Body composition in offspring of New Zealand women: ethnic and gender differences at age 1-3 years in 2005-2009

Metformin in Gestational Diabetes The Offspring Follow Up (MiGTOFU): Associations between maternal characteristics and size and adiposity of boys and girls at nine years

Data from 98 women recruited in the Metformin in Gestational Diabetes trial and dual-energy X-ray absorptiometry studies of their children at nine years were analysed to investigate associations between maternal measures during pregnancy and their children's size and adiposity. Mothers of boys (n = 56) and girls (n = 42) had been randomised to metformin or insulin treatment at 30.1 ± 2.8 and 29.3 ± 4.1 weeks gestation, respectively. In boys, fat-free mass indexed to height squared was associated with maternal weight, body mass index, maternal glycaemia and metformin treatment. In boys and girls, fat mass indexed to height squared was associated with maternal glycaemia measures before gestational diabetes treatment.

Long-term effects of metformin use in gestational diabetes mellitus on offspring health

Metformin is the first-line drug for the treatment of type 2 diabetes mellitus, but its role in gestational diabetes mellitus (GDM) management is not clear. Recent evidence suggests a certain beneficial effect of metformin in the treatment of GDM, but a high treatment failure rate leads to the initiation of additional medications, such as insulin. Moreover, since metformin crosses the placental barrier and reaches a significant level in the fetus, it is likely to influence the fetal metabolic milieu. The evidence indicates the long-term safety in children exposed to metformin in utero except for mild adverse anthropometric profiles. Diligent follow-up of metformin-exposed offspring is warranted from the clinician’s point of view.

Short- and long-term outcomes of gestational diabetes and its treatment on fetal development

Globally the prevalence of gestational diabetes mellitus (GDM) is rising mainly due to the increase in maternal obesity. A number of different methods to screen for and diagnose GDM have been described although consensus on the preferred methods does not yet exist. GDM has significant short- and long-term health risks for the mother, developing fetus and the children born to mothers with GDM. Short-term risks for the fetus include macrosomia (excessive birthweight), shoulder dystocia, birth trauma, and hypoglycaemia in the immediate postpartum period. Long-term risks for offspring born to mothers with GDM include increased rates of childhood and adulthood obesity and an increased cardiometabolic risk. A number of pharmacological treatments for GDM have been identified, these include insulin and oral glucose-lowering drugs metformin and glibenclamide. Whilst these oral glucose-lowering drugs show similar short-term childhood outcomes to insulin there is increasing evidence that these drugs may have adverse long-term outcomes on children and adults exposed to the drugs in utero. Future research on treatments for GDM should include long-term follow- up of children exposed to glucose lowering medication in utero to determine the long-term cardiometabolic risk in the offspring born to mothers with GDM.

Utility of published skinfold thickness equations for prediction of body composition in very young New Zealand children

Measurement of body composition is increasingly important in research and clinical settings but is difficult in very young children. Bioelectrical impedance analysis (BIA) and air displacement plethysmography (ADP) are well-established but require specialist equipment so are not always feasible. Our aim was to determine if anthropometry and skinfold thickness measurements can be used as a substitute for BIA or ADP for assessing body composition in very young New Zealand children. We used three multi-ethnic cohorts: 217 children at a mean age of 24·2 months with skinfold and BIA measurements; seventy-nine infants at a mean age of 20·9 weeks and seventy-three infants at a mean age of 16·2 weeks, both with skinfold and ADP measurements. We used Bland-Altman plots to compare fat and fat-free mass calculated using all potentially relevant equations with measurements using BIA or ADP. We also calculated the proportion of children in the same tertile for measured fat or fat-free mass and tertiles (i) calculated using each equation, (ii) each absolute skinfold, and (iii) sum of skinfold thicknesses. We found that even for the best equation for each cohort, the 95 % limits of agreement with standard measures were wide (25-200 % of the mean) and the proportion of children whose standard measures fell in the same tertile as the skinfold estimates was ≤69 %. We conclude that none of the available published skinfold thickness equations provides good prediction of body composition in multi-ethnic cohorts of very young New Zealand children with different birth history and growth patterns.

