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Abstract
Objectives To evaluate the association between long-term dietary quality, measured by the 2010 Alternative Healthy Eating Index, and risk of rheumatoid arthritis (RA) in women.
Methods We prospectively followed 76 597 women in the Nurses' Health Study aged 30–55 years and 93 392 women in the Nurses' Health Study II aged 25–42 years at baseline and free from RA or other connective tissue diseases. The lifestyle, environmental exposure and anthropometric information were collected at baseline and updated biennially. Cumulative follow-up rates were more than 90% for both cohorts. The primary outcome was RA alone with two subtypes of the disease: seropositive and seronegative RA.
Results During 3 678 104 person-years, 1007 RA cases were confirmed. In the multivariable-adjusted model, long-term adherence to healthy eating patterns was marginally associated with reduced RA risk. To assess potential effect modification by age at diagnosis, we stratified by age. Among women aged ≤55 years, better quality diet was associated with lower RA risk (HRQ4 vs Q1: 0.67; 95% CI 0.51 to 0.88; p trend: 0.002), but no significant association was found for women aged >55 years (p interaction: 0.005). When stratifying by serostatus, the inverse association among those aged ≤55 years was strongest for seropositive RA (HRQ4 vs Q1: 0.60; 95% CI 0.42 to 0.86; p trend: 0.003).
Conclusions A healthier diet was associated with a reduced risk of RA occurring at 55 years of age or younger, particularly seropositive RA.
- Rheumatoid Arthritis
- Epidemiology
- Ant-CCP
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Introduction
Rheumatoid arthritis (RA) is a common autoimmune disease, affecting approximately 1.3 million Americans including 2.5 times as many women as men.1 Although the aetiology of RA is not completely understood, it is widely recognised that both genetic and environmental exposures including lifestyle and dietary risk factors contribute to the development of RA. Our group and others have reported that high intake of alcohol, fish, olive oil and cooked vegetables confer a protective effect against the development of RA,2–6 whereas red meat and sugar-sweetened soda intake may increase the risk of RA.7 ,8 However, not all studies confirmed such associations.9–11 One explanation for the inconsistent findings may be that individual food/nutrients only confer modest beneficial effects, so that any protective effects would not be observed unless groups of dietary factors are consumed together. Dietary pattern analysis in relation to disease risk addresses these limitations as it integrates the complexity of overall diet.12
The 2010 Alternative Healthy Eating Index (AHEI-2010) is a dietary quality score based on the recent Dietary Guidelines for Americans composed of 11 foods and nutrients that have been consistently associated with risk of chronic diseases.13 Among 11 foods/nutrients included in the dietary index, fruits, vegetables, whole grains, nuts, long-chain (n-3) fat (% of total energy), polyunsaturated fat (% of total energy) and moderate alcohol consumption were considered as healthy items, while sugar-sweetened beverages (including fruit juice), red/processed meat, trans fat (% of total energy) and sodium intake were deemed as unhealthy components. Higher scores of AHEI-2010 have been strongly associated with reduced risk for major chronic diseases including cardiovascular diseases (CVD), type 2 diabetes (T2D) and certain types of cancer.14–19 No study has investigated the associations between overall dietary quality and risk of autoimmune diseases, such as RA. Our primary aim was to investigate associations between AHEI-2010 score and risk of RA in two large prospective cohort studies of women: Nurses' Health Study (NHS) and NHSII.
Previous studies on CVD have showed that the influence of established risk factors such as smoking, body mass index (BMI), hypertension, diabetes, hyperlipidaemia diminished with advancing age,20–22 which is likely due to blunted response to autonomic nervous system stimuli23 ,24 that is triggered by these modifiable factors. Similar phenomenon was observed in our previous analysis that demonstrated a significant trend towards increased risk of RA diagnosed at age ≤55 years among overweight women and women with obesity, but not in women aged >55 years.25 Moreover, literature suggest that RA occurred at younger and older age are aetiologically different in many respects.26 ,27 Thus, our secondary aim was also to examine the diet quality and RA associations in both younger age (≤55 years) and older age (>55 years).
