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Pineda E, Stockton J, Mindell JS. The Retail Food Environment Index and its association with dietary patterns, body mass index, and socioeconomic position: A multilevel assessment in Mexico. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003819. [PMID: 39388394 PMCID: PMC11466391 DOI: 10.1371/journal.pgph.0003819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 09/18/2024] [Indexed: 10/12/2024]
Abstract
In Mexico, 75% of the population are affected by overweight or obesity, and the availability and affordability of high-calorie-dense foods and beverages are high. This study tested the association between the retail food environment index (RFEI), dietary patterns, body mass index (BMI), and socioeconomic position (SEP) in Mexico. Cross-sectional diet, health, and sociodemographic population-based secondary data analyses were conducted. The RFEI was calculated by dividing the total number of fast-food outlets and convenience stores by the total number of supermarkets and fruit and vegetable stores per census tract area. Associations between BMI, dietary patterns, SEP and the RFEI were tested using multilevel linear regression, including interactions of the RFEI with SEP, gender, and age. Living in neighbourhoods with a higher RFEI was associated with a 0.01kg/m2 higher BMI (β = 0.01, 95%CI: 0.0005, 0.02, p = 0.04), equivalent to a mean 0.046 weight gain for a 1.60m tall person per 10% higher RFEI. Unhealthy dietary patterns were more likely in neighbourhoods with a higher RFEI (β = 0.100, 95%CI: 0.03, 0.12, p = 0.001). Multilevel linear regression showed that lower SEP households had a higher RFEI compared to higher SEP households (β = 0.020, 95% CI: -0.006 to 0.04, p = 0.10). Generalised structural equation models revealed a graded relationship between RFEI and SEP, showing that lower SEP households were exposed to a higher RFEI (β = 0.060, 95% CI: 0.05 to 0.07, p < 0.001.) The study identified significant associations between higher proportions of fast-food outlets and convenience stores, higher BMI, and unhealthy dietary patterns. It was particularly evident that low-income populations are more likely to be exposed to obesogenic food environments.
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Affiliation(s)
- Elisa Pineda
- The George Institute for Global Health UK, London, United Kingdom
- School of Public Health, Imperial College London, London, United Kingdom
- Research Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Jemima Stockton
- Research Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Jennifer S. Mindell
- Research Department of Epidemiology and Public Health, University College London, London, United Kingdom
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Hobbs M, McLeod GFH, Mackenbach JD, Marek L, Wiki J, Deng B, Eggleton P, Boden JM, Bhubaneswor D, Campbell M, Horwood LJ. Change in the food environment and measured adiposity in adulthood in the Christchurch Health and development birth cohort, Aotearoa, New Zealand: A birth cohort study. Health Place 2023; 83:103078. [PMID: 37517383 DOI: 10.1016/j.healthplace.2023.103078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/11/2023] [Accepted: 06/21/2023] [Indexed: 08/01/2023]
Abstract
This study investigated associations between change in the food environment and change in measured body mass index (BMI) and waist circumference (WC) in the Christchurch Health and Development Study (CHDS) birth cohort. Our findings suggest that cohort members who experienced the greatest proportional change towards better access to fast food outlets had the slightly larger increases in BMI and WC. Contrastingly, cohort members who experienced the greatest proportional change towards shorter distance and better access to supermarkets had slightly smaller increases in BMI and WC. Our findings may help explain the changes in BMI and WC at a population level.
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Affiliation(s)
- Matthew Hobbs
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; The Cluster for Community and Urban Resilience (CURe), University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand.
