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Hoenink JC, Huang Y, Keeble M, Mackenbach JD, de Pinho MG, Vanderlee L, Hammond D, White CM, Burgoine T, Adams J. Physical and online food outlet availability and its influence on out-of-home dietary behaviours in Great Britain: A repeated cross-sectional study. SSM Popul Health 2025; 30:101773. [PMID: 40129558 PMCID: PMC11932679 DOI: 10.1016/j.ssmph.2025.101773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2024] [Revised: 02/10/2025] [Accepted: 03/04/2025] [Indexed: 03/26/2025] Open
Abstract
Background As online food delivery service (OFDS) platforms gain popularity, understanding their impact on diet alongside physical food outlets is important for addressing suboptimal dietary quality. This study examined the independent and combined associations between physical and online food outlet availability and out-of-home dietary behaviours in 2019 and 2022. We also explored whether associations between physical outlet availability and dietary behaviours are modified by online food outlet availability. Methods In this repeated cross-sectional analysis, we used British data from the adult International Food Policy Study (IFPS) in 2019 (n = 2912) and 2022 (n = 3544). Postcodes were used to assess neighbourhood food outlet availability using Ordnance Survey data and to determine OFDS availability on three platforms through web scraping. Associations were examined between neighbourhood outlet and OFDS availability with self-reported frequency of physical food outlet use, online food outlet use, and consuming meals prepared out-of-home. Results In 2019 and 2022, both neighbourhood and OFDS availability were positively associated with all outcome measures. In 2019, after mutual adjustment, both availability measures remained associated with online food outlet use and consuming meals prepared out-of-home. However, in 2022, only OFDS availability was associated with these outcomes. For example, a one standard deviation increase in OFDS availability was associated with a 9% (95%CI 3%-14%) increase in frequency of consuming meals prepared out-of-home after adjusting for neighbourhood outlet availability. OFDS availability also modified associations between neighbourhood outlets and both online food outlet use and out-of-home meal consumption. As OFDS availability increased, the link between neighbourhood outlets and out-of-home meal consumption weakened. Conclusion Neighbourhood outlet availability may influence out-of-home dietary behaviours, but its impact appears to weaken when OFDS availability is considered. Public health strategies should address the growing influence of OFDS platforms to improve dietary quality.
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Affiliation(s)
- Jody C. Hoenink
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
- Upstream Team, www.upstreamteam.nl, Amsterdam UMC, the Netherlands
| | - Yuru Huang
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
| | - Matthew Keeble
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
- Department of Marketing, Faculty of Business and Economics, University of Antwerp, Antwerp, Belgium
| | - Joreintje D. Mackenbach
- Upstream Team, www.upstreamteam.nl, Amsterdam UMC, the Netherlands
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Epidemiology and Data Science, De Boelelaan 1117, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
| | - Maria G.M. de Pinho
- Upstream Team, www.upstreamteam.nl, Amsterdam UMC, the Netherlands
- Copernicus Institute of Sustainable Development, Department Environmental Sciences, Utrecht University, Utrecht, the Netherlands
| | | | - David Hammond
- School of Public Health Sciences, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Christine M. White
- School of Public Health Sciences, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Thomas Burgoine
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
| | - Jean Adams
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
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Huang Y, Burgoine T, White CM, Keeble M, Bishop TRP, Hammond D, Adams J. Neighbourhood out-of-home food environment, menu healthiness, and their associations with meal purchasing and diet quality: a multiverse analysis. Nutr J 2025; 24:56. [PMID: 40211333 PMCID: PMC11983832 DOI: 10.1186/s12937-025-01119-3] [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: 01/10/2024] [Accepted: 03/31/2025] [Indexed: 04/14/2025] Open
Abstract
BACKGROUND Governments worldwide have implemented various interventions to improve the healthiness of food offered by out-of-home outlets. However, there is limited evidence on whether healthier menus would influence individual dietary behaviours and quality. In this cross-sectional study, we investigated associations between different measures of the neighbourhood out-of-home food environment, incorporating menu healthiness, and out-of-home meal purchasing and diet quality. METHODS We used a sample of 3,481 adults in Great Britain (GB) with valid home postcodes from the 2021 International Food Policy Study. We linked this sample to a national database of food outlet geographical locations to characterise individuals' exposure to the out-of-home food environment. The exposure metrics included menu healthiness scores, availability, proximity, and relative composition of out-of-home food outlets in various neighbourhood buffers around the home (i.e., 500 - 1600 m). Outcomes considered were out-of-home meal consumption and overall diet quality. Using multiverse analyses, where multiple reasonable analytical choices can be tested, we investigated the associations between different exposure measures and these outcomes. RESULTS GB adults had access to an average of 97 (95% CI 91, 104) out-of-home food outlets within 1600 m of their homes. The number of both healthier and less healthy out-of-home food outlets was positively associated with the number of meals purchased out-of-home across all neighbourhood buffers, e.g., every 10 additional less healthy out-of-home food outlets within 500 m of the home corresponded to a 6% (95% CI = 2, 11) increase in the frequency of out-of-home meal purchases in the previous week. Proximity, relative composition, and menu healthiness of neighbourhood out-of-home outlets were not associated with out-of-home meal purchase frequency after adjusting for multiple comparisons. There were no consistent associations between out-of-home food environment exposures and diet quality. CONCLUSION The only aspect of the neighbourhood out-of-home food environment associated with out-of-home meal purchase frequency was the number of out-of-home food outlets. Menu healthiness of out-of-home food outlets was not associated with how often people purchased out-of-home meals or overall diet quality. Interventions focusing on mitigating the proliferation of out-of-home food outlets may be more effective in changing individual dietary behaviour than those focusing on food served.
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Affiliation(s)
- Yuru Huang
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.
- Department of Human Ecology, University of California, Davis, CA, USA.
| | - Thomas Burgoine
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Christine M White
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Matthew Keeble
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Department of Marketing, Faculty of Business and Economics, University of Antwerp, Antwerp, Belgium
| | - Tom R P Bishop
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - David Hammond
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Jean Adams
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
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Wray A, Martin G, Seabrook JA, Doherty S, Gilliland J. Does outdoor advertising correlate with retail food purchases made by adolescents? A cross-sectional study in Canada. Health Promot Int 2025; 40:daaf016. [PMID: 40099960 PMCID: PMC11915500 DOI: 10.1093/heapro/daaf016] [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] [Indexed: 03/20/2025] Open
Abstract
Food marketing plays a substantial role in shaping adolescent diets, having wide-ranging ramifications for health behaviours and outcomes throughout the life course. Yet, there remains a dearth of research about how outdoor advertising as a specific channel of food marketing affects purchasing behaviours. We examine self-reported purchases made at retail food outlets by adolescents as it relates to the availability of outdoor food and beverage advertising around each participant's home, school, and along the journey to and from school. We also consider the impacts of sociodemographics and consumption attitudes on purchasing, as compared to the geographic availability of outdoor advertising. Data are drawn from a survey completed by 545 adolescents in 2018 across four secondary schools in the Middlesex-London region of Ontario, Canada. The availability of outdoor advertising in the home and school environment is marginally correlated with self-reported purchases made at fast food, table-based, grocery, and variety retail outlets. However, consumption attitudes, cultural background, and gender are significantly correlated with purchases, with substantially larger effect sizes. The overall results were consistent between estimating the availability of outdoor advertising in the immediate area surrounding the home and along the journey to and from school. There is considerable health promotion policy interest in regulating outdoor advertising around child-serving locations. However, scarce health promotion resources would be better allocated to educational programming that addresses the substantial role of consumption attitudes in affecting adolescent purchasing behaviour, as compared to the considerably weaker impact of outdoor food advertising observed in our analysis.
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Affiliation(s)
- Alexander Wray
- Department of Geography & Environment, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
| | - Gina Martin
- Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Faculty of Health Disciplines, Athabasca University, 1 University Drive, Athabasca, Alberta T9S 3A3, Canada
| | - Jamie A Seabrook
- Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Department of Paediatrics, Brescia School of Food and Nutritional Sciences, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Department of Epidemiology & Biostatistics, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
| | - Sean Doherty
- Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Department of Geography & Environmental Studies, Wilfrid Laurier University, 75 University Avenue West, Waterloo, Ontario N2L 3C5, Canada
| | - Jason Gilliland
- Department of Geography & Environment, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Department of Epidemiology & Biostatistics, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
- Department of Paediatrics, School of Health Studies, Western University, 1151 Richmond Street, London, Ontario N6A 3K7, Canada
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Patterson R, Ogilvie D, Hoenink JC, Burgoine T, Sharp SJ, Hajna S, Panter J. Combined associations of takeaway food availability and walkability with adiposity: Cross-sectional and longitudinal analyses. Health Place 2025; 91:103405. [PMID: 39826337 DOI: 10.1016/j.healthplace.2024.103405] [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: 08/28/2024] [Revised: 11/27/2024] [Accepted: 12/16/2024] [Indexed: 01/22/2025]
Abstract
BACKGROUND Diet and physical activity are important determinants of energy balance, body weight and chronic health conditions. Peoples' health and behaviour are shaped by their environment. For example, the availability of unhealthy takeaway food in residential neighbourhoods and the ability to easily walk to a range of local destinations (high "walkability") influence diets and physical activity levels. Most existing evidence on the associations between residential neighbourhood and adiposity is cross-sectional and examines either walkability or takeaway availability, but not both in combination.We examined the cross-sectional and longitudinal associations of residential neighbourhood walkability and takeaway food availability with markers of adiposity separately and combined. METHODS With data from the Fenland Study (Cambridgeshire, UK; n = 12,435), we used linear regression to estimate associations for walkability and takeaway availability separately and in mutually adjusted models, in addition to combining both into a measure of neighbourhood supportiveness for active living and healthy eating. Objective measures of BMI were examined cross-sectionally at baseline (2005-2015) and as change between baseline and follow-up (2014-2020). Additional outcomes (percentage body fat, waist circumference and hip circumference) were also examined both cross-sectionally and longitudinally. RESULTS Complete case analyses indicated that neighbourhoods with greater walkability and lower takeaway availability were associated with lower BMI (n = 10,607) and more favourable trends over time (n = 5508). For example, compared with the lowest exposure group (Q1), Q4 of walkability and takeaway food availability was associated with a difference in BMI of -0.69 kg/m2 (95% CI = -1.09 to -0.29) and 0.99 kg/m2 (95% CI = 0.58 to 1.39) respectively. These associations were more consistent when both neighbourhood measures were included in mutually adjusted models. The combined supportiveness measure was associated with lower BMI. High walkability and low takeaway availability were also associated with lower body fat percentage, waist circumference and hip circumference. CONCLUSIONS These findings are consistent with the residential environment having a role in shaping people's health and behaviour. Living in an area that supports walking and cycling and affords less access to unhealthy food may support people to maintain a healthy lifestyle. It was important to consider walkability and takeaway food availability together because to examine them separately risks unobserved confounding by the other. Future research could incorporate additional environmental measures, especially those likely to be correlated.
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Affiliation(s)
- Richard Patterson
- MRC Epidemiology Unit, University of Cambridge, Box 285 Institute of Metabolic Science, CB2 0QQ, Cambridge, UK.
| | - David Ogilvie
- MRC Epidemiology Unit, University of Cambridge, Box 285 Institute of Metabolic Science, CB2 0QQ, Cambridge, UK
| | - Jody C Hoenink
- MRC Epidemiology Unit, University of Cambridge, Box 285 Institute of Metabolic Science, CB2 0QQ, Cambridge, UK
| | - Thomas Burgoine
- MRC Epidemiology Unit, University of Cambridge, Box 285 Institute of Metabolic Science, CB2 0QQ, Cambridge, UK
| | - Stephen J Sharp
- MRC Epidemiology Unit, University of Cambridge, Box 285 Institute of Metabolic Science, CB2 0QQ, Cambridge, UK
| | - Samantha Hajna
- Faculty of Applied Health Sciences, Brock University, St. Catherines, ON, L2S 3A1, Canada
| | - Jenna Panter
- MRC Epidemiology Unit, University of Cambridge, Box 285 Institute of Metabolic Science, CB2 0QQ, Cambridge, UK
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Bernsdorf KA, Bøggild H, Aadahl M, Toft U. Measuring associations between the food environment and dietary habits: comparing the proportion and density of food outlets. BMC Public Health 2024; 24:3445. [PMID: 39696158 DOI: 10.1186/s12889-024-20976-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: 10/16/2023] [Accepted: 12/04/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND The food environment plays a crucial role in shaping our dietary choices and overall health. Spatial measures provide distinct perspectives on the physical food environment and its impact on diet. While proportion measures are theoretically considered to provide a more accurate representation of the overall physical food environment than density measures, it is important to recognize that the association between food environments and diet can vary depending on the context. Therefore, relying solely on one measure may not be appropriate. METHODS We systematically assessed the density and proportion of multiple food outlet types (fast-food outlets, convenience stores, supermarkets, and restaurants) around individuals homes using a large cross-sectional Danish study (N = 71,840). Densities were modeled in separate multilevel linear regression models, incorporating random intercepts from linear splines for each of the four food outlet types. Proportions were modeled without splines. Through the association with a dietary quality score (DQS), we examined the impact of quantifying the foodscape from density versus proportion measures. Associations were compared using parameter estimates, p-values, Akaike Information Criterion (AIC) values, and Akaike weights. RESULTS AIC values and Akaike weights were in favor of models including density measures. Across all outlet types, density measures were consistently negatively associated with the DQS until reaching densities of 3-5 (count/km2), at which point the direction of association became positive, indicating a shift towards a healthier DQS. After correcting for multiple comparisons, the most significant effect was observed for the sole significant proportion measure. A 10% increase in the proportion of fast-food outlets among "eating out options" was associated with a 7% decrease in the DQS, towards poorer dietary quality. CONCLUSIONS The associations highlight that choosing food outlet density versus proportions to quantify the foodscape impact findings of substantial importance when considering the significance level and direction of association. Findings suggests a threshold effect when using density measures indicating abundance of many food outlets, at which the association with dietary quality alters significantly towards healthier diet quality.
