Background-Numerous interventions have been shown to increase physical activity, but have not been ranked by effectiveness or cost.

Objectives Twenty-eight states in the U.S. have legalized medical marijuana, yet its impacts on severe health consequences such as hospitalizations remain unknown. Meanwhile, the prevalence of opioid pain reliever (OPR) use and outcomes has increased dramatically. Recent studies suggested unintended impacts of legalizing medical marijuana on OPR, but the evidence is still limited. This study examined the associations between state medical marijuana policies and hospitalizations related to marijuana and OPR. Methods State-level annual administrative records of hospital discharges during 1997–2014 were obtained from the State Inpatient Databases (SID). The outcome variables were rates of hospitalizations involving marijuana dependence or abuse, opioid dependence or abuse, and OPR overdose in 1,000 discharges. Linear time-series regressions were used to assess the associations of implementing medical marijuana policies to hospitalizations, controlling for other marijuana- and OPR-related policies, socioeconomic factors, and state and year fixed effects. Results Hospitalizations related to marijuana and OPR increased sharply by 300% on average in all states. Medical marijuana legalization was associated with 23% (p=.008) and 13% (p=.025) reductions in hospitalizations related to opioid dependence or abuse and OPR overdose, respectively; lagged effects were observed after policy implementation. The operation of medical marijuana dispensaries had no independent impacts on OPR- related hospitalizations. Medical marijuana polices had no associations with marijuana-related hospitalizations. Conclusion Medical marijuana policies were significantly associated with reduced OPR-related hospitalizations but had no associations with marijuana-related hospitalizations. Given the epidemic of problematic use of OPR, future investigation is needed to explore the causal pathways of these findings.

IMPORTANCE Cigarette marketing contributes to initiation of cigarette smoking among young people, which has led to restrictions on use of cigarette advertising. However, little is known about other tobacco advertising and progression to tobacco use in youth and young adults. OBJECTIVE To investigate whether receptivity to tobacco advertising among youth and young adults is associated with progression (being a susceptible never user or ever user) to use of the product advertised, as well as conventional cigarette smoking. DESIGN, SETTING, AND PARTICIPANTS The Population Assessment of Tobacco and Health (PATH) Study at wave 1 (2013-2014) and 1-year follow-up at wave 2 (2014-2015) was conducted in a US population-based sample of never tobacco users aged 12 to 24 years from wave 1 of the PATH Study (N = 10 989). Household interviews using audio computer-assisted self-interviews were conducted. EXPOSURES Advertising for conventional cigarettes, electronic cigarettes (e-cigarettes), cigars, and smokeless tobacco products at wave 1. MAIN OUTCOMES AND MEASURES Progression to susceptibility or ever tobacco use at 1-year follow-up in wave 2. RESULTS Of the 10 989 participants (5410 male [weighted percentage, 48.3%]; 5579 female [weighted percentage, 51.7%]), receptivity to any tobacco advertising at wave 1 was high for those aged 12 to 14 years (44.0%; 95% confidence limit [CL], 42.6%-45.4%) but highest for those aged 18 to 21 years (68.7%; 95% CL, 64.9%-72.2%). e-Cigarette advertising had the highest receptivity among all age groups. For those aged 12 to 17 years, susceptibility to use a product at wave 1 was significantly associated with product use at wave 2 for conventional cigarettes, e-cigarettes, cigars, and smokeless tobacco products. Among committed never users aged 12 to 17 years at wave 1, any receptivity was associated with progression toward use of the product at wave 2

Employers struggle with the high cost of health care, lost productivity, and turnover in their workforce. The present study aims to understand the association between overall well-being and these employer outcomes. In a sample of 11,700 employees who took the Well-being Assessment, the authors used multivariate linear and logistic regression to investigate overall well-being as a predictor of health care outcomes (total health care expenditure, emergency room visits, hospitalizations), productivity outcomes (unscheduled absence, short-term disability leave, presenteeism, job performance ratings), and retention outcomes (intention to stay, voluntary turnover, involuntary turnover). Testing this hypothesis both cross-sectionally and longitudinally, the authors investigated the association between baseline well-being and these outcomes in the following year, and the relationship between change in overall well-being and change in these outcomes over 1 year. The results demonstrated that baseline overall well-being was a significant predictor of all outcomes in the following year when holding baseline employee characteristics constant. Change in overall well-being over 1 year also was significantly associated with the change in employer outcomes, with the exception that the relationship to change in manager-rated job performance was marginally significant. The relationships between overall wellbeing and outcomes suggest that implementing a well-being improvement solution could have a significant bottom and top line impact on business performance. (Population Health Management 2013;16:397-405)