Tobacco Use and Health Consequences

Chapter 1

1.0 Introduction

1.1. Health effects of smoking

Tobacco smoking is a major public health problem in the society (1). The World Health Organization (WHO) estimated that the use of tobacco kills approximately half of its users (2). Statistically, approximately six million deaths occur each year attributable to tobacco usage worldwide (2, 14). In the US, Centre for Disease Control and Prevention(CDC), report mortality related to cigarette smoking in both male and female is three time higher than non-smokers. Approximately 500,000 reported deaths annually in the US are attributable to smoking including second hand smoking (66). Similarly, in the UK, National Health Service (24, 25, 34) reported that in 2016/17, 484,000 were admitted with diseases attributable to tobacco smoking. According to the 2017 Action on smoking and Health (ASH) a UK public health charity report, the prevalence of smoking in the UK is estimated at just under 1 in 5 adults in 2017 counting for approximately 100,000 deaths per year in the UK (4). In 2013/14, more than 1.6 million hospital admissions in England were attributed to smoking (4, 5). In spite of the vastly improved awareness of the risks associated with tobacco use, smoking remains a major public health problem in the UK and continues to represent the primary cause of preventable and premature death in the UK (5). Research on contents of tobacco smoke has revealed that it contain large number of harmful chemicals, some of which have been linked with the development of different cancers type owing to their genotoxic properties (7, 8, 9). As such, tobacco smoke has been cited as a causative agent in the development of cancers of the lungs, breast, larynx, trachea, oesophagus, kidney, pancreas, bladder, cervix, and colon (10,6). Research also suggests the average life expectancy of smokers is decreased by a minimum of ten years as compared to never smokers and the number of disease-free years have shown a reduction of 5.8 years in long term cigarette smokers (11,12).

1.1.2 Patterns of smoking prevalence, addictive effects and socio economic inequality in the UK.

Smoking prevalence is determined by multiple factors, and an understanding of these is essential in the design and implementation of effective tobacco control strategies (15). Several studies indicate that there are significant demographic and social economic differences in smoking rates in the UK. According to the 2014 opinions and lifestyles (OPN) survey, the highest recorded level of smoking prevalence is amongst the 16 to 24 (23 per cent) and the 25 to 34 year old (25 per cent) age groups, with people aged 60 years recording the lowest prevalence of smoking (11 per cent) (71). Regional variations show significant difference between smoking rates in the norths and the south of the UK (72). In terms of breakdown, the UK comprise of four countries (England, Scotland, Wales and Northern Ireland) and the division of England into nine administrative regions incorporating the East of England, the East Midlands, London, the North East, the North West, the South West, the South East, Yorkshire and the Humber and the West Midlands. The integrated household Survey (IHS) 2014 reveals that the North East, North West and Yorkshire and the Humber have the highest smoking prevalence (above 19 Per cent) while the South East and the South West (17 per cent) have markedly lower rates of smoking (71). The Study further shows that smoking prevalence is increased in relation to other markers such as socio-economic (measured in terms of unemployment, the least educated, area ,low income earners and occupation.) disadvantage. These disadvantaged socio-economic groups, have shown an increased smoking prevalence. This study found that smoking is higher in the most deprived areas where people are more than twice as likely to smoke (with men (32.9%), women (26.1%) compared to those in the least deprived (14.3% and 10.2% respectively) in the UK. As this group are four times more likely to smoke than the affluent sector of the British society (15, 19). While a 2013 OPN survey suggests that, the unemployed people (35 per cent) are approximately twice as likely to smoke as people who work (19 per cent), as they have an increased tendency to adopt unhealthy behaviours, possibly in an attempt to reduce stress associated with a disadvantaged living environment. Additionally, the higher levels of economic deprivation resulting in unemployment may also make it less likely that this group feel able to afford over the counter smoking cessation aids such as counselling, nicotine replacement therapies, or electronic cigarettes than other, more affluent groups (19). Viewed from this perspective, there can be little doubt that smoking prevalence is associated with location and social economic status. Studies conducted by Phillips et al. (2017) and Lorant et al. (2015) on usage of tobacco product particularly smoking found that it is the biggest preventable cause of both socioeconomic (income and education) and health inequalities that in turn leads into significant effect on both individuals and society(20,21). The cost of tobacco represents a greater proportion of household income in the poorer smokers, this means that tobacco use, contributes to trapping people into poverty as well as causing damages to health (20,21). Furthermore, it is notable that as an individual is more likely to smoke if they have family members who smoke, smoking prevalence can continue down the generations of a family as the younger members take up smoking, thus increasing the likelihood of subsequent generations smoking and so on(18,22).

1.1.3. Cost of Smoking

Financially, smoking causes huge cost to the society measured in terms of loss productivity, treatment cost, and cost of buying. WHO (2015) estimate cost treatment and care linked to tobacco smoking at £2.7 billion per year for direct care costs, and £2.5 billion from the resulting loss of productivity from unwell and prematurely deceased working aged adults. In an attempt to counteract the potential disease burden and associated care costs of smoking-related diseases most government and institution have increasingly focused on reducing tobacco usage as an effective approach to tackling the problem and promoting public health worldwide (13,14). Studies on smoking cessation services have indicated a considerable amount of money is spent on medication prescription and provision of the local stop smoking service provided by the National Health Services (NHS) (24, 25). The research carried out in the UK by the ASH, found out that in England the annual cost of smoking is £13.9 billion (14, 23). Research smoking cessation by Health and Social Care Information Centre (2015) revealed that there are 1.8 million prescriptions made in England in 2013/2014, with these prescription medications net ingredient cost totalling about £48.8 million. In comparison to the cost of treating the smoking related disease and its economic effects, the cessation services are considerably high cost effective approach. Therefore, it is imperative that the government creates a public health smoking cessation services that are able to help people quit smoking in order to address the widening health inequalities resulting from tobacco consumption.

