James C. Anthony’s research while affiliated with Michigan State University and other places

Background and Objectives Prenatal cannabis use prevalence in the United States has increased. Relaxation of state‐level cannabis policy may be contributing to the diminished risk perception of using cannabis. The main psychoactive constituent of cannabis, delta‐9‐tetrahydrocannabinol, crosses the placenta, interacting with functional cannabinoid receptors in the fetus. Here, we assess the association between prenatal cannabis exposure (PCE) and a set of birth outcomes. Methods Using the Michigan Archive for Research on Child Health, a prospective pregnancy cohort, we linked prenatal survey data with neonatal data from state‐archived birth records. Recruitment occurred in 23 clinics across Michigan. Pregnant participants with live birth records between October 2017 and January 2022, after exclusion for missing data on cannabis use, birth outcomes, and covariates, were included in the final analytic sample ( n = 584). Analyses involved generalized linear models. Results An estimated 15% (95% confidence interval [CI]: 12%, 18%) of participants reported using cannabis during pregnancy. Covariate‐adjusted models revealed an association between PCE and birth size ( ß = −0.3; 95% CI: −0.5, −0.003). Discussion and Conclusions Findings suggest a relationship between PCE and smaller birth size. Clinicians should follow guidelines outlined by the American College of Obstetricians and Gynecologists when counseling pregnant patients on cannabis use. Scientific Significance We detected a significant association between PCE and birth size. Most studies focus only on the extremes of birth size, however, use of z ‐scores allow for assessment of the sex‐specific birth weight‐for‐gestational age distribution, increasing the accuracy of detecting an effect of cannabis exposure on birth size.

Background Health impacts of pediatric fruit and vegetable prescription programs (FVPPs) are unclear. This study assessed whether exposure to an FVPP that provided $15 produce prescriptions during pediatric visits was associated with differences in child diet, food security, physical activity, weight status, and blood pressure. Methods This cross-sectional analysis included data from caregiver-child dyads with varying levels of exposure to the FVPP. Dyads completed surveys at pediatric offices. Trained research assistants measured height and weight of children and recorded blood pressure through chart review. Causal inference analyses using propensity score adjustments compared outcomes of exposure groups. Results 680 dyads enrolled. Youth who received ≥1 prescription (exposed) reported greater physical activity compared to youth who received no prescriptions (unexposed). Blood pressure percentiles were lower among exposed when compared to unexposed youth (63.273 versus 75.060 for SBP; 71.472 versus 77.548 for DBP); and fewer exposed children recorded elevated blood pressure when compared to unexposed (0.141 versus 0.343 for SBP; 0.199 versus 0.344 for DBP; and 0.286 versus 0.531 overall). Similar findings were obtained using duration as a measure of exposure. Conclusion Youth exposed to the FVPP experienced greater physical activity and healthier blood pressure. Findings may indicate novel health-promoting effects of pediatric FVPPs. Impact When compared to youth with no exposure, youth exposed to a pediatric fruit and vegetable prescription program recorded greater physical activity and healthier blood pressure. Youth with high exposure (≥24 months) to the fruit and vegetable prescription program experienced greater physical activity and healthier blood pressure when compared to youth with low exposure (<24 months). This extends evaluation of pediatric fruit and vegetable prescription programs beyond feasibility and preliminary effectiveness to indicate potential of such programs in positively influencing physical activity and blood pressure of participating youth. Findings indicate novel health-promoting effects of pediatric fruit and vegetable prescription programs.

Liberalized state-level recreational cannabis policies in the United States (US) fostered important policy evaluations with a focus on epidemiological parameters such as proportions [e.g., active cannabis use prevalence; cannabis use disorder (CUD) prevalence]. This cannabis policy evaluation project adds novel evidence on a neglected parameter–namely, estimated occurrence of newly incident cannabis use for underage (<21 years) versus older adults. The project’s study populations were specified to yield nationally representative estimates for all 51 major US jurisdictions, with probability sample totals of 819,543 non-institutionalized US civilian residents between 2008 and 2019. Standardized items to measure cannabis onsets are from audio computer-assisted self-interviews. Policy effect estimates are from event study difference-in-difference (DiD) models that allow for causal inference when policy implementation is staggered. The evidence indicates no policy-associated changes in the occurrence of newly incident cannabis onsets for underage persons, but an increased occurrence of newly onset cannabis use among older adults (i.e., >21 years). We offer a tentative conclusion of public health importance: Legalized cannabis retail sales might be followed by the increased occurrence of cannabis onsets for older adults, but not for underage persons who cannot buy cannabis products in a retail outlet. Cannabis policy research does not yet qualify as a mature science. We argue that modeling newly incident cannabis use might be more informative than the modeling of prevalences when evaluating policy effects and provide evidence of the advantages of the event study model over regression methods that seek to adjust for confounding factors.

The population relationship between coefficient alpha and scale reliability is studied in the widely used setting of unidimensional multicomponent measuring instruments. It is demonstrated that for any set of component loadings on the common factor, regardless of the extent of their inequality, the discrepancy between alpha and reliability can be arbitrarily small in any considered population and hence practically ignorable. In addition, the set of parameter values where this discrepancy is negligible is shown to possess the same dimensionality as that of the underlying model parameter space. The article contributes to the measurement and related literature by pointing out that (a) approximate or strict loading identity is not a necessary condition for the utility of alpha as a trustworthy index of scale reliability, and (b) coefficient alpha can be a dependable reliability measure with any extent of inequality in the component loadings.