To investigate the associations between cardiorespiratory fitness (CRF) and the level of cardiovascular (CV) risk factors in patients with ankylosing spondylitis (AS) and controls.
To investigate the associations between cardiorespiratory fitness (CRF) and the level of cardiovascular (CV) risk factors in patients with ankylosing spondylitis (AS) and controls.
In a cross-sectional comparative study, CRF was measured with a maximal treadmill test for estimation of peak oxygen uptake. Metabolic syndrome (MS), body composition, traditional CV risk factors, and inflammatory markers were assessed. Multivariable linear regression models were used to study the associations between CRF and CV risk factors. All models were adjusted for age, sex, and smoking, and for inflammation when C-reactive protein (CRP) level or erythrocyte sedimentation rate (ESR) were not already included as dependent variables.
A total of 126 patients (mean ± SD age 47.9 ± 10.8 years) and 111 controls (mean ± SD age 52.1 ± 11.1 years) were included. There were significant inverse associations between CRF and body mass index, waist circumference, triglycerides, CRP level, and ESR (P < 0.001–0.03) for patients and controls. Also, significant associations were found between CRF and high-density lipoprotein (HDL) cholesterol (β = 0.03, P < 0.001) and blood pressure (BP; β = −0.9 for systolic and β = −0.6 for diastolic; P < 0.01) in controls, but these associations were not found in patients (β = 0, P = 0.69 for HDL cholesterol; β = −0.04, P = 0.87 for systolic pressure; and β = −0.14, P = 0.34 for diastolic pressure) (additional adjustments for medication). Higher CRF was associated with a lower risk for MS in both patients (odds ratio [OR] 0.91, P = 0.03) and controls (OR 0.89, P = 0.01).
CRF was associated with favorable levels of CV risk factors and lower risk of MS in both AS patients and controls. However, established findings of an association between CRF and BP and HDL cholesterol in healthy adults were not confirmed in AS patients.
Ankylosing spondylitis (AS) is an inflammatory rheumatic disease with an overall prevalence between 0.1% and 1.4% . The disease might lead to structural and functional impairment and a decrease in quality of life. Currently, there is an increasing focus on the high risk of cardiovascular (CV) diseases in patients with AS [2-4]. It has been reported that the mortality rate in patients with AS is higher than expected, with standardized mortality ratios between 1.5 and 1.9, and the excess mortality is predominantly due to CV diseases . The reason for the increased CV disease risk is assumed to be related to the inflammatory process of the disease and an increased prevalence of traditional risk factors [2, 6].
For the general population, it is well established that cardiorespiratory fitness (CRF) has a protective effect against CV disease prevalence and mortality [7, 8]. It is generally believed that this effect is mediated through the association between CRF and traditional risk factors for CV diseases such as waist circumference, blood pressure (BP), triglycerides, high-density lipoprotein (HDL) cholesterol, and insulin sensitivity [9, 10]. Furthermore, high CRF is reported to be associated with low systemic inflammation in adults without inflammatory diseases [11-14]. These associations are not established in patients with AS. Because of the inflammatory burden of the disease, and the fact that inflammation itself accentuates established CV risk factors , this relationship might be different in patients with AS. Therefore, the aim of this study was to investigate the associations between CRF and levels of CV risk factors in AS patients and in a group of population controls.
This was a cross-sectional comparative study, carried out at Diakonhjemmet Hospital in Oslo, Norway, between 2008 and 2010. All participants gave written informed consent to participate, and the procedures followed the World Medical Association Declaration of Helsinki. The project was approved by the Regional Medical Ethics Committee and the Norwegian Social Sciences Data Services.
Patients were recruited from a database of AS patients fulfilling the New York classification criteria . All patients with a residence located ≤50 kilometers from the hospital and who were ages ≤70 years were invited to participate through posted mail. Altogether, 250 patients were invited and 163 gave their informed consent to participate. Of these, 14 did not attend the clinical examination. Thus, 149 of 250 (60%) of the invited patients completed the study.
