Cigarette smoking continues to be the single greatest preventable cause of disease and death in the United States [1]. The US federal government's first nationally-representative survey of cigarette smoking and other tobacco use behaviors took place in 1955 as a supplement to the US Census [2]. Since then federally sponsored tobacco surveillance has grown to include several established data collection systems routinely implemented at the national level, some of which have been adapted, sponsored, and implemented at the state level [3–5]. As one of the World Health Organization (WHO) MPOWER package's six proven tobacco prevention and control policies [6], tobacco prevention and control monitoring systems and their maintenance and enhancement are an essential part of public health practice [7]. Specifically, WHO calls for monitoring systems that track multiple anti- and protobacco attitude, behavior, and policy indicators; disseminate findings to facilitate utilization; provide overall as well as demographic subpopulation data at the national, state, and, where practicable, local levels; maximize system sustainability through cross-discipline collaboration, strong management and organization, and sound funding [6].

Understanding, documenting, and quantifying the characteristics of the tobacco user, or potential user, have been key to tobacco control efforts [4]. A variety of existing monitoring, research, and evaluation systems are available to collect such information [4], with increasing demand for surveillance data to inform evidence-based public health tobacco initiatives necessitating their periodic review [5]. At the national level, the National Health Interview Survey (NHIS) has been the data source used to measure progress on Healthy People adult tobacco-use prevalence objectives since the first ever release of national health objectives (Healthy People 1990) [8, 9]. Adult tobacco-use prevalence can be estimated from other national surveys as well [3], allowing evaluation of any differences in prevalence magnitude or in trends over time between data sources; however, there have been few studies comparing their smoking prevalence estimates [10]. A comparison of estimates from the 1997 NHIS and national estimates from the 1997 Behavioral Risk Factor Surveillance System (BRFSS) surveys [11] found current smoking prevalence to be significantly higher in NHIS than in BRFSS (24.7% versus 23.1%). Differences were also observed in a Substance Abuse and Mental Health Services Administration (SAMHSA) report [12] that described smoking prevalence estimates from the 2005 National Survey on Drug Use and Health (NSDUH). SAMHSA reported that estimates from NSDUH were higher (26.5%) than estimates obtained from the 2005 NHIS (20.9%), even after applying the NHIS current smoking definition to NSDUH data limiting smokers only to those who reported smoking ≥100 cigarettes in their lifetime (24.7% in NSDUH using NHIS definition). In a 2009 report comparing NHIS and NSDUH current smoking prevalence for the period 1998–2005, Rodu and Cole [10] describe an increasingly divergent picture of smoking prevalence in the USA between 1999 and 2005. Rodu's secondary analysis of NHIS and NSDUH data indicated that by 2005 NHIS prevalence had declined to approximately 21% while the NSDUH estimate was approximately 25%, with the latter but not the former suggesting a plateau in smoking prevalence. This pattern then reversed with a 2010 report using NHIS data that indicated a stall in the prevalence of adult smoking from 2005 (20.9%) to 2009 (20.6%) [13] while SAMHSA's primary analysis of NSDUH data suggested a continuing decline from 26.5% to 24.9% during the same period [12].

Key methodological issues, such as sampling design, survey mode and setting, and survey question standardization and context, have the potential to influence data quality and comparability [4]. Differences in the survey questions used to define current smoking are thought to be one of the probable methodological sources of discrepancy between NHIS and NSDUH smoking estimates. Most notably, NHIS limits its question of current smoking to respondents who on a previous question reported smoking ≥100 cigarettes in their lifetime (i.e., NHIS “ever smokers,” with “never smokers” then defined as respondents with lifetime smoking anywhere between 0 and 99 cigarettes). NSDUH also limits its current smoking definition based on reported ever smoking behavior; however, other than an implicit zero, it does not designate a cut-point for number of lifetime cigarettes smoked for categorizing “ever smokers” versus “never smokers.”

