five

Descriptive statistics (N = 3,108).

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://figshare.com/articles/dataset/Descriptive_statistics_N_3_108_/25641169
下载链接
链接失效反馈
官方服务:
资源简介:
To prevent obesity and diabetes environmental interventions such as eliminating food deserts, restricting proliferation of food swamps, and improving park access are essential. In the United States, however, studies that examine the food and park access relationship with obesity and diabetes using both global and local regression are lacking. To guide county, state, and federal policy in combating obesity and diabetes, there is a need for cross-scale analyses to identify that relationship at national and local levels. This study applied spatial regression and geographically weighted regression to the 3,108 counties in the contiguous United States. Global regression show food deserts exposure and density of fast-food restaurants have non-significant association with obesity and diabetes while park access has a significant inverse association with both diseases. Geographically weighted regression that takes into account spatial heterogeneity shows that, among southern states that show high prevalence of obesity and diabetes, Alabama and Mississippi stand out as having opportunity to improve park access. Results suggest food deserts exposure are positively associated with obesity and diabetes in counties close to Alabama, Georgia, and Tennessee while density of fast-food restaurants show positive association with two diseases in counties of western New York and northwestern Pennsylvania. These findings will help policymakers and public health agencies in determining which geographic areas need to be prioritized when implementing public interventions such as promoting healthy food access, limiting unhealthy food options, and increasing park access.

为预防肥胖与糖尿病,采取消除食物荒漠(food deserts)、遏制食物沼泽(food swamps)蔓延、优化公园可达性等环境干预举措至关重要。然而在美国,目前尚缺乏同时采用全局回归与局域回归方法,探究食物与公园可达性同肥胖、糖尿病之间关联的研究。为指导县级、州级及联邦层面的政策制定以应对肥胖与糖尿病问题,亟需开展跨尺度分析,从而在国家与地方层面明确上述关联机制。本研究针对美国本土48州的3108个县域,应用空间回归(spatial regression)与地理加权回归(geographically weighted regression)模型开展分析。全局回归结果显示,食物荒漠暴露程度与快餐店密度均与肥胖、糖尿病无显著关联,而公园可达性则与这两种疾病均存在显著负相关关系。考虑空间异质性的地理加权回归结果表明,在肥胖与糖尿病患病率较高的南部各州中,阿拉巴马州与密西西比州在改善公园可达性方面具备显著的优化潜力。研究结果显示,在毗邻阿拉巴马州、佐治亚州和田纳西州的县域内,食物荒漠暴露度与肥胖、糖尿病呈正相关;而在纽约州西部与宾夕法尼亚州西北部的县域中,快餐店密度与这两种疾病呈正相关。上述研究成果将助力政策制定者与公共卫生机构,在推行促进健康食物可达性、限制不健康食品选择、提升公园可达性等公共干预措施时,精准确定需要优先关注的地理区域。
创建时间:
2024-04-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作