Clin Rheumatol (2014) 33:111–117 DOI 10.1007/s10067-013-2410-4

ORIGINAL ARTICLE

Modifiable cardiovascular risk factors in patients with ankylosing spondylitis Björn Sundström & Gunnar Johansson & Ingegerd Johansson & Solveig Wållberg-Jonsson

Received: 7 March 2013 / Revised: 10 May 2013 / Accepted: 27 June 2013 / Published online: 19 October 2013 # Clinical Rheumatology 2013

Abstract The aim of this study was to evaluate whether modifiable cardiovascular disease (CVD) risk factors, e.g. atherogenic blood lipids, hypertension and lifestyle-related factors such as smoking, diet and physical inactivity, differ among patients with ankylosing spondylitis (AS) in comparison to the general population. Eighty-eight patients diagnosed with AS were identified by analysis of the databases of a previous community intervention programme, the Västerbotten intervention programme. The patients were compared with 351 controls matched for age, sex and study period. These databases include the results of blood samples analysed for cholesterol, triglycerides and plasma glucose, as well as data on hypertension, height, weight, smoking and dietary habits and physical activity. No significant differences were found between patients and controls regarding hypertension, body mass index, physical activity, diet or smoking. Levels of serum triglycerides (p <0.01) and cholesterol (p <0.01) were significantly lower in the patient group. Among the patients, the level of triglycerides correlated inversely with the intake of

Electronic supplementary material The online version of this article (doi:10.1007/s10067-013-2410-4) contains supplementary material, which is available to authorized users. B. Sundström : S. Wållberg-Jonsson Department of Public Health and Clinical Medicine, Rheumatology, Umeå University, Umeå, Sweden G. Johansson School of Social and Health Sciences, Halmstad University, Halmstad, Sweden I. Johansson Department of Odontology, Cariology, Umeå University, Umeå, Sweden B. Sundström (*) Department of Public Health and Clinical Medicine, Rheumatology, University Hospital, 90185 Umeå, Sweden e-mail: [email protected]

total fat (r s =−0.25, p <0.05), monounsaturated fats (r s = −0.29, p <0.05) and positively correlated to the intake of carbohydrates (r s =0.26, p <0.05). These associations were not apparent among the controls. In the cohort of AS patients studied, no differences were found regarding the modifiable risk factors for CVD compared with the general population. Hence, the increased presence of CVD in patients with AS may be caused by other factors such as differences in metabolism and medication such as NSAID or the chronic low-grade inflammation present in the disease. Keywords Ankylosing spondylitis . Cardiovascular disease . Hypertension

Introduction An increased incidence of cardiovascular diseases (CVD) is now a well-established condition in patients with ankylosing spondylitis (AS). The involvement of heart valve and conduction disorders in AS were the first aspects of CVD to be described [1]. The inflammation and fibrosis observed in the mitral valve and aortic root among AS patients may, if extended to the interventricular septum, the atrioventricular node and the bundle branches, play an important role in conduction disturbances [2, 3]. Conduction and rhythmic abnormalities are amongst the most commonly observed cardiac manifestations within patients with AS and may have a role in the increased mortality due to CVD observed in AS patients during the recent years [4]. In addition to these co-morbidities, it is now well documented that there is an increased morbidity and mortality due to ischaemic heart disease and myocardial infarction (MI) among patients with AS [5–7]. In the general population, modifiable risk factors such as blood pressure, atherogenic blood lipids, hyperglycaemia, weight, smoking, diet and exercise have been demonstrated to have a significant impact for CVD [8, 9]. In patients with

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rheumatic disease, CVD has been suggested to be linked to the presence of inflammation, which is considered to be a risk factor in its own right, in addition to the classic risk factors. Currently, there are some data suggesting that the low-grade inflammation associated with AS has an influence on this increased incidence of CVD [10]; however, it is not yet elucidated how, or if, AS patients differ from the general population in regard to the classic modifiable risk factors. The aim of this study was to evaluate whether traditional, modifiable risk factors for CVD, such as hypertension, hyperglycaemia and atherogenic blood lipids or lifestylerelated risk factors such as smoking, diet, physical activity and body mass index (BMI) differ among AS patients compared with those of the general population.

