The Effect of Fast‐Food Availability on Obesity: An Analysis by Gender, Race, and Residential Location

Abstract

This paper employs an identification strategy based on county‐level variation in the number of fast‐food restaurants to investigate the effect of fast‐food availability on weight outcomes by geographic location, gender, and race/ethnicity. The number of interstate exits in the county of residence is employed as an instrument for restaurant location. Using the 2004–2006 Behavioral Risk Factor Surveillance System and self‐collected data on the number of fast‐food restaurants, I find that availability does not affect weight outcomes in rural counties, but does tend to increase body mass index among females and non‐Whites in medium‐density counties. These results are robust to specification choices.

An economy of scales: A selective review of obesity's economic causes, consequences, and solutions

“…Two studies use features of the interstate highway system as instruments for fast food density or distance in order to estimate the causal effects of fast food availability on weight. Dunn (2010) uses the number of interstate highway exits as an instrument for number of fast food restaurants in a county, with the rationale that nearby highway exit ramps imply more visitor traffic that supports additional fast food outlets for reasons that have nothing to do with the demand of residents. Dunn (2010) cannot reject the null hypothesis of no impact of availability or density of fast food outlets on the BMI of white residents in low-density or high-density counties, but finds some evidence that the number of outlets increases BMI among women and non-whites in medium-density counties.…”

Food away from home expenditures and obesity among older Europeans: are there gender differences?

“…While a number of recent papers have explicitly focused on availability of fast food restaurants as potential contributors to obesity (e.g., Rashad et al 2006;Dunn 2007Dunn , 2010; Anderson and Matsa 2009;Currie et al 2010;Chou et al 2008), few studies have examined the relationship between FAFH expenditures and obesity. You and Davis (2010) assessed the influence of household food expenditures, parental time allocation, and other parental factors on children's obesity-related health outcomes.…”

The Heterogeneity of the Cigarette Price Effect on Body Mass Index

“…If cigarette prices have heterogeneous effects on BMI both across BMI levels and demographic and socioeconomic characteristics, then it stands to reason that the influences of other environmental characteristics may be heterogeneous as well. Interesting insights may emerge from applying a similar methodological approach to the one used here to study 21 For a sample of research exploring these possibilities, see Lakdawalla and Philipson (2002), Philipson and Posner (2003), Cutler et al (2003), Chou et al (2004), Rashad (2006), Eid et al (2008), Chou et al (2008), Currie et al (2010), Dunn (2010), Zhao and Kaestner (2010), Courtemanche and Carden (2011), Anderson and Matsa (2011), Andreyeva et al (2011), Courtemanche (2011), andGoldman et al (forthcoming).…”