Population controls were randomly drawn by Statistics Norway from the national register of inhabitants to match AS patients for age, sex, and residential area on a group level. The only exclusion criterion was a history of inflammatory arthritis. The population controls were also invited to participate through posted mail. A total of 329 population controls were invited and 140 gave their informed consent to participate. One was excluded due to language difficulties and 6 did not attend the clinical examination. Thus, 133 of 329 (40%) of the invited controls completed the study.
Participating patients and controls were older (P = 0.04 and P = 0.003, respectively) and more likely to live in a western part of the city with a higher socioeconomic status (P = 0.01 and P = 0.06, respectively) than the nonparticipating subjects. There were no statistically significant differences in sex between the participating and nonparticipating subjects.
In the present study, patients and population controls with established CV diseases were excluded from the analyses. All participants underwent a consultation with a cardiologist. Information about CV diseases, defined as ever having experienced a myocardial infarction, angina, or stroke, was self-reported, but the diagnosis was confirmed by the cardiologist. In addition, subjects who did not perform the CRF test were excluded.
Among the participating AS patients, 18 subjects were excluded due to established CV disease, and 5 were excluded because they did not perform the CRF test. Hence, 126 patients were included in the analyses. Among the participating population controls, 11 subjects were excluded due to established CV diseases, and 11 were excluded because they did not perform the CRF test. Hence, 111 population controls were included in the analyses. The reasons for not performing the CRF were similar in both groups, i.e., not showing up at the test, not able to perform the test due to severely reduced physical function, or contraindications against maximal exercise testing.
In addition, because not all subjects completed the fasting requirement and because of technical problems during testing, the number of participants ranged from 123 to 126 among AS patients and from 106 to 111 among population controls in the different variables.
Brachial BP was measured after a 5-minute rest in a supine position using the OMRON M7 (Omron Healthcare). The BP measurements were repeated until 2 subsequent results differed by ≤5 mm Hg in both systolic and diastolic pressure with heart rate differing by less than 5 beats per minute. The average of the 2 last measurements was calculated and used in the analyses. Blood samples were drawn after at least 4 hours of fasting  and analyzed immediately for concentration of CV risk factors, except the glucose samples, which were analyzed from serum frozen at −80°C. Triglycerides, HDL cholesterol, glucose, and C-reactive protein (CRP) level were analyzed by COBAS 6000 (Roche Diagnostics) and erythrocyte sedimentation rate (ESR) by the Westergren method. Low-density lipoprotein (LDL) cholesterol was calculated based on the Friedewald equation .
Weight and height were measured, and body mass index (BMI) was calculated as body weight/height (kg/m2). Waist circumference (cm) was measured in a standing position with a measuring tape at the height of umbilicus.
The International Diabetes Federation definition for metabolic syndrome (MS) was used . This definition includes increased waist circumference (Europeans: men ≥94 cm and women ≥80 cm) plus any 2 of the following: 1) raised triglycerides (>1.7 mmoles/liter) or specific treatment for this lipid abnormality, 2) reduced HDL cholesterol (<1.03 mmoles/liter in men and <1.29 mmoles/liter in women or specific treatment for this lipid abnormality), 3) raised BP (systolic ≥130 mm Hg, diastolic ≥85 mm Hg) or treatment of previously diagnosed hypertension, and 4) raised fasting plasma glucose (≥5.6 mmoles/liter) or previously diagnosed diabetes mellitus.
