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Zha Y. The "uneven road" to food: Socioeconomic disparities in the mobility burden of food purchasing behavior in major US cities, 2019-2023. Health Place 2025; 91:103404. [PMID: 39721432 DOI: 10.1016/j.healthplace.2024.103404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 11/28/2024] [Accepted: 12/15/2024] [Indexed: 12/28/2024]
Abstract
Socioeconomic factors contribute to distinct patterns of food-purchasing behaviors, placing a higher burden of mobility on vulnerable, deprived populations. Traditional approaches often overlook the dynamics of human activity as contextual influences, simulating a perceived food environment that contradicts the actual use thereof. The rise of large-scale mobile phone data presents a unique opportunity to capture real behavioral patterns and their mobility implications at a fine-grained level. Using a Time-Weighted Kernel Density Estimation (TWKDE) model on mobile phone data, this study introduces two novel measures - the Spatial Engel's Coefficient (SEC) index and the Distance-to-Activity Curve (DAC) - to assess the equity of food-purchasing travel across nine U.S. cities over five years, analyzed by socioeconomic status, time period, and location. Our findings reveal that lower socioeconomic status is strongly associated with greater mobility burdens in food-purchasing travel. This mobility gap between the highest and lowest socioeconomic groups was further exacerbated during the COVID-19 pandemic, manifesting in the form of spatial segregation of opportunities within cities. This paper contributes to the literature by developing novel activity-based tools that offer a more nuanced understanding of the behavioral characteristics of food-purchasing activities. These empirical insights can help policymakers identify the communities facing the greatest mobility burdens and guide targeted, place-based interventions to promote equity in food access.
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Affiliation(s)
- Yilun Zha
- School of Architecture, Georgia Institute of Technology, United States.
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2
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García Bulle Bueno B, Horn AL, Bell BM, Bahrami M, Bozkaya B, Pentland A, de la Haye K, Moro E. Effect of mobile food environments on fast food visits. Nat Commun 2024; 15:2291. [PMID: 38480685 PMCID: PMC10937966 DOI: 10.1038/s41467-024-46425-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 02/26/2024] [Indexed: 03/17/2024] Open
Abstract
Poor diets are a leading cause of morbidity and mortality. Exposure to low-quality food environments saturated with fast food outlets is hypothesized to negatively impact diet. However, food environment research has predominantly focused on static food environments around home neighborhoods and generated mixed findings. In this work, we leverage population-scale mobility data in the U.S. to examine 62M people's visits to food outlets and evaluate how food choice is influenced by the food environments people are exposed to as they move through their daily routines. We find that a 10% increase in exposure to fast food outlets in mobile environments increases individuals' odds of visitation by 20%. Using our results, we simulate multiple policy strategies for intervening on food environments to reduce fast-food outlet visits. This analysis suggests that optimal interventions are informed by spatial, temporal, and behavioral features and could have 2x to 4x larger effect than traditional interventions focused on home food environments.
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Affiliation(s)
| | - Abigail L Horn
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, 90089, USA
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, 90292, USA
| | - Brooke M Bell
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, 06510, USA
| | - Mohsen Bahrami
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Burçin Bozkaya
- Sabanci Business School, Sabanci University, 34956, Tuzla, Istanbul, Turkey
| | - Alex Pentland
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Kayla de la Haye
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, 90089, USA
| | - Esteban Moro
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Grupo Interdisciplinar de Sistemas Complejos (GISC), Department of Mathematics and GISC, Universidad Carlos III de Madrid, 28911, Leganés, Spain.
- Network Science Institute, Northeastern University, Boston, MA, 02115, USA.
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3
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Siddiqui NZ, Wei L, Mackenbach JD, Pinho MGM, Helbich M, Schoonmade LJ, Beulens JWJ. Global positioning system-based food environment exposures, diet-related, and cardiometabolic health outcomes: a systematic review and research agenda. Int J Health Geogr 2024; 23:3. [PMID: 38321477 PMCID: PMC10848400 DOI: 10.1186/s12942-024-00362-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 01/24/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Geographic access to food may affect dietary choices and health outcomes, but the strength and direction of associations may depend on the operationalization of exposure measures. We aimed to systematically review the literature on up-to-date evidence on the association between food environment exposures based on Global Positioning System (GPS) and diet-related and cardiometabolic health outcomes. METHODS The databases PubMed, Embase.com, APA PsycInfo (via Ebsco), Cinahl (via Ebsco), the Web of Science Core Collection, Scopus, and the International Bibliography of the Social Sciences (via ProQuest) were searched from inception to October 31, 2022. We included studies that measured the activity space through GPS tracking data to identify exposure to food outlets and assessed associations with either diet-related or cardiometabolic health outcomes. Quality assessment was evaluated using the criteria from a modified version of the Newcastle-Ottawa Scale (NOS) for cross-sectional studies. We additionally used four items from a quality assessment tool to specifically assess the quality of GPS measurements. RESULTS Of 2949 studies retrieved, 14 studies fulfilled our inclusion criteria. They were heterogeneous and represent inconsistent evidence. Yet, three studies found associations between food outlets and food purchases, for example, more exposure to junk food outlets was associated with higher odds of junk food purchases. Two studies found associations between greater exposure to fast food outlets and higher fast food consumption and out of three studies that investigated food environment in relation to metabolic outcomes, two studies found that higher exposure to an unhealthy food environment was associated with higher odds of being overweight. CONCLUSIONS The current and limited evidence base does not provide strong evidence for consistent associations of GPS-based exposures of the food environment with diet-related and cardiometabolic health outcomes.
