Obesity and risk knowledge

Kan, Kamhon; Tsai, Wei Der

doi:10.1016/j.jhealeco.2003.12.006

Cited by 98 publications

(79 citation statements)

References 37 publications

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“…As in other studies, we find that education is one of the most significant variables in explaining obesity (Chou et al, 2004;Kan and Tsai, 2004). The plot corresponding to YEARS OF EDUCATION shows that individuals with more years of completed education have a lower BMI value than individuals with a shorter education career (coefficients are negative).…”

Section: (Continued )supporting

confidence: 80%

“…Kan and Tsai (2004) found that EDUCATION was statistically significant for all percentiles, while INCOME and INCOMESQ were not. Sanz-de-Galdeano (2005) found that the income effect was relevant for females but not for males.…”

Section: (Continued )mentioning

confidence: 89%

“…i) Following Kan and Tsai (2004) we enter the age and age squared of each respondent at the date of the interview to capture non-linear effects across age groups.…”

Section: Model Specificationmentioning

confidence: 99%

“…Therefore, in this context, working with the entire BMI distribution represents a clear advantage. 10 This approach is followed by Kan and Tsai (2004) to explore the relationship between knowledge of health risks and body mass at each quantile of the distribution.…”

Section: Introductionmentioning

confidence: 99%

“…Evidence in Sanz-de-Galdeano (2005) and Michaud et al (2007) suggests that cross-country differences in the returns to relevant determinants of obesity can be nonnegligible even between similar countries. Moreover, these factors have been shown to exert a heterogeneous influence on individuals' BMI at different points of its distribution (Kan and Tsai, 2004;Ruhm, 2007).…”

mentioning

confidence: 99%

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Decomposing body mass index gaps between Mediterranean countries: A counterfactual quantile regression analysis

Costa‐Font

Fabbri

Gil

2009

Economics & Human Biology

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Section: (Continued )supporting

confidence: 80%

Section: (Continued )mentioning

confidence: 89%

“…i) Following Kan and Tsai (2004) we enter the age and age squared of each respondent at the date of the interview to capture non-linear effects across age groups.…”

Section: Model Specificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Decomposing body mass index gaps between Mediterranean countries: A counterfactual quantile regression analysis

Costa‐Font

Fabbri

Gil

2009

Economics & Human Biology

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Expanding wallets and waistlines: the impact of family income on the BMI of women and men eligible for the Earned Income Tax Credit

2009

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The rising rate of obesity has reached epidemic proportions and is now one of the most serious public health challenges facing the U.S. (U.S. DHHS, 2001). But the underlying causes for this increase are unclear. This paper adds to the causal literature on this topic by exploring the importance of exogenous increases in family income on obesity measured using Body Mass Index (BMI) in the National Longitudinal Survey of Youth 1979 cohort. It does so by using exogenous variation in family income in a sample of low-income women and men obtained from the correlation of their family income with differences in the level of their state's Earned Income Tax Credit (EITC) supplement and variations in the federal EITC. Income significantly raises the BMI of EITC eligible men and women. An additional $1,000 increases men's (women's) BMI by 0.5 (1.4) pounds. These results imply that family income increases from 1990 to 2002 explain 3 percent of men's BMI increases and 15 percent women's BMI increases in the sample. JEL classifications: I12; I18; I38

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Do They Know What Is at Risk? Health Risk Perception Among the Obese

Winter

Wuppermann²

2013

Health Economics

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The perception of health risks and risky health behaviors are closely associated. In this paper, we investigate the accuracy of health risk perceptions among obese individuals, aged 50-62 years. We compare subjective risk perceptions for various diseases elicited in the American Life Panel to individual's objective risks of the same diseases. We find that obese individuals significantly underestimate their 5-year risks of arthritis or rheumatism and hypertension, whereas they systematically overestimate their 5-year risks of a heart attack and a stroke. Obese individuals are thus aware of some but not all obesity-related health risks. For given diseases, we document substantial heterogeneities in the accuracy of expectations across individuals.

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Obesity and risk knowledge

Cited by 98 publications

References 37 publications

Decomposing body mass index gaps between Mediterranean countries: A counterfactual quantile regression analysis

Decomposing body mass index gaps between Mediterranean countries: A counterfactual quantile regression analysis

Expanding wallets and waistlines: the impact of family income on the BMI of women and men eligible for the Earned Income Tax Credit

Do They Know What Is at Risk? Health Risk Perception Among the Obese

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