Published online before print September 21, 2006, doi: 10.1161/01.ATV.0000245804.56871.31
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© 2006 American Heart Association, Inc.
Atherosclerosis and Lipoproteins |
Relationship Between Lipid Abnormalities and Insulin Resistance in Japanese School Children
From the Department of Child Health and Welfare, Faculty of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan.
Correspondence to Dr Takao Ohta, Department of Pediatrics, Faculty of Medicine, University of the Ryukyus, 207 Uehara, Nishihara, Okinawa, 903-0125 Japan. E-mail tohta{at}med.u-ryukyu.ac.jp
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Abstract |
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Objective— Dyslipidemia and insulin resistance (IR) are risk factors for coronary heart disease (CHD) in adults. To help prevent the development of CHD, it may be useful to understand the relationship between lipid abnormalities and IR during childhood.
Methods and Results— IR was assessed by the homeostasis model approximation index. We studied 1175 Japanese school children (642 boys and 533 girls), aged between 7 and 12 years. Obesity was defined by the body mass index standard deviation score (BMISD) (obese: BMISD 
2.0). BMISD was most significantly associated with IR in nonobese children (P=0.000). Associations of IR with lipid-related parameters were affected by BMISD. After being corrected by BMISD, in nonobese children, log triglycerides (TG), apoB and low-density lipoprotein (LDL) size in boys and log TG, LDL size, and high-density lipoprotein (HDL) cholesterol in girls were still significantly associated with IR (P=0.000 to 0.017). In obese children, all parameters except for LDL cholesterol in boys and LDL size in girls were significantly associated with IR (P=0.000 to 0.030). Multiple regression analysis showed that log TG and LDL size in nonobese children, log TG in obese boys and LDL size in obese girls were independently associated with IR. Children with IIb and IV hyperlipidemia had significantly higher IR than those with normolipidemia and IIa, even after correcting for BMISD and age.
Conclusion— Our results suggest that in addition to controlling body weight, it may be important for school children to characterize lipid phenotypes to prevent progression to CHD and/or type 2 diabetes and to identify subjects who are at high risk for these disorders.
Dyslipidemia and insulin resistance (IR) are risk factors for coronary heart disease (CHD) in adults. To help prevent the development of CHD, it may be useful to understand the relationship between lipid abnormalities and IR during childhood. Our results suggest that in addition to controlling body weight, it may be important for school children to characterize lipid phenotypes to prevent progression to CHD and/or type 2 diabetes and to identify subjects who are at high risk for these disorders.
Key Words: hyperlipidemia • insulin resistance • obesity • school children • type 2 diabetes
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Introduction |
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Dyslipidemia, insulin resistance (IR), and obesity are risk factors for atherosclerotic coronary heart disease (CHD) in adults.1,2 Pathologically, atherosclerotic changes in coronary arteries originate during childhood, and the extent of atherosclerotic lesions in children and adolescent increases with the number of risk factors.3,4 In our previous study, we showed the prevalence of dyslipidemia was 1.91% (familial hypercholesterolemia [FHD]: 0.19%, IIa: 0.87%, IIb: 0.26%, IV: 0.20%, low high-density lipoprotein [HDL]: 0.39%) in preschool Japanese children and children with dyslipidemia had more family or genetic background than adults.5 Okada et al reported that >10% of Japanese school children had hypercholesterolemia (IIa and IIb).6 Although these studies were performed in different regions, the prevalence of hypercholesterolemia in school children was much higher than that in preschool children. This suggests that the expression of hypercholesterolemia is severely affected by nongenetic factors (environmental factors). Among Japanese school children, the prevalence of type 2 diabetes increased from 0.2 to 7.3 per 100 000 children per year between 1976 and 1995.7 The increase was attributed to changing dietary patterns and increase rates of obesity among these children.7 Obese children have a higher prevalence of IR, type 2 diabetes, and dyslipidemia.8,9 IR is also risk factor for impaired glucose tolerance and type 2 diabetes, even in children.8 Furthermore, dyslipidemia, IR, and obesity are core phenotypes of the metabolic syndrome.10–12 Thus, it seems important to clarify the relationship between dyslipidemia, IR, and obesity in children.
The metabolic syndrome is becoming a common disorder even in children, because of the increasing prevalence of obese children.13–15 To help prevent the future development of CHD or type 2 diabetes, it is reasonable to identify children who are at high risk for these disorders. In the present study, as a first step in detecting a high-risk group, we investigated the relationship between dyslipidemia, IR, and obesity in Japanese school children.
