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Erschienen in: BMC Public Health 1/2022

Open Access 01.12.2022 | Research article

Association of mass media exposure with combustible and smokeless tobacco use among Indian population: findings from a panel survey

verfasst von: Ronak Paul, Rashmi Rashmi, Shobhit Srivastava

Erschienen in: BMC Public Health | Ausgabe 1/2022

Abstract

Background

Despite introducing different policies and initiatives, India is recognized as one of the global players in the tobacco epidemic race. Our study explores the association between tobacco consumption and mass media exposure among the Indian population, considering the contextual factors affecting the clustering at the community and state levels.

Methods

Using two waves of the India Human Development Survey (IHDS) conducted in 2005 and 2012 for 16,661 individuals, the present study explores the association of mass media exposure and tobacco consumption in the short-term and the long-term period of Cigarettes and Other Tobacco Products Act (COTPA) implementation, which came into existence in 2004. Bivariate analysis using the chi-square test for association showed the correlation of tobacco consumption with its respective predictors. Multivariable analysis using three-level random intercept logit models showed the adjusted association between tobacco consumption and its relevant covariates and the extent of clustering of tobacco consumption behaviour of persons in the communities and states.

Results

We found that watching television (TV) [(OR:1.03; CI:0.92–1.15) in 2004–05 and (OR:0.99; CI:0.88–1.12) in 2011–12], listening radio [(OR: 0.99; CI:0.90–1.10) in 2004–05 and (OR:1.04; CI:0.94–1.15) in 2011–12] and reading newspaper [(OR:1.02; CI:0.91–1.15) in 2004–05 and (OR:0.96; CI:0.87–1.06) in 2011–12] did not have any significant effect on consumption of combustible tobacco. Similarly, no effect of mass media was found on smokeless tobacco consumption. Further, the clustering of combustible and smokeless tobacco usage was higher at the community level than at the state level. In both rounds, smokeless tobacco consumption was found to be higher than combustible tobacco.

Discussion

The present study provides evidence that COTPA has achieved its aim of nullifying the significant effect of mass media on combustible and smokeless tobacco consumption among the Indian population. However, the influence of state- and community- level clustering had failed in curbing the increment of smokeless tobacco consumption. There is a need for policy reforms to curb the significant impact of factors that promotes smokeless tobacco consumption in India. Further, initiatives must focus on specific communities from high-risk states, reducing the time and cost required for implementation.
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Abkürzungen
IHDS
India Human Development Survey
COPTA
Cigarettes and Other Tobacco Products Act
OR
Odds ratio
ICC
Intra-class Correlation Coefficient
OBC
Other Backward Classes
SC
Scheduled Castes
ST
Scheduled Tribes
CI
Confidence Interval

Background

Combustible and smokeless tobacco consumption is the most significant preventable cause of death worldwide [1]. Being the second-largest tobacco consumer, India is one of the global players in the tobacco epidemic race [2]. In 2016, tobacco consumption (including smoking, smokeless tobacco and second-hand smoke) had alone contributed 6% DALYs (Disability-adjusted life-years) in India, and the burden was higher among the men (8.3% of total DALYs) than in women (3% of total DALYs) [3]. Existing evidence from India has shown the trends in the prevalence of different forms of tobacco consumption [46]. Several studies linked combustible and smokeless tobacco consumption with family, friends, and peer influence (social support for tobacco use) [7]. A couple of studies have linked tobacco consumption with illiteracy and working stress [8, 9]. Other studies identified affordability and social acceptability [10], socioeconomic inequality [11], pro-tobacco media campaigns by tobacco companies to attract the population, especially the youngsters [12], as factors leading to a hike in smokeless and combustible tobacco consumption. Additionally, the powerful influence of films and advertisements featuring the macho image of characters who smoke has an everlasting impact on children and adolescents’ minds, leading them to adopt similar tobacco consumption behaviour [13]. Some studies have also shown the differential in smoking and smokeless tobacco usage across the Indian states and communities [5, 6]. A cross-sectional study from India had tried to reveal geographic variation in tobacco consumption and showed the importance of local contextual factors and policies that shape tobacco use [14].
Despite such prominent explanatory factors of tobacco consumption, a recent reduction in combustible tobacco has been noticed among Indian individuals [15, 16]. However, a different concern of increased smokeless tobacco consumption compared to smoking has come up [17]. It is worth noting that India, Bangladesh and Myanmar jointly contribute 71% of world smokeless tobacco consumers [18]. One study showed that a ban on smoking in public places in India had resulted in an increment in smokeless tobacco consumption [19]. Another research from three countries (Bangladesh, India, Nepal) of Southeast Asian regions revealed that tobacco companies’ misleading tobacco advertisements continuously drove smokers to the alternative of smokeless tobacco consumption [17]. The study noted that the marketing of tobacco products was done by promoting them as an inalienable part of the consumer’s lifestyle. Direct and surrogate advertising of these products through the media influences the consumers and encourages them to use them [20]. However, the Indian parliament had introduced the Cigarettes and Other Tobacco Products Act (COTPA), 2003, which came into effect from May 2004 to ensure that Indian people do not indulge in or increase their tobacco consumption by being influenced by the media content [21]. Ample evidence from India, since 2005, revealed that media exposure still plays an essential role in increasing combustible and smokeless tobacco usage among people [22, 23].
The present study examines the association between tobacco use and mass media exposure among the Indian population, considering the contextual factors that may affect the clustering of tobacco consumption at both community and state levels. The rationale for such analysis is as follows. First, minimal attempts have been made to understand the effect of the tobacco advertisement ban through mass media on the likelihood of combustible and smokeless tobacco use in the Indian context. One study using National Family Health Survey 2005–06 data (i.e., after COTPA act implementation) showed the association between smoking and smokeless tobacco use and mass media exposure among Indian adults aged 15–54 years [24]. However, it could not provide similar evidence for adolescents and the elderly. Second, rather than proceeding with a before-after impact assessment of the COTPA act, this study wants to utilize the panel nature of the India Human Development Survey (IHDS) dataset conducted in 2005 and 2012, to explore the association of mass media exposure and different tobacco consumption in the short-term (in the early phase of a 1-year leap) and the long-term (in the later phase of 7 years leap) period among the same individuals after the COTPA act implementation. Third, a dearth of evidence on the association of tobacco consumption and mass media exposure after considering the contextual level factors convince us to explore the variation in combustible and smokeless tobacco consumption clustering using a three-level multilevel approach.

