Smoking cessation interventions for patients with coronary heart disease and comorbidities: an observational cross-sectional study in primary care

David N Blane; Daniel Mackay; Bruce Guthrie; Stewart W Mercer

doi:10.3399/bjgp16X688405

Abstract

Background Little is known about how smoking cessation practices in primary care differ for patients with coronary heart disease (CHD) who have different comorbidities.

Aim To determine the association between different patterns of comorbidity and smoking rates and smoking cessation interventions in primary care for patients with CHD.

Design and setting Cross-sectional study of 81 456 adults with CHD in primary care in Scotland.

Method Details of eight concordant physical comorbidities, 23 discordant physical comorbidities, and eight mental health comorbidities were extracted from electronic health records between April 2006 and March 2007. Multilevel binary logistic regression models were constructed to determine the association between these patterns of comorbidity and smoking status, smoking cessation advice, and smoking cessation medication (nicotine replacement therapy) prescribed.

Results The most deprived quintile had nearly three times higher odds of being current smokers than the least deprived (odds ratio [OR] 2.76; 95% confidence interval [CI] = 2.49 to 3.05). People with CHD and two or more mental health comorbidities had more than twice the odds of being current smokers than those with no mental health conditions (OR 2.11; 95% CI = 1.99 to 2.24). Despite this, those with two or more mental health comorbidities (OR 0.77; 95% CI = 0.61 to 0.98) were less likely to receive smoking cessation advice, but absolute differences were small.

Conclusion Patterns of comorbidity are associated with variation in smoking status and the delivery of smoking cessation advice among people with CHD in primary care. Those from the most deprived areas and those with mental health problems are considerably more likely to be current smokers and require additional smoking cessation support.

INTRODUCTION

Coronary heart disease (CHD) is the leading cause of death worldwide.¹ It is now recognised that most patients with CHD have additional comorbidities, with important implications for how patients are treated and how services are organised.²^,³ The type of comorbidity is also important, as different conditions may be more or less challenging to manage alongside CHD. For example, concordant physical conditions that share the same pathophysiological risk profile as CHD, such as hypertension, are more likely to share the same treatment and self-management plan, and are likely to present fewer problems in management than discordant physical conditions that are not directly related in either their pathogenesis or management.⁴ Similarly, patients with CHD and mental health comorbidities may not receive optimal care of physical conditions if they are mostly seen by mental health teams.⁵

Tobacco smoking is one of the main risk factors for the development of CHD,⁶ and stopping smoking reduces the risk of mortality in individuals with established CHD.⁷^,⁸ Smoking cessation practice in UK primary care involves three strands:

recording of smoking status;
offering brief interventions⁹ involving advice and encouragement to stop smoking; and
offering nicotine replacement therapy (NRT) or other smoking cessation medication and/or referral to specialist smoking cessation services.

Since 2004, UK GPs have been incentivised through the Quality and Outcomes Framework (QOF) to provide smoking cessation interventions for smokers who have certain chronic conditions, including CHD, that are regarded as a priority for smoking cessation. Yet there has been relatively little research into the quality of smoking cessation practice for patients with CHD in UK primary care.¹⁰ This study uses individual-level data to explore the relationship between three strands of smoking cessation practice (recorded smoking status, smoking cessation advice, and NRT prescribing) and three different patterns of comorbidity in patients with CHD, taking account of age, sex, deprivation, and the effect of clustering by practice.

The following three research questions were posed:

Does current smoking status in patients with CHD vary by patterns of comorbidity?
Does receipt of smoking cessation advice in current smokers with CHD vary by patterns of comorbidity?
Does receipt of smoking cessation medication in current smokers with CHD vary by patterns of comorbidity?

How this fits in

Smoking cessation improves health outcomes for adults with coronary heart disease (CHD), and primary care practitioners are ideally positioned to support people to stop smoking. This study has shown that the quality of smoking cessation care provided in primary care is generally high for adults with CHD, but that more targeted support for particular groups (such as those from deprived areas and those with mental health problems) is required.

METHOD

Study design and population

An observational cross-sectional study design was applied using population data from GP electronic medical records for one-third of the Scottish population. The data have previously been used to examine the prevalence of multimorbidity in the Scottish population and have been fully described in a previous paper.² Data were extracted from a dataset held by the Primary Care Clinical Informatics Unit (PCCIU) at the University of Aberdeen. The dataset comprises complete copies of clinical data for all registered patients from 314 general practices caring for 1 754 133 patients, approximately one-third of the Scottish population, and has previously been shown to be representative of all Scottish patients in terms of age, sex, and socioeconomic status.¹¹ Data were collected between April 2006 and March 2007.

Study variables

Smoking cessation practice

The three outcomes of interest in this study were recorded smoking status, recorded smoking cessation advice in the last 15 months, and recorded NRT prescribing in the last 15 months. Recorded smoking status was based on 30 Read Codes (the standard coding system used in UK primary care) in the original dataset, re-coded into ‘Ex-smoker’, ‘Never smoked’, or ‘Current smoker’. For the regression modelling, the categories were re-grouped into the binary outcome of ‘Current smoker’ versus ‘Ex/Never smoked’. Previous research has found good validity of GP recording of smoking status, comparable to nationally representative population surveys.¹²^–¹⁵

Recorded smoking cessation advice in the last 15 months (the timeframe used for the QOF) was based on 21 different Read Codes re-coded into ‘Advice recorded’ or ‘Advice not recorded’ (defined as the absence of a smoking cessation advice code). This timeframe was also used for recorded NRT prescribing, which was defined as NRT in British National Formulary section 4.10.2. All types of NRT (such as patches and gum) were grouped together. Read Code lists are provided in Appendix 1.

Comorbidities

Data on the presence of 40 conditions (that is, CHD and 39 comorbid conditions) were previously extracted by a team of researchers, and have been described in detail elsewhere.² The present study explored the effect of three different patterns of comorbidity on smoking cessation practice. These were:

concordant physical comorbidities, defined as physical conditions (vascular and respiratory) for which smoking is a significant risk factor, and for which smoking cessation is considered critical;
discordant physical comorbidities (the remaining physical conditions where smoking cessation is less critical); and
comorbid mental health conditions.

