the history and epidemiology of cigarette smoking--briefly kenneth a. perkins, ph.d., professor of...
TRANSCRIPT
The history and epidemiology of
cigarette smoking--briefly
Kenneth A. Perkins, Ph.D.,Professor of Psychiatry
Historical Factors Increasing Cigarette Smoking
1850s Invention of the safety match--portable lighting device that enabled one to smoke almost anywhere.
Late 1800s Development of tobacco “blends”--reduced harshness of smoking.
1880s Invention of cigarette rolling machine--greatly increased supply and drove down cost of
cigarettes, which were previously made by hand.
Early 1900s Modern marketing strategies--increased demandfor cigarettes.
from Kluger R (1996) Ashes to ashes. New York: Knopf.
Note that cigarettes are a highly engineered product continually being refined to enhance “acceptability” to smokers (e.g. ammonia to increase nicotine uptake, flavorings like cocoa, menthol).
Per Capita Cigarette Consumption--U.S.
0
5001000
1500
20002500
3000
3500
40004500
5000
Year
Cig
are
ttes
World War I
Great Depression
End ofWWII
1stSmoking-CancerConcern
1st SurgeonGeneral's
Report BroadcastAd Ban
Nonsmokers'Rights
MovementBegins
Federal Cigarette
TaxDoubles
FairnessDoctrine
Messages onTV and Radio
Tobacco Execs testify in Congress
Cigarettes were 2% of all tobacco intake in 1900; 80% in 1963
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990
Decreases in Smoking by Education
1980 1990 200019650
5
10
15
20
25
30
35
40
45
50
SM
OK
ING
PR
EV
ALE
NC
E
HighSchoolgrad
Collegegrad
Trend in Quitting by Age
20001990198019650
10
20
30
40
50
60
70
80
90
EV
ER
SM
OK
ER
S W
HO
QU
IT (
%)
under 25
25-44
45-64
over 65
Prevalence has dropped by half since 1964: 42% to 21%. Men: 52% to 23%Women: 34% to 19% “Heavy” smoking (>25/day) has dropped from 29% of all smokers in 1980 to 12% in 2004.
Top: Drop in prevalence is much greater with higher education.
Bottom: Quitting has increased in all age groups, but less so for younger versus older smokers.
From Giovino et al. (2002).
Recent trends in smoking prevalence and quitting
Characteristics of current
smokersCurrent smoking is associated with poverty and low education.
Men: little difference by ethnicity except higher in Native American.
Women: lower prevalence in non-White ethnicities except Native Am.
Comorbidity of smoking and psychiatric or substance abuse
problemsSmoking prevalence is higher in those with psychiatric or substance abuse problems (“hardening”?)
Depression history: 30-50%Schizophrenia: 70%PTSD: 40-50%ADHD: elevated but little prevalence dataAlcohol dependence: 80-90%Cocaine dependence: 80%Opiate dependence: 90%
Cotinine
0.4 1.10.70
50
100
150
200
250
300
BRAND NICOTINE "YIELD"
CO
TIN
INE
(n
g/m
l)
Carbon Monoxide
0.4 1.10.70
10
20
30
40
BRAND NICOTINE "YIELD"
CA
RB
ON
MO
NO
XID
E
(pp
m)
Cigarettes Per Day
0.4 1.10.70
10
20
30
BRAND NICOTINE "YIELD"
CIG
AR
ET
TE
S P
ER
DA
Y
Smoking behavior and smoke exposure after switching to “light” brands (i.e. those with lower nicotine “yields”).
Ninety percent of commercial brands have yields within the range of yields across these brands, 0.4-1.1 mg nicotine.
Adapted from Zacny & Stitzer (1988).
“Lights” do not reduce exposure or risk
“Occasional” smokersPrevalence of non-daily smoking is increasing, as overall prevalence of daily smoking is decreasing . Non-daily are 20% of all smokers.
Characteristics more common in non-daily (“some day”) vs daily smoking:
Younger age
Non-white ethnicity
Higher education
Higher income
Hassmiller et al. (2003) AJPH, 93: 1321-7.
