Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2021 Jun 1.
Published in final edited form as: Addict Behav. 2021 Jan 21;117:106838. doi: 10.1016/j.addbeh.2021.106838

Prospective estimation of the age of initiation of hookah use among youth: Findings from the Population Assessment of Tobacco and Health (PATH) study waves 1–4 (2013–2017)

Adriana Pérez a,b, Arnold E Kuk b, Meagan A Bluestein b, Melissa B Harrell b,c, Cheryl L Perry d, Baojiang Chen a,b
PMCID: PMC7956064  NIHMSID: NIHMS1665365  PMID: 33545623

Abstract

Objective

This study reports the prospectively estimated age of initiation of susceptibility to, ever, past 30-day, and fairly regular hookah use.

Design

Secondary data analyses of the first four waves (2013–2017) of the PATH study, a nationally representative longitudinal cohort study of US youth (ages 12–17).

Methods:

Youth who were never hookah users at their first wave of participation were identified (n = 16,678; N = 31,136,834). Four outcomes were analyzed, age of first report of: (i) susceptibility to use, (ii) ever use, (iii) past 30-day use, and (iv) fairly regular hookah use. The age of hookah initiation of each outcome was estimated. Weighted interval censoring survival analyses and Cox regression models were conducted to estimate the age of initiation of each hookah use outcome, and to estimate differences in age of initiation by sex and by race, respectively.

Results:

Around 11% of youth were classified as susceptible to hookah use by 13 years of age, 8% reported initiating ever hookah use by age 17, almost 10% reported initiating past 30-day hookah use by age 19, and 3% reported initiating fairly regular hookah use by age 20. Females and Hispanics were at higher risk of becoming susceptible to and ever hookah use at earlier ages compared to males and Non-Hispanic White youth.

Conclusion:

Education, communication campaigns, and proven culturally targeted tobacco interventions that reach youth at ages before they first become susceptible or start using hookah use are needed to prevent the onset of hookah use among vulnerable youth.

Keywords: water pipe tobacco, narghile, shisha, adolescents

1. Introduction

Use of hookah (also known as water pipe tobacco, narghile, shisha, maassel, or argileh) can cause lung, gastro-intestinal, and bladder malignancies in addition to pulmonary, cardiovascular, and hematological impairments among others (Bentur et al., 2014; Hakim et al., 2011; US Department of Health and Human Services, 2014; US Department of Health and Human Services., 2012; Yadav & Rawal, 2018). Because hookah sessions are typically long and involve higher burning temperatures, hookah users may absorb even more harmful chemicals and tar, compared to cigarette smokers (Aljarrah, Ababneh, & Al-Delaimy, 2009; Centers for Disease Control and Prevention (CDC); Cobb, Ward, Maziak, Shihadeh, & Eissenberg, 2010; Monzer, Sepetdjian, Saliba, & Shihadeh, 2008; Shihadeh & Saleh, 2005; Shihadeh et al., 2015). The number of puffs, volume of smoke inhaled, amount of nicotine, and concentration of heavy metals are higher after a typical 1-hour hookah session when compared to smoking a pack of cigarettes (Ansari, 2014; Noland et al., 2016; WHO Regional Office for the Eastern Mediterranean, 2006). Additionally, studies suggest that hookah is increasingly becoming the first tobacco product used by young adults (Kulak, Saddleson, et al., 2018; Meier, Tackett, Miller, Grant, & Wagener, 2015; Sutfin et al., 2015), and other researchers also suggest that hookah use can serve as a gateway to cigarette use among youth and young adults (Hampson, Tildesley, Andrews, Barckley, & Peterson, 2013; Jensen, Cortes, Engholm, Kremers, & Gislum, 2010). Despite these concerning findings, research on the initiation of hookah use behaviors in youth remains scant.

Few studies have reported youth susceptibility to hookah use (Gentzke, Wang, Robinson, Phillips, & King, 2019; Trinidad et al., 2017; T. W. Wang et al., 2019). Susceptibility to tobacco use has been associated with tobacco initiation as many as 3–4 years before first use (Pierce, Choi, Gilpin, Farkas, & Merritt, 1996). Data from 2013–2014 Population Assessment of Tobacco and Health (PATH) study indicated that 22% youth (12–17 years old) were susceptible to hookah use (Trinidad et al., 2017). Data from the 2016 and 2019 National Youth Tobacco Survey (NYTS) reported that susceptibility to hookah use among middle and high school students rose from 15.6% in 2016 (Gentzke et al., 2019) to 29.9% in 2019 (representing 7.3 million middle and high school students) (T. W. Wang et al., 2019). Understanding the age of onset of susceptibility to hookah use and how the age of onset may vary by demographic characteristics can inform the development of educational campaigns and/or policies among youth to reduce the appeal of hookah.

Several studies have reported the cross-sectional prevalence of hookah use outcomes and correlates in U.S. youth and adults (Cooper et al., 2019; Gentzke et al., 2019; Kasza et al., 2017; Kasza et al., 2020; Majeed, Sterling, Weaver, Pechacek, & Eriksen, 2017; Salloum et al., 2017; T. W. Wang et al., 2018; T. W. Wang et al., 2019). PATH data from 2013–2014 found that 7.5% and 1.7% overall youth reported ever and past 30-day hookah use, and that the prevalence of ever hookah use increased as age increased with 2% at 13 years old and 18.3% at 17 years old (Kasza et al., 2017). NYTS 2019 data reported 7.1% as ever hookah users, representing 1.9 million middle and high school students (T. W. Wang et al., 2019), as well as reporting the 2019 prevalence of hookah use for susceptibility, ever, and past 30-day use by sex and race/ethnicity. Another PATH study found that the prevalence in 2013–2014 among young adults (18–24 years old) was 44.2% and 10.7% for ever and past 30-day hookah use, respectively (Salloum et al., 2017). Additionally, the prevalence in 2013–2014 among adults (18–75+ years) was 16.4% and 4.2% for ever and past 30-day hookah use, respectively, in the U.S (Kasza et al., 2017). While it is true that the prevalence of hookah use is higher in adults, understanding the age of hookah initiation in youth will be vital to reducing hookah initiation overall by targeting prevention and intervention programs to youth of specific ages. Results from the 2014–2015 Tobacco Products and Risk Perceptions Surveys among U.S. adults (18–65+ years old) reported 15.8% and 3.6% as ever and past 30-day hookah users (Majeed et al., 2017). A PATH study has shown that youth who are susceptible to hookah use are more likely than youth who are not susceptible to hookah use to initiate hookah use later (Barrington-Trimis et al., 2019). Thus, it is important to understand youth susceptibility to hookah use to curtail the initiation of ever, past 30-day, and fairly regular use of hookah.

Few studies report a longitudinal analysis of hookah use. Previously, we reported that among youth never hookah users (ages 12–17 years old in 2013–2014), 3.1% initiated ever hookah use one year later (Carey, Wilkinson, Harrell, Cohn, & Perry, 2018). A different study of PATH data among never hookah youth users in 2013–2014 reported 8.9% ever hookah use one or two years later (Stanton et al., 2020). One cross-sectional study of data from 2014–2016 of students in grades 6–12 reported the median recalled age of hookah use was 14 years old (Sharapova et al., 2020), however this is subject recall bias (Grimes & Schulz, 2002; Sackett, 1979). These studies indicate that hookah use has increased in recent years among youth, but there is a gap in the literature and it is important to understand the age at which hookah use behaviors first emerge with longitudinal data that has a longer follow-up period than previous studies.

