Tar level of cigarettes smoked and risk of smoking-related diseases

Figures & data

Table 1. Studies of tar yield and major smoking-related diseases.

	References^a	Location, Study type^b	Lung Cancer	Heart disease	Stroke	COPD
1^c^,^d	Hammond et al. (1976); Lee & Garfinkel (1981)	USA, P	✓	✓	✓	✓
2	Higenbottam et al. (1982)	UK, P	✓	✓	–	–
3^e	Vutuc & Kunze (1982, 1983)	Austria, CC	✓	–	–	–
4^f	Kaufman et al. (1983)	USA, CC	–	✓	–	–
5	Lubin et al. (1984)	Western Europe, CC	✓	–	–	–
6	Alderson et al. (1985, 1986)	UK, CC	✓	✓	✓	✓^g
7^h	Petitti & Friedman (1985a,b); Sidney et al. (1993)	USA, P	✓	✓	✓	✓
8^i	Garfinkel & Stellman (1988); Harris et al. (2004)	USA, P	✓	–	–	–
9	Gillis et al. (1988)	UK, CC	✓	–	–	–
10	Wilcox et al. (1988)	USA, CC	✓	–	–	–
11	Wynder & Kabat (1988)	USA, CC	✓	–	–	–
12	Kaufman et al. (1989)	USA and Canada, CC	✓	–	–	–
13^f	Palmer et al. (1989)	USA, CC	–	✓	–	–
14^j	Kuller et al. (1991); Ockene et al. (1990)	USA, P	✓	✓	–	–
15	Negri et al. (1993)	Italy, CC	–	✓	–	–
16	Benhamou et al. (1994)	France, CC	✓	–	–	–
17	Parish et al. (1995)	UK, CC	–	✓	–	–
18^k	Tang et al. (1995)	UK, P	✓	✓	✓	✓
19	Bosetti et al. (1999)	Italy, CC	–	✓	–	–
20	Speizer et al. (1999)	USA, P	✓	–	–	–
21^l	Woodward (2001); Woodward et al. (1999)	Scotland, P	✓	✓	✓	–
22	Tavani et al. (2001)	Italy, CC	–	✓	–	–
23	Sauer et al. (2002)	USA, CC	–	✓	–	–
24^m	Gallus et al. (2007)	Italy, CC	–	✓	–	–
25	Zhang et al. (2011)	Germany, P	–	✓	–	–
26	Lee et al. (2017b)	5 European countries, CC	✓	–	–	–

Or surrogate measure as indicated by footnotes d and f.

^a Multiple references to the same study are shown on the same line.

^b Study type: CC: case–control; P: prospective.

^c The earlier reference gives results for lung cancer and heart disease, the later reference for all four diseases.

^d Comparisons based on a combined tar and nicotine index, see Table A1 for details.

^e The earlier reference gives results for women, the later reference for men.

^f Comparisons based on nicotine.

^g Originally described as “chronic bronchitis” and omitted from the earlier review (Forey et al., 2011), the outcome definition was subsequently corrected to COPD (Lee et al., 2014).

^h The earlier reference gives results for all diseases for 4 years follow-up, the later reference for lung cancer for 6 years follow-up.

ⁱ The earlier reference gives results for 4 years follow-up, the later reference for 6 years follow-up.

^j Both references give results for 10.5 years follow-up but give results with different confounder adjustment.

^k Combined evidence from four studies, including studies 2 and 9.

^l The earlier reference gives results for heart disease only for 8 years follow-up, the later reference for all three diseases listed for 13 years follow-up.

^m Combined evidence from females in study 19, all subjects in study 15 and subjects collected over a longer period than those considered in study 22.

Table 2. Relative risks of lung cancer in lower compared to higher tar cigarette smokers.

