We discuss semiparametric regression when only the ranks of responses are observed. The model is $Y_i = F (\mathbf{x}_i'{\boldsymbol\beta}_0 + \varepsilon_i)$, where $Y_i$ is the unobserved response, $F$ is a monotone increasing function, $\mathbf{x}_i$ is a known $p-$vector of covariates, ${\boldsymbol\beta}_0$ is an unknown $p$-vector of interest, and $\varepsilon_i$ is an error term independent of $\mathbf{x}_i$. We observe $\{(\mathbf{x}_i,R_n(Y_i)) : i = 1,\ldots ,n\}$, where $R_n$ is the ordinal rank function. We explore a novel estimator under Gaussian assumptions. We discuss the literature, apply the method to an Alzheimer's disease biomarker, conduct simulation studies, and prove consistency and asymptotic normality.

Background

Individuals with mental health conditions (MHC) have disproportionately high tobacco-related morbidity and mortality due to high smoking prevalence rates. As high consumers of cigarettes, smokers with MHC may consider using e-cigarettes as an alternative form of nicotine delivery.

Objective

Examination of the susceptibility to use e-cigarettes by individuals with MHC.

Methods

A U.S. population survey with a national probability sample (n=10,041) was used to assess ever use and current use of regular cigarettes, e-cigarettes, and U.S. Food and Drug Administration-approved pharmacotherapy for smoking cessation. Survey respondents provided information about whether they had been diagnosed with an anxiety disorder, depression, or other MHC.

Results

Individuals with MHC were more likely to have tried e-cigarettes (14.8%) and to be current users of e-cigarettes (3.1%) than those without MHC (6.6% and 1.1%, respectively; p<0.01). Ever smokers with MHC were also more likely to have tried approved pharmacotherapy (52.2% vs. 31.1%, p<0.01) and to be currently using these products (9.9% vs. 3.5%, p<0.01) than those without MHC. Additionally, current smokers with MHC were more susceptible to future use of e-cigarettes than smokers without MHC (60.5% vs. 45.3%, respectively, p<0.01).

Conclusions

Smokers with MHC are differentially affected by the rise in popularity of e-cigarettes. Clinical interventions and policies for tobacco control on e-cigarettes should take into account the possible outcomes and their implications for this priority population.

Background

Varenicline is known to have greater efficacy than other pharmacotherapy for treating nicotine dependence and has gained popularity since its introduction in 2006. This study examines if adding varenicline to existing pharmacotherapies increased the population cessation rate.

Methods

Data are from two cross-sectional US Current Population Surveys-Tobacco Use Supplements (2003 and 2010-2011). Smokers and recent quitters 18 or older (N=34 869 in 2003, N=27 751 in 2010-2011) were asked if they had used varenicline, bupropion or nicotine replacement therapies (NRT) in their most recent quit attempt. The annual cessation rate, as well as the per cent of smokers who had quit for ≥3 months, was compared between surveys.

Results

Varenicline use increased from 0% in 2003 to 10.9% in 2010-2011, while use of bupropion decreased from 9.1% to 3.5%, and NRT from 24.5% to 22.4%. Use of any pharmacotherapy increased by 2.4 percentage points. Varenicline users stayed on cessation aids longer and were less likely to relapse than users of other pharmacotherapies in the first 3 months of a quit attempt, after which the difference was no longer significant. The change in annual cessation rate was negligible, from 4.5% in 2003 to 4.7% in 2010-2011 (p=0.36).

Conclusions

Addition of varenicline to the list of approved cessation aids has mainly led to displacement of other therapies. As a result, there was no meaningful change in population cessation rate despite a remarkable increase in varenicline use. The population impact of a new therapy is a function of more than efficacy or reach of the therapy.

Introduction

Most successful trials of financial incentives for smoking cessation have offered large rewards contingent on outcomes. This study examines whether more modest incentives to encourage engagement, non-contingent on outcomes, also increase cessation; whether sending medications directly to participants boosts quitting; and whether these strategies are effective in Medicaid.

Study design

Three-group RCT of usual care (UC); nicotine patch (NP); and NP and financial incentive (NP+FI).

Setting/participants

Medicaid beneficiaries calling the California Smokers' Helpline, 2012-2013 (N=3,816). Data were analyzed in 2017.

Intervention

All participants enrolled in evidence-based, multisession telephone counseling. All received proof of enrollment with which they could obtain free quitting aids at their pharmacy. NP and NP+FI also received nicotine patches sent to their homes. NP+FI received up to $60 for completing counseling calls.

Main outcome measures

Quit attempt rate, 7-day and 30-day abstinence at 2 and 7 months, and 6-month prolonged abstinence (primary outcome).

Results

In both complete-case and intention-to-treat analyses, outcomes trended upward from UC to NP to NP+FI. Differences between NP and UC were generally nonsignificant. By contrast, the NP+FI group significantly outperformed the other groups on all measures. In intention-to-treat analysis, compared with UC, NP+FI was more likely to make a quit attempt (68.4% vs 54.3%, p<0.001); be abstinent for 7 days at 2 months (36.1% vs 25.5%, p<0.001) and 7 months (21.2% vs 16.1%, p=0.002); be abstinent for 30 days at 2 months (30.0% vs 18.9%, p<0.001) and 7 months (21.5% vs 16.7%, p=0.004); and achieve 6-month prolonged abstinence (13.2% vs 9.0%, p=0.001).