Population Exposure to Drugs (U.S.)
HeroinStimulantsTobacco CocaineCannabisAlcohol0
20
40
60
80
100
DRUG
EV
ER
US
ED
DR
UG
S (
%)
Rate of Dependence Among Ever Users
HeroinStimulantsTobacco CocaineCannabisAlcohol0
5
10
15
20
25
30
35
DRUG
DE
PE
ND
EN
CE
RA
TE
(%
)
Top: Percentage of the U.S. population ever using various drugs of abuse at least once. Bottom: Percentage of those ever using a drug who become dependent on that drug.
Note that, although only a minority of ever users become dependent, the risk of dependence is highest among those ever using tobacco and exceeds even those for cocaine and heroin. Data from Anthony et al. (1994).
What accounts for high rates of dependence on tobacco smoking?
Smoking (<60 sec)
Gum/“Inhaler” (20 min)
IV (1-2 min)
Patch (hrs)
Nasal spray (5 min)
Time to peak arterial concentration
INSERT FIG SHOWING KINETICS OF CIGS AND NRT, to illustrate why NRT might not work that well
Predictors of Sustained Abstinence
• Fewer cigs/day• Fewer years/smoking• Longer duration of prior
abstinence• Older age at initiation• Ever quit before• Fewer lapses during
current quit attempt• No comorbid conditions
(Ockene et al. 2000, Health Psychology)(Ockene et al. 2000, Health Psychology)
Hymowitz N et al. (1997) Tobacco Control 6(suppl 2): S57-S62.
Any smoking at all on or after quit day strongly predicts failure
Perkins et al. (2001) Journal of Consulting & Clin Psychol 69: 604-613.
Reach for a Lucky…
Women and Smoking: A Report of the Surgeon General. Washington, DC: US Dept of Health and Human Services, Public Health Service, Office of the Surgeon General; 2001.
Lung Cancer Risk
International Early Lung Cancer Action Program Investigators (2006) Women's Susceptibility to Tobacco Carcinogens and Survival After Diagnosis of Lung CancerJAMA. 296:180-184.
Table 2. Logistic Regression Analysis of 14 435 Baseline Screenings for Lung Cancer, Prevalence Odds Ratio, Women vs Men by Controlled Covariates
Odds Ratio (CI) P Value†
None 1.6 (1.2-2.0) .002
Age and smoking 1.7 (1.3-2.3) .001
†Two-sided.
Dransfield MT, Davis JJ, Gerald LB, et al. (2006) Racial and gender differences in susceptibility to tobacco smoke among patients with chronic obstructive pulmonary disease. RESPIRATORY MEDICINE 100: 1110-1116
N=330 smokers over 45 years old
Figure 2. Susceptibility Indices (SI). The SI represents the change in lung function (race-adjusted % predicted FEV1) per pack-year smoked as calculated by the formula (%FEV1-100%)/pack-years. *Caucasians lost lung function at a slower rate than did African-Americans (p<.01) as did †men compared to women (p=.001).