Methods

Data source

This study used the India Human Development Survey (IHDS) round-I and round-II. IHDS round-I is a large-scale, nationally representative and multi-topic survey of 41,554 households across 382 districts of India conducted during 2004–05 [25]. The IHDS round-II, conducted during 2011–12, surveyed 42,152 households across 384 districts of India [26]. IHDS round-II re-interviewed 83% of the original households from round-I. National Council for Applied Economic Research (NCAER) India, in collaboration with the University of Maryland, USA, conducted both rounds of IHDS in all the Indian states and union territories (except for Andaman & Nicobar Islands and Lakshadweep). IHDS used multi-stage stratified random sampling, and further details regarding the sample selection procedure are available elsewhere [27, 28].
IHDS collected combustible and smokeless tobacco consumption data from 33,116 and 34,090 persons during round-I and round-II. The current study used the panel data of 16,661 individuals nested within 2175 communities across 33 states from both rounds for analysis. By community, this study refers to the primary sampling units (PSU), which are villages in rural areas and census enumeration blocks in urban areas, respectively. In our study panel, 61% of 16,661 persons smoked tobacco during round-I, which decreased to 41% during round-II. Moreover, nearly 59% of persons consumed smokeless tobacco in both rounds of IHDS.

Outcome variables

The two outcome variables of this study are the binary indicators denoting whether an individual consumed combustible tobacco and smokeless tobacco, respectively. During IHDS round-I and round-II, interviewers collected information about “whether an individual smokes cigarettes, bidis or hookah” (combustible tobacco products) and “whether an individual chews tobacco or gutkha” (smokeless tobacco products), respectively. Persons who consumed one or more combustible or smokeless tobacco products were coded as “Yes” and otherwise coded as “No”. Both the outcome variables had no records with missing information in both rounds of the panel data.

Explanatory variables

The three binary indicators of mass media exposure – whether anyone in the household “watches television (TV)”, “listens to radio”, and “reads the newspaper” are the explanatory variables in both rounds of IHDS. During both survey rounds, interviewers asked a respondent from each household about how often do people in the family “listen to radio”, “read the newspaper”, and “watch TV”. Owing to skewed distribution, households in the “sometimes” and “daily” categories were coded as “yes”; otherwise, they were recoded to “no”. The three explanatory variables had no records with missing information in both rounds.

Control variables

The current study identified several confounding factors associated with tobacco consumption and mass media exposure among individuals based on existing research. The individual-level characteristics were – age group (children and youth, adults, elderly), sex (male, female), level of education (no formal schooling, 1–5 years of schooling, 6–10 years of schooling, more than 10 years of schooling), current working status (not working, working) and current marital status (currently married, currently not married). The household characteristics were – wealth quintile (poorest, poor, middle, rich, richest), the caste of household head (Other Backward Classes (OBC), Scheduled Castes (SC), Scheduled Tribes (ST), others) and religion of household head (Hinduism, Islam, others). Further, we included the following contextual variables at the community level – Percentage of individuals in the community with no formal education (0 to 25%, 25 to 50%, 50 to 75%, 75 to 100%), Percentage of individuals in the community from poorest/poor wealth quintile (0 to 25%, 25 to 50%, 50 to 75%, 75 to 100%) and Percentage of individuals in community belonging to SC/ST caste (0 to 25%, 25 to 50%, 50 to 75%, 75 to 100%). Additionally, place of residence (rural, urban) is included as a community-level characteristic. Country regions (central, northern, southern, western, eastern and north-eastern) is included as a state-level characteristic.
In our study sample, the population distribution by age is skewed with fewer people in the young and old age categories. Therefore, persons aged 24 years and less were coded as “children and youth”, those aged between 25 to 64 years were coded as “adults”, and “elderly” included persons 65 years and above in the age group variable.
We estimated the wealth quintile for all households in both rounds of IHDS. We generated the wealth scores using the standard procedure of principal component analysis using household data on asset ownership, building material type, type of household water source, type of household sanitation facility and the number of living rooms in the household. Details of the standard procedure are available elsewhere [29, 30]. Based on the wealth score, the families were classified into five categories (poorest, poor, middle, rich, richest) such that the households with the lowest 20 percentile score belonged to the “poorest” category, families with the next low 20 percentile score belonged to the “poor” class and so forth [30, 31].
Contextual characteristics of the community where a person belongs are known to influence their behaviour. Therefore, in a multicultural country like India, these factors might significantly affect the tobacco consumption behaviour of individuals. Accordingly, we controlled for the effect of the community’s educational, economic, and social composition. The community-level education composition has been shown by the percentage of the population with no formal education in a community. The community social composition is determined by the percentage of Scheduled Tribes (ST) and Scheduled Castes (SC) population in a community. The percentage of the people belonging to the poorest and poor wealth quintile shows the economic composition of the community. All the three indicators have four categories – 0 to 25%, 25 to 50%, 50 to 75%, and 75 to 100%. We divided the 33 Indian states and union territories into six regions based on administrative classification [32].

