Behavior of insulin resistance and its metabolic correlates in prepubertal children: a longitudinal study (EarlyBird 32)

Insulin sensitivity from preschool to school age in patients with severe obesity

Background

Insulin sensitivity decreases at puberty transition, but little information has been provided on its earlier time-course. Aim of the present study was to describe the time-course of insulin sensitivity in severely obese children at the transition from preschool to school age.

Research design and methods

Retrospective study of a cohort of 47 severely obese [Body Mass Index (BMI) ≥99° percentile] preschoolers evaluated twice, once between 2 and 6 years of age, and once before age 8. Glucose tolerance, Whole Body Insulin Sensitivity Index (WBISI), Insulinogenic Index (IGI); β-cell demand index (BCDI) and Insulin Secretion-Sensitivity Index 2 (ISSI-2) were longitudinally estimated during the oral glucose tolerance test.

Results

After a median follow-up of 2.23 (1–4.52) y, obese patients showed significant decrease in WBISI (p<0.0001), and increase in fasting (p = 0.005) and 2 h glucose (2HG, p = 0.001). One child in preschool age and 4 school age children presented with 2HG between 7.8–11.1 mmol/l. Best predictors of WBISI, 2HG and BCDI in the school age were changes in BMI z-score (R² = 0.309; p = 0.002; β = −0.556), ISSI-2 (R² = 0.465; p<0.0001; β = −0.682), and BMI z-score (R² = 0.246; p = 0.008; 0.496), respectively.

Conclusions

In morbidly obese children, insulin sensitivity seems to decline even before pubertal transition, but changes in total adiposity can only partially explain this variation.

Effects of changes in adiposity and physical activity on preadolescent insulin resistance: the Australian LOOK longitudinal study

Background

In a previous longitudinal analysis of our cohort as 8 to 10 year-olds, insulin resistance (IR) increased with age, but was not modified by changes in percent body fat (%BF), and was only responsive to changes in physical activity (PA) in boys. We aimed to determine whether these responses persisted as the children approached adolescence.

Methods

In this prospective cohort study, 256 boys and 278 girls were assessed at ages 8, 10 and 12 years for fasting blood glucose and insulin, %BF (dual energy X-ray absorptiometry); PA (7-day pedometers), fitness (multistage run); and pubertal development (Tanner stage).

Results

From age 8 to 12 years, the median homeostatic model of IR (HOMA-IR) doubled in boys and increased 250% in girls. By age 12, 23% of boys and 31% of girls had elevated IR, as indicated by HOMA-IR greater than 3. Longitudinal relationships, with important adjustments for covariates body weight, PA, %BF, Tanner score and socioeconomic status showed that, on average, for every 1 unit reduction of %BF, HOMA-IR was lowered by 2.2% (95% CI 0.04–4) in girls and 1.6% (95% CI 0–3.2) in boys. Furthermore, in boys but not girls, HOMA-IR was decreased by 3.5% (95%CI 0.5–6.5) if PA was increased by 2100 steps/day.

Conclusion

Evidence that a quarter of our apparently healthy 12 year-old Australians possessed elevated IR suggests that community-based education and prevention strategies may be warranted. Responsiveness of IR to changes in %BF in both sexes during late preadolescence and to changes in PA in the boys provides a specific basis for targeting elevated IR. That body weight was a strong covariate of IR, independent of %BF, points to the importance of adjusting for weight in correctly assessing these relationships in growing children.

Contrasting longitudinal and cross-sectional relationships between insulin resistance and percentage of body fat, fitness, and physical activity in children-the LOOK study

BACKGROUND

Knowledge of individual changes in insulin resistance (IR) and longitudinal relationships of IR with lifestyle-associated factors are of important practical significance, but little longitudinal data exist in asymptomatic children. We aimed to determine (a) changes in the homeostatic model of insulin resistance (HOMA-IR) over a 2-yr period and (b) comparisons of longitudinal and cross-sectional relationships between HOMA-IR and lifestyle-related risk factors.

METHODS

Our subjects, 241 boys and 257 girls, were assessed at age 8.1 yr (SD 0.35) and again 2 yr later for fasting blood glucose and insulin, dual X-ray absorptiometry-assessed percentage of body fat (%BF), pedometer-assessed physical activity (PA), and cardio-respiratory fitness (CRF) by multistage running test.

RESULTS

HOMA-IR was initially 9% greater in girls than boys and 27% greater 2 yr later. There was no evidence of longitudinal relationships between HOMA-IR and %BF in boys or girls, despite significant cross-sectional relationships (p < 0.001). In boys, there was evidence of a longitudinal relationship between HOMA-IR and both PA (p < 0.001) and CRF (p = 0.05). In girls, we found a cross-sectional relationship between HOMA-IR and CRF (p < 0.001).

CONCLUSIONS

HOMA-IR increases between 8 and 10 yr of age and to a greater extent in girls. Longitudinal, unlike cross-sectional, relationships do not support the premise that body fat has any impact on HOMA-IR during this period or that PA or CRF changes affect HOMA-IR in girls. These data draw attention to difficulties in interpreting observational studies in young children.