Study	References	Location, Study type^a	Comparison	Gender^b	RR (95% CI) Unadjusted for cigs/day^c	RR (95% CI) Adjusted for cigs/day^d
1	Lee & Garfinkel (1981)	USA, P	Low versus High T/N	M^e		0.82 (0.63–1.07)
				M		0.80 (0.58–1.10)
				F^e		0.57 (0.36–0.90)
				F		0.63 (0.42–0.95)
2	Higenbottam et al. (1982)	UK, P	18–23 versus 33+ mg tar	M	0.68 (0.46–1.00)	0.53 (0.34–0.83)
3	Vutuc & Kunze (1982)	Austria, CC	<15 versus 24 mg tar	F	0.32 (0.09–1.17)	0.29 (0.09–0.95)
3	Vutuc & Kunze (1983)	Austria, CC	<15 versus 24 mg tar	M	0.32 (0.09–1.08)	0.30 (0.11–0.81)
5	Lubin & Blot (1984)	West Europe, CC	Low versus high tar	M	0.98 (0.75–1.28)	0.71 (0.55–0.93)
				F	0.67 (0.38–1.20)	0.67(0.38–1.18)
6	Alderson et al. (1986)	England, CC	17–22 versus 29+ mg tar	M		0.83 (0.57–1.20)
				F		1.12 (0.77–1.64)
9	Gillis et al. (1988)	Scotland, CC	<23 versus 23+ mg tar	M	0.73 (0.52–1.01)	0.74 (0.53–1.03)
10	Wilcox et al. (1988)	USA, CC	≤14 versus 21 mg tar	M	0.53 (0.29–0.97)	0.61 (0.32–1.13)
11	Wynder & Kabat (1988)	USA, CC	<10 versus 15+ mg tar	M	1.32 (0.89–1.96)
				F	0.97 (0.63–1.49)
12	Kaufman et al. (1989)	USA, Canada, CC	<22 versus 29+ mg tar	M	0.11 (0.04–0.30)	0.25 (0.08–0.83)
				F	0.17 (0.07–0.43)	0.21 (0.05–0.91)
14	Kuller et al. (1991)	USA, P	<16 versus 20+ mg tar	M	0.73 (0.38–1.41)	0.88 (0.52–1.49)
7	Sidney et al. (1993)	USA, P	<11 versus >18 mg tar	M	0.92 (0.63–1.32)	0.79 (0.41–1.49)
				F	1.49 (0.78–2.87)	1.49 (0.76–2.94)
16	Benhamou et al. (1994)	France, CC	“Light imported” versus 30+ mg tar	M	0.26 (0.14–0.48)	0.30 (0.10–0.91)
18	Tang et al. (1995)	UK, P	Per 15 mg tar decrease	M		0.75 (0.52–1.09)
20	Speizer et al. (1999)	USA, P	low versus high tar tertile	F	0.50 (0.36–0.67)	1.00 (0.71–1.43)
21	Woodward (2001)	Scotland, P	<10 versus 15+ mg tar	B	0.31 (0.11–0.86)	0.43 (0.15–1.23)
8	Harris et al. (2004)	USA, P	0–7 versus 22+ mg tar	M	0.81 (0.63–1.05)	0.78 (0.60–1.00)
				F	0.60 (0.44–0.81)	0.56 (0.41–0.76)
26	Lee et al. (2017b)	Europe, CC	≤3 versus 10+ mg tar	B	0.86 (0.61–1.20)	0.73 (0.50–1.06)

Tables A1 and A2 give more details of the tar groupings used (and of the T/N [combined tar and nicotine] grouping used in study 1), as well as giving details on the factors adjusted for and on the derivation of estimates. Studies are shown in chronological order of the reference used.

Studies 2 and 9 are included in the analysis of study 18.

Studies 3 and 16 are included in the analysis of study 5.

^a Study type: P: prospective; C: case–control.

^b Gender: M: males; F: females; B: both.

^c Most-adjusted estimate not including cigarettes/day.

^d Most-adjusted estimate including cigarettes/day.

^e First estimate is for 1960–1966 follow-up, and second is for 1966–1972 follow-up.

Table 3. Meta-analyses for lung cancer.

Estimates selected^a	N	RR (95% CI)^b	Het chisq, df^c	Het p
Including studies 2, 3, 9 and 16
Unadjusted estimates only	20	0.65 (0.53–0.79)	71.4, 19	<.001
Adjusted estimates only	25	0.72 (0.65–0.81)	36.4, 24	.05
Excluding studies 2, 3, 9 and 16
Unadjusted estimates only	15	0.70 (0.55–0.87)	56.5, 14	<.001
Adjusted estimates only	20	0.76 (0.68–0.84)	25.9, 19	.13
Prefer unadjusted estimates	22	0.74 (0.63–0.86)	63.3, 21	<.001
Prefer adjusted estimates	22	0.78 (0.70–0.88)	34.0, 21	.04
– all
– by period of publication
1981–1985	6	0.73 (0.63–0.84)	2.8, 5	.73
1986–1995	11	0.88 (0.71–1.09)	18.3, 10	.05
1996+	5	0.73 (0.59–0.91)	7.2, 4	.13
Between periods			5.7, 2	.06
– by gender
Male	11	0.80 (0.71–0.91)	11.8, 9	.30
Female	9	0.78 (0.61–1.00)	20.7, 8	.008
Combined	2	0.69 (0.48–0.96)	0.9, 2	.35
Between genders			0.7, 2	.71
– by study design
Prospective	12	0.76 (0.67–0.86)	14.2, 10	.22
Case–control	10	0.80 (0.65–1.00)	19.0, 9	.03
Between designs			0.9, 1	.34
– by number of confounders
<5	14	0.84 (0.73–0.97)	21.8, 12	.06
5+	8	0.68 (0.56–0.82)	9.5, 7	.22
Between groups			2.7, 1	.10
– by continent
North America	15	0.78 (0.67–0.92)	28.2, 14	.01
Europe	7	0.78 (0.67–0.90)	5.8, 6	.45
Between continents			0.03, 1	.87
– excluding estimated based on tar and nicotine	18	0.80 (0.73–0.88)	30.8, 17	.02

^a Unadjusted and adjusted relate to cigs/day.

^b Estimates are random effects.

^c Het chisq: heterogeneity chi-squared. For single analyses, this relates to variable between estimates within analysis. For comparison of subgroups (e.g. by period of publication or gender), this relates to variation between subgroups.

Table 4. Relative risk of heart disease in lower compared to higher tar cigarette smokers.

