估计存在测量误差的肥胖率

Donal O’neill, Olive Sweetman
{"title":"估计存在测量误差的肥胖率","authors":"Donal O’neill, Olive Sweetman","doi":"10.2139/ssrn.2238321","DOIUrl":null,"url":null,"abstract":"Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. In this paper we examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. We combine self-reported data on BMI with estimated misclassification rates obtained from auxiliary data to derive upper and lower bounds for the population obesity rate for ten European countries. For men it is possible to obtain meaningful comparisons across countries even after accounting for measurement error. In particular the self-reported data identifies a set of low obesity countries consisting of Denmark, Ireland, Italy, Greece and Portugal and a set of high obesity countries consisting of Spain and Finland. However, it is more difficult to rank countries by female obesity rates. Meaningful rankings only emerge when the misclassification rate is bounded at a level that is much lower than that observed in auxiliary data. A similar limit on misclassification rates is also needed before we can begin to observe meaningful gender differences in obesity rates within countries.","PeriodicalId":216327,"journal":{"name":"FoodSciRN: Other Functional Foods","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Estimating Obesity Rates in the Presence of Measurement Error\",\"authors\":\"Donal O’neill, Olive Sweetman\",\"doi\":\"10.2139/ssrn.2238321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. In this paper we examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. We combine self-reported data on BMI with estimated misclassification rates obtained from auxiliary data to derive upper and lower bounds for the population obesity rate for ten European countries. For men it is possible to obtain meaningful comparisons across countries even after accounting for measurement error. In particular the self-reported data identifies a set of low obesity countries consisting of Denmark, Ireland, Italy, Greece and Portugal and a set of high obesity countries consisting of Spain and Finland. However, it is more difficult to rank countries by female obesity rates. Meaningful rankings only emerge when the misclassification rate is bounded at a level that is much lower than that observed in auxiliary data. A similar limit on misclassification rates is also needed before we can begin to observe meaningful gender differences in obesity rates within countries.\",\"PeriodicalId\":216327,\"journal\":{\"name\":\"FoodSciRN: Other Functional Foods\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FoodSciRN: Other Functional Foods\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2238321\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FoodSciRN: Other Functional Foods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2238321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

为了制定有效的政策来解决肥胖的成本问题,可靠的肥胖措施至关重要。在这篇论文中,我们研究了在允许可能的测量误差的情况下,我们可以通过自我报告的BMI来了解肥胖率,如果有的话。我们将自我报告的BMI数据与从辅助数据中获得的估计误分类率结合起来,得出了10个欧洲国家人口肥胖率的上限和下限。对于男性来说,即使考虑到测量误差,也有可能获得各国之间有意义的比较。特别是自我报告的数据确定了一系列低肥胖国家,包括丹麦、爱尔兰、意大利、希腊和葡萄牙,以及一系列高肥胖国家,包括西班牙和芬兰。然而,要根据女性肥胖率对各国进行排名就比较困难了。只有当误分类率被限制在远低于辅助数据中观察到的水平时,才会出现有意义的排名。在我们开始观察到各国肥胖率有意义的性别差异之前,也需要对错误分类率进行类似的限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating Obesity Rates in the Presence of Measurement Error
Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. In this paper we examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. We combine self-reported data on BMI with estimated misclassification rates obtained from auxiliary data to derive upper and lower bounds for the population obesity rate for ten European countries. For men it is possible to obtain meaningful comparisons across countries even after accounting for measurement error. In particular the self-reported data identifies a set of low obesity countries consisting of Denmark, Ireland, Italy, Greece and Portugal and a set of high obesity countries consisting of Spain and Finland. However, it is more difficult to rank countries by female obesity rates. Meaningful rankings only emerge when the misclassification rate is bounded at a level that is much lower than that observed in auxiliary data. A similar limit on misclassification rates is also needed before we can begin to observe meaningful gender differences in obesity rates within countries.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信