1.2 Benefits of smoking cessation

There are enormous health benefits of smoking cessation. Illustrating the chemical components of tobacco smoke and consequential effects to smokers, CDC (2016) stated that of the estimate of 7,000 chemicals, hundreds are harmful and about 70 are associated with cancer. Building on the findings, the health effects of smoking tobacco that include cancer and other terminal diseases, research has pointed that quitting smoking greatly reduces the risk for lung cancer, heart disease, stroke, peripheral vascular disease, respiratory symptoms, risk of developing lungs diseases (chronic obstructive disease), mental health, and infertility and stillbirth (26,27,28). A study by Ahmed et al. (2015) found that in light-to-moderate ex-smokers, who for over 15 years had quit smoking, there is decreased risk of developing heart failure to a level similar to those who had never smoked (aHR, 0.99; 95% CI, 0.85-1.16), as well as the overall mortality decreasing to a level comparable to the never smokers (aHR, 1.08; 95% CI, 0.96-1.20) (73). However, for heavy smoker who had quit for over 15years the risk did not decline (47). Although, there may have been bias introduced in the study as it relied on self-reported data, these findings indicate the notable impact smoking cessation can have, despite previous smoking habits. The cumulative risk of lung cancer development by age 75, is shown to have reduced from 15.9% in continuing male smokers to 1.7%, 3%, 6%, and 9.9%, in men who quit smoking within the ages of 30,40,50 and 60 respectively (29). Similarly, women have also shown cumulative risk reduction from 9.5% in continuing smokers to 5.3% and 2.2% in female tobacco quitters around age 50 and 60 respectively. (29). However, from the data, it can be seen that the benefits are greatest in those who quit before age 40, there remains significant benefits from quitting at other ages.

1.3. Tobacco control strategies and Government policies

Globally, government and health-oriented organizations have increasingly focused their effort on reducing tobacco usage, grounded on realization of the health and socio-economic (social discrimination, isolation, medical spending, and productivity) benefits. According to Pope III et al. (2011) and (WHO, 2015), reducing tobacco usage is an important focus for health organisations worldwide (13,14). In 1998 (revised in 2000) the “Smoking Kills” white paper was produced to identify that unless action was taken, 120,000 people would die in the UK every year from smoking-related disease (31). This white paper set out government strategies for controlling tobacco consumption within the UK, and ultimately reducing uptake. This included a ban on tobacco advertising and corporate sponsorship across Europe, and a public health publicity campaign designed to change smoker’s attitudes towards the risks of smoking (33,34,35). Over the past decades, governments not only in the UK but globally have intensified implementation of policies and campaigns driven by making unaffordability of tobacco, preventing tobacco promotion, reducing second-hand exposure, improving awareness on harm of smoking, and regulation tobacco products (34,36,37). Furthermore, the white paper looked at reducing exposure to second hand smoke in the workplace to protect non-smokers, along with specific strategies for reducing the incidence of smoking amongst children. The white paper promised a budget of up to £60 million (31), to help set up a National Health Service (NHS) run smoking cessation services, specifically targeting those individuals from poorer socio-economic backgrounds who as previously discussed, are more likely to smoke, and less likely to afford smoking cessation help (31). Ten years later, the charity Action on Smoking and Health (ASH) produced a report in conjunction with the charity Cancer Research UK, which summarised that the measures introduced following the publication of the “Smoking Kills” white paper had been a success, but that more work was needed to address the health inequalities associated with smoking (39). Following these publications, in 2011 the Department of Health addressed the continuing disease burden made on the NHS by smoking as part of the “Healthy Lives, Healthy People” policy. This expanded on the recommendations originally made in the “Smoking Kills” white paper by recommending extending UK tobacco control policies by banning tobacco advertising entirely, and increasing the price of tobacco via taxation to make tobacco less affordable (39). The policy also recommended reviewing smoking cessation service provision (40).

1.4. Stop Smoking Services in England

The Stop Smoking Service was established in 1999-2000, after the ‘smoking kills’ white paper in 1998 to encourage and support successful smoking quit attempts (31). The local smoking cessation services delivered through the NHS, was intended to prioritise supporting those individuals from a less affluent socio-economic backgrounds. This was done in recognition of smoking, as one of the biggest contributing cause of widening health inequality. As argued by Beard et al. (2016) and Dobbie et al. (2015), this intervention set out a comprehensive smoking cessation approach, which can vary from a less intensive approach such as brief advice from a general practitioner (GP), to more intensive services like the pharmacological (Smoking cessation treatment) or behavioural (SSS). Department of Health (2015) illustrated that this medication approach aid in the reduction of nicotine withdrawal effects and tobacco craving. These Services were delivered locally, initially Via the NHS, and more recently through the local authorities (42). As provision has changed, it is important to see if it is still meeting the needs of the regions.

