Accuracy of Anthropometric Indexes of Obesity to ...

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original contributions

Accuracy of Anthropometric Indexes of Obesity to Predict Diabetes Mellitus Type 2 Among Men and Women With Hypertension Aline Marcadenti1,2, Sandra C. Fuchs1,2, Leila B. Moreira1,2, Mario Wiehe1, Miguel Gus1,2 and Flavio D. Fuchs1,2 Background Anthropometric measurements and indexes that assess excess of adiposity are associated with cardiovascular risk factors, and predict diabetes mellitus. Methods This cross-sectional study reported the performance of adiposity indexes to detect or turn diabetes unlikely in patients with hypertension. Patients with hypertension (blood pressure (BP) ≥140/90 mm Hg or antihypertensive drug use) aged 18–80 years, being 150 men and 332 women, had weight, height, waist circumference (WC), hip circumference, body mass index (BMI), waist-hip ratio (WHR), waist-to-height ratio (WHtR), and waist-tosquare height ratio (WHt2R) calculated. Diabetes was diagnosed by fasting blood glucose ≥126 mg/dl or antidiabetic drug use (23% of the sample). Results All anthropometric indexes were associated with diabetes in a modified Poisson regression, adjusting for age, smoking, and

The incidence of obesity and of obesity-related diseases, particularly of hypertension and diabetes, is increasing worldwide.1,2 Beside to share a common risk factor, the coexistence of diabetes and hypertension multiplies their individual risks. The potential to identify patients with hypertension at higher risk of diabetes because of excess of adiposity is clinically appealing. The prevalence of obesity has been reported through a simple weight to height index—body mass index (BMI)—which allows to detecting overall adiposity by the same cutoff in men and women. On the other side, the cutoffs for anthropo metric indexes of abdominal adiposity vary by sex and ethnic 1Hospital de Clinicas de Porto Alegre, Division of Cardiology, and the National

Institute for Science and Technology for Health Technology Assessment (IATS), R. Ramiro Barcelos 2350, Centro de Pesquisas, Cardiolab-Hipertensão, Porto Alegre, Brazil; 2Postgraduate Studies Program in Cardiology, Universidade Federal do Rio Grande do Sul, School of Medicine, R. Ramiro Barcelos 2600, Porto Alegre, Brazil. Correspondence: Sandra C. Fuchs ([email protected]) Received 17 May 2010; first decision 13 June 2010; accepted 29 August 2010. © 2010 American Journal of Hypertension, Ltd. AMERICAN JOURNAL OF HYPERTENSION

physical activity, in women, but not in men. In men, only the area under the receiver-operating characteristic curve (AUC) for WHR was statistically associated with diabetes (0.67, 95% confidence interval (CI) 0.57–0.77). A cutoff of ≥0.95 had sensitivity of 84.6% (73.3–95.9) and negative post-test probability of 12.8% (3.2–22.4). Among women, WC >88 cm, WHR ≥0.85, and WHtR > 0.54 had sensitivity >93% and negative post-test probability 88.0 cm, and WHtR >0.54 for women and WHR ≥0.95 for men are highly suggestive of diabetes among this population of hypertensive patients. Indexes below these cutoffs turn diabetes unlikely in this context. The investigation of reproducibility of this performance in other outpatient clinics is warranted. Keywords: anthropometric indexes; blood pressure; central obesity; diabetes mellitus; diagnosis; hypertension; obesity; sensitivity American Journal of Hypertension, advance online publication 30 September 2010; doi:10.1038/ajh.2010.212

group, but have been consistently associated with cardiovascular risk,3,4 prevalence of diabetes mellitus,5 and incidence of hypertension.6 Waist circumference (WC) was adopted as the abdominal adiposity criteria for metabolic syndrome diagnosis, but the cutoffs vary according to different guidelines.7,8 WC cutoffs between 102 and 94 cm for men, and 88 and 80 cm for women7 and of specific values for different ethnic groups8 have been proposed. Besides the variation of values, the isolate measurement of WC does not take into account the differences in height. Other anthropometric indexes of abdominal adiposity had been developed, such as waist-to-height ratio (WHtR), which was able to predict the need of weight management,9 intra-abdominal fat,10 cardiovascular risk,3,4 and mortality,11 In a population-based study conducted in the Chinese adult population, WHtR was the best anthropometric index predicting diabetes mellitus.12 The diagnostic accuracy of anthropometric indexes of obesity to detect diabetes mellitus has been shown in studies conducted in populations4,13–15 and outpatient clinic.16 As far, we know, there is no study examining the accuracy of the indexes to detect diabetes mellitus in patients with 1

