Tobacco and Alcohol Associated Mortality among Men by Socio-Economic Status in India

Mangesh S. Pednekar, Jooi Vasa, Sameer S. Narake, Dhirendra N. Sinha, Prakash C. Gupta

Healis Sekhsaria Institute for Public Health, Mahape, Navi Mumbai, IndiaIndia
School of Preventive Oncology, Patna, IndiaIndia

DOI: https://doi.org/10.17140/epoj-1-102 · Published 2016-03-07 · Licence: https://creativecommons.org/licenses/by/4.0 · © 2016 The Author(s)

Also available as PDF (figures and tables appear in the PDF).

Keywords: Alcohol; India; Mortality; Risk ratios; Smokeless tobacco; Smoking; Socioeco nomic status; Socioeco- nomic status

Introduction

Globally, tobacco kills approximately 6 million people and causes more than a trillion

dollars of economic damage each year.1 Similarly, the use of alcohol kills approximately 2.3

million people each year. More than half of these deaths occur from NCDs (Non-communica-

ble disease) including cancer, cardiovascular disease, and liver cirrhosis.2 Nearly, 80% of NCD

alcohol use together accounts for about 18% of global deaths. In addition to communicable

diseases, NCDs are becoming major threat in India for increasing the burden of diseases. Age

(per 100,000 populations) ranges from 571 among women to 782

4-11

tices prevalent in India contribute to increasing the disease burden. The mortality patterns

may also vary by Socioeconomic status (SES). The common observed association between

SES and health outcomes has been of a strong inverse relationship with those in lower SES

5-9

groups having higher mortality.5-9 Thus, examining tobacco and/

or alcohol associated mortality by SES may delineate the health

disparities that may further help to address the disparities

Using the Mumbai cohort study, we had previously

reported tobacco as an independent risk factor for deaths from

NCDs and communicable diseases. These earlier results on to-

bacco associated mortality, based on follow-up of 99,570 men

and women (age=>35 year), showed higher Hazard Ratios

(HRs) for bidi, cigarette smokers, and smokeless tobacco (SLT)

users compared to never-users.8 These HRs were adjusted for

age and education (surrogate for socioeconomic status: referred

here after as SES) but not for alcohol use (alcohol consumption

information was not available for these 99570 individuals). Al-

cohol use information however, was available for a subsequent

9-12

cohort9-12 of 34,055 men (age=>45 year) and the follow-up re-

sults from this cohort9 showed that alcohol use was associated

with excess risk for all-causes mortality [Hazard Ratio (HR)

1.22, 95% Confidence Intervals (CIs) 1.13-1.31, adjusted for

age, education, and tobacco use]. Since tobacco use and alcohol

consumption were closely associated,9-10 we now report results

on the effect of adjustment of alcohol use on HRs associated

with tobacco use. Furthermore, we are extending our findings to

examine these associations by socioeconomic differences. Ear-

lier, we had demonstrated the joint effect of tobacco and alcohol

use on all-causes mortality.9 In this paper, we present the joint

effect of tobacco (SLT use, bidi, cigarette smoking) and alcohol

use on all-causes mortality stratified by SES.

Methods

9-11

This cohort9-11 of 34,055 men (age=>45 year) was re-

cruited through house-to-house visits and face-to-face inter-

views in the city of Mumbai during 1994 to 1997. The survey

area was restricted to the main city, covering an area of around

70 sq. km. The persons were recruited from voter’s list which

provided name, age, sex, and address of all individuals 18 years

and older. Some individuals not listed on the voters’ list were

included when they insisted that they were permanent residents

(having ration card issued by the government considered as resi-

dence proof) of the place. This only formed ~5% of the sample.

Additional recruitment detail is published elsewhere.7 Verbal in-

formed consent was taken from each participant. Data analyses

plan was approved from Healis-Sekhsaria Institute for Public

Health Institutional Review Board (IRB).

Follow-Up

An active house-to house follow-up was conducted

during 1999 to 2003 for recording the participant’s vital status.

Field investigators were provided with names and addresses of

the cohort individuals and were ask to revisit each person. Deaths

recorded were then linked with the information obtained from

Mumbai (Bombay) Municipal Corporation death registers. The

causes of death information were abstracted from the Municipal

Corporation death records and an underlying cause of death was

es (ICD Version 10) guidelines. Less than 5% participants were

lost-to-follow-up, the most common reason being demolition of

their residence for re-development. Additional details regarding

the follow-up methodology and estimation of person-years of

8 7-16

follow-up have been published previously.

Measures

Tobacco use was categorized into three categories: (1)

never tobacco users (2) ever used SLT and (3) ever smoked to-

bacco (may include smokers who use smokeless tobacco as well).