Lung function: COPD
Relative risk of myocardial infarction for current
smokers compared with never smokers, by sex
Prescott et al. (1998) Smoking and risk of myocardial infarction in women and men: longitudinal population study. Brit Med J 316:
1043-1047
Women
Men
CV risk due to smoking in F vs M
-------------------------------------------
Quit ratio (former/ever) in men vs women
Smoking and Tobacco Control Monographs, Monograph 12: Population Based Smoking Cessation (2000)
1995-96 data (18 and older)
Current Former Quit Ratio
Men: 25.66% 25.80% 50.14%
Women: 20.73% 18.07% 46.56%
Adapted from Wetter DW et al. (1999) Gender differences in smoking
cessation. Journal of Consulting and Clinical Psychology, 67:555-562
0
10
20
30
40%
Abs
tinen
t
Men Women
NIC patch
placebo
(N=632)
Nicotine patch outcome at 6 months, by sex
Review: New reviewComparison: 01 ORs, ala munafo Outcome: 01 InterORS
Study InterORS (fixed) Weight InterORS (fixed)or sub-category log[InterORS] (SE) 95% CI % 95% CI
01 Munafo reproducedabelin 0.4700 (0.8370) 0.88 1.60 [0.31, 8.25] ehrsam 0.1740 (1.6190) 0.24 1.19 [0.05, 28.42] tonnesen -1.6090 (1.3390) 0.34 0.20 [0.01, 2.76] sachs 0.7610 (0.7520) 1.09 2.14 [0.49, 9.35] richmond -0.0300 (0.6340) 1.54 0.97 [0.28, 3.36] yudkin -0.0510 (0.3800) 4.28 0.95 [0.45, 2.00] paoletti 0.7320 (0.7480) 1.10 2.08 [0.48, 9.01] killen 0.8500 (0.6940) 1.28 2.34 [0.60, 9.12] lewis 1.3960 (1.5330) 0.26 4.04 [0.20, 81.50] hughes 1.1120 (0.6750) 1.36 3.04 [0.81, 11.42] jorenby 0.2390 (0.5180) 2.30 1.27 [0.46, 3.51]
Subtotal (95% CI) 14.68 1.39 [0.93, 2.07]Test for heterogeneity: Chi² = 6.50, df = 10 (P = 0.77), I² = 0%Test for overall effect: Z = 1.59 (P = 0.11)
02 Munafo reprod. + wetter & davisabelin 0.4700 (0.8370) 0.88 1.60 [0.31, 8.25] ehrsam 0.1740 (1.6190) 0.24 1.19 [0.05, 28.42] tonnesen -1.6090 (1.3390) 0.34 0.20 [0.01, 2.76] sachs 0.7610 (0.7520) 1.09 2.14 [0.49, 9.35] davis 0.6090 (0.6640) 1.40 1.84 [0.50, 6.76] richmond -0.0300 (0.6340) 1.54 0.97 [0.28, 3.36] yudkin -0.0510 (0.3800) 4.28 0.95 [0.45, 2.00] paoletti 0.7320 (0.7480) 1.10 2.08 [0.48, 9.01] killen 0.8500 (0.6940) 1.28 2.34 [0.60, 9.12] lewis 1.3960 (1.5330) 0.26 4.04 [0.20, 81.50] hughes 1.1120 (0.6750) 1.36 3.04 [0.81, 11.42] jorenby 0.2390 (0.5180) 2.30 1.27 [0.46, 3.51] wetter 0.2500 (0.4490) 3.07 1.28 [0.53, 3.10]
Subtotal (95% CI) 19.15 1.40 [0.98, 1.99]Test for heterogeneity: Chi² = 6.70, df = 12 (P = 0.88), I² = 0%Test for overall effect: Z = 1.86 (P = 0.06)
03 munafo meta + davis + wetterdavis 0.6090 (0.6640) 1.40 1.84 [0.50, 6.76] wetter 0.2500 (0.4490) 3.07 1.28 [0.53, 3.10] munafometa 0.2850 (0.1930) 16.59 1.33 [0.91, 1.94]
Subtotal (95% CI) 21.06 1.35 [0.97, 1.89]Test for heterogeneity: Chi² = 0.23, df = 2 (P = 0.89), I² = 0%Test for overall effect: Z = 1.76 (P = 0.08)
