Abstracts
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.
Adiposity; adipose tissue; abdominal fat; C-reactive protein; risk factors
OBJETIVO: Examinar como a adiposidade global e a adiposidade abdominal, expressas pela circunferência da cintura (CC), pelo índice de massa corporal (IMC) e pelo somatório de dobras cutâneas (sigmaDC), influenciam os níveis de proteína C-reativa (PCR) em mulheres idosas. MÉTODOS: A amostra foi composta por 387 mulheres idosas, com idade superior a 60 anos (média, 68,9; desvio padrão, 5,9 anos). Foram avaliados o IMC, a CC, o sigmaDC, e os níveis de PCR. Foi utilizada a análise estatística ANOVA one-way para verificar as diferenças nas variáveis entre as categorias investigadas. Para avaliar a influência das medidas de adiposidade nos níveis de PCR foi utilizada a regressão logística. O nível de significância adotado foi de p < 0,05. RESULTADOS: A análise de variância demonstrou que o valor médio da CC foi menor na categoria normal de PCR, quando comparada aos níveis elevados de PCR. A regressão logística analisou a influência dos quartis do IMC, da CC e do sigmaDC nos níveis de PCR, em que apenas a CC foi preditora de níveis elevados de PCR, tendo o quartil extremo superior (ponto de corte de 94,0 cm) apresentado níveis quase duas vezes maiores que o quartil extremo inferior (risco estimado = 2,23; intervalo de confiança de 95% = 1,92-4,18; p = 0,012). CONCLUSÃO: Os resultados do presente estudo apontam que a adiposidade abdominal é um forte preditor de níveis elevados de PCR.
Adiposidade; tecido adiposo; gordura abdominal; tecido adiposo abdominal; proteína C-reativa; fatores de risco
ORIGINAL ARTICLE
Influence of overall and abdominal adiposity on C-reactive protein levels in elderly women
Jeffer Eidi Sasaki; Maressa Priscila Krause; Mirnaluci P. R. Gama; Tatiane Hallage; Cosme Franklin Buzzachera; Maria Gisele dos Santos; Sergio Gregorio da Silva
Universidade Federal do Paraná e Faculdade Evangélica do Paraná Curitiba, PR Brazil
Mailing address Mailing address: Jeffer Eidi Sasaki Rua Antônio José de Castro 606 38800-000 - São Gotardo, MG - Brazil E-mail: jeffersasaki@gmail.com
SUMMARY
OBJECTIVE: To investigate how overall and abdominal adiposity, measured by waist circumference (WC), body mass index (BMI), and sum of skinfolds (SSK), 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, SSK, 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 SSK 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.
Key words: Adiposity; risk factors; atherosclerosis; women.
Introduction
Cardiovascular diseases have been a constant cause for concern of modern civilization, and they are the leading cause of death in the Western world and in the Brazilian population1,2. Most cardiovascular disorders result from atherosclerosis, a condition that may be influenced by risk factors such as obesity, smoking, diabetes, hypertension, and sedentariness3,4.
The pathogenesis of atherosclerosis involves a chronic, persistent inflammatory process of the arterial wall, thereby activating cell proliferation, forming an atheroma and, ultimately, the fibroatheroma3,5,6.
The development of atherosclerosis is asymptomatic and increases with age. Chronic atherosclerosis is a slow, progressive condition, but there are also acute cases. Clinical diagnosis depends on the progression of the atherosclerotic plaque, which, in turn, may be affected by both aging and factors that predispose to thrombosis, as well as genetic background and environmental factors6.
Persistent inflammation of the arterial wall in the atherosclerotic process tends to elevate plasma C-reactive protein (CRP) levels, an acute-phase protein that increases in response to inflammation and infection7. For this reason, CRP measurement may be used as a diagnostic tool for predicting cardiovascular risks8, provided it is performed in the absence of other inflammations and infections.
High plasma CRP levels are an independent risk factor for cardiovascular and coronary artery diseases9,10. Hypertension and diabetes may also be related to increased CRP levels9. Nevertheless, body adiposity seems to be the risk factor most related to these changes11-16.
Excess (body) fat, particularly visceral fat, is an indicator of metabolic disorders, such as hypertriglyceridemia, high level of low-density lipoprotein cholesterol (LDL-cholesterol), low level of high-density lipoprotein cholesterol (HDL-cholesterol), and greater insulin resistance and glucose intolerance, all of which may potentiate atherosclerosis.