For all three patterns, the authors used a simple unweighted count of 0, 1, or ≥2 conditions. There were eight concordant physical conditions — five broadly vascular (hypertension, diabetes, chronic kidney disease [CKD], stroke/transient ischaemic attack [TIA], and peripheral vascular disease [PVD]) and three respiratory (asthma, chronic obstructive pulmonary disease [COPD], and bronchiectasis). These conditions were considered to be concordant in relation to smoking cessation in that they are all exacerbated by smoking, and smoking cessation is of upmost importance in their management. Most of these conditions are also included in the QOF, and patients with these conditions are routinely invited to chronic disease management clinics in primary care, where smoking cessation interventions should be initiated.¹⁶^,¹⁷ The eight mental health conditions and 23 discordant physical conditions can be found in Appendix 2, with their prevalences in this population.

Deprivation status

Socioeconomic deprivation was quantified using the Carstairs score, grouped into quintiles. This area-based measure of deprivation, derived from census and other routine data, has been widely used in health research.¹⁸

Statistical analysis

Descriptive analysis of the study population examined how smoking status, receipt of smoking cessation advice, and receipt of NRT varied by patient characteristics. For the three outcome variables of interest, multilevel binary logistic regression models were constructed in order to account for the clustering of patients within practices. Results are presented as univariate (crude) and multivariate (adjusted) odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment made for age group, sex, deprivation, and the three patterns of comorbidity. Analysis was carried out using STATA-MP version 14.0.

RESULTS

A total of 81 456 adults aged ≥25 years with a recorded diagnosis of CHD were included in the first regression model, representing a prevalence of CHD in the population studied of 4.64% (95% CI = 4.61 to 4.67). The distribution of study variables and outcomes and the characteristics of the study population are presented in Tables 1 and 2 respectively.

View this table:

Table 1.

Distribution of variables and outcomes

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Table 2.

Characteristics of total study population by smoking status, and of current smokers by receipt of smoking cessation advice and receipt of NRT

Smoking status

Smoking status was recorded in 99.6% of patients with CHD, with 16 745 (20.6%) recorded as current smokers, and 35 967 (44.2%) as ex-smokers. Table 3 shows the unadjusted and adjusted ORs of being a current smoker. There were marked differences in the odds of being a smoker by age group, deprivation quintile, and different patterns of comorbidity. Fewer females were smokers than males, but, in the fully adjusted model, differences between males and females were not statistically significant (OR 0.99; 95% CI = 0.95 to 1.03).

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Table 3.

Logistic regression model for being a current smoker

The odds of being a current smoker decreased with age, with lower odds for each age group compared with the reference group of <55-year-olds (42.8% of whom were current smokers). The percentage of current smokers rose with increasing deprivation, from 11.4% in the most affluent quintile to 30.4% in the most deprived. In the adjusted model, the odds of being a current smoker increased with each quintile of increased deprivation, such that those in the most deprived quintile had nearly three times the odds of being a current smoker compared with those in the most affluent quintile (OR 2.76; 95% CI = 2.49 to 3.05).

In terms of the effect of different patterns of comorbidity, for patients with one concordant physical comorbidity, the odds of being a current smoker were reduced compared with those without (OR 0.88; 95% CI = 0.84 to 0.93). For those with two or more concordant comorbidities, the odds ratio of being a smoker was not statistically significantly different. The odds of being a current smoker also decreased with additional discordant physical comorbidities, from OR 0.86 (95% CI = 0.83 to 0.90) for those with one discordant physical condition to OR 0.72 (95% CI = 0.69 to 0.75) for those with two or more. Those with two or more comorbid mental health conditions had more than twice the odds of being current smokers than those without (OR 2.11; 95% CI = 1.99 to 2.24).

Smoking cessation advice

In all, 15 395 (91.9%) current smokers were recorded as being given smoking cessation advice in the previous 15 months. Table 4 presents the multilevel binary logistic regression model for receipt of smoking cessation advice by current smokers. In the adjusted model, females had slightly higher odds of receiving smoking cessation advice compared with males (OR 1.15; 95% CI = 1.01 to 1.30), although absolute differences were small.

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Table 4.

Logistic regression model for receipt of smoking cessation advice by current smokers

In terms of deprivation status, adults with CHD from the most deprived quintile had lower odds of receiving smoking cessation advice than those in the most affluent quintile in the unadjusted model, but this was no longer statistically significant after adjustment (OR 0.80; 95% CI = 0.62 to 1.02). It is worth noting that more than 90% of smokers in every quintile received advice, which was the QOF threshold for this target.

Those with concordant physical conditions were more likely to receive smoking advice than those without, with OR 2.10 (95% CI = 1.77 to 2.51) for those with two or more concordant physical conditions compared with those with none, but with small absolute differences (94.1% compared with 89.1%). There was a similar, though less marked, relationship between additional discordant physical conditions and receipt of smoking cessation advice. Those with mental health conditions had significantly lower odds of receiving smoking cessation advice (for example, OR 0.74; 95% CI = 0.62 to 0.88, for those with one mental health comorbidity) but, again, absolute differences were small.

Smoking cessation medication

There were 2427 (14.5%) current smokers who received a prescription for NRT in the 15 months prior to data collection. Table 5 presents the multilevel binary logistic regression model for receipt of NRT by current smokers.

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Table 5.

Logistic regression model for receipt of NRT by current smokers

A greater proportion of females who were current smokers (17.1%) received NRT than males (12.8%, OR 1.48; 95% CI = 1.35 to 1.62). The proportion of smokers receiving NRT decreased with age, such that 21.2% of those smokers aged <55 years received NRT, compared with just 7.1% of those aged ≥75 years (OR 0.22; 95% CI = 0.19 to 0.27). In terms of deprivation, the percentage of smokers receiving NRT increased from 11.8% in the most affluent quintile to 15.7% in the most deprived quintile (OR 1.41; 95% CI = 1.11 to 1.80).

In terms of different patterns of comorbidity, the percentage of smokers receiving NRT was 13.2% for those with no concordant physical conditions, and 15.4% for those with two or more concordant physical conditions (OR 1.39; 95% CI = 1.24 to 1.56), with similar percentages for discordant physical conditions. Smokers with one or more mental health conditions were more likely to receive NRT (16.7% for one condition, and 16.2% for two or more) than those without any mental health comorbidity (13.1%). However, in the adjusted model, the OR was only significant for those smokers with one mental health condition (OR 1.18; 95% CI = 1.07 to 1.31).

DISCUSSION

Summary

This large nationally representative cross-sectional study has highlighted marked differences in smoking status among adults with coronary heart disease by age, sex, deprivation, and different patterns of comorbidity. Younger adults (<55 years), those living in the most deprived areas, and those with mental health comorbidities were more likely to be current smokers.

