The factor structure of neuropsychological functioning among a large sample (N = 831) of American youth (ages 12-21 at baseline) was investigated in order to identify an optimal model. Candidate models were selected based on their potential to provide service to the study of adolescent development and the effects of heavy episodic alcohol consumption. Data on neuropsychological functioning were obtained from the NCANDA study. This is a longitudinal community study of the effects of alcohol exposure on neurodevelopment. Three conceptually motivated and one empirically motivated factor analysis model of neuropsychological domains were compared based on penalized-likelihood selection criteria and model fit statistics. Two conceptually-motivated models were found to have adequate fit and pattern invariance to function as a measurement model for the Penn Computerized Neurocognitive Battery (Penn CNB) anchored neuropsychological battery in NCANDA. Corroboration of previous factor analysis models was obtained, in addition to the identification of an alternative factor model that has higher discriminant capacity for neuropsychological domains hypothesized to be most sensitive to alcohol exposure in human adolescents. The findings support the use of a factor model developed originally for the Penn CNB and a model developed specifically for the NCANDA project. The NCANDA 8-Factor Model has conceptual and empirical advantages that were identified in the current and prior studies. These advantages are particularly valuable when applied in alcohol research settings.

We examined whether the often-reported protective association of alcohol with cardiovascular disease (CVD) risk could arise from confounding. Our sample comprised 908 men (56−67 years), free of prevalent CVD. Participants were categorized into 6 groups: never drinkers, former drinkers, and very light (1−4 drinks in past 14 days), light (5−14 drinks), moderate (15−28 drinks), and at-risk (>28 drinks) drinkers. Generalized linear mixed effect models examined the associations of alcohol use with three established CVD risk scores: The Framingham Risk Score (FRS); the atherosclerotic CVD (ASCVD) risk score; and the Metabolic Syndrome (MetS) Severity score, adjusting for group differences in demographics, body size, and health-related behaviors. In separate models we additionally adjusted for several groups of potentially explanatory factors including socioeconomic status, social support, physical and mental health status, childhood factors, and prior history of alcohol misuse. Results showed lower CVD risk among light and moderate alcohol drinkers, relative to very light drinkers, for all CVD risk scores, independent of demographics, body size, and health-related behaviors. Alcohol-CVD risk associations were robust to further adjustment for several groups of potential explanatory factors. Study limitations include the all-male sample with limited racial and ethnic diversity, and the inability to adjust for sugar consumption and for patterns of alcohol consumption. Although this observational study does not address causation, results show that middle-aged men who consume alcohol in moderation have lower CVD risk and better cardiometabolic health than men who consume little or no alcohol, independent of a variety of health, behavioral, psychosocial, and earlier life factors.

Objective

To determine associations of alcohol use with cognitive aging among middle-aged men.

Method

1,608 male twins (mean 57 years at baseline) participated in up to three visits over 12 years, from 2003-2007 to 2016-2019. Participants were classified into six groups based on current and past self-reported alcohol use: lifetime abstainers, former drinkers, very light (1-4 drinks in past 14 days), light (5-14 drinks), moderate (15-28 drinks), and at-risk drinkers (>28 drinks in past 14 days). Linear mixed-effects regressions modeled cognitive trajectories by alcohol group, with time-based models evaluating rate of decline as a function of baseline alcohol use, and age-based models evaluating age-related differences in performance by current alcohol use. Analyses used standardized cognitive domain factor scores and adjusted for sociodemographic and health-related factors.

Results

Performance decreased over time in all domains. Relative to very light drinkers, former drinkers showed worse verbal fluency performance, by -0.21 SD (95% CI -0.35, -0.07), and at-risk drinkers showed faster working memory decline, by 0.14 SD (95% CI 0.02, -0.20) per decade. There was no evidence of protective associations of light/moderate drinking on rate of decline. In age-based models, light drinkers displayed better memory performance at advanced ages than very light drinkers (+0.14 SD; 95% CI 0.02, 0.20 per 10-years older age); likely attributable to residual confounding or reverse association.

Conclusions

Alcohol consumption showed minimal associations with cognitive aging among middle-aged men. Stronger associations of alcohol with cognitive aging may become apparent at older ages, when cognitive abilities decline more rapidly.

Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (m_age = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.