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Hoenink JC, Huang Y, Keeble M, Mackenbach JD, de Pinho MG, Vanderlee L, Hammond D, White CM, Burgoine T, Adams J. Physical and online food outlet availability and its influence on out-of-home dietary behaviours in Great Britain: A repeated cross-sectional study. SSM Popul Health 2025; 30:101773. [PMID: 40129558 PMCID: PMC11932679 DOI: 10.1016/j.ssmph.2025.101773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2024] [Revised: 02/10/2025] [Accepted: 03/04/2025] [Indexed: 03/26/2025] Open
Abstract
Background As online food delivery service (OFDS) platforms gain popularity, understanding their impact on diet alongside physical food outlets is important for addressing suboptimal dietary quality. This study examined the independent and combined associations between physical and online food outlet availability and out-of-home dietary behaviours in 2019 and 2022. We also explored whether associations between physical outlet availability and dietary behaviours are modified by online food outlet availability. Methods In this repeated cross-sectional analysis, we used British data from the adult International Food Policy Study (IFPS) in 2019 (n = 2912) and 2022 (n = 3544). Postcodes were used to assess neighbourhood food outlet availability using Ordnance Survey data and to determine OFDS availability on three platforms through web scraping. Associations were examined between neighbourhood outlet and OFDS availability with self-reported frequency of physical food outlet use, online food outlet use, and consuming meals prepared out-of-home. Results In 2019 and 2022, both neighbourhood and OFDS availability were positively associated with all outcome measures. In 2019, after mutual adjustment, both availability measures remained associated with online food outlet use and consuming meals prepared out-of-home. However, in 2022, only OFDS availability was associated with these outcomes. For example, a one standard deviation increase in OFDS availability was associated with a 9% (95%CI 3%-14%) increase in frequency of consuming meals prepared out-of-home after adjusting for neighbourhood outlet availability. OFDS availability also modified associations between neighbourhood outlets and both online food outlet use and out-of-home meal consumption. As OFDS availability increased, the link between neighbourhood outlets and out-of-home meal consumption weakened. Conclusion Neighbourhood outlet availability may influence out-of-home dietary behaviours, but its impact appears to weaken when OFDS availability is considered. Public health strategies should address the growing influence of OFDS platforms to improve dietary quality.
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Affiliation(s)
- Jody C. Hoenink
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
- Upstream Team, www.upstreamteam.nl, Amsterdam UMC, the Netherlands
| | - Yuru Huang
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
| | - Matthew Keeble
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
- Department of Marketing, Faculty of Business and Economics, University of Antwerp, Antwerp, Belgium
| | - Joreintje D. Mackenbach
- Upstream Team, www.upstreamteam.nl, Amsterdam UMC, the Netherlands
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Epidemiology and Data Science, De Boelelaan 1117, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
| | - Maria G.M. de Pinho
- Upstream Team, www.upstreamteam.nl, Amsterdam UMC, the Netherlands
- Copernicus Institute of Sustainable Development, Department Environmental Sciences, Utrecht University, Utrecht, the Netherlands
| | | | - David Hammond
- School of Public Health Sciences, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Christine M. White
- School of Public Health Sciences, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Thomas Burgoine
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
| | - Jean Adams
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
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Giacomini G, Scacchi A, Ragusa P, Prinzivalli A, Elhadidy HSMA, Gianino MM. Which variables and determinants influence online food delivery consumption among workers and students? Results from the DELIvery Choice In OUr Society (DELICIOUS) cross-sectional study. Front Public Health 2024; 11:1326628. [PMID: 38259773 PMCID: PMC10801387 DOI: 10.3389/fpubh.2023.1326628] [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: 10/23/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction Online food delivery (OFD) applications provide easy access to food, eliminating the need for cooking and meal planning. However, they predominantly promote processed and calorie-dense foods, potentially impacting diet and health. This study aimed to describe the use of OFD services in a sample of Italian workers and students, to explore potential determinants of OFD usage and to assess possible differences in use between these two categories. Methods Data were collected through an online survey (convenience sampling) distributed on social media platforms between July 12, 2022, and February 1, 2023. The sample included individuals aged 18 and above, currently residing in Italy. The sample was stratified according to worker/student status. Descriptive analyses were performed on key variables. A multivariable logistic regression analysis was conducted to assess the effects of variables on OFD usage, treated as a dichotomous variable (usage or non-usage). Results This study analyzed 3,502 questionnaires (2,594 from workers and 908 from students) after excluding 323 non-student and non-worker responses. Positive associations with OFD use included higher income, remote working, smoking, elevated BMI, depression risk, and impulsive buying among workers, while being female, frequent screen-watching during meals, daily smoking, higher BMI, and impulsive buying were associated with OFD use among students. Factors negatively associated with OFD use included older age (workers and students), living in suburbs (workers and students) or in an outline town (workers), being single (workers and students), adhering to the Mediterranean diet (students), having low health literacy (students), and job dissatisfaction (workers). Discussion OFD consumption was associated with some risky behaviors and conditions, such as high BMI or smoking, suggesting that it might be influenced by individual tendencies. Healthier habits, such as physical activity, did not significantly impact OFD usage, especially among workers. Whereas, among students, factors such as low health literacy and better eating habits were associated with less use of OFD, so that they could be more prone to use OFD in a measured way. Further research is needed to better understand potential associations between OFD and risky habits, as well as its role in promoting access to healthy food in underserved areas.