original contributions hypertension. Since diabetes and hypertension are strongly independent17 and clustered predictors of cardiovascular disease,18,19 the screening for type 2 diabetes in adults with sustained high blood pressure (BP) may help to provide an early diagnosis through relatively inexpensive tests. The aim of this study was therefore to examine the accuracy of different cutoff points of five anthropometric indexes of obesity for the detection of diabetes among patients with hypertension. Methods

Study population. This study included men and women, aged 18–80 years, mostly from low and middle income families, living in the urban area of Porto Alegre, the capital of the southern state in Brazil, with >1.5 million inhabitants. Patients were referred to our hypertension clinic, in the university hospital (Hospital de Clínicas de Porto Alegre) for the management of hypertension by the city and state clinical centers. There was no a priori condition for referring patients from health-care centers. Therefore, they were not likely to systematically differ from other outpatient hypertension clinics, and those with hypertension in all stages were screened to participate of this cross-sectional study. This analysis included 482 subjects (150 men, 332 women), with BP (systolic ≥140 or diastolic ≥90 mm Hg), without heart failure, myocardial infarction, or stroke in the past 6 months and other relevant chronic diseases. Pregnant women were excluded. The institution review board approved the protocol and patients signed an informed consent to participate. Demographic characteristics (age, sex, and self-reported skin color) and questions pertaining to education (years at school), lifestyle (smoking, abusive alcohol consumption, physical activity) among other variables were collected by certified interviewers using standardized questionnaires. Usual daily alcohol consumption was determined through the type, quantity, and frequency of each beverage consumed in the previous months. Men and women who consumed 30 or 15 g of ethanol or more per day, respectively, were classified as alcohol abusers. Current smokers were those who reported smoking every day or some days at the time of the interview. Physical activity was evaluated by the short version of the International Physical Activity Questionnaire (IPAQ), and it was categorized as low to moderate or high. Standardized assessments of BP and anthropometric measurements were conducted by certified medical students under supervision of an attending physician. Patients had office BP measured with aneroid sphygmomanometer (mean of six measurements in three office visits) using a cuff size according to the arm circumference and 24 h ambulatory BP monitoring assessed according to guidelines.20 Hypertension was diagnosed by the average of office BP measurements ≥140/90 mm Hg or use of lowering medication. Fasting blood glucose ≥126 mg/dl or antidiabetic drug use, recorded by the physician or informed by the patient, identified those with type 2 diabetes mellitus.21 Weight (kg) was measured with patients in light clothing and barefoot to the nearest 100 g with a scale (Filizola Scale, 2