Materials and method Study area and settings In Sweden, free medical care is provided for all citizens based on tax-based funding systems. This medical care is administered by 20 geographical divided counties, each of which has the authority to organise the care in the best way, with reference to local conditions and to national regulations. The county of Västerbotten (total population in 2011 was 259,876 citizens) is a mainly rural area in far northern Sweden with three main population centres, namely Umeå, Skellefteå and Lycksele. The county had one of the highest incidences of MI and CVD in the late 1970s and early 1980s. Due to this, a healthscreening and intervention project was started in Norsjö, during 1985 [11, 12]. The project was aimed at the screening of risk factors for CVD with subsequent appropriate clinical intervention. The project was gradually extended, as the Västerbotten Intervention Programme (VIP), to include all citizens aged 40, 50 and 60 years (before 1996, 30 years old also participated) in the whole county in 1991 [11]. The participation rate of the VIP has varied; it was 48–57 % during 1991 to 1995 and thereafter increased to approximately 70 % of the county population since 2005 [13]. The differences in social characteristics between participants and non-participants have been described as being marginal [13]. As part of the VIP, health-screening data and blood samples have been collected and archived in the Northern Sweden Medical Biobank for future research. Identification of patients In the county of Västerbotten, all patients with a verified diagnosis of AS according to modified New York criteria [14] have the opportunity to receive treatment and regular assessment at the Department of Rheumatology at Norrland's University Hospital. Patients with milder disease who do not

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need regular monitoring by a rheumatologist are offered annual monitoring at the physiotherapy section of the department. By means of careful investigation of medical records at the Department of Rheumatology, including the physiotherapy section, covering the period between May 2002 to May 2007, 166 patients aged between 18 and 70 years, with a validated diagnosis of definite AS were identified. Written consent was requested from these patients to investigate whether they had data recorded from VIP in the Northern Sweden Medical Biobank. Of the 166 subjects, 148 gave their consent for participation in the present investigation. Of these 148 patients, 89 (60 %) were found to be included in the VIP database. Only one patient was found in the age group of 30 years old and was omitted to simplify and enable stratification for further analyses. For each of the remaining 88 patients with AS, four control subjects (n =351) matched for age (±2.5 years), gender and date incorporated into the VIP (±2 months) were identified within the same database and used for comparison. Study variables As part of the VIP, participants donated blood samples and were measured for blood pressure (in supine position), height (metre) and weight (kilogram). Blood samples, which were drawn after >4 h of fasting, were analysed for serum cholesterol (millimoles per litre), serum triglycerides (millimoles per litre) and plasma glucose (fasting and 2 h after a glucose challenge). All analyses were performed using routine pathology protocols. Additionally all participants completed questionnaires concerning any diagnosis of diabetes mellitus, previous myocardial infarction, education, medication(s), smoking habits, diet, use of nutritional supplements and physical activity. Medication was assessed by questions directed at the participant's consumption of anti-hypertensive drugs, cardioprotective drugs, sedatives or sleeping drugs, ulceroprotective drugs and/or lipidlowering drugs during the preceding 14-day period. Physical activity at work was assessed on a 5-point scale graded from sedentary/standing work to physically hard work. Physical activity during leisure time was assessed as the number of training sessions per week in the preceding 3 months on a scale graded from never to more than 3 times per week. The background of the questionnaires has been described previously [12]. Dietary habits were assessed using a semi-quantitative food frequency questionnaire (FFQ). The FFQ has differed slightly over the years. The first version, containing 84 questions, has been validated [15], but since 1996, shorter versions containing 64–66 questions have been used. Comparisons in subjects answering both variants have shown that ranking is similar, but absolute levels tend to be slightly lower when using the shorter FFQ [16]. The intake frequency for food types was reported on a nine-level scale ranging from never to four times

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or more per day. The questionnaire contained examples of portion sizes on four different plates regarding vegetables, meat or fish and staple foods such as rice, pasta or potatoes. The frequencies and portion sizes from the FFQ were used to calculate daily energy and nutritional intake. Standard values in the reference databases were used for those foods where the examples depicted on plates were not valid for estimating portion size. The calculations were based on reference databases from the Swedish National Food Administration [17]. Consumption of nutritional supplements was assessed by direct questions as to whether participants had consumed multivitamins, multi-minerals, iron, selenium or other supplements during the previous year, or the previous 14-day period, respectively.

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correlation test was used to evaluate internal associations in the patient and control groups. In multiple linear regression modelling of energy intake, co-variates were selected based on univariate analyses and scientific rationale. In the protocols for analysing triglycerides, the use of equipment not recording values below 0.80 mmol/L is not uncommon throughout the county causing non-normally distributed data, and consequently, non-parametric analysis was performed on these data. Statistical calculations were performed with SPSS 20 for Macintosh. The study was approved by the regional ethical committee at the medical faculty at Umeå University (Dnr 07-082M, Dnr 2010-89-32) and was performed in concert with the Helsinki declaration.