Statistical methods

We undertook bivariate and multivariable analyses to fulfil the study objectives. We performed two similar sets of evaluations separately for examining the association of combustible and smokeless tobacco consumption with mass media exposure among the same population during round-I and round-II, respectively. Bivariate analysis showed the correlation of tobacco consumption with its respective predictors, using the chi-square test for association. Multivariable analysis using three-level random intercept logit models showed the association between tobacco consumption and its relevant covariates and the extent of clustering of tobacco consumption behaviour of persons in the communities and states, respectively [33, 34]. We used a three-level multilevel model owing to the hierarchical structure of the data where 16,661 persons (level 1) are nested within 2175 communities (level 2), which in turn are nested within 21 states (level 3). Note that, owing to the skewed distribution of population across the 33 states, we have merged them into 21 groups such that the five union territories (Delhi, Chandigarh, Daman & Diu, Dadra & Nagar Haveli and Pondicherry), the seven north-eastern states (see section Control variables) and Maharashtra & Goa are in distinct groups. Further, a multilevel logit model was necessary, as the outcome variables of this study are binary.
The use of a three-level model allows us to adjust for unexplained inter-community and inter-state variation (heterogeneity) in the risk of tobacco consumption. These models give odds ratios that are the odds of tobacco consumption among all the persons in a particular category compared to the reference category for the specific explanatory variable, given that the effect of all the other explanatory variables and the group-level effects remains constant. The multivariable models give the Intra-class Correlation Coefficient (ICC) that measures the expected degree of similarity (homogeneity) of tobacco consumption among persons belonging to the same group [34]. The community-level ICC for persons belonging to the same community (and therefore the same state) is the sum of state-level and community-level variance divided by the total variance in the model [35]. The state-level ICC for persons belonging to the same state (but not necessarily from the same community) is the proportion of state-level variance out of the total variance.
Extant studies have shown that it is incorrect to undertake cross-group comparisons of odds ratios obtained from logistic regression models, even if they have a similar set of dependent and independent variables [36, 37]. Therefore, to overcome this limitation and facilitate comparisons of the risk of tobacco consumption across both rounds of IHDS, we estimated marginal predicted probabilities of combustible tobacco consumption (or smokeless tobacco consumption) for a particular independent variable, at the median values (margins) of other independent variables [37].
We checked for multicollinearity in the multivariable regression models and found that the mean-variance inflation factor (VIF) across all models was less than 2.85 in both rounds, implying the non-necessity of adjusting for multicollinearity in the regression models [38]. All statistical estimations in the study were performed using the STATA software, version 13.0 [39].

Results

Descriptive analysis

Table 1 represents the numeric (N) and percentage (%) population distribution by relevant socioeconomic and demographic characteristics in the cross-sectional and panel datasets during IHDS round-I and round-II, respectively. We found that about 67 and 79% of household members watched TV in 2004–05 and 2011–12. Nearly 48 and 28% of household members listened to the radio in 2004–05 and 2011–12. About 39 and 48% of household members read newspapers in 2004–05 and 2011–12. About 7% of the study population had more than 10 years of schooling in 2004–05 and 2011–12.
Table 1
Population distribution by explanatory characteristics in the cross-sectional and panel datasets during two IHDS rounds
Characteristics
IHDS round-I
IHDS round-II
Cross-sectional dataset
Panel dataset
Absolute difference
Cross-sectional dataset
Panel dataset
Absolute difference
N
%
N
%
%
N
%
N
%
%
Household members watch TV
 No
10,126
30.6
5538
33.2
2.6
6398
18.8
3447
20.7
1.9
 Yes
22,990
69.4
11,123
66.8
2.6
27,692
81.2
13,214
79.3
1.9
Household members listen to radio
 No
16,930
51.1
8724
52.4
1.3
24,172
70.9
11,910
71.5
0.6
 Yes
16,186
48.9
7937
47.6
1.3
9918
29.1
4751
28.5
0.6
Household members read newspaper
 No
18,576
56.1
10,186
61.1
5.0
16,584
48.6
8620
51.7
3.1
 Yes
14,540
43.9
6475
38.9
5.0
17,506
51.4
8041
48.3
3.1
Age group of individual
 Children and youth
2411
7.3
1004
6.0
1.3
2510
7.4
90
0.5
6.9
 Adults
27,151
82.0
14,527
87.2
5.2
27,095
79.5
13,952
83.7
4.2
 Elderly
3554
10.7
1130
6.8
3.9
4485
13.2
2619
15.7
2.5
Gender of individual
 Male
27,609
83.4
14,889
89.4
6.0
28,306
83.0
14,892
89.4
6.4
 Female
5507
16.6
1772
10.6
6.0
5784
17.0
1769
10.6
6.4
Level of education of individual
 No formal schooling
13,555
40.9
6984
41.9
1.0
12,542
36.8
6881
41.3
4.5
 1–5 years of schooling
6715
20.3
3581
21.5
1.2
6947
20.4
3738
22.4
2.0
 6–10 years of schooling
9825
29.7
4935
29.6
0.1
10,959
32.1
4810
28.9
3.2
 More than 10 years of schooling
3021
9.1
1161
7.0
2.1
3642
10.7
1232
7.4
3.3
Current working status of individual
 Not working
15,373
46.4
6787
40.7
5.7
7191
21.1
2705
16.2
4.9
 Working
17,743
53.6
9874
59.3
5.7
26,899
78.9
13,956
83.8
4.9
Current marital status of individual
 Currently married
28,455
85.9
15,123
90.8
4.9
28,335
83.1
14,884
89.3
6.2
 Currently not married
4661
14.1
1538
9.2
4.9
5755
16.9
1777
10.7
6.2
Wealth quintile of household
 Poorest
7460
22.5
4442
26.7
4.2
7463
21.9
4060
24.4
2.5
 Poor
7147
21.6
3897
23.4
1.8
7933
23.3
4108
24.7
1.4
 Medium
6958
21.0
3585
21.5
0.5
7399
21.7
3703
22.2
0.5
 Rich
6547
19.8
2903
17.4
2.4
6158
18.1
2850
17.1
1.0
 Richest
5004
15.1
1834
11.0
4.1
5137
15.1
1940
11.6
3.5
Caste of household head
 Other Backward Classes
12,811
38.7
6634
39.8
1.1
13,649
40.1
6576
39.5
0.6
 Scheduled Castes
7521
22.7
4066
24.4
1.7
8005
23.5
4111
24.7
1.2
 Scheduled Tribes
3983
12.0
1944
11.7
0.3
3921
11.5
1974
11.8
0.3
 Others
8801
26.6
4017
24.1
2.5
8470
24.9
4000
24.0
0.9
Religion of household head
 Hindu
27,046
81.7
13,945
83.7
2.0
28,235
82.8
14,100
84.6
1.8
 Muslim
3657
11.0
1740
10.4
0.6
3980
11.7
1754
10.5
1.2
 Others
2413
7.3
976
5.9
1.4
1875
5.5
807
4.8
0.7
Place of residence
 Rural
24,641
74.4
13,223
79.4
5.0
24,795
72.7
12,904
77.5
4.8
 Urban
8475
25.6
3438
20.6
5.0
9295
27.3
3757
22.5
4.8
Country regions
 Central
7663
23.1
4898
29.4
6.3
9615
28.2
4898
29.4
1.2
 Northern
6522
19.7
3368
20.2
0.5
6925
20.3
3368
20.2
0.1
 Southern
5683
17.2
2418
14.5
2.7
5566
16.3
2418
14.5
1.8
 Western
4302
13.0
1931
11.6
1.4
4186
12.3
1931
11.6
0.7
 Eastern
6572
19.8
3356
20.1
0.3
6206
18.2
3356
20.1
1.9
 North-eastern
2374
7.2
690
4.1
3.1
1592
4.7
690
4.1
0.6
Overall
33,116
100
16,661
100
0
34,090
100
16,661
100
0
From the “absolute difference” column, we observe that the percentage population distribution by socioeconomic and demographic characteristics is similar across the cross-sectional and panel datasets in both rounds of IHDS, respectively. In round-I, the distribution of persons by gender and country regions differed by more than 6% between the cross-sectional and panel datasets. Similarly, population distribution by gender and current marital status differed by more than 6% during round-II.

