Stability of the factorial structure of metabolic syndrome from childhood to adolescence: a 6-year follow-up study

Social jetlag is associated with adverse cardiometabolic latent traits in early adolescence: an observational study

Introduction

Adolescence is marked by physiological and social changes, such as puberty, increased responsibilities and earlier school start times. This often leads to insufficient sleep on school nights and the need to compensate for lost sleep on weekends, causing a misalignment between biological and social times, which has been termed social jetlag (SJL). SJL triggers stress responses and is associated with several negative health outcomes, including higher cardiometabolic risk in adults. In adolescence, however, SJL has only been consistently related to increases in adiposity but its association with other cardiometabolic indicators are unclear.

Method

In a sample of 278 healthy early adolescents (9-15 years of age; 168 girls) we investigated: 1) whether self-reported SJL is associated (using path analyses) with a cardiometabolic status latent factor obtained by testing the best fitting model via confirmatory factor analyses from an initial set of eight indicators [body mass index (BMI), waist/height ratio, triglyceride concentration, diastolic and systolic blood pressure, glycated hemoglobin, total cholesterol/high-density lipoprotein ratio (chol/HDL), and % body fat]; and 2) whether age and/or pubertal status influence the association between SJL and cardiometabolic status.

Result

We found that, for girls, higher SJL was associated with more adverse cardiometabolic latent scores (the shared variance of BMI, waist/height ratio, chol/HDL and systolic blood pressure, which had acceptable model fit indices). However, the role of age and pubertal status in this association was unclear for both sexes.

Discussion

SJL was associated with adverse cardiometabolic latent traits beyond increases in adiposity in this observational study in early female adolescents. Because disruptions of circadian rhythms are believed to lead to dysregulated energy homeostasis and not vice-versa, our findings highlight the need for sleep interventions in adolescence to help reduce the global burden of cardiometabolic ill health, especially in girls.

Stability and Transformation of Metabolic Syndrome in Adolescents: A Prospective Assessment in Relation to the Change of Cardiometabolic Risk Factors

Underlying pathophysiological mechanisms drive excessive clustering of cardiometabolic risk factors, causing metabolic syndrome (MetS). MetS status may transform as adolescents transition to young adulthood. This study investigated the latent clustering structure and its stability for MetS during adolescence, and assessed the anthropometric and clinical metabolic determinants for MetS transformation. A community-based representative adolescent cohort (n = 1516) was evaluated for MetS using four diagnostic criteria, and was followed for 2.2 years to identify new-onset MetS. The clustering structure underlying cardiometabolic parameters was stable across adolescence; both comprised a fat—blood pressure (BP)—glucose three-factor structure (total variance explained: 68.8% and 69.7% at baseline and follow-up, respectively). Among adolescents with MetS-negative at baseline, 3.2–4.4% had incident MetS after 2.2 years. Among adolescents with MetS-positive at baseline, 52.0–61.9% experienced MetS remission, and 38.1–48.0% experienced MetS persistence. Increased systolic BP (SBP) was associated with a high MetS incidence risk, while decreased levels of SBP and glucose were associated with MetS remission. Compared with adolescents with a normal metabolic status at baseline, those with an initial abdominal obesity and increased triglycerides level had a 15.0- and 5.7-fold greater risk for persistent abnormality, respectively. Abdominal obesity and low high-density lipoprotein cholesterol are two abnormal MetS components that highly persist during adolescence, and are the intervention targets for reducing the future risk of cardiometabolic disorders.

Health-related physical fitness indicators and clustered cardiometabolic risk factors in adolescents: A longitudinal study

Background/Objective

This study examined relationships between health-related physical fitness indicators and clustered cardiometabolic risk factors in adolescents between 2014 and 2017.

Methods

The sample consisted of 93 students (60% girls), with complete data sets in both 2014 and 2017. The physical fitness components evaluated were: flexibility (sit and reach), muscular fitness (curl-up and push-up), cardiorespiratory fitness (progressive aerobic cardiovascular endurance run), and body fat (BMI). The cardiometabolic risk factors were: waist circumference, blood pressure, high-density lipoprotein cholesterol (HDL-C), triglycerides and fasting blood glucose. Z-scores were calculated for each risk factor, with the sum of risk factor z-scores values used to represent clustered cardiometabolic risk.