Classification and handling of data Results The subjects were classified as smokers when reporting a consumption of an average of one or more cigarettes per day. Hypertension was defined by either a systolic pressure over 140 mm/Hg, diastolic pressure greater than 90 mm/Hg or medication with anti-hypertensive pharmaceuticals. Increased serum cholesterol was defined as a level over 6.5 mmol/L and increased serum triglycerides as over 1.7 mmol/L. Hyperglycaemia was defined by either: (1) a fasting blood glucose level of over 7.0 mm/L, (2) 2-h glucose loading test over 11 mmol/L, (3) medication or (4) a reported diagnosis of diabetes mellitus. Physical activity at work and during leisure time constituted the basis for a table of the calculated value of physical activity level (PAL; 18). Since this calculation required a 4-point scale on physical activity at work, the second and third response options (of five) in the VIP data were merged into one. When evaluating food intake, five patients who had responded in 1996 or earlier, and their corresponding controls, were excluded because they used a slightly different FFQ. For the remainder of the participants, frequencies and portion sizes from the FFQ were used to calculate the energy intake (EI) and the nutrient content. A food intake level (FIL) was calculated for all cases and controls as EI divided by the estimated amount of daily energy expended at total rest, i.e. the basal metabolic rate (BMR 19); FIL=EI/BMR [20]. Subjects with an FIL below the 5th percentile or above the 97.5 percentile were classified as under- and over-reporters, respectively, and were removed from further calculations on diet. The cut-off at the fifth percentile was used since under-reporting is more common than overreporting in dietary surveys [21]. For the remaining subjects, the dietary intake was expressed as energy adjusted macronutrients, according to the energy density method [22]. Statistics For comparisons between patients and controls, conditional logistic regression analysis was performed. Spearman's rank

Demographic and clinical data of the AS patients (n =88) and their controls are presented in Table 1. Thirty-three patients were aged 40, 31 aged 50 and 24 were aged 60. No significant differences between patients and controls were found for hypertension and hyperglycaemia, neither when considering the group as whole nor when analysing subgroups divided by age. There were significantly lower levels of serum triglycerides and cholesterol among AS patients (p <0.01 and p <0.01, respectively; Table 1) as well as significantly fewer AS patients that had increased serum triglycerides (≥1.7 mmol/L) or cholesterol (≥6.5 mmol/L; p <0.01 for both). Among the patients, levels of triglycerides were inversely correlated to the intake of total fat (r s =−0.25, p <0.05; Table 2), monounsaturated fats (r s =−0.29, p <0.05) and positively associated with the intake of carbohydrates (r s = 0.26, p < 0.05). Similar associations were not found among the control subjects. Regarding the levels of cholesterol, a positive correlation to energy intake of carbohydrates (r s =0.26, p <0.05) was noted among the patients but not among the controls. Concerning self-reported use of pharmaceuticals, there was significantly higher use of ulceroprotective drugs among the patients compared with the controls (p <0.01; Table 1), and there was a trend towards more frequent use of antihypertensive medications among the patients compared with controls (p =0.09). The calculated energy intake was significantly higher among patients than controls (1,940 vs. 1,819 kcal, p < 0.05; Supplementary Table 1) Apart from trends towards a lower intake of monounsaturated fats (p = 0.07) as well as total fat (p = 0.07) among the patients, there were no differences regarding diet compared with controls. The difference in the calculated energy intake remained after adjustments for PAL, weight, sex and age (Table 3).

114 Table 1 Demographic and clinical data for 88 patients with ankylosing spondylitis and matched 351 controls

PAL physical activity level IQR interquertile range a

Hypertension defined either as: systolic pressure >140 mm/Hg, diastolic pressure >90 mm/Hg or medication with anti-hypertensive medication

b

Hyperglycaemis defined either as: fasting blood glucose over 7.0 mmol/L, 2 h post-glucose loading test over 11 mmol/L, medication or a report of diabetes

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Patients (n =88)

Controls (n =351)

p value

Gender, m/f Age, years, median (range) No regular exercise during leisure time, n PAL, median (IQR) Higher education, n

68/20 50 (40–60) 51 (59.3 %) 1.6 (1.5–1.8) 27 (31 %)

