Source: ZDHS,2014



According to figure (3.8), the link between men's cigarette smoking behaviour and regions within Zambia indicated the highest proportion of men who smoked cigarettes came from the Western region (28.22%) while the least proportion of men who smoked cigarettes came from the Southern Region (14.33%). The link between men's cigarette smoking and region was significant (p-value <0.001) varying across all regions in Zambia.

Figure 3.8. Shows % of male smoking by region

Source: ZDHS,2014

3.3 Multivariate Analysis using binary logistic regression models

Table 3.2 presents the odds ratios, significant levels and confidence intervals from the binary logistic regression models estimating the effects of men's age, household wealth index category, and educational level attained as independent variables, as well as the effects of the control variables on men's cigarette smoking behaviour. The first model specified to predict the effects of men's age, household wealth index category and men's educational level attained on men's cigarette smoking behaviour. The second model controls for men's individual background characteristics such as occupation and marital status. The third model controls for men's individual characteristics such as religion, residence and region.

According to table 3.2, the first model illustrates the likelihood of men smoking cigarettes. Results revealed that significantly high for men aged 20-29 years old (OR:7.953; CI:6.43-9.83), men aged 30-39 years (OR:11.165; CI: 9.03-13.7), men aged 40-49 years old (OR:15.464; CI:12.4-19.1), men aged 50-59 years (OR:13.872; CI: 10.9-17.5) in comparison to men aged 15-19 years old (reference category). The likelihood of men smoking cigarettes was significantly low for men from the middle household wealth index (OR: 0.615; CI: 0.54-0.69) and men from the rich household wealth index category (OR: 0.567; CI: 0.50-0.63) in comparison to men from the poor household wealth index category (reference category). The likelihood of men smoking cigarettes was significantly low for men with secondary education (OR:0.989; CI:0.53-0.80) and men with higher education (OR: 0.272; CI:0.20-0.36) in comparison to men with no education (reference category).

In the second model, the trends of smoking was significant and consistently high for men aged 20-29 years old (OR:7.077; CI:5.63-8.88), men aged 30-39 years (OR:10.036; CI: 7.79-12.9), men aged 40-49 years old (OR:14.003; CI:10.8-18.1), men aged 50-59 years (OR:12.700; CI: 9.64-16.7) in comparison to men aged 15-19 years old. The trends of smoking cigarettes was significant and consistently low for men from the middle household wealth index (OR:0.578; CI:0.51-0.65) and men from the rich household wealth index category (OR: 0.504; CI: 0.44-0.57) in comparison to men from the poor household wealth index category. The likelihood of men smoking cigarettes was significant and consistently low for men with secondary education (OR:0.650; CI:0.52-0.79) and men with higher education (OR: 0.313; CI:0.23-0.42) in comparison to men with no education. Men's occupation, the likelihood of cigarette smoking was significantly high for men with clerical and sales occupations (OR:1.361; CI:1.10-1.67), men with agricultural occupation (OR:1.310;CI: 1.09-1.56), men with skilled and unskilled manual occupations (OR:1.625;CI:1.33-1.97) and men with service and other occupations (OR:1.853;CI:1.48-2.31) in comparison to men with not working (reference category). With reference to men's marital status, the likelihood of cigarette smoking was significantly high for men who were separated via divorce, widowers and no longer cohabiting (OR:2.112; CI:1.71-2.60) in comparison to men who were never married (reference category).

In the third model, the trend of men smoking cigarettes was significant and consistently high for men aged 20-29 years old (OR:6.759; CI:5.37-8.50), men aged 30-39 years (OR:9.326; CI: 7.22-12), men aged 40-49 years old (OR:13.180; CI:10.1-17.1), men aged 50-59 years (OR:11.451; CI: 8.67-15.1) in comparison to men aged 15-19 years old. With reference to men's household wealth index category, the trend of men smoking cigarettes was significant and consistently low for men from the middle household wealth index (OR:0.566; CI:0.49-0.64) and men from the rich household wealth index category (OR: 0.375; CI: 0.31-0.44) in comparison to men from the poor household wealth index category. With reference to men's educational level attained, the likelihood of men smoking cigarettes was significant and consistently low for men with secondary education (OR:0.623; CI:0.50-0.76) and men with higher education (OR: 0.287; CI:0.21-0.39) in comparison to men with no education.

