NLS user since 1992
More than fifteen years ago, I got an email from an old college friend, the gifted pediatrician and health services researcher Richard Strauss. Rick worked in pediatric GI, and he did a lot of work with overweight kids. He was noticing increasing numbers of really obese kids in his practice. We decided that we should pull some data from the National Longitudinal Survey of Youth 1979 (NLSY79) to investigate. We found dramatic increases in child overweight between 1986 and 1998.
We also documented the emergence of race/ethnic and class disparities that hadn’t existed at the beginning of the time period we studied. We noted, within the confines of our tight conclusion section, some of the major contributing factors: Declining relative prices of fattening foods, rising costs of parental time that might be used for healthy food preparation, declining physical activity among children and youth.
Our analysis appeared in JAMA in 2001. Many more elaborate papers have appeared on the topic since then. I think JAMA published our simple paper because we produced one killer Powerpoint slide. Still, we were among the first to use nationally representative data in such a prominent forum. So our paper had an impact in child health policy. I remain grateful to Rick for initiating that work, which appeared at a critical moment of my career.
We had no specific grant to fund it. We employed zero research assistants. Our paper could have been written by a smart college senior.
We could do that work because we could download high-quality, nationally representative NLSY79 data. Youth born between 1958 and 1964 (and subsequently many of their own children) were followed over time, in some cases interviewed 25 times over the past 30 years.
NLSY79 data include kids’ heights and weights, well-implemented standardized tests, household composition and incomes, a variety of earnings records, self-reported health status and health behaviors, and much more. These rich datasets with high response rates allow researchers and policymakers to address many important questions people might not have thought of when the data were collected, and perhaps could not be answered any other way.