This study sought to estimate the distribution of the age of initiation of (i) susceptibility to hookah use, (ii) ever use, (iii) past 30-day use, and (iv) “fairly regular” hookah use by conducting prospective, secondary analyses of the Population Assessment of Tobacco and Health (PATH) study overall, by sex and by race/ethnicity. PATH is a representative longitudinal study of youth (aged 12–17) living in the United States who began participation in 2013–2014 (wave 1) and were followed-up annually through 2016–2017 (wave 4)(United States Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, Food and Drug Administration, & Center for Tobacco Products, 2020a, 2020b). We are presenting novel data by providing hazard functions of the age of initiation of hookah use among youth for each outcome to tailor prevention interventions and/or regulations to curb the progression of hookah use behaviors. A previous systematic review reported mixed findings on the associations between sex and hookah use (Cooper et al., 2019). Three studies in that systematic review, found no significant associations between sex and hookah use (Amrock, Gordon, Zelikoff, & Weitzman, 2014; Huang et al., 2017; Smith et al., 2011), while other six studies showed that male youth are more likely than female youth to report ever and past 30-day hookah use (Barnett, Curbow, Weitz, Johnson, & Smith-Simone, 2009; Palamar, Zhou, Sherman, & Weitzman, 2014; Primack et al., 2015; Primack, Walsh, Bryce, & Eissenberg, 2009; Sterling & Mermelstein, 2011; B. Wang, King, Corey, Arrazola, & Johnson, 2014). This systematic review also reported four studies showing that Hispanic youth had the highest prevalence of ever and past 30-day hookah use than any other race/ethnicity groups (Arrazola, Neff, Kennedy, Holder-Hayes, & Jones, 2014; Harrell, Naqvi, Plunk, Ji, & Martins, 2017; Jamal et al., 2017; Singh et al., 2016). Additionally, other six studies found that black youth were less likely than any other race/ethnicity groups to use hookah (Barnett et al., 2009; Fedele et al., 2016; Palamar et al., 2014; Primack, Carroll, Shensa, Davis, & Levine, 2016; Sterling & Mermelstein, 2011; B. Wang et al., 2014). Given these mixed results, and the fact that none of the previously mentioned studies explored differences in the age of hookah initiation, we explored differences by sex and by race/ethnicity on the age of initiation of four hookah use outcomes.

2. Methods

PATH used a stratified address-based area-probability sampling method that oversampled African Americans, young adults and tobacco users to generate a nationally representative sample of the United States population aged 12 and older in 2013 (Hyland et al., 2017; Trinidad et al., 2017). The details of the PATH study have been disclosed elsewhere with a summary presented here (Hyland et al., 2017). Between September 2013 to December 2014, 13,651 youth (aged 12–17) participated in the study (wave 1), with annual waves conducted thereafter: wave 2: October 2014 – October 2015, wave 3: October 2015 – October 2016, and wave 4: December 2016 – January 2018. Additionally, family members of PATH participants who were aged 9–11 at wave 1 were considered “shadow youth” and were invited to participate in the study when they reached age 12, with 2,091 and 2,045 12 years old participants entering the study in waves 2 and 3, respectively (United States Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, Food and Drug Administration, & Center for Tobacco Products, 2019). When youth participants turned 18, they were invited to participate in the adult study: 1,915, 1907, and 1,900 participated in the adult measurements for waves 2–4, respectively (United States Department of Health and Human Services et al., 2019). IRB approval for this study was obtained from the Committee for the Protection of Human Subjects at the University of Texas Health Center at Houston with number HSC-SPH-17–0368.

2.1. Measures

Age of initiation was measured for four hookah use outcomes: (i) susceptibility to use, (ii) ever use, (iii) past 30-day use, and (iv) “fairly regular” hookah use.

2.1.1. Susceptibility to hookah use

PATH measured susceptibility to hookah among never hookah users using the responses to 3 questions in waves 1–4: “Have you ever been curious about smoking tobacco in a hookah?”, “Do you think you will try smoking tobacco in a hookah soon?”, and “If one of your best friends were to offer you a hookah, would you smoke it?”. Response options to the first question were “Very curious,” “Somewhat curious,” “A little curious,” or “Not at all curious.” Response options to the next two questions were “Definitely yes,” “Probably yes,” “Probably not,” or “Definitely not.” Never hookah users who responded “Not at all curious” and “Definitely not” to all 3 questions were classified as not susceptible to hookah and all others were classified as susceptible to hookah use. Participants who were classified as non-susceptible at their wave of entry into PATH (waves 1–3) were included in the analytic sample to prospectively estimate the first report of susceptibility to hookah use.

2.1.2. Ever hookah use

At waves 1–4, youth were asked “Have you ever smoked tobacco in a hookah, even one or two puffs?” and response options were “Yes,” “No,” and “Don’t Know.” Participants who answered “No” to this question at their wave of entry into PATH were included in the analytic sample and were considered never hookah users. Participants who answered “Yes” at subsequent PATH waves (2–4) were considered ever hookah users.

2.1.3. Past 30-day hookah use

At waves 2–4, youth were asked “When was the last time you smoked tobacco in a hookah, even one or two puffs?” and response options were “Earlier today,” “Not today but sometime in the past 7 days,” “Not in the past 7 days but sometime in the past 30 days,” “Not in the past 30 days but sometime in the past 6 months,” “Not in the past 6 months but sometime in the past year,” “1 to 4 years ago,” and “5 or more years ago.” Participants who answered “Earlier today,” “Not today but sometime in the past 7 days” or “Not in the past 7 days but sometime in the past 30 days” to this question were considered past 30-day hookah users.

2.1.4. Fairly regular hookah use

At waves 2–4, youth were asked “Have you ever smoked hookah fairly regularly?” and response options were “Yes,” “No,” and “Don’t know.” Participants who answered “Yes” to this question were considered “fairly regular” hookah users.

2.1.5. Sex and race/ethnicity

Biological sex was queried and categorized participants as male or female. PATH imputed the sex of participants in wave 1 but not in the other waves (see details in their methodology (United States Department of Health and Human Services et al., 2020b)). PATH also measured participant race and ethnicity, with the following categories for race: “White race alone,” “Black race alone,” “Asian race alone,” and “Other race,” (including multi-racial) and the categories for ethnicity were either Hispanic or non-Hispanic. Following prior studies and the Surgeon General’s reports, we collapsed these categories as Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Other (including Non-Hispanic Asian, multi-race, and others), and Hispanic (Kasza et al., 2020; Trinidad et al., 2017; US Department of Health and Human Services., 2012; T. W. Wang et al., 2019).

2.2. Age of initiation

Although the PATH study collected the date of birth of youth, that information was not available to the researchers in the restricted dataset (United States Department of Health and Human Services et al., 2020b). Instead, the restricted-dataset available to researchers contains a derived variable for youth age in years at each wave. PATH also provided a variable measuring the number of weeks between the study waves youth participated in. Using the age of the youth at their first wave of entry into PATH, the number of weeks between waves of PATH participation, and youths’ responses to questions about the hookah use outcomes, the age of initiation of hookah use outcomes were estimated. In order to obtain a more precise estimation of the age of initiation, we first identified the wave of the first report of each of the four hookah outcomes to obtain a lower and upper age bound. Hookah initiation was estimated to occur between these intervals within a week’s precision. The lower age bound was the age at the last wave where youth reported non-use (or non-susceptibility) of hookah. The upper age bound was calculated by adding the lower age bound and the number of weeks between the last wave youth reported non-use (or non-susceptibility) and the first wave youth reported each outcome. Youth who remained never users (or non-susceptible) of hookah were censored in their upper age bound The estimate of the age of initiation was then converted back to years on a continuous scale. Each hookah outcome is estimated to occur in the interval between the wave of initiation (i.e. first report) and the previous wave.

