Using simulated data to investigate the spatial patterns of obesity prevalence at the census tract level in metropolitan Detroit
Using simulated data to investigate the spatial patterns of obesity prevalence at the census tract level in metropolitan Detroit
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DOI：
10.1016/j.apgeog.2015.03.016
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发表时间：
2015-08-01
影响因子：
4.9
通讯作者：
Vojnovic, Igor
中科院分区：
文献类型：
--
作者：
Koh, Keumseok;Grady, Sue C.;Vojnovic, Igor
肥胖症在美国是一个严重的公共卫生问题。重要的是要估计地方一级的肥胖患病率，以针对方案和政策干预措施。然而，获得当地肥胖患病率的估计值具有挑战性，因为国家健康调查，如疾病控制和预防中心（CDC）行为风险因素监测系统（BRFSS），由于人口样本量小，需要保护个人机密，因此并不是为了在地方一级（例如人口普查区）产生直接估计值。在这项研究中，我们解决的问题，估计当地的肥胖患病率，通过实施空间微观模拟建模技术，按比例复制人口特征的BRFSS受访者在底特律大都市的人口普查区人口。肥胖患病率检查高和低空间集群，并研究与美国农业部（USDA）的措施，低收入社区和当地的食物沙漠和疾病预防控制中心的措施，健康和不太健康的食品环境目前用于目标肥胖减少倡议。这项研究发现，肥胖症的流行主要集中在底特律市向北延伸到邻近的郊区。最高肥胖患病率区域的空间模式与美国农业部定义的低收入区域和CDC的不太健康的食物区域最相似。美国农业部食物沙漠地带的位置很少与肥胖患病率最高的地带重叠。这项研究展示了一种新的方法，通过这种方法来评估当地未来需要肥胖干预的地区。(C)2015爱思唯尔有限公司版权所有。
Obesity is a serious public health problem in the United States. It is important to estimate obesity prevalence at the local level to target programmatic and policy interventions. It is challenging, however, to obtain local estimates of obesity prevalence because national health surveys such as the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS) are not designed to produce direct estimates at the local levels (e.g. census tracts) due to small population samples and the need to preserve individual confidentiality. In this study we address the problem of estimating local obesity prevalence rates by implementing a spatial microsimulation modeling technique to proportionally replicate the demographic characteristics of BRFSS respondents to census tract populations in metropolitan Detroit. Obesity prevalence rates are examined for high and low spatial clusters and studied in relation to the U.S. Department of Agriculture's (USDA) measures of low-income neighborhoods and local food deserts and CDC's measure of healthy and less healthy food environments currently used to target obesity reduction initiatives. This study found that obesity prevalence was largely clustered in the City of Detroit extending north into contiguous suburbs. The spatial patterns of highest obesity prevalence tracts were most similarly aligned with USDA-defined low-income tracts and CDC's less healthy food tracts. The locations of USDA's food desert tracts rarely overlapped with the highest obesity prevalence tracts. This study demonstrated a new methodology by which to assess local areas in need of future obesity interventions. (C) 2015 Elsevier Ltd. All rights reserved.