Abstract
Objective
To characterize BMI in Chinese patients with RA vs US patients and examine its association with joint damage in Chinese patients.
Methods
Each of the 1318 patients from a real-world Chinese RA population was first stratified by gender and then individually age-matched with one American RA patient from the US National Health and Nutritional Examination Survey 1999–2018. Data on BMI, bilateral hand radiographs and risk factors at enrolment were collected but radiographs were unavailable for the American patients. Logistic regression was used to evaluate the association of BMI with radiographic joint damage (RJD) in Chinese patients.
Results
Chinese patients had a significantly lower BMI [(weighted) median 21.8 vs 29.8 kg/m2; P < 0.001] and a higher prevalence of being underweight (15.2% vs 1.1%; P < 0.05) than their American counterparts. Underweight Chinese patients (BMI <18.5) had higher modified total Sharp scores (median 17 vs 10) and joint space narrowing (JSN) subscores (median 6 vs 2) (both P < 0.05) than normal-weight patients (BMI ≥18.5–<24). After controlling for confounding, continuous BMI was cross-sectionally negatively associated with RJD [adjusted prevalence odds ratio (OR) 0.90 (95% CI 0.85, 0.96)] and JSN [adjusted prevalence OR 0.92 (95% CI 0.87, 0.96)]; being underweight vs normal weight was associated with RJD [adjusted prevalence OR 2.14 (95% CI 1.37, 3.35)] and JSN [adjusted prevalence OR 1.77 (95% CI 1.10, 2.84)].
Conclusion
Low BMI and being underweight were cross-sectionally associated with joint damage in Chinese RA patients, especially JSN, suggesting the clinical importance of identifying underweight patients and focusing on weight gain to prevent joint damage.
Keywords: rheumatoid arthritis, body mass index, underweight, joint space narrowing
Key messages.
This first comparative study shows more underweight in Chinese RA patients than US RA patients.
Chinese RA patients show an L-shaped relationship between ageing and an odds ratio of being underweight.
Being underweight is associated with a higher likelihood of joint damage in Chinese RA patients.
Introduction
RA is a chronic inflammatory disease leading to irreversible erosive joint destruction [1]. Previous studies in Western countries have demonstrated that elevated BMI is linked to RA onset and obesity affects the performance and response to therapies in RA [2–5]. Weight gain and obesity cause inflamed and dysfunctional adipocytes and infiltration of immune cells in adipose tissue [6, 7]. These abnormalities result in an increased production of adipokines and inflammatory cytokines correlated with worse disease activity, more impairments in physical function and poorer treatment response [6, 7]. Generally, adiposity harms cardiovascular health and mortality [8]. However, being overweight or obese in RA is paradoxically protective against all-cause and cardiovascular disease mortality and associated with less radiographic progression compared with normal-weight patients with RA [9–12]. In contrast, underweight individuals or those with time-varying weight loss have the highest relative mortality risk in patients with RA [13, 14].
It has been confirmed that chronic inflammation in RA can cause a hypermetabolic and catabolic state, resulting in weight loss, poor nutrition or even cachexia [15, 16]. We previously studied Chinese patients with established RA and found that they had a lower BMI and an ≈10% higher frequency of underweight patients (17.7% vs 7.8%) than Chinese controls from a metacity (Shanghai) in China [17]. Similarly, other studies from Asian countries have also reported fewer obese but more underweight patients with RA [18–20], while other studies of RA patients in Western countries have reported more obese but fewer underweight patients [14, 18, 19, 21]. These prior findings might imply a need for different weight management strategies for RA patients in China and Western countries. However, there is a lack of evidence about the direct comparison of RA patients in China and Western countries concerning body weight health conditions. Given the availability of data from a nationally representative sample in the US National Health and Nutritional Examination Survey (NHANES), we aimed to characterize BMI, BMI-defined body weight health conditions and other characteristics in Chinese RA patients relative to American RA patients from the NHANES and to evaluate the associations of BMI with RA disease characteristics, especially joint damage, in a subgroup analysis of Chinese RA patients.
Methods
Study design, data sources and study populations
A 1:1 individually matched case–case comparative study was conducted to characterize BMI and BMI-defined body weight health conditions of patients with RA between China and the USA, where cases were patients with RA. The matching is described in the Statistical analysis section.
