ARC Epidemiology Unit, University of Manchester Medical School, Manchester, 1 EPIC-Norfolk, Institute of Public Health, University of Cambridge, Cambridge and 2 Norfolk Arthritis Register, Norfolk and Norwich University Hospital, Norwich, UK.
Correspondence to: D. P. M. Symmons, ARC Epidemiology Unit, Stopford Building, University of Manchester, Oxford Road, Manchester M13 9PT, UK. E-mail: Deborah.Symmons{at}man.ac.uk
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Abstract |
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Methods. In a population-based, prospective nested casecontrol study, 25 600 people aged 4575 yr participated in a health survey, including standard CVD risk factor assessment, between the years 1993 and 1997. There were 91 incident IP cases (one-third were seropositive at presentation) identified during follow-up to the end of July 2001. Baseline CVD risk factors in the IP cases were compared with those in two age/gender-matched controls.
Results. Current smokers had an odds ratio of 2.0 (95% CI 1.04.0) for IP. Other risk factors, including total and LDL cholesterol, systolic and diastolic blood pressure and obesity, did not differ significantly between cases and controls. Importantly, in combination, using a standard coronary disease risk score, these factors only had a modest association with future IP, and no association when analysis was restricted to the smaller number of cases who were seropositive.
Conclusion. Of the traditional cardiovascular risk factors, only smoking increases CVD risk prior to the onset of IP. Therefore the increased CVD observed in these patients is likely to be a consequence of factors operating after the onset of the arthritis.
KEY WORDS: Cardiovascular risk factors, Inflammatory polyarthritis, smoking, rheumatoid factor.
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Introduction |
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There are a number of possible explanations for the increased cardiovascular mortality following the onset of IP in general and RA in particular. One is that the inflammatory disease burden associated with IP may promote atherosclerosis in these patients. Markers of inflammation, such as elevated CRP, have been found to predict the future risk of coronary artery disease in the general population [810] and data from studies of patients with RA suggest that it is those with the most active inflammatory disease that carry the greatest increased risk of CVD mortality [1113] and all-cause mortality [14].
Another explanation for the increased cardiovascular disease risk is the possibility that IP and cardiovascular disease share the same risk factors. The strongest candidate is cigarette smoking. There are now many studies which have consistently shown an increased risk of the development of inflammatory joint disease in smokers [1518]. This is particularly true for the development of RF-positive arthritis [19], consistent with data showing that smoking is associated with the development of RF in the general population [20]. There may, however, be other shared risk factors. Obesity was found to be associated with an increased rate of recent-onset IP in a cross-sectional casecontrol study within NOAR [16], and Pima Indians, who are known to have the highest prevalence of RA in the world [21], also have very high rates of diabetes, obesity [22] and hypertension [23]. However, a prospective study is required to assess the temporal relationship between obesity and IP, as physical inactivity may be responsible for weight gain around the time of arthritis onset.
Dyslipidaemia is recognized as a complication of RA [24]. However, as the inflammatory disease process and treatments may modify the lipid profile [25, 26], it is not possible to assess whether the observed lipid abnormalities existed prior to the onset of arthritis. There are limited data on the relationship between blood lipid levels and the subsequent risk of IP. However, a prospective population-based study carried out in Finland did report that total serum cholesterol levels were associated with a moderate increase in the risk of developing seropositive RA in men and seronegative RA in women [27].
Data on other risk factors, such as high blood pressure (BP), are also difficult to obtain in retrospective enquiries. Thus, ideally, a large-scale population-based prospective study is needed to examine accurately the relationship between traditional coronary disease factors and the subsequent development of inflammatory polyarthritis.
We have been able to take advantage of the co-occurrence of two major prospective population-based studies within the same population in Norfolk, UK. The first is the Norfolk Arthritis Register [28], mentioned above. The second is the Norfolk arm of the European Prospective investigation into Cancer (EPIC). This is a population-based cohort study in which, at the baseline survey in 199397, a number of traditional cardiovascular risk factors were measured. The cohort was followed prospectively to examine the incidence of a number of major diseases, including coronary disease [29].
We examined the hypothesis that traditional coronary disease risk factors are also associated with an increased risk of development of IP, which may explain the substantial cardiac disease risk in patients with IP.
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Participants and methods |
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EPIC baseline survey
This has been described elsewhere [29]. Briefly, 25 633 men and women aged between 45 and 75 yr, identified from primary care agesex registers within Norfolk between 1993 and 1997, participated in a prospective study on health and lifestyle and chronic disease which included a health check examination during which cardiovascular disease risk factors were assessed. Smoking history was obtained by questionnaire. Dates of stopping and starting smoking were recorded as well as the number of cigarettes smoked daily. Participants were categorised as current, ex-smokers and non-smokers at the time of the questionnaire ever smoking being defined as at least one cigarette a day for at least 1 yr. The numbers of pack-years were also estimated for each decade of life. The history of diabetes was obtained by self-report. Height was measured to the nearest millimetre without shoes. Weight was measured without shoes in light clothing to the nearest 200 g using digital scales. Blood pressure was measured after the participant had sat for 3 min and two measurements were taken of both diastolic and systolic BP and the mean calculated. A non-fasting blood sample was obtained and the following lipids measured: total cholesterol, HDL cholesterol and triglyceride. Friedewald's formula was used to estimate LDL cholesterol [30].