Results

The results of cross-sectional analysis indicated that muscle fitness (curl-up: β = −0.37, p < 0.001; push-up: β = −0.38, p < 0.005) and cardiorespiratory fitness (β = −0.56, p < 0.001) were inversely associated with clustered cardiometabolic risk, with BMI positively associated (β = 0.58, p < 0.001). In the longitudinal analysis, cardiorespiratory fitness (β = −0.33; p < 0.005) and body fat (β = 0.46, p < 0.001) demonstrated a significant association with clustered cardiometabolic risk. However, no significant associations between the health-related physical fitness and clustered cardiometabolic risk were observed after adjustment for baseline values.

Conclusion

Our cross-sectional findings highlight the importance of health-related physical fitness indicators to adolescents. In regarding the longitudinal analysis, further studies are needed in order to clarify the influence of physical fitness in the adolescence and cardiometabolic risk later in life.

Muscle strength field-based tests to identify European adolescents at risk of metabolic syndrome: The HELENA study

OBJECTIVES

To determine whether handgrip strength (HG) and/or standing long jump (SLJ) are capable of detecting risk of metabolic syndrome (MetS) in European adolescents, and to identify age- and sex-specific cut points for these tests.

DESIGN

Cross-sectional study.

METHODS

Participants included 969 (aged 12.5-17.5 years old) adolescents from 9 European countries (n = 520 girls). Absolute and relative HG and SLJ tests were used to assess upper and lower muscle strength, respectively. MetS status was determined using the age- and sex-specific cut points proposed by Jolliffe and Janssen´s, Additionally, we computed a continuous cardiometabolic risk index with the average z-score of four cardiometabolic risk factors: Wait circumference, mean arterial pressure, triglycerides/high-density lipoprotein cholesterol, and fasting insulin.

RESULTS

The prevalence of MetS was 3.1% in European adolescents. Relative HG and absolute SLJ were the best tests for detecting the presence of MetS (Area under the receiver operating characteristic (AUC) = 0.799, 95%CI:0.773-0.824; and AUC = 0.695 95%CI:0.665-0.724), respectively) and elevated cardiometabolic risk index (AUC = 0.873, 95%CI:0.838-0.902; and AUC = 0.728 95%CI:0.698-0.756), respectively) and, regardless of cardiorespiratory fitness. We provide age- and sex-specific cut points of upper and lower muscle strength for European adolescents to identify the presence of MetS and elevated cardiometabolic risk index.

CONCLUSIONS

The proposed health-related cut points could be used as a starting point to define health-related levels of upper and lower muscle strength in adolescents. Likewise, the diagnostic statistics provided herein can be used to offer feedback to adolescents, parents, and education and health professionals about what it means to meet or fail test standards.

Movement behaviors and cardiometabolic risk in schoolchildren

Growing evidence has accumulated in recent years showing that movement behaviors have important implications for health in children, especially for cardiovascular health, whose risk factors could track from childhood to adulthood. However, these findings are mixed and inconsistent in children. The aim of this study was to examine the relationship between different movement behaviors (sedentary behavior, physical activity and sleep duration) and cardiometabolic risk in schoolchildren. The study shows cross-sectional results of baseline measurement from 146 Spanish schoolchildren, aged 8-to-11 years old, participating in the MOVI-2 study. Movement behaviors were determined using accelerometry combined with self-reported sleep time. Cardiometabolic risk was assessed using a validated metabolic syndrome index. Logistic regression analysis showed that higher levels of vigorous physical activity (OR = 0.110, p = 0.004) and sleeping more than 9 hours (OR = 0.269, p = 0.015) could be protective factors against metabolic syndrome risk in children. ANCOVA analysis showed associations between vigorous physical activity and waist circumference (p < 0.001), and sleep time with insulin resistance (p = 0.017) and lipid profile (p = 0.035). No association was observed between light and moderate physical activity, sedentary behavior and metabolic syndrome (index and components). No statistically significant differences were found for blood pressure and any of the movement behaviors. Our data suggest that both the amount of vigorous physical activity accumulated and sleep duration are independently associated with higher cardiometabolic risk in children.