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Affiliation(s)
| | | | - Paolo Ragusa
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Alessandro Prinzivalli
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
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Jing H, Teng Y, Chacha S, Wang Z, Shi G, Mi B, Zhang B, Cai J, Liu Y, Li Q, Shen Y, Yang J, Kang Y, Li S, Liu D, Wang D, Yan H, Dang S. Is Increasing Diet Diversity of Animal-Source Foods Related to Better Health-Related Quality of Life among Chinese Men and Women? Nutrients 2023; 15:4183. [PMID: 37836467 PMCID: PMC10574670 DOI: 10.3390/nu15194183] [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: 08/20/2023] [Revised: 09/12/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
Diet plays a crucial role in regulating individuals' lifestyles and is closely related to health. The intake of animal-sourced foods (ASF) provides the human body with high-quality protein and various micronutrients. This study aimed to investigate whether the diversity of animal foods has a positive impact on the health-related quality of life (HRQoL) among residents. The data came from the Shaanxi baseline survey of the Northwest Chinese Regional Ethnic Cohort Study, which recruited more than 100 thousand participants aged 35 to 74 from five provinces between June 2018 and May 2019. A total of 39,997 participants in Shaanxi (mean age: 50 years; 64% women) were finally included in this current study. The animal source food diet diversity score (ASFDDS) was established based on the frequency of consuming pork, mutton, beef, poultry, seafood, eggs, pure milk, and yogurt. The physical component score (PCS) and mental component score (MCS), ranging from 0 to 100 on the 12-Item Short Form Survey (SF-12), were used to assess participants' HRQoL. Better PCS/MCS was defined as scores higher than the 90th percentile. The results showed that men had a higher intake of ASF and ASFDDS than women. After adjusting for potential confounders, compared with those who never or rarely consumed animal foods, the likelihood of having better PCS and MCS increased by 16% (OR = 1.16, 95%CI: 1.01-1.34) and 24% (OR = 1.24, 95%CI: 1.03-1.448), respectively, in men with an ASFDDS ≥ 2. In women, a 34% increase (OR = l.34, 95%CI: 116-l.54) likelihood for better PCS was observed for an ASFDDS ≥ 2, but no association was observed for MCS. Increasing each specific animal source's food intake was associated with better PCS after adjusting for all covariates. However, for MCS, positive associations were only observed in seafood consumption among men and eggs among women. Restricted cubic splines showed a substantial dose-response association between intake frequency of animal-source foods and PCS, both in men and women. The study suggests that a diverse intake of animal-sourced foods can potentially improve the HRQoL of Chinese adults.
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Affiliation(s)
- Hui Jing
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yuxin Teng
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Samuel Chacha
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Ziping Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Guoshuai Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Baibing Mi
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Binyan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Jiaxin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yezhou Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Qiang Li
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yuan Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Jiaomei Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yijun Kang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Shanshan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Danmeng Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Duolao Wang
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool L7 8XZ, UK;
| | - Hong Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Shaonong Dang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
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Bianchi F, Luick M, Bandy L, Bone J, Kelly S, Farrington J, Leung J, Mottershow A, Murar F, Jebb SA, Harper H, Pechey R. The impact of altering restaurant and menu option position on food selected from an experimental food delivery platform: a randomised controlled trial. Int J Behav Nutr Phys Act 2023; 20:60. [PMID: 37208720 PMCID: PMC10197857 DOI: 10.1186/s12966-023-01456-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 04/24/2023] [Indexed: 05/21/2023] Open
Abstract
BACKGROUND Overconsumption is one of the most serious public health challenges in the UK and has been linked to increased consumption of food ordered through delivery platforms. This study tested whether repositioning foods and/or restaurant options in a simulated food delivery platform could help to reduce the energy content of users' shopping basket. METHODS UK adult food delivery platform users (N = 9,003) selected a meal in a simulated platform. Participants were randomly allocated to a control condition (choices listed randomly) or to one of four intervention groups, (1) food options listed in ascending order of energy content, (2) restaurant options listed in ascending order of average energy content per main meal, (3) interventions 1 and 2 combined (4) interventions 1 and 2 combined, but food and restaurant options repositioned based on a kcal/price index to display options lower in energy but higher in price at the top. Gamma regressions assessed the impact of interventions on total energy content of baskets at checkout. RESULTS The energy content of participants' baskets in the control condition was 1382 kcals. All interventions significantly reduced energy content of baskets: Compared to control, repositioning both foods and restaurants purely based on energy content of options resulted in the greatest effect (-209kcal; 95%CIs: -248,-168), followed by repositioning restaurants (-161kcal; 95%CIs: -201,-121), repositioning restaurants and foods based on a kcal/price index (-117kcals; 95%CI: -158,-74) and repositioning foods based on energy content (-88kcals; 95%CI: -130,-45). All interventions reduced the basket price compared to the control, except for the intervention repositioning restaurants and foods based on a kcal/price index, which increased the basket price. CONCLUSIONS This proof-of-concept study suggests repositioning lower-energy options more prominently may encourage lower energy food choices in online delivery platforms and can be implemented in a sustainable business model.
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Affiliation(s)
| | - Madison Luick
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
| | - Lauren Bandy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Stefan Kelly
- Behavioural Insights Team, London, UK
- Nesta, London, UK
| | | | | | | | | | - Susan A Jebb
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Hugo Harper
- Behavioural Insights Team, London, UK
- Nesta, London, UK
| | - Rachel Pechey
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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Popkin BM. Does excessive fast-food consumption impair our health? Am J Clin Nutr 2022; 116:11-12. [PMID: 35679428 DOI: 10.1093/ajcn/nqac110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Barry M Popkin
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.,Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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