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Int. J. Environ. Res. Public Health 2017, 14(2), 177; doi:10.3390/ijerph14020177

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

School of Business, Western Sydney University, Parramatta, NSW 2150, Australia
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Received: 6 December 2016 / Accepted: 6 February 2017 / Published: 10 February 2017
(This article belongs to the Section Global Health)
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Abstract

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. View Full-Text
Keywords: obesity; panel model; generalized ordered probit obesity; panel model; generalized ordered probit
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Avsar, G.; Ham, R.; Tannous, W.K. Factors Influencing the Incidence of Obesity in Australia: A Generalized Ordered Probit Model. Int. J. Environ. Res. Public Health 2017, 14, 177.

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