Anthropometric Indexes of Obesity Predict Diabetes

model 31; IN Filizola—SA, São Paulo, Brazil), and height (cm) was measured maintaining the Frankfort plane, to the nearest 0.1 cm, using Tonelli Stadiometer, model E120 A (IN Tonelli—SA, Santa Catarina, Brazil). BMI was calculated by weight (kg)/height (m)2. WC was measured with a flexible inelastic plastic-fiber tape measure placed on the midpoint between the lower rib margin and the iliac crest in a perpendicular plane to the long axis of the body, while the subject stood balanced on both feet, ~20 cm apart, and with both arms hanging freely.22 Hip circumference was measured at the level of the widest circumference over the buttocks,22 with the research assistant kneeling at the side of the participant so that the level of maximum extension could be seen. Anthropometry was performed in duplicate, 1 week apart, by trained interviewers independently and periodically reassessed. Agreement between anthropometric measurements was assessed by Bland and Altman test, using the Analyze-it for Microsoft Excel program (version 2.12, 2008). Anthropometric indexes were calculated by the average of two measurements. Waist-hip ratio (WHR) was the ratio of the two circumferences, waist to the hip (both in centimeters). WHtR was calculated by the ratio between WC (cm) and height (cm), and the waist-height2 ratio (WHt2R) between WC (cm) and square height (m2). Sample size calculation and statistical analysis. The sample size calculation was based on an estimated range of sensitivity (98–88%), for 95% confidence interval (CI) and with 80% power, among patients with high prevalence of diabetes (25% or high), and a ratio of 3:4 of noncases to cases, which resulted in a sample of ~470 patients. Data are presented as mean and s.d. or frequencies and were compared by analysis of variance or Pearson’s χ2 test (SPSS version 14.0, SPSS, Chicago, IL). Receiver-operating characteristic curves were calculated separately for men and women to determine the cutoffs for BMI, WC, WHR, WHtR, and WHt2R, using the Epidat (version 3.1; Dirección Xeral de Saúde Pública, Xunta de Galicia; OPS– OMS). The differences between areas under the receiver-operating characteristic curve (AUC) of the anthropometric indexes were compared using a nonparametrical test.23 A diagnostic test with an AUC value of 1 is perfectly accurate, and one with 0.5 has no discrimination power. Sensitivity, specificity, positive and negative post-test probability for different cutoffs of BMI, WC, WHR, WHtR, and WHT2R to detect diabetes mellitus were calculated. The best cutoff was determined by those with high AUC, sensitivity and low negative post-test probability. The associations between anthropometric indexes of obesity and diabetes mellitus were analyzed by modified Poisson regression expressed as risk ratios and 95% CI adjusted for age, current smoking, and low to moderate physical activity, and presented separately for men and women. The Institutional Review Board and the Ethics Committee of our institution approved the protocol, and all participants provided informed consent. AMERICAN JOURNAL OF HYPERTENSION



Table 1 | Characteristics of the participants according to diabetes (mean ± s.d. or N (%))

Age (years)

Overall sample N = 468

Diabetes mellitus N = 106

No diabetes mellitus N = 362

P value

57.1 ± 12.2

59.9 ± 10.7

56.3 ± 12.5

0.007 0.08

Sex Male

144 (30.8)

40 (27.8)

104 (72.2)

Female

324 (69.2)

66 (20.4)

258 (79.6) 0.8

Race White

309 (66)

69 (22.3)

240 (77.7)

Nonwhite

159 (34)

37 (23.3)

122 (76.7)

7.6 ± 4.2

7.1 ± 4.4

7.8 ± 4.1

Current

125 (26.7)

19 (15.2)

106 (84.8)

Ex- or nonsmoker

343 (73.3)

87 (25.4)

256 (74.6)

Yes

40 (8.5)

9 (22.5)

31 (77.5)

No

428 (91.5)

97 (22.7)

331 (77.3)

367 (78.4)

90 (24.5)

277 (75.5)

97 (21.6)

16 (16.5)

81 (83.5)

224 (47.9)

39 (17.4)

185 (82.6)

Years at school

0.02

Smoking

1.0

Alcohol abuse

0.09

Physical activity Low to moderate High Body mass index (kg/m2) 0.54

86.8 (74.8–98.9)

26.5 (17.4–35.5)

30.6 (21.4–39.7)

15.6 (1.5–29.8)

0.60 (0.50–0.70)

≥30.0

92.1 (82.2–100)

16.7 (8.9–24.4)

29.2 (20.6–37.7)

14.0 (0–33.1)

0.67 (0.57–0.77)

≥0.95

84.6 (73.3––95.9)

39.4 (30.0–48.8)

34.4 (24.9–43.9)

12.8 (3.2–22.4)

BMI

0.62 (0.55–0.69)

≥27.5

81.8 (71.8–91.9)

34.2 (28.3–40.2)

24.2 (18.4–30.1)

12.0 (5.1–18.9)

WC

0.65 (0.58–0.72)

>88.0

95.5 (89.7–100)

22.2 (16.9–27.5)

24.0 (18.6–29.3)

5.0 (0–11.3)

Men

WHt2R

WHR Women

WHtR

0.64 (0.57–0.71)

>0.54

95.5 (89.7–100)

19.8 (14.8–24.9)

23.4 (18.2–28.7)

5.6 (0–12.6)

WHt2R

0.61 (0.54–0.68)

≥35.0

90.9 (83.2–98.6)

24.1 (18.7–29.6)

23.5 (18.1–28.9)

8.8 (1.3–16.3)

WHR

0.66 (0.58–0.73)

≥0.85

93.9 (87.4–100)

19.5 (14.4–24.5)

23.1 (17.8–28.3)

7.4 (0–15.3)

AUC, area under the curve; BMI, body mass index; CI, confidence interval; NPPT, negative post-test probability; PPPT, positive post-test probability; Se, sensitivity; Sp, specificity; WC, waist circumference; WHR, waist-hip ratio; WHtR, waist-to-height ratio; WHt2R, waist-to-square height ratio.