Relationship between BMI and adiposity among different ethnic groups in 2-year-old New Zealand children

Age- and sex-based BMI cut-offs are used to define overweight and obesity, but the relationship between BMI and body composition has not been very well studied in children or compared between children of different ethnic groups. Body size and composition in childhood are also influenced by size at birth. Our aim was to compare body size and composition at 2 years in children with different ethnicity and size at birth. We prospectively followed a multi-ethnic cohort of 300 children born with risk factors for neonatal hypoglycaemia (infants of diabetics, large or small at birth or late preterm) to 2 years corrected age. Complete data on weight, height and head circumference and body composition using bioelectrical impedance 24±1 months corrected age were available in 209 children. At birth, compared with European children, Chinese, Indian and other ethnicity children were lighter, and Indian children had smaller head circumferences, but birth lengths were similar in all ethnic groups. At 2 years, Pacific children were heavier and had higher BMI z scores, and Indian children had smaller head circumferences and lower BMI z scores than those from other ethnic groups. However, fat mass and fat-free mass indices were similar in all groups. At median BMI, fat mass:fat-free mass ratio was 23 % lower in Pacific than in Indian children (0·22 v. 0·27, P=0·03). BMI is not a good indicator of adiposity in this multi-ethnic cohort of 2-year-old New Zealand children.

Metformin in gestational diabetes: the offspring follow-up (MiG TOFU): body composition and metabolic outcomes at 7-9 years of age

OBJECTIVE

To compare body composition and metabolic outcomes at 7-9 years in offspring of women with gestational diabetes (GDM) randomized to metformin (±insulin) or insulin treatment during pregnancy.

RESEARCH DESIGN AND METHODS

Children were assessed at 7 years in Adelaide (n=109/181) and 9 years in Auckland (n=99/396) by anthropometry, bioimpedance analysis (BIA), dual-energy X-ray absorptiometry (DXA), magnetic resonance imaging (MRI) (n=92/99) and fasting bloods (n=82/99).

RESULTS

In the Adelaide subgroup, mothers were similar at enrollment. Women randomized to metformin versus insulin had higher treatment glycemia (p=0.002) and more infants with birth weight >90th percentile (20.7% vs 5.9%; p=0.029). At 7 years, there were no differences in offspring measures. In Auckland, at enrollment, women randomized to metformin had a higher body mass index (BMI) (p=0.08) but gained less weight during treatment (p=0.07). Offspring birth measures were similar. At 9 years, metformin offspring were larger by measures of weight, arm and waist circumferences, waist:height (p<0.05); BMI, triceps skinfold (p=0.05); DXA fat mass and lean mass (p=0.07); MRI abdominal fat volume (p=0.051). Body fat percent was similar between treatment groups by DXA and BIA. Abdominal fat percentages (visceral adipose tissue, subcutaneous adipose tissue and liver) were similar by MRI. Fasting glucose, triglyceride, insulin, insulin resistance, glycosylated hemoglobin (HbA1c), cholesterol, liver transaminases, leptin and adiponectin were similar.

CONCLUSIONS

Metformin or insulin for GDM was associated with similar offspring total and abdominal body fat percent and metabolic measures at 7-9 years. Metformin-exposed children were larger at 9 years. Metformin may interact with fetal environmental factors to influence offspring outcomes.

Excessive adiposity at low BMI levels among women in rural Bangladesh

Asian populations have a higher percentage body fat (%BF) and are at higher risk for CVD and related complications at a given BMI compared with those of European descent. We explored whether %BF was disproportionately elevated in rural Bangladeshi women with low BMI. Height, weight, mid-upper arm circumference, triceps and subscapular skinfolds and bioelectrical impedance analysis (BIA) were measured in 1555 women at 3 months postpartum. %BF was assessed by skinfolds and by BIA. BMI was calculated in adults and BMI Z-scores were calculated for females <20 years old. Receiver operating characteristic (ROC) curves found the BMI and BMI Z-score cut-offs that optimally classified women as having moderately excessive adipose tissue (defined as >30 % body fat). Linear regressions estimated the association between BMI and BMI Z-score (among adolescents) and %BF. Mean BMI was 19·2 (sd 2·2) kg/m², and mean %BF was calculated as 23·7 (sd 4·8) % by skinfolds and 23·3 (sd 4·9) % by BIA. ROC analyses indicated that a BMI value of approximately 21 kg/m² optimised sensitivity (83·6 %) and specificity (84·2 %) for classifying subjects with >30 % body fat according to BIA among adults. This BMI level is substantially lower than the WHO recommended standard cut-off point of BMI ≥ 25 kg/m². The equivalent cut-off among adolescents was a BMI Z-score of –0·36, with a sensitivity of 81·3 % and specificity of 80·9 %. These findings suggest that Bangladeshi women exhibit excess adipose tissue at substantially lower BMI compared with non-South Asian populations. This is important for the identification and prevention of obesity-related metabolic diseases.