1.4.1. Evaluation of the Local Stop Smoking Service

The Department of Health required that all individual primary care trusts monitor the effectiveness of local service provision, including smoking cessation, by reporting the number of people who had quit 4 weeks after treatment and those who had committed to set a “quit date” (42,43). With regards to the provision of smoking cessation services in the UK, a 2001 review by the NHS reported that in general, smoking cessation services were effective in helping people quit. As smokers who received support from the NHS, were 3.14times more likely to successfully quit than those who made unaided quit attempts (44). Smoking cessation therapy was also found to be cost effective, with a cost per life year saved reported as £900; comparatively costs per life year of between £5000 and £10,000 may be considered to be good value for money, therefore £900 per year proves highly cost effective (43). The review also found that approximately 60% of the patients accessing the services were amongst the poorer members of society and were exempted from NHS prescription charges (43). Using a systematic review, Bauld et al. (2009) evaluated the effectiveness of NHS smoking cessation services. The authors reported that overall, NHS smoking cessation services were effective, with quitting (measured by carbon monoxide exhalation) rates of 53% at 4 weeks after intensive treatment, falling to 15% at 1 year (43). A trend towards increased effectiveness for group therapy and “buddy” therapy (where the patient is teamed with another patient in order that they may provide each other with support and encouragement) was also reported. However, it was apparent that women, younger smokers, pregnant smokers, and those from more deprived areas had lower short term quit rates than other groups, even though these groups were the most likely to access the cessation services (45). This is supported by other studies, which have shown that smokers from deprived socioeconomic groups are less likely to quit successfully even when accessing smoking cessation support, likely as the result of barriers presented by the patient’s personal social circumstances e.g. material hardships (46).

1.4.2 Effectiveness of the Local Stop Smoking Services

In respect to the government’s aim in reducing smoking and curbing smoking related health inequalities, research was conducted to assess the extent of effectiveness of the smoking cessation service in the more deprived regions. This research was commissioned with the knowledge that health care services are more accessible to the affluent groups, which is often known as the ‘inverse care law’. The study conducted in 2001-2002 using twenty-five smoking cessation centres showed that in 19 stop smoking services, one in three service users were from most deprived area compared to one in ten which are from the affluent areas (74). This demonstrated the effectiveness of the stop smoking services at both reaching and treating smokers in the most deprived regions, which are also areas with high smoking prevalence. Another study also analysed the stop smoking services records between July 2010 and June 2011 for 202,084 smokers in 49 services (11,46). The study suggests that the service was reaching the deprived groups: 59% of the service users were eligible for free prescriptions when the general population considered eligible was about 50% (47). Additionally, 14% were unemployed people at a time when the national unemployment rate was 8%.

1.5 Recent concern about Local Stop Smoking Support

Although local smoking cessation support has largely been considered to be cost effective and useful in supporting patients to quit smoking, concern has risen in recent years that quit rates are falling (71). Despite making considerable contribution in promoting reducing health inequalities in smoking prevalence, the UK government approach of implementing stop smoking services has faced number of challenges that include requirement for developing more innovative cessation particularly to accommodate most addicts as well as approaches towards controlling effects of smoking such related illness (48). According to Peto et al. (2015) and Bauld et al. (2007), whilst services were set up to provide free services to all across the country, things have changed so that what is provided in each region may now be different because they are commissioned to different providers(49,50). It is not clear that all smokers now get the same level of access to services. If not, there are possible dangers that, local provision may be accentuating inequalities in smoking and hence health. The regular evaluation of NHS smoking cessation services undertaken by the Health and Social Care Information Centre (HSCIC) showed that in 2012-2013, 4 weeks after treatment, 373,872 reported having quit, which was a 7% decrease on the 2011-2012 figure of 400,955 (51). This fell again for the year 2014-2015 to 229,688 (51). Suggested reasons for this fall include, the previous success of the campaign, where previous smokers who had good motivation for quitting have already done so through to weaknesses in the design of cessation services, where service providers have failed to take into account the complex reasons for smoking (51), particularly in areas of socio-economic deprivation. For example, it is thought these patients may lack social support from friends and family to quit, especially if the patient is exposed to many people who continue to smoke (51,53). Despite increased campaigns and advocacy against smoking, there is difference in priority of tobacco control and cut in cessation funds (76). ASH reported that smoking cessation funding was cut in 39% of upper-tier local authorities in England in 2015-16 (54). According to the study (75), this cut in budget has been happening over time where it reduced by 16% in 2014, 39% in 2015, and 59% in 2016. Cuts in smoking cessation budgets were principally due to cuts to the public health grant and wider cuts to local authority budgets (75). This shows that although, political support for tobacco control in UK local authorities mitigates, it does not remove the risk of cuts to budgets for cessation services (76).

Following the change from the primary care trusts to local government as part of the recommendations made by the Health and Social Care Act (Department of Health 2012), ASH and Cancer Research UK commissioned a report into the effectiveness of smoking cessation services, which aimed to identify any gaps in service provision caused by the restructuring process. In some regions this resulted in the outsourcing of smoking cessation service provision to outside companies, which it was feared may result in unequal quality of service provision between areas. This review generally concluded that the benefits of moving service provision responsibility to local government included increased constructive interdisciplinary relationships, along with the inclusion of tobacco control issues within more local council action and policy, and increased access for service providers to more people, for example through increased interaction with large employers and local communities and schools (Cheeseman 2016). Since many services have been decommissioned, there is however ongoing concern that needs are not being met and that changes may have led to poorer or less availability of services (ASH 2016).

1.6 Research problems and justification

Despite different strategies set in place by the UK government aimed to curb smoking through approaches that enhance public awareness and helping people quit smoking, the prevalence of the smoking still remains high due to failure to translate the policy into long term abstinence. Therefore, it is imperative that the government sustains public health smoking cessation services that are able to help people quit smoking in order to address the widening health inequalities resulting from tobacco consumption. Looking at the smoking cessation services, a considerable amount of money is spent on medication prescription and provision of the local stop smoking service provided by the National Health Services (NHS). This highlights the necessity to identify and provide the most effective intervention techniques. Studies have demonstrated the cost of smoking in terms of economic effects and cost of treating associated illness while relating to cessation services. The findings indicate a huge difference approach in attempt to curb the smoking. It is vital to recognise that the local smoking cessation intervention is one of the most cost effective interventions in medicine, which can be used to justify the continuation of cessation process.