Smokers were further categorized as cigarette smokers and bidi

smokers (may include bidi smokers who also use cigarette or

other smoking forms). Information regarding the frequency per

day of tobacco use was sub-divided into three groups: 1-5 times,

6-10 times and >10 times per day. Alcohol usage was categorized

as never drinkers and ever drinkers. Alcohol ever drinkers were

further categorized as country/desi drinker (brewed and distilled

locally made using fruits or grains)9 and any other type drinkers

(such as Indian Made Foreign Liquor (IMFL), beer, toddy and

9-10

spirits not presented due to smaller number in each form). IMFL

are distilled and marketed in India, which include whisky, rum,

brandy and gin. Frequency of drinking was categorized as those

who drank once a month, five or less times a month, three or less

times a week (recoded by clubbing these three categories into

one referred as less than four times a week), four to five times

a week and more than five times a week (recoded by clubbing

these two categories into one and referred as four or more times

a week).9

Socioeconomic status (SES) was defined using educa-

tion as proxy. It was broadly categorised into two groups: low

SES (included education level of illiterate, primary school-up to

5 yrs of education, and middle school-6 to 8 yrs of education)

and high SES (included education level of secondary school-9 to

12 yrs of education, and college-above 12 yrs of education).

Statistical Analysis

SPSS Version 13 (IBM, USA) was used for all analysis.

The analysis for this study was conducted in 2014. Cox propor-

tional hazards model was used to estimate tobacco associated

HRs adjusted for age, education and alcohol consumption, and

alcohol associated HRs adjusted for age, education, and tobacco

usage status. HRs for tobacco and alcohol associated all-cause

and cause-specific mortality were further stratified by SES. HRs

for joint effect of tobacco and alcohol consumption stratified by

SES were also presented. HRs for joint effect of frequency of

tobacco use and frequency of alcohol use by SES were also pre-

sented.

Results

Demographics

Table 1 presents demographics of the 34,055 men ac-

bacco users while around 30% of tobacco users were alcohol

users. Cigarette smoking was more common among high SES

(2789/4631=64%), while in contrast, SLT use (6473/10169=60%)

and bidi smoking (5479/7111=77%) was common among low

SES.

SES Differences in Mortality from Use of Tobacco

Referring to Table 2, stratification of HRs by SES for

all-cause mortality shows higher HR for high SES bidi smoker

Age group 45-49 5111

Alcohol Never 11013

Education level Higher 6377

+=may include bidi plus mixed (bidi and cigarette) smokers

Table 1. Sample characteristics of 34,055 men.

a Cause of Death

All-causes

Person year 55648 45608

Deaths(n=) 1074 1046

e HR (95% CI) 1 1.22(1.12, 1.33) 1.41(1.27, 1.57) 1.61(1.47, 1.76)

f HR (95% CI) 1 1.18(1.08, 1.28) 1.33(1.20, 1.48) 1.52(1.38, 1.67)

Percent change in HR 3.28

g

Person year 31040 17922

Deaths(n=) 541 325

h HR (95% CI) 1 1.20(1.05, 1.38) 1.32(1.14, 1.53) 2.08(1.77, 2.44)

i HR (95% CI) 1 1.18(1.03, 1.36) 1.28(1.10, 1.48) 2.01(1.71, 2.37)

Percent change in HR 1.67

g Low SES

Person year 24607 27686

Deaths(n=) 533 721

(HR=2.01) than low SES bidi smoker (HR=1.41). Additionally,

within high SES smokers, HR for bidi smokers (2.01) was high-

er than cigarette smokers (1.28), while within low SES smoker

the HRs were similar (1.40) for bidi and cigarette smokers. Bidi

smoking increased the risk of mortality from respiratory diseas-

es, TB, and neoplasm among smokers from both high as well

as low SES, while cigarette smoking increased risk of mortality

from neoplasms. SLT use increased the risk of mortality from re-

spiratory diseases and neoplasms (only high SES), and TB (only

low SES).

+ Non user Smokeless Only Cigarette Bidi

N=12144 N=10169 N=4631 N=7111

3912 1721 2615

50-54 1980 2047 863 1451

55-59 1435 1399 633 860

60-64 1325 1119 578 949

65-69 929 786 393 578

70-74 720 475 257 378

75-79 333 244 118 153

80-84 182 117 48 90

85+ 129 70 20 37

7179 2924 4516

Ever 1131 2990 1707 2595

3696 2789 1632

Lower 5767 6473 1842 5479

Never b c

Smokeless Tobacco User Smoker

Tobacco User

d Only Cigarette Bidi

21126 30449

550 915

5.67 5.29

12923 7388

268 208

3.03 3.37

8203 23060

282 707

h HR (95% CI) 1 1.27(1.13, 1.42) 1.49(1.29, 1.73) 1.51(1.35, 1.69)

i HR (95% CI) 1 1.21(1.08, 1.35) 1.40(1.21, 1.62) 1.41(1.26, 1.59)

Percent change in HR 4.72

Respiratory system diseases [J00-J99]

