitive to local changes in access to specific types of green and blue spaces. Deriving green and blue spaces changes from planning data is needed to overcome temporal uncertainties. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (Project number 16/07/07) and will be published in full in Public Health Research; Vol. 11, No. 10. Sarah Rodgers is part-funded by the NIHR Applied Research Collaboration North West Coast.
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Affiliation(s)
- Rebecca S Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | | | - Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Amy Mizen
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Francis M Rowney
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Jiao Song
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Mathew P White
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Alan Watkins
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Ronan A Lyons
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | | | - Ashley Akbari
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Sarah C Parker
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Richard Fry
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Dialechti Tsimpida
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
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Baugh Littlejohns L, Near E, McKee G, Rasali D, Naiman D, Faulkner G. A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach? Health Res Policy Syst 2023; 21:18. [PMID: 36864409 PMCID: PMC9979563 DOI: 10.1186/s12961-023-00961-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/11/2023] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND Complex systems approaches are increasingly used in health promotion and noncommunicable disease prevention research, policy and practice. Questions emerge as to the best ways to take a complex systems approach, specifically with respect to population physical activity (PA). Using an Attributes Model is one way to understand complex systems. We aimed to examine the types of complex systems methods used in current PA research and identify what methods align with a whole system approach as reflected by an Attributes Model. METHODS A scoping review was conducted and two databases were searched. Twenty-five articles were selected and data analysis was based upon the following: the complex systems research methods used, research aims, if participatory methods were used and evidence of discussion regarding attributes of systems. RESULTS There were three groups of methods used: system mapping, simulation modelling and network analysis. System mapping methods appeared to align best with a whole system approach to PA promotion because they largely aimed to understand complex systems, examined interactions and feedback among variables, and used participatory methods. Most of these articles focused on PA (as opposed to integrated studies). Simulation modelling methods were largely focused on examining complex problems and identifying interventions. These methods did not generally focus on PA or use participatory methods. While network analysis articles focused on examining complex systems and identifying interventions, they did not focus on PA nor use participatory methods. All attributes were discussed in some way in the articles. Attributes were explicitly reported on in terms of findings or were part of discussion and conclusion sections. System mapping methods appear to be well aligned with a whole system approach because these methods addressed all attributes in some way. We did not find this pattern with other methods. CONCLUSIONS Future research using complex systems methods may benefit from applying the Attributes Model in conjunction with system mapping methods. Simulation modelling and network analysis methods are seen as complementary and could be used when system mapping methods identify priorities for further investigation (e.g. what interventions to implement or how densely connected relationships are in systems).
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Affiliation(s)
- Lori Baugh Littlejohns
- BC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC, V5Z 4R4, Canada. .,School of Kinesiology, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC, V6T 1Z1, Canada.
| | - Erin Near
- grid.34429.380000 0004 1936 8198Department of Population Medicine, University of Guelph, Stewart Building, Building #45, Rm 2509, Guelph, ON N1G 2W1 Canada
| | - Geoff McKee
- grid.418246.d0000 0001 0352 641XBC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC V5Z 4R4 Canada ,grid.17091.3e0000 0001 2288 9830School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC V6T 1Z3 Canada
| | - Drona Rasali
- grid.418246.d0000 0001 0352 641XBC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC V5Z 4R4 Canada ,grid.17091.3e0000 0001 2288 9830School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC V6T 1Z3 Canada
| | - Daniel Naiman
- grid.453059.e0000000107220098BC Ministry of Health, Stn Prov Govt, PO Box 9646, Victoria, BC V8W 9P1 Canada
| | - Guy Faulkner
- grid.17091.3e0000 0001 2288 9830School of Kinesiology, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC V6T 1Z1 Canada
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Hystad P, Amram O, Oje F, Larkin A, Boakye K, Avery A, Gebremedhin A, Duncan G. Bring Your Own Location Data: Use of Google Smartphone Location History Data for Environmental Health Research. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:117005. [PMID: 36356208 PMCID: PMC9648904 DOI: 10.1289/ehp10829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
BACKGROUND Environmental exposures are commonly estimated using spatial methods, with most epidemiological studies relying on home addresses. Passively collected smartphone location data, like Google Location History (GLH) data, may present an opportunity to integrate existing long-term time-activity data. OBJECTIVES We aimed to evaluate the potential use of GLH data for capturing long-term retrospective time-activity data for environmental health research. METHODS We included 378 individuals who participated in previous Global Positioning System (GPS) studies within the Washington State Twin Registry. GLH data consists of location information that has been routinely collected since 2010 when location sharing was enabled within android operating systems or Google apps. We created instructions for participants to download their GLH data and provide it through secure data transfer. We summarized the GLH data provided, compared it to available GPS data, and conducted an exposure assessment for nitrogen dioxide (NO2) air pollution. RESULTS Of 378 individuals contacted, we received GLH data from 61 individuals (16.1%) and 53 (14.0%) indicated interest but did not have historical GLH data available. The provided GLH data spanned 2010-2021 and included 34 million locations, capturing 66,677 participant days. The median number of days with GLH data per participant was 752, capturing 442 unique locations. When we compared GLH data to 2-wk GPS data (∼1.8 million points), 95% of GPS time-activity points were within 100m of GLH locations. We observed important differences between NO2 exposures assigned at home locations compared with GLH locations, highlighting the importance of GLH data to environmental exposure assessment. DISCUSSION We believe collecting GLH data is a feasible and cost-effective method for capturing retrospective time-activity patterns for large populations that presents new opportunities for environmental epidemiology. Cohort studies should consider adding GLH data collection to capture historical time-activity patterns of participants, employing a "bring-your-own-location-data" citizen science approach. Privacy remains a concern that needs to be carefully managed when using GLH data. https://doi.org/10.1289/EHP10829.