Study	References	Location, Study type^a	Comparison	Gender^b	RR (95% CI) Unadjusted for cigs/day^c	RR (95% CI) Adjusted for cigs/day^d
1	Lee & Garfinkel (1981)	USA, P	Low versus High T/N	M^e		0.94 (0.84–1.05)
				M		0.81 (0.69–0.95)
				F^e		0.81 (0.69–0.96)
				F		0.81 (0.68–0.97)
2	Higenbottam et al. (1982)	UK, P	18–23 versus 33+ mg tar	M	0.82 (0.63–1.06)	0.75 (0.57–1.00)
4	Kaufman et al. (1983)	USA, CC	<0.8 versus 1.5+ mg nicotine	M	1.19 (0.67–2.10)
7	Petitti & Friedman (1985a)	USA, P	Per 5 mg tar decrease	B		0.80 (0.63–1.01)^f
				B		0.85 (0.68–1.06)^g
6	Alderson et al. (1986)	England, CC	17–22 versus 29+ mg tar	M		0.93 (0.56–1.57)^h
				M		1.16 (0.60–2.26)^i
				F		0.90 (0.51–1.59)^h
				F		1.33 (0.79–2.24)^i
13	Palmer et al. (1989)	USA, CC	<0.4 versus 1.3+ mg nicotine	F	1.12 (0.55–2.28)
14	Kuller et al. (1991)	USA, P	≤15 versus 20+ mg tar	M	0.94 (0.65–1.35)	0.84 (0.61–1.16)
15	Negri et al. (1993)	Italy, CC	<10 versus >20 mg tar	B	1.03 (0.56–1.87)	1.00 (0.56–2.00)
17	Parish et al. (1995)	UK, CC	<10 versus 10+ mg tar	B	0.83 (0.73–0.94)^j	0.86 (0.75–0.98)^j
				B	0.96 (0.81–1.12)^k	0.99 (0.84–1.17)^k
18	Tang et al. (1995)	UK, P	Per 15 mg tar disease	M		0.77 (0.61–0.97)
19	Bosetti et al. (1999)	Italy, CC	<10 versus 15+ mg tar	M	1.15 (0.72–1.82)
				F	0.71 (0.34–1.49)
22	Tavani et al. (2001)	Italy, CC	Low versus High tar	B	1.15 (0.65–2.04)
21	Woodward (2001)	Scotland, P	<10 versus 15+ mg tar	B	0.79 (0.46–1.37)	0.96 (0.46–2.04)
23	Sauer et al. (2002)	USA, CC	≤6 versus 12+ mg tar	B	0.45 (0.30–0.68)	0.53 (0.38–0.75)
24	Gallus et al. (2007)	Italy, CC	<10 versus 20+ mg tar	B	0.80 (0.51–1.25)	0.78 (0.50–1.23)
25	Zhang et al. (2011)	Germany, P	1–12 versus 13+ mg tar	M		0.75 (0.49–1.15)
				F		0.58 (0.20–1.70)

Tables A1 and A3 give more details of the tar and nicotine groupings used (including the T/N [combined tar and nicotine] index used in study 1), as well as giving details on the factors adjusted for and on the derivation of estimates. Studies are shown in chronological order of the reference used.

Study 2 is included in the analysis of study 18.

Study 15 is included in the analysis of study 19 which is included in the analysis of study 24.

Study 22 is included in the analysis of study 24.

^a Study type: P: prospective; C: case–control.

^b Gender: M: males; F: females; B: both.

^c Most-adjusted estimate not including cigarettes/day.

^d Most-adjusted estimate including cigarettes/day.

^e First estimate is for 1960–1966 follow-up, and second is for 1966–1972 follow-up.

^f RR for acute myocardial infarction.

^g RR for other ischemic heart disease.

^h Estimates for age 35–54 years.

ⁱ Estimates for age 55–74 years.

^j Estimates for age 30–59 years.

^k Estimates for age 60–79 years.

Table 5. Meta-analyses for heart disease.

Estimates selected^a	N	RR (95% CI)^b	Het chisq, df^c	Het p
Including studies 2, 15, 19 and 22
Unadjusted estimates only	13	0.87 (0.77–0.98)	17.1, 12	.15
Adjusted estimates only	21	0.85 (0.81–0.90)	21.6, 20	.36
Excluding studies 2, 15, 19 and 22
Unadjusted estimates only	8	0.84 (0.72–0.99)	13.9, 7	.05
Adjusted estimates only	19	0.85 (0.80–0.90)	20.5, 18	.31
Prefer unadjusted estimates	21	0.85 (0.80–0.90)	23.5, 20	.26
Prefer adjusted estimates	21	0.86 (0.81–0.91)	22.3, 20	.33
– all
– by period of publication
1981–1989	12	0.87 (0.82–0.93)	9.5, 11	.58
1990–1999	4	0.88 (0.80–0.97)	3.4, 3	.33
2000+	5	0.67 (0.54–0.83)	3.5, 4	.48
Between periods			5.91, 2	.05
– by gender
Male	8	0.88 (0.81–0.95)	5.4, 7	.61
Female	6	0.85 (0.75–0.96)	5.3, 5	.38
Combined	7	0.83 (0.73–0.94)	11.2, 6	.08
Between genders			0.4, 2	.82
– by study design
Prospective	11	0.85 (0.80–0.90)	6.0, 10	.82
Case–control	10	0.90 (0.77–1.04)	15.4, 9	.08
Between designs			0.9, 1	.34
– by number of confounders
<5	8	0.90 (0.82–0.98)	6.4, 7	.50
5+	13	0.84 (0.79–0.90)	14.7, 12	.26
Between groups			1.2, 1	.26
– by continent
North America	10	0.83 (0.76–0.91)	13.7, 9	.13
Europe	11	0.89 (0.82–0.97)	7.9, 10	.64
Between continents			0.8, 1	.38
– excluding estimates not based specifically on tar	15	0.85 (0.78–0.92)	16.5, 14	.28
– excluding estimates based on nicotine	19	0.85 (0.80–0.90)	20.5, 18	.31

^a Unadjusted and adjusted relate to cigarettes/day.