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Affiliation(s)
- Kamille Almer Bernsdorf
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
| | - Henrik Bøggild
- Public Health and Epidemiology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Mette Aadahl
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Ulla Toft
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark
- Department of Public Health, Section of Social Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Department for Prevention, Health Promotion and Community Care, Herlev, Denmark
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Hoenink JC, Burgoine T, Forouhi NG, Monsivais P, Sharp SJ, Panter J, Adams J. Associations of takeaway outlets with takeaway food consumption and adiposity: longitudinal analysis of the Fenland cohort. Obesity (Silver Spring) 2024; 32:2388-2397. [PMID: 39385512 PMCID: PMC11589533 DOI: 10.1002/oby.24152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 07/04/2024] [Accepted: 08/16/2024] [Indexed: 10/12/2024]
Abstract
OBJECTIVE This study builds on prior findings that link increased availability of takeaway food outlets in home, workplace, and commuting environments to greater takeaway consumption and adiposity. Using longitudinal data, we examine associations of takeaway availability at baseline with changes in consumption and adiposity between baseline and follow-up. METHODS We analyzed data from the Fenland Study, with baseline data from 2005 to 2015 and follow-up from 2015 to 2020. Takeaway outlet availability within 1 mile of participants' home and workplace addresses, based on 2011 local authority data, was assessed. Outcomes included takeaway food consumption (from a food frequency questionnaire) and body fat percentage (measured via dual-energy x-ray absorptiometry) at follow-up. RESULTS Among 7581 participants (mean [SD] age, 49.3 [7.4] years) with a mean follow-up of 6.7 years, no positive association was found between takeaway outlet availability at baseline and changes in consumption or body fat percentage. However, among the 12 associations tested, the highest combined home-workplace availability of takeaway outlets, compared with none, was associated with a 0.68 decrease in body fat percentage (95% CI: 0.24-1.12). CONCLUSIONS Although takeaway outlet availability was linked to greater consumption and adiposity at baseline, it did not predict changes over time, underscoring the complexity of dietary behaviors and their relationship with the neighborhood food environment.
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Affiliation(s)
- Jody C. Hoenink
- MRC Epidemiology UnitUniversity of Cambridge School of Clinical Medicine, Institute of Metabolic ScienceCambridgeUK
| | - Thomas Burgoine
- MRC Epidemiology UnitUniversity of Cambridge School of Clinical Medicine, Institute of Metabolic ScienceCambridgeUK
| | - Nita G. Forouhi
- MRC Epidemiology UnitUniversity of Cambridge School of Clinical Medicine, Institute of Metabolic ScienceCambridgeUK
| | - Pablo Monsivais
- Elson S. Floyd College of MedicineWashington State UniversitySpokaneWashingtonUSA
| | - Stephen J. Sharp
- MRC Epidemiology UnitUniversity of Cambridge School of Clinical Medicine, Institute of Metabolic ScienceCambridgeUK
| | - Jenna Panter
- MRC Epidemiology UnitUniversity of Cambridge School of Clinical Medicine, Institute of Metabolic ScienceCambridgeUK
| | - Jean Adams
- MRC Epidemiology UnitUniversity of Cambridge School of Clinical Medicine, Institute of Metabolic ScienceCambridgeUK
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Yamamoto E, Takagi D, Hashimoto H. Association between snack intake behaviors of children and neighboring women: A population-based cross-sectional analysis with spatial regionalization. SSM Popul Health 2024; 28:101720. [PMID: 39506981 PMCID: PMC11539136 DOI: 10.1016/j.ssmph.2024.101720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 10/10/2024] [Accepted: 10/12/2024] [Indexed: 11/08/2024] Open
Abstract
Background Accumulated evidence indicates that neighborhood environments affect children's health behaviors. However, measuring neighborhood environments remains challenging because there exist strengths and weaknesses both in objective and perceived environment measures. Drawing on a recent conceptual model of how environment, perception, and behavior interact, we hypothesized that neighbors' behavioral similarities indicate the combined influence of physical and social environmental opportunities on specific behaviors. We then examined how these similarities (i.e. the behavioral tendencies of children's adult neighbors) relate to children's obesogenic dietary behaviors. Methods We used data for 2275 women and 821 elementary schoolchildren from a 2012-2013 population-based survey in greater Tokyo, Japan. Snack intake was defined as the total consumption of various types of snacks, estimated using a validated self-administered diet history questionnaire. Spatial regionalization, a type of spatial clustering, was used to empirically identify segments that could effectively differentiate regional variation in women's snack intake behaviors. We conducted multiple regression analysis to assess the cross-sectional association between children's snack intake and the mean snack intake of neighborhood women, adjusting for mother's intake. Results A 1-g increase in the mean snack intake of neighborhood women was associated with a 0.23-g (95% confidence interval: 0.00-0.45) increase in children's intake, while a 1-g increase in mother's intake was associated with a 0.34-g (95% confidence interval: 0.26-0.41) increase in children's intake. Discussion The results suggest that the out-of-home physical and social neighborhood environments may have non-ignorable associations with children's dietary behaviors by offering behavioral opportunities in addition to maternal influence.
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Affiliation(s)
- Emiko Yamamoto
- Department of Health and Social Behavior, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Daisuke Takagi
- Department of Health and Social Behavior, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Hideki Hashimoto
- Department of Health and Social Behavior, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
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Moore HJ, O'Malley CL, Lloyd S, Eskandari F, Rose K, Butler M, Townshend TG, Brown H, Clarkson D, Lake AA. Measuring the association between the opening of a new multi-national restaurant with young people's eating behaviours. Appetite 2024; 203:107651. [PMID: 39216823 DOI: 10.1016/j.appet.2024.107651] [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] [Received: 03/07/2024] [Revised: 08/02/2024] [Accepted: 08/29/2024] [Indexed: 09/04/2024]
Abstract
Out-of-home eating (takeaway, take-out and fast-foods) is associated with intakes of higher energy and fat, and lower intakes of micronutrients, and is associated with excess weight gain. In 2017, a unique opportunity arose to measure the association between the opening of a new multi-national fast-food restaurant (McDonald's) and consumption of fast-food on young people aged 11-16. This study uses a repeated cross-sectional design to explore group level change over time with respect to out-of-home eating behaviours of young people. Two secondary schools in Redcar and Cleveland agreed to participate and facilitated the completion of a questionnaire on their pupils eating behaviours at three timepoints a) prior to the new restaurant opening, b) three months post-opening and c) nine months post opening. Reported frequency of visits to McDonald's showed a statistically significant increase in visits between 3 and 9 months of the restaurant opening. This research asks and explores the question of whether the introduction of a new multi-national fast-food restaurant influences eating habits of young people attending schools near the new outlet.
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Affiliation(s)
- Helen J Moore
- School of Social Sciences, Humanities & Law, Teesside University, Middlesbrough, UK; Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK.
| | - Claire L O'Malley
- Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK; Centre for Public Health Research, School of Health & Life Sciences, Teesside University, Middlesbrough, UK
| | - Scott Lloyd
- Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK; Public Health South Tees, Middlesbrough, UK
| | - Fatemeh Eskandari
- Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK; Centre for Public Health Research, School of Health & Life Sciences, Teesside University, Middlesbrough, UK
| | - Kelly Rose
- Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK; Durham County Council, UK
| | - Mark Butler
- Centre for Public Health Research, School of Health & Life Sciences, Teesside University, Middlesbrough, UK
| | - Tim G Townshend
- Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK; School of Architecture, Planning & Landscape, Newcastle University, Newcastle Upon Tyne, UK
| | - Heather Brown
- Division of Health Research, Lancaster University, UK
| | | | - Amelia A Lake
- Fuse-The Centre for Translational Research in Public Health, Newcastle Upon Tyne, UK; Centre for Public Health Research, School of Health & Life Sciences, Teesside University, Middlesbrough, UK
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Clynes S, Moran A, Cardel M, Foster G, Phelan S. Weight Loss Maintainers Sustain High Diet Quality in Diverse Residential Retail Food Environments. J Acad Nutr Diet 2024; 124:957-963.e3. [PMID: 38556111 DOI: 10.1016/j.jand.2024.03.012] [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] [Received: 09/01/2023] [Revised: 03/09/2024] [Accepted: 03/27/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND The relationship between the retail food environment and diet quality has received minimal investigation among weight loss maintainers. OBJECTIVE The aim of this study was to investigate the association between the residential retail food environment and diet quality in weight loss maintainers from WeightWatchers in the United States. DESIGN Cross-sectional data were collected between January 2018 and February 2020. The Retail Food Environment Index (RFEI), based on geocoded home addresses, classified the environment as follows: RFEI <1.6 = healthiest; RFEI 1.6 to <2.5 = moderately healthy; RFEI 2.5 to <4.0 = moderately unhealthy; RFEI ≥4.0 = least healthy. Dietary data were obtained using a food frequency questionnaire. PARTICIPANTS/SETTING Adult participants (n = 1,159) who had lost weight using WeightWatchers and maintained ≥9.1-kg weight loss for ≥1 year (mean 24.7-kg loss for 3.4 years). MAIN OUTCOME MEASURES Healthy Eating Index 2015 (HEI-2015) component and total scores (0-100; higher scores indicate better alignment with the 2015-2020 Dietary Guidelines for Americans). STATISTICAL ANALYSES PERFORMED Regression models included RFEI category, the independent variable, and HEI-2015 and component scores (outcomes) controlling for age, sex, race and ethnicity, educational attainment, and household income. RESULTS Compared with individuals living in the healthiest food environments (mean HEI-2015 score = 71.5) those in the unhealthiest environments had a mean HEI-2015 score of 70.1 (95% CI 68.8 to 71.3), those in moderately unhealthy environments had a score of 71.3 (95% CI 70.3 to 73.1) and those in moderately healthy environments had a score of 70.3 (95% CI 68.9 to 71.2), indicating a nonlinear relationship. Compared with those in the healthiest environments, those in the least healthy environments had an approximately 0.47 lower added sugar HEI-2015 component score (95% CI -0.86 to -0.08), indicating approximately 5% higher added sugar intake. CONCLUSIONS Weight loss maintainers maintained high diet quality in diverse retail food environments. Compared with those in the healthiest food environments, those in the least healthy had a higher consumption of added sugars.
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Affiliation(s)
- Sasha Clynes
- Department of Health Policy, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
| | - Alyssa Moran
- Department of Health Policy, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Michelle Cardel
- WeightWatchers, New York, New York; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, Florida
| | - Gary Foster
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Suzanne Phelan
- Departments of Kinesiology and Public Health and Center for Health Research, California Polytechnic State University, San Luis Obispo, California
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Wong KYY, Moy FM, Shafie A, Rampal S. Identifying obesogenic environment through spatial clustering of body mass index among adults. Int J Health Geogr 2024; 23:16. [PMID: 38926856 PMCID: PMC11201309 DOI: 10.1186/s12942-024-00376-5] [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: 12/15/2023] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND The escalating trend of obesity in Malaysia is surmounting, and the lack of evidence on the environmental influence on obesity is untenable. Obesogenic environmental factors often emerge as a result of shared environmental, demographic, or cultural effects among neighbouring regions that impact lifestyle. Employing spatial clustering can effectively elucidate the geographical distribution of obesity and pinpoint regions with potential obesogenic environments, thereby informing public health interventions and further exploration on the local environments. This study aimed to determine the spatial clustering of body mass index (BMI) among adults in Malaysia. METHOD This study utilized information of respondents aged 18 to 59 years old from the National Health and Morbidity Survey (NHMS) 2014 and 2015 at Peninsular Malaysia and East Malaysia. Fast food restaurant proximity, district population density, and district median household income were determined from other sources. The analysis was conducted for total respondents and stratified by sex. Multilevel regression was used to produce the BMI estimates on a set of variables, adjusted for data clustering at enumeration blocks. Global Moran's I and Local Indicator of Spatial Association statistics were applied to assess the general clustering and location of spatial clusters of BMI, respectively using point locations of respondents and spatial weights of 8 km Euclidean radius or 5 nearest neighbours. RESULTS Spatial clustering of BMI independent of individual sociodemographic was significant (p < 0.001) in Peninsular and East Malaysia with Global Moran's index of 0.12 and 0.15, respectively. High-BMI clusters (hotspots) were in suburban districts, whilst the urban districts were low-BMI clusters (cold spots). Spatial clustering was greater among males with hotspots located closer to urban areas, whereas hotspots for females were in less urbanized areas. CONCLUSION Obesogenic environment was identified in suburban districts, where spatial clusters differ between males and females in certain districts. Future studies and interventions on creating a healthier environment should be geographically targeted and consider gender differences.
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Affiliation(s)
- Kimberly Yuin Y'ng Wong
- Centre of Epidemiology and Evidence Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia
| | - Foong Ming Moy
- Centre of Epidemiology and Evidence Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia.
| | - Aziz Shafie
- Department of Geography, Faculty of Social Sciences, University Malaya, Kuala Lumpur, Malaysia
| | - Sanjay Rampal
- Centre of Epidemiology and Evidence Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia
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11
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Lam TM, den Braver NR, Ohanyan H, Wagtendonk AJ, Vaartjes I, Beulens JW, Lakerveld J. The neighourhood obesogenic built environment characteristics (OBCT) index: Practice versus theory. ENVIRONMENTAL RESEARCH 2024; 251:118625. [PMID: 38467360 DOI: 10.1016/j.envres.2024.118625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 02/22/2024] [Accepted: 03/03/2024] [Indexed: 03/13/2024]
Abstract
BACKGROUND Obesity is a key risk factor for major chronic diseases such as type 2 diabetes and cardiovascular diseases. To extensively characterise the obesogenic built environment, we recently developed a novel Obesogenic Built environment CharacterisTics (OBCT) index, consisting of 17 components that capture both food and physical activity (PA) environments. OBJECTIVES We aimed to assess the association between the OBCT index and body mass index (BMI) in a nationwide health monitor. Furthermore, we explored possible ways to improve the index using unsupervised and supervised methods. METHODS The OBCT index was constructed for 12,821 Dutch administrative neighbourhoods and linked to residential addresses of eligible adult participants in the 2016 Public Health Monitor. We split the data randomly into a training (two-thirds; n = 255,187) and a testing subset (one-third; n = 127,428). In the training set, we used non-parametric restricted cubic regression spline to assess index's association with BMI, adjusted for individual demographic characteristics. Effect modification by age, sex, socioeconomic status (SES) and urbanicity was examined. As improvement, we (1) adjusted the food environment for address density, (2) added housing price to the index and (3) adopted three weighting strategies, two methods were supervised by BMI (variable selection and random forest) in the training set. We compared these methods in the testing set by examining their model fit with BMI as outcome. RESULTS The OBCT index had a significant non-linear association with BMI in a fully-adjusted model (p<0.05), which was modified by age, sex, SES and urbanicity. However, variance in BMI explained by the index was low (<0.05%). Supervised methods increased this explained variance more than non-supervised methods, though overall improvements were limited as highest explained variance remained <0.5%. DISCUSSION The index, despite its potential to highlight disparity in obesogenic environments, had limited association with BMI. Complex improvements are not necessarily beneficial, and the components should be re-operationalised.
