McCormack Lacey A, MacKenzie Debra A, Deutsch Arielle, Beene Daniel, Hockett Christine W, Ziegler Katherine, Knapp Emily A, Kress Amii M, Li Zone R, Bakre Shivani, Habre Rima, Jacobson Lisa, Karagas Margaret R, LeWinn Kaja, Nozadi Sara S, Alshawabkeh Akram, Aris Izzuddin M, Bekelman Traci A, Bendixsen Casper G, Camargo Carlos, Cassidy-Bushrow Andrea E, Croen Lisa, Assiamira Ferrara, Fry Rebecca, Gebretsadik Tebeb, Hartert Tina, Hirko Kelly A, Karr Catherine J, Kloog Itai, Loftus Christine, Magee Kelsey E, McEvoy Cindy, Neiderhiser Jenae M, O'Connor Thomas G, O'Shea Mike, Straughen Jennifer K, Urquhart Audrey, Wright Rosalind, Elliott Amy J
Avera Research Institute, Avera McKennan Hospital, Sioux Falls, South Dakota, USA.
Department of Pediatrics, University of South Dakota Sanford School of Medicine, Sioux Falls, South Dakota, USA.
J Rural Health. 2025 Jan;41(1):e12908. doi: 10.1111/jrh.12908.
The Environmental influences on Child Health Outcomes (ECHO) Cohort has enrolled over 60,000 children to examine how early environmental factors (broadly defined) are associated with key child health outcomes. The ECHO Cohort may be well-positioned to contribute to our understanding of rural environments and contexts, which has implications for rural health disparities research. The present study examined the outcome of child obesity to not only illustrate the suitability of ECHO Cohort data for these purposes but also determine how various definitions of rural and urban populations impact the presentation of findings and their interpretation.
This analysis uses data from children in the ECHO Cohort study who had residential address information between January 2010 and October 2023, including a subset who also had height and weight data. Several rural-urban classification schemes were examined with and without collapsing into binary rural/urban groupings (ie, the Rural-Urban Continuum Codes, 2010 Rural-Urban Commuting Area [RUCA] Codes, and Urban Influence Codes).
Various rural/urban definitions and classification schemes produce similar obesity prevalence (17%) when collapsed into binary categories (rural vs urban) and for urban participants in general. When all categories within a classification scheme are examined, however, the rural child obesity prevalence ranges from 5.8% to 24%.
Collapsing rural-urban classification schemes into binary groupings erases nuance and context needed for interpreting findings, ultimately impacting health disparities research. Future work should leverage both individual- and community-level datasets to provide context, and all categories of classification schemes should be used when examining rural populations.
环境对儿童健康结果的影响(ECHO)队列已招募了6万多名儿童,以研究早期环境因素(广义定义)如何与关键儿童健康结果相关联。ECHO队列可能处于有利地位,有助于我们了解农村环境和背景,这对农村健康差异研究具有重要意义。本研究考察了儿童肥胖的结果,不仅是为了说明ECHO队列数据适用于这些目的,还为了确定农村和城市人口的各种定义如何影响研究结果的呈现及其解释。
本分析使用了ECHO队列研究中2010年1月至2023年10月有居住地址信息的儿童数据,包括一部分也有身高和体重数据的儿童。研究了几种城乡分类方案,有无合并为二元农村/城市分组(即农村-城市连续体代码、2010年农村-城市通勤区[RUCA]代码和城市影响代码)。
当合并为二元类别(农村与城市)时,以及对于一般城市参与者,各种农村/城市定义和分类方案产生相似的肥胖患病率(17%)。然而,当检查分类方案中的所有类别时,农村儿童肥胖患病率范围为5.8%至24%。
将城乡分类方案合并为二元分组消除了解释研究结果所需的细微差别和背景,最终影响健康差异研究。未来的工作应利用个体和社区层面的数据集来提供背景信息,并且在研究农村人口时应使用分类方案的所有类别。