^b Estimates are random effects.

^c Het chisq: heterogeneity chi-squared. For single analyses, this relates to variable between estimates within analysis. For comparison of subgroups (e.g. by period of publication or gender), this relates to variation between subgroups.

Table 6. Relative risks of stroke in lower compared to higher tar cigarette smokers.

Study	References	Location, study type^a	Comparison	Gender^b	RR (95% CI) Adjusted for cigs/day
1	Lee & Garfinkel (1981)	USA, P	Low versus High T/N	M	0.71 (0.57–0.88)
				F	0.98 (0.81–1.19)
7	Petitti & Friedman (1985b)	USA, P	Per 5 mg tar decrease	B	0.57 (0.37–0.89)
6	Alderson et al. (1986)	UK, P	17–22 versus 29+ mg tar	M	0.53 (0.31–0.91)
				F	1.00 (0.62–1.62)
18	Tang et al. (1995)	UK, P	Per 15 mg tar decrease	M	0.86 (0.50–1.50)
21	Woodward (2001)	Scotland, P	<10 versus 15+ mg tar	B	0.29 (0.04–2.38)
			Number of estimates		7
			Combined RR (95% CI)		0.77 (0.62–0.95)
			Heterogeneity chi-squared		11.79
			df		6
			p		.07

Tables A1 and A4 give more details of the tar groupings used (including the T/N [combined tar and nicotine] index used in study 1), as well as details on the factors adjusted for and on derivation of estimates. Studies are shown in chronological order of the reference used.

^a P: prospective study.

^b M: male; F: female; B: both sexes.

Table 7. Relative risks of COPD in lower compared to higher tar cigarette smokers.

Study	References	Location, study type^a	Comparison	Gender^b	RR (95% CI) Adjusted for cigs/day
1	Lee & Garfinkel (1981)	USA, P	Low versus high T/N	M	0.78 (0.53–1.15)
				F	0.59 (0.32–1.09)
7	Petitti & Friedman (1985b)	USA, P	Per 5 mg tar decrease	B	1.00 (0.90–1.10)
6	Alderson et al. (1986)	UK, P	17–22 versus 29+ mg tar	M	0.55 (0.35–0.86)
				F	1.03 (0.65–1.64)
18	Tang et al. (1995)	UK, P	Per 15 mg tar decrease	M	0.78 (0.41–1.48)
			Number of estimates		6
			Combined RR (95% CI)		0.81 (0.65–1.02)
			Heterogeneity chi-squared		10.48
			df		5
			p		.06

Tables A1 and A5 give more details of the tar groupings used (including the T/N [combined tar and nicotine] index used in study 1), as well as details on the factors adjusted for and on derivation of estimates. Studies are shown in chronological order of the reference used.

^a P: prospective study.

^b M: male; F: female; B: both sexes.

Figure 1. Forest plot of relative risks of lung cancer in lower compared to higher tar cigarette smokers (preferring adjusted estimates and excluding studies 2, 3, 9 and 16 to avoid overlaps).

Figure 2. Forest plot of relative risks of heart disease in lower compared to higher tar cigarette smokers (preferring adjusted estimates and excluding studies 2, 15, 19 and 22 to avoid overlaps).

Table A1. Further details of the studies.

	Study population^a	Controls^b	Age^c	Details of groupings used (only lowest and highest levels used in Tables 2–7)
1	Member of household with person age >45, excluding migrant workers		30+/30+	For 1960–1966 high T/N was defined as >2.0 mg nicotine and 2.5 mg tar, low T/N as less than 1.2 mg nicotine and less than 17.6 mg tar, and medium T/N as intermediate. For 1966–1972, the definition of low T/N was the same but that of high T/N was lowered “somewhat”
2	Civil servants		40–69/89	18–23, 24–32, 33+ mg tar
3	General	Diseased	Unrestricted	<15, 15–24, 24+ mg tar
4	General	Diseased	40–69	<0.8, 0.8–0.9, 1.0–1.1, 1.2–1.4, 1.5+ mg nicotine
5	General	Diseased	Unrestricted	Categories were the within-country 10, 25, 50, 75 and 90th percentiles. Mean tar values within categories were 15.6, 18.5, 20.6, 23.6, 25.2 and 29.8 mg.
6	General	Diseased	35–74	17–22, 23–28, 29+ mg tar
7	Attending screening		30+/30+	For lung cancer <11, 11–18, >18 mg tar For other diseases per 5.0 mg tar decrease
8	General		30+/30+	0–7, 8–14, 15–21, 22+ mg tar
9	General	Diseased	Unrestricted	<17, 17–22, 23–28, 29+ mg tar (as the extreme groupings had very little data the comparison used was <23 versus 23+ mg tar).
10	General	Healthy + decedents	Unrestricted	≤14, 14.1–17.5, 17.6–21.0, 21.1–28.0 mg tar
11	General	Diseased	Unrestricted	<10, 10–14, 15+ mg tar
12	General	Diseased	40–69	<22, 22–28, 29+ mg tar
13	General	Diseased	25–64	<0.40, 0.40–0.63, 0.64–0.75, 0.76–1.00, 1.01–1.06, 1.07–1.29, 1.30+ mg nicotine
14	Attending screening, with high coronary risk		35–57/69	≤15, 16–19, 20+ mg tar
15	General	Diseased	Unrestricted	<10, 10–15, >15–20, >20 mg tar
16	General	Diseased	Unrestricted	Light imported (unknown tar levels) for life, and use of 30+ mg tar cigs for ≤50%, 51–75% or >75% of years smoked
17	General	Healthy	30–79	<10, 10+ mg tar
18	4 cohorts: professional, civil service, factory, residents		35–78/98	Per 15 mg tar decrease
19	General	Diseased	<75	<10, 10–15, >15 mg tar
20	Nurses		30–55/71	Tertiles of tar (values not stated)
21	General		40–59/74	<10, 10–14, 15+ mg tar
22	General	Diseased	25–79	Low, high tar not further defined
23	General (with telephone and English speaking)	Healthy	30–65	≤6, 7–12, >12 mg tar
24	General	Diseased	Unrestricted	<10, 10–19, 20+ mg tar
25	General		25–74/90	1–12, 13+ mg tar
26	General	Diseased	Unrestricted	≤3 mg, 10+ mg tar