1.7 Rationale of the study

Smoking is a major cause of health inequality and there are big regional differences in smoking prevalence and cessation, which are likely to be the result of differences in population, socio-economic disadvantage, and services. Despite approaches set up by the UK government to mitigate and reduce the problem such as developing legislation and policy, the prevalence of smoking particularly in different regions in UK calls for different strategy on smoking cessation. More so, although smoking cessation services have been available for some years, there are recent changes which mean that what is provided regionally may not be the same for each region. Interventions to support smoking cessation can be from brief advice in primary care to intensive support at a smoking cessation clinic. It is important that public health interventions promote smoking cessation work to reduce health inequality. It is also important that regional provision of services meets the regional need for services. If so, we would expect that provision of support for smoking cessation and use of services would be higher in regions with high smoking prevalence. In this perspective, there is a call for outlining the regional smoking prevalence and subsequently determining whether regions with the greatest prevalence of smoking have the greatest smoking cessation support and services provision. The primary care service employed different measures of support technique aimed at providing successful quit attempt. These cessation support for smokers can include brief advice provided by the GP, through to intensive behavioural therapy with or without pharmacological agent (43). Looking at regional differences in all of these types of support and how these relate to need (smoking prevalence), is important as the result identifies what proportion of smokers are receiving which level of cessation support. This aids when drawing conclusions regarding fair provision of smoking cessation support across all regions of England and to determine whether regions with increased cessation needs are adequately supported.

Aims and Objectives

This project investigated the regional smoking prevalence and service provision using relevant clinical data. This study further explored whether the correlation between need for services and services provision is seen for different socio-economic, gender and age groups. It helped establish whether gaps in provision of services are reducing or increasing health inequalities.

Study objectives

To describe the regional patterns in smoking prevalence across England

To describe the regional patterns in provision of support for smoking cessation, in primary care and in local stop smoking services.

To determine the association between regional need for services and regional support for smoking cessation

Chapter 2: Methodology

2.1Study design

An ecological study design which is a type of epidemiological study that looks at aggregate population level rather than an individual level. This design was used to explore the prevalence of in different regions across England and investigating whether cessation needs are being met by the services at regional level in the country in terms of techniques set in place supporting smoking cessation. This approach was appropriate as the study aimed to investigate geographical comparisons of smoking prevalence and service provision of the regions in England.

2.2 Data source and study population

The data used in this research were extracted from two data sources. THIN data and the NHS SSS data. The THIN data were provided for this research as aggregate data. While the NHS SSS data is an existing data formed from an annual report, which presents results from the yearly monitoring of the NHS Stop Smoking Services in England. It should be noted that the study used those aged 16 and over available on the THIN database and only people registered to a general practice, contributed to the prospectively collected data recorded in the THIN database. All data supplied covered the period between April 2014 and March 2015. Using the Read code and the Additional Health Data (AHD) codes, interventions related to smoking such as smokers who have received smoking cessation advice, prescription of cessation medication was identified and extracted from the THIN database. The THIN data is coded using READ code. Developed by Dr James Read, the READ codes are clinical terms, synonyms, and abbreviations covering the patients’ variables that include symptoms and signs, diagnosis, lab results, treatments and therapy, and prescribed drugs. Smoking prevalence was used as a marker of smoking cessation need while the GP’s advice, medication, and use of SSS was used as an indicator of cessation services support provided.

2.2.1THIN cessation data

The Health Improvement Network (THIN) is a large UK general practice database which contains anonymised longitudinal patient records from over 600 General Practitioner (GP) practices with about 6% of the UK population registered in the system. The patient data are organized in four standardized and one linked file per practice that will be presented in the Table 1 below. The variables used within the study as presented in THIN database (shown in table1), shows patients’ demographics, medical information that includes date and location of diagnosis, therapy as medical services, Additional Health Data (AHD) such as vaccinations, patient’s height, birth, death, and pregnancy status, consultation including date, time, and duration, referrals, and role of services providers during data collection. The main information obtained from the THIN database used in this study, was the regional smoking prevalence both overall and by sociodemographic group, and regional measures of smoking cessation support provided in the primary care, including advice from GPs. The data provided by THUN, was in the format of an excel spreadsheet with the number of patients who are registered with the GP practice (denominators), number of current smokers per region, number of smokers referred to cessation service, receiving advice and the number of people on pharmacological intervention in individual columns all broken down by region of residence within England, socio-economic group, gender and age. Following analysis, the data was then be manipulated by aggregating across variables such as gender and age groups to give an overall regional prevalence. Moreover, CSD medical research technique was employed to check for reliability and validity of THIN data.

2.2.2 NHS Smoking Cessation Data

The study also used the secondary data obtained by the Health and Social Care Information Centre (HSCIC) from the NHS SSS data available from April 2015 to March 2016. These data were used to establish the regional rate of people setting a quit date through NHS Stop Smoking Services in 2015/16, and the rate of successful quitting. The NHS SSS dataset is aggregated data including the number of people setting a quit date and the number of people who have successfully quit (self-reported) after 4 week who had their result validated by carbon monoxide verification (CO). These results are provided by gender and age groups in England in 2015/2016. However, there was no provision of data by sociodemographic variables in the NHS SSS data.