| | - Geraldine F H McLeod
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Joreintje D Mackenbach
- Department of Epidemiology and Data Science, Amsterdam UMC Location Vrije University, Amsterdam, the Netherlands; Upstream Team, www.upstreamteam.nl, Amsterdam UMC, Amsterdam, the Netherlands
| | - Lukas Marek
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Jesse Wiki
- Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland - Waipapa Taumata Rau, Auckland, New Zealand
| | - Bingyu Deng
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Phoebe Eggleton
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Joseph M Boden
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Dhakal Bhubaneswor
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Malcolm Campbell
- Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; School of Earth and Environment, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - L John Horwood
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
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M H, N B, L M, J W, J K, R T, T R, J B, H T, S H, B M. The environment a young person grows up in is associated with their mental health: A nationwide geospatial study using the integrated data infrastructure, New Zealand. Soc Sci Med 2023; 326:115893. [PMID: 37119566 DOI: 10.1016/j.socscimed.2023.115893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 03/19/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND Mental health conditions often arise during adolescence, are multifaceted in aetiology, and may be related to the type of environment in which young people reside. This study used nationwide population-level data to investigate whether the environment a young person grows up in is associated with their mental health. METHOD Data were extracted from the Integrated Data Infrastructure (IDI), a large nationwide research repository, for 917,211 young people (aged 10-24 years) including sociodemographic and mental health data (i.e. emotional, behavioural, substance problems, and self-harm). Environmental data were sourced from the nationwide area-based Healthy Location Index (HLI), which has comprehensive data on the location of several health-constraining (i.e. fast-food outlets) and health-promoting features (i.e. physical activity facilities). Environments were classified as: i) health-promoting, ii) health-constraining, or iii) neither. Associations between the HLI and mental health were investigated using multi-level mixed effects logistic regression modelling. RESULTS Overall, there was evidence of an association between the environment a young person resided in and their mental health. Young people residing in health-constraining environments had higher odds of any mental health condition (Adjusted Odds Ratio (AOR) = 1.020 [1.001, 1.040]) and any emotional condition (AOR = 1.037 [1.012, 1.062]). Young people residing in health-promoting environments had lower odds of substance problems (AOR = 0.950 [0.905, 0.997]). There were no significant effects of the environment on behavioural conditions. CONCLUSION Our study utilises a large national sample of almost one million young people to confirm the importance of environmental determinants for mental health. It is possible that leverage points for improving the mental health of young people, and reducing the burden to the health system of mental health, can be sought in upstream environmental based interventions.
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Affiliation(s)
- Hobbs M
- Faculty of Health, University of Canterbury, Christchurch, Canterbury, New Zealand; GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - Bowden N
- Department of Women's and Children's Health, University of Otago, Dunedin, New Zealand
| | - Marek L
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Wiki J
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Kokaua J
- Va'a O Tautai - Centre for Pacific Health, Health Sciences, University of Otago, Dunedin, New Zealand
| | - Theodore R
- National Centre for Lifecourse Research, University of Otago, Dunedin, New Zealand
| | - Ruhe T
- Va'a O Tautai - Centre for Pacific Health, Health Sciences, University of Otago, Dunedin, New Zealand
| | - Boden J
- Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago Christchurch, New Zealand
| | - Thabrew H
- The Werry Centre, Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Hetrick S
- The Werry Centre, Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Milne B
- Centre of Methods and Policy Application in the Social Sciences, University of Auckland, Auckland, New Zealand
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Kalbus A, Ballatore A, Cornelsen L, Greener R, Cummins S. Associations between area deprivation and changes in the digital food environment during the COVID-19 pandemic: Longitudinal analysis of three online food delivery platforms. Health Place 2023; 80:102976. [PMID: 36758447 PMCID: PMC9899780 DOI: 10.1016/j.healthplace.2023.102976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 01/11/2023] [Accepted: 01/24/2023] [Indexed: 02/09/2023]
Abstract
Online food delivery services facilitate access to unhealthy foods and have proliferated during the COVID-19 pandemic. This study explores associations between neighbourhood deprivation and exposure to online food delivery services and changes in exposure by deprivation during the first year of the pandemic. Data on food outlets delivering to 661 postcode districts in London and the North of England in 2020 and 2021 were collected from three online delivery platforms. The association between area deprivation and overall exposure to online food delivery services was moderated by region, with evidence of a positive relationship between count of outlets and deprivation in the North of England, and a negative relationship in London. There was no association between area deprivation and growth of online food delivery services. Associations between neighbourhood deprivation and exposure to the digital food environment vary geographically. Consequently, policies aimed at the digital food environment need to be tailored to the local context.
