Using individual-level variation in famine exposure and intensity based on individual month-year-region of birth and historical data on the size of narrowly-defined birth cohorts, I find that exposure to famine negatively impacts adult height, lowers BMI, negatively affects health status, and reduces incidence of serious illness and hypertension. I use Inverse Probability Weighting and Joint Modeling of Longitudinal and Survival Data to account for selective mortality bias in health outcome equations. Contributions are mainly threefold: first, I exploit individual-level variation in timing and length of exposure, which serves as a more precise proxy for famine. Secondly, I include additional health variables into my analysis. Finally, I apply innovative techniques to account for selective mortality bias.