2.3. Exposures and Outcomes

2.3.1 Regional prevalence of smoking (exposure)

This study compared smoking prevalence with two outcomes;

Local stop smoking service data

Smoking cessation support in primary care

With the NHS Stop Smoking Service data, the variables identified are the regional rate of service users per 1000 population in England in 2015/2016 and the proportion of successful quitters at 4 weeks. Subsequently, the proportion of successful quitters at 4 weeks was estimated. This was achieved by dividing the number of regional quitters by the regional number of those using the service. The proportions of successful quitters are the self-reported quitters after 4 weeks who had their results confirmed by Carbon Monoxide (CO) verification in 2015/16. Using the THIN databases, the study estimated the prevalence of smoking across the nine geographic region of the UK. The key variables in determining smoking prevalence, were the people reported as smokers in the database regionally. Using this data, the study estimated the proportion of smokers registered to a GP practice and the level of support they receive from them regionally. To estimate the smoking prevalence, which was used as a measure of cessation need in the study, those registered to a GP practice (denominators), were divided by number of current smokers per region. The study also determined the regional level of cessation support provided in the primary care by estimating the proportion of smokers using each of the stop smoking support provided. For example the percentage of smoker receiving GP’S advice and pharmacological intervention were calculated. The study also looked at the variation in the cessation service available to smokers in different social class in the regions, the deprivation level index (Townsend index) was subcategorized to include Townsend index high and low deprivation area. The Townsend index 1 was categorized as the low area of deprivation deprived area while the Townsend index 5 as the highly deprived area. The association of each indexes with both services provided was assessed, using a graph plot.

2.3.2. Measure of regional smoking cessation (Outcome)

Proportion of receiving smoking cessation advices from GPs were measured by observing the number of facilities providing the services in the given regions. Presumably, all the listed smoking cessation services centres offered advice to smokers to quit and guidance into quitting successful. Furthermore, regional smoking cessation as determined by measure on the current number of smokers, those receiving advice from GPs, and those under medication while also taking proportion rate per region population. Additionally, it observes the successful quitters rating per current smokers.

2.4 Statistical analysis

All statistical analysis dataset was imported from the raw data provided on excel spreadsheet to and analysed using Stata version 13 software. Scatterplots and correlations were used to look at the association between regional smoking prevalence and measures of smoking cessation support. This was done to determine whether the regional stop smoking service provision are meeting the regional smoking cessation need and to establish if a linear relationship between the two variables exist. The Pearson correlation was suitable for the plot because the variables were not on an ordinal scale as would have in spearman correlation. The p value for the level of significance was set at 0.05 and the Pearson’s correlation result was assessed in relation to the value of p < 0.05. Similarly, from the THIN datasets, a scatter graph was plotted using the prevalence of smoking against each measure of smoking cessation support.

2.5 Ethical consideration

Full ethical approval for the use of the THIN was obtained from University of Nottingham Division of Epidemiology and Public health ethics committee and the IMH Health Science Research Council (SRC) committee.

Chapter 3: Results

The rate of service user per 1000 regionally was calculated by dividing the number of users by an estimate of the regional population obtained from the Office of National Statistic (ONS) figures (ONS, 2016). The population statistic ONS’s population data, is a data estimated by single year in the UK, for England and Wales, Scotland and Northern Ireland (mid 2014) (office for National Population 2016). All participant were of the age group 16 and over.

3.1 Descriptive Analysis

3.1.1 Regional Smoking Prevalence and Provision of Advice and Treatment

The prevalence of smoking by region is shown in table 1. From the study, the highest proportion of smokers is found in the North East of England (21%) and Yorkshire and the Humber (20 %). While the East Midlands is seen to have the lowest smoking prevalence of 14%. However, the East of England, London, South East, and West Midlands, there was no variation in the amount of smokers, as they tend to have equal amount of 17% in the proportion of smokers in these regions. The study clearly indicates disparities between smokers receiving GP’s advice to stop smoking and those receiving medication in different regions of England. (i.e. a higher proportion of smokers are receiving GP’s advice to Stop Smoking as compared to those receiving medications to help with quitting). Although there appears to be minimum regional variation in people receiving quit advice, the North East has the majority of people receiving cessation advice (8%) while the highest reported smokers on cessation mediation is the South East (2%) region. The full description of the dataset is well illustrated in the Figure 1 and Table 2

3.1.2 Regional Stop smoking service data

The rate of Stop Smoking Service (SSS) users per 1000 regional population making quit attempts in all regions in England between April 2014 and March 2015 (Table 3) suggests that, the North East (11.59 per cent) and North West (10.44 per cent) regions had the highest rate of SSS service user per 1000 population. Whereas the South east had a lower rate of service use (6.47 per cent) in comparison to South west region (6.86 per cent), Yorkshire and Humber which reports approximately equal amount in the rate of SSS use per a thousand population (6.77 per cent). The success rate of giving up smoking (self-reported) also presented in table 3, generally showed little difference between regions in successful quitters in the England. Just over half (above 50%) of the proportion of people who set a quit date with the NHS stop smoking service made a successfully quit attempt. However, in the North East (43%) and the North West (45%) regions, the success rate of given up smoking appears to be less than 50%.

3.2 The association between smoking prevalence, provision of advice, and treatment

The smoking cessation service (GP advice and medication) distribution from THIN, showed no obvious departure from normality, when accessed for normality by a histogram. The relationship between smoking prevalence and provision of cessation provision seemed different for both graphs of the cessation services (Figure 2 and Figure 3 below).