Men's occupation, the likelihood of cigarette smoking was significant and consistently high for men with clerical and sales occupations (OR:1.264; CI:1.02-1.55), men with agricultural occupation (OR:1.424; CI:1.18-1.71), men with skilled and unskilled manual occupations (OR:1.557; CI:1.27-1.89) and men with service and other occupations (OR:1.763;CI:1.40-2.21) in comparison to men with not working. With reference to men's marital status, the trends of cigarette smoking was significant and consistently high for men who were separated (OR:2.110; CI:1.70-2.60) in comparison to men who were never married. With reference to men's religious affiliation, the trends of cigarette smoking was significantly low for men who were affiliated to the protestant religion (OR:0.684; CI:0.61-0.76) in comparison to men affiliated to the Catholic religion (reference category). Again, the trend of cigarette smoking was significantly high for men who affiliated to other religions (OR:1.769; CI:1.24-2.52) in comparison to men affiliated to the Catholic religion. With reference to men's residences, the trend of cigarette smoking was significantly low for men resident in the rural areas (OR:0.617; CI:0.57-0.78) in comparison to men resident in the urban areas (reference category). The likelihood of cigarette smoking was significantly high for men resident in Copperbelt region (OR:1.873; CI:1.52-2.29), men resident in Luapula region (OR:1.644; CI:1.31-2.05), men resident in Muchinga region (OR:1.443;CI:1.13-1.83) and men resident in Western region (OR:1.808;CI:1.42-2.28) in comparison to men resident in the Central region of Zambia (reference category).

Table 3.2 Regression analysis Results Presents the odds ratios, significant levels and confidence intervals from the binary logistic regression models

	Model 1: OR CI SIG	Model 2: OR CI SIG	Model 3: OR CI SIG
15-19-year-old 20-29-year-old	RC 7.953(6.43-9.83) **	RC 7.077(5.63-8.88) **	RC 6.759(5.37-8.50) **
30-39-year-old	11.165(9.03-13.7) **	10.036(7.79-12.92) **	9.326(7.22-12.03) **
40-49-year-old	15.464(12.4- 19.1) **	14.003(10.80-18.15) **	13.180(10.14-17.12) **
50-59-year-old Poor	13.872(10.9- 17.5) ** RC	12.700(9.64-16.72) ** RC	11.451(8.67-15.11) ** RC
Middle	0.615(0 .54-0.69)**	0.578(0.51-0.65) **	0.566(0.49-0.64) **
Rich No Education	0.567(0.50-0.63) ** RC	0.504(0.44-0.57) ** RC	0.375(0.31-0.44) ** RC
Primary Education	0.989(0.81-1.19)	0.984(0.80-1.19)	0.996(0.81-1.21)
Secondary Education	0.661(0.53-0.80) **	0.650(0.52-079) **	0.623(0.50-0.76) **
Higher Education Not Working	0.272(0.20-0.36) **	0.313(0.23-0.42) ** RC	0.287(0.21-0.39) ** RC
Professional/Technical/Managerial		0.940(0.67-1.30)	0.949(0.68-1.32)
Clerical/Sales		1.361(1.10-1.67) **	1.264(1.02-1.55) *
Agriculture		1.310(1.09-1.56) **	1.424(1.18-1.71) **
Skilled/Unskilled manual		1.625(1.33-1.97) **	1.557(1.27-1.89) **
Service/others Never Married		1.853(1.48-2.31) ** RC	1.763(1.40-2.21) ** RC
Married		0.875(0.75-1.01)	0.944(0.81-1.09)
Living with partner		0.845(0.49-1.43)	0.764 (0.44-1.30)
Separated Catholic		2.112(1.71-2.60) **	2.110(1.70-2.60) ** RC
Protestant			0.684(0.61-076) **
Muslim			1.278(0.80-2.02)
Others Urban			1.769(1.24-2.52) ** RC
Rural Central			0.671(0.57-0.78) ** RC
Copperbelt			1.873(1.52-2.29) **
Eastern			1.011(0.82-1.24)
Luapula			1.644(1.31-2.05) **
Lusaka			1.196(0.96-1.47)
Muchinga			1.443(1.13-1.83) **
Northern			1.229(0.98-1.53)
North Western			1.025(0.77-1.34)
Southern			0.852(0.69-1.05)
Western			1.808(1.42-2.28) **
N	14,762	14,689	14,632