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Affiliation(s)
- Alexandra Kalbus
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, WC1H 9SH, United Kingdom.
| | - Andrea Ballatore
- Department of Digital Humanities, King's College London, Strand, London, WC2R 2LS, United Kingdom
| | - Laura Cornelsen
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, WC1H 9SH, United Kingdom
| | - Robert Greener
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, WC1H 9SH, United Kingdom
| | - Steven Cummins
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, WC1H 9SH, United Kingdom
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Hobbs M, Stewart T, Marek L, Duncan S, Campbell M, Kingham S. Health-promoting and health-constraining environmental features and physical activity and sedentary behaviour in adolescence: a geospatial cross-sectional study. Health Place 2022; 77:102887. [DOI: 10.1016/j.healthplace.2022.102887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/04/2022]
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Dolton PJ, Tafesse W. Childhood obesity, is fast food exposure a factor? ECONOMICS AND HUMAN BIOLOGY 2022; 46:101153. [PMID: 35809404 DOI: 10.1016/j.ehb.2022.101153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 06/14/2022] [Accepted: 06/20/2022] [Indexed: 06/15/2023]
Abstract
Access to fast food has often been blamed for the rise in obesity which in turn has motivated policies to curb the spread of fast food. However, robust evidence in this area is scarce, particularly using data outside of the US. It is difficult to estimate a causal effect of fast food given spatial sorting and ever-present exposure. We investigate whether the residential access to fast food increased BMI of adolescents at a time when fast food restaurants started to open in the UK. The time period presents the study with large spatial and temporal differences in exposure as well as plausibly exogenous variation. We merge data on the location and timing of the first openings of all fast food outlets in the UK from 1968-1986, with data on objectively measured BMI from the 1970 British Cohort Survey. The relationship between adolescent BMI and the distance from the respondents' homes and time since opening, is studied using OLS and Instrumental Variables regression. We find that fast food exposure had no effect on BMI. Extensive robustness checks do not change our conclusion.
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Affiliation(s)
- Peter J Dolton
- Department of Economics, University of Sussex, Brighton BN1 9SL, UK; National Institute of Economic and Social Research, 2 Dean Trench Street, Smith Square, London SW1P 3HE, UK
| | - Wiktoria Tafesse
- Centre for Health Economics, University of York, Heslington, York YO10 5DD, UK..
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Cong N, Zhao A, Kwan MP, Yang J, Gong P. An Indicator Measuring the Influence of the Online Public Food Environment: An Analytical Framework and Case Study. Front Nutr 2022; 9:818374. [PMID: 35845771 PMCID: PMC9281549 DOI: 10.3389/fnut.2022.818374] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 05/23/2022] [Indexed: 12/03/2022] Open
Abstract
The online public food environment (OPFE) has had a considerable impact on people's lifestyles over the past decade; however, research on its exposure is sparse. The results of the existing research on the impact of the food environment on human health are inconsistent. In response to the lack of food elements in the definition of the food environment and the lack of a clear method to assess the health attributes and the impact degree of the food environment, we proposed a new analytical framework based on the latest disease burden research, combining the characteristics of China's current food environment, from the perspective of environmental science. We redefined the food environment and proposed that food and its physical space are two core elements of the food environment. Accordingly, we extracted four domains of characteristics to describe the basic components of the food environment. Using the sales records, we designed an approach by referring to the standard process of environmental health indicators, including the health attributes and the impact degree of the food environment, to measure the OPFE of takeaway food outlets. Further, we conducted a case study and extracted three domains of characteristics for more than 18,000 effective takeaway meals from 812 takeaway food outlets located in 10 administrative subdivisions in the Haidian District and Xicheng District of Beijing Municipality. The results showed that more than 60% of single meals sold by takeaway food outlets were considered as healthy, and only 15% of takeaway food outlets sold healthy meals exclusively. Additionally, there were significant differences in health effects among different types of food environments, and high-risk areas of different types of food environments can be spatially identified. Compared with the counting method in the availability of food environment, the proposed new approach can depict food environment characteristics not only in the macro-scale like the counting method but also in the meal-scale. The indicators could be useful for large-scale and long-term monitoring of food environmental changes due to their simple calculation and design depending on the food delivery platform.