The relationship between abdominal adiposity and CRP levels increases when body fat distribution is measured by waist circumference (WC)17,18. Waist and hip circumferences have shown correlations of 0.62 and 0.65, respectively, with CRP levels adjusted for age, while body mass index (BMI) has shown lesser association (r = 0,14)19. Therefore, CRP appears to be a method that is easy to use and reproduce, both in clinical practice and epidemiological studies. The aim of this study is to determine how overall adiposity and abdominal adiposity, measured by BMI, total sum of skinfolds (SSK), and waist circumference (WC), affect CRP levels in elderly women.
Methods
This was a cross-sectional, observational, descriptive study. Data were collected between April and July, 2006.
Sample population - In order to select a stratified sample, the following steps were taken: 1) Registering of community groups in Curitiba, state of Paraná, a joint effort with institutions focused on recreational activities for the population of the respective geographic area. 2) Mapping of all groups registered with the eight districts of the municipality. 3) Simple random selection of the groups that would be invited to participate in the study, per district. 4) Visit to the groups to explain study procedures and invite voluntary participation not only of the subjects but also of their family members and close friends.
After sample selection, as described, a timeframe for data collection was developed. Study sample included 387 women (mean age 68.9; standard deviation 5.9) who were 60 years or older at the time data were collected.
After being fully informed of the purpose of the study, as well as its procedures, benefits and potential risks, each subject signed an informed consent for voluntary participation in the study. The study protocol was approved by the Ethics Committee of the Setor de Ciências Biológicas of the Universidade Federal do Paraná, in accordance with the guidelines set forth in the Helsinki Declaration and also with Resolution No 196/96 of the Conselho Nacional de Saúde (National Health Board) for research involving human subjects.
Instruments and procedures - To avoid any influence of circadian variations, all measurements were performed at the same time of the day (8:00 to 10:00).In addition, subjects were instructed to refrain from vigorous physical activity on the preceding day and not to eat for two hours prior to the tests. Measurements were performed at the Physical Education Department - Physiology Laboratory of the Research Center Research Unit for Exercise and Sports of the Universidade Federal do Paraná.
Study variables - Anthropometric variables were taken as described by Lohman et al.20. Body height (in centimeters) was measured with subjects standing barefoot, feet together, and wearing as little clothing as possible. Also, patients were instructed to hold their breath and keep their head at 90 degrees, according to the Frankfurt plane, with heels, pelvic girdle, shoulder girdle, and occipital region against a wall-mounted stadiometer (SANNY, STANDARD model, accurate to 0.1 cm). Body mass (in kilograms) was measured with subjects standing barefoot and wearing as little clothing as possible. Body weight should be evenly distributed between both legs while standing on the weighing scale (2096 PP TOLEDO, accurate to 0.1 kg). Body mass index was calculated from the formula weight in kilograms divided by height in meters squared. Waist circumference (in centimeters) was measured midway between the iliac crest and the lowest rib, using a nonstretch measuring tape accurate to 0.1 cm.
Skinfolds were measured to the nearest 0.05 mm using a Lange skinfold caliper at the following anatomical sites: triceps, abdomen, supra-iliac, mid-thigh, and mid-calf, all on the right side of the body. Body fat was estimated according to the Jackson and Pollocks equation21.
To prevent inter-rater variability, all anthropometric variables (BMI, height, WC, and skinfolds), in all subjects, were taken by the same previously trained rater.
C-reactive protein levels were determined by a particle-enhanced turbidimetric method using the COBAS MIRA PLUS spectrophotometer (Roche Diagnostics), with calibrator and control serum supplied by Biosystem (Bayer®).
Confounding variables The presence of diseases was based on self-report through the following question: "Have you been diagnosed by your doctor as having (disease)? Thus, this variable was coded as dichotomous (yes/no).
Statistical analysis - The Kolmogorov-Smirnov normality test was applied, indicating that variables had a parametric distribution. Measures of central tendency and variability were used to determine descriptive values (mean and standard deviation), as well as absolute and relative frequencies. One-way ANOVA was used to detect differences between independent variables in the CRP concentration ranges of < 1.0 mg/dL and > 1.0 mg/dL.
Logistic regression analysis, adjusted for confounding variables, was used to check the relationship between the independent variables and CRP levels, which were treated as dichotomous variables (0 = CRP < 1.0 mg/dL and 1 = CRP > 1.0 mg/dL). Our results indicate odds ratio and 95% confidence interval; the significance level was set at less than 0.05.