* p<0.05; ** p<0.01

3.4 Testing hypothesis

In view of the study hypotheses, the results from the multivariate binary logistic regression models reveal men who belong to the middle and rich household wealth index categories are consistently less likely to smoke cigarettes across all three models estimate. Men with secondary and higher levels of educational attainment are consistently less likely to smoke cigarettes across all three models. With reference to men who employed in professional/technical/managerial occupations even though not significant, they are consistently less like to smoke cigarettes as observed across model two and three. Equally, with regarding marital status, men who are married and men living with a partner or cohabiting even though not significant are consistently less likely to smoke cigarettes observed across model two and three. The result revealed that men's age and place of residence particular from the rural were associated with higher rate on smoking cigarette across all three models.



4. DISCUSSION, LIMITATION, CONCLUSION AND RECOMMENDATIONS

4.0 Introduction

This chapter includes discussion, limitations, conclusion and recommendations. The major goal of the study was to examining and investigate the socio-economic and demographic factors linked with smoking habit among men in Zambia and contribute to the literature on smoking cigarettes behaviour.

4.1 Discussion

Findings made it clear that age had a significant correlation on the initiating cigarettes smoking habit for men in Zambia, unchanging pattern of smoking was concentrated and predominantly in all ages. However, the odds increased among the older age groups. In particular, individuals who was in the older age group was in a risk to smoke cigarette in comparison to those in the younger age group (15-19 years old). Except the consequence was great and although there was, a decrease after the age of 50-59 years, moreover, the odds of smoking was never smaller than in the reference category.

The possible reasons could be ignores, traditions, and changes in an person income caused by poverty in Zambia. Studies also, found that smoking was a physical and psychological forces that could influenced commenced smoking cigarette to release pain. Brain changes and development as well emotional are the factors that changing from one stage to another as well as the age does over time. In addition, longer smoker's man from his adolescent age had developed habits towards smoking cigarette and was less likely and hard to quit smoking as he grew older. On the one hand, lack of appropriate awareness for adults on smoking effects. Seeking popularity among peers could linked to smoking as many Zambian men believes that cigarette is a symbol of authority for a strong and famous man. Also, tobacco farms/plantations and affordable cigarette prices in Zambia can be a strong contributor for smoking behaviour. Early studies have shown that smokers grow up with more problems that are psychological depression and anxiety which could associate to the age (Breslau and Peterson, 1996). In U. S, Madagascar (Mamudu et al, 2013), Ghana (Doku et al, (2013), Dickson and Ahinkorah, (2017) and Townsend et al.,(2006), found same situation, smoking habit was developed as age increased.

There was a significant link between wealth index and cigarette smoking, findings shows that the middle and rich man was less likely to initiating smoking habit. Men with low- income status were more likely to smoke; the prevalence systematically decreases for the middle and rich. In other study done by Jarvis and Wardle (2005), observed that high risk to cigarette smoking increased to those in low-income groups. Shin et al, (2013), in their studies found that those groups with low SES were more often adopt smoke behaviour as a way of coping with the stress, shame and humiliation that come with such status.

