Analysis of factors affecting alcohol and tobacco concurrent use by bivariate probit model in Turkey

Alkan, Ömer; Abar, Hayri; Gençer, Özge

doi:10.1007/s11356-021-12849-2

Cited by 21 publications

(13 citation statements)

References 20 publications

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“…Urban residence increased the odds of CT and CTHD among women. Consistent with previous research 23 – 26 , we found that men had 28.5 times higher CTHD than women. In terms of CHD, men only had 3.4 times higher rates than women, which is similar to a 3.9 male–female ratio of higher risk drinking in Mongolia 49 .…”

Section: Discussionsupporting

confidence: 93%

“…Concurrent alcohol and tobacco use is associated with several sociodemographic and health indicators. Sociodemographic factors associated with concurrent alcohol and tobacco use include, level of education (lower education among young US emergency department patients 22 , and higher education among the general adult population in Turkey 23 ), male sex 23 – 26 , middle age 1 , 27 – 29 , lower socioeconomic status 17 , 19 , 24 , 25 , 29 , 30 , and residence status 24 . In Thailand the poorest group had a high tobacco consumption only and a high prevalence of alcohol consumption was observed in the richest group 17 , while in Korea lower education was associated with tobacco use only and higher education was associated with alcohol use only 19 .…”

Section: Introductionmentioning

confidence: 99%

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Trends in concurrent tobacco use and heavy drinking among individuals 15 years and older in Mongolia

Pengpid

Peltzer

2022

Sci Rep

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The study aimed to evaluate trends in the prevalence and correlates of current tobacco use only (= CT), current heavy drinking only (= CHD), and current tobacco use and current heavy drinking (= CTHD) in people 15 years and older from 2009 to 2019 in Mongolia. Cross-sectional data were analyzed from 5,438 individuals (15–64 years) of the Mongolia STEPS 2009 survey, 6,013 (15–69 years) of the Mongolia STEPS 2013 survey, and 6,654 persons (15–69 years) of the Mongolia STEPS 2019 survey and responded to questions about substance use, other health risk behaviours and physical measurements. Trend analysis shows that the prevalence of CT increased from 14.4% in 2009 to 15.3% in 2019, and the prevalence of CHD significantly decreased from 13.3% in 2009 to 10.3% in 2019, and the prevalence of CTHD significantly decreased from 14.2% in 2009 to 9.4% in 2019. Middle and older age, male sex (13 times higher for CT, 3.4 times higher for CHD, and 28 times higher for CTHD) and high physical activity significantly increased the odds of CT, CHD and CTHD. Higher education decreased the odds of CT but increased the odds of CHD. Urban residence was positively associated with CT, and among women with CTHD. Underweight decreased the odds of CT, CHD, and CTHD, and obesity decreased the odds of CT and CTHD and increased the odds of CHD. Hypertension was positively associated with CHD and CTHD, while sedentary behaviour was positively associated with CT and CTHD. Being Khalkh by ethnicity increased the odds of CT and inadequate fruit and vegetable intake increased the odds of CHD. More than one in six persons 15 years and older engaged in CT and more than one in ten engaged in CHD and CTHD. Several sociodemographic factors, such as male sex and middle and/or older age, and health variables, such as obesity and hypertension for CHD, were identified associated with CT, CHD, and CTHD that can help in guiding public interventions.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Trends in concurrent tobacco use and heavy drinking among individuals 15 years and older in Mongolia

Pengpid

Peltzer

2022

Sci Rep

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“…Table 1 also shows the variance inflation factor (VIF) values calculated for each characteristic to be used in the estimation of equations modelling the likelihood of incidence of OOP expenditures in the three categories. Variables with a VIF value of 5 but less than 10 are considered to indicate a moderate degree of multicollinearity, while those with a VIF value of 10 and higher show a high degree of multicollinearity 132 . However, none of the variables included in the modelling has a VIF value of five or higher (Table 1) indicating the absence of moderate or severe multicollinearity between the selected regressors.…”