2.3. Data management and statistical analysis

Secondary analysis of PATH restricted-use data sets were conducted (United States Department of Health and Human Services et al., 2020b). We used the sampling weight, 100 balanced repeated replicate (BRR) weights and Fay’s correction factor of 0.3 (Fay, 1989; Judkins, 1990; Rao & Shao, 1999). The sampling weights for youth at their first wave of participation in PATH were used. Analyses of the age of onset of susceptibility to hookah use were limited to youth who were not susceptible to hookah use at their first wave of participation in PATH waves 1–3 (n=5,547; N=10,386,739). Analyses of the age of initiation of ever use, past 30-day use, and “fairly regular” use were limited to youth who were never hookah users at their entry into the study in waves 1–3 (n=16,678; N=31,136,834). Age of initiation (i.e., first report) of all outcomes was obtained in waves 2–4. The age of hookah initiation was estimated using interval-censoring survival analysis (Finkelstein, 1986; Gentleman & Geyer, 1994; Goodall, Dunn, & Babiker, 2004; Ng, 2002; Sun, 2001) because we do not have the exact dates that youth first initiate hookah use. Estimates were obtained for each outcome overall, as well as stratified by sex and by race/ethnicity using SAS 9.4. Interval-censoring Cox regression (Betensky, Rabinowitz, & Tsiatis, 2001; Sparling, Younes, Lachin, & Bautista, 2006) analyses were implemented to estimate the differences in age of hookah initiation by sex and by race/ethnicity. If sex or race/ethnicity was not significantly associated with the age of initiation of each hookah use outcome, then the hazard function displaying the full distribution of ages stratified by that variable was not estimated. The hazard function and Turnbull (Turnbull, 1976) non-parametric estimators for each significant outcome were estimated and are displayed as figures. Each analysis lasted from approximately 20 minutes to 1 hour, resulting in a total run time of approximately 100 hours for each outcome.

3. Results

Demographic information for PATH youth (aged 12–17) used in this study is presented in Table 1. To estimate the age of onset of susceptibility, 5,547 youth were included in this analysis, representing 10,386,739 U.S. youth who were never hookah users and were non-susceptible to hookah use at their first wave of participation in the PATH study (waves 1–3, 2013–2016), with the majority (76.6%) entering the study at wave 1 (2013–2014). Among these youth, the average age at their first wave of participation in PATH was 14 years old, with the majority being males (51%) and Non-Hispanic White (50.6%), while almost one fourth were Hispanic (23.8%). To estimate the age of initiation of ever use, past 30-day use, and “fairly regular” hookah use, 16,678 youth were included in the analysis, representing 31,136,834 U.S. youth who were never hookah users at their first wave of participation in the PATH study. This sample had similar demographic characteristics as the non-susceptible youth to hookah use (Table 1).

Table 1.

Demographic characteristics of PATH¥ youth (aged 12–17) non-susceptible or never hookah use at their first wave of study participation (2013–2016).

Variable Non-susceptible to hookah use at first wave of study participation Never hookah users at their first wave of study participation
n=5,547; N=10,386,739 n=16,678; N=31,136,834
N Weighted % (SE) N Weighted % (SE)
Wave of entry into PATH Wave 1 7,952,670 76.6% (0.51) 29,914,456 73.6% (0.12)
Wave 2 1,147,244 11.0% (0.36) 4,079,970 13.1% (0.11)
Wave 3 1,286,825 12.4% (0.39) 4,142,408 13.3% (0.14)
Weighted mean age at entry into study (SE) 14.01 (0.0251) 13.76 (0.006)
Sex Female 5,071,261 48.9% (0.59) 15,116,449 48.6% (0.14)
Male 5,308,115 51.1% (0.59) 16,000,436 51.4% (0.14)
Missing 7,363 (weighted) 19,949 (weighted)
Race/ethnicity NHa White 5,241,552 50.6% (0.65) 16,682,962 53.7% (0.17)
Hispanic 2,470,980 23.8% (0.56) 7,037,681 22.7% (0.14)
NHa Black 1,498,576 14.5% (0.43) 4,276,542 13.8% (0.09)
NHa otherb 1,149,666 11.1% (0.45) 3,057,344 9.8% (0.13)
Missing 25,965 (weighted) 82,305 (weighted)
Open in a new tab
¥

Disclosure received on April 14, 2020 (United States Department of Health and Human Services et al., 2020a).

a

NH: Non-Hispanic

b

Non-Hispanic other includes Asian, multi-race, etc.

Table 2 shows the distribution of cumulative probabilities (i.e., cumulative incidence) of the estimated age of initiation for each one of the four outcomes by age, and Figure 1 shows these hazard functions within a week’s precision. By age 20, 57.5% of youth had reported susceptibility to hookah use, 24.3% reported ever hookah use, 12.5% reported hookah use in the past 30-days, and 3.0% reported “fairly regular” hookah use. The most notable increases in the age of onset of susceptibility to hookah use occurred between the ages of 12 and 13 years and between the ages of 16 and 17 years. In contrast, the most notable increases in the age of initiation of ever and past 30-day hookah use occurred between the ages of 17 and 18 years. “Fairly regular” hookah use exhibited only minor increases in initiation across ages.

Table 2.

Estimated hazard functiona (95% confidence interval) of the age of initiation of hookah use outcomes among PATH¥ youth.

Age of Initiation Weighted percentage of hookah use by each age (95% CI)a
Susceptibility to Hookah Use Ever Hookah Use Past 30-Day Hookah Use Fairly Regular Hookah Use
12 0 0 0 0
13 10.9 (9.9–11.9) 0.6 (0.4–0.8) 0.2 (0–0.3) 0.1 (0.009–0.2)
14 16.9 (15.8–18.1) 1.4 (1.1–1.7) 0.3 (0–5.9) 0.3 (0.1–0.4)
15 25.4 (23.8–26.9) 2.9 (1.4–4.4) 0.5 (0.3–0.8) 0.3 (0.2–0.4)
16 32.9 (31.4–34.5) 4.8 (4.1–5.6) 1.2 (0.1–2.3) 0.7 (0.3–1.0)
17 44.6 (39.1–50.1) 8.3 (5.8–10.7) 3.3 (1.7–5.0) 1.2 (0.7–1.8)
17.5 44.6 (42.9–46.4) 12.4 (11.4–13.5) 5.3 (4.6–6.0) 1.2 (0.9–1.5)
18 51.3 (43.1–59.4) 19.7 (13.9–25.4) 9.7 (7.9–11.4) 1.8 (0.8–2.8)
19 53.6 (49.9–57.3) 21.4 (19.2–23.7) 9.9 (8.4–11.6) 2.1 (1.7–2.6)
20 57.5 (54.3–60.8) 24.3 (22.2–26.4) 12.5 (10.9–14.0) 3.0 (2.1–3.9)
Open in a new tab
¥

Disclosure received on March 2, 2020 and April 14, 2020 (United States Department of Health and Human Services et al., 2020a).

a

Hazards are reported as cumulative percentages (i.e., cumulative incidence) and 95% CI: Turnbull 95% confidence interval.

Figure 1.

Figure 1.

Open in a new tab

Estimated hazard function of the age of initiation of hookah use overall: Panel (a) shows susceptibility to hookah use, panel (b) shows ever hookah use, panel (c) shows past 30-day hookah use, and panel (d) shows fairly regular hookah use

Table 3 presents the hazard ratios comparing the age of initiation of each hookah use outcome by sex and by race/ethnicity. Our analysis revealed that the risk of both first reporting susceptibility to hookah use and ever hookah use at earlier ages was 13% lower in males compared to females. Hispanics had a 34%, 24%, and 47% increase in the risk of first reporting susceptibility to, ever use, and past 30-day hookah use at earlier ages compared to Non-Hispanic Whites. Compared to Non-Hispanic Whites, the risk of initiating past 30-day hookah use at earlier ages was 32% higher for non-Hispanic Blacks, and 44% higher for Non-Hispanics of other races. There were no statistically significant differences by race/ethnicity for the age of initiation of “fairly regular” hookah use.

Table 3.

Hazard ratios (and 95% confidence intervals) for age of initiation of hookah use outcomes in PATH¥ youth by sex and by race/ethnicity.