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Affiliation(s)
- Na Cong
- Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, China
| | - Ai Zhao
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Mei-Po Kwan
- Department of Geography and Resource Management and Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Jun Yang
- Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, China
| | - Peng Gong
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, China
- Department of Geography and Earth Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- *Correspondence: Peng Gong
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Li M, Yuan F. Historical redlining and food environments: A study of 102 urban areas in the United States. Health Place 2022; 75:102775. [PMID: 35286901 DOI: 10.1016/j.healthplace.2022.102775] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 10/30/2021] [Accepted: 02/15/2022] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Unhealthy food environments are disproportionally concentrated in neighborhoods with clustering of racial/ethnic minorities and poverty. This disparity has been blamed, in part, on market self-regulation. This explanation risks overlooking past and current practices of racial segregation that have created and reinforced the obstacles blocking investments from food retailers in marginalized neighborhoods. We fill this gap by investigating how the long-term ramifications of redlining, discriminatory housing practices enacted by federal Home Owner Lending Corporation (HOLC) in the 1930s, has evolved generations later to disproportionally exposing neighborhoods to unhealthy food environments. METHODS We overlaid historical redlining maps over 2010 food environment observations at the census tract level to identify areas with less healthy food environments and to assess the historical context of those areas. For 11,651 census tracts within 102 U.S. urban areas, we described the healthiness of food environments as measured by the modified retail food environment index (mRFEI). Using hurdle models with random effects, we further examined the association between redlining housing practice and food environments. RESULTS The results indicate that historically redlined neighborhoods show a higher likelihood for unhealthy retail food environments even for census tracts with present-day economic and racial privilege. CONCLUSION The current evidence shows how structural discrimination manifested by unjust housing practices and racial residential segregation fueled an uneven food environment where minority neighborhoods disproportionally bore the brunt of restrictive food access. It highlights an urgent need to ameliorate patterns of housing inequality as a fix to unequal food environments.
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Affiliation(s)
- Min Li
- Department of Anthropology & Sociology, Western Carolina University, Cullowhee, 28723, NC, USA.
| | - Faxi Yuan
- Zachry Department of Civil Engineering, Texas A&M University, College Station, 77843, TX, USA
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Bauer JM, Nielsen KS, Hofmann W, Reisch LA. Healthy eating in the wild: An experience-sampling study of how food environments and situational factors shape out-of-home dietary success. Soc Sci Med 2022; 299:114869. [PMID: 35278829 DOI: 10.1016/j.socscimed.2022.114869] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 02/17/2022] [Accepted: 02/24/2022] [Indexed: 01/09/2023]
Abstract
Across many parts of the world, people increasingly eat out-of-home. Simultaneously, many people strive to eat a healthier diet, but it remains unclear to what extent and how eating out helps or hinders people in achieving their dietary goals. The present study investigated how characteristics of the physical micro-environment in out-of-home food outlets (e.g., cafeterias, supermarkets, and restaurants) influence the healthiness of food choices among a sample of German adults with a goal to eat healthier. We used an experience sampling method to obtain detailed information about people's motivation for selecting a specific food outlet and the outlet's micro-environment. We further asked for people's mood, visceral state, and thoughts during their food choice and obtained evaluations of food choices reported near their occurrence and in externally valid conditions. The data was collected via a mobile app over a period of six to eleven days between November and December of 2018 in Germany with a sample of 409 participants (nobs = 6447). We find that even health-conscious people select food outlets and their respective micro-environments based on short-term goals, such as ease, taste, and speed of a consumption episode rather than long-term health outcomes. Using multiple regression, we show that micro-environments that promote healthy food, make such food more appealing and easier to select facilitate healthy food choices. We further identify some of the psychological mechanisms through which the micro-environment can affect food choices, as well as how individual characteristics moderate the relationship between specific micro-environmental factors and goal success. Taken together, our findings suggest the opportunity for, and arguably also necessity of, reshaping food environments to better facilitate healthier choices and support public health in the face of increasing out-of-home food consumption and the adverse consequences of unhealthy diets.
