Flow diagram of house-to-house follow-up of the study participants, Mumbai Cohort Study, India.

<p>Flow diagram of house-to-house follow-up of the study participants, Mumbai Cohort Study, India.</p

Person years HRs and associated 95% CIs by sex, categories of BMI and various tobacco habits, MCS, India.

<p>Abbreviation: MCS, mumbai cohort study; TB, tuberculosis; HR, hazard ratio; CI, confidence interval; BMI, body mass index  =  weight (kg)/height (m)².</p>*<p>adjusted for age, education, religion, and mother tongue; note that all hazard ratios significantly different from the referent are denoted by the use of bold font.</p>†<p>excluding deaths occurring in the first two years to reduce effect of weight loss or smoking cessation due to symptoms of disease.</p>‡<p>includes all types of smokeless tobacco products.</p>§<p>may include smokers plus mixed (smoking and smokeless) users.</p>#<p>may include bidi plus cigarette smokers; presented only adjusted HRs.</p

Summary of Descriptive Data by gender, MCS, India.

<p>Abbreviation: MCS, mumbai cohort study; TB, tuberculosis; yr, year; BMI, body mass index  =  weight (kg)/height (m)².</p>§<p>may include smokers plus mixed (smoking and smokeless) users.</p>#<p>may include bidi plus cigarette smokers.</p

Attitudes and life skills: Comparisons of responses from 8^th grade control schools, 8^th grade intervention schools and 9^th grade intervention schools.

*<p>Response 1: I don't know; Response 2: I know.</p><p>Odds ratios adjusted for age, gender, mother's education and school.</p

Knowledge of tobacco and tobacco control legislation: Comparisons of responses from 8^th grade control schools, 8^th grade intervention schools and 9^th grade intervention schools.

*<p>Response 1: Nicotine; Response 2: Others.</p><p>Odds ratios adjusted for age, gender, mother's education and school.</p

Media use characteristics by rural/urban strata among women and men in India.

<p>Media use characteristics by rural/urban strata among women and men in India.</p

Socioeconomic, demographic, and media use characteristics by tobacco use among men in the 2005–2006 National Family Health Survey of India.

1<p>Indicates the percentage of men in the population with that particular characteristic.</p>2<p>Indicates the percentage of men with that particular socioeconomic, demographic, or media use characteristic who smoke.</p>3<p>Indicates the percentage of men with that particular socioeconomic, demographic, or media use characteristic who chew tobacco.</p

Adjusted relative risk (RR) and 95% confidence intervals (CI) for the association between media use and tobacco use among men and women in the 2005–2006 National Family Health Survey.

<p>Note: Results are mutually adjusted for the other media use variables as well as wealth, education, caste, occupation, location, religion, age, marital status, and state.</p

Geospatial Analysis on the Distributions of Tobacco Smoking and Alcohol Drinking in India

<div><p>Background</p><p>Tobacco smoking and binge alcohol drinking are two of the leading risk factors for premature mortality worldwide. In India, studies have examined the geographic distributions of tobacco smoking and alcohol drinking only at the state-level; sub-state variations and the spatial association between the two consumptions are poorly understood.</p><p>Methodology</p><p>We used data from the Special Fertility and Mortality Survey conducted in 1998 to examine the geographic distributions of tobacco smoking and alcohol drinking at the district and postal code levels. We used kriging interpolation to generate smoking and drinking distributions at the postal code level. We also examined spatial autocorrelations and identified spatial clusters of high and low prevalence of smoking and drinking. Finally, we used bivariate analyses to examine the spatial correlations between smoking and drinking, and between cigarette and bidi smoking.</p><p>Results</p><p>There was a high prevalence of any smoking in the central and northeastern states, and a high prevalence of any drinking in Himachal Pradesh, Arunachal Pradesh, and eastern Madhya Pradesh. Spatial clusters of early smoking (started smoking before age 20) were identified in the central states. Cigarette and bidi smoking showed distinctly different geographic patterns, with high levels of cigarette smoking in the northeastern states and high levels of bidi smoking in the central states. The geographic pattern of bidi smoking was similar to early smoking. Cigarette smoking was spatially associated with any drinking. Smoking prevalences in 1998 were correlated with prevalences in 2004 at the district level and 2010 at the state level.</p><p>Conclusion</p><p>These results along with earlier evidence on the complementarities between tobacco smoking and alcohol drinking suggest that local public health action on smoking might also help to reduce alcohol consumption, and vice versa. Surveys that properly represent tobacco and alcohol consumptions at the district level are recommended.</p></div

Smoking and drinking prevalence at the district and postal code levels.

<p>Prevalence at district level was age standardized using Census of India 2001 national population; prevalence at postal code level was estimated crude prevalence from kriging interpolation. State abbreviations: AP - Andhra Pradesh, AR - Arunachal Pradesh, AS - Assam, BR - Bihar, CH - Chandigarh, DD - Daman and Diu, DL - Delhi, DN - Dadra & Nagar Haveli, GA - Goa, GJ - Gujarat, HP - Himachal Pradesh, HR - Haryana, JK - Jammu & Kashmir, KA - Karnataka, KL - Kerala, MG - Meghalaya, MH - Maharashtra, MN - Manipur, MP - Madhya Pradesh, MZ - Mizoram, NL - Nagaland, OR - Orissa, PB - Punjab, PD - Pondicherry, RJ - Rajasthan, SK - Sikkim, TN - Tamil Nadu, TR - Tripura, UP - Uttar Pradesh, WB - West Bengal. <b>A.</b> Any smoking prevalence at district and postal code levels. <b>B.</b> Early smoking (before age 20) prevalence at district and postal code levels. <b>C.</b> Any drinking prevalence at district and postal code levels.</p