The foodscape: classification and field validation of secondary data sources across urban/rural and socio-economic classifications in England.
The foodscape: classification and field validation of secondary data sources across urban/rural and socio-economic classifications in England.
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DOI：
10.1186/1479-5868-9-37
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发表时间：
2012-04-02
期刊：
影响因子：
--
通讯作者：
Grieve R
中科院分区：
文献类型：
--
作者：
Lake AA;Burgoine T;Stamp E;Grieve R
近年来，随着超重和肥胖患病率呈指数级增长，食品环境（foodscape）也发生了变化。这项研究的重点是用于测量和分类食物景观的方法。本文描述了城市/农村和社会经济鸿沟的食品景观。它通过进行实地调查（实地调查），跨城市/农村和社会经济鸿沟，检查从地方当局来源（二级和基于案头）获得的食品店数据库的有效性。此外，本文还测试了使用基于桌面的分类系统来描述食品店的有效性，并与地面实况进行了比较。在英格兰东北部有目的地选择了六个地理定义的研究区域，每个区域由两个低超级输出区域（LSOA；一个小型行政地理区域）组成。从相关地方当局（二级和办公桌）获得了食品店名单，并进行了实地调查（实地调查）。使用现有工具对食品店进行分类。进行阳性预测值（PPV）和敏感性分析来探索二手数据源的验证。评估了基于“柜台”和“现场”的食品店分类之间的一致性。所有研究区域内共有 438 个食品店；城市低社会经济地位（SES）地区的网点总数最多（n = 210），而农村高社会经济地位（SES）地区的网点总数最少（n = 19）。不同地区的网点类型存在差异。将地方当局清单与跨地理区域的实地工作进行比较，得出了一系列 PPV 值；其中城市低社会经济地位地区最高（87%），农村混合社会经济地位最低（79%）。而敏感性范围从农村混合社会经济地位地区的 95% 到农村低社会经济地位地区的 60%。跨任何部门的现场/案头百分比协议之间没有显着关联。尽管区域数量相对较少，但这项工作进一步加深了我们对使用二手数据源来识别和分类各种地理环境中食物景观的有效性的理解。虽然使用二级地方当局食品店数据和从互联网获得的信息对食品景观进行分类并非没有困难，但基于案头的分类将是实地工作的可接受的替代方案，但应谨慎使用。
In recent years, alongside the exponential increase in the prevalence of overweight and obesity, there has been a change in the food environment (foodscape). This research focuses on methods used to measure and classify the foodscape. This paper describes the foodscape across urban/rural and socio-economic divides. It examines the validity of a database of food outlets obtained from Local Authority sources (secondary level & desk based), across urban/rural and socio-economic divides by conducting fieldwork (ground-truthing). Additionally this paper tests the efficacy of using a desk based classification system to describe food outlets, compared with ground-truthing. Six geographically defined study areas were purposively selected within North East England consisting of two Lower Super Output Areas (LSOAs; a small administrative geography) each. Lists of food outlets were obtained from relevant Local Authorities (secondary level & desk based) and fieldwork (ground-truthing) was conducted. Food outlets were classified using an existing tool. Positive predictive values (PPVs) and sensitivity analysis was conducted to explore validation of secondary data sources. Agreement between 'desk' and 'field' based classifications of food outlets were assessed. There were 438 food outlets within all study areas; the urban low socio-economic status (SES) area had the highest number of total outlets (n = 210) and the rural high SES area had the least (n = 19). Differences in the types of outlets across areas were observed. Comparing the Local Authority list to fieldwork across the geographical areas resulted in a range of PPV values obtained; with the highest in urban low SES areas (87%) and the lowest in Rural mixed SES (79%). While sensitivity ranged from 95% in the rural mixed SES area to 60% in the rural low SES area. There were no significant associations between field/desk percentage agreements across any of the divides. Despite the relatively small number of areas, this work furthers our understanding of the validity of using secondary data sources to identify and classify the foodscape in a variety of geographical settings. While classification of the foodscape using secondary Local Authority food outlet data with information obtained from the internet, is not without its difficulties, desk based classification would be an acceptable alternative to fieldwork, although it should be used with caution.
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DOI：
10.1186/1479-5868-3-2
发表时间：
2006-01-01
影响因子：
8.7
作者：
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通讯作者：
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影响因子：
5.5
作者：
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