Methods
Study population
In 1976, NHS was initiated and included 121 700 female registered nurses aged 30–55 years. In 1989, 116 671 female registered nurses aged 25–42 years enrolled in NHSII. Participants from both prospective cohorts provided information regarding lifestyle behaviours, medical history and diseases through self-administered questionnaires at entry and updated every 2 years. The response rate was maintained over 90% for every 2-year period in both cohorts.29 ,30 The baselines for NHS and NHSII in the current study were 1984 and 1991 when a comprehensive Food Frequency Questionnaire (FFQ) was introduced in each cohort. A total of 76 597 and 93 392 participants from each cohort were included in the final analysis after excluding those who did not answer the FFQ and those who had RA or other connective tissue diseases at baseline. We censored all women who reported psoriasis, psoriatic arthritis or other connective tissue diseases at the self-reported date, unless the diagnosis was subsequently confirmed as RA. Women lost to follow-up were censored at their last response to questionnaires. The institutional review board at Partners Healthcare approved the study protocol.
Assessment of dietary factors and AHEI-2010
We used a 133-item semi-quantitative FFQ to collect dietary data approximately every 4 years from 1984 to 2010 in the NHS and 1991–2011 in NHSII.28 About 84% of NHS participants and 90% of NHSII participants answered FFQ at respective baseline. Participants who returned FFQ with more than 70 missing items, total energy intake <500 kcal/day or >3500 kcal/day were excluded from the analysis.8 Validation studies from two parallel cohorts showed high correlation coefficients between FFQ and multiple dietary records for the dietary factors.28 ,31 We calculated nutrient intakes by multiplying the frequency of intake for each food by its nutrient content and summing nutrient contributions across all food items, using previously validated methods.32
As a scoring system, the AHEI-2010 integrates the dietary data to evaluate the overall dietary quality. The rationale of food items selection and score criteria of AHEI-2010 has been discussed elsewhere.13 Women with moderate alcohol intake defined as 0.5–1.5 drinks/day received a maximum score of 10 but non-drinkers or heavy drinkers were assigned lower scores, reflecting the U-shaped association of alcohol consumption with chronic diseases.13 All AHEI-2010 components are scored from 0 (worst) to 10 (best), and the total AHEI-2010 score can range from 0 to 110 (non-adherence to perfect adherence). A higher AHEI-2010 score indicates better diet quality. In order to investigate the potential cumulative effect of a long-term diet, we calculated cumulative average AHEI-2010 from all of the preceding measures over the study period.8 ,33 The missing cycles of FFQ were excluded from the estimates of cumulative average dietary measures.
Identification of RA
The identification of RA cases consisted of two steps. In the first step, participants who self-reported a physician diagnosis of RA received the connective tissue disease (CTD) screening questionnaire (CSQ) through mail. For those with positive screening for RA or other CTDs based on CSQ, medical records were requested.34 In the second step, two rheumatologists independently reviewed medical records according to the 1987 American College of Rheumatology classification.35 The serologic phenotype of RA was determined from medical records by positive rheumatoid factors (available since baseline) or cyclic citrullinated peptide antibodies (available since the early 2000s).34 ,36
Assessment of time-varying covariates
Information regarding participants' demographic, reproductive, clinical and behavioural factors has been collected with the biennial follow-up questionnaires. BMI was calculated as weight in kilograms divided by height in metres and was categorised into five levels: <18.49, 18.5–22.9, 23–24.9, 25–30 and ≥30 kg/m2. Four categories were created for smoking status: never, past, current 1–14 cigarettes/day, current ≥15 cigarettes/day. Recreational physical activity levels were categorised as: 0–2.9, 3–8.9, 9–17.9, 18–26.9 and ≥27 metabolic equivalents/week.37 Parity and breast feeding status were jointly defined as: nulliparous, parous/no breast feeding, parous/1–12 months breast feeding, parous/>12 months breast feeding. Age at menarche was classified into three categories: <12, 12, >12 years and we defined the hormone use status as: premenopausal, postmenopausal with never use, current use and past use. Census tract median family income and total energy intake were ranked using quartiles and quintiles, respectively.
