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Erschienen in: BMC Public Health 1/2018

Open Access 01.12.2018 | Research article

Smoking-related general and cause-specific mortality in Estonia

verfasst von: Gea Kõks, Krista Fischer, Sulev Kõks

Erschienen in: BMC Public Health | Ausgabe 1/2018

Abstract

Background

Tobacco smoking is known to be the single largest cause of premature death worldwide. The aim of present study was to analyse the effect of smoking on general and cause-specific mortality in the Estonian population.

Methods

The data from 51,756 adults in the Estonian Genome Center of the University of Tartu was used. Information on dates and causes of death was retrieved from the National Causes of Death Registry. Smoking status, general survival, general mortality and cause-specific mortality were analysed using Kaplan-Meier estimator and Cox proportional hazards models.

Results

The study found that smoking reduces median survival in men by 11.4 years and in women by 5.8 years. Tobacco smoking produces a very specific pattern in the cause of deaths, significantly increasing the risks for different cancers and cardiovascular diseases as causes of death for men and women. This study also identified that external causes, such as alcohol intoxication and intentional self-harm, are more prevalent causes of death among smokers than non-smokers. Additionally, smoking cessation was found to reverse the increased risks for premature mortality.

Conclusions

Tobacco smoking remains the major cause for losses of life inducing cancers and cardiovascular diseases. In addition to the common diseases, external causes also reduce substantially the years of life. External causes of death indicate that smoking has a long-term influence on the behaviour of smokers, provoking self-destructive behaviour. Our study supports the idea, that tobacco smoking generates complex harm to our health increasing mortality from both somatic and mental disorders.
Hinweise
An erratum to this article is available at https://​doi.​org/​10.​1186/​s12889-017-4709-6.

Background

Tobacco smoking is a single major cause of premature death worldwide [1, 2]. Despite substantial reduction in the use of tobacco, smoking still causes more deaths globally than diseases like tuberculosis, HIV and malaria combined, making it the largest preventable health risk factor [3, 4]. The use of tobacco is legally allowed and therefore the prevalence of smoking behaviour is still very high. While in the developed countries tobacco use is reduced and restricted, in developing countries the tobacco epidemic is still in the growing phase [1, 5]. It has been estimated that tobacco smoking causes globally 6 million deaths in a year [6]. 80% of these deaths are premature and affect lower income individuals [5]. This all makes tobacco smoking the largest single avoidable cause for mortality. Reducing the prevalence of smoking increases the health of the general population by avoiding premature disability and death. Smoking cessation and support to stop smoking are the easiest tools to improve the quality of life in population [7, 8].
While it is clear that smoking increases mortality, the association between smoking and mortality is different across specific causes of death. Cancers, chronic obstructive diseases of respiratory system and cardiovascular diseases are the most commonly referred smoking-induced causes of death.
The association between smoking and lung cancer has been described already in 1950 and following years [912]. Later studies found clear association with other cancers as well [13]. Tobacco smoking is known to cause cancers of upper gastrointestinal tract, pancreas, prostate [14]. While the association is conclusive for lung and upper respiratory tract cancers, the connection between smoking and other cancers does not have conclusive evidence.
Tobacco smoking is reported to cause 90% of all chronic obstructive pulmonary disease (COPD) mortality and smoking cessation is the best measure to avoid this outcome [15]. The relative risk for smokers to die from COPD is 25.6 in men and 22.3 in women, compared to non-smokers [16]. Therefore, one of the most common health problems in smokers is COPD [16, 17]. The development of COPD is dependent on the chronic persistent inflammation in the lung tissue that induces tissue-remodelling [18]. COPD is the most common and the most prevalent disease in smokers and smokers have very highly increased risk for COPD.
Cardiovascular diseases have been found to be the third major cause of death caused by smoking [16, 19]. The main causes for death are ischaemic heart disease, cerebrovascular disease and other heart diseases [16]. Interestingly the risks caused by smoking of death due coronary heart disease are remarkably different between men and women [20]. Women who smoke have four times increased risk of death from ischaemic heart disease, while male smokers only have twofold increased risk [20]. For cerebrovascular diseases, this sex difference in risk has not been found [21]. This influence of sex on the risk of ischaemic heart disease is striking and its mechanism could be biological or behavioural.
Increased prevalence of chronic diseases suggests increased inflammatory activity in smokers. Indeed, several studies indicate chronic inflammation in the smokers and different immunomodulating toxins in the smoke probably cause increased immune reactivity [22, 23]. A recent study analysed RNA expression profiles in the blood of smokers and non-smokers and identified a highly significant increase in the expression of GPR15 gene [24]. GPR15 is an orphan receptor that is responsible for the homing of tissue-specific immune cells [25].
Several previous studies have shown that the association between smoking with different causes of deaths is variable [26]. There are some large-scale population studies where causes of death and association with smoking have been addressed [7, 13, 16]. However, more detailed differential risk analyses for smoking and causes of death are not that common [27]. The goal of present study was to analyse the smoking-caused mortality in the Estonian Genome Center cohort and to describe the differential sensitivity for the different specific causes of death.