Initially, all participants underwent a clinical interview, an electrocardiogram, and echocardiography to detect any possible contraindications to physical fitness testing. CRF was tested with a maximal walking test on a treadmill, according to the modified Balke protocol [19, 20]. Estimating peak oxygen uptake (VO 2 peak) from a maximal test is considered the second most valid test for CRF after measurement of VO2 by ergospirometry during a maximal test . The participants were encouraged to avoid handrail grasp when this was not necessary. They started by warming up with walking on the treadmill for 5 minutes with an individually adapted speed and 2.5% inclination. Most participants started at a speed of approximately 4.8 km/hour. For some the speed was higher (5.0–7.4 km/hour) in order to avoid a prolonged test time, and for others the speed was lower (2.6–4.3 km/hour). The speed was kept constant in the beginning of the test, while the inclination increased 1.5% every minute. If 15% inclination was reached, the speed was increased by 0.3 km/hour every minute. At the end of each workload, the participants were asked to rate their perceived exertion (RPE) on the Borgs Scale (range 6–20, where 6 = very, very light and 20 = maximal exertion) , and their heart rate was recorded (Polar Sport Tester). The test was stopped when the participants could not further increase either the inclination or the speed and reported an RPE between 17–20 on the Borgs scale.
There were no differences between the groups at the end of the treadmill test with regard to heart rate (mean ± SD heart rate 174 ± 16 for patients and 174 ± 16 for controls; P = 0.42) or RPE (mean ± SD RPE 19 ± 1.2 for patients and 19 ± 1.4 for controls; P = 0.57). The estimated VO 2 peak was calculated based on the American College of Sports Medicine formula for graded walking or running :
Speeds ≤8.0 km/hour: VO2 = (0.1 × ms−1 + 1.8 × ms−1 × inclination [%] + 3.5) Speeds >8.0 km/hour: VO2 = (0.2 × ms−1 + 0.9 × ms−1 × inclination [%] + 3.5)
where ms = treadmill speed and VO2peak is given in ml × kg−1 × minute−1.
Demographic information (e.g., age, education, employment, disability pension, marital status, smoking habits, and medications) was obtained from a questionnaire. In addition, the use of medications was validated through an interview.
The Ankylosing Spondylitis Disease Activity Score (ASDAS) was used to assess disease activity . The ASDAS is a well-validated and highly discriminatory instrument for assessing disease activity in AS. It is a continuous measure based on patient-reported outcomes (back pain, duration of morning stiffness, patient global assessment, and peripheral joint complaints) and CRP level. Increasing values indicate higher disease activity.
The Bath Ankylosing Spondylitis Functional Index (BASFI) was used to assess physical function . The BASFI consists of 8 items regarding physical functioning and 2 questions reflecting the patient's ability to cope with everyday life. Each item is reported on a 10-point numeric rating scale (0–10, where 10 is the worst), the mean of which gives the BASFI score. In addition, the Bath Ankylosing Spondylitis Metrology Index (BASMI) was used to assess flexibility of the body . The BASMI gives a score from 0 to 10 (10 being the worst) .
Variables are presented as mean ± SD or median with range for skewed distributions. The frequency (%) is given for counts.
Since CRP level and ESR were skewed, these variables were log-transformed for analytic purposes. Differences between AS patients and population controls in personal characteristics and CV risk factors were examined by chi-square test for categorical variables, and univariate analyses of covariance were performed to explore group differences for continuous variables with adjustments for covariates.
The focus for the analyses was to elucidate associations as they appear in 2 different groups. Thus, stratified group analyses were done. Multivariate linear regression models were used to study the association between CRF (independent variable) and each of the individual CV risk factors (dependent variables) for AS patients and population controls separately. All models were adjusted for sex, age, and smoking status (current smoker/nonsmoker). All models were also adjusted for CRP level (<5 mg/liter and ≥5 mg/liter) except when CRP level or ESR were already included as dependent variables.
Additional adjustments were performed for use of statins (currently using statins/not using statins) when analyzing HDL cholesterol, LDL cholesterol, and triglycerides. Additional adjustments for BP medication (currently using BP medication/not using BP medication) were performed when analyzing BP and, likewise, additional adjustments for kyphosis (>15 cm distance between the tragus and the wall/≤15 cm distance between the tragus and the wall) when analyzing BMI and waist circumference in AS patients.
A logistic regression model was used to explore the associations between MS (dependent variable) and CRF (independent variable) with adjustments for age, sex, smoking, and inflammation.
Analyses were conducted using SPSS, version 18, and the level of statistical significance was set at a P value less than 0.05 for all analyses.