Deaths(n=) 70 76

e HR (95% CI) 1 1.40(1.01,1.95) 1.63(1.10, 2.43) 2.86(2.09, 3.93)

f HR (95% CI) 1 1.32(0.95,1.84) 1.49(1.00, 2.23) 2.62(1.89, 3.64)

Percent change in HR 5.71

Pneumonia [J18]

Deaths(n=) 12 20

e HR (95% CI) 1 2.44(1.18, 5.04) 1.08(0.35, 3.35) 4.51(2.14, 9.53)

f HR (95% CI) 1 2.33(1.12, 4.86) 1.00(0.32, 3.15) 4.19(1.95, 9.01)

Percent change in HR 4.51

Copd [J42-J46]

Deaths(n=) 48 51

e HR (95% CI) 1 1.31(0.88, 1.95) 1.84(1.16, 2.91) 2.73(1.87, 3.98)

f HR (95% CI) 1 1.24(0.83, 1.85) 1.71(1.07, 2.72) 2.53(1.72, 3.73)

Percent change in HR 5.34

Respiratory system diseases [J00-J99]

g

Deaths(n=) 33 27

h HR (95% CI) 1 1.78(1.07, 2.97) 1.47(0.82, 2.64) 3.20(1.77, 5.78)

i HR (95% CI) 1 1.76(1.05, 2.94) 1.41(0.77, 2.58) 3.10(1.70, 5.66)

Percent change in HR 1.12

g Low SES

Deaths(n=) 37 49

h HR (95% CI) 1 1.36(0.89, 2.09) 1.68(0.98, 2.88) 2.83(1.92, 4.18)

i HR (95% CI) 1 1.24(0.80, 1.92) 1.51(0.87, 2.61) 2.53(1.70, 3.78)

Percent change in HR 8.82

Tb [A15-A19]

Deaths(n=) 40 64

e HR (95% CI) 1 1.94(1.30, 2.90) 1.74(1.05, 2.87) 2.95(1.96, 4.45)

f HR (95% CI) 1 1.54(1.03, 2.33) 1.27(0.76, 2.13) 2.19(1.43, 3.35)

Percent change in HR 20.62

g

Deaths(n=) 22 18

h HR (95% CI) 1 1.42(0.76, 2.65) 1.43(0.72, 2.84) 4.49(2.49, 8.10)

i HR (95% CI) 1 1.16(0.61, 2.19) 1.02(0.50, 2.06) 3.31(1.79, 6.09)

Percent change in HR 18.31

g Low SES

Deaths(n=) 18 46

h HR (95% CI) 1 2.37(1.37, 4.10) 1.95(0.94, 4.07) 2.46(1.41, 4.31)

6.04 6.62

38 103

8.59 8.39

4 21

7.41 7.10

30 74

7.07 7.33

17 17

4.08 3.13

21 86

10.12 10.60

25 63

27.01 25.76

13 23

28.67 26.28

12 40

i HR (95% CI) 1 1.89(1.08, 3.31)

Percent change in HR 20.25

Neoplasms [C00-C97]

Deaths(n=) 39 53

e HR (95% CI) 1 1.88(1.24, 2.86)

f HR (95% CI) 1 1.83(1.20, 2.79)

Percent change in HR 2.66

Oral and pharynx neoplasms [C00-C14]

Deaths(n=) 1 3

e HR (95% CI) 1 3.63(0.37, 35.50) 7.89(0.82, 76.07) 22.42(2.71, 185.29)

f HR (95% CI) 1 3.23(0.33, 31.98) 6.62(0.67, 65.20) 19.46(2.31, 163.95)

Percent change in HR 11.02

Respiratory neoplasms [C30-C39]

Deaths(n=) 3 8

e HR (95% CI) 1 3.26(0.86, 12.41) 6.84(1.81, 25.90) 10.35(2.93, 36.56)

f HR (95% CI) 1 2.99(0.78, 11.49) 6.06(1.57, 23.37) 9.23(2.57, 33.14)

Percent change in HR 8.28

Neoplasms [C00-C97]

g

Deaths(n=) 18 19

h HR (95% CI) 1 2.25(1.18, 4.30)

i HR (95% CI) 1 2.26(1.18, 4.33)

Percent change in HR -0.44

g Low SES

Deaths(n=) 21 34

h HR (95% CI) 1 1.55(0.90, 2.68)

i HR (95% CI) 1 1.45(0.83, 2.53)

Percent change in HR 6.45

Circulatory system diseases [I00-I99]

Deaths(n=) 367 291

e HR (95% CI) 1 1.09(0.94, 1.28)

f HR (95% CI) 1 1.07(0.91, 1.25)

Percent change in HR 1.83

g

Deaths(n=) 199 114

h HR (95% CI) 1 1.18(0.94, 1.49)

i HR (95% CI) 1 1.19(0.94, 1.50)