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Methods |
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Subjects
The present study was approved by the Review Board of the University of the Ryukyus. Informed consent was obtained from the parents of all of the children. We studied 1175 Japanese children (642 boys and 533 girls) aged 7 to 12 years, who underwent screening and were enrolled in a care program for lifestyle-related diseases since 2001 in Okinawa, Japan. Sex maturity stages in the children studied were equal to or less than Tanner Stage 3. The subjects were not patients who visited our hospital. Body mass index (BMI) was calculated as weight [kg]/height2 [m2]. BMI standard deviation scores (BMISD) adjusted for age and sex were obtained based on data on Japanese school children provided by the Ministry of Education, Culture, Sports, Science, and Technology (unpublished data). Obesity was defined as BMISD
2.0. None of the children studied were receiving therapy for weight reduction or drugs that might affect lipid metabolism. None had a smoking habit. Venous blood was drawn after an overnight fast.
Laboratory Measurements
Serum insulin was measured by 2-step sandwich enzyme-linked immunosorbent assay (SRL, Inc, Hachioji, Japan). Routine chemical methods were used to determine the serum concentrations of total cholesterol (TC), HDL cholesterol (HDL-C), triglycerides (TG), and glucose. Low-density lipoprotein cholesterol (LDL-C) was calculated as [TC – HDL-C – TG/5]. Apolipoprotein B (apoB) was measured by the turbidity immunoassay method.16 IR and insulin sensitivity were calculated using the homeostasis model approximation index (HOMA-R) and the quantitative insulin-sensitivity check index (QUICKI).17,18 LDL size was evaluated by electrophoresis in nondenaturing polyacrylamide gradient gels on precast MULTIGEL-LP (2% to 15%) according to the procedure specified by the manufacturer (Daiichi Pure Chemicals Co, LTD, Tokyo, Japan). Standards used for size calibration included latex beads (37 nm) (Dow Chemical Company) and high-molecular-weight standards (Pharmacia). The stained gels were scanned with a laser scanning densitometer to provide a quantitative measurement of the size of the peak and its distance from the origin. Particle diameter was calculated from a plot of the log of the known diameters of the standards (latex beads 37 nm, thyroglobulin 17.0 nm, apoferritin 12.2 nm) on the y-axis against their positions from the origin of the gel (Rf) on the x-axis.
Statistical Evaluation
The significance of differences in clinical and chemical data between nonobese and obese children were determined by the Mann-Whitney U test. The distributions of HOMA-R and levels of insulin and triglyceride were markedly skewed. Thus, these parameters were normalized by log-transformation. Pearson and partial correlation coefficients were then computed to assess the associations between log HOMA-R and various parameters. A stepwise multiple regression analysis was performed by entering the independent variable with the highest partial correlation coefficient at each step, until no variable remained with an F value of 4. Age-adjusted and BMISD-adjusted differences in parameters among subjects with normal, IIa, IIb, and IV were determined by an analysis of covariance. Parameters in these 4 groups were compared using Scheffe’s multiple comparison test. Group differences or correlations with P<0.05 were considered to be statistically significant.
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Results |
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As shown in Table 1, adiposity-related differences were found in all of the parameters studied. Obese children showed more atherogenic lipid and apolipoprotein profiles and greater IR than nonobese children. Thus, we separated the data for nonobese and obese children in the following analysis. Tables 2 and 3
show Pearson and partial correlations between IR (log HOMA-R) and the other parameters studied. In nonobese boys, log HOMA-R was correlated with all of the parameters listed (P=0.000). In obese boys, log HOMA-R was correlated with BMISD, log TG, apoB and HDL-C (P=0.000 to 0.002). After being corrected by age and BMISD, log HOMA-R was correlated with log TG, apoB, and LDL size in nonobese boys (P=0.000 to 0.017). In obese boys, all parameters except for LDL-C were correlated with log HOMA-R (P=0.000 to 0.010), even after being corrected by BMISD and age. Age, BMISD, TC, log TG, LDL-C, LDL size, and HDL cholesterol (HDL-C) in nonobese girls and age, BMISD, and LDL size in obese girls were significantly correlated with log HOMA-R (P=0.002 to 0.003). After being corrected by age and BMISD, log TG, LDL size, and HDL-C in nonobese girls and LDL size in obese girls were significantly correlated with log HOMA-R (P=0.000 to 0.024). Because each of these parameters can potentially contribute directly to the regulation of log HOMA-R, we performed a stepwise multiple regression analysis with log HOMA-R as the dependent variable and the other parameters listed in Tables 2 and 3 as independent variables. In nonobese boys, BMISD had the most significant association with log HOMA-R and accounted for 45.8% of the variability in log HOMA-R. Age, log TG, and LDL size had additional effects (6.2%, 2.7%, and 1.3%, respectively) (Table 4). In obese boys, log TG had the most significant association with log HOMA-R and accounted for 20.6% of the variability in log HOMA-R. BMISD had an additional effect (6.6%). In nonobese girls, BMISD had the most significant association with log HOMA-R and accounted for 32.7% of the variability in log HOMA-R. Age, log TG, and LDL size had additional effects (20.8%, 2.1%, and 1.1%, respectively) (Table 4). In obese girls, age had the most significant association with log HOMA-R and accounted for 17.1% of the variability in log HOMA-R. BMISD and LDL size had additional effects (11.3% and 4.5%, respectively).