Zambia is among the middle developing country where the population living in extreme poverty (more than 60% are poor). Hence, lack of income, job or low wages can be possible factors contributing men involving in smoking. Smoking has a direct role and link to the poverty cycle among the poor people. Zambian economy are based on mining industry. Copper mining is crucial to economic prospects that covers 85% of all country's exports earning, but worries still that the economy does not differ enough to deal with the collapse of international copper prices. Hence, we can say that Zambia need to boost her economy so that to eliminate poverty by enhancing rural population which are many and are the most poor. Hu et al, (2005), in China, revealed that poor rural family spent over 10 percent of their total income expenses on cigarettes.

The study also found that education was a significant linked with smoking habit. The odds of smoking seem to decrease as the level of education increased. Particularly, men with secondary and higher education were less likely to smoke in comparison to those with no education or primary level. Education can reflect on one's knowledge and ability to make health decisions, including smoking habit. Education's enhance and enable people to understand both negative and positive impacts of cigarette (Villanti et al., 2016. Education level was one of the predictors for smoking habit in this study, and findings show that education levels differences in Zambia was strongly connected with poverty and health risks. In one hand, communication barriers, seven common languages before English used in primary and secondary schools. Pupils and students use Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja and Tonga. This can be a reasons why low level educated people were more likely to initiate smoking due to the fact that they do not have enough information on smoking risks. On the other hand, cigarette health warning are written in English while many cannot read and understand the language written. Findings shows that those with no education and primary education level were in high risk of smoking cigarette. The same situation found in the U.S (Mettlin, 1973; Shin et al, 2013), where educated groups were less likely to smoke cigarette in comparison to less educated.

The results shows that type of job has influenced smoking, men with the clerical/sales jobs were more likely to smoke than those with not working. In addition, men with agricultural works, skilled/unskilled manual workers, and services were in higher risk to initiating smoke compared with men not working. Possible reasons could be nature and hardship of the jobs, alcoholism, pear group at work low wages and income from these jobs could influenced habit towards smoking cigarette in Zambia. Also, low cigarette price, buying cigarette in the country is affordable with everybody. For the men owned tobacco farms that are common in Zambia could also influence smoking cigarette from the young age to the older age. Furthermore, stress can be possible reasons influencing smoking habit among other factors. These results agreed with previous studies in Nepal which found that adults in the workplace were more likely to smoke than those with no jobs (Aryal et al, 2014). Type of occupation was also significantly associated with cigarette smoking in Madagascar (Mamudu et al., 2013), and China (Wang et al., 2018).

Findings shows that there was a significant correlation between marital status and smoking. Particular, separated men were more likely to smoke cigarette in comparison to those never married. In explaining how separated leads to high-risk prevalence of cigarette smoking Loke et al (2010), argue that stressful and creation of new health behaviour will occur. In the Zambian case social problems, poverty and lack of basic needs could led men towards smoking habits to release stress. HIV infection and polygamy could possible led to stress among men, hence, initiated new behaviours towards smoking.

In fact, marriage takes away some of the stressful situations that may lead to cigarette smoking. Again, partners or marriages regulate health behaviours of each other surveillance (Hill et al., 200. Strong bond within the family contributes significantly people to eliminate smoking behaviour (Loke et al., 2010). This finding could attribute to the link between divorce and health behaviour. It expected that formerly married men in their bid to overcome the consequences of divorce or death of a partner would turn to cigarette smoking. In the Scandinavian countries Lindström et al., (2000), found that partner was the most person linked to the social networking, marriages or relationships which increased support information, material and emotional issues, and gave marriage a greater proportion to avoiding smoking habit.