Levels of cigarette consumption—such as number of cigarettes smoked per day, number of days smoked per month, and amount of lifetime cigarette use—have often served as a proxy for other key tobacco control indicators, such as secondhand smoke exposure, nicotine addiction, and health risk [14]. This, however, may not necessarily be advisable practice. A review by Husten (2009) [14] concluded that consumption is a crude measure of both toxin exposure and nicotine dependence and, with respect to toxin exposure, likely inaccurate as well. Likewise, with respect to health risk, the review concluded that no level of consumption could be considered “safe,” and thus used to demarcate a risk threshold. Research specific to whether 100 lifetime cigarettes is a discriminating cut-point for distinguishing ever smokers versus never smokers—and, subsequently, for defining who is, ever has been, or may become a current smoker—is limited [15] but indicates that it too may be unsuitable. In a study of craving patterns, tolerance, and subjective responses to the pharmacological effects of smoking, findings from Pomerleau et al. (2004) [16] indicated 20 cigarettes per lifetime may be a more prudent marker than 100 for such a differentiation. Others have proposed that liability for dependence and subsequent uptake of smoking may even be distinguishable after an individual's very first puff [17]. Additionally, non-daily and light daily smoking—behaviors consistent with current cigarette smoking but lifetime smoking <100 cigarettes—have been found to significantly vary across racial/ethnic subpopulations [18–24]. Findings from Trinidad et al. (2009) [24] indicated non-Hispanic black, Asian/Pacific Islander, and Hispanic/Latino smokers were more likely to be nondaily and light daily smokers compared with non-Hispanic whites, even after controlling for age, gender, and education level. This was particularly true of Hispanic/Latino smokers, who were 3.2 times more likely to be non-daily smokers and 4.6 times more likely to be daily smokers who smoke ≤5 cigarettes per day as compared with non-Hispanic white smokers. Furthermore, Hispanic/Latino non-daily smokers smoked fewer days per month and smoked fewer cigarettes per day on the days they did smoke compared with non-Hispanic whites.

Infrequent smoking and smoking trajectories among adults remain open research issues. Youth data emerging over the past decade, however, have consistently concluded the trajectory of smoking begins with the loss of autonomy that occurs during infrequent use [25–30]. Among adults who have adopted the practice of infrequent smoking, research not only suggests it can remain a stable pattern lasting long periods of time [31–33] but that it also poses substantial health risk with adverse outcomes paralleling dangers observed among daily smoking, especially for cardiovascular disease [34]. Such results have notable implications for the understanding of tobacco dependence and the development of prevention and cessation strategies, especially for racial/ethnic minorities.

While differences in current smoking estimates between NHIS and NSDUH have been previously reported [10, 12], more in-depth examination directed specifically at methodology and how differences may affect comparability with other surveys is needed [10, 35]. Therefore, the current report makes comparisons between NHIS and NSDUH prevalence estimates using, for NHIS data, the standard NHIS definition of current smoking, which includes a screener question for a level of lifetime smoking ≥100 cigarettes and, for NSDUH data, using both the standard NSDUH definition of current smoking, which does not use the screener question, and a modified definition that applies the NHIS current smoking definition (i.e., with 100-cigarette restriction) to NSDUH data. Specifically, the following research questions are addressed: (1) how and for what subpopulations and smoking behaviors might the ≥100 lifetime cigarettes criterion affect adult prevalence estimates? and (2) what subpopulations are most likely to have smoked during the past 30 days but not meet the ≥100 lifetime cigarettes criterion? Findings are presented by sociodemographic characteristics for current smoking and for daily smoking among current smokers.

In comparisons between NHIS and NSDUH, NSDUH consistently yielded higher national overall and subpopulation estimates of current cigarette smoking among adults than NHIS and, among current smokers, lower estimates of daily smoking. However, with the use of the modified NSDUH-M current smoking variable definition that, like the NHIS definition, is restricted to respondents with lifetime cigarette use ≥100 cigarettes, estimates generally shifted closer to NHIS estimates, and several subgroups differences that were statistically significant for NHIS versus NSDUH-S became comparable for NHIS versus NSDUH-M. Specifically, estimate comparability occurred for the current smoking variable among 35–49-year olds, females, non-Hispanic black respondents, and those with <high school, high school graduate, or some college educational level, and, for the daily smoking variable, among 26–34 year olds and Asian respondents. Among Hispanic respondents, comparability occurred for both the current smoking variable and the daily smoking variable. In these instances, enough NSDUH respondents who reported smoking during the past 30 days had smoked fewer than 100 lifetime cigarettes (i.e., NSDUH-M) to negate the significant differences originally observed when level of lifetime cigarette use was not taken into account (i.e., NSDUH-S). The 100 cigarette prerequisite appeared to impact current smoking estimates much more extensively than it did smoking frequency estimates; that is, inclusion of the prerequisite produced comparability in estimates extensively across all four demographic categories for current smoking, whereas comparability occurred only minimally for daily smoking.

Subpopulations most impacted by the restriction of the current smoker variable definition to respondents with lifetime cigarette use ≥100 cigarettes appear to be younger adults and racial/ethnic minorities. The current smoking estimate comparability that occurred with use of the NSDUH-M current smoking definition represents a loss of significant differences originally observed between NHIS and NSDUH-S for the 35–49-years age group, females, non-Hispanic blacks, Hispanics, and the <high school, high school graduate, and some college educational levels. The daily smoking estimate comparability that occurred represents a loss of significant differences originally observed between NHIS and NSDUH-S for the 26–34-years age group, Asians, and Hispanics. Within this, Hispanic smoking prevalence appeared to be the most sensitive to differences in smoking variable definitions as this was the only group for which estimate comparability occurred across both current smoking and daily smoking.

