DIABETES TECHNOLOGY & THERAPEUTICS Volume 16, Number 2, 2014 ª Mary Ann Liebert, Inc. DOI: 10.1089/dia.2013.0239
ORIGINAL ARTICLE
Association Between Nontraditional Risk Factors and Metabolic Syndrome in Indigenous Argentinean Schoolchildren Valeria Hirschler, MD,1 Gustavo Maccallini, MS,2 Claudia Molinari, MS,1 Ine´s M. Urrutia, MD,3 and Luis A. Castano, MD,3 on behalf of the San Antonio de los Cobres Study Group*
Abstract Background: Whether apolipoproteins (Apos) are better cardiovascular disease (CVD) markers than metabolic syndrome (MS) is widely debated. Measurement of Apo B is standardized, simple, and inexpensive and does not require fasting. The aim of this study was to compare the ability of nontraditional CVD markers such as Apo B, Apo B/Apo A, non–high-density lipoprotein cholesterol (HDL-C), vitamin D, and homeostasis model assessment of insulin resistance (HOMA-IR) to identify children with MS. Subjects and Methods: A cross-sectional study of 355 Argentinean Koya schoolchildren (166 boys) 9.6 – 2.3 years old was performed in November 2011. Anthropometric measures, blood pressure, Tanner stages, and serum levels of glucose, lipids, insulin, Apo A, Apo B, and vitamin D were measured. Results: The prevalence of overweight/obesity was 10.7% (n = 38), and that of underweight was 14.6% (n = 52) using Centers for Disease Control and Prevention criteria. The prevalence of central obesity was 10.9% (38/355), high triglycerides was 11.1% (39/355), low HDL-C was 44.9% (158/355), hypertension was 12.8% (45/355), hyperglycemia was 0.3% (1/355), and MS was 4.2% (15/355). Several multiple logistic regression analyses showed that MS was significantly associated with HOMA-IR (odds ratio [OR], 3.6 [95% confidence interval (CI) 1.51–8.52]), non-HDL-C (OR, 1.03 [95% CI 1.007–1.049]), Apo B (OR, 1.06 [95% CI 1.03–1.09]), and Apo B/Apo A (OR, 78.3 [95% CI 3.67–1,674.4]) adjusted for age and gender. Furthermore, the areas under the receiver operator characteristic curves were as follows: Apo B, 0.77 (95% CI 0.63–0.90); Apo B/Apo A, 0.76 (95% CI 0.63–0.88); non-HDL-C, 0.72 (95% CI 0.57–0.85); and HOMA-IR, 0.69 (95% CI 0.49–0.90). These values indicate that these variables were acceptable predictors for MS. Conclusions: This is the first study of nontraditional markers in South American Indian children. MS was associated with multiple nontraditional markers of future CVD risk such as non-HDL-C, Apo B, and Apo B/Apo A. However, Apo B was the best predictor for MS, suggesting that it could be used as a risk marker of future CVD in this community. understood. However, studies have clearly shown that traditional determinants are inadequate, especially when assessing younger ages.3 The increased understanding of the pathophysiology of CVD allows for the consideration of a range of new nontraditional CVD risk factors such as apolipoprotein (Apo) B, Apo B/Apo A ratio, vitamin D deficiency, and homeostasis model assessment of insulin resistance (HOMA-IR). Previous studies in adults showed that Apo B was a better marker of risk for CVD than low-density lipoprotein cholesterol (LDL-C).4,5 In the clinical setting, measurement of triglycerides and HDL-C, two of the components
Background
E
arly identification of the metabolic syndrome (MS) is crucial in halting the progression of cardiovascular disease (CVD) and protecting the future health of children and adolescents.1 MS is defined as three or more of the following components: hyperglycemia, low level of high-density lipoprotein cholesterol (HDL-C), high level of triglycerides, hypertension, and central obesity.2 MS predicts subclinical atherosclerosis in early adulthood.1 The relationship between traditional CVD risk factors and the occurrence of CVD is well 1
University of Buenos Aires, Buenos Aires, Argentina. Hidalgo Laboratories, Martı´nez, Buenos Aires, Argentina. 3 Cruces Hospital, University of Basque Country, CIBERDEM, CIBERER, Bilbao, Spain. *Collaborators are Milva Sanchez, San Antonio de los Cobres Hospital, Salta, Argentina; Graciela Colque, University of Buenos Aires; Claudio Aranda, MS, University of Buenos Aires; Mariana Hidalgo, MS, Hidalgo Laboratories; and Mirta Urzagasti, San Antonio de los Cobres Hospital. 2
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APO B IN ARGENTINEAN INDIAN CHILDREN of MS, demands at least a 12-h fast. In contrast, the measurement of Apos is standardized, simple, and inexpensive and can be done with samples obtained from nonfasting individuals.6 Therefore, in real practice, measurement of Apo B may be a more easily accessible tool for identifying subjects at risk of CVD than the MS.7 The pathophysiological basis for why ApoB is better than LDL-C is as follows: each LDL-C contains one molecule of Apo B; therefore, the number of plasma Apo B molecules equals the total number of LDL-C. Small, dense LDL-C particles are common, and, when present, LDL-C concentration underestimates the number of LDLC particles.6 Because risk of atherosclerosis appears to be more directly related to the number of circulating atherogenic particles that enter the arterial wall than to the concentrations of LDL-C, Apo B would be a better predictor of CVD risk than serum LDL-C in Koya children. We have previously demonstrated that Koya Indian children experience a disproportionately elevated prevalence of dyslipidemia.8 This study was performed in San Antonio de los Cobres, a small town located in the mountains of Salta Province, northwestern Argentina. Most of the population are Koya Indian and live in poverty.9 They have lower body mass index (BMI) values than urbanized populations with higher prevalence of dyslipidemia.8 We are unaware of any previous studies examining the predictive value of nontraditional CVD markers to identify South American children with MS. Whether nontraditional risk factors identify children with MS in a group of apparently healthy Koya children should be further explored. The objective of this study was to compare the ability of nontraditional CVD markers such as Apo B, Apo B/Apo A, non-HDL-C, vitamin D, and HOMA-IR to identify children with MS. Subjects and Methods San Antonio de los Cobres is a town with a population of 4,274 inhabitants (approximately 500 children), located in a mountainous region only recently accessible by road and isolated from urbanization and economic development.9 With its elevation of 3,750 m (2.34 miles) above sea level, it is one of the highest inhabited elevations in Argentina.9 In this crosssectional study, schoolchildren from 4 to 15 years of age were evaluated in November 2011, which is in the spring season. Anthropometric measures were performed on all the schoolchildren (approximately 500). Free examinations were offered to 417 children. Exclusion criteria included (1) any of the five components of MS not being measured, (2) not fasting for at least 12 h, (3) the presence of diabetes or other chronic diseases, (4) the use of medication that would affect blood pressure, glucose, or lipid metabolism, (5) and the informed consent form not being signed. The study was approved by the Human Rights Committee of the Salta Health Ministry. Each parent and subject gave written informed consent after an explanation of the study and before its initiation. However, 58 participants were excluded because at least one of the five components of MS was not assessed, and four participants were excluded because the informed consent was not signed. Therefore, 355 children participated in the survey. The sample size was determined by the ability to provide a precise estimate of the prevalence of obesity. Given that the prevalence of obesity was approximately 3% among children in the Salta province,9 the sample size was estimated to achieve that
85 percentage with an error less than 0.02 with 95% confidence. A cluster sampling was used in the first stage, and in the second stage a random sample was surveyed. Height and weight were measured with subjects wearing light clothing and without shoes. Weight was measured to the nearest 0.1 kg on a medical balance scale. Height was measured to the nearest 0.1 cm with a wall-mounted stadiometer. Children were classified as normal weight (BMI < 85%), overweight (BMI 85% to < 95%), or obese (BMI ‡ 95%) according to Centers for Disease Control and Prevention norms.10 Central obesity was defined as waist circumference ‡ 90th percentile based on 3,000 Argentinean schoolchildren (authors’ unpublished data). Blood pressure measurements were recorded by a trained technician using a random-zero sphygmomanometer after the participant was seated at rest for 5 min.11 The physical examination also included determination of the stage of puberty according to the criteria of Tanner.12 The pubertal stages of 100 children were not measured as they refused to be examined. Blood samples were obtained from subjects after a 12-h overnight fast for measurement of glucose, insulin, and lipid levels. All samples were analyzed in a single laboratory. Glucose, lipids, Apo A, and Apo B were analyzed by standardized methods using the Architect c 16000 instrument (Toshiba, Tokyo, Japan) and dedicated reagents from Abbott Laboratories (Abbott Park, IL). 25-Hydroxyvitamin D was analyzed by chemiluminescent microparticle immunoassay methods using the Architect i 4000 instrument and dedicated reagents from Abbott Laboratories. Internal quality control materials (assay chemistry bilevel lot 14410) were used from Bio-Rad Laboratories (Irvine, CA). Interassay coefficients of variation (CVs) were as follows: cholesterol, 0.62% and 0.95%; glucose, 1.55% and 1.37 %; HDL-C, 2.00% and 3.08%; and triglycerides, 0.87% and 1.11%, respectively. For 25(OH)vitamin D, the 25(OH)-vitamin D controls (three levels; lot 00512I000) from Abbott Diagnostics (Abbott Park) were used. The inter-assay CVs were 7.3%, 6.4%, and 6.2%, respectively. Concentrations of non-HDL-C were calculated as total cholesterol minus HDL-C. LDL-C concentrations were calculated with the formula of Friedewald et al.13: [total cholesterol] – [HDL-C] – ([triglycerides]/2.2). Lipid abnormalities were defined according to the reference standards from the American Heart Association. Triglyceride concentrations of ‡ 150 mg/ dL or HDL-C levels of £ 35 mg/dL were considered abnormal for children.14 Optimal levels for vitamin D were defined as ‡ 30 ng/mL.15 The following equation was used for HOMAIR index: fasting insulin (lU/L) · fasting glucose (mmol/L)/ 22.5.16 MS was assessed using the criteria applied in the U.S. National Health and Nutrition Examination Survey, 1988–1994,2 and children were diagnosed with MS if they met at least three of the following five conditions: (1) central obesity (waist circumference > 90th percentile); (2) high triglycerides; (3) low HDL-C; (4) blood pressure > 90th percentile for age, sex, and height; and (5) hyperglycemia. Data analysis The v2 test was used to compare proportions. When more than 20% of the cells had expected frequencies of < 5, Fisher’s exact test was used. The fit to normal distribution of continuous variables was assessed using the Shapiro–Wilks test.
