Factors Associated with Single-Use and Co-Use of Tobacco and Alcohol: A Multinomial Modeling Approach

Noh, Jin‐Won; Kim, Kyoung-Beom; Cheon, Jooyoung; Lee, Yejin; Yoo, Keun-Young

doi:10.3390/ijerph16193506

Cited by 11 publications

(13 citation statements)

References 46 publications

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“…In other words, an individual’s health-related behavior is directly or indirectly influenced by the socioeconomic, built environment, and policy characteristics of the region, and by the operation of local health services throughout the region [ 45 ]. In previous studies, there was a difference in health behavior according to the area of residence [ 46 , 47 , 48 , 49 ], and in this study, both men and women were affected by access to local exercise facilities and the type of residential areas (urban, rural, etc.).…”

Section: Discussionmentioning

confidence: 56%

Residential Characteristics as Factors Related to Healthy Behavior Practices—Decision Tree Model Analysis Using a Community Health Survey from Korea

Seo

Park

2022

IJERPH

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In this study, we sought to identify relevant factors in healthy behavior practices, including not only individual-level variables but also regional and physical environments. Data from the Korea Community Health Survey (KCHS) of Gyeongsangnam-do in 2018 were used, with data from 16,519 of the 17,947 individuals (excluding 1428 individuals who had missing values) who participated in the survey. Healthy behavior practices were defined as meeting the criteria for all three modifiable healthy behaviors (non-smoking, moderate alcohol consumption, regular walking). A decision tree analysis was performed. In men, healthy behavior practices were lower in the unemployed population, in those aged 40–50 years, living in rural residential areas, and with stress. For women who lived in areas with small populations (<100,000 population), healthy behavior practices were below-average. Men and women who had below-average healthy behavior practices reported poor access to places for exercise and fair or poor self-rated health statuses. It is necessary to implement a health behavior practice intervention that considers not only individual characteristics but also access to local exercise facilities and residential area characteristics (urban, rural). Since age is an important variable in healthy behaviors for both men and women, customized programs that consider age should be provided.

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Section: Discussionmentioning

confidence: 56%

Residential Characteristics as Factors Related to Healthy Behavior Practices—Decision Tree Model Analysis Using a Community Health Survey from Korea

Seo

Park

2022

IJERPH

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“…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 . In the Korea study having obesity decreased the odds of tobacco use only and increased the odds of alcohol use only, hypertension increased the odds of alcohol use only, hyperlipidemia increased the odds of tobacco use only but decreased the odds of alcohol use only 19 . In Hongkong, lower income, male sex and increasing age were associated with concurrent alcohol and tobacco use 31 .…”

Section: Introductionmentioning

confidence: 91%

“…In Laos, the prevalence of CTHD was 18.6%, CT 15.2% and CHD 28.4% 18 . In Korea, the prevalence of currently smoking and drinking monthly was 13.1%, currently smoking only 4.2%, and drinking monthly only 38.7% 19 . In Sri Lanka, the prevalence of concurrent current alcohol and current tobacco use in urban areas was 20.1% and in rural areas 14% 20 , and in metropolitan China, the last 12 months alcohol use only was 14%, tobacco use only 21% and past 12 months concurrent alcohol and tobacco use 23% 21 .…”

Section: Introductionmentioning

confidence: 98%

“…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%

“…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 . In the Korea study having obesity decreased the odds of tobacco use only and increased the odds of alcohol use only, hypertension increased the odds of alcohol use only, hyperlipidemia increased the odds of tobacco use only but decreased the odds of 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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Tobacco and alcohol co‐use: Lifestyle and sociodemographic factors, and personality aspects as potential predictors in the “Seguimiento Universidad de Navarra” cohort

Neddermann‐Carrillo,

Abidi,

Gea

et al. 2024

Research in Nursing & Health

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Tobacco and alcohol co‐use are two major lifestyle modifiable risk factors. Understanding the determinants of both behaviors helps to develop interventions to prevent these exposures. However, previous studies have focused on predictors of individual tobacco or alcohol use. This study aims to explore the potential predictors of tobacco and alcohol co‐use among Spanish university graduates from the “Seguimiento Universidad de Navarra” (SUN) cohort study. A total of 7175 participants who were co‐users of tobacco and alcohol were selected for this cross‐sectional analysis. Their mean age was 39.1 years (12.04 SD) and 57.3% were women. Univariate regression models were used to select the potential predictors of tobacco and alcohol co‐use, and the areas under the ROC curves (AUC) were calculated. Multivariable logistic regression models were used to create a predictive model. Baseline potential predictors included sociodemographic factors, lifestyle habits, and perceived personality aspects. In the multivariable model, the main significant potential predictors of tobacco and alcohol co‐use were driving under the influence of alcohol (odds ratio [OR] = 1.65 [1.43–1.90]), drinking 1–2 cups of coffee daily (OR = 1.50 [1.24–1.84]), and drinking three or more cups of coffee daily (OR = 1.61 [1.35–1.91]) when compared with the reference group. Conversely, those who were married (OR = 0.87 [0.75–0.99], ate at home 7 days a week (OR = 0.69 [0.60–0.80]), did more physical activity than recommended (OR = 1.18 [1.02–1.34]), or had a high perceived level of competitiveness (OR = 0.83 [0.72–0.95]) had a lower risk of co‐use (AUC 0.61 [confidence interval 95% 0.59–0.63]), compared to the reference group. These results could be used by healthcare professionals, especially nurses, to effectively assess patients at higher risk of tobacco and alcohol co‐use.

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Factors Associated with Single-Use and Co-Use of Tobacco and Alcohol: A Multinomial Modeling Approach

Cited by 11 publications

References 46 publications

Residential Characteristics as Factors Related to Healthy Behavior Practices—Decision Tree Model Analysis Using a Community Health Survey from Korea

Residential Characteristics as Factors Related to Healthy Behavior Practices—Decision Tree Model Analysis Using a Community Health Survey from Korea

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

Tobacco and alcohol co‐use: Lifestyle and sociodemographic factors, and personality aspects as potential predictors in the “Seguimiento Universidad de Navarra” cohort

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