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To elucidate the relationship between lipid phenotypes and IR, we divided school children into normolipidemia (NL) and type IIa (IIa), IIb, and IV hyperlipidemia groups. We defined hyperlipidemia based on serum lipid levels in Japanese school children.6 When serum concentrations of TC, TG, and LDL-C were >90th percentiles for the respective age-matched and gender-matched values, we considered the children to be hyper TC, hyper TG, and hyper LDL-C (IIa, hyper LDL-C alone; IIb, hyper LDL-C and hyper TG; IV, hyper TG alone). NL was defined as serum concentrations of LDL-C and TG of <90th percentiles. Table 5 shows BMISD-adjusted and age-adjusted chemical parameters in children with NL, IIa, IIb, and IV. In boys, serum concentrations of HDL-C in IIb and IV were significantly lower than those in NL and IIa (P<0.0001). LDL sizes in IIb and IV were significantly smaller than that in NL (P<0.05 to 0.0001). LDL size in IIb was significantly smaller than that in IIa (P<0.001). Serum concentrations of glucose were significantly higher in IIa and IIb than in NL (P<0.01). Serum concentrations of insulin and the levels of HOMA-R in IIa, IIb, and IV were significantly higher than those in NL and those in IIb and IV were significantly higher than those in IIa (P<0.01 to 0.0001). Differences between IIb and IV were not significant. The levels of QUICKI in IIa, IIb, and IV were significantly lower than that in NL (P<0.0001). Those in IIb and IV were significantly lower than that in IIa (P<0.0001). In girls, serum concentrations of HDL-C in IIb and IV were significantly lower than those in NL and IIa (P<0.0001). The difference between IIb and IV was not significant. LDL size in IIb and IV were significantly smaller than those in NL and IIa (P<0.05 to 0.0001). Serum concentrations of glucose were similar in all groups. Serum concentrations of insulin and the levels of HOMA-R in IIb and IV were significantly higher than those in NL and IIa (P<0.01 to 0.0001). Differences between IIb and IV were not significant. The levels of QUICKI in IIb and IV were significantly lower than those in NL and IIa (P<0.0001). Those in IIb and IV were significantly lower than that in IIa (P<0.0001). The difference between IIb and IV was not significant.
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Discussion |
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Because the sample size in our study was large (total number of subject 1175), IR and insulin sensitivity were determined by HOMA-R and QUICKI, respectively. The accuracy and precision of HOMA-R and QUICKI as measures of IR and insulin sensitivity have been determined elsewhere by comparison with euglycemic and hyperglycemic clamps and the intravenous glucose tolerance test.17,18 Recent data have shown that these indices are reliably sensitive and specific for evaluating IR even in children.19,20 In the present study, we have shown that: (1) associations of IR (HOMA-R) with parameters of lipids and lipoproteins were affected by BMISD and age in our school children; (2) BMISD had the most significant association with IR in nonobese children. Among lipids and lipoprotein parameters, TG and LDL size were significantly associated with IR. Especially, TG had the most significant association with IR in obese boys. In obese girls, age had the most significant association with IR. Only LDL size among lipids and lipoprotein parameters was significantly associated with IR; and (3) both boys and girls with IIb and IV hyperlipidemia had significantly higher IR than those with IIa and NL.