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Affiliation(s)
- Thao Minh Lam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands; Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands; Upstream Team, Amsterdam UMC, VU University Amsterdam, De Boelelaan 1089a, 1081HV, Amsterdam, the Netherlands.
| | - Nicolette R den Braver
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands; Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands; Upstream Team, Amsterdam UMC, VU University Amsterdam, De Boelelaan 1089a, 1081HV, Amsterdam, the Netherlands
| | - Haykanush Ohanyan
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands; Upstream Team, Amsterdam UMC, VU University Amsterdam, De Boelelaan 1089a, 1081HV, Amsterdam, the Netherlands; Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Alfred J Wagtendonk
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands; Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands; Upstream Team, Amsterdam UMC, VU University Amsterdam, De Boelelaan 1089a, 1081HV, Amsterdam, the Netherlands
| | - Ilonca Vaartjes
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Internal Mail No. Str6.131, P.O. Box 85500, 3508, GA, Utrecht, the Netherlands
| | - Joline Wj Beulens
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands; Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Internal Mail No. Str6.131, P.O. Box 85500, 3508, GA, Utrecht, the Netherlands
| | - Jeroen Lakerveld
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands; Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands; Upstream Team, Amsterdam UMC, VU University Amsterdam, De Boelelaan 1089a, 1081HV, Amsterdam, the Netherlands
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12
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Lozano PM, Bobb JF, Kapos FP, Cruz M, Mooney SJ, Hurvitz PM, Anau J, Theis MK, Cook A, Moudon AV, Arterburn DE, Drewnowski A. Residential Density Is Associated With BMI Trajectories in Children and Adolescents: Findings From the Moving to Health Study. AJPM FOCUS 2024; 3:100225. [PMID: 38682047 PMCID: PMC11046231 DOI: 10.1016/j.focus.2024.100225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/01/2024]
Abstract
Introduction This study investigates the associations between built environment features and 3-year BMI trajectories in children and adolescents. Methods This retrospective cohort study utilized electronic health records of individuals aged 5-18 years living in King County, Washington, from 2005 to 2017. Built environment features such as residential density; counts of supermarkets, fast-food restaurants, and parks; and park area were measured using SmartMaps at 1,600-meter buffers. Linear mixed-effects models performed in 2022 tested whether built environment variables at baseline were associated with BMI change within age cohorts (5, 9, and 13 years), adjusting for sex, age, race/ethnicity, Medicaid, BMI, and residential property values (SES measure). Results At 3-year follow-up, higher residential density was associated with lower BMI increase for girls across all age cohorts and for boys in age cohorts of 5 and 13 years but not for the age cohort of 9 years. Presence of fast food was associated with higher BMI increase for boys in the age cohort of 5 years and for girls in the age cohort of 9 years. There were no significant associations between BMI change and counts of parks, and park area was only significantly associated with BMI change among boys in the age cohort of 5 years. Conclusions Higher residential density was associated with lower BMI increase in children and adolescents. The effect was small but may accumulate over the life course. Built environment factors have limited independent impact on 3-year BMI trajectories in children and adolescents.
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Affiliation(s)
- Paula Maria Lozano
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Jennifer F. Bobb
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Flavia P. Kapos
- Department of Orthopaedic Surgery and Duke Clinical Research Institute, Duke School of Medicine, Durham, North Carolina
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington
| | - Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Harborview Injury Prevention & Research Center, University of Washington, Seattle, Washington
| | - Philip M. Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, Washington
- Center for Studies in Demography & Ecology, University of Washington, Seattle, Washington
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, Washington
| | - David E. Arterburn
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Adam Drewnowski
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Center for Public Health Nutrition, University of Washington, Seattle, Washington
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Tharrey M, Bohn T, Klein O, Bulaev D, Van Beek J, Nazare JA, Franco M, Malisoux L, Perchoux C. Local retail food environment exposure and diet quality in rural and urban adults: A longitudinal analysis of the ORISCAV-LUX cohort study. Health Place 2024; 87:103240. [PMID: 38593577 DOI: 10.1016/j.healthplace.2024.103240] [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: 12/07/2023] [Revised: 03/26/2024] [Accepted: 03/26/2024] [Indexed: 04/11/2024]
Abstract
Despite growing interest in understanding how food environments shape dietary behaviors, European longitudinal evidence is scarce. We aimed to investigate the associations of 9-year average and change in exposure to local retail food environments with the diet quality of residents in Luxembourg. We used data from 566 adults enrolled in both waves of the nationwide ORISCAV-LUX study (2007-2017). Dietary quality was assessed by the Diet Quality Index-International (DQI-I). Exposure to "healthy" and "less healthy" food outlets was assessed by both absolute and relative GIS-based measurements. The results showed a 56.3% increase in less healthy food outlets over the period. In adjusted linear mixed models, high (vs. low) 9-year average exposure to less healthy food outlets was associated with lower DQI-I, when examining spatial access (β = -1.25, 95% CI: -2.29, -0.22) and proportions (β = -1.24, 95% CI: -2.15, -0.33). Stratified analyses showed these associations to be significant only among urban residents. There was no association between change in exposure to less healthy food outlets and DQI-I. Increased exposure to healthy outlets in rural areas, using absolute measurements, was associated with worsened DQI-I. Neighborhood socioeconomic status did not moderate the above associations. Findings suggest that the proliferation of less healthy food outlets may have contributed to the deterioration of the diet quality of urban residents, and support the use of relative measurements to fully capture the healthiness of food environments.
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Affiliation(s)
- Marion Tharrey
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte des Sciences, 4366, Esch-sur-Alzette, Luxembourg; Department of Precision Health, Luxembourg Institute of Health, 1A-B Rue Thomas Edison, 1445, Strassen, Luxembourg.
| | - Torsten Bohn
- Department of Precision Health, Luxembourg Institute of Health, 1A-B Rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Olivier Klein
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte des Sciences, 4366, Esch-sur-Alzette, Luxembourg
| | - Dmitry Bulaev
- Competence Center for Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Juliette Van Beek
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte des Sciences, 4366, Esch-sur-Alzette, Luxembourg; Department of Geography and Spatial Planning, Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Esch/Alzette, Luxembourg
| | - Julie-Anne Nazare
- Centre de Recherche en Nutrition Humaine Rhône-Alpes, CarMeN Laboratory, Univ-Lyon, INSERM, INRAe, Claude Bernard Lyon 1 University, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Manuel Franco
- Surgery and Medical and Social Sciences Department, Public Health and Epidemiology Research Group, School of Medicine and Health Sciences, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Laurent Malisoux
- Department of Precision Health, Luxembourg Institute of Health, 1A-B Rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Camille Perchoux
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte des Sciences, 4366, Esch-sur-Alzette, Luxembourg
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Ramírez-Toscano Y, Skaba D, de Matos VP, Pérez-Ferrer C, Barrientos-Gutiérrez T, López-Olmedo N, Pina MDF. Agreement between a web collaborative dataset and an administrative dataset to assess the retail food environment in Mexico. BMC Public Health 2024; 24:930. [PMID: 38556871 PMCID: PMC10983718 DOI: 10.1186/s12889-024-18410-3] [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] [Received: 09/07/2023] [Accepted: 03/21/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Latin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation. METHODS In this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland-Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa. RESULTS The CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42). CONCLUSIONS Google could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.
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Affiliation(s)
- Yenisei Ramírez-Toscano
- Center for Population Health Research, National Institute of Public Health, Avenida Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos CP, 62100, Mexico
| | - Daniel Skaba
- Instituto de Comunicação E Informação Científica E Tecnológica Em Saúde / Fundação Oswaldo Cruz - ICICT/FIOCRUZ, Rio de Janeiro, Brazil
| | - Vanderlei Pascoal de Matos
- Instituto de Comunicação E Informação Científica E Tecnológica Em Saúde / Fundação Oswaldo Cruz - ICICT/FIOCRUZ, Rio de Janeiro, Brazil
| | - Carolina Pérez-Ferrer
- Center for Population Health Research, National Institute of Public Health, Avenida Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos CP, 62100, Mexico
| | - Tonatiuh Barrientos-Gutiérrez
- Center for Population Health Research, National Institute of Public Health, Avenida Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos CP, 62100, Mexico
| | - Nancy López-Olmedo
- Center for Population Health Research, National Institute of Public Health, Avenida Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos CP, 62100, Mexico.
| | - Maria de Fátima Pina
- Instituto de Comunicação E Informação Científica E Tecnológica Em Saúde / Fundação Oswaldo Cruz - ICICT/FIOCRUZ, Rio de Janeiro, Brazil.
- Instituto de Investigação E Inovação Em Saúde Universidade Do Porto, Porto, Portugal.
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15
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Libuy N, Church D, Ploubidis G, Fitzsimons E. Fast food proximity and weight gain in childhood and adolescence: Evidence from Great Britain. HEALTH ECONOMICS 2024; 33:449-465. [PMID: 37971895 PMCID: PMC10952272 DOI: 10.1002/hec.4770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 09/08/2023] [Accepted: 09/18/2023] [Indexed: 11/19/2023]
Abstract
We study the relationship between proximity to fast food restaurants and weight gain from late childhood to early adolescence. We use the Millennium Cohort Study, a UK-wide nationally representative longitudinal study, linked with granular geocoded food outlet data to measure the presence of fast food outlets around children's homes and schools from ages 7 to 14. We find that proximity to fast food outlets is associated with increased weight (body mass index, overweight, obese, body fat, weight), but only among those with maternal education below degree level. Within this sample, those with lower levels of emotional regulation are at heightened risk of weight gain.
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Affiliation(s)
- Nicolás Libuy
- Centre for Longitudinal Studies, Social Research Institute, UCLLondonUK
| | - David Church
- Centre for Longitudinal Studies, Social Research Institute, UCLLondonUK
| | - George Ploubidis
- Centre for Longitudinal Studies, Social Research Institute, UCLLondonUK
| | - Emla Fitzsimons
- Centre for Longitudinal Studies, Social Research Institute, UCLLondonUK
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16
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Akl C, El-Helou N, Safadi G, Semaan A, El Sammak A, Trabelsi T, Sassi S, Akik C, El Ati J, Traissac P, Ghattas H. Urban school neighbourhoods dominated by unhealthy food retailers and advertisements in Greater Tunis: a geospatial study in the midst of the nutrition transition. Public Health Nutr 2024; 27:e44. [PMID: 38169454 PMCID: PMC10882541 DOI: 10.1017/s1368980023002860] [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: 01/05/2024]
Abstract
OBJECTIVE Food environments are a major determinant of children's nutritional status. Scarce evidence on food environments exists in low- and middle-income countries (LMIC). This study aims to fill this gap by documenting the obesogenicity of food environments around schools in Greater Tunis, Tunisia - an LMIC of the Middle East and North Africa region with an ongoing nutrition transition and increasing rates of childhood obesity. DESIGN In this cross-sectional study, we assessed built food environments around fifty primary schools. Ground-truthing was performed to collect geographic coordinates and pictures of food retailers and food advertisement sets within an 800-m road network buffer of each school. Retailers and advertisement sets were categorised as healthy or unhealthy according to a NOVA-based classification. Associations between school characteristics and retailers or advertisement sets were explored using multinomial regression models. SETTING Greater Tunis, Tunisia. PARTICIPANTS Random sample of fifty (thirty-five public and fifteen private) primary schools. RESULTS Overall, 3621 food retailers and 2098 advertisement sets were mapped. About two-thirds of retailers and advertisement sets were labelled as unhealthy. Most retailers were traditional corner stores (22 %) and only 6 % were fruit and vegetable markets. The prevailing food group promoted was carbonated and sugar-sweetened beverages (22 %). The proportion of unhealthy retailers was significantly higher in the richest v. poorest areas. CONCLUSIONS School neighbourhood food environments included predominantly unhealthy retailers and advertisements. Mapping of LMIC food environments is crucial to document the impact of the nutrition transition on children's nutritional status. This will inform policies and interventions to curb the emergent childhood obesity epidemic.
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Affiliation(s)
- Christelle Akl
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Nehmat El-Helou
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Gloria Safadi
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Aline Semaan
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | - Aya El Sammak
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Tarek Trabelsi
- INNTA (National Institute of Nutrition and Food Technology), SURVEN (Nutrition Surveillance and Epidemiology in Tunisia) Research Laboratory, Tunis1007, Tunisia
| | - Sonia Sassi
- INNTA (National Institute of Nutrition and Food Technology), SURVEN (Nutrition Surveillance and Epidemiology in Tunisia) Research Laboratory, Tunis1007, Tunisia
| | - Chaza Akik
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Jalila El Ati
- INNTA (National Institute of Nutrition and Food Technology), SURVEN (Nutrition Surveillance and Epidemiology in Tunisia) Research Laboratory, Tunis1007, Tunisia
| | - Pierre Traissac
- MoISA - University of Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, France
| | - Hala Ghattas
- Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
- Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC29208, USA
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17
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Huang Y, Burgoine T, Bishop TRP, Adams J. Assessing the healthiness of menus of all out-of-home food outlets and its socioeconomic patterns in Great Britain. Health Place 2024; 85:103146. [PMID: 38056051 DOI: 10.1016/j.healthplace.2023.103146] [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: 02/27/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 12/08/2023]
Abstract
Food environment research predominantly focuses on the spatial distribution of out-of-home food outlets. However, the healthiness of food choices available within these outlets has been understudied, largely due to resource constraints. In this study, we propose an innovative, low-resource approach to characterise the healthiness of out-of-home food outlets at scale. Menu healthiness scores were calculated for food outlets on JustEat, and a deep learning model was trained to predict these scores for all physical out-of-home outlets in Great Britain, based on outlet names. Our findings highlight the "double burden" of the unhealthy food environment in deprived areas where there tend to be more out-of-home food outlets, and these outlets tend to be less healthy. This methodological advancement provides a nuanced understanding of out-of-home food environments, with potential for automation and broad geographic application.
