每日,每周和每月午餐时间卡路里的变化

Anya Skatova, Neil Stewart, Edward Flavahan, James Goulding
{"title":"每日,每周和每月午餐时间卡路里的变化","authors":"Anya Skatova, Neil Stewart, Edward Flavahan, James Goulding","doi":"10.23889/ijpds.v8i3.2288","DOIUrl":null,"url":null,"abstract":"Introduction & BackgroundDespite the level of attention that healthy and unhealthy eating receive from academic research, policymakers and the wider public, objective data on food consumption is limited. This is because studies of individual eating patterns using food diaries are subject to underreporting, particularly by people who are overweight. For example, the UK population is estimated to consume between 30% to 50% more calories than they report in surveys. New data sources such as office canteen ordering systems and individual records of supermarket transactions recorded through supermarket loyalty or bonus cards offer larger and potentially more robust data on real world individual eating behaviours.
 Objectives & ApproachWe used 2,831,403 machine-recorded ‘meal deal’ transactions from 205,781 individuals over the course of one year from one of the UK’s largest suppliers of lunch time foods to investigate whether there is a relationship between patterns of choice and higher calorie consumption. A meal deal comprises three items; a main (e.g., a sandwich or a salad), a snack (e.g., crisps, fruit or a chocolate bar) and a drink (e.g., a smoothie or a bottle of water). In contrast to diary studies or aggregate transactional data from supermarkets, our dataset included “meal deal’ purchase which is highly likely to be made by an individual for their own consumption or soon afterwards.
 Relevance to Digital FootprintsLunch time food consumption can reflect the overall diet the individual is exposed to, helping to understand population level patterns of people’s food choices through a type of digital footprints data - shopping history records.
 ResultsControlling for gender, general index of variety in the choice of lunch food items, income and education, we found that individuals who vary in their calorie consumption most across the time of day, day of the week, and month of the year are the individuals who consume the greatest number of calories overall. These time sensitivity effects are large, together explaining a substantial amount of variance in calorie consumption. Time sensitivity effects are strongly correlated across all three time scales suggesting they measure a stable underlying trait.
 Conclusions & ImplicationsIndividuals vary calorific composition of their lunch over time of the day, day of the week and month of the year by 100 calories per meal between highest and lowest in sensitivity which is about 9% of the recommended amount of lunchtime calories. Those whose consumption varies the most with time consume the most calories, independently of income and gender. The variation in calories at all three time scales demonstrates the properties of an individual disposition. These findings can be used to understand why and when people make unhealthy food choices.","PeriodicalId":132937,"journal":{"name":"International Journal for Population Data Science","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Daily, Weekly and Monthly Variation in Lunch Time Calories\",\"authors\":\"Anya Skatova, Neil Stewart, Edward Flavahan, James Goulding\",\"doi\":\"10.23889/ijpds.v8i3.2288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction & BackgroundDespite the level of attention that healthy and unhealthy eating receive from academic research, policymakers and the wider public, objective data on food consumption is limited. This is because studies of individual eating patterns using food diaries are subject to underreporting, particularly by people who are overweight. For example, the UK population is estimated to consume between 30% to 50% more calories than they report in surveys. New data sources such as office canteen ordering systems and individual records of supermarket transactions recorded through supermarket loyalty or bonus cards offer larger and potentially more robust data on real world individual eating behaviours.
 Objectives & ApproachWe used 2,831,403 machine-recorded ‘meal deal’ transactions from 205,781 individuals over the course of one year from one of the UK’s largest suppliers of lunch time foods to investigate whether there is a relationship between patterns of choice and higher calorie consumption. A meal deal comprises three items; a main (e.g., a sandwich or a salad), a snack (e.g., crisps, fruit or a chocolate bar) and a drink (e.g., a smoothie or a bottle of water). In contrast to diary studies or aggregate transactional data from supermarkets, our dataset included “meal deal’ purchase which is highly likely to be made by an individual for their own consumption or soon afterwards.
 Relevance to Digital FootprintsLunch time food consumption can reflect the overall diet the individual is exposed to, helping to understand population level patterns of people’s food choices through a type of digital footprints data - shopping history records.
 ResultsControlling for gender, general index of variety in the choice of lunch food items, income and education, we found that individuals who vary in their calorie consumption most across the time of day, day of the week, and month of the year are the individuals who consume the greatest number of calories overall. These time sensitivity effects are large, together explaining a substantial amount of variance in calorie consumption. Time sensitivity effects are strongly correlated across all three time scales suggesting they measure a stable underlying trait.