The patient group was significantly younger than the population controls (mean ± SD age 47.9 ± 10.8 years versus 52.1 ± 11.1 years; P < 0.01) and had a higher educational level (P = 0.03) (Table 1). Furthermore, the patients had significantly lower CRF than controls when adjusting for age and educational level (mean difference −2.3; 95% confidence interval [95% CI] −3.9, −0.7, P < 0.01).
|AS patients (n = 126)||Controls (n = 111)||P|
|Male, no. (%)||78 (62)||65 (59)||0.69b|
|Age, years||47.9 ± 10.8||52.1 ± 11.1||< 0.01c|
|>12 years education, no. (%)||91 (73)||65 (59)||0.03b|
|Current smoker, no. (%)||24 (19)||23 (21)||0.87b|
|VO 2 peak (ml × kg−1 × min−1)||40 (7)||41 (7)||< 0.01d|
|Medication, no. (%)|
|Anti-TNFα medication||24 (19)|
|NSAIDs||84 (67)||13 (12)||< 0.01|
|BP medication||25 (20)||19 (17)||0.62b|
|Statins||7 (6)||10 (9)||0.45b|
|Comorbidities, no. (%)|
|Diabetes mellitus||5 (4)||2 (2)||0.45b|
|Cancer||5 (4)||3 (3)||0.73b|
|ASDAS||2.2 ± 1.0|
|ASDAS >2.1, no. (%)||62 (52)|
|BASMI score||3.2 ± 1.8|
|BASFI score||2.4 ± 1.6|
|Levels of cardiovascular risk factors|
|BMI, kg/m2||25.4 ± 3.5||25.9 ± 3.8||0.37e|
|Waist circumference, cm||90 ± 11||90 ± 13||0.52e|
|Systolic BP, mm Hg||126 ± 16||129 ± 19||0.91f|
|Diastolic BP, mm Hg||78 ± 10||78 ± 12||0.24f|
|LDL cholesterol, mmoles/liter||3.2 ± 1.0||3.5 ± 0.7||0.02g|
|HDL cholesterol, mmoles/liter||1.6 ± 0.5||1.7 ± 0.5||0.63g|
|Glucose, mmoles/liter||5.0 ± 0.6||5.0 ± 0.6||0.82e|
|Triglycerides, median (range) mmoles/liter||1.2 (0.4–5.9)||1.1 (0.5–3.5)||0.65g|
|Sedimentation rate, median (range) mm/hour||17 (1–90)||8 (1–62)||< 0.001h|
|CRP level, median (range) mg/liter||3.0 (1–57)||1.0 (1–103)||< 0.001h|
The controls had a higher concentration of LDL cholesterol than patients (P = 0.02). Although not significant, there was a tendency toward a higher proportion of patients with reduced HDL cholesterol than controls (P = 0.07) (Table 2). As expected, patients had higher CRP levels (P < 0.001) and ESR (P < 0.001) than controls. Except for those mentioned above, no differences between patients and controls in background variables, characteristics, and CV factors were found.
|AS patients (n = 123–126)||Controls (n = 106–111)||Pb|
|BMI ≥25 kg/m2||66 (50)||67 (55)||0.45|
|Waist circumference (males ≥94 cm, females ≥80 cm)||67 (54)||56 (53)||1.00|
|Systolic BP ≥130 mm Hg||44 (35)||46 (42)||0.35|
|Diastolic BP ≥85 mm Hg||35 (27)||26 (24)||0.55|
|HDL cholesterol (males <1.03 mmoles/liter, females <1.29 mmoles/liter)||20 (16)||8 (7)||0.07|
|Triglycerides >1.7 mmoles/liter||33 (28)||28 (26)||0.88|
|Fasting plasma glucose ≥5.6 mmoles/liter||12 (10)||15 (14)||0.31|
|ESR (males >10 mm/hour, females >20 mm/hour)||73 (58)||23 (21)||< 0.001|
|C-reactive protein level ≥5 mg/liter||60 (46)||7 (6)||< 0.001|
|Metabolic syndrome||26 (22)||23 (21)||0.87|
In the patient group, 24 of 126 (19%) used anti–tumor necrosis factor medication while none of the controls used this type of medication (Table 1). Also, more patients used nonsteroidal antiinflammatory drugs (NSAIDs) than did controls (84 of 126 [67%] versus 13 of 111 [12%]; P < 0.01). There were no differences between the groups in the use of BP and statin medication.