Susceptibility to hookah use Ever hookah use Past 30-day hookah use Fairly regular hookah use
Sex
Female 1.00 1.00 1.00 1.00
Male 0.87 (0.80–0.95) 0.87 (0.77–0.99) 0.89 (0.74–1.06) 0.75 (0.53–1.07)
Race/ethnicity
NHa White 1.00 1.00 1.00 1.00
Hispanic 1.34 (1.20–1.48) 1.24 (1.04–1.48) 1.47 (1.16–1.85) 1.49 (0.99–2.22)
NHa Black 1.11 (0.94–1.29) 1.04 (0.86–1.26) 1.32 (1.02–1.71) 1.19 (0.69–2.05)
NHa otherb 1.17 (0.94–1.46) 1.20 (0.94–1.53) 1.44 (1.01–2.06) 1.37 (0.71–2.63)
Open in a new tab
¥

Disclosure received on April 14, 2020 (United States Department of Health and Human Services et al., 2020a).

a

NH: Non-Hispanic

b

Non-Hispanic other includes Asian, multi-race, etc.

Table 4 shows the distribution of the estimated age of first reporting susceptibility to and ever hookah use by sex, and Figure 2 shows these hazard functions within a week’s precision. There were no significant differences in the age of initiation for past 30-day and “fairly regular” hookah use by sex. Findings show that the largest increase in the onset of susceptibility to hookah use occurred between 16 and 17 years of age for males and between 18 and 19 years of age for females. In contrast, the biggest increase in age of initiation ever hookah use occurred between 17 and 18 years for both males and females.

Table 4.

Estimated hazard functionsa (and 95% confidence intervals) in PATH¥ youth of the age of first report of hookah use outcomes by sex.

Weighted percentage of hookah use by each age (95% CI)a
Age Male Female Male Female
Susceptibility to hookah use Ever hookah use
12 0 0 0 0
13 10.4 (8.7–12.0) 11.5 (10.1–12.9) 0.6 (0.4–0.9) 0.6 (0.2–0.9)
14 16.2 (14.5–17.9) 17.7 (15.9–19.5) 1.2 (0.9–1.5) 1.6 (0.2–2.9)
15 24.0 (20.5–27.5) 26.8 (24.6–29.0) 1.2 (0.9–1.5) 3.4 (2.2–4.5)
16 29.0 (20.7–37.3) 35.0 (32.7–37.3) 3.9 (1.6–6.3) 5.5 (4.4–6.5)
17 42.5 (36.6–48.5) 44.5 (33.6–55.4) 5.4 (3.2–7.5) 10.4 (6.1–14.6)
17.5 42.5 (39.9–45.2) 47.1 (44.6–49.6) 11.6 (10.3–12.8) 13.5 (11.9–15.2)
18 49.1 (43.3–54.9) 47.1 (43.2–50.9) 17.3 (9.5–25.0) 21.5 (15.8–27.2)
19 49.2 (45.3–53.1) 57.5 (52.3–62.7) 21.7 (17.7–25.7) 21.5 (18.6–24.5)
20 54.4 (50.8–58.1) 61.2 (56.5–65.9) 23.0 (20.3–25.8) 25.3 (22.5–28.0)
Open in a new tab
¥

Disclosure received on March 2, 2020 and April 14, 2020 (United States Department of Health and Human Services et al., 2020a).

a

Hazards are reported as cumulative percentages (i.e., cumulative incidence) and 95% CI: Turnbull 95% confidence interval

Figure 2.

Figure 2.

Open in a new tab

Estimated hazard function of the age of initiation of hookah use by sex: Panel (a) shows susceptibility to hookah use and panel (b) shows ever hookah use

Table 5 shows the distribution of the estimated age of first reporting susceptibility to, ever use, and past 30-day hookah use by race/ethnicity, and Figure 3 shows these hazard functions within a week’s precision. There were no statistically significant differences in the age of initiation for “fairly regular” hookah use by race/ethnicity. Findings show that the largest increase in first reporting susceptibility to hookah use occurred between 16 and 17 years for Non-Hispanic Whites and Hispanics, while it was between 17 and 18 years for non-Hispanic Blacks and Non-Hispanic Others. Similarly, the biggest increase in initiation of ever hookah use occurred between 17 and 18 years for Non-Hispanic Whites and Hispanics, and between 18 and 19 years for Non-Hispanic Blacks and Non-Hispanic Others. All race/ethnicity groups showed the largest increase in initiation of past 30-day hookah use between 17 and 18 years.

Table 5.

Estimated functionsa (and 95% confidence intervals) in PATH youth of the age of first report of hookah use outcomes by race/ethnicity

Age Weighted percentage of hookah use by each age (95% CI)a
Non-Hispanic White Hispanic Non-Hispanic Black Non-Hispanic Otherb
Susceptibility to hookah use
12 0 0 0 0
13 8.9 (7.5–10.4) 14.4 (11.5–17.3) 11.6 (1.4–21.9) 11.3 (7.3–15.2)
14 14.9 (13.1–16.7) 20.5 (17.8–23.2) 18.1 (15.2–21.1) 17.0 (9.0–25.0)
15 22.6 (20.3–24.9) 30.4 (27.7–33.1) 23.2 (11.9–34.5) 21.3 (10.1–32.4)
16 30.0 (27.8–32.3) 37.4 (30.3–44.4) 26.9 (21.7–32.1) 36.9 (22.9–50.9)
17 42.0 (33.4–50.6) 49.7 (40.5–58.9) 33.4 (29.2–37.5) 36.9 (29.1–44.7)
18 48.0 (38.4–57.7) 52.0 (44.1–59.9) 45.6 (40.8–50.3) 53.4 (38.8–67.9)
19 49.1 (44.2–53.9) 60.6 (55.7–65.6) 51.6 (45.7–57.6) 55.7 (46.0–65.3)
20 55.2 (51.0–59.4) 61.3 (57.0–65.5) 60.1 (48.5–71.7) 68.5 (53.1–83.8)
Ever hookah use
12 0 0 0 0
13 0.4 (0–0.8) 1.1 (0.7–1.5) 0.7 (0.2–1.1) 0.8 (0.3–1.3)
14 1.3 (0.4–2.1) 2.2 (0.04–4.3) 0.7 (0.2–1.2) 1.0 (0.5–1.5)
15 2.8 (0.5–5.1) 3.7 (1.5–5.8) 2.2 (1.5–2.9) 2.6 (0.1–5.0)
16 2.9 (0.7–5.0) 5.8 (4.4–7.1) 4.1 (0.4–7.7) 4.2 (1.8–6.6)
17 7.0 (3.9–10.2) 10.5 (4.2–16.7) 4.1 (2.8–5.3) 6.1 (2.3–9.9)
18 16.1 (9.1–22.9) 21.6 (16.6–26.7) 11.9 (6.4–17.3) 14.6 (10.3–18.9)
19 19.3 (17.1–21.5) 22.6 (17.9–27.2) 21.3 (17.7–25.0) 28.7 (21.8–35.7)
20 22.8 (20.4–25.3) 27.5 (22.8–32.2) 26.7 (21.2–32.2) 30.0 (23.9–36.1)
Past 30-day hookah use
12 0 0 0 0
13 0.08 (0.02–0.1) 0.3 (0.05–0.5) 0.3 (0.04–0.6) 0.3 (0–0.5)
14 0.1 (0–0.4) 0.6 (0.3–1.0) 0.3 (0–0.7) 0.3 (0.08–0.4)
15 0.5 (0.2–0.7) 0.8 (0.3–1.4) 0.4 (0.07–0.7) 1.0 (0.3–1.7)
16 1.0 (0.3–1.8) 1.4 (0.7–2.0) 1.3 (0.09–2.6) 1.3 (0.4–2.0)
17 3.1 (1.2–4.9) 2.3 (0.1–4.5) 1.3 (0.6–2.0) 2.0 (0–4.2)
18 7.3 (3.6–11.1) 11.5 (8.8–14.1) 7.0 (0–14.6) 12.4 (0.5–24.2)
19 8.5 (6.9–10.2) 12.8 (8.6–16.9) 10.8 (7.9–13.7) 13.1 (8.1–18.2)
20 9.8 (7.9–11.8) 15.4 (11.9–18.9) 15.3 (9.8–20.8) 19.1 (11.8–26.3)
Open in a new tab
¥

Disclosure received on March 2, 2020 and April 14, 2020 (United States Department of Health and Human Services et al., 2020a).

a

Hazards are reported as cumulative percentages (i.e., cumulative incidence) and 95% CI: Turnbull 95% confidence interval

b

Non-Hispanic other includes Asian, multi-race, and etc.