Percent change in HR -0.85

g Low SES

Deaths(n=) 168 177

h HR (95% CI) 1 1.06(0.85, 1.31)

i HR (95% CI) 1 1.00(0.80, 1.24)

1.50(0.71, 3.17) 1.88(1.06, 3.36)

23.08 23.58

45 66

3.03(1.97, 4.66) 3.66(2.42, 5.54)

2.90(1.87, 4.50) 3.51(2.30, 5.36)

4.29 4.10

3 11

16.10 13.20

8 16

11.40 10.82

23 19

3.50(1.88, 6.49) 6.37(3.33, 12.21)

3.53(1.88, 6.65) 6.43(3.32, 12.45)

-0.86 -0.94

22 47

2.79(1.53, 5.08) 2.50(1.49, 4.19)

2.57(1.40, 4.74) 2.31(1.36, 3.92)

7.89 7.60

164 205

1.26(1.05, 1.52) 1.24(1.04, 1.49)

1.22(1.01, 1.48) 1.20(1.00, 1.44)

3.17 3.23

83 53

1.17(0.90, 1.51) 1.59(1.17, 2.16)

1.19(0.91, 1.55) 1.61(1.18, 2.19)

-1.71 -1.26

81 152

1.38(1.06, 1.81) 1.10(0.88, 1.38)

1.30(0.99, 1.70) 1.03(0.82, 1.30)

Percent change in HR 5.66

Digestive system diseases [K00-93]

Deaths(n=) 28 30

e HR (95% CI) 1 1.41(0.84, 2.38) 1.41(0.75, 2.65) 2.04(1.16, 3.59)

f HR (95% CI) 1 1.07(0.63, 1.84) 0.96(0.50, 1.84) 1.43(0.80, 2.57)

Percent change in HR 24.11

Liver [K70-77]

Deaths(n=) 21 22

e HR (95% CI) 1 1.34(0.73, 2.46) 1.75(0.89, 3.45) 2.43(1.31, 4.50)

f HR (95% CI) 1 0.99(0.53, 1.84) 1.14(0.56, 2.30) 1.64(0.86, 3.11)

Percent change in HR 26.12

Digestive system diseases [K00-93]

g

Deaths(n=) 21 15

h HR (95% CI) 1 1.27(0.65, 2.47) 0.81(0.35, 1.92) 1.33(0.54, 3.32)

i HR (95% CI) 1 1.00(0.51, 1.99) 0.55(0.23, 1.33) 0.95(0.37, 2.41)

Percent change in HR 21.26

g Low SES

Deaths(n=) 7 15

h HR (95% CI) 1 2.00(0.81, 4.92) 3.49(1.26, 9.68) 3.18(1.33, 7.60)

i HR (95% CI) 1 1.47(0.58, 3.69) 2.41(0.84, 6.87) 2.19(0.89, 5.41)

Percent change in HR 26.50

Others

Deaths(n=) 530 532

e HR (95% CI) 1 1.22(1.08, 1.38) 1.40(1.20, 1.62) 1.51(1.33, 1.72)

f HR (95% CI) 1 1.20(1.06, 1.35) 1.36(1.16, 1.58) 1.47(1.28, 1.68)

Percent change in HR 1.64

g

Deaths(n=) 248 132

h HR (95% CI) 1 1.08(0.87, 1.33) 1.35(1.09, 1.67) 1.99(1.56, 2.54)

i HR (95% CI) 1 1.07(0.87, 1.33) 1.34(1.07, 1.67) 1.97(1.54, 2.53)

Percent change in HR 0.93

g Low SES

Deaths(n=) 282 400

h HR (95% CI) 1 1.32(1.13, 1.54) 1.41(1.15, 1.73) 1.46(1.25, 1.71)

i HR (95% CI) 1 1.29(1.10, 1.50) 1.36(1.11, 1.68) 1.42(1.21, 1.66)

Percent change in HR 2.27

a=Coded as per ICD 10

b=only non-smoker

c=may include smokers plus mixed (smoking and smokeless tobacco) users

d=may include bidi plus mixed (bidi and cigarette) smokers

e=age and education adjusted hazard ratios (HRs) and 95% confidence intervals (CIs)

f=age, education and alcohol adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

g=low SES (those reporting education below high school) and high SES (those reporting education high school or above)

h=age adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

i=age and alcohol adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

Table 2. Hazard Ratios in tobacco users for deaths reported among 34,055 men.

5.80 6.36

15 25

31.91 29.90

14 23

34.86 32.51

7 6

32.10 28.57

8 19

30.95 31.13

263 453

2.86 2.65

125 90

0.74 1.01

138 363

3.55 2.74

by using Cox regression model

SES Differences in Mortality from Use of Alcohol

Referring to Table 3, stratification of HRs by SES for

all-cause mortality shows higher HRs for both high (1.56) and

low (1.31) SES country/desi drinkers compared to any other

type drinkers. Country/desi drinking increased the risk of mor-

tality from respiratory diseases, TB, and digestive diseases for

both high as well as low SES drinkers.

