Abstract
The effect of socioeconomic status on adolescent smoking behaviors is unclear, and sparse studies are available about the potential association. The present study aimed to measure and explain socioeconomic inequality in smoking behavior among a sample of Iranian adolescents. In a cross-sectional survey, a multistage sample of adolescents (n = 1,064) was recruited from high school students in Zanjan city, northwest of Iran. Principal component analysis was used to measure economic status of adolescents. Concentration index was used to measure socioeconomic inequality in smoking behavior, and then it was decomposed to reveal inequality contributors. Concentration index and its 95% confidence interval for never, experimental, and regular smoking behaviors were 0.004 [−0.03, 0.04], 0.05 [0.02, 0.11], and −0.10 [−0.04, −0.19], respectively. The contribution of economic status to measured inequality in experimental and regular smoking was 80.0% and 68.8%, respectively. Household economic status could be targeted as one of the relevant factors in the unequal distribution of smoking behavior among adolescents.
Introduction
Descriptive meta-analysis and review studies have revealed that many developed countries are in the middle of a smoking epidemic, and most developing countries are in the initial stages of this epidemic (Harper & McKinnon, 2012; Nazarzadeh et al., 2013; Zatonski, Przewozniak, Sulkowska, West, & Wojtyla, 2012). It is well established that health-related determinants depend on socioeconomic circumstances (Harper & McKinnon, 2012), but the relationship between smoking behaviors, one of the most important health-related behaviors, and socioeconomic status (SES) is not well explored. Based on the literature, SES plays an important role in the transition from monthly to daily smoking (Schaefer, Haas, & Bishop, 2012; Tjora, Hetland, Aaro, & Overland, 2011). Studies have indicated that adolescents who come from families with low SES, low education level, and poor employment of parents run higher risks of adopting a detrimental habit of smoking. This situation is typically known as “socioeconomic inequality in smoking” (Hanson & Chen, 2007; Mathur, Erickson, Stigler, Forster, & Finnegan, 2013).
There are currently a couple of methods developed to measure and quantify health-related inequalities. Concentration index is the most frequently used method in this regard. As a vantage point, concentration index can be decomposed into its constructing components, that is, inequality contributors (Kakwani, Wagstaff, & van Doorslaer, 1997; Wagstaff & van Doorslaer, 2004; Wagstaff, van Doorslaer, & Watanabe, 2003). Considering the ostensible importance of socioeconomic factors in smoking behavior distribution, knowledge of magnitude and effect of contributing factors to the distribution can be of sheer importance for health policy makers concerned with preventive measures. The effect of SES on adolescent smoking behaviors is unclear, and few studies are available about the potential association.
The aim of this research is to contribute to a better understanding of the SES determinants of smoking in adolescents by (1) assessing whether adolescents with a low SES have different motivates for smoking or nonsmoking from those with a high SES and (2) assessing the magnitude of inequality in distribution of smoking behavior among a sample of Iranian high school adolescents along with decomposing the inequality of responsible factors.
Method
Survey Design
Methods of this survey are similar to those reported in previous studies (Menati et al., 2016; Nazarzadeh et al., 2013). However, study participants were recruited from 61 classes selected randomly from 42 high schools in Zanjan city. Zanjan is the capital city of Zanjan province in northwestern Iran.
Initially, about 12,000 high school students in 9th, 10th, 11th, and 12th grades were identified, and 1,100 (9.1%) of them were selected by multistage sampling. Sampling procedure was done by considering the school type (stratum), the number of students in each school, the number of classrooms, and city regions (north and south). Researchers visited all 61 classes and explained the study to the students, invited them to participate, and distributed a self-administered multiple-choice questionnaire. To comply with research ethical codes and to decrease false negative responses, participants were ensured that the information would remain confidential and that data would be analyzed collectively. It is important to note that participants were free to leave the study at any time. Also, to facilitate a maximum response rate, questionnaires were distributed before the beginning of class and no personal information was registered.
Data Collection Tools and Measures
A specific questionnaire developed to measure smoking stages among adolescents was used to measure the required data. Validity and reliability of this instrument and its constructing scales are reported in detail elsewhere (Alireza Ayatollahi, Mohammadpoorasl, & Rajaeifard, 2005). This questionnaire was specifically tailored for addiction research among Iranian adolescents and has already been used in many addiction-related studies (Mohammadpoorasl, Fakhari, Rostami, & Vahidi, 2007; Nazarzadeh, Bidel, & Carson, 2014; Nazarzadeh, Bidel, Mosavi Jarahi, et al., 2014; Nazarzadeh et al., 2013). The questionnaire gathers the following data: demographical characteristics of students and their family members, SES, cigarette smoking behavior, general risk taking behavior, cigarette smoking norms, self-esteem, attitude toward cigarette smoking, and positive outlook toward cigarette smoking. An algorithm validated by a latent class analysis model was used to determine the cigarette smoking stage that a person resides in (Mohammadpoorasl et al., 2013). Accordingly, students were categorized into three stages: (1) never smoker: adolescents who have never smoked (even a puff), (2) experimenter smoker: adolescents who have already tried the cigarette (even a puff) but have smoked less than 100 cigarettes in lifetime, and (3) regular smoker: adolescents who have smoked 100 cigarettes and more in lifetime, without considering their present consumption.