Ascertainment of inflammatory polyarthritis
The subjects who participated in EPIC-Norfolk were also part of the target population for ascertainment of new-onset IP cases arising within Norfolk (NOAR). This study has also been described in detail elsewhere [28]. In brief, any adult presenting to their primary care physician with swelling of two or more joints lasting at least 4 weeks is notified to NOAR for standardized evaluation that includes a detailed history, structured joint examination and RF estimation. The American College of Rheumatology (ACR) 1987 classification criteria for RA [31] are applied at baseline and at yearly intervals subsequently.
Analysis
The EPIC and NOAR databases were merged using date of birth and other demographic details as the identifiers to link subjects who had previously participated in the EPIC baseline assessment and then subsequently entered NOAR as a case of IP. Each case identified was matched to two EPIC participants who had not developed IP. Matching was done on gender, date of birth (to within 3 yr of the case year of birth) and date of EPIC assessment (to within 3 months of the case assessment date). The coronary disease risk factors mentioned above were assessed as continuous variables, though cigarette smoking was analysed in three ways: (i) by ever, never or current status; (ii) by dividing current smokers into those with heavy smoking (> 20 pack-years) and those with less smoking; and (iii) by treating pack-years as a continuous variable. Body mass index (BMI) was calculated as weight in kilograms divided by height in metres squared and was analysed as both a continuous variable and as a categorical variable according to WHO definitions of overweight and obesity [32]. The cardiovascular risk factors were also pooled to derive a coronary disease risk prediction score [33] based on the Framingham equation, which calculates the percentage likelihood of a cardiovascular event over a 10-yr period. Using the cardiac risk assessor computer program [34], we derived the 10-yr coronary heart disease event risk as a percentage based on gender, age, systolic and diastolic BP, current smoking status, serum total cholesterol, HDL cholesterol and self-report of diabetes. Current guidelines suggest that people with a 10-yr coronary risk score in excess of 15% should be defined as high-risk patients and those with a score in excess of 30% should be urgently targeted for risk reduction interventions. The calculated percentage 10-yr coronary risk was initially treated as a continuous variable, and was then dichotomized by dividing the subjects into those with high coronary risk (10-yr risk > 15%) and those without (10 year risk 15%).
The matched triplets were maintained for analysis, and univariate conditional logistic regression was used to determine the association between the development of IP and individual risk factors. The risk factors in combination were examined by assessing the association between IP and the coronary risk prediction score. Subjects recruited to both NOAR and EPIC gave informed consent to participation in these respective studies. Both studies were approved by the local research ethics committee.
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Results |
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The distribution of coronary disease risk factors for the incident cases and their matched controls is shown in Table 1. The data for triglycerides and pack-years of smoking were not normally distributed and are displayed as medians and IQRs. The cases were well matched to the controls for gender and age, as expected. Self-reported diabetes was rare, but more common in the cases than the controls. A higher proportion (20.9%) of the cases were current smokers compared with the controls (11.6%), and not only were the cases more likely to smoke but they were also more likely to be heavy smokers. Thus, smoking more than 20 pack-years was reported by 62% of the ever-smoking cases compared with 40% of the ever-smoking controls. There was little difference observed in the distributions of serum lipid concentrations, systolic or diastolic BP or BMI between the two groups. BMI was analysed both as a continuous variable and using arbitrary cut-off points. Thus, using the WHO criteria for hypertension, there were 41 (45%) cases and 78 (43%) controls with systolic BP > 140 mmHg, and there were 22 (24%) cases and 78 (25%) controls with diastolic blood pressure > 90 mmHg. Similarly, using the WHO criteria for hypercholesterolaemia, there were 63 (75%) cases and 131 (78%) controls with cholesterol > 5.2 mmol/l.
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Finally, we did not observe a statistically significant association between obesity and the subsequent development of IP, although there was a trend towards increased obesity prior to IP onset in women but not in men. The previous, though cross-sectional, casecontrol study of NOAR patients found that obesity (BMI > 30) was associated with IP and RA [16]. One possible explanation for the lack of consistency between these study findings might be that obesity is a risk factor for IP only if it is present in the period just prior to the onset of joint symptoms. A number of patients in the current study had their BMI assessed several years prior to the onset of IP. Thus, it is possible that some of these patients may have increased their weight during this intervening period. In order to investigate this, the time between the EPIC assessment and the onset of IP symptoms was divided into tertiles. When the analysis was repeated, stratified by the duration between the health assessment and the onset of IP symptoms, we found that obesity was significantly associated with IP in those patients who developed their arthritis within 18 months of their EPIC health examination [OR 4.79 (95% CI 1.17, 19.6)] (Table 3). Obesity was not identified as a risk factor in those patients with longer intervals between BMI measurement and the onset of IP. The association was only demonstrated in women; the small number of males prevented further subanalysis.
