The Sequencing of a College Degree during the Transition to Adulthood: Implications for Obesity

In this study we consider the health implications of the sequencing of a college degree vis-à-vis familial roles during the transition to adulthood. We hypothesize that people who earned a college degree before assuming familial roles will have better health than people who earned a college degree afterwards. To test this hypothesis, we focus on obesity and use data from the National Longitudinal Study of Adolescent Health. Results show that marriage before completion of college was associated with a 50% higher probability of becoming obese when compared with marriage after completion of college. Parenthood before college completion was associated with a greater-than two-fold increase in the probability of becoming obese when compared to parenthood afterwards for Black men. These findings suggest that the well-established association of education with health depends on its place in a sequence of roles

Monitoring the Future national survey results on drug use, 1975-2019: Volume II, college students and adults ages 19-60

http://deepblue.lib.umich.edu/bitstream/2027.42/162576/1/2019-20 VOL II FINAL 3.pdfSEL

Monitoring the Future national survey results on drug use, 1975-2019: Volume I, Secondary school students

http://deepblue.lib.umich.edu/bitstream/2027.42/162578/4/license_rdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162578/1/Vol 1 2019 FINAL (original).pdfSEL

Checking Assumptions in Latent Class Regression Models via a Markov Chain Monte Carlo Estimation Approach: An Application to Depression and Socio-Economic Status

Latent class regression models are useful tools for assessing associations between covariates and latent variables. However, evaluation of key model assumptions cannot be performed using methods from standard regression models due to the unobserved nature of latent outcome variables. This paper presents graphical diagnostic tools to evaluate whether or not latent class regression models adhere to standard assumptions of the model: conditional independence and non-differential measurement. An integral part of these methods is the use of a Markov Chain Monte Carlo estimation procedure. Unlike standard maximum likelihood implementations for latent class regression model estimation, the MCMC approach allows us to calculate posterior distributions and point estimates of any functions of parameters. It is this convenience that allows us to provide the diagnostic methods that we introduce. As a motivating example we present an analysis focusing on the association between depression and socioeconomic status, using data from the Epidemiologic Catchment Area study. We consider a latent class regression analysis investigating the association between depression and socioeconomic status measures, where the latent variable depression is regressed on education and income indicators, in addition to age, gender, and marital status variables. While the fitted latent class regression model yields interesting results, the model parameters are found to be invalid due to the violation of model assumptions. The violation of these assumptions is clearly identified by the presented diagnostic plots. These methods can be applied to standard latent class and latent class regression models, and the general principle can be extended to evaluate model assumptions in other types of models

Monitoring the Future national survey results on drug use, 1975-2019: Overview, key findings on adolescent drug use

http://deepblue.lib.umich.edu/bitstream/2027.42/162579/1/FINAL.pdfSEL

Demographic subgroup trends among adolescents in the use of various licit and illicit drugs, 1975-2019 (Monitoring the Future Occasional Paper No. 94)

http://deepblue.lib.umich.edu/bitstream/2027.42/162581/1/mtf-occ94.pdfSEL

Monitoring the Future national survey results on drug use, 1975-2018: Volume II, college students and adults ages 19-60

https://deepblue.lib.umich.edu/bitstream/2027.42/150623/1/2018-19 VOL II FINAL 2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150623/3/license_rd

Monitoring the Future national survey results on drug use, 1975-2018: Overview, key findings on adolescent drug use

https://deepblue.lib.umich.edu/bitstream/2027.42/150621/1/Overview 2018 FINAL print 2-25.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150621/3/license_rd

Monitoring the Future national survey results on drug use, 1975-2018: Volume I, Secondary school students

https://deepblue.lib.umich.edu/bitstream/2027.42/150622/1/Vol 1 2018 FINAL3.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150622/2/Vol 1 2018 FINAL3.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150622/4/license_rd

A life course model of self-rated health through adolescence and young adulthood

This paper proposes and tests a life course model of self-rated health (SRH) extending from late childhood to young adulthood, drawing on three waves of panel data from the U.S. National Longitudinal Study of Adolescent Health (Add Health). Very little research has examined SRH during the early decades, or whether and how these self-assessments reflect experiences in the family of origin. Background characteristics (parental education, income, and family structure), parental health conditions (asthma, diabetes, obesity, migraines), and early health challenges (physical abuse, presence of a disability, and parental alcoholism and smoking) predict SRH from adolescence to young adulthood. These experiences in the family-of-origin are substantially mediated by the young person’s health and health behaviors (as indicated by obesity, depression, smoking, drinking, and inactivity), although direct effects remain (especially for early health challenges). Associations between SRH and these mediators (especially obesity) strengthen with age. In turn, efforts to promote healthy behaviors in young adulthood, after the completion of secondary school, may be especially strategic in the promotion of health in later adulthood