Statistical analysis
Baseline characteristics were expressed as mean (SD) or median for continuous variables and percentage was used for categorical variables according to quartiles of AHEI-2010 score. In order to assess age-specific effects and potential effect modifiers, we pooled the data from both cohorts to include a wide range of age groups. To control for possible cohort effects given secular trends in food supply according to calendar year, an indicator variable for cohorts was used in model stratification. For the primary analysis, time-varying Cox proportional hazards models were employed to assess the association between AHEI-2010 and risk of RA. All cases RA, both seropositive and seronegative, were separate outcomes in the analysis. Cumulative averaged AHEI-2010 score was included in the model as a time-varying exposure for which the values were updated during the follow-up. The proportional hazard assumption was evaluated by including an interaction term between continuous AHEI-2010 and logarithm of person-time and was met in all analyses. The main model adjusted for potential risk factors of RA that are also associated with AHEI including age, smoking, age at menarche, parity/breast feeding, hormone use and total energy intake. We additionally adjusted for BMI to assess its potential mediation effects in a separate model. The median value of each quartile was used as a continuous variable to calculate the p value for trend.
For the secondary aim, we stratified the participants by age rounded to integer (age ≤55 and age >55 years) based on our prespecified hypotheses.8 ,25 Women were followed-up from baseline to age 55 years, and from age 56 years to the end of cohorts, respectively. The interaction was tested by comparing two β coefficients for the continuous AHEI-2010 score from respective multivariable models in a χ2 test. We also conducted an exploratory analysis to evaluate the effect of each individual component score of AHEI-2010 in relation to RA risk.
In addition, we performed sensitivity analyses to examine the robustness of our findings. First, to maximally control for residual confounding effects, we further included variables that varied by AHEI but are less associated with RA in the NHS including census tract median family income, physical activity, multivitamin use and self-reported T2D. Second, after we identified that red meat and alcohol were two individual components of AHEI-2010 that showed particular beneficial effects against RA risk for women aged 55 years or younger, we repeated the analysis using AHEI-2010 without either of these two components, to assess whether the observed associations were driven by single food item. Missing covariate data were carried forward one questionnaire cycle. All statistical tests were two-sided with significant level of 0.05 and performed using SAS V.9.3 (SAS Institute, Cary, North Carolina, USA).
Results
A total of 1007 RA cases (624 seropositive, 383 seronegative) were identified during 3 678 104 person-years of follow-up. The mean follow-up time was 21.6 years. The ranges of AHEI-2010 score were 15.6–100.1 and 13.7–95.8 at baseline for NHS and NHSII, respectively. In both cohorts, higher baseline AHEI-2010 score was positively associated with desirable lifestyle and socioeconomic status including family median income, physical activity, alcohol consumption and multivitamin use (table 1). Participants with higher AHEI-2010 score also tended to have lower BMI and total energy intake, and were less likely to be parous and current smokers. BMI and AHEI were significantly negatively correlated but the Spearman's correlation coefficient was small (−0.08, p<0.001) (data not shown).
