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  Table of Contents  
ORIGINAL ARTICLE
Year : 2012  |  Volume : 49  |  Issue : 4  |  Page : 401-409
 

Social disparities in tobacco use in India: The roles of occupation, education and gender


Healis Sekhsaria Institute for Public Health, Navi Mumbai, India

Date of Web Publication26-Feb-2013

Correspondence Address:
B Prabhakar
Healis Sekhsaria Institute for Public Health, Navi Mumbai
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0019-509X.107747

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 » Abstract 

Background: Identifying social disparities in patterns of tobacco use with regard to education, occupation, and gender characteristics can provide valuable insights into the tobacco use patterns of the population. Aim: We assessed social disparities in tobacco use, smoking, and smokeless tobacco use by examining occupation-, education-, and gender-specific patterns. Setting: About 69,030 Indian residents ΃15 years in 29 States and 2 Union Territories (UT). Design: Three-stage sampling in urban areas and two-stage sampling in rural areas for selection of households. Materials and Methods: Data has been derived from GATS 2009-2010, wherein the sample was collected through household interviews. Statistical Analysis: Percentages, proportions, adjusted odds ratios (ORs), and 95% confidence interval (CI) were reported. Results: As a person entered adulthood, the prevalence of ever tobacco use increased by 51.5% among men and 28.8% among women. Prevalence was 2.5 times higher in men (mainly smoking) as compared to women (predominantly smokeless form). ORs for tobacco use were higher among illiterate respondents as compared to the college educated (male OR = 4.23, female OR = 8.15). Unemployed, able to work (male OR = 1.50, female OR = 1.23) showed highest risk, while students (male OR = 0.35, female OR = 0.52) showed the least. The combined effect of occupation and education showed synergistic interaction among females and antagonistic interaction among males. Conclusion: The study clearly underscores the individual and joint effects of education and occupation on tobacco use besides discussing variations based on gender. This can have far-reaching policy implications in addressing disparities in tobacco use.


Keywords: Smokeless tobacco use, smoking, social determinants


How to cite this article:
Prabhakar B, Narake S S, Pednekar M S. Social disparities in tobacco use in India: The roles of occupation, education and gender. Indian J Cancer 2012;49:401-9

How to cite this URL:
Prabhakar B, Narake S S, Pednekar M S. Social disparities in tobacco use in India: The roles of occupation, education and gender. Indian J Cancer [serial online] 2012 [cited 2019 Oct 22];49:401-9. Available from: http://www.indianjcancer.com/text.asp?2012/49/4/401/107747



 » Introduction Top


Tobacco imposes a colossal burden of disease and death leading to catastrophic health, social, economic, and environmental effects. [1] Estimates indicate that over 1.1 billion people smoke worldwide and approximately four million persons die annually due to smoking. Cigarette smoking and other tobacco use currently accounts for one of every ten adult deaths. [2] Tobacco consumption continues to grow at 2-3% per annum. [1] It is estimated that by 2030, the proportion will be one in six or 10 million deaths per year - more than any other single cause. [3]

In India estimates reveal that roughly one-third of women and two-thirds of men use tobacco in one form or another. The estimated number of tobacco users in India is 274.9 million, with 163.7 million users of only smokeless tobacco; 68.9 million are exclusive smokers, and 42.3 million users of both smoking and smokeless tobacco. Nearly two in five (38%) adults in rural areas and one in four (25%) adults in urban areas use tobacco in some form. Prevalence of smoking among males is 24%, whereas, the prevalence among females is 3%. The extent of use of smokeless tobacco products among males (33%) is higher than among females (18%). [4] Overall, the smoking epidemic is spreading from its original focus - among men in high-income countries to women in high-income countries and men in low-income regions. [3]

Education entered into the model first as the strongest predictor of smoking (P < 0.001) among both men and women. [5] Smoking prevalence was high in illiterates and in literates with less than seven years of schooling, but decreased significantly with the increase in education status after attaining secondary education and more. [6] Men with no education were 1.8 times more likely to be smokers than men with college education, and women with no education were 3.7 times more likely than those with college education. [5]

Occupation is one category highly relevant to social disparities in health. People in manual occupations were more likely to smoke than those in professional or supervisory occupations. [3] In the occupational groups, agriculture and labor class had the highest prevalence as compared to other groups. [6] Nearly nine (9) national US studies on occupation and smoking likewise report that workers in working-class occupations (e.g., blue collar) are more likely to smoke.

