The study included 430 subjects, with an average age of 33.98 ± 9.99 years (Min 17, Max 55), with the following age structure: 77 (17.9%) in the group < 21 years,196 (45.6%) in the group 21–39 years, while 157 respondents belonged to the category over 40 (36.5%).
In the surveyed population, there were 77 students and pupils (17.9%), 65 with completed primary education (15.1%), 159 with completed secondary education (37.0%) and 124 men who have completed higher school or college (28. 8%) Such data was not obtained for five subjects (1.2%).
In comparison to tobacco consumption in the study population, the smoking frequency was statistically significantly different concerning age (p < 0.001). Regardless of the age category involved, awareness on the effect of smoking on one's own health as well as on the health of a female partner concerning pregnancy is consistent (p = 0.163).
When considering answers to questions about the state of awareness of the effects of smoking for fertile health, we registered as "fully" having knowledge about the consequences to the general health of the respondents themselves, as well as their own fertile health due to tobacco consumption and their partners’ by providing positive information (at least three pieces of information, with examples regarding male gender: effects on the heart, blood pressure, lungs, potency, fertility, etc., and factors related to females: fertility, pregnancy, fetal status, risks of miscarriage, or bleeding in pregnancy).
Also, there were no statistically significant differences regarding their plans for futurebehaviour in relation to smoking (p = 0.134).
Judging from the answers received regarding the frequency of alcohol consumption, awareness of its effects and plans in relation tofuture behaviour and its use, no statistically significant differences were found concerning age categories, as shown by the Chi-square test (p = 0.077, p = 0.082, p = 0568).
Knowledge and awareness of the impact of tobacco on general and fertile health with regard to alcohol consumption is uniform with respect to age categories, that is, there is no statistically significant difference in relation to age (p = 0.082) (Table 1).
Table 1
Current behaviour, knowledge and further plans concerning tobacco and alcohol consumption by age category
|
Age (years)
|
χ2
|
p1
|
Current tobacco-related behaviour
|
< 20 %
|
21–40 %
|
≥ 41 %
|
|
Not smoking
|
41
|
23.2
|
87
|
27.6
|
51
|
38.9
|
43.43
|
< 0.001
|
Up to 10 cigarettes a day
|
20
|
42.9
|
54
|
44.4
|
45
|
51.0
|
Up to 2 packs a day
|
13
|
2.6
|
35
|
17.9
|
48
|
8.3
|
Over 2 packs a day
|
0
|
0.0
|
5
|
2.6
|
13
|
1.9
|
Without response
|
3
|
0.0
|
15
|
7.7
|
0
|
0.0
|
Awareness of the effects of smoking on health
|
Fully informed about effects on their health
|
48
|
42.3
|
107
|
70.9
|
101
|
77.1
|
8.78
|
0.163
|
Partially informed about effects on their health
|
25
|
32.5
|
81
|
25.5
|
50
|
21.0
|
Without basic knowledge
|
0
|
0.0
|
3
|
1.0
|
3
|
0.0
|
Without response (unknown)
|
4
|
5.2
|
5
|
2.6
|
3
|
1.9
|
For smokers: prediction of behaviour
|
Quitting smoking
|
20
|
14.3
|
25
|
24.0
|
26
|
19.7
|
10.16
|
0.137
|
Decreasing the number of cigarettes
|
21
|
14.3
|
44
|
22.4
|
44
|
22.3
|
No change in behaviour
|
27
|
62.3
|
24
|
50.0
|
17
|
54.1
|
Without response (unknown)
|
9
|
9.1
|
6
|
3.6
|
10
|
3.8
|
Current alcohol-related behaviour
|
No consumption
|
25
|
45.5
|
59
|
31.6
|
54
|
40.1
|
11.38
|
0.077
|
Up to 2 drinks a day
|
43
|
49.4
|
104
|
55.1
|
84
|
53.5
|
Regularly over 2 drinks a day
|
6
|
3.9
|
22
|
9.2
|
14
|
5.7
|
Intoxicated at least once a month
Without response (unknown)
|
1
2
|
1.3
0.5
|
8
3
|
4.1
0.0
|
3
2
|
0.6
0.1
|
Knowledge of the effects of alcohol consumption
|
Fully informed about effects on their health
|
48
|
62.3
|
110
|
66.3
|
102
|
77.7
|
11.23
|
0.082
|
Partially informed about effects on reproductive health
|
24
|
31.2
|
67
|
29.1
|
42
|
20.4
|
No information
|
3
|
0.0
|
12
|
1.0
|
10
|
0.0
|
Without response (unknown)
|
2
|
6.5
|
7
|
3.6
|
3
|
1.9
|
Future behaviour concerning alcohol
|
Quitting alcohol
|
6
|
10.4
|
20
|
10.7
|
22
|
12.1
|
4.81
|
0.568
|
Decreasing consumption
|
39
|
20.8
|
84
|
20.9
|
78
|
15.3
|
No change in behaviour
|
26
|
58.4
|
82
|
61.7
|
46
|
67.5
|
Without response (unknown)
|
6
|
10.4
|
10
|
6.6
|
11
|
5.1
|
Fertility diagnosis
|
Oligospermia
|
6
|
7.8
|
54
|
27.6
|
49
|
31.2
|
24.08
|
< 0.001
|
Azoospermia
|
1
|
1.3
|
14
|
7.1
|
14
|
8.9
|
Control group
|
70
|
90.9
|
128
|
65.3
|
94
|
59.9
|
1 Chi-square test |
Statistical indicators on smoking, knowledge of its effects and prediction of further behaviour according to a fertile status of the respondents are as follows: The frequency of smoking is statistically significantly different in relation to a diagnostic status, with the highest proportion of smokers among infertile subjects.