Age-standardised baseline characteristics of participants from Nurses' Health Study (NHS) (N=76 597 in 1984) and study participants from NHSII (N=93 392 in 1991) according to AHEI-2010 quartile*
In multivariable-adjusted model, women in the highest quartile of AHEI-2010 had 15% reduced risk (HRQ4 vs Q1=0.85, 95% CI 0.70 to 1.02; p trend: 0.08) compared with the women in the lowest quartile (table 2). The association was slightly attenuated after additional adjustment for BMI (HRQ4 vs Q1=0.87, 95% CI 0.73 to 1.05; p trend: 0.16). Results for both serologic subtypes of RA suggested an inverse association, but neither was statistically significant. In analyses restricted to women aged 55 years or younger (444 RA cases), a significant inverse dose-response relationship was found between AHEI-2010 and RA incidence (table 3). Women in the top quartile of AHEI-2010 had 33% (HRQ4 vs Q1=0.67, 95% CI 0.51 to 0.88; p trend: 0.002) lower risk of RA compared with those in the lowest quartile and the observed association remained statistically significant after additional BMI adjustment (HRQ4 vs Q1=0.71, 95% CI 0.54 to 0.94; p trend: 0.009). Further stratification analysis by two serologic subtypes of RA showed significant inverse associations for seropositive RA. No significant associations were detected for women aged over 55 years (p for age by AHEI-2010 interaction: 0.005).
Pooled HRs (95% CI) for incident RA according to cumulative AHEI-2010 quartile in Nurses' Health Study (NHS, 1984–2012) and NHSII (1991–2013)
Pooled HRs (95% CI) for incident RA according to cumulative AHEI-2010 quartile in Nurses' Health Study (NHS, 1984–2012) and NHSII (1991–2013) stratified by age before or after 55 years
As an exploratory analysis, we further examined the association between each AHEI component and RA risk among women aged 55 years or younger (table 4). A higher score of alcohol (moderate intake) or red meat consumption (lower intake) was significantly associated with a reduced RA risk independent of current BMI and other covariates, while no significant associations were observed for other AHEI components.
Pooled HRs (95% CI) for incident RA according to cumulative AHEI-2010 individual component score quartile for women aged 55 years or younger in Nurses' Health Study (NHS, 1984–2012) and NHSII (1991–2013)*
In sensitivity analyses that additionally adjusted for census tract median family income, physical activity, multivitamin use and patient's history of diabetes, the results were unchanged. Both alcohol-excluded and red meat-excluded AHEI-2010 yielded comparable estimates to the primary stratified analysis, so it is unlikely that these items alone were responsible for the findings.
Discussion
Data from these two large cohort studies of women suggest that long-term adherence to higher dietary quality guidelines was associated with reduced RA risk, in particular for seropositive RA with onset at age 55 years or earlier. Among the individual components of AHEI-2010 score, moderate alcohol consumption and lower red meat intake were found to be most associated with decreased early-onset RA risk, while the associations of other components with RA risk were not strong enough to reach statistical significance. These results indicate that an overall healthy diet quality may be more beneficial for RA risk reduction than individual foods and nutrients, particularly for early-onset seropositive RA.
The observed inverse associations between AHEI-2010 score and RA risk are generally expected as most of the score's components are biologically relevant in reducing RA risk. Owing to the rich contents of dietary antioxidants, fruits and vegetables have long been suggested as healthy foods that may be effective for RA prevention. In our previous study evaluating association of Alternate Mediterranean Diet Score (AMED) with RA risk, we did not observe a significant association of AMED score as well as the fruit and vegetable consumption components with overall RA risk, but did not investigate whether this was associated with earlier onset RA.33 AMED is the simple sum of nine dichotomised components at median, not including detailed amount of actual dietary intakes. We previously found another AHEI-2010 component, sugar-sweetened beverages, to be linked to increased risk of later onset RA (diagnosed after age 55 years) using different comparison groups from the current study.8 While the EPIC-Norfolk study found an elevated risk of RA among people with higher red meat consumption,7 our group assessed the red meat-RA association in NHS 9 years ago and did not confirm such associations.38 However, our current findings do not necessarily contradict our previous report. In the current analysis, we combined data from two cohorts with more incident RA cases and longer follow-up of both younger and older women than the previous analyses, allowing us to detect potential differing effects of diet quality on RA occurred in younger and older age.