Bivariate analysis

Table 2 presents the bivariate association of relevant individual-level, socioeconomic and community-level variables with combustible and smokeless tobacco consumption during 2004–05 and 2011–12, respectively. A higher percentage of individuals who do not watch TV consumed combustible tobacco [61% in 2004–05 and 54% in 2011–12]. Nearly 62% and 53% of the study population who listened to radio indulged in combustible tobacco in 2004–05 and 2011–12, respectively. Similarly, a higher percentage of individuals who do not read newspapers consumed combustible tobacco [62% in 2004–05 and 53% in 2011–12]. A higher proportion of adults [62% in 2004–05 and 53% in 2011–12] consumed combustible tobacco, whereas a higher percentage of males consumed combustible tobacco [66% in 2004–05 and 58% in 2011–12]. Communities with a lower percentage of the non-educated population had a higher percentage of combustible tobacco consumption in 2004–05 but the relationship inversed in 2011–12. Similarly, a community with a lower percentage of poor individuals had a higher percentage of combustible tobacco consumption in 2004–05 and 2011–12. More rural residents consumed combustible tobacco [62% in 2004–05 and 54% in 2011–12]. Combustible tobacco consumption was highest in the northern region of India [83% in 2004–05 and 77% in 2011–12].
Table 2
Bivariate analysis showing the association of individual-level, community-level and relevant socioeconomic variables with combustible and smokeless tobacco use during IHDS round-I and round-II, respectively
Characteristics
IHDS round-I
IHDS round-II
Combustible tobacco
Smokeless tobacco
Combustible tobacco
Smokeless tobacco
Total
Yes
Chi2 test
p-value
Total
Yes
Chi2 test
p-value
Total
Yes
Chi2 test
p-value
Total
Yes
Chi2 test
p-value
N
%
N
%
N
%
N
%
Household members watch TV
 No
5538
61.1
0.765
5538
61.6
< 0.001
3447
53.6
0.298
3447
63.2
< 0.001
 Yes
11,123
60.9
11,123
57.3
13,214
52.6
13,214
58.0
Household members listen to radio
 No
8724
59.8
0.002
8724
57.2
< 0.001
11,910
52.6
0.463
11,910
58.4
0.003
 Yes
7937
62.2
7937
60.5
4751
53.3
4751
60.9
Household members read newspaper
 No
10,186
61.8
0.009
10,186
59.7
0.001
8620
53.2
0.256
8620
61.2
< 0.001
 Yes
6475
59.7
6475
57.2
8041
52.4
8041
56.8
Age group of individual
 Children and youth
1004
46.8
< 0.001
1004
73.1
< 0.001
90
31.1
< 0.001
90
83.3
< 0.001
 Adults
14,527
62.2
14,527
57.5
13,952
53.0
13,952
59.0
 Elderly
1130
58.0
1130
61.7
2619
52.4
2619
58.7
Gender of individual
 Male
14,889
66.3
< 0.001
14,889
55.4
< 0.001
14,892
57.5
< 0.001
14,892
55.7
< 0.001
 Female
1772
16.3
1772
87.1
1769
13.1
1769
87.9
Level of education of individual
 No formal schooling
6984
60.4
< 0.001
6984
60.2
< 0.001
6881
53.0
< 0.001
6881
61.3
< 0.001
 1–5 years of schooling
3581
63.3
3581
59.6
3738
55.8
3738
58.2
 6–10 years of schooling
4935
61.7
4935
55.6
4810
52.4
4810
56.4
 More than 10 years of schooling
1161
53.8
1161
60.5
1232
44.2
1232
60.4
Current working status of individual
 Not working
6787
57.6
< 0.001
6787
61.3
< 0.001
2705
38.0
< 0.001
2705
66.1
< 0.001
 Working
9874
63.3
9874
57.0
13,956
55.7
13,956
57.7
Current marital status of individual
 Currently married
15,123
62.4
< 0.001
15,123
57.7
< 0.001
14,884
54.1
< 0.001
14,884
58.0
< 0.001
 Currently not married
1538
47.1
1538
69.4
1777
42.4
1777
68.0
Wealth quintile of household
 Poorest
4442
54.6
< 0.001
4442
71.3
< 0.001
4060
49.0
< 0.001
4060
73.0
< 0.001
 Poor
3897
62.6
3897
62.3
4108
52.4
4108
63.6
 Medium
3585
64.8
3585
53.1
3703
55.1
3703
54.7
 Rich
2903
64.2
2903
50.1
2850
55.3
2850
48.6
 Richest
1834
60.3
1834
45.5
1940
53.7
1940
44.2
Caste of household head
 Other Backward Classes
6634
59.5
< 0.001
6634
62.1
< 0.001
6576
51.7
< 0.001
6576
62.6
< 0.001
 Scheduled Castes
4066
65.2
4066
55.6
4111
57.8
4111
54.9
 Scheduled Tribes
1944
50.1
1944
72.5
1974
43.3
1974
68.7
 Others
4017
64.5
4017
49.6
4000
54.3
4000
52.8
Religion of household head
 Hindu
13,945
60.4
< 0.001
13,945
59.3
< 0.001
14,100
52.4
< 0.001
14,100
60.3
< 0.001
 Muslim
1740
69.5
1740
53.0
1754
60.8
1754
53.2
 Others
976
53.7
976
61.1
807
43.5
807
50.4
Percentage of individuals in community with no formal education
 0 to 25%
4076
62.2
0.036
4076
52.6
< 0.001
4220
53.1
0.030
4220
52.9
< 0.001
 25 to 50%
5549
61.4
5549
60.5
5602
53.4
5602
60.1
 50 to 75%
5224
59.4
5224
63.5
5160
51.3
5160
64.0
 75 to 100%
1812
61.4
1812
53.4
1679
54.9
1679
56.1
Percentage of individuals in community from poorest/poor wealth quintile
 0 to 25%
5205
67.4
< 0.001
5205
44.5
< 0.001
5476
57.5
< 0.001
5476
44.8
< 0.001
 25 to 50%
2553
64.4
2553
51.9
2637
55.0
2637
55.6
 50 to 75%
3195
57.5
3195
63.3
3237
51.5
3237
63.7
 75 to 100%
5708
55.6
5708
72.2
5311
47.8
5311
72.7
Percentage of individuals in community belonging to SC/ST caste
 0 to 25%
6835
62.6
< 0.001
6835
56.1
< 0.001
6837
53.7
< 0.001
6837
58.1
< 0.001
 25 to 50%
4443
59.2
4443
61.1
4337
52.6
4337
61.8
 50 to 75%
2663
62.7
2663
56.6
2860
54.8
2860
56.8
 75 to 100%
2720
58.2
2720
63.7
2627
48.8
2627
59.6
Place of residence
 Rural
13,223
61.5
0.003
13,223
59.2
0.012
12,904
53.8
< 0.001
12,904
59.9
< 0.001
 Urban
3438
58.8
3438
56.9
3757
49.5
3757
56.4
Country regions
 Central
4898
58.6
< 0.001
4898
71.7
< 0.001
4898
52.8
< 0.001
4898
72.4
< 0.001
 Northern
3368
83.2
3368
24.1
3368
76.8
3368
29.3
 Southern
2418
66.2
2418
38.3
2418
61.0
2418
41.1
 Western
1931
35.7
1931
76.4
1931
28.3
1931
75.5
 Eastern
3356
50.2
3356
75.3
3356
36.0
3356
74.5
 North-eastern
690
73.9
690
78.0
690
58.0
690
52.3
Overall
16,661
61.0
 