04 Munafo reprod. + wetter & davis & shiffmanabelin 0.4700 (0.8370) 0.88 1.60 [0.31, 8.25] ehrsam 0.1740 (1.6190) 0.24 1.19 [0.05, 28.42] tonnesen -1.6090 (1.3390) 0.34 0.20 [0.01, 2.76] sachs 0.7610 (0.7520) 1.09 2.14 [0.49, 9.35] davis 0.6090 (0.6640) 1.40 1.84 [0.50, 6.76] richmond -0.0300 (0.6340) 1.54 0.97 [0.28, 3.36] yudkin -0.0510 (0.3800) 4.28 0.95 [0.45, 2.00] paoletti 0.7320 (0.7480) 1.10 2.08 [0.48, 9.01] killen 0.8500 (0.6940) 1.28 2.34 [0.60, 9.12] lewis 1.3960 (1.5330) 0.26 4.04 [0.20, 81.50] hughes 1.1120 (0.6750) 1.36 3.04 [0.81, 11.42] jorenby 0.2390 (0.5180) 2.30 1.27 [0.46, 3.51] wetter 0.2500 (0.4490) 3.07 1.28 [0.53, 3.10] shiffman 0.6450 (0.5020) 2.45 1.91 [0.71, 5.10]
Subtotal (95% CI) 21.60 1.45 [1.04, 2.02]Test for heterogeneity: Chi² = 7.04, df = 13 (P = 0.90), I² = 0%Test for overall effect: Z = 2.19 (P = 0.03)
05 munafo meta + davis + wetter + shiffmandavis 0.6090 (0.6640) 1.40 1.84 [0.50, 6.76] wetter 0.2500 (0.4490) 3.07 1.28 [0.53, 3.10] munafometa 0.2850 (0.1930) 16.59 1.33 [0.91, 1.94] shiffman 0.6450 (0.5020) 2.45 1.91 [0.71, 5.10]
Subtotal (95% CI) 23.51 1.40 [1.02, 1.93]Test for heterogeneity: Chi² = 0.65, df = 3 (P = 0.88), I² = 0%Test for overall effect: Z = 2.08 (P = 0.04)
Total (95% CI) 100.00 1.40 [1.20, 1.63]Test for heterogeneity: Chi² = 21.22, df = 44 (P = 1.00), I² = 0%Test for overall effect: Z = 4.26 (P < 0.0001)
0.001 0.01 0.1 1 10 100 1000
Favours treatment Favours control
Update of Munafo et al (2004) meta-analysis of 11 NRT patch trials, adding 3 more trials: Women do significantly worse on NRT patch (OR of 1.45, p=.03)
Study log [OR] (SE) OR CI weight OR (95% CI)
See Perkins & Scott (2005) Nic Tob Res 7:915-916; Munafo et al. (2004)Nic Tob Res 6: 769-776 and 865-867.
Update of Munafo et al (2004)
Bupropion meta-analysis
Scharf & Shiffman (2004, Addiction)—12 studies of bupropion vs placebo for smoking cessation.
No sex diff due to bupropion vs placebo but lower abstinence in women overall.
Bupropion vs placebo in men OR =2.53 (1.88-3.4)Bupropion vs placebo in women OR = 2.47 (1.92-
3.17)
However, overall, women were less likely than men to quit, whether on bupropion, OR=0.79 (0.65-0.95), or on placebo, OR=0.75 (0.59-0.94)
DRD2 Genotype and Nicotine Patch Outcome (6 months)Treatment x genotype x sex interaction (p<.001)
02468101214161820
Men-CT,TT
Men-CC Women-CT,TT
Women-CC
NicotinePlacebo
Yudkin, Munafo, Hey, et al. (2004) British Med J (online version)
N=307 men, 445 women (41% CT,TT [A1/A1, A1/A2]; 59% CC [A2/A2])
Worldwide Smoking Prevalence is still rising
• Currently 1.2 billion smokers consuming 6 trillion cigarettes per year (so, 4% of smokers are U.S.)
• Smoking kills 5 million per year, or one every 6 sec (9% of smoking deaths are U.S.)
• China, with 350 million smokers, produces about 50% of world’s tobacco (U.S. is distant second at about 10%).
• Traditional treatment approaches (e.g. medications, one-on-one counseling) not likely to be practical. Policy and prevention are needed.
• WHO and other international org’s helping to reduce tobacco use (also Framework Agreement on curbing tobacco, advertising, etc.)
• FDA issue: Regulation of nicotine levels and/or non-nicotine constituents responsible for health risks, enhancement of dependence, etc.