Table 4 shows joint effect of tobacco and alcohol use

stratified by SES. Exclusive drinking was associated with excess

mortality among low SES drinkers. Similarly, exclusive SLT

use was associated with excess mortality among low SES users.

While, exclusive cigarette and exclusive bidi smoking were as-

sociated with excess mortality among both low as well as high

a Cause of Death Never Alcohol User

All

Person year 114459

Deaths 2556

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Person year 52933

Deaths 999

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Low SES

Person year 61526

Deaths 1557

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Disease of respiratory [J00-J99]

Deaths 198

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Deaths 70

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

SES smokers. The HRs were higher among those who drank and

used tobacco compared to those who only drank or only used

tobacco.

Table 5 shows the joint effect of frequency of tobacco

and frequency of alcohol use stratified by SES.

Attenuation of Tobacco Hazard Ratios

Table 2 also shows the attenuation of tobacco associ-

ated HRs after adjusting for alcohol use. Among smokers and

SLT users, the attenuation in HRs was highest (>20%) for deaths

from digestive system diseases; mainly driven by deaths from

liver diseases and for deaths from tuberculosis (TB). The next

highest attenuation in HRs ranged between 10% to 20% for

Ever Alcohol user

Any type Country/desi liquor

38372 25819

1029 746

1.34(1.25, 1.44) 1.50(1.38, 1.63)

1.23(1.14, 1.33) 1.37(1.26, 1.49)

8.21 8.67

16341 7731

343 193

1.26(1.11, 1.43) 1.77(1.51, 2.06)

1.12(0.99, 1.28) 1.56(1.33, 1.84)

11.11 11.86

22031 18087

686 553

1.36(1.24, 1.49) 1.42(1.29, 1.56)

1.26(1.15, 1.38) 1.31(1.19, 1.45)

7.35 7.15

89 69

1.66(1.29, 2.14) 2.00(1.51, 2.65)

1.39(1.07, 1.81) 1.68(1.26, 2.24)

16.27 16.00

24 15

1.35(0.85, 2.15) 2.38(1.35, 4.21)

1.13(0.70, 1.84) 1.91(1.06, 3.45)

16.3 19.75

Low SES

Deaths 128

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

TB [A15-A19]

Deaths 100

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Deaths 38

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Low SES

Deaths 62

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Neoplasms [C00-C97]

Deaths 141

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Deaths 58

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Low SES

Deaths 83

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Disease of circulatory [I00-I99]

Deaths 772

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Deaths 356

65 54

1.75(1.30, 2.37) 1.96(1.42, 2.70)

1.48(1.08, 2.02) 1.66(1.19, 2.31)

15.43 15.31

92 81

2.95(2.21, 3.92) 3.91(2.89, 5.28)

2.56(1.90, 3.45) 3.38(2.47, 4.63)

13.22 13.55

38 32

3.16(2.01, 4.96) 5.78(3.59, 9.30)

2.71(1.69, 4.35) 5.03(3.02, 8.38)

14.24 12.98

54 49

2.62(1.82, 3.79) 3.04(2.08, 4.45)

2.29(1.56, 3.35) 2.64(1.78, 3.91)

12.6 13.16

62 41

1.51(1.12, 2.05) 1.65(1.15, 2.36)

1.18(0.86, 1.60) 1.28(0.89, 1.84)

21.85 22.42

21 11

1.39(0.84, 2.30) 1.90(0.99, 3.66)

0.95(0.57, 1.59) 1.24(0.64, 2.42)

31.65 34.74

41 30

1.58(1.08, 2.30) 1.53(1.01, 2.34)

1.33(0.91, 1.96) 1.30(0.84, 2.00)

15.82 15.03

255 156

1.19(1.03, 1.38) 1.22(1.02, 1.45)

1.14(0.98, 1.32) 1.16(0.97, 1.40)

4.20 4.92

93 39

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Low SES

Deaths 416

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Digestive [K00-93]

Deaths 49

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Deaths 26

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Low SES

Deaths 23

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Others

Deaths 1296

b HR (95% CI) 1

c HR (95% CI) 1

Percent change in HR

Deaths 451

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

Low SES

Deaths 845

d HR (95% CI) 1

e HR (95% CI) 1

Percent change in HR

a=Coded as per ICD 10

b=age and education adjusted hazard ratios (HRs) and confidence intervals (CIs) by using Cox model.

c=age, education and tobacco adjusted hazard ratios (HRs) and confidence intervals (CIs) by using Cox model

d= age adjusted hazard ratios (HRs) and confidence intervals (CIs) by using Cox model.

e=age and tobacco adjusted hazard ratios (HRs) and confidence intervals (CIs) by using Cox model

Table 3. Number of deaths and hazard ratios by cause of death and alcohol use among 34,055 men.

