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Costa GMA, Vidal NAC, Almeida NB, Aragão LS, Menezes RCE, Longo-Silva G, Silveira JAC. The food retail environment around schools in a low-income Brazilian city: a street audit evaluation. CIENCIA & SAUDE COLETIVA 2025; 30:e08472023. [PMID: 40298713 DOI: 10.1590/1413-81232025304.08472023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 02/21/2024] [Indexed: 04/30/2025] Open
Abstract
This cross-sectional study evaluated the retail food environment (FE) around early childhood education centers (ECEC) in Rio Largo/AL, Brazil. Food retail outlets (FRO) were identified through a city street survey and audited using the Brazilian version of the Nutrition Environment Measurement Survey for Stores (NEMS-S). The Department of Education provided the ECEC's addresses, which were validated and geocoded (n=21). Schools' surroundings were defined by 400- and 800-meter buffers. The FE was analyzed using the healthy food availability index (HFAI), average distance between FRO and ECEC, and distribution and density of FRO according to the predominant type of food marketed (healthy, mixed, and unhealthy). Respectively, 332 (57.7%) and 505 (87.8%) FRO were identified in the 400- and 800-meter buffers. On average, 23 (400 m) and 54 (800 m) FRO were around schools, where ~60% were unhealthy (clustered throughout the city). The HFAI was very low for both buffers (400m: -1 points [IQR -6; 10]; 800m: -2 points [IQR -6; 10]). In conclusion, the city does not offer a supportive community food environment for children to develop and maintain healthy eating patterns.
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Affiliation(s)
- Gabriel M A Costa
- Programa de Pós-Graduação em Nutrição, Universidade Federal de Alagoas. Maceió AL Brasil
| | - Nicole A C Vidal
- Programa de Pós-Graduação em Nutrição, Universidade Federal de Alagoas. Maceió AL Brasil
| | - Nykholle B Almeida
- Programa de Pós-Graduação em Nutrição, Universidade Federal de Alagoas. Maceió AL Brasil
| | - Luan S Aragão
- Programa de Pós-Graduação em Nutrição, Universidade Federal de Alagoas. Maceió AL Brasil
| | - Rísia C E Menezes
- Programa de Pós-Graduação em Nutrição, Universidade Federal de Alagoas. Maceió AL Brasil
| | - Giovana Longo-Silva
- Programa de Pós-Graduação em Nutrição, Universidade Federal de Alagoas. Maceió AL Brasil
| | - Jonas A C Silveira
- Departamento de Nutrição, Universidade Federal do Paraná. Av. Prefeito Lothário Meissner 632, Jardim Botânico. 80210-170 Curitiba PR Brasil.
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Bernsdorf KA, Bøggild H, Aadahl M, Toft U. Food outlet availability differs according to area socioeconomic status in Denmark. BMC Public Health 2025; 25:843. [PMID: 40033275 DOI: 10.1186/s12889-025-21909-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: 05/29/2024] [Accepted: 02/11/2025] [Indexed: 03/05/2025] Open
Abstract
BACKGROUND Disparities in access to specific foods may contribute to inequalities in diet-related diseases seen at a global and National level. METHODS Based on aggregated population data on income, education, and employment, area-level socioeconomic differences in food outlet availability were analyzed for 53,368 study participants residing across parishes in the Capital Region of Denmark. Validated data on fast-food outlets, convenience stores, supermarkets, and restaurants were used. Information on individual characteristics, home address and corresponding parishes were linked to the participants through the Danish Civil Registration System. Three multilevel hurdle models were applied for each food outlet type to analyze food outlet density (count/km²) within an 800-meter network buffer around participants' homes across four levels of parish socioeconomic status (SES). Model 1 provided a basic examination of the association between density and area SES. Model 2 adjusted for individual characteristics while Model 3 further included urbanity at the area level. The structure of the chosen hurdle models included was Part (1) a logistic multilevel regression modelling the probability of food outlet presence by using the entire dataset and, Part (2) a standard linear multilevel regression modelling the 10 base logarithmic transformation of only positive food outlet densities with a lognormal distribution. RESULTS No statistically significant spatial patterning of food outlets across area SES was found in Model 1 and 2, however positive and strong significant odds were seen in part 1 of Model 3 for supermarkets, convenience stores and fast-food outlets. Thus, residents in more disadvantaged SES areas had higher odds of having a supermarket, convenience store, or fast-food outlet near their homes compared to those living in the most advantaged areas. No differences were seen in the density across area SES. CONCLUSION Area SES influenced the presence of supermarkets, convenience stores, and fast-food outlets, but not the density of these establishments.
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Affiliation(s)
- Kamille Almer Bernsdorf
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Frederiksberg, Denmark.
- Steno Diabetes Center Copenhagen, Department for Prevention, Health Promotion and Community Care, Herlev, 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, Frederiksberg, Denmark
- Department of Public Health, Section of Social Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla Toft
- 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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Silva-Neto LGR, Borges CA, Bueno NB, Dos Santos TLF, de Menezes RCE, de Menezes Toledo Florêncio TM. Anaemia, overweight and abdominal obesity in mothers and children are associated with the food environment in socially vulnerable areas of a northeastern Brazilian capital. NUTR BULL 2025; 50:91-105. [PMID: 39737580 DOI: 10.1111/nbu.12728] [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: 01/24/2024] [Revised: 11/26/2024] [Accepted: 11/26/2024] [Indexed: 01/01/2025]
Abstract
This study aimed to assess the association between community and consumer food environment (FE) measures and anaemia, overweight and abdominal obesity in mother-child dyads living in situations of social vulnerability. A cross-sectional study was carried out in 40 favelas in a capital city in the northeast of Brazil. The sample consisted of 1882 women and 665 children aged under 5 years. The community FE was assessed using a scale of perception of the availability of healthy food in the neighbourhood. Consumer FE was assessed by auditing 624 retail food stores using the AUDITNOVA instrument. This investigated various aspects of the food environment and evaluated the availability of 18 ultra-processed foods (UPF) most consumed by the Brazilian population available in these stores. The presence of overweight was assessed by measuring the weight and height of the mother and the child, and abdominal obesity was assessed by measuring the mother's waist circumference. The presence of anaemia in the mother and the child was assessed by measuring haemoglobin. Adjusted multilevel regression models were used to verify associations between the FE and malnutrition in mother-child dyads. Low perception of community FE was associated with higher risk of women being overweight (OR: 1.35; 95% CI: 1.05-1.73) and abdominally obese (OR: 1.38; 95% CI: 1.04-1.84); low health scores in food shops were associated with higher risk of abdominal obesity (OR: 1.35; 95% CI: 1.01-1.79) and anaemia (OR: 1.16; 95% CI: 1.02-1.98) in women and overweight in children (OR: 1.69; 95% CI: 1.05-2.73); and the high availability of UPF in retail shops was associated with increased odds of overweight (OR: 2.64; 95% CI: 1.61-4.33) and anaemia (OR: 2.11; 95% CI: 1.38-3.02) in children by 164% and 111%, respectively. It was observed that less healthy food environments are associated with greater chances of anaemia, overweight and abdominal obesity in mothers and children under 5 years in situations of social vulnerability in Brazil.
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Affiliation(s)
| | - Camila Aparecida Borges
- Núcleo de Pesquisas Epidemiológicas em Nutrição e Saúde, Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, Brazil
| | - Nassib Bezerra Bueno
- Programa de Pós-Graduação em Nutrição, Faculdade de Nutrição, Universidade Federal de Alagoas, Maceió, Brazil
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4
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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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5
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Needham C, Strugnell C, Orellana L, Allender S, Sacks G, Blake MR, Horta A. Using spatial analysis to examine inequalities and temporal trends in food retail accessibility. Public Health Nutr 2024; 27:e222. [PMID: 39445498 PMCID: PMC11604324 DOI: 10.1017/s1368980024001344] [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: 03/22/2023] [Revised: 06/26/2024] [Accepted: 07/11/2024] [Indexed: 10/25/2024]
Abstract
OBJECTIVE In this paper, we examined whether there are inequalities in access to food retail (by type and healthiness) across local government areas (LGA) in Greater Melbourne and by LGA grouped based on their distance from the central business district and Growth Area designation. We also examined whether these inequalities persisted over time. DESIGN This is a secondary analysis of a repeated cross-sectional census of food outlets collected at four time points (2008, 2012, 2014 and 2016) across 31 LGA. Using Geographical Information Systems, we present a spatial analysis of food retail environments in Melbourne, Australia, at these four times over eight years. SETTING Greater Melbourne, Australia. PARTICIPANTS 31 LGA in Greater Melbourne. RESULTS Findings show significant inequalities in access to healthy food retail persisting over time at the LGA level. Residents in lower density urban growth areas had the least access to healthy food retail. Unhealthy food retail was comparatively more accessible, with a temporal trend indicating increased accessibility over time in urban growth areas only. CONCLUSION Accessibility to food outlets, particularly healthy food outlets and supermarkets, in Greater Melbourne is not equal. To identify and address health inequalities associated with rapid urban growth, further understanding of how people interact with the food environment needs to be explored.
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Affiliation(s)
- Cindy Needham
- Deakin University, Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Geelong3220, Australia
| | - Claudia Strugnell
- Deakin University, Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Geelong3220, Australia
- Deakin University, Institute for Physical Activity and Nutrition, Geelong, Australia
| | - Liliana Orellana
- Deakin University, Biostatistics Unit, Faculty of Health, Geelong, Australia
| | - Steven Allender
- Deakin University, Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Geelong3220, Australia
| | - Gary Sacks
- Deakin University, Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Geelong3220, Australia
| | - Miranda R Blake
- Deakin University, Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Geelong3220, Australia
| | - Ana Horta
- Charles Sturt University, Faculty of Science and Health, Albury-Wodonga, NSW, Australia
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Mizen A, Thompson DA, Watkins A, Akbari A, Garrett JK, Geary R, Lovell R, Lyons RA, Nieuwenhuijsen M, Parker SC, Rowney FM, Song J, Stratton G, Wheeler BW, White J, White MP, Williams S, Rodgers SE, Fry R. The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2024; 34:753-760. [PMID: 38424359 PMCID: PMC11446865 DOI: 10.1038/s41370-024-00650-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 01/24/2024] [Accepted: 01/24/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging. OBJECTIVE Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies. METHODS We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300 m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300 m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types. RESULTS Mean EVI for a 300 m radius surrounding households in Wales was 0.28 (IQR = 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (β = < 0.0001, 95% CI: 0.0000, 0.0000; β = 0.0001, 95% CI: 0.0001, 0.0001 respectively). In urban areas, as average garden size increases by 1 m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500 m2. The very small β values represent no 'measurable real-world' associations. When stratified by type, we observed no strong associations between greenspace and EVI. IMPACT It is a widely implemented assumption in epidiological studies that an increase in EVI is equivalent to an increase in greenness and/or green space. We used linear regression models to test associations between EVI and potential sources of green reflectance at a neighbourhood level using satellite imagery from 2018. We compared EVI measures with a 'gold standard' vector-based dataset that defines publicly accessible and private green spaces. We found that EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.
