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  • Research note
  • Open Access

Satisfaction with job and family life, and association with smoking and alcohol drinking behaviors among young men in Malawi: analysis from a multiple indicator survey

BMC Research Notes201912:57

https://doi.org/10.1186/s13104-019-4096-4

  • Received: 11 December 2018
  • Accepted: 17 January 2019
  • Published:

Abstract

Objective

The objective of the present study was to investigate if satisfaction with job and family life has any connection with smoking and alcohol drinking behavior among young men in Malawi.

Results

Results of multivariable logistic regression analysis indicate that compared to men who were unemployed, those who were dissatisfied were 0.90 times less likely to be non-smokers [OR = 0.90; 95% CI = 0.36–2.24], 0.83 times [OR = 0.83; 95% CI = 0.63–1.08] as likely to try drinking alcohol. Among those who reported being satisfied with job, the odds of trying alcohol was relatively more [OR = 0.77; 95% CI = 0.63–0.93], however the odds of cigarette smoking were less [OR = 1.05; 95% CI = 0.48–2.31] relative to those who were unemployed. Results also showed that not being satisfied with overall life increased the odds of smoking and alcohol drinking [OR = 0.60; 95% CI = 0.24–1.46] and [OR = 0.95; 95% CI = 0.72–1.24] respectively compared to those who were satisfied with overall life.

Keywords

  • Satisfaction
  • Job
  • Overall family life
  • Alcohol drinking
  • Smoking
  • Global health
  • Malawi

Introduction

Smoking and alcohol intake are growing public health concerns. The World Health Organization (WHO) estimates that there are more than 1 billion users of tobacco worldwide, more than 80% of whom are males [1]. In Africa in particular, the gap between male and female smokers is narrowing with more women smoking than before [2]. However, there are gender variations in the prevalence of smoking in different countries; in Malawi, a study has reported that more males (25.9%) compared to females (2.9%) are smokers [3]. In fact, Malawi is one of the sub-Saharan African countries with a higher prevalence of smoking [2, 3].

Concerning alcohol intake, WHO estimates almost 2 billion consumers, 76 million of whom are already experiencing alcohol use disorders [4]. The rate of alcohol consumption in Africa is predicted to be on the increase owing to the emergence of new consumers like young people and women [4]. It has also been noted that the increase in alcohol consumption is high in underdeveloped countries and such increases are likely to hinder further development [5]. Malawi, a developing country in Africa, has little or no available information about alcohol consumption among its population.

Smoking and alcohol intake both have multiple causes. For tobacco use, some documented factors can be grouped into social and physical environmental factors such as religious activity, educational attainment, socioeconomic status, peer influences and cognitive decision-making factors about tobacco use and its consequences [6]. A study has also found parental smoking and the associated nicotine dependence as a risk factor for adolescent smoking [7]. Nevertheless, other studies have reported personality factors, cognitive factors, coping resources, family influences, media influences, tobacco availability, occupational stress, peer pressure and domestic stress as factors underlying smoking habits [810].

For alcohol intake, a study has reported that the presence of high antisocial behavior, high impulsivity and high externality are factors related to alcohol dependence specifically for women [11]. Yet, another study has highlighted genetic risk factors, biological markers, childhood behaviors and psychiatric disorders to be associated to alcohol intake [12]. Also, some studies found that students who dropped out of high school were more than 6 times as likely to resort to alcohol use/abuse in adulthood. The studies thus concluded that education as well as race were associated with higher alcohol consumption behaviors [13, 14].

Besides education, wealth index has been often cited as a factor related to smoking and alcohol consumption. In one study, an increased risk of drinking in wealthier individuals was found with a rather lower risk of smoking [15]. In another study, the rise in wealth inequity was independently associated with alcohol drinking problems only [16]. Nonetheless, not only is there uncertainty about factors driving smoking and drinking, literature on this topic is also limited especially in a developing country like Malawi with likely fewer and less paid jobs but larger families. It was thus necessary to investigate if satisfaction with job and family life has any connection with smoking and drinking behaviors among young men in Malawi.

Main text

Materials and methods

The study used data from the latest (5th round of the) Multiple Indicator Cluster Survey (MICS) that was conducted in Malawi from 2013 to 14. The MICS program was developed by UNICEF, it is a global initiative, aimed at providing internationally comparable data on various health indicators and it is operational in more than 100 countries. The outcomes of the surveys have been instrumental in monitoring progress towards the millennium development goals (MDGs) and developing health policies and programs to meet internationally agreed commitments by participating nations.