Methods

The aim, design and setting of the study

The aim of the study was to analyse smoking-induced mortality profile in Estonia using data at the Estonian Genome Center. Estonian Genome Center at the University of Tartu is a population-based biobank that recruited a cohort of 51,756 participants, including adults from all counties in Estonia, accounting for approximately 5% of the Estonian adult population during the recruitment period. Recruitment was performed during the period from 2002 to 2012 [28]. At baseline, an extensive phenotype questionnaire was conducted together with a measurement panel. Follow-up data is available from linkage with national health-related registries and the Estonian Health Insurance database. Mortality information was retrieved from the Estonian Causes of Death Registry and last retrieval was performed in September 2015.
The Ethics Review Committee on Human Research of the University of Tartu approved the protocols and informed-consent forms used in this study. All of the participants signed a written informed-consent form.

Smoking data

Smoking data were collected during the recruitment of donors to the Estonian Genome Center. The following questions were asked:
1)
“If you have ever smoked regularly, when did you start?”
 
2)
“How many of the tobacco products have you used during the last 12 months?”
 
3)
“For how many years have you used tobacco products with this amount?”
 
4)
“What is the amount of tobacco products you used most commonly?”
 
5)
“For how many years you have used tobacco products as described?”
 
Smoking behaviour was divided into three major categories: current smokers, former smokers and never smoked. Former smokers were individuals who had not smoked for at least one year prior to recruitment.

Statistical analysis

All statistical analyses were stratified by sex, as previous analysis indicated significant differences in the smoking patterns between males and females. Statistical analysis was performed in R studio and packages “survival”, “epitools”, “Publish”, “dplyr” were used. Survival data were modelled by using Cox model [29]. Survival was calculated from the date when subjects joined the Estonian Genome Centre cohort (2002–2012) and censored at date of death, retrieved from the National Death Registry, or September 2015, whichever came first.
The data on smoking status, smoking intensity and smoking pattern was categorized (current, former and never smokers; smoking up to 10, 10–20 or more than 20 cigarettes per day; up to 20 years or more than 20 years of smoking history) and tabulated by four age groups (18–25, 26–45, 46–65 and more than 65 years).
Mortality data was tabulated according to the cause of death, smoking status and sex of all participants. For survival analysis, the Kaplan-Meier estimator was used to plot survival curves. Starting time-point was the date when subjects joined the Estonian Genome Centre cohort and the end-point was the date of data retrieval from the National Death Registry. Cox proportional hazards regression analysis was used to calculate hazard ratio for all-cause mortality and cause-specific mortality, comparing current and former smokers with never-smokers, using age as a time scale (to account for left-truncation in the data). Cox regression was also used to estimate the effects of smoking intensity (cigarettes per day) and length of smoking history on overall survival. Using the Kaplan-Meier method for left-truncated data, the median survival time for current, former and never smokers in the cohort also was estimated with a 95% confidence interval.
For cause-specific mortality, the causes of death according to the 10th Revision of International Statistical Classification of Diseases and Related Health Problems (ICD-10) were analysed separately in men and women.

Results

General smoking characteristics in the cohort

The Estonian Genome Center includes 51,756 participants: 17,777 men and 33,979 women (Table 1), aged 18 and over at recruitment. The recruitment period was between 2002 and 2012.
Table 1
Age distribution in the cohort of the Estonian Genome Center of the University of Tartu 2002–2012
 