272/79 50 (40–61) 207 (60.3 %) 1.6 (1.5–1.8) 100 (27.9 %)

– – p =0.902 p =0.32 p =0.60

Height (cm), mean (SD) Weight (kg), mean (SD) Body mass index (kg m−2), mean (SD) Smoker, n Triglycerides (mmol/L), median (IQR) Cholesterol (mmol/L), mean (SD) Increased serum cholesterol (≥6.5 mmol/L), n Increased serum triglycerides (≥1,7 mmol/L), n Systolic blood pressure (mm), mean (SD) Diastolic blood pressure (mm), mean (SD) Hypertensiona, n Hyperglycaemiab, n Anti-hypertensive drugs, n Cardioprotective drugs, n Sedatives or sleeping drugs, n Ulceroprotective drugs, n Lipid-lowering drugs, n

174.0 80.7 (15.2) 26.5 (3.81) 14 (16.7 %) 1.08 (0.80–1.44) 5.12 (1.05) 7 (8.0 %) 12 (14.1 %) 126 (16.1) 79 (10.2) 26 (31.7 %) 6 (6.8 %) 18 (21.7 %) 1 (1.2 %) 3 (3.6 %) 14 (16.9 %) 4 (4.8 %)

176.0 82.3 (15.5) 26.5 (4.73) 44 (13.3 %) 1.21 (0.84–1.79) 5.50 (1.21) 66 (18.9 %) 88 (26.1 %) 127 (16.9) 79 (10.5) 94 (29.2 %) 26 (7.4 %) 44 (13.6 %) 13 (4.0 %) 15 (4.6 %) 19 (5.9 %) 14 (4.4 %)

p <0.01 p =0.38 p =0.93 p =0.48 p <0.01 p <0.01 p <0.05 p <0.05 p =0.88 p =0.58 p =0.68 p =1.0 p =0.09 p =0.32 p =1.00 p <0.01 p =0.77

Discussion In this well-defined cohort of Swedish patients with AS, no differences were found compared to controls, either in terms

of biological modifiable risk factors such as hypertension and hyperglycaemia or lifestyle-related risk factors, i.e. physical activity, diet or smoking, that may help to explain an increased prevalence of CVD in patients with AS.

Table 2 Associations between background data, dietary intake and atherogenic lipids among 77 patients with ankylosing spondylitis and 307 matched controls

BMI PAL Leisure exercise (n/week) Fat Protein Carbohydrate Saturated fatty acids Monounsaturated fatty acids Polyunsaturated fatty acids

Patients (n =77)

Controls (n =307)

Correlations to atherogenic lipids

Correlations to atherogenic lipids

Triglycerides (mmol/L)

Cholesterol (mmol/L)

Triglycerides (mmol/L)

Cholesterol (mmol/L)

0.30** 0.12 0.10 −0.25* −0.14 0.26* -0.21 −0.29* −0.14

-0.19 0.01 0.02 −0.20 −0.21 0.26* -0.10 −0.28* −0.15

0.38** −0.09 −0.08 0.01 0.01 −0.02 0.03 0.03 −0.06

0.08 −0.09 −0.08 −0.10 −0.07 0.10 −0.07 −0.14* −0.10

Spearman rank test used for correlation on all variables PAL physical activity level, BMI body mass index *p <0.05 **p <0.01

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Table 3 Multiple linear regression analysis of determinants of energy intake among 77 patients with ankylosing spondylitis and 307 controls Variable

β (95 % CI)

p value

Diagnosis of AS (+/−) Weight (kg) PAL Age (years)

140 (19–260) 291 (4–579) 3,3 (−0.1–6.7) −0.9 (−7.0–5.1)

<0.05 <0.05 0.06 0.76

432 (311–-552)