T/N: combined tar and nicotine index.

^a “general” indicates that population was of a general nature with no major inclusion or exclusion criteria.

^b For CC studies, the control group is described as diseased (includes hospital controls), healthy (includes community controls) or decedent.

^c For case–control studies the age range is shown, with “unrestricted” indicating no restriction on the age of cases. For prospective studies the age range at baseline and at final follow-up are shown separated by a “/”.

Table A2. Further details associated with Table 2 (lung cancer).

	RRs unadjusted for cigs/day^a		RRs adjusted for cigs/day^b
Study	Derivation of estimates from source tables^c	Covariates considered	Derivation of estimates from source tables^c	Covariates considered^d
1	–	–	Table 5 gives the RRs. The 95% CIs were estimated using method 6, with the additional assumption that the ratio of cases for low to high tar is 40:60 (based on additional data in Hammond et al. (1976))	Age, race, residence, education, occupational exposures, history of lung cancer, history of heart disease, age start, cigs/day
2	Estimated from Table 4, first estimating the rates combined over inhalation × cigs/day groups given, then method 5	Age, employment grade	Estimated from Table 4, first estimating the RR/CI within each inhalation × cigs/day group given, then method 3	+ inhalation, cigs/day
3	Estimated from Table 1 using method 1	Unadjusted	Estimated from Table 1 using method 4	Years smoked, cigs/day
5	Estimated from Table X using method 1	Unadjusted	Estimated from Table X using method 6	Age, study center, years smoked, years quit, cigs/day
6	–	–	Estimated from Table 13F using methods 6 and 8, with the additional assumption that the loss due to missing tar data was the same in controls as in cases	Age, cigs/day
9	Estimated from Table 5 using method 1	Unadjusted	Estimated from Table 5 using method 1	Cigs/day
10	Given in Table 2	Unadjusted	Given in Table 2	Cigs/day
11	Estimated from Figures 1 and 2, summing over LC types then method 1	Unadjusted	–	–
12	Estimated from Table 5 using method 1	Unadjusted	Estimated from Table 5 using method 8	Age, race, region, education, years of interview, age start, cigs/day
14	Estimated from Table 8 using method 1	Unadjusted	Estimated from Table 8 using method 8	Cigs/day
7	Estimated from Table 3 using methods 5 and 6	Age	Estimated from Table 3 using method 8	+ race, education, years smoked, cigs/day
16	Estimated from Table 3 using method 8	Age	Estimated from Table 3 using method 8	+ inhalation, tobacco type, use of filter cigarettes, years smoked, cigs/day
18	–	–	Given in Table 5	Age, study, cigs/day
20	Estimated from text on p477 using method 8	Age start	Estimated from text on p477 using method 8	+ cigs/day
21	Estimated from Table 3 using method 8	Age, gender	Estimated from Table 3 using method 8	+ social class, Bortner score, β-carotene, α-tocopherol and vitamin C consumption, BMI, urinary potassium, years smoked, cigs/day
8	Estimated from Table 5 using method 4	Education, race, marital status, occupation, vegetables and citrus fruit consumption, use of vitamin A, C or E, occupation, age start	Estimated from Table 5 using method 4	+ cigs/day
26	Given in Table 2	Unadjusted	Given in Table 2	Gender, age, country, education, age start, tar level^e, cigs/day^e

BMI: body mass index.

Comparisons used: See Table 2 and Table A1 for details of the groupings used and the comparisons made.

^a Most-adjusted estimate not including cigs/day.

^b Most-adjusted estimate including cigs/day.

^c The method numbers refer to the methods described fully in Lee et al. (2012) – see Additional File S1, section “Derivation of RR”. In brief, the methods used here are (1) calculated from 2 × 2 table; (3) combining independent estimates; (4) combining non-independent estimates by the method of Hamling et al. (2008); (5) ratio of rates; (6) CI for the adjusted RR estimated from the crude numbers; (8) low/high estimated from high/low by inversion.

^d + implies that the covariates listed are additional to those used for the unadjusted RRs.