Men
Women
Total
Variable
n
%
n
%
n
%
Age group
 18–25
3896
7.5
5302
10.3
9198
17.8
 26–45
6016
11.6
12,436
24.0
18,452
35.6
 46–65
5292
10.2
11,257
21.8
16,549
32.0
 over 65
2573
5.0
4984
9.6
7557
14.6
Total
17,777
34.3
33,979
66.7
51,756
100.0
Basic demographic information and smoking characteristics are given in the Tables 2 and 3. Of all 17,777 men (Table 2), 39.4% were never-smokers, 20.8% former and 39.8% current smokers. Of all 33,979 women (Table 3), 67.3% were never-smokers, 10.0% former and 22.7% current smokers. This indicates clearly higher prevalence of smoking in Estonian men than women. The proportion of smokers in the cohort is similar to that of the general Estonian population [1]. According to the recent WHO data, the smoking prevalence in Estonian men is 41.2% and in women 24.9% [1].
Table 2
Smoking characteristics by age-group in the male cohort of the Estonian Genome Center of the University of Tartu 2002–2012
 
Age group
 
18–25
26–45
46–65
Over 65
Total
Variable
n
%
n
%
n
%
n
%
n
%
Smoking status
Total
3896
100.0
6016
100.0
5292
100.0
2573
100.0
17,777
100.0
 Never smoker
1854
47.6
2281
37.9
1783
33.7
1093
42.5
7011
39.4
 Former smoker
218
5.6
1013
16.8
1409
26.6
1058
41.1
3698
20.8
 Current smoker
1824
46.8
2722
45.3
2100
39.7
422
16.4
7068
39.8
 Age at start (SD)
16
(2.4)
18
(3.5)
19
(4.5)
20
(5.4)
18
(4.2)
 
Current smokers
Years smoked (SD)
5
(2.8)
17
(6.5)
35
(7.1)
51
(8.0)
108
(14.7)
 Up to 20 years
1773
100.0
1772
66.8
52
2.5
4
0.9
3601
52.3
 Over 20 years
0
0.0
879
33.2
1991
97.5
409
99.1
3279
47.7
Cigarettes per day
 Number of persons
1807
100.0
2698
100.0
2084
100.0
419
100.0
7008
100.0
 Up to 10
634
35.1
551
20.4
299
14.4
102
24.3
1586
22.6
 10–20
1101
60.9
1898
70.4
1555
74.6
295
70.4
4849
69.2
 Over 20
72
4.0
249
9.2
230
11.0
22
5.3
572
8.2
 
Former smokers
Years smoked (SD)
4
(2.6)
11
(6.5)
22
(11.3)
29
(15.2)
20
(13.7)
 Up to 20 years
192
100.0
893
91.2
645
47.1
340
33.0
2070
58.0
 Over 20 years
0
0.0
86
8.8
724
52.9
691
67.0
1501
42.0
Cigarettes per day
 Number of persons
163
100.0
766
100.0
1095
100.0
869
100.0
2893
100.0
 Up to 10
87
53.4
184
24.0
161
14.7
126
14.5
558
19.3
 10–20
72
44.2
515
67.2
791
72.3
661
76.1
2039
70.5
 Over 20
4
2.4
67
8.8
143
13.0
82
9.4
296
10.2
Table 3
Smoking characteristics by age-group in the female cohort of the Estonian Genome Center of the University of Tartu 2002–2012
 
Age group
 
18–25
26–45
46–65
Over 65
Total
Variable
n
%
n
%
n
%
n
%
n
%
Smoking status
Total
5302
100.0
12,436
100.0
11,257
100.0
4984
100.0
33,979
100.0
 Never smoker
3390
63.9
7587
61.0
7471
66.4
4407
88.4
22,855
67.3
 Former smoker
328
6.2
1374
11.0
1334
11.8
366
7.3
3402
10.0
 Current smoker
1584
29.9
3475
28.0
2452
21.8
211
4.3
7722
22.7
 Age at start (SD)
16
(2.2)
20
(4.4)
23
(7.3)
27
(10.0)
21
(6.3)
 
Current smokers
Years smoked (SD)
5
(2.7)
16
(6.2)
29
(8.3)
42
(11.0)
92
(11.7)
 Up to 20 years
1540
100.0
2556
76.4
314
13.1
10
4.8
4420
 
 Over 20 years
0
0.0
790
23.6
2076
86.9
197
95.2
3063
 
Cigarettes per day
 Number of persons
1570
100.0
3435
100.0
2436
100.0
211
100.0
7652
100.0
 Up to 10
968
61.7
1510
44.0
1020
41.9
104
49.3
3602
47.0
 10–20
584
37.2
1842
53.6
1363
55.9
104
49.3
3893
51.0
 Over 20
18
1.1
83
2.4
53
2.2
3
1.4
157
2.0
 