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Affiliation(s)
- Jan M Bauer
- Department of Management, Society and Communication, Copenhagen Business School, Denmark.
| | | | | | - Lucia A Reisch
- El-Erian Institute for Behavioural Economics and Policy, Cambridge Judge Business School, University of Cambridge, UK.
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Loh VHY, Poelman M, Veitch J, McNaughton SA, Leech R, Timperio A. Neighbourhood food typologies, fast food outlet visitation and snack food purchasing among adolescents in Melbourne, Australia. Public Health Nutr 2022; 25:729-737. [PMID: 34629138 PMCID: PMC9991780 DOI: 10.1017/s1368980021004298] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 10/01/2021] [Accepted: 10/06/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Despite the increased attention on neighbourhood food environments and dietary behaviours, studies focusing on adolescents are limited. This study aims to characterise typologies of food environments surrounding adolescents and their associations with fast food outlet visitation and snack food purchasing to/from school. DESIGN The number of food outlets (supermarket; green grocers; butcher/seafood/deli; bakeries; convenience stores; fast food/takeaways; café and restaurants) within a 1 km buffer from home was determined using a Geographic Information System. Adolescents' self-reported frequency of fast food outlet visitation and snack food purchasing to/from school. Latent Profile Analysis was conducted to identify typologies of the food environment. Cross-sectional multilevel logistic regression analyses were conducted to examine the relationships between food typologies, fast food outlet visitations and snack food purchasing to/from school. SETTING Melbourne, Australia. PARTICIPANTS Totally, 410 adolescents (mean age= 15·5 (sd = 1·5) years). RESULTS Four distinct typologies of food outlets were identified: (1) limited variety/low number; (2) some variety/low number; (3) high variety/medium number and (4) high variety/high number. Adolescents living in Typologies 1 and 2 had three times higher odds of visiting fast food outlets ≥1 per week (Typology 1: OR = 3·71, 95 % CI 1·23, 11·19; Typology 2: OR = 3·65, 95 % CI 1·21, 10·99) than those living in Typology 4. No evidence of association was found between typologies of the food environments and snack food purchasing behaviour to/from school among adolescents. CONCLUSION Local government could emphasise an overall balance of food outlets when designing neighbourhoods to reduce propensity for fast food outlet visitation among adolescents.
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Affiliation(s)
- Venurs HY Loh
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong Waurn Ponds Campus, 75 Pidgons Road, Waurn Ponds, Geelong, VIC3216, Australia
| | - Maartje Poelman
- Chair Group Consumption and Healthy Lifestyles, Wageningen University & Research, Wageningen, The Netherlands
| | - Jenny Veitch
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong Waurn Ponds Campus, 75 Pidgons Road, Waurn Ponds, Geelong, VIC3216, Australia
| | - Sarah A McNaughton
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong Waurn Ponds Campus, 75 Pidgons Road, Waurn Ponds, Geelong, VIC3216, Australia
| | - Rebecca Leech
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong Waurn Ponds Campus, 75 Pidgons Road, Waurn Ponds, Geelong, VIC3216, Australia
| | - Anna Timperio
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong Waurn Ponds Campus, 75 Pidgons Road, Waurn Ponds, Geelong, VIC3216, Australia
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Clark S, Lomax N, Birkin M, Morris M. A foresight whole systems obesity classification for the English UK biobank cohort. BMC Public Health 2022; 22:349. [PMID: 35180877 PMCID: PMC8856870 DOI: 10.1186/s12889-022-12650-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 01/18/2022] [Indexed: 12/20/2022] Open
Abstract
Background The number of people living with obesity or who are overweight presents a global challenge, and the development of effective interventions is hampered by a lack of research which takes a joined up, whole system, approach that considers multiple elements of the complex obesity system together. We need to better understand the collective characteristics and behaviours of those who are overweight or have obesity and how these differ from those who maintain a healthy weight. Methods Using the UK Biobank cohort we develop an obesity classification system using k-means clustering. Variable selection from the UK Biobank cohort is informed by the Foresight obesity system map across key domains (Societal Influences, Individual Psychology, Individual Physiology, Individual Physical Activity, Physical Activity Environment). Results Our classification identifies eight groups of people, similar in respect to their exposure to known drivers of obesity: ‘Younger, urban hard-pressed’, ‘Comfortable, fit families’, ‘Healthy, active and retirees’, ‘Content, rural and retirees’, ‘Comfortable professionals’, ‘Stressed and not in work’, ‘Deprived with less healthy lifestyles’ and ‘Active manual workers’. Pen portraits are developed to describe the characteristics of these different groups. Multinomial logistic regression is used to demonstrate that the classification can effectively detect groups of individuals more likely to be living with overweight or obesity. The group identified as ‘Comfortable, fit families’ are observed to have a higher proportion of healthy weight, while three groups have increased relative risk of being overweight or having obesity: ‘Active manual workers’, ‘Stressed and not in work’ and ‘Deprived with less healthy lifestyles’. Conclusions This paper presents the first study of UK Biobank participants to adopt this obesity system approach to characterising participants. It provides an innovative new approach to better understand the complex drivers of obesity which has the potential to produce meaningful tools for policy makers to better target interventions across the whole system to reduce overweight and obesity. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-12650-x.