Confounding variables Self-reported heart disease, hypertension, rheumatoid arthritis, diabetes, cancer, and tendinitis were included in the model as dichotomous variables, except for age, which was included as continuous variable. The other independent variables were treated as categorical and divided in quartiles, and the first quartile served as reference.
Data analysis was performed using Statistical Package for the Social Sciences (SPSS 13.0 for Windows).
Results
Table 1 presents means and frequencies according to CRP levels. The results demonstrate that the majority of population is within normal ranges (54.1%).
Table 2 shows the frequencies of self-reported diseases according to CRP levels. Hypertension was the most common disease, striking nearly half of the sample. However, less than 20% of the subjects reported heart disease.
Table 3 shows descriptive values for age and body fat, according to CRP levels. Subjects with values < 1.0 mg/L are within normal ranges, while subject with values > 1.0 mg/L are at higher cardiovascular risk.
Mean WC values were lower in subjects with normal CRP levels. However, no significant differences were found in other measures of body fat between the CRP levels investigated.
The results of the logistic regression analysis are shown in Table 4. Only the highest quartile of waist circumference was found to be associated with increased CRP levels (> 1.0 mg/l), as compared to the lowest quartile; therefore, the risk of having CRP levels above the normal range (odds ratio 2.23) is twice as high in subjects with WC greater than 94.0 cm. Age, self-reported diseases, BMI, and SSF were not predictive of CRP levels.
Discussion
Obesity, which has been described as a secondary cardiovascular risk factor, is usually related to metabolic changes, hypertension, type-2 diabetes, and dyslipidemias22. These abnormalities contribute to the development of atherosclerosis6,23,24. In addition to its relationship with these factors, obesity is directly related to CRP levels25.
Our results corroborate these findings, although only abdominal fat has been associated with increased CRP levels, regardless of the confounding variables, whereas BMI and SSK have shown no significant association. Nevertheless, the relationship between BMI and CRP levels has been demonstrated in epidemiological studies 11,13.
Body fat distribution based on WC shows a more accurate relationship with elevated CRP levels in overweight subjects than other measurements of overall adiposity, such as BMI or SSF17,19,26. However, waist-to-hip ratio (WHR), another method for assessing abdominal adiposity, seems to predict mortality causes, in addition to being associated with metabolic changes related to excess body fat in Brazilian elderly women22,27. These findings demonstrate that excess abdominal fat may affect general health in elderly women.
In a study correlating WC with atherosclerosis progression, subjects with waist circumference greater than 93 cm had increased carotid artery intima-media thickness (p = 0.035), as well as higher plaque size (p = 0.013)17. In another study on the risks associated with abdominal fat, a significant correlation was found between WC and CRP levels (0.37; p < 0.0001)26. In the present study, subjects with WC equal to or greater than 94.0 cm were twice as likely to have elevated CRP levels (odds ratio 2.23; 95% CI: 1.92-4.18) than subjects with WC less than 80.0 cm.
According to Ridker28, CRP levels < 1, between 1 and 3, and > 3 mg/L are associated with low, moderate, and high cardiac risks, respectively. The highest quartile of waist circumference (> 94.0 cm), as demonstrated by regression analysis, has moderate cardiac risk. In this sample, however, 17.8% of these subjects were classified as having high cardiac risk (CRP > 3 mg/L; n = 69) (Table 1).
These reference values indicate that most elderly women in this study seem to be healthy, despite reporting several diseases; the diseases reported, however, failed to influence the analysis. Still, women with the largest WC were found to have the highest cardiovascular risk.
The metabolic disorders that usually come with this type of adiposity may explain the correlation between abdominal fat and CRP levels17,29. The primary concern regarding overweight subjects with high CRP levels is related with the development of atherosclerosis, since the low-level, persistent, chronic inflammatory process of the arterial wall is described as the main cause of endothelial dysfunction and insulin resistance6,25.
C-reactive protein levels have shown to be independent predictors for mortality from coronary artery disease in patients with type-2 diabetes, and are positively associated with overall and cardiovascular mortality30,31.
Today, obesity is highly prevalent in most countries, regardless of age, and this condition may cause a number of health problems, as stated previously. This may increase public health costs, in addition to making the elderly less functional and more vulnerable to other diseases, thereby triggering other organic disorders. Therefore, controlling CRP levels in subjects with high abdominal fat may be effective to lower atherogenic and cardiovascular risks.
