A social-contextual investigation of smoking among rural women: multi-level factors associated with smoking status and considerations for cessation

Nemeth, Julianna M.; Thomson, Tiffany; Lü, Bo; Peng, Juan; Krebs, Valdis; Doogan, Nathan J.; Ferketich, Amy K.; Post, Douglas M.; Browning, Christopher R.; Paskett, Electra D.; Wewers, Mary Ellen

doi:10.22605/rrh4338

Cited by 9 publications

(7 citation statements)

References 39 publications

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“…On the determinants of cigarette smoking among women, evidence indicates that familial and partner influences [ 20 ], low income [ 4 , 5 , 7 , 9 , 21 , 22 , 26 , 27 ], low education [ 4 , 7 , 9 , 18 , 21 , 22 , 28 , 29 ], greater education [ 30 , 31 ], urban areas [ 5 , 7 , 21 ], rural areas [ 10 ], older age [ 5 , 18 , 19 , 27 ], younger age [ 26 ], being married [ 5 ], being formerly married (divorced/separated/widowed) [ 18 , 27 ], female-headed household [ 29 ], being employed [ 7 ], unemployment [ 4 ], perceiving distance as a problem in seeking healthcare [ 7 ], religion [ 27 ], severely food insecure women [ 32 ], depression and stress [ 26 ], narcissistic and impulsive personality traits [ 28 ], region heterogeneity [ 7 , 21 ], multiparity [ 4 ], television viewing [ 23 ], and intimate partner sexual violence [ 33 ] increased the likelihood of cigarette smoking among women of reproductive age.…”

Section: Introductionmentioning

confidence: 99%

Determinants of cigarette smoking and smoking frequency among women of reproductive age in Nigeria: evidence from a nationwide cross-sectional survey

Ogbuabor

Igwe

2023

Subst Abuse Treat Prev Policy

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Background Smoking is a leading cause of avoidable deaths and attributable disability-adjusted life years globally. Yet, the determinants of smoking practices among women are understudied. This study assessed the determinants of smoking and smoking frequency among women of reproductive age in Nigeria. Methods and materials Data from the 2018 Nigeria Demographic and Health Survey (NDHS) were used in this study (n = 41,821). The data were adjusted for sampling weight, stratification, and cluster sampling design. The outcome variables were smoking status and smoking frequency (daily smoking and occasional smoking). The predictor variables included women’s socio-demographic and household characteristics. Pearson’s chi-squared test was used to evaluate the association between outcome and predictor variables. All variables significant in bivariate analyses were further analysed using complex sample logistics regression. Statistical significance was set at a p-value < 0.05. Results The prevalence of smoking among women of reproductive age is 0.3%. The prevalence of smoking frequency is 0.1% (daily) and 0.2% (occasionally). Overall, women aged 25-34 (AOR = 2.13, 95%CI: 1.06-4.29, ρ = 0.034), residing in the South-south region (AOR = 9.45, 95%CI: 2.04-43.72, ρ <0.001), being formerly married (AOR = 3.75, 95%CI: 1.52-9.21, ρ = 0.004), in female-headed households (AOR = 2.56, 95%CI: 1.29-5.08, ρ = 0.007) and owning mobile phones (AOR = 2.10, 95%CI: 1.13-3.90, ρ = 0.020) were more likely to smoke. Whereas female-headed households (AOR = 4.34, 95%CI: 1.37-13.77, ρ = 0.013) and being formerly married (AOR = 6.37, 95%CI: 1.67-24.24, ρ = 0.007) predisposed to daily smoking, age 15-24 (AOR = 0.11, 95%CI: 0.02-0.64, ρ = 0.014) was protective of daily smoking among women. Owning mobile phones (AOR = 2.43, 95%CI: 1.17-5.06, ρ = 0.018) increased the odds of occasional smoking among women. Conclusions The prevalence rates of smoking and smoking frequency are low among women of reproductive age in Nigeria. Women-centred approaches to tobacco prevention and cessation must become evidence-informed by incorporating these determinants into interventions targeting women of reproductive age in Nigeria.