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Affiliation(s)
- Stephen Clark
- Consumer Data Research Centre and School of Geography, University of Leeds, LEEDS, LS2 9JT, UK.
| | - Nik Lomax
- School of Geography and Consumer Data Research Centre, University of Leeds, LEEDS, LS2 9JT, UK
| | - Mark Birkin
- Consumer Data Research Centre and School of Geography, University of Leeds, LEEDS, LS2 9JT, UK
| | - Michelle Morris
- School of Medicine and Consumer Data Research Centre, University of Leeds, LEEDS, UK
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Marshall Q, Fanzo J, Barrett CB, Jones AD, Herforth A, McLaren R. Building a Global Food Systems Typology: A New Tool for Reducing Complexity in Food Systems Analysis. FRONTIERS IN SUSTAINABLE FOOD SYSTEMS 2021. [DOI: 10.3389/fsufs.2021.746512] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Food systems have a profound impact on diets, nutrition, health, economic development, and environmental sustainability. Yet their complexity poses a persistent challenge in identifying the policy actions that are needed to improve human and planetary health outcomes. Typologies are a useful classification tool to identify similarities and differences among food systems, while reducing this analytical complexity. This study presents a new food system typology, implemented at the country level using parsimonious data that characterize food supply chains, food environments, consumer-related factors, and key outcomes, including dietary intake, nutritional status, health, and environmental impacts. Five food system types are identified: rural and traditional; informal and expanding; emerging and diversifying; modernizing and formalizing; and industrial and consolidated. Patterns across the five system types in key outcome variables align with narratives provided by the food systems and nutrition transition literature, demonstrating the usefulness of this classification method. Substantial heterogeneity nonetheless still exists within individual food system types. Therefore, the recommended use of the typology is in early stages of hypothesis generation, to identify potential risk factors or constraints in the food system that can be explored further at national and sub-national levels.
