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Can nutritional label use influence body weight outcomes?

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dc.contributor.author Drichoutis, AC en
dc.contributor.author Nayga Jr, RM en
dc.contributor.author Lazaridis, P en
dc.date.accessioned 2014-06-06T06:49:13Z
dc.date.available 2014-06-06T06:49:13Z
dc.date.issued 2009 en
dc.identifier.issn 00235962 en
dc.identifier.uri http://dx.doi.org/10.1111/j.1467-6435.2009.00448.x en
dc.identifier.uri http://62.217.125.90/xmlui/handle/123456789/4495
dc.subject.other data set en
dc.subject.other estimation method en
dc.subject.other heterogeneity en
dc.subject.other nutrition en
dc.subject.other New York [New York (STT)] en
dc.subject.other New York [United States] en
dc.subject.other North America en
dc.subject.other United States en
dc.title Can nutritional label use influence body weight outcomes? en
heal.type journalArticle en
heal.identifier.primary 10.1111/j.1467-6435.2009.00448.x en
heal.publicationDate 2009 en
heal.abstract Many countries around the world have already mandated, or plan to mandate, the presence of nutrition related information on most pre-packaged food products. Health advocates and lobbyists would like to see similar laws mandating nutrition information in the restaurant and fast-food market as well. In fact, New York City has already taken a step forward and now requires all chain restaurants with 15 or more establishments anywhere in US to show calorie information on their menus and menu board. The benefits were estimated to be as much as 150,000 fewer obese New Yorkers over the next five years.The implied benefits of the presence of nutrition information are that consumers will be able to observe such information and then make informed (and hopefully healthier) food choices. In this study, we use the latest available dataset from the US National Health and Nutrition Examination Survey (2005-2006) to explore whether reading such nutrition information really has an effect on body weight outcomes. In order to deal with the inherent problem of cross-sectional datasets, namely self-selection, and the possible occurrence of reverse causality we use a propensity score matching approach to estimate causal treatment effects.We conducted a series of tests related to variable choice of the propensity score specification, quality of matching indicators, robustness checks, and sensitivity to unobserved heterogeneity, using Rosenbaum bounds to validate our propensity score exercise. Our results generally suggest that reading nutrition information does not affect body mass index. The implications of our findings are also discussed. © 2009 Blackwell Publishing Ltd. en
heal.journalName Kyklos en
dc.identifier.issue 4 en
dc.identifier.volume 62 en
dc.identifier.doi 10.1111/j.1467-6435.2009.00448.x en
dc.identifier.spage 500 en
dc.identifier.epage 525 en


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