Former smokers
Years smoked (SD)
3
(2.4)
9
(6.1)
18
(10.7)
24
(14.9)
14
(10.9)
 Up to 20 years
293
100.0
1210
94.7
768
60.9
162
45.6
2433
76.3
 Over 20 years
0
0.0
68
5.3
494
39.1
193
54.4
755
23.7
Cigarettes per day
 Number of persons
259
100.0
1051
100.0
1049
100.0
300
100.0
2659
100.0
 Up to 10
183
70.6
573
54.5
571
54.4
160
53.3
1487
55.9
 10–20
75
29.0
470
44.7
458
43.7
136
45.3
1139
42.9
 Over 20
1
0.4
8
0.8
20
1.9
4
1.4
33
1.2
The average age to start smoking in men was 18 (SD 4.2) years and in women 21 (SD 6.3) years. Analysis of the different age groups indicated that nowadays people start smoking at a younger age than in the past. Men in the age group 65+ had started smoking at age 20 and women at age 27 in the average. On the other hand, average age of starting to smoke in the youngest age group (18–25) was 16 for both, men and women.
The cohort was divided into two groups according to the duration of smoking – up to 20 years and over 20 years of smoking. In the study cohort, most of the smokers were smoking for less than 20 years. This trend also was valid in all subgroups of the cohort.
The number of cigarettes per day differed significantly between male and female smokers. On average, men smoked 15 (SD 9) and women smoked 9 (SD 7) cigarettes per day. The average number of cigarettes per day was similar in current and former smokers.

All-cause mortality

By September 2015, 3364 (1649 men and 1715 women) people the cohort had died. The average age at death was 69 (SD 14) and 74 (SD 14) years for men and women, respectively. A general description of the more frequent causes of death and their association with smoking is given in the Table 4.
Table 4
Basic characteristics of smoking, number of all causes of death and the most common cause-specific deaths in the studied cohort
 
Variable
Men
Women
 
Smoking status
Current
Former
Never
Current
Former
Never
  
n
n
n
n
n
n
 
Persons in cohort
7068
3698
7011
7722
3402
22,855
 
All causes death in cohort
627
548
474
270
147
1298
C16
Malignant neoplasm of stomach
8
13
10
10
5
34
C18
Malignant neoplasm of colon
3
10
9
4
1
25
C25
Malignant neoplasm of pancreas
11
18
11
12
6
32
C34
Malignant neoplasm of bronchus and lung
73
42
5
15
6
19
C50
Malignant neoplasm of breast
12
8
35
C56
Malignant neoplasm of ovary
5
8
25
C61
Malignant neoplasm of prostate
16
17
29
C80
Malignant neoplasm without specification of site
9
2
4
9
I11
Hypertensive heart disease
41
41
39
20
22
190
I13
Hypertensive heart and renal disease
8
10
13
5
4
28
I21
Acute myocardial infarction
16
11
12
6
4
31
I22
Subsequent myocardial infarction
12
9
2
2
2
11
I25
Chronic ischaemic heart disease
80
113
100
21
21
243
I35
Nonrheumatic aortic valve disorders
5
2
6
1
1
17
I42
Cardiomyopathy
16
9
12
5
2
11
I50
Heart failure
10
2
1
4
1
17
I63
Cerebral infarction
16
30
13
9
9
79
I70
Atherosclerosis
2
3
5
2
1
11
J15
Bacterial pneumonia
1
4
3
3
2
7
J44
Chronic obstructive pulmonary disease
17
18
2
7
1
10
K70
Alcoholic liver disease
8
7
6
7
0
2
R99
Ill-defined and unspecified causes of mortality
6
3
4
5
0
2
X45
Accidental poisoning by and exposure to alcohol
14
1
3
2
0
1
X70
Intentional self-harm by hanging, strangulation and suffocation
13
3
8
5
1
5
The Kaplan-Meier curves for overall survival were significantly different in current, former and never smokers, in both men and women (Fig. 1). The test for survival curve differences in men between three different smoking categories (“Never”, “Former”, “Current”) was highly significant (p = 1.8*10−40). In case of women, the difference was also highly significant (p = 1.3*10−14) for three-group comparison. The never smoked group had the longest survival and current smokers had the shortest survival. Survival of former smokers was in-between the never and current smokers indicating beneficial effect of quitting.
Age-adjusted Cox regression of all-cause mortality in both sexes indicated significantly increased hazard ratio (HR) and 95% confidence interval (CI), for current 3.1 (CI 2.8–3.4) and former 1.6 (CI 1.5–1.8) smokers, compared to never smokers. When different sexes were analysed separately, almost similar results were seen. In male current smokers HR was 2.5 (CI 2.2–2.8) and in former smokers 1.3 (CI 1.2–1.5) for all-cause mortality. Currently smoking women had HR 2.6 (CI 2.2–3.0) and former smokers had 1.3 (CI 1.1–1.5) for all-cause mortality. Taken together, smoking status was significantly associated with increased all-cause mortality and this association was similar for men and women.