These scattered plots generated from THIN with patients receiving GP’s advice plotted against smoking prevalence in the regions, in 2014/2015. Figure 2 depicts an association between patient receiving GP advice and the regional smoking prevalence. This relationship suggests, a higher proportion of smokers are getting GP’s advice in regions where there is higher smoking prevalence. The results of Pearson’s correlation coefficient displayed in table 4, indicates significant positive correlation between smoking prevalence and proportion receiving advice (r= 0.79, p=0.01),

The association between the regional smoking prevalence and the proportion of smokers getting medication (the r value 0.4, p= 0.275) produced from the scatter plots as seen in figure 3. This showed that there appears to be little association between regional smoking prevalence and the proportion receiving medication.

3.3 The association between smoking prevalence using the THIN and the NHS SSS dataset from April 2014 to March 2015.

3.3.1 The association between regional smoking prevalence and regional rates of Stop Smoking Service use

To ascertain the association between the regional smoking prevalence and regional rates of stop smoking service use, the correlation coefficient for the regional smoking prevalence versus the regional rate of smokers per 1000 service use was calculated (table 5). These suggest a positive association (the r value of 0.2). That is, the rate of smokers setting a quit date is higher in regions where the prevalence of smoking is higher but this is a weak correlation and not statistically significant (p=0.539). Although, this positively correlated, it was not strong enough to conclude an association (table 5).

3.2.3 The Association between Regional Smoking Prevalence and Regional Proportions of 4 week quitters at SSS.

The scatterplot and correlation coefficient for smoking prevalence and successful quit after 4 weeks suggests a negative association which means the proportion of successful quit attempts tends to be lower in regions with a high smoking prevalence, but this is a weak and did not show a statistically significant association (r=-0.334, p=0.379) as shown in the table 5 and figure 4.

In this perspective, Pearson’s correlation coefficient analysis has shown a statistically significant and strong enough correlation between smoking cessation advice and smoking cessation needs. This is suggestive that GPs are offering adequate advice. This is important as this physician’s cessation advice could help drive decisions to quit.

3.3 Association between service provision and needs across genders, age groups, and social class

From the results of the correlation analysis conducted to establish the relationship between the cessation service provision and smoking cessation needs across gender, age groups, and social economic class (appendix 1 to 4), it is clear that the report observed some health inequalities in the association of service provision in the male and female gender (table 6). This is more so in the provision of the medication service. As a larger association was seen in male smokers (r= 0.731, p=0.045) than the female gender (r=0.0048, p=0.990).

Looking at the association of GP’s advice in different age groups, it was shown that a significant and higher (r=0.708, p=0.033) relationship exist in the age groups 45-59 in comparison with all the other age groups (Table 7 below). Moreover, availability of medication as support mechanisms to smoking cessation was average for individuals aged between 16 and 34 years (r =0.551, p=0.124) while the coefficient (r) for those 60 years and above is the lowest (0.160) but highest p value being the highest (p=0.682). These suggest that GP cessation advice is targeted to young (16-34 years) age group. However, with increasing age, the analysis showed reduced association with smokers on prescribed medication.

Conversely, for the correlation coefficient analysis for different indexes of deprivation across the social economic class, it was seen that a significant highly correlated association (r=0.830, p=0.006) occurred between the provision of advice and smokers in the most deprived class in the regions (index 5). This was in sharp contrast to the medication service as a stronger association was seen in the least deprived region (index 1) than the most affluent social class across regions. (Scatter plot is shown in appendix 1 to 3). This has shown that while GPs cessation advice appeared to be adequately attending to cessation needs in the most deprived region, medication service seems to be addressing more cessation needs in affluent regions.

Chapter 4: Discussion

4.1 Summary of Key Findings

Prevalence varies across the country while it is highest in the North East, Yorkshire and Humber region, the East Midlands has the lowest prevalence. Similarly, the North East is associated with an increased rate of NHS SSS users per 1000 regional population as compared to the lowest the South East. However, this did not translate into increased proportion of successful quitters at 4 weeks as little difference was seen (Table 3) across the regions, with the lowest in the North east, while the South east has the highest. On cessation support, the regional provision of support for smokers in terms of GP advice seems to correlate with smoking prevalence. But for other indicators of support including pharmacological support, and NHS smoking cessation service usage, there appeared to be no observable correlation with the smoking prevalence. This reveals similar reports to the 2014 integrated household Survey (IHS) which shows the North East, North West and Yorkshire and the Humber have highest smoking prevalence (above 19%) while the South East and the South West (17%) have markedly lower rates of smoking (7%). The plot also reflects that regions with high cessation needs are also not being targeted for increased medication. The correlation coefficient (r) of smokers on medication showed a low positive correlation with regional smoking prevalence that is not statistically significant.

4.2 Findings in Relation to other studies

The first objective for this dissertation was to describe the regional smoking prevalence across the UK. From this analysis, the North East (21%) region of England has shown to have the greatest proportion of smokers than the London, South East, and the East of England (17%). This prevalence, from the primary care data is comparative to the HSCIC report on smoking in England. Similar report is also documented in the integrated household Survey(IHS) 2014, ASH 2015 and ASH 2016 report, Where the North East, North West and Yorkshire and the Humber were recorded as area of the high smoking prevalence (above 19 Per cent) while the South East and the South West (17 per cent) lower rates of smoking (ASH 2015). Regional pattern in prevalence of smoking largely follows deprivation. The North East of England is comparatively less affluent than other areas of England, with high levels of social deprivation and reduced life expectancy People from this area are less likely to have good health. Death rates from smoking-related illnesses are higher than the national average (276.1 compared with the national average of 206.8, or the affluent South West at 171.7 and South East 174.9) (Public Health England 2010). These observations are supported by other studies on smoking patterns in this region. A secondary analysis of household survey data from the areas of the North East covered by Middleborough council (Blackman 2008), reported smoking prevalence in these areas ranging from 10.3% to 74.5%. Unemployment was associated with smoking prevalence above 50%, as were low income, low levels of further education. (Blackman 2008). The authors cited low levels of status, control, and social participation as markers of social deprivation, which were also associated with an increased incidence in smoking (Blackman, 2008). However, this study goes further than previous studies to look at whether, the level of support for smokers by region correlates with prevalence. First, the proportion of smokers on cessation medication plotted against the regional smoking prevalence indicated correlation between the two variables suggesting areas with high smoking prevalence, GPs focus more on providing advice to smokers in which should lead to reduced prevalence. North east with highest (11.59%) rate of service users has a success rate of 43.47% whereas south east which has the lowest rate of services has the highest successful quits. This Suggests that, apart from the East Midlands where prevalence is lowest, regions where needs are highest, are not being targeted for medication.