Chinese RA patients
Chinese patients with RA were consecutively recruited from January 2011 to January 2023 at the Department of Rheumatology and Immunology, Sun Yat-Sen Memorial Hospital, China [17]. The patients with RA were diagnosed according to the 1987 ACR [22] or 2010 ACR/EULAR criteria [23]. Patients with data available on age, gender, body weight, height and conventional radiographs of bilateral hands at enrolment were included in this study. Those who overlapped with other autoimmune diseases or malignancies were excluded. The Ethics Committee of Sun Yat-sen Memorial Hospital approved this study (SYSEC-KY-KS-012 and SYSEC-KY-KS-2022–078). All patients consented to participate and signed informed consent. The study was conducted in accordance with the Declaration of Helsinki.
The US RA patients
The US patients with RA were selected from the US NHANES database 1999–2018. The NHANES has become a continuous annual survey of a national sample of ≈5000 persons representative of the non-institutional civilian resident population in the USA since 1999 [24]. The NHANES program was performed by the Centers for Disease Control and Prevention (Atlanta, GA, USA). A multistage probability sampling method with oversampling of several subgroups was used to collect data with in-person face-to-face interviews and physical examinations [24]. Participants came from diverse racial and ethnic groups, including non-Hispanic Whites, non-Hispanic Blacks, other Hispanic Americans, Mexican Americans and other racial/ethnic Americans. Data were released to the public in 2-year cycles with a 2-year sample size of ≈10 000 individuals [25]. We used data from 10 data-releasing cycles covering the period 1999–2018. Arthritis in the NHANES was classified into RA, OA and other types of arthritis. Participants with arthritis were identified if they answered ‘yes’ to the question ‘Doctor ever said you had arthritis?’ in the medical condition questionnaire. If their arthritis was classified as RA [26, 27], they were deemed patients with RA. In this study, we included American RA patients with data available on age, gender, body weight and height. Those overlapped with other autoimmune diseases, malignancies or pregnancy were excluded.
Anthropometric measures and BMI
Anthropometric measurements were collected among Chinese RA patients at enrolment and among the US RA patients at the annual NHANES since 1999. Both weight and height measurements were performed using the standardized protocol in our study and the NHANES, respectively [25, 28]. BMI was calculated as the weight (in kg) divided by height (in m2). As recommended by the Working Group on Obesity in China, body weight health condition was categorized using BMI as underweight (<18.5 kg/m2), normal weight (≥18.5–<24 kg/m2), overweight (≥24–<28 kg/m2) and obese (≥28 kg/m2) [29]. In US RA patients, according to the definition of the World Health Organization, body weight health condition was classified into underweight (BMI <18.5 kg/m2), normal weight (BMI ≥18.5–<25 kg/m2), overweight (≥25–<30 kg/m2) and obese (≥30 kg/m2) [30].
Demographic, smoking and clinical factors
Demographic, smoking and clinical data of Chinese RA patients were collected at enrolment, as we previously reported [17, 31], including gender, age, active smoking and clinical factors [RA disease duration, ESR, CRP, RF status, ACPA status, RA disease activity, physical function, comorbidities (i.e. hypertension, diabetes, cardiovascular diseases and dyslipidaemia) and previous medications]. Disease activity was assessed by the Clinical Disease Activity Index (CDAI). An HAQ disability index (HAQ-DI) score >1 indicated physical dysfunction [31, 32].
Information for US RA patients available in the NHANES and equivalent to Chinese patients was selected, such as gender, age, active smoking, race/ethnicity, CRP and comorbidities (i.e. hypertension, diabetes, cardiovascular diseases and dyslipidaemia) [26, 27].
Joint damage at enrolment
Conventional radiographs of bilateral hands (anteroposterior view) were collected at enrolment among Chinese RA patients. The radiographic damage was assessed, including the Sharp/van der Heijde modified total Sharp score (mTSS), joint space narrowing (JSN) subscore and joint erosion (JE) subscore [33]. The radiographic joint damage (RJD) was indicated as a mTSS >10 and the presence of JSN and JE were indicated with a corresponding subscore >0 [32]. However, equivalent data on joint damage were unavailable in the NHANES 1999–2018.
Statistical analysis
Chinese RA patients were initially stratified by gender and then each of them was matched with one American RA patient for age and gender to balance the heterogeneity of age and gender across Chinese and US RA patients. The pre- and post-matching standardized mean differences (SMDs) of age and gender between the groups were reported. The absolute value of post-matching SMD between the groups for each variable should be <0.1. Further sensitivity analysis was performed, in which the calendar year of enrolment was included as a matching factor.