Does Cardiorespiratory Fitness Attenuate the Adverse Effects of Severe/Morbid Obesity on Cardiometabolic Risk and Insulin Resistance in Children? A Pooled Analysis

OBJECTIVE

To investigate 1) differences in cardiometabolic risk and HOMA of insulin resistance (HOMA-IR) across BMI categories (underweight to morbid obesity), 2) whether fit children have lower cardiometabolic risk/HOMA-IR than unfit children in each BMI category, and 3) differences in cardiometabolic risk/HOMA-IR in normal-weight unfit children and obese fit children.

RESEARCH DESIGN AND METHODS

A pooled study including cross-sectional data from three projects (n = 1,247 children aged 8-11 years). Cardiometabolic risk was assessed using the sum of the sex- and age-specific z scores for triglycerides, HDL cholesterol, glucose, and the average of systolic and diastolic blood pressure and HOMA-IR.

RESULTS

A significant linear association was observed between the risk score and BMI categories (P trend ≤0.001), with every incremental rise in BMI category being associated with a 0.5 SD higher risk score (standardized β = 0.474, P < 0.001). A trend was found showing that as BMI categories rose, cardiorespiratory fitness (CRF) attenuated the risk score, with the biggest differences observed in the most obese children (-0.8 SD); however, this attenuation was significant only in mild obesity (-0.2 SD, P = 0.048). Normal-weight unfit children had a significantly lower risk score than obese fit children (P < 0.001); however, a significant reduction in the risk score was found in obese fit compared with unfit children (-0.4 SD, P = 0.027). Similar results were obtained for HOMA-IR.

CONCLUSIONS

As BMI categories rose so did cardiometabolic risk and HOMA-IR, which highlights the need for obesity prevention/treatment programs in childhood. Furthermore, CRF may play an important role in lowering the risk of cardiometabolic diseases in obese children.

siMS Score: Simple Method for Quantifying Metabolic Syndrome

Objective

To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk.

Materials and Methods

Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TA_systolic/130—HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score.

Results

Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively).

Conclusions

siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.

Liver enzymes and clustering cardiometabolic risk factors in European adolescents: the HELENA study

OBJECTIVES

This study aimed to explore the associations of liver biomarkers with cardiometabolic risk factors and their clustering, and to provide reference values (percentiles) and cut-off points for liver biomarkers associated with high cardiometabolic risk in European adolescents.

METHODS

Alanine aminotransferase (ALT), gamma-glutamyltransferase (GGT), aspartate aminotransferase to ALT ratio (AST/ALT), waist circumference, blood pressure, triglycerides, high-density lipoprotein cholesterol and insulin were measured in 1084 adolescents. We computed a continuous cardiometabolic risk score and defined the high cardiometabolic risk.

RESULTS

Higher ALT and GGT and lower AST/ALT were associated with adiposity and with the number of adverse cardiometabolic risk factors (Ps < 0.05). Higher GGT and lower AST/ALT were associated with higher cardiometabolic risk score (Ps < 0.001) in males and females, and ALT only in males (Ps < 0.001). Gender- and age-specific percentiles for liver biomarkers were provided. Receiver operating characteristic analyses showed a significant discriminatory accuracy of AST/ALT in identifying the low/high cardiometabolic risk (Ps < 0.01) and thresholds were provided.

CONCLUSIONS

Higher GGT and lower AST/ALT are associated with higher cardiometabolic risk factors and their clustering in male and female European adolescents, whereas the associations of ALT were gender dependent. Our results suggest the usefulness of AST/ALT as a screening test in the assessment of adolescents with high cardiometabolic risk and provide gender- and age-specific thresholds that might be of clinical interest.

Probing the factor structure of metabolic syndrome in Sardinian genetic isolates

BACKGROUND AND AIMS

Owing to the multiplicity of the key components of metabolic syndrome (MetS), its diagnosis is very complex. The lack of a unique definition is responsible for the prevalence variability observed among studies; therefore, a definition based on continuous variables was recommended. The aim of this study was to compare competing models of the MetS factor structure for selecting the one that explains the best clustering pattern and to propose an algorithm for computing MetS as a continuous variable.