Limitations
The study sample consisted of elderly women living near the city of Curitiba, state of Paraná, who attended community groups. Thus, it did not reach subjects with a higher level of dependence, who usually remain in their homes. Abdominal fat was based solely on WC. Confounding variables, except for age, were determined by the self-report method, which, despite being widely used, may under- or overestimate the results. Moreover, CRP levels could have been measured using a high-sensitivity assay (hs-CRP); however, the method used in this study has been described in several studies assessing cardiovascular risk.
To perform a binary logistic regression analysis, the dependent variable must be defined as dichotomous. Therefore, the CRP value of 1.0 mg/dL was used as the cut-off point, lower values being defined as normal and greater values, as increased risk. We suggest, therefore, that further studies be conducted using other indicators of abdominal obesity, methods more sensitive to determine CRP levels, and other cut-off points for different risk levels, to improve our understanding of the influence of body fat on CRP values.
Conclusions
It was concluded that, in this population of elderly women, abdominal fat was predictive of abnormal CRP levels, regardless of the self-reported diseases. However, other indicators of overall adiposity, such as BMI and SSF, had no influence on CRP levels. This finding shows that women with greater abdominal fat are at higher cardiovascular risk.
Potential Conflict of Interest
No potential conflict of interest relevant to this article was reported.
Sources of Funding
There were no external funding sources for this study.
Study Association
This study is not associated with any graduation program.
References
Manuscript received July 12, 2006; revised manuscript received March 26, 2007; accepted April 19, 2007
- 1. Ross R. The pathogenesis of atherosclerosis. In: Braunwald E. (ed.). Heart disease. A Textbook of cardiovascular medicine. 4th ed. Philadelphia (PA): W. B. Saunders Company; 1992. p. 1106-23.
- 2. Camarano AA. O envelhecimento da população brasileira: uma contribuição demográfica. São Paulo: Instituto de Pesquisa e Estatística Aplicada IPEA; 2002. p. 1-97.
- 3. Boyle EM, Lille ST, Allaire E, Clowes AW, Verrier ED. Atherosclerosis. Ann Thorac Surg. 1997; 64: 47-56.
- 4. Affiune A. Envelhecimento cardiovascular. In: Freitas EV, Py L, Neri AL, Cançado F, Gorzoni ML, Rocha M. (eds.). Tratado de geriatria e gerontologia. Rio de Janeiro: Guanabara Koogan; 2002.
- 5. Bhattacharrya G, Libby P. In: Lilly LS. Atherosclerosis: pathophysiology of heart disease. 2nd ed. Pennsylvania (USA): Lippincott Williams & Wilkins; 1998. p. 101-18.
- 6. Taddei CFG, Franken RA. Aterosclerose: fisiopatologia e prevenção de fatores de risco. In: Freitas EV, Py L, Neri AL, Cançado F, Gorzoni ML, Rocha M. Tratado de geriatria e gerontologia. Rio de Janeiro: Guanabara Koogan; 2002.
- 7. Libby P, Ridker PM. Inflammation and atherosclerosis: role of C-reactive protein in the risk assessment. Am J Med. 2004; 116 (6A): 9S-16S.
- 8. Pepsys MB, Berger A. The renaissance of C-reactive protein. Br Med J. 2001; 321: 4-5.
- 9. Saito M, Ishimitsu T, Minami J, Ono H, Ohrui M, Matsuoka H. Relations of plasma high-sensitivity C-reactive protein to traditional cardiovascular risk factors. Atherosclerosis. 2003; 167: 73-9.
- 10. Anand SS, Razak F, Yi Q, Davis B, Jacobs R, Vuksan V, et al. C-reactive protein as a screening test for cardiovascular risk in a multiethnic population. Arterioscler Thromb Vasc Biol. 2004; 21: 1509-15.
- 11. Ford ES. Body mass index, diabetes, and C-reactive protein among U.S. adults. Diabetes Care. 1999; 22 (12): 1971-7.
- 12. Cook DG, Mendall MA, Whincup PH, Carey IM, Ballam L, Morris JE, et al. C-reactive protein concentration in children: relationship to adiposity and other cardiovascular risk factors. Atherosclerosis. 2000; 149: 139-50.