Type of residence had statistics significant on smoking behaviour. The place of residence also highlighted the important connection with smoking cigarettes in Zambia; rural men show the odds of higher risk in cigarette smoking. Studies found that men, as they change their place of residence, were more likely to initiate smoking habit. This is quite different from that observed in other studies elsewhere, that showed a significant difference on smoking between rural areas and urban. Other empirical evidence states that people from the rural had less likely to initiate smoking habit because exposures to the new lifestyle compared to urban is low (Pampel, 2008), although some studies have not seen the ratio in this forecast (Doescher et al., 2006). New lifestyle starting from the cities/towns and later spread to the rural areas. However, shops and cigarette manufacturing are mainly located in cities which simplifies and encourages cigarette smoking habits in urban areas. Bobak et al, (2000), argue that given relationship between behaviours and the social environment, changing environments and interactions within and between environments shape behaviours and contributing towards adopting a new behaviour of a person. Possible reasons in the Zambian case could be, globalization is everywhere now and media through television, radio and other advertisements strategies that spread and targeted populations as it focused to increase income by sales her services and products. Listening and watch does not need any training but is just watch or listening and practice. These can contribute smoking habit among men in Zambia.

The findings reveal that men residence in the following regions; Copper belt, Luapula, Muchinga, and Western were in the higher risk of cigarette smoking habit. Possible explanations linked with these could be nature of key economic activities in the Copperbelt region and Western region being mining, tourism, and constructions that have attracted many foreigners particularly Chinese's companies and Indian businesspersons as well as tourists whom their mother countries are in a high pick of smoking. However, behaviour towards cigarette smoking among workers in mines is very high not only in Zambia but also around the world. In addition, the odds of high cigarette smoking in other regions such as Luapula, and Muchinga, could be due to the fact that tobacco cultivated in these regions. SES among men also is very low and children tend to learn smoking from a very early and tender age, adopting behavior from their parents' farmers and other adults working group who are smoke. Luapula and Muchinga was one region before 2011 where it divided into two, hence, they share culture and value as well as poverty cycle as their population are agriculture and fishing activities dependent which does not pay well in Zambia.

Also, results revealed that by religion, higher proportion of men who smoked cigarettes were men who belonged to religious groups classified in Zambia as others. While the least proportion of men who smoked cigarettes was, men affiliated to the Protestant faith. The correlation between smoking and religion was with variations across the various religious groups in Zambia. Evidence from Ethiopia (Schoenmaker et al., 2005), and in Nepal (Aryal et al, 2014), suggested that religion had a strong connection among society, constitutes social network where not only social support exists but also behaviour shared. Religious promotes and enhancing behaviours change such as no cigarette smoking, alcohol use, and other bad habits according to their beliefs.

4.2 Limitation of the study

In the African perceptive, smoking characterized by gender and age. Culturally women are restricted and prohibited from smoking cigarette or acknowledging publicly the fact that they smoke cigarettes. The link between SES and smoking may vary from gender to rural areas, the differences in the economic position seemed to be different from gender.Men are the most predominated in all economic spheres in Zambia. Gender bias was also the limitation of this study since the researcher relied and focused on men only aged 15-59 years old.

4.3 Conclusion

It has found that smoking cigarette is most prevalent and associated with rural adult's poor men with a low level of education, showing overall the rise in popularity smoking cigarette among men in rural areas is alarming in Zambia. A large concentration of smokers among non-educated and poor people also emphasizes the possible differences and lack of educational equity and health information on smoking effects in general. Also, study found that men trapped in a dangerous zone as cigarette epidemic leads to high mortality rates in young and economically productive age groups.

