Obesity Research & Clinical Practice
Volume 4, Issue 3 , Pages e231-e237, July 2010

Effect of modest changes in BMI on cardiovascular disease risk markers in severely obese, minority adolescents

  • Unab I. Khan

      Affiliations

    • Department of Pediatrics, Division of Adolescent Medicine, Children's Hospital at Montefiore, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States
    • Corresponding Author InformationCorresponding author. Tel.: +1 718 920 5098; fax: +1 718 920 5289.
    • ,
  • Jessica Rieder

      Affiliations

    • Department of Pediatrics, Division of Adolescent Medicine, Children's Hospital at Montefiore, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States
    • ,
  • Hillel W. Cohen

      Affiliations

    • Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
    • ,
  • Susan M. Coupey

      Affiliations

    • Department of Pediatrics, Division of Adolescent Medicine, Children's Hospital at Montefiore, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States
    • ,
  • Rachel P. Wildman

      Affiliations

    • Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States

Received 5 May 2009; received in revised form 2 March 2010; accepted 4 March 2010.

Article Outline

Summary 

Background

African American and Hispanic adolescents have disproportionately higher rates of obesity compared to white adolescents. In adults, modest weight loss of five percent improves CVD risk marker levels. Less is known about the effects of modest changes in BMI on CVD risk markers in adolescents, particularly newer markers such as C reactive protein (CRP), lipoprotein (a) and homocysteine.

Objective

To examine the effect of modest BMI change on CVD risk marker levels in a group of severely obese, African American and Hispanic adolescents.

Study design

A six-month longitudinal analysis.

Subjects

Eighty-three African American and Hispanic adolescents were recruited (mean age±sd: 15.1±2.0 years); 50 (60%) were reevaluated at 6±2 months.

Results

At baseline, mean BMI was 42.3±7.8kg/m2. BMI directly correlated with CRP (p=<0.001); homocysteine (p=0.02); insulin (p=0.05); and systolic and diastolic blood pressures (both p=<0.001). BMI remained significantly associated with CRP and insulin after adjusting for age, sex and ethnicity (p=0.001). At six-month follow up, there was a significant p for trend between the three groups of BMI change (those with a ≥5% BMI decrease, those who maintained BMI within 5% and those with ≥5% BMI increase) and CRP (p=0.05) and insulin (p=0.04).

Conclusions

A modest decrease in BMI is associated with improvement in CRP and insulin levels. Obese adolescents should be encouraged to continue with modest weight loss goals as they result in improvement in cardiovascular disease risk markers.

Keywords: Adolescent obesity, C reactive protein, Cardiovascular disease risk markers

 

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Introduction 

In the United States, African American and Hispanic adolescents have disproportionately higher rates of obesity, especially severe obesity, compared to white adolescents and are at a high risk of developing cardiovascular disease (CVD) as they progress into adulthood [1], [2], [3], [4], [5]. For severely obese adolescents, gradual increase in obesity is common [6], [7], and achievement of significant weight loss is unusual even with participation in medical weight loss programs [8], [9], [10].

In adults, a modest weight loss of up to 5% improves cardiovascular health [11], [12], [13], with improvement in levels of both traditional CVD risk markers such as blood pressure and measures of glucose and lipid metabolism [14], [15], and newer CVD risk markers such as C reactive protein, lipoprotein (a) and homocysteine [16], [17], [18], [19]. During adolescence, because of continued growth in height, BMI is considered a more reliable measure of obesity than weight alone [20]. In obese adolescents, a decrease in BMI of 10% has shown to improve levels of both traditional and newer risk markers such as CRP [21]. As the utility of newer markers in CVD risk assessment continues to be evaluated in adolescents [22], [23], the association of modest changes in BMI with levels of CVD risk markers could aid in deciding if more modest, but achievable, BMI loss goals are clinically useful for these adolescents.

In this study, we examined the association of a five percent change in BMI over a six-month time period on levels of traditional and newer CVD risk markers in a clinical population of severely obese African American and Hispanic adolescents.