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Affiliation(s)
- Amy Mizen
- Swansea University Medical School, Swansea University, Swansea, UK.
| | | | - Alan Watkins
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Ashley Akbari
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Rebecca Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Ronan A Lyons
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Sarah C Parker
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Francis M Rowney
- School of Geography, Earth and Environmental Sciences, University of Plymouth, Plymouth, UK
| | | | - Gareth Stratton
- ASTEM Research Centre, Faculty of Science and Engineering, Swansea University, Swansea, UK
| | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | - Mathew P White
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
- Cognitive Science Hub, University of Vienna, Vienna, Austria
| | | | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Richard Fry
- Swansea University Medical School, Swansea University, Swansea, UK
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7
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Lang IM, Antonakos CL, Judd SE, Colabianchi N. Intake of Snacks and Sweets in a National Study of Built and Social Environments: the REasons for Geographic And Racial Differences in Stroke Study. J Nutr 2024; 154:2300-2314. [PMID: 38795742 PMCID: PMC11923438 DOI: 10.1016/j.tjnut.2024.05.017] [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: 11/14/2023] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 05/28/2024] Open
Abstract
BACKGROUND Few national studies across the United States' rural-urban continuum examine neighborhood effects on snacks and sweets intake among adults. OBJECTIVES This study examines associations of urbanicity/rurality-tailored measures of food store availability and neighborhood socioeconomic status (NSES) with the intake of snacks and sweets in a national sample of middle and older age adults. METHODS This cross-sectional study used food frequency questionnaire data collected in the REasons for Geographic And Racial Differences in Stroke study (N = 21,204). What We Eat in America food group categorizations guided outcome classification into 1 main category (total snacks and sweets) and 4 subcategories (savory snacks and crackers; sweet bakery products; candy and desserts; nutrition bars and low-fat snacks and sweets). NSES and food store availability were determined using geographic information systems. Food store availability was characterized as geographic access to primary food stores (e.g., supermarkets, supercenters, and select food retailers) in urbanicity/rurality-tailored neighborhood-based buffers. Multiple linear regression was used to predict each outcome. RESULTS Living in neighborhoods with a high density of primary food stores was associated with 8.6%, 9.5%, and 5.8% lower intake of total snacks and sweets, sweet bakery products, and candy and desserts, respectively. Living in the highest NSES quartile was associated with 11.3%, 5.8%, and 18.9% lower intake of total snacks and sweets, savory snacks and crackers, and sweet bakery products, respectively. Depending on primary food store availability, higher household income was associated with significantly greater intake of nutrition bars and low-fat snacks and sweets. Living in a United States Department of Agriculture-defined food desert was not associated with intake. CONCLUSIONS In a geographically diverse sample of middle and older age United States adults, living in neighborhoods with no primary food stores or neighborhoods of low-SES was associated with higher intake of total snacks and sweets and subgroups of snacks and sweets.
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Affiliation(s)
- Ian-Marshall Lang
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
| | - Cathy L Antonakos
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
| | - Suzanne E Judd
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Natalie Colabianchi
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States; Institute for Social Research, University of Michigan, Ann Arbor, MI, United States.
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8
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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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Keeble M, Adams J, Amies-Cull B, Chang M, Cummins S, Derbyshire D, Hammond D, Hassan S, Liu B, Medina-Lara A, Mytton O, Rahilly J, Rogers N, Savory B, Smith R, Thompson C, White CM, White M, Burgoine T. Public acceptability of proposals to manage new takeaway food outlets near schools: cross-sectional analysis of the 2021 International Food Policy Study. CITIES & HEALTH 2024; 8:1094-1107. [PMID: 39635458 PMCID: PMC11614041 DOI: 10.1080/23748834.2024.2336311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 03/25/2024] [Indexed: 12/07/2024]
Abstract
Global trends indicate that takeaway food is commonly accessible in neighbourhood food environments. Local governments in England can use spatial planning to manage the opening of new takeaway outlets in 'takeaway management zones around schools' (known sometimes as 'exclusion zones'). We analysed data from the 2021 International Food Policy Study to investigate public acceptability of takeaway management zones around schools. Among adults living in Great Britain (n = 3323), 50.8% supported, 8.9% opposed, and 37.3% were neutral about the adoption of these zones. Almost three-quarters (70.4%) believed that these zones would help young people to eat better. Among 16-17 year olds (n = 354), 33.3% agreed that young people would consume takeaway food less often if there were fewer takeaways near schools. Using adjusted logistic regression, we identified multiple correlates of public support for and perceived effectiveness of takeaway management zones. Odds of support were strongest among adults reporting that there were currently too many takeaways in their neighbourhood food environment (odds ratio: 2.32; 95% confidence intervals: 1.61, 3.35). High levels of support alongside limited opposition indicate that proposals for takeaway management zones around schools would not receive substantial public disapproval. Policy makers should not, therefore, use limited public support to rationalise policy inertia.
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Affiliation(s)
- Matthew Keeble
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jean Adams
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Ben Amies-Cull
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Michael Chang
- Department of Health and Social Care, Office for Health Improvement and Disparities, UK
| | - Steven Cummins
- Population Health Innovation Lab, Department of Public Health, Environments & Society, Faculty of Public Health & Policy, London School of Tropical Hygiene and Medicine, London, UK
| | - Daniel Derbyshire
- Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - David Hammond
- School of Public Sciences, Faculty of Health, University of Waterloo, Waterloo, Canada
| | - Suzan Hassan
- Population Health Innovation Lab, Department of Public Health, Environments & Society, Faculty of Public Health & Policy, London School of Tropical Hygiene and Medicine, London, UK
| | - Bochu Liu
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Department of Urban Planning, College of Architecture and Urban Planning, Tongji University, Shanghai, China
| | - Antonieta Medina-Lara
- Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Oliver Mytton
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Great Ormond Street Institute of Child Health, University College London, London, UK
| | - John Rahilly
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Nina Rogers
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Bea Savory
- Population Health Innovation Lab, Department of Public Health, Environments & Society, Faculty of Public Health & Policy, London School of Tropical Hygiene and Medicine, London, UK
| | - Richard Smith
- Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Claire Thompson
- School of Health and Social Work, University of Hertfordshire, Hertfordshire, UK
| | - Christine M. White
- School of Public Sciences, Faculty of Health, University of Waterloo, Waterloo, Canada
| | - Martin White
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Thomas Burgoine
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
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Cao Y, Yang JA, Nara A, Jankowska MM. Designing and Evaluating a Hierarchical Framework for Matching Food Outlets across Multi-sourced Geospatial Datasets: a Case Study of San Diego County. J Urban Health 2024; 101:155-169. [PMID: 38167974 PMCID: PMC10897078 DOI: 10.1007/s11524-023-00817-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/29/2023] [Indexed: 01/05/2024]
Abstract
Research on retail food environment (RFE) relies on data availability and accuracy. However, the discrepancies in RFE datasets may lead to imprecision when measuring association with health outcomes. In this research, we present a two-tier hierarchical point of interest (POI) matching framework to compare and triangulate food outlets across multiple geospatial data sources. Two matching parameters were used including the geodesic distance between businesses and the similarity of business names according to Levenshtein distance (LD) and Double Metaphone (DM). Sensitivity analysis was conducted to determine thresholds of matching parameters. Our Tier 1 matching used more restricted parameters to generate high confidence-matched POIs, whereas in Tier 2 we opted for relaxed matching parameters and applied a weighted multi-attribute model on the previously unmatched records. Our case study in San Diego County, California used government, commercial, and crowdsourced data and returned 20.2% matched records from Tier 1 and 18.6% matched from Tier 2. Our manual validation shows a 100% matching rate for Tier 1 and up to 30.6% for Tier 2. Matched and unmatched records from Tier 1 were further analyzed for spatial patterns and categorical differences. Our hierarchical POI matching framework generated highly confident food POIs by conflating datasets and identified some food POIs that are unique to specific data sources. Triangulating RFE data can reduce uncertain and invalid POI listings when representing food environment using multiple data sources. Studies investigating associations between food environment and health outcomes may benefit from improved quality of RFE.
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Affiliation(s)
- Yanjia Cao
- Department of Geography, The University of Hong Kong, Pok Fu Lam, Hong Kong.
| | - Jiue-An Yang
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Atsushi Nara
- Department of Geography, San Diego State University, San Diego, CA, USA
| | - Marta M Jankowska
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA
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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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12
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Boise S, Crossa A, Etheredge AJ, McCulley EM, Lovasi GS. Concepts, Characterizations, and Cautions: A Public Health Guide and Glossary for Planning Food Environment Measurement. THE OPEN PUBLIC HEALTH JOURNAL 2023; 16:e187494452308210. [PMID: 38179222 PMCID: PMC10766432 DOI: 10.2174/18749445-v16-230821-2023-51] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 07/13/2023] [Accepted: 07/30/2023] [Indexed: 01/06/2024]
Abstract
Background There is no singular approach to measuring the food environment suitable for all studies. Understanding terminology, methodology, and common issues is crucial to choosing the best approach. Objective This review is designed to support a shared understanding so diverse multi-institutional teams engaged in food environment measurement can justify their measurement choices and have informed discussions about reasons for measurement strategies to vary across projects. Methods This guide defines key terms and provides annotated resources identified as a useful starting point for exploring the food environment literature. The writing team was an academic-practice collaboration, reflecting on the experience of a multi-institutional team focused on retail environments across the US relevant to cardiovascular disease. Results Terms and annotated resources are divided into three sections: food environment constructs, classification and measures, and errors and strategies to reduce error. Two examples of methods and challenges encountered while measuring the food environment in the context of a US health department are provided. Researchers and practice professionals are directed to the Food Environment Electronic Database Directory (https://www.foodenvironmentdirectory.com/) for comparing available data resources for food environment measurement, focused on the US; this resource incorporates updates informed by user input and literature reviews. Discussion Measuring the food environment is complex and risks oversimplification. This guide serves as a starting point but only partially captures some aspects of neighborhood food environment measurement. Conclusions No single food environment measure or data source meets all research and practice objectives. This shared starting point can facilitate theoretically grounded food environment measurement.
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Affiliation(s)
- Sarah Boise
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia PA
- Penn Medicine Medical Group, University of Pennsylvania Health System, Penn Medicine
| | - Aldo Crossa
- Department of Health and Mental Hygiene, New York, NY
| | | | - Edwin M. McCulley
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia PA
| | - Gina S. Lovasi
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia PA
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia PA
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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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Titis E, Di Salvatore J, Procter R. Socio-economic correlates of childhood obesity in urban and rural England. Public Health Nutr 2023; 26:1815-1827. [PMID: 37271723 PMCID: PMC10478054 DOI: 10.1017/s1368980023000952] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/06/2023] [Accepted: 04/25/2023] [Indexed: 06/06/2023]
Abstract
OBJECTIVE Physical access to food may affect diet and thus obesity rates. We build upon existing work to better understand how socio-economic characteristics of locations are associated with childhood overweight. DESIGN Using cross-sectional design and publicly available data, the study specifically compares rural and urban areas, including interactions of distance from supermarkets with income and population density. SETTING We examine cross-sectional associations with obesity prevalence both in the national scale and across urban and rural areas differing in household wealth. PARTICIPANTS Children in reception class (aged 4-5) from all state-maintained schools in England taking part in the National Child Measurement Programme (n 6772). RESULTS Income was the main predictor of childhood obesity (adj. R-sq=.316, p<.001), whereas distance played only a marginal role (adj. R-sq=.01, p<.001). In urban areas, distance and density correlate with obesity directly and conditionally. Urban children were slightly more obese, but the opposite was true for children in affluent areas. Association between income poverty and obesity rates was stronger in urban areas (7·59 %) than rural areas (4·95 %), the former which also showed stronger association between distance and obesity. CONCLUSIONS Obesogenic environments present heightened risks in deprived urban and affluent rural areas. The results have potential value for policy making as for planning and targeting of services for vulnerable groups.