Insulin sensitivity in prepubertal Caucasian normal weight children

BACKGROUND

Determining whether or not a child is insulin resistant is becoming a matter of fundamental interest even in childhood, as the incidence of metabolic complications of insulin resistance is rising. Thus reference values are needed.

AIM

To set percentiles for HOMA-IR and WBISI in Caucasian normal weight prepubertal children.

POPULATION

238 normal weight prepubertal Caucasian children (126 males/112 females).

METHODS

After physical examination including anthropometric measurements all children underwent an oral glucose tolerance test from which HOMA-IR and WBISI were calculated.

RESULTS

HOMA-IR values above the 95th percentile (2.03) and WBISI values below the 5th percentile (5.67) represent the cut-off values for the determination of insulin resistance.

CONCLUSION

These reference values are useful to easily detect insulin resistance within the prepubertal Caucasian population representing a helpful tool for clinicians to target such children in order to improve insulin sensitivity.

Distribution of adiponectin, leptin, and metabolic correlates of insulin resistance: a longitudinal study in British children; 1: Prepuberty (EarlyBird 15)

BACKGROUND

The emergence of type 2 diabetes in young populations has mirrored a rising prevalence of obesity and insulin resistance during childhood and adolescence. At the same time, the role of adipokines as links between obesity and insulin resistance is becoming more appreciated. We sought to establish age- and sex-specific distributions of metabolic correlates of insulin resistance in healthy prepubertal children.

METHODS

We collected fasting blood samples from a contemporary cohort of 307 British children at ages 5, 6, 7, and 8 years and measured insulin, glucose, triglycerides, total and HDL cholesterol, urate, glycohemoglobin, sex hormone-binding globulin (SHBG), leptin, and adiponectin. We used homeostasis model assessment (HOMA 2) to estimate insulin sensitivity (HOMA-%S) and beta-cell function (HOMA-%B). Anthropometric measures included body mass index.

RESULTS

Body mass index increased from age 5 to 8 years (P < 0.001). HOMA-%B decreased (P < 0.001) and HOMA-%S increased (P < 0.05), but glucose also increased (P < 0.001) whereas glycohemoglobin decreased (P < 0.001). Consistent with the rise in insulin sensitivity, HDL cholesterol increased (P < 0.001) and triglycerides decreased (NS), whereas adiponectin decreased (P = 0.02). The patterns were similar in boys and girls, although girls were less insulin sensitive throughout. Accordingly, triglycerides tended to be higher in the girls, and HDL cholesterol and SHBG lower.

CONCLUSIONS

The metabolic disturbances associated with insulin resistance appear to be more advanced in girls. Markers of metabolic health improve in both sexes from 5 to 8 years, despite rising adiposity.

Trends, associations and predictions of insulin resistance in prepubertal children (EarlyBird 29)

BACKGROUND

Rising obesity has been observed in all age groups. Anthropometric cut-points have been used to predict metabolic risk in children, although they are not based on known outcomes.

AIM

We examined the trends, associations and predictions of metabolic health from anthropometry in prepubertal children.

METHOD

Three hundred and seven healthy children were examined annually between 5 and 8 yr.

MEASURES

height, weight, body mass index (BMI), sum of skinfold thickness at five sites (SSF) and waist circumference (WC).

OUTCOME MEASURES

homeostasis model assessment of insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG).

RESULTS

Two hundred and thirty-one [131 boys (B) and 100 girls (G)] children had complete data sets at all four time points. (i) All measures of adiposity rose from 5 to 8 yr (BMI - B: +3.4%, G: +5.7%; WC - B: +10.4%, G: +11.8%; SSF - B: +23.3%, G: +30.7%, all p < 0.001). HOMA-IR unexpectedly fell (B: -16.6%, p = 0.01; G: -32.5%, p < 0.001). This fall was significant between 5 and 6 yr in both genders (5-6 yr - B: -17.8%, p < 0.001; G: -20.0%, p = 0.002) and between 6 and 7 yr in girls only (6-7 yr - B: -10.8%, p = 0.12; G: -19.2%, p = 0.001). HDL-C rose (B: +17.8%, G: +17.1%, both p < 0.001) and TG fell (B: -4.8%, p = 0.16; G: -11.6%, p = 0.006). (ii) Correlations between insulin resistance (IR) and anthropometry were poor at 5 yr but strengthened by 8 yr (BMI - B: r = 0.20/0.38, G: r = 0.28/0.49; WC - B: r = 0.25/0.40, G: r = 0.32/0.58; SSF - B: r = 0.11/0.36, G: r = 0.18/0.53). (iii) In girls, but not boys, adiposity at 5 yr predicted IR better at 8 yr (BMI - r(2 )= 0.17; WC - r(2 )= 0.28; SSF - r(2 )= 0.17, all p < 0.001) than it did at 5 yr (BMI - r(2 )= 0.08, p < 0.01; WC - r(2 )= 0.10, p < 0.01; SSF - r(2 )= 0.03, p = 0.07).

CONCLUSIONS

Cross-sectional association cannot indicate direction of trend or predict the future. Predicting metabolic health from anthropometric measures in prepubertal children requires longitudinal data, tracking variables from childhood into adulthood. Until the data set reaches adulthood, it is probably not safe to make recommendations on which children to 'target' or whether early intervention would be of benefit.