Tobacco use and self-reported morbidity among rural Indian adults.
Aim To measure the prevalence of self-reported morbidity and its associated factors among adults (aged ⩾15 years) in a select rural Indian population.



Self-reporting of smoking has been validated as population-based surveys using self-reported data provide reasonably consistent estimates of smoking prevalence, and are generally considered to be sufficiently accurate for tracking the general pattern of morbidity associated with tobacco use in populations. However, to gauge the true disease burden using self-reported morbidity data requires cautious interpretation.



During 2010-2011, a cross-sectional survey was conducted under the banner of the Health and Demographic Surveillance System, Birbhum, an initiative of the Department of Health and Family Welfare, Government of West Bengal, India. With over 93.6% response rate from the population living in 12 300 households, this study uses the responses from 16 354 individuals: 8012 smokers, and 8333 smokeless tobacco users. Smokers and smokeless tobacco users were asked whether they have developed any morbidity symptoms due to smoking, or smokeless tobacco use. Bivariate, as well as multivariate logistic regression analyses were deployed to attain the study objective. Findings Over 20% of smokers and over 9% of smokeless tobacco users reported any morbidity. Odds ratio (OR) with 95% confidence interval (CI) estimated using logistic regression shows that women are less likely to report any morbidity attributable to smoking (OR: 0.69; CI: 0.54-0.87), and more likely to report any morbidity due to smokeless tobacco use (OR: 1.68; CI: 1.36-2.09). Non-Hindus have higher odds, whereas the wealthiest respondents have lower odds of reporting any morbidity. With a culturally appropriate intervention to change behaviour, youth (both men and women) could be targeted with comprehensive tobacco cessation assistance programmes. A focussed intervention could be designed for unprocessed tobacco users to curb hazardous effects of tobacco use.
1Research Coordinator,Society for Health and Demographic Surveillance, Suri,Birbhum,West Bengal,India.
Anamitra
A
Barik
3Senior Research Scientist,Society for Health and Demographic Surveillance, Suri,Birbhum,West Bengal,India.
Rajesh Kumar
RK
Rai
4Project Director,Society for Health and Demographic Surveillance, Suri,Birbhum,West Bengal,India.
Abhijit
A
Chowdhury
D000293:Adolescent; D000328:Adult; D000368:Aged; D015984:Causality; D015897:Comorbidity; D003371:Cough / Q000453:epidemiology*; D005260:Female; D006209:Halitosis / Q000453:epidemiology*; D006801:Humans; D007194:India / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D010146:Pain / Q000453:epidemiology*; D015995:Prevalence; D012424:Rural Population / Q000706:statistics & numerical data; D057566:Self Report; D014029:Tobacco Use Disorder / Q000453:epidemiology*; D055815:Young Adult
India; Tobacco; morbidity; non-communicable diseases; smoking