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Methods 

Subjects 

We recruited obese (BMI>95th percentile for age and sex) African American and Hispanic adolescents (aged 12–20 years) at their initial visit to a children's hospital weight loss clinic. One hundred and forty-three consecutive adolescents were approached; 96 consented; 83 had baseline fasting blood tests and were included in this study. Fifty of the 83 subjects (60%) completed the reevaluation after a mean of 6±2 months. Table 1 provides the baseline demographics and levels of CVD risk markers in our study sample.

Table 1. Baseline anthropometrics and levels of cardiovascular disease markers.
CharacteristicsN=83
Mean age, years±sd15.1±2.0
Females, N (%)50 (60)
Ethnicity, N (%)
Hispanic47 (57)
African American36 (43)
Mean weight, kg±sd117.2±26.2
Mean BMI, kg/m2±sd42.3±7.8
Mean BMI z-score±sd2.58±0.3
Median C-reactive protein, mg/dl(IQR)0.5 (0.1, 1.1)
Median lipoprotein (a), mg/dl (IQR)21 (9, 64)
Median homocysteine, μmol/L (IQR)6.3 (5.5, 7.7)
Mean cholesterol, mg/dl±sd167±33
Mean LDL, mg/dl±sd99±29
Mean HDL, mg/dl±sd45±10
Mean triglycerides, mg/dl±sd110±52
Mean fasting glucose, mg/dl±sd88±7
Median fasting insulin, units/l (IQR)88 (83, 93)
Median HOMA-IR (IQR)5.7 (4.2, 7.5)
Mean systolic blood pressure, mmHg±sd118±11
Mean diastolic blood pressure, mmHg±sd66±7

We excluded adolescents with acute infections or chronic inflammatory conditions, as that may invalidate the inflammatory marker assessment. The Montefiore Medical Center Institutional Review Board approved the study protocol. All subjects and their parents provided written informed consent.

Measures 

We measured height and weight in light clothing on a Scaletronix® stadiometer and calculated the BMI. BMI z-score, which is the BMI standardized for age and sex, was calculated using the Epi info software from the Centers for Disease Control and Prevention (CDC) [24]. Severe obesity was defined as BMI of >99th percentile for age and sex [20]. An adolescent medicine physician performed Tanner staging for sexual maturity rating on all subjects.

Blood samples were obtained after an overnight fast of 8–12h. Samples were centrifuged within 1h of collection. CRP levels were measured using latex enhanced immunoturbidometry (CRP ultra wide reagent kit, Equal Diagnostics, Pennsylvania, USA) on the Olympus AU400/400 analyzer (Olympus Life and Material Science Europa GmbH, Lismeehan, Ireland). The analyzer has a lower limit of detection of 0.1mg/dL. Lp(a) concentration was measured by immunoturbidometry with the Olympus analyzer AU400/400. Hcy levels were measured using immunoreaction using the Immulite 2000 kit and analyzer. Glucose, total cholesterol, HDL and triglycerides were measured using calorimetric methods (Olympus reagents, Olympus Life and Material Science Europa GmbH, Lismeehan, Ireland) using the Olympus AU400/400 analyzer. Insulin levels were measured by radioimmunoassay using human insulin RIA kits (Millipore, Massachusetts, USA). Intra-assay coefficients of variation were <5% for all measures. LDL was calculated using the Friedewald formula [25].

HOMA-IR was calculated as fasting insulin (μU/ml)×fasting glucose (mg/dl) divided by 22.5 and used as a surrogate marker of insulin sensitivity. Although not the gold standard for measuring insulin sensitivity, HOMA-IR is identified as one of the best non-invasive techniques with sensitivity and specificity of 76% and 66% respectively, with a cutoff value of 3.16 [26].