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When comparing two groups with normally distributed data, Student’s t test was performed. When the homogeneity of the variances could not be proven, the Brown Forsyth test was used. Variables with an asymmetric distribution were logtransformed for analysis. Univariate analyses were performed using Spearman coefficients. Separate stepwise multiple logistic regression analyses were performed to examine the relationship between the MS as the dependent variable and the values for vitamin D, HOMA-IR, non-HDL-C, Apo B, and Apo B/Apo A ratio as the independent variables, adjusted for age and gender. Observed associations were expressed as odds ratios (OR) and 95% confidence intervals (CIs). The areas under the receiver operating characteristic (ROC) curves were calculated for HOMA-IR, vitamin D, non-HDL-C, Apo B, and Apo B/Apo A ratio, and the difference between these areas was used to determine which marker was a predictor for MS. MS was used as the dichotomous variable. Values of P < 0.05 were considered significant. Bonferroni’s adjustment was carried out when numerous comparisons were performed. Data are presented as mean – SD values. Analyses were done using the SPSS (Chicago, IL) statistical software package SPSS version 17.0. Results Socioeconomic class, pubertal stages, and clinical characteristics The study group comprises 355 Argentinean Koya Indian schoolchildren (166 boys) 9.6 – 2.3 years of age. There was no significant difference in age, BMI, gender, or socioeconomic class between all the schoolchildren (n = 500) and those who underwent testing (n = 355). All participants came from a low socioeconomic level, with 87.7% of the parents having only an elementary school education or less. Approximately 31% of
the families did not have a refrigerator, and 32% had a dirt floor. The prevalence of Tanner stages 1, 2, 3, and 4 was 51%, 26%, 18%, and 5% respectively. Approximately half of the children were prepubertal. However, Tanner staging was done on a smaller proportion of this community because 100 children refused to be examined. General features are shown in Table 1. Children were also divided according to gender. There was no significant difference in age, BMI, waist circumference, and lipid levels between genders. Mean values of glucose and vitamin D were significantly lower in girls than in boys. Analysis of data according to MS and its components Of the 355 Koya children, 28 (7.9%) were overweight, 10 (2.8%) were obese, and 52 (14.6%) were underweight (Table 2). The difference in the prevalence of underweight, overweight, or obesity between genders was not significant. There was a significantly higher prevalence of central obesity in girls than in boys (Table 2). The prevalence of low HDL-C was the most common risk factor in Koya children, whereas the prevalence of hyperglycemia was less frequent in the sample. The difference in the prevalence of hyperglycemia, hypertension, dyslipidemia, or MS between genders was not significant. Fifty-three percent (189/355) of the children had at least one component of MS, and 21% (76/355) had two or more components of MS. Only one child had optimal vitamin D levels ( > 30 ng/mL), and 7.2% (21/355) had vitamin D levels between 20 and 30 ng/mL. Children were divided in two groups according to the presence of MS (Table 3). The difference in the mean age between groups was not significant. Mean levels of BMI, waist circumference, systolic blood pressure, triglycerides, HOMAIR, non-HDL-C, Apo B, and Apo B/Apo A ratio were significantly higher, whereas HDL-C was lower, in children with MS versus those without (Fig. 1).
Table 1. Clinical and Metabolic Characteristics of Schoolchildren According to Gender
Age (years) Height percentile WC (cm) z-BMIa SBP (mm Hg) TC (mg/dL) HDL-C (mg/dL) TG (mg/dL) LDL-C (mg/dL) Non-HDL-C (mg/dL) Apo B (mg/dL) Apo A (mg/dL) Apo B/Apo A Glucose (mg/dL)b HOMA-IR Vitamin D (ng/mL)c
Males
Females
Total
9.62 – 2.56 36.28 – 27.57 61 – 9 - 0.54 – 1.20 83 – 11 151.06 – 27.20 43.20 – 11.67 106.25 – 45.52 88.73 – 21.67 107.97 – 26.25 71.83 – 15.46 119.41 – 19.54 0.61 – 0.15 78.59 – 9.15 0.80 – 0.62 15.56 – 4.21
9.61 – 2.14 34.00 – 26.98 62 – 8 - 0.50 – 2.29 81 – 10 154.23 – 27.56 41.76 – 8.77 108.52 – 39.26 92.90 – 22.25 111.56 – 25.67 74.17 – 15.14 118.38 – 20.05 0.64 – 0.14 75.29 – 11.89 0.89 – 0.58 13.66 – 3.67
9.61 – 2.34 35.06 – 27.24 62 – 9 - 0.52 – 1.86 81 – 10 152.75 – 27.38 42.43 – 10.23 107.47 – 42.24 90.97 – 22.05 109.89 – 25.95 73.10 – 15.31 118.85 – 19.79 0.63 – 0.15 76.83 – 10.81 0.84 – 0.60 14.55 – 4.03
Data are mean – SD values. a The z-score is a quantitative measure of the deviation of a specific variable taken from the mean of that population. In particular, the Centers for Disease Control and Prevention’s z-body mass index (BMI) takes into account age and sex. The significance of differences in values between genders was calculated; Bonferroni’s adjustment was carried out as many comparisons were performed: bP < 0.05, cP < 0.001. Apo, apolipoprotein; HDL-C, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, lowdensity lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides; WC, waist circumference.
APO B IN ARGENTINEAN INDIAN CHILDREN
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Table 2. Estimated Prevalence for Components of the Metabolic Syndrome Among Schoolchildren (n = 355) Males Overweight/obese Underweight WC > 90th percentilea Hypertension Hyperglycemia Low HDL-C High TG MS
16/166 24/166 7/166 26/166 0/166 67/166 17/166 7/166
Females
(99.6%) (14.5%) (4.3%) (15.9%) (0%) (41.1%) (10.4%) (4.2%)
22/189 28/189 31/189 18/189 1/189 91/189 22/189 8/189
(11.7%) (14.9%) (16.7%) (9.6%) (5.0%) (48.4%) (11.7%) (4.3%)
Total 38/355 52/355 38/355 45/355 1/355 45/355 39/355 15/355
(10.7%) (14.6%) (10.7%) (12.8%) (0.3%) (44.9%) (11.1%) (4.2%)
Data are numbers (percentages). a Significantly difference between sexes using Bonferroni’s adjustment: P < 0.01. HDL-C, high-density lipoprotein cholesterol; MS, metabolic syndrome; TG, triglycerides; WC, waist circumference.
