Public Nutrition Programs and Child Health

Two interesting working papers this week on the effect of major U.S. nutrition programs and child health. The first, by Douglas Almond and coauthors, examines the effect of the Food Stamp Program (FSP) on birth outcomes. Using variation in the roll-out of the program (Food Stamps became operative in different counties at different times during the 60s and 70s) to identify causal effects, the authors find that women exposed to the policy for three months or more of their pregnancy gave birth to heavier babies.

Daniel Millimet and coauthors study the School Breakfast Program (SBP) and the National School Lunch Program (NLSP), looking at the link between school feeding and childhood obesity. The authors find that the SBP works against the rising tide of childhood obesity while NSLP exacerbates it. Unfortunately, they offer little intuition for these opposing findings, especially when the two programs have similar inclusion criteria (i.e., they target poor students). One possibility might be the scope of the program: the NSLP serves twice as many students as the SBP. Another is the nutritional content of the meal: lunch is higher in calories (though similar in "healthiness").

Besides discussing issues of intrinsic interest to public health, these two papers are also noteworthy in their rigor in pursuing causal effects. The Millimet, et al study, in particular, uses a methodology where, recognizing that kids who enroll in SBP and NSLP are likely different than those who do not, they study the sensitivity of their results to different degrees of selection bias. Basically, the authors define a parameter for non-random selection into the program, and dial the level of this parameter up and down to see how their econometric results change. Very clever stuff. It's nice to see that, lacking experimental or even quasi-experimental program variation, such as that exploited in the Almond paper, it is still possible to say something about causality. The selection correction method utilized by Millimet, et al is simple and intuitive: I hope it finds it way into medical journals soon!