On inspection of smoking cessation service support and the prevalence of cessation needs (fig 4), did not lead to an overall statistically significant increase during the period of the study (r=0.237, p=0.539). The lack of significant increase and low correlation coefficient suggest smoking cessation support has not potentially met the regional cessation needs, especially in regions where needs are higher. Findings suggest that regional basis SSS is not doing any better in regions with high smoking prevalence. When further analysis was conducted to establish similarities in trends and outcome in cessation service provision and smoking cessation needs across gender, age groups, and social economic class in smokers (appendix 1 to 4). The report observed some variations and inequalities in service provision and needs in the men and women, different age groups and social economic classes. In general, the analysis showed little difference in the association across age and sex groups suggesting that any inequality of services provision in not different between these groups. Nevertheless, lack of increase in the medication from GP as identified in this study, has possibly not supported or encouraged these regions with higher prevalence, initiate a successful quit attempts. Some studies have also identified the lack of increase in medication of smoking cessation medication by the GP or might be that smokers are not receptive to using smoking cessation medication (Langley et al., 2010; Huang et al., 2013). However, the question to why this has failed is beyond the scope of this study. Previous study by (Lader 2009) on behalf of the Office of National Statistics has suggested that only 8% of smoker’s in the north east region, access NHS SSS (Lader 2009). As a result, efforts have been made to identify the barriers faced by people (i.e. smokers) in this region to access care, so they may be addressed by smoking cessation service support. Barriers identified include a high level of manual workers, who are more likely to smoke and thus surrounded by colleagues who smoke and with a perception of smoking as the norm. Another is inconvenient timing or location of smoking cessation clinics, or a lack of childcare to allow people attend services. Therefore, it is important that provision of services become as great in areas of high deprivation and high smoking prevalence, such as the North East (21%) and Yorkshire and the Humber (20%), as to provide adequate support to aid quit attempts. This reveals similar reports to the 2014 integrated household Survey (IHS) which shows the North East, North West and Yorkshire and the Humber have highest smoking prevalence (above 19%) while the South East and the South West (17%) have markedly lower rates of smoking (7%). Studies have also shown that physicians are vital and effective in initiating the quitting process (McEwen, et al., 2004) and could draw more smokers to using the cessation service support. It is very imperative that Physicians continue to provide cessation advice. Moreover, the findings of this study indicate the proportions of patients on GP Advice and medication did appear to vary significantly between areas. Analysis of Table 2 by region suggests that despite the previously discussed difference in the proportion of smokers in deprived areas such as the North East in comparison with areas such as the affluent South East, a similar proportion of smokers in both regions received smoking cessation help. Table 2 suggests that the availability and provision of smoking cessation services in the deprived North East in comparison with the affluent South East does not correspond to needs.

From the findings, GP advice service appears to be meeting more needs, as a higher proportion of smokers are getting above 70% of cessation advice in regions where there is higher smoking prevalence (that is North East, Yorkshire and the Humber regions). This finding was statistically significant and highly correlated (r=0.793, p=0.010) meaning advice given by doctors increases chance of smoker making a quit attempt. As such, it should ultimately reduce smoking prevalence. However, this is not so for the provision of medication service at regional level, as the scatter plots from the correlation analysis, reflects little provision of medication in regions with high cessation needs. With only approximately 5% pharmacological therapy provision, in Yorkshire and the Humber and 7% in the North East regions (regions with high smoking prevalence). This medication provision, showed a low correlation, which is not statistically significant (r=0.408, p= 0.275). This means the medication service provision is not adequately meeting the cessation needs. Although, GP advice service appears to be reaching more needs in all regions than the pharmacological therapy (table 2). It is important to note that although there exit a strong correlation between prevalence and GP’s advice, it does not necessarily mean that high prevalence areas are getting ‘enough’ support. Therefore, the advice and medical treatment being given is not helping to reduce maximum inequalities in smoking across the regions. This finding is however supported by a review of primary studies undertaken on this subject by the National Institute of Health and Care Excellence (NICE) to investigate the effectiveness of NHS smoking cessation therapy in England. This concluded that despite previous concerns, 4 good quality studies by (48–51) showed that smoking cessation advice did now appear to be reaching deprived populations, therefore the report concluded that health inequalities in deprived areas had been at least partially addressed in this regard (NICE 2013). This disagrees with the findings of this study because regions with high smoking cessation services indicate lowest successful quit rate. The correlation found suggest provision of cessation services might not be reaching deprived regions or changes affecting services provision or prevalence of smoking in different region. The services or prevalence may not be as equal now as they were or nor providing as well as low SES groups as they were then.