Awareness of smoking effects was statistically significantly different concerning the study groups (p = 0.003). Subjects with normozoospermia were well-informed, while the least informed ones were among the subjects with azoospermia. Intentions for further behaviour in relation to their fertility status differ statistically significantly (p < 0.001), with the majority of subjects in the control group not intending to change their behaviour, with a significantly smaller proportion of subjects with azoospermia not intending to change their behaviour.
The majority of subjects with azoospermia planned to quit smoking completely, while oligospermicpatients were more likely to express themselves in terms of reducing their consumption.
The incidence of alcohol consumption is statistically significantly different in relation to the diagnoses tested, with the least frequent consumption in people with normozoospermia. Azoospermical patients have more than 2 drinks a day regularly, while almost a third of this category get intoxicated.
Knowledge of the effects of alcohol was statistically significantly different from fertility diagnoses (p < 0.001). The category of normozoospermic subjects had full knowledge about health effects.
Future alcohol-related behaviour was statistically significantly different in relation to diagnoses (p < 0.001). The majority of subjects with azoospermia (one in two) spoke in favour of quitting alcohol completely, while the majority of those with oligospermia stated they would decrease consumption of alcohol in the future (Table 2).
Table 2
Frequency of smoking and alcohol consumption, awareness on health effects of smoking and the further behaviour in the study population in relation to diagnoses
|
Dg
|
χ2
|
p
|
Oligospermia
|
Azoospermia
|
Control group
|
Smoking*
|
|
|
|
|
|
|
|
|
Not smoking
|
24
|
4.6
|
0
|
0.0
|
131
|
44.9
|
227.78
|
< 0.001
|
Up to 10 cigarettes a day
|
57
|
49.5
|
11
|
37.9
|
129
|
44.2
|
Up to 2 packs a day
|
17
|
36.7
|
11
|
37.9
|
24
|
8.2
|
Over 2 packs a day
|
3
|
2.8
|
7
|
24.2
|
0
|
0.0
|
Without response
|
8
|
6.4
|
0
|
0.0
|
8
|
2.7
|
Awareness of the effects of smoking on health
|
Fully aware
|
72
|
66.1
|
12
|
41.4
|
224
|
76.7
|
16.10
|
0.003
|
Partially aware
|
32
|
29.4
|
8
|
27.6
|
66
|
22.6
|
None
Without response
|
5
0
|
4.5
0.0
|
9
0
|
31.0
0.0
|
2
0
|
0.7
0.0
|
Future smoking-related behaviour⸷
|
Quitting smoking
|
16
|
18.4
|
12
|
48.0
|
31
|
17.8
|
37.82
|
< 0.001
|
Decreasing the number of cigarettes
|
47
|
54.0
|
17
|
51.9
|
49
|
16.8
|
No change in behaviour
Without response
|
24
*
|
27.6
*
|
0
|
0.0
|
29
*
|
65.4
*
|
Alcohol
|
No consumption
|
21
|
19.3
|
0
|
0.0
|
139
|
47.6
|
105.78
|
< 0.001
|
Up to 2 drinks a day
|
72
|
66.0
|
10
|
34.5
|
148
|
50.7
|
Regularly over 2 drinks a day
|
13
|
11.9
|
12
|
41.4
|
5
|
1.7
|
Intoxicated at least once a month
|
3
|
2.8
|
7
|
24.1
|
0
|
0.0
|
Awareness of the effects of alcohol on health**
|
Fully aware
|
64
|
58.7
|
10
|
45.5
|
226
|
78.2
|
26.03
|
< 0.001
|
Partially aware
|
29
|
26.6
|
18
|
50.0
|
66
|
21.8
|
None
Without response
|
1
15
|
0.9
13.8
|
1
0
|
4.5
0.0
|
0
0
|
0.0
0.0
|
Future alcohol-related behaviour⸷⸷
|
Quitting alcohol
|
16
|
14.7
|
11
|
37.9
|
21
|
7.2
|
50.45
|
< 0.001
|
Decreasing consumption
|
31
|
28.4
|
4
|
13.8
|
46
|
15.8
|
No change in behaviour
Without response
|
53
9
|
48.6
8.3
|
7
7
|
24.1
24.1
|
212
13
|
72.6
4.4
|
1 Chi-square test, *16 respondents did not answer, ⸷ out of 233 smokers, 205 (88.0%) answered in relation to further smoking behaviour, **15 respondents did not answer, ⸷⸷ 29 respondents did not answer |
It was found that there was a statistically significant difference in the incidence of concurrent consumption of cigarettes and alcohol compared to the study groups (χ2 = 91.97, p < 0.001). At the same time, tobacco and alcohol were consumed by all azoospermic subjects, 76.8% of those with oligospermia and the least of controls. (Graph 1).