In the Chinese RA population, the mean (s.d.) was used for normally distributed continuous variables and median [interquartile range (IQR)] was used for non-normally distributed continuous variables, while categorical variables were expressed as number (%). Sampling weights were used in accordance with the NHANES analytic guidelines to account for its complex multistage sampling designs [34]. The weights are equal to two-tenths of the weights for 1999–2002 or one-tenth of the weights for 2003–2018 [34]. A weighted mean and its 95% confidence interval (CI) as well as a weighted median and its IQR were calculated for a continuous variable, while an unweighted number, its relevant weighted percentage and the 95% CI of the weighted percentage were calculated for a categorical variable. A weighted t-test or Mann–Whitney U test was used to compare differences in BMI and weighted χ2 tests or Fisher’s exact tests were used to compare differences of BMI categories between Chinese and American RA patients, while the weights in Chinese RA patients were set to 1. Restricted cubic spline (RCS) regression analysis was carried out to examine the non-linear relationship between the prevalence of being underweight and age in Chinese RA patients and their American RA counterparts (weighted), respectively.
A subgroup analysis of Chinese RA patients was conducted to evaluate the cross-sectional association of the body weight health condition with joint damage, as data on the exposure, covariates and outcome were collected at enrolment. One-way analysis of variance was used to compare differences in a covariate among BMI categories in Chinese RA patients for normally distributed variables, while the Kruskal–Wallis test was used for non-normally distributed variables. The χ2 test or Fisher’s exact test was used to compare differences between groups for categorical variables. Further, the polynomial contrast procedure test for the trend was used for continuous variables and the Cochran–Armitage test for trend was used for categorical data according to BMI categories. Univariate and multivariate logistic regression analyses were performed to evaluate the association of BMI categories and joint damage in Chinese RA patients. The potential risk factors for joint damage, including demographic, smoking and clinical factors, or those variables with a P-value <0.1 in univariate analysis were included in the multivariate analysis. All data were analysed using SPSS version 25.0 (IBM, Armonk, NY, USA) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). P-values ≤0.05 from the two-sided test were considered statistically significant.
Results
Demographic and clinical characteristics of Chinese RA patients and matched US RA patients
A total of 1318 RA patients were included in this study after 271 patients were excluded from 1589 Chinese RA patients in the parent study because of overlap with other autoimmune diseases, having malignancies or a lack of BMI data (Fig. 1). The mean age of the Chinese patients with RA was 51.9 years (s.d. 12.7) and 1047 (79.4%) were female. The median disease duration was 48 months (IQR 18–118). There were 1075 (81.6%) patients with active disease (CDAI >2.8) and 306 (23.2%) treatment-naïve patients who had not received glucocorticoid or DMARD therapy for 6 months before enrolment (Table 1).
Figure 1.
Flow chart to include Chinese RA patients and matched US RA patients
Table 1.
