Which is the best cutoff of body mass index to identify obesity in female patients with rheumatoid arthritis? A study using dual energy X -ray absorptiometry body composition

Guimarães, Maria Fernanda Brandão Resende; Pinto, Manuel R.; Raid, Renata G. Santos Couto; Andrade, Marcus Vinícius Melo de; Kakehasi, Adriana María

doi:10.1016/j.rbre.2016.02.008

Cited by 9 publications

(14 citation statements)

References 36 publications

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“…1) . Twenty-seven studies (29 articles) assessed BMI 44,[46][47][48][49][50][51][52][53][54][58][59][60][61][64][65][66][67][68][69][70][71][72][73][74][75][76][77][78] , and 15 (19 articles) reported on waist measurements such as WC [43][44][45][46][47][49][50][51][52][53][57][58][59][60]62,63 , WHR [43][44][45][46][47][49][50]…”

Section: Resultsmentioning

confidence: 99%

“…Fourteen studies were community-based 44,46,51,58,[62][63][64][66][67][68]70,73,75,76,78 , fourteen were primary care-or hospitalbased 45,47,49,50,[52][53][54]57,[59][60][61]69,72,74,77 , two were community-and hospital-based 43,48,55,56 , one study was based in the army 65 and one did not report its setting 71 . Six studies included patients with various diseases or physical or cognitive disabilities 50,[52][53][54]59,61,66,74 . Four studies stratified analyses by age groups 43,44,46,55,56,58...…”

Section: Resultsmentioning

confidence: 99%

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The performance of anthropometric tools to determine obesity: a systematic review and meta-analysis

Sommer

Teufer

Szelag

et al. 2020

Sci Rep

102

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the aim of this systematic review was to assess the performance of anthropometric tools to determine obesity in the general population (CRD42018086888). Our review included 32 studies. To detect obesity with body mass index (BMI), the meta-analyses rendered a sensitivity of 51.4% (95% CI 38.5-64.2%) and a specificity of 95.4% (95% CI 90.7-97.8%) in women, and 49.6% (95% CI 34.8-64.5%) and 97.3% (95% CI 92.1-99.1%), respectively, in men. For waist circumference (WC), the summary estimates for the sensitivity were 62.4% (95% CI 49.2-73.9%) and 88.1% for the specificity (95% CI 77.0-94.2%) in men, and 57.0% (95% CI 32.2-79.0%) and 94.8% (95% CI 85.8-98.2%), respectively, in women. The data were insufficient to pool the results for waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) but were similar to BMI and WC. In conclusion, BMI and WC have serious limitations for use as obesity screening tools in clinical practice despite their widespread use. No evidence supports that WHR and WHtR are more suitable than BMI or WC to assess body fat. However, due to the lack of more accurate and feasible alternatives, BMI and WC might still have a role as initial tools for assessing individuals for excess adiposity until new evidence emerges. Obesity is widely recognised as a pandemic public health problem. According to the World Health Organization (WHO), in 2016 more than 650 million adults worldwide were obese 1. These numbers have almost tripled since 1975 2. Obesity increases the risk for many chronic diseases, such as diabetes mellitus, cardiovascular diseases and cancers 3 , and is possibly associated with mental health disorders 4. Associations have been shown to be strongest between obesity and the incidence of diabetes mellitus, particularly in women (risk ratio [RR] 12.41, 95% confidence interval [CI] 9.03-17.06). Primary care is considered one of the main settings for the prevention, screening and management of obesity 5. Individual studies indicate that patients are more likely to lose weight when they receive recommendations for lifestyle changes from their primary care physicians 6. Because it can be difficult for physicians to accurately determine obesity solely through visually inspecting their patients 7 , they need a reliable, efficient screening tool in order to ensure that those who need management and treatment receive it. WHO conceptualises obesity as "abnormal or excessive fat accumulation that may impair health" 1. It is most commonly assessed using body mass index (BMI), a simple and quick anthropometric tool that has a low cost. Adults with a BMI greater than or equal to 30 are classified as being obese 1 (Table 1). However, several researchers and professional associations 8-14 consider the use of BMI as the primary clinical index of obesity insufficient. They have called for a new definition that fully accounts for the complexity of the disease relating to the quantity, distribution and secretory function of adipose tissue. A substantial body of evidence has shown that obesity (BMI ≥ 30) is ass...