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Table 3 | Association between abnormal anthropometric indexes of obesity and diabetes mellitus, expressed through risk ratio (95% CI), for men and women Men Cutoff

Risk ratioa (95% CI)

BMI

>25.0

WC

>94.0

Women P value

Cutoff

Risk ratioa (95% CI)

1.4 (0.7–2.8)

0.3

≥27.5

1.8 (1.0–3.0)

0.04

1.1 (0.6–2.1)

0.7

>88.0

3.7 (1.4–9.8)

0.008

P value

WHtR

>0.54

1.3 (0.6–2.6)

0.5

>0.54

4.5 (1.2–17.8)

0.03

WHt2R

≥30.0

1.2 (0.4–3.4)

0.7

≥35.0

5.1 (1.3–20.4)

0.02

WHR

≥0.95

2.8 (1.3–6.2)

0.009

≥0.85

2.7 (1.2–6.5)

0.03

BMI, body mass index; CI, confidence interval; WC, waist circumference; WHR, waist-hip ratio; WHtR, waist-to-height ratio; WHt2R, waist-to-square height ratio. aRisk ratio, calculated by modified Poisson regression, adjusted for age, smoking, and physical activity.

frequently reported. Nonetheless, the investigation of the performance of anthropometric indexes to predict diabetes mellitus among subjects with hypertension has not been done to date. We were able to confirm that the WHR is a good predictor of diabetes mellitus for both men and women, whereas WC and WHtR are also accurate predictors among women. In men, the 95% CI of most anthropometric indexes included 0.5 meaning no discrimination power, and only WHR was far from it. Among women, the AUC of all indexes were superior to 0.61 and no CIs included 0.5. Overall, the AUCs were lower than those observed among German,4 American,15 Chinese,3,12 and Turkish24 general population. This might be related to the context of data collection, which included only patients with hypertension, with higher rates of obesity. The best cutoffs for WHR were ≥0.95, for men, and ≥0.85, for women. This cutoff was recommended by the World Health Organization to detect central obesity among Caucasian women.25 In this study, three anthropometric indexes, among women, reached sensitivity >94% and negative post-test probability 88 cm is above13,14,16 or below4,15 most of the cutoffs previously reported for predicting diabetes mellitus, but it was able to detect 96% of hypertensive diabetic women. The choice of the most appropriate cutoffs depends on the relative importance placed on maximizing sensitivity or specificity, and the purpose of testing subjects. Patients with hypertension are likely to have excessive weight for height and, consequently, are more prone to develop diabetes. Therefore, all hypertensive patients should be tested for diabetes or, alternatively, a strategy would be to further identify those at higher risk. In an ideal scenario, a test with 100% sensitivity would be able to detect all diabetic patients and, consequently, a negative test rule out such diagnosis. Considering that no anthropometric index had 100% sensitivity, it is meaningful to determine how many patients with a negative test would be undetected. So, our approach to establish the best cutoff for each anthropometric index was based on the highest sensitivity, at expenses of loosing specificity, and the lowest negative post-test probability. AMERICAN JOURNAL OF HYPERTENSION

