Spatial distribution and correlates of smoking in Zambia

Nyirenda, Herbert Tato; Mulenga, David; Silitongo, Moono; Nyirenda, Herbert Bc; Nyirenda, Tambulani

doi:10.1136/bmjopen-2019-030044

Cited by 8 publications

(12 citation statements)

References 16 publications

(25 reference statements)

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“…Men aged 30-44 and 45-59 years had a higher likelihood of risky health behaviour compared with men aged 15-29 years. This nding is in line with other study nding from Zambia (25), Namibia (26) and India (27). This could be due to the fact that as age increase, they can afford the cost and their job and family stress causing individual to take smoking and drinking as coping mechanism.…”

Section: Discussionsupporting

confidence: 91%

Spatial Distribution and Factors Associated with Risky Health Behaviour Among Adult Males Aged 15-59 Years in Ethiopia; Generalized Structural Equation Modelling

Kebede

Weldesenbet

Tusa

2020

Preprint

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Background: Alcohol drinking and tobacco smoking are the largest preventable cause of death and important risk factors for a number of non-communicable diseases and cause premature death and many socioeconomic consequences. Therefore, the present study aimed to assess the spatial distribution of risky health behaviour and its associated factors among adult males in Ethiopia. Methods: Secondary data analysis was conducted among 12,688 men (aged 15–59 years). The distribution of risky health behaviour across the country was observed by ArcGIS software. In SaTScan software, the Bernoulli model was fitted by Kulldorff methods to identify the purely spatial clusters of risky health behaviour. Generalized Structural Equation Model (GSEM) was used to determine factors associated with each domain of risky health behaviour (regular alcohol drinking and tobacco smoking).Results: Risky health behaviour had spatial variation across the country. The primary clusters were located in Tigray, Amhara and north-eastern Benishangul national regional states. Spatial scan statistics identified 118 primary clusters (Log-Likelihood ratio (LLR) =524.8, p < 0.001). Residence, frequency of listening to a radio, occupation and frequency of watching television were significantly associated with drinking alcohol whereas wealth index was associated with tobacco smoking. Age, region, educational status, marital status and religion had association with both domains of risky health behaviour.Conclusion: Risky health behaviour had spatial variation across the country. The national press media in ban of advertising and promotion of alcohol and tobacco should be strengthen. Aggressive health education efforts should be directed toward this high-risk population (Tigray, Amhara and north-eastern Benishangul regional states). Improving risky health behaviour is an important approach to reducing health disparities and for more cost-effective utilization of scarce resources in the public health sector.

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Section: Discussionsupporting

confidence: 91%

Spatial Distribution and Factors Associated with Risky Health Behaviour Among Adult Males Aged 15-59 Years in Ethiopia; Generalized Structural Equation Modelling

Kebede

Weldesenbet

Tusa

2020

Preprint

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“…Eleven (11) independent variables were considered in this study. They comprised, country, age, The choice of these independent variables was based on previous studies [6,[11][12][13][14][15][16][17] that found them to be statistically significantly associated with tobacco use as well as their availability in the DHS dataset.…”

Section: Independent Variablesmentioning

confidence: 99%

“…This has led to researchers focusing on the adverse health outcomes and the consequences of tobacco use [7][8][9]. Much attention has been focused on cigarette smoking [2,[10][11][12][13][14] and creating a dearth of knowledge on the other forms of tobacco use. Also, the focus has been on adult men and women and their socio-economic inequalities in tobacco use [15][16][17].…”

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confidence: 99%

Prevalence and Drivers of Tobacco use Among Young Men in Sub-Saharan Africa: Evidence from 21 Nationally Representative Surveys

Darteh¹,

Yaya²,

Dickson³

et al. 2020

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Background Tobacco consumption – including smoking, chewing tobacco and snuff has been recognized as a global public health issue and a major cause of premature mortality and morbidity. An annual estimated figure of more than 7 million people dies due to tobacco consumption with more than 6 million of those deaths attributed to direct tobacco use and about 890, 000 resulting from exposure to second-hand smoke. This paper seeks to examine the prevalence and drivers of tobacco use among young men in sub-Saharan Africa.Methods Using pooled data from the most recent Demographic and Health Survey (DHS) conducted between January 1, 2010, and December 3, 2018, in 21 countries that had data on tobacco use in SSA this paper examines tobacco use among young men in sub-Saharan Africa. A chi-square was conducted at the bivariate level to test for the significance of tobacco use across the socio-demographic characteristics. A binary logistic regression test was conducted at the multi-variate level to estimate the determinants of tobacco use among young people in SSA. The confidence interval for both the bivariate and multivariate tests was 95%.Results The overall prevalence of tobacco use was 9.34% (95% CI: 7.52–11.16) with the lowest prevalence in Ghana (1.46%) and the highest in Lesotho (39.19%). It was also found that those aged 20–24 [AOR = 3.080, CI = 2.840–3.341], engaged in unskilled labour [AOR = 2.651, CI = 2.333–3.012], who are widowed/divorced/separated [AOR = 2.747, CI= [2.301–3.279] and with no religion [AOR = 1.460, CI = 1.273–1.676] had higher odds of using tobacco. On the other hand, young, men with secondary [AOR = 0.726, CI = 0.645–0.818] and higher [AOR = 0.563, CI= [0.446–0.710] level of education, those in the richest wealth quintile[AOR = 0.758, CI = 0.660–0.871], those in rural areas [AOR = 0.869, CI = 0.795–0.950], and those who read newspaper or magazine at least once a week [AOR = 0.898, CI = 0.808–0.998] had lower odds of tobacco use.Conclusion Age, level of education, wealth status, working status, marital status, religion and place of residence were statistically significant association with tobacco use among young men in SSA. These socioeconomic factors should be considered when trying to tackle tobacco use in SSA. Specific public health interventions should take into account these socio-economic factors to reduce tobacco use among young people in SSA

