Objective:Little consensus exists regarding the relationship between socioeconomic status (SES) and substance use. This study examined the associations of three indicators of family SES during chil...

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.

Adolescent alcohol consumption is a major public health problem in the United States and a high priority for organizations, such as the Office of the Surgeon General,¹ Centers for Disease Control and Prevention,² World Health Organization,³ American Academy of Pediatrics,⁴ and National Institute on Alcohol Abuse and Alcoholism.⁵ Approximately 5000 persons younger than 21 years die each year from alcohol-related fatalities,⁶ while problems linked to underage drinking were estimated in 2001 to cost about $62 billion.⁷ Underage drinking is also a predictor of alcohol problems and early mortality in adulthood.^8-11

We apply latent transition analysis (LTA) to characterize transitions over time in substance use behavior profiles among first-year college students. Advantages of modeling substance use behavior as a categorical latent variable are demonstrated. Alcohol use (any drinking and binge drinking), cigarette use, and marijuana use were assessed in a sample (N=718) of college students during the fall and spring semesters. Four profiles of 14-day substance use behavior were identified: (1) Non-Users; (2) Cigarette Smokers; (3) Binge Drinkers; and (4) Bingers with Marijuana Use. The most prevalent behavior profile at both times was the Non-Users (with over half of the students having this profile), followed by Binge Drinkers and Bingers with Marijuana Use. Cigarette Smokers were the least prevalent behavior profile. Gender, race/ethnicity, early onset of alcohol use, grades in high school, membership in the honors program, and friendship goals were all significant predictors of substance use behavior profile.

Objective To prospectively examine vaping as a predictor of future cigarette smoking among youth with and without previous cigarette smoking experience. A secondary aim is to investigate whether vaping may desensitise youth to the dangers of smoking. Methods Analysis of prospective longitudinal panel data from the nationally representative Monitoring the Future study. The analysis is based on 347 12th grade students who were part of a randomly selected subsample that completed in-school surveys in 2014 and were resurveyed 1-year later. Results Among youth who had never smoked a cigarette by 12th grade, baseline, recent vapers were more than 4 times (relative risk (RR)=4.78) more likely to report past-year cigarette smoking at follow-up, even among youth who reported the highest possible level of perceived risk for cigarette smoking at baseline. Among 12th grade students who had smoked in the past but had not recently smoked at baseline, recent vapers were twice (RR=2.15) as likely to report smoking in the past 12 months at the follow-up. Vaping did not predict cessation of smoking among recent smokers at baseline. Among never-smokers at baseline, recent vapers were more than 4 times (RR=4.73) more likely to move away from the perception of cigarettes as posing a ‘great risk’ of harm, a finding consistent with a desensitisation process. Conclusions These results contribute to the growing body of evidence supporting vaping as a one-way bridge to cigarette smoking among youth. Vaping as a risk factor for future smoking is a strong, scientifically-based rationale for restricting youth access to e-cigarettes.