Analysis of data according to Apo B quartiles Figure 2 shows the distribution of serum Apo B levels among the children in the study. The Apo B level ranged from 34 to 121 mg/dL. The median plasma levels or 50th percentile of Apo B was 72 mg/dL (Fig. 1). Children in the higher quartiles of Apo B had significantly higher levels of triglycerides, LDL-C, non-HDL-C, and Apo B/Apo A ratio than children in the lower quartiles of Apo B, whereas vitamin D levels decreased significantly. Mean levels of age, BMI, waist circumference, systolic blood pressure, glucose, HDL-C, and HOMA-IR were not significantly different among Apo B quartiles. When values were adjusted for age and gender, results did not change (Table 4). Multiple logistic regression analyses The multiple logistic regression models showed that MS was significantly associated with HOMA-IR (OR, 3.6 [95% CI Table 3. Clinical and Metabolic Characteristics According to the Presence of Metabolic Syndrome
Age (years) z-BMIac BMI (kg/m2)c WC (cm)c SBP (mm Hg)c Glucose (mg/dL)c TG (mg/dL)c TC (mg/dL) HDL-C (mg/dL)c Non-HDL-C (mg/dL)c LDL-C (mg/dL) Apo B (mg/dL)c Apo B/Apo A HOMA-IRb
Non-MS
MS
9.60 – 2.37 - 0.58 – 1.86 16.45 – 2.63 61.15 – 7.80 81.72 – 10.52 76.56 – 10.81 103.74 – 36.93 152.23 – 27.28 42.89 – 10.15 108.82 – 25.48 90.88 – 21.98 72.36 – 14.87 0.62 – 0.14 0.80 – 0.53
10.27 – 1.91 0.92 – 1.05 21.35 – 5.54 76.39 – 13.25 90.00 – 7.56 83.40 – 8.42 190.93 – 63.73 161.62 – 27.91 32.33 – 5.56 128.47 – 27.84 92.67 – 25.71 88.24 – 17.12 0.74 – 0.12 1.52 – 1.16
Data are mean – SD values. a The z-score is a quantitative measure of the deviation of a specific variable taken from the mean of that population. In particular, the Centers for Disease Control and Prevention’s z-body mass index (BMI) takes into account age and sex. The significance of differences in values between the groups with and without metabolic syndrome (MS) was calculated: bP < 0.05, c P < 0.001. Apo, apolipoprotein; HDL-C, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, lowdensity lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides; WC, waist circumference.
1.51–8.52]), non-HDL-C (OR, 1.03 [95% CI 1.007–1.049]), Apo B (OR, 1.06 [95% CI 1.03–1.09]), and Apo B/Apo A (OR, 78.3 [95% CI 3.67–1,674.4]) adjusted for age and gender. LDL-C, vitamin D, and Apo A levels were not significantly associated with MS. ROC curves To determine if non-HDL-C, Apo B, vitamin D, Apo B/Apo A ratio, and insulin resistance (HOMA-IR) were significant predictors for MS, ROC curves were generated with MS as the dichotomous variable. The area under the ROC curves were significantly different from 0.5 in Apo B (0.77 [95% CI 0.63– 0.90]), Apo B/Apo A (0.73 [95% CI 0.63–0.88]), non-HDL-C (0.72 [95% CI 0.57–0.85]), and HOMA-IR (0.69 [95% CI 0.49– 0.90]). Thresholds for optimal sensitivity and specificity for predicting MS among Koya children were as follows: Apo B, 83 ng/mL (sensitivity, 0.80; specificity, 0.79); Apo B/Apo A, 0.71 (sensitivity, 0.67; specificity, 0.82); non-HDL-C, 116 mg/ dL (sensitivity, 0.77; specificity, 0.66); and HOMA-IR, 0.98 (sensitivity, 0.67; specificity, 0.68). Results from the ROC curves indicate that Apo B and Apo A/Apo B were acceptable predictors for MS in Koya children because the areas under
FIG. 1. Boxplot of apolipoprotein B (Apo B). Median Apo B and interquartile range are presented separately for children with and without metabolic syndrome (MS) of both genders. The boxes define the 25th and 75th percentiles and enclose the median; the extensions define the range of values.
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FIG. 2. Histogram of plasma apolipoprotein B (APO B) levels among 355 children from San Antonio de los Cobres. the curve were > 0.7. Furthermore, Apo B was the stronger predictor for MS. In contrast, the areas under the ROC curves were not significantly different for vitamin D (0.51 [95% CI 0.39–0.62]) and LDL-C (0.50 [95% CI 0.33–0.68]) in identifying children with MS, indicating that these two markers were not acceptable predictors for MS. Discussion Our data showed that nontraditional risk factors such as non-HDL-C, Apo B, Apo B/Apo A ratio, and HOMA-IR were associated with MS adjusted for age and gender in Koya children. Most studies have focused on whites, whereas in our study all of the subjects were South American Indian children. To our knowledge, no studies have examined the association
between nontraditional markers and MS in a representative sample of South American Indian children and adolescents. Furthermore, the ROC curves showed that Apo B, Apo B/ Apo A, non-HDL-C, and HOMA-IR identified children with MS, with Apo B showing the strongest association. In contrast, the area under the ROC curve for LDL-C was not significant, which reflects that nontraditional risk factors were stronger variables than LDL-C for identifying MS in Koya Indian children. The association between MS and morbidity justifies looking for nontraditional markers of CVD in all children. Although the prevalence of overweight and obesity was low in Koya children, the prevalence of MS was very similar to that of the United States (4%).2 Furthermore, consistent with a previous study performed by our group in the same community,8 we found that those Koya Indian children presented a high prevalence of low HDL-C. This observation in the MS profile in the present study is consistent with results of previous studies performed in the United States.17 The present study showed that half of all children had at least one risk factor for MS. It is increasingly clear that lipid concentrations can be elevated during childhood and that this is associated with increased risk of atherosclerosis and CVD in adulthood.18 Previous studies have demonstrated that Apo B was a better marker of CVD risk than traditional markers.6,7 Plasma LDL-C is often found to be normal in patients with CVD.19 Consistent with these studies, we found that the area under the ROC curve for LDL-C was not significant for identifying MS, suggesting that nontraditional risk factors were stronger predictors for MS in this community. We have previously demonstrated that Koya Indian children experience a disproportionately elevated prevalence of hypovitaminosis D.20 A high prevalence of low vitamin D levels among Native Amerindian or Inuit children has also been described in Canada.21 Consistent with these studies, we found that the prevalence of hypovitaminosis D was 97% in the community studied. Vitamin D is considered a
Table 4. Mean Clinical Characteristics According to Apolipoprotein B Quartile
Age (years) BMI (mg/kg2) WC (cm) SBP (mm Hg) HDL-C (mg/dL) LDL-C (mg/dL)a TG (mg/dL)b Non-HDL-C (mg/dL)a Glucose (mg/dL) HOMA-IR Vitamin D (ng/mL)c Apo B/Apo Ad
Quartile 1 (n = 88) (34.0–63.8 mg/dL)
Quartile 2 (n = 90) (64.0–71.7 mg/dL)
Quartile 3 (n = 91) (71.9–81.8 mg/dL)
Quartile 4 (n = 86) (82.0–121.0 mg/dL)
9.69 – 2.44 16.22 – 2.42 60.89 – 7.02 81.84 – 11.51 41.51 – 10.12 67.62 – 11.63 90.83 – 32.81 81.82 – 10.83 75.67 – 11.66 0.86 – 0.62 16.13 – 4.41 0.52 – 0.14
9.62 – 2.26 16.60 – 2.84 61.21 – 7.81 82.10 – 10.92 43.14 – 12.53 85.78 – 9.79 99.33 – 34.28 99.48 – 14.33 76.95 – 10.90 0.78 – 0.44 14.14 – 3.97 0.60 – 0.10
9.92 – 2.33 16.68 – 2.77 61.94 – 8.02 82.03 – 11.25 44.10 – 8.21 96.37 – 10.61 108.51 – 30.17 113.90 – 10.07 76.14 – 13.35 0.80 – 0.48 13.87 – 3.81 0.62 – 0.09
9.74 – 2.38 17.44 – 3.77 64.50 – 10.87 83.04 – 9.79 41.22 – 9.78 119.31 – 18.49 135.23 – 57.05 140.90 – 19.31 79.34 – 7.97 1.05 – 0.80 13.62 – 3.63 0.76 – 0.13
Data are mean – SD values. a Significance found between each group, P < 0.01. b Significance found in comparison of Quartile 4 with Quartiles 1–3 and Quartile 1 with Quartile 3, P < 0.01. c Significance found in comparison of Quartile 1 with Quartiles 2–4, P < 0.01. d Significance found between each group except for Quartile 2 with Quartile 3, P < 0.01. Apo, apolipoprotein; BMI, body mass index; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol, TG, triglycerides; WC, waist circumference.