Figure 3.

Figure 3.

Open in a new tab

Estimated hazard function of the age of initiation of hookah use by race/ethnicity: Panel (a) shows susceptibility to hookah use, panel (b) shows ever hookah use, and panel (c) shows past 30‐day hookah use

4. Discussion

This study reports the prospectively estimated distributions of the age of first reporting (i.e., initiation) of susceptibility to, ever use, past 30-day use, and “fairly regular” use of hookah among United States youth (12–17 years old) with details on the ages of initiation of hookah use by sex and by race/ethnicity. Importantly, we found that around 11% of the youth become susceptible to hookah use by 13 years, and that the percentage increases to 51.3% by age 18. Therefore, education and intervention campaigns are needed urgently to prevent youth from becoming susceptible to hookah use, certainly before early adolescence. Prominently, susceptibility to hookah use increases the risk of ever hookah use among youth (Barrington-Trimis et al., 2019). For tobacco regulatory science, our computed probability of becoming susceptible to hookah use at specific ages identifies the appropriate window to implement intervention programs to prevent youth from becoming susceptible to hookah use. For example, over 10% of U.S. youth who had never used hookah become susceptible to hookah use between ages 12 and 13 (10.4%), implying that there is the opportunity to prevent at least one tenth of U.S. youth from becoming susceptible to hookah if interventions awareness campaigns communicating the health risks to youth are conducted in early adolescence.

PATH 2013–2014 reported 7.5% and 1.7% of ever and past 30-day hookah use among youth 12–17 years old (Kasza et al., 2017). A panel sample of New Jersey high school students reported 15.9% and 7.0% of ever and frequent hookah use (10 or more days per month of use) in 2016, respectively (Kulak et al., 2019). The National Youth Tobacco Survey of middle and high school students in 2019 reported that, overall, 7.1% ever tried hookah while 2.6% reported past 30-day hookah use (T. W. Wang et al., 2019). In contrast, our estimates are 19.7% and 9.7% for ever and past 30-day hookah use by age 18, respectively. This demonstrates that prevention campaigns are warranted before 18 years old so that youth do not progress to more frequent hookah use before they move away from home to work or college.

We also included the subjective measure of “fairly regular” hookah use seeking to capture habitual hookah use behaviors. PATH 2013–2014 reported 0.1% daily hookah use among youth 12–17 years old (Kasza et al., 2017) while a panel sample of New Jersey high school students reported 2.9% and 1.6% of frequent hookah use (10 or more days per month of use) in 2014 and 2016, respectively (Kulak et al., 2019). Both of these studies were cross-sectional and reported hookah use for all youth as a whole instead of by age. Similarly, we found prospectively, that only 1.8% of U.S. youth who had never smoked hookah progress to report “fairly regular” hookah use by age 18. Other prior studies suggest that frequent hookah use is associated with cigarette and cigar use (Doran & Brikmanis, 2016; Haider et al., 2015), indicating that hookah use put youth at risk toward multi tobacco product use.

The detailed information provided by our study for four hookah use outcomes identifies for interventionists by what age prevention campaigns should be implemented to reduce the public health burden of youth hookah initiation. The information in this study is important to tobacco regulatory science, as age defines the legal ability to buy tobacco products. Despite the fact that youth in our sample could not legally buy tobacco products until they were 18, many report initiation of ever, past 30-day, and “fairly regular” hookah use prior to the age of 18, and this is consistent with other studies (Gentzke et al., 2019; Kasza et al., 2017; Kulak et al., 2019; Kulak, Manderski, et al., 2018; Stanton et al., 2020; T. W. Wang et al., 2019). Moreover, initiation of hookah use occurred at earlier ages among females, Hispanics, and Non-Hispanic Blacks, suggesting these sub-groups are particularly vulnerable to use hookah at earlier ages. Importantly, as of December 20, 2019, the legal minimum age to purchase tobacco products is now 21 (U.S. Food & Drug Administration). Future analyses should consider the impact of this new nationwide law on the age of initiation of hookah use and whether this law widens or narrows disparities in use, like those reported here.

Consistent with some prior prevalence studies in 2016 and 2019, our results indicated that males had 13% lower risk to become susceptible to hookah use at earlier ages than females (Gentzke et al., 2019; T. W. Wang et al., 2019). Between 2011 and 2014, lifetime hookah use by females in Florida almost doubled, while that of males stayed almost the same (Barnett et al., 2017), and another study found that female students have higher odds of ever using hookah than male students (AOR= 2.62; 95%CI= 1.8–3.9) (Roods, Jasek, & Farley, 2018). While there is no scientific evidence explaining this result, we hypothesize that the result could be due to females’ tendency to hang out with older males, or females having stronger preferences for hookah flavors and smells, or females might be more likely to go to hookah venues for socializing (Kassem et al., 2015). Our results are contrary to 2019 NYTS data, as their study found that 7.3% of males and 6.9% of females had ever used hookah in cross-sectional analyses (T. W. Wang et al., 2019). The earlier age of hookah initiation among females in our study may reflect the greater sensitivity of survival analysis to estimate the distribution of the age of initiation of hookah use because age is part of the outcome in combination with hookah initiation, rather than examining hookah initiation alone. Future research should explore on factors that are affecting females’ higher risk for becoming susceptible and initiating hookah use at earlier ages, including how flavors impact the initiation of hookah use, possibly by making the product more appealing.

Our findings also suggest that Hispanic youth become susceptible to hookah use at earlier ages than Non-Hispanic Whites. For example, 14.4.4% of Hispanics became susceptible to hookah use by age 13, while only 8.9% of Non-Hispanic Whites became susceptible to hookah use by age 13. Thus, educational strategies or intervention programs should be implemented in early adolescence that are culturally relevant to Hispanic youth. Because almost 9% of other race/ethnicities are also at risk of becoming susceptible by age 13 interventions are urgently needed across all race/ethnicities. The benefits of developing educational interventions around the health risks of hookah that are implemented when youth are showing curiosity before 13 years old can redirect their appeal to prevent hookah use initiation. Our results also serve as targets to determine if an intervention successfully reduces youth becoming susceptible to hookah use and can be used for future researchers.

There are strengths and limitations to our study. Conducting secondary data analyses with the PATH study that is a nationally representative longitudinal cohort provides strong evidence for the results provided. Estimating the age of initiation of four hookah use outcomes using time-to-event analyses overall, by sex and race/ethnicity have never been reported before. The contribution of a more precise calculation of the age of initiation for the four hookah outcomes using prospective data instead of self-report recall data, and identifying which subgroups are at highest risk to hookah use in youth is unique. Other researches prefer to include hookah users in their estimates by using their recalled age of initiation or treat them as left-censored and left-truncated when the time-to-event can be asked directly to individuals (Cain et al., 2011). Comparisons evaluating the different methodologies were out of the scope of this study as it is not feasible to ask youth the exact date that they initiated hookah use. Still, we depend on self-reported data from waves 1–4 for initiation of hookah use outcomes from these youth. However, these limitations were overcome by the way age of initiation was derived, and upheld the privacy protections for youth. Another limitation of this study is that these PATH findings here cannot be generalized to youth outside of the U.S.; however these findings can be used as a comparison for other international studies, as hookah use is common in other countries around the world (Fakhari, Mohammadpoorasl, Nedjat, Sharif Hosseini, & Fotouhi, 2015; Galimov, El Shahawy, Unger, Masagutov, & Sussman, 2019; Minaker, Shuh, Burkhalter, & Manske, 2015). It is also worth noting that our measure of hookah use was not biochemically verified with biomarker data from the PATH study.