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Affiliation(s)
- Noreen Z Siddiqui
- Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands.
- Amsterdam Public Health, Health Behaviors and Chronic Diseases, Amsterdam, The Netherlands.
| | - Lai Wei
- Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, The Netherlands
| | - Joreintje D Mackenbach
- Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Public Health, Health Behaviors and Chronic Diseases, Amsterdam, The Netherlands
- Upstream Team, Amsterdam, the Netherlands
| | - Maria G M Pinho
- Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Public Health, Health Behaviors and Chronic Diseases, Amsterdam, The Netherlands
- Upstream Team, Amsterdam, the Netherlands
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands
| | - Marco Helbich
- Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, The Netherlands
| | - Linda J Schoonmade
- Medical Library, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Joline W J Beulens
- Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Public Health, Health Behaviors and Chronic Diseases, Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
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Horn AL, Bell BM, Bulle Bueno BG, Bahrami M, Bozkaya B, Cui Y, Wilson JP, Pentland A, Moro E, de la Haye K. Population mobility data provides meaningful indicators of fast food intake and diet-related diseases in diverse populations. NPJ Digit Med 2023; 6:208. [PMID: 37968446 PMCID: PMC10651929 DOI: 10.1038/s41746-023-00949-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 10/18/2023] [Indexed: 11/17/2023] Open
Abstract
The characteristics of food environments people are exposed to, such as the density of fast food (FF) outlets, can impact their diet and risk for diet-related chronic disease. Previous studies examining the relationship between food environments and nutritional health have produced mixed findings, potentially due to the predominant focus on static food environments around people's homes. As smartphone ownership increases, large-scale data on human mobility (i.e., smartphone geolocations) represents a promising resource for studying dynamic food environments that people have access to and visit as they move throughout their day. This study investigates whether mobility data provides meaningful indicators of diet, measured as FF intake, and diet-related disease, evaluating its usefulness for food environment research. Using a mobility dataset consisting of 14.5 million visits to geolocated food outlets in Los Angeles County (LAC) across a representative sample of 243,644 anonymous and opted-in adult smartphone users in LAC, we construct measures of visits to FF outlets aggregated over users living in neighborhood. We find that the aggregated measures strongly and significantly correspond to self-reported FF intake, obesity, and diabetes in a diverse, representative sample of 8,036 LAC adults included in a population health survey carried out by the LAC Department of Public Health. Visits to FF outlets were a better predictor of individuals' obesity and diabetes than their self-reported FF intake, controlling for other known risks. These findings suggest mobility data represents a valid tool to study people's use of dynamic food environments and links to diet and health.