Generally, all models were adjusted for age, sex, and smoking, as well as adjusted for inflammation when CRP level or ESR was not already included as dependent variables in the models. Additional adjustments are presented for each model when relevant.
VO2peak was inversely and significantly associated with BMI (P < 0.001) and waist circumference (P < 0.001) for patients and controls (additional adjustments for kyphosis in patients) (Table 3). Every 1-unit increment in VO2peak was associated with a mean (β) −0.3 kg/m2 (95% CI −0.4, −0.2) decrease in BMI in patients, and a mean (β) −0.3 kg/m2 (95% CI −0.5, −0.2) in controls. Also, every 1-unit increment in VO2peak was associated with a mean (β) −0.8 cm (95% CI −1.1, −0.5) decrease in waist circumference in patients, and a mean (β) −1.0 cm (95% CI −1.4, −0.6) decrease in waist circumference in controls.
|Model number: dependent variables||AS patients (n = 123–126)||Controls (n = 106–111)|
|β (95% CI)||P||β (95% CI)||P|
|1: BMI, kg/m2||−0.3 (−0.4, −0.2)b||< 0.001b||−0.3 (−0.5, −0.2)||< 0.001|
|2: Waist circumference, cm||−0.8 (−1.1, −0.5)b||< 0.001b||−1.0 (−1.4, −0.6)||< 0.001|
|3: Systolic blood pressure, mm Hg||−0.04 (−0.50, 0.42)c||0.87c||−0.89 (−1.46, −0.33)c||< 0.01c|
|4: Diastolic blood pressure, mm Hg||−0.14 (−0.42, 0.15)c||0.34c||−0.55 (−0.92, −0.18)c||< 0.01c|
|5: HDL cholesterol, mmoles/liter||0.00 (−0.01, 0.02)d||0.69d||0.03 (0.01, 0.04)d||0.001d|
|6: LDL cholesterol, mmoles/liter||−0.03 (−0.06, 0.004)d||0.09d||−0.01 (−0.03, 0.02)d||0.58d|
|7: Triglycerides, mmoles/liter||−0.03 (−0.6, −0.04)d||0.03d||−0.03 (−0.05, −0.003)d||0.03d|
|8: Glucose, mmoles/liter||−0.01 (−0.03, 0.01)||0.14||0.02 (−0.01, 0.04)||0.15|
|9: C-reactive protein level, mg/litere||−0.01 (−0.08, −0.004)||< 0.001||−0.08 (−0.61, −0.01)||0.02|
|10: Sedimentation rate, mm/houre||−0.05 (−0.37, −0.01)||< 0.01||−0.03 (−0.24, −0.003)||0.001|
VO 2 peak was significantly and inversely associated with systolic (P < 0.01) and diastolic (P < 0.01) BP in controls, but not in patients (additional adjustments for BP medication) (Table 3). In controls, every 1-unit increment in VO 2 peak was associated with a mean (β) −0.89 mm Hg (95% CI −1.46, −0.33) decrease in systolic BP and a mean (β) −0.55 mm Hg (95% CI −0.92, −0.18) decrease in diastolic BP.
VO2peak was positively and significantly associated with HDL cholesterol in controls (P = 0.001), but not in patients (additional adjustments for statins) (Table 3). For controls, every 1-unit increment in VO2peak was associated with a mean (β) 0.03 mmoles/liter (95% CI 0.01, 0.04) increase in HDL cholesterol. There were no associations between VO2peak and LDL cholesterol (with additional adjustments for statins) in either controls or patients.
VO2peak was significantly and inversely associated with triglycerides (with additional adjustments for statins) in both patients (P = 0.03) and controls (P = 0.03). Every 1-unit increment in VO 2 peak was associated with a mean (β) −0.03 mmoles/liter (95% CI −0.06, −0.04) decrease in triglycerides in patients, and a mean (β) −0.03 mmoles/liter (95% CI −0.05, −0.003) decrease in triglycerides in controls. There were no associations between CRF and glucose in patients or controls.
VO2peak was significantly and inversely associated with CRP level and ESR in both patients and controls (P < 0.001–0.02) (Table 3). Every 1- unit increment in VO 2 peak was associated with a mean (β) −0.01 mg/liter (95% CI −0.08, −0.004) decrease in CRP level in patients and a mean (β) −0.08 mg/liter (95% CI −0.61, −0.01) decrease in controls. Also, every 1-unit increment in VO 2 peak was associated with a mean (β) −0.05 mm/hour (95% CI −0.37, −0.01) decrease in ESR in patients, and a mean (β) −0.03 mm/hour (95% CI −0.24, −0.003) decrease in controls.
In the logistic regression analysis, higher VO2peak was associated with a lower risk for having MS for patients (odds ratio [OR] 0.91 [95% CI 0.83, 0.99], P = 0.03) and controls (OR 0.89 [95% CI 0.81, 0.97], P = 0.01).
The results of this study showed that high CRF was significantly associated with favorable levels of CV risk factors and lower risk for having MS in patients with AS and population controls. However, the significant associations between CRF and BP and HDL cholesterol observed in population controls were not confirmed in patients with AS.
In healthy adults there is strong evidence of an association between CRF and CV risk factors [9, 10, 28]. To our knowledge, this has not been investigated previously in patients with AS or other rheumatic diseases. However, a recent study reported that physical activity level (total energy expenditure) was positively related to fat-free BMI and inversely related to CRP level in patients with AS . In line with this, Metsios et al  reported that physically inactive patients with rheumatoid arthritis (RA) had a significantly worse cardiovascular disease profile than physically active patients, which is in agreement with our results. Although physical fitness is shown to be related to physical activity level , the relationship between physical fitness and CV risk factors, as studied in the current study, has not been established previously in AS patients. This relationship is of interest, and in 3 recently published studies, the authors concluded that CRF matters more than physical activity in controlling CV diseases in healthy adults [8, 10, 28].
We found that high CRF was associated with lower odds of having MS in AS patients and controls. Despite this, no associations between CRF and HDL cholesterol and BP, 2 of the main elements in MS, were observed in AS patients. However, the definition of MS used in the present study includes increased waist circumference as an absolute criterion; we did observe a strong inverse association between CRF and waist circumference, which is recognized as essential in the development of other MS components . Hence, it is reasonable to assume that the observed association between CRF and MS is indirectly influenced by the strong association between CRF and waist circumference.
Inflammation is known to play a key role in the development of CV diseases because it contributes to the development of atherosclerosis and accentuates established CV risk factors . In relation to this, we found an inverse association between CRF and inflammatory markers in AS patients and controls. This result is in agreement with a recent study in which the authors concluded that physical activity level was inversely related to CRP level in AS patients . Also, in RA patients physical activity level has been reported to be inversely related to inflammatory markers , and intervention studies have shown that exercise (planned physical activity with the aim of improving physical fitness) reduces inflammation [32, 33]. In addition, a similar relationship is reported in the general population [11-14]. On one hand, a reduction in disease activity may cause a lower functional impairment that is associated with an easier exercise and higher VO2peak. On the other hand, as an explanation for this relationship, it is suggested that CRP levels are indirectly reduced by the exercise-induced reduction in BP, triglycerides, and apolipoproteins . Moreover, exercise may have a direct antiinflammatory effect because muscle contractions are involved in the regulation of proinflammatory cytokines, and an indirect effect by reducing adipose tissue, which also is an endocrine organ that produces several proinflammatory cytokines . Thus, exercise might have a potential to mediate inflammation in patients, both indirectly by a reduction in adipose tissue and directly by a reduction in inflammatory markers.
Established findings of an inverse relationship between physical fitness and BP and a positive relationship between physical fitness and HDL cholesterol were found in controls, but not in patients, in the present study. In accordance with this, Metsios et al  found no relationship between physical activity level and HDL cholesterol and diastolic BP in patients with RA. The association between CRF and BP is explained through an exercise-induced reduction in vascular resistance due to a positive influence on the sympathetic nervous system . Furthermore, the association between CRF and HDL cholesterol is explained by increased energy expenditure and increased lipoprotein lipase [37, 38]. Hence, the present results indicate that other factors than CRF are more important in explaining BP and HDL cholesterol levels in AS patients compared to the general population. Therefore, AS and RA patients may possibly respond differently to cardiorespiratory exercise than adults without a rheumatic disease. The lack of associations between CRF and HDL cholesterol and BP observed in the present study might be related to either the pathology of AS and RA or to the medications used in treatment of these diseases (e.g., NSAIDs). It should also be mentioned that although the present results were adjusted for the current inflammation, the total burden of inflammation during the disease history was not taken into account. Thus, prospective studies are needed to investigate the BP and HDL cholesterol response to cardiorespiratory exercise in patients with AS.
It is well documented that aerobic exercise may lead to increased CRF, and we observed that CRF was associated with favorable values of some of the CV risk factors and lower risk of having MS in both patients and controls. Exercise is recommended as a cornerstone in the treatment of AS . However, as shown in a systematic review, the main focus has traditionally been flexibility exercises , and most likely, flexibility exercises do not lead to increased CRF. Thus, our results suggest that there should also be a focus on improvement of CRF in AS patients, with the aim at reducing the risk of CV disease.
A strength of this study is a relatively large heterogeneous sample of AS patients with varying degrees of disease activity and severity, indicating that the results may be generalized. In addition, the controls were randomly drawn from the general population, and we found similar associations between CRF and CV risk factors in our control group as previously reported in several large epidemiologic studies of healthy adults [9, 10, 28]. Therefore, since previously reported results in healthy adults were reproduced, the inclusion of controls in this study validates the study protocol. Furthermore, both AS patients and controls underwent a comprehensive assessment of CV risk factors and CRF. However, a limitation is that CRF was estimated based on a maximal walking test and was not measured by the criterion measure. The CRP level, not the ASDAS, was used to adjust for disease activity. This was done because the ASDAS is a measure of both patient-reported outcomes (back pain, pain in other joints, morning stiffness, and self-reported rating of disease activity) and CRP level. In relation to this, a Cochrane review from 2008 reported that physical therapy interventions mainly consisting of physical activity reduced pain and stiffness in AS patients . Hence, adjusting for the ASDAS while investigating the relationship between physical fitness and CV risk factors could possibly have masked the influence of CRF. Even if multiple comparisons were made in this study, a Bonferroni correction was not performed because it was considered too strict for this relatively small sample size viewed in an epidemiologic tradition. However, some of the results remained statistically significant also after a Bonferroni correction. Furthermore, no causal pathways can be suggested due to the cross-sectional design of this study.
In conclusion, this study showed that high CRF was significantly associated with lower risk of MS and favorable levels of CV risk factors in AS patients and controls. However, the significant inverse relationship between CRF and BP and the significant positive relationship between physical fitness and HDL cholesterol as observed in controls were not confirmed in AS patients. Thus, more studies on the effect of exercise on CV risk factors in AS patients are needed.
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be submitted for publication. Ms Halvorsen had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study conception and design. Halvorsen, V⊘llestad, Provan, Semb, Hagen, Dagfinrud.
Acquisition of data. Halvorsen, Provan, Semb, Hagen, Dagfinrud.
Analysis and interpretation of data. Halvorsen, V⊘llestad, Semb, van der Heijde, Hagen, Dagfinrud.