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Affiliation(s)
- Elzbieta Titis
- Warwick Institute for the Science of Cities, Department of Computer Science, University of Warwick, Coventry, UK
| | - Jessica Di Salvatore
- Department of Politics and International Studies, University of Warwick, Coventry, UK
| | - Rob Procter
- Department of Computer Science, University of Warwick, Coventry, UK
- Human-Centred Computing Division, Institute for Data Science and AI, London, UK
- Alan Turing Institute for Data Science and AI, London, UK
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15
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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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Figueroa R, Baker K, Capellan J, Pinheiro LC, Burd L, Lim J, Chiong R, Eboh R, Phillips E. Residential urban food environment profiles and diet outcomes among adults in Brooklyn, New York: a cross-sectional study. Public Health Nutr 2023; 26:877-885. [PMID: 36384640 PMCID: PMC10131155 DOI: 10.1017/s1368980022002476] [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: 09/13/2021] [Revised: 10/10/2022] [Accepted: 11/09/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To assess the clustering properties of residential urban food environment indicators across neighbourhoods and to determine if clustering profiles are associated with diet outcomes among adults in Brooklyn, New York. DESIGN Cross-sectional. SETTING Five neighbourhoods in Brooklyn, New York. PARTICIPANTS Survey data (n 1493) were collected among adults in Brooklyn, New York between April 2019 and September 2019. Data for food environment indicators (fast-food restaurants, bodegas, supermarkets, farmer's markets, community kitchens, Supplemental Nutrition Assistance Program application centres, food pantries) were drawn from New York databases. Latent profile analysis (LPA) was used to identify individuals' food access-related profiles, based on food environments measured by the availability of each outlet within each participant's 800-m buffer. Profile memberships were associated with dietary outcomes using mixed linear regression. RESULTS LPA identified four residential urban food environment profiles (with significant high clusters ranging from 17 to 57 across profiles): limited/low food access, (n 587), bodega-dense (n 140), food swamp (n 254) and high food access (n 512) profiles. Diet outcomes were not statistically different across identified profiles. Only participants in the limited/low food access profile were more likely to consume sugar-sweetened beverages (SSB) than those in the bodega-dense profile (b = 0·44, P < 0·05) in adjusted models. CONCLUSIONS Individuals in limited and low food access neighbourhoods are vulnerable to consuming significant amounts of SSB compared with those in bodega-dense communities. Further research is warranted to elucidate strategies to improve fruit and vegetable consumption while reducing SSB intake within residential urban food environments.
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Affiliation(s)
- Roger Figueroa
- Division of Nutritional Sciences, College of Human Ecology, Cornell University, 244 Garden Avenue, Ithaca, NY14853, USA
| | - Katherine Baker
- Division of Nutritional Sciences, College of Human Ecology, Cornell University, 244 Garden Avenue, Ithaca, NY14853, USA
| | - Joel Capellan
- Law & Justice Studies, Rowan University, 215 Mullica Road, Glassboro, NJ08028, USA
| | - Laura C Pinheiro
- Division of General Internal Medicine, Department of Medicine, Cornell Center for Health Equity, Weill Cornell Medicine College, 338 East 66th Street, New York, NY10065, USA
| | - Laura Burd
- Division of Nutritional Sciences, College of Human Ecology, Cornell University, 244 Garden Avenue, Ithaca, NY14853, USA
| | - Jane Lim
- Division of Nutritional Sciences, College of Human Ecology, Cornell University, 244 Garden Avenue, Ithaca, NY14853, USA
| | - Reah Chiong
- Division of Nutritional Sciences, College of Human Ecology, Cornell University, 244 Garden Avenue, Ithaca, NY14853, USA
| | - Relicious Eboh
- Master of Public Health, College of Veterinary Medicine, Cornell University, 602 Tower Road, Ithaca, NY14853, USA
| | - Erica Phillips
- Division of General Internal Medicine, Department of Medicine, Cornell Center for Health Equity, Weill Cornell Medicine College, 338 East 66th Street, New York, NY10065, USA
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Morais L, Lopes A, Rocha J, Nogueira PJ. Beyond Usual Geographical Scales of Analysis: Implications for Healthcare Management and Urban Planning. PORTUGUESE JOURNAL OF PUBLIC HEALTH 2023; 40:140-154. [PMID: 39469257 PMCID: PMC11320098 DOI: 10.1159/000527162] [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: 04/02/2022] [Accepted: 09/19/2022] [Indexed: 10/30/2024] Open
Abstract
Introduction In the context of climate emergency, advances in geographic information systems, geocoding, and geomedicine allow us to go beyond the conventional usual scales and be aligned with people's needs, improving knowledge and accuracy of the spatial pattern of health outcomes. This study shows that the geographical scale of analysis affects the interpretation of health outcomes. Methods All mortality that occurred in Portugal in 2014-2017 was geocoded. From 435,291 addresses, 412,608 were geocoded with success. As an example, we use the spatial patterns of the elderly's heat-related cardiorespiratory mortality. Results It is shown: (i) it is possible to have high quality and accuracy of spatial data used in health outcomes analysis; (ii) how geographic scales reveal different degrees of detail in health outcomes analysis; (iii) the neighbourhood scale revealed different patterns of cardiorespiratory mortality from the usually available scale (parish). Discussion Our findings suggest the relevance of geocoding health outcomes with a finer scale in tackling the challenges of the healthcare sector, and in support of planning decision-making, closely matching citizens' needs. Without running the risk of losing potentially major prospects, better healthcare management is achievable, with optimal resource allocation, and improved detailed and informed policymaking, allowing enhanced climate health equity in cities promotion.
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Affiliation(s)
- Liliane Morais
- ISAMB − Instituto de Saúde Ambiental, Instituto de Medicina Preventiva, Faculdade de Medicina da Universidade de Lisboa, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
| | - António Lopes
- Laboratório Associado TERRA, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Institute of Geography and Spatial Planning (IGOT), University of Lisbon, Lisbon, Portugal
| | - Jorge Rocha
- Laboratório Associado TERRA, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Institute of Geography and Spatial Planning (IGOT), University of Lisbon, Lisbon, Portugal
| | - Paulo Jorge Nogueira
- ISAMB − Instituto de Saúde Ambiental, Instituto de Medicina Preventiva, Faculdade de Medicina da Universidade de Lisboa, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
- Laboratório Associado TERRA, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Área Disciplinar Autónoma da Bioestatística (laboratório de Biomatemática), Instituto de Medicina Preventiva, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
- CIDNUR − Centro de Investigação, Inovação e Desenvolvimento em Enfermagem de Lisboa, Escola Superior de Enfermagem de Lisboa, Lisbon, Portugal
- National School of Public Health (CISP), New University of Lisbon, Lisbon, Portugal
- NOVA National School of Public Health, Public Health Research Centre, Universidade NOVA de Lisboa, Comprehensive Health Research Center (CHRC), Lisbon, Portugal
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Acciai F, DeWeese RS, Yedidia MJ, Lloyd K, Tulloch D, DeLia D, Ohri-Vachaspati P. Differential Associations Between Changes in Food Environment and Changes in BMI Among Adults Living in Urban, Low-Income Communities. J Nutr 2022; 152:2582-2590. [PMID: 36774124 PMCID: PMC9644168 DOI: 10.1093/jn/nxac186] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/12/2022] [Accepted: 08/16/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Food environments can contribute to excess weight gain among adults, but the evidence is mixed. OBJECTIVES This longitudinal study investigated the associations between changes in the food environment and changes in BMI in adults and whether changes in the food environment differentially impact various subgroups. METHODS At 2 time points, BMI was calculated using self-reported height and weight data from 517 adults (mean age, 41 years) living in 4 New Jersey cities. The counts of different types of food outlets within 0.4, 0.8, and 1.6 km of respondents' residences were collected at baseline and tracked until follow-up. A binary measure of social standing (social-advantage group, n = 219; social-disadvantage group, n = 298) was created through a latent class analysis using social, economic, and demographic variables. Multivariable linear regression modeled the associations between changes in BMI with measures of the food environment; additionally, interaction terms between the measures of food environment and social standing were examined. RESULTS Overall, over 18 months, an increase in the number of small grocery stores within 0.4 km of a respondent's residence was associated with a decrease in BMI (β = -1.0; 95% CI: -1.9, -0.1; P = 0.024), while an increase in the number of fast-food restaurants within 1.6 km was associated with an increase in BMI (β = 0.1; 95% CI: 0.01, 0.2; P = 0.027). These overall findings, however, masked some group-specific associations. Interaction analyses suggested that associations between changes in the food environment and changes in BMI varied by social standing. For instance, the association between changes in fast-food restaurants and changes in BMI was only observed in the social-disadvantage group (β = 0.1; 95% CI: 0.02, 0.2; P = 0.021). CONCLUSIONS In a sample of adults living in New Jersey, changes in the food environment had differential effects on individuals' BMIs, based on their social standing.
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Affiliation(s)
- Francesco Acciai
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA.
| | - Robin S DeWeese
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
| | - Michael J Yedidia
- Center for State Health Policy, Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA
| | - Kristen Lloyd
- Center for State Health Policy, Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA
| | - David Tulloch
- Department of Landscape Architecture, Rutgers University, New Brunswick, NJ, USA
| | - Derek DeLia
- Edward J. Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ, USA; Department of Plastic and Reconstructive Surgery, Georgetown University School of Medicine, Washington, DC, USA
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D’Hooghe S, Inaç Y, De Clercq E, Deforche B, Dury S, Vandevijvere S, Van de Weghe N, Van Dyck D, De Ridder K. The CIVISANO protocol: a mixed-method study about the role of objective and perceived environmental factors on physical activity and eating behavior among socioeconomically disadvantaged adults. Arch Public Health 2022; 80:219. [PMID: 36199109 PMCID: PMC9533259 DOI: 10.1186/s13690-022-00956-6] [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: 09/14/2021] [Accepted: 08/19/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Overweight and obesity have a strong socioeconomic profile. Unhealthy behaviors like insufficient physical activity and an unbalanced diet, which are causal factors of overweight and obesity, tend to be more pronounced in socioeconomically disadvantaged groups in high income countries. The CIVISANO project aims to identify objective and perceived environmental factors among different socioeconomic population groups that impede or facilitate physical activity and healthy eating behavior in the local context of two peri-urban Flemish municipalities in Belgium. We also aim to identify and discuss possible local interventions and evaluate the participatory processes of the project. METHODS This study (2020-2023) will use community-based participatory tools, involving collaborative partnerships with civic and stakeholder members of the community and regular exchanges among all partners to bridge knowledge development and health promotion for socioeconomically disadvantaged citizens. Furthermore, a mixed-methods approach will be used. A population survey and geographic analysis will explore potential associations between the physical activity and eating behaviors of socioeconomically disadvantaged adults (25-65 years old) and both their perceived and objective physical, food and social environments. Profound perceptive context information will be gathered from socioeconomically disadvantaged adults by using participatory methods like photovoice, walk-along, individual map creation and group model building. An evaluation of the participatory process will be conducted simultaneously. DISCUSSION The CIVISANO project will identify factors in the local environment that might provoke inequities in adopting a healthy lifestyle. The combination of perceived and objective measures using validated strategies will provide a robust assessment of the municipality environment. Through this analysis, the project will investigate to what extent community engagement can be a useful strategy to reduce health inequities. The strong knowledge exchange and capacity-building in a local setting is expected to contribute to our understanding of how to maximize research impact in this field and generate evidence about potential linkages between a health enhancing lifestyle among socioeconomically disadvantaged groups and their physical, food and social environments.