METHODS AND RESULTS

Data were from isolated Sardinian populations (n = 8102). Confirmatory factor analysis (CFA) and two-group CFA by gender were performed to evaluate the sex-specific factor structure of MetS. After selecting the best model, an algorithm was obtained using factor loadings/residual variances. The quality of the MetS score was evaluated by the receiver operating characteristics curve and the area under the curve. Cross-validation was performed to validate the score and to determine the best cut point. The best fit model was a bifactor one with a general factor (MetS) and three specific factors (f1: obesity/adiposity trait; f2: hypertension/blood pressure trait; and f3: lipid trait). Gender-specific algorithms were implemented to obtain MetS scores showing a good diagnostic performance (0.80 specificity and 0.80 sensitivity for the cut point). Furthermore, cross-validation confirmed these results.

CONCLUSION

These analyses suggested that the bifactor model was the most representative one. In addition, they provided a score and a cut point that are both clinically accessible and interpretable measures for MetS diagnosis and likely useful for evaluating the association with adverse cardiovascular disease and diabetes and for investigating the MetS genetic component.

Validation of metabolic syndrome score by confirmatory factor analysis in children and adults and prediction of cardiometabolic outcomes in adults

AIMS/HYPOTHESIS

We validated the metabolic syndrome (MetS) score by confirmatory factor analysis (CFA) in children, middle-aged men, and older women and men and by investigating the relationships of the MetS score to incident type 2 diabetes, myocardial infarction, and cardiovascular and overall death in middle-aged men.

METHODS

We assessed the core features of MetS, calculated the MetS score using z scores for waist circumference, insulin, glucose, triacylglycerols, HDL-cholesterol and blood pressure, and carried out CFA to investigate whether MetS represents a single entity in population samples of 491 children, 1,900 middle-aged men, 614 older women and 555 older men from Finland. We also followed-up incident type 2 diabetes for 11 years and other outcomes for 17-18 years in middle-aged men.

RESULTS

We carried out second-order CFAs in which the MetS was represented by a second-order latent variable underlying four latent variables characterised by abdominal obesity, insulin resistance, dyslipidaemia and raised blood pressure in different age groups. These second-order factors and factors derived from first-order CFA using previously proposed models were strongly associated with a composite MetS score in all age groups (r = 0.84-0.94) and similarly predicted type 2 diabetes, cardiovascular outcomes and mortality in middle-aged men. The risk of type 2 diabetes, myocardial infarction, cardiovascular death and overall death increased 3.67-, 1.38-, 1.56- and 1.44-fold, respectively, for a 1 SD increase in the MetS score.

CONCLUSIONS

The MetS can be described as a single entity in all age groups. The MetS score is a valid tool for research evaluating cardiometabolic risk in different age groups. Further research is needed to define cut-off points for risk estimation in clinical practice.

Are field measures of adiposity sufficient to establish fatness-related linkages with metabolic outcomes in adolescents?

OBJECTIVE

To examine the associations between the adiposity-related information conveyed by field fatness measures: body mass index (BMI), waist circumference (WC) and sum of triceps and subscapular skinfolds (SUM SF) relative to dual-energy X-ray absorptiometry (DXA), beyond their common intercorrelations, with three important metabolic variables in US adolescents.

METHODS

We analyzed data on adiposity and insulin resistance (HOMA-IR), serum triglycerides (TGs) and total cholesterol (TC) from three US national surveys. In two-stage least-square modeling, we first calculated the common adiposity variance, and then used multivariate linear and quantile regressions to access residual associations with each measure.

RESULTS

Basic associations for each of the adiposity measures were similar but differences emerged in residual adiposity analyses scaled by s.d. units. While a 1 s.d. change in residual variance in DXA total fat beyond that accounted for by BMI (DXA|BMI) was strongly and significantly associated with all outcomes, associations with DXA accounting for SUM SF (DXA|SUM SF) and WC (DXA|WC) were weak or nonsignificant. Contrasted amongst themselves, the residual score association between BMI|SUM SF (β=0.06, P<0.0001) and HOMA-IR was weaker, and half as strong as that for the converse, SUM SF|BMI (β=0.13, P=0.020). SUM SF|WC was stronger than WC|SUM SF (β=0.08, P<0.0001 vs SUM SF|WC β=0.13, P<0.0001). Associations were similar for TGs and TC.

CONCLUSIONS

Laboratory methods like DXA offer minimal explanatory advantage over field methods in assessing adiposity-related contributions to metabolic outcomes in adolescents. Among the simple fatness measures, skinfolds convey additional information beyond BMI and WC when estimating associations both at the population mean and at the upper extremes of metabolic factors.