The quality of smoking cessation care provided in primary care was generally high — smoking status was recorded in 99.6% of patients with CHD, and recent smoking cessation advice recorded for 91.9% of current smokers, with only small absolute differences between groups. There was a modest but consistent trend for higher NRT prescription among those more deprived and those with more comorbidities.

Strengths and limitations

The strengths of this study include the large size of the dataset (>80 000 patients with CHD), the fact it was nationally representative, and the relatively large number of comorbid conditions included. Limitations include the fact that it was a cross-sectional study, so it was not possible to ascertain causality or temporality of any of the observed associations. As with any secondary data analysis, the quality and validity of the findings are only as good as the quality of the original data. In this case, confidence in the accuracy and consistency of the data is increased because the main outcome variables of interest were either collected routinely for QOF or were prescribing data, which are known to be well recorded.¹⁹ With regard to NRT prescriptions, the observed trend for higher NRT prescriptions among those more deprived and those with more comorbidities should be interpreted with caution, as the findings do not account for over-the-counter (OTC) NRT. This was widely available at relatively low cost in the UK at the time of the study, but may be more affordable and accessible to the more affluent.²⁰^,²¹

Finally, the authors are unable to specify what sort of smoking cessation advice was given or how often this was reinforced. The content and quality of GP ‘brief advice’ varies considerably, but this is not captured in this data — an important caveat when interpreting these results.²²^,²³ Previous studies have demonstrated reluctance by GPs to discuss smoking in depth, with only a fraction of opportunities to give smoking advice taken up.²⁴^,²⁵ The reasons for this reluctance are complex, but include lack of time, lack of confidence, and concerns about the impact on the doctor–patient relationship.²⁶^,²⁷

Comparison with existing literature

This study is one of only two that the authors are aware of that have assessed the associations between different patterns of comorbidity and smoking rates and smoking cessation interventions in primary care for patients with CHD. Further, it is the first to have examined concordant comorbidities in this regard. Consistent with this paper, Hippisley-Cox et al examined patients with CHD and serious mental health comorbidity (predominately schizophrenia or bipolar disorder) and found that most CHD care indicators — including recording of smoking status and smoking cessation advice — were achieved equally for patients with and without a serious mental health problem.²⁸

Individuals with CHD and one or more mental health comorbidity were more likely to be current smokers than those without; a finding that is consistent with previous research.²⁹^–³¹

The quality of care for physical health problems in patients with mental health conditions has come under scrutiny.⁵^,³² In a US study, smoking cessation counselling was included as one of five quality indicators used to compare the quality of care among patients with or without mental illness, and the impact of this on risk of mortality 1-year post-myocardial infarction (MI) was examined.³³ Deficits in quality of care explained a substantial proportion of the excess mortality experienced by patients with mental disorders after MI, but differences in smoking cessation counselling did not contribute to this.

Implications for research and practice

In this study, approximately 85% of current smokers did not receive any NRT. This may simply reflect best-practice recommendations to only prescribe NRT to those who are committed to stopping smoking.³⁴ It is clear, however, that better ways of converting patients with CHD who are current smokers into non-smokers are needed, particularly for those from more deprived areas and those with mental health comorbidity.

Current NHS stop smoking services are reaching disadvantaged smokers,³⁵ but a number of other barriers exist, including more challenging life circumstances, lack of social support, and higher nicotine dependency.³⁶^–³⁸ There are no easy solutions to these challenges,³⁹ but more proactive identification of smokers who want to quit, with referral to smoking cessation services, has been shown to increase quit attempts in previous primary-care-based studies.⁴⁰^,⁴¹

With regard to mental health comorbidity, the Royal College of General Practitioners (RCGP) has produced succinct primary care guidance on smoking and mental health, which outlines the physical, mental, and financial benefits of stopping smoking, and provides practitioners with advice on medication dose adjustment and monitoring of mental health during smoking cessation attempts.⁴² Clear communication and coordination between smoking cessation services and prescribers in primary and secondary care are recommended.

This study adds to a growing body of research that explores the effect of different combinations of comorbidity on quality of care outcomes.³^,⁴³^,⁴⁴ The grouping of concordant vascular physical conditions that the authors used in this study may be useful to clinical practice in the future, as they share a common pathophysiology or management. The study also adds to the large body of evidence on disparities between those with physical and mental health problems.⁵^,⁴⁵^,⁴⁶ Improving integration and coordination of care for people with multimorbidity is one of the key healthcare challenges of the 21st century.⁴⁷^,⁴⁸

Acknowledgments

The authors thank the Chief Scientist Office of the Scottish Government Health Directorates (Applied Research Programme Grant ARPG/07/1), the Scottish School of Primary Care, which part-supported Stewart W Mercer’s post and the development of the Applied Research Programme, and the Primary Care Clinical Informatics Unit at the University of Aberdeen, which provided the data. The views in this article are not necessarily the views of the University of Aberdeen or University of Glasgow, their agents, or employees. The authors also thank Katie Wilde and Fiona Chaloner of the University of Aberdeen, who performed the initial data extraction and management.

Appendix 1. Read Codes for the three smoking-related outcome variables^a

Smoking status
Read Code	Description	Coding
137.	Tobacco consumption	2
1371.	Never smoked tobacco	0
1372.	Trivial smoker <1 cigarette/day	2
1373.	Light smoker 1–9 cigarettes/day	2
1374.	Moderate smoker 10–19 cigarettes/day	2
1375.	Heavy smoker 20–39 cigarettes/day	2
1376.	Very heavy smoker 40+ cigarettes/day	2
1377.	Ex-trivial smoker (<1/day)	1
1378.	Ex-light smoker (1–9/day)	1
1379.	Ex-moderate smoker (10–19/day)	1
137A.	Ex-heavy smoker (20–39/day)	1
137B.	Ex-very heavy smoker (40+/day)	1
137C.	Keeps trying to stop smoking	2
137D.	Admitted tobacco consumption untrue	SYSMIS
137E.	Tobacco consumption unknown	SYSMIS
137F.	Ex-smoker — amount unknown	1
137G.	Trying to give up smoking	2
137H.	Pipe smoker	2
137I.	Passive smoker	SYSMIS
137J.	Cigar smoker	2
137K.	Stopped smoking	1
137L.	Current non-smoker	1
137M.	Rolls own cigarettes	2
137N.	Ex-pipe smoker	1
137O.	Ex-cigar smoker	1
137P.	Cigarette smoker	2
137Q.	Smoking started	2
137R.	Current smoker	2
137S.	Ex-smoker	1
137Z.	Tobacco consumption NOS	2
Smoking cessation advice
Read Code	Description	Coding
9OOZ.	Stop-smoking monitor administration NOS	1
9OOA.	Stop-smoking monitor check done	1
9OO9.	Stop-smoking monitoring deletion	1
9OO7.	Stop-smoking monitor verbal interview	1
9OO2.	Refuses stop-smoking monitor	0
9OO1.	Attends stop-smoking monitor	1
9OO.	Anti-smoking monitoring administration	1
9N4M.	Did not attend smoking cessation advice	0
8HTK.	Referral to stop-smoking clinic	1
8H7i.	Referral to smoking cessation adviser	1
8CAL.	Smoking cessation advice	1
8B3Y.1	Over-the-counter nicotine replacement therapy provided free
8B2B.	Nicotine replacement therapy	1
67H1.	Lifestyle advice re: smoking	1
6791.	Health education — smoking	1
13p5.	Smoking cessation programme start date	1
13p1.	Smoking status at 4 weeks	1
13p.	Smoking cessation milestones	1