5. Conclusions

This study identified important windows of opportunity, in regards to appropriate ages for which intervention is especially relevant in order to prevent the onset and progression in hookah use. For example, we found that over 10% of U.S. youth are estimated to become susceptible to hookah use by age 13 and expect over a quarter of U.S. youth to become susceptible by age 15. Our results also show that while only 0.6% and 0.2% of U.S. youth are ever and past 30-day users of hookah by age 13, respectively, it is estimated to increase to 19.7% and 9.7% by the time the youth become young adults, suggesting that prevention campaigns are necessary for youth before they turn 18, if not during early adolescence. We also identified important demographic targets for intervention, showing that females and Hispanics are at higher risk of initiating hookah use compared to males and Non-Hispanic Whites, suggesting that interventionists should pay more attention to females and Hispanics.

Highlights.

  • Estimation of the age of initiation of four hookah use outcomes among U.S. youth.

  • Female were at higher risk for susceptibility to hookah use at early ages.

  • Females were at higher risk of ever hookah use at early ages.

  • Hispanics were at higher risk for susceptibility to hookah use at early ages.

  • Hispanics were at higher risk of ever hookah use at early ages.

Funding acknowledgements:

Research reported in this publication was supported by grant number [1R01CA234205-01A1] from the National Cancer Institute (NCI) and the FDA Center for Tobacco Products (CTP). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH) or the Food and Drug Administration (FDA).

Role of Funding Sources

Funding for this study was provided by National Cancer Institute (NCI) and the FDA Center for Tobacco Products (CTP) Grant number [1R01CA234205-01A1]. NCI and FDA Center for Tobacco Products had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflict of interests: The authors have no conflicts of interest to disclose except Dr. Harrell is a consultant in litigation involving the vaping industry.

Datasets: All the data from waves 1-4 are available from the Population Assessment of Tobacco and Health (PATH) Study [United States] Restricted-Use Files. Inter-university Consortium for Political and Social Research [distributor], 2020-06-24. https://doi.org/10.3886/ICPSR36231.v25.