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

The performance of anthropometric tools to determine obesity: a systematic review and meta-analysis

Sommer

Teufer

Szelag

et al. 2020

Sci Rep

102

View full text Add to dashboard Cite

show abstract

“…To evaluate body fat, we use bioimpedance equipment. For future studies that need to perform the same stratification we suggest the use of Dual X-ray absorptiometry (DXA) that has been referenced as reference standard (35).…”

Section: Discussionmentioning

confidence: 99%

Polycystic ovary syndrome associated with increased adiposity interferes with serum levels of TNF-alpha and IL-6 differently from leptin and adiponectin

Cardoso

Ribeiro

Dutra

et al. 2020

Archives of Endocrinology and Metabolism

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Objective: The aim of this study was to investigate polycystic ovary syndrome (PCOS) and to explore the relationship between body fat percentage and metabolic markers. Subjects and methods: Sedentary women were assigned to PCOS (N = 60) and CONTROL (N = 60) groups. Each group was subdivided into three subgroups according to body fat percentage (22-27%, 27-32% and 32-37%). The protocol consisted of assessments of glucose, insulin, androgens, follicle stimulating hormone (FSH), luteinizing hormone (LH), 17-hydroxyprogesterone (17-OHP), leptin, adiponectin, tumor necrosis factor (TNF-α) and interleukin-6 (IL-6). Results: The PCOS subgroups showed higher concentrations of androgens, LH and 17-OHP. Leptin showed direct relationship with increased body fat percentage, whereas adiponectin showed the inverse effect. However, both were unaffected by PCOS. TNF-α and IL-6 were higher in PCOS women and showed a direct relationship with increased body fat percentage. Glucose showed direct relationship with body fat percentage, whereas insulin presented higher values in PCOS women and direct relationship with increased body fat percentage. Conclusions: Our findings indicate that PCOS and body fat percentage directly influence concentrations of insulin, TNF-α and IL-6, whereas leptin and adiponectin are influenced only by the increase in body fat percentage in these women.

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“…However, the use of BMI as a measure of obesity may be confounded by variations in body composition (fat vs. lean mass), compromising the accuracy of the method in this patient population. Our group and other researchers have therefore proposed alternative cut-off values for obesity in RA patients [38,39]. Another strategy, adopted in the present study, is to employ WC in addition to BMI as an indicator of obesity.…”

Section: Discussionmentioning

confidence: 99%

High prevalence of obesity in rheumatoid arthritis patients: association with disease activity, hypertension, dyslipidemia and diabetes, a multi-center study

et al. 2019

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Introduction: Rheumatoid arthritis (RA) is a well-documented independent risk factor for cardiovascular disease. Obesity may provide an additional link between inflammation and accelerated atherosclerosis in RA. Objective: To evaluate the association between obesity and disease parameters and cardiovascular risk factors in RA patients. Method: Cross-sectional study of a cohort of RA patients from three Brazilian teaching hospitals. Information on demographics, clinical parameters and the presence of cardiovascular risk factors was collected. Blood pressure, weight, height and waist circumference (WC) were measured during the first consultation. Laboratory data were retrieved from medical records. Obesity was defined according to the NCEP/ATPIII and IDF guidelines. The prevalence of obesity was determined cross-sectionally. Disease activity was evaluated using the DAS28 system (remission < 2.6; low 2.6-3.1; moderate 3.2-5.0; high > 5.1). Results: The sample consisted of 791 RA patients aged 54.7 ± 12.0 years, of whom 86.9% were women and 59.9% were Caucasian. The mean disease duration was 12.8 ± 8.9 years. Three quarters were rheumatoid factor-positive, the mean body mass index (BMI) was 27.1 ± 4.9, and the mean WC was 93.5 ± 12.5 cm. The observed risk factors included dyslipidemia (34.3%), type-2 diabetes (15%), hypertension (49.2%) and family history of premature cardiovascular disease (16.5%). BMIdefined obesity was highly prevalent (26.9%) and associated with age, hypertension and dyslipidemia. Increased WC was associated with diabetes, hypertension, dyslipidemia and disease activity. Conclusion: Obesity was highly prevalent in RA patients and associated with disease activity.

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Which is the best cutoff of body mass index to identify obesity in female patients with rheumatoid arthritis? A study using dual energy X -ray absorptiometry body composition

Abstract: A large percentage of patients were obese. The traditional cutoff points used for obesity were not suitable for our sample. For this female population with established RA, BMI cutoff point of 25kg/m and WC cutoff point of 86cm were the most appropriate to detect obesity.

Cited by 9 publications

References 36 publications

The performance of anthropometric tools to determine obesity: a systematic review and meta-analysis

The performance of anthropometric tools to determine obesity: a systematic review and meta-analysis

Polycystic ovary syndrome associated with increased adiposity interferes with serum levels of TNF-alpha and IL-6 differently from leptin and adiponectin

High prevalence of obesity in rheumatoid arthritis patients: association with disease activity, hypertension, dyslipidemia and diabetes, a multi-center study

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