Information on age of students, their household size, level of parents’ education, allowance use, private room ownership, area of residential building, nonacademic extracurricular attendance, sports team membership, and ownership of some assets was obtained. Asset (wealth) index method was used to measure students’ household economic status. Principal component analysis was used to measure asset index (Rutstein & Johnson, 2004). The investigated assets were as follows: car, washing machine, dishwasher, fridge/freezer, vacuum cleaner, personal computer and laptop, microwave, and LCD or LED TV. After determining economic status, participants were divided into five groups by economic quintiles, starting from the richest down to the poorest.
Statistical Analysis
Distribution of continuous and ordinal variables was assessed by histogram plot and Kolmogorov–Smirnov test. According to normality of data, independent t test and Mann–Whitney U test were used to compare SES characteristics across smoking stages. In addition, chi-square test was used to assess categorical variables.
Concentration curve and index were used to measure and decompose socioeconomic inequality in smoking behavior (smoking stages) among selected representative samples of student adolescents in Zanjan city. The two key variables underlying the concentration curve were the health variable, the distribution of which is the subject of interest, and a variable that measures economic status, against which the distribution is to be assessed. The concentration curve plots the cumulative percentage of the health variable (y-axis) against the cumulative percentage of the sample ranked by economic status, starting from the poorest (x-axis). If everyone, irrespective of their economic status, has exactly the same value of health variable, the concentration curve will be a 45-degree line, running from the bottom left-hand corner to the top right-hand corner. This is known as the line of equality. If, in contrast, the health sector variable takes higher (lower) values among poorer people, the concentration curve will lie above (below) the line of equality. In fact, concentration index reports the distance between the concentration curve and the line of equality. Concentration index ranges from −1 to +1, with negative values indicating that the concentration curve lies above the line of equality and vice versa.
Wagstaff et al. (2003) demonstrated that a concentration index can be decomposed into contributions of individual factors to measure inequality in which each contribution is the product of sensitivity (relationship) of a health variable with that factor and the degree of economic inequality in the factor.
For any linear additive regression model of health, such as
the concentration index for y can be written as
where µ is the mean of y,
The residual component (total concentration minus the sum of absolute contribution of each determinant) reflects the part of inequality in health (measured as health concentration index) that is not explained by systematic variation in the regressors across SES, which should approach zero for a well-specified model.
Statistical analyses were conducted using Distributive Analysis Stata Package in Stata software (Version 11/SE; StataCorp, 2007). The level of statistical significance for the tests mentioned above was set at p ≤ .05.
Results
The nonresponse rate was nearly 10%. Sociodemographic characteristics of study participants are reported in Table 1. Mean ± standard deviation of age for never, experimental, and regular smokers was 17.12 ± 0.05, 17.46 ± 0.08, and 17.93 ± 14.00, respectively (range: 14-21 years). Totally, 242 (23.40%) and 112 (10.80%) students acknowledged that they were experimental and regular smokers, respectively. Father’s education, allowance use, sports team membership, economic status, age, area of residential building, and number of house rooms were significantly different between regular smokers and never smokers (p < .05).
Sociodemographic Characteristics of High School Students (N = 1,064) According to Their Smoking Behaviors.
Categorical variables shown as n (%) with p value according to χ2, continuous variables shown as mean (standard deviation). bShown as median (interquartile range). cp value according to indipendent t test and Mann–Whitney test, respectively.
p ≤ .05.
Concentration index and its 95% confidence intervals for never, experimental, and regular smoker were 0.004 [−0.03, 0.04, 0.10 [0.40, 0.19], and −0.05 [−0.02, −0.11], respectively (Figure 1). Decomposition of the concentration index for regular smokers reported that parent education, nonacademic extracurricular attendance, and sports team membership had low to modest contribution to measured socioeconomic inequality in smoking behavior, and economic status had the highest contribution (60.80%). Likewise, the contribution of economic status among experimental smokers was highest (80.00%). Table 2 illustrates the decomposition results.
Concentration curves for different smoking behaviors.
Results of Decomposition of Concentration Index for Smoking Behavior Among High School Adolescents.
Note. CI = Concentration Index.
Discussion
To the best of our knowledge, the present study is the first attempt to decompose socioeconomic inequality in smoking behavior among high school adolescents in Iran. The current study reported that experimental and regular smoking behaviors were unequally distributed among high school adolescents. Experimental and regular smoking behaviors were more concentrated among richer and poorer Iranian adolescents, respectively. Moreover, economic status had the highest contribution to the measured inequality. The measured inequality was not significant for never smokers.