Prevalence of metabolic syndrome in a cohort of Chinese schoolchildren: comparison of two definitions and assessment of adipokines as components by factor analysis

BACKGROUND

Although attention to metabolic syndrome (MetS) in children has increased, there is still no universally accepted definition and its pathogenesis remains unclear. Our aim was to compare the current definitions of childhood MetS in a Chinese cohort and to examine the clustering pattern of MetS risk factors, particularly inclusion of leptin and adiponectin as additional components.

METHODS

3373 schoolchildren aged 6 to 18 years were recruited. Anthropometric and biochemical parameters and adipokines were measured. MetS was identified using both the International Diabetes Federation (IDF) and a modified Adult Treatment Panel III (ATP III) definitions. Exploratory factor analysis was performed to establish grouping of metabolic characteristics.

RESULTS

For children ≥ 10 years, the prevalence of MetS was 14.3% in the obese group and 3.7% in the overweight group according to the new IDF definition, and 32.3% in the obese group and 8.4% in the overweight group according to the modified ATPIII definition. Frequency of hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), impaired fasting glucose, elevated blood pressure, and central obesity according to the new IDF definition was 16.7%, 20.7%, 15.8%, 25.5% and 75.5% in obese boys and 14.7%, 24.0%, 12.0%, 11.0% and 89.0% in obese girls, respectively. Metabolic abnormalities in children under 10 years of age were also noted. Using factor analysis on eight conventional variables led to the extraction of 3 factors. Waist circumference (WC) provided a connection between two factors in boys and all three factors in girls, suggesting its central role in the clustering of metabolic risk factors. Addition of leptin and adiponectin also led to the extraction of 3 factors, with leptin providing a connection between two factors in girls. When using WC, mean arterial pressure, triglyceride/HDL-C ratio, HOMA-IR and leptin/adiponectin ratio as variables, a single-factor model was extracted. WC had the biggest factor loading, followed by leptin/adiponectin ratio.

CONCLUSIONS

MetS was highly prevalent amongst obese children and adolescents in this cohort, regardless of the definition used. Central obesity is the key player in the clustering of metabolic risk factors in children, supporting the new IDF definition. Moreover, our findings suggest that a common factor may underlie MetS. Leptin/adiponectin ratio as a possible component of MetS deserves further consideration.

Tracking of clustered cardiovascular disease risk factors from childhood to adolescence

BACKGROUND

Clustering of cardiovascular disease (CVD) risk factors has been found in children as young as 9 y of age. However, the stability of this clustering over the course of childhood has yet to be determined. The purpose of this study was to determine the tracking of clustered CVD risk from young school age through adolescence and to examine differences in tracking between levels of overweight/obesity and cardiorespiratory fitness (VO(2peak)).

METHODS

Beginning at 6 y, children (n = 434) were measured three times in 7 y. Anthropometrics, blood pressure, and VO(2peak) were measured. Fasting blood samples were analyzed for CVD risk factors. A clustered risk score (z-score) was constructed by adding sex-specific z-scores for blood pressure, homeostatic model assessment (HOMA-IR), triglyceride (TG), skinfolds, and negative values of high-density lipoprotein cholesterol (HDLc) and VO(2peak).

RESULTS

Significant tracking coefficients were found between clustered z-score at all time intervals (r = 0.514, 0.559, and 0.381 between ages 6-9, 9-13, and 6-13 y, respectively, all P < 0.0001). Tracking was higher for low-fit children, whereas no clear pattern was found for different levels of body fat.

CONCLUSION

We found that clustered z-score is a fairly stable characteristic through childhood. Implementation of preventive strategies could therefore start at early school age.

Early signs of atherosclerosis are associated with insulin resistance in non-obese adolescent and young adults with type 1 diabetes

Background

Patients with type 1 diabetes have a substantial risk of developing cardiovascular complications early in life. We aimed to explore the role of insulin sensitivity (S_i) as an early factor of atherosclerosis in young type 1 diabetes vs. non-diabetic subjects.

Methods

Forty adolescent and young adult individuals (20 type 1 diabetics and 20 non-diabetics), age 14–20 years, without characteristics of the metabolic syndrome, participated in this cross-sectional study. After an overnight fast, S_i was measured by hyperinsulinemic euglycemic clamp (40 mU/m²) and calculated by glucose infusion rate (GIR). Carotid intima-media thickness (cIMT) was measured in the common carotid artery with high-resolution ultrasonography. Risk factors of atherosclerosis (Body mass index [BMI], waist circumference, systolic blood pressure [sBP], triglycerides, low HDL-cholesterol and HbA_1c) were also investigated.