APO B IN ARGENTINEAN INDIAN CHILDREN nontraditional risk for CVD. Several previous studies showed significant associations between CVD and low vitamin D levels.22,23 However, there are conflicting findings on the relationship between vitamin D levels and CVD. A recent study showed no significant association between risk factors for type 2 diabetes and vitamin D levels in children and adolescents.24 Although we found a significant association between MS and vitamin D in the multivariate analysis, the area under the ROC curve showed no significant results. A general overrepresentation of vitamin D–deficient and –insufficient subjects in our cohort may have resulted in the lack of a relationship between vitamin D and MS in the ROC curve. We tested the hypothesis that Apo B/Apo A identifies children with MS in the general population. Even though we found a significant association in the regression analysis between MS and Apo B/Apo A, the OR had a very large 95% CI, a result of the range of Apo B (0.3–1.33 mg/dL) with the OR related to a change in 1 unit of Apo B/Apo A. Ratios are particularly complex to compare because the final result might differ, depending on the numerator and the denominator. For example, in the Framingham Offspring Study25 the ratio of Apo B/Apo A1 and the traditional lipid ratios were equivalent, but Apo B was a better risk factor. Accordingly, in this community Apo B was a stronger predictor of MS than the Apo B/Apo A ratio. Previous studies in adults showed that Apo B was a better marker of risk for CVD than LDL-C.4,5 In the clinical setting, measurement of triglycerides, LDL-C, and HDL-C demands at least a 12-h fast. In contrast, measurement of nontraditional risk factors such as Apo B is more convenient because they can be measured at any time, regardless of food intake.6,7 Therefore, as fasting is an issue in the pediatric population, measurement of Apo B may be a more easily accessible tool for identifying children at risk of MS. However, despite the close relationship between Apo B and MS, few data are available on this association in South American Indian children. We found a significantly higher level of Apo B in the group of Koya children with MS than in the group without MS. Furthermore, the regression analysis showed a significant association between MS and Apo B adjusted for confounding variables. Taken together, this suggests that prediction of future CVD in Koya children could be improved by measuring Apo B levels. It could be argued that non-HDL-C could be an equally accurate predictor of MS compared with Apo B. In addition, non-HDL-C measures the cholesterol content of all Apo B– containing lipoproteins, which have the potential to deliver cholesterol into the arterial wall and contribute to atherosclerotic lesions.7 Measurement of non-HDL-C is less reliable because this measurement depends on fasting and on variation in measurements of both total cholesterol (CV within, 6.0%) and HDL-C (7.1%). The measurement of Apo B has been standardized by the International Federation of Clinical Chemistry, and fasting samples are not required.7 Accordingly, we demonstrated that the Apo B area under the curve was stronger than the area of the non-HDL-C for identifying Koya children with MS. In addition, Apo B reflects atherogenic risk not captured by LDL-C measurement alone. A likely explanation for this is that although LDL-C is an estimate of the mass of cholesterol in the low-density lipoprotein fraction only, the value for Apo B is a measurement of the total number of atherogenic particles (including low-density lipo-
89 protein, intermediate-density lipoprotein, very low-density lipoprotein, chylomicrons, and chylomicron remnants) because each of these contain only a single molecule of Apo B.26 Several case-control studies have shown that levels of Apo B were more strongly associated with the presence of CVD than levels of total or LDL-C.6,27 Apo B has the advantage that its interindividual biological CV is lower than that of LDL-C (CV within, 6.9% vs. 8.3%), making repeated measurements of Apo B more reliable in the single patient. Consistent with these observations, this study showed that the LDL-C area under the ROC curve was not significant, whereas the Apo B area under the curve was acceptable for identifying Koya children with MS. For these reasons, we suggest that prediction of future CVD could be improved by measuring Apo B levels in this community. Several limitations of this study should be acknowledged. First, it was a cross-sectional study, and thus the directionality of the associations cannot be established. Second, hereditary factors could not be considered because few mothers knew about the presence or absence of CVD in the parental families. Third, only two measurements of blood pressure instead of three were performed, which might have produced a bias. The strengths of our study included our large schoolchildren population-based sample, which was more likely to represent the general population of Koya children, the important response rate of the children, and the use of regression models and simultaneous adjustment of confounding variables. Finally, few if any previous studies in Koya schoolchildren have examined the association between nontraditional CVD risk factors and vitamin D, taking into account the potential confounding effect of anthropometric measures. Conclusions This is the first study of nontraditional CVD markers in South American Indian children. MS was associated with multiple nontraditional markers of future CVD risk such as non-HDL-C, Apo B, and Apo B/Apo A. However, Apo B was the best predictor for MS, suggesting that it could be used as a risk marker of future CVD in this community. Additional longitudinal studies should be performed to further confirm these findings. Author Disclosure Statement G.M. is an employee of Hidalgo Laboratories. V.H., C.M., I.M.U. and L.A.C. declare no competing financial interests exist. References 1. Berenson GS, Srinivasan SR, Bao W, Newman WP 3rd, Tracy RE, Wattigney WA: Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl J Med 1998;338:1650–1656. 2. Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH: Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988–1994. Arch Pediatr Adolesc Med 2003;157:821–827. 3. Marma AK, Berry JD, Ning H, Persell SD, Lloyd-Jones DM: Distribution of 10-year and lifetime predicted risks for cardiovascular disease in US adults: findings from the National
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HIRSCHLER ET AL. Health and Nutrition Examination Survey 2003–2006. Circ Cardiovasc Qual Outcomes 2010;3:8–14. Lamarche B, Moorjani S, Lupien PJ, Cantin B, Bernard PM, Dagenais GR, Despre´s JP: Apolipoprotein A-1 and B levels and the risk of ischemic heart disease during a five-year follow-up of men in the Quebec Cardiovascular Study. Circulation 1996;94:273–278. Brunzell JD, Davidson M, Furberg CD, Goldberg RB, Howard BV, Stein JH, Witztum JL; American Diabetes Association; American College of Cardiology Foundation: Lipoprotein management in patients with cardiometabolic risk: consensus statement from the American Diabetes Association and the American College of Cardiology Foundation. Diabetes Care 2008;31:811–822. McQueen MJ, Hawken S, Wang X, Ounpuu S, Sniderman A, Probstfield J, Steyn K, Sanderson JE, Hasani M, Volkova E, Kazmi K, Yusuf S; INTERHEART Study Investigators: Lipids, lipoproteins, and apolipoproteins as risk markers of myocardial infarction in 52 countries (the INTERHEART study): a case-control study. Lancet 2008;372:224–233. Marcovina SM, Albers JJ, Kennedy H, Mei JV, Henderson LO, Hannon WH; International Federation of Clinical Chemistry Standardization Project for Measurements of Apolipoproteins A-I and B: Comparability of Apo B values by use of international reference material. Clin Chem 1994;40:586–592. Hirschler V, Maccallini G, Aranda C, Molinari C; San Antonio de los Cobres Study Group: Dyslipidemia without obesity in indigenous Argentinean children living at high altitude. J Pediatr 2012;161:646–651. Censo 2010. www.censo2010.indec.gov.ar (accessed October 23, 2011). Kuczmarski R, Ogden C, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, Wei R, Curtin LR, Roche AF, Johnson CL: 2000 CDC growth charts for the United States: methods and development. Vital Health Stat 11 2002;(246):1–190. National High Blood Pressure Education Working Group on High Blood Pressure in Children and Adolescents: The fourth report on the diagnosis, evaluation and treatment on high blood pressure in children and adolescents. Pediatrics 2004;114:555–576. Tanner JM: Growth at Adolescence: With a General Consideration of the Effects of Hereditary and Environmental Factors upon Growth and Maturation from Birth to Maturity, 2nd ed. Oxford, United Kingdom: Blackwell Scientific, 1962. Friedewald WT, Levy RI, Fredrickson DS: Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499–502. Kavey RE, Daniels SR, Lauer RM, Atkins DL, Hayman LL, Taubert K; American Heart Association: American Heart Association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. Circulation 2003;107:1562–1566. Bischoff-Ferrari HA, Giovannucci E, Willett WC, Dietrich T, Dawson-Hughes B: Estimation of optimal serum concen-