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Affiliation(s)
- Yuru Huang
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
| | - Thomas Burgoine
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Tom R P Bishop
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Jean Adams
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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18
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Chuvileva YE, Manangan A, Chew A, Rutherford G, Barillas-Basterrechea M, Barnoya J, Breysse PN, Blanck H, Liburd L. What North American retail food environment indices miss in Guatemala: Cultural considerations for the study of place and health. APPLIED GEOGRAPHY (SEVENOAKS, ENGLAND) 2024; 164:10.1016/j.apgeog.2024.103204. [PMID: 38532832 PMCID: PMC10964928 DOI: 10.1016/j.apgeog.2024.103204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
We evaluated the cross-context validity and equivalence of the US- and Canada-originated Retail Food Environment Index (RFEI) and modified RFEI (mRFEI) against a retail food environment dataset from the indigenous-majority city of Quetzaltenango (Xela), Guatemala. The RFEI/mRFEI failed to identify 77% of retailers and misclassified the healthiness of 42% of the remaining retailers in Xela, inaccurately labeling the city a food swamp. The RFEI/mRFEI are not currently suitable for mapping retail food environments in places like Quetzaltenango. Alternative functional and temporal classifications of retail food environments may provide measures with greater contextual fit, highlighting important cultural considerations for the study of place and dietary health.
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Affiliation(s)
- Yulia E. Chuvileva
- Division of Adolescent and School Health (DASH), National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP), Centers for Disease Control and Prevention (CDC), USA
| | - Arie Manangan
- Division of Environmental Health Science and Practice (DEHSP), National Center for Environmental Health (NCEH), CDC, Atlanta, GA, USA
| | - Aiken Chew
- Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - George Rutherford
- University of California San Francisco (UCSF), San Francisco, CA, USA
| | | | - Joaquín Barnoya
- Unidad de Cirugía Cardiovascular de Guatemala and Universidad Rafael Landivar, Guatemala City, Guatemala
| | - Patrick N. Breysse
- NCEH/Agency for Toxic Substances and Disease Registry (ATSDR), CDC, Atlanta, GA, USA
| | - Heidi Blanck
- Division of Nutrition, Physical Activity, and Obesity (DNPAO), NCCDPHP, CDC, Atlanta, GA, USA
| | - Leandris Liburd
- Office of Minority Health and Health Equity (OMHHE), CDC, Atlanta, GA, USA
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Recchia D, Perignon M, Rollet P, Bricas N, Vonthron S, Perrin C, Sirieix L, Charreire H, Méjean C. Store-specific grocery shopping patterns and their association with objective and perceived retail food environments. Public Health Nutr 2023; 27:e13. [PMID: 38072395 PMCID: PMC10830372 DOI: 10.1017/s1368980023002720] [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] [Received: 03/01/2023] [Revised: 10/24/2023] [Accepted: 11/30/2023] [Indexed: 01/06/2024]
Abstract
OBJECTIVE To explore store-specific grocery shopping patterns and assess associations with the objective and perceived retail food environment (RFE). DESIGN This cross-sectional study used principal component analysis and hierarchical cluster analysis to identify grocery shopping patterns and logistic regression models to assess their associations with the RFE, while adjusting for household characteristics. SETTING The Montpellier Metropolitan Area, France. PARTICIPANTS To be eligible for inclusion, participants had to be 18 years of age or older and reside in the Montpellier Metropolitan Area. Analyses were carried out on 415 households. RESULTS Households of cluster 'Supermarket' (49 % of households) primarily shopped at supermarkets and were less likely to live near a convenience store. Households of cluster 'Diversified' (18 %) shopped mostly at organic stores, at markets, at specialised stores, and from producers and were more likely to have a market in their activity space. Households of cluster 'Discount' (12 %) primarily shopped at discounters and were less likely to perceive a producer in their activity space. Households of cluster 'Convenience' (12 %) mostly shopped online or in convenience stores. Finally, households of cluster 'Specialized' (9 %) had high expenditures in greengrocers and in other specialised food stores and were more likely to live near a specialised food store. CONCLUSIONS This study highlighted the importance of considering both perceived and objective RFE indicators, as well as assessments around the home and in activity space. Understanding how people buy food and interact with their RFE is crucial for policymakers seeking to improve urban food policies.
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Affiliation(s)
- Daisy Recchia
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
| | - Marlène Perignon
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
| | - Pascaline Rollet
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
| | - Nicolas Bricas
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
- CIRAD, UMR MoISA, F-34398 Montpellier, Occitanie, France
| | - Simon Vonthron
- INNOVATION, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, Occitanie, France
| | - Coline Perrin
- INNOVATION, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, Occitanie, France
| | - Lucie Sirieix
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
| | - Hélène Charreire
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
| | - Caroline Méjean
- MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, Occitanie, France
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Lake AA, Moore HJ, Cotton M, O'Malley CL. Opportunities to improve population health: possibilities for healthier food environments. Proc Nutr Soc 2023; 82:264-271. [PMID: 37057804 DOI: 10.1017/s0029665123002677] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Abstract
The recent Covid-19 pandemic highlighted stark social inequalities, notably around access to food, nutrition and to green or blue space (i.e. outdoor spaces with vegetation and water). Consequently, obesity is socio-economically patterned by this inequality; and while the environmental drivers of obesity are widely acknowledged, there is currently little upstream intervention. We know that living with obesity contributes to increasing health inequalities, and places healthcare systems under huge strain. Our environment could broadly be described obesogenic, in the sense of supporting unhealthful eating patterns and sedentary behaviour. Evidence points to the existence of nearly 700 UK obesity policies, all of which have had little success. Obesity prevention and treatment has focused on educational and behavioural interventions targeted at individual consumers. A more sustainable approach would be to try and change the environments that promote less healthy eating and high energy intake as well as sedentary behaviour. Approaches which modify the environment have the potential to assist in the prevention of this complex condition. This review paper focuses on the role of wider food environments or foodscapes. While there is an imperfect evidence base relating to the role of the foodscape in terms of the obesity crisis, policy, practice, civic society and industry must work together and take action now, in areas where current evidence suggests change is required. Despite the current cost-of-living crisis, shaping the foodscape to better support healthful eating decisions has the potential to be a key aspect of a successful obesity prevention intervention.
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Affiliation(s)
- Amelia A Lake
- School of Health and Life Sciences, Teesside University, Middlesbrough, UK
- Fuse, The Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
| | - Helen J Moore
- School of Social Sciences, Humanities and Law, Teesside University, Middlesbrough, UK
- Fuse, The Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
| | - Matthew Cotton
- School of Social Sciences, Humanities and Law, Teesside University, Middlesbrough, UK
- Fuse, The Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
| | - Claire L O'Malley
- School of Health and Life Sciences, Teesside University, Middlesbrough, UK
- Fuse, The Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
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21
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Wood SM, Alston L, Beks H, Mc Namara K, Coffee NT, Clark RA, Wong Shee A, Versace VL. Quality appraisal of spatial epidemiology and health geography research: A scoping review of systematic reviews. Health Place 2023; 83:103108. [PMID: 37651961 DOI: 10.1016/j.healthplace.2023.103108] [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: 04/24/2023] [Revised: 08/19/2023] [Accepted: 08/22/2023] [Indexed: 09/02/2023]
Abstract
A scoping review of peer-reviewed literature was conducted to understand how systematic reviews assess the methodological quality of spatial epidemiology and health geography research. Fifty-nine eligible reviews were identified and included. Variations in the use of quality appraisal tools were found. Reviews applied existing quality appraisal tools with no adaptations (n = 32; 54%), existing quality appraisal tools with adaptations (n = 9; 15%), adapted tools or methods from other reviews (n = 13; 22%), and developed new quality appraisal tools for the review (n = 5; 8%). Future research should focus on developing and validating a quality appraisal tool that evaluates the spatial methodology within studies.
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Affiliation(s)
- Sarah M Wood
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia.
| | - Laura Alston
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia; Research Unit, Colac Area Health, Colac, Vic, Australia
| | - Hannah Beks
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia
| | - Kevin Mc Namara
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia; Grampians Health, Ballarat, Vic, Australia
| | - Neil T Coffee
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia; Australian Centre for Housing Research, The University of Adelaide, Adelaide, SA, Australia
| | - Robyn A Clark
- Caring Futures Institute, Flinders University, SA, Australia; Southern Adelaide Health Care Services, SA, Australia
| | - Anna Wong Shee
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia; Grampians Health, Ballarat, Vic, Australia
| | - Vincent L Versace
- Deakin Rural Health, School of Medicine, Faculty of Health, Deakin University, Warrnambool Campus, Vic, Australia; Grampians Health, Ballarat, Vic, Australia
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Hobbs M, McLeod GFH, Mackenbach JD, Marek L, Wiki J, Deng B, Eggleton P, Boden JM, Bhubaneswor D, Campbell M, Horwood LJ. Change in the food environment and measured adiposity in adulthood in the Christchurch Health and development birth cohort, Aotearoa, New Zealand: A birth cohort study. Health Place 2023; 83:103078. [PMID: 37517383 DOI: 10.1016/j.healthplace.2023.103078] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/11/2023] [Accepted: 06/21/2023] [Indexed: 08/01/2023]
Abstract
This study investigated associations between change in the food environment and change in measured body mass index (BMI) and waist circumference (WC) in the Christchurch Health and Development Study (CHDS) birth cohort. Our findings suggest that cohort members who experienced the greatest proportional change towards better access to fast food outlets had the slightly larger increases in BMI and WC. Contrastingly, cohort members who experienced the greatest proportional change towards shorter distance and better access to supermarkets had slightly smaller increases in BMI and WC. Our findings may help explain the changes in BMI and WC at a population level.
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Affiliation(s)
- Matthew Hobbs
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; The Cluster for Community and Urban Resilience (CURe), University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand.
| | - Geraldine F H McLeod
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Joreintje D Mackenbach
- Department of Epidemiology and Data Science, Amsterdam UMC Location Vrije University, Amsterdam, the Netherlands; Upstream Team, www.upstreamteam.nl, Amsterdam UMC, Amsterdam, the Netherlands
| | - Lukas Marek
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Jesse Wiki
- Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland - Waipapa Taumata Rau, Auckland, New Zealand
| | - Bingyu Deng
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Phoebe Eggleton
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Joseph M Boden
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Dhakal Bhubaneswor
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Malcolm Campbell
- Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; School of Earth and Environment, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - L John Horwood
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
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23
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Ferdinands AR, Brown JA, Nielsen CC, Nykiforuk CIJ, Raine KD. What counts? Adding nuance to retail food environment measurement tools in a Canadian context. Public Health Nutr 2023; 26:1326-1337. [PMID: 37073692 PMCID: PMC10346037 DOI: 10.1017/s1368980023000733] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 02/20/2023] [Accepted: 03/24/2023] [Indexed: 04/20/2023]
Abstract
OBJECTIVE Limitations of traditional geospatial measures, like the modified Retail Food Environment Index (mRFEI), are well documented. In response, we aimed to: (1) extend existing food environment measures by inductively developing subcategories to increase the granularity of healthy v. less healthy food retailers; (2) establish replicable coding processes and procedures; and (3) demonstrate how a food retailer codebook and database can be used in healthy public policy advocacy. DESIGN We expanded the mRFEI measure such that 'healthy' food retailers included grocery stores, supermarkets, hypermarkets, wholesalers, bulk food stores, produce outlets, butchers, delis, fish and seafood shops, juice/smoothie bars, and fresh and healthy quick-service retailers; and 'less healthy' food retailers included fast-food restaurants, convenience stores, coffee shops, dollar stores, pharmacies, bubble tea restaurants, candy stores, frozen dessert restaurants, bakeries, and food trucks. Based on 2021 government food premise licences, we used geographic information systems software to evaluate spatial accessibility of healthy and less healthy food retailers across census tracts and in proximity to schools, calculating differences between the traditional v. expanded mRFEI. SETTING Calgary and Edmonton, Canada. PARTICIPANTS N/A. RESULTS Of the 10 828 food retailers geocoded, 26 % were included using traditional mRFEI measures, while 53 % were included using our expanded categorisation. Changes in mean mRFEI across census tracts were minimal, but the healthfulness of food environments surrounding schools significantly decreased. CONCLUSIONS Overall, we show how our mRFEI adaptation, and transparent reporting on its use, can promote more nuanced and comprehensive food environment assessments to better support local research, policy and practice innovations.
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Affiliation(s)
- Alexa Rae Ferdinands
- School of Public Health; 3-300 Edmonton Clinic Health Academy, 11405 – 87 Ave, University of Alberta, EdmontonT6G 1C9, AB, Canada
| | - Jennifer Ann Brown
- School of Public Health; 3-300 Edmonton Clinic Health Academy, 11405 – 87 Ave, University of Alberta, EdmontonT6G 1C9, AB, Canada
| | - Charlene C Nielsen
- School of Public Health; 3-300 Edmonton Clinic Health Academy, 11405 – 87 Ave, University of Alberta, EdmontonT6G 1C9, AB, Canada
| | - Candace IJ Nykiforuk
- School of Public Health; 3-300 Edmonton Clinic Health Academy, 11405 – 87 Ave, University of Alberta, EdmontonT6G 1C9, AB, Canada
| | - Kim D Raine
- School of Public Health; 3-300 Edmonton Clinic Health Academy, 11405 – 87 Ave, University of Alberta, EdmontonT6G 1C9, AB, Canada
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24
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Madlala SS, Hill J, Kunneke E, Lopes T, Faber M. Adult food choices in association with the local retail food environment and food access in resource-poor communities: a scoping review. BMC Public Health 2023; 23:1083. [PMID: 37280606 PMCID: PMC10243040 DOI: 10.1186/s12889-023-15996-y] [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: 11/23/2022] [Accepted: 05/26/2023] [Indexed: 06/08/2023] Open
Abstract
BACKGROUND There is a growing body of research on local retail food environments globally in both urban and rural settings. Despite this, little research has been conducted on adult food choices, local retail environments, and healthy food access in resource-poor communities. The purpose of this study is therefore to provide an overview of the evidence on adult food choices (measured as dietary intake) in association with the local retail food environment and food access in resource-poor communities (defined as low-income communities and/or households). METHODS We searched nine databases for studies published from July 2005 to March 2022 and identified 2426 records in the primary and updated search. Observational studies, empirical and theoretical studies, focused on adults ≤ 65 years, published in English peer-reviewed journals, examining local retail food environments and food access, were included. Two independent reviewers screened identified articles using the selection criteria and data extraction form. Study characteristics and findings were summarized for all studies and relevant themes summarized for qualitative and mixed methods studies. RESULTS A total of 47 studies were included in this review. Most studies were cross sectional (93.6%) and conducted in the United States of America (70%). Nineteen (40.4%) studies assessed the association between food choice outcomes and local retail food environment exposures, and evidence on these associations are inconclusive. Associations of certain food choice outcomes with healthy food retail environments were positive for healthy foods (in 11 studies) and unhealthy foods (in 3 studies). Associations of certain food choice outcomes with unhealthy retail food environment exposures were positive for unhealthy foods in 1 study and negative for healthy foods in 3 studies. In 9 studies, some of the food choice outcomes were not associated with retail food environment exposures. A healthy food store type and lower food prices were found to be major facilitators for healthy food access in resource-poor communities, while cost and transportation were the main barriers. CONCLUSIONS More research is needed on the local retail food environment in communities in low- and middle-income countries to develop better interventions to improve food choices and access to healthy foods in resource-poor communities.