↵a Smoking cessation medication: with regard to the recording of NRT prescriptions, there were 123 different ways of recording these prescriptions, including brand names and different forms of delivery (for example, lozenges, patches, gum). For the purposes of re-coding, all of the 123 different names began with just seven different combinations of first letters — Niq, NiQ, NIQ, niq, Nic, NIC, and nic. Again, a binary variable was formed with ‘NRT not prescribed’ (0) versus ‘NRT prescribed’ (1). NRT = nicotine replacement therapy. SYSMIS = missing.

Appendix 2. The three patterns of comorbid conditions, with their prevalences^a

Concordant physical comorbidity	Prevalence (%)
Hypertension	51.7
Diabetes	21.5
Chronic kidney disease	14.0
COPD/Bronchitis	13.3
Stroke/TIA	13.1
Peripheral vascular disease	9.2
Asthma	7.5
Bronchiectasis	0.5
Mental health comorbidity
Depression	16.9
Anxiety	10.5
Psychoactive drugs	8.9
Alcohol	4.8
Dementia	3.1
Schizophrenia/bipolar disorder	0.9
Anorexia/bulimia	0.2
Learning disability	0.1
Discordant physical comorbidity
Pain	24.2
Heart failure	13.8
Rheumatoid arthritis	12.0
Thyroid disorders	11.8
Atrial fibrillation	11.0
Constipation	10.5
Hearing loss	10.3
Diverticular disease	10.0
Cancer	7.8
Dyspepsia	7.0
Irritable bowel syndrome	4.8
Prostate problems	4.2
Glaucoma	3.6
Blindness	2.1

↵a Other discordant physical conditions with prevalence of less than 2% in the sample population: epilepsy (1.2), psoriasis/eczema (1.2), inflammatory bowel disease (1.1), Parkinson’s (0.8), chronic sinusitis (0.8), migraine (0.6), chronic liver disease (0.4), multiple sclerosis (0.2), and viral hepatitis (0.0). COPD = chronic obstructive pulmonary disease. TIA = transient ischaemic attack.

Notes

Funding

No funding was obtained for this study.

Ethical approval

The NHS National Research Ethics Service had previously approved the anonymous use of these data for research purposes, therefore this study did not need individual ethics approval.

Provenance

Freely submitted; externally peer reviewed.

Competing interests

The authors have declared no competing interests.

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Received June 16, 2016.
Revision requested July 25, 2016.
Accepted September 22, 2016.