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trations of 25-hydroxyvitamin D for multiple health outcomes. Am J Clin Nutr 2006;84:18–28. McAuley K, Williams S, Mann J, Walker R, Lewis-Barned N, Temple L, Duncan A: Diagnosing insulin resistance in the general population. Diabetes Care 2001;24:460–464. de Ferranti SD, Gauvreau K, Ludwig DS, Neufeld EJ, Newburger JW, Rifai N: Prevalence of the metabolic syndrome in American adolescents: findings from the Third National Health and Nutrition Examination Survey. Circulation 2004;110:2494–2497. Newman WP 3rd, Freedman DS, Voors AW, Gard PD, Srinivasan SR, Cresanta JL, Williamson GD, Webber LS, Berenson GS: Relation of serum lipoprotein levels and systolic blood pressure to early atherosclerosis. The Bogalusa Heart Study. N Engl J Med 1986;314:138–144. Reilly MP, Rader DJ: The metabolic syndrome: more than the sum of its parts? Circulation 2003;108:1546–1551. Hirschler V, Maccallini G, Molinari C, Aranda C; San Antonio de los Cobres Study Group: Low vitamin D concentrations among indigenous Argentinean children living at high altitudes. Pediatr Diabetes 2013;14:203–210. Ward LM, Gaboury I, Ladhani M, Zlotkin S: Vitamin deficiency rickets among children in Canada. CMAJ 2007;177: 161–166. Liu E, Meigs JB, Pittas AG, McKeown NM, Economos CD, Booth SL, Jacques PF: Plasma 25-hydroxyvitamin D is associated with markers of the insulin resistant phenotype in nondiabetic adults. J Nutr 2009;39:329–334. Fiscella K, Franks P: Vitamin D, race, and cardiovascular mortality: findings from a national US sample. Ann Fam Med 2010;8:11–18. de Las Heras J, Rajakumar K, Lee S, Bacha F, Holick MF, Arslanian SA: 25- Hydroxyvitamin D in obese youth across the spectrum of glucose tolerance from normal to prediabetes to type 2 diabetes. Diabetes Care 2013;36:2048–2053. Ingelsson E, Schaefer EJ, Contois JH, McNamara JR, Sullivan L, Keyes MJ, Pencina MJ, Schoonmaker C, Wilson PW, D’Agostino RB, Vasan RS: Clinical utility of different lipid measures for prediction of coronary heart disease in men and women. JAMA 2007;298:776–785. Ballantyne CM, Andrews TC, Hsia JA, Kramer JH, Shear C; ACCESS Study Group: Correlation of non-high-density lipoprotein cholesterol with apolipoprotein B: effect of 5 hydroxymethylglutaryl coenzyme A reductase inhibitors on non-high-density lipoprotein cholesterol levels. Am J Cardiol 2001;88:265–269. Sniderman AD, Furberg CD, Keech A, van Lennep JR, Frohlich J, Jungner I, Walldius G: Apolipoproteins versus lipids as indices of coronary risk and as targets for statin treatment. Lancet 2003;361:777–780.
Address correspondence to: Valeria Hirschler, MD Maipu 812 5 M Buenos Aires (1006), Argentina E-mail: [email protected]
ORIGINAL ARTICLE
Association Between Nontraditional Risk Factors and Metabolic Syndrome in Indigenous Argentinean Schoolchildren Valeria Hirschler, MD,1 Gustavo Maccallini, MS,2 Claudia Molinari, MS,1 Ine´s M. Urrutia, MD,3 and Luis A. Castano, MD,3 on behalf of the San Antonio de los Cobres Study Group*
Abstract Background: Whether apolipoproteins (Apos) are better cardiovascular disease (CVD) markers than metabolic syndrome (MS) is widely debated. Measurement of Apo B is standardized, simple, and inexpensive and does not require fasting. The aim of this study was to compare the ability of nontraditional CVD markers such as Apo B, Apo B/Apo A, non–high-density lipoprotein cholesterol (HDL-C), vitamin D, and homeostasis model assessment of insulin resistance (HOMA-IR) to identify children with MS. Subjects and Methods: A cross-sectional study of 355 Argentinean Koya schoolchildren (166 boys) 9.6 – 2.3 years old was performed in November 2011. Anthropometric measures, blood pressure, Tanner stages, and serum levels of glucose, lipids, insulin, Apo A, Apo B, and vitamin D were measured. Results: The prevalence of overweight/obesity was 10.7% (n = 38), and that of underweight was 14.6% (n = 52) using Centers for Disease Control and Prevention criteria. The prevalence of central obesity was 10.9% (38/355), high triglycerides was 11.1% (39/355), low HDL-C was 44.9% (158/355), hypertension was 12.8% (45/355), hyperglycemia was 0.3% (1/355), and MS was 4.2% (15/355). Several multiple logistic regression analyses showed that MS was significantly associated with HOMA-IR (odds ratio [OR], 3.6 [95% confidence interval (CI) 1.51–8.52]), non-HDL-C (OR, 1.03 [95% CI 1.007–1.049]), Apo B (OR, 1.06 [95% CI 1.03–1.09]), and Apo B/Apo A (OR, 78.3 [95% CI 3.67–1,674.4]) adjusted for age and gender. Furthermore, the areas under the receiver operator characteristic curves were as follows: Apo B, 0.77 (95% CI 0.63–0.90); Apo B/Apo A, 0.76 (95% CI 0.63–0.88); non-HDL-C, 0.72 (95% CI 0.57–0.85); and HOMA-IR, 0.69 (95% CI 0.49–0.90). These values indicate that these variables were acceptable predictors for MS. Conclusions: This is the first study of nontraditional markers in South American Indian children. MS was associated with multiple nontraditional markers of future CVD risk such as non-HDL-C, Apo B, and Apo B/Apo A. However, Apo B was the best predictor for MS, suggesting that it could be used as a risk marker of future CVD in this community. understood. However, studies have clearly shown that traditional determinants are inadequate, especially when assessing younger ages.3 The increased understanding of the pathophysiology of CVD allows for the consideration of a range of new nontraditional CVD risk factors such as apolipoprotein (Apo) B, Apo B/Apo A ratio, vitamin D deficiency, and homeostasis model assessment of insulin resistance (HOMA-IR). Previous studies in adults showed that Apo B was a better marker of risk for CVD than low-density lipoprotein cholesterol (LDL-C).4,5 In the clinical setting, measurement of triglycerides and HDL-C, two of the components
Background
E
arly identification of the metabolic syndrome (MS) is crucial in halting the progression of cardiovascular disease (CVD) and protecting the future health of children and adolescents.1 MS is defined as three or more of the following components: hyperglycemia, low level of high-density lipoprotein cholesterol (HDL-C), high level of triglycerides, hypertension, and central obesity.2 MS predicts subclinical atherosclerosis in early adulthood.1 The relationship between traditional CVD risk factors and the occurrence of CVD is well 1
University of Buenos Aires, Buenos Aires, Argentina. Hidalgo Laboratories, Martı´nez, Buenos Aires, Argentina. 3 Cruces Hospital, University of Basque Country, CIBERDEM, CIBERER, Bilbao, Spain. *Collaborators are Milva Sanchez, San Antonio de los Cobres Hospital, Salta, Argentina; Graciela Colque, University of Buenos Aires; Claudio Aranda, MS, University of Buenos Aires; Mariana Hidalgo, MS, Hidalgo Laboratories; and Mirta Urzagasti, San Antonio de los Cobres Hospital. 2
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APO B IN ARGENTINEAN INDIAN CHILDREN of MS, demands at least a 12-h fast. In contrast, the measurement of Apos is standardized, simple, and inexpensive and can be done with samples obtained from nonfasting individuals.6 Therefore, in real practice, measurement of Apo B may be a more easily accessible tool for identifying subjects at risk of CVD than the MS.7 The pathophysiological basis for why ApoB is better than LDL-C is as follows: each LDL-C contains one molecule of Apo B; therefore, the number of plasma Apo B molecules equals the total number of LDL-C. Small, dense LDL-C particles are common, and, when present, LDL-C concentration underestimates the number of LDLC particles.6 Because risk of atherosclerosis appears to be more directly related to the number of circulating atherogenic particles that enter the arterial wall than to the concentrations of LDL-C, Apo B would be a better predictor of CVD risk than serum LDL-C in Koya children. We have previously demonstrated that Koya Indian children experience a disproportionately elevated prevalence of dyslipidemia.8 This study was performed in San Antonio de los Cobres, a small town located in the mountains of Salta Province, northwestern Argentina. Most of the population are Koya Indian and live in poverty.9 They have lower body mass index (BMI) values than urbanized populations with higher prevalence of dyslipidemia.8 We are unaware of any previous studies examining the predictive value of nontraditional CVD markers to identify South American children with MS. Whether nontraditional risk factors identify children with MS in a group of apparently healthy Koya