Results

cIMT was increased (0.52 ± 0.1 vs. 0.47 ± 0.1 mm, P < 0.01), whereas GIR was decreased (5.0 ± 2.1 vs. 7.1 ± 2.2 mg/kg/min, P < 0.01) in type 1 diabetics vs. non-diabetics. The differences in cIMT were negatively associated with S_i (r = −0.4, P < 0.01) and positively associated with waist circumference (r = 0.34, P = 0.03), with no such associations between BMI (r = 0.15, P = 0.32), sBP (r = 0.09, P = 0.58), triglycerides (r = 0.07, P = 0.66), HDL-cholesterol (r = 0.10, P = 0.55) and HbA_1c (r = 0.24, P = 0.13). In a multivariate regression model, between cIMT (dependent) and group (explanatory), only adjustment for S_i affected the significance (ß = 0.08, P = 0.11) vs. (ß = 0.07, P < 0.01) for the whole model. No interaction between cIMT, groups and S_i was observed.

Conclusions

cIMT is increased and associated with insulin resistance in adolescent, non-obese type 1 diabetic subjects. Although, no conclusions toward a causal relationship can be drawn from current findings, insulin resistance emerges as an important factor reflecting early signs of atherosclerosis in this small cohort.

A confirmatory factor analysis of the metabolic syndrome in adolescents: an examination of sex and racial/ethnic differences

Objective

The metabolic syndrome (MetS) is a cluster of clinical indices that signals increased risk for cardiovascular disease and Type 2 diabetes. The diagnosis of MetS is typically based on cut-off points for various components, e.g. waist circumference and blood pressure. Because current MetS criteria result in racial/ethnic discrepancies, our goal was to use confirmatory factor analysis to delineate differential contributions to MetS by sub-group.

Research Design and Methods

Using 1999–2010 data from the National Health and Nutrition Examination Survey (NHANES), we performed a confirmatory factor analysis of a single MetS factor that allowed differential loadings across sex and race/ethnicity, resulting in a continuous MetS risk score that is sex and race/ethnicity-specific.

Results

Loadings to the MetS score differed by racial/ethnic and gender subgroup with respect to triglycerides and HDL-cholesterol. ROC-curve analysis revealed high area-under-the-curve concordance with MetS by traditional criteria (0.96), and with elevations in MetS-associated risk markers, including high-sensitivity C-reactive protein (0.71), uric acid (0.75) and fasting insulin (0.82). Using a cut off for this score derived from ROC-curve analysis, the MetS risk score exhibited increased sensitivity for predicting elevations in ≥2 of these risk markers as compared with traditional pediatric MetS criteria.

Conclusions

The equations from this sex- and race/ethnicity-specific analysis provide a clinically-accessible and interpretable continuous measure of MetS that can be used to identify children at higher risk for developing adult diseases related to MetS, who could then be targeted for intervention. These equations also provide a powerful new outcome for use in childhood obesity and MetS research.

Bicycling to school is associated with improvements in physical fitness over a 6-year follow-up period in Swedish children

OBJECTIVE

To examine whether modes of commuting to school at baseline and changes in commuting were related to 6-year changes in cardiorespiratory fitness in youth.

METHODS

A total of 262 (142 girls) Swedish children (9 years at entry) were measured at baseline (1998/9) and follow-up (2004/5). Mode of commuting to school was assessed by questionnaire and fitness by a maximal bicycle test.

RESULTS

At baseline, 34% of children used passive modes of commuting (e.g., car, motorcycle, bus, train), 54% walked, and 12% bicycled to school. Six years later the percentage of bicyclists increased 19% and the percentage of walkers decreased 19%. On average, children who bicycled to school increased their fitness 13% (p=0.03) more than those who used passive modes and 20% (p=0.002) more than those who walked. Children who used passive modes or walked at baseline and bicycled to school at 6 years later increased their fitness 14% (p=0.001) more than those who remained using passive modes or walking at follow-up.

CONCLUSIONS

Implementing initiatives that encourage bicycling to school may be a useful strategy to increase cardiorespiratory fitness of children.