Statistical analysis 

To define the prevalence of CVD risk factors in our severely obese subjects, we evaluated the proportion of subjects with abnormal levels of CVD risk markers at baseline, using adult cutoff values for CRP, Lp(a) and Hcy [27], and adolescent cutoff values for traditional CVD risk markers [28], [29], [30].

Of the cardiovascular risk markers evaluated, the anthropometric parameters, lipid markers and blood pressures were normally distributed. Insulin and the newer markers had skewed distributions. In order to maintain clinical relevance of the results, variables with non-normal distribution were not transformed and appropriate non-parametric tests were conducted as indicated below.

We examined bivariate associations between BMI and CVD risk markers using Pearson correlation for normally distributed variables and Spearman correlation for non-normally distributed variables. Linear regression models were constructed for the CVD risk markers that showed significant bivariate associations with BMI and adjusted for age, sex and ethnicity.

Longitudinal comparisons of anthropometrics and CVD risk markers were conducted at six months, using paired t-test for normally distributed variables and Wilcoxon matched-pairs signed-rank test for variables that were not normally distributed.

We divided the 50 subjects who returned at six months for reevaluation into three groups defined by a modest change in BMI: those who had a ≥5% BMI decrease, those who maintained BMI within 5% and those with a ≥5% BMI increase. p for trend was tested between the change in anthropometric and CVD risk markers and the three BMI groups.

A two-tailed alpha of 0.05 was used to determine statistical significance. Analyses were performed using Stata 10.0.

Using the number of subjects in the three groups of BMI change, and the standard deviations obtained from our results, we performed post hoc power analysis for the CVD risk markers studied. Although we did not have sufficient power to detect statistical differences in changes in some of the CVD risk markers, we did have greater than 80% power to detect differences in changes in cholesterol and HDL levels, and changes in insulin, HOMA-IR and CRP levels. We also had 73% power to detect differences in Hcy levels between the three groups of BMI change.

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Results 

Baseline anthropometrics and cardiovascular disease risk marker levels 

Subjects had a mean±sd age of 15.1±2.0 years and most (90%) were severely obese (Table 1). Mean BMI percentile was 99.28±0.58, with a mean BMI z-score of 2.58 standard deviations above the CDC 2000 population mean. Mean and median levels of the CVD risk markers are shown. For the sample as a whole, none of the mean or median levels was abnormal. A higher proportion of girls vs. boys were Tanner stages 4 and 5, representing later stages of pubertal development (70% vs. 92%; Chi square=9.77; p=0.002).

Thirty-three percent of the total sample had elevated CRP levels (>0.9mg/L) and 21% of the sample had CRP levels that placed them in the high-risk category for CVD by adult standards (>3.0mg/L). Furthermore, 35% of the total sample had elevated Lp(a) levels of >30mg/dl, 29% had elevated triglyceride levels, 80% had HOMA-IR levels greater than 3.6 and 34% had mean systolic blood pressures greater than the 99th percentile for their age, sex and height. On the other hand, only two percent of the sample had elevated total cholesterol levels and 8% had fasting blood glucose of >100mg/dL.

Examining the association between severity of obesity and CVD risk markers, we found a significant direct correlation between BMI and both CRP levels (Spearman's rho=0.50, p=<0.001) and Hcy levels (Spearman's rho=0.25, p=0.03) (Table 2). We also found a significant direct correlation between BMI and fasting insulin levels (Spearman's rho=0.22, p=0.05); mean systolic blood pressure (Pearson's r=0.43, p=<0.001) and mean diastolic blood pressure (Pearson's r=0.4, p=<0.001). However, in our sample, we found no correlation between BMI and any of the traditional lipid markers (Table 2).

Table 2. Correlations between BMI and cardiovascular disease risk markers at baseline.
VariableCorrelationp-Value
CRP0.50a<0.001
Lipoprotein (a)10.07a0.57
Homocysteine0.25a0.03
Cholesterol0.06b0.63
LDL0.04b0.77
HDL−0.01b0.92
Triglycerides0.09b0.45
Glucose0.13b0.26
Insulin0.22a0.05
HOMA-IR0.27a0.02
Systolic blood pressure0.43b<0.001
Diastolic blood pressure0.40b<0.001

aSpearman's rho used for non-normally distributed variables.

bPearson's correlation used for normally distributed variables.