MICSs employ a multistage cluster-sampling strategy to select country representative samples. For the 5th MICS conducted in Malawi, the sample was selected from the Northern, Central and Southern Regions and included both urban and rural areas across 27 districts of the country (excluding Likoma). An English questionnaire that was pretested and then translated into Chichewa and Tumbuka was used for data collection. The Malawi 2013–2014 MICS successfully interviewed 6842 men aged between 15 and 49 years. Further details regarding the survey are published in reports elsewhere [1, 2].

Variables

Study variables were characteristics of participants from whom data was collected. Main outcome variables were self-reported past or current smoking/alcohol drinking, or both smoking (Yes, No) and alcohol drinking (Yes, No). Explanatory variables were satisfaction with job and life overall (Very satisfied, somewhat satisfied, neither satisfied nor unsatisfied, somewhat unsatisfied, very unsatisfied), Age (15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49); Region (Northern, Central, Southern); Religion (Christian, Islam, Other); Education (None, Primary, Secondary, Higher); Wealth index (Poorest, Second, Middle, Fourth, Richest).

Data analysis

Data were analyzed with SPSS version 24. Sample characteristics were presented with descriptive statistics such as frequencies and percentages. The proportion of sample population with smoking and drinking habits were calculated using cross-tabulation for all the explanatory variables. Chi squared bivariate tests were used to measure the significance of the associations. Following that, binary logistic regression analyses were run to measure the multivariate association between smoking and drinking with self-reported satisfaction with job and life. The results were reported as odds ratios and 95% CI. P-value were regarded as significant at 5% for all analyses.

Results

Characteristics of study participants

The characteristics of study participants are presented in Table 1. More than half (58.6%) of the participants were aged 15–19 years and 48.2% of them were residing in the southern regions of the country. Majority of the participants (81.1%) were Christians, most of whom (62.4%) had attained only the primary level of education. Seven hundred and thirty-nine (26.2%) of the participants were from households with the richest wealth quintile and 44.6% of them were satisfied with their jobs while 88.5% of them were satisfied with their overall life. About half (50.6%) of the participants were not currently smoking tobacco while 70.8% of them have never drank alcohol.
Table 1

Sample characteristics (n = 2824), Malawi MICS 2013–2014

Variables

N

%

Age

15–19

1654

58.6

20–24

1170

41.4

Region

Northern

363

12.9

Central

1100

38.9

Southern

1361

48.2

Religion

Christian

2291

81.1

Islam

418

14.8

Other

115

4.1

Education

None

69

2.4

Primary

1761

62.4

Secondary

927

32.8

Higher

66

2.3

Wealth index quintile

Poorest

472

16.7

Second

511

18.1

Middle

512

18.1

Fourth

591

20.9

Richest

739

26.2

Satisfaction with job

Unemployed

1176

41.2

Unsatisfied

407

14.3

Satisfied

1273

44.6

Satisfaction with overall life

Unsatisfied

327

11.5

Satisfied

2524

88.5

Currently smoking cigarettes

Yes

774

49.4

No

794

50.6

Ever drunk alcohol

Yes

825

29.2

No

1999

70.8

N frequency, % frequency in percentage

Prevalence and correlates of smoking and alcohol drinking among young men in Malawi

Prevalence of smoking and drinking across participants’ characteristics are presented in Table 2. Smoking and drinking was more prevalent among participants who ended their education at primary school level. While participants with the poorest household wealth were more likely to smoke, those with the richest household wealth were more likely to drink. Results of multivariable logistic regression analysis indicate that compared to men who were unemployed, those who were dissatisfied were 0.90 times less likely to be non-smokers [OR = 0.90; 95% CI = 0.36–2.24], 0.83 times [OR = 0.83; 95% CI = 0.63–1.08] as likely to try drinking alcohol. Among those who reported being satisfied with job, the odds of drinking alcohol were significantly higher [OR = 0.77; 95% CI = 0.63–0.93]. Results also showed that not being satisfied with overall life increased the odds of smoking and alcohol drinking [OR = 0.60; 95% CI = 0.24–1.46] and [OR = 0.95; 95% CI = 0.72–1.24] respectively compared to those who were satisfied with overall life (Table 3). However, these findings were not statistically significant.
Table 2

