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Factors Influencing the Incidence of Obesity in Australia: A Generalized Ordered Probit Model

机译:影响澳大利亚肥胖发生率的因素:广义有序Probit模型

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摘要

The increasing health costs of and the risks factors associated with obesity are well documented. From this perspective, it is important that the propensity of individuals towards obesity is analyzed. This paper uses longitudinal data from the Household Income and Labour Dynamics in Australia (HILDA) Survey for 2005 to 2010 to model those variables which condition the probability of being obese. The model estimated is a random effects generalized ordered probit, which exploits two sources of heterogeneity; the individual heterogeneity of panel data models and heterogeneity across body mass index (BMI) categories. The latter is associated with non-parallel thresholds in the generalized ordered model, where the thresholds are functions of the conditioning variables, which comprise economic, social, and demographic and lifestyle variables. To control for potential predisposition to obesity, personality traits augment the empirical model. The results support the view that the probability of obesity is significantly determined by the conditioning variables. Particularly, personality is found to be important and these outcomes reinforce other work examining personality and obesity.
机译:肥胖引起的健康成本增加和与之相关的风险因素已得到充分证明。从这个角度来看,重要的是分析个体的肥胖倾向。本文使用2005年至2010年澳大利亚家庭收入和劳动力动态调查(HILDA)的纵向数据来对那些决定肥胖可能性的变量进行建模。估计的模型是一种随机效应的广义有序概率,它利用了两种异质性来源。面板数据模型的个体异质性和体重指数(BMI)类别的异质性。后者与广义有序模型中的非平行阈值相关,其中阈值是条件变量的函数,条件变量包括经济,社会,人口统计和生活方式变量。为了控制肥胖的潜在易感性,人格特质增强了经验模型。结果支持这样的观点,肥胖的机率很大程度上取决于条件变量。特别是,发现人格很重要,这些结果加强了其他检查人格和肥胖的工作。

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