4.3 Strength and limitations

4.3.1 Strength of the Study

The main strength of this study is that, it was based on two large data sets; the THIN data had a very large sample size of over 14.5 million patients, while the NHS Smoking cessation data is fully representative to include every smokers who attends the SSS. By using a large sample size means that estimates obtained from the datasets are estimated with high precision, which increases both the reliability and validity of the data, and therefore of any conclusions drawn from its analysis (Chatburn RL. et. al, 2010). Both data sets also contained individuals from varying backgrounds, therefore the conclusions drawn from the analysis of this data can be considered to apply to the general population, as it is anticipated that both data sets were a representative sample. However, confirming this with further analysis may benefit this study (Roberts P, et. al. 2010). Additionally, this THIN data was processed and validated by Cegedim Strategic Data (CSD) Medical Research UK, which further confirms the reliability of it, as the validation process would likely have detected any anomalies (Ray S, Fitzpatrick S, Golubic R, et al. 2016). Although previous studies on smoking prevalence across England and the UK have demonstrated regional difference in prevalence, this study was the first to investigate whether variations in provision of smoking support like GP advice and medication varies regionally. The assertion obtained is that geographical and socio-economic components associable to region have an influence on prevalence and availability of support of cessation. Additionally, the study explores whether variation in support had an impact increasing or reducing smoking related health inequalities. An ecological study best suited the aims and objectives of this project as it allows investigation of factors affecting a large population of people, like England which this study is based on. Another strength of the study type is that it enables a quicker and cheaper data analysis from a large population.

4.3.2 Limitation

Based on the average regional population, the measure of an exposure used in an ecological study is only a proxy. Therefore, caution was needed when applying the result to individual level, as there is problem of ecological fallacy. The association observed between prevalence and availability of support mechanism may be only applicable at a group levels such that individuals in areas perceived to have high prevalence may not be getting better support. Although THIN is that provide huge data, recording remains is strongly associated with chronic disease indicating direct effect on clinical behaviour (77). As this study utilises a secondary data analysis approach, the reliability of its findings will be affected by the reliability of the original, primary results (67). There is a possibility that the little association in provision seen in the result, which is a non-significant findings may be due to lack of power might and have arisen by chance. Identifying or accounting for confounding and any bias variables in an ecological study or when the data was not primarily collected is difficult. As not all the information about the way the data was gathered is necessarily available, there could be confounders at the time the data was gathered which were not assessed for (67). This study focused on univariate associations and not adjusted for any confounders. It is possible that the age, sex, and SES distributions vary between regions and that these explained the observed patterns or findings seen in the study. The measures of smoking cessation support used may have been biased and unlikely to be accurate. For example, evidence favouring the Northern region as regions with the highest rate of service use, may be due to the fact that some smokers in those deprived regions are more likely to visit or use the GP practices. As they are likely to easily take ill due to other healthy factors (for example poor dietary, increased stress from work and finance) factors than their counterparts in more affluent areas. Although there have been studies on how complete/valid the THIN data on smoking are (Aparasu RR, et.al. 2014),( Ray S, Ray S, Fitzpatrick S, Golubic R, et al. 2016)

4.4 Reliability/validity/credibility

Validity, credibility, and reliability are important practice in any research. Several steps have been taken by the researcher to ensure the study validity (by ensuring the study design answered the research), credibility (ensured it is believable) and reliability (repeatability). To allow accurate replication of the study, a clear study method has been provided including all graphs and tables from the analysis to ensure the credibility and reliability of the study. However, as this study utilizes a secondary data analysis approach, the reliability of its findings will be affected by the reliability of the original, primary results (Aparasu RR, et.al. 2014). As previously discussed, accounting for bias and confounders was difficult due to the nature of the data. There may be confounding factors were not assessed for during data collection. However, as the presence of any confounding variables such as this are unknown, it is also unknown as to whether they affect the reliability of the results presented (Hulley SB, et.al 2013). The validity of the results presented in Chapter 3 was supported with an analysis of Pearson’s correlation coefficient, a statistical method used to evaluate the variations amongst a data set of observations in order to determine whether an observed effect is likely due to chance (Hirsch RP. 2016). This analysis gave a p value of 0.05 as the level of significance. For the relationships between the exposure and outcome variables, suggesting that this relationship was likely to be reliable and valid (Hirsch RP, 2016).

Chapter 5: Conclusion

This study has shown that smoking is more prevalent in the more deprived regions of England, specifically the North East, in comparison with the more affluent areas (for example the South East and South West), and has identified an inequality in the proportion of smokers accessing smoking cessation support, both with the smoking cessation advice and medication across all areas. The analysis has also shown a statistically significant and strong enough correlation between smoking cessation advice and smoking prevalence, meaning that the physicians are offering smoking cessation advice more in regions with more smokers. This is important as a previous study has shown this could help drive decisions to quit, and increase quit attempts. However, there was no statistically significant association between smoking need and provision of cessation medication, although positively correlated it was weak. This is to say, these services are not providing adequate support to the smokers in terms of medications. Since these medications are vital in preventing withdrawal symptoms and relapse. It is difficult to say these cessation services meet cessation needs. This study has shown no strong enough association and statistically significant evidence between smoking cessation service provision and cessation needs. Suggesting that regional smoking cessation provision has not met the regional cessation needs.

6. Recommendation

The results of this study suggest that on a general level, smoking cessation support availability is comparable across all regions. However, the incidence of smoking is still higher in more deprived regions such as the North East, therefore research should continue in this area to identify potential barriers to patients accessing these services, and health professionals should receive training and advice on how best to engage these patients in smoking cessation services so as to limit the health inequalities that affect these patients. Care should also be taken to limit differences in service provision organization between areas of affluence and in deprived areas.

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