Characteristics of Chinese and US RA patients before and after matching
| Characteristics | Before matching |
After matching |
||||||
|---|---|---|---|---|---|---|---|---|
| Chinese RA (n = 1318) | US RA (n = 2305) | P-value | SMD | Chinese RA (n = 1318) | US RA (n = 1318) | P-value | SMD | |
| Female, n (%)a | 1047 (79.4) | 1346 (57.5) [54.6, 60.3] | <0.001 | 0.39 | 1047 (79.4) | 1047 (79.4) [74.6, 82.2] | 1.000 | 0 |
| Age, yearsa | 51.9 (s.d. 12.7) | 56.4 (55.6, 57.2) | <0.001 | 0.37 | 51.9 (s.d. 12.7) | 52.3 (51.8, 53.6) | 0.471 | 0.03 |
| RA disease duration, months | 183 (115–248) | – | – | – | 183 (115, 248) | – | – | – |
| Active smoking, n (%) | 206 (15.6) | 1241 (57.3) [54.2, 60.4] | <0.001 | 0.89 | 206 (15.6) | 658 (54.9) [50.8,59.0] | 0.76 | |
| BMI, kg/m2 | 21.8 (19.6–24.1) | 29.4 (25.0, 34.4) | <0.001 | 1.00 | 21.8 (19.6, 24.1) | 29.8 (25.1, 35.6) | <0.001 | 1.41 |
| BMI categories, n (%) | <0.001 | 0.65 | <0.001 | 0.69 | ||||
| Underweight | 200 (15.2) | 28 (1.1) [0.7, 1.7] | 200 (15.2) | 16 (1.1) [0.6, 2.0] | ||||
| Normal weight | 780 (59.2) | 505 (23.9) [21.4, 26.7] | 780 (59.2) | 247 (23.0) [19.4, 27.0] | ||||
| Overweight | 278 (21.1) | 685 (28.6) [26.3, 30.9] | 278 (21.1) | 361 (27.0) [24.0, 30.2] | ||||
| Obese | 60 (4.6) | 1087 (46.4) [43.5,49.3] | 60 (4.6) | 694 (49.0) [45.3, 52.6] | ||||
| Race/Ethnicity, n (%) | ||||||||
| Asian | 1318 (100) | – | – | 1318 (100) | – | – | ||
| Non-Hispanic White | – | 873 (63.7) [60.2, 67.2] | – | – | – | 419 (58.3) [53.8, 62.7] | – | – |
| Non-Hispanic Black | – | 710 (18.0) [15.7, 20.6] | – | – | – | 436 (20.4) [17.4, 23.7] | – | – |
| Mexican American | – | 398 (7.0) [5.7, 8.6] | – | – | – | 238 (7.9) [6.3, 9.7] | – | – |
| Other Hispanic | – | 196 (5.3) [4.1, 6.9] | – | – | – | 140 (6.7) [5.2, 8.7] | – | – |
| Other race | – | 128 (5.9) [4.5, 7.7] | – | – | – | 85 (6.8) [4.8,9.4] | – | – |
| CRP, mg/lb | 5.3 (3.3–21.0) | 3.2 (1.2, 7.8) | <0.001 | 0.17 | 5.3 (3.3–21.0) | 3.9 (1.5, 9.0) | <0.001 | 0.07 |
| Comorbidities, n (%) | ||||||||
| Hypertension | 388 (29.4) | 1506 (59.4) [56.1, 62.6] | <0.001 | 0.70 | 388 (29.4) | 813 (56.9) [53.5, 61.3] | <0.001 | 0.58 |
| Diabetes | 146 (11.1) | 698 (23.0) [21.0, 25.2] | <0.001 | 0.49 | 146 (11.1) | 381 (21.7) [19.1, 24.5] | <0.001 | 0.51 |
| Cardiovascular diseases | 133 (10.1) | 554 (21.7) [19.6, 24.0] | <0.001 | 0.38 | 133 (10.1) | 237 (17.7) [15.1, 24.5] | <0.001 | 0.23 |
| Dyslipidaemia) | 368 (27.9) | 1784 (77.5) [74.9, 79.9] | <0.001 | 1.20 | 368 (27.9) | 1003 (75.3) [71.6, 78.7] | <0.001 | 1.67 |
Data for Chinese RA patients are shown as n (%), mean (s.d.) and median (IQR), as appropriate. Data for US RA patients are shown as unweighted n (weighted %) [95% CI], weighted mean (95% CI) and weighted median (IQR), as appropriate. Significant values in bold.
Used for matching.
CRP was only available in 1334 US RA patients before matching and 926 patients after matching.
Among 2951 US RA patients from the NHANES, 646 were excluded using the same criteria as the Chinese patients (Fig. 1). A total of 1318 US RA patients were age and gender matched to Chinese RA patients individually at a ratio of 1:1 (Fig. 1), with 1049 (79.4%) females (post-matching SMD = 0; Table 1), a weighted mean age of 52.3 years (95% CI 51.8, 53.6) (post-matching SMD = 0.03) and 58.3% non-Hispanic Whites, 20.4% non-Hispanic Blacks, 7.9% Mexican Americans, 6.7% other Hispanics and 6.8% other racial/ethnic Americans (Table 1).
Chinese RA patients had a statistically significantly higher level of CRP but a lower prevalence of hypertension, diabetes, cardiovascular diseases and dyslipidaemia than their US counterparts (all P < 0.05; Table 1).