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Affiliation(s)
- Samukelisiwe S Madlala
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa.
- School of Public Health, Faculty of Community and Health Sciences, University of the Western Cape, Cape Town, South Africa.
| | - Jillian Hill
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa
| | - Ernesta Kunneke
- Department of Dietetics and Nutrition, University of the Western Cape, Cape Town, South Africa
| | - Tatum Lopes
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa
- Division of Chemical Pathology, Department of Pathology, Faculty of Medicine and Health Sciences, University of Stellenbosch, Tygerberg Hospital, Cape Town, South Africa
| | - Mieke Faber
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa
- Department of Dietetics and Nutrition, University of the Western Cape, Cape Town, South Africa
- Centre of Excellence for Nutrition, North-West University, Potchefstroom, South Africa
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25
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M H, N B, L M, J W, J K, R T, T R, J B, H T, S H, B M. The environment a young person grows up in is associated with their mental health: A nationwide geospatial study using the integrated data infrastructure, New Zealand. Soc Sci Med 2023; 326:115893. [PMID: 37119566 DOI: 10.1016/j.socscimed.2023.115893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 03/19/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND Mental health conditions often arise during adolescence, are multifaceted in aetiology, and may be related to the type of environment in which young people reside. This study used nationwide population-level data to investigate whether the environment a young person grows up in is associated with their mental health. METHOD Data were extracted from the Integrated Data Infrastructure (IDI), a large nationwide research repository, for 917,211 young people (aged 10-24 years) including sociodemographic and mental health data (i.e. emotional, behavioural, substance problems, and self-harm). Environmental data were sourced from the nationwide area-based Healthy Location Index (HLI), which has comprehensive data on the location of several health-constraining (i.e. fast-food outlets) and health-promoting features (i.e. physical activity facilities). Environments were classified as: i) health-promoting, ii) health-constraining, or iii) neither. Associations between the HLI and mental health were investigated using multi-level mixed effects logistic regression modelling. RESULTS Overall, there was evidence of an association between the environment a young person resided in and their mental health. Young people residing in health-constraining environments had higher odds of any mental health condition (Adjusted Odds Ratio (AOR) = 1.020 [1.001, 1.040]) and any emotional condition (AOR = 1.037 [1.012, 1.062]). Young people residing in health-promoting environments had lower odds of substance problems (AOR = 0.950 [0.905, 0.997]). There were no significant effects of the environment on behavioural conditions. CONCLUSION Our study utilises a large national sample of almost one million young people to confirm the importance of environmental determinants for mental health. It is possible that leverage points for improving the mental health of young people, and reducing the burden to the health system of mental health, can be sought in upstream environmental based interventions.
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Affiliation(s)
- Hobbs M
- Faculty of Health, University of Canterbury, Christchurch, Canterbury, New Zealand; GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - Bowden N
- Department of Women's and Children's Health, University of Otago, Dunedin, New Zealand
| | - Marek L
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Wiki J
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Kokaua J
- Va'a O Tautai - Centre for Pacific Health, Health Sciences, University of Otago, Dunedin, New Zealand
| | - Theodore R
- National Centre for Lifecourse Research, University of Otago, Dunedin, New Zealand
| | - Ruhe T
- Va'a O Tautai - Centre for Pacific Health, Health Sciences, University of Otago, Dunedin, New Zealand
| | - Boden J
- Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago Christchurch, New Zealand
| | - Thabrew H
- The Werry Centre, Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Hetrick S
- The Werry Centre, Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Milne B
- Centre of Methods and Policy Application in the Social Sciences, University of Auckland, Auckland, New Zealand
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Longitudinal association between density of retail food stores and body mass index in Mexican school children and adolescents. Int J Obes (Lond) 2023; 47:365-374. [PMID: 36792910 PMCID: PMC10147568 DOI: 10.1038/s41366-023-01273-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/17/2023]
Abstract
BACKGROUND Obesity is rapidly increasing in Mexican children and adolescents, while food environments are rapidly changing. We evaluated the association between changes in retail food stores and change in body mass index (BMI) in Mexican children and adolescents. METHODS Data on 7507 participants aged 5-19 years old came from the Mexican Family Life Survey 2002-2012. Density of food stores at the municipal-level (number of food stores/area in km2) came from the Economic Censuses of 1999, 2004 and 2009. We categorized food stores as small food retail (small neighborhood stores, tiendas de abarrotes in Mexico), specialty foods, fruit/vegetables, convenience foods, and supermarkets. Associations between change in food stores and change in BMI were estimated using five longitudinal linear fixed-effects regression models (one per type of food store) adjusted for age, parental education, municipal-level socioeconomic deprivation and population density. Density of each food store type was operationalized as quartiles. Analyses were stratified by urbanization. RESULTS There was an inverse dose-response association between increases in fruit/vegetable store density and BMI (β = -0.455 kg/m2, β = -0.733 kg/m2, and β = -0.838 kg/m2 in the second, third, and fourth quartile). In non-urban areas, children living in municipalities with the highest density of small food retail stores experienced a reduction in BMI (β = -0.840 kg/m2). In urban areas, there was an inverse association between specialty food stores with BMI (β = -0.789 kg/m2 in third quartile, and β = -1.204 kg/m2 in fourth quartile). We observed dynamic associations with age; results suggested stronger associations in adolescents. CONCLUSIONS The availability of fruit/vegetable stores may influence a reduction in children and adolescents BMI. These results indicate that policy approaches could be tailored by type of food store - with some consideration for level of urbanization and children's age.
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Rossi CE, Pinho MGM, Corrêa EN, de Abreu ÂH, Rech CR, Ferreira JRDC, de Vasconcelos FDAG. Neighborhood Availability and Use of Food, Physical Activity, and Social Services Facilities in Relation to Overweight and Obesity in Children and Adolescents. Food Nutr Bull 2023; 44:12-26. [PMID: 36601667 DOI: 10.1177/03795721221146215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
OBJECTIVE To evaluate the association of a combined measure of availability and use of facilities from the food environment and overweight (including obesity) among schoolchildren, while taking into account the physical activity and social-assistance environments. METHODS Cross-sectional study with a probabilistic sample of schoolchildren aged 7 to 14 years living in a southern Brazilian city (n = 2026). Multilevel analyses were performed with overweight as outcome and the food environment as main exposure. Models were adjusted for the physical activity and social-assistance environments, as well as individual and other residential neighborhood characteristics. RESULTS Greater availability of restaurants around the home was associated with higher odds of overweight (odds ratio [OR] = 1.40; 95% CI = 1.06-1.85). Stronger associations were found for schoolchildren reporting to use restaurants (OR = 1.48; 95% CI = 1.15-1.90). This association remained significant after adjusting for the presence of other food retailers. Schoolchildren who had social-assistance facilities around their homes, but reported not to use them, showed consistently higher odds of being overweight (OR = 1.34; 95% CI = 1.01-1.78) as compared to schoolchildren who had these facilities near home and used them. The physical activity environment was not associated with the outcome. CONCLUSIONS Availability and use of the food and social-assistance environments were significantly associated with overweight (including obesity) among the schoolchildren. Future research should consider the use of environmental facilities in combination to their geographical availability. Our results highlight the need for policies that limit the access to obesogenic food outlets by children and adolescents.
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Affiliation(s)
| | - Maria Gabriela M Pinho
- Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands.,Upstream Team, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands
| | - Elizabeth Nappi Corrêa
- Universidade Federal de Santa Catarina. Rua Engenheiro Agronômico Andrei Cristian Ferreira, s/n-Centro de Ciências da Saúde, Trindade, Florianópolis-Santa Catarina, Brazil
| | - Ângelo Horta de Abreu
- Gis Especialist. Imagem-Enterprise for Geographic Intelligence Solutions. Belo Horizonte-Minas Gerais, Brazil
| | - Cassiano Ricardo Rech
- Programa de Pós-Graduação em Educação Física (PPGEF), Campus Universitário Trindade, Florianópolis-Santa Catarina, Brazil
| | | | - Francisco de Assis Guedes de Vasconcelos
- Universidade Federal de Santa Catarina. Rua Engenheiro Agronômico Andrei Cristian Ferreira, s/n-Centro de Ciências da Saúde, Trindade, Florianópolis-Santa Catarina, Brazil
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Wray A, Martin G, Doherty S, Gilliland J. Analyzing differences between spatial exposure estimation methods: A case study of outdoor food and beverage advertising in London, Canada. Health Place 2023; 79:102641. [PMID: 34344617 DOI: 10.1016/j.healthplace.2021.102641] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 07/09/2021] [Accepted: 07/16/2021] [Indexed: 10/20/2022]
Abstract
Exposure assessment in the context of mobility-oriented health research often is challenged by the type of spatial measurement technique used to estimate exposures to environmental features. The purpose of this study is to compare smartphone global positioning system (GPS), shortest network path mobility, and buffer-based approaches in estimating exposure to outdoor food and beverage advertising among a sample of 154 teenagers involved in the SmartAPPetite study during 2018 in London, Ontario, Canada. Participants were asked to report their home postal code, age, gender identity, ethnicity, and number of purchases they had made at a retail food outlet in the past month. During the same time period, a mobile phone application was used to log their mobility and specifically record when a participant was in close proximity to outdoor advertising. The results of negative binomial regression modelling reveal significant differences in estimates of advertising exposure, and the relationship to self-reported purchasing. Spatial exposure estimation methods showed differences across regression models, with the buffer and observed GPS approaches delivering the best fitting models, depending on the type of retail food outlet. There is a clear need for more robust research of spatial exposure measurement techniques in the context of mobility and food (information) environment research.
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Affiliation(s)
- Alexander Wray
- Department of Geography & Environment, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada; Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Gina Martin
- Faculty of Health Disciplines, Athabasca University, 1 University Drive, Athabasca, Alberta, T9S 3A3, Canada; Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Sean Doherty
- Department of Geography & Environmental Studies, Wilfrid Laurier University, 75 University Avenue West, Waterloo, Ontario, N2L 3C5, Canada; Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Jason Gilliland
- Department of Geography & Environment, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada; Department of Pediatrics, Department of Epidemiology & Biostatistics, School of Health Studies, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada; Human Environments Analysis Lab, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada.
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Lam TM, Wagtendonk AJ, den Braver NR, Karssenberg D, Vaartjes I, Timmermans EJ, Beulens JWJ, Lakerveld J. Development of a neighborhood obesogenic built environment characteristics index for the Netherlands. Obesity (Silver Spring) 2023; 31:214-224. [PMID: 36541154 PMCID: PMC10108038 DOI: 10.1002/oby.23610] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/26/2022] [Accepted: 08/04/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Environmental factors that drive obesity are often studied individually, whereas obesogenic environments are likely to consist of multiple factors from food and physical activity (PA) environments. This study aimed to compose and describe a comprehensive, theory-based, expert-informed index to quantify obesogenicity for all neighborhoods in the Netherlands. METHODS The Obesogenic Built Environment CharacterisTics (OBCT) index consists of 17 components. The index was calculated as an average of componential scores across both food and PA environments and was scaled from 0 to 100. The index was visualized and summarized with sensitivity analysis for weighting methods. RESULTS The OBCT index for all 12,821 neighborhoods was right-skewed, with a median of 44.6 (IQR = 10.1). Obesogenicity was lower in more urbanized neighborhoods except for the extremely urbanized neighborhoods (>2500 addresses/km2 ), where obesogenicity was highest. The overall OBCT index score was moderately correlated with the food environment (Spearman ρ = 0.55, p <0.05) and with the PA environment (ρ = 0.38, p <0.05). Hierarchical weighting increased index correlations with the PA environment but decreased correlations with the food environment. CONCLUSIONS The novel OBCT index and its comprehensive environmental scores are potentially useful tools to quantify obesogenicity of neighborhoods.
