Mexico experiences an unbalanced distribution of wealth that causes a fifth of its population to suffer from food poverty. This has motivated several assistance programs. Most recently, in 2013, the Mexican government set in motion Sin Hambre (SH), one of the largest national strategies ever implemented in Mexico to fight hunger. I use a difference in difference approach exploiting timing and regional variations in exposure to SH to evaluate the impact of this strategy on birth outcomes. Since municipalities were not randomly assigned linear regression methodologies may lead to biased estimates. In order to address this concern and obtain causal estimates, I employ a multiperiod difference-in-difference matching method as proposed by Imai, Kim and Wang (2019). This method compares each treated unit to a control unit built to be similar to the treated observation in terms of outcome and covariate histories. I find that exposure to SH has moderate positive effects on birth weight on the year of implementation of at most 5 grams. The poorest municipalities, the set treated first by SH, show slightly larger effects but only in the longer-term of at most 10 grams.