- 13. Mendall MA, Strachan DP, Butland BK, Ballam L, Morris J, Sweetnam PM, et al. C-reactive protein: relation to total mortality, cardiovascular mortality and cardiovascular risk factors in men. Eur Heart J. 2000; 21: 1584-90.
- 14. Rawson E, Freedson PS, Osganian SK, Matthews CE, Reed G, Ockene I. Body mass index, but not physical activity, is associated with C-reactive protein. Med Sci Sports Exerc. 2003; 35 (7): 1160-6.
- 15. Vikram NK, Misra A, Dwivedi M, Sharma R, Pandey RM, Luthra K, et al. Correlations of C-reactive protein levels with anthropometric profile, percentage of body fat, and lipids in healthy adolescents and young adults in urban North India. Atherosclerosis. 2003; 168: 305-13.
- 16. Chrysohoou C, Pitsavos C, Panagiotakos DB, Skoumas J, Stefanadis C. Association between prehypertension status and inflammatory markers related to atherosclerotic disease. Am J Hypertens. 2004; 17: 568-73.
- 17. Lakka T, Lakka HM, Salonen R, Kaplan GA, Salonen JT. Abdominal obesity is associated with accelerated progression of carotid atherosclerosis in men. Atherosclerosis. 2001; 154: 497-504.
- 18. Heillbronn LK, Clifton PM. C-reactive protein and coronary artery disease: influence of obesity, caloric restriction and weight loss. J Nutr Biochem. 2002; 13: 316-21.
- 19. Hak AE, Stehower CDA, Bots ML, Polderman KH, Schalkwijk CG, Westendorp IC, et al. Associations of C-reactive protein with measures of obesity, insulin resistance, and subclinical atherosclerosis, in healthy, middle-aged women. Arterioscler Thromb Vasc Biol. 1999; 19: 1986-91.
- 20. Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual abridged edition. Champaign (IL): Human Kinetics; 1988.
- 21. Jackson AS, Pollock ML. Practical assessment of body composition. Physic Sportsmed. 1985; 13: 76-90.
- 22. Cabrera MAS, Jacob Filho W. Obesidade em idosos: prevalência, distribuição e associação com hábitos e co-morbidades. Arq Bras Endocrinol Metab. 2001; 45: 494-501.
- 23. Sowers JR. Obesity and cardiovascular disease. Clin Chem. 1998; 44 (8): 1821-5.
- 24. Abate N. Obesity and cardiovascular disease: pathogenic role of metabolic syndrome and therapeutic implications. J Diabetes Complications. 2000; 14: 154-74.
- 25. Yudkin JS, Stehowe CD, Emeis J, Coppack SW. C-reactive protein in healthy subjects: associations with obesity, insulin resistance, and endothelial dysfunction: a potential role for cytokines originating from adipose tissue. Arterioscler Thromb Vasc Biol. 1999; 19: 972-8.
- 26. Lemieux I, Pascot A, Prudhomme D, Alméras N, Bogaty P, Nadeauet A, et al. Elevated C-reactive protein: another component of the atherothrombotic profile of abdominal obesity. Arterioscler Thromb Vasc Biol. 2001; 21: 961-7.
- 27. Cabrera MAS, Wajngarten M, Gebara OCE, Diament J. Relação do índice de massa corporal, da relação cintura quadril e da circunferência abdominal com a mortalidade em mulheres idosas: seguimento de 5 anos. Cad Saúde Pública. 2005; 21: 767-75.
- 28. Ridker PM. Clinical application of C-reactive protein for cardiovascular disease detection and prevention. Circulation. 2003; 107: 363-9.
- 29. Frohlich M, Imhof A, Berg G, Hutchinson WL, Pepys MB, Boeing H, et al. Association between C-reactive protein and features of the metabolic syndrome: a population-based study. Diabetes Care. 2000; 23: 1835-9.
- 30. Strandberg TE, Tilvis RS. C-reactive protein, cardiovascular risk factors, and mortality in a prospective study in the elderly. Arterioscler Thromb Vasc Biol. 2000; 20: 1057-60.
- 31. Soinio M, Marniemi J, Laksoo M, Lehto S, Rönnemaa T. High-sensitivity C-reactive protein and coronary heart disease mortality in patients with type 2 diabetes. Diabetes Care. 2006; 29: 329-33.
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Publication Dates
-
Publication in this collection
18 Apr 2008 -
Date of issue
Oct 2007
History
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Reviewed
26 Mar 2007 -
Received
12 July 2006 -
Accepted
19 Apr 2007