16,661
58.7
 
16,661
52.8
 
16,661
59.1
 
(a)Significance of the Chi-square (Chi2) test for association is shown using p-value
A higher percentage of individuals, who do not watch TV, consumed smokeless tobacco [62% in 2004–05 and 63% in 2011–12]. Similarly, a higher percentage of individuals who do not read newspapers consumed smokeless tobacco [60% in 2004–05 and 61% in 2011–12]. More children and youth consumed smokeless tobacco [73% in 2004–05 and 83% in 2011–12]. A higher percentage of females consumed smokeless tobacco [87% in 2004–05 and 88% in 2011–2012]. Communities with a higher proportion of poor individuals had a higher smokeless tobacco consumption. The prevalence of smokeless tobacco consumption was high among rural residents [59% in 2004–05 and 60% in 2011–12]. Smokeless tobacco consumption was highest in the western region of India [76% in 2004–05 and 76% in 2011–12].

Multivariable analysis

The fixed-effect part of Tables 3 and 4 shows the multivariable association between combustible and smokeless tobacco consumption with mass media exposure using random-intercept logistic regression models during IHDS round-I and round-II, respectively. We found that watching TV [(OR:1.03; CI:0.92–1.15) in 2004–05 and (OR:0.99; CI:0.88–1.12) in 2011–12], listening radio [(OR: 0.99; CI:0.90–1.10) in 2004–05 and (OR:1.04; CI:0.94–1.15) in 2011–12] and reading newspaper [(OR:1.02; CI:0.91–1.15) in 2004–05 and (OR:0.96; CI:0.87–1.06) in 2011–12] did not have any significant effect on consumption of combustible tobacco. Similarly, watching TV [(OR:1.02; CI:0.91–1.15) in 2004–05) and (OR:1.11; CI:0.98–1.25) in 2011–12], listening radio [(OR:0.92; CI:0.83–1.02) in 2004–05 and (OR:0.91; CI:0.82–1.02) in 2011–12] and reading newspaper [(OR:1.05; CI:0.93–1.19) in 2004–05 and (OR:1.01; CI:0.91–1.12) in 2011–12] did not have any significant effect on consumption of smokeless tobacco.
Table 3
Multivariable association between tobacco use with mass media exposure and community-level and state-level effects from random intercept logit models during IHDS round-I
 