Smoking awareness is statistically significantly different depending on the level of education (p < 0.001). It increases in line with the increase in educational level, but at the same time, there is no statistically significant difference concerning further behaviour related to cigarette consumption. Also, knowledge about alcohol is statistically significantly different in relation to education level (p < 0.001), with the highest level of knowledge shown by the most educated respondents. However, the availability of adequate information did not significantly lead to the adoption of healthier lifestyles in relation to the risk factors considered (p = 0.060; p = 0.617 and p = 0.742, respectively) (Table 3).
Table 3
Behaviour, awareness and intentions for future behaviour in relation to education level
|
Education level
|
χ2
|
p1
|
Smoking
|
Primary
|
Secondary
|
University
|
|
Not smoking
|
62
|
43.7
|
50
|
31.4
|
43
|
33.3
|
14.972
|
0.060
|
Up to 10 cigarettes a day
|
63
|
44.4
|
70
|
44.0
|
62
|
48.1
|
Up to 2 packs a day
|
8
|
5.6
|
27
|
17.0
|
16
|
12.4
|
Over 2 packs a day
|
6
|
4.2
|
6
|
3.8
|
2
|
1.6
|
Without response
|
3
|
2.1
|
6
|
3.8
|
6
|
4.7
|
Awareness of the effects of smoking on health
|
Fully aware
|
65
|
45.8
|
120
|
75.5
|
128
|
99.2
|
102.558
|
< 0.001
|
Partially aware
|
71
|
50.0
|
39
|
24.5
|
1
|
0.8
|
None
|
2
|
1.4
|
0
|
0.0
|
0
|
0.0
|
Without response
|
4
|
2.8
|
0
|
0.0
|
0
|
0
|
Future smoking-related behaviour
|
Quitting smoking
|
21
|
14.8
|
39
|
24.5
|
24
|
18.6
|
19.664
|
0.003
|
Decreasing the number of cigarettes
|
24
|
16.9
|
38
|
23.9
|
38
|
29.5
|
No change in behaviour
|
93
|
65.5
|
82
|
51.6
|
67
|
51.9
|
Without response
|
4
|
2.8
|
0
|
0.0
|
0
|
0.0
|
Alcohol
|
No consumption
|
51
|
35.9
|
59
|
37.1
|
48
|
37.2
|
4.445
|
0.617
|
Up to 2 drinks a day
|
76
|
53.5
|
80
|
50.3
|
73
|
56.6
|
Regularly over 2 drinks a day
|
10
|
7.0
|
16
|
10.1
|
6
|
4.7
|
Intoxicated
|
5
|
3.5
|
4
|
2.5
|
2
|
1.6
|
Awareness of the effects of alcohol on health
|
Fully aware
|
64
|
45.1
|
115
|
72.3
|
126
|
97.7
|
94.029
|
< 0.001
|
Partially aware
|
71
|
50.0
|
43
|
27.0
|
3
|
2.3
|
None
|
2
|
1.4
|
0
|
0.0
|
0.0
|
0.0
|
Without response
|
5
|
3.5
|
1
|
0.6
|
0
|
0
|
Future alcohol-related behaviour
|
Quitting alcohol
|
15
|
10.6
|
20
|
12.6
|
15
|
11.6
|
3.517
|
0.742
|
Decreasing consumption
|
35
|
23.9
|
31
|
19.5
|
32
|
24.8
|
No change in behaviour
|
89
|
62.7
|
106
|
66.7
|
81
|
62.8
|
Without response
|
4
|
2.8
|
2
|
1.3
|
1
|
0.8
|
Logistic regression analysis showed that independent statistically significant risk factors for azoospermia were age, knowledge about smoking and alcohol. For oligozoospermia, statistically significant independent risk factors are age, smoking, and alcohol consumption. The most influential risk factor for oligozoospermia is smoking. Smokers are 12 times more likely to develop oligozoospermia than non-smokers (OR 12.311). Risk factors for disturbed normozoospermia are age, smoking, alcohol consumption, and insufficient knowledge of the effects of alcohol in relation to complete knowledge of the impact of alcohol. For a disorder of normozoospermia, smoking is also the strongest risk factor. Smokers are 14.5 times more likely to endanger normozoospermia than non-smokers (OR 14.493) (Table 4).