Not only is occupation the link that binds education and income, but it is also an important determinant of health in its own right. Its importance lies in the ways in which work affects health, whether directly by hazardous exposures or, more indirectly, by influencing health behaviors. According to a study among Asians, current smoking was highest among those with less education and less income and in occupations classified as either "service" or "blue collar. [3]

In the present study, we assessed the disparities in tobacco use based on educational and occupational differences, including total tobacco use, bidi and cigarette smoking, and smokeless tobacco use, in a large sample derived from the Global Adult Tobacco Survey (GATS) India 2009-2010. [4] Additionally, variations on the basis of gender and age have also been assessed.


 » Materials and Methods Top


The data has been derived from GATS 2009-2010, which was conducted in 29 States of the country and the 2 Union Territories (UT) of Chandigarh and Puducherry covering about 99.9 percent of the total population in both urban and rural areas.

Study population

The eligibility criteria for respondents included in the survey was defined as all Indian residents 15 years of age or above living in their primary residence prior to the survey date. Eligibility for the survey was decided on the basis of age reported in the household interview.

Sampling design

The design comprised of a three stage sampling in urban areas and two-stage sampling in rural areas for selection of households. Sampling was done independently in each State/UT and within the State/UT, independently in urban and rural areas. In urban areas, the primary sampling units (PSUs) were the city wards, secondary sampling units (SSUs) were census enumeration blocks (CEBs), and tertiary sampling units (TSUs) were households. The required sample at each stage was selected using probability proportional to size (PPS).

In rural areas, the PSUs were villages and SSUs were households. Villages were stratified based on geographical regions, village size, proportion of scheduled caste, scheduled tribe population, and female literacy. Within each stratum, the required number of villages, i.e., PSUs, was selected according to the PPS sampling and from this the required number of households was selected. However, in all large villages with 300 or more households sampling design became a three-stage design. [4]

Sample size

The total number of persons interviewed was 69,296, which represent 94.8% of the total 79,690 persons sampled. The figures for the number of persons with completed interviews were 41,825 in rural and 27,471 in urban areas, thus covering 94.4% and 95.5% of the sampled persons by rural and urban residence, respectively. Finally, a total sample of 69,030 was analyzed. 266 respondents were excluded in this analysis because in these there were non-response variables in the occupation and the education categories.

Measures

In the present study, the primary outcome was to assess tobacco use, categorized as follows: (1) Having never used tobacco either in the past or present ("never user"), (2) former user (either smoking and use of smokeless tobacco in the past),(3) current smokeless tobacco user (including betel quid, mishri, and creamy snuff), (4) current cigarette smoker, and (5) current other smoker (including other forms of smoked tobacco, e.g. bidi, chilum, and hooka). Occupation was assessed according to respondents' self-reports and were coded as follows: Government employee, non-government employee, self-employed, unemployed (able to work), unemployed (unable to work), retired, homemaker, and student. Education level was classified as illiterate, primary school-, middle school-, secondary school-educated, and college/post graduate degree.

Data analysis

Data was analyzed using SPSS-13 software. For the overall population, descriptive characteristics were calculated separately for men and women. Multivariate analysis was done with tobacco use, only current smokeless tobacco use, current manufactured cigarette use, and current other smokers as the dependent variable (Tobacco use in any form =1 and Never use =0). Age-adjusted odds ratios for tobacco use were calculated for education and occupation categories for both men and women.

The interaction effect of occupation and education on tobacco use patterns was also studied in the analysis. Self-employed individuals, who had attained up to a college/post graduate education, were taken as the reference group. Odds ratios (ORs) were estimated for each of these interacting categories for both the genders at 95% Confidence Intervals (CIs). Analyses were conducted to study the multiplicative and additive effect of occupation and education status on tobacco use. Expected odds ratios for multiplicative model were calculated by multiplying individual ORs for the various categories of occupation across education and for additive model by adding individual ORs and then subtracting one from total. The interaction was termed synergistic when the observed ORs were higher than the calculated expected ORs, and antagonistic if they were lower.