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Affiliation(s)
- Abigail L Horn
- Information Sciences Institute and Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Brooke M Bell
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, USA
| | | | - Mohsen Bahrami
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Burçin Bozkaya
- Sabanci Business School, Sabanci University, Istanbul, Turkey
| | - Yan Cui
- Los Angeles County Department of Public Health, Los Angeles, CA, USA
| | - John P Wilson
- Spatial Sciences Institute, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
- Departments of Civil & Environmental Engineering and Computer Science, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Alex Pentland
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Esteban Moro
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA
- Departamento de Matemáticas & GISC, Universidad Carlos III de Madrid, Leganés, Spain
| | - Kayla de la Haye
- Institute for Food System Equity, Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
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5
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Wirtz Baker JM, Pou SA, Niclis C, Haluszka E, Aballay LR. Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments. Int J Obes (Lond) 2023:10.1038/s41366-023-01331-3. [PMID: 37393408 DOI: 10.1038/s41366-023-01331-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 06/01/2023] [Accepted: 06/21/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND The complex nature of obesity increasingly requires a comprehensive approach that includes the role of environmental factors. For understanding contextual determinants, the resources provided by technological advances could become a key factor in obesogenic environment research. This study aims to identify different sources of non-traditional data and their applications, considering the domains of obesogenic environments: physical, sociocultural, political and economic. METHODS We conducted a systematic search in PubMed, Scopus and LILACS databases by two independent groups of reviewers, from September to December 2021. We included those studies oriented to adult obesity research using non-traditional data sources, published in the last 5 years in English, Spanish or Portuguese. The overall reporting followed the PRISMA guidelines. RESULTS The initial search yielded 1583 articles, 94 articles were kept for full-text screening, and 53 studies met the eligibility criteria and were included. We extracted information about countries of origin, study design, observation units, obesity-related outcomes, environment variables, and non-traditional data sources used. Our results revealed that most of the studies originated from high-income countries (86.54%) and used geospatial data within a GIS (76.67%), social networks (16.67%), and digital devices (11.66%) as data sources. Geospatial data were the most utilised data source and mainly contributed to the study of the physical domains of obesogenic environments, followed by social networks providing data to the analysis of the sociocultural domain. A gap in the literature exploring the political domain of environments was also evident. CONCLUSION The disparities between countries are noticeable. Geospatial and social network data sources contributed to studying the physical and sociocultural environments, which could be a valuable complement to those traditionally used in obesity research. We propose the use of information available on the Internet, addressed by artificial intelligence-based tools, to increase the knowledge on political and economic dimensions of the obesogenic environment.
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Affiliation(s)
- Julia Mariel Wirtz Baker
- Health Sciences Research Institute (INICSA), National Council of Scientific and Technical Research (CONICET), Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
- Human Nutrition Research Centre (CenINH), School of Nutrition, Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
| | - Sonia Alejandra Pou
- Health Sciences Research Institute (INICSA), National Council of Scientific and Technical Research (CONICET), Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
- Human Nutrition Research Centre (CenINH), School of Nutrition, Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
| | - Camila Niclis
- Health Sciences Research Institute (INICSA), National Council of Scientific and Technical Research (CONICET), Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
- Human Nutrition Research Centre (CenINH), School of Nutrition, Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
| | - Eugenia Haluszka
- Health Sciences Research Institute (INICSA), National Council of Scientific and Technical Research (CONICET), Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
- Human Nutrition Research Centre (CenINH), School of Nutrition, Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
| | - Laura Rosana Aballay
- Human Nutrition Research Centre (CenINH), School of Nutrition, Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina.
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Klein S, Brondeel R, Chaix B, Klein O, Thierry B, Kestens Y, Gerber P, Perchoux C. What triggers selective daily mobility among older adults? A study comparing trip and environmental characteristics between observed path and shortest path. Health Place 2023; 79:102730. [PMID: 34955424 DOI: 10.1016/j.healthplace.2021.102730] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 11/19/2021] [Accepted: 11/29/2021] [Indexed: 10/19/2022]
Abstract
Interest is growing in neighborhood effects on health beyond individual's home locations. However, few studies accounted for selective daily mobility bias. Selective mobility of 470 older adults (aged 67-94) living in urban and suburban areas of Luxembourg, was measured through detour percentage between their observed GPS-based paths and their shortest paths. Multilevel negative binomial regression tested associations between detour percentage, trips characteristics and environmental exposures. Detour percentage was higher for walking trips (28%) than car trips (16%). Low-speed areas and connectivity differences between observed and shortest paths vary by transport mode, indicating a potential selective daily mobility bias. The positive effects of amenities, street connectivity, low-speed areas and greenness on walking detour reinforce the existing evidence on older adults' active transportation. Urban planning interventions favoring active transportation will also promote walking trips with longer detours, helping older adults to increase their physical activity levels and ultimately promote healthy aging.
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Affiliation(s)
- Sylvain Klein
- Luxembourg Institute of Socio-Economic Research, Urban and Mobility Department, Esch/Alzette, L-4366, Luxembourg.