children should be further explored. The objective of this study was to compare the ability of nontraditional CVD markers such as Apo B, Apo B/Apo A, non-HDL-C, vitamin D, and HOMA-IR to identify children with MS. Subjects and Methods San Antonio de los Cobres is a town with a population of 4,274 inhabitants (approximately 500 children), located in a mountainous region only recently accessible by road and isolated from urbanization and economic development.9 With its elevation of 3,750 m (2.34 miles) above sea level, it is one of the highest inhabited elevations in Argentina.9 In this crosssectional study, schoolchildren from 4 to 15 years of age were evaluated in November 2011, which is in the spring season. Anthropometric measures were performed on all the schoolchildren (approximately 500). Free examinations were offered to 417 children. Exclusion criteria included (1) any of the five components of MS not being measured, (2) not fasting for at least 12 h, (3) the presence of diabetes or other chronic diseases, (4) the use of medication that would affect blood pressure, glucose, or lipid metabolism, (5) and the informed consent form not being signed. The study was approved by the Human Rights Committee of the Salta Health Ministry. Each parent and subject gave written informed consent after an explanation of the study and before its initiation. However, 58 participants were excluded because at least one of the five components of MS was not assessed, and four participants were excluded because the informed consent was not signed. Therefore, 355 children participated in the survey. The sample size was determined by the ability to provide a precise estimate of the prevalence of obesity. Given that the prevalence of obesity was approximately 3% among children in the Salta province,9 the sample size was estimated to achieve that
85 percentage with an error less than 0.02 with 95% confidence. A cluster sampling was used in the first stage, and in the second stage a random sample was surveyed. Height and weight were measured with subjects wearing light clothing and without shoes. Weight was measured to the nearest 0.1 kg on a medical balance scale. Height was measured to the nearest 0.1 cm with a wall-mounted stadiometer. Children were classified as normal weight (BMI < 85%), overweight (BMI 85% to < 95%), or obese (BMI ‡ 95%) according to Centers for Disease Control and Prevention norms.10 Central obesity was defined as waist circumference ‡ 90th percentile based on 3,000 Argentinean schoolchildren (authors’ unpublished data). Blood pressure measurements were recorded by a trained technician using a random-zero sphygmomanometer after the participant was seated at rest for 5 min.11 The physical examination also included determination of the stage of puberty according to the criteria of Tanner.12 The pubertal stages of 100 children were not measured as they refused to be examined. Blood samples were obtained from subjects after a 12-h overnight fast for measurement of glucose, insulin, and lipid levels. All samples were analyzed in a single laboratory. Glucose, lipids, Apo A, and Apo B were analyzed by standardized methods using the Architect c 16000 instrument (Toshiba, Tokyo, Japan) and dedicated reagents from Abbott Laboratories (Abbott Park, IL). 25-Hydroxyvitamin D was analyzed by chemiluminescent microparticle immunoassay methods using the Architect i 4000 instrument and dedicated reagents from Abbott Laboratories. Internal quality control materials (assay chemistry bilevel lot 14410) were used from Bio-Rad Laboratories (Irvine, CA). Interassay coefficients of variation (CVs) were as follows: cholesterol, 0.62% and 0.95%; glucose, 1.55% and 1.37 %; HDL-C, 2.00% and 3.08%; and triglycerides, 0.87% and 1.11%, respectively. For 25(OH)vitamin D, the 25(OH)-vitamin D controls (three levels; lot 00512I000) from Abbott Diagnostics (Abbott Park) were used. The inter-assay CVs were 7.3%, 6.4%, and 6.2%, respectively. Concentrations of non-HDL-C were calculated as total cholesterol minus HDL-C. LDL-C concentrations were calculated with the formula of Friedewald et al.13: [total cholesterol] – [HDL-C] – ([triglycerides]/2.2). Lipid abnormalities were defined according to the reference standards from the American Heart Association. Triglyceride concentrations of ‡ 150 mg/ dL or HDL-C levels of £ 35 mg/dL were considered abnormal for children.14 Optimal levels for vitamin D were defined as ‡ 30 ng/mL.15 The following equation was used for HOMAIR index: fasting insulin (lU/L) · fasting glucose (mmol/L)/ 22.5.16 MS was assessed using the criteria applied in the U.S. National Health and Nutrition Examination Survey, 1988–1994,2 and children were diagnosed with MS if they met at least three of the following five conditions: (1) central obesity (waist circumference > 90th percentile); (2) high triglycerides; (3) low HDL-C; (4) blood pressure > 90th percentile for age, sex, and height; and (5) hyperglycemia. Data analysis The v2 test was used to compare proportions. When more than 20% of the cells had expected frequencies of < 5, Fisher’s exact test was used. The fit to normal distribution of continuous variables was assessed using the Shapiro–Wilks test.
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When comparing two groups with normally distributed data, Student’s t test was performed. When the homogeneity of the variances could not be proven, the Brown Forsyth test was used. Variables with an asymmetric distribution were logtransformed for analysis. Univariate analyses were performed using Spearman coefficients. Separate stepwise multiple logistic regression analyses were performed to examine the relationship between the MS as the dependent variable and the values for vitamin D, HOMA-IR, non-HDL-C, Apo B, and Apo B/Apo A ratio as the independent variables, adjusted for age and gender. Observed associations were expressed as odds ratios (OR) and 95% confidence intervals (CIs). The areas under the receiver operating characteristic (ROC) curves were calculated for HOMA-IR, vitamin D, non-HDL-C, Apo B, and Apo B/Apo A ratio, and the difference between these areas was used to determine which marker was a predictor for MS. MS was used as the dichotomous variable. Values of P < 0.05 were considered significant. Bonferroni’s adjustment was carried out when numerous comparisons were performed. Data are presented as mean – SD values. Analyses were done using the SPSS (Chicago, IL) statistical software package SPSS version 17.0. Results Socioeconomic class, pubertal stages, and clinical characteristics The study group comprises 355 Argentinean Koya Indian schoolchildren (166 boys) 9.6 – 2.3 years of age. There was no significant difference in age, BMI, gender, or socioeconomic class between all the schoolchildren (n = 500) and those who underwent testing (n = 355). All participants came from a low socioeconomic level, with 87.7% of the parents having only an elementary school education or less. Approximately 31% of
the families did not have a refrigerator, and 32% had a dirt floor. The prevalence of Tanner stages 1, 2, 3, and 4 was 51%, 26%, 18%, and 5% respectively. Approximately half of the children were prepubertal. However, Tanner staging was done on a smaller proportion of this community because 100 children refused to be examined. General features are shown in Table 1. Children were also divided according to gender. There was no significant difference in age, BMI, waist circumference, and lipid levels between genders. Mean values of glucose and vitamin D were significantly lower in girls than in boys. Analysis of data according to MS and its components Of the 355 Koya children, 28 (7.9%) were overweight, 10 (2.8%) were obese, and 52 (14.6%) were underweight (Table 2). The difference in the prevalence of underweight, overweight, or obesity between genders was not significant. There was a significantly higher prevalence of central obesity in girls than in boys (Table 2). The prevalence of low HDL-C was the most common risk factor in Koya children, whereas the prevalence of hyperglycemia was less frequent in the sample. The difference in the prevalence of hyperglycemia, hypertension, dyslipidemia, or MS between genders was not significant. Fifty-three percent (189/355) of the children had at least one component of MS, and 21% (76/355) had two or more components of MS. Only one child had optimal vitamin D levels ( > 30 ng/mL), and 7.2% (21/355) had vitamin D levels between 20 and 30 ng/mL. Children were divided in two groups according to the presence of MS (Table 3). The difference in the mean age between groups was not significant. Mean levels of BMI, waist circumference, systolic blood pressure, triglycerides, HOMAIR, non-HDL-C, Apo B, and Apo B/Apo A ratio were significantly higher, whereas HDL-C was lower, in children with MS versus those without (Fig. 1).