In multivariate regression, after adjusting for age, sex and race/ethnicity, there was a significant association between BMI and CRP (β estimate: 0.04; 95% CI: 0.02–0.04, p<0.001); insulin (β estimate: 0.93; 95% CI: 0.58–1.28, p<0.001); and systolic blood pressure β estimate: 0.24; 95% CI: 0.07–0.41, p<0.001). No statistically significant associations were found between BMI and other CVD risk markers.

Longitudinal comparison of changes in cardiovascular disease risk marker levels with change in BMI after six months 

Of the 83 subjects, 50 returned for reevaluation at 6±2 months. There were no significant differences in the baseline demographics, anthropometric measures or CVD risk marker levels between subjects who returned for reevaluation and those who did not.

We divided the subjects into groups according to modest changes in BMI defined as ≥5% BMI change. Ten subjects had a ≥5% BMI decrease; eight subjects had a ≥5% BMI increase whereas 32 maintained their BMI within 5%. Comparing changes in CVD risk marker levels across the three BMI groups, we found a significant p for trend across the three groups for CRP (p=0.05) and insulin levels (p=0.04) (Table 3) (Fig. 1).

Table 3. Six-month change (Δ) in cardiovascular disease risk markers according to percent change in BMI.
≥5% BMI increase N=8BMI within 5% N=32≥5% BMI decrease N=10p – for trend
ΔMean BMI kg/m2±sd3.8±1.20.36±1.2−3.9±1.0<0.001
ΔMean BMI z-score±sd0.11±0.07−0.04±0.14−0.21±0.22<0.001
ΔMedian CRP, mg/dl (IQR)0.1 (0, 0.5)0 (−0.2, 0.2)0 (−0.4, 0)0.05
ΔMedian lipoprotein (a), mg/dl (IQR)28.5 (9, 50)13 (0, 63)0 (0, 8)0.10
ΔMedian homocysteine, μmol/L (IQR)−1 (−1.7, 0.6)−0.6 (−1.6,0.9)0.3 (−1.2,1.7)0.38
ΔMean cholesterol, mg/dl±sd4±114±25−13±−80.16
ΔMean LDL, mg/dl±sd−3±110.5±22−9±−40.99
ΔMean HDL, mg/dl±sd7±62.5±65±30.70
ΔMean triglycerides, mg/dl±sd8±39−16.5±42−11±560.27
ΔMedian glucose, mg/dl (IQR)3 (−9, 4)3.5 (−3, 8.5)−4 (−8, 0.5)0.30
ΔMedian Insulin, units/l (IQR)3.6 (0, 10)0.35 (−8,16)−8.5 (−16, −7)0.04
ΔMedian HOMA-IR (IQR)0.58 (−0.18, 2.89)0.13 (−1.3, 4.67)−1.59 (−15.26,−.02)0.11
ΔMean systolic Blood Pressure, mg/dl±sd1±10−2±9−5±90.78
ΔMean diastolic blood pressure, mg/dl±sd−3±6−3±9−1±80.54
  • View full-size image.
  • Figure 1. 

    Change in CRP and insulin levels with modest changes in BMI. Box plots where upper and lower lines of the box represent the 25th and 75th percentiles and the middle line represents the median value. Whiskers represent 1.5 times the inter-quartile range. Change in CRP and insulin levels across the three groups of BMI change is significant (p for trend <0.05). (In the group with ≥5% BMI decrease, the median and 75th percentile values of change in CRP are 0).