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Affiliation(s)
- Thao Minh Lam
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands
- Upstream Team, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Alfred J Wagtendonk
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands
- Upstream Team, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Nicolette R den Braver
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands
- Upstream Team, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Derek Karssenberg
- Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands
| | - Ilonca Vaartjes
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Erik J Timmermans
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Joline W J Beulens
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Jeroen Lakerveld
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Health Behaviours and Chronic Diseases, Amsterdam, the Netherlands
- Upstream Team, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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Zhou RZ, Hu Y, Tirabassi JN, Ma Y, Xu Z. Deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data for enhancing obesity estimation. Int J Health Geogr 2022; 21:22. [PMID: 36585658 PMCID: PMC9801358 DOI: 10.1186/s12942-022-00321-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 12/10/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Obesity is a serious public health problem. Existing research has shown a strong association between obesity and an individual's diet and physical activity. If we extend such an association to the neighborhood level, information about the diet and physical activity of the residents of a neighborhood may improve the estimate of neighborhood-level obesity prevalence and help identify the neighborhoods that are more likely to suffer from obesity. However, it is challenging to measure neighborhood-level diet and physical activity through surveys and interviews, especially for a large geographic area. METHODS We propose a method for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data, and examine the extent to which the derived measurements can enhance obesity estimation, in addition to the socioeconomic and demographic variables typically used in the literature. We conduct case studies in three different U.S. cities, which are New York City, Los Angeles, and Buffalo, using anonymized mobile phone location data from the company SafeGraph. We employ five different statistical and machine learning models to test the potential enhancement brought by the derived measurements for obesity estimation. RESULTS We find that it is feasible to derive neighborhood-level diet and physical activity measurements from anonymized mobile phone location data. The derived measurements provide only a small enhancement for obesity estimation, compared with using a comprehensive set of socioeconomic and demographic variables. However, using these derived measurements alone can achieve a moderate accuracy for obesity estimation, and they may provide a stronger enhancement when comprehensive socioeconomic and demographic data are not available (e.g., in some developing countries). From a methodological perspective, spatially explicit models overall perform better than non-spatial models for neighborhood-level obesity estimation. CONCLUSIONS Our proposed method can be used for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone data. The derived measurements can enhance obesity estimation, and can be especially useful when comprehensive socioeconomic and demographic data are not available. In addition, these derived measurements can be used to study obesity-related health behaviors, such as visit frequency of neighborhood residents to fast-food restaurants, and to identify primary places contributing to obesity-related issues.
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Affiliation(s)
- Ryan Zhenqi Zhou
- GeoAI Lab, Department of Geography, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Yingjie Hu
- GeoAI Lab, Department of Geography, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
| | - Jill N Tirabassi
- Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Yue Ma
- GeoAI Lab, Department of Geography, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Zhen Xu
- College of Landscape Architecture, Nanjing Forestry University, Nanjing, Jiangsu, 210037, China
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Christensen A, Griffiths C, Hobbs M, Gorse C, Radley D. Investigating where adolescents engage in moderate to vigorous physical activity and sedentary behaviour: An exploratory study. PLoS One 2022; 17:e0276934. [PMID: 36472978 PMCID: PMC9725162 DOI: 10.1371/journal.pone.0276934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 10/17/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND There is a persistent lack of understanding on the influence of the environment on behaviour and health. While the environment is considered an important modifiable determinant of health behaviour, past research assessing environments often relies on static, researcher-defined buffers of arbitrary distance. This likely leads to misrepresentation of true environmental exposures. This exploratory study aims to compare researcher-defined and self-drawn buffers in reflecting the spaces and time adolescents engage in physical activity (PA) and sedentary behaviour. It also investigates if adolescent's access the PA facility and greenspace nearest their home or school for PA, as well as examine how much time adolescents spent in PA at any PA facilities and greenspaces. METHODS Adolescents (aged 14-18 years; n = 34) were recruited from schools in West Yorkshire, England. Seven consecutive days of global positioning system (GPS) and accelerometer data were collected at 15 second intervals. Using ArcGIS, we compared 30 different researcher-defined buffers including: radial, network and ellipse buffers at 400m, 800m, 1000m, 1600m and 3000m and participant-defined self-drawn neighbourhoods to objectively measured PA and sedentary space and PA time. Location of PA was also compared to Points of Interest data to determine if adolescents use the nearest PA facility or greenspace to their home or school and to examine how much PA was undertaken within these locations. RESULTS Our exploratory findings show the inadequacy of researcher-defined buffer size in assessing MVPA space or sedentary space. Furthermore, less than 35% of adolescents used the greenspaces or PA facilities nearest to their home or school. Approximately 50% of time spent in PA did not occur within the home, school, PA facility, or greenspace environments. CONCLUSION Our exploratory findings help to begin to quantify the inadequacy of researcher-defined, and self-drawn buffers in capturing adolescent MVPA and sedentary space, as well as time spent in PA. Adolescents often do not use PA facilities and greenspaces nearest their home and school and a large proportion of PA is achieved outside PA facilities and greenspaces. Further research with larger samples are needed to confirm the findings of this exploratory study.
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Affiliation(s)
- Alex Christensen
- Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom
- * E-mail:
| | - Claire Griffiths
- Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom
| | - Matthew Hobbs
- Faculty of Health, University of Canterbury, Christchurch, Canterbury, New Zealand
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Chris Gorse
- School of Built Environment and Engineering, Carnegie, Leeds Beckett University, Leeds, United Kingdom
| | - Duncan Radley
- Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom
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Christensen A, Radley D, Hobbs M, Gorse C, Griffiths C. Investigating how researcher-defined buffers and self-drawn neighbourhoods capture adolescent availability to physical activity facilities and greenspaces: An exploratory study. Spat Spatiotemporal Epidemiol 2022; 43:100538. [PMID: 36460456 DOI: 10.1016/j.sste.2022.100538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/16/2022] [Accepted: 09/13/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Modifying the environment is considered an effective population-level approach for increasing healthy behaviours, but associations remain ambiguous. This exploratory study aims to compare researcher-defined buffers and self-drawn neighbourhoods (SDN) to objectively measured availability of physical activity (PA) facilities and greenspaces in adolescents. METHODS Seven consecutive days of GPS data were collected in an adolescent sample of 14-18 year olds (n = 69). Using Points of Interest and greenspace data, availability of PA opportunities within activity spaces were determined. We compared 30 different definitions of researcher-defined neighbourhoods and SDNs to objectively measured availability. RESULTS Findings showed low agreement for all researcher-defined buffers in measuring the availability of PA facilities in activity spaces. However, results were less clear for greenspace. SDNs also demonstrate low agreement for capturing availability to the PA environment. CONCLUSION This exploratory study highlights the inadequacy of researcher-defined buffers and SDNs to define availability to environmental features.
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Affiliation(s)
- A Christensen
- Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom, LS6 3QT, UK.
| | - D Radley
- Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom, LS6 3QT, UK
| | - M Hobbs
- Faculty of Health, University of Canterbury, Christchurch, Canterbury, New Zealand; GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - C Gorse
- School of Built Environment and Engineering, Carnegie, Leeds Beckett University, Leeds, LS6 3QT, UK
| | - C Griffiths
- Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom, LS6 3QT, UK
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Sánchez BN, Fu H, Matsuzaki M, Sanchez-Vaznaugh E. Characterizing food environments near schools in California: A latent class approach simultaneously using multiple food outlet types and two spatial scales. Prev Med Rep 2022; 29:101937. [PMID: 35928596 PMCID: PMC9344015 DOI: 10.1016/j.pmedr.2022.101937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 07/21/2022] [Accepted: 07/26/2022] [Indexed: 11/30/2022] Open
Abstract
It is challenging to evaluate associations between the food environment near schools with either prevalence of childhood obesity or with socioeconomic characteristics of schools. This is because the food environment has many dimensions, including its spatial distribution. We used latent class analysis to classify public schools in urban, suburban, and rural areas in California into food environment classes based on the availability and spatial distribution of multiple types of unhealthy food outlets nearby. All urban schools had at least one unhealthy food outlet nearby, compared to seventy-two percent of schools in rural areas did. Food environment classes varied in the quantity of available food outlets, the relative mix of food outlet types, and the outlets' spatial distribution near schools. Regardless of urbanicity, schools in low-income neighborhoods had greater exposure to unhealthy food outlets. The direction of associations between food environment classes and school size, type, and race/ethnic composition depends on the level of urbanicity of the school locations. Urban schools attended primarily by African American and Asian children are more likely to have greater exposures to unhealthy food outlets. In urban and rural but not suburban areas, schools attended primarily by Latino students had more outlets offering unhealthy foods or beverages nearby. In suburban areas, differences in the spatial distribution of food outlets indicates that food outlets are more likely to cluster near K-12 schools and high schools compared to elementary schools. Intervention design and future research need to consider that the associations between food environment exposures and school characteristics differ by urbanicity.
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Affiliation(s)
- Brisa N. Sánchez
- Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, PA 19104, USA
| | - Han Fu
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48104, USA
| | - Mika Matsuzaki
- Department of International Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Emma Sanchez-Vaznaugh
- Health Education Department, San Francisco State University, San Francisco, CA 94132, USA
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Bernsdorf KA, Bøggild H, Aadahl M, Toft U. Validation of retail food outlet data from a Danish government inspection database. Nutr J 2022; 21:60. [PMID: 36163058 PMCID: PMC9513017 DOI: 10.1186/s12937-022-00809-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 08/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Globally, unhealthy diet is one of the leading global risks to health, thus it is central to consider aspects of the food environment that are modifiable and may enable healthy eating. Food retail data can be used to present and facilitate analyses of food environments that in turn may direct strategies towards improving dietary patterns among populations. Though food retail data are available in many countries, their completeness and accuracy differ. METHODS We applied a systematically name-based procedure combined with a manual procedure on Danish administrative food retailer data (i.e. the Smiley register) to identify, locate and classify food outlets. Food outlets were classified into the most commonly used classifications (i.e. fast food, restaurants, convenience stores, supermarkets, fruit and vegetable stores and miscellaneous) each divided into three commonly used definitions; narrow, moderate and broad. Classifications were based on branch code, name, and/or information on the internal and external appearance of the food outlet. From ground-truthing we validated the information in the register for its sensitivity and positive predictive value. RESULTS In 361 randomly selected areas of the Capital region of Denmark we identified a total of 1887 food outlets compared with 1861 identified in the register. We obtained a sensitivity of 0.75 and a positive predictive value of 0.76. Across classifications, the positive predictive values varied with highest values for the moderate and broad definitions of fast food, convenience stores and supermarkets (ranging from 0.89 to 0.97). CONCLUSION Information from the Smiley Register is considered to be representative to the Danish food environment and may be used for future research.
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Affiliation(s)
- Kamille Almer Bernsdorf
- Center for Clinical Research and Prevention, Section for Health Promotion and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
| | - Henrik Bøggild
- Epidemiology and Biostatistics, Public Health and Epidemiology Group, Aalborg University Hospital, Aalborg, Denmark
| | - Mette Aadahl
- Center for Clinical Research and Prevention, Section for Health Promotion and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.,Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla Toft
- Center for Clinical Research and Prevention, Section for Health Promotion and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
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Cruz M, Drewnowski A, Bobb JF, Hurvitz PM, Moudon AV, Cook A, Mooney SJ, Buszkiewicz JH, Lozano P, Rosenberg DE, Kapos F, Theis MK, Anau J, Arterburn D. Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study. Epidemiology 2022; 33:747-755. [PMID: 35609209 PMCID: PMC9378543 DOI: 10.1097/ede.0000000000001505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight. METHODS Kaiser Permanente Washington electronic health records were used to identify 21,502 members aged 18-64 who moved within King County, WA between 2005 and 2017. We linked body weight measures to environment measures, including population, residential, and street intersection densities (800 m and 1,600 m Euclidian buffers) and access to supermarkets and fast foods (1,600 m and 5,000 m network distances). We used linear mixed models to estimate associations between postmove changes in environment and changes in body weight. RESULTS In general, moving from high-density to moderate- or low-density neighborhoods was associated with greater weight gain postmove. For example, those moving from high to low residential density neighborhoods (within 1,600 m) gained an average of 4.5 (95% confidence interval [CI] = 3.0, 5.9) lbs 3 years after moving, whereas those moving from low to high-density neighborhoods gained an average of 1.3 (95% CI = -0.2, 2.9) lbs. Also, those moving from neighborhoods without fast-food access (within 1600m) to other neighborhoods without fast-food access gained less weight (average 1.6 lbs [95% CI = 0.9, 2.4]) than those moving from and to neighborhoods with fast-food access (average 2.8 lbs [95% CI = 2.5, 3.2]). CONCLUSIONS Moving to higher-density neighborhoods may be associated with reductions in adult weight gain.
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Affiliation(s)
- Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Adam Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Jennifer F. Bobb
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
- Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, 98195-3410, USA
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - James H. Buszkiewicz
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Dori E. Rosenberg
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Flavia Kapos
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
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Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III. SSM Popul Health 2022; 19:101158. [PMID: 35813186 PMCID: PMC9260622 DOI: 10.1016/j.ssmph.2022.101158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/24/2022] [Accepted: 06/25/2022] [Indexed: 11/25/2022] Open
Abstract
Objective To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI). Methods The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change. Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed. Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change. There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.
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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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Winkler MR, Mui Y, Hunt SL, Laska MN, Gittelsohn J, Tracy M. Applications of Complex Systems Models to Improve Retail Food Environments for Population Health: A Scoping Review. Adv Nutr 2022; 13:1028-1043. [PMID: 34999752 PMCID: PMC9340968 DOI: 10.1093/advances/nmab138] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/10/2021] [Accepted: 11/17/2021] [Indexed: 12/11/2022] Open
Abstract
Retail food environments (RFEs) are complex systems with important implications for population health. Studying the complexity within RFEs comes with challenges. Complex systems models are computational tools that can help. We performed a systematic scoping review of studies that used complex systems models to study RFEs for population health. We examined the purpose for using the model, RFE features represented, extent to which the complex systems approach was maximized, and quality and transparency of methods employed. The PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines were followed. Studies using agent-based modeling, system dynamics, discrete event simulations, networks, hybrid, or microsimulation models were identified from 7 multidisciplinary databases. Fifty-six studies met the inclusion criteria, including 23 microsimulation, 13 agent-based, 10 hybrid, 4 system dynamics, 4 network, and 2 discrete event simulation models. Most studies (n = 45) used models for experimental purposes and evaluated effects of simulated RFE policies and interventions. RFE characteristics simulated in models were diverse, and included the features (e.g., prices) customers encounter when shopping (n = 55), the settings (e.g., restaurants, supermarkets) where customers purchase food and beverages (n = 30), and the actors (e.g., store managers, suppliers) who make decisions that influence RFEs (n = 25). All models incorporated characteristics of complexity (e.g., feedbacks, conceptual representation of multiple levels), but these were captured to varying degrees across model types. The quality of methods was adequate overall; however, few studies engaged stakeholders (n = 10) or provided sufficient transparency to verify the model (n = 12). Complex systems models are increasingly utilized to study RFEs and their contributions to public health. Opportunities to advance the use of these approaches remain, and areas to improve future research are discussed. This comprehensive review provides the first marker of the utility of leveraging these approaches to address RFEs for population health.