1.01(0.80, 1.27) 1.13(0.81, 1.58)

0.94(0.74, 1.19) 1.03(0.73, 1.45)

6.93 8.85

162 117

1.30(1.08, 1.56) 1.26(1.02, 1.55)

1.27(1.05, 1.54) 1.23(0.99, 1.53)

2.31 2.38

49 37

3.21(2.15, 4.78) 4.01(2.58, 6.23)

3.07(2.02, 4.68) 3.86(2.42, 6.15)

4.36 3.74

23 15

2.90(1.65, 5.09) 4.31(2.26, 8.21)

3.16(1.74, 5.71) 4.85(2.43, 9.68)

-8.97 -12.53

26 22

3.48(1.97, 6.13) 3.73(2.06, 6.76)

2.94(1.63, 5.30) 3.16(1.70, 5.84)

15.52 15.28

482 362

1.21(1.09, 1.35) 1.35(1.20, 1.52)

1.11(1.00, 1.24) 1.24(1.10, 1.40)

8.26 8.15

144 81

1.16(0.96, 1.40) 1.61(1.26, 2.04)

1.03(0.85, 1.25) 1.43(1.12, 1.84)

11.21 11.18

338 281

1.22(1.07, 1.38) 1.29(1.13, 1.48)

1.13(0.99, 1.28) 1.19(1.03, 1.37)

7.38 7.75

Alcohol use Never Smokeless Only cigarette Bidi

Never 1 1.15(1.04, 1.26) 1.36(1.20, 1.54) 1.43(1.29, 1.60)

Person year 50081 32111 13061 19206

Deaths(n=) 975 714 338 529

Ever 1.03(0.84, 1.27) 1.46(1.28, 1.65) 1.52(1.31, 1.77) 1.96(1.74, 2.21)

Person year 5567 13497 8066 11242

Deaths(n=) 99 332 212 386

g

Never 1 0.98(0.83, 1.15) 1.31(1.10, 1.57) 1.63(1.33, 1.99)

Person year 27491 12937 7845 4659

Deaths(n=) 494 220 166 119

Ever 0.81(0.60, 1.10) 1.51(1.22, 1.87) 1.34(1.08, 1.66) 2.25(1.79, 2.83)

Person year 3549 4985 5078 2729

Deaths(n=) 47 105 102 89

g Low SES

Never 1 1.26(1.11, 1.43) 1.39(1.16, 1.65) 1.41(1.23, 1.61)

Person year 22590 19174 5215 14547

Deaths(n=) 481 494 172 410

Ever 1.35(1.01, 1.80) 1.44(1.23, 1.69) 1.72(1.39, 2.11) 1.91(1.65, 2.21)

Person year 2018 8512 2988 8513

Deaths(n=) 52 227 110 297

b=only non-smoker

c=may include smokers plus mixed (smoking and smokeless tobacco) users

d=may include bidi plus mixed (bidi and cigarette) smokers

e=age and education adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

g=low SES (those reporting education below high school) and high SES (those reporting education

h=age adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

Table 4. Hazard Ratios in tobacco and alcohol users for deaths among 34,055 men.

deaths from oral pharynx and respiratory neoplasm.

Discussion

It is well known in India (and in Mumbai) that bidi

smoking is more prevalent among individuals in low SES and

cigarette smoking among high SES.4-7 The HRs in this study

however, were higher among high SES bidi smokers and low

SES cigarette smokers than their corresponding SES counter-

part. Similarly, country/desi drinking was more prevalent in this

study among individuals in low SES but higher HRs were ob-

e HRs (95% CIs)

Tobacco use

c Smoker

b d

h HRs(95% CIs)

high school or above)

association of SES with risk factors (tobacco and alcohol use)

in terms of prevalence and in terms of mortality risk needs ad-

ditional cohort studies from other locations.

A general perspective is that risky behaviors such as

smoking and alcohol consumption are more prevalent in lower

4-7

SES groups, therefore population attributable risks are expected

to be higher in low SES groups.17 At present, a lot of research

exists for explaining socioeconomic differences for tobacco use

4-5,18-19 6-7

within India including Mumbai with higher prevalence

of smoking and smokeless forms among lower SES groups.