Lower BMI and more underweight in Chinese RA patients compared with the US RA patients
The distribution of BMI was right-skewed in Chinese and American RA patients (Fig. 2A). Compared with US RA patients, Chinese RA patients had a statistically significantly lower BMI [(weighted) median 21.8 kg/m2 (range 13.7–34.7) vs 29.8 kg/m2 (range 15.2–67.8); P < 0.001; Fig. 2A and B]. There were significant differences in the proportions of patients in four BMI categories between Chinese RA patients and US RA patients, as more Chinese RA patients were underweight and had normal weight but fewer were obese than their American counterparts (15.2% vs 1.1% underweight, 59.2% vs 23.0% normal weight, 4.6% vs 49.0% obese and 21.1% vs 27.0% overweight; P < 0.001; Fig. 2C). After the stratification by gender, both male and female Chinese RA patients showed a lower BMI [male: (weighted) median 21.9 kg/m2vs 29.2 kg/m2; female: (weighted) median 21.7 kg/m2vs 29.9 kg/m2] and a higher proportion being underweight than their US counterparts (male: 19.2% vs 1.3%; female: 14.1% vs 1.2%; both P < 0.001; Figs 2B and 2C).
Figure 2.
The characteristics of BMI between Chinese RA patients and matched US RA patients. ***P < 0.001
In our sensitivity analysis, the additional inclusion of the enrolment calendar year for matching led to 600 Chinese RA patients who were 1:1 individually matched to 600 US RA patients. Results were similar (Supplementary Fig. S1A and B, available at Rheumatology Advances in Practice online).
L-shaped relationship between age and the prevalence odds ratio (OR) of being underweight in Chinese and American RA patients
In Chinese RA patients, BMI was statistically significantly associated with age (Ptrend < 0.001; Fig. 2D) in all patients and by gender (Ptrend for male = 0.02, Ptrend for female <0.001; Figs 2E and 2F): the association was positive among all patients and females ≤40–49 years of age and males ≤30–39 years of age but disappeared among those older than the corresponding age category. Male and female Chinese RA patients showed similar distribution of BMI with similar BMI values (median 21.9 kg/m2vs 21.7 kg/m2; P = 0.58; Fig. 3A). An L-shaped relationship between age and the prevalence OR of being underweight was statistically significant in Chinese RA patients by gender, in which the OR decreased dramatically among those <30 years of age, decreased gradually between 30 and 40 years of age and then remained flat among those >40 years of age (both Pnon-linear for male and female < 0.05; Fig. 3B), along with higher ORs in males than females ≤40 years of age (Pinteraction = 0.013).
Figure 3.
The distributions of BMI and the association of age with the prevalence OR of being underweight in Chinese RA patients and matched US RA patients by gender
In the matched US RA patients, BMI was statistically significantly associated with age in all patients (Ptrend = 0.005; Fig. 2D) and females (Ptrend for male = 0.68, Ptrend for female = 0.03; Fig. 2E and F): the association was positive in those ≤40–49 years of age but negative among those >49 years (Ptrend < 0.001; Fig. 2D). Male and female US patients showed different distributions of BMI, in which females had a higher weighted median BMI than males (29.9 kg/m2vs 29.2 kg/m2; P < 0.001; Fig. 3C). However, non-linear associations of age with the OR of being underweight were not observed by gender in US patients, which might be because of fewer underweight individuals (Pnon-linear > 0.05, Pinteraction for gender = 0.59; Fig. 3D).
More joint damage in underweight Chinese RA patients
There were 200 (15.2%) underweight Chinese RA patients. Compared with normal-weight patients, underweight patients were younger, had more active smokers and had higher mTSS and JSN subscores (Table 2) (all P < 0.05). Both overweight and obese patients had a higher prevalence of hypertension (all P < 0.05) than those having normal weight. In addition, overweight patients had a higher prevalence of diabetes (P < 0.05) than normal-weight patients.
Table 2.