IHDS round-I
Combustible tobacco(d)
Smokeless tobacco(e)
OR (95% CI)
OR (95% CI)
Fixed effect characteristics
Household members watch TV
  No
Ref.
Ref.
  Yes
1.03 (0.92, 1.15)
1.02 (0.91, 1.15)
Household members listen to radio
  No
Ref.
Ref.
  Yes
0.99 (0.90, 1.10)
0.92 (0.83, 1.02)
Household members read newspaper
  No
Ref.
Ref.
  Yes
1.02 (0.91, 1.15)
1.05 (0.93, 1.19)
Age group of individual
  Children and youth
Ref.
Ref.
  Adults
2.51* (2.10, 3.00)
0.40* (0.32, 0.48)
  Elderly
2.24* (1.76, 2.85)
0.48* (0.37, 0.63)
Gender of individual
  Male
Ref.
Ref.
  Female
0.059* (0.049, 0.070)
5.15* (4.25, 6.24)
Percentage of individuals in community with no formal education
  0 to 25%
Ref.
Ref.
  25 to 50%
1.01 (0.83, 1.23)
1.16 (0.93, 1.45)
  50 to 75%
0.92 (0.75, 1.14)
1.32* (1.04, 1.67)
  75 to 100%
0.95 (0.72, 1.27)
0.82 (0.60, 1.12)
Percentage of individuals in community from poorest/poor wealth quintile
  0 to 25%
Ref.
Ref.
  25 to 50%
0.90 (0.75, 1.08)
1.26* (1.03, 1.55)
  50 to 75%
0.99 (0.80, 1.23)
1.12 (0.88, 1.42)
  75 to 100%
0.91 (0.72, 1.15)
1.36* (1.05, 1.76)
Percentage of individuals in community belonging to SC/ST caste
  0 to 25%
Ref.
Ref.
  25 to 50%
0.99 (0.78, 1.25)
0.91 (0.70, 1.17)
  50 to 75%
0.81 (0.63, 1.04)
1.16 (0.88, 1.53)
  75 to 100%
0.88 (0.68, 1.15)
1.17 (0.88, 1.57)
Place of residence
  Rural
Ref.
Ref.
  Urban
0.89 (0.73, 1.07)
1.06 (0.85, 1.31)
Country regions
  Central
Ref.
Ref.
  Northern
5.39* (1.92, 15.1)
0.11* (0.03, 0.39)
  Southern
1.47 (0.48, 4.49)
0.13* (0.03, 0.48)
  Western
0.27* (0.08, 0.92)
1.06 (0.25, 4.44)
  Eastern
0.79 (0.25, 2.47)
3.39 (0.86, 13.4)
  North-eastern
2.80 (0.47, 16.8)
1.94 (0.23, 16.7)
Random effect parameters
Level 3: State
  Variance
0.634
0.925
  Intraclass Correlation Coefficient (in %)
12.20
15.59
Level 2: Community
  Variance
1.276
1.717
  Intraclass Correlation Coefficient (in %)
36.74
44.54
Likelihood ratio test
***
***
No of states
21
21
No of communities
2175
2175
No of persons
16,661
16,661
(a)OR Odds ratio, CI 95% Confidence Interval
(b)Ref. represents the reference category
(c)Statistical significance is denoted by asterisks where * indicates p-value< 0.05, *** indicates p-value< 0.0001
(d)Combustible tobacco use categorized into – No, Yes
(e)Smokeless tobacco use categorized into – No, Yes
(f)The results are adjusted for level of education, working status, marital status, household wealth quintile, caste, religion of household head
(g)Likelihood ratio test shows the significance of using a multilevel logistic model over a standard logistic model
Table 4
Multivariable association between tobacco use with mass media exposure and community-level and state-level effects from random intercept logit models during IHDS round-II
 
IHDS round-II
Combustible tobacco(d)
Smokeless tobacco(e)
OR (95% CI)
OR (95% CI)
Fixed effect characteristics
Household members watch TV
  No
Ref.
Ref.
  Yes
0.99 (0.88, 1.12)
1.11 (0.98, 1.25)
Household members listen to radio
  No
Ref.
Ref.
  Yes
1.04 (0.94, 1.15)
0.91 (0.82, 1.02)
Household members read newspaper
  No
Ref.
Ref.
  Yes
0.96 (0.87, 1.06)
1.01 (0.91, 1.12)
Age group of individual
  Children and youth
Ref.
Ref.
  Adults
3.58* (2.06, 6.22)
0.28* (0.14, 0.54)
  Elderly
3.75* (2.13, 6.59)
0.26* (0.13, 0.51)
Gender of individual
  Male
Ref.
Ref.
  Female
0.088* (0.072, 0.11)
5.29* (4.32, 6.48)
Percentage of individuals in community with no formal education
  0 to 25%
Ref.
Ref.
  25 to 50%
1.04 (0.88, 1.23)
0.85 (0.70, 1.02)
  50 to 75%
0.93 (0.77, 1.11)
1.01 (0.83, 1.24)
  75 to 100%
0.96 (0.75, 1.22)
0.91 (0.69, 1.19)
Percentage of individuals in community from poorest/poor wealth quintile
  0 to 25%
Ref.
Ref.
  25 to 50%
0.91 (0.78, 1.07)
1.26* (1.06, 1.51)
  50 to 75%
0.93 (0.78, 1.12)
0.99 (0.81, 1.21)
  75 to 100%
0.78* (0.64, 0.96)
1.13 (0.90, 1.41)
Percentage of individuals in community belonging to SC/ST caste
  0 to 25%
Ref.
Ref.
  25 to 50%
1.01 (0.83, 1.23)
1.10 (0.88, 1.37)
  50 to 75%
0.91 (0.73, 1.12)
1.18 (0.93, 1.49)
  75 to 100%
0.88 (0.70, 1.12)
1.20 (0.93, 1.56)
Place of residence
  Rural
Ref.
Ref.
  Urban
0.80* (0.68, 0.94)
1.17 (0.98, 1.40)
Country regions
  Central
Ref.
Ref.
  Northern
3.78* (1.35, 10.6)
0.17* (0.05, 0.48)
  Southern
1.28 (0.42, 3.95)
0.19* (0.06, 0.59)
  Western
0.34 (0.10, 1.14)
1.25 (0.36, 4.27)
  Eastern
0.30* (0.09, 0.96)
2.12 (0.66, 6.82)
  North-eastern
1.57 (0.25, 9.67)
0.43 (0.06, 2.69)
Random effect parameters
Level 3: State
  Variance
0.667
0.677
  Intraclass Correlation Coefficient (in %)
14.01
13.29
Level 2: Community
  Variance
0.802
1.125
  Intraclass Correlation Coefficient (in %)
30.87
35.38
Likelihood ratio test
***
***
No of states
21
21
No of communities
2175
2175
No of persons
16,661
16,661
(a)OR Odds ratio, CI 95% Confidence Interval
(b)Ref. represents the reference category
(c)Statistical significance is denoted by asterisks where * indicates p-value< 0.05, *** indicates p-value< 0.0001
(d)Combustible tobacco use categorized into – No, Yes
(e)Smokeless tobacco use categorized into – No, Yes
(f)The results are adjusted for level of education, working status, marital status, household wealth quintile, caste, religion of household head
(g)Likelihood ratio test shows the significance of using a multilevel logistic model over a standard logistic model
The random-effect part of Tables 3 and 4 provides the group-level effects (community-level and state-level variance and ICC) from the random intercept logit models during round-I and round-II. During round-I, the high community-level ICC (37% for combustible and 45% for smokeless tobacco consumption) indicates that people from the same community of the same state have a greater or lower likelihood of consumption than people from other communities of the same state (implying high correlation). Further, the high state-level ICC (12 and 16%) indicate a high correlation of combustible and smokeless tobacco consumption among individuals belonging to the same state. Similar observations can be made for round-II, where community-level ICC (31 and 35%) is high for combustible and smokeless tobacco consumption of people belonging to the same community. Moreover, the high state-level ICC (14% for combustible and 13% for smokeless tobacco consumption) indicate a high correlation of tobacco consumption among individuals belonging to the same state.