Prevalence of past and or currently smoking and alcohol drinking across participants’ characteristics in Malawi (n = 2824)

 

Smoking

p

Drinking alcohol

p

Education

< 0.0001

 

< 0.0001

None

5.00

2.40

Primary

32.60

25.60

Secondary

11.20

15.20

Higher

0.50

2.30

Wealth index

< 0.0001

 

0.041

Poorest

13.50

7.10

Second

11.60

8.20

Middle

9.80

8.80

Fourth

8.20

9.50

Richest

6.20

11.90

Satisfaction with job

0.651

 

< 0.0001

Unemployed

6.00

9.40

Dissatisfied

6.30

4.30

Satisfied

15.90

14.10

Satisfaction with overall life

0.253

 

0.585

Dissatisfied

4.40

3.30

Satisfied

23.50

24.40

P P-value

Table 3

Association between satisfactions with job and family life and ever trying smoking, drinking, or trying both among men in Malawi (multivariate regression analysis)

 

Smoking

Drinking alcohol

aOR (95% CI)

aOR (95% CI)

Unemployed

Satisfaction with job

Dissatisfied

0.90 (0.36–2.24)

0.83 (0.63–1.08)

Satisfied

1.05 (0.48–2.31)

0.77 (0.63–0.93)

Satisfaction with overall life

Satisfied

  

Dissatisfied

0.60 (0.24–1.46)

0.95 (0.72–1.24)

aOR adjusted odds ratio

This study examined the connection between satisfaction with job and family life and smoking and drinking among men in Malawi. Results show that when compared with those without a job, young men who had a job and were satisfied were relatively more likely not to resort to cigarette smoking. However, those who had a job but were dissatisfied were more likely to resort to smoking than those who were without a job. This finding is consistent with those of previous studies which found that the odds of smoking among those who were unemployed were greater compared to higher managers and professionals [17, 18]. Although the precise mechanism by which unemployment is related to smoking has not been well explored in studies, the possible role of psychosocial factors underlying this relationship such as one’s inability to control emotions have been hinted [17].

Regarding the association of satisfaction/dissatisfaction with job and smoking, this study revealed that those who were dissatisfied with their job were more likely to smoke than those who were unemployed. This is also consistent with results of previous studies demonstrating that the impact of working conditions/job dissatisfaction is related with smoking [19, 20]. Our study also revealed that dissatisfaction with overall family life was associated with higher smoking prevalence. This is also consistent with results of similar [2022]. It is perceived that cigarette smoking relieves the stress arising from dissatisfaction with family life [21, 22].

Our study observed no increase in drinking behavior related to unemployment but only changes in the drinking patterns. This is similar to observations from other studies arguing that unemployment does not lead to alcohol consumption [23, 24]. Also, we found no significant relationship between drinking and overall satisfaction with life. However, it has be suspected that both dissatisfaction with life and unemployment are associated with low socio-economic status which might lead to actual reduction in drinking habit due in part to the economic situation [2527].

Education and wealth status were consistently associated with both smoking and alcohol consumption. More educated participants were less likely to resort to both smoking and alcohol consumption. Previous studies have reported similar findings, with low education being noted as an independent risk factor for smoking and alcohol intake [2830].

With regards to wealth index and association with smoking and drinking behavior, non-linear relationships were observed. While the poorest are more likely to resort to smoking and alcohol consumption compared to the poor and middle-income individuals, the relationship changes when wealth index quintile improves; the rich and richest are more likely than middle income and poor household individuals to resort to smoking and drinking. Similar studies have reported these same findings [31, 32].

Limitations

Our findings might be limited considering the secondary nature of the data we used which allowed us little control over the variables to include in our analysis, and the fact that we assessed only the association of satisfaction with job and family life, with smoking and drinking while omitting variables such as ethnicity, marital status, beliefs, values and attitudes and men’s age which might influence smoking and drinking behaviors. However, we worked within the confines of the objectives and other correlates of smoking and drinking could be explored in another study.