In the present study, economic status was measured at the household level. Whether the economic status should be measured at the household or individual level for adolescents has been argued for decades in economics. For instance, a study in Finland identified that economic status at the household level was not significantly associated with smoking behavior among adolescents (Paavola, Vartiainen, & Haukkala, 2004). Other studies, in contrast, have identified a weak association in that level (Epstein, Botvin, & Diaz, 1999; Tuinstra, Groothoff, van den Heuvel, & Post, 1998), and some report that smoking behavior is more related to individual-level characteristics than to household ones (Richter & Leppin, 2007).
On the contrary, other researchers believe that household income information can empower researchers to illustrate any relationship between income and smoking (Nakamura et al., 1994). However, individual or household, one should note that income and expenditure are usually used as proxy of economic status in inequality studies. Valid estimation of these variables among (high school) adolescents can be very biased and challenging. Instead, adolescents’ response to ownership of household assets can be less daunting and bias-inducing. Due to these reasons and considering all pros and cons, the authors of this article decided to use the latter method to determine high school adolescents’ economic status.
More important, in the current study, household economic status had the highest contribution to measured inequality in smoking behavior (experimental and regular), and this was higher for experimental smokers. Previous studies have similarly reported that adolescent smoking is strongly related to families’ economic status (De Vries, 1995; Koivusilta, Rimpelä, & Kautiainen, 2006). Doku, Koivusilta, Rainio, and Rimpelä (2010) reported that such an inequality in distribution of smoking behavior becomes stable over time, a matter that calls for proper smoking prevention policy making and intervention for adolescents. However, as high school adolescents have not yet finished school education and can still move upward socially, interpretation of the effect of family economic status on adolescents’ smoking behavior should be done cautiously. The current study reported that 32% of regular smoker students received some allowance less than 50,000 rials (≅1.88 USD) per day. A daily smoking habit costs less than 63,000 rials (≅2.37 USD) in Iran (Tafti et al., 2006). So poorer students who smoke spend a disproportionate share of their allowance on cigarette smoking compared to more affluent students who smoke. Authors believe that such a behavior might be related to cultural issues. Therefore, an in-depth qualitative scrutiny is needed to explore reasons for such a phenomenon.
As per some other studies (Hanson & Chen, 2007), the current study also identified that parental education plays an important role in the unequal distribution of smoking behavior, experimental or regular. Father’s education level (low level of education), particularly, had a notable contribution to the inequality in regular smoking behavior. Zaloudikova, Hruba, and Samara (2012) have reported that mother’s education level had a protective role in adolescents’ tendency toward smoking. As a reason for such a role of parent education in smoking, it can be postulated that higher level of parental education facilitates the speed and process of information exchange to adolescents, which acts as a buffer against the tendency to smoke.
The present study identified that area of residential building had a positive contribution to inequality, in both experimental and regular smoking. As a reason for such an observation, the authors believe that bigger areas provide more private conditions for smoking in adolescents so that they can hide from parental supervision. However, Fukuda, Nakamura, and Takano (2005), in contrast, reported that there is no significant relationship between these two variables. Rigorous research on this issue is needed in the future.
The current study has some limitations that are worth considering. First, social determinants such as parental occupation were not included in the current study. In a previous study, investigators identified that the influence of parental occupation on adolescent smoking in low- compared with high-SES parents was different (Tjora et al., 2011). Second, as in cross-sectional studies, no cause-effect can be pinned down, and assured, longitudinal studies are needed to assess the temporality of the reported association. Also, studies like Oaxaca decomposition are needed to investigate the persistence of revealed inequality in smoking. Third, as data gathering was done by self-administered questionnaire, some response and information biases can be induced, a matter that should be kept in mind when interpreting the findings.
Conclusion
In conclusion, smoking behavior was unequally distributed among (a sample of) Iranian high school adolescents, and economic status had the highest contribution to inequality in smoking behavior. Regular adolescent smokers were mostly concentrated among the poorer households of society, and experimental smokers were concentrated among affluent households. Household economic status could be targeted as one of the most relevant factors in the unequal distribution of smoking behaviors among adolescents in future research.
Footnotes
Acknowledgements
We wish to thank Zanjan University of Medical Science, Iran, for financial support. We also thank Dr. Fatemeh Jafari for her valuable critical appraisal on the research proposal; Abolfazl Bahrami, Hadi Vaezi, Mehdi Bagheri, Reza Najafi, and Asaad Kohi for their dedicated efforts in data collection procedures; and Mohsen Rahimi for management of the data entry procedure. We also appreciate all the students and teachers of Zanjan city high schools for their valuable collaboration with the researchers.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was performed with financial support from Zanjan University of Medical Science (ZUMS), Iran (Fund No. 113795). ZUMS had no role in the study design; collection, analysis, or interpretation of the data; writing the manuscript; or the decision to submit the manuscript for publication.