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Affiliation(s)
- Megan R Winkler
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Yeeli Mui
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Shanda L Hunt
- Health Sciences Library, University of Minnesota, Minneapolis, MN, USA
| | - Melissa N Laska
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Joel Gittelsohn
- Center for Human Nutrition, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Melissa Tracy
- Department of Epidemiology and Biostatistics, University at Albany School of Public Health, Rensselaer, NY, USA
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Medina C, Piña-Pozas M, Aburto TC, Chavira J, López U, Moreno M, Olvera AG, Gonzalez C, Huang TTK, Barquera S. Systematic literature review of instruments that measure the healthfulness of food and beverages sold in informal food outlets. Int J Behav Nutr Phys Act 2022; 19:89. [PMID: 35842649 PMCID: PMC9288710 DOI: 10.1186/s12966-022-01320-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 06/20/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Informal food outlets, defined as vendors who rarely have access to water and toilets, much less shelter and electricity, are a common component of the food environment, particularly in many non-Western countries. The purpose of this study was to review available instruments that measure the quality and particularly the healthfulness of food and beverages sold within informal food outlets. METHODS PubMed, LILACS, Web of Science, and Scopus databases were used. Articles were included if they reported instruments that measured the availability or type of healthy and unhealthy foods and beverages by informal food outlets, were written in English or Spanish, and published between January 1, 2010, and July 31, 2020. Two trained researchers reviewed the title, abstract and full text of selected articles; discrepancies were solved by two independent researchers. In addition, the list of references for selected articles was reviewed for any additional articles of relevance. The quality of published articles and documents was evaluated using JBI Critical appraisal checklist for analytical cross-sectional studies. RESULTS We identified 1078 articles of which 14 were included after applying the selection criteria. Three additional articles were considered after reviewing the references from the selected articles. From the final 17 articles, 13 measurement tools were identified. Most of the instruments were used in low- and middle-income countries (LMIC). Products were classified as healthy/unhealthy or produce/non-produce or processed/unprocessed based on availability and type. Six studies reported psychometric tests, whereas one was tested within the informal food sector. CONCLUSIONS Few instruments can measure the healthfulness of food and beverages sold in informal food outlets, of which the most valid and reliable have been used to measure formal food outlets as well. Therefore, it is necessary to develop an instrument that manages to measure, specifically, the elements available within an informal one. These actions are extremely important to better understand the food environment that is a central contributor to poor diets that are increasingly associated with the obesity and Non-communicable disease (NCD) pandemic.
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Affiliation(s)
- Catalina Medina
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Maricela Piña-Pozas
- Center for Information for Public Health Decisions, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Tania C Aburto
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Julissa Chavira
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Uzzi López
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Mildred Moreno
- School of Engineering and Architecture (ESIA), National Polytechnic Institute (IPN), México, Avenida Fuentes de los Leones 28, Lomas de Tecamachalco. CP. 53955. Tecamachalco, Naucalpan, Mexico
| | - Armando G Olvera
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Citlali Gonzalez
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico
| | - Terry T-K Huang
- Center for Systems and Community Design and NYU-CUNY Prevention Research Center, Graduate School of Public Health and Health Policy, City University of New York, 55W. 125 Street, Room 803, New York, NY, 10027, USA
| | - Simón Barquera
- Center for Health and Nutrition Research, National Institute of Public Health, Mexico. Avenida Universidad 655, Santa María Ahuacatitlán. CP. 06210, Cuernavaca, Morelos, Mexico.
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On-campus food environment, purchase behaviours, preferences and opinions in a Norwegian university community. Public Health Nutr 2022; 25:1619-1630. [PMID: 34176546 PMCID: PMC9991706 DOI: 10.1017/s136898002100272x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
OBJECTIVE To assess the food environment at OsloMet, through the nutritional profile and processing level of available commercial foods and drinks, as well as to determine food-purchasing behaviours, preferences and opinions on the food environment, in order to identify whether interventions on campus need to be conducted. DESIGN Cross-sectional descriptive study. SETTING Pilestredet and Kjeller campus of OsloMet (Norway). PARTICIPANTS To analyse the nutritional profile of products offered at all food outlets (seven canteens, three coffee shops and two vending machines) at the main campuses three criteria were applied: those proposed by the Spanish Agency for Food Safety and Nutrition, the UK nutrient profiling model and those of the Food and Drink Industry Professional Practices Committee Norway. In addition, products were classified by processing level, using the NOVA system. Food purchasing, food choice behaviours and opinions were analysed through a survey online, in which 129 subjects participated. RESULTS With regard to the first of the objectives, the combination of the above-mentioned criteria showed that 39·8 % of the products were 'unhealthy' and 85·9 % were 'ultra-processed'. Regarding the second objective, the most important determinants of food choice were taste, convenience, and cost and nutrition/health value. The most common improvements suggested were lowering the cost, improving the allergen information on labelling and increasing the variety of fresh and healthy foods. CONCLUSIONS A high proportion of the products offered were considered 'unhealthy' and highly processed. Interventions that improve food prices, availability and information on labelling would be well-received in this community.
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Hobbs M, Milfont TL, Marek L, Yogeeswaran K, Sibley CG. The environment an adult resides within is associated with their health behaviours, and their mental and physical health outcomes: a nationwide geospatial study. Soc Sci Med 2022; 301:114801. [PMID: 35366459 DOI: 10.1016/j.socscimed.2022.114801] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 01/24/2022] [Accepted: 02/07/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND The determinants of health behaviours and health outcomes are multifaceted and the surrounding environment is increasingly considered as an important influence. This pre-registered study investigated the associations between the geospatial environment people live within and their health behaviours as well as their mental and physical health outcomes. METHOD We used the newly developed Healthy Location Index (HLI) to identify health-promoting and health-constraining environmental features where people live. We then used Time 10 (2018) data from the New Zealand Attitudes and Values Survey (NZAVS; N = 47,951), a national probability sample of New Zealand adults, to gauge mental health outcomes including depression, anxiety and psychological distress, physical health outcomes including BMI and type II diabetes, and health behaviours such as tobacco smoking and vaping. Linear and logistic multilevel mixed effect regression models with random intercepts of individuals nested within geographical areas (meshblocks) were employed. RESULTS The presence of health-constraining environmental features were adversely associated with self-reported mental health outcomes of depression, anxiety and psychological distress, physical health outcomes of BMI and type II diabetes, and negative health behaviours of tobacco smoking and vaping. By contrast, health-promoting environmental features were uniquely associated only with physical health outcomes of BMI and type II diabetes. CONCLUSION The current study advances research on environmental determinants of health behaviours by demonstrating that close proximity to health-constraining environmental features is related to a number of self-reported physical and mental health outcomes or behaviours. We provide some evidence to support the notion that preventive population-health interventions should be sought.
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Affiliation(s)
- M Hobbs
- Faculty of Health, University, Christchurch, Canterbury, New Zealand; GeoHealth Laboratory, Geospatial Research Institute, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - T L Milfont
- School of Psychology, University of Waikato, Tauranga, New Zealand
| | - L Marek
- GeoHealth Laboratory, Geospatial Research Institute, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - K Yogeeswaran
- School of Psychology, Speech and Hearing, College of Science, University of Canterbury, Christchurch, New Zealand
| | - C G Sibley
- School of Psychology, University of Auckland, Auckland, New Zealand
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Atanasova P, Kusuma D, Pineda E, Frost G, Sassi F, Miraldo M. The impact of the consumer and neighbourhood food environment on dietary intake and obesity-related outcomes: A systematic review of causal impact studies. Soc Sci Med 2022; 299:114879. [PMID: 35290815 PMCID: PMC8987734 DOI: 10.1016/j.socscimed.2022.114879] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 02/19/2022] [Accepted: 03/04/2022] [Indexed: 12/16/2022]
Abstract
BACKGROUND The food environment has been found to impact population dietary behaviour. Our study aimed to systematically review the impact of different elements of the food environment on dietary intake and obesity. METHODS We searched MEDLINE, Embase, PsychInfo, EconLit databases to identify literature that assessed the relationship between the built food environments (intervention) and dietary intake and obesity (outcomes), published between database inception to March 26, 2020. All human studies were eligible except for those on clinical sub-groups. Only studies with causal inference methods were assessed. Studies focusing on the food environment inside homes, workplaces and schools were excluded. A risk of bias assessment was conducted using the CASP appraisal checklist. Findings were summarized using a narrative synthesis approach. FINDINGS 58 papers were included, 55 of which were conducted in high-income countries. 70% of papers focused on the consumer food environments and found that in-kind/financial incentives, healthy food saliency, and health primes, but not calorie menu labelling significantly improved dietary quality of children and adults, while BMI results were null. 30% of the papers focused on the neighbourhood food environments and found that the number of and distance to unhealthy food outlets increased the likelihood of fast-food consumption and higher BMI for children of any SES; among adults only selected groups were impacted - females, black, and Hispanics living in low and medium density areas. The availability and distance to healthy food outlets significantly improved children's dietary intake and BMI but null results were found for adults. INTERPRETATION Evidence suggests certain elements of the consumer and neighbourhood food environments could improve populations dietary intake, while effect on BMI was observed among children and selected adult populations. Underprivileged groups are most likely to experience and impact on BMI. Future research should investigate whether findings translate in other countries.
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Affiliation(s)
- Petya Atanasova
- Centre for Health Economics & Policy Innovation, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK.
| | - Dian Kusuma
- Centre for Health Economics & Policy Innovation, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK
| | - Elisa Pineda
- Centre for Health Economics & Policy Innovation, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK; School of Public Health, Imperial College London, Medical School Building, St Mary's Hospital, Norfolk Place, London, W2 1PG, UK
| | - Gary Frost
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Faculty Building South Kensington Campus, London, SW7 2AZ, UK
| | - Franco Sassi
- Centre for Health Economics & Policy Innovation, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK; Department of Economics and Public Policy, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK
| | - Marisa Miraldo
- Centre for Health Economics & Policy Innovation, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK; Department of Economics and Public Policy, Imperial College Business School, South Kensington Campus, Exhibition Rd, London, SW7 2AZ, UK
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Titis E, Procter R, Walasek L. Assessing physical access to healthy food across United Kingdom: A systematic review of measures and findings. Obes Sci Pract 2022; 8:233-246. [PMID: 35388348 PMCID: PMC8976549 DOI: 10.1002/osp4.563] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/16/2021] [Accepted: 08/24/2021] [Indexed: 11/09/2022] Open
Abstract
Background Existing research suggests that physical access to food can affect diet quality and thus obesity rates. When defining retail food environment (RFE) quantitatively, there is a little agreement on how to measure "lack of healthy food" and what parameters to use, resulting in a heterogeneity of study designs and outcome measures. In turn, this leads to a conflicting evidence base being one of the many barriers to using evidence in policy-making. Aims This systematic review aimed to identify and describe methods used to assess food accessibility in the United Kingdom (UK) to overcome heterogeneity by providing a classification of measures. Materials & Methods The literature search included electronic and manual searches of peer-reviewed literature and was restricted to studies published in English between January 2010 and March 2021. A total of 9365 articles were assessed for eligibility, of which 44 articles were included in the review. All included studies were analysed with regards to their main characteristics (e.g., associations between variables of interest, setting, sample, design, etc.) and definition of RFE and its metrics. When defining these metrics, the present review distinguishes between a point of origin (centroid, address) from which distance was calculated, summary statistic of accessibility (proximity, buffer, Kernel), and definition of distance (Euclidean, network distance). Trends, gaps and limitations are identified and recommendations made for food accessibility research in UK. Results Multiple theoretical and methodological constructs are currently used, mostly quantifying distance by means of Euclidean and ring-buffer distance, using both proximity- and density-based approaches, and ranging from absolute to relative measures. The association between RFE and diet and health in rural areas, as well as a spatiotemporal domain of food access, remains largely unaccounted. Discussion Evidence suggests that the duration of exposure may bear a greater importance than the level of exposure and that density-based measures may better capture RFE when compared with proximity-based measures, however, using more complex measures not necessarily produce better results. To move the field forward, studies have called for a greater focus on causality, individual access and the use of various measures, neighbourhood definitions and potential confounders to capture different aspects and dimensions of the RFE, which requires using univariate measures of accessibility and considering the overall context in terms of varying types of neighbourhoods. Conclusion In order to render ongoing heterogeneity in measuring RFE, researchers should prioritise measures that may provide a more accurate and realistic account of people's lives and follow an intuitive approach based on convergence of results until consensus could be reached on using some useful standards.
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Affiliation(s)
- Elzbieta Titis
- Department of Computer ScienceWarwick Institute for the Science of CitiesUniversity of WarwickCoventryUK
| | - Rob Procter
- Department of Computer ScienceUniversity of WarwickCoventryUK
- Alan Turing InstituteLondonUK
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Chumpunuch P, Jaraeprapal U. The social determinants of health influencing obesity for the aged in the Pakpoon community context: A qualitative study. Int J Nurs Sci 2022; 9:211-221. [PMID: 35509696 PMCID: PMC9052257 DOI: 10.1016/j.ijnss.2022.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 02/18/2022] [Accepted: 02/25/2022] [Indexed: 10/26/2022] Open
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Salvo D, Lemoine P, Janda KM, Ranjit N, Nielsen A, van den Berg A. Exploring the Impact of Policies to Improve Geographic and Economic Access to Vegetables among Low-Income, Predominantly Latino Urban Residents: An Agent-Based Model. Nutrients 2022; 14:646. [PMID: 35277005 PMCID: PMC8839639 DOI: 10.3390/nu14030646] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 01/19/2022] [Accepted: 01/26/2022] [Indexed: 02/05/2023] Open
Abstract
Modifying the food environment of cities is a promising strategy for improving dietary behaviors, but using traditional empirical methods to test the effectiveness of these strategies remains challenging. We developed an agent-based model to simulate the food environment of Austin, Texas, USA, and to test the impact of different food access policies on vegetable consumption among low-income, predominantly Latino residents. The model was developed and calibrated using empirical data from the FRESH-Austin Study, a natural experiment. We simulated five policy scenarios: (1) business as usual; (2)−(4) expanding geographic and/or economic healthy food access via the Fresh for Less program (i.e., through farm stands, mobile markets, and healthy corner stores); and (5) expanding economic access to vegetables in supermarkets and small grocers. The model predicted that increasing geographic and/or economic access to healthy corner stores will not meaningfully improve vegetable intake, whilst implementing high discounts (>85%) on the cost of vegetables, or jointly increasing geographic and economic access to mobile markets or farm stands, will increase vegetable intake among low-income groups. Implementing discounts at supermarkets and small grocers is also predicted to be an effective policy for increasing vegetable consumption. This work highlights the utility of agent-based modeling for informing food access policies.