^e Mean of brands smoked 21–50 years before interview.

Table A3. Further details associated with Table 4 (heart disease).

	RRs unadjusted for cigs/day^a		RRs adjusted for cigs/day^b
Study	Derivation of estimates from source tables^c	Covariates considered	Derivation of estimates from source tables^c	Covariates considered^d
1	–	–	Table 7 gives the RRs. The 95% CIs were estimated using method 6, with the additional assumption that the ratio of cases for low to high tar is 40:60 (based on additional data in Hammond et al. (1976)).	Age, race, residence, education, occupational exposures, history of lung cancer, history of heart disease, history of stroke, history of diabetes, history of blood pressure, exercise, obesity, coffee/tea, alcohol, aspirin, occupation, age start, cigs/day.
2	Estimated from Table 6, first estimating the rates combined over inhalation × cigs/day groups given, then method 5	Age, employment grade	Estimated from Table 6, first estimating the RR/CI within each inhalation × cigs/day group given, and using method 2 for a group with zero cases, then method 3	+ inhalation, cigs/day
4	Estimated from Table 3 using method 4	Age, region, treatment for hypertension, cholesterol, treatment for diabetes, family history of MI or stroke, personality, alcohol, religion, marital status	–	–
7	Estimated from Table 3 model 3 (for AMI and other IHD) using method 8	–	Estimated from Table 3 (for AMI and other IHD) using method 8	Age, gender, race, Quetelet index, cholesterol, history of hypertension, alcohol, cigs/day
6	–	–	Estimated from Tables 15F and 16F using methods 6 and 8, with the additional assumption that the loss due to missing tar data was the same in controls as in cases	Age, cigs/day
13	Estimated from Table 3 using method 4	Age, history of hypertension, history of angina, history of diabetes, history of raised cholesterol, family history of MI before age 60, menopause, BMI, type A score, exercise, education, residence, use of OCs, use of estrogen, coffee, alcohol	–	–
14	Estimated from Table 8 using method 1	Unadjusted	Estimated from Table 8 using method 8	Age, cholesterol, blood pressure, cigs/day
15	Estimated from Tables II and III using method 4	Age, gender, education, cholesterol, history of diabetes and hypertension, family history of AMI, BMI, coffee	Estimated from Table III using method 8	+ cigs/day
17	Estimated from Table III using method 8	Age, gender	Estimated from Table III using method 8	+ cigs/day
18	–	–	Given in Table 5	Age, study, cigs/day
19	Estimated from Table 2 using method 4	Age, education, study center, cholesterol, history of diabetes, hypertension and hyperlipidemia, family history of AMI, coffee, alcohol, BMI	–	–
22	Estimated from Table 3 using method 4	Age, gender, education, BMI, cholesterol, coffee, alcohol, physical activity, hyperlipidemia, diabetes, hypertension, family history of AMI	–	–
21	Estimated from Table 3 using method 8	Age, gender	Estimated from Table 3 using method 8	+ social class, Bortner score, β-carotene, α-tocopherol and vitamin C, potassium, years smoked, cigs/day
23	Estimated from Table 2 using method 1	Unadjusted	Estimated from Table 8 using method 8	Age, gender, race, BMI, history of CHD, hypertension, diabetes or hypercholesterolemia, family history of CHD, exercise, vitamin use, education, years smoked, cigs/day
24	Estimated from Table 4 using method 8	Age, gender, study, education, BMI, alcohol, coffee, cholesterol, family history of AMI, history of diabetes and hypertension	Estimated from Table 4 using method 8	+ years smoked, cigs/day
25	–	–	Estimated from Table 3 using method 4	Age, survey, alcohol, hypertension, cholesterol/HDL-C ratio, physical inactivity, diabetes, cigs/day

AMI: acute myocardial infarction; BMI: body mass index; CHD: coronary heart disease; HDL-C: high density lipoprotein cholesterol; IHD: ischemic heart disease; OC: oral contraceptives.

Comparisons used: See Table 4 and Table A1 for details of the groupings used and the comparisons made.

^a Most-adjusted estimate not including cigs/day.

^b Most-adjusted estimate including cigs/day.

^c The method numbers refer to the methods described fully in Lee et al. (2012) – see Additional File S1, section “Derivation of RR”. In brief, the methods used here are (1) calculated from 2 × 2 table; (4) combining non-independent estimates (Hamling et al., 2008); (6) CI for the adjusted RR estimated from the crude numbers; (8) low/high estimated from high/low by inversion.

^d + implies that the covariates listed are additional to those used for the unadjusted RRs.

Table A4. Further details associated with Table 6 (stroke).

Study	Derivation of estimates from source tables^a	Covariates considered
1	Table 6 gives the RRs. The 95% CIs were estimated using method 6, with the additional assumption that the ratio of cases for low to high tar is 40:60 (based on additional data in Hammond et al. (1976)).	Age, race, residence, education, occupational exposures, history of lung cancer, history of heart disease, age start, cigs/day
7	Estimated from Table 3 model 3, using method 8	Age, sex, race, Quetelet index, serum cholesterol, history of hypertension, alcohol, cigs/day.
6	Estimated from Table 17F using methods 6 and 8, with the additional assumption that the loss due to missing tar data was the same in controls as in cases	Age, cigs/day
18	Given in Table 5	Age/study, cigs/day
21	Estimated from Table 3 using method 8	+ social class, Bortner score, β-carotene, α-tocopherol and vitamin C consumption, BMI, urinary potassium, years smoked, cigs/day

BMI: body mass index.