Median age at death and loss of life years

Smoking significantly reduced median age of death. In the entire study group, median age of death in never smokers was 85.7 (CI 85.4–86.2), in former smokers 80.6 (CI 79.6–81.6) and in current smokers 74.7 (CI 73.5–75.7) years.
The median age of death for men who never smoked was 82.6 (CI 81.4–83.6), for former smokers 78.4 (CI 77.1–79.4) and for current smokers 71.2 (CI 70.2–72.3) years. Median age of death for women who never smoked was 86.4 (CI 86.1–86.8), for former smokers 85.8 (CI 83.4–88.1) and for current smokers 80.6 (CI 77.9–81.8) years.
Therefore, we estimate that the median loss of life years in smoking men is 11.4 years and in women 5.8 years at lost. In the case of men, former smokers lived significantly longer than current smokers, but significantly less than never smokers. In the case of women, the difference in age of death of former and never smokers were very small.

Effect of smoking duration and smoking intensity on all-cause mortality

The increased risk for all-cause mortality was also significantly associated with smoking duration. Men who smoked more than 20 years had HR 2.1 (CI 1.9–2.3) and men who smoked less than 20 years had HR 2.3 (CI 2.1–2.5). Women with smoking duration more than 20 years had HR 2.7 (CI 2.4–3.1) and with less than 20 years had HR 1.4 (CI 1.3–1.6). However, the number of cigarettes per day had a less severe influence on the all-cause mortality than smoking duration.

Cause-specific mortality

The subsequent analysis involved specific causes for mortality. The study cohort altogether had 272 unique ICD-10 main categories as cause of death. The most frequent causes of death (more than 100 cases) were chronic ischaemic heart disease (I25), hypertensive heart disease (I11), malignant neoplasm of bronchus and lung (C34) and cerebral infarction (I63) across the entire cohort (Table 4). Men and women also were analysed separately and for specific causes of death age-adjusted hazard ratio was calculated with non-smokers as reference. Statistically significant findings are shown in Tables 5 and 6.
Table 5
Smoking related adjusted hazard ratio (HR) and 95% confidence intervals (CI 95%) for the statistically significant cause-specific mortality in men
 
Variable
Current smokers
Former smokers
 
ICD-10 code for cause of death
HR
CI 95%
HR
CI 95%
C34
Malignant neoplasm of bronchus and lung
32.9
13.2–82.0
9.2
3.7–23.4
C80
Malignant neoplasm without specification of site
7.8
1.5–39.5
C16–C80
Malignant neoplasms
4.0
2.1–5.4
1.7
1.2–2.3
I11
Hypertensive heart disease
2.1
1.3–3.3
1.2
0.8–1.8
I22
Subsequent myocardial infarction
9.4
2.0–43.3
5.4
1.2–24.8
I25
Chronic ischaemic heart disease
1.9
1.4–2.6
1.3
0.9–1.7
I50
Heart failure
24.4
2.8–213.1
2.1
0.2–23.4
I63
Cerebral infarction
3.3
1.5–7.0
2.7
1.4–5.3
I00–I99
Diseases of the circulatory system
2.6
1.8–2.7
1.3
1.1–1.5
J44
Chronic obstructive pulmonary disease
23.1
5.2–101.8
9.7
2.3–41.7
J00–J99
Diseases of the respiratory system
7.8
3.2–18.7
4.2
1.8–9.7
X45
Accidental poisoning by and exposure to alcohol
3.6
1.1–12.7
0.5
0.05–5.1
V01–Y98
External causes of morbidity and mortality
2.2
1.5–3.3
0.8
0.5–1.4
Table 6
Smoking related adjusted hazard ratio (HR) and 95% confidence intervals (CI 95%) for the statistically significant cause-specific mortality in women
 