Never user 1

b Smokeless

Frequency per day 1.16(1.03, 1.30)

1 to 5

6 to 10 1.08(0.91, 1.29)

>10 1.18(0.91, 1.54)

c Smoker

Only cigarette

Frequency per day

1 to 5

6 to 10 1.39(1.14, 1.69)

>10 1.41(1.17, 1.70)

d Bidi

Frequency per day

1 to 5

6 to 10 1.46(1.19, 1.79)

>10 1.55(1.36, 1.76)

g

Never user 1

b Smokeless

Frequency per day 1.04(0.85, 1.27)

1 to 5

6 to 10 1.07(0.79, 1.46)

>10 1.12(0.69, 1.82)

c Smoker

Only cigarette

Frequency per day

1 to 5

6 to 10 1.06(0.78, 1.44)

>10 1.58(1.22, 2.03)

d Bidi

Frequency per day

1 to 5

6 to 10 1.04(0.62, 1.73)

>10 2.13(1.69, 2.69)

g Low SES

Never user 1

b Smokeless

Frequency per day

1 to 5 1.28(1.11, 1.48)

6 to 10 1.13(0.91, 1.40)

>10 1.20(0.88, 1.65)

c Smoker

Only cigarette

Alcohol use frequency

Never user <4 times a week >=4 times a week

0.94(0.70, 1.25) 1.16(0.87, 1.54)

1.12(0.85, 1.47) 1.84(1.55, 2.19)

1.18(0.80, 1.75) 1.31(0.96, 1.81)

0.99(0.49, 1.99) 1.92(1.35, 2.72)

1.28(1.04, 1.56) 0.75(0.45, 1.26) 1.52(1.11, 2.07)

1.30(0.85, 1.98) 1.55(1.12, 2.13)

1.63(1.15, 2.33) 2.04(1.58, 2.63)

1.25(0.99, 1.58) 1.03(0.57, 1.88) 1.94(1.37, 2.73)

1.67(1.17, 2.40) 2.16(1.61, 2.90)

1.54(1.17, 2.02) 2.40(2.06, 2.80)

0.75(0.51, 1.09) 0.80(0.50, 1.28)

1.48(0.99, 2.20) 2.04(1.48, 2.82)

1.41(0.73, 2.72) 1.26(0.63, 2.54)

0.55(0.14, 2.20) 3.81(2.03, 7.16)

1.24(0.93, 1.64) 0.37(0.15, 0.90) 1.36(0.84, 2.22)

0.99(0.54, 1.80) 1.21(0.73, 2.03)

1.42(0.91, 2.22) 2.00(1.41, 2.84)

1.60(1.02, 2.51) 1.47(0.55, 3.94) 2.58(1.33, 5.00)

2.29(1.08, 4.83) 1.98(1.02, 3.83)

2.18(1.32, 3.59) 2.71(1.99, 3.70)

1.23(0.78, 1.95) 1.52(1.07, 2.17)

0.95(0.65, 1.38) 1.84(1.49, 2.27)

1.09(0.67, 1.77) 1.36(0.95, 1.95)

1.30(0.58, 2.91) 1.61(1.06, 2.45)

Frequency per day

1 to 5

6 to 10 1.75(1.34, 2.28)

>10 1.24(0.94, 1.64)

d Bidi

Frequency per day

1 to 5

6 to 10 1.57(1.25, 1.98)

>10 1.40(1.21, 1.63)

b=only non-smoker

c=may include smokers plus mixed (smoking and smokeless tobacco) users

d=may include bidi plus mixed (bidi and cigarette) smokers

e=age and education adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

g=low SES (those reporting education below high school) and high SES (those reporting education high school or above)

h=age adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox regression model

Table 5. Hazard Ratios and 95% confidence intervals for frequency of tobacco and frequency of alcohol use for deaths among 34,055 men.

with only one study showing cancer mortality being higher

among men with no formal education adjusting for ever-chew-

ing of tobacco. The higher HRs observed in this study for high

SES ‘country/desi’ drinkers counters study findings from other

countries showing individuals of lower educational status hav-

ing higher alcohol-attributable mortality compared to those with

21-23

higher education. Thus the higher HRs among high SES bidi

smokers and high SES ‘country/desi’ drinkers, deviates from

widespread notion that higher risks or mortality are seen among

12-13,15-17

lower SES groups, requires further examination. Given

these examples, though this data is limited to one study area and

does not provide a complete socioeconomic picture of India, the

results pose importance of examining for socioeconomic differ-

ences. Additionally, findings from this study reiterate the need

for further research into risks and mortality outcomes for bidi

smokers.

Although, this study shows the increase in the risk of

all-cause mortality due to tobacco use (in smoking or SLT form)

was attenuated minimally after adjusting for alcohol use. For

alcohol associated diseases, such as TB and digestive system

diseases (mainly liver diseases) the attenuation was over 20%

among SLT users, cigarette and bidi smokers.

The attenuation in the excess risk of mortality for liver

diseases among smokers (mainly bidi smokers) and SLT users is

consistent with the well-established finding of alcohol intake af-

fecting the liver. However, it may be pointed out that the smok-

ing association with liver diseases [OR=1.6, 95% CI (1.4–1.9)]

remained unchanged even after adjusting for alcohol use in a na-

tionally representative case-control study from India.24 Howev-

er, these results were neither stratified nor adjusted for SLT use

and the liver disease category included causes such as cirrhosis,

hepatitis, jaundice, ascites, alcoholism, and alcohol poisoning.