Comparisons used: See Table 6 and Table A1 for details of the groupings used and the comparisons made.

^a The method numbers refer to the methods described fully in Lee et al. (2012) – see Additional File S1, section “Derivation of RR”. In brief, the methods used here are (6) CI for the adjusted RR estimated from the crude numbers; (8) low/high estimated from high/low by inversion.

Table A5. Further details associated with Table 7 (COPD).

Study	Derivation of estimates from source tables^a	Covariates considered
1	Table 7 gives the RRs. The 95% CIs were estimated using method 6, with the additional assumption that the ratio of cases for low to high tar is 40:60 (based on additional data in Hammond et al. (1976)).	Age, race, residence, education, occupational exposures, history of lung cancer, history of heart disease, age start, cigs/day
7	Given in Table 3	Age, gender, race, cigs/day
6	Estimated from Table 14F using methods 6 and 8, with the additional assumption that the loss due to missing tar data was the same in controls as in cases	Age, cigs/day
18	Given in Table 5	Age/study, cigs/day

COPD: chronic obstructive pulmonary disease.

Comparisons used: See Table 7 and Table A1 for details of the groupings used and the comparisons made.

^a The method numbers refer to the methods described fully in Lee et al. (2012) – see Additional File S1, section “Derivation of RR”. In brief, the methods used here are (6) CI for the adjusted RR estimated from the crude numbers; (8) low/high estimated from high/low by inversion.

Hammond EC, Garfinkel L, Seidman H, Lew EA. (1976). “Tar” and nicotine content of cigarette smoke in relation to death rates. Environ Res 12:263–74.

 PubMed Web of Science ®Google Scholar

Lee PN, Garfinkel L. (1981). Mortality and type of cigarette smoked. J Epidemiol Community Health 35:16–22.

 PubMed Web of Science ®Google Scholar

Higenbottam T, Shipley MJ, Rose G. (1982). Cigarettes, lung cancer, and coronary heart disease: the effects of inhalation and tar yield. J Epidemiol Community Health 36:113–7.

 PubMed Web of Science ®Google Scholar

Vutuc C, Kunze M. (1982). Lung cancer risk in women in relation to tar yields of cigarettes. Prev Med 11:713–6.

 PubMed Web of Science ®Google Scholar

Vutuc C, Kunze M. (1983). Tar yields of cigarettes and male lung cancer risk. J Natl Cancer Inst 71:435–7.

 PubMedGoogle Scholar

Kaufman DW, Helmrich SP, Rosenberg L, et al. (1983). Nicotine and carbon monoxide content of cigarette smoke and the risk of myocardial infarction in young men. N Engl J Med 308:409–13.

 PubMed Web of Science ®Google Scholar

Lubin JH, Blot WJ, Berrino F, et al. (1984). Patterns of lung cancer risk according to type of cigarette smoked. Int J Cancer 33:569–76.

 PubMed Web of Science ®Google Scholar

Alderson MR, Lee PN, Wang R. (1985). Risks of lung cancer, chronic bronchitis, ischaemic heart disease, and stroke in relation to type of cigarette smoked. J Epidemiol Community Health 39:286–93.

 PubMed Web of Science ®Google Scholar

Alderson MR, Lee PN, Wang R. (1986). Risk of lung cancer, chronic bronchitis, ischaemic heart disease, and stroke in relation to type of cigarette smoked, passive smoking and other factors. Sutton, Surrey: P. N. Lee Statistics and Computing Ltd. Available from: www.pnlee.co.uk/Reports.htm [Download ALDERS1986].

 Google Scholar

Petitti DB, Friedman GD. (1985a). Cardiovascular and other diseases in smokers of low yield cigarettes. J Chronic Dis 38:581–8.

 PubMedGoogle Scholar

Sidney S, Tekawa IS, Friedman GD. (1993). A prospective study of cigarette tar yield and lung cancer. Cancer Causes Control 4:3–10.

 PubMed Web of Science ®Google Scholar

Garfinkel L, Stellman SD. (1988). Smoking and lung cancer in women: findings in a prospective study. Cancer Res 48:6951–5.

 PubMed Web of Science ®Google Scholar

Harris JE, Thun MJ, Mondul AM, Calle EE. (2004). Cigarette tar yields in relation to mortality from lung cancer in the cancer prevention study II prospective cohort, 1982-8. BMJ 328:72–6.

 PubMed Web of Science ®Google Scholar

Gillis CR, Hole DJ, Boyle P. (1988). Cigarette smoking and male lung cancer in an area of very high incidence. I. Report of a case-control study in the West of Scotland. J Epidemiol Community Health 42:38–43.

 PubMed Web of Science ®Google Scholar

Wilcox HB, Schoenberg JB, Mason TJ, et al. (1988). Smoking and lung cancer: risk as a function of cigarette tar content. Prev Med 17:263–72.

 PubMed Web of Science ®Google Scholar

Wynder EL, Kabat GC. (1988). The effect of low-yield cigarette smoking on lung cancer risk. Cancer 62:1223–30.

 PubMed Web of Science ®Google Scholar

Kaufman DW, Palmer JR, Rosenberg L, et al. (1989). Tar content of cigarettes in relation to lung cancer. Am J Epidemiol 129:703–11.