| | - Ruben Brondeel
- Scientific Directorate of Epidemiology and Public Health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - Basile Chaix
- INSERM, Sorbonne Université, Institut Pierre Louis d'épidémiologie et de Santé Publique, IPLESP UMR-S1136, F75012, Paris, France
| | - Olivier Klein
- Luxembourg Institute of Socio-Economic Research, Urban and Mobility Department, Esch/Alzette, L-4366, Luxembourg
| | - Benoit Thierry
- Centre de Recherche de l'université de Montréal (CRCHUM), Université de Montréal, QCL, Canada
| | - Yan Kestens
- Centre de Recherche de l'université de Montréal (CRCHUM), Université de Montréal, QCL, Canada
| | - Philippe Gerber
- Luxembourg Institute of Socio-Economic Research, Urban and Mobility Department, Esch/Alzette, L-4366, Luxembourg
| | - Camille Perchoux
- Luxembourg Institute of Socio-Economic Research, Urban and Mobility Department, Esch/Alzette, L-4366, Luxembourg
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7
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Kim EK, Conrow L, Röcke C, Chaix B, Weibel R, Perchoux C. Advances and challenges in sensor-based research in mobility, health, and place. Health Place 2023; 79:102972. [PMID: 36740543 DOI: 10.1016/j.healthplace.2023.102972] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/21/2022] [Accepted: 01/13/2023] [Indexed: 02/05/2023]
Affiliation(s)
- Eun-Kyeong Kim
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research (LISER), Esch-sur-Alzette, Luxembourg; Department of Geography, University of Zurich, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.
| | - Lindsey Conrow
- Department of Geography, University of Canterbury, New Zealand
| | - Christina Röcke
- University Research Priority Program (URPP) Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland; Center for Gerontology, University of Zurich, Zurich, Switzerland
| | - Basile Chaix
- Sorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Nemesis research team, Paris, France
| | - Robert Weibel
- Department of Geography, University of Zurich, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Camille Perchoux
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research (LISER), Esch-sur-Alzette, Luxembourg
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8
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Mackenbach JD, Widener MJ, van der Gaag E, Pinho MG. Survey-derived activity space-based exposures to fast food outlets and their cross-sectional associations with use of fast food outlets, diet quality and BMI. Health Place 2023; 79:102966. [PMID: 36608585 DOI: 10.1016/j.healthplace.2023.102966] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 12/21/2022] [Accepted: 12/27/2022] [Indexed: 01/06/2023]
Abstract
There is a need for conceptual and methodological innovation in food environment-health research. We compared different operationalizations of survey-derived activity space exposures to fast food outlets (FFOs) in associations with use of FFO, diet quality and body mass index (BMI). FFO exposure was determined for home, work and a maximum of sixteen other locations reported by 1728 Dutch adults. Considerable differences in count of FFO between locations were found. Adjusted linear regression analyses resulted in small, unexpected associations with use of FFO, diet quality and BMI, whereby the strength of associations differed between exposure measures. Using home and work areas may be a cost-efficient compromise to capture large parts of the exposure to FFOs.
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Affiliation(s)
- Joreintje D Mackenbach
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Epidemiology and Data Science, Amsterdam, Netherlands; Upstream Team, Amsterdam UMC, Netherlands.
| | - Michael J Widener
- Department of Geography and Planning, University of Toronto - St George, Toronto, Canada
| | - Emilie van der Gaag
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Epidemiology and Data Science, Amsterdam, Netherlands
| | - Maria Gm Pinho
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Epidemiology and Data Science, Amsterdam, Netherlands; Upstream Team, Amsterdam UMC, Netherlands
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9
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Hobbs M, Stewart T, Marek L, Duncan S, Campbell M, Kingham S. Health-promoting and health-constraining environmental features and physical activity and sedentary behaviour in adolescence: a geospatial cross-sectional study. Health Place 2022; 77:102887. [DOI: 10.1016/j.healthplace.2022.102887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/04/2022]
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10
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Marwa WL, Radley D, Davis S, McKenna J, Griffiths C. Exploring factors affecting individual GPS-based activity space and how researcher-defined food environments represent activity space, exposure and use of food outlets. Int J Health Geogr 2021; 20:34. [PMID: 34320996 PMCID: PMC8316713 DOI: 10.1186/s12942-021-00287-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/12/2021] [Indexed: 11/10/2022] Open
Abstract
Background Obesity remains one of the most challenging public health issues of our modern time. Despite the face validity of claims for influence, studies on the causes of obesity have reported the influence of the food environment to be inconsistent. This inconsistency has been attributed to the variability of measures used by researchers to represent the food environments—Researcher-Defined Food Environments (RDFE) like circular, street-network buffers, and others. This study (i.) determined an individual’s Activity Space (AS) (ii.) explored the accuracy of the RDFE in representing the AS, (iii.) investigated the accuracy of the RDFE in representing actual exposure, and (iv.) explored whether exposure to food outlet reflects the use of food outlets. Methods Data were collected between June and December 2018. A total of 65 participants collected Global Positioning System (GPS) data, kept receipt of all their food purchases, completed a questionnaire about their personal information and had their weight and height measured. A buffer was created around the GPS points and merged to form an AS (GPS-based AS). Results Statistical and geospatial analyses found that the AS size of participants working away from home was positively related to the Euclidean distance from home to workplace; the orientation (shape) of AS was also influenced by the direction of workplace from home and individual characteristics were not predictive of the size of AS. Consistent with some previous studies, all types and sizes of RDFE variably misrepresented individual exposure in the food environments. Importantly, the accuracy of the RDFE was significantly improved by including both the home and workplace domains. The study also found no correlation between exposure and use of food outlets. Conclusions Home and workplace are key activity nodes in modelling AS or food environments and the relationship between exposure and use is more complex than is currently suggested in both empirical and policy literature.