So there are few inconsistencies within and between countries

but the IARC evaluated the evidence for relationship between

smoking and liver cancer and found to be sufficient after adjust-

ing for potential confounders.25

The high risk of all-cause and various specific causes

1.28(0.96, 1.70) 1.46(0.78, 2.73) 1.65(1.09, 2.49)

1.65(0.91, 3.01) 1.88(1.24, 2.84)

1.83(1.03, 3.25) 1.98(1.36, 2.89)

1.13(0.85, 1.49) 0.87(0.41, 1.84) 1.73(1.16, 2.59)

1.47(0.97, 2.22) 2.22(1.59, 3.09)

1.32(0.96, 1.83) 2.27(1.90, 2.72)

of mortality after adjustment for alcohol consumption among

smokers observed in this study is consistent with findings from

24,26 27

other studies within India and a study from China. Higher

HRs among bidi smokers than cigarette smokers for all-cause

and for specific causes of death reconfirm bidi smoking being

8,28

as harmful as cigarette smoking.8,28 This finding has important

public health implication in India because about 90% of alcohol

drinkers are tobacco users (Table 1) and 66% of smokers are bidi

smokers.4 These results suggest for giving similar priority to bidi

smoking and its health effects in addition to cigarette smoking.

This current study also supports the conclusion made by Thun et

al29 that after adjusting for age, further adjustment for behavioral

and socioeconomic differences between smokers and non-smok-

ers minimally affects the risk estimates associated with smoking.

For SLT users, the high risk of all-cause mortality af-

ter adjusting for alcohol use observed in this study is consis-

tent with findings reported from two cohorts from USA30 but

is little different from Trivandrum (India) cohort fndings.26 For

specific causes, such as cancer, the increase in risk observed in

our study was similar to other studies within India26 and outside

India.30 While, for most other causes (such as respiratory, cir-

culatory and digestive system diseases) our findings were little

different.30 Additionally, inconsistencies were also reported for

SLT use between cohorts within country. These inconsistent as-

sociations of SLT use with all-causes and various specific causes

within and between countries probably point out towards more

complex nature of SLT products used in different countries and

their systemic effect. To further delineate alcohol adjusted SLT

and mortality association, there is a need for undertaking mul-

ticentre prospective studies in countries where SLT and alcohol

use are prevalent.

There are a few limitations with this study. The sample

is not representative of the population as individuals residing in

upper-middle-class and upper-class housing were excluded. This

exclusion was purposive due to reasons of it being difficult to

approach because of security constraints and lack of cooperation

from the individuals. Hence, these results may not apply to this

division of society. This may partially explain the results that we

are seeing with this study. Stratifying the analysis by socioeco-

nomic status, namely education, as high education and low edu-

cation, the high SES individuals in this sample are different from

the affluent group (upper-middle-class and upper-class). These

high SES individuals may still have lower education and lower

income compared to those affluent individuals and therefore we

observe such findings from this study of higher HRs among high

SES bidi smokers and high SES country/desi drinkers. Addition-

ally, these high SES individuals might have some competing risk

factors which is not known and not measured which possibly

needs to be further explored. In relation to this, this study is lim-

ited to city of Mumbai, thus the results may be varied in other

cities or areas within India, for which further research is neces-

sary. Finally, this study reports results only for men. Although

women in India do not smoke very much (~3%) but they do

report the use of SLT (~18%). However, alcohol drinking among

women is not expected to be major confounder for tobacco as-

sociated mortality because the prevalence of alcohol use among

women in India is rather low (~2%).31

Conclusion

This study demonstrates the prominent role of SES in

explaining mortality differences for risks from bidi smoking and

‘country/desi’ drinking for which multicentre additional studies

are required. In addition to focusing on smoking forms of tobac-

co use, our study findings highlight the importance of estimating

alcohol adjusted risk estimates for SLT users. Furthermore, the

findings underscore the important role of alcohol use in tobacco

associated mortality for causes such as TB and digestive dis-

eases (mainly liver diseases).

Acknowledgements

Authors acknowledge the technical support from the South East

Asia Office of the World Health Organisation. The authors also

wish to acknowledge the co-operation of the Municipal Corpo-

ration of Greater Mumbai (BMC) in providing access to cause

of death information and would also like to thank the entire field

and study team for their valuable contribution to the study.

Author’S Contribution

Conceived and designed experiment: MSP. Analysed the data:

MSP, PCG, SSN. Wrote the paper: MSP, PCG, DNS, JV. Su-

pervised the field work: MSP. Oversaw the data management,

the statistical procedures and tests: MSP. Interpreted the results:

MSP, PCG, DNS, SSN. Conducted the literature search and in-

teracted with co-authors in subsequent drafts of the paper: MSP,

JV.

Conflicts Of Interest

We do not have any conflict of interest.

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