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Affiliation(s)
- Suzannah D’Hooghe
- grid.508031.fSciensano, Department of Epidemiology and Public Health, Brussels, Belgium ,grid.5342.00000 0001 2069 7798Ghent University, Faculty of Medicine and Health Sciences, Department of Public Health and Primary Care, Ghent, Belgium ,grid.8767.e0000 0001 2290 8069Vrije Universiteit Brussel (VUB), Faculty of Psychology and Educational Sciences, Adult Educational Sciences, Brussels, Belgium
| | - Yasemin Inaç
- grid.508031.fSciensano, Department of Epidemiology and Public Health, Brussels, Belgium ,grid.8767.e0000 0001 2290 8069Vrije Universiteit Brussel (VUB), Faculty of Psychology and Educational Sciences, Adult Educational Sciences, Brussels, Belgium ,grid.5342.00000 0001 2069 7798Ghent University, Faculty of Sciences, Department of Geography, Ghent, Belgium
| | - Eva De Clercq
- grid.508031.fSciensano, Department of Chemical and Physical Health Risks, Brussels, Belgium
| | - Benedicte Deforche
- grid.5342.00000 0001 2069 7798Ghent University, Faculty of Medicine and Health Sciences, Department of Public Health and Primary Care, Ghent, Belgium ,grid.8767.e0000 0001 2290 8069Vrije Universiteit Brussel (VUB), Faculty of Physical Education and Physiotherapy, Department of Movement and Sport Sciences, Brussels, Belgium
| | - Sarah Dury
- grid.8767.e0000 0001 2290 8069Vrije Universiteit Brussel (VUB), Faculty of Psychology and Educational Sciences, Adult Educational Sciences, Brussels, Belgium
| | - Stefanie Vandevijvere
- grid.508031.fSciensano, Department of Epidemiology and Public Health, Brussels, Belgium
| | - Nico Van de Weghe
- grid.5342.00000 0001 2069 7798Ghent University, Faculty of Sciences, Department of Geography, Ghent, Belgium
| | - Delfien Van Dyck
- grid.5342.00000 0001 2069 7798Ghent University, Faculty of Medicine and Health Sciences, Department of Movement and Sports Sciences, Brussels, Belgium
| | - Karin De Ridder
- grid.508031.fSciensano, Department of Epidemiology and Public Health, Brussels, Belgium
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20
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Pontin FL, Jenneson VL, Morris MA, Clarke GP, Lomax NM. Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework. Int J Behav Nutr Phys Act 2022; 19:119. [PMID: 36104757 PMCID: PMC9476279 DOI: 10.1186/s12966-022-01352-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 08/18/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Objective measures of built environment and physical activity provide the opportunity to directly compare their relationship across different populations and spatial contexts. This systematic review synthesises the current body of knowledge and knowledge gaps around the impact of objectively measured built environment metrics on physical activity levels in adults (≥ 18 years). Additionally, this review aims to address the need for improved quality of methodological reporting to evaluate studies and improve inter-study comparability though the creation of a reporting framework.
Methods
A systematic search of the literature was conducted following the PRISMA guidelines. After abstract and full-text screening, 94 studies were included in the final review. Results were synthesised using an association matrix to show overall association between built environment and physical activity variables. Finally, the new PERFORM (’Physical and Environmental Reporting Framework for Objectively Recorded Measures’) checklist was created and applied to the included studies rating them on their reporting quality across four key areas: study design and characteristics, built environment exposures, physical activity metrics, and the association between built environment and physical activity.
Results
Studies came from 21 countries and ranged from two days to six years in duration. Accelerometers and using geographic information system (GIS) to define the spatial extent of exposure around a pre-defined geocoded location were the most popular tools to capture physical activity and built environment respectively. Ethnicity and socio-economic status of participants were generally poorly reported. Moderate-to-vigorous physical activity (MVPA) was the most common metric of physical activity used followed by walking. Commonly investigated elements of the built environment included walkability, access to parks and green space. Areas where there was a strong body of evidence for a positive or negative association between the built environment and physical activity were identified. The new PERFORM checklist was devised and poorly reported areas identified, included poor reporting of built environment data sources and poor justification of method choice.
Conclusions
This systematic review highlights key gaps in studies objectively measuring the built environment and physical activity both in terms of the breadth and quality of reporting. Broadening the variety measures of the built environment and physical activity across different demographic groups and spatial areas will grow the body and quality of evidence around built environment effect on activity behaviour. Whilst following the PERFORM reporting guidance will ensure the high quality, reproducibility, and comparability of future research.
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21
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Kharmats AY, Corrigan AE, Curriero FC, Neff R, Caulfield L, Kennedy CE, Whitley J, Montazer JS, Hu L, Gittelsohn J. Geospatial Food Environment Exposure and Obesity Among Low Income Baltimore City Children: Associations Differ by Data Source and Processing Method. JOURNAL OF HUNGER & ENVIRONMENTAL NUTRITION 2022; 19:694-717. [PMID: 39600470 PMCID: PMC11588286 DOI: 10.1080/19320248.2022.2090882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Due to the high prevalence of childhood obesity, it is imperative to assess the relationship children's access to food retailers and obesity. However, the influence of methodological decisions on these associations has been understudied. We examined relationships between different measures of geospatial food environment (using 4 data sources, and 2 data processing methods), and BMI in a sample of low-income children in Baltimore, Maryland. The choice of data sources and data processing methods produced large differences in estimates of children's exposures to certain store types, such as supermarket-like stores, but had less impact on associations with BMI z-scores.
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Affiliation(s)
- Anna Y. Kharmats
- New York University Grossman School of Medicine, Department of Population Health, Baltimore, MD
- Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD
| | - Anne E. Corrigan
- Johns Hopkins University, Spatial Science for Public Health Center, Baltimore, MD
| | - Frank C. Curriero
- Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology, Department of Biostatistics, Baltimore, MD
| | - Roni Neff
- Johns Hopkins Bloomberg School of Public Health, Department of Environmental Health and Engineering, Department of Health Policy and Management, Baltimore, MD
| | - Laura Caulfield
- Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD
| | - Caitlin E. Kennedy
- Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD
- Johns Hopkins Bloomberg School of Public Health, Department of Health, Behavior, and Society, Baltimore, MD
| | - Jessica Whitley
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Jaleh S. Montazer
- University of Maryland School of Public Health, Department of Health Policy and Management, College Park, Maryland
| | - Lu Hu
- New York University Grossman School of Medicine, Department of Population Health, Baltimore, MD
| | - Joel Gittelsohn
- Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD
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22
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van Erpecum CPL, van Zon SKR, Bültmann U, Smidt N. The association between fast-food outlet proximity and density and Body Mass Index: Findings from 147,027 Lifelines Cohort Study participants. Prev Med 2022; 155:106915. [PMID: 34922992 DOI: 10.1016/j.ypmed.2021.106915] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 09/30/2021] [Accepted: 12/12/2021] [Indexed: 12/17/2022]
Abstract
Unhealthy food environments may contribute to an elevated Body Mass Index (BMI), which is a chronic disease risk factor. We examined the association between residential fast-food outlet exposure, in terms of proximity and density, and BMI in the Dutch adult general population. Additionally, we investigated to what extent this association was modified by urbanisation level. In this cross-sectional study, we linked residential addresses of baseline adult Lifelines Cohort participants (n = 147,027) to fast-food outlet locations using geo-coding. We computed residential fast-food outlet proximity, and density within 500 m, 1, 3, and 5 km. We used stratified (urban versus rural areas) multilevel linear regression models, adjusting for age, sex, partner status, education, employment, neighbourhood deprivation, and address density. The mean BMI of participants was 26.1 (SD 4.3) kg/m2. Participants had a mean (SD) age of 44.9 (13.0), 57.3% was female, and 67.0% lived in a rural area. Having two or more (urban areas) or five or more (rural areas) fast-food outlets within 1 km was associated with a higher BMI (B = 0.32, 95% confidence interval (CI): 0.03, 0.62; B = 0.23, 95% CI: 0.10, 0.36, respectively). Participants in urban and rural areas with a fast-food outlet within <250 m had a higher BMI (B = 0.30, 95% CI: 0.03, 0.57; B = 0.20, 95% CI: 0.09, 0.31, respectively). In rural areas, participants also had a higher BMI when having at least one fast-food outlet within 500 m (B = 0.10, 95% CI: 0.02, 0.18). In conclusion, fast-food outlet exposure within 1 km from the residential address was associated with BMI in urban and rural areas. Also, fast-food outlet exposure within 500 m was associated with BMI in rural areas, but not in urban areas. In the future, natural experiments should investigate changes in the fast-food environment over time.
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Affiliation(s)
- Carel-Peter L van Erpecum
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9700 RB Groningen, the Netherlands.
| | - Sander K R van Zon
- University of Groningen, University Medical Center Groningen, Department of Health Sciences, Community and Occupational Medicine, Hanzeplein 1, 9700 RB Groningen, the Netherlands.
| | - Ute Bültmann
- University of Groningen, University Medical Center Groningen, Department of Health Sciences, Community and Occupational Medicine, Hanzeplein 1, 9700 RB Groningen, the Netherlands.
| | - Nynke Smidt
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9700 RB Groningen, the Netherlands.
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23
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A Proposed Research Agenda for Promoting Healthy Retail Food Environments in the East Asia-Pacific Region. Curr Nutr Rep 2021; 10:267-281. [PMID: 34894342 DOI: 10.1007/s13668-021-00381-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/20/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE OF REVIEW This paper aimed to summarise existing literature on strategies to improve the healthiness of retail food environments in the East Asia and Pacific (EAP) region, and propose a prioritised research agenda on this topic. RECENT FINDINGS Little research on retail food environments has been conducted in the EAP region. Several approaches for measuring retail food environments were identified, although none have been tailored to the EAP context. A small number of policies and initiatives to promote healthy retail food environments have been implemented in EAP. Lessons learnt from successful implementation of initiatives in other regions could be applied in EAP. Retail food environments have a strong influence on food choices and health outcomes. Research can contribute to efforts to improve the healthiness of retail food environments in EAP by (1) describing the current state of retail food environments to highlight areas of good practice and concern and (2) identifying policies and initiatives that are likely to be effective, and mechanisms for their successful implementation.
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24
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Keeble M, Adams J, Bishop TR, Burgoine T. Socioeconomic inequalities in food outlet access through an online food delivery service in England: A cross-sectional descriptive analysis. APPLIED GEOGRAPHY (SEVENOAKS, ENGLAND) 2021; 133:None. [PMID: 34345056 PMCID: PMC8288297 DOI: 10.1016/j.apgeog.2021.102498] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 06/04/2021] [Accepted: 06/21/2021] [Indexed: 05/05/2023]
Abstract
Online food delivery services facilitate 'online' access to food outlets selling food prepared away-from-home. Online food outlet access has not previously been investigated in England or across an entire country. Systematic differences in online food outlet access could exacerbate existing health inequalities, which is a public health concern. However, this is not known. Across postcode districts in England (n = 2118), we identified and described the number of food outlets and unique cuisine types accessible online from the market leader (Just Eat). We investigated associations with area-level deprivation using adjusted negative binomial regression models. We also compared the number of food outlets accessible online with the number physically accessible in the neighbourhood (1600m Euclidean buffers of postcode district geographic centroids) and investigated associations with deprivation using an adjusted general linear model. For each outcome, we predicted means and 95% confidence intervals. In November 2019, 29,232 food outlets were registered to accept orders online. Overall, the median number of food outlets accessible online per postcode district was 63.5 (IQR; 16.0-156.0). For the number of food outlets accessible online as a percentage of the number accessible within the neighbourhood, the median was 63.4% (IQR; 35.6-96.5). Analysis using negative binomial regression showed that online food outlet access was highest in the most deprived postcode districts (n = 106.1; 95% CI: 91.9, 120.3). The number of food outlets accessible online as a percentage of those accessible within the neighbourhood was highest in the least deprived postcode districts (n = 86.2%; 95% CI: 78.6, 93.7). In England, online food outlet access is socioeconomically patterned. Further research is required to understand how online food outlet access is related to using online food delivery services.
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Affiliation(s)
- Matthew Keeble
- 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
| | - Jean Adams
- 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
| | - 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
| | - 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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25
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Carducci B, Oh C, Roth DE, Neufeld LM, Frongillo EA, L'Abbe MR, Fanzo J, Herforth A, Sellen DW, Bhutta ZA. Gaps and priorities in assessment of food environments for children and adolescents in low- and middle-income countries. NATURE FOOD 2021; 2:396-403. [PMID: 37118231 DOI: 10.1038/s43016-021-00299-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Accepted: 05/06/2021] [Indexed: 04/30/2023]
Abstract
School-aged children and adolescents have complex interactions with their food environments-the point of engagement of individuals with the food system-and are influenced by a diversity of individual, household and organizational factors. Although a wide range of methods have been proposed to define, monitor and evaluate food environments, few are tailored to school-aged children and adolescents. Here, we interrogate published literature on food metrics and methodologies for the characterization of food environments for school-aged children and adolescents living in low- and middle-income counties. We identify key priority actions and potential indicators for better monitoring and evaluation to galvanize policymaking to improve the healthiness of these interactions, which are so crucial to future adult well-being.