Predicted probabilities

Table 5 presents marginal predicted probabilities of combustible and smokeless tobacco use from random intercept logistic regression models calculated at the median value of relevant person-level, community-level and socioeconomic variables during IHDS round-I and round-II, respectively. The probability of combustible tobacco consumption declined among individuals who watched television [MPP: 0.835 to 0.732], listened radio [MPP: 0.833 to 0.740] and read newspaper [MPP: 0.837 to 0.724] from 2004-05 to 2011–12 respectively. However, the probability of smokeless tobacco consumption increased among individuals who watched television [MPP: 0.236 to 0.271], listened to radio [MPP: 0221 to 0.253] and read newspapers [MPP: 0.245 to 0.273] from 2004-05 to 2011–12 respectively.
Table 5
Marginal predicted probabilities of combustible and smokeless tobacco use from random intercept logistic regression models calculated at the median value of relevant person-level, community-level and socioeconomic variables during IHDS round-I and round-II, respectively
Characteristics
IHDS round-I
IHDS round-II
Combustible tobacco(b)
Smokeless tobacco(c)
Combustible tobacco(b)
Smokeless tobacco(c)
MPP
MPP
MPP
MPP
Household members watch TV
 No
0.831
0.232
0.734
0.251
 Yes
0.835
0.236
0.732
0.271
Household members listen to radio
 No
0.835
0.236
0.732
0.271
 Yes
0.833
0.221
0.740
0.253
Household members read newspaper
 No
0.835
0.236
0.732
0.271
 Yes
0.837
0.245
0.724
0.273
Age group of individual
 Children and youth
0.668
0.435
0.433
0.571
 Adults
0.835
0.236
0.732
0.271
 Elderly
0.818
0.270
0.741
0.257
Gender of individual
 Male
0.835
0.236
0.732
0.271
 Female
0.230
0.614
0.194
0.663
Level of education of individual
 No formal schooling
0.849
0.215
0.748
0.265
 1–5 years of schooling
0.835
0.236
0.732
0.271
 6–10 years of schooling
0.777
0.251
0.652
0.323
 More than 10 years of schooling
0.721
0.274
0.567
0.359
Current working status of individual
 Not working
0.835
0.224
0.706
0.235
 Working
0.835
0.236
0.732
0.271
Current marital status of individual
 Currently married
0.835
0.236
0.732
0.271
 Currently not married
0.800
0.255
0.724
0.290
Wealth quintile of household
 Poorest
0.824
0.247
0.767
0.302
 Poor
0.835
0.236
0.744
0.287
 Medium
0.805
0.267
0.732
0.271
 Rich
0.801
0.234
0.737
0.230
 Richest
0.761
0.208
0.718
0.203
Caste of household head
 Other Backward Classes
0.824
0.232
0.704
0.284
 Scheduled Castes
0.835
0.236
0.732
0.271
 Scheduled Tribes
0.806
0.243
0.725
0.263
 Others
0.799
0.251
0.672
0.301
Religion of household head
 Hindu
0.835
0.236
0.732
0.271
 Muslim
0.851
0.229
0.751
0.271
 Others
0.775
0.243
0.657
0.298
Percentage of individuals in community with no formal education
 0 to 25%
0.833
0.210
0.725
0.305
 25 to 50%
0.835
0.236
0.732
0.271
 50 to 75%
0.821
0.260
0.710
0.307
 75 to 100%
0.826
0.179
0.716
0.285
Percentage of individuals in community from poorest/poor wealth quintile
 0 to 25%
0.849
0.197
0.751
0.228
 25 to 50%
0.835
0.236
0.732
0.271
 50 to 75%
0.848
0.215
0.737
0.226
 75 to 100%
0.836
0.250
0.701
0.250
Percentage of individuals in community belonging to SC/ST caste
 0 to 25%
0.862
0.210
0.751
0.240
 25 to 50%
0.861
0.195
0.752
0.258
 50 to 75%
0.835
0.236
0.732
0.271
 75 to 100%
0.846
0.237
0.726
0.275
Place of residence
 Rural
0.835
0.236
0.732
0.271
 Urban
0.818
0.246
0.687
0.303
Country regions
 Central
0.775
0.704
0.681
0.662
 Northern
0.949
0.207
0.890
0.250
 Southern
0.835
0.236
0.732
0.271
 Western
0.481
0.716
0.421
0.710
 Eastern
0.731
0.889
0.391
0.806
 North-eastern
0.906
0.822
0.771
0.457
(a)MPP stands for marginal predicted probability
(b)Combustible tobacco use is categorized into - No, Yes
(c)Smokeless tobacco use is categorized into - No, Yes