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Discussion |
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The major conclusion with regard to the study hypothesis is that standard cardiovascular risk factors are not (with the exception of cigarette smoking) increased prior to the onset of IP; and that the overall risk profile of subjects destined to develop IP is modest. Therefore, the excess CVD mortality in these patients must be explained by other factors.
This study had a number of strengths. The coronary disease risk factors were ascertained prospectively and not subject to recall error or problems with retrospective assessment. The questions on smoking and diabetes were based on self-report and not subject to further individual validation in this study. The validity of such self-reports for these variables is considered acceptable in large epidemiological studies and any misclassification, given the prospective nature of the study, would have been random between the future cases and non-cases. Cases were ascertained from a population base and controls from the same population and so there are unlikely to be any selection factors that could have contributed to obtaining the results shown. Data on the occurrence of IP were obtained in real time using standardized techniques and do not rely, as is the case in other prospective studies, on subjects self-report.
However, there are a number of limitations. Despite the large size of the EPIC cohort, which recruited over 25 000 subjects, only 91 participants developed IP during follow-up, of whom only 28 were male. This reflects the overall low population incidence of the disease and hence the difficulty in undertaking sufficiently large studies to obtain sufficient incident cases for analysis. The confidence intervals around the key estimates, particularly the coronary disease risk, do not suggest that an important effect may have been missed. More minor influences would not have been detectable, however, and this is particularly true for some of the less frequent risk factors, such as diabetes. For this variable the confidence intervals were so wide as to preclude useful comment.
Secondly, the cases for this study were defined as having IP and not RA. We have argued elsewhere that classifying individuals as having RA is not appropriate in the early stages of IP [35] and that the ACR criteria for RA, for example, are unstable in this situation [36]. We have reported, however, that on follow-up the numbers of subjects satisfying criteria for RA increase substantially [37]. Interestingly we have also previously demonstrated that, within NOAR, the presence of RF was the major predictive factor for future cardiovascular mortality. Indeed, satisfying criteria for RA was not predictive [7]. It was therefore interesting to note that an analysis restricted to the group that were RF-positive at baseline showed no difference in results, despite the smaller numbers. Thus, the observation within the NOAR cohort of increased CVD mortality in seropositive subjects cannot be explained by their premorbid cardiovascular risk.
Although smoking is a key risk factor for the development of IP, particularly in men, other factors have to be sought to explain the increased cardiovascular disease mortality in subjects with RA. Indeed, studies have failed to identify smoking as a predictor of CVD mortality in RA [4] and IP [7]. Traditional cardiovascular risk factors, although highly prevalent in clinic-based populations of established RA patients [38, 39], do not seem to explain the increased CVD event rates observed in RA compared with the general population [40]. It seems that there are other key factors that are responsible for promoting CVD in these patients.
Several novel CVD risk factors identified in the general population are of particular interest in RA. It has emerged in recent years that inflammation is an important marker of increased CVD risk in the general population. CRP levels have been found to be associated with the risk of developing coronary heart disease events in the general population [8, 10] and were also found to be associated with coronary death or myocardial infarction in patients with known CVD [41]. In RA populations, the amount of inflammation, as measured longitudinally by disease activity assessments, has been shown to predict all-cause mortality [14], and increased inflamed joint counts [11] and elevated erythrocyte sedimentation rates [42] have both been associated with increased cardiovascular mortality. There are many other markers of inflammation common to atherosclerosis and RA; these include elevated levels of soluble adhesion molecules, macrophage activation leading to elevated TNF-, IL-6 and metalloproteinase expression, and T-cell and B-cell activation [43]. Therefore, it seems likely that, if coronary heart disease is an inflammatory disease, inflammatory comorbid conditions such as RA may potentiate atherosclerosis.
Other factors that may be important following the onset of IP include treatments. For example, drugs such as methotrexate and sulphasalazine may increase the homocysteine level [44], which has been recognized to be a novel risk factor for CVD [45]. Chronic NSAID use may potentiate hypertension. Use of ibuprofen seems to reduce the CVD-protective, antiplatelet effects of aspirin [46] and there are ongoing concerns about the CVD safety of the selective cyclooxygenase 2 inhibitors [47]. Corticosteroids have many potential adverse CVD side-effects [48], although their prolonged use was not found to be associated with increased CVD mortality in a study by Wållberg-Jonsson et al. [42].
Many of the data on coronary disease risk in subjects with RA relate to mortality, and it would be important to separate out those factors in the disease that predict coronary disease onset from those that predict mortality once arterial disease is present. However, we suggest that the increased CVD mortality observed in RA is more likely to be caused by factors that develop either with the inflammatory disease process or its treatment than by increased traditional CVD risk factors prior to disease onset.
This study, therefore, is concerned with factors associated with the onset of IP and is not about risk factors for cardiovascular disease per se. The fact that traditional CVD risk factors are not increased prior to the onset of IP does not mean that IP patients with elevated coronary heart disease risk scores are not candidates for primary interventions to reduce CVD risk. In fact, one could argue that RA may be an independent risk factor for coronary heart disease (similar to diabetes) and future work is required to investigate whether the presence or absence of RA should be factored in to future CVD risk assessment calculations.
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Acknowledgments |
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References |
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