 » Results Top


Sample characteristics

Analysis revealed that nearly half of the respondents were between 25-44 years of age [Table 1] and [Table 2]. The number of women was higher in the sample as compared to men. Some 11,688 (34.7%) of the men were in service-related occupation (government and non-government employees), while 15,284 (45.4%) were self-employed. Among women, nearly two-third (23,079 or 65.3%) were homemakers. The proportion of illiterates among women (12,658 or 35.8%) was almost twice than among men (6077 or 18%).
Table 1: Tobacco use among men by occupation, education and age

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Table 2: Tobacco use among women by occupation, education and age

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Tobacco use prevalence

[Table 1] and [Table 2] reveal that among men the prevalence of tobacco use (current or past) was higher (54%) than among women (23%). While among women smokeless tobacco use prevalence was highest, smoking was comparatively more common in men. Moreover, among men, a 51.5% increase in prevalence of ever tobacco use was seen as a person entered adulthood from adolescence (19.6% in 15-19 years age group to 40.4% in 21-25 years age group). In women, this increase was 28.8% (9.6% in 15-19 years age group and 13.4% in 21-25 years age group).

The proportion of men and women using tobacco was higher among those who were self-employed, non-government employees or unemployed. The prevalence of current tobacco use was seen to be the lowest among students for both men and women.

Education was found to be a strong gradient in determining the type of tobacco use. The prevalence of all tobacco use declined as the education level of respondents increased. Among men, however, the trend was reversed for cigarette use, where the prevalence increased with increasing education status.

When the joint effects of occupation and education on tobacco use were assessed [Table 3], it was found that the prevalence of tobacco use was highest in respondents who were illiterate and unemployed, unable to work. Moreover, in men as well as women the prevalence was higher in illiterates across most of the occupation categories.
Table 3: Joint effects of occupation and education on ever tobacco use+

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Multivariate analyses

[Table 4] presents gender-specific tobacco use odds ratios comparing current tobacco users, current smokeless tobacco users, current cigarette smokers, and smokers of bidi, and other forms of tobacco with individuals reporting never use of any form of tobacco product. Odds ratios according to occupation and education were adjusted for age.
Table 4: Adjusted odds ratios‡ (and 95% confidence Intervals) for various forms of tobacco use (vs. never use), by education, occupation, and gender

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Across all types of tobacco use the odds of using tobacco increased as the education level declined. The odds ratios according to education were higher among women as compared to men for overall tobacco use. These were especially high for those using smokeless tobacco in women, while for men, these were higher for bidi and other smoking forms of tobacco.

Among men, the odds of all types of tobacco use were found to be significant in those unemployed. Odds ratio were also higher for men who were homemakers, especially in those who were illiterate. Additionally, the odds of using cigarette were high in male government employees. In females, the odds of smoking bidi and other forms (excluding cigarettes) were the highest among those unemployed. It was found that women who were homemakers and retired men showed lower odds of using tobacco when compared with those self-employed. Students particularly exhibited lower odds ratio (both men and women), across all categories as compared to the reference group.

A joint adverse effect of occupation and education on prevalence is also discernible from this study. When the interaction effect due to these two factors was calculated using additive and multiplicative models [Table 5] and [Table 6], the observed values were higher than expected for females indicating a synergistic interaction, while among males this interaction was largely antagonistic.
Table 5: Interaction effect of education and occupation on risk of tobacco use-men

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Table 6: Interaction effect of education and occupation on risk of tobacco use-women

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 » Discussion Top


Prevalence of smoking varies widely among different age groups across different studies. [7],[8],[9],[10],[11] In a study among Asian Americans, the mean age at initiation of tobacco use was found to be 18.3 years. [12] According to GATS India 2009-2010, the mean age at initiation of daily tobacco use for tobacco users is 17.8 years. [4] The present study substantiated these findings, and a sharp rise in tobacco use prevalence was observed as one entered adulthood from adolescence. Older age was associated with greater prevalence of tobacco use, with women aged 65 and above and men aged 45 and above more likely to be tobacco users as compared to those of younger age-groups. The prevalence and practices of tobacco use based on gender are varied and disparate. [6],[13] In our study the current tobacco users among men were 50.2%, mostly smokers (30.3%). Among females, the prevalence of current tobacco use was found to be 20.6%, predominantly in smokeless form (16.9%).