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“…These studies found that adult manual laborers engaging in activities such as construction or farming were more likely to smoke than their formally employed counterparts. Such occupations are likely to lead people to smoke tobacco as a form of stress relief [23,43]. The results of our study could be explained by the fact that most students were young and subjected to rules at school that prohibit smoking while homemakers were women.…”

Section: Discussionmentioning

confidence: 73%

“…Two other studies have reported a tobacco smoking prevalence of 20% among Zambian men, with the most affected being those aged 24-39 years [21,22]. A recent study estimated an overall tobacco smoking prevalence of 8.2% and 11% among urban and rural Zambians of both genders, respectively [23]. In addition, alcohol per capita consumption has remained rather stable over the years at 5 litres of pure alcohol per year in the general Zambian population, which was over three times higher among drinkers (18 litres) [24].…”

Section: Introductionmentioning

confidence: 99%

Social Risk Factors Associated With Daily Tobacco Smoking and Binge Drinking Among Zambians: Evidence From the 2017 STEPS Survey

Silumbwe¹,

Sabastian²,

Michelo³

et al. 2021

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Background: The burden of disease attributable to tobacco smoking and harmful alcohol consumption poses a major threat to sustainable development in most low- and middle-income countries. However, evidence on tobacco use and harmful alcohol consumption to inform context-specific interventions addressing these harmful social behaviours is limited in the African context. This study aimed to determine the social risk factors associated with daily tobacco smoking and binge drinking in Zambia.Methods: The study stems from nationwide population-based representative survey data collected using the World Health Organization’s STEPwise approach for non-communicable disease risk factor surveillance in 2017 among 18–69-year-old Zambians. The main outcomes were daily tobacco smoking and binge drinking, and the demographic and socioeconomic variables included sex, marital status, age, residence, level of education and occupation. Prevalence ratios were calculated using log-binomial regression analysis.Results: Overall, 4302 individuals (weighted percentage 49.0% men and 51.0% women) participated in the survey. The prevalence of daily tobacco smoking was 9.04%, and 11.6% of participants engaged in binge drinking, both of which were higher among men than women (17.1% vs. 1.28% and 18.6% vs. 5.29%, respectively). The risk of daily tobacco smoking was significantly higher in men (PR 14.3; 95% CI [9.74, 21.0]) than women, in the >45-year-old group (PR 1.44; 95% CI [1.03, 1.99]) compared to the 18–29-year-old group, and in those with no education (PR 2.70; 95% CI [1.79, 2.99]) or primary education (PR 1.86; 95% CI [1.22, 2.83]) compared to those with higher secondary or tertiary education. The risk of binge drinking was 3.67 times higher (95% CI [2.83, 4.76]) in men than in women. Significantly lower levels of binge drinking were observed among rural residents (PR 0.59; 95% CI [0.46, 0.77]) compared to urban residents and students/homemakers (PR 0.58; 95% CI [0.35, 0.94]) compared to the employed.Conclusion: This study shows huge differences between men and women regarding tobacco smoking and binge drinking in Zambia. A high occurrence of tobacco smoking was observed among men, older members of society and those with lower levels of education, while binge drinking was more common in men and in those living in urban areas. There is a need to reshape and refine preventive and control interventions for tobacco smoking and binge drinking to target the most at-risk groups in the country.

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Spatial distribution and correlates of smoking in Zambia

Cited by 8 publications

References 16 publications

Spatial Distribution and Factors Associated with Risky Health Behaviour Among Adult Males Aged 15-59 Years in Ethiopia; Generalized Structural Equation Modelling

Spatial Distribution and Factors Associated with Risky Health Behaviour Among Adult Males Aged 15-59 Years in Ethiopia; Generalized Structural Equation Modelling

Prevalence and Drivers of Tobacco use Among Young Men in Sub-Saharan Africa: Evidence from 21 Nationally Representative Surveys

Social Risk Factors Associated With Daily Tobacco Smoking and Binge Drinking Among Zambians: Evidence From the 2017 STEPS Survey

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