Abbreviations

aOR: 

adjusted odds ratio

CI: 

confidence interval

OR: 

odds ratio

MDG: 

millennium development goal

MICS: 

multiple indicator cluster survey

N: 

frequency

OR: 

odds ratio

WHO: 

World Health Organization

Declarations

Authors’ contributions

SY and GB contributed to the conception and design of the study. SY did the acquisition of data. SY, GB and AB conducted the statistical analysis and interpreted the original results. All authors read and approved the final manuscript.

Acknowledgements

The authors thank the MICS program for their support and for free access to the original data.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

Data for this study were sourced from the UNICEF website: http://mics.unicef.org/.

Consent to publish

Not applicable.

Ethics approval and consent to participate

Ethics approval for this study was not required since the data is secondary and is available in the public domain.

Funding

The authors have no support or funding to report.

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.

Authors’ Affiliations

(1)
School of International Development and Global Studies, Faculty of Social Sciences, University of Ottawa, 120, University Private, Ottawa, ON, K1N 6N5, Canada
(2)
Interdisciplinary School of Health Sciences, Faculty of Health Sciences, University of Ottawa, 25 University Private, Ottawa, ON, K1N 7K4, Canada

References

  1. WHO. Tobacco or health: a global status report. (Book, 1997) [WorldCat.org]. Geneva: World Health Organization; 1997. http://www.worldcat.org/title/tobacco-or-health-a-global-status-report/oclc/37385998. Accessed 12 Nov 2016.
  2. Taha A, Ball K. Smoking and Africa: the coming epidemic. BMJ. 1980;280(6219):991–3.PubMedView ArticleGoogle Scholar
  3. Brathwaite R, Addo J, Smeeth L, Lock K. A systematic review of tobacco smoking prevalence and description of tobacco control strategies in sub-Saharan African Countries; 2007 to 2014. PLOS ONE. 2015;10:7.View ArticleGoogle Scholar
  4. Francis JM, Grosskurth H, Changalucha J, Kapiga SH, Weiss HA. Systematic review and meta-analysis: prevalence of alcohol use among young people in eastern Africa. Tropical Med Int Health. 2014;19(4):476–88.View ArticleGoogle Scholar
  5. Hoel E, Azalde G, Munthali AC, Eide AH, Natvig H, Braathen SH. Context and consequences of liquor sachets use among young people in Malawi. Afr J Drug Alcohol Stud. 2014;13:2.Google Scholar
  6. Preventing tobacco use among youth and young adults: a report of the Surgeon General. Rockville, MD.: US Dept. of Health and Human Services, Public Health Service, Office of the Surgeon General; 2012.Google Scholar
  7. Selya AS, Dierker LC, Rose JS, Hedeker D, Mermelstein RJ. Risk factors for adolescent smoking: parental smoking and the mediating role of nicotine dependence. Drug Alcohol Depend. 2012;124(3):311–8.PubMedPubMed CentralView ArticleGoogle Scholar
  8. Ah DV, Ebert S, Ngamvitroj A, Park N, Kang D-H. factors related to cigarette smoking initiation and use among college students. Tob Induced Dis Tobacco Induced Dis. 2005;3(1):27.View ArticleGoogle Scholar
  9. Scarinci IC, Silveira AF, Santos DFD, Beech BM. Sociocultural factors associated with cigarette smoking among women in Brazilian worksites: a qualitative study. Health Promotion Int. 2007;22(2):146–54.View ArticleGoogle Scholar
  10. Nizami S, Sobani ZA, Raza E, Baloch N, Khan JA. Causes of smoking in Pakistan: an analysis of social factors. J Pak Med Assoc. 2011;61(2):198.PubMedGoogle Scholar
  11. Poikolainen K. Risk factors for alcohol dependence: a case-control study. Alcohol Alcohol. 2000;35(2):190–6.PubMedView ArticleGoogle Scholar
  12. Youth Drinking: Risk Factors and Consequences—Alcohol Alert No. 37-1997. US National Library of Medicine. US National Library of Medicine. http://pubs.niaaa.nih.gov/publications/aa37.htm. Accessed 12 Nov 2016.
  13. Crum RM, Helzer JE, Anthony JC. Level of education and alcohol abuse and dependence in adulthood: a further inquiry. Am J Public Health. 1993;83(6):830–7.PubMedPubMed CentralView ArticleGoogle Scholar