Table 4
Risk factors for azoospermia, oligozoospermia and normozoospermia (univariate logistic regression)
Risk factors
|
Azoospermia
|
Oligospermia
|
Control group
|
OR
|
95%CI
|
p
|
OR
|
95%CI
|
p
|
OR
|
95%CI
|
p
|
Univariate model
|
|
Age
|
1.072
|
1.026–1.120
|
0.002
|
1.053
|
1.031–1.076
|
< 0.001
|
1.069
|
1.046–1.092
|
< 0.001
|
University degree
|
0.882
|
0.380–2.046
|
0.769
|
1.097
|
0.712–1.691
|
0.673
|
1.056
|
0.695–1.606
|
0.797
|
Smoking
|
5.911
|
0.742–47.121
|
0.093
|
12.311
|
6.492–23.344
|
< 0.001
|
13.279
|
7.136–24.710
|
< 0.001
|
Awareness of smoking effects
|
|
Fully aware
|
RC
|
|
|
RC
|
|
|
RC
|
|
|
Partially aware
|
2.408
|
1.090–5.319
|
0.030
|
1.399
|
0.893–2.190
|
0.142
|
1.753
|
1.132–2.715
|
0.012
|
None
|
19.867
|
1.184–333.271
|
0.038
|
2.130
|
0.132–34.401
|
0.594
|
|
|
|
Alcohol
|
|
|
|
1.571
|
1.257–1.963
|
< 0.001
|
1.820
|
1.458–2.272
|
< 0.001
|
Awareness on alcohol effects
|
|
|
|
|
|
|
|
|
|
Fully aware
|
RC
|
|
|
RC
|
|
|
RC
|
|
|
Partially aware
|
2.808
|
1.261–6.253
|
0.012
|
1.538
|
0.989–2.390
|
0.056
|
1.987
|
1.290–3.061
|
0.002
|
None
|
22.462
|
1.330–379.457
|
0.031
|
2.211
|
0.137–35.716
|
0.576
|
–
|
|
0.999
|
Multivariate model
|
Age
|
1.255
|
1.072–1.471
|
0.005
|
1.104
|
1.070–1.138
|
< 0.001
|
1.138
|
1.099–1.178
|
< 0.001
|
University degree
|
1.034
|
0.139–7.688
|
0.974
|
0.704
|
0.387–1.281
|
0.251
|
0.657
|
0.353–1.225
|
0.187
|
Smoking
|
-
|
|
|
16.002
|
7.850–32.622
|
< 0.001
|
22.828
|
10.70–48.701
|
< 0.001
|
Awareness of smoking effects
|
|
Fully aware
|
RC
|
|
|
RC
|
|
|
RC
|
|
|
Partially aware
|
0.172
|
0.009–3.405
|
0.248
|
1.179
|
0.382–3.643
|
0.775
|
0.642
|
0.195–2.108
|
0.465
|
None
|
-
|
|
1.000
|
43899
|
0.000–
|
1.000
|
–
|
|
|
Alcohol
|
-
|
|
|
1.940
|
1.105–3.404
|
0.021
|
2.556
|
1.414–4.620
|
0.002
|
Awareness of alcohol effects
|
|
Fully aware
|
|
|
|
RC
|
|
|
RC
|
|
|
Partially aware
|
|
|
|
|
|
|
|
|
|
None
|
5.577
|
0.321–96.900
|
0.238
|
1.103
|
0.367–3.312
|
0.861
|
2.209
|
0.692–7.053
|
0.181
|
Hosmer-Lemeshow test
|
0.975
|
|
|
0.290
|
|
|
0.718
|
|
|
OR – odds ratio, 95%CI – 95% confidence interval |