Selected Risk Factors' Contribution to State-Level Incidence of DiagnosedDiabetes, 2005-2007

L. Barker, E. Tierney, A. Lanza, K. Kirtland
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引用次数: 1

Abstract

Introduction: Differences in incidence of diabetes and prevalence of risk factors for diabetes exist among states. It is unknown how much of this variability in incidence of diagnosed diabetes is due to variability in risk factor prevalence. We investigate the contribution of selected risk factors to state level incidence of diagnosed diabetes. Materials and Methods: Using 2005-2007 data from the Behavioral Risk Factor Surveillance System, we conducted two logistic regressions, both with incident case status as dependent variable. One model considered only state of residence as an independent variable. The other added: age; sex; race/ethnicity; education; inactive lifestyle; and obesity. We compared adjusted and unadjusted odds of incident diabetes among states, and calculated excess risk. Results: Adjusted and unadjusted odds of incident diabetes were similar. Sensitivity analyses showed that this differed little if we used data from earlier years or if we included income or insurance as a risk factor. In most states, the excess risk associated with risk factors was less than 30%. Discussion: Factors other than age, sex, race/ethnicity, education, inactivity, and obesity (i.e., established risk factors for diabetes) might substantially influence the differences in state incidence rates. These factors' identities are unknown. If these factors are identified and modifiable, states might use them to reduce between-state disparities in diabetes incidence.
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2005-2007年选定的危险因素对国家一级诊断糖尿病发病率的贡献
前言:糖尿病的发病率和糖尿病危险因素的流行在各州之间存在差异。目前尚不清楚诊断糖尿病发病率的这种变异性有多少是由于危险因素患病率的变异性造成的。我们调查选定的危险因素对国家水平诊断糖尿病发病率的贡献。材料和方法:使用行为风险因素监测系统2005-2007年的数据,我们进行了两次logistic回归,均以事件病例状态为因变量。一个模型只考虑居住状态作为一个独立变量。另一个补充道:年龄;性;种族/民族;教育;不活跃的生活方式;和肥胖。我们比较了各州调整和未调整的糖尿病发生率,并计算了超额风险。结果:调整后和未调整后的糖尿病发生率相似。敏感性分析表明,如果我们使用早些年的数据,或者如果我们将收入或保险作为风险因素,这种差异很小。在大多数州,与风险因素相关的超额风险低于30%。讨论:年龄、性别、种族/民族、教育程度、缺乏运动和肥胖(即糖尿病的既定危险因素)以外的因素可能会对各州发病率的差异产生实质性影响。这些因素的身份是未知的。如果这些因素被识别和修改,各州可以利用它们来减少各州之间糖尿病发病率的差异。
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