Table 1. Clinical and Metabolic Characteristics of Schoolchildren According to Gender
Age (years) Height percentile WC (cm) z-BMIa SBP (mm Hg) TC (mg/dL) HDL-C (mg/dL) TG (mg/dL) LDL-C (mg/dL) Non-HDL-C (mg/dL) Apo B (mg/dL) Apo A (mg/dL) Apo B/Apo A Glucose (mg/dL)b HOMA-IR Vitamin D (ng/mL)c
Males
Females
Total
9.62 – 2.56 36.28 – 27.57 61 – 9 - 0.54 – 1.20 83 – 11 151.06 – 27.20 43.20 – 11.67 106.25 – 45.52 88.73 – 21.67 107.97 – 26.25 71.83 – 15.46 119.41 – 19.54 0.61 – 0.15 78.59 – 9.15 0.80 – 0.62 15.56 – 4.21
9.61 – 2.14 34.00 – 26.98 62 – 8 - 0.50 – 2.29 81 – 10 154.23 – 27.56 41.76 – 8.77 108.52 – 39.26 92.90 – 22.25 111.56 – 25.67 74.17 – 15.14 118.38 – 20.05 0.64 – 0.14 75.29 – 11.89 0.89 – 0.58 13.66 – 3.67
9.61 – 2.34 35.06 – 27.24 62 – 9 - 0.52 – 1.86 81 – 10 152.75 – 27.38 42.43 – 10.23 107.47 – 42.24 90.97 – 22.05 109.89 – 25.95 73.10 – 15.31 118.85 – 19.79 0.63 – 0.15 76.83 – 10.81 0.84 – 0.60 14.55 – 4.03
Data are mean – SD values. a The z-score is a quantitative measure of the deviation of a specific variable taken from the mean of that population. In particular, the Centers for Disease Control and Prevention’s z-body mass index (BMI) takes into account age and sex. The significance of differences in values between genders was calculated; Bonferroni’s adjustment was carried out as many comparisons were performed: bP < 0.05, cP < 0.001. Apo, apolipoprotein; HDL-C, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, lowdensity lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides; WC, waist circumference.
APO B IN ARGENTINEAN INDIAN CHILDREN
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Table 2. Estimated Prevalence for Components of the Metabolic Syndrome Among Schoolchildren (n = 355) Males Overweight/obese Underweight WC > 90th percentilea Hypertension Hyperglycemia Low HDL-C High TG MS
16/166 24/166 7/166 26/166 0/166 67/166 17/166 7/166
Females
(99.6%) (14.5%) (4.3%) (15.9%) (0%) (41.1%) (10.4%) (4.2%)
22/189 28/189 31/189 18/189 1/189 91/189 22/189 8/189
(11.7%) (14.9%) (16.7%) (9.6%) (5.0%) (48.4%) (11.7%) (4.3%)
Total 38/355 52/355 38/355 45/355 1/355 45/355 39/355 15/355
(10.7%) (14.6%) (10.7%) (12.8%) (0.3%) (44.9%) (11.1%) (4.2%)
Data are numbers (percentages). a Significantly difference between sexes using Bonferroni’s adjustment: P < 0.01. HDL-C, high-density lipoprotein cholesterol; MS, metabolic syndrome; TG, triglycerides; WC, waist circumference.
Analysis of data according to Apo B quartiles Figure 2 shows the distribution of serum Apo B levels among the children in the study. The Apo B level ranged from 34 to 121 mg/dL. The median plasma levels or 50th percentile of Apo B was 72 mg/dL (Fig. 1). Children in the higher quartiles of Apo B had significantly higher levels of triglycerides, LDL-C, non-HDL-C, and Apo B/Apo A ratio than children in the lower quartiles of Apo B, whereas vitamin D levels decreased significantly. Mean levels of age, BMI, waist circumference, systolic blood pressure, glucose, HDL-C, and HOMA-IR were not significantly different among Apo B quartiles. When values were adjusted for age and gender, results did not change (Table 4). Multiple logistic regression analyses The multiple logistic regression models showed that MS was significantly associated with HOMA-IR (OR, 3.6 [95% CI Table 3. Clinical and Metabolic Characteristics According to the Presence of Metabolic Syndrome
Age (years) z-BMIac BMI (kg/m2)c WC (cm)c SBP (mm Hg)c Glucose (mg/dL)c TG (mg/dL)c TC (mg/dL) HDL-C (mg/dL)c Non-HDL-C (mg/dL)c LDL-C (mg/dL) Apo B (mg/dL)c Apo B/Apo A HOMA-IRb
Non-MS
MS
9.60 – 2.37 - 0.58 – 1.86 16.45 – 2.63 61.15 – 7.80 81.72 – 10.52 76.56 – 10.81 103.74 – 36.93 152.23 – 27.28 42.89 – 10.15 108.82 – 25.48 90.88 – 21.98 72.36 – 14.87 0.62 – 0.14 0.80 – 0.53
10.27 – 1.91 0.92 – 1.05 21.35 – 5.54 76.39 – 13.25 90.00 – 7.56 83.40 – 8.42 190.93 – 63.73 161.62 – 27.91 32.33 – 5.56 128.47 – 27.84 92.67 – 25.71 88.24 – 17.12 0.74 – 0.12 1.52 – 1.16
Data are mean – SD values. a The z-score is a quantitative measure of the deviation of a specific variable taken from the mean of that population. In particular, the Centers for Disease Control and Prevention’s z-body mass index (BMI) takes into account age and sex. The significance of differences in values between the groups with and without metabolic syndrome (MS) was calculated: bP < 0.05, c P < 0.001. Apo, apolipoprotein; HDL-C, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, lowdensity lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides; WC, waist circumference.
1.51–8.52]), non-HDL-C (OR, 1.03 [95% CI 1.007–1.049]), Apo B (OR, 1.06 [95% CI 1.03–1.09]), and Apo B/Apo A (OR, 78.3 [95% CI 3.67–1,674.4]) adjusted for age and gender. LDL-C, vitamin D, and Apo A levels were not significantly associated with MS. ROC curves To determine if non-HDL-C, Apo B, vitamin D, Apo B/Apo A ratio, and insulin resistance (HOMA-IR) were significant predictors for MS, ROC curves were generated with MS as the dichotomous variable. The area under the ROC curves were significantly different from 0.5 in Apo B (0.77 [95% CI 0.63– 0.90]), Apo B/Apo A (0.73 [95% CI 0.63–0.88]), non-HDL-C (0.72 [95% CI 0.57–0.85]), and HOMA-IR (0.69 [95% CI 0.49– 0.90]). Thresholds for optimal sensitivity and specificity for predicting MS among Koya children were as follows: Apo B, 83 ng/mL (sensitivity, 0.80; specificity, 0.79); Apo B/Apo A, 0.71 (sensitivity, 0.67; specificity, 0.82); non-HDL-C, 116 mg/ dL (sensitivity, 0.77; specificity, 0.66); and HOMA-IR, 0.98 (sensitivity, 0.67; specificity, 0.68). Results from the ROC curves indicate that Apo B and Apo A/Apo B were acceptable predictors for MS in Koya children because the areas under
FIG. 1. Boxplot of apolipoprotein B (Apo B). Median Apo B and interquartile range are presented separately for children with and without metabolic syndrome (MS) of both genders. The boxes define the 25th and 75th percentiles and enclose the median; the extensions define the range of values.