REFERENCES

1.↵
1. GBD 2013 Mortality and Causes of Death Collaborators.
(2015) Global, regional, and national age–sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 385(9963):117–171.
OpenUrl CrossRef PubMed
2.↵
1. Barnett K,
2. Mercer SW,
3. Norbury M,
4. et al.
(2012) Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 380(9836):37–43.
OpenUrl CrossRef PubMed
3.↵
1. Boyd CM,
2. Leff B,
3. Wolff JL,
4. et al.
(2011) Informing clinical practice guideline development and implementation: prevalence of coexisting conditions among adults with coronary heart disease. J Am Geriatr Soc 59(5):797–805.
OpenUrl CrossRef PubMed
4.↵
1. Piette JD,
2. Kerr EA
(2006) The impact of comorbid chronic conditions on diabetes care. Diabetes Care 29(3):725–731.
OpenUrl FREE Full Text
5.↵
1. Woodhead C,
2. Ashworth M,
3. Broadbent M,
4. et al.
(2016) Br J Gen Pract, Cardiovascular disease treatment among patients with severe mental illness: a data linkage study between primary and secondary care. DOI: https://doi.org/10.3399/bjgp16X685189.
6.↵
1. Conroy RM,
2. Pyörälä K,
3. Fitzgerald AP,
4. et al.
(2003) Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 24(11):987–1003.
OpenUrl CrossRef PubMed
7.↵
1. Critchley JA,
2. Capewell S
(2003) Mortality risk reduction associated with smoking cessation in patients with coronary heart disease: a systematic review. JAMA 290(1):86–97.
OpenUrl CrossRef PubMed
8.↵
1. Wilson K,
2. Gibson N,
3. Willan A,
4. Cook D
(2000) Effect of smoking cessation on mortality after myocardial infarction: meta-analysis of cohort studies. Arch Intern Med 160(7):939–944.
OpenUrl CrossRef PubMed
9.↵
1. Stead LF,
2. Buitrago D,
3. Preciado N,
4. et al.
(2013) Physician advice for smoking cessation. Cochrane Database Syst Rev 5:CD000165, doi:10.1002/14651858.CD000165.pub4.
OpenUrl CrossRef PubMed
10.↵
1. Langley TE,
2. Szatkowski L,
3. McNeill A,
4. et al.
(2012) Prescribing of nicotine replacement therapy to cardiovascular disease patients in England. Addiction 107(7):1341–1348.
OpenUrl CrossRef PubMed
11.↵
1. Elder R,
2. Kirkpatrick M,
3. Ramsay W,
4. et al.
(2007) Measuring quality in primary medical services using data from SPICE (Information and Statistics Division, NHS National Services Scotland, Edinburgh).
12.↵
1. Langley TE,
2. Szatkowski LC,
3. Wythe S,
4. Lewis SA
(2011) Can primary care data be used to monitor regional smoking prevalence? An analysis of The Health Improvement Network primary care data. BMC Public Health 11(1):773.
OpenUrl CrossRef PubMed
13.
1. Marston L,
2. Carpenter JR,
3. Walters KR,
4. et al.
(2014) Smoker, ex-smoker or non-smoker? The validity of routinely recorded smoking status in UK primary care: a cross-sectional study. BMJ Open 4(4):e004958.
OpenUrl Abstract/FREE Full Text
14.
1. Szatkowski L,
2. Lewis S,
3. McNeill A,
4. et al.
(2012) Can data from primary care medical records be used to monitor national smoking prevalence? J Epidemiol Community Health 66(9):791–795.
OpenUrl Abstract/FREE Full Text
15.↵
1. Booth HP,
2. Prevost AT,
3. Gulliford MC
(2013) Validity of smoking prevalence estimates from primary care electronic health records compared with national population survey data for England, 2007 to 2011. Pharmacoepidemiol Drug Saf 22(12):1357–1361.
OpenUrl CrossRef PubMed
16.↵
1. Coleman T,
2. Lewis S,
3. Hubbard R,
4. Smith C
(2007) Impact of contractual financial incentives on the ascertainment and management of smoking in primary care. Addiction 102(5):803–808.
OpenUrl CrossRef PubMed
17.↵
1. West R,
2. McNeill A,
3. Raw M
(2000) Smoking cessation guidelines for health professionals: an update. Health Education Authority. Thorax 55(12):987–999.
OpenUrl Abstract/FREE Full Text
18.↵
1. Carstairs V,
2. Morris R
(1991) Deprivation and health in Scotland (Aberdeen University Press, Aberdeen).
19.↵
1. Whitelaw FG,
2. Nevin SL,
3. Milne RM,
4. et al.
(1996) Completeness and accuracy of morbidity and repeat prescribing records held on general practice computers in Scotland. Br J Gen Pract 46(404):181–186.
OpenUrl Abstract/FREE Full Text
20.↵
1. Bernstein SL,
2. Cabral L,
3. Maantay J,
4. et al.
(2009) Disparities in access to over-the-counter nicotine replacement products in New York city pharmacies. Am J Public Health 99(9):1699–1704.
OpenUrl CrossRef PubMed
21.↵
1. Bonevski B,
2. Bryant J,
3. Paul C
(2011) Encouraging smoking cessation among disadvantaged groups: a qualitative study of the financial aspects of cessation. Drug Alcohol Rev 30(4):411–418.
OpenUrl CrossRef PubMed
22.↵
1. Coleman T
(2010) Do financial incentives for delivering health promotion counselling work? Analysis of smoking cessation activities stimulated by the quality and outcomes framework. BMC Public Health 10(1):167.
OpenUrl CrossRef PubMed
23.↵
1. Coleman T,
2. Cheater F,
3. Murphy E
(2004) Qualitative study investigating the process of giving anti-smoking advice in general practice. Patient Educ Couns 52(2):159–163.
OpenUrl CrossRef PubMed
24.↵
1. Coleman T,
2. Wynn AT,
3. Barrett S,
4. et al.
(2001) Intervention study to evaluate pilot health promotion payment aimed at increasing general practitioners’ antismoking advice to smokers. BMJ 323(7310):435–436.
OpenUrl FREE Full Text
25.↵
1. Coleman T,
2. Wilson A
(2000) Anti-smoking advice from general practitioners: is a population-based approach to advice-giving feasible? Br J Gen Pract 50(461):1001–1004.
OpenUrl Abstract/FREE Full Text
26.↵
1. Vogt F,
2. Hall S,
3. Marteau TM
(2005) General practitioners’ and family physicians’ negative beliefs and attitudes towards discussing smoking cessation with patients: a systematic review. Addiction 100(10):1423–1431.
OpenUrl CrossRef PubMed
27.↵
1. Coleman T,
2. Murphy E,
3. Cheater F
(2000) Factors influencing discussion of smoking between general practitioners and patients who smoke: a qualitative study. Br J Gen Pract 50(452):207–210.
OpenUrl Abstract/FREE Full Text
28.↵
1. Hippisley-Cox J,
2. Parker C,
3. Coupland C,
4. Vinogradova Y
(2007) Inequalities in the primary care of patients with coronary heart disease and serious mental health problems: a cross-sectional study. Heart 93(10):1256–1262.
OpenUrl Abstract/FREE Full Text
29.↵
1. Breslau N,
2. Kilbey MM,
3. Andreski P
(1994) DSM-III-R nicotine dependence in young adults: prevalence, correlates and associated psychiatric disorders. Addiction 89(6):743–754.
OpenUrl CrossRef PubMed
30.
1. Lasser K,
2. Boyd JW,
3. Woolhandler S,
4. et al.
(2000) Smoking and mental illness: a population-based prevalence study. JAMA 284(20):2606–2610.
OpenUrl CrossRef PubMed
31.↵
1. Osborn DP,
2. Nazareth I,
3. King MB
(2006) Risk for coronary heart disease in people with severe mental illness: cross-sectional comparative study in primary care. Br J Psychiatry 188:271–277.
OpenUrl Abstract/FREE Full Text
32.↵
1. Mitchell AJ,
2. Malone D,
3. Doebbeling CC
(2009) Quality of medical care for people with and without comorbid mental illness and substance misuse: systematic review of comparative studies. Br J Psychiatry 194(6):491–499.
OpenUrl Abstract/FREE Full Text
33.↵
1. Druss BG,
2. Bradford WD,
3. Rosenheck RA,
4. et al.
(2001) Quality of medical care and excess mortality in older patients with mental disorders. Arch Gen Psychiatry 58(6):565–572.
OpenUrl CrossRef PubMed
34.↵
1. National Institute for Health and Care Excellence
(2008) Review of Public Health guidance Smoking cessation services in primary care, pharmacies, local authorities and workplaces, particularly for manual working groups, pregnant women and hard to reach communities PH10 (NICE, London).
35.↵
1. Hiscock R,
2. Bauld L
(2013) Stop smoking services and health inequalities. National Centre for Smoking Cessation and Training.
36.↵
1. Chandola T,
2. Head J,
3. Bartley M
(2004) Sociodemographic predictors of quitting smoking: how important are household factors? Addiction 99(6):770–777.
OpenUrl CrossRef PubMed
37.
1. Paul CL,
2. Ross S,
3. Bryant J,
4. et al.
(2010) The social context of smoking: a qualitative study comparing smokers of high versus low socioeconomic position. BMC Public Health 10(1):211.
OpenUrl CrossRef PubMed
38.↵
1. Siahpush M,
2. McNeill A,
3. Borland R,
4. Fong GT
(2006) Socioeconomic variations in nicotine dependence, self-efficacy, and intention to quit across four countries: findings from the International Tobacco Control (ITC) Four Country Survey. Tob Control 15(suppl 3):iii71–iii75.
OpenUrl Abstract/FREE Full Text
39.↵
1. Murray RL,
2. Bauld L,
3. Hackshaw LE,
4. McNeill A
(2009) Improving access to smoking cessation services for disadvantaged groups: a systematic review. J Public Health 31(2):258–277.
OpenUrl CrossRef PubMed
40.↵
1. McEwen A,
2. Condliffe L,
3. Gilbert A
(2010) Promoting engagement with a Stop Smoking Service via pro-active telephone calls. Patient Educ Couns 80(2):277–279.
OpenUrl CrossRef PubMed
41.↵
1. Murray RL,
2. Coleman T,
3. Antoniak M,
4. et al.
(2008) The effect of proactively identifying smokers and offering smoking cessation support in primary care populations: a cluster-randomized trial. Addiction 103(6):998–1006.
OpenUrl CrossRef PubMed
42.↵
1. Campion J,
2. Shiers D,
3. Britton J,
4. et al.
(2014) Primary care guidance on smoking and mental disorders — 2014 update (Royal College of General Practitioners and Royal College of Psychiatrists).
43.↵
1. Redelmeier DA,
2. Tan SH,
3. Booth GL
(1998) The treatment of unrelated disorders in patients with chronic medical diseases. N Engl J Med 338(21):1516–1520.
OpenUrl CrossRef PubMed
44.↵
1. Turner BJ,
2. Hollenbeak CS,
3. Weiner M,
4. et al.
(2008) Effect of unrelated comorbid conditions on hypertension management. Ann Intern Med 148(8):578–586.
OpenUrl CrossRef PubMed
45.↵
1. Chang CK,
2. Hayes RD,
3. Perera G,
4. et al.
(2011) Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London. PLoS One 6(5):e19590.
OpenUrl CrossRef PubMed
46.↵
1. Phelan M,
2. Stradins L,
3. Morrison S
(2001) Physical health of people with severe mental illness. BMJ 322(7284):443–444.
OpenUrl FREE Full Text
47.↵
1. Guthrie B,
2. Payne K,
3. Alderson P,
4. et al.
(2012) Adapting clinical guidelines to take account of multimorbidity. BMJ 345:e6341.
OpenUrl FREE Full Text
48.↵
1. Starfield B
(2011) Challenges to primary care from co- and multi-morbidity. Prim Health Care Res Dev 12(1):1–2.
OpenUrl CrossRef PubMed