Conclusions

Financial incentives increased treatment engagement and short- and long-term smoking cessation, despite being modest and non-contingent on outcomes. The study found that incentives can be effective in a Medicaid population, and can feasibly be integrated into existing quitline services.

Trial registration

The trial is registered at www.clinicaltrials.gov NCT01502306.

Supplement information

This article is part of a supplement entitled Advancing Smoking Cessation in California's Medicaid Population, which is sponsored by the California Department of Public Health.

Objectives

We examined smoking cessation rate by education and determined how much of the difference can be attributed to the rate of quit attempts and how much to the success of these attempts.

Methods

We analyzed data from the National Health Interview Survey (NHIS, 1991-2010) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS, 1992-2011). Smokers (≥ 25 years) were divided into lower- and higher-education groups (≤ 12 years and >12 years).

Results

A significant difference in cessation rate between the lower- and the higher-education groups persisted over the last 2 decades. On average, the annual cessation rate for the former was about two thirds that of the latter (3.5% vs 5.2%; P<.001, for both NHIS and TUS-CPS). About half the difference in cessation rate can be attributed to the difference in quit attempt rate and half to the difference in success rate.

Conclusions

Smokers in the lower-education group have consistently lagged behind their higher-education counterparts in quitting. In addition to the usual concern about improving their success in quitting, tobacco control programs need to find ways to increase quit attempts in this group.

Background

E-cigarettes are purchased through multiple channels, including general retail, online, and specialty smoke and vape shops. We examine how e-cigarette users' primary purchase place relates to e-cigarette use and smoking cessation behaviors.

Methods

Probability-based samples of the U.S. population who were current e-cigarette users were surveyed in 2014 (N = 879) and 2016 (N = 743), with responses combined for most analyses. E-cigarette use and smoking cessation behaviors were compared across users' primary purchase place.

Results

Higher percentages of vape shop (59.1%) and internet (42.9%) customers were current daily users of e-cigarettes compared to retail (19.7%) and smoke shop (23.2%) customers (p-values < 0.001). Higher percentages of vape shop (40.2%) and internet (35.1%) customers were also former smokers, compared to 17.7% of retail and 19.3% of smoke shop customers (p's < 0.001). Among those smoking 12 months prior to survey, smoking cessation rates were higher for vape shop (22.2%) and internet customers (22.5%) than for retail customers (10.7%, p = 0.010 and p = 0.022, respectively), even though retail customers were more likely to use FDA-approved smoking cessation aids. The percentage of customers purchasing from vape shops increased from 20.4% in 2014 to 37.6% in 2016, surpassing general retail (27.7%) as the most likely channel in 2016.

Conclusions

E-cigarette customers differed in significant ways by channels of purchase, most notably in their smoking cessation behaviors. Previous population studies have relied mostly on retail channel data, which accounted for less than 30% of all products sold by 2016. Future studies of e-cigarette use should consider a broader set of channels.

The term "mapping" in the context of brain imaging conveys to most the concept of localization; that is, a brain map is meant to reveal a relationship between some condition or parameter and specific sites within the brain. However, in reality, conventional voxel-based maps of brain function, or for that matter of brain structure, are generally constructed using analyses that yield no basis for inferences regarding the spatial nonuniformity of the effects. In the normal analysis path for functional images, for example, there is nowhere a statistical comparison of the observed effect in any voxel relative to that in any other voxel. Under these circumstances, strictly speaking, the presence of significant activation serves as a legitimate basis only for inferences about the brain as a unit. In their discussion of results, investigators rarely are content to confirm the brain's role, and instead generally prefer to interpret the spatial patterns they have observed. Since "pattern" implies nonuniform effects over the map, this is equivalent to interpreting results without bothering to test their significance, a practice most of the experimentally-trained would eschew in other contexts. In this review, we appeal to investigators to adopt a new standard of data presentation that facilitates comparison of effects across the map. Evidence for sufficient effect size difference between the effects in structures of interest should be a prerequisite to the interpretation of spatial patterns of activation.

Background

In recent decades the overall smoking prevalence in the US has fallen steadily. This study examines whether the same trend is seen in the Medicaid population.

Methods and findings

National Health Interview Survey (NHIS) data from 17 consecutive annual surveys from 1997 to 2013 (combined N = 514,043) were used to compare smoking trends for 4 insurance groups: Medicaid, the Uninsured, Private Insurance, and Other Coverage. Rates of chronic disease and psychological distress were also compared.

Results

Adjusted smoking prevalence showed no detectable decline in the Medicaid population (from 33.8% in 1997 to 31.8% in 2013, trend test P = 0.13), while prevalence in the other insurance groups showed significant declines (38.6%-34.7% for the Uninsured, 21.3%-15.8% for Private Insurance, and 22.6%-16.8% for Other Coverage; all P's<0.005). Among individuals who have ever smoked, Medicaid recipients were less likely to have quit (38.8%) than those in Private Insurance (62.3%) or Other Coverage (69.8%; both P's<0.001). Smokers in Medicaid were more likely than those in Private Insurance and the Uninsured to have chronic disease (55.0% vs 37.3% and 32.4%, respectively; both P's<0.01). Smokers in Medicaid were also more likely to experience severe psychological distress (16.2% for Medicaid vs 3.2% for Private Insurance and 7.6% for the Uninsured; both P's<0.001).

Conclusions

The high and relatively unchanging smoking prevalence in the Medicaid population, low quit ratio, and high rates of chronic disease and severe psychological distress highlight the need to focus on this population. A targeted and sustained campaign to help Medicaid recipients quit smoking is urgently needed.