Discussion

Using two rounds of IHDS, this panel study examined the association of combustible and smokeless tobacco consumption with mass media exposure among the Indian population considering the extent of clustering and heterogeneous risk of tobacco consumption at the state and community levels. The results revealed no significant association between mass media exposure and combustible and smokeless tobacco consumption across the two rounds. While comparing both rounds using marginal predicted probability, this study further shows a minimal change in smoking behaviour and an increment in smokeless tobacco consumption from the short-term to the long-term period after COTPA act implementation. It was worth noting that, in the short-term and long-term phase after the COTPA act implementation, exposure to television, radio and newspaper was no longer associated with tobacco consumption. These findings are similar to a 2015 Indian study that showed how strategies like banning advertisements had efficiently nullified the association between mass media exposure and tobacco consumption [40]. However, the results of this study were also contradictory with another Indian study, using 2005–06 data for 15–49 aged women and 15–54 aged men [24]. This study highlighted the association of television and radio with a higher prevalence of tobacco chewing among men and newspaper reading with a lower likelihood of smokeless tobacco consumption among women [24].
Further, the current study observed the presence of clustering among individuals and a significant level of unobserved contextual risk of combustible and smokeless tobacco at the community and state levels. Community-level clustering was more pronounced as compared to the state-level in both rounds. Although, along with the nationally-implemented acts, India had witnessed different community-level initiatives (e.g. tobacco-free village) for tobacco control [41] and the state administration partnership helping various states win the tag of “smoke-free state”. Some studies contradict such association, providing evidence of increment in tobacco use in movies to promote such behaviour among youngsters at both state and community levels [42]. India has various entertainment sources across different communities and states and diverse cultures. The content shown in such entertainment sources might be the reason for promoting combustible and smokeless tobacco in India.
This study further revealed that education among individuals and the community had helped decrease combustible tobacco consumption. Besides, the smokeless tobacco consumption had increased from the short-term to the long-term phase of COTPA act implementation, and this result was consistent with a couple of studies [24, 43]. Smoking was higher among adults, and the elderly, whereas women were inclined towards smokeless tobacco consumption, and such results are consistent with an extant Indian study [10]. The high prevalence of smokeless tobacco consumption among Indian women occurred because it was culturally acceptable among some communities [42, 43] and was readily available due to its inexpensiveness. Further, the growing campaigns [12] and efforts of the government to air anti-tobacco television ads [44] adversely affect smoking behaviour across the country, making the tobacco industry more inclined towards the marketing of smokeless tobacco and introducing it as a quick replacement for combustible tobacco.
Exposure to radio has been a common means of communication and entertainment among people for many years, unlike, television which was seen as a newcomer and yet influential to every individual’s life [45]. Radio is a means of communication available in different languages and is readily accepted by individuals irrespective of their literacy status or age. Also, radio usage are common among some communities whose individual’s sit together and usually share their experience and behaviour. In such a situation, any pro- and anti-tobacco advertisements can influence many individuals in a community. Like radio, a newspaper is also a media type commonly seen among some communities, but more than this, it is an individual choice media which is common among the literate and the higher section of society. Although radio and newspaper exposure was not associated with tobacco consumption, a higher amount of community-level clustering in tobacco consumption among the Indian population may be explained by the effect of mass media on the communities. Besides, the variation in geographic level factors was also consistent with an Indian study [14].
One of the key strengths of this study is that rather than providing any impact assessment of the COTPA act, we have tried to examine the changes from the short term to the long-term period of COTPA act implementation on the combustible and smokeless tobacco consumption behaviour among Indian population using panel data. The study provided the opportunity to understand how the growing ban of tobacco advertisements on mass media after COTPA act implementation had reduced combustible tobacco consumption but paved the way for increment in smokeless tobacco marketing due to their inexpensive and readily available nature. The study also provided significant evidence that the risk of smoking and consuming smokeless tobacco varies significantly at the community and state levels. However, the study has its shortcomings too. Although past literature had brought forward the association between tobacco use and mass media exposure before and after the COTPA act implementation, the present study could not analyze such association due to the unavailability of information in IHDS data. Moreover, the study assumed that exposure to mass media involves involuntary exposure to advertisements promoted by commercial organizations through these media. However, to verify this assumption, one needs data on the media content type that an individual is exposed to, which was not possible in this study due to a lack of data. Primary studies considering the quality of content in the mass media can be conducted to address this limitation. Lastly, this study examines the correlation between tobacco consumption and mass media exposure, and the findings do not imply causality.

Conclusion

The present study found a minimal change in the significant effect of mass media on combustible tobacco consumption among the Indian population after the COTPA act implementation. However, an increment of smokeless tobacco consumption during the two rounds, along with higher community-level clustering in tobacco consumption, had indicated the growing burden of smokeless tobacco behaviour. In terms of research implications, the findings show that mass media exposure cannot be considered as a strong predictor of combustible tobacco consumption in the Indian population. However, there is a need to view the content of media exposure as the type of content usually changes with the type of  medium. In terms of policy implications, there is a need for policy reforms to curb the significant effect of factors that promotes smokeless tobacco consumption in India, along with health warning labels on all types of tobacco to increase awareness in the individuals [46]. Moreover, clustering implies that such policies need to be implemented in specific high-risk communities from high-risk states, thereby reducing the time and cost required for implementation.

Acknowledgements

Not applicable.

Declarations

IHDS datasets used for analysis were publicly available with no information that discloses the identity of the respondents. Thus, there was no need for prior ethical approval for using the datasets. The data can be obtained from the Inter-university Consortium for Political and Social Research (ICPSR) data repository [25, 26].
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Metadaten
Titel
Association of mass media exposure with combustible and smokeless tobacco use among Indian population: findings from a panel survey
verfasst von
Ronak Paul
Rashmi Rashmi
Shobhit Srivastava
Publikationsdatum
01.12.2022
Verlag
BioMed Central
Erschienen in
BMC Public Health / Ausgabe 1/2022
Elektronische ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-021-12459-0

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