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Affiliation(s)
- Bianca Carducci
- Centre for Global Child Health, Peter Gilgan Centre for Research, Learning Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Christina Oh
- Centre for Global Child Health, Peter Gilgan Centre for Research, Learning Hospital for Sick Children, Toronto, Ontario, Canada
| | - Daniel E Roth
- Centre for Global Child Health, Peter Gilgan Centre for Research, Learning Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada
- Dalla Lana School of Public, Health University of Toronto, Toronto, Ontario, Canada
- Joannah and Brian Lawson Centre for Child Nutrition, University of Toronto, Toronto, Ontario, Canada
| | | | - Edward A Frongillo
- Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Mary R L'Abbe
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Joannah and Brian Lawson Centre for Child Nutrition, University of Toronto, Toronto, Ontario, Canada
| | - Jessica Fanzo
- Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, USA
- Johns Hopkins Nitze School of Advanced International Studies, Johns Hopkins University, Washington DC, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anna Herforth
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Daniel W Sellen
- Centre for Global Child Health, Peter Gilgan Centre for Research, Learning Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Joannah and Brian Lawson Centre for Child Nutrition, University of Toronto, Toronto, Ontario, Canada
- Department of Anthropology, University of Toronto, Toronto, Ontario, Canada
| | - Zulfiqar A Bhutta
- Centre for Global Child Health, Peter Gilgan Centre for Research, Learning Hospital for Sick Children, Toronto, Ontario, Canada.
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada.
- Dalla Lana School of Public, Health University of Toronto, Toronto, Ontario, Canada.
- Joannah and Brian Lawson Centre for Child Nutrition, University of Toronto, Toronto, Ontario, Canada.
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Institute for Global Health and Development, Aga Khan University, Karachi, Pakistan.
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26
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Marek L, Hobbs M, Wiki J, Kingham S, Campbell M. The good, the bad, and the environment: developing an area-based measure of access to health-promoting and health-constraining environments in New Zealand. Int J Health Geogr 2021; 20:16. [PMID: 33823853 PMCID: PMC8025579 DOI: 10.1186/s12942-021-00269-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/17/2021] [Indexed: 02/07/2023] Open
Abstract
Background Accounting for the co-occurrence of multiple environmental influences is a more accurate reflection of population exposure than considering isolated influences, aiding in understanding the complex interactions between environments, behaviour and health. This study examines how environmental ‘goods’ such as green spaces and environmental ‘bads’ such as alcohol outlets co-occur to develop a nationwide area-level healthy location index (HLI) for New Zealand. Methods Nationwide data were collected, processed, and geocoded on a comprehensive range of environmental exposures. Health-constraining ‘bads’ were represented by: (i) fast-food outlets, (ii) takeaway outlets, (iii) dairy outlets and convenience stores, (iv) alcohol outlets, (v) and gaming venues. Health-promoting ‘goods’ were represented by: (i) green spaces, (ii) blue spaces, (iii) physical activity facilities, (iv) fruit and vegetable outlets, and (v) supermarkets. The HLI was developed based on ranked access to environmental domains. The HLI was then used to investigate socio-spatial patterning by area-level deprivation and rural/urban classification. Results Results showed environmental ‘goods’ and ‘bads’ co-occurred together and were patterned by area-level deprivation. The novel HLI shows that the most deprived areas of New Zealand often have the most environmental ‘bads’ and less access to environmental ‘goods’. Conclusions The index, that is now publicly available, is able to capture both inter-regional and local variations in accessibility to health-promoting and health-constraining environments and their combination. Results in this study further reinforce the need to embrace the multidimensional nature of neighbourhood and place not only when designing health-promoting places, but also when studying the effect of existing built environments on population health. Supplementary Information The online version contains supplementary material available at 10.1186/s12942-021-00269-x.
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Affiliation(s)
- Lukas Marek
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.
| | - Matthew Hobbs
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.,School of Health Sciences, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Jesse Wiki
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand
| | - Simon Kingham
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.,School of Earth and Environment, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Malcolm Campbell
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.,School of Earth and Environment, University of Canterbury, Christchurch, Canterbury, New Zealand
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27
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Hirsch JA, Moore KA, Cahill J, Quinn J, Zhao Y, Bayer FJ, Rundle A, Lovasi GS. Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology. J Urban Health 2021; 98:271-284. [PMID: 33005987 PMCID: PMC8079597 DOI: 10.1007/s11524-020-00482-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/04/2020] [Indexed: 12/31/2022]
Abstract
Retail environments, such as healthcare locations, food stores, and recreation facilities, may be relevant to many health behaviors and outcomes. However, minimal guidance on how to collect, process, aggregate, and link these data results in inconsistent or incomplete measurement that can introduce misclassification bias and limit replication of existing research. We describe the following steps to leverage business data for longitudinal neighborhood health research: re-geolocating establishment addresses, preliminary classification using standard industrial codes, systematic checks to refine classifications, incorporation and integration of complementary data sources, documentation of a flexible hierarchical classification system and variable naming conventions, and linking to neighborhoods and participant residences. We show results of this classification from a dataset of locations (over 77 million establishment locations) across the contiguous U.S. from 1990 to 2014. By incorporating complementary data sources, through manual spot checks in Google StreetView and word and name searches, we enhanced a basic classification using only standard industrial codes. Ultimately, providing these enhanced longitudinal data and supplying detailed methods for researchers to replicate our work promotes consistency, replicability, and new opportunities in neighborhood health research.
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Affiliation(s)
- Jana A. Hirsch
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, PA Philadelphia, USA
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Kari A. Moore
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Jesse Cahill
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY USA
| | - James Quinn
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY USA
| | - Yuzhe Zhao
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Felicia J. Bayer
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Andrew Rundle
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY USA
| | - Gina S. Lovasi
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, PA Philadelphia, USA
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
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28
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Contributions of Food Environments to Dietary Quality and Cardiovascular Disease Risk. Curr Atheroscler Rep 2021; 23:14. [PMID: 33594516 DOI: 10.1007/s11883-021-00912-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2021] [Indexed: 01/18/2023]
Abstract
PURPOSE OF REVIEW To evaluate the multidimensional influence of food environments on food choice, dietary quality, and diet-related health and identify critical gaps necessary to develop effective population interventions that influence food choice. RECENT FINDINGS Multicomponent interventions that interact with multiple layers of the food environment show limited but consistent effects on dietary behaviors and may have wider and substantive population-level reach with greater incorporation of validated, holistic measurement tools. Opportunities to use smartphone technology to measure multiple components of the food environment will facilitate future interventions, particularly as food environments expand into online settings and interact with consumers in novel ways to shape food choice. While studies suggest that all dimensions of the food environment influence diet and health outcomes, robust and consistent measurements of food environments that integrate objective and subjective components are essential for developing stronger evidence needed to shift public policies.
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29
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Smith M, Cui J, Ikeda E, Mavoa S, Hasanzadeh K, Zhao J, Rinne TE, Donnellan N, Kyttä M. Objective measurement of children's physical activity geographies: A systematic search and scoping review. Health Place 2021; 67:102489. [PMID: 33302122 PMCID: PMC7883215 DOI: 10.1016/j.healthplace.2020.102489] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/20/2020] [Accepted: 11/20/2020] [Indexed: 12/21/2022]
Abstract
This study aimed to systematically identify, map out, and describe geographical information systems (GIS)-based approaches that have been employed to measure children's neighborhood geographies for physical activity behaviors. Forty studies were included, most were conducted in the USA. Heterogeneity in GIS methods and measures was found. The majority of studies estimated children's environments using Euclidean or network buffers ranging from 100 m to 5 km. No singular approach to measuring children's physical activity geographies was identified as optimal. Geographic diversity in studies as well as increased use of measures of actual neighborhood exposure are needed. Improved consistency and transparency in reporting research methods is urgently required.
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Affiliation(s)
- Melody Smith
- School of Nursing, The University of Auckland, Auckland, New Zealand.
| | - Jianqiang Cui
- School of Environment and Science, Griffith University, Brisbane, Australia.
| | - Erika Ikeda
- Centre for Diet & Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
| | - Suzanne Mavoa
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
| | | | - Jinfeng Zhao
- School of Nursing, The University of Auckland, Auckland, New Zealand.
| | - Tiina E Rinne
- Active Life Lab, South-Eastern Finland University of Applied Sciences, Mikkeli, Finland.
| | - Niamh Donnellan
- School of Nursing, University of Auckland, Auckland, New Zealand.
| | - Marketta Kyttä
- Department of Built Environment, Aalto University, Espoo, Finland.
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30
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Investigating change in the food environment over 10 years in urban New Zealand: A longitudinal and nationwide geospatial study. Soc Sci Med 2020; 269:113522. [PMID: 33339682 DOI: 10.1016/j.socscimed.2020.113522] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 10/08/2020] [Accepted: 11/10/2020] [Indexed: 01/20/2023]
Abstract
BACKGROUND While it is likely that changing food environments have contributed to the rise in obesity rates, very few studies have explored historical trends in the food environment with little, if any, consideration at a nationwide level. This longitudinal, nationwide, and geospatial study aims to examine change over time in proximity to food environments in all urban areas of New Zealand from 2005 to 2015. METHOD This study used high quality food outlet data by area-level deprivation within the three largest urban areas of Auckland, Christchurch and Wellington. We hypothesise that distance and travel time by car to supermarkets and fast-food outlets will have decreased over time with the most notable decreases in distance and time occuring in the most deprived areas of urban New Zealand. Change in major chain "fast-food" and "supermarket" outlets as identified by Territorial Authorities between 2005 and 2015 was analysed through the use of multilevel regression models. RESULTS Findings show a decrease in distance and time to both fast-food outlets and supermarkets. The biggest decrease in distance for supermarkets was seen in the most deprived areas. CONCLUSION Our findings contrast and add to previous evidence to demonstrate how changes in the food environment are not uniform, varying by area-level deprivation and by city with more equitable access to supermarkets occurring over time.
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31
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Thornton LE, Lamb KE, White SR. The use and misuse of ratio and proportion exposure measures in food environment research. Int J Behav Nutr Phys Act 2020; 17:118. [PMID: 32957988 PMCID: PMC7507725 DOI: 10.1186/s12966-020-01019-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 09/07/2020] [Indexed: 01/06/2023] Open
Abstract
Background The food stores within residential environments are increasingly investigated as a possible mechanism driving food behaviours and health outcomes. Whilst increased emphasis is being placed on the type of study designs used and how we measure the outcomes, surprisingly little attention gets diverted to the measures of the food environment beyond calls for standardised approaches for food store coding and geographic scales of exposure. Food environments are a challenging concept to measure and model and the use of ratio and proportion measures are becoming more common in food environment research. Whilst these are seemingly an advance on single store type indicators, such as simply counting the number of supermarkets or fast food restaurants present, they have several limitations that do not appear to have been fully considered. Main body In this article we report on five issues related to the use of ratio and proportion food environment measures: 1) binary categorisation of food stores; 2) whether they truly reflect a more or less healthy food environment; 3) issues with these measures not reflecting the quantity of food stores; 4) difficulties when no stores are present; and 5) complications in statistical treatment and interpretation of ratio and proportion measures. Each of these issues are underappreciated in the literature to date and highlight that ratio and proportion measures need to be treated with caution. Conclusion Calls for the broader adoption of relative food environment measures may be misguided. Whilst we should continue to search for better ways to represent the complexity of food environments, ratio and proportion measures are unlikely to be the answer.