Men is the breadwinner in the Zambian context, hence the death of men or ill health condition will hinder poverty prevention effort, at the end have a stagnant economy in the society as well as the nation at large. Design and implementation of programs that prohibit the establishment and maintenance of smoking behaviour between men and the whole communities are in high demand in Zambia. In addition, we found that men living in a low SES group were in a high risk initiating smoking habit, men who belong to the poor category of the wealth index, less educated or no education, clerical/sales, agriculturalists, manual workers and services were more likely to smoke cigarette. In addition, separated men, residing in the rural were more like to smoke cigarette than men residing in the urban areas as well as those men affiliated from other denomination were more likely to smoke. Hence, a combination of action is required, with wider attempts to address SES differences and health risks of smoking among the Zambian population. Handle with care for those groups with high prevalence of smoking in Zambian societies during sensitization programs is in a higher demand. Concerted efforts are needed to empower men to eliminate smoking, promote education and encourage the utilization of entrepreneurship targeting the rural poor men

4.4 Further Research

Across administrative regions in Zambia, smoking varies substantially and age has shown high risk initiating smoking. However, smokers and non-smokers all face same consequences hence, further research on ineffectiveness of tobacco control policy in Zambia will enhance and reinforcement information that can be used to develop effective interventions to eliminate smoking habit in Zambia.

4.5 Recommendations

Based on the findings of this study, smoking habit had a higher peak from age 20-50 years old, to the poor and less educated groups and rural resident, The following, therefore, are the recommendation of this study:

1 . Education of both poor and rich is good and should be more encouraged. It can help to build more positive, high self-esteem among men as grow up, thus, eliminating instances of smoking habit. Educated and rich men are less likely to smoke cigarette. The SES and demographic gaps widened situations that tend to consolidate the lower status of groups, and one of such is illiteracy and low educational status and its attendant consequences such as unemployment, and poverty. However, encouraging more health education and the use of country's common languages from the primary schools to the higher level should be encouraged.

2 . Awareness, health education on smoking should be in Zambian curricular, all these could bring about some redress and promote health awareness on smoking cigarette behaviour in a long-term goals.

3. Immediate short-term measure to mitigate smoking prevalence in Zambia would be for the government and other stakeholders to invest in programs. Promoting health awareness reorientation and attitudinal transformation changing the current poor value attributed to the most men. Establish and encourage entrepreneurs' groups, provide skills and small capitals so that to enhance men's income that could eliminate poverty and health risks in general.

4. Religious-affiliated people and leaders, through their teachings, could be a strong voice against smoking habit and be persuaded to be strong agents in the drive for value reorientation to quell instances and the prevalence of tobacco use as well as against cigarette smoking in Zambia.

5. There is a need to speed up the implementation of the following; intervention required should focus on restructuring in behavioural issues that focus on the most vulnerable groups. Sensitization programs should target all groups of poor, less educated, unemployed and all manual workers men so that to build self- awareness on the harm of smoking.

6. All programs aimed at meaningfully forestalling tobacco productions and smoking cigarette prevalence in Zambia should adequately include both rural and urban because without this low SES groups might continue to suffer irrespective of their wealth, level of education, social status, and prestige

7. Support reforms shift from tobacco to other key economic activities instead of tobacco production and introduce entrepreneurship skills which is in higher demand in to empower all low SES men.

8. Improve or establish psychological centres where people can visit and get free advice or counselling during their problems since smoking habit for some reasons was a psychological problems since many is poor to afford paying specialists.



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APPENDIX I

Table 2.1 Shows Study Variables

Variable	Measurement
Cigarette Smoking	0 = Non cigarette smoker 1 = Cigarette Smoker
Age	1 = 15-19 years old (Reference category) 2 = 20-29 years old 3 = 30-39 years old 4= 40-49 years old 5= 50-59 years old
Wealth Index	1 = Poor (Reference category) 2 = Middle 3 = Rich
Education	1 = No Education (Reference category) 2 = Primary Education 3 = Secondary Education 4 = Higher Education
Occupation	1 = Not Working (Reference category) 2 = Professional/Technical/Managerial 3 = Clerical/Sales/service 4 = Agriculture 5 = Manual 6 = Others
Marital Status	1 = Never Married (Reference category)

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