Tobacco use in LMICs Leading preventable cause of death worldwide Death toll will rise from 5 million per year to 8 million per year 200 million smokeless.

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Tobacco use in LMICs Leading preventable cause of death worldwide Death toll will rise from 5 million per year to 8 million per year 200 million smokeless tobacco (SLT) users in Bangladesh and India 2 World Health Organization WHO Report on the Global Tobacco Epidemic: the MPOWER package. Geneva, Switzerland: World Health Organization, 2008 Global Adult Tobacco Survey (GATS) India Report Global Adult Tobacco Survey (GATS) Bangladesh Report 2009.

Pan Smokeless tobacco in India and Bangladesh. 3

Pan masala Gutkha Mawa 4

Health effects Smokeless tobacco causes adverse health effects, including: 5 Gupta PC & Ray CS. Smokeless tobacco and health in India and South Asia. Respirology. 2003;8(4): ; Mushtaq N, Beebe LA, Thompson DM, Skaggs VJ. Smokeless tobacco and prevalence of cardiovascular disease. Journal of the Oklahoma State Medical Association. 2010;103(11- 12): ; International Agency for Research on Cancer: IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans. Vol. 85. Betel-quid and Areca-nut Chewing; and some Areca-Nut-Derived Nitrosamines. Lyon, France ; Gupta PC, Pednekar MS, Parkin DM, Sankaranarayanan R. A cohort study of 99,570 individuals in Mumbai, India for tobacco-associated mortality. International Journal of Epidemiology. 2005;34(6): Oral cancer Mouth disease Heart disease Addiction Reproductive health problems

Smokeless tobacco policies Bangladesh No health warnings India Health warnings Gutka banned in 33 states and union territories 6

7

Rationale 8 Little evidence to guide policy makers. Graphic pictures of disease may violate cultural norms. The current study was among the first to test text and pictorial health warning labels for smokeless tobacco packages in India and Bangladesh. Hammond D. Health warning messages on tobacco packages: a review. Tobacco Control. 2011; doi: /tc ; BRC Marketing and Social Research. Smoking health earnings study: Optimizing smoking health warnings—Stage 2 text graphics, size and color testing. Wellington, NZ: Ministry of Health; 2004.

1.Do different executional styles enhance perceived effectiveness of health warnings? 2. What role do individual-level factors play in perceived effectiveness of health warnings? Does country influence perceived effectiveness? 3. How do perceptions of current Indian warnings compare to the previous warning? Research Questions 9

10 Methodology Face-to-face interviews Between subjects experiment 4 warning label conditions: 1) text, 2) symbolic, 3) graphic, 4) testimonial

Protocol 1. Screening -age, gender, SLT use (for adults) 2. Background items 3. Random assignment to experimental conditions 4. Viewing and rating warning labels 5. Post-experimental measures Methodology 11

TextSymbolicGraphicTestimonial Oral cancer Mouth disease Heart disease Addiction Death Experimental Conditions Health effects

Condition #1: Text-only 13

Condition #2: Symbolic imagery 14

Condition #3: Graphic health effects 15

Condition #4: Personal Testimonial 16

Translation EnglishHindi Marathi Bengali 17

Label ratings: Perceived effectiveness 18 Overall, on a scale of 1 to 10, how effective is this health warning Not at all In the Middle Extremely

Health effects: ranking task 19

TextSymbolicGraphicTestimonial Oral cancer Mouth disease Heart disease Addiction Death 20 Experimental Conditions Health effects

Results 21

Results 22 BANGLADESHINDIA Adults (n=569) Youth (n=512) Adults (n=502) Youth (n=500) Gender Female45.9% (261)49.6% (254)49.8% (250)50.0% (250) Male54.1% (308)50.4% (258)50.2% (252)50.0% (250) Age mean years (SD)38.6 (12.5)17.1 (0.8)36.0 (9.2)17.5 (0.7) Smokeless tobacco use Daily94.4% (537)14.5% (74)93.6% (470)29.0% (145) Non-daily5.6% (32)11.7% (60)6.4% (32)5.8% (29) Non-user susceptible--15.4% (79)--21.2% (106) Non-user non- susceptible % (299)--44.0% (220)

Age Gender Smokeless tobacco use Experimental condition Interaction term: Country by experimental condition Analyses Linear regression models adjusting for: 23

TextSymbolicGraphicTestimonial Oral cancer Mouth disease Heart disease Addiction Death Experimental Conditions Health effects Perceived effectiveness by experimental condition

Perceived effectiveness by theme Compared to text-only warnings, all other pictorial warnings were rated as more effective. (p<.001) Vs. Text-based Graphic health effects Personal testimonials Symbolic imagery β=.36 β=2.39 β=1.88

26 Perceived effectiveness by theme Compared to symbolic warnings, warnings with graphic health effects and personal testimonials were rated as more effective. (p<.001) Vs. Graphic health effects Personal testimonials Symbolic imagery β=2.03 β=1.52

27 Personal testimonials Graphic health effects Vs. Perceived effectiveness by theme Compared to personal testimonial warnings, warnings with graphic health effects were rated as more effective. (p<.001) β=0.50

Adults gave higher ratings than youth (p=.002). Females gave higher ratings than males (p=.02). No differences found between SLT users and non-users. No differences for country by condition interaction. 28 Individual-level factors

TextSymbolicGraphicTestimonial Oral cancer Mouth disease Heart disease Addiction Death 29 Health warnings ranking task

30 Mouth disease Heart disease Addiction Death Oral cancer Symbolic Testimonial TextGraphic Ranking task Most effective

31 Mouth disease Heart disease Addiction Oral cancer Mean ranking 1.3 (SD 0.7)Mean ranking 1.6 (SD 0.8) Mean ranking 1.4 (SD 0.9) Mean ranking 1.3 (SD 0.7)

32 Mouth disease Heart disease Addiction Death Oral cancer Symbolic Testimonial TextGraphic Ranking task Most effective

33 Ranking task Most effective Mean ranking 1.6 (SD 0.8)Mean ranking 2.2 (SD 0.9)

34 Current round of Indian warning labels Adults (n=499) 4.5 (1.1)3.0 (1.3)2.7 (1.2)2.6 (1.2)2.2 (1.2) Youth (n=497) 4.5 (1.1)3.0 (1.2)2.7 (1.2)2.5 (1.2)2.3 (1.3) Mean rank* (SD) of current round of Indian health warnings *Lower numbers associated with higher levels of perceived effectiveness

35 Conclusions Pictorial smokeless tobacco warnings more effective than text-only. Graphic health effects may have the greatest impact overall. Same pattern of findings for both India and Bangladesh. Consistent with research from high-income countries on cigarette warnings.

David Hammond PhD University of Waterloo, Canada Seema Mutti PhD candidate University of Waterloo, Canada Nigar Nargis PhD University of Dhaka, Bangladesh Jessica L. Reid MSc University of Waterloo, Canada Ghulam Hussain PhD candidate University of Dhaka, Bangladesh Mangesh Pednekar PhD Healis-Institute, Navi Mumbai, India Guari Dhumal MSc Healis-Institute, Navi Mumbai, India Geoffrey T. Fong PhD University of Waterloo, Canada James F. Thrasher PhD University of South Carolina, USA 36 Acknowledgements & Funding