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[1] 1.↵
GBD 2013 Mortality and Causes of Death Collaborators.
(2015) Global, regional, and national age–sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 385(9963):117–171.
OpenUrl CrossRef PubMed

[2] GBD 2013 Mortality and Causes of Death Collaborators.

[3] 2.↵
Barnett K,
Mercer SW,
Norbury M,
et al.
(2012) Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 380(9836):37–43.
OpenUrl CrossRef PubMed

[4] Barnett K,

[5] Mercer SW,

[6] Norbury M,

[7] et al.

[8] 3.↵
Boyd CM,
Leff B,
Wolff JL,
et al.
(2011) Informing clinical practice guideline development and implementation: prevalence of coexisting conditions among adults with coronary heart disease. J Am Geriatr Soc 59(5):797–805.
OpenUrl CrossRef PubMed

[9] Boyd CM,

[10] Leff B,

[11] Wolff JL,

[12] et al.

[13] 4.↵
Piette JD,
Kerr EA
(2006) The impact of comorbid chronic conditions on diabetes care. Diabetes Care 29(3):725–731.
OpenUrl FREE Full Text

[14] Piette JD,

[15] Kerr EA

[16] 5.↵
Woodhead C,
Ashworth M,
Broadbent M,
et al.
(2016) Br J Gen Pract, Cardiovascular disease treatment among patients with severe mental illness: a data linkage study between primary and secondary care. DOI: https://doi.org/10.3399/bjgp16X685189.

[17] Woodhead C,

[18] Ashworth M,

[19] Broadbent M,

[20] et al.

[21] 6.↵
Conroy RM,
Pyörälä K,
Fitzgerald AP,
et al.
(2003) Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 24(11):987–1003.
OpenUrl CrossRef PubMed

[22] Conroy RM,

[23] Pyörälä K,

[24] Fitzgerald AP,

[25] et al.

[26] 7.↵
Critchley JA,
Capewell S
(2003) Mortality risk reduction associated with smoking cessation in patients with coronary heart disease: a systematic review. JAMA 290(1):86–97.
OpenUrl CrossRef PubMed

[27] Critchley JA,

[28] Capewell S

[29] 8.↵
Wilson K,
Gibson N,
Willan A,
Cook D
(2000) Effect of smoking cessation on mortality after myocardial infarction: meta-analysis of cohort studies. Arch Intern Med 160(7):939–944.
OpenUrl CrossRef PubMed

[30] Wilson K,

[31] Gibson N,

[32] Willan A,

[33] Cook D

[34] 9.↵
Stead LF,
Buitrago D,
Preciado N,
et al.
(2013) Physician advice for smoking cessation. Cochrane Database Syst Rev 5:CD000165, doi:10.1002/14651858.CD000165.pub4.
OpenUrl CrossRef PubMed

[35] Stead LF,

[36] Buitrago D,

[37] Preciado N,

[38] et al.

[39] 10.↵
Langley TE,
Szatkowski L,
McNeill A,
et al.
(2012) Prescribing of nicotine replacement therapy to cardiovascular disease patients in England. Addiction 107(7):1341–1348.
OpenUrl CrossRef PubMed

[40] Langley TE,

[41] Szatkowski L,

[42] McNeill A,

[43] et al.

[44] 11.↵
Elder R,
Kirkpatrick M,
Ramsay W,
et al.
(2007) Measuring quality in primary medical services using data from SPICE (Information and Statistics Division, NHS National Services Scotland, Edinburgh).

[45] Elder R,

[46] Kirkpatrick M,

[47] Ramsay W,

[48] et al.