Insulin regulates many aspects of lipoprotein metabolism. Resistance to the normal actions of insulin causes the hepatic overproduction of TG and apoB, which thereby enhances the secretion of very low-density lipoproteins from the liver.21 In addition, IR decreases lipoprotein lipase activity, resulting in a delayed clearance of TG-rich lipoproteins.22 It is generally believed that a delayed clearance of TG-rich lipoprotein is associated with the generation of small dense LDL and lower concentrations of HDL-C.23,24 IR was significantly correlated with TG, apoB, HDL-C, and LDL size in our school children. Taken together, these findings suggest that IR may play an important role in lipid metabolism even in school children. However, BMISD and age were also significantly associated with IR in our school children. Adiposity, especially the accumulation of visceral fat, increases intraportal free fatty acid (FFA) levels and flux, thereby inhibiting insulin clearance and promoting IR.25 In addition, an increased or decreased in the secretion of adipocytokines form adipocytes, such as leptin, tumor necrosis factor (TNF)-
, adiponectin, etc., may cause IR.26–28 An age-related reduction in insulin receptor expression has also been reported.25 Thus, to exclude effects of adiposity and age, BMISD and age were adjusted for by partial correlation. Because age did not affect the relationship between insulin resistance and lipid-related parameters (data not shown), the partial correlation in Tables 2 and 3
reflected the effect of BMISD. After being corrected by BMISD, correlations between IR and lipid-related parameters were weakened in girls and nonobese boys, and strengthened in obese boys (Tables 2 and 3). Although several parameters were significant after being corrected by BMISD, multiple regression analysis showed that only two (TG and/or LDL size) were independently associated with IR in our school children (Table 4). However, these parameters can only account for 3.3% to 4.5% of the variability in IR in girls and nonobese boys. In contrast, TG in obese boys was the strongest predictor for IR and accounted for 20.6% of the variability in IR. These findings suggest that weight gain (adiposity) can mostly explain the relationship between IR and lipid-related parameters in girls and nonobese boys. However, in obese boys, TG metabolism might be more important for IR than adiposity. Although further studies are needed, genetic factors may exacerbate TG metabolism (overproduction of very low-density lipoprotein or delayed clearance of TG-rich lipoprotein) in obese boys.
The question is whether increased TG or decreased LDL size precedes or follows IR. As mentioned, IR itself can induce hypertriglyceridemia and make LDL size smaller.21–24 A substantial reduction of serum TG levels with fibrate treatment did not improve IR.29,30 Improvement of IR reduced small dense LDL particles.31 To date, no data are available on whether the improvement of LDL size can affect IR. Interestingly, the state of insulin resistance in familial combined hyperlipidemia (FCHL) is associated with the lipid phenotype.32 Subjects with FCHL based on hyper TG (IV) or combined hyperlipidemia (IIb) are more insulin-resistant than FCHL subjects based on hyper TC (IIa) even after correcting for BMI.32 As in FCHL, school children with IIb and IV showed more IR and smaller LDL size than those with NL and IIa (Table 5). Because a family study was not performed in the present study, we could not diagnose FCHL in our school children. However, the characteristics of school children with IIb and IV were very similar to those of FCHL patients. In addition, as shown in our previous study, most young children (preschool) with IIb were FCHL based on a familial study.5 Taken together, these results might extend our previous finding (ie, that most young children with IIb are FCHL) to school children. If our notion is valid, a genetic background that regulates serum TG and/or LDL size such as in FCHL might contribute to the relationship between TG, LDL size, and IR. Weight gain may exacerbate IR and lipid abnormalities in these children.
With respect to the differences between boys and girls, it is well known that sex hormone affect the lipid metabolism. Because most of our children were pre-puberty, we did not measure sex hormone. However, age was strongly associated with IR especially in girls. This may suggest that subtle change of sex hormone may be responsible for the gender differences of our data. Further studies are needed to clarify a complex interplay between sex hormone, BMI, and insulin action.
In conclusion, TG and/or LDL size were significantly associated with IR, and lipid phenotypes (IIb and IV) showed higher IR, but neither of these associations could be fully explained by their BMISD. School children with types IIb and IV showed characteristics similar to those in subjects with FCHL. Thus, it is important for school children to control body weight to prevent progression to the metabolic syndrome and a familial study should be performed in children with IIb and IV to screen for those at high risk for CHD and/ or type 2 diabetes.
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Acknowledgments |
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Sources of Funding
This work was supported by Health Sciences Research Grants (Research on Specific Diseases) from the Ministry of Health, Labor and Welfare and by a grant-in-aid for Scientific Research (B:17390303) from the Ministry of Education, Culture, Sports, Science, and Technology.
Disclosures
None.
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Footnotes |
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Original received April 27, 2006; final version accepted August 25, 2006.
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