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Discussion 

In our sample of severely obese African American and Hispanic adolescents, we found that while one-third of subjects had elevated levels of CRP and Lp(a), only 2% had high cholesterol levels and 16% had abnormal LDL and HDL levels. Abnormalities in lipid markers have consistently been linked with increased CVD risk [31], [32], but up to 25% of adults with CVD may not show abnormalities in traditional lipid markers [33]. Our results are consistent with these findings and underscore the importance of the use of newer markers for CVD risk assessment in obese adolescents.

The significant p for trend in CRP levels among the three groups of BMI shows that modest changes in BMI do affect CVD risk favorably. Cross-sectional studies in adolescents report a strong association between inflammation and severity of obesity [22], [23]. And, a decrease in CRP levels has been reported in adolescents with a significant (10%) decrease in BMI [21]. In adults, prospective studies show elevated CRP levels to be predictive of CVD in both healthy subjects and those with past history of CVD [34], [35]. As adolescent obesity is associated with early atherogenesis [36], improvement in CRP levels with modest decreases in BMI will lead to improvement in CVD risk profile.

Like previous studies [37], we found that the association between CRP and BMI persisted after adjustment for age, sex and ethnicity. This association, independent of demographic variables indicates the potential value of using this marker to compare CVD risks among different populations.

Our study sample demonstrated high insulin resistance with 80% subjects having elevated HOMA-IR levels. Although there is an increase in insulin resistance during mid-puberty secondary to changes in sex hormones, growth hormones and redistribution of body fat [38], it is also linked independently to overweight [39] and obesity [40] and increases CVD risk [39], [41], [42]. As more than 70% of our subjects were in late puberty (defined as Tanner stages 4 and 5 by breast and genital development), the direct effect of adiposity is more likely responsible for the elevated insulin resistance noted in our sample. This is confirmed by the direct correlation between both baseline HOMA-IR and insulin with BMI, and the significant association with BMI after adjusting for age, sex and race/ethnicity. Although the p for trend was not significant between change in HOMA-IR and groups of BMI change, the significant p for trend of change in insulin levels seen across the three groups of BMI change underscores the importance of modest BMI changes in improving measures of glucose metabolism in these adolescents with high CVD risk profiles.

We found that adolescents with a modest BMI decrease had a greater decrease in systolic blood pressure, whereas an increase was noted in those with a modest BMI increase. However, our study was not powered to detect statistical differences. An interesting observation was a decrease in diastolic blood pressure across all three groups of BMI change. Physical activity has been known to decrease blood pressure despite modest changes in weight in adolescents and adults [43], [44], [45]. It is possible that although a large number of participants did not show a change in BMI, the increase in physical activity by participation in the weight management program, led to a decrease in diastolic blood pressure. In addition the combined effect of physical activity and weight loss led to a greater decrease in systolic blood pressure in teens with modest decrease in BMI.

Our findings need to be considered in light of certain limitations. Our high attrition rate with 60% subjects returning for reevaluation decreased the power to detect associations with BMI change. However, we did have sufficient power to detect differences in both cholesterol and HDL levels which were not seen. This suggests that modest changes in BMI are more closely associated with changes in measures of inflammation and glucose metabolism than lipid metabolism. Also, our analysis looks at a six-month change in markers of CVD risk with change in BMI. A longer time interval, with larger changes in BMI from baseline, might show changes in other biomarker levels. In future studies, a direct measure of atherogenesis to evaluate if changes in CVD risk markers are directly associated with change in CVD risk.

Despite these limitations, by performing a longitudinal assessment in this group of severely obese African American and Hispanic adolescents who were participating in a weigh management program in a real-world setting, we were able to demonstrate significant improvement in insulin levels and inflammation as measured by CRP, with modest changes in BMI. As the prevalence of obesity continues to increase in African American and Hispanic adolescents, these results provide clinicians with encouragement to continue to offer lifestyle interventions to obese youth even if only modest BMI changes are achieved from these efforts.

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PII: S1871-403X(10)00011-6

doi:10.1016/j.orcp.2010.03.001

Obesity Research & Clinical Practice
Volume 4, Issue 3 , Pages e231-e237, July 2010

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