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Affiliation(s)
- Lukar E Thornton
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia.
| | - Karen E Lamb
- Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia
| | - Simon R White
- Medical Research Council (MRC) Biostatistics Unit, University of Cambridge, Cambridge, UK
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Almeida LFF, Novaes TG, Pessoa MC, do Carmo AS, Mendes LL, Ribeiro AQ. Socioeconomic Disparities in the Community Food Environment of a Medium-Sized City of Brazil. J Am Coll Nutr 2020; 40:253-260. [PMID: 32459572 DOI: 10.1080/07315724.2020.1755911] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Objective: The purpose of this ecological study was to characterize the community food environment according to the socioeconomic condition of census tracts (CTs) in the urban area of a medium-sized city of southeastern Brazil in 2016.Method: Food establishments were identified on the streets covered by raters and information about type was collected through objective assessment. Geocoding was carried out from address observed by raters. Food establishments were categorized into establishments with predominant sale of natural or minimally processed foods, mixed establishments, and establishments with predominant sale of ultra-processed foods. The distribution of the number of establishments, by category, was evaluated according to tertiles of per capita income of the CT. The kernel estimation was used to analyze the density of establishments by category. The spatial pattern of the categories of establishments was investigated using the univariate Ripley's K-function.Results: A total of 656 establishments were evaluated. In all, 11.1% had predominant sale of natural or minimally processed foods, 44.5% were mixed, and 44.4% had predominant sale of ultra-processed foods. The average of establishments with predominant sale of natural or minimally processed foods, of ultra-processed foods, and all categories increased according to the income of the CT. There was a clustering of all categories of establishments in high-income CTs downtown. However, peripheral and low-income CTs were composed of a higher number of mixed establishments or those with predominant sale of ultra-processed foods than establishments with predominant sale of natural or minimally processed foods.Conclusions: On average, the number of all categories of establishments increased according to the per capita income of the CT and were clustered in central and higher-income regions of the city. These findings may have practical implications for the development of public policies to increase the availability of healthy foods and to reduce the sale of unhealthy foods.
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Affiliation(s)
| | | | - Milene Cristine Pessoa
- Department of Nutrition, Nursing School, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Ariene Silva do Carmo
- Department of Nutrition, Nursing School, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.,Department of Nutrition and Health, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
| | - Larissa Loures Mendes
- Department of Nutrition, Nursing School, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Andréia Queiroz Ribeiro
- Department of Nutrition and Health, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
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Liu B, Widener M, Burgoine T, Hammond D. Association between time-weighted activity space-based exposures to fast food outlets and fast food consumption among young adults in urban Canada. Int J Behav Nutr Phys Act 2020; 17:62. [PMID: 32404175 PMCID: PMC7222540 DOI: 10.1186/s12966-020-00967-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 05/04/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Despite increased attention on retail food environments and fast food consumption, results from previous studies have been inconsistent. Variation in measurement of exposure to retail food environments and the context of the built environment are possible reasons for inconsistencies. The purpose of the current study is to examine the association between exposure to fast food environment and fast food consumption among young adults, and to explore possible associations between built environment and fast food consumption. METHODS We employed an observational, cross-sectional study design. Cross-sectional surveys were conducted in 2016 and 2017. In a sample of 591 young adults aged 16-30 years in five Canadian cities, we constructed and computed individual-level time-weighted number and ratio of fast food outlets in activity spaces derived from GPS trajectory data. Negative binomial regression models estimated the associations between exposure measures and frequency of fast food consumption (number of times consuming fast food meals in a seven-day period), controlling for built environment characterization and individual-level characteristics. RESULTS Significant positive associations were found between time-weighted number of fast food outlets and count of fast food meals consumed per week in models using a radius of 500 m (IRR = 1.078, 95% CI: 0.999, 1.163), 1 km (IRR = 1.135, 95% CI: 1.024, 1.259), or 1.5 km (IRR = 1.138, 95% CI: 1.004, 1.289) around GPS tracks, when generating activity spaces. However, time-weighted ratio of fast food outlets was only significantly associated with count of fast food meals consumed when a radius of 500 m is used (IRR = 1.478, 95% CI: 1.032, 2.123). The time-weighted Active Living Environment Index with Transit measure was significantly negatively related to count of fast food meals consumed across all models. CONCLUSIONS Our study demonstrated associations of time-weighted activity space-based exposure to fast food outlets and fast food consumption frequency in a sample of young adults in urban Canada, and provides evidence of the association between context of built environment and fast food consumption, furthering discussion on the utility of individual-level, activity space-based data and methods in food environment research. These results imply that both food retail composition and activity spaces in urban areas are important factors to consider when studying diets.
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Affiliation(s)
- Bochu Liu
- Department of Geography and Planning, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada.
| | - Michael Widener
- Department of Geography and Planning, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada
| | - Thomas Burgoine
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - David Hammond
- School of Public Health and Health Systems, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada
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Introducing the Facility List Coder: A New Dataset/Method to Evaluate Community Food Environments. DATA 2020. [DOI: 10.3390/data5010023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Community food environments have been shown to be important determinants to explain dietary patterns. This data descriptor describes a typical dataset obtained after applying the Facility List Coder (FLC), a new tool to asses community food environments that was validated and presented. The FLC was developed in Python 3.7 combining GIS analysis with standard data techniques. It offers a low-cost, scalable, efficient, and user-friendly way to indirectly identify community nutritional environments in any context. The FLC uses the most open access information to identify the facilities (e.g., convenience food store, bar, bakery, etc.) present around a location of interest (e.g., school, hospital, or university). As a result, researchers will have a comprehensive list of facilities around any location of interest allowing the assessment of key research questions on the influence of the community food environment on different health outcomes (e.g., obesity, physical inactivity, or diet quality). The FLC can be used either as a main source of information or to complement traditional methods such as store census and official commercial lists, among others.
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Open Campus Policies: How Built, Food, Social, and Organizational Environments Matter for Oregon's Public High School Students' Health. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17020469. [PMID: 31936808 PMCID: PMC7013906 DOI: 10.3390/ijerph17020469] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 01/01/2020] [Accepted: 01/04/2020] [Indexed: 11/17/2022]
Abstract
Open campus policies that grant access to the off-campus food environment may influence U.S. high school students’ exposure to unhealthy foods, yet predictors of these policies are unknown. Policy holding and built (walkability), food (access to grocery stores), social (school-to-neighborhood demographic similarity), and organizational (policy holding of neighboring schools) environment data were collected for 200 Oregon public high schools. These existing data were derived from the Oregon School Board Association, WalkScore.com, the 2010 Decennial Census, the 2010–2014 American Community Survey, the Supplemental Nutrition Assistance Program, TDLinex, Nielson directories, the U.S. Department of Education, the National Center for Education Statistics, and the Common Core of Data. Most (67%) of Oregon public high schools have open campus policies. Logistic regression analyses modeled open campus policy holding as a function of built, food, social, and organizational environment influences. With health and policy implications, the results indicate that the schools’ walkability, food access, and extent of neighboring open campus policy-schools are significantly associated with open campus policy holding in Oregon.
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Arcila-Agudelo AM, Muñoz-Mora JC, Farran-Codina A. Validity and Reliability of the Facility List Coder, a New Tool to Evaluate Community Food Environments. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16193578. [PMID: 31557810 PMCID: PMC6801652 DOI: 10.3390/ijerph16193578] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 09/21/2019] [Accepted: 09/23/2019] [Indexed: 11/20/2022]
Abstract
A community food environment plays an essential role in explaining the healthy lifestyle patterns of its community members. However, there is a lack of compelling quantitative approaches to evaluate these environments. This study introduces and validates a new tool named the facility list coder (FLC), whose purpose is to assess food environments based on data sources and classification algorithms. Using the case of Mataró (Spain), we randomly selected 301 grids areas (100 m2), in which we conducted street audits in order to physically identify all the facilities by name, address, and type. Then, audit-identified facilities were matched with those automatically-identified and were classified using the FLC to determine its quality. Our results suggest that automatically-identified and audit-identified food environments have a high level of agreement. The intra-class correlation coefficient (ICC) estimates and their respective 95% confidence intervals for the overall sample yield the result “excellent” (ICC ≥ 0.9) for the level of reliability of the FLC.
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Affiliation(s)
- Ana María Arcila-Agudelo
- Department of Nutrition, Food Science, and Gastronomy, XaRTA–INSA, Faculty of Pharmacy, University of Barcelona, Av. Prat de la Riba, Campus de l’Alimentació de Torribera, 171, Santa Coloma de Gramenet, E-08921 Barcelona, Spain;
| | - Juan Carlos Muñoz-Mora
- Department of Economics, Universidad EAFIT, Carrera 49, N 7 sur 50, Medellín 050024, Antioquia, Colombia;
| | - Andreu Farran-Codina
- Department of Nutrition, Food Science, and Gastronomy, XaRTA–INSA, Faculty of Pharmacy, University of Barcelona, Av. Prat de la Riba, Campus de l’Alimentació de Torribera, 171, Santa Coloma de Gramenet, E-08921 Barcelona, Spain;
- Correspondence:
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Assessing the Retail Food Environment in Madrid: An Evaluation of Administrative Data against Ground Truthing. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16193538. [PMID: 31546670 PMCID: PMC6801710 DOI: 10.3390/ijerph16193538] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 09/13/2019] [Accepted: 09/19/2019] [Indexed: 12/30/2022]
Abstract
Previous studies have suggested that European settings face unique food environment issues; however, retail food environments (RFE) outside Anglo-Saxon contexts remain understudied. We assessed the completeness and accuracy of an administrative dataset against ground truthing, using the example of Madrid (Spain). Further, we tested whether its completeness differed by its area-level socioeconomic status (SES) and population density. First, we collected data on the RFE through the ground truthing of 42 census tracts. Second, we retrieved data on the RFE from an administrative dataset covering the entire city (n = 2412 census tracts), and matched outlets using location matching and location/name matching. Third, we validated the administrative dataset against the gold standard of ground truthing. Using location matching, the administrative dataset had a high sensitivity (0.95; [95% CI = 0.89, 0.98]) and positive predictive values (PPV) (0.79; [95% CI = 0.70, 0.85]), while these values were substantially lower using location/name matching (0.55 and 0.45, respectively). Accuracy was slightly higher using location/name matching (k = 0.71 vs 0.62). We found some evidence for systematic differences in PPV by area-level SES using location matching, and in both sensitivity and PPV by population density using location/name matching. Administrative datasets may offer a reliable and cost-effective source to measure retail food access; however, their accuracy needs to be evaluated before using them for research purposes.
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A Systematic Review on Socioeconomic Differences in the Association between the Food Environment and Dietary Behaviors. Nutrients 2019; 11:nu11092215. [PMID: 31540267 PMCID: PMC6769523 DOI: 10.3390/nu11092215] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 09/06/2019] [Accepted: 09/09/2019] [Indexed: 12/25/2022] Open
Abstract
Little is known about socioeconomic differences in the association between the food environment and dietary behavior. We systematically reviewed four databases for original studies conducted in adolescents and adults. Food environments were defined as all objective and perceived aspects of the physical and economic food environment outside the home. The 43 included studies were diverse in the measures used to define the food environment, socioeconomic position (SEP) and dietary behavior, as well as in their results. Based on studies investigating the economic (n = 6) and school food environment (n = 4), somewhat consistent evidence suggests that low SEP individuals are more responsive to changes in food prices and benefit more from healthy options in the school food environment. Evidence for different effects of availability of foods and objectively measured access, proximity and quality of food stores on dietary behavior across SEP groups was inconsistent. In conclusion, there was no clear evidence for socioeconomic differences in the association between food environments and dietary behavior, although a limited number of studies focusing on economic and school food environments generally observed stronger associations in low SEP populations. (Prospero registration: CRD42017073587)
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Camargo DFM, Belon AP, Marín-León L, Souza BFDNJD, Pérez-Escamilla R, Segall-Corrêa AM. Comparing food environment and food purchase in areas with low and high prevalence of obesity: data from a mapping, in-store audit, and population-based survey. CAD SAUDE PUBLICA 2019; 35:e00247218. [PMID: 31508702 DOI: 10.1590/0102-311x00247218] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 03/22/2019] [Indexed: 11/21/2022] Open
Abstract
Our study aimed to compare key aspects of the food environment in two low-income areas in the city of Campinas, São Paulo State, Brazil: one with low and the other with high prevalence of obesity. We compared the availability of retail food establishments, the types of food sold, and the residents' eating habits. Demographic and socioeconomic data and eating habits were obtained from a population-based health survey. We also analyzed local food environment data collected from remote mapping of the retail food establishments and audit of the foods sold. For comparison purposes, the areas were selected according to obesity prevalence (body mass index - BMI ≥ 30kg/m²), defined as low prevalence (< 25%) and high prevalence (> 45%). Only 18 out of the 150 points of sale for food products sold fruits and vegetables across the areas. Areas with high obesity prevalence had more grocery stores and shops specialized in fruits and vegetables, as well as more supermarkets that sold fruits and vegetables. With less schooling, residents in the areas with high obesity prevalence reported purchasing food more often in supermarket chains and specialized shops with fruits and vegetables, although they consumed more sodas when compared with residents of areas with low obesity prevalence. Our results suggest interventions in low-income areas should consider the diverse environmental contexts and the interaction between schooling and food purchase behaviors in settings less prone to healthy eating.
