A large proportion of this group of women with SLE was obese. Using the most common body composition measure, BMI, almost 30% were obese; using a more sensitive measure, DEXA, half met the criterion for obesity. Substantial portions of women were misclassified by the anthropometric measures. The majority of misclassifications were due to women who were obese by the DEXA standard but did not meet the anthropometric criterion for obesity; relatively few women were found to be obese by anthropometric methods and not obese by DEXA. Women who were misclassified as not obese by anthropometric measures exhibited different patterns of fat distribution than those who were correctly classified, and tended to have a lower proportion of their fat accumulation in the trunk and a greater proportion in their arms and/or legs.
Our analyses suggest new cut-points for defining obesity among women with SLE: BMI ≥ 26.8 kg/m2
, waist circumference ≥ 84.75 cm, and a waist-hip ratio ≥ 0.80. In each case, the revised cut-points are substantially lower than those traditionally used. For example, the traditional BMI cut-point for obesity is ≥ 30 kg/m2
; the revised cut-point is closer to the traditional cut-point used to define overweight (25.0 kg/m2
). The inaccuracy of BMI in identifying high adiposity in mid-range BMI values has been noted previously. For example, a meta-analysis yielded a pooled sensitivity of BMI to identify excess body fat of 0.50, and a pooled specificity of 0.90, with considerable heterogeneity among studies(36
). The BMI cut-point we identified is similar to cut-points derived in other studies(37
). For example, in a study using NHANES data, a BMI of 25.5 was identified as the best cut-point to identify high body fat (>35% for women). In our study and those cited above, results suggest that lean mass was relatively lower, and fat mass relatively higher than might be expected by BMI. Whether this is a general population trend or relevant specifically to SLE is not known. Likewise, whether disease factors (e.g., inflammation), treatment (e.g., glucocorticoid use), or behavior (e.g., low physical activity), or the combination of these, have a differential impact on the body composition, including infiltration of muscle with fat, of women with SLE is not known.
Sensitivity and specificity of BMI and WC to detect obesity using the revised cut-points was high. The waist-hip ratio, however, did not perform well, even when using an adjusted cut-point, so this measure should be used with caution as a proxy for estimating obesity in women with SLE. Others have also found that WHR did not correspond with body fatness as well as BMI and WC(39
There is a strong relationship between obesity, defined by BMI and waist circumference, and cardiovascular morbidity(9
). However, the actual risk conferred by high BMI or waist circumference is that of high adiposity. An examination of NHANES data found that among more than 6,000 women who had “normal” BMI’s, almost one-third had body fat greater than 35%(40
). Among this group of “normal weight obese” women, metabolic syndrome, dyslipidemia, and cardiovascular disease were each elevated. Because of the elevated rate of cardiovascular disease in SLE(41
), this phenomenon might be expected to be even more prevalent. We found elevated cardiovascular risk scores among women meeting both the traditional and revised anthropometric criteria of obesity. Although the absolute 10-year risk of a cardiovascular event was relatively low for all groups, the risk of both obese groups (~5.5% for the two BMI obese groups) was about 80% higher than that of the non-obese group (~3%). Annual monitoring of BMI is recommended as a quality indicator to screen for cardiovascular risk(42
), but a lower BMI cut-point to define risk conferred by high adiposity may be appropriate for women with SLE to permit earlier and/or better identification of individuals at risk. In addition, based on findings from rheumatoid arthritis, in which women who had higher levels of appendicular fat had greater risk of disability, these new cut points may also be more useful in predicting development or progression of disability than the traditional ones.
This study included a relatively small number of women with SLE (n = 145), so larger studies may yield different results, as may studies that include subjects who are different from this cohort in racial/ethnic composition or disease severity. In addition, prospective studies are clearly needed to identify the value of the suggested revised cutpoints in terms of identifying both cardiovascular or disability risk. It is also possible that other analyses of body composition, such as studies of fat infiltration into muscle, may yield information regarding alterations of body composition among women with SLE that confer additional risk for poor health or functional outcomes(12
In conclusion, we suggest consideration of revised criteria to define obesity in women with SLE when using anthropometric methods. These revised criteria provide greater sensitivity to body fat and greater correspondence with DEXA-defined obesity. Using these cut-points, both BMI and waist circumference provided robust proxies of DEXA-defined obesity. Waist-hip ratio was less useful, and based on these data, would not be recommended as a proxy measure for obesity in women with SLE. Our results suggest that cardiovascular risk of women who meet the revised obesity criterion is equivalent to that of women who meet traditional anthropometric obesity criteria, suggesting that the traditional criteria may under-estimate obesity-related cardiovascular risk. The utility of the revised cut-points compared to the traditional cut-points in identifying risk of cardiovascular disease or disability remains to be examined in prospective studies.