Variable
Current smokers
Former smokers
 
ICD-10 code for cause of death
HR
CI 95%
HR
CI 95%
C25
Malignant neoplasm of pancreas
4.0
1.9–8.3
1.9
0.8–4.7
C34
Malignant neoplasm of bronchus and lung
6.7
3.2–14.4
3.0
1.2–7.6
C56
Malignant neoplasm of ovary
0.9
0.3–2.5
2.4
1.1–5.3
C16–C80
Malignant neoplasms
2.7
1.9–3.7
1.8
1.2–2.6
I11
Hypertensive heart disease
2.2
1.3–3.6
1.4
0.9–2.2
I13
Hypertensive heart and renal disease
3.3
1.1–9.8
1.7
0.6–4.9
I21
Acute myocardial infarction
4.7
1.9–12.2
1.6
0.6–4.6
I25
Chronic ischaemic heart disease
2.1
1.3–3.3
1.1
0.7–1.7
I50
Heart failure
10.3
2.9–35.8
0.9
0.1–6.6
I63
Cerebral infarction
3.4
1.6–7.0
1.6
0.8–3.1
I70
Atherosclerosis
10.2
1.8–57.4
1.2
0.2–9.6
I00–I99
Diseases of the circulatory system
2.7
2.1–3.5
1.3
1.0–1.7
J15
Bacterial pneumonia
6.4
1.3–32.2
3.2
0.7–15.8
J44
Chronic obstructive pulmonary disease
19.3
7.1–52.6
1.3
0.2–10.2
J00–J99
Diseases of the respiratory system
12.0
5.3–27.3
1.8
0.5–6.1
K70
Alcoholic liver disease
13.9
2.6–75.8
R99
Ill-defined and unspecified causes of mortality
8.5
1.6–45.6
X70
Intentional self-harm by hanging, strangulation and suffocation
4.6
1.2–18.1
1.6
0.2–13.7
V01–Y98
External causes of morbidity and mortality
7.6
3.9–14.7
2.6
1.0–6.5
The most significant specific causes for mortality in currently smoking men were malignant neoplasm of bronchus and lung (C34, HR 32.9), heart failure (I50, HR 24.4), chronic obstructive pulmonary disease (J44, HR 23.1) and subsequent myocardial infarction (I22, HR 9.4) (Table 5, Fig. 2). Current smokers also had a significantly increased hazard ratio to die from malignant neoplasms at unspecified sites (C80, HR 7.8). Interestingly, current smokers also had a significantly elevated hazard ratio for accidental poisoning by an exposure to alcohol (X45, HR 3.6), for cerebral infarction (I63, HR 3.3), for hypertensive heart disease (I11, HR 2.1) and chronic ischaemic disease (I25, HR 1.9) as causes of death.
Compared to current smokers, former male smokers (Table 5) had significantly lower hazard ratio values for most of the causes of death. This finding illustrates a clear health benefit of quitting smoking as the general risk for death reduced from 2.5 to 1.3 and the number of specific causes for death decreased. In men who stopped smoking, only four causes of death remained statistically significant compared to those who have never smoked. These causes of death were chronic obstructive pulmonary disease (J44, HR 9.7), malignant neoplasm of bronchus and lung (C34, HR 9.2), subsequent myocardial infraction (I22, HR 5.4) and cerebral infarction (I63, HR 2.7).
In the case of currently smoking women (Table 6, Fig. 3) the highest hazard ratio as a cause of death were for chronic obstructive pulmonary disease (J44, HR 19.3), for alcoholic liver disease (K70, HR 13.9), for heart failure (I50, HR 10.3) and for atherosclerosis (I70, HR 10.2). Current smokers also had increased hazard ratio for ill-defined and unspecified causes of mortality (R99, HR 8.5), for malignant neoplasm of bronchus and lung (C34, HR 6.7), for bacterial pneumonia (J15, HR 6.4), for acute myocardial infarction (I21, HR 4.7) and intentional self-harm by hanging, strangulation and suffocation (X70, HR 4.6) as a cause of death. In currently smoking women, the hazard ratio for accidental poisoning by an exposure to alcohol (X45) was elevated, but this increase did not reach statistical significance.
Smoking cessation significantly reduced the risks for specific causes of death and most of the hazard ratios were not different compared to the never smoked group (Table 6). In former smokers only malignant neoplasm of the bronchus and lung (C34, HR 3.0) and malignant neoplasm of the ovaries (C56, HR 2.4) remained significant specific causes of death.
Taken together, current smokers have significantly increased mortality and a specific pattern of cause of death. Respiratory and cardiovascular diseases were the most significant causes of death. This indicates, that smoking does the most harm to the lungs and cardiovascular system. The former smokers group had significantly less mortality than current smokers and therefore, smoking cessation significantly reduces the hazard ratio for cause-specific mortality. Former smokers still have significantly increased hazard to die from the lung diseases.