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Affiliation(s)
| | | | - Leticia Marín-León
- Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, Brasil
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Pinho MGM, Mackenbach JD, Charreire H, Oppert JM, Rutter H, Beulens JWJ, Brug J, Lakerveld J. Comparing Different Residential Neighborhood Definitions and the Association Between Density of Restaurants and Home Cooking Among Dutch Adults. Nutrients 2019; 11:E1796. [PMID: 31382624 PMCID: PMC6722945 DOI: 10.3390/nu11081796] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 07/31/2019] [Accepted: 08/01/2019] [Indexed: 11/16/2022] Open
Abstract
The definition of neighborhoods as areas of exposure to the food environment is a challenge in food environment research. We aimed to test the association of density of restaurants with home cooking using four different definitions of residential neighborhoods. We also tested effect modification by age, length of residency, education, and income. This innovative cross-sectional study was conducted in the Netherlands (N = 1245 adults). We calculated geographic information system-based measures of restaurant density using residential administrative neighborhood boundaries, 800 m and 1600 m buffers around the home and respondents' self-defined boundaries (drawn by the respondents on a map of their residential area). We used adjusted Poisson regression to test associations of restaurant density (tertiles) and the outcome "weekly consumption of home-cooked meals" (six to seven as compared to five days per week (day/week) or fewer). Most respondents reported eating home-cooked meals for at least 6 day/week (74.2%). Regardless of the neighborhood definition used, no association between food environment and home cooking was observed. No effect modification was found. Although exposure in terms of density of restaurants was different according to the four different neighborhood definitions, we found no evidence that the area under study influences the association between density of restaurants and home cooking among Dutch adults.
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Affiliation(s)
- Maria Gabriela M Pinho
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands.
| | - Joreintje D Mackenbach
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands
| | - Hélène Charreire
- Université Paris Est Créteil (UPEC), LabUrba, UPEC, 61 Avenue du Général de Gaulle, 94010 Créteil, France
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, 74 Rue Marcel Cachin, 93017 Bobigny, France
| | - Jean-Michel Oppert
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, 74 Rue Marcel Cachin, 93017 Bobigny, France
- Department of Nutrition, Institute of Cardiometabolism and Nutrition, Sorbonne Université, Pitié-Salpêtrière Hospital, 47-83 Boulevard de l'Hôpital, 75013 Paris, France
| | - Harry Rutter
- Department of Social and Policy Sciences, University of Bath, Bath BA2 7AY, UK
| | - Joline W J Beulens
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Huispost Str. 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands
| | - Johannes Brug
- Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands
- National Institute for Public Health and the Environment, Antoni van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands
| | - Jeroen Lakerveld
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Huispost Str. 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands
- Faculty of Geosciences, Utrecht University, Vening Meinesz building A, Princetonlaan 8a, 3584 CB Utrecht, The Netherlands
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Blow J, Gregg R, Davies IG, Patel S. Type and density of independent takeaway outlets: a geographical mapping study in a low socioeconomic ward, Manchester. BMJ Open 2019; 9:e023554. [PMID: 31340954 PMCID: PMC6661625 DOI: 10.1136/bmjopen-2018-023554] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVES The socioeconomic disparity in childhood and early adult obesity prevalence has been well characterised. Takeaway outlets may cluster in lower socioeconomic areas and their proximity to schools is of concern. This study aimed to map takeaway food outlets, characterise takeaway types and their proximity to educational institutions within a low socioeconomic ward in Manchester. DESIGN The Rusholme ward and a 2 km Euclidean buffer were included as the study area. Local authority Environmental Health data were used to map the takeaway outlets, using QGIS V.2.18.0 (OPENGIS.ch LLC, Einsiedeln, Switzerland). The types of takeaway outlets and major roads were included. Number of outlets within a 400 m Euclidean walking buffer of educational institutions were mapped. SETTING Rusholme, Manchester, UK. RESULTS Within the study area, 202 takeaway food outlets were identified and mapped as cluster points. Of these, 62.3% are located on major (A and B) roads, while the remaining outlets were located on minor roads. The majority (57.4%) of takeaway outlets sold similar items (fried chicken, burgers, pizzas, kebabs), with the remainder offering more diverse menus. Of the 53 schools, colleges and universities within the study area, 28 (52.8%) had 1-5 takeaway food outlets within 400 m, 9 (17.0%) had 6-10 outlets; 4 (7.5%) more than 11 outlets with 12 (22.6%) having zero outlets within 400 m. CONCLUSION Within this low socioeconomic area, there was a high concentration of takeaway food outlets, predominantly along major roads and in easy walking distance of educational establishments with the majority offering similar foods. In addition, a high proportion of these outlets were in easy walking distance of educational establishments. Public health policy needs to consider the implications of current takeaway food outlets and not just the proliferation of these outlets with current planning laws.
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Affiliation(s)
- Jennifer Blow
- Health Professionals, Faculty of Health Psychology and Social Care, Manchester Metropolitan University, Manchester, UK
| | - Rebecca Gregg
- Health Professionals, Faculty of Health Psychology and Social Care, Manchester Metropolitan University, Manchester, UK
| | - Ian G Davies
- Education, Health and Community, Liverpool John Moores University, Liverpool, UK
| | - Sumaiya Patel
- Health Professionals, Faculty of Health Psychology and Social Care, Manchester Metropolitan University, Manchester, UK
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Hobbs M, Green M, Roberts K, Griffiths C, McKenna J. Reconsidering the relationship between fast-food outlets, area-level deprivation, diet quality and body mass index: an exploratory structural equation modelling approach. J Epidemiol Community Health 2019; 73:861-866. [PMID: 31171581 DOI: 10.1136/jech-2018-211798] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 03/14/2019] [Accepted: 04/21/2019] [Indexed: 11/04/2022]
Abstract
BACKGROUND Internationally, the prevalence of adults with obesity is a major public health concern. Few studies investigate the explanatory pathways between fast-food outlets and body mass index (BMI). We use structural equation modelling to explore an alternative hypothesis to existing research using area-level deprivation as the predictor of BMI and fast-food outlets and diet quality as mediators. METHODS Adults (n=7544) from wave II of the Yorkshire Health Study provided self-reported diet, height and weight (used to calculate BMI). Diet quality was based on sugary drinks, wholemeal (wholegrain) bread and portions of fruit and vegetables. Fast-food outlets were mapped using the Ordnance Survey Points of Interest within 2 km radial buffers around home postcode which were summed to indicate availability. Age (years), gender (female/male) and long-standing health conditions (yes/no) were included as covariates. RESULTS There was little evidence linking fast-food outlets to diet or BMI. An independent association between fast-food outlet availability and BMI operated counterintuitively and was small in effect. There was also little evidence of mediation between fast-food outlet availability and BMI. However, there was more evidence that area-level deprivation was associated with increased BMI, both as an independent effect and through poorer diet quality. CONCLUSION This exploratory study offers a first step for considering complexity and pathways linking fast-food outlets, area-level deprivation, diet quality and BMI. Research should respond to and build on the hypothesised pathways and our simple framework presented within our study.
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Affiliation(s)
- Matthew Hobbs
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand .,Carnegie School of Sport, Leeds Beckett University, Leeds, UK
| | - Mark Green
- Geography and Planning, University of Liverpool, Liverpool, UK
| | - Kath Roberts
- Public Health Section, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | | | - Jim McKenna
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK
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Bivoltsis A, Trapp G, Knuiman M, Hooper P, Ambrosini GL. The evolution of local food environments within established neighbourhoods and new developments in Perth, Western Australia. Health Place 2019; 57:204-217. [PMID: 31103776 DOI: 10.1016/j.healthplace.2019.04.011] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 03/01/2019] [Accepted: 04/26/2019] [Indexed: 10/26/2022]
Abstract
Temporal changes in the location of food outlets can result in disparities in the availability and access of food across geographic areas, contributing to health inequalities. This study used mixed linear models to investigate how the location of food outlets around the home evolved over time with respect to area-level socio-economic status (SES) and urban design within established neighbourhoods and new residential developments. Food outlet data (supermarket/greengrocers, convenience stores, café restaurants and takeaway/fast food) were sourced from commercial database listings (SENSIS Pty. Ltd.) in 2004, 2006, 2007, and 2011. Using 2468 addresses from the RESIDential Environments Project (RESIDE), in Perth, Western Australia (WA), a count of each food outlet type and percentage of healthy food outlets within a 1.6 km road network buffer around the home, along with the road network distance to nearest food outlet were generated relative to each address at each time point. Proximity to and count of all food outlets increased over time in both new developments and established neighbourhoods. However, unhealthy food outlets were always in greater numbers and proximity to the home. The percentage of healthy food outlets was significantly greater in established neighbourhoods compared to new developments at all four time points. There were significantly more food outlets, and within closer proximity to the home, in established neighbourhoods compared to new developments at each time point. In established neighbourhoods, there were more convenience stores, takeaway/fast food and café restaurants, a lower percentage of healthy food outlets, and closer proximity to convenience stores in lower compared to high SES areas. In new developments there were significantly less supermarket/greengrocers, a lower percentage of healthy food outlets and greater proximity to takeaway/fast food and café restaurants in low compared to high SES areas. New developments designed according to the WA government's "Liveable Neighbourhoods Community Design Guidelines" policy had significantly more of all food outlets compared to other new developments. As such, people living in new developments, and low SES areas of Perth, may be disadvantaged with poorer access to healthy food outlets and greater exposure to unhealthy food outlets. Future urban planning and policy should focus on providing incentives that support the early development of supermarkets and healthy food outlets within new developments and low SES areas of Perth.
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Affiliation(s)
- Alexia Bivoltsis
- School of Population and Global Health, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009, Australia.
| | - Gina Trapp
- School of Population and Global Health, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009, Australia; Telethon Kids Institute, PO Box 855, West Perth, Western Australia, 6872, Australia.
| | - Matthew Knuiman
- School of Population and Global Health, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009, Australia.
| | - Paula Hooper
- School of Agriculture and Environment and the School of Human Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009, Australia.
| | - Gina Leslie Ambrosini
- School of Population and Global Health, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia, 6009, Australia.
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Wilkins E, Morris M, Radley D, Griffiths C. Methods of measuring associations between the Retail Food Environment and weight status: Importance of classifications and metrics. SSM Popul Health 2019; 8:100404. [PMID: 31245526 PMCID: PMC6582068 DOI: 10.1016/j.ssmph.2019.100404] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 03/26/2019] [Accepted: 04/24/2019] [Indexed: 12/29/2022] Open
Abstract
Despite considerable research, evidence supporting associations between the 'Retail Food Environment' (RFE) and obesity remains mixed. Differences in the methods used to measure the RFE may explain this heterogeneity. Using data on a large (n = 10,111) sample of adults from the Yorkshire Health Study (UK), we modelled cross-sectional associations between the RFE and weight status using (i) multiple definitions of 'Fast Food', 'Convenience' and 'Supermarkets' and (ii) multiple RFE metrics, identified in a prior systematic review to be common in the literature. Both the choice of outlet definition and the choice of RFE metric substantively impacted observed associations with weight status. Findings differed in relation to statistical significance, effect sizes, and directions of association. This study provides novel evidence that the diversity of RFE measurement methods is contributing to heterogeneous study findings and conflicting policy messages. Greater attention is needed when selecting and communicating RFE measures in research.
