1

School Nutrition Programs and the Incidence

of Childhood ObesityRusty Tchernis

Indiana University

Daniel MillimetSouthern Methodist University

Muna HussainSouthern Methodist University

2

Motivation

• If policy is to be effective it needs to target children before habits are formed

• Here we look at the role of school nutrition programs: School Breakfast Program (SBP) and National School Lunch Program (NSLP)

• We use panel data to measure the “long run” effect of SBP and NSLP

3

Prevalence of Childhood Obesity

Source: CDC

4

Program Description

• NSLP started in 1946 and covers 95% of schools, 29M children, with 17.5M receiving reduced price or free lunch.

• SBP started in 1966, covers 82,000 schools (or 83% of schools on NSLP) and 9.6M children, with 7.7M receiving reduced price or free breakfast.

• For 100 students on NSLP roughly 45 are on SBP

5

Previous Studies• Fertig, Glomm, and Tchernis (2006) show that

consuming fewer meals (skipping breakfast) increases weight

• Bhattacharya, Currie, and Haider (2006) show that school breakfast improves the nutritional quality of the diet

• von Hippel, Powell, Downey, and Rowland (2007) show that most of the weight gain takes place during summer

• Hence, our prior beliefs were that the effects of SBP are positive

6

Economics of food transfersConsumption

A

C

B

■

■

Food

7

Data Set

• Early Childhood Longitudinal Study-Kindergarten Class of 1998-99 (ECLS-K)

• The sample includes over 13,500 children from kindergarten to third grade

• Treatment – SBP in kindergarten (20%)• Outcome – multiple weight measures in

spring third grade

8

SBP Results (OLS)Dep. Var.

Sample

BMI BMI growth rate

BMI percentile

Pr(Obese)

Full 0.281* 0.010* 2.176* 0.055

Normal 0.319* 0.014* 3.148* 0.185*

Overweight -0.159 -0.010 -1.524 -0.104

Obese 0.580‡ 0.017‡ 0.499 0.129

‡ p<0.10, † p<0.05, * p<0.01

9

SBP No SBP

NSLP Participation (1 = Yes) 0.893 0.42Urban Fringe & Large Town (1 = Yes) 0.259 0.419

South (1 = Yes) 0.508 0.286

Household Income (dollars) 34,544 57,415Number of Children's Books in Household 48.646 81.193

Summary Statistics

10

Future Work

• Better control for observable differences between treated and untreated populations (propensity scores)

• Gauge the effect of selection on unobserved variables

• Use Instrumental Variables to deal with selection into treatment