<0.001

Sex

AS ankylosing spondylitis, PAL physical activity level

The normal prevalence of hypertension found in our study is contradictory to some published epidemiological studies on AS populations [23, 24] but is consistent with a meta-analysis reported in 2011 [25]. This discrepancy may be influenced by the selection bias often present in epidemiological surveys. In this study, we used data and controls from a community-based health-screening programme aimed at the general population, of whom approximately 70 % chose to participate [13]. This may yield different results compared with studies using hospital and/or health care visits as primary sources of data. Furthermore, many patients with mild AS can manage their disease without regular contact with health care facilities or by only sporadic contact with GPs. Consequently, there is often a selection bias favouring more severely ill patients or patients with more complex and multi-disability problems in those studies of AS patients recruited from hospitals or specialist centres. The regional model for care of AS patients, by offering annual assessment through the physiotherapy department, allows monitoring and inclusion of patients with milder disease. Although this study lacks measurements of disease activity, previous studies on the same cohort of patients with AS suggested a rather low disease activity overall (a median Bath Ankylosing Spondylitis Disease Activity Index, BASDAI, score of 4.1 and 3.8, an erythrocyte sedimentation rate (ESR) of 14.9 mm/h and a high sensitive c-reactive protein (hsCRP) of 4.2 mg/L) [26, 27]. Due to the wide variety of patients, covering the wide spectrum of AS symptoms, the present study may give a different picture than that of the typical AS patient compared with studies in which the selection of patients is biased towards more complex diseases and higher disease activity. Despite these indications of low disease activity and the lack of differences in hyperglycaemia and hypertension, the levels of triglycerides and cholesterol were significantly lower in patients with AS compared with the general population. These lower levels of atherogenic lipids in AS patients is in line with those described by other research groups [28, 29] and concluded in a meta-analysis review [25]. However, as in the case of hypertension, there are publications based on epidemiological data that report conflicting results [23, 24] The metabolic alterations among AS patients have been discussed by other authors and have been suggested to be induced by a low-grade

inflammatory response [10, 30]. This study indicates that diet has a stronger association with lipid levels and, therefore with metabolism, in comparison to the general population. Our findings, that a higher intake of carbohydrates yields higher triglyceride levels whilst a greater consumption of monounsaturated fats is associated with lower fasting levels of both triglycerides and cholesterol, have previously been described in larger studies of the general population [31]. However, since the calculated correlations did not reach statistical significance in the control cohort, despite being four times larger in number than the patients, suggests that there may be a more direct influence of diet on blood lipids in patients with AS. The higher energy intake among patients compared with controls may implicate a greater resting energy expenditure and BMR among patients with AS, similar to that described in other inflammatory conditions [32, 33]. Increased energy intake can also be due to other factors, such as greater physical activity and weight. However, the significant association between energy intake and AS disease per se remained when undertaking multiple regression analysis adjusted for weight and PAL. This result, together with our findings of more pronounced correlations between diet and atherogenic lipids in the patient cohort, raises questions as to whether there are alterations in metabolism among AS patients. No differences were found between patients and controls in terms of smoking and dietary habits nor was there any difference on the reported exercise and physical activity habits. This is surprising given that physical activity is emphasised as a cornerstone in the treatment of AS [34]. The fact that almost 60 % of the patients studied do not exercise on a weekly regular basis stresses the need for research as to why the patients do not exercise more frequently. A major strength of this study was the well-defined cohort of patients together with extensive data for randomly selected matched controls drawn from the general population. This differs with those studies in which the populations compared were drawn from individuals attending health care or hospital visits. Such populations may comprise patients with higher disease activity and, therefore, may bias the results towards patients suffering more pain, experiencing poorer sleep patterns and more drug-induced side-effects, such as those caused by corticosteroids. This may introduce a risk of cardiovascular disease by affecting the level of physical activity, blood pressure, weight and hyperglycaemia. Although we did not find any differences that may explain the higher prevalence of CVD in AS, we did find other interesting differences, mainly regarding blood lipids and metabolism. However, some caution should be taken into these findings since cases and controls are compared on multiple parameters, thereby increasing a risk of type I errors. The main limitation of the present study is that limited data were available from the VIP cohort. Certainly more data on blood lipids, such as high-density lipoproteins or apolipoproteins and markers of disease activity, such as hsCRP and ESR would be of great interest, as well as data on consumption of NSAIDs.

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In conclusion, no difference could be found in this cohort of AS patients compared with individuals drawn from the general population regarding modifiable risk factors that may offer some explanation for the increased prevalence of CVD. Hence, the increased presence of CVD in AS patients may be influenced by other factors, such as inflammation and fibrosis in the heart and vascular vessels, differences in metabolism and/or medication, such as use of NSAID. Acknowledgments We gratefully acknowledge Sonja Odeblom for skilful administrative help. Åsa Ågren and Anna-Sara Molin at Northern Sweden Medical Research Bank are thanked for help in gaining access to the data. This work was supported by grants from the northern county councils Visare Norr, the Borgerskapet fund in Umeå, the Department of Research Norrbotten county council and the Swedish Rheumatism Association. Disclosures None.

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