Objective To investigate the characteristics of body composition (BC) in gout patients and its clinical significance. Methods Consecutive gout patients were recruited between August 2017 and December 2018. Demographic information, clinical characteristics and comorbidities were collected. BC was assessed by bioelectric impedance analysis including body fat percentage (BF% ), trunk and limb BF%, appendicular skeletal muscle index. Overfat was defined by BF%≥25% for male and≥35% for female. The association between BC and serum uric acid (sUA) was evaluated by multiple linear regression. Results A total of 362 gout patients were recruited with median age 38 (30, 52) years, 96.1% (348/362) were male. Mean sUA was(551±133)μmol/L. The mean BF% was (25.8±6.4)% with 53.6%(194/362) patients overfat. Male gout patients with overfat showed more affected joints [4(2, 6) vs. 2(2, 5)], higher sUA [(576 ± 126)μmol/L vs. (523 ± 134) μmol/L], higher prevalence of dyslipidemia [70.1%(131/187) vs. 54.0%(87/161)], metabolic syndrome [60.8%(118/187) vs. 28.0%(47/161)], fatty liver [58.2%(113/187) vs. 35.1%(59/161)] and hypertension [44.4%(83/187) vs. 25.5%(41/161)] than male patients with normal fat (all P<0.05). Their BF% , trunk BF% and limb BF% were positively correlated with the numbers of affected joints, sUA, metabolic syndrome, fatty liver, and hypertension, respectively (r=0.154-0.435, all P<0.05). Multivariable linear regression suggested that BF% (β=4.29, P=0.020) and trunk BF% (β=9.11, P=0.007), but not limb BF% , were positively correlated with sUA. Conclusion Overfat is very common in gout patients. The proportion of trunk fat in male patients is positively correlated with sUA. When assessing obesity in gout patients clinically, body composition analysis should be performed simultaneously.

Objective: To investigate the characteristics of body composition (BC) in gout patients and its clinical significance. Methods: Consecutive gout patients were recruited between August 2017 and December 2018. Demographic information, clinical characteristics and comorbidities were collected. BC was assessed by bioelectric impedance analysis including body fat percentage (BF%), trunk and limb BF%, appendicular skeletal muscle index. Overfat was defined by BF% ≥25% for male and ≥35% for female. The association between BC and serum uric acid (sUA) was evaluated by multiple linear regression. Results: A total of 362 gout patients were recruited with median age 38 (30, 52) years, 96.1% (348/362) were male. Mean sUA was (551±133) μmol/L. The mean BF% was (25.8±6.4)% with 53.6%(194/362) patients overfat. Male gout patients with overfat showed more affected joints [4(2, 6) vs. 2(2, 5)], higher sUA [(576±126)μmol/L vs. (523±134) μmol/L], higher prevalence of dyslipidemia [70.1%(131/187) vs. 54.0%(87/161)], metabolic syndrome [60.8%(118/187) vs. 28.0%(47/161)], fatty liver [58.2%(113/187) vs. 35.1%(59/161)] and hypertension [44.4%(83/187) vs. 25.5%(41/161)] than male patients with normal fat (all P<0.05). Their BF%, trunk BF% and limb BF% were positively correlated with the numbers of affected joints, sUA, metabolic syndrome, fatty liver, and hypertension, respectively (r=0.154-0.435, all P<0.05). Multivariable linear regression suggested that BF% (β=4.29, P=0.020) and trunk BF% (β=9.11, P=0.007), but not limb BF%, were positively correlated with sUA. Conclusion Overfat is very common in gout patients. The proportion of trunk fat in male patients is positively correlated with sUA. When assessing obesity in gout patients clinically, body composition analysis should be performed simultaneously.

Objective:To investigate the prevalence of hypertension and its associated factors in rheumatoid arthritis (RA) patients.Methods:Consecutive Chinese patients with RA were recruited from August 2015 to September 2019 at Department of Rheumatology, Sun Yat-sen Memorial Hospital. Demo-graphic data and clinical data were collected including indicators of disease activity, functional assessment and radiographic assessment, comorbidities and previous medications. Logistic regression analysis was used to evaluate the related factors of hypertension in RA patients.Results:There were 674 RA patients recruited with 82.3%(555/674) female and mean age (50±13) years. The prevalence rate of hypertension was 32.9% (222/674), followed by dyslipidemia (9.9%, n=67), type 2 diabetes (8.8%, n=59), hyperuricemia (8.5%, n=43), fatty liver disease (8.0%, n=54), cardiovascular disease (6.2%, n=42) and chronic kidney disease (3.3%, n=22). Compared with those without hypertension, RA patients with hypertension had advanced age with longstanding disease duration, higher disease activity indicators, worse joint destruction, and higher proportions of comorbidities. Multivariate logistic regression analysis showed that comorbidities including hyperuricemia [ OR=1.977, 95% CI(1.002, 3.900)], dyslipidemia [ OR=1.903, 95% CI(1.102, 3.288)] and fatty liver disease [ OR=2.335, 95% CI(1.278, 4.265)] were risk factors of hypertension after adjustment for age and gender. Conclusion:Hyperten-sion is the most common comorbidity in RA patients which is associated with comor-bidities including hyperuricemia, dyslipidemia and fatty liver disease. Detection and management of hyperten-sion and other cardiovascular disease related comorbidities in RA patients should be emphasized.

Objective:To investigate the characteristics of functional limitation and associated factors in patients with rheumatoid arthritis (RA).Methods:Consecutive patients with RA were recruited from August 2015 to June 2019 at Department of Rheumatology, Sun Yat-Sen Memorial Hospital. Demographic and clinical characteristics including age, gender, erythrocyte sedimentation rate (ESR), visual analogue scale (VAS) of pain, clinical disease activity index (CDAI), modified total Sharp score were collected. Physical function was assessed by the Stanford health assessment questionnaire disability index (HAQ-DI).Ordered logistic regression was used to analyze the related factors of HAQ-DI.Results:A total of 643 RA patients were finally recruited including 114 males and 529 females with mean age (49.7±12.9) years. There were 399 (62.1%) patients having different degrees of functional limitation, who were classified as mild (293, 45.6%), moderate (73, 11.4%) and severe (33, 5.1%). The prevalence of functional limitation was positively correlated with age and disease activity. The most restricted activity was walking [43.5% (280/643)], followed by gripping [36.1% (232/643)], reaching [35.5% (228/643)], daily activities [33.4% (215/643)], hygiene [33.0% (212/643)], dressing and grooming [29.7% (191/643)] and arising [29.1% (187/643)], and the last eating [18.4% (118/643)]. Multivariate ordered logistic regression analysis showed that age ( OR=1.019, 95% CI 1.004-1.035),pain VAS ( OR=1.820, 95% CI 1.616-2.050), ESR ( OR=1.009, 95% CI 1.001-1.017), CDAI ( OR=1.080, 95% CI 1.059-1.102) and modified total Sharp score ( OR=1.010, 95% CI 1.004-1.015) were associated factors of functional limitation. Conclusion:The majority RA patients have functional limitation. Age, pain and active disease are independent associated factors. Therefore, target treatment and control of pain should be emphasized in RA patients.