Section: Resultsmentioning

confidence: 99%

“…Variables with a VIF value of 5 but less than 10 are considered to indicate a moderate degree of multicollinearity, while those with a VIF value of 10 and higher show a high degree of multicollinearity. 132 However, none of the variables included in the modelling has a VIF value of five or higher (Table 1) indicating the absence of moderate or severe multicollinearity between the selected regressors. Abbreviation: VIF, variance inflation factor.…”

Section: Summary Statisticsmentioning

confidence: 99%

Determinants of Turkish households' out‐of‐pocket expenditures on three categories of health care services: A multivariate probit approach

Demir

Alkan

Bilgiç

et al. 2022

Health Planning & Management

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This study identifies the driving forces that contribute to the probabilities of incidence of out-of-pocket (OOP) expenditures by households in Turkey. Factors affecting the probability of OOP expenditures on medical products/devices/ supplies (MP), outpatient services (OTS), and inpatient services (ITS) are examined using the Household Budget Survey data gathered by the Turkish Statistical Institute in 2018. The study applies the multivariate probit model.The incidence of OOP spending varied with 48.9% of the households reporting OOP expenditure on MP, 22.4% on OTS, and 25.4% on ITS. The largest probability changes were associated with household disposable annual income, household type and size, age category, and having private health insurance. Gender and marital status also influenced expenditures in some categories. Lifestyle choices had small and mixed effects, with smoking and alcohol consumption lowering the probability of OOP spending. From a policy standpoint, households with the lowest incomes, large households, and those where the household head was 'others' (retiree, student, housewife, not actively working, etc.) or had a condition preventing employment seemed to report OOP expenditures less frequently and may have chosen not to receive healthcare services, leading to the need for more healthcare services later.

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“…Ordinal and nominal variables were defined as dummy variables to examine the effects of all variables included in the binary logistic regression model on their categories. 87 …”

Section: Methodsmentioning

confidence: 99%

Secondhand smoke exposure for different education levels: findings from a large, nationally representative survey in Turkey

Alkan

Ünver

2022

BMJ Open

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ObjectivesThe aim of this study is to determine the factors that influence individuals’ exposure to tobacco smoke in Turkey according to their education level.DesignSecondary data analysis.ParticipantsAltogether, 17 084 individuals aged 15 and over were included in this study.SettingsData set of the Turkey Health Survey in 2019.MethodsBinary logistic regression analysis was used to determine the factors associated with individuals’ exposure to tobacco smoke.Primary and secondary outcome measuresThe variables age, gender, marital status, general health status, employment status, receipt of psychosocial support and tobacco use were found to be correlated with exposure to tobacco smoke.ResultsThe study determined that individuals who are illiterate/unschooled were exposed to tobacco smoke at a rate of 32.61%, primary school graduates at a rate of 34.32%, primary education graduates at a rate of 41.75%, high school graduates at a rate of 41.04% and university graduates at a rate of 40.34%.ConclusionAs a result of the study, it is emphasised that men, young individuals, individuals with moderate and very good general health status, those who use tobacco, those who are unemployed and those who receive psychosocial support should be targeted. In addition, appropriate strategies for reducing secondhand smoke (SHS) exposure should be developed, taking into account public health strategies for increasing awareness of the adverse health effects of SHS exposure and the determinants of tobacco exposure according to the study.

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Analysis of factors affecting alcohol and tobacco concurrent use by bivariate probit model in Turkey

Cited by 21 publications

References 20 publications

Trends in concurrent tobacco use and heavy drinking among individuals 15 years and older in Mongolia

Trends in concurrent tobacco use and heavy drinking among individuals 15 years and older in Mongolia

Determinants of Turkish households' out‐of‐pocket expenditures on three categories of health care services: A multivariate probit approach

Secondhand smoke exposure for different education levels: findings from a large, nationally representative survey in Turkey

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