Developing synthetic birth cohort-specific smoking histories using Global Adult Tobacco Surveys - an example from India

Background Nearly 111 million adults smoke in India, and a tenth (nearly 1.2 million) of these die from smoking attributable diseases every year. Predicting future trends based on current prevalence and other epidemiologic variables are essential for policymaking. However, given the paucity of reli...

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Bibliographic Details
Main Authors: Deepak Sharma, Pranay Lal, Ashish Pandey
Format: Article
Language:English
Published: European Publishing 2018-03-01
Series:Tobacco Induced Diseases
Subjects:
Online Access:http://www.journalssystem.com/tid/Developing-synthetic-birth-cohort-specific-smoking-histories-using-Global-Adult-Tobacco,84336,0,2.html
Description
Summary:Background Nearly 111 million adults smoke in India, and a tenth (nearly 1.2 million) of these die from smoking attributable diseases every year. Predicting future trends based on current prevalence and other epidemiologic variables are essential for policymaking. However, given the paucity of reliable population level data, several high prevalence use countries especially in the developing world have been unable develop models that can inform policy process. We present the first such model for India based on GATS 2009 and 2017. Methods Using data from population-wide survey, we develop a synthetic cohort of smoking trends from 2010 to 2050 based on initiation, cessation, intensity, and prevalence patterns India between 2009 and 2017. Results We estimate that till 2037-2040, the number of smokers in India would be same as current rate of smoking prevalence, following which it begins to decline marginally (at about 0.8 to 1.2 percent on a year on year basis). Conclusions Policymakers need to take of this as smoking-related deaths will continue to rise beyond 2070 at current trends. This calls from stricter approaches for tobacco control in India like a "sinking lid" approach to reduce and eventually eliminate tobacco use in a given timeframe.
ISSN:1617-9625