  14. Assari S, Lankarani MM. Education and alcohol consumption among Older Americans; black-white differences. Front Public Health Front Public Health. 2016;2016:4.Google Scholar
  15. van Kippersluis H, Galama TJ. Why the rich drink more but smoke less: the impact of wealth on health behaviors. RAND Working Paper Series WR-988; 2013. https://doi.org/10.2139/ssrn.2252071.
  16. Jirapramukpitak T, Abas M, Tangchonlatip K, Punpuing S. The effect of asset-based wealth inequality on problem drinking among rural Thai elders: a prospective population-based cohort study. Soc Sci Med. 2014;100:107–14.PubMedPubMed CentralView ArticleGoogle Scholar
  17. Vogli RD. Unemployment and smoking: does psychosocial stress matter? Tobacco Control. 2005;14(6):389–95.PubMedPubMed CentralView ArticleGoogle Scholar
  18. Waldron I, Lye D. Employment, unemployment, occupation, and smoking. Am J Prev Med. 1989;5(3):142–9.PubMedView ArticleGoogle Scholar
  19. Peretti-Watel P, Constance J, Seror V, Beck F. Working conditions, job dissatisfaction and smoking behaviours among French clerks and manual workers. J Occup Environ Med. 2009;51(3):343–50.PubMedView ArticleGoogle Scholar
  20. Jung Y, Oh J, Huh S, Kawachi I. The effects of employment conditions on smoking status and smoking intensity: the analysis of korean labor & income panel 8th–10th wave. PLoS ONE. 2013;8:2.Google Scholar
  21. Shin SS, Wan X, Wang Q, Raymond HF, Liu H, Ding D, et al. Perceived discrimination and smoking among rural-to-urban migrant women in China. J Immigr Minor Health. 2012;15(1):132–40.View ArticleGoogle Scholar
  22. Cui X, Rockett IR, Yang T, Cao R. Work stress, life stress, and smoking among rural–urban migrant workers in China. BMC Public Health. 2012;12:1.View ArticleGoogle Scholar
  23. Forcier MW. Unemployment and alcohol abuse: a review. Journal of Occupation Medicine. 1988;30(3):246–51.Google Scholar
  24. Heather N, Laybourn P, Macpherson B. A prospective study of the effects of unemployment on drinking behaviour. Social Psychiatry. 1987;22(4):226–33.PubMedView ArticleGoogle Scholar
  25. Hammer T. Unemployment and use of drug and alcohol among young people: a longitudinal study in the general population. Addiction. 1992;87(11):1571–81.View ArticleGoogle Scholar
  26. Lahelma E, Kangas R, Manderbacka K. Drinking and unemployment: contrasting patterns among men and women. Drug Alcohol Depend. 1995;37(1):71–82.PubMedView ArticleGoogle Scholar
  27. Lee AJ, Crombie IK, Smith WCS, Tunstall-Pedoe H. Alcohol consumption and unemployment among men: the Scottish Heart Health Study. Addiction. 1990;85(9):1165–70.View ArticleGoogle Scholar
  28. Gilman SE, Martin LT, Abrams DB, Kawachi I, Kubzansky L, Loucks EB, et al. Educational attainment and cigarette smoking: a causal association? Int J Epidemiol. 2008;37(3):615–24.PubMedPubMed CentralView ArticleGoogle Scholar
  29. Urbán R, Kugler G, Oláh A, Szilágyi Z. Smoking and education: do psychosocial variables explain the relationship between education and smoking behavior? Nicot Tobac Res. 2006;8(4):565–73.View ArticleGoogle Scholar
  30. Johnson W, Kyvik KO, Mortensen EL, Skytthe A, Batty GD, Deary IJ. Does education confer a culture of healthy behavior? Smoking and drinking patterns in danish twins. Am J Epidemiol. 2010;173(1):55–63.PubMedView ArticleGoogle Scholar
  31. Kendler KS, Gardner CO, Hickman M, Heron J, Macleod J, Lewis G, et al. Socioeconomic status and alcohol-related behaviors in mid- to late adolescence in the avon longitudinal study of parents and children. J Stud Alcohol Drugs. 2014;75(4):541–5.PubMedPubMed CentralView ArticleGoogle Scholar
  32. Humensky JL. Are adolescents with high socioeconomic status more likely to engage in alcohol and illicit drug use in early adulthood? Subst Abuse Treat Prev Policy Substance Abuse Treatment. Prev Policy. 2010;5(1):19.Google Scholar

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