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Affiliation(s)
- Deborah Salvo
- Prevention Research Center, Brown School, Washington University in Saint Louis, Saint Louis, MO 63130, USA
| | - Pablo Lemoine
- Centro Nacional de Consultoría, Bogotá 110221, Colombia;
| | - Kathryn M. Janda
- UTHealth School of Public Health, Austin, TX 78701, USA; (K.M.J.); (N.R.); (A.N.); (A.v.d.B.)
| | - Nalini Ranjit
- UTHealth School of Public Health, Austin, TX 78701, USA; (K.M.J.); (N.R.); (A.N.); (A.v.d.B.)
| | - Aida Nielsen
- UTHealth School of Public Health, Austin, TX 78701, USA; (K.M.J.); (N.R.); (A.N.); (A.v.d.B.)
| | - Alexandra van den Berg
- UTHealth School of Public Health, Austin, TX 78701, USA; (K.M.J.); (N.R.); (A.N.); (A.v.d.B.)
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Kegler MC, Prakash R, Hermstad A, Anderson K, Haardörfer R, Raskind IG. Food Acquisition Practices, Body Mass Index, and Dietary Outcomes by Level of Rurality. J Rural Health 2022; 38:228-239. [PMID: 33200835 PMCID: PMC8126566 DOI: 10.1111/jrh.12536] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
PURPOSE Rural residents are more likely to be obese than urban residents. Research on how people navigate their local food environments through food acquisition behaviors, such as food shopping and restaurant use, in different types of communities may help to create a deeper understanding of the multilevel determinants of obesity. METHODS Data are from a national sample of US adults ages 18-75. Respondents were recruited from an online survey panel in 2015 and asked about food shopping, restaurant use, diet and weight (N = 3,883). Comparisons were made by level of rurality as assessed by Rural-Urban Continuum Codes (RUCC) and self-reported rurality of the area around their home. FINDINGS Food acquisition behaviors varied minimally by RUCC-defined level of rurality, with the exceptions of type and distance to primary food store. Rural residents drove further and were more likely to shop at small grocery stores and supercenters than were residents of semiurban or urban counties. In contrast, all of the food acquisition behaviors varied by self-reported rurality of residential areas. Respondents living in rural areas shopped for groceries less frequently, drove further, more commonly shopped at small grocery stores and supercenters, and used restaurants less frequently. In multivariable analyses, rural, small town, and suburban areas were each significantly associated with BMI and fruit and vegetable intake, but not percent energy from fat. CONCLUSION Findings show that self-reported rurality of residential area is associated with food acquisition behaviors and may partly explain rural-urban differences in obesity and diet quality.
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Affiliation(s)
- Michelle C. Kegler
- Emory Prevention Research Center, Department of Behavioral Sciences and Health Education, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Radhika Prakash
- Emory Prevention Research Center, Department of Behavioral Sciences and Health Education, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - April Hermstad
- Emory Prevention Research Center, Department of Behavioral Sciences and Health Education, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Kate Anderson
- Emory Prevention Research Center, Department of Behavioral Sciences and Health Education, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Regine Haardörfer
- Emory Prevention Research Center, Department of Behavioral Sciences and Health Education, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Ilana G. Raskind
- Stanford Prevention Research Center, Stanford University School of Medicine, Palo Alto, California
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Bishop TR, von Hinke S, Hollingsworth B, Lake AA, Brown H, Burgoine T. Automatic classification of takeaway food outlet cuisine type using machine (deep) learning. MACHINE LEARNING WITH APPLICATIONS 2021; 6:None. [PMID: 34977839 PMCID: PMC8700226 DOI: 10.1016/j.mlwa.2021.100106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 07/05/2021] [Accepted: 07/05/2021] [Indexed: 10/25/2022] Open
Abstract
BACKGROUND AND PURPOSE Researchers have not disaggregated neighbourhood exposure to takeaway ('fast-') food outlets by cuisine type sold, which would otherwise permit examination of differential impacts on diet, obesity and related disease. This is partly due to the substantial resource challenge of manual classification of unclassified takeaway outlets at scale. We describe the development of a new model to automatically classify takeaway food outlets, by 10 major cuisine types, based on business name alone. MATERIAL AND METHODS We used machine (deep) learning, and specifically a Long Short Term Memory variant of a Recurrent Neural Network, to develop a predictive model trained on labelled outlets (n = 14,145), from an online takeaway food ordering platform. We validated the accuracy of predictions on unseen labelled outlets (n = 4,000) from the same source. RESULTS Although accuracy of prediction varied by cuisine type, overall the model (or 'classifier') made a correct prediction approximately three out of four times. We demonstrated the potential of the classifier to public health researchers and for surveillance to support decision-making, through using it to characterise nearly 55,000 takeaway food outlets in England by cuisine type, for the first time. CONCLUSIONS Although imperfect, we successfully developed a model to classify takeaway food outlets, by 10 major cuisine types, from business name alone, using innovative data science methods. We have made the model available for use elsewhere by others, including in other contexts and to characterise other types of food outlets, and for further development.
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Affiliation(s)
- Tom R.P. Bishop
- 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
| | - Stephanie von Hinke
- School of Economics, University of Bristol, Bristol BS8 1TU, UK
- Erasmus School of Economics, Erasmus University Rotterdam, Netherlands
| | | | - Amelia A. Lake
- School of Health and Life Sciences, Centre for Public Health Research, Teesside University, Middlesbrough TS1 3BX, UK
- Fuse – Centre for Translational Research in Public Health, Newcastle NE1 4LP, UK
| | - Heather Brown
- Fuse – Centre for Translational Research in Public Health, Newcastle NE1 4LP, UK
- Population Health Sciences Institute, Newcastle University, NE1 4LP, UK
| | - 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
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Green MA, Hobbs M, Ding D, Widener M, Murray J, Reece L, Singleton A. The Association between Fast Food Outlets and Overweight in Adolescents Is Confounded by Neighbourhood Deprivation: A Longitudinal Analysis of the Millennium Cohort Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182413212. [PMID: 34948820 PMCID: PMC8703340 DOI: 10.3390/ijerph182413212] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/02/2021] [Accepted: 12/09/2021] [Indexed: 11/28/2022]
Abstract
The aim of our study is to utilise longitudinal data to explore if the association between the retail fast food environment and overweight in adolescents is confounded by neighbourhood deprivation. Data from the Millennium Cohort Study for England were obtained for waves 5 (ages 11/12; 2011/12; n = 13,469) and 6 (ages 14/15; 2014/15; n = 11,884). Our outcome variable was overweight/obesity defined using age and sex-specific International Obesity Task Force cut points. Individuals were linked, based on their residential location, to data on the density of fast food outlets and neighbourhood deprivation. Structural Equation Models were used to model associations and test for observed confounding. A small positive association was initially detected between fast food outlets and overweight (e.g., at age 11/12, Odds Ratio (OR) = 1.0006, 95% Confidence Intervals (CI) = 1.0002–1.0009). Following adjusting for the confounding role of neighbourhood deprivation, this association was non-significant. Individuals who resided in the most deprived neighbourhoods had higher odds of overweight than individuals in the least deprived neighbourhoods (e.g., at age 11/12 OR = 1.95, 95% CIs = 1.64–2.32). Neighbourhood deprivation was also positively associated to the density of fast food outlets (at age 11/12 Incidence Rate Ratio = 3.03, 95% CIs = 2.80–3.28).
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Affiliation(s)
- Mark A. Green
- Geographic Data Science Lab, Department of Geography & Planning, University of Liverpool, Liverpool L69 7ZT, UK; (J.M.); (A.S.)
- Correspondence:
| | - Matthew Hobbs
- GeoHealth Laboratory, University of Canterbury, Christchurch 8140, New Zealand;
- School of Health Sciences, University of Canterbury, Christchurch 8140, New Zealand
| | - Ding Ding
- School of Public Health, University of Sydney, Sydney 2006, Australia; (D.D.); (L.R.)
| | - Michael Widener
- Department of Geography & Planning, University of Toronto, Toronto, ON M5S 3G3, Canada;
| | - John Murray
- Geographic Data Science Lab, Department of Geography & Planning, University of Liverpool, Liverpool L69 7ZT, UK; (J.M.); (A.S.)
| | - Lindsey Reece
- School of Public Health, University of Sydney, Sydney 2006, Australia; (D.D.); (L.R.)
| | - Alex Singleton
- Geographic Data Science Lab, Department of Geography & Planning, University of Liverpool, Liverpool L69 7ZT, UK; (J.M.); (A.S.)
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Jenneson VL, Pontin F, Greenwood DC, Clarke GP, Morris MA. A systematic review of supermarket automated electronic sales data for population dietary surveillance. Nutr Rev 2021; 80:1711-1722. [PMID: 34757399 PMCID: PMC9086796 DOI: 10.1093/nutrit/nuab089] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Context Most dietary assessment methods are limited by self-report biases, how long they take for participants to complete, and cost of time for dietitians to extract content. Electronically recorded, supermarket-obtained transactions are an objective measure of food purchases, with reduced bias and improved timeliness and scale. Objective The use, breadth, context, and utility of electronic purchase records for dietary research is assessed and discussed in this systematic review. Data sources Four electronic databases (MEDLINE, EMBASE, PsycINFO, Global Health) were searched. Included studies used electronically recorded supermarket transactions to investigate the diet of healthy, free-living adults. Data extraction Searches identified 3422 articles, of which 145 full texts were retrieved and 72 met inclusion criteria. Study quality was assessed using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Data analysis Purchase records were used in observational studies, policy evaluations, and experimental designs. Nutrition outcomes included dietary patterns, nutrients, and food category sales. Transactions were linked to nutrient data from retailers, commercial data sources, and national food composition databases. Conclusion Electronic sales data have the potential to transform dietary assessment and worldwide understanding of dietary behavior. Validation studies are warranted to understand limits to agreement and extrapolation to individual-level diets. Systematic Review Registration PROSPERO registration no. CRD42018103470
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Affiliation(s)
- Victoria L Jenneson
- V.L. Jenneson, F. Pontin, D.C. Greenwood, and M.A. Morris are with the Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom. V.L. Jenneson, F. Pontin, and G.P. Clarke are with the School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom. D.C. Greenwood and M.A. Morris are with the School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Francesca Pontin
- V.L. Jenneson, F. Pontin, D.C. Greenwood, and M.A. Morris are with the Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom. V.L. Jenneson, F. Pontin, and G.P. Clarke are with the School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom. D.C. Greenwood and M.A. Morris are with the School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Darren C Greenwood
- V.L. Jenneson, F. Pontin, D.C. Greenwood, and M.A. Morris are with the Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom. V.L. Jenneson, F. Pontin, and G.P. Clarke are with the School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom. D.C. Greenwood and M.A. Morris are with the School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Graham P Clarke
- V.L. Jenneson, F. Pontin, D.C. Greenwood, and M.A. Morris are with the Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom. V.L. Jenneson, F. Pontin, and G.P. Clarke are with the School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom. D.C. Greenwood and M.A. Morris are with the School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Michelle A Morris
- V.L. Jenneson, F. Pontin, D.C. Greenwood, and M.A. Morris are with the Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom. V.L. Jenneson, F. Pontin, and G.P. Clarke are with the School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom. D.C. Greenwood and M.A. Morris are with the School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
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Keeble M, Adams J, Vanderlee L, Hammond D, Burgoine T. Associations between online food outlet access and online food delivery service use amongst adults in the UK: a cross-sectional analysis of linked data. BMC Public Health 2021; 21:1968. [PMID: 34719382 PMCID: PMC8557109 DOI: 10.1186/s12889-021-11953-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 10/06/2021] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Online food delivery services facilitate 'online' access to food outlets that typically sell lenergy-dense nutrient-poor food. Greater online food outlet access might be related to the use of this purchasing format and living with excess bodyweight, however, this is not known. We aimed to investigate the association between aspects of online food outlet access and online food delivery service use, and differences according to customer sociodemographic characteristics, as well as the association between the number of food outlets accessible online and bodyweight. METHODS In 2019, we used an automated data collection method to collect data on all food outlets in the UK registered with the leading online food delivery service Just Eat (n = 33,204). We linked this with contemporaneous data on food purchasing, bodyweight, and sociodemographic information collected through the International Food Policy Study (analytic sample n = 3067). We used adjusted binomial logistic, linear, and multinomial logistic regression models to examine associations. RESULTS Adults in the UK had online access to a median of 85 food outlets (IQR: 34-181) and 85 unique types of cuisine (IQR: 64-108), and 15.1% reported online food delivery service use in the previous week. Those with the greatest number of accessible food outlets (quarter four, 182-879) had 71% greater odds of online food delivery service use (OR: 1.71; 95% CI: 1.09, 2.68) compared to those with the least (quarter one, 0-34). This pattern was evident amongst adults with a university degree (OR: 2.11; 95% CI: 1.15, 3.85), adults aged between 18 and 29 years (OR: 3.27, 95% CI: 1.59, 6.72), those living with children (OR: 1.94; 95% CI: 1.01; 3.75), and females at each level of increased exposure. We found no association between the number of unique types of cuisine accessible online and online food delivery service use, or between the number of food outlets accessible online and bodyweight. CONCLUSIONS The number of food outlets accessible online is positively associated with online food delivery service use. Adults with the highest education, younger adults, those living with children, and females, were particularly susceptible to the greatest online food outlet access. Further research is required to investigate the possible health implications of online food delivery service use.
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Affiliation(s)
- Matthew Keeble
- grid.5335.00000000121885934MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ UK
| | - Jean Adams
- grid.5335.00000000121885934MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ UK
| | - Lana Vanderlee
- grid.23856.3a0000 0004 1936 8390École de Nutrition, Université Laval, Pavillon des Services, bureau 2729-E, 2440 boul. Hochelaga, Quebec City, QC G1V 0A6 Canada
| | - David Hammond
- grid.46078.3d0000 0000 8644 1405School of Public Health and Health Systems, Faculty of Health, University of Waterloo, Waterloo, ON N2L 3G1 Canada
| | - Thomas Burgoine
- grid.5335.00000000121885934MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ UK
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