The modified Poisson regression was run separately for each index and in women, all anthropometric indexes were independently associated with diabetes mellitus. These results confirmed that abnormal cutoff values of WC, WHtR, WHt2R, and WHR increased the risk of having diabetes mellitus, in comparison to the normal cutoffs.4,13–16 However, differently of other studies conducted in general populations,4,13–15 our findings were obtained in women with established hypertension. The association between BMI and diabetes mellitus was not statistically significant because the 95% CI of the risk ratio included one. The results contrast with recent findings in regard to the association by sex, since in the study of Liu et al.27 WC and BMI were independently associated with increased risk of insulin resistance in men, but not in women. This study is not directly comparable with our in face of the studied population, sampling frame (healthy volunteers vs. hypertensive patients), WC cutoff for men (102 vs. 94 cm), outcomes—insulin resistance (defined by the top tertile of steady-state plasma glucose concentrations), instead of diabetes mellitus (fasting glucose ≥126 mg/day or use of antidiabetes medicine), and the multivariate analysis (logistic regression vs. modified Poisson regression). Serum uric acid is another potential predictor of diabetes among patients with hypertension,28 but its predictive performance lessened after adjustment for BMI. The study conducted among the Chinese population detected positive and independent associations of BMI, WC, and WHtR with glucose tolerance abnormalities among men and women.12 Besides the ethnicity of volunteers (72% Caucasians),27 population-based Chinese,12 and 66% of white skin color patients in this study, these populations have other differences, such as prevalence of diabetes, hypertension, and obesity. All studies detected associations toward the AUC above 0.5 for men and women, and the indexes might perform better among those with high prevalence of obesity. Therefore, the phenomenon seems to be the same, but its detection depends on statistical power, sampling frame, and characteristics of the studied population. Among the potential limitations of this cross-sectional study, diabetes was diagnosed by one fasting glucose measure ≥126 mg/dl or use of antidiabetes medicine. This criterion, however, was recommended by the American Diabetes 5

original contributions Association21 for use in epidemiological studies. It would be worth having a single index and a single cutoff, such as BMI, for men and women. However, the only index with equivalent performance for both genders was WHR, but with different cutoffs, which might be expected in face of differences in the proportion and distribution of fat by sex. Besides to confirm the association between anthropometric indexes and diabetes demonstrated in other settings, our study is the first to explore this association exclusively among patients with hypertension. The identification of an abnormal anthropometric index during the physical examination may be taken as an indicator of risk for diabetes in a patient with hypertension, whereas normal indexes help to turn diabetes unlikely. These indexes could be acknowledged as a “quick” screening method in the clinical scenario, particularly when a glucose test is prohibitively expensive or otherwise difficult. In conclusion, WHR ≥0.85, WC >88.0 cm, and WHtR >0.54 for women and WHR ≥0.95 for men are highly suggestive of diabetes among this population of hypertensive patients. Indexes below these cutoffs turn diabetes unlikely in this context. The investigation of reproducibility of this performance in other outpatient clinics is warranted. Acknowledgments: This study was funded, in part, by National Counsel of Technological and Scientific Development (CNPq), the National Institute for Science and Technology for Health Technology Assessment (IATS/Brazil)— CNPq/Brazil, FIPE-Hospital de Clínicas de Porto Alegre, RS, Brazil. Disclosure: The authors declared no conflict of interest. 1. Tuck ML, Corry DB. Prevalence of obesity, hypertension, diabetes, and metabolic syndrome and its cardiovascular complications. Curr Hypertens Rev 2010; 6:73–82. 2. Hossain P, Kawar B, El Nahas M. Obesity and diabetes in the developing world–a growing challenge. N Engl J Med 2007; 356:213–215. 3. Ho SY, Lam TH, Janus ED. Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices. Ann Epidemiol 2003; 13:683–691. 4. Schneider HJ, Glaesmer H, Klotsche J, Böhler S, Lehnert H, Zeiher AM, März W, Pittrow D, Stalla GK, Wittchen HU; DETECT Study Group. Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. J Clin Endocrinol Metab 2007; 92:589–594. 5. Koh-Banerjee P, Wang Y, Hu FB, Spiegelman D, Willett WC, Rimm EB. Changes in body weight and body fat distribution as risk factors for clinical diabetes in US men. Am J Epidemiol 2004; 159:1150–1159. 6. Gus M, Cichelero FT, Moreira CM, Escobar GF, Moreira LB, Wiehe M, Fuchs SC, Fuchs FD. Waist circumference cut-off values to predict the incidence of hypertension: an estimation from a Brazilian population-based cohort. Nutr Metab Cardiovasc Dis 2009; 19:15–19. 7. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F; American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/ National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 112:2735–2752.

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