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Does policy adoption influence the association between socio-economic differences and smoking prevalence? A longitudinal analysis 2008-2015

Bempong, Nefti-Eboni LU (2017) MPHN40 20171
Social Medicine and Global Health
Abstract
Abstract
Introduction: Smoking is a major public health concern, accounting for nearly 700,000
deaths on an annual basis, globally. The socio-economic differences within smoking are well established, reflected in a social gradient that is estimated to account for half of the socio- economic differences in mortality for men aged 35-69 years in developed settings, such as the European region.

Aim: The study aimed to investigate the association between socio-economic differences and smoking prevalence, and furthermore to explore the influence of policy adoption on the association between socio-economic differences and smoking prevalence.

Methodology: This ecological longitudinal study adopted a quantitative approach to methodology,... (More)
Abstract
Introduction: Smoking is a major public health concern, accounting for nearly 700,000
deaths on an annual basis, globally. The socio-economic differences within smoking are well established, reflected in a social gradient that is estimated to account for half of the socio- economic differences in mortality for men aged 35-69 years in developed settings, such as the European region.

Aim: The study aimed to investigate the association between socio-economic differences and smoking prevalence, and furthermore to explore the influence of policy adoption on the association between socio-economic differences and smoking prevalence.

Methodology: This ecological longitudinal study adopted a quantitative approach to methodology, modelling panel data from 2008-2015. Data for units of analysis (n = 7) were extracted from public data sources including the World Bank, OECD, ESPAD and WHO’s Global Observatory. Statistical analysis was conducted using R software, for multivariable linear regression in the form of fixed effects regression models and interaction terms.

Results: Smoking prevalence showed statistical significance in association to education (p=8.07x10-6)(p=7.63x10-5)(p=2.79x10-5),and employment rate (p=0.002)(p=0.003)(p=0.003), which were negatively and positively associated, respectively. In isolation, policy adoption of tobacco control strategies showed no statistical significance (p=0.696)(p=0.459) in association to smoking prevalence. However both models, which incorporated a measure for policy adoption, indicated statistical significance (p=2.80x10-9) (p=2.31x10-9), yet at a slightly decreased significance level when compared to the model that did not (p=5.99x10-10).

Conclusions: All three models, with and without incorporated measures for policy adoption influenced the association between smoking prevalence and socio-economic differences, which could be deduced to omitted variable bias. Findings suggest policy regarding tobacco control needs to be stronger and more clearly regulated, with shifted focus on health education, in order to have a truly significant effect, and to overcome the socio-economic differences present within smoking.

Key words: Tobacco, Tobacco control, Tobacco prevention and Socio-economic status (Less)
Popular Abstract
Is the fight against smoking a losing battle?

Despite knowing the devastating consequences associated with smoking, it remains a major problem within society, upping its death poll (which is noticeably higher in more disadvantaged segments of the population), year by year. The public health sphere has devised tobacco control strategies as a response to tackle the growing epidemic. These strategies may range from banning smoking in work places, placing shocking images on your cigarette packet or simply increasing the price of cigarettes. Not only do these strategies aim to reduce smoking as a whole, they also hope to even out the disparities present within smoking. What is perhaps most remarkable about these strategies, is that hey come... (More)
Is the fight against smoking a losing battle?

Despite knowing the devastating consequences associated with smoking, it remains a major problem within society, upping its death poll (which is noticeably higher in more disadvantaged segments of the population), year by year. The public health sphere has devised tobacco control strategies as a response to tackle the growing epidemic. These strategies may range from banning smoking in work places, placing shocking images on your cigarette packet or simply increasing the price of cigarettes. Not only do these strategies aim to reduce smoking as a whole, they also hope to even out the disparities present within smoking. What is perhaps most remarkable about these strategies, is that hey come with no direct, financial cost to the individual.

But on the contrary, recent findings have shown that better education was more likely in lowering your chances of smoking, and increasing the probability of quitting, than the proposed strategies. Therefore, for these strategies to be successful the EU would need to reinforce stricter and more clearly regulated policies. However, increasing the tax on tobacco has proven extremely successful in the past, and NGO’s alongside many health boards, are advocating for further increases in the price of tobacco– to increase its effectiveness. (Less)
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author
Bempong, Nefti-Eboni LU
supervisor
organization
course
MPHN40 20171
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Tobacco, Tobacco control, Tobacco prevention and Socio-economic status
language
English
id
8919038
date added to LUP
2017-07-17 09:15:06
date last changed
2017-07-17 09:15:06
@misc{8919038,
  abstract     = {{Abstract
Introduction: Smoking is a major public health concern, accounting for nearly 700,000
deaths on an annual basis, globally. The socio-economic differences within smoking are well established, reflected in a social gradient that is estimated to account for half of the socio- economic differences in mortality for men aged 35-69 years in developed settings, such as the European region.

Aim: The study aimed to investigate the association between socio-economic differences and smoking prevalence, and furthermore to explore the influence of policy adoption on the association between socio-economic differences and smoking prevalence.

Methodology: This ecological longitudinal study adopted a quantitative approach to methodology, modelling panel data from 2008-2015. Data for units of analysis (n = 7) were extracted from public data sources including the World Bank, OECD, ESPAD and WHO’s Global Observatory. Statistical analysis was conducted using R software, for multivariable linear regression in the form of fixed effects regression models and interaction terms.

Results: Smoking prevalence showed statistical significance in association to education (p=8.07x10-6)(p=7.63x10-5)(p=2.79x10-5),and employment rate (p=0.002)(p=0.003)(p=0.003), which were negatively and positively associated, respectively. In isolation, policy adoption of tobacco control strategies showed no statistical significance (p=0.696)(p=0.459) in association to smoking prevalence. However both models, which incorporated a measure for policy adoption, indicated statistical significance (p=2.80x10-9) (p=2.31x10-9), yet at a slightly decreased significance level when compared to the model that did not (p=5.99x10-10).

Conclusions: All three models, with and without incorporated measures for policy adoption influenced the association between smoking prevalence and socio-economic differences, which could be deduced to omitted variable bias. Findings suggest policy regarding tobacco control needs to be stronger and more clearly regulated, with shifted focus on health education, in order to have a truly significant effect, and to overcome the socio-economic differences present within smoking.

Key words: Tobacco, Tobacco control, Tobacco prevention and Socio-economic status}},
  author       = {{Bempong, Nefti-Eboni}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Does policy adoption influence the association between socio-economic differences and smoking prevalence? A longitudinal analysis 2008-2015}},
  year         = {{2017}},
}