ORCID Profile
0000-0001-6107-3682
Current Organisations
Tianjin University
,
China University of Geosciences
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Publisher: Springer Science and Business Media LLC
Date: 18-03-2021
DOI: 10.1038/S41598-021-85557-Z
Abstract: Several early childhood obesity prediction models have been developed, but none for New Zealand's erse population. We aimed to develop and validate a model for predicting obesity in 4–5-year-old New Zealand children, using parental and infant data from the Growing Up in New Zealand (GUiNZ) cohort. Obesity was defined as body mass index (BMI) for age and sex ≥ 95th percentile. Data on GUiNZ children were used for derivation (n = 1731) and internal validation (n = 713). External validation was performed using data from the Prevention of Overweight in Infancy Study (POI, n = 383) and Pacific Islands Families Study (PIF, n = 135) cohorts. The final model included: birth weight, maternal smoking during pregnancy, maternal pre-pregnancy BMI, paternal BMI, and infant weight gain. Discrimination accuracy was adequate [AUROC = 0.74 (0.71–0.77)], remained so when validated internally [AUROC = 0.73 (0.68–0.78)] and externally on PIF [AUROC = 0.74 [0.66–0.82)] and POI [AUROC = 0.80 (0.71–0.90)]. Positive predictive values were variable but low across the risk threshold range (GUiNZ derivation 19–54% GUiNZ validation 19–48% and POI 8–24%), although more consistent in the PIF cohort (52–61%), all indicating high rates of false positives. Although this early childhood obesity prediction model could inform early obesity prevention, high rates of false positives might create unwarranted anxiety for families.
Publisher: IEEE
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 31-07-2023
DOI: 10.1038/S41430-023-01317-4
Abstract: Bioimpedance devices are practical for measuring body composition in preschool children, but their application is limited by the lack of validated equations. To develop and validate fat-free mass (FFM) bioimpedance prediction equations among New Zealand 3.5-year olds, with dual-energy X-ray absorptiometry (DXA) as the reference method. Bioelectrical impedance spectroscopy (SFB7, ImpediMed) and DXA (iDXA, GE Lunar) measurements were conducted on 65 children. An equation incorporating weight, sex, ethnicity, and impedance was developed and validated. Performance was compared with published equations and mixture theory prediction. The equation developed in ~70% ( n = 45) of the population (FFM [kg] = 1.39 + 0.30 weight [kg] + 0.39 length 2 /resistance at 50 kHz [cm 2 /Ω] + 0.30 sex [M = 1/F = 0] + 0.28 ethnicity [1 = Asian/0 = non-Asian]) explained 88% of the variance in FFM and predicted FFM with a root mean squared error of 0.39 kg (3.4% of mean FFM). When internally validated ( n = 20), bias was small (40 g, 0.3% of mean FFM), with limits of agreement (LOA) ±7.6% of mean FFM (95% LOA: –0.82, 0.90 kg). Published equations evaluated had similar LOA, but with marked bias ( .5% of mean FFM) when validated in our cohort, likely due to DXA differences. Of mixture theory methods assessed, the SFB7 inbuilt equation with personalized body geometry values performed best. However, bias and LOA were larger than with the empirical equations (–0.43 kg [95% LOA: –1.65, 0.79], p 0.001). We developed and validated a bioimpedance equation that can accurately predict FFM. Further external validation of the equation is required.
Publisher: BMJ
Date: 04-2019
DOI: 10.1136/BMJOPEN-2018-026174
Abstract: Animal studies showed that germ-free mice inoculated with normal mouse gut bacteria developed obesity, insulin resistance and higher triglyceride levels, despite similar food intake. In humans, an association has been found between obesity and gut microbiome dysbiosis. However, gut microbiome transfer has not been evaluated for the treatment of human obesity. We will examine the effectiveness of gut microbiome transfer using encapsulated material for the treatment of obesity in adolescents. A two-arm, double-blind, placebo-controlled, randomised clinical trial of a single course of gut microbiome transfer will be conducted in 80 obese [body mass index (BMI) ≥30 kg/m 2 ] adolescents (males and females, aged 14–18 years) in Auckland, New Zealand. Healthy lean donors (males and females, aged 18–28 years) will provide fresh stool s les from which bacteria will be isolated and double encapsulated. Participants (recipients) will be randomised at 1:1 to control (placebo) or treatment (gut microbiome transfer), stratified by sex. Recipients will receive 28 capsules over two consecutive mornings (~14 mL of frozen microbial suspension or saline). Clinical assessments will be performed at baseline, 6, 12 and 26 weeks, and will include: anthropometry, blood pressure, fasting metabolic markers, dietary intake, physical activity levels and health-related quality of life. Insulin sensitivity (Matsuda index), gut microbiota population structure characterised by 16S rRNA licon sequencing and body composition (using dual-energy X-ray absorptiometry) will be assessed at baseline, 6, 12 and 26 weeks. 24-hour ambulatory blood pressure monitoring will be performed at baseline and at 6 weeks. The primary outcome is BMI SD scores (SDS) at 6 weeks, with BMI SDS at 12 and 26 weeks as secondary outcomes. Other secondary outcomes include insulin sensitivity, adiposity (total body fat percentage) and gut microbial composition at 6, 12 and 26 weeks. Statistical analysis will be performed on the principle of intention to treat. Ethics approval was provided by the Northern A Health and Disability Ethics Committee (Ministry of Health, New Zealand 16/NTA/172). The trial results will be published in peer-reviewed journals and presented at international conferences. ACTRN12615001351505 Pre-results.
Publisher: Springer Science and Business Media LLC
Date: 18-11-2020
DOI: 10.1038/S41598-020-76921-6
Abstract: Metabolic diseases are increasing among adolescents with obesity. Although the reported prevalence of metabolic syndrome is approximately 30% worldwide, its prevalence is largely unknown among New Zealand adolescents. Therefore, we assessed the health of adolescents with obesity (BMI ≥ 30 kg/m 2 ) enrolled in a randomised clinical trial (Gut Bugs Trial), to identify the prevalence of undiagnosed comorbidities. Assessments included anthropometry, 24-h ambulatory blood pressure monitoring, and insulin sensitivity. We report on baseline data (pre-randomisation) on 87 participants (14–18 years 59% females), with mean BMI 36.9 ± 5.3 kg/m 2 (BMI SDS 3.33 ± 0.79). Approximately 40% of participants had undiagnosed metabolic syndrome, which was twice as common among males. Half (53%) had pre-diabetes and 92% a reduction in insulin sensitivity. Moreover, 31% had pre-hypertension/hypertension, 69% dyslipidaemia, and 25% abnormal liver function. Participants with class III obesity had a greater risk of metabolic syndrome than those with classes I/II [relative risk 1.99 (95% CI 1.19, 3.34)]. Risks for pre-hypertension/hypertension and inflammation were also greater among those with class III obesity. We identified a high prevalence of undiagnosed comorbidities among adolescents with obesity in New Zealand. As adolescent obesity tracks into adulthood, early interventions are needed to prevent progression to overt cardiometabolic diseases.
No related grants have been discovered for Wayne Cutfield.