The polyunsaturated, particularly long-chain n-3 fatty acids, have been found to be effective in both reducing RA risk and improving symptoms in patients with RA through the mechanism of promoting the anti-inflammatory eicosanoid synthesis.39 ,40 Additionally, we have also demonstrated a U-shaped association between alcohol consumption and RA risk, in which women with moderate alcohol consumption had the lowest risk of RA.2 A recently published nested case-control studies reported that high sodium consumption was associated with increased risk of RA particularly among smokers,41 ,42 and experimental studies have suggested that sodium may be able to promote the development of autoimmune diseases through the induction of pathogenic T helper 17 in a process mediated by serum glucocorticoid kinase 1.43 ,44 Finally, legumes, nuts and whole grains, which are abundant in dietary fibre and antioxidants may have potential to mitigate the RA risk.33
In the current study, we have found that the protective effects of higher diet quality on RA risk are strongest among women aged ≤55 years. This result is similar to our previous finding that the positive association between obesity and RA is also restricted among women with RA diagnosed at younger age. This may imply different risk factors for earlier and later onset RA. It is proposed that later onset RA may be different from earlier onset RA in terms of genetic predisposition and immune dysfunction, and hormonal changes with menopause can be a source of RA activation in older female patients.45
The strengths of our study include the use of two large cohort studies with long-term follow-up, dietary pattern analysis, repeated assessments of diet and potential confounders and high rates of follow-up. There are several limitations in our study. First, residual confounding by other unmeasured or unknown factors might still exist, and better diet quality could be a marker for healthy lifestyle. However, because we have carefully adjusted for major lifestyle factors, it is unlikely that the residual confounding completely explain the observed inverse associations. Second, the AHEI-2010 is a hypothesis-driven dietary index based on observed associations between single dietary components and the risk of major diseases,13 which was not specifically derived for RA. The AHEI-2010 did not incorporate all dietary items that may have beneficial effects for lowering RA risk. Thus, it is not clear that AHEI-2010 is the optimal dietary index for RA prevention. Third, the pooled analysis may generate spurious results when the distribution of exposure variable is different in each study (Simpson’s paradox).46 ,47 However, NHS and NHSII have the similar research designs, so it is unlikely that our findings were severely biased by Simpson’s paradox. Fourth, since the dietary information was collected every 4 years, we were unable to capture the variation of diet intake within this interval. However, the use of cumulative average dietary intake largely reduced the impact of day-to-day variation and could better reflect the long-term intake. Fifth, the majority of RA cases in our cohorts were diagnosed from age 45 to 65 years, we were unable to have enough RA cases to repeat the analyses among more extreme age groups, such as age<45 years or >65 years. Lastly, the dietary quality within these cohorts of mostly white, well-educated healthcare professionals may not be representative of the dietary quality in the USA and other countries. However, it is unlikely that the underlying biological mechanisms differ substantially by race. The observed associations of AHEI with other chronic diseases in NHS cohorts are very similar to other studies around the world.48
Conclusions
In summary, the results from this study indicate that greater long-term adherence to a healthy dietary pattern may reduce RA risk in women, particularly seropositive RA diagnosis at age 55 years or younger. Further studies are warranted to replicate our findings.
References
Supplementary materials
Lay summary
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Footnotes
Handling editor Tore K Kvien
Contributors YH and BL designed the study, analyse the data and wrote the first draft. SM contributed to the data analysis. BL, EWK, KHC, JAS and FBH were involved in data collection. 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 published. YH and BL had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Funding This study was supported by the National Institutes of Health under Award Number AR061362, AR049880, AR052403, AR047782, AR059073, AR066953, AR069688, AR066109 and CA186107, CA176726, CA49449, CA67262. Dr Sparks was also supported by the Rheumatology Research Foundation Scientific Development Award. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Competing interests None declared.
Ethics approval Partners Health Care, Inc.
Provenance and peer review Not commissioned; externally peer reviewed.