Low socioeconomic status (SES) has a strong negative impact on health in adulthood; however, very little is known about how SES impacts health during childhood. We propose that the effect of SES may not be consistent throughout all of childhood and adolescence, but rather, may change in strength as children pass through different stages of development. Documenting SES differences from early childhood through late adolescence is important because previous studies have often investigated childhood SES effects based on a wide age range of children. This approach runs the risk of drawing misleading conclusions (e.g., that SES impacts health across all of childhood) if in fact SES effects are attributable only to specific periods of childhood (e.g., early childhood but not adolescence). In the present study, we propose to conduct an empirical test of the interrelationships among age, SES and childhood health by analyzing two large, national datasets (National Health Interview Survey, 1994, and National Longitudinal Study of Youth- Children) that contain information about SES and childhood respiratory (e.g., asthma) and cardiovascular health outcomes. Through this secondary data analysis, we will test the hypothesis that the relationship between SES and health varies by age, and follows one of three patterns: Persistence model (constant effects of SES on health from early childhood through adolescence); Childhood limited model (SES effects on health that are strong in early childhood but decrease over time); or Adolescent emergent model (SES effects that are small early in life but gradually increase over time). The two datasets will allow us to address our hypotheses both cross-sectionally and longitudinally. Longitudinally, we will be able to address questions of whether early childhood SES continues to have a persistent effect on children's health (regardless of improvements in family SES later in life), and whether certain patterns of family SES (e.g., persistent poverty versus fluctuating SES) are most strongly associated with health as children age. Finally, given the large sample size, we can also begin to tease apart the effects of SES versus race on children's health. These analyses could have implications for how to time interventions to reduce health disparities in children, and for understanding the mediators that drive the relationship between SES and childhood health.