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Affiliation(s)
| | | | - Samantha Davis
- Leeds Beckett University, City Campus, Leeds, LS1 3HE, UK
| | - James McKenna
- Leeds Beckett University, Headingley Campus, Leeds, LS6 3QS, UK
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11
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Duncan GE, Hurvitz PM, Moudon AV, Avery AR, Tsang S. Measurement of neighborhood-based physical activity bouts. Health Place 2021; 70:102595. [PMID: 34090126 PMCID: PMC8328921 DOI: 10.1016/j.healthplace.2021.102595] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 05/13/2021] [Accepted: 05/15/2021] [Indexed: 12/30/2022]
Abstract
This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the "neighborhood-effects" literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.
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Affiliation(s)
- Glen E Duncan
- Department of Nutrition and Exercise Physiology, Washington State University Health Sciences Spokane, Spokane, WA, USA.
| | - Philip M Hurvitz
- Urban Form Lab, University of Washington, Seattle, WA, USA; Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA
| | | | - Ally R Avery
- Department of Nutrition and Exercise Physiology, Washington State University Health Sciences Spokane, Spokane, WA, USA
| | - Siny Tsang
- Department of Nutrition and Exercise Physiology, Washington State University Health Sciences Spokane, Spokane, WA, USA
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12
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Liu B, Widener M, Burgoine T, Hammond D. Association between time-weighted activity space-based exposures to fast food outlets and fast food consumption among young adults in urban Canada. Int J Behav Nutr Phys Act 2020; 17:62. [PMID: 32404175 PMCID: PMC7222540 DOI: 10.1186/s12966-020-00967-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 05/04/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Despite increased attention on retail food environments and fast food consumption, results from previous studies have been inconsistent. Variation in measurement of exposure to retail food environments and the context of the built environment are possible reasons for inconsistencies. The purpose of the current study is to examine the association between exposure to fast food environment and fast food consumption among young adults, and to explore possible associations between built environment and fast food consumption. METHODS We employed an observational, cross-sectional study design. Cross-sectional surveys were conducted in 2016 and 2017. In a sample of 591 young adults aged 16-30 years in five Canadian cities, we constructed and computed individual-level time-weighted number and ratio of fast food outlets in activity spaces derived from GPS trajectory data. Negative binomial regression models estimated the associations between exposure measures and frequency of fast food consumption (number of times consuming fast food meals in a seven-day period), controlling for built environment characterization and individual-level characteristics. RESULTS Significant positive associations were found between time-weighted number of fast food outlets and count of fast food meals consumed per week in models using a radius of 500 m (IRR = 1.078, 95% CI: 0.999, 1.163), 1 km (IRR = 1.135, 95% CI: 1.024, 1.259), or 1.5 km (IRR = 1.138, 95% CI: 1.004, 1.289) around GPS tracks, when generating activity spaces. However, time-weighted ratio of fast food outlets was only significantly associated with count of fast food meals consumed when a radius of 500 m is used (IRR = 1.478, 95% CI: 1.032, 2.123). The time-weighted Active Living Environment Index with Transit measure was significantly negatively related to count of fast food meals consumed across all models. CONCLUSIONS Our study demonstrated associations of time-weighted activity space-based exposure to fast food outlets and fast food consumption frequency in a sample of young adults in urban Canada, and provides evidence of the association between context of built environment and fast food consumption, furthering discussion on the utility of individual-level, activity space-based data and methods in food environment research. These results imply that both food retail composition and activity spaces in urban areas are important factors to consider when studying diets.
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Affiliation(s)
- Bochu Liu
- Department of Geography and Planning, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada.
| | - Michael Widener
- Department of Geography and Planning, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada
| | - Thomas Burgoine
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - David Hammond
- School of Public Health and Health Systems, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada
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Perchoux C, Chaix B, Kestens Y. Activity spaces in place and health research: Novel exposure measures, data collection tools, and designs. Health Place 2019; 58:102130. [DOI: 10.1016/j.healthplace.2019.05.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 05/07/2019] [Indexed: 12/01/2022]
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