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Section: Introductionmentioning

confidence: 99%

Determinants of cigarette smoking and smoking frequency among women of reproductive age in Nigeria: evidence from a nationwide cross-sectional survey

Ogbuabor

Igwe

2023

Subst Abuse Treat Prev Policy

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“…These limitations could be difficult to analyze by trajectory itself because cigarette smoking variables are categorical. Nonetheless, we used the Cnorm model of trajectory analysis [23,24]. This model was originally used for continuous variables.…”

Section: Discussionmentioning

confidence: 99%

Trajectory of Smoking and Incidence of Atherosclerotic Cardiovascular Disease among Korean Young Adult Men

Jee

Jeon

Back

et al. 2019

IJERPH

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Introduction: Smoking among young adults is associated with atherosclerotic cardiovascular disease (ASCVD) in middle age. Our aim was to analyze the trajectory of smoking in young adults and analyze the effects of the trajectory group on incident ASCVD. Methods: This study was conducted among 60,709 young adult men aged 20–29 years who received health screening every two years from 1992–2004. Trajectory analysis was performed through smoking survey data measured 7 times during this period. ASCVD, including ischemic heart disease (IHD) and stroke events were confirmed from 2005–2015. The association between the trajectory group and ASCVD risk was analyzed using Cox proportional hazard models, controlling for covariates and mediators. Results: Trajectory analysis showed that smoking categorized into five groups as follows: Group 1 (28.3%), low steady; Group 2 (14.7%), lowering; Group 3 (17.3%), high steady; Group 4 (15.6%), rise and fall; and Group 5 (24.2%), very high steady. The model performance of the trajectory model (Akaike information criterion; AIC = 51,670.78) with mediators was better than the model (AIC = 51,847.85) without mediators. Group 5 showed a 49% higher risk of ASCVD than Group 1. The risk of IHD was 1.63-times higher for Group 5 and 1.31-times higher for Group 4, compared to Group 1. Compared to Group 1, Group 5 had a 1.36- and 1.58-times higher risk for total stroke and ischemic stroke, respectively. Conclusions: In young adult men, the multiple measured trajectory model with mediators was far more informative than one-time smoking for explaining the association with cardiovascular disease.

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“…Another potential cause for a normalized culture of tobacco use in rural areas may be community and family connectedness. Though it is unclear whether connectedness differs as a function of rural/nonrural community type, among rural women, the odds of being a smoker increases by 12%–14% as neighborhood cohesion increases, which may be due to stronger perceptions of tobacco’s social acceptability among cohesive neighborhoods (Nemeth et al, 2018). Family members also sometimes enable youth tobacco use in rural communities (Bernat & Choi, 2018; Hart et al, 2018), subsequently reducing their perceptions of tobacco as harmful (Chaffee & Cheng, 2018; Couch et al, 2017).…”

Section: Drivers Of Tobacco Use In Rural Areasmentioning

confidence: 99%

Cumulative disadvantage as a framework for understanding rural tobacco use disparities.

Ozga¹,

Romm²,

Turiano³

et al. 2021

Experimental and Clinical Psychopharmacology

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Traditional tobacco product (cigarettes and smokeless tobacco) and polytobacco use rates are significantly higher among rural adolescents and adults compared to their nonrural counterparts. Such disparities are due to several factors that promote tobacco use initiation and continuation, including individual-level psychopharmacological factors and structural-level factors such as fewer tobacco control efforts (e.g., fewer smoke-free policies and lower tobacco excise taxes), targeted tobacco marketing, less access to healthrelevant resources, and more positive cultural norms surrounding tobacco use in rural communities. In this review, we use cumulative disadvantage theory as a framework for understanding how psychopharmacological and structural-level factors serve as drivers of tobacco use in rural areas. We start by describing how structural-level differences between rural-nonrural communities impact psychopharmacological influences and, when available, how these factors influence tobacco use. We conclude by discussing the interplay between factors, providing suggestions for ways to assess our application of cumulative disadvantage theory empirically and making recommendations for research and policy implementation in rural areas. Public Health SignificanceDespite public health efforts, rural-nonrural disparities for traditional tobacco products (cigarettes and smokeless tobacco) have only widened in recent years. We use cumulative disadvantage theory as a framework for describing the interplay between psychopharmacological and structural-level drivers of tobacco use in rural areas. Based on this framework, we suggest ways to assess our proposed model empirically and make research and policy recommendations for reducing tobacco use in rural areas.

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A social-contextual investigation of smoking among rural women: multi-level factors associated with smoking status and considerations for cessation

Cited by 9 publications

References 39 publications

Determinants of cigarette smoking and smoking frequency among women of reproductive age in Nigeria: evidence from a nationwide cross-sectional survey

Determinants of cigarette smoking and smoking frequency among women of reproductive age in Nigeria: evidence from a nationwide cross-sectional survey

Trajectory of Smoking and Incidence of Atherosclerotic Cardiovascular Disease among Korean Young Adult Men

Cumulative disadvantage as a framework for understanding rural tobacco use disparities.

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