The clinical characteristics of Chinese RA patients by body weight health condition
| Characteristics | Underweight (n = 200) | Normal weight (n = 780) | Overweight (n = 278) | Obese (n = 60) | P-value | P trend |
|---|---|---|---|---|---|---|
| Female, n (%) | 148 (74.0) | 631 (80.9) | 217 (78.1) | 51 (85.0) | 0.11 | 0.20 |
| Age, years, mean (s.d.) | 47.3 (15.8)a | 52.0 (12.2) | 54.7 (10.7)a | 53.7 (10.9) | <0.001 | <0.001 |
| Disease duration, months, median (IQR) | 46 (18–104) | 51 (15–119) | 49 (20–119) | 62 (21–140) | 0.49 | 0.35 |
| Active smoking, n (%) | 41 (20.5) | 119 (15.3) | 42 (15.1) | 4 (6.7) | 0.047 | 0.02 |
| Positive RF, n (%) | 145 (72.5) | 542 (69.7) | 181 (65.6) | 40 (67.8) | 0.42 | 0.42 |
| Positive ACPA, n (%) | 143 (71.5) | 566 (72.8) | 182 (65.9) | 40 (67.8) | 0.18 | 0.18 |
| Core disease activity indicators, median (IQR) | ||||||
| 28TJC | 3 (1–8) | 3 (1–8) | 3 (0–8) | 2 (1–8) | 0.37 | 0.78 |
| 28SJC | 2 (0–5) | 2 (0–5) | 2 (0–5) | 1 (0–3) | 0.26 | 0.89 |
| PtGA | 4 (2–6) | 4 (1–6) | 3 (1–6) | 3 (1–6) | 0.59 | 0.10 |
| PrGA | 4 (2–5) | 3 (1–5) | 3 (1–5) | 2 (1–5) | 0.38 | 0.22 |
| PainVAS | 3 (2–4) | 2 (2–4) | 3 (1–5) | 2 (1–5) | 0.91 | 0.81 |
| ESR, mm/h | 33 (15–67) | 33 (16–63) | 29 (18–54) | 32 (20–53) | 0.64 | 0.08 |
| CRP, mg/l | 7.2 (3.3–24.1) | 5.3 (3.3–21.2) | 4.7 (3.3–20.0) | 5.1(3.3–11.9) | 0.41 | 0.13 |
| CDAI | 13 (6–24) | 12 (5–22) | 13 (4–24) | 10 (4–24) | 0.39 | 0.53 |
| Active RA | 167 (83.5) | 645 (82.7) | 216 (77.7) | 47 (78.3) | 0.23 | 0.23 |
| Functional indicators | ||||||
| HAQ-DI, median (IQR) | 0.3 (0–1.1) | 0.3 (0–0.9) | 0.3 (0–0.9) | 0.1 (0–1.0) | 0.61 | 0.34 |
| Physical dysfunction, n (%) | 51 (25.5) | 164 (21.0) | 54 (19.4) | 14 (23.3) | 0.42 | 0.42 |
| Radiographic assessments | ||||||
| mTSS, median (IQR) | 17 (3–47)a | 10 (3–28) | 9 (3–26) | 11 (4–41) | 0.03 | 0.02 |
| RJD (mTSS >10), n (%) | 120 (60.0) | 368 (47.2) | 122 (43.8) | 31 (51.5) | 0.03 | 0.04 |
| JSN subscore, median (IQR) | 6 (0–23)a | 2 (0–11) | 2 (0–9) | 2 (0–19) | 0.005 | 0.003 |
| JSN subscore >0, n (%) | 150 (74.8) | 507 (65.0) | 166 (59.6) | 35 (57.5) | 0.04 | 0.005 |
| JE subscore, median (IQR) | 9 (3–26) | 6 (1–17) | 6 (2–15) | 9 (3–19) | 0.50 | 0.07 |
| JE subscore >0, n (%) | 166 (83.0) | 626 (80.3) | 221 (79.5) | 55 (90.9) | 0.42 | 0.86 |
| Comorbidities, n (%) | ||||||
| Hypertension | 37 (18.5) | 205 (26.3) | 116 (41.7)a | 30 (50.0)a | <0.001 | <0.001 |
| Diabetes | 14 (7.0) | 74 (9.5) | 50 (18.0)a | 8 (13.3) | <0.001 | <0.001 |
| Cardiovascular diseases | 18 (9.0) | 78 (10.0) | 29 (10.4) | 8 (13.3) | 0.80 | 0.38 |
| Dyslipidaemia | 53 (29.4) | 242 (35.6) | 107 (42.5) | 22 (41.5) | 0.04 | 0.005 |
| Previous medications, n (%) | ||||||
| Treatment naïve | 34 (17.0) | 190 (24.4) | 69 (24.8) | 13 (21.7) | 0.15 | 0.18 |
| Glucocorticoids | 111 (55.5) | 387 (49.6) | 125 (45.0) | 28 (46.7) | 0.15 | 0.03 |
| csDMARD | 146 (73.0) | 526 (67.4) | 188 (67.6) | 42 (70.0) | 0.49 | 0.44 |
| bDMARD/tsDMARDs | 22 (11.0) | 71 (9.1) | 35 (2.7) | 6 (10.0) | 0.41 | 0.54 |
Compared with normal-weight patients, P < 0.05. P < 0.05 was defined as statistical significance and values are in bold.