REFERENCES

  1. Aljarrah K, Ababneh ZQ, & Al-Delaimy WK (2009). Perceptions of hookah smoking harmfulness: Predictors and characteristics among current hookah users. Tobacco Induced Diseases, 5(1), 16. doi: 10.1186/1617-9625-5-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Amrock SM, Gordon T, Zelikoff JT, & Weitzman M (2014). Hookah use among adolescents in the United States: Results of a national survey. Nicotine & Tobacco Research : Official Journal of the Society for Research on Nicotine and Tobacco, 16(2), 231–237. doi: 10.1093/ntr/ntt160 [DOI] [PubMed] [Google Scholar]
  3. Ansari H (2014). Hookah use among youth and young adults: A public health challenge. Health Scope, 3(3), e20632. doi: 10.17795/jhealthscope-20632 [DOI] [Google Scholar]
  4. Arrazola RA, Neff LJ, Kennedy SM, Holder-Hayes E, & Jones CD (2014). Tobacco use among middle and high school students--United States, 2013. Morbidity and Mortality Weekly Report, 63(45), 1021–1026. [PMC free article] [PubMed] [Google Scholar]
  5. Barnett TE, Curbow BA, Weitz JR, Johnson TM, & Smith-Simone SY (2009). Water pipe tobacco smoking among middle and high school students. American Journal of Public Health, 99(11), 2014–2019. doi: 10.2105/ajph.2008.151225 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Barnett TE, Tomar SL, Lorenzo FE, Forrest JR, Porter L, & Gurka MJ (2017). Hookah use among Florida high school students, 2011–2014. American Journal of Preventive Medicine, 52(2), 220–223. doi: 10.1016/j.amepre.2016.10.027 [DOI] [PubMed] [Google Scholar]
  7. Barrington-Trimis JL, Liu F, Unger JB, Alonzo T, Cruz TB, Urman R, … McConnell R (2019). Evaluating the predictive value of measures of susceptibility to tobacco and alternative tobacco products. Addictive Behaviors, 96, 50–55. doi: 10.1016/j.addbeh.2019.03.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bentur L, Hellou E, Goldbart A, Pillar G, Monovich E, Salameh M, … Bentur Y (2014). Laboratory and clinical acute effects of active and passive indoor group water-pipe (narghile) smoking. Chest, 145(4), 803–809. doi: 10.1378/chest.13-0960 [DOI] [PubMed] [Google Scholar]
  9. Betensky RA, Rabinowitz D, & Tsiatis AA (2001). Computationally simple accelerated failure time regression for interval censored data. Biometrika, 88, 703–711. [Google Scholar]
  10. Cain KC, Harlow SD, Little RJ, Nan B, Yosef M, Taffe JR, & Elliott MR (2011). Bias due to left truncation and left censoring in longitudinal studies of developmental and disease processes. American Journal of Epidemiology, 173(9), 1078–1084. doi: 10.1093/aje/kwq481 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Carey FR, Wilkinson AV, Harrell MB, Cohn EA, & Perry CL (2018). Measurement and predictive value of susceptibility to cigarettes, e-cigarettes, cigars, and hookah among texas adolescents. Addict Behav Rep, 8, 95–101. doi: 10.1016/j.abrep.2018.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Centers for Disease Control and Prevention (CDC). Smoking & tobacco use: Hookahs (fact sheet). Retrieved from https://www.cdc.gov/tobacco/data_statistics/fact_sheets/tobacco_industry/hookahs/index.htm
  13. Cobb C, Ward KD, Maziak W, Shihadeh AL, & Eissenberg T (2010). Waterpipe tobacco smoking: An emerging health crisis in the United States. American Journal of Health Behavior, 34(3), 275–285. doi: 10.5993/ajhb.34.3.3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Cooper M, Pacek LR, Guy MC, Barrington-Trimis JL, Simon P, Stanton C, & Kong G (2019). Hookah use among US youth: A systematic review of the literature from 2009 to 2017. Nicotine & Tobacco Research : Official Journal of the Society for Research on Nicotine and Tobacco, 21(12), 1590–1599. doi: 10.1093/ntr/nty135 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Doran N, & Brikmanis K (2016). Expectancies for and use of e-cigarettes and hookah among young adult non-daily smokers. Addictive Behaviors, 60, 154–159. doi: 10.1016/j.addbeh.2016.04.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Fakhari A, Mohammadpoorasl A, Nedjat S, Sharif Hosseini M, & Fotouhi A (2015). Hookah smoking in high school students and its determinants in iran: A longitudinal study. Am J Mens Health, 9(3), 186–192. doi: 10.1177/1557988314535236 [DOI] [PubMed] [Google Scholar]
  17. Fay RE (1989). Theory and application of replicate weighting for variance calculations. Paper presented at the Proceedings of the Survey Research Methods Section of the American Statistical Association. [Google Scholar]
  18. Fedele DA, Barnett TE, Dekevich D, Gibson-Young LM, Martinasek M, & Jagger MA (2016). Prevalence of and beliefs about electronic cigarettes and hookah among high school students with asthma. Ann Epidemiol, 26(12), 865–869. doi: 10.1016/j.annepidem.2016.10.004 [DOI] [PubMed] [Google Scholar]
  19. Finkelstein DM (1986). A proportional hazards model for interval-censored failure time data. Biometrics, 42(4), 845–854. doi: 10.2307/2530698 [DOI] [PubMed] [Google Scholar]
  20. Galimov A, El Shahawy O, Unger JB, Masagutov R, & Sussman S (2019). Hookah use among russian adolescents: Prevalence and correlates. Addictive Behaviors, 90, 258–264. doi: 10.1016/j.addbeh.2018.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Gentleman R, & Geyer CJ (1994). Maximum likelihood for interval censored data: Consistency and computation. Biometrika, 81(3), 618–623. doi: 10.2307/2337135 [DOI] [Google Scholar]
  22. Gentzke AS, Wang B, Robinson JN, Phillips E, & King BA (2019). Curiosity about and susceptibility toward hookah smoking among middle and high school students. Preventing Chronic Disease, 16, E04. doi: 10.5888/pcd16.180288 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Goodall RL, Dunn DT, & Babiker AG (2004). Interval‐censored survival time data: Confidence intervals for the non‐parametric survivor function. Statistics in Medicine, 23(7), 1131–1145. doi: 10.1002/sim.1682 [DOI] [PubMed] [Google Scholar]
  24. Grimes DA, & Schulz KF (2002). Bias and causal associations in observational research. The Lancet, 359(9302), 248–252. doi: 10.1016/s0140-6736(02)07451-2 [DOI] [PubMed] [Google Scholar]
  25. Haider MR, Salloum RG, Islam F, Ortiz KS, Kates FR, & Maziak W (2015). Factors associated with smoking frequency among current waterpipe smokers in the United States: Findings from the National College Health Assessment II. Drug and Alcohol Dependence, 153, 359–363. doi: 10.1016/j.drugalcdep.2015.05.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Hakim F, Hellou E, Goldbart A, Katz R, Bentur Y, & Bentur L (2011). The acute effects of waterpipe smoking on the cardiorespiratory system. Chest, 139(4), 775–781. doi: 10.1378/chest.10-1833 [DOI] [PubMed] [Google Scholar]
  27. Hampson SE, Tildesley E, Andrews JA, Barckley M, & Peterson M (2013). Smoking trajectories across high school: Sensation seeking and hookah use. Nicotine & Tobacco Research : Official Journal of the Society for Research on Nicotine and Tobacco, 15(8), 1400–1408. doi: 10.1093/ntr/nts338 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Harrell PT, Naqvi SMH, Plunk AD, Ji M, & Martins SS (2017). Patterns of youth tobacco and polytobacco usage: The shift to alternative tobacco products. Am J Drug Alcohol Abuse, 43(6), 694–702. doi: 10.1080/00952990.2016.1225072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Huang LL, Sutfin EL, Kowitt S, Patel T, Ranney L, & Goldstein AO (2017). Trends and correlates of hookah use among high school students in north carolina. North Carolina Medical Journal, 78(3), 149–155. doi: 10.18043/ncm.78.3.149 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Hyland A, Ambrose BK, Conway KP, Borek N, Lambert E, Carusi C, … Compton WM (2017). Design and methods of the Population Assessment of Tobacco and Health (PATH) study. Tobacco Control, 26(4), 371–378. doi: 10.1136/tobaccocontrol-2016-052934 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Jamal A, Gentzke A, Hu SS, Cullen KA, Apelberg BJ, Homa DM, & King BA (2017). Tobacco use among middle and high school students United States, 2011–2016. Morbidity and Mortality Weekly Report, 66(23), 597–603. doi: 10.15585/mmwr.mm6623a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Jensen PD, Cortes R, Engholm G, Kremers S, & Gislum M (2010). Waterpipe use predicts progression to regular cigarette smoking among Danish youth. Substance Use & Misuse, 45(7–8), 1245–1261. doi: 10.3109/10826081003682909 [DOI] [PubMed] [Google Scholar]
  33. Judkins D (1990). Fay’s method for variance estimation. Journal of Official Statistics, 6(3), 223. [Google Scholar]
  34. Kassem NO, Jackson SR, Boman-Davis M, Kassem NO, Liles S, Daffa RM, … Hovell MF (2015). Hookah smoking and facilitators/barriers to lounge use among students at a US university. American Journal of Health Behavior, 39(6), 832–848. doi: 10.5993/ajhb.39.6.11 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Kasza KA, Ambrose BK, Conway KP, Borek N, Taylor K, Goniewicz ML, … Hyland AJ. (2017). Tobacco-product use by adults and youths in the United States in 2013 and 2014. The New English Journal of Medicine, 376(4), 342–353. doi: 10.1056/NEJMsa1607538 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Kasza KA, Edwards KC, Tang Z, Stanton CA, Sharma E, Halenar MJ, … Hyland A (2020). Correlates of tobacco product initiation among youth and adults in the USA: Findings from the PATH study waves 1–3 (2013–2016). Tobacco Control, 29(Suppl 3), s191–s202. doi: 10.1136/tobaccocontrol-2020-055671 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Kulak JA, Bover Manderski MT, Delnevo CD, Hrywna M, Homish GG, & Giovino GA (2019). Differential trends in hookah use among New Jersey youth. Preventing Chronic Disease, 16, E138. doi: 10.5888/pcd16.190097 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Kulak JA, Manderski MBT, Travers MJ, Delnevo CD, Hrywna M, Bansal-Travers M, … Giovino GA (2018). Patterns and trends of hookah use among New Jersey youth: New Jersey Youth Tobacco Survey 2008–2014. American Journal of Health Behavior, 42(2), 21–35. doi: 10.5993/ajhb.42.2.3 [DOI] [PubMed] [Google Scholar]
  39. Kulak JA, Saddleson ML, Travers MJ, Bansal-Travers M, Homish GG, Mahoney MC, & Giovino GA (2018). Examining hookah as an introduction to nicotine products among college students. Substance Use & Misuse, 53(11), 1869–1877. doi: 10.1080/10826084.2018.1441308 [DOI] [PubMed] [Google Scholar]