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FIG. 2. Histogram of plasma apolipoprotein B (APO B) levels among 355 children from San Antonio de los Cobres. the curve were > 0.7. Furthermore, Apo B was the stronger predictor for MS. In contrast, the areas under the ROC curves were not significantly different for vitamin D (0.51 [95% CI 0.39–0.62]) and LDL-C (0.50 [95% CI 0.33–0.68]) in identifying children with MS, indicating that these two markers were not acceptable predictors for MS. Discussion Our data showed that nontraditional risk factors such as non-HDL-C, Apo B, Apo B/Apo A ratio, and HOMA-IR were associated with MS adjusted for age and gender in Koya children. Most studies have focused on whites, whereas in our study all of the subjects were South American Indian children. To our knowledge, no studies have examined the association
between nontraditional markers and MS in a representative sample of South American Indian children and adolescents. Furthermore, the ROC curves showed that Apo B, Apo B/ Apo A, non-HDL-C, and HOMA-IR identified children with MS, with Apo B showing the strongest association. In contrast, the area under the ROC curve for LDL-C was not significant, which reflects that nontraditional risk factors were stronger variables than LDL-C for identifying MS in Koya Indian children. The association between MS and morbidity justifies looking for nontraditional markers of CVD in all children. Although the prevalence of overweight and obesity was low in Koya children, the prevalence of MS was very similar to that of the United States (4%).2 Furthermore, consistent with a previous study performed by our group in the same community,8 we found that those Koya Indian children presented a high prevalence of low HDL-C. This observation in the MS profile in the present study is consistent with results of previous studies performed in the United States.17 The present study showed that half of all children had at least one risk factor for MS. It is increasingly clear that lipid concentrations can be elevated during childhood and that this is associated with increased risk of atherosclerosis and CVD in adulthood.18 Previous studies have demonstrated that Apo B was a better marker of CVD risk than traditional markers.6,7 Plasma LDL-C is often found to be normal in patients with CVD.19 Consistent with these studies, we found that the area under the ROC curve for LDL-C was not significant for identifying MS, suggesting that nontraditional risk factors were stronger predictors for MS in this community. We have previously demonstrated that Koya Indian children experience a disproportionately elevated prevalence of hypovitaminosis D.20 A high prevalence of low vitamin D levels among Native Amerindian or Inuit children has also been described in Canada.21 Consistent with these studies, we found that the prevalence of hypovitaminosis D was 97% in the community studied. Vitamin D is considered a
Table 4. Mean Clinical Characteristics According to Apolipoprotein B Quartile
Age (years) BMI (mg/kg2) WC (cm) SBP (mm Hg) HDL-C (mg/dL) LDL-C (mg/dL)a TG (mg/dL)b Non-HDL-C (mg/dL)a Glucose (mg/dL) HOMA-IR Vitamin D (ng/mL)c Apo B/Apo Ad
Quartile 1 (n = 88) (34.0–63.8 mg/dL)
Quartile 2 (n = 90) (64.0–71.7 mg/dL)
Quartile 3 (n = 91) (71.9–81.8 mg/dL)
Quartile 4 (n = 86) (82.0–121.0 mg/dL)
9.69 – 2.44 16.22 – 2.42 60.89 – 7.02 81.84 – 11.51 41.51 – 10.12 67.62 – 11.63 90.83 – 32.81 81.82 – 10.83 75.67 – 11.66 0.86 – 0.62 16.13 – 4.41 0.52 – 0.14
9.62 – 2.26 16.60 – 2.84 61.21 – 7.81 82.10 – 10.92 43.14 – 12.53 85.78 – 9.79 99.33 – 34.28 99.48 – 14.33 76.95 – 10.90 0.78 – 0.44 14.14 – 3.97 0.60 – 0.10
9.92 – 2.33 16.68 – 2.77 61.94 – 8.02 82.03 – 11.25 44.10 – 8.21 96.37 – 10.61 108.51 – 30.17 113.90 – 10.07 76.14 – 13.35 0.80 – 0.48 13.87 – 3.81 0.62 – 0.09
9.74 – 2.38 17.44 – 3.77 64.50 – 10.87 83.04 – 9.79 41.22 – 9.78 119.31 – 18.49 135.23 – 57.05 140.90 – 19.31 79.34 – 7.97 1.05 – 0.80 13.62 – 3.63 0.76 – 0.13
Data are mean – SD values. a Significance found between each group, P < 0.01. b Significance found in comparison of Quartile 4 with Quartiles 1–3 and Quartile 1 with Quartile 3, P < 0.01. c Significance found in comparison of Quartile 1 with Quartiles 2–4, P < 0.01. d Significance found between each group except for Quartile 2 with Quartile 3, P < 0.01. Apo, apolipoprotein; BMI, body mass index; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol, TG, triglycerides; WC, waist circumference.
APO B IN ARGENTINEAN INDIAN CHILDREN nontraditional risk for CVD. Several previous studies showed significant associations between CVD and low vitamin D levels.22,23 However, there are conflicting findings on the relationship between vitamin D levels and CVD. A recent study showed no significant association between risk factors for type 2 diabetes and vitamin D levels in children and adolescents.24 Although we found a significant association between MS and vitamin D in the multivariate analysis, the area under the ROC curve showed no significant results. A general overrepresentation of vitamin D–deficient and –insufficient subjects in our cohort may have resulted in the lack of a relationship between vitamin D and MS in the ROC curve. We tested the hypothesis that Apo B/Apo A identifies children with MS in the general population. Even though we found a significant association in the regression analysis between MS and Apo B/Apo A, the OR had a very large 95% CI, a result of the range of Apo B (0.3–1.33 mg/dL) with the OR related to a change in 1 unit of Apo B/Apo A. Ratios are particularly complex to compare because the final result might differ, depending on the numerator and the denominator. For example, in the Framingham Offspring Study25 the ratio of Apo B/Apo A1 and the traditional lipid ratios were equivalent, but Apo B was a better risk factor. Accordingly, in this community Apo B was a stronger predictor of MS than the Apo B/Apo A ratio. Previous studies in adults showed that Apo B was a better marker of risk for CVD than LDL-C.4,5 In the clinical setting, measurement of triglycerides, LDL-C, and HDL-C demands at least a 12-h fast. In contrast, measurement of nontraditional risk factors such as Apo B is more convenient because they can be measured at any time, regardless of food intake.6,7 Therefore, as fasting is an issue in the pediatric population, measurement of Apo B may be a more easily accessible tool for identifying children at risk of MS. However, despite the close relationship between Apo B and MS, few data are available on this association in South American Indian children. We found a significantly higher level of Apo B in the group of Koya children with MS than in the group without MS. Furthermore, the regression analysis showed a significant association between MS and Apo B adjusted for confounding variables. Taken together, this suggests that prediction of future CVD in Koya children could be improved by measuring Apo B levels. It could be argued that non-HDL-C could be an equally accurate predictor of MS compared with Apo B. In addition, non-HDL-C measures the cholesterol content of all Apo B– containing lipoproteins, which have the potential to deliver cholesterol into the arterial wall and contribute to atherosclerotic lesions.7 Measurement of non-HDL-C is less reliable because this measurement depends on fasting and on variation in measurements of both total cholesterol (CV within, 6.0%) and HDL-C (7.1%). The measurement of Apo B has been standardized by the International Federation of Clinical Chemistry, and fasting samples are not required.7 Accordingly, we demonstrated that the Apo B area under the curve was stronger than the area of the non-HDL-C for identifying Koya children with MS. In addition, Apo B reflects atherogenic risk not captured by LDL-C measurement alone. A likely explanation for this is that although LDL-C is an estimate of the mass of cholesterol in the low-density lipoprotein fraction only, the value for Apo B is a measurement of the total number of atherogenic particles (including low-density lipo-
89 protein, intermediate-density lipoprotein, very low-density lipoprotein, chylomicrons, and chylomicron remnants) because each of these contain only a single molecule of Apo B.26 Several case-control studies have shown that levels of Apo B were more strongly associated with the presence of CVD than levels of total or LDL-C.6,27 Apo B has the advantage that its interindividual biological CV is lower than that of LDL-C (CV within, 6.9% vs. 8.3%), making repeated measurements of Apo B more reliable in the single patient. Consistent with these observations, this study showed that the LDL-C area under the ROC curve was not significant, whereas the Apo B area under the curve was acceptable for identifying Koya children with MS. For these reasons, we suggest that prediction of future CVD could be improved by measuring Apo B levels in this community. Several limitations of this study should be acknowledged. First, it was a cross-sectional study, and thus the directionality of the associations cannot be established. Second, hereditary factors could not be considered because few mothers knew about the presence or absence of CVD in the parental families. Third, only two measurements of blood pressure instead of three were performed, which might have produced a bias. The strengths of our study included our large schoolchildren population-based sample, which was more likely to represent the general population of Koya children, the important response rate of the children, and the use of regression models and simultaneous adjustment of confounding variables. Finally, few if any previous studies in Koya schoolchildren have examined the association between nontraditional CVD risk factors and vitamin D, taking into account the potential confounding effect of anthropometric measures. Conclusions This is the first study of nontraditional CVD markers in South American Indian children. MS was associated with multiple nontraditional markers of future CVD risk such as non-HDL-C, Apo B, and Apo B/Apo A. However, Apo B was the best predictor for MS, suggesting that it could be used as a risk marker of future CVD in this community. Additional longitudinal studies should be performed to further confirm these findings. Author Disclosure Statement G.M. is an employee of Hidalgo Laboratories. V.H., C.M., I.M.U. and L.A.C. declare no competing financial interests exist. References 1. Berenson GS, Srinivasan SR, Bao W, Newman WP 3rd, Tracy RE, Wattigney WA: Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl J Med 1998;338:1650–1656. 2. Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH: Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988–1994. Arch Pediatr Adolesc Med 2003;157:821–827. 3. Marma AK, Berry JD, Ning H, Persell SD, Lloyd-Jones DM: Distribution of 10-year and lifetime predicted risks for cardiovascular disease in US adults: findings from the National
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Address correspondence to: Valeria Hirschler, MD Maipu 812 5 M Buenos Aires (1006), Argentina E-mail: [email protected]