28TJC: 28-joint tender joint count; 28SJC: 28-joint swollen joint count; PtGA: patient global assessment of disease activity; PrGA: provider global assessment of disease activity; PainVAS: pain visual analogue scale; csDMARD: conventional synthetic DMARD; bDMARD: biologic DMARD; tsDMARD: targeted synthetic DMARD.
The prevalence of joint damage was 48.9%, 65.3% and 81.0% for RJD, JSN and JE, respectively, in the Chinese patients. From underweight to obese BMI categories, the prevalence of RJD (Ptrend = 0.036) and JSN (Ptrend = 0.005) was statistically significantly decreasing separately, but not JE (Ptrend = 0.86). However, there were no differences in the prevalence of RJD or JSN in underweight, overweight or obese Chinese RA patients in pairwise comparison with normal-weight patients (all adjusted P > 0.05; Table 2).
Logistical regression analysis of the association of BMI and joint damage in Chinese RA patients
Fig. 4 shows a negative association of the continuous BMI with RJD and JSN, but not JE, without controlling for potential confounding. Being underweight vs normal weight was statistically significantly associated with prevalent RJD [unadjusted prevalence OR 1.68 (95% CI 1.14, 2.47)] and JSN [unadjusted prevalence OR 1.60 (95% CI 1.04, 2.46)], but not JE. After adjusting for gender, age, active smoking, disease duration, RF status, ACPA status, ESR, CRP, CDAI, HAQ-DI, comorbidities and previous treatment, the negative association of the continuous BMI with RJD and JSN remained similar [adjusted prevalence OR 0.90 (95% CI 0.85, 0.96) for RJD and 0.92 (0.87–0.96) for JSN], but not JE [0.97 (0.92, 1.03)]. After adjusting for potential confounders, the magnitude of the association of being underweight vs normal weight with joint damage was increased for RJD [OR 2.15 (95% CI 1.37, 3.35)] and remained similar for JSN [OR 1.77 (95% CI 1.10, 2.84)]. However, there was no association of being overweight or obese with the prevalence odds of RJD, JSN or JE (all P > 0.05).
Figure 4.
Logistic regression analysis of the cross-sectional association of continuous and categorized BMI and joint damage at enrolment in Chinese RA patients. (A) RJD, (B) JSN and (C) JE. RJD indicated as mTSS >10; JSN indicated as JSN subscore >0; JE indicated as JE subscore >0. csDMARD: conventional synthetic DMARD; bDMARD: biologic DMARD; tsDMARD: targeted synthetic DMARD
Discussion
This case–case comparative analysis revealed an 11-fold higher underweight prevalence in Chinese RA patients than in US RA patients for the first time. BMI was negatively cross-sectionally associated with joint damage in Chinese patients. With normal weight as the reference BMI category, the adjusted prevalent odds of joint damage were 2.1-fold higher for radiographic joint damage and 1.8-fold higher for JSN but not JE, given being underweight in Chinese patients, indicating that being underweight was cross-sectionally associated with joint damage in RA, especially JSN. Our findings might imply the necessity of clinical practice and care specific for Chinese RA patients to reduce joint damage, such as nutritional interventions for underweight RA patients.
Previous studies in Western countries showed more obese (12.9–58.0%) but fewer underweight (1.1–3.3%) RA patients [9, 13, 14, 21, 29]. However, our study was the first comparative study to show that Chinese RA patients had a lower BMI and extremely higher underweight prevalence than their US counterparts, suggesting the clinical importance of identifying and treating underweight Chinese RA patients.
Data from 24 535 US RA patients participating in the National Data Bank for Rheumatic Diseases showed that their BMI increased to its maximum at 50 years of age for both men and women [9], which was different from our finding, probably because our American patients were selected through matching with Chinese counterparts. However, there was no large-scale study to illustrate the BMI trend with aging among Asian RA patients. Our study first showed an association of BMI with age in Chinese RA patients and an L-shaped relationship between age and the underweight prevalence OR. This undernutrition status, especially among young patients, implied a specific need for nutritional support in underweight Chinese RA patients.