Discussion

Based on the epidemiological analysis of tobacco smoking in the cohort of the Estonian Genome Center, this study concluded that Estonia still belongs to the group of countries with high number of smokers. On average, there are two times more smokers in Estonia than in Western-European countries. The high number of smokers also is characteristic for other Eastern-European countries. This statement is particularly true in men. In Estonia and other Eastern-European countries around 40% of men are smokers, whereas in Western-European countries only 10–20% of men are smokers. In the case of female smokers, Estonia is similar to Western-European countries, where 20% of women smoke [1]. This fits the typical epidemiologic pattern seen in Europe and developed countries. Differences between different countries are smaller in case of women and are prominent in the case of men. These differences also explain the significantly worse health of men in Eastern-European countries. Men smoke too much and they pay for that with their health and quality of life as seen by the reduced life span.
The smoking prevalence in the Estonian Genome Center cohort is similar to the prevalence described in other study based on general population in three Baltic states [30]. In addition, the age-group prevalence of the Estonian Genome Center cohort is similar to the general Estonian population [28]. Therefore, our results are generalizable for the entire Estonian population.
While the proportion of smokers in Estonia has been stable for 20 years, the age at which individuals start smoking tobacco has decreased remarkably. At present, people start to smoke at the median age of 16 and this is similar for men and women. This trend is worrisome and has an important impact on the health of the Estonian population.
The age-group analysis indicated that men start to quit smoking at the age 46–65, women start quitting 26–45. This indicates that women smoke for a shorter period of their life. Taken together, men start smoking earlier, they smoke more cigarettes per day (mostly 20 cigarettes per day) and they quit smoking later. At the same time, women smoke less (mostly 10 cigarettes per day) they start smoking later and give up smoking earlier. This difference could also be detectable as the difference in survival and causes of death. Therefore smoking has a significantly larger impact on men’s health than in women.
There present study analysed the impact of tobacco smoking on the hazard of all-cause and cause-specific mortality. Survival analysis clearly indicated shorter median survival in smokers compared to non-smokers. Survival analysis also indicated that smoking cessation is beneficial for the survival. This means that toxic effects of smoking are reversible. The positive effect of quitting on the survival has been described in many previous studies [16, 17, 19].
Interestingly, in women the general survival differences caused by tobacco smoking were less prominent. For example, men who smoked lived on average 11.4 years less than non-smokers, bud women who smoked only lost 5.8 years on average. In some previous studies, similar sex-differences in smoking effects have been found [31]. This sex-difference may be explained by the lower smoking activity in women. In our sample women smoked 9 cigarettes per day while men smoked 15 cigarettes per day on average. Women also start smoking later and quit earlier that makes their smoking duration shorter and this explains the reduced number of cigarettes smoked by women. Previous studies support this idea. If women smoke more they have mortality and morbidity profile similar to men and the sex differences disappear [32, 33].
The loss of years found from the survival analysis in the present study was similar to the findings from previous studies where loss of at least 10 years was found [17]. This indicates that the study design used and the results are comparable with other studies. For example, the study of Jha et al. analysed survival from the age 25 [17]. The present study included people from the age 18 and mortality data were retrieved from the National Death Registry. This approach has been used for many previous studies.
The impact of smoking duration on general mortality gave somewhat controversial results as in men we found increased mortality in both groups compared to non-smokers. In case of men, the difference in general mortality between smoking more than 20 years and less than 20 years was very small (HR 2.1 versus 2.3) and statistically not significant. In case of women, the difference related to smoking duration was significant. Women smoking more than 20 years had HR 2.7 (CI 2.4–3.1) and women smoking less than 20 years have HR 1.4 (CI 1.3–1.6). This finding is similar to the previously published findings [34]. Similarly, we found that number of cigarettes per day does not have impact on the all-cause mortality.
The cause-specific analysis of death should describe the most common reasons why smokers lose years of their life. The comparison of causes of death induced by smoking in men and women identified very high similarities between both sexes in the pattern of cause of death. Namely, the most significantly smoking-associated causes of death were diseases of the respiratory and cardiovascular systems both in men and women. This indicates that there is a common biological mechanism behind the smoking that increases morbidity and mortality. This mechanism is the same in men and women. One very good candidate for this common pathway is the GPR15 that was recently found to be upregulated in both male and female smokers [24].
In addition to the lung and heart diseases, the one of the largest hazard ratio was related to external causes of death. In men, this cause was death from accidental poisoning by an exposure to alcohol (X45). In women, these causes were alcoholic liver disease (K70) and intentional self-harm by hanging, strangulation, suffocation (X70). Alcoholic liver disease (K70) is closely related to a poisoning by an exposure to alcohol (X45) and should be taken as an external cause of disease. The significantly increased risks for external causes of death have been described in few previous studies and more detailed analysis is difficult to find [14]. The prevalence of alcohol poisoning and self-harm in former smokers as causes of death were the same in former smoker and non-smokers. This means that the increased incidence of suicide and alcohol intoxication in current smokers could reflect particular biologically determined behavioural endophentoype and personality characteristics of current smokers. Smokers could be more impulsive or more prone to risk taking. One side of this behaviour is increased alcohol consumption, binge drinking and suicide. Not many studies indicate causes for this kind of association, but most probably there is common genetic variation between smokers and suicide victims. One recent study found an association between the polymorphic variable number tandem repeat (VNTR) in the SLC6A4 gene and increased risk for tobacco use disorder [35]. The association between polymorphisms in the BDNF gene and nicotine dependence also has been described [36]. Moreover, as tobacco smoking behaviour is often explained in conjunction with mood disorders, the link between suicide and smoking is not that surprising. At least one deletion in the GSTM1 and GSTT1 genes has been described in anxious smokers while no association with mood disorders have been found [37].
One of the limitations of the study is the small number of several specific causes of death that could make our analysis imprecise. This small number is caused by the short time for observation. Currently it is impossible to get better estimations and this study can be a starting point for the repeated mortality analysis of the Estonian Genome Center cohort. Extended observation will eventually increase the number of specific causes and improve the precision of the analysis. In order to improve the regression analysis, we merged some cases (like J44, J45 and J47) that increased the power to estimate proportional hazard for smokers and ex-smokers. This helped to get more reliable HR estimations.