[49] 12.↵
Langley TE,
Szatkowski LC,
Wythe S,
Lewis SA
(2011) Can primary care data be used to monitor regional smoking prevalence? An analysis of The Health Improvement Network primary care data. BMC Public Health 11(1):773.
OpenUrl CrossRef PubMed

[50] Langley TE,

[51] Szatkowski LC,

[52] Wythe S,

[53] Lewis SA

[54] 13.
Marston L,
Carpenter JR,
Walters KR,
et al.
(2014) Smoker, ex-smoker or non-smoker? The validity of routinely recorded smoking status in UK primary care: a cross-sectional study. BMJ Open 4(4):e004958.
OpenUrl Abstract/FREE Full Text

[55] Marston L,

[56] Carpenter JR,

[57] Walters KR,

[58] et al.

[59] 14.
Szatkowski L,
Lewis S,
McNeill A,
et al.
(2012) Can data from primary care medical records be used to monitor national smoking prevalence? J Epidemiol Community Health 66(9):791–795.
OpenUrl Abstract/FREE Full Text

[60] Szatkowski L,

[61] Lewis S,

[62] McNeill A,

[63] et al.

[64] 15.↵
Booth HP,
Prevost AT,
Gulliford MC
(2013) Validity of smoking prevalence estimates from primary care electronic health records compared with national population survey data for England, 2007 to 2011. Pharmacoepidemiol Drug Saf 22(12):1357–1361.
OpenUrl CrossRef PubMed

[65] Booth HP,

[66] Prevost AT,

[67] Gulliford MC

[68] 16.↵
Coleman T,
Lewis S,
Hubbard R,
Smith C
(2007) Impact of contractual financial incentives on the ascertainment and management of smoking in primary care. Addiction 102(5):803–808.
OpenUrl CrossRef PubMed

[69] Coleman T,

[70] Lewis S,

[71] Hubbard R,

[72] Smith C

[73] 17.↵
West R,
McNeill A,
Raw M
(2000) Smoking cessation guidelines for health professionals: an update. Health Education Authority. Thorax 55(12):987–999.
OpenUrl Abstract/FREE Full Text

[74] West R,

[75] McNeill A,

[76] Raw M

[77] 18.↵
Carstairs V,
Morris R
(1991) Deprivation and health in Scotland (Aberdeen University Press, Aberdeen).

[78] Carstairs V,

[79] Morris R

[80] 19.↵
Whitelaw FG,
Nevin SL,
Milne RM,
et al.
(1996) Completeness and accuracy of morbidity and repeat prescribing records held on general practice computers in Scotland. Br J Gen Pract 46(404):181–186.
OpenUrl Abstract/FREE Full Text

[81] Whitelaw FG,

[82] Nevin SL,

[83] Milne RM,

[84] et al.

[85] 20.↵
Bernstein SL,
Cabral L,
Maantay J,
et al.
(2009) Disparities in access to over-the-counter nicotine replacement products in New York city pharmacies. Am J Public Health 99(9):1699–1704.
OpenUrl CrossRef PubMed

[86] Bernstein SL,

[87] Cabral L,

[88] Maantay J,

[89] et al.

[90] 21.↵
Bonevski B,
Bryant J,
Paul C
(2011) Encouraging smoking cessation among disadvantaged groups: a qualitative study of the financial aspects of cessation. Drug Alcohol Rev 30(4):411–418.
OpenUrl CrossRef PubMed

[91] Bonevski B,

[92] Bryant J,

[93] Paul C

[94] 22.↵
Coleman T
(2010) Do financial incentives for delivering health promotion counselling work? Analysis of smoking cessation activities stimulated by the quality and outcomes framework. BMC Public Health 10(1):167.
OpenUrl CrossRef PubMed

[95] Coleman T

[96] 23.↵
Coleman T,
Cheater F,
Murphy E
(2004) Qualitative study investigating the process of giving anti-smoking advice in general practice. Patient Educ Couns 52(2):159–163.
OpenUrl CrossRef PubMed

[97] Coleman T,

[98] Cheater F,

[99] Murphy E

[100] 24.↵
Coleman T,
Wynn AT,
Barrett S,
et al.
(2001) Intervention study to evaluate pilot health promotion payment aimed at increasing general practitioners’ antismoking advice to smokers. BMJ 323(7310):435–436.
OpenUrl FREE Full Text

[101] Coleman T,

[102] Wynn AT,

[103] Barrett S,

[104] et al.

[105] 25.↵
Coleman T,
Wilson A
(2000) Anti-smoking advice from general practitioners: is a population-based approach to advice-giving feasible? Br J Gen Pract 50(461):1001–1004.
OpenUrl Abstract/FREE Full Text

[106] Coleman T,

[107] Wilson A

[108] 26.↵
Vogt F,
Hall S,
Marteau TM
(2005) General practitioners’ and family physicians’ negative beliefs and attitudes towards discussing smoking cessation with patients: a systematic review. Addiction 100(10):1423–1431.
OpenUrl CrossRef PubMed

[109] Vogt F,

[110] Hall S,

[111] Marteau TM

[112] 27.↵
Coleman T,
Murphy E,
Cheater F
(2000) Factors influencing discussion of smoking between general practitioners and patients who smoke: a qualitative study. Br J Gen Pract 50(452):207–210.
OpenUrl Abstract/FREE Full Text

[113] Coleman T,

[114] Murphy E,

[115] Cheater F

[116] 28.↵
Hippisley-Cox J,
Parker C,
Coupland C,
Vinogradova Y
(2007) Inequalities in the primary care of patients with coronary heart disease and serious mental health problems: a cross-sectional study. Heart 93(10):1256–1262.
OpenUrl Abstract/FREE Full Text

[117] Hippisley-Cox J,

[118] Parker C,

[119] Coupland C,

[120] Vinogradova Y

[121] 29.↵
Breslau N,
Kilbey MM,
Andreski P
(1994) DSM-III-R nicotine dependence in young adults: prevalence, correlates and associated psychiatric disorders. Addiction 89(6):743–754.
OpenUrl CrossRef PubMed

[122] Breslau N,

[123] Kilbey MM,

[124] Andreski P

[125] 30.
Lasser K,
Boyd JW,
Woolhandler S,
et al.
(2000) Smoking and mental illness: a population-based prevalence study. JAMA 284(20):2606–2610.
OpenUrl CrossRef PubMed

[126] Lasser K,

[127] Boyd JW,

[128] Woolhandler S,

[129] et al.