  40. Majeed BA, Sterling KL, Weaver SR, Pechacek TF, & Eriksen MP (2017). Prevalence and harm perceptions of hookah smoking among U.S. Adults, 2014–2015. Addictive Behaviors, 69, 78–86. doi: 10.1016/j.addbeh.2017.01.032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Meier EM, Tackett AP, Miller MB, Grant DM, & Wagener TL (2015). Which nicotine products are gateways to regular use? First-tried tobacco and current use in college students. American Journal of Preventive Medicine, 48(1 Suppl 1), S86–93. doi: 10.1016/j.amepre.2014.09.018 [DOI] [PubMed] [Google Scholar]
  42. Minaker LM, Shuh A, Burkhalter RJ, & Manske SR (2015). Hookah use prevalence, predictors, and perceptions among canadian youth: Findings from the 2012/2013 youth smoking survey. Cancer Causes Control, 26(6), 831–838. doi: 10.1007/s10552-015-0556-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Monzer B, Sepetdjian E, Saliba N, & Shihadeh A (2008). Charcoal emissions as a source of CO and carcinogenic PAH in mainstream narghile waterpipe smoke. Food and Chemical Toxicology : an International Journal Published for the British Industrial Biological Research Association, 46(9), 2991–2995. doi: 10.1016/j.fct.2008.05.031 [DOI] [PubMed] [Google Scholar]
  44. Ng MP (2002). A modification of peto’s nonparametric estimation of survival curves for interval-censored data. Biometrics, 58(2), 439–442. doi: 10.1111/j.0006-341x.2002.00439.x [DOI] [PubMed] [Google Scholar]
  45. Noland M, Ickes MJ, Rayens MK, Butler K, Wiggins AT, & Hahn EJ (2016). Social influences on use of cigarettes, e-cigarettes, and hookah by college students. Journal of American College Health, 64(4), 319–328. doi: 10.1080/07448481.2016.1138478 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Palamar JJ, Zhou S, Sherman S, & Weitzman M (2014). Hookah use among US high school seniors. Pediatrics, 134(2), 227–234. doi: 10.1542/peds.2014-0538 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Pierce JP, Choi WS, Gilpin EA, Farkas AJ, & Merritt RK (1996). Validation of susceptibility as a predictor of which adolescents take up smoking in the United States. Health Psychology : Official Journal of the Division of Health Psychology, American Psychological Association, 15(5), 355–361. doi: 10.1037//0278-6133.15.5.355 [DOI] [PubMed] [Google Scholar]
  48. Primack BA, Carroll MV, Shensa A, Davis W, & Levine MD (2016). Sex differences in hookah-related images posted on tumblr: A content analysis. J Health Commun, 21(3), 366–375. doi: 10.1080/10810730.2015.1095814 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Primack BA, Freedman-Doan P, Sidani JE, Rosen D, Shensa A, James AE, & Wallace J (2015). Sustained waterpipe tobacco smoking and trends over time. American Journal of Preventive Medicine, 49(6), 859–867. doi: 10.1016/j.amepre.2015.06.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Primack BA, Walsh M, Bryce C, & Eissenberg T (2009). Water-pipe tobacco smoking among middle and high school students in arizona. Pediatrics, 123(2), e282–288. doi: 10.1542/peds.2008-1663 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Rao JNK, & Shao J (1999). Modified balanced repeated replication for complex survey data. Biometrika, 86(2), 403–415. doi: 10.1093/biomet/86.2.403 [DOI] [Google Scholar]
  52. Roods K, Jasek J, & Farley SM (2018). Trends in hookah use among New York City middle and high school students, 2008–2014. Preventing Chronic Disease, 15, E20. doi: 10.5888/pcd15.170283 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Sackett DL (1979). Bias in analytic research. Journal of Chronic Diseases, 32(1–2), 51–63. doi: 10.1016/0021-9681(79)90012-2 [DOI] [PubMed] [Google Scholar]
  54. Salloum RG, Thrasher JF, Getz KR, Barnett TE, Asfar T, & Maziak W (2017). Patterns of waterpipe tobacco smoking among U.S. Young adults, 2013–2014. American Journal of Preventive Medicine, 52(4), 507–512. doi: 10.1016/j.amepre.2016.10.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Sharapova S, Reyes-Guzman C, Singh T, Phillips E, Marynak KL, & Agaku I (2020). Age of tobacco use initiation and association with current use and nicotine dependence among US middle and high school students, 2014–2016. Tobacco Control, 29(1), 49–54. doi: 10.1136/tobaccocontrol-2018-054593 [DOI] [PubMed] [Google Scholar]
  56. Shihadeh A, & Saleh R (2005). Polycyclic aromatic hydrocarbons, carbon monoxide, “tar”, and nicotine in the mainstream smoke aerosol of the narghile water pipe. Food and Chemical Toxicology : an International Journal Published for the British Industrial Biological Research Association, 43(5), 655–661. doi: 10.1016/j.fct.2004.12.013 [DOI] [PubMed] [Google Scholar]
  57. Shihadeh A, Schubert J, Klaiany J, El Sabban M, Luch A, & Saliba NA (2015). Toxicant content, physical properties and biological activity of waterpipe tobacco smoke and its tobacco-free alternatives. Tobacco Control, 24(Suppl 1), i22–30. doi: 10.1136/tobaccocontrol-2014-051907 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Singh T, Arrazola RA, Corey CG, Husten CG, Neff LJ, Homa DM, & King BA (2016). Tobacco use among middle and high school students--United States, 2011–2015. Morbidity and Mortality Weekly Report, 65(14), 361–367. doi: 10.15585/mmwr.mm6514a1 [DOI] [PubMed] [Google Scholar]
  59. Smith JR, Novotny TE, Edland SD, Hofstetter CR, Lindsay SP, & Al-Delaimy WK (2011). Determinants of hookah use among high school students. Nicotine & Tobacco Research : Official Journal of the Society for Research on Nicotine and Tobacco, 13(7), 565–572. doi: 10.1093/ntr/ntr041 [DOI] [PubMed] [Google Scholar]
  60. Sparling YH, Younes N, Lachin JM, & Bautista OM (2006). Parametric survival models for interval-censored data with time-dependent covariates. Biostatistics, 7, 599–614. [DOI] [PubMed] [Google Scholar]
  61. Stanton CA, Sharma E, Seaman EL, Kasza KA, Edwards KC, Halenar MJ, … Hyland A (2020). Initiation of any tobacco and five tobacco products across 3 years among youth, young adults and adults in the USA: Findings from the PATH study waves 1–3 (2013–2016). Tobacco Control, 29(Suppl 3), s178–190. doi: 10.1136/tobaccocontrol-2019-055573 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Sterling KL, & Mermelstein R (2011). Examining hookah smoking among a cohort of adolescent ever smokers. Nicotine & Tobacco Research : Official Journal of the Society for Research on Nicotine and Tobacco, 13(12), 1202–1209. doi: 10.1093/ntr/ntr146 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Sun J (2001). Variance estimation of a survival function for interval-censored survival data. Statistics in Medicine, 20(8), 1249–1257. doi: 10.1002/sim.719 [DOI] [PubMed] [Google Scholar]
  64. Sutfin EL, Sparks A, Pockey JR, Suerken CK, Reboussin BA, Wagoner KG, … Wolfson M (2015). First tobacco product tried: Associations with smoking status and demographics among college students. Addictive Behaviors, 51, 152–157. doi: 10.1016/j.addbeh.2015.07.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Trinidad DR, Pierce JP, Sargent JD, White MM, Strong DR, Portnoy DB, … Messer K (2017). Susceptibility to tobacco product use among youth in wave 1 of the Population Assessment of Tobacco and Health (PATH) study. Preventive Medicine, 101, 8–14. doi: 10.1016/j.ypmed.2017.05.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Turnbull BW (1976). The empirical distribution function with arbitrarily grouped, censored and truncated data. Journal of the Royal Statistical Society: Series B (Methodological), 38(3), 290 – 295. doi: 10.1111/j.2517-6161.1976.tb01597.x [DOI] [Google Scholar]
  67. U.S. Food & Drug Administration. Tobacco 21. Retrieved from https://www.fda.gov/tobaccoproducts/retail-sales-tobacco-products/tobacco-21 [Google Scholar]
  68. United States Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, Food and Drug Administration, & Center for Tobacco Products. (2019). Population Assessment of Tobacco and Health (PATH) study [United States] public-use files, user guide. [Google Scholar]
  69. United States Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, Food and Drug Administration, & Center for Tobacco Products. (2020a). Population Assessment of Tobacco and Health (PATH) study [United States] restricted-use files. [Google Scholar]
  70. United States Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, Food and Drug Administration, & Center for Tobacco Products. (2020b). Population Assessment of Tobacco and Health (PATH) study [United States] restricted-use files, user guide. [Google Scholar]
  71. US Department of Health and Human Services. (2014). The health consequences of smoking: 50 years of progress: A report of the Surgeon General. Atlanta, Georgia: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. [Google Scholar]
  72. US Department of Health and Human Services. (2012). Preventing tobacco use among youth and young adults: A report of the Surgeon General. Atlanta, Georgia: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. [Google Scholar]
  73. Wang B, King BA, Corey CG, Arrazola RA, & Johnson SE (2014). Awareness and use of non-conventional tobacco products among U.S. Students, 2012. American Journal of Preventive Medicine, 47(2 Suppl 1), S36–52. doi: 10.1016/j.amepre.2014.05.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Wang TW, Gentzke A, Sharapova S, Cullen KA, Ambrose BK, & Jamal A (2018). Tobacco product use among middle and high school students - United States, 2011–2017. Morbidity and Mortality Weekly Report, 67(22), 629–633. doi: 10.15585/mmwr.mm6722a3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Wang TW, Gentzke AS, Creamer MR, Cullen KA, Holder-Hayes E, Sawdey MD, … Neff LJ (2019). Tobacco product use and associated factors among middle and high school students United States, 2019. MMWR Surveillance Summaries, 68(12), 1–22. doi: 10.15585/mmwr.ss6812a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. WHO Regional Office for the Eastern Mediterranean. (2006). Tobacco use in shisha: Studies on waterpipe smoking in Egypt: World Health Organization. [Google Scholar]
  77. Yadav S, & Rawal G (2018). Waterpipe tobacco smoking: A mini-review. Journal of Translational Internal Medicine, 6(4), 173–175. doi: 10.1515/jtim-2016-0013 [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES