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Keywords:

  • Rheumatoid arthritis;
  • Antioxidants;
  • Cardiovascular risk factors

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Objective

To compare antioxidants and other novel and traditional cardiovascular disease (CVD) risk factors in participants with rheumatoid arthritis (RA) and non-RA controls in a large population sample.

Methods

The Third National Health and Nutrition Examination Survey (NHANES-III) was a cross-sectional population survey in which subjects ages ≥60 underwent a musculoskeletal examination. RA subjects were defined as those who met ≥3 of 6 available 1987 American College of Rheumatology (ACR) criteria. Non-RA subjects were defined as those who met no ACR criteria. We performed univariate and multivariate analyses of the association between RA and each novel and traditional CVD risk factor in RA versus non-RA subjects.

Results

The sample included 5,302 subjects ages ≥60, with 131 (2.5%) RA and 4,444 (84%) non-RA participants. A total of 727 subjects were excluded. Plasma levels of antioxidants α-carotene, β-cryptoxanthin, lutein/zeaxanthin, and lycopene were significantly lower in RA subjects compared with non-RA subjects in multivariate analysis adjusting for potential confounders. Compared with non-RA participants, RA subjects were more likely to have increased C-reactive protein (CRP) levels in multivariate analysis adjusting for potential confounders. RA and non-RA participants had similar prevalence of traditional CVD risk factors and previous CVD.

Conclusion

In this large population study, RA subjects had similar prevalence of previous CVD and traditional CVD risk factors as controls. Among novel CVD risk factors, plasma carotenoid levels were significantly lower and CRP level was significantly higher in RA compared with non-RA subjects after adjustment for potential confounders. Further research should evaluate whether these differences account for the observed increased incidence of CVD in individuals with RA.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Rheumatoid arthritis (RA), the most common systemic, chronic inflammatory, autoimmune disease, is associated with excess cardiovascular morbidity and mortality that is not entirely explained by traditional risk factors for cardiovascular disease (CVD) (1–4). Novel risk factors for CVD including inflammatory biomarkers, antioxidants, and/or vitamins may contribute to excess CVD in persons with RA.

RA and atherosclerosis share common inflammatory mechanisms (5, 6). There is an association between inflammatory markers and subsequent CVD in healthy subjects (7–10). Therefore, chronic systemic inflammation may contribute to the higher incidence of CVD in persons with RA (11–14).

Moreover, there is a complex relationship between inflammation, antioxidant vitamin status, and the risk of CVD. Previous reports have demonstrated inverse associations between inflammation and antioxidant serum levels, in particular carotenoids (15–17). Furthermore, intakes of antioxidant vitamins and other micronutrients or their serum concentrations, including carotenoids (18–20), vitamin C (21–23), vitamin E (24, 25), and folate and homocysteine (26–28), have been reported to be inversely associated with CVD incidence and mortality.

An inverse association between vitamin D levels and CVD risk and risk factors has been suggested based on the biologic effects of vitamin D, which include immunomodulatory effects (29, 30), antiproliferative effects on myocardiocytes (31, 32), and effects on the renin–angiotensin system (33, 34). Thus, in the context of a chronic inflammatory disease, deficiency of antioxidants and/or vitamins may be associated with accelerated atherosclerosis in persons with RA. The objective of the present study was to compare novel risk factors for CVD, including inflammatory biomarkers, antioxidants and vitamins, and traditional CVD risk factors, between subjects with RA and subjects without RA in a large cross-sectional survey of the US population.

SUBJECTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Data source.

Data were derived from the Third National Health and Nutrition Examination Survey (NHANES-III). NHANES-III was conducted between 1988 and 1994 to assess the health and nutrition of a large representative sample of the civilian, noninstitutionalized US population. The sampling frame was as a multistage, stratified, clustered survey to ensure representativeness (35, 36). All participants provided informed consent. No personal identifiers were included. Data including demographic characteristics, signs and symptoms of RA, traditional CVD risk factors, history of cardiovascular events, and information on prescription drug use were collected through an interview in the participants' homes. All interviewed persons were invited for a medical examination performed by a physician at the mobile examination center (MEC), where blood samples were also obtained. The musculoskeletal examination was performed for subjects ages ≥60 years.

Demographics.

Demographic information included age, sex, race, marital status, educational level, and poverty index. The poverty index is defined as a ratio of family income to the national poverty threshold, as determined annually by the US Census Bureau, age of the family reference person, and calendar year in which the family was interviewed (35, 36). Education was coded as the number of years of formal education completed.

Novel risk factors for CVD.

A priori, we considered biomarkers including levels of antioxidants and vitamins, inflammatory biomarkers, and lipoproteins as novel risk factors for CVD (37). We examined serum levels of antioxidants/vitamins (vitamin A, vitamin C, vitamin D, vitamin E, α-carotene, β-carotene, β-cryptoxanthin, lutein/ zeaxanthin, and lycopene), homocysteine, folate, and inflammatory biomarkers (serum C-reactive protein [CRP] level, fibrinogen, white blood cell count, platelet volume, and hemoglobin). Serum CRP level was categorized as undetectable (<22 mg/dl), detectable (0.22–1 mg/dl), and elevated (>1 mg/dl) as previously defined (16). Fasting blood samples were tested for lipids (serum triglycerides, total cholesterol, high-density lipoprotein [HDL] cholesterol, and low-density lipoprotein [LDL] cholesterol), lipoproteins (lipoprotein[a], apolipoprotein A-1, apolipoprotein B), and biomarkers considered as novel potential risk factors for CVD (37).

Traditional risk factors for CVD and previous CVD.

A priori, we considered smoking, diabetes, hypertension, dyslipidemia, family history of premature myocardial infarction (MI), obesity/body mass index (BMI), and sedentary lifestyle as traditional CVD risk factors. Smoking status was assessed during the household interview. Respondents were classified as never smokers (<100 cigarettes in their lifetime), former smokers (≥100 lifetime cigarettes, not currently smoking), and current smokers (≥100 lifetime cigarettes, currently smoking). Information on pack-years of smoking was also recorded. Diabetes was defined as a fasting plasma glucose level >126 mg/dl, the presence of a 2-hour glucose tolerance test result >200 mg/dl (the 2-hour glucose tolerance test was performed only among subjects ages 60–74 years not receiving insulin), or self-report of a physician diagnosis. Blood pressure was measured 3 times during the home interview and 3 times during the physical examination. Mean blood pressure was calculated by using all available systolic and diastolic readings. Hypertension was defined as mean systolic blood pressure >140 mm Hg, mean diastolic blood pressure >90 mm Hg, or use of antihypertensive medications. Dyslipidemia was defined by use of medications to treat hypercholesterolemia, fasting total serum cholesterol level >240 mg/dl, or LDL cholesterol level >160 mg/dl, or by self-report of high cholesterol. Framingham risk score was also calculated for all subjects (38). History of stroke, MI, and congestive heart failure was obtained by self-report of a physician diagnosis. Information on current use of postmenopausal hormone (PMH) and use of vitamin or mineral supplements was obtained by self-report. Nutrient intake was estimated from a 24-hour dietary recall (36). Alcohol consumption was determined from a food frequency questionnaire. Physical activity was based on leisure-time physical activity in the past month (39) and was reported in metabolic equivalent units. Sedentary lifestyle was defined by denial of any leisure-time physical activity.

Anthropometric measures such as body weight, height, and waist and hip circumferences were obtained from physical examination. BMI was calculated as weight (in kg) divided by the square of height (in meters). Waist circumference was measured at the level of the high point of the iliac crest and hip circumference was measured at the level of maximum extension of the buttocks. The waist-to-hip ratio (WHR) was calculated as waist circumference divided by hip circumference (in cm).

Assessment of rheumatoid arthritis.

RA was defined based on the 1987 American College of Rheumatology (ACR; formerly the American Rheumatism Association) criteria for classification of RA using self-report of morning stiffness, objective findings of synovitis from physical examination, and positive rheumatoid factor (40). Radiographs of the hands and wrists were obtained in all subjects older than 60 years, but interpretation of the radiographs was not available at the time of this study. Therefore, 6 of the 7 ACR criteria for RA classification were available.

Participants who met at least 3 of 6 available ACR criteria were defined as having RA as previously described (41–43). Briefly, a recent study identified subjects with RA in NHANES-III (41) by applying the “n of k” rule (40) identifying subjects with 3 of 6 ACR criteria. Recent RA studies used these methods to define RA cases in NHANES (42, 43). Participants who met no ACR criteria were defined as non-RA subjects. Subjects who met 1–2 ACR criteria were excluded from the analysis.

Medication data.

We assessed use of nonsteroidal antiinflammatory drugs (NSAIDs), oral corticosteroids, and disease-modifying antirheumatic drugs (DMARDs). Information on medication use in the last month was based on self-report of a prescription (41).

Statistical analysis.

Summary statistics are presented as the mean ± SD for continuous measures and frequencies for all discrete variables. First, we compared RA subjects with non-RA subjects. Second, we compared seropositive RA individuals with seronegative RA individuals in a subset analysis. We used multivariate linear and logistic regression models for each novel and traditional CVD risk factor, adjusted for age, race/ethnicity, and sex.

Multiple linear regression was used to determine whether the level of antioxidant micronutrients was independently associated with RA. In addition to age, race/ethnicity, sex, poverty index, and education, these models were adjusted for known determinants of antioxidant micronutrient levels including vitamin intake, carotenoid intake, total caloric intake, BMI, total cholesterol, HDL, smoking, diabetes, PMH, and alcohol consumption. Carotenoid intake was entered in the multivariate model as a continuous variable. An exploratory model further adjusted for CRP level.

Multivariate linear regression models were used to determine whether the level of biomarkers was independently associated with RA. The analyses were conducted among subjects with complete information on each biomarker. The models were adjusted for age, race, sex, smoking, diabetes, BMI, PMH, WHR, alcohol intake, previous CVD, poverty index, and education.

Multivariate logistic regression was used to determine whether a given traditional CVD risk factor was associated with RA, adjusting for potential confounders including smoking, PMH, alcohol intake, diabetes, BMI, WHR, previous CVD, poverty index, and education. Finally, to evaluate to what extent differences in physical activity or antiinflammatory medications explain differences between RA and non-RA subjects, sedentary lifestyle and physical activity and/or medications were entered in the multivariate models.

We used Stata software (StataCorp, College Station, TX) survey data commands and applied NHANES-III weights to all analyses. A P value less than 0.05 was considered as statistically significant. Formal alpha adjustments were not performed (44–46).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Among 5,302 subjects ages ≥60 years who had examination variables, 131 (2.5%) met 3 of 6 ACR criteria for RA and 4,444 (84%) subjects were defined as non-RA controls. A total of 727 subjects were excluded. Sociodemographic characteristics and clinical factors are described in Table 1. RA participants were slightly older than controls (mean ± SD age 74 ± 8 years versus 72 ± 8 years; P < 0.006). RA subjects were more likely to be taking NSAIDs (P < 0.001) and DMARDs (P < 0.001) than non-RA subjects. Seropositive RA participants were more likely to be taking DMARDs (P = 0.03) but not NSAIDs (P = 0.3) or steroids (P = 0.4) compared with those with seronegative RA. Hemoglobin levels were significantly lower in RA subjects compared with non-RA subjects (mean ± SD 13.3 ± 1.6 gm/dl versus 14 ± 1.4 gm/dl; P = 0.006).

Table 1. Characteristics of RA cases and controls from the Third National Health and Nutrition Examination Survey (NHANES-III)*
CharacteristicRA (n = 131)Non-RA (n = 4,444)
  • *

    Values are the number (percentage) unless otherwise indicated. RA = rheumatoid arthritis; CVD = cardiovascular disease; CHD = coronary heart disease; METs = metabolic equivalent units; BMI = body mass index; WHR = waist-to-hip ratio; ACR = American College of Rheumatology; RE = retinol equivalent.

  • P < 0.05.

  • Classified as never smokers (smoked <100 cigarettes in their lifetime), former smokers (≥100 lifetime cigarettes, not currently smoking), and current smokers (≥100 lifetime cigarettes, currently smoking).

  • §

    Percent risk of a CHD event over 10 years based on Framingham risk score (38).

  • Based on leisure-time physical activity (39), defined as a continuous variable reported in METs.

  • #

    Calculated as weight in kilograms divided by the square of height in meters.

  • **

    Calculated as waist circumference divided by hip circumference (in cm). Waist circumference was measured at the level of the high point of the iliac crest and hip circumference at the level of maximum extension of the buttocks.

Age, mean ± SD years74 ± 872 ± 8
Female sex75 (57)2,229 (50)
White race/ethnicity78 (60)2,590 (57)
Married70 (53)2,493 (56)
Education, median (interquartile range) years9 (6)10 (5)
Poverty index, median (interquartile range)1.4 (1.8)1.7 (2.1)
Smoking status  
 Current16 (12)674 (15)
 Former47 (36)1,674 (38)
 Never67 (52)2,083 (47)
Personal history of CVD  
 Myocardial infarction11 (9)492 (11)
 Congestive heart failure12 (9)383 (9)
 Stroke10 (8)321 (7)
10-year CHD risk, mean ± SD§20 ± 1420 ± 13
Physical activity, median (interquartile range) METs18 (105)41 (146)
BMI, median (interquartile range) kg/m2#26 (7)26.4 (6.3)
WHR, median (interquartile range)**0.96 (0.1)0.97 (0.1)
ACR criteria  
 004,444
 399 (76)0
 ≥432 (24)0
Dietary intake (n = 121/4,217)  
 Alcohol, mean ± SD grams3.3 ± 114.2 ± 15
 Energy, median (interquartile range) kcal1,455 (780)1,550 (902)
 Carotene, median (interquartile range) RE189 (503)229 (601)
 Vitamin A, median (interquartile range) IU4,249 (5,494)4,152 (6,830)
 Vitamin C, median (interquartile range) mg73 (107)79 (103)
 Vitamin E, median (interquartile range) equivalents5.4 (5.2)6 (5.6)

Among novel risk factors for CVD, the plasma levels of antioxidants were significantly lower in RA subjects compared with non-RA subjects, specifically carotenoids such as α-carotene, lutein/zeaxanthin, lycopene, and β-cryptoxanthin, in age-, race-, and sex-adjusted models (Table 2). This association remained significant with further adjustments in the multivariate model for smoking; alcohol consumption; BMI; PMH; total cholesterol; HDL; and vitamin, carotenoid, and energy intake. An exploratory model further adjusting for CRP level attenuated the difference but results remained significant. Overall, carotenoid intake was significantly correlated with carotenoid plasma levels (P < 0.001).

Table 2. Multivariate analyses of antioxidant levels among subjects ages ≥60 years from the Third National Health and Nutrition Examination Survey (NHANES-III)*
AntioxidantsRA (n = 119)Non-RA (n = 4,188)Multivariate adjusted, β (95% CI)Multivariate fully adjusted, β (95% CI)Multivariate fully adjusted, β (95% CI)§
  • *

    Values are the median (interquartile range) unless otherwise indicated. RA = rheumatoid arthritis; β = mean difference between RA cases and controls; 95% CI = 95% confidence interval.

  • Multivariate model adjusted for age, race, and sex.

  • Multivariate linear regression model adjusted for age, race, sex, smoking, diabetes, body mass index, postmenopausal hormone, alcohol intake, energy intake, vitamin (A, C, E) intake, carotenoid intake, high-density lipoprotein, total cholesterol, poverty index, and education.

  • §

    Multivariate linear regression model adjusted for age, race, sex, smoking, diabetes, body mass index, postmenopausal hormone, alcohol intake, energy intake, vitamin (A, C, E) intake, carotenoid intake, high-density lipoprotein, total cholesterol, poverty index, education, and C-reactive protein.

Vitamins     
 Retinyl esters (μg/dl)5 (5)6.0 (5.9)−0.1 (−1.5, 1.2)0.1 (−1.2, 1.4)0.2 (−1.1, 1.5)
 Vitamin A (μg/dl)64 (24)61 (21)2.9 (−4.4, 10.1)3.6 (−2.7, 9.8)4.3 (−2.1, 10.8)
 Vitamin C (mg/dl)0.7 (0.6)0.8 (0.7)−0.1 (−0.2, 0.1)−0.002 (−0.2, 0.2)0.02 (−0.2, 0.2)
 Vitamin D (ng/ml)64 (38)62 (34)−2.4 (−8.3, 3.6)−1.8 (−7.8, 4.2)−1.4 (−7.4, 4.5)
 Vitamin E (μ/dl)1,245 (623)1,220 (549)47 (−249, 342)82 (−172, 336)80.5 (−169, 330)
Carotenoids     
 β-carotene (μg/dl)17 (20)19 (20)−2.2 (−8.8, 4.4)−0.5 (−6.6, 5.6)0.2 (−6.0, 6.5)
 α-carotene (μg/dl)4 (3)4 (3)−1.7 (−2.3, −1.1)−1.3 (−1.9, −0.7)−1.1 (−1.8, −0.5)
 β-cryptoxanthin (μg/dl)7 (6)8 (8)−2.6 (−3.8, −1.4)−1.8 (−3.2, −0.5)−1.6 (−2.9, −0.3)
 Lutein/zeaxanthin (μg/dl)20 (15)23 (15)−4.2 (−6.7, −1.7)−3.1 (−6.0, −0.3)−2.9 (−5.8, −0.1)
 Lycopene (μg/dl)12 (10)15 (14)−3.6 (−5.8, −1.5)−2.8 (−5.3, −0.3)−2.5 (−4.9, −0.1)

There was no difference in the plasma concentration of β-carotene and vitamins A, C, D, and E (Table 2). In contrast, RA participants had higher levels of inflammatory markers such as fibrinogen (mean ± SD 352 ± 114 mg/dl versus 331 ± 90 mg/dl; P = 0.1) and CRP level (0.9 ± 1.4 mg/dl versus 0.6 ± 1.0 mg/dl; P = 0.01). RA participants were significantly more likely to have clinically elevated CRP levels in multivariate analysis adjusted for age, race, and sex (odds ratio [OR] 3.1; 95% confidence interval [95% CI] 1.6, 5.8), and with further adjustment for education, poverty income ratio, smoking, BMI, WHR, PMH, diabetes, alcohol intake, and previous CVD (OR 3.2; 95% CI 1.4, 7.2) (Table 3). A model further adjusting for physical activity and medications yielded similar results (OR 2.9; 95% CI 1.2, 6.9). RA subjects tended to have slightly lower plasma concentrations of lipids, lipoproteins, homocysteine, folate, and red blood cell folate than non-RA subjects, but none of the differences were significant in multivariate models (Table 3). In a subset analysis limited to participants with RA, seropositive subjects were more likely to have elevated CRP levels in age-, race-, and sex-adjusted analysis (OR 10.2; 95% CI 3.3, 31.8) and multivariate analysis (OR 14.6; 95% CI 2.3, 91.6) compared with seronegative RA subjects.

Table 3. Multivariate analyses of novel risk factors for cardiovascular disease among subjects ages ≥60 years from the Third National Health and Nutrition Examination Survey (NHANES-III)*
BiomarkersNo. RA/ non-RARANon-RAMultivariate adjusted, β (95% CI)Multivariate fully adjusted, β (95% CI)§OR (95% CI)OR (95% CI)#
  • *

    Values are the median (interquartile range) unless otherwise indicated. RA = rheumatoid arthritis; β = mean difference between RA cases and controls; 95% CI = 95% confidence interval; OR = odds ratio; LDL = low-density lipoprotein; HDL = high-density lipoprotein; RBC = red blood cell; WBC = white blood cell; CRP = C-reactive protein.

  • Sample size corresponding to each biomarker.

  • Multivariate linear regression model adjusted for age, race, and sex.

  • §

    Multivariate linear regression model adjusted for age, race, sex, smoking, diabetes, body mass index, postmenopausal hormone, waist-to-hip ratio, alcohol intake, previous cardiovascular disease, poverty index, and education.

  • Multivariate logistic regression model adjusted for age, race, and sex.

  • #

    Multivariate logistic regression model adjusted for age, race, sex, smoking, diabetes, body mass index, postmenopausal hormone, waist-to-hip ratio, alcohol intake, previous cardiovascular disease, poverty index, and education.

  • **

    Serum CRP level was categorized as undetectable (<22 mg/dl), detectable (0.22–1 mg/dl), and elevated (>1 mg/dl) as previously defined (16).

Cholesterol (mg/dl)120/4,213213 (65)220 (57)−2.5 (−17, 12)−6.8 (−16, 2.4)  
LDL (mg/dl)60/1,791131 (51)139 (48)−5.9 (−20, 8.5)−1.6 (−14, 11)  
HDL (mg/dl)121/4,18750 (22)49 (20)−0.4 (−4.1, 3.3)0.1 (−4.2, 4.5)  
Triglycerides (mg/dl)119/4,208134 (98)135 (95)−5.2 (−31, 20)−8.3 (−29, 13)  
Apolipoprotein A-1 (mg/dl)102/2,015146 (28)148 (27)0.03 (−6.1, 6.2)2.8 (−3.9, 9.6)  
Apolipoprotein B-1 (mg/dl)102/2,017139 (43)144 (34)−0.9 (−9.4, 7.6)−3.9 (−9.2, 1.5)  
Lipoprotein(a) (mg/dl)19/2,18616 (48)17 (32)0.9 (−8.3, 10.2)2.8 (−6, 12)  
Homocysteine (μmoles/ liter)16/1,8699.3 (6)10.5 (5)1.5 (−3.0, 6.1)1.5 (−3.5, 6.6)  
Folate (ng/ml)123/4,2325.8 (7.6)6.3 (6.4)2.2 (−4.1, 8.5)2.7 (−5, 10.5)  
RBC folate (ng/ml)123/4,248192 (194)194 (192)49 (−22, 119)51 (−31, 133)  
WBC117/4,2356.6 (2.7)6.8 (2.5)−0.1 (−0.6, 0.4)−0.1 (−0.7, 0.4)  
Platelet volume117/4,2368.2 (1.2)8.4 (1.3)−0.1 (−0.4, 0.1)−0.1 (−0.4, 0.2)  
Fibrinogen (mg/dl)111/4,094328 (159)318 (98)25 (−8.4, 59)26 (−12, 64)  
CRP categories**119/4,172      
 Undetectable CRP65/2,467    1.001.00
 Detectable CRP27/1,222    0.9 (0.5, 1.8)1.1 (0.6, 2.2)
 Clinically elevated CRP27/483    3.1 (1.6, 5.8)3.2 (1.4, 7.2)

RA participants tended to have a slightly higher prevalence of hypertension (70% versus 62%), dyslipidemia (43% versus 34%), diabetes (28% versus 26%), family history of early MI (10% versus 9%), and sedentary lifestyle (40% versus 29%) than non-RA individuals (Table 4). However, these differences were not significant after adjustment for potential confounders. Framingham risk score was similar among RA and non-RA participants (20% versus 19%). None of the differences in smoking, previous CVD, BMI, WHR, and leisure-time physical activity were statistically significant (Table 1).

Table 4. Multivariate analyses of traditional risk factors for cardiovascular disease among subjects ages ≥60 years from the Third National Health and Nutrition Examination Survey (NHANES-III)*
Clinical factorsRA (n = 131)Non-RA (n = 4,444)Multivariate adjusted, OR (95% CI)Multivariate fully adjusted, OR (95% CI)
  • *

    Values are the number (percentage) unless otherwise indicated. RA = rheumatoid arthritis; OR = odds ratio; 95% CI = 95% confidence interval; MI = myocardial infarction.

  • Multivariate logistic regression model adjusted for age, race, and sex.

  • Multivariate logistic regression model adjusted for age, race, sex, smoking, diabetes, body mass index, postmenopausal hormone, waist-to-hip ratio, alcohol intake, poverty index, and education.

  • §

    Diabetes was defined by the presence of a fasting plasma glucose level >126 mg/dl, presence of a 2-hour glucose tolerance test result >200 mg/dl (performed only among subjects ages 60–74 years not receiving insulin), or self-report of a physician diagnosis. The multivariate logistic regression model was adjusted for age, race, sex, smoking, body mass index, postmenopausal hormone, waist-to-hip ratio, alcohol intake, poverty index, and education.

  • Blood pressure was measured 3 times during the home interview and 3 times during the physical examination. A mean blood pressure was calculated by using all available systolic and diastolic readings. Hypertension was defined as mean systolic blood pressure >140 mm Hg, mean diastolic blood pressure >90 mm Hg, or use of antihypertensive medications.

  • #

    Dyslipidemia was defined by use of medications to treat hypercholesterolemia, fasting total serum cholesterol level >240 mg/dl, or low-density lipoprotein cholesterol level >160 mg/dl, or by self-report of high cholesterol.

  • **

    Data available for 124 RA cases and 4,352 controls.

Diabetes§37 (28)1,165 (26)1.1 (0.7, 2.0)0.9 (0.5, 1.7)
Hypertension92 (70)2,757 (62)1.5 (1.0, 2.4)1.4 (0.8, 2.2)
Dyslipidemia#56 (43)1,493 (34)1.4 (0.9, 2.1)1.2 (0.7, 2.1)
Family history early MI**12 (10)410 (9)1.0 (0.5, 2.2)1.1 (0.4, 2.5)
Sedentary lifestyle52 (40)1,282 (29)1.9 (1.2, 3.0)1.2 (0.6, 2.4)

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Among novel CVD risk factors, the levels of antioxidants α-carotene, β-cryptoxanthin, lutein/zeaxanthin, and lycopene were significantly lower in RA participants compared with non-RA participants in this large population-based study. These associations remained significant after adjustment for known and potential confounders. CRP level was significantly higher in subjects with RA. Furthermore, seropositive RA subjects were more likely to have a higher CRP level than seronegative RA subjects. Participants with RA in NHANES-III had a similar prevalence of traditional CVD risk factors and personal history of CVD compared with non-RA controls.

Our findings of lower antioxidant micronutrient levels in RA compared with non-RA participants may be explained by inflammation. Several studies have demonstrated inverse associations between inflammation and plasma concentrations of carotenoids and retinol (15–17). An inverse relationship between markers of inflammation and antioxidant levels has been observed among individuals with RA (47). A prospective cohort study of women found an inverse association of β-cryptoxanthin with risk of RA (48) and a recent population-based study reported an inverse association between intake of β-cryptoxanthin and risk of inflammatory polyarthritis (49), suggesting that intake of certain antioxidant micronutrients may be protective against the development of RA.

The lower antioxidant concentrations among participants with RA may have resulted from lower intake of antioxidants, increased metabolism of antioxidants, or both. Adjusting for dietary nutrient intake is helpful in establishing how much of the antioxidant deficit may be attributable to inadequate intake of antioxidants. After adjusting for nutrient intake, subjects with RA still had lower concentrations of antioxidants. This finding suggests that increased metabolism of antioxidants probably results in the reduced antioxidant concentrations found among participants with RA.

Previous studies have demonstrated that plasma carotenoid concentrations are reflective of dietary intake (50–54). The magnitude of the correlation varies depending on the specific carotenoid and the dietary assessment tool (55). Overall, there was a significant correlation between carotenoid intake and carotenoid plasma levels. Lower plasma concentrations of the carotenoids α-carotene, β-cryptoxanthin, lutein/zeaxanthin, and lycopene in RA subjects compared with controls persisted after controlling for age, sex, race, smoking, alcohol consumption, diabetes, BMI, PMH, total cholesterol, HDL, vitamin, carotenoid, and energy intake, suggesting that RA may cause an increased metabolic turnover of antioxidants.

Cigarette smoking is a dose- and time-dependent risk factor for RA (56). Smoking also affects the serum concentrations of antioxidant micronutrients (57). Therefore, residual confounding by smoking is a concern. However, adjusting for smoking using pack-years did not alter the results (data not shown).

Controlling for CRP level attenuated the difference between the groups but results remained significant. The inflammatory process in RA, through the production of reactive oxygen species, may deplete stores of antioxidants, but we cannot rule out other causes such as decreased intake, decreased absorption, or transport of antioxidant micronutrients in subjects with RA. Nevertheless, a low antioxidant status might increase the potential for oxidative damage. Several epidemiologic studies have found inverse associations between serum carotenoid levels and CVD (18–20). The magnitude of the reduction has ranged from only small decreases to a more than 50% reduction in risk (18). In addition, cohort studies of dietary carotenoid intake and CVD found a lower risk of coronary events in individuals consuming greater amounts of carotenoids (58, 59). Plasma levels of lycopene are inversely related to risk of ischemic stroke (19), risk of MI (60), and risk of atherosclerosis (61–63). In general, the epidemiologic evidence suggests that a diet rich in high carotenoid foods is associated with a reduced risk of CVD. Further research should evaluate the causal pathway of the lower carotenoid levels in RA and whether they account for the observed increased incidence of CVD in patients with RA. An inverse association between CVD risk and CVD risk factors and low levels of vitamin D has been suggested (64–66). Low intake of vitamin D and low serum levels of 1,25-dihydroxyvitamin D were significantly predictive of acute MI and stroke when adjusted for age, sex, smoking, and functional capacity in a recent study of subjects older than 65 years followed up for 10 years (67). Furthermore, in a cohort of elderly women, a greater intake of vitamin D had an inverse association with incident RA (68). However, we did not find differences in vitamin D concentrations between RA cases and controls.

The inflammatory markers CRP and fibrinogen are associated with CVD and its severity (7, 10, 69), and it has been postulated that atherosclerosis and RA share common inflammatory mechanisms (5, 6). CRP level was significantly higher in subjects with RA, which is expected given the inflammatory nature of the disease. CRP is an acute-phase protein produced by the liver in response to interleukin-6. Evidence suggests that CRP has atherosclerosis-promoting effects on the vascular wall, including the production of cellular adhesion molecules by endothelial cells (70–72). CRP levels are associated with RA disease activity and severity, which has been associated with CVD mortality (73, 74). Furthermore, a recent study demonstrated that CRP level is a predictor of cardiovascular mortality in patients with RA and inflammatory polyarthritis, independent of disease severity (75). Therefore, chronic inflammation in RA may lead to accelerated atherosclerosis, which in turn may be responsible for the higher incidence of CVD in patients with RA (11–14, 76).

Conventional risk factors for CVD appear to account for approximately 80–90% of all coronary heart disease events in the general population (77, 78). However, previous studies have demonstrated that RA is associated with excess cardiovascular morbidity and mortality that is not entirely explained by traditional risk factors for CVD (1–4). A recent prospective study found that women with RA had a significantly 2-fold increased risk of MI compared with those without RA, adjusting for age, traditional risk factors, oral glucocorticoid use, NSAID use, and intake of folate, omega-3 fatty acids, and vitamin E supplements (2), suggesting that the disease itself is responsible for increased risk. In a recent retrospective cohort study, patients with RA were twice as likely to experience unrecognized MI and sudden deaths compared with non-RA subjects. Also, patients with RA were less likely to have symptoms of angina and were less likely to receive coronary artery bypass graft, suggesting that CVD manifests differently in RA (79). Patients with RA may have altered lipid profiles as a result of the rheumatoid inflammatory process (80); however, the adverse lipid profiles associated with active RA have been shown to improve substantially following effective treatment of RA without the use of lipid-lowering agents (81). In the present study, we did not find altered lipid profiles in RA participants, and in contrast to previous observations of excess cardiovascular morbidity in persons with RA, the prevalence of CVD in RA participants was similar to non-RA controls. Similarly, the prevalence of traditional risk factors for CVD in subjects with RA was similar to non-RA controls, in contrast to previous studies suggesting that patients with RA may have a higher prevalence of traditional risk factors compared with subjects without RA (82–87). The results are in agreement with the findings of a recent study of the distribution of known CVD risk factors in women participating in the Nurses' Health Study, where most traditional CVD risk factors were similar between women with RA and controls. However, as expected, biomarkers of inflammation associated with CVD were generally elevated in women with RA (88). Advantages of our study include the population-based design, inclusion of both women and men, and the evaluation of novel risk factors for CVD including antioxidant levels.

Strengths of the present study include the weighted estimates that were generalizable to the US population at the time of NHANES-III. In addition, this is the first population-based study examining the prevalence of novel and traditional CVD risk factors in RA. Also, the RA case definition was based on findings on physical examination for ACR criteria for classification of RA based on a previously described method for case definition in NHANES-III (41–43).

The analyses of associations between novel and traditional CVD risk factors and RA involved multiple tests of significance. A potential limitation relates to multiple testing, because multiple comparisons are associated with an increased chance for a Type I error. However, the utility of formal adjustments for multiple comparisons in an epidemiologic context has been questioned (44–46). We therefore chose not to perform any formal alpha adjustments in the present study, but we acknowledge the need to consider with caution the statistical significance of such associations.

The definition of RA was based on objective criteria (40, 41). However, our findings may not be generalizable to younger individuals with RA because the study sample included subjects ages 60 years or older. Misclassification is possible because RA diagnosis was not confirmed by medical record review. Indeed, the use of ACR criteria that rely on the presence of signs and symptoms of disease may lead to an underascertainment of RA cases (89, 90). For instance, persons with severe RA could have been missed because they were unable to attend the MEC evaluations or chose not to participate. Similarly, participants in a period of inactive, mild, or early disease may not have fulfilled a minimum of 3 ACR criteria for RA. We excluded participants with 1 or 2 ACR criteria from the analyses to reduce this misclassification.

Seropositivity was present in 27% of this population sample, suggesting that seronegative RA may be overrepresented in this sample, or it may be that the case definition captured a less severe disease with inflammatory polyarthritis. However, a similarly low prevalence of rheumatoid factor has been described in other recent samples (91–93). Moreover, given that RA joint deformity is not part of the ACR criteria, subjects with inactive disease at the time of the examination who had joint deformity could have been misclassified as controls. In a sensitivity analysis, we excluded all controls with hand deformities and the results were unchanged.

In this large population study, the prevalence of traditional CVD risk factors in RA cases compared with controls was similar. Among novel CVD risk factors, CRP level was significantly higher, and antioxidant levels were significantly lower in RA subjects compared with non-RA subjects. Further research should evaluate whether antioxidant differences account for the observed increased incidence of CVD in persons with RA.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Dr. de Pablo 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 design. Dietrich, Karlson, de Pablo.

Acquisition of data. de Pablo.

Analysis and interpretation of data. Dietrich, Karlson, de Pablo.

Manuscript preparation. Dietrich, Karlson, de Pablo.

Statistical analysis. Dietrich, de Pablo.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

We are grateful to Dr. Matthew H. Liang for providing valuable comments on the manuscript, and Drs. Jenny Huang and Roland Bassett for providing statistical support.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
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