Education seems to be a strong predictor of tobacco use. Numerous surveys worldwide and in India show a greater prevalence of tobacco use among the less educated and illiterate. In a cross-sectional sample survey (Sentinel Survey) of the ICMR and WHO on 35,288 persons aged 10 and above in Karnataka and 29,931 in Uttar Pradesh, a negative association between education and tobacco use was observed overall and in most of the age groups. [14],[15],[16] Tobacco use by the least educated is in large measure practiced in ignorance of the health consequences and a desire for a low cost source of pleasure and satisfaction. Among the more educated and urban population, tobacco use seems to be more in response to peer pressures and advertising. [1],[15],[17] In the multivariate analysis, the number of school years emerged as one of the strongest predictors - in terms of odds ratio - for both smoking and chewing among both men and women. [18] In a large population based study in Mumbai, [13] the odds ratios for any kind of tobacco use among the illiterate as compared to the college educated were 7.4 for males and 20.3 for females after adjusting for age and occupation. [14] In our study, this was found to be 4.23 (3.86, 4.62) for males and 8.15 (6.87, 9.66) for females, whenadjusted for age. Another study conducted in the western Indian state of Rajasthan showed that in the illiterate subjects the odds ratios and 95 per cent CIs for smoking or tobacco use as compared to the highest educational groups in rural as well as larger urban studies were significantly greater (P < 0.01). [19] An important trend encountered for tobacco use in India was that smokers with college-level education status tend to consume more cigarettes, which are relatively more expensive, while smokers with low levels of education status consume larger numbers of the inexpensive bidis.[3] In the present study this was found to be true for males, while in case of females tobacco use prevalence for all forms increased as the education level declined.

Occupational status is the conventional measure of one's position in the socioeconomic hierarchy, and it is more closely connected with working conditions than other socioeconomic indicators. [20] There are many misperceptions with regard to tobacco use, for example that it helps in concentration, suppresses appetite, reduces anxiety and tension, causes skeletal muscle relaxation, and induces feelings of pleasure. Partly as a result of these perceived benefits tobacco consumption is highest in the labor classes and among those from a low socioeconomic status. [21],[22] In our study, the prevalence was highest among the unemployed and least among students and government employees for both men and women. Similar results were shown by a study conducted in the United States where unemployed people were the most likely to smoke and retired individuals and students were the least likely to smoke. [23] Another study revealed that smoking rates were high among the unemployed, and quitting behaviors varied by sociodemographic factors and length of unemployment. Compared with students, the odds of daily smoking were higher among blue-collar workers (odds ratio, 2.66). [13],[24] The results of our study show that odds of current smoking were higher among unemployed and government employees, and least among students.

In all the above studies individual effect of education and occupation on tobacco use has been reported. Smoking prevalence is related not only to educational level but also to occupational class and measures of accumulated wealth (other than income). [25] Educational level and occupational status link people to social structure. Several studies have shown that tobacco use is higher among the less educated or illiterate, and the poor and marginalized groups. [21],[22] Greater neighborhood unemployment and poverty were associated with reduced odds of smoking abstinence, while greater neighborhood education was associated with higher odds of abstinence. [26] Education independently reduces the odds of a manual class person smoking relative to a non-manual by 12%. [27] When compared to their individual effect, the present study highlights that together they greatly increase the risk. This was further reiterated by the observation that the risk increased across all occupation categories as the education level of individuals declined. Illiterate non-government employees among men showed nearly five times increased risk of tobacco use as compared to the reference category, while this was found to be seven times higher in illiterate and unemployed (able to work) respondents among women.

The current study clearly underscores the individual and joint effects of education and occupation on tobacco use. It also emphasizes the variations in patterns of using tobacco based on gender, which was also found to determine the type of tobacco product used. The chief forms of tobacco use were smoking in case of men and smokeless forms in case of women. Education status was found to be a strong determinant as the odds ratios for tobacco use increased as the literacy level of respondents declined. Cigarette use was not found to be increasing with increasing education status, suggesting a departure from findings reported in previous literature. Occupation was found to have a greater impact with regard to men's tobacco use than that of women, because a large proportion of the women in the sample were housewives (65%) and 36% were illiterate.

The study reiterates the importance of identifying social disparities in patterns of tobacco use with regard to education, occupation and gender characteristics. Addressing these disparities can have far-reaching policy implications in tobacco control.


 » Acknowledgments Top


This work would not have been possible without the data collected for the Global Adult Tobacco Survey (GATS) 2009-2010 in India. We sincerely acknowledge the contributions of Ministry of Health and Family Welfare (MoHFW), Government of India; IIPS, Mumbai; World Health Organization (WHO) Country office for India, WHO SEARO; Centers for Disease Control and Prevention (CDC); CDC Foundation, Atlanta; Research Triangle Institute (RTI) International and Johns Hopkins Bloomberg School of Public Health (JHSPH) for their dedicated efforts in publishing the findings in this survey. Lastly, we gratefully recognize the support extended by all respondents who participated in GATS-India project.

 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]

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