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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: 18] [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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Carroll SJ, Turrell G, Dale MJ, Daniel M. Associations between supermarket availability and body size in Australia: a cross-sectional observational study comparing state and territory capital cities. BMC Public Health 2021; 21:407. [PMID: 33632182 PMCID: PMC7908780 DOI: 10.1186/s12889-021-10458-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 02/17/2021] [Indexed: 11/22/2022] Open
Abstract
Background Residential environment features such as availability of supermarkets may shape dietary behaviour and thus overweight and obesity. This relationship may not be consistent between cities. This Australian national-level study examined: 1) the relationship between supermarket availability and body size; and 2) whether this relationship varied by capital city. Methods This study used 2017–18 Australian National Health Survey data including individual-level socio-demographic information (age, sex, country of birth, education, occupation, household income), and measured body size (height and weight to derive body mass index [BMI], and waist circumference [WC]). Objectively-expressed measures of residential environments included: counts of supermarkets (major chain outlets), counts of amenities (representing walkable destinations including essential services, recreation, and entertainment), and area of public open space - each expressed within road-network buffers at 1000 m and 1500 m; population density (1km2 grid cells); and neighbourhood disadvantage (Index of Relative Socioeconomic Disadvantage) expressed within Statistical Area Level 1 units. Data for adult respondents ≥18 years residing in each of Australia’s state and territory capital cities (n = 9649) were used in multilevel models to estimate associations between supermarket availability and body size sequentially accounting for individual and other environment measures. An interaction term estimated city-specific differences in associations between supermarket availability and body size. Models were consequently repeated stratified by city. Results Body size (BMI and WC) and supermarket availability varied between cities. Initial inverse associations between supermarket availability and body size (BMI and WC) were attenuated to null with inclusion of all covariates, except for BMI in the 1000 m buffer model (beta = − 0.148, 95%CI -0.27, − 0.01, p = 0.025). In stratified analyses, the strengths of associations varied between cities, remaining statistically significant only for some cities (BMI: Melbourne, Brisbane Hobart; WC: Brisbane, Hobart) in fully adjusted models. Different patterns of attenuation of associations with inclusion of covariates were evident for different cities. Conclusions For Australian capital cities, greater availability of supermarkets is associated with healthful body size. Marked between-city variations in body size, supermarket availability, and relationships between supermarket availability and body size do not, however, support universal, “one-size-fits-all” solutions to change built environments to support healthful body size.
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Affiliation(s)
- Suzanne J Carroll
- Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, 23B21, 11 Kirinari St, Bruce, ACT, Australia.
| | - Gavin Turrell
- Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, 23B21, 11 Kirinari St, Bruce, ACT, Australia
| | - Michael J Dale
- Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, 23B21, 11 Kirinari St, Bruce, ACT, Australia
| | - Mark Daniel
- Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, 23B21, 11 Kirinari St, Bruce, ACT, Australia.,Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, Victoria, Australia
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Downs SM, Ahmed S, Fanzo J, Herforth A. Food Environment Typology: Advancing an Expanded Definition, Framework, and Methodological Approach for Improved Characterization of Wild, Cultivated, and Built Food Environments toward Sustainable Diets. Foods 2020; 9:E532. [PMID: 32331424 PMCID: PMC7230632 DOI: 10.3390/foods9040532] [Citation(s) in RCA: 155] [Impact Index Per Article: 38.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 04/01/2020] [Accepted: 04/10/2020] [Indexed: 02/07/2023] Open
Abstract
The food environment is a critical place in the food system to implement interventions to support sustainable diets and address the global syndemic of obesity, undernutrition, and climate change, because it contains the total scope of options within which consumers make decisions about which foods to acquire and consume. In this paper, we build on existing definitions of the food environment, and provide an expanded definition that includes the parameter of sustainability properties of foods and beverages, in order to integrate linkages between food environments and sustainable diets. We further provide a graphical representation of the food environment using a socio-ecological framework. Next, we provide a typology with descriptions of the different types of food environments that consumers have access to in low-, middle-, and high-income countries including wild, cultivated, and built food environments. We characterize the availability, affordability, convenience, promotion and quality (previously termed desirability), and sustainability properties of food and beverages for each food environment type. Lastly, we identify a methodological approach with potential objective and subjective tools and metrics for measuring the different properties of various types of food environments. The definition, framework, typology, and methodological toolbox presented here are intended to facilitate scholars and practitioners to identify entry points in the food environment for implementing and evaluating interventions that support sustainable diets for enhancing human and planetary health.
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Affiliation(s)
- Shauna M. Downs
- Department of Urban-Global Public Health, School of Public Health, Rutgers University, Newark, NJ 07102, USA;
| | - Selena Ahmed
- Sustainable Food Systems Program, Department of Health and Human Development, Montana State University, Bozeman, MT 59717, USA
| | - Jessica Fanzo
- Berman Institute of Bioethics, Nitze School of Advanced International Studies and Bloomberg School of Public Health, Johns Hopkins University, Washington, DC 21205, USA;
| | - Anna Herforth
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard, University Boston, MA 02125, USA;
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