 Conclusions & ImplicationsIndividuals vary calorific composition of their lunch over time of the day, day of the week and month of the year by 100 calories per meal between highest and lowest in sensitivity which is about 9% of the recommended amount of lunchtime calories. Those whose consumption varies the most with time consume the most calories, independently of income and gender. The variation in calories at all three time scales demonstrates the properties of an individual disposition. These findings can be used to understand why and when people make unhealthy food choices.\",\"PeriodicalId\":132937,\"journal\":{\"name\":\"International Journal for Population Data Science\",\"volume\":\"121 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal for Population Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23889/ijpds.v8i3.2288\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Population Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23889/ijpds.v8i3.2288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

介绍,尽管健康和不健康饮食受到学术研究、政策制定者和广大公众的高度关注,但有关食品消费的客观数据有限。这是因为使用食物日记对个人饮食模式进行的研究容易被低估,尤其是对于超重的人。例如,据估计,英国人消耗的卡路里比调查中报告的要多30%到50%。新的数据来源,如办公室食堂订餐系统和通过超市忠诚卡或奖励卡记录的超市交易的个人记录,提供了关于现实世界中个人饮食行为的更大、可能更可靠的数据。目标,研究方法我们使用了机器记录的2831403笔来自英国最大的午餐时间食品供应商之一的205781个人的“用餐交易”记录,在一年的时间里调查了选择模式和高卡路里消耗之间是否存在关系。一顿饭包括三样东西;一份主菜(如三明治或沙拉),一份零食(如薯片、水果或巧克力棒)和一份饮料(如冰沙或一瓶水)。与日记研究或来自超市的汇总交易数据相比,我们的数据集包括“套餐交易”购买,这很可能是个人为自己消费或不久后消费而购买的。与数字足迹的相关性午餐时间的食物消费可以反映个人所接触的整体饮食,通过一种数字足迹数据-购物历史记录,帮助了解人们食物选择的人口水平模式。 结果:在控制了性别、午餐食物选择的总体多样性指数、收入和教育水平后,我们发现,在一天中的不同时间、一周中的某一天、一年中的某一个月里,卡路里消耗变化最大的个体,总体上消耗的卡路里数量最多。这些时间敏感性影响很大,共同解释了卡路里消耗的大量差异。时间敏感性效应在所有三个时间尺度上都有很强的相关性,这表明它们测量了一种稳定的潜在特征。 结论,每个人在一天中的不同时间,一周中的不同日子,一年中的不同月份,每顿饭的热量组成在敏感度最高和最低之间变化100卡路里,这大约是午餐热量推荐量的9%。摄入量随时间变化最大的人摄入的卡路里最多,与收入和性别无关。在所有三个时间尺度上卡路里的变化表明了个体性格的特性。这些发现可以用来理解人们为什么以及何时选择不健康的食物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Daily, Weekly and Monthly Variation in Lunch Time Calories
Introduction & BackgroundDespite the level of attention that healthy and unhealthy eating receive from academic research, policymakers and the wider public, objective data on food consumption is limited. This is because studies of individual eating patterns using food diaries are subject to underreporting, particularly by people who are overweight. For example, the UK population is estimated to consume between 30% to 50% more calories than they report in surveys. New data sources such as office canteen ordering systems and individual records of supermarket transactions recorded through supermarket loyalty or bonus cards offer larger and potentially more robust data on real world individual eating behaviours. Objectives & ApproachWe used 2,831,403 machine-recorded ‘meal deal’ transactions from 205,781 individuals over the course of one year from one of the UK’s largest suppliers of lunch time foods to investigate whether there is a relationship between patterns of choice and higher calorie consumption. A meal deal comprises three items; a main (e.g., a sandwich or a salad), a snack (e.g., crisps, fruit or a chocolate bar) and a drink (e.g., a smoothie or a bottle of water). In contrast to diary studies or aggregate transactional data from supermarkets, our dataset included “meal deal’ purchase which is highly likely to be made by an individual for their own consumption or soon afterwards. Relevance to Digital FootprintsLunch time food consumption can reflect the overall diet the individual is exposed to, helping to understand population level patterns of people’s food choices through a type of digital footprints data - shopping history records. ResultsControlling for gender, general index of variety in the choice of lunch food items, income and education, we found that individuals who vary in their calorie consumption most across the time of day, day of the week, and month of the year are the individuals who consume the greatest number of calories overall. These time sensitivity effects are large, together explaining a substantial amount of variance in calorie consumption. Time sensitivity effects are strongly correlated across all three time scales suggesting they measure a stable underlying trait. Conclusions & ImplicationsIndividuals vary calorific composition of their lunch over time of the day, day of the week and month of the year by 100 calories per meal between highest and lowest in sensitivity which is about 9% of the recommended amount of lunchtime calories. Those whose consumption varies the most with time consume the most calories, independently of income and gender. The variation in calories at all three time scales demonstrates the properties of an individual disposition. These findings can be used to understand why and when people make unhealthy food choices.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Using novel data linkage of biobank data with administrative health data to inform genomic analysis for future precision medicine treatment of congenital heart disease Common governance model: a way to avoid data segregation between existing trusted research environment Federated learning for generating synthetic data: a scoping review Health Data Governance for Research Use in Alberta Establishment of a birth-to-education cohort of 1 million Palestinian refugees using electronic medical records and electronic education records
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1