In our study, although there were no differences in RA disease activity and inflammatory markers between underweight and normal-weight RA patients, our findings of the association of lower BMI and being underweight relative to normal weight with greater odds of radiographic joint damage were consistent with previous studies in both early and established RA patients [20, 32]. Biological mechanisms underlying the association are not fully understood and need to be further investigated.
Taken together, our findings provide basic but important evidence. The evidence suggests that weight management strategies in clinical care for patients with RA might be different between China and the USA. The 2022 ACR Guideline for Exercise, Rehabilitation, Diet, and Additional Integrative Interventions for RA [35] recommends maintaining a healthy body weight for individuals with RA in order to optimize long-term RA and general health outcomes. However, the guideline focuses on identifying overweight or obese patients with RA and highlights the need for weight loss for these patients but does not provide any recommendations for underweight RA patients. Therefore, our findings support the need to increase clinicians’ awareness of the limitations of this guideline to be applied to Chinese RA patients and to develop appropriate weight management strategies and a guideline for them.
There were several limitations in this study. Only gender and age were used to match Chinese RA patients with their American counterparts because of the limited available data on factors common to both patient populations. However, gender and age were common matching factors. Thus our findings provided fundamental evidence to improve clinical care, healthcare policy and guidelines for Chinese RA patients. The findings from our subgroup analysis of Chinese RA patients were cross-sectional and thus could not establish a temporal order between BMI and joint damage. However, we generated a hypothesized causal relationship of being underweight and joint damage to be further investigated in the longitudinal study. Owing to a lack of available detailed RA-related clinical data and radiographs in US RA patients, we could not validate our findings of this association in US RA patients. Our evidence supports the need for an external validation study. Although TNF-α and IL-6 inhibitor treatment could promote weight gain in RA patients, prospective studies investigating the influence of weight gain with various approaches, including nutrition intervention, on joint damage in underweight Chinese RA patients could generate strong evidence to improve clinical practice to treat these patients.
In conclusion, this first comparative study revealed a higher prevalence of being underweight in Chinese RA patients than in US RA patients. Continuous low BMI and being underweight were cross-sectionally associated with joint damage in Chinese RA patients separately, especially JSN. Our findings suggest the clinical importance of identifying underweight RA patients and focusing on their weight gain to prevent joint damage in Chinese RA patients. More studies are needed to investigate the causal role of being underweight in joint damage.
Supplementary Material
Contributor Information
Jie Pan, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Tao Wu, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Yao-Wei Zou, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Qi-Hua Li, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Zhi-Ming Ouyang, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Jian-Da Ma, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China; Department of Rheumatology and Immunology, Shenshan Medical Center, Memorial Hospital of Sun Yat-Sen University, Shanwei, P.R. China.
Pei-Wen Jia, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Hu-Wei Zheng, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Jian-Zi Lin, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Ye Lu, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Ying Yang, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Le-Feng Chen, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Kui-Min Yang, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Jun Dai, Department of Public Health, College of Health Sciences, Des Moines University, West Des Moines, IA, USA.
Lie Dai, Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Supplementary material
Supplementary material is available at Rheumatology Advances in Practice online.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author upon appropriate request.
Authors’ contributions
J.P. and T.W. participated in conceiving and designing the study, reading and analyzing documents, performing statistical analysis, drafting and revising the manuscript. Y.-W.Z., Q.-H.L., Z.-M.O. and J.-D.M. conceived and participated in its design, analyzed documents. P.-W.J., H.-W.Z., Y.L., Y.Y., K.-M.Y. participated in data collection. J.-Z.L. and L.-F.C. carried out the radiographic assessment. J.D. and L.D. conceived and participated in its design, read and analyzed documents, and edited the manuscript.
Funding
This research was funded by the Chinese National Key Technology R&D Program, Ministry of Science and Technology (2022YFC2504600 and 2022YFC2504601), National Natural Science Foundation of China (82171780, 81971527 and 82101892) and Guangdong Basic and Applied Basic Research Foundation (2022A1515010524 and 2023A1515030253).
Disclosure statement: The authors have declared no conflicts of interest.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author upon appropriate request.