Peer effects, fast food consumption and adolescent weight gain

Abstract

This paper aims at opening the black box of peer effects in adolescent weight gain. Using Add Health data on secondary schools in the U.S., we investigate whether these effects partly flow through the eating habits channel. Adolescents are assumed to interact through a friendship social network. We first propose a social interaction model of fast food consumption. Our approach allows to control for correlated effects at the network level and to solve the simultaneity (reflection) problem. We exploit results by Bramoullé, Djebbari and Fortin (2009) which show that if there are two agents who are separated by a link of distance 3 within a network (i.e., two adolescents who are not friends but are linked by two friends), peer effects are identified. The model is estimated using maximum likelihood and generalized 2SLS strategies. We also estimate a panel dynamic weight gain production function relating an adolescent's Body Mass Index (BMI) to his current fast food consumption and his lagged BMI level. Results show that there are positive significant peer effects in fast food consumption among adolescents belonging to a same friendship school network. The estimated social multiplier is 1.59. Our results also suggest that, at the network level, an extra day of weekly fast food restaurant visits increases BMI by 2.4%, when peer effects are taken into account.

High School Students Residing in Educational Public Institutions: Health-Risk Behaviors

“…This change has resulted in many public health challenges, as these ultraprocessed foods are dense in energy, trans fats, sugars, sodium, and chemical additives [52,53] and have been associated with overweightness and cardiovascular disease in the Brazilian population [47,54], including adolescents [55]. Foods listed by PENSE as markers of a healthy diet are basically natural or minimally processed, whereas ultraprocessed foods are unhealthy markers.…”

A Model of Addiction and Social Interactions

“…Despite the fact that these two phenomena often coexist-particularly among "sin goods"-they are usually examined in isolation. Empirical analyses of social interactions have examined their effect on alcohol (Kremer and Levy 2008), crime (Glaeser, Sacerdote, and Scheinkman 1996), disadvantaged youth (Case and Katz 1991), grades (Sacerdote 2001), obesity (Blanchflower, Van Landeghem, and Oswald 2009;Christakis and Fowler 2007;Fortin and Yazbeck 2015), and smoking (Fletcher 2010;Krauth 2007;Powell, Tauras, and Ross 2005). Prominent studies of addiction include Becker, Grossman, and Murphy (1994), Chaloupka (1991), Crawford (2010), Demuynck and Verriest (2013), and Gruber and Koszegi (2001).…”

Identity Economics: Social Influence and Skill Development

“…This is true for educational performance (Calvó‐Armengol et al ., ; Lin, ), and it remains the case even after employing methods to handle the endogeneity of friend selection (Goldsmith‐Pinkham and Imbens, ; Hsieh and Lee, ). This is also true for studies on friend influence and risky behaviors such as alcohol consumption, smoking, drug use, fighting, fast food consumption, and sexual behaviors (Ajilore, ; Fortin and Yazbeck, ; Lin, ; Fletcher and Ross, ).…”