OBJECTIVE: To investigate how overall and abdominal adiposity, measured by waist circumference (WC), body mass index (BMI), and sum of skinfolds (sigmaSK), affect plasma C-reactive protein levels (CRP) in elderly women. METHODS: Study sample consisted of 387 women older than 60 years (mean age 68.9; standard deviation 5.9 years). BMI, WC, sigmaSK, and CRP levels were all measured. One-way ANOVA was performed to detect differences in study variables among the CRP levels investigated. Logistic regression analysis was used to determine the influence of body fat measurements on CRP levels. The significance level was set at p < 0.05. RESULTS: The analysis of variance showed that mean WC was lower in women with normal CRP levels, as compared to those with high CRP levels. Logistic regression analysis examined the influence of BMI, WC, and sigmaSK quartiles on CRP levels, yielding the following results: only WC was predictive of elevated CRP levels, its highest quartile (cut-off point of 94.0 cm) showing levels nearly two times higher than its lowest quartile (odds ratio = 2.23; 95% confidence interval = 1.92-4.18; p = 0.012). CONCLUSION: The results of this study indicate that abdominal adiposity is a strong predictor of elevated CRP levels.
OBJECTIVE: To investigate how overall and abdominal adiposity, measured by waist circumference (WC), body mass index (BMI), and sum of skinfolds (sigmaSK), affect plasma C-reactive protein levels (CRP) in elderly women. METHODS: Study sample consisted of 387 women older than 60 years (mean age 68.9; standard deviation 5.9 years). BMI, WC, sigmaSK, and CRP levels were all measured. One-way ANOVA was performed to detect differences in study variables among the CRP levels investigated. Logistic regression analysis was used to determine the influence of body fat measurements on CRP levels. The significance level was set at p < 0.05. RESULTS: The analysis of variance showed that mean WC was lower in women with normal CRP levels, as compared to those with high CRP levels. Logistic regression analysis examined the influence of BMI, WC, and sigmaSK quartiles on CRP levels, yielding the following results: only WC was predictive of elevated CRP levels, its highest quartile (cut-off point of 94.0 cm) showing levels nearly two times higher than its lowest quartile (odds ratio = 2.23; 95% confidence interval = 1.92-4.18; p = 0.012). CONCLUSION: The results of this study indicate that abdominal adiposity is a strong predictor of elevated CRP levels.