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Affiliation(s)
- Perry Hystad
- College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA
| | - Ofer Amram
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University (WSU), Spokane, Washington, USA
- Paul G. Allen School for Global Animal Health, WSU, Pullman, Washington, USA
| | - Funso Oje
- School of Electrical Engineering and Computer Science, WSU, Pullman, Washington, USA
| | - Andrew Larkin
- College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA
| | - Kwadwo Boakye
- College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA
| | - Ally Avery
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University (WSU), Spokane, Washington, USA
| | - Assefaw Gebremedhin
- School of Electrical Engineering and Computer Science, WSU, Pullman, Washington, USA
| | - Glen Duncan
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University (WSU), Spokane, Washington, USA
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Nau T, Bauman A, Smith BJ, Bellew W. A scoping review of systems approaches for increasing physical activity in populations. Health Res Policy Syst 2022; 20:104. [PMID: 36175916 PMCID: PMC9524093 DOI: 10.1186/s12961-022-00906-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/02/2022] [Indexed: 11/27/2022] Open
Abstract
Introduction The past decade has increasingly seen systems approaches as a featured theme in public health studies and policy documents. This trend is evident in the area of physical activity, which is a significant global health risk factor that is addressed in WHO’s Global Action Plan on Physical Activity. We undertook a comprehensive scoping review to characterize the application of systems approaches to physical activity, to develop a typology of the objectives, themes and methods of research papers that purported to apply systems thinking to this issue. Methods We searched electronic databases (PubMed, Web of Science, Scopus and PsycINFO) for studies published during the period 2010–2021 that explicitly applied systems approaches or methods to investigate and/or address population physical activity. A framework using systems-based methodological approaches was adapted to classify physical activity studies according to their predominant approach, covering basic descriptive, complex analytical and advanced forms of practice. We selected case studies from retained studies to depict the current “state of the art”. Results We included 155 articles in our narrative account. Literature reporting the application of systems approaches to physical activity is skewed towards basic methods and frameworks, with most attention devoted to conceptual framing and predictive modelling. There are few well-described examples of physical activity interventions which have been planned, implemented and evaluated using a systems perspective. There is some evidence of “retrofitted” complex system framing to describe programmes and interventions which were not designed as such. Discussion We propose a classification of systems-based approaches to physical activity promotion together with an explanation of the strategies encompassed. The classification is designed to stimulate debate amongst policy-makers, practitioners and researchers to inform the further implementation and evaluation of systems approaches to physical activity. Conclusion The use of systems approaches within the field of physical activity is at an early stage of development, with a preponderance of descriptive approaches and a dearth of more complex analyses. We need to see movement towards a more sophisticated research agenda spanning the development, implementation and evaluation of systems-level interventions. Supplementary Information The online version contains supplementary material available at 10.1186/s12961-022-00906-2.
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Affiliation(s)
- Tracy Nau
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia. .,The Australian Prevention Partnership Centre, Sydney, NSW, Australia.
| | - Adrian Bauman
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,The Australian Prevention Partnership Centre, Sydney, NSW, Australia
| | - Ben J Smith
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,The Australian Prevention Partnership Centre, Sydney, NSW, Australia
| | - William Bellew
- Prevention Research Collaboration, Charles Perkins Centre, School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,The Australian Prevention Partnership Centre, Sydney, NSW, Australia
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Salvo D, Garcia L, Reis RS, Stankov I, Goel R, Schipperijn J, Hallal PC, Ding D, Pratt M. Physical Activity Promotion and the United Nations Sustainable Development Goals: Building Synergies to Maximize Impact. J Phys Act Health 2021; 18:1163-1180. [PMID: 34257157 DOI: 10.1123/jpah.2021-0413] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 11/18/2022]
Abstract
BACKGROUND Many of the known solutions to the physical inactivity pandemic operate across sectors relevant to the United Nations Sustainable Development Goals (SDGs). METHODS The authors examined the contribution of physical activity promotion strategies toward achieving the SDGs through a conceptual linkage exercise, a scoping review, and an agent-based model. RESULTS Possible benefits of physical activity promotion were identified for 15 of the 17 SDGs, with more robust evidence supporting benefits for SDGs 3 (good health and well-being), 9 (industry, innovation, and infrastructure), 11 (sustainable cities and communities), 13 (climate action), and 16 (peace, justice, and strong institutions). Current evidence supports prioritizing at-scale physical activity-promoting transport and urban design strategies and community-based programs. Expected physical activity gains are greater for low-and middle-income countries. In high-income countries with high car dependency, physical activity promotion strategies may help reduce air pollution and traffic-related deaths, but shifts toward more active forms of travel and recreation, and climate change mitigation, may require complementary policies that disincentivize driving. CONCLUSIONS The authors call for a synergistic approach to physical activity promotion and SDG achievement, involving multiple sectors beyond health around their goals and values, using physical activity promotion as a lever for a healthier planet.
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