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Affiliation(s)
- Emma Wilkins
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK
| | - Michelle Morris
- Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds, UK
| | - Duncan Radley
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK
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Wilkins E, Radley D, Morris M, Hobbs M, Christensen A, Marwa WL, Morrin A, Griffiths C. A systematic review employing the GeoFERN framework to examine methods, reporting quality and associations between the retail food environment and obesity. Health Place 2019; 57:186-199. [PMID: 31060018 DOI: 10.1016/j.healthplace.2019.02.007] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 01/24/2019] [Accepted: 02/26/2019] [Indexed: 11/17/2022]
Abstract
This systematic review quantifies methods used to measure the 'retail food environment' (RFE), appraises the quality of methodological reporting, and examines associations with obesity, accounting for differences in methods. Only spatial measures of the RFE, such as food outlet proximity were included. Across the 113 included studies, methods for measuring the RFE were extremely diverse, yet reporting of methods was poor (average reporting quality score: 58.6%). Null associations dominated across all measurement methods, comprising 76.0% of 1937 associations in total. Outcomes varied across measurement methods (e.g. narrow definitions of 'supermarket': 20.7% negative associations vs 1.7% positive; broad definitions of 'supermarket': 9.0% negative associations vs 10.4% positive). Researchers should report methods more clearly, and should articulate findings in the context of the measurement methods employed.
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Affiliation(s)
- Emma Wilkins
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
| | - Duncan Radley
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK
| | - Michelle Morris
- Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds, UK
| | - Matthew Hobbs
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK; GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand
| | | | | | - Adele Morrin
- Carnegie School of Sport, Leeds Beckett University, Leeds, UK
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Narciso J, Silva AJ, Rodrigues V, Monteiro MJ, Almeida A, Saavedra R, Costa AM. Behavioral, contextual and biological factors associated with obesity during adolescence: A systematic review. PLoS One 2019; 14:e0214941. [PMID: 30958850 PMCID: PMC6453458 DOI: 10.1371/journal.pone.0214941] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 03/22/2019] [Indexed: 02/06/2023] Open
Abstract
INTRODUCTION/OBJECTIVE Adolescence is a critical period for the development of obesity. Obesity arises from a complex interaction between several factors, which are not yet fully understood. Therefore, the purpose of this review was to identify and assess the peer-reviewed scientific literature on the behavioral, contextual and biological factors associated with obesity in adolescents. METHODS PubMed and Scopus were systematically searched to identify prospective cohort studies concerning the relation between behavioral, contextual and biological factors and obesity in adolescents aged 10 to 18 years. RESULTS 40 studies published between the year 2000 and 2018 were included. A positive consistent association between genetic factors and obesity during adolescence was found. Also, there is evidence to support the association between socioeconomic status and obesity. There was conflicting evidence for the contribution of dietary intake, physical activity, sedentary behavior, sleep, food store environment, school food environment. For the remaining factors no associations were found, or no conclusions could be drawn due to the limited number of studies identified. CONCLUSIONS Further prospective studies that assess multiple obesity determinants simultaneously and use state-of-art measures are warranted to aid in the development of effective strategies and interventions to prevent obesity during adolescence.
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Affiliation(s)
- Janine Narciso
- Department of Sports Sciences, University of Beira Interior, Covilhã, Portugal
| | - António José Silva
- Department of Sports, Exercise and Health Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
- Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, Vila Real, Portugal
| | - Vitor Rodrigues
- Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, Vila Real, Portugal
- Superior School of Health, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
| | - Maria João Monteiro
- Superior School of Health, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
- Center for Health Technology and Services Research, CINTESIS, Porto, Portugal
| | - António Almeida
- Superior School of Health, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
| | - Raquel Saavedra
- Department of Sports, Exercise and Health Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
| | - Aldo Matos Costa
- Department of Sports Sciences, University of Beira Interior, Covilhã, Portugal
- Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, Vila Real, Portugal
- Health Sciences Research Center, CICS-UBI, Covilhã, Portugal
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Hobbs M, Griffiths C, Green M, Christensen A, McKenna J. Examining longitudinal associations between the recreational physical activity environment, change in body mass index, and obesity by age in 8864 Yorkshire Health Study participants. Soc Sci Med 2019; 227:76-83. [DOI: 10.1016/j.socscimed.2018.06.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 05/14/2018] [Accepted: 06/23/2018] [Indexed: 11/16/2022]
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Shen Y, Clarke P, Gomez-Lopez IN, Hill AB, Romero DM, Goodspeed R, Berrocal VJ, Vydiswaran VGV, Veinot TC. Using social media to assess the consumer nutrition environment: comparing Yelp reviews with a direct observation audit instrument for grocery stores. Public Health Nutr 2019; 22:257-264. [PMID: 30406742 PMCID: PMC10260597 DOI: 10.1017/s1368980018002872] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2018] [Revised: 09/21/2018] [Accepted: 09/25/2018] [Indexed: 11/06/2022]
Abstract
OBJECTIVE To examine the feasibility of using social media to assess the consumer nutrition environment by comparing sentiment expressed in Yelp reviews with information obtained from a direct observation audit instrument for grocery stores. DESIGN Trained raters used the Nutrition Environment Measures Survey in Stores (NEMS-S) in 100 grocery stores from July 2015 to March 2016. Yelp reviews were available for sixty-nine of these stores and were retrieved in February 2017 using the Yelp Application Program Interface. A sentiment analysis was conducted to quantify the perceptions of the consumer nutrition environment in the review text. Pearson correlation coefficients (ρ) were used to compare NEMS-S scores with Yelp review text on food availability, quality, price and shopping experience. SETTING Detroit, Michigan, USA.ParticipantsNone. RESULTS Yelp reviews contained more comments about food availability and the overall shopping experience than food price and food quality. Negative sentiment about food prices in Yelp review text and the number of dollar signs on Yelp were positively correlated with observed food prices in stores (ρ=0·413 and 0·462, respectively). Stores with greater food availability were rated as more expensive on Yelp. Other aspects of the food store environment (e.g. overall quality and shopping experience) were captured only in Yelp. CONCLUSIONS While Yelp cannot replace in-person audits for collecting detailed information on the availability, quality and cost of specific food items, Yelp holds promise as a cost-effective means to gather information on the overall cost, quality and experience of food stores, which may be relevant for nutrition outcomes.
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Affiliation(s)
- Ying Shen
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Philippa Clarke
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
- Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI48104, USA
| | - Iris N Gomez-Lopez
- Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI48104, USA
| | - Alex B Hill
- Detroit Food Map Initiative, Detroit, MI, USA
| | - Daniel M Romero
- School of Information, University of Michigan, Ann Arbor, MI, USA
| | - Robert Goodspeed
- Taubman College of Architecture and Urban Planning, University of Michigan, Ann Arbor, MI, USA
| | | | - VG Vinod Vydiswaran
- School of Information, University of Michigan, Ann Arbor, MI, USA
- Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI, USA
| | - Tiffany C Veinot
- School of Information, University of Michigan, Ann Arbor, MI, USA
- Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, MI, USA
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Costa BVDL, Freitas PPD, Menezes MCD, Guimarães LMF, Ferreira LDF, Alves MDSC, Lopes ACS. [Food environment: validation of a method for measurement and characterization in the territory with the Health Academy Program]. CAD SAUDE PUBLICA 2018; 34:e00168817. [PMID: 30208180 DOI: 10.1590/0102-311x00168817] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 04/18/2018] [Indexed: 11/22/2022] Open
Abstract
The study aimed to verify the validity of secondary data in the investigation of the food environment and to analyze the characteristics of the community environment and consumers in territories covered by a health promotion service. This was an ecological study in 18 units of the Health Academy Program in Belo Horizonte, Minas Gerais, Brazil, selected by simple cluster sampling. Validation of the establishments marketing fruits and vegetables, obtained from public databases, was done via telephone contact, Google Street View, and on-site audit. The following variables were investigated in the community food environment: type and location of the establishment; consumer's environment: availability, variety, price, and advertising of fruits and vegetables; availability and variety of ultra-processed foods; and hygienic and sanitary conditions. The access to healthy foods index was used to measure access to these foods. The on-site audit revealed weak concordance (45.7%) with the secondary databases. Of the 298 establishments, the majority were bulk grocery stores and open-air markets (61.3%), which showed the highest availability of healthy foods, but also marketed large amounts of ultra-processed foods (60.7%). One-third of the establishments showed substandard hygienic and sanitary conditions. The secondary databases showed low validity, emphasizing the need to audit the establishments. The establishments also showed a striking presence of ultra-processed foods and poor hygiene and sanitation.
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50
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Bivoltsis A, Cervigni E, Trapp G, Knuiman M, Hooper P, Ambrosini GL. Food environments and dietary intakes among adults: does the type of spatial exposure measurement matter? A systematic review. Int J Health Geogr 2018; 17:19. [PMID: 29885662 PMCID: PMC5994245 DOI: 10.1186/s12942-018-0139-7] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Accepted: 06/01/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The relationships between food environments and dietary intake have been assessed via a range of methodologically diverse measures of spatial exposure to food outlets, resulting in a largely inconclusive body of evidence, limiting informed policy intervention. OBJECTIVE This systematic review aims to evaluate the influence of methodological choice on study outcomes by examining the within-study effect of availability (e.g., counts) versus accessibility (e.g., proximity) spatial exposure measures on associations with diet. METHODS (PROSPERO registration: CRD42018085250). PubMed, Web of Science, Scopus and ScienceDirect databases were searched for empirical studies from 1980 to 2017, in the English language, involving adults and reporting on the statistical association between a dietary outcome and spatial exposure measures of both availability and accessibility. Studies were appraised using an eight-point quality criteria with a narrative synthesis of results. RESULTS A total of 205 associations and 44 relationships (i.e., multiple measures of spatial exposure relating to a particular food outlet type and dietary outcome) were extracted from 14 eligible articles. Comparative measures were dominated by counts (availability) and proximity (accessibility). Few studies compared more complex measures and all counts were derived from place-based measures of exposure. Sixteen of the 44 relationships had a significant effect involving an availability measure whilst only 8 had a significant effect from an accessibility measure. The largest effect sizes in relationships were mostly for availability measures. After stratification by scale, availability measure had the greatest effect size in 139 of the 176 pairwise comparisons. Of the 33% (68/205) of associations that reached significance, 53/68 (78%) were from availability measures. There was no relationship between study quality and reported study outcomes. CONCLUSIONS The limited evidence suggests that availability measures may produce significant and greater effect sizes than accessibility measures. However, both availability and accessibility measures may be important concepts of spatial exposure depending on the food outlet type and dietary outcome examined. More studies reporting on multi-method effects are required to differentiate findings by the type of spatial exposure assessment and build an evidence base regarding the appropriateness and robustness of measures under different circumstances.
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Affiliation(s)
- Alexia Bivoltsis
- School of Population and Global Health, The University of Western Australia, M451, 35 Stirling Highway, Crawley, Perth, WA, 6009, Australia.
| | - Eleanor Cervigni
- School of Human Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
| | - Gina Trapp
- School of Population and Global Health, The University of Western Australia, M451, 35 Stirling Highway, Crawley, Perth, WA, 6009, Australia.,Telethon Kids Institute, The University of Western Australia, PO Box 855, West Perth, WA, 6872, Australia
| | - Matthew Knuiman
- School of Population and Global Health, The University of Western Australia, M451, 35 Stirling Highway, Crawley, Perth, WA, 6009, Australia
| | - Paula Hooper
- School of Agriculture and Environment and the School of Human Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
| | - Gina Leslie Ambrosini
- School of Population and Global Health, The University of Western Australia, M451, 35 Stirling Highway, Crawley, Perth, WA, 6009, Australia
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