These findings are consistent with other studies showing restriction of the adult current smoking definition to respondents with lifetime cigarette use ≥100 cigarettes leads to lower prevalence estimates [10, 12, 13], especially among minorities [46]. They are also consistent with previous studies that specifically found Hispanic smokers were most likely to be nondaily smokers and to smoke fewer days per month than non-Hispanic respondents [18, 19, 21–24, 31, 47]. It was the tobacco industry itself, however, that showed foresight into the relevance of such nuances and the subsequent opportunities afforded by what it termed “occasional smokers,” and during the 1990s took an interest in this group. Indeed, tobacco industry workshop materials from 1996 explained that occasional smokers may or may not self-identify as a smoker [47]. Data collection efforts by Philip Morris that took place in the late 1990s specifically focused on those who did not identify as a smoker and defined occasional smokers simply to be people who referred to themselves as nonsmokers, responded “yes” when asked if they smoked one or more cigarettes in the past year, and responded “no” when asked if they presently smoke at least a pack a week [48]. Internal communications summarizing the resulting data noted that “Hispanics represent substantially more than their fair share of occasional smokers” [49].

Husten (2009) [14] states that the stability of the behavior within any definitional category or categories of occasional use is an important consideration in determining a definition of the term. We take this line of thought a step further by applying stability criteria within a particular variable definition and across multiple subpopulations. The current analysis indicates that WHO's call for the provision of overall as well as demographic subpopulation data [6] may not be accurately met if a single current smoking definition is utilized for all subgroups when those same groups are known to differ on a key component of the variable's definition (i.e., occasional use). Like Husten, we reason that levels of consumption may be best left as continuous variables rather than presumptive cut-points, as there do not seem to be clear consumption levels that correlate with the onset of dependence or health risk. As noted, data that definitionally include rather than exclude lower consumption patterns have significant implications for the understanding of tobacco use and addiction and the development of prevention and cessation strategies—such as the extent to which intervention messages do versus do not address non-daily smoking [20], health risks of any smoking [31], motivations other than health effects [20], beliefs about ability to quit [23], situational triggers [31], social and cultural forces [23], and attitude changes [50]—especially for racial/ethnic minorities.

Measures relevant to occasional smokers are needed to be able to adequately monitor and describe their cigarette use, motivations, nicotine dependence, and cessation behaviors [50], underscoring the importance for national surveillance systems to use multiple comparable prevalence measures to capture diverse smoking behaviors, especially among subgroups. Consideration must be taken with regards, but not limited to, any screener questions, skip patterns, or closed data edits that result in a complete drop of certain respondents such that they are unable to be added back in when calculating prevalence estimates. An assumption of dropping respondents from certain questions is that the answers to these questions, had they been asked, would in most cases have been “no” or “not applicable” [15]. Much could thus be gained by maintaining one or two key smoking behavior questions across surveys, allowing researchers to retain rather than relinquish the ability to test this assumption [15] and subsequently capture, assess, and use these data to their fullest capacity. Further investigation of associations between the knowledge, attitudes, and behaviors of true never smokers (i.e., lifetime smoking level = 0) and graded levels of lifetime cigarette use >0 may provide additional help in determining whether a judicious cut-point exists for categorizing a respondent as an ever smoker versus a never smoker and, subsequently, in defining current smokers. In the meantime, investigators should use data most appropriate for addressing their specific research questions and subgroups of interest (e.g., relevant consumption levels, age group, racial/ethnic minority status, etc.).

Our study provides further information on how different smoking definitions between two national surveys may impact the overall and subpopulation prevalence estimates observed for some smoking behaviors. Our findings can be used to further inform tobacco control research and surveillance with regards to measurement of adult smoking behavior, including current use and frequency of use. Moreover, these findings may also inform how and why estimates differ by demographic subpopulation. Evidence-based, statewide tobacco control programs that are comprehensive, sustained, and accountable have been shown to reduce smoking rates, tobacco-related deaths, and diseases caused by smoking, with tobacco use monitoring critical to ensuring that program-related effects can be clearly measured [7]. Further research on methodological issues related to differing smoking prevalence estimates across tobacco control monitoring systems is needed, in particular to enhance the capacity of tobacco control surveillance to evaluate progress and further tobacco control efforts. Better understanding of why estimates may vary across data systems and among specific subpopulations, coupled with continued surveillance efforts, permits more accurate assessment of adult smoking prevalence and tobacco use behaviors.