 PubMed Web of Science ®Google Scholar

Palmer JR, Rosenberg L, Shapiro S. (1989). “Low yield” cigarettes and the risk of nonfatal myocardial infarction in women. N Engl J Med 320:1569–73.

 PubMed Web of Science ®Google Scholar

Kuller LH, Ockene JK, Meilahn E, et al. (1991). Cigarette smoking and mortality. MRFIT Research Group. Prev Med 20:638–54.

 PubMed Web of Science ®Google Scholar

Ockene JK, Kuller LH, Svendsen KH, Meilahn E. (1990). The relationship of smoking cessation to coronary heart disease and lung cancer in the Multiple Risk Factor Intervention Trial (MRFIT). Am J Public Health 80:954–8.

 PubMed Web of Science ®Google Scholar

Negri E, Franzosi MG, La Vecchia C, et al. (1993). Tar yield of cigarettes and risk of acute myocardial infarction. GISSI-EFRIM Investigators. BMJ 306:1567–70.

 PubMedGoogle Scholar

Benhamou S, Benhamou E, Auquier A, Flamant R. (1994). Differential effects of tar content, type of tobacco and use of a filter on lung cancer risk in male cigarette smokers. Int J Epidemiol 23:437–43.

 PubMed Web of Science ®Google Scholar

Parish S, Collins R, Peto R, et al. (1995). Cigarette smoking, tar yields, and non-fatal myocardial infarction: 14,000 cases and 32,000 controls in the United Kingdom. The International Studies of Infarct Survival (ISIS) Collaborators. BMJ 311:471–7.

 PubMed Web of Science ®Google Scholar

Tang J-L, Morris JK, Wald NJ, et al. (1995). Mortality in relation to tar yield of cigarettes: a prospective study of four cohorts. BMJ 311:1530–3.

 PubMedGoogle Scholar

Bosetti C, Negri E, Tavani A, et al. (1999). Smoking and acute myocardial infarction among women and men: a case-control study in Italy. Prev Med 29:343–8.

 PubMed Web of Science ®Google Scholar

Speizer FE, Colditz GA, Hunter DJ, et al. (1999). Prospective study of smoking, antioxidant intake, and lung cancer in middle-aged women (USA). Cancer Causes Control 10:475–82.

 PubMed Web of Science ®Google Scholar

Woodward M. (2001). Is compulsory restriction of tar yield of cigarettes a worthwhile public health policy? Am J Prev Med 21:284–90.

 PubMed Web of Science ®Google Scholar

Woodward M, Moohan M, Tunstall-Pedoe H. (1999). Self-reported smoking, cigarette yields and inhalation biochemistry related to the incidence of coronary heart disease: results from the Scottish heart health study. J Epidemiol Biostat 4:285–95.

 PubMedGoogle Scholar

Tavani A, Bertuzzi M, Negri E, et al. (2001). Alcohol, smoking, coffee and risk of non-fatal acute myocardial infarction in Italy. Eur J Epidemiol 17:1131–7.

 PubMed Web of Science ®Google Scholar

Sauer WH, Berlin JA, Strom BL, et al. (2002). Cigarette yield and the risk of myocardial infarction in smokers. Arch Intern Med 162:300–6.

 PubMedGoogle Scholar

Gallus S, Randi G, Negri E, et al. (2007). Tar yield and risk of acute myocardial infarction: pooled analysis from three case-control studies. Eur J Cardiovasc Prev Rehabil 14:299–303.

 PubMedGoogle Scholar

Zhang Q-L, Baumert J, Ladwig K-H, et al. (2011). Association of daily tar and nicotine intake with incident myocardial infarction: results from the population-based MONICA/KORA Augsburg Cohort Study 1984-2002. BMC Public Health 11:273.

 PubMed Web of Science ®Google Scholar

Lee PN, Fry JS, Hamling JS. (2017b). Investigation into the risk of ultra-low tar cigarettes and lung cancer. Regul Toxicol Pharmacol 89:112–7.

 PubMed Web of Science ®Google Scholar

Forey BA, Thornton AJ, Lee PN. (2011). Systematic review with meta-analysis of the epidemiological evidence relating smoking to COPD, chronic bronchitis and emphysema. BMC Pulm Med 11:36.

 PubMed Web of Science ®Google Scholar

Lee PN, Fry JS, Forey BA. (2014). Estimating the decline in excess risk of chronic obstructive pulmonary disease following quitting smoking – a systematic review based on the negative exponential model. Regul Toxicol Pharmacol 68:231–9.

 PubMed Web of Science ®Google Scholar

Lubin JH, Blot WJ. (1984). Assessment of lung cancer risk factors by histologic category. J Natl Cancer Inst 73:383–9.

 PubMedGoogle Scholar

Petitti DB, Friedman GD. (1985b). Respiratory morbidity in smokers of low- and high-yield cigarettes. Prev Med 14:217–25.

 PubMed Web of Science ®Google Scholar

Lee PN, Forey BA, Coombs KJ. (2012). Systematic review with meta-analysis of the epidemiological evidence in the 1900s relating smoking to lung cancer. BMC Cancer 12:385.

 PubMed Web of Science ®Google Scholar

Hamling J, Lee P, Weitkunat R, Ambühl M. (2008). Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category. Stat Med 27:954–70.

 PubMed Web of Science ®Google Scholar