Conclusions

In conclusion, the prevalence of tobacco smoking is still high in Estonia and men smoke at least two times more than women. This high prevalence is reflected in substantial loss of years of life and shorter survival of men. Smoking cessation can reverse the increased mortality, but the time needed for this reversal is not known. The two main types of cause of death in smokers were diseases of lung and cardiovascular system. The third group of cause of death is self-destructive behaviour. This finding suggests a common biological substrate in the brain of nicotine addicts and risk-taking behaviour. Better knowledge about the link between psychiatric illnesses and smoking could help to develop more effective interventions. Further studies are required to understand the genetic and biological background of this association.

Acknowledgements

The friendly support from the staff of Estonian Genome Centre is acknowledged. Financial support from Estonian Ministry of Education and Research (institutional research grants IUT20–46 and IUT20–60 of the), from the European Commission (H2020 programme grants 668989 Transgeno and 692145 ePerMed) and from the European Regional Development Fund (project no. 2014–2020.4.01.15–0012, Gentransmed) are acknowledged.

Funding

GK was supported by Estonian Research Agency grant IUT20–46 and by the H2020 ERA-chair grant (agreement 668,989, project Transgeno);
KF was supported by Estonian Research Agency grant IUT20–60 and by the H2020 project ePerMed (grant no. 692145);
SK was supported by Estonian Research Agency grant IUT20–46 and by the H2020 ERA-chair grant (agreement 668,989, project Transgeno).

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
The Ethics Review Committee on Human Research of the University of Tartu approved the protocols and informed-consent forms used in this study. All of the participants signed a written informedconsent form.
Not applicable.

Competing interests

Authors declare that they do not have any competing interests regarding to the present manuscript and funding.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
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Metadaten
Titel
Smoking-related general and cause-specific mortality in Estonia
verfasst von
Gea Kõks
Krista Fischer
Sulev Kõks
Publikationsdatum
01.12.2018
Verlag
BioMed Central
Erschienen in
BMC Public Health / Ausgabe 1/2018
Elektronische ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-017-4590-3

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