[130] 31.↵
Osborn DP,
Nazareth I,
King MB
(2006) Risk for coronary heart disease in people with severe mental illness: cross-sectional comparative study in primary care. Br J Psychiatry 188:271–277.
OpenUrl Abstract/FREE Full Text

[131] Osborn DP,

[132] Nazareth I,

[133] King MB

[134] 32.↵
Mitchell AJ,
Malone D,
Doebbeling CC
(2009) Quality of medical care for people with and without comorbid mental illness and substance misuse: systematic review of comparative studies. Br J Psychiatry 194(6):491–499.
OpenUrl Abstract/FREE Full Text

[135] Mitchell AJ,

[136] Malone D,

[137] Doebbeling CC

[138] 33.↵
Druss BG,
Bradford WD,
Rosenheck RA,
et al.
(2001) Quality of medical care and excess mortality in older patients with mental disorders. Arch Gen Psychiatry 58(6):565–572.
OpenUrl CrossRef PubMed

[139] Druss BG,

[140] Bradford WD,

[141] Rosenheck RA,

[142] et al.

[143] 34.↵
National Institute for Health and Care Excellence
(2008) Review of Public Health guidance Smoking cessation services in primary care, pharmacies, local authorities and workplaces, particularly for manual working groups, pregnant women and hard to reach communities PH10 (NICE, London).

[144] National Institute for Health and Care Excellence

[145] 35.↵
Hiscock R,
Bauld L
(2013) Stop smoking services and health inequalities. National Centre for Smoking Cessation and Training.

[146] Hiscock R,

[147] Bauld L

[148] 36.↵
Chandola T,
Head J,
Bartley M
(2004) Sociodemographic predictors of quitting smoking: how important are household factors? Addiction 99(6):770–777.
OpenUrl CrossRef PubMed

[149] Chandola T,

[150] Head J,

[151] Bartley M

[152] 37.
Paul CL,
Ross S,
Bryant J,
et al.
(2010) The social context of smoking: a qualitative study comparing smokers of high versus low socioeconomic position. BMC Public Health 10(1):211.
OpenUrl CrossRef PubMed

[153] Paul CL,

[154] Ross S,

[155] Bryant J,

[156] et al.

[157] 38.↵
Siahpush M,
McNeill A,
Borland R,
Fong GT
(2006) Socioeconomic variations in nicotine dependence, self-efficacy, and intention to quit across four countries: findings from the International Tobacco Control (ITC) Four Country Survey. Tob Control 15(suppl 3):iii71–iii75.
OpenUrl Abstract/FREE Full Text

[158] Siahpush M,

[159] McNeill A,

[160] Borland R,

[161] Fong GT

[162] 39.↵
Murray RL,
Bauld L,
Hackshaw LE,
McNeill A
(2009) Improving access to smoking cessation services for disadvantaged groups: a systematic review. J Public Health 31(2):258–277.
OpenUrl CrossRef PubMed

[163] Murray RL,

[164] Bauld L,

[165] Hackshaw LE,

[166] McNeill A

[167] 40.↵
McEwen A,
Condliffe L,
Gilbert A
(2010) Promoting engagement with a Stop Smoking Service via pro-active telephone calls. Patient Educ Couns 80(2):277–279.
OpenUrl CrossRef PubMed

[168] McEwen A,

[169] Condliffe L,

[170] Gilbert A

[171] 41.↵
Murray RL,
Coleman T,
Antoniak M,
et al.
(2008) The effect of proactively identifying smokers and offering smoking cessation support in primary care populations: a cluster-randomized trial. Addiction 103(6):998–1006.
OpenUrl CrossRef PubMed

[172] Murray RL,

[173] Coleman T,

[174] Antoniak M,

[175] et al.

[176] 42.↵
Campion J,
Shiers D,
Britton J,
et al.
(2014) Primary care guidance on smoking and mental disorders — 2014 update (Royal College of General Practitioners and Royal College of Psychiatrists).

[177] Campion J,

[178] Shiers D,

[179] Britton J,

[180] et al.

[181] 43.↵
Redelmeier DA,
Tan SH,
Booth GL
(1998) The treatment of unrelated disorders in patients with chronic medical diseases. N Engl J Med 338(21):1516–1520.
OpenUrl CrossRef PubMed

[182] Redelmeier DA,

[183] Tan SH,

[184] Booth GL

[185] 44.↵
Turner BJ,
Hollenbeak CS,
Weiner M,
et al.
(2008) Effect of unrelated comorbid conditions on hypertension management. Ann Intern Med 148(8):578–586.
OpenUrl CrossRef PubMed

[186] Turner BJ,

[187] Hollenbeak CS,

[188] Weiner M,

[189] et al.

[190] 45.↵
Chang CK,
Hayes RD,
Perera G,
et al.
(2011) Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London. PLoS One 6(5):e19590.
OpenUrl CrossRef PubMed

[191] Chang CK,

[192] Hayes RD,

[193] Perera G,

[194] et al.

[195] 46.↵
Phelan M,
Stradins L,
Morrison S
(2001) Physical health of people with severe mental illness. BMJ 322(7284):443–444.
OpenUrl FREE Full Text

[196] Phelan M,

[197] Stradins L,

[198] Morrison S

[199] 47.↵
Guthrie B,
Payne K,
Alderson P,
et al.
(2012) Adapting clinical guidelines to take account of multimorbidity. BMJ 345:e6341.
OpenUrl FREE Full Text

[200] Guthrie B,

[201] Payne K,

[202] Alderson P,

[203] et al.

[204] 48.↵
Starfield B
(2011) Challenges to primary care from co- and multi-morbidity. Prim Health Care Res Dev 12(1):1–2.
OpenUrl CrossRef PubMed

[205] Starfield B

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Smoking cessation interventions for patients with coronary heart disease and comorbidities: an observational cross-sectional study in primary care

Abstract

INTRODUCTION

How this fits in

METHOD

Study design and population

Study variables

Smoking cessation practice

Comorbidities

Deprivation status

Statistical analysis

RESULTS

Smoking status

Smoking cessation advice

Smoking cessation medication

DISCUSSION

Summary

Strengths and limitations

Comparison with existing literature

Implications for research and practice

Acknowledgments

Appendix 1. Read Codes for the three smoking-related outcome variablesa

Appendix 2. The three patterns of comorbid conditions, with their prevalencesa

Notes

Funding

Ethical approval

Provenance

Competing interests

Discuss this article

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Appendix